diff --git a/runs/llama-2-7b-instruct-together-32k/w.16-x.16-y.16/w.fp16-x.fp16-y.fp16/w.tnsr.fp16-x.tnsr.fp16-y.tnsr.fp16/default-pileval.128x1024.[0-0]/run-241119.183703/config-241119.183703.yaml b/runs/llama-2-7b-instruct-together-32k/w.16-x.16-y.16/w.fp16-x.fp16-y.fp16/w.tnsr.fp16-x.tnsr.fp16-y.tnsr.fp16/default-pileval.128x1024.[0-0]/run-241119.183703/config-241119.183703.yaml new file mode 100644 index 0000000000000000000000000000000000000000..946b55078d7502826f72a4e7bfe5683aede3ed5c --- /dev/null +++ b/runs/llama-2-7b-instruct-together-32k/w.16-x.16-y.16/w.fp16-x.fp16-y.fp16/w.tnsr.fp16-x.tnsr.fp16-y.tnsr.fp16/default-pileval.128x1024.[0-0]/run-241119.183703/config-241119.183703.yaml @@ -0,0 +1,85 @@ +cache: + root: runs/shang + path: + rotation: '' + reorder: '' + smooth: '' + wgts: '' + acts: '' +output: + root: runs/shang + dirname: default-pileval.128x1024.[0-0] + job: run +model: + name: llama-2-7b-instruct-together-32k + family: llama-2 + path: /home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k + root: '' + local_path: /home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k + local_root: /home/yujunlin/models + dtype: torch.float16 +eval: + num_gpus: 1 + batch_size: 8 + tasks: + - wikitext + max_seq_length: -4096 + evaluators: + - gptq +quant: + wgts: + dtype: null + zero_point: null + group_shapes: + - - -1 + - -1 + - -1 + scale_dtypes: + - null + intermediate_dtypes: [] + intermediate_levels: [] + needs_dequant_saturation: false + skips: [] + enable_kernel_gptq: false + enable_calib_range: false + ipts: + dtype: null + zero_point: null + group_shapes: + - - -1 + - -1 + - -1 + scale_dtypes: + - null + skips: [] + static: false + enable_calib_range: false + opts: + dtype: null + zero_point: null + group_shapes: + - - -1 + - -1 + - -1 + scale_dtypes: + - null + skips: [] + static: false + enable_calib_range: false + calib: + data: pileval + num_samples: 128 + path: mit-han-lab/pile-val-backup + seq_length: 1024 + min_seq_length: 0 + max_seq_length: 0 + local_path: '' + enable_rotation: false + enable_reorder: false + enable_smooth: false + develop_dtype: torch.float32 +seed: 12345 +skip_eval: false +load_from: '' +save_model: false +copy_on_save: false diff --git a/runs/llama-2-7b-instruct-together-32k/w.16-x.16-y.16/w.fp16-x.fp16-y.fp16/w.tnsr.fp16-x.tnsr.fp16-y.tnsr.fp16/default-pileval.128x1024.[0-0]/run-241119.183703/results-241119.183703.json b/runs/llama-2-7b-instruct-together-32k/w.16-x.16-y.16/w.fp16-x.fp16-y.fp16/w.tnsr.fp16-x.tnsr.fp16-y.tnsr.fp16/default-pileval.128x1024.[0-0]/run-241119.183703/results-241119.183703.json new file mode 100644 index 0000000000000000000000000000000000000000..546fd56b91360aa246fa4992861acf68198fd4a4 --- /dev/null +++ b/runs/llama-2-7b-instruct-together-32k/w.16-x.16-y.16/w.fp16-x.fp16-y.fp16/w.tnsr.fp16-x.tnsr.fp16-y.tnsr.fp16/default-pileval.128x1024.[0-0]/run-241119.183703/results-241119.183703.json @@ -0,0 +1,32 @@ +{ + "gptq": { + "2048": { + "results": { + "wikitext": { + "word_perplexity": 6.443161573358209 + } + }, + "versions": { + "wikitext": 1 + }, + "config": { + "model": "llama-2-7b-instruct-together-32k" + }, + "model": "llama-2-7b-instruct-together-32k" + }, + "4096": { + "results": { + "wikitext": { + "word_perplexity": 5.964906855443073 + } + }, + "versions": { + "wikitext": 1 + }, + "config": { + "model": "llama-2-7b-instruct-together-32k" + }, + "model": "llama-2-7b-instruct-together-32k" + } + } +} \ No newline at end of file diff --git a/runs/llama-2-7b-instruct-together-32k/w.16-x.16-y.16/w.fp16-x.fp16-y.fp16/w.tnsr.fp16-x.tnsr.fp16-y.tnsr.fp16/default-pileval.128x1024.[0-0]/run-241119.183703/run-241119.183703.log b/runs/llama-2-7b-instruct-together-32k/w.16-x.16-y.16/w.fp16-x.fp16-y.fp16/w.tnsr.fp16-x.tnsr.fp16-y.tnsr.fp16/default-pileval.128x1024.[0-0]/run-241119.183703/run-241119.183703.log new file mode 100644 index 0000000000000000000000000000000000000000..19a3a0a8e5eb3b1e8913e018244c6f8a309f1937 --- /dev/null +++ b/runs/llama-2-7b-instruct-together-32k/w.16-x.16-y.16/w.fp16-x.fp16-y.fp16/w.tnsr.fp16-x.tnsr.fp16-y.tnsr.fp16/default-pileval.128x1024.[0-0]/run-241119.183703/run-241119.183703.log @@ -0,0 +1,219 @@ +24-11-19 18:37:03 | I | === Configurations === +24-11-19 18:37:03 | I | LlmPtqRunConfig( +24-11-19 18:37:03 | I | cache=LlmCacheConfig( +24-11-19 18:37:03 | I | root=runs/shang, +24-11-19 18:37:03 | I | dirpath=LlmQuantCacheConfig( +24-11-19 18:37:03 | I | rotation=, +24-11-19 18:37:03 | I | reorder=, +24-11-19 18:37:03 | I | smooth=, +24-11-19 18:37:03 | I | wgts=, +24-11-19 18:37:03 | I | acts=), +24-11-19 18:37:03 | I | path=LlmQuantCacheConfig( +24-11-19 18:37:03 | I | rotation=, +24-11-19 18:37:03 | I | reorder=, +24-11-19 18:37:03 | I | smooth=, +24-11-19 18:37:03 | I | wgts=, +24-11-19 18:37:03 | I | acts=)), +24-11-19 18:37:03 | I | output=OutputConfig( +24-11-19 18:37:03 | I | root=runs/shang, +24-11-19 18:37:03 | I | dirname=default-pileval.128x1024.[0-0], +24-11-19 18:37:03 | I | job=run, +24-11-19 18:37:03 | I | dirpath=runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.16-x.16-y.16/w.fp16-x.fp16-y.fp16/w.tnsr.fp16-x.tnsr.fp16-y.tnsr.fp16/default-pileval.128x1024.[0-0], +24-11-19 18:37:03 | I | timestamp=241119.183703), +24-11-19 18:37:03 | I | model=LlmModelConfig( +24-11-19 18:37:03 | I | name=llama-2-7b-instruct-together-32k, +24-11-19 18:37:03 | I | family=llama-2, +24-11-19 18:37:03 | I | path=/home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k, +24-11-19 18:37:03 | I | root=, +24-11-19 18:37:03 | I | local_path=/home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k, +24-11-19 18:37:03 | I | local_root=/home/yujunlin/models, +24-11-19 18:37:03 | I | size=7.0, +24-11-19 18:37:03 | I | variant=instruct-together-32k, +24-11-19 18:37:03 | I | dtype=torch.float16, +24-11-19 18:37:03 | I | orig_dtype=torch.float16), +24-11-19 18:37:03 | I | eval=LlmEvalConfig( +24-11-19 18:37:03 | I | num_gpus=1, +24-11-19 18:37:03 | I | batch_size=8, +24-11-19 18:37:03 | I | tasks=['wikitext'], +24-11-19 18:37:03 | I | max_seq_length=-4096, +24-11-19 18:37:03 | I | evaluators=['gptq']), +24-11-19 18:37:03 | I | quant=LlmQuantConfig( +24-11-19 18:37:03 | I | wgts=LlmWeightQuantizerConfig( +24-11-19 18:37:03 | I | dtype=None, +24-11-19 18:37:03 | I | zero_point=None, +24-11-19 18:37:03 | I | group_shapes=((-1, -1, -1),), +24-11-19 18:37:03 | I | scale_dtypes=(None,), +24-11-19 18:37:03 | I | intermediate_dtypes=(), +24-11-19 18:37:03 | I | intermediate_levels=(), +24-11-19 18:37:03 | I | needs_dequant_saturation=False, +24-11-19 18:37:03 | I | skips=[], +24-11-19 18:37:03 | I | static=False, +24-11-19 18:37:03 | I | kernel_gptq=None, +24-11-19 18:37:03 | I | calib_range=None), +24-11-19 18:37:03 | I | ipts=LlmActivationQuantizerConfig( +24-11-19 18:37:03 | I | dtype=None, +24-11-19 18:37:03 | I | zero_point=None, +24-11-19 18:37:03 | I | group_shapes=((-1, -1, -1),), +24-11-19 18:37:03 | I | scale_dtypes=(None,), +24-11-19 18:37:03 | I | intermediate_dtypes=(), +24-11-19 18:37:03 | I | intermediate_levels=(), +24-11-19 18:37:03 | I | needs_dequant_saturation=False, +24-11-19 18:37:03 | I | skips=[], +24-11-19 18:37:03 | I | static=False, +24-11-19 18:37:03 | I | kernel_gptq=None, +24-11-19 18:37:03 | I | calib_range=None), +24-11-19 18:37:03 | I | opts=LlmActivationQuantizerConfig( +24-11-19 18:37:03 | I | dtype=None, +24-11-19 18:37:03 | I | zero_point=None, +24-11-19 18:37:03 | I | group_shapes=((-1, -1, -1),), +24-11-19 18:37:03 | I | scale_dtypes=(None,), +24-11-19 18:37:03 | I | intermediate_dtypes=(), +24-11-19 18:37:03 | I | intermediate_levels=(), +24-11-19 18:37:03 | I | needs_dequant_saturation=False, +24-11-19 18:37:03 | I | skips=[], +24-11-19 18:37:03 | I | static=False, +24-11-19 18:37:03 | I | kernel_gptq=None, +24-11-19 18:37:03 | I | calib_range=None), +24-11-19 18:37:03 | I | calib=LlmCalibDataLoaderConfig( +24-11-19 18:37:03 | I | data=pileval, +24-11-19 18:37:03 | I | num_samples=128, +24-11-19 18:37:03 | I | batch_size=1, +24-11-19 18:37:03 | I | path=mit-han-lab/pile-val-backup, +24-11-19 18:37:03 | I | seq_length=1024, +24-11-19 18:37:03 | I | min_seq_length=0, +24-11-19 18:37:03 | I | max_seq_length=0, +24-11-19 18:37:03 | I | local_path=), +24-11-19 18:37:03 | I | rotation=None, +24-11-19 18:37:03 | I | reorder=None, +24-11-19 18:37:03 | I | smooth=None, +24-11-19 18:37:03 | I | develop_dtype=torch.float32), +24-11-19 18:37:03 | I | seed=12345, +24-11-19 18:37:03 | I | skip_eval=False, +24-11-19 18:37:03 | I | load_from=, +24-11-19 18:37:03 | I | save_model=False, +24-11-19 18:37:03 | I | copy_on_save=False) +24-11-19 18:37:03 | I | === Dumped Configurations === +24-11-19 18:37:03 | I | { 'cache': {'path': {'acts': '', 'reorder': '', 'rotation': '', 'smooth': '', 'wgts': ''}, 'root': 'runs/shang'}, +24-11-19 18:37:03 | I | 'copy_on_save': False, +24-11-19 18:37:03 | I | 'eval': {'batch_size': 8, 'evaluators': ['gptq'], 'max_seq_length': -4096, 'num_gpus': 1, 'tasks': ['wikitext']}, +24-11-19 18:37:03 | I | 'load_from': '', +24-11-19 18:37:03 | I | 'model': { 'dtype': 'torch.float16', +24-11-19 18:37:03 | I | 'family': 'llama-2', +24-11-19 18:37:03 | I | 'local_path': '/home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k', +24-11-19 18:37:03 | I | 'local_root': '/home/yujunlin/models', +24-11-19 18:37:03 | I | 'name': 'llama-2-7b-instruct-together-32k', +24-11-19 18:37:03 | I | 'path': '/home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k', +24-11-19 18:37:03 | I | 'root': ''}, +24-11-19 18:37:03 | I | 'output': {'dirname': 'default-pileval.128x1024.[0-0]', 'job': 'run', 'root': 'runs/shang'}, +24-11-19 18:37:03 | I | 'quant': { 'calib': { 'data': 'pileval', +24-11-19 18:37:03 | I | 'local_path': '', +24-11-19 18:37:03 | I | 'max_seq_length': 0, +24-11-19 18:37:03 | I | 'min_seq_length': 0, +24-11-19 18:37:03 | I | 'num_samples': 128, +24-11-19 18:37:03 | I | 'path': 'mit-han-lab/pile-val-backup', +24-11-19 18:37:03 | I | 'seq_length': 1024}, +24-11-19 18:37:03 | I | 'develop_dtype': 'torch.float32', +24-11-19 18:37:03 | I | 'enable_reorder': False, +24-11-19 18:37:03 | I | 'enable_rotation': False, +24-11-19 18:37:03 | I | 'enable_smooth': False, +24-11-19 18:37:03 | I | 'ipts': { 'dtype': None, +24-11-19 18:37:03 | I | 'enable_calib_range': False, +24-11-19 18:37:03 | I | 'group_shapes': [[-1, -1, -1]], +24-11-19 18:37:03 | I | 'scale_dtypes': [None], +24-11-19 18:37:03 | I | 'skips': [], +24-11-19 18:37:03 | I | 'static': False, +24-11-19 18:37:03 | I | 'zero_point': None}, +24-11-19 18:37:03 | I | 'opts': { 'dtype': None, +24-11-19 18:37:03 | I | 'enable_calib_range': False, +24-11-19 18:37:03 | I | 'group_shapes': [[-1, -1, -1]], +24-11-19 18:37:03 | I | 'scale_dtypes': [None], +24-11-19 18:37:03 | I | 'skips': [], +24-11-19 18:37:03 | I | 'static': False, +24-11-19 18:37:03 | I | 'zero_point': None}, +24-11-19 18:37:03 | I | 'wgts': { 'dtype': None, +24-11-19 18:37:03 | I | 'enable_calib_range': False, +24-11-19 18:37:03 | I | 'enable_kernel_gptq': False, +24-11-19 18:37:03 | I | 'group_shapes': [[-1, -1, -1]], +24-11-19 18:37:03 | I | 'intermediate_dtypes': [], +24-11-19 18:37:03 | I | 'intermediate_levels': [], +24-11-19 18:37:03 | I | 'needs_dequant_saturation': False, +24-11-19 18:37:03 | I | 'scale_dtypes': [None], +24-11-19 18:37:03 | I | 'skips': [], +24-11-19 18:37:03 | I | 'zero_point': None}}, +24-11-19 18:37:03 | I | 'save_model': False, +24-11-19 18:37:03 | I | 'seed': 12345, +24-11-19 18:37:03 | I | 'skip_eval': False} +24-11-19 18:37:03 | I | === Output Directory === +24-11-19 18:37:03 | I | runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.16-x.16-y.16/w.fp16-x.fp16-y.fp16/w.tnsr.fp16-x.tnsr.fp16-y.tnsr.fp16/default-pileval.128x1024.[0-0]/run-241119.183703 +24-11-19 18:37:03 | I | === Start Evaluating === +24-11-19 18:37:03 | I | * Building model llama-2-7b-instruct-together-32k from /home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k +24-11-19 18:37:03 | I | We will use 90% of the memory on device 0 for storing the model, and 10% for the buffer to avoid OOM. You can set `max_memory` in to a higher value to use more memory (at your own risk). +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.0.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.1.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.2.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.3.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.4.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.5.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.6.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.7.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.8.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.9.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.10.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.11.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.12.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.13.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.14.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.15.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.16.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.17.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.18.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.19.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.20.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.21.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.22.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.23.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.24.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.25.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.26.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.27.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.28.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.29.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.30.self_attn +24-11-19 18:37:12 | I | - Patching LlamaSdpaAttention.forward in model.layers.31.self_attn +24-11-19 18:37:12 | I | * Development dtype is torch.float32 +24-11-19 18:37:12 | I | * Evaluating model +24-11-19 18:37:12 | W | `pretrained` model kwarg is not of type `str`. Many other model arguments may be ignored. Please do not launch via accelerate or use `parallelize=True` if passing an existing model this way. +24-11-19 18:37:12 | I | Using model type 'default' +24-11-19 18:37:12 | W | Passed an already-initialized model through `pretrained`, assuming single-process call to evaluate() or custom distributed integration +24-11-19 18:37:12 | I | - Evaluator: gptq +24-11-19 18:37:12 | I | - Tasks: ['wikitext'] +24-11-19 18:37:12 | I | - Batch_size: 8 +24-11-19 18:37:12 | I | + Max_seq_length: 2048 +24-11-19 18:37:12 | D | Starting new HTTPS connection (1): huggingface.co:443 +24-11-19 18:37:18 | W | Using the latest cached version of the dataset since wikitext couldn't be found on the Hugging Face Hub +24-11-19 18:37:18 | W | Found the latest cached dataset configuration 'wikitext-2-raw-v1' at /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3 (last modified on Tue Oct 8 19:51:38 2024). +24-11-19 18:37:18 | D | Attempting to acquire lock 23438952619984 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 18:37:18 | D | Lock 23438952619984 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 18:37:18 | D | open file: /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3/dataset_info.json +24-11-19 18:37:18 | D | Attempting to release lock 23438952619984 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 18:37:18 | D | Lock 23438952619984 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 18:37:31 | I | - Results: +24-11-19 18:37:32 | I | | Task |Version| Metric |Value | |Stderr| +24-11-19 18:37:32 | I | |--------|------:|---------------|-----:|---|-----:| +24-11-19 18:37:32 | I | |wikitext| 1|word_perplexity|6.4432|± |6.4432| +24-11-19 18:37:32 | I | +24-11-19 18:37:32 | I | + Max_seq_length: 4096 +24-11-19 18:37:32 | D | Starting new HTTPS connection (2): huggingface.co:443 +24-11-19 18:37:38 | W | Using the latest cached version of the dataset since wikitext couldn't be found on the Hugging Face Hub +24-11-19 18:37:38 | W | Found the latest cached dataset configuration 'wikitext-2-raw-v1' at /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3 (last modified on Tue Oct 8 19:51:38 2024). +24-11-19 18:37:38 | D | Attempting to acquire lock 23438952626944 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 18:37:38 | D | Lock 23438952626944 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 18:37:38 | D | open file: /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3/dataset_info.json +24-11-19 18:37:38 | D | Attempting to release lock 23438952626944 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 18:37:38 | D | Lock 23438952626944 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 18:37:50 | I | - Results: +24-11-19 18:37:50 | I | | Task |Version| Metric |Value | |Stderr| +24-11-19 18:37:50 | I | |--------|------:|---------------|-----:|---|-----:| +24-11-19 18:37:50 | I | |wikitext| 1|word_perplexity|5.9649|± |5.9649| +24-11-19 18:37:50 | I | +24-11-19 18:37:50 | I | * Saving results to runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.16-x.16-y.16/w.fp16-x.fp16-y.fp16/w.tnsr.fp16-x.tnsr.fp16-y.tnsr.fp16/default-pileval.128x1024.[0-0]/run-241119.183703 diff --git a/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200548/config-241119.200548.yaml b/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200548/config-241119.200548.yaml new file mode 100644 index 0000000000000000000000000000000000000000..1a12ba3372f2b8bd989eb5ba9d798b6ee845d85e --- /dev/null +++ b/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200548/config-241119.200548.yaml @@ -0,0 +1,146 @@ +cache: + root: runs/shang + path: + rotation: runs/shang/llm/cache/quant/rotation/hadamard/llama-2-7b-instruct-together-32k.pt + reorder: '' + smooth: runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/llama-2-7b-instruct-together-32k.pt + wgts: runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-2-7b-instruct-together-32k.pt + acts: runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-2-7b-instruct-together-32k.pt +output: + root: runs/shang + dirname: skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0] + job: run +model: + name: llama-2-7b-instruct-together-32k + family: llama-2 + path: /home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k + root: '' + local_path: /home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k + local_root: /home/yujunlin/models + dtype: torch.float16 +eval: + num_gpus: 1 + batch_size: 8 + tasks: + - wikitext + max_seq_length: -4096 + evaluators: + - gptq +quant: + wgts: + dtype: sint8 + zero_point: null + group_shapes: + - - 1 + - -1 + - -1 + scale_dtypes: + - torch.float16 + intermediate_dtypes: [] + intermediate_levels: [] + needs_dequant_saturation: false + skips: [] + enable_kernel_gptq: true + kernel_gptq: + damp_percentage: 0.01 + block_size: 128 + num_inv_tries: 250 + hessian_block_size: 512 + enable_calib_range: true + calib_range: + degree: 2 + objective: OutputsError + strategy: GridSearch + granularity: Group + element_batch_size: 64 + sample_batch_size: -1 + element_size: 512 + sample_size: -1 + pre_reshape: true + outputs_device: cpu + ratio: 1.0 + max_shrink: 0.2 + max_expand: 1.0 + num_grids: 80 + allow_scale: false + skips: [] + ipts: + dtype: sint8 + zero_point: null + group_shapes: + - - 1 + - -1 + - -1 + scale_dtypes: + - torch.float16 + skips: [] + static: false + enable_calib_range: false + opts: + dtype: sint8 + zero_point: null + group_shapes: + - - -1 + - -1 + - -1 + scale_dtypes: + - torch.float16 + skips: + - attn_q + static: true + enable_calib_range: true + calib_range: + degree: 2 + objective: OutputsError + strategy: Manual + granularity: Layer + element_batch_size: -1 + sample_batch_size: -1 + element_size: -1 + sample_size: -1 + pre_reshape: true + outputs_device: cpu + ratio: 1.0 + max_shrink: 0.2 + max_expand: 1.0 + num_grids: 80 + allow_scale: false + skips: [] + calib: + data: pileval + num_samples: 128 + path: mit-han-lab/pile-val-backup + seq_length: 1024 + min_seq_length: 0 + max_seq_length: 0 + local_path: '' + enable_rotation: true + rotation: + random: false + transforms: + - out_proj + enable_reorder: false + enable_smooth: true + smooth: + enable_proj: false + enable_attn: true + attn: + degree: 2 + strategy: GridSearch + sample_batch_size: -1 + sample_size: -1 + outputs_device: cpu + allow_a_quant: true + allow_b_quant: true + spans: + - - AbsMax + - AbsMax + alpha: 0.5 + beta: -2 + num_grids: 20 + 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b/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200548/results-241119.200548.json @@ -0,0 +1,32 @@ +{ + "gptq": { + "2048": { + "results": { + "wikitext": { + "word_perplexity": 6.503797370202683 + } + }, + "versions": { + "wikitext": 1 + }, + "config": { + "model": "llama-2-7b-instruct-together-32k" + }, + "model": "llama-2-7b-instruct-together-32k" + }, + "4096": { + "results": { + "wikitext": { + "word_perplexity": 6.014449215881915 + } + }, + "versions": { + "wikitext": 1 + }, + "config": { + "model": "llama-2-7b-instruct-together-32k" + }, + "model": "llama-2-7b-instruct-together-32k" + } + } +} \ No newline at end of file diff --git a/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200548/run-241119.185856.log b/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200548/run-241119.185856.log new file mode 100644 index 0000000000000000000000000000000000000000..d2c363c3e3621e9339cffd7bd40b20678e459beb --- /dev/null +++ b/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200548/run-241119.185856.log @@ -0,0 +1,15947 @@ +24-11-19 18:58:56 | I | === Configurations === +24-11-19 18:58:56 | I | LlmPtqRunConfig( +24-11-19 18:58:56 | I | cache=LlmCacheConfig( +24-11-19 18:58:56 | I | root=runs/shang, +24-11-19 18:58:56 | I | dirpath=LlmQuantCacheConfig( +24-11-19 18:58:56 | I | rotation=runs/shang/llm/cache/quant/rotation/hadamard, +24-11-19 18:58:56 | I | reorder=, +24-11-19 18:58:56 | I | smooth=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2, +24-11-19 18:58:56 | I | wgts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[], +24-11-19 18:58:56 | I | acts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]), +24-11-19 18:58:56 | I | path=LlmQuantCacheConfig( +24-11-19 18:58:56 | I | rotation=runs/shang/llm/cache/quant/rotation/hadamard/llama-2-7b-instruct-together-32k.pt, +24-11-19 18:58:56 | I | reorder=, +24-11-19 18:58:56 | I | smooth=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/llama-2-7b-instruct-together-32k.pt, +24-11-19 18:58:56 | I | wgts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-2-7b-instruct-together-32k.pt, +24-11-19 18:58:56 | I | acts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-2-7b-instruct-together-32k.pt)), +24-11-19 18:58:56 | I | output=OutputConfig( +24-11-19 18:58:56 | I | root=runs/shang, +24-11-19 18:58:56 | I | dirname=skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0], +24-11-19 18:58:56 | I | job=run, +24-11-19 18:58:56 | I | dirpath=runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0], +24-11-19 18:58:56 | I | timestamp=241119.185856), +24-11-19 18:58:56 | I | model=LlmModelConfig( +24-11-19 18:58:56 | I | name=llama-2-7b-instruct-together-32k, +24-11-19 18:58:56 | I | family=llama-2, +24-11-19 18:58:56 | I | path=/home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k, +24-11-19 18:58:56 | I | root=, +24-11-19 18:58:56 | I | local_path=/home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k, +24-11-19 18:58:56 | I | local_root=/home/yujunlin/models, +24-11-19 18:58:56 | I | size=7.0, +24-11-19 18:58:56 | I | variant=instruct-together-32k, +24-11-19 18:58:56 | I | dtype=torch.float16, +24-11-19 18:58:56 | I | orig_dtype=torch.float16), +24-11-19 18:58:56 | I | eval=LlmEvalConfig( +24-11-19 18:58:56 | I | num_gpus=1, +24-11-19 18:58:56 | I | batch_size=8, +24-11-19 18:58:56 | I | tasks=['wikitext'], +24-11-19 18:58:56 | I | max_seq_length=-4096, +24-11-19 18:58:56 | I | evaluators=['gptq']), +24-11-19 18:58:56 | I | quant=LlmQuantConfig( +24-11-19 18:58:56 | I | wgts=LlmWeightQuantizerConfig( +24-11-19 18:58:56 | I | dtype=sint8, +24-11-19 18:58:56 | I | zero_point=None, +24-11-19 18:58:56 | I | group_shapes=((1, -1, -1),), +24-11-19 18:58:56 | I | scale_dtypes=(torch.float16,), +24-11-19 18:58:56 | I | intermediate_dtypes=(), +24-11-19 18:58:56 | I | intermediate_levels=(), +24-11-19 18:58:56 | I | needs_dequant_saturation=False, +24-11-19 18:58:56 | I | skips=[], +24-11-19 18:58:56 | I | static=True, +24-11-19 18:58:56 | I | kernel_gptq=QuantGptqConfig( +24-11-19 18:58:56 | I | damp_percentage=0.01, +24-11-19 18:58:56 | I | block_size=128, +24-11-19 18:58:56 | I | num_inv_tries=250, +24-11-19 18:58:56 | I | hessian_block_size=512), +24-11-19 18:58:56 | I | calib_range=SkipBasedDynamicRangeCalibConfig( +24-11-19 18:58:56 | I | degree=2, +24-11-19 18:58:56 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 18:58:56 | I | strategy=SearchBasedCalibStrategy.GridSearch, +24-11-19 18:58:56 | I | granularity=SearchBasedCalibGranularity.Group, +24-11-19 18:58:56 | I | element_batch_size=64, +24-11-19 18:58:56 | I | sample_batch_size=-1, +24-11-19 18:58:56 | I | element_size=512, +24-11-19 18:58:56 | I | sample_size=-1, +24-11-19 18:58:56 | I | pre_reshape=True, +24-11-19 18:58:56 | I | outputs_device=cpu, +24-11-19 18:58:56 | I | ratio=1.0, +24-11-19 18:58:56 | I | max_shrink=0.2, +24-11-19 18:58:56 | I | max_expand=1.0, +24-11-19 18:58:56 | I | num_grids=80, +24-11-19 18:58:56 | I | allow_scale=False, +24-11-19 18:58:56 | I | skips=[])), +24-11-19 18:58:56 | I | ipts=LlmActivationQuantizerConfig( +24-11-19 18:58:56 | I | dtype=sint8, +24-11-19 18:58:56 | I | zero_point=None, +24-11-19 18:58:56 | I | group_shapes=((1, -1, -1),), +24-11-19 18:58:56 | I | scale_dtypes=(torch.float16,), +24-11-19 18:58:56 | I | intermediate_dtypes=(), +24-11-19 18:58:56 | I | intermediate_levels=(), +24-11-19 18:58:56 | I | needs_dequant_saturation=False, +24-11-19 18:58:56 | I | skips=[], +24-11-19 18:58:56 | I | static=False, +24-11-19 18:58:56 | I | kernel_gptq=None, +24-11-19 18:58:56 | I | calib_range=None), +24-11-19 18:58:56 | I | opts=LlmActivationQuantizerConfig( +24-11-19 18:58:56 | I | dtype=sint8, +24-11-19 18:58:56 | I | zero_point=None, +24-11-19 18:58:56 | I | group_shapes=((-1, -1, -1),), +24-11-19 18:58:56 | I | scale_dtypes=(torch.float16,), +24-11-19 18:58:56 | I | intermediate_dtypes=(), +24-11-19 18:58:56 | I | intermediate_levels=(), +24-11-19 18:58:56 | I | needs_dequant_saturation=False, +24-11-19 18:58:56 | I | skips=['attn_q'], +24-11-19 18:58:56 | I | static=True, +24-11-19 18:58:56 | I | kernel_gptq=None, +24-11-19 18:58:56 | I | calib_range=SkipBasedDynamicRangeCalibConfig( +24-11-19 18:58:56 | I | degree=2, +24-11-19 18:58:56 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 18:58:56 | I | strategy=SearchBasedCalibStrategy.Manual, +24-11-19 18:58:56 | I | granularity=SearchBasedCalibGranularity.Layer, +24-11-19 18:58:56 | I | element_batch_size=-1, +24-11-19 18:58:56 | I | sample_batch_size=-1, +24-11-19 18:58:56 | I | element_size=-1, +24-11-19 18:58:56 | I | sample_size=-1, +24-11-19 18:58:56 | I | pre_reshape=True, +24-11-19 18:58:56 | I | outputs_device=cpu, +24-11-19 18:58:56 | I | ratio=1.0, +24-11-19 18:58:56 | I | max_shrink=0.2, +24-11-19 18:58:56 | I | max_expand=1.0, +24-11-19 18:58:56 | I | num_grids=80, +24-11-19 18:58:56 | I | allow_scale=False, +24-11-19 18:58:56 | I | skips=[])), +24-11-19 18:58:56 | I | calib=LlmCalibDataLoaderConfig( +24-11-19 18:58:56 | I | data=pileval, +24-11-19 18:58:56 | I | num_samples=128, +24-11-19 18:58:56 | I | batch_size=1, +24-11-19 18:58:56 | I | path=mit-han-lab/pile-val-backup, +24-11-19 18:58:56 | I | seq_length=1024, +24-11-19 18:58:56 | I | min_seq_length=0, +24-11-19 18:58:56 | I | max_seq_length=0, +24-11-19 18:58:56 | I | local_path=), +24-11-19 18:58:56 | I | rotation=QuantRotationConfig( +24-11-19 18:58:56 | I | random=False, +24-11-19 18:58:56 | I | transforms=['out_proj']), +24-11-19 18:58:56 | I | reorder=None, +24-11-19 18:58:56 | I | smooth=SmoothTransfomerConfig( +24-11-19 18:58:56 | I | proj=None, +24-11-19 18:58:56 | I | attn=SmoothAttentionCalibConfig( +24-11-19 18:58:56 | I | degree=2, +24-11-19 18:58:56 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 18:58:56 | I | strategy=SearchBasedCalibStrategy.GridSearch, +24-11-19 18:58:56 | I | granularity=SearchBasedCalibGranularity.Layer, +24-11-19 18:58:56 | I | element_batch_size=-1, +24-11-19 18:58:56 | I | sample_batch_size=-1, +24-11-19 18:58:56 | I | element_size=-1, +24-11-19 18:58:56 | I | sample_size=-1, +24-11-19 18:58:56 | I | pre_reshape=True, +24-11-19 18:58:56 | I | outputs_device=cpu, +24-11-19 18:58:56 | I | allow_a_quant=True, +24-11-19 18:58:56 | I | allow_b_quant=True, +24-11-19 18:58:56 | I | spans=[(, )], +24-11-19 18:58:56 | I | a_spans=[], +24-11-19 18:58:56 | I | b_spans=[], +24-11-19 18:58:56 | I | alpha=0.5, +24-11-19 18:58:56 | I | beta=-2, +24-11-19 18:58:56 | I | num_grids=20, +24-11-19 18:58:56 | I | allow_low_rank=False)), +24-11-19 18:58:56 | I | develop_dtype=torch.float32), +24-11-19 18:58:56 | I | seed=12345, +24-11-19 18:58:56 | I | skip_eval=False, +24-11-19 18:58:56 | I | load_from=, +24-11-19 18:58:56 | I | save_model=False, +24-11-19 18:58:56 | I | copy_on_save=False) +24-11-19 18:58:56 | I | === Dumped Configurations === +24-11-19 18:58:56 | I | { 'cache': { 'path': { 'acts': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-2-7b-instruct-together-32k.pt', +24-11-19 18:58:56 | I | 'reorder': '', +24-11-19 18:58:56 | I | 'rotation': 'runs/shang/llm/cache/quant/rotation/hadamard/llama-2-7b-instruct-together-32k.pt', +24-11-19 18:58:56 | I | 'smooth': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/llama-2-7b-instruct-together-32k.pt', +24-11-19 18:58:56 | I | 'wgts': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-2-7b-instruct-together-32k.pt'}, +24-11-19 18:58:56 | I | 'root': 'runs/shang'}, +24-11-19 18:58:56 | I | 'copy_on_save': False, +24-11-19 18:58:56 | I | 'eval': {'batch_size': 8, 'evaluators': ['gptq'], 'max_seq_length': -4096, 'num_gpus': 1, 'tasks': ['wikitext']}, +24-11-19 18:58:56 | I | 'load_from': '', +24-11-19 18:58:56 | I | 'model': { 'dtype': 'torch.float16', +24-11-19 18:58:56 | I | 'family': 'llama-2', +24-11-19 18:58:56 | I | 'local_path': '/home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k', +24-11-19 18:58:56 | I | 'local_root': '/home/yujunlin/models', +24-11-19 18:58:56 | I | 'name': 'llama-2-7b-instruct-together-32k', +24-11-19 18:58:56 | I | 'path': '/home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k', +24-11-19 18:58:56 | I | 'root': ''}, +24-11-19 18:58:56 | I | 'output': { 'dirname': 'skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]', +24-11-19 18:58:56 | I | 'job': 'run', +24-11-19 18:58:56 | I | 'root': 'runs/shang'}, +24-11-19 18:58:56 | I | 'quant': { 'calib': { 'data': 'pileval', +24-11-19 18:58:56 | I | 'local_path': '', +24-11-19 18:58:56 | I | 'max_seq_length': 0, +24-11-19 18:58:56 | I | 'min_seq_length': 0, +24-11-19 18:58:56 | I | 'num_samples': 128, +24-11-19 18:58:56 | I | 'path': 'mit-han-lab/pile-val-backup', +24-11-19 18:58:56 | I | 'seq_length': 1024}, +24-11-19 18:58:56 | I | 'develop_dtype': 'torch.float32', +24-11-19 18:58:56 | I | 'enable_reorder': False, +24-11-19 18:58:56 | I | 'enable_rotation': True, +24-11-19 18:58:56 | I | 'enable_smooth': True, +24-11-19 18:58:56 | I | 'ipts': { 'dtype': 'sint8', +24-11-19 18:58:56 | I | 'enable_calib_range': False, +24-11-19 18:58:56 | I | 'group_shapes': [[1, -1, -1]], +24-11-19 18:58:56 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 18:58:56 | I | 'skips': [], +24-11-19 18:58:56 | I | 'static': False, +24-11-19 18:58:56 | I | 'zero_point': None}, +24-11-19 18:58:56 | I | 'opts': { 'calib_range': { 'allow_scale': False, +24-11-19 18:58:56 | I | 'degree': 2, +24-11-19 18:58:56 | I | 'element_batch_size': -1, +24-11-19 18:58:56 | I | 'element_size': -1, +24-11-19 18:58:56 | I | 'granularity': 'Layer', +24-11-19 18:58:56 | I | 'max_expand': 1.0, +24-11-19 18:58:56 | I | 'max_shrink': 0.2, +24-11-19 18:58:56 | I | 'num_grids': 80, +24-11-19 18:58:56 | I | 'objective': 'OutputsError', +24-11-19 18:58:56 | I | 'outputs_device': 'cpu', +24-11-19 18:58:56 | I | 'pre_reshape': True, +24-11-19 18:58:56 | I | 'ratio': 1.0, +24-11-19 18:58:56 | I | 'sample_batch_size': -1, +24-11-19 18:58:56 | I | 'sample_size': -1, +24-11-19 18:58:56 | I | 'skips': [], +24-11-19 18:58:56 | I | 'strategy': 'Manual'}, +24-11-19 18:58:56 | I | 'dtype': 'sint8', +24-11-19 18:58:56 | I | 'enable_calib_range': True, +24-11-19 18:58:56 | I | 'group_shapes': [[-1, -1, -1]], +24-11-19 18:58:56 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 18:58:56 | I | 'skips': ['attn_q'], +24-11-19 18:58:56 | I | 'static': True, +24-11-19 18:58:56 | I | 'zero_point': None}, +24-11-19 18:58:56 | I | 'rotation': {'random': False, 'transforms': ['out_proj']}, +24-11-19 18:58:56 | I | 'smooth': { 'attn': { 'allow_a_quant': True, +24-11-19 18:58:56 | I | 'allow_b_quant': True, +24-11-19 18:58:56 | I | 'alpha': 0.5, +24-11-19 18:58:56 | I | 'beta': -2, +24-11-19 18:58:56 | I | 'degree': 2, +24-11-19 18:58:56 | I | 'num_grids': 20, +24-11-19 18:58:56 | I | 'outputs_device': 'cpu', +24-11-19 18:58:56 | I | 'sample_batch_size': -1, +24-11-19 18:58:56 | I | 'sample_size': -1, +24-11-19 18:58:56 | I | 'spans': [['AbsMax', 'AbsMax']], +24-11-19 18:58:56 | I | 'strategy': 'GridSearch'}, +24-11-19 18:58:56 | I | 'enable_attn': True, +24-11-19 18:58:56 | I | 'enable_proj': False}, +24-11-19 18:58:56 | I | 'wgts': { 'calib_range': { 'allow_scale': False, +24-11-19 18:58:56 | I | 'degree': 2, +24-11-19 18:58:56 | I | 'element_batch_size': 64, +24-11-19 18:58:56 | I | 'element_size': 512, +24-11-19 18:58:56 | I | 'granularity': 'Group', +24-11-19 18:58:56 | I | 'max_expand': 1.0, +24-11-19 18:58:56 | I | 'max_shrink': 0.2, +24-11-19 18:58:56 | I | 'num_grids': 80, +24-11-19 18:58:56 | I | 'objective': 'OutputsError', +24-11-19 18:58:56 | I | 'outputs_device': 'cpu', +24-11-19 18:58:56 | I | 'pre_reshape': True, +24-11-19 18:58:56 | I | 'ratio': 1.0, +24-11-19 18:58:56 | I | 'sample_batch_size': -1, +24-11-19 18:58:56 | I | 'sample_size': -1, +24-11-19 18:58:56 | I | 'skips': [], +24-11-19 18:58:56 | I | 'strategy': 'GridSearch'}, +24-11-19 18:58:56 | I | 'dtype': 'sint8', +24-11-19 18:58:56 | I | 'enable_calib_range': True, +24-11-19 18:58:56 | I | 'enable_kernel_gptq': True, +24-11-19 18:58:56 | I | 'group_shapes': [[1, -1, -1]], +24-11-19 18:58:56 | I | 'intermediate_dtypes': [], +24-11-19 18:58:56 | I | 'intermediate_levels': [], +24-11-19 18:58:56 | I | 'kernel_gptq': { 'block_size': 128, +24-11-19 18:58:56 | I | 'damp_percentage': 0.01, +24-11-19 18:58:56 | I | 'hessian_block_size': 512, +24-11-19 18:58:56 | I | 'num_inv_tries': 250}, +24-11-19 18:58:56 | I | 'needs_dequant_saturation': False, +24-11-19 18:58:56 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 18:58:56 | I | 'skips': [], +24-11-19 18:58:56 | I | 'zero_point': None}}, +24-11-19 18:58:56 | I | 'save_model': False, +24-11-19 18:58:56 | I | 'seed': 12345, +24-11-19 18:58:56 | I | 'skip_eval': False} +24-11-19 18:58:56 | I | === Output Directory === +24-11-19 18:58:56 | I | runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.185856 +24-11-19 18:58:56 | I | === Start Evaluating === +24-11-19 18:58:56 | I | * Building model llama-2-7b-instruct-together-32k from /home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k +24-11-19 18:58:57 | I | We will use 90% of the memory on device 0 for storing the model, and 10% for the buffer to avoid OOM. You can set `max_memory` in to a higher value to use more memory (at your own risk). +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.0.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.1.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.2.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.3.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.4.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.5.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.6.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.7.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.8.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.9.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.10.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.11.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.12.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.13.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.14.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.15.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.16.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.17.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.18.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.19.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.20.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.21.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.22.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.23.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.24.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.25.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.26.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.27.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.28.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.29.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.30.self_attn +24-11-19 18:59:00 | I | - Patching LlamaSdpaAttention.forward in model.layers.31.self_attn +24-11-19 18:59:00 | I | * Rotating model +24-11-19 18:59:00 | I | - Generating rotation +24-11-19 18:59:00 | D | - Transforming norm and linear in model.layers.0 +24-11-19 18:59:00 | D | - Transforming norm and linear in model.layers.1 +24-11-19 18:59:00 | D | - Transforming norm and linear in model.layers.2 +24-11-19 18:59:00 | D | - Transforming norm and linear in model.layers.3 +24-11-19 18:59:00 | D | - Transforming norm and linear in model.layers.4 +24-11-19 18:59:01 | D | - Transforming norm and linear in model.layers.5 +24-11-19 18:59:01 | D | - Transforming norm and linear in model.layers.6 +24-11-19 18:59:01 | D | - Transforming norm and linear in model.layers.7 +24-11-19 18:59:01 | D | - Transforming norm and linear in model.layers.8 +24-11-19 18:59:01 | D | - Transforming norm and linear in model.layers.9 +24-11-19 18:59:01 | D | - Transforming norm and linear in model.layers.10 +24-11-19 18:59:01 | D | - Transforming norm and linear in model.layers.11 +24-11-19 18:59:01 | D | - Transforming norm and linear in model.layers.12 +24-11-19 18:59:01 | D | - Transforming norm and linear in model.layers.13 +24-11-19 18:59:01 | D | - Transforming norm and linear in model.layers.14 +24-11-19 18:59:01 | D | - Transforming norm and linear in model.layers.15 +24-11-19 18:59:01 | D | - Transforming norm and linear in model.layers.16 +24-11-19 18:59:02 | D | - Transforming norm and linear in model.layers.17 +24-11-19 18:59:02 | D | - Transforming norm and linear in model.layers.18 +24-11-19 18:59:02 | D | - Transforming norm and linear in model.layers.19 +24-11-19 18:59:02 | D | - Transforming norm and linear in model.layers.20 +24-11-19 18:59:02 | D | - Transforming norm and linear in model.layers.21 +24-11-19 18:59:02 | D | - Transforming norm and linear in model.layers.22 +24-11-19 18:59:02 | D | - Transforming norm and linear in model.layers.23 +24-11-19 18:59:02 | D | - Transforming norm and linear in model.layers.24 +24-11-19 18:59:02 | D | - Transforming norm and linear in model.layers.25 +24-11-19 18:59:02 | D | - Transforming norm and linear in model.layers.26 +24-11-19 18:59:02 | D | - Transforming norm and linear in model.layers.27 +24-11-19 18:59:02 | D | - Transforming norm and linear in model.layers.28 +24-11-19 18:59:03 | D | - Transforming norm and linear in model.layers.29 +24-11-19 18:59:03 | D | - Transforming norm and linear in model.layers.30 +24-11-19 18:59:03 | D | - Transforming norm and linear in model.layers.31 +24-11-19 18:59:03 | D | - Transforming model.norm +24-11-19 18:59:03 | D | - Rotating model.embed_tokens +24-11-19 18:59:03 | D | - Rotating model.layers.0 +24-11-19 18:59:03 | D | - Rotating model.layers.0.self_attn.q_proj (in) +24-11-19 18:59:03 | D | - Rotating model.layers.0.self_attn.k_proj (in) +24-11-19 18:59:03 | D | - Rotating model.layers.0.self_attn.v_proj (in) +24-11-19 18:59:03 | D | - Rotating model.layers.0.self_attn.o_proj (out) +24-11-19 18:59:03 | D | - Rotating model.layers.0.self_attn.v_proj (out) +24-11-19 18:59:03 | D | - Rotating model.layers.0.self_attn.o_proj (in) +24-11-19 18:59:03 | D | - Rotating model.layers.0.mlp.up_proj (in) +24-11-19 18:59:03 | D | - Rotating model.layers.0.mlp.gate_proj (in) +24-11-19 18:59:03 | D | - Rotating model.layers.0.mlp.down_proj (out) +24-11-19 18:59:03 | D | - Rotating model.layers.1 +24-11-19 18:59:03 | D | - Rotating model.layers.1.self_attn.q_proj (in) +24-11-19 18:59:03 | D | - Rotating model.layers.1.self_attn.k_proj (in) +24-11-19 18:59:03 | D | - Rotating model.layers.1.self_attn.v_proj (in) +24-11-19 18:59:03 | D | - Rotating model.layers.1.self_attn.o_proj (out) +24-11-19 18:59:03 | D | - Rotating model.layers.1.self_attn.v_proj (out) +24-11-19 18:59:03 | D | - Rotating model.layers.1.self_attn.o_proj (in) +24-11-19 18:59:03 | D | - Rotating model.layers.1.mlp.up_proj (in) +24-11-19 18:59:03 | D | - Rotating model.layers.1.mlp.gate_proj (in) +24-11-19 18:59:03 | D | - Rotating model.layers.1.mlp.down_proj (out) +24-11-19 18:59:03 | D | - Rotating model.layers.2 +24-11-19 18:59:03 | D | - Rotating model.layers.2.self_attn.q_proj (in) +24-11-19 18:59:03 | D | - Rotating model.layers.2.self_attn.k_proj (in) +24-11-19 18:59:03 | D | - Rotating model.layers.2.self_attn.v_proj (in) +24-11-19 18:59:03 | D | - Rotating model.layers.2.self_attn.o_proj (out) +24-11-19 18:59:03 | D | - Rotating model.layers.2.self_attn.v_proj (out) +24-11-19 18:59:03 | D | - Rotating model.layers.2.self_attn.o_proj (in) +24-11-19 18:59:03 | D | - Rotating model.layers.2.mlp.up_proj (in) +24-11-19 18:59:03 | D | - Rotating model.layers.2.mlp.gate_proj (in) +24-11-19 18:59:03 | D | - Rotating model.layers.2.mlp.down_proj (out) +24-11-19 18:59:03 | D | - Rotating model.layers.3 +24-11-19 18:59:03 | D | - Rotating model.layers.3.self_attn.q_proj (in) +24-11-19 18:59:03 | D | - Rotating model.layers.3.self_attn.k_proj (in) +24-11-19 18:59:03 | D | - Rotating model.layers.3.self_attn.v_proj (in) +24-11-19 18:59:03 | D | - Rotating model.layers.3.self_attn.o_proj (out) +24-11-19 18:59:03 | D | - Rotating model.layers.3.self_attn.v_proj (out) +24-11-19 18:59:03 | D | - Rotating model.layers.3.self_attn.o_proj (in) +24-11-19 18:59:03 | D | - Rotating model.layers.3.mlp.up_proj (in) +24-11-19 18:59:03 | D | - Rotating model.layers.3.mlp.gate_proj (in) +24-11-19 18:59:03 | D | - Rotating model.layers.3.mlp.down_proj (out) +24-11-19 18:59:04 | D | - Rotating model.layers.4 +24-11-19 18:59:04 | D | - Rotating model.layers.4.self_attn.q_proj (in) +24-11-19 18:59:04 | D | - Rotating model.layers.4.self_attn.k_proj (in) +24-11-19 18:59:04 | D | - Rotating model.layers.4.self_attn.v_proj (in) +24-11-19 18:59:04 | D | - Rotating model.layers.4.self_attn.o_proj (out) +24-11-19 18:59:04 | D | - Rotating model.layers.4.self_attn.v_proj (out) +24-11-19 18:59:04 | D | - Rotating model.layers.4.self_attn.o_proj (in) +24-11-19 18:59:04 | D | - Rotating model.layers.4.mlp.up_proj (in) +24-11-19 18:59:04 | D | - Rotating model.layers.4.mlp.gate_proj (in) +24-11-19 18:59:04 | D | - Rotating model.layers.4.mlp.down_proj (out) +24-11-19 18:59:04 | D | - Rotating model.layers.5 +24-11-19 18:59:04 | D | - Rotating model.layers.5.self_attn.q_proj (in) +24-11-19 18:59:04 | D | - Rotating model.layers.5.self_attn.k_proj (in) +24-11-19 18:59:04 | D | - Rotating model.layers.5.self_attn.v_proj (in) +24-11-19 18:59:04 | D | - Rotating model.layers.5.self_attn.o_proj (out) +24-11-19 18:59:04 | D | - Rotating model.layers.5.self_attn.v_proj (out) +24-11-19 18:59:04 | D | - Rotating model.layers.5.self_attn.o_proj (in) +24-11-19 18:59:04 | D | - Rotating model.layers.5.mlp.up_proj (in) +24-11-19 18:59:04 | D | - Rotating model.layers.5.mlp.gate_proj (in) +24-11-19 18:59:04 | D | - Rotating model.layers.5.mlp.down_proj (out) +24-11-19 18:59:04 | D | - Rotating model.layers.6 +24-11-19 18:59:04 | D | - Rotating model.layers.6.self_attn.q_proj (in) +24-11-19 18:59:04 | D | - Rotating model.layers.6.self_attn.k_proj (in) +24-11-19 18:59:04 | D | - Rotating model.layers.6.self_attn.v_proj (in) +24-11-19 18:59:04 | D | - Rotating model.layers.6.self_attn.o_proj (out) +24-11-19 18:59:04 | D | - Rotating model.layers.6.self_attn.v_proj (out) +24-11-19 18:59:04 | D | - Rotating model.layers.6.self_attn.o_proj (in) +24-11-19 18:59:04 | D | - Rotating model.layers.6.mlp.up_proj (in) +24-11-19 18:59:04 | D | - 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Rotating model.layers.27.self_attn.v_proj (out) +24-11-19 18:59:06 | D | - Rotating model.layers.27.self_attn.o_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.27.mlp.up_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.27.mlp.gate_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.27.mlp.down_proj (out) +24-11-19 18:59:06 | D | - Rotating model.layers.28 +24-11-19 18:59:06 | D | - Rotating model.layers.28.self_attn.q_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.28.self_attn.k_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.28.self_attn.v_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.28.self_attn.o_proj (out) +24-11-19 18:59:06 | D | - Rotating model.layers.28.self_attn.v_proj (out) +24-11-19 18:59:06 | D | - Rotating model.layers.28.self_attn.o_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.28.mlp.up_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.28.mlp.gate_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.28.mlp.down_proj (out) +24-11-19 18:59:06 | D | - Rotating model.layers.29 +24-11-19 18:59:06 | D | - Rotating model.layers.29.self_attn.q_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.29.self_attn.k_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.29.self_attn.v_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.29.self_attn.o_proj (out) +24-11-19 18:59:06 | D | - Rotating model.layers.29.self_attn.v_proj (out) +24-11-19 18:59:06 | D | - Rotating model.layers.29.self_attn.o_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.29.mlp.up_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.29.mlp.gate_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.29.mlp.down_proj (out) +24-11-19 18:59:06 | D | - Rotating model.layers.30 +24-11-19 18:59:06 | D | - Rotating model.layers.30.self_attn.q_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.30.self_attn.k_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.30.self_attn.v_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.30.self_attn.o_proj (out) +24-11-19 18:59:06 | D | - Rotating model.layers.30.self_attn.v_proj (out) +24-11-19 18:59:06 | D | - Rotating model.layers.30.self_attn.o_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.30.mlp.up_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.30.mlp.gate_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.30.mlp.down_proj (out) +24-11-19 18:59:06 | D | - Rotating model.layers.31 +24-11-19 18:59:06 | D | - Rotating model.layers.31.self_attn.q_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.31.self_attn.k_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.31.self_attn.v_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.31.self_attn.o_proj (out) +24-11-19 18:59:06 | D | - Rotating model.layers.31.self_attn.v_proj (out) +24-11-19 18:59:06 | D | - Rotating model.layers.31.self_attn.o_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.31.mlp.up_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.31.mlp.gate_proj (in) +24-11-19 18:59:06 | D | - Rotating model.layers.31.mlp.down_proj (out) +24-11-19 18:59:06 | D | - Rotating lm_head (in) +24-11-19 18:59:06 | I | - Saving rotation to runs/shang/llm/cache/quant/rotation/hadamard/llama-2-7b-instruct-together-32k.pt +24-11-19 18:59:06 | I | - Linking rotation to runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.185856.RUNNING/cache/rotation.pt +24-11-19 18:59:07 | I | * Development dtype is torch.float32 +24-11-19 18:59:07 | I | * Smoothing model for quantization +24-11-19 18:59:07 | I | - Generating smooth scales +24-11-19 18:59:07 | D | Starting new HTTPS connection (1): huggingface.co:443 +24-11-19 18:59:13 | D | Starting new HTTPS connection (2): huggingface.co:443 +24-11-19 18:59:25 | D | Starting new HTTPS connection (1): s3.amazonaws.com:443 +24-11-19 18:59:37 | W | Repo card metadata block was not found. Setting CardData to empty. +24-11-19 18:59:37 | D | Starting new HTTPS connection (3): huggingface.co:443 +24-11-19 18:59:49 | W | Using the latest cached version of the dataset since mit-han-lab/pile-val-backup couldn't be found on the Hugging Face Hub +24-11-19 18:59:49 | W | Found the latest cached dataset configuration 'default' at /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4 (last modified on Tue Oct 8 18:58:39 2024). +24-11-19 18:59:49 | D | Attempting to acquire lock 23438952609504 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 18:59:49 | D | Lock 23438952609504 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 18:59:49 | D | open file: /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4/dataset_info.json +24-11-19 18:59:49 | D | Attempting to release lock 23438952609504 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 18:59:49 | D | Lock 23438952609504 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 19:00:05 | D | - Smoothing model.layers.0 +24-11-19 19:00:05 | D | - model.layers.0.self_attn.attn_k +24-11-19 19:00:05 | D | + w: None +24-11-19 19:00:05 | D | + x: None +24-11-19 19:00:05 | D | + y: sint8 +24-11-19 19:00:05 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:00:05 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:00:05 | D | + x - AbsMax +24-11-19 19:00:05 | D | + x = [min=0.4373, max=13.5312] +24-11-19 19:00:05 | D | + y - AbsMax +24-11-19 19:00:05 | D | + y = [min=0.3921, max=6.5820] +24-11-19 19:00:05 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:00:12 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:00:12 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:00:12 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:00:12 | D | - sum error = [ 1.7228, 1.5810, 1.5973, 1.4693, 1.4285] +24-11-19 19:00:12 | D | - best error = [ 1.7228, 1.5810, 1.5810, 1.4693, 1.4285] +24-11-19 19:00:12 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:00:12 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:00:12 | D | - sum error = [ 1.4102, 1.3227, 1.2721, 1.2090, 1.1628] +24-11-19 19:00:12 | D | - best error = [ 1.4102, 1.3227, 1.2721, 1.2090, 1.1628] +24-11-19 19:00:12 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:00:12 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:00:12 | D | - sum error = [ 1.1366, 1.0865, 1.0528, 1.0467, 1.0157] +24-11-19 19:00:12 | D | - best error = [ 1.1366, 1.0865, 1.0528, 1.0467, 1.0157] +24-11-19 19:00:12 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:00:12 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:00:12 | D | - sum error = [ 0.9874, 0.9699, 0.9477, 0.9454, 0.9290] +24-11-19 19:00:12 | D | - best error = [ 0.9874, 0.9699, 0.9477, 0.9454, 0.9290] +24-11-19 19:00:12 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:00:12 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:00:12 | D | - sum error = [ 6.0591, 4.8045, 4.2276, 3.7446, 3.1639] +24-11-19 19:00:12 | D | - best error = [ 0.9290, 0.9290, 0.9290, 0.9290, 0.9290] +24-11-19 19:00:12 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:00:12 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:00:12 | D | - sum error = [ 2.7355, 2.4262, 2.2063, 1.8670, 1.7219] +24-11-19 19:00:12 | D | - best error = [ 0.9290, 0.9290, 0.9290, 0.9290, 0.9290] +24-11-19 19:00:12 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:00:12 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:00:12 | D | - sum error = [ 1.5780, 1.4761, 1.3670, 1.2454, 1.1947] +24-11-19 19:00:12 | D | - best error = [ 0.9290, 0.9290, 0.9290, 0.9290, 0.9290] +24-11-19 19:00:12 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:00:12 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:00:12 | D | - sum error = [ 1.0999, 1.0355, 0.9904, 0.9349] +24-11-19 19:00:12 | D | - best error = [ 0.9290, 0.9290, 0.9290, 0.9290] +24-11-19 19:00:12 | D | + error = 0.9290 +24-11-19 19:00:12 | D | + scale = [min=0.4109, max=5.9902] +24-11-19 19:00:21 | D | - Smoothing model.layers.1 +24-11-19 19:00:21 | D | - model.layers.1.self_attn.attn_k +24-11-19 19:00:21 | D | + w: None +24-11-19 19:00:21 | D | + x: None +24-11-19 19:00:21 | D | + y: sint8 +24-11-19 19:00:21 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:00:21 | D | + finished parsing calibration arguments, ram usage: 11.9 +24-11-19 19:00:21 | D | + x - AbsMax +24-11-19 19:00:21 | D | + x = [min=0.3020, max=12.4375] +24-11-19 19:00:21 | D | + y - AbsMax +24-11-19 19:00:21 | D | + y = [min=0.4658, max=10.4844] +24-11-19 19:00:21 | D | + finished reseting calibrator, ram usage: 12.0 +24-11-19 19:00:28 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:00:28 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:00:28 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:00:28 | D | - sum error = [ 7.8129, 7.5119, 7.2588, 6.9965, 6.7476] +24-11-19 19:00:28 | D | - best error = [ 7.8129, 7.5119, 7.2588, 6.9965, 6.7476] +24-11-19 19:00:28 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:00:28 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:00:28 | D | - sum error = [ 6.5225, 6.2851, 6.0966, 5.9000, 5.7247] +24-11-19 19:00:28 | D | - best error = [ 6.5225, 6.2851, 6.0966, 5.9000, 5.7247] +24-11-19 19:00:28 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:00:28 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:00:28 | D | - sum error = [ 5.5324, 5.3581, 5.2004, 5.0431, 4.8894] +24-11-19 19:00:28 | D | - best error = [ 5.5324, 5.3581, 5.2004, 5.0431, 4.8894] +24-11-19 19:00:28 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:00:28 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:00:28 | D | - sum error = [ 4.7652, 4.6072, 4.4808, 4.3677, 4.2528] +24-11-19 19:00:28 | D | - best error = [ 4.7652, 4.6072, 4.4808, 4.3677, 4.2528] +24-11-19 19:00:28 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:00:28 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:00:28 | D | - sum error = [ 18.6260, 16.4492, 14.6185, 13.1595, 11.7397] +24-11-19 19:00:28 | D | - best error = [ 4.2528, 4.2528, 4.2528, 4.2528, 4.2528] +24-11-19 19:00:28 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:00:28 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:00:28 | D | - sum error = [ 10.6859, 9.8375, 9.0439, 8.3064, 7.7256] +24-11-19 19:00:28 | D | - best error = [ 4.2528, 4.2528, 4.2528, 4.2528, 4.2528] +24-11-19 19:00:28 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:00:28 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:00:28 | D | - sum error = [ 7.1513, 6.6591, 6.2219, 5.8219, 5.4774] +24-11-19 19:00:28 | D | - best error = [ 4.2528, 4.2528, 4.2528, 4.2528, 4.2528] +24-11-19 19:00:28 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:00:28 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:00:28 | D | - sum error = [ 5.1611, 4.8605, 4.6068, 4.3463] +24-11-19 19:00:28 | D | - best error = [ 4.2528, 4.2528, 4.2528, 4.2528] +24-11-19 19:00:28 | D | + error = 4.2528 +24-11-19 19:00:28 | D | + scale = [min=0.4840, max=9.3221] +24-11-19 19:00:36 | D | - Smoothing model.layers.2 +24-11-19 19:00:36 | D | - model.layers.2.self_attn.attn_k +24-11-19 19:00:36 | D | + w: None +24-11-19 19:00:36 | D | + x: None +24-11-19 19:00:36 | D | + y: sint8 +24-11-19 19:00:36 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:00:36 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:00:36 | D | + x - AbsMax +24-11-19 19:00:36 | D | + x = [min=0.9668, max=14.4141] +24-11-19 19:00:36 | D | + y - AbsMax +24-11-19 19:00:36 | D | + y = [min=0.9209, max=20.4219] +24-11-19 19:00:36 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:00:43 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:00:43 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:00:43 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:00:43 | D | - sum error = [ 30.6587, 29.7901, 28.5235, 26.7437, 24.4116] +24-11-19 19:00:43 | D | - best error = [ 30.6587, 29.7901, 28.5235, 26.7437, 24.4116] +24-11-19 19:00:43 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:00:43 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:00:43 | D | - sum error = [ 22.9037, 21.4300, 20.6400, 20.4109, 19.6865] +24-11-19 19:00:43 | D | - best error = [ 22.9037, 21.4300, 20.6400, 20.4109, 19.6865] +24-11-19 19:00:43 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:00:43 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:00:43 | D | - sum error = [ 19.0991, 18.0012, 17.1008, 16.8691, 16.3393] +24-11-19 19:00:43 | D | - best error = [ 19.0991, 18.0012, 17.1008, 16.8691, 16.3393] +24-11-19 19:00:43 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:00:43 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:00:43 | D | - sum error = [ 15.6705, 15.3244, 14.6696, 14.2632, 13.9555] +24-11-19 19:00:43 | D | - best error = [ 15.6705, 15.3244, 14.6696, 14.2632, 13.9555] +24-11-19 19:00:43 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:00:43 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:00:43 | D | - sum error = [ 82.5501, 72.7963, 63.3515, 53.8082, 47.5184] +24-11-19 19:00:43 | D | - best error = [ 13.9555, 13.9555, 13.9555, 13.9555, 13.9555] +24-11-19 19:00:43 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:00:43 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:00:43 | D | - sum error = [ 44.8010, 38.1817, 33.5651, 30.2114, 28.9812] +24-11-19 19:00:43 | D | - best error = [ 13.9555, 13.9555, 13.9555, 13.9555, 13.9555] +24-11-19 19:00:43 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:00:43 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:00:43 | D | - sum error = [ 25.3365, 21.9724, 20.4368, 19.4267, 17.6549] +24-11-19 19:00:43 | D | - best error = [ 13.9555, 13.9555, 13.9555, 13.9555, 13.9555] +24-11-19 19:00:43 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:00:43 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:00:43 | D | - sum error = [ 17.0899, 16.0824, 15.0317, 14.2164] +24-11-19 19:00:43 | D | - best error = [ 13.9555, 13.9555, 13.9555, 13.9555] +24-11-19 19:00:43 | D | + error = 13.9555 +24-11-19 19:00:43 | D | + scale = [min=0.9247, max=17.5627] +24-11-19 19:00:50 | D | - Smoothing model.layers.3 +24-11-19 19:00:50 | D | - model.layers.3.self_attn.attn_k +24-11-19 19:00:50 | D | + w: None +24-11-19 19:00:50 | D | + x: None +24-11-19 19:00:50 | D | + y: sint8 +24-11-19 19:00:50 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:00:50 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:00:50 | D | + x - AbsMax +24-11-19 19:00:50 | D | + x = [min=1.1270, max=16.4375] +24-11-19 19:00:51 | D | + y - AbsMax +24-11-19 19:00:51 | D | + y = [min=0.9590, max=21.3438] +24-11-19 19:00:51 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:00:58 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:00:58 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:00:58 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:00:58 | D | - sum error = [ 34.7710, 31.5107, 29.9783, 28.9037, 27.3133] +24-11-19 19:00:58 | D | - best error = [ 34.7710, 31.5107, 29.9783, 28.9037, 27.3133] +24-11-19 19:00:58 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:00:58 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:00:58 | D | - sum error = [ 25.5844, 24.9115, 23.9078, 22.9369, 21.9868] +24-11-19 19:00:58 | D | - best error = [ 25.5844, 24.9115, 23.9078, 22.9369, 21.9868] +24-11-19 19:00:58 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:00:58 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:00:58 | D | - sum error = [ 21.1401, 20.8640, 20.2118, 19.5003, 19.1975] +24-11-19 19:00:58 | D | - best error = [ 21.1401, 20.8640, 20.2118, 19.5003, 19.1975] +24-11-19 19:00:58 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:00:58 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:00:58 | D | - sum error = [ 19.1625, 18.8624, 18.1127, 17.4782, 17.3695] +24-11-19 19:00:58 | D | - best error = [ 19.1625, 18.8624, 18.1127, 17.4782, 17.3695] +24-11-19 19:00:58 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:00:58 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:00:58 | D | - sum error = [ 83.6758, 76.1594, 69.6303, 62.3324, 53.5902] +24-11-19 19:00:58 | D | - best error = [ 17.3695, 17.3695, 17.3695, 17.3695, 17.3695] +24-11-19 19:00:58 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:00:58 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:00:58 | D | - sum error = [ 49.6000, 43.1993, 38.1728, 35.2013, 30.5946] +24-11-19 19:00:58 | D | - best error = [ 17.3695, 17.3695, 17.3695, 17.3695, 17.3695] +24-11-19 19:00:58 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:00:58 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:00:58 | D | - sum error = [ 27.9573, 26.3663, 24.1081, 22.3888, 20.9917] +24-11-19 19:00:58 | D | - best error = [ 17.3695, 17.3695, 17.3695, 17.3695, 17.3695] +24-11-19 19:00:58 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:00:58 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:00:58 | D | - sum error = [ 19.9336, 19.0932, 18.3331, 17.3644] +24-11-19 19:00:58 | D | - best error = [ 17.3695, 17.3695, 17.3695, 17.3644] +24-11-19 19:00:58 | D | + error = 17.3644 +24-11-19 19:00:58 | D | + scale = [min=0.9553, max=16.4633] +24-11-19 19:01:05 | D | - Smoothing model.layers.4 +24-11-19 19:01:05 | D | - model.layers.4.self_attn.attn_k +24-11-19 19:01:05 | D | + w: None +24-11-19 19:01:05 | D | + x: None +24-11-19 19:01:05 | D | + y: sint8 +24-11-19 19:01:05 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:01:05 | D | + finished parsing calibration arguments, ram usage: 12.2 +24-11-19 19:01:06 | D | + x - AbsMax +24-11-19 19:01:06 | D | + x = [min=1.4141, max=16.4062] +24-11-19 19:01:06 | D | + y - AbsMax +24-11-19 19:01:06 | D | + y = [min=1.2734, max=23.8750] +24-11-19 19:01:06 | D | + finished reseting calibrator, ram usage: 12.0 +24-11-19 19:01:13 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:01:13 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:01:13 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:01:13 | D | - sum error = [ 52.3433, 47.8819, 44.4576, 41.9792, 39.1686] +24-11-19 19:01:13 | D | - best error = [ 52.3433, 47.8819, 44.4576, 41.9792, 39.1686] +24-11-19 19:01:13 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:01:13 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:01:13 | D | - sum error = [ 37.4844, 36.2012, 35.5720, 35.3928, 33.7557] +24-11-19 19:01:13 | D | - best error = [ 37.4844, 36.2012, 35.5720, 35.3928, 33.7557] +24-11-19 19:01:13 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:01:13 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:01:13 | D | - sum error = [ 32.0659, 30.1883, 29.5008, 28.6459, 27.4519] +24-11-19 19:01:13 | D | - best error = [ 32.0659, 30.1883, 29.5008, 28.6459, 27.4519] +24-11-19 19:01:13 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:01:13 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:01:13 | D | - sum error = [ 27.2515, 26.7574, 26.3427, 25.1909, 24.2969] +24-11-19 19:01:13 | D | - best error = [ 27.2515, 26.7574, 26.3427, 25.1909, 24.2969] +24-11-19 19:01:13 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:01:13 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:01:13 | D | - sum error = [ 126.2777, 118.0829, 106.7871, 92.9084, 80.3774] +24-11-19 19:01:13 | D | - best error = [ 24.2969, 24.2969, 24.2969, 24.2969, 24.2969] +24-11-19 19:01:13 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:01:13 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:01:13 | D | - sum error = [ 71.6082, 66.1321, 57.6765, 49.4493, 46.2229] +24-11-19 19:01:13 | D | - best error = [ 24.2969, 24.2969, 24.2969, 24.2969, 24.2969] +24-11-19 19:01:13 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:01:13 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:01:13 | D | - sum error = [ 40.1926, 37.4037, 36.1869, 33.4424, 30.9468] +24-11-19 19:01:13 | D | - best error = [ 24.2969, 24.2969, 24.2969, 24.2969, 24.2969] +24-11-19 19:01:13 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:01:13 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:01:13 | D | - sum error = [ 28.9171, 27.5045, 26.4871, 24.8784] +24-11-19 19:01:13 | D | - best error = [ 24.2969, 24.2969, 24.2969, 24.2969] +24-11-19 19:01:13 | D | + error = 24.2969 +24-11-19 19:01:13 | D | + scale = [min=1.2581, max=20.3726] +24-11-19 19:01:20 | D | - Smoothing model.layers.5 +24-11-19 19:01:20 | D | - model.layers.5.self_attn.attn_k +24-11-19 19:01:20 | D | + w: None +24-11-19 19:01:20 | D | + x: None +24-11-19 19:01:20 | D | + y: sint8 +24-11-19 19:01:20 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:01:20 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:01:20 | D | + x - AbsMax +24-11-19 19:01:20 | D | + x = [min=1.5879, max=17.6250] +24-11-19 19:01:20 | D | + y - AbsMax +24-11-19 19:01:20 | D | + y = [min=1.6338, max=24.2188] +24-11-19 19:01:20 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:01:27 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:01:27 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:01:27 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:01:27 | D | - sum error = [ 55.4265, 51.5180, 48.2088, 44.5840, 43.2982] +24-11-19 19:01:27 | D | - best error = [ 55.4265, 51.5180, 48.2088, 44.5840, 43.2982] +24-11-19 19:01:27 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:01:27 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:01:27 | D | - sum error = [ 42.5459, 39.9370, 38.1654, 37.0993, 36.3616] +24-11-19 19:01:27 | D | - best error = [ 42.5459, 39.9370, 38.1654, 37.0993, 36.3616] +24-11-19 19:01:27 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:01:27 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:01:27 | D | - sum error = [ 35.0268, 33.3756, 31.8923, 31.1928, 30.5271] +24-11-19 19:01:27 | D | - best error = [ 35.0268, 33.3756, 31.8923, 31.1928, 30.5271] +24-11-19 19:01:27 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:01:27 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:01:27 | D | - sum error = [ 28.2597, 28.4351, 27.1582, 26.1363, 25.5704] +24-11-19 19:01:27 | D | - best error = [ 28.2597, 28.2597, 27.1582, 26.1363, 25.5704] +24-11-19 19:01:27 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:01:27 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:01:27 | D | - sum error = [ 127.1598, 116.4117, 99.8502, 85.4778, 75.8242] +24-11-19 19:01:27 | D | - best error = [ 25.5704, 25.5704, 25.5704, 25.5704, 25.5704] +24-11-19 19:01:27 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:01:27 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:01:27 | D | - sum error = [ 69.9461, 62.6819, 57.9801, 50.4264, 45.6441] +24-11-19 19:01:27 | D | - best error = [ 25.5704, 25.5704, 25.5704, 25.5704, 25.5704] +24-11-19 19:01:27 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:01:27 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:01:27 | D | - sum error = [ 42.7189, 37.3181, 35.5815, 33.8616, 31.4454] +24-11-19 19:01:27 | D | - best error = [ 25.5704, 25.5704, 25.5704, 25.5704, 25.5704] +24-11-19 19:01:27 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:01:27 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:01:27 | D | - sum error = [ 30.2780, 28.0228, 27.3186, 25.6065] +24-11-19 19:01:27 | D | - best error = [ 25.5704, 25.5704, 25.5704, 25.5704] +24-11-19 19:01:27 | D | + error = 25.5704 +24-11-19 19:01:27 | D | + scale = [min=1.5942, max=20.6511] +24-11-19 19:01:35 | D | - Smoothing model.layers.6 +24-11-19 19:01:35 | D | - model.layers.6.self_attn.attn_k +24-11-19 19:01:35 | D | + w: None +24-11-19 19:01:35 | D | + x: None +24-11-19 19:01:35 | D | + y: sint8 +24-11-19 19:01:35 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:01:35 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:01:35 | D | + x - AbsMax +24-11-19 19:01:35 | D | + x = [min=0.9209, max=19.8125] +24-11-19 19:01:35 | D | + y - AbsMax +24-11-19 19:01:35 | D | + y = [min=0.9209, max=21.0781] +24-11-19 19:01:35 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:01:42 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:01:42 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:01:42 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:01:42 | D | - sum error = [ 56.5486, 55.2232, 52.6686, 49.4369, 46.8464] +24-11-19 19:01:42 | D | - best error = [ 56.5486, 55.2232, 52.6686, 49.4369, 46.8464] +24-11-19 19:01:42 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:01:42 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:01:42 | D | - sum error = [ 45.9686, 44.1049, 43.3547, 40.6443, 39.8255] +24-11-19 19:01:42 | D | - best error = [ 45.9686, 44.1049, 43.3547, 40.6443, 39.8255] +24-11-19 19:01:42 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:01:42 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:01:42 | D | - sum error = [ 39.1064, 37.6679, 37.7915, 37.4431, 35.8188] +24-11-19 19:01:42 | D | - best error = [ 39.1064, 37.6679, 37.6679, 37.4431, 35.8188] +24-11-19 19:01:42 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:01:42 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:01:42 | D | - sum error = [ 34.4250, 32.8996, 33.0999, 32.5613, 30.8768] +24-11-19 19:01:42 | D | - best error = [ 34.4250, 32.8996, 32.8996, 32.5613, 30.8768] +24-11-19 19:01:42 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:01:42 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:01:42 | D | - sum error = [ 120.4077, 106.3987, 99.2071, 89.1735, 81.6198] +24-11-19 19:01:42 | D | - best error = [ 30.8768, 30.8768, 30.8768, 30.8768, 30.8768] +24-11-19 19:01:42 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:01:42 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:01:42 | D | - sum error = [ 73.9235, 67.5316, 60.1128, 56.7436, 51.1773] +24-11-19 19:01:42 | D | - best error = [ 30.8768, 30.8768, 30.8768, 30.8768, 30.8768] +24-11-19 19:01:42 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:01:42 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:01:42 | D | - sum error = [ 46.9763, 44.7691, 42.4587, 39.1987, 37.4154] +24-11-19 19:01:42 | D | - best error = [ 30.8768, 30.8768, 30.8768, 30.8768, 30.8768] +24-11-19 19:01:42 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:01:42 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:01:42 | D | - sum error = [ 37.7173, 34.4472, 32.5340, 31.7909] +24-11-19 19:01:42 | D | - best error = [ 30.8768, 30.8768, 30.8768, 30.8768] +24-11-19 19:01:42 | D | + error = 30.8768 +24-11-19 19:01:42 | D | + scale = [min=0.9247, max=18.0984] +24-11-19 19:01:50 | D | - Smoothing model.layers.7 +24-11-19 19:01:50 | D | - model.layers.7.self_attn.attn_k +24-11-19 19:01:50 | D | + w: None +24-11-19 19:01:50 | D | + x: None +24-11-19 19:01:50 | D | + y: sint8 +24-11-19 19:01:50 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:01:50 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:01:50 | D | + x - AbsMax +24-11-19 19:01:50 | D | + x = [min=0.9023, max=20.9688] +24-11-19 19:01:50 | D | + y - AbsMax +24-11-19 19:01:50 | D | + y = [min=0.9697, max=22.1250] +24-11-19 19:01:50 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:01:57 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:01:57 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:01:57 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:01:57 | D | - sum error = [ 65.7182, 63.1715, 60.5451, 57.7282, 54.9743] +24-11-19 19:01:57 | D | - best error = [ 65.7182, 63.1715, 60.5451, 57.7282, 54.9743] +24-11-19 19:01:57 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:01:57 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:01:57 | D | - sum error = [ 53.0333, 51.5994, 49.1824, 46.9750, 44.8077] +24-11-19 19:01:57 | D | - best error = [ 53.0333, 51.5994, 49.1824, 46.9750, 44.8077] +24-11-19 19:01:57 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:01:57 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:01:57 | D | - sum error = [ 43.5300, 42.6784, 41.5360, 43.6079, 43.2206] +24-11-19 19:01:57 | D | - best error = [ 43.5300, 42.6784, 41.5360, 41.5360, 41.5360] +24-11-19 19:01:57 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:01:57 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:01:57 | D | - sum error = [ 40.6874, 38.3094, 39.0007, 38.0313, 37.2867] +24-11-19 19:01:57 | D | - best error = [ 40.6874, 38.3094, 38.3094, 38.0313, 37.2867] +24-11-19 19:01:57 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:01:57 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:01:57 | D | - sum error = [ 149.7650, 136.4382, 119.4466, 106.3115, 99.0194] +24-11-19 19:01:57 | D | - best error = [ 37.2867, 37.2867, 37.2867, 37.2867, 37.2867] +24-11-19 19:01:57 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:01:57 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:01:57 | D | - sum error = [ 91.8269, 83.0328, 73.3637, 67.9189, 62.3183] +24-11-19 19:01:57 | D | - best error = [ 37.2867, 37.2867, 37.2867, 37.2867, 37.2867] +24-11-19 19:01:57 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:01:57 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:01:57 | D | - sum error = [ 59.0191, 54.9294, 50.6752, 46.4945, 44.6085] +24-11-19 19:01:57 | D | - best error = [ 37.2867, 37.2867, 37.2867, 37.2867, 37.2867] +24-11-19 19:01:57 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:01:57 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:01:57 | D | - sum error = [ 43.0194, 43.1562, 39.0598, 38.4225] +24-11-19 19:01:57 | D | - best error = [ 37.2867, 37.2867, 37.2867, 37.2867] +24-11-19 19:01:57 | D | + error = 37.2867 +24-11-19 19:01:57 | D | + scale = [min=0.9712, max=18.9513] +24-11-19 19:02:04 | D | - Smoothing model.layers.8 +24-11-19 19:02:04 | D | - model.layers.8.self_attn.attn_k +24-11-19 19:02:04 | D | + w: None +24-11-19 19:02:04 | D | + x: None +24-11-19 19:02:04 | D | + y: sint8 +24-11-19 19:02:04 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:02:04 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:02:04 | D | + x - AbsMax +24-11-19 19:02:04 | D | + x = [min=1.4893, max=18.1719] +24-11-19 19:02:04 | D | + y - AbsMax +24-11-19 19:02:04 | D | + y = [min=1.1504, max=22.1562] +24-11-19 19:02:04 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:02:12 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:02:12 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:02:12 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:02:12 | D | - sum error = [ 74.9415, 72.7188, 69.5883, 67.1767, 65.9589] +24-11-19 19:02:12 | D | - best error = [ 74.9415, 72.7188, 69.5883, 67.1767, 65.9589] +24-11-19 19:02:12 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:02:12 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:02:12 | D | - sum error = [ 63.4478, 62.1736, 60.1511, 59.9975, 56.3674] +24-11-19 19:02:12 | D | - best error = [ 63.4478, 62.1736, 60.1511, 59.9975, 56.3674] +24-11-19 19:02:12 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:02:12 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:02:12 | D | - sum error = [ 52.3779, 51.9780, 51.0741, 48.1213, 46.2566] +24-11-19 19:02:12 | D | - best error = [ 52.3779, 51.9780, 51.0741, 48.1213, 46.2566] +24-11-19 19:02:12 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:02:12 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:02:12 | D | - sum error = [ 45.6477, 45.8751, 43.6437, 42.5045, 41.7378] +24-11-19 19:02:12 | D | - best error = [ 45.6477, 45.6477, 43.6437, 42.5045, 41.7378] +24-11-19 19:02:12 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:02:12 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:02:12 | D | - sum error = [ 144.6048, 131.2452, 115.5700, 105.3989, 99.0033] +24-11-19 19:02:12 | D | - best error = [ 41.7378, 41.7378, 41.7378, 41.7378, 41.7378] +24-11-19 19:02:12 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:02:12 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:02:12 | D | - sum error = [ 91.0833, 83.9469, 77.1914, 68.7010, 63.7970] +24-11-19 19:02:12 | D | - best error = [ 41.7378, 41.7378, 41.7378, 41.7378, 41.7378] +24-11-19 19:02:12 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:02:12 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:02:12 | D | - sum error = [ 60.3414, 57.3368, 52.8071, 49.8406, 47.8973] +24-11-19 19:02:12 | D | - best error = [ 41.7378, 41.7378, 41.7378, 41.7378, 41.7378] +24-11-19 19:02:12 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:02:12 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:02:12 | D | - sum error = [ 45.6297, 45.4987, 42.6714, 41.8436] +24-11-19 19:02:12 | D | - best error = [ 41.7378, 41.7378, 41.7378, 41.7378] +24-11-19 19:02:12 | D | + error = 41.7378 +24-11-19 19:02:12 | D | + scale = [min=1.1424, max=18.9767] +24-11-19 19:02:19 | D | - Smoothing model.layers.9 +24-11-19 19:02:19 | D | - model.layers.9.self_attn.attn_k +24-11-19 19:02:19 | D | + w: None +24-11-19 19:02:19 | D | + x: None +24-11-19 19:02:19 | D | + y: sint8 +24-11-19 19:02:19 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:02:19 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:02:19 | D | + x - AbsMax +24-11-19 19:02:19 | D | + x = [min=1.6016, max=15.4375] +24-11-19 19:02:19 | D | + y - AbsMax +24-11-19 19:02:19 | D | + y = [min=1.6768, max=23.0625] +24-11-19 19:02:19 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:02:26 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:02:26 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:02:26 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:02:26 | D | - sum error = [ 90.3677, 86.6223, 83.6882, 77.7615, 74.8306] +24-11-19 19:02:26 | D | - best error = [ 90.3677, 86.6223, 83.6882, 77.7615, 74.8306] +24-11-19 19:02:26 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:02:26 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:02:26 | D | - sum error = [ 71.9863, 69.5460, 67.5820, 66.9981, 64.3081] +24-11-19 19:02:26 | D | - best error = [ 71.9863, 69.5460, 67.5820, 66.9981, 64.3081] +24-11-19 19:02:26 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:02:26 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:02:26 | D | - sum error = [ 62.3828, 61.2223, 58.5736, 56.2080, 55.2067] +24-11-19 19:02:26 | D | - best error = [ 62.3828, 61.2223, 58.5736, 56.2080, 55.2067] +24-11-19 19:02:26 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:02:26 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:02:26 | D | - sum error = [ 52.9293, 51.8598, 51.1288, 49.5857, 47.7009] +24-11-19 19:02:26 | D | - best error = [ 52.9293, 51.8598, 51.1288, 49.5857, 47.7009] +24-11-19 19:02:26 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:02:26 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:02:26 | D | - sum error = [ 178.8452, 161.3788, 144.8501, 131.0208, 120.0681] +24-11-19 19:02:26 | D | - best error = [ 47.7009, 47.7009, 47.7009, 47.7009, 47.7009] +24-11-19 19:02:26 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:02:26 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:02:26 | D | - sum error = [ 111.1248, 102.4463, 92.6454, 84.3472, 80.9726] +24-11-19 19:02:26 | D | - best error = [ 47.7009, 47.7009, 47.7009, 47.7009, 47.7009] +24-11-19 19:02:26 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:02:26 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:02:26 | D | - sum error = [ 72.4275, 68.8170, 65.1492, 62.0174, 59.2527] +24-11-19 19:02:26 | D | - best error = [ 47.7009, 47.7009, 47.7009, 47.7009, 47.7009] +24-11-19 19:02:26 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:02:26 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:02:26 | D | - sum error = [ 57.0106, 52.9464, 51.4067, 48.9480] +24-11-19 19:02:26 | D | - best error = [ 47.7009, 47.7009, 47.7009, 47.7009] +24-11-19 19:02:26 | D | + error = 47.7009 +24-11-19 19:02:26 | D | + scale = [min=1.6340, max=19.7134] +24-11-19 19:02:34 | D | - Smoothing model.layers.10 +24-11-19 19:02:34 | D | - model.layers.10.self_attn.attn_k +24-11-19 19:02:34 | D | + w: None +24-11-19 19:02:34 | D | + x: None +24-11-19 19:02:34 | D | + y: sint8 +24-11-19 19:02:34 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:02:34 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:02:34 | D | + x - AbsMax +24-11-19 19:02:34 | D | + x = [min=1.3184, max=17.5469] +24-11-19 19:02:34 | D | + y - AbsMax +24-11-19 19:02:34 | D | + y = [min=1.3682, max=21.7188] +24-11-19 19:02:34 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:02:41 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:02:41 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:02:41 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:02:41 | D | - sum error = [ 91.0518, 87.5287, 85.0299, 81.8762, 80.0339] +24-11-19 19:02:41 | D | - best error = [ 91.0518, 87.5287, 85.0299, 81.8762, 80.0339] +24-11-19 19:02:41 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:02:41 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:02:41 | D | - sum error = [ 76.7217, 73.5363, 71.3525, 69.0355, 67.0164] +24-11-19 19:02:41 | D | - best error = [ 76.7217, 73.5363, 71.3525, 69.0355, 67.0164] +24-11-19 19:02:41 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:02:41 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:02:41 | D | - sum error = [ 65.2007, 63.4376, 61.8754, 61.2959, 58.7469] +24-11-19 19:02:41 | D | - best error = [ 65.2007, 63.4376, 61.8754, 61.2959, 58.7469] +24-11-19 19:02:41 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:02:41 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:02:41 | D | - sum error = [ 57.1917, 56.3138, 54.7100, 54.1634, 52.9332] +24-11-19 19:02:41 | D | - best error = [ 57.1917, 56.3138, 54.7100, 54.1634, 52.9332] +24-11-19 19:02:41 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:02:41 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:02:41 | D | - sum error = [ 196.4248, 176.1799, 156.8833, 142.5212, 129.0110] +24-11-19 19:02:41 | D | - best error = [ 52.9332, 52.9332, 52.9332, 52.9332, 52.9332] +24-11-19 19:02:41 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:02:41 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:02:41 | D | - sum error = [ 115.9903, 106.8735, 98.6588, 92.0684, 86.1303] +24-11-19 19:02:41 | D | - best error = [ 52.9332, 52.9332, 52.9332, 52.9332, 52.9332] +24-11-19 19:02:41 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:02:41 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:02:41 | D | - sum error = [ 80.6844, 74.7290, 70.7779, 65.5496, 62.7512] +24-11-19 19:02:41 | D | - best error = [ 52.9332, 52.9332, 52.9332, 52.9332, 52.9332] +24-11-19 19:02:41 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:02:41 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:02:41 | D | - sum error = [ 60.7018, 57.5323, 56.1986, 54.1837] +24-11-19 19:02:41 | D | - best error = [ 52.9332, 52.9332, 52.9332, 52.9332] +24-11-19 19:02:41 | D | + error = 52.9332 +24-11-19 19:02:41 | D | + scale = [min=1.3469, max=18.6206] +24-11-19 19:02:49 | D | - Smoothing model.layers.11 +24-11-19 19:02:49 | D | - model.layers.11.self_attn.attn_k +24-11-19 19:02:49 | D | + w: None +24-11-19 19:02:49 | D | + x: None +24-11-19 19:02:49 | D | + y: sint8 +24-11-19 19:02:49 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:02:49 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:02:49 | D | + x - AbsMax +24-11-19 19:02:49 | D | + x = [min=1.3359, max=19.1719] +24-11-19 19:02:49 | D | + y - AbsMax +24-11-19 19:02:49 | D | + y = [min=1.2051, max=20.3750] +24-11-19 19:02:49 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:02:56 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:02:56 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:02:56 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:02:56 | D | - sum error = [ 80.2327, 78.0969, 75.3688, 73.4296, 70.9778] +24-11-19 19:02:56 | D | - best error = [ 80.2327, 78.0969, 75.3688, 73.4296, 70.9778] +24-11-19 19:02:56 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:02:56 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:02:56 | D | - sum error = [ 68.9544, 66.0412, 62.9115, 61.9238, 60.4516] +24-11-19 19:02:56 | D | - best error = [ 68.9544, 66.0412, 62.9115, 61.9238, 60.4516] +24-11-19 19:02:56 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:02:56 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:02:56 | D | - sum error = [ 58.5941, 56.9243, 54.2233, 52.7368, 51.9095] +24-11-19 19:02:56 | D | - best error = [ 58.5941, 56.9243, 54.2233, 52.7368, 51.9095] +24-11-19 19:02:56 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:02:56 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:02:56 | D | - sum error = [ 50.9758, 51.0215, 50.6361, 49.5057, 48.5403] +24-11-19 19:02:56 | D | - best error = [ 50.9758, 50.9758, 50.6361, 49.5057, 48.5403] +24-11-19 19:02:56 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:02:56 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:02:56 | D | - sum error = [ 183.9097, 162.0672, 143.1764, 131.6704, 121.4634] +24-11-19 19:02:56 | D | - best error = [ 48.5403, 48.5403, 48.5403, 48.5403, 48.5403] +24-11-19 19:02:56 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:02:56 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:02:56 | D | - sum error = [ 108.2144, 101.8690, 97.6335, 87.1878, 77.7855] +24-11-19 19:02:56 | D | - best error = [ 48.5403, 48.5403, 48.5403, 48.5403, 48.5403] +24-11-19 19:02:56 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:02:56 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:02:56 | D | - sum error = [ 72.5076, 66.8699, 63.7544, 60.3065, 57.3156] +24-11-19 19:02:56 | D | - best error = [ 48.5403, 48.5403, 48.5403, 48.5403, 48.5403] +24-11-19 19:02:56 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:02:56 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:02:56 | D | - sum error = [ 54.6428, 52.2019, 51.1069, 49.2400] +24-11-19 19:02:56 | D | - best error = [ 48.5403, 48.5403, 48.5403, 48.5403] +24-11-19 19:02:56 | D | + error = 48.5403 +24-11-19 19:02:56 | D | + scale = [min=1.1939, max=17.5244] +24-11-19 19:03:03 | D | - Smoothing model.layers.12 +24-11-19 19:03:03 | D | - model.layers.12.self_attn.attn_k +24-11-19 19:03:03 | D | + w: None +24-11-19 19:03:03 | D | + x: None +24-11-19 19:03:03 | D | + y: sint8 +24-11-19 19:03:03 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:03:03 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:03:03 | D | + x - AbsMax +24-11-19 19:03:03 | D | + x = [min=1.0918, max=18.9531] +24-11-19 19:03:03 | D | + y - AbsMax +24-11-19 19:03:03 | D | + y = [min=1.2236, max=21.7500] +24-11-19 19:03:03 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:03:10 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:03:10 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:03:10 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:03:10 | D | - sum error = [ 96.7037, 91.7791, 89.1003, 85.8438, 84.8113] +24-11-19 19:03:10 | D | - best error = [ 96.7037, 91.7791, 89.1003, 85.8438, 84.8113] +24-11-19 19:03:10 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:03:10 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:03:10 | D | - sum error = [ 81.0865, 79.1127, 77.5323, 73.8906, 71.2690] +24-11-19 19:03:10 | D | - best error = [ 81.0865, 79.1127, 77.5323, 73.8906, 71.2690] +24-11-19 19:03:10 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:03:10 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:03:10 | D | - sum error = [ 69.0493, 67.9360, 65.7097, 64.1423, 63.3235] +24-11-19 19:03:10 | D | - best error = [ 69.0493, 67.9360, 65.7097, 64.1423, 63.3235] +24-11-19 19:03:10 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:03:10 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:03:10 | D | - sum error = [ 61.9999, 59.8115, 58.9760, 57.8621, 56.9408] +24-11-19 19:03:10 | D | - best error = [ 61.9999, 59.8115, 58.9760, 57.8621, 56.9408] +24-11-19 19:03:10 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:03:10 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:03:10 | D | - sum error = [ 208.9434, 190.4078, 172.9478, 154.2248, 138.9159] +24-11-19 19:03:10 | D | - best error = [ 56.9408, 56.9408, 56.9408, 56.9408, 56.9408] +24-11-19 19:03:10 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:03:10 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:03:10 | D | - sum error = [ 128.0464, 117.5631, 110.9383, 100.1023, 93.4916] +24-11-19 19:03:10 | D | - best error = [ 56.9408, 56.9408, 56.9408, 56.9408, 56.9408] +24-11-19 19:03:10 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:03:10 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:03:10 | D | - sum error = [ 85.2480, 81.3697, 77.9645, 72.5509, 67.5516] +24-11-19 19:03:10 | D | - best error = [ 56.9408, 56.9408, 56.9408, 56.9408, 56.9408] +24-11-19 19:03:10 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:03:10 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:03:10 | D | - sum error = [ 65.0529, 62.4870, 59.5103, 58.1751] +24-11-19 19:03:10 | D | - best error = [ 56.9408, 56.9408, 56.9408, 56.9408] +24-11-19 19:03:10 | D | + error = 56.9408 +24-11-19 19:03:10 | D | + scale = [min=1.2113, max=18.6460] +24-11-19 19:03:18 | D | - Smoothing model.layers.13 +24-11-19 19:03:18 | D | - model.layers.13.self_attn.attn_k +24-11-19 19:03:18 | D | + w: None +24-11-19 19:03:18 | D | + x: None +24-11-19 19:03:18 | D | + y: sint8 +24-11-19 19:03:18 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:03:18 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:03:18 | D | + x - AbsMax +24-11-19 19:03:18 | D | + x = [min=1.5947, max=17.3594] +24-11-19 19:03:18 | D | + y - AbsMax +24-11-19 19:03:18 | D | + y = [min=1.3652, max=21.7500] +24-11-19 19:03:18 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:03:26 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:03:26 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:03:26 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:03:26 | D | - sum error = [ 96.5115, 92.9470, 88.4158, 87.1405, 82.6643] +24-11-19 19:03:26 | D | - best error = [ 96.5115, 92.9470, 88.4158, 87.1405, 82.6643] +24-11-19 19:03:26 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:03:26 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:03:26 | D | - sum error = [ 80.1738, 79.7063, 76.3979, 73.5535, 72.6975] +24-11-19 19:03:26 | D | - best error = [ 80.1738, 79.7063, 76.3979, 73.5535, 72.6975] +24-11-19 19:03:26 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:03:26 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:03:26 | D | - sum error = [ 69.1522, 67.5257, 65.9985, 64.2419, 62.4780] +24-11-19 19:03:26 | D | - best error = [ 69.1522, 67.5257, 65.9985, 64.2419, 62.4780] +24-11-19 19:03:26 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:03:26 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:03:26 | D | - sum error = [ 60.5638, 60.2257, 58.9218, 58.3426, 58.1111] +24-11-19 19:03:26 | D | - best error = [ 60.5638, 60.2257, 58.9218, 58.3426, 58.1111] +24-11-19 19:03:26 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:03:26 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:03:26 | D | - sum error = [ 215.5257, 195.9574, 173.5989, 158.9456, 144.1391] +24-11-19 19:03:26 | D | - best error = [ 58.1111, 58.1111, 58.1111, 58.1111, 58.1111] +24-11-19 19:03:26 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:03:26 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:03:26 | D | - sum error = [ 132.5144, 117.8943, 104.5661, 97.2665, 92.5413] +24-11-19 19:03:26 | D | - best error = [ 58.1111, 58.1111, 58.1111, 58.1111, 58.1111] +24-11-19 19:03:26 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:03:26 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:03:26 | D | - sum error = [ 88.8898, 80.2776, 75.3747, 70.9191, 67.9789] +24-11-19 19:03:26 | D | - best error = [ 58.1111, 58.1111, 58.1111, 58.1111, 58.1111] +24-11-19 19:03:26 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:03:26 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:03:26 | D | - sum error = [ 65.3554, 62.8851, 59.8222, 58.4018] +24-11-19 19:03:26 | D | - best error = [ 58.1111, 58.1111, 58.1111, 58.1111] +24-11-19 19:03:26 | D | + error = 58.1111 +24-11-19 19:03:26 | D | + scale = [min=1.3441, max=18.6460] +24-11-19 19:03:33 | D | - Smoothing model.layers.14 +24-11-19 19:03:33 | D | - model.layers.14.self_attn.attn_k +24-11-19 19:03:33 | D | + w: None +24-11-19 19:03:33 | D | + x: None +24-11-19 19:03:33 | D | + y: sint8 +24-11-19 19:03:33 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:03:33 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:03:34 | D | + x - AbsMax +24-11-19 19:03:34 | D | + x = [min=1.3896, max=18.0781] +24-11-19 19:03:34 | D | + y - AbsMax +24-11-19 19:03:34 | D | + y = [min=1.5293, max=21.6875] +24-11-19 19:03:34 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:03:41 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:03:41 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:03:41 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:03:41 | D | - sum error = [ 97.9763, 94.8931, 92.3563, 88.8772, 85.1473] +24-11-19 19:03:41 | D | - best error = [ 97.9763, 94.8931, 92.3563, 88.8772, 85.1473] +24-11-19 19:03:41 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:03:41 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:03:41 | D | - sum error = [ 81.7763, 79.7450, 77.3807, 74.2415, 72.4725] +24-11-19 19:03:41 | D | - best error = [ 81.7763, 79.7450, 77.3807, 74.2415, 72.4725] +24-11-19 19:03:41 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:03:41 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:03:41 | D | - sum error = [ 71.2931, 70.0383, 68.0129, 66.3535, 65.9981] +24-11-19 19:03:41 | D | - best error = [ 71.2931, 70.0383, 68.0129, 66.3535, 65.9981] +24-11-19 19:03:41 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:03:41 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:03:41 | D | - sum error = [ 63.8531, 61.4157, 59.9552, 60.4050, 58.0588] +24-11-19 19:03:41 | D | - best error = [ 63.8531, 61.4157, 59.9552, 59.9552, 58.0588] +24-11-19 19:03:41 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:03:41 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:03:41 | D | - sum error = [ 182.3174, 166.4572, 153.5110, 139.8755, 127.9880] +24-11-19 19:03:41 | D | - best error = [ 58.0588, 58.0588, 58.0588, 58.0588, 58.0588] +24-11-19 19:03:41 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:03:41 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:03:41 | D | - sum error = [ 118.6044, 109.0547, 98.1584, 92.6997, 89.0745] +24-11-19 19:03:41 | D | - best error = [ 58.0588, 58.0588, 58.0588, 58.0588, 58.0588] +24-11-19 19:03:41 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:03:41 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:03:41 | D | - sum error = [ 80.9897, 78.1357, 74.3965, 69.4894, 66.7606] +24-11-19 19:03:41 | D | - best error = [ 58.0588, 58.0588, 58.0588, 58.0588, 58.0588] +24-11-19 19:03:41 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:03:41 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:03:41 | D | - sum error = [ 64.3819, 63.4137, 61.1396, 59.9950] +24-11-19 19:03:41 | D | - best error = [ 58.0588, 58.0588, 58.0588, 58.0588] +24-11-19 19:03:41 | D | + error = 58.0588 +24-11-19 19:03:41 | D | + scale = [min=1.4972, max=18.5951] +24-11-19 19:03:49 | D | - Smoothing model.layers.15 +24-11-19 19:03:49 | D | - model.layers.15.self_attn.attn_k +24-11-19 19:03:49 | D | + w: None +24-11-19 19:03:49 | D | + x: None +24-11-19 19:03:49 | D | + y: sint8 +24-11-19 19:03:49 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:03:49 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:03:49 | D | + x - AbsMax +24-11-19 19:03:49 | D | + x = [min=1.8525, max=18.3906] +24-11-19 19:03:49 | D | + y - AbsMax +24-11-19 19:03:49 | D | + y = [min=1.6855, max=20.2031] +24-11-19 19:03:49 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:03:57 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:03:57 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:03:57 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:03:57 | D | - sum error = [ 101.0036, 97.7015, 93.6507, 90.5764, 88.0062] +24-11-19 19:03:57 | D | - best error = [ 101.0036, 97.7015, 93.6507, 90.5764, 88.0062] +24-11-19 19:03:57 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:03:57 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:03:57 | D | - sum error = [ 84.9320, 84.1426, 83.1378, 78.7728, 77.2556] +24-11-19 19:03:57 | D | - best error = [ 84.9320, 84.1426, 83.1378, 78.7728, 77.2556] +24-11-19 19:03:57 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:03:57 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:03:57 | D | - sum error = [ 75.2047, 73.7590, 73.4689, 71.2491, 68.8498] +24-11-19 19:03:57 | D | - best error = [ 75.2047, 73.7590, 73.4689, 71.2491, 68.8498] +24-11-19 19:03:57 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:03:57 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:03:57 | D | - sum error = [ 68.0689, 65.9756, 64.7270, 63.8135, 63.0234] +24-11-19 19:03:57 | D | - best error = [ 68.0689, 65.9756, 64.7270, 63.8135, 63.0234] +24-11-19 19:03:57 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:03:57 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:03:57 | D | - sum error = [ 222.8548, 199.6228, 183.5855, 164.6590, 151.2870] +24-11-19 19:03:57 | D | - best error = [ 63.0234, 63.0234, 63.0234, 63.0234, 63.0234] +24-11-19 19:03:57 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:03:57 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:03:57 | D | - sum error = [ 136.6125, 124.4657, 115.0880, 107.2211, 98.8134] +24-11-19 19:03:57 | D | - best error = [ 63.0234, 63.0234, 63.0234, 63.0234, 63.0234] +24-11-19 19:03:57 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:03:57 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:03:57 | D | - sum error = [ 94.4272, 88.5929, 82.2398, 77.2196, 74.7895] +24-11-19 19:03:57 | D | - best error = [ 63.0234, 63.0234, 63.0234, 63.0234, 63.0234] +24-11-19 19:03:57 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:03:57 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:03:57 | D | - sum error = [ 71.2717, 68.4915, 65.3407, 63.9529] +24-11-19 19:03:57 | D | - best error = [ 63.0234, 63.0234, 63.0234, 63.0234] +24-11-19 19:03:57 | D | + error = 63.0234 +24-11-19 19:03:57 | D | + scale = [min=1.6421, max=17.3839] +24-11-19 19:04:05 | D | - Smoothing model.layers.16 +24-11-19 19:04:05 | D | - model.layers.16.self_attn.attn_k +24-11-19 19:04:05 | D | + w: None +24-11-19 19:04:05 | D | + x: None +24-11-19 19:04:05 | D | + y: sint8 +24-11-19 19:04:05 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:04:05 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:04:05 | D | + x - AbsMax +24-11-19 19:04:05 | D | + x = [min=1.8320, max=19.7656] +24-11-19 19:04:05 | D | + y - AbsMax +24-11-19 19:04:05 | D | + y = [min=1.5576, max=20.6719] +24-11-19 19:04:05 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:04:12 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:04:12 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:04:12 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:04:12 | D | - sum error = [ 110.2322, 106.8472, 102.5123, 98.2407, 96.0015] +24-11-19 19:04:12 | D | - best error = [ 110.2322, 106.8472, 102.5123, 98.2407, 96.0015] +24-11-19 19:04:12 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:04:12 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:04:12 | D | - sum error = [ 94.2749, 90.9885, 88.9908, 86.2693, 84.3383] +24-11-19 19:04:12 | D | - best error = [ 94.2749, 90.9885, 88.9908, 86.2693, 84.3383] +24-11-19 19:04:12 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:04:12 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:04:12 | D | - sum error = [ 82.2865, 81.2316, 79.8244, 77.8727, 76.4014] +24-11-19 19:04:12 | D | - best error = [ 82.2865, 81.2316, 79.8244, 77.8727, 76.4014] +24-11-19 19:04:12 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:04:12 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:04:12 | D | - sum error = [ 75.8180, 75.3602, 75.6135, 75.1231, 74.0518] +24-11-19 19:04:12 | D | - best error = [ 75.8180, 75.3602, 75.3602, 75.1231, 74.0518] +24-11-19 19:04:12 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:04:12 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:04:12 | D | - sum error = [ 241.3668, 217.8641, 197.1326, 179.3913, 164.7238] +24-11-19 19:04:12 | D | - best error = [ 74.0518, 74.0518, 74.0518, 74.0518, 74.0518] +24-11-19 19:04:12 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:04:12 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:04:12 | D | - sum error = [ 149.3634, 134.8807, 126.4069, 119.0065, 108.8766] +24-11-19 19:04:12 | D | - best error = [ 74.0518, 74.0518, 74.0518, 74.0518, 74.0518] +24-11-19 19:04:12 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:04:12 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:04:12 | D | - sum error = [ 101.7252, 96.9450, 91.2375, 88.5287, 83.7496] +24-11-19 19:04:12 | D | - best error = [ 74.0518, 74.0518, 74.0518, 74.0518, 74.0518] +24-11-19 19:04:12 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:04:12 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:04:12 | D | - sum error = [ 79.4929, 76.8897, 75.3207, 74.6387] +24-11-19 19:04:12 | D | - best error = [ 74.0518, 74.0518, 74.0518, 74.0518] +24-11-19 19:04:12 | D | + error = 74.0518 +24-11-19 19:04:12 | D | + scale = [min=1.5235, max=17.7669] +24-11-19 19:04:20 | D | - Smoothing model.layers.17 +24-11-19 19:04:20 | D | - model.layers.17.self_attn.attn_k +24-11-19 19:04:20 | D | + w: None +24-11-19 19:04:20 | D | + x: None +24-11-19 19:04:20 | D | + y: sint8 +24-11-19 19:04:20 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:04:20 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:04:20 | D | + x - AbsMax +24-11-19 19:04:20 | D | + x = [min=1.6250, max=19.6406] +24-11-19 19:04:20 | D | + y - AbsMax +24-11-19 19:04:20 | D | + y = [min=1.5977, max=27.4688] +24-11-19 19:04:20 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:04:28 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:04:28 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:04:28 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:04:28 | D | - sum error = [ 131.7590, 125.8310, 119.3432, 112.1954, 106.6708] +24-11-19 19:04:28 | D | - best error = [ 131.7590, 125.8310, 119.3432, 112.1954, 106.6708] +24-11-19 19:04:28 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:04:28 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:04:28 | D | - sum error = [ 102.2878, 97.8022, 94.3709, 90.8298, 88.8452] +24-11-19 19:04:28 | D | - best error = [ 102.2878, 97.8022, 94.3709, 90.8298, 88.8452] +24-11-19 19:04:28 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:04:28 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:04:28 | D | - sum error = [ 86.2011, 84.8875, 82.4946, 78.9466, 74.9168] +24-11-19 19:04:28 | D | - best error = [ 86.2011, 84.8875, 82.4946, 78.9466, 74.9168] +24-11-19 19:04:28 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:04:28 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:04:28 | D | - sum error = [ 73.6871, 71.6933, 68.5138, 66.5113, 64.9389] +24-11-19 19:04:28 | D | - best error = [ 73.6871, 71.6933, 68.5138, 66.5113, 64.9389] +24-11-19 19:04:28 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:04:28 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:04:28 | D | - sum error = [ 313.2267, 277.2412, 247.9266, 216.7625, 193.0869] +24-11-19 19:04:28 | D | - best error = [ 64.9389, 64.9389, 64.9389, 64.9389, 64.9389] +24-11-19 19:04:28 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:04:28 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:04:28 | D | - sum error = [ 174.4442, 153.9595, 140.7961, 131.1162, 119.8509] +24-11-19 19:04:28 | D | - best error = [ 64.9389, 64.9389, 64.9389, 64.9389, 64.9389] +24-11-19 19:04:28 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:04:28 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:04:28 | D | - sum error = [ 107.3807, 100.0329, 93.1239, 88.7405, 84.8693] +24-11-19 19:04:28 | D | - best error = [ 64.9389, 64.9389, 64.9389, 64.9389, 64.9389] +24-11-19 19:04:28 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:04:28 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:04:28 | D | - sum error = [ 79.8199, 73.0449, 69.9364, 65.9679] +24-11-19 19:04:28 | D | - best error = [ 64.9389, 64.9389, 64.9389, 64.9389] +24-11-19 19:04:28 | D | + error = 64.9389 +24-11-19 19:04:28 | D | + scale = [min=1.5607, max=23.2754] +24-11-19 19:04:35 | D | - Smoothing model.layers.18 +24-11-19 19:04:35 | D | - model.layers.18.self_attn.attn_k +24-11-19 19:04:35 | D | + w: None +24-11-19 19:04:35 | D | + x: None +24-11-19 19:04:35 | D | + y: sint8 +24-11-19 19:04:35 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:04:35 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:04:35 | D | + x - AbsMax +24-11-19 19:04:35 | D | + x = [min=1.4844, max=17.8594] +24-11-19 19:04:35 | D | + y - AbsMax +24-11-19 19:04:35 | D | + y = [min=1.5127, max=22.4375] +24-11-19 19:04:35 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:04:43 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:04:43 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:04:43 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:04:43 | D | - sum error = [ 121.3368, 116.7562, 112.2498, 108.0235, 103.9992] +24-11-19 19:04:43 | D | - best error = [ 121.3368, 116.7562, 112.2498, 108.0235, 103.9992] +24-11-19 19:04:43 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:04:43 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:04:43 | D | - sum error = [ 100.0245, 97.3002, 95.1598, 93.5306, 91.7219] +24-11-19 19:04:43 | D | - best error = [ 100.0245, 97.3002, 95.1598, 93.5306, 91.7219] +24-11-19 19:04:43 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:04:43 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:04:43 | D | - sum error = [ 89.4479, 88.1076, 85.7930, 83.5164, 81.0687] +24-11-19 19:04:43 | D | - best error = [ 89.4479, 88.1076, 85.7930, 83.5164, 81.0687] +24-11-19 19:04:43 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:04:43 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:04:43 | D | - sum error = [ 79.6369, 78.4767, 77.7844, 76.9709, 75.4120] +24-11-19 19:04:43 | D | - best error = [ 79.6369, 78.4767, 77.7844, 76.9709, 75.4120] +24-11-19 19:04:43 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:04:43 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:04:43 | D | - sum error = [ 245.3794, 216.8021, 195.6054, 178.3176, 162.8831] +24-11-19 19:04:43 | D | - best error = [ 75.4120, 75.4120, 75.4120, 75.4120, 75.4120] +24-11-19 19:04:43 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:04:43 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:04:43 | D | - sum error = [ 148.4314, 137.3956, 128.4928, 119.4872, 112.0514] +24-11-19 19:04:43 | D | - best error = [ 75.4120, 75.4120, 75.4120, 75.4120, 75.4120] +24-11-19 19:04:43 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:04:43 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:04:43 | D | - sum error = [ 105.1128, 98.7404, 93.6893, 89.4097, 86.8676] +24-11-19 19:04:43 | D | - best error = [ 75.4120, 75.4120, 75.4120, 75.4120, 75.4120] +24-11-19 19:04:43 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:04:43 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:04:43 | D | - sum error = [ 82.4209, 78.6670, 77.7587, 76.5489] +24-11-19 19:04:43 | D | - best error = [ 75.4120, 75.4120, 75.4120, 75.4120] +24-11-19 19:04:43 | D | + error = 75.4120 +24-11-19 19:04:43 | D | + scale = [min=1.4817, max=19.2055] +24-11-19 19:04:50 | D | - Smoothing model.layers.19 +24-11-19 19:04:50 | D | - model.layers.19.self_attn.attn_k +24-11-19 19:04:50 | D | + w: None +24-11-19 19:04:50 | D | + x: None +24-11-19 19:04:50 | D | + y: sint8 +24-11-19 19:04:50 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:04:50 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:04:50 | D | + x - AbsMax +24-11-19 19:04:50 | D | + x = [min=1.6582, max=17.9062] +24-11-19 19:04:51 | D | + y - AbsMax +24-11-19 19:04:51 | D | + y = [min=1.3662, max=23.0000] +24-11-19 19:04:51 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:04:58 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:04:58 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:04:58 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:04:58 | D | - sum error = [ 115.2352, 111.7047, 107.7932, 102.6576, 98.2449] +24-11-19 19:04:58 | D | - best error = [ 115.2352, 111.7047, 107.7932, 102.6576, 98.2449] +24-11-19 19:04:58 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:04:58 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:04:58 | D | - sum error = [ 95.1150, 92.5190, 88.7240, 85.8527, 84.8628] +24-11-19 19:04:58 | D | - best error = [ 95.1150, 92.5190, 88.7240, 85.8527, 84.8628] +24-11-19 19:04:58 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:04:58 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:04:58 | D | - sum error = [ 83.0633, 80.6343, 78.8196, 76.8089, 75.5965] +24-11-19 19:04:58 | D | - best error = [ 83.0633, 80.6343, 78.8196, 76.8089, 75.5965] +24-11-19 19:04:58 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:04:58 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:04:58 | D | - sum error = [ 74.1095, 72.4249, 71.7556, 70.2395, 69.7695] +24-11-19 19:04:58 | D | - best error = [ 74.1095, 72.4249, 71.7556, 70.2395, 69.7695] +24-11-19 19:04:58 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:04:58 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:04:58 | D | - sum error = [ 256.4257, 228.2687, 203.8998, 184.3285, 166.6241] +24-11-19 19:04:58 | D | - best error = [ 69.7695, 69.7695, 69.7695, 69.7695, 69.7695] +24-11-19 19:04:58 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:04:58 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:04:58 | D | - sum error = [ 151.6238, 138.5699, 129.4812, 120.8802, 113.5060] +24-11-19 19:04:58 | D | - best error = [ 69.7695, 69.7695, 69.7695, 69.7695, 69.7695] +24-11-19 19:04:58 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:04:58 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:04:58 | D | - sum error = [ 104.8479, 96.7185, 89.3960, 84.7945, 81.2600] +24-11-19 19:04:58 | D | - best error = [ 69.7695, 69.7695, 69.7695, 69.7695, 69.7695] +24-11-19 19:04:58 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:04:58 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:04:58 | D | - sum error = [ 78.3223, 75.5882, 73.1606, 70.2875] +24-11-19 19:04:58 | D | - best error = [ 69.7695, 69.7695, 69.7695, 69.7695] +24-11-19 19:04:58 | D | + error = 69.7695 +24-11-19 19:04:58 | D | + scale = [min=1.3451, max=19.6626] +24-11-19 19:05:05 | D | - Smoothing model.layers.20 +24-11-19 19:05:05 | D | - model.layers.20.self_attn.attn_k +24-11-19 19:05:05 | D | + w: None +24-11-19 19:05:05 | D | + x: None +24-11-19 19:05:05 | D | + y: sint8 +24-11-19 19:05:05 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:05:05 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:05:05 | D | + x - AbsMax +24-11-19 19:05:05 | D | + x = [min=1.3486, max=19.3906] +24-11-19 19:05:05 | D | + y - AbsMax +24-11-19 19:05:05 | D | + y = [min=1.2031, max=22.0000] +24-11-19 19:05:05 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:05:13 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:05:13 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:05:13 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:05:13 | D | - sum error = [ 109.2531, 106.0931, 101.5399, 97.2202, 93.7378] +24-11-19 19:05:13 | D | - best error = [ 109.2531, 106.0931, 101.5399, 97.2202, 93.7378] +24-11-19 19:05:13 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:05:13 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:05:13 | D | - sum error = [ 92.2830, 89.2812, 86.2809, 84.4490, 83.2031] +24-11-19 19:05:13 | D | - best error = [ 92.2830, 89.2812, 86.2809, 84.4490, 83.2031] +24-11-19 19:05:13 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:05:13 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:05:13 | D | - sum error = [ 81.9549, 81.2345, 79.2660, 78.6104, 75.7168] +24-11-19 19:05:13 | D | - best error = [ 81.9549, 81.2345, 79.2660, 78.6104, 75.7168] +24-11-19 19:05:13 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:05:13 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:05:13 | D | - sum error = [ 74.1725, 73.4752, 71.8994, 70.3654, 68.9584] +24-11-19 19:05:13 | D | - best error = [ 74.1725, 73.4752, 71.8994, 70.3654, 68.9584] +24-11-19 19:05:13 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:05:13 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:05:13 | D | - sum error = [ 249.9975, 227.4349, 207.7789, 187.0166, 170.0908] +24-11-19 19:05:13 | D | - best error = [ 68.9584, 68.9584, 68.9584, 68.9584, 68.9584] +24-11-19 19:05:13 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:05:13 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:05:13 | D | - sum error = [ 152.7598, 141.3602, 126.0956, 115.2151, 111.9169] +24-11-19 19:05:13 | D | - best error = [ 68.9584, 68.9584, 68.9584, 68.9584, 68.9584] +24-11-19 19:05:13 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:05:13 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:05:13 | D | - sum error = [ 102.0886, 94.6054, 88.6440, 84.3816, 81.3475] +24-11-19 19:05:13 | D | - best error = [ 68.9584, 68.9584, 68.9584, 68.9584, 68.9584] +24-11-19 19:05:13 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:05:13 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:05:13 | D | - sum error = [ 78.9076, 75.6783, 74.0426, 70.0807] +24-11-19 19:05:13 | D | - best error = [ 68.9584, 68.9584, 68.9584, 68.9584] +24-11-19 19:05:13 | D | + error = 68.9584 +24-11-19 19:05:13 | D | + scale = [min=1.1921, max=18.8496] +24-11-19 19:05:20 | D | - Smoothing model.layers.21 +24-11-19 19:05:20 | D | - model.layers.21.self_attn.attn_k +24-11-19 19:05:20 | D | + w: None +24-11-19 19:05:20 | D | + x: None +24-11-19 19:05:20 | D | + y: sint8 +24-11-19 19:05:20 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:05:20 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:05:20 | D | + x - AbsMax +24-11-19 19:05:20 | D | + x = [min=1.1523, max=19.7500] +24-11-19 19:05:20 | D | + y - AbsMax +24-11-19 19:05:20 | D | + y = [min=1.1641, max=23.0781] +24-11-19 19:05:20 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:05:27 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:05:27 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:05:27 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:05:27 | D | - sum error = [ 115.8834, 110.7742, 105.6946, 103.0396, 99.3401] +24-11-19 19:05:27 | D | - best error = [ 115.8834, 110.7742, 105.6946, 103.0396, 99.3401] +24-11-19 19:05:27 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:05:27 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:05:27 | D | - sum error = [ 96.1711, 92.8839, 91.1089, 89.3962, 86.0816] +24-11-19 19:05:27 | D | - best error = [ 96.1711, 92.8839, 91.1089, 89.3962, 86.0816] +24-11-19 19:05:27 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:05:27 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:05:27 | D | - sum error = [ 84.6621, 81.8986, 79.9653, 78.9270, 78.0512] +24-11-19 19:05:27 | D | - best error = [ 84.6621, 81.8986, 79.9653, 78.9270, 78.0512] +24-11-19 19:05:27 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:05:27 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:05:27 | D | - sum error = [ 75.3127, 74.0835, 73.0764, 71.5893, 70.0050] +24-11-19 19:05:27 | D | - best error = [ 75.3127, 74.0835, 73.0764, 71.5893, 70.0050] +24-11-19 19:05:27 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:05:27 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:05:27 | D | - sum error = [ 272.2707, 241.4818, 215.8137, 194.1373, 180.0140] +24-11-19 19:05:27 | D | - best error = [ 70.0050, 70.0050, 70.0050, 70.0050, 70.0050] +24-11-19 19:05:27 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:05:27 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:05:27 | D | - sum error = [ 159.8926, 143.1309, 132.5119, 120.9751, 113.5905] +24-11-19 19:05:27 | D | - best error = [ 70.0050, 70.0050, 70.0050, 70.0050, 70.0050] +24-11-19 19:05:27 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:05:27 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:05:27 | D | - sum error = [ 105.8886, 99.8359, 92.7187, 88.9456, 83.4070] +24-11-19 19:05:27 | D | - best error = [ 70.0050, 70.0050, 70.0050, 70.0050, 70.0050] +24-11-19 19:05:27 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:05:27 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:05:27 | D | - sum error = [ 80.0753, 78.0143, 73.6812, 71.4808] +24-11-19 19:05:27 | D | - best error = [ 70.0050, 70.0050, 70.0050, 70.0050] +24-11-19 19:05:27 | D | + error = 70.0050 +24-11-19 19:05:27 | D | + scale = [min=1.1553, max=19.7261] +24-11-19 19:05:35 | D | - Smoothing model.layers.22 +24-11-19 19:05:35 | D | - model.layers.22.self_attn.attn_k +24-11-19 19:05:35 | D | + w: None +24-11-19 19:05:35 | D | + x: None +24-11-19 19:05:35 | D | + y: sint8 +24-11-19 19:05:35 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:05:35 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:05:35 | D | + x - AbsMax +24-11-19 19:05:35 | D | + x = [min=1.1621, max=20.6562] +24-11-19 19:05:35 | D | + y - AbsMax +24-11-19 19:05:35 | D | + y = [min=1.1426, max=25.5469] +24-11-19 19:05:35 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:05:42 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:05:42 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:05:42 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:05:42 | D | - sum error = [ 154.5830, 151.5216, 146.8099, 139.2115, 133.3572] +24-11-19 19:05:42 | D | - best error = [ 154.5830, 151.5216, 146.8099, 139.2115, 133.3572] +24-11-19 19:05:42 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:05:42 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:05:42 | D | - sum error = [ 129.9696, 128.9901, 124.3566, 123.3030, 120.9813] +24-11-19 19:05:42 | D | - best error = [ 129.9696, 128.9901, 124.3566, 123.3030, 120.9813] +24-11-19 19:05:42 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:05:42 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:05:42 | D | - sum error = [ 117.9249, 114.9502, 108.1954, 103.8889, 99.4249] +24-11-19 19:05:42 | D | - best error = [ 117.9249, 114.9502, 108.1954, 103.8889, 99.4249] +24-11-19 19:05:42 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:05:42 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:05:42 | D | - sum error = [ 96.9538, 95.5661, 93.8870, 92.9683, 90.0055] +24-11-19 19:05:42 | D | - best error = [ 96.9538, 95.5661, 93.8870, 92.9683, 90.0055] +24-11-19 19:05:42 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:05:42 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:05:42 | D | - sum error = [ 432.8173, 326.2102, 290.4845, 264.9907, 247.0701] +24-11-19 19:05:42 | D | - best error = [ 90.0055, 90.0055, 90.0055, 90.0055, 90.0055] +24-11-19 19:05:42 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:05:42 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:05:42 | D | - sum error = [ 221.6092, 213.1000, 189.7283, 165.7785, 153.6222] +24-11-19 19:05:42 | D | - best error = [ 90.0055, 90.0055, 90.0055, 90.0055, 90.0055] +24-11-19 19:05:42 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:05:42 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:05:42 | D | - sum error = [ 139.4801, 131.3892, 127.3219, 120.5583, 116.5390] +24-11-19 19:05:42 | D | - best error = [ 90.0055, 90.0055, 90.0055, 90.0055, 90.0055] +24-11-19 19:05:42 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:05:42 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:05:42 | D | - sum error = [ 107.8514, 100.4656, 96.1034, 92.3107] +24-11-19 19:05:42 | D | - best error = [ 90.0055, 90.0055, 90.0055, 90.0055] +24-11-19 19:05:42 | D | + error = 90.0055 +24-11-19 19:05:42 | D | + scale = [min=1.1350, max=21.7256] +24-11-19 19:05:50 | D | - Smoothing model.layers.23 +24-11-19 19:05:50 | D | - model.layers.23.self_attn.attn_k +24-11-19 19:05:50 | D | + w: None +24-11-19 19:05:50 | D | + x: None +24-11-19 19:05:50 | D | + y: sint8 +24-11-19 19:05:50 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:05:50 | D | + finished parsing calibration arguments, ram usage: 12.2 +24-11-19 19:05:50 | D | + x - AbsMax +24-11-19 19:05:50 | D | + x = [min=1.0938, max=18.7500] +24-11-19 19:05:50 | D | + y - AbsMax +24-11-19 19:05:50 | D | + y = [min=1.0469, max=24.5000] +24-11-19 19:05:50 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:05:57 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:05:57 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:05:57 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:05:57 | D | - sum error = [ 133.5701, 129.0765, 124.2718, 119.7242, 115.8328] +24-11-19 19:05:57 | D | - best error = [ 133.5701, 129.0765, 124.2718, 119.7242, 115.8328] +24-11-19 19:05:57 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:05:57 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:05:57 | D | - sum error = [ 114.0879, 111.1828, 108.7492, 105.9292, 103.6476] +24-11-19 19:05:57 | D | - best error = [ 114.0879, 111.1828, 108.7492, 105.9292, 103.6476] +24-11-19 19:05:57 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:05:57 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:05:57 | D | - sum error = [ 101.9240, 99.2168, 96.3025, 93.3207, 91.2695] +24-11-19 19:05:57 | D | - best error = [ 101.9240, 99.2168, 96.3025, 93.3207, 91.2695] +24-11-19 19:05:57 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:05:57 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:05:57 | D | - sum error = [ 89.4302, 87.5190, 86.6993, 85.5090, 84.6296] +24-11-19 19:05:57 | D | - best error = [ 89.4302, 87.5190, 86.6993, 85.5090, 84.6296] +24-11-19 19:05:57 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:05:57 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:05:57 | D | - sum error = [ 307.9043, 267.7400, 237.1959, 214.0379, 193.0160] +24-11-19 19:05:57 | D | - best error = [ 84.6296, 84.6296, 84.6296, 84.6296, 84.6296] +24-11-19 19:05:57 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:05:57 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:05:57 | D | - sum error = [ 176.3580, 161.3469, 149.3729, 138.3056, 127.3990] +24-11-19 19:05:57 | D | - best error = [ 84.6296, 84.6296, 84.6296, 84.6296, 84.6296] +24-11-19 19:05:57 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:05:57 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:05:57 | D | - sum error = [ 119.3898, 112.2468, 107.3574, 102.6307, 99.6231] +24-11-19 19:05:57 | D | - best error = [ 84.6296, 84.6296, 84.6296, 84.6296, 84.6296] +24-11-19 19:05:57 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:05:57 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:05:57 | D | - sum error = [ 95.8405, 90.4823, 87.6195, 84.8535] +24-11-19 19:05:57 | D | - best error = [ 84.6296, 84.6296, 84.6296, 84.6296] +24-11-19 19:05:57 | D | + error = 84.6296 +24-11-19 19:05:57 | D | + scale = [min=1.0445, max=20.8789] +24-11-19 19:06:05 | D | - Smoothing model.layers.24 +24-11-19 19:06:05 | D | - model.layers.24.self_attn.attn_k +24-11-19 19:06:05 | D | + w: None +24-11-19 19:06:05 | D | + x: None +24-11-19 19:06:05 | D | + y: sint8 +24-11-19 19:06:05 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:06:05 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:06:05 | D | + x - AbsMax +24-11-19 19:06:05 | D | + x = [min=1.0059, max=18.2188] +24-11-19 19:06:05 | D | + y - AbsMax +24-11-19 19:06:05 | D | + y = [min=1.0029, max=25.1875] +24-11-19 19:06:05 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:06:12 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:06:12 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:06:12 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:06:12 | D | - sum error = [ 161.8267, 154.8331, 147.6170, 142.7274, 136.2084] +24-11-19 19:06:12 | D | - best error = [ 161.8267, 154.8331, 147.6170, 142.7274, 136.2084] +24-11-19 19:06:12 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:06:12 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:06:12 | D | - sum error = [ 131.9338, 127.7955, 124.3648, 121.1652, 117.4740] +24-11-19 19:06:12 | D | - best error = [ 131.9338, 127.7955, 124.3648, 121.1652, 117.4740] +24-11-19 19:06:12 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:06:12 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:06:12 | D | - sum error = [ 113.2640, 111.0918, 108.2560, 105.7142, 103.2220] +24-11-19 19:06:12 | D | - best error = [ 113.2640, 111.0918, 108.2560, 105.7142, 103.2220] +24-11-19 19:06:12 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:06:12 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:06:12 | D | - sum error = [ 101.8279, 99.5097, 96.2850, 93.2178, 91.7045] +24-11-19 19:06:12 | D | - best error = [ 101.8279, 99.5097, 96.2850, 93.2178, 91.7045] +24-11-19 19:06:12 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:06:12 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:06:12 | D | - sum error = [ 345.1504, 315.5131, 283.5547, 251.9834, 227.3337] +24-11-19 19:06:12 | D | - best error = [ 91.7045, 91.7045, 91.7045, 91.7045, 91.7045] +24-11-19 19:06:12 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:06:12 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:06:12 | D | - sum error = [ 209.2598, 185.8867, 170.2454, 158.5534, 148.1941] +24-11-19 19:06:12 | D | - best error = [ 91.7045, 91.7045, 91.7045, 91.7045, 91.7045] +24-11-19 19:06:12 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:06:12 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:06:12 | D | - sum error = [ 136.7777, 129.4545, 120.7756, 115.5341, 108.1949] +24-11-19 19:06:12 | D | - best error = [ 91.7045, 91.7045, 91.7045, 91.7045, 91.7045] +24-11-19 19:06:12 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:06:12 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:06:12 | D | - sum error = [ 103.6753, 100.7622, 98.1304, 92.6854] +24-11-19 19:06:12 | D | - best error = [ 91.7045, 91.7045, 91.7045, 91.7045] +24-11-19 19:06:12 | D | + error = 91.7045 +24-11-19 19:06:12 | D | + scale = [min=1.0028, max=21.4351] +24-11-19 19:06:20 | D | - Smoothing model.layers.25 +24-11-19 19:06:20 | D | - model.layers.25.self_attn.attn_k +24-11-19 19:06:20 | D | + w: None +24-11-19 19:06:20 | D | + x: None +24-11-19 19:06:20 | D | + y: sint8 +24-11-19 19:06:20 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:06:20 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:06:20 | D | + x - AbsMax +24-11-19 19:06:20 | D | + x = [min=1.0840, max=18.4844] +24-11-19 19:06:20 | D | + y - AbsMax +24-11-19 19:06:20 | D | + y = [min=1.1045, max=23.4062] +24-11-19 19:06:20 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:06:27 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:06:27 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:06:27 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:06:27 | D | - sum error = [ 124.4955, 119.7991, 115.4817, 110.4804, 106.4021] +24-11-19 19:06:27 | D | - best error = [ 124.4955, 119.7991, 115.4817, 110.4804, 106.4021] +24-11-19 19:06:27 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:06:27 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:06:27 | D | - sum error = [ 103.0698, 100.6031, 97.4572, 94.2408, 92.3320] +24-11-19 19:06:27 | D | - best error = [ 103.0698, 100.6031, 97.4572, 94.2408, 92.3320] +24-11-19 19:06:27 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:06:27 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:06:27 | D | - sum error = [ 89.6070, 86.9234, 85.2917, 83.0622, 81.5800] +24-11-19 19:06:27 | D | - best error = [ 89.6070, 86.9234, 85.2917, 83.0622, 81.5800] +24-11-19 19:06:27 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:06:27 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:06:27 | D | - sum error = [ 80.7450, 79.8997, 78.0896, 76.0016, 75.3056] +24-11-19 19:06:27 | D | - best error = [ 80.7450, 79.8997, 78.0896, 76.0016, 75.3056] +24-11-19 19:06:27 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:06:27 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:06:27 | D | - sum error = [ 269.9083, 241.0349, 215.8141, 192.6236, 173.1228] +24-11-19 19:06:27 | D | - best error = [ 75.3056, 75.3056, 75.3056, 75.3056, 75.3056] +24-11-19 19:06:27 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:06:27 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:06:27 | D | - sum error = [ 156.0186, 144.3524, 132.3078, 122.8598, 114.3497] +24-11-19 19:06:27 | D | - best error = [ 75.3056, 75.3056, 75.3056, 75.3056, 75.3056] +24-11-19 19:06:27 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:06:27 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:06:27 | D | - sum error = [ 107.7168, 102.6006, 96.1715, 90.7319, 86.6623] +24-11-19 19:06:27 | D | - best error = [ 75.3056, 75.3056, 75.3056, 75.3056, 75.3056] +24-11-19 19:06:27 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:06:27 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:06:27 | D | - sum error = [ 83.5380, 81.1085, 78.5299, 76.0474] +24-11-19 19:06:27 | D | - best error = [ 75.3056, 75.3056, 75.3056, 75.3056] +24-11-19 19:06:27 | D | + error = 75.3056 +24-11-19 19:06:27 | D | + scale = [min=1.0990, max=19.9924] +24-11-19 19:06:35 | D | - Smoothing model.layers.26 +24-11-19 19:06:35 | D | - model.layers.26.self_attn.attn_k +24-11-19 19:06:35 | D | + w: None +24-11-19 19:06:35 | D | + x: None +24-11-19 19:06:35 | D | + y: sint8 +24-11-19 19:06:35 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:06:35 | D | + finished parsing calibration arguments, ram usage: 12.1 +24-11-19 19:06:35 | D | + x - AbsMax +24-11-19 19:06:35 | D | + x = [min=1.0654, max=19.7500] +24-11-19 19:06:35 | D | + y - AbsMax +24-11-19 19:06:35 | D | + y = [min=1.0107, max=24.1562] +24-11-19 19:06:35 | D | + finished reseting calibrator, ram usage: 12.2 +24-11-19 19:06:42 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:06:42 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:06:42 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:06:42 | D | - sum error = [ 176.6294, 170.6721, 162.9413, 157.3015, 151.3187] +24-11-19 19:06:42 | D | - best error = [ 176.6294, 170.6721, 162.9413, 157.3015, 151.3187] +24-11-19 19:06:42 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:06:42 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:06:42 | D | - sum error = [ 146.2965, 141.6896, 137.0569, 135.1660, 130.7110] +24-11-19 19:06:42 | D | - best error = [ 146.2965, 141.6896, 137.0569, 135.1660, 130.7110] +24-11-19 19:06:42 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:06:42 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:06:42 | D | - sum error = [ 125.3298, 122.7710, 119.0498, 117.0996, 115.3907] +24-11-19 19:06:42 | D | - best error = [ 125.3298, 122.7710, 119.0498, 117.0996, 115.3907] +24-11-19 19:06:42 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:06:42 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:06:42 | D | - sum error = [ 113.7602, 108.6447, 107.4863, 104.6015, 101.7446] +24-11-19 19:06:42 | D | - best error = [ 113.7602, 108.6447, 107.4863, 104.6015, 101.7446] +24-11-19 19:06:42 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:06:42 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:06:42 | D | - sum error = [ 402.3793, 355.5022, 322.9071, 291.7374, 260.8252] +24-11-19 19:06:42 | D | - best error = [ 101.7446, 101.7446, 101.7446, 101.7446, 101.7446] +24-11-19 19:06:42 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:06:42 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:06:42 | D | - sum error = [ 233.4702, 214.9958, 198.0702, 181.9368, 166.9791] +24-11-19 19:06:42 | D | - best error = [ 101.7446, 101.7446, 101.7446, 101.7446, 101.7446] +24-11-19 19:06:42 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:06:42 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:06:42 | D | - sum error = [ 158.5837, 149.4075, 136.7975, 130.3050, 126.7558] +24-11-19 19:06:42 | D | - best error = [ 101.7446, 101.7446, 101.7446, 101.7446, 101.7446] +24-11-19 19:06:42 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:06:42 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:06:42 | D | - sum error = [ 117.1433, 117.0846, 108.9640, 104.2982] +24-11-19 19:06:42 | D | - best error = [ 101.7446, 101.7446, 101.7446, 101.7446] +24-11-19 19:06:42 | D | + error = 101.7446 +24-11-19 19:06:42 | D | + scale = [min=1.0102, max=20.6005] +24-11-19 19:06:49 | D | - Smoothing model.layers.27 +24-11-19 19:06:49 | D | - model.layers.27.self_attn.attn_k +24-11-19 19:06:49 | D | + w: None +24-11-19 19:06:49 | D | + x: None +24-11-19 19:06:49 | D | + y: sint8 +24-11-19 19:06:49 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:06:49 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:06:50 | D | + x - AbsMax +24-11-19 19:06:50 | D | + x = [min=1.9199, max=19.4375] +24-11-19 19:06:50 | D | + y - AbsMax +24-11-19 19:06:50 | D | + y = [min=1.9277, max=26.6250] +24-11-19 19:06:50 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:06:57 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:06:57 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:06:57 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:06:57 | D | - sum error = [ 187.8449, 180.4803, 174.5803, 168.7410, 163.9097] +24-11-19 19:06:57 | D | - best error = [ 187.8449, 180.4803, 174.5803, 168.7410, 163.9097] +24-11-19 19:06:57 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:06:57 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:06:57 | D | - sum error = [ 158.8646, 154.2019, 150.3960, 145.6950, 142.4149] +24-11-19 19:06:57 | D | - best error = [ 158.8646, 154.2019, 150.3960, 145.6950, 142.4149] +24-11-19 19:06:57 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:06:57 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:06:57 | D | - sum error = [ 139.1551, 136.1943, 132.2128, 129.4009, 126.9880] +24-11-19 19:06:57 | D | - best error = [ 139.1551, 136.1943, 132.2128, 129.4009, 126.9880] +24-11-19 19:06:57 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:06:57 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:06:57 | D | - sum error = [ 123.8790, 121.6354, 119.1425, 117.1206, 116.3880] +24-11-19 19:06:57 | D | - best error = [ 123.8790, 121.6354, 119.1425, 117.1206, 116.3880] +24-11-19 19:06:57 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:06:57 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:06:57 | D | - sum error = [ 391.5092, 346.9194, 311.0756, 279.9701, 255.6172] +24-11-19 19:06:57 | D | - best error = [ 116.3880, 116.3880, 116.3880, 116.3880, 116.3880] +24-11-19 19:06:57 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:06:57 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:06:57 | D | - sum error = [ 233.2942, 216.5682, 199.5965, 184.5872, 171.4483] +24-11-19 19:06:57 | D | - best error = [ 116.3880, 116.3880, 116.3880, 116.3880, 116.3880] +24-11-19 19:06:57 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:06:57 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:06:57 | D | - sum error = [ 161.9577, 153.6735, 147.2471, 141.6402, 135.3242] +24-11-19 19:06:57 | D | - best error = [ 116.3880, 116.3880, 116.3880, 116.3880, 116.3880] +24-11-19 19:06:57 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:06:57 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:06:57 | D | - sum error = [ 129.6566, 124.1971, 120.2212, 116.9232] +24-11-19 19:06:57 | D | - best error = [ 116.3880, 116.3880, 116.3880, 116.3880] +24-11-19 19:06:57 | D | + error = 116.3880 +24-11-19 19:06:57 | D | + scale = [min=1.8655, max=22.5957] +24-11-19 19:07:04 | D | - Smoothing model.layers.28 +24-11-19 19:07:04 | D | - model.layers.28.self_attn.attn_k +24-11-19 19:07:04 | D | + w: None +24-11-19 19:07:04 | D | + x: None +24-11-19 19:07:04 | D | + y: sint8 +24-11-19 19:07:04 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:07:04 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:07:04 | D | + x - AbsMax +24-11-19 19:07:04 | D | + x = [min=1.3467, max=20.7812] +24-11-19 19:07:04 | D | + y - AbsMax +24-11-19 19:07:04 | D | + y = [min=1.3350, max=24.9219] +24-11-19 19:07:04 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:07:11 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:07:11 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:07:11 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:07:11 | D | - sum error = [ 176.2940, 170.9585, 163.9334, 157.4644, 152.0732] +24-11-19 19:07:11 | D | - best error = [ 176.2940, 170.9585, 163.9334, 157.4644, 152.0732] +24-11-19 19:07:11 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:07:11 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:07:11 | D | - sum error = [ 145.8097, 141.5871, 137.1227, 134.1868, 131.6519] +24-11-19 19:07:11 | D | - best error = [ 145.8097, 141.5871, 137.1227, 134.1868, 131.6519] +24-11-19 19:07:11 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:07:11 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:07:11 | D | - sum error = [ 128.2209, 125.7053, 122.4925, 121.3563, 119.0794] +24-11-19 19:07:11 | D | - best error = [ 128.2209, 125.7053, 122.4925, 121.3563, 119.0794] +24-11-19 19:07:11 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:07:11 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:07:11 | D | - sum error = [ 116.8512, 114.3282, 111.6986, 109.5080, 107.9740] +24-11-19 19:07:11 | D | - best error = [ 116.8512, 114.3282, 111.6986, 109.5080, 107.9740] +24-11-19 19:07:11 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:07:11 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:07:11 | D | - sum error = [ 432.6196, 385.8789, 346.4381, 307.2907, 277.5208] +24-11-19 19:07:11 | D | - best error = [ 107.9740, 107.9740, 107.9740, 107.9740, 107.9740] +24-11-19 19:07:11 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:07:11 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:07:11 | D | - sum error = [ 249.4027, 225.4546, 206.1540, 191.7069, 177.2122] +24-11-19 19:07:11 | D | - best error = [ 107.9740, 107.9740, 107.9740, 107.9740, 107.9740] +24-11-19 19:07:11 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:07:11 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:07:11 | D | - sum error = [ 163.2227, 152.0773, 143.2166, 133.6014, 127.9676] +24-11-19 19:07:11 | D | - best error = [ 107.9740, 107.9740, 107.9740, 107.9740, 107.9740] +24-11-19 19:07:11 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:07:11 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:07:11 | D | - sum error = [ 123.6863, 118.7282, 114.6157, 109.9148] +24-11-19 19:07:11 | D | - best error = [ 107.9740, 107.9740, 107.9740, 107.9740] +24-11-19 19:07:11 | D | + error = 107.9740 +24-11-19 19:07:11 | D | + scale = [min=1.3158, max=21.2203] +24-11-19 19:07:19 | D | - Smoothing model.layers.29 +24-11-19 19:07:19 | D | - model.layers.29.self_attn.attn_k +24-11-19 19:07:19 | D | + w: None +24-11-19 19:07:19 | D | + x: None +24-11-19 19:07:19 | D | + y: sint8 +24-11-19 19:07:19 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:07:19 | D | + finished parsing calibration arguments, ram usage: 12.0 +24-11-19 19:07:19 | D | + x - AbsMax +24-11-19 19:07:19 | D | + x = [min=1.9150, max=19.4062] +24-11-19 19:07:19 | D | + y - AbsMax +24-11-19 19:07:19 | D | + y = [min=1.3242, max=28.0312] +24-11-19 19:07:19 | D | + finished reseting calibrator, ram usage: 12.0 +24-11-19 19:07:26 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:07:26 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:07:26 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:07:26 | D | - sum error = [ 208.3516, 198.6404, 190.3080, 184.3759, 176.2336] +24-11-19 19:07:26 | D | - best error = [ 208.3516, 198.6404, 190.3080, 184.3759, 176.2336] +24-11-19 19:07:26 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:07:26 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:07:26 | D | - sum error = [ 169.8585, 164.7273, 159.0953, 153.9140, 148.9205] +24-11-19 19:07:26 | D | - best error = [ 169.8585, 164.7273, 159.0953, 153.9140, 148.9205] +24-11-19 19:07:26 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:07:26 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:07:26 | D | - sum error = [ 144.1357, 140.4974, 136.6752, 132.4619, 128.9950] +24-11-19 19:07:26 | D | - best error = [ 144.1357, 140.4974, 136.6752, 132.4619, 128.9950] +24-11-19 19:07:26 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:07:26 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:07:26 | D | - sum error = [ 125.7766, 123.6149, 120.7668, 118.6932, 116.8830] +24-11-19 19:07:26 | D | - best error = [ 125.7766, 123.6149, 120.7668, 118.6932, 116.8830] +24-11-19 19:07:26 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:07:26 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:07:26 | D | - sum error = [ 489.0459, 431.4095, 380.9155, 340.3689, 305.3898] +24-11-19 19:07:26 | D | - best error = [ 116.8830, 116.8830, 116.8830, 116.8830, 116.8830] +24-11-19 19:07:26 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:07:26 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:07:26 | D | - sum error = [ 274.1419, 246.9323, 223.0533, 204.3887, 190.5014] +24-11-19 19:07:26 | D | - best error = [ 116.8830, 116.8830, 116.8830, 116.8830, 116.8830] +24-11-19 19:07:26 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:07:26 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:07:26 | D | - sum error = [ 178.1513, 166.5563, 156.2291, 147.9483, 140.7211] +24-11-19 19:07:26 | D | - best error = [ 116.8830, 116.8830, 116.8830, 116.8830, 116.8830] +24-11-19 19:07:26 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:07:26 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:07:26 | D | - sum error = [ 134.7850, 126.9145, 122.6121, 118.2869] +24-11-19 19:07:26 | D | - best error = [ 116.8830, 116.8830, 116.8830, 116.8830] +24-11-19 19:07:26 | D | + error = 116.8830 +24-11-19 19:07:26 | D | + scale = [min=1.3058, max=23.7280] +24-11-19 19:07:34 | D | - Smoothing model.layers.30 +24-11-19 19:07:34 | D | - model.layers.30.self_attn.attn_k +24-11-19 19:07:34 | D | + w: None +24-11-19 19:07:34 | D | + x: None +24-11-19 19:07:34 | D | + y: sint8 +24-11-19 19:07:34 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:07:34 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:07:34 | D | + x - AbsMax +24-11-19 19:07:34 | D | + x = [min=1.8291, max=18.8438] +24-11-19 19:07:34 | D | + y - AbsMax +24-11-19 19:07:34 | D | + y = [min=1.8379, max=23.5938] +24-11-19 19:07:34 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:07:41 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:07:41 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:07:41 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:07:41 | D | - sum error = [ 190.3850, 182.9329, 176.5341, 170.1066, 164.2133] +24-11-19 19:07:41 | D | - best error = [ 190.3850, 182.9329, 176.5341, 170.1066, 164.2133] +24-11-19 19:07:41 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:07:41 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:07:41 | D | - sum error = [ 161.8397, 156.0007, 153.2589, 148.3334, 142.6647] +24-11-19 19:07:41 | D | - best error = [ 161.8397, 156.0007, 153.2589, 148.3334, 142.6647] +24-11-19 19:07:41 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:07:41 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:07:41 | D | - sum error = [ 139.7519, 136.8929, 134.9450, 132.8190, 130.7213] +24-11-19 19:07:41 | D | - best error = [ 139.7519, 136.8929, 134.9450, 132.8190, 130.7213] +24-11-19 19:07:41 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:07:41 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:07:41 | D | - sum error = [ 128.0375, 125.9413, 124.4638, 123.8639, 121.9439] +24-11-19 19:07:41 | D | - best error = [ 128.0375, 125.9413, 124.4638, 123.8639, 121.9439] +24-11-19 19:07:41 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:07:41 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:07:41 | D | - sum error = [ 371.9354, 337.4149, 306.4796, 280.6675, 257.1954] +24-11-19 19:07:41 | D | - best error = [ 121.9439, 121.9439, 121.9439, 121.9439, 121.9439] +24-11-19 19:07:41 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:07:41 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:07:41 | D | - sum error = [ 235.9391, 216.2860, 200.8942, 184.6022, 172.0330] +24-11-19 19:07:41 | D | - best error = [ 121.9439, 121.9439, 121.9439, 121.9439, 121.9439] +24-11-19 19:07:41 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:07:41 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:07:41 | D | - sum error = [ 162.4561, 156.0973, 147.9637, 140.0101, 135.0797] +24-11-19 19:07:41 | D | - best error = [ 121.9439, 121.9439, 121.9439, 121.9439, 121.9439] +24-11-19 19:07:41 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:07:41 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:07:41 | D | - sum error = [ 132.1672, 128.3193, 124.2607, 123.6011] +24-11-19 19:07:41 | D | - best error = [ 121.9439, 121.9439, 121.9439, 121.9439] +24-11-19 19:07:41 | D | + error = 121.9439 +24-11-19 19:07:41 | D | + scale = [min=1.7828, max=20.1445] +24-11-19 19:07:48 | D | - Smoothing model.layers.31 +24-11-19 19:07:48 | D | - model.layers.31.self_attn.attn_k +24-11-19 19:07:48 | D | + w: None +24-11-19 19:07:48 | D | + x: None +24-11-19 19:07:48 | D | + y: sint8 +24-11-19 19:07:48 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:07:48 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:07:48 | D | + x - AbsMax +24-11-19 19:07:48 | D | + x = [min=2.4414, max=18.7188] +24-11-19 19:07:48 | D | + y - AbsMax +24-11-19 19:07:48 | D | + y = [min=1.7520, max=27.7344] +24-11-19 19:07:48 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:07:55 | D | - x / w range = AbsMax / AbsMax +24-11-19 19:07:55 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 19:07:55 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:07:55 | D | - sum error = [ 256.1913, 232.8340, 228.3092, 222.2790, 224.7645] +24-11-19 19:07:55 | D | - best error = [ 256.1913, 232.8340, 228.3092, 222.2790, 222.2790] +24-11-19 19:07:55 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 19:07:55 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:07:55 | D | - sum error = [ 197.8928, 193.1070, 176.9190, 172.2750, 162.4194] +24-11-19 19:07:55 | D | - best error = [ 197.8928, 193.1070, 176.9190, 172.2750, 162.4194] +24-11-19 19:07:55 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 19:07:55 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:07:55 | D | - sum error = [ 159.5317, 153.2872, 149.4159, 146.4509, 138.9807] +24-11-19 19:07:55 | D | - best error = [ 159.5317, 153.2872, 149.4159, 146.4509, 138.9807] +24-11-19 19:07:55 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:07:55 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 19:07:55 | D | - sum error = [ 137.8195, 132.3851, 130.0834, 124.5412, 124.2167] +24-11-19 19:07:55 | D | - best error = [ 137.8195, 132.3851, 130.0834, 124.5412, 124.2167] +24-11-19 19:07:55 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 19:07:55 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 19:07:55 | D | - sum error = [ 515.5238, 463.1440, 413.1954, 390.8741, 342.0212] +24-11-19 19:07:55 | D | - best error = [ 124.2167, 124.2167, 124.2167, 124.2167, 124.2167] +24-11-19 19:07:55 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 19:07:55 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 19:07:55 | D | - sum error = [ 310.2220, 282.7929, 263.3723, 232.3214, 210.1590] +24-11-19 19:07:55 | D | - best error = [ 124.2167, 124.2167, 124.2167, 124.2167, 124.2167] +24-11-19 19:07:55 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 19:07:55 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 19:07:55 | D | - sum error = [ 198.2946, 186.1040, 176.9863, 165.1639, 152.6569] +24-11-19 19:07:55 | D | - best error = [ 124.2167, 124.2167, 124.2167, 124.2167, 124.2167] +24-11-19 19:07:55 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 19:07:55 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 19:07:55 | D | - sum error = [ 142.2854, 136.6341, 129.2876, 124.3030] +24-11-19 19:07:55 | D | - best error = [ 124.2167, 124.2167, 124.2167, 124.2167] +24-11-19 19:07:55 | D | + error = 124.2167 +24-11-19 19:07:55 | D | + scale = [min=1.7035, max=23.4892] +24-11-19 19:07:56 | I | - Saving smooth scales to runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/llama-2-7b-instruct-together-32k.pt +24-11-19 19:07:56 | I | - Linking smooth scales to runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.185856.RUNNING/cache/smooth.pt +24-11-19 19:07:56 | I | * Quantizing weights +24-11-19 19:07:56 | I | - Generating weight quantizer settings +24-11-19 19:07:56 | D | Starting new HTTPS connection (4): huggingface.co:443 +24-11-19 19:08:02 | D | Starting new HTTPS connection (5): huggingface.co:443 +24-11-19 19:08:14 | D | Starting new HTTPS connection (2): s3.amazonaws.com:443 +24-11-19 19:08:26 | W | Repo card metadata block was not found. Setting CardData to empty. +24-11-19 19:08:26 | D | Starting new HTTPS connection (6): huggingface.co:443 +24-11-19 19:08:38 | W | Using the latest cached version of the dataset since mit-han-lab/pile-val-backup couldn't be found on the Hugging Face Hub +24-11-19 19:08:38 | W | Found the latest cached dataset configuration 'default' at /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4 (last modified on Tue Oct 8 18:58:39 2024). +24-11-19 19:08:38 | D | Attempting to acquire lock 23438308977760 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 19:08:38 | D | Lock 23438308977760 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 19:08:38 | D | open file: /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4/dataset_info.json +24-11-19 19:08:38 | D | Attempting to release lock 23438308977760 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 19:08:38 | D | Lock 23438308977760 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 19:08:53 | D | - Quantizing layer model.layers.0 +24-11-19 19:08:53 | D | - Calibrating model.layers.0.self_attn.q_proj.weight +24-11-19 19:08:53 | D | + w: sint8 +24-11-19 19:08:53 | D | + x: None +24-11-19 19:08:53 | D | + y: None +24-11-19 19:08:53 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:08:53 | D | + finished parsing calibration arguments, ram usage: 12.0 +24-11-19 19:08:53 | D | + finished reseting calibrator, ram usage: 12.0 +24-11-19 19:08:54 | D | + finished calculating the original outputs, ram usage: 12.0 +24-11-19 19:08:54 | D | - range ratio = [ 1.0000] +24-11-19 19:08:54 | D | sum error = [ 0.1420] +24-11-19 19:08:54 | D | best error = [ 0.1420] +24-11-19 19:09:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:09:07 | D | sum error = [ 0.1428, 0.1457, 0.1490, 0.1555, 0.1687] +24-11-19 19:09:07 | D | best error = [ 0.1420, 0.1420, 0.1420, 0.1420, 0.1420] +24-11-19 19:09:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:09:07 | D | sum error = [ 0.1841, 0.2059, 0.2316, 0.2553, 0.2869] +24-11-19 19:09:07 | D | best error = [ 0.1420, 0.1420, 0.1420, 0.1420, 0.1420] +24-11-19 19:09:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:09:07 | D | sum error = [ 0.3291, 0.3732, 0.4251, 0.4849, 0.5542] +24-11-19 19:09:07 | D | best error = [ 0.1420, 0.1420, 0.1420, 0.1420, 0.1420] +24-11-19 19:09:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:09:07 | D | sum error = [ 0.6361, 0.7289, 0.8119, 0.9243, 1.0487] +24-11-19 19:09:07 | D | best error = [ 0.1420, 0.1420, 0.1420, 0.1420, 0.1420] +24-11-19 19:09:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:09:07 | D | sum error = [ 1.1699, 1.3174, 1.4808, 1.6674, 1.8691] +24-11-19 19:09:07 | D | best error = [ 0.1420, 0.1420, 0.1420, 0.1420, 0.1420] +24-11-19 19:09:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:09:07 | D | sum error = [ 2.0882, 2.3296, 2.5975, 2.8946, 3.2224] +24-11-19 19:09:07 | D | best error = [ 0.1420, 0.1420, 0.1420, 0.1420, 0.1420] +24-11-19 19:09:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:09:07 | D | sum error = [ 3.5769, 3.9610, 4.3830, 4.8485, 5.3513] +24-11-19 19:09:07 | D | best error = [ 0.1420, 0.1420, 0.1420, 0.1420, 0.1420] +24-11-19 19:09:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:09:07 | D | sum error = [ 5.8957, 6.4915, 7.1415, 7.8367, 8.5972] +24-11-19 19:09:07 | D | best error = [ 0.1420, 0.1420, 0.1420, 0.1420, 0.1420] +24-11-19 19:09:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:09:07 | D | sum error = [ 9.4221, 10.2950, 11.2400, 12.2652, 13.3626] +24-11-19 19:09:07 | D | best error = [ 0.1420, 0.1420, 0.1420, 0.1420, 0.1420] +24-11-19 19:09:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:09:07 | D | sum error = [ 14.5410, 15.7974, 17.1439, 18.5785, 20.1055] +24-11-19 19:09:07 | D | best error = [ 0.1420, 0.1420, 0.1420, 0.1420, 0.1420] +24-11-19 19:09:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:09:07 | D | sum error = [ 21.7319, 23.4551, 25.2829, 27.2287, 29.3039] +24-11-19 19:09:07 | D | best error = [ 0.1420, 0.1420, 0.1420, 0.1420, 0.1420] +24-11-19 19:09:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:09:07 | D | sum error = [ 31.4882, 33.8188, 36.2636, 38.8352, 41.5710] +24-11-19 19:09:07 | D | best error = [ 0.1420, 0.1420, 0.1420, 0.1420, 0.1420] +24-11-19 19:09:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:09:07 | D | sum error = [ 44.4375, 47.4713, 50.6462, 53.9937, 57.5014] +24-11-19 19:09:07 | D | best error = [ 0.1420, 0.1420, 0.1420, 0.1420, 0.1420] +24-11-19 19:09:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:09:07 | D | sum error = [ 61.1948, 65.0797, 69.1233, 73.3657, 77.8089] +24-11-19 19:09:07 | D | best error = [ 0.1420, 0.1420, 0.1420, 0.1420, 0.1420] +24-11-19 19:09:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:09:07 | D | sum error = [ 82.4655, 87.3163, 92.4202, 97.7426, 103.2979] +24-11-19 19:09:07 | D | best error = [ 0.1420, 0.1420, 0.1420, 0.1420, 0.1420] +24-11-19 19:09:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:09:07 | D | sum error = [ 109.1124, 115.1729, 121.5069, 128.1111, 135.0178] +24-11-19 19:09:07 | D | best error = [ 0.1420, 0.1420, 0.1420, 0.1420, 0.1420] +24-11-19 19:09:07 | D | + error = [0.1420] +24-11-19 19:09:08 | D | - Calibrating model.layers.0.self_attn.k_proj.weight +24-11-19 19:09:08 | D | + w: sint8 +24-11-19 19:09:08 | D | + x: None +24-11-19 19:09:08 | D | + y: None +24-11-19 19:09:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:09:08 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:09:08 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:09:08 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:09:08 | D | - range ratio = [ 1.0000] +24-11-19 19:09:08 | D | sum error = [ 0.1549] +24-11-19 19:09:08 | D | best error = [ 0.1549] +24-11-19 19:09:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:09:21 | D | sum error = [ 0.1458, 0.1582, 0.1578, 0.1626, 0.1717] +24-11-19 19:09:21 | D | best error = [ 0.1458, 0.1458, 0.1458, 0.1458, 0.1458] +24-11-19 19:09:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:09:21 | D | sum error = [ 0.1929, 0.2206, 0.2346, 0.2676, 0.2940] +24-11-19 19:09:21 | D | best error = [ 0.1458, 0.1458, 0.1458, 0.1458, 0.1458] +24-11-19 19:09:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:09:21 | D | sum error = [ 0.3356, 0.3654, 0.4200, 0.4689, 0.5624] +24-11-19 19:09:21 | D | best error = [ 0.1458, 0.1458, 0.1458, 0.1458, 0.1458] +24-11-19 19:09:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:09:21 | D | sum error = [ 0.6174, 0.6971, 0.7923, 0.8714, 0.9903] +24-11-19 19:09:21 | D | best error = [ 0.1458, 0.1458, 0.1458, 0.1458, 0.1458] +24-11-19 19:09:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:09:21 | D | sum error = [ 1.1291, 1.2425, 1.3805, 1.5514, 1.7043] +24-11-19 19:09:21 | D | best error = [ 0.1458, 0.1458, 0.1458, 0.1458, 0.1458] +24-11-19 19:09:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:09:21 | D | sum error = [ 1.9204, 2.1240, 2.3778, 2.6776, 2.9780] +24-11-19 19:09:21 | D | best error = [ 0.1458, 0.1458, 0.1458, 0.1458, 0.1458] +24-11-19 19:09:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:09:21 | D | sum error = [ 3.3203, 3.6921, 4.1180, 4.5550, 5.0757] +24-11-19 19:09:21 | D | best error = [ 0.1458, 0.1458, 0.1458, 0.1458, 0.1458] +24-11-19 19:09:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:09:21 | D | sum error = [ 5.5471, 6.1071, 6.7246, 7.3681, 8.0673] +24-11-19 19:09:21 | D | best error = [ 0.1458, 0.1458, 0.1458, 0.1458, 0.1458] +24-11-19 19:09:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:09:21 | D | sum error = [ 8.8266, 9.5993, 10.5156, 11.4406, 12.4801] +24-11-19 19:09:21 | D | best error = [ 0.1458, 0.1458, 0.1458, 0.1458, 0.1458] +24-11-19 19:09:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:09:21 | D | sum error = [ 13.6210, 14.7660, 16.0293, 17.4026, 18.7951] +24-11-19 19:09:21 | D | best error = [ 0.1458, 0.1458, 0.1458, 0.1458, 0.1458] +24-11-19 19:09:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:09:21 | D | sum error = [ 20.3004, 21.9017, 23.5879, 25.4642, 27.3346] +24-11-19 19:09:21 | D | best error = [ 0.1458, 0.1458, 0.1458, 0.1458, 0.1458] +24-11-19 19:09:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:09:21 | D | sum error = [ 29.3595, 31.4768, 33.7555, 36.1498, 38.6782] +24-11-19 19:09:21 | D | best error = [ 0.1458, 0.1458, 0.1458, 0.1458, 0.1458] +24-11-19 19:09:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:09:21 | D | sum error = [ 41.4086, 44.1675, 47.1734, 50.3294, 53.6068] +24-11-19 19:09:21 | D | best error = [ 0.1458, 0.1458, 0.1458, 0.1458, 0.1458] +24-11-19 19:09:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:09:21 | D | sum error = [ 57.0581, 60.7524, 64.5082, 68.5784, 72.7902] +24-11-19 19:09:21 | D | best error = [ 0.1458, 0.1458, 0.1458, 0.1458, 0.1458] +24-11-19 19:09:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:09:21 | D | sum error = [ 77.2817, 81.9047, 86.8142, 91.9789, 97.3321] +24-11-19 19:09:21 | D | best error = [ 0.1458, 0.1458, 0.1458, 0.1458, 0.1458] +24-11-19 19:09:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:09:21 | D | sum error = [ 103.0246, 108.9470, 115.1289, 121.6703, 128.5530] +24-11-19 19:09:21 | D | best error = [ 0.1458, 0.1458, 0.1458, 0.1458, 0.1458] +24-11-19 19:09:21 | D | + error = [0.1458] +24-11-19 19:09:21 | D | - Calibrating model.layers.0.self_attn.v_proj.weight +24-11-19 19:09:21 | D | + w: sint8 +24-11-19 19:09:21 | D | + x: None +24-11-19 19:09:21 | D | + y: None +24-11-19 19:09:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:09:21 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:09:21 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:09:21 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:09:21 | D | - range ratio = [ 1.0000] +24-11-19 19:09:21 | D | sum error = [ 0.1651] +24-11-19 19:09:21 | D | best error = [ 0.1651] +24-11-19 19:09:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:09:22 | D | sum error = [ 0.1647, 0.1643, 0.1650, 0.1667, 0.1701] +24-11-19 19:09:22 | D | best error = [ 0.1588, 0.1555, 0.1537, 0.1526, 0.1520] +24-11-19 19:09:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:09:22 | D | sum error = [ 0.1745, 0.1805, 0.1884, 0.1978, 0.2083] +24-11-19 19:09:22 | D | best error = [ 0.1518, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 19:09:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:09:22 | D | sum error = [ 0.2216, 0.2363, 0.2523, 0.2711, 0.2914] +24-11-19 19:09:22 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 19:09:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:09:22 | D | sum error = [ 0.3135, 0.3375, 0.3639, 0.3929, 0.4232] +24-11-19 19:09:22 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 19:09:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:09:22 | D | sum error = [ 0.4577, 0.4936, 0.5329, 0.5751, 0.6201] +24-11-19 19:09:22 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 19:09:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:09:22 | D | sum error = [ 0.6685, 0.7205, 0.7772, 0.8383, 0.9034] +24-11-19 19:09:22 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 19:09:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:09:22 | D | sum error = [ 0.9723, 1.0473, 1.1282, 1.2155, 1.3080] +24-11-19 19:09:22 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 19:09:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:09:22 | D | sum error = [ 1.4062, 1.5131, 1.6266, 1.7496, 1.8799] +24-11-19 19:09:22 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 19:09:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:09:22 | D | sum error = [ 2.0190, 2.1704, 2.3298, 2.5019, 2.6858] +24-11-19 19:09:22 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 19:09:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:09:22 | D | sum error = [ 2.8805, 3.0913, 3.3127, 3.5499, 3.8043] +24-11-19 19:09:22 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 19:09:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:09:22 | D | sum error = [ 4.0728, 4.3559, 4.6612, 4.9893, 5.3296] +24-11-19 19:09:22 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 19:09:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:09:22 | D | sum error = [ 5.6925, 6.0727, 6.4826, 6.9085, 7.3523] +24-11-19 19:09:22 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 19:09:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:09:22 | D | sum error = [ 7.8266, 8.3350, 8.8687, 9.4163, 9.9942] +24-11-19 19:09:22 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 19:09:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:09:22 | D | sum error = [ 10.6022, 11.2399, 11.9030, 12.5901, 13.3304] +24-11-19 19:09:22 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 19:09:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:09:22 | D | sum error = [ 14.0796, 14.8659, 15.6744, 16.5281, 17.3983] +24-11-19 19:09:22 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 19:09:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:09:22 | D | sum error = [ 18.3058, 19.2532, 20.2299, 21.2235, 22.2691] +24-11-19 19:09:22 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 19:09:22 | D | + error = [0.1517] +24-11-19 19:09:22 | D | - Calibrating model.layers.0.self_attn.o_proj.weight +24-11-19 19:09:22 | D | + w: sint8 +24-11-19 19:09:22 | D | + x: None +24-11-19 19:09:22 | D | + y: None +24-11-19 19:09:22 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:09:22 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:09:22 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:09:22 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:09:22 | D | - range ratio = [ 1.0000] +24-11-19 19:09:22 | D | sum error = [ 0.1585] +24-11-19 19:09:22 | D | best error = [ 0.1585] +24-11-19 19:09:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:09:22 | D | sum error = [ 0.1591, 0.1617, 0.1624, 0.1693, 0.1741] +24-11-19 19:09:22 | D | best error = [ 0.1245, 0.1112, 0.1047, 0.1010, 0.0989] +24-11-19 19:09:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:09:22 | D | sum error = [ 0.1799, 0.1878, 0.2007, 0.2118, 0.2274] +24-11-19 19:09:22 | D | best error = [ 0.0979, 0.0974, 0.0971, 0.0969, 0.0968] +24-11-19 19:09:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:09:22 | D | sum error = [ 0.2414, 0.2578, 0.2752, 0.2941, 0.3122] +24-11-19 19:09:22 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 19:09:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:09:22 | D | sum error = [ 0.3338, 0.3557, 0.3783, 0.4040, 0.4267] +24-11-19 19:09:22 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 19:09:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:09:22 | D | sum error = [ 0.4520, 0.4809, 0.5094, 0.5403, 0.5700] +24-11-19 19:09:22 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 19:09:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:09:22 | D | sum error = [ 0.6029, 0.6375, 0.6712, 0.7089, 0.7474] +24-11-19 19:09:22 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 19:09:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:09:22 | D | sum error = [ 0.7874, 0.8281, 0.8726, 0.9187, 0.9661] +24-11-19 19:09:22 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 19:09:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:09:22 | D | sum error = [ 1.0138, 1.0659, 1.1194, 1.1759, 1.2330] +24-11-19 19:09:22 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 19:09:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:09:22 | D | sum error = [ 1.2957, 1.3596, 1.4265, 1.4964, 1.5682] +24-11-19 19:09:22 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 19:09:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:09:22 | D | sum error = [ 1.6440, 1.7248, 1.8088, 1.8963, 1.9871] +24-11-19 19:09:22 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 19:09:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:09:22 | D | sum error = [ 2.0834, 2.1848, 2.2892, 2.4001, 2.5167] +24-11-19 19:09:22 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 19:09:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:09:22 | D | sum error = [ 2.6383, 2.7670, 2.9031, 3.0450, 3.1961] +24-11-19 19:09:22 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 19:09:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:09:22 | D | sum error = [ 3.3544, 3.5217, 3.6982, 3.8857, 4.0827] +24-11-19 19:09:22 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 19:09:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:09:22 | D | sum error = [ 4.2919, 4.5125, 4.7458, 4.9922, 5.2527] +24-11-19 19:09:22 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 19:09:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:09:22 | D | sum error = [ 5.5272, 5.8189, 6.1279, 6.4531, 6.7987] +24-11-19 19:09:22 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 19:09:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:09:22 | D | sum error = [ 7.1634, 7.5504, 7.9601, 8.3933, 8.8511] +24-11-19 19:09:22 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 19:09:22 | D | + error = [0.0968] +24-11-19 19:09:22 | D | - Calibrating model.layers.0.mlp.up_proj.weight +24-11-19 19:09:22 | D | + w: sint8 +24-11-19 19:09:22 | D | + x: None +24-11-19 19:09:22 | D | + y: None +24-11-19 19:09:22 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:09:22 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:09:23 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:09:23 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:09:23 | D | - range ratio = [ 1.0000] +24-11-19 19:09:23 | D | sum error = [ 1.1909] +24-11-19 19:09:23 | D | best error = [ 1.1909] +24-11-19 19:09:24 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:09:24 | D | sum error = [ 1.1896, 1.1912, 1.1942, 1.2135, 1.2267] +24-11-19 19:09:24 | D | best error = [ 0.9639, 0.8905, 0.8553, 0.8367, 0.8267] +24-11-19 19:09:24 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:09:24 | D | sum error = [ 1.2651, 1.3033, 1.3596, 1.4170, 1.4855] +24-11-19 19:09:24 | D | best error = [ 0.8211, 0.8183, 0.8168, 0.8162, 0.8160] +24-11-19 19:09:24 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:09:24 | D | sum error = [ 1.5698, 1.6663, 1.7880, 1.9086, 2.0377] +24-11-19 19:09:24 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 19:09:24 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:09:24 | D | sum error = [ 2.1845, 2.3469, 2.5103, 2.6824, 2.8712] +24-11-19 19:09:24 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 19:09:24 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:09:24 | D | sum error = [ 3.0858, 3.2954, 3.5312, 3.7807, 4.0482] +24-11-19 19:09:24 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 19:09:24 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:09:24 | D | sum error = [ 4.3289, 4.6241, 4.9414, 5.2806, 5.6338] +24-11-19 19:09:24 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 19:09:24 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:09:24 | D | sum error = [ 6.0131, 6.4134, 6.8432, 7.2953, 7.7748] +24-11-19 19:09:24 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 19:09:24 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:09:24 | D | sum error = [ 8.2771, 8.8130, 9.3706, 9.9703, 10.5992] +24-11-19 19:09:24 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 19:09:24 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:09:24 | D | sum error = [ 11.2583, 11.9629, 12.6926, 13.4807, 14.3066] +24-11-19 19:09:24 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 19:09:24 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:09:24 | D | sum error = [ 15.1677, 16.0742, 17.0267, 18.0283, 19.0877] +24-11-19 19:09:24 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 19:09:24 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:09:24 | D | sum error = [ 20.2076, 21.3658, 22.5883, 23.8657, 25.2196] +24-11-19 19:09:24 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 19:09:24 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:09:24 | D | sum error = [ 26.6283, 28.1046, 29.6638, 31.2889, 32.9748] +24-11-19 19:09:24 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 19:09:24 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:09:24 | D | sum error = [ 34.7493, 36.6031, 38.5300, 40.5536, 42.6550] +24-11-19 19:09:24 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 19:09:24 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:09:24 | D | sum error = [ 44.8413, 47.1220, 49.4933, 51.9612, 54.5278] +24-11-19 19:09:24 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 19:09:24 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:09:24 | D | sum error = [ 57.1925, 59.9486, 62.8100, 65.7718, 68.8487] +24-11-19 19:09:24 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 19:09:24 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:09:24 | D | sum error = [ 72.0004, 75.2732, 78.6429, 82.1056, 85.6962] +24-11-19 19:09:24 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 19:09:24 | D | + error = [0.8159] +24-11-19 19:09:24 | D | - Calibrating model.layers.0.mlp.gate_proj.weight +24-11-19 19:09:24 | D | + w: sint8 +24-11-19 19:09:24 | D | + x: None +24-11-19 19:09:24 | D | + y: None +24-11-19 19:09:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:09:24 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:09:24 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:09:24 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:09:24 | D | - range ratio = [ 1.0000] +24-11-19 19:09:24 | D | sum error = [ 1.2261] +24-11-19 19:09:24 | D | best error = [ 1.2261] +24-11-19 19:09:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:09:25 | D | sum error = [ 1.2228, 1.2240, 1.2227, 1.2215, 1.2575] +24-11-19 19:09:25 | D | best error = [ 0.9923, 0.9162, 0.8771, 0.8572, 0.8462] +24-11-19 19:09:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:09:25 | D | sum error = [ 1.2904, 1.3260, 1.3903, 1.4514, 1.5391] +24-11-19 19:09:25 | D | best error = [ 0.8404, 0.8374, 0.8360, 0.8356, 0.8354] +24-11-19 19:09:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:09:25 | D | sum error = [ 1.6162, 1.7164, 1.8486, 1.9557, 2.1090] +24-11-19 19:09:25 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 19:09:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:09:25 | D | sum error = [ 2.2725, 2.4345, 2.6098, 2.8141, 3.0235] +24-11-19 19:09:25 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 19:09:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:09:25 | D | sum error = [ 3.2487, 3.4873, 3.7392, 4.0344, 4.3169] +24-11-19 19:09:25 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 19:09:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:09:25 | D | sum error = [ 4.6387, 4.9655, 5.3252, 5.7069, 6.1135] +24-11-19 19:09:25 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 19:09:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:09:25 | D | sum error = [ 6.5312, 6.9945, 7.4755, 7.9901, 8.5411] +24-11-19 19:09:25 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 19:09:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:09:25 | D | sum error = [ 9.1271, 9.7505, 10.3938, 11.0987, 11.8283] +24-11-19 19:09:25 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 19:09:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:09:25 | D | sum error = [ 12.6093, 13.4416, 14.3235, 15.2500, 16.2560] +24-11-19 19:09:25 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 19:09:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:09:25 | D | sum error = [ 17.3044, 18.4119, 19.5856, 20.8203, 22.1306] +24-11-19 19:09:25 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 19:09:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:09:25 | D | sum error = [ 23.5209, 24.9777, 26.5307, 28.1436, 29.8596] +24-11-19 19:09:25 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 19:09:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:09:25 | D | sum error = [ 31.6606, 33.5640, 35.5502, 37.6384, 39.8411] +24-11-19 19:09:25 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 19:09:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:09:25 | D | sum error = [ 42.1556, 44.5896, 47.1313, 49.7897, 52.5754] +24-11-19 19:09:25 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 19:09:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:09:25 | D | sum error = [ 55.4889, 58.5547, 61.7181, 65.0343, 68.5025] +24-11-19 19:09:25 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 19:09:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:09:25 | D | sum error = [ 72.0883, 75.8171, 79.6830, 83.6831, 87.8505] +24-11-19 19:09:25 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 19:09:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:09:25 | D | sum error = [ 92.1099, 96.5682, 101.1458, 105.8582, 110.7472] +24-11-19 19:09:25 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 19:09:25 | D | + error = [0.8353] +24-11-19 19:09:25 | D | - Calibrating model.layers.0.mlp.down_proj.weight +24-11-19 19:09:25 | D | + w: sint8 +24-11-19 19:09:25 | D | + x: None +24-11-19 19:09:25 | D | + y: None +24-11-19 19:09:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:09:25 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:09:25 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:09:25 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:09:25 | D | - range ratio = [ 1.0000] +24-11-19 19:09:25 | D | sum error = [ 0.1969] +24-11-19 19:09:25 | D | best error = [ 0.1969] +24-11-19 19:09:26 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:09:26 | D | sum error = [ 0.1958, 0.1934, 0.1939, 0.1916, 0.1926] +24-11-19 19:09:26 | D | best error = [ 0.1723, 0.1613, 0.1548, 0.1501, 0.1468] +24-11-19 19:09:26 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:09:26 | D | sum error = [ 0.1940, 0.1927, 0.1943, 0.1959, 0.2003] +24-11-19 19:09:26 | D | best error = [ 0.1439, 0.1415, 0.1397, 0.1383, 0.1370] +24-11-19 19:09:26 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:09:26 | D | sum error = [ 0.2050, 0.2100, 0.2159, 0.2226, 0.2311] +24-11-19 19:09:26 | D | best error = [ 0.1359, 0.1350, 0.1343, 0.1336, 0.1331] +24-11-19 19:09:26 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:09:26 | D | sum error = [ 0.2425, 0.2537, 0.2670, 0.2824, 0.2989] +24-11-19 19:09:26 | D | best error = [ 0.1327, 0.1324, 0.1321, 0.1319, 0.1318] +24-11-19 19:09:26 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:09:26 | D | sum error = [ 0.3182, 0.3375, 0.3598, 0.3831, 0.4070] +24-11-19 19:09:26 | D | best error = [ 0.1317, 0.1316, 0.1315, 0.1315, 0.1315] +24-11-19 19:09:26 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:09:26 | D | sum error = [ 0.4339, 0.4634, 0.4938, 0.5284, 0.5646] +24-11-19 19:09:26 | D | best error = [ 0.1315, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 19:09:26 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:09:26 | D | sum error = [ 0.6028, 0.6435, 0.6871, 0.7324, 0.7807] +24-11-19 19:09:26 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 19:09:26 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:09:26 | D | sum error = [ 0.8318, 0.8868, 0.9467, 1.0090, 1.0750] +24-11-19 19:09:26 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 19:09:26 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:09:26 | D | sum error = [ 1.1466, 1.2227, 1.3037, 1.3909, 1.4844] +24-11-19 19:09:26 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 19:09:26 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:09:26 | D | sum error = [ 1.5837, 1.6905, 1.8034, 1.9263, 2.0549] +24-11-19 19:09:26 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 19:09:26 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:09:26 | D | sum error = [ 2.1937, 2.3409, 2.4986, 2.6667, 2.8447] +24-11-19 19:09:26 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 19:09:26 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:09:26 | D | sum error = [ 3.0351, 3.2381, 3.4543, 3.6836, 3.9283] +24-11-19 19:09:26 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 19:09:26 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:09:26 | D | sum error = [ 4.1887, 4.4644, 4.7576, 5.0692, 5.3994] +24-11-19 19:09:26 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 19:09:26 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:09:26 | D | sum error = [ 5.7502, 6.1222, 6.5158, 6.9324, 7.3718] +24-11-19 19:09:26 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 19:09:26 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:09:26 | D | sum error = [ 7.8354, 8.3247, 8.8396, 9.3798, 9.9482] +24-11-19 19:09:26 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 19:09:26 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:09:26 | D | sum error = [ 10.5434, 11.1681, 11.8215, 12.5041, 13.2160] +24-11-19 19:09:26 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 19:09:26 | D | + error = [0.1314] +24-11-19 19:09:26 | D | - Quantizing model.layers.0.self_attn.q_proj.weight +24-11-19 19:09:27 | D | - Quantizing model.layers.0.self_attn.k_proj.weight +24-11-19 19:09:28 | D | - Quantizing model.layers.0.self_attn.v_proj.weight +24-11-19 19:09:29 | D | - Quantizing model.layers.0.self_attn.o_proj.weight +24-11-19 19:09:30 | D | - Quantizing model.layers.0.mlp.up_proj.weight +24-11-19 19:09:31 | D | - Quantizing model.layers.0.mlp.gate_proj.weight +24-11-19 19:09:32 | D | - Quantizing model.layers.0.mlp.down_proj.weight +24-11-19 19:09:41 | D | - Quantizing layer model.layers.1 +24-11-19 19:09:41 | D | - Calibrating model.layers.1.self_attn.q_proj.weight +24-11-19 19:09:41 | D | + w: sint8 +24-11-19 19:09:41 | D | + x: None +24-11-19 19:09:41 | D | + y: None +24-11-19 19:09:41 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:09:41 | D | + finished parsing calibration arguments, ram usage: 12.2 +24-11-19 19:09:41 | D | + finished reseting calibrator, ram usage: 12.2 +24-11-19 19:09:42 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:09:42 | D | - range ratio = [ 1.0000] +24-11-19 19:09:42 | D | sum error = [ 0.4039] +24-11-19 19:09:42 | D | best error = [ 0.4039] +24-11-19 19:09:54 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:09:54 | D | sum error = [ 0.4050, 0.4280, 0.4196, 0.4291, 0.4470] +24-11-19 19:09:54 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 19:09:54 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:09:54 | D | sum error = [ 0.4490, 0.4861, 0.4796, 0.5312, 0.5452] +24-11-19 19:09:54 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 19:09:54 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:09:54 | D | sum error = [ 0.6537, 0.6778, 0.7827, 0.8412, 0.8916] +24-11-19 19:09:54 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 19:09:54 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:09:54 | D | sum error = [ 1.0044, 1.1357, 1.2189, 1.3995, 1.5554] +24-11-19 19:09:54 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 19:09:54 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:09:54 | D | sum error = [ 1.7525, 1.9493, 2.1717, 2.4203, 2.7137] +24-11-19 19:09:54 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 19:09:54 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:09:54 | D | sum error = [ 3.0228, 3.3666, 3.7529, 4.1300, 4.5957] +24-11-19 19:09:54 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 19:09:54 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:09:54 | D | sum error = [ 5.1728, 5.6903, 6.3227, 6.9852, 7.7269] +24-11-19 19:09:54 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 19:09:54 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:09:54 | D | sum error = [ 8.5172, 9.3292, 10.2920, 11.3213, 12.3856] +24-11-19 19:09:54 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 19:09:54 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:09:54 | D | sum error = [ 13.5872, 14.8684, 16.2530, 17.7976, 19.4390] +24-11-19 19:09:54 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 19:09:54 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:09:54 | D | sum error = [ 21.1856, 23.0632, 25.1190, 27.3279, 29.6852] +24-11-19 19:09:54 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 19:09:54 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:09:54 | D | sum error = [ 32.2085, 34.9247, 37.8044, 40.8660, 44.0968] +24-11-19 19:09:54 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 19:09:54 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:09:54 | D | sum error = [ 47.5743, 51.2632, 55.1704, 59.3570, 63.7604] +24-11-19 19:09:54 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 19:09:54 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:09:54 | D | sum error = [ 68.4052, 73.3043, 78.5020, 84.0300, 89.7942] +24-11-19 19:09:54 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 19:09:54 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:09:54 | D | sum error = [ 95.8877, 102.3335, 109.0797, 116.1452, 123.5799] +24-11-19 19:09:54 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 19:09:54 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:09:54 | D | sum error = [ 131.3846, 139.5707, 148.0954, 156.9777, 166.2451] +24-11-19 19:09:54 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 19:09:54 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:09:54 | D | sum error = [ 175.9245, 185.9426, 196.3630, 207.1999, 218.3913] +24-11-19 19:09:54 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 19:09:54 | D | + error = [0.4039] +24-11-19 19:09:55 | D | - Calibrating model.layers.1.self_attn.k_proj.weight +24-11-19 19:09:55 | D | + w: sint8 +24-11-19 19:09:55 | D | + x: None +24-11-19 19:09:55 | D | + y: None +24-11-19 19:09:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:09:55 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:09:55 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:09:55 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:09:55 | D | - range ratio = [ 1.0000] +24-11-19 19:09:55 | D | sum error = [ 0.4855] +24-11-19 19:09:55 | D | best error = [ 0.4855] +24-11-19 19:10:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:10:08 | D | sum error = [ 0.4998, 0.4904, 0.5114, 0.5006, 0.5107] +24-11-19 19:10:08 | D | best error = [ 0.4855, 0.4855, 0.4855, 0.4855, 0.4855] +24-11-19 19:10:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:10:08 | D | sum error = [ 0.5990, 0.5574, 0.6292, 0.6141, 0.6765] +24-11-19 19:10:08 | D | best error = [ 0.4855, 0.4855, 0.4855, 0.4855, 0.4855] +24-11-19 19:10:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:10:08 | D | sum error = [ 0.7238, 0.8061, 0.8506, 0.9710, 1.1198] +24-11-19 19:10:08 | D | best error = [ 0.4855, 0.4855, 0.4855, 0.4855, 0.4855] +24-11-19 19:10:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:10:08 | D | sum error = [ 1.1930, 1.3237, 1.4685, 1.6347, 1.7683] +24-11-19 19:10:08 | D | best error = [ 0.4855, 0.4855, 0.4855, 0.4855, 0.4855] +24-11-19 19:10:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:10:08 | D | sum error = [ 1.9972, 2.2244, 2.4514, 2.7955, 3.0098] +24-11-19 19:10:08 | D | best error = [ 0.4855, 0.4855, 0.4855, 0.4855, 0.4855] +24-11-19 19:10:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:10:08 | D | sum error = [ 3.3705, 3.7311, 4.1439, 4.6552, 5.0608] +24-11-19 19:10:08 | D | best error = [ 0.4855, 0.4855, 0.4855, 0.4855, 0.4855] +24-11-19 19:10:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:10:08 | D | sum error = [ 5.6665, 6.2172, 6.8599, 7.5150, 8.3517] +24-11-19 19:10:08 | D | best error = [ 0.4855, 0.4855, 0.4855, 0.4855, 0.4855] +24-11-19 19:10:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:10:08 | D | sum error = [ 9.1802, 10.0054, 11.0374, 12.0796, 13.1757] +24-11-19 19:10:08 | D | best error = [ 0.4855, 0.4855, 0.4855, 0.4855, 0.4855] +24-11-19 19:10:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:10:08 | D | sum error = [ 14.4771, 15.7940, 17.2133, 18.8118, 20.4486] +24-11-19 19:10:08 | D | best error = [ 0.4855, 0.4855, 0.4855, 0.4855, 0.4855] +24-11-19 19:10:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:10:08 | D | sum error = [ 22.4425, 24.2829, 26.3341, 28.6137, 31.0570] +24-11-19 19:10:08 | D | best error = [ 0.4855, 0.4855, 0.4855, 0.4855, 0.4855] +24-11-19 19:10:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:10:08 | D | sum error = [ 33.4902, 36.3212, 39.2451, 42.3698, 45.6673] +24-11-19 19:10:08 | D | best error = [ 0.4855, 0.4855, 0.4855, 0.4855, 0.4855] +24-11-19 19:10:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:10:08 | D | sum error = [ 49.2942, 53.1633, 56.9443, 61.2041, 65.8527] +24-11-19 19:10:08 | D | best error = [ 0.4855, 0.4855, 0.4855, 0.4855, 0.4855] +24-11-19 19:10:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:10:08 | D | sum error = [ 70.6326, 75.5553, 80.8498, 86.4438, 92.0383] +24-11-19 19:10:08 | D | best error = [ 0.4855, 0.4855, 0.4855, 0.4855, 0.4855] +24-11-19 19:10:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:10:08 | D | sum error = [ 98.2117, 104.8204, 111.4698, 118.7073, 126.1929] +24-11-19 19:10:08 | D | best error = [ 0.4855, 0.4855, 0.4855, 0.4855, 0.4855] +24-11-19 19:10:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:10:08 | D | sum error = [ 133.9233, 142.0305, 150.5723, 159.5762, 168.8800] +24-11-19 19:10:08 | D | best error = [ 0.4855, 0.4855, 0.4855, 0.4855, 0.4855] +24-11-19 19:10:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:10:08 | D | sum error = [ 177.7837, 187.9848, 198.1369, 209.1880, 220.3423] +24-11-19 19:10:08 | D | best error = [ 0.4855, 0.4855, 0.4855, 0.4855, 0.4855] +24-11-19 19:10:08 | D | + error = [0.4855] +24-11-19 19:10:08 | D | - Calibrating model.layers.1.self_attn.v_proj.weight +24-11-19 19:10:08 | D | + w: sint8 +24-11-19 19:10:08 | D | + x: None +24-11-19 19:10:08 | D | + y: None +24-11-19 19:10:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:10:08 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:10:08 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:10:08 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:10:08 | D | - range ratio = [ 1.0000] +24-11-19 19:10:08 | D | sum error = [ 0.5679] +24-11-19 19:10:08 | D | best error = [ 0.5679] +24-11-19 19:10:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:10:08 | D | sum error = [ 0.5627, 0.5603, 0.5617, 0.5667, 0.5797] +24-11-19 19:10:08 | D | best error = [ 0.4618, 0.4273, 0.4105, 0.4014, 0.3963] +24-11-19 19:10:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:10:08 | D | sum error = [ 0.6023, 0.6175, 0.6359, 0.6753, 0.7081] +24-11-19 19:10:08 | D | best error = [ 0.3935, 0.3918, 0.3911, 0.3907, 0.3906] +24-11-19 19:10:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:10:08 | D | sum error = [ 0.7568, 0.7966, 0.8521, 0.9004, 0.9724] +24-11-19 19:10:08 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 19:10:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:10:08 | D | sum error = [ 1.0364, 1.1099, 1.1929, 1.2776, 1.3714] +24-11-19 19:10:08 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 19:10:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:10:08 | D | sum error = [ 1.4677, 1.5680, 1.6871, 1.8023, 1.9202] +24-11-19 19:10:08 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 19:10:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:10:08 | D | sum error = [ 2.0587, 2.1935, 2.3487, 2.5043, 2.6679] +24-11-19 19:10:08 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 19:10:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:10:08 | D | sum error = [ 2.8503, 3.0405, 3.2322, 3.4504, 3.6688] +24-11-19 19:10:08 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 19:10:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:10:08 | D | sum error = [ 3.9028, 4.1470, 4.4098, 4.6826, 4.9729] +24-11-19 19:10:08 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 19:10:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:10:08 | D | sum error = [ 5.2767, 5.6024, 5.9407, 6.2933, 6.6711] +24-11-19 19:10:08 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 19:10:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:10:08 | D | sum error = [ 7.0604, 7.4788, 7.9150, 8.3674, 8.8420] +24-11-19 19:10:08 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 19:10:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:10:08 | D | sum error = [ 9.3425, 9.8636, 10.4107, 10.9835, 11.5830] +24-11-19 19:10:08 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 19:10:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:10:08 | D | sum error = [ 12.2013, 12.8571, 13.5404, 14.2493, 15.0002] +24-11-19 19:10:08 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 19:10:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:10:08 | D | sum error = [ 15.7839, 16.6026, 17.4595, 18.3437, 19.2687] +24-11-19 19:10:08 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 19:10:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:10:08 | D | sum error = [ 20.2355, 21.2376, 22.2767, 23.3614, 24.4906] +24-11-19 19:10:08 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 19:10:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:10:08 | D | sum error = [ 25.6674, 26.8769, 28.1362, 29.4452, 30.8034] +24-11-19 19:10:08 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 19:10:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:10:08 | D | sum error = [ 32.1976, 33.6411, 35.1321, 36.6641, 38.2524] +24-11-19 19:10:08 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 19:10:08 | D | + error = [0.3905] +24-11-19 19:10:09 | D | - Calibrating model.layers.1.self_attn.o_proj.weight +24-11-19 19:10:09 | D | + w: sint8 +24-11-19 19:10:09 | D | + x: None +24-11-19 19:10:09 | D | + y: None +24-11-19 19:10:09 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:10:09 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:10:09 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:10:09 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:10:09 | D | - range ratio = [ 1.0000] +24-11-19 19:10:09 | D | sum error = [ 0.1965] +24-11-19 19:10:09 | D | best error = [ 0.1965] +24-11-19 19:10:09 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:10:09 | D | sum error = [ 0.1936, 0.1951, 0.1969, 0.1994, 0.2043] +24-11-19 19:10:09 | D | best error = [ 0.1709, 0.1608, 0.1561, 0.1534, 0.1524] +24-11-19 19:10:09 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:10:09 | D | sum error = [ 0.2113, 0.2203, 0.2320, 0.2440, 0.2573] +24-11-19 19:10:09 | D | best error = [ 0.1518, 0.1514, 0.1514, 0.1513, 0.1513] +24-11-19 19:10:09 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:10:09 | D | sum error = [ 0.2714, 0.2889, 0.3084, 0.3294, 0.3506] +24-11-19 19:10:09 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 19:10:09 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:10:09 | D | sum error = [ 0.3744, 0.3999, 0.4273, 0.4563, 0.4857] +24-11-19 19:10:09 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 19:10:09 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:10:09 | D | sum error = [ 0.5169, 0.5507, 0.5858, 0.6230, 0.6619] +24-11-19 19:10:09 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 19:10:09 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:10:09 | D | sum error = [ 0.7029, 0.7464, 0.7909, 0.8374, 0.8870] +24-11-19 19:10:09 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 19:10:09 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:10:09 | D | sum error = [ 0.9382, 0.9923, 1.0491, 1.1075, 1.1697] +24-11-19 19:10:09 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 19:10:09 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:10:09 | D | sum error = [ 1.2346, 1.3029, 1.3743, 1.4495, 1.5282] +24-11-19 19:10:09 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 19:10:09 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:10:09 | D | sum error = [ 1.6111, 1.6968, 1.7873, 1.8829, 1.9818] +24-11-19 19:10:09 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 19:10:09 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:10:09 | D | sum error = [ 2.0868, 2.1954, 2.3099, 2.4311, 2.5568] +24-11-19 19:10:09 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 19:10:09 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:10:09 | D | sum error = [ 2.6892, 2.8285, 2.9732, 3.1272, 3.2879] +24-11-19 19:10:09 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 19:10:09 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:10:09 | D | sum error = [ 3.4565, 3.6337, 3.8202, 4.0149, 4.2214] +24-11-19 19:10:09 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 19:10:09 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:10:09 | D | sum error = [ 4.4376, 4.6648, 4.9036, 5.1567, 5.4230] +24-11-19 19:10:09 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 19:10:09 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:10:09 | D | sum error = [ 5.7038, 6.0005, 6.3127, 6.6433, 6.9919] +24-11-19 19:10:09 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 19:10:09 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:10:09 | D | sum error = [ 7.3614, 7.7524, 8.1671, 8.6062, 9.0704] +24-11-19 19:10:09 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 19:10:09 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:10:09 | D | sum error = [ 9.5632, 10.0868, 10.6433, 11.2357, 11.8668] +24-11-19 19:10:09 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 19:10:09 | D | + error = [0.1513] +24-11-19 19:10:09 | D | - Calibrating model.layers.1.mlp.up_proj.weight +24-11-19 19:10:09 | D | + w: sint8 +24-11-19 19:10:09 | D | + x: None +24-11-19 19:10:09 | D | + y: None +24-11-19 19:10:09 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:10:09 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:10:09 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:10:09 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:10:09 | D | - range ratio = [ 1.0000] +24-11-19 19:10:09 | D | sum error = [ 2.3730] +24-11-19 19:10:09 | D | best error = [ 2.3730] +24-11-19 19:10:10 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:10:10 | D | sum error = [ 2.3524, 2.3463, 2.3538, 2.3893, 2.4150] +24-11-19 19:10:10 | D | best error = [ 1.9925, 1.8628, 1.7962, 1.7622, 1.7429] +24-11-19 19:10:10 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:10:10 | D | sum error = [ 2.4722, 2.5622, 2.6751, 2.8130, 2.9392] +24-11-19 19:10:10 | D | best error = [ 1.7316, 1.7263, 1.7238, 1.7226, 1.7221] +24-11-19 19:10:10 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:10:10 | D | sum error = [ 3.1116, 3.3103, 3.5159, 3.7411, 4.0345] +24-11-19 19:10:10 | D | best error = [ 1.7220, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 19:10:10 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:10:10 | D | sum error = [ 4.3123, 4.5982, 4.9315, 5.2790, 5.6708] +24-11-19 19:10:10 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 19:10:10 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:10:10 | D | sum error = [ 6.0540, 6.4773, 6.9410, 7.4385, 7.9501] +24-11-19 19:10:10 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 19:10:10 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:10:10 | D | sum error = [ 8.4716, 9.0513, 9.6646, 10.3111, 10.9734] +24-11-19 19:10:10 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 19:10:10 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:10:10 | D | sum error = [ 11.7016, 12.4488, 13.2451, 14.0826, 14.9797] +24-11-19 19:10:10 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 19:10:10 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:10:10 | D | sum error = [ 15.8858, 16.8646, 17.8843, 18.9890, 20.1107] +24-11-19 19:10:10 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 19:10:10 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:10:10 | D | sum error = [ 21.3112, 22.5706, 23.8762, 25.2662, 26.7092] +24-11-19 19:10:10 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 19:10:10 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:10:10 | D | sum error = [ 28.2216, 29.7950, 31.4456, 33.1857, 34.9997] +24-11-19 19:10:10 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 19:10:10 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:10:10 | D | sum error = [ 36.8938, 38.8597, 40.9382, 43.0930, 45.3355] +24-11-19 19:10:10 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 19:10:10 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:10:10 | D | sum error = [ 47.6846, 50.1142, 52.6510, 55.2993, 58.0427] +24-11-19 19:10:10 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 19:10:10 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:10:10 | D | sum error = [ 60.8767, 63.8604, 66.9521, 70.1733, 73.5008] +24-11-19 19:10:10 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 19:10:10 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:10:10 | D | sum error = [ 76.9799, 80.5566, 84.2876, 88.1192, 92.1060] +24-11-19 19:10:10 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 19:10:10 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:10:10 | D | sum error = [ 96.2272, 100.4889, 104.8844, 109.4229, 114.0851] +24-11-19 19:10:10 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 19:10:10 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:10:10 | D | sum error = [ 118.9130, 123.8612, 129.0039, 134.2502, 139.6823] +24-11-19 19:10:10 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 19:10:10 | D | + error = [1.7219] +24-11-19 19:10:10 | D | - Calibrating model.layers.1.mlp.gate_proj.weight +24-11-19 19:10:10 | D | + w: sint8 +24-11-19 19:10:10 | D | + x: None +24-11-19 19:10:10 | D | + y: None +24-11-19 19:10:10 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:10:10 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:10:11 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:10:11 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:10:11 | D | - range ratio = [ 1.0000] +24-11-19 19:10:11 | D | sum error = [ 2.5173] +24-11-19 19:10:11 | D | best error = [ 2.5173] +24-11-19 19:10:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:10:12 | D | sum error = [ 2.5051, 2.4915, 2.5118, 2.5234, 2.5656] +24-11-19 19:10:12 | D | best error = [ 2.1197, 1.9763, 1.9103, 1.8737, 1.8523] +24-11-19 19:10:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:10:12 | D | sum error = [ 2.6445, 2.7302, 2.8286, 2.9743, 3.1267] +24-11-19 19:10:12 | D | best error = [ 1.8399, 1.8348, 1.8318, 1.8307, 1.8303] +24-11-19 19:10:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:10:12 | D | sum error = [ 3.3029, 3.5057, 3.7394, 3.9769, 4.2588] +24-11-19 19:10:12 | D | best error = [ 1.8302, 1.8302, 1.8302, 1.8302, 1.8302] +24-11-19 19:10:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:10:12 | D | sum error = [ 4.5576, 4.8873, 5.2473, 5.6112, 6.0030] +24-11-19 19:10:12 | D | best error = [ 1.8302, 1.8302, 1.8302, 1.8302, 1.8302] +24-11-19 19:10:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:10:12 | D | sum error = [ 6.4587, 6.9178, 7.3977, 7.9281, 8.4849] +24-11-19 19:10:12 | D | best error = [ 1.8302, 1.8302, 1.8302, 1.8302, 1.8302] +24-11-19 19:10:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:10:12 | D | sum error = [ 9.0752, 9.7178, 10.3636, 11.0841, 11.8096] +24-11-19 19:10:12 | D | best error = [ 1.8302, 1.8302, 1.8302, 1.8302, 1.8302] +24-11-19 19:10:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:10:12 | D | sum error = [ 12.6128, 13.4368, 14.3187, 15.2548, 16.2461] +24-11-19 19:10:12 | D | best error = [ 1.8302, 1.8302, 1.8302, 1.8302, 1.8302] +24-11-19 19:10:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:10:12 | D | sum error = [ 17.2979, 18.4065, 19.5816, 20.8366, 22.1463] +24-11-19 19:10:12 | D | best error = [ 1.8302, 1.8302, 1.8302, 1.8302, 1.8302] +24-11-19 19:10:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:10:12 | D | sum error = [ 23.5438, 25.0079, 26.5532, 28.2098, 29.9575] +24-11-19 19:10:12 | D | best error = [ 1.8302, 1.8302, 1.8302, 1.8302, 1.8302] +24-11-19 19:10:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:10:12 | D | sum error = [ 31.7862, 33.7527, 35.8237, 37.9799, 40.2585] +24-11-19 19:10:12 | D | best error = [ 1.8302, 1.8302, 1.8302, 1.8302, 1.8302] +24-11-19 19:10:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:10:12 | D | sum error = [ 42.6681, 45.1922, 47.8709, 50.7206, 53.6643] +24-11-19 19:10:12 | D | best error = [ 1.8302, 1.8302, 1.8302, 1.8302, 1.8302] +24-11-19 19:10:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:10:12 | D | sum error = [ 56.8384, 60.1512, 63.6208, 67.2630, 71.1783] +24-11-19 19:10:12 | D | best error = [ 1.8302, 1.8302, 1.8302, 1.8302, 1.8302] +24-11-19 19:10:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:10:12 | D | sum error = [ 75.2360, 79.4769, 83.9565, 88.6282, 93.5334] +24-11-19 19:10:12 | D | best error = [ 1.8302, 1.8302, 1.8302, 1.8302, 1.8302] +24-11-19 19:10:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:10:12 | D | sum error = [ 98.6198, 103.9959, 109.5514, 115.3614, 121.4233] +24-11-19 19:10:12 | D | best error = [ 1.8302, 1.8302, 1.8302, 1.8302, 1.8302] +24-11-19 19:10:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:10:12 | D | sum error = [ 127.7355, 134.2992, 141.0499, 148.0399, 155.2970] +24-11-19 19:10:12 | D | best error = [ 1.8302, 1.8302, 1.8302, 1.8302, 1.8302] +24-11-19 19:10:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:10:12 | D | sum error = [ 162.7708, 170.4917, 178.4467, 186.6689, 195.1853] +24-11-19 19:10:12 | D | best error = [ 1.8302, 1.8302, 1.8302, 1.8302, 1.8302] +24-11-19 19:10:12 | D | + error = [1.8302] +24-11-19 19:10:12 | D | - Calibrating model.layers.1.mlp.down_proj.weight +24-11-19 19:10:12 | D | + w: sint8 +24-11-19 19:10:12 | D | + x: None +24-11-19 19:10:12 | D | + y: None +24-11-19 19:10:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:10:12 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:10:12 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:10:12 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:10:12 | D | - range ratio = [ 1.0000] +24-11-19 19:10:12 | D | sum error = [ 35.6272] +24-11-19 19:10:12 | D | best error = [ 35.6272] +24-11-19 19:10:13 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:10:13 | D | sum error = [ 35.3511, 34.8778, 34.4003, 33.9123, 33.7587] +24-11-19 19:10:13 | D | best error = [ 24.5900, 16.9671, 12.2808, 9.6114, 8.2018] +24-11-19 19:10:13 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:10:13 | D | sum error = [ 33.7387, 32.7809, 32.4198, 32.3384, 32.1480] +24-11-19 19:10:13 | D | best error = [ 7.2416, 6.5723, 6.0817, 5.7002, 5.3976] +24-11-19 19:10:13 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:10:13 | D | sum error = [ 31.5263, 31.0902, 30.7054, 30.5513, 30.1341] +24-11-19 19:10:13 | D | best error = [ 5.1238, 4.8816, 4.6627, 4.4783, 4.3329] +24-11-19 19:10:13 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:10:13 | D | sum error = [ 29.6254, 29.4070, 29.1674, 28.7128, 28.5493] +24-11-19 19:10:13 | D | best error = [ 4.2109, 4.0856, 3.9673, 3.8793, 3.8201] +24-11-19 19:10:13 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:10:13 | D | sum error = [ 28.1544, 27.5836, 27.3711, 27.5750, 26.6946] +24-11-19 19:10:13 | D | best error = [ 3.7374, 3.6173, 3.5231, 3.4417, 3.3676] +24-11-19 19:10:13 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:10:13 | D | sum error = [ 26.3869, 26.1256, 25.5815, 25.3842, 25.8750] +24-11-19 19:10:13 | D | best error = [ 3.2757, 3.1956, 3.1273, 3.0639, 2.9985] +24-11-19 19:10:13 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:10:13 | D | sum error = [ 26.4870, 29.6355, 35.1209, 42.8619, 53.5281] +24-11-19 19:10:13 | D | best error = [ 2.9357, 2.8690, 2.7895, 2.7473, 2.7004] +24-11-19 19:10:13 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:10:13 | D | sum error = [ 67.2994, 85.3638, 107.8677, 135.9069, 169.3931] +24-11-19 19:10:13 | D | best error = [ 2.6636, 2.6156, 2.5760, 2.5329, 2.5117] +24-11-19 19:10:13 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:10:13 | D | sum error = [ 208.1805, 252.5022, 302.6287, 358.4828, 420.0673] +24-11-19 19:10:13 | D | best error = [ 2.4815, 2.4663, 2.4451, 2.4353, 2.4248] +24-11-19 19:10:13 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:10:13 | D | sum error = [ 487.0281, 559.1489, 635.7403, 716.9677, 802.3596] +24-11-19 19:10:13 | D | best error = [ 2.4201, 2.4056, 2.4000, 2.3945, 2.3914] +24-11-19 19:10:13 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:10:13 | D | sum error = [ 891.1713, 983.4263, 1078.5267, 1176.1946, 1276.0319] +24-11-19 19:10:13 | D | best error = [ 2.3880, 2.3864, 2.3834, 2.3826, 2.3823] +24-11-19 19:10:13 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:10:13 | D | sum error = [ 1377.9215, 1481.3574, 1586.1902, 1692.2789, 1799.3465] +24-11-19 19:10:13 | D | best error = [ 2.3823, 2.3818, 2.3818, 2.3814, 2.3814] +24-11-19 19:10:13 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:10:13 | D | sum error = [ 1907.1543, 2015.7445, 2124.8930, 2234.5359, 2344.6598] +24-11-19 19:10:13 | D | best error = [ 2.3814, 2.3814, 2.3814, 2.3814, 2.3814] +24-11-19 19:10:13 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:10:13 | D | sum error = [ 2455.0720, 2565.8203, 2676.9417, 2788.2949, 2899.6342] +24-11-19 19:10:13 | D | best error = [ 2.3814, 2.3814, 2.3814, 2.3814, 2.3814] +24-11-19 19:10:13 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:10:13 | D | sum error = [ 3011.2252, 3122.9826, 3234.8981, 3346.8872, 3459.0072] +24-11-19 19:10:13 | D | best error = [ 2.3814, 2.3814, 2.3814, 2.3814, 2.3814] +24-11-19 19:10:13 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:10:13 | D | sum error = [ 3571.1423, 3683.3959, 3795.7484, 3908.1891, 4020.7898] +24-11-19 19:10:13 | D | best error = [ 2.3814, 2.3814, 2.3814, 2.3814, 2.3814] +24-11-19 19:10:13 | D | + error = [2.3814] +24-11-19 19:10:13 | D | - Quantizing model.layers.1.self_attn.q_proj.weight +24-11-19 19:10:14 | D | - Quantizing model.layers.1.self_attn.k_proj.weight +24-11-19 19:10:15 | D | - Quantizing model.layers.1.self_attn.v_proj.weight +24-11-19 19:10:16 | D | - Quantizing model.layers.1.self_attn.o_proj.weight +24-11-19 19:10:17 | D | - Quantizing model.layers.1.mlp.up_proj.weight +24-11-19 19:10:18 | D | - Quantizing model.layers.1.mlp.gate_proj.weight +24-11-19 19:10:19 | D | - Quantizing model.layers.1.mlp.down_proj.weight +24-11-19 19:10:27 | D | - Quantizing layer model.layers.2 +24-11-19 19:10:27 | D | - Calibrating model.layers.2.self_attn.q_proj.weight +24-11-19 19:10:27 | D | + w: sint8 +24-11-19 19:10:27 | D | + x: None +24-11-19 19:10:27 | D | + y: None +24-11-19 19:10:27 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:10:27 | D | + finished parsing calibration arguments, ram usage: 11.9 +24-11-19 19:10:27 | D | + finished reseting calibrator, ram usage: 11.9 +24-11-19 19:10:28 | D | + finished calculating the original outputs, ram usage: 11.9 +24-11-19 19:10:28 | D | - range ratio = [ 1.0000] +24-11-19 19:10:28 | D | sum error = [ 1.0905] +24-11-19 19:10:28 | D | best error = [ 1.0905] +24-11-19 19:10:40 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:10:40 | D | sum error = [ 1.1224, 1.1057, 1.1102, 1.1332, 1.1802] +24-11-19 19:10:40 | D | best error = [ 1.0905, 1.0905, 1.0905, 1.0905, 1.0905] +24-11-19 19:10:40 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:10:40 | D | sum error = [ 1.2294, 1.2512, 1.3019, 1.4474, 1.5367] +24-11-19 19:10:40 | D | best error = [ 1.0905, 1.0905, 1.0905, 1.0905, 1.0905] +24-11-19 19:10:40 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:10:40 | D | sum error = [ 1.7097, 1.7772, 2.0516, 2.2537, 2.5152] +24-11-19 19:10:40 | D | best error = [ 1.0905, 1.0905, 1.0905, 1.0905, 1.0905] +24-11-19 19:10:40 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:10:40 | D | sum error = [ 2.8381, 3.1305, 3.5286, 3.9846, 4.3311] +24-11-19 19:10:40 | D | best error = [ 1.0905, 1.0905, 1.0905, 1.0905, 1.0905] +24-11-19 19:10:40 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:10:40 | D | sum error = [ 4.8691, 5.4463, 6.0151, 6.6790, 7.5096] +24-11-19 19:10:40 | D | best error = [ 1.0905, 1.0905, 1.0905, 1.0905, 1.0905] +24-11-19 19:10:40 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:10:40 | D | sum error = [ 8.4751, 9.4963, 10.5642, 11.7651, 13.1774] +24-11-19 19:10:40 | D | best error = [ 1.0905, 1.0905, 1.0905, 1.0905, 1.0905] +24-11-19 19:10:40 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:10:40 | D | sum error = [ 14.5132, 16.2137, 18.0924, 20.1199, 22.1687] +24-11-19 19:10:40 | D | best error = [ 1.0905, 1.0905, 1.0905, 1.0905, 1.0905] +24-11-19 19:10:40 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:10:40 | D | sum error = [ 24.5018, 27.0648, 29.9388, 32.9037, 36.1226] +24-11-19 19:10:40 | D | best error = [ 1.0905, 1.0905, 1.0905, 1.0905, 1.0905] +24-11-19 19:10:40 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:10:40 | D | sum error = [ 39.7946, 43.6480, 47.9340, 52.6891, 57.6673] +24-11-19 19:10:40 | D | best error = [ 1.0905, 1.0905, 1.0905, 1.0905, 1.0905] +24-11-19 19:10:40 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:10:40 | D | sum error = [ 63.1323, 69.1868, 75.6623, 82.8375, 90.3495] +24-11-19 19:10:40 | D | best error = [ 1.0905, 1.0905, 1.0905, 1.0905, 1.0905] +24-11-19 19:10:40 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:10:40 | D | sum error = [ 98.7539, 107.7886, 117.5127, 128.2206, 139.8419] +24-11-19 19:10:40 | D | best error = [ 1.0905, 1.0905, 1.0905, 1.0905, 1.0905] +24-11-19 19:10:40 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:10:40 | D | sum error = [ 152.2279, 165.5719, 180.0737, 195.7865, 212.6005] +24-11-19 19:10:40 | D | best error = [ 1.0905, 1.0905, 1.0905, 1.0905, 1.0905] +24-11-19 19:10:40 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:10:40 | D | sum error = [ 231.1787, 251.3377, 273.1103, 296.9763, 322.6583] +24-11-19 19:10:40 | D | best error = [ 1.0905, 1.0905, 1.0905, 1.0905, 1.0905] +24-11-19 19:10:40 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:10:40 | D | sum error = [ 350.6681, 381.1140, 413.7090, 449.2726, 487.3271] +24-11-19 19:10:40 | D | best error = [ 1.0905, 1.0905, 1.0905, 1.0905, 1.0905] +24-11-19 19:10:40 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:10:40 | D | sum error = [ 528.4619, 572.2434, 619.0108, 668.4398, 720.8225] +24-11-19 19:10:40 | D | best error = [ 1.0905, 1.0905, 1.0905, 1.0905, 1.0905] +24-11-19 19:10:40 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:10:40 | D | sum error = [ 775.5709, 832.7285, 891.3432, 951.0228, 1011.2417] +24-11-19 19:10:40 | D | best error = [ 1.0905, 1.0905, 1.0905, 1.0905, 1.0905] +24-11-19 19:10:40 | D | + error = [1.0905] +24-11-19 19:10:40 | D | - Calibrating model.layers.2.self_attn.k_proj.weight +24-11-19 19:10:40 | D | + w: sint8 +24-11-19 19:10:40 | D | + x: None +24-11-19 19:10:40 | D | + y: None +24-11-19 19:10:40 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:10:40 | D | + finished parsing calibration arguments, ram usage: 11.9 +24-11-19 19:10:41 | D | + finished reseting calibrator, ram usage: 11.9 +24-11-19 19:10:41 | D | + finished calculating the original outputs, ram usage: 11.9 +24-11-19 19:10:41 | D | - range ratio = [ 1.0000] +24-11-19 19:10:41 | D | sum error = [ 1.1917] +24-11-19 19:10:41 | D | best error = [ 1.1917] +24-11-19 19:10:53 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:10:53 | D | sum error = [ 1.1836, 1.1501, 1.1897, 1.2513, 1.3436] +24-11-19 19:10:53 | D | best error = [ 1.1836, 1.1501, 1.1501, 1.1501, 1.1501] +24-11-19 19:10:53 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:10:53 | D | sum error = [ 1.3521, 1.4515, 1.4431, 1.7343, 1.9569] +24-11-19 19:10:53 | D | best error = [ 1.1501, 1.1501, 1.1501, 1.1501, 1.1501] +24-11-19 19:10:53 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:10:53 | D | sum error = [ 2.2314, 2.1900, 2.4968, 2.8445, 3.2085] +24-11-19 19:10:53 | D | best error = [ 1.1501, 1.1501, 1.1501, 1.1501, 1.1501] +24-11-19 19:10:53 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:10:53 | D | sum error = [ 3.3898, 3.8490, 4.3178, 4.8010, 5.2553] +24-11-19 19:10:53 | D | best error = [ 1.1501, 1.1501, 1.1501, 1.1501, 1.1501] +24-11-19 19:10:53 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:10:53 | D | sum error = [ 6.1321, 6.6891, 7.7390, 8.3846, 9.1546] +24-11-19 19:10:53 | D | best error = [ 1.1501, 1.1501, 1.1501, 1.1501, 1.1501] +24-11-19 19:10:53 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:10:53 | D | sum error = [ 10.1265, 11.4324, 12.6195, 13.9524, 15.0151] +24-11-19 19:10:53 | D | best error = [ 1.1501, 1.1501, 1.1501, 1.1501, 1.1501] +24-11-19 19:10:53 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:10:53 | D | sum error = [ 16.4223, 18.3109, 20.2404, 22.2793, 24.5979] +24-11-19 19:10:53 | D | best error = [ 1.1501, 1.1501, 1.1501, 1.1501, 1.1501] +24-11-19 19:10:53 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:10:53 | D | sum error = [ 26.6156, 28.9177, 32.1192, 34.6157, 38.1338] +24-11-19 19:10:53 | D | best error = [ 1.1501, 1.1501, 1.1501, 1.1501, 1.1501] +24-11-19 19:10:53 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:10:53 | D | sum error = [ 41.9411, 45.8878, 49.5028, 55.3206, 59.0122] +24-11-19 19:10:53 | D | best error = [ 1.1501, 1.1501, 1.1501, 1.1501, 1.1501] +24-11-19 19:10:53 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:10:53 | D | sum error = [ 66.1491, 70.9186, 76.7410, 84.9807, 91.7586] +24-11-19 19:10:53 | D | best error = [ 1.1501, 1.1501, 1.1501, 1.1501, 1.1501] +24-11-19 19:10:53 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:10:53 | D | sum error = [ 100.0739, 108.2526, 118.8324, 127.2894, 140.6651] +24-11-19 19:10:53 | D | best error = [ 1.1501, 1.1501, 1.1501, 1.1501, 1.1501] +24-11-19 19:10:53 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:10:53 | D | sum error = [ 151.5374, 165.5799, 181.0462, 197.3772, 212.0723] +24-11-19 19:10:53 | D | best error = [ 1.1501, 1.1501, 1.1501, 1.1501, 1.1501] +24-11-19 19:10:53 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:10:53 | D | sum error = [ 234.5520, 252.7123, 278.0785, 302.2785, 331.0868] +24-11-19 19:10:53 | D | best error = [ 1.1501, 1.1501, 1.1501, 1.1501, 1.1501] +24-11-19 19:10:53 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:10:53 | D | sum error = [ 358.8891, 391.6884, 425.9108, 460.8178, 502.3107] +24-11-19 19:10:53 | D | best error = [ 1.1501, 1.1501, 1.1501, 1.1501, 1.1501] +24-11-19 19:10:53 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:10:53 | D | sum error = [ 541.8388, 587.2856, 639.0105, 686.3470, 742.5918] +24-11-19 19:10:53 | D | best error = [ 1.1501, 1.1501, 1.1501, 1.1501, 1.1501] +24-11-19 19:10:53 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:10:53 | D | sum error = [ 794.0008, 855.0102, 912.0720, 976.1534, 1034.3504] +24-11-19 19:10:53 | D | best error = [ 1.1501, 1.1501, 1.1501, 1.1501, 1.1501] +24-11-19 19:10:53 | D | + error = [1.1501] +24-11-19 19:10:54 | D | - Calibrating model.layers.2.self_attn.v_proj.weight +24-11-19 19:10:54 | D | + w: sint8 +24-11-19 19:10:54 | D | + x: None +24-11-19 19:10:54 | D | + y: None +24-11-19 19:10:54 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:10:54 | D | + finished parsing calibration arguments, ram usage: 11.9 +24-11-19 19:10:54 | D | + finished reseting calibrator, ram usage: 11.9 +24-11-19 19:10:54 | D | + finished calculating the original outputs, ram usage: 11.9 +24-11-19 19:10:54 | D | - range ratio = [ 1.0000] +24-11-19 19:10:54 | D | sum error = [ 2.0518] +24-11-19 19:10:54 | D | best error = [ 2.0518] +24-11-19 19:10:54 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:10:54 | D | sum error = [ 2.0427, 2.0470, 2.0602, 2.0769, 2.0981] +24-11-19 19:10:54 | D | best error = [ 1.7777, 1.6932, 1.6466, 1.6217, 1.6046] +24-11-19 19:10:54 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:10:54 | D | sum error = [ 2.1664, 2.2377, 2.3240, 2.4422, 2.5627] +24-11-19 19:10:54 | D | best error = [ 1.5972, 1.5937, 1.5923, 1.5918, 1.5917] +24-11-19 19:10:54 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:10:54 | D | sum error = [ 2.7115, 2.8706, 3.0461, 3.2625, 3.4878] +24-11-19 19:10:54 | D | best error = [ 1.5916, 1.5915, 1.5915, 1.5915, 1.5915] +24-11-19 19:10:54 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:10:54 | D | sum error = [ 3.7456, 3.9865, 4.2995, 4.6108, 4.9222] +24-11-19 19:10:54 | D | best error = [ 1.5915, 1.5915, 1.5915, 1.5915, 1.5915] +24-11-19 19:10:54 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:10:54 | D | sum error = [ 5.2913, 5.6456, 6.0480, 6.4652, 6.9387] +24-11-19 19:10:54 | D | best error = [ 1.5915, 1.5915, 1.5915, 1.5915, 1.5915] +24-11-19 19:10:54 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:10:54 | D | sum error = [ 7.3982, 7.9157, 8.4589, 9.0373, 9.6408] +24-11-19 19:10:54 | D | best error = [ 1.5915, 1.5915, 1.5915, 1.5915, 1.5915] +24-11-19 19:10:54 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:10:54 | D | sum error = [ 10.2680, 10.9363, 11.6455, 12.4070, 13.1854] +24-11-19 19:10:54 | D | best error = [ 1.5915, 1.5915, 1.5915, 1.5915, 1.5915] +24-11-19 19:10:54 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:10:54 | D | sum error = [ 14.0040, 14.8780, 15.7847, 16.7573, 17.7785] +24-11-19 19:10:54 | D | best error = [ 1.5915, 1.5915, 1.5915, 1.5915, 1.5915] +24-11-19 19:10:54 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:10:54 | D | sum error = [ 18.8373, 19.9708, 21.1397, 22.3712, 23.6712] +24-11-19 19:10:54 | D | best error = [ 1.5915, 1.5915, 1.5915, 1.5915, 1.5915] +24-11-19 19:10:54 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:10:54 | D | sum error = [ 25.0137, 26.4374, 27.9179, 29.4697, 31.0836] +24-11-19 19:10:54 | D | best error = [ 1.5915, 1.5915, 1.5915, 1.5915, 1.5915] +24-11-19 19:10:54 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:10:54 | D | sum error = [ 32.8062, 34.5867, 36.4447, 38.4117, 40.4423] +24-11-19 19:10:54 | D | best error = [ 1.5915, 1.5915, 1.5915, 1.5915, 1.5915] +24-11-19 19:10:54 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:10:54 | D | sum error = [ 42.5645, 44.8027, 47.1062, 49.5257, 52.0409] +24-11-19 19:10:54 | D | best error = [ 1.5915, 1.5915, 1.5915, 1.5915, 1.5915] +24-11-19 19:10:54 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:10:54 | D | sum error = [ 54.6609, 57.3861, 60.2238, 63.1844, 66.2500] +24-11-19 19:10:54 | D | best error = [ 1.5915, 1.5915, 1.5915, 1.5915, 1.5915] +24-11-19 19:10:54 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:10:54 | D | sum error = [ 69.4446, 72.7740, 76.2057, 79.7876, 83.4851] +24-11-19 19:10:54 | D | best error = [ 1.5915, 1.5915, 1.5915, 1.5915, 1.5915] +24-11-19 19:10:54 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:10:54 | D | sum error = [ 87.3097, 91.2702, 95.3587, 99.5908, 103.9499] +24-11-19 19:10:54 | D | best error = [ 1.5915, 1.5915, 1.5915, 1.5915, 1.5915] +24-11-19 19:10:54 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:10:54 | D | sum error = [ 108.4411, 113.0830, 117.8523, 122.7664, 127.8251] +24-11-19 19:10:54 | D | best error = [ 1.5915, 1.5915, 1.5915, 1.5915, 1.5915] +24-11-19 19:10:54 | D | + error = [1.5915] +24-11-19 19:10:54 | D | - Calibrating model.layers.2.self_attn.o_proj.weight +24-11-19 19:10:54 | D | + w: sint8 +24-11-19 19:10:54 | D | + x: None +24-11-19 19:10:54 | D | + y: None +24-11-19 19:10:54 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:10:54 | D | + finished parsing calibration arguments, ram usage: 11.9 +24-11-19 19:10:54 | D | + finished reseting calibrator, ram usage: 11.9 +24-11-19 19:10:55 | D | + finished calculating the original outputs, ram usage: 11.9 +24-11-19 19:10:55 | D | - range ratio = [ 1.0000] +24-11-19 19:10:55 | D | sum error = [ 0.2227] +24-11-19 19:10:55 | D | best error = [ 0.2227] +24-11-19 19:10:55 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:10:55 | D | sum error = [ 0.2207, 0.2207, 0.2203, 0.2222, 0.2259] +24-11-19 19:10:55 | D | best error = [ 0.2102, 0.2049, 0.2017, 0.1998, 0.1986] +24-11-19 19:10:55 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:10:55 | D | sum error = [ 0.2312, 0.2389, 0.2467, 0.2577, 0.2701] +24-11-19 19:10:55 | D | best error = [ 0.1979, 0.1976, 0.1973, 0.1972, 0.1971] +24-11-19 19:10:55 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:10:55 | D | sum error = [ 0.2839, 0.3013, 0.3196, 0.3396, 0.3621] +24-11-19 19:10:55 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 19:10:55 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:10:55 | D | sum error = [ 0.3866, 0.4135, 0.4423, 0.4729, 0.5061] +24-11-19 19:10:55 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 19:10:55 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:10:55 | D | sum error = [ 0.5425, 0.5791, 0.6202, 0.6632, 0.7087] +24-11-19 19:10:55 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 19:10:55 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:10:55 | D | sum error = [ 0.7567, 0.8087, 0.8633, 0.9206, 0.9824] +24-11-19 19:10:55 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 19:10:55 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:10:55 | D | sum error = [ 1.0466, 1.1149, 1.1868, 1.2626, 1.3432] +24-11-19 19:10:55 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 19:10:55 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:10:55 | D | sum error = [ 1.4282, 1.5176, 1.6116, 1.7113, 1.8166] +24-11-19 19:10:55 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 19:10:55 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:10:55 | D | sum error = [ 1.9275, 2.0449, 2.1674, 2.2973, 2.4334] +24-11-19 19:10:55 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 19:10:55 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:10:55 | D | sum error = [ 2.5771, 2.7280, 2.8876, 3.0550, 3.2309] +24-11-19 19:10:55 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 19:10:55 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:10:55 | D | sum error = [ 3.4161, 3.6105, 3.8152, 4.0300, 4.2553] +24-11-19 19:10:55 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 19:10:55 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:10:55 | D | sum error = [ 4.4921, 4.7402, 5.0002, 5.2727, 5.5581] +24-11-19 19:10:55 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 19:10:55 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:10:55 | D | sum error = [ 5.8573, 6.1693, 6.4964, 6.8387, 7.1956] +24-11-19 19:10:55 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 19:10:55 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:10:55 | D | sum error = [ 7.5687, 7.9573, 8.3628, 8.7847, 9.2239] +24-11-19 19:10:55 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 19:10:55 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:10:55 | D | sum error = [ 9.6807, 10.1561, 10.6494, 11.1611, 11.6920] +24-11-19 19:10:55 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 19:10:55 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:10:55 | D | sum error = [ 12.2417, 12.8108, 13.3988, 14.0069, 14.6341] +24-11-19 19:10:55 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 19:10:55 | D | + error = [0.1970] +24-11-19 19:10:55 | D | - Calibrating model.layers.2.mlp.up_proj.weight +24-11-19 19:10:55 | D | + w: sint8 +24-11-19 19:10:55 | D | + x: None +24-11-19 19:10:55 | D | + y: None +24-11-19 19:10:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:10:55 | D | + finished parsing calibration arguments, ram usage: 11.9 +24-11-19 19:10:55 | D | + finished reseting calibrator, ram usage: 11.9 +24-11-19 19:10:55 | D | + finished calculating the original outputs, ram usage: 11.9 +24-11-19 19:10:55 | D | - range ratio = [ 1.0000] +24-11-19 19:10:55 | D | sum error = [ 3.1968] +24-11-19 19:10:55 | D | best error = [ 3.1968] +24-11-19 19:10:56 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:10:56 | D | sum error = [ 3.1533, 3.1477, 3.1665, 3.2118, 3.2477] +24-11-19 19:10:56 | D | best error = [ 2.7835, 2.6499, 2.5824, 2.5458, 2.5265] +24-11-19 19:10:56 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:10:56 | D | sum error = [ 3.3500, 3.4577, 3.5933, 3.7505, 3.9512] +24-11-19 19:10:56 | D | best error = [ 2.5164, 2.5115, 2.5095, 2.5086, 2.5082] +24-11-19 19:10:56 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:10:56 | D | sum error = [ 4.1672, 4.4456, 4.7134, 5.0279, 5.3794] +24-11-19 19:10:56 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 19:10:56 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:10:56 | D | sum error = [ 5.7417, 6.1622, 6.5841, 7.0704, 7.5751] +24-11-19 19:10:56 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 19:10:56 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:10:56 | D | sum error = [ 8.1090, 8.7000, 9.3044, 9.9432, 10.6337] +24-11-19 19:10:56 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 19:10:56 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:10:56 | D | sum error = [ 11.3738, 12.1381, 12.9409, 13.7995, 14.6898] +24-11-19 19:10:56 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 19:10:56 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:10:56 | D | sum error = [ 15.6536, 16.6403, 17.6946, 18.8006, 19.9683] +24-11-19 19:10:56 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 19:10:56 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:10:56 | D | sum error = [ 21.1921, 22.4580, 23.8179, 25.2213, 26.7064] +24-11-19 19:10:56 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 19:10:56 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:10:56 | D | sum error = [ 28.2312, 29.8539, 31.5542, 33.3140, 35.1813] +24-11-19 19:10:56 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 19:10:56 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:10:56 | D | sum error = [ 37.1130, 39.1327, 41.2539, 43.4533, 45.7435] +24-11-19 19:10:56 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 19:10:56 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:10:56 | D | sum error = [ 48.1405, 50.6154, 53.1981, 55.8863, 58.6694] +24-11-19 19:10:56 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 19:10:56 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:10:56 | D | sum error = [ 61.5598, 64.5519, 67.6628, 70.8796, 74.2018] +24-11-19 19:10:56 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 19:10:56 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:10:56 | D | sum error = [ 77.6482, 81.1933, 84.8696, 88.6608, 92.5809] +24-11-19 19:10:56 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 19:10:56 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:10:56 | D | sum error = [ 96.6197, 100.7907, 105.0724, 109.5042, 114.0421] +24-11-19 19:10:56 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 19:10:56 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:10:56 | D | sum error = [ 118.7233, 123.5457, 128.4915, 133.5869, 138.8218] +24-11-19 19:10:56 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 19:10:56 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:10:56 | D | sum error = [ 144.1903, 149.7129, 155.3765, 161.1961, 167.1652] +24-11-19 19:10:56 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 19:10:56 | D | + error = [2.5081] +24-11-19 19:10:56 | D | - Calibrating model.layers.2.mlp.gate_proj.weight +24-11-19 19:10:56 | D | + w: sint8 +24-11-19 19:10:56 | D | + x: None +24-11-19 19:10:56 | D | + y: None +24-11-19 19:10:56 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:10:56 | D | + finished parsing calibration arguments, ram usage: 11.9 +24-11-19 19:10:56 | D | + finished reseting calibrator, ram usage: 11.9 +24-11-19 19:10:56 | D | + finished calculating the original outputs, ram usage: 11.9 +24-11-19 19:10:56 | D | - range ratio = [ 1.0000] +24-11-19 19:10:56 | D | sum error = [ 3.4185] +24-11-19 19:10:56 | D | best error = [ 3.4185] +24-11-19 19:10:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:10:57 | D | sum error = [ 3.3799, 3.3823, 3.3910, 3.4285, 3.4884] +24-11-19 19:10:57 | D | best error = [ 2.9814, 2.8405, 2.7684, 2.7289, 2.7084] +24-11-19 19:10:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:10:57 | D | sum error = [ 3.5885, 3.7103, 3.8656, 4.0462, 4.2538] +24-11-19 19:10:57 | D | best error = [ 2.6974, 2.6922, 2.6898, 2.6891, 2.6889] +24-11-19 19:10:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:10:57 | D | sum error = [ 4.5256, 4.7818, 5.1149, 5.4591, 5.8246] +24-11-19 19:10:57 | D | best error = [ 2.6888, 2.6888, 2.6888, 2.6888, 2.6888] +24-11-19 19:10:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:10:57 | D | sum error = [ 6.2414, 6.6822, 7.1541, 7.6607, 8.2200] +24-11-19 19:10:57 | D | best error = [ 2.6888, 2.6888, 2.6888, 2.6888, 2.6888] +24-11-19 19:10:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:10:57 | D | sum error = [ 8.8205, 9.4340, 10.1078, 10.8003, 11.5488] +24-11-19 19:10:57 | D | best error = [ 2.6888, 2.6888, 2.6888, 2.6888, 2.6888] +24-11-19 19:10:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:10:57 | D | sum error = [ 12.3448, 13.1996, 14.0724, 15.0101, 16.0107] +24-11-19 19:10:57 | D | best error = [ 2.6888, 2.6888, 2.6888, 2.6888, 2.6888] +24-11-19 19:10:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:10:57 | D | sum error = [ 17.0548, 18.1555, 19.3209, 20.5680, 21.8574] +24-11-19 19:10:57 | D | best error = [ 2.6888, 2.6888, 2.6888, 2.6888, 2.6888] +24-11-19 19:10:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:10:57 | D | sum error = [ 23.2258, 24.6838, 26.2143, 27.7872, 29.4699] +24-11-19 19:10:57 | D | best error = [ 2.6888, 2.6888, 2.6888, 2.6888, 2.6888] +24-11-19 19:10:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:10:57 | D | sum error = [ 31.2355, 33.0859, 35.0169, 37.0536, 39.2042] +24-11-19 19:10:57 | D | best error = [ 2.6888, 2.6888, 2.6888, 2.6888, 2.6888] +24-11-19 19:10:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:10:57 | D | sum error = [ 41.4299, 43.7789, 46.2293, 48.7988, 51.4891] +24-11-19 19:10:57 | D | best error = [ 2.6888, 2.6888, 2.6888, 2.6888, 2.6888] +24-11-19 19:10:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:10:57 | D | sum error = [ 54.3019, 57.2514, 60.3225, 63.5165, 66.8771] +24-11-19 19:10:57 | D | best error = [ 2.6888, 2.6888, 2.6888, 2.6888, 2.6888] +24-11-19 19:10:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:10:57 | D | sum error = [ 70.3460, 73.9645, 77.7376, 81.6780, 85.7605] +24-11-19 19:10:57 | D | best error = [ 2.6888, 2.6888, 2.6888, 2.6888, 2.6888] +24-11-19 19:10:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:10:57 | D | sum error = [ 90.0128, 94.4270, 99.0184, 103.7757, 108.7135] +24-11-19 19:10:57 | D | best error = [ 2.6888, 2.6888, 2.6888, 2.6888, 2.6888] +24-11-19 19:10:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:10:57 | D | sum error = [ 113.8411, 119.1561, 124.6358, 130.3337, 136.1993] +24-11-19 19:10:57 | D | best error = [ 2.6888, 2.6888, 2.6888, 2.6888, 2.6888] +24-11-19 19:10:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:10:57 | D | sum error = [ 142.2865, 148.5769, 155.0721, 161.7821, 168.7025] +24-11-19 19:10:57 | D | best error = [ 2.6888, 2.6888, 2.6888, 2.6888, 2.6888] +24-11-19 19:10:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:10:57 | D | sum error = [ 175.8410, 183.1951, 190.7606, 198.5570, 206.5691] +24-11-19 19:10:57 | D | best error = [ 2.6888, 2.6888, 2.6888, 2.6888, 2.6888] +24-11-19 19:10:57 | D | + error = [2.6888] +24-11-19 19:10:57 | D | - Calibrating model.layers.2.mlp.down_proj.weight +24-11-19 19:10:57 | D | + w: sint8 +24-11-19 19:10:57 | D | + x: None +24-11-19 19:10:57 | D | + y: None +24-11-19 19:10:57 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:10:57 | D | + finished parsing calibration arguments, ram usage: 11.9 +24-11-19 19:10:58 | D | + finished reseting calibrator, ram usage: 11.9 +24-11-19 19:10:58 | D | + finished calculating the original outputs, ram usage: 11.9 +24-11-19 19:10:58 | D | - range ratio = [ 1.0000] +24-11-19 19:10:58 | D | sum error = [ 0.3957] +24-11-19 19:10:58 | D | best error = [ 0.3957] +24-11-19 19:10:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:10:59 | D | sum error = [ 0.3912, 0.3878, 0.3860, 0.3856, 0.3843] +24-11-19 19:10:59 | D | best error = [ 0.3663, 0.3535, 0.3464, 0.3413, 0.3375] +24-11-19 19:10:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:10:59 | D | sum error = [ 0.3880, 0.3912, 0.3959, 0.4065, 0.4171] +24-11-19 19:10:59 | D | best error = [ 0.3345, 0.3323, 0.3308, 0.3298, 0.3291] +24-11-19 19:10:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:10:59 | D | sum error = [ 0.4312, 0.4470, 0.4663, 0.4876, 0.5117] +24-11-19 19:10:59 | D | best error = [ 0.3285, 0.3282, 0.3280, 0.3279, 0.3278] +24-11-19 19:10:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:10:59 | D | sum error = [ 0.5384, 0.5696, 0.6036, 0.6399, 0.6820] +24-11-19 19:10:59 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 19:10:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:10:59 | D | sum error = [ 0.7260, 0.7756, 0.8306, 0.8901, 0.9548] +24-11-19 19:10:59 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 19:10:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:10:59 | D | sum error = [ 1.0240, 1.0991, 1.1798, 1.2661, 1.3588] +24-11-19 19:10:59 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 19:10:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:10:59 | D | sum error = [ 1.4588, 1.5642, 1.6774, 1.7984, 1.9267] +24-11-19 19:10:59 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 19:10:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:10:59 | D | sum error = [ 2.0640, 2.2098, 2.3643, 2.5275, 2.6999] +24-11-19 19:10:59 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 19:10:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:10:59 | D | sum error = [ 2.8833, 3.0772, 3.2832, 3.4997, 3.7283] +24-11-19 19:10:59 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 19:10:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:10:59 | D | sum error = [ 3.9702, 4.2243, 4.4911, 4.7718, 5.0657] +24-11-19 19:10:59 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 19:10:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:10:59 | D | sum error = [ 5.3740, 5.6978, 6.0373, 6.3944, 6.7682] +24-11-19 19:10:59 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 19:10:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:10:59 | D | sum error = [ 7.1598, 7.5695, 7.9975, 8.4451, 8.9127] +24-11-19 19:10:59 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 19:10:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:10:59 | D | sum error = [ 9.4005, 9.9090, 10.4391, 10.9916, 11.5667] +24-11-19 19:10:59 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 19:10:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:10:59 | D | sum error = [ 12.1646, 12.7856, 13.4308, 14.1018, 14.7946] +24-11-19 19:10:59 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 19:10:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:10:59 | D | sum error = [ 15.5143, 16.2598, 17.0316, 17.8299, 18.6556] +24-11-19 19:10:59 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 19:10:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:10:59 | D | sum error = [ 19.5095, 20.3908, 21.3016, 22.2413, 23.2103] +24-11-19 19:10:59 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 19:10:59 | D | + error = [0.3277] +24-11-19 19:10:59 | D | - Quantizing model.layers.2.self_attn.q_proj.weight +24-11-19 19:11:00 | D | - Quantizing model.layers.2.self_attn.k_proj.weight +24-11-19 19:11:00 | D | - Quantizing model.layers.2.self_attn.v_proj.weight +24-11-19 19:11:01 | D | - Quantizing model.layers.2.self_attn.o_proj.weight +24-11-19 19:11:02 | D | - Quantizing model.layers.2.mlp.up_proj.weight +24-11-19 19:11:03 | D | - Quantizing model.layers.2.mlp.gate_proj.weight +24-11-19 19:11:04 | D | - Quantizing model.layers.2.mlp.down_proj.weight +24-11-19 19:11:13 | D | - Quantizing layer model.layers.3 +24-11-19 19:11:13 | D | - Calibrating model.layers.3.self_attn.q_proj.weight +24-11-19 19:11:13 | D | + w: sint8 +24-11-19 19:11:13 | D | + x: None +24-11-19 19:11:13 | D | + y: None +24-11-19 19:11:13 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:11:13 | D | + finished parsing calibration arguments, ram usage: 12.0 +24-11-19 19:11:13 | D | + finished reseting calibrator, ram usage: 12.0 +24-11-19 19:11:13 | D | + finished calculating the original outputs, ram usage: 12.0 +24-11-19 19:11:13 | D | - range ratio = [ 1.0000] +24-11-19 19:11:13 | D | sum error = [ 2.0167] +24-11-19 19:11:13 | D | best error = [ 2.0167] +24-11-19 19:11:26 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:11:26 | D | sum error = [ 2.1272, 2.0655, 2.1005, 2.0967, 2.1272] +24-11-19 19:11:26 | D | best error = [ 2.0167, 2.0167, 2.0167, 2.0167, 2.0167] +24-11-19 19:11:26 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:11:26 | D | sum error = [ 2.1105, 2.2563, 2.3462, 2.4504, 2.6515] +24-11-19 19:11:26 | D | best error = [ 2.0167, 2.0167, 2.0167, 2.0167, 2.0167] +24-11-19 19:11:26 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:11:26 | D | sum error = [ 2.7488, 3.0984, 3.2493, 3.7084, 4.0849] +24-11-19 19:11:26 | D | best error = [ 2.0167, 2.0167, 2.0167, 2.0167, 2.0167] +24-11-19 19:11:26 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:11:26 | D | sum error = [ 4.5273, 4.6718, 5.1923, 5.7296, 6.1387] +24-11-19 19:11:26 | D | best error = [ 2.0167, 2.0167, 2.0167, 2.0167, 2.0167] +24-11-19 19:11:26 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:11:26 | D | sum error = [ 6.8675, 7.6518, 8.4296, 9.2827, 10.1846] +24-11-19 19:11:26 | D | best error = [ 2.0167, 2.0167, 2.0167, 2.0167, 2.0167] +24-11-19 19:11:26 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:11:26 | D | sum error = [ 11.0974, 12.4474, 13.8600, 15.3884, 16.9080] +24-11-19 19:11:26 | D | best error = [ 2.0167, 2.0167, 2.0167, 2.0167, 2.0167] +24-11-19 19:11:26 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:11:26 | D | sum error = [ 18.7228, 20.7603, 23.1109, 25.1734, 28.0632] +24-11-19 19:11:26 | D | best error = [ 2.0167, 2.0167, 2.0167, 2.0167, 2.0167] +24-11-19 19:11:26 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:11:26 | D | sum error = [ 30.9588, 33.9111, 37.3000, 41.1305, 45.2013] +24-11-19 19:11:26 | D | best error = [ 2.0167, 2.0167, 2.0167, 2.0167, 2.0167] +24-11-19 19:11:26 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:11:26 | D | sum error = [ 49.5217, 54.3465, 59.6429, 65.1593, 71.3553] +24-11-19 19:11:26 | D | best error = [ 2.0167, 2.0167, 2.0167, 2.0167, 2.0167] +24-11-19 19:11:26 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:11:26 | D | sum error = [ 78.0784, 85.1803, 93.0347, 101.6169, 111.2486] +24-11-19 19:11:26 | D | best error = [ 2.0167, 2.0167, 2.0167, 2.0167, 2.0167] +24-11-19 19:11:26 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:11:26 | D | sum error = [ 121.4166, 132.8318, 144.8389, 157.8616, 172.2626] +24-11-19 19:11:26 | D | best error = [ 2.0167, 2.0167, 2.0167, 2.0167, 2.0167] +24-11-19 19:11:26 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:11:26 | D | sum error = [ 187.9312, 204.7506, 222.3633, 242.0475, 263.2055] +24-11-19 19:11:26 | D | best error = [ 2.0167, 2.0167, 2.0167, 2.0167, 2.0167] +24-11-19 19:11:26 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:11:26 | D | sum error = [ 285.4209, 310.0460, 336.7392, 365.6827, 397.0335] +24-11-19 19:11:26 | D | best error = [ 2.0167, 2.0167, 2.0167, 2.0167, 2.0167] +24-11-19 19:11:26 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:11:26 | D | sum error = [ 431.0689, 467.6566, 507.2949, 550.2202, 596.1541] +24-11-19 19:11:26 | D | best error = [ 2.0167, 2.0167, 2.0167, 2.0167, 2.0167] +24-11-19 19:11:26 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:11:26 | D | sum error = [ 645.6583, 697.8804, 753.3889, 812.3496, 874.1370] +24-11-19 19:11:26 | D | best error = [ 2.0167, 2.0167, 2.0167, 2.0167, 2.0167] +24-11-19 19:11:26 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:11:26 | D | sum error = [ 939.4703, 1007.0892, 1078.1579, 1150.5293, 1223.9253] +24-11-19 19:11:26 | D | best error = [ 2.0167, 2.0167, 2.0167, 2.0167, 2.0167] +24-11-19 19:11:26 | D | + error = [2.0167] +24-11-19 19:11:26 | D | - Calibrating model.layers.3.self_attn.k_proj.weight +24-11-19 19:11:26 | D | + w: sint8 +24-11-19 19:11:26 | D | + x: None +24-11-19 19:11:26 | D | + y: None +24-11-19 19:11:26 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:11:26 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:11:26 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:11:26 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:11:26 | D | - range ratio = [ 1.0000] +24-11-19 19:11:26 | D | sum error = [ 2.4360] +24-11-19 19:11:26 | D | best error = [ 2.4360] +24-11-19 19:11:39 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:11:39 | D | sum error = [ 2.4034, 2.2510, 2.7047, 2.4543, 2.4213] +24-11-19 19:11:39 | D | best error = [ 2.4034, 2.2510, 2.2510, 2.2510, 2.2510] +24-11-19 19:11:39 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:11:39 | D | sum error = [ 2.5884, 2.4951, 2.9633, 3.3704, 3.5346] +24-11-19 19:11:39 | D | best error = [ 2.2510, 2.2510, 2.2510, 2.2510, 2.2510] +24-11-19 19:11:39 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:11:39 | D | sum error = [ 3.5265, 3.7155, 4.3305, 4.8576, 5.2966] +24-11-19 19:11:39 | D | best error = [ 2.2510, 2.2510, 2.2510, 2.2510, 2.2510] +24-11-19 19:11:39 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:11:39 | D | sum error = [ 6.2538, 6.2422, 7.1003, 7.6734, 8.4709] +24-11-19 19:11:39 | D | best error = [ 2.2510, 2.2510, 2.2510, 2.2510, 2.2510] +24-11-19 19:11:39 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:11:39 | D | sum error = [ 9.0974, 10.0819, 11.4152, 12.3714, 13.4107] +24-11-19 19:11:39 | D | best error = [ 2.2510, 2.2510, 2.2510, 2.2510, 2.2510] +24-11-19 19:11:39 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:11:39 | D | sum error = [ 14.5816, 16.3188, 17.7635, 18.9815, 20.8296] +24-11-19 19:11:39 | D | best error = [ 2.2510, 2.2510, 2.2510, 2.2510, 2.2510] +24-11-19 19:11:39 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:11:39 | D | sum error = [ 22.5937, 24.5566, 27.1559, 28.8719, 31.6330] +24-11-19 19:11:39 | D | best error = [ 2.2510, 2.2510, 2.2510, 2.2510, 2.2510] +24-11-19 19:11:39 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:11:39 | D | sum error = [ 34.5045, 37.3514, 40.6215, 43.9411, 47.0187] +24-11-19 19:11:39 | D | best error = [ 2.2510, 2.2510, 2.2510, 2.2510, 2.2510] +24-11-19 19:11:39 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:11:39 | D | sum error = [ 51.0976, 55.3782, 60.2371, 65.1545, 70.6087] +24-11-19 19:11:39 | D | best error = [ 2.2510, 2.2510, 2.2510, 2.2510, 2.2510] +24-11-19 19:11:39 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:11:39 | D | sum error = [ 77.0999, 83.7129, 90.6667, 99.1041, 107.7650] +24-11-19 19:11:39 | D | best error = [ 2.2510, 2.2510, 2.2510, 2.2510, 2.2510] +24-11-19 19:11:39 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:11:39 | D | sum error = [ 117.2465, 127.3010, 138.4207, 149.5758, 163.1476] +24-11-19 19:11:39 | D | best error = [ 2.2510, 2.2510, 2.2510, 2.2510, 2.2510] +24-11-19 19:11:39 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:11:39 | D | sum error = [ 177.2038, 193.0569, 209.8121, 227.4695, 248.3331] +24-11-19 19:11:39 | D | best error = [ 2.2510, 2.2510, 2.2510, 2.2510, 2.2510] +24-11-19 19:11:39 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:11:39 | D | sum error = [ 268.8456, 291.6786, 316.6899, 344.0742, 376.9404] +24-11-19 19:11:39 | D | best error = [ 2.2510, 2.2510, 2.2510, 2.2510, 2.2510] +24-11-19 19:11:39 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:11:39 | D | sum error = [ 407.2249, 447.1477, 483.1091, 522.5171, 567.2305] +24-11-19 19:11:39 | D | best error = [ 2.2510, 2.2510, 2.2510, 2.2510, 2.2510] +24-11-19 19:11:39 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:11:39 | D | sum error = [ 613.0566, 668.7399, 721.7783, 782.1763, 842.9247] +24-11-19 19:11:39 | D | best error = [ 2.2510, 2.2510, 2.2510, 2.2510, 2.2510] +24-11-19 19:11:39 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:11:39 | D | sum error = [ 908.4379, 977.5851, 1045.7100, 1119.3671, 1193.8637] +24-11-19 19:11:39 | D | best error = [ 2.2510, 2.2510, 2.2510, 2.2510, 2.2510] +24-11-19 19:11:39 | D | + error = [2.2510] +24-11-19 19:11:39 | D | - Calibrating model.layers.3.self_attn.v_proj.weight +24-11-19 19:11:39 | D | + w: sint8 +24-11-19 19:11:39 | D | + x: None +24-11-19 19:11:39 | D | + y: None +24-11-19 19:11:39 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:11:39 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:11:39 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:11:39 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:11:39 | D | - range ratio = [ 1.0000] +24-11-19 19:11:39 | D | sum error = [ 3.1706] +24-11-19 19:11:39 | D | best error = [ 3.1706] +24-11-19 19:11:39 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:11:39 | D | sum error = [ 3.1660, 3.1279, 3.1505, 3.1895, 3.2413] +24-11-19 19:11:39 | D | best error = [ 2.8480, 2.7361, 2.6846, 2.6565, 2.6406] +24-11-19 19:11:39 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:11:39 | D | sum error = [ 3.3541, 3.4517, 3.5666, 3.7338, 3.9333] +24-11-19 19:11:39 | D | best error = [ 2.6332, 2.6299, 2.6281, 2.6278, 2.6277] +24-11-19 19:11:39 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:11:39 | D | sum error = [ 4.1650, 4.4322, 4.7030, 5.0033, 5.3494] +24-11-19 19:11:39 | D | best error = [ 2.6276, 2.6276, 2.6276, 2.6276, 2.6276] +24-11-19 19:11:39 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:11:39 | D | sum error = [ 5.7114, 6.1291, 6.5650, 7.0458, 7.5581] +24-11-19 19:11:39 | D | best error = [ 2.6276, 2.6276, 2.6276, 2.6276, 2.6276] +24-11-19 19:11:39 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:11:39 | D | sum error = [ 8.0964, 8.6721, 9.2963, 9.9548, 10.6288] +24-11-19 19:11:39 | D | best error = [ 2.6276, 2.6276, 2.6276, 2.6276, 2.6276] +24-11-19 19:11:39 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:11:39 | D | sum error = [ 11.3693, 12.1552, 12.9588, 13.8474, 14.7824] +24-11-19 19:11:39 | D | best error = [ 2.6276, 2.6276, 2.6276, 2.6276, 2.6276] +24-11-19 19:11:39 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:11:39 | D | sum error = [ 15.7430, 16.7828, 17.8507, 19.0113, 20.1979] +24-11-19 19:11:39 | D | best error = [ 2.6276, 2.6276, 2.6276, 2.6276, 2.6276] +24-11-19 19:11:39 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:11:39 | D | sum error = [ 21.4800, 22.8115, 24.1978, 25.6872, 27.2160] +24-11-19 19:11:39 | D | best error = [ 2.6276, 2.6276, 2.6276, 2.6276, 2.6276] +24-11-19 19:11:39 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:11:39 | D | sum error = [ 28.8699, 30.5675, 32.3739, 34.2506, 36.2385] +24-11-19 19:11:39 | D | best error = [ 2.6276, 2.6276, 2.6276, 2.6276, 2.6276] +24-11-19 19:11:39 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:11:39 | D | sum error = [ 38.2760, 40.4485, 42.6884, 45.0550, 47.5271] +24-11-19 19:11:39 | D | best error = [ 2.6276, 2.6276, 2.6276, 2.6276, 2.6276] +24-11-19 19:11:39 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:11:39 | D | sum error = [ 50.0836, 52.7734, 55.5666, 58.4940, 61.5511] +24-11-19 19:11:39 | D | best error = [ 2.6276, 2.6276, 2.6276, 2.6276, 2.6276] +24-11-19 19:11:39 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:11:39 | D | sum error = [ 64.7368, 68.0533, 71.5216, 75.1339, 78.8851] +24-11-19 19:11:39 | D | best error = [ 2.6276, 2.6276, 2.6276, 2.6276, 2.6276] +24-11-19 19:11:39 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:11:39 | D | sum error = [ 82.7933, 86.8490, 91.0599, 95.4308, 99.9572] +24-11-19 19:11:39 | D | best error = [ 2.6276, 2.6276, 2.6276, 2.6276, 2.6276] +24-11-19 19:11:39 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:11:39 | D | sum error = [ 104.6321, 109.4795, 114.5202, 119.7338, 125.1312] +24-11-19 19:11:39 | D | best error = [ 2.6276, 2.6276, 2.6276, 2.6276, 2.6276] +24-11-19 19:11:39 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:11:39 | D | sum error = [ 130.7124, 136.4779, 142.4454, 148.6013, 154.9425] +24-11-19 19:11:39 | D | best error = [ 2.6276, 2.6276, 2.6276, 2.6276, 2.6276] +24-11-19 19:11:39 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:11:39 | D | sum error = [ 161.4925, 168.2351, 175.1854, 182.3413, 189.7056] +24-11-19 19:11:39 | D | best error = [ 2.6276, 2.6276, 2.6276, 2.6276, 2.6276] +24-11-19 19:11:39 | D | + error = [2.6276] +24-11-19 19:11:39 | D | - Calibrating model.layers.3.self_attn.o_proj.weight +24-11-19 19:11:39 | D | + w: sint8 +24-11-19 19:11:39 | D | + x: None +24-11-19 19:11:39 | D | + y: None +24-11-19 19:11:39 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:11:39 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:11:39 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:11:40 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:11:40 | D | - range ratio = [ 1.0000] +24-11-19 19:11:40 | D | sum error = [ 0.2488] +24-11-19 19:11:40 | D | best error = [ 0.2488] +24-11-19 19:11:40 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:11:40 | D | sum error = [ 0.2462, 0.2457, 0.2470, 0.2486, 0.2532] +24-11-19 19:11:40 | D | best error = [ 0.2354, 0.2292, 0.2260, 0.2240, 0.2227] +24-11-19 19:11:40 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:11:40 | D | sum error = [ 0.2589, 0.2665, 0.2761, 0.2869, 0.3018] +24-11-19 19:11:40 | D | best error = [ 0.2219, 0.2215, 0.2212, 0.2210, 0.2209] +24-11-19 19:11:40 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:11:40 | D | sum error = [ 0.3182, 0.3358, 0.3564, 0.3797, 0.4041] +24-11-19 19:11:40 | D | best error = [ 0.2208, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 19:11:40 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:11:40 | D | sum error = [ 0.4315, 0.4607, 0.4929, 0.5265, 0.5638] +24-11-19 19:11:40 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 19:11:40 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:11:40 | D | sum error = [ 0.6028, 0.6449, 0.6889, 0.7371, 0.7880] +24-11-19 19:11:40 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 19:11:40 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:11:40 | D | sum error = [ 0.8410, 0.8980, 0.9578, 1.0216, 1.0888] +24-11-19 19:11:40 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 19:11:40 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:11:40 | D | sum error = [ 1.1606, 1.2359, 1.3161, 1.3997, 1.4898] +24-11-19 19:11:40 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 19:11:40 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:11:40 | D | sum error = [ 1.5824, 1.6826, 1.7865, 1.8977, 2.0138] +24-11-19 19:11:40 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 19:11:40 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:11:40 | D | sum error = [ 2.1376, 2.2669, 2.4037, 2.5476, 2.6999] +24-11-19 19:11:40 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 19:11:40 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:11:40 | D | sum error = [ 2.8608, 3.0289, 3.2072, 3.3940, 3.5910] +24-11-19 19:11:40 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 19:11:40 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:11:40 | D | sum error = [ 3.7980, 4.0163, 4.2454, 4.4861, 4.7395] +24-11-19 19:11:40 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 19:11:40 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:11:40 | D | sum error = [ 5.0054, 5.2852, 5.5780, 5.8859, 6.2090] +24-11-19 19:11:40 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 19:11:40 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:11:40 | D | sum error = [ 6.5478, 6.9027, 7.2743, 7.6632, 8.0707] +24-11-19 19:11:40 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 19:11:40 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:11:40 | D | sum error = [ 8.4969, 8.9420, 9.4076, 9.8928, 10.4005] +24-11-19 19:11:40 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 19:11:40 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:11:40 | D | sum error = [ 10.9290, 11.4795, 12.0534, 12.6506, 13.2708] +24-11-19 19:11:40 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 19:11:40 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:11:40 | D | sum error = [ 13.9145, 14.5828, 15.2749, 15.9925, 16.7344] +24-11-19 19:11:40 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 19:11:40 | D | + error = [0.2207] +24-11-19 19:11:40 | D | - Calibrating model.layers.3.mlp.up_proj.weight +24-11-19 19:11:40 | D | + w: sint8 +24-11-19 19:11:40 | D | + x: None +24-11-19 19:11:40 | D | + y: None +24-11-19 19:11:40 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:11:40 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:11:40 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:11:40 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:11:40 | D | - range ratio = [ 1.0000] +24-11-19 19:11:40 | D | sum error = [ 4.0371] +24-11-19 19:11:40 | D | best error = [ 4.0371] +24-11-19 19:11:41 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:11:41 | D | sum error = [ 3.9997, 3.9891, 4.0198, 4.0567, 4.1421] +24-11-19 19:11:41 | D | best error = [ 3.5556, 3.3917, 3.3174, 3.2756, 3.2531] +24-11-19 19:11:41 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:11:41 | D | sum error = [ 4.2349, 4.3860, 4.5690, 4.8016, 5.0211] +24-11-19 19:11:41 | D | best error = [ 3.2408, 3.2357, 3.2339, 3.2333, 3.2330] +24-11-19 19:11:41 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:11:41 | D | sum error = [ 5.3260, 5.6451, 6.0028, 6.4385, 6.8618] +24-11-19 19:11:41 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 19:11:41 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:11:41 | D | sum error = [ 7.3533, 7.8699, 8.4187, 9.0236, 9.6617] +24-11-19 19:11:41 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 19:11:41 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:11:41 | D | sum error = [ 10.3400, 11.0782, 11.8345, 12.6674, 13.5208] +24-11-19 19:11:41 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 19:11:41 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:11:41 | D | sum error = [ 14.4554, 15.4173, 16.4414, 17.5209, 18.6666] +24-11-19 19:11:41 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 19:11:41 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:11:41 | D | sum error = [ 19.8547, 21.1249, 22.4490, 23.8494, 25.3316] +24-11-19 19:11:41 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 19:11:41 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:11:41 | D | sum error = [ 26.8635, 28.4739, 30.1801, 31.9588, 33.8146] +24-11-19 19:11:41 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 19:11:41 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:11:41 | D | sum error = [ 35.7730, 37.8166, 39.9380, 42.1771, 44.4934] +24-11-19 19:11:41 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 19:11:41 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:11:41 | D | sum error = [ 46.9164, 49.4361, 52.0725, 54.7795, 57.6262] +24-11-19 19:11:41 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 19:11:41 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:11:41 | D | sum error = [ 60.5796, 63.6715, 66.8605, 70.1693, 73.5972] +24-11-19 19:11:41 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 19:11:41 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:11:41 | D | sum error = [ 77.1622, 80.8415, 84.6597, 88.6176, 92.6898] +24-11-19 19:11:41 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 19:11:41 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:11:41 | D | sum error = [ 96.9010, 101.2543, 105.7461, 110.3730, 115.1352] +24-11-19 19:11:41 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 19:11:41 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:11:41 | D | sum error = [ 120.0343, 125.0633, 130.2710, 135.6182, 141.1119] +24-11-19 19:11:41 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 19:11:41 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:11:41 | D | sum error = [ 146.7442, 152.5281, 158.4692, 164.5602, 170.8085] +24-11-19 19:11:41 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 19:11:41 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:11:41 | D | sum error = [ 177.2113, 183.7805, 190.5081, 197.4101, 204.4939] +24-11-19 19:11:41 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 19:11:41 | D | + error = [3.2330] +24-11-19 19:11:41 | D | - Calibrating model.layers.3.mlp.gate_proj.weight +24-11-19 19:11:41 | D | + w: sint8 +24-11-19 19:11:41 | D | + x: None +24-11-19 19:11:41 | D | + y: None +24-11-19 19:11:41 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:11:41 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:11:41 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:11:42 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:11:42 | D | - range ratio = [ 1.0000] +24-11-19 19:11:42 | D | sum error = [ 4.3528] +24-11-19 19:11:42 | D | best error = [ 4.3528] +24-11-19 19:11:42 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:11:42 | D | sum error = [ 4.3124, 4.3101, 4.3310, 4.3907, 4.4582] +24-11-19 19:11:42 | D | best error = [ 3.8366, 3.6601, 3.5781, 3.5332, 3.5096] +24-11-19 19:11:42 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:11:42 | D | sum error = [ 4.5715, 4.7273, 4.8956, 5.1579, 5.4426] +24-11-19 19:11:42 | D | best error = [ 3.4969, 3.4921, 3.4897, 3.4891, 3.4889] +24-11-19 19:11:42 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:11:42 | D | sum error = [ 5.7226, 6.0866, 6.4692, 6.8953, 7.3639] +24-11-19 19:11:42 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 19:11:42 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:11:42 | D | sum error = [ 7.8899, 8.4681, 9.0681, 9.7274, 10.4372] +24-11-19 19:11:42 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 19:11:42 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:11:42 | D | sum error = [ 11.1614, 11.9549, 12.7852, 13.7114, 14.6360] +24-11-19 19:11:42 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 19:11:42 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:11:42 | D | sum error = [ 15.6397, 16.7247, 17.8433, 19.0212, 20.2679] +24-11-19 19:11:42 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 19:11:42 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:11:42 | D | sum error = [ 21.5937, 22.9821, 24.4543, 26.0112, 27.6266] +24-11-19 19:11:42 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 19:11:42 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:11:42 | D | sum error = [ 29.3294, 31.1147, 33.0042, 34.9827, 37.0529] +24-11-19 19:11:42 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 19:11:42 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:11:42 | D | sum error = [ 39.2308, 41.4904, 43.8937, 46.3923, 49.0047] +24-11-19 19:11:42 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 19:11:42 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:11:42 | D | sum error = [ 51.7467, 54.6220, 57.6328, 60.7766, 64.0713] +24-11-19 19:11:42 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 19:11:42 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:11:42 | D | sum error = [ 67.4904, 71.0608, 74.7897, 78.6753, 82.7282] +24-11-19 19:11:42 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 19:11:42 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:11:42 | D | sum error = [ 86.9353, 91.3115, 95.8780, 100.6373, 105.5657] +24-11-19 19:11:42 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 19:11:42 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:11:42 | D | sum error = [ 110.7025, 116.0258, 121.5374, 127.2422, 133.1710] +24-11-19 19:11:42 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 19:11:42 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:11:42 | D | sum error = [ 139.2816, 145.5712, 152.1072, 158.8479, 165.8217] +24-11-19 19:11:42 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 19:11:42 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:11:42 | D | sum error = [ 173.0248, 180.4731, 188.1764, 196.1141, 204.2949] +24-11-19 19:11:42 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 19:11:42 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:11:42 | D | sum error = [ 212.7332, 221.4085, 230.3369, 239.5203, 248.9592] +24-11-19 19:11:42 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 19:11:42 | D | + error = [3.4889] +24-11-19 19:11:43 | D | - Calibrating model.layers.3.mlp.down_proj.weight +24-11-19 19:11:43 | D | + w: sint8 +24-11-19 19:11:43 | D | + x: None +24-11-19 19:11:43 | D | + y: None +24-11-19 19:11:43 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:11:43 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:11:43 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:11:43 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:11:43 | D | - range ratio = [ 1.0000] +24-11-19 19:11:43 | D | sum error = [ 0.4792] +24-11-19 19:11:43 | D | best error = [ 0.4792] +24-11-19 19:11:44 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:11:44 | D | sum error = [ 0.4748, 0.4717, 0.4686, 0.4680, 0.4671] +24-11-19 19:11:44 | D | best error = [ 0.4655, 0.4580, 0.4525, 0.4486, 0.4455] +24-11-19 19:11:44 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:11:44 | D | sum error = [ 0.4693, 0.4722, 0.4786, 0.4866, 0.4974] +24-11-19 19:11:44 | D | best error = [ 0.4430, 0.4413, 0.4400, 0.4392, 0.4387] +24-11-19 19:11:44 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:11:44 | D | sum error = [ 0.5096, 0.5257, 0.5444, 0.5669, 0.5928] +24-11-19 19:11:44 | D | best error = [ 0.4384, 0.4382, 0.4380, 0.4379, 0.4379] +24-11-19 19:11:44 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:11:44 | D | sum error = [ 0.6226, 0.6562, 0.6938, 0.7355, 0.7811] +24-11-19 19:11:44 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 19:11:44 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:11:44 | D | sum error = [ 0.8315, 0.8871, 0.9463, 1.0106, 1.0806] +24-11-19 19:11:44 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 19:11:44 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:11:44 | D | sum error = [ 1.1559, 1.2362, 1.3219, 1.4152, 1.5138] +24-11-19 19:11:44 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 19:11:44 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:11:44 | D | sum error = [ 1.6188, 1.7316, 1.8506, 1.9775, 2.1127] +24-11-19 19:11:44 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 19:11:44 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:11:44 | D | sum error = [ 2.2569, 2.4093, 2.5726, 2.7428, 2.9250] +24-11-19 19:11:44 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 19:11:44 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:11:44 | D | sum error = [ 3.1173, 3.3218, 3.5368, 3.7653, 4.0059] +24-11-19 19:11:44 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 19:11:44 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:11:44 | D | sum error = [ 4.2604, 4.5291, 4.8116, 5.1098, 5.4236] +24-11-19 19:11:44 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 19:11:44 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:11:44 | D | sum error = [ 5.7537, 6.1017, 6.4668, 6.8510, 7.2545] +24-11-19 19:11:44 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 19:11:44 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:11:44 | D | sum error = [ 7.6787, 8.1231, 8.5895, 9.0782, 9.5907] +24-11-19 19:11:44 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 19:11:44 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:11:44 | D | sum error = [ 10.1269, 10.6881, 11.2749, 11.8881, 12.5280] +24-11-19 19:11:44 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 19:11:44 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:11:44 | D | sum error = [ 13.1961, 13.8924, 14.6190, 15.3770, 16.1627] +24-11-19 19:11:44 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 19:11:44 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:11:44 | D | sum error = [ 16.9821, 17.8337, 18.7185, 19.6373, 20.5902] +24-11-19 19:11:44 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 19:11:44 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:11:44 | D | sum error = [ 21.5774, 22.6006, 23.6589, 24.7537, 25.8856] +24-11-19 19:11:44 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 19:11:44 | D | + error = [0.4379] +24-11-19 19:11:44 | D | - Quantizing model.layers.3.self_attn.q_proj.weight +24-11-19 19:11:45 | D | - Quantizing model.layers.3.self_attn.k_proj.weight +24-11-19 19:11:46 | D | - Quantizing model.layers.3.self_attn.v_proj.weight +24-11-19 19:11:46 | D | - Quantizing model.layers.3.self_attn.o_proj.weight +24-11-19 19:11:47 | D | - Quantizing model.layers.3.mlp.up_proj.weight +24-11-19 19:11:48 | D | - Quantizing model.layers.3.mlp.gate_proj.weight +24-11-19 19:11:49 | D | - Quantizing model.layers.3.mlp.down_proj.weight +24-11-19 19:11:58 | D | - Quantizing layer model.layers.4 +24-11-19 19:11:58 | D | - Calibrating model.layers.4.self_attn.q_proj.weight +24-11-19 19:11:58 | D | + w: sint8 +24-11-19 19:11:58 | D | + x: None +24-11-19 19:11:58 | D | + y: None +24-11-19 19:11:58 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:11:58 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:11:58 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:11:58 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:11:58 | D | - range ratio = [ 1.0000] +24-11-19 19:11:58 | D | sum error = [ 2.5448] +24-11-19 19:11:58 | D | best error = [ 2.5448] +24-11-19 19:12:11 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:12:11 | D | sum error = [ 2.4785, 2.5326, 2.5048, 2.6454, 2.6806] +24-11-19 19:12:11 | D | best error = [ 2.4785, 2.4785, 2.4785, 2.4785, 2.4785] +24-11-19 19:12:11 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:12:11 | D | sum error = [ 2.8771, 2.9659, 3.1129, 3.5654, 3.6731] +24-11-19 19:12:11 | D | best error = [ 2.4785, 2.4785, 2.4785, 2.4785, 2.4785] +24-11-19 19:12:11 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:12:11 | D | sum error = [ 3.8449, 4.5025, 5.0322, 5.7382, 6.3903] +24-11-19 19:12:11 | D | best error = [ 2.4785, 2.4785, 2.4785, 2.4785, 2.4785] +24-11-19 19:12:11 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:12:11 | D | sum error = [ 6.9367, 7.7685, 8.9943, 9.9490, 11.1535] +24-11-19 19:12:11 | D | best error = [ 2.4785, 2.4785, 2.4785, 2.4785, 2.4785] +24-11-19 19:12:11 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:12:11 | D | sum error = [ 12.6241, 13.5904, 15.0773, 16.6732, 18.5516] +24-11-19 19:12:11 | D | best error = [ 2.4785, 2.4785, 2.4785, 2.4785, 2.4785] +24-11-19 19:12:11 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:12:11 | D | sum error = [ 20.6115, 22.1859, 24.8444, 26.9888, 29.5211] +24-11-19 19:12:11 | D | best error = [ 2.4785, 2.4785, 2.4785, 2.4785, 2.4785] +24-11-19 19:12:11 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:12:11 | D | sum error = [ 32.3240, 35.2176, 38.3578, 42.2783, 45.9943] +24-11-19 19:12:11 | D | best error = [ 2.4785, 2.4785, 2.4785, 2.4785, 2.4785] +24-11-19 19:12:11 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:12:11 | D | sum error = [ 50.2286, 54.5576, 59.5963, 65.0616, 70.8185] +24-11-19 19:12:11 | D | best error = [ 2.4785, 2.4785, 2.4785, 2.4785, 2.4785] +24-11-19 19:12:11 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:12:11 | D | sum error = [ 77.2425, 83.9460, 90.9869, 98.5067, 106.7946] +24-11-19 19:12:11 | D | best error = [ 2.4785, 2.4785, 2.4785, 2.4785, 2.4785] +24-11-19 19:12:11 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:12:11 | D | sum error = [ 115.8833, 125.4325, 135.8004, 146.8687, 158.6615] +24-11-19 19:12:11 | D | best error = [ 2.4785, 2.4785, 2.4785, 2.4785, 2.4785] +24-11-19 19:12:11 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:12:11 | D | sum error = [ 171.7839, 185.1734, 200.3124, 216.1618, 233.2766] +24-11-19 19:12:11 | D | best error = [ 2.4785, 2.4785, 2.4785, 2.4785, 2.4785] +24-11-19 19:12:11 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:12:11 | D | sum error = [ 251.5865, 271.1675, 292.1509, 313.9859, 338.2363] +24-11-19 19:12:11 | D | best error = [ 2.4785, 2.4785, 2.4785, 2.4785, 2.4785] +24-11-19 19:12:11 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:12:11 | D | sum error = [ 363.9450, 391.4892, 420.4151, 452.2286, 485.3800] +24-11-19 19:12:11 | D | best error = [ 2.4785, 2.4785, 2.4785, 2.4785, 2.4785] +24-11-19 19:12:11 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:12:11 | D | sum error = [ 520.9769, 558.9521, 598.8525, 641.6928, 685.6901] +24-11-19 19:12:11 | D | best error = [ 2.4785, 2.4785, 2.4785, 2.4785, 2.4785] +24-11-19 19:12:11 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:12:11 | D | sum error = [ 732.0339, 780.3515, 830.2672, 882.9478, 937.1592] +24-11-19 19:12:11 | D | best error = [ 2.4785, 2.4785, 2.4785, 2.4785, 2.4785] +24-11-19 19:12:11 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:12:11 | D | sum error = [ 992.9558, 1050.2744, 1109.1132, 1169.0017, 1229.0472] +24-11-19 19:12:11 | D | best error = [ 2.4785, 2.4785, 2.4785, 2.4785, 2.4785] +24-11-19 19:12:11 | D | + error = [2.4785] +24-11-19 19:12:11 | D | - Calibrating model.layers.4.self_attn.k_proj.weight +24-11-19 19:12:11 | D | + w: sint8 +24-11-19 19:12:11 | D | + x: None +24-11-19 19:12:11 | D | + y: None +24-11-19 19:12:11 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:12:11 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:12:11 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:12:11 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:12:11 | D | - range ratio = [ 1.0000] +24-11-19 19:12:11 | D | sum error = [ 3.1204] +24-11-19 19:12:11 | D | best error = [ 3.1204] +24-11-19 19:12:24 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:12:24 | D | sum error = [ 2.7053, 3.0133, 2.9007, 2.7861, 2.8392] +24-11-19 19:12:24 | D | best error = [ 2.7053, 2.7053, 2.7053, 2.7053, 2.7053] +24-11-19 19:12:24 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:12:24 | D | sum error = [ 3.0098, 3.0288, 3.1419, 3.3919, 3.4416] +24-11-19 19:12:24 | D | best error = [ 2.7053, 2.7053, 2.7053, 2.7053, 2.7053] +24-11-19 19:12:24 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:12:24 | D | sum error = [ 3.6613, 3.9935, 4.3324, 4.4709, 5.1599] +24-11-19 19:12:24 | D | best error = [ 2.7053, 2.7053, 2.7053, 2.7053, 2.7053] +24-11-19 19:12:24 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:12:24 | D | sum error = [ 5.5236, 6.0200, 6.7723, 7.1389, 7.8929] +24-11-19 19:12:24 | D | best error = [ 2.7053, 2.7053, 2.7053, 2.7053, 2.7053] +24-11-19 19:12:24 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:12:24 | D | sum error = [ 8.6940, 9.3863, 10.5070, 11.5818, 12.3576] +24-11-19 19:12:24 | D | best error = [ 2.7053, 2.7053, 2.7053, 2.7053, 2.7053] +24-11-19 19:12:24 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:12:24 | D | sum error = [ 13.7946, 14.9311, 16.3630, 17.9169, 19.5665] +24-11-19 19:12:24 | D | best error = [ 2.7053, 2.7053, 2.7053, 2.7053, 2.7053] +24-11-19 19:12:24 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:12:24 | D | sum error = [ 21.3781, 22.8189, 25.4141, 27.7811, 29.8229] +24-11-19 19:12:24 | D | best error = [ 2.7053, 2.7053, 2.7053, 2.7053, 2.7053] +24-11-19 19:12:24 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:12:24 | D | sum error = [ 32.9482, 35.4109, 39.1848, 42.7895, 46.2932] +24-11-19 19:12:24 | D | best error = [ 2.7053, 2.7053, 2.7053, 2.7053, 2.7053] +24-11-19 19:12:24 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:12:24 | D | sum error = [ 49.8819, 54.4230, 59.2034, 64.6878, 70.9386] +24-11-19 19:12:24 | D | best error = [ 2.7053, 2.7053, 2.7053, 2.7053, 2.7053] +24-11-19 19:12:24 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:12:24 | D | sum error = [ 77.6824, 84.6958, 92.3684, 100.7592, 109.9728] +24-11-19 19:12:24 | D | best error = [ 2.7053, 2.7053, 2.7053, 2.7053, 2.7053] +24-11-19 19:12:24 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:12:24 | D | sum error = [ 119.3064, 129.9084, 140.4274, 153.0560, 165.5716] +24-11-19 19:12:24 | D | best error = [ 2.7053, 2.7053, 2.7053, 2.7053, 2.7053] +24-11-19 19:12:24 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:12:24 | D | sum error = [ 179.4096, 195.2553, 210.6185, 229.5530, 249.5868] +24-11-19 19:12:24 | D | best error = [ 2.7053, 2.7053, 2.7053, 2.7053, 2.7053] +24-11-19 19:12:24 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:12:24 | D | sum error = [ 267.5125, 290.3834, 315.3088, 343.0815, 372.9874] +24-11-19 19:12:24 | D | best error = [ 2.7053, 2.7053, 2.7053, 2.7053, 2.7053] +24-11-19 19:12:24 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:12:24 | D | sum error = [ 401.1590, 434.8569, 469.2495, 507.5208, 544.8426] +24-11-19 19:12:24 | D | best error = [ 2.7053, 2.7053, 2.7053, 2.7053, 2.7053] +24-11-19 19:12:24 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:12:24 | D | sum error = [ 590.1071, 636.0161, 686.6617, 737.6952, 789.8554] +24-11-19 19:12:24 | D | best error = [ 2.7053, 2.7053, 2.7053, 2.7053, 2.7053] +24-11-19 19:12:24 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:12:24 | D | sum error = [ 846.7394, 906.1880, 973.2306, 1035.9277, 1097.6359] +24-11-19 19:12:24 | D | best error = [ 2.7053, 2.7053, 2.7053, 2.7053, 2.7053] +24-11-19 19:12:24 | D | + error = [2.7053] +24-11-19 19:12:24 | D | - Calibrating model.layers.4.self_attn.v_proj.weight +24-11-19 19:12:24 | D | + w: sint8 +24-11-19 19:12:24 | D | + x: None +24-11-19 19:12:24 | D | + y: None +24-11-19 19:12:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:12:24 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:12:24 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:12:24 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:12:24 | D | - range ratio = [ 1.0000] +24-11-19 19:12:24 | D | sum error = [ 3.0384] +24-11-19 19:12:24 | D | best error = [ 3.0384] +24-11-19 19:12:24 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:12:24 | D | sum error = [ 3.0270, 3.0164, 3.0418, 3.0731, 3.1219] +24-11-19 19:12:24 | D | best error = [ 2.7709, 2.6786, 2.6301, 2.6047, 2.5902] +24-11-19 19:12:24 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:12:24 | D | sum error = [ 3.2047, 3.3073, 3.4541, 3.6162, 3.8042] +24-11-19 19:12:24 | D | best error = [ 2.5836, 2.5813, 2.5805, 2.5803, 2.5802] +24-11-19 19:12:24 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:12:24 | D | sum error = [ 4.0292, 4.2747, 4.5390, 4.8609, 5.2120] +24-11-19 19:12:24 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 19:12:24 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:12:24 | D | sum error = [ 5.5777, 5.9704, 6.4027, 6.8546, 7.3643] +24-11-19 19:12:24 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 19:12:24 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:12:24 | D | sum error = [ 7.8792, 8.4509, 9.0501, 9.6931, 10.3519] +24-11-19 19:12:24 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 19:12:24 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:12:24 | D | sum error = [ 11.0566, 11.8162, 12.5972, 13.4364, 14.3396] +24-11-19 19:12:24 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 19:12:24 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:12:24 | D | sum error = [ 15.2620, 16.2621, 17.2999, 18.4258, 19.5771] +24-11-19 19:12:24 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 19:12:24 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:12:24 | D | sum error = [ 20.8034, 22.1005, 23.4454, 24.8734, 26.3451] +24-11-19 19:12:24 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 19:12:24 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:12:24 | D | sum error = [ 27.9078, 29.5527, 31.2713, 33.0918, 34.9919] +24-11-19 19:12:24 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 19:12:24 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:12:24 | D | sum error = [ 36.9778, 39.0678, 41.2550, 43.5380, 45.9257] +24-11-19 19:12:24 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 19:12:24 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:12:24 | D | sum error = [ 48.4315, 51.0496, 53.7856, 56.6462, 59.6298] +24-11-19 19:12:24 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 19:12:24 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:12:24 | D | sum error = [ 62.7414, 66.0026, 69.3890, 72.9159, 76.5764] +24-11-19 19:12:24 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 19:12:24 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:12:24 | D | sum error = [ 80.3936, 84.3580, 88.4768, 92.7508, 97.1872] +24-11-19 19:12:24 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 19:12:24 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:12:24 | D | sum error = [ 101.7907, 106.5680, 111.5170, 116.6478, 121.9534] +24-11-19 19:12:24 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 19:12:24 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:12:24 | D | sum error = [ 127.4489, 133.1293, 139.0124, 145.0850, 151.3515] +24-11-19 19:12:24 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 19:12:24 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:12:24 | D | sum error = [ 157.8163, 164.4659, 171.3258, 178.3835, 185.6452] +24-11-19 19:12:24 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 19:12:24 | D | + error = [2.5802] +24-11-19 19:12:25 | D | - Calibrating model.layers.4.self_attn.o_proj.weight +24-11-19 19:12:25 | D | + w: sint8 +24-11-19 19:12:25 | D | + x: None +24-11-19 19:12:25 | D | + y: None +24-11-19 19:12:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:12:25 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:12:25 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:12:25 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:12:25 | D | - range ratio = [ 1.0000] +24-11-19 19:12:25 | D | sum error = [ 0.3585] +24-11-19 19:12:25 | D | best error = [ 0.3585] +24-11-19 19:12:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:12:25 | D | sum error = [ 0.3563, 0.3550, 0.3550, 0.3582, 0.3637] +24-11-19 19:12:25 | D | best error = [ 0.3405, 0.3319, 0.3269, 0.3237, 0.3218] +24-11-19 19:12:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:12:25 | D | sum error = [ 0.3715, 0.3826, 0.3958, 0.4126, 0.4323] +24-11-19 19:12:25 | D | best error = [ 0.3205, 0.3198, 0.3193, 0.3189, 0.3186] +24-11-19 19:12:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:12:25 | D | sum error = [ 0.4551, 0.4804, 0.5101, 0.5424, 0.5793] +24-11-19 19:12:25 | D | best error = [ 0.3185, 0.3185, 0.3184, 0.3184, 0.3184] +24-11-19 19:12:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:12:25 | D | sum error = [ 0.6168, 0.6602, 0.7054, 0.7551, 0.8084] +24-11-19 19:12:25 | D | best error = [ 0.3184, 0.3184, 0.3183, 0.3183, 0.3183] +24-11-19 19:12:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:12:25 | D | sum error = [ 0.8653, 0.9271, 0.9910, 1.0615, 1.1343] +24-11-19 19:12:25 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 19:12:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:12:25 | D | sum error = [ 1.2126, 1.2961, 1.3831, 1.4776, 1.5763] +24-11-19 19:12:25 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 19:12:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:12:25 | D | sum error = [ 1.6822, 1.7936, 1.9113, 2.0366, 2.1675] +24-11-19 19:12:25 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 19:12:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:12:25 | D | sum error = [ 2.3079, 2.4553, 2.6101, 2.7735, 2.9472] +24-11-19 19:12:25 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 19:12:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:12:25 | D | sum error = [ 3.1291, 3.3211, 3.5231, 3.7359, 3.9615] +24-11-19 19:12:25 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 19:12:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:12:25 | D | sum error = [ 4.1980, 4.4471, 4.7102, 4.9856, 5.2767] +24-11-19 19:12:25 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 19:12:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:12:25 | D | sum error = [ 5.5809, 5.9014, 6.2392, 6.5924, 6.9641] +24-11-19 19:12:25 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 19:12:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:12:25 | D | sum error = [ 7.3531, 7.7604, 8.1870, 8.6341, 9.1011] +24-11-19 19:12:25 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 19:12:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:12:25 | D | sum error = [ 9.5910, 10.1026, 10.6376, 11.1960, 11.7795] +24-11-19 19:12:25 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 19:12:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:12:25 | D | sum error = [ 12.3876, 13.0226, 13.6837, 14.3717, 15.0877] +24-11-19 19:12:25 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 19:12:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:12:25 | D | sum error = [ 15.8317, 16.6033, 17.4033, 18.2331, 19.0928] +24-11-19 19:12:25 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 19:12:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:12:25 | D | sum error = [ 19.9825, 20.9033, 21.8550, 22.8382, 23.8535] +24-11-19 19:12:25 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 19:12:25 | D | + error = [0.3183] +24-11-19 19:12:25 | D | - Calibrating model.layers.4.mlp.up_proj.weight +24-11-19 19:12:25 | D | + w: sint8 +24-11-19 19:12:25 | D | + x: None +24-11-19 19:12:25 | D | + y: None +24-11-19 19:12:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:12:25 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:12:25 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:12:25 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:12:25 | D | - range ratio = [ 1.0000] +24-11-19 19:12:25 | D | sum error = [ 4.3383] +24-11-19 19:12:25 | D | best error = [ 4.3383] +24-11-19 19:12:26 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:12:26 | D | sum error = [ 4.3001, 4.2760, 4.3106, 4.3732, 4.4277] +24-11-19 19:12:26 | D | best error = [ 3.8851, 3.7306, 3.6572, 3.6171, 3.5952] +24-11-19 19:12:26 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:12:26 | D | sum error = [ 4.5706, 4.7020, 4.8952, 5.1225, 5.4098] +24-11-19 19:12:26 | D | best error = [ 3.5857, 3.5816, 3.5799, 3.5793, 3.5791] +24-11-19 19:12:26 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:12:26 | D | sum error = [ 5.7090, 6.0500, 6.4233, 6.8670, 7.3467] +24-11-19 19:12:26 | D | best error = [ 3.5791, 3.5791, 3.5791, 3.5791, 3.5791] +24-11-19 19:12:26 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:12:26 | D | sum error = [ 7.8606, 8.4178, 9.0019, 9.6471, 10.3321] +24-11-19 19:12:26 | D | best error = [ 3.5791, 3.5791, 3.5791, 3.5791, 3.5791] +24-11-19 19:12:26 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:12:26 | D | sum error = [ 11.0812, 11.8573, 12.6783, 13.5417, 14.4911] +24-11-19 19:12:26 | D | best error = [ 3.5791, 3.5791, 3.5791, 3.5791, 3.5791] +24-11-19 19:12:26 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:12:26 | D | sum error = [ 15.4649, 16.5246, 17.6271, 18.7982, 20.0249] +24-11-19 19:12:26 | D | best error = [ 3.5791, 3.5791, 3.5791, 3.5791, 3.5791] +24-11-19 19:12:26 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:12:26 | D | sum error = [ 21.3293, 22.6964, 24.1360, 25.6623, 27.2494] +24-11-19 19:12:26 | D | best error = [ 3.5791, 3.5791, 3.5791, 3.5791, 3.5791] +24-11-19 19:12:26 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:12:26 | D | sum error = [ 28.9358, 30.7033, 32.5699, 34.5204, 36.5490] +24-11-19 19:12:26 | D | best error = [ 3.5791, 3.5791, 3.5791, 3.5791, 3.5791] +24-11-19 19:12:26 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:12:26 | D | sum error = [ 38.7021, 40.9372, 43.2843, 45.7431, 48.3014] +24-11-19 19:12:26 | D | best error = [ 3.5791, 3.5791, 3.5791, 3.5791, 3.5791] +24-11-19 19:12:26 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:12:26 | D | sum error = [ 50.9634, 53.7593, 56.6605, 59.6958, 62.8777] +24-11-19 19:12:26 | D | best error = [ 3.5791, 3.5791, 3.5791, 3.5791, 3.5791] +24-11-19 19:12:26 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:12:26 | D | sum error = [ 66.1851, 69.6177, 73.2069, 76.9274, 80.7890] +24-11-19 19:12:26 | D | best error = [ 3.5791, 3.5791, 3.5791, 3.5791, 3.5791] +24-11-19 19:12:26 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:12:26 | D | sum error = [ 84.8014, 88.9536, 93.2564, 97.7343, 102.3538] +24-11-19 19:12:26 | D | best error = [ 3.5791, 3.5791, 3.5791, 3.5791, 3.5791] +24-11-19 19:12:26 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:12:26 | D | sum error = [ 107.1414, 112.0950, 117.2189, 122.5137, 127.9859] +24-11-19 19:12:26 | D | best error = [ 3.5791, 3.5791, 3.5791, 3.5791, 3.5791] +24-11-19 19:12:26 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:12:26 | D | sum error = [ 133.6376, 139.4814, 145.5194, 151.7352, 158.1535] +24-11-19 19:12:26 | D | best error = [ 3.5791, 3.5791, 3.5791, 3.5791, 3.5791] +24-11-19 19:12:26 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:12:26 | D | sum error = [ 164.7758, 171.5914, 178.6151, 185.8407, 193.2762] +24-11-19 19:12:26 | D | best error = [ 3.5791, 3.5791, 3.5791, 3.5791, 3.5791] +24-11-19 19:12:26 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:12:26 | D | sum error = [ 200.9255, 208.7860, 216.8716, 225.1819, 233.7189] +24-11-19 19:12:26 | D | best error = [ 3.5791, 3.5791, 3.5791, 3.5791, 3.5791] +24-11-19 19:12:26 | D | + error = [3.5791] +24-11-19 19:12:26 | D | - Calibrating model.layers.4.mlp.gate_proj.weight +24-11-19 19:12:26 | D | + w: sint8 +24-11-19 19:12:26 | D | + x: None +24-11-19 19:12:26 | D | + y: None +24-11-19 19:12:26 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:12:26 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:12:27 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:12:27 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:12:27 | D | - range ratio = [ 1.0000] +24-11-19 19:12:27 | D | sum error = [ 4.7997] +24-11-19 19:12:27 | D | best error = [ 4.7997] +24-11-19 19:12:28 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:12:28 | D | sum error = [ 4.7718, 4.7539, 4.7674, 4.8342, 4.9220] +24-11-19 19:12:28 | D | best error = [ 4.2994, 4.1343, 4.0496, 4.0080, 3.9855] +24-11-19 19:12:28 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:12:28 | D | sum error = [ 5.0565, 5.2182, 5.4480, 5.6939, 6.0149] +24-11-19 19:12:28 | D | best error = [ 3.9736, 3.9684, 3.9666, 3.9661, 3.9659] +24-11-19 19:12:28 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:12:28 | D | sum error = [ 6.3448, 6.7273, 7.1695, 7.6448, 8.1802] +24-11-19 19:12:28 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 19:12:28 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:12:28 | D | sum error = [ 8.7679, 9.3779, 10.0538, 10.7922, 11.5455] +24-11-19 19:12:28 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 19:12:28 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:12:28 | D | sum error = [ 12.4017, 13.2769, 14.2058, 15.2078, 16.2785] +24-11-19 19:12:28 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 19:12:28 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:12:28 | D | sum error = [ 17.3866, 18.5976, 19.8612, 21.1873, 22.6160] +24-11-19 19:12:28 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 19:12:28 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:12:28 | D | sum error = [ 24.1066, 25.6883, 27.3473, 29.1064, 30.9626] +24-11-19 19:12:28 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 19:12:28 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:12:28 | D | sum error = [ 32.9196, 34.9647, 37.1621, 39.4360, 41.8597] +24-11-19 19:12:28 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 19:12:28 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:12:28 | D | sum error = [ 44.3980, 47.0783, 49.8890, 52.8190, 55.9239] +24-11-19 19:12:28 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 19:12:28 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:12:28 | D | sum error = [ 59.1761, 62.5969, 66.1864, 69.9436, 73.8993] +24-11-19 19:12:28 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 19:12:28 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:12:28 | D | sum error = [ 78.0220, 82.3718, 86.9186, 91.6902, 96.6692] +24-11-19 19:12:28 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 19:12:28 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:12:28 | D | sum error = [ 101.8739, 107.3323, 113.0444, 118.9921, 125.1947] +24-11-19 19:12:28 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 19:12:28 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:12:28 | D | sum error = [ 131.6473, 138.4162, 145.4536, 152.7809, 160.4143] +24-11-19 19:12:28 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 19:12:28 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:12:28 | D | sum error = [ 168.3764, 176.6380, 185.2425, 194.1603, 203.4250] +24-11-19 19:12:28 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 19:12:28 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:12:28 | D | sum error = [ 213.0495, 223.0284, 233.3550, 244.0284, 255.0495] +24-11-19 19:12:28 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 19:12:28 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:12:28 | D | sum error = [ 266.4275, 278.1797, 290.2871, 302.7753, 315.6256] +24-11-19 19:12:28 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 19:12:28 | D | + error = [3.9659] +24-11-19 19:12:28 | D | - Calibrating model.layers.4.mlp.down_proj.weight +24-11-19 19:12:28 | D | + w: sint8 +24-11-19 19:12:28 | D | + x: None +24-11-19 19:12:28 | D | + y: None +24-11-19 19:12:28 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:12:28 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:12:28 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:12:28 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:12:28 | D | - range ratio = [ 1.0000] +24-11-19 19:12:28 | D | sum error = [ 0.7610] +24-11-19 19:12:28 | D | best error = [ 0.7610] +24-11-19 19:12:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:12:29 | D | sum error = [ 0.7554, 0.7529, 0.7528, 0.7559, 0.7587] +24-11-19 19:12:29 | D | best error = [ 0.6896, 0.6605, 0.6453, 0.6345, 0.6267] +24-11-19 19:12:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:12:29 | D | sum error = [ 0.7759, 0.7886, 0.8137, 0.8392, 0.8715] +24-11-19 19:12:29 | D | best error = [ 0.6213, 0.6177, 0.6149, 0.6128, 0.6112] +24-11-19 19:12:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:12:29 | D | sum error = [ 0.9092, 0.9504, 0.9979, 1.0510, 1.1083] +24-11-19 19:12:29 | D | best error = [ 0.6102, 0.6096, 0.6093, 0.6090, 0.6089] +24-11-19 19:12:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:12:29 | D | sum error = [ 1.1738, 1.2474, 1.3172, 1.3990, 1.4895] +24-11-19 19:12:29 | D | best error = [ 0.6088, 0.6087, 0.6087, 0.6087, 0.6087] +24-11-19 19:12:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:12:29 | D | sum error = [ 1.5875, 1.6907, 1.8037, 1.9219, 2.0559] +24-11-19 19:12:29 | D | best error = [ 0.6087, 0.6087, 0.6087, 0.6087, 0.6087] +24-11-19 19:12:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:12:29 | D | sum error = [ 2.1920, 2.3428, 2.5003, 2.6669, 2.8412] +24-11-19 19:12:29 | D | best error = [ 0.6087, 0.6087, 0.6087, 0.6087, 0.6087] +24-11-19 19:12:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:12:29 | D | sum error = [ 3.0299, 3.2308, 3.4409, 3.6655, 3.9078] +24-11-19 19:12:29 | D | best error = [ 0.6087, 0.6087, 0.6087, 0.6087, 0.6087] +24-11-19 19:12:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:12:29 | D | sum error = [ 4.1624, 4.4298, 4.7138, 5.0108, 5.3308] +24-11-19 19:12:29 | D | best error = [ 0.6087, 0.6087, 0.6087, 0.6087, 0.6087] +24-11-19 19:12:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:12:29 | D | sum error = [ 5.6655, 6.0201, 6.3919, 6.7864, 7.2007] +24-11-19 19:12:29 | D | best error = [ 0.6087, 0.6087, 0.6087, 0.6087, 0.6087] +24-11-19 19:12:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:12:29 | D | sum error = [ 7.6466, 8.1083, 8.5964, 9.1107, 9.6514] +24-11-19 19:12:29 | D | best error = [ 0.6087, 0.6087, 0.6087, 0.6087, 0.6087] +24-11-19 19:12:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:12:29 | D | sum error = [ 10.2230, 10.8211, 11.4492, 12.1152, 12.8118] +24-11-19 19:12:29 | D | best error = [ 0.6087, 0.6087, 0.6087, 0.6087, 0.6087] +24-11-19 19:12:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:12:29 | D | sum error = [ 13.5442, 14.3145, 15.1209, 15.9647, 16.8544] +24-11-19 19:12:29 | D | best error = [ 0.6087, 0.6087, 0.6087, 0.6087, 0.6087] +24-11-19 19:12:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:12:29 | D | sum error = [ 17.7856, 18.7609, 19.7844, 20.8579, 21.9835] +24-11-19 19:12:29 | D | best error = [ 0.6087, 0.6087, 0.6087, 0.6087, 0.6087] +24-11-19 19:12:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:12:29 | D | sum error = [ 23.1593, 24.3873, 25.6717, 27.0125, 28.4026] +24-11-19 19:12:29 | D | best error = [ 0.6087, 0.6087, 0.6087, 0.6087, 0.6087] +24-11-19 19:12:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:12:29 | D | sum error = [ 29.8519, 31.3579, 32.9245, 34.5538, 36.2423] +24-11-19 19:12:29 | D | best error = [ 0.6087, 0.6087, 0.6087, 0.6087, 0.6087] +24-11-19 19:12:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:12:29 | D | sum error = [ 37.9927, 39.8060, 41.6846, 43.6292, 45.6398] +24-11-19 19:12:29 | D | best error = [ 0.6087, 0.6087, 0.6087, 0.6087, 0.6087] +24-11-19 19:12:29 | D | + error = [0.6087] +24-11-19 19:12:29 | D | - Quantizing model.layers.4.self_attn.q_proj.weight +24-11-19 19:12:30 | D | - Quantizing model.layers.4.self_attn.k_proj.weight +24-11-19 19:12:31 | D | - Quantizing model.layers.4.self_attn.v_proj.weight +24-11-19 19:12:32 | D | - Quantizing model.layers.4.self_attn.o_proj.weight +24-11-19 19:12:33 | D | - Quantizing model.layers.4.mlp.up_proj.weight +24-11-19 19:12:34 | D | - Quantizing model.layers.4.mlp.gate_proj.weight +24-11-19 19:12:35 | D | - Quantizing model.layers.4.mlp.down_proj.weight +24-11-19 19:12:43 | D | - Quantizing layer model.layers.5 +24-11-19 19:12:43 | D | - Calibrating model.layers.5.self_attn.q_proj.weight +24-11-19 19:12:43 | D | + w: sint8 +24-11-19 19:12:43 | D | + x: None +24-11-19 19:12:43 | D | + y: None +24-11-19 19:12:43 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:12:43 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:12:43 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:12:44 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:12:44 | D | - range ratio = [ 1.0000] +24-11-19 19:12:44 | D | sum error = [ 2.9655] +24-11-19 19:12:44 | D | best error = [ 2.9655] +24-11-19 19:12:56 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:12:56 | D | sum error = [ 2.9329, 2.8743, 2.8866, 2.9650, 2.9503] +24-11-19 19:12:56 | D | best error = [ 2.9329, 2.8743, 2.8743, 2.8743, 2.8743] +24-11-19 19:12:56 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:12:56 | D | sum error = [ 3.2066, 3.2995, 3.5442, 3.5854, 3.9695] +24-11-19 19:12:56 | D | best error = [ 2.8743, 2.8743, 2.8743, 2.8743, 2.8743] +24-11-19 19:12:56 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:12:56 | D | sum error = [ 4.2771, 4.5821, 4.9704, 5.3762, 5.9441] +24-11-19 19:12:56 | D | best error = [ 2.8743, 2.8743, 2.8743, 2.8743, 2.8743] +24-11-19 19:12:56 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:12:56 | D | sum error = [ 6.6297, 7.2768, 7.6908, 8.6884, 9.5875] +24-11-19 19:12:56 | D | best error = [ 2.8743, 2.8743, 2.8743, 2.8743, 2.8743] +24-11-19 19:12:56 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:12:56 | D | sum error = [ 10.4198, 11.3614, 12.5685, 13.9179, 15.0399] +24-11-19 19:12:56 | D | best error = [ 2.8743, 2.8743, 2.8743, 2.8743, 2.8743] +24-11-19 19:12:56 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:12:56 | D | sum error = [ 16.8511, 18.1043, 19.4849, 21.4426, 23.2746] +24-11-19 19:12:56 | D | best error = [ 2.8743, 2.8743, 2.8743, 2.8743, 2.8743] +24-11-19 19:12:56 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:12:56 | D | sum error = [ 25.6593, 27.7755, 30.3506, 33.0040, 36.0656] +24-11-19 19:12:56 | D | best error = [ 2.8743, 2.8743, 2.8743, 2.8743, 2.8743] +24-11-19 19:12:56 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:12:56 | D | sum error = [ 39.1326, 42.5534, 46.2594, 50.1247, 54.5414] +24-11-19 19:12:56 | D | best error = [ 2.8743, 2.8743, 2.8743, 2.8743, 2.8743] +24-11-19 19:12:56 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:12:56 | D | sum error = [ 59.1846, 64.2342, 69.7848, 75.6752, 81.9216] +24-11-19 19:12:56 | D | best error = [ 2.8743, 2.8743, 2.8743, 2.8743, 2.8743] +24-11-19 19:12:56 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:12:56 | D | sum error = [ 88.6630, 96.2860, 104.1336, 112.9359, 122.0129] +24-11-19 19:12:56 | D | best error = [ 2.8743, 2.8743, 2.8743, 2.8743, 2.8743] +24-11-19 19:12:56 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:12:56 | D | sum error = [ 131.9401, 142.8429, 154.5518, 166.9974, 180.6847] +24-11-19 19:12:56 | D | best error = [ 2.8743, 2.8743, 2.8743, 2.8743, 2.8743] +24-11-19 19:12:56 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:12:56 | D | sum error = [ 195.4280, 211.4738, 228.6581, 247.1379, 266.7798] +24-11-19 19:12:56 | D | best error = [ 2.8743, 2.8743, 2.8743, 2.8743, 2.8743] +24-11-19 19:12:56 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:12:56 | D | sum error = [ 288.0944, 310.7121, 335.1333, 361.5875, 389.9896] +24-11-19 19:12:56 | D | best error = [ 2.8743, 2.8743, 2.8743, 2.8743, 2.8743] +24-11-19 19:12:56 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:12:56 | D | sum error = [ 420.3688, 453.4552, 488.7777, 526.8010, 567.9191] +24-11-19 19:12:56 | D | best error = [ 2.8743, 2.8743, 2.8743, 2.8743, 2.8743] +24-11-19 19:12:56 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:12:56 | D | sum error = [ 612.0329, 659.4565, 710.1938, 764.7393, 822.6062] +24-11-19 19:12:56 | D | best error = [ 2.8743, 2.8743, 2.8743, 2.8743, 2.8743] +24-11-19 19:12:56 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:12:56 | D | sum error = [ 883.9982, 948.9135, 1017.1701, 1087.8751, 1161.1746] +24-11-19 19:12:56 | D | best error = [ 2.8743, 2.8743, 2.8743, 2.8743, 2.8743] +24-11-19 19:12:56 | D | + error = [2.8743] +24-11-19 19:12:56 | D | - Calibrating model.layers.5.self_attn.k_proj.weight +24-11-19 19:12:56 | D | + w: sint8 +24-11-19 19:12:56 | D | + x: None +24-11-19 19:12:56 | D | + y: None +24-11-19 19:12:56 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:12:56 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:12:56 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:12:57 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:12:57 | D | - range ratio = [ 1.0000] +24-11-19 19:12:57 | D | sum error = [ 3.1831] +24-11-19 19:12:57 | D | best error = [ 3.1831] +24-11-19 19:13:09 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:13:09 | D | sum error = [ 3.2702, 3.3368, 3.3009, 3.2426, 3.0821] +24-11-19 19:13:09 | D | best error = [ 3.1831, 3.1831, 3.1831, 3.1831, 3.0821] +24-11-19 19:13:09 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:13:09 | D | sum error = [ 3.3581, 3.3319, 3.7461, 3.8123, 4.2407] +24-11-19 19:13:09 | D | best error = [ 3.0821, 3.0821, 3.0821, 3.0821, 3.0821] +24-11-19 19:13:09 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:13:09 | D | sum error = [ 4.1606, 4.8030, 4.8727, 5.4263, 5.5593] +24-11-19 19:13:09 | D | best error = [ 3.0821, 3.0821, 3.0821, 3.0821, 3.0821] +24-11-19 19:13:09 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:13:09 | D | sum error = [ 6.3842, 6.9905, 7.4584, 7.9243, 8.7907] +24-11-19 19:13:09 | D | best error = [ 3.0821, 3.0821, 3.0821, 3.0821, 3.0821] +24-11-19 19:13:09 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:13:09 | D | sum error = [ 9.3730, 10.0051, 11.4372, 12.1632, 13.2595] +24-11-19 19:13:09 | D | best error = [ 3.0821, 3.0821, 3.0821, 3.0821, 3.0821] +24-11-19 19:13:09 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:13:09 | D | sum error = [ 14.1209, 15.1707, 17.0214, 18.3788, 19.9952] +24-11-19 19:13:09 | D | best error = [ 3.0821, 3.0821, 3.0821, 3.0821, 3.0821] +24-11-19 19:13:09 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:13:09 | D | sum error = [ 21.6647, 23.6242, 25.7503, 28.0886, 30.4976] +24-11-19 19:13:09 | D | best error = [ 3.0821, 3.0821, 3.0821, 3.0821, 3.0821] +24-11-19 19:13:09 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:13:09 | D | sum error = [ 33.3216, 36.9209, 39.5982, 44.0496, 47.7418] +24-11-19 19:13:09 | D | best error = [ 3.0821, 3.0821, 3.0821, 3.0821, 3.0821] +24-11-19 19:13:09 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:13:09 | D | sum error = [ 51.4359, 55.6959, 60.3699, 66.5141, 71.9032] +24-11-19 19:13:09 | D | best error = [ 3.0821, 3.0821, 3.0821, 3.0821, 3.0821] +24-11-19 19:13:09 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:13:09 | D | sum error = [ 78.7794, 84.6173, 92.8857, 99.6977, 108.2635] +24-11-19 19:13:09 | D | best error = [ 3.0821, 3.0821, 3.0821, 3.0821, 3.0821] +24-11-19 19:13:09 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:13:09 | D | sum error = [ 118.0754, 127.2699, 139.0165, 149.8720, 163.3518] +24-11-19 19:13:09 | D | best error = [ 3.0821, 3.0821, 3.0821, 3.0821, 3.0821] +24-11-19 19:13:09 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:13:09 | D | sum error = [ 175.8991, 192.6615, 206.3537, 226.5235, 244.3020] +24-11-19 19:13:09 | D | best error = [ 3.0821, 3.0821, 3.0821, 3.0821, 3.0821] +24-11-19 19:13:09 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:13:09 | D | sum error = [ 263.1867, 286.2285, 308.2771, 335.7621, 361.2872] +24-11-19 19:13:09 | D | best error = [ 3.0821, 3.0821, 3.0821, 3.0821, 3.0821] +24-11-19 19:13:09 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:13:09 | D | sum error = [ 394.2322, 425.4286, 460.7903, 497.0872, 535.1453] +24-11-19 19:13:09 | D | best error = [ 3.0821, 3.0821, 3.0821, 3.0821, 3.0821] +24-11-19 19:13:09 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:13:09 | D | sum error = [ 581.2697, 626.7944, 676.7247, 732.5025, 791.6091] +24-11-19 19:13:09 | D | best error = [ 3.0821, 3.0821, 3.0821, 3.0821, 3.0821] +24-11-19 19:13:09 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:13:09 | D | sum error = [ 850.1286, 917.2842, 982.0931, 1055.9034, 1128.7963] +24-11-19 19:13:09 | D | best error = [ 3.0821, 3.0821, 3.0821, 3.0821, 3.0821] +24-11-19 19:13:09 | D | + error = [3.0821] +24-11-19 19:13:09 | D | - Calibrating model.layers.5.self_attn.v_proj.weight +24-11-19 19:13:09 | D | + w: sint8 +24-11-19 19:13:09 | D | + x: None +24-11-19 19:13:09 | D | + y: None +24-11-19 19:13:09 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:13:09 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:13:09 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:13:09 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:13:09 | D | - range ratio = [ 1.0000] +24-11-19 19:13:09 | D | sum error = [ 3.2208] +24-11-19 19:13:09 | D | best error = [ 3.2208] +24-11-19 19:13:10 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:13:10 | D | sum error = [ 3.1969, 3.1903, 3.1892, 3.2317, 3.2917] +24-11-19 19:13:10 | D | best error = [ 2.9506, 2.8579, 2.8138, 2.7876, 2.7750] +24-11-19 19:13:10 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:13:10 | D | sum error = [ 3.3909, 3.4902, 3.6575, 3.8258, 4.0204] +24-11-19 19:13:10 | D | best error = [ 2.7692, 2.7671, 2.7665, 2.7663, 2.7662] +24-11-19 19:13:10 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:13:10 | D | sum error = [ 4.2643, 4.5132, 4.8046, 5.1438, 5.4983] +24-11-19 19:13:10 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 19:13:10 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:13:10 | D | sum error = [ 5.8857, 6.2883, 6.7550, 7.2587, 7.7489] +24-11-19 19:13:10 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 19:13:10 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:13:10 | D | sum error = [ 8.3176, 8.9075, 9.5343, 10.2068, 10.9130] +24-11-19 19:13:10 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 19:13:10 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:13:10 | D | sum error = [ 11.6733, 12.4658, 13.3039, 14.1977, 15.1291] +24-11-19 19:13:10 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 19:13:10 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:13:10 | D | sum error = [ 16.1117, 17.1531, 18.2548, 19.4176, 20.6279] +24-11-19 19:13:10 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 19:13:10 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:13:10 | D | sum error = [ 21.9204, 23.2820, 24.6948, 26.1918, 27.7648] +24-11-19 19:13:10 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 19:13:10 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:13:10 | D | sum error = [ 29.3957, 31.1204, 32.9500, 34.8587, 36.8561] +24-11-19 19:13:10 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 19:13:10 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:13:10 | D | sum error = [ 38.9582, 41.1487, 43.4336, 45.8379, 48.3481] +24-11-19 19:13:10 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 19:13:10 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:13:10 | D | sum error = [ 50.9693, 53.7004, 56.5459, 59.5428, 62.6485] +24-11-19 19:13:10 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 19:13:10 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:13:10 | D | sum error = [ 65.8934, 69.2718, 72.8064, 76.4727, 80.2879] +24-11-19 19:13:10 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 19:13:10 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:13:10 | D | sum error = [ 84.2450, 88.3653, 92.6561, 97.1059, 101.7286] +24-11-19 19:13:10 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 19:13:10 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:13:10 | D | sum error = [ 106.5230, 111.5017, 116.6572, 121.9962, 127.5332] +24-11-19 19:13:10 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 19:13:10 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:13:10 | D | sum error = [ 133.2521, 139.1577, 145.2603, 151.5502, 158.0380] +24-11-19 19:13:10 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 19:13:10 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:13:10 | D | sum error = [ 164.7411, 171.6522, 178.7700, 186.0985, 193.6482] +24-11-19 19:13:10 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 19:13:10 | D | + error = [2.7662] +24-11-19 19:13:10 | D | - Calibrating model.layers.5.self_attn.o_proj.weight +24-11-19 19:13:10 | D | + w: sint8 +24-11-19 19:13:10 | D | + x: None +24-11-19 19:13:10 | D | + y: None +24-11-19 19:13:10 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:13:10 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:13:10 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:13:10 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:13:10 | D | - range ratio = [ 1.0000] +24-11-19 19:13:10 | D | sum error = [ 0.5578] +24-11-19 19:13:10 | D | best error = [ 0.5578] +24-11-19 19:13:10 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:13:10 | D | sum error = [ 0.5512, 0.5489, 0.5468, 0.5503, 0.5523] +24-11-19 19:13:10 | D | best error = [ 0.5290, 0.5152, 0.5064, 0.5009, 0.4969] +24-11-19 19:13:10 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:13:10 | D | sum error = [ 0.5603, 0.5684, 0.5816, 0.5974, 0.6193] +24-11-19 19:13:10 | D | best error = [ 0.4942, 0.4922, 0.4909, 0.4899, 0.4893] +24-11-19 19:13:10 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:13:10 | D | sum error = [ 0.6422, 0.6693, 0.7014, 0.7367, 0.7780] +24-11-19 19:13:10 | D | best error = [ 0.4890, 0.4888, 0.4887, 0.4886, 0.4885] +24-11-19 19:13:10 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:13:10 | D | sum error = [ 0.8234, 0.8722, 0.9256, 0.9846, 1.0471] +24-11-19 19:13:10 | D | best error = [ 0.4884, 0.4884, 0.4883, 0.4883, 0.4883] +24-11-19 19:13:10 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:13:10 | D | sum error = [ 1.1165, 1.1897, 1.2678, 1.3514, 1.4425] +24-11-19 19:13:10 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 19:13:10 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:13:10 | D | sum error = [ 1.5388, 1.6375, 1.7474, 1.8600, 1.9822] +24-11-19 19:13:10 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 19:13:10 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:13:10 | D | sum error = [ 2.1104, 2.2476, 2.3916, 2.5425, 2.7040] +24-11-19 19:13:10 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 19:13:10 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:13:10 | D | sum error = [ 2.8734, 3.0515, 3.2396, 3.4380, 3.6479] +24-11-19 19:13:10 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 19:13:10 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:13:10 | D | sum error = [ 3.8668, 4.0980, 4.3402, 4.5956, 4.8623] +24-11-19 19:13:10 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 19:13:10 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:13:10 | D | sum error = [ 5.1446, 5.4389, 5.7475, 6.0718, 6.4130] +24-11-19 19:13:10 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 19:13:10 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:13:10 | D | sum error = [ 6.7694, 7.1430, 7.5331, 7.9416, 8.3700] +24-11-19 19:13:10 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 19:13:10 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:13:10 | D | sum error = [ 8.8171, 9.2839, 9.7733, 10.2832, 10.8156] +24-11-19 19:13:10 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 19:13:10 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:13:10 | D | sum error = [ 11.3714, 11.9507, 12.5548, 13.1840, 13.8401] +24-11-19 19:13:10 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 19:13:10 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:13:10 | D | sum error = [ 14.5230, 15.2335, 15.9732, 16.7399, 17.5391] +24-11-19 19:13:10 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 19:13:10 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:13:10 | D | sum error = [ 18.3693, 19.2329, 20.1324, 21.0656, 22.0341] +24-11-19 19:13:10 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 19:13:10 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:13:10 | D | sum error = [ 23.0417, 24.0882, 25.1750, 26.3052, 27.4791] +24-11-19 19:13:10 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 19:13:10 | D | + error = [0.4883] +24-11-19 19:13:10 | D | - Calibrating model.layers.5.mlp.up_proj.weight +24-11-19 19:13:10 | D | + w: sint8 +24-11-19 19:13:10 | D | + x: None +24-11-19 19:13:10 | D | + y: None +24-11-19 19:13:10 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:13:10 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:13:10 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:13:11 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:13:11 | D | - range ratio = [ 1.0000] +24-11-19 19:13:11 | D | sum error = [ 4.5865] +24-11-19 19:13:11 | D | best error = [ 4.5865] +24-11-19 19:13:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:13:12 | D | sum error = [ 4.5516, 4.5467, 4.5680, 4.6272, 4.7099] +24-11-19 19:13:12 | D | best error = [ 4.2260, 4.0968, 4.0323, 3.9954, 3.9758] +24-11-19 19:13:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:13:12 | D | sum error = [ 4.8310, 5.0019, 5.1826, 5.4276, 5.7134] +24-11-19 19:13:12 | D | best error = [ 3.9665, 3.9628, 3.9613, 3.9608, 3.9607] +24-11-19 19:13:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:13:12 | D | sum error = [ 6.0547, 6.4218, 6.8322, 7.2942, 7.7937] +24-11-19 19:13:12 | D | best error = [ 3.9607, 3.9607, 3.9607, 3.9607, 3.9607] +24-11-19 19:13:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:13:12 | D | sum error = [ 8.3415, 8.9360, 9.5831, 10.2775, 11.0013] +24-11-19 19:13:12 | D | best error = [ 3.9607, 3.9607, 3.9607, 3.9607, 3.9607] +24-11-19 19:13:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:13:12 | D | sum error = [ 11.7901, 12.6286, 13.5189, 14.4613, 15.4734] +24-11-19 19:13:12 | D | best error = [ 3.9607, 3.9607, 3.9607, 3.9607, 3.9607] +24-11-19 19:13:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:13:12 | D | sum error = [ 16.5216, 17.6451, 18.8331, 20.0863, 21.4126] +24-11-19 19:13:12 | D | best error = [ 3.9607, 3.9607, 3.9607, 3.9607, 3.9607] +24-11-19 19:13:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:13:12 | D | sum error = [ 22.8186, 24.2783, 25.8362, 27.4702, 29.1930] +24-11-19 19:13:12 | D | best error = [ 3.9607, 3.9607, 3.9607, 3.9607, 3.9607] +24-11-19 19:13:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:13:12 | D | sum error = [ 30.9872, 32.8858, 34.8654, 36.9582, 39.1431] +24-11-19 19:13:12 | D | best error = [ 3.9607, 3.9607, 3.9607, 3.9607, 3.9607] +24-11-19 19:13:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:13:12 | D | sum error = [ 41.4343, 43.8395, 46.3714, 48.9993, 51.7678] +24-11-19 19:13:12 | D | best error = [ 3.9607, 3.9607, 3.9607, 3.9607, 3.9607] +24-11-19 19:13:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:13:12 | D | sum error = [ 54.6516, 57.6798, 60.8211, 64.1213, 67.5577] +24-11-19 19:13:12 | D | best error = [ 3.9607, 3.9607, 3.9607, 3.9607, 3.9607] +24-11-19 19:13:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:13:12 | D | sum error = [ 71.1423, 74.8788, 78.7811, 82.8398, 87.0635] +24-11-19 19:13:12 | D | best error = [ 3.9607, 3.9607, 3.9607, 3.9607, 3.9607] +24-11-19 19:13:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:13:12 | D | sum error = [ 91.4710, 96.0313, 100.7915, 105.7353, 110.8506] +24-11-19 19:13:12 | D | best error = [ 3.9607, 3.9607, 3.9607, 3.9607, 3.9607] +24-11-19 19:13:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:13:12 | D | sum error = [ 116.1699, 121.6834, 127.4149, 133.3491, 139.5000] +24-11-19 19:13:12 | D | best error = [ 3.9607, 3.9607, 3.9607, 3.9607, 3.9607] +24-11-19 19:13:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:13:12 | D | sum error = [ 145.8594, 152.4436, 159.2340, 166.2585, 173.5151] +24-11-19 19:13:12 | D | best error = [ 3.9607, 3.9607, 3.9607, 3.9607, 3.9607] +24-11-19 19:13:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:13:12 | D | sum error = [ 181.0014, 188.7152, 196.6623, 204.8477, 213.2877] +24-11-19 19:13:12 | D | best error = [ 3.9607, 3.9607, 3.9607, 3.9607, 3.9607] +24-11-19 19:13:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:13:12 | D | sum error = [ 221.9832, 230.9308, 240.1221, 249.5785, 259.2927] +24-11-19 19:13:12 | D | best error = [ 3.9607, 3.9607, 3.9607, 3.9607, 3.9607] +24-11-19 19:13:12 | D | + error = [3.9607] +24-11-19 19:13:12 | D | - Calibrating model.layers.5.mlp.gate_proj.weight +24-11-19 19:13:12 | D | + w: sint8 +24-11-19 19:13:12 | D | + x: None +24-11-19 19:13:12 | D | + y: None +24-11-19 19:13:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:13:12 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:13:12 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:13:12 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:13:12 | D | - range ratio = [ 1.0000] +24-11-19 19:13:12 | D | sum error = [ 5.1220] +24-11-19 19:13:12 | D | best error = [ 5.1220] +24-11-19 19:13:13 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:13:13 | D | sum error = [ 5.0717, 5.0709, 5.1107, 5.1681, 5.2537] +24-11-19 19:13:13 | D | best error = [ 4.7114, 4.5667, 4.4944, 4.4538, 4.4337] +24-11-19 19:13:13 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:13:13 | D | sum error = [ 5.3884, 5.5706, 5.7926, 6.0720, 6.3918] +24-11-19 19:13:13 | D | best error = [ 4.4240, 4.4198, 4.4183, 4.4179, 4.4178] +24-11-19 19:13:13 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:13:13 | D | sum error = [ 6.7618, 7.1759, 7.6665, 8.1628, 8.7249] +24-11-19 19:13:13 | D | best error = [ 4.4177, 4.4177, 4.4177, 4.4177, 4.4177] +24-11-19 19:13:13 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:13:13 | D | sum error = [ 9.3426, 10.0091, 10.7379, 11.5171, 12.3398] +24-11-19 19:13:13 | D | best error = [ 4.4177, 4.4177, 4.4177, 4.4177, 4.4177] +24-11-19 19:13:13 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:13:13 | D | sum error = [ 13.2511, 14.1947, 15.2035, 16.2800, 17.4205] +24-11-19 19:13:13 | D | best error = [ 4.4177, 4.4177, 4.4177, 4.4177, 4.4177] +24-11-19 19:13:13 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:13:13 | D | sum error = [ 18.6502, 19.9377, 21.3058, 22.7546, 24.2972] +24-11-19 19:13:13 | D | best error = [ 4.4177, 4.4177, 4.4177, 4.4177, 4.4177] +24-11-19 19:13:13 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:13:13 | D | sum error = [ 25.9075, 27.6046, 29.4311, 31.3537, 33.3543] +24-11-19 19:13:13 | D | best error = [ 4.4177, 4.4177, 4.4177, 4.4177, 4.4177] +24-11-19 19:13:13 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:13:13 | D | sum error = [ 35.4900, 37.7380, 40.0919, 42.6042, 45.2209] +24-11-19 19:13:13 | D | best error = [ 4.4177, 4.4177, 4.4177, 4.4177, 4.4177] +24-11-19 19:13:13 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:13:13 | D | sum error = [ 47.9981, 50.9428, 54.0338, 57.2726, 60.7066] +24-11-19 19:13:13 | D | best error = [ 4.4177, 4.4177, 4.4177, 4.4177, 4.4177] +24-11-19 19:13:13 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:13:13 | D | sum error = [ 64.3231, 68.1055, 72.0971, 76.2818, 80.6776] +24-11-19 19:13:13 | D | best error = [ 4.4177, 4.4177, 4.4177, 4.4177, 4.4177] +24-11-19 19:13:13 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:13:13 | D | sum error = [ 85.2933, 90.1496, 95.2442, 100.5823, 106.1827] +24-11-19 19:13:13 | D | best error = [ 4.4177, 4.4177, 4.4177, 4.4177, 4.4177] +24-11-19 19:13:13 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:13:13 | D | sum error = [ 112.0338, 118.1614, 124.5760, 131.2816, 138.2912] +24-11-19 19:13:13 | D | best error = [ 4.4177, 4.4177, 4.4177, 4.4177, 4.4177] +24-11-19 19:13:13 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:13:13 | D | sum error = [ 145.5980, 153.2466, 161.2272, 169.5535, 178.2481] +24-11-19 19:13:13 | D | best error = [ 4.4177, 4.4177, 4.4177, 4.4177, 4.4177] +24-11-19 19:13:13 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:13:13 | D | sum error = [ 187.3040, 196.6985, 206.4790, 216.6375, 227.1945] +24-11-19 19:13:13 | D | best error = [ 4.4177, 4.4177, 4.4177, 4.4177, 4.4177] +24-11-19 19:13:13 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:13:13 | D | sum error = [ 238.1435, 249.4976, 261.3018, 273.4952, 286.1203] +24-11-19 19:13:13 | D | best error = [ 4.4177, 4.4177, 4.4177, 4.4177, 4.4177] +24-11-19 19:13:13 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:13:13 | D | sum error = [ 299.1501, 312.6059, 326.4914, 340.8155, 355.5794] +24-11-19 19:13:13 | D | best error = [ 4.4177, 4.4177, 4.4177, 4.4177, 4.4177] +24-11-19 19:13:13 | D | + error = [4.4177] +24-11-19 19:13:13 | D | - Calibrating model.layers.5.mlp.down_proj.weight +24-11-19 19:13:13 | D | + w: sint8 +24-11-19 19:13:13 | D | + x: None +24-11-19 19:13:13 | D | + y: None +24-11-19 19:13:13 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:13:13 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:13:13 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:13:13 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:13:13 | D | - range ratio = [ 1.0000] +24-11-19 19:13:13 | D | sum error = [ 0.7727] +24-11-19 19:13:13 | D | best error = [ 0.7727] +24-11-19 19:13:14 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:13:14 | D | sum error = [ 0.7661, 0.7601, 0.7551, 0.7531, 0.7533] +24-11-19 19:13:14 | D | best error = [ 0.7498, 0.7365, 0.7271, 0.7205, 0.7156] +24-11-19 19:13:14 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:13:14 | D | sum error = [ 0.7556, 0.7603, 0.7699, 0.7808, 0.7977] +24-11-19 19:13:14 | D | best error = [ 0.7118, 0.7091, 0.7073, 0.7061, 0.7054] +24-11-19 19:13:14 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:13:14 | D | sum error = [ 0.8166, 0.8428, 0.8730, 0.9090, 0.9479] +24-11-19 19:13:14 | D | best error = [ 0.7048, 0.7044, 0.7042, 0.7041, 0.7040] +24-11-19 19:13:14 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:13:14 | D | sum error = [ 0.9965, 1.0487, 1.1083, 1.1726, 1.2463] +24-11-19 19:13:14 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 19:13:14 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:13:14 | D | sum error = [ 1.3243, 1.4127, 1.5071, 1.6091, 1.7184] +24-11-19 19:13:14 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 19:13:14 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:13:14 | D | sum error = [ 1.8385, 1.9657, 2.1022, 2.2504, 2.4074] +24-11-19 19:13:14 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 19:13:14 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:13:14 | D | sum error = [ 2.5759, 2.7546, 2.9460, 3.1494, 3.3647] +24-11-19 19:13:14 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 19:13:14 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:13:14 | D | sum error = [ 3.5943, 3.8369, 4.0961, 4.3683, 4.6588] +24-11-19 19:13:14 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 19:13:14 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:13:14 | D | sum error = [ 4.9652, 5.2909, 5.6347, 5.9973, 6.3799] +24-11-19 19:13:14 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 19:13:14 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:13:14 | D | sum error = [ 6.7826, 7.2089, 7.6569, 8.1300, 8.6270] +24-11-19 19:13:14 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 19:13:14 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:13:14 | D | sum error = [ 9.1505, 9.7004, 10.2777, 10.8851, 11.5225] +24-11-19 19:13:14 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 19:13:14 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:13:14 | D | sum error = [ 12.1923, 12.8942, 13.6294, 14.4011, 15.2078] +24-11-19 19:13:14 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 19:13:14 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:13:14 | D | sum error = [ 16.0524, 16.9346, 17.8555, 18.8171, 19.8212] +24-11-19 19:13:14 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 19:13:14 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:13:14 | D | sum error = [ 20.8682, 21.9588, 23.0965, 24.2819, 25.5103] +24-11-19 19:13:14 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 19:13:14 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:13:14 | D | sum error = [ 26.7900, 28.1190, 29.4987, 30.9302, 32.4143] +24-11-19 19:13:14 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 19:13:14 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:13:14 | D | sum error = [ 33.9507, 35.5417, 37.1877, 38.8896, 40.6471] +24-11-19 19:13:14 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 19:13:14 | D | + error = [0.7039] +24-11-19 19:13:14 | D | - Quantizing model.layers.5.self_attn.q_proj.weight +24-11-19 19:13:15 | D | - Quantizing model.layers.5.self_attn.k_proj.weight +24-11-19 19:13:16 | D | - Quantizing model.layers.5.self_attn.v_proj.weight +24-11-19 19:13:17 | D | - Quantizing model.layers.5.self_attn.o_proj.weight +24-11-19 19:13:18 | D | - Quantizing model.layers.5.mlp.up_proj.weight +24-11-19 19:13:19 | D | - Quantizing model.layers.5.mlp.gate_proj.weight +24-11-19 19:13:20 | D | - Quantizing model.layers.5.mlp.down_proj.weight +24-11-19 19:13:28 | D | - Quantizing layer model.layers.6 +24-11-19 19:13:28 | D | - Calibrating model.layers.6.self_attn.q_proj.weight +24-11-19 19:13:28 | D | + w: sint8 +24-11-19 19:13:28 | D | + x: None +24-11-19 19:13:28 | D | + y: None +24-11-19 19:13:28 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:13:28 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:13:28 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:13:28 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:13:29 | D | - range ratio = [ 1.0000] +24-11-19 19:13:29 | D | sum error = [ 4.6700] +24-11-19 19:13:29 | D | best error = [ 4.6700] +24-11-19 19:13:41 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:13:41 | D | sum error = [ 4.6750, 4.7239, 4.7278, 4.8146, 4.7828] +24-11-19 19:13:41 | D | best error = [ 4.6700, 4.6700, 4.6700, 4.6700, 4.6700] +24-11-19 19:13:41 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:13:41 | D | sum error = [ 5.0617, 5.2364, 5.4943, 5.7208, 5.9844] +24-11-19 19:13:41 | D | best error = [ 4.6700, 4.6700, 4.6700, 4.6700, 4.6700] +24-11-19 19:13:41 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:13:41 | D | sum error = [ 6.5477, 7.2029, 7.4979, 8.2730, 9.0476] +24-11-19 19:13:41 | D | best error = [ 4.6700, 4.6700, 4.6700, 4.6700, 4.6700] +24-11-19 19:13:41 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:13:41 | D | sum error = [ 9.7993, 10.7557, 11.5630, 12.8223, 13.9924] +24-11-19 19:13:41 | D | best error = [ 4.6700, 4.6700, 4.6700, 4.6700, 4.6700] +24-11-19 19:13:41 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:13:41 | D | sum error = [ 15.5425, 16.8561, 18.4920, 20.5847, 22.2137] +24-11-19 19:13:41 | D | best error = [ 4.6700, 4.6700, 4.6700, 4.6700, 4.6700] +24-11-19 19:13:41 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:13:41 | D | sum error = [ 24.3358, 26.7379, 29.3975, 32.1480, 35.1902] +24-11-19 19:13:41 | D | best error = [ 4.6700, 4.6700, 4.6700, 4.6700, 4.6700] +24-11-19 19:13:41 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:13:41 | D | sum error = [ 38.2022, 41.6859, 45.8444, 50.0551, 54.3244] +24-11-19 19:13:41 | D | best error = [ 4.6700, 4.6700, 4.6700, 4.6700, 4.6700] +24-11-19 19:13:41 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:13:41 | D | sum error = [ 59.2080, 64.4778, 70.0443, 76.1474, 82.7438] +24-11-19 19:13:41 | D | best error = [ 4.6700, 4.6700, 4.6700, 4.6700, 4.6700] +24-11-19 19:13:41 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:13:41 | D | sum error = [ 89.7087, 97.1147, 105.1384, 113.6623, 123.2000] +24-11-19 19:13:41 | D | best error = [ 4.6700, 4.6700, 4.6700, 4.6700, 4.6700] +24-11-19 19:13:41 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:13:41 | D | sum error = [ 133.5006, 144.3030, 155.7727, 168.2150, 181.3308] +24-11-19 19:13:41 | D | best error = [ 4.6700, 4.6700, 4.6700, 4.6700, 4.6700] +24-11-19 19:13:41 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:13:41 | D | sum error = [ 196.1718, 211.2352, 227.7402, 245.5673, 264.5330] +24-11-19 19:13:41 | D | best error = [ 4.6700, 4.6700, 4.6700, 4.6700, 4.6700] +24-11-19 19:13:41 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:13:41 | D | sum error = [ 285.0087, 307.0197, 330.6353, 355.4358, 382.6037] +24-11-19 19:13:41 | D | best error = [ 4.6700, 4.6700, 4.6700, 4.6700, 4.6700] +24-11-19 19:13:41 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:13:41 | D | sum error = [ 411.1865, 441.7375, 474.5358, 509.5006, 546.4653] +24-11-19 19:13:41 | D | best error = [ 4.6700, 4.6700, 4.6700, 4.6700, 4.6700] +24-11-19 19:13:41 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:13:41 | D | sum error = [ 586.1287, 628.2980, 672.9362, 721.0849, 771.5676] +24-11-19 19:13:41 | D | best error = [ 4.6700, 4.6700, 4.6700, 4.6700, 4.6700] +24-11-19 19:13:41 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:13:41 | D | sum error = [ 825.5303, 882.3098, 942.6563, 1005.8367, 1072.1671] +24-11-19 19:13:41 | D | best error = [ 4.6700, 4.6700, 4.6700, 4.6700, 4.6700] +24-11-19 19:13:41 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:13:41 | D | sum error = [ 1141.4528, 1213.7207, 1288.7543, 1365.9211, 1444.6009] +24-11-19 19:13:41 | D | best error = [ 4.6700, 4.6700, 4.6700, 4.6700, 4.6700] +24-11-19 19:13:41 | D | + error = [4.6700] +24-11-19 19:13:41 | D | - Calibrating model.layers.6.self_attn.k_proj.weight +24-11-19 19:13:41 | D | + w: sint8 +24-11-19 19:13:41 | D | + x: None +24-11-19 19:13:41 | D | + y: None +24-11-19 19:13:41 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:13:41 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:13:41 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:13:41 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:13:42 | D | - range ratio = [ 1.0000] +24-11-19 19:13:42 | D | sum error = [ 5.7505] +24-11-19 19:13:42 | D | best error = [ 5.7505] +24-11-19 19:13:56 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:13:56 | D | sum error = [ 5.4750, 5.4976, 6.1457, 5.5231, 5.4962] +24-11-19 19:13:56 | D | best error = [ 5.4750, 5.4750, 5.4750, 5.4750, 5.4750] +24-11-19 19:13:56 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:13:56 | D | sum error = [ 6.3173, 6.2474, 6.4362, 6.9268, 7.0909] +24-11-19 19:13:56 | D | best error = [ 5.4750, 5.4750, 5.4750, 5.4750, 5.4750] +24-11-19 19:13:56 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:13:56 | D | sum error = [ 7.5608, 8.4274, 8.5150, 8.9072, 10.2853] +24-11-19 19:13:56 | D | best error = [ 5.4750, 5.4750, 5.4750, 5.4750, 5.4750] +24-11-19 19:13:56 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:13:56 | D | sum error = [ 10.8493, 11.5263, 12.4442, 13.6594, 15.1788] +24-11-19 19:13:56 | D | best error = [ 5.4750, 5.4750, 5.4750, 5.4750, 5.4750] +24-11-19 19:13:56 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:13:56 | D | sum error = [ 16.0114, 17.0496, 18.6888, 20.3273, 22.5581] +24-11-19 19:13:56 | D | best error = [ 5.4750, 5.4750, 5.4750, 5.4750, 5.4750] +24-11-19 19:13:56 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:13:56 | D | sum error = [ 24.4466, 26.3848, 28.0951, 31.0218, 33.7470] +24-11-19 19:13:56 | D | best error = [ 5.4750, 5.4750, 5.4750, 5.4750, 5.4750] +24-11-19 19:13:56 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:13:56 | D | sum error = [ 37.3633, 40.2911, 43.7053, 47.2241, 52.3809] +24-11-19 19:13:56 | D | best error = [ 5.4750, 5.4750, 5.4750, 5.4750, 5.4750] +24-11-19 19:13:56 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:13:56 | D | sum error = [ 56.3834, 61.5024, 66.3461, 71.5802, 77.5664] +24-11-19 19:13:56 | D | best error = [ 5.4750, 5.4750, 5.4750, 5.4750, 5.4750] +24-11-19 19:13:56 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:13:56 | D | sum error = [ 83.6096, 90.7290, 96.9278, 104.5080, 113.7445] +24-11-19 19:13:56 | D | best error = [ 5.4750, 5.4750, 5.4750, 5.4750, 5.4750] +24-11-19 19:13:56 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:13:56 | D | sum error = [ 122.1632, 131.7243, 141.0236, 152.3265, 163.3957] +24-11-19 19:13:56 | D | best error = [ 5.4750, 5.4750, 5.4750, 5.4750, 5.4750] +24-11-19 19:13:56 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:13:56 | D | sum error = [ 176.9555, 190.9484, 205.5617, 221.6904, 239.1222] +24-11-19 19:13:56 | D | best error = [ 5.4750, 5.4750, 5.4750, 5.4750, 5.4750] +24-11-19 19:13:56 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:13:56 | D | sum error = [ 256.8721, 276.9553, 298.7258, 321.2790, 347.0927] +24-11-19 19:13:56 | D | best error = [ 5.4750, 5.4750, 5.4750, 5.4750, 5.4750] +24-11-19 19:13:56 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:13:56 | D | sum error = [ 374.0420, 402.7993, 436.9676, 470.0307, 506.4744] +24-11-19 19:13:56 | D | best error = [ 5.4750, 5.4750, 5.4750, 5.4750, 5.4750] +24-11-19 19:13:56 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:13:56 | D | sum error = [ 546.8396, 586.5588, 630.2835, 677.2356, 727.9194] +24-11-19 19:13:56 | D | best error = [ 5.4750, 5.4750, 5.4750, 5.4750, 5.4750] +24-11-19 19:13:56 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:13:56 | D | sum error = [ 782.2698, 837.0147, 900.1980, 965.5169, 1035.1636] +24-11-19 19:13:56 | D | best error = [ 5.4750, 5.4750, 5.4750, 5.4750, 5.4750] +24-11-19 19:13:56 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:13:56 | D | sum error = [ 1103.5014, 1180.5714, 1259.0198, 1338.7300, 1416.4178] +24-11-19 19:13:56 | D | best error = [ 5.4750, 5.4750, 5.4750, 5.4750, 5.4750] +24-11-19 19:13:56 | D | + error = [5.4750] +24-11-19 19:13:56 | D | - Calibrating model.layers.6.self_attn.v_proj.weight +24-11-19 19:13:56 | D | + w: sint8 +24-11-19 19:13:56 | D | + x: None +24-11-19 19:13:56 | D | + y: None +24-11-19 19:13:56 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:13:56 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:13:56 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:13:57 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:13:57 | D | - range ratio = [ 1.0000] +24-11-19 19:13:57 | D | sum error = [ 3.6928] +24-11-19 19:13:57 | D | best error = [ 3.6928] +24-11-19 19:13:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:13:57 | D | sum error = [ 3.6648, 3.6437, 3.6947, 3.7206, 3.7831] +24-11-19 19:13:57 | D | best error = [ 3.4311, 3.3330, 3.2874, 3.2598, 3.2446] +24-11-19 19:13:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:13:57 | D | sum error = [ 3.8906, 4.0172, 4.1883, 4.3905, 4.6269] +24-11-19 19:13:57 | D | best error = [ 3.2388, 3.2364, 3.2355, 3.2353, 3.2353] +24-11-19 19:13:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:13:57 | D | sum error = [ 4.9076, 5.2115, 5.5427, 5.9107, 6.3146] +24-11-19 19:13:57 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 19:13:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:13:57 | D | sum error = [ 6.7705, 7.2611, 7.7659, 8.3416, 8.9460] +24-11-19 19:13:57 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 19:13:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:13:57 | D | sum error = [ 9.5945, 10.2385, 10.9685, 11.7527, 12.5632] +24-11-19 19:13:57 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 19:13:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:13:57 | D | sum error = [ 13.4454, 14.3635, 15.3296, 16.3725, 17.4663] +24-11-19 19:13:57 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 19:13:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:13:57 | D | sum error = [ 18.6168, 19.8268, 21.1176, 22.4533, 23.8950] +24-11-19 19:13:57 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 19:13:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:13:57 | D | sum error = [ 25.3937, 26.9887, 28.6646, 30.4160, 32.2781] +24-11-19 19:13:57 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 19:13:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:13:57 | D | sum error = [ 34.2165, 36.2774, 38.4243, 40.6717, 43.0373] +24-11-19 19:13:57 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 19:13:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:13:57 | D | sum error = [ 45.5284, 48.1278, 50.8394, 53.7038, 56.6952] +24-11-19 19:13:57 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 19:13:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:13:57 | D | sum error = [ 59.8256, 63.1082, 66.5452, 70.1399, 73.9136] +24-11-19 19:13:57 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 19:13:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:13:57 | D | sum error = [ 77.8500, 81.9612, 86.2641, 90.7390, 95.4136] +24-11-19 19:13:57 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 19:13:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:13:57 | D | sum error = [ 100.2888, 105.3622, 110.6377, 116.1274, 121.8474] +24-11-19 19:13:57 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 19:13:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:13:57 | D | sum error = [ 127.7896, 133.9561, 140.3634, 147.0228, 153.9045] +24-11-19 19:13:57 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 19:13:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:13:57 | D | sum error = [ 161.0448, 168.4564, 176.1124, 184.0266, 192.1992] +24-11-19 19:13:57 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 19:13:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:13:57 | D | sum error = [ 200.6282, 209.3283, 218.2851, 227.5169, 237.0098] +24-11-19 19:13:57 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 19:13:57 | D | + error = [3.2353] +24-11-19 19:13:57 | D | - Calibrating model.layers.6.self_attn.o_proj.weight +24-11-19 19:13:57 | D | + w: sint8 +24-11-19 19:13:57 | D | + x: None +24-11-19 19:13:57 | D | + y: None +24-11-19 19:13:57 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:13:57 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:13:57 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:13:57 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:13:57 | D | - range ratio = [ 1.0000] +24-11-19 19:13:57 | D | sum error = [ 0.5783] +24-11-19 19:13:57 | D | best error = [ 0.5783] +24-11-19 19:13:58 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:13:58 | D | sum error = [ 0.5729, 0.5699, 0.5723, 0.5766, 0.5851] +24-11-19 19:13:58 | D | best error = [ 0.5435, 0.5273, 0.5186, 0.5126, 0.5089] +24-11-19 19:13:58 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:13:58 | D | sum error = [ 0.5989, 0.6154, 0.6376, 0.6647, 0.6923] +24-11-19 19:13:58 | D | best error = [ 0.5064, 0.5049, 0.5039, 0.5032, 0.5027] +24-11-19 19:13:58 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:13:58 | D | sum error = [ 0.7299, 0.7701, 0.8166, 0.8674, 0.9228] +24-11-19 19:13:58 | D | best error = [ 0.5024, 0.5021, 0.5020, 0.5019, 0.5019] +24-11-19 19:13:58 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:13:58 | D | sum error = [ 0.9812, 1.0491, 1.1188, 1.1956, 1.2778] +24-11-19 19:13:58 | D | best error = [ 0.5018, 0.5018, 0.5018, 0.5017, 0.5017] +24-11-19 19:13:58 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:13:58 | D | sum error = [ 1.3660, 1.4608, 1.5573, 1.6627, 1.7765] +24-11-19 19:13:58 | D | best error = [ 0.5017, 0.5017, 0.5017, 0.5017, 0.5017] +24-11-19 19:13:58 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:13:58 | D | sum error = [ 1.8951, 2.0214, 2.1554, 2.2974, 2.4467] +24-11-19 19:13:58 | D | best error = [ 0.5017, 0.5017, 0.5017, 0.5017, 0.5017] +24-11-19 19:13:58 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:13:58 | D | sum error = [ 2.6048, 2.7715, 2.9480, 3.1333, 3.3274] +24-11-19 19:13:58 | D | best error = [ 0.5017, 0.5017, 0.5017, 0.5017, 0.5017] +24-11-19 19:13:58 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:13:58 | D | sum error = [ 3.5339, 3.7523, 3.9809, 4.2242, 4.4766] +24-11-19 19:13:58 | D | best error = [ 0.5017, 0.5017, 0.5017, 0.5017, 0.5017] +24-11-19 19:13:58 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:13:58 | D | sum error = [ 4.7426, 5.0236, 5.3168, 5.6257, 5.9502] +24-11-19 19:13:58 | D | best error = [ 0.5017, 0.5017, 0.5017, 0.5017, 0.5017] +24-11-19 19:13:58 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:13:58 | D | sum error = [ 6.2917, 6.6469, 7.0208, 7.4140, 7.8254] +24-11-19 19:13:58 | D | best error = [ 0.5017, 0.5017, 0.5017, 0.5017, 0.5017] +24-11-19 19:13:58 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:13:58 | D | sum error = [ 8.2565, 8.7085, 9.1813, 9.6751, 10.1932] +24-11-19 19:13:58 | D | best error = [ 0.5017, 0.5017, 0.5017, 0.5017, 0.5017] +24-11-19 19:13:58 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:13:58 | D | sum error = [ 10.7342, 11.2983, 11.8893, 12.5048, 13.1480] +24-11-19 19:13:58 | D | best error = [ 0.5017, 0.5017, 0.5017, 0.5017, 0.5017] +24-11-19 19:13:58 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:13:58 | D | sum error = [ 13.8199, 14.5200, 15.2507, 16.0111, 16.8048] +24-11-19 19:13:58 | D | best error = [ 0.5017, 0.5017, 0.5017, 0.5017, 0.5017] +24-11-19 19:13:58 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:13:58 | D | sum error = [ 17.6300, 18.4889, 19.3804, 20.3072, 21.2712] +24-11-19 19:13:58 | D | best error = [ 0.5017, 0.5017, 0.5017, 0.5017, 0.5017] +24-11-19 19:13:58 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:13:58 | D | sum error = [ 22.2705, 23.3054, 24.3813, 25.4962, 26.6524] +24-11-19 19:13:58 | D | best error = [ 0.5017, 0.5017, 0.5017, 0.5017, 0.5017] +24-11-19 19:13:58 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:13:58 | D | sum error = [ 27.8489, 29.0865, 30.3669, 31.6888, 33.0528] +24-11-19 19:13:58 | D | best error = [ 0.5017, 0.5017, 0.5017, 0.5017, 0.5017] +24-11-19 19:13:58 | D | + error = [0.5017] +24-11-19 19:13:58 | D | - Calibrating model.layers.6.mlp.up_proj.weight +24-11-19 19:13:58 | D | + w: sint8 +24-11-19 19:13:58 | D | + x: None +24-11-19 19:13:58 | D | + y: None +24-11-19 19:13:58 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:13:58 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:13:58 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:13:58 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:13:58 | D | - range ratio = [ 1.0000] +24-11-19 19:13:58 | D | sum error = [ 4.8868] +24-11-19 19:13:58 | D | best error = [ 4.8868] +24-11-19 19:13:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:13:59 | D | sum error = [ 4.8526, 4.8473, 4.8578, 4.9151, 5.0189] +24-11-19 19:13:59 | D | best error = [ 4.5251, 4.3951, 4.3257, 4.2898, 4.2701] +24-11-19 19:13:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:13:59 | D | sum error = [ 5.1386, 5.3008, 5.5296, 5.7892, 6.1032] +24-11-19 19:13:59 | D | best error = [ 4.2616, 4.2576, 4.2565, 4.2562, 4.2561] +24-11-19 19:13:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:13:59 | D | sum error = [ 6.4435, 6.8459, 7.3014, 7.7976, 8.3383] +24-11-19 19:13:59 | D | best error = [ 4.2561, 4.2561, 4.2561, 4.2561, 4.2561] +24-11-19 19:13:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:13:59 | D | sum error = [ 8.9146, 9.5470, 10.2415, 10.9671, 11.7432] +24-11-19 19:13:59 | D | best error = [ 4.2561, 4.2561, 4.2561, 4.2561, 4.2561] +24-11-19 19:13:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:13:59 | D | sum error = [ 12.5941, 13.4806, 14.4302, 15.4483, 16.5033] +24-11-19 19:13:59 | D | best error = [ 4.2561, 4.2561, 4.2561, 4.2561, 4.2561] +24-11-19 19:13:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:13:59 | D | sum error = [ 17.6261, 18.8277, 20.1050, 21.4230, 22.8487] +24-11-19 19:13:59 | D | best error = [ 4.2561, 4.2561, 4.2561, 4.2561, 4.2561] +24-11-19 19:13:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:13:59 | D | sum error = [ 24.3463, 25.9056, 27.5620, 29.2974, 31.1417] +24-11-19 19:13:59 | D | best error = [ 4.2561, 4.2561, 4.2561, 4.2561, 4.2561] +24-11-19 19:13:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:13:59 | D | sum error = [ 33.0720, 35.0909, 37.2343, 39.4900, 41.8288] +24-11-19 19:13:59 | D | best error = [ 4.2561, 4.2561, 4.2561, 4.2561, 4.2561] +24-11-19 19:13:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:13:59 | D | sum error = [ 44.3002, 46.8902, 49.6097, 52.4599, 55.4499] +24-11-19 19:13:59 | D | best error = [ 4.2561, 4.2561, 4.2561, 4.2561, 4.2561] +24-11-19 19:13:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:13:59 | D | sum error = [ 58.5778, 61.8499, 65.2713, 68.8473, 72.5825] +24-11-19 19:13:59 | D | best error = [ 4.2561, 4.2561, 4.2561, 4.2561, 4.2561] +24-11-19 19:13:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:13:59 | D | sum error = [ 76.4811, 80.5292, 84.7510, 89.1709, 93.7458] +24-11-19 19:13:59 | D | best error = [ 4.2561, 4.2561, 4.2561, 4.2561, 4.2561] +24-11-19 19:13:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:13:59 | D | sum error = [ 98.5141, 103.4853, 108.6489, 114.0203, 119.6062] +24-11-19 19:13:59 | D | best error = [ 4.2561, 4.2561, 4.2561, 4.2561, 4.2561] +24-11-19 19:13:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:13:59 | D | sum error = [ 125.4152, 131.4308, 137.6773, 144.1438, 150.8558] +24-11-19 19:13:59 | D | best error = [ 4.2561, 4.2561, 4.2561, 4.2561, 4.2561] +24-11-19 19:13:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:13:59 | D | sum error = [ 157.8072, 164.9976, 172.4483, 180.1497, 188.1039] +24-11-19 19:13:59 | D | best error = [ 4.2561, 4.2561, 4.2561, 4.2561, 4.2561] +24-11-19 19:13:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:13:59 | D | sum error = [ 196.3324, 204.8250, 213.5883, 222.6248, 231.9443] +24-11-19 19:13:59 | D | best error = [ 4.2561, 4.2561, 4.2561, 4.2561, 4.2561] +24-11-19 19:13:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:13:59 | D | sum error = [ 241.5457, 251.4337, 261.6185, 272.0969, 282.8699] +24-11-19 19:13:59 | D | best error = [ 4.2561, 4.2561, 4.2561, 4.2561, 4.2561] +24-11-19 19:13:59 | D | + error = [4.2561] +24-11-19 19:13:59 | D | - Calibrating model.layers.6.mlp.gate_proj.weight +24-11-19 19:13:59 | D | + w: sint8 +24-11-19 19:13:59 | D | + x: None +24-11-19 19:13:59 | D | + y: None +24-11-19 19:13:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:13:59 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:13:59 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:13:59 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:13:59 | D | - range ratio = [ 1.0000] +24-11-19 19:13:59 | D | sum error = [ 5.5708] +24-11-19 19:13:59 | D | best error = [ 5.5708] +24-11-19 19:14:00 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:14:00 | D | sum error = [ 5.5257, 5.5206, 5.5440, 5.6020, 5.7024] +24-11-19 19:14:00 | D | best error = [ 5.1657, 5.0142, 4.9350, 4.8906, 4.8679] +24-11-19 19:14:00 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:14:00 | D | sum error = [ 5.8673, 6.0628, 6.3068, 6.5890, 6.9531] +24-11-19 19:14:00 | D | best error = [ 4.8583, 4.8541, 4.8523, 4.8517, 4.8517] +24-11-19 19:14:00 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:14:00 | D | sum error = [ 7.3549, 7.8205, 8.3322, 8.9105, 9.5245] +24-11-19 19:14:00 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 19:14:00 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:14:00 | D | sum error = [ 10.2049, 10.9272, 11.7395, 12.5951, 13.4909] +24-11-19 19:14:00 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 19:14:00 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:14:00 | D | sum error = [ 14.4834, 15.5509, 16.6435, 17.8385, 19.1146] +24-11-19 19:14:00 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 19:14:00 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:14:00 | D | sum error = [ 20.4456, 21.8713, 23.3787, 24.9956, 26.6805] +24-11-19 19:14:00 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 19:14:00 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:14:00 | D | sum error = [ 28.4716, 30.3584, 32.3989, 34.5069, 36.7645] +24-11-19 19:14:00 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 19:14:00 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:14:00 | D | sum error = [ 39.1378, 41.6594, 44.3049, 47.1076, 50.0818] +24-11-19 19:14:00 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 19:14:00 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:14:00 | D | sum error = [ 53.1925, 56.4771, 59.9486, 63.6140, 67.4627] +24-11-19 19:14:00 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 19:14:00 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:14:00 | D | sum error = [ 71.5451, 75.8416, 80.3759, 85.1460, 90.1827] +24-11-19 19:14:00 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 19:14:00 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:14:00 | D | sum error = [ 95.4732, 101.0523, 106.9108, 113.0898, 119.5657] +24-11-19 19:14:00 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 19:14:00 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:14:00 | D | sum error = [ 126.3725, 133.5318, 141.0499, 148.9133, 157.1639] +24-11-19 19:14:00 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 19:14:00 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:14:00 | D | sum error = [ 165.7884, 174.8106, 184.2436, 194.0914, 204.3838] +24-11-19 19:14:00 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 19:14:00 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:14:00 | D | sum error = [ 215.1292, 226.3252, 237.9960, 250.1310, 262.7556] +24-11-19 19:14:00 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 19:14:00 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:14:00 | D | sum error = [ 275.8788, 289.4897, 303.6384, 318.2862, 333.4500] +24-11-19 19:14:00 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 19:14:00 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:14:00 | D | sum error = [ 349.1338, 365.3483, 382.1046, 399.3921, 417.1923] +24-11-19 19:14:00 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 19:14:00 | D | + error = [4.8517] +24-11-19 19:14:00 | D | - Calibrating model.layers.6.mlp.down_proj.weight +24-11-19 19:14:00 | D | + w: sint8 +24-11-19 19:14:00 | D | + x: None +24-11-19 19:14:00 | D | + y: None +24-11-19 19:14:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:14:00 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:14:00 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:14:01 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:14:01 | D | - range ratio = [ 1.0000] +24-11-19 19:14:01 | D | sum error = [ 0.9535] +24-11-19 19:14:01 | D | best error = [ 0.9535] +24-11-19 19:14:02 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:14:02 | D | sum error = [ 0.9436, 0.9375, 0.9317, 0.9281, 0.9297] +24-11-19 19:14:02 | D | best error = [ 0.9212, 0.9046, 0.8930, 0.8841, 0.8773] +24-11-19 19:14:02 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:14:02 | D | sum error = [ 0.9322, 0.9372, 0.9484, 0.9647, 0.9844] +24-11-19 19:14:02 | D | best error = [ 0.8727, 0.8693, 0.8666, 0.8649, 0.8636] +24-11-19 19:14:02 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:14:02 | D | sum error = [ 1.0102, 1.0420, 1.0785, 1.1235, 1.1751] +24-11-19 19:14:02 | D | best error = [ 0.8628, 0.8623, 0.8620, 0.8618, 0.8618] +24-11-19 19:14:02 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:14:02 | D | sum error = [ 1.2335, 1.3001, 1.3728, 1.4545, 1.5467] +24-11-19 19:14:02 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 19:14:02 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:14:02 | D | sum error = [ 1.6455, 1.7546, 1.8723, 2.0005, 2.1401] +24-11-19 19:14:02 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 19:14:02 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:14:02 | D | sum error = [ 2.2900, 2.4511, 2.6242, 2.8074, 3.0064] +24-11-19 19:14:02 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 19:14:02 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:14:02 | D | sum error = [ 3.2159, 3.4399, 3.6778, 3.9337, 4.2030] +24-11-19 19:14:02 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 19:14:02 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:14:02 | D | sum error = [ 4.4896, 4.7923, 5.1159, 5.4554, 5.8161] +24-11-19 19:14:02 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 19:14:02 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:14:02 | D | sum error = [ 6.2006, 6.6042, 7.0316, 7.4807, 7.9567] +24-11-19 19:14:02 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 19:14:02 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:14:02 | D | sum error = [ 8.4580, 8.9864, 9.5420, 10.1281, 10.7431] +24-11-19 19:14:02 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 19:14:02 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:14:02 | D | sum error = [ 11.3893, 12.0694, 12.7830, 13.5336, 14.3207] +24-11-19 19:14:02 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 19:14:02 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:14:02 | D | sum error = [ 15.1457, 16.0094, 16.9142, 17.8618, 18.8519] +24-11-19 19:14:02 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 19:14:02 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:14:02 | D | sum error = [ 19.8884, 20.9715, 22.1013, 23.2818, 24.5146] +24-11-19 19:14:02 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 19:14:02 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:14:02 | D | sum error = [ 25.7978, 27.1355, 28.5290, 29.9792, 31.4838] +24-11-19 19:14:02 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 19:14:02 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:14:02 | D | sum error = [ 33.0494, 34.6752, 36.3626, 38.1131, 39.9279] +24-11-19 19:14:02 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 19:14:02 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:14:02 | D | sum error = [ 41.8080, 43.7531, 45.7670, 47.8468, 49.9960] +24-11-19 19:14:02 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 19:14:02 | D | + error = [0.8617] +24-11-19 19:14:02 | D | - Quantizing model.layers.6.self_attn.q_proj.weight +24-11-19 19:14:03 | D | - Quantizing model.layers.6.self_attn.k_proj.weight +24-11-19 19:14:04 | D | - Quantizing model.layers.6.self_attn.v_proj.weight +24-11-19 19:14:05 | D | - Quantizing model.layers.6.self_attn.o_proj.weight +24-11-19 19:14:06 | D | - Quantizing model.layers.6.mlp.up_proj.weight +24-11-19 19:14:06 | D | - Quantizing model.layers.6.mlp.gate_proj.weight +24-11-19 19:14:07 | D | - Quantizing model.layers.6.mlp.down_proj.weight +24-11-19 19:14:16 | D | - Quantizing layer model.layers.7 +24-11-19 19:14:16 | D | - Calibrating model.layers.7.self_attn.q_proj.weight +24-11-19 19:14:16 | D | + w: sint8 +24-11-19 19:14:16 | D | + x: None +24-11-19 19:14:16 | D | + y: None +24-11-19 19:14:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:14:16 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:14:16 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:14:16 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:14:17 | D | - range ratio = [ 1.0000] +24-11-19 19:14:17 | D | sum error = [ 5.7777] +24-11-19 19:14:17 | D | best error = [ 5.7777] +24-11-19 19:14:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:14:29 | D | sum error = [ 5.7407, 5.6097, 5.6596, 5.7477, 5.8856] +24-11-19 19:14:29 | D | best error = [ 5.7407, 5.6097, 5.6097, 5.6097, 5.6097] +24-11-19 19:14:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:14:29 | D | sum error = [ 6.1071, 6.2710, 6.6864, 6.8946, 7.3665] +24-11-19 19:14:29 | D | best error = [ 5.6097, 5.6097, 5.6097, 5.6097, 5.6097] +24-11-19 19:14:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:14:29 | D | sum error = [ 7.9093, 8.3577, 9.0307, 9.7711, 10.5771] +24-11-19 19:14:29 | D | best error = [ 5.6097, 5.6097, 5.6097, 5.6097, 5.6097] +24-11-19 19:14:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:14:29 | D | sum error = [ 11.3287, 12.3909, 13.4795, 14.4396, 16.0996] +24-11-19 19:14:29 | D | best error = [ 5.6097, 5.6097, 5.6097, 5.6097, 5.6097] +24-11-19 19:14:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:14:29 | D | sum error = [ 17.4708, 18.7769, 20.5659, 22.3029, 24.3901] +24-11-19 19:14:29 | D | best error = [ 5.6097, 5.6097, 5.6097, 5.6097, 5.6097] +24-11-19 19:14:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:14:29 | D | sum error = [ 26.3611, 28.5844, 31.2362, 33.9339, 36.7184] +24-11-19 19:14:29 | D | best error = [ 5.6097, 5.6097, 5.6097, 5.6097, 5.6097] +24-11-19 19:14:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:14:29 | D | sum error = [ 39.9617, 43.1135, 46.5977, 50.7457, 54.4608] +24-11-19 19:14:29 | D | best error = [ 5.6097, 5.6097, 5.6097, 5.6097, 5.6097] +24-11-19 19:14:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:14:29 | D | sum error = [ 59.1278, 64.0592, 69.3174, 74.8004, 80.8568] +24-11-19 19:14:29 | D | best error = [ 5.6097, 5.6097, 5.6097, 5.6097, 5.6097] +24-11-19 19:14:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:14:29 | D | sum error = [ 87.0061, 93.8476, 101.0565, 108.8031, 117.1694] +24-11-19 19:14:29 | D | best error = [ 5.6097, 5.6097, 5.6097, 5.6097, 5.6097] +24-11-19 19:14:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:14:29 | D | sum error = [ 126.0272, 135.3264, 145.4948, 156.1120, 167.6839] +24-11-19 19:14:29 | D | best error = [ 5.6097, 5.6097, 5.6097, 5.6097, 5.6097] +24-11-19 19:14:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:14:29 | D | sum error = [ 180.0065, 193.3172, 207.3848, 222.6236, 239.0787] +24-11-19 19:14:29 | D | best error = [ 5.6097, 5.6097, 5.6097, 5.6097, 5.6097] +24-11-19 19:14:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:14:29 | D | sum error = [ 256.4296, 275.5210, 295.9608, 317.7160, 340.5723] +24-11-19 19:14:29 | D | best error = [ 5.6097, 5.6097, 5.6097, 5.6097, 5.6097] +24-11-19 19:14:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:14:29 | D | sum error = [ 365.4246, 391.7005, 419.8869, 450.4499, 482.7434] +24-11-19 19:14:29 | D | best error = [ 5.6097, 5.6097, 5.6097, 5.6097, 5.6097] +24-11-19 19:14:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:14:29 | D | sum error = [ 517.4251, 554.3522, 593.9722, 636.3381, 681.6176] +24-11-19 19:14:29 | D | best error = [ 5.6097, 5.6097, 5.6097, 5.6097, 5.6097] +24-11-19 19:14:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:14:29 | D | sum error = [ 730.4799, 782.6742, 838.5379, 898.4130, 961.7934] +24-11-19 19:14:29 | D | best error = [ 5.6097, 5.6097, 5.6097, 5.6097, 5.6097] +24-11-19 19:14:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:14:29 | D | sum error = [ 1029.1126, 1100.2484, 1175.2427, 1253.5778, 1335.0885] +24-11-19 19:14:29 | D | best error = [ 5.6097, 5.6097, 5.6097, 5.6097, 5.6097] +24-11-19 19:14:29 | D | + error = [5.6097] +24-11-19 19:14:29 | D | - Calibrating model.layers.7.self_attn.k_proj.weight +24-11-19 19:14:29 | D | + w: sint8 +24-11-19 19:14:29 | D | + x: None +24-11-19 19:14:29 | D | + y: None +24-11-19 19:14:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:14:29 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:14:29 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:14:29 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:14:30 | D | - range ratio = [ 1.0000] +24-11-19 19:14:30 | D | sum error = [ 6.9518] +24-11-19 19:14:30 | D | best error = [ 6.9518] +24-11-19 19:14:42 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:14:42 | D | sum error = [ 6.7436, 6.9658, 7.1503, 6.8437, 7.0993] +24-11-19 19:14:42 | D | best error = [ 6.7436, 6.7436, 6.7436, 6.7436, 6.7436] +24-11-19 19:14:42 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:14:42 | D | sum error = [ 7.4116, 7.2481, 8.2024, 8.4700, 8.5990] +24-11-19 19:14:42 | D | best error = [ 6.7436, 6.7436, 6.7436, 6.7436, 6.7436] +24-11-19 19:14:42 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:14:42 | D | sum error = [ 9.3609, 10.7539, 10.7903, 11.2920, 12.6172] +24-11-19 19:14:42 | D | best error = [ 6.7436, 6.7436, 6.7436, 6.7436, 6.7436] +24-11-19 19:14:42 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:14:42 | D | sum error = [ 13.2621, 13.7309, 14.4405, 16.2962, 17.3971] +24-11-19 19:14:42 | D | best error = [ 6.7436, 6.7436, 6.7436, 6.7436, 6.7436] +24-11-19 19:14:42 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:14:42 | D | sum error = [ 18.7270, 20.0929, 21.5511, 23.3203, 25.0086] +24-11-19 19:14:42 | D | best error = [ 6.7436, 6.7436, 6.7436, 6.7436, 6.7436] +24-11-19 19:14:42 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:14:42 | D | sum error = [ 27.2728, 29.3446, 31.6626, 33.9906, 37.0571] +24-11-19 19:14:42 | D | best error = [ 6.7436, 6.7436, 6.7436, 6.7436, 6.7436] +24-11-19 19:14:42 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:14:42 | D | sum error = [ 38.9800, 42.5265, 45.8377, 49.7357, 53.5695] +24-11-19 19:14:42 | D | best error = [ 6.7436, 6.7436, 6.7436, 6.7436, 6.7436] +24-11-19 19:14:42 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:14:42 | D | sum error = [ 57.4468, 62.4807, 67.1450, 72.2667, 77.4250] +24-11-19 19:14:42 | D | best error = [ 6.7436, 6.7436, 6.7436, 6.7436, 6.7436] +24-11-19 19:14:42 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:14:42 | D | sum error = [ 82.8948, 90.1151, 96.0039, 103.9683, 110.8745] +24-11-19 19:14:42 | D | best error = [ 6.7436, 6.7436, 6.7436, 6.7436, 6.7436] +24-11-19 19:14:42 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:14:42 | D | sum error = [ 120.5548, 128.8296, 139.1286, 150.0434, 162.1093] +24-11-19 19:14:42 | D | best error = [ 6.7436, 6.7436, 6.7436, 6.7436, 6.7436] +24-11-19 19:14:42 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:14:42 | D | sum error = [ 173.4120, 187.7263, 202.6241, 219.0363, 235.7236] +24-11-19 19:14:42 | D | best error = [ 6.7436, 6.7436, 6.7436, 6.7436, 6.7436] +24-11-19 19:14:42 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:14:42 | D | sum error = [ 254.8771, 273.2521, 294.7983, 315.8959, 341.8814] +24-11-19 19:14:42 | D | best error = [ 6.7436, 6.7436, 6.7436, 6.7436, 6.7436] +24-11-19 19:14:42 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:14:42 | D | sum error = [ 367.1309, 395.5684, 425.6873, 457.9436, 488.7940] +24-11-19 19:14:42 | D | best error = [ 6.7436, 6.7436, 6.7436, 6.7436, 6.7436] +24-11-19 19:14:42 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:14:42 | D | sum error = [ 527.4846, 565.5319, 608.3560, 653.5290, 703.0045] +24-11-19 19:14:42 | D | best error = [ 6.7436, 6.7436, 6.7436, 6.7436, 6.7436] +24-11-19 19:14:42 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:14:42 | D | sum error = [ 753.1551, 807.5044, 865.6135, 927.0159, 992.0618] +24-11-19 19:14:42 | D | best error = [ 6.7436, 6.7436, 6.7436, 6.7436, 6.7436] +24-11-19 19:14:42 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:14:42 | D | sum error = [ 1063.1412, 1134.8160, 1212.8288, 1288.8004, 1368.4243] +24-11-19 19:14:42 | D | best error = [ 6.7436, 6.7436, 6.7436, 6.7436, 6.7436] +24-11-19 19:14:42 | D | + error = [6.7436] +24-11-19 19:14:42 | D | - Calibrating model.layers.7.self_attn.v_proj.weight +24-11-19 19:14:42 | D | + w: sint8 +24-11-19 19:14:42 | D | + x: None +24-11-19 19:14:42 | D | + y: None +24-11-19 19:14:42 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:14:42 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:14:43 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:14:43 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:14:43 | D | - range ratio = [ 1.0000] +24-11-19 19:14:43 | D | sum error = [ 3.9002] +24-11-19 19:14:43 | D | best error = [ 3.9002] +24-11-19 19:14:43 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:14:43 | D | sum error = [ 3.8519, 3.8352, 3.8782, 3.9069, 3.9715] +24-11-19 19:14:43 | D | best error = [ 3.6236, 3.5196, 3.4708, 3.4423, 3.4285] +24-11-19 19:14:43 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:14:43 | D | sum error = [ 4.0955, 4.2104, 4.3846, 4.6033, 4.8357] +24-11-19 19:14:43 | D | best error = [ 3.4219, 3.4185, 3.4173, 3.4170, 3.4169] +24-11-19 19:14:43 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:14:43 | D | sum error = [ 5.1188, 5.4421, 5.7933, 6.1733, 6.6066] +24-11-19 19:14:43 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 19:14:43 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:14:43 | D | sum error = [ 7.0727, 7.5623, 8.1098, 8.6841, 9.3167] +24-11-19 19:14:43 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 19:14:43 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:14:43 | D | sum error = [ 9.9591, 10.6856, 11.4290, 12.2552, 13.0897] +24-11-19 19:14:43 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 19:14:43 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:14:43 | D | sum error = [ 13.9783, 14.9441, 15.9403, 17.0249, 18.1539] +24-11-19 19:14:43 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 19:14:43 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:14:43 | D | sum error = [ 19.3621, 20.6181, 21.9405, 23.3478, 24.8358] +24-11-19 19:14:43 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 19:14:43 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:14:43 | D | sum error = [ 26.3916, 28.0474, 29.7766, 31.6025, 33.5216] +24-11-19 19:14:43 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 19:14:43 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:14:43 | D | sum error = [ 35.5528, 37.6781, 39.9009, 42.2430, 44.7178] +24-11-19 19:14:43 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 19:14:43 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:14:43 | D | sum error = [ 47.3009, 50.0156, 52.8701, 55.8495, 58.9748] +24-11-19 19:14:43 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 19:14:43 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:14:43 | D | sum error = [ 62.2366, 65.6819, 69.2664, 73.0066, 76.9261] +24-11-19 19:14:43 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 19:14:43 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:14:43 | D | sum error = [ 81.0240, 85.3018, 89.7770, 94.4380, 99.2953] +24-11-19 19:14:43 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 19:14:43 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:14:43 | D | sum error = [ 104.3625, 109.6503, 115.1451, 120.8413, 126.7709] +24-11-19 19:14:43 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 19:14:43 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:14:43 | D | sum error = [ 132.9270, 139.3083, 145.9399, 152.8254, 159.9451] +24-11-19 19:14:43 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 19:14:43 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:14:43 | D | sum error = [ 167.3254, 174.9741, 182.8784, 191.0587, 199.5057] +24-11-19 19:14:43 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 19:14:43 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:14:43 | D | sum error = [ 208.2222, 217.2098, 226.4783, 236.0036, 245.8037] +24-11-19 19:14:43 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 19:14:43 | D | + error = [3.4169] +24-11-19 19:14:43 | D | - Calibrating model.layers.7.self_attn.o_proj.weight +24-11-19 19:14:43 | D | + w: sint8 +24-11-19 19:14:43 | D | + x: None +24-11-19 19:14:43 | D | + y: None +24-11-19 19:14:43 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:14:43 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:14:43 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:14:43 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:14:43 | D | - range ratio = [ 1.0000] +24-11-19 19:14:43 | D | sum error = [ 0.6822] +24-11-19 19:14:43 | D | best error = [ 0.6822] +24-11-19 19:14:44 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:14:44 | D | sum error = [ 0.6771, 0.6734, 0.6722, 0.6737, 0.6836] +24-11-19 19:14:44 | D | best error = [ 0.6387, 0.6183, 0.6056, 0.5974, 0.5921] +24-11-19 19:14:44 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:14:44 | D | sum error = [ 0.6927, 0.7078, 0.7282, 0.7488, 0.7758] +24-11-19 19:14:44 | D | best error = [ 0.5881, 0.5851, 0.5831, 0.5815, 0.5803] +24-11-19 19:14:44 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:14:44 | D | sum error = [ 0.8116, 0.8515, 0.8949, 0.9437, 0.9986] +24-11-19 19:14:44 | D | best error = [ 0.5793, 0.5787, 0.5782, 0.5778, 0.5775] +24-11-19 19:14:44 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:14:44 | D | sum error = [ 1.0603, 1.1239, 1.1965, 1.2733, 1.3576] +24-11-19 19:14:44 | D | best error = [ 0.5772, 0.5770, 0.5769, 0.5767, 0.5765] +24-11-19 19:14:44 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:14:44 | D | sum error = [ 1.4468, 1.5426, 1.6433, 1.7527, 1.8714] +24-11-19 19:14:44 | D | best error = [ 0.5765, 0.5764, 0.5764, 0.5764, 0.5763] +24-11-19 19:14:44 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:14:44 | D | sum error = [ 1.9932, 2.1214, 2.2619, 2.4079, 2.5603] +24-11-19 19:14:44 | D | best error = [ 0.5763, 0.5763, 0.5763, 0.5763, 0.5763] +24-11-19 19:14:44 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:14:44 | D | sum error = [ 2.7269, 2.9010, 3.0800, 3.2787, 3.4797] +24-11-19 19:14:44 | D | best error = [ 0.5763, 0.5763, 0.5763, 0.5763, 0.5763] +24-11-19 19:14:44 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:14:44 | D | sum error = [ 3.6955, 3.9234, 4.1639, 4.4187, 4.6848] +24-11-19 19:14:44 | D | best error = [ 0.5763, 0.5763, 0.5763, 0.5763, 0.5763] +24-11-19 19:14:44 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:14:44 | D | sum error = [ 4.9649, 5.2610, 5.5717, 5.9008, 6.2463] +24-11-19 19:14:44 | D | best error = [ 0.5763, 0.5763, 0.5763, 0.5763, 0.5763] +24-11-19 19:14:44 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:14:44 | D | sum error = [ 6.6072, 6.9881, 7.3871, 7.8065, 8.2451] +24-11-19 19:14:44 | D | best error = [ 0.5763, 0.5763, 0.5763, 0.5763, 0.5763] +24-11-19 19:14:44 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:14:44 | D | sum error = [ 8.7057, 9.1889, 9.6941, 10.2218, 10.7746] +24-11-19 19:14:44 | D | best error = [ 0.5763, 0.5763, 0.5763, 0.5763, 0.5763] +24-11-19 19:14:44 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:14:44 | D | sum error = [ 11.3524, 11.9564, 12.5865, 13.2442, 13.9311] +24-11-19 19:14:44 | D | best error = [ 0.5763, 0.5763, 0.5763, 0.5763, 0.5763] +24-11-19 19:14:44 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:14:44 | D | sum error = [ 14.6529, 15.4021, 16.1849, 17.0010, 17.8534] +24-11-19 19:14:44 | D | best error = [ 0.5763, 0.5763, 0.5763, 0.5763, 0.5763] +24-11-19 19:14:44 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:14:44 | D | sum error = [ 18.7398, 19.6635, 20.6246, 21.6226, 22.6618] +24-11-19 19:14:44 | D | best error = [ 0.5763, 0.5763, 0.5763, 0.5763, 0.5763] +24-11-19 19:14:44 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:14:44 | D | sum error = [ 23.7430, 24.8632, 26.0275, 27.2357, 28.4891] +24-11-19 19:14:44 | D | best error = [ 0.5763, 0.5763, 0.5763, 0.5763, 0.5763] +24-11-19 19:14:44 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:14:44 | D | sum error = [ 29.7862, 31.1309, 32.5216, 33.9585, 35.4435] +24-11-19 19:14:44 | D | best error = [ 0.5763, 0.5763, 0.5763, 0.5763, 0.5763] +24-11-19 19:14:44 | D | + error = [0.5763] +24-11-19 19:14:44 | D | - Calibrating model.layers.7.mlp.up_proj.weight +24-11-19 19:14:44 | D | + w: sint8 +24-11-19 19:14:44 | D | + x: None +24-11-19 19:14:44 | D | + y: None +24-11-19 19:14:44 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:14:44 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:14:44 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:14:44 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:14:44 | D | - range ratio = [ 1.0000] +24-11-19 19:14:44 | D | sum error = [ 5.1920] +24-11-19 19:14:44 | D | best error = [ 5.1920] +24-11-19 19:14:45 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:14:45 | D | sum error = [ 5.1498, 5.1432, 5.1692, 5.2221, 5.3232] +24-11-19 19:14:45 | D | best error = [ 4.8321, 4.6933, 4.6240, 4.5842, 4.5645] +24-11-19 19:14:45 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:14:45 | D | sum error = [ 5.4592, 5.6338, 5.8796, 6.1610, 6.4736] +24-11-19 19:14:45 | D | best error = [ 4.5555, 4.5517, 4.5506, 4.5502, 4.5501] +24-11-19 19:14:45 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:14:45 | D | sum error = [ 6.8356, 7.2765, 7.7301, 8.2413, 8.8251] +24-11-19 19:14:45 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 19:14:45 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:14:45 | D | sum error = [ 9.4562, 10.1135, 10.8458, 11.6168, 12.4611] +24-11-19 19:14:45 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 19:14:45 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:14:45 | D | sum error = [ 13.3467, 14.2924, 15.3070, 16.3903, 17.5342] +24-11-19 19:14:45 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 19:14:45 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:14:45 | D | sum error = [ 18.7518, 20.0179, 21.3823, 22.8118, 24.3243] +24-11-19 19:14:45 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 19:14:45 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:14:45 | D | sum error = [ 25.9169, 27.5959, 29.3615, 31.2257, 33.1933] +24-11-19 19:14:45 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 19:14:45 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:14:45 | D | sum error = [ 35.2522, 37.4295, 39.7044, 42.1111, 44.6416] +24-11-19 19:14:45 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 19:14:45 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:14:45 | D | sum error = [ 47.2872, 50.0625, 52.9707, 56.0307, 59.2174] +24-11-19 19:14:45 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 19:14:45 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:14:45 | D | sum error = [ 62.5661, 66.0665, 69.7374, 73.5684, 77.5554] +24-11-19 19:14:45 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 19:14:45 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:14:45 | D | sum error = [ 81.7311, 86.0991, 90.6478, 95.3981, 100.3433] +24-11-19 19:14:45 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 19:14:45 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:14:45 | D | sum error = [ 105.5078, 110.8759, 116.4620, 122.2661, 128.3248] +24-11-19 19:14:45 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 19:14:45 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:14:45 | D | sum error = [ 134.5946, 141.1160, 147.8888, 154.9135, 162.1922] +24-11-19 19:14:45 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 19:14:45 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:14:45 | D | sum error = [ 169.7329, 177.5444, 185.6345, 194.0001, 202.6577] +24-11-19 19:14:45 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 19:14:45 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:14:45 | D | sum error = [ 211.5966, 220.8346, 230.3688, 240.2066, 250.3324] +24-11-19 19:14:45 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 19:14:45 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:14:45 | D | sum error = [ 260.7892, 271.5527, 282.6357, 294.0341, 305.7573] +24-11-19 19:14:45 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 19:14:45 | D | + error = [4.5501] +24-11-19 19:14:45 | D | - Calibrating model.layers.7.mlp.gate_proj.weight +24-11-19 19:14:45 | D | + w: sint8 +24-11-19 19:14:45 | D | + x: None +24-11-19 19:14:45 | D | + y: None +24-11-19 19:14:45 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:14:45 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:14:45 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:14:45 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:14:45 | D | - range ratio = [ 1.0000] +24-11-19 19:14:45 | D | sum error = [ 5.9221] +24-11-19 19:14:45 | D | best error = [ 5.9221] +24-11-19 19:14:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:14:46 | D | sum error = [ 5.8660, 5.8524, 5.8825, 5.9468, 6.0567] +24-11-19 19:14:46 | D | best error = [ 5.5032, 5.3447, 5.2633, 5.2171, 5.1943] +24-11-19 19:14:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:14:46 | D | sum error = [ 6.2012, 6.4217, 6.6794, 6.9980, 7.3554] +24-11-19 19:14:46 | D | best error = [ 5.1832, 5.1790, 5.1776, 5.1770, 5.1770] +24-11-19 19:14:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:14:46 | D | sum error = [ 7.7938, 8.2659, 8.8199, 9.3937, 10.0526] +24-11-19 19:14:46 | D | best error = [ 5.1769, 5.1769, 5.1769, 5.1769, 5.1769] +24-11-19 19:14:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:14:46 | D | sum error = [ 10.7763, 11.5585, 12.3879, 13.2940, 14.2463] +24-11-19 19:14:46 | D | best error = [ 5.1769, 5.1769, 5.1769, 5.1769, 5.1769] +24-11-19 19:14:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:14:46 | D | sum error = [ 15.2809, 16.3902, 17.5615, 18.7878, 20.1113] +24-11-19 19:14:46 | D | best error = [ 5.1769, 5.1769, 5.1769, 5.1769, 5.1769] +24-11-19 19:14:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:14:46 | D | sum error = [ 21.5266, 23.0142, 24.6229, 26.3058, 28.0825] +24-11-19 19:14:46 | D | best error = [ 5.1769, 5.1769, 5.1769, 5.1769, 5.1769] +24-11-19 19:14:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:14:46 | D | sum error = [ 29.9975, 32.0231, 34.1273, 36.3974, 38.7792] +24-11-19 19:14:46 | D | best error = [ 5.1769, 5.1769, 5.1769, 5.1769, 5.1769] +24-11-19 19:14:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:14:46 | D | sum error = [ 41.3092, 44.0000, 46.8244, 49.8119, 52.9721] +24-11-19 19:14:46 | D | best error = [ 5.1769, 5.1769, 5.1769, 5.1769, 5.1769] +24-11-19 19:14:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:14:46 | D | sum error = [ 56.3125, 59.8579, 63.5769, 67.5156, 71.6633] +24-11-19 19:14:46 | D | best error = [ 5.1769, 5.1769, 5.1769, 5.1769, 5.1769] +24-11-19 19:14:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:14:46 | D | sum error = [ 76.0436, 80.6703, 85.5243, 90.6642, 96.0776] +24-11-19 19:14:46 | D | best error = [ 5.1769, 5.1769, 5.1769, 5.1769, 5.1769] +24-11-19 19:14:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:14:46 | D | sum error = [ 101.7709, 107.7612, 114.0737, 120.7223, 127.7257] +24-11-19 19:14:46 | D | best error = [ 5.1769, 5.1769, 5.1769, 5.1769, 5.1769] +24-11-19 19:14:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:14:46 | D | sum error = [ 135.0806, 142.7966, 150.9221, 159.4426, 168.3805] +24-11-19 19:14:46 | D | best error = [ 5.1769, 5.1769, 5.1769, 5.1769, 5.1769] +24-11-19 19:14:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:14:46 | D | sum error = [ 177.7624, 187.5724, 197.8648, 208.6298, 219.8615] +24-11-19 19:14:46 | D | best error = [ 5.1769, 5.1769, 5.1769, 5.1769, 5.1769] +24-11-19 19:14:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:14:46 | D | sum error = [ 231.5773, 243.8082, 256.5854, 269.8825, 283.7028] +24-11-19 19:14:46 | D | best error = [ 5.1769, 5.1769, 5.1769, 5.1769, 5.1769] +24-11-19 19:14:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:14:46 | D | sum error = [ 298.0777, 312.9982, 328.4922, 344.5637, 361.2095] +24-11-19 19:14:46 | D | best error = [ 5.1769, 5.1769, 5.1769, 5.1769, 5.1769] +24-11-19 19:14:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:14:46 | D | sum error = [ 378.4391, 396.2545, 414.6666, 433.6665, 453.2291] +24-11-19 19:14:46 | D | best error = [ 5.1769, 5.1769, 5.1769, 5.1769, 5.1769] +24-11-19 19:14:46 | D | + error = [5.1769] +24-11-19 19:14:46 | D | - Calibrating model.layers.7.mlp.down_proj.weight +24-11-19 19:14:46 | D | + w: sint8 +24-11-19 19:14:46 | D | + x: None +24-11-19 19:14:46 | D | + y: None +24-11-19 19:14:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:14:46 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:14:46 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:14:46 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:14:47 | D | - range ratio = [ 1.0000] +24-11-19 19:14:47 | D | sum error = [ 1.1056] +24-11-19 19:14:47 | D | best error = [ 1.1056] +24-11-19 19:14:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:14:47 | D | sum error = [ 1.0948, 1.0876, 1.0832, 1.0787, 1.0800] +24-11-19 19:14:47 | D | best error = [ 1.0685, 1.0492, 1.0366, 1.0263, 1.0187] +24-11-19 19:14:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:14:47 | D | sum error = [ 1.0857, 1.0927, 1.1053, 1.1243, 1.1482] +24-11-19 19:14:47 | D | best error = [ 1.0130, 1.0090, 1.0061, 1.0039, 1.0027] +24-11-19 19:14:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:14:47 | D | sum error = [ 1.1786, 1.2161, 1.2603, 1.3108, 1.3694] +24-11-19 19:14:47 | D | best error = [ 1.0016, 1.0009, 1.0006, 1.0003, 1.0002] +24-11-19 19:14:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:14:47 | D | sum error = [ 1.4398, 1.5148, 1.6006, 1.6960, 1.8010] +24-11-19 19:14:47 | D | best error = [ 1.0002, 1.0001, 1.0001, 1.0000, 1.0000] +24-11-19 19:14:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:14:47 | D | sum error = [ 1.9160, 2.0420, 2.1779, 2.3251, 2.4856] +24-11-19 19:14:47 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 19:14:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:14:47 | D | sum error = [ 2.6562, 2.8410, 3.0382, 3.2493, 3.4751] +24-11-19 19:14:47 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 19:14:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:14:47 | D | sum error = [ 3.7157, 3.9732, 4.2475, 4.5371, 4.8457] +24-11-19 19:14:47 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 19:14:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:14:47 | D | sum error = [ 5.1741, 5.5214, 5.8900, 6.2797, 6.6938] +24-11-19 19:14:47 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 19:14:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:14:47 | D | sum error = [ 7.1310, 7.5929, 8.0812, 8.5967, 9.1416] +24-11-19 19:14:47 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 19:14:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:14:47 | D | sum error = [ 9.7135, 10.3177, 10.9567, 11.6284, 12.3346] +24-11-19 19:14:47 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 19:14:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:14:47 | D | sum error = [ 13.0791, 13.8610, 14.6823, 15.5454, 16.4511] +24-11-19 19:14:47 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 19:14:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:14:47 | D | sum error = [ 17.4018, 18.3975, 19.4410, 20.5334, 21.6781] +24-11-19 19:14:47 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 19:14:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:14:47 | D | sum error = [ 22.8753, 24.1262, 25.4329, 26.7956, 28.2179] +24-11-19 19:14:47 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 19:14:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:14:47 | D | sum error = [ 29.7017, 31.2468, 32.8575, 34.5357, 36.2766] +24-11-19 19:14:47 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 19:14:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:14:47 | D | sum error = [ 38.0884, 39.9709, 41.9260, 43.9526, 46.0542] +24-11-19 19:14:47 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 19:14:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:14:47 | D | sum error = [ 48.2303, 50.4831, 52.8161, 55.2289, 57.7203] +24-11-19 19:14:47 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 19:14:47 | D | + error = [1.0000] +24-11-19 19:14:48 | D | - Quantizing model.layers.7.self_attn.q_proj.weight +24-11-19 19:14:49 | D | - Quantizing model.layers.7.self_attn.k_proj.weight +24-11-19 19:14:50 | D | - Quantizing model.layers.7.self_attn.v_proj.weight +24-11-19 19:14:50 | D | - Quantizing model.layers.7.self_attn.o_proj.weight +24-11-19 19:14:51 | D | - Quantizing model.layers.7.mlp.up_proj.weight +24-11-19 19:14:52 | D | - Quantizing model.layers.7.mlp.gate_proj.weight +24-11-19 19:14:53 | D | - Quantizing model.layers.7.mlp.down_proj.weight +24-11-19 19:15:02 | D | - Quantizing layer model.layers.8 +24-11-19 19:15:02 | D | - Calibrating model.layers.8.self_attn.q_proj.weight +24-11-19 19:15:02 | D | + w: sint8 +24-11-19 19:15:02 | D | + x: None +24-11-19 19:15:02 | D | + y: None +24-11-19 19:15:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:15:02 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:15:02 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:15:02 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:15:02 | D | - range ratio = [ 1.0000] +24-11-19 19:15:02 | D | sum error = [ 6.6568] +24-11-19 19:15:02 | D | best error = [ 6.6568] +24-11-19 19:15:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:15:15 | D | sum error = [ 6.7027, 6.6026, 6.7461, 6.6979, 7.1054] +24-11-19 19:15:15 | D | best error = [ 6.6568, 6.6026, 6.6026, 6.6026, 6.6026] +24-11-19 19:15:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:15:15 | D | sum error = [ 7.2053, 7.4399, 7.5464, 8.0204, 8.3461] +24-11-19 19:15:15 | D | best error = [ 6.6026, 6.6026, 6.6026, 6.6026, 6.6026] +24-11-19 19:15:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:15:15 | D | sum error = [ 8.9671, 9.6468, 10.3506, 11.0675, 12.0571] +24-11-19 19:15:15 | D | best error = [ 6.6026, 6.6026, 6.6026, 6.6026, 6.6026] +24-11-19 19:15:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:15:15 | D | sum error = [ 12.8547, 14.2223, 15.0894, 16.4606, 17.6941] +24-11-19 19:15:15 | D | best error = [ 6.6026, 6.6026, 6.6026, 6.6026, 6.6026] +24-11-19 19:15:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:15:15 | D | sum error = [ 19.4474, 20.8510, 22.6262, 24.6468, 27.0588] +24-11-19 19:15:15 | D | best error = [ 6.6026, 6.6026, 6.6026, 6.6026, 6.6026] +24-11-19 19:15:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:15:15 | D | sum error = [ 29.1888, 31.5008, 34.3754, 37.4222, 40.4444] +24-11-19 19:15:15 | D | best error = [ 6.6026, 6.6026, 6.6026, 6.6026, 6.6026] +24-11-19 19:15:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:15:15 | D | sum error = [ 43.9419, 48.0637, 51.8089, 56.0477, 60.9838] +24-11-19 19:15:15 | D | best error = [ 6.6026, 6.6026, 6.6026, 6.6026, 6.6026] +24-11-19 19:15:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:15:15 | D | sum error = [ 65.8023, 71.2440, 76.6359, 83.1781, 89.8891] +24-11-19 19:15:15 | D | best error = [ 6.6026, 6.6026, 6.6026, 6.6026, 6.6026] +24-11-19 19:15:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:15:15 | D | sum error = [ 96.9013, 104.6458, 112.8342, 121.1031, 130.4413] +24-11-19 19:15:15 | D | best error = [ 6.6026, 6.6026, 6.6026, 6.6026, 6.6026] +24-11-19 19:15:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:15:15 | D | sum error = [ 140.5297, 151.6709, 163.0762, 175.6685, 188.8534] +24-11-19 19:15:15 | D | best error = [ 6.6026, 6.6026, 6.6026, 6.6026, 6.6026] +24-11-19 19:15:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:15:15 | D | sum error = [ 203.0281, 218.3846, 234.6544, 251.7249, 270.3133] +24-11-19 19:15:15 | D | best error = [ 6.6026, 6.6026, 6.6026, 6.6026, 6.6026] +24-11-19 19:15:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:15:15 | D | sum error = [ 289.9704, 311.0696, 333.3061, 356.9647, 382.7254] +24-11-19 19:15:15 | D | best error = [ 6.6026, 6.6026, 6.6026, 6.6026, 6.6026] +24-11-19 19:15:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:15:15 | D | sum error = [ 409.4754, 438.2837, 468.9375, 502.0829, 536.7736] +24-11-19 19:15:15 | D | best error = [ 6.6026, 6.6026, 6.6026, 6.6026, 6.6026] +24-11-19 19:15:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:15:15 | D | sum error = [ 574.0705, 613.9205, 656.1231, 701.0352, 748.5425] +24-11-19 19:15:15 | D | best error = [ 6.6026, 6.6026, 6.6026, 6.6026, 6.6026] +24-11-19 19:15:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:15:15 | D | sum error = [ 798.8507, 852.0595, 908.2194, 967.2405, 1028.6116] +24-11-19 19:15:15 | D | best error = [ 6.6026, 6.6026, 6.6026, 6.6026, 6.6026] +24-11-19 19:15:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:15:15 | D | sum error = [ 1092.5453, 1159.1203, 1227.8640, 1298.5213, 1370.6639] +24-11-19 19:15:15 | D | best error = [ 6.6026, 6.6026, 6.6026, 6.6026, 6.6026] +24-11-19 19:15:15 | D | + error = [6.6026] +24-11-19 19:15:15 | D | - Calibrating model.layers.8.self_attn.k_proj.weight +24-11-19 19:15:15 | D | + w: sint8 +24-11-19 19:15:15 | D | + x: None +24-11-19 19:15:15 | D | + y: None +24-11-19 19:15:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:15:15 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:15:15 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:15:15 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:15:16 | D | - range ratio = [ 1.0000] +24-11-19 19:15:16 | D | sum error = [ 7.4562] +24-11-19 19:15:16 | D | best error = [ 7.4562] +24-11-19 19:15:28 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:15:28 | D | sum error = [ 7.4555, 7.3306, 7.2508, 7.3498, 8.0811] +24-11-19 19:15:28 | D | best error = [ 7.4555, 7.3306, 7.2508, 7.2508, 7.2508] +24-11-19 19:15:28 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:15:28 | D | sum error = [ 7.5799, 7.9949, 7.9510, 9.5577, 9.4071] +24-11-19 19:15:28 | D | best error = [ 7.2508, 7.2508, 7.2508, 7.2508, 7.2508] +24-11-19 19:15:28 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:15:28 | D | sum error = [ 9.6263, 10.3487, 10.8710, 12.6325, 12.7525] +24-11-19 19:15:28 | D | best error = [ 7.2508, 7.2508, 7.2508, 7.2508, 7.2508] +24-11-19 19:15:28 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:15:28 | D | sum error = [ 13.5666, 14.6885, 16.6453, 17.4364, 18.8285] +24-11-19 19:15:28 | D | best error = [ 7.2508, 7.2508, 7.2508, 7.2508, 7.2508] +24-11-19 19:15:28 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:15:28 | D | sum error = [ 20.0788, 21.9693, 24.0035, 25.6047, 27.3060] +24-11-19 19:15:28 | D | best error = [ 7.2508, 7.2508, 7.2508, 7.2508, 7.2508] +24-11-19 19:15:28 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:15:28 | D | sum error = [ 30.5483, 32.7097, 35.1909, 38.8904, 42.2028] +24-11-19 19:15:28 | D | best error = [ 7.2508, 7.2508, 7.2508, 7.2508, 7.2508] +24-11-19 19:15:28 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:15:28 | D | sum error = [ 45.4731, 48.4411, 53.2094, 57.4237, 61.4549] +24-11-19 19:15:28 | D | best error = [ 7.2508, 7.2508, 7.2508, 7.2508, 7.2508] +24-11-19 19:15:28 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:15:28 | D | sum error = [ 66.9344, 71.4417, 77.6806, 82.7266, 88.8758] +24-11-19 19:15:28 | D | best error = [ 7.2508, 7.2508, 7.2508, 7.2508, 7.2508] +24-11-19 19:15:28 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:15:28 | D | sum error = [ 95.4823, 102.7812, 110.6713, 119.0286, 127.4862] +24-11-19 19:15:28 | D | best error = [ 7.2508, 7.2508, 7.2508, 7.2508, 7.2508] +24-11-19 19:15:28 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:15:28 | D | sum error = [ 137.8112, 148.2254, 158.9834, 170.0650, 184.6044] +24-11-19 19:15:28 | D | best error = [ 7.2508, 7.2508, 7.2508, 7.2508, 7.2508] +24-11-19 19:15:28 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:15:28 | D | sum error = [ 198.3071, 212.5955, 229.8620, 248.8856, 266.1165] +24-11-19 19:15:28 | D | best error = [ 7.2508, 7.2508, 7.2508, 7.2508, 7.2508] +24-11-19 19:15:28 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:15:28 | D | sum error = [ 286.2495, 306.5250, 331.0419, 355.1625, 382.5287] +24-11-19 19:15:28 | D | best error = [ 7.2508, 7.2508, 7.2508, 7.2508, 7.2508] +24-11-19 19:15:28 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:15:28 | D | sum error = [ 407.9957, 443.0930, 472.3119, 507.9750, 543.1706] +24-11-19 19:15:28 | D | best error = [ 7.2508, 7.2508, 7.2508, 7.2508, 7.2508] +24-11-19 19:15:28 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:15:28 | D | sum error = [ 583.4226, 622.8522, 664.8342, 707.9251, 763.0745] +24-11-19 19:15:28 | D | best error = [ 7.2508, 7.2508, 7.2508, 7.2508, 7.2508] +24-11-19 19:15:28 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:15:28 | D | sum error = [ 811.9380, 862.5910, 921.2876, 985.0636, 1044.2370] +24-11-19 19:15:28 | D | best error = [ 7.2508, 7.2508, 7.2508, 7.2508, 7.2508] +24-11-19 19:15:28 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:15:28 | D | sum error = [ 1111.6939, 1176.7485, 1248.2151, 1321.5130, 1393.8748] +24-11-19 19:15:28 | D | best error = [ 7.2508, 7.2508, 7.2508, 7.2508, 7.2508] +24-11-19 19:15:28 | D | + error = [7.2508] +24-11-19 19:15:28 | D | - Calibrating model.layers.8.self_attn.v_proj.weight +24-11-19 19:15:28 | D | + w: sint8 +24-11-19 19:15:28 | D | + x: None +24-11-19 19:15:28 | D | + y: None +24-11-19 19:15:28 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:15:28 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:15:28 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:15:28 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:15:28 | D | - range ratio = [ 1.0000] +24-11-19 19:15:28 | D | sum error = [ 3.9345] +24-11-19 19:15:28 | D | best error = [ 3.9345] +24-11-19 19:15:28 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:15:28 | D | sum error = [ 3.8924, 3.8774, 3.8875, 3.9320, 4.0104] +24-11-19 19:15:28 | D | best error = [ 3.6512, 3.5505, 3.4997, 3.4698, 3.4534] +24-11-19 19:15:28 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:15:28 | D | sum error = [ 4.1240, 4.2451, 4.4286, 4.6280, 4.8907] +24-11-19 19:15:28 | D | best error = [ 3.4464, 3.4441, 3.4435, 3.4434, 3.4434] +24-11-19 19:15:28 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:15:28 | D | sum error = [ 5.1537, 5.4629, 5.8161, 6.2124, 6.6281] +24-11-19 19:15:28 | D | best error = [ 3.4434, 3.4434, 3.4434, 3.4434, 3.4434] +24-11-19 19:15:28 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:15:28 | D | sum error = [ 7.1002, 7.6161, 8.1568, 8.7651, 9.3817] +24-11-19 19:15:28 | D | best error = [ 3.4434, 3.4434, 3.4434, 3.4434, 3.4434] +24-11-19 19:15:28 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:15:28 | D | sum error = [ 10.0546, 10.7866, 11.5488, 12.3539, 13.2217] +24-11-19 19:15:28 | D | best error = [ 3.4434, 3.4434, 3.4434, 3.4434, 3.4434] +24-11-19 19:15:28 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:15:28 | D | sum error = [ 14.1498, 15.1210, 16.1430, 17.2317, 18.3878] +24-11-19 19:15:28 | D | best error = [ 3.4434, 3.4434, 3.4434, 3.4434, 3.4434] +24-11-19 19:15:28 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:15:28 | D | sum error = [ 19.6044, 20.8938, 22.2464, 23.6883, 25.2038] +24-11-19 19:15:28 | D | best error = [ 3.4434, 3.4434, 3.4434, 3.4434, 3.4434] +24-11-19 19:15:28 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:15:28 | D | sum error = [ 26.7949, 28.4770, 30.2608, 32.1333, 34.0959] +24-11-19 19:15:28 | D | best error = [ 3.4434, 3.4434, 3.4434, 3.4434, 3.4434] +24-11-19 19:15:28 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:15:28 | D | sum error = [ 36.1611, 38.3396, 40.6261, 43.0290, 45.5562] +24-11-19 19:15:28 | D | best error = [ 3.4434, 3.4434, 3.4434, 3.4434, 3.4434] +24-11-19 19:15:28 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:15:28 | D | sum error = [ 48.2214, 50.9974, 53.9322, 56.9947, 60.2137] +24-11-19 19:15:28 | D | best error = [ 3.4434, 3.4434, 3.4434, 3.4434, 3.4434] +24-11-19 19:15:28 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:15:28 | D | sum error = [ 63.5772, 67.1118, 70.7911, 74.6486, 78.6870] +24-11-19 19:15:28 | D | best error = [ 3.4434, 3.4434, 3.4434, 3.4434, 3.4434] +24-11-19 19:15:28 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:15:28 | D | sum error = [ 82.9053, 87.2938, 91.8889, 96.6989, 101.7258] +24-11-19 19:15:28 | D | best error = [ 3.4434, 3.4434, 3.4434, 3.4434, 3.4434] +24-11-19 19:15:28 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:15:28 | D | sum error = [ 106.9594, 112.4231, 118.1159, 124.0434, 130.2282] +24-11-19 19:15:28 | D | best error = [ 3.4434, 3.4434, 3.4434, 3.4434, 3.4434] +24-11-19 19:15:28 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:15:28 | D | sum error = [ 136.6595, 143.3382, 150.2890, 157.5103, 164.9857] +24-11-19 19:15:28 | D | best error = [ 3.4434, 3.4434, 3.4434, 3.4434, 3.4434] +24-11-19 19:15:28 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:15:28 | D | sum error = [ 172.7417, 180.7681, 189.0796, 197.6733, 206.5505] +24-11-19 19:15:28 | D | best error = [ 3.4434, 3.4434, 3.4434, 3.4434, 3.4434] +24-11-19 19:15:28 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:15:28 | D | sum error = [ 215.7408, 225.2104, 234.9755, 245.0355, 255.3930] +24-11-19 19:15:28 | D | best error = [ 3.4434, 3.4434, 3.4434, 3.4434, 3.4434] +24-11-19 19:15:28 | D | + error = [3.4434] +24-11-19 19:15:29 | D | - Calibrating model.layers.8.self_attn.o_proj.weight +24-11-19 19:15:29 | D | + w: sint8 +24-11-19 19:15:29 | D | + x: None +24-11-19 19:15:29 | D | + y: None +24-11-19 19:15:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:15:29 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:15:29 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:15:29 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:15:29 | D | - range ratio = [ 1.0000] +24-11-19 19:15:29 | D | sum error = [ 0.8097] +24-11-19 19:15:29 | D | best error = [ 0.8097] +24-11-19 19:15:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:15:29 | D | sum error = [ 0.8000, 0.7995, 0.7971, 0.8014, 0.8064] +24-11-19 19:15:29 | D | best error = [ 0.7585, 0.7360, 0.7214, 0.7120, 0.7054] +24-11-19 19:15:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:15:29 | D | sum error = [ 0.8217, 0.8379, 0.8561, 0.8853, 0.9186] +24-11-19 19:15:29 | D | best error = [ 0.7013, 0.6979, 0.6958, 0.6944, 0.6934] +24-11-19 19:15:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:15:29 | D | sum error = [ 0.9598, 1.0034, 1.0573, 1.1127, 1.1828] +24-11-19 19:15:29 | D | best error = [ 0.6927, 0.6921, 0.6918, 0.6915, 0.6913] +24-11-19 19:15:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:15:29 | D | sum error = [ 1.2529, 1.3328, 1.4174, 1.5079, 1.6082] +24-11-19 19:15:29 | D | best error = [ 0.6912, 0.6911, 0.6910, 0.6910, 0.6909] +24-11-19 19:15:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:15:29 | D | sum error = [ 1.7179, 1.8306, 1.9562, 2.0893, 2.2329] +24-11-19 19:15:29 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 19:15:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:15:29 | D | sum error = [ 2.3795, 2.5404, 2.7091, 2.8879, 3.0774] +24-11-19 19:15:29 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 19:15:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:15:29 | D | sum error = [ 3.2811, 3.4931, 3.7223, 3.9590, 4.2095] +24-11-19 19:15:29 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 19:15:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:15:29 | D | sum error = [ 4.4749, 4.7534, 5.0479, 5.3596, 5.6880] +24-11-19 19:15:29 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 19:15:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:15:29 | D | sum error = [ 6.0302, 6.3917, 6.7732, 7.1747, 7.5949] +24-11-19 19:15:29 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 19:15:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:15:29 | D | sum error = [ 8.0369, 8.5020, 8.9923, 9.5044, 10.0419] +24-11-19 19:15:29 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 19:15:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:15:29 | D | sum error = [ 10.6060, 11.1953, 11.8135, 12.4590, 13.1390] +24-11-19 19:15:29 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 19:15:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:15:29 | D | sum error = [ 13.8465, 14.5857, 15.3609, 16.1677, 17.0100] +24-11-19 19:15:29 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 19:15:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:15:29 | D | sum error = [ 17.8861, 18.8019, 19.7516, 20.7397, 21.7692] +24-11-19 19:15:29 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 19:15:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:15:29 | D | sum error = [ 22.8397, 23.9512, 25.1066, 26.3050, 27.5465] +24-11-19 19:15:29 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 19:15:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:15:29 | D | sum error = [ 28.8341, 30.1677, 31.5515, 32.9835, 34.4632] +24-11-19 19:15:29 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 19:15:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:15:29 | D | sum error = [ 35.9921, 37.5713, 39.2019, 40.8844, 42.6205] +24-11-19 19:15:29 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 19:15:29 | D | + error = [0.6909] +24-11-19 19:15:29 | D | - Calibrating model.layers.8.mlp.up_proj.weight +24-11-19 19:15:29 | D | + w: sint8 +24-11-19 19:15:29 | D | + x: None +24-11-19 19:15:29 | D | + y: None +24-11-19 19:15:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:15:29 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:15:29 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:15:29 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:15:29 | D | - range ratio = [ 1.0000] +24-11-19 19:15:29 | D | sum error = [ 5.3774] +24-11-19 19:15:29 | D | best error = [ 5.3774] +24-11-19 19:15:30 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:15:30 | D | sum error = [ 5.3321, 5.3350, 5.3543, 5.3945, 5.5054] +24-11-19 19:15:30 | D | best error = [ 5.0131, 4.8726, 4.8011, 4.7575, 4.7362] +24-11-19 19:15:30 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:15:30 | D | sum error = [ 5.6526, 5.8394, 6.0769, 6.3601, 6.6943] +24-11-19 19:15:30 | D | best error = [ 4.7259, 4.7212, 4.7197, 4.7195, 4.7194] +24-11-19 19:15:30 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:15:30 | D | sum error = [ 7.0792, 7.5252, 7.9922, 8.5439, 9.1426] +24-11-19 19:15:30 | D | best error = [ 4.7194, 4.7194, 4.7194, 4.7194, 4.7194] +24-11-19 19:15:30 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:15:30 | D | sum error = [ 9.7790, 10.4757, 11.2244, 12.0130, 12.9018] +24-11-19 19:15:30 | D | best error = [ 4.7194, 4.7194, 4.7194, 4.7194, 4.7194] +24-11-19 19:15:30 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:15:30 | D | sum error = [ 13.8252, 14.7987, 15.8302, 16.9527, 18.1382] +24-11-19 19:15:30 | D | best error = [ 4.7194, 4.7194, 4.7194, 4.7194, 4.7194] +24-11-19 19:15:30 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:15:30 | D | sum error = [ 19.3876, 20.7025, 22.1012, 23.5768, 25.1250] +24-11-19 19:15:30 | D | best error = [ 4.7194, 4.7194, 4.7194, 4.7194, 4.7194] +24-11-19 19:15:30 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:15:30 | D | sum error = [ 26.7780, 28.5053, 30.3337, 32.2628, 34.2885] +24-11-19 19:15:30 | D | best error = [ 4.7194, 4.7194, 4.7194, 4.7194, 4.7194] +24-11-19 19:15:30 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:15:30 | D | sum error = [ 36.4273, 38.6807, 41.0496, 43.5424, 46.1706] +24-11-19 19:15:30 | D | best error = [ 4.7194, 4.7194, 4.7194, 4.7194, 4.7194] +24-11-19 19:15:30 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:15:30 | D | sum error = [ 48.9080, 51.7838, 54.8086, 57.9861, 61.3054] +24-11-19 19:15:30 | D | best error = [ 4.7194, 4.7194, 4.7194, 4.7194, 4.7194] +24-11-19 19:15:30 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:15:30 | D | sum error = [ 64.7939, 68.4409, 72.2606, 76.2755, 80.4812] +24-11-19 19:15:30 | D | best error = [ 4.7194, 4.7194, 4.7194, 4.7194, 4.7194] +24-11-19 19:15:30 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:15:30 | D | sum error = [ 84.8720, 89.4504, 94.2392, 99.2448, 104.4621] +24-11-19 19:15:30 | D | best error = [ 4.7194, 4.7194, 4.7194, 4.7194, 4.7194] +24-11-19 19:15:30 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:15:30 | D | sum error = [ 109.9073, 115.5756, 121.4897, 127.6396, 134.0398] +24-11-19 19:15:30 | D | best error = [ 4.7194, 4.7194, 4.7194, 4.7194, 4.7194] +24-11-19 19:15:30 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:15:30 | D | sum error = [ 140.7111, 147.6458, 154.8530, 162.3424, 170.1160] +24-11-19 19:15:30 | D | best error = [ 4.7194, 4.7194, 4.7194, 4.7194, 4.7194] +24-11-19 19:15:30 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:15:30 | D | sum error = [ 178.1846, 186.5521, 195.2340, 204.2228, 213.5341] +24-11-19 19:15:30 | D | best error = [ 4.7194, 4.7194, 4.7194, 4.7194, 4.7194] +24-11-19 19:15:30 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:15:30 | D | sum error = [ 223.1589, 233.1220, 243.4057, 254.0308, 264.9829] +24-11-19 19:15:30 | D | best error = [ 4.7194, 4.7194, 4.7194, 4.7194, 4.7194] +24-11-19 19:15:30 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:15:30 | D | sum error = [ 276.2891, 287.9317, 299.9300, 312.2731, 324.9833] +24-11-19 19:15:30 | D | best error = [ 4.7194, 4.7194, 4.7194, 4.7194, 4.7194] +24-11-19 19:15:30 | D | + error = [4.7194] +24-11-19 19:15:30 | D | - Calibrating model.layers.8.mlp.gate_proj.weight +24-11-19 19:15:30 | D | + w: sint8 +24-11-19 19:15:30 | D | + x: None +24-11-19 19:15:30 | D | + y: None +24-11-19 19:15:30 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:15:30 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:15:31 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:15:31 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:15:31 | D | - range ratio = [ 1.0000] +24-11-19 19:15:31 | D | sum error = [ 5.9224] +24-11-19 19:15:31 | D | best error = [ 5.9224] +24-11-19 19:15:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:15:32 | D | sum error = [ 5.8853, 5.8684, 5.8974, 5.9719, 6.0745] +24-11-19 19:15:32 | D | best error = [ 5.5284, 5.3735, 5.2927, 5.2479, 5.2242] +24-11-19 19:15:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:15:32 | D | sum error = [ 6.2319, 6.4435, 6.7129, 7.0224, 7.4131] +24-11-19 19:15:32 | D | best error = [ 5.2130, 5.2084, 5.2067, 5.2062, 5.2061] +24-11-19 19:15:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:15:32 | D | sum error = [ 7.8405, 8.2981, 8.8501, 9.4462, 10.1134] +24-11-19 19:15:32 | D | best error = [ 5.2061, 5.2061, 5.2061, 5.2061, 5.2061] +24-11-19 19:15:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:15:32 | D | sum error = [ 10.8439, 11.6139, 12.4487, 13.3603, 14.3226] +24-11-19 19:15:32 | D | best error = [ 5.2061, 5.2061, 5.2061, 5.2061, 5.2061] +24-11-19 19:15:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:15:32 | D | sum error = [ 15.3510, 16.4837, 17.6714, 18.9109, 20.2573] +24-11-19 19:15:32 | D | best error = [ 5.2061, 5.2061, 5.2061, 5.2061, 5.2061] +24-11-19 19:15:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:15:32 | D | sum error = [ 21.7038, 23.2126, 24.8293, 26.5215, 28.3555] +24-11-19 19:15:32 | D | best error = [ 5.2061, 5.2061, 5.2061, 5.2061, 5.2061] +24-11-19 19:15:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:15:32 | D | sum error = [ 30.2848, 32.3119, 34.4788, 36.7647, 39.1836] +24-11-19 19:15:32 | D | best error = [ 5.2061, 5.2061, 5.2061, 5.2061, 5.2061] +24-11-19 19:15:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:15:32 | D | sum error = [ 41.7482, 44.4484, 47.3123, 50.3338, 53.5254] +24-11-19 19:15:32 | D | best error = [ 5.2061, 5.2061, 5.2061, 5.2061, 5.2061] +24-11-19 19:15:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:15:32 | D | sum error = [ 56.9280, 60.5082, 64.2801, 68.2668, 72.4800] +24-11-19 19:15:32 | D | best error = [ 5.2061, 5.2061, 5.2061, 5.2061, 5.2061] +24-11-19 19:15:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:15:32 | D | sum error = [ 76.9084, 81.6137, 86.5466, 91.7697, 97.2710] +24-11-19 19:15:32 | D | best error = [ 5.2061, 5.2061, 5.2061, 5.2061, 5.2061] +24-11-19 19:15:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:15:32 | D | sum error = [ 103.0761, 109.1871, 115.5881, 122.3347, 129.4301] +24-11-19 19:15:32 | D | best error = [ 5.2061, 5.2061, 5.2061, 5.2061, 5.2061] +24-11-19 19:15:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:15:32 | D | sum error = [ 136.8622, 144.6860, 152.8867, 161.5080, 170.5360] +24-11-19 19:15:32 | D | best error = [ 5.2061, 5.2061, 5.2061, 5.2061, 5.2061] +24-11-19 19:15:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:15:32 | D | sum error = [ 180.0041, 189.8963, 200.2564, 211.0675, 222.3633] +24-11-19 19:15:32 | D | best error = [ 5.2061, 5.2061, 5.2061, 5.2061, 5.2061] +24-11-19 19:15:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:15:32 | D | sum error = [ 234.1720, 246.4642, 259.2908, 272.6553, 286.5567] +24-11-19 19:15:32 | D | best error = [ 5.2061, 5.2061, 5.2061, 5.2061, 5.2061] +24-11-19 19:15:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:15:32 | D | sum error = [ 300.9770, 315.9676, 331.5106, 347.6509, 364.3246] +24-11-19 19:15:32 | D | best error = [ 5.2061, 5.2061, 5.2061, 5.2061, 5.2061] +24-11-19 19:15:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:15:32 | D | sum error = [ 381.5986, 399.4342, 417.8461, 436.8476, 456.4322] +24-11-19 19:15:32 | D | best error = [ 5.2061, 5.2061, 5.2061, 5.2061, 5.2061] +24-11-19 19:15:32 | D | + error = [5.2061] +24-11-19 19:15:32 | D | - Calibrating model.layers.8.mlp.down_proj.weight +24-11-19 19:15:32 | D | + w: sint8 +24-11-19 19:15:32 | D | + x: None +24-11-19 19:15:32 | D | + y: None +24-11-19 19:15:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:15:32 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:15:32 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:15:32 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:15:32 | D | - range ratio = [ 1.0000] +24-11-19 19:15:32 | D | sum error = [ 1.2621] +24-11-19 19:15:32 | D | best error = [ 1.2621] +24-11-19 19:15:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:15:33 | D | sum error = [ 1.2511, 1.2410, 1.2354, 1.2296, 1.2295] +24-11-19 19:15:33 | D | best error = [ 1.2153, 1.1890, 1.1711, 1.1578, 1.1479] +24-11-19 19:15:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:15:33 | D | sum error = [ 1.2362, 1.2419, 1.2569, 1.2740, 1.3011] +24-11-19 19:15:33 | D | best error = [ 1.1411, 1.1357, 1.1322, 1.1298, 1.1283] +24-11-19 19:15:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:15:33 | D | sum error = [ 1.3331, 1.3709, 1.4173, 1.4760, 1.5384] +24-11-19 19:15:33 | D | best error = [ 1.1273, 1.1264, 1.1260, 1.1257, 1.1256] +24-11-19 19:15:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:15:33 | D | sum error = [ 1.6121, 1.6956, 1.7865, 1.8906, 2.0040] +24-11-19 19:15:33 | D | best error = [ 1.1255, 1.1255, 1.1255, 1.1255, 1.1254] +24-11-19 19:15:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:15:33 | D | sum error = [ 2.1276, 2.2643, 2.4096, 2.5702, 2.7452] +24-11-19 19:15:33 | D | best error = [ 1.1254, 1.1254, 1.1254, 1.1254, 1.1254] +24-11-19 19:15:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:15:33 | D | sum error = [ 2.9298, 3.1302, 3.3440, 3.5728, 3.8185] +24-11-19 19:15:33 | D | best error = [ 1.1254, 1.1254, 1.1254, 1.1254, 1.1254] +24-11-19 19:15:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:15:33 | D | sum error = [ 4.0812, 4.3603, 4.6612, 4.9759, 5.3143] +24-11-19 19:15:33 | D | best error = [ 1.1254, 1.1254, 1.1254, 1.1254, 1.1254] +24-11-19 19:15:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:15:33 | D | sum error = [ 5.6716, 6.0509, 6.4553, 6.8815, 7.3322] +24-11-19 19:15:33 | D | best error = [ 1.1254, 1.1254, 1.1254, 1.1254, 1.1254] +24-11-19 19:15:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:15:33 | D | sum error = [ 7.8094, 8.3163, 8.8510, 9.4148, 10.0100] +24-11-19 19:15:33 | D | best error = [ 1.1254, 1.1254, 1.1254, 1.1254, 1.1254] +24-11-19 19:15:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:15:33 | D | sum error = [ 10.6377, 11.2999, 11.9976, 12.7324, 13.5058] +24-11-19 19:15:33 | D | best error = [ 1.1254, 1.1254, 1.1254, 1.1254, 1.1254] +24-11-19 19:15:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:15:33 | D | sum error = [ 14.3175, 15.1729, 16.0687, 17.0116, 17.9998] +24-11-19 19:15:33 | D | best error = [ 1.1254, 1.1254, 1.1254, 1.1254, 1.1254] +24-11-19 19:15:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:15:33 | D | sum error = [ 19.0354, 20.1201, 21.2562, 22.4459, 23.6911] +24-11-19 19:15:33 | D | best error = [ 1.1254, 1.1254, 1.1254, 1.1254, 1.1254] +24-11-19 19:15:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:15:33 | D | sum error = [ 24.9934, 26.3545, 27.7762, 29.2617, 30.8110] +24-11-19 19:15:33 | D | best error = [ 1.1254, 1.1254, 1.1254, 1.1254, 1.1254] +24-11-19 19:15:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:15:33 | D | sum error = [ 32.4270, 34.1128, 35.8677, 37.6992, 39.5972] +24-11-19 19:15:33 | D | best error = [ 1.1254, 1.1254, 1.1254, 1.1254, 1.1254] +24-11-19 19:15:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:15:33 | D | sum error = [ 41.5752, 43.6314, 45.7679, 47.9849, 50.2870] +24-11-19 19:15:33 | D | best error = [ 1.1254, 1.1254, 1.1254, 1.1254, 1.1254] +24-11-19 19:15:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:15:33 | D | sum error = [ 52.6759, 55.1512, 57.7184, 60.3760, 63.1260] +24-11-19 19:15:33 | D | best error = [ 1.1254, 1.1254, 1.1254, 1.1254, 1.1254] +24-11-19 19:15:33 | D | + error = [1.1254] +24-11-19 19:15:33 | D | - Quantizing model.layers.8.self_attn.q_proj.weight +24-11-19 19:15:34 | D | - Quantizing model.layers.8.self_attn.k_proj.weight +24-11-19 19:15:35 | D | - Quantizing model.layers.8.self_attn.v_proj.weight +24-11-19 19:15:36 | D | - Quantizing model.layers.8.self_attn.o_proj.weight +24-11-19 19:15:37 | D | - Quantizing model.layers.8.mlp.up_proj.weight +24-11-19 19:15:38 | D | - Quantizing model.layers.8.mlp.gate_proj.weight +24-11-19 19:15:39 | D | - Quantizing model.layers.8.mlp.down_proj.weight +24-11-19 19:15:48 | D | - Quantizing layer model.layers.9 +24-11-19 19:15:48 | D | - Calibrating model.layers.9.self_attn.q_proj.weight +24-11-19 19:15:48 | D | + w: sint8 +24-11-19 19:15:48 | D | + x: None +24-11-19 19:15:48 | D | + y: None +24-11-19 19:15:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:15:48 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:15:48 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:15:48 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:15:48 | D | - range ratio = [ 1.0000] +24-11-19 19:15:48 | D | sum error = [ 7.4294] +24-11-19 19:15:48 | D | best error = [ 7.4294] +24-11-19 19:16:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:16:01 | D | sum error = [ 7.5192, 7.4398, 7.4554, 7.6639, 7.6646] +24-11-19 19:16:01 | D | best error = [ 7.4294, 7.4294, 7.4294, 7.4294, 7.4294] +24-11-19 19:16:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:16:01 | D | sum error = [ 7.9599, 8.2195, 8.4226, 8.7082, 9.5521] +24-11-19 19:16:01 | D | best error = [ 7.4294, 7.4294, 7.4294, 7.4294, 7.4294] +24-11-19 19:16:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:16:01 | D | sum error = [ 10.0537, 10.4887, 11.2105, 12.0819, 13.0146] +24-11-19 19:16:01 | D | best error = [ 7.4294, 7.4294, 7.4294, 7.4294, 7.4294] +24-11-19 19:16:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:16:01 | D | sum error = [ 13.8575, 14.8776, 16.3062, 17.5908, 18.9363] +24-11-19 19:16:01 | D | best error = [ 7.4294, 7.4294, 7.4294, 7.4294, 7.4294] +24-11-19 19:16:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:16:01 | D | sum error = [ 20.5365, 22.0076, 23.9179, 25.9892, 28.3062] +24-11-19 19:16:01 | D | best error = [ 7.4294, 7.4294, 7.4294, 7.4294, 7.4294] +24-11-19 19:16:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:16:01 | D | sum error = [ 30.5105, 33.0572, 35.7357, 38.6066, 41.6598] +24-11-19 19:16:01 | D | best error = [ 7.4294, 7.4294, 7.4294, 7.4294, 7.4294] +24-11-19 19:16:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:16:01 | D | sum error = [ 45.2105, 48.5165, 52.5641, 56.7420, 61.4608] +24-11-19 19:16:01 | D | best error = [ 7.4294, 7.4294, 7.4294, 7.4294, 7.4294] +24-11-19 19:16:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:16:01 | D | sum error = [ 66.3178, 71.3711, 77.0664, 83.0792, 89.9654] +24-11-19 19:16:01 | D | best error = [ 7.4294, 7.4294, 7.4294, 7.4294, 7.4294] +24-11-19 19:16:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:16:01 | D | sum error = [ 96.9366, 104.4459, 112.4716, 121.5973, 130.6872] +24-11-19 19:16:01 | D | best error = [ 7.4294, 7.4294, 7.4294, 7.4294, 7.4294] +24-11-19 19:16:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:16:01 | D | sum error = [ 140.7940, 151.5746, 163.3019, 175.8614, 188.9633] +24-11-19 19:16:01 | D | best error = [ 7.4294, 7.4294, 7.4294, 7.4294, 7.4294] +24-11-19 19:16:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:16:01 | D | sum error = [ 203.1664, 218.3153, 234.6297, 251.6789, 270.0897] +24-11-19 19:16:01 | D | best error = [ 7.4294, 7.4294, 7.4294, 7.4294, 7.4294] +24-11-19 19:16:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:16:01 | D | sum error = [ 289.9166, 311.2142, 334.0901, 358.6020, 385.1249] +24-11-19 19:16:01 | D | best error = [ 7.4294, 7.4294, 7.4294, 7.4294, 7.4294] +24-11-19 19:16:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:16:01 | D | sum error = [ 413.4448, 443.7694, 476.2275, 511.0145, 548.7447] +24-11-19 19:16:01 | D | best error = [ 7.4294, 7.4294, 7.4294, 7.4294, 7.4294] +24-11-19 19:16:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:16:01 | D | sum error = [ 588.5262, 631.6568, 677.5260, 726.8635, 779.3777] +24-11-19 19:16:01 | D | best error = [ 7.4294, 7.4294, 7.4294, 7.4294, 7.4294] +24-11-19 19:16:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:16:01 | D | sum error = [ 836.1264, 896.3895, 960.4735, 1028.5078, 1100.6559] +24-11-19 19:16:01 | D | best error = [ 7.4294, 7.4294, 7.4294, 7.4294, 7.4294] +24-11-19 19:16:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:16:01 | D | sum error = [ 1176.4046, 1255.6562, 1338.0210, 1423.3582, 1510.6942] +24-11-19 19:16:01 | D | best error = [ 7.4294, 7.4294, 7.4294, 7.4294, 7.4294] +24-11-19 19:16:01 | D | + error = [7.4294] +24-11-19 19:16:01 | D | - Calibrating model.layers.9.self_attn.k_proj.weight +24-11-19 19:16:01 | D | + w: sint8 +24-11-19 19:16:01 | D | + x: None +24-11-19 19:16:01 | D | + y: None +24-11-19 19:16:01 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:16:01 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:16:01 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:16:01 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:16:01 | D | - range ratio = [ 1.0000] +24-11-19 19:16:01 | D | sum error = [ 8.3650] +24-11-19 19:16:01 | D | best error = [ 8.3650] +24-11-19 19:16:14 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:16:14 | D | sum error = [ 7.5902, 7.5797, 8.0061, 7.7352, 8.0941] +24-11-19 19:16:14 | D | best error = [ 7.5902, 7.5797, 7.5797, 7.5797, 7.5797] +24-11-19 19:16:14 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:16:14 | D | sum error = [ 8.4721, 8.5309, 9.0063, 9.3398, 9.9654] +24-11-19 19:16:14 | D | best error = [ 7.5797, 7.5797, 7.5797, 7.5797, 7.5797] +24-11-19 19:16:14 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:16:14 | D | sum error = [ 10.5713, 11.5230, 12.2167, 13.2079, 13.7670] +24-11-19 19:16:14 | D | best error = [ 7.5797, 7.5797, 7.5797, 7.5797, 7.5797] +24-11-19 19:16:14 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:16:14 | D | sum error = [ 15.0382, 16.1540, 18.0755, 18.7368, 20.4862] +24-11-19 19:16:14 | D | best error = [ 7.5797, 7.5797, 7.5797, 7.5797, 7.5797] +24-11-19 19:16:14 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:16:14 | D | sum error = [ 22.3514, 24.1148, 26.4923, 28.5097, 31.3675] +24-11-19 19:16:14 | D | best error = [ 7.5797, 7.5797, 7.5797, 7.5797, 7.5797] +24-11-19 19:16:14 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:16:14 | D | sum error = [ 33.9250, 35.7217, 38.9696, 42.9014, 45.4920] +24-11-19 19:16:14 | D | best error = [ 7.5797, 7.5797, 7.5797, 7.5797, 7.5797] +24-11-19 19:16:14 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:16:14 | D | sum error = [ 48.8105, 53.2336, 57.3843, 61.0604, 65.9029] +24-11-19 19:16:14 | D | best error = [ 7.5797, 7.5797, 7.5797, 7.5797, 7.5797] +24-11-19 19:16:14 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:16:14 | D | sum error = [ 71.8185, 76.5735, 82.5975, 89.6132, 96.7789] +24-11-19 19:16:14 | D | best error = [ 7.5797, 7.5797, 7.5797, 7.5797, 7.5797] +24-11-19 19:16:14 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:16:14 | D | sum error = [ 103.8037, 112.0585, 120.4080, 130.7610, 140.1875] +24-11-19 19:16:14 | D | best error = [ 7.5797, 7.5797, 7.5797, 7.5797, 7.5797] +24-11-19 19:16:14 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:16:14 | D | sum error = [ 151.4617, 162.6274, 175.5439, 189.5339, 202.6955] +24-11-19 19:16:14 | D | best error = [ 7.5797, 7.5797, 7.5797, 7.5797, 7.5797] +24-11-19 19:16:14 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:16:14 | D | sum error = [ 218.1367, 232.9140, 249.3803, 267.7505, 287.6535] +24-11-19 19:16:14 | D | best error = [ 7.5797, 7.5797, 7.5797, 7.5797, 7.5797] +24-11-19 19:16:14 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:16:14 | D | sum error = [ 308.3870, 330.6389, 355.7312, 379.3327, 407.8690] +24-11-19 19:16:14 | D | best error = [ 7.5797, 7.5797, 7.5797, 7.5797, 7.5797] +24-11-19 19:16:14 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:16:14 | D | sum error = [ 436.3086, 467.9511, 500.3007, 535.7919, 573.1247] +24-11-19 19:16:14 | D | best error = [ 7.5797, 7.5797, 7.5797, 7.5797, 7.5797] +24-11-19 19:16:14 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:16:14 | D | sum error = [ 612.6517, 653.4589, 700.3955, 749.0009, 802.6286] +24-11-19 19:16:14 | D | best error = [ 7.5797, 7.5797, 7.5797, 7.5797, 7.5797] +24-11-19 19:16:14 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:16:14 | D | sum error = [ 857.1658, 915.5947, 979.5129, 1046.1636, 1115.1090] +24-11-19 19:16:14 | D | best error = [ 7.5797, 7.5797, 7.5797, 7.5797, 7.5797] +24-11-19 19:16:14 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:16:14 | D | sum error = [ 1189.3919, 1263.6253, 1345.8251, 1428.1338, 1512.0490] +24-11-19 19:16:14 | D | best error = [ 7.5797, 7.5797, 7.5797, 7.5797, 7.5797] +24-11-19 19:16:14 | D | + error = [7.5797] +24-11-19 19:16:14 | D | - Calibrating model.layers.9.self_attn.v_proj.weight +24-11-19 19:16:14 | D | + w: sint8 +24-11-19 19:16:14 | D | + x: None +24-11-19 19:16:14 | D | + y: None +24-11-19 19:16:14 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:16:14 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:16:14 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:16:14 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:16:14 | D | - range ratio = [ 1.0000] +24-11-19 19:16:14 | D | sum error = [ 4.1009] +24-11-19 19:16:14 | D | best error = [ 4.1009] +24-11-19 19:16:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:16:15 | D | sum error = [ 4.0545, 4.0667, 4.0656, 4.1177, 4.1878] +24-11-19 19:16:15 | D | best error = [ 3.8250, 3.7304, 3.6784, 3.6505, 3.6345] +24-11-19 19:16:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:16:15 | D | sum error = [ 4.2955, 4.4417, 4.6286, 4.8513, 5.1077] +24-11-19 19:16:15 | D | best error = [ 3.6277, 3.6244, 3.6230, 3.6227, 3.6227] +24-11-19 19:16:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:16:15 | D | sum error = [ 5.3818, 5.7390, 6.1032, 6.5147, 6.9541] +24-11-19 19:16:15 | D | best error = [ 3.6227, 3.6227, 3.6227, 3.6227, 3.6227] +24-11-19 19:16:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:16:15 | D | sum error = [ 7.4458, 7.9870, 8.5427, 9.1588, 9.8104] +24-11-19 19:16:15 | D | best error = [ 3.6227, 3.6227, 3.6227, 3.6227, 3.6227] +24-11-19 19:16:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:16:15 | D | sum error = [ 10.5238, 11.2662, 12.0608, 12.8952, 13.7979] +24-11-19 19:16:15 | D | best error = [ 3.6227, 3.6227, 3.6227, 3.6227, 3.6227] +24-11-19 19:16:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:16:15 | D | sum error = [ 14.7601, 15.7644, 16.8401, 17.9784, 19.1675] +24-11-19 19:16:15 | D | best error = [ 3.6227, 3.6227, 3.6227, 3.6227, 3.6227] +24-11-19 19:16:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:16:15 | D | sum error = [ 20.4468, 21.7907, 23.2136, 24.6886, 26.2664] +24-11-19 19:16:15 | D | best error = [ 3.6227, 3.6227, 3.6227, 3.6227, 3.6227] +24-11-19 19:16:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:16:15 | D | sum error = [ 27.9118, 29.6726, 31.5099, 33.4359, 35.4694] +24-11-19 19:16:15 | D | best error = [ 3.6227, 3.6227, 3.6227, 3.6227, 3.6227] +24-11-19 19:16:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:16:15 | D | sum error = [ 37.6122, 39.8586, 42.2342, 44.7195, 47.3275] +24-11-19 19:16:15 | D | best error = [ 3.6227, 3.6227, 3.6227, 3.6227, 3.6227] +24-11-19 19:16:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:16:15 | D | sum error = [ 50.0815, 52.9639, 55.9965, 59.1856, 62.5131] +24-11-19 19:16:15 | D | best error = [ 3.6227, 3.6227, 3.6227, 3.6227, 3.6227] +24-11-19 19:16:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:16:15 | D | sum error = [ 66.0166, 69.6752, 73.5065, 77.5305, 81.7247] +24-11-19 19:16:15 | D | best error = [ 3.6227, 3.6227, 3.6227, 3.6227, 3.6227] +24-11-19 19:16:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:16:15 | D | sum error = [ 86.0994, 90.6752, 95.4540, 100.4581, 105.6764] +24-11-19 19:16:15 | D | best error = [ 3.6227, 3.6227, 3.6227, 3.6227, 3.6227] +24-11-19 19:16:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:16:15 | D | sum error = [ 111.1109, 116.7686, 122.6485, 128.7622, 135.1357] +24-11-19 19:16:15 | D | best error = [ 3.6227, 3.6227, 3.6227, 3.6227, 3.6227] +24-11-19 19:16:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:16:15 | D | sum error = [ 141.7569, 148.6388, 155.7773, 163.1991, 170.8677] +24-11-19 19:16:15 | D | best error = [ 3.6227, 3.6227, 3.6227, 3.6227, 3.6227] +24-11-19 19:16:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:16:15 | D | sum error = [ 178.8272, 187.0738, 195.5992, 204.4246, 213.5477] +24-11-19 19:16:15 | D | best error = [ 3.6227, 3.6227, 3.6227, 3.6227, 3.6227] +24-11-19 19:16:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:16:15 | D | sum error = [ 222.9685, 232.6832, 242.6998, 253.0152, 263.6432] +24-11-19 19:16:15 | D | best error = [ 3.6227, 3.6227, 3.6227, 3.6227, 3.6227] +24-11-19 19:16:15 | D | + error = [3.6227] +24-11-19 19:16:15 | D | - Calibrating model.layers.9.self_attn.o_proj.weight +24-11-19 19:16:15 | D | + w: sint8 +24-11-19 19:16:15 | D | + x: None +24-11-19 19:16:15 | D | + y: None +24-11-19 19:16:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:16:15 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:16:15 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:16:15 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:16:15 | D | - range ratio = [ 1.0000] +24-11-19 19:16:15 | D | sum error = [ 0.9777] +24-11-19 19:16:15 | D | best error = [ 0.9777] +24-11-19 19:16:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:16:15 | D | sum error = [ 0.9669, 0.9611, 0.9568, 0.9630, 0.9680] +24-11-19 19:16:15 | D | best error = [ 0.9212, 0.8939, 0.8770, 0.8658, 0.8583] +24-11-19 19:16:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:16:15 | D | sum error = [ 0.9800, 0.9952, 1.0202, 1.0479, 1.0820] +24-11-19 19:16:15 | D | best error = [ 0.8528, 0.8488, 0.8460, 0.8439, 0.8423] +24-11-19 19:16:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:16:15 | D | sum error = [ 1.1219, 1.1696, 1.2279, 1.2907, 1.3589] +24-11-19 19:16:15 | D | best error = [ 0.8409, 0.8398, 0.8390, 0.8382, 0.8376] +24-11-19 19:16:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:16:15 | D | sum error = [ 1.4398, 1.5251, 1.6176, 1.7219, 1.8313] +24-11-19 19:16:15 | D | best error = [ 0.8372, 0.8368, 0.8366, 0.8364, 0.8363] +24-11-19 19:16:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:16:15 | D | sum error = [ 1.9512, 2.0795, 2.2216, 2.3631, 2.5200] +24-11-19 19:16:15 | D | best error = [ 0.8362, 0.8362, 0.8361, 0.8361, 0.8361] +24-11-19 19:16:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:16:15 | D | sum error = [ 2.6872, 2.8630, 3.0543, 3.2520, 3.4660] +24-11-19 19:16:15 | D | best error = [ 0.8361, 0.8361, 0.8360, 0.8360, 0.8360] +24-11-19 19:16:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:16:15 | D | sum error = [ 3.6872, 3.9279, 4.1803, 4.4490, 4.7305] +24-11-19 19:16:15 | D | best error = [ 0.8360, 0.8360, 0.8360, 0.8360, 0.8360] +24-11-19 19:16:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:16:15 | D | sum error = [ 5.0257, 5.3404, 5.6723, 6.0198, 6.3872] +24-11-19 19:16:15 | D | best error = [ 0.8360, 0.8360, 0.8360, 0.8360, 0.8360] +24-11-19 19:16:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:16:15 | D | sum error = [ 6.7751, 7.1805, 7.6078, 8.0591, 8.5284] +24-11-19 19:16:15 | D | best error = [ 0.8360, 0.8360, 0.8360, 0.8360, 0.8360] +24-11-19 19:16:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:16:15 | D | sum error = [ 9.0259, 9.5437, 10.0891, 10.6585, 11.2584] +24-11-19 19:16:15 | D | best error = [ 0.8360, 0.8360, 0.8360, 0.8360, 0.8360] +24-11-19 19:16:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:16:15 | D | sum error = [ 11.8884, 12.5436, 13.2341, 13.9525, 14.7069] +24-11-19 19:16:15 | D | best error = [ 0.8360, 0.8360, 0.8360, 0.8360, 0.8360] +24-11-19 19:16:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:16:15 | D | sum error = [ 15.4952, 16.3206, 17.1818, 18.0822, 19.0204] +24-11-19 19:16:15 | D | best error = [ 0.8360, 0.8360, 0.8360, 0.8360, 0.8360] +24-11-19 19:16:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:16:15 | D | sum error = [ 20.0012, 21.0221, 22.0865, 23.1989, 24.3570] +24-11-19 19:16:15 | D | best error = [ 0.8360, 0.8360, 0.8360, 0.8360, 0.8360] +24-11-19 19:16:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:16:15 | D | sum error = [ 25.5618, 26.8140, 28.1166, 29.4665, 30.8684] +24-11-19 19:16:15 | D | best error = [ 0.8360, 0.8360, 0.8360, 0.8360, 0.8360] +24-11-19 19:16:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:16:15 | D | sum error = [ 32.3246, 33.8359, 35.4034, 37.0274, 38.7120] +24-11-19 19:16:15 | D | best error = [ 0.8360, 0.8360, 0.8360, 0.8360, 0.8360] +24-11-19 19:16:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:16:15 | D | sum error = [ 40.4570, 42.2631, 44.1309, 46.0633, 48.0593] +24-11-19 19:16:15 | D | best error = [ 0.8360, 0.8360, 0.8360, 0.8360, 0.8360] +24-11-19 19:16:15 | D | + error = [0.8360] +24-11-19 19:16:15 | D | - Calibrating model.layers.9.mlp.up_proj.weight +24-11-19 19:16:15 | D | + w: sint8 +24-11-19 19:16:15 | D | + x: None +24-11-19 19:16:15 | D | + y: None +24-11-19 19:16:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:16:15 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:16:16 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:16:16 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:16:16 | D | - range ratio = [ 1.0000] +24-11-19 19:16:16 | D | sum error = [ 5.5466] +24-11-19 19:16:16 | D | best error = [ 5.5466] +24-11-19 19:16:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:16:17 | D | sum error = [ 5.4913, 5.4791, 5.5003, 5.5605, 5.6675] +24-11-19 19:16:17 | D | best error = [ 5.1787, 5.0374, 4.9624, 4.9215, 4.9002] +24-11-19 19:16:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:16:17 | D | sum error = [ 5.8181, 5.9876, 6.2359, 6.5250, 6.8830] +24-11-19 19:16:17 | D | best error = [ 4.8915, 4.8868, 4.8854, 4.8849, 4.8849] +24-11-19 19:16:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:16:17 | D | sum error = [ 7.2777, 7.7256, 8.2077, 8.7731, 9.3781] +24-11-19 19:16:17 | D | best error = [ 4.8849, 4.8849, 4.8849, 4.8849, 4.8849] +24-11-19 19:16:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:16:17 | D | sum error = [ 10.0320, 10.7637, 11.5316, 12.3480, 13.2424] +24-11-19 19:16:17 | D | best error = [ 4.8849, 4.8849, 4.8849, 4.8849, 4.8849] +24-11-19 19:16:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:16:17 | D | sum error = [ 14.2062, 15.2148, 16.2720, 17.4197, 18.6321] +24-11-19 19:16:17 | D | best error = [ 4.8849, 4.8849, 4.8849, 4.8849, 4.8849] +24-11-19 19:16:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:16:17 | D | sum error = [ 19.9299, 21.2893, 22.7330, 24.2651, 25.8743] +24-11-19 19:16:17 | D | best error = [ 4.8849, 4.8849, 4.8849, 4.8849, 4.8849] +24-11-19 19:16:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:16:17 | D | sum error = [ 27.5724, 29.3725, 31.2681, 33.2745, 35.3927] +24-11-19 19:16:17 | D | best error = [ 4.8849, 4.8849, 4.8849, 4.8849, 4.8849] +24-11-19 19:16:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:16:17 | D | sum error = [ 37.6113, 39.9465, 42.4061, 45.0009, 47.7313] +24-11-19 19:16:17 | D | best error = [ 4.8849, 4.8849, 4.8849, 4.8849, 4.8849] +24-11-19 19:16:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:16:17 | D | sum error = [ 50.5832, 53.5898, 56.7468, 60.0729, 63.5518] +24-11-19 19:16:17 | D | best error = [ 4.8849, 4.8849, 4.8849, 4.8849, 4.8849] +24-11-19 19:16:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:16:17 | D | sum error = [ 67.2057, 71.0290, 75.0367, 79.2563, 83.6595] +24-11-19 19:16:17 | D | best error = [ 4.8849, 4.8849, 4.8849, 4.8849, 4.8849] +24-11-19 19:16:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:16:17 | D | sum error = [ 88.2527, 93.0746, 98.1198, 103.3929, 108.8803] +24-11-19 19:16:17 | D | best error = [ 4.8849, 4.8849, 4.8849, 4.8849, 4.8849] +24-11-19 19:16:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:16:17 | D | sum error = [ 114.6119, 120.5857, 126.8178, 133.3097, 140.0794] +24-11-19 19:16:17 | D | best error = [ 4.8849, 4.8849, 4.8849, 4.8849, 4.8849] +24-11-19 19:16:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:16:17 | D | sum error = [ 147.1230, 154.4497, 162.0531, 169.9629, 178.1720] +24-11-19 19:16:17 | D | best error = [ 4.8849, 4.8849, 4.8849, 4.8849, 4.8849] +24-11-19 19:16:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:16:17 | D | sum error = [ 186.6854, 195.5167, 204.6831, 214.1803, 224.0053] +24-11-19 19:16:17 | D | best error = [ 4.8849, 4.8849, 4.8849, 4.8849, 4.8849] +24-11-19 19:16:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:16:17 | D | sum error = [ 234.1736, 244.6942, 255.5670, 266.8026, 278.3869] +24-11-19 19:16:17 | D | best error = [ 4.8849, 4.8849, 4.8849, 4.8849, 4.8849] +24-11-19 19:16:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:16:17 | D | sum error = [ 290.3588, 302.6919, 315.3977, 328.4764, 341.9400] +24-11-19 19:16:17 | D | best error = [ 4.8849, 4.8849, 4.8849, 4.8849, 4.8849] +24-11-19 19:16:17 | D | + error = [4.8849] +24-11-19 19:16:17 | D | - Calibrating model.layers.9.mlp.gate_proj.weight +24-11-19 19:16:17 | D | + w: sint8 +24-11-19 19:16:17 | D | + x: None +24-11-19 19:16:17 | D | + y: None +24-11-19 19:16:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:16:17 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:16:17 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:16:17 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:16:17 | D | - range ratio = [ 1.0000] +24-11-19 19:16:17 | D | sum error = [ 5.9939] +24-11-19 19:16:17 | D | best error = [ 5.9939] +24-11-19 19:16:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:16:18 | D | sum error = [ 5.9600, 5.9394, 5.9731, 6.0394, 6.1470] +24-11-19 19:16:18 | D | best error = [ 5.6099, 5.4622, 5.3850, 5.3408, 5.3185] +24-11-19 19:16:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:16:18 | D | sum error = [ 6.3049, 6.5091, 6.7853, 7.1296, 7.5126] +24-11-19 19:16:18 | D | best error = [ 5.3080, 5.3036, 5.3019, 5.3016, 5.3016] +24-11-19 19:16:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:16:18 | D | sum error = [ 7.9472, 8.4339, 8.9929, 9.6359, 10.3026] +24-11-19 19:16:18 | D | best error = [ 5.3015, 5.3015, 5.3015, 5.3015, 5.3015] +24-11-19 19:16:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:16:18 | D | sum error = [ 11.0483, 11.8554, 12.7102, 13.6568, 14.6414] +24-11-19 19:16:18 | D | best error = [ 5.3015, 5.3015, 5.3015, 5.3015, 5.3015] +24-11-19 19:16:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:16:18 | D | sum error = [ 15.7258, 16.8587, 18.0783, 19.3741, 20.7547] +24-11-19 19:16:18 | D | best error = [ 5.3015, 5.3015, 5.3015, 5.3015, 5.3015] +24-11-19 19:16:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:16:18 | D | sum error = [ 22.2077, 23.7591, 25.4184, 27.1548, 29.0128] +24-11-19 19:16:18 | D | best error = [ 5.3015, 5.3015, 5.3015, 5.3015, 5.3015] +24-11-19 19:16:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:16:18 | D | sum error = [ 30.9587, 33.0416, 35.2525, 37.5895, 40.0653] +24-11-19 19:16:18 | D | best error = [ 5.3015, 5.3015, 5.3015, 5.3015, 5.3015] +24-11-19 19:16:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:16:18 | D | sum error = [ 42.6787, 45.4517, 48.3813, 51.4688, 54.7462] +24-11-19 19:16:18 | D | best error = [ 5.3015, 5.3015, 5.3015, 5.3015, 5.3015] +24-11-19 19:16:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:16:18 | D | sum error = [ 58.2115, 61.8755, 65.7362, 69.8104, 74.1448] +24-11-19 19:16:18 | D | best error = [ 5.3015, 5.3015, 5.3015, 5.3015, 5.3015] +24-11-19 19:16:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:16:18 | D | sum error = [ 78.6870, 83.4757, 88.5453, 93.8816, 99.5039] +24-11-19 19:16:18 | D | best error = [ 5.3015, 5.3015, 5.3015, 5.3015, 5.3015] +24-11-19 19:16:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:16:18 | D | sum error = [ 105.4542, 111.7049, 118.2818, 125.2024, 132.5058] +24-11-19 19:16:18 | D | best error = [ 5.3015, 5.3015, 5.3015, 5.3015, 5.3015] +24-11-19 19:16:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:16:18 | D | sum error = [ 140.1694, 148.2109, 156.6659, 165.5226, 174.8005] +24-11-19 19:16:18 | D | best error = [ 5.3015, 5.3015, 5.3015, 5.3015, 5.3015] +24-11-19 19:16:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:16:18 | D | sum error = [ 184.5274, 194.7026, 205.3355, 216.4459, 228.0718] +24-11-19 19:16:18 | D | best error = [ 5.3015, 5.3015, 5.3015, 5.3015, 5.3015] +24-11-19 19:16:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:16:18 | D | sum error = [ 240.2160, 252.8907, 266.0965, 279.8376, 294.1283] +24-11-19 19:16:18 | D | best error = [ 5.3015, 5.3015, 5.3015, 5.3015, 5.3015] +24-11-19 19:16:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:16:18 | D | sum error = [ 308.9718, 324.4191, 340.4470, 357.0544, 374.2504] +24-11-19 19:16:18 | D | best error = [ 5.3015, 5.3015, 5.3015, 5.3015, 5.3015] +24-11-19 19:16:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:16:18 | D | sum error = [ 392.0573, 410.4793, 429.5016, 449.1203, 469.3235] +24-11-19 19:16:18 | D | best error = [ 5.3015, 5.3015, 5.3015, 5.3015, 5.3015] +24-11-19 19:16:18 | D | + error = [5.3015] +24-11-19 19:16:18 | D | - Calibrating model.layers.9.mlp.down_proj.weight +24-11-19 19:16:18 | D | + w: sint8 +24-11-19 19:16:18 | D | + x: None +24-11-19 19:16:18 | D | + y: None +24-11-19 19:16:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:16:18 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:16:18 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:16:18 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:16:18 | D | - range ratio = [ 1.0000] +24-11-19 19:16:18 | D | sum error = [ 1.3282] +24-11-19 19:16:18 | D | best error = [ 1.3282] +24-11-19 19:16:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:16:19 | D | sum error = [ 1.3162, 1.3048, 1.3009, 1.2970, 1.2975] +24-11-19 19:16:19 | D | best error = [ 1.2828, 1.2590, 1.2436, 1.2310, 1.2224] +24-11-19 19:16:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:16:19 | D | sum error = [ 1.3006, 1.3130, 1.3287, 1.3526, 1.3819] +24-11-19 19:16:19 | D | best error = [ 1.2158, 1.2114, 1.2085, 1.2062, 1.2049] +24-11-19 19:16:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:16:19 | D | sum error = [ 1.4182, 1.4627, 1.5168, 1.5789, 1.6507] +24-11-19 19:16:19 | D | best error = [ 1.2040, 1.2035, 1.2032, 1.2031, 1.2029] +24-11-19 19:16:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:16:19 | D | sum error = [ 1.7325, 1.8254, 1.9297, 2.0460, 2.1717] +24-11-19 19:16:19 | D | best error = [ 1.2029, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 19:16:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:16:19 | D | sum error = [ 2.3107, 2.4589, 2.6223, 2.7966, 2.9873] +24-11-19 19:16:19 | D | best error = [ 1.2028, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 19:16:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:16:19 | D | sum error = [ 3.1921, 3.4114, 3.6475, 3.8979, 4.1641] +24-11-19 19:16:19 | D | best error = [ 1.2028, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 19:16:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:16:19 | D | sum error = [ 4.4489, 4.7551, 5.0772, 5.4226, 5.7888] +24-11-19 19:16:19 | D | best error = [ 1.2028, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 19:16:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:16:19 | D | sum error = [ 6.1747, 6.5874, 7.0237, 7.4835, 7.9702] +24-11-19 19:16:19 | D | best error = [ 1.2028, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 19:16:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:16:19 | D | sum error = [ 8.4896, 9.0352, 9.6110, 10.2198, 10.8628] +24-11-19 19:16:19 | D | best error = [ 1.2028, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 19:16:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:16:19 | D | sum error = [ 11.5395, 12.2542, 13.0068, 13.7980, 14.6317] +24-11-19 19:16:19 | D | best error = [ 1.2028, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 19:16:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:16:19 | D | sum error = [ 15.5062, 16.4277, 17.3931, 18.4101, 19.4748] +24-11-19 19:16:19 | D | best error = [ 1.2028, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 19:16:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:16:19 | D | sum error = [ 20.5931, 21.7662, 22.9941, 24.2812, 25.6298] +24-11-19 19:16:19 | D | best error = [ 1.2028, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 19:16:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:16:19 | D | sum error = [ 27.0398, 28.5145, 30.0535, 31.6599, 33.3365] +24-11-19 19:16:19 | D | best error = [ 1.2028, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 19:16:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:16:19 | D | sum error = [ 35.0834, 36.9027, 38.7978, 40.7728, 42.8188] +24-11-19 19:16:19 | D | best error = [ 1.2028, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 19:16:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:16:19 | D | sum error = [ 44.9490, 47.1611, 49.4565, 51.8399, 54.3100] +24-11-19 19:16:19 | D | best error = [ 1.2028, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 19:16:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:16:19 | D | sum error = [ 56.8675, 59.5129, 62.2502, 65.0794, 68.0041] +24-11-19 19:16:19 | D | best error = [ 1.2028, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 19:16:19 | D | + error = [1.2028] +24-11-19 19:16:19 | D | - Quantizing model.layers.9.self_attn.q_proj.weight +24-11-19 19:16:20 | D | - Quantizing model.layers.9.self_attn.k_proj.weight +24-11-19 19:16:21 | D | - Quantizing model.layers.9.self_attn.v_proj.weight +24-11-19 19:16:22 | D | - Quantizing model.layers.9.self_attn.o_proj.weight +24-11-19 19:16:23 | D | - Quantizing model.layers.9.mlp.up_proj.weight +24-11-19 19:16:24 | D | - Quantizing model.layers.9.mlp.gate_proj.weight +24-11-19 19:16:25 | D | - Quantizing model.layers.9.mlp.down_proj.weight +24-11-19 19:16:34 | D | - Quantizing layer model.layers.10 +24-11-19 19:16:34 | D | - Calibrating model.layers.10.self_attn.q_proj.weight +24-11-19 19:16:34 | D | + w: sint8 +24-11-19 19:16:34 | D | + x: None +24-11-19 19:16:34 | D | + y: None +24-11-19 19:16:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:16:34 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:16:34 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:16:34 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:16:34 | D | - range ratio = [ 1.0000] +24-11-19 19:16:34 | D | sum error = [ 8.6642] +24-11-19 19:16:34 | D | best error = [ 8.6642] +24-11-19 19:16:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:16:47 | D | sum error = [ 8.6269, 8.5793, 8.6532, 8.6186, 8.8470] +24-11-19 19:16:47 | D | best error = [ 8.6269, 8.5793, 8.5793, 8.5793, 8.5793] +24-11-19 19:16:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:16:47 | D | sum error = [ 9.0996, 9.4198, 9.7873, 10.1917, 11.1088] +24-11-19 19:16:47 | D | best error = [ 8.5793, 8.5793, 8.5793, 8.5793, 8.5793] +24-11-19 19:16:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:16:47 | D | sum error = [ 11.4841, 12.6357, 13.2202, 14.2928, 15.1945] +24-11-19 19:16:47 | D | best error = [ 8.5793, 8.5793, 8.5793, 8.5793, 8.5793] +24-11-19 19:16:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:16:47 | D | sum error = [ 16.5391, 17.6722, 19.1620, 20.5754, 22.2497] +24-11-19 19:16:47 | D | best error = [ 8.5793, 8.5793, 8.5793, 8.5793, 8.5793] +24-11-19 19:16:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:16:47 | D | sum error = [ 24.1699, 26.1763, 28.2813, 30.5834, 33.2464] +24-11-19 19:16:47 | D | best error = [ 8.5793, 8.5793, 8.5793, 8.5793, 8.5793] +24-11-19 19:16:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:16:47 | D | sum error = [ 35.3743, 38.5094, 41.8185, 44.8203, 48.2629] +24-11-19 19:16:47 | D | best error = [ 8.5793, 8.5793, 8.5793, 8.5793, 8.5793] +24-11-19 19:16:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:16:47 | D | sum error = [ 52.0584, 56.1744, 60.6045, 65.3809, 70.6489] +24-11-19 19:16:47 | D | best error = [ 8.5793, 8.5793, 8.5793, 8.5793, 8.5793] +24-11-19 19:16:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:16:47 | D | sum error = [ 75.8024, 81.9670, 88.3051, 95.1185, 101.9368] +24-11-19 19:16:47 | D | best error = [ 8.5793, 8.5793, 8.5793, 8.5793, 8.5793] +24-11-19 19:16:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:16:47 | D | sum error = [ 109.9586, 118.0731, 127.0407, 136.6166, 146.8244] +24-11-19 19:16:47 | D | best error = [ 8.5793, 8.5793, 8.5793, 8.5793, 8.5793] +24-11-19 19:16:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:16:47 | D | sum error = [ 157.7280, 169.3380, 181.8718, 195.3024, 209.5821] +24-11-19 19:16:47 | D | best error = [ 8.5793, 8.5793, 8.5793, 8.5793, 8.5793] +24-11-19 19:16:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:16:47 | D | sum error = [ 225.0565, 241.4148, 258.7525, 277.5306, 297.4158] +24-11-19 19:16:47 | D | best error = [ 8.5793, 8.5793, 8.5793, 8.5793, 8.5793] +24-11-19 19:16:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:16:47 | D | sum error = [ 318.9926, 341.6381, 365.9977, 391.7468, 419.2606] +24-11-19 19:16:47 | D | best error = [ 8.5793, 8.5793, 8.5793, 8.5793, 8.5793] +24-11-19 19:16:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:16:47 | D | sum error = [ 448.5633, 479.9761, 513.5959, 549.3847, 587.0829] +24-11-19 19:16:47 | D | best error = [ 8.5793, 8.5793, 8.5793, 8.5793, 8.5793] +24-11-19 19:16:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:16:47 | D | sum error = [ 627.2407, 669.8500, 714.8897, 762.3982, 812.3796] +24-11-19 19:16:47 | D | best error = [ 8.5793, 8.5793, 8.5793, 8.5793, 8.5793] +24-11-19 19:16:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:16:47 | D | sum error = [ 864.8827, 920.1202, 978.0222, 1038.2867, 1101.0808] +24-11-19 19:16:47 | D | best error = [ 8.5793, 8.5793, 8.5793, 8.5793, 8.5793] +24-11-19 19:16:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:16:47 | D | sum error = [ 1165.9444, 1232.5699, 1301.2949, 1371.1343, 1442.1843] +24-11-19 19:16:47 | D | best error = [ 8.5793, 8.5793, 8.5793, 8.5793, 8.5793] +24-11-19 19:16:47 | D | + error = [8.5793] +24-11-19 19:16:47 | D | - Calibrating model.layers.10.self_attn.k_proj.weight +24-11-19 19:16:47 | D | + w: sint8 +24-11-19 19:16:47 | D | + x: None +24-11-19 19:16:47 | D | + y: None +24-11-19 19:16:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:16:47 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:16:47 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:16:47 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:16:47 | D | - range ratio = [ 1.0000] +24-11-19 19:16:47 | D | sum error = [ 8.5503] +24-11-19 19:16:47 | D | best error = [ 8.5503] +24-11-19 19:17:00 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:17:00 | D | sum error = [ 8.7965, 8.8796, 9.1296, 9.1793, 9.3974] +24-11-19 19:17:00 | D | best error = [ 8.5503, 8.5503, 8.5503, 8.5503, 8.5503] +24-11-19 19:17:00 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:17:00 | D | sum error = [ 9.3687, 9.8813, 10.1844, 10.5497, 10.9590] +24-11-19 19:17:00 | D | best error = [ 8.5503, 8.5503, 8.5503, 8.5503, 8.5503] +24-11-19 19:17:00 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:17:00 | D | sum error = [ 12.0623, 12.5632, 13.6805, 15.1318, 15.6237] +24-11-19 19:17:00 | D | best error = [ 8.5503, 8.5503, 8.5503, 8.5503, 8.5503] +24-11-19 19:17:00 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:17:00 | D | sum error = [ 17.1874, 18.3056, 19.4632, 21.4336, 23.2007] +24-11-19 19:17:00 | D | best error = [ 8.5503, 8.5503, 8.5503, 8.5503, 8.5503] +24-11-19 19:17:00 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:17:00 | D | sum error = [ 24.9233, 27.5249, 29.8296, 31.7967, 34.4696] +24-11-19 19:17:00 | D | best error = [ 8.5503, 8.5503, 8.5503, 8.5503, 8.5503] +24-11-19 19:17:00 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:17:00 | D | sum error = [ 37.7411, 40.7132, 44.2841, 48.2687, 53.0012] +24-11-19 19:17:00 | D | best error = [ 8.5503, 8.5503, 8.5503, 8.5503, 8.5503] +24-11-19 19:17:00 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:17:00 | D | sum error = [ 56.9333, 61.6298, 67.7849, 73.2582, 80.1435] +24-11-19 19:17:00 | D | best error = [ 8.5503, 8.5503, 8.5503, 8.5503, 8.5503] +24-11-19 19:17:00 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:17:00 | D | sum error = [ 85.9341, 93.7832, 101.9901, 110.2153, 119.3903] +24-11-19 19:17:00 | D | best error = [ 8.5503, 8.5503, 8.5503, 8.5503, 8.5503] +24-11-19 19:17:00 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:17:00 | D | sum error = [ 128.4701, 138.7719, 150.5960, 162.7040, 175.4989] +24-11-19 19:17:00 | D | best error = [ 8.5503, 8.5503, 8.5503, 8.5503, 8.5503] +24-11-19 19:17:00 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:17:00 | D | sum error = [ 189.9911, 204.4832, 218.1974, 235.7869, 252.2585] +24-11-19 19:17:00 | D | best error = [ 8.5503, 8.5503, 8.5503, 8.5503, 8.5503] +24-11-19 19:17:00 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:17:00 | D | sum error = [ 270.8111, 289.3519, 311.1313, 330.9820, 356.1453] +24-11-19 19:17:00 | D | best error = [ 8.5503, 8.5503, 8.5503, 8.5503, 8.5503] +24-11-19 19:17:00 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:17:00 | D | sum error = [ 379.3317, 406.1740, 434.6543, 464.4938, 494.0364] +24-11-19 19:17:00 | D | best error = [ 8.5503, 8.5503, 8.5503, 8.5503, 8.5503] +24-11-19 19:17:00 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:17:00 | D | sum error = [ 527.6090, 559.3864, 594.8661, 633.3010, 670.5722] +24-11-19 19:17:00 | D | best error = [ 8.5503, 8.5503, 8.5503, 8.5503, 8.5503] +24-11-19 19:17:00 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:17:00 | D | sum error = [ 710.5755, 757.2131, 802.8264, 854.3942, 903.7756] +24-11-19 19:17:00 | D | best error = [ 8.5503, 8.5503, 8.5503, 8.5503, 8.5503] +24-11-19 19:17:00 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:17:00 | D | sum error = [ 953.9156, 1013.8875, 1066.8916, 1125.5025, 1190.6178] +24-11-19 19:17:00 | D | best error = [ 8.5503, 8.5503, 8.5503, 8.5503, 8.5503] +24-11-19 19:17:00 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:17:00 | D | sum error = [ 1252.9993, 1312.9588, 1382.0313, 1448.5027, 1513.0298] +24-11-19 19:17:00 | D | best error = [ 8.5503, 8.5503, 8.5503, 8.5503, 8.5503] +24-11-19 19:17:00 | D | + error = [8.5503] +24-11-19 19:17:00 | D | - Calibrating model.layers.10.self_attn.v_proj.weight +24-11-19 19:17:00 | D | + w: sint8 +24-11-19 19:17:00 | D | + x: None +24-11-19 19:17:00 | D | + y: None +24-11-19 19:17:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:17:00 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:17:00 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:17:00 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:17:00 | D | - range ratio = [ 1.0000] +24-11-19 19:17:00 | D | sum error = [ 4.0797] +24-11-19 19:17:00 | D | best error = [ 4.0797] +24-11-19 19:17:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:17:01 | D | sum error = [ 4.0370, 4.0420, 4.0607, 4.0985, 4.1819] +24-11-19 19:17:01 | D | best error = [ 3.8200, 3.7193, 3.6694, 3.6407, 3.6236] +24-11-19 19:17:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:17:01 | D | sum error = [ 4.2805, 4.4297, 4.6168, 4.8388, 5.0936] +24-11-19 19:17:01 | D | best error = [ 3.6166, 3.6141, 3.6130, 3.6126, 3.6126] +24-11-19 19:17:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:17:01 | D | sum error = [ 5.4033, 5.7125, 6.0765, 6.4938, 6.9608] +24-11-19 19:17:01 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 19:17:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:17:01 | D | sum error = [ 7.4512, 7.9760, 8.5479, 9.1516, 9.8169] +24-11-19 19:17:01 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 19:17:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:17:01 | D | sum error = [ 10.5209, 11.2584, 12.0703, 12.9258, 13.8193] +24-11-19 19:17:01 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 19:17:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:17:01 | D | sum error = [ 14.7841, 15.8084, 16.8647, 17.9981, 19.2119] +24-11-19 19:17:01 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 19:17:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:17:01 | D | sum error = [ 20.4720, 21.8124, 23.2411, 24.7240, 26.3018] +24-11-19 19:17:01 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 19:17:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:17:01 | D | sum error = [ 27.9732, 29.7229, 31.5767, 33.5133, 35.5683] +24-11-19 19:17:01 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 19:17:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:17:01 | D | sum error = [ 37.7102, 39.9980, 42.3704, 44.8748, 47.5145] +24-11-19 19:17:01 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 19:17:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:17:01 | D | sum error = [ 50.2612, 53.1814, 56.2487, 59.4627, 62.8285] +24-11-19 19:17:01 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 19:17:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:17:01 | D | sum error = [ 66.3579, 70.0641, 73.9292, 78.0037, 82.2514] +24-11-19 19:17:01 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 19:17:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:17:01 | D | sum error = [ 86.7094, 91.3607, 96.2280, 101.3112, 106.6221] +24-11-19 19:17:01 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 19:17:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:17:01 | D | sum error = [ 112.1484, 117.9141, 123.9158, 130.1672, 136.6859] +24-11-19 19:17:01 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 19:17:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:17:01 | D | sum error = [ 143.4645, 150.5239, 157.8555, 165.4749, 173.3659] +24-11-19 19:17:01 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 19:17:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:17:01 | D | sum error = [ 181.5587, 190.0368, 198.8024, 207.8706, 217.2398] +24-11-19 19:17:01 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 19:17:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:17:01 | D | sum error = [ 226.9185, 236.9098, 247.2238, 257.8451, 268.7980] +24-11-19 19:17:01 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 19:17:01 | D | + error = [3.6126] +24-11-19 19:17:01 | D | - Calibrating model.layers.10.self_attn.o_proj.weight +24-11-19 19:17:01 | D | + w: sint8 +24-11-19 19:17:01 | D | + x: None +24-11-19 19:17:01 | D | + y: None +24-11-19 19:17:01 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:17:01 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:17:01 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:17:01 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:17:01 | D | - range ratio = [ 1.0000] +24-11-19 19:17:01 | D | sum error = [ 1.1246] +24-11-19 19:17:01 | D | best error = [ 1.1246] +24-11-19 19:17:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:17:01 | D | sum error = [ 1.1142, 1.1090, 1.1144, 1.1146, 1.1315] +24-11-19 19:17:01 | D | best error = [ 1.0519, 1.0179, 0.9993, 0.9857, 0.9770] +24-11-19 19:17:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:17:01 | D | sum error = [ 1.1521, 1.1798, 1.2108, 1.2517, 1.3076] +24-11-19 19:17:01 | D | best error = [ 0.9712, 0.9677, 0.9649, 0.9630, 0.9619] +24-11-19 19:17:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:17:01 | D | sum error = [ 1.3720, 1.4367, 1.5177, 1.6078, 1.7036] +24-11-19 19:17:01 | D | best error = [ 0.9616, 0.9612, 0.9608, 0.9606, 0.9605] +24-11-19 19:17:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:17:01 | D | sum error = [ 1.8042, 1.9298, 2.0554, 2.1887, 2.3385] +24-11-19 19:17:01 | D | best error = [ 0.9604, 0.9604, 0.9604, 0.9604, 0.9604] +24-11-19 19:17:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:17:01 | D | sum error = [ 2.4898, 2.6555, 2.8329, 3.0265, 3.2236] +24-11-19 19:17:01 | D | best error = [ 0.9604, 0.9604, 0.9604, 0.9604, 0.9604] +24-11-19 19:17:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:17:01 | D | sum error = [ 3.4353, 3.6590, 3.9057, 4.1563, 4.4224] +24-11-19 19:17:01 | D | best error = [ 0.9604, 0.9603, 0.9603, 0.9603, 0.9603] +24-11-19 19:17:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:17:01 | D | sum error = [ 4.7125, 5.0115, 5.3255, 5.6594, 6.0099] +24-11-19 19:17:01 | D | best error = [ 0.9603, 0.9603, 0.9603, 0.9603, 0.9603] +24-11-19 19:17:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:17:01 | D | sum error = [ 6.3792, 6.7708, 7.1812, 7.6142, 8.0728] +24-11-19 19:17:01 | D | best error = [ 0.9603, 0.9603, 0.9603, 0.9603, 0.9603] +24-11-19 19:17:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:17:01 | D | sum error = [ 8.5487, 9.0545, 9.5834, 10.1378, 10.7226] +24-11-19 19:17:01 | D | best error = [ 0.9603, 0.9603, 0.9603, 0.9603, 0.9603] +24-11-19 19:17:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:17:01 | D | sum error = [ 11.3354, 11.9771, 12.6476, 13.3528, 14.0869] +24-11-19 19:17:01 | D | best error = [ 0.9603, 0.9603, 0.9603, 0.9603, 0.9603] +24-11-19 19:17:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:17:01 | D | sum error = [ 14.8640, 15.6662, 16.5128, 17.3957, 18.3176] +24-11-19 19:17:01 | D | best error = [ 0.9603, 0.9603, 0.9603, 0.9603, 0.9603] +24-11-19 19:17:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:17:01 | D | sum error = [ 19.2790, 20.2820, 21.3299, 22.4167, 23.5507] +24-11-19 19:17:01 | D | best error = [ 0.9603, 0.9603, 0.9603, 0.9603, 0.9603] +24-11-19 19:17:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:17:01 | D | sum error = [ 24.7310, 25.9596, 27.2374, 28.5684, 29.9508] +24-11-19 19:17:01 | D | best error = [ 0.9603, 0.9603, 0.9603, 0.9603, 0.9603] +24-11-19 19:17:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:17:01 | D | sum error = [ 31.3886, 32.8786, 34.4253, 36.0285, 37.6912] +24-11-19 19:17:01 | D | best error = [ 0.9603, 0.9603, 0.9603, 0.9603, 0.9603] +24-11-19 19:17:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:17:01 | D | sum error = [ 39.4149, 41.2033, 43.0552, 44.9694, 46.9497] +24-11-19 19:17:01 | D | best error = [ 0.9603, 0.9603, 0.9603, 0.9603, 0.9603] +24-11-19 19:17:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:17:01 | D | sum error = [ 48.9959, 51.1105, 53.2943, 55.5465, 57.8689] +24-11-19 19:17:01 | D | best error = [ 0.9603, 0.9603, 0.9603, 0.9603, 0.9603] +24-11-19 19:17:01 | D | + error = [0.9603] +24-11-19 19:17:02 | D | - Calibrating model.layers.10.mlp.up_proj.weight +24-11-19 19:17:02 | D | + w: sint8 +24-11-19 19:17:02 | D | + x: None +24-11-19 19:17:02 | D | + y: None +24-11-19 19:17:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:17:02 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:17:02 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:17:02 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:17:02 | D | - range ratio = [ 1.0000] +24-11-19 19:17:02 | D | sum error = [ 5.6643] +24-11-19 19:17:02 | D | best error = [ 5.6643] +24-11-19 19:17:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:17:03 | D | sum error = [ 5.6304, 5.6145, 5.6357, 5.7086, 5.8115] +24-11-19 19:17:03 | D | best error = [ 5.2984, 5.1557, 5.0791, 5.0368, 5.0152] +24-11-19 19:17:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:17:03 | D | sum error = [ 5.9448, 6.1655, 6.4031, 6.7123, 7.0653] +24-11-19 19:17:03 | D | best error = [ 5.0036, 4.9997, 4.9977, 4.9972, 4.9971] +24-11-19 19:17:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:17:03 | D | sum error = [ 7.4810, 7.9485, 8.4605, 9.0365, 9.6695] +24-11-19 19:17:03 | D | best error = [ 4.9971, 4.9971, 4.9971, 4.9971, 4.9971] +24-11-19 19:17:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:17:03 | D | sum error = [ 10.3585, 11.0751, 11.8605, 12.7322, 13.6501] +24-11-19 19:17:03 | D | best error = [ 4.9971, 4.9971, 4.9971, 4.9971, 4.9971] +24-11-19 19:17:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:17:03 | D | sum error = [ 14.6348, 15.6671, 16.7956, 17.9777, 19.2282] +24-11-19 19:17:03 | D | best error = [ 4.9971, 4.9971, 4.9971, 4.9971, 4.9971] +24-11-19 19:17:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:17:03 | D | sum error = [ 20.5553, 21.9677, 23.4657, 25.0364, 26.6831] +24-11-19 19:17:03 | D | best error = [ 4.9971, 4.9971, 4.9971, 4.9971, 4.9971] +24-11-19 19:17:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:17:03 | D | sum error = [ 28.4557, 30.3107, 32.2790, 34.3327, 36.5010] +24-11-19 19:17:03 | D | best error = [ 4.9971, 4.9971, 4.9971, 4.9971, 4.9971] +24-11-19 19:17:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:17:03 | D | sum error = [ 38.8010, 41.1946, 43.7340, 46.3923, 49.2034] +24-11-19 19:17:03 | D | best error = [ 4.9971, 4.9971, 4.9971, 4.9971, 4.9971] +24-11-19 19:17:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:17:03 | D | sum error = [ 52.1551, 55.2612, 58.5155, 61.9245, 65.5171] +24-11-19 19:17:03 | D | best error = [ 4.9971, 4.9971, 4.9971, 4.9971, 4.9971] +24-11-19 19:17:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:17:03 | D | sum error = [ 69.2789, 73.1983, 77.3339, 81.6573, 86.1866] +24-11-19 19:17:03 | D | best error = [ 4.9971, 4.9971, 4.9971, 4.9971, 4.9971] +24-11-19 19:17:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:17:03 | D | sum error = [ 90.9378, 95.8933, 101.0825, 106.5205, 112.1903] +24-11-19 19:17:03 | D | best error = [ 4.9971, 4.9971, 4.9971, 4.9971, 4.9971] +24-11-19 19:17:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:17:03 | D | sum error = [ 118.1265, 124.3159, 130.7751, 137.5110, 144.5390] +24-11-19 19:17:03 | D | best error = [ 4.9971, 4.9971, 4.9971, 4.9971, 4.9971] +24-11-19 19:17:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:17:03 | D | sum error = [ 151.8561, 159.4727, 167.3991, 175.6427, 184.2275] +24-11-19 19:17:03 | D | best error = [ 4.9971, 4.9971, 4.9971, 4.9971, 4.9971] +24-11-19 19:17:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:17:03 | D | sum error = [ 193.1342, 202.3820, 211.9767, 221.9368, 232.2378] +24-11-19 19:17:03 | D | best error = [ 4.9971, 4.9971, 4.9971, 4.9971, 4.9971] +24-11-19 19:17:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:17:03 | D | sum error = [ 242.9134, 253.9704, 265.4019, 277.2073, 289.3979] +24-11-19 19:17:03 | D | best error = [ 4.9971, 4.9971, 4.9971, 4.9971, 4.9971] +24-11-19 19:17:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:17:03 | D | sum error = [ 301.9906, 314.9822, 328.3737, 342.1556, 356.3425] +24-11-19 19:17:03 | D | best error = [ 4.9971, 4.9971, 4.9971, 4.9971, 4.9971] +24-11-19 19:17:03 | D | + error = [4.9971] +24-11-19 19:17:03 | D | - Calibrating model.layers.10.mlp.gate_proj.weight +24-11-19 19:17:03 | D | + w: sint8 +24-11-19 19:17:03 | D | + x: None +24-11-19 19:17:03 | D | + y: None +24-11-19 19:17:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:17:03 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:17:03 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:17:03 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:17:03 | D | - range ratio = [ 1.0000] +24-11-19 19:17:03 | D | sum error = [ 6.0749] +24-11-19 19:17:03 | D | best error = [ 6.0749] +24-11-19 19:17:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:17:04 | D | sum error = [ 6.0328, 6.0197, 6.0440, 6.1078, 6.2272] +24-11-19 19:17:04 | D | best error = [ 5.6860, 5.5349, 5.4515, 5.4035, 5.3798] +24-11-19 19:17:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:17:04 | D | sum error = [ 6.3920, 6.6094, 6.8937, 7.2041, 7.5789] +24-11-19 19:17:04 | D | best error = [ 5.3680, 5.3633, 5.3619, 5.3615, 5.3611] +24-11-19 19:17:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:17:04 | D | sum error = [ 8.0234, 8.5241, 9.0947, 9.7048, 10.3945] +24-11-19 19:17:04 | D | best error = [ 5.3611, 5.3611, 5.3611, 5.3611, 5.3611] +24-11-19 19:17:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:17:04 | D | sum error = [ 11.1271, 11.9412, 12.7869, 13.7252, 14.7154] +24-11-19 19:17:04 | D | best error = [ 5.3611, 5.3611, 5.3611, 5.3611, 5.3611] +24-11-19 19:17:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:17:04 | D | sum error = [ 15.7935, 16.9464, 18.1487, 19.4487, 20.8304] +24-11-19 19:17:04 | D | best error = [ 5.3611, 5.3611, 5.3611, 5.3611, 5.3611] +24-11-19 19:17:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:17:04 | D | sum error = [ 22.2948, 23.8642, 25.5175, 27.2902, 29.1512] +24-11-19 19:17:04 | D | best error = [ 5.3611, 5.3611, 5.3611, 5.3611, 5.3611] +24-11-19 19:17:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:17:04 | D | sum error = [ 31.1382, 33.2470, 35.4671, 37.8579, 40.3340] +24-11-19 19:17:04 | D | best error = [ 5.3611, 5.3611, 5.3611, 5.3611, 5.3611] +24-11-19 19:17:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:17:04 | D | sum error = [ 42.9915, 45.7940, 48.7840, 51.9255, 55.2581] +24-11-19 19:17:04 | D | best error = [ 5.3611, 5.3611, 5.3611, 5.3611, 5.3611] +24-11-19 19:17:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:17:04 | D | sum error = [ 58.8085, 62.5216, 66.4703, 70.6333, 75.0338] +24-11-19 19:17:04 | D | best error = [ 5.3611, 5.3611, 5.3611, 5.3611, 5.3611] +24-11-19 19:17:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:17:04 | D | sum error = [ 79.7076, 84.6116, 89.7864, 95.2748, 101.0394] +24-11-19 19:17:04 | D | best error = [ 5.3611, 5.3611, 5.3611, 5.3611, 5.3611] +24-11-19 19:17:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:17:04 | D | sum error = [ 107.1343, 113.5426, 120.3213, 127.4560, 134.9584] +24-11-19 19:17:04 | D | best error = [ 5.3611, 5.3611, 5.3611, 5.3611, 5.3611] +24-11-19 19:17:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:17:04 | D | sum error = [ 142.8331, 151.1376, 159.8326, 168.9909, 178.5836] +24-11-19 19:17:04 | D | best error = [ 5.3611, 5.3611, 5.3611, 5.3611, 5.3611] +24-11-19 19:17:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:17:04 | D | sum error = [ 188.6276, 199.1703, 210.1953, 221.7307, 233.8146] +24-11-19 19:17:04 | D | best error = [ 5.3611, 5.3611, 5.3611, 5.3611, 5.3611] +24-11-19 19:17:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:17:04 | D | sum error = [ 246.4030, 259.5228, 273.2275, 287.4979, 302.3623] +24-11-19 19:17:04 | D | best error = [ 5.3611, 5.3611, 5.3611, 5.3611, 5.3611] +24-11-19 19:17:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:17:04 | D | sum error = [ 317.8299, 333.8950, 350.5820, 367.8945, 385.8132] +24-11-19 19:17:04 | D | best error = [ 5.3611, 5.3611, 5.3611, 5.3611, 5.3611] +24-11-19 19:17:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:17:04 | D | sum error = [ 404.3715, 423.5556, 443.3655, 463.8214, 484.9074] +24-11-19 19:17:04 | D | best error = [ 5.3611, 5.3611, 5.3611, 5.3611, 5.3611] +24-11-19 19:17:04 | D | + error = [5.3611] +24-11-19 19:17:04 | D | - Calibrating model.layers.10.mlp.down_proj.weight +24-11-19 19:17:04 | D | + w: sint8 +24-11-19 19:17:04 | D | + x: None +24-11-19 19:17:04 | D | + y: None +24-11-19 19:17:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:17:04 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:17:04 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:17:04 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:17:04 | D | - range ratio = [ 1.0000] +24-11-19 19:17:04 | D | sum error = [ 1.4171] +24-11-19 19:17:04 | D | best error = [ 1.4171] +24-11-19 19:17:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:17:05 | D | sum error = [ 1.4054, 1.3955, 1.3866, 1.3825, 1.3823] +24-11-19 19:17:05 | D | best error = [ 1.3650, 1.3389, 1.3208, 1.3075, 1.2981] +24-11-19 19:17:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:17:05 | D | sum error = [ 1.3870, 1.3981, 1.4141, 1.4368, 1.4713] +24-11-19 19:17:05 | D | best error = [ 1.2903, 1.2848, 1.2812, 1.2788, 1.2771] +24-11-19 19:17:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:17:05 | D | sum error = [ 1.5089, 1.5594, 1.6129, 1.6793, 1.7576] +24-11-19 19:17:05 | D | best error = [ 1.2760, 1.2754, 1.2751, 1.2748, 1.2747] +24-11-19 19:17:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:17:05 | D | sum error = [ 1.8422, 1.9447, 2.0515, 2.1734, 2.3084] +24-11-19 19:17:05 | D | best error = [ 1.2746, 1.2746, 1.2745, 1.2745, 1.2745] +24-11-19 19:17:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:17:05 | D | sum error = [ 2.4558, 2.6142, 2.7896, 2.9767, 3.1786] +24-11-19 19:17:05 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 19:17:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:17:05 | D | sum error = [ 3.3929, 3.6282, 3.8773, 4.1462, 4.4299] +24-11-19 19:17:05 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 19:17:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:17:05 | D | sum error = [ 4.7341, 5.0583, 5.4026, 5.7711, 6.1609] +24-11-19 19:17:05 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 19:17:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:17:05 | D | sum error = [ 6.5752, 7.0126, 7.4824, 7.9737, 8.4940] +24-11-19 19:17:05 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 19:17:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:17:05 | D | sum error = [ 9.0456, 9.6276, 10.2458, 10.8968, 11.5828] +24-11-19 19:17:05 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 19:17:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:17:05 | D | sum error = [ 12.3054, 13.0653, 13.8697, 14.7141, 15.6043] +24-11-19 19:17:05 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 19:17:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:17:05 | D | sum error = [ 16.5358, 17.5191, 18.5465, 19.6285, 20.7680] +24-11-19 19:17:05 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 19:17:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:17:05 | D | sum error = [ 21.9603, 23.2103, 24.5215, 25.8918, 27.3268] +24-11-19 19:17:05 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 19:17:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:17:05 | D | sum error = [ 28.8301, 30.3991, 32.0401, 33.7531, 35.5387] +24-11-19 19:17:05 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 19:17:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:17:05 | D | sum error = [ 37.4051, 39.3466, 41.3690, 43.4787, 45.6648] +24-11-19 19:17:05 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 19:17:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:17:05 | D | sum error = [ 47.9394, 50.3048, 52.7583, 55.3028, 57.9413] +24-11-19 19:17:05 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 19:17:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:17:05 | D | sum error = [ 60.6752, 63.5046, 66.4338, 69.4609, 72.5880] +24-11-19 19:17:05 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 19:17:05 | D | + error = [1.2745] +24-11-19 19:17:05 | D | - Quantizing model.layers.10.self_attn.q_proj.weight +24-11-19 19:17:06 | D | - Quantizing model.layers.10.self_attn.k_proj.weight +24-11-19 19:17:07 | D | - Quantizing model.layers.10.self_attn.v_proj.weight +24-11-19 19:17:08 | D | - Quantizing model.layers.10.self_attn.o_proj.weight +24-11-19 19:17:09 | D | - Quantizing model.layers.10.mlp.up_proj.weight +24-11-19 19:17:10 | D | - Quantizing model.layers.10.mlp.gate_proj.weight +24-11-19 19:17:11 | D | - Quantizing model.layers.10.mlp.down_proj.weight +24-11-19 19:17:19 | D | - Quantizing layer model.layers.11 +24-11-19 19:17:19 | D | - Calibrating model.layers.11.self_attn.q_proj.weight +24-11-19 19:17:19 | D | + w: sint8 +24-11-19 19:17:19 | D | + x: None +24-11-19 19:17:19 | D | + y: None +24-11-19 19:17:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:17:19 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:17:19 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:17:20 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:17:20 | D | - range ratio = [ 1.0000] +24-11-19 19:17:20 | D | sum error = [ 9.5721] +24-11-19 19:17:20 | D | best error = [ 9.5721] +24-11-19 19:17:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:17:32 | D | sum error = [ 9.5849, 9.6185, 9.5024, 9.8250, 9.7703] +24-11-19 19:17:32 | D | best error = [ 9.5721, 9.5721, 9.5024, 9.5024, 9.5024] +24-11-19 19:17:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:17:32 | D | sum error = [ 10.1095, 10.7028, 10.8915, 11.6038, 12.3380] +24-11-19 19:17:32 | D | best error = [ 9.5024, 9.5024, 9.5024, 9.5024, 9.5024] +24-11-19 19:17:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:17:32 | D | sum error = [ 12.9453, 13.8687, 14.8852, 15.7789, 17.1262] +24-11-19 19:17:32 | D | best error = [ 9.5024, 9.5024, 9.5024, 9.5024, 9.5024] +24-11-19 19:17:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:17:32 | D | sum error = [ 18.5729, 20.1353, 21.5519, 23.2435, 25.6879] +24-11-19 19:17:32 | D | best error = [ 9.5024, 9.5024, 9.5024, 9.5024, 9.5024] +24-11-19 19:17:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:17:32 | D | sum error = [ 27.7113, 29.9588, 32.2705, 35.1893, 37.6810] +24-11-19 19:17:32 | D | best error = [ 9.5024, 9.5024, 9.5024, 9.5024, 9.5024] +24-11-19 19:17:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:17:32 | D | sum error = [ 40.5814, 44.1285, 47.5227, 51.8345, 56.0538] +24-11-19 19:17:32 | D | best error = [ 9.5024, 9.5024, 9.5024, 9.5024, 9.5024] +24-11-19 19:17:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:17:32 | D | sum error = [ 60.1396, 65.1991, 70.0418, 75.6592, 81.6131] +24-11-19 19:17:32 | D | best error = [ 9.5024, 9.5024, 9.5024, 9.5024, 9.5024] +24-11-19 19:17:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:17:32 | D | sum error = [ 87.5905, 94.8372, 102.0342, 109.6933, 117.8917] +24-11-19 19:17:32 | D | best error = [ 9.5024, 9.5024, 9.5024, 9.5024, 9.5024] +24-11-19 19:17:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:17:32 | D | sum error = [ 127.0273, 136.4968, 146.7061, 157.5079, 168.6300] +24-11-19 19:17:32 | D | best error = [ 9.5024, 9.5024, 9.5024, 9.5024, 9.5024] +24-11-19 19:17:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:17:32 | D | sum error = [ 181.0460, 194.3645, 208.4530, 223.6427, 239.7965] +24-11-19 19:17:32 | D | best error = [ 9.5024, 9.5024, 9.5024, 9.5024, 9.5024] +24-11-19 19:17:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:17:32 | D | sum error = [ 257.1219, 276.0716, 296.0841, 318.0176, 341.2248] +24-11-19 19:17:32 | D | best error = [ 9.5024, 9.5024, 9.5024, 9.5024, 9.5024] +24-11-19 19:17:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:17:32 | D | sum error = [ 365.9676, 392.7489, 421.6126, 452.0710, 484.8396] +24-11-19 19:17:32 | D | best error = [ 9.5024, 9.5024, 9.5024, 9.5024, 9.5024] +24-11-19 19:17:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:17:32 | D | sum error = [ 520.4738, 558.0980, 598.3837, 641.2039, 686.7912] +24-11-19 19:17:32 | D | best error = [ 9.5024, 9.5024, 9.5024, 9.5024, 9.5024] +24-11-19 19:17:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:17:32 | D | sum error = [ 735.2757, 787.1918, 842.1469, 900.5626, 961.8381] +24-11-19 19:17:32 | D | best error = [ 9.5024, 9.5024, 9.5024, 9.5024, 9.5024] +24-11-19 19:17:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:17:32 | D | sum error = [ 1026.7321, 1095.0582, 1166.9061, 1241.8713, 1319.8947] +24-11-19 19:17:32 | D | best error = [ 9.5024, 9.5024, 9.5024, 9.5024, 9.5024] +24-11-19 19:17:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:17:32 | D | sum error = [ 1400.4780, 1483.5014, 1568.5807, 1655.0035, 1742.4691] +24-11-19 19:17:32 | D | best error = [ 9.5024, 9.5024, 9.5024, 9.5024, 9.5024] +24-11-19 19:17:32 | D | + error = [9.5024] +24-11-19 19:17:32 | D | - Calibrating model.layers.11.self_attn.k_proj.weight +24-11-19 19:17:32 | D | + w: sint8 +24-11-19 19:17:32 | D | + x: None +24-11-19 19:17:32 | D | + y: None +24-11-19 19:17:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:17:32 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:17:32 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:17:32 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:17:33 | D | - range ratio = [ 1.0000] +24-11-19 19:17:33 | D | sum error = [ 9.7714] +24-11-19 19:17:33 | D | best error = [ 9.7714] +24-11-19 19:17:45 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:17:45 | D | sum error = [ 10.5018, 10.0793, 9.8956, 10.0024, 10.8729] +24-11-19 19:17:45 | D | best error = [ 9.7714, 9.7714, 9.7714, 9.7714, 9.7714] +24-11-19 19:17:45 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:17:45 | D | sum error = [ 10.9678, 11.6215, 11.6720, 12.2885, 12.7575] +24-11-19 19:17:45 | D | best error = [ 9.7714, 9.7714, 9.7714, 9.7714, 9.7714] +24-11-19 19:17:45 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:17:45 | D | sum error = [ 13.8890, 14.7186, 16.0007, 17.5130, 18.0192] +24-11-19 19:17:45 | D | best error = [ 9.7714, 9.7714, 9.7714, 9.7714, 9.7714] +24-11-19 19:17:45 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:17:45 | D | sum error = [ 19.4211, 21.3235, 23.2372, 24.3584, 25.9215] +24-11-19 19:17:45 | D | best error = [ 9.7714, 9.7714, 9.7714, 9.7714, 9.7714] +24-11-19 19:17:45 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:17:45 | D | sum error = [ 28.4383, 30.1563, 31.7738, 34.9747, 37.3639] +24-11-19 19:17:45 | D | best error = [ 9.7714, 9.7714, 9.7714, 9.7714, 9.7714] +24-11-19 19:17:45 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:17:45 | D | sum error = [ 40.3696, 43.4505, 46.5634, 49.6411, 53.3464] +24-11-19 19:17:45 | D | best error = [ 9.7714, 9.7714, 9.7714, 9.7714, 9.7714] +24-11-19 19:17:45 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:17:45 | D | sum error = [ 58.1692, 62.8699, 67.4321, 72.6140, 78.1970] +24-11-19 19:17:45 | D | best error = [ 9.7714, 9.7714, 9.7714, 9.7714, 9.7714] +24-11-19 19:17:45 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:17:45 | D | sum error = [ 84.4276, 91.0898, 97.1001, 104.2482, 112.5818] +24-11-19 19:17:45 | D | best error = [ 9.7714, 9.7714, 9.7714, 9.7714, 9.7714] +24-11-19 19:17:45 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:17:45 | D | sum error = [ 121.1090, 130.5514, 140.1698, 150.8740, 162.0503] +24-11-19 19:17:45 | D | best error = [ 9.7714, 9.7714, 9.7714, 9.7714, 9.7714] +24-11-19 19:17:45 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:17:45 | D | sum error = [ 173.4268, 187.6187, 201.6001, 216.3569, 232.3939] +24-11-19 19:17:45 | D | best error = [ 9.7714, 9.7714, 9.7714, 9.7714, 9.7714] +24-11-19 19:17:45 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:17:45 | D | sum error = [ 251.7209, 271.1845, 291.2991, 313.1966, 336.6277] +24-11-19 19:17:45 | D | best error = [ 9.7714, 9.7714, 9.7714, 9.7714, 9.7714] +24-11-19 19:17:45 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:17:45 | D | sum error = [ 362.9808, 390.3268, 418.5395, 451.2963, 484.7836] +24-11-19 19:17:45 | D | best error = [ 9.7714, 9.7714, 9.7714, 9.7714, 9.7714] +24-11-19 19:17:45 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:17:45 | D | sum error = [ 521.7465, 559.2971, 599.2099, 644.4082, 689.3932] +24-11-19 19:17:45 | D | best error = [ 9.7714, 9.7714, 9.7714, 9.7714, 9.7714] +24-11-19 19:17:45 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:17:45 | D | sum error = [ 738.7603, 788.6791, 845.0479, 905.5490, 964.6473] +24-11-19 19:17:45 | D | best error = [ 9.7714, 9.7714, 9.7714, 9.7714, 9.7714] +24-11-19 19:17:45 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:17:45 | D | sum error = [ 1031.5552, 1098.2843, 1170.3388, 1246.8270, 1322.3017] +24-11-19 19:17:45 | D | best error = [ 9.7714, 9.7714, 9.7714, 9.7714, 9.7714] +24-11-19 19:17:45 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:17:45 | D | sum error = [ 1406.4603, 1490.0513, 1575.5423, 1663.7714, 1753.0911] +24-11-19 19:17:45 | D | best error = [ 9.7714, 9.7714, 9.7714, 9.7714, 9.7714] +24-11-19 19:17:45 | D | + error = [9.7714] +24-11-19 19:17:45 | D | - Calibrating model.layers.11.self_attn.v_proj.weight +24-11-19 19:17:45 | D | + w: sint8 +24-11-19 19:17:45 | D | + x: None +24-11-19 19:17:45 | D | + y: None +24-11-19 19:17:45 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:17:45 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:17:45 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:17:45 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:17:45 | D | - range ratio = [ 1.0000] +24-11-19 19:17:45 | D | sum error = [ 4.6933] +24-11-19 19:17:45 | D | best error = [ 4.6933] +24-11-19 19:17:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:17:46 | D | sum error = [ 4.6470, 4.6465, 4.6588, 4.7325, 4.7963] +24-11-19 19:17:46 | D | best error = [ 4.3733, 4.2549, 4.1904, 4.1555, 4.1374] +24-11-19 19:17:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:17:46 | D | sum error = [ 4.9319, 5.0873, 5.2971, 5.5363, 5.8397] +24-11-19 19:17:46 | D | best error = [ 4.1269, 4.1230, 4.1222, 4.1221, 4.1221] +24-11-19 19:17:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:17:46 | D | sum error = [ 6.1903, 6.5667, 7.0053, 7.4606, 7.9868] +24-11-19 19:17:46 | D | best error = [ 4.1221, 4.1221, 4.1221, 4.1221, 4.1221] +24-11-19 19:17:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:17:46 | D | sum error = [ 8.5364, 9.1486, 9.8067, 10.5327, 11.2819] +24-11-19 19:17:46 | D | best error = [ 4.1221, 4.1221, 4.1221, 4.1221, 4.1221] +24-11-19 19:17:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:17:46 | D | sum error = [ 12.0981, 12.9555, 13.8605, 14.8543, 15.8851] +24-11-19 19:17:46 | D | best error = [ 4.1221, 4.1221, 4.1221, 4.1221, 4.1221] +24-11-19 19:17:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:17:46 | D | sum error = [ 16.9861, 18.1509, 19.3923, 20.6797, 22.0835] +24-11-19 19:17:46 | D | best error = [ 4.1221, 4.1221, 4.1221, 4.1221, 4.1221] +24-11-19 19:17:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:17:46 | D | sum error = [ 23.5247, 25.0772, 26.7027, 28.4195, 30.2606] +24-11-19 19:17:46 | D | best error = [ 4.1221, 4.1221, 4.1221, 4.1221, 4.1221] +24-11-19 19:17:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:17:46 | D | sum error = [ 32.1855, 34.2048, 36.3249, 38.5767, 40.9299] +24-11-19 19:17:46 | D | best error = [ 4.1221, 4.1221, 4.1221, 4.1221, 4.1221] +24-11-19 19:17:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:17:46 | D | sum error = [ 43.4228, 46.0331, 48.7894, 51.6671, 54.6933] +24-11-19 19:17:46 | D | best error = [ 4.1221, 4.1221, 4.1221, 4.1221, 4.1221] +24-11-19 19:17:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:17:46 | D | sum error = [ 57.8718, 61.2041, 64.6919, 68.3259, 72.1504] +24-11-19 19:17:46 | D | best error = [ 4.1221, 4.1221, 4.1221, 4.1221, 4.1221] +24-11-19 19:17:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:17:46 | D | sum error = [ 76.1302, 80.3114, 84.6731, 89.2503, 94.0336] +24-11-19 19:17:46 | D | best error = [ 4.1221, 4.1221, 4.1221, 4.1221, 4.1221] +24-11-19 19:17:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:17:46 | D | sum error = [ 99.0329, 104.2400, 109.6758, 115.3619, 121.2796] +24-11-19 19:17:46 | D | best error = [ 4.1221, 4.1221, 4.1221, 4.1221, 4.1221] +24-11-19 19:17:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:17:46 | D | sum error = [ 127.4586, 133.8965, 140.6024, 147.5764, 154.8185] +24-11-19 19:17:46 | D | best error = [ 4.1221, 4.1221, 4.1221, 4.1221, 4.1221] +24-11-19 19:17:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:17:46 | D | sum error = [ 162.3529, 170.1902, 178.3088, 186.7321, 195.4539] +24-11-19 19:17:46 | D | best error = [ 4.1221, 4.1221, 4.1221, 4.1221, 4.1221] +24-11-19 19:17:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:17:46 | D | sum error = [ 204.4881, 213.8393, 223.5286, 233.5340, 243.8838] +24-11-19 19:17:46 | D | best error = [ 4.1221, 4.1221, 4.1221, 4.1221, 4.1221] +24-11-19 19:17:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:17:46 | D | sum error = [ 254.5668, 265.5877, 276.9461, 288.6522, 300.7083] +24-11-19 19:17:46 | D | best error = [ 4.1221, 4.1221, 4.1221, 4.1221, 4.1221] +24-11-19 19:17:46 | D | + error = [4.1221] +24-11-19 19:17:46 | D | - Calibrating model.layers.11.self_attn.o_proj.weight +24-11-19 19:17:46 | D | + w: sint8 +24-11-19 19:17:46 | D | + x: None +24-11-19 19:17:46 | D | + y: None +24-11-19 19:17:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:17:46 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:17:46 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:17:46 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:17:46 | D | - range ratio = [ 1.0000] +24-11-19 19:17:46 | D | sum error = [ 1.0946] +24-11-19 19:17:46 | D | best error = [ 1.0946] +24-11-19 19:17:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:17:46 | D | sum error = [ 1.0882, 1.0824, 1.0782, 1.0814, 1.0887] +24-11-19 19:17:46 | D | best error = [ 1.0160, 0.9784, 0.9562, 0.9401, 0.9294] +24-11-19 19:17:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:17:46 | D | sum error = [ 1.1040, 1.1290, 1.1529, 1.1848, 1.2217] +24-11-19 19:17:46 | D | best error = [ 0.9221, 0.9165, 0.9124, 0.9097, 0.9074] +24-11-19 19:17:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:17:46 | D | sum error = [ 1.2738, 1.3319, 1.3954, 1.4695, 1.5440] +24-11-19 19:17:46 | D | best error = [ 0.9056, 0.9045, 0.9037, 0.9029, 0.9024] +24-11-19 19:17:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:17:46 | D | sum error = [ 1.6301, 1.7293, 1.8329, 1.9525, 2.0702] +24-11-19 19:17:46 | D | best error = [ 0.9018, 0.9015, 0.9012, 0.9009, 0.9007] +24-11-19 19:17:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:17:46 | D | sum error = [ 2.2008, 2.3435, 2.4900, 2.6471, 2.8186] +24-11-19 19:17:46 | D | best error = [ 0.9005, 0.9004, 0.9003, 0.9003, 0.9002] +24-11-19 19:17:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:17:46 | D | sum error = [ 3.0060, 3.1993, 3.4030, 3.6202, 3.8505] +24-11-19 19:17:46 | D | best error = [ 0.9001, 0.9001, 0.9001, 0.9001, 0.9001] +24-11-19 19:17:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:17:46 | D | sum error = [ 4.0987, 4.3546, 4.6318, 4.9145, 5.2238] +24-11-19 19:17:46 | D | best error = [ 0.9001, 0.9001, 0.9001, 0.9001, 0.9001] +24-11-19 19:17:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:17:46 | D | sum error = [ 5.5439, 5.8819, 6.2420, 6.6172, 7.0142] +24-11-19 19:17:46 | D | best error = [ 0.9001, 0.9001, 0.9001, 0.9001, 0.9001] +24-11-19 19:17:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:17:46 | D | sum error = [ 7.4319, 7.8693, 8.3339, 8.8177, 9.3266] +24-11-19 19:17:46 | D | best error = [ 0.9001, 0.9001, 0.9001, 0.9001, 0.9001] +24-11-19 19:17:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:17:46 | D | sum error = [ 9.8607, 10.4231, 11.0110, 11.6311, 12.2724] +24-11-19 19:17:46 | D | best error = [ 0.9001, 0.9001, 0.9001, 0.9001, 0.9001] +24-11-19 19:17:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:17:46 | D | sum error = [ 12.9513, 13.6575, 14.4005, 15.1739, 15.9833] +24-11-19 19:17:46 | D | best error = [ 0.9001, 0.9001, 0.9001, 0.9001, 0.9001] +24-11-19 19:17:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:17:46 | D | sum error = [ 16.8360, 17.7215, 18.6417, 19.6049, 20.6147] +24-11-19 19:17:46 | D | best error = [ 0.9001, 0.9001, 0.9001, 0.9001, 0.9001] +24-11-19 19:17:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:17:46 | D | sum error = [ 21.6612, 22.7516, 23.8893, 25.0671, 26.2970] +24-11-19 19:17:46 | D | best error = [ 0.9001, 0.9001, 0.9001, 0.9001, 0.9001] +24-11-19 19:17:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:17:46 | D | sum error = [ 27.5737, 28.9027, 30.2770, 31.7039, 33.1880] +24-11-19 19:17:46 | D | best error = [ 0.9001, 0.9001, 0.9001, 0.9001, 0.9001] +24-11-19 19:17:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:17:46 | D | sum error = [ 34.7249, 36.3176, 37.9691, 39.6789, 41.4472] +24-11-19 19:17:46 | D | best error = [ 0.9001, 0.9001, 0.9001, 0.9001, 0.9001] +24-11-19 19:17:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:17:46 | D | sum error = [ 43.2779, 45.1721, 47.1251, 49.1425, 51.2271] +24-11-19 19:17:46 | D | best error = [ 0.9001, 0.9001, 0.9001, 0.9001, 0.9001] +24-11-19 19:17:46 | D | + error = [0.9001] +24-11-19 19:17:46 | D | - Calibrating model.layers.11.mlp.up_proj.weight +24-11-19 19:17:46 | D | + w: sint8 +24-11-19 19:17:46 | D | + x: None +24-11-19 19:17:46 | D | + y: None +24-11-19 19:17:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:17:46 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:17:46 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:17:47 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:17:47 | D | - range ratio = [ 1.0000] +24-11-19 19:17:47 | D | sum error = [ 5.8967] +24-11-19 19:17:47 | D | best error = [ 5.8967] +24-11-19 19:17:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:17:47 | D | sum error = [ 5.8648, 5.8513, 5.8743, 5.9440, 6.0463] +24-11-19 19:17:47 | D | best error = [ 5.5134, 5.3595, 5.2767, 5.2300, 5.2060] +24-11-19 19:17:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:17:47 | D | sum error = [ 6.2068, 6.4161, 6.6829, 6.9981, 7.3705] +24-11-19 19:17:47 | D | best error = [ 5.1934, 5.1885, 5.1866, 5.1860, 5.1859] +24-11-19 19:17:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:17:47 | D | sum error = [ 7.8015, 8.2825, 8.8186, 9.4264, 10.0645] +24-11-19 19:17:47 | D | best error = [ 5.1858, 5.1858, 5.1858, 5.1858, 5.1858] +24-11-19 19:17:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:17:47 | D | sum error = [ 10.7816, 11.5632, 12.3790, 13.2851, 14.2257] +24-11-19 19:17:47 | D | best error = [ 5.1858, 5.1858, 5.1858, 5.1858, 5.1858] +24-11-19 19:17:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:17:47 | D | sum error = [ 15.2433, 16.3215, 17.4912, 18.7118, 20.0208] +24-11-19 19:17:47 | D | best error = [ 5.1858, 5.1858, 5.1858, 5.1858, 5.1858] +24-11-19 19:17:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:17:47 | D | sum error = [ 21.4164, 22.8784, 24.4280, 26.0773, 27.8138] +24-11-19 19:17:47 | D | best error = [ 5.1858, 5.1858, 5.1858, 5.1858, 5.1858] +24-11-19 19:17:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:17:47 | D | sum error = [ 29.6524, 31.5865, 33.6369, 35.7827, 38.0691] +24-11-19 19:17:47 | D | best error = [ 5.1858, 5.1858, 5.1858, 5.1858, 5.1858] +24-11-19 19:17:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:17:47 | D | sum error = [ 40.4627, 42.9864, 45.6296, 48.4013, 51.3436] +24-11-19 19:17:47 | D | best error = [ 5.1858, 5.1858, 5.1858, 5.1858, 5.1858] +24-11-19 19:17:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:17:47 | D | sum error = [ 54.4175, 57.6588, 61.0561, 64.6021, 68.3448] +24-11-19 19:17:47 | D | best error = [ 5.1858, 5.1858, 5.1858, 5.1858, 5.1858] +24-11-19 19:17:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:17:47 | D | sum error = [ 72.2462, 76.3634, 80.6482, 85.1424, 89.8528] +24-11-19 19:17:47 | D | best error = [ 5.1858, 5.1858, 5.1858, 5.1858, 5.1858] +24-11-19 19:17:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:17:47 | D | sum error = [ 94.7881, 99.9326, 105.3144, 110.9491, 116.8161] +24-11-19 19:17:47 | D | best error = [ 5.1858, 5.1858, 5.1858, 5.1858, 5.1858] +24-11-19 19:17:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:17:47 | D | sum error = [ 122.9549, 129.3563, 136.0345, 142.9889, 150.2256] +24-11-19 19:17:47 | D | best error = [ 5.1858, 5.1858, 5.1858, 5.1858, 5.1858] +24-11-19 19:17:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:17:47 | D | sum error = [ 157.7768, 165.6265, 173.7803, 182.2500, 191.0485] +24-11-19 19:17:47 | D | best error = [ 5.1858, 5.1858, 5.1858, 5.1858, 5.1858] +24-11-19 19:17:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:17:47 | D | sum error = [ 200.1696, 209.6421, 219.4524, 229.6337, 240.1665] +24-11-19 19:17:47 | D | best error = [ 5.1858, 5.1858, 5.1858, 5.1858, 5.1858] +24-11-19 19:17:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:17:47 | D | sum error = [ 251.0686, 262.3541, 274.0141, 286.0695, 298.4929] +24-11-19 19:17:47 | D | best error = [ 5.1858, 5.1858, 5.1858, 5.1858, 5.1858] +24-11-19 19:17:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:17:47 | D | sum error = [ 311.3395, 324.5742, 338.2199, 352.2746, 366.7368] +24-11-19 19:17:47 | D | best error = [ 5.1858, 5.1858, 5.1858, 5.1858, 5.1858] +24-11-19 19:17:47 | D | + error = [5.1858] +24-11-19 19:17:48 | D | - Calibrating model.layers.11.mlp.gate_proj.weight +24-11-19 19:17:48 | D | + w: sint8 +24-11-19 19:17:48 | D | + x: None +24-11-19 19:17:48 | D | + y: None +24-11-19 19:17:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:17:48 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:17:48 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:17:48 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:17:48 | D | - range ratio = [ 1.0000] +24-11-19 19:17:48 | D | sum error = [ 6.2444] +24-11-19 19:17:48 | D | best error = [ 6.2444] +24-11-19 19:17:49 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:17:49 | D | sum error = [ 6.2030, 6.1873, 6.2248, 6.2787, 6.3904] +24-11-19 19:17:49 | D | best error = [ 5.8278, 5.6702, 5.5841, 5.5337, 5.5073] +24-11-19 19:17:49 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:17:49 | D | sum error = [ 6.5537, 6.7829, 7.0594, 7.4141, 7.7926] +24-11-19 19:17:49 | D | best error = [ 5.4949, 5.4899, 5.4882, 5.4879, 5.4877] +24-11-19 19:17:49 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:17:49 | D | sum error = [ 8.2535, 8.7637, 9.3457, 9.9888, 10.6774] +24-11-19 19:17:49 | D | best error = [ 5.4877, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 19:17:49 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:17:49 | D | sum error = [ 11.4497, 12.2913, 13.1842, 14.1227, 15.1668] +24-11-19 19:17:49 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 19:17:49 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:17:49 | D | sum error = [ 16.2640, 17.4577, 18.7191, 20.0563, 21.5033] +24-11-19 19:17:49 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 19:17:49 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:17:49 | D | sum error = [ 23.0240, 24.6573, 26.3793, 28.2336, 30.1763] +24-11-19 19:17:49 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 19:17:49 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:17:49 | D | sum error = [ 32.2369, 34.4264, 36.7510, 39.2155, 41.7983] +24-11-19 19:17:49 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 19:17:49 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:17:49 | D | sum error = [ 44.5805, 47.4947, 50.6060, 53.8463, 57.3440] +24-11-19 19:17:49 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 19:17:49 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:17:49 | D | sum error = [ 60.9850, 64.8565, 68.9538, 73.2795, 77.8278] +24-11-19 19:17:49 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 19:17:49 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:17:49 | D | sum error = [ 82.6716, 87.7627, 93.1488, 98.8136, 104.8249] +24-11-19 19:17:49 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 19:17:49 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:17:49 | D | sum error = [ 111.1568, 117.8254, 124.8701, 132.2692, 140.0316] +24-11-19 19:17:49 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 19:17:49 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:17:49 | D | sum error = [ 148.1956, 156.7939, 165.8136, 175.2726, 185.1968] +24-11-19 19:17:49 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 19:17:49 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:17:49 | D | sum error = [ 195.5825, 206.4846, 217.8698, 229.8012, 242.2703] +24-11-19 19:17:49 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 19:17:49 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:17:49 | D | sum error = [ 255.2994, 268.8699, 283.0102, 297.7383, 313.0497] +24-11-19 19:17:49 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 19:17:49 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:17:49 | D | sum error = [ 328.9893, 345.5262, 362.6879, 380.5096, 398.9384] +24-11-19 19:17:49 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 19:17:49 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:17:49 | D | sum error = [ 418.0178, 437.7343, 458.0975, 479.1189, 500.7910] +24-11-19 19:17:49 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 19:17:49 | D | + error = [5.4876] +24-11-19 19:17:49 | D | - Calibrating model.layers.11.mlp.down_proj.weight +24-11-19 19:17:49 | D | + w: sint8 +24-11-19 19:17:49 | D | + x: None +24-11-19 19:17:49 | D | + y: None +24-11-19 19:17:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:17:49 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:17:49 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:17:49 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:17:49 | D | - range ratio = [ 1.0000] +24-11-19 19:17:49 | D | sum error = [ 1.4773] +24-11-19 19:17:49 | D | best error = [ 1.4773] +24-11-19 19:17:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:17:50 | D | sum error = [ 1.4650, 1.4558, 1.4489, 1.4458, 1.4460] +24-11-19 19:17:50 | D | best error = [ 1.4247, 1.3988, 1.3804, 1.3668, 1.3573] +24-11-19 19:17:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:17:50 | D | sum error = [ 1.4526, 1.4634, 1.4841, 1.5088, 1.5452] +24-11-19 19:17:50 | D | best error = [ 1.3499, 1.3447, 1.3411, 1.3388, 1.3375] +24-11-19 19:17:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:17:50 | D | sum error = [ 1.5883, 1.6346, 1.6948, 1.7676, 1.8499] +24-11-19 19:17:50 | D | best error = [ 1.3366, 1.3359, 1.3356, 1.3354, 1.3352] +24-11-19 19:17:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:17:50 | D | sum error = [ 1.9452, 2.0485, 2.1694, 2.2943, 2.4365] +24-11-19 19:17:50 | D | best error = [ 1.3352, 1.3352, 1.3351, 1.3351, 1.3351] +24-11-19 19:17:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:17:50 | D | sum error = [ 2.5921, 2.7562, 2.9391, 3.1361, 3.3514] +24-11-19 19:17:50 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 19:17:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:17:50 | D | sum error = [ 3.5780, 3.8232, 4.0848, 4.3658, 4.6669] +24-11-19 19:17:50 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 19:17:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:17:50 | D | sum error = [ 4.9860, 5.3262, 5.6864, 6.0717, 6.4778] +24-11-19 19:17:50 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 19:17:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:17:50 | D | sum error = [ 6.9115, 7.3704, 7.8601, 8.3755, 8.9212] +24-11-19 19:17:50 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 19:17:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:17:50 | D | sum error = [ 9.4969, 10.1059, 10.7477, 11.4286, 12.1474] +24-11-19 19:17:50 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 19:17:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:17:50 | D | sum error = [ 12.9024, 13.6976, 14.5389, 15.4210, 16.3503] +24-11-19 19:17:50 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 19:17:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:17:50 | D | sum error = [ 17.3269, 18.3551, 19.4328, 20.5689, 21.7588] +24-11-19 19:17:50 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 19:17:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:17:50 | D | sum error = [ 23.0080, 24.3143, 25.6854, 27.1193, 28.6233] +24-11-19 19:17:50 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 19:17:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:17:50 | D | sum error = [ 30.1936, 31.8353, 33.5497, 35.3378, 37.2066] +24-11-19 19:17:50 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 19:17:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:17:50 | D | sum error = [ 39.1523, 41.1814, 43.2921, 45.4904, 47.7675] +24-11-19 19:17:50 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 19:17:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:17:50 | D | sum error = [ 50.1354, 52.5972, 55.1538, 57.8019, 60.5497] +24-11-19 19:17:50 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 19:17:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:17:50 | D | sum error = [ 63.3952, 66.3376, 69.3790, 72.5218, 75.7683] +24-11-19 19:17:50 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 19:17:50 | D | + error = [1.3351] +24-11-19 19:17:50 | D | - Quantizing model.layers.11.self_attn.q_proj.weight +24-11-19 19:17:51 | D | - Quantizing model.layers.11.self_attn.k_proj.weight +24-11-19 19:17:52 | D | - Quantizing model.layers.11.self_attn.v_proj.weight +24-11-19 19:17:53 | D | - Quantizing model.layers.11.self_attn.o_proj.weight +24-11-19 19:17:54 | D | - Quantizing model.layers.11.mlp.up_proj.weight +24-11-19 19:17:55 | D | - Quantizing model.layers.11.mlp.gate_proj.weight +24-11-19 19:17:56 | D | - Quantizing model.layers.11.mlp.down_proj.weight +24-11-19 19:18:04 | D | - Quantizing layer model.layers.12 +24-11-19 19:18:04 | D | - Calibrating model.layers.12.self_attn.q_proj.weight +24-11-19 19:18:04 | D | + w: sint8 +24-11-19 19:18:04 | D | + x: None +24-11-19 19:18:04 | D | + y: None +24-11-19 19:18:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:18:04 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:18:04 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:18:04 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:18:05 | D | - range ratio = [ 1.0000] +24-11-19 19:18:05 | D | sum error = [ 10.2844] +24-11-19 19:18:05 | D | best error = [ 10.2844] +24-11-19 19:18:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:18:17 | D | sum error = [ 10.2282, 10.2895, 10.2929, 10.2877, 10.6592] +24-11-19 19:18:17 | D | best error = [ 10.2282, 10.2282, 10.2282, 10.2282, 10.2282] +24-11-19 19:18:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:18:17 | D | sum error = [ 10.8929, 11.4490, 11.9359, 12.3683, 13.2820] +24-11-19 19:18:17 | D | best error = [ 10.2282, 10.2282, 10.2282, 10.2282, 10.2282] +24-11-19 19:18:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:18:17 | D | sum error = [ 14.2046, 14.9213, 16.0692, 17.6587, 18.6991] +24-11-19 19:18:17 | D | best error = [ 10.2282, 10.2282, 10.2282, 10.2282, 10.2282] +24-11-19 19:18:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:18:17 | D | sum error = [ 20.2863, 22.2475, 24.0741, 26.0709, 27.9133] +24-11-19 19:18:17 | D | best error = [ 10.2282, 10.2282, 10.2282, 10.2282, 10.2282] +24-11-19 19:18:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:18:17 | D | sum error = [ 30.4626, 32.6898, 36.1014, 39.2554, 41.9840] +24-11-19 19:18:17 | D | best error = [ 10.2282, 10.2282, 10.2282, 10.2282, 10.2282] +24-11-19 19:18:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:18:17 | D | sum error = [ 45.1649, 48.8845, 53.1768, 57.0626, 61.3850] +24-11-19 19:18:17 | D | best error = [ 10.2282, 10.2282, 10.2282, 10.2282, 10.2282] +24-11-19 19:18:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:18:17 | D | sum error = [ 66.3377, 71.3166, 77.0221, 83.3496, 89.2806] +24-11-19 19:18:17 | D | best error = [ 10.2282, 10.2282, 10.2282, 10.2282, 10.2282] +24-11-19 19:18:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:18:17 | D | sum error = [ 96.2946, 103.3164, 110.9121, 119.1371, 127.8727] +24-11-19 19:18:17 | D | best error = [ 10.2282, 10.2282, 10.2282, 10.2282, 10.2282] +24-11-19 19:18:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:18:17 | D | sum error = [ 137.8436, 148.2240, 159.2151, 171.3017, 184.4872] +24-11-19 19:18:17 | D | best error = [ 10.2282, 10.2282, 10.2282, 10.2282, 10.2282] +24-11-19 19:18:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:18:17 | D | sum error = [ 197.9814, 213.4403, 229.3217, 246.4760, 265.0633] +24-11-19 19:18:17 | D | best error = [ 10.2282, 10.2282, 10.2282, 10.2282, 10.2282] +24-11-19 19:18:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:18:17 | D | sum error = [ 285.0271, 306.1731, 329.4024, 353.6423, 379.4314] +24-11-19 19:18:17 | D | best error = [ 10.2282, 10.2282, 10.2282, 10.2282, 10.2282] +24-11-19 19:18:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:18:17 | D | sum error = [ 407.2109, 436.6026, 468.1721, 501.9608, 537.9396] +24-11-19 19:18:17 | D | best error = [ 10.2282, 10.2282, 10.2282, 10.2282, 10.2282] +24-11-19 19:18:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:18:17 | D | sum error = [ 576.3791, 617.7648, 661.9989, 708.2545, 758.1346] +24-11-19 19:18:17 | D | best error = [ 10.2282, 10.2282, 10.2282, 10.2282, 10.2282] +24-11-19 19:18:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:18:17 | D | sum error = [ 811.0398, 867.2670, 926.8412, 990.3289, 1057.1431] +24-11-19 19:18:17 | D | best error = [ 10.2282, 10.2282, 10.2282, 10.2282, 10.2282] +24-11-19 19:18:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:18:17 | D | sum error = [ 1127.7675, 1202.0159, 1280.3967, 1361.8088, 1446.5909] +24-11-19 19:18:17 | D | best error = [ 10.2282, 10.2282, 10.2282, 10.2282, 10.2282] +24-11-19 19:18:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:18:17 | D | sum error = [ 1535.0223, 1625.7713, 1719.1693, 1814.0547, 1909.9685] +24-11-19 19:18:17 | D | best error = [ 10.2282, 10.2282, 10.2282, 10.2282, 10.2282] +24-11-19 19:18:17 | D | + error = [10.2282] +24-11-19 19:18:17 | D | - Calibrating model.layers.12.self_attn.k_proj.weight +24-11-19 19:18:17 | D | + w: sint8 +24-11-19 19:18:17 | D | + x: None +24-11-19 19:18:17 | D | + y: None +24-11-19 19:18:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:18:17 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:18:17 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:18:17 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:18:18 | D | - range ratio = [ 1.0000] +24-11-19 19:18:18 | D | sum error = [ 10.6760] +24-11-19 19:18:18 | D | best error = [ 10.6760] +24-11-19 19:18:30 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:18:30 | D | sum error = [ 10.2407, 10.8296, 10.7425, 10.8142, 10.3854] +24-11-19 19:18:30 | D | best error = [ 10.2407, 10.2407, 10.2407, 10.2407, 10.2407] +24-11-19 19:18:30 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:18:30 | D | sum error = [ 11.3288, 11.4429, 12.2349, 12.6797, 13.2443] +24-11-19 19:18:30 | D | best error = [ 10.2407, 10.2407, 10.2407, 10.2407, 10.2407] +24-11-19 19:18:30 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:18:30 | D | sum error = [ 14.0989, 14.5013, 15.6469, 16.6525, 18.2614] +24-11-19 19:18:30 | D | best error = [ 10.2407, 10.2407, 10.2407, 10.2407, 10.2407] +24-11-19 19:18:30 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:18:30 | D | sum error = [ 19.2753, 20.8598, 22.8252, 24.6978, 26.2188] +24-11-19 19:18:30 | D | best error = [ 10.2407, 10.2407, 10.2407, 10.2407, 10.2407] +24-11-19 19:18:30 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:18:30 | D | sum error = [ 28.0277, 30.2621, 33.0606, 35.2495, 37.8843] +24-11-19 19:18:30 | D | best error = [ 10.2407, 10.2407, 10.2407, 10.2407, 10.2407] +24-11-19 19:18:30 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:18:30 | D | sum error = [ 40.4901, 43.4619, 47.1975, 51.1566, 54.0976] +24-11-19 19:18:30 | D | best error = [ 10.2407, 10.2407, 10.2407, 10.2407, 10.2407] +24-11-19 19:18:30 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:18:30 | D | sum error = [ 58.8013, 63.3151, 67.6811, 72.8435, 78.2397] +24-11-19 19:18:30 | D | best error = [ 10.2407, 10.2407, 10.2407, 10.2407, 10.2407] +24-11-19 19:18:30 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:18:30 | D | sum error = [ 83.9909, 90.8672, 97.7019, 105.5517, 113.2123] +24-11-19 19:18:30 | D | best error = [ 10.2407, 10.2407, 10.2407, 10.2407, 10.2407] +24-11-19 19:18:30 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:18:30 | D | sum error = [ 121.4698, 131.3890, 141.0374, 152.1910, 163.0380] +24-11-19 19:18:30 | D | best error = [ 10.2407, 10.2407, 10.2407, 10.2407, 10.2407] +24-11-19 19:18:30 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:18:30 | D | sum error = [ 175.8534, 191.0543, 204.9076, 221.2389, 239.2397] +24-11-19 19:18:30 | D | best error = [ 10.2407, 10.2407, 10.2407, 10.2407, 10.2407] +24-11-19 19:18:30 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:18:30 | D | sum error = [ 255.8280, 276.1647, 296.3186, 319.7334, 343.9565] +24-11-19 19:18:30 | D | best error = [ 10.2407, 10.2407, 10.2407, 10.2407, 10.2407] +24-11-19 19:18:30 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:18:30 | D | sum error = [ 368.7250, 399.6273, 427.2983, 457.4083, 493.9112] +24-11-19 19:18:30 | D | best error = [ 10.2407, 10.2407, 10.2407, 10.2407, 10.2407] +24-11-19 19:18:30 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:18:30 | D | sum error = [ 529.1843, 564.8053, 610.4943, 651.8058, 701.1541] +24-11-19 19:18:30 | D | best error = [ 10.2407, 10.2407, 10.2407, 10.2407, 10.2407] +24-11-19 19:18:30 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:18:30 | D | sum error = [ 749.6613, 804.6476, 863.0804, 925.8856, 994.7191] +24-11-19 19:18:30 | D | best error = [ 10.2407, 10.2407, 10.2407, 10.2407, 10.2407] +24-11-19 19:18:30 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:18:30 | D | sum error = [ 1060.2206, 1133.0329, 1214.8130, 1297.3447, 1375.3572] +24-11-19 19:18:30 | D | best error = [ 10.2407, 10.2407, 10.2407, 10.2407, 10.2407] +24-11-19 19:18:30 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:18:30 | D | sum error = [ 1467.8320, 1557.0810, 1655.0356, 1750.3094, 1843.1806] +24-11-19 19:18:30 | D | best error = [ 10.2407, 10.2407, 10.2407, 10.2407, 10.2407] +24-11-19 19:18:30 | D | + error = [10.2407] +24-11-19 19:18:30 | D | - Calibrating model.layers.12.self_attn.v_proj.weight +24-11-19 19:18:30 | D | + w: sint8 +24-11-19 19:18:30 | D | + x: None +24-11-19 19:18:30 | D | + y: None +24-11-19 19:18:30 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:18:30 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:18:30 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:18:30 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:18:30 | D | - range ratio = [ 1.0000] +24-11-19 19:18:30 | D | sum error = [ 4.6459] +24-11-19 19:18:30 | D | best error = [ 4.6459] +24-11-19 19:18:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:18:31 | D | sum error = [ 4.5951, 4.5834, 4.6234, 4.6632, 4.7592] +24-11-19 19:18:31 | D | best error = [ 4.3299, 4.2096, 4.1516, 4.1121, 4.0946] +24-11-19 19:18:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:18:31 | D | sum error = [ 4.8809, 5.0241, 5.2426, 5.4987, 5.7910] +24-11-19 19:18:31 | D | best error = [ 4.0867, 4.0827, 4.0816, 4.0814, 4.0813] +24-11-19 19:18:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:18:31 | D | sum error = [ 6.1181, 6.4931, 6.9257, 7.3964, 7.9225] +24-11-19 19:18:31 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 19:18:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:18:31 | D | sum error = [ 8.4831, 9.0884, 9.7511, 10.4521, 11.2149] +24-11-19 19:18:31 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 19:18:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:18:31 | D | sum error = [ 12.0061, 12.8747, 13.8079, 14.8005, 15.8066] +24-11-19 19:18:31 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 19:18:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:18:31 | D | sum error = [ 16.9061, 18.0577, 19.2810, 20.5749, 21.9565] +24-11-19 19:18:31 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 19:18:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:18:31 | D | sum error = [ 23.4133, 24.9266, 26.5566, 28.2510, 30.0623] +24-11-19 19:18:31 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 19:18:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:18:31 | D | sum error = [ 31.9262, 33.9482, 36.0497, 38.2320, 40.5694] +24-11-19 19:18:31 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 19:18:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:18:31 | D | sum error = [ 43.0094, 45.5926, 48.2894, 51.1401, 54.1301] +24-11-19 19:18:31 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 19:18:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:18:31 | D | sum error = [ 57.2734, 60.5390, 63.9819, 67.5897, 71.3614] +24-11-19 19:18:31 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 19:18:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:18:31 | D | sum error = [ 75.2947, 79.4380, 83.7498, 88.2723, 92.9951] +24-11-19 19:18:31 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 19:18:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:18:31 | D | sum error = [ 97.9195, 103.0703, 108.4298, 114.0170, 119.8437] +24-11-19 19:18:31 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 19:18:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:18:31 | D | sum error = [ 125.9298, 132.2537, 138.8337, 145.6699, 152.7713] +24-11-19 19:18:31 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 19:18:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:18:31 | D | sum error = [ 160.1581, 167.8077, 175.7303, 183.9608, 192.4691] +24-11-19 19:18:31 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 19:18:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:18:31 | D | sum error = [ 201.2910, 210.4151, 219.8461, 229.6076, 239.6792] +24-11-19 19:18:31 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 19:18:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:18:31 | D | sum error = [ 250.0816, 260.8095, 271.8628, 283.2425, 294.9707] +24-11-19 19:18:31 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 19:18:31 | D | + error = [4.0813] +24-11-19 19:18:31 | D | - Calibrating model.layers.12.self_attn.o_proj.weight +24-11-19 19:18:31 | D | + w: sint8 +24-11-19 19:18:31 | D | + x: None +24-11-19 19:18:31 | D | + y: None +24-11-19 19:18:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:18:31 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:18:31 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:18:31 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:18:31 | D | - range ratio = [ 1.0000] +24-11-19 19:18:31 | D | sum error = [ 1.1831] +24-11-19 19:18:31 | D | best error = [ 1.1831] +24-11-19 19:18:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:18:31 | D | sum error = [ 1.1709, 1.1592, 1.1589, 1.1621, 1.1670] +24-11-19 19:18:31 | D | best error = [ 1.1020, 1.0621, 1.0379, 1.0220, 1.0095] +24-11-19 19:18:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:18:31 | D | sum error = [ 1.1713, 1.1854, 1.2072, 1.2296, 1.2699] +24-11-19 19:18:31 | D | best error = [ 1.0010, 0.9940, 0.9883, 0.9838, 0.9810] +24-11-19 19:18:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:18:31 | D | sum error = [ 1.3103, 1.3595, 1.4177, 1.4816, 1.5493] +24-11-19 19:18:31 | D | best error = [ 0.9784, 0.9765, 0.9750, 0.9739, 0.9731] +24-11-19 19:18:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:18:31 | D | sum error = [ 1.6307, 1.7241, 1.8169, 1.9255, 2.0410] +24-11-19 19:18:31 | D | best error = [ 0.9726, 0.9722, 0.9718, 0.9714, 0.9712] +24-11-19 19:18:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:18:31 | D | sum error = [ 2.1684, 2.3057, 2.4536, 2.6061, 2.7787] +24-11-19 19:18:31 | D | best error = [ 0.9711, 0.9709, 0.9708, 0.9708, 0.9708] +24-11-19 19:18:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:18:31 | D | sum error = [ 2.9583, 3.1539, 3.3594, 3.5744, 3.8095] +24-11-19 19:18:31 | D | best error = [ 0.9708, 0.9707, 0.9707, 0.9707, 0.9707] +24-11-19 19:18:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:18:31 | D | sum error = [ 4.0575, 4.3171, 4.5945, 4.8904, 5.1986] +24-11-19 19:18:31 | D | best error = [ 0.9707, 0.9707, 0.9707, 0.9707, 0.9707] +24-11-19 19:18:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:18:31 | D | sum error = [ 5.5273, 5.8683, 6.2345, 6.6239, 7.0279] +24-11-19 19:18:31 | D | best error = [ 0.9707, 0.9707, 0.9707, 0.9707, 0.9707] +24-11-19 19:18:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:18:31 | D | sum error = [ 7.4588, 7.9103, 8.3835, 8.8858, 9.4144] +24-11-19 19:18:31 | D | best error = [ 0.9707, 0.9707, 0.9707, 0.9707, 0.9707] +24-11-19 19:18:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:18:31 | D | sum error = [ 9.9682, 10.5527, 11.1622, 11.8067, 12.4820] +24-11-19 19:18:31 | D | best error = [ 0.9707, 0.9707, 0.9707, 0.9707, 0.9707] +24-11-19 19:18:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:18:31 | D | sum error = [ 13.1973, 13.9408, 14.7247, 15.5443, 16.4035] +24-11-19 19:18:31 | D | best error = [ 0.9707, 0.9707, 0.9707, 0.9707, 0.9707] +24-11-19 19:18:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:18:31 | D | sum error = [ 17.3025, 18.2407, 19.2256, 20.2518, 21.3240] +24-11-19 19:18:31 | D | best error = [ 0.9707, 0.9707, 0.9707, 0.9707, 0.9707] +24-11-19 19:18:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:18:31 | D | sum error = [ 22.4466, 23.6146, 24.8385, 26.1106, 27.4370] +24-11-19 19:18:31 | D | best error = [ 0.9707, 0.9707, 0.9707, 0.9707, 0.9707] +24-11-19 19:18:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:18:31 | D | sum error = [ 28.8198, 30.2605, 31.7592, 33.3154, 34.9377] +24-11-19 19:18:31 | D | best error = [ 0.9707, 0.9707, 0.9707, 0.9707, 0.9707] +24-11-19 19:18:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:18:31 | D | sum error = [ 36.6207, 38.3664, 40.1776, 42.0559, 44.0055] +24-11-19 19:18:31 | D | best error = [ 0.9707, 0.9707, 0.9707, 0.9707, 0.9707] +24-11-19 19:18:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:18:31 | D | sum error = [ 46.0228, 48.1064, 50.2568, 52.4813, 54.7784] +24-11-19 19:18:31 | D | best error = [ 0.9707, 0.9707, 0.9707, 0.9707, 0.9707] +24-11-19 19:18:31 | D | + error = [0.9707] +24-11-19 19:18:31 | D | - Calibrating model.layers.12.mlp.up_proj.weight +24-11-19 19:18:31 | D | + w: sint8 +24-11-19 19:18:31 | D | + x: None +24-11-19 19:18:31 | D | + y: None +24-11-19 19:18:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:18:31 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:18:31 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:18:32 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:18:32 | D | - range ratio = [ 1.0000] +24-11-19 19:18:32 | D | sum error = [ 6.1527] +24-11-19 19:18:32 | D | best error = [ 6.1527] +24-11-19 19:18:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:18:33 | D | sum error = [ 6.1113, 6.0893, 6.1191, 6.1871, 6.3088] +24-11-19 19:18:33 | D | best error = [ 5.7407, 5.5777, 5.4921, 5.4430, 5.4177] +24-11-19 19:18:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:18:33 | D | sum error = [ 6.4502, 6.6850, 6.9269, 7.2823, 7.6471] +24-11-19 19:18:33 | D | best error = [ 5.4061, 5.4012, 5.3991, 5.3985, 5.3985] +24-11-19 19:18:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:18:33 | D | sum error = [ 8.0934, 8.6084, 9.1642, 9.7617, 10.4474] +24-11-19 19:18:33 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 19:18:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:18:33 | D | sum error = [ 11.2022, 11.9927, 12.8629, 13.7795, 14.7703] +24-11-19 19:18:33 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 19:18:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:18:33 | D | sum error = [ 15.8322, 16.9703, 18.1542, 19.4294, 20.7889] +24-11-19 19:18:33 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 19:18:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:18:33 | D | sum error = [ 22.2258, 23.7496, 25.3585, 27.0506, 28.8562] +24-11-19 19:18:33 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 19:18:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:18:33 | D | sum error = [ 30.7625, 32.7605, 34.8825, 37.1081, 39.4629] +24-11-19 19:18:33 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 19:18:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:18:33 | D | sum error = [ 41.9425, 44.5368, 47.2798, 50.1553, 53.1828] +24-11-19 19:18:33 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 19:18:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:18:33 | D | sum error = [ 56.3457, 59.6815, 63.1749, 66.8437, 70.7060] +24-11-19 19:18:33 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 19:18:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:18:33 | D | sum error = [ 74.7466, 78.9586, 83.3820, 88.0132, 92.8769] +24-11-19 19:18:33 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 19:18:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:18:33 | D | sum error = [ 97.9492, 103.2418, 108.7809, 114.5685, 120.6135] +24-11-19 19:18:33 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 19:18:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:18:33 | D | sum error = [ 126.9093, 133.4863, 140.3346, 147.4698, 154.9042] +24-11-19 19:18:33 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 19:18:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:18:33 | D | sum error = [ 162.6448, 170.6895, 179.0635, 187.7677, 196.8154] +24-11-19 19:18:33 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 19:18:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:18:33 | D | sum error = [ 206.2055, 215.9490, 226.0517, 236.5275, 247.3554] +24-11-19 19:18:33 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 19:18:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:18:33 | D | sum error = [ 258.5881, 270.1932, 282.1901, 294.5801, 307.3661] +24-11-19 19:18:33 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 19:18:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:18:33 | D | sum error = [ 320.5628, 334.1622, 348.1727, 362.5990, 377.4415] +24-11-19 19:18:33 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 19:18:33 | D | + error = [5.3984] +24-11-19 19:18:33 | D | - Calibrating model.layers.12.mlp.gate_proj.weight +24-11-19 19:18:33 | D | + w: sint8 +24-11-19 19:18:33 | D | + x: None +24-11-19 19:18:33 | D | + y: None +24-11-19 19:18:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:18:33 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:18:33 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:18:33 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:18:33 | D | - range ratio = [ 1.0000] +24-11-19 19:18:33 | D | sum error = [ 6.4117] +24-11-19 19:18:33 | D | best error = [ 6.4117] +24-11-19 19:18:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:18:34 | D | sum error = [ 6.3730, 6.3468, 6.3863, 6.4427, 6.5695] +24-11-19 19:18:34 | D | best error = [ 5.9816, 5.8119, 5.7246, 5.6759, 5.6493] +24-11-19 19:18:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:18:34 | D | sum error = [ 6.7513, 6.9809, 7.2660, 7.6065, 8.0018] +24-11-19 19:18:34 | D | best error = [ 5.6365, 5.6309, 5.6287, 5.6281, 5.6280] +24-11-19 19:18:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:18:34 | D | sum error = [ 8.4811, 9.0037, 9.5973, 10.2539, 10.9895] +24-11-19 19:18:34 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 19:18:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:18:34 | D | sum error = [ 11.7747, 12.6336, 13.5449, 14.5289, 15.5915] +24-11-19 19:18:34 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 19:18:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:18:34 | D | sum error = [ 16.7318, 17.9441, 19.2317, 20.6148, 22.0724] +24-11-19 19:18:34 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 19:18:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:18:34 | D | sum error = [ 23.6374, 25.3001, 27.0534, 28.9067, 30.9014] +24-11-19 19:18:34 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 19:18:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:18:34 | D | sum error = [ 32.9752, 35.2035, 37.5527, 40.0467, 42.6939] +24-11-19 19:18:34 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 19:18:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:18:34 | D | sum error = [ 45.5000, 48.4498, 51.5868, 54.8872, 58.3713] +24-11-19 19:18:34 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 19:18:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:18:34 | D | sum error = [ 62.0745, 65.9893, 70.1388, 74.5009, 79.1160] +24-11-19 19:18:34 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 19:18:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:18:34 | D | sum error = [ 83.9698, 89.1093, 94.5360, 100.2260, 106.2473] +24-11-19 19:18:34 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 19:18:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:18:34 | D | sum error = [ 112.5880, 119.2599, 126.2842, 133.6660, 141.4290] +24-11-19 19:18:34 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 19:18:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:18:34 | D | sum error = [ 149.5790, 158.1309, 167.0987, 176.5122, 186.3900] +24-11-19 19:18:34 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 19:18:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:18:34 | D | sum error = [ 196.7282, 207.5544, 218.8850, 230.7369, 243.1478] +24-11-19 19:18:34 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 19:18:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:18:34 | D | sum error = [ 256.0977, 269.6243, 283.7218, 298.4087, 313.6768] +24-11-19 19:18:34 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 19:18:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:18:34 | D | sum error = [ 329.5703, 346.0894, 363.2257, 380.9729, 399.3668] +24-11-19 19:18:34 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 19:18:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:18:34 | D | sum error = [ 418.4157, 438.0983, 458.4359, 479.4176, 501.0456] +24-11-19 19:18:34 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 19:18:34 | D | + error = [5.6280] +24-11-19 19:18:34 | D | - Calibrating model.layers.12.mlp.down_proj.weight +24-11-19 19:18:34 | D | + w: sint8 +24-11-19 19:18:34 | D | + x: None +24-11-19 19:18:34 | D | + y: None +24-11-19 19:18:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:18:34 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:18:34 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:18:34 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:18:34 | D | - range ratio = [ 1.0000] +24-11-19 19:18:34 | D | sum error = [ 1.5792] +24-11-19 19:18:34 | D | best error = [ 1.5792] +24-11-19 19:18:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:18:35 | D | sum error = [ 1.5653, 1.5541, 1.5507, 1.5437, 1.5459] +24-11-19 19:18:35 | D | best error = [ 1.5246, 1.4961, 1.4779, 1.4643, 1.4539] +24-11-19 19:18:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:18:35 | D | sum error = [ 1.5533, 1.5658, 1.5871, 1.6129, 1.6502] +24-11-19 19:18:35 | D | best error = [ 1.4458, 1.4406, 1.4366, 1.4341, 1.4321] +24-11-19 19:18:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:18:35 | D | sum error = [ 1.6922, 1.7471, 1.8147, 1.8886, 1.9764] +24-11-19 19:18:35 | D | best error = [ 1.4308, 1.4300, 1.4296, 1.4293, 1.4292] +24-11-19 19:18:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:18:35 | D | sum error = [ 2.0784, 2.1867, 2.3105, 2.4468, 2.5972] +24-11-19 19:18:35 | D | best error = [ 1.4291, 1.4290, 1.4290, 1.4289, 1.4289] +24-11-19 19:18:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:18:35 | D | sum error = [ 2.7630, 2.9412, 3.1337, 3.3458, 3.5714] +24-11-19 19:18:35 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 19:18:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:18:35 | D | sum error = [ 3.8094, 4.0697, 4.3495, 4.6474, 4.9628] +24-11-19 19:18:35 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 19:18:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:18:35 | D | sum error = [ 5.3026, 5.6600, 6.0441, 6.4514, 6.8823] +24-11-19 19:18:35 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 19:18:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:18:35 | D | sum error = [ 7.3408, 7.8274, 8.3450, 8.8892, 9.4649] +24-11-19 19:18:35 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 19:18:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:18:35 | D | sum error = [ 10.0717, 10.7163, 11.3968, 12.1158, 12.8724] +24-11-19 19:18:35 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 19:18:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:18:35 | D | sum error = [ 13.6713, 14.5155, 15.4050, 16.3401, 17.3200] +24-11-19 19:18:35 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 19:18:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:18:35 | D | sum error = [ 18.3562, 19.4423, 20.5820, 21.7800, 23.0384] +24-11-19 19:18:35 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 19:18:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:18:35 | D | sum error = [ 24.3570, 25.7389, 27.1877, 28.7020, 30.2873] +24-11-19 19:18:35 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 19:18:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:18:35 | D | sum error = [ 31.9443, 33.6756, 35.4843, 37.3718, 39.3380] +24-11-19 19:18:35 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 19:18:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:18:35 | D | sum error = [ 41.3905, 43.5267, 45.7520, 48.0705, 50.4722] +24-11-19 19:18:35 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 19:18:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:18:35 | D | sum error = [ 52.9746, 55.5704, 58.2663, 61.0586, 63.9526] +24-11-19 19:18:35 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 19:18:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:18:35 | D | sum error = [ 66.9519, 70.0512, 73.2588, 76.5747, 79.9976] +24-11-19 19:18:35 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 19:18:35 | D | + error = [1.4289] +24-11-19 19:18:35 | D | - Quantizing model.layers.12.self_attn.q_proj.weight +24-11-19 19:18:36 | D | - Quantizing model.layers.12.self_attn.k_proj.weight +24-11-19 19:18:37 | D | - Quantizing model.layers.12.self_attn.v_proj.weight +24-11-19 19:18:38 | D | - Quantizing model.layers.12.self_attn.o_proj.weight +24-11-19 19:18:39 | D | - Quantizing model.layers.12.mlp.up_proj.weight +24-11-19 19:18:40 | D | - Quantizing model.layers.12.mlp.gate_proj.weight +24-11-19 19:18:41 | D | - Quantizing model.layers.12.mlp.down_proj.weight +24-11-19 19:18:49 | D | - Quantizing layer model.layers.13 +24-11-19 19:18:49 | D | - Calibrating model.layers.13.self_attn.q_proj.weight +24-11-19 19:18:49 | D | + w: sint8 +24-11-19 19:18:49 | D | + x: None +24-11-19 19:18:49 | D | + y: None +24-11-19 19:18:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:18:49 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:18:49 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:18:49 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:18:50 | D | - range ratio = [ 1.0000] +24-11-19 19:18:50 | D | sum error = [ 10.1321] +24-11-19 19:18:50 | D | best error = [ 10.1321] +24-11-19 19:19:02 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:19:02 | D | sum error = [ 10.1483, 10.1012, 10.2031, 10.2397, 10.5548] +24-11-19 19:19:02 | D | best error = [ 10.1321, 10.1012, 10.1012, 10.1012, 10.1012] +24-11-19 19:19:02 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:19:02 | D | sum error = [ 10.8774, 11.0764, 11.5369, 12.2848, 12.8564] +24-11-19 19:19:02 | D | best error = [ 10.1012, 10.1012, 10.1012, 10.1012, 10.1012] +24-11-19 19:19:02 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:19:02 | D | sum error = [ 13.5074, 14.6708, 15.6637, 16.8921, 18.1717] +24-11-19 19:19:02 | D | best error = [ 10.1012, 10.1012, 10.1012, 10.1012, 10.1012] +24-11-19 19:19:02 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:19:02 | D | sum error = [ 19.5171, 21.1514, 23.0993, 25.2559, 27.4016] +24-11-19 19:19:02 | D | best error = [ 10.1012, 10.1012, 10.1012, 10.1012, 10.1012] +24-11-19 19:19:02 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:19:02 | D | sum error = [ 29.3752, 32.3591, 35.2120, 38.0129, 41.0950] +24-11-19 19:19:02 | D | best error = [ 10.1012, 10.1012, 10.1012, 10.1012, 10.1012] +24-11-19 19:19:02 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:19:02 | D | sum error = [ 45.0215, 49.0144, 53.5700, 57.8990, 63.1769] +24-11-19 19:19:02 | D | best error = [ 10.1012, 10.1012, 10.1012, 10.1012, 10.1012] +24-11-19 19:19:02 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:19:02 | D | sum error = [ 69.0964, 74.8733, 81.2029, 88.4835, 95.8423] +24-11-19 19:19:02 | D | best error = [ 10.1012, 10.1012, 10.1012, 10.1012, 10.1012] +24-11-19 19:19:02 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:19:02 | D | sum error = [ 104.0907, 113.0680, 122.2254, 131.7673, 142.5892] +24-11-19 19:19:02 | D | best error = [ 10.1012, 10.1012, 10.1012, 10.1012, 10.1012] +24-11-19 19:19:02 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:19:02 | D | sum error = [ 153.8584, 166.4493, 179.2235, 193.2367, 207.8377] +24-11-19 19:19:02 | D | best error = [ 10.1012, 10.1012, 10.1012, 10.1012, 10.1012] +24-11-19 19:19:02 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:19:02 | D | sum error = [ 223.6548, 240.6567, 258.8455, 278.0298, 299.0690] +24-11-19 19:19:02 | D | best error = [ 10.1012, 10.1012, 10.1012, 10.1012, 10.1012] +24-11-19 19:19:02 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:19:02 | D | sum error = [ 321.2660, 345.0293, 370.5002, 397.7888, 427.0913] +24-11-19 19:19:02 | D | best error = [ 10.1012, 10.1012, 10.1012, 10.1012, 10.1012] +24-11-19 19:19:02 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:19:02 | D | sum error = [ 458.2378, 491.5592, 527.3275, 565.5321, 606.5642] +24-11-19 19:19:02 | D | best error = [ 10.1012, 10.1012, 10.1012, 10.1012, 10.1012] +24-11-19 19:19:02 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:19:02 | D | sum error = [ 650.1304, 697.8234, 748.4162, 802.3157, 860.2365] +24-11-19 19:19:02 | D | best error = [ 10.1012, 10.1012, 10.1012, 10.1012, 10.1012] +24-11-19 19:19:02 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:19:02 | D | sum error = [ 922.0010, 988.7853, 1058.9931, 1134.6005, 1214.7031] +24-11-19 19:19:02 | D | best error = [ 10.1012, 10.1012, 10.1012, 10.1012, 10.1012] +24-11-19 19:19:02 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:19:02 | D | sum error = [ 1300.2976, 1390.9448, 1486.8620, 1588.3371, 1695.1032] +24-11-19 19:19:02 | D | best error = [ 10.1012, 10.1012, 10.1012, 10.1012, 10.1012] +24-11-19 19:19:02 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:19:02 | D | sum error = [ 1807.1301, 1923.9388, 2044.6676, 2168.5331, 2294.3574] +24-11-19 19:19:02 | D | best error = [ 10.1012, 10.1012, 10.1012, 10.1012, 10.1012] +24-11-19 19:19:02 | D | + error = [10.1012] +24-11-19 19:19:02 | D | - Calibrating model.layers.13.self_attn.k_proj.weight +24-11-19 19:19:02 | D | + w: sint8 +24-11-19 19:19:02 | D | + x: None +24-11-19 19:19:02 | D | + y: None +24-11-19 19:19:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:19:02 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:19:02 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:19:02 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:19:03 | D | - range ratio = [ 1.0000] +24-11-19 19:19:03 | D | sum error = [ 10.5483] +24-11-19 19:19:03 | D | best error = [ 10.5483] +24-11-19 19:19:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:19:15 | D | sum error = [ 10.4097, 10.5413, 10.8442, 10.8085, 11.7501] +24-11-19 19:19:15 | D | best error = [ 10.4097, 10.4097, 10.4097, 10.4097, 10.4097] +24-11-19 19:19:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:19:15 | D | sum error = [ 11.0740, 12.2299, 11.8732, 13.1902, 13.4138] +24-11-19 19:19:15 | D | best error = [ 10.4097, 10.4097, 10.4097, 10.4097, 10.4097] +24-11-19 19:19:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:19:15 | D | sum error = [ 14.7444, 15.4776, 17.0949, 17.7960, 18.4666] +24-11-19 19:19:15 | D | best error = [ 10.4097, 10.4097, 10.4097, 10.4097, 10.4097] +24-11-19 19:19:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:19:15 | D | sum error = [ 20.2647, 21.4396, 23.7183, 25.2158, 27.1683] +24-11-19 19:19:15 | D | best error = [ 10.4097, 10.4097, 10.4097, 10.4097, 10.4097] +24-11-19 19:19:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:19:15 | D | sum error = [ 29.8072, 32.2171, 34.5994, 38.1338, 41.0978] +24-11-19 19:19:15 | D | best error = [ 10.4097, 10.4097, 10.4097, 10.4097, 10.4097] +24-11-19 19:19:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:19:15 | D | sum error = [ 43.8422, 48.5740, 52.6695, 56.2893, 60.9829] +24-11-19 19:19:15 | D | best error = [ 10.4097, 10.4097, 10.4097, 10.4097, 10.4097] +24-11-19 19:19:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:19:15 | D | sum error = [ 66.6779, 72.0389, 77.9218, 84.5814, 91.7510] +24-11-19 19:19:15 | D | best error = [ 10.4097, 10.4097, 10.4097, 10.4097, 10.4097] +24-11-19 19:19:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:19:15 | D | sum error = [ 99.2115, 107.1995, 115.8573, 125.3044, 135.6308] +24-11-19 19:19:15 | D | best error = [ 10.4097, 10.4097, 10.4097, 10.4097, 10.4097] +24-11-19 19:19:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:19:15 | D | sum error = [ 146.8178, 158.9925, 171.6647, 185.7690, 199.2951] +24-11-19 19:19:15 | D | best error = [ 10.4097, 10.4097, 10.4097, 10.4097, 10.4097] +24-11-19 19:19:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:19:15 | D | sum error = [ 216.0789, 232.5176, 251.2536, 269.3070, 291.2670] +24-11-19 19:19:15 | D | best error = [ 10.4097, 10.4097, 10.4097, 10.4097, 10.4097] +24-11-19 19:19:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:19:15 | D | sum error = [ 314.6138, 337.6434, 362.2039, 389.1490, 419.7487] +24-11-19 19:19:15 | D | best error = [ 10.4097, 10.4097, 10.4097, 10.4097, 10.4097] +24-11-19 19:19:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:19:15 | D | sum error = [ 450.4323, 483.8069, 522.5240, 561.4894, 605.8218] +24-11-19 19:19:15 | D | best error = [ 10.4097, 10.4097, 10.4097, 10.4097, 10.4097] +24-11-19 19:19:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:19:15 | D | sum error = [ 651.5719, 696.6632, 756.3684, 809.6756, 872.9483] +24-11-19 19:19:15 | D | best error = [ 10.4097, 10.4097, 10.4097, 10.4097, 10.4097] +24-11-19 19:19:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:19:15 | D | sum error = [ 936.5184, 1007.5658, 1079.1923, 1161.1271, 1249.2725] +24-11-19 19:19:15 | D | best error = [ 10.4097, 10.4097, 10.4097, 10.4097, 10.4097] +24-11-19 19:19:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:19:15 | D | sum error = [ 1334.7600, 1435.1895, 1532.7340, 1638.9124, 1748.3870] +24-11-19 19:19:15 | D | best error = [ 10.4097, 10.4097, 10.4097, 10.4097, 10.4097] +24-11-19 19:19:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:19:15 | D | sum error = [ 1869.9866, 1990.6944, 2113.1478, 2232.6124, 2365.2648] +24-11-19 19:19:15 | D | best error = [ 10.4097, 10.4097, 10.4097, 10.4097, 10.4097] +24-11-19 19:19:15 | D | + error = [10.4097] +24-11-19 19:19:15 | D | - Calibrating model.layers.13.self_attn.v_proj.weight +24-11-19 19:19:15 | D | + w: sint8 +24-11-19 19:19:15 | D | + x: None +24-11-19 19:19:15 | D | + y: None +24-11-19 19:19:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:19:15 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:19:15 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:19:15 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:19:15 | D | - range ratio = [ 1.0000] +24-11-19 19:19:15 | D | sum error = [ 4.8724] +24-11-19 19:19:15 | D | best error = [ 4.8724] +24-11-19 19:19:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:19:15 | D | sum error = [ 4.8570, 4.8478, 4.8928, 4.9403, 5.0350] +24-11-19 19:19:15 | D | best error = [ 4.5666, 4.4406, 4.3757, 4.3401, 4.3216] +24-11-19 19:19:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:19:15 | D | sum error = [ 5.1420, 5.3159, 5.5353, 5.7934, 6.0996] +24-11-19 19:19:15 | D | best error = [ 4.3122, 4.3076, 4.3062, 4.3057, 4.3054] +24-11-19 19:19:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:19:15 | D | sum error = [ 6.4862, 6.8477, 7.3030, 7.8128, 8.3451] +24-11-19 19:19:15 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 19:19:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:19:15 | D | sum error = [ 8.9102, 9.5648, 10.2553, 10.9906, 11.7627] +24-11-19 19:19:15 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 19:19:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:19:15 | D | sum error = [ 12.6247, 13.4883, 14.4503, 15.4499, 16.5293] +24-11-19 19:19:15 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 19:19:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:19:15 | D | sum error = [ 17.6579, 18.8805, 20.1465, 21.5062, 22.9195] +24-11-19 19:19:15 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 19:19:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:19:15 | D | sum error = [ 24.4168, 26.0180, 27.6725, 29.4331, 31.2971] +24-11-19 19:19:15 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 19:19:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:19:15 | D | sum error = [ 33.2407, 35.3174, 37.4805, 39.7675, 42.1661] +24-11-19 19:19:15 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 19:19:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:19:15 | D | sum error = [ 44.6823, 47.3392, 50.1088, 53.0262, 56.1021] +24-11-19 19:19:15 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 19:19:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:19:15 | D | sum error = [ 59.2941, 62.6703, 66.1807, 69.8460, 73.6888] +24-11-19 19:19:15 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 19:19:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:19:15 | D | sum error = [ 77.6998, 81.8888, 86.2709, 90.8356, 95.6036] +24-11-19 19:19:15 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 19:19:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:19:15 | D | sum error = [ 100.5852, 105.7533, 111.1544, 116.7749, 122.6122] +24-11-19 19:19:15 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 19:19:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:19:15 | D | sum error = [ 128.7000, 135.0239, 141.5893, 148.4093, 155.4729] +24-11-19 19:19:15 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 19:19:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:19:15 | D | sum error = [ 162.7969, 170.4015, 178.2882, 186.4409, 194.8805] +24-11-19 19:19:15 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 19:19:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:19:15 | D | sum error = [ 203.6055, 212.6172, 221.9261, 231.5290, 241.4427] +24-11-19 19:19:15 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 19:19:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:19:15 | D | sum error = [ 251.6549, 262.1859, 273.0395, 284.2093, 295.7071] +24-11-19 19:19:15 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 19:19:15 | D | + error = [4.3054] +24-11-19 19:19:16 | D | - Calibrating model.layers.13.self_attn.o_proj.weight +24-11-19 19:19:16 | D | + w: sint8 +24-11-19 19:19:16 | D | + x: None +24-11-19 19:19:16 | D | + y: None +24-11-19 19:19:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:19:16 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:19:16 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:19:16 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:19:16 | D | - range ratio = [ 1.0000] +24-11-19 19:19:16 | D | sum error = [ 1.3071] +24-11-19 19:19:16 | D | best error = [ 1.3071] +24-11-19 19:19:16 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:19:16 | D | sum error = [ 1.2980, 1.2913, 1.2807, 1.2907, 1.3001] +24-11-19 19:19:16 | D | best error = [ 1.2180, 1.1782, 1.1526, 1.1366, 1.1240] +24-11-19 19:19:16 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:19:16 | D | sum error = [ 1.3079, 1.3284, 1.3612, 1.3943, 1.4381] +24-11-19 19:19:16 | D | best error = [ 1.1144, 1.1071, 1.1018, 1.0979, 1.0954] +24-11-19 19:19:16 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:19:16 | D | sum error = [ 1.4832, 1.5456, 1.6204, 1.6993, 1.7902] +24-11-19 19:19:16 | D | best error = [ 1.0932, 1.0917, 1.0903, 1.0890, 1.0884] +24-11-19 19:19:16 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:19:16 | D | sum error = [ 1.8816, 1.9999, 2.1175, 2.2471, 2.3891] +24-11-19 19:19:16 | D | best error = [ 1.0877, 1.0871, 1.0866, 1.0863, 1.0860] +24-11-19 19:19:16 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:19:16 | D | sum error = [ 2.5436, 2.7013, 2.8758, 3.0680, 3.2699] +24-11-19 19:19:16 | D | best error = [ 1.0859, 1.0858, 1.0857, 1.0856, 1.0856] +24-11-19 19:19:16 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:19:16 | D | sum error = [ 3.4814, 3.7086, 3.9449, 4.2047, 4.4795] +24-11-19 19:19:16 | D | best error = [ 1.0856, 1.0856, 1.0856, 1.0856, 1.0856] +24-11-19 19:19:16 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:19:16 | D | sum error = [ 4.7647, 5.0749, 5.3988, 5.7357, 6.1025] +24-11-19 19:19:16 | D | best error = [ 1.0855, 1.0855, 1.0855, 1.0855, 1.0855] +24-11-19 19:19:16 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:19:16 | D | sum error = [ 6.4849, 6.8837, 7.3097, 7.7640, 8.2352] +24-11-19 19:19:16 | D | best error = [ 1.0855, 1.0855, 1.0855, 1.0855, 1.0855] +24-11-19 19:19:16 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:19:16 | D | sum error = [ 8.7347, 9.2636, 9.8193, 10.4041, 11.0176] +24-11-19 19:19:16 | D | best error = [ 1.0855, 1.0855, 1.0855, 1.0855, 1.0855] +24-11-19 19:19:16 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:19:16 | D | sum error = [ 11.6638, 12.3434, 13.0564, 13.8084, 14.5900] +24-11-19 19:19:16 | D | best error = [ 1.0855, 1.0855, 1.0855, 1.0855, 1.0855] +24-11-19 19:19:16 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:19:16 | D | sum error = [ 15.4196, 16.2819, 17.1917, 18.1441, 19.1407] +24-11-19 19:19:16 | D | best error = [ 1.0855, 1.0855, 1.0855, 1.0855, 1.0855] +24-11-19 19:19:16 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:19:16 | D | sum error = [ 20.1816, 21.2767, 22.4193, 23.6124, 24.8625] +24-11-19 19:19:16 | D | best error = [ 1.0855, 1.0855, 1.0855, 1.0855, 1.0855] +24-11-19 19:19:16 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:19:16 | D | sum error = [ 26.1621, 27.5173, 28.9324, 30.4082, 31.9451] +24-11-19 19:19:16 | D | best error = [ 1.0855, 1.0855, 1.0855, 1.0855, 1.0855] +24-11-19 19:19:16 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:19:16 | D | sum error = [ 33.5413, 35.2089, 36.9402, 38.7344, 40.6026] +24-11-19 19:19:16 | D | best error = [ 1.0855, 1.0855, 1.0855, 1.0855, 1.0855] +24-11-19 19:19:16 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:19:16 | D | sum error = [ 42.5405, 44.5512, 46.6363, 48.7957, 51.0375] +24-11-19 19:19:16 | D | best error = [ 1.0855, 1.0855, 1.0855, 1.0855, 1.0855] +24-11-19 19:19:16 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:19:16 | D | sum error = [ 53.3585, 55.7622, 58.2473, 60.8142, 63.4686] +24-11-19 19:19:16 | D | best error = [ 1.0855, 1.0855, 1.0855, 1.0855, 1.0855] +24-11-19 19:19:16 | D | + error = [1.0855] +24-11-19 19:19:16 | D | - Calibrating model.layers.13.mlp.up_proj.weight +24-11-19 19:19:16 | D | + w: sint8 +24-11-19 19:19:16 | D | + x: None +24-11-19 19:19:16 | D | + y: None +24-11-19 19:19:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:19:16 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:19:16 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:19:17 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:19:17 | D | - range ratio = [ 1.0000] +24-11-19 19:19:17 | D | sum error = [ 6.4066] +24-11-19 19:19:17 | D | best error = [ 6.4066] +24-11-19 19:19:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:19:17 | D | sum error = [ 6.3675, 6.3464, 6.3547, 6.4482, 6.5660] +24-11-19 19:19:17 | D | best error = [ 5.9573, 5.7810, 5.6865, 5.6343, 5.6075] +24-11-19 19:19:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:19:17 | D | sum error = [ 6.7206, 6.9632, 7.2473, 7.6055, 7.9945] +24-11-19 19:19:17 | D | best error = [ 5.5929, 5.5868, 5.5847, 5.5842, 5.5842] +24-11-19 19:19:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:19:17 | D | sum error = [ 8.4613, 8.9806, 9.5553, 10.2154, 10.8873] +24-11-19 19:19:17 | D | best error = [ 5.5841, 5.5841, 5.5841, 5.5841, 5.5841] +24-11-19 19:19:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:19:17 | D | sum error = [ 11.6764, 12.5202, 13.4126, 14.3876, 15.4175] +24-11-19 19:19:17 | D | best error = [ 5.5841, 5.5841, 5.5841, 5.5841, 5.5841] +24-11-19 19:19:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:19:17 | D | sum error = [ 16.5271, 17.7119, 18.9560, 20.2975, 21.6975] +24-11-19 19:19:17 | D | best error = [ 5.5841, 5.5841, 5.5841, 5.5841, 5.5841] +24-11-19 19:19:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:19:17 | D | sum error = [ 23.1992, 24.7763, 26.4663, 28.2427, 30.1137] +24-11-19 19:19:17 | D | best error = [ 5.5841, 5.5841, 5.5841, 5.5841, 5.5841] +24-11-19 19:19:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:19:17 | D | sum error = [ 32.0777, 34.1967, 36.3845, 38.7117, 41.1539] +24-11-19 19:19:17 | D | best error = [ 5.5841, 5.5841, 5.5841, 5.5841, 5.5841] +24-11-19 19:19:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:19:17 | D | sum error = [ 43.7442, 46.4505, 49.3078, 52.3090, 55.4621] +24-11-19 19:19:17 | D | best error = [ 5.5841, 5.5841, 5.5841, 5.5841, 5.5841] +24-11-19 19:19:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:19:17 | D | sum error = [ 58.7766, 62.2600, 65.9226, 69.7798, 73.8111] +24-11-19 19:19:17 | D | best error = [ 5.5841, 5.5841, 5.5841, 5.5841, 5.5841] +24-11-19 19:19:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:19:17 | D | sum error = [ 78.0369, 82.4738, 87.1180, 91.9636, 97.0537] +24-11-19 19:19:17 | D | best error = [ 5.5841, 5.5841, 5.5841, 5.5841, 5.5841] +24-11-19 19:19:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:19:17 | D | sum error = [ 102.3658, 107.9246, 113.7313, 119.8125, 126.1415] +24-11-19 19:19:17 | D | best error = [ 5.5841, 5.5841, 5.5841, 5.5841, 5.5841] +24-11-19 19:19:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:19:17 | D | sum error = [ 132.7421, 139.6315, 146.8200, 154.3036, 162.0917] +24-11-19 19:19:17 | D | best error = [ 5.5841, 5.5841, 5.5841, 5.5841, 5.5841] +24-11-19 19:19:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:19:17 | D | sum error = [ 170.1823, 178.5952, 187.3582, 196.4417, 205.8733] +24-11-19 19:19:17 | D | best error = [ 5.5841, 5.5841, 5.5841, 5.5841, 5.5841] +24-11-19 19:19:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:19:17 | D | sum error = [ 215.6813, 225.8469, 236.3892, 247.3240, 258.6234] +24-11-19 19:19:17 | D | best error = [ 5.5841, 5.5841, 5.5841, 5.5841, 5.5841] +24-11-19 19:19:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:19:17 | D | sum error = [ 270.3396, 282.4503, 294.9722, 307.9017, 321.2512] +24-11-19 19:19:17 | D | best error = [ 5.5841, 5.5841, 5.5841, 5.5841, 5.5841] +24-11-19 19:19:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:19:17 | D | sum error = [ 335.0150, 349.1907, 363.8149, 378.8696, 394.3505] +24-11-19 19:19:17 | D | best error = [ 5.5841, 5.5841, 5.5841, 5.5841, 5.5841] +24-11-19 19:19:17 | D | + error = [5.5841] +24-11-19 19:19:18 | D | - Calibrating model.layers.13.mlp.gate_proj.weight +24-11-19 19:19:18 | D | + w: sint8 +24-11-19 19:19:18 | D | + x: None +24-11-19 19:19:18 | D | + y: None +24-11-19 19:19:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:19:18 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:19:18 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:19:18 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:19:18 | D | - range ratio = [ 1.0000] +24-11-19 19:19:18 | D | sum error = [ 6.5603] +24-11-19 19:19:18 | D | best error = [ 6.5603] +24-11-19 19:19:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:19:19 | D | sum error = [ 6.5320, 6.5097, 6.5485, 6.6249, 6.7406] +24-11-19 19:19:19 | D | best error = [ 6.1089, 5.9359, 5.8445, 5.7904, 5.7609] +24-11-19 19:19:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:19:19 | D | sum error = [ 6.9073, 7.1636, 7.4520, 7.7877, 8.2077] +24-11-19 19:19:19 | D | best error = [ 5.7474, 5.7415, 5.7398, 5.7391, 5.7390] +24-11-19 19:19:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:19:19 | D | sum error = [ 8.6920, 9.2310, 9.8413, 10.5120, 11.2334] +24-11-19 19:19:19 | D | best error = [ 5.7389, 5.7389, 5.7389, 5.7389, 5.7389] +24-11-19 19:19:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:19:19 | D | sum error = [ 12.0362, 12.9196, 13.8394, 14.8576, 15.9490] +24-11-19 19:19:19 | D | best error = [ 5.7389, 5.7389, 5.7389, 5.7389, 5.7389] +24-11-19 19:19:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:19:19 | D | sum error = [ 17.1102, 18.3274, 19.6688, 21.0849, 22.5762] +24-11-19 19:19:19 | D | best error = [ 5.7389, 5.7389, 5.7389, 5.7389, 5.7389] +24-11-19 19:19:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:19:19 | D | sum error = [ 24.1962, 25.9038, 27.6946, 29.6193, 31.6567] +24-11-19 19:19:19 | D | best error = [ 5.7389, 5.7389, 5.7389, 5.7389, 5.7389] +24-11-19 19:19:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:19:19 | D | sum error = [ 33.8162, 36.0930, 38.5157, 41.0814, 43.8118] +24-11-19 19:19:19 | D | best error = [ 5.7389, 5.7389, 5.7389, 5.7389, 5.7389] +24-11-19 19:19:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:19:19 | D | sum error = [ 46.6907, 49.7758, 53.0003, 56.4382, 60.0549] +24-11-19 19:19:19 | D | best error = [ 5.7389, 5.7389, 5.7389, 5.7389, 5.7389] +24-11-19 19:19:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:19:19 | D | sum error = [ 63.8893, 67.9151, 72.2146, 76.7294, 81.5251] +24-11-19 19:19:19 | D | best error = [ 5.7389, 5.7389, 5.7389, 5.7389, 5.7389] +24-11-19 19:19:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:19:19 | D | sum error = [ 86.5869, 91.9275, 97.5793, 103.5392, 109.8257] +24-11-19 19:19:19 | D | best error = [ 5.7389, 5.7389, 5.7389, 5.7389, 5.7389] +24-11-19 19:19:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:19:19 | D | sum error = [ 116.4273, 123.3784, 130.6988, 138.4056, 146.4965] +24-11-19 19:19:19 | D | best error = [ 5.7389, 5.7389, 5.7389, 5.7389, 5.7389] +24-11-19 19:19:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:19:19 | D | sum error = [ 154.9954, 163.9443, 173.3371, 183.2140, 193.5419] +24-11-19 19:19:19 | D | best error = [ 5.7389, 5.7389, 5.7389, 5.7389, 5.7389] +24-11-19 19:19:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:19:19 | D | sum error = [ 204.3878, 215.7254, 227.6218, 240.0473, 253.0381] +24-11-19 19:19:19 | D | best error = [ 5.7389, 5.7389, 5.7389, 5.7389, 5.7389] +24-11-19 19:19:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:19:19 | D | sum error = [ 266.6066, 280.7426, 295.4745, 310.8074, 326.7425] +24-11-19 19:19:19 | D | best error = [ 5.7389, 5.7389, 5.7389, 5.7389, 5.7389] +24-11-19 19:19:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:19:19 | D | sum error = [ 343.3072, 360.5256, 378.3840, 396.9047, 416.1001] +24-11-19 19:19:19 | D | best error = [ 5.7389, 5.7389, 5.7389, 5.7389, 5.7389] +24-11-19 19:19:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:19:19 | D | sum error = [ 435.9625, 456.5009, 477.7197, 499.6289, 522.2193] +24-11-19 19:19:19 | D | best error = [ 5.7389, 5.7389, 5.7389, 5.7389, 5.7389] +24-11-19 19:19:19 | D | + error = [5.7389] +24-11-19 19:19:19 | D | - Calibrating model.layers.13.mlp.down_proj.weight +24-11-19 19:19:19 | D | + w: sint8 +24-11-19 19:19:19 | D | + x: None +24-11-19 19:19:19 | D | + y: None +24-11-19 19:19:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:19:19 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:19:19 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:19:19 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:19:19 | D | - range ratio = [ 1.0000] +24-11-19 19:19:19 | D | sum error = [ 1.7327] +24-11-19 19:19:19 | D | best error = [ 1.7327] +24-11-19 19:19:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:19:20 | D | sum error = [ 1.7166, 1.7056, 1.6973, 1.6934, 1.6960] +24-11-19 19:19:20 | D | best error = [ 1.6725, 1.6404, 1.6199, 1.6052, 1.5946] +24-11-19 19:19:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:19:20 | D | sum error = [ 1.7011, 1.7139, 1.7364, 1.7666, 1.8048] +24-11-19 19:19:20 | D | best error = [ 1.5863, 1.5795, 1.5749, 1.5715, 1.5694] +24-11-19 19:19:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:19:20 | D | sum error = [ 1.8531, 1.9107, 1.9767, 2.0594, 2.1509] +24-11-19 19:19:20 | D | best error = [ 1.5680, 1.5671, 1.5666, 1.5663, 1.5661] +24-11-19 19:19:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:19:20 | D | sum error = [ 2.2550, 2.3713, 2.5021, 2.6492, 2.8102] +24-11-19 19:19:20 | D | best error = [ 1.5659, 1.5659, 1.5658, 1.5658, 1.5658] +24-11-19 19:19:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:19:20 | D | sum error = [ 2.9810, 3.1743, 3.3794, 3.6015, 3.8424] +24-11-19 19:19:20 | D | best error = [ 1.5658, 1.5658, 1.5658, 1.5658, 1.5658] +24-11-19 19:19:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:19:20 | D | sum error = [ 4.0996, 4.3727, 4.6693, 4.9876, 5.3255] +24-11-19 19:19:20 | D | best error = [ 1.5658, 1.5658, 1.5658, 1.5658, 1.5658] +24-11-19 19:19:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:19:20 | D | sum error = [ 5.6841, 6.0701, 6.4766, 6.9126, 7.3740] +24-11-19 19:19:20 | D | best error = [ 1.5658, 1.5658, 1.5658, 1.5658, 1.5658] +24-11-19 19:19:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:19:20 | D | sum error = [ 7.8655, 8.3824, 8.9358, 9.5198, 10.1361] +24-11-19 19:19:20 | D | best error = [ 1.5658, 1.5658, 1.5658, 1.5658, 1.5658] +24-11-19 19:19:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:19:20 | D | sum error = [ 10.7867, 11.4780, 12.2106, 12.9793, 13.7917] +24-11-19 19:19:20 | D | best error = [ 1.5658, 1.5658, 1.5658, 1.5658, 1.5658] +24-11-19 19:19:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:19:20 | D | sum error = [ 14.6506, 15.5545, 16.5083, 17.5137, 18.5734] +24-11-19 19:19:20 | D | best error = [ 1.5658, 1.5658, 1.5658, 1.5658, 1.5658] +24-11-19 19:19:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:19:20 | D | sum error = [ 19.6844, 20.8537, 22.0849, 23.3780, 24.7335] +24-11-19 19:19:20 | D | best error = [ 1.5658, 1.5658, 1.5658, 1.5658, 1.5658] +24-11-19 19:19:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:19:20 | D | sum error = [ 26.1590, 27.6514, 29.2166, 30.8562, 32.5730] +24-11-19 19:19:20 | D | best error = [ 1.5658, 1.5658, 1.5658, 1.5658, 1.5658] +24-11-19 19:19:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:19:20 | D | sum error = [ 34.3683, 36.2466, 38.2084, 40.2568, 42.3944] +24-11-19 19:19:20 | D | best error = [ 1.5658, 1.5658, 1.5658, 1.5658, 1.5658] +24-11-19 19:19:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:19:20 | D | sum error = [ 44.6263, 46.9508, 49.3731, 51.9005, 54.5214] +24-11-19 19:19:20 | D | best error = [ 1.5658, 1.5658, 1.5658, 1.5658, 1.5658] +24-11-19 19:19:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:19:20 | D | sum error = [ 57.2518, 60.0887, 63.0355, 66.0932, 69.2641] +24-11-19 19:19:20 | D | best error = [ 1.5658, 1.5658, 1.5658, 1.5658, 1.5658] +24-11-19 19:19:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:19:20 | D | sum error = [ 72.5491, 75.9469, 79.4616, 83.0928, 86.8506] +24-11-19 19:19:20 | D | best error = [ 1.5658, 1.5658, 1.5658, 1.5658, 1.5658] +24-11-19 19:19:20 | D | + error = [1.5658] +24-11-19 19:19:20 | D | - Quantizing model.layers.13.self_attn.q_proj.weight +24-11-19 19:19:21 | D | - Quantizing model.layers.13.self_attn.k_proj.weight +24-11-19 19:19:22 | D | - Quantizing model.layers.13.self_attn.v_proj.weight +24-11-19 19:19:23 | D | - Quantizing model.layers.13.self_attn.o_proj.weight +24-11-19 19:19:24 | D | - Quantizing model.layers.13.mlp.up_proj.weight +24-11-19 19:19:25 | D | - Quantizing model.layers.13.mlp.gate_proj.weight +24-11-19 19:19:25 | D | - Quantizing model.layers.13.mlp.down_proj.weight +24-11-19 19:19:34 | D | - Quantizing layer model.layers.14 +24-11-19 19:19:34 | D | - Calibrating model.layers.14.self_attn.q_proj.weight +24-11-19 19:19:34 | D | + w: sint8 +24-11-19 19:19:34 | D | + x: None +24-11-19 19:19:34 | D | + y: None +24-11-19 19:19:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:19:34 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:19:34 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:19:34 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:19:34 | D | - range ratio = [ 1.0000] +24-11-19 19:19:34 | D | sum error = [ 11.6816] +24-11-19 19:19:34 | D | best error = [ 11.6816] +24-11-19 19:19:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:19:47 | D | sum error = [ 11.7610, 11.9221, 11.8006, 11.9387, 12.1078] +24-11-19 19:19:47 | D | best error = [ 11.6816, 11.6816, 11.6816, 11.6816, 11.6816] +24-11-19 19:19:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:19:47 | D | sum error = [ 12.2536, 12.7172, 13.1906, 13.7954, 14.8542] +24-11-19 19:19:47 | D | best error = [ 11.6816, 11.6816, 11.6816, 11.6816, 11.6816] +24-11-19 19:19:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:19:47 | D | sum error = [ 15.4631, 16.6001, 17.6968, 18.9340, 20.3617] +24-11-19 19:19:47 | D | best error = [ 11.6816, 11.6816, 11.6816, 11.6816, 11.6816] +24-11-19 19:19:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:19:47 | D | sum error = [ 21.6506, 23.5689, 25.3739, 26.9377, 29.1631] +24-11-19 19:19:47 | D | best error = [ 11.6816, 11.6816, 11.6816, 11.6816, 11.6816] +24-11-19 19:19:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:19:47 | D | sum error = [ 31.5727, 33.9945, 36.7024, 39.5532, 42.7269] +24-11-19 19:19:47 | D | best error = [ 11.6816, 11.6816, 11.6816, 11.6816, 11.6816] +24-11-19 19:19:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:19:47 | D | sum error = [ 46.0018, 50.0288, 53.7463, 57.7371, 62.0150] +24-11-19 19:19:47 | D | best error = [ 11.6816, 11.6816, 11.6816, 11.6816, 11.6816] +24-11-19 19:19:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:19:47 | D | sum error = [ 66.4545, 71.3765, 76.9153, 83.0077, 88.9368] +24-11-19 19:19:47 | D | best error = [ 11.6816, 11.6816, 11.6816, 11.6816, 11.6816] +24-11-19 19:19:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:19:47 | D | sum error = [ 95.4229, 102.0148, 109.9925, 117.9624, 126.7191] +24-11-19 19:19:47 | D | best error = [ 11.6816, 11.6816, 11.6816, 11.6816, 11.6816] +24-11-19 19:19:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:19:47 | D | sum error = [ 135.8877, 146.0431, 156.3336, 167.7444, 180.2849] +24-11-19 19:19:47 | D | best error = [ 11.6816, 11.6816, 11.6816, 11.6816, 11.6816] +24-11-19 19:19:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:19:47 | D | sum error = [ 193.0168, 207.0499, 222.0887, 238.4433, 255.8007] +24-11-19 19:19:47 | D | best error = [ 11.6816, 11.6816, 11.6816, 11.6816, 11.6816] +24-11-19 19:19:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:19:47 | D | sum error = [ 274.2251, 294.2908, 315.3267, 338.4022, 362.5397] +24-11-19 19:19:47 | D | best error = [ 11.6816, 11.6816, 11.6816, 11.6816, 11.6816] +24-11-19 19:19:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:19:47 | D | sum error = [ 388.7262, 416.6062, 446.4595, 478.1083, 511.8845] +24-11-19 19:19:47 | D | best error = [ 11.6816, 11.6816, 11.6816, 11.6816, 11.6816] +24-11-19 19:19:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:19:47 | D | sum error = [ 547.8452, 586.2953, 627.4019, 671.1677, 718.4629] +24-11-19 19:19:47 | D | best error = [ 11.6816, 11.6816, 11.6816, 11.6816, 11.6816] +24-11-19 19:19:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:19:47 | D | sum error = [ 768.5853, 822.2797, 879.3719, 940.3911, 1005.5169] +24-11-19 19:19:47 | D | best error = [ 11.6816, 11.6816, 11.6816, 11.6816, 11.6816] +24-11-19 19:19:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:19:47 | D | sum error = [ 1074.6897, 1148.1897, 1226.0691, 1308.1225, 1394.5172] +24-11-19 19:19:47 | D | best error = [ 11.6816, 11.6816, 11.6816, 11.6816, 11.6816] +24-11-19 19:19:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:19:47 | D | sum error = [ 1485.1698, 1579.3157, 1676.8932, 1776.9961, 1879.2921] +24-11-19 19:19:47 | D | best error = [ 11.6816, 11.6816, 11.6816, 11.6816, 11.6816] +24-11-19 19:19:47 | D | + error = [11.6816] +24-11-19 19:19:47 | D | - Calibrating model.layers.14.self_attn.k_proj.weight +24-11-19 19:19:47 | D | + w: sint8 +24-11-19 19:19:47 | D | + x: None +24-11-19 19:19:47 | D | + y: None +24-11-19 19:19:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:19:47 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:19:47 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:19:47 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:19:47 | D | - range ratio = [ 1.0000] +24-11-19 19:19:47 | D | sum error = [ 12.6069] +24-11-19 19:19:47 | D | best error = [ 12.6069] +24-11-19 19:20:00 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:20:00 | D | sum error = [ 11.6886, 11.3525, 11.9976, 12.1975, 12.5511] +24-11-19 19:20:00 | D | best error = [ 11.6886, 11.3525, 11.3525, 11.3525, 11.3525] +24-11-19 19:20:00 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:20:00 | D | sum error = [ 12.8294, 13.5803, 13.8708, 14.6869, 14.8431] +24-11-19 19:20:00 | D | best error = [ 11.3525, 11.3525, 11.3525, 11.3525, 11.3525] +24-11-19 19:20:00 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:20:00 | D | sum error = [ 16.1572, 17.1731, 18.1425, 19.7399, 20.1719] +24-11-19 19:20:00 | D | best error = [ 11.3525, 11.3525, 11.3525, 11.3525, 11.3525] +24-11-19 19:20:00 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:20:00 | D | sum error = [ 22.6725, 23.8326, 25.5361, 28.0958, 28.9949] +24-11-19 19:20:00 | D | best error = [ 11.3525, 11.3525, 11.3525, 11.3525, 11.3525] +24-11-19 19:20:00 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:20:00 | D | sum error = [ 31.7967, 34.9749, 37.9137, 40.5689, 44.5927] +24-11-19 19:20:00 | D | best error = [ 11.3525, 11.3525, 11.3525, 11.3525, 11.3525] +24-11-19 19:20:00 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:20:00 | D | sum error = [ 47.5984, 51.1684, 56.1563, 60.8127, 65.6867] +24-11-19 19:20:00 | D | best error = [ 11.3525, 11.3525, 11.3525, 11.3525, 11.3525] +24-11-19 19:20:00 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:20:00 | D | sum error = [ 70.8784, 75.9663, 82.3813, 89.1940, 95.8398] +24-11-19 19:20:00 | D | best error = [ 11.3525, 11.3525, 11.3525, 11.3525, 11.3525] +24-11-19 19:20:00 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:20:00 | D | sum error = [ 104.1928, 111.0265, 120.3325, 128.7988, 138.2914] +24-11-19 19:20:00 | D | best error = [ 11.3525, 11.3525, 11.3525, 11.3525, 11.3525] +24-11-19 19:20:00 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:20:00 | D | sum error = [ 148.8280, 159.6604, 171.5655, 183.3298, 196.7554] +24-11-19 19:20:00 | D | best error = [ 11.3525, 11.3525, 11.3525, 11.3525, 11.3525] +24-11-19 19:20:00 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:20:00 | D | sum error = [ 210.0494, 225.8600, 241.1520, 257.8422, 275.8602] +24-11-19 19:20:00 | D | best error = [ 11.3525, 11.3525, 11.3525, 11.3525, 11.3525] +24-11-19 19:20:00 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:20:00 | D | sum error = [ 294.9333, 315.2745, 336.5660, 359.8144, 384.4121] +24-11-19 19:20:00 | D | best error = [ 11.3525, 11.3525, 11.3525, 11.3525, 11.3525] +24-11-19 19:20:00 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:20:00 | D | sum error = [ 409.6756, 437.1437, 465.7888, 496.7328, 530.0511] +24-11-19 19:20:00 | D | best error = [ 11.3525, 11.3525, 11.3525, 11.3525, 11.3525] +24-11-19 19:20:00 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:20:00 | D | sum error = [ 564.8134, 601.3868, 641.3244, 684.9573, 727.1826] +24-11-19 19:20:00 | D | best error = [ 11.3525, 11.3525, 11.3525, 11.3525, 11.3525] +24-11-19 19:20:00 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:20:00 | D | sum error = [ 775.4966, 827.2901, 879.8464, 937.1027, 999.3858] +24-11-19 19:20:00 | D | best error = [ 11.3525, 11.3525, 11.3525, 11.3525, 11.3525] +24-11-19 19:20:00 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:20:00 | D | sum error = [ 1067.9992, 1139.6109, 1212.4824, 1294.0382, 1378.6822] +24-11-19 19:20:00 | D | best error = [ 11.3525, 11.3525, 11.3525, 11.3525, 11.3525] +24-11-19 19:20:00 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:20:00 | D | sum error = [ 1464.1334, 1556.8744, 1655.6860, 1754.6979, 1859.7063] +24-11-19 19:20:00 | D | best error = [ 11.3525, 11.3525, 11.3525, 11.3525, 11.3525] +24-11-19 19:20:00 | D | + error = [11.3525] +24-11-19 19:20:00 | D | - Calibrating model.layers.14.self_attn.v_proj.weight +24-11-19 19:20:00 | D | + w: sint8 +24-11-19 19:20:00 | D | + x: None +24-11-19 19:20:00 | D | + y: None +24-11-19 19:20:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:20:00 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:20:00 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:20:00 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:20:00 | D | - range ratio = [ 1.0000] +24-11-19 19:20:00 | D | sum error = [ 4.9191] +24-11-19 19:20:00 | D | best error = [ 4.9191] +24-11-19 19:20:00 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:20:00 | D | sum error = [ 4.9057, 4.8907, 4.9003, 4.9575, 5.0519] +24-11-19 19:20:00 | D | best error = [ 4.5779, 4.4427, 4.3761, 4.3348, 4.3182] +24-11-19 19:20:00 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:20:00 | D | sum error = [ 5.1866, 5.3674, 5.5955, 5.8636, 6.1741] +24-11-19 19:20:00 | D | best error = [ 4.3089, 4.3036, 4.3027, 4.3024, 4.3024] +24-11-19 19:20:00 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:20:00 | D | sum error = [ 6.5322, 6.9028, 7.3725, 7.8691, 8.4093] +24-11-19 19:20:00 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 19:20:00 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:20:00 | D | sum error = [ 8.9963, 9.6656, 10.3795, 11.0902, 11.9038] +24-11-19 19:20:00 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 19:20:00 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:20:00 | D | sum error = [ 12.7702, 13.6652, 14.6253, 15.6656, 16.7341] +24-11-19 19:20:00 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 19:20:00 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:20:00 | D | sum error = [ 17.8810, 19.0733, 20.3612, 21.7231, 23.1685] +24-11-19 19:20:00 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 19:20:00 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:20:00 | D | sum error = [ 24.6600, 26.2371, 27.9261, 29.6771, 31.5416] +24-11-19 19:20:00 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 19:20:00 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:20:00 | D | sum error = [ 33.5083, 35.5826, 37.7305, 40.0056, 42.4114] +24-11-19 19:20:00 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 19:20:00 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:20:00 | D | sum error = [ 44.9359, 47.5713, 50.3350, 53.2528, 56.2960] +24-11-19 19:20:00 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 19:20:00 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:20:00 | D | sum error = [ 59.5060, 62.8397, 66.3427, 70.0113, 73.8499] +24-11-19 19:20:00 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 19:20:00 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:20:00 | D | sum error = [ 77.8682, 82.0373, 86.4081, 90.9749, 95.7306] +24-11-19 19:20:00 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 19:20:00 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:20:00 | D | sum error = [ 100.6903, 105.8396, 111.2194, 116.8007, 122.6455] +24-11-19 19:20:00 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 19:20:00 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:20:00 | D | sum error = [ 128.6977, 135.0114, 141.5686, 148.3804, 155.4540] +24-11-19 19:20:00 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 19:20:00 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:20:00 | D | sum error = [ 162.7843, 170.3772, 178.2485, 186.4108, 194.8484] +24-11-19 19:20:00 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 19:20:00 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:20:00 | D | sum error = [ 203.5759, 212.6114, 221.9457, 231.5955, 241.5481] +24-11-19 19:20:00 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 19:20:00 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:20:00 | D | sum error = [ 251.8121, 262.4021, 273.3090, 284.5448, 296.0943] +24-11-19 19:20:00 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 19:20:00 | D | + error = [4.3024] +24-11-19 19:20:00 | D | - Calibrating model.layers.14.self_attn.o_proj.weight +24-11-19 19:20:00 | D | + w: sint8 +24-11-19 19:20:00 | D | + x: None +24-11-19 19:20:00 | D | + y: None +24-11-19 19:20:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:20:00 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:20:00 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:20:01 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:20:01 | D | - range ratio = [ 1.0000] +24-11-19 19:20:01 | D | sum error = [ 1.3101] +24-11-19 19:20:01 | D | best error = [ 1.3101] +24-11-19 19:20:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:20:01 | D | sum error = [ 1.3044, 1.2959, 1.2962, 1.3011, 1.3101] +24-11-19 19:20:01 | D | best error = [ 1.2224, 1.1802, 1.1546, 1.1377, 1.1247] +24-11-19 19:20:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:20:01 | D | sum error = [ 1.3366, 1.3619, 1.3959, 1.4451, 1.4986] +24-11-19 19:20:01 | D | best error = [ 1.1171, 1.1119, 1.1088, 1.1064, 1.1050] +24-11-19 19:20:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:20:01 | D | sum error = [ 1.5667, 1.6427, 1.7278, 1.8184, 1.9252] +24-11-19 19:20:01 | D | best error = [ 1.1038, 1.1035, 1.1030, 1.1026, 1.1024] +24-11-19 19:20:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:20:01 | D | sum error = [ 2.0441, 2.1691, 2.3098, 2.4575, 2.6240] +24-11-19 19:20:01 | D | best error = [ 1.1022, 1.1021, 1.1020, 1.1019, 1.1018] +24-11-19 19:20:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:20:01 | D | sum error = [ 2.7947, 2.9767, 3.1739, 3.3847, 3.6096] +24-11-19 19:20:01 | D | best error = [ 1.1017, 1.1017, 1.1016, 1.1016, 1.1016] +24-11-19 19:20:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:20:01 | D | sum error = [ 3.8468, 4.0986, 4.3639, 4.6526, 4.9515] +24-11-19 19:20:01 | D | best error = [ 1.1016, 1.1016, 1.1016, 1.1016, 1.1016] +24-11-19 19:20:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:20:01 | D | sum error = [ 5.2616, 5.6006, 5.9535, 6.3203, 6.7110] +24-11-19 19:20:01 | D | best error = [ 1.1016, 1.1016, 1.1016, 1.1016, 1.1016] +24-11-19 19:20:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:20:01 | D | sum error = [ 7.1270, 7.5570, 8.0100, 8.4847, 8.9967] +24-11-19 19:20:01 | D | best error = [ 1.1016, 1.1016, 1.1016, 1.1016, 1.1016] +24-11-19 19:20:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:20:01 | D | sum error = [ 9.5183, 10.0786, 10.6634, 11.2807, 11.9285] +24-11-19 19:20:01 | D | best error = [ 1.1016, 1.1016, 1.1016, 1.1016, 1.1016] +24-11-19 19:20:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:20:01 | D | sum error = [ 12.6065, 13.3196, 14.0705, 14.8513, 15.6740] +24-11-19 19:20:01 | D | best error = [ 1.1016, 1.1016, 1.1016, 1.1016, 1.1016] +24-11-19 19:20:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:20:01 | D | sum error = [ 16.5301, 17.4293, 18.3694, 19.3498, 20.3725] +24-11-19 19:20:01 | D | best error = [ 1.1016, 1.1016, 1.1016, 1.1016, 1.1016] +24-11-19 19:20:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:20:01 | D | sum error = [ 21.4392, 22.5505, 23.7084, 24.9135, 26.1723] +24-11-19 19:20:01 | D | best error = [ 1.1016, 1.1016, 1.1016, 1.1016, 1.1016] +24-11-19 19:20:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:20:01 | D | sum error = [ 27.4824, 28.8511, 30.2682, 31.7439, 33.2787] +24-11-19 19:20:01 | D | best error = [ 1.1016, 1.1016, 1.1016, 1.1016, 1.1016] +24-11-19 19:20:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:20:01 | D | sum error = [ 34.8708, 36.5216, 38.2358, 40.0122, 41.8554] +24-11-19 19:20:01 | D | best error = [ 1.1016, 1.1016, 1.1016, 1.1016, 1.1016] +24-11-19 19:20:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:20:01 | D | sum error = [ 43.7679, 45.7478, 47.8018, 49.9300, 52.1344] +24-11-19 19:20:01 | D | best error = [ 1.1016, 1.1016, 1.1016, 1.1016, 1.1016] +24-11-19 19:20:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:20:01 | D | sum error = [ 54.4159, 56.7753, 59.2166, 61.7401, 64.3459] +24-11-19 19:20:01 | D | best error = [ 1.1016, 1.1016, 1.1016, 1.1016, 1.1016] +24-11-19 19:20:01 | D | + error = [1.1016] +24-11-19 19:20:01 | D | - Calibrating model.layers.14.mlp.up_proj.weight +24-11-19 19:20:01 | D | + w: sint8 +24-11-19 19:20:01 | D | + x: None +24-11-19 19:20:01 | D | + y: None +24-11-19 19:20:01 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:20:01 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:20:01 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:20:01 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:20:01 | D | - range ratio = [ 1.0000] +24-11-19 19:20:01 | D | sum error = [ 6.6595] +24-11-19 19:20:01 | D | best error = [ 6.6595] +24-11-19 19:20:02 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:20:02 | D | sum error = [ 6.6362, 6.6375, 6.6593, 6.7336, 6.8480] +24-11-19 19:20:02 | D | best error = [ 6.1985, 6.0236, 5.9275, 5.8741, 5.8453] +24-11-19 19:20:02 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:20:02 | D | sum error = [ 7.0199, 7.2540, 7.5582, 7.9123, 8.3357] +24-11-19 19:20:02 | D | best error = [ 5.8320, 5.8258, 5.8233, 5.8226, 5.8225] +24-11-19 19:20:02 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:20:02 | D | sum error = [ 8.8046, 9.3676, 9.9606, 10.6100, 11.3385] +24-11-19 19:20:02 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 19:20:02 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:20:02 | D | sum error = [ 12.1672, 13.0269, 13.9715, 14.9579, 16.0201] +24-11-19 19:20:02 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 19:20:02 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:20:02 | D | sum error = [ 17.1810, 18.4064, 19.7032, 21.0661, 22.5575] +24-11-19 19:20:02 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 19:20:02 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:20:02 | D | sum error = [ 24.1130, 25.7592, 27.5033, 29.3538, 31.2908] +24-11-19 19:20:02 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 19:20:02 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:20:02 | D | sum error = [ 33.3502, 35.5214, 37.7919, 40.2093, 42.7384] +24-11-19 19:20:02 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 19:20:02 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:20:02 | D | sum error = [ 45.4180, 48.2404, 51.2009, 54.3166, 57.6065] +24-11-19 19:20:02 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 19:20:02 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:20:02 | D | sum error = [ 61.0390, 64.6446, 68.4398, 72.3995, 76.5934] +24-11-19 19:20:02 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 19:20:02 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:20:02 | D | sum error = [ 80.9718, 85.5474, 90.3647, 95.4043, 100.6712] +24-11-19 19:20:02 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 19:20:02 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:20:02 | D | sum error = [ 106.1791, 111.9676, 117.9712, 124.2830, 130.8638] +24-11-19 19:20:02 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 19:20:02 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:20:02 | D | sum error = [ 137.7130, 144.8524, 152.3097, 160.0667, 168.1457] +24-11-19 19:20:02 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 19:20:02 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:20:02 | D | sum error = [ 176.5553, 185.2825, 194.3714, 203.7965, 213.5960] +24-11-19 19:20:02 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 19:20:02 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:20:02 | D | sum error = [ 223.7473, 234.2979, 245.2180, 256.5586, 268.2570] +24-11-19 19:20:02 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 19:20:02 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:20:02 | D | sum error = [ 280.3927, 292.9394, 305.9118, 319.3071, 333.1350] +24-11-19 19:20:02 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 19:20:02 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:20:02 | D | sum error = [ 347.3972, 362.1159, 377.2873, 392.8907, 408.9558] +24-11-19 19:20:02 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 19:20:02 | D | + error = [5.8224] +24-11-19 19:20:02 | D | - Calibrating model.layers.14.mlp.gate_proj.weight +24-11-19 19:20:02 | D | + w: sint8 +24-11-19 19:20:02 | D | + x: None +24-11-19 19:20:02 | D | + y: None +24-11-19 19:20:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:20:02 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:20:02 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:20:03 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:20:03 | D | - range ratio = [ 1.0000] +24-11-19 19:20:03 | D | sum error = [ 6.8366] +24-11-19 19:20:03 | D | best error = [ 6.8366] +24-11-19 19:20:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:20:03 | D | sum error = [ 6.7898, 6.7881, 6.8271, 6.8999, 7.0230] +24-11-19 19:20:03 | D | best error = [ 6.3563, 6.1788, 6.0810, 6.0266, 5.9980] +24-11-19 19:20:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:20:03 | D | sum error = [ 7.1998, 7.4512, 7.7568, 8.1143, 8.5340] +24-11-19 19:20:03 | D | best error = [ 5.9829, 5.9760, 5.9734, 5.9727, 5.9726] +24-11-19 19:20:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:20:03 | D | sum error = [ 9.0372, 9.5975, 10.2483, 10.9294, 11.6896] +24-11-19 19:20:03 | D | best error = [ 5.9726, 5.9726, 5.9726, 5.9726, 5.9726] +24-11-19 19:20:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:20:03 | D | sum error = [ 12.5095, 13.4138, 14.3823, 15.4555, 16.5634] +24-11-19 19:20:03 | D | best error = [ 5.9726, 5.9726, 5.9726, 5.9726, 5.9726] +24-11-19 19:20:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:20:03 | D | sum error = [ 17.7470, 19.0358, 20.4054, 21.8779, 23.4320] +24-11-19 19:20:03 | D | best error = [ 5.9726, 5.9726, 5.9726, 5.9726, 5.9726] +24-11-19 19:20:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:20:03 | D | sum error = [ 25.0953, 26.8394, 28.6961, 30.6771, 32.7712] +24-11-19 19:20:03 | D | best error = [ 5.9726, 5.9726, 5.9726, 5.9726, 5.9726] +24-11-19 19:20:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:20:03 | D | sum error = [ 34.9900, 37.3386, 39.8335, 42.4628, 45.2566] +24-11-19 19:20:03 | D | best error = [ 5.9726, 5.9726, 5.9726, 5.9726, 5.9726] +24-11-19 19:20:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:20:03 | D | sum error = [ 48.2022, 51.3379, 54.6385, 58.1278, 61.8086] +24-11-19 19:20:03 | D | best error = [ 5.9726, 5.9726, 5.9726, 5.9726, 5.9726] +24-11-19 19:20:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:20:03 | D | sum error = [ 65.7207, 69.8088, 74.1790, 78.7957, 83.6383] +24-11-19 19:20:03 | D | best error = [ 5.9726, 5.9726, 5.9726, 5.9726, 5.9726] +24-11-19 19:20:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:20:03 | D | sum error = [ 88.7689, 94.1963, 99.9154, 105.9473, 112.2886] +24-11-19 19:20:03 | D | best error = [ 5.9726, 5.9726, 5.9726, 5.9726, 5.9726] +24-11-19 19:20:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:20:03 | D | sum error = [ 118.9678, 126.0238, 133.4152, 141.2138, 149.3953] +24-11-19 19:20:03 | D | best error = [ 5.9726, 5.9726, 5.9726, 5.9726, 5.9726] +24-11-19 19:20:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:20:03 | D | sum error = [ 158.0031, 167.0421, 176.5291, 186.4819, 196.9478] +24-11-19 19:20:03 | D | best error = [ 5.9726, 5.9726, 5.9726, 5.9726, 5.9726] +24-11-19 19:20:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:20:03 | D | sum error = [ 207.9043, 219.3760, 231.3968, 243.9686, 257.0933] +24-11-19 19:20:03 | D | best error = [ 5.9726, 5.9726, 5.9726, 5.9726, 5.9726] +24-11-19 19:20:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:20:03 | D | sum error = [ 270.8092, 285.1206, 300.0439, 315.5936, 331.7662] +24-11-19 19:20:03 | D | best error = [ 5.9726, 5.9726, 5.9726, 5.9726, 5.9726] +24-11-19 19:20:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:20:03 | D | sum error = [ 348.5919, 366.0331, 384.1474, 402.9245, 422.3847] +24-11-19 19:20:03 | D | best error = [ 5.9726, 5.9726, 5.9726, 5.9726, 5.9726] +24-11-19 19:20:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:20:03 | D | sum error = [ 442.5132, 463.3503, 484.8296, 506.9937, 529.8658] +24-11-19 19:20:03 | D | best error = [ 5.9726, 5.9726, 5.9726, 5.9726, 5.9726] +24-11-19 19:20:03 | D | + error = [5.9726] +24-11-19 19:20:04 | D | - Calibrating model.layers.14.mlp.down_proj.weight +24-11-19 19:20:04 | D | + w: sint8 +24-11-19 19:20:04 | D | + x: None +24-11-19 19:20:04 | D | + y: None +24-11-19 19:20:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:20:04 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:20:04 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:20:04 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:20:04 | D | - range ratio = [ 1.0000] +24-11-19 19:20:04 | D | sum error = [ 1.8797] +24-11-19 19:20:04 | D | best error = [ 1.8797] +24-11-19 19:20:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:20:05 | D | sum error = [ 1.8615, 1.8489, 1.8400, 1.8361, 1.8358] +24-11-19 19:20:05 | D | best error = [ 1.8151, 1.7824, 1.7604, 1.7439, 1.7318] +24-11-19 19:20:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:20:05 | D | sum error = [ 1.8432, 1.8534, 1.8779, 1.9067, 1.9519] +24-11-19 19:20:05 | D | best error = [ 1.7220, 1.7150, 1.7099, 1.7069, 1.7047] +24-11-19 19:20:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:20:05 | D | sum error = [ 1.9970, 2.0592, 2.1348, 2.2234, 2.3195] +24-11-19 19:20:05 | D | best error = [ 1.7032, 1.7024, 1.7017, 1.7012, 1.7010] +24-11-19 19:20:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:20:05 | D | sum error = [ 2.4353, 2.5618, 2.7040, 2.8625, 3.0344] +24-11-19 19:20:05 | D | best error = [ 1.7010, 1.7009, 1.7008, 1.7008, 1.7008] +24-11-19 19:20:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:20:05 | D | sum error = [ 3.2251, 3.4346, 3.6598, 3.9029, 4.1665] +24-11-19 19:20:05 | D | best error = [ 1.7007, 1.7007, 1.7007, 1.7007, 1.7007] +24-11-19 19:20:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:20:05 | D | sum error = [ 4.4473, 4.7493, 5.0745, 5.4196, 5.7950] +24-11-19 19:20:05 | D | best error = [ 1.7007, 1.7007, 1.7007, 1.7007, 1.7007] +24-11-19 19:20:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:20:05 | D | sum error = [ 6.1907, 6.6069, 7.0575, 7.5352, 8.0407] +24-11-19 19:20:05 | D | best error = [ 1.7007, 1.7007, 1.7007, 1.7007, 1.7007] +24-11-19 19:20:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:20:05 | D | sum error = [ 8.5779, 9.1520, 9.7577, 10.3953, 11.0732] +24-11-19 19:20:05 | D | best error = [ 1.7007, 1.7007, 1.7007, 1.7007, 1.7007] +24-11-19 19:20:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:20:05 | D | sum error = [ 11.7882, 12.5484, 13.3479, 14.1969, 15.0886] +24-11-19 19:20:05 | D | best error = [ 1.7007, 1.7007, 1.7007, 1.7007, 1.7007] +24-11-19 19:20:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:20:05 | D | sum error = [ 16.0275, 17.0196, 18.0660, 19.1651, 20.3241] +24-11-19 19:20:05 | D | best error = [ 1.7007, 1.7007, 1.7007, 1.7007, 1.7007] +24-11-19 19:20:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:20:05 | D | sum error = [ 21.5408, 22.8203, 24.1645, 25.5783, 27.0576] +24-11-19 19:20:05 | D | best error = [ 1.7007, 1.7007, 1.7007, 1.7007, 1.7007] +24-11-19 19:20:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:20:05 | D | sum error = [ 28.6089, 30.2360, 31.9430, 33.7262, 35.5907] +24-11-19 19:20:05 | D | best error = [ 1.7007, 1.7007, 1.7007, 1.7007, 1.7007] +24-11-19 19:20:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:20:05 | D | sum error = [ 37.5425, 39.5777, 41.7052, 43.9221, 46.2341] +24-11-19 19:20:05 | D | best error = [ 1.7007, 1.7007, 1.7007, 1.7007, 1.7007] +24-11-19 19:20:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:20:05 | D | sum error = [ 48.6476, 51.1574, 53.7707, 56.4942, 59.3172] +24-11-19 19:20:05 | D | best error = [ 1.7007, 1.7007, 1.7007, 1.7007, 1.7007] +24-11-19 19:20:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:20:05 | D | sum error = [ 62.2541, 65.3021, 68.4664, 71.7462, 75.1474] +24-11-19 19:20:05 | D | best error = [ 1.7007, 1.7007, 1.7007, 1.7007, 1.7007] +24-11-19 19:20:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:20:05 | D | sum error = [ 78.6710, 82.3150, 86.0836, 89.9811, 94.0050] +24-11-19 19:20:05 | D | best error = [ 1.7007, 1.7007, 1.7007, 1.7007, 1.7007] +24-11-19 19:20:05 | D | + error = [1.7007] +24-11-19 19:20:05 | D | - Quantizing model.layers.14.self_attn.q_proj.weight +24-11-19 19:20:06 | D | - Quantizing model.layers.14.self_attn.k_proj.weight +24-11-19 19:20:07 | D | - Quantizing model.layers.14.self_attn.v_proj.weight +24-11-19 19:20:08 | D | - Quantizing model.layers.14.self_attn.o_proj.weight +24-11-19 19:20:09 | D | - Quantizing model.layers.14.mlp.up_proj.weight +24-11-19 19:20:10 | D | - Quantizing model.layers.14.mlp.gate_proj.weight +24-11-19 19:20:11 | D | - Quantizing model.layers.14.mlp.down_proj.weight +24-11-19 19:20:19 | D | - Quantizing layer model.layers.15 +24-11-19 19:20:19 | D | - Calibrating model.layers.15.self_attn.q_proj.weight +24-11-19 19:20:19 | D | + w: sint8 +24-11-19 19:20:19 | D | + x: None +24-11-19 19:20:19 | D | + y: None +24-11-19 19:20:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:20:19 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:20:19 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:20:20 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:20:20 | D | - range ratio = [ 1.0000] +24-11-19 19:20:20 | D | sum error = [ 11.1548] +24-11-19 19:20:20 | D | best error = [ 11.1548] +24-11-19 19:20:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:20:33 | D | sum error = [ 11.0971, 11.0511, 11.3575, 11.2416, 11.6104] +24-11-19 19:20:33 | D | best error = [ 11.0971, 11.0511, 11.0511, 11.0511, 11.0511] +24-11-19 19:20:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:20:33 | D | sum error = [ 12.0229, 12.3043, 12.6515, 13.2987, 14.7140] +24-11-19 19:20:33 | D | best error = [ 11.0511, 11.0511, 11.0511, 11.0511, 11.0511] +24-11-19 19:20:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:20:33 | D | sum error = [ 15.0004, 15.8795, 17.4033, 18.3988, 19.8088] +24-11-19 19:20:33 | D | best error = [ 11.0511, 11.0511, 11.0511, 11.0511, 11.0511] +24-11-19 19:20:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:20:33 | D | sum error = [ 21.0817, 22.5522, 24.6323, 26.6012, 28.1135] +24-11-19 19:20:33 | D | best error = [ 11.0511, 11.0511, 11.0511, 11.0511, 11.0511] +24-11-19 19:20:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:20:33 | D | sum error = [ 30.1710, 32.8390, 35.7168, 38.2702, 41.2608] +24-11-19 19:20:33 | D | best error = [ 11.0511, 11.0511, 11.0511, 11.0511, 11.0511] +24-11-19 19:20:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:20:33 | D | sum error = [ 44.4196, 47.7897, 51.4712, 55.4142, 59.9536] +24-11-19 19:20:33 | D | best error = [ 11.0511, 11.0511, 11.0511, 11.0511, 11.0511] +24-11-19 19:20:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:20:33 | D | sum error = [ 64.4819, 69.5782, 75.3122, 80.7371, 86.9800] +24-11-19 19:20:33 | D | best error = [ 11.0511, 11.0511, 11.0511, 11.0511, 11.0511] +24-11-19 19:20:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:20:33 | D | sum error = [ 93.9861, 101.1249, 108.5602, 116.9530, 125.7611] +24-11-19 19:20:33 | D | best error = [ 11.0511, 11.0511, 11.0511, 11.0511, 11.0511] +24-11-19 19:20:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:20:33 | D | sum error = [ 135.5729, 145.9003, 156.8790, 168.8261, 181.6110] +24-11-19 19:20:33 | D | best error = [ 11.0511, 11.0511, 11.0511, 11.0511, 11.0511] +24-11-19 19:20:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:20:33 | D | sum error = [ 195.4817, 210.0007, 226.1645, 243.0607, 261.8021] +24-11-19 19:20:33 | D | best error = [ 11.0511, 11.0511, 11.0511, 11.0511, 11.0511] +24-11-19 19:20:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:20:33 | D | sum error = [ 281.0490, 301.9648, 324.5224, 348.2544, 373.6558] +24-11-19 19:20:33 | D | best error = [ 11.0511, 11.0511, 11.0511, 11.0511, 11.0511] +24-11-19 19:20:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:20:33 | D | sum error = [ 401.3239, 430.6473, 462.2429, 496.0276, 532.2351] +24-11-19 19:20:33 | D | best error = [ 11.0511, 11.0511, 11.0511, 11.0511, 11.0511] +24-11-19 19:20:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:20:33 | D | sum error = [ 571.0132, 613.1366, 658.3128, 706.0915, 757.9904] +24-11-19 19:20:33 | D | best error = [ 11.0511, 11.0511, 11.0511, 11.0511, 11.0511] +24-11-19 19:20:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:20:33 | D | sum error = [ 812.9842, 872.1625, 935.1157, 1002.5199, 1074.1194] +24-11-19 19:20:33 | D | best error = [ 11.0511, 11.0511, 11.0511, 11.0511, 11.0511] +24-11-19 19:20:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:20:33 | D | sum error = [ 1150.2052, 1231.1825, 1316.1401, 1406.5411, 1501.3194] +24-11-19 19:20:33 | D | best error = [ 11.0511, 11.0511, 11.0511, 11.0511, 11.0511] +24-11-19 19:20:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:20:33 | D | sum error = [ 1600.7917, 1704.7072, 1812.5031, 1923.7270, 2037.8553] +24-11-19 19:20:33 | D | best error = [ 11.0511, 11.0511, 11.0511, 11.0511, 11.0511] +24-11-19 19:20:33 | D | + error = [11.0511] +24-11-19 19:20:33 | D | - Calibrating model.layers.15.self_attn.k_proj.weight +24-11-19 19:20:33 | D | + w: sint8 +24-11-19 19:20:33 | D | + x: None +24-11-19 19:20:33 | D | + y: None +24-11-19 19:20:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:20:33 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:20:33 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:20:33 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:20:33 | D | - range ratio = [ 1.0000] +24-11-19 19:20:33 | D | sum error = [ 12.0494] +24-11-19 19:20:33 | D | best error = [ 12.0494] +24-11-19 19:20:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:20:46 | D | sum error = [ 12.0384, 12.2507, 11.4442, 12.1964, 11.7937] +24-11-19 19:20:46 | D | best error = [ 12.0384, 12.0384, 11.4442, 11.4442, 11.4442] +24-11-19 19:20:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:20:46 | D | sum error = [ 12.1268, 12.8093, 14.3249, 14.1659, 14.9985] +24-11-19 19:20:46 | D | best error = [ 11.4442, 11.4442, 11.4442, 11.4442, 11.4442] +24-11-19 19:20:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:20:46 | D | sum error = [ 15.5145, 16.7894, 17.4335, 19.2148, 20.5096] +24-11-19 19:20:46 | D | best error = [ 11.4442, 11.4442, 11.4442, 11.4442, 11.4442] +24-11-19 19:20:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:20:46 | D | sum error = [ 22.4910, 24.3247, 25.9988, 28.3986, 29.6494] +24-11-19 19:20:46 | D | best error = [ 11.4442, 11.4442, 11.4442, 11.4442, 11.4442] +24-11-19 19:20:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:20:46 | D | sum error = [ 32.8606, 35.2753, 37.4575, 40.9944, 44.0439] +24-11-19 19:20:46 | D | best error = [ 11.4442, 11.4442, 11.4442, 11.4442, 11.4442] +24-11-19 19:20:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:20:46 | D | sum error = [ 47.0133, 51.0263, 54.5273, 59.8623, 62.8703] +24-11-19 19:20:46 | D | best error = [ 11.4442, 11.4442, 11.4442, 11.4442, 11.4442] +24-11-19 19:20:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:20:46 | D | sum error = [ 68.4596, 74.3027, 78.9486, 84.5782, 92.0233] +24-11-19 19:20:46 | D | best error = [ 11.4442, 11.4442, 11.4442, 11.4442, 11.4442] +24-11-19 19:20:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:20:46 | D | sum error = [ 99.3928, 107.1274, 114.9634, 124.1862, 131.8974] +24-11-19 19:20:46 | D | best error = [ 11.4442, 11.4442, 11.4442, 11.4442, 11.4442] +24-11-19 19:20:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:20:46 | D | sum error = [ 140.1876, 150.6730, 163.5865, 175.1832, 187.9044] +24-11-19 19:20:46 | D | best error = [ 11.4442, 11.4442, 11.4442, 11.4442, 11.4442] +24-11-19 19:20:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:20:46 | D | sum error = [ 203.0127, 219.5245, 235.8653, 255.1839, 275.9349] +24-11-19 19:20:46 | D | best error = [ 11.4442, 11.4442, 11.4442, 11.4442, 11.4442] +24-11-19 19:20:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:20:46 | D | sum error = [ 297.0991, 319.8789, 343.4497, 370.2897, 397.5603] +24-11-19 19:20:46 | D | best error = [ 11.4442, 11.4442, 11.4442, 11.4442, 11.4442] +24-11-19 19:20:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:20:46 | D | sum error = [ 426.7069, 459.9900, 492.9480, 527.7177, 570.8498] +24-11-19 19:20:46 | D | best error = [ 11.4442, 11.4442, 11.4442, 11.4442, 11.4442] +24-11-19 19:20:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:20:46 | D | sum error = [ 610.3172, 656.0489, 704.5830, 757.7819, 815.3714] +24-11-19 19:20:46 | D | best error = [ 11.4442, 11.4442, 11.4442, 11.4442, 11.4442] +24-11-19 19:20:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:20:46 | D | sum error = [ 872.6788, 937.1451, 1003.5909, 1074.6713, 1144.2338] +24-11-19 19:20:46 | D | best error = [ 11.4442, 11.4442, 11.4442, 11.4442, 11.4442] +24-11-19 19:20:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:20:46 | D | sum error = [ 1227.7737, 1305.1959, 1390.7583, 1479.5182, 1575.4223] +24-11-19 19:20:46 | D | best error = [ 11.4442, 11.4442, 11.4442, 11.4442, 11.4442] +24-11-19 19:20:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:20:46 | D | sum error = [ 1670.7381, 1773.4031, 1875.9214, 1987.8784, 2095.4238] +24-11-19 19:20:46 | D | best error = [ 11.4442, 11.4442, 11.4442, 11.4442, 11.4442] +24-11-19 19:20:46 | D | + error = [11.4442] +24-11-19 19:20:46 | D | - Calibrating model.layers.15.self_attn.v_proj.weight +24-11-19 19:20:46 | D | + w: sint8 +24-11-19 19:20:46 | D | + x: None +24-11-19 19:20:46 | D | + y: None +24-11-19 19:20:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:20:46 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:20:47 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:20:47 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:20:47 | D | - range ratio = [ 1.0000] +24-11-19 19:20:47 | D | sum error = [ 5.0148] +24-11-19 19:20:47 | D | best error = [ 5.0148] +24-11-19 19:20:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:20:47 | D | sum error = [ 4.9669, 4.9390, 4.9746, 5.0359, 5.1361] +24-11-19 19:20:47 | D | best error = [ 4.6546, 4.5192, 4.4471, 4.4086, 4.3891] +24-11-19 19:20:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:20:47 | D | sum error = [ 5.2448, 5.4039, 5.6158, 5.8912, 6.2289] +24-11-19 19:20:47 | D | best error = [ 4.3791, 4.3752, 4.3738, 4.3734, 4.3734] +24-11-19 19:20:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:20:47 | D | sum error = [ 6.5700, 6.9726, 7.4190, 7.9129, 8.4602] +24-11-19 19:20:47 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 19:20:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:20:47 | D | sum error = [ 9.0724, 9.7041, 10.4120, 11.1580, 11.9753] +24-11-19 19:20:47 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 19:20:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:20:47 | D | sum error = [ 12.8109, 13.7261, 14.6952, 15.7517, 16.8178] +24-11-19 19:20:47 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 19:20:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:20:47 | D | sum error = [ 17.9797, 19.2311, 20.5208, 21.8910, 23.3508] +24-11-19 19:20:47 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 19:20:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:20:47 | D | sum error = [ 24.8863, 26.4810, 28.1887, 29.9747, 31.8837] +24-11-19 19:20:47 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 19:20:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:20:47 | D | sum error = [ 33.8858, 35.9513, 38.1688, 40.4729, 42.8969] +24-11-19 19:20:47 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 19:20:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:20:47 | D | sum error = [ 45.4739, 48.1639, 50.9809, 53.9229, 57.0228] +24-11-19 19:20:47 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 19:20:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:20:47 | D | sum error = [ 60.2677, 63.6883, 67.2307, 70.9739, 74.8772] +24-11-19 19:20:47 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 19:20:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:20:47 | D | sum error = [ 78.9432, 83.2028, 87.6570, 92.3024, 97.1611] +24-11-19 19:20:47 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 19:20:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:20:47 | D | sum error = [ 102.2362, 107.5147, 113.0434, 118.7778, 124.7597] +24-11-19 19:20:47 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 19:20:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:20:47 | D | sum error = [ 130.9763, 137.4392, 144.1700, 151.1553, 158.4098] +24-11-19 19:20:47 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 19:20:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:20:47 | D | sum error = [ 165.9113, 173.6904, 181.7490, 190.1058, 198.7702] +24-11-19 19:20:47 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 19:20:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:20:47 | D | sum error = [ 207.7244, 216.9782, 226.5471, 236.4393, 246.6368] +24-11-19 19:20:47 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 19:20:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:20:47 | D | sum error = [ 257.1537, 267.9992, 279.1538, 290.6464, 302.4713] +24-11-19 19:20:47 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 19:20:47 | D | + error = [4.3734] +24-11-19 19:20:47 | D | - Calibrating model.layers.15.self_attn.o_proj.weight +24-11-19 19:20:47 | D | + w: sint8 +24-11-19 19:20:47 | D | + x: None +24-11-19 19:20:47 | D | + y: None +24-11-19 19:20:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:20:47 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:20:47 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:20:47 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:20:47 | D | - range ratio = [ 1.0000] +24-11-19 19:20:47 | D | sum error = [ 1.4542] +24-11-19 19:20:47 | D | best error = [ 1.4542] +24-11-19 19:20:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:20:48 | D | sum error = [ 1.4388, 1.4299, 1.4266, 1.4342, 1.4417] +24-11-19 19:20:48 | D | best error = [ 1.3636, 1.3224, 1.2956, 1.2785, 1.2661] +24-11-19 19:20:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:20:48 | D | sum error = [ 1.4527, 1.4829, 1.5148, 1.5569, 1.6123] +24-11-19 19:20:48 | D | best error = [ 1.2570, 1.2506, 1.2464, 1.2429, 1.2410] +24-11-19 19:20:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:20:48 | D | sum error = [ 1.6726, 1.7410, 1.8273, 1.9217, 2.0303] +24-11-19 19:20:48 | D | best error = [ 1.2395, 1.2387, 1.2380, 1.2375, 1.2370] +24-11-19 19:20:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:20:48 | D | sum error = [ 2.1463, 2.2764, 2.4128, 2.5631, 2.7310] +24-11-19 19:20:48 | D | best error = [ 1.2368, 1.2366, 1.2365, 1.2364, 1.2364] +24-11-19 19:20:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:20:48 | D | sum error = [ 2.9064, 3.0974, 3.3068, 3.5223, 3.7582] +24-11-19 19:20:48 | D | best error = [ 1.2363, 1.2363, 1.2363, 1.2363, 1.2363] +24-11-19 19:20:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:20:48 | D | sum error = [ 4.0054, 4.2713, 4.5545, 4.8545, 5.1693] +24-11-19 19:20:48 | D | best error = [ 1.2363, 1.2363, 1.2363, 1.2363, 1.2363] +24-11-19 19:20:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:20:48 | D | sum error = [ 5.5026, 5.8565, 6.2334, 6.6261, 7.0427] +24-11-19 19:20:48 | D | best error = [ 1.2363, 1.2363, 1.2363, 1.2363, 1.2363] +24-11-19 19:20:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:20:48 | D | sum error = [ 7.4895, 7.9560, 8.4460, 8.9655, 9.5169] +24-11-19 19:20:48 | D | best error = [ 1.2363, 1.2363, 1.2363, 1.2363, 1.2363] +24-11-19 19:20:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:20:48 | D | sum error = [ 10.0918, 10.7038, 11.3393, 12.0133, 12.7227] +24-11-19 19:20:48 | D | best error = [ 1.2363, 1.2363, 1.2363, 1.2363, 1.2363] +24-11-19 19:20:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:20:48 | D | sum error = [ 13.4735, 14.2557, 15.0784, 15.9412, 16.8476] +24-11-19 19:20:48 | D | best error = [ 1.2363, 1.2363, 1.2363, 1.2363, 1.2363] +24-11-19 19:20:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:20:48 | D | sum error = [ 17.7978, 18.7959, 19.8336, 20.9227, 22.0604] +24-11-19 19:20:48 | D | best error = [ 1.2363, 1.2363, 1.2363, 1.2363, 1.2363] +24-11-19 19:20:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:20:48 | D | sum error = [ 23.2524, 24.5011, 25.7978, 27.1558, 28.5752] +24-11-19 19:20:48 | D | best error = [ 1.2363, 1.2363, 1.2363, 1.2363, 1.2363] +24-11-19 19:20:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:20:48 | D | sum error = [ 30.0531, 31.5981, 33.2087, 34.8834, 36.6291] +24-11-19 19:20:48 | D | best error = [ 1.2363, 1.2363, 1.2363, 1.2363, 1.2363] +24-11-19 19:20:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:20:48 | D | sum error = [ 38.4473, 40.3375, 42.3031, 44.3438, 46.4663] +24-11-19 19:20:48 | D | best error = [ 1.2363, 1.2363, 1.2363, 1.2363, 1.2363] +24-11-19 19:20:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:20:48 | D | sum error = [ 48.6704, 50.9523, 53.3219, 55.7795, 58.3288] +24-11-19 19:20:48 | D | best error = [ 1.2363, 1.2363, 1.2363, 1.2363, 1.2363] +24-11-19 19:20:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:20:48 | D | sum error = [ 60.9673, 63.7033, 66.5302, 69.4538, 72.4738] +24-11-19 19:20:48 | D | best error = [ 1.2363, 1.2363, 1.2363, 1.2363, 1.2363] +24-11-19 19:20:48 | D | + error = [1.2363] +24-11-19 19:20:48 | D | - Calibrating model.layers.15.mlp.up_proj.weight +24-11-19 19:20:48 | D | + w: sint8 +24-11-19 19:20:48 | D | + x: None +24-11-19 19:20:48 | D | + y: None +24-11-19 19:20:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:20:48 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:20:48 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:20:48 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:20:48 | D | - range ratio = [ 1.0000] +24-11-19 19:20:48 | D | sum error = [ 6.9891] +24-11-19 19:20:48 | D | best error = [ 6.9891] +24-11-19 19:20:49 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:20:49 | D | sum error = [ 6.9562, 6.9153, 6.9443, 7.0244, 7.1469] +24-11-19 19:20:49 | D | best error = [ 6.4950, 6.3042, 6.2015, 6.1467, 6.1164] +24-11-19 19:20:49 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:20:49 | D | sum error = [ 7.3387, 7.5869, 7.9218, 8.2718, 8.7123] +24-11-19 19:20:49 | D | best error = [ 6.1024, 6.0969, 6.0946, 6.0938, 6.0938] +24-11-19 19:20:49 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:20:49 | D | sum error = [ 9.2201, 9.7988, 10.4476, 11.1339, 11.9183] +24-11-19 19:20:49 | D | best error = [ 6.0937, 6.0937, 6.0937, 6.0937, 6.0937] +24-11-19 19:20:49 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:20:49 | D | sum error = [ 12.7395, 13.6591, 14.6573, 15.7021, 16.8176] +24-11-19 19:20:49 | D | best error = [ 6.0937, 6.0937, 6.0937, 6.0937, 6.0937] +24-11-19 19:20:49 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:20:49 | D | sum error = [ 18.0232, 19.3105, 20.6763, 22.1368, 23.6764] +24-11-19 19:20:49 | D | best error = [ 6.0937, 6.0937, 6.0937, 6.0937, 6.0937] +24-11-19 19:20:49 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:20:49 | D | sum error = [ 25.3186, 27.0501, 28.8722, 30.8248, 32.8719] +24-11-19 19:20:49 | D | best error = [ 6.0937, 6.0937, 6.0937, 6.0937, 6.0937] +24-11-19 19:20:49 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:20:49 | D | sum error = [ 35.0516, 37.3293, 39.7547, 42.2827, 44.9626] +24-11-19 19:20:49 | D | best error = [ 6.0937, 6.0937, 6.0937, 6.0937, 6.0937] +24-11-19 19:20:49 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:20:49 | D | sum error = [ 47.7980, 50.7493, 53.8822, 57.1752, 60.6286] +24-11-19 19:20:49 | D | best error = [ 6.0937, 6.0937, 6.0937, 6.0937, 6.0937] +24-11-19 19:20:49 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:20:49 | D | sum error = [ 64.2594, 68.0806, 72.0874, 76.2934, 80.7070] +24-11-19 19:20:49 | D | best error = [ 6.0937, 6.0937, 6.0937, 6.0937, 6.0937] +24-11-19 19:20:49 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:20:49 | D | sum error = [ 85.3374, 90.1960, 95.2730, 100.6273, 106.1995] +24-11-19 19:20:49 | D | best error = [ 6.0937, 6.0937, 6.0937, 6.0937, 6.0937] +24-11-19 19:20:49 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:20:49 | D | sum error = [ 112.0577, 118.1542, 124.5177, 131.1649, 138.1191] +24-11-19 19:20:49 | D | best error = [ 6.0937, 6.0937, 6.0937, 6.0937, 6.0937] +24-11-19 19:20:49 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:20:49 | D | sum error = [ 145.3640, 152.9342, 160.8193, 169.0202, 177.5615] +24-11-19 19:20:49 | D | best error = [ 6.0937, 6.0937, 6.0937, 6.0937, 6.0937] +24-11-19 19:20:49 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:20:49 | D | sum error = [ 186.4594, 195.7081, 205.3211, 215.2947, 225.6579] +24-11-19 19:20:49 | D | best error = [ 6.0937, 6.0937, 6.0937, 6.0937, 6.0937] +24-11-19 19:20:49 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:20:49 | D | sum error = [ 236.4134, 247.5658, 259.1263, 271.1152, 283.5102] +24-11-19 19:20:49 | D | best error = [ 6.0937, 6.0937, 6.0937, 6.0937, 6.0937] +24-11-19 19:20:49 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:20:49 | D | sum error = [ 296.3473, 309.6354, 323.3695, 337.5640, 352.2210] +24-11-19 19:20:49 | D | best error = [ 6.0937, 6.0937, 6.0937, 6.0937, 6.0937] +24-11-19 19:20:49 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:20:49 | D | sum error = [ 367.3275, 382.9138, 398.9747, 415.5033, 432.5000] +24-11-19 19:20:49 | D | best error = [ 6.0937, 6.0937, 6.0937, 6.0937, 6.0937] +24-11-19 19:20:49 | D | + error = [6.0937] +24-11-19 19:20:49 | D | - Calibrating model.layers.15.mlp.gate_proj.weight +24-11-19 19:20:49 | D | + w: sint8 +24-11-19 19:20:49 | D | + x: None +24-11-19 19:20:49 | D | + y: None +24-11-19 19:20:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:20:49 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:20:49 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:20:49 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:20:49 | D | - range ratio = [ 1.0000] +24-11-19 19:20:49 | D | sum error = [ 7.1712] +24-11-19 19:20:49 | D | best error = [ 7.1712] +24-11-19 19:20:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:20:50 | D | sum error = [ 7.1040, 7.1006, 7.1257, 7.2034, 7.3494] +24-11-19 19:20:50 | D | best error = [ 6.6443, 6.4581, 6.3560, 6.2982, 6.2687] +24-11-19 19:20:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:20:50 | D | sum error = [ 7.5380, 7.7915, 8.1132, 8.4940, 8.9461] +24-11-19 19:20:50 | D | best error = [ 6.2546, 6.2477, 6.2456, 6.2452, 6.2449] +24-11-19 19:20:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:20:50 | D | sum error = [ 9.4641, 10.0899, 10.7238, 11.4599, 12.2417] +24-11-19 19:20:50 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 19:20:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:20:50 | D | sum error = [ 13.1167, 14.0598, 15.0826, 16.1819, 17.3477] +24-11-19 19:20:50 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 19:20:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:20:50 | D | sum error = [ 18.6093, 19.9466, 21.4047, 22.9080, 24.5507] +24-11-19 19:20:50 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 19:20:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:20:50 | D | sum error = [ 26.2959, 28.1121, 30.0752, 32.1414, 34.3256] +24-11-19 19:20:50 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 19:20:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:20:50 | D | sum error = [ 36.6659, 39.1314, 41.7663, 44.5145, 47.4412] +24-11-19 19:20:50 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 19:20:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:20:50 | D | sum error = [ 50.5495, 53.8270, 57.2998, 60.9544, 64.8489] +24-11-19 19:20:50 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 19:20:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:20:50 | D | sum error = [ 68.9410, 73.2769, 77.8378, 82.6792, 87.7439] +24-11-19 19:20:50 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 19:20:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:20:50 | D | sum error = [ 93.1184, 98.7964, 104.7796, 111.0940, 117.7813] +24-11-19 19:20:50 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 19:20:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:20:50 | D | sum error = [ 124.7912, 132.2078, 139.9991, 148.2007, 156.8029] +24-11-19 19:20:50 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 19:20:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:20:50 | D | sum error = [ 165.8662, 175.3643, 185.3443, 195.8254, 206.7970] +24-11-19 19:20:50 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 19:20:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:20:50 | D | sum error = [ 218.3113, 230.3489, 242.9178, 256.0910, 269.8593] +24-11-19 19:20:50 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 19:20:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:20:50 | D | sum error = [ 284.2238, 299.2012, 314.8113, 331.1156, 348.0112] +24-11-19 19:20:50 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 19:20:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:20:50 | D | sum error = [ 365.6242, 383.9129, 402.8933, 422.5576, 442.9579] +24-11-19 19:20:50 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 19:20:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:20:50 | D | sum error = [ 464.0777, 485.8929, 508.4168, 531.6390, 555.5749] +24-11-19 19:20:50 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 19:20:50 | D | + error = [6.2449] +24-11-19 19:20:50 | D | - Calibrating model.layers.15.mlp.down_proj.weight +24-11-19 19:20:50 | D | + w: sint8 +24-11-19 19:20:50 | D | + x: None +24-11-19 19:20:50 | D | + y: None +24-11-19 19:20:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:20:50 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:20:51 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:20:51 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:20:51 | D | - range ratio = [ 1.0000] +24-11-19 19:20:51 | D | sum error = [ 2.1369] +24-11-19 19:20:51 | D | best error = [ 2.1369] +24-11-19 19:20:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:20:52 | D | sum error = [ 2.1193, 2.1062, 2.0948, 2.0911, 2.0894] +24-11-19 19:20:52 | D | best error = [ 2.0653, 2.0283, 2.0026, 1.9850, 1.9698] +24-11-19 19:20:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:20:52 | D | sum error = [ 2.0954, 2.1100, 2.1356, 2.1708, 2.2162] +24-11-19 19:20:52 | D | best error = [ 1.9582, 1.9501, 1.9438, 1.9392, 1.9361] +24-11-19 19:20:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:20:52 | D | sum error = [ 2.2738, 2.3420, 2.4231, 2.5197, 2.6364] +24-11-19 19:20:52 | D | best error = [ 1.9346, 1.9333, 1.9323, 1.9318, 1.9314] +24-11-19 19:20:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:20:52 | D | sum error = [ 2.7608, 2.9063, 3.0671, 3.2434, 3.4413] +24-11-19 19:20:52 | D | best error = [ 1.9311, 1.9311, 1.9310, 1.9310, 1.9310] +24-11-19 19:20:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:20:52 | D | sum error = [ 3.6536, 3.8902, 4.1390, 4.4165, 4.7111] +24-11-19 19:20:52 | D | best error = [ 1.9310, 1.9309, 1.9309, 1.9309, 1.9309] +24-11-19 19:20:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:20:52 | D | sum error = [ 5.0256, 5.3715, 5.7321, 6.1188, 6.5395] +24-11-19 19:20:52 | D | best error = [ 1.9309, 1.9309, 1.9309, 1.9309, 1.9309] +24-11-19 19:20:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:20:52 | D | sum error = [ 6.9770, 7.4514, 7.9504, 8.4871, 9.0549] +24-11-19 19:20:52 | D | best error = [ 1.9309, 1.9309, 1.9309, 1.9309, 1.9309] +24-11-19 19:20:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:20:52 | D | sum error = [ 9.6561, 10.2958, 10.9787, 11.6921, 12.4490] +24-11-19 19:20:52 | D | best error = [ 1.9309, 1.9309, 1.9309, 1.9309, 1.9309] +24-11-19 19:20:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:20:52 | D | sum error = [ 13.2540, 14.1034, 15.0001, 15.9467, 16.9468] +24-11-19 19:20:52 | D | best error = [ 1.9309, 1.9309, 1.9309, 1.9309, 1.9309] +24-11-19 19:20:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:20:52 | D | sum error = [ 18.0012, 19.1104, 20.2823, 21.5147, 22.8113] +24-11-19 19:20:52 | D | best error = [ 1.9309, 1.9309, 1.9309, 1.9309, 1.9309] +24-11-19 19:20:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:20:52 | D | sum error = [ 24.1777, 25.6163, 27.1214, 28.7028, 30.3620] +24-11-19 19:20:52 | D | best error = [ 1.9309, 1.9309, 1.9309, 1.9309, 1.9309] +24-11-19 19:20:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:20:52 | D | sum error = [ 32.1032, 33.9304, 35.8441, 37.8471, 39.9451] +24-11-19 19:20:52 | D | best error = [ 1.9309, 1.9309, 1.9309, 1.9309, 1.9309] +24-11-19 19:20:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:20:52 | D | sum error = [ 42.1368, 44.4308, 46.8248, 49.3238, 51.9318] +24-11-19 19:20:52 | D | best error = [ 1.9309, 1.9309, 1.9309, 1.9309, 1.9309] +24-11-19 19:20:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:20:52 | D | sum error = [ 54.6551, 57.4887, 60.4401, 63.5154, 66.7058] +24-11-19 19:20:52 | D | best error = [ 1.9309, 1.9309, 1.9309, 1.9309, 1.9309] +24-11-19 19:20:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:20:52 | D | sum error = [ 70.0263, 73.4749, 77.0595, 80.7783, 84.6348] +24-11-19 19:20:52 | D | best error = [ 1.9309, 1.9309, 1.9309, 1.9309, 1.9309] +24-11-19 19:20:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:20:52 | D | sum error = [ 88.6329, 92.7715, 97.0552, 101.4890, 106.0722] +24-11-19 19:20:52 | D | best error = [ 1.9309, 1.9309, 1.9309, 1.9309, 1.9309] +24-11-19 19:20:52 | D | + error = [1.9309] +24-11-19 19:20:52 | D | - Quantizing model.layers.15.self_attn.q_proj.weight +24-11-19 19:20:53 | D | - Quantizing model.layers.15.self_attn.k_proj.weight +24-11-19 19:20:54 | D | - Quantizing model.layers.15.self_attn.v_proj.weight +24-11-19 19:20:55 | D | - Quantizing model.layers.15.self_attn.o_proj.weight +24-11-19 19:20:56 | D | - Quantizing model.layers.15.mlp.up_proj.weight +24-11-19 19:20:57 | D | - Quantizing model.layers.15.mlp.gate_proj.weight +24-11-19 19:20:58 | D | - Quantizing model.layers.15.mlp.down_proj.weight +24-11-19 19:21:06 | D | - Quantizing layer model.layers.16 +24-11-19 19:21:06 | D | - Calibrating model.layers.16.self_attn.q_proj.weight +24-11-19 19:21:06 | D | + w: sint8 +24-11-19 19:21:06 | D | + x: None +24-11-19 19:21:06 | D | + y: None +24-11-19 19:21:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:21:06 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:21:06 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:21:07 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:21:07 | D | - range ratio = [ 1.0000] +24-11-19 19:21:07 | D | sum error = [ 12.5225] +24-11-19 19:21:07 | D | best error = [ 12.5225] +24-11-19 19:21:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:21:19 | D | sum error = [ 12.4517, 12.5036, 12.5118, 12.5523, 12.8330] +24-11-19 19:21:19 | D | best error = [ 12.4517, 12.4517, 12.4517, 12.4517, 12.4517] +24-11-19 19:21:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:21:19 | D | sum error = [ 13.3793, 13.6634, 14.3045, 14.7735, 15.8356] +24-11-19 19:21:19 | D | best error = [ 12.4517, 12.4517, 12.4517, 12.4517, 12.4517] +24-11-19 19:21:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:21:19 | D | sum error = [ 16.5411, 17.7463, 18.9582, 20.5656, 21.6998] +24-11-19 19:21:19 | D | best error = [ 12.4517, 12.4517, 12.4517, 12.4517, 12.4517] +24-11-19 19:21:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:21:19 | D | sum error = [ 23.2613, 25.2151, 27.1419, 29.3522, 31.9739] +24-11-19 19:21:19 | D | best error = [ 12.4517, 12.4517, 12.4517, 12.4517, 12.4517] +24-11-19 19:21:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:21:19 | D | sum error = [ 34.0720, 36.6944, 39.5619, 42.5934, 46.0619] +24-11-19 19:21:19 | D | best error = [ 12.4517, 12.4517, 12.4517, 12.4517, 12.4517] +24-11-19 19:21:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:21:19 | D | sum error = [ 49.4440, 53.3521, 57.3720, 61.9981, 66.9402] +24-11-19 19:21:19 | D | best error = [ 12.4517, 12.4517, 12.4517, 12.4517, 12.4517] +24-11-19 19:21:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:21:19 | D | sum error = [ 71.6536, 77.4918, 83.0056, 89.1814, 96.0409] +24-11-19 19:21:19 | D | best error = [ 12.4517, 12.4517, 12.4517, 12.4517, 12.4517] +24-11-19 19:21:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:21:19 | D | sum error = [ 103.1442, 110.9891, 119.4091, 128.2043, 137.7813] +24-11-19 19:21:19 | D | best error = [ 12.4517, 12.4517, 12.4517, 12.4517, 12.4517] +24-11-19 19:21:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:21:19 | D | sum error = [ 147.8462, 158.9053, 170.4265, 183.4805, 196.6162] +24-11-19 19:21:19 | D | best error = [ 12.4517, 12.4517, 12.4517, 12.4517, 12.4517] +24-11-19 19:21:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:21:19 | D | sum error = [ 211.4779, 226.9552, 243.4616, 261.6449, 280.4709] +24-11-19 19:21:19 | D | best error = [ 12.4517, 12.4517, 12.4517, 12.4517, 12.4517] +24-11-19 19:21:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:21:19 | D | sum error = [ 300.8426, 322.9340, 346.4657, 371.4196, 398.4196] +24-11-19 19:21:19 | D | best error = [ 12.4517, 12.4517, 12.4517, 12.4517, 12.4517] +24-11-19 19:21:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:21:19 | D | sum error = [ 427.4814, 458.0844, 490.9688, 526.7740, 564.6910] +24-11-19 19:21:19 | D | best error = [ 12.4517, 12.4517, 12.4517, 12.4517, 12.4517] +24-11-19 19:21:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:21:19 | D | sum error = [ 605.4973, 649.5468, 696.3663, 747.0697, 801.4456] +24-11-19 19:21:19 | D | best error = [ 12.4517, 12.4517, 12.4517, 12.4517, 12.4517] +24-11-19 19:21:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:21:19 | D | sum error = [ 859.7287, 922.7083, 990.7938, 1064.2040, 1143.4381] +24-11-19 19:21:19 | D | best error = [ 12.4517, 12.4517, 12.4517, 12.4517, 12.4517] +24-11-19 19:21:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:21:19 | D | sum error = [ 1228.6858, 1320.2223, 1418.6941, 1524.1478, 1636.6496] +24-11-19 19:21:19 | D | best error = [ 12.4517, 12.4517, 12.4517, 12.4517, 12.4517] +24-11-19 19:21:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:21:19 | D | sum error = [ 1756.0421, 1883.4266, 2017.9511, 2158.6007, 2305.6803] +24-11-19 19:21:19 | D | best error = [ 12.4517, 12.4517, 12.4517, 12.4517, 12.4517] +24-11-19 19:21:19 | D | + error = [12.4517] +24-11-19 19:21:20 | D | - Calibrating model.layers.16.self_attn.k_proj.weight +24-11-19 19:21:20 | D | + w: sint8 +24-11-19 19:21:20 | D | + x: None +24-11-19 19:21:20 | D | + y: None +24-11-19 19:21:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:21:20 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:21:20 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:21:20 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:21:20 | D | - range ratio = [ 1.0000] +24-11-19 19:21:20 | D | sum error = [ 12.6272] +24-11-19 19:21:20 | D | best error = [ 12.6272] +24-11-19 19:21:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:21:33 | D | sum error = [ 12.7478, 12.1397, 12.7803, 13.6401, 13.1733] +24-11-19 19:21:33 | D | best error = [ 12.6272, 12.1397, 12.1397, 12.1397, 12.1397] +24-11-19 19:21:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:21:33 | D | sum error = [ 13.1634, 13.7587, 14.6275, 15.1975, 15.4459] +24-11-19 19:21:33 | D | best error = [ 12.1397, 12.1397, 12.1397, 12.1397, 12.1397] +24-11-19 19:21:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:21:33 | D | sum error = [ 16.5752, 18.1928, 20.2849, 20.8166, 22.0796] +24-11-19 19:21:33 | D | best error = [ 12.1397, 12.1397, 12.1397, 12.1397, 12.1397] +24-11-19 19:21:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:21:33 | D | sum error = [ 23.8825, 26.0955, 27.6437, 29.5152, 31.8062] +24-11-19 19:21:33 | D | best error = [ 12.1397, 12.1397, 12.1397, 12.1397, 12.1397] +24-11-19 19:21:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:21:33 | D | sum error = [ 35.3805, 37.3253, 40.2603, 43.4792, 47.1920] +24-11-19 19:21:33 | D | best error = [ 12.1397, 12.1397, 12.1397, 12.1397, 12.1397] +24-11-19 19:21:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:21:33 | D | sum error = [ 50.0031, 53.1439, 57.7163, 62.5376, 67.7453] +24-11-19 19:21:33 | D | best error = [ 12.1397, 12.1397, 12.1397, 12.1397, 12.1397] +24-11-19 19:21:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:21:33 | D | sum error = [ 72.3262, 77.8483, 83.0509, 90.3958, 96.0145] +24-11-19 19:21:33 | D | best error = [ 12.1397, 12.1397, 12.1397, 12.1397, 12.1397] +24-11-19 19:21:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:21:33 | D | sum error = [ 102.5639, 110.0025, 118.2848, 126.3806, 135.7999] +24-11-19 19:21:33 | D | best error = [ 12.1397, 12.1397, 12.1397, 12.1397, 12.1397] +24-11-19 19:21:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:21:33 | D | sum error = [ 145.6823, 157.3881, 167.6006, 179.9773, 192.5253] +24-11-19 19:21:33 | D | best error = [ 12.1397, 12.1397, 12.1397, 12.1397, 12.1397] +24-11-19 19:21:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:21:33 | D | sum error = [ 206.9996, 223.7668, 240.8125, 259.3031, 279.2275] +24-11-19 19:21:33 | D | best error = [ 12.1397, 12.1397, 12.1397, 12.1397, 12.1397] +24-11-19 19:21:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:21:33 | D | sum error = [ 300.7479, 323.9746, 350.0342, 376.3651, 405.4036] +24-11-19 19:21:33 | D | best error = [ 12.1397, 12.1397, 12.1397, 12.1397, 12.1397] +24-11-19 19:21:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:21:33 | D | sum error = [ 435.6633, 466.6302, 503.0759, 541.3405, 581.6130] +24-11-19 19:21:33 | D | best error = [ 12.1397, 12.1397, 12.1397, 12.1397, 12.1397] +24-11-19 19:21:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:21:33 | D | sum error = [ 624.3177, 670.5136, 716.1420, 770.6256, 827.4623] +24-11-19 19:21:33 | D | best error = [ 12.1397, 12.1397, 12.1397, 12.1397, 12.1397] +24-11-19 19:21:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:21:33 | D | sum error = [ 884.2222, 951.8985, 1017.3126, 1089.7435, 1167.7862] +24-11-19 19:21:33 | D | best error = [ 12.1397, 12.1397, 12.1397, 12.1397, 12.1397] +24-11-19 19:21:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:21:33 | D | sum error = [ 1253.3568, 1337.5724, 1438.0898, 1540.8734, 1646.8632] +24-11-19 19:21:33 | D | best error = [ 12.1397, 12.1397, 12.1397, 12.1397, 12.1397] +24-11-19 19:21:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:21:33 | D | sum error = [ 1766.2522, 1889.4346, 2020.0592, 2156.6699, 2298.9187] +24-11-19 19:21:33 | D | best error = [ 12.1397, 12.1397, 12.1397, 12.1397, 12.1397] +24-11-19 19:21:33 | D | + error = [12.1397] +24-11-19 19:21:33 | D | - Calibrating model.layers.16.self_attn.v_proj.weight +24-11-19 19:21:33 | D | + w: sint8 +24-11-19 19:21:33 | D | + x: None +24-11-19 19:21:33 | D | + y: None +24-11-19 19:21:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:21:33 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:21:33 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:21:33 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:21:33 | D | - range ratio = [ 1.0000] +24-11-19 19:21:33 | D | sum error = [ 5.3645] +24-11-19 19:21:33 | D | best error = [ 5.3645] +24-11-19 19:21:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:21:34 | D | sum error = [ 5.3299, 5.3274, 5.3293, 5.3944, 5.4893] +24-11-19 19:21:34 | D | best error = [ 4.9932, 4.8533, 4.7710, 4.7253, 4.7035] +24-11-19 19:21:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:21:34 | D | sum error = [ 5.6367, 5.8264, 6.0924, 6.3377, 6.6850] +24-11-19 19:21:34 | D | best error = [ 4.6940, 4.6897, 4.6876, 4.6868, 4.6867] +24-11-19 19:21:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:21:34 | D | sum error = [ 7.0380, 7.4851, 7.9768, 8.4949, 9.1010] +24-11-19 19:21:34 | D | best error = [ 4.6867, 4.6867, 4.6867, 4.6867, 4.6867] +24-11-19 19:21:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:21:34 | D | sum error = [ 9.7138, 10.4182, 11.1517, 11.9934, 12.8203] +24-11-19 19:21:34 | D | best error = [ 4.6867, 4.6867, 4.6867, 4.6867, 4.6867] +24-11-19 19:21:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:21:34 | D | sum error = [ 13.7455, 14.7338, 15.7658, 16.8738, 18.0559] +24-11-19 19:21:34 | D | best error = [ 4.6867, 4.6867, 4.6867, 4.6867, 4.6867] +24-11-19 19:21:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:21:34 | D | sum error = [ 19.3045, 20.6297, 22.0174, 23.4948, 25.0600] +24-11-19 19:21:34 | D | best error = [ 4.6867, 4.6867, 4.6867, 4.6867, 4.6867] +24-11-19 19:21:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:21:34 | D | sum error = [ 26.6932, 28.4023, 30.2484, 32.1575, 34.1826] +24-11-19 19:21:34 | D | best error = [ 4.6867, 4.6867, 4.6867, 4.6867, 4.6867] +24-11-19 19:21:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:21:34 | D | sum error = [ 36.3030, 38.5542, 40.8759, 43.3554, 45.9373] +24-11-19 19:21:34 | D | best error = [ 4.6867, 4.6867, 4.6867, 4.6867, 4.6867] +24-11-19 19:21:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:21:34 | D | sum error = [ 48.6709, 51.5214, 54.4955, 57.6242, 60.9103] +24-11-19 19:21:34 | D | best error = [ 4.6867, 4.6867, 4.6867, 4.6867, 4.6867] +24-11-19 19:21:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:21:34 | D | sum error = [ 64.3259, 67.9130, 71.6445, 75.5538, 79.6352] +24-11-19 19:21:34 | D | best error = [ 4.6867, 4.6867, 4.6867, 4.6867, 4.6867] +24-11-19 19:21:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:21:34 | D | sum error = [ 83.8991, 88.3382, 92.9856, 97.8382, 102.8837] +24-11-19 19:21:34 | D | best error = [ 4.6867, 4.6867, 4.6867, 4.6867, 4.6867] +24-11-19 19:21:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:21:34 | D | sum error = [ 108.1429, 113.6149, 119.3090, 125.2378, 131.4037] +24-11-19 19:21:34 | D | best error = [ 4.6867, 4.6867, 4.6867, 4.6867, 4.6867] +24-11-19 19:21:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:21:34 | D | sum error = [ 137.8084, 144.4694, 151.3785, 158.5237, 165.9737] +24-11-19 19:21:34 | D | best error = [ 4.6867, 4.6867, 4.6867, 4.6867, 4.6867] +24-11-19 19:21:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:21:34 | D | sum error = [ 173.6659, 181.6497, 189.9068, 198.4520, 207.2699] +24-11-19 19:21:34 | D | best error = [ 4.6867, 4.6867, 4.6867, 4.6867, 4.6867] +24-11-19 19:21:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:21:34 | D | sum error = [ 216.3913, 225.7962, 235.5211, 245.5521, 255.8918] +24-11-19 19:21:34 | D | best error = [ 4.6867, 4.6867, 4.6867, 4.6867, 4.6867] +24-11-19 19:21:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:21:34 | D | sum error = [ 266.5257, 277.4904, 288.7607, 300.3473, 312.2650] +24-11-19 19:21:34 | D | best error = [ 4.6867, 4.6867, 4.6867, 4.6867, 4.6867] +24-11-19 19:21:34 | D | + error = [4.6867] +24-11-19 19:21:34 | D | - Calibrating model.layers.16.self_attn.o_proj.weight +24-11-19 19:21:34 | D | + w: sint8 +24-11-19 19:21:34 | D | + x: None +24-11-19 19:21:34 | D | + y: None +24-11-19 19:21:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:21:34 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:21:34 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:21:34 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:21:34 | D | - range ratio = [ 1.0000] +24-11-19 19:21:34 | D | sum error = [ 1.6722] +24-11-19 19:21:34 | D | best error = [ 1.6722] +24-11-19 19:21:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:21:34 | D | sum error = [ 1.6593, 1.6520, 1.6511, 1.6612, 1.6750] +24-11-19 19:21:34 | D | best error = [ 1.5608, 1.5098, 1.4782, 1.4582, 1.4444] +24-11-19 19:21:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:21:34 | D | sum error = [ 1.7011, 1.7281, 1.7796, 1.8423, 1.9131] +24-11-19 19:21:34 | D | best error = [ 1.4350, 1.4287, 1.4240, 1.4218, 1.4201] +24-11-19 19:21:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:21:34 | D | sum error = [ 1.9965, 2.0872, 2.1926, 2.3099, 2.4445] +24-11-19 19:21:34 | D | best error = [ 1.4191, 1.4184, 1.4178, 1.4175, 1.4172] +24-11-19 19:21:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:21:34 | D | sum error = [ 2.6046, 2.7617, 2.9363, 3.1287, 3.3351] +24-11-19 19:21:34 | D | best error = [ 1.4168, 1.4167, 1.4166, 1.4166, 1.4166] +24-11-19 19:21:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:21:34 | D | sum error = [ 3.5612, 3.7922, 4.0509, 4.3179, 4.6061] +24-11-19 19:21:34 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 19:21:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:21:34 | D | sum error = [ 4.9180, 5.2497, 5.5909, 5.9590, 6.3557] +24-11-19 19:21:34 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 19:21:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:21:34 | D | sum error = [ 6.7663, 7.2057, 7.6640, 8.1546, 8.6693] +24-11-19 19:21:34 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 19:21:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:21:34 | D | sum error = [ 9.2142, 9.7908, 10.3990, 11.0386, 11.7153] +24-11-19 19:21:34 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 19:21:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:21:34 | D | sum error = [ 12.4221, 13.1681, 13.9465, 14.7764, 15.6393] +24-11-19 19:21:34 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 19:21:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:21:34 | D | sum error = [ 16.5576, 17.5137, 18.5207, 19.5841, 20.6972] +24-11-19 19:21:34 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 19:21:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:21:34 | D | sum error = [ 21.8655, 23.0932, 24.3769, 25.7260, 27.1349] +24-11-19 19:21:34 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 19:21:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:21:34 | D | sum error = [ 28.6189, 30.1700, 31.7919, 33.4847, 35.2564] +24-11-19 19:21:34 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 19:21:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:21:34 | D | sum error = [ 37.1090, 39.0358, 41.0561, 43.1665, 45.3663] +24-11-19 19:21:34 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 19:21:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:21:34 | D | sum error = [ 47.6571, 50.0374, 52.5160, 55.0974, 57.7779] +24-11-19 19:21:34 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 19:21:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:21:34 | D | sum error = [ 60.5643, 63.4537, 66.4528, 69.5623, 72.7892] +24-11-19 19:21:34 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 19:21:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:21:34 | D | sum error = [ 76.1327, 79.5952, 83.1755, 86.8780, 90.7087] +24-11-19 19:21:34 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 19:21:34 | D | + error = [1.4166] +24-11-19 19:21:34 | D | - Calibrating model.layers.16.mlp.up_proj.weight +24-11-19 19:21:34 | D | + w: sint8 +24-11-19 19:21:34 | D | + x: None +24-11-19 19:21:34 | D | + y: None +24-11-19 19:21:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:21:34 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:21:34 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:21:35 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:21:35 | D | - range ratio = [ 1.0000] +24-11-19 19:21:35 | D | sum error = [ 7.4574] +24-11-19 19:21:35 | D | best error = [ 7.4574] +24-11-19 19:21:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:21:36 | D | sum error = [ 7.3823, 7.3822, 7.3901, 7.4681, 7.6146] +24-11-19 19:21:36 | D | best error = [ 6.9160, 6.7104, 6.6029, 6.5385, 6.5041] +24-11-19 19:21:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:21:36 | D | sum error = [ 7.8015, 8.0687, 8.4294, 8.8200, 9.2558] +24-11-19 19:21:36 | D | best error = [ 6.4881, 6.4813, 6.4791, 6.4785, 6.4782] +24-11-19 19:21:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:21:36 | D | sum error = [ 9.8093, 10.4239, 11.0876, 11.8312, 12.6417] +24-11-19 19:21:36 | D | best error = [ 6.4782, 6.4782, 6.4782, 6.4782, 6.4782] +24-11-19 19:21:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:21:36 | D | sum error = [ 13.5319, 14.5160, 15.5390, 16.6466, 17.8687] +24-11-19 19:21:36 | D | best error = [ 6.4782, 6.4782, 6.4782, 6.4782, 6.4782] +24-11-19 19:21:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:21:36 | D | sum error = [ 19.1348, 20.4818, 21.9363, 23.4631, 25.0944] +24-11-19 19:21:36 | D | best error = [ 6.4782, 6.4782, 6.4782, 6.4782, 6.4782] +24-11-19 19:21:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:21:36 | D | sum error = [ 26.8384, 28.6639, 30.6115, 32.6519, 34.8588] +24-11-19 19:21:36 | D | best error = [ 6.4782, 6.4782, 6.4782, 6.4782, 6.4782] +24-11-19 19:21:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:21:36 | D | sum error = [ 37.1389, 39.5563, 42.1482, 44.8168, 47.6700] +24-11-19 19:21:36 | D | best error = [ 6.4782, 6.4782, 6.4782, 6.4782, 6.4782] +24-11-19 19:21:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:21:36 | D | sum error = [ 50.6680, 53.8224, 57.1381, 60.6387, 64.3067] +24-11-19 19:21:36 | D | best error = [ 6.4782, 6.4782, 6.4782, 6.4782, 6.4782] +24-11-19 19:21:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:21:36 | D | sum error = [ 68.1778, 72.2588, 76.5362, 81.0264, 85.7546] +24-11-19 19:21:36 | D | best error = [ 6.4782, 6.4782, 6.4782, 6.4782, 6.4782] +24-11-19 19:21:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:21:36 | D | sum error = [ 90.6854, 95.8907, 101.3351, 107.0612, 113.0271] +24-11-19 19:21:36 | D | best error = [ 6.4782, 6.4782, 6.4782, 6.4782, 6.4782] +24-11-19 19:21:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:21:36 | D | sum error = [ 119.2688, 125.8423, 132.6864, 139.8445, 147.3283] +24-11-19 19:21:36 | D | best error = [ 6.4782, 6.4782, 6.4782, 6.4782, 6.4782] +24-11-19 19:21:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:21:36 | D | sum error = [ 155.1345, 163.2792, 171.8007, 180.6839, 189.9323] +24-11-19 19:21:36 | D | best error = [ 6.4782, 6.4782, 6.4782, 6.4782, 6.4782] +24-11-19 19:21:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:21:36 | D | sum error = [ 199.5746, 209.6082, 220.0472, 230.9236, 242.2229] +24-11-19 19:21:36 | D | best error = [ 6.4782, 6.4782, 6.4782, 6.4782, 6.4782] +24-11-19 19:21:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:21:36 | D | sum error = [ 253.9524, 266.1343, 278.7653, 291.8708, 305.4414] +24-11-19 19:21:36 | D | best error = [ 6.4782, 6.4782, 6.4782, 6.4782, 6.4782] +24-11-19 19:21:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:21:36 | D | sum error = [ 319.4770, 333.9912, 349.0156, 364.5585, 380.6093] +24-11-19 19:21:36 | D | best error = [ 6.4782, 6.4782, 6.4782, 6.4782, 6.4782] +24-11-19 19:21:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:21:36 | D | sum error = [ 397.1621, 414.2361, 431.8347, 449.9404, 468.5944] +24-11-19 19:21:36 | D | best error = [ 6.4782, 6.4782, 6.4782, 6.4782, 6.4782] +24-11-19 19:21:36 | D | + error = [6.4782] +24-11-19 19:21:36 | D | - Calibrating model.layers.16.mlp.gate_proj.weight +24-11-19 19:21:36 | D | + w: sint8 +24-11-19 19:21:36 | D | + x: None +24-11-19 19:21:36 | D | + y: None +24-11-19 19:21:36 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:21:36 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:21:36 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:21:36 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:21:36 | D | - range ratio = [ 1.0000] +24-11-19 19:21:36 | D | sum error = [ 7.6664] +24-11-19 19:21:36 | D | best error = [ 7.6664] +24-11-19 19:21:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:21:37 | D | sum error = [ 7.6077, 7.5893, 7.6234, 7.7350, 7.8516] +24-11-19 19:21:37 | D | best error = [ 7.1301, 6.9205, 6.8048, 6.7427, 6.7086] +24-11-19 19:21:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:21:37 | D | sum error = [ 8.0634, 8.3360, 8.6856, 9.0859, 9.5819] +24-11-19 19:21:37 | D | best error = [ 6.6941, 6.6877, 6.6849, 6.6839, 6.6837] +24-11-19 19:21:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:21:37 | D | sum error = [ 10.1342, 10.7673, 11.4834, 12.2636, 13.1067] +24-11-19 19:21:37 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 19:21:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:21:37 | D | sum error = [ 14.0633, 15.0755, 16.1904, 17.3719, 18.6041] +24-11-19 19:21:37 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 19:21:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:21:37 | D | sum error = [ 19.9841, 21.4410, 22.9853, 24.6392, 26.4199] +24-11-19 19:21:37 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 19:21:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:21:37 | D | sum error = [ 28.2930, 30.2716, 32.3864, 34.6266, 37.0034] +24-11-19 19:21:37 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 19:21:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:21:37 | D | sum error = [ 39.5257, 42.2167, 45.0457, 48.0562, 51.2300] +24-11-19 19:21:37 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 19:21:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:21:37 | D | sum error = [ 54.5835, 58.1685, 61.9743, 65.9947, 70.2141] +24-11-19 19:21:37 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 19:21:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:21:37 | D | sum error = [ 74.7049, 79.4083, 84.4365, 89.6915, 95.2676] +24-11-19 19:21:37 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 19:21:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:21:37 | D | sum error = [ 101.1613, 107.3877, 113.9410, 120.8668, 128.2069] +24-11-19 19:21:37 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 19:21:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:21:37 | D | sum error = [ 135.9115, 144.0103, 152.5694, 161.5914, 171.0748] +24-11-19 19:21:37 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 19:21:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:21:37 | D | sum error = [ 181.0345, 191.5404, 202.5569, 214.1269, 226.2656] +24-11-19 19:21:37 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 19:21:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:21:37 | D | sum error = [ 238.9680, 252.2967, 266.2103, 280.7749, 295.9732] +24-11-19 19:21:37 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 19:21:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:21:37 | D | sum error = [ 311.8424, 328.4058, 345.6776, 363.6672, 382.3851] +24-11-19 19:21:37 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 19:21:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:21:37 | D | sum error = [ 401.8375, 422.0374, 443.0049, 464.7626, 487.3009] +24-11-19 19:21:37 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 19:21:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:21:37 | D | sum error = [ 510.5785, 534.6472, 559.4975, 585.1137, 611.5047] +24-11-19 19:21:37 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 19:21:37 | D | + error = [6.6836] +24-11-19 19:21:37 | D | - Calibrating model.layers.16.mlp.down_proj.weight +24-11-19 19:21:37 | D | + w: sint8 +24-11-19 19:21:37 | D | + x: None +24-11-19 19:21:37 | D | + y: None +24-11-19 19:21:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:21:37 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:21:37 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:21:37 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:21:37 | D | - range ratio = [ 1.0000] +24-11-19 19:21:37 | D | sum error = [ 2.7201] +24-11-19 19:21:37 | D | best error = [ 2.7201] +24-11-19 19:21:38 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:21:38 | D | sum error = [ 2.7032, 2.6876, 2.6643, 2.6539, 2.6508] +24-11-19 19:21:38 | D | best error = [ 2.5824, 2.5109, 2.4638, 2.4305, 2.4046] +24-11-19 19:21:38 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:21:38 | D | sum error = [ 2.6505, 2.6692, 2.6889, 2.7267, 2.7701] +24-11-19 19:21:38 | D | best error = [ 2.3833, 2.3668, 2.3549, 2.3474, 2.3413] +24-11-19 19:21:38 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:21:38 | D | sum error = [ 2.8254, 2.9007, 2.9913, 3.0958, 3.2108] +24-11-19 19:21:38 | D | best error = [ 2.3372, 2.3343, 2.3323, 2.3309, 2.3303] +24-11-19 19:21:38 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:21:38 | D | sum error = [ 3.3523, 3.5216, 3.6987, 3.9055, 4.1389] +24-11-19 19:21:38 | D | best error = [ 2.3297, 2.3293, 2.3291, 2.3290, 2.3289] +24-11-19 19:21:38 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:21:38 | D | sum error = [ 4.3852, 4.6710, 4.9795, 5.3152, 5.6730] +24-11-19 19:21:38 | D | best error = [ 2.3289, 2.3288, 2.3288, 2.3288, 2.3288] +24-11-19 19:21:38 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:21:38 | D | sum error = [ 6.0648, 6.4920, 6.9382, 7.4291, 7.9464] +24-11-19 19:21:38 | D | best error = [ 2.3288, 2.3288, 2.3288, 2.3288, 2.3288] +24-11-19 19:21:38 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:21:38 | D | sum error = [ 8.5027, 9.0917, 9.7228, 10.3973, 11.1107] +24-11-19 19:21:38 | D | best error = [ 2.3288, 2.3288, 2.3288, 2.3288, 2.3288] +24-11-19 19:21:38 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:21:38 | D | sum error = [ 11.8682, 12.6818, 13.5423, 14.4542, 15.4252] +24-11-19 19:21:38 | D | best error = [ 2.3288, 2.3288, 2.3288, 2.3288, 2.3288] +24-11-19 19:21:38 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:21:38 | D | sum error = [ 16.4521, 17.5483, 18.7000, 19.9112, 21.1963] +24-11-19 19:21:38 | D | best error = [ 2.3288, 2.3288, 2.3288, 2.3288, 2.3288] +24-11-19 19:21:38 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:21:38 | D | sum error = [ 22.5494, 23.9761, 25.4766, 27.0563, 28.7187] +24-11-19 19:21:38 | D | best error = [ 2.3288, 2.3288, 2.3288, 2.3288, 2.3288] +24-11-19 19:21:38 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:21:38 | D | sum error = [ 30.4675, 32.3088, 34.2383, 36.2683, 38.3932] +24-11-19 19:21:38 | D | best error = [ 2.3288, 2.3288, 2.3288, 2.3288, 2.3288] +24-11-19 19:21:38 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:21:38 | D | sum error = [ 40.6310, 42.9782, 45.4329, 48.0051, 50.6866] +24-11-19 19:21:38 | D | best error = [ 2.3288, 2.3288, 2.3288, 2.3288, 2.3288] +24-11-19 19:21:38 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:21:38 | D | sum error = [ 53.4993, 56.4318, 59.4954, 62.6943, 66.0320] +24-11-19 19:21:38 | D | best error = [ 2.3288, 2.3288, 2.3288, 2.3288, 2.3288] +24-11-19 19:21:38 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:21:38 | D | sum error = [ 69.5165, 73.1456, 76.9264, 80.8653, 84.9465] +24-11-19 19:21:38 | D | best error = [ 2.3288, 2.3288, 2.3288, 2.3288, 2.3288] +24-11-19 19:21:38 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:21:38 | D | sum error = [ 89.1973, 93.6100, 98.1918, 102.9430, 107.8686] +24-11-19 19:21:38 | D | best error = [ 2.3288, 2.3288, 2.3288, 2.3288, 2.3288] +24-11-19 19:21:38 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:21:38 | D | sum error = [ 112.9726, 118.2523, 123.7138, 129.3567, 135.1898] +24-11-19 19:21:38 | D | best error = [ 2.3288, 2.3288, 2.3288, 2.3288, 2.3288] +24-11-19 19:21:38 | D | + error = [2.3288] +24-11-19 19:21:38 | D | - Quantizing model.layers.16.self_attn.q_proj.weight +24-11-19 19:21:39 | D | - Quantizing model.layers.16.self_attn.k_proj.weight +24-11-19 19:21:40 | D | - Quantizing model.layers.16.self_attn.v_proj.weight +24-11-19 19:21:41 | D | - Quantizing model.layers.16.self_attn.o_proj.weight +24-11-19 19:21:42 | D | - Quantizing model.layers.16.mlp.up_proj.weight +24-11-19 19:21:43 | D | - Quantizing model.layers.16.mlp.gate_proj.weight +24-11-19 19:21:44 | D | - Quantizing model.layers.16.mlp.down_proj.weight +24-11-19 19:21:52 | D | - Quantizing layer model.layers.17 +24-11-19 19:21:52 | D | - Calibrating model.layers.17.self_attn.q_proj.weight +24-11-19 19:21:52 | D | + w: sint8 +24-11-19 19:21:52 | D | + x: None +24-11-19 19:21:52 | D | + y: None +24-11-19 19:21:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:21:52 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:21:52 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:21:53 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:21:53 | D | - range ratio = [ 1.0000] +24-11-19 19:21:53 | D | sum error = [ 11.2599] +24-11-19 19:21:53 | D | best error = [ 11.2599] +24-11-19 19:22:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:22:06 | D | sum error = [ 11.2053, 11.2431, 11.3517, 11.3444, 11.6018] +24-11-19 19:22:06 | D | best error = [ 11.2053, 11.2053, 11.2053, 11.2053, 11.2053] +24-11-19 19:22:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:22:06 | D | sum error = [ 11.9775, 12.3497, 12.8835, 13.8243, 14.2236] +24-11-19 19:22:06 | D | best error = [ 11.2053, 11.2053, 11.2053, 11.2053, 11.2053] +24-11-19 19:22:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:22:06 | D | sum error = [ 15.0331, 16.3472, 17.0901, 18.2943, 19.4523] +24-11-19 19:22:06 | D | best error = [ 11.2053, 11.2053, 11.2053, 11.2053, 11.2053] +24-11-19 19:22:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:22:06 | D | sum error = [ 20.7119, 22.6235, 24.0898, 26.1896, 28.2493] +24-11-19 19:22:06 | D | best error = [ 11.2053, 11.2053, 11.2053, 11.2053, 11.2053] +24-11-19 19:22:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:22:06 | D | sum error = [ 30.7436, 33.2658, 35.7397, 38.7954, 41.8666] +24-11-19 19:22:06 | D | best error = [ 11.2053, 11.2053, 11.2053, 11.2053, 11.2053] +24-11-19 19:22:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:22:06 | D | sum error = [ 45.6020, 49.3904, 53.3846, 57.8328, 62.7432] +24-11-19 19:22:06 | D | best error = [ 11.2053, 11.2053, 11.2053, 11.2053, 11.2053] +24-11-19 19:22:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:22:06 | D | sum error = [ 67.6264, 73.2011, 79.4976, 86.1935, 92.9042] +24-11-19 19:22:06 | D | best error = [ 11.2053, 11.2053, 11.2053, 11.2053, 11.2053] +24-11-19 19:22:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:22:06 | D | sum error = [ 100.1571, 108.4973, 117.2863, 126.0742, 135.7097] +24-11-19 19:22:06 | D | best error = [ 11.2053, 11.2053, 11.2053, 11.2053, 11.2053] +24-11-19 19:22:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:22:06 | D | sum error = [ 145.6943, 156.4228, 168.3649, 180.7566, 193.9433] +24-11-19 19:22:06 | D | best error = [ 11.2053, 11.2053, 11.2053, 11.2053, 11.2053] +24-11-19 19:22:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:22:06 | D | sum error = [ 208.0321, 223.9131, 240.1641, 258.0883, 277.3190] +24-11-19 19:22:06 | D | best error = [ 11.2053, 11.2053, 11.2053, 11.2053, 11.2053] +24-11-19 19:22:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:22:06 | D | sum error = [ 297.8735, 320.0581, 343.9527, 369.8266, 397.5272] +24-11-19 19:22:06 | D | best error = [ 11.2053, 11.2053, 11.2053, 11.2053, 11.2053] +24-11-19 19:22:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:22:06 | D | sum error = [ 427.3567, 460.0686, 494.8681, 532.1892, 572.9547] +24-11-19 19:22:06 | D | best error = [ 11.2053, 11.2053, 11.2053, 11.2053, 11.2053] +24-11-19 19:22:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:22:06 | D | sum error = [ 617.4723, 665.4843, 717.7705, 774.4549, 835.9045] +24-11-19 19:22:06 | D | best error = [ 11.2053, 11.2053, 11.2053, 11.2053, 11.2053] +24-11-19 19:22:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:22:06 | D | sum error = [ 902.9735, 976.0824, 1055.7476, 1142.4450, 1237.1968] +24-11-19 19:22:06 | D | best error = [ 11.2053, 11.2053, 11.2053, 11.2053, 11.2053] +24-11-19 19:22:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:22:06 | D | sum error = [ 1340.0783, 1452.4906, 1574.1388, 1708.3454, 1853.0637] +24-11-19 19:22:06 | D | best error = [ 11.2053, 11.2053, 11.2053, 11.2053, 11.2053] +24-11-19 19:22:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:22:06 | D | sum error = [ 2010.0197, 2180.4359, 2361.0047, 2557.3780, 2763.9770] +24-11-19 19:22:06 | D | best error = [ 11.2053, 11.2053, 11.2053, 11.2053, 11.2053] +24-11-19 19:22:06 | D | + error = [11.2053] +24-11-19 19:22:06 | D | - Calibrating model.layers.17.self_attn.k_proj.weight +24-11-19 19:22:06 | D | + w: sint8 +24-11-19 19:22:06 | D | + x: None +24-11-19 19:22:06 | D | + y: None +24-11-19 19:22:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:22:06 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:22:06 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:22:06 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:22:06 | D | - range ratio = [ 1.0000] +24-11-19 19:22:06 | D | sum error = [ 11.4013] +24-11-19 19:22:06 | D | best error = [ 11.4013] +24-11-19 19:22:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:22:19 | D | sum error = [ 11.4355, 11.6157, 12.0068, 12.7584, 12.9823] +24-11-19 19:22:19 | D | best error = [ 11.4013, 11.4013, 11.4013, 11.4013, 11.4013] +24-11-19 19:22:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:22:19 | D | sum error = [ 13.1175, 13.3410, 13.6013, 15.0782, 15.5448] +24-11-19 19:22:19 | D | best error = [ 11.4013, 11.4013, 11.4013, 11.4013, 11.4013] +24-11-19 19:22:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:22:19 | D | sum error = [ 16.2789, 16.9953, 18.5729, 20.0912, 21.4199] +24-11-19 19:22:19 | D | best error = [ 11.4013, 11.4013, 11.4013, 11.4013, 11.4013] +24-11-19 19:22:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:22:19 | D | sum error = [ 23.1507, 24.8593, 26.8037, 28.8663, 30.1994] +24-11-19 19:22:19 | D | best error = [ 11.4013, 11.4013, 11.4013, 11.4013, 11.4013] +24-11-19 19:22:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:22:19 | D | sum error = [ 33.3764, 36.1111, 38.8427, 41.9187, 45.3963] +24-11-19 19:22:19 | D | best error = [ 11.4013, 11.4013, 11.4013, 11.4013, 11.4013] +24-11-19 19:22:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:22:19 | D | sum error = [ 48.6630, 53.0055, 57.3705, 61.2843, 65.5164] +24-11-19 19:22:19 | D | best error = [ 11.4013, 11.4013, 11.4013, 11.4013, 11.4013] +24-11-19 19:22:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:22:19 | D | sum error = [ 71.4920, 76.7367, 82.4615, 88.6103, 96.5118] +24-11-19 19:22:19 | D | best error = [ 11.4013, 11.4013, 11.4013, 11.4013, 11.4013] +24-11-19 19:22:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:22:19 | D | sum error = [ 102.7555, 109.8842, 118.6393, 127.1654, 137.4088] +24-11-19 19:22:19 | D | best error = [ 11.4013, 11.4013, 11.4013, 11.4013, 11.4013] +24-11-19 19:22:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:22:19 | D | sum error = [ 147.6462, 157.3088, 168.7241, 181.4358, 195.3880] +24-11-19 19:22:19 | D | best error = [ 11.4013, 11.4013, 11.4013, 11.4013, 11.4013] +24-11-19 19:22:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:22:19 | D | sum error = [ 208.7529, 224.5260, 240.8019, 257.4730, 277.2720] +24-11-19 19:22:19 | D | best error = [ 11.4013, 11.4013, 11.4013, 11.4013, 11.4013] +24-11-19 19:22:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:22:19 | D | sum error = [ 296.7655, 320.6966, 344.9467, 368.7093, 396.2388] +24-11-19 19:22:19 | D | best error = [ 11.4013, 11.4013, 11.4013, 11.4013, 11.4013] +24-11-19 19:22:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:22:19 | D | sum error = [ 427.6259, 458.7561, 493.2968, 534.6412, 575.8048] +24-11-19 19:22:19 | D | best error = [ 11.4013, 11.4013, 11.4013, 11.4013, 11.4013] +24-11-19 19:22:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:22:19 | D | sum error = [ 620.6776, 668.2681, 727.5767, 784.2637, 844.4839] +24-11-19 19:22:19 | D | best error = [ 11.4013, 11.4013, 11.4013, 11.4013, 11.4013] +24-11-19 19:22:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:22:19 | D | sum error = [ 917.1930, 990.7473, 1068.3659, 1156.0949, 1258.4708] +24-11-19 19:22:19 | D | best error = [ 11.4013, 11.4013, 11.4013, 11.4013, 11.4013] +24-11-19 19:22:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:22:19 | D | sum error = [ 1357.5866, 1475.7407, 1598.0578, 1741.9811, 1883.2965] +24-11-19 19:22:19 | D | best error = [ 11.4013, 11.4013, 11.4013, 11.4013, 11.4013] +24-11-19 19:22:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:22:19 | D | sum error = [ 2043.4610, 2220.7641, 2402.1216, 2602.0848, 2809.3853] +24-11-19 19:22:19 | D | best error = [ 11.4013, 11.4013, 11.4013, 11.4013, 11.4013] +24-11-19 19:22:19 | D | + error = [11.4013] +24-11-19 19:22:19 | D | - Calibrating model.layers.17.self_attn.v_proj.weight +24-11-19 19:22:19 | D | + w: sint8 +24-11-19 19:22:19 | D | + x: None +24-11-19 19:22:19 | D | + y: None +24-11-19 19:22:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:22:19 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:22:19 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:22:19 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:22:19 | D | - range ratio = [ 1.0000] +24-11-19 19:22:19 | D | sum error = [ 5.5375] +24-11-19 19:22:19 | D | best error = [ 5.5375] +24-11-19 19:22:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:22:20 | D | sum error = [ 5.4939, 5.4808, 5.5062, 5.5653, 5.6938] +24-11-19 19:22:20 | D | best error = [ 5.1548, 4.9952, 4.9139, 4.8717, 4.8497] +24-11-19 19:22:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:22:20 | D | sum error = [ 5.8230, 6.0108, 6.2412, 6.5429, 6.8831] +24-11-19 19:22:20 | D | best error = [ 4.8392, 4.8339, 4.8318, 4.8313, 4.8311] +24-11-19 19:22:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:22:20 | D | sum error = [ 7.2810, 7.7349, 8.2368, 8.7761, 9.3884] +24-11-19 19:22:20 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 19:22:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:22:20 | D | sum error = [ 10.0646, 10.7881, 11.5538, 12.3648, 13.2499] +24-11-19 19:22:20 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 19:22:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:22:20 | D | sum error = [ 14.1867, 15.2240, 16.2812, 17.4204, 18.6297] +24-11-19 19:22:20 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 19:22:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:22:20 | D | sum error = [ 19.8905, 21.2692, 22.7061, 24.2038, 25.8053] +24-11-19 19:22:20 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 19:22:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:22:20 | D | sum error = [ 27.5119, 29.2928, 31.1963, 33.1689, 35.2814] +24-11-19 19:22:20 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 19:22:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:22:20 | D | sum error = [ 37.4936, 39.8292, 42.2755, 44.8392, 47.5285] +24-11-19 19:22:20 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 19:22:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:22:20 | D | sum error = [ 50.3625, 53.3174, 56.4173, 59.6706, 63.0949] +24-11-19 19:22:20 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 19:22:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:22:20 | D | sum error = [ 66.6624, 70.3791, 74.2845, 78.3585, 82.6270] +24-11-19 19:22:20 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 19:22:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:22:20 | D | sum error = [ 87.0643, 91.6964, 96.5657, 101.6269, 106.9146] +24-11-19 19:22:20 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 19:22:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:22:20 | D | sum error = [ 112.3938, 118.1169, 124.0662, 130.2588, 136.7104] +24-11-19 19:22:20 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 19:22:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:22:20 | D | sum error = [ 143.4156, 150.3911, 157.6542, 165.1635, 172.9627] +24-11-19 19:22:20 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 19:22:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:22:20 | D | sum error = [ 181.0315, 189.3610, 198.0042, 206.9254, 216.1643] +24-11-19 19:22:20 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 19:22:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:22:20 | D | sum error = [ 225.7201, 235.5754, 245.7698, 256.2763, 267.1197] +24-11-19 19:22:20 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 19:22:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:22:20 | D | sum error = [ 278.2843, 289.7905, 301.6306, 313.8285, 326.3605] +24-11-19 19:22:20 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 19:22:20 | D | + error = [4.8310] +24-11-19 19:22:20 | D | - Calibrating model.layers.17.self_attn.o_proj.weight +24-11-19 19:22:20 | D | + w: sint8 +24-11-19 19:22:20 | D | + x: None +24-11-19 19:22:20 | D | + y: None +24-11-19 19:22:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:22:20 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:22:20 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:22:20 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:22:20 | D | - range ratio = [ 1.0000] +24-11-19 19:22:20 | D | sum error = [ 1.3724] +24-11-19 19:22:20 | D | best error = [ 1.3724] +24-11-19 19:22:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:22:21 | D | sum error = [ 1.3637, 1.3561, 1.3555, 1.3638, 1.3789] +24-11-19 19:22:21 | D | best error = [ 1.2850, 1.2440, 1.2185, 1.2032, 1.1920] +24-11-19 19:22:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:22:21 | D | sum error = [ 1.3974, 1.4284, 1.4696, 1.5176, 1.5850] +24-11-19 19:22:21 | D | best error = [ 1.1841, 1.1787, 1.1742, 1.1710, 1.1690] +24-11-19 19:22:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:22:21 | D | sum error = [ 1.6487, 1.7344, 1.8275, 1.9288, 2.0450] +24-11-19 19:22:21 | D | best error = [ 1.1671, 1.1658, 1.1645, 1.1637, 1.1630] +24-11-19 19:22:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:22:21 | D | sum error = [ 2.1719, 2.3090, 2.4594, 2.6251, 2.8000] +24-11-19 19:22:21 | D | best error = [ 1.1623, 1.1617, 1.1614, 1.1609, 1.1607] +24-11-19 19:22:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:22:21 | D | sum error = [ 2.9862, 3.1916, 3.4061, 3.6355, 3.8810] +24-11-19 19:22:21 | D | best error = [ 1.1604, 1.1603, 1.1602, 1.1600, 1.1598] +24-11-19 19:22:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:22:21 | D | sum error = [ 4.1371, 4.4117, 4.7082, 5.0184, 5.3479] +24-11-19 19:22:21 | D | best error = [ 1.1598, 1.1597, 1.1597, 1.1597, 1.1597] +24-11-19 19:22:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:22:21 | D | sum error = [ 5.6967, 6.0641, 6.4543, 6.8671, 7.2983] +24-11-19 19:22:21 | D | best error = [ 1.1596, 1.1596, 1.1596, 1.1596, 1.1596] +24-11-19 19:22:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:22:21 | D | sum error = [ 7.7596, 8.2421, 8.7542, 9.2921, 9.8577] +24-11-19 19:22:21 | D | best error = [ 1.1596, 1.1596, 1.1596, 1.1596, 1.1596] +24-11-19 19:22:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:22:21 | D | sum error = [ 10.4538, 11.0854, 11.7456, 12.4369, 13.1697] +24-11-19 19:22:21 | D | best error = [ 1.1596, 1.1596, 1.1596, 1.1596, 1.1596] +24-11-19 19:22:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:22:21 | D | sum error = [ 13.9348, 14.7378, 15.5785, 16.4600, 17.3855] +24-11-19 19:22:21 | D | best error = [ 1.1596, 1.1596, 1.1596, 1.1596, 1.1596] +24-11-19 19:22:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:22:21 | D | sum error = [ 18.3547, 19.3739, 20.4392, 21.5540, 22.7162] +24-11-19 19:22:21 | D | best error = [ 1.1596, 1.1596, 1.1596, 1.1596, 1.1596] +24-11-19 19:22:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:22:21 | D | sum error = [ 23.9298, 25.1949, 26.5189, 27.8973, 29.3317] +24-11-19 19:22:21 | D | best error = [ 1.1596, 1.1596, 1.1596, 1.1596, 1.1596] +24-11-19 19:22:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:22:21 | D | sum error = [ 30.8274, 32.3854, 34.0095, 35.6993, 37.4577] +24-11-19 19:22:21 | D | best error = [ 1.1596, 1.1596, 1.1596, 1.1596, 1.1596] +24-11-19 19:22:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:22:21 | D | sum error = [ 39.2818, 41.1767, 43.1426, 45.1836, 47.2942] +24-11-19 19:22:21 | D | best error = [ 1.1596, 1.1596, 1.1596, 1.1596, 1.1596] +24-11-19 19:22:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:22:21 | D | sum error = [ 49.4815, 51.7440, 54.0847, 56.5104, 59.0221] +24-11-19 19:22:21 | D | best error = [ 1.1596, 1.1596, 1.1596, 1.1596, 1.1596] +24-11-19 19:22:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:22:21 | D | sum error = [ 61.6147, 64.2958, 67.0651, 69.9251, 72.8717] +24-11-19 19:22:21 | D | best error = [ 1.1596, 1.1596, 1.1596, 1.1596, 1.1596] +24-11-19 19:22:21 | D | + error = [1.1596] +24-11-19 19:22:21 | D | - Calibrating model.layers.17.mlp.up_proj.weight +24-11-19 19:22:21 | D | + w: sint8 +24-11-19 19:22:21 | D | + x: None +24-11-19 19:22:21 | D | + y: None +24-11-19 19:22:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:22:21 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:22:21 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:22:21 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:22:21 | D | - range ratio = [ 1.0000] +24-11-19 19:22:21 | D | sum error = [ 7.8792] +24-11-19 19:22:21 | D | best error = [ 7.8792] +24-11-19 19:22:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:22:22 | D | sum error = [ 7.8204, 7.8244, 7.8413, 7.9091, 8.0732] +24-11-19 19:22:22 | D | best error = [ 7.3240, 7.1112, 6.9978, 6.9308, 6.8960] +24-11-19 19:22:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:22:22 | D | sum error = [ 8.2724, 8.5573, 8.8967, 9.3022, 9.8442] +24-11-19 19:22:22 | D | best error = [ 6.8794, 6.8724, 6.8699, 6.8694, 6.8692] +24-11-19 19:22:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:22:22 | D | sum error = [ 10.3901, 11.0339, 11.7503, 12.5607, 13.4180] +24-11-19 19:22:22 | D | best error = [ 6.8692, 6.8692, 6.8692, 6.8692, 6.8692] +24-11-19 19:22:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:22:22 | D | sum error = [ 14.3963, 15.4033, 16.5071, 17.7058, 18.9548] +24-11-19 19:22:22 | D | best error = [ 6.8692, 6.8692, 6.8692, 6.8692, 6.8692] +24-11-19 19:22:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:22:22 | D | sum error = [ 20.3269, 21.7517, 23.3202, 24.9172, 26.6674] +24-11-19 19:22:22 | D | best error = [ 6.8692, 6.8692, 6.8692, 6.8692, 6.8692] +24-11-19 19:22:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:22:22 | D | sum error = [ 28.5001, 30.4395, 32.4943, 34.6781, 36.9683] +24-11-19 19:22:22 | D | best error = [ 6.8692, 6.8692, 6.8692, 6.8692, 6.8692] +24-11-19 19:22:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:22:22 | D | sum error = [ 39.3953, 41.9775, 44.6610, 47.5099, 50.5241] +24-11-19 19:22:22 | D | best error = [ 6.8692, 6.8692, 6.8692, 6.8692, 6.8692] +24-11-19 19:22:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:22:22 | D | sum error = [ 53.6969, 57.0253, 60.5333, 64.2122, 68.0844] +24-11-19 19:22:22 | D | best error = [ 6.8692, 6.8692, 6.8692, 6.8692, 6.8692] +24-11-19 19:22:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:22:22 | D | sum error = [ 72.1470, 76.4347, 80.9172, 85.6103, 90.5054] +24-11-19 19:22:22 | D | best error = [ 6.8692, 6.8692, 6.8692, 6.8692, 6.8692] +24-11-19 19:22:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:22:22 | D | sum error = [ 95.6866, 101.0863, 106.7306, 112.6275, 118.8088] +24-11-19 19:22:22 | D | best error = [ 6.8692, 6.8692, 6.8692, 6.8692, 6.8692] +24-11-19 19:22:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:22:22 | D | sum error = [ 125.2808, 132.0202, 139.0498, 146.4074, 154.0905] +24-11-19 19:22:22 | D | best error = [ 6.8692, 6.8692, 6.8692, 6.8692, 6.8692] +24-11-19 19:22:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:22:22 | D | sum error = [ 162.1188, 170.4571, 179.1316, 188.1952, 197.6255] +24-11-19 19:22:22 | D | best error = [ 6.8692, 6.8692, 6.8692, 6.8692, 6.8692] +24-11-19 19:22:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:22:22 | D | sum error = [ 207.4280, 217.6200, 228.2175, 239.2189, 250.6406] +24-11-19 19:22:22 | D | best error = [ 6.8692, 6.8692, 6.8692, 6.8692, 6.8692] +24-11-19 19:22:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:22:22 | D | sum error = [ 262.4982, 274.7887, 287.5391, 300.7585, 314.4253] +24-11-19 19:22:22 | D | best error = [ 6.8692, 6.8692, 6.8692, 6.8692, 6.8692] +24-11-19 19:22:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:22:22 | D | sum error = [ 328.5869, 343.2083, 358.3038, 373.8943, 390.0030] +24-11-19 19:22:22 | D | best error = [ 6.8692, 6.8692, 6.8692, 6.8692, 6.8692] +24-11-19 19:22:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:22:22 | D | sum error = [ 406.6084, 423.7443, 441.3875, 459.5421, 478.2119] +24-11-19 19:22:22 | D | best error = [ 6.8692, 6.8692, 6.8692, 6.8692, 6.8692] +24-11-19 19:22:22 | D | + error = [6.8692] +24-11-19 19:22:22 | D | - Calibrating model.layers.17.mlp.gate_proj.weight +24-11-19 19:22:22 | D | + w: sint8 +24-11-19 19:22:22 | D | + x: None +24-11-19 19:22:22 | D | + y: None +24-11-19 19:22:22 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:22:22 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:22:22 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:22:22 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:22:22 | D | - range ratio = [ 1.0000] +24-11-19 19:22:22 | D | sum error = [ 8.2309] +24-11-19 19:22:22 | D | best error = [ 8.2309] +24-11-19 19:22:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:22:23 | D | sum error = [ 8.1931, 8.1539, 8.1855, 8.2715, 8.4386] +24-11-19 19:22:23 | D | best error = [ 7.6670, 7.4396, 7.3179, 7.2483, 7.2124] +24-11-19 19:22:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:22:23 | D | sum error = [ 8.6627, 8.9529, 9.3201, 9.7596, 10.2715] +24-11-19 19:22:23 | D | best error = [ 7.1939, 7.1857, 7.1831, 7.1821, 7.1817] +24-11-19 19:22:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:22:23 | D | sum error = [ 10.8832, 11.5593, 12.3071, 13.1651, 14.0811] +24-11-19 19:22:23 | D | best error = [ 7.1817, 7.1817, 7.1817, 7.1817, 7.1817] +24-11-19 19:22:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:22:23 | D | sum error = [ 15.0923, 16.1779, 17.3448, 18.5938, 19.9581] +24-11-19 19:22:23 | D | best error = [ 7.1817, 7.1817, 7.1817, 7.1817, 7.1817] +24-11-19 19:22:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:22:23 | D | sum error = [ 21.4028, 22.9662, 24.5872, 26.3680, 28.2497] +24-11-19 19:22:23 | D | best error = [ 7.1817, 7.1817, 7.1817, 7.1817, 7.1817] +24-11-19 19:22:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:22:23 | D | sum error = [ 30.2577, 32.3700, 34.6300, 37.0340, 39.5556] +24-11-19 19:22:23 | D | best error = [ 7.1817, 7.1817, 7.1817, 7.1817, 7.1817] +24-11-19 19:22:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:22:23 | D | sum error = [ 42.2407, 45.0809, 48.0887, 51.2753, 54.6922] +24-11-19 19:22:23 | D | best error = [ 7.1817, 7.1817, 7.1817, 7.1817, 7.1817] +24-11-19 19:22:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:22:23 | D | sum error = [ 58.2394, 62.0141, 66.0088, 70.2172, 74.6781] +24-11-19 19:22:23 | D | best error = [ 7.1817, 7.1817, 7.1817, 7.1817, 7.1817] +24-11-19 19:22:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:22:23 | D | sum error = [ 79.3875, 84.3523, 89.5686, 95.1276, 100.9762] +24-11-19 19:22:23 | D | best error = [ 7.1817, 7.1817, 7.1817, 7.1817, 7.1817] +24-11-19 19:22:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:22:23 | D | sum error = [ 107.1442, 113.6643, 120.5260, 127.7810, 135.4131] +24-11-19 19:22:23 | D | best error = [ 7.1817, 7.1817, 7.1817, 7.1817, 7.1817] +24-11-19 19:22:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:22:23 | D | sum error = [ 143.4824, 151.9876, 160.9219, 170.3158, 180.1716] +24-11-19 19:22:23 | D | best error = [ 7.1817, 7.1817, 7.1817, 7.1817, 7.1817] +24-11-19 19:22:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:22:23 | D | sum error = [ 190.5757, 201.4941, 212.9546, 224.9961, 237.5958] +24-11-19 19:22:23 | D | best error = [ 7.1817, 7.1817, 7.1817, 7.1817, 7.1817] +24-11-19 19:22:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:22:23 | D | sum error = [ 250.7861, 264.6225, 279.1227, 294.2578, 310.0626] +24-11-19 19:22:23 | D | best error = [ 7.1817, 7.1817, 7.1817, 7.1817, 7.1817] +24-11-19 19:22:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:22:23 | D | sum error = [ 326.5871, 343.8045, 361.7617, 380.4359, 399.8702] +24-11-19 19:22:23 | D | best error = [ 7.1817, 7.1817, 7.1817, 7.1817, 7.1817] +24-11-19 19:22:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:22:23 | D | sum error = [ 420.0779, 441.0649, 462.8473, 485.4126, 508.7812] +24-11-19 19:22:23 | D | best error = [ 7.1817, 7.1817, 7.1817, 7.1817, 7.1817] +24-11-19 19:22:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:22:23 | D | sum error = [ 532.9567, 557.9723, 583.7675, 610.3587, 637.7722] +24-11-19 19:22:23 | D | best error = [ 7.1817, 7.1817, 7.1817, 7.1817, 7.1817] +24-11-19 19:22:23 | D | + error = [7.1817] +24-11-19 19:22:23 | D | - Calibrating model.layers.17.mlp.down_proj.weight +24-11-19 19:22:23 | D | + w: sint8 +24-11-19 19:22:23 | D | + x: None +24-11-19 19:22:23 | D | + y: None +24-11-19 19:22:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:22:23 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:22:23 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:22:23 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:22:23 | D | - range ratio = [ 1.0000] +24-11-19 19:22:23 | D | sum error = [ 2.6173] +24-11-19 19:22:23 | D | best error = [ 2.6173] +24-11-19 19:22:24 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:22:24 | D | sum error = [ 2.5872, 2.5730, 2.5640, 2.5516, 2.5508] +24-11-19 19:22:24 | D | best error = [ 2.5151, 2.4675, 2.4349, 2.4084, 2.3880] +24-11-19 19:22:24 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:22:24 | D | sum error = [ 2.5639, 2.5828, 2.6088, 2.6592, 2.7126] +24-11-19 19:22:24 | D | best error = [ 2.3736, 2.3634, 2.3549, 2.3494, 2.3452] +24-11-19 19:22:24 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:22:24 | D | sum error = [ 2.7867, 2.8663, 2.9667, 3.0962, 3.2344] +24-11-19 19:22:24 | D | best error = [ 2.3426, 2.3409, 2.3397, 2.3390, 2.3385] +24-11-19 19:22:24 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:22:24 | D | sum error = [ 3.3907, 3.5706, 3.7744, 3.9968, 4.2453] +24-11-19 19:22:24 | D | best error = [ 2.3381, 2.3379, 2.3378, 2.3377, 2.3376] +24-11-19 19:22:24 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:22:24 | D | sum error = [ 4.5161, 4.8051, 5.1278, 5.4675, 5.8450] +24-11-19 19:22:24 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 19:22:24 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:22:24 | D | sum error = [ 6.2423, 6.6705, 7.1342, 7.6250, 8.1523] +24-11-19 19:22:24 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 19:22:24 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:22:24 | D | sum error = [ 8.7131, 9.3135, 9.9485, 10.6257, 11.3436] +24-11-19 19:22:24 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 19:22:24 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:22:24 | D | sum error = [ 12.1074, 12.9193, 13.7812, 14.6848, 15.6475] +24-11-19 19:22:24 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 19:22:24 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:22:24 | D | sum error = [ 16.6659, 17.7406, 18.8726, 20.0747, 21.3383] +24-11-19 19:22:24 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 19:22:24 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:22:24 | D | sum error = [ 22.6733, 24.0716, 25.5465, 27.0987, 28.7264] +24-11-19 19:22:24 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 19:22:24 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:22:24 | D | sum error = [ 30.4394, 32.2398, 34.1254, 36.1090, 38.1843] +24-11-19 19:22:24 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 19:22:24 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:22:24 | D | sum error = [ 40.3615, 42.6400, 45.0308, 47.5259, 50.1375] +24-11-19 19:22:24 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 19:22:24 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:22:24 | D | sum error = [ 52.8705, 55.7167, 58.6942, 61.7952, 65.0318] +24-11-19 19:22:24 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 19:22:24 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:22:24 | D | sum error = [ 68.3993, 71.9103, 75.5622, 79.3686, 83.3069] +24-11-19 19:22:24 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 19:22:24 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:22:24 | D | sum error = [ 87.4033, 91.6552, 96.0653, 100.6361, 105.3706] +24-11-19 19:22:24 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 19:22:24 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:22:24 | D | sum error = [ 110.2744, 115.3464, 120.5914, 126.0173, 131.6225] +24-11-19 19:22:24 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 19:22:24 | D | + error = [2.3376] +24-11-19 19:22:24 | D | - Quantizing model.layers.17.self_attn.q_proj.weight +24-11-19 19:22:25 | D | - Quantizing model.layers.17.self_attn.k_proj.weight +24-11-19 19:22:26 | D | - Quantizing model.layers.17.self_attn.v_proj.weight +24-11-19 19:22:27 | D | - Quantizing model.layers.17.self_attn.o_proj.weight +24-11-19 19:22:28 | D | - Quantizing model.layers.17.mlp.up_proj.weight +24-11-19 19:22:29 | D | - Quantizing model.layers.17.mlp.gate_proj.weight +24-11-19 19:22:30 | D | - Quantizing model.layers.17.mlp.down_proj.weight +24-11-19 19:22:39 | D | - Quantizing layer model.layers.18 +24-11-19 19:22:39 | D | - Calibrating model.layers.18.self_attn.q_proj.weight +24-11-19 19:22:39 | D | + w: sint8 +24-11-19 19:22:39 | D | + x: None +24-11-19 19:22:39 | D | + y: None +24-11-19 19:22:39 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:22:39 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:22:39 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:22:39 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:22:39 | D | - range ratio = [ 1.0000] +24-11-19 19:22:39 | D | sum error = [ 12.1743] +24-11-19 19:22:39 | D | best error = [ 12.1743] +24-11-19 19:22:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:22:52 | D | sum error = [ 12.0100, 12.1289, 12.2449, 12.2380, 12.5672] +24-11-19 19:22:52 | D | best error = [ 12.0100, 12.0100, 12.0100, 12.0100, 12.0100] +24-11-19 19:22:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:22:52 | D | sum error = [ 13.0011, 13.4546, 14.2459, 15.1128, 15.8509] +24-11-19 19:22:52 | D | best error = [ 12.0100, 12.0100, 12.0100, 12.0100, 12.0100] +24-11-19 19:22:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:22:52 | D | sum error = [ 16.6735, 17.9322, 19.1621, 20.3150, 21.9907] +24-11-19 19:22:52 | D | best error = [ 12.0100, 12.0100, 12.0100, 12.0100, 12.0100] +24-11-19 19:22:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:22:52 | D | sum error = [ 23.4268, 25.3891, 27.3111, 29.2230, 32.0182] +24-11-19 19:22:52 | D | best error = [ 12.0100, 12.0100, 12.0100, 12.0100, 12.0100] +24-11-19 19:22:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:22:52 | D | sum error = [ 34.3329, 37.4693, 40.5476, 43.8460, 47.3474] +24-11-19 19:22:52 | D | best error = [ 12.0100, 12.0100, 12.0100, 12.0100, 12.0100] +24-11-19 19:22:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:22:52 | D | sum error = [ 51.1154, 55.5476, 59.7801, 64.5310, 69.3694] +24-11-19 19:22:52 | D | best error = [ 12.0100, 12.0100, 12.0100, 12.0100, 12.0100] +24-11-19 19:22:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:22:52 | D | sum error = [ 74.6449, 80.9816, 87.0855, 93.6648, 100.9339] +24-11-19 19:22:52 | D | best error = [ 12.0100, 12.0100, 12.0100, 12.0100, 12.0100] +24-11-19 19:22:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:22:52 | D | sum error = [ 109.2228, 117.5544, 127.2670, 136.8788, 147.4322] +24-11-19 19:22:52 | D | best error = [ 12.0100, 12.0100, 12.0100, 12.0100, 12.0100] +24-11-19 19:22:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:22:52 | D | sum error = [ 159.1908, 171.6280, 184.7239, 198.5852, 213.9410] +24-11-19 19:22:52 | D | best error = [ 12.0100, 12.0100, 12.0100, 12.0100, 12.0100] +24-11-19 19:22:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:22:52 | D | sum error = [ 230.4036, 247.9022, 267.0165, 287.0660, 308.6418] +24-11-19 19:22:52 | D | best error = [ 12.0100, 12.0100, 12.0100, 12.0100, 12.0100] +24-11-19 19:22:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:22:52 | D | sum error = [ 331.7906, 356.9456, 384.4459, 413.4180, 444.7563] +24-11-19 19:22:52 | D | best error = [ 12.0100, 12.0100, 12.0100, 12.0100, 12.0100] +24-11-19 19:22:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:22:52 | D | sum error = [ 479.3891, 516.0664, 556.3624, 599.8124, 646.8815] +24-11-19 19:22:52 | D | best error = [ 12.0100, 12.0100, 12.0100, 12.0100, 12.0100] +24-11-19 19:22:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:22:52 | D | sum error = [ 698.5263, 755.2687, 817.0830, 884.6358, 959.0237] +24-11-19 19:22:52 | D | best error = [ 12.0100, 12.0100, 12.0100, 12.0100, 12.0100] +24-11-19 19:22:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:22:52 | D | sum error = [ 1041.0667, 1130.2119, 1227.5748, 1334.4463, 1452.5059] +24-11-19 19:22:52 | D | best error = [ 12.0100, 12.0100, 12.0100, 12.0100, 12.0100] +24-11-19 19:22:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:22:52 | D | sum error = [ 1582.3280, 1724.2446, 1881.4296, 2052.5688, 2241.3245] +24-11-19 19:22:52 | D | best error = [ 12.0100, 12.0100, 12.0100, 12.0100, 12.0100] +24-11-19 19:22:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:22:52 | D | sum error = [ 2448.2304, 2672.7544, 2916.3182, 3176.7057, 3454.8598] +24-11-19 19:22:52 | D | best error = [ 12.0100, 12.0100, 12.0100, 12.0100, 12.0100] +24-11-19 19:22:52 | D | + error = [12.0100] +24-11-19 19:22:52 | D | - Calibrating model.layers.18.self_attn.k_proj.weight +24-11-19 19:22:52 | D | + w: sint8 +24-11-19 19:22:52 | D | + x: None +24-11-19 19:22:52 | D | + y: None +24-11-19 19:22:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:22:52 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:22:52 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:22:52 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:22:52 | D | - range ratio = [ 1.0000] +24-11-19 19:22:52 | D | sum error = [ 13.3908] +24-11-19 19:22:52 | D | best error = [ 13.3908] +24-11-19 19:23:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:23:05 | D | sum error = [ 13.1663, 12.7001, 14.1396, 13.5041, 13.4940] +24-11-19 19:23:05 | D | best error = [ 13.1663, 12.7001, 12.7001, 12.7001, 12.7001] +24-11-19 19:23:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:23:05 | D | sum error = [ 14.0597, 13.5364, 15.8240, 15.3715, 16.4311] +24-11-19 19:23:05 | D | best error = [ 12.7001, 12.7001, 12.7001, 12.7001, 12.7001] +24-11-19 19:23:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:23:05 | D | sum error = [ 17.1081, 18.6776, 20.0540, 20.6684, 22.5762] +24-11-19 19:23:05 | D | best error = [ 12.7001, 12.7001, 12.7001, 12.7001, 12.7001] +24-11-19 19:23:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:23:05 | D | sum error = [ 24.1206, 25.9813, 28.3979, 30.9946, 32.9024] +24-11-19 19:23:05 | D | best error = [ 12.7001, 12.7001, 12.7001, 12.7001, 12.7001] +24-11-19 19:23:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:23:05 | D | sum error = [ 36.6135, 39.3123, 42.2370, 45.9915, 49.5656] +24-11-19 19:23:05 | D | best error = [ 12.7001, 12.7001, 12.7001, 12.7001, 12.7001] +24-11-19 19:23:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:23:05 | D | sum error = [ 54.0314, 57.7303, 60.9634, 65.1903, 70.8019] +24-11-19 19:23:05 | D | best error = [ 12.7001, 12.7001, 12.7001, 12.7001, 12.7001] +24-11-19 19:23:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:23:05 | D | sum error = [ 74.0506, 80.9654, 87.3020, 93.5873, 99.4956] +24-11-19 19:23:05 | D | best error = [ 12.7001, 12.7001, 12.7001, 12.7001, 12.7001] +24-11-19 19:23:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:23:05 | D | sum error = [ 106.2213, 114.3450, 123.1978, 131.3438, 141.1077] +24-11-19 19:23:05 | D | best error = [ 12.7001, 12.7001, 12.7001, 12.7001, 12.7001] +24-11-19 19:23:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:23:05 | D | sum error = [ 153.2922, 163.2538, 175.5105, 188.4264, 204.1975] +24-11-19 19:23:05 | D | best error = [ 12.7001, 12.7001, 12.7001, 12.7001, 12.7001] +24-11-19 19:23:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:23:05 | D | sum error = [ 221.2961, 237.8559, 257.3029, 279.0980, 302.7894] +24-11-19 19:23:05 | D | best error = [ 12.7001, 12.7001, 12.7001, 12.7001, 12.7001] +24-11-19 19:23:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:23:05 | D | sum error = [ 325.8980, 353.5526, 383.3060, 410.8838, 444.7841] +24-11-19 19:23:05 | D | best error = [ 12.7001, 12.7001, 12.7001, 12.7001, 12.7001] +24-11-19 19:23:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:23:05 | D | sum error = [ 480.2293, 518.6247, 561.9329, 602.8532, 648.3187] +24-11-19 19:23:05 | D | best error = [ 12.7001, 12.7001, 12.7001, 12.7001, 12.7001] +24-11-19 19:23:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:23:05 | D | sum error = [ 702.7124, 762.9623, 823.9624, 889.0828, 964.2877] +24-11-19 19:23:05 | D | best error = [ 12.7001, 12.7001, 12.7001, 12.7001, 12.7001] +24-11-19 19:23:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:23:05 | D | sum error = [ 1048.3309, 1135.5019, 1230.7912, 1349.0270, 1460.7979] +24-11-19 19:23:05 | D | best error = [ 12.7001, 12.7001, 12.7001, 12.7001, 12.7001] +24-11-19 19:23:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:23:05 | D | sum error = [ 1592.4735, 1726.8214, 1910.2656, 2076.0177, 2261.0418] +24-11-19 19:23:05 | D | best error = [ 12.7001, 12.7001, 12.7001, 12.7001, 12.7001] +24-11-19 19:23:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:23:05 | D | sum error = [ 2455.2566, 2717.2490, 2952.4742, 3203.6554, 3511.7303] +24-11-19 19:23:05 | D | best error = [ 12.7001, 12.7001, 12.7001, 12.7001, 12.7001] +24-11-19 19:23:05 | D | + error = [12.7001] +24-11-19 19:23:05 | D | - Calibrating model.layers.18.self_attn.v_proj.weight +24-11-19 19:23:05 | D | + w: sint8 +24-11-19 19:23:05 | D | + x: None +24-11-19 19:23:05 | D | + y: None +24-11-19 19:23:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:23:05 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:23:05 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:23:05 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:23:05 | D | - range ratio = [ 1.0000] +24-11-19 19:23:05 | D | sum error = [ 6.0867] +24-11-19 19:23:05 | D | best error = [ 6.0867] +24-11-19 19:23:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:23:06 | D | sum error = [ 6.0342, 6.0291, 6.0671, 6.1266, 6.2388] +24-11-19 19:23:06 | D | best error = [ 5.6819, 5.5204, 5.4350, 5.3882, 5.3642] +24-11-19 19:23:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:23:06 | D | sum error = [ 6.3998, 6.6332, 6.8719, 7.2202, 7.6201] +24-11-19 19:23:06 | D | best error = [ 5.3497, 5.3445, 5.3424, 5.3419, 5.3419] +24-11-19 19:23:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:23:06 | D | sum error = [ 8.0339, 8.5457, 9.1216, 9.7222, 10.4060] +24-11-19 19:23:06 | D | best error = [ 5.3419, 5.3419, 5.3419, 5.3419, 5.3419] +24-11-19 19:23:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:23:06 | D | sum error = [ 11.1615, 11.9250, 12.7928, 13.7020, 14.6907] +24-11-19 19:23:06 | D | best error = [ 5.3419, 5.3419, 5.3419, 5.3419, 5.3419] +24-11-19 19:23:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:23:06 | D | sum error = [ 15.7476, 16.8738, 18.0187, 19.2812, 20.6479] +24-11-19 19:23:06 | D | best error = [ 5.3419, 5.3419, 5.3419, 5.3419, 5.3419] +24-11-19 19:23:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:23:06 | D | sum error = [ 22.0405, 23.5533, 25.1447, 26.7867, 28.5424] +24-11-19 19:23:06 | D | best error = [ 5.3419, 5.3419, 5.3419, 5.3419, 5.3419] +24-11-19 19:23:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:23:06 | D | sum error = [ 30.4294, 32.3934, 34.4410, 36.6372, 38.9144] +24-11-19 19:23:06 | D | best error = [ 5.3419, 5.3419, 5.3419, 5.3419, 5.3419] +24-11-19 19:23:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:23:06 | D | sum error = [ 41.3304, 43.8759, 46.5509, 49.3768, 52.3312] +24-11-19 19:23:06 | D | best error = [ 5.3419, 5.3419, 5.3419, 5.3419, 5.3419] +24-11-19 19:23:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:23:06 | D | sum error = [ 55.4412, 58.6856, 62.0822, 65.6546, 69.3930] +24-11-19 19:23:06 | D | best error = [ 5.3419, 5.3419, 5.3419, 5.3419, 5.3419] +24-11-19 19:23:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:23:06 | D | sum error = [ 73.3313, 77.4608, 81.7668, 86.2467, 90.9616] +24-11-19 19:23:06 | D | best error = [ 5.3419, 5.3419, 5.3419, 5.3419, 5.3419] +24-11-19 19:23:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:23:06 | D | sum error = [ 95.8785, 100.9991, 106.3720, 111.9522, 117.7612] +24-11-19 19:23:06 | D | best error = [ 5.3419, 5.3419, 5.3419, 5.3419, 5.3419] +24-11-19 19:23:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:23:06 | D | sum error = [ 123.8242, 130.1271, 136.6961, 143.5240, 150.6373] +24-11-19 19:23:06 | D | best error = [ 5.3419, 5.3419, 5.3419, 5.3419, 5.3419] +24-11-19 19:23:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:23:06 | D | sum error = [ 158.0033, 165.6429, 173.5732, 181.8314, 190.3735] +24-11-19 19:23:06 | D | best error = [ 5.3419, 5.3419, 5.3419, 5.3419, 5.3419] +24-11-19 19:23:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:23:06 | D | sum error = [ 199.2454, 208.4084, 217.8931, 227.7171, 237.8589] +24-11-19 19:23:06 | D | best error = [ 5.3419, 5.3419, 5.3419, 5.3419, 5.3419] +24-11-19 19:23:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:23:06 | D | sum error = [ 248.3500, 259.1779, 270.3617, 281.8989, 293.8026] +24-11-19 19:23:06 | D | best error = [ 5.3419, 5.3419, 5.3419, 5.3419, 5.3419] +24-11-19 19:23:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:23:06 | D | sum error = [ 306.0665, 318.6899, 331.6936, 345.0607, 358.8049] +24-11-19 19:23:06 | D | best error = [ 5.3419, 5.3419, 5.3419, 5.3419, 5.3419] +24-11-19 19:23:06 | D | + error = [5.3419] +24-11-19 19:23:06 | D | - Calibrating model.layers.18.self_attn.o_proj.weight +24-11-19 19:23:06 | D | + w: sint8 +24-11-19 19:23:06 | D | + x: None +24-11-19 19:23:06 | D | + y: None +24-11-19 19:23:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:23:06 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:23:06 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:23:06 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:23:06 | D | - range ratio = [ 1.0000] +24-11-19 19:23:06 | D | sum error = [ 1.5069] +24-11-19 19:23:06 | D | best error = [ 1.5069] +24-11-19 19:23:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:23:06 | D | sum error = [ 1.4956, 1.4868, 1.4836, 1.4937, 1.5133] +24-11-19 19:23:06 | D | best error = [ 1.4179, 1.3751, 1.3492, 1.3327, 1.3218] +24-11-19 19:23:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:23:06 | D | sum error = [ 1.5353, 1.5719, 1.6157, 1.6717, 1.7380] +24-11-19 19:23:06 | D | best error = [ 1.3149, 1.3094, 1.3060, 1.3035, 1.3018] +24-11-19 19:23:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:23:06 | D | sum error = [ 1.8183, 1.9073, 2.0060, 2.1270, 2.2480] +24-11-19 19:23:06 | D | best error = [ 1.3005, 1.2996, 1.2987, 1.2981, 1.2976] +24-11-19 19:23:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:23:06 | D | sum error = [ 2.3891, 2.5437, 2.7093, 2.8909, 3.0871] +24-11-19 19:23:06 | D | best error = [ 1.2975, 1.2973, 1.2971, 1.2970, 1.2969] +24-11-19 19:23:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:23:06 | D | sum error = [ 3.2969, 3.5153, 3.7557, 4.0129, 4.2864] +24-11-19 19:23:06 | D | best error = [ 1.2968, 1.2968, 1.2968, 1.2967, 1.2967] +24-11-19 19:23:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:23:06 | D | sum error = [ 4.5715, 4.8776, 5.2072, 5.5479, 5.9180] +24-11-19 19:23:06 | D | best error = [ 1.2967, 1.2967, 1.2967, 1.2967, 1.2967] +24-11-19 19:23:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:23:06 | D | sum error = [ 6.3043, 6.7169, 7.1472, 7.6031, 8.0885] +24-11-19 19:23:06 | D | best error = [ 1.2967, 1.2967, 1.2967, 1.2966, 1.2966] +24-11-19 19:23:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:23:06 | D | sum error = [ 8.5999, 9.1403, 9.7037, 10.3006, 10.9349] +24-11-19 19:23:06 | D | best error = [ 1.2966, 1.2966, 1.2966, 1.2966, 1.2966] +24-11-19 19:23:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:23:06 | D | sum error = [ 11.5938, 12.2956, 13.0298, 13.7978, 14.6106] +24-11-19 19:23:06 | D | best error = [ 1.2966, 1.2966, 1.2966, 1.2966, 1.2966] +24-11-19 19:23:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:23:06 | D | sum error = [ 15.4609, 16.3547, 17.2927, 18.2760, 19.3091] +24-11-19 19:23:06 | D | best error = [ 1.2966, 1.2966, 1.2966, 1.2966, 1.2966] +24-11-19 19:23:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:23:06 | D | sum error = [ 20.3878, 21.5195, 22.7065, 23.9485, 25.2493] +24-11-19 19:23:06 | D | best error = [ 1.2966, 1.2966, 1.2966, 1.2966, 1.2966] +24-11-19 19:23:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:23:06 | D | sum error = [ 26.6055, 28.0233, 29.5056, 31.0531, 32.6705] +24-11-19 19:23:06 | D | best error = [ 1.2966, 1.2966, 1.2966, 1.2966, 1.2966] +24-11-19 19:23:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:23:06 | D | sum error = [ 34.3517, 36.1050, 37.9329, 39.8349, 41.8121] +24-11-19 19:23:06 | D | best error = [ 1.2966, 1.2966, 1.2966, 1.2966, 1.2966] +24-11-19 19:23:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:23:06 | D | sum error = [ 43.8702, 46.0060, 48.2279, 50.5366, 52.9284] +24-11-19 19:23:06 | D | best error = [ 1.2966, 1.2966, 1.2966, 1.2966, 1.2966] +24-11-19 19:23:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:23:06 | D | sum error = [ 55.4135, 57.9842, 60.6464, 63.4019, 66.2515] +24-11-19 19:23:06 | D | best error = [ 1.2966, 1.2966, 1.2966, 1.2966, 1.2966] +24-11-19 19:23:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:23:06 | D | sum error = [ 69.1970, 72.2388, 75.3831, 78.6303, 81.9788] +24-11-19 19:23:06 | D | best error = [ 1.2966, 1.2966, 1.2966, 1.2966, 1.2966] +24-11-19 19:23:06 | D | + error = [1.2966] +24-11-19 19:23:07 | D | - Calibrating model.layers.18.mlp.up_proj.weight +24-11-19 19:23:07 | D | + w: sint8 +24-11-19 19:23:07 | D | + x: None +24-11-19 19:23:07 | D | + y: None +24-11-19 19:23:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:23:07 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:23:07 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:23:07 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:23:07 | D | - range ratio = [ 1.0000] +24-11-19 19:23:07 | D | sum error = [ 8.2844] +24-11-19 19:23:07 | D | best error = [ 8.2844] +24-11-19 19:23:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:23:08 | D | sum error = [ 8.2268, 8.1978, 8.2436, 8.3212, 8.4733] +24-11-19 19:23:08 | D | best error = [ 7.7102, 7.4805, 7.3631, 7.2950, 7.2569] +24-11-19 19:23:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:23:08 | D | sum error = [ 8.6931, 8.9807, 9.3398, 9.7964, 10.2957] +24-11-19 19:23:08 | D | best error = [ 7.2390, 7.2305, 7.2280, 7.2268, 7.2266] +24-11-19 19:23:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:23:08 | D | sum error = [ 10.8955, 11.5481, 12.3121, 13.1349, 14.0382] +24-11-19 19:23:08 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 19:23:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:23:08 | D | sum error = [ 15.0210, 16.0826, 17.2448, 18.4578, 19.8004] +24-11-19 19:23:08 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 19:23:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:23:08 | D | sum error = [ 21.1857, 22.7120, 24.2950, 25.9931, 27.8195] +24-11-19 19:23:08 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 19:23:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:23:08 | D | sum error = [ 29.7324, 31.7576, 33.9132, 36.1796, 38.5928] +24-11-19 19:23:08 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 19:23:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:23:08 | D | sum error = [ 41.1137, 43.7736, 46.6002, 49.5580, 52.6961] +24-11-19 19:23:08 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 19:23:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:23:08 | D | sum error = [ 55.9811, 59.4739, 63.1151, 66.9603, 70.9934] +24-11-19 19:23:08 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 19:23:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:23:08 | D | sum error = [ 75.2213, 79.6633, 84.3149, 89.2122, 94.3414] +24-11-19 19:23:08 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 19:23:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:23:08 | D | sum error = [ 99.7014, 105.3108, 111.1993, 117.3500, 123.7899] +24-11-19 19:23:08 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 19:23:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:23:08 | D | sum error = [ 130.4968, 137.5313, 144.8588, 152.5443, 160.5276] +24-11-19 19:23:08 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 19:23:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:23:08 | D | sum error = [ 168.8732, 177.5590, 186.6137, 196.0293, 205.8112] +24-11-19 19:23:08 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 19:23:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:23:08 | D | sum error = [ 215.9813, 226.5496, 237.5230, 248.9141, 260.7208] +24-11-19 19:23:08 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 19:23:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:23:08 | D | sum error = [ 272.9735, 285.6839, 298.8581, 312.4891, 326.6155] +24-11-19 19:23:08 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 19:23:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:23:08 | D | sum error = [ 341.2050, 356.3040, 371.8967, 387.9993, 404.5966] +24-11-19 19:23:08 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 19:23:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:23:08 | D | sum error = [ 421.7225, 439.3668, 457.5286, 476.2249, 495.4507] +24-11-19 19:23:08 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 19:23:08 | D | + error = [7.2266] +24-11-19 19:23:08 | D | - Calibrating model.layers.18.mlp.gate_proj.weight +24-11-19 19:23:08 | D | + w: sint8 +24-11-19 19:23:08 | D | + x: None +24-11-19 19:23:08 | D | + y: None +24-11-19 19:23:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:23:08 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:23:08 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:23:08 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:23:08 | D | - range ratio = [ 1.0000] +24-11-19 19:23:08 | D | sum error = [ 8.7728] +24-11-19 19:23:08 | D | best error = [ 8.7728] +24-11-19 19:23:09 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:23:09 | D | sum error = [ 8.7093, 8.6804, 8.7035, 8.7890, 8.9786] +24-11-19 19:23:09 | D | best error = [ 8.1662, 7.9337, 7.8041, 7.7282, 7.6878] +24-11-19 19:23:09 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:23:09 | D | sum error = [ 9.2124, 9.5062, 9.9066, 10.3619, 10.9344] +24-11-19 19:23:09 | D | best error = [ 7.6678, 7.6594, 7.6565, 7.6558, 7.6555] +24-11-19 19:23:09 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:23:09 | D | sum error = [ 11.5677, 12.2642, 13.0969, 13.9571, 14.9445] +24-11-19 19:23:09 | D | best error = [ 7.6555, 7.6555, 7.6555, 7.6555, 7.6555] +24-11-19 19:23:09 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:23:09 | D | sum error = [ 16.0160, 17.1806, 18.4263, 19.7759, 21.2079] +24-11-19 19:23:09 | D | best error = [ 7.6555, 7.6555, 7.6555, 7.6555, 7.6555] +24-11-19 19:23:09 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:23:09 | D | sum error = [ 22.7694, 24.4246, 26.1833, 28.0645, 30.0141] +24-11-19 19:23:09 | D | best error = [ 7.6555, 7.6555, 7.6555, 7.6555, 7.6555] +24-11-19 19:23:09 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:23:09 | D | sum error = [ 32.1363, 34.3566, 36.7497, 39.2941, 41.9488] +24-11-19 19:23:09 | D | best error = [ 7.6555, 7.6555, 7.6555, 7.6555, 7.6555] +24-11-19 19:23:09 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:23:09 | D | sum error = [ 44.7796, 47.7662, 50.9394, 54.3022, 57.8541] +24-11-19 19:23:09 | D | best error = [ 7.6555, 7.6555, 7.6555, 7.6555, 7.6555] +24-11-19 19:23:09 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:23:09 | D | sum error = [ 61.6113, 65.5902, 69.7967, 74.2525, 78.9408] +24-11-19 19:23:09 | D | best error = [ 7.6555, 7.6555, 7.6555, 7.6555, 7.6555] +24-11-19 19:23:09 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:23:09 | D | sum error = [ 83.8767, 89.1176, 94.6725, 100.5067, 106.6558] +24-11-19 19:23:09 | D | best error = [ 7.6555, 7.6555, 7.6555, 7.6555, 7.6555] +24-11-19 19:23:09 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:23:09 | D | sum error = [ 113.1382, 119.9976, 127.2091, 134.7893, 142.8046] +24-11-19 19:23:09 | D | best error = [ 7.6555, 7.6555, 7.6555, 7.6555, 7.6555] +24-11-19 19:23:09 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:23:09 | D | sum error = [ 151.2031, 160.0138, 169.3145, 179.0648, 189.3257] +24-11-19 19:23:09 | D | best error = [ 7.6555, 7.6555, 7.6555, 7.6555, 7.6555] +24-11-19 19:23:09 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:23:09 | D | sum error = [ 200.0913, 211.4145, 223.2731, 235.7394, 248.7805] +24-11-19 19:23:09 | D | best error = [ 7.6555, 7.6555, 7.6555, 7.6555, 7.6555] +24-11-19 19:23:09 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:23:09 | D | sum error = [ 262.4427, 276.7446, 291.6972, 307.3183, 323.6225] +24-11-19 19:23:09 | D | best error = [ 7.6555, 7.6555, 7.6555, 7.6555, 7.6555] +24-11-19 19:23:09 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:23:09 | D | sum error = [ 340.6626, 358.4074, 376.8927, 396.1098, 416.0688] +24-11-19 19:23:09 | D | best error = [ 7.6555, 7.6555, 7.6555, 7.6555, 7.6555] +24-11-19 19:23:09 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:23:09 | D | sum error = [ 436.8241, 458.3707, 480.7099, 503.8489, 527.7955] +24-11-19 19:23:09 | D | best error = [ 7.6555, 7.6555, 7.6555, 7.6555, 7.6555] +24-11-19 19:23:09 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:23:09 | D | sum error = [ 552.5589, 578.1724, 604.5887, 631.8214, 659.8782] +24-11-19 19:23:09 | D | best error = [ 7.6555, 7.6555, 7.6555, 7.6555, 7.6555] +24-11-19 19:23:09 | D | + error = [7.6555] +24-11-19 19:23:09 | D | - Calibrating model.layers.18.mlp.down_proj.weight +24-11-19 19:23:09 | D | + w: sint8 +24-11-19 19:23:09 | D | + x: None +24-11-19 19:23:09 | D | + y: None +24-11-19 19:23:09 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:23:09 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:23:09 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:23:09 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:23:09 | D | - range ratio = [ 1.0000] +24-11-19 19:23:09 | D | sum error = [ 2.9065] +24-11-19 19:23:09 | D | best error = [ 2.9065] +24-11-19 19:23:10 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:23:10 | D | sum error = [ 2.8779, 2.8643, 2.8413, 2.8310, 2.8319] +24-11-19 19:23:10 | D | best error = [ 2.7905, 2.7321, 2.6904, 2.6615, 2.6397] +24-11-19 19:23:10 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:23:10 | D | sum error = [ 2.8470, 2.8707, 2.9071, 2.9591, 3.0275] +24-11-19 19:23:10 | D | best error = [ 2.6227, 2.6094, 2.6004, 2.5941, 2.5893] +24-11-19 19:23:10 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:23:10 | D | sum error = [ 3.1052, 3.2067, 3.3244, 3.4639, 3.6243] +24-11-19 19:23:10 | D | best error = [ 2.5855, 2.5833, 2.5822, 2.5811, 2.5806] +24-11-19 19:23:10 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:23:10 | D | sum error = [ 3.8151, 4.0260, 4.2538, 4.5049, 4.7869] +24-11-19 19:23:10 | D | best error = [ 2.5803, 2.5801, 2.5799, 2.5798, 2.5798] +24-11-19 19:23:10 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:23:10 | D | sum error = [ 5.0965, 5.4281, 5.7882, 6.1836, 6.6076] +24-11-19 19:23:10 | D | best error = [ 2.5798, 2.5798, 2.5798, 2.5798, 2.5798] +24-11-19 19:23:10 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:23:10 | D | sum error = [ 7.0593, 7.5457, 8.0653, 8.6297, 9.2252] +24-11-19 19:23:10 | D | best error = [ 2.5798, 2.5798, 2.5798, 2.5798, 2.5798] +24-11-19 19:23:10 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:23:10 | D | sum error = [ 9.8612, 10.5436, 11.2643, 12.0344, 12.8502] +24-11-19 19:23:10 | D | best error = [ 2.5798, 2.5798, 2.5798, 2.5798, 2.5798] +24-11-19 19:23:10 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:23:10 | D | sum error = [ 13.7152, 14.6317, 15.6089, 16.6374, 17.7306] +24-11-19 19:23:10 | D | best error = [ 2.5798, 2.5798, 2.5798, 2.5798, 2.5798] +24-11-19 19:23:10 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:23:10 | D | sum error = [ 18.8804, 20.1014, 21.3877, 22.7424, 24.1766] +24-11-19 19:23:10 | D | best error = [ 2.5798, 2.5798, 2.5798, 2.5798, 2.5798] +24-11-19 19:23:10 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:23:10 | D | sum error = [ 25.6792, 27.2674, 28.9376, 30.7026, 32.5480] +24-11-19 19:23:10 | D | best error = [ 2.5798, 2.5798, 2.5798, 2.5798, 2.5798] +24-11-19 19:23:10 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:23:10 | D | sum error = [ 34.4875, 36.5251, 38.6614, 40.9027, 43.2585] +24-11-19 19:23:10 | D | best error = [ 2.5798, 2.5798, 2.5798, 2.5798, 2.5798] +24-11-19 19:23:10 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:23:10 | D | sum error = [ 45.7198, 48.2983, 50.9978, 53.8172, 56.7706] +24-11-19 19:23:10 | D | best error = [ 2.5798, 2.5798, 2.5798, 2.5798, 2.5798] +24-11-19 19:23:10 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:23:10 | D | sum error = [ 59.8555, 63.0708, 66.4266, 69.9292, 73.5745] +24-11-19 19:23:10 | D | best error = [ 2.5798, 2.5798, 2.5798, 2.5798, 2.5798] +24-11-19 19:23:10 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:23:10 | D | sum error = [ 77.3742, 81.3245, 85.4355, 89.7113, 94.1414] +24-11-19 19:23:10 | D | best error = [ 2.5798, 2.5798, 2.5798, 2.5798, 2.5798] +24-11-19 19:23:10 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:23:10 | D | sum error = [ 98.7456, 103.5227, 108.4698, 113.5953, 118.9008] +24-11-19 19:23:10 | D | best error = [ 2.5798, 2.5798, 2.5798, 2.5798, 2.5798] +24-11-19 19:23:10 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:23:10 | D | sum error = [ 124.3905, 130.0705, 135.9440, 142.0070, 148.2663] +24-11-19 19:23:10 | D | best error = [ 2.5798, 2.5798, 2.5798, 2.5798, 2.5798] +24-11-19 19:23:10 | D | + error = [2.5798] +24-11-19 19:23:10 | D | - Quantizing model.layers.18.self_attn.q_proj.weight +24-11-19 19:23:11 | D | - Quantizing model.layers.18.self_attn.k_proj.weight +24-11-19 19:23:12 | D | - Quantizing model.layers.18.self_attn.v_proj.weight +24-11-19 19:23:13 | D | - Quantizing model.layers.18.self_attn.o_proj.weight +24-11-19 19:23:14 | D | - Quantizing model.layers.18.mlp.up_proj.weight +24-11-19 19:23:15 | D | - Quantizing model.layers.18.mlp.gate_proj.weight +24-11-19 19:23:16 | D | - Quantizing model.layers.18.mlp.down_proj.weight +24-11-19 19:23:24 | D | - Quantizing layer model.layers.19 +24-11-19 19:23:24 | D | - Calibrating model.layers.19.self_attn.q_proj.weight +24-11-19 19:23:24 | D | + w: sint8 +24-11-19 19:23:24 | D | + x: None +24-11-19 19:23:24 | D | + y: None +24-11-19 19:23:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:23:24 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:23:24 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:23:25 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:23:25 | D | - range ratio = [ 1.0000] +24-11-19 19:23:25 | D | sum error = [ 11.5501] +24-11-19 19:23:25 | D | best error = [ 11.5501] +24-11-19 19:23:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:23:37 | D | sum error = [ 11.4934, 11.5033, 11.7908, 11.8116, 11.8356] +24-11-19 19:23:37 | D | best error = [ 11.4934, 11.4934, 11.4934, 11.4934, 11.4934] +24-11-19 19:23:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:23:37 | D | sum error = [ 12.3430, 12.7610, 13.2893, 13.9351, 14.5809] +24-11-19 19:23:37 | D | best error = [ 11.4934, 11.4934, 11.4934, 11.4934, 11.4934] +24-11-19 19:23:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:23:37 | D | sum error = [ 15.4352, 16.2944, 17.6233, 18.5792, 19.7427] +24-11-19 19:23:37 | D | best error = [ 11.4934, 11.4934, 11.4934, 11.4934, 11.4934] +24-11-19 19:23:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:23:37 | D | sum error = [ 21.4252, 23.0349, 24.7445, 26.8046, 28.7460] +24-11-19 19:23:37 | D | best error = [ 11.4934, 11.4934, 11.4934, 11.4934, 11.4934] +24-11-19 19:23:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:23:37 | D | sum error = [ 31.0881, 33.2594, 35.7828, 39.0720, 41.6580] +24-11-19 19:23:37 | D | best error = [ 11.4934, 11.4934, 11.4934, 11.4934, 11.4934] +24-11-19 19:23:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:23:37 | D | sum error = [ 45.2924, 48.6261, 52.4882, 56.7861, 61.1677] +24-11-19 19:23:37 | D | best error = [ 11.4934, 11.4934, 11.4934, 11.4934, 11.4934] +24-11-19 19:23:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:23:37 | D | sum error = [ 65.7794, 71.0692, 76.5899, 82.5484, 89.0614] +24-11-19 19:23:37 | D | best error = [ 11.4934, 11.4934, 11.4934, 11.4934, 11.4934] +24-11-19 19:23:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:23:37 | D | sum error = [ 96.0012, 103.1482, 110.9953, 119.7997, 129.0430] +24-11-19 19:23:37 | D | best error = [ 11.4934, 11.4934, 11.4934, 11.4934, 11.4934] +24-11-19 19:23:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:23:37 | D | sum error = [ 138.5736, 149.0537, 160.4064, 172.4900, 185.5280] +24-11-19 19:23:37 | D | best error = [ 11.4934, 11.4934, 11.4934, 11.4934, 11.4934] +24-11-19 19:23:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:23:37 | D | sum error = [ 199.4688, 214.4297, 230.4677, 247.4932, 266.0974] +24-11-19 19:23:37 | D | best error = [ 11.4934, 11.4934, 11.4934, 11.4934, 11.4934] +24-11-19 19:23:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:23:37 | D | sum error = [ 286.3101, 307.5011, 330.4288, 354.5590, 381.1679] +24-11-19 19:23:37 | D | best error = [ 11.4934, 11.4934, 11.4934, 11.4934, 11.4934] +24-11-19 19:23:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:23:37 | D | sum error = [ 409.7526, 440.2600, 473.6066, 509.5778, 548.2543] +24-11-19 19:23:37 | D | best error = [ 11.4934, 11.4934, 11.4934, 11.4934, 11.4934] +24-11-19 19:23:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:23:37 | D | sum error = [ 590.4901, 636.3854, 686.7139, 741.2834, 801.3089] +24-11-19 19:23:37 | D | best error = [ 11.4934, 11.4934, 11.4934, 11.4934, 11.4934] +24-11-19 19:23:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:23:37 | D | sum error = [ 867.7123, 940.6957, 1020.6140, 1109.8814, 1207.9721] +24-11-19 19:23:37 | D | best error = [ 11.4934, 11.4934, 11.4934, 11.4934, 11.4934] +24-11-19 19:23:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:23:37 | D | sum error = [ 1316.3930, 1436.8071, 1571.0221, 1720.0238, 1884.5607] +24-11-19 19:23:37 | D | best error = [ 11.4934, 11.4934, 11.4934, 11.4934, 11.4934] +24-11-19 19:23:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:23:37 | D | sum error = [ 2067.3179, 2267.7073, 2489.2117, 2730.1331, 2991.8075] +24-11-19 19:23:37 | D | best error = [ 11.4934, 11.4934, 11.4934, 11.4934, 11.4934] +24-11-19 19:23:37 | D | + error = [11.4934] +24-11-19 19:23:38 | D | - Calibrating model.layers.19.self_attn.k_proj.weight +24-11-19 19:23:38 | D | + w: sint8 +24-11-19 19:23:38 | D | + x: None +24-11-19 19:23:38 | D | + y: None +24-11-19 19:23:38 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:23:38 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:23:38 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:23:38 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:23:38 | D | - range ratio = [ 1.0000] +24-11-19 19:23:38 | D | sum error = [ 12.4330] +24-11-19 19:23:38 | D | best error = [ 12.4330] +24-11-19 19:23:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:23:51 | D | sum error = [ 12.4605, 12.2540, 12.0008, 12.3495, 12.7041] +24-11-19 19:23:51 | D | best error = [ 12.4330, 12.2540, 12.0008, 12.0008, 12.0008] +24-11-19 19:23:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:23:51 | D | sum error = [ 13.0003, 13.7324, 15.2598, 15.4036, 17.4704] +24-11-19 19:23:51 | D | best error = [ 12.0008, 12.0008, 12.0008, 12.0008, 12.0008] +24-11-19 19:23:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:23:51 | D | sum error = [ 16.9492, 18.4776, 19.1859, 21.5921, 22.8723] +24-11-19 19:23:51 | D | best error = [ 12.0008, 12.0008, 12.0008, 12.0008, 12.0008] +24-11-19 19:23:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:23:51 | D | sum error = [ 24.4098, 25.9809, 27.7968, 30.6217, 32.7934] +24-11-19 19:23:51 | D | best error = [ 12.0008, 12.0008, 12.0008, 12.0008, 12.0008] +24-11-19 19:23:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:23:51 | D | sum error = [ 35.5675, 38.7120, 40.3601, 44.7805, 47.5005] +24-11-19 19:23:51 | D | best error = [ 12.0008, 12.0008, 12.0008, 12.0008, 12.0008] +24-11-19 19:23:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:23:51 | D | sum error = [ 51.8806, 56.1755, 60.4404, 64.7321, 69.5529] +24-11-19 19:23:51 | D | best error = [ 12.0008, 12.0008, 12.0008, 12.0008, 12.0008] +24-11-19 19:23:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:23:51 | D | sum error = [ 75.2385, 81.4297, 86.7769, 95.4360, 101.9323] +24-11-19 19:23:51 | D | best error = [ 12.0008, 12.0008, 12.0008, 12.0008, 12.0008] +24-11-19 19:23:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:23:51 | D | sum error = [ 110.0285, 118.6317, 127.1756, 136.6377, 147.8334] +24-11-19 19:23:51 | D | best error = [ 12.0008, 12.0008, 12.0008, 12.0008, 12.0008] +24-11-19 19:23:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:23:51 | D | sum error = [ 159.7843, 171.5162, 183.4553, 198.2052, 212.7222] +24-11-19 19:23:51 | D | best error = [ 12.0008, 12.0008, 12.0008, 12.0008, 12.0008] +24-11-19 19:23:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:23:51 | D | sum error = [ 229.6639, 246.8046, 265.7005, 287.3668, 307.5427] +24-11-19 19:23:51 | D | best error = [ 12.0008, 12.0008, 12.0008, 12.0008, 12.0008] +24-11-19 19:23:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:23:51 | D | sum error = [ 330.1659, 355.7536, 383.9545, 413.4946, 446.8452] +24-11-19 19:23:51 | D | best error = [ 12.0008, 12.0008, 12.0008, 12.0008, 12.0008] +24-11-19 19:23:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:23:51 | D | sum error = [ 480.4926, 517.8899, 554.6214, 600.9067, 645.5222] +24-11-19 19:23:51 | D | best error = [ 12.0008, 12.0008, 12.0008, 12.0008, 12.0008] +24-11-19 19:23:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:23:51 | D | sum error = [ 696.8201, 748.7484, 810.9958, 873.2998, 943.4725] +24-11-19 19:23:51 | D | best error = [ 12.0008, 12.0008, 12.0008, 12.0008, 12.0008] +24-11-19 19:23:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:23:51 | D | sum error = [ 1018.0865, 1101.8842, 1190.5858, 1292.3754, 1407.3294] +24-11-19 19:23:51 | D | best error = [ 12.0008, 12.0008, 12.0008, 12.0008, 12.0008] +24-11-19 19:23:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:23:51 | D | sum error = [ 1527.3667, 1666.8499, 1809.3575, 1952.5215, 2134.6203] +24-11-19 19:23:51 | D | best error = [ 12.0008, 12.0008, 12.0008, 12.0008, 12.0008] +24-11-19 19:23:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:23:51 | D | sum error = [ 2334.3301, 2549.9212, 2769.3987, 3028.7027, 3283.1662] +24-11-19 19:23:51 | D | best error = [ 12.0008, 12.0008, 12.0008, 12.0008, 12.0008] +24-11-19 19:23:51 | D | + error = [12.0008] +24-11-19 19:23:51 | D | - Calibrating model.layers.19.self_attn.v_proj.weight +24-11-19 19:23:51 | D | + w: sint8 +24-11-19 19:23:51 | D | + x: None +24-11-19 19:23:51 | D | + y: None +24-11-19 19:23:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:23:51 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:23:51 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:23:51 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:23:51 | D | - range ratio = [ 1.0000] +24-11-19 19:23:51 | D | sum error = [ 6.1234] +24-11-19 19:23:51 | D | best error = [ 6.1234] +24-11-19 19:23:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:23:51 | D | sum error = [ 6.0848, 6.0657, 6.0866, 6.1490, 6.2940] +24-11-19 19:23:51 | D | best error = [ 5.7215, 5.5624, 5.4801, 5.4269, 5.4036] +24-11-19 19:23:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:23:51 | D | sum error = [ 6.4281, 6.6478, 6.9058, 7.2411, 7.6320] +24-11-19 19:23:51 | D | best error = [ 5.3892, 5.3828, 5.3809, 5.3797, 5.3797] +24-11-19 19:23:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:23:51 | D | sum error = [ 8.0718, 8.5794, 9.1549, 9.7669, 10.4389] +24-11-19 19:23:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 19:23:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:23:51 | D | sum error = [ 11.1837, 11.9706, 12.8504, 13.7768, 14.7617] +24-11-19 19:23:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 19:23:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:23:51 | D | sum error = [ 15.7864, 16.9367, 18.1505, 19.4223, 20.7719] +24-11-19 19:23:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 19:23:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:23:51 | D | sum error = [ 22.1960, 23.6862, 25.3272, 27.0102, 28.7567] +24-11-19 19:23:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 19:23:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:23:51 | D | sum error = [ 30.6524, 32.6161, 34.7140, 36.9094, 39.2205] +24-11-19 19:23:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 19:23:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:23:51 | D | sum error = [ 41.6579, 44.2143, 46.8890, 49.7146, 52.6768] +24-11-19 19:23:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 19:23:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:23:51 | D | sum error = [ 55.7682, 59.0284, 62.4751, 66.0449, 69.7904] +24-11-19 19:23:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 19:23:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:23:51 | D | sum error = [ 73.7470, 77.8839, 82.2013, 86.7138, 91.4350] +24-11-19 19:23:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 19:23:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:23:51 | D | sum error = [ 96.3373, 101.4757, 106.8360, 112.4278, 118.2485] +24-11-19 19:23:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 19:23:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:23:51 | D | sum error = [ 124.3271, 130.6733, 137.2622, 144.1316, 151.2760] +24-11-19 19:23:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 19:23:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:23:51 | D | sum error = [ 158.6967, 166.4085, 174.4075, 182.7063, 191.3131] +24-11-19 19:23:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 19:23:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:23:51 | D | sum error = [ 200.2203, 209.4548, 219.0012, 228.8653, 239.0827] +24-11-19 19:23:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 19:23:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:23:51 | D | sum error = [ 249.6310, 260.5255, 271.7724, 283.3942, 295.3883] +24-11-19 19:23:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 19:23:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:23:51 | D | sum error = [ 307.7526, 320.4951, 333.6329, 347.1567, 361.0439] +24-11-19 19:23:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 19:23:51 | D | + error = [5.3796] +24-11-19 19:23:52 | D | - Calibrating model.layers.19.self_attn.o_proj.weight +24-11-19 19:23:52 | D | + w: sint8 +24-11-19 19:23:52 | D | + x: None +24-11-19 19:23:52 | D | + y: None +24-11-19 19:23:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:23:52 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:23:52 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:23:52 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:23:52 | D | - range ratio = [ 1.0000] +24-11-19 19:23:52 | D | sum error = [ 1.4442] +24-11-19 19:23:52 | D | best error = [ 1.4442] +24-11-19 19:23:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:23:52 | D | sum error = [ 1.4344, 1.4278, 1.4233, 1.4338, 1.4451] +24-11-19 19:23:52 | D | best error = [ 1.3581, 1.3190, 1.2933, 1.2784, 1.2675] +24-11-19 19:23:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:23:52 | D | sum error = [ 1.4696, 1.5053, 1.5472, 1.5958, 1.6678] +24-11-19 19:23:52 | D | best error = [ 1.2605, 1.2558, 1.2527, 1.2507, 1.2497] +24-11-19 19:23:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:23:52 | D | sum error = [ 1.7432, 1.8305, 1.9274, 2.0374, 2.1607] +24-11-19 19:23:52 | D | best error = [ 1.2490, 1.2486, 1.2483, 1.2480, 1.2479] +24-11-19 19:23:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:23:52 | D | sum error = [ 2.2961, 2.4412, 2.6038, 2.7776, 2.9608] +24-11-19 19:23:52 | D | best error = [ 1.2478, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 19:23:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:23:52 | D | sum error = [ 3.1609, 3.3782, 3.6095, 3.8475, 4.1064] +24-11-19 19:23:52 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 19:23:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:23:52 | D | sum error = [ 4.3840, 4.6764, 4.9823, 5.3108, 5.6562] +24-11-19 19:23:52 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 19:23:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:23:52 | D | sum error = [ 6.0199, 6.4098, 6.8197, 7.2506, 7.7089] +24-11-19 19:23:52 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 19:23:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:23:52 | D | sum error = [ 8.1905, 8.7002, 9.2357, 9.8028, 10.3949] +24-11-19 19:23:52 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 19:23:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:23:52 | D | sum error = [ 11.0228, 11.6865, 12.3786, 13.1121, 13.8775] +24-11-19 19:23:52 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 19:23:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:23:52 | D | sum error = [ 14.6820, 15.5286, 16.4139, 17.3494, 18.3293] +24-11-19 19:23:52 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 19:23:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:23:52 | D | sum error = [ 19.3540, 20.4311, 21.5552, 22.7361, 23.9694] +24-11-19 19:23:52 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 19:23:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:23:52 | D | sum error = [ 25.2599, 26.6085, 28.0185, 29.4956, 31.0344] +24-11-19 19:23:52 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 19:23:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:23:52 | D | sum error = [ 32.6448, 34.3181, 36.0676, 37.8856, 39.7827] +24-11-19 19:23:52 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 19:23:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:23:52 | D | sum error = [ 41.7571, 43.8062, 45.9328, 48.1425, 50.4381] +24-11-19 19:23:52 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 19:23:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:23:52 | D | sum error = [ 52.8201, 55.2890, 57.8483, 60.4967, 63.2384] +24-11-19 19:23:52 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 19:23:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:23:52 | D | sum error = [ 66.0728, 68.9980, 72.0185, 75.1448, 78.3704] +24-11-19 19:23:52 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 19:23:52 | D | + error = [1.2477] +24-11-19 19:23:52 | D | - Calibrating model.layers.19.mlp.up_proj.weight +24-11-19 19:23:52 | D | + w: sint8 +24-11-19 19:23:52 | D | + x: None +24-11-19 19:23:52 | D | + y: None +24-11-19 19:23:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:23:52 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:23:52 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:23:52 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:23:52 | D | - range ratio = [ 1.0000] +24-11-19 19:23:52 | D | sum error = [ 8.5690] +24-11-19 19:23:52 | D | best error = [ 8.5690] +24-11-19 19:23:53 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:23:53 | D | sum error = [ 8.4891, 8.4581, 8.4861, 8.6028, 8.7570] +24-11-19 19:23:53 | D | best error = [ 7.9734, 7.7406, 7.6124, 7.5434, 7.5082] +24-11-19 19:23:53 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:23:53 | D | sum error = [ 8.9985, 9.2996, 9.6524, 10.1221, 10.6437] +24-11-19 19:23:53 | D | best error = [ 7.4897, 7.4821, 7.4797, 7.4789, 7.4787] +24-11-19 19:23:53 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:23:53 | D | sum error = [ 11.2533, 11.9660, 12.7165, 13.6163, 14.5494] +24-11-19 19:23:53 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 19:23:53 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:23:53 | D | sum error = [ 15.5719, 16.6998, 17.8664, 19.1546, 20.5486] +24-11-19 19:23:53 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 19:23:53 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:23:53 | D | sum error = [ 22.0096, 23.5564, 25.2415, 27.0080, 28.8850] +24-11-19 19:23:53 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 19:23:53 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:23:53 | D | sum error = [ 30.8387, 32.9887, 35.2015, 37.5531, 40.0532] +24-11-19 19:23:53 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 19:23:53 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:23:53 | D | sum error = [ 42.6625, 45.4301, 48.3514, 51.4128, 54.6613] +24-11-19 19:23:53 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 19:23:53 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:23:53 | D | sum error = [ 58.0756, 61.6824, 65.4551, 69.4130, 73.5951] +24-11-19 19:23:53 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 19:23:53 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:23:53 | D | sum error = [ 77.9743, 82.5543, 87.3695, 92.4232, 97.6952] +24-11-19 19:23:53 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 19:23:53 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:23:53 | D | sum error = [ 103.2488, 109.0555, 115.1453, 121.5037, 128.1708] +24-11-19 19:23:53 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 19:23:53 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:23:53 | D | sum error = [ 135.1352, 142.4182, 150.0235, 157.9659, 166.2377] +24-11-19 19:23:53 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 19:23:53 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:23:53 | D | sum error = [ 174.8825, 183.8772, 193.2434, 202.9946, 213.1204] +24-11-19 19:23:53 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 19:23:53 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:23:53 | D | sum error = [ 223.6545, 234.6080, 245.9682, 257.7597, 269.9789] +24-11-19 19:23:53 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 19:23:53 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:23:53 | D | sum error = [ 282.6447, 295.7720, 309.3676, 323.4507, 338.0017] +24-11-19 19:23:53 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 19:23:53 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:23:53 | D | sum error = [ 353.0507, 368.6050, 384.6826, 401.2770, 418.3948] +24-11-19 19:23:53 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 19:23:53 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:23:53 | D | sum error = [ 436.0428, 454.2445, 473.0017, 492.3111, 512.1710] +24-11-19 19:23:53 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 19:23:53 | D | + error = [7.4786] +24-11-19 19:23:53 | D | - Calibrating model.layers.19.mlp.gate_proj.weight +24-11-19 19:23:53 | D | + w: sint8 +24-11-19 19:23:53 | D | + x: None +24-11-19 19:23:53 | D | + y: None +24-11-19 19:23:53 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:23:53 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:23:54 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:23:54 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:23:54 | D | - range ratio = [ 1.0000] +24-11-19 19:23:54 | D | sum error = [ 9.0825] +24-11-19 19:23:54 | D | best error = [ 9.0825] +24-11-19 19:23:55 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:23:55 | D | sum error = [ 9.0300, 8.9883, 9.0398, 9.1338, 9.3224] +24-11-19 19:23:55 | D | best error = [ 8.4721, 8.2228, 8.0918, 8.0192, 7.9824] +24-11-19 19:23:55 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:23:55 | D | sum error = [ 9.5319, 9.8617, 10.2886, 10.7676, 11.3340] +24-11-19 19:23:55 | D | best error = [ 7.9635, 7.9555, 7.9524, 7.9514, 7.9511] +24-11-19 19:23:55 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:23:55 | D | sum error = [ 11.9793, 12.7090, 13.5281, 14.4875, 15.4838] +24-11-19 19:23:55 | D | best error = [ 7.9511, 7.9511, 7.9511, 7.9511, 7.9511] +24-11-19 19:23:55 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:23:55 | D | sum error = [ 16.5748, 17.7597, 19.0574, 20.4221, 21.9248] +24-11-19 19:23:55 | D | best error = [ 7.9511, 7.9511, 7.9511, 7.9511, 7.9511] +24-11-19 19:23:55 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:23:55 | D | sum error = [ 23.4889, 25.1801, 26.9978, 28.9027, 30.9528] +24-11-19 19:23:55 | D | best error = [ 7.9511, 7.9511, 7.9511, 7.9511, 7.9511] +24-11-19 19:23:55 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:23:55 | D | sum error = [ 33.1293, 35.4128, 37.8689, 40.4578, 43.1800] +24-11-19 19:23:55 | D | best error = [ 7.9511, 7.9511, 7.9511, 7.9511, 7.9511] +24-11-19 19:23:55 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:23:55 | D | sum error = [ 46.0687, 49.1556, 52.4046, 55.8280, 59.4568] +24-11-19 19:23:55 | D | best error = [ 7.9511, 7.9511, 7.9511, 7.9511, 7.9511] +24-11-19 19:23:55 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:23:55 | D | sum error = [ 63.2710, 67.3116, 71.5999, 76.0796, 80.8520] +24-11-19 19:23:55 | D | best error = [ 7.9511, 7.9511, 7.9511, 7.9511, 7.9511] +24-11-19 19:23:55 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:23:55 | D | sum error = [ 85.8822, 91.1827, 96.8017, 102.6808, 108.9117] +24-11-19 19:23:55 | D | best error = [ 7.9511, 7.9511, 7.9511, 7.9511, 7.9511] +24-11-19 19:23:55 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:23:55 | D | sum error = [ 115.4788, 122.3770, 129.6337, 137.2881, 145.3353] +24-11-19 19:23:55 | D | best error = [ 7.9511, 7.9511, 7.9511, 7.9511, 7.9511] +24-11-19 19:23:55 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:23:55 | D | sum error = [ 153.7728, 162.6531, 171.9710, 181.7459, 192.0390] +24-11-19 19:23:55 | D | best error = [ 7.9511, 7.9511, 7.9511, 7.9511, 7.9511] +24-11-19 19:23:55 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:23:55 | D | sum error = [ 202.7871, 214.0899, 225.9239, 238.3152, 251.2900] +24-11-19 19:23:55 | D | best error = [ 7.9511, 7.9511, 7.9511, 7.9511, 7.9511] +24-11-19 19:23:55 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:23:55 | D | sum error = [ 264.8812, 279.0381, 293.8302, 309.2615, 325.3665] +24-11-19 19:23:55 | D | best error = [ 7.9511, 7.9511, 7.9511, 7.9511, 7.9511] +24-11-19 19:23:55 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:23:55 | D | sum error = [ 342.1542, 359.6467, 377.8732, 396.8452, 416.5623] +24-11-19 19:23:55 | D | best error = [ 7.9511, 7.9511, 7.9511, 7.9511, 7.9511] +24-11-19 19:23:55 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:23:55 | D | sum error = [ 437.0391, 458.2714, 480.2746, 503.0498, 526.6386] +24-11-19 19:23:55 | D | best error = [ 7.9511, 7.9511, 7.9511, 7.9511, 7.9511] +24-11-19 19:23:55 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:23:55 | D | sum error = [ 550.9656, 576.1484, 602.1276, 628.9317, 656.5275] +24-11-19 19:23:55 | D | best error = [ 7.9511, 7.9511, 7.9511, 7.9511, 7.9511] +24-11-19 19:23:55 | D | + error = [7.9511] +24-11-19 19:23:55 | D | - Calibrating model.layers.19.mlp.down_proj.weight +24-11-19 19:23:55 | D | + w: sint8 +24-11-19 19:23:55 | D | + x: None +24-11-19 19:23:55 | D | + y: None +24-11-19 19:23:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:23:55 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:23:55 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:23:55 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:23:55 | D | - range ratio = [ 1.0000] +24-11-19 19:23:55 | D | sum error = [ 3.1571] +24-11-19 19:23:55 | D | best error = [ 3.1571] +24-11-19 19:23:56 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:23:56 | D | sum error = [ 3.1302, 3.1109, 3.0919, 3.0961, 3.1011] +24-11-19 19:23:56 | D | best error = [ 3.0238, 2.9599, 2.9145, 2.8818, 2.8583] +24-11-19 19:23:56 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:23:56 | D | sum error = [ 3.1155, 3.1495, 3.1977, 3.2595, 3.3496] +24-11-19 19:23:56 | D | best error = [ 2.8369, 2.8210, 2.8102, 2.8025, 2.7971] +24-11-19 19:23:56 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:23:56 | D | sum error = [ 3.4446, 3.5696, 3.7103, 3.8777, 4.0652] +24-11-19 19:23:56 | D | best error = [ 2.7932, 2.7904, 2.7888, 2.7875, 2.7869] +24-11-19 19:23:56 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:23:56 | D | sum error = [ 4.2743, 4.5097, 4.7707, 5.0540, 5.3663] +24-11-19 19:23:56 | D | best error = [ 2.7864, 2.7860, 2.7858, 2.7857, 2.7857] +24-11-19 19:23:56 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:23:56 | D | sum error = [ 5.7126, 6.0803, 6.4812, 6.9122, 7.3715] +24-11-19 19:23:56 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 19:23:56 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:23:56 | D | sum error = [ 7.8768, 8.4042, 8.9709, 9.5873, 10.2357] +24-11-19 19:23:56 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 19:23:56 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:23:56 | D | sum error = [ 10.9317, 11.6662, 12.4539, 13.2902, 14.1804] +24-11-19 19:23:56 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 19:23:56 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:23:56 | D | sum error = [ 15.1188, 16.1225, 17.1844, 18.3056, 19.4929] +24-11-19 19:23:56 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 19:23:56 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:23:56 | D | sum error = [ 20.7458, 22.0742, 23.4708, 24.9493, 26.5057] +24-11-19 19:23:56 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 19:23:56 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:23:56 | D | sum error = [ 28.1440, 29.8718, 31.6909, 33.6068, 35.6154] +24-11-19 19:23:56 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 19:23:56 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:23:56 | D | sum error = [ 37.7390, 39.9563, 42.2843, 44.7266, 47.2874] +24-11-19 19:23:56 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 19:23:56 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:23:56 | D | sum error = [ 49.9675, 52.7740, 55.7136, 58.7850, 61.9955] +24-11-19 19:23:56 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 19:23:56 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:23:56 | D | sum error = [ 65.3498, 68.8482, 72.4989, 76.3052, 80.2716] +24-11-19 19:23:56 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 19:23:56 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:23:56 | D | sum error = [ 84.4105, 88.7113, 93.1990, 97.8746, 102.7093] +24-11-19 19:23:56 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 19:23:56 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:23:56 | D | sum error = [ 107.7438, 112.9628, 118.3740, 123.9845, 129.7975] +24-11-19 19:23:56 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 19:23:56 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:23:56 | D | sum error = [ 135.8172, 142.0444, 148.4837, 155.1414, 162.0155] +24-11-19 19:23:56 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 19:23:56 | D | + error = [2.7857] +24-11-19 19:23:56 | D | - Quantizing model.layers.19.self_attn.q_proj.weight +24-11-19 19:23:57 | D | - Quantizing model.layers.19.self_attn.k_proj.weight +24-11-19 19:23:58 | D | - Quantizing model.layers.19.self_attn.v_proj.weight +24-11-19 19:23:59 | D | - Quantizing model.layers.19.self_attn.o_proj.weight +24-11-19 19:24:00 | D | - Quantizing model.layers.19.mlp.up_proj.weight +24-11-19 19:24:00 | D | - Quantizing model.layers.19.mlp.gate_proj.weight +24-11-19 19:24:01 | D | - Quantizing model.layers.19.mlp.down_proj.weight +24-11-19 19:24:10 | D | - Quantizing layer model.layers.20 +24-11-19 19:24:10 | D | - Calibrating model.layers.20.self_attn.q_proj.weight +24-11-19 19:24:10 | D | + w: sint8 +24-11-19 19:24:10 | D | + x: None +24-11-19 19:24:10 | D | + y: None +24-11-19 19:24:10 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:24:10 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:24:10 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:24:10 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:24:10 | D | - range ratio = [ 1.0000] +24-11-19 19:24:10 | D | sum error = [ 12.0445] +24-11-19 19:24:10 | D | best error = [ 12.0445] +24-11-19 19:24:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:24:22 | D | sum error = [ 11.8250, 11.6962, 11.8806, 12.1996, 12.1639] +24-11-19 19:24:22 | D | best error = [ 11.8250, 11.6962, 11.6962, 11.6962, 11.6962] +24-11-19 19:24:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:24:22 | D | sum error = [ 12.9435, 13.2300, 13.5492, 14.4248, 15.0321] +24-11-19 19:24:22 | D | best error = [ 11.6962, 11.6962, 11.6962, 11.6962, 11.6962] +24-11-19 19:24:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:24:22 | D | sum error = [ 15.9083, 16.9810, 17.9613, 19.3066, 20.6926] +24-11-19 19:24:22 | D | best error = [ 11.6962, 11.6962, 11.6962, 11.6962, 11.6962] +24-11-19 19:24:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:24:22 | D | sum error = [ 22.2919, 23.9811, 25.7252, 28.0148, 30.2306] +24-11-19 19:24:22 | D | best error = [ 11.6962, 11.6962, 11.6962, 11.6962, 11.6962] +24-11-19 19:24:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:24:22 | D | sum error = [ 32.6014, 35.1395, 38.3364, 40.9666, 44.5052] +24-11-19 19:24:22 | D | best error = [ 11.6962, 11.6962, 11.6962, 11.6962, 11.6962] +24-11-19 19:24:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:24:22 | D | sum error = [ 48.2164, 51.6860, 55.8707, 60.0997, 65.0834] +24-11-19 19:24:22 | D | best error = [ 11.6962, 11.6962, 11.6962, 11.6962, 11.6962] +24-11-19 19:24:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:24:22 | D | sum error = [ 70.0869, 75.0076, 81.0449, 87.1105, 94.0452] +24-11-19 19:24:22 | D | best error = [ 11.6962, 11.6962, 11.6962, 11.6962, 11.6962] +24-11-19 19:24:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:24:22 | D | sum error = [ 100.8994, 108.3548, 116.4579, 125.2055, 134.3906] +24-11-19 19:24:22 | D | best error = [ 11.6962, 11.6962, 11.6962, 11.6962, 11.6962] +24-11-19 19:24:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:24:22 | D | sum error = [ 144.3806, 154.8035, 166.3203, 178.4848, 191.2267] +24-11-19 19:24:22 | D | best error = [ 11.6962, 11.6962, 11.6962, 11.6962, 11.6962] +24-11-19 19:24:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:24:22 | D | sum error = [ 205.2832, 220.3712, 236.0008, 253.5471, 271.7883] +24-11-19 19:24:22 | D | best error = [ 11.6962, 11.6962, 11.6962, 11.6962, 11.6962] +24-11-19 19:24:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:24:22 | D | sum error = [ 291.5656, 312.7741, 335.9045, 360.2497, 386.4875] +24-11-19 19:24:22 | D | best error = [ 11.6962, 11.6962, 11.6962, 11.6962, 11.6962] +24-11-19 19:24:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:24:22 | D | sum error = [ 415.1503, 445.4763, 477.6206, 512.7243, 549.9026] +24-11-19 19:24:22 | D | best error = [ 11.6962, 11.6962, 11.6962, 11.6962, 11.6962] +24-11-19 19:24:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:24:22 | D | sum error = [ 590.0885, 633.7321, 681.1287, 732.3150, 788.4273] +24-11-19 19:24:22 | D | best error = [ 11.6962, 11.6962, 11.6962, 11.6962, 11.6962] +24-11-19 19:24:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:24:22 | D | sum error = [ 849.6523, 916.2192, 988.7432, 1068.7137, 1155.7729] +24-11-19 19:24:22 | D | best error = [ 11.6962, 11.6962, 11.6962, 11.6962, 11.6962] +24-11-19 19:24:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:24:22 | D | sum error = [ 1251.2733, 1356.6328, 1472.3962, 1600.3269, 1741.3947] +24-11-19 19:24:22 | D | best error = [ 11.6962, 11.6962, 11.6962, 11.6962, 11.6962] +24-11-19 19:24:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:24:22 | D | sum error = [ 1896.7402, 2068.7595, 2258.1996, 2467.1081, 2698.4414] +24-11-19 19:24:22 | D | best error = [ 11.6962, 11.6962, 11.6962, 11.6962, 11.6962] +24-11-19 19:24:22 | D | + error = [11.6962] +24-11-19 19:24:23 | D | - Calibrating model.layers.20.self_attn.k_proj.weight +24-11-19 19:24:23 | D | + w: sint8 +24-11-19 19:24:23 | D | + x: None +24-11-19 19:24:23 | D | + y: None +24-11-19 19:24:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:24:23 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:24:23 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:24:23 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:24:23 | D | - range ratio = [ 1.0000] +24-11-19 19:24:23 | D | sum error = [ 14.3360] +24-11-19 19:24:23 | D | best error = [ 14.3360] +24-11-19 19:24:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:24:36 | D | sum error = [ 13.3825, 13.9593, 14.1764, 12.5218, 13.8721] +24-11-19 19:24:36 | D | best error = [ 13.3825, 13.3825, 13.3825, 12.5218, 12.5218] +24-11-19 19:24:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:24:36 | D | sum error = [ 13.7646, 14.1940, 15.5270, 16.1576, 16.6758] +24-11-19 19:24:36 | D | best error = [ 12.5218, 12.5218, 12.5218, 12.5218, 12.5218] +24-11-19 19:24:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:24:36 | D | sum error = [ 17.5548, 17.9180, 20.4531, 20.9509, 23.5606] +24-11-19 19:24:36 | D | best error = [ 12.5218, 12.5218, 12.5218, 12.5218, 12.5218] +24-11-19 19:24:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:24:36 | D | sum error = [ 24.1584, 26.5971, 29.2176, 30.7621, 34.1173] +24-11-19 19:24:36 | D | best error = [ 12.5218, 12.5218, 12.5218, 12.5218, 12.5218] +24-11-19 19:24:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:24:36 | D | sum error = [ 35.8343, 39.1093, 41.9770, 45.9992, 49.4815] +24-11-19 19:24:36 | D | best error = [ 12.5218, 12.5218, 12.5218, 12.5218, 12.5218] +24-11-19 19:24:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:24:36 | D | sum error = [ 53.4998, 58.4936, 63.1187, 68.5641, 73.4325] +24-11-19 19:24:36 | D | best error = [ 12.5218, 12.5218, 12.5218, 12.5218, 12.5218] +24-11-19 19:24:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:24:36 | D | sum error = [ 79.3874, 85.7461, 93.4095, 99.9469, 109.3342] +24-11-19 19:24:36 | D | best error = [ 12.5218, 12.5218, 12.5218, 12.5218, 12.5218] +24-11-19 19:24:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:24:36 | D | sum error = [ 118.9685, 127.4355, 135.8479, 149.1908, 160.6798] +24-11-19 19:24:36 | D | best error = [ 12.5218, 12.5218, 12.5218, 12.5218, 12.5218] +24-11-19 19:24:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:24:36 | D | sum error = [ 173.1929, 185.1872, 200.4165, 214.4017, 228.7492] +24-11-19 19:24:36 | D | best error = [ 12.5218, 12.5218, 12.5218, 12.5218, 12.5218] +24-11-19 19:24:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:24:36 | D | sum error = [ 246.4035, 263.2410, 281.7942, 303.2193, 326.4058] +24-11-19 19:24:36 | D | best error = [ 12.5218, 12.5218, 12.5218, 12.5218, 12.5218] +24-11-19 19:24:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:24:36 | D | sum error = [ 347.8794, 374.6652, 401.0965, 433.2170, 461.8011] +24-11-19 19:24:36 | D | best error = [ 12.5218, 12.5218, 12.5218, 12.5218, 12.5218] +24-11-19 19:24:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:24:36 | D | sum error = [ 498.8457, 534.6354, 571.0931, 614.6379, 655.8880] +24-11-19 19:24:36 | D | best error = [ 12.5218, 12.5218, 12.5218, 12.5218, 12.5218] +24-11-19 19:24:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:24:36 | D | sum error = [ 704.8044, 757.3226, 815.1653, 882.0022, 951.0022] +24-11-19 19:24:36 | D | best error = [ 12.5218, 12.5218, 12.5218, 12.5218, 12.5218] +24-11-19 19:24:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:24:36 | D | sum error = [ 1026.1562, 1103.9760, 1195.1092, 1298.1074, 1403.9817] +24-11-19 19:24:36 | D | best error = [ 12.5218, 12.5218, 12.5218, 12.5218, 12.5218] +24-11-19 19:24:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:24:36 | D | sum error = [ 1529.5103, 1648.6297, 1793.8371, 1950.5721, 2110.6655] +24-11-19 19:24:36 | D | best error = [ 12.5218, 12.5218, 12.5218, 12.5218, 12.5218] +24-11-19 19:24:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:24:36 | D | sum error = [ 2308.3373, 2518.6027, 2733.4860, 2973.4253, 3237.8275] +24-11-19 19:24:36 | D | best error = [ 12.5218, 12.5218, 12.5218, 12.5218, 12.5218] +24-11-19 19:24:36 | D | + error = [12.5218] +24-11-19 19:24:36 | D | - Calibrating model.layers.20.self_attn.v_proj.weight +24-11-19 19:24:36 | D | + w: sint8 +24-11-19 19:24:36 | D | + x: None +24-11-19 19:24:36 | D | + y: None +24-11-19 19:24:36 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:24:36 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:24:36 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:24:36 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:24:36 | D | - range ratio = [ 1.0000] +24-11-19 19:24:36 | D | sum error = [ 6.2684] +24-11-19 19:24:36 | D | best error = [ 6.2684] +24-11-19 19:24:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:24:37 | D | sum error = [ 6.2177, 6.1890, 6.2651, 6.2987, 6.4249] +24-11-19 19:24:37 | D | best error = [ 5.8543, 5.6910, 5.6083, 5.5547, 5.5270] +24-11-19 19:24:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:24:37 | D | sum error = [ 6.5902, 6.7916, 7.0917, 7.4224, 7.7917] +24-11-19 19:24:37 | D | best error = [ 5.5143, 5.5088, 5.5070, 5.5063, 5.5060] +24-11-19 19:24:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:24:37 | D | sum error = [ 8.2306, 8.7554, 9.3384, 9.9470, 10.6291] +24-11-19 19:24:37 | D | best error = [ 5.5059, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 19:24:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:24:37 | D | sum error = [ 11.3716, 12.1933, 13.0446, 13.9741, 14.9416] +24-11-19 19:24:37 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 19:24:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:24:37 | D | sum error = [ 16.0624, 17.1491, 18.3730, 19.6301, 20.9821] +24-11-19 19:24:37 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 19:24:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:24:37 | D | sum error = [ 22.4533, 23.9499, 25.5791, 27.2781, 29.0746] +24-11-19 19:24:37 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 19:24:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:24:37 | D | sum error = [ 30.9801, 32.9661, 35.1017, 37.3400, 39.6680] +24-11-19 19:24:37 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 19:24:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:24:37 | D | sum error = [ 42.1297, 44.7227, 47.4434, 50.3082, 53.3087] +24-11-19 19:24:37 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 19:24:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:24:37 | D | sum error = [ 56.4384, 59.7400, 63.1949, 66.7975, 70.5890] +24-11-19 19:24:37 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 19:24:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:24:37 | D | sum error = [ 74.5438, 78.6971, 83.0215, 87.5474, 92.2680] +24-11-19 19:24:37 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 19:24:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:24:37 | D | sum error = [ 97.2038, 102.3680, 107.7537, 113.3448, 119.1767] +24-11-19 19:24:37 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 19:24:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:24:37 | D | sum error = [ 125.2445, 131.5580, 138.1335, 144.9621, 152.0467] +24-11-19 19:24:37 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 19:24:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:24:37 | D | sum error = [ 159.4230, 167.0630, 175.0075, 183.2257, 191.7373] +24-11-19 19:24:37 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 19:24:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:24:37 | D | sum error = [ 200.5669, 209.6964, 219.1363, 228.8951, 238.9699] +24-11-19 19:24:37 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 19:24:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:24:37 | D | sum error = [ 249.3734, 260.1044, 271.1818, 282.6131, 294.4029] +24-11-19 19:24:37 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 19:24:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:24:37 | D | sum error = [ 306.5367, 319.0720, 331.9570, 345.2159, 358.8675] +24-11-19 19:24:37 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 19:24:37 | D | + error = [5.5058] +24-11-19 19:24:37 | D | - Calibrating model.layers.20.self_attn.o_proj.weight +24-11-19 19:24:37 | D | + w: sint8 +24-11-19 19:24:37 | D | + x: None +24-11-19 19:24:37 | D | + y: None +24-11-19 19:24:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:24:37 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:24:37 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:24:37 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:24:37 | D | - range ratio = [ 1.0000] +24-11-19 19:24:37 | D | sum error = [ 1.6047] +24-11-19 19:24:37 | D | best error = [ 1.6047] +24-11-19 19:24:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:24:37 | D | sum error = [ 1.5925, 1.5805, 1.5857, 1.6032, 1.6209] +24-11-19 19:24:37 | D | best error = [ 1.4783, 1.4200, 1.3869, 1.3671, 1.3518] +24-11-19 19:24:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:24:37 | D | sum error = [ 1.6510, 1.6909, 1.7529, 1.8245, 1.9036] +24-11-19 19:24:37 | D | best error = [ 1.3413, 1.3340, 1.3287, 1.3255, 1.3228] +24-11-19 19:24:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:24:37 | D | sum error = [ 2.0025, 2.1188, 2.2474, 2.3781, 2.5334] +24-11-19 19:24:37 | D | best error = [ 1.3206, 1.3193, 1.3187, 1.3180, 1.3174] +24-11-19 19:24:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:24:37 | D | sum error = [ 2.7059, 2.8768, 3.0772, 3.2922, 3.5149] +24-11-19 19:24:37 | D | best error = [ 1.3172, 1.3169, 1.3166, 1.3165, 1.3164] +24-11-19 19:24:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:24:37 | D | sum error = [ 3.7614, 4.0187, 4.2986, 4.5884, 4.9021] +24-11-19 19:24:37 | D | best error = [ 1.3163, 1.3163, 1.3161, 1.3161, 1.3161] +24-11-19 19:24:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:24:37 | D | sum error = [ 5.2410, 5.5906, 5.9704, 6.3666, 6.7918] +24-11-19 19:24:37 | D | best error = [ 1.3161, 1.3161, 1.3161, 1.3161, 1.3161] +24-11-19 19:24:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:24:37 | D | sum error = [ 7.2340, 7.7001, 8.1985, 8.7271, 9.2760] +24-11-19 19:24:37 | D | best error = [ 1.3161, 1.3161, 1.3161, 1.3161, 1.3161] +24-11-19 19:24:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:24:37 | D | sum error = [ 9.8616, 10.4828, 11.1287, 11.8094, 12.5243] +24-11-19 19:24:37 | D | best error = [ 1.3161, 1.3161, 1.3161, 1.3161, 1.3161] +24-11-19 19:24:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:24:37 | D | sum error = [ 13.2864, 14.0766, 14.9107, 15.7906, 16.7124] +24-11-19 19:24:37 | D | best error = [ 1.3161, 1.3161, 1.3161, 1.3161, 1.3161] +24-11-19 19:24:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:24:37 | D | sum error = [ 17.6788, 18.6883, 19.7515, 20.8725, 22.0440] +24-11-19 19:24:37 | D | best error = [ 1.3161, 1.3161, 1.3161, 1.3161, 1.3161] +24-11-19 19:24:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:24:37 | D | sum error = [ 23.2721, 24.5680, 25.9174, 27.3396, 28.8235] +24-11-19 19:24:37 | D | best error = [ 1.3161, 1.3161, 1.3161, 1.3161, 1.3161] +24-11-19 19:24:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:24:37 | D | sum error = [ 30.3779, 32.0079, 33.7098, 35.4905, 37.3446] +24-11-19 19:24:37 | D | best error = [ 1.3161, 1.3161, 1.3161, 1.3161, 1.3161] +24-11-19 19:24:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:24:37 | D | sum error = [ 39.2877, 41.3138, 43.4289, 45.6399, 47.9409] +24-11-19 19:24:37 | D | best error = [ 1.3161, 1.3161, 1.3161, 1.3161, 1.3161] +24-11-19 19:24:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:24:37 | D | sum error = [ 50.3345, 52.8211, 55.4016, 58.0883, 60.8734] +24-11-19 19:24:37 | D | best error = [ 1.3161, 1.3161, 1.3161, 1.3161, 1.3161] +24-11-19 19:24:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:24:37 | D | sum error = [ 63.7623, 66.7615, 69.8722, 73.0949, 76.4330] +24-11-19 19:24:37 | D | best error = [ 1.3161, 1.3161, 1.3161, 1.3161, 1.3161] +24-11-19 19:24:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:24:37 | D | sum error = [ 79.8868, 83.4567, 87.1470, 90.9519, 94.8858] +24-11-19 19:24:37 | D | best error = [ 1.3161, 1.3161, 1.3161, 1.3161, 1.3161] +24-11-19 19:24:37 | D | + error = [1.3161] +24-11-19 19:24:37 | D | - Calibrating model.layers.20.mlp.up_proj.weight +24-11-19 19:24:37 | D | + w: sint8 +24-11-19 19:24:37 | D | + x: None +24-11-19 19:24:37 | D | + y: None +24-11-19 19:24:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:24:37 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:24:37 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:24:38 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:24:38 | D | - range ratio = [ 1.0000] +24-11-19 19:24:38 | D | sum error = [ 8.8653] +24-11-19 19:24:38 | D | best error = [ 8.8653] +24-11-19 19:24:39 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:24:39 | D | sum error = [ 8.7907, 8.7807, 8.7993, 8.8913, 9.0736] +24-11-19 19:24:39 | D | best error = [ 8.2411, 8.0054, 7.8695, 7.7956, 7.7557] +24-11-19 19:24:39 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:24:39 | D | sum error = [ 9.3097, 9.6132, 9.9981, 10.4630, 11.0297] +24-11-19 19:24:39 | D | best error = [ 7.7356, 7.7268, 7.7236, 7.7223, 7.7220] +24-11-19 19:24:39 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:24:39 | D | sum error = [ 11.6514, 12.3828, 13.1600, 14.0527, 15.0233] +24-11-19 19:24:39 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 19:24:39 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:24:39 | D | sum error = [ 16.0745, 17.2034, 18.4511, 19.7853, 21.1866] +24-11-19 19:24:39 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 19:24:39 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:24:39 | D | sum error = [ 22.7064, 24.3035, 26.0147, 27.8598, 29.7860] +24-11-19 19:24:39 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 19:24:39 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:24:39 | D | sum error = [ 31.8365, 34.0225, 36.3282, 38.7614, 41.3224] +24-11-19 19:24:39 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 19:24:39 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:24:39 | D | sum error = [ 44.0569, 46.9202, 49.9452, 53.1462, 56.5016] +24-11-19 19:24:39 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 19:24:39 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:24:39 | D | sum error = [ 60.0360, 63.7923, 67.7208, 71.8454, 76.2305] +24-11-19 19:24:39 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 19:24:39 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:24:39 | D | sum error = [ 80.7665, 85.5910, 90.6187, 95.8915, 101.4193] +24-11-19 19:24:39 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 19:24:39 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:24:39 | D | sum error = [ 107.2225, 113.2948, 119.6502, 126.3208, 133.2853] +24-11-19 19:24:39 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 19:24:39 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:24:39 | D | sum error = [ 140.5750, 148.1899, 156.1296, 164.4450, 173.1077] +24-11-19 19:24:39 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 19:24:39 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:24:39 | D | sum error = [ 182.1468, 191.5570, 201.3939, 211.6280, 222.2927] +24-11-19 19:24:39 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 19:24:39 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:24:39 | D | sum error = [ 233.3483, 244.8610, 256.8227, 269.2520, 282.1515] +24-11-19 19:24:39 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 19:24:39 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:24:39 | D | sum error = [ 295.5087, 309.3651, 323.7311, 338.6107, 353.9893] +24-11-19 19:24:39 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 19:24:39 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:24:39 | D | sum error = [ 369.9060, 386.3699, 403.3695, 420.9417, 439.0770] +24-11-19 19:24:39 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 19:24:39 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:24:39 | D | sum error = [ 457.7666, 477.0337, 496.8793, 517.3177, 538.3203] +24-11-19 19:24:39 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 19:24:39 | D | + error = [7.7219] +24-11-19 19:24:39 | D | - Calibrating model.layers.20.mlp.gate_proj.weight +24-11-19 19:24:39 | D | + w: sint8 +24-11-19 19:24:39 | D | + x: None +24-11-19 19:24:39 | D | + y: None +24-11-19 19:24:39 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:24:39 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:24:39 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:24:39 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:24:39 | D | - range ratio = [ 1.0000] +24-11-19 19:24:39 | D | sum error = [ 9.4606] +24-11-19 19:24:39 | D | best error = [ 9.4606] +24-11-19 19:24:40 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:24:40 | D | sum error = [ 9.3631, 9.3589, 9.3922, 9.5035, 9.6871] +24-11-19 19:24:40 | D | best error = [ 8.7995, 8.5405, 8.3998, 8.3216, 8.2800] +24-11-19 19:24:40 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:24:40 | D | sum error = [ 9.9491, 10.2756, 10.6808, 11.2230, 11.8118] +24-11-19 19:24:40 | D | best error = [ 8.2574, 8.2478, 8.2442, 8.2433, 8.2431] +24-11-19 19:24:40 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:24:40 | D | sum error = [ 12.4921, 13.2898, 14.1578, 15.0826, 16.1448] +24-11-19 19:24:40 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 19:24:40 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:24:40 | D | sum error = [ 17.2954, 18.5224, 19.8818, 21.3322, 22.8648] +24-11-19 19:24:40 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 19:24:40 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:24:40 | D | sum error = [ 24.5388, 26.3139, 28.1777, 30.2014, 32.3300] +24-11-19 19:24:40 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 19:24:40 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:24:40 | D | sum error = [ 34.5730, 36.9752, 39.5280, 42.2337, 45.0654] +24-11-19 19:24:40 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 19:24:40 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:24:40 | D | sum error = [ 48.1022, 51.2752, 54.6581, 58.2592, 62.0042] +24-11-19 19:24:40 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 19:24:40 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:24:40 | D | sum error = [ 66.0278, 70.2287, 74.6922, 79.4063, 84.3932] +24-11-19 19:24:40 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 19:24:40 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:24:40 | D | sum error = [ 89.6646, 95.2225, 101.0851, 107.2615, 113.7668] +24-11-19 19:24:40 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 19:24:40 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:24:40 | D | sum error = [ 120.6073, 127.8133, 135.3859, 143.3567, 151.7414] +24-11-19 19:24:40 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 19:24:40 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:24:40 | D | sum error = [ 160.5817, 169.8463, 179.5968, 189.8460, 200.6096] +24-11-19 19:24:40 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 19:24:40 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:24:40 | D | sum error = [ 211.8561, 223.6736, 236.0646, 249.0022, 262.5649] +24-11-19 19:24:40 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 19:24:40 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:24:40 | D | sum error = [ 276.7368, 291.5796, 307.0656, 323.2551, 340.1263] +24-11-19 19:24:40 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 19:24:40 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:24:40 | D | sum error = [ 357.7369, 376.1194, 395.2576, 415.1421, 435.8699] +24-11-19 19:24:40 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 19:24:40 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:24:40 | D | sum error = [ 457.3788, 479.6822, 502.7996, 526.7703, 551.6028] +24-11-19 19:24:40 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 19:24:40 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:24:40 | D | sum error = [ 577.2820, 603.8266, 631.2117, 659.4606, 688.5729] +24-11-19 19:24:40 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 19:24:40 | D | + error = [8.2430] +24-11-19 19:24:40 | D | - Calibrating model.layers.20.mlp.down_proj.weight +24-11-19 19:24:40 | D | + w: sint8 +24-11-19 19:24:40 | D | + x: None +24-11-19 19:24:40 | D | + y: None +24-11-19 19:24:40 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:24:40 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:24:40 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:24:40 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:24:40 | D | - range ratio = [ 1.0000] +24-11-19 19:24:40 | D | sum error = [ 3.4713] +24-11-19 19:24:40 | D | best error = [ 3.4713] +24-11-19 19:24:41 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:24:41 | D | sum error = [ 3.4367, 3.4105, 3.3993, 3.3891, 3.3953] +24-11-19 19:24:41 | D | best error = [ 3.3105, 3.2335, 3.1800, 3.1415, 3.1136] +24-11-19 19:24:41 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:24:41 | D | sum error = [ 3.4134, 3.4467, 3.4994, 3.5597, 3.6437] +24-11-19 19:24:41 | D | best error = [ 3.0928, 3.0765, 3.0650, 3.0555, 3.0490] +24-11-19 19:24:41 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:24:41 | D | sum error = [ 3.7657, 3.8946, 4.0476, 4.2459, 4.4459] +24-11-19 19:24:41 | D | best error = [ 3.0447, 3.0410, 3.0392, 3.0380, 3.0373] +24-11-19 19:24:41 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:24:41 | D | sum error = [ 4.6806, 4.9446, 5.2503, 5.5605, 5.9162] +24-11-19 19:24:41 | D | best error = [ 3.0367, 3.0362, 3.0361, 3.0359, 3.0359] +24-11-19 19:24:41 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:24:41 | D | sum error = [ 6.3004, 6.7239, 7.1719, 7.6589, 8.1863] +24-11-19 19:24:41 | D | best error = [ 3.0358, 3.0358, 3.0358, 3.0358, 3.0358] +24-11-19 19:24:41 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:24:41 | D | sum error = [ 8.7449, 9.3420, 9.9799, 10.6709, 11.4030] +24-11-19 19:24:41 | D | best error = [ 3.0358, 3.0358, 3.0358, 3.0358, 3.0358] +24-11-19 19:24:41 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:24:41 | D | sum error = [ 12.1881, 13.0134, 13.8935, 14.8294, 15.8184] +24-11-19 19:24:41 | D | best error = [ 3.0358, 3.0358, 3.0358, 3.0358, 3.0358] +24-11-19 19:24:41 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:24:41 | D | sum error = [ 16.8833, 17.9864, 19.1779, 20.4159, 21.7391] +24-11-19 19:24:41 | D | best error = [ 3.0358, 3.0358, 3.0358, 3.0358, 3.0358] +24-11-19 19:24:41 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:24:41 | D | sum error = [ 23.1403, 24.6163, 26.1683, 27.8119, 29.5453] +24-11-19 19:24:41 | D | best error = [ 3.0358, 3.0358, 3.0358, 3.0358, 3.0358] +24-11-19 19:24:41 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:24:41 | D | sum error = [ 31.3717, 33.2916, 35.3163, 37.4499, 39.6844] +24-11-19 19:24:41 | D | best error = [ 3.0358, 3.0358, 3.0358, 3.0358, 3.0358] +24-11-19 19:24:41 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:24:41 | D | sum error = [ 42.0395, 44.5101, 47.1018, 49.8299, 52.6788] +24-11-19 19:24:41 | D | best error = [ 3.0358, 3.0358, 3.0358, 3.0358, 3.0358] +24-11-19 19:24:41 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:24:41 | D | sum error = [ 55.6720, 58.8068, 62.0827, 65.5163, 69.1127] +24-11-19 19:24:41 | D | best error = [ 3.0358, 3.0358, 3.0358, 3.0358, 3.0358] +24-11-19 19:24:41 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:24:41 | D | sum error = [ 72.8651, 76.7927, 80.8788, 85.1442, 89.5939] +24-11-19 19:24:41 | D | best error = [ 3.0358, 3.0358, 3.0358, 3.0358, 3.0358] +24-11-19 19:24:41 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:24:41 | D | sum error = [ 94.2209, 99.0431, 104.0570, 109.2762, 114.6914] +24-11-19 19:24:41 | D | best error = [ 3.0358, 3.0358, 3.0358, 3.0358, 3.0358] +24-11-19 19:24:41 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:24:41 | D | sum error = [ 120.3313, 126.1769, 132.2476, 138.5398, 145.0533] +24-11-19 19:24:41 | D | best error = [ 3.0358, 3.0358, 3.0358, 3.0358, 3.0358] +24-11-19 19:24:41 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:24:41 | D | sum error = [ 151.7916, 158.7629, 165.9697, 173.4158, 181.0996] +24-11-19 19:24:41 | D | best error = [ 3.0358, 3.0358, 3.0358, 3.0358, 3.0358] +24-11-19 19:24:41 | D | + error = [3.0358] +24-11-19 19:24:41 | D | - Quantizing model.layers.20.self_attn.q_proj.weight +24-11-19 19:24:42 | D | - Quantizing model.layers.20.self_attn.k_proj.weight +24-11-19 19:24:43 | D | - Quantizing model.layers.20.self_attn.v_proj.weight +24-11-19 19:24:44 | D | - Quantizing model.layers.20.self_attn.o_proj.weight +24-11-19 19:24:45 | D | - Quantizing model.layers.20.mlp.up_proj.weight +24-11-19 19:24:46 | D | - Quantizing model.layers.20.mlp.gate_proj.weight +24-11-19 19:24:47 | D | - Quantizing model.layers.20.mlp.down_proj.weight +24-11-19 19:24:55 | D | - Quantizing layer model.layers.21 +24-11-19 19:24:55 | D | - Calibrating model.layers.21.self_attn.q_proj.weight +24-11-19 19:24:55 | D | + w: sint8 +24-11-19 19:24:55 | D | + x: None +24-11-19 19:24:55 | D | + y: None +24-11-19 19:24:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:24:55 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:24:55 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:24:56 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:24:56 | D | - range ratio = [ 1.0000] +24-11-19 19:24:56 | D | sum error = [ 11.9866] +24-11-19 19:24:56 | D | best error = [ 11.9866] +24-11-19 19:25:09 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:25:09 | D | sum error = [ 11.8281, 11.7541, 11.7702, 11.9590, 12.1799] +24-11-19 19:25:09 | D | best error = [ 11.8281, 11.7541, 11.7541, 11.7541, 11.7541] +24-11-19 19:25:09 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:25:09 | D | sum error = [ 12.6224, 13.0254, 13.6726, 14.2923, 15.0765] +24-11-19 19:25:09 | D | best error = [ 11.7541, 11.7541, 11.7541, 11.7541, 11.7541] +24-11-19 19:25:09 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:25:09 | D | sum error = [ 15.8931, 17.1293, 18.2030, 19.3745, 20.7897] +24-11-19 19:25:09 | D | best error = [ 11.7541, 11.7541, 11.7541, 11.7541, 11.7541] +24-11-19 19:25:09 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:25:09 | D | sum error = [ 22.7386, 24.3770, 26.1409, 28.0676, 30.3720] +24-11-19 19:25:09 | D | best error = [ 11.7541, 11.7541, 11.7541, 11.7541, 11.7541] +24-11-19 19:25:09 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:25:09 | D | sum error = [ 32.6909, 35.4177, 38.1205, 41.1714, 44.0041] +24-11-19 19:25:09 | D | best error = [ 11.7541, 11.7541, 11.7541, 11.7541, 11.7541] +24-11-19 19:25:09 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:25:09 | D | sum error = [ 47.5056, 51.1161, 55.2266, 59.4387, 63.9310] +24-11-19 19:25:09 | D | best error = [ 11.7541, 11.7541, 11.7541, 11.7541, 11.7541] +24-11-19 19:25:09 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:25:09 | D | sum error = [ 68.7509, 73.8783, 79.3628, 85.7369, 92.5663] +24-11-19 19:25:09 | D | best error = [ 11.7541, 11.7541, 11.7541, 11.7541, 11.7541] +24-11-19 19:25:09 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:25:09 | D | sum error = [ 99.1825, 106.8083, 114.7660, 123.7893, 132.7749] +24-11-19 19:25:09 | D | best error = [ 11.7541, 11.7541, 11.7541, 11.7541, 11.7541] +24-11-19 19:25:09 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:25:09 | D | sum error = [ 143.0949, 153.8987, 165.6710, 178.4276, 191.6968] +24-11-19 19:25:09 | D | best error = [ 11.7541, 11.7541, 11.7541, 11.7541, 11.7541] +24-11-19 19:25:09 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:25:09 | D | sum error = [ 206.7937, 222.5388, 239.9955, 258.7355, 278.8276] +24-11-19 19:25:09 | D | best error = [ 11.7541, 11.7541, 11.7541, 11.7541, 11.7541] +24-11-19 19:25:09 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:25:09 | D | sum error = [ 301.2798, 324.6054, 350.2767, 377.1628, 407.3763] +24-11-19 19:25:09 | D | best error = [ 11.7541, 11.7541, 11.7541, 11.7541, 11.7541] +24-11-19 19:25:09 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:25:09 | D | sum error = [ 438.9197, 474.2359, 511.6656, 553.0627, 598.2184] +24-11-19 19:25:09 | D | best error = [ 11.7541, 11.7541, 11.7541, 11.7541, 11.7541] +24-11-19 19:25:09 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:25:09 | D | sum error = [ 647.5859, 701.1198, 759.9303, 824.0659, 894.1339] +24-11-19 19:25:09 | D | best error = [ 11.7541, 11.7541, 11.7541, 11.7541, 11.7541] +24-11-19 19:25:09 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:25:09 | D | sum error = [ 971.0573, 1055.5213, 1147.7271, 1250.0414, 1361.9391] +24-11-19 19:25:09 | D | best error = [ 11.7541, 11.7541, 11.7541, 11.7541, 11.7541] +24-11-19 19:25:09 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:25:09 | D | sum error = [ 1486.1204, 1621.4267, 1772.6366, 1939.0771, 2121.9896] +24-11-19 19:25:09 | D | best error = [ 11.7541, 11.7541, 11.7541, 11.7541, 11.7541] +24-11-19 19:25:09 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:25:09 | D | sum error = [ 2323.3741, 2542.9821, 2783.6736, 3043.7973, 3323.3593] +24-11-19 19:25:09 | D | best error = [ 11.7541, 11.7541, 11.7541, 11.7541, 11.7541] +24-11-19 19:25:09 | D | + error = [11.7541] +24-11-19 19:25:09 | D | - Calibrating model.layers.21.self_attn.k_proj.weight +24-11-19 19:25:09 | D | + w: sint8 +24-11-19 19:25:09 | D | + x: None +24-11-19 19:25:09 | D | + y: None +24-11-19 19:25:09 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:25:09 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:25:09 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:25:09 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:25:10 | D | - range ratio = [ 1.0000] +24-11-19 19:25:10 | D | sum error = [ 13.8416] +24-11-19 19:25:10 | D | best error = [ 13.8416] +24-11-19 19:25:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:25:22 | D | sum error = [ 14.4208, 12.9454, 13.5944, 14.2178, 14.2845] +24-11-19 19:25:22 | D | best error = [ 13.8416, 12.9454, 12.9454, 12.9454, 12.9454] +24-11-19 19:25:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:25:22 | D | sum error = [ 15.7810, 14.8908, 15.4148, 16.1484, 16.7428] +24-11-19 19:25:22 | D | best error = [ 12.9454, 12.9454, 12.9454, 12.9454, 12.9454] +24-11-19 19:25:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:25:22 | D | sum error = [ 18.5232, 20.2263, 20.7328, 23.2894, 24.1877] +24-11-19 19:25:22 | D | best error = [ 12.9454, 12.9454, 12.9454, 12.9454, 12.9454] +24-11-19 19:25:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:25:22 | D | sum error = [ 26.8170, 28.6895, 30.1315, 34.3806, 35.6808] +24-11-19 19:25:22 | D | best error = [ 12.9454, 12.9454, 12.9454, 12.9454, 12.9454] +24-11-19 19:25:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:25:22 | D | sum error = [ 37.5742, 40.9730, 45.4950, 47.9289, 52.7542] +24-11-19 19:25:22 | D | best error = [ 12.9454, 12.9454, 12.9454, 12.9454, 12.9454] +24-11-19 19:25:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:25:22 | D | sum error = [ 55.8132, 59.7924, 65.2540, 68.6365, 73.1911] +24-11-19 19:25:22 | D | best error = [ 12.9454, 12.9454, 12.9454, 12.9454, 12.9454] +24-11-19 19:25:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:25:22 | D | sum error = [ 79.5166, 86.7540, 92.1463, 98.8196, 107.0677] +24-11-19 19:25:22 | D | best error = [ 12.9454, 12.9454, 12.9454, 12.9454, 12.9454] +24-11-19 19:25:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:25:22 | D | sum error = [ 113.8891, 122.5158, 131.6457, 142.8470, 151.5179] +24-11-19 19:25:22 | D | best error = [ 12.9454, 12.9454, 12.9454, 12.9454, 12.9454] +24-11-19 19:25:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:25:22 | D | sum error = [ 162.3483, 175.6074, 188.4279, 201.5157, 215.1043] +24-11-19 19:25:22 | D | best error = [ 12.9454, 12.9454, 12.9454, 12.9454, 12.9454] +24-11-19 19:25:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:25:22 | D | sum error = [ 231.6356, 248.4124, 266.5503, 285.8302, 308.4940] +24-11-19 19:25:22 | D | best error = [ 12.9454, 12.9454, 12.9454, 12.9454, 12.9454] +24-11-19 19:25:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:25:22 | D | sum error = [ 331.8481, 354.3796, 382.1007, 408.9556, 441.6332] +24-11-19 19:25:22 | D | best error = [ 12.9454, 12.9454, 12.9454, 12.9454, 12.9454] +24-11-19 19:25:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:25:22 | D | sum error = [ 475.2607, 512.6591, 551.6308, 597.5971, 644.1121] +24-11-19 19:25:22 | D | best error = [ 12.9454, 12.9454, 12.9454, 12.9454, 12.9454] +24-11-19 19:25:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:25:22 | D | sum error = [ 693.4847, 749.9110, 808.9417, 877.5213, 948.9040] +24-11-19 19:25:22 | D | best error = [ 12.9454, 12.9454, 12.9454, 12.9454, 12.9454] +24-11-19 19:25:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:25:22 | D | sum error = [ 1028.1988, 1117.8862, 1207.6523, 1308.4780, 1426.2989] +24-11-19 19:25:22 | D | best error = [ 12.9454, 12.9454, 12.9454, 12.9454, 12.9454] +24-11-19 19:25:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:25:22 | D | sum error = [ 1560.2041, 1698.2384, 1856.9029, 2022.4965, 2202.1072] +24-11-19 19:25:22 | D | best error = [ 12.9454, 12.9454, 12.9454, 12.9454, 12.9454] +24-11-19 19:25:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:25:22 | D | sum error = [ 2422.8241, 2644.5754, 2888.1419, 3154.2841, 3438.9927] +24-11-19 19:25:22 | D | best error = [ 12.9454, 12.9454, 12.9454, 12.9454, 12.9454] +24-11-19 19:25:22 | D | + error = [12.9454] +24-11-19 19:25:22 | D | - Calibrating model.layers.21.self_attn.v_proj.weight +24-11-19 19:25:22 | D | + w: sint8 +24-11-19 19:25:22 | D | + x: None +24-11-19 19:25:22 | D | + y: None +24-11-19 19:25:22 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:25:22 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:25:22 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:25:22 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:25:22 | D | - range ratio = [ 1.0000] +24-11-19 19:25:22 | D | sum error = [ 6.8644] +24-11-19 19:25:22 | D | best error = [ 6.8644] +24-11-19 19:25:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:25:23 | D | sum error = [ 6.7995, 6.8021, 6.8280, 6.8793, 7.0114] +24-11-19 19:25:23 | D | best error = [ 6.4110, 6.2229, 6.1236, 6.0671, 6.0377] +24-11-19 19:25:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:25:23 | D | sum error = [ 7.1781, 7.4559, 7.7364, 8.0925, 8.5118] +24-11-19 19:25:23 | D | best error = [ 6.0212, 6.0134, 6.0106, 6.0093, 6.0093] +24-11-19 19:25:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:25:23 | D | sum error = [ 9.0165, 9.5812, 10.1963, 10.9046, 11.6104] +24-11-19 19:25:23 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 19:25:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:25:23 | D | sum error = [ 12.4523, 13.3142, 14.2450, 15.2726, 16.3762] +24-11-19 19:25:23 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 19:25:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:25:23 | D | sum error = [ 17.5315, 18.7748, 20.1116, 21.5343, 23.0043] +24-11-19 19:25:23 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 19:25:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:25:23 | D | sum error = [ 24.5833, 26.2312, 27.9947, 29.8758, 31.8156] +24-11-19 19:25:23 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 19:25:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:25:23 | D | sum error = [ 33.8870, 36.0874, 38.3480, 40.7743, 43.3334] +24-11-19 19:25:23 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 19:25:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:25:23 | D | sum error = [ 45.9982, 48.8285, 51.7802, 54.8838, 58.1195] +24-11-19 19:25:23 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 19:25:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:25:23 | D | sum error = [ 61.5669, 65.1576, 68.9274, 72.8476, 76.9743] +24-11-19 19:25:23 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 19:25:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:25:23 | D | sum error = [ 81.2860, 85.7951, 90.5050, 95.4164, 100.5750] +24-11-19 19:25:23 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 19:25:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:25:23 | D | sum error = [ 105.9165, 111.5185, 117.3646, 123.4396, 129.7795] +24-11-19 19:25:23 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 19:25:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:25:23 | D | sum error = [ 136.3743, 143.2217, 150.3615, 157.7703, 165.4515] +24-11-19 19:25:23 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 19:25:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:25:23 | D | sum error = [ 173.4324, 181.7046, 190.2707, 199.1561, 208.3571] +24-11-19 19:25:23 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 19:25:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:25:23 | D | sum error = [ 217.8732, 227.7365, 237.9256, 248.4675, 259.3373] +24-11-19 19:25:23 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 19:25:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:25:23 | D | sum error = [ 270.5376, 282.0953, 294.0316, 306.3224, 318.9792] +24-11-19 19:25:23 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 19:25:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:25:23 | D | sum error = [ 332.0064, 345.4083, 359.1927, 373.3705, 387.9375] +24-11-19 19:25:23 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 19:25:23 | D | + error = [6.0092] +24-11-19 19:25:23 | D | - Calibrating model.layers.21.self_attn.o_proj.weight +24-11-19 19:25:23 | D | + w: sint8 +24-11-19 19:25:23 | D | + x: None +24-11-19 19:25:23 | D | + y: None +24-11-19 19:25:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:25:23 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:25:23 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:25:23 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:25:23 | D | - range ratio = [ 1.0000] +24-11-19 19:25:23 | D | sum error = [ 1.3078] +24-11-19 19:25:23 | D | best error = [ 1.3078] +24-11-19 19:25:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:25:23 | D | sum error = [ 1.2977, 1.2921, 1.2942, 1.2999, 1.3198] +24-11-19 19:25:23 | D | best error = [ 1.2232, 1.1854, 1.1625, 1.1471, 1.1379] +24-11-19 19:25:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:25:23 | D | sum error = [ 1.3549, 1.3893, 1.4382, 1.4959, 1.5669] +24-11-19 19:25:23 | D | best error = [ 1.1320, 1.1280, 1.1252, 1.1236, 1.1224] +24-11-19 19:25:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:25:23 | D | sum error = [ 1.6503, 1.7424, 1.8441, 1.9683, 2.0887] +24-11-19 19:25:23 | D | best error = [ 1.1217, 1.1213, 1.1210, 1.1208, 1.1207] +24-11-19 19:25:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:25:23 | D | sum error = [ 2.2327, 2.3764, 2.5520, 2.7316, 2.9163] +24-11-19 19:25:23 | D | best error = [ 1.1207, 1.1205, 1.1205, 1.1205, 1.1204] +24-11-19 19:25:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:25:23 | D | sum error = [ 3.1258, 3.3391, 3.5661, 3.8171, 4.0799] +24-11-19 19:25:23 | D | best error = [ 1.1204, 1.1204, 1.1204, 1.1204, 1.1204] +24-11-19 19:25:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:25:23 | D | sum error = [ 4.3562, 4.6547, 4.9702, 5.2998, 5.6498] +24-11-19 19:25:23 | D | best error = [ 1.1204, 1.1204, 1.1204, 1.1204, 1.1204] +24-11-19 19:25:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:25:23 | D | sum error = [ 6.0201, 6.4129, 6.8316, 7.2696, 7.7303] +24-11-19 19:25:23 | D | best error = [ 1.1204, 1.1204, 1.1204, 1.1204, 1.1204] +24-11-19 19:25:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:25:23 | D | sum error = [ 8.2143, 8.7282, 9.2709, 9.8411, 10.4442] +24-11-19 19:25:23 | D | best error = [ 1.1204, 1.1204, 1.1204, 1.1204, 1.1204] +24-11-19 19:25:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:25:23 | D | sum error = [ 11.0729, 11.7348, 12.4338, 13.1684, 13.9366] +24-11-19 19:25:23 | D | best error = [ 1.1204, 1.1204, 1.1204, 1.1204, 1.1204] +24-11-19 19:25:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:25:23 | D | sum error = [ 14.7446, 15.5927, 16.4792, 17.4172, 18.3954] +24-11-19 19:25:23 | D | best error = [ 1.1204, 1.1204, 1.1204, 1.1204, 1.1204] +24-11-19 19:25:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:25:23 | D | sum error = [ 19.4132, 20.4843, 21.6031, 22.7721, 23.9957] +24-11-19 19:25:23 | D | best error = [ 1.1204, 1.1204, 1.1204, 1.1204, 1.1204] +24-11-19 19:25:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:25:23 | D | sum error = [ 25.2727, 26.6061, 27.9981, 29.4502, 30.9642] +24-11-19 19:25:23 | D | best error = [ 1.1204, 1.1204, 1.1204, 1.1204, 1.1204] +24-11-19 19:25:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:25:23 | D | sum error = [ 32.5434, 34.1877, 35.9036, 37.6825, 39.5345] +24-11-19 19:25:23 | D | best error = [ 1.1204, 1.1204, 1.1204, 1.1204, 1.1204] +24-11-19 19:25:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:25:23 | D | sum error = [ 41.4592, 43.4605, 45.5369, 47.6946, 49.9248] +24-11-19 19:25:23 | D | best error = [ 1.1204, 1.1204, 1.1204, 1.1204, 1.1204] +24-11-19 19:25:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:25:23 | D | sum error = [ 52.2421, 54.6398, 57.1252, 59.6915, 62.3433] +24-11-19 19:25:23 | D | best error = [ 1.1204, 1.1204, 1.1204, 1.1204, 1.1204] +24-11-19 19:25:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:25:23 | D | sum error = [ 65.0835, 67.9127, 70.8355, 73.8481, 76.9543] +24-11-19 19:25:23 | D | best error = [ 1.1204, 1.1204, 1.1204, 1.1204, 1.1204] +24-11-19 19:25:23 | D | + error = [1.1204] +24-11-19 19:25:24 | D | - Calibrating model.layers.21.mlp.up_proj.weight +24-11-19 19:25:24 | D | + w: sint8 +24-11-19 19:25:24 | D | + x: None +24-11-19 19:25:24 | D | + y: None +24-11-19 19:25:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:25:24 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:25:24 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:25:24 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:25:24 | D | - range ratio = [ 1.0000] +24-11-19 19:25:24 | D | sum error = [ 9.1198] +24-11-19 19:25:24 | D | best error = [ 9.1198] +24-11-19 19:25:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:25:25 | D | sum error = [ 9.0838, 9.0520, 9.0977, 9.1813, 9.3563] +24-11-19 19:25:25 | D | best error = [ 8.5042, 8.2546, 8.1234, 8.0429, 7.9983] +24-11-19 19:25:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:25:25 | D | sum error = [ 9.6173, 9.9372, 10.3391, 10.8012, 11.3553] +24-11-19 19:25:25 | D | best error = [ 7.9773, 7.9679, 7.9639, 7.9624, 7.9623] +24-11-19 19:25:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:25:25 | D | sum error = [ 12.0435, 12.7858, 13.6292, 14.5403, 15.5514] +24-11-19 19:25:25 | D | best error = [ 7.9622, 7.9622, 7.9622, 7.9622, 7.9622] +24-11-19 19:25:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:25:25 | D | sum error = [ 16.6607, 17.8375, 19.1385, 20.4913, 21.9805] +24-11-19 19:25:25 | D | best error = [ 7.9622, 7.9622, 7.9622, 7.9622, 7.9622] +24-11-19 19:25:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:25:25 | D | sum error = [ 23.5636, 25.2178, 26.9867, 28.8987, 30.9344] +24-11-19 19:25:25 | D | best error = [ 7.9622, 7.9622, 7.9622, 7.9622, 7.9622] +24-11-19 19:25:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:25:25 | D | sum error = [ 33.0459, 35.2856, 37.6697, 40.1969, 42.8537] +24-11-19 19:25:25 | D | best error = [ 7.9622, 7.9622, 7.9622, 7.9622, 7.9622] +24-11-19 19:25:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:25:25 | D | sum error = [ 45.6564, 48.6105, 51.7277, 55.0164, 58.4976] +24-11-19 19:25:25 | D | best error = [ 7.9622, 7.9622, 7.9622, 7.9622, 7.9622] +24-11-19 19:25:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:25:25 | D | sum error = [ 62.1340, 65.9476, 69.9992, 74.2598, 78.7266] +24-11-19 19:25:25 | D | best error = [ 7.9622, 7.9622, 7.9622, 7.9622, 7.9622] +24-11-19 19:25:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:25:25 | D | sum error = [ 83.4108, 88.3309, 93.4764, 98.9135, 104.6086] +24-11-19 19:25:25 | D | best error = [ 7.9622, 7.9622, 7.9622, 7.9622, 7.9622] +24-11-19 19:25:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:25:25 | D | sum error = [ 110.5559, 116.8094, 123.3358, 130.1741, 137.3206] +24-11-19 19:25:25 | D | best error = [ 7.9622, 7.9622, 7.9622, 7.9622, 7.9622] +24-11-19 19:25:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:25:25 | D | sum error = [ 144.7676, 152.5847, 160.7211, 169.2182, 178.0561] +24-11-19 19:25:25 | D | best error = [ 7.9622, 7.9622, 7.9622, 7.9622, 7.9622] +24-11-19 19:25:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:25:25 | D | sum error = [ 187.3026, 196.9315, 206.9478, 217.3834, 228.2507] +24-11-19 19:25:25 | D | best error = [ 7.9622, 7.9622, 7.9622, 7.9622, 7.9622] +24-11-19 19:25:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:25:25 | D | sum error = [ 239.5389, 251.2717, 263.4630, 276.1193, 289.2521] +24-11-19 19:25:25 | D | best error = [ 7.9622, 7.9622, 7.9622, 7.9622, 7.9622] +24-11-19 19:25:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:25:25 | D | sum error = [ 302.8742, 316.9890, 331.6049, 346.7412, 362.3970] +24-11-19 19:25:25 | D | best error = [ 7.9622, 7.9622, 7.9622, 7.9622, 7.9622] +24-11-19 19:25:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:25:25 | D | sum error = [ 378.5923, 395.3339, 412.6006, 430.4172, 448.7769] +24-11-19 19:25:25 | D | best error = [ 7.9622, 7.9622, 7.9622, 7.9622, 7.9622] +24-11-19 19:25:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:25:25 | D | sum error = [ 467.7063, 487.1852, 507.2479, 527.8788, 549.1039] +24-11-19 19:25:25 | D | best error = [ 7.9622, 7.9622, 7.9622, 7.9622, 7.9622] +24-11-19 19:25:25 | D | + error = [7.9622] +24-11-19 19:25:25 | D | - Calibrating model.layers.21.mlp.gate_proj.weight +24-11-19 19:25:25 | D | + w: sint8 +24-11-19 19:25:25 | D | + x: None +24-11-19 19:25:25 | D | + y: None +24-11-19 19:25:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:25:25 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:25:25 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:25:25 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:25:25 | D | - range ratio = [ 1.0000] +24-11-19 19:25:25 | D | sum error = [ 9.8574] +24-11-19 19:25:25 | D | best error = [ 9.8574] +24-11-19 19:25:26 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:25:26 | D | sum error = [ 9.7581, 9.7542, 9.7944, 9.8991, 10.0855] +24-11-19 19:25:26 | D | best error = [ 9.1685, 8.9014, 8.7468, 8.6643, 8.6188] +24-11-19 19:25:26 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:25:26 | D | sum error = [ 10.3642, 10.7094, 11.1392, 11.6684, 12.2968] +24-11-19 19:25:26 | D | best error = [ 8.5958, 8.5857, 8.5819, 8.5803, 8.5797] +24-11-19 19:25:26 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:25:26 | D | sum error = [ 13.0140, 13.7863, 14.7243, 15.7218, 16.8090] +24-11-19 19:25:26 | D | best error = [ 8.5796, 8.5795, 8.5794, 8.5794, 8.5794] +24-11-19 19:25:26 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:25:26 | D | sum error = [ 18.0291, 19.3381, 20.7017, 22.2035, 23.7939] +24-11-19 19:25:26 | D | best error = [ 8.5794, 8.5794, 8.5794, 8.5794, 8.5794] +24-11-19 19:25:26 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:25:26 | D | sum error = [ 25.5313, 27.3885, 29.3225, 31.3945, 33.6078] +24-11-19 19:25:26 | D | best error = [ 8.5794, 8.5794, 8.5794, 8.5794, 8.5794] +24-11-19 19:25:26 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:25:26 | D | sum error = [ 35.9342, 38.4198, 41.0615, 43.8497, 46.8177] +24-11-19 19:25:26 | D | best error = [ 8.5794, 8.5794, 8.5794, 8.5794, 8.5794] +24-11-19 19:25:26 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:25:26 | D | sum error = [ 49.9498, 53.2131, 56.7299, 60.4158, 64.3279] +24-11-19 19:25:26 | D | best error = [ 8.5794, 8.5794, 8.5794, 8.5794, 8.5794] +24-11-19 19:25:26 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:25:26 | D | sum error = [ 68.4499, 72.7784, 77.3719, 82.2295, 87.3258] +24-11-19 19:25:26 | D | best error = [ 8.5794, 8.5794, 8.5794, 8.5794, 8.5794] +24-11-19 19:25:26 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:25:26 | D | sum error = [ 92.7397, 98.4139, 104.4259, 110.7292, 117.3709] +24-11-19 19:25:26 | D | best error = [ 8.5794, 8.5794, 8.5794, 8.5794, 8.5794] +24-11-19 19:25:26 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:25:26 | D | sum error = [ 124.3540, 131.7213, 139.4452, 147.5719, 156.1298] +24-11-19 19:25:26 | D | best error = [ 8.5794, 8.5794, 8.5794, 8.5794, 8.5794] +24-11-19 19:25:26 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:25:26 | D | sum error = [ 165.1128, 174.5639, 184.4536, 194.8503, 205.7482] +24-11-19 19:25:26 | D | best error = [ 8.5794, 8.5794, 8.5794, 8.5794, 8.5794] +24-11-19 19:25:26 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:25:26 | D | sum error = [ 217.1627, 229.1184, 241.6565, 254.7690, 268.5015] +24-11-19 19:25:26 | D | best error = [ 8.5794, 8.5794, 8.5794, 8.5794, 8.5794] +24-11-19 19:25:26 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:25:26 | D | sum error = [ 282.8421, 297.8334, 313.4911, 329.8097, 346.8051] +24-11-19 19:25:26 | D | best error = [ 8.5794, 8.5794, 8.5794, 8.5794, 8.5794] +24-11-19 19:25:26 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:25:26 | D | sum error = [ 364.5392, 382.9851, 402.1744, 422.1404, 442.8901] +24-11-19 19:25:26 | D | best error = [ 8.5794, 8.5794, 8.5794, 8.5794, 8.5794] +24-11-19 19:25:26 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:25:26 | D | sum error = [ 464.4080, 486.7300, 509.8719, 533.8220, 558.6129] +24-11-19 19:25:26 | D | best error = [ 8.5794, 8.5794, 8.5794, 8.5794, 8.5794] +24-11-19 19:25:26 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:25:26 | D | sum error = [ 584.2231, 610.6847, 637.9795, 666.1279, 695.1006] +24-11-19 19:25:26 | D | best error = [ 8.5794, 8.5794, 8.5794, 8.5794, 8.5794] +24-11-19 19:25:26 | D | + error = [8.5794] +24-11-19 19:25:26 | D | - Calibrating model.layers.21.mlp.down_proj.weight +24-11-19 19:25:26 | D | + w: sint8 +24-11-19 19:25:26 | D | + x: None +24-11-19 19:25:26 | D | + y: None +24-11-19 19:25:26 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:25:26 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:25:26 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:25:26 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:25:26 | D | - range ratio = [ 1.0000] +24-11-19 19:25:26 | D | sum error = [ 3.5337] +24-11-19 19:25:26 | D | best error = [ 3.5337] +24-11-19 19:25:27 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:25:27 | D | sum error = [ 3.5089, 3.4773, 3.4575, 3.4541, 3.4518] +24-11-19 19:25:27 | D | best error = [ 3.3740, 3.2956, 3.2414, 3.2034, 3.1736] +24-11-19 19:25:27 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:25:27 | D | sum error = [ 3.4713, 3.4931, 3.5501, 3.6073, 3.6865] +24-11-19 19:25:27 | D | best error = [ 3.1519, 3.1335, 3.1214, 3.1122, 3.1053] +24-11-19 19:25:27 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:25:27 | D | sum error = [ 3.7920, 3.9185, 4.0714, 4.2427, 4.4385] +24-11-19 19:25:27 | D | best error = [ 3.1014, 3.0985, 3.0965, 3.0955, 3.0944] +24-11-19 19:25:27 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:25:27 | D | sum error = [ 4.6676, 4.9250, 5.2203, 5.5260, 5.8771] +24-11-19 19:25:27 | D | best error = [ 3.0938, 3.0936, 3.0935, 3.0934, 3.0933] +24-11-19 19:25:27 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:25:27 | D | sum error = [ 6.2602, 6.6663, 7.1179, 7.6076, 8.1327] +24-11-19 19:25:27 | D | best error = [ 3.0933, 3.0933, 3.0933, 3.0933, 3.0933] +24-11-19 19:25:27 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:25:27 | D | sum error = [ 8.6820, 9.2909, 9.9262, 10.6183, 11.3485] +24-11-19 19:25:27 | D | best error = [ 3.0933, 3.0933, 3.0933, 3.0933, 3.0933] +24-11-19 19:25:27 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:25:27 | D | sum error = [ 12.1374, 12.9732, 13.8652, 14.8117, 15.8166] +24-11-19 19:25:27 | D | best error = [ 3.0933, 3.0933, 3.0933, 3.0933, 3.0933] +24-11-19 19:25:27 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:25:27 | D | sum error = [ 16.8929, 18.0298, 19.2421, 20.5119, 21.8661] +24-11-19 19:25:27 | D | best error = [ 3.0933, 3.0933, 3.0933, 3.0933, 3.0933] +24-11-19 19:25:27 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:25:27 | D | sum error = [ 23.2926, 24.8020, 26.3997, 28.0843, 29.8571] +24-11-19 19:25:27 | D | best error = [ 3.0933, 3.0933, 3.0933, 3.0933, 3.0933] +24-11-19 19:25:27 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:25:27 | D | sum error = [ 31.7299, 33.6970, 35.7738, 37.9574, 40.2494] +24-11-19 19:25:27 | D | best error = [ 3.0933, 3.0933, 3.0933, 3.0933, 3.0933] +24-11-19 19:25:27 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:25:27 | D | sum error = [ 42.6594, 45.1939, 47.8489, 50.6429, 53.5596] +24-11-19 19:25:27 | D | best error = [ 3.0933, 3.0933, 3.0933, 3.0933, 3.0933] +24-11-19 19:25:27 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:25:27 | D | sum error = [ 56.6243, 59.8234, 63.1828, 66.6905, 70.3510] +24-11-19 19:25:27 | D | best error = [ 3.0933, 3.0933, 3.0933, 3.0933, 3.0933] +24-11-19 19:25:27 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:25:27 | D | sum error = [ 74.1821, 78.1741, 82.3471, 86.6879, 91.2231] +24-11-19 19:25:27 | D | best error = [ 3.0933, 3.0933, 3.0933, 3.0933, 3.0933] +24-11-19 19:25:27 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:25:27 | D | sum error = [ 95.9395, 100.8514, 105.9602, 111.2850, 116.7886] +24-11-19 19:25:27 | D | best error = [ 3.0933, 3.0933, 3.0933, 3.0933, 3.0933] +24-11-19 19:25:27 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:25:27 | D | sum error = [ 122.5101, 128.4463, 134.6088, 140.9875, 147.5936] +24-11-19 19:25:27 | D | best error = [ 3.0933, 3.0933, 3.0933, 3.0933, 3.0933] +24-11-19 19:25:27 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:25:27 | D | sum error = [ 154.4281, 161.4955, 168.7934, 176.3322, 184.1049] +24-11-19 19:25:27 | D | best error = [ 3.0933, 3.0933, 3.0933, 3.0933, 3.0933] +24-11-19 19:25:27 | D | + error = [3.0933] +24-11-19 19:25:27 | D | - Quantizing model.layers.21.self_attn.q_proj.weight +24-11-19 19:25:28 | D | - Quantizing model.layers.21.self_attn.k_proj.weight +24-11-19 19:25:29 | D | - Quantizing model.layers.21.self_attn.v_proj.weight +24-11-19 19:25:30 | D | - Quantizing model.layers.21.self_attn.o_proj.weight +24-11-19 19:25:31 | D | - Quantizing model.layers.21.mlp.up_proj.weight +24-11-19 19:25:32 | D | - Quantizing model.layers.21.mlp.gate_proj.weight +24-11-19 19:25:33 | D | - Quantizing model.layers.21.mlp.down_proj.weight +24-11-19 19:25:41 | D | - Quantizing layer model.layers.22 +24-11-19 19:25:41 | D | - Calibrating model.layers.22.self_attn.q_proj.weight +24-11-19 19:25:41 | D | + w: sint8 +24-11-19 19:25:41 | D | + x: None +24-11-19 19:25:41 | D | + y: None +24-11-19 19:25:41 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:25:41 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:25:41 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:25:42 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:25:42 | D | - range ratio = [ 1.0000] +24-11-19 19:25:42 | D | sum error = [ 13.8056] +24-11-19 19:25:42 | D | best error = [ 13.8056] +24-11-19 19:25:54 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:25:54 | D | sum error = [ 13.4341, 13.5134, 13.5344, 13.9007, 13.7957] +24-11-19 19:25:54 | D | best error = [ 13.4341, 13.4341, 13.4341, 13.4341, 13.4341] +24-11-19 19:25:54 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:25:54 | D | sum error = [ 14.3548, 14.6849, 15.4488, 16.2880, 17.1529] +24-11-19 19:25:54 | D | best error = [ 13.4341, 13.4341, 13.4341, 13.4341, 13.4341] +24-11-19 19:25:54 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:25:54 | D | sum error = [ 17.9408, 19.0095, 20.6540, 21.7466, 23.4535] +24-11-19 19:25:54 | D | best error = [ 13.4341, 13.4341, 13.4341, 13.4341, 13.4341] +24-11-19 19:25:54 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:25:54 | D | sum error = [ 24.8228, 26.9557, 28.9846, 31.2571, 34.0447] +24-11-19 19:25:54 | D | best error = [ 13.4341, 13.4341, 13.4341, 13.4341, 13.4341] +24-11-19 19:25:54 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:25:54 | D | sum error = [ 36.4074, 39.5674, 42.3919, 45.8701, 49.6381] +24-11-19 19:25:54 | D | best error = [ 13.4341, 13.4341, 13.4341, 13.4341, 13.4341] +24-11-19 19:25:54 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:25:54 | D | sum error = [ 53.7207, 57.8569, 62.2898, 67.3720, 72.3356] +24-11-19 19:25:54 | D | best error = [ 13.4341, 13.4341, 13.4341, 13.4341, 13.4341] +24-11-19 19:25:54 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:25:54 | D | sum error = [ 78.1356, 84.5281, 90.9975, 98.4793, 105.8879] +24-11-19 19:25:54 | D | best error = [ 13.4341, 13.4341, 13.4341, 13.4341, 13.4341] +24-11-19 19:25:54 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:25:54 | D | sum error = [ 114.6741, 123.2374, 132.6416, 143.3464, 154.1825] +24-11-19 19:25:54 | D | best error = [ 13.4341, 13.4341, 13.4341, 13.4341, 13.4341] +24-11-19 19:25:54 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:25:54 | D | sum error = [ 166.1642, 178.9190, 192.8792, 207.6546, 223.7874] +24-11-19 19:25:54 | D | best error = [ 13.4341, 13.4341, 13.4341, 13.4341, 13.4341] +24-11-19 19:25:54 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:25:54 | D | sum error = [ 240.8428, 259.4263, 279.6176, 300.4847, 323.4240] +24-11-19 19:25:54 | D | best error = [ 13.4341, 13.4341, 13.4341, 13.4341, 13.4341] +24-11-19 19:25:54 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:25:54 | D | sum error = [ 347.8307, 374.3390, 403.8049, 434.5132, 468.1953] +24-11-19 19:25:54 | D | best error = [ 13.4341, 13.4341, 13.4341, 13.4341, 13.4341] +24-11-19 19:25:54 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:25:54 | D | sum error = [ 504.8316, 543.9710, 586.5635, 632.5083, 681.8825] +24-11-19 19:25:54 | D | best error = [ 13.4341, 13.4341, 13.4341, 13.4341, 13.4341] +24-11-19 19:25:54 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:25:54 | D | sum error = [ 736.6863, 795.7457, 861.5978, 931.4714, 1008.7108] +24-11-19 19:25:54 | D | best error = [ 13.4341, 13.4341, 13.4341, 13.4341, 13.4341] +24-11-19 19:25:54 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:25:54 | D | sum error = [ 1094.0572, 1186.7951, 1290.1473, 1401.6596, 1525.2424] +24-11-19 19:25:54 | D | best error = [ 13.4341, 13.4341, 13.4341, 13.4341, 13.4341] +24-11-19 19:25:54 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:25:54 | D | sum error = [ 1661.4011, 1809.1050, 1973.8808, 2154.6183, 2351.8112] +24-11-19 19:25:54 | D | best error = [ 13.4341, 13.4341, 13.4341, 13.4341, 13.4341] +24-11-19 19:25:54 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:25:54 | D | sum error = [ 2568.5496, 2807.1624, 3063.9662, 3345.3622, 3647.7400] +24-11-19 19:25:54 | D | best error = [ 13.4341, 13.4341, 13.4341, 13.4341, 13.4341] +24-11-19 19:25:54 | D | + error = [13.4341] +24-11-19 19:25:55 | D | - Calibrating model.layers.22.self_attn.k_proj.weight +24-11-19 19:25:55 | D | + w: sint8 +24-11-19 19:25:55 | D | + x: None +24-11-19 19:25:55 | D | + y: None +24-11-19 19:25:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:25:55 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:25:55 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:25:55 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:25:55 | D | - range ratio = [ 1.0000] +24-11-19 19:25:55 | D | sum error = [ 15.7808] +24-11-19 19:25:55 | D | best error = [ 15.7808] +24-11-19 19:26:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:26:08 | D | sum error = [ 17.4953, 17.2447, 16.4450, 17.1014, 19.2438] +24-11-19 19:26:08 | D | best error = [ 15.7808, 15.7808, 15.7808, 15.7808, 15.7808] +24-11-19 19:26:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:26:08 | D | sum error = [ 16.9188, 19.1645, 17.9878, 18.8511, 23.6142] +24-11-19 19:26:08 | D | best error = [ 15.7808, 15.7808, 15.7808, 15.7808, 15.7808] +24-11-19 19:26:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:26:08 | D | sum error = [ 21.2571, 24.2697, 24.1119, 26.3866, 28.4585] +24-11-19 19:26:08 | D | best error = [ 15.7808, 15.7808, 15.7808, 15.7808, 15.7808] +24-11-19 19:26:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:26:08 | D | sum error = [ 31.0627, 32.8429, 34.2002, 37.3406, 41.8861] +24-11-19 19:26:08 | D | best error = [ 15.7808, 15.7808, 15.7808, 15.7808, 15.7808] +24-11-19 19:26:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:26:08 | D | sum error = [ 43.3805, 47.7248, 48.8736, 53.0044, 58.4659] +24-11-19 19:26:08 | D | best error = [ 15.7808, 15.7808, 15.7808, 15.7808, 15.7808] +24-11-19 19:26:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:26:08 | D | sum error = [ 62.2846, 66.4142, 70.5846, 78.4012, 82.5693] +24-11-19 19:26:08 | D | best error = [ 15.7808, 15.7808, 15.7808, 15.7808, 15.7808] +24-11-19 19:26:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:26:08 | D | sum error = [ 89.1237, 94.5786, 102.2175, 113.4711, 120.2160] +24-11-19 19:26:08 | D | best error = [ 15.7808, 15.7808, 15.7808, 15.7808, 15.7808] +24-11-19 19:26:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:26:08 | D | sum error = [ 129.0433, 138.3524, 151.1152, 162.0916, 174.0416] +24-11-19 19:26:08 | D | best error = [ 15.7808, 15.7808, 15.7808, 15.7808, 15.7808] +24-11-19 19:26:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:26:08 | D | sum error = [ 193.0882, 206.1958, 223.0968, 239.7624, 256.5624] +24-11-19 19:26:08 | D | best error = [ 15.7808, 15.7808, 15.7808, 15.7808, 15.7808] +24-11-19 19:26:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:26:08 | D | sum error = [ 275.3410, 297.0958, 318.3080, 345.2437, 372.4669] +24-11-19 19:26:08 | D | best error = [ 15.7808, 15.7808, 15.7808, 15.7808, 15.7808] +24-11-19 19:26:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:26:08 | D | sum error = [ 404.1360, 434.6209, 469.4233, 506.9003, 544.2509] +24-11-19 19:26:08 | D | best error = [ 15.7808, 15.7808, 15.7808, 15.7808, 15.7808] +24-11-19 19:26:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:26:08 | D | sum error = [ 588.1378, 634.9242, 683.7103, 741.6543, 793.8181] +24-11-19 19:26:08 | D | best error = [ 15.7808, 15.7808, 15.7808, 15.7808, 15.7808] +24-11-19 19:26:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:26:08 | D | sum error = [ 867.1568, 935.7906, 1013.3579, 1088.8113, 1176.3210] +24-11-19 19:26:08 | D | best error = [ 15.7808, 15.7808, 15.7808, 15.7808, 15.7808] +24-11-19 19:26:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:26:08 | D | sum error = [ 1279.4291, 1369.5345, 1485.6947, 1619.3242, 1769.1206] +24-11-19 19:26:08 | D | best error = [ 15.7808, 15.7808, 15.7808, 15.7808, 15.7808] +24-11-19 19:26:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:26:08 | D | sum error = [ 1906.3237, 2071.7683, 2255.8538, 2433.3331, 2651.0182] +24-11-19 19:26:08 | D | best error = [ 15.7808, 15.7808, 15.7808, 15.7808, 15.7808] +24-11-19 19:26:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:26:08 | D | sum error = [ 2878.4970, 3133.6919, 3368.4976, 3643.7562, 3955.2621] +24-11-19 19:26:08 | D | best error = [ 15.7808, 15.7808, 15.7808, 15.7808, 15.7808] +24-11-19 19:26:08 | D | + error = [15.7808] +24-11-19 19:26:08 | D | - Calibrating model.layers.22.self_attn.v_proj.weight +24-11-19 19:26:08 | D | + w: sint8 +24-11-19 19:26:08 | D | + x: None +24-11-19 19:26:08 | D | + y: None +24-11-19 19:26:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:26:08 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:26:08 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:26:08 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:26:08 | D | - range ratio = [ 1.0000] +24-11-19 19:26:08 | D | sum error = [ 6.9749] +24-11-19 19:26:08 | D | best error = [ 6.9749] +24-11-19 19:26:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:26:08 | D | sum error = [ 6.9373, 6.9066, 6.9609, 7.0468, 7.1697] +24-11-19 19:26:08 | D | best error = [ 6.5131, 6.3257, 6.2211, 6.1614, 6.1258] +24-11-19 19:26:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:26:08 | D | sum error = [ 7.3340, 7.6015, 7.8551, 8.2550, 8.7082] +24-11-19 19:26:08 | D | best error = [ 6.1097, 6.1026, 6.1000, 6.0983, 6.0981] +24-11-19 19:26:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:26:08 | D | sum error = [ 9.1972, 9.7554, 10.3967, 11.0714, 11.8424] +24-11-19 19:26:08 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 19:26:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:26:08 | D | sum error = [ 12.6837, 13.6031, 14.5735, 15.6219, 16.7604] +24-11-19 19:26:08 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 19:26:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:26:08 | D | sum error = [ 17.9540, 19.2456, 20.5265, 21.9812, 23.5129] +24-11-19 19:26:08 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 19:26:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:26:08 | D | sum error = [ 25.1404, 26.8290, 28.6331, 30.5457, 32.5350] +24-11-19 19:26:08 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 19:26:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:26:08 | D | sum error = [ 34.6670, 36.8681, 39.2093, 41.7117, 44.2938] +24-11-19 19:26:08 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 19:26:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:26:08 | D | sum error = [ 47.0484, 49.9117, 52.9486, 56.0989, 59.4395] +24-11-19 19:26:08 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 19:26:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:26:08 | D | sum error = [ 62.9379, 66.6012, 70.4849, 74.5045, 78.7123] +24-11-19 19:26:08 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 19:26:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:26:08 | D | sum error = [ 83.1485, 87.7775, 92.6005, 97.6685, 102.9384] +24-11-19 19:26:08 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 19:26:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:26:08 | D | sum error = [ 108.4264, 114.1943, 120.1817, 126.4470, 132.9668] +24-11-19 19:26:08 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 19:26:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:26:08 | D | sum error = [ 139.7477, 146.7842, 154.1309, 161.7547, 169.6388] +24-11-19 19:26:08 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 19:26:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:26:08 | D | sum error = [ 177.8581, 186.3561, 195.2031, 204.3428, 213.8222] +24-11-19 19:26:08 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 19:26:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:26:08 | D | sum error = [ 223.6213, 233.7819, 244.2870, 255.1590, 266.3614] +24-11-19 19:26:08 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 19:26:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:26:08 | D | sum error = [ 277.9623, 289.8922, 302.2159, 314.9041, 327.9798] +24-11-19 19:26:08 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 19:26:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:26:08 | D | sum error = [ 341.4300, 355.2761, 369.5305, 384.2036, 399.2677] +24-11-19 19:26:08 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 19:26:08 | D | + error = [6.0980] +24-11-19 19:26:09 | D | - Calibrating model.layers.22.self_attn.o_proj.weight +24-11-19 19:26:09 | D | + w: sint8 +24-11-19 19:26:09 | D | + x: None +24-11-19 19:26:09 | D | + y: None +24-11-19 19:26:09 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:26:09 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:26:09 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:26:09 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:26:09 | D | - range ratio = [ 1.0000] +24-11-19 19:26:09 | D | sum error = [ 1.5648] +24-11-19 19:26:09 | D | best error = [ 1.5648] +24-11-19 19:26:09 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:26:09 | D | sum error = [ 1.5486, 1.5492, 1.5548, 1.5658, 1.5862] +24-11-19 19:26:09 | D | best error = [ 1.4815, 1.4436, 1.4211, 1.4076, 1.3987] +24-11-19 19:26:09 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:26:09 | D | sum error = [ 1.6227, 1.6736, 1.7312, 1.8046, 1.8893] +24-11-19 19:26:09 | D | best error = [ 1.3928, 1.3888, 1.3864, 1.3846, 1.3835] +24-11-19 19:26:09 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:26:09 | D | sum error = [ 1.9907, 2.1009, 2.2261, 2.3721, 2.5230] +24-11-19 19:26:09 | D | best error = [ 1.3828, 1.3822, 1.3818, 1.3816, 1.3814] +24-11-19 19:26:09 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:26:09 | D | sum error = [ 2.6907, 2.8736, 3.0648, 3.2758, 3.5006] +24-11-19 19:26:09 | D | best error = [ 1.3813, 1.3812, 1.3811, 1.3810, 1.3810] +24-11-19 19:26:09 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:26:09 | D | sum error = [ 3.7468, 4.0008, 4.2801, 4.5662, 4.8722] +24-11-19 19:26:09 | D | best error = [ 1.3809, 1.3809, 1.3809, 1.3809, 1.3808] +24-11-19 19:26:09 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:26:09 | D | sum error = [ 5.2000, 5.5502, 5.9163, 6.3050, 6.7179] +24-11-19 19:26:09 | D | best error = [ 1.3808, 1.3808, 1.3808, 1.3808, 1.3808] +24-11-19 19:26:09 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:26:09 | D | sum error = [ 7.1492, 7.6130, 8.1001, 8.6079, 9.1505] +24-11-19 19:26:09 | D | best error = [ 1.3808, 1.3808, 1.3808, 1.3808, 1.3808] +24-11-19 19:26:09 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:26:09 | D | sum error = [ 9.7212, 10.3209, 10.9516, 11.6177, 12.3193] +24-11-19 19:26:09 | D | best error = [ 1.3808, 1.3808, 1.3808, 1.3808, 1.3808] +24-11-19 19:26:09 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:26:09 | D | sum error = [ 13.0554, 13.8350, 14.6499, 15.5099, 16.4136] +24-11-19 19:26:09 | D | best error = [ 1.3808, 1.3808, 1.3808, 1.3808, 1.3808] +24-11-19 19:26:09 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:26:09 | D | sum error = [ 17.3613, 18.3633, 19.4127, 20.5148, 21.6722] +24-11-19 19:26:09 | D | best error = [ 1.3808, 1.3808, 1.3808, 1.3808, 1.3808] +24-11-19 19:26:09 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:26:09 | D | sum error = [ 22.8835, 24.1636, 25.5008, 26.9044, 28.3778] +24-11-19 19:26:09 | D | best error = [ 1.3808, 1.3808, 1.3808, 1.3808, 1.3808] +24-11-19 19:26:09 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:26:09 | D | sum error = [ 29.9230, 31.5437, 33.2336, 35.0041, 36.8599] +24-11-19 19:26:09 | D | best error = [ 1.3808, 1.3808, 1.3808, 1.3808, 1.3808] +24-11-19 19:26:09 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:26:09 | D | sum error = [ 38.8003, 40.8283, 42.9484, 45.1639, 47.4750] +24-11-19 19:26:09 | D | best error = [ 1.3808, 1.3808, 1.3808, 1.3808, 1.3808] +24-11-19 19:26:09 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:26:09 | D | sum error = [ 49.8816, 52.3927, 55.0057, 57.7322, 60.5616] +24-11-19 19:26:09 | D | best error = [ 1.3808, 1.3808, 1.3808, 1.3808, 1.3808] +24-11-19 19:26:09 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:26:09 | D | sum error = [ 63.5065, 66.5696, 69.7427, 73.0382, 76.4556] +24-11-19 19:26:09 | D | best error = [ 1.3808, 1.3808, 1.3808, 1.3808, 1.3808] +24-11-19 19:26:09 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:26:09 | D | sum error = [ 79.9951, 83.6629, 87.4578, 91.3826, 95.4396] +24-11-19 19:26:09 | D | best error = [ 1.3808, 1.3808, 1.3808, 1.3808, 1.3808] +24-11-19 19:26:09 | D | + error = [1.3808] +24-11-19 19:26:09 | D | - Calibrating model.layers.22.mlp.up_proj.weight +24-11-19 19:26:09 | D | + w: sint8 +24-11-19 19:26:09 | D | + x: None +24-11-19 19:26:09 | D | + y: None +24-11-19 19:26:09 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:26:09 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:26:09 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:26:09 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:26:09 | D | - range ratio = [ 1.0000] +24-11-19 19:26:09 | D | sum error = [ 9.4736] +24-11-19 19:26:09 | D | best error = [ 9.4736] +24-11-19 19:26:10 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:26:10 | D | sum error = [ 9.4110, 9.3690, 9.4095, 9.5212, 9.7017] +24-11-19 19:26:10 | D | best error = [ 8.8010, 8.5264, 8.3839, 8.3012, 8.2563] +24-11-19 19:26:10 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:26:10 | D | sum error = [ 9.9500, 10.2576, 10.6996, 11.1983, 11.8111] +24-11-19 19:26:10 | D | best error = [ 8.2318, 8.2226, 8.2187, 8.2175, 8.2172] +24-11-19 19:26:10 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:26:10 | D | sum error = [ 12.4640, 13.2181, 14.1028, 15.0292, 16.0579] +24-11-19 19:26:10 | D | best error = [ 8.2171, 8.2170, 8.2170, 8.2170, 8.2170] +24-11-19 19:26:10 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:26:10 | D | sum error = [ 17.2239, 18.4274, 19.7748, 21.1738, 22.6689] +24-11-19 19:26:10 | D | best error = [ 8.2170, 8.2170, 8.2170, 8.2170, 8.2170] +24-11-19 19:26:10 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:26:10 | D | sum error = [ 24.2971, 26.0040, 27.8556, 29.7833, 31.8876] +24-11-19 19:26:10 | D | best error = [ 8.2170, 8.2170, 8.2170, 8.2170, 8.2170] +24-11-19 19:26:10 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:26:10 | D | sum error = [ 34.0588, 36.3667, 38.8448, 41.4108, 44.1697] +24-11-19 19:26:10 | D | best error = [ 8.2170, 8.2170, 8.2170, 8.2170, 8.2170] +24-11-19 19:26:10 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:26:10 | D | sum error = [ 47.0672, 50.0996, 53.3178, 56.7299, 60.2901] +24-11-19 19:26:10 | D | best error = [ 8.2170, 8.2170, 8.2170, 8.2170, 8.2170] +24-11-19 19:26:10 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:26:10 | D | sum error = [ 64.0565, 67.9970, 72.1482, 76.5484, 81.1406] +24-11-19 19:26:10 | D | best error = [ 8.2170, 8.2170, 8.2170, 8.2170, 8.2170] +24-11-19 19:26:10 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:26:10 | D | sum error = [ 85.9575, 91.0345, 96.3383, 101.9173, 107.7502] +24-11-19 19:26:10 | D | best error = [ 8.2170, 8.2170, 8.2170, 8.2170, 8.2170] +24-11-19 19:26:10 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:26:10 | D | sum error = [ 113.8720, 120.2695, 127.0040, 134.0128, 141.3316] +24-11-19 19:26:10 | D | best error = [ 8.2170, 8.2170, 8.2170, 8.2170, 8.2170] +24-11-19 19:26:10 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:26:10 | D | sum error = [ 149.0097, 156.9916, 165.3541, 174.0823, 183.1696] +24-11-19 19:26:10 | D | best error = [ 8.2170, 8.2170, 8.2170, 8.2170, 8.2170] +24-11-19 19:26:10 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:26:10 | D | sum error = [ 192.6481, 202.5277, 212.8126, 223.5194, 234.6498] +24-11-19 19:26:10 | D | best error = [ 8.2170, 8.2170, 8.2170, 8.2170, 8.2170] +24-11-19 19:26:10 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:26:10 | D | sum error = [ 246.2207, 258.2444, 270.7463, 283.7183, 297.1902] +24-11-19 19:26:10 | D | best error = [ 8.2170, 8.2170, 8.2170, 8.2170, 8.2170] +24-11-19 19:26:10 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:26:10 | D | sum error = [ 311.1547, 325.6179, 340.5954, 356.1009, 372.1385] +24-11-19 19:26:10 | D | best error = [ 8.2170, 8.2170, 8.2170, 8.2170, 8.2170] +24-11-19 19:26:10 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:26:10 | D | sum error = [ 388.7156, 405.8517, 423.5693, 441.8240, 460.6784] +24-11-19 19:26:10 | D | best error = [ 8.2170, 8.2170, 8.2170, 8.2170, 8.2170] +24-11-19 19:26:10 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:26:10 | D | sum error = [ 480.1032, 500.1353, 520.7774, 541.9981, 563.8365] +24-11-19 19:26:10 | D | best error = [ 8.2170, 8.2170, 8.2170, 8.2170, 8.2170] +24-11-19 19:26:10 | D | + error = [8.2170] +24-11-19 19:26:10 | D | - Calibrating model.layers.22.mlp.gate_proj.weight +24-11-19 19:26:10 | D | + w: sint8 +24-11-19 19:26:10 | D | + x: None +24-11-19 19:26:10 | D | + y: None +24-11-19 19:26:10 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:26:10 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:26:11 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:26:11 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:26:11 | D | - range ratio = [ 1.0000] +24-11-19 19:26:11 | D | sum error = [ 10.2651] +24-11-19 19:26:11 | D | best error = [ 10.2651] +24-11-19 19:26:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:26:12 | D | sum error = [ 10.1789, 10.1785, 10.2410, 10.3561, 10.5122] +24-11-19 19:26:12 | D | best error = [ 9.5286, 9.2418, 9.0873, 9.0034, 8.9499] +24-11-19 19:26:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:26:12 | D | sum error = [ 10.8137, 11.1443, 11.6001, 12.1647, 12.7853] +24-11-19 19:26:12 | D | best error = [ 8.9246, 8.9146, 8.9101, 8.9084, 8.9080] +24-11-19 19:26:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:26:12 | D | sum error = [ 13.5207, 14.3708, 15.2989, 16.3630, 17.4738] +24-11-19 19:26:12 | D | best error = [ 8.9079, 8.9078, 8.9078, 8.9078, 8.9078] +24-11-19 19:26:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:26:12 | D | sum error = [ 18.7214, 20.0607, 21.5007, 23.0413, 24.7251] +24-11-19 19:26:12 | D | best error = [ 8.9078, 8.9078, 8.9078, 8.9078, 8.9078] +24-11-19 19:26:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:26:12 | D | sum error = [ 26.4989, 28.4076, 30.3992, 32.5352, 34.8317] +24-11-19 19:26:12 | D | best error = [ 8.9078, 8.9078, 8.9078, 8.9078, 8.9078] +24-11-19 19:26:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:26:12 | D | sum error = [ 37.2516, 39.7905, 42.5509, 45.4050, 48.4724] +24-11-19 19:26:12 | D | best error = [ 8.9078, 8.9078, 8.9078, 8.9078, 8.9078] +24-11-19 19:26:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:26:12 | D | sum error = [ 51.7215, 55.1189, 58.7323, 62.5569, 66.5918] +24-11-19 19:26:12 | D | best error = [ 8.9078, 8.9078, 8.9078, 8.9078, 8.9078] +24-11-19 19:26:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:26:12 | D | sum error = [ 70.8193, 75.3309, 80.0524, 85.0598, 90.3148] +24-11-19 19:26:12 | D | best error = [ 8.9078, 8.9078, 8.9078, 8.9078, 8.9078] +24-11-19 19:26:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:26:12 | D | sum error = [ 95.8628, 101.7170, 107.9114, 114.3948, 121.2391] +24-11-19 19:26:12 | D | best error = [ 8.9078, 8.9078, 8.9078, 8.9078, 8.9078] +24-11-19 19:26:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:26:12 | D | sum error = [ 128.3896, 135.9643, 143.9186, 152.2474, 161.0635] +24-11-19 19:26:12 | D | best error = [ 8.9078, 8.9078, 8.9078, 8.9078, 8.9078] +24-11-19 19:26:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:26:12 | D | sum error = [ 170.2309, 179.9139, 190.0618, 200.6747, 211.8230] +24-11-19 19:26:12 | D | best error = [ 8.9078, 8.9078, 8.9078, 8.9078, 8.9078] +24-11-19 19:26:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:26:12 | D | sum error = [ 223.4703, 235.6821, 248.4539, 261.8300, 275.7974] +24-11-19 19:26:12 | D | best error = [ 8.9078, 8.9078, 8.9078, 8.9078, 8.9078] +24-11-19 19:26:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:26:12 | D | sum error = [ 290.4172, 305.6241, 321.5439, 338.1144, 355.3792] +24-11-19 19:26:12 | D | best error = [ 8.9078, 8.9078, 8.9078, 8.9078, 8.9078] +24-11-19 19:26:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:26:12 | D | sum error = [ 373.3598, 392.0495, 411.5180, 431.7444, 452.7443] +24-11-19 19:26:12 | D | best error = [ 8.9078, 8.9078, 8.9078, 8.9078, 8.9078] +24-11-19 19:26:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:26:12 | D | sum error = [ 474.5159, 497.0589, 520.4456, 544.6495, 569.7028] +24-11-19 19:26:12 | D | best error = [ 8.9078, 8.9078, 8.9078, 8.9078, 8.9078] +24-11-19 19:26:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:26:12 | D | sum error = [ 595.5661, 622.2993, 649.8793, 678.3291, 707.6420] +24-11-19 19:26:12 | D | best error = [ 8.9078, 8.9078, 8.9078, 8.9078, 8.9078] +24-11-19 19:26:12 | D | + error = [8.9078] +24-11-19 19:26:12 | D | - Calibrating model.layers.22.mlp.down_proj.weight +24-11-19 19:26:12 | D | + w: sint8 +24-11-19 19:26:12 | D | + x: None +24-11-19 19:26:12 | D | + y: None +24-11-19 19:26:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:26:12 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:26:12 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:26:12 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:26:12 | D | - range ratio = [ 1.0000] +24-11-19 19:26:12 | D | sum error = [ 3.6775] +24-11-19 19:26:12 | D | best error = [ 3.6775] +24-11-19 19:26:13 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:26:13 | D | sum error = [ 3.6484, 3.6173, 3.6001, 3.5989, 3.6025] +24-11-19 19:26:13 | D | best error = [ 3.5215, 3.4388, 3.3824, 3.3441, 3.3173] +24-11-19 19:26:13 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:26:13 | D | sum error = [ 3.6188, 3.6417, 3.6961, 3.7578, 3.8575] +24-11-19 19:26:13 | D | best error = [ 3.2961, 3.2791, 3.2676, 3.2585, 3.2522] +24-11-19 19:26:13 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:26:13 | D | sum error = [ 3.9581, 4.0864, 4.2416, 4.4242, 4.6363] +24-11-19 19:26:13 | D | best error = [ 3.2477, 3.2445, 3.2426, 3.2412, 3.2405] +24-11-19 19:26:13 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:26:13 | D | sum error = [ 4.8711, 5.1514, 5.4474, 5.7778, 6.1474] +24-11-19 19:26:13 | D | best error = [ 3.2402, 3.2399, 3.2398, 3.2398, 3.2397] +24-11-19 19:26:13 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:26:13 | D | sum error = [ 6.5547, 6.9872, 7.4682, 7.9740, 8.5380] +24-11-19 19:26:13 | D | best error = [ 3.2396, 3.2396, 3.2396, 3.2396, 3.2396] +24-11-19 19:26:13 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:26:13 | D | sum error = [ 9.1221, 9.7593, 10.4463, 11.1771, 11.9490] +24-11-19 19:26:13 | D | best error = [ 3.2396, 3.2396, 3.2396, 3.2396, 3.2396] +24-11-19 19:26:13 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:26:13 | D | sum error = [ 12.7732, 13.6603, 14.5999, 15.6012, 16.6572] +24-11-19 19:26:13 | D | best error = [ 3.2396, 3.2396, 3.2396, 3.2396, 3.2396] +24-11-19 19:26:13 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:26:13 | D | sum error = [ 17.7767, 18.9680, 20.2282, 21.5538, 22.9663] +24-11-19 19:26:13 | D | best error = [ 3.2396, 3.2396, 3.2396, 3.2396, 3.2396] +24-11-19 19:26:13 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:26:13 | D | sum error = [ 24.4587, 26.0267, 27.6925, 29.4496, 31.2933] +24-11-19 19:26:13 | D | best error = [ 3.2396, 3.2396, 3.2396, 3.2396, 3.2396] +24-11-19 19:26:13 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:26:13 | D | sum error = [ 33.2483, 35.2983, 37.4594, 39.7361, 42.1263] +24-11-19 19:26:13 | D | best error = [ 3.2396, 3.2396, 3.2396, 3.2396, 3.2396] +24-11-19 19:26:13 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:26:13 | D | sum error = [ 44.6369, 47.2713, 50.0296, 52.9349, 55.9665] +24-11-19 19:26:13 | D | best error = [ 3.2396, 3.2396, 3.2396, 3.2396, 3.2396] +24-11-19 19:26:13 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:26:13 | D | sum error = [ 59.1554, 62.4887, 65.9805, 69.6344, 73.4515] +24-11-19 19:26:13 | D | best error = [ 3.2396, 3.2396, 3.2396, 3.2396, 3.2396] +24-11-19 19:26:13 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:26:13 | D | sum error = [ 77.4385, 81.6056, 85.9512, 90.4828, 95.1978] +24-11-19 19:26:13 | D | best error = [ 3.2396, 3.2396, 3.2396, 3.2396, 3.2396] +24-11-19 19:26:13 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:26:13 | D | sum error = [ 100.1154, 105.2233, 110.5373, 116.0751, 121.8074] +24-11-19 19:26:13 | D | best error = [ 3.2396, 3.2396, 3.2396, 3.2396, 3.2396] +24-11-19 19:26:13 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:26:13 | D | sum error = [ 127.7679, 133.9526, 140.3601, 146.9992, 153.8698] +24-11-19 19:26:13 | D | best error = [ 3.2396, 3.2396, 3.2396, 3.2396, 3.2396] +24-11-19 19:26:13 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:26:13 | D | sum error = [ 160.9855, 168.3401, 175.9431, 183.7948, 191.8976] +24-11-19 19:26:13 | D | best error = [ 3.2396, 3.2396, 3.2396, 3.2396, 3.2396] +24-11-19 19:26:13 | D | + error = [3.2396] +24-11-19 19:26:13 | D | - Quantizing model.layers.22.self_attn.q_proj.weight +24-11-19 19:26:14 | D | - Quantizing model.layers.22.self_attn.k_proj.weight +24-11-19 19:26:15 | D | - Quantizing model.layers.22.self_attn.v_proj.weight +24-11-19 19:26:16 | D | - Quantizing model.layers.22.self_attn.o_proj.weight +24-11-19 19:26:17 | D | - Quantizing model.layers.22.mlp.up_proj.weight +24-11-19 19:26:18 | D | - Quantizing model.layers.22.mlp.gate_proj.weight +24-11-19 19:26:19 | D | - Quantizing model.layers.22.mlp.down_proj.weight +24-11-19 19:26:27 | D | - Quantizing layer model.layers.23 +24-11-19 19:26:27 | D | - Calibrating model.layers.23.self_attn.q_proj.weight +24-11-19 19:26:27 | D | + w: sint8 +24-11-19 19:26:27 | D | + x: None +24-11-19 19:26:27 | D | + y: None +24-11-19 19:26:27 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:26:27 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:26:27 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:26:28 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:26:28 | D | - range ratio = [ 1.0000] +24-11-19 19:26:28 | D | sum error = [ 12.9037] +24-11-19 19:26:28 | D | best error = [ 12.9037] +24-11-19 19:26:40 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:26:40 | D | sum error = [ 12.8544, 12.5628, 12.6807, 12.7850, 12.9713] +24-11-19 19:26:40 | D | best error = [ 12.8544, 12.5628, 12.5628, 12.5628, 12.5628] +24-11-19 19:26:40 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:26:40 | D | sum error = [ 13.3835, 13.5992, 14.1400, 15.1587, 16.0218] +24-11-19 19:26:40 | D | best error = [ 12.5628, 12.5628, 12.5628, 12.5628, 12.5628] +24-11-19 19:26:40 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:26:40 | D | sum error = [ 16.7265, 17.7780, 19.1583, 20.8867, 22.0073] +24-11-19 19:26:40 | D | best error = [ 12.5628, 12.5628, 12.5628, 12.5628, 12.5628] +24-11-19 19:26:40 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:26:40 | D | sum error = [ 23.8492, 25.3958, 27.5012, 30.1392, 32.5638] +24-11-19 19:26:40 | D | best error = [ 12.5628, 12.5628, 12.5628, 12.5628, 12.5628] +24-11-19 19:26:40 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:26:40 | D | sum error = [ 34.8928, 37.7929, 40.7858, 44.2543, 47.4600] +24-11-19 19:26:40 | D | best error = [ 12.5628, 12.5628, 12.5628, 12.5628, 12.5628] +24-11-19 19:26:40 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:26:40 | D | sum error = [ 51.1294, 55.4047, 59.6638, 64.6178, 69.7431] +24-11-19 19:26:40 | D | best error = [ 12.5628, 12.5628, 12.5628, 12.5628, 12.5628] +24-11-19 19:26:40 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:26:40 | D | sum error = [ 74.9691, 81.0424, 87.1898, 93.9816, 101.1352] +24-11-19 19:26:40 | D | best error = [ 12.5628, 12.5628, 12.5628, 12.5628, 12.5628] +24-11-19 19:26:40 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:26:40 | D | sum error = [ 108.1528, 116.5716, 125.2471, 134.2760, 144.2800] +24-11-19 19:26:40 | D | best error = [ 12.5628, 12.5628, 12.5628, 12.5628, 12.5628] +24-11-19 19:26:40 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:26:40 | D | sum error = [ 155.3364, 167.0114, 179.6368, 193.3839, 208.1921] +24-11-19 19:26:40 | D | best error = [ 12.5628, 12.5628, 12.5628, 12.5628, 12.5628] +24-11-19 19:26:40 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:26:40 | D | sum error = [ 223.9629, 241.0999, 259.0108, 278.0078, 299.4367] +24-11-19 19:26:40 | D | best error = [ 12.5628, 12.5628, 12.5628, 12.5628, 12.5628] +24-11-19 19:26:40 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:26:40 | D | sum error = [ 321.7755, 346.2950, 372.4281, 401.1105, 432.0261] +24-11-19 19:26:40 | D | best error = [ 12.5628, 12.5628, 12.5628, 12.5628, 12.5628] +24-11-19 19:26:40 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:26:40 | D | sum error = [ 465.7149, 502.1172, 541.3681, 583.6106, 628.9670] +24-11-19 19:26:40 | D | best error = [ 12.5628, 12.5628, 12.5628, 12.5628, 12.5628] +24-11-19 19:26:40 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:26:40 | D | sum error = [ 679.3277, 733.8465, 793.1891, 857.2686, 928.2820] +24-11-19 19:26:40 | D | best error = [ 12.5628, 12.5628, 12.5628, 12.5628, 12.5628] +24-11-19 19:26:40 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:26:40 | D | sum error = [ 1005.2760, 1090.3282, 1183.4904, 1286.4755, 1399.1605] +24-11-19 19:26:40 | D | best error = [ 12.5628, 12.5628, 12.5628, 12.5628, 12.5628] +24-11-19 19:26:40 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:26:40 | D | sum error = [ 1523.6308, 1660.5541, 1812.1149, 1978.6603, 2160.8837] +24-11-19 19:26:40 | D | best error = [ 12.5628, 12.5628, 12.5628, 12.5628, 12.5628] +24-11-19 19:26:40 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:26:40 | D | sum error = [ 2360.8964, 2579.7810, 2818.2111, 3077.9129, 3356.0051] +24-11-19 19:26:40 | D | best error = [ 12.5628, 12.5628, 12.5628, 12.5628, 12.5628] +24-11-19 19:26:40 | D | + error = [12.5628] +24-11-19 19:26:41 | D | - Calibrating model.layers.23.self_attn.k_proj.weight +24-11-19 19:26:41 | D | + w: sint8 +24-11-19 19:26:41 | D | + x: None +24-11-19 19:26:41 | D | + y: None +24-11-19 19:26:41 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:26:41 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:26:41 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:26:41 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:26:41 | D | - range ratio = [ 1.0000] +24-11-19 19:26:41 | D | sum error = [ 14.7670] +24-11-19 19:26:41 | D | best error = [ 14.7670] +24-11-19 19:26:54 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:26:54 | D | sum error = [ 14.8254, 14.4086, 14.3059, 15.1874, 15.0895] +24-11-19 19:26:54 | D | best error = [ 14.7670, 14.4086, 14.3059, 14.3059, 14.3059] +24-11-19 19:26:54 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:26:54 | D | sum error = [ 14.9467, 16.4472, 17.2081, 17.8701, 18.3870] +24-11-19 19:26:54 | D | best error = [ 14.3059, 14.3059, 14.3059, 14.3059, 14.3059] +24-11-19 19:26:54 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:26:54 | D | sum error = [ 19.8266, 20.8122, 22.7032, 24.7122, 26.0710] +24-11-19 19:26:54 | D | best error = [ 14.3059, 14.3059, 14.3059, 14.3059, 14.3059] +24-11-19 19:26:54 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:26:54 | D | sum error = [ 28.0128, 29.5608, 32.0255, 33.9737, 36.9934] +24-11-19 19:26:54 | D | best error = [ 14.3059, 14.3059, 14.3059, 14.3059, 14.3059] +24-11-19 19:26:54 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:26:54 | D | sum error = [ 40.2923, 44.1581, 47.1895, 51.2419, 54.7090] +24-11-19 19:26:54 | D | best error = [ 14.3059, 14.3059, 14.3059, 14.3059, 14.3059] +24-11-19 19:26:54 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:26:54 | D | sum error = [ 59.0807, 64.5298, 68.9174, 73.9380, 79.3775] +24-11-19 19:26:54 | D | best error = [ 14.3059, 14.3059, 14.3059, 14.3059, 14.3059] +24-11-19 19:26:54 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:26:54 | D | sum error = [ 84.6057, 91.5295, 99.0437, 105.0476, 112.4204] +24-11-19 19:26:54 | D | best error = [ 14.3059, 14.3059, 14.3059, 14.3059, 14.3059] +24-11-19 19:26:54 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:26:54 | D | sum error = [ 120.8262, 130.6721, 141.1102, 151.6751, 163.2959] +24-11-19 19:26:54 | D | best error = [ 14.3059, 14.3059, 14.3059, 14.3059, 14.3059] +24-11-19 19:26:54 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:26:54 | D | sum error = [ 176.0693, 189.1986, 204.7854, 219.9837, 238.0522] +24-11-19 19:26:54 | D | best error = [ 14.3059, 14.3059, 14.3059, 14.3059, 14.3059] +24-11-19 19:26:54 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:26:54 | D | sum error = [ 256.4018, 275.3641, 296.8476, 320.1546, 343.6176] +24-11-19 19:26:54 | D | best error = [ 14.3059, 14.3059, 14.3059, 14.3059, 14.3059] +24-11-19 19:26:54 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:26:54 | D | sum error = [ 370.7160, 397.6895, 426.5989, 459.9413, 496.3137] +24-11-19 19:26:54 | D | best error = [ 14.3059, 14.3059, 14.3059, 14.3059, 14.3059] +24-11-19 19:26:54 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:26:54 | D | sum error = [ 534.8683, 574.0219, 621.6777, 666.0621, 719.7964] +24-11-19 19:26:54 | D | best error = [ 14.3059, 14.3059, 14.3059, 14.3059, 14.3059] +24-11-19 19:26:54 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:26:54 | D | sum error = [ 778.7489, 840.3001, 910.0369, 981.6945, 1061.2800] +24-11-19 19:26:54 | D | best error = [ 14.3059, 14.3059, 14.3059, 14.3059, 14.3059] +24-11-19 19:26:54 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:26:54 | D | sum error = [ 1144.9757, 1245.6501, 1350.3519, 1459.2867, 1580.8585] +24-11-19 19:26:54 | D | best error = [ 14.3059, 14.3059, 14.3059, 14.3059, 14.3059] +24-11-19 19:26:54 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:26:54 | D | sum error = [ 1715.5270, 1866.5153, 2028.6056, 2190.1016, 2389.4628] +24-11-19 19:26:54 | D | best error = [ 14.3059, 14.3059, 14.3059, 14.3059, 14.3059] +24-11-19 19:26:54 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:26:54 | D | sum error = [ 2595.4412, 2831.9668, 3063.4151, 3324.8501, 3610.6527] +24-11-19 19:26:54 | D | best error = [ 14.3059, 14.3059, 14.3059, 14.3059, 14.3059] +24-11-19 19:26:54 | D | + error = [14.3059] +24-11-19 19:26:54 | D | - Calibrating model.layers.23.self_attn.v_proj.weight +24-11-19 19:26:54 | D | + w: sint8 +24-11-19 19:26:54 | D | + x: None +24-11-19 19:26:54 | D | + y: None +24-11-19 19:26:54 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:26:54 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:26:54 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:26:54 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:26:54 | D | - range ratio = [ 1.0000] +24-11-19 19:26:54 | D | sum error = [ 7.7977] +24-11-19 19:26:54 | D | best error = [ 7.7977] +24-11-19 19:26:55 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:26:55 | D | sum error = [ 7.7398, 7.7077, 7.7648, 7.8592, 7.9752] +24-11-19 19:26:55 | D | best error = [ 7.2649, 7.0369, 6.9211, 6.8551, 6.8182] +24-11-19 19:26:55 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:26:55 | D | sum error = [ 8.1975, 8.4918, 8.8036, 9.2440, 9.6928] +24-11-19 19:26:55 | D | best error = [ 6.7993, 6.7918, 6.7888, 6.7881, 6.7879] +24-11-19 19:26:55 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:26:55 | D | sum error = [ 10.2607, 10.9180, 11.6062, 12.3646, 13.2645] +24-11-19 19:26:55 | D | best error = [ 6.7878, 6.7878, 6.7878, 6.7878, 6.7878] +24-11-19 19:26:55 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:26:55 | D | sum error = [ 14.1701, 15.1785, 16.2431, 17.4003, 18.6633] +24-11-19 19:26:55 | D | best error = [ 6.7878, 6.7878, 6.7878, 6.7878, 6.7878] +24-11-19 19:26:55 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:26:55 | D | sum error = [ 19.9805, 21.4088, 22.8943, 24.5182, 26.2245] +24-11-19 19:26:55 | D | best error = [ 6.7878, 6.7878, 6.7878, 6.7878, 6.7878] +24-11-19 19:26:55 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:26:55 | D | sum error = [ 27.9852, 29.9183, 31.9533, 34.0515, 36.3114] +24-11-19 19:26:55 | D | best error = [ 6.7878, 6.7878, 6.7878, 6.7878, 6.7878] +24-11-19 19:26:55 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:26:55 | D | sum error = [ 38.6627, 41.1816, 43.8078, 46.5521, 49.4589] +24-11-19 19:26:55 | D | best error = [ 6.7878, 6.7878, 6.7878, 6.7878, 6.7878] +24-11-19 19:26:55 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:26:55 | D | sum error = [ 52.4981, 55.6951, 59.0817, 62.5954, 66.3359] +24-11-19 19:26:55 | D | best error = [ 6.7878, 6.7878, 6.7878, 6.7878, 6.7878] +24-11-19 19:26:55 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:26:55 | D | sum error = [ 70.2252, 74.2964, 78.5756, 83.0529, 87.7653] +24-11-19 19:26:55 | D | best error = [ 6.7878, 6.7878, 6.7878, 6.7878, 6.7878] +24-11-19 19:26:55 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:26:55 | D | sum error = [ 92.6642, 97.8046, 103.1712, 108.7865, 114.6475] +24-11-19 19:26:55 | D | best error = [ 6.7878, 6.7878, 6.7878, 6.7878, 6.7878] +24-11-19 19:26:55 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:26:55 | D | sum error = [ 120.7477, 127.1280, 133.7158, 140.6244, 147.8055] +24-11-19 19:26:55 | D | best error = [ 6.7878, 6.7878, 6.7878, 6.7878, 6.7878] +24-11-19 19:26:55 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:26:55 | D | sum error = [ 155.3014, 163.0703, 171.1390, 179.5133, 188.2137] +24-11-19 19:26:55 | D | best error = [ 6.7878, 6.7878, 6.7878, 6.7878, 6.7878] +24-11-19 19:26:55 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:26:55 | D | sum error = [ 197.2483, 206.6381, 216.3630, 226.4353, 236.8851] +24-11-19 19:26:55 | D | best error = [ 6.7878, 6.7878, 6.7878, 6.7878, 6.7878] +24-11-19 19:26:55 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:26:55 | D | sum error = [ 247.6792, 258.8415, 270.3804, 282.3153, 294.6110] +24-11-19 19:26:55 | D | best error = [ 6.7878, 6.7878, 6.7878, 6.7878, 6.7878] +24-11-19 19:26:55 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:26:55 | D | sum error = [ 307.3158, 320.4299, 333.9411, 347.8336, 362.1334] +24-11-19 19:26:55 | D | best error = [ 6.7878, 6.7878, 6.7878, 6.7878, 6.7878] +24-11-19 19:26:55 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:26:55 | D | sum error = [ 376.8564, 392.0002, 407.5659, 423.5859, 440.0718] +24-11-19 19:26:55 | D | best error = [ 6.7878, 6.7878, 6.7878, 6.7878, 6.7878] +24-11-19 19:26:55 | D | + error = [6.7878] +24-11-19 19:26:55 | D | - Calibrating model.layers.23.self_attn.o_proj.weight +24-11-19 19:26:55 | D | + w: sint8 +24-11-19 19:26:55 | D | + x: None +24-11-19 19:26:55 | D | + y: None +24-11-19 19:26:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:26:55 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:26:55 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:26:55 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:26:55 | D | - range ratio = [ 1.0000] +24-11-19 19:26:55 | D | sum error = [ 1.4847] +24-11-19 19:26:55 | D | best error = [ 1.4847] +24-11-19 19:26:55 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:26:55 | D | sum error = [ 1.4773, 1.4677, 1.4728, 1.4862, 1.5075] +24-11-19 19:26:55 | D | best error = [ 1.4112, 1.3750, 1.3536, 1.3401, 1.3319] +24-11-19 19:26:55 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:26:55 | D | sum error = [ 1.5426, 1.5860, 1.6349, 1.7013, 1.7801] +24-11-19 19:26:55 | D | best error = [ 1.3267, 1.3234, 1.3215, 1.3202, 1.3194] +24-11-19 19:26:55 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:26:55 | D | sum error = [ 1.8742, 1.9773, 2.0931, 2.2218, 2.3634] +24-11-19 19:26:55 | D | best error = [ 1.3190, 1.3186, 1.3184, 1.3183, 1.3182] +24-11-19 19:26:55 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:26:55 | D | sum error = [ 2.5186, 2.6882, 2.8671, 3.0640, 3.2751] +24-11-19 19:26:55 | D | best error = [ 1.3181, 1.3180, 1.3179, 1.3179, 1.3179] +24-11-19 19:26:55 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:26:55 | D | sum error = [ 3.4905, 3.7280, 3.9842, 4.2500, 4.5333] +24-11-19 19:26:55 | D | best error = [ 1.3179, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 19:26:55 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:26:55 | D | sum error = [ 4.8346, 5.1537, 5.4914, 5.8499, 6.2239] +24-11-19 19:26:55 | D | best error = [ 1.3179, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 19:26:55 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:26:55 | D | sum error = [ 6.6231, 7.0414, 7.4835, 7.9523, 8.4389] +24-11-19 19:26:55 | D | best error = [ 1.3179, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 19:26:55 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:26:55 | D | sum error = [ 8.9561, 9.5012, 10.0754, 10.6723, 11.3094] +24-11-19 19:26:55 | D | best error = [ 1.3179, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 19:26:55 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:26:55 | D | sum error = [ 11.9809, 12.6758, 13.4130, 14.1838, 14.9935] +24-11-19 19:26:55 | D | best error = [ 1.3179, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 19:26:55 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:26:55 | D | sum error = [ 15.8435, 16.7330, 17.6665, 18.6436, 19.6663] +24-11-19 19:26:55 | D | best error = [ 1.3179, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 19:26:55 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:26:55 | D | sum error = [ 20.7365, 21.8586, 23.0310, 24.2580, 25.5449] +24-11-19 19:26:55 | D | best error = [ 1.3179, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 19:26:55 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:26:55 | D | sum error = [ 26.8863, 28.2869, 29.7528, 31.2786, 32.8723] +24-11-19 19:26:55 | D | best error = [ 1.3179, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 19:26:55 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:26:55 | D | sum error = [ 34.5311, 36.2592, 38.0595, 39.9359, 41.8912] +24-11-19 19:26:55 | D | best error = [ 1.3179, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 19:26:55 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:26:55 | D | sum error = [ 43.9238, 46.0411, 48.2383, 50.5278, 52.8992] +24-11-19 19:26:55 | D | best error = [ 1.3179, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 19:26:55 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:26:55 | D | sum error = [ 55.3637, 57.9206, 60.5730, 63.3170, 66.1597] +24-11-19 19:26:55 | D | best error = [ 1.3179, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 19:26:55 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:26:55 | D | sum error = [ 69.0992, 72.1408, 75.2847, 78.5355, 81.8906] +24-11-19 19:26:55 | D | best error = [ 1.3179, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 19:26:55 | D | + error = [1.3179] +24-11-19 19:26:55 | D | - Calibrating model.layers.23.mlp.up_proj.weight +24-11-19 19:26:55 | D | + w: sint8 +24-11-19 19:26:55 | D | + x: None +24-11-19 19:26:55 | D | + y: None +24-11-19 19:26:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:26:55 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:26:55 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:26:56 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:26:56 | D | - range ratio = [ 1.0000] +24-11-19 19:26:56 | D | sum error = [ 9.8256] +24-11-19 19:26:56 | D | best error = [ 9.8256] +24-11-19 19:26:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:26:57 | D | sum error = [ 9.7548, 9.7359, 9.7549, 9.8674, 10.0538] +24-11-19 19:26:57 | D | best error = [ 9.1275, 8.8528, 8.7000, 8.6133, 8.5641] +24-11-19 19:26:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:26:57 | D | sum error = [ 10.2795, 10.6346, 11.0887, 11.5910, 12.1701] +24-11-19 19:26:57 | D | best error = [ 8.5396, 8.5279, 8.5239, 8.5224, 8.5218] +24-11-19 19:26:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:26:57 | D | sum error = [ 12.8759, 13.6922, 14.5476, 15.5265, 16.6080] +24-11-19 19:26:57 | D | best error = [ 8.5218, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 19:26:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:26:57 | D | sum error = [ 17.7953, 19.0286, 20.3873, 21.8499, 23.4165] +24-11-19 19:26:57 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 19:26:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:26:57 | D | sum error = [ 25.0714, 26.8809, 28.7447, 30.7732, 32.9189] +24-11-19 19:26:57 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 19:26:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:26:57 | D | sum error = [ 35.1865, 37.5837, 40.1245, 42.8178, 45.6548] +24-11-19 19:26:57 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 19:26:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:26:57 | D | sum error = [ 48.6418, 51.7908, 55.1059, 58.5981, 62.2625] +24-11-19 19:26:57 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 19:26:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:26:57 | D | sum error = [ 66.1295, 70.2004, 74.4542, 78.9553, 83.6563] +24-11-19 19:26:57 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 19:26:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:26:57 | D | sum error = [ 88.6142, 93.8011, 99.2563, 104.9307, 110.9218] +24-11-19 19:26:57 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 19:26:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:26:57 | D | sum error = [ 117.1657, 123.7220, 130.5776, 137.7431, 145.1953] +24-11-19 19:26:57 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 19:26:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:26:57 | D | sum error = [ 153.0224, 161.1804, 169.6927, 178.5606, 187.8257] +24-11-19 19:26:57 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 19:26:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:26:57 | D | sum error = [ 197.4835, 207.5084, 217.9634, 228.8324, 240.1387] +24-11-19 19:26:57 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 19:26:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:26:57 | D | sum error = [ 251.9088, 264.1203, 276.8067, 289.9459, 303.5853] +24-11-19 19:26:57 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 19:26:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:26:57 | D | sum error = [ 317.7196, 332.3509, 347.4867, 363.1307, 379.3226] +24-11-19 19:26:57 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 19:26:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:26:57 | D | sum error = [ 396.0551, 413.3413, 431.2040, 449.6171, 468.6263] +24-11-19 19:26:57 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 19:26:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:26:57 | D | sum error = [ 488.2035, 508.3659, 529.1081, 550.4467, 572.3907] +24-11-19 19:26:57 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 19:26:57 | D | + error = [8.5217] +24-11-19 19:26:57 | D | - Calibrating model.layers.23.mlp.gate_proj.weight +24-11-19 19:26:57 | D | + w: sint8 +24-11-19 19:26:57 | D | + x: None +24-11-19 19:26:57 | D | + y: None +24-11-19 19:26:57 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:26:57 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:26:57 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:26:57 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:26:57 | D | - range ratio = [ 1.0000] +24-11-19 19:26:57 | D | sum error = [ 10.5799] +24-11-19 19:26:57 | D | best error = [ 10.5799] +24-11-19 19:26:58 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:26:58 | D | sum error = [ 10.4922, 10.4794, 10.5360, 10.6537, 10.8386] +24-11-19 19:26:58 | D | best error = [ 9.8182, 9.5219, 9.3601, 9.2697, 9.2153] +24-11-19 19:26:58 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:26:58 | D | sum error = [ 11.1492, 11.4903, 11.9716, 12.5278, 13.1560] +24-11-19 19:26:58 | D | best error = [ 9.1915, 9.1796, 9.1760, 9.1749, 9.1746] +24-11-19 19:26:58 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:26:58 | D | sum error = [ 13.9365, 14.7886, 15.7768, 16.8213, 18.0019] +24-11-19 19:26:58 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 19:26:58 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:26:58 | D | sum error = [ 19.2701, 20.6381, 22.1343, 23.7196, 25.4413] +24-11-19 19:26:58 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 19:26:58 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:26:58 | D | sum error = [ 27.2435, 29.1692, 31.2740, 33.4758, 35.8269] +24-11-19 19:26:58 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 19:26:58 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:26:58 | D | sum error = [ 38.3227, 40.9621, 43.7764, 46.7295, 49.8914] +24-11-19 19:26:58 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 19:26:58 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:26:58 | D | sum error = [ 53.1864, 56.7060, 60.3905, 64.3075, 68.4369] +24-11-19 19:26:58 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 19:26:58 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:26:58 | D | sum error = [ 72.7875, 77.3853, 82.1985, 87.2889, 92.6532] +24-11-19 19:26:58 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 19:26:58 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:26:58 | D | sum error = [ 98.3015, 104.2510, 110.5287, 117.1001, 124.0446] +24-11-19 19:26:58 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 19:26:58 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:26:58 | D | sum error = [ 131.3335, 138.9841, 147.0442, 155.4821, 164.3398] +24-11-19 19:26:58 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 19:26:58 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:26:58 | D | sum error = [ 173.6309, 183.3487, 193.5543, 204.2361, 215.4630] +24-11-19 19:26:58 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 19:26:58 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:26:58 | D | sum error = [ 227.1644, 239.4223, 252.2242, 265.5801, 279.5443] +24-11-19 19:26:58 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 19:26:58 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:26:58 | D | sum error = [ 294.1127, 309.2929, 325.1086, 341.5979, 358.7572] +24-11-19 19:26:58 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 19:26:58 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:26:58 | D | sum error = [ 376.6162, 395.2064, 414.5140, 434.5787, 455.3841] +24-11-19 19:26:58 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 19:26:58 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:26:58 | D | sum error = [ 476.9582, 499.3131, 522.4514, 546.4019, 571.2022] +24-11-19 19:26:58 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 19:26:58 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:26:58 | D | sum error = [ 596.7633, 623.1835, 650.4275, 678.5199, 707.4450] +24-11-19 19:26:58 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 19:26:58 | D | + error = [9.1746] +24-11-19 19:26:58 | D | - Calibrating model.layers.23.mlp.down_proj.weight +24-11-19 19:26:58 | D | + w: sint8 +24-11-19 19:26:58 | D | + x: None +24-11-19 19:26:58 | D | + y: None +24-11-19 19:26:58 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:26:58 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:26:58 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:26:58 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:26:58 | D | - range ratio = [ 1.0000] +24-11-19 19:26:58 | D | sum error = [ 3.8382] +24-11-19 19:26:58 | D | best error = [ 3.8382] +24-11-19 19:26:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:26:59 | D | sum error = [ 3.7954, 3.7728, 3.7509, 3.7439, 3.7603] +24-11-19 19:26:59 | D | best error = [ 3.6767, 3.5965, 3.5433, 3.5019, 3.4735] +24-11-19 19:26:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:26:59 | D | sum error = [ 3.7770, 3.8180, 3.8670, 3.9416, 4.0337] +24-11-19 19:26:59 | D | best error = [ 3.4525, 3.4371, 3.4246, 3.4154, 3.4106] +24-11-19 19:26:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:26:59 | D | sum error = [ 4.1597, 4.2996, 4.4627, 4.6615, 4.8934] +24-11-19 19:26:59 | D | best error = [ 3.4066, 3.4043, 3.4022, 3.4010, 3.4006] +24-11-19 19:26:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:26:59 | D | sum error = [ 5.1561, 5.4444, 5.7620, 6.1164, 6.5149] +24-11-19 19:26:59 | D | best error = [ 3.4001, 3.3998, 3.3997, 3.3997, 3.3996] +24-11-19 19:26:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:26:59 | D | sum error = [ 6.9465, 7.4092, 7.9003, 8.4463, 9.0288] +24-11-19 19:26:59 | D | best error = [ 3.3996, 3.3996, 3.3996, 3.3996, 3.3996] +24-11-19 19:26:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:26:59 | D | sum error = [ 9.6559, 10.3368, 11.0574, 11.8283, 12.6452] +24-11-19 19:26:59 | D | best error = [ 3.3996, 3.3996, 3.3996, 3.3996, 3.3996] +24-11-19 19:26:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:26:59 | D | sum error = [ 13.5219, 14.4470, 15.4503, 16.4966, 17.6105] +24-11-19 19:26:59 | D | best error = [ 3.3996, 3.3996, 3.3996, 3.3996, 3.3996] +24-11-19 19:26:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:26:59 | D | sum error = [ 18.8000, 20.0566, 21.3879, 22.7918, 24.2810] +24-11-19 19:26:59 | D | best error = [ 3.3996, 3.3996, 3.3996, 3.3996, 3.3996] +24-11-19 19:26:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:26:59 | D | sum error = [ 25.8473, 27.5085, 29.2543, 31.1135, 33.0578] +24-11-19 19:26:59 | D | best error = [ 3.3996, 3.3996, 3.3996, 3.3996, 3.3996] +24-11-19 19:26:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:26:59 | D | sum error = [ 35.1070, 37.2669, 39.5362, 41.9211, 44.4225] +24-11-19 19:26:59 | D | best error = [ 3.3996, 3.3996, 3.3996, 3.3996, 3.3996] +24-11-19 19:26:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:26:59 | D | sum error = [ 47.0558, 49.8139, 52.7001, 55.7370, 58.9161] +24-11-19 19:26:59 | D | best error = [ 3.3996, 3.3996, 3.3996, 3.3996, 3.3996] +24-11-19 19:26:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:26:59 | D | sum error = [ 62.2401, 65.7190, 69.3541, 73.1658, 77.1396] +24-11-19 19:26:59 | D | best error = [ 3.3996, 3.3996, 3.3996, 3.3996, 3.3996] +24-11-19 19:26:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:26:59 | D | sum error = [ 81.2897, 85.6159, 90.1294, 94.8313, 99.7197] +24-11-19 19:26:59 | D | best error = [ 3.3996, 3.3996, 3.3996, 3.3996, 3.3996] +24-11-19 19:26:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:26:59 | D | sum error = [ 104.8146, 110.1024, 115.6031, 121.3248, 127.2518] +24-11-19 19:26:59 | D | best error = [ 3.3996, 3.3996, 3.3996, 3.3996, 3.3996] +24-11-19 19:26:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:26:59 | D | sum error = [ 133.4138, 139.7978, 146.4233, 153.2755, 160.3768] +24-11-19 19:26:59 | D | best error = [ 3.3996, 3.3996, 3.3996, 3.3996, 3.3996] +24-11-19 19:26:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:26:59 | D | sum error = [ 167.7178, 175.3020, 183.1434, 191.2339, 199.5852] +24-11-19 19:26:59 | D | best error = [ 3.3996, 3.3996, 3.3996, 3.3996, 3.3996] +24-11-19 19:26:59 | D | + error = [3.3996] +24-11-19 19:26:59 | D | - Quantizing model.layers.23.self_attn.q_proj.weight +24-11-19 19:27:00 | D | - Quantizing model.layers.23.self_attn.k_proj.weight +24-11-19 19:27:01 | D | - Quantizing model.layers.23.self_attn.v_proj.weight +24-11-19 19:27:02 | D | - Quantizing model.layers.23.self_attn.o_proj.weight +24-11-19 19:27:03 | D | - Quantizing model.layers.23.mlp.up_proj.weight +24-11-19 19:27:04 | D | - Quantizing model.layers.23.mlp.gate_proj.weight +24-11-19 19:27:05 | D | - Quantizing model.layers.23.mlp.down_proj.weight +24-11-19 19:27:14 | D | - Quantizing layer model.layers.24 +24-11-19 19:27:14 | D | - Calibrating model.layers.24.self_attn.q_proj.weight +24-11-19 19:27:14 | D | + w: sint8 +24-11-19 19:27:14 | D | + x: None +24-11-19 19:27:14 | D | + y: None +24-11-19 19:27:14 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:27:14 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:27:14 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:27:14 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:27:15 | D | - range ratio = [ 1.0000] +24-11-19 19:27:15 | D | sum error = [ 15.5414] +24-11-19 19:27:15 | D | best error = [ 15.5414] +24-11-19 19:27:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:27:29 | D | sum error = [ 15.3086, 15.3242, 15.2980, 15.6920, 16.2240] +24-11-19 19:27:29 | D | best error = [ 15.3086, 15.3086, 15.2980, 15.2980, 15.2980] +24-11-19 19:27:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:27:29 | D | sum error = [ 16.5334, 17.5158, 17.7590, 18.8539, 20.7604] +24-11-19 19:27:29 | D | best error = [ 15.2980, 15.2980, 15.2980, 15.2980, 15.2980] +24-11-19 19:27:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:27:29 | D | sum error = [ 21.4191, 22.9759, 24.7339, 26.7647, 29.0331] +24-11-19 19:27:29 | D | best error = [ 15.2980, 15.2980, 15.2980, 15.2980, 15.2980] +24-11-19 19:27:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:27:29 | D | sum error = [ 30.6011, 33.3517, 35.8068, 39.1462, 42.2808] +24-11-19 19:27:29 | D | best error = [ 15.2980, 15.2980, 15.2980, 15.2980, 15.2980] +24-11-19 19:27:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:27:29 | D | sum error = [ 46.4911, 49.8014, 52.3771, 57.2970, 61.6601] +24-11-19 19:27:29 | D | best error = [ 15.2980, 15.2980, 15.2980, 15.2980, 15.2980] +24-11-19 19:27:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:27:29 | D | sum error = [ 66.9473, 71.6912, 78.1522, 82.7336, 89.1131] +24-11-19 19:27:29 | D | best error = [ 15.2980, 15.2980, 15.2980, 15.2980, 15.2980] +24-11-19 19:27:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:27:29 | D | sum error = [ 96.4211, 103.7622, 111.4288, 120.4852, 128.7201] +24-11-19 19:27:29 | D | best error = [ 15.2980, 15.2980, 15.2980, 15.2980, 15.2980] +24-11-19 19:27:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:27:29 | D | sum error = [ 139.4392, 150.1401, 161.8453, 173.7984, 186.2616] +24-11-19 19:27:29 | D | best error = [ 15.2980, 15.2980, 15.2980, 15.2980, 15.2980] +24-11-19 19:27:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:27:29 | D | sum error = [ 200.6531, 215.0939, 230.4394, 248.4699, 266.5310] +24-11-19 19:27:29 | D | best error = [ 15.2980, 15.2980, 15.2980, 15.2980, 15.2980] +24-11-19 19:27:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:27:29 | D | sum error = [ 285.4396, 305.8242, 327.7634, 351.9349, 377.3161] +24-11-19 19:27:29 | D | best error = [ 15.2980, 15.2980, 15.2980, 15.2980, 15.2980] +24-11-19 19:27:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:27:29 | D | sum error = [ 403.8597, 431.6792, 461.6226, 493.7525, 528.0882] +24-11-19 19:27:29 | D | best error = [ 15.2980, 15.2980, 15.2980, 15.2980, 15.2980] +24-11-19 19:27:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:27:29 | D | sum error = [ 565.0981, 605.5358, 647.3774, 693.0238, 742.3512] +24-11-19 19:27:29 | D | best error = [ 15.2980, 15.2980, 15.2980, 15.2980, 15.2980] +24-11-19 19:27:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:27:29 | D | sum error = [ 795.5057, 853.0912, 914.2298, 981.0598, 1053.8136] +24-11-19 19:27:29 | D | best error = [ 15.2980, 15.2980, 15.2980, 15.2980, 15.2980] +24-11-19 19:27:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:27:29 | D | sum error = [ 1133.2976, 1220.1419, 1313.7202, 1417.1273, 1527.7450] +24-11-19 19:27:29 | D | best error = [ 15.2980, 15.2980, 15.2980, 15.2980, 15.2980] +24-11-19 19:27:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:27:29 | D | sum error = [ 1649.5959, 1782.8932, 1926.7410, 2085.2440, 2257.9773] +24-11-19 19:27:29 | D | best error = [ 15.2980, 15.2980, 15.2980, 15.2980, 15.2980] +24-11-19 19:27:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:27:29 | D | sum error = [ 2446.8065, 2654.3245, 2877.2078, 3116.7951, 3371.8986] +24-11-19 19:27:29 | D | best error = [ 15.2980, 15.2980, 15.2980, 15.2980, 15.2980] +24-11-19 19:27:29 | D | + error = [15.2980] +24-11-19 19:27:29 | D | - Calibrating model.layers.24.self_attn.k_proj.weight +24-11-19 19:27:29 | D | + w: sint8 +24-11-19 19:27:29 | D | + x: None +24-11-19 19:27:29 | D | + y: None +24-11-19 19:27:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:27:29 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:27:29 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:27:30 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:27:30 | D | - range ratio = [ 1.0000] +24-11-19 19:27:30 | D | sum error = [ 20.0827] +24-11-19 19:27:30 | D | best error = [ 20.0827] +24-11-19 19:27:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:27:46 | D | sum error = [ 19.0233, 20.3792, 18.3240, 18.2692, 18.7098] +24-11-19 19:27:46 | D | best error = [ 19.0233, 19.0233, 18.3240, 18.2692, 18.2692] +24-11-19 19:27:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:27:46 | D | sum error = [ 20.3655, 20.8299, 20.7004, 22.4467, 22.5296] +24-11-19 19:27:46 | D | best error = [ 18.2692, 18.2692, 18.2692, 18.2692, 18.2692] +24-11-19 19:27:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:27:46 | D | sum error = [ 25.5818, 26.5989, 27.7839, 31.1476, 32.0435] +24-11-19 19:27:46 | D | best error = [ 18.2692, 18.2692, 18.2692, 18.2692, 18.2692] +24-11-19 19:27:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:27:46 | D | sum error = [ 34.2135, 36.5527, 39.1476, 43.2848, 46.7822] +24-11-19 19:27:46 | D | best error = [ 18.2692, 18.2692, 18.2692, 18.2692, 18.2692] +24-11-19 19:27:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:27:46 | D | sum error = [ 49.3468, 52.4746, 55.8441, 61.7056, 66.4410] +24-11-19 19:27:46 | D | best error = [ 18.2692, 18.2692, 18.2692, 18.2692, 18.2692] +24-11-19 19:27:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:27:46 | D | sum error = [ 69.9948, 77.3614, 82.3038, 87.1710, 93.8839] +24-11-19 19:27:46 | D | best error = [ 18.2692, 18.2692, 18.2692, 18.2692, 18.2692] +24-11-19 19:27:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:27:46 | D | sum error = [ 99.4387, 107.1295, 116.0112, 124.8446, 134.5425] +24-11-19 19:27:46 | D | best error = [ 18.2692, 18.2692, 18.2692, 18.2692, 18.2692] +24-11-19 19:27:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:27:46 | D | sum error = [ 144.5858, 154.6392, 166.3071, 181.7511, 194.2611] +24-11-19 19:27:46 | D | best error = [ 18.2692, 18.2692, 18.2692, 18.2692, 18.2692] +24-11-19 19:27:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:27:46 | D | sum error = [ 206.3694, 226.0200, 241.4263, 258.5735, 277.3803] +24-11-19 19:27:46 | D | best error = [ 18.2692, 18.2692, 18.2692, 18.2692, 18.2692] +24-11-19 19:27:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:27:46 | D | sum error = [ 297.3567, 316.0987, 340.0592, 363.3430, 387.6812] +24-11-19 19:27:46 | D | best error = [ 18.2692, 18.2692, 18.2692, 18.2692, 18.2692] +24-11-19 19:27:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:27:46 | D | sum error = [ 414.9516, 445.8422, 479.0576, 507.4793, 543.6752] +24-11-19 19:27:46 | D | best error = [ 18.2692, 18.2692, 18.2692, 18.2692, 18.2692] +24-11-19 19:27:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:27:46 | D | sum error = [ 581.1844, 618.8376, 660.0743, 709.5433, 761.6620] +24-11-19 19:27:46 | D | best error = [ 18.2692, 18.2692, 18.2692, 18.2692, 18.2692] +24-11-19 19:27:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:27:46 | D | sum error = [ 818.3335, 881.8879, 946.5789, 1010.9487, 1088.6741] +24-11-19 19:27:46 | D | best error = [ 18.2692, 18.2692, 18.2692, 18.2692, 18.2692] +24-11-19 19:27:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:27:46 | D | sum error = [ 1170.9555, 1261.7615, 1360.4057, 1463.6416, 1590.1399] +24-11-19 19:27:46 | D | best error = [ 18.2692, 18.2692, 18.2692, 18.2692, 18.2692] +24-11-19 19:27:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:27:46 | D | sum error = [ 1716.4779, 1859.6460, 2014.5406, 2182.3900, 2361.6226] +24-11-19 19:27:46 | D | best error = [ 18.2692, 18.2692, 18.2692, 18.2692, 18.2692] +24-11-19 19:27:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:27:46 | D | sum error = [ 2556.5718, 2773.7412, 2984.2724, 3250.3917, 3514.7270] +24-11-19 19:27:46 | D | best error = [ 18.2692, 18.2692, 18.2692, 18.2692, 18.2692] +24-11-19 19:27:46 | D | + error = [18.2692] +24-11-19 19:27:46 | D | - Calibrating model.layers.24.self_attn.v_proj.weight +24-11-19 19:27:46 | D | + w: sint8 +24-11-19 19:27:46 | D | + x: None +24-11-19 19:27:46 | D | + y: None +24-11-19 19:27:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:27:46 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:27:46 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:27:46 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:27:46 | D | - range ratio = [ 1.0000] +24-11-19 19:27:46 | D | sum error = [ 7.5831] +24-11-19 19:27:46 | D | best error = [ 7.5831] +24-11-19 19:27:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:27:47 | D | sum error = [ 7.4951, 7.4983, 7.5468, 7.6343, 7.7737] +24-11-19 19:27:47 | D | best error = [ 7.0518, 6.8502, 6.7476, 6.6821, 6.6460] +24-11-19 19:27:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:27:47 | D | sum error = [ 7.9662, 8.2177, 8.5664, 8.9474, 9.4383] +24-11-19 19:27:47 | D | best error = [ 6.6287, 6.6211, 6.6180, 6.6166, 6.6165] +24-11-19 19:27:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:27:47 | D | sum error = [ 10.0044, 10.5968, 11.2809, 12.0598, 12.8548] +24-11-19 19:27:47 | D | best error = [ 6.6165, 6.6165, 6.6165, 6.6165, 6.6165] +24-11-19 19:27:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:27:47 | D | sum error = [ 13.7971, 14.7656, 15.8220, 16.9393, 18.1520] +24-11-19 19:27:47 | D | best error = [ 6.6165, 6.6165, 6.6165, 6.6165, 6.6165] +24-11-19 19:27:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:27:47 | D | sum error = [ 19.4638, 20.8264, 22.3029, 23.8330, 25.4942] +24-11-19 19:27:47 | D | best error = [ 6.6165, 6.6165, 6.6165, 6.6165, 6.6165] +24-11-19 19:27:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:27:47 | D | sum error = [ 27.2447, 29.0680, 31.0166, 33.1077, 35.2633] +24-11-19 19:27:47 | D | best error = [ 6.6165, 6.6165, 6.6165, 6.6165, 6.6165] +24-11-19 19:27:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:27:47 | D | sum error = [ 37.5319, 39.9560, 42.5058, 45.1700, 47.9824] +24-11-19 19:27:47 | D | best error = [ 6.6165, 6.6165, 6.6165, 6.6165, 6.6165] +24-11-19 19:27:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:27:47 | D | sum error = [ 50.9509, 54.0655, 57.3360, 60.7352, 64.3621] +24-11-19 19:27:47 | D | best error = [ 6.6165, 6.6165, 6.6165, 6.6165, 6.6165] +24-11-19 19:27:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:27:47 | D | sum error = [ 68.1362, 72.1075, 76.2860, 80.5924, 85.1689] +24-11-19 19:27:47 | D | best error = [ 6.6165, 6.6165, 6.6165, 6.6165, 6.6165] +24-11-19 19:27:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:27:47 | D | sum error = [ 89.9192, 94.9048, 100.1079, 105.5366, 111.2277] +24-11-19 19:27:47 | D | best error = [ 6.6165, 6.6165, 6.6165, 6.6165, 6.6165] +24-11-19 19:27:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:27:47 | D | sum error = [ 117.1258, 123.3119, 129.7352, 136.4518, 143.4206] +24-11-19 19:27:47 | D | best error = [ 6.6165, 6.6165, 6.6165, 6.6165, 6.6165] +24-11-19 19:27:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:27:47 | D | sum error = [ 150.6841, 158.2030, 166.0581, 174.1697, 182.6127] +24-11-19 19:27:47 | D | best error = [ 6.6165, 6.6165, 6.6165, 6.6165, 6.6165] +24-11-19 19:27:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:27:47 | D | sum error = [ 191.3761, 200.4573, 209.8690, 219.6423, 229.7514] +24-11-19 19:27:47 | D | best error = [ 6.6165, 6.6165, 6.6165, 6.6165, 6.6165] +24-11-19 19:27:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:27:47 | D | sum error = [ 240.2095, 251.0327, 262.2178, 273.7911, 285.7119] +24-11-19 19:27:47 | D | best error = [ 6.6165, 6.6165, 6.6165, 6.6165, 6.6165] +24-11-19 19:27:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:27:47 | D | sum error = [ 298.0143, 310.7103, 323.7952, 337.2684, 351.1618] +24-11-19 19:27:47 | D | best error = [ 6.6165, 6.6165, 6.6165, 6.6165, 6.6165] +24-11-19 19:27:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:27:47 | D | sum error = [ 365.4432, 380.1426, 395.2754, 410.8485, 426.8685] +24-11-19 19:27:47 | D | best error = [ 6.6165, 6.6165, 6.6165, 6.6165, 6.6165] +24-11-19 19:27:47 | D | + error = [6.6165] +24-11-19 19:27:47 | D | - Calibrating model.layers.24.self_attn.o_proj.weight +24-11-19 19:27:47 | D | + w: sint8 +24-11-19 19:27:47 | D | + x: None +24-11-19 19:27:47 | D | + y: None +24-11-19 19:27:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:27:47 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:27:47 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:27:47 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:27:47 | D | - range ratio = [ 1.0000] +24-11-19 19:27:47 | D | sum error = [ 1.6954] +24-11-19 19:27:47 | D | best error = [ 1.6954] +24-11-19 19:27:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:27:48 | D | sum error = [ 1.6808, 1.6693, 1.6710, 1.6756, 1.6908] +24-11-19 19:27:48 | D | best error = [ 1.5745, 1.5195, 1.4885, 1.4672, 1.4520] +24-11-19 19:27:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:27:48 | D | sum error = [ 1.7203, 1.7567, 1.8015, 1.8592, 1.9348] +24-11-19 19:27:48 | D | best error = [ 1.4424, 1.4343, 1.4293, 1.4257, 1.4236] +24-11-19 19:27:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:27:48 | D | sum error = [ 2.0276, 2.1279, 2.2329, 2.3609, 2.5035] +24-11-19 19:27:48 | D | best error = [ 1.4219, 1.4210, 1.4201, 1.4196, 1.4193] +24-11-19 19:27:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:27:48 | D | sum error = [ 2.6607, 2.8327, 3.0170, 3.2229, 3.4418] +24-11-19 19:27:48 | D | best error = [ 1.4192, 1.4190, 1.4188, 1.4187, 1.4186] +24-11-19 19:27:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:27:48 | D | sum error = [ 3.6853, 3.9417, 4.2106, 4.4982, 4.8091] +24-11-19 19:27:48 | D | best error = [ 1.4186, 1.4186, 1.4186, 1.4186, 1.4186] +24-11-19 19:27:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:27:48 | D | sum error = [ 5.1369, 5.4924, 5.8593, 6.2476, 6.6677] +24-11-19 19:27:48 | D | best error = [ 1.4186, 1.4186, 1.4186, 1.4186, 1.4186] +24-11-19 19:27:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:27:48 | D | sum error = [ 7.1180, 7.5858, 8.0783, 8.6044, 9.1582] +24-11-19 19:27:48 | D | best error = [ 1.4186, 1.4186, 1.4186, 1.4186, 1.4186] +24-11-19 19:27:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:27:48 | D | sum error = [ 9.7473, 10.3745, 11.0294, 11.7275, 12.4613] +24-11-19 19:27:48 | D | best error = [ 1.4186, 1.4186, 1.4186, 1.4186, 1.4186] +24-11-19 19:27:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:27:48 | D | sum error = [ 13.2358, 14.0568, 14.9245, 15.8394, 16.7998] +24-11-19 19:27:48 | D | best error = [ 1.4186, 1.4186, 1.4186, 1.4186, 1.4186] +24-11-19 19:27:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:27:48 | D | sum error = [ 17.8138, 18.8820, 20.0012, 21.1809, 22.4256] +24-11-19 19:27:48 | D | best error = [ 1.4186, 1.4186, 1.4186, 1.4186, 1.4186] +24-11-19 19:27:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:27:48 | D | sum error = [ 23.7292, 25.1075, 26.5486, 28.0631, 29.6572] +24-11-19 19:27:48 | D | best error = [ 1.4186, 1.4186, 1.4186, 1.4186, 1.4186] +24-11-19 19:27:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:27:48 | D | sum error = [ 31.3238, 33.0744, 34.9141, 36.8440, 38.8665] +24-11-19 19:27:48 | D | best error = [ 1.4186, 1.4186, 1.4186, 1.4186, 1.4186] +24-11-19 19:27:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:27:48 | D | sum error = [ 40.9805, 43.1912, 45.5094, 47.9310, 50.4595] +24-11-19 19:27:48 | D | best error = [ 1.4186, 1.4186, 1.4186, 1.4186, 1.4186] +24-11-19 19:27:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:27:48 | D | sum error = [ 53.1000, 55.8529, 58.7268, 61.7238, 64.8297] +24-11-19 19:27:48 | D | best error = [ 1.4186, 1.4186, 1.4186, 1.4186, 1.4186] +24-11-19 19:27:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:27:48 | D | sum error = [ 68.0602, 71.4210, 74.9031, 78.5175, 82.2670] +24-11-19 19:27:48 | D | best error = [ 1.4186, 1.4186, 1.4186, 1.4186, 1.4186] +24-11-19 19:27:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:27:48 | D | sum error = [ 86.1510, 90.1862, 94.3612, 98.6832, 103.1549] +24-11-19 19:27:48 | D | best error = [ 1.4186, 1.4186, 1.4186, 1.4186, 1.4186] +24-11-19 19:27:48 | D | + error = [1.4186] +24-11-19 19:27:48 | D | - Calibrating model.layers.24.mlp.up_proj.weight +24-11-19 19:27:48 | D | + w: sint8 +24-11-19 19:27:48 | D | + x: None +24-11-19 19:27:48 | D | + y: None +24-11-19 19:27:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:27:48 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:27:48 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:27:48 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:27:48 | D | - range ratio = [ 1.0000] +24-11-19 19:27:48 | D | sum error = [ 10.1793] +24-11-19 19:27:48 | D | best error = [ 10.1793] +24-11-19 19:27:49 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:27:49 | D | sum error = [ 10.0911, 10.0501, 10.0864, 10.2415, 10.3965] +24-11-19 19:27:49 | D | best error = [ 9.4021, 9.1065, 8.9461, 8.8596, 8.8091] +24-11-19 19:27:49 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:27:49 | D | sum error = [ 10.6641, 11.0446, 11.4702, 12.0137, 12.6394] +24-11-19 19:27:49 | D | best error = [ 8.7847, 8.7732, 8.7684, 8.7669, 8.7666] +24-11-19 19:27:49 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:27:49 | D | sum error = [ 13.3530, 14.2020, 15.0935, 16.1366, 17.2342] +24-11-19 19:27:49 | D | best error = [ 8.7666, 8.7666, 8.7666, 8.7666, 8.7666] +24-11-19 19:27:49 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:27:49 | D | sum error = [ 18.4309, 19.7369, 21.1775, 22.6625, 24.2800] +24-11-19 19:27:49 | D | best error = [ 8.7666, 8.7666, 8.7666, 8.7666, 8.7666] +24-11-19 19:27:49 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:27:49 | D | sum error = [ 26.0481, 27.8856, 29.8480, 31.9229, 34.1464] +24-11-19 19:27:49 | D | best error = [ 8.7666, 8.7666, 8.7666, 8.7666, 8.7666] +24-11-19 19:27:49 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:27:49 | D | sum error = [ 36.4887, 38.9603, 41.5912, 44.3362, 47.2610] +24-11-19 19:27:49 | D | best error = [ 8.7666, 8.7666, 8.7666, 8.7666, 8.7666] +24-11-19 19:27:49 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:27:49 | D | sum error = [ 50.3604, 53.5841, 57.0062, 60.6050, 64.4001] +24-11-19 19:27:49 | D | best error = [ 8.7666, 8.7666, 8.7666, 8.7666, 8.7666] +24-11-19 19:27:49 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:27:49 | D | sum error = [ 68.3633, 72.5932, 76.9908, 81.6381, 86.4945] +24-11-19 19:27:49 | D | best error = [ 8.7666, 8.7666, 8.7666, 8.7666, 8.7666] +24-11-19 19:27:49 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:27:49 | D | sum error = [ 91.6061, 96.9663, 102.5995, 108.4743, 114.6405] +24-11-19 19:27:49 | D | best error = [ 8.7666, 8.7666, 8.7666, 8.7666, 8.7666] +24-11-19 19:27:49 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:27:49 | D | sum error = [ 121.1269, 127.8748, 134.9563, 142.3328, 150.0550] +24-11-19 19:27:49 | D | best error = [ 8.7666, 8.7666, 8.7666, 8.7666, 8.7666] +24-11-19 19:27:49 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:27:49 | D | sum error = [ 158.1169, 166.5094, 175.2687, 184.4028, 193.9132] +24-11-19 19:27:49 | D | best error = [ 8.7666, 8.7666, 8.7666, 8.7666, 8.7666] +24-11-19 19:27:49 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:27:49 | D | sum error = [ 203.8141, 214.1284, 224.8464, 235.9997, 247.5715] +24-11-19 19:27:49 | D | best error = [ 8.7666, 8.7666, 8.7666, 8.7666, 8.7666] +24-11-19 19:27:49 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:27:49 | D | sum error = [ 259.5914, 272.0716, 285.0225, 298.4302, 312.3343] +24-11-19 19:27:49 | D | best error = [ 8.7666, 8.7666, 8.7666, 8.7666, 8.7666] +24-11-19 19:27:49 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:27:49 | D | sum error = [ 326.7252, 341.6395, 357.0590, 372.9943, 389.4702] +24-11-19 19:27:49 | D | best error = [ 8.7666, 8.7666, 8.7666, 8.7666, 8.7666] +24-11-19 19:27:49 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:27:49 | D | sum error = [ 406.4886, 424.0437, 442.1540, 460.8272, 480.0792] +24-11-19 19:27:49 | D | best error = [ 8.7666, 8.7666, 8.7666, 8.7666, 8.7666] +24-11-19 19:27:49 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:27:49 | D | sum error = [ 499.8660, 520.2699, 541.2383, 562.8022, 584.9616] +24-11-19 19:27:49 | D | best error = [ 8.7666, 8.7666, 8.7666, 8.7666, 8.7666] +24-11-19 19:27:49 | D | + error = [8.7666] +24-11-19 19:27:49 | D | - Calibrating model.layers.24.mlp.gate_proj.weight +24-11-19 19:27:49 | D | + w: sint8 +24-11-19 19:27:49 | D | + x: None +24-11-19 19:27:49 | D | + y: None +24-11-19 19:27:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:27:49 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:27:49 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:27:49 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:27:49 | D | - range ratio = [ 1.0000] +24-11-19 19:27:49 | D | sum error = [ 10.9379] +24-11-19 19:27:49 | D | best error = [ 10.9379] +24-11-19 19:27:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:27:50 | D | sum error = [ 10.8679, 10.8292, 10.8482, 10.9818, 11.1959] +24-11-19 19:27:50 | D | best error = [ 10.1236, 9.8020, 9.6280, 9.5267, 9.4703] +24-11-19 19:27:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:27:50 | D | sum error = [ 11.4686, 11.8780, 12.3425, 12.9481, 13.6201] +24-11-19 19:27:50 | D | best error = [ 9.4422, 9.4305, 9.4254, 9.4237, 9.4234] +24-11-19 19:27:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:27:50 | D | sum error = [ 14.4037, 15.2861, 16.3273, 17.4114, 18.6366] +24-11-19 19:27:50 | D | best error = [ 9.4234, 9.4233, 9.4233, 9.4233, 9.4233] +24-11-19 19:27:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:27:50 | D | sum error = [ 19.9510, 21.3938, 22.9408, 24.6144, 26.4156] +24-11-19 19:27:50 | D | best error = [ 9.4233, 9.4233, 9.4233, 9.4233, 9.4233] +24-11-19 19:27:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:27:50 | D | sum error = [ 28.3296, 30.3524, 32.4957, 34.8230, 37.2545] +24-11-19 19:27:50 | D | best error = [ 9.4233, 9.4233, 9.4233, 9.4233, 9.4233] +24-11-19 19:27:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:27:50 | D | sum error = [ 39.8645, 42.5899, 45.5252, 48.6067, 51.8855] +24-11-19 19:27:50 | D | best error = [ 9.4233, 9.4233, 9.4233, 9.4233, 9.4233] +24-11-19 19:27:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:27:50 | D | sum error = [ 55.3159, 58.9598, 62.7984, 66.8474, 71.1091] +24-11-19 19:27:50 | D | best error = [ 9.4233, 9.4233, 9.4233, 9.4233, 9.4233] +24-11-19 19:27:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:27:50 | D | sum error = [ 75.6198, 80.3589, 85.3457, 90.6173, 96.1436] +24-11-19 19:27:50 | D | best error = [ 9.4233, 9.4233, 9.4233, 9.4233, 9.4233] +24-11-19 19:27:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:27:50 | D | sum error = [ 102.0062, 108.0824, 114.5322, 121.2573, 128.3406] +24-11-19 19:27:50 | D | best error = [ 9.4233, 9.4233, 9.4233, 9.4233, 9.4233] +24-11-19 19:27:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:27:50 | D | sum error = [ 135.8354, 143.7009, 151.8965, 160.5522, 169.5834] +24-11-19 19:27:50 | D | best error = [ 9.4233, 9.4233, 9.4233, 9.4233, 9.4233] +24-11-19 19:27:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:27:50 | D | sum error = [ 179.0506, 189.0078, 199.4301, 210.3216, 221.7229] +24-11-19 19:27:50 | D | best error = [ 9.4233, 9.4233, 9.4233, 9.4233, 9.4233] +24-11-19 19:27:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:27:50 | D | sum error = [ 233.6552, 246.1301, 259.1492, 272.7185, 286.8738] +24-11-19 19:27:50 | D | best error = [ 9.4233, 9.4233, 9.4233, 9.4233, 9.4233] +24-11-19 19:27:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:27:50 | D | sum error = [ 301.6689, 317.0784, 333.1394, 349.8226, 367.2019] +24-11-19 19:27:50 | D | best error = [ 9.4233, 9.4233, 9.4233, 9.4233, 9.4233] +24-11-19 19:27:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:27:50 | D | sum error = [ 385.2613, 404.0700, 423.5875, 443.8493, 464.8466] +24-11-19 19:27:50 | D | best error = [ 9.4233, 9.4233, 9.4233, 9.4233, 9.4233] +24-11-19 19:27:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:27:50 | D | sum error = [ 486.5896, 509.1028, 532.4111, 556.4971, 581.4192] +24-11-19 19:27:50 | D | best error = [ 9.4233, 9.4233, 9.4233, 9.4233, 9.4233] +24-11-19 19:27:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:27:50 | D | sum error = [ 607.1408, 633.6961, 661.0602, 689.2524, 718.2974] +24-11-19 19:27:50 | D | best error = [ 9.4233, 9.4233, 9.4233, 9.4233, 9.4233] +24-11-19 19:27:50 | D | + error = [9.4233] +24-11-19 19:27:50 | D | - Calibrating model.layers.24.mlp.down_proj.weight +24-11-19 19:27:50 | D | + w: sint8 +24-11-19 19:27:50 | D | + x: None +24-11-19 19:27:50 | D | + y: None +24-11-19 19:27:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:27:50 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:27:50 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:27:50 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:27:50 | D | - range ratio = [ 1.0000] +24-11-19 19:27:50 | D | sum error = [ 3.9006] +24-11-19 19:27:50 | D | best error = [ 3.9006] +24-11-19 19:27:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:27:51 | D | sum error = [ 3.8708, 3.8526, 3.8228, 3.8143, 3.8165] +24-11-19 19:27:51 | D | best error = [ 3.7467, 3.6719, 3.6176, 3.5793, 3.5513] +24-11-19 19:27:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:27:51 | D | sum error = [ 3.8299, 3.8646, 3.9239, 3.9860, 4.0876] +24-11-19 19:27:51 | D | best error = [ 3.5300, 3.5137, 3.5022, 3.4937, 3.4876] +24-11-19 19:27:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:27:51 | D | sum error = [ 4.2029, 4.3396, 4.5059, 4.6968, 4.9250] +24-11-19 19:27:51 | D | best error = [ 3.4834, 3.4812, 3.4795, 3.4784, 3.4779] +24-11-19 19:27:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:27:51 | D | sum error = [ 5.1787, 5.4658, 5.7801, 6.1234, 6.5194] +24-11-19 19:27:51 | D | best error = [ 3.4776, 3.4775, 3.4774, 3.4773, 3.4773] +24-11-19 19:27:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:27:51 | D | sum error = [ 6.9443, 7.4021, 7.9030, 8.4358, 9.0152] +24-11-19 19:27:51 | D | best error = [ 3.4773, 3.4773, 3.4773, 3.4773, 3.4772] +24-11-19 19:27:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:27:51 | D | sum error = [ 9.6426, 10.3145, 11.0310, 11.8064, 12.6214] +24-11-19 19:27:51 | D | best error = [ 3.4772, 3.4772, 3.4772, 3.4772, 3.4772] +24-11-19 19:27:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:27:51 | D | sum error = [ 13.4956, 14.4268, 15.4200, 16.4682, 17.5921] +24-11-19 19:27:51 | D | best error = [ 3.4772, 3.4772, 3.4772, 3.4772, 3.4772] +24-11-19 19:27:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:27:51 | D | sum error = [ 18.7880, 20.0430, 21.3879, 22.7989, 24.2954] +24-11-19 19:27:51 | D | best error = [ 3.4772, 3.4772, 3.4772, 3.4772, 3.4772] +24-11-19 19:27:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:27:51 | D | sum error = [ 25.8737, 27.5510, 29.3140, 31.1698, 33.1259] +24-11-19 19:27:51 | D | best error = [ 3.4772, 3.4772, 3.4772, 3.4772, 3.4772] +24-11-19 19:27:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:27:51 | D | sum error = [ 35.1930, 37.3701, 39.6548, 42.0540, 44.5909] +24-11-19 19:27:51 | D | best error = [ 3.4772, 3.4772, 3.4772, 3.4772, 3.4772] +24-11-19 19:27:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:27:51 | D | sum error = [ 47.2421, 50.0344, 52.9562, 56.0252, 59.2341] +24-11-19 19:27:51 | D | best error = [ 3.4772, 3.4772, 3.4772, 3.4772, 3.4772] +24-11-19 19:27:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:27:51 | D | sum error = [ 62.6004, 66.1195, 69.8077, 73.6586, 77.6843] +24-11-19 19:27:51 | D | best error = [ 3.4772, 3.4772, 3.4772, 3.4772, 3.4772] +24-11-19 19:27:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:27:51 | D | sum error = [ 81.8808, 86.2515, 90.8214, 95.5797, 100.5360] +24-11-19 19:27:51 | D | best error = [ 3.4772, 3.4772, 3.4772, 3.4772, 3.4772] +24-11-19 19:27:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:27:51 | D | sum error = [ 105.6954, 111.0646, 116.6507, 122.4591, 128.4653] +24-11-19 19:27:51 | D | best error = [ 3.4772, 3.4772, 3.4772, 3.4772, 3.4772] +24-11-19 19:27:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:27:51 | D | sum error = [ 134.7078, 141.1826, 147.8951, 154.8499, 162.0485] +24-11-19 19:27:51 | D | best error = [ 3.4772, 3.4772, 3.4772, 3.4772, 3.4772] +24-11-19 19:27:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:27:51 | D | sum error = [ 169.4971, 177.1965, 185.1537, 193.3761, 201.8553] +24-11-19 19:27:51 | D | best error = [ 3.4772, 3.4772, 3.4772, 3.4772, 3.4772] +24-11-19 19:27:51 | D | + error = [3.4772] +24-11-19 19:27:51 | D | - Quantizing model.layers.24.self_attn.q_proj.weight +24-11-19 19:27:52 | D | - Quantizing model.layers.24.self_attn.k_proj.weight +24-11-19 19:27:53 | D | - Quantizing model.layers.24.self_attn.v_proj.weight +24-11-19 19:27:54 | D | - Quantizing model.layers.24.self_attn.o_proj.weight +24-11-19 19:27:55 | D | - Quantizing model.layers.24.mlp.up_proj.weight +24-11-19 19:27:56 | D | - Quantizing model.layers.24.mlp.gate_proj.weight +24-11-19 19:27:57 | D | - Quantizing model.layers.24.mlp.down_proj.weight +24-11-19 19:28:06 | D | - Quantizing layer model.layers.25 +24-11-19 19:28:06 | D | - Calibrating model.layers.25.self_attn.q_proj.weight +24-11-19 19:28:06 | D | + w: sint8 +24-11-19 19:28:06 | D | + x: None +24-11-19 19:28:06 | D | + y: None +24-11-19 19:28:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:28:06 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:28:06 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:28:06 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:28:06 | D | - range ratio = [ 1.0000] +24-11-19 19:28:06 | D | sum error = [ 13.9668] +24-11-19 19:28:06 | D | best error = [ 13.9668] +24-11-19 19:28:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:28:20 | D | sum error = [ 13.6150, 13.9500, 13.8881, 14.1094, 14.4120] +24-11-19 19:28:20 | D | best error = [ 13.6150, 13.6150, 13.6150, 13.6150, 13.6150] +24-11-19 19:28:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:28:20 | D | sum error = [ 14.8541, 15.1978, 15.7925, 16.7341, 17.2293] +24-11-19 19:28:20 | D | best error = [ 13.6150, 13.6150, 13.6150, 13.6150, 13.6150] +24-11-19 19:28:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:28:20 | D | sum error = [ 18.3899, 19.5957, 21.0581, 22.2786, 23.9909] +24-11-19 19:28:20 | D | best error = [ 13.6150, 13.6150, 13.6150, 13.6150, 13.6150] +24-11-19 19:28:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:28:20 | D | sum error = [ 25.6597, 27.9423, 30.0446, 32.0865, 34.8492] +24-11-19 19:28:20 | D | best error = [ 13.6150, 13.6150, 13.6150, 13.6150, 13.6150] +24-11-19 19:28:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:28:20 | D | sum error = [ 37.3629, 40.5713, 43.8761, 47.0863, 50.7255] +24-11-19 19:28:20 | D | best error = [ 13.6150, 13.6150, 13.6150, 13.6150, 13.6150] +24-11-19 19:28:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:28:20 | D | sum error = [ 54.8517, 58.7120, 63.8264, 68.4561, 73.5200] +24-11-19 19:28:20 | D | best error = [ 13.6150, 13.6150, 13.6150, 13.6150, 13.6150] +24-11-19 19:28:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:28:20 | D | sum error = [ 79.0070, 85.2840, 91.2872, 98.0902, 105.4492] +24-11-19 19:28:20 | D | best error = [ 13.6150, 13.6150, 13.6150, 13.6150, 13.6150] +24-11-19 19:28:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:28:20 | D | sum error = [ 113.0241, 121.4509, 130.3998, 140.0622, 150.3001] +24-11-19 19:28:20 | D | best error = [ 13.6150, 13.6150, 13.6150, 13.6150, 13.6150] +24-11-19 19:28:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:28:20 | D | sum error = [ 161.2058, 173.1346, 186.0180, 199.6248, 214.0463] +24-11-19 19:28:20 | D | best error = [ 13.6150, 13.6150, 13.6150, 13.6150, 13.6150] +24-11-19 19:28:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:28:20 | D | sum error = [ 230.3275, 247.1308, 265.2883, 285.0486, 306.1528] +24-11-19 19:28:20 | D | best error = [ 13.6150, 13.6150, 13.6150, 13.6150, 13.6150] +24-11-19 19:28:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:28:20 | D | sum error = [ 328.9598, 353.8661, 380.4655, 409.4404, 441.5213] +24-11-19 19:28:20 | D | best error = [ 13.6150, 13.6150, 13.6150, 13.6150, 13.6150] +24-11-19 19:28:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:28:20 | D | sum error = [ 475.3569, 512.0408, 553.2166, 597.5953, 646.0549] +24-11-19 19:28:20 | D | best error = [ 13.6150, 13.6150, 13.6150, 13.6150, 13.6150] +24-11-19 19:28:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:28:20 | D | sum error = [ 699.7308, 758.8185, 823.4370, 894.7971, 973.5496] +24-11-19 19:28:20 | D | best error = [ 13.6150, 13.6150, 13.6150, 13.6150, 13.6150] +24-11-19 19:28:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:28:20 | D | sum error = [ 1060.3778, 1155.8244, 1262.0369, 1379.2222, 1508.2529] +24-11-19 19:28:20 | D | best error = [ 13.6150, 13.6150, 13.6150, 13.6150, 13.6150] +24-11-19 19:28:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:28:20 | D | sum error = [ 1652.3629, 1812.1861, 1990.3635, 2190.3352, 2411.1008] +24-11-19 19:28:20 | D | best error = [ 13.6150, 13.6150, 13.6150, 13.6150, 13.6150] +24-11-19 19:28:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:28:20 | D | sum error = [ 2658.3305, 2931.6691, 3234.7779, 3571.2571, 3938.8528] +24-11-19 19:28:20 | D | best error = [ 13.6150, 13.6150, 13.6150, 13.6150, 13.6150] +24-11-19 19:28:20 | D | + error = [13.6150] +24-11-19 19:28:20 | D | - Calibrating model.layers.25.self_attn.k_proj.weight +24-11-19 19:28:20 | D | + w: sint8 +24-11-19 19:28:20 | D | + x: None +24-11-19 19:28:20 | D | + y: None +24-11-19 19:28:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:28:20 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:28:20 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:28:20 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:28:20 | D | - range ratio = [ 1.0000] +24-11-19 19:28:20 | D | sum error = [ 16.9887] +24-11-19 19:28:20 | D | best error = [ 16.9887] +24-11-19 19:28:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:28:33 | D | sum error = [ 16.8789, 15.6994, 16.4972, 16.9976, 17.1129] +24-11-19 19:28:33 | D | best error = [ 16.8789, 15.6994, 15.6994, 15.6994, 15.6994] +24-11-19 19:28:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:28:33 | D | sum error = [ 16.3974, 17.5283, 18.5398, 19.1692, 21.2924] +24-11-19 19:28:33 | D | best error = [ 15.6994, 15.6994, 15.6994, 15.6994, 15.6994] +24-11-19 19:28:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:28:33 | D | sum error = [ 22.4699, 23.6727, 25.6329, 25.9107, 28.3852] +24-11-19 19:28:33 | D | best error = [ 15.6994, 15.6994, 15.6994, 15.6994, 15.6994] +24-11-19 19:28:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:28:33 | D | sum error = [ 31.8409, 34.6808, 36.2646, 38.4251, 41.8655] +24-11-19 19:28:33 | D | best error = [ 15.6994, 15.6994, 15.6994, 15.6994, 15.6994] +24-11-19 19:28:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:28:33 | D | sum error = [ 45.2303, 48.3227, 52.4330, 55.5470, 60.1236] +24-11-19 19:28:33 | D | best error = [ 15.6994, 15.6994, 15.6994, 15.6994, 15.6994] +24-11-19 19:28:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:28:33 | D | sum error = [ 64.5026, 68.6345, 73.6671, 79.3864, 85.4557] +24-11-19 19:28:33 | D | best error = [ 15.6994, 15.6994, 15.6994, 15.6994, 15.6994] +24-11-19 19:28:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:28:33 | D | sum error = [ 91.1211, 98.3092, 106.2838, 114.2401, 122.0878] +24-11-19 19:28:33 | D | best error = [ 15.6994, 15.6994, 15.6994, 15.6994, 15.6994] +24-11-19 19:28:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:28:33 | D | sum error = [ 131.4540, 140.5595, 151.8318, 162.6511, 174.3130] +24-11-19 19:28:33 | D | best error = [ 15.6994, 15.6994, 15.6994, 15.6994, 15.6994] +24-11-19 19:28:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:28:33 | D | sum error = [ 187.0141, 200.6065, 214.6198, 230.6693, 245.7116] +24-11-19 19:28:33 | D | best error = [ 15.6994, 15.6994, 15.6994, 15.6994, 15.6994] +24-11-19 19:28:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:28:33 | D | sum error = [ 263.3951, 283.9861, 303.3959, 326.3462, 351.5331] +24-11-19 19:28:33 | D | best error = [ 15.6994, 15.6994, 15.6994, 15.6994, 15.6994] +24-11-19 19:28:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:28:33 | D | sum error = [ 378.4800, 407.6231, 440.1873, 474.0546, 509.3034] +24-11-19 19:28:33 | D | best error = [ 15.6994, 15.6994, 15.6994, 15.6994, 15.6994] +24-11-19 19:28:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:28:33 | D | sum error = [ 550.5846, 591.0425, 639.3525, 692.2870, 748.1552] +24-11-19 19:28:33 | D | best error = [ 15.6994, 15.6994, 15.6994, 15.6994, 15.6994] +24-11-19 19:28:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:28:33 | D | sum error = [ 811.6539, 874.9516, 947.4902, 1026.7038, 1112.9041] +24-11-19 19:28:33 | D | best error = [ 15.6994, 15.6994, 15.6994, 15.6994, 15.6994] +24-11-19 19:28:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:28:33 | D | sum error = [ 1208.0227, 1312.4024, 1431.2803, 1560.9061, 1697.0535] +24-11-19 19:28:33 | D | best error = [ 15.6994, 15.6994, 15.6994, 15.6994, 15.6994] +24-11-19 19:28:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:28:33 | D | sum error = [ 1858.9107, 2024.6281, 2210.2004, 2426.6841, 2645.0406] +24-11-19 19:28:33 | D | best error = [ 15.6994, 15.6994, 15.6994, 15.6994, 15.6994] +24-11-19 19:28:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:28:33 | D | sum error = [ 2912.1930, 3182.7366, 3498.8049, 3840.3771, 4201.9015] +24-11-19 19:28:33 | D | best error = [ 15.6994, 15.6994, 15.6994, 15.6994, 15.6994] +24-11-19 19:28:33 | D | + error = [15.6994] +24-11-19 19:28:34 | D | - Calibrating model.layers.25.self_attn.v_proj.weight +24-11-19 19:28:34 | D | + w: sint8 +24-11-19 19:28:34 | D | + x: None +24-11-19 19:28:34 | D | + y: None +24-11-19 19:28:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:28:34 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:28:34 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:28:34 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:28:34 | D | - range ratio = [ 1.0000] +24-11-19 19:28:34 | D | sum error = [ 8.5744] +24-11-19 19:28:34 | D | best error = [ 8.5744] +24-11-19 19:28:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:28:34 | D | sum error = [ 8.4819, 8.4720, 8.5308, 8.6379, 8.7936] +24-11-19 19:28:34 | D | best error = [ 7.9243, 7.6883, 7.5637, 7.4922, 7.4521] +24-11-19 19:28:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:28:34 | D | sum error = [ 8.9695, 9.2968, 9.7193, 10.0967, 10.6745] +24-11-19 19:28:34 | D | best error = [ 7.4286, 7.4189, 7.4155, 7.4140, 7.4136] +24-11-19 19:28:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:28:34 | D | sum error = [ 11.2796, 11.9377, 12.7632, 13.6025, 14.4911] +24-11-19 19:28:34 | D | best error = [ 7.4136, 7.4136, 7.4136, 7.4136, 7.4136] +24-11-19 19:28:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:28:34 | D | sum error = [ 15.5428, 16.6421, 17.8073, 19.1457, 20.4842] +24-11-19 19:28:34 | D | best error = [ 7.4136, 7.4136, 7.4136, 7.4136, 7.4136] +24-11-19 19:28:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:28:34 | D | sum error = [ 21.9516, 23.4853, 25.1720, 26.9282, 28.7703] +24-11-19 19:28:34 | D | best error = [ 7.4136, 7.4136, 7.4136, 7.4136, 7.4136] +24-11-19 19:28:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:28:34 | D | sum error = [ 30.7715, 32.8924, 35.0741, 37.4050, 39.8247] +24-11-19 19:28:34 | D | best error = [ 7.4136, 7.4136, 7.4136, 7.4136, 7.4136] +24-11-19 19:28:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:28:34 | D | sum error = [ 42.4567, 45.2095, 48.0895, 51.1661, 54.3848] +24-11-19 19:28:34 | D | best error = [ 7.4136, 7.4136, 7.4136, 7.4136, 7.4136] +24-11-19 19:28:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:28:34 | D | sum error = [ 57.7064, 61.2842, 64.9777, 68.8678, 72.9808] +24-11-19 19:28:34 | D | best error = [ 7.4136, 7.4136, 7.4136, 7.4136, 7.4136] +24-11-19 19:28:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:28:34 | D | sum error = [ 77.2654, 81.7381, 86.4268, 91.3563, 96.5021] +24-11-19 19:28:34 | D | best error = [ 7.4136, 7.4136, 7.4136, 7.4136, 7.4136] +24-11-19 19:28:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:28:34 | D | sum error = [ 101.9035, 107.5089, 113.3875, 119.5114, 125.8782] +24-11-19 19:28:34 | D | best error = [ 7.4136, 7.4136, 7.4136, 7.4136, 7.4136] +24-11-19 19:28:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:28:34 | D | sum error = [ 132.5441, 139.4636, 146.6958, 154.2140, 162.0269] +24-11-19 19:28:34 | D | best error = [ 7.4136, 7.4136, 7.4136, 7.4136, 7.4136] +24-11-19 19:28:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:28:34 | D | sum error = [ 170.1405, 178.5917, 187.3747, 196.4743, 205.8986] +24-11-19 19:28:34 | D | best error = [ 7.4136, 7.4136, 7.4136, 7.4136, 7.4136] +24-11-19 19:28:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:28:34 | D | sum error = [ 215.6869, 225.8278, 236.3331, 247.1896, 258.4305] +24-11-19 19:28:34 | D | best error = [ 7.4136, 7.4136, 7.4136, 7.4136, 7.4136] +24-11-19 19:28:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:28:34 | D | sum error = [ 270.0377, 282.0444, 294.4418, 307.2738, 320.5059] +24-11-19 19:28:34 | D | best error = [ 7.4136, 7.4136, 7.4136, 7.4136, 7.4136] +24-11-19 19:28:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:28:34 | D | sum error = [ 334.1706, 348.2873, 362.8341, 377.8297, 393.2610] +24-11-19 19:28:34 | D | best error = [ 7.4136, 7.4136, 7.4136, 7.4136, 7.4136] +24-11-19 19:28:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:28:34 | D | sum error = [ 409.1235, 425.4270, 442.1742, 459.3849, 477.0683] +24-11-19 19:28:34 | D | best error = [ 7.4136, 7.4136, 7.4136, 7.4136, 7.4136] +24-11-19 19:28:34 | D | + error = [7.4136] +24-11-19 19:28:34 | D | - Calibrating model.layers.25.self_attn.o_proj.weight +24-11-19 19:28:34 | D | + w: sint8 +24-11-19 19:28:34 | D | + x: None +24-11-19 19:28:34 | D | + y: None +24-11-19 19:28:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:28:34 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:28:34 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:28:34 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:28:34 | D | - range ratio = [ 1.0000] +24-11-19 19:28:34 | D | sum error = [ 1.6134] +24-11-19 19:28:34 | D | best error = [ 1.6134] +24-11-19 19:28:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:28:35 | D | sum error = [ 1.5964, 1.5916, 1.5986, 1.6190, 1.6443] +24-11-19 19:28:35 | D | best error = [ 1.5113, 1.4667, 1.4403, 1.4230, 1.4133] +24-11-19 19:28:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:28:35 | D | sum error = [ 1.6768, 1.7241, 1.7902, 1.8667, 1.9577] +24-11-19 19:28:35 | D | best error = [ 1.4057, 1.4004, 1.3966, 1.3936, 1.3911] +24-11-19 19:28:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:28:35 | D | sum error = [ 2.0622, 2.1802, 2.3104, 2.4599, 2.6197] +24-11-19 19:28:35 | D | best error = [ 1.3898, 1.3888, 1.3881, 1.3875, 1.3871] +24-11-19 19:28:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:28:35 | D | sum error = [ 2.7984, 2.9911, 3.2042, 3.4234, 3.6671] +24-11-19 19:28:35 | D | best error = [ 1.3867, 1.3865, 1.3863, 1.3863, 1.3862] +24-11-19 19:28:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:28:35 | D | sum error = [ 3.9175, 4.1976, 4.4831, 4.7990, 5.1234] +24-11-19 19:28:35 | D | best error = [ 1.3860, 1.3859, 1.3859, 1.3858, 1.3857] +24-11-19 19:28:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:28:35 | D | sum error = [ 5.4772, 5.8453, 6.2315, 6.6518, 7.0936] +24-11-19 19:28:35 | D | best error = [ 1.3857, 1.3857, 1.3857, 1.3856, 1.3856] +24-11-19 19:28:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:28:35 | D | sum error = [ 7.5536, 8.0382, 8.5551, 9.0919, 9.6689] +24-11-19 19:28:35 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 19:28:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:28:35 | D | sum error = [ 10.2706, 10.9069, 11.5830, 12.2762, 13.0196] +24-11-19 19:28:35 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 19:28:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:28:35 | D | sum error = [ 13.7997, 14.6133, 15.4739, 16.3685, 17.3092] +24-11-19 19:28:35 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 19:28:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:28:35 | D | sum error = [ 18.2950, 19.3330, 20.4146, 21.5443, 22.7299] +24-11-19 19:28:35 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 19:28:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:28:35 | D | sum error = [ 23.9685, 25.2681, 26.6248, 28.0398, 29.5152] +24-11-19 19:28:35 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 19:28:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:28:35 | D | sum error = [ 31.0624, 32.6736, 34.3508, 36.1029, 37.9315] +24-11-19 19:28:35 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 19:28:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:28:35 | D | sum error = [ 39.8375, 41.8192, 43.8823, 46.0272, 48.2575] +24-11-19 19:28:35 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 19:28:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:28:35 | D | sum error = [ 50.5745, 52.9734, 55.4678, 58.0589, 60.7374] +24-11-19 19:28:35 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 19:28:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:28:35 | D | sum error = [ 63.5134, 66.3834, 69.3585, 72.4331, 75.6092] +24-11-19 19:28:35 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 19:28:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:28:35 | D | sum error = [ 78.8863, 82.2663, 85.7620, 89.3650, 93.0770] +24-11-19 19:28:35 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 19:28:35 | D | + error = [1.3856] +24-11-19 19:28:35 | D | - Calibrating model.layers.25.mlp.up_proj.weight +24-11-19 19:28:35 | D | + w: sint8 +24-11-19 19:28:35 | D | + x: None +24-11-19 19:28:35 | D | + y: None +24-11-19 19:28:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:28:35 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:28:35 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:28:35 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:28:35 | D | - range ratio = [ 1.0000] +24-11-19 19:28:35 | D | sum error = [ 10.5096] +24-11-19 19:28:35 | D | best error = [ 10.5096] +24-11-19 19:28:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:28:36 | D | sum error = [ 10.4076, 10.4055, 10.4462, 10.5562, 10.7389] +24-11-19 19:28:36 | D | best error = [ 9.7088, 9.4014, 9.2417, 9.1461, 9.0935] +24-11-19 19:28:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:28:36 | D | sum error = [ 11.0328, 11.4181, 11.8611, 12.3914, 13.0595] +24-11-19 19:28:36 | D | best error = [ 9.0678, 9.0564, 9.0524, 9.0505, 9.0500] +24-11-19 19:28:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:28:36 | D | sum error = [ 13.7901, 14.6639, 15.5812, 16.6120, 17.7904] +24-11-19 19:28:36 | D | best error = [ 9.0500, 9.0500, 9.0500, 9.0500, 9.0500] +24-11-19 19:28:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:28:36 | D | sum error = [ 19.0042, 20.3933, 21.8165, 23.4095, 25.0687] +24-11-19 19:28:36 | D | best error = [ 9.0500, 9.0500, 9.0500, 9.0500, 9.0500] +24-11-19 19:28:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:28:36 | D | sum error = [ 26.8446, 28.7656, 30.7789, 32.9081, 35.2142] +24-11-19 19:28:36 | D | best error = [ 9.0500, 9.0500, 9.0500, 9.0500, 9.0500] +24-11-19 19:28:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:28:36 | D | sum error = [ 37.6376, 40.2103, 42.9054, 45.7592, 48.7725] +24-11-19 19:28:36 | D | best error = [ 9.0500, 9.0500, 9.0500, 9.0500, 9.0500] +24-11-19 19:28:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:28:36 | D | sum error = [ 51.9369, 55.3025, 58.8297, 62.5602, 66.4800] +24-11-19 19:28:36 | D | best error = [ 9.0500, 9.0500, 9.0500, 9.0500, 9.0500] +24-11-19 19:28:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:28:36 | D | sum error = [ 70.6031, 74.9649, 79.5024, 84.2860, 89.3076] +24-11-19 19:28:36 | D | best error = [ 9.0500, 9.0500, 9.0500, 9.0500, 9.0500] +24-11-19 19:28:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:28:36 | D | sum error = [ 94.5645, 100.0769, 105.8857, 111.9777, 118.3136] +24-11-19 19:28:36 | D | best error = [ 9.0500, 9.0500, 9.0500, 9.0500, 9.0500] +24-11-19 19:28:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:28:36 | D | sum error = [ 124.9905, 131.9433, 139.2529, 146.8567, 154.8029] +24-11-19 19:28:36 | D | best error = [ 9.0500, 9.0500, 9.0500, 9.0500, 9.0500] +24-11-19 19:28:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:28:36 | D | sum error = [ 163.1185, 171.7682, 180.7958, 190.1993, 200.0231] +24-11-19 19:28:36 | D | best error = [ 9.0500, 9.0500, 9.0500, 9.0500, 9.0500] +24-11-19 19:28:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:28:36 | D | sum error = [ 210.2103, 220.8376, 231.8730, 243.3306, 255.2550] +24-11-19 19:28:36 | D | best error = [ 9.0500, 9.0500, 9.0500, 9.0500, 9.0500] +24-11-19 19:28:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:28:36 | D | sum error = [ 267.6244, 280.4559, 293.7851, 307.5604, 321.8501] +24-11-19 19:28:36 | D | best error = [ 9.0500, 9.0500, 9.0500, 9.0500, 9.0500] +24-11-19 19:28:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:28:36 | D | sum error = [ 336.6573, 351.9746, 367.8431, 384.2143, 401.1638] +24-11-19 19:28:36 | D | best error = [ 9.0500, 9.0500, 9.0500, 9.0500, 9.0500] +24-11-19 19:28:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:28:36 | D | sum error = [ 418.6286, 436.6586, 455.2789, 474.4848, 494.2933] +24-11-19 19:28:36 | D | best error = [ 9.0500, 9.0500, 9.0500, 9.0500, 9.0500] +24-11-19 19:28:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:28:36 | D | sum error = [ 514.6850, 535.6824, 557.2745, 579.4671, 602.2777] +24-11-19 19:28:36 | D | best error = [ 9.0500, 9.0500, 9.0500, 9.0500, 9.0500] +24-11-19 19:28:36 | D | + error = [9.0500] +24-11-19 19:28:36 | D | - Calibrating model.layers.25.mlp.gate_proj.weight +24-11-19 19:28:36 | D | + w: sint8 +24-11-19 19:28:36 | D | + x: None +24-11-19 19:28:36 | D | + y: None +24-11-19 19:28:36 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:28:36 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:28:36 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:28:36 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:28:36 | D | - range ratio = [ 1.0000] +24-11-19 19:28:36 | D | sum error = [ 11.2778] +24-11-19 19:28:36 | D | best error = [ 11.2778] +24-11-19 19:28:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:28:37 | D | sum error = [ 11.1931, 11.1402, 11.2190, 11.3305, 11.5484] +24-11-19 19:28:37 | D | best error = [ 10.4328, 10.0911, 9.9250, 9.8235, 9.7680] +24-11-19 19:28:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:28:37 | D | sum error = [ 11.8258, 12.2417, 12.7221, 13.3281, 14.0440] +24-11-19 19:28:37 | D | best error = [ 9.7391, 9.7280, 9.7229, 9.7218, 9.7214] +24-11-19 19:28:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:28:37 | D | sum error = [ 14.8762, 15.7785, 16.8497, 17.9847, 19.2627] +24-11-19 19:28:37 | D | best error = [ 9.7214, 9.7214, 9.7214, 9.7214, 9.7214] +24-11-19 19:28:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:28:37 | D | sum error = [ 20.5964, 22.1060, 23.6764, 25.3889, 27.2385] +24-11-19 19:28:37 | D | best error = [ 9.7214, 9.7214, 9.7214, 9.7214, 9.7214] +24-11-19 19:28:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:28:37 | D | sum error = [ 29.1925, 31.2890, 33.4772, 35.8701, 38.3596] +24-11-19 19:28:37 | D | best error = [ 9.7214, 9.7214, 9.7214, 9.7214, 9.7214] +24-11-19 19:28:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:28:37 | D | sum error = [ 40.9956, 43.8138, 46.8115, 49.9571, 53.2937] +24-11-19 19:28:37 | D | best error = [ 9.7214, 9.7214, 9.7214, 9.7214, 9.7214] +24-11-19 19:28:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:28:37 | D | sum error = [ 56.8362, 60.5515, 64.5201, 68.6790, 73.0717] +24-11-19 19:28:37 | D | best error = [ 9.7214, 9.7214, 9.7214, 9.7214, 9.7214] +24-11-19 19:28:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:28:37 | D | sum error = [ 77.7084, 82.6096, 87.7405, 93.1405, 98.8512] +24-11-19 19:28:37 | D | best error = [ 9.7214, 9.7214, 9.7214, 9.7214, 9.7214] +24-11-19 19:28:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:28:37 | D | sum error = [ 104.8560, 111.2126, 117.8519, 124.8180, 132.1638] +24-11-19 19:28:37 | D | best error = [ 9.7214, 9.7214, 9.7214, 9.7214, 9.7214] +24-11-19 19:28:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:28:37 | D | sum error = [ 139.9026, 147.9763, 156.4543, 165.3553, 174.6835] +24-11-19 19:28:37 | D | best error = [ 9.7214, 9.7214, 9.7214, 9.7214, 9.7214] +24-11-19 19:28:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:28:37 | D | sum error = [ 184.4619, 194.7169, 205.4259, 216.6708, 228.4049] +24-11-19 19:28:37 | D | best error = [ 9.7214, 9.7214, 9.7214, 9.7214, 9.7214] +24-11-19 19:28:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:28:37 | D | sum error = [ 240.7051, 253.5425, 266.9432, 280.9296, 295.5280] +24-11-19 19:28:37 | D | best error = [ 9.7214, 9.7214, 9.7214, 9.7214, 9.7214] +24-11-19 19:28:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:28:37 | D | sum error = [ 310.7539, 326.5920, 343.1587, 360.3761, 378.2743] +24-11-19 19:28:37 | D | best error = [ 9.7214, 9.7214, 9.7214, 9.7214, 9.7214] +24-11-19 19:28:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:28:37 | D | sum error = [ 396.8729, 416.1970, 436.2440, 457.0870, 478.6754] +24-11-19 19:28:37 | D | best error = [ 9.7214, 9.7214, 9.7214, 9.7214, 9.7214] +24-11-19 19:28:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:28:37 | D | sum error = [ 501.0643, 524.2658, 548.2463, 573.0243, 598.6549] +24-11-19 19:28:37 | D | best error = [ 9.7214, 9.7214, 9.7214, 9.7214, 9.7214] +24-11-19 19:28:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:28:37 | D | sum error = [ 625.0564, 652.3694, 680.5201, 709.5512, 739.4287] +24-11-19 19:28:37 | D | best error = [ 9.7214, 9.7214, 9.7214, 9.7214, 9.7214] +24-11-19 19:28:37 | D | + error = [9.7214] +24-11-19 19:28:37 | D | - Calibrating model.layers.25.mlp.down_proj.weight +24-11-19 19:28:37 | D | + w: sint8 +24-11-19 19:28:37 | D | + x: None +24-11-19 19:28:37 | D | + y: None +24-11-19 19:28:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:28:37 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:28:37 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:28:38 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:28:38 | D | - range ratio = [ 1.0000] +24-11-19 19:28:38 | D | sum error = [ 3.9736] +24-11-19 19:28:38 | D | best error = [ 3.9736] +24-11-19 19:28:39 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:28:39 | D | sum error = [ 3.9441, 3.9208, 3.8898, 3.8829, 3.8789] +24-11-19 19:28:39 | D | best error = [ 3.8248, 3.7472, 3.6928, 3.6561, 3.6245] +24-11-19 19:28:39 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:28:39 | D | sum error = [ 3.9028, 3.9301, 3.9877, 4.0519, 4.1291] +24-11-19 19:28:39 | D | best error = [ 3.6031, 3.5884, 3.5789, 3.5714, 3.5658] +24-11-19 19:28:39 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:28:39 | D | sum error = [ 4.2431, 4.3762, 4.5361, 4.7221, 4.9492] +24-11-19 19:28:39 | D | best error = [ 3.5624, 3.5600, 3.5583, 3.5576, 3.5573] +24-11-19 19:28:39 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:28:39 | D | sum error = [ 5.1933, 5.4765, 5.7922, 6.1460, 6.5314] +24-11-19 19:28:39 | D | best error = [ 3.5569, 3.5567, 3.5566, 3.5566, 3.5565] +24-11-19 19:28:39 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:28:39 | D | sum error = [ 6.9505, 7.4085, 7.9109, 8.4413, 9.0253] +24-11-19 19:28:39 | D | best error = [ 3.5565, 3.5565, 3.5565, 3.5565, 3.5565] +24-11-19 19:28:39 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:28:39 | D | sum error = [ 9.6519, 10.3222, 11.0430, 11.8155, 12.6326] +24-11-19 19:28:39 | D | best error = [ 3.5565, 3.5565, 3.5565, 3.5565, 3.5565] +24-11-19 19:28:39 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:28:39 | D | sum error = [ 13.5152, 14.4471, 15.4419, 16.4963, 17.6256] +24-11-19 19:28:39 | D | best error = [ 3.5565, 3.5565, 3.5565, 3.5565, 3.5565] +24-11-19 19:28:39 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:28:39 | D | sum error = [ 18.8172, 20.0827, 21.4208, 22.8298, 24.3253] +24-11-19 19:28:39 | D | best error = [ 3.5565, 3.5565, 3.5565, 3.5565, 3.5565] +24-11-19 19:28:39 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:28:39 | D | sum error = [ 25.9152, 27.5859, 29.3452, 31.2097, 33.1664] +24-11-19 19:28:39 | D | best error = [ 3.5565, 3.5565, 3.5565, 3.5565, 3.5565] +24-11-19 19:28:39 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:28:39 | D | sum error = [ 35.2363, 37.4192, 39.7137, 42.1239, 44.6610] +24-11-19 19:28:39 | D | best error = [ 3.5565, 3.5565, 3.5565, 3.5565, 3.5565] +24-11-19 19:28:39 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:28:39 | D | sum error = [ 47.3301, 50.1238, 53.0558, 56.1312, 59.3492] +24-11-19 19:28:39 | D | best error = [ 3.5565, 3.5565, 3.5565, 3.5565, 3.5565] +24-11-19 19:28:39 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:28:39 | D | sum error = [ 62.7251, 66.2586, 69.9523, 73.8133, 77.8551] +24-11-19 19:28:39 | D | best error = [ 3.5565, 3.5565, 3.5565, 3.5565, 3.5565] +24-11-19 19:28:39 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:28:39 | D | sum error = [ 82.0750, 86.4831, 91.0766, 95.8650, 100.8473] +24-11-19 19:28:39 | D | best error = [ 3.5565, 3.5565, 3.5565, 3.5565, 3.5565] +24-11-19 19:28:39 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:28:39 | D | sum error = [ 106.0407, 111.4459, 117.0723, 122.9190, 128.9718] +24-11-19 19:28:39 | D | best error = [ 3.5565, 3.5565, 3.5565, 3.5565, 3.5565] +24-11-19 19:28:39 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:28:39 | D | sum error = [ 135.2621, 141.7750, 148.5348, 155.5289, 162.7789] +24-11-19 19:28:39 | D | best error = [ 3.5565, 3.5565, 3.5565, 3.5565, 3.5565] +24-11-19 19:28:39 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:28:39 | D | sum error = [ 170.2836, 178.0330, 186.0476, 194.3253, 202.8710] +24-11-19 19:28:39 | D | best error = [ 3.5565, 3.5565, 3.5565, 3.5565, 3.5565] +24-11-19 19:28:39 | D | + error = [3.5565] +24-11-19 19:28:39 | D | - Quantizing model.layers.25.self_attn.q_proj.weight +24-11-19 19:28:40 | D | - Quantizing model.layers.25.self_attn.k_proj.weight +24-11-19 19:28:40 | D | - Quantizing model.layers.25.self_attn.v_proj.weight +24-11-19 19:28:41 | D | - Quantizing model.layers.25.self_attn.o_proj.weight +24-11-19 19:28:42 | D | - Quantizing model.layers.25.mlp.up_proj.weight +24-11-19 19:28:43 | D | - Quantizing model.layers.25.mlp.gate_proj.weight +24-11-19 19:28:44 | D | - Quantizing model.layers.25.mlp.down_proj.weight +24-11-19 19:28:53 | D | - Quantizing layer model.layers.26 +24-11-19 19:28:53 | D | - Calibrating model.layers.26.self_attn.q_proj.weight +24-11-19 19:28:53 | D | + w: sint8 +24-11-19 19:28:53 | D | + x: None +24-11-19 19:28:53 | D | + y: None +24-11-19 19:28:53 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:28:53 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:28:54 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:28:54 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:28:54 | D | - range ratio = [ 1.0000] +24-11-19 19:28:54 | D | sum error = [ 17.5949] +24-11-19 19:28:54 | D | best error = [ 17.5949] +24-11-19 19:29:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:29:07 | D | sum error = [ 17.5189, 17.6906, 17.9450, 17.4584, 18.2477] +24-11-19 19:29:07 | D | best error = [ 17.5189, 17.5189, 17.5189, 17.4584, 17.4584] +24-11-19 19:29:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:29:07 | D | sum error = [ 18.6415, 19.2604, 20.0252, 20.7307, 21.9079] +24-11-19 19:29:07 | D | best error = [ 17.4584, 17.4584, 17.4584, 17.4584, 17.4584] +24-11-19 19:29:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:29:07 | D | sum error = [ 23.5573, 24.6395, 26.3981, 28.5961, 30.3712] +24-11-19 19:29:07 | D | best error = [ 17.4584, 17.4584, 17.4584, 17.4584, 17.4584] +24-11-19 19:29:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:29:07 | D | sum error = [ 32.6505, 34.6891, 37.3976, 40.5434, 43.7039] +24-11-19 19:29:07 | D | best error = [ 17.4584, 17.4584, 17.4584, 17.4584, 17.4584] +24-11-19 19:29:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:29:07 | D | sum error = [ 47.0916, 50.8730, 54.9298, 58.6447, 63.0100] +24-11-19 19:29:07 | D | best error = [ 17.4584, 17.4584, 17.4584, 17.4584, 17.4584] +24-11-19 19:29:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:29:07 | D | sum error = [ 68.6380, 73.3775, 79.8063, 86.0556, 92.5109] +24-11-19 19:29:07 | D | best error = [ 17.4584, 17.4584, 17.4584, 17.4584, 17.4584] +24-11-19 19:29:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:29:07 | D | sum error = [ 100.1335, 107.2435, 115.5728, 123.8734, 133.4408] +24-11-19 19:29:07 | D | best error = [ 17.4584, 17.4584, 17.4584, 17.4584, 17.4584] +24-11-19 19:29:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:29:07 | D | sum error = [ 143.3872, 154.8589, 166.2346, 178.1916, 190.7585] +24-11-19 19:29:07 | D | best error = [ 17.4584, 17.4584, 17.4584, 17.4584, 17.4584] +24-11-19 19:29:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:29:07 | D | sum error = [ 205.1937, 220.1223, 236.4050, 253.5239, 271.5220] +24-11-19 19:29:07 | D | best error = [ 17.4584, 17.4584, 17.4584, 17.4584, 17.4584] +24-11-19 19:29:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:29:07 | D | sum error = [ 290.9397, 312.3919, 335.4296, 359.6839, 386.0495] +24-11-19 19:29:07 | D | best error = [ 17.4584, 17.4584, 17.4584, 17.4584, 17.4584] +24-11-19 19:29:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:29:07 | D | sum error = [ 414.2203, 445.2424, 477.3294, 512.7129, 550.4293] +24-11-19 19:29:07 | D | best error = [ 17.4584, 17.4584, 17.4584, 17.4584, 17.4584] +24-11-19 19:29:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:29:07 | D | sum error = [ 591.5235, 636.0893, 684.7992, 736.3814, 791.9343] +24-11-19 19:29:07 | D | best error = [ 17.4584, 17.4584, 17.4584, 17.4584, 17.4584] +24-11-19 19:29:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:29:07 | D | sum error = [ 853.0543, 918.4817, 988.6740, 1065.8690, 1148.0083] +24-11-19 19:29:07 | D | best error = [ 17.4584, 17.4584, 17.4584, 17.4584, 17.4584] +24-11-19 19:29:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:29:07 | D | sum error = [ 1238.4084, 1336.4175, 1442.3369, 1558.0140, 1683.3111] +24-11-19 19:29:07 | D | best error = [ 17.4584, 17.4584, 17.4584, 17.4584, 17.4584] +24-11-19 19:29:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:29:07 | D | sum error = [ 1820.3336, 1967.2754, 2127.0103, 2300.4858, 2488.8401] +24-11-19 19:29:07 | D | best error = [ 17.4584, 17.4584, 17.4584, 17.4584, 17.4584] +24-11-19 19:29:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:29:07 | D | sum error = [ 2691.3183, 2910.5683, 3143.8174, 3393.9039, 3657.8364] +24-11-19 19:29:07 | D | best error = [ 17.4584, 17.4584, 17.4584, 17.4584, 17.4584] +24-11-19 19:29:07 | D | + error = [17.4584] +24-11-19 19:29:07 | D | - Calibrating model.layers.26.self_attn.k_proj.weight +24-11-19 19:29:07 | D | + w: sint8 +24-11-19 19:29:07 | D | + x: None +24-11-19 19:29:07 | D | + y: None +24-11-19 19:29:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:29:07 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:29:07 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:29:07 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:29:08 | D | - range ratio = [ 1.0000] +24-11-19 19:29:08 | D | sum error = [ 20.2437] +24-11-19 19:29:08 | D | best error = [ 20.2437] +24-11-19 19:29:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:29:20 | D | sum error = [ 20.1445, 20.6856, 21.8284, 21.0462, 25.6399] +24-11-19 19:29:20 | D | best error = [ 20.1445, 20.1445, 20.1445, 20.1445, 20.1445] +24-11-19 19:29:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:29:20 | D | sum error = [ 22.1327, 22.8173, 26.5427, 26.0324, 28.1357] +24-11-19 19:29:20 | D | best error = [ 20.1445, 20.1445, 20.1445, 20.1445, 20.1445] +24-11-19 19:29:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:29:20 | D | sum error = [ 28.7950, 31.8461, 31.1837, 34.2149, 35.0657] +24-11-19 19:29:20 | D | best error = [ 20.1445, 20.1445, 20.1445, 20.1445, 20.1445] +24-11-19 19:29:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:29:20 | D | sum error = [ 37.1445, 43.3718, 45.0636, 46.8897, 49.5583] +24-11-19 19:29:20 | D | best error = [ 20.1445, 20.1445, 20.1445, 20.1445, 20.1445] +24-11-19 19:29:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:29:20 | D | sum error = [ 53.6857, 58.5330, 62.5240, 68.0213, 75.0638] +24-11-19 19:29:20 | D | best error = [ 20.1445, 20.1445, 20.1445, 20.1445, 20.1445] +24-11-19 19:29:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:29:20 | D | sum error = [ 81.9149, 87.9802, 95.9998, 103.8779, 117.1131] +24-11-19 19:29:20 | D | best error = [ 20.1445, 20.1445, 20.1445, 20.1445, 20.1445] +24-11-19 19:29:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:29:20 | D | sum error = [ 124.2773, 134.0870, 145.1392, 157.3448, 170.4831] +24-11-19 19:29:20 | D | best error = [ 20.1445, 20.1445, 20.1445, 20.1445, 20.1445] +24-11-19 19:29:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:29:20 | D | sum error = [ 181.2292, 199.5028, 210.5240, 222.4993, 237.1375] +24-11-19 19:29:20 | D | best error = [ 20.1445, 20.1445, 20.1445, 20.1445, 20.1445] +24-11-19 19:29:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:29:20 | D | sum error = [ 248.5291, 265.2235, 282.0190, 299.5447, 320.5587] +24-11-19 19:29:20 | D | best error = [ 20.1445, 20.1445, 20.1445, 20.1445, 20.1445] +24-11-19 19:29:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:29:20 | D | sum error = [ 337.4466, 360.2089, 379.8659, 402.6089, 426.9538] +24-11-19 19:29:20 | D | best error = [ 20.1445, 20.1445, 20.1445, 20.1445, 20.1445] +24-11-19 19:29:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:29:20 | D | sum error = [ 455.9177, 485.5909, 517.2492, 553.7925, 590.9060] +24-11-19 19:29:20 | D | best error = [ 20.1445, 20.1445, 20.1445, 20.1445, 20.1445] +24-11-19 19:29:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:29:20 | D | sum error = [ 627.9932, 673.4050, 721.2542, 772.6679, 829.9657] +24-11-19 19:29:20 | D | best error = [ 20.1445, 20.1445, 20.1445, 20.1445, 20.1445] +24-11-19 19:29:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:29:20 | D | sum error = [ 890.9935, 959.2363, 1029.6282, 1105.5509, 1189.8882] +24-11-19 19:29:20 | D | best error = [ 20.1445, 20.1445, 20.1445, 20.1445, 20.1445] +24-11-19 19:29:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:29:20 | D | sum error = [ 1282.7599, 1384.7122, 1499.4176, 1616.0009, 1741.3145] +24-11-19 19:29:20 | D | best error = [ 20.1445, 20.1445, 20.1445, 20.1445, 20.1445] +24-11-19 19:29:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:29:20 | D | sum error = [ 1880.8797, 2023.6901, 2191.9503, 2363.8682, 2551.6471] +24-11-19 19:29:20 | D | best error = [ 20.1445, 20.1445, 20.1445, 20.1445, 20.1445] +24-11-19 19:29:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:29:20 | D | sum error = [ 2756.5803, 2973.2672, 3209.6614, 3467.0500, 3723.3791] +24-11-19 19:29:20 | D | best error = [ 20.1445, 20.1445, 20.1445, 20.1445, 20.1445] +24-11-19 19:29:20 | D | + error = [20.1445] +24-11-19 19:29:20 | D | - Calibrating model.layers.26.self_attn.v_proj.weight +24-11-19 19:29:20 | D | + w: sint8 +24-11-19 19:29:20 | D | + x: None +24-11-19 19:29:20 | D | + y: None +24-11-19 19:29:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:29:20 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:29:20 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:29:20 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:29:20 | D | - range ratio = [ 1.0000] +24-11-19 19:29:20 | D | sum error = [ 8.4098] +24-11-19 19:29:20 | D | best error = [ 8.4098] +24-11-19 19:29:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:29:21 | D | sum error = [ 8.3899, 8.3301, 8.3668, 8.4865, 8.6155] +24-11-19 19:29:21 | D | best error = [ 7.8146, 7.5708, 7.4437, 7.3743, 7.3339] +24-11-19 19:29:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:29:21 | D | sum error = [ 8.8434, 9.0995, 9.5167, 9.9572, 10.4809] +24-11-19 19:29:21 | D | best error = [ 7.3150, 7.3072, 7.3029, 7.3020, 7.3020] +24-11-19 19:29:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:29:21 | D | sum error = [ 11.0351, 11.7494, 12.5420, 13.3417, 14.2719] +24-11-19 19:29:21 | D | best error = [ 7.3018, 7.3018, 7.3018, 7.3018, 7.3018] +24-11-19 19:29:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:29:21 | D | sum error = [ 15.2834, 16.3262, 17.5315, 18.7887, 20.1170] +24-11-19 19:29:21 | D | best error = [ 7.3018, 7.3018, 7.3018, 7.3018, 7.3018] +24-11-19 19:29:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:29:21 | D | sum error = [ 21.5035, 23.0618, 24.6874, 26.4024, 28.1868] +24-11-19 19:29:21 | D | best error = [ 7.3018, 7.3018, 7.3018, 7.3018, 7.3018] +24-11-19 19:29:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:29:21 | D | sum error = [ 30.1015, 32.1638, 34.3246, 36.6444, 38.9716] +24-11-19 19:29:21 | D | best error = [ 7.3018, 7.3018, 7.3018, 7.3018, 7.3018] +24-11-19 19:29:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:29:21 | D | sum error = [ 41.5282, 44.1544, 46.9516, 49.9194, 53.0301] +24-11-19 19:29:21 | D | best error = [ 7.3018, 7.3018, 7.3018, 7.3018, 7.3018] +24-11-19 19:29:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:29:21 | D | sum error = [ 56.2952, 59.7354, 63.3448, 67.1231, 71.1218] +24-11-19 19:29:21 | D | best error = [ 7.3018, 7.3018, 7.3018, 7.3018, 7.3018] +24-11-19 19:29:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:29:21 | D | sum error = [ 75.2598, 79.6247, 84.2226, 88.9922, 93.9815] +24-11-19 19:29:21 | D | best error = [ 7.3018, 7.3018, 7.3018, 7.3018, 7.3018] +24-11-19 19:29:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:29:21 | D | sum error = [ 99.2157, 104.6940, 110.4120, 116.3509, 122.5724] +24-11-19 19:29:21 | D | best error = [ 7.3018, 7.3018, 7.3018, 7.3018, 7.3018] +24-11-19 19:29:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:29:21 | D | sum error = [ 129.0487, 135.7700, 142.7753, 150.0800, 157.6380] +24-11-19 19:29:21 | D | best error = [ 7.3018, 7.3018, 7.3018, 7.3018, 7.3018] +24-11-19 19:29:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:29:21 | D | sum error = [ 165.5226, 173.6774, 182.1603, 190.9395, 200.0594] +24-11-19 19:29:21 | D | best error = [ 7.3018, 7.3018, 7.3018, 7.3018, 7.3018] +24-11-19 19:29:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:29:21 | D | sum error = [ 209.5068, 219.2993, 229.4334, 239.9369, 250.8221] +24-11-19 19:29:21 | D | best error = [ 7.3018, 7.3018, 7.3018, 7.3018, 7.3018] +24-11-19 19:29:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:29:21 | D | sum error = [ 262.0626, 273.6954, 285.7023, 298.1064, 310.8641] +24-11-19 19:29:21 | D | best error = [ 7.3018, 7.3018, 7.3018, 7.3018, 7.3018] +24-11-19 19:29:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:29:21 | D | sum error = [ 324.0691, 337.6802, 351.6791, 366.1032, 380.9632] +24-11-19 19:29:21 | D | best error = [ 7.3018, 7.3018, 7.3018, 7.3018, 7.3018] +24-11-19 19:29:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:29:21 | D | sum error = [ 396.2526, 411.9799, 428.1378, 444.7268, 461.7659] +24-11-19 19:29:21 | D | best error = [ 7.3018, 7.3018, 7.3018, 7.3018, 7.3018] +24-11-19 19:29:21 | D | + error = [7.3018] +24-11-19 19:29:21 | D | - Calibrating model.layers.26.self_attn.o_proj.weight +24-11-19 19:29:21 | D | + w: sint8 +24-11-19 19:29:21 | D | + x: None +24-11-19 19:29:21 | D | + y: None +24-11-19 19:29:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:29:21 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:29:21 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:29:21 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:29:21 | D | - range ratio = [ 1.0000] +24-11-19 19:29:21 | D | sum error = [ 2.2266] +24-11-19 19:29:21 | D | best error = [ 2.2266] +24-11-19 19:29:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:29:22 | D | sum error = [ 2.2027, 2.1795, 2.1740, 2.1639, 2.1500] +24-11-19 19:29:22 | D | best error = [ 2.0789, 2.0087, 1.9657, 1.9324, 1.9071] +24-11-19 19:29:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:29:22 | D | sum error = [ 2.1589, 2.1693, 2.1775, 2.1969, 2.2287] +24-11-19 19:29:22 | D | best error = [ 1.8865, 1.8706, 1.8576, 1.8454, 1.8355] +24-11-19 19:29:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:29:22 | D | sum error = [ 2.2543, 2.2985, 2.3569, 2.4228, 2.4988] +24-11-19 19:29:22 | D | best error = [ 1.8266, 1.8190, 1.8125, 1.8068, 1.8019] +24-11-19 19:29:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:29:22 | D | sum error = [ 2.5910, 2.6852, 2.7966, 2.9372, 3.0590] +24-11-19 19:29:22 | D | best error = [ 1.7975, 1.7938, 1.7905, 1.7877, 1.7858] +24-11-19 19:29:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:29:22 | D | sum error = [ 3.2267, 3.3942, 3.5858, 3.7907, 4.0111] +24-11-19 19:29:22 | D | best error = [ 1.7840, 1.7828, 1.7819, 1.7811, 1.7807] +24-11-19 19:29:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:29:22 | D | sum error = [ 4.2500, 4.5120, 4.7790, 5.0738, 5.3947] +24-11-19 19:29:22 | D | best error = [ 1.7802, 1.7794, 1.7792, 1.7790, 1.7788] +24-11-19 19:29:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:29:22 | D | sum error = [ 5.7423, 6.1027, 6.4915, 6.9057, 7.3354] +24-11-19 19:29:22 | D | best error = [ 1.7786, 1.7786, 1.7783, 1.7783, 1.7782] +24-11-19 19:29:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:29:22 | D | sum error = [ 7.8109, 8.3064, 8.8365, 9.3991, 10.0080] +24-11-19 19:29:22 | D | best error = [ 1.7781, 1.7781, 1.7780, 1.7779, 1.7779] +24-11-19 19:29:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:29:22 | D | sum error = [ 10.6437, 11.3290, 12.0490, 12.8066, 13.6203] +24-11-19 19:29:22 | D | best error = [ 1.7779, 1.7779, 1.7779, 1.7779, 1.7779] +24-11-19 19:29:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:29:22 | D | sum error = [ 14.4858, 15.3966, 16.3680, 17.3918, 18.4759] +24-11-19 19:29:22 | D | best error = [ 1.7779, 1.7779, 1.7779, 1.7779, 1.7779] +24-11-19 19:29:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:29:22 | D | sum error = [ 19.6174, 20.8290, 22.1195, 23.4720, 24.9026] +24-11-19 19:29:22 | D | best error = [ 1.7779, 1.7779, 1.7779, 1.7779, 1.7779] +24-11-19 19:29:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:29:22 | D | sum error = [ 26.4120, 28.0034, 29.6805, 31.4585, 33.3306] +24-11-19 19:29:22 | D | best error = [ 1.7779, 1.7779, 1.7779, 1.7779, 1.7779] +24-11-19 19:29:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:29:22 | D | sum error = [ 35.2950, 37.3651, 39.5485, 41.8451, 44.2558] +24-11-19 19:29:22 | D | best error = [ 1.7779, 1.7779, 1.7779, 1.7779, 1.7779] +24-11-19 19:29:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:29:22 | D | sum error = [ 46.7774, 49.4297, 52.2068, 55.1223, 58.1762] +24-11-19 19:29:22 | D | best error = [ 1.7779, 1.7779, 1.7779, 1.7779, 1.7779] +24-11-19 19:29:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:29:22 | D | sum error = [ 61.3743, 64.7158, 68.2209, 71.8774, 75.6975] +24-11-19 19:29:22 | D | best error = [ 1.7779, 1.7779, 1.7779, 1.7779, 1.7779] +24-11-19 19:29:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:29:22 | D | sum error = [ 79.6855, 83.8448, 88.1784, 92.6861, 97.3808] +24-11-19 19:29:22 | D | best error = [ 1.7779, 1.7779, 1.7779, 1.7779, 1.7779] +24-11-19 19:29:22 | D | + error = [1.7779] +24-11-19 19:29:22 | D | - Calibrating model.layers.26.mlp.up_proj.weight +24-11-19 19:29:22 | D | + w: sint8 +24-11-19 19:29:22 | D | + x: None +24-11-19 19:29:22 | D | + y: None +24-11-19 19:29:22 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:29:22 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:29:22 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:29:22 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:29:22 | D | - range ratio = [ 1.0000] +24-11-19 19:29:22 | D | sum error = [ 10.8622] +24-11-19 19:29:22 | D | best error = [ 10.8622] +24-11-19 19:29:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:29:23 | D | sum error = [ 10.7833, 10.7699, 10.8016, 10.9305, 11.1500] +24-11-19 19:29:23 | D | best error = [ 10.0299, 9.7115, 9.5462, 9.4505, 9.3989] +24-11-19 19:29:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:29:23 | D | sum error = [ 11.4085, 11.8118, 12.2582, 12.8784, 13.5507] +24-11-19 19:29:23 | D | best error = [ 9.3701, 9.3577, 9.3538, 9.3523, 9.3519] +24-11-19 19:29:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:29:23 | D | sum error = [ 14.2930, 15.2034, 16.1923, 17.2664, 18.4675] +24-11-19 19:29:23 | D | best error = [ 9.3517, 9.3517, 9.3517, 9.3517, 9.3517] +24-11-19 19:29:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:29:23 | D | sum error = [ 19.7565, 21.1553, 22.6964, 24.3038, 26.0354] +24-11-19 19:29:23 | D | best error = [ 9.3517, 9.3517, 9.3517, 9.3517, 9.3517] +24-11-19 19:29:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:29:23 | D | sum error = [ 27.8850, 29.8422, 31.9635, 34.1579, 36.6065] +24-11-19 19:29:23 | D | best error = [ 9.3517, 9.3517, 9.3517, 9.3517, 9.3517] +24-11-19 19:29:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:29:23 | D | sum error = [ 39.0769, 41.7267, 44.5194, 47.5149, 50.6347] +24-11-19 19:29:23 | D | best error = [ 9.3517, 9.3517, 9.3517, 9.3517, 9.3517] +24-11-19 19:29:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:29:23 | D | sum error = [ 53.9350, 57.4321, 61.1439, 65.0089, 69.0969] +24-11-19 19:29:23 | D | best error = [ 9.3517, 9.3517, 9.3517, 9.3517, 9.3517] +24-11-19 19:29:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:29:23 | D | sum error = [ 73.4056, 77.9124, 82.6548, 87.6413, 92.8798] +24-11-19 19:29:23 | D | best error = [ 9.3517, 9.3517, 9.3517, 9.3517, 9.3517] +24-11-19 19:29:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:29:23 | D | sum error = [ 98.3912, 104.1514, 110.2066, 116.5280, 123.1581] +24-11-19 19:29:23 | D | best error = [ 9.3517, 9.3517, 9.3517, 9.3517, 9.3517] +24-11-19 19:29:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:29:23 | D | sum error = [ 130.1189, 137.3725, 144.9796, 152.9250, 161.2283] +24-11-19 19:29:23 | D | best error = [ 9.3517, 9.3517, 9.3517, 9.3517, 9.3517] +24-11-19 19:29:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:29:23 | D | sum error = [ 169.9211, 178.9562, 188.4212, 198.2648, 208.5312] +24-11-19 19:29:23 | D | best error = [ 9.3517, 9.3517, 9.3517, 9.3517, 9.3517] +24-11-19 19:29:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:29:23 | D | sum error = [ 219.2260, 230.3624, 241.9218, 253.9636, 266.4964] +24-11-19 19:29:23 | D | best error = [ 9.3517, 9.3517, 9.3517, 9.3517, 9.3517] +24-11-19 19:29:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:29:23 | D | sum error = [ 279.4901, 292.9904, 306.9960, 321.5194, 336.5784] +24-11-19 19:29:23 | D | best error = [ 9.3517, 9.3517, 9.3517, 9.3517, 9.3517] +24-11-19 19:29:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:29:23 | D | sum error = [ 352.1897, 368.3355, 385.0679, 402.3536, 420.2314] +24-11-19 19:29:23 | D | best error = [ 9.3517, 9.3517, 9.3517, 9.3517, 9.3517] +24-11-19 19:29:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:29:23 | D | sum error = [ 438.6798, 457.7509, 477.4278, 497.7216, 518.6516] +24-11-19 19:29:23 | D | best error = [ 9.3517, 9.3517, 9.3517, 9.3517, 9.3517] +24-11-19 19:29:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:29:23 | D | sum error = [ 540.1877, 562.3886, 585.2057, 608.6713, 632.7985] +24-11-19 19:29:23 | D | best error = [ 9.3517, 9.3517, 9.3517, 9.3517, 9.3517] +24-11-19 19:29:23 | D | + error = [9.3517] +24-11-19 19:29:23 | D | - Calibrating model.layers.26.mlp.gate_proj.weight +24-11-19 19:29:23 | D | + w: sint8 +24-11-19 19:29:23 | D | + x: None +24-11-19 19:29:23 | D | + y: None +24-11-19 19:29:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:29:23 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:29:23 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:29:23 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:29:23 | D | - range ratio = [ 1.0000] +24-11-19 19:29:23 | D | sum error = [ 11.6632] +24-11-19 19:29:23 | D | best error = [ 11.6632] +24-11-19 19:29:24 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:29:24 | D | sum error = [ 11.6070, 11.5728, 11.6088, 11.7387, 11.9194] +24-11-19 19:29:24 | D | best error = [ 10.7952, 10.4506, 10.2601, 10.1528, 10.0944] +24-11-19 19:29:24 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:29:24 | D | sum error = [ 12.2268, 12.6303, 13.1438, 13.8046, 14.5257] +24-11-19 19:29:24 | D | best error = [ 10.0662, 10.0530, 10.0470, 10.0456, 10.0452] +24-11-19 19:29:24 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:29:24 | D | sum error = [ 15.3560, 16.2922, 17.3648, 18.5522, 19.8586] +24-11-19 19:29:24 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 19:29:24 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:29:24 | D | sum error = [ 21.2618, 22.7818, 24.4263, 26.1926, 28.0693] +24-11-19 19:29:24 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 19:29:24 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:29:24 | D | sum error = [ 30.0906, 32.2486, 34.5619, 37.0174, 39.6217] +24-11-19 19:29:24 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 19:29:24 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:29:24 | D | sum error = [ 42.3643, 45.2707, 48.3770, 51.6288, 55.0969] +24-11-19 19:29:24 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 19:29:24 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:29:24 | D | sum error = [ 58.7801, 62.6472, 66.7399, 71.0778, 75.6870] +24-11-19 19:29:24 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 19:29:24 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:29:24 | D | sum error = [ 80.5192, 85.6083, 90.9948, 96.6550, 102.6078] +24-11-19 19:29:24 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 19:29:24 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:29:24 | D | sum error = [ 108.9184, 115.5102, 122.4500, 129.7469, 137.4361] +24-11-19 19:29:24 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 19:29:24 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:29:24 | D | sum error = [ 145.4665, 153.9623, 162.8661, 172.2119, 182.0134] +24-11-19 19:29:24 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 19:29:24 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:29:24 | D | sum error = [ 192.2944, 203.0950, 214.4189, 226.2775, 238.6701] +24-11-19 19:29:24 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 19:29:24 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:29:24 | D | sum error = [ 251.6538, 265.2394, 279.4064, 294.2448, 309.7524] +24-11-19 19:29:24 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 19:29:24 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:29:24 | D | sum error = [ 325.9327, 342.7899, 360.3740, 378.7153, 397.8194] +24-11-19 19:29:24 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 19:29:24 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:29:24 | D | sum error = [ 417.7058, 438.3621, 459.8067, 482.0798, 505.1650] +24-11-19 19:29:24 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 19:29:24 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:29:24 | D | sum error = [ 529.1234, 553.9273, 579.6192, 606.1972, 633.6792] +24-11-19 19:29:24 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 19:29:24 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:29:24 | D | sum error = [ 662.0350, 691.3068, 721.4783, 752.5888, 784.5945] +24-11-19 19:29:24 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 19:29:24 | D | + error = [10.0450] +24-11-19 19:29:24 | D | - Calibrating model.layers.26.mlp.down_proj.weight +24-11-19 19:29:24 | D | + w: sint8 +24-11-19 19:29:24 | D | + x: None +24-11-19 19:29:24 | D | + y: None +24-11-19 19:29:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:29:24 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:29:24 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:29:24 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:29:24 | D | - range ratio = [ 1.0000] +24-11-19 19:29:24 | D | sum error = [ 4.1822] +24-11-19 19:29:24 | D | best error = [ 4.1822] +24-11-19 19:29:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:29:25 | D | sum error = [ 4.1420, 4.1120, 4.0803, 4.0876, 4.0872] +24-11-19 19:29:25 | D | best error = [ 4.0139, 3.9315, 3.8716, 3.8344, 3.8062] +24-11-19 19:29:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:29:25 | D | sum error = [ 4.0923, 4.1325, 4.1914, 4.2557, 4.3428] +24-11-19 19:29:25 | D | best error = [ 3.7833, 3.7678, 3.7587, 3.7509, 3.7443] +24-11-19 19:29:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:29:25 | D | sum error = [ 4.4596, 4.5981, 4.7634, 4.9671, 5.1986] +24-11-19 19:29:25 | D | best error = [ 3.7410, 3.7385, 3.7371, 3.7363, 3.7355] +24-11-19 19:29:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:29:25 | D | sum error = [ 5.4590, 5.7537, 6.0769, 6.4396, 6.8432] +24-11-19 19:29:25 | D | best error = [ 3.7353, 3.7351, 3.7348, 3.7348, 3.7348] +24-11-19 19:29:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:29:25 | D | sum error = [ 7.2902, 7.7646, 8.2804, 8.8483, 9.4558] +24-11-19 19:29:25 | D | best error = [ 3.7348, 3.7348, 3.7348, 3.7348, 3.7348] +24-11-19 19:29:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:29:25 | D | sum error = [ 10.1133, 10.8093, 11.5653, 12.3775, 13.2398] +24-11-19 19:29:25 | D | best error = [ 3.7348, 3.7348, 3.7348, 3.7348, 3.7348] +24-11-19 19:29:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:29:25 | D | sum error = [ 14.1585, 15.1370, 16.1691, 17.2822, 18.4597] +24-11-19 19:29:25 | D | best error = [ 3.7348, 3.7348, 3.7348, 3.7348, 3.7348] +24-11-19 19:29:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:29:25 | D | sum error = [ 19.7070, 21.0101, 22.4210, 23.8980, 25.4655] +24-11-19 19:29:25 | D | best error = [ 3.7348, 3.7348, 3.7348, 3.7348, 3.7348] +24-11-19 19:29:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:29:25 | D | sum error = [ 27.1222, 28.8661, 30.7141, 32.6664, 34.7239] +24-11-19 19:29:25 | D | best error = [ 3.7348, 3.7348, 3.7348, 3.7348, 3.7348] +24-11-19 19:29:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:29:25 | D | sum error = [ 36.8901, 39.1663, 41.5661, 44.0847, 46.7373] +24-11-19 19:29:25 | D | best error = [ 3.7348, 3.7348, 3.7348, 3.7348, 3.7348] +24-11-19 19:29:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:29:25 | D | sum error = [ 49.5192, 52.4402, 55.5105, 58.7214, 62.0876] +24-11-19 19:29:25 | D | best error = [ 3.7348, 3.7348, 3.7348, 3.7348, 3.7348] +24-11-19 19:29:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:29:25 | D | sum error = [ 65.6154, 69.3040, 73.1711, 77.2087, 81.4378] +24-11-19 19:29:25 | D | best error = [ 3.7348, 3.7348, 3.7348, 3.7348, 3.7348] +24-11-19 19:29:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:29:25 | D | sum error = [ 85.8464, 90.4409, 95.2394, 100.2371, 105.4459] +24-11-19 19:29:25 | D | best error = [ 3.7348, 3.7348, 3.7348, 3.7348, 3.7348] +24-11-19 19:29:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:29:25 | D | sum error = [ 110.8670, 116.5103, 122.3778, 128.4885, 134.8058] +24-11-19 19:29:25 | D | best error = [ 3.7348, 3.7348, 3.7348, 3.7348, 3.7348] +24-11-19 19:29:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:29:25 | D | sum error = [ 141.3800, 148.1943, 155.2652, 162.5878, 170.1632] +24-11-19 19:29:25 | D | best error = [ 3.7348, 3.7348, 3.7348, 3.7348, 3.7348] +24-11-19 19:29:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:29:25 | D | sum error = [ 178.0051, 186.1071, 194.4793, 203.1296, 212.0599] +24-11-19 19:29:25 | D | best error = [ 3.7348, 3.7348, 3.7348, 3.7348, 3.7348] +24-11-19 19:29:25 | D | + error = [3.7348] +24-11-19 19:29:25 | D | - Quantizing model.layers.26.self_attn.q_proj.weight +24-11-19 19:29:27 | D | - Quantizing model.layers.26.self_attn.k_proj.weight +24-11-19 19:29:27 | D | - Quantizing model.layers.26.self_attn.v_proj.weight +24-11-19 19:29:28 | D | - Quantizing model.layers.26.self_attn.o_proj.weight +24-11-19 19:29:29 | D | - Quantizing model.layers.26.mlp.up_proj.weight +24-11-19 19:29:30 | D | - Quantizing model.layers.26.mlp.gate_proj.weight +24-11-19 19:29:31 | D | - Quantizing model.layers.26.mlp.down_proj.weight +24-11-19 19:29:40 | D | - Quantizing layer model.layers.27 +24-11-19 19:29:40 | D | - Calibrating model.layers.27.self_attn.q_proj.weight +24-11-19 19:29:40 | D | + w: sint8 +24-11-19 19:29:40 | D | + x: None +24-11-19 19:29:40 | D | + y: None +24-11-19 19:29:40 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:29:40 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:29:40 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:29:41 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:29:41 | D | - range ratio = [ 1.0000] +24-11-19 19:29:41 | D | sum error = [ 16.8308] +24-11-19 19:29:41 | D | best error = [ 16.8308] +24-11-19 19:29:56 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:29:56 | D | sum error = [ 17.0831, 16.5294, 16.9723, 16.9757, 17.2767] +24-11-19 19:29:56 | D | best error = [ 16.8308, 16.5294, 16.5294, 16.5294, 16.5294] +24-11-19 19:29:56 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:29:56 | D | sum error = [ 17.8610, 18.2925, 19.4788, 20.4086, 21.5678] +24-11-19 19:29:56 | D | best error = [ 16.5294, 16.5294, 16.5294, 16.5294, 16.5294] +24-11-19 19:29:56 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:29:56 | D | sum error = [ 22.5774, 25.3530, 26.1735, 28.5685, 30.3893] +24-11-19 19:29:56 | D | best error = [ 16.5294, 16.5294, 16.5294, 16.5294, 16.5294] +24-11-19 19:29:56 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:29:56 | D | sum error = [ 32.1785, 34.7177, 37.4546, 40.3420, 43.7001] +24-11-19 19:29:56 | D | best error = [ 16.5294, 16.5294, 16.5294, 16.5294, 16.5294] +24-11-19 19:29:56 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:29:56 | D | sum error = [ 47.3915, 51.3281, 55.8529, 59.4312, 63.4952] +24-11-19 19:29:56 | D | best error = [ 16.5294, 16.5294, 16.5294, 16.5294, 16.5294] +24-11-19 19:29:56 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:29:56 | D | sum error = [ 68.6721, 73.9019, 79.9184, 85.9097, 91.9983] +24-11-19 19:29:56 | D | best error = [ 16.5294, 16.5294, 16.5294, 16.5294, 16.5294] +24-11-19 19:29:56 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:29:56 | D | sum error = [ 98.3096, 105.8113, 112.9407, 121.3358, 130.2243] +24-11-19 19:29:56 | D | best error = [ 16.5294, 16.5294, 16.5294, 16.5294, 16.5294] +24-11-19 19:29:56 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:29:56 | D | sum error = [ 140.0578, 149.6248, 160.6319, 172.5790, 185.5768] +24-11-19 19:29:56 | D | best error = [ 16.5294, 16.5294, 16.5294, 16.5294, 16.5294] +24-11-19 19:29:56 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:29:56 | D | sum error = [ 199.7055, 213.8015, 230.2203, 247.5930, 266.5677] +24-11-19 19:29:56 | D | best error = [ 16.5294, 16.5294, 16.5294, 16.5294, 16.5294] +24-11-19 19:29:56 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:29:56 | D | sum error = [ 286.1848, 307.3759, 330.9283, 355.1088, 381.1623] +24-11-19 19:29:56 | D | best error = [ 16.5294, 16.5294, 16.5294, 16.5294, 16.5294] +24-11-19 19:29:56 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:29:56 | D | sum error = [ 409.3327, 439.8337, 472.8382, 508.7406, 547.4999] +24-11-19 19:29:56 | D | best error = [ 16.5294, 16.5294, 16.5294, 16.5294, 16.5294] +24-11-19 19:29:56 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:29:56 | D | sum error = [ 589.7798, 635.0149, 684.6195, 737.2098, 795.2099] +24-11-19 19:29:56 | D | best error = [ 16.5294, 16.5294, 16.5294, 16.5294, 16.5294] +24-11-19 19:29:56 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:29:56 | D | sum error = [ 858.3948, 926.7994, 1001.1352, 1083.4653, 1172.8401] +24-11-19 19:29:56 | D | best error = [ 16.5294, 16.5294, 16.5294, 16.5294, 16.5294] +24-11-19 19:29:56 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:29:56 | D | sum error = [ 1271.2341, 1378.8788, 1499.1574, 1629.1538, 1773.2319] +24-11-19 19:29:56 | D | best error = [ 16.5294, 16.5294, 16.5294, 16.5294, 16.5294] +24-11-19 19:29:56 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:29:56 | D | sum error = [ 1930.9118, 2105.2500, 2297.4620, 2508.7466, 2741.2858] +24-11-19 19:29:56 | D | best error = [ 16.5294, 16.5294, 16.5294, 16.5294, 16.5294] +24-11-19 19:29:56 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:29:56 | D | sum error = [ 2999.4249, 3283.5865, 3598.1348, 3940.5987, 4313.0133] +24-11-19 19:29:56 | D | best error = [ 16.5294, 16.5294, 16.5294, 16.5294, 16.5294] +24-11-19 19:29:56 | D | + error = [16.5294] +24-11-19 19:29:57 | D | - Calibrating model.layers.27.self_attn.k_proj.weight +24-11-19 19:29:57 | D | + w: sint8 +24-11-19 19:29:57 | D | + x: None +24-11-19 19:29:57 | D | + y: None +24-11-19 19:29:57 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:29:57 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:29:57 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:29:57 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:29:58 | D | - range ratio = [ 1.0000] +24-11-19 19:29:58 | D | sum error = [ 20.2655] +24-11-19 19:29:58 | D | best error = [ 20.2655] +24-11-19 19:30:11 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:30:11 | D | sum error = [ 19.5204, 19.2978, 19.4022, 19.6932, 19.5159] +24-11-19 19:30:11 | D | best error = [ 19.5204, 19.2978, 19.2978, 19.2978, 19.2978] +24-11-19 19:30:11 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:30:11 | D | sum error = [ 20.4805, 21.2972, 22.3094, 23.4612, 24.8395] +24-11-19 19:30:11 | D | best error = [ 19.2978, 19.2978, 19.2978, 19.2978, 19.2978] +24-11-19 19:30:11 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:30:11 | D | sum error = [ 25.8810, 27.0910, 30.0673, 32.8662, 34.3041] +24-11-19 19:30:11 | D | best error = [ 19.2978, 19.2978, 19.2978, 19.2978, 19.2978] +24-11-19 19:30:11 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:30:11 | D | sum error = [ 36.3502, 38.2160, 41.9719, 44.7539, 49.1378] +24-11-19 19:30:11 | D | best error = [ 19.2978, 19.2978, 19.2978, 19.2978, 19.2978] +24-11-19 19:30:11 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:30:11 | D | sum error = [ 52.5297, 58.7203, 63.4347, 68.6439, 73.9642] +24-11-19 19:30:11 | D | best error = [ 19.2978, 19.2978, 19.2978, 19.2978, 19.2978] +24-11-19 19:30:11 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:30:11 | D | sum error = [ 80.6405, 86.8964, 96.4223, 102.5400, 113.3300] +24-11-19 19:30:11 | D | best error = [ 19.2978, 19.2978, 19.2978, 19.2978, 19.2978] +24-11-19 19:30:11 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:30:11 | D | sum error = [ 120.5586, 130.3991, 140.0407, 152.6434, 165.0399] +24-11-19 19:30:11 | D | best error = [ 19.2978, 19.2978, 19.2978, 19.2978, 19.2978] +24-11-19 19:30:11 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:30:11 | D | sum error = [ 180.7559, 193.5679, 205.4069, 221.0775, 238.0079] +24-11-19 19:30:11 | D | best error = [ 19.2978, 19.2978, 19.2978, 19.2978, 19.2978] +24-11-19 19:30:11 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:30:11 | D | sum error = [ 253.5900, 274.6244, 293.8623, 312.4671, 333.2077] +24-11-19 19:30:11 | D | best error = [ 19.2978, 19.2978, 19.2978, 19.2978, 19.2978] +24-11-19 19:30:11 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:30:11 | D | sum error = [ 356.5512, 379.9843, 404.6619, 431.7100, 456.7179] +24-11-19 19:30:11 | D | best error = [ 19.2978, 19.2978, 19.2978, 19.2978, 19.2978] +24-11-19 19:30:11 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:30:11 | D | sum error = [ 486.6557, 516.6577, 550.1825, 583.9509, 622.9823] +24-11-19 19:30:11 | D | best error = [ 19.2978, 19.2978, 19.2978, 19.2978, 19.2978] +24-11-19 19:30:11 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:30:11 | D | sum error = [ 672.3876, 714.0108, 762.4606, 818.5092, 878.1113] +24-11-19 19:30:11 | D | best error = [ 19.2978, 19.2978, 19.2978, 19.2978, 19.2978] +24-11-19 19:30:11 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:30:11 | D | sum error = [ 943.3622, 1010.1756, 1090.2074, 1170.4375, 1258.1448] +24-11-19 19:30:11 | D | best error = [ 19.2978, 19.2978, 19.2978, 19.2978, 19.2978] +24-11-19 19:30:11 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:30:11 | D | sum error = [ 1359.1050, 1464.1766, 1576.9290, 1700.9555, 1840.5231] +24-11-19 19:30:11 | D | best error = [ 19.2978, 19.2978, 19.2978, 19.2978, 19.2978] +24-11-19 19:30:11 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:30:11 | D | sum error = [ 1989.4244, 2166.5545, 2347.7685, 2552.6828, 2789.8998] +24-11-19 19:30:11 | D | best error = [ 19.2978, 19.2978, 19.2978, 19.2978, 19.2978] +24-11-19 19:30:11 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:30:11 | D | sum error = [ 3056.3475, 3337.5866, 3640.6565, 3975.8959, 4351.1123] +24-11-19 19:30:11 | D | best error = [ 19.2978, 19.2978, 19.2978, 19.2978, 19.2978] +24-11-19 19:30:11 | D | + error = [19.2978] +24-11-19 19:30:11 | D | - Calibrating model.layers.27.self_attn.v_proj.weight +24-11-19 19:30:11 | D | + w: sint8 +24-11-19 19:30:11 | D | + x: None +24-11-19 19:30:11 | D | + y: None +24-11-19 19:30:11 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:30:11 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:30:11 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:30:11 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:30:11 | D | - range ratio = [ 1.0000] +24-11-19 19:30:11 | D | sum error = [ 8.7444] +24-11-19 19:30:11 | D | best error = [ 8.7444] +24-11-19 19:30:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:30:12 | D | sum error = [ 8.6583, 8.6656, 8.6785, 8.8054, 8.9230] +24-11-19 19:30:12 | D | best error = [ 8.0868, 7.8394, 7.6998, 7.6214, 7.5780] +24-11-19 19:30:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:30:12 | D | sum error = [ 9.1534, 9.5019, 9.8704, 10.3346, 10.8673] +24-11-19 19:30:12 | D | best error = [ 7.5573, 7.5478, 7.5445, 7.5436, 7.5432] +24-11-19 19:30:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:30:12 | D | sum error = [ 11.5044, 12.1961, 13.0168, 13.8875, 14.8566] +24-11-19 19:30:12 | D | best error = [ 7.5432, 7.5432, 7.5432, 7.5432, 7.5432] +24-11-19 19:30:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:30:12 | D | sum error = [ 15.8718, 17.0338, 18.2339, 19.5208, 20.9627] +24-11-19 19:30:12 | D | best error = [ 7.5432, 7.5432, 7.5432, 7.5432, 7.5432] +24-11-19 19:30:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:30:12 | D | sum error = [ 22.4892, 24.0738, 25.7139, 27.5122, 29.4368] +24-11-19 19:30:12 | D | best error = [ 7.5432, 7.5432, 7.5432, 7.5432, 7.5432] +24-11-19 19:30:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:30:12 | D | sum error = [ 31.4861, 33.5721, 35.8793, 38.2554, 40.7687] +24-11-19 19:30:12 | D | best error = [ 7.5432, 7.5432, 7.5432, 7.5432, 7.5432] +24-11-19 19:30:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:30:12 | D | sum error = [ 43.4491, 46.2161, 49.1460, 52.2403, 55.4840] +24-11-19 19:30:12 | D | best error = [ 7.5432, 7.5432, 7.5432, 7.5432, 7.5432] +24-11-19 19:30:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:30:12 | D | sum error = [ 58.9231, 62.5106, 66.3167, 70.3136, 74.4914] +24-11-19 19:30:12 | D | best error = [ 7.5432, 7.5432, 7.5432, 7.5432, 7.5432] +24-11-19 19:30:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:30:12 | D | sum error = [ 78.9193, 83.4974, 88.3044, 93.3388, 98.6263] +24-11-19 19:30:12 | D | best error = [ 7.5432, 7.5432, 7.5432, 7.5432, 7.5432] +24-11-19 19:30:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:30:12 | D | sum error = [ 104.1350, 109.8944, 115.9314, 122.2568, 128.8207] +24-11-19 19:30:12 | D | best error = [ 7.5432, 7.5432, 7.5432, 7.5432, 7.5432] +24-11-19 19:30:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:30:12 | D | sum error = [ 135.6478, 142.7544, 150.1508, 157.8391, 165.8253] +24-11-19 19:30:12 | D | best error = [ 7.5432, 7.5432, 7.5432, 7.5432, 7.5432] +24-11-19 19:30:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:30:12 | D | sum error = [ 174.1016, 182.7242, 191.6912, 200.9851, 210.6414] +24-11-19 19:30:12 | D | best error = [ 7.5432, 7.5432, 7.5432, 7.5432, 7.5432] +24-11-19 19:30:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:30:12 | D | sum error = [ 220.6460, 231.0147, 241.7357, 252.8515, 264.3551] +24-11-19 19:30:12 | D | best error = [ 7.5432, 7.5432, 7.5432, 7.5432, 7.5432] +24-11-19 19:30:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:30:12 | D | sum error = [ 276.2458, 288.5519, 301.2394, 314.3584, 327.8689] +24-11-19 19:30:12 | D | best error = [ 7.5432, 7.5432, 7.5432, 7.5432, 7.5432] +24-11-19 19:30:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:30:12 | D | sum error = [ 341.7883, 356.1581, 370.9726, 386.2257, 401.9051] +24-11-19 19:30:12 | D | best error = [ 7.5432, 7.5432, 7.5432, 7.5432, 7.5432] +24-11-19 19:30:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:30:12 | D | sum error = [ 418.0710, 434.6749, 451.7505, 469.3280, 487.4068] +24-11-19 19:30:12 | D | best error = [ 7.5432, 7.5432, 7.5432, 7.5432, 7.5432] +24-11-19 19:30:12 | D | + error = [7.5432] +24-11-19 19:30:12 | D | - Calibrating model.layers.27.self_attn.o_proj.weight +24-11-19 19:30:12 | D | + w: sint8 +24-11-19 19:30:12 | D | + x: None +24-11-19 19:30:12 | D | + y: None +24-11-19 19:30:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:30:12 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:30:12 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:30:12 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:30:12 | D | - range ratio = [ 1.0000] +24-11-19 19:30:12 | D | sum error = [ 2.1054] +24-11-19 19:30:12 | D | best error = [ 2.1054] +24-11-19 19:30:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:30:12 | D | sum error = [ 2.0874, 2.0795, 2.0812, 2.0924, 2.1131] +24-11-19 19:30:12 | D | best error = [ 1.9901, 1.9376, 1.9065, 1.8862, 1.8729] +24-11-19 19:30:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:30:12 | D | sum error = [ 2.1472, 2.1904, 2.2633, 2.3375, 2.4317] +24-11-19 19:30:12 | D | best error = [ 1.8646, 1.8582, 1.8544, 1.8520, 1.8507] +24-11-19 19:30:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:30:12 | D | sum error = [ 2.5405, 2.6758, 2.8154, 2.9754, 3.1543] +24-11-19 19:30:12 | D | best error = [ 1.8498, 1.8494, 1.8490, 1.8489, 1.8486] +24-11-19 19:30:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:30:12 | D | sum error = [ 3.3478, 3.5666, 3.8065, 4.0555, 4.3278] +24-11-19 19:30:12 | D | best error = [ 1.8485, 1.8485, 1.8484, 1.8484, 1.8484] +24-11-19 19:30:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:30:12 | D | sum error = [ 4.6233, 4.9386, 5.2665, 5.6295, 6.0046] +24-11-19 19:30:12 | D | best error = [ 1.8484, 1.8484, 1.8484, 1.8484, 1.8484] +24-11-19 19:30:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:30:12 | D | sum error = [ 6.4127, 6.8397, 7.2910, 7.7708, 8.2899] +24-11-19 19:30:12 | D | best error = [ 1.8484, 1.8484, 1.8484, 1.8484, 1.8484] +24-11-19 19:30:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:30:12 | D | sum error = [ 8.8256, 9.4010, 10.0008, 10.6431, 11.3223] +24-11-19 19:30:12 | D | best error = [ 1.8484, 1.8484, 1.8484, 1.8484, 1.8484] +24-11-19 19:30:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:30:12 | D | sum error = [ 12.0320, 12.7890, 13.5786, 14.4137, 15.2965] +24-11-19 19:30:12 | D | best error = [ 1.8484, 1.8484, 1.8484, 1.8484, 1.8484] +24-11-19 19:30:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:30:12 | D | sum error = [ 16.2270, 17.2025, 18.2328, 19.3147, 20.4578] +24-11-19 19:30:12 | D | best error = [ 1.8484, 1.8484, 1.8484, 1.8484, 1.8484] +24-11-19 19:30:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:30:12 | D | sum error = [ 21.6518, 22.9060, 24.2282, 25.6162, 27.0792] +24-11-19 19:30:12 | D | best error = [ 1.8484, 1.8484, 1.8484, 1.8484, 1.8484] +24-11-19 19:30:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:30:12 | D | sum error = [ 28.6102, 30.2129, 31.8984, 33.6574, 35.5017] +24-11-19 19:30:12 | D | best error = [ 1.8484, 1.8484, 1.8484, 1.8484, 1.8484] +24-11-19 19:30:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:30:12 | D | sum error = [ 37.4338, 39.4540, 41.5687, 43.7791, 46.0927] +24-11-19 19:30:12 | D | best error = [ 1.8484, 1.8484, 1.8484, 1.8484, 1.8484] +24-11-19 19:30:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:30:12 | D | sum error = [ 48.5026, 51.0226, 53.6530, 56.3958, 59.2497] +24-11-19 19:30:12 | D | best error = [ 1.8484, 1.8484, 1.8484, 1.8484, 1.8484] +24-11-19 19:30:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:30:12 | D | sum error = [ 62.2263, 65.3269, 68.5514, 71.9174, 75.4003] +24-11-19 19:30:12 | D | best error = [ 1.8484, 1.8484, 1.8484, 1.8484, 1.8484] +24-11-19 19:30:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:30:12 | D | sum error = [ 79.0255, 82.7901, 86.6939, 90.7475, 94.9462] +24-11-19 19:30:12 | D | best error = [ 1.8484, 1.8484, 1.8484, 1.8484, 1.8484] +24-11-19 19:30:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:30:12 | D | sum error = [ 99.2900, 103.7844, 108.4285, 113.2319, 118.1878] +24-11-19 19:30:12 | D | best error = [ 1.8484, 1.8484, 1.8484, 1.8484, 1.8484] +24-11-19 19:30:12 | D | + error = [1.8484] +24-11-19 19:30:12 | D | - Calibrating model.layers.27.mlp.up_proj.weight +24-11-19 19:30:12 | D | + w: sint8 +24-11-19 19:30:12 | D | + x: None +24-11-19 19:30:12 | D | + y: None +24-11-19 19:30:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:30:12 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:30:12 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:30:13 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:30:13 | D | - range ratio = [ 1.0000] +24-11-19 19:30:13 | D | sum error = [ 11.2415] +24-11-19 19:30:13 | D | best error = [ 11.2415] +24-11-19 19:30:13 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:30:13 | D | sum error = [ 11.1656, 11.1359, 11.1451, 11.2841, 11.5237] +24-11-19 19:30:13 | D | best error = [ 10.3592, 10.0244, 9.8464, 9.7475, 9.6964] +24-11-19 19:30:13 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:30:13 | D | sum error = [ 11.7884, 12.1966, 12.7037, 13.3108, 13.9739] +24-11-19 19:30:13 | D | best error = [ 9.6672, 9.6549, 9.6503, 9.6488, 9.6482] +24-11-19 19:30:13 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:30:13 | D | sum error = [ 14.8393, 15.7339, 16.7932, 17.8974, 19.1483] +24-11-19 19:30:13 | D | best error = [ 9.6482, 9.6482, 9.6482, 9.6482, 9.6482] +24-11-19 19:30:13 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:30:13 | D | sum error = [ 20.4978, 21.9687, 23.5248, 25.1948, 27.0142] +24-11-19 19:30:13 | D | best error = [ 9.6482, 9.6482, 9.6482, 9.6482, 9.6482] +24-11-19 19:30:13 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:30:13 | D | sum error = [ 28.9428, 30.9786, 33.1772, 35.5040, 37.9648] +24-11-19 19:30:13 | D | best error = [ 9.6482, 9.6482, 9.6482, 9.6482, 9.6482] +24-11-19 19:30:13 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:30:13 | D | sum error = [ 40.5504, 43.3588, 46.2455, 49.3195, 52.6025] +24-11-19 19:30:13 | D | best error = [ 9.6482, 9.6482, 9.6482, 9.6482, 9.6482] +24-11-19 19:30:13 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:30:13 | D | sum error = [ 56.0305, 59.6611, 63.4965, 67.5425, 71.7762] +24-11-19 19:30:13 | D | best error = [ 9.6482, 9.6482, 9.6482, 9.6482, 9.6482] +24-11-19 19:30:13 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:30:13 | D | sum error = [ 76.2755, 80.9827, 85.9449, 91.1867, 96.6708] +24-11-19 19:30:13 | D | best error = [ 9.6482, 9.6482, 9.6482, 9.6482, 9.6482] +24-11-19 19:30:13 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:30:13 | D | sum error = [ 102.4302, 108.4663, 114.8240, 121.4551, 128.4149] +24-11-19 19:30:13 | D | best error = [ 9.6482, 9.6482, 9.6482, 9.6482, 9.6482] +24-11-19 19:30:13 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:30:13 | D | sum error = [ 135.6967, 143.3268, 151.2954, 159.6274, 168.3646] +24-11-19 19:30:13 | D | best error = [ 9.6482, 9.6482, 9.6482, 9.6482, 9.6482] +24-11-19 19:30:13 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:30:13 | D | sum error = [ 177.4641, 186.9880, 196.9341, 207.3030, 218.1222] +24-11-19 19:30:13 | D | best error = [ 9.6482, 9.6482, 9.6482, 9.6482, 9.6482] +24-11-19 19:30:13 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:30:13 | D | sum error = [ 229.4136, 241.1601, 253.3855, 266.1076, 279.3930] +24-11-19 19:30:13 | D | best error = [ 9.6482, 9.6482, 9.6482, 9.6482, 9.6482] +24-11-19 19:30:13 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:30:13 | D | sum error = [ 293.1857, 307.4889, 322.3757, 337.8105, 353.8463] +24-11-19 19:30:13 | D | best error = [ 9.6482, 9.6482, 9.6482, 9.6482, 9.6482] +24-11-19 19:30:13 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:30:13 | D | sum error = [ 370.4904, 387.7429, 405.6199, 424.1331, 443.2536] +24-11-19 19:30:13 | D | best error = [ 9.6482, 9.6482, 9.6482, 9.6482, 9.6482] +24-11-19 19:30:13 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:30:13 | D | sum error = [ 463.0583, 483.5186, 504.6280, 526.4308, 548.9186] +24-11-19 19:30:13 | D | best error = [ 9.6482, 9.6482, 9.6482, 9.6482, 9.6482] +24-11-19 19:30:13 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:30:13 | D | sum error = [ 572.0747, 595.9697, 620.5625, 645.8732, 671.9250] +24-11-19 19:30:13 | D | best error = [ 9.6482, 9.6482, 9.6482, 9.6482, 9.6482] +24-11-19 19:30:13 | D | + error = [9.6482] +24-11-19 19:30:14 | D | - Calibrating model.layers.27.mlp.gate_proj.weight +24-11-19 19:30:14 | D | + w: sint8 +24-11-19 19:30:14 | D | + x: None +24-11-19 19:30:14 | D | + y: None +24-11-19 19:30:14 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:30:14 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:30:14 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:30:14 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:30:14 | D | - range ratio = [ 1.0000] +24-11-19 19:30:14 | D | sum error = [ 12.0688] +24-11-19 19:30:14 | D | best error = [ 12.0688] +24-11-19 19:30:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:30:15 | D | sum error = [ 11.9305, 11.9408, 11.9773, 12.1410, 12.3583] +24-11-19 19:30:15 | D | best error = [ 11.1054, 10.7478, 10.5560, 10.4542, 10.3976] +24-11-19 19:30:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:30:15 | D | sum error = [ 12.6531, 13.0555, 13.6234, 14.2599, 14.9617] +24-11-19 19:30:15 | D | best error = [ 10.3719, 10.3602, 10.3553, 10.3535, 10.3531] +24-11-19 19:30:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:30:15 | D | sum error = [ 15.8358, 16.8170, 17.9057, 19.1352, 20.4404] +24-11-19 19:30:15 | D | best error = [ 10.3531, 10.3531, 10.3531, 10.3531, 10.3531] +24-11-19 19:30:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:30:15 | D | sum error = [ 21.8931, 23.4590, 25.1339, 26.9731, 28.8841] +24-11-19 19:30:15 | D | best error = [ 10.3531, 10.3531, 10.3531, 10.3531, 10.3531] +24-11-19 19:30:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:30:15 | D | sum error = [ 30.9768, 33.2321, 35.5694, 38.0770, 40.7258] +24-11-19 19:30:15 | D | best error = [ 10.3531, 10.3531, 10.3531, 10.3531, 10.3531] +24-11-19 19:30:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:30:15 | D | sum error = [ 43.5925, 46.6040, 49.7458, 53.1154, 56.7202] +24-11-19 19:30:15 | D | best error = [ 10.3531, 10.3531, 10.3531, 10.3531, 10.3531] +24-11-19 19:30:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:30:15 | D | sum error = [ 60.4959, 64.4568, 68.6611, 73.0819, 77.7722] +24-11-19 19:30:15 | D | best error = [ 10.3531, 10.3531, 10.3531, 10.3531, 10.3531] +24-11-19 19:30:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:30:15 | D | sum error = [ 82.7491, 88.0169, 93.5066, 99.3645, 105.5211] +24-11-19 19:30:15 | D | best error = [ 10.3531, 10.3531, 10.3531, 10.3531, 10.3531] +24-11-19 19:30:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:30:15 | D | sum error = [ 111.9770, 118.7974, 125.9759, 133.5247, 141.4702] +24-11-19 19:30:15 | D | best error = [ 10.3531, 10.3531, 10.3531, 10.3531, 10.3531] +24-11-19 19:30:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:30:15 | D | sum error = [ 149.8231, 158.5534, 167.7750, 177.4322, 187.5842] +24-11-19 19:30:15 | D | best error = [ 10.3531, 10.3531, 10.3531, 10.3531, 10.3531] +24-11-19 19:30:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:30:15 | D | sum error = [ 198.2422, 209.4175, 221.1227, 233.3894, 246.2967] +24-11-19 19:30:15 | D | best error = [ 10.3531, 10.3531, 10.3531, 10.3531, 10.3531] +24-11-19 19:30:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:30:15 | D | sum error = [ 259.7915, 273.8866, 288.6489, 304.1256, 320.2453] +24-11-19 19:30:15 | D | best error = [ 10.3531, 10.3531, 10.3531, 10.3531, 10.3531] +24-11-19 19:30:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:30:15 | D | sum error = [ 337.1510, 354.7688, 373.1200, 392.2503, 412.2192] +24-11-19 19:30:15 | D | best error = [ 10.3531, 10.3531, 10.3531, 10.3531, 10.3531] +24-11-19 19:30:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:30:15 | D | sum error = [ 433.0159, 454.6300, 477.1534, 500.5311, 524.7777] +24-11-19 19:30:15 | D | best error = [ 10.3531, 10.3531, 10.3531, 10.3531, 10.3531] +24-11-19 19:30:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:30:15 | D | sum error = [ 549.9665, 576.0993, 603.1733, 631.2696, 660.3320] +24-11-19 19:30:15 | D | best error = [ 10.3531, 10.3531, 10.3531, 10.3531, 10.3531] +24-11-19 19:30:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:30:15 | D | sum error = [ 690.3760, 721.3728, 753.3330, 786.2933, 820.2761] +24-11-19 19:30:15 | D | best error = [ 10.3531, 10.3531, 10.3531, 10.3531, 10.3531] +24-11-19 19:30:15 | D | + error = [10.3531] +24-11-19 19:30:15 | D | - Calibrating model.layers.27.mlp.down_proj.weight +24-11-19 19:30:15 | D | + w: sint8 +24-11-19 19:30:15 | D | + x: None +24-11-19 19:30:15 | D | + y: None +24-11-19 19:30:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:30:15 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:30:15 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:30:15 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:30:15 | D | - range ratio = [ 1.0000] +24-11-19 19:30:15 | D | sum error = [ 4.5001] +24-11-19 19:30:15 | D | best error = [ 4.5001] +24-11-19 19:30:16 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:30:16 | D | sum error = [ 4.4560, 4.4262, 4.4098, 4.3946, 4.3927] +24-11-19 19:30:16 | D | best error = [ 4.3070, 4.2164, 4.1578, 4.1139, 4.0834] +24-11-19 19:30:16 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:30:16 | D | sum error = [ 4.4066, 4.4390, 4.4815, 4.5616, 4.6530] +24-11-19 19:30:16 | D | best error = [ 4.0590, 4.0417, 4.0264, 4.0169, 4.0104] +24-11-19 19:30:16 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:30:16 | D | sum error = [ 4.7680, 4.8988, 5.0863, 5.2859, 5.5161] +24-11-19 19:30:16 | D | best error = [ 4.0058, 4.0026, 4.0012, 3.9997, 3.9990] +24-11-19 19:30:16 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:30:16 | D | sum error = [ 5.7899, 6.0884, 6.4210, 6.8011, 7.2024] +24-11-19 19:30:16 | D | best error = [ 3.9987, 3.9983, 3.9981, 3.9980, 3.9979] +24-11-19 19:30:16 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:30:16 | D | sum error = [ 7.6526, 8.1410, 8.6886, 9.2665, 9.8915] +24-11-19 19:30:16 | D | best error = [ 3.9979, 3.9979, 3.9979, 3.9979, 3.9979] +24-11-19 19:30:16 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:30:16 | D | sum error = [ 10.5805, 11.2970, 12.0744, 12.9167, 13.8001] +24-11-19 19:30:16 | D | best error = [ 3.9979, 3.9979, 3.9979, 3.9979, 3.9979] +24-11-19 19:30:16 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:30:16 | D | sum error = [ 14.7531, 15.7728, 16.8505, 18.0012, 19.2159] +24-11-19 19:30:16 | D | best error = [ 3.9979, 3.9979, 3.9979, 3.9979, 3.9979] +24-11-19 19:30:16 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:30:16 | D | sum error = [ 20.5171, 21.8877, 23.3548, 24.8823, 26.5213] +24-11-19 19:30:16 | D | best error = [ 3.9979, 3.9979, 3.9979, 3.9979, 3.9979] +24-11-19 19:30:16 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:30:16 | D | sum error = [ 28.2452, 30.0631, 31.9937, 34.0174, 36.1625] +24-11-19 19:30:16 | D | best error = [ 3.9979, 3.9979, 3.9979, 3.9979, 3.9979] +24-11-19 19:30:16 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:30:16 | D | sum error = [ 38.4265, 40.7969, 43.3067, 45.9415, 48.7166] +24-11-19 19:30:16 | D | best error = [ 3.9979, 3.9979, 3.9979, 3.9979, 3.9979] +24-11-19 19:30:16 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:30:16 | D | sum error = [ 51.6309, 54.6838, 57.8952, 61.2682, 64.7924] +24-11-19 19:30:16 | D | best error = [ 3.9979, 3.9979, 3.9979, 3.9979, 3.9979] +24-11-19 19:30:16 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:30:16 | D | sum error = [ 68.4935, 72.3736, 76.4307, 80.6720, 85.1083] +24-11-19 19:30:16 | D | best error = [ 3.9979, 3.9979, 3.9979, 3.9979, 3.9979] +24-11-19 19:30:16 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:30:16 | D | sum error = [ 89.7535, 94.5940, 99.6489, 104.9149, 110.4059] +24-11-19 19:30:16 | D | best error = [ 3.9979, 3.9979, 3.9979, 3.9979, 3.9979] +24-11-19 19:30:16 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:30:16 | D | sum error = [ 116.1207, 122.0770, 128.2761, 134.7242, 141.4004] +24-11-19 19:30:16 | D | best error = [ 3.9979, 3.9979, 3.9979, 3.9979, 3.9979] +24-11-19 19:30:16 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:30:16 | D | sum error = [ 148.3425, 155.5418, 163.0096, 170.7481, 178.7622] +24-11-19 19:30:16 | D | best error = [ 3.9979, 3.9979, 3.9979, 3.9979, 3.9979] +24-11-19 19:30:16 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:30:16 | D | sum error = [ 187.0526, 195.6319, 204.4920, 213.6521, 223.1054] +24-11-19 19:30:16 | D | best error = [ 3.9979, 3.9979, 3.9979, 3.9979, 3.9979] +24-11-19 19:30:16 | D | + error = [3.9979] +24-11-19 19:30:16 | D | - Quantizing model.layers.27.self_attn.q_proj.weight +24-11-19 19:30:17 | D | - Quantizing model.layers.27.self_attn.k_proj.weight +24-11-19 19:30:18 | D | - Quantizing model.layers.27.self_attn.v_proj.weight +24-11-19 19:30:19 | D | - Quantizing model.layers.27.self_attn.o_proj.weight +24-11-19 19:30:20 | D | - Quantizing model.layers.27.mlp.up_proj.weight +24-11-19 19:30:21 | D | - Quantizing model.layers.27.mlp.gate_proj.weight +24-11-19 19:30:22 | D | - Quantizing model.layers.27.mlp.down_proj.weight +24-11-19 19:30:30 | D | - Quantizing layer model.layers.28 +24-11-19 19:30:30 | D | - Calibrating model.layers.28.self_attn.q_proj.weight +24-11-19 19:30:30 | D | + w: sint8 +24-11-19 19:30:30 | D | + x: None +24-11-19 19:30:30 | D | + y: None +24-11-19 19:30:30 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:30:30 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:30:30 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:30:30 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:30:31 | D | - range ratio = [ 1.0000] +24-11-19 19:30:31 | D | sum error = [ 18.7788] +24-11-19 19:30:31 | D | best error = [ 18.7788] +24-11-19 19:30:43 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:30:43 | D | sum error = [ 18.7679, 18.8861, 18.8486, 18.9488, 19.2768] +24-11-19 19:30:43 | D | best error = [ 18.7679, 18.7679, 18.7679, 18.7679, 18.7679] +24-11-19 19:30:43 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:30:43 | D | sum error = [ 20.3743, 20.4717, 22.2187, 22.6680, 24.3455] +24-11-19 19:30:43 | D | best error = [ 18.7679, 18.7679, 18.7679, 18.7679, 18.7679] +24-11-19 19:30:43 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:30:43 | D | sum error = [ 25.7538, 26.5814, 28.5234, 30.1514, 33.0979] +24-11-19 19:30:43 | D | best error = [ 18.7679, 18.7679, 18.7679, 18.7679, 18.7679] +24-11-19 19:30:43 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:30:43 | D | sum error = [ 34.6792, 37.9789, 41.0398, 43.4004, 47.0807] +24-11-19 19:30:43 | D | best error = [ 18.7679, 18.7679, 18.7679, 18.7679, 18.7679] +24-11-19 19:30:43 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:30:43 | D | sum error = [ 50.5046, 55.0043, 58.9767, 63.7599, 67.4833] +24-11-19 19:30:43 | D | best error = [ 18.7679, 18.7679, 18.7679, 18.7679, 18.7679] +24-11-19 19:30:43 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:30:43 | D | sum error = [ 73.5563, 79.1615, 86.0048, 93.0311, 100.1150] +24-11-19 19:30:43 | D | best error = [ 18.7679, 18.7679, 18.7679, 18.7679, 18.7679] +24-11-19 19:30:43 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:30:43 | D | sum error = [ 107.6223, 116.4695, 125.4132, 135.6659, 145.1165] +24-11-19 19:30:43 | D | best error = [ 18.7679, 18.7679, 18.7679, 18.7679, 18.7679] +24-11-19 19:30:43 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:30:43 | D | sum error = [ 156.6569, 168.6560, 182.1363, 194.2433, 209.4460] +24-11-19 19:30:43 | D | best error = [ 18.7679, 18.7679, 18.7679, 18.7679, 18.7679] +24-11-19 19:30:43 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:30:43 | D | sum error = [ 224.8753, 240.9971, 257.8126, 277.3253, 296.4623] +24-11-19 19:30:43 | D | best error = [ 18.7679, 18.7679, 18.7679, 18.7679, 18.7679] +24-11-19 19:30:43 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:30:43 | D | sum error = [ 318.5433, 342.2586, 367.1316, 394.7030, 423.7895] +24-11-19 19:30:43 | D | best error = [ 18.7679, 18.7679, 18.7679, 18.7679, 18.7679] +24-11-19 19:30:43 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:30:43 | D | sum error = [ 454.6470, 487.4471, 523.0448, 561.4805, 602.8036] +24-11-19 19:30:43 | D | best error = [ 18.7679, 18.7679, 18.7679, 18.7679, 18.7679] +24-11-19 19:30:43 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:30:43 | D | sum error = [ 646.5668, 694.5869, 745.6242, 800.9957, 860.2510] +24-11-19 19:30:43 | D | best error = [ 18.7679, 18.7679, 18.7679, 18.7679, 18.7679] +24-11-19 19:30:43 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:30:43 | D | sum error = [ 924.8735, 994.7975, 1071.7940, 1154.0450, 1243.1488] +24-11-19 19:30:43 | D | best error = [ 18.7679, 18.7679, 18.7679, 18.7679, 18.7679] +24-11-19 19:30:43 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:30:43 | D | sum error = [ 1341.7577, 1449.2143, 1567.6069, 1698.8528, 1841.4967] +24-11-19 19:30:43 | D | best error = [ 18.7679, 18.7679, 18.7679, 18.7679, 18.7679] +24-11-19 19:30:43 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:30:43 | D | sum error = [ 1999.2310, 2173.6387, 2366.4776, 2579.1361, 2814.2628] +24-11-19 19:30:43 | D | best error = [ 18.7679, 18.7679, 18.7679, 18.7679, 18.7679] +24-11-19 19:30:43 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:30:43 | D | sum error = [ 3075.2275, 3363.4381, 3680.2907, 4029.3178, 4410.4240] +24-11-19 19:30:43 | D | best error = [ 18.7679, 18.7679, 18.7679, 18.7679, 18.7679] +24-11-19 19:30:43 | D | + error = [18.7679] +24-11-19 19:30:43 | D | - Calibrating model.layers.28.self_attn.k_proj.weight +24-11-19 19:30:43 | D | + w: sint8 +24-11-19 19:30:43 | D | + x: None +24-11-19 19:30:43 | D | + y: None +24-11-19 19:30:43 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:30:43 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:30:43 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:30:44 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:30:44 | D | - range ratio = [ 1.0000] +24-11-19 19:30:44 | D | sum error = [ 22.1443] +24-11-19 19:30:44 | D | best error = [ 22.1443] +24-11-19 19:30:56 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:30:56 | D | sum error = [ 21.3415, 22.6504, 21.7591, 22.3892, 23.5648] +24-11-19 19:30:56 | D | best error = [ 21.3415, 21.3415, 21.3415, 21.3415, 21.3415] +24-11-19 19:30:56 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:30:56 | D | sum error = [ 23.3029, 25.2611, 25.4104, 26.5496, 29.2179] +24-11-19 19:30:56 | D | best error = [ 21.3415, 21.3415, 21.3415, 21.3415, 21.3415] +24-11-19 19:30:56 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:30:56 | D | sum error = [ 29.6127, 32.9373, 32.3034, 37.5743, 40.3733] +24-11-19 19:30:56 | D | best error = [ 21.3415, 21.3415, 21.3415, 21.3415, 21.3415] +24-11-19 19:30:56 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:30:56 | D | sum error = [ 43.1356, 44.7309, 47.8809, 53.9544, 57.8230] +24-11-19 19:30:56 | D | best error = [ 21.3415, 21.3415, 21.3415, 21.3415, 21.3415] +24-11-19 19:30:56 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:30:56 | D | sum error = [ 61.0793, 65.2571, 70.6117, 76.0571, 81.1862] +24-11-19 19:30:56 | D | best error = [ 21.3415, 21.3415, 21.3415, 21.3415, 21.3415] +24-11-19 19:30:56 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:30:56 | D | sum error = [ 87.4067, 92.0694, 98.5343, 105.8371, 113.3714] +24-11-19 19:30:56 | D | best error = [ 21.3415, 21.3415, 21.3415, 21.3415, 21.3415] +24-11-19 19:30:56 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:30:56 | D | sum error = [ 121.6317, 130.1619, 138.1101, 148.0585, 157.7035] +24-11-19 19:30:56 | D | best error = [ 21.3415, 21.3415, 21.3415, 21.3415, 21.3415] +24-11-19 19:30:56 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:30:56 | D | sum error = [ 168.7104, 179.2076, 193.6793, 207.9542, 222.1336] +24-11-19 19:30:56 | D | best error = [ 21.3415, 21.3415, 21.3415, 21.3415, 21.3415] +24-11-19 19:30:56 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:30:56 | D | sum error = [ 238.0638, 255.0741, 272.8838, 292.5107, 313.2390] +24-11-19 19:30:56 | D | best error = [ 21.3415, 21.3415, 21.3415, 21.3415, 21.3415] +24-11-19 19:30:56 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:30:56 | D | sum error = [ 334.7526, 357.6432, 381.8855, 408.7673, 437.5067] +24-11-19 19:30:56 | D | best error = [ 21.3415, 21.3415, 21.3415, 21.3415, 21.3415] +24-11-19 19:30:56 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:30:56 | D | sum error = [ 468.9198, 502.9545, 542.1556, 579.7937, 625.0347] +24-11-19 19:30:56 | D | best error = [ 21.3415, 21.3415, 21.3415, 21.3415, 21.3415] +24-11-19 19:30:56 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:30:56 | D | sum error = [ 669.4771, 720.8829, 775.9294, 832.7974, 906.0599] +24-11-19 19:30:56 | D | best error = [ 21.3415, 21.3415, 21.3415, 21.3415, 21.3415] +24-11-19 19:30:56 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:30:56 | D | sum error = [ 973.0245, 1050.3292, 1133.8896, 1228.0449, 1328.4409] +24-11-19 19:30:56 | D | best error = [ 21.3415, 21.3415, 21.3415, 21.3415, 21.3415] +24-11-19 19:30:56 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:30:56 | D | sum error = [ 1438.7660, 1564.8825, 1687.6026, 1831.5298, 1994.4731] +24-11-19 19:30:56 | D | best error = [ 21.3415, 21.3415, 21.3415, 21.3415, 21.3415] +24-11-19 19:30:56 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:30:56 | D | sum error = [ 2157.4775, 2340.7242, 2539.4488, 2761.1414, 3000.0253] +24-11-19 19:30:56 | D | best error = [ 21.3415, 21.3415, 21.3415, 21.3415, 21.3415] +24-11-19 19:30:56 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:30:56 | D | sum error = [ 3276.8860, 3567.5644, 3884.3581, 4253.9438, 4613.7937] +24-11-19 19:30:56 | D | best error = [ 21.3415, 21.3415, 21.3415, 21.3415, 21.3415] +24-11-19 19:30:56 | D | + error = [21.3415] +24-11-19 19:30:56 | D | - Calibrating model.layers.28.self_attn.v_proj.weight +24-11-19 19:30:56 | D | + w: sint8 +24-11-19 19:30:56 | D | + x: None +24-11-19 19:30:56 | D | + y: None +24-11-19 19:30:56 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:30:56 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:30:56 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:30:57 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:30:57 | D | - range ratio = [ 1.0000] +24-11-19 19:30:57 | D | sum error = [ 9.1233] +24-11-19 19:30:57 | D | best error = [ 9.1233] +24-11-19 19:30:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:30:57 | D | sum error = [ 9.0501, 9.0801, 9.1003, 9.2266, 9.3541] +24-11-19 19:30:57 | D | best error = [ 8.4571, 8.2022, 8.0670, 7.9892, 7.9511] +24-11-19 19:30:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:30:57 | D | sum error = [ 9.5990, 9.9026, 10.3098, 10.8341, 11.3582] +24-11-19 19:30:57 | D | best error = [ 7.9323, 7.9228, 7.9182, 7.9175, 7.9174] +24-11-19 19:30:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:30:57 | D | sum error = [ 12.0497, 12.7902, 13.6460, 14.5241, 15.4965] +24-11-19 19:30:57 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 19:30:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:30:57 | D | sum error = [ 16.6176, 17.7950, 19.0561, 20.3889, 21.8792] +24-11-19 19:30:57 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 19:30:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:30:57 | D | sum error = [ 23.3695, 25.0749, 26.8445, 28.6717, 30.6268] +24-11-19 19:30:57 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 19:30:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:30:57 | D | sum error = [ 32.7446, 34.9025, 37.2537, 39.7406, 42.3423] +24-11-19 19:30:57 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 19:30:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:30:57 | D | sum error = [ 45.1074, 47.9738, 51.0476, 54.2785, 57.6558] +24-11-19 19:30:57 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 19:30:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:30:57 | D | sum error = [ 61.2640, 64.9597, 68.8845, 73.0158, 77.3673] +24-11-19 19:30:57 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 19:30:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:30:57 | D | sum error = [ 81.9135, 86.6916, 91.7234, 96.9422, 102.4271] +24-11-19 19:30:57 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 19:30:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:30:57 | D | sum error = [ 108.1510, 114.1752, 120.4243, 126.9883, 133.8490] +24-11-19 19:30:57 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 19:30:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:30:57 | D | sum error = [ 141.0038, 148.4584, 156.2055, 164.2971, 172.6731] +24-11-19 19:30:57 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 19:30:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:30:57 | D | sum error = [ 181.4360, 190.5568, 199.9950, 209.7777, 219.9344] +24-11-19 19:30:57 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 19:30:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:30:57 | D | sum error = [ 230.5038, 241.4300, 252.7360, 264.4537, 276.5891] +24-11-19 19:30:57 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 19:30:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:30:57 | D | sum error = [ 289.1350, 302.1486, 315.5957, 329.4751, 343.7893] +24-11-19 19:30:57 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 19:30:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:30:57 | D | sum error = [ 358.5384, 373.7349, 389.4025, 405.5668, 422.2052] +24-11-19 19:30:57 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 19:30:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:30:57 | D | sum error = [ 439.3431, 456.9945, 475.1448, 493.8317, 513.0228] +24-11-19 19:30:57 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 19:30:57 | D | + error = [7.9174] +24-11-19 19:30:57 | D | - Calibrating model.layers.28.self_attn.o_proj.weight +24-11-19 19:30:57 | D | + w: sint8 +24-11-19 19:30:57 | D | + x: None +24-11-19 19:30:57 | D | + y: None +24-11-19 19:30:57 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:30:57 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:30:57 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:30:57 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:30:57 | D | - range ratio = [ 1.0000] +24-11-19 19:30:57 | D | sum error = [ 2.1609] +24-11-19 19:30:57 | D | best error = [ 2.1609] +24-11-19 19:30:58 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:30:58 | D | sum error = [ 2.1408, 2.1420, 2.1586, 2.1939, 2.2390] +24-11-19 19:30:58 | D | best error = [ 2.0366, 1.9843, 1.9549, 1.9366, 1.9249] +24-11-19 19:30:58 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:30:58 | D | sum error = [ 2.3028, 2.3916, 2.4967, 2.6190, 2.7690] +24-11-19 19:30:58 | D | best error = [ 1.9164, 1.9106, 1.9072, 1.9046, 1.9028] +24-11-19 19:30:58 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:30:58 | D | sum error = [ 2.9363, 3.1241, 3.3326, 3.5538, 3.8003] +24-11-19 19:30:58 | D | best error = [ 1.9016, 1.9010, 1.9006, 1.9004, 1.9004] +24-11-19 19:30:58 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:30:58 | D | sum error = [ 4.0561, 4.3480, 4.6493, 4.9741, 5.3083] +24-11-19 19:30:58 | D | best error = [ 1.9002, 1.9002, 1.9002, 1.9002, 1.9002] +24-11-19 19:30:58 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:30:58 | D | sum error = [ 5.6810, 6.0732, 6.4758, 6.9208, 7.3737] +24-11-19 19:30:58 | D | best error = [ 1.9001, 1.9001, 1.9001, 1.9001, 1.9001] +24-11-19 19:30:58 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:30:58 | D | sum error = [ 7.8637, 8.3611, 8.9041, 9.4671, 10.0661] +24-11-19 19:30:58 | D | best error = [ 1.9001, 1.9001, 1.9001, 1.9001, 1.9001] +24-11-19 19:30:58 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:30:58 | D | sum error = [ 10.6871, 11.3410, 12.0312, 12.7690, 13.5353] +24-11-19 19:30:58 | D | best error = [ 1.9001, 1.9001, 1.9001, 1.9001, 1.9001] +24-11-19 19:30:58 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:30:58 | D | sum error = [ 14.3354, 15.1917, 16.0790, 17.0142, 17.9929] +24-11-19 19:30:58 | D | best error = [ 1.9001, 1.9001, 1.9001, 1.9001, 1.9001] +24-11-19 19:30:58 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:30:58 | D | sum error = [ 19.0247, 20.1105, 21.2380, 22.4322, 23.6813] +24-11-19 19:30:58 | D | best error = [ 1.9001, 1.9001, 1.9001, 1.9001, 1.9001] +24-11-19 19:30:58 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:30:58 | D | sum error = [ 24.9940, 26.3792, 27.8231, 29.3399, 30.9247] +24-11-19 19:30:58 | D | best error = [ 1.9001, 1.9001, 1.9001, 1.9001, 1.9001] +24-11-19 19:30:58 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:30:58 | D | sum error = [ 32.5901, 34.3385, 36.1710, 38.0869, 40.0924] +24-11-19 19:30:58 | D | best error = [ 1.9001, 1.9001, 1.9001, 1.9001, 1.9001] +24-11-19 19:30:58 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:30:58 | D | sum error = [ 42.1841, 44.3755, 46.6632, 49.0553, 51.5571] +24-11-19 19:30:58 | D | best error = [ 1.9001, 1.9001, 1.9001, 1.9001, 1.9001] +24-11-19 19:30:58 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:30:58 | D | sum error = [ 54.1649, 56.8877, 59.7333, 62.7022, 65.7942] +24-11-19 19:30:58 | D | best error = [ 1.9001, 1.9001, 1.9001, 1.9001, 1.9001] +24-11-19 19:30:58 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:30:58 | D | sum error = [ 69.0117, 72.3615, 75.8583, 79.4940, 83.2668] +24-11-19 19:30:58 | D | best error = [ 1.9001, 1.9001, 1.9001, 1.9001, 1.9001] +24-11-19 19:30:58 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:30:58 | D | sum error = [ 87.1915, 91.2737, 95.5139, 99.9155, 104.4719] +24-11-19 19:30:58 | D | best error = [ 1.9001, 1.9001, 1.9001, 1.9001, 1.9001] +24-11-19 19:30:58 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:30:58 | D | sum error = [ 109.1933, 114.0808, 119.1353, 124.3562, 129.7486] +24-11-19 19:30:58 | D | best error = [ 1.9001, 1.9001, 1.9001, 1.9001, 1.9001] +24-11-19 19:30:58 | D | + error = [1.9001] +24-11-19 19:30:58 | D | - Calibrating model.layers.28.mlp.up_proj.weight +24-11-19 19:30:58 | D | + w: sint8 +24-11-19 19:30:58 | D | + x: None +24-11-19 19:30:58 | D | + y: None +24-11-19 19:30:58 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:30:58 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:30:58 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:30:58 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:30:58 | D | - range ratio = [ 1.0000] +24-11-19 19:30:58 | D | sum error = [ 11.5523] +24-11-19 19:30:58 | D | best error = [ 11.5523] +24-11-19 19:30:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:30:59 | D | sum error = [ 11.4993, 11.4883, 11.4809, 11.6242, 11.8435] +24-11-19 19:30:59 | D | best error = [ 10.6639, 10.3166, 10.1307, 10.0300, 9.9768] +24-11-19 19:30:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:30:59 | D | sum error = [ 12.1662, 12.5575, 13.0444, 13.6598, 14.4297] +24-11-19 19:30:59 | D | best error = [ 9.9485, 9.9359, 9.9307, 9.9296, 9.9292] +24-11-19 19:30:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:30:59 | D | sum error = [ 15.2427, 16.1700, 17.2359, 18.4159, 19.7335] +24-11-19 19:30:59 | D | best error = [ 9.9292, 9.9292, 9.9292, 9.9292, 9.9292] +24-11-19 19:30:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:30:59 | D | sum error = [ 21.0858, 22.5846, 24.2390, 25.9613, 27.8960] +24-11-19 19:30:59 | D | best error = [ 9.9292, 9.9292, 9.9292, 9.9292, 9.9292] +24-11-19 19:30:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:30:59 | D | sum error = [ 29.8693, 31.9747, 34.2617, 36.6413, 39.1875] +24-11-19 19:30:59 | D | best error = [ 9.9292, 9.9292, 9.9292, 9.9292, 9.9292] +24-11-19 19:30:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:30:59 | D | sum error = [ 41.8974, 44.7937, 47.8091, 51.0448, 54.4063] +24-11-19 19:30:59 | D | best error = [ 9.9292, 9.9292, 9.9292, 9.9292, 9.9292] +24-11-19 19:30:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:30:59 | D | sum error = [ 58.0062, 61.7830, 65.7992, 70.0255, 74.4746] +24-11-19 19:30:59 | D | best error = [ 9.9292, 9.9292, 9.9292, 9.9292, 9.9292] +24-11-19 19:30:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:30:59 | D | sum error = [ 79.1456, 84.0910, 89.2641, 94.6930, 100.4564] +24-11-19 19:30:59 | D | best error = [ 9.9292, 9.9292, 9.9292, 9.9292, 9.9292] +24-11-19 19:30:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:30:59 | D | sum error = [ 106.5133, 112.8471, 119.5348, 126.5226, 133.8717] +24-11-19 19:30:59 | D | best error = [ 9.9292, 9.9292, 9.9292, 9.9292, 9.9292] +24-11-19 19:30:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:30:59 | D | sum error = [ 141.5797, 149.6586, 158.1263, 166.9825, 176.2936] +24-11-19 19:30:59 | D | best error = [ 9.9292, 9.9292, 9.9292, 9.9292, 9.9292] +24-11-19 19:30:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:30:59 | D | sum error = [ 185.9952, 196.1724, 206.8162, 217.9417, 229.5415] +24-11-19 19:30:59 | D | best error = [ 9.9292, 9.9292, 9.9292, 9.9292, 9.9292] +24-11-19 19:30:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:30:59 | D | sum error = [ 241.6793, 254.3216, 267.5253, 281.3402, 295.7060] +24-11-19 19:30:59 | D | best error = [ 9.9292, 9.9292, 9.9292, 9.9292, 9.9292] +24-11-19 19:30:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:30:59 | D | sum error = [ 310.7049, 326.3001, 342.5297, 359.4277, 376.9899] +24-11-19 19:30:59 | D | best error = [ 9.9292, 9.9292, 9.9292, 9.9292, 9.9292] +24-11-19 19:30:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:30:59 | D | sum error = [ 395.2534, 414.2291, 433.9081, 454.3394, 475.5190] +24-11-19 19:30:59 | D | best error = [ 9.9292, 9.9292, 9.9292, 9.9292, 9.9292] +24-11-19 19:30:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:30:59 | D | sum error = [ 497.4388, 520.1496, 543.6192, 567.8975, 593.0246] +24-11-19 19:30:59 | D | best error = [ 9.9292, 9.9292, 9.9292, 9.9292, 9.9292] +24-11-19 19:30:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:30:59 | D | sum error = [ 618.9493, 645.7091, 673.3014, 701.7370, 731.0267] +24-11-19 19:30:59 | D | best error = [ 9.9292, 9.9292, 9.9292, 9.9292, 9.9292] +24-11-19 19:30:59 | D | + error = [9.9292] +24-11-19 19:30:59 | D | - Calibrating model.layers.28.mlp.gate_proj.weight +24-11-19 19:30:59 | D | + w: sint8 +24-11-19 19:30:59 | D | + x: None +24-11-19 19:30:59 | D | + y: None +24-11-19 19:30:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:30:59 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:30:59 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:30:59 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:30:59 | D | - range ratio = [ 1.0000] +24-11-19 19:30:59 | D | sum error = [ 12.2295] +24-11-19 19:30:59 | D | best error = [ 12.2295] +24-11-19 19:31:00 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:31:00 | D | sum error = [ 12.1349, 12.1053, 12.1750, 12.3341, 12.4892] +24-11-19 19:31:00 | D | best error = [ 11.2763, 10.9069, 10.7142, 10.6117, 10.5496] +24-11-19 19:31:00 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:31:00 | D | sum error = [ 12.8240, 13.2973, 13.8475, 14.5017, 15.2518] +24-11-19 19:31:00 | D | best error = [ 10.5200, 10.5071, 10.5019, 10.5006, 10.5002] +24-11-19 19:31:00 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:31:00 | D | sum error = [ 16.1098, 17.1345, 18.2082, 19.4972, 20.8527] +24-11-19 19:31:00 | D | best error = [ 10.5000, 10.5000, 10.5000, 10.5000, 10.5000] +24-11-19 19:31:00 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:31:00 | D | sum error = [ 22.3263, 23.9262, 25.6239, 27.4706, 29.4944] +24-11-19 19:31:00 | D | best error = [ 10.5000, 10.5000, 10.5000, 10.5000, 10.5000] +24-11-19 19:31:00 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:31:00 | D | sum error = [ 31.6155, 33.8623, 36.2842, 38.8757, 41.6286] +24-11-19 19:31:00 | D | best error = [ 10.5000, 10.5000, 10.5000, 10.5000, 10.5000] +24-11-19 19:31:00 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:31:00 | D | sum error = [ 44.5286, 47.6227, 50.9096, 54.3287, 58.0157] +24-11-19 19:31:00 | D | best error = [ 10.5000, 10.5000, 10.5000, 10.5000, 10.5000] +24-11-19 19:31:00 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:31:00 | D | sum error = [ 61.8519, 65.9766, 70.3050, 74.9015, 79.7879] +24-11-19 19:31:00 | D | best error = [ 10.5000, 10.5000, 10.5000, 10.5000, 10.5000] +24-11-19 19:31:00 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:31:00 | D | sum error = [ 84.8978, 90.2625, 96.0000, 102.0168, 108.3326] +24-11-19 19:31:00 | D | best error = [ 10.5000, 10.5000, 10.5000, 10.5000, 10.5000] +24-11-19 19:31:00 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:31:00 | D | sum error = [ 115.0969, 122.1221, 129.5772, 137.4136, 145.6679] +24-11-19 19:31:00 | D | best error = [ 10.5000, 10.5000, 10.5000, 10.5000, 10.5000] +24-11-19 19:31:00 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:31:00 | D | sum error = [ 154.3359, 163.4695, 173.0644, 183.1774, 193.7778] +24-11-19 19:31:00 | D | best error = [ 10.5000, 10.5000, 10.5000, 10.5000, 10.5000] +24-11-19 19:31:00 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:31:00 | D | sum error = [ 204.8918, 216.5085, 228.7044, 241.5389, 254.9446] +24-11-19 19:31:00 | D | best error = [ 10.5000, 10.5000, 10.5000, 10.5000, 10.5000] +24-11-19 19:31:00 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:31:00 | D | sum error = [ 269.0483, 283.7598, 299.2001, 315.3343, 332.1942] +24-11-19 19:31:00 | D | best error = [ 10.5000, 10.5000, 10.5000, 10.5000, 10.5000] +24-11-19 19:31:00 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:31:00 | D | sum error = [ 349.8637, 368.2362, 387.4854, 407.5654, 428.4828] +24-11-19 19:31:00 | D | best error = [ 10.5000, 10.5000, 10.5000, 10.5000, 10.5000] +24-11-19 19:31:00 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:31:00 | D | sum error = [ 450.2639, 472.9022, 496.4664, 520.9614, 546.3813] +24-11-19 19:31:00 | D | best error = [ 10.5000, 10.5000, 10.5000, 10.5000, 10.5000] +24-11-19 19:31:00 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:31:00 | D | sum error = [ 572.7641, 600.1173, 628.4540, 657.8114, 688.2355] +24-11-19 19:31:00 | D | best error = [ 10.5000, 10.5000, 10.5000, 10.5000, 10.5000] +24-11-19 19:31:00 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:31:00 | D | sum error = [ 719.6862, 752.1763, 785.7047, 820.2430, 855.7757] +24-11-19 19:31:00 | D | best error = [ 10.5000, 10.5000, 10.5000, 10.5000, 10.5000] +24-11-19 19:31:00 | D | + error = [10.5000] +24-11-19 19:31:00 | D | - Calibrating model.layers.28.mlp.down_proj.weight +24-11-19 19:31:00 | D | + w: sint8 +24-11-19 19:31:00 | D | + x: None +24-11-19 19:31:00 | D | + y: None +24-11-19 19:31:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:31:00 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:31:00 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:31:00 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:31:00 | D | - range ratio = [ 1.0000] +24-11-19 19:31:00 | D | sum error = [ 5.0248] +24-11-19 19:31:00 | D | best error = [ 5.0248] +24-11-19 19:31:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:31:01 | D | sum error = [ 4.9763, 4.9391, 4.9121, 4.8924, 4.8764] +24-11-19 19:31:01 | D | best error = [ 4.7570, 4.6340, 4.5636, 4.5108, 4.4690] +24-11-19 19:31:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:31:01 | D | sum error = [ 4.8937, 4.9177, 4.9501, 5.0176, 5.1059] +24-11-19 19:31:01 | D | best error = [ 4.4393, 4.4177, 4.4024, 4.3910, 4.3819] +24-11-19 19:31:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:31:01 | D | sum error = [ 5.2137, 5.3504, 5.5049, 5.7102, 5.9411] +24-11-19 19:31:01 | D | best error = [ 4.3776, 4.3736, 4.3711, 4.3698, 4.3689] +24-11-19 19:31:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:31:01 | D | sum error = [ 6.2030, 6.5100, 6.8544, 7.2269, 7.6535] +24-11-19 19:31:01 | D | best error = [ 4.3685, 4.3681, 4.3679, 4.3678, 4.3678] +24-11-19 19:31:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:31:01 | D | sum error = [ 8.1228, 8.6211, 9.1863, 9.7938, 10.4478] +24-11-19 19:31:01 | D | best error = [ 4.3677, 4.3677, 4.3677, 4.3677, 4.3677] +24-11-19 19:31:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:31:01 | D | sum error = [ 11.1622, 11.9210, 12.7450, 13.6054, 14.5566] +24-11-19 19:31:01 | D | best error = [ 4.3677, 4.3677, 4.3677, 4.3677, 4.3677] +24-11-19 19:31:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:31:01 | D | sum error = [ 15.5531, 16.6300, 17.7758, 18.9858, 20.2784] +24-11-19 19:31:01 | D | best error = [ 4.3677, 4.3677, 4.3677, 4.3677, 4.3677] +24-11-19 19:31:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:31:01 | D | sum error = [ 21.6447, 23.0989, 24.6540, 26.2970, 28.0238] +24-11-19 19:31:01 | D | best error = [ 4.3677, 4.3677, 4.3677, 4.3677, 4.3677] +24-11-19 19:31:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:31:01 | D | sum error = [ 29.8565, 31.7906, 33.8474, 36.0100, 38.3160] +24-11-19 19:31:01 | D | best error = [ 4.3677, 4.3677, 4.3677, 4.3677, 4.3677] +24-11-19 19:31:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:31:01 | D | sum error = [ 40.7194, 43.2761, 45.9594, 48.7789, 51.7565] +24-11-19 19:31:01 | D | best error = [ 4.3677, 4.3677, 4.3677, 4.3677, 4.3677] +24-11-19 19:31:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:31:01 | D | sum error = [ 54.8682, 58.1623, 61.6162, 65.2423, 69.0459] +24-11-19 19:31:01 | D | best error = [ 4.3677, 4.3677, 4.3677, 4.3677, 4.3677] +24-11-19 19:31:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:31:01 | D | sum error = [ 73.0375, 77.2279, 81.6092, 86.2058, 91.0163] +24-11-19 19:31:01 | D | best error = [ 4.3677, 4.3677, 4.3677, 4.3677, 4.3677] +24-11-19 19:31:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:31:01 | D | sum error = [ 96.0430, 101.3022, 106.7995, 112.5259, 118.5145] +24-11-19 19:31:01 | D | best error = [ 4.3677, 4.3677, 4.3677, 4.3677, 4.3677] +24-11-19 19:31:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:31:01 | D | sum error = [ 124.7558, 131.2664, 138.0454, 145.1108, 152.4404] +24-11-19 19:31:01 | D | best error = [ 4.3677, 4.3677, 4.3677, 4.3677, 4.3677] +24-11-19 19:31:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:31:01 | D | sum error = [ 160.0728, 168.0038, 176.2401, 184.7870, 193.6524] +24-11-19 19:31:01 | D | best error = [ 4.3677, 4.3677, 4.3677, 4.3677, 4.3677] +24-11-19 19:31:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:31:01 | D | sum error = [ 202.8360, 212.3483, 222.1910, 232.3701, 242.8934] +24-11-19 19:31:01 | D | best error = [ 4.3677, 4.3677, 4.3677, 4.3677, 4.3677] +24-11-19 19:31:01 | D | + error = [4.3677] +24-11-19 19:31:01 | D | - Quantizing model.layers.28.self_attn.q_proj.weight +24-11-19 19:31:02 | D | - Quantizing model.layers.28.self_attn.k_proj.weight +24-11-19 19:31:03 | D | - Quantizing model.layers.28.self_attn.v_proj.weight +24-11-19 19:31:04 | D | - Quantizing model.layers.28.self_attn.o_proj.weight +24-11-19 19:31:05 | D | - Quantizing model.layers.28.mlp.up_proj.weight +24-11-19 19:31:06 | D | - Quantizing model.layers.28.mlp.gate_proj.weight +24-11-19 19:31:07 | D | - Quantizing model.layers.28.mlp.down_proj.weight +24-11-19 19:31:15 | D | - Quantizing layer model.layers.29 +24-11-19 19:31:15 | D | - Calibrating model.layers.29.self_attn.q_proj.weight +24-11-19 19:31:15 | D | + w: sint8 +24-11-19 19:31:15 | D | + x: None +24-11-19 19:31:15 | D | + y: None +24-11-19 19:31:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:31:15 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:31:16 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:31:16 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:31:16 | D | - range ratio = [ 1.0000] +24-11-19 19:31:16 | D | sum error = [ 18.6165] +24-11-19 19:31:16 | D | best error = [ 18.6165] +24-11-19 19:31:28 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:31:28 | D | sum error = [ 18.5951, 18.8088, 18.6813, 18.7585, 19.4048] +24-11-19 19:31:28 | D | best error = [ 18.5951, 18.5951, 18.5951, 18.5951, 18.5951] +24-11-19 19:31:28 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:31:28 | D | sum error = [ 20.0301, 20.8528, 21.0710, 22.5892, 23.7791] +24-11-19 19:31:28 | D | best error = [ 18.5951, 18.5951, 18.5951, 18.5951, 18.5951] +24-11-19 19:31:28 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:31:28 | D | sum error = [ 25.5680, 26.3706, 28.6969, 30.5508, 33.0597] +24-11-19 19:31:28 | D | best error = [ 18.5951, 18.5951, 18.5951, 18.5951, 18.5951] +24-11-19 19:31:28 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:31:28 | D | sum error = [ 35.3452, 38.4375, 41.8081, 44.9222, 48.3913] +24-11-19 19:31:28 | D | best error = [ 18.5951, 18.5951, 18.5951, 18.5951, 18.5951] +24-11-19 19:31:28 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:31:28 | D | sum error = [ 52.3376, 57.1691, 62.2979, 66.8243, 72.6190] +24-11-19 19:31:28 | D | best error = [ 18.5951, 18.5951, 18.5951, 18.5951, 18.5951] +24-11-19 19:31:28 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:31:28 | D | sum error = [ 78.0738, 84.3536, 91.9350, 99.2943, 107.0555] +24-11-19 19:31:28 | D | best error = [ 18.5951, 18.5951, 18.5951, 18.5951, 18.5951] +24-11-19 19:31:28 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:31:28 | D | sum error = [ 115.9609, 125.2336, 134.9892, 146.2418, 156.8527] +24-11-19 19:31:28 | D | best error = [ 18.5951, 18.5951, 18.5951, 18.5951, 18.5951] +24-11-19 19:31:28 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:31:28 | D | sum error = [ 169.3246, 182.5967, 196.7389, 212.2734, 228.7525] +24-11-19 19:31:28 | D | best error = [ 18.5951, 18.5951, 18.5951, 18.5951, 18.5951] +24-11-19 19:31:28 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:31:28 | D | sum error = [ 246.8976, 265.2406, 284.8949, 307.6661, 331.1339] +24-11-19 19:31:28 | D | best error = [ 18.5951, 18.5951, 18.5951, 18.5951, 18.5951] +24-11-19 19:31:28 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:31:28 | D | sum error = [ 357.1162, 383.4967, 412.7330, 443.9128, 476.4416] +24-11-19 19:31:28 | D | best error = [ 18.5951, 18.5951, 18.5951, 18.5951, 18.5951] +24-11-19 19:31:28 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:31:28 | D | sum error = [ 511.2721, 548.9126, 588.8325, 631.3130, 677.6652] +24-11-19 19:31:28 | D | best error = [ 18.5951, 18.5951, 18.5951, 18.5951, 18.5951] +24-11-19 19:31:28 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:31:28 | D | sum error = [ 727.0548, 779.2992, 836.6833, 896.9590, 962.4332] +24-11-19 19:31:28 | D | best error = [ 18.5951, 18.5951, 18.5951, 18.5951, 18.5951] +24-11-19 19:31:28 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:31:28 | D | sum error = [ 1032.7512, 1108.8552, 1190.7679, 1278.7974, 1374.4372] +24-11-19 19:31:28 | D | best error = [ 18.5951, 18.5951, 18.5951, 18.5951, 18.5951] +24-11-19 19:31:28 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:31:28 | D | sum error = [ 1479.5342, 1592.7051, 1715.3177, 1848.8142, 1993.8956] +24-11-19 19:31:28 | D | best error = [ 18.5951, 18.5951, 18.5951, 18.5951, 18.5951] +24-11-19 19:31:28 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:31:28 | D | sum error = [ 2151.0702, 2322.2172, 2506.6586, 2707.6189, 2924.7181] +24-11-19 19:31:28 | D | best error = [ 18.5951, 18.5951, 18.5951, 18.5951, 18.5951] +24-11-19 19:31:28 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:31:28 | D | sum error = [ 3156.4806, 3405.8912, 3676.0038, 3963.0652, 4267.1377] +24-11-19 19:31:28 | D | best error = [ 18.5951, 18.5951, 18.5951, 18.5951, 18.5951] +24-11-19 19:31:28 | D | + error = [18.5951] +24-11-19 19:31:28 | D | - Calibrating model.layers.29.self_attn.k_proj.weight +24-11-19 19:31:28 | D | + w: sint8 +24-11-19 19:31:28 | D | + x: None +24-11-19 19:31:28 | D | + y: None +24-11-19 19:31:28 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:31:28 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:31:29 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:31:29 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:31:29 | D | - range ratio = [ 1.0000] +24-11-19 19:31:29 | D | sum error = [ 22.0098] +24-11-19 19:31:29 | D | best error = [ 22.0098] +24-11-19 19:31:41 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:31:41 | D | sum error = [ 23.0975, 21.5774, 21.8955, 23.3785, 21.5489] +24-11-19 19:31:41 | D | best error = [ 22.0098, 21.5774, 21.5774, 21.5774, 21.5489] +24-11-19 19:31:41 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:31:41 | D | sum error = [ 22.6999, 23.2288, 25.0848, 26.0478, 26.8135] +24-11-19 19:31:41 | D | best error = [ 21.5489, 21.5489, 21.5489, 21.5489, 21.5489] +24-11-19 19:31:41 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:31:41 | D | sum error = [ 28.3918, 30.4718, 31.8457, 34.1714, 38.2494] +24-11-19 19:31:41 | D | best error = [ 21.5489, 21.5489, 21.5489, 21.5489, 21.5489] +24-11-19 19:31:41 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:31:41 | D | sum error = [ 40.2533, 44.8619, 48.5474, 53.0754, 59.6837] +24-11-19 19:31:41 | D | best error = [ 21.5489, 21.5489, 21.5489, 21.5489, 21.5489] +24-11-19 19:31:41 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:31:41 | D | sum error = [ 62.5156, 67.6793, 73.5782, 76.9809, 83.4486] +24-11-19 19:31:41 | D | best error = [ 21.5489, 21.5489, 21.5489, 21.5489, 21.5489] +24-11-19 19:31:41 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:31:41 | D | sum error = [ 89.7640, 99.3693, 103.7953, 111.9060, 119.4963] +24-11-19 19:31:41 | D | best error = [ 21.5489, 21.5489, 21.5489, 21.5489, 21.5489] +24-11-19 19:31:41 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:31:41 | D | sum error = [ 128.5489, 138.4008, 150.0321, 160.9166, 173.4467] +24-11-19 19:31:41 | D | best error = [ 21.5489, 21.5489, 21.5489, 21.5489, 21.5489] +24-11-19 19:31:41 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:31:41 | D | sum error = [ 187.4658, 200.5248, 216.9717, 232.7608, 251.5181] +24-11-19 19:31:41 | D | best error = [ 21.5489, 21.5489, 21.5489, 21.5489, 21.5489] +24-11-19 19:31:41 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:31:41 | D | sum error = [ 269.0968, 287.0654, 303.8107, 328.9386, 347.6940] +24-11-19 19:31:41 | D | best error = [ 21.5489, 21.5489, 21.5489, 21.5489, 21.5489] +24-11-19 19:31:41 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:31:41 | D | sum error = [ 371.3192, 394.8420, 425.2852, 450.3017, 482.0880] +24-11-19 19:31:41 | D | best error = [ 21.5489, 21.5489, 21.5489, 21.5489, 21.5489] +24-11-19 19:31:41 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:31:41 | D | sum error = [ 512.3374, 549.0744, 588.4929, 627.7208, 669.1460] +24-11-19 19:31:41 | D | best error = [ 21.5489, 21.5489, 21.5489, 21.5489, 21.5489] +24-11-19 19:31:41 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:31:41 | D | sum error = [ 709.4834, 762.1266, 819.2005, 874.9980, 937.0556] +24-11-19 19:31:41 | D | best error = [ 21.5489, 21.5489, 21.5489, 21.5489, 21.5489] +24-11-19 19:31:41 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:31:41 | D | sum error = [ 1007.7491, 1077.9018, 1152.8885, 1237.5467, 1329.2052] +24-11-19 19:31:41 | D | best error = [ 21.5489, 21.5489, 21.5489, 21.5489, 21.5489] +24-11-19 19:31:41 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:31:41 | D | sum error = [ 1429.1930, 1525.2110, 1641.7541, 1767.8913, 1903.8713] +24-11-19 19:31:41 | D | best error = [ 21.5489, 21.5489, 21.5489, 21.5489, 21.5489] +24-11-19 19:31:41 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:31:41 | D | sum error = [ 2046.5907, 2203.0331, 2377.4442, 2566.5351, 2767.9717] +24-11-19 19:31:41 | D | best error = [ 21.5489, 21.5489, 21.5489, 21.5489, 21.5489] +24-11-19 19:31:41 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:31:41 | D | sum error = [ 2995.8124, 3240.4677, 3509.2606, 3795.5714, 4101.5587] +24-11-19 19:31:41 | D | best error = [ 21.5489, 21.5489, 21.5489, 21.5489, 21.5489] +24-11-19 19:31:41 | D | + error = [21.5489] +24-11-19 19:31:42 | D | - Calibrating model.layers.29.self_attn.v_proj.weight +24-11-19 19:31:42 | D | + w: sint8 +24-11-19 19:31:42 | D | + x: None +24-11-19 19:31:42 | D | + y: None +24-11-19 19:31:42 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:31:42 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:31:42 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:31:42 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:31:42 | D | - range ratio = [ 1.0000] +24-11-19 19:31:42 | D | sum error = [ 8.9298] +24-11-19 19:31:42 | D | best error = [ 8.9298] +24-11-19 19:31:42 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:31:42 | D | sum error = [ 8.8430, 8.8171, 8.8609, 8.9813, 9.1410] +24-11-19 19:31:42 | D | best error = [ 8.2218, 7.9539, 7.8111, 7.7367, 7.6946] +24-11-19 19:31:42 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:31:42 | D | sum error = [ 9.3804, 9.6648, 10.0279, 10.5653, 11.0972] +24-11-19 19:31:42 | D | best error = [ 7.6744, 7.6648, 7.6624, 7.6609, 7.6607] +24-11-19 19:31:42 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:31:42 | D | sum error = [ 11.7378, 12.4421, 13.2533, 14.1655, 15.1473] +24-11-19 19:31:42 | D | best error = [ 7.6606, 7.6606, 7.6606, 7.6606, 7.6606] +24-11-19 19:31:42 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:31:42 | D | sum error = [ 16.2388, 17.4153, 18.6277, 19.9434, 21.3438] +24-11-19 19:31:42 | D | best error = [ 7.6606, 7.6606, 7.6606, 7.6606, 7.6606] +24-11-19 19:31:42 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:31:42 | D | sum error = [ 22.8226, 24.4788, 26.1956, 27.9890, 29.8986] +24-11-19 19:31:42 | D | best error = [ 7.6606, 7.6606, 7.6606, 7.6606, 7.6606] +24-11-19 19:31:42 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:31:42 | D | sum error = [ 31.9566, 34.1239, 36.3699, 38.8132, 41.4060] +24-11-19 19:31:42 | D | best error = [ 7.6606, 7.6606, 7.6606, 7.6606, 7.6606] +24-11-19 19:31:42 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:31:42 | D | sum error = [ 44.0450, 46.8787, 49.8574, 52.9809, 56.3178] +24-11-19 19:31:42 | D | best error = [ 7.6606, 7.6606, 7.6606, 7.6606, 7.6606] +24-11-19 19:31:42 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:31:42 | D | sum error = [ 59.7743, 63.4692, 67.2627, 71.2838, 75.4948] +24-11-19 19:31:42 | D | best error = [ 7.6606, 7.6606, 7.6606, 7.6606, 7.6606] +24-11-19 19:31:42 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:31:42 | D | sum error = [ 79.9252, 84.5203, 89.3966, 94.5102, 99.7973] +24-11-19 19:31:42 | D | best error = [ 7.6606, 7.6606, 7.6606, 7.6606, 7.6606] +24-11-19 19:31:42 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:31:42 | D | sum error = [ 105.3362, 111.1020, 117.1616, 123.4602, 130.0236] +24-11-19 19:31:42 | D | best error = [ 7.6606, 7.6606, 7.6606, 7.6606, 7.6606] +24-11-19 19:31:42 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:31:42 | D | sum error = [ 136.8522, 143.9927, 151.4015, 159.1098, 167.1378] +24-11-19 19:31:42 | D | best error = [ 7.6606, 7.6606, 7.6606, 7.6606, 7.6606] +24-11-19 19:31:42 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:31:42 | D | sum error = [ 175.4699, 184.1450, 193.1263, 202.3853, 211.9916] +24-11-19 19:31:42 | D | best error = [ 7.6606, 7.6606, 7.6606, 7.6606, 7.6606] +24-11-19 19:31:42 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:31:42 | D | sum error = [ 221.9936, 232.3169, 243.0249, 254.1144, 265.5893] +24-11-19 19:31:42 | D | best error = [ 7.6606, 7.6606, 7.6606, 7.6606, 7.6606] +24-11-19 19:31:42 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:31:42 | D | sum error = [ 277.4577, 289.6893, 302.3276, 315.3776, 328.8160] +24-11-19 19:31:42 | D | best error = [ 7.6606, 7.6606, 7.6606, 7.6606, 7.6606] +24-11-19 19:31:42 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:31:42 | D | sum error = [ 342.6769, 356.9381, 371.6930, 386.8499, 402.4431] +24-11-19 19:31:42 | D | best error = [ 7.6606, 7.6606, 7.6606, 7.6606, 7.6606] +24-11-19 19:31:42 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:31:42 | D | sum error = [ 418.4816, 434.9785, 451.9332, 469.3350, 487.2005] +24-11-19 19:31:42 | D | best error = [ 7.6606, 7.6606, 7.6606, 7.6606, 7.6606] +24-11-19 19:31:42 | D | + error = [7.6606] +24-11-19 19:31:42 | D | - Calibrating model.layers.29.self_attn.o_proj.weight +24-11-19 19:31:42 | D | + w: sint8 +24-11-19 19:31:42 | D | + x: None +24-11-19 19:31:42 | D | + y: None +24-11-19 19:31:42 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:31:42 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:31:42 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:31:42 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:31:42 | D | - range ratio = [ 1.0000] +24-11-19 19:31:42 | D | sum error = [ 2.0423] +24-11-19 19:31:42 | D | best error = [ 2.0423] +24-11-19 19:31:43 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:31:43 | D | sum error = [ 2.0304, 2.0284, 2.0450, 2.0709, 2.1252] +24-11-19 19:31:43 | D | best error = [ 1.9217, 1.8661, 1.8334, 1.8138, 1.8035] +24-11-19 19:31:43 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:31:43 | D | sum error = [ 2.1947, 2.2771, 2.3878, 2.5031, 2.6594] +24-11-19 19:31:43 | D | best error = [ 1.7960, 1.7915, 1.7889, 1.7866, 1.7853] +24-11-19 19:31:43 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:31:43 | D | sum error = [ 2.8231, 2.9977, 3.2021, 3.4220, 3.6672] +24-11-19 19:31:43 | D | best error = [ 1.7843, 1.7836, 1.7833, 1.7829, 1.7827] +24-11-19 19:31:43 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:31:43 | D | sum error = [ 3.9407, 4.2192, 4.5198, 4.8425, 5.1797] +24-11-19 19:31:43 | D | best error = [ 1.7826, 1.7826, 1.7825, 1.7825, 1.7825] +24-11-19 19:31:43 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:31:43 | D | sum error = [ 5.5556, 5.9385, 6.3600, 6.7879, 7.2523] +24-11-19 19:31:43 | D | best error = [ 1.7825, 1.7825, 1.7824, 1.7824, 1.7824] +24-11-19 19:31:43 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:31:43 | D | sum error = [ 7.7446, 8.2565, 8.8158, 9.3740, 9.9848] +24-11-19 19:31:43 | D | best error = [ 1.7824, 1.7824, 1.7824, 1.7824, 1.7824] +24-11-19 19:31:43 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:31:43 | D | sum error = [ 10.6184, 11.2994, 12.0023, 12.7470, 13.5374] +24-11-19 19:31:43 | D | best error = [ 1.7824, 1.7824, 1.7824, 1.7824, 1.7824] +24-11-19 19:31:43 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:31:43 | D | sum error = [ 14.3677, 15.2406, 16.1550, 17.1274, 18.1365] +24-11-19 19:31:43 | D | best error = [ 1.7824, 1.7824, 1.7824, 1.7824, 1.7824] +24-11-19 19:31:43 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:31:43 | D | sum error = [ 19.2023, 20.3194, 21.4983, 22.7302, 24.0271] +24-11-19 19:31:43 | D | best error = [ 1.7824, 1.7824, 1.7824, 1.7824, 1.7824] +24-11-19 19:31:43 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:31:43 | D | sum error = [ 25.3903, 26.8121, 28.3007, 29.8685, 31.5102] +24-11-19 19:31:43 | D | best error = [ 1.7824, 1.7824, 1.7824, 1.7824, 1.7824] +24-11-19 19:31:43 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:31:43 | D | sum error = [ 33.2322, 35.0325, 36.9132, 38.8941, 40.9498] +24-11-19 19:31:43 | D | best error = [ 1.7824, 1.7824, 1.7824, 1.7824, 1.7824] +24-11-19 19:31:43 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:31:43 | D | sum error = [ 43.1037, 45.3508, 47.6990, 50.1569, 52.7201] +24-11-19 19:31:43 | D | best error = [ 1.7824, 1.7824, 1.7824, 1.7824, 1.7824] +24-11-19 19:31:43 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:31:43 | D | sum error = [ 55.3828, 58.1605, 61.0537, 64.0643, 67.1987] +24-11-19 19:31:43 | D | best error = [ 1.7824, 1.7824, 1.7824, 1.7824, 1.7824] +24-11-19 19:31:43 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:31:43 | D | sum error = [ 70.4607, 73.8609, 77.3896, 81.0645, 84.8700] +24-11-19 19:31:43 | D | best error = [ 1.7824, 1.7824, 1.7824, 1.7824, 1.7824] +24-11-19 19:31:43 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:31:43 | D | sum error = [ 88.8244, 92.9191, 97.1628, 101.5536, 106.1038] +24-11-19 19:31:43 | D | best error = [ 1.7824, 1.7824, 1.7824, 1.7824, 1.7824] +24-11-19 19:31:43 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:31:43 | D | sum error = [ 110.8081, 115.6735, 120.6980, 125.8793, 131.2258] +24-11-19 19:31:43 | D | best error = [ 1.7824, 1.7824, 1.7824, 1.7824, 1.7824] +24-11-19 19:31:43 | D | + error = [1.7824] +24-11-19 19:31:43 | D | - Calibrating model.layers.29.mlp.up_proj.weight +24-11-19 19:31:43 | D | + w: sint8 +24-11-19 19:31:43 | D | + x: None +24-11-19 19:31:43 | D | + y: None +24-11-19 19:31:43 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:31:43 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:31:43 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:31:43 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:31:43 | D | - range ratio = [ 1.0000] +24-11-19 19:31:43 | D | sum error = [ 12.0016] +24-11-19 19:31:43 | D | best error = [ 12.0016] +24-11-19 19:31:44 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:31:44 | D | sum error = [ 11.9177, 11.8740, 11.9717, 12.0802, 12.3130] +24-11-19 19:31:44 | D | best error = [ 10.9815, 10.6100, 10.4214, 10.3156, 10.2544] +24-11-19 19:31:44 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:31:44 | D | sum error = [ 12.6099, 13.0408, 13.5658, 14.2109, 14.9813] +24-11-19 19:31:44 | D | best error = [ 10.2256, 10.2118, 10.2058, 10.2042, 10.2035] +24-11-19 19:31:44 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:31:44 | D | sum error = [ 15.8366, 16.7995, 17.9158, 19.1457, 20.4468] +24-11-19 19:31:44 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 19:31:44 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:31:44 | D | sum error = [ 21.8670, 23.4375, 25.1409, 26.9108, 28.8532] +24-11-19 19:31:44 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 19:31:44 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:31:44 | D | sum error = [ 30.9377, 33.1493, 35.4658, 37.9385, 40.5992] +24-11-19 19:31:44 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 19:31:44 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:31:44 | D | sum error = [ 43.4071, 46.3439, 49.5862, 52.8542, 56.4132] +24-11-19 19:31:44 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 19:31:44 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:31:44 | D | sum error = [ 60.1633, 64.1052, 68.3473, 72.7426, 77.4481] +24-11-19 19:31:44 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 19:31:44 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:31:44 | D | sum error = [ 82.3635, 87.5969, 93.0828, 98.8568, 104.9262] +24-11-19 19:31:44 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 19:31:44 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:31:44 | D | sum error = [ 111.3531, 118.0712, 125.1966, 132.6840, 140.5808] +24-11-19 19:31:44 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 19:31:44 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:31:44 | D | sum error = [ 148.8445, 157.6361, 166.7912, 176.4213, 186.4641] +24-11-19 19:31:44 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 19:31:44 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:31:44 | D | sum error = [ 197.0897, 208.1911, 219.7915, 232.0197, 244.8284] +24-11-19 19:31:44 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 19:31:44 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:31:44 | D | sum error = [ 258.1975, 272.2246, 286.8483, 302.1780, 318.2409] +24-11-19 19:31:44 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 19:31:44 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:31:44 | D | sum error = [ 334.8983, 352.3161, 370.5325, 389.5056, 409.2264] +24-11-19 19:31:44 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 19:31:44 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:31:44 | D | sum error = [ 429.7875, 451.1891, 473.3847, 496.4039, 520.2932] +24-11-19 19:31:44 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 19:31:44 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:31:44 | D | sum error = [ 545.1478, 570.8294, 597.4286, 624.9714, 653.5071] +24-11-19 19:31:44 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 19:31:44 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:31:44 | D | sum error = [ 682.9235, 713.2853, 744.6061, 776.9288, 810.2242] +24-11-19 19:31:44 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 19:31:44 | D | + error = [10.2035] +24-11-19 19:31:44 | D | - Calibrating model.layers.29.mlp.gate_proj.weight +24-11-19 19:31:44 | D | + w: sint8 +24-11-19 19:31:44 | D | + x: None +24-11-19 19:31:44 | D | + y: None +24-11-19 19:31:44 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:31:44 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:31:44 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:31:44 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:31:44 | D | - range ratio = [ 1.0000] +24-11-19 19:31:44 | D | sum error = [ 12.5810] +24-11-19 19:31:44 | D | best error = [ 12.5810] +24-11-19 19:31:45 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:31:45 | D | sum error = [ 12.4596, 12.4589, 12.4843, 12.6734, 12.9045] +24-11-19 19:31:45 | D | best error = [ 11.5091, 11.1216, 10.9155, 10.8043, 10.7426] +24-11-19 19:31:45 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:31:45 | D | sum error = [ 13.2261, 13.6934, 14.2553, 14.8514, 15.7029] +24-11-19 19:31:45 | D | best error = [ 10.7124, 10.6976, 10.6925, 10.6909, 10.6906] +24-11-19 19:31:45 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:31:45 | D | sum error = [ 16.6672, 17.6758, 18.8308, 20.0791, 21.5188] +24-11-19 19:31:45 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 19:31:45 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:31:45 | D | sum error = [ 23.0483, 24.6954, 26.5319, 28.3987, 30.4923] +24-11-19 19:31:45 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 19:31:45 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:31:45 | D | sum error = [ 32.6783, 35.0842, 37.5537, 40.2973, 43.0551] +24-11-19 19:31:45 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 19:31:45 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:31:45 | D | sum error = [ 46.1192, 49.3478, 52.7251, 56.3491, 60.1042] +24-11-19 19:31:45 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 19:31:45 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:31:45 | D | sum error = [ 64.1692, 68.4320, 72.9636, 77.6768, 82.7224] +24-11-19 19:31:45 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 19:31:45 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:31:45 | D | sum error = [ 88.0705, 93.6791, 99.6452, 105.8947, 112.5248] +24-11-19 19:31:45 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 19:31:45 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:31:45 | D | sum error = [ 119.5115, 126.8593, 134.6111, 142.7919, 151.3726] +24-11-19 19:31:45 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 19:31:45 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:31:45 | D | sum error = [ 160.4420, 169.9621, 180.0184, 190.5207, 201.6648] +24-11-19 19:31:45 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 19:31:45 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:31:45 | D | sum error = [ 213.3232, 225.5498, 238.4417, 251.9414, 266.1259] +24-11-19 19:31:45 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 19:31:45 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:31:45 | D | sum error = [ 280.9441, 296.4272, 312.6838, 329.7270, 347.4896] +24-11-19 19:31:45 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 19:31:45 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:31:45 | D | sum error = [ 366.0918, 385.5125, 405.7771, 426.9479, 449.0079] +24-11-19 19:31:45 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 19:31:45 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:31:45 | D | sum error = [ 472.0217, 495.9489, 520.8416, 546.7601, 573.6207] +24-11-19 19:31:45 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 19:31:45 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:31:45 | D | sum error = [ 601.5028, 630.4383, 660.3661, 691.3596, 723.4399] +24-11-19 19:31:45 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 19:31:45 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:31:45 | D | sum error = [ 756.5239, 790.7638, 826.0404, 862.3939, 899.7872] +24-11-19 19:31:45 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 19:31:45 | D | + error = [10.6905] +24-11-19 19:31:45 | D | - Calibrating model.layers.29.mlp.down_proj.weight +24-11-19 19:31:45 | D | + w: sint8 +24-11-19 19:31:45 | D | + x: None +24-11-19 19:31:45 | D | + y: None +24-11-19 19:31:45 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:31:45 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:31:45 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:31:46 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:31:46 | D | - range ratio = [ 1.0000] +24-11-19 19:31:46 | D | sum error = [ 5.7945] +24-11-19 19:31:46 | D | best error = [ 5.7945] +24-11-19 19:31:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:31:47 | D | sum error = [ 5.8180, 6.0093, 6.3348, 6.8262, 7.4210] +24-11-19 19:31:47 | D | best error = [ 5.4535, 5.3265, 5.2432, 5.1866, 5.1410] +24-11-19 19:31:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:31:47 | D | sum error = [ 8.1027, 8.8831, 9.7038, 10.5909, 11.5101] +24-11-19 19:31:47 | D | best error = [ 5.1055, 5.0817, 5.0638, 5.0491, 5.0378] +24-11-19 19:31:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:31:47 | D | sum error = [ 12.4870, 13.4806, 14.5143, 15.5763, 16.6735] +24-11-19 19:31:47 | D | best error = [ 5.0305, 5.0250, 5.0218, 5.0197, 5.0183] +24-11-19 19:31:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:31:47 | D | sum error = [ 17.7971, 18.9368, 20.1158, 21.3317, 22.5597] +24-11-19 19:31:47 | D | best error = [ 5.0173, 5.0170, 5.0167, 5.0164, 5.0163] +24-11-19 19:31:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:31:47 | D | sum error = [ 23.8143, 25.1172, 26.4383, 27.7991, 29.1965] +24-11-19 19:31:47 | D | best error = [ 5.0163, 5.0162, 5.0162, 5.0162, 5.0162] +24-11-19 19:31:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:31:47 | D | sum error = [ 30.6215, 32.0952, 33.6031, 35.1576, 36.7574] +24-11-19 19:31:47 | D | best error = [ 5.0162, 5.0162, 5.0162, 5.0162, 5.0162] +24-11-19 19:31:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:31:47 | D | sum error = [ 38.3985, 40.0852, 41.8267, 43.6327, 45.4780] +24-11-19 19:31:47 | D | best error = [ 5.0162, 5.0162, 5.0162, 5.0162, 5.0162] +24-11-19 19:31:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:31:47 | D | sum error = [ 47.3944, 49.3831, 51.4456, 53.5730, 55.7831] +24-11-19 19:31:47 | D | best error = [ 5.0162, 5.0162, 5.0162, 5.0162, 5.0162] +24-11-19 19:31:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:31:47 | D | sum error = [ 58.0744, 60.4622, 62.9472, 65.5249, 68.2151] +24-11-19 19:31:47 | D | best error = [ 5.0162, 5.0162, 5.0162, 5.0162, 5.0162] +24-11-19 19:31:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:31:47 | D | sum error = [ 71.0083, 73.9285, 76.9713, 80.1460, 83.4569] +24-11-19 19:31:47 | D | best error = [ 5.0162, 5.0162, 5.0162, 5.0162, 5.0162] +24-11-19 19:31:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:31:47 | D | sum error = [ 86.9209, 90.5427, 94.3185, 98.2635, 102.3898] +24-11-19 19:31:47 | D | best error = [ 5.0162, 5.0162, 5.0162, 5.0162, 5.0162] +24-11-19 19:31:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:31:47 | D | sum error = [ 106.7103, 111.2312, 115.9495, 120.8892, 126.0553] +24-11-19 19:31:47 | D | best error = [ 5.0162, 5.0162, 5.0162, 5.0162, 5.0162] +24-11-19 19:31:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:31:47 | D | sum error = [ 131.4622, 137.1161, 143.0278, 149.2056, 155.6645] +24-11-19 19:31:47 | D | best error = [ 5.0162, 5.0162, 5.0162, 5.0162, 5.0162] +24-11-19 19:31:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:31:47 | D | sum error = [ 162.4069, 169.4528, 176.7824, 184.4590, 192.4311] +24-11-19 19:31:47 | D | best error = [ 5.0162, 5.0162, 5.0162, 5.0162, 5.0162] +24-11-19 19:31:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:31:47 | D | sum error = [ 200.7360, 209.3867, 218.3908, 227.7731, 237.5284] +24-11-19 19:31:47 | D | best error = [ 5.0162, 5.0162, 5.0162, 5.0162, 5.0162] +24-11-19 19:31:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:31:47 | D | sum error = [ 247.6602, 258.1862, 269.1225, 280.4540, 292.2007] +24-11-19 19:31:47 | D | best error = [ 5.0162, 5.0162, 5.0162, 5.0162, 5.0162] +24-11-19 19:31:47 | D | + error = [5.0162] +24-11-19 19:31:47 | D | - Quantizing model.layers.29.self_attn.q_proj.weight +24-11-19 19:31:48 | D | - Quantizing model.layers.29.self_attn.k_proj.weight +24-11-19 19:31:48 | D | - Quantizing model.layers.29.self_attn.v_proj.weight +24-11-19 19:31:49 | D | - Quantizing model.layers.29.self_attn.o_proj.weight +24-11-19 19:31:50 | D | - Quantizing model.layers.29.mlp.up_proj.weight +24-11-19 19:31:51 | D | - Quantizing model.layers.29.mlp.gate_proj.weight +24-11-19 19:31:52 | D | - Quantizing model.layers.29.mlp.down_proj.weight +24-11-19 19:32:00 | D | - Quantizing layer model.layers.30 +24-11-19 19:32:00 | D | - Calibrating model.layers.30.self_attn.q_proj.weight +24-11-19 19:32:00 | D | + w: sint8 +24-11-19 19:32:00 | D | + x: None +24-11-19 19:32:00 | D | + y: None +24-11-19 19:32:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:32:00 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:32:01 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:32:01 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:32:01 | D | - range ratio = [ 1.0000] +24-11-19 19:32:01 | D | sum error = [ 18.3175] +24-11-19 19:32:01 | D | best error = [ 18.3175] +24-11-19 19:32:14 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:32:14 | D | sum error = [ 18.7475, 18.1989, 18.5641, 19.7136, 19.5517] +24-11-19 19:32:14 | D | best error = [ 18.3175, 18.1989, 18.1989, 18.1989, 18.1989] +24-11-19 19:32:14 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:32:14 | D | sum error = [ 20.0738, 20.4857, 21.9983, 22.4350, 24.0976] +24-11-19 19:32:14 | D | best error = [ 18.1989, 18.1989, 18.1989, 18.1989, 18.1989] +24-11-19 19:32:14 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:32:14 | D | sum error = [ 25.0164, 26.9178, 29.9856, 30.8491, 32.6854] +24-11-19 19:32:14 | D | best error = [ 18.1989, 18.1989, 18.1989, 18.1989, 18.1989] +24-11-19 19:32:14 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:32:14 | D | sum error = [ 35.4656, 38.8436, 41.0038, 44.1377, 47.4779] +24-11-19 19:32:14 | D | best error = [ 18.1989, 18.1989, 18.1989, 18.1989, 18.1989] +24-11-19 19:32:14 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:32:14 | D | sum error = [ 51.4422, 55.8757, 60.1481, 64.8391, 70.6427] +24-11-19 19:32:14 | D | best error = [ 18.1989, 18.1989, 18.1989, 18.1989, 18.1989] +24-11-19 19:32:14 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:32:14 | D | sum error = [ 76.3982, 81.9126, 89.3878, 95.4566, 104.0701] +24-11-19 19:32:14 | D | best error = [ 18.1989, 18.1989, 18.1989, 18.1989, 18.1989] +24-11-19 19:32:14 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:32:14 | D | sum error = [ 112.6034, 121.8275, 131.5228, 142.5998, 154.4491] +24-11-19 19:32:14 | D | best error = [ 18.1989, 18.1989, 18.1989, 18.1989, 18.1989] +24-11-19 19:32:14 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:32:14 | D | sum error = [ 166.2196, 178.5074, 193.4313, 210.7175, 228.0068] +24-11-19 19:32:14 | D | best error = [ 18.1989, 18.1989, 18.1989, 18.1989, 18.1989] +24-11-19 19:32:14 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:32:14 | D | sum error = [ 245.5100, 266.2241, 288.0192, 311.4579, 336.4766] +24-11-19 19:32:14 | D | best error = [ 18.1989, 18.1989, 18.1989, 18.1989, 18.1989] +24-11-19 19:32:14 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:32:14 | D | sum error = [ 362.5192, 392.1248, 423.4866, 457.3514, 494.3738] +24-11-19 19:32:14 | D | best error = [ 18.1989, 18.1989, 18.1989, 18.1989, 18.1989] +24-11-19 19:32:14 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:32:14 | D | sum error = [ 534.7060, 579.3625, 625.3464, 677.0015, 732.6956] +24-11-19 19:32:14 | D | best error = [ 18.1989, 18.1989, 18.1989, 18.1989, 18.1989] +24-11-19 19:32:14 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:32:14 | D | sum error = [ 792.0602, 857.8837, 928.3258, 1004.8679, 1087.9523] +24-11-19 19:32:14 | D | best error = [ 18.1989, 18.1989, 18.1989, 18.1989, 18.1989] +24-11-19 19:32:14 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:32:14 | D | sum error = [ 1178.2651, 1275.0171, 1380.2717, 1494.5867, 1619.9889] +24-11-19 19:32:14 | D | best error = [ 18.1989, 18.1989, 18.1989, 18.1989, 18.1989] +24-11-19 19:32:14 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:32:14 | D | sum error = [ 1756.5337, 1904.9714, 2068.9560, 2247.7445, 2444.0171] +24-11-19 19:32:14 | D | best error = [ 18.1989, 18.1989, 18.1989, 18.1989, 18.1989] +24-11-19 19:32:14 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:32:14 | D | sum error = [ 2658.5855, 2890.6427, 3147.5649, 3428.8297, 3736.0248] +24-11-19 19:32:14 | D | best error = [ 18.1989, 18.1989, 18.1989, 18.1989, 18.1989] +24-11-19 19:32:14 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:32:14 | D | sum error = [ 4070.0791, 4434.7764, 4831.7877, 5258.6764, 5719.0604] +24-11-19 19:32:14 | D | best error = [ 18.1989, 18.1989, 18.1989, 18.1989, 18.1989] +24-11-19 19:32:14 | D | + error = [18.1989] +24-11-19 19:32:14 | D | - Calibrating model.layers.30.self_attn.k_proj.weight +24-11-19 19:32:14 | D | + w: sint8 +24-11-19 19:32:14 | D | + x: None +24-11-19 19:32:14 | D | + y: None +24-11-19 19:32:14 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:32:14 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:32:14 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:32:14 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:32:14 | D | - range ratio = [ 1.0000] +24-11-19 19:32:14 | D | sum error = [ 21.4844] +24-11-19 19:32:14 | D | best error = [ 21.4844] +24-11-19 19:32:27 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:32:27 | D | sum error = [ 21.6210, 22.2755, 22.2144, 23.7119, 23.6576] +24-11-19 19:32:27 | D | best error = [ 21.4844, 21.4844, 21.4844, 21.4844, 21.4844] +24-11-19 19:32:27 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:32:27 | D | sum error = [ 23.4193, 24.3436, 25.3987, 26.2141, 31.8614] +24-11-19 19:32:27 | D | best error = [ 21.4844, 21.4844, 21.4844, 21.4844, 21.4844] +24-11-19 19:32:27 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:32:27 | D | sum error = [ 29.8080, 33.9342, 34.1835, 38.2642, 42.9277] +24-11-19 19:32:27 | D | best error = [ 21.4844, 21.4844, 21.4844, 21.4844, 21.4844] +24-11-19 19:32:27 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:32:27 | D | sum error = [ 42.7558, 45.1582, 51.0906, 52.4995, 57.3349] +24-11-19 19:32:27 | D | best error = [ 21.4844, 21.4844, 21.4844, 21.4844, 21.4844] +24-11-19 19:32:27 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:32:27 | D | sum error = [ 59.4642, 67.5574, 71.5434, 76.1925, 80.3587] +24-11-19 19:32:27 | D | best error = [ 21.4844, 21.4844, 21.4844, 21.4844, 21.4844] +24-11-19 19:32:27 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:32:27 | D | sum error = [ 87.8129, 96.0067, 104.2224, 111.3450, 119.7413] +24-11-19 19:32:27 | D | best error = [ 21.4844, 21.4844, 21.4844, 21.4844, 21.4844] +24-11-19 19:32:27 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:32:27 | D | sum error = [ 130.6227, 141.3135, 150.1254, 161.0511, 173.6893] +24-11-19 19:32:27 | D | best error = [ 21.4844, 21.4844, 21.4844, 21.4844, 21.4844] +24-11-19 19:32:27 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:32:27 | D | sum error = [ 186.8773, 200.8058, 214.2091, 231.9590, 248.4278] +24-11-19 19:32:27 | D | best error = [ 21.4844, 21.4844, 21.4844, 21.4844, 21.4844] +24-11-19 19:32:27 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:32:27 | D | sum error = [ 268.0322, 289.6467, 310.7310, 335.1951, 361.0323] +24-11-19 19:32:27 | D | best error = [ 21.4844, 21.4844, 21.4844, 21.4844, 21.4844] +24-11-19 19:32:27 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:32:27 | D | sum error = [ 387.3741, 418.9634, 453.6218, 485.6783, 526.1023] +24-11-19 19:32:27 | D | best error = [ 21.4844, 21.4844, 21.4844, 21.4844, 21.4844] +24-11-19 19:32:27 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:32:27 | D | sum error = [ 564.6960, 606.2791, 653.4186, 707.8430, 764.2435] +24-11-19 19:32:27 | D | best error = [ 21.4844, 21.4844, 21.4844, 21.4844, 21.4844] +24-11-19 19:32:27 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:32:27 | D | sum error = [ 822.6199, 887.9714, 958.9391, 1033.8171, 1112.6663] +24-11-19 19:32:27 | D | best error = [ 21.4844, 21.4844, 21.4844, 21.4844, 21.4844] +24-11-19 19:32:27 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:32:27 | D | sum error = [ 1204.0288, 1299.2077, 1393.6028, 1507.5910, 1619.8864] +24-11-19 19:32:27 | D | best error = [ 21.4844, 21.4844, 21.4844, 21.4844, 21.4844] +24-11-19 19:32:27 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:32:27 | D | sum error = [ 1760.0343, 1916.7944, 2066.5205, 2243.9001, 2429.6757] +24-11-19 19:32:27 | D | best error = [ 21.4844, 21.4844, 21.4844, 21.4844, 21.4844] +24-11-19 19:32:27 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:32:27 | D | sum error = [ 2628.1056, 2856.9252, 3090.9290, 3356.3510, 3648.7664] +24-11-19 19:32:27 | D | best error = [ 21.4844, 21.4844, 21.4844, 21.4844, 21.4844] +24-11-19 19:32:27 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:32:27 | D | sum error = [ 3944.6860, 4278.8248, 4642.2271, 5034.4064, 5460.2579] +24-11-19 19:32:27 | D | best error = [ 21.4844, 21.4844, 21.4844, 21.4844, 21.4844] +24-11-19 19:32:27 | D | + error = [21.4844] +24-11-19 19:32:27 | D | - Calibrating model.layers.30.self_attn.v_proj.weight +24-11-19 19:32:27 | D | + w: sint8 +24-11-19 19:32:27 | D | + x: None +24-11-19 19:32:27 | D | + y: None +24-11-19 19:32:27 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:32:27 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:32:27 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:32:27 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:32:27 | D | - range ratio = [ 1.0000] +24-11-19 19:32:27 | D | sum error = [ 9.5458] +24-11-19 19:32:27 | D | best error = [ 9.5458] +24-11-19 19:32:28 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:32:28 | D | sum error = [ 9.4702, 9.4380, 9.5000, 9.5575, 9.7636] +24-11-19 19:32:28 | D | best error = [ 8.7482, 8.4664, 8.3197, 8.2334, 8.1870] +24-11-19 19:32:28 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:32:28 | D | sum error = [ 10.0507, 10.3481, 10.7469, 11.2845, 11.8348] +24-11-19 19:32:28 | D | best error = [ 8.1664, 8.1561, 8.1528, 8.1519, 8.1518] +24-11-19 19:32:28 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:32:28 | D | sum error = [ 12.5300, 13.2980, 14.1313, 15.1043, 16.1399] +24-11-19 19:32:28 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 19:32:28 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:32:28 | D | sum error = [ 17.2535, 18.4395, 19.7515, 21.1641, 22.6934] +24-11-19 19:32:28 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 19:32:28 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:32:28 | D | sum error = [ 24.2956, 25.9901, 27.7821, 29.7244, 31.7998] +24-11-19 19:32:28 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 19:32:28 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:32:28 | D | sum error = [ 34.0006, 36.2800, 38.7415, 41.2802, 43.9635] +24-11-19 19:32:28 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 19:32:28 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:32:28 | D | sum error = [ 46.8257, 49.9096, 53.1170, 56.4660, 59.9707] +24-11-19 19:32:28 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 19:32:28 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:32:28 | D | sum error = [ 63.7422, 67.6544, 71.7303, 76.0516, 80.5501] +24-11-19 19:32:28 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 19:32:28 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:32:28 | D | sum error = [ 85.2360, 90.1959, 95.3682, 100.7918, 106.4842] +24-11-19 19:32:28 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 19:32:28 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:32:28 | D | sum error = [ 112.4325, 118.5880, 125.0927, 131.8876, 138.9841] +24-11-19 19:32:28 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 19:32:28 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:32:28 | D | sum error = [ 146.3605, 154.0476, 162.0888, 170.4678, 179.1706] +24-11-19 19:32:28 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 19:32:28 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:32:28 | D | sum error = [ 188.2525, 197.6966, 207.5106, 217.6978, 228.2823] +24-11-19 19:32:28 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 19:32:28 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:32:28 | D | sum error = [ 239.2719, 250.7131, 262.5388, 274.7980, 287.4824] +24-11-19 19:32:28 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 19:32:28 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:32:28 | D | sum error = [ 300.6032, 314.1689, 328.2185, 342.7215, 357.7000] +24-11-19 19:32:28 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 19:32:28 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:32:28 | D | sum error = [ 373.1789, 389.0885, 405.4824, 422.3672, 439.7411] +24-11-19 19:32:28 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 19:32:28 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:32:28 | D | sum error = [ 457.6245, 476.0235, 494.9597, 514.4400, 534.4480] +24-11-19 19:32:28 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 19:32:28 | D | + error = [8.1517] +24-11-19 19:32:28 | D | - Calibrating model.layers.30.self_attn.o_proj.weight +24-11-19 19:32:28 | D | + w: sint8 +24-11-19 19:32:28 | D | + x: None +24-11-19 19:32:28 | D | + y: None +24-11-19 19:32:28 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:32:28 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:32:28 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:32:28 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:32:28 | D | - range ratio = [ 1.0000] +24-11-19 19:32:28 | D | sum error = [ 2.6059] +24-11-19 19:32:28 | D | best error = [ 2.6059] +24-11-19 19:32:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:32:29 | D | sum error = [ 2.5897, 2.5788, 2.5842, 2.6157, 2.6579] +24-11-19 19:32:29 | D | best error = [ 2.4311, 2.3504, 2.3035, 2.2755, 2.2551] +24-11-19 19:32:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:32:29 | D | sum error = [ 2.7085, 2.7931, 2.8915, 3.0153, 3.1566] +24-11-19 19:32:29 | D | best error = [ 2.2411, 2.2317, 2.2244, 2.2196, 2.2160] +24-11-19 19:32:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:32:29 | D | sum error = [ 3.3317, 3.5236, 3.7422, 3.9751, 4.2398] +24-11-19 19:32:29 | D | best error = [ 2.2131, 2.2104, 2.2089, 2.2077, 2.2066] +24-11-19 19:32:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:32:29 | D | sum error = [ 4.5237, 4.8439, 5.1821, 5.5371, 5.9336] +24-11-19 19:32:29 | D | best error = [ 2.2057, 2.2052, 2.2047, 2.2042, 2.2040] +24-11-19 19:32:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:32:29 | D | sum error = [ 6.3414, 6.7894, 7.2715, 7.7738, 8.3060] +24-11-19 19:32:29 | D | best error = [ 2.2039, 2.2038, 2.2038, 2.2038, 2.2036] +24-11-19 19:32:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:32:29 | D | sum error = [ 8.8682, 9.4670, 10.1189, 10.7966, 11.5119] +24-11-19 19:32:29 | D | best error = [ 2.2036, 2.2035, 2.2034, 2.2034, 2.2034] +24-11-19 19:32:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:32:29 | D | sum error = [ 12.2755, 13.0859, 13.9241, 14.8136, 15.7778] +24-11-19 19:32:29 | D | best error = [ 2.2034, 2.2034, 2.2034, 2.2034, 2.2034] +24-11-19 19:32:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:32:29 | D | sum error = [ 16.7846, 17.8420, 18.9660, 20.1400, 21.4056] +24-11-19 19:32:29 | D | best error = [ 2.2034, 2.2034, 2.2034, 2.2034, 2.2034] +24-11-19 19:32:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:32:29 | D | sum error = [ 22.7313, 24.1183, 25.5979, 27.1601, 28.7960] +24-11-19 19:32:29 | D | best error = [ 2.2034, 2.2034, 2.2034, 2.2034, 2.2034] +24-11-19 19:32:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:32:29 | D | sum error = [ 30.5250, 32.3512, 34.2712, 36.2932, 38.4180] +24-11-19 19:32:29 | D | best error = [ 2.2034, 2.2034, 2.2034, 2.2034, 2.2034] +24-11-19 19:32:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:32:29 | D | sum error = [ 40.6532, 42.9959, 45.4615, 48.0470, 50.7794] +24-11-19 19:32:29 | D | best error = [ 2.2034, 2.2034, 2.2034, 2.2034, 2.2034] +24-11-19 19:32:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:32:29 | D | sum error = [ 53.6368, 56.6342, 59.7740, 63.0699, 66.5163] +24-11-19 19:32:29 | D | best error = [ 2.2034, 2.2034, 2.2034, 2.2034, 2.2034] +24-11-19 19:32:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:32:29 | D | sum error = [ 70.1220, 73.8991, 77.8319, 81.9449, 86.2388] +24-11-19 19:32:29 | D | best error = [ 2.2034, 2.2034, 2.2034, 2.2034, 2.2034] +24-11-19 19:32:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:32:29 | D | sum error = [ 90.7111, 95.3788, 100.2417, 105.3168, 110.5839] +24-11-19 19:32:29 | D | best error = [ 2.2034, 2.2034, 2.2034, 2.2034, 2.2034] +24-11-19 19:32:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:32:29 | D | sum error = [ 116.0699, 121.7613, 127.6648, 133.7816, 140.1284] +24-11-19 19:32:29 | D | best error = [ 2.2034, 2.2034, 2.2034, 2.2034, 2.2034] +24-11-19 19:32:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:32:29 | D | sum error = [ 146.6965, 153.4942, 160.5192, 167.7633, 175.2448] +24-11-19 19:32:29 | D | best error = [ 2.2034, 2.2034, 2.2034, 2.2034, 2.2034] +24-11-19 19:32:29 | D | + error = [2.2034] +24-11-19 19:32:29 | D | - Calibrating model.layers.30.mlp.up_proj.weight +24-11-19 19:32:29 | D | + w: sint8 +24-11-19 19:32:29 | D | + x: None +24-11-19 19:32:29 | D | + y: None +24-11-19 19:32:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:32:29 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:32:29 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:32:29 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:32:29 | D | - range ratio = [ 1.0000] +24-11-19 19:32:29 | D | sum error = [ 12.3273] +24-11-19 19:32:29 | D | best error = [ 12.3273] +24-11-19 19:32:30 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:32:30 | D | sum error = [ 12.3244, 12.1790, 12.2749, 12.3696, 12.6244] +24-11-19 19:32:30 | D | best error = [ 11.2631, 10.8309, 10.6306, 10.4989, 10.4399] +24-11-19 19:32:30 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:32:30 | D | sum error = [ 12.9395, 13.3326, 13.9026, 14.5357, 15.3072] +24-11-19 19:32:30 | D | best error = [ 10.4126, 10.3984, 10.3929, 10.3913, 10.3905] +24-11-19 19:32:30 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:32:30 | D | sum error = [ 16.1745, 17.1668, 18.2519, 19.5093, 20.9506] +24-11-19 19:32:30 | D | best error = [ 10.3905, 10.3905, 10.3905, 10.3905, 10.3905] +24-11-19 19:32:30 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:32:30 | D | sum error = [ 22.3874, 23.9443, 25.7366, 27.5713, 29.6246] +24-11-19 19:32:30 | D | best error = [ 10.3905, 10.3905, 10.3905, 10.3905, 10.3905] +24-11-19 19:32:30 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:32:30 | D | sum error = [ 31.7305, 34.0606, 36.5050, 39.0744, 41.8415] +24-11-19 19:32:30 | D | best error = [ 10.3905, 10.3905, 10.3905, 10.3905, 10.3905] +24-11-19 19:32:30 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:32:30 | D | sum error = [ 44.7349, 47.9190, 51.1986, 54.7310, 58.4897] +24-11-19 19:32:30 | D | best error = [ 10.3905, 10.3905, 10.3905, 10.3905, 10.3905] +24-11-19 19:32:30 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:32:30 | D | sum error = [ 62.4585, 66.7299, 71.2310, 75.9169, 80.9362] +24-11-19 19:32:30 | D | best error = [ 10.3905, 10.3905, 10.3905, 10.3905, 10.3905] +24-11-19 19:32:30 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:32:30 | D | sum error = [ 86.2924, 91.8712, 97.8739, 104.1063, 110.7954] +24-11-19 19:32:30 | D | best error = [ 10.3905, 10.3905, 10.3905, 10.3905, 10.3905] +24-11-19 19:32:30 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:32:30 | D | sum error = [ 117.7866, 125.2081, 133.1738, 141.4894, 150.3934] +24-11-19 19:32:30 | D | best error = [ 10.3905, 10.3905, 10.3905, 10.3905, 10.3905] +24-11-19 19:32:30 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:32:30 | D | sum error = [ 159.7098, 169.6295, 179.9974, 191.0933, 202.7776] +24-11-19 19:32:30 | D | best error = [ 10.3905, 10.3905, 10.3905, 10.3905, 10.3905] +24-11-19 19:32:30 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:32:30 | D | sum error = [ 215.1818, 228.2247, 242.0377, 256.5167, 271.7889] +24-11-19 19:32:30 | D | best error = [ 10.3905, 10.3905, 10.3905, 10.3905, 10.3905] +24-11-19 19:32:30 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:32:30 | D | sum error = [ 288.1187, 305.3040, 323.1943, 342.0563, 361.9297] +24-11-19 19:32:30 | D | best error = [ 10.3905, 10.3905, 10.3905, 10.3905, 10.3905] +24-11-19 19:32:30 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:32:30 | D | sum error = [ 382.7590, 404.5950, 427.6727, 451.6517, 476.8258] +24-11-19 19:32:30 | D | best error = [ 10.3905, 10.3905, 10.3905, 10.3905, 10.3905] +24-11-19 19:32:30 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:32:30 | D | sum error = [ 502.9722, 530.7732, 559.5290, 589.2930, 620.1007] +24-11-19 19:32:30 | D | best error = [ 10.3905, 10.3905, 10.3905, 10.3905, 10.3905] +24-11-19 19:32:30 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:32:30 | D | sum error = [ 652.5062, 685.9621, 720.9409, 756.9249, 794.3347] +24-11-19 19:32:30 | D | best error = [ 10.3905, 10.3905, 10.3905, 10.3905, 10.3905] +24-11-19 19:32:30 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:32:30 | D | sum error = [ 832.7446, 872.5109, 913.7442, 956.1577, 1000.0876] +24-11-19 19:32:30 | D | best error = [ 10.3905, 10.3905, 10.3905, 10.3905, 10.3905] +24-11-19 19:32:30 | D | + error = [10.3905] +24-11-19 19:32:30 | D | - Calibrating model.layers.30.mlp.gate_proj.weight +24-11-19 19:32:30 | D | + w: sint8 +24-11-19 19:32:30 | D | + x: None +24-11-19 19:32:30 | D | + y: None +24-11-19 19:32:30 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:32:30 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:32:30 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:32:30 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:32:30 | D | - range ratio = [ 1.0000] +24-11-19 19:32:30 | D | sum error = [ 12.9618] +24-11-19 19:32:30 | D | best error = [ 12.9618] +24-11-19 19:32:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:32:31 | D | sum error = [ 12.8898, 12.7886, 12.8999, 13.0752, 13.3491] +24-11-19 19:32:31 | D | best error = [ 11.8094, 11.3890, 11.1651, 11.0541, 10.9930] +24-11-19 19:32:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:32:31 | D | sum error = [ 13.6171, 14.1136, 14.6512, 15.4763, 16.1472] +24-11-19 19:32:31 | D | best error = [ 10.9618, 10.9461, 10.9412, 10.9399, 10.9395] +24-11-19 19:32:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:32:31 | D | sum error = [ 17.1046, 18.2075, 19.3742, 20.7486, 22.1559] +24-11-19 19:32:31 | D | best error = [ 10.9393, 10.9393, 10.9393, 10.9393, 10.9393] +24-11-19 19:32:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:32:31 | D | sum error = [ 23.7371, 25.4035, 27.2480, 29.2124, 31.3501] +24-11-19 19:32:31 | D | best error = [ 10.9393, 10.9393, 10.9393, 10.9393, 10.9393] +24-11-19 19:32:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:32:31 | D | sum error = [ 33.6425, 36.0673, 38.6114, 41.3950, 44.2971] +24-11-19 19:32:31 | D | best error = [ 10.9393, 10.9393, 10.9393, 10.9393, 10.9393] +24-11-19 19:32:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:32:31 | D | sum error = [ 47.5015, 50.7647, 54.4194, 58.1750, 62.1449] +24-11-19 19:32:31 | D | best error = [ 10.9393, 10.9393, 10.9393, 10.9393, 10.9393] +24-11-19 19:32:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:32:31 | D | sum error = [ 66.2911, 70.9260, 75.6614, 80.7561, 86.1083] +24-11-19 19:32:31 | D | best error = [ 10.9393, 10.9393, 10.9393, 10.9393, 10.9393] +24-11-19 19:32:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:32:31 | D | sum error = [ 91.7582, 97.7398, 104.0799, 110.7873, 117.9208] +24-11-19 19:32:31 | D | best error = [ 10.9393, 10.9393, 10.9393, 10.9393, 10.9393] +24-11-19 19:32:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:32:31 | D | sum error = [ 125.5229, 133.4369, 141.7949, 150.8228, 160.3223] +24-11-19 19:32:31 | D | best error = [ 10.9393, 10.9393, 10.9393, 10.9393, 10.9393] +24-11-19 19:32:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:32:31 | D | sum error = [ 170.3138, 180.9868, 192.1402, 204.0178, 216.5537] +24-11-19 19:32:31 | D | best error = [ 10.9393, 10.9393, 10.9393, 10.9393, 10.9393] +24-11-19 19:32:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:32:31 | D | sum error = [ 229.8265, 243.8629, 258.7939, 274.4646, 291.0069] +24-11-19 19:32:31 | D | best error = [ 10.9393, 10.9393, 10.9393, 10.9393, 10.9393] +24-11-19 19:32:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:32:31 | D | sum error = [ 308.5581, 327.0061, 346.0631, 366.4753, 387.8506] +24-11-19 19:32:31 | D | best error = [ 10.9393, 10.9393, 10.9393, 10.9393, 10.9393] +24-11-19 19:32:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:32:31 | D | sum error = [ 410.3856, 433.7856, 458.5585, 484.1200, 510.9724] +24-11-19 19:32:31 | D | best error = [ 10.9393, 10.9393, 10.9393, 10.9393, 10.9393] +24-11-19 19:32:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:32:31 | D | sum error = [ 539.1215, 568.4787, 598.8097, 630.8828, 664.3180] +24-11-19 19:32:31 | D | best error = [ 10.9393, 10.9393, 10.9393, 10.9393, 10.9393] +24-11-19 19:32:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:32:31 | D | sum error = [ 699.1049, 735.3235, 772.7373, 811.4147, 851.4614] +24-11-19 19:32:31 | D | best error = [ 10.9393, 10.9393, 10.9393, 10.9393, 10.9393] +24-11-19 19:32:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:32:31 | D | sum error = [ 893.0200, 935.7450, 980.2144, 1026.0521, 1073.1241] +24-11-19 19:32:31 | D | best error = [ 10.9393, 10.9393, 10.9393, 10.9393, 10.9393] +24-11-19 19:32:31 | D | + error = [10.9393] +24-11-19 19:32:31 | D | - Calibrating model.layers.30.mlp.down_proj.weight +24-11-19 19:32:31 | D | + w: sint8 +24-11-19 19:32:31 | D | + x: None +24-11-19 19:32:31 | D | + y: None +24-11-19 19:32:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:32:31 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:32:31 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:32:31 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:32:31 | D | - range ratio = [ 1.0000] +24-11-19 19:32:31 | D | sum error = [ 32.8947] +24-11-19 19:32:31 | D | best error = [ 32.8947] +24-11-19 19:32:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:32:32 | D | sum error = [ 32.9649, 32.3555, 32.4948, 31.9586, 32.3374] +24-11-19 19:32:32 | D | best error = [ 22.0535, 17.6597, 15.1461, 13.3060, 12.0934] +24-11-19 19:32:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:32:32 | D | sum error = [ 31.3548, 30.5329, 30.3977, 29.7681, 29.6872] +24-11-19 19:32:32 | D | best error = [ 11.0634, 10.2984, 9.7388, 9.3051, 8.9640] +24-11-19 19:32:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:32:32 | D | sum error = [ 29.8809, 29.0727, 29.0870, 28.9773, 28.4235] +24-11-19 19:32:32 | D | best error = [ 8.7869, 8.5997, 8.4567, 8.3538, 8.2513] +24-11-19 19:32:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:32:32 | D | sum error = [ 28.4185, 28.3898, 27.8323, 27.8542, 27.6269] +24-11-19 19:32:32 | D | best error = [ 8.1828, 8.1271, 8.0911, 8.0552, 8.0263] +24-11-19 19:32:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:32:32 | D | sum error = [ 27.5679, 27.6039, 26.9756, 26.9169, 27.0205] +24-11-19 19:32:32 | D | best error = [ 8.0067, 7.9955, 7.9835, 7.9750, 7.9696] +24-11-19 19:32:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:32:32 | D | sum error = [ 27.3147, 27.5219, 27.6365, 27.9719, 27.8293] +24-11-19 19:32:32 | D | best error = [ 7.9673, 7.9652, 7.9638, 7.9633, 7.9631] +24-11-19 19:32:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:32:32 | D | sum error = [ 28.3988, 29.2083, 29.5034, 30.3068, 31.1056] +24-11-19 19:32:32 | D | best error = [ 7.9623, 7.9619, 7.9619, 7.9619, 7.9619] +24-11-19 19:32:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:32:32 | D | sum error = [ 32.1191, 32.9296, 34.4174, 35.5909, 37.1864] +24-11-19 19:32:32 | D | best error = [ 7.9619, 7.9614, 7.9614, 7.9614, 7.9614] +24-11-19 19:32:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:32:32 | D | sum error = [ 39.0219, 40.7857, 42.9164, 45.2853, 48.0439] +24-11-19 19:32:32 | D | best error = [ 7.9614, 7.9614, 7.9614, 7.9614, 7.9614] +24-11-19 19:32:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:32:32 | D | sum error = [ 51.4247, 55.6407, 61.0284, 68.1181, 77.1223] +24-11-19 19:32:32 | D | best error = [ 7.9614, 7.9614, 7.9614, 7.9614, 7.9614] +24-11-19 19:32:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:32:32 | D | sum error = [ 89.5570, 105.0727, 125.2329, 150.7083, 182.8153] +24-11-19 19:32:32 | D | best error = [ 7.9614, 7.9614, 7.9614, 7.9614, 7.9614] +24-11-19 19:32:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:32:32 | D | sum error = [ 222.2832, 270.3147, 327.2502, 392.8238, 467.3016] +24-11-19 19:32:32 | D | best error = [ 7.9614, 7.9614, 7.9614, 7.9614, 7.9614] +24-11-19 19:32:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:32:32 | D | sum error = [ 550.7352, 642.5631, 742.1451, 848.8885, 961.7383] +24-11-19 19:32:32 | D | best error = [ 7.9614, 7.9614, 7.9614, 7.9614, 7.9614] +24-11-19 19:32:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:32:32 | D | sum error = [ 1079.6973, 1202.4500, 1329.0562, 1458.8685, 1590.8417] +24-11-19 19:32:32 | D | best error = [ 7.9614, 7.9614, 7.9614, 7.9614, 7.9614] +24-11-19 19:32:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:32:32 | D | sum error = [ 1725.0264, 1860.9871, 1998.3255, 2136.8513, 2276.4039] +24-11-19 19:32:32 | D | best error = [ 7.9614, 7.9614, 7.9614, 7.9614, 7.9614] +24-11-19 19:32:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:32:32 | D | sum error = [ 2416.8671, 2558.0842, 2699.9987, 2842.4492, 2985.5104] +24-11-19 19:32:32 | D | best error = [ 7.9614, 7.9614, 7.9614, 7.9614, 7.9614] +24-11-19 19:32:32 | D | + error = [7.9614] +24-11-19 19:32:32 | D | - Quantizing model.layers.30.self_attn.q_proj.weight +24-11-19 19:32:33 | D | - Quantizing model.layers.30.self_attn.k_proj.weight +24-11-19 19:32:34 | D | - Quantizing model.layers.30.self_attn.v_proj.weight +24-11-19 19:32:35 | D | - Quantizing model.layers.30.self_attn.o_proj.weight +24-11-19 19:32:36 | D | - Quantizing model.layers.30.mlp.up_proj.weight +24-11-19 19:32:37 | D | - Quantizing model.layers.30.mlp.gate_proj.weight +24-11-19 19:32:38 | D | - Quantizing model.layers.30.mlp.down_proj.weight +24-11-19 19:32:46 | D | - Quantizing layer model.layers.31 +24-11-19 19:32:46 | D | - Calibrating model.layers.31.self_attn.q_proj.weight +24-11-19 19:32:46 | D | + w: sint8 +24-11-19 19:32:46 | D | + x: None +24-11-19 19:32:46 | D | + y: None +24-11-19 19:32:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:32:46 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:32:46 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:32:47 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:32:47 | D | - range ratio = [ 1.0000] +24-11-19 19:32:47 | D | sum error = [ 15.2309] +24-11-19 19:32:47 | D | best error = [ 15.2309] +24-11-19 19:32:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:32:59 | D | sum error = [ 15.2300, 14.9017, 15.6784, 16.0106, 15.8535] +24-11-19 19:32:59 | D | best error = [ 15.2300, 14.9017, 14.9017, 14.9017, 14.9017] +24-11-19 19:32:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:32:59 | D | sum error = [ 16.5644, 17.6916, 17.6116, 20.0073, 21.5944] +24-11-19 19:32:59 | D | best error = [ 14.9017, 14.9017, 14.9017, 14.9017, 14.9017] +24-11-19 19:32:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:32:59 | D | sum error = [ 23.0723, 24.2231, 27.8784, 29.2527, 31.7167] +24-11-19 19:32:59 | D | best error = [ 14.9017, 14.9017, 14.9017, 14.9017, 14.9017] +24-11-19 19:32:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:32:59 | D | sum error = [ 36.6730, 39.7447, 42.1324, 46.4711, 52.1586] +24-11-19 19:32:59 | D | best error = [ 14.9017, 14.9017, 14.9017, 14.9017, 14.9017] +24-11-19 19:32:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:32:59 | D | sum error = [ 56.5208, 61.5259, 65.5426, 71.9465, 78.2752] +24-11-19 19:32:59 | D | best error = [ 14.9017, 14.9017, 14.9017, 14.9017, 14.9017] +24-11-19 19:32:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:32:59 | D | sum error = [ 85.5574, 92.9050, 100.3884, 106.6621, 115.5760] +24-11-19 19:32:59 | D | best error = [ 14.9017, 14.9017, 14.9017, 14.9017, 14.9017] +24-11-19 19:32:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:32:59 | D | sum error = [ 123.4987, 133.1578, 142.7878, 152.7419, 165.8456] +24-11-19 19:32:59 | D | best error = [ 14.9017, 14.9017, 14.9017, 14.9017, 14.9017] +24-11-19 19:32:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:32:59 | D | sum error = [ 177.9080, 191.1243, 205.9360, 221.1104, 238.6545] +24-11-19 19:32:59 | D | best error = [ 14.9017, 14.9017, 14.9017, 14.9017, 14.9017] +24-11-19 19:32:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:32:59 | D | sum error = [ 257.2198, 276.5981, 297.9585, 322.3910, 347.0776] +24-11-19 19:32:59 | D | best error = [ 14.9017, 14.9017, 14.9017, 14.9017, 14.9017] +24-11-19 19:32:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:32:59 | D | sum error = [ 374.3156, 402.9693, 433.8871, 466.4161, 500.8553] +24-11-19 19:32:59 | D | best error = [ 14.9017, 14.9017, 14.9017, 14.9017, 14.9017] +24-11-19 19:32:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:32:59 | D | sum error = [ 538.8487, 578.5865, 620.7356, 667.4042, 716.8604] +24-11-19 19:32:59 | D | best error = [ 14.9017, 14.9017, 14.9017, 14.9017, 14.9017] +24-11-19 19:32:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:32:59 | D | sum error = [ 769.9843, 826.9978, 886.8174, 952.6801, 1021.2540] +24-11-19 19:32:59 | D | best error = [ 14.9017, 14.9017, 14.9017, 14.9017, 14.9017] +24-11-19 19:32:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:32:59 | D | sum error = [ 1096.5603, 1176.7311, 1262.3246, 1354.1073, 1454.6264] +24-11-19 19:32:59 | D | best error = [ 14.9017, 14.9017, 14.9017, 14.9017, 14.9017] +24-11-19 19:32:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:32:59 | D | sum error = [ 1561.2804, 1675.8465, 1799.5381, 1932.6122, 2074.6730] +24-11-19 19:32:59 | D | best error = [ 14.9017, 14.9017, 14.9017, 14.9017, 14.9017] +24-11-19 19:32:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:32:59 | D | sum error = [ 2226.1103, 2388.0509, 2561.2970, 2746.1919, 2944.9039] +24-11-19 19:32:59 | D | best error = [ 14.9017, 14.9017, 14.9017, 14.9017, 14.9017] +24-11-19 19:32:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:32:59 | D | sum error = [ 3158.0168, 3384.6953, 3628.3024, 3888.4689, 4166.4352] +24-11-19 19:32:59 | D | best error = [ 14.9017, 14.9017, 14.9017, 14.9017, 14.9017] +24-11-19 19:32:59 | D | + error = [14.9017] +24-11-19 19:32:59 | D | - Calibrating model.layers.31.self_attn.k_proj.weight +24-11-19 19:32:59 | D | + w: sint8 +24-11-19 19:32:59 | D | + x: None +24-11-19 19:32:59 | D | + y: None +24-11-19 19:32:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:32:59 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:32:59 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:33:00 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:33:00 | D | - range ratio = [ 1.0000] +24-11-19 19:33:00 | D | sum error = [ 20.1726] +24-11-19 19:33:00 | D | best error = [ 20.1726] +24-11-19 19:33:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:33:12 | D | sum error = [ 20.5938, 19.8401, 19.2526, 20.6042, 22.4208] +24-11-19 19:33:12 | D | best error = [ 20.1726, 19.8401, 19.2526, 19.2526, 19.2526] +24-11-19 19:33:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:33:12 | D | sum error = [ 20.5257, 22.8083, 22.8916, 24.5405, 26.9309] +24-11-19 19:33:12 | D | best error = [ 19.2526, 19.2526, 19.2526, 19.2526, 19.2526] +24-11-19 19:33:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:33:12 | D | sum error = [ 30.5307, 30.3211, 29.6185, 33.2826, 41.5417] +24-11-19 19:33:12 | D | best error = [ 19.2526, 19.2526, 19.2526, 19.2526, 19.2526] +24-11-19 19:33:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:33:12 | D | sum error = [ 39.5978, 46.3488, 50.8601, 52.9394, 60.9084] +24-11-19 19:33:12 | D | best error = [ 19.2526, 19.2526, 19.2526, 19.2526, 19.2526] +24-11-19 19:33:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:33:12 | D | sum error = [ 63.4696, 69.7324, 72.7378, 82.6496, 92.4313] +24-11-19 19:33:12 | D | best error = [ 19.2526, 19.2526, 19.2526, 19.2526, 19.2526] +24-11-19 19:33:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:33:12 | D | sum error = [ 98.5479, 105.2682, 112.8517, 121.3404, 129.8832] +24-11-19 19:33:12 | D | best error = [ 19.2526, 19.2526, 19.2526, 19.2526, 19.2526] +24-11-19 19:33:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:33:12 | D | sum error = [ 138.8376, 145.6192, 159.3882, 168.2572, 179.2583] +24-11-19 19:33:12 | D | best error = [ 19.2526, 19.2526, 19.2526, 19.2526, 19.2526] +24-11-19 19:33:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:33:12 | D | sum error = [ 191.6457, 204.2890, 220.0507, 237.4581, 254.3612] +24-11-19 19:33:12 | D | best error = [ 19.2526, 19.2526, 19.2526, 19.2526, 19.2526] +24-11-19 19:33:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:33:12 | D | sum error = [ 269.8441, 287.3338, 306.4860, 322.2841, 342.7561] +24-11-19 19:33:12 | D | best error = [ 19.2526, 19.2526, 19.2526, 19.2526, 19.2526] +24-11-19 19:33:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:33:12 | D | sum error = [ 367.7977, 392.8095, 420.9730, 450.0959, 480.6254] +24-11-19 19:33:12 | D | best error = [ 19.2526, 19.2526, 19.2526, 19.2526, 19.2526] +24-11-19 19:33:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:33:12 | D | sum error = [ 514.1130, 550.0589, 592.1998, 635.3128, 682.2547] +24-11-19 19:33:12 | D | best error = [ 19.2526, 19.2526, 19.2526, 19.2526, 19.2526] +24-11-19 19:33:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:33:12 | D | sum error = [ 734.4746, 790.2585, 848.2824, 912.9709, 979.6762] +24-11-19 19:33:12 | D | best error = [ 19.2526, 19.2526, 19.2526, 19.2526, 19.2526] +24-11-19 19:33:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:33:12 | D | sum error = [ 1053.9609, 1129.1747, 1208.6635, 1302.5928, 1399.8267] +24-11-19 19:33:12 | D | best error = [ 19.2526, 19.2526, 19.2526, 19.2526, 19.2526] +24-11-19 19:33:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:33:12 | D | sum error = [ 1515.2155, 1629.8399, 1754.7523, 1886.3416, 2031.6419] +24-11-19 19:33:12 | D | best error = [ 19.2526, 19.2526, 19.2526, 19.2526, 19.2526] +24-11-19 19:33:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:33:12 | D | sum error = [ 2186.1600, 2360.8889, 2542.5625, 2741.3181, 2948.7579] +24-11-19 19:33:12 | D | best error = [ 19.2526, 19.2526, 19.2526, 19.2526, 19.2526] +24-11-19 19:33:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:33:12 | D | sum error = [ 3175.6643, 3416.1434, 3684.8262, 3960.8582, 4256.8986] +24-11-19 19:33:12 | D | best error = [ 19.2526, 19.2526, 19.2526, 19.2526, 19.2526] +24-11-19 19:33:12 | D | + error = [19.2526] +24-11-19 19:33:13 | D | - Calibrating model.layers.31.self_attn.v_proj.weight +24-11-19 19:33:13 | D | + w: sint8 +24-11-19 19:33:13 | D | + x: None +24-11-19 19:33:13 | D | + y: None +24-11-19 19:33:13 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:33:13 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:33:13 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:33:13 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:33:13 | D | - range ratio = [ 1.0000] +24-11-19 19:33:13 | D | sum error = [ 7.1424] +24-11-19 19:33:13 | D | best error = [ 7.1424] +24-11-19 19:33:13 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:33:13 | D | sum error = [ 7.0743, 7.0775, 7.1223, 7.1759, 7.3253] +24-11-19 19:33:13 | D | best error = [ 6.5571, 6.3475, 6.2426, 6.1818, 6.1500] +24-11-19 19:33:13 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:33:13 | D | sum error = [ 7.4908, 7.7639, 8.0274, 8.4425, 8.8786] +24-11-19 19:33:13 | D | best error = [ 6.1346, 6.1274, 6.1243, 6.1234, 6.1233] +24-11-19 19:33:13 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:33:13 | D | sum error = [ 9.3646, 9.9785, 10.5791, 11.2915, 12.0630] +24-11-19 19:33:13 | D | best error = [ 6.1233, 6.1232, 6.1232, 6.1232, 6.1232] +24-11-19 19:33:13 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:33:13 | D | sum error = [ 12.9325, 13.8333, 14.8189, 15.8855, 17.0366] +24-11-19 19:33:13 | D | best error = [ 6.1232, 6.1232, 6.1232, 6.1232, 6.1232] +24-11-19 19:33:13 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:33:13 | D | sum error = [ 18.2383, 19.5469, 20.8743, 22.3205, 23.8823] +24-11-19 19:33:13 | D | best error = [ 6.1232, 6.1232, 6.1232, 6.1232, 6.1232] +24-11-19 19:33:13 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:33:13 | D | sum error = [ 25.4864, 27.2180, 29.0511, 30.9617, 32.9829] +24-11-19 19:33:13 | D | best error = [ 6.1232, 6.1232, 6.1232, 6.1232, 6.1232] +24-11-19 19:33:13 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:33:13 | D | sum error = [ 35.1293, 37.4131, 39.8031, 42.3104, 44.9297] +24-11-19 19:33:13 | D | best error = [ 6.1232, 6.1232, 6.1232, 6.1232, 6.1232] +24-11-19 19:33:13 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:33:13 | D | sum error = [ 47.7155, 50.6460, 53.7068, 56.9329, 60.3290] +24-11-19 19:33:13 | D | best error = [ 6.1232, 6.1232, 6.1232, 6.1232, 6.1232] +24-11-19 19:33:13 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:33:13 | D | sum error = [ 63.8696, 67.6159, 71.5238, 75.6103, 79.8986] +24-11-19 19:33:13 | D | best error = [ 6.1232, 6.1232, 6.1232, 6.1232, 6.1232] +24-11-19 19:33:13 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:33:13 | D | sum error = [ 84.3823, 89.0937, 94.0278, 99.1451, 104.5056] +24-11-19 19:33:13 | D | best error = [ 6.1232, 6.1232, 6.1232, 6.1232, 6.1232] +24-11-19 19:33:13 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:33:13 | D | sum error = [ 110.1022, 115.9353, 121.9911, 128.3104, 134.9472] +24-11-19 19:33:13 | D | best error = [ 6.1232, 6.1232, 6.1232, 6.1232, 6.1232] +24-11-19 19:33:13 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:33:13 | D | sum error = [ 141.8061, 148.9300, 156.3557, 164.0508, 172.0327] +24-11-19 19:33:13 | D | best error = [ 6.1232, 6.1232, 6.1232, 6.1232, 6.1232] +24-11-19 19:33:13 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:33:13 | D | sum error = [ 180.3183, 188.9340, 197.8609, 207.0748, 216.6354] +24-11-19 19:33:13 | D | best error = [ 6.1232, 6.1232, 6.1232, 6.1232, 6.1232] +24-11-19 19:33:13 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:33:13 | D | sum error = [ 226.4947, 236.6884, 247.2248, 258.1081, 269.3420] +24-11-19 19:33:13 | D | best error = [ 6.1232, 6.1232, 6.1232, 6.1232, 6.1232] +24-11-19 19:33:13 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:33:13 | D | sum error = [ 280.9384, 292.8805, 305.2140, 317.8907, 330.9920] +24-11-19 19:33:13 | D | best error = [ 6.1232, 6.1232, 6.1232, 6.1232, 6.1232] +24-11-19 19:33:13 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:33:13 | D | sum error = [ 344.4591, 358.3476, 372.6141, 387.2949, 402.3753] +24-11-19 19:33:13 | D | best error = [ 6.1232, 6.1232, 6.1232, 6.1232, 6.1232] +24-11-19 19:33:13 | D | + error = [6.1232] +24-11-19 19:33:13 | D | - Calibrating model.layers.31.self_attn.o_proj.weight +24-11-19 19:33:13 | D | + w: sint8 +24-11-19 19:33:13 | D | + x: None +24-11-19 19:33:13 | D | + y: None +24-11-19 19:33:13 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:33:13 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:33:13 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:33:13 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:33:13 | D | - range ratio = [ 1.0000] +24-11-19 19:33:13 | D | sum error = [ 3.3443] +24-11-19 19:33:13 | D | best error = [ 3.3443] +24-11-19 19:33:14 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:33:14 | D | sum error = [ 3.2881, 3.3082, 3.3383, 3.3732, 3.4691] +24-11-19 19:33:14 | D | best error = [ 3.0139, 2.8866, 2.8129, 2.7658, 2.7319] +24-11-19 19:33:14 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:33:14 | D | sum error = [ 3.5924, 3.7281, 3.9159, 4.1593, 4.4164] +24-11-19 19:33:14 | D | best error = [ 2.7108, 2.6916, 2.6782, 2.6695, 2.6628] +24-11-19 19:33:14 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:33:14 | D | sum error = [ 4.7285, 5.0602, 5.4456, 5.8569, 6.3146] +24-11-19 19:33:14 | D | best error = [ 2.6588, 2.6557, 2.6535, 2.6519, 2.6506] +24-11-19 19:33:14 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:33:14 | D | sum error = [ 6.8168, 7.3350, 7.9439, 8.5991, 9.2737] +24-11-19 19:33:14 | D | best error = [ 2.6500, 2.6494, 2.6490, 2.6486, 2.6482] +24-11-19 19:33:14 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:33:14 | D | sum error = [ 10.0451, 10.8293, 11.7144, 12.6342, 13.6557] +24-11-19 19:33:14 | D | best error = [ 2.6481, 2.6479, 2.6479, 2.6478, 2.6478] +24-11-19 19:33:14 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:33:14 | D | sum error = [ 14.7128, 15.8535, 17.1118, 18.4397, 19.9018] +24-11-19 19:33:14 | D | best error = [ 2.6478, 2.6478, 2.6478, 2.6478, 2.6478] +24-11-19 19:33:14 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:33:14 | D | sum error = [ 21.4309, 23.0933, 24.8657, 26.7862, 28.8335] +24-11-19 19:33:14 | D | best error = [ 2.6478, 2.6478, 2.6478, 2.6478, 2.6478] +24-11-19 19:33:14 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:33:14 | D | sum error = [ 31.0341, 33.3608, 35.8866, 38.5483, 41.4353] +24-11-19 19:33:14 | D | best error = [ 2.6478, 2.6478, 2.6478, 2.6478, 2.6478] +24-11-19 19:33:14 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:33:14 | D | sum error = [ 44.5067, 47.7682, 51.2554, 54.9620, 58.9402] +24-11-19 19:33:14 | D | best error = [ 2.6478, 2.6478, 2.6478, 2.6478, 2.6478] +24-11-19 19:33:14 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:33:14 | D | sum error = [ 63.1687, 67.6644, 72.4317, 77.5094, 82.8911] +24-11-19 19:33:14 | D | best error = [ 2.6478, 2.6478, 2.6478, 2.6478, 2.6478] +24-11-19 19:33:14 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:33:14 | D | sum error = [ 88.6038, 94.6394, 101.0339, 107.7901, 114.9508] +24-11-19 19:33:14 | D | best error = [ 2.6478, 2.6478, 2.6478, 2.6478, 2.6478] +24-11-19 19:33:14 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:33:14 | D | sum error = [ 122.4965, 130.4686, 138.8790, 147.7431, 157.0741] +24-11-19 19:33:14 | D | best error = [ 2.6478, 2.6478, 2.6478, 2.6478, 2.6478] +24-11-19 19:33:14 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:33:14 | D | sum error = [ 166.8926, 177.2277, 188.0570, 199.4068, 211.2900] +24-11-19 19:33:14 | D | best error = [ 2.6478, 2.6478, 2.6478, 2.6478, 2.6478] +24-11-19 19:33:14 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:33:14 | D | sum error = [ 223.7337, 236.7357, 250.3015, 264.4684, 279.1845] +24-11-19 19:33:14 | D | best error = [ 2.6478, 2.6478, 2.6478, 2.6478, 2.6478] +24-11-19 19:33:14 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:33:14 | D | sum error = [ 294.5080, 310.4536, 326.9902, 344.1436, 361.9437] +24-11-19 19:33:14 | D | best error = [ 2.6478, 2.6478, 2.6478, 2.6478, 2.6478] +24-11-19 19:33:14 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:33:14 | D | sum error = [ 380.3679, 399.4367, 419.1481, 439.5086, 460.5025] +24-11-19 19:33:14 | D | best error = [ 2.6478, 2.6478, 2.6478, 2.6478, 2.6478] +24-11-19 19:33:14 | D | + error = [2.6478] +24-11-19 19:33:14 | D | - Calibrating model.layers.31.mlp.up_proj.weight +24-11-19 19:33:14 | D | + w: sint8 +24-11-19 19:33:14 | D | + x: None +24-11-19 19:33:14 | D | + y: None +24-11-19 19:33:14 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:33:14 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:33:14 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:33:14 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:33:14 | D | - range ratio = [ 1.0000] +24-11-19 19:33:14 | D | sum error = [ 11.4366] +24-11-19 19:33:14 | D | best error = [ 11.4366] +24-11-19 19:33:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:33:15 | D | sum error = [ 11.3799, 11.3384, 11.3954, 11.5103, 11.7406] +24-11-19 19:33:15 | D | best error = [ 10.4751, 10.1290, 9.9463, 9.8410, 9.7823] +24-11-19 19:33:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:33:15 | D | sum error = [ 12.0190, 12.4810, 12.9880, 13.5763, 14.3245] +24-11-19 19:33:15 | D | best error = [ 9.7553, 9.7432, 9.7388, 9.7373, 9.7370] +24-11-19 19:33:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:33:15 | D | sum error = [ 15.1344, 16.1371, 17.1924, 18.3543, 19.6644] +24-11-19 19:33:15 | D | best error = [ 9.7370, 9.7368, 9.7368, 9.7368, 9.7368] +24-11-19 19:33:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:33:15 | D | sum error = [ 21.0820, 22.6088, 24.2977, 26.1383, 28.0553] +24-11-19 19:33:15 | D | best error = [ 9.7368, 9.7368, 9.7368, 9.7368, 9.7368] +24-11-19 19:33:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:33:15 | D | sum error = [ 30.1314, 32.3250, 34.7168, 37.2662, 40.0404] +24-11-19 19:33:15 | D | best error = [ 9.7368, 9.7368, 9.7368, 9.7368, 9.7368] +24-11-19 19:33:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:33:15 | D | sum error = [ 42.9129, 46.0280, 49.3473, 52.8256, 56.6104] +24-11-19 19:33:15 | D | best error = [ 9.7368, 9.7368, 9.7368, 9.7368, 9.7368] +24-11-19 19:33:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:33:15 | D | sum error = [ 60.6317, 64.8826, 69.4931, 74.2728, 79.3580] +24-11-19 19:33:15 | D | best error = [ 9.7368, 9.7368, 9.7368, 9.7368, 9.7368] +24-11-19 19:33:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:33:15 | D | sum error = [ 84.7707, 90.6701, 96.8723, 103.4138, 110.4619] +24-11-19 19:33:15 | D | best error = [ 9.7368, 9.7368, 9.7368, 9.7368, 9.7368] +24-11-19 19:33:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:33:15 | D | sum error = [ 117.9647, 125.8765, 134.3403, 143.2995, 152.8250] +24-11-19 19:33:15 | D | best error = [ 9.7368, 9.7368, 9.7368, 9.7368, 9.7368] +24-11-19 19:33:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:33:15 | D | sum error = [ 163.0101, 173.7658, 185.1863, 197.3233, 210.1796] +24-11-19 19:33:15 | D | best error = [ 9.7368, 9.7368, 9.7368, 9.7368, 9.7368] +24-11-19 19:33:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:33:15 | D | sum error = [ 223.8617, 238.2744, 253.5430, 269.7565, 286.8811] +24-11-19 19:33:15 | D | best error = [ 9.7368, 9.7368, 9.7368, 9.7368, 9.7368] +24-11-19 19:33:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:33:15 | D | sum error = [ 305.0085, 324.1660, 344.3311, 365.5890, 388.0447] +24-11-19 19:33:15 | D | best error = [ 9.7368, 9.7368, 9.7368, 9.7368, 9.7368] +24-11-19 19:33:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:33:15 | D | sum error = [ 411.6695, 436.4170, 462.5495, 489.9288, 518.6311] +24-11-19 19:33:15 | D | best error = [ 9.7368, 9.7368, 9.7368, 9.7368, 9.7368] +24-11-19 19:33:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:33:15 | D | sum error = [ 548.7241, 580.1823, 613.1511, 647.5557, 683.3891] +24-11-19 19:33:15 | D | best error = [ 9.7368, 9.7368, 9.7368, 9.7368, 9.7368] +24-11-19 19:33:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:33:15 | D | sum error = [ 720.8537, 759.8876, 800.5243, 842.7326, 886.5424] +24-11-19 19:33:15 | D | best error = [ 9.7368, 9.7368, 9.7368, 9.7368, 9.7368] +24-11-19 19:33:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:33:15 | D | sum error = [ 931.9426, 979.0549, 1027.7505, 1078.0859, 1130.0276] +24-11-19 19:33:15 | D | best error = [ 9.7368, 9.7368, 9.7368, 9.7368, 9.7368] +24-11-19 19:33:15 | D | + error = [9.7368] +24-11-19 19:33:15 | D | - Calibrating model.layers.31.mlp.gate_proj.weight +24-11-19 19:33:15 | D | + w: sint8 +24-11-19 19:33:15 | D | + x: None +24-11-19 19:33:15 | D | + y: None +24-11-19 19:33:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:33:15 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:33:15 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:33:15 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:33:15 | D | - range ratio = [ 1.0000] +24-11-19 19:33:15 | D | sum error = [ 12.1306] +24-11-19 19:33:15 | D | best error = [ 12.1306] +24-11-19 19:33:16 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:33:16 | D | sum error = [ 12.0061, 11.9936, 12.0398, 12.2099, 12.4275] +24-11-19 19:33:16 | D | best error = [ 11.0943, 10.7178, 10.5276, 10.4187, 10.3644] +24-11-19 19:33:16 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:33:16 | D | sum error = [ 12.7496, 13.2094, 13.7162, 14.3702, 15.1648] +24-11-19 19:33:16 | D | best error = [ 10.3369, 10.3245, 10.3195, 10.3179, 10.3178] +24-11-19 19:33:16 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:33:16 | D | sum error = [ 16.0512, 17.0461, 18.1594, 19.5131, 20.8501] +24-11-19 19:33:16 | D | best error = [ 10.3177, 10.3177, 10.3177, 10.3177, 10.3177] +24-11-19 19:33:16 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:33:16 | D | sum error = [ 22.3876, 24.0356, 25.8342, 27.7368, 29.8162] +24-11-19 19:33:16 | D | best error = [ 10.3177, 10.3177, 10.3177, 10.3177, 10.3177] +24-11-19 19:33:16 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:33:16 | D | sum error = [ 32.0537, 34.4049, 37.0360, 39.7627, 42.6576] +24-11-19 19:33:16 | D | best error = [ 10.3177, 10.3177, 10.3177, 10.3177, 10.3177] +24-11-19 19:33:16 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:33:16 | D | sum error = [ 45.7449, 49.0984, 52.6144, 56.2887, 60.3411] +24-11-19 19:33:16 | D | best error = [ 10.3177, 10.3177, 10.3177, 10.3177, 10.3177] +24-11-19 19:33:16 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:33:16 | D | sum error = [ 64.5856, 69.0621, 73.8511, 78.9242, 84.3783] +24-11-19 19:33:16 | D | best error = [ 10.3177, 10.3177, 10.3177, 10.3177, 10.3177] +24-11-19 19:33:16 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:33:16 | D | sum error = [ 90.1027, 96.2213, 102.7126, 109.5843, 116.9501] +24-11-19 19:33:16 | D | best error = [ 10.3177, 10.3177, 10.3177, 10.3177, 10.3177] +24-11-19 19:33:16 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:33:16 | D | sum error = [ 124.7800, 133.0864, 141.8766, 151.3126, 161.2283] +24-11-19 19:33:16 | D | best error = [ 10.3177, 10.3177, 10.3177, 10.3177, 10.3177] +24-11-19 19:33:16 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:33:16 | D | sum error = [ 171.8616, 183.1138, 195.0718, 207.7804, 221.2465] +24-11-19 19:33:16 | D | best error = [ 10.3177, 10.3177, 10.3177, 10.3177, 10.3177] +24-11-19 19:33:16 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:33:16 | D | sum error = [ 235.4823, 250.6889, 266.7370, 283.7250, 301.6973] +24-11-19 19:33:16 | D | best error = [ 10.3177, 10.3177, 10.3177, 10.3177, 10.3177] +24-11-19 19:33:16 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:33:16 | D | sum error = [ 320.6506, 340.7263, 361.8243, 384.1050, 407.5015] +24-11-19 19:33:16 | D | best error = [ 10.3177, 10.3177, 10.3177, 10.3177, 10.3177] +24-11-19 19:33:16 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:33:16 | D | sum error = [ 432.2031, 458.0954, 485.3580, 513.9498, 543.9688] +24-11-19 19:33:16 | D | best error = [ 10.3177, 10.3177, 10.3177, 10.3177, 10.3177] +24-11-19 19:33:16 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:33:16 | D | sum error = [ 575.4348, 608.4035, 642.7428, 678.5908, 716.0710] +24-11-19 19:33:16 | D | best error = [ 10.3177, 10.3177, 10.3177, 10.3177, 10.3177] +24-11-19 19:33:16 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:33:16 | D | sum error = [ 755.1167, 795.7082, 837.9862, 881.8384, 927.3434] +24-11-19 19:33:16 | D | best error = [ 10.3177, 10.3177, 10.3177, 10.3177, 10.3177] +24-11-19 19:33:16 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:33:16 | D | sum error = [ 974.4008, 1023.0813, 1073.4030, 1125.3214, 1178.8433] +24-11-19 19:33:16 | D | best error = [ 10.3177, 10.3177, 10.3177, 10.3177, 10.3177] +24-11-19 19:33:16 | D | + error = [10.3177] +24-11-19 19:33:16 | D | - Calibrating model.layers.31.mlp.down_proj.weight +24-11-19 19:33:16 | D | + w: sint8 +24-11-19 19:33:16 | D | + x: None +24-11-19 19:33:16 | D | + y: None +24-11-19 19:33:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:33:16 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 19:33:16 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 19:33:17 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 19:33:17 | D | - range ratio = [ 1.0000] +24-11-19 19:33:17 | D | sum error = [ 16.3841] +24-11-19 19:33:17 | D | best error = [ 16.3841] +24-11-19 19:33:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:33:17 | D | sum error = [ 16.2092, 15.9894, 15.8519, 15.7846, 15.5122] +24-11-19 19:33:17 | D | best error = [ 14.5012, 13.7486, 13.2793, 12.9790, 12.7374] +24-11-19 19:33:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:33:17 | D | sum error = [ 15.4297, 15.3096, 15.2452, 15.0511, 14.8316] +24-11-19 19:33:17 | D | best error = [ 12.5494, 12.3791, 12.2445, 12.1232, 12.0073] +24-11-19 19:33:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:33:17 | D | sum error = [ 14.8772, 14.8839, 14.7522, 14.7280, 14.8249] +24-11-19 19:33:17 | D | best error = [ 11.9096, 11.8175, 11.7303, 11.6569, 11.5940] +24-11-19 19:33:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:33:17 | D | sum error = [ 14.6987, 14.6707, 14.8954, 14.9789, 15.0438] +24-11-19 19:33:17 | D | best error = [ 11.5384, 11.4980, 11.4655, 11.4393, 11.4098] +24-11-19 19:33:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:33:17 | D | sum error = [ 15.3758, 15.6142, 16.0402, 16.4436, 16.8746] +24-11-19 19:33:17 | D | best error = [ 11.3898, 11.3767, 11.3637, 11.3539, 11.3458] +24-11-19 19:33:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:33:17 | D | sum error = [ 17.5240, 18.1299, 18.8934, 19.7686, 20.6993] +24-11-19 19:33:17 | D | best error = [ 11.3417, 11.3358, 11.3338, 11.3312, 11.3293] +24-11-19 19:33:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:33:17 | D | sum error = [ 21.7740, 22.9278, 24.2367, 25.6662, 27.2465] +24-11-19 19:33:17 | D | best error = [ 11.3285, 11.3276, 11.3274, 11.3274, 11.3274] +24-11-19 19:33:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:33:17 | D | sum error = [ 28.9888, 30.8874, 32.8882, 35.1135, 37.5520] +24-11-19 19:33:17 | D | best error = [ 11.3274, 11.3270, 11.3270, 11.3270, 11.3270] +24-11-19 19:33:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:33:17 | D | sum error = [ 40.1527, 43.0003, 46.0953, 49.3555, 52.9457] +24-11-19 19:33:17 | D | best error = [ 11.3270, 11.3267, 11.3267, 11.3267, 11.3267] +24-11-19 19:33:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:33:17 | D | sum error = [ 56.7601, 60.9167, 65.4341, 70.2988, 75.5258] +24-11-19 19:33:17 | D | best error = [ 11.3267, 11.3267, 11.3267, 11.3267, 11.3267] +24-11-19 19:33:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:33:17 | D | sum error = [ 81.2349, 87.3119, 93.9724, 101.2357, 109.0232] +24-11-19 19:33:17 | D | best error = [ 11.3267, 11.3267, 11.3267, 11.3267, 11.3267] +24-11-19 19:33:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:33:17 | D | sum error = [ 117.5079, 126.7846, 136.9175, 147.8684, 159.8459] +24-11-19 19:33:17 | D | best error = [ 11.3267, 11.3267, 11.3267, 11.3267, 11.3267] +24-11-19 19:33:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:33:17 | D | sum error = [ 172.9527, 187.0886, 202.5641, 219.4374, 237.7669] +24-11-19 19:33:17 | D | best error = [ 11.3267, 11.3267, 11.3267, 11.3267, 11.3267] +24-11-19 19:33:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:33:17 | D | sum error = [ 257.6667, 279.2085, 302.6121, 327.8041, 355.0271] +24-11-19 19:33:17 | D | best error = [ 11.3267, 11.3267, 11.3267, 11.3267, 11.3267] +24-11-19 19:33:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:33:17 | D | sum error = [ 384.4676, 416.1868, 450.3341, 486.9438, 526.2538] +24-11-19 19:33:17 | D | best error = [ 11.3267, 11.3267, 11.3267, 11.3267, 11.3267] +24-11-19 19:33:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:33:17 | D | sum error = [ 568.3646, 613.4346, 661.5883, 712.8881, 767.5766] +24-11-19 19:33:17 | D | best error = [ 11.3267, 11.3267, 11.3267, 11.3267, 11.3267] +24-11-19 19:33:17 | D | + error = [11.3267] +24-11-19 19:33:18 | D | - Quantizing model.layers.31.self_attn.q_proj.weight +24-11-19 19:33:18 | D | - Quantizing model.layers.31.self_attn.k_proj.weight +24-11-19 19:33:19 | D | - Quantizing model.layers.31.self_attn.v_proj.weight +24-11-19 19:33:20 | D | - Quantizing model.layers.31.self_attn.o_proj.weight +24-11-19 19:33:21 | D | - Quantizing model.layers.31.mlp.up_proj.weight +24-11-19 19:33:22 | D | - Quantizing model.layers.31.mlp.gate_proj.weight +24-11-19 19:33:23 | D | - Quantizing model.layers.31.mlp.down_proj.weight +24-11-19 19:33:26 | I | - Saving weight quantizer settings to runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-2-7b-instruct-together-32k.pt +24-11-19 19:33:26 | I | - Linking weight quantizer settings to runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.185856.RUNNING/cache/wgts.pt +24-11-19 19:33:26 | I | * Quantizing activations +24-11-19 19:33:26 | I | - Generating activation quantizer settings +24-11-19 19:33:26 | D | Starting new HTTPS connection (7): huggingface.co:443 +24-11-19 19:33:32 | D | Starting new HTTPS connection (8): huggingface.co:443 +24-11-19 19:33:44 | D | Starting new HTTPS connection (3): s3.amazonaws.com:443 +24-11-19 19:33:56 | W | Repo card metadata block was not found. Setting CardData to empty. +24-11-19 19:33:56 | D | Starting new HTTPS connection (9): huggingface.co:443 +24-11-19 19:34:09 | W | Using the latest cached version of the dataset since mit-han-lab/pile-val-backup couldn't be found on the Hugging Face Hub +24-11-19 19:34:09 | W | Found the latest cached dataset configuration 'default' at /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4 (last modified on Tue Oct 8 18:58:39 2024). +24-11-19 19:34:09 | D | Attempting to acquire lock 23438309350752 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 19:34:09 | D | Lock 23438309350752 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 19:34:09 | D | open file: /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4/dataset_info.json +24-11-19 19:34:09 | D | Attempting to release lock 23438309350752 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 19:34:09 | D | Lock 23438309350752 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 19:34:22 | D | - Quantizing layer model.layers.0 +24-11-19 19:34:22 | D | - Calibrating model.layers.0.self_attn.v_proj.input +24-11-19 19:34:22 | D | - Calibrating model.layers.0.self_attn.k_rotary_emb.output +24-11-19 19:34:22 | D | + w: None +24-11-19 19:34:22 | D | + x: None +24-11-19 19:34:22 | D | + y: sint8 +24-11-19 19:34:22 | E | === Error === +24-11-19 19:34:22 | E | Traceback (most recent call last): +24-11-19 19:34:22 | E | File "/home/yujunlin/projects/deepcompressor/llm/deepcompressor/app/llm/ptq.py", line 384, in +24-11-19 19:34:22 | E | main(config, logging_level=tools.logging.DEBUG) +24-11-19 19:34:22 | E | File "/home/yujunlin/projects/deepcompressor/llm/deepcompressor/app/llm/ptq.py", line 352, in main +24-11-19 19:34:22 | E | model = ptq( +24-11-19 19:34:22 | E | ^^^^ +24-11-19 19:34:22 | E | File "/home/yujunlin/projects/deepcompressor/llm/deepcompressor/app/llm/ptq.py", line 290, in ptq +24-11-19 19:34:22 | E | quantizer_state_dict = quantize_llm_activations( +24-11-19 19:34:22 | E | ^^^^^^^^^^^^^^^^^^^^^^^^^ +24-11-19 19:34:22 | E | File "/home/yujunlin/miniconda3/envs/llm/lib/python3.12/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context +24-11-19 19:34:22 | E | return func(*args, **kwargs) +24-11-19 19:34:22 | E | ^^^^^^^^^^^^^^^^^^^^^ +24-11-19 19:34:22 | E | File "/home/yujunlin/projects/deepcompressor/llm/deepcompressor/app/llm/quant/activation.py", line 238, in quantize_llm_activations +24-11-19 19:34:22 | E | quantize_llm_layer_activations( +24-11-19 19:34:22 | E | File "/home/yujunlin/miniconda3/envs/llm/lib/python3.12/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context +24-11-19 19:34:22 | E | return func(*args, **kwargs) +24-11-19 19:34:22 | E | ^^^^^^^^^^^^^^^^^^^^^ +24-11-19 19:34:22 | E | File "/home/yujunlin/projects/deepcompressor/llm/deepcompressor/app/llm/quant/activation.py", line 153, in quantize_llm_layer_activations +24-11-19 19:34:22 | E | quantizer.calibrate_dynamic_range( +24-11-19 19:34:22 | E | File "/home/yujunlin/projects/deepcompressor/llm/deepcompressor/app/llm/quant/quantizer/quantizer.py", line 113, in calibrate_dynamic_range +24-11-19 19:34:22 | E | self.dynamic_range = calibrate_dynamic_range( +24-11-19 19:34:22 | E | ^^^^^^^^^^^^^^^^^^^^^^^^ +24-11-19 19:34:22 | E | File "/home/yujunlin/projects/deepcompressor/llm/deepcompressor/calib/range.py", line 395, in calibrate_dynamic_range +24-11-19 19:34:22 | E | ).calibrate( +24-11-19 19:34:22 | E | ^^^^^^^^^^ +24-11-19 19:34:22 | E | File "/home/yujunlin/projects/deepcompressor/llm/deepcompressor/calib/search.py", line 616, in calibrate +24-11-19 19:34:22 | E | ) = self._parse_args( +24-11-19 19:34:22 | E | ^^^^^^^^^^^^^^^^^ +24-11-19 19:34:22 | E | File "/home/yujunlin/projects/deepcompressor/llm/deepcompressor/calib/search.py", line 351, in _parse_args +24-11-19 19:34:22 | E | assert all( +24-11-19 19:34:22 | E | ^^^^ +24-11-19 19:34:22 | E | File "/home/yujunlin/projects/deepcompressor/llm/deepcompressor/calib/search.py", line 352, in +24-11-19 19:34:22 | E | p is w for (p, _), w in zip(orig_y_wgts, y_wgts, strict=False) +24-11-19 19:34:22 | E | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +24-11-19 19:34:22 | E | ValueError: zip() argument 2 is shorter than argument 1 +24-11-19 19:34:22 | E | diff --git a/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200548/run-241119.200548.log b/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200548/run-241119.200548.log new file mode 100644 index 0000000000000000000000000000000000000000..17bde528b6c93df1d9c5ad05d5e6c079f883044e --- /dev/null +++ b/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200548/run-241119.200548.log @@ -0,0 +1,1323 @@ +24-11-19 20:05:48 | I | === Configurations === +24-11-19 20:05:48 | I | LlmPtqRunConfig( +24-11-19 20:05:48 | I | cache=LlmCacheConfig( +24-11-19 20:05:48 | I | root=runs/shang, +24-11-19 20:05:48 | I | dirpath=LlmQuantCacheConfig( +24-11-19 20:05:48 | I | rotation=runs/shang/llm/cache/quant/rotation/hadamard, +24-11-19 20:05:48 | I | reorder=, +24-11-19 20:05:48 | I | smooth=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2, +24-11-19 20:05:48 | I | wgts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[], +24-11-19 20:05:48 | I | acts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]), +24-11-19 20:05:48 | I | path=LlmQuantCacheConfig( +24-11-19 20:05:48 | I | rotation=runs/shang/llm/cache/quant/rotation/hadamard/llama-2-7b-instruct-together-32k.pt, +24-11-19 20:05:48 | I | reorder=, +24-11-19 20:05:48 | I | smooth=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/llama-2-7b-instruct-together-32k.pt, +24-11-19 20:05:48 | I | wgts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-2-7b-instruct-together-32k.pt, +24-11-19 20:05:48 | I | acts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-2-7b-instruct-together-32k.pt)), +24-11-19 20:05:48 | I | output=OutputConfig( +24-11-19 20:05:48 | I | root=runs/shang, +24-11-19 20:05:48 | I | dirname=skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0], +24-11-19 20:05:48 | I | job=run, +24-11-19 20:05:48 | I | dirpath=runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0], +24-11-19 20:05:48 | I | timestamp=241119.200548), +24-11-19 20:05:48 | I | model=LlmModelConfig( +24-11-19 20:05:48 | I | name=llama-2-7b-instruct-together-32k, +24-11-19 20:05:48 | I | family=llama-2, +24-11-19 20:05:48 | I | path=/home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k, +24-11-19 20:05:48 | I | root=, +24-11-19 20:05:48 | I | local_path=/home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k, +24-11-19 20:05:48 | I | local_root=/home/yujunlin/models, +24-11-19 20:05:48 | I | size=7.0, +24-11-19 20:05:48 | I | variant=instruct-together-32k, +24-11-19 20:05:48 | I | dtype=torch.float16, +24-11-19 20:05:48 | I | orig_dtype=torch.float16), +24-11-19 20:05:48 | I | eval=LlmEvalConfig( +24-11-19 20:05:48 | I | num_gpus=1, +24-11-19 20:05:48 | I | batch_size=8, +24-11-19 20:05:48 | I | tasks=['wikitext'], +24-11-19 20:05:48 | I | max_seq_length=-4096, +24-11-19 20:05:48 | I | evaluators=['gptq']), +24-11-19 20:05:48 | I | quant=LlmQuantConfig( +24-11-19 20:05:48 | I | wgts=LlmWeightQuantizerConfig( +24-11-19 20:05:48 | I | dtype=sint8, +24-11-19 20:05:48 | I | zero_point=None, +24-11-19 20:05:48 | I | group_shapes=((1, -1, -1),), +24-11-19 20:05:48 | I | scale_dtypes=(torch.float16,), +24-11-19 20:05:48 | I | intermediate_dtypes=(), +24-11-19 20:05:48 | I | intermediate_levels=(), +24-11-19 20:05:48 | I | needs_dequant_saturation=False, +24-11-19 20:05:48 | I | skips=[], +24-11-19 20:05:48 | I | static=True, +24-11-19 20:05:48 | I | kernel_gptq=QuantGptqConfig( +24-11-19 20:05:48 | I | damp_percentage=0.01, +24-11-19 20:05:48 | I | block_size=128, +24-11-19 20:05:48 | I | num_inv_tries=250, +24-11-19 20:05:48 | I | hessian_block_size=512), +24-11-19 20:05:48 | I | calib_range=SkipBasedDynamicRangeCalibConfig( +24-11-19 20:05:48 | I | degree=2, +24-11-19 20:05:48 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 20:05:48 | I | strategy=SearchBasedCalibStrategy.GridSearch, +24-11-19 20:05:48 | I | granularity=SearchBasedCalibGranularity.Group, +24-11-19 20:05:48 | I | element_batch_size=64, +24-11-19 20:05:48 | I | sample_batch_size=-1, +24-11-19 20:05:48 | I | element_size=512, +24-11-19 20:05:48 | I | sample_size=-1, +24-11-19 20:05:48 | I | pre_reshape=True, +24-11-19 20:05:48 | I | outputs_device=cpu, +24-11-19 20:05:48 | I | ratio=1.0, +24-11-19 20:05:48 | I | max_shrink=0.2, +24-11-19 20:05:48 | I | max_expand=1.0, +24-11-19 20:05:48 | I | num_grids=80, +24-11-19 20:05:48 | I | allow_scale=False, +24-11-19 20:05:48 | I | skips=[])), +24-11-19 20:05:48 | I | ipts=LlmActivationQuantizerConfig( +24-11-19 20:05:48 | I | dtype=sint8, +24-11-19 20:05:48 | I | zero_point=None, +24-11-19 20:05:48 | I | group_shapes=((1, -1, -1),), +24-11-19 20:05:48 | I | scale_dtypes=(torch.float16,), +24-11-19 20:05:48 | I | intermediate_dtypes=(), +24-11-19 20:05:48 | I | intermediate_levels=(), +24-11-19 20:05:48 | I | needs_dequant_saturation=False, +24-11-19 20:05:48 | I | skips=[], +24-11-19 20:05:48 | I | static=False, +24-11-19 20:05:48 | I | kernel_gptq=None, +24-11-19 20:05:48 | I | calib_range=None), +24-11-19 20:05:48 | I | opts=LlmActivationQuantizerConfig( +24-11-19 20:05:48 | I | dtype=sint8, +24-11-19 20:05:48 | I | zero_point=None, +24-11-19 20:05:48 | I | group_shapes=((-1, -1, -1),), +24-11-19 20:05:48 | I | scale_dtypes=(torch.float16,), +24-11-19 20:05:48 | I | intermediate_dtypes=(), +24-11-19 20:05:48 | I | intermediate_levels=(), +24-11-19 20:05:48 | I | needs_dequant_saturation=False, +24-11-19 20:05:48 | I | skips=['attn_q'], +24-11-19 20:05:48 | I | static=True, +24-11-19 20:05:48 | I | kernel_gptq=None, +24-11-19 20:05:48 | I | calib_range=SkipBasedDynamicRangeCalibConfig( +24-11-19 20:05:48 | I | degree=2, +24-11-19 20:05:48 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 20:05:48 | I | strategy=SearchBasedCalibStrategy.Manual, +24-11-19 20:05:48 | I | granularity=SearchBasedCalibGranularity.Layer, +24-11-19 20:05:48 | I | element_batch_size=-1, +24-11-19 20:05:48 | I | sample_batch_size=-1, +24-11-19 20:05:48 | I | element_size=-1, +24-11-19 20:05:48 | I | sample_size=-1, +24-11-19 20:05:48 | I | pre_reshape=True, +24-11-19 20:05:48 | I | outputs_device=cpu, +24-11-19 20:05:48 | I | ratio=1.0, +24-11-19 20:05:48 | I | max_shrink=0.2, +24-11-19 20:05:48 | I | max_expand=1.0, +24-11-19 20:05:48 | I | num_grids=80, +24-11-19 20:05:48 | I | allow_scale=False, +24-11-19 20:05:48 | I | skips=[])), +24-11-19 20:05:48 | I | calib=LlmCalibDataLoaderConfig( +24-11-19 20:05:48 | I | data=pileval, +24-11-19 20:05:48 | I | num_samples=128, +24-11-19 20:05:48 | I | batch_size=1, +24-11-19 20:05:48 | I | path=mit-han-lab/pile-val-backup, +24-11-19 20:05:48 | I | seq_length=1024, +24-11-19 20:05:48 | I | min_seq_length=0, +24-11-19 20:05:48 | I | max_seq_length=0, +24-11-19 20:05:48 | I | local_path=), +24-11-19 20:05:48 | I | rotation=QuantRotationConfig( +24-11-19 20:05:48 | I | random=False, +24-11-19 20:05:48 | I | transforms=['out_proj']), +24-11-19 20:05:48 | I | reorder=None, +24-11-19 20:05:48 | I | smooth=SmoothTransfomerConfig( +24-11-19 20:05:48 | I | proj=None, +24-11-19 20:05:48 | I | attn=SmoothAttentionCalibConfig( +24-11-19 20:05:48 | I | degree=2, +24-11-19 20:05:48 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 20:05:48 | I | strategy=SearchBasedCalibStrategy.GridSearch, +24-11-19 20:05:48 | I | granularity=SearchBasedCalibGranularity.Layer, +24-11-19 20:05:48 | I | element_batch_size=-1, +24-11-19 20:05:48 | I | sample_batch_size=-1, +24-11-19 20:05:48 | I | element_size=-1, +24-11-19 20:05:48 | I | sample_size=-1, +24-11-19 20:05:48 | I | pre_reshape=True, +24-11-19 20:05:48 | I | outputs_device=cpu, +24-11-19 20:05:48 | I | allow_a_quant=True, +24-11-19 20:05:48 | I | allow_b_quant=True, +24-11-19 20:05:48 | I | spans=[(, )], +24-11-19 20:05:48 | I | a_spans=[], +24-11-19 20:05:48 | I | b_spans=[], +24-11-19 20:05:48 | I | alpha=0.5, +24-11-19 20:05:48 | I | beta=-2, +24-11-19 20:05:48 | I | num_grids=20, +24-11-19 20:05:48 | I | allow_low_rank=False)), +24-11-19 20:05:48 | I | develop_dtype=torch.float32), +24-11-19 20:05:48 | I | seed=12345, +24-11-19 20:05:48 | I | skip_eval=False, +24-11-19 20:05:48 | I | load_from=, +24-11-19 20:05:48 | I | save_model=true, +24-11-19 20:05:48 | I | copy_on_save=False) +24-11-19 20:05:48 | I | === Dumped Configurations === +24-11-19 20:05:48 | I | { 'cache': { 'path': { 'acts': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-2-7b-instruct-together-32k.pt', +24-11-19 20:05:48 | I | 'reorder': '', +24-11-19 20:05:48 | I | 'rotation': 'runs/shang/llm/cache/quant/rotation/hadamard/llama-2-7b-instruct-together-32k.pt', +24-11-19 20:05:48 | I | 'smooth': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/llama-2-7b-instruct-together-32k.pt', +24-11-19 20:05:48 | I | 'wgts': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-2-7b-instruct-together-32k.pt'}, +24-11-19 20:05:48 | I | 'root': 'runs/shang'}, +24-11-19 20:05:48 | I | 'copy_on_save': False, +24-11-19 20:05:48 | I | 'eval': {'batch_size': 8, 'evaluators': ['gptq'], 'max_seq_length': -4096, 'num_gpus': 1, 'tasks': ['wikitext']}, +24-11-19 20:05:48 | I | 'load_from': '', +24-11-19 20:05:48 | I | 'model': { 'dtype': 'torch.float16', +24-11-19 20:05:48 | I | 'family': 'llama-2', +24-11-19 20:05:48 | I | 'local_path': '/home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k', +24-11-19 20:05:48 | I | 'local_root': '/home/yujunlin/models', +24-11-19 20:05:48 | I | 'name': 'llama-2-7b-instruct-together-32k', +24-11-19 20:05:48 | I | 'path': '/home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k', +24-11-19 20:05:48 | I | 'root': ''}, +24-11-19 20:05:48 | I | 'output': { 'dirname': 'skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]', +24-11-19 20:05:48 | I | 'job': 'run', +24-11-19 20:05:48 | I | 'root': 'runs/shang'}, +24-11-19 20:05:48 | I | 'quant': { 'calib': { 'data': 'pileval', +24-11-19 20:05:48 | I | 'local_path': '', +24-11-19 20:05:48 | I | 'max_seq_length': 0, +24-11-19 20:05:48 | I | 'min_seq_length': 0, +24-11-19 20:05:48 | I | 'num_samples': 128, +24-11-19 20:05:48 | I | 'path': 'mit-han-lab/pile-val-backup', +24-11-19 20:05:48 | I | 'seq_length': 1024}, +24-11-19 20:05:48 | I | 'develop_dtype': 'torch.float32', +24-11-19 20:05:48 | I | 'enable_reorder': False, +24-11-19 20:05:48 | I | 'enable_rotation': True, +24-11-19 20:05:48 | I | 'enable_smooth': True, +24-11-19 20:05:48 | I | 'ipts': { 'dtype': 'sint8', +24-11-19 20:05:48 | I | 'enable_calib_range': False, +24-11-19 20:05:48 | I | 'group_shapes': [[1, -1, -1]], +24-11-19 20:05:48 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 20:05:48 | I | 'skips': [], +24-11-19 20:05:48 | I | 'static': False, +24-11-19 20:05:48 | I | 'zero_point': None}, +24-11-19 20:05:48 | I | 'opts': { 'calib_range': { 'allow_scale': False, +24-11-19 20:05:48 | I | 'degree': 2, +24-11-19 20:05:48 | I | 'element_batch_size': -1, +24-11-19 20:05:48 | I | 'element_size': -1, +24-11-19 20:05:48 | I | 'granularity': 'Layer', +24-11-19 20:05:48 | I | 'max_expand': 1.0, +24-11-19 20:05:48 | I | 'max_shrink': 0.2, +24-11-19 20:05:48 | I | 'num_grids': 80, +24-11-19 20:05:48 | I | 'objective': 'OutputsError', +24-11-19 20:05:48 | I | 'outputs_device': 'cpu', +24-11-19 20:05:48 | I | 'pre_reshape': True, +24-11-19 20:05:48 | I | 'ratio': 1.0, +24-11-19 20:05:48 | I | 'sample_batch_size': -1, +24-11-19 20:05:48 | I | 'sample_size': -1, +24-11-19 20:05:48 | I | 'skips': [], +24-11-19 20:05:48 | I | 'strategy': 'Manual'}, +24-11-19 20:05:48 | I | 'dtype': 'sint8', +24-11-19 20:05:48 | I | 'enable_calib_range': True, +24-11-19 20:05:48 | I | 'group_shapes': [[-1, -1, -1]], +24-11-19 20:05:48 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 20:05:48 | I | 'skips': ['attn_q'], +24-11-19 20:05:48 | I | 'static': True, +24-11-19 20:05:48 | I | 'zero_point': None}, +24-11-19 20:05:48 | I | 'rotation': {'random': False, 'transforms': ['out_proj']}, +24-11-19 20:05:48 | I | 'smooth': { 'attn': { 'allow_a_quant': True, +24-11-19 20:05:48 | I | 'allow_b_quant': True, +24-11-19 20:05:48 | I | 'alpha': 0.5, +24-11-19 20:05:48 | I | 'beta': -2, +24-11-19 20:05:48 | I | 'degree': 2, +24-11-19 20:05:48 | I | 'num_grids': 20, +24-11-19 20:05:48 | I | 'outputs_device': 'cpu', +24-11-19 20:05:48 | I | 'sample_batch_size': -1, +24-11-19 20:05:48 | I | 'sample_size': -1, +24-11-19 20:05:48 | I | 'spans': [['AbsMax', 'AbsMax']], +24-11-19 20:05:48 | I | 'strategy': 'GridSearch'}, +24-11-19 20:05:48 | I | 'enable_attn': True, +24-11-19 20:05:48 | I | 'enable_proj': False}, +24-11-19 20:05:48 | I | 'wgts': { 'calib_range': { 'allow_scale': False, +24-11-19 20:05:48 | I | 'degree': 2, +24-11-19 20:05:48 | I | 'element_batch_size': 64, +24-11-19 20:05:48 | I | 'element_size': 512, +24-11-19 20:05:48 | I | 'granularity': 'Group', +24-11-19 20:05:48 | I | 'max_expand': 1.0, +24-11-19 20:05:48 | I | 'max_shrink': 0.2, +24-11-19 20:05:48 | I | 'num_grids': 80, +24-11-19 20:05:48 | I | 'objective': 'OutputsError', +24-11-19 20:05:48 | I | 'outputs_device': 'cpu', +24-11-19 20:05:48 | I | 'pre_reshape': True, +24-11-19 20:05:48 | I | 'ratio': 1.0, +24-11-19 20:05:48 | I | 'sample_batch_size': -1, +24-11-19 20:05:48 | I | 'sample_size': -1, +24-11-19 20:05:48 | I | 'skips': [], +24-11-19 20:05:48 | I | 'strategy': 'GridSearch'}, +24-11-19 20:05:48 | I | 'dtype': 'sint8', +24-11-19 20:05:48 | I | 'enable_calib_range': True, +24-11-19 20:05:48 | I | 'enable_kernel_gptq': True, +24-11-19 20:05:48 | I | 'group_shapes': [[1, -1, -1]], +24-11-19 20:05:48 | I | 'intermediate_dtypes': [], +24-11-19 20:05:48 | I | 'intermediate_levels': [], +24-11-19 20:05:48 | I | 'kernel_gptq': { 'block_size': 128, +24-11-19 20:05:48 | I | 'damp_percentage': 0.01, +24-11-19 20:05:48 | I | 'hessian_block_size': 512, +24-11-19 20:05:48 | I | 'num_inv_tries': 250}, +24-11-19 20:05:48 | I | 'needs_dequant_saturation': False, +24-11-19 20:05:48 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 20:05:48 | I | 'skips': [], +24-11-19 20:05:48 | I | 'zero_point': None}}, +24-11-19 20:05:48 | I | 'save_model': 'true', +24-11-19 20:05:48 | I | 'seed': 12345, +24-11-19 20:05:48 | I | 'skip_eval': False} +24-11-19 20:05:48 | I | === Output Directory === +24-11-19 20:05:48 | I | runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200548 +24-11-19 20:05:48 | I | === Start Evaluating === +24-11-19 20:05:48 | I | * Building model llama-2-7b-instruct-together-32k from /home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k +24-11-19 20:05:48 | I | We will use 90% of the memory on device 0 for storing the model, and 10% for the buffer to avoid OOM. You can set `max_memory` in to a higher value to use more memory (at your own risk). +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.0.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.1.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.2.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.3.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.4.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.5.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.6.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.7.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.8.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.9.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.10.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.11.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.12.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.13.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.14.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.15.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.16.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.17.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.18.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.19.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.20.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.21.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.22.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.23.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.24.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.25.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.26.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.27.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.28.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.29.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.30.self_attn +24-11-19 20:05:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.31.self_attn +24-11-19 20:05:52 | I | * Rotating model +24-11-19 20:05:52 | I | - Loading rotation from runs/shang/llm/cache/quant/rotation/hadamard/llama-2-7b-instruct-together-32k.pt +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.0 +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.1 +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.2 +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.3 +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.4 +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.5 +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.6 +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.7 +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.8 +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.9 +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.10 +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.11 +24-11-19 20:05:54 | D | - Transforming norm and linear in model.layers.12 +24-11-19 20:05:54 | D | - Transforming norm and linear in model.layers.13 +24-11-19 20:05:54 | D | - Transforming norm and linear in model.layers.14 +24-11-19 20:05:54 | D | - Transforming norm and linear in model.layers.15 +24-11-19 20:05:54 | D | - Transforming norm and linear in model.layers.16 +24-11-19 20:05:54 | D | - Transforming norm and linear in model.layers.17 +24-11-19 20:05:54 | D | - Transforming norm and linear in model.layers.18 +24-11-19 20:05:54 | D | - Transforming norm and linear in model.layers.19 +24-11-19 20:05:54 | D | - Transforming norm and linear in model.layers.20 +24-11-19 20:05:54 | D | - Transforming norm and linear in model.layers.21 +24-11-19 20:05:54 | D | - Transforming norm and linear in model.layers.22 +24-11-19 20:05:54 | D | - Transforming norm and linear in model.layers.23 +24-11-19 20:05:54 | D | - Transforming norm and linear in model.layers.24 +24-11-19 20:05:55 | D | - Transforming norm and linear in model.layers.25 +24-11-19 20:05:55 | D | - Transforming norm and linear in model.layers.26 +24-11-19 20:05:55 | D | - Transforming norm and linear in model.layers.27 +24-11-19 20:05:55 | D | - Transforming norm and linear in model.layers.28 +24-11-19 20:05:55 | D | - Transforming norm and linear in model.layers.29 +24-11-19 20:05:55 | D | - Transforming norm and linear in model.layers.30 +24-11-19 20:05:55 | D | - Transforming norm and linear in model.layers.31 +24-11-19 20:05:55 | D | - Transforming model.norm +24-11-19 20:05:55 | D | - Rotating model.embed_tokens +24-11-19 20:05:55 | D | - Rotating model.layers.0 +24-11-19 20:05:55 | D | - Rotating model.layers.0.self_attn.q_proj (in) +24-11-19 20:05:55 | D | - Rotating model.layers.0.self_attn.k_proj (in) +24-11-19 20:05:55 | D | - Rotating model.layers.0.self_attn.v_proj (in) +24-11-19 20:05:55 | D | - Rotating model.layers.0.self_attn.o_proj (out) +24-11-19 20:05:55 | D | - Rotating model.layers.0.self_attn.v_proj (out) +24-11-19 20:05:55 | D | - Rotating model.layers.0.self_attn.o_proj (in) +24-11-19 20:05:55 | D | - Rotating model.layers.0.mlp.up_proj (in) +24-11-19 20:05:55 | D | - Rotating model.layers.0.mlp.gate_proj (in) +24-11-19 20:05:55 | D | - Rotating model.layers.0.mlp.down_proj (out) +24-11-19 20:05:55 | D | - Rotating model.layers.1 +24-11-19 20:05:55 | D | - Rotating model.layers.1.self_attn.q_proj (in) +24-11-19 20:05:55 | D | - Rotating model.layers.1.self_attn.k_proj (in) +24-11-19 20:05:55 | D | - Rotating model.layers.1.self_attn.v_proj (in) +24-11-19 20:05:55 | D | - Rotating model.layers.1.self_attn.o_proj (out) +24-11-19 20:05:55 | D | - Rotating model.layers.1.self_attn.v_proj (out) +24-11-19 20:05:55 | D | - Rotating model.layers.1.self_attn.o_proj (in) +24-11-19 20:05:55 | D | - Rotating model.layers.1.mlp.up_proj (in) +24-11-19 20:05:55 | D | - Rotating model.layers.1.mlp.gate_proj (in) +24-11-19 20:05:55 | D | - Rotating model.layers.1.mlp.down_proj (out) +24-11-19 20:05:55 | D | - Rotating model.layers.2 +24-11-19 20:05:55 | D | - Rotating model.layers.2.self_attn.q_proj (in) +24-11-19 20:05:55 | D | - Rotating model.layers.2.self_attn.k_proj (in) +24-11-19 20:05:55 | D | - Rotating model.layers.2.self_attn.v_proj (in) +24-11-19 20:05:55 | D | - Rotating model.layers.2.self_attn.o_proj (out) +24-11-19 20:05:55 | D | - Rotating model.layers.2.self_attn.v_proj (out) +24-11-19 20:05:55 | D | - Rotating model.layers.2.self_attn.o_proj (in) +24-11-19 20:05:55 | D | - Rotating model.layers.2.mlp.up_proj (in) +24-11-19 20:05:55 | D | - Rotating model.layers.2.mlp.gate_proj (in) +24-11-19 20:05:55 | D | - Rotating model.layers.2.mlp.down_proj (out) +24-11-19 20:05:55 | D | - Rotating model.layers.3 +24-11-19 20:05:55 | D | - Rotating model.layers.3.self_attn.q_proj (in) +24-11-19 20:05:55 | D | - Rotating model.layers.3.self_attn.k_proj (in) +24-11-19 20:05:55 | D | - Rotating model.layers.3.self_attn.v_proj (in) +24-11-19 20:05:55 | D | - Rotating model.layers.3.self_attn.o_proj (out) +24-11-19 20:05:55 | D | - Rotating model.layers.3.self_attn.v_proj (out) +24-11-19 20:05:55 | D | - Rotating model.layers.3.self_attn.o_proj (in) +24-11-19 20:05:55 | D | - Rotating model.layers.3.mlp.up_proj (in) +24-11-19 20:05:55 | D | - Rotating model.layers.3.mlp.gate_proj (in) +24-11-19 20:05:55 | D | - Rotating model.layers.3.mlp.down_proj (out) +24-11-19 20:05:56 | D | - Rotating model.layers.4 +24-11-19 20:05:56 | D | - Rotating model.layers.4.self_attn.q_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.4.self_attn.k_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.4.self_attn.v_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.4.self_attn.o_proj (out) +24-11-19 20:05:56 | D | - Rotating model.layers.4.self_attn.v_proj (out) +24-11-19 20:05:56 | D | - Rotating model.layers.4.self_attn.o_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.4.mlp.up_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.4.mlp.gate_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.4.mlp.down_proj (out) +24-11-19 20:05:56 | D | - Rotating model.layers.5 +24-11-19 20:05:56 | D | - Rotating model.layers.5.self_attn.q_proj (in) +24-11-19 20:05:56 | D | - 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Rotating model.layers.27.self_attn.v_proj (out) +24-11-19 20:05:57 | D | - Rotating model.layers.27.self_attn.o_proj (in) +24-11-19 20:05:57 | D | - Rotating model.layers.27.mlp.up_proj (in) +24-11-19 20:05:57 | D | - Rotating model.layers.27.mlp.gate_proj (in) +24-11-19 20:05:57 | D | - Rotating model.layers.27.mlp.down_proj (out) +24-11-19 20:05:58 | D | - Rotating model.layers.28 +24-11-19 20:05:58 | D | - Rotating model.layers.28.self_attn.q_proj (in) +24-11-19 20:05:58 | D | - Rotating model.layers.28.self_attn.k_proj (in) +24-11-19 20:05:58 | D | - Rotating model.layers.28.self_attn.v_proj (in) +24-11-19 20:05:58 | D | - Rotating model.layers.28.self_attn.o_proj (out) +24-11-19 20:05:58 | D | - Rotating model.layers.28.self_attn.v_proj (out) +24-11-19 20:05:58 | D | - Rotating model.layers.28.self_attn.o_proj (in) +24-11-19 20:05:58 | D | - Rotating model.layers.28.mlp.up_proj (in) +24-11-19 20:05:58 | D | - Rotating model.layers.28.mlp.gate_proj (in) +24-11-19 20:05:58 | D | - Rotating model.layers.28.mlp.down_proj (out) +24-11-19 20:05:58 | D | - Rotating model.layers.29 +24-11-19 20:05:58 | D | - Rotating model.layers.29.self_attn.q_proj (in) +24-11-19 20:05:58 | D | - Rotating model.layers.29.self_attn.k_proj (in) +24-11-19 20:05:58 | D | - Rotating model.layers.29.self_attn.v_proj (in) +24-11-19 20:05:58 | D | - Rotating model.layers.29.self_attn.o_proj (out) +24-11-19 20:05:58 | D | - Rotating model.layers.29.self_attn.v_proj (out) +24-11-19 20:05:58 | D | - Rotating model.layers.29.self_attn.o_proj (in) +24-11-19 20:05:58 | D | - Rotating model.layers.29.mlp.up_proj (in) +24-11-19 20:05:58 | D | - Rotating model.layers.29.mlp.gate_proj (in) +24-11-19 20:05:58 | D | - Rotating model.layers.29.mlp.down_proj (out) +24-11-19 20:05:58 | D | - Rotating model.layers.30 +24-11-19 20:05:58 | D | - Rotating model.layers.30.self_attn.q_proj (in) +24-11-19 20:05:58 | D | - Rotating model.layers.30.self_attn.k_proj (in) +24-11-19 20:05:58 | D | - Rotating model.layers.30.self_attn.v_proj (in) +24-11-19 20:05:58 | D | - Rotating model.layers.30.self_attn.o_proj (out) +24-11-19 20:05:58 | D | - Rotating model.layers.30.self_attn.v_proj (out) +24-11-19 20:05:58 | D | - Rotating model.layers.30.self_attn.o_proj (in) +24-11-19 20:05:58 | D | - Rotating model.layers.30.mlp.up_proj (in) +24-11-19 20:05:58 | D | - Rotating model.layers.30.mlp.gate_proj (in) +24-11-19 20:05:58 | D | - Rotating model.layers.30.mlp.down_proj (out) +24-11-19 20:05:58 | D | - Rotating model.layers.31 +24-11-19 20:05:58 | D | - Rotating model.layers.31.self_attn.q_proj (in) +24-11-19 20:05:58 | D | - Rotating model.layers.31.self_attn.k_proj (in) +24-11-19 20:05:58 | D | - Rotating model.layers.31.self_attn.v_proj (in) +24-11-19 20:05:58 | D | - Rotating model.layers.31.self_attn.o_proj (out) +24-11-19 20:05:58 | D | - Rotating model.layers.31.self_attn.v_proj (out) +24-11-19 20:05:58 | D | - Rotating model.layers.31.self_attn.o_proj (in) +24-11-19 20:05:58 | D | - Rotating model.layers.31.mlp.up_proj (in) +24-11-19 20:05:58 | D | - Rotating model.layers.31.mlp.gate_proj (in) +24-11-19 20:05:58 | D | - Rotating model.layers.31.mlp.down_proj (out) +24-11-19 20:05:58 | D | - Rotating lm_head (in) +24-11-19 20:05:58 | I | - Linking rotation to runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200548.RUNNING/model/rotation.pt +24-11-19 20:05:58 | I | * Development dtype is torch.float32 +24-11-19 20:05:58 | I | * Smoothing model for quantization +24-11-19 20:05:58 | I | - Loading smooth scales from runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/llama-2-7b-instruct-together-32k.pt +24-11-19 20:05:58 | D | - Smoothing model.layers.0 +24-11-19 20:05:58 | D | - model.layers.0.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.1 +24-11-19 20:05:58 | D | - model.layers.1.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.2 +24-11-19 20:05:58 | D | - model.layers.2.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.3 +24-11-19 20:05:58 | D | - model.layers.3.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.4 +24-11-19 20:05:58 | D | - model.layers.4.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.5 +24-11-19 20:05:58 | D | - model.layers.5.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.6 +24-11-19 20:05:58 | D | - model.layers.6.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.7 +24-11-19 20:05:58 | D | - model.layers.7.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.8 +24-11-19 20:05:58 | D | - model.layers.8.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.9 +24-11-19 20:05:58 | D | - model.layers.9.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.10 +24-11-19 20:05:58 | D | - model.layers.10.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.11 +24-11-19 20:05:58 | D | - model.layers.11.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.12 +24-11-19 20:05:58 | D | - model.layers.12.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.13 +24-11-19 20:05:58 | D | - model.layers.13.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.14 +24-11-19 20:05:58 | D | - model.layers.14.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.15 +24-11-19 20:05:58 | D | - model.layers.15.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.16 +24-11-19 20:05:58 | D | - model.layers.16.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.17 +24-11-19 20:05:58 | D | - model.layers.17.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.18 +24-11-19 20:05:58 | D | - model.layers.18.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.19 +24-11-19 20:05:58 | D | - model.layers.19.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.20 +24-11-19 20:05:58 | D | - model.layers.20.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.21 +24-11-19 20:05:58 | D | - model.layers.21.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.22 +24-11-19 20:05:58 | D | - model.layers.22.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.23 +24-11-19 20:05:58 | D | - model.layers.23.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.24 +24-11-19 20:05:58 | D | - model.layers.24.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.25 +24-11-19 20:05:58 | D | - model.layers.25.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.26 +24-11-19 20:05:58 | D | - model.layers.26.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.27 +24-11-19 20:05:58 | D | - model.layers.27.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.28 +24-11-19 20:05:58 | D | - model.layers.28.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.29 +24-11-19 20:05:58 | D | - model.layers.29.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.30 +24-11-19 20:05:58 | D | - model.layers.30.self_attn.attn_k +24-11-19 20:05:58 | D | - Smoothing model.layers.31 +24-11-19 20:05:58 | D | - model.layers.31.self_attn.attn_k +24-11-19 20:05:58 | I | - Linking smooth scales to runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200548.RUNNING/model/smooth.pt +24-11-19 20:05:58 | I | * Quantizing weights +24-11-19 20:05:58 | I | - Loading weight quantizer settings from runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-2-7b-instruct-together-32k.pt +24-11-19 20:05:58 | D | Starting new HTTPS connection (1): huggingface.co:443 +24-11-19 20:06:38 | D | Starting new HTTPS connection (2): huggingface.co:443 +24-11-19 20:06:55 | D | Starting new HTTPS connection (1): s3.amazonaws.com:443 +24-11-19 20:07:13 | W | Repo card metadata block was not found. Setting CardData to empty. +24-11-19 20:07:13 | D | Starting new HTTPS connection (3): huggingface.co:443 +24-11-19 20:07:25 | W | Using the latest cached version of the dataset since mit-han-lab/pile-val-backup couldn't be found on the Hugging Face Hub +24-11-19 20:07:25 | W | Found the latest cached dataset configuration 'default' at /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4 (last modified on Tue Oct 8 18:58:39 2024). +24-11-19 20:07:25 | D | Attempting to acquire lock 23438951268128 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:07:25 | D | Lock 23438951268128 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:07:25 | D | open file: /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4/dataset_info.json +24-11-19 20:07:25 | D | Attempting to release lock 23438951268128 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:07:25 | D | Lock 23438951268128 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:07:39 | D | - Quantizing layer model.layers.0 +24-11-19 20:07:39 | D | - Quantizing model.layers.0.self_attn.q_proj.weight +24-11-19 20:07:40 | D | - Quantizing model.layers.0.self_attn.k_proj.weight +24-11-19 20:07:41 | D | - Quantizing model.layers.0.self_attn.v_proj.weight +24-11-19 20:07:42 | D | - Quantizing model.layers.0.self_attn.o_proj.weight +24-11-19 20:07:42 | D | - Quantizing model.layers.0.mlp.up_proj.weight +24-11-19 20:07:43 | D | - Quantizing model.layers.0.mlp.gate_proj.weight +24-11-19 20:07:44 | D | - Quantizing model.layers.0.mlp.down_proj.weight +24-11-19 20:07:53 | D | - Quantizing layer model.layers.1 +24-11-19 20:07:53 | D | - Quantizing model.layers.1.self_attn.q_proj.weight +24-11-19 20:07:54 | D | - Quantizing model.layers.1.self_attn.k_proj.weight +24-11-19 20:07:54 | D | - Quantizing model.layers.1.self_attn.v_proj.weight +24-11-19 20:07:55 | D | - Quantizing model.layers.1.self_attn.o_proj.weight +24-11-19 20:07:56 | D | - Quantizing model.layers.1.mlp.up_proj.weight +24-11-19 20:07:57 | D | - Quantizing model.layers.1.mlp.gate_proj.weight +24-11-19 20:07:58 | D | - Quantizing model.layers.1.mlp.down_proj.weight +24-11-19 20:08:06 | D | - Quantizing layer model.layers.2 +24-11-19 20:08:06 | D | - Quantizing model.layers.2.self_attn.q_proj.weight +24-11-19 20:08:07 | D | - Quantizing model.layers.2.self_attn.k_proj.weight +24-11-19 20:08:08 | D | - Quantizing model.layers.2.self_attn.v_proj.weight +24-11-19 20:08:09 | D | - Quantizing model.layers.2.self_attn.o_proj.weight +24-11-19 20:08:09 | D | - Quantizing model.layers.2.mlp.up_proj.weight +24-11-19 20:08:10 | D | - Quantizing model.layers.2.mlp.gate_proj.weight +24-11-19 20:08:11 | D | - Quantizing model.layers.2.mlp.down_proj.weight +24-11-19 20:08:19 | D | - Quantizing layer model.layers.3 +24-11-19 20:08:19 | D | - Quantizing model.layers.3.self_attn.q_proj.weight +24-11-19 20:08:20 | D | - Quantizing model.layers.3.self_attn.k_proj.weight +24-11-19 20:08:21 | D | - Quantizing model.layers.3.self_attn.v_proj.weight +24-11-19 20:08:22 | D | - Quantizing model.layers.3.self_attn.o_proj.weight +24-11-19 20:08:22 | D | - Quantizing model.layers.3.mlp.up_proj.weight +24-11-19 20:08:23 | D | - Quantizing model.layers.3.mlp.gate_proj.weight +24-11-19 20:08:24 | D | - Quantizing model.layers.3.mlp.down_proj.weight +24-11-19 20:08:32 | D | - Quantizing layer model.layers.4 +24-11-19 20:08:32 | D | - Quantizing model.layers.4.self_attn.q_proj.weight +24-11-19 20:08:33 | D | - Quantizing model.layers.4.self_attn.k_proj.weight +24-11-19 20:08:34 | D | - Quantizing model.layers.4.self_attn.v_proj.weight +24-11-19 20:08:35 | D | - Quantizing model.layers.4.self_attn.o_proj.weight +24-11-19 20:08:35 | D | - Quantizing model.layers.4.mlp.up_proj.weight +24-11-19 20:08:36 | D | - Quantizing model.layers.4.mlp.gate_proj.weight +24-11-19 20:08:37 | D | - Quantizing model.layers.4.mlp.down_proj.weight +24-11-19 20:08:45 | D | - Quantizing layer model.layers.5 +24-11-19 20:08:45 | D | - Quantizing model.layers.5.self_attn.q_proj.weight +24-11-19 20:08:47 | D | - 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Quantizing model.layers.29.mlp.gate_proj.weight +24-11-19 20:14:53 | D | - Quantizing model.layers.29.mlp.down_proj.weight +24-11-19 20:15:02 | D | - Quantizing layer model.layers.30 +24-11-19 20:15:02 | D | - Quantizing model.layers.30.self_attn.q_proj.weight +24-11-19 20:15:02 | D | - Quantizing model.layers.30.self_attn.k_proj.weight +24-11-19 20:15:03 | D | - Quantizing model.layers.30.self_attn.v_proj.weight +24-11-19 20:15:04 | D | - Quantizing model.layers.30.self_attn.o_proj.weight +24-11-19 20:15:05 | D | - Quantizing model.layers.30.mlp.up_proj.weight +24-11-19 20:15:06 | D | - Quantizing model.layers.30.mlp.gate_proj.weight +24-11-19 20:15:07 | D | - Quantizing model.layers.30.mlp.down_proj.weight +24-11-19 20:15:16 | D | - Quantizing layer model.layers.31 +24-11-19 20:15:16 | D | - Quantizing model.layers.31.self_attn.q_proj.weight +24-11-19 20:15:17 | D | - Quantizing model.layers.31.self_attn.k_proj.weight +24-11-19 20:15:18 | D | - Quantizing model.layers.31.self_attn.v_proj.weight +24-11-19 20:15:19 | D | - Quantizing model.layers.31.self_attn.o_proj.weight +24-11-19 20:15:20 | D | - Quantizing model.layers.31.mlp.up_proj.weight +24-11-19 20:15:21 | D | - Quantizing model.layers.31.mlp.gate_proj.weight +24-11-19 20:15:22 | D | - Quantizing model.layers.31.mlp.down_proj.weight +24-11-19 20:15:25 | I | - Linking weight quantizer settings to runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200548.RUNNING/model/wgts.pt +24-11-19 20:15:25 | I | - Saving model checkpoint to runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200548.RUNNING/model +24-11-19 20:15:40 | I | * Quantizing activations +24-11-19 20:15:40 | I | - Loading activation quantizer settings from runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-2-7b-instruct-together-32k.pt +24-11-19 20:15:40 | D | - Quantizing layer model.layers.0 +24-11-19 20:15:40 | D | - Quantizing model.layers.0.self_attn.q_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.0.self_attn.k_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.0.self_attn.v_proj (inputs and outputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.0.self_attn.o_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.0.self_attn.k_rotary_emb (outputs) +24-11-19 20:15:40 | D | - 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Quantizing model.layers.26.self_attn.k_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.26.self_attn.v_proj (inputs and outputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.26.self_attn.o_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.26.self_attn.k_rotary_emb (outputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.26.mlp.gate_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.26.mlp.up_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.26.mlp.down_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing layer model.layers.27 +24-11-19 20:15:40 | D | - Quantizing model.layers.27.self_attn.q_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.27.self_attn.k_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.27.self_attn.v_proj (inputs and outputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.27.self_attn.o_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.27.self_attn.k_rotary_emb (outputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.27.mlp.gate_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.27.mlp.up_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.27.mlp.down_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing layer model.layers.28 +24-11-19 20:15:40 | D | - Quantizing model.layers.28.self_attn.q_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.28.self_attn.k_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.28.self_attn.v_proj (inputs and outputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.28.self_attn.o_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.28.self_attn.k_rotary_emb (outputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.28.mlp.gate_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.28.mlp.up_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.28.mlp.down_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing layer model.layers.29 +24-11-19 20:15:40 | D | - Quantizing model.layers.29.self_attn.q_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.29.self_attn.k_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.29.self_attn.v_proj (inputs and outputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.29.self_attn.o_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.29.self_attn.k_rotary_emb (outputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.29.mlp.gate_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.29.mlp.up_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.29.mlp.down_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing layer model.layers.30 +24-11-19 20:15:40 | D | - Quantizing model.layers.30.self_attn.q_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.30.self_attn.k_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.30.self_attn.v_proj (inputs and outputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.30.self_attn.o_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.30.self_attn.k_rotary_emb (outputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.30.mlp.gate_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.30.mlp.up_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.30.mlp.down_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing layer model.layers.31 +24-11-19 20:15:40 | D | - Quantizing model.layers.31.self_attn.q_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.31.self_attn.k_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.31.self_attn.v_proj (inputs and outputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.31.self_attn.o_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.31.self_attn.k_rotary_emb (outputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.31.mlp.gate_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.31.mlp.up_proj (inputs) +24-11-19 20:15:40 | D | - Quantizing model.layers.31.mlp.down_proj (inputs) +24-11-19 20:15:40 | I | - Linking activation quantizer settings to runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200548.RUNNING/model/acts.pt +24-11-19 20:15:40 | I | * Evaluating model +24-11-19 20:15:40 | W | `pretrained` model kwarg is not of type `str`. Many other model arguments may be ignored. Please do not launch via accelerate or use `parallelize=True` if passing an existing model this way. +24-11-19 20:15:40 | I | Using model type 'default' +24-11-19 20:15:40 | W | Passed an already-initialized model through `pretrained`, assuming single-process call to evaluate() or custom distributed integration +24-11-19 20:15:40 | I | - Evaluator: gptq +24-11-19 20:15:40 | I | - Tasks: ['wikitext'] +24-11-19 20:15:40 | I | - Batch_size: 8 +24-11-19 20:15:40 | I | + Max_seq_length: 2048 +24-11-19 20:15:40 | D | Starting new HTTPS connection (4): huggingface.co:443 +24-11-19 20:16:10 | W | Using the latest cached version of the dataset since wikitext couldn't be found on the Hugging Face Hub +24-11-19 20:16:10 | W | Found the latest cached dataset configuration 'wikitext-2-raw-v1' at /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3 (last modified on Tue Oct 8 19:51:38 2024). +24-11-19 20:16:10 | D | Attempting to acquire lock 23438644455920 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:16:10 | D | Lock 23438644455920 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:16:10 | D | open file: /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3/dataset_info.json +24-11-19 20:16:10 | D | Attempting to release lock 23438644455920 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:16:10 | D | Lock 23438644455920 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:16:48 | I | - Results: +24-11-19 20:16:49 | I | | Task |Version| Metric |Value | |Stderr| +24-11-19 20:16:49 | I | |--------|------:|---------------|-----:|---|-----:| +24-11-19 20:16:49 | I | |wikitext| 1|word_perplexity|6.5038|± |6.5038| +24-11-19 20:16:49 | I | +24-11-19 20:16:49 | I | + Max_seq_length: 4096 +24-11-19 20:16:49 | D | Starting new HTTPS connection (5): huggingface.co:443 +24-11-19 20:17:29 | W | Using the latest cached version of the dataset since wikitext couldn't be found on the Hugging Face Hub +24-11-19 20:17:29 | W | Found the latest cached dataset configuration 'wikitext-2-raw-v1' at /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3 (last modified on Tue Oct 8 19:51:38 2024). +24-11-19 20:17:29 | D | Attempting to acquire lock 23438912816960 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:17:29 | D | Lock 23438912816960 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:17:29 | D | open file: /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3/dataset_info.json +24-11-19 20:17:29 | D | Attempting to release lock 23438912816960 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:17:29 | D | Lock 23438912816960 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:18:01 | I | - Results: +24-11-19 20:18:01 | I | | Task |Version| Metric |Value | |Stderr| +24-11-19 20:18:01 | I | |--------|------:|---------------|-----:|---|-----:| +24-11-19 20:18:01 | I | |wikitext| 1|word_perplexity|6.0144|± |6.0144| +24-11-19 20:18:01 | I | +24-11-19 20:18:01 | I | * Saving results to runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200548 diff --git a/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200727.RUNNING/config-241119.200727.yaml b/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200727.RUNNING/config-241119.200727.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e4d1cdfd1e915e4d62c707f610163901b7aa6fcc --- /dev/null +++ b/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200727.RUNNING/config-241119.200727.yaml @@ -0,0 +1,146 @@ +cache: + root: runs/shang + path: + rotation: runs/shang/llm/cache/quant/rotation/hadamard/llama-2-7b-instruct-together-32k.pt + reorder: '' + smooth: runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/llama-2-7b-instruct-together-32k.pt + wgts: runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-2-7b-instruct-together-32k.pt + acts: runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-2-7b-instruct-together-32k.pt +output: + root: runs/shang + dirname: skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0] + job: run +model: + name: llama-2-7b-instruct-together-32k + family: llama-2 + path: /home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k + root: '' + local_path: /home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k + local_root: /home/yujunlin/models + dtype: torch.float16 +eval: + num_gpus: 1 + batch_size: 8 + tasks: + - wikitext + max_seq_length: -4096 + evaluators: + - gptq +quant: + wgts: + dtype: sint8 + zero_point: null + group_shapes: + - - 1 + - -1 + - -1 + scale_dtypes: + - torch.float16 + intermediate_dtypes: [] + intermediate_levels: [] + needs_dequant_saturation: false + skips: [] + enable_kernel_gptq: true + kernel_gptq: + damp_percentage: 0.01 + block_size: 128 + num_inv_tries: 250 + hessian_block_size: 512 + enable_calib_range: true + calib_range: + degree: 2 + objective: OutputsError + strategy: GridSearch + granularity: Group + element_batch_size: 64 + sample_batch_size: -1 + element_size: 512 + sample_size: -1 + pre_reshape: true + outputs_device: cpu + ratio: 1.0 + max_shrink: 0.2 + max_expand: 1.0 + num_grids: 80 + allow_scale: false + skips: [] + ipts: + dtype: sint8 + zero_point: null + group_shapes: + - - 1 + - -1 + - -1 + scale_dtypes: + - torch.float16 + skips: [] + static: false + enable_calib_range: false + opts: + dtype: sint8 + zero_point: null + group_shapes: + - - -1 + - -1 + - -1 + scale_dtypes: + - torch.float16 + skips: + - attn_q + static: true + enable_calib_range: true + calib_range: + degree: 2 + objective: OutputsError + strategy: Manual + granularity: Layer + element_batch_size: -1 + sample_batch_size: -1 + element_size: -1 + sample_size: -1 + pre_reshape: true + outputs_device: cpu + ratio: 1.0 + max_shrink: 0.2 + max_expand: 1.0 + num_grids: 80 + allow_scale: false + skips: [] + calib: + data: pileval + num_samples: 128 + path: mit-han-lab/pile-val-backup + seq_length: 1024 + min_seq_length: 0 + max_seq_length: 0 + local_path: '' + enable_rotation: true + rotation: + random: false + transforms: + - out_proj + enable_reorder: false + enable_smooth: true + smooth: + enable_proj: false + enable_attn: true + attn: + degree: 2 + strategy: Manual + sample_batch_size: -1 + sample_size: -1 + outputs_device: cpu + allow_a_quant: true + allow_b_quant: true + spans: + - - AbsMax + - AbsMax + alpha: 0.5 + beta: 0 + num_grids: 20 + develop_dtype: torch.float32 +seed: 12345 +skip_eval: false +load_from: '' +save_model: 'true' +copy_on_save: false diff --git a/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200727.RUNNING/model/model.pt b/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200727.RUNNING/model/model.pt new file mode 100644 index 0000000000000000000000000000000000000000..2c58126f91efa6343ea41e0eb8953ff1e5acef40 --- /dev/null +++ b/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200727.RUNNING/model/model.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c7707587af5ec67ddc0f3f7dbfdbd9c86f9ded33e10c5bf4b0246518c228199f +size 13476951926 diff --git 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b/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200727.RUNNING/model/wgts.pt new file mode 100644 index 0000000000000000000000000000000000000000..8aa94af02534bbcf9b0bfcb84762c4ddc130186f --- /dev/null +++ b/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200727.RUNNING/model/wgts.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:90a45af762722116d586b0e7011d9acfcc8950086c0470898c078c05af779d0e +size 5527158 diff --git a/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200727.RUNNING/run-241119.200727.log b/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200727.RUNNING/run-241119.200727.log new file mode 100644 index 0000000000000000000000000000000000000000..8e572f547f1e1c96832e694d00f120d26840dec0 --- /dev/null +++ b/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200727.RUNNING/run-241119.200727.log @@ -0,0 +1,16093 @@ +24-11-19 20:07:27 | I | === Configurations === +24-11-19 20:07:27 | I | LlmPtqRunConfig( +24-11-19 20:07:27 | I | cache=LlmCacheConfig( +24-11-19 20:07:27 | I | root=runs/shang, +24-11-19 20:07:27 | I | dirpath=LlmQuantCacheConfig( +24-11-19 20:07:27 | I | rotation=runs/shang/llm/cache/quant/rotation/hadamard, +24-11-19 20:07:27 | I | reorder=, +24-11-19 20:07:27 | I | smooth=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0, +24-11-19 20:07:27 | I | wgts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[], +24-11-19 20:07:27 | I | acts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]), +24-11-19 20:07:27 | I | path=LlmQuantCacheConfig( +24-11-19 20:07:27 | I | rotation=runs/shang/llm/cache/quant/rotation/hadamard/llama-2-7b-instruct-together-32k.pt, +24-11-19 20:07:27 | I | reorder=, +24-11-19 20:07:27 | I | smooth=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/llama-2-7b-instruct-together-32k.pt, +24-11-19 20:07:27 | I | wgts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-2-7b-instruct-together-32k.pt, +24-11-19 20:07:27 | I | acts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-2-7b-instruct-together-32k.pt)), +24-11-19 20:07:27 | I | output=OutputConfig( +24-11-19 20:07:27 | I | root=runs/shang, +24-11-19 20:07:27 | I | dirname=skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0], +24-11-19 20:07:27 | I | job=run, +24-11-19 20:07:27 | I | dirpath=runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0], +24-11-19 20:07:27 | I | timestamp=241119.200727), +24-11-19 20:07:27 | I | model=LlmModelConfig( +24-11-19 20:07:27 | I | name=llama-2-7b-instruct-together-32k, +24-11-19 20:07:27 | I | family=llama-2, +24-11-19 20:07:27 | I | path=/home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k, +24-11-19 20:07:27 | I | root=, +24-11-19 20:07:27 | I | local_path=/home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k, +24-11-19 20:07:27 | I | local_root=/home/yujunlin/models, +24-11-19 20:07:27 | I | size=7.0, +24-11-19 20:07:27 | I | variant=instruct-together-32k, +24-11-19 20:07:27 | I | dtype=torch.float16, +24-11-19 20:07:27 | I | orig_dtype=torch.float16), +24-11-19 20:07:27 | I | eval=LlmEvalConfig( +24-11-19 20:07:27 | I | num_gpus=1, +24-11-19 20:07:27 | I | batch_size=8, +24-11-19 20:07:27 | I | tasks=['wikitext'], +24-11-19 20:07:27 | I | max_seq_length=-4096, +24-11-19 20:07:27 | I | evaluators=['gptq']), +24-11-19 20:07:27 | I | quant=LlmQuantConfig( +24-11-19 20:07:27 | I | wgts=LlmWeightQuantizerConfig( +24-11-19 20:07:27 | I | dtype=sint8, +24-11-19 20:07:27 | I | zero_point=None, +24-11-19 20:07:27 | I | group_shapes=((1, -1, -1),), +24-11-19 20:07:27 | I | scale_dtypes=(torch.float16,), +24-11-19 20:07:27 | I | intermediate_dtypes=(), +24-11-19 20:07:27 | I | intermediate_levels=(), +24-11-19 20:07:27 | I | needs_dequant_saturation=False, +24-11-19 20:07:27 | I | skips=[], +24-11-19 20:07:27 | I | static=True, +24-11-19 20:07:27 | I | kernel_gptq=QuantGptqConfig( +24-11-19 20:07:27 | I | damp_percentage=0.01, +24-11-19 20:07:27 | I | block_size=128, +24-11-19 20:07:27 | I | num_inv_tries=250, +24-11-19 20:07:27 | I | hessian_block_size=512), +24-11-19 20:07:27 | I | calib_range=SkipBasedDynamicRangeCalibConfig( +24-11-19 20:07:27 | I | degree=2, +24-11-19 20:07:27 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 20:07:27 | I | strategy=SearchBasedCalibStrategy.GridSearch, +24-11-19 20:07:27 | I | granularity=SearchBasedCalibGranularity.Group, +24-11-19 20:07:27 | I | element_batch_size=64, +24-11-19 20:07:27 | I | sample_batch_size=-1, +24-11-19 20:07:27 | I | element_size=512, +24-11-19 20:07:27 | I | sample_size=-1, +24-11-19 20:07:27 | I | pre_reshape=True, +24-11-19 20:07:27 | I | outputs_device=cpu, +24-11-19 20:07:27 | I | ratio=1.0, +24-11-19 20:07:27 | I | max_shrink=0.2, +24-11-19 20:07:27 | I | max_expand=1.0, +24-11-19 20:07:27 | I | num_grids=80, +24-11-19 20:07:27 | I | allow_scale=False, +24-11-19 20:07:27 | I | skips=[])), +24-11-19 20:07:27 | I | ipts=LlmActivationQuantizerConfig( +24-11-19 20:07:27 | I | dtype=sint8, +24-11-19 20:07:27 | I | zero_point=None, +24-11-19 20:07:27 | I | group_shapes=((1, -1, -1),), +24-11-19 20:07:27 | I | scale_dtypes=(torch.float16,), +24-11-19 20:07:27 | I | intermediate_dtypes=(), +24-11-19 20:07:27 | I | intermediate_levels=(), +24-11-19 20:07:27 | I | needs_dequant_saturation=False, +24-11-19 20:07:27 | I | skips=[], +24-11-19 20:07:27 | I | static=False, +24-11-19 20:07:27 | I | kernel_gptq=None, +24-11-19 20:07:27 | I | calib_range=None), +24-11-19 20:07:27 | I | opts=LlmActivationQuantizerConfig( +24-11-19 20:07:27 | I | dtype=sint8, +24-11-19 20:07:27 | I | zero_point=None, +24-11-19 20:07:27 | I | group_shapes=((-1, -1, -1),), +24-11-19 20:07:27 | I | scale_dtypes=(torch.float16,), +24-11-19 20:07:27 | I | intermediate_dtypes=(), +24-11-19 20:07:27 | I | intermediate_levels=(), +24-11-19 20:07:27 | I | needs_dequant_saturation=False, +24-11-19 20:07:27 | I | skips=['attn_q'], +24-11-19 20:07:27 | I | static=True, +24-11-19 20:07:27 | I | kernel_gptq=None, +24-11-19 20:07:27 | I | calib_range=SkipBasedDynamicRangeCalibConfig( +24-11-19 20:07:27 | I | degree=2, +24-11-19 20:07:27 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 20:07:27 | I | strategy=SearchBasedCalibStrategy.Manual, +24-11-19 20:07:27 | I | granularity=SearchBasedCalibGranularity.Layer, +24-11-19 20:07:27 | I | element_batch_size=-1, +24-11-19 20:07:27 | I | sample_batch_size=-1, +24-11-19 20:07:27 | I | element_size=-1, +24-11-19 20:07:27 | I | sample_size=-1, +24-11-19 20:07:27 | I | pre_reshape=True, +24-11-19 20:07:27 | I | outputs_device=cpu, +24-11-19 20:07:27 | I | ratio=1.0, +24-11-19 20:07:27 | I | max_shrink=0.2, +24-11-19 20:07:27 | I | max_expand=1.0, +24-11-19 20:07:27 | I | num_grids=80, +24-11-19 20:07:27 | I | allow_scale=False, +24-11-19 20:07:27 | I | skips=[])), +24-11-19 20:07:27 | I | calib=LlmCalibDataLoaderConfig( +24-11-19 20:07:27 | I | data=pileval, +24-11-19 20:07:27 | I | num_samples=128, +24-11-19 20:07:27 | I | batch_size=1, +24-11-19 20:07:27 | I | path=mit-han-lab/pile-val-backup, +24-11-19 20:07:27 | I | seq_length=1024, +24-11-19 20:07:27 | I | min_seq_length=0, +24-11-19 20:07:27 | I | max_seq_length=0, +24-11-19 20:07:27 | I | local_path=), +24-11-19 20:07:27 | I | rotation=QuantRotationConfig( +24-11-19 20:07:27 | I | random=False, +24-11-19 20:07:27 | I | transforms=['out_proj']), +24-11-19 20:07:27 | I | reorder=None, +24-11-19 20:07:27 | I | smooth=SmoothTransfomerConfig( +24-11-19 20:07:27 | I | proj=None, +24-11-19 20:07:27 | I | attn=SmoothAttentionCalibConfig( +24-11-19 20:07:27 | I | degree=2, +24-11-19 20:07:27 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 20:07:27 | I | strategy=SearchBasedCalibStrategy.Manual, +24-11-19 20:07:27 | I | granularity=SearchBasedCalibGranularity.Layer, +24-11-19 20:07:27 | I | element_batch_size=-1, +24-11-19 20:07:27 | I | sample_batch_size=-1, +24-11-19 20:07:27 | I | element_size=-1, +24-11-19 20:07:27 | I | sample_size=-1, +24-11-19 20:07:27 | I | pre_reshape=True, +24-11-19 20:07:27 | I | outputs_device=cpu, +24-11-19 20:07:27 | I | allow_a_quant=True, +24-11-19 20:07:27 | I | allow_b_quant=True, +24-11-19 20:07:27 | I | spans=[(, )], +24-11-19 20:07:27 | I | a_spans=[], +24-11-19 20:07:27 | I | b_spans=[], +24-11-19 20:07:27 | I | alpha=0.5, +24-11-19 20:07:27 | I | beta=0, +24-11-19 20:07:27 | I | num_grids=20, +24-11-19 20:07:27 | I | allow_low_rank=False)), +24-11-19 20:07:27 | I | develop_dtype=torch.float32), +24-11-19 20:07:27 | I | seed=12345, +24-11-19 20:07:27 | I | skip_eval=False, +24-11-19 20:07:27 | I | load_from=, +24-11-19 20:07:27 | I | save_model=true, +24-11-19 20:07:27 | I | copy_on_save=False) +24-11-19 20:07:27 | I | === Dumped Configurations === +24-11-19 20:07:27 | I | { 'cache': { 'path': { 'acts': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-2-7b-instruct-together-32k.pt', +24-11-19 20:07:27 | I | 'reorder': '', +24-11-19 20:07:27 | I | 'rotation': 'runs/shang/llm/cache/quant/rotation/hadamard/llama-2-7b-instruct-together-32k.pt', +24-11-19 20:07:27 | I | 'smooth': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/llama-2-7b-instruct-together-32k.pt', +24-11-19 20:07:27 | I | 'wgts': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-2-7b-instruct-together-32k.pt'}, +24-11-19 20:07:27 | I | 'root': 'runs/shang'}, +24-11-19 20:07:27 | I | 'copy_on_save': False, +24-11-19 20:07:27 | I | 'eval': {'batch_size': 8, 'evaluators': ['gptq'], 'max_seq_length': -4096, 'num_gpus': 1, 'tasks': ['wikitext']}, +24-11-19 20:07:27 | I | 'load_from': '', +24-11-19 20:07:27 | I | 'model': { 'dtype': 'torch.float16', +24-11-19 20:07:27 | I | 'family': 'llama-2', +24-11-19 20:07:27 | I | 'local_path': '/home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k', +24-11-19 20:07:27 | I | 'local_root': '/home/yujunlin/models', +24-11-19 20:07:27 | I | 'name': 'llama-2-7b-instruct-together-32k', +24-11-19 20:07:27 | I | 'path': '/home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k', +24-11-19 20:07:27 | I | 'root': ''}, +24-11-19 20:07:27 | I | 'output': { 'dirname': 'skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]', +24-11-19 20:07:27 | I | 'job': 'run', +24-11-19 20:07:27 | I | 'root': 'runs/shang'}, +24-11-19 20:07:27 | I | 'quant': { 'calib': { 'data': 'pileval', +24-11-19 20:07:27 | I | 'local_path': '', +24-11-19 20:07:27 | I | 'max_seq_length': 0, +24-11-19 20:07:27 | I | 'min_seq_length': 0, +24-11-19 20:07:27 | I | 'num_samples': 128, +24-11-19 20:07:27 | I | 'path': 'mit-han-lab/pile-val-backup', +24-11-19 20:07:27 | I | 'seq_length': 1024}, +24-11-19 20:07:27 | I | 'develop_dtype': 'torch.float32', +24-11-19 20:07:27 | I | 'enable_reorder': False, +24-11-19 20:07:27 | I | 'enable_rotation': True, +24-11-19 20:07:27 | I | 'enable_smooth': True, +24-11-19 20:07:27 | I | 'ipts': { 'dtype': 'sint8', +24-11-19 20:07:27 | I | 'enable_calib_range': False, +24-11-19 20:07:27 | I | 'group_shapes': [[1, -1, -1]], +24-11-19 20:07:27 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 20:07:27 | I | 'skips': [], +24-11-19 20:07:27 | I | 'static': False, +24-11-19 20:07:27 | I | 'zero_point': None}, +24-11-19 20:07:27 | I | 'opts': { 'calib_range': { 'allow_scale': False, +24-11-19 20:07:27 | I | 'degree': 2, +24-11-19 20:07:27 | I | 'element_batch_size': -1, +24-11-19 20:07:27 | I | 'element_size': -1, +24-11-19 20:07:27 | I | 'granularity': 'Layer', +24-11-19 20:07:27 | I | 'max_expand': 1.0, +24-11-19 20:07:27 | I | 'max_shrink': 0.2, +24-11-19 20:07:27 | I | 'num_grids': 80, +24-11-19 20:07:27 | I | 'objective': 'OutputsError', +24-11-19 20:07:27 | I | 'outputs_device': 'cpu', +24-11-19 20:07:27 | I | 'pre_reshape': True, +24-11-19 20:07:27 | I | 'ratio': 1.0, +24-11-19 20:07:27 | I | 'sample_batch_size': -1, +24-11-19 20:07:27 | I | 'sample_size': -1, +24-11-19 20:07:27 | I | 'skips': [], +24-11-19 20:07:27 | I | 'strategy': 'Manual'}, +24-11-19 20:07:27 | I | 'dtype': 'sint8', +24-11-19 20:07:27 | I | 'enable_calib_range': True, +24-11-19 20:07:27 | I | 'group_shapes': [[-1, -1, -1]], +24-11-19 20:07:27 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 20:07:27 | I | 'skips': ['attn_q'], +24-11-19 20:07:27 | I | 'static': True, +24-11-19 20:07:27 | I | 'zero_point': None}, +24-11-19 20:07:27 | I | 'rotation': {'random': False, 'transforms': ['out_proj']}, +24-11-19 20:07:27 | I | 'smooth': { 'attn': { 'allow_a_quant': True, +24-11-19 20:07:27 | I | 'allow_b_quant': True, +24-11-19 20:07:27 | I | 'alpha': 0.5, +24-11-19 20:07:27 | I | 'beta': 0, +24-11-19 20:07:27 | I | 'degree': 2, +24-11-19 20:07:27 | I | 'num_grids': 20, +24-11-19 20:07:27 | I | 'outputs_device': 'cpu', +24-11-19 20:07:27 | I | 'sample_batch_size': -1, +24-11-19 20:07:27 | I | 'sample_size': -1, +24-11-19 20:07:27 | I | 'spans': [['AbsMax', 'AbsMax']], +24-11-19 20:07:27 | I | 'strategy': 'Manual'}, +24-11-19 20:07:27 | I | 'enable_attn': True, +24-11-19 20:07:27 | I | 'enable_proj': False}, +24-11-19 20:07:27 | I | 'wgts': { 'calib_range': { 'allow_scale': False, +24-11-19 20:07:27 | I | 'degree': 2, +24-11-19 20:07:27 | I | 'element_batch_size': 64, +24-11-19 20:07:27 | I | 'element_size': 512, +24-11-19 20:07:27 | I | 'granularity': 'Group', +24-11-19 20:07:27 | I | 'max_expand': 1.0, +24-11-19 20:07:27 | I | 'max_shrink': 0.2, +24-11-19 20:07:27 | I | 'num_grids': 80, +24-11-19 20:07:27 | I | 'objective': 'OutputsError', +24-11-19 20:07:27 | I | 'outputs_device': 'cpu', +24-11-19 20:07:27 | I | 'pre_reshape': True, +24-11-19 20:07:27 | I | 'ratio': 1.0, +24-11-19 20:07:27 | I | 'sample_batch_size': -1, +24-11-19 20:07:27 | I | 'sample_size': -1, +24-11-19 20:07:27 | I | 'skips': [], +24-11-19 20:07:27 | I | 'strategy': 'GridSearch'}, +24-11-19 20:07:27 | I | 'dtype': 'sint8', +24-11-19 20:07:27 | I | 'enable_calib_range': True, +24-11-19 20:07:27 | I | 'enable_kernel_gptq': True, +24-11-19 20:07:27 | I | 'group_shapes': [[1, -1, -1]], +24-11-19 20:07:27 | I | 'intermediate_dtypes': [], +24-11-19 20:07:27 | I | 'intermediate_levels': [], +24-11-19 20:07:27 | I | 'kernel_gptq': { 'block_size': 128, +24-11-19 20:07:27 | I | 'damp_percentage': 0.01, +24-11-19 20:07:27 | I | 'hessian_block_size': 512, +24-11-19 20:07:27 | I | 'num_inv_tries': 250}, +24-11-19 20:07:27 | I | 'needs_dequant_saturation': False, +24-11-19 20:07:27 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 20:07:27 | I | 'skips': [], +24-11-19 20:07:27 | I | 'zero_point': None}}, +24-11-19 20:07:27 | I | 'save_model': 'true', +24-11-19 20:07:27 | I | 'seed': 12345, +24-11-19 20:07:27 | I | 'skip_eval': False} +24-11-19 20:07:27 | I | === Output Directory === +24-11-19 20:07:27 | I | runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200727 +24-11-19 20:07:27 | I | === Start Evaluating === +24-11-19 20:07:27 | I | * Building model llama-2-7b-instruct-together-32k from /home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k +24-11-19 20:07:28 | I | We will use 90% of the memory on device 0 for storing the model, and 10% for the buffer to avoid OOM. You can set `max_memory` in to a higher value to use more memory (at your own risk). +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.0.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.1.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.2.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.3.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.4.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.5.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.6.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.7.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.8.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.9.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.10.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.11.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.12.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.13.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.14.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.15.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.16.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.17.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.18.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.19.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.20.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.21.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.22.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.23.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.24.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.25.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.26.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.27.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.28.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.29.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.30.self_attn +24-11-19 20:07:31 | I | - Patching LlamaSdpaAttention.forward in model.layers.31.self_attn +24-11-19 20:07:31 | I | * Rotating model +24-11-19 20:07:31 | I | - Loading rotation from runs/shang/llm/cache/quant/rotation/hadamard/llama-2-7b-instruct-together-32k.pt +24-11-19 20:07:31 | D | - Transforming norm and linear in model.layers.0 +24-11-19 20:07:32 | D | - Transforming norm and linear in model.layers.1 +24-11-19 20:07:32 | D | - Transforming norm and linear in model.layers.2 +24-11-19 20:07:32 | D | - Transforming norm and linear in model.layers.3 +24-11-19 20:07:32 | D | - Transforming norm and linear in model.layers.4 +24-11-19 20:07:32 | D | - Transforming norm and linear in model.layers.5 +24-11-19 20:07:32 | D | - Transforming norm and linear in model.layers.6 +24-11-19 20:07:32 | D | - Transforming norm and linear in model.layers.7 +24-11-19 20:07:33 | D | - Transforming norm and linear in model.layers.8 +24-11-19 20:07:33 | D | - Transforming norm and linear in model.layers.9 +24-11-19 20:07:33 | D | - Transforming norm and linear in model.layers.10 +24-11-19 20:07:33 | D | - Transforming norm and linear in model.layers.11 +24-11-19 20:07:33 | D | - Transforming norm and linear in model.layers.12 +24-11-19 20:07:33 | D | - Transforming norm and linear in model.layers.13 +24-11-19 20:07:33 | D | - Transforming norm and linear in model.layers.14 +24-11-19 20:07:34 | D | - Transforming norm and linear in model.layers.15 +24-11-19 20:07:34 | D | - Transforming norm and linear in model.layers.16 +24-11-19 20:07:34 | D | - Transforming norm and linear in model.layers.17 +24-11-19 20:07:34 | D | - Transforming norm and linear in model.layers.18 +24-11-19 20:07:34 | D | - Transforming norm and linear in model.layers.19 +24-11-19 20:07:34 | D | - Transforming norm and linear in model.layers.20 +24-11-19 20:07:34 | D | - Transforming norm and linear in model.layers.21 +24-11-19 20:07:35 | D | - Transforming norm and linear in model.layers.22 +24-11-19 20:07:35 | D | - Transforming norm and linear in model.layers.23 +24-11-19 20:07:35 | D | - Transforming norm and linear in model.layers.24 +24-11-19 20:07:35 | D | - Transforming norm and linear in model.layers.25 +24-11-19 20:07:35 | D | - Transforming norm and linear in model.layers.26 +24-11-19 20:07:35 | D | - Transforming norm and linear in model.layers.27 +24-11-19 20:07:35 | D | - Transforming norm and linear in model.layers.28 +24-11-19 20:07:36 | D | - Transforming norm and linear in model.layers.29 +24-11-19 20:07:36 | D | - Transforming norm and linear in model.layers.30 +24-11-19 20:07:36 | D | - Transforming norm and linear in model.layers.31 +24-11-19 20:07:36 | D | - Transforming model.norm +24-11-19 20:07:36 | D | - Rotating model.embed_tokens +24-11-19 20:07:36 | D | - Rotating model.layers.0 +24-11-19 20:07:36 | D | - Rotating model.layers.0.self_attn.q_proj (in) +24-11-19 20:07:36 | D | - Rotating model.layers.0.self_attn.k_proj (in) +24-11-19 20:07:36 | D | - Rotating model.layers.0.self_attn.v_proj (in) +24-11-19 20:07:36 | D | - Rotating model.layers.0.self_attn.o_proj (out) +24-11-19 20:07:36 | D | - Rotating model.layers.0.self_attn.v_proj (out) +24-11-19 20:07:36 | D | - Rotating model.layers.0.self_attn.o_proj (in) +24-11-19 20:07:36 | D | - 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Rotating model.layers.20 +24-11-19 20:07:39 | D | - Rotating model.layers.20.self_attn.q_proj (in) +24-11-19 20:07:39 | D | - Rotating model.layers.20.self_attn.k_proj (in) +24-11-19 20:07:39 | D | - Rotating model.layers.20.self_attn.v_proj (in) +24-11-19 20:07:39 | D | - Rotating model.layers.20.self_attn.o_proj (out) +24-11-19 20:07:39 | D | - Rotating model.layers.20.self_attn.v_proj (out) +24-11-19 20:07:39 | D | - Rotating model.layers.20.self_attn.o_proj (in) +24-11-19 20:07:39 | D | - Rotating model.layers.20.mlp.up_proj (in) +24-11-19 20:07:39 | D | - Rotating model.layers.20.mlp.gate_proj (in) +24-11-19 20:07:39 | D | - Rotating model.layers.20.mlp.down_proj (out) +24-11-19 20:07:39 | D | - Rotating model.layers.21 +24-11-19 20:07:39 | D | - Rotating model.layers.21.self_attn.q_proj (in) +24-11-19 20:07:39 | D | - Rotating model.layers.21.self_attn.k_proj (in) +24-11-19 20:07:39 | D | - Rotating model.layers.21.self_attn.v_proj (in) +24-11-19 20:07:39 | D | - Rotating model.layers.21.self_attn.o_proj (out) +24-11-19 20:07:39 | D | - Rotating model.layers.21.self_attn.v_proj (out) +24-11-19 20:07:39 | D | - Rotating model.layers.21.self_attn.o_proj (in) +24-11-19 20:07:39 | D | - Rotating model.layers.21.mlp.up_proj (in) +24-11-19 20:07:39 | D | - Rotating model.layers.21.mlp.gate_proj (in) +24-11-19 20:07:39 | D | - Rotating model.layers.21.mlp.down_proj (out) +24-11-19 20:07:40 | D | - Rotating model.layers.22 +24-11-19 20:07:40 | D | - Rotating model.layers.22.self_attn.q_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.22.self_attn.k_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.22.self_attn.v_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.22.self_attn.o_proj (out) +24-11-19 20:07:40 | D | - Rotating model.layers.22.self_attn.v_proj (out) +24-11-19 20:07:40 | D | - Rotating model.layers.22.self_attn.o_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.22.mlp.up_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.22.mlp.gate_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.22.mlp.down_proj (out) +24-11-19 20:07:40 | D | - Rotating model.layers.23 +24-11-19 20:07:40 | D | - Rotating model.layers.23.self_attn.q_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.23.self_attn.k_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.23.self_attn.v_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.23.self_attn.o_proj (out) +24-11-19 20:07:40 | D | - Rotating model.layers.23.self_attn.v_proj (out) +24-11-19 20:07:40 | D | - Rotating model.layers.23.self_attn.o_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.23.mlp.up_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.23.mlp.gate_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.23.mlp.down_proj (out) +24-11-19 20:07:40 | D | - Rotating model.layers.24 +24-11-19 20:07:40 | D | - Rotating model.layers.24.self_attn.q_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.24.self_attn.k_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.24.self_attn.v_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.24.self_attn.o_proj (out) +24-11-19 20:07:40 | D | - Rotating model.layers.24.self_attn.v_proj (out) +24-11-19 20:07:40 | D | - Rotating model.layers.24.self_attn.o_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.24.mlp.up_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.24.mlp.gate_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.24.mlp.down_proj (out) +24-11-19 20:07:40 | D | - Rotating model.layers.25 +24-11-19 20:07:40 | D | - Rotating model.layers.25.self_attn.q_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.25.self_attn.k_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.25.self_attn.v_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.25.self_attn.o_proj (out) +24-11-19 20:07:40 | D | - Rotating model.layers.25.self_attn.v_proj (out) +24-11-19 20:07:40 | D | - Rotating model.layers.25.self_attn.o_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.25.mlp.up_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.25.mlp.gate_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.25.mlp.down_proj (out) +24-11-19 20:07:40 | D | - Rotating model.layers.26 +24-11-19 20:07:40 | D | - Rotating model.layers.26.self_attn.q_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.26.self_attn.k_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.26.self_attn.v_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.26.self_attn.o_proj (out) +24-11-19 20:07:40 | D | - Rotating model.layers.26.self_attn.v_proj (out) +24-11-19 20:07:40 | D | - Rotating model.layers.26.self_attn.o_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.26.mlp.up_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.26.mlp.gate_proj (in) +24-11-19 20:07:40 | D | - Rotating model.layers.26.mlp.down_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.27 +24-11-19 20:07:41 | D | - Rotating model.layers.27.self_attn.q_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.27.self_attn.k_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.27.self_attn.v_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.27.self_attn.o_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.27.self_attn.v_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.27.self_attn.o_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.27.mlp.up_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.27.mlp.gate_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.27.mlp.down_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.28 +24-11-19 20:07:41 | D | - Rotating model.layers.28.self_attn.q_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.28.self_attn.k_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.28.self_attn.v_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.28.self_attn.o_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.28.self_attn.v_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.28.self_attn.o_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.28.mlp.up_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.28.mlp.gate_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.28.mlp.down_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.29 +24-11-19 20:07:41 | D | - Rotating model.layers.29.self_attn.q_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.29.self_attn.k_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.29.self_attn.v_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.29.self_attn.o_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.29.self_attn.v_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.29.self_attn.o_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.29.mlp.up_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.29.mlp.gate_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.29.mlp.down_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.30 +24-11-19 20:07:41 | D | - Rotating model.layers.30.self_attn.q_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.30.self_attn.k_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.30.self_attn.v_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.30.self_attn.o_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.30.self_attn.v_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.30.self_attn.o_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.30.mlp.up_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.30.mlp.gate_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.30.mlp.down_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.31 +24-11-19 20:07:41 | D | - Rotating model.layers.31.self_attn.q_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.31.self_attn.k_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.31.self_attn.v_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.31.self_attn.o_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.31.self_attn.v_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.31.self_attn.o_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.31.mlp.up_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.31.mlp.gate_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.31.mlp.down_proj (out) +24-11-19 20:07:41 | D | - Rotating lm_head (in) +24-11-19 20:07:41 | I | - Linking rotation to runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200727.RUNNING/model/rotation.pt +24-11-19 20:07:42 | I | * Development dtype is torch.float32 +24-11-19 20:07:42 | I | * Smoothing model for quantization +24-11-19 20:07:42 | I | - Generating smooth scales +24-11-19 20:07:42 | D | Starting new HTTPS connection (1): huggingface.co:443 +24-11-19 20:08:02 | D | Starting new HTTPS connection (2): huggingface.co:443 +24-11-19 20:08:39 | D | Starting new HTTPS connection (1): s3.amazonaws.com:443 +24-11-19 20:08:51 | W | Repo card metadata block was not found. Setting CardData to empty. +24-11-19 20:08:51 | D | Starting new HTTPS connection (3): huggingface.co:443 +24-11-19 20:09:28 | W | Using the latest cached version of the dataset since mit-han-lab/pile-val-backup couldn't be found on the Hugging Face Hub +24-11-19 20:09:28 | W | Found the latest cached dataset configuration 'default' at /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4 (last modified on Tue Oct 8 18:58:39 2024). +24-11-19 20:09:28 | D | Attempting to acquire lock 23438954475936 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:09:28 | D | Lock 23438954475936 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:09:28 | D | open file: /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4/dataset_info.json +24-11-19 20:09:28 | D | Attempting to release lock 23438954475936 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:09:28 | D | Lock 23438954475936 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:09:51 | D | - Smoothing model.layers.0 +24-11-19 20:09:51 | D | - model.layers.0.self_attn.attn_k +24-11-19 20:09:51 | D | + w: None +24-11-19 20:09:51 | D | + x: None +24-11-19 20:09:51 | D | + y: sint8 +24-11-19 20:09:51 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:09:51 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:09:52 | D | + x - AbsMax +24-11-19 20:09:52 | D | + x = [min=0.4373, max=13.5312] +24-11-19 20:09:52 | D | + y - AbsMax +24-11-19 20:09:52 | D | + y = [min=0.3921, max=6.5820] +24-11-19 20:09:52 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:09:53 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:09:53 | D | - alpha = [ 0.5000] +24-11-19 20:09:53 | D | - beta = [ 0.0000] +24-11-19 20:09:53 | D | - sum error = [ 1.1366] +24-11-19 20:09:53 | D | - best error = [ 1.1366] +24-11-19 20:09:53 | D | + error = 1.1366 +24-11-19 20:09:53 | D | + scale = [min=0.6262, max=2.5655] +24-11-19 20:10:03 | D | - Smoothing model.layers.1 +24-11-19 20:10:03 | D | - model.layers.1.self_attn.attn_k +24-11-19 20:10:03 | D | + w: None +24-11-19 20:10:03 | D | + x: None +24-11-19 20:10:03 | D | + y: sint8 +24-11-19 20:10:03 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:10:03 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:10:03 | D | + x - AbsMax +24-11-19 20:10:03 | D | + x = [min=0.3020, max=12.4375] +24-11-19 20:10:03 | D | + y - AbsMax +24-11-19 20:10:03 | D | + y = [min=0.4658, max=10.4844] +24-11-19 20:10:03 | D | + finished reseting calibrator, ram usage: 13.0 +24-11-19 20:10:04 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:10:04 | D | - alpha = [ 0.5000] +24-11-19 20:10:04 | D | - beta = [ 0.0000] +24-11-19 20:10:04 | D | - sum error = [ 5.5324] +24-11-19 20:10:04 | D | - best error = [ 5.5324] +24-11-19 20:10:04 | D | + error = 5.5324 +24-11-19 20:10:04 | D | + scale = [min=0.6825, max=3.2380] +24-11-19 20:10:13 | D | - Smoothing model.layers.2 +24-11-19 20:10:13 | D | - model.layers.2.self_attn.attn_k +24-11-19 20:10:13 | D | + w: None +24-11-19 20:10:13 | D | + x: None +24-11-19 20:10:13 | D | + y: sint8 +24-11-19 20:10:13 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:10:13 | D | + finished parsing calibration arguments, ram usage: 14.1 +24-11-19 20:10:13 | D | + x - AbsMax +24-11-19 20:10:13 | D | + x = [min=0.9668, max=14.4141] +24-11-19 20:10:13 | D | + y - AbsMax +24-11-19 20:10:13 | D | + y = [min=0.9209, max=20.4219] +24-11-19 20:10:13 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:10:14 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:10:14 | D | - alpha = [ 0.5000] +24-11-19 20:10:14 | D | - beta = [ 0.0000] +24-11-19 20:10:14 | D | - sum error = [ 19.0991] +24-11-19 20:10:14 | D | - best error = [ 19.0991] +24-11-19 20:10:14 | D | + error = 19.0991 +24-11-19 20:10:14 | D | + scale = [min=0.9596, max=4.5191] +24-11-19 20:10:22 | D | - Smoothing model.layers.3 +24-11-19 20:10:22 | D | - model.layers.3.self_attn.attn_k +24-11-19 20:10:22 | D | + w: None +24-11-19 20:10:22 | D | + x: None +24-11-19 20:10:22 | D | + y: sint8 +24-11-19 20:10:22 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:10:22 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:10:22 | D | + x - AbsMax +24-11-19 20:10:22 | D | + x = [min=1.1270, max=16.4375] +24-11-19 20:10:23 | D | + y - AbsMax +24-11-19 20:10:23 | D | + y = [min=0.9590, max=21.3438] +24-11-19 20:10:23 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:10:24 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:10:24 | D | - alpha = [ 0.5000] +24-11-19 20:10:24 | D | - beta = [ 0.0000] +24-11-19 20:10:24 | D | - sum error = [ 21.1401] +24-11-19 20:10:24 | D | - best error = [ 21.1401] +24-11-19 20:10:24 | D | + error = 21.1401 +24-11-19 20:10:24 | D | + scale = [min=0.9793, max=4.6199] +24-11-19 20:10:33 | D | - Smoothing model.layers.4 +24-11-19 20:10:33 | D | - model.layers.4.self_attn.attn_k +24-11-19 20:10:33 | D | + w: None +24-11-19 20:10:33 | D | + x: None +24-11-19 20:10:33 | D | + y: sint8 +24-11-19 20:10:33 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:10:33 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:10:33 | D | + x - AbsMax +24-11-19 20:10:33 | D | + x = [min=1.4141, max=16.4062] +24-11-19 20:10:33 | D | + y - AbsMax +24-11-19 20:10:33 | D | + y = [min=1.2734, max=23.8750] +24-11-19 20:10:33 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:10:34 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:10:34 | D | - alpha = [ 0.5000] +24-11-19 20:10:34 | D | - beta = [ 0.0000] +24-11-19 20:10:34 | D | - sum error = [ 32.0659] +24-11-19 20:10:34 | D | - best error = [ 32.0659] +24-11-19 20:10:34 | D | + error = 32.0659 +24-11-19 20:10:34 | D | + scale = [min=1.1285, max=4.8862] +24-11-19 20:10:44 | D | - Smoothing model.layers.5 +24-11-19 20:10:44 | D | - model.layers.5.self_attn.attn_k +24-11-19 20:10:44 | D | + w: None +24-11-19 20:10:44 | D | + x: None +24-11-19 20:10:44 | D | + y: sint8 +24-11-19 20:10:44 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:10:44 | D | + finished parsing calibration arguments, ram usage: 14.2 +24-11-19 20:10:44 | D | + x - AbsMax +24-11-19 20:10:44 | D | + x = [min=1.5879, max=17.6250] +24-11-19 20:10:45 | D | + y - AbsMax +24-11-19 20:10:45 | D | + y = [min=1.6338, max=24.2188] +24-11-19 20:10:45 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:10:46 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:10:46 | D | - alpha = [ 0.5000] +24-11-19 20:10:46 | D | - beta = [ 0.0000] +24-11-19 20:10:46 | D | - sum error = [ 35.0268] +24-11-19 20:10:46 | D | - best error = [ 35.0268] +24-11-19 20:10:46 | D | + error = 35.0268 +24-11-19 20:10:46 | D | + scale = [min=1.2782, max=4.9213] +24-11-19 20:10:54 | D | - Smoothing model.layers.6 +24-11-19 20:10:54 | D | - model.layers.6.self_attn.attn_k +24-11-19 20:10:54 | D | + w: None +24-11-19 20:10:54 | D | + x: None +24-11-19 20:10:54 | D | + y: sint8 +24-11-19 20:10:54 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:10:54 | D | + finished parsing calibration arguments, ram usage: 14.5 +24-11-19 20:10:54 | D | + x - AbsMax +24-11-19 20:10:54 | D | + x = [min=0.9209, max=19.8125] +24-11-19 20:10:55 | D | + y - AbsMax +24-11-19 20:10:55 | D | + y = [min=0.9209, max=21.0781] +24-11-19 20:10:55 | D | + finished reseting calibrator, ram usage: 14.6 +24-11-19 20:10:56 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:10:56 | D | - alpha = [ 0.5000] +24-11-19 20:10:56 | D | - beta = [ 0.0000] +24-11-19 20:10:56 | D | - sum error = [ 39.1064] +24-11-19 20:10:56 | D | - best error = [ 39.1064] +24-11-19 20:10:56 | D | + error = 39.1064 +24-11-19 20:10:56 | D | + scale = [min=0.9596, max=4.5911] +24-11-19 20:11:04 | D | - Smoothing model.layers.7 +24-11-19 20:11:04 | D | - model.layers.7.self_attn.attn_k +24-11-19 20:11:04 | D | + w: None +24-11-19 20:11:04 | D | + x: None +24-11-19 20:11:04 | D | + y: sint8 +24-11-19 20:11:04 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:04 | D | + finished parsing calibration arguments, ram usage: 14.2 +24-11-19 20:11:04 | D | + x - AbsMax +24-11-19 20:11:04 | D | + x = [min=0.9023, max=20.9688] +24-11-19 20:11:04 | D | + y - AbsMax +24-11-19 20:11:04 | D | + y = [min=0.9697, max=22.1250] +24-11-19 20:11:04 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:11:05 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:05 | D | - alpha = [ 0.5000] +24-11-19 20:11:05 | D | - beta = [ 0.0000] +24-11-19 20:11:05 | D | - sum error = [ 43.5300] +24-11-19 20:11:05 | D | - best error = [ 43.5300] +24-11-19 20:11:05 | D | + error = 43.5300 +24-11-19 20:11:05 | D | + scale = [min=0.9847, max=4.7037] +24-11-19 20:11:14 | D | - Smoothing model.layers.8 +24-11-19 20:11:14 | D | - model.layers.8.self_attn.attn_k +24-11-19 20:11:14 | D | + w: None +24-11-19 20:11:14 | D | + x: None +24-11-19 20:11:14 | D | + y: sint8 +24-11-19 20:11:14 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:14 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:11:14 | D | + x - AbsMax +24-11-19 20:11:14 | D | + x = [min=1.4893, max=18.1719] +24-11-19 20:11:14 | D | + y - AbsMax +24-11-19 20:11:14 | D | + y = [min=1.1504, max=22.1562] +24-11-19 20:11:14 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:11:15 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:15 | D | - alpha = [ 0.5000] +24-11-19 20:11:15 | D | - beta = [ 0.0000] +24-11-19 20:11:15 | D | - sum error = [ 52.3779] +24-11-19 20:11:15 | D | - best error = [ 52.3779] +24-11-19 20:11:15 | D | + error = 52.3779 +24-11-19 20:11:15 | D | + scale = [min=1.0726, max=4.7070] +24-11-19 20:11:22 | D | - Smoothing model.layers.9 +24-11-19 20:11:22 | D | - model.layers.9.self_attn.attn_k +24-11-19 20:11:22 | D | + w: None +24-11-19 20:11:22 | D | + x: None +24-11-19 20:11:22 | D | + y: sint8 +24-11-19 20:11:22 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:22 | D | + finished parsing calibration arguments, ram usage: 14.1 +24-11-19 20:11:23 | D | + x - AbsMax +24-11-19 20:11:23 | D | + x = [min=1.6016, max=15.4375] +24-11-19 20:11:23 | D | + y - AbsMax +24-11-19 20:11:23 | D | + y = [min=1.6768, max=23.0625] +24-11-19 20:11:23 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:11:23 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:23 | D | - alpha = [ 0.5000] +24-11-19 20:11:23 | D | - beta = [ 0.0000] +24-11-19 20:11:23 | D | - sum error = [ 62.3828] +24-11-19 20:11:23 | D | - best error = [ 62.3828] +24-11-19 20:11:23 | D | + error = 62.3828 +24-11-19 20:11:23 | D | + scale = [min=1.2949, max=4.8023] +24-11-19 20:11:31 | D | - Smoothing model.layers.10 +24-11-19 20:11:31 | D | - model.layers.10.self_attn.attn_k +24-11-19 20:11:31 | D | + w: None +24-11-19 20:11:31 | D | + x: None +24-11-19 20:11:31 | D | + y: sint8 +24-11-19 20:11:31 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:31 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:11:32 | D | + x - AbsMax +24-11-19 20:11:32 | D | + x = [min=1.3184, max=17.5469] +24-11-19 20:11:32 | D | + y - AbsMax +24-11-19 20:11:32 | D | + y = [min=1.3682, max=21.7188] +24-11-19 20:11:32 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:11:32 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:32 | D | - alpha = [ 0.5000] +24-11-19 20:11:32 | D | - beta = [ 0.0000] +24-11-19 20:11:32 | D | - sum error = [ 65.2007] +24-11-19 20:11:32 | D | - best error = [ 65.2007] +24-11-19 20:11:32 | D | + error = 65.2007 +24-11-19 20:11:32 | D | + scale = [min=1.1697, max=4.6603] +24-11-19 20:11:41 | D | - Smoothing model.layers.11 +24-11-19 20:11:41 | D | - model.layers.11.self_attn.attn_k +24-11-19 20:11:41 | D | + w: None +24-11-19 20:11:41 | D | + x: None +24-11-19 20:11:41 | D | + y: sint8 +24-11-19 20:11:41 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:41 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:11:41 | D | + x - AbsMax +24-11-19 20:11:41 | D | + x = [min=1.3359, max=19.1719] +24-11-19 20:11:41 | D | + y - AbsMax +24-11-19 20:11:41 | D | + y = [min=1.2051, max=20.3750] +24-11-19 20:11:41 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:11:42 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:42 | D | - alpha = [ 0.5000] +24-11-19 20:11:42 | D | - beta = [ 0.0000] +24-11-19 20:11:42 | D | - sum error = [ 58.5941] +24-11-19 20:11:42 | D | - best error = [ 58.5941] +24-11-19 20:11:42 | D | + error = 58.5941 +24-11-19 20:11:42 | D | + scale = [min=1.0978, max=4.5139] +24-11-19 20:11:50 | D | - Smoothing model.layers.12 +24-11-19 20:11:50 | D | - model.layers.12.self_attn.attn_k +24-11-19 20:11:50 | D | + w: None +24-11-19 20:11:50 | D | + x: None +24-11-19 20:11:50 | D | + y: sint8 +24-11-19 20:11:50 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:50 | D | + finished parsing calibration arguments, ram usage: 14.3 +24-11-19 20:11:50 | D | + x - AbsMax +24-11-19 20:11:50 | D | + x = [min=1.0918, max=18.9531] +24-11-19 20:11:50 | D | + y - AbsMax +24-11-19 20:11:50 | D | + y = [min=1.2236, max=21.7500] +24-11-19 20:11:50 | D | + finished reseting calibrator, ram usage: 14.3 +24-11-19 20:11:51 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:51 | D | - alpha = [ 0.5000] +24-11-19 20:11:51 | D | - beta = [ 0.0000] +24-11-19 20:11:51 | D | - sum error = [ 69.0493] +24-11-19 20:11:51 | D | - best error = [ 69.0493] +24-11-19 20:11:51 | D | + error = 69.0493 +24-11-19 20:11:51 | D | + scale = [min=1.1062, max=4.6637] +24-11-19 20:12:00 | D | - Smoothing model.layers.13 +24-11-19 20:12:00 | D | - model.layers.13.self_attn.attn_k +24-11-19 20:12:00 | D | + w: None +24-11-19 20:12:00 | D | + x: None +24-11-19 20:12:00 | D | + y: sint8 +24-11-19 20:12:00 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:00 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:12:00 | D | + x - AbsMax +24-11-19 20:12:00 | D | + x = [min=1.5947, max=17.3594] +24-11-19 20:12:00 | D | + y - AbsMax +24-11-19 20:12:00 | D | + y = [min=1.3652, max=21.7500] +24-11-19 20:12:00 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:12:01 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:01 | D | - alpha = [ 0.5000] +24-11-19 20:12:01 | D | - beta = [ 0.0000] +24-11-19 20:12:01 | D | - sum error = [ 69.1522] +24-11-19 20:12:01 | D | - best error = [ 69.1522] +24-11-19 20:12:01 | D | + error = 69.1522 +24-11-19 20:12:01 | D | + scale = [min=1.1684, max=4.6637] +24-11-19 20:12:09 | D | - Smoothing model.layers.14 +24-11-19 20:12:09 | D | - model.layers.14.self_attn.attn_k +24-11-19 20:12:09 | D | + w: None +24-11-19 20:12:09 | D | + x: None +24-11-19 20:12:09 | D | + y: sint8 +24-11-19 20:12:09 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:09 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:12:10 | D | + x - AbsMax +24-11-19 20:12:10 | D | + x = [min=1.3896, max=18.0781] +24-11-19 20:12:10 | D | + y - AbsMax +24-11-19 20:12:10 | D | + y = [min=1.5293, max=21.6875] +24-11-19 20:12:10 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:12:11 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:11 | D | - alpha = [ 0.5000] +24-11-19 20:12:11 | D | - beta = [ 0.0000] +24-11-19 20:12:11 | D | - sum error = [ 71.2931] +24-11-19 20:12:11 | D | - best error = [ 71.2931] +24-11-19 20:12:11 | D | + error = 71.2931 +24-11-19 20:12:11 | D | + scale = [min=1.2366, max=4.6570] +24-11-19 20:12:19 | D | - Smoothing model.layers.15 +24-11-19 20:12:19 | D | - model.layers.15.self_attn.attn_k +24-11-19 20:12:19 | D | + w: None +24-11-19 20:12:19 | D | + x: None +24-11-19 20:12:19 | D | + y: sint8 +24-11-19 20:12:19 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:19 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:12:19 | D | + x - AbsMax +24-11-19 20:12:19 | D | + x = [min=1.8525, max=18.3906] +24-11-19 20:12:20 | D | + y - AbsMax +24-11-19 20:12:20 | D | + y = [min=1.6855, max=20.2031] +24-11-19 20:12:20 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:12:20 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:20 | D | - alpha = [ 0.5000] +24-11-19 20:12:20 | D | - beta = [ 0.0000] +24-11-19 20:12:20 | D | - sum error = [ 75.2047] +24-11-19 20:12:20 | D | - best error = [ 75.2047] +24-11-19 20:12:20 | D | + error = 75.2047 +24-11-19 20:12:20 | D | + scale = [min=1.2983, max=4.4948] +24-11-19 20:12:29 | D | - Smoothing model.layers.16 +24-11-19 20:12:29 | D | - model.layers.16.self_attn.attn_k +24-11-19 20:12:29 | D | + w: None +24-11-19 20:12:29 | D | + x: None +24-11-19 20:12:29 | D | + y: sint8 +24-11-19 20:12:29 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:29 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:12:29 | D | + x - AbsMax +24-11-19 20:12:29 | D | + x = [min=1.8320, max=19.7656] +24-11-19 20:12:30 | D | + y - AbsMax +24-11-19 20:12:30 | D | + y = [min=1.5576, max=20.6719] +24-11-19 20:12:30 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:12:30 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:30 | D | - alpha = [ 0.5000] +24-11-19 20:12:30 | D | - beta = [ 0.0000] +24-11-19 20:12:30 | D | - sum error = [ 82.2865] +24-11-19 20:12:30 | D | - best error = [ 82.2865] +24-11-19 20:12:30 | D | + error = 82.2865 +24-11-19 20:12:30 | D | + scale = [min=1.2480, max=4.5466] +24-11-19 20:12:38 | D | - Smoothing model.layers.17 +24-11-19 20:12:38 | D | - model.layers.17.self_attn.attn_k +24-11-19 20:12:38 | D | + w: None +24-11-19 20:12:38 | D | + x: None +24-11-19 20:12:38 | D | + y: sint8 +24-11-19 20:12:38 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:38 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:12:38 | D | + x - AbsMax +24-11-19 20:12:38 | D | + x = [min=1.6250, max=19.6406] +24-11-19 20:12:39 | D | + y - AbsMax +24-11-19 20:12:39 | D | + y = [min=1.5977, max=27.4688] +24-11-19 20:12:39 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:12:39 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:39 | D | - alpha = [ 0.5000] +24-11-19 20:12:39 | D | - beta = [ 0.0000] +24-11-19 20:12:39 | D | - sum error = [ 86.2011] +24-11-19 20:12:39 | D | - best error = [ 86.2011] +24-11-19 20:12:39 | D | + error = 86.2011 +24-11-19 20:12:39 | D | + scale = [min=1.2640, max=5.2411] +24-11-19 20:12:47 | D | - Smoothing model.layers.18 +24-11-19 20:12:47 | D | - model.layers.18.self_attn.attn_k +24-11-19 20:12:47 | D | + w: None +24-11-19 20:12:47 | D | + x: None +24-11-19 20:12:47 | D | + y: sint8 +24-11-19 20:12:47 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:47 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:12:47 | D | + x - AbsMax +24-11-19 20:12:47 | D | + x = [min=1.4844, max=17.8594] +24-11-19 20:12:48 | D | + y - AbsMax +24-11-19 20:12:48 | D | + y = [min=1.5127, max=22.4375] +24-11-19 20:12:48 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:12:48 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:48 | D | - alpha = [ 0.5000] +24-11-19 20:12:48 | D | - beta = [ 0.0000] +24-11-19 20:12:48 | D | - sum error = [ 89.4479] +24-11-19 20:12:48 | D | - best error = [ 89.4479] +24-11-19 20:12:48 | D | + error = 89.4479 +24-11-19 20:12:48 | D | + scale = [min=1.2299, max=4.7368] +24-11-19 20:12:57 | D | - Smoothing model.layers.19 +24-11-19 20:12:57 | D | - model.layers.19.self_attn.attn_k +24-11-19 20:12:57 | D | + w: None +24-11-19 20:12:57 | D | + x: None +24-11-19 20:12:57 | D | + y: sint8 +24-11-19 20:12:57 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:57 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:12:57 | D | + x - AbsMax +24-11-19 20:12:57 | D | + x = [min=1.6582, max=17.9062] +24-11-19 20:12:57 | D | + y - AbsMax +24-11-19 20:12:57 | D | + y = [min=1.3662, max=23.0000] +24-11-19 20:12:57 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:12:57 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:57 | D | - alpha = [ 0.5000] +24-11-19 20:12:57 | D | - beta = [ 0.0000] +24-11-19 20:12:57 | D | - sum error = [ 83.0633] +24-11-19 20:12:57 | D | - best error = [ 83.0633] +24-11-19 20:12:57 | D | + error = 83.0633 +24-11-19 20:12:57 | D | + scale = [min=1.1689, max=4.7958] +24-11-19 20:13:06 | D | - Smoothing model.layers.20 +24-11-19 20:13:06 | D | - model.layers.20.self_attn.attn_k +24-11-19 20:13:06 | D | + w: None +24-11-19 20:13:06 | D | + x: None +24-11-19 20:13:06 | D | + y: sint8 +24-11-19 20:13:06 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:06 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:13:06 | D | + x - AbsMax +24-11-19 20:13:06 | D | + x = [min=1.3486, max=19.3906] +24-11-19 20:13:06 | D | + y - AbsMax +24-11-19 20:13:06 | D | + y = [min=1.2031, max=22.0000] +24-11-19 20:13:06 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:13:06 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:06 | D | - alpha = [ 0.5000] +24-11-19 20:13:06 | D | - beta = [ 0.0000] +24-11-19 20:13:06 | D | - sum error = [ 81.9549] +24-11-19 20:13:06 | D | - best error = [ 81.9549] +24-11-19 20:13:06 | D | + error = 81.9549 +24-11-19 20:13:06 | D | + scale = [min=1.0969, max=4.6904] +24-11-19 20:13:14 | D | - Smoothing model.layers.21 +24-11-19 20:13:14 | D | - model.layers.21.self_attn.attn_k +24-11-19 20:13:14 | D | + w: None +24-11-19 20:13:14 | D | + x: None +24-11-19 20:13:14 | D | + y: sint8 +24-11-19 20:13:14 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:14 | D | + finished parsing calibration arguments, ram usage: 14.1 +24-11-19 20:13:14 | D | + x - AbsMax +24-11-19 20:13:14 | D | + x = [min=1.1523, max=19.7500] +24-11-19 20:13:14 | D | + y - AbsMax +24-11-19 20:13:14 | D | + y = [min=1.1641, max=23.0781] +24-11-19 20:13:14 | D | + finished reseting calibrator, ram usage: 14.2 +24-11-19 20:13:15 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:15 | D | - alpha = [ 0.5000] +24-11-19 20:13:15 | D | - beta = [ 0.0000] +24-11-19 20:13:15 | D | - sum error = [ 84.6621] +24-11-19 20:13:15 | D | - best error = [ 84.6621] +24-11-19 20:13:15 | D | + error = 84.6621 +24-11-19 20:13:15 | D | + scale = [min=1.0789, max=4.8040] +24-11-19 20:13:23 | D | - Smoothing model.layers.22 +24-11-19 20:13:23 | D | - model.layers.22.self_attn.attn_k +24-11-19 20:13:23 | D | + w: None +24-11-19 20:13:23 | D | + x: None +24-11-19 20:13:23 | D | + y: sint8 +24-11-19 20:13:23 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:23 | D | + finished parsing calibration arguments, ram usage: 14.3 +24-11-19 20:13:23 | D | + x - AbsMax +24-11-19 20:13:23 | D | + x = [min=1.1621, max=20.6562] +24-11-19 20:13:24 | D | + y - AbsMax +24-11-19 20:13:24 | D | + y = [min=1.1426, max=25.5469] +24-11-19 20:13:24 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:13:24 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:24 | D | - alpha = [ 0.5000] +24-11-19 20:13:24 | D | - beta = [ 0.0000] +24-11-19 20:13:24 | D | - sum error = [ 117.9249] +24-11-19 20:13:24 | D | - best error = [ 117.9249] +24-11-19 20:13:24 | D | + error = 117.9249 +24-11-19 20:13:24 | D | + scale = [min=1.0689, max=5.0544] +24-11-19 20:13:32 | D | - Smoothing model.layers.23 +24-11-19 20:13:32 | D | - model.layers.23.self_attn.attn_k +24-11-19 20:13:32 | D | + w: None +24-11-19 20:13:32 | D | + x: None +24-11-19 20:13:32 | D | + y: sint8 +24-11-19 20:13:32 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:32 | D | + finished parsing calibration arguments, ram usage: 14.2 +24-11-19 20:13:32 | D | + x - AbsMax +24-11-19 20:13:32 | D | + x = [min=1.0938, max=18.7500] +24-11-19 20:13:32 | D | + y - AbsMax +24-11-19 20:13:32 | D | + y = [min=1.0469, max=24.5000] +24-11-19 20:13:32 | D | + finished reseting calibrator, ram usage: 14.2 +24-11-19 20:13:33 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:33 | D | - alpha = [ 0.5000] +24-11-19 20:13:33 | D | - beta = [ 0.0000] +24-11-19 20:13:33 | D | - sum error = [ 101.9240] +24-11-19 20:13:33 | D | - best error = [ 101.9240] +24-11-19 20:13:33 | D | + error = 101.9240 +24-11-19 20:13:33 | D | + scale = [min=1.0232, max=4.9497] +24-11-19 20:13:41 | D | - Smoothing model.layers.24 +24-11-19 20:13:41 | D | - model.layers.24.self_attn.attn_k +24-11-19 20:13:41 | D | + w: None +24-11-19 20:13:41 | D | + x: None +24-11-19 20:13:41 | D | + y: sint8 +24-11-19 20:13:41 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:41 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:13:41 | D | + x - AbsMax +24-11-19 20:13:41 | D | + x = [min=1.0059, max=18.2188] +24-11-19 20:13:41 | D | + y - AbsMax +24-11-19 20:13:41 | D | + y = [min=1.0029, max=25.1875] +24-11-19 20:13:41 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:13:42 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:42 | D | - alpha = [ 0.5000] +24-11-19 20:13:42 | D | - beta = [ 0.0000] +24-11-19 20:13:42 | D | - sum error = [ 113.2640] +24-11-19 20:13:42 | D | - best error = [ 113.2640] +24-11-19 20:13:42 | D | + error = 113.2640 +24-11-19 20:13:42 | D | + scale = [min=1.0015, max=5.0187] +24-11-19 20:13:50 | D | - Smoothing model.layers.25 +24-11-19 20:13:50 | D | - model.layers.25.self_attn.attn_k +24-11-19 20:13:50 | D | + w: None +24-11-19 20:13:50 | D | + x: None +24-11-19 20:13:50 | D | + y: sint8 +24-11-19 20:13:50 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:50 | D | + finished parsing calibration arguments, ram usage: 14.3 +24-11-19 20:13:50 | D | + x - AbsMax +24-11-19 20:13:50 | D | + x = [min=1.0840, max=18.4844] +24-11-19 20:13:50 | D | + y - AbsMax +24-11-19 20:13:50 | D | + y = [min=1.1045, max=23.4062] +24-11-19 20:13:50 | D | + finished reseting calibrator, ram usage: 14.3 +24-11-19 20:13:51 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:51 | D | - alpha = [ 0.5000] +24-11-19 20:13:51 | D | - beta = [ 0.0000] +24-11-19 20:13:51 | D | - sum error = [ 89.6070] +24-11-19 20:13:51 | D | - best error = [ 89.6070] +24-11-19 20:13:51 | D | + error = 89.6070 +24-11-19 20:13:51 | D | + scale = [min=1.0509, max=4.8380] +24-11-19 20:13:59 | D | - Smoothing model.layers.26 +24-11-19 20:13:59 | D | - model.layers.26.self_attn.attn_k +24-11-19 20:13:59 | D | + w: None +24-11-19 20:13:59 | D | + x: None +24-11-19 20:13:59 | D | + y: sint8 +24-11-19 20:13:59 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:59 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:13:59 | D | + x - AbsMax +24-11-19 20:13:59 | D | + x = [min=1.0654, max=19.7500] +24-11-19 20:13:59 | D | + y - AbsMax +24-11-19 20:13:59 | D | + y = [min=1.0107, max=24.1562] +24-11-19 20:13:59 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:13:59 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:59 | D | - alpha = [ 0.5000] +24-11-19 20:13:59 | D | - beta = [ 0.0000] +24-11-19 20:13:59 | D | - sum error = [ 125.3298] +24-11-19 20:13:59 | D | - best error = [ 125.3298] +24-11-19 20:13:59 | D | + error = 125.3298 +24-11-19 20:13:59 | D | + scale = [min=1.0054, max=4.9149] +24-11-19 20:14:07 | D | - Smoothing model.layers.27 +24-11-19 20:14:07 | D | - model.layers.27.self_attn.attn_k +24-11-19 20:14:07 | D | + w: None +24-11-19 20:14:07 | D | + x: None +24-11-19 20:14:07 | D | + y: sint8 +24-11-19 20:14:07 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:14:07 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:14:08 | D | + x - AbsMax +24-11-19 20:14:08 | D | + x = [min=1.9199, max=19.4375] +24-11-19 20:14:08 | D | + y - AbsMax +24-11-19 20:14:08 | D | + y = [min=1.9277, max=26.6250] +24-11-19 20:14:08 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:14:08 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:14:08 | D | - alpha = [ 0.5000] +24-11-19 20:14:08 | D | - beta = [ 0.0000] +24-11-19 20:14:08 | D | - sum error = [ 139.1551] +24-11-19 20:14:08 | D | - best error = [ 139.1551] +24-11-19 20:14:08 | D | + error = 139.1551 +24-11-19 20:14:08 | D | + scale = [min=1.3884, max=5.1599] +24-11-19 20:14:16 | D | - Smoothing model.layers.28 +24-11-19 20:14:16 | D | - model.layers.28.self_attn.attn_k +24-11-19 20:14:16 | D | + w: None +24-11-19 20:14:16 | D | + x: None +24-11-19 20:14:16 | D | + y: sint8 +24-11-19 20:14:16 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:14:16 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:14:17 | D | + x - AbsMax +24-11-19 20:14:17 | D | + x = [min=1.3467, max=20.7812] +24-11-19 20:14:17 | D | + y - AbsMax +24-11-19 20:14:17 | D | + y = [min=1.3350, max=24.9219] +24-11-19 20:14:17 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:14:18 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:14:18 | D | - alpha = [ 0.5000] +24-11-19 20:14:18 | D | - beta = [ 0.0000] +24-11-19 20:14:18 | D | - sum error = [ 128.2209] +24-11-19 20:14:18 | D | - best error = [ 128.2209] +24-11-19 20:14:18 | D | + error = 128.2209 +24-11-19 20:14:18 | D | + scale = [min=1.1554, max=4.9922] +24-11-19 20:14:26 | D | - Smoothing model.layers.29 +24-11-19 20:14:26 | D | - model.layers.29.self_attn.attn_k +24-11-19 20:14:26 | D | + w: None +24-11-19 20:14:26 | D | + x: None +24-11-19 20:14:26 | D | + y: sint8 +24-11-19 20:14:26 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:14:26 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:14:26 | D | + x - AbsMax +24-11-19 20:14:26 | D | + x = [min=1.9150, max=19.4062] +24-11-19 20:14:27 | D | + y - AbsMax +24-11-19 20:14:27 | D | + y = [min=1.3242, max=28.0312] +24-11-19 20:14:27 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:14:27 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:14:27 | D | - alpha = [ 0.5000] +24-11-19 20:14:27 | D | - beta = [ 0.0000] +24-11-19 20:14:27 | D | - sum error = [ 144.1357] +24-11-19 20:14:27 | D | - best error = [ 144.1357] +24-11-19 20:14:27 | D | + error = 144.1357 +24-11-19 20:14:27 | D | + scale = [min=1.1507, max=5.2945] +24-11-19 20:14:36 | D | - Smoothing model.layers.30 +24-11-19 20:14:36 | D | - model.layers.30.self_attn.attn_k +24-11-19 20:14:36 | D | + w: None +24-11-19 20:14:36 | D | + x: None +24-11-19 20:14:36 | D | + y: sint8 +24-11-19 20:14:36 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:14:36 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:14:36 | D | + x - AbsMax +24-11-19 20:14:36 | D | + x = [min=1.8291, max=18.8438] +24-11-19 20:14:36 | D | + y - AbsMax +24-11-19 20:14:36 | D | + y = [min=1.8379, max=23.5938] +24-11-19 20:14:36 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:14:37 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:14:37 | D | - alpha = [ 0.5000] +24-11-19 20:14:37 | D | - beta = [ 0.0000] +24-11-19 20:14:37 | D | - sum error = [ 139.7519] +24-11-19 20:14:37 | D | - best error = [ 139.7519] +24-11-19 20:14:37 | D | + error = 139.7519 +24-11-19 20:14:37 | D | + scale = [min=1.3557, max=4.8573] +24-11-19 20:14:45 | D | - Smoothing model.layers.31 +24-11-19 20:14:45 | D | - model.layers.31.self_attn.attn_k +24-11-19 20:14:45 | D | + w: None +24-11-19 20:14:45 | D | + x: None +24-11-19 20:14:45 | D | + y: sint8 +24-11-19 20:14:45 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:14:45 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:14:45 | D | + x - AbsMax +24-11-19 20:14:45 | D | + x = [min=2.4414, max=18.7188] +24-11-19 20:14:45 | D | + y - AbsMax +24-11-19 20:14:45 | D | + y = [min=1.7520, max=27.7344] +24-11-19 20:14:45 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:14:46 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:14:46 | D | - alpha = [ 0.5000] +24-11-19 20:14:46 | D | - beta = [ 0.0000] +24-11-19 20:14:46 | D | - sum error = [ 159.5317] +24-11-19 20:14:46 | D | - best error = [ 159.5317] +24-11-19 20:14:46 | D | + error = 159.5317 +24-11-19 20:14:46 | D | + scale = [min=1.3236, max=5.2663] +24-11-19 20:14:47 | I | - Saving smooth scales to runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/llama-2-7b-instruct-together-32k.pt +24-11-19 20:14:47 | I | - Linking smooth scales to runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200727.RUNNING/model/smooth.pt +24-11-19 20:14:47 | I | * Quantizing weights +24-11-19 20:14:47 | I | - Generating weight quantizer settings +24-11-19 20:14:47 | D | Starting new HTTPS connection (4): huggingface.co:443 +24-11-19 20:14:53 | D | Starting new HTTPS connection (5): huggingface.co:443 +24-11-19 20:15:05 | D | Starting new HTTPS connection (2): s3.amazonaws.com:443 +24-11-19 20:15:17 | W | Repo card metadata block was not found. Setting CardData to empty. +24-11-19 20:15:17 | D | Starting new HTTPS connection (6): huggingface.co:443 +24-11-19 20:15:47 | W | Using the latest cached version of the dataset since mit-han-lab/pile-val-backup couldn't be found on the Hugging Face Hub +24-11-19 20:15:47 | W | Found the latest cached dataset configuration 'default' at /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4 (last modified on Tue Oct 8 18:58:39 2024). +24-11-19 20:15:47 | D | Attempting to acquire lock 23438705778160 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:15:47 | D | Lock 23438705778160 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:15:47 | D | open file: /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4/dataset_info.json +24-11-19 20:15:47 | D | Attempting to release lock 23438705778160 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:15:47 | D | Lock 23438705778160 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:16:00 | D | - Quantizing layer model.layers.0 +24-11-19 20:16:00 | D | - Calibrating model.layers.0.self_attn.q_proj.weight +24-11-19 20:16:00 | D | + w: sint8 +24-11-19 20:16:00 | D | + x: None +24-11-19 20:16:00 | D | + y: None +24-11-19 20:16:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:16:00 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:16:00 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:16:01 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:16:01 | D | - range ratio = [ 1.0000] +24-11-19 20:16:01 | D | sum error = [ 0.1431] +24-11-19 20:16:01 | D | best error = [ 0.1431] +24-11-19 20:16:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:16:15 | D | sum error = [ 0.1409, 0.1453, 0.1495, 0.1556, 0.1677] +24-11-19 20:16:15 | D | best error = [ 0.1409, 0.1409, 0.1409, 0.1409, 0.1409] +24-11-19 20:16:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:16:15 | D | sum error = [ 0.1849, 0.2062, 0.2292, 0.2549, 0.2838] +24-11-19 20:16:15 | D | best error = [ 0.1409, 0.1409, 0.1409, 0.1409, 0.1409] +24-11-19 20:16:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:16:15 | D | sum error = [ 0.3282, 0.3751, 0.4210, 0.4847, 0.5516] +24-11-19 20:16:15 | D | best error = [ 0.1409, 0.1409, 0.1409, 0.1409, 0.1409] +24-11-19 20:16:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:16:15 | D | sum error = [ 0.6340, 0.7241, 0.8090, 0.9232, 1.0486] +24-11-19 20:16:15 | D | best error = [ 0.1409, 0.1409, 0.1409, 0.1409, 0.1409] +24-11-19 20:16:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:16:15 | D | sum error = [ 1.1670, 1.3183, 1.4809, 1.6669, 1.8685] +24-11-19 20:16:15 | D | best error = [ 0.1409, 0.1409, 0.1409, 0.1409, 0.1409] +24-11-19 20:16:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:16:15 | D | sum error = [ 2.0915, 2.3288, 2.5993, 2.8966, 3.2181] +24-11-19 20:16:15 | D | best error = [ 0.1409, 0.1409, 0.1409, 0.1409, 0.1409] +24-11-19 20:16:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:16:15 | D | sum error = [ 3.5737, 3.9595, 4.3856, 4.8498, 5.3488] +24-11-19 20:16:15 | D | best error = [ 0.1409, 0.1409, 0.1409, 0.1409, 0.1409] +24-11-19 20:16:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:16:15 | D | sum error = [ 5.8968, 6.4887, 7.1421, 7.8396, 8.5995] +24-11-19 20:16:15 | D | best error = [ 0.1409, 0.1409, 0.1409, 0.1409, 0.1409] +24-11-19 20:16:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:16:15 | D | sum error = [ 9.4213, 10.2926, 11.2456, 12.2682, 13.3661] +24-11-19 20:16:15 | D | best error = [ 0.1409, 0.1409, 0.1409, 0.1409, 0.1409] +24-11-19 20:16:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:16:15 | D | sum error = [ 14.5407, 15.8031, 17.1512, 18.5805, 20.1027] +24-11-19 20:16:15 | D | best error = [ 0.1409, 0.1409, 0.1409, 0.1409, 0.1409] +24-11-19 20:16:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:16:15 | D | sum error = [ 21.7350, 23.4519, 25.2865, 27.2323, 29.3036] +24-11-19 20:16:15 | D | best error = [ 0.1409, 0.1409, 0.1409, 0.1409, 0.1409] +24-11-19 20:16:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:16:15 | D | sum error = [ 31.4926, 33.8146, 36.2662, 38.8359, 41.5753] +24-11-19 20:16:15 | D | best error = [ 0.1409, 0.1409, 0.1409, 0.1409, 0.1409] +24-11-19 20:16:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:16:15 | D | sum error = [ 44.4442, 47.4688, 50.6614, 53.9924, 57.5066] +24-11-19 20:16:15 | D | best error = [ 0.1409, 0.1409, 0.1409, 0.1409, 0.1409] +24-11-19 20:16:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:16:15 | D | sum error = [ 61.2018, 65.0616, 69.1190, 73.3544, 77.8014] +24-11-19 20:16:15 | D | best error = [ 0.1409, 0.1409, 0.1409, 0.1409, 0.1409] +24-11-19 20:16:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:16:15 | D | sum error = [ 82.4618, 87.3463, 92.4249, 97.7492, 103.3080] +24-11-19 20:16:15 | D | best error = [ 0.1409, 0.1409, 0.1409, 0.1409, 0.1409] +24-11-19 20:16:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:16:15 | D | sum error = [ 109.1151, 115.1615, 121.5032, 128.0919, 134.9879] +24-11-19 20:16:15 | D | best error = [ 0.1409, 0.1409, 0.1409, 0.1409, 0.1409] +24-11-19 20:16:15 | D | + error = [0.1409] +24-11-19 20:16:15 | D | - Calibrating model.layers.0.self_attn.k_proj.weight +24-11-19 20:16:15 | D | + w: sint8 +24-11-19 20:16:15 | D | + x: None +24-11-19 20:16:15 | D | + y: None +24-11-19 20:16:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:16:15 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:16:15 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:16:15 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:16:16 | D | - range ratio = [ 1.0000] +24-11-19 20:16:16 | D | sum error = [ 0.1423] +24-11-19 20:16:16 | D | best error = [ 0.1423] +24-11-19 20:16:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:16:29 | D | sum error = [ 0.1491, 0.1528, 0.1576, 0.1576, 0.1775] +24-11-19 20:16:29 | D | best error = [ 0.1423, 0.1423, 0.1423, 0.1423, 0.1423] +24-11-19 20:16:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:16:29 | D | sum error = [ 0.1941, 0.2174, 0.2484, 0.2740, 0.3039] +24-11-19 20:16:29 | D | best error = [ 0.1423, 0.1423, 0.1423, 0.1423, 0.1423] +24-11-19 20:16:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:16:29 | D | sum error = [ 0.3396, 0.3634, 0.4293, 0.4758, 0.5502] +24-11-19 20:16:29 | D | best error = [ 0.1423, 0.1423, 0.1423, 0.1423, 0.1423] +24-11-19 20:16:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:16:29 | D | sum error = [ 0.6174, 0.6857, 0.7930, 0.8770, 1.0124] +24-11-19 20:16:29 | D | best error = [ 0.1423, 0.1423, 0.1423, 0.1423, 0.1423] +24-11-19 20:16:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:16:29 | D | sum error = [ 1.1292, 1.2456, 1.3711, 1.5542, 1.7141] +24-11-19 20:16:29 | D | best error = [ 0.1423, 0.1423, 0.1423, 0.1423, 0.1423] +24-11-19 20:16:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:16:29 | D | sum error = [ 1.9274, 2.1396, 2.4039, 2.6682, 2.9856] +24-11-19 20:16:29 | D | best error = [ 0.1423, 0.1423, 0.1423, 0.1423, 0.1423] +24-11-19 20:16:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:16:29 | D | sum error = [ 3.3430, 3.7093, 4.1218, 4.5615, 5.0560] +24-11-19 20:16:29 | D | best error = [ 0.1423, 0.1423, 0.1423, 0.1423, 0.1423] +24-11-19 20:16:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:16:29 | D | sum error = [ 5.5773, 6.1138, 6.7324, 7.3604, 8.0742] +24-11-19 20:16:29 | D | best error = [ 0.1423, 0.1423, 0.1423, 0.1423, 0.1423] +24-11-19 20:16:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:16:29 | D | sum error = [ 8.8245, 9.6296, 10.5480, 11.4733, 12.5441] +24-11-19 20:16:29 | D | best error = [ 0.1423, 0.1423, 0.1423, 0.1423, 0.1423] +24-11-19 20:16:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:16:29 | D | sum error = [ 13.6349, 14.7947, 16.0485, 17.3757, 18.8117] +24-11-19 20:16:29 | D | best error = [ 0.1423, 0.1423, 0.1423, 0.1423, 0.1423] +24-11-19 20:16:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:16:29 | D | sum error = [ 20.3264, 21.8989, 23.6553, 25.4237, 27.3205] +24-11-19 20:16:29 | D | best error = [ 0.1423, 0.1423, 0.1423, 0.1423, 0.1423] +24-11-19 20:16:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:16:29 | D | sum error = [ 29.3219, 31.4966, 33.7823, 36.1538, 38.6793] +24-11-19 20:16:29 | D | best error = [ 0.1423, 0.1423, 0.1423, 0.1423, 0.1423] +24-11-19 20:16:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:16:29 | D | sum error = [ 41.3657, 44.2002, 47.1601, 50.2504, 53.6161] +24-11-19 20:16:29 | D | best error = [ 0.1423, 0.1423, 0.1423, 0.1423, 0.1423] +24-11-19 20:16:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:16:29 | D | sum error = [ 57.0670, 60.7177, 64.5392, 68.5613, 72.8116] +24-11-19 20:16:29 | D | best error = [ 0.1423, 0.1423, 0.1423, 0.1423, 0.1423] +24-11-19 20:16:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:16:29 | D | sum error = [ 77.2610, 81.9196, 86.8232, 91.9585, 97.3522] +24-11-19 20:16:29 | D | best error = [ 0.1423, 0.1423, 0.1423, 0.1423, 0.1423] +24-11-19 20:16:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:16:29 | D | sum error = [ 103.0119, 108.9271, 115.1553, 121.6635, 128.4887] +24-11-19 20:16:29 | D | best error = [ 0.1423, 0.1423, 0.1423, 0.1423, 0.1423] +24-11-19 20:16:29 | D | + error = [0.1423] +24-11-19 20:16:29 | D | - Calibrating model.layers.0.self_attn.v_proj.weight +24-11-19 20:16:29 | D | + w: sint8 +24-11-19 20:16:29 | D | + x: None +24-11-19 20:16:29 | D | + y: None +24-11-19 20:16:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:16:29 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:16:29 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:16:29 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:16:29 | D | - range ratio = [ 1.0000] +24-11-19 20:16:29 | D | sum error = [ 0.1651] +24-11-19 20:16:29 | D | best error = [ 0.1651] +24-11-19 20:16:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:16:29 | D | sum error = [ 0.1647, 0.1643, 0.1650, 0.1667, 0.1701] +24-11-19 20:16:29 | D | best error = [ 0.1588, 0.1555, 0.1537, 0.1526, 0.1520] +24-11-19 20:16:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:16:29 | D | sum error = [ 0.1745, 0.1805, 0.1884, 0.1978, 0.2083] +24-11-19 20:16:29 | D | best error = [ 0.1518, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:16:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:16:29 | D | sum error = [ 0.2216, 0.2363, 0.2523, 0.2711, 0.2914] +24-11-19 20:16:29 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:16:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:16:29 | D | sum error = [ 0.3135, 0.3375, 0.3639, 0.3929, 0.4232] +24-11-19 20:16:29 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:16:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:16:29 | D | sum error = [ 0.4577, 0.4936, 0.5329, 0.5751, 0.6201] +24-11-19 20:16:29 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:16:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:16:29 | D | sum error = [ 0.6685, 0.7205, 0.7772, 0.8383, 0.9034] +24-11-19 20:16:29 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:16:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:16:29 | D | sum error = [ 0.9723, 1.0473, 1.1282, 1.2155, 1.3080] +24-11-19 20:16:29 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:16:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:16:29 | D | sum error = [ 1.4062, 1.5131, 1.6266, 1.7496, 1.8799] +24-11-19 20:16:29 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:16:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:16:29 | D | sum error = [ 2.0190, 2.1704, 2.3298, 2.5019, 2.6858] +24-11-19 20:16:29 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:16:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:16:29 | D | sum error = [ 2.8805, 3.0913, 3.3127, 3.5499, 3.8043] +24-11-19 20:16:29 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:16:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:16:29 | D | sum error = [ 4.0728, 4.3559, 4.6612, 4.9893, 5.3296] +24-11-19 20:16:29 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:16:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:16:29 | D | sum error = [ 5.6925, 6.0727, 6.4826, 6.9085, 7.3523] +24-11-19 20:16:29 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:16:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:16:29 | D | sum error = [ 7.8266, 8.3350, 8.8687, 9.4163, 9.9942] +24-11-19 20:16:29 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:16:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:16:29 | D | sum error = [ 10.6022, 11.2399, 11.9030, 12.5901, 13.3304] +24-11-19 20:16:29 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:16:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:16:29 | D | sum error = [ 14.0796, 14.8659, 15.6744, 16.5281, 17.3983] +24-11-19 20:16:29 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:16:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:16:29 | D | sum error = [ 18.3058, 19.2532, 20.2299, 21.2235, 22.2691] +24-11-19 20:16:29 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:16:29 | D | + error = [0.1517] +24-11-19 20:16:30 | D | - Calibrating model.layers.0.self_attn.o_proj.weight +24-11-19 20:16:30 | D | + w: sint8 +24-11-19 20:16:30 | D | + x: None +24-11-19 20:16:30 | D | + y: None +24-11-19 20:16:30 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:16:30 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:16:30 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:16:30 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:16:30 | D | - range ratio = [ 1.0000] +24-11-19 20:16:30 | D | sum error = [ 0.1585] +24-11-19 20:16:30 | D | best error = [ 0.1585] +24-11-19 20:16:30 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:16:30 | D | sum error = [ 0.1591, 0.1617, 0.1624, 0.1693, 0.1741] +24-11-19 20:16:30 | D | best error = [ 0.1245, 0.1112, 0.1047, 0.1010, 0.0989] +24-11-19 20:16:30 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:16:30 | D | sum error = [ 0.1799, 0.1878, 0.2007, 0.2118, 0.2274] +24-11-19 20:16:30 | D | best error = [ 0.0979, 0.0974, 0.0971, 0.0969, 0.0968] +24-11-19 20:16:30 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:16:30 | D | sum error = [ 0.2414, 0.2578, 0.2752, 0.2941, 0.3122] +24-11-19 20:16:30 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:16:30 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:16:30 | D | sum error = [ 0.3338, 0.3557, 0.3783, 0.4040, 0.4267] +24-11-19 20:16:30 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:16:30 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:16:30 | D | sum error = [ 0.4520, 0.4809, 0.5094, 0.5403, 0.5700] +24-11-19 20:16:30 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:16:30 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:16:30 | D | sum error = [ 0.6028, 0.6375, 0.6712, 0.7089, 0.7474] +24-11-19 20:16:30 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:16:30 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:16:30 | D | sum error = [ 0.7874, 0.8281, 0.8725, 0.9187, 0.9661] +24-11-19 20:16:30 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:16:30 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:16:30 | D | sum error = [ 1.0137, 1.0659, 1.1194, 1.1759, 1.2330] +24-11-19 20:16:30 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:16:30 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:16:30 | D | sum error = [ 1.2957, 1.3596, 1.4265, 1.4964, 1.5682] +24-11-19 20:16:30 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:16:30 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:16:30 | D | sum error = [ 1.6440, 1.7248, 1.8089, 1.8963, 1.9871] +24-11-19 20:16:30 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:16:30 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:16:30 | D | sum error = [ 2.0834, 2.1848, 2.2892, 2.4001, 2.5167] +24-11-19 20:16:30 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:16:30 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:16:30 | D | sum error = [ 2.6383, 2.7670, 2.9031, 3.0450, 3.1961] +24-11-19 20:16:30 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:16:30 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:16:30 | D | sum error = [ 3.3544, 3.5217, 3.6983, 3.8857, 4.0827] +24-11-19 20:16:30 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:16:30 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:16:30 | D | sum error = [ 4.2920, 4.5126, 4.7459, 4.9923, 5.2528] +24-11-19 20:16:30 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:16:30 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:16:30 | D | sum error = [ 5.5273, 5.8190, 6.1280, 6.4532, 6.7988] +24-11-19 20:16:30 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:16:30 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:16:30 | D | sum error = [ 7.1636, 7.5506, 7.9603, 8.3935, 8.8513] +24-11-19 20:16:30 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:16:30 | D | + error = [0.0968] +24-11-19 20:16:30 | D | - Calibrating model.layers.0.mlp.up_proj.weight +24-11-19 20:16:30 | D | + w: sint8 +24-11-19 20:16:30 | D | + x: None +24-11-19 20:16:30 | D | + y: None +24-11-19 20:16:30 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:16:30 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:16:30 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:16:31 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:16:31 | D | - range ratio = [ 1.0000] +24-11-19 20:16:31 | D | sum error = [ 1.1909] +24-11-19 20:16:31 | D | best error = [ 1.1909] +24-11-19 20:16:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:16:31 | D | sum error = [ 1.1896, 1.1912, 1.1942, 1.2135, 1.2268] +24-11-19 20:16:31 | D | best error = [ 0.9639, 0.8905, 0.8553, 0.8367, 0.8267] +24-11-19 20:16:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:16:31 | D | sum error = [ 1.2651, 1.3033, 1.3597, 1.4171, 1.4855] +24-11-19 20:16:31 | D | best error = [ 0.8211, 0.8183, 0.8168, 0.8163, 0.8160] +24-11-19 20:16:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:16:31 | D | sum error = [ 1.5698, 1.6663, 1.7880, 1.9086, 2.0377] +24-11-19 20:16:31 | D | best error = [ 0.8160, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 20:16:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:16:31 | D | sum error = [ 2.1845, 2.3469, 2.5103, 2.6824, 2.8711] +24-11-19 20:16:31 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 20:16:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:16:31 | D | sum error = [ 3.0858, 3.2954, 3.5313, 3.7806, 4.0482] +24-11-19 20:16:31 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 20:16:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:16:31 | D | sum error = [ 4.3289, 4.6241, 4.9415, 5.2807, 5.6337] +24-11-19 20:16:31 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 20:16:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:16:31 | D | sum error = [ 6.0131, 6.4133, 6.8433, 7.2954, 7.7748] +24-11-19 20:16:31 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 20:16:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:16:31 | D | sum error = [ 8.2772, 8.8130, 9.3706, 9.9703, 10.5992] +24-11-19 20:16:31 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 20:16:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:16:31 | D | sum error = [ 11.2583, 11.9630, 12.6927, 13.4808, 14.3067] +24-11-19 20:16:31 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 20:16:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:16:31 | D | sum error = [ 15.1677, 16.0743, 17.0267, 18.0283, 19.0876] +24-11-19 20:16:31 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 20:16:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:16:31 | D | sum error = [ 20.2076, 21.3658, 22.5883, 23.8657, 25.2197] +24-11-19 20:16:31 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 20:16:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:16:31 | D | sum error = [ 26.6284, 28.1046, 29.6639, 31.2890, 32.9749] +24-11-19 20:16:31 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 20:16:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:16:31 | D | sum error = [ 34.7494, 36.6033, 38.5302, 40.5538, 42.6553] +24-11-19 20:16:31 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 20:16:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:16:31 | D | sum error = [ 44.8414, 47.1222, 49.4935, 51.9614, 54.5280] +24-11-19 20:16:31 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 20:16:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:16:31 | D | sum error = [ 57.1927, 59.9488, 62.8102, 65.7721, 68.8489] +24-11-19 20:16:31 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 20:16:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:16:31 | D | sum error = [ 72.0007, 75.2735, 78.6432, 82.1058, 85.6965] +24-11-19 20:16:31 | D | best error = [ 0.8159, 0.8159, 0.8159, 0.8159, 0.8159] +24-11-19 20:16:31 | D | + error = [0.8159] +24-11-19 20:16:32 | D | - Calibrating model.layers.0.mlp.gate_proj.weight +24-11-19 20:16:32 | D | + w: sint8 +24-11-19 20:16:32 | D | + x: None +24-11-19 20:16:32 | D | + y: None +24-11-19 20:16:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:16:32 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:16:32 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:16:32 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:16:32 | D | - range ratio = [ 1.0000] +24-11-19 20:16:32 | D | sum error = [ 1.2261] +24-11-19 20:16:32 | D | best error = [ 1.2261] +24-11-19 20:16:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:16:33 | D | sum error = [ 1.2228, 1.2239, 1.2226, 1.2215, 1.2576] +24-11-19 20:16:33 | D | best error = [ 0.9923, 0.9161, 0.8771, 0.8572, 0.8462] +24-11-19 20:16:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:16:33 | D | sum error = [ 1.2904, 1.3260, 1.3903, 1.4515, 1.5392] +24-11-19 20:16:33 | D | best error = [ 0.8404, 0.8374, 0.8360, 0.8355, 0.8353] +24-11-19 20:16:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:16:33 | D | sum error = [ 1.6163, 1.7165, 1.8486, 1.9558, 2.1090] +24-11-19 20:16:33 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 20:16:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:16:33 | D | sum error = [ 2.2726, 2.4347, 2.6099, 2.8144, 3.0236] +24-11-19 20:16:33 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 20:16:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:16:33 | D | sum error = [ 3.2486, 3.4876, 3.7394, 4.0343, 4.3168] +24-11-19 20:16:33 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 20:16:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:16:33 | D | sum error = [ 4.6388, 4.9653, 5.3253, 5.7070, 6.1137] +24-11-19 20:16:33 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 20:16:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:16:33 | D | sum error = [ 6.5313, 6.9945, 7.4754, 7.9902, 8.5415] +24-11-19 20:16:33 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 20:16:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:16:33 | D | sum error = [ 9.1272, 9.7508, 10.3936, 11.0987, 11.8281] +24-11-19 20:16:33 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 20:16:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:16:33 | D | sum error = [ 12.6097, 13.4419, 14.3238, 15.2500, 16.2558] +24-11-19 20:16:33 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 20:16:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:16:33 | D | sum error = [ 17.3044, 18.4120, 19.5855, 20.8205, 22.1311] +24-11-19 20:16:33 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 20:16:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:16:33 | D | sum error = [ 23.5214, 24.9776, 26.5306, 28.1439, 29.8597] +24-11-19 20:16:33 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 20:16:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:16:33 | D | sum error = [ 31.6604, 33.5641, 35.5506, 37.6390, 39.8416] +24-11-19 20:16:33 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 20:16:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:16:33 | D | sum error = [ 42.1561, 44.5900, 47.1316, 49.7902, 52.5759] +24-11-19 20:16:33 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 20:16:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:16:33 | D | sum error = [ 55.4897, 58.5550, 61.7187, 65.0351, 68.5031] +24-11-19 20:16:33 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 20:16:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:16:33 | D | sum error = [ 72.0890, 75.8175, 79.6838, 83.6838, 87.8512] +24-11-19 20:16:33 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 20:16:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:16:33 | D | sum error = [ 92.1109, 96.5692, 101.1466, 105.8592, 110.7484] +24-11-19 20:16:33 | D | best error = [ 0.8353, 0.8353, 0.8353, 0.8353, 0.8353] +24-11-19 20:16:33 | D | + error = [0.8353] +24-11-19 20:16:33 | D | - Calibrating model.layers.0.mlp.down_proj.weight +24-11-19 20:16:33 | D | + w: sint8 +24-11-19 20:16:33 | D | + x: None +24-11-19 20:16:33 | D | + y: None +24-11-19 20:16:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:16:33 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:16:33 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:16:33 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:16:33 | D | - range ratio = [ 1.0000] +24-11-19 20:16:33 | D | sum error = [ 0.1969] +24-11-19 20:16:33 | D | best error = [ 0.1969] +24-11-19 20:16:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:16:34 | D | sum error = [ 0.1958, 0.1934, 0.1939, 0.1917, 0.1926] +24-11-19 20:16:34 | D | best error = [ 0.1723, 0.1613, 0.1548, 0.1501, 0.1468] +24-11-19 20:16:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:16:34 | D | sum error = [ 0.1940, 0.1927, 0.1943, 0.1959, 0.2003] +24-11-19 20:16:34 | D | best error = [ 0.1439, 0.1415, 0.1397, 0.1383, 0.1370] +24-11-19 20:16:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:16:34 | D | sum error = [ 0.2050, 0.2100, 0.2159, 0.2226, 0.2311] +24-11-19 20:16:34 | D | best error = [ 0.1359, 0.1351, 0.1343, 0.1336, 0.1331] +24-11-19 20:16:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:16:34 | D | sum error = [ 0.2425, 0.2537, 0.2670, 0.2825, 0.2989] +24-11-19 20:16:34 | D | best error = [ 0.1327, 0.1324, 0.1321, 0.1319, 0.1318] +24-11-19 20:16:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:16:34 | D | sum error = [ 0.3182, 0.3375, 0.3598, 0.3831, 0.4070] +24-11-19 20:16:34 | D | best error = [ 0.1317, 0.1316, 0.1315, 0.1315, 0.1315] +24-11-19 20:16:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:16:34 | D | sum error = [ 0.4340, 0.4635, 0.4938, 0.5285, 0.5646] +24-11-19 20:16:34 | D | best error = [ 0.1315, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 20:16:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:16:34 | D | sum error = [ 0.6028, 0.6435, 0.6871, 0.7324, 0.7808] +24-11-19 20:16:34 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 20:16:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:16:34 | D | sum error = [ 0.8319, 0.8868, 0.9468, 1.0090, 1.0750] +24-11-19 20:16:34 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 20:16:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:16:34 | D | sum error = [ 1.1467, 1.2227, 1.3038, 1.3910, 1.4844] +24-11-19 20:16:34 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 20:16:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:16:34 | D | sum error = [ 1.5837, 1.6906, 1.8035, 1.9264, 2.0550] +24-11-19 20:16:34 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 20:16:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:16:34 | D | sum error = [ 2.1938, 2.3410, 2.4987, 2.6668, 2.8448] +24-11-19 20:16:34 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 20:16:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:16:34 | D | sum error = [ 3.0352, 3.2382, 3.4544, 3.6837, 3.9285] +24-11-19 20:16:34 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 20:16:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:16:34 | D | sum error = [ 4.1888, 4.4646, 4.7577, 5.0693, 5.3996] +24-11-19 20:16:34 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 20:16:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:16:34 | D | sum error = [ 5.7503, 6.1223, 6.5160, 6.9326, 7.3720] +24-11-19 20:16:34 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 20:16:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:16:34 | D | sum error = [ 7.8356, 8.3249, 8.8398, 9.3800, 9.9484] +24-11-19 20:16:34 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 20:16:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:16:34 | D | sum error = [ 10.5437, 11.1683, 11.8217, 12.5044, 13.2162] +24-11-19 20:16:34 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 20:16:34 | D | + error = [0.1314] +24-11-19 20:16:34 | D | - Quantizing model.layers.0.self_attn.q_proj.weight +24-11-19 20:16:37 | D | - Quantizing model.layers.0.self_attn.k_proj.weight +24-11-19 20:16:39 | D | - Quantizing model.layers.0.self_attn.v_proj.weight +24-11-19 20:16:41 | D | - Quantizing model.layers.0.self_attn.o_proj.weight +24-11-19 20:16:43 | D | - Quantizing model.layers.0.mlp.up_proj.weight +24-11-19 20:16:47 | D | - Quantizing model.layers.0.mlp.gate_proj.weight +24-11-19 20:16:49 | D | - Quantizing model.layers.0.mlp.down_proj.weight +24-11-19 20:17:00 | D | - Quantizing layer model.layers.1 +24-11-19 20:17:00 | D | - Calibrating model.layers.1.self_attn.q_proj.weight +24-11-19 20:17:00 | D | + w: sint8 +24-11-19 20:17:00 | D | + x: None +24-11-19 20:17:00 | D | + y: None +24-11-19 20:17:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:17:00 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:17:00 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:17:00 | D | + finished calculating the original outputs, ram usage: 13.4 +24-11-19 20:17:00 | D | - range ratio = [ 1.0000] +24-11-19 20:17:00 | D | sum error = [ 0.4162] +24-11-19 20:17:00 | D | best error = [ 0.4162] +24-11-19 20:17:13 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:13 | D | sum error = [ 0.4111, 0.4250, 0.4332, 0.4422, 0.4610] +24-11-19 20:17:13 | D | best error = [ 0.4111, 0.4111, 0.4111, 0.4111, 0.4111] +24-11-19 20:17:13 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:13 | D | sum error = [ 0.4425, 0.4857, 0.4809, 0.5539, 0.5561] +24-11-19 20:17:13 | D | best error = [ 0.4111, 0.4111, 0.4111, 0.4111, 0.4111] +24-11-19 20:17:13 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:13 | D | sum error = [ 0.6454, 0.6695, 0.7733, 0.8237, 0.9051] +24-11-19 20:17:13 | D | best error = [ 0.4111, 0.4111, 0.4111, 0.4111, 0.4111] +24-11-19 20:17:13 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:13 | D | sum error = [ 1.0068, 1.1354, 1.2127, 1.3787, 1.5630] +24-11-19 20:17:13 | D | best error = [ 0.4111, 0.4111, 0.4111, 0.4111, 0.4111] +24-11-19 20:17:13 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:13 | D | sum error = [ 1.7511, 1.9369, 2.1867, 2.4236, 2.7271] +24-11-19 20:17:13 | D | best error = [ 0.4111, 0.4111, 0.4111, 0.4111, 0.4111] +24-11-19 20:17:13 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:13 | D | sum error = [ 3.0245, 3.3718, 3.7514, 4.1295, 4.5903] +24-11-19 20:17:13 | D | best error = [ 0.4111, 0.4111, 0.4111, 0.4111, 0.4111] +24-11-19 20:17:13 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:13 | D | sum error = [ 5.1820, 5.6843, 6.3155, 6.9974, 7.7279] +24-11-19 20:17:13 | D | best error = [ 0.4111, 0.4111, 0.4111, 0.4111, 0.4111] +24-11-19 20:17:13 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:13 | D | sum error = [ 8.5101, 9.3356, 10.2903, 11.3113, 12.3892] +24-11-19 20:17:13 | D | best error = [ 0.4111, 0.4111, 0.4111, 0.4111, 0.4111] +24-11-19 20:17:13 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:13 | D | sum error = [ 13.5613, 14.8580, 16.2549, 17.7841, 19.4371] +24-11-19 20:17:13 | D | best error = [ 0.4111, 0.4111, 0.4111, 0.4111, 0.4111] +24-11-19 20:17:13 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:13 | D | sum error = [ 21.1996, 23.0572, 25.1054, 27.3389, 29.7099] +24-11-19 20:17:13 | D | best error = [ 0.4111, 0.4111, 0.4111, 0.4111, 0.4111] +24-11-19 20:17:13 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:13 | D | sum error = [ 32.1983, 34.9332, 37.8065, 40.8642, 44.1078] +24-11-19 20:17:13 | D | best error = [ 0.4111, 0.4111, 0.4111, 0.4111, 0.4111] +24-11-19 20:17:13 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:13 | D | sum error = [ 47.5744, 51.2742, 55.1739, 59.3057, 63.7669] +24-11-19 20:17:13 | D | best error = [ 0.4111, 0.4111, 0.4111, 0.4111, 0.4111] +24-11-19 20:17:13 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:13 | D | sum error = [ 68.4046, 73.3170, 78.5196, 83.9922, 89.7661] +24-11-19 20:17:13 | D | best error = [ 0.4111, 0.4111, 0.4111, 0.4111, 0.4111] +24-11-19 20:17:13 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:13 | D | sum error = [ 95.8752, 102.3165, 109.0857, 116.1493, 123.5845] +24-11-19 20:17:13 | D | best error = [ 0.4111, 0.4111, 0.4111, 0.4111, 0.4111] +24-11-19 20:17:13 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:13 | D | sum error = [ 131.3844, 139.5696, 148.0726, 156.9506, 166.2265] +24-11-19 20:17:13 | D | best error = [ 0.4111, 0.4111, 0.4111, 0.4111, 0.4111] +24-11-19 20:17:13 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:13 | D | sum error = [ 175.8792, 185.9757, 196.3708, 207.1546, 218.3686] +24-11-19 20:17:13 | D | best error = [ 0.4111, 0.4111, 0.4111, 0.4111, 0.4111] +24-11-19 20:17:13 | D | + error = [0.4111] +24-11-19 20:17:13 | D | - Calibrating model.layers.1.self_attn.k_proj.weight +24-11-19 20:17:13 | D | + w: sint8 +24-11-19 20:17:13 | D | + x: None +24-11-19 20:17:13 | D | + y: None +24-11-19 20:17:13 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:17:13 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:17:14 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:17:14 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:17:14 | D | - range ratio = [ 1.0000] +24-11-19 20:17:14 | D | sum error = [ 0.4810] +24-11-19 20:17:14 | D | best error = [ 0.4810] +24-11-19 20:17:27 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:27 | D | sum error = [ 0.4982, 0.4972, 0.5120, 0.5080, 0.5181] +24-11-19 20:17:27 | D | best error = [ 0.4810, 0.4810, 0.4810, 0.4810, 0.4810] +24-11-19 20:17:27 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:27 | D | sum error = [ 0.5869, 0.5634, 0.6119, 0.6191, 0.6800] +24-11-19 20:17:27 | D | best error = [ 0.4810, 0.4810, 0.4810, 0.4810, 0.4810] +24-11-19 20:17:27 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:27 | D | sum error = [ 0.7247, 0.7877, 0.8317, 0.9796, 1.1090] +24-11-19 20:17:27 | D | best error = [ 0.4810, 0.4810, 0.4810, 0.4810, 0.4810] +24-11-19 20:17:27 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:27 | D | sum error = [ 1.2177, 1.3367, 1.4646, 1.6172, 1.7734] +24-11-19 20:17:27 | D | best error = [ 0.4810, 0.4810, 0.4810, 0.4810, 0.4810] +24-11-19 20:17:27 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:27 | D | sum error = [ 2.0228, 2.2713, 2.4468, 2.7623, 2.9983] +24-11-19 20:17:27 | D | best error = [ 0.4810, 0.4810, 0.4810, 0.4810, 0.4810] +24-11-19 20:17:27 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:27 | D | sum error = [ 3.3308, 3.7296, 4.1537, 4.6782, 5.0801] +24-11-19 20:17:27 | D | best error = [ 0.4810, 0.4810, 0.4810, 0.4810, 0.4810] +24-11-19 20:17:27 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:27 | D | sum error = [ 5.6086, 6.1725, 6.8159, 7.5072, 8.3463] +24-11-19 20:17:27 | D | best error = [ 0.4810, 0.4810, 0.4810, 0.4810, 0.4810] +24-11-19 20:17:27 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:27 | D | sum error = [ 9.1378, 10.0515, 11.0125, 12.0756, 13.1901] +24-11-19 20:17:27 | D | best error = [ 0.4810, 0.4810, 0.4810, 0.4810, 0.4810] +24-11-19 20:17:27 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:27 | D | sum error = [ 14.4604, 15.8127, 17.2647, 18.8699, 20.5253] +24-11-19 20:17:27 | D | best error = [ 0.4810, 0.4810, 0.4810, 0.4810, 0.4810] +24-11-19 20:17:27 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:27 | D | sum error = [ 22.4284, 24.3053, 26.3159, 28.5836, 30.9711] +24-11-19 20:17:27 | D | best error = [ 0.4810, 0.4810, 0.4810, 0.4810, 0.4810] +24-11-19 20:17:27 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:27 | D | sum error = [ 33.5465, 36.3380, 39.2191, 42.3355, 45.7226] +24-11-19 20:17:27 | D | best error = [ 0.4810, 0.4810, 0.4810, 0.4810, 0.4810] +24-11-19 20:17:27 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:27 | D | sum error = [ 49.2193, 52.9975, 56.9320, 61.2348, 65.7445] +24-11-19 20:17:27 | D | best error = [ 0.4810, 0.4810, 0.4810, 0.4810, 0.4810] +24-11-19 20:17:27 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:27 | D | sum error = [ 70.5551, 75.3863, 80.7366, 86.4034, 92.1328] +24-11-19 20:17:27 | D | best error = [ 0.4810, 0.4810, 0.4810, 0.4810, 0.4810] +24-11-19 20:17:27 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:27 | D | sum error = [ 98.3366, 104.8468, 111.7613, 118.6620, 126.1229] +24-11-19 20:17:27 | D | best error = [ 0.4810, 0.4810, 0.4810, 0.4810, 0.4810] +24-11-19 20:17:27 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:27 | D | sum error = [ 133.9761, 142.0961, 150.4402, 159.2050, 168.5896] +24-11-19 20:17:27 | D | best error = [ 0.4810, 0.4810, 0.4810, 0.4810, 0.4810] +24-11-19 20:17:27 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:27 | D | sum error = [ 178.0944, 188.1060, 198.4471, 209.4591, 220.3400] +24-11-19 20:17:27 | D | best error = [ 0.4810, 0.4810, 0.4810, 0.4810, 0.4810] +24-11-19 20:17:27 | D | + error = [0.4810] +24-11-19 20:17:27 | D | - Calibrating model.layers.1.self_attn.v_proj.weight +24-11-19 20:17:27 | D | + w: sint8 +24-11-19 20:17:27 | D | + x: None +24-11-19 20:17:27 | D | + y: None +24-11-19 20:17:27 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:17:27 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:17:27 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:17:28 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:17:28 | D | - range ratio = [ 1.0000] +24-11-19 20:17:28 | D | sum error = [ 0.5679] +24-11-19 20:17:28 | D | best error = [ 0.5679] +24-11-19 20:17:28 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:28 | D | sum error = [ 0.5626, 0.5602, 0.5617, 0.5667, 0.5797] +24-11-19 20:17:28 | D | best error = [ 0.4617, 0.4273, 0.4105, 0.4014, 0.3963] +24-11-19 20:17:28 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:28 | D | sum error = [ 0.6023, 0.6175, 0.6358, 0.6753, 0.7081] +24-11-19 20:17:28 | D | best error = [ 0.3935, 0.3918, 0.3911, 0.3908, 0.3907] +24-11-19 20:17:28 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:28 | D | sum error = [ 0.7568, 0.7966, 0.8521, 0.9004, 0.9724] +24-11-19 20:17:28 | D | best error = [ 0.3906, 0.3906, 0.3906, 0.3906, 0.3906] +24-11-19 20:17:28 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:28 | D | sum error = [ 1.0364, 1.1098, 1.1929, 1.2775, 1.3714] +24-11-19 20:17:28 | D | best error = [ 0.3906, 0.3906, 0.3906, 0.3906, 0.3906] +24-11-19 20:17:28 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:28 | D | sum error = [ 1.4677, 1.5680, 1.6871, 1.8023, 1.9202] +24-11-19 20:17:28 | D | best error = [ 0.3906, 0.3906, 0.3906, 0.3906, 0.3906] +24-11-19 20:17:28 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:28 | D | sum error = [ 2.0587, 2.1934, 2.3486, 2.5043, 2.6679] +24-11-19 20:17:28 | D | best error = [ 0.3906, 0.3906, 0.3906, 0.3906, 0.3906] +24-11-19 20:17:28 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:28 | D | sum error = [ 2.8503, 3.0405, 3.2322, 3.4503, 3.6688] +24-11-19 20:17:28 | D | best error = [ 0.3906, 0.3906, 0.3906, 0.3906, 0.3906] +24-11-19 20:17:28 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:28 | D | sum error = [ 3.9028, 4.1470, 4.4098, 4.6826, 4.9729] +24-11-19 20:17:28 | D | best error = [ 0.3906, 0.3906, 0.3906, 0.3906, 0.3906] +24-11-19 20:17:28 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:28 | D | sum error = [ 5.2767, 5.6024, 5.9407, 6.2933, 6.6711] +24-11-19 20:17:28 | D | best error = [ 0.3906, 0.3906, 0.3906, 0.3906, 0.3906] +24-11-19 20:17:28 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:28 | D | sum error = [ 7.0604, 7.4788, 7.9150, 8.3674, 8.8420] +24-11-19 20:17:28 | D | best error = [ 0.3906, 0.3906, 0.3906, 0.3906, 0.3906] +24-11-19 20:17:28 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:28 | D | sum error = [ 9.3424, 9.8636, 10.4106, 10.9835, 11.5830] +24-11-19 20:17:28 | D | best error = [ 0.3906, 0.3906, 0.3906, 0.3906, 0.3906] +24-11-19 20:17:28 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:28 | D | sum error = [ 12.2013, 12.8571, 13.5404, 14.2492, 15.0002] +24-11-19 20:17:28 | D | best error = [ 0.3906, 0.3906, 0.3906, 0.3906, 0.3906] +24-11-19 20:17:28 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:28 | D | sum error = [ 15.7839, 16.6027, 17.4595, 18.3437, 19.2687] +24-11-19 20:17:28 | D | best error = [ 0.3906, 0.3906, 0.3906, 0.3906, 0.3906] +24-11-19 20:17:28 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:28 | D | sum error = [ 20.2355, 21.2376, 22.2767, 23.3615, 24.4907] +24-11-19 20:17:28 | D | best error = [ 0.3906, 0.3906, 0.3906, 0.3906, 0.3906] +24-11-19 20:17:28 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:28 | D | sum error = [ 25.6674, 26.8769, 28.1361, 29.4453, 30.8034] +24-11-19 20:17:28 | D | best error = [ 0.3906, 0.3906, 0.3906, 0.3906, 0.3906] +24-11-19 20:17:28 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:28 | D | sum error = [ 32.1976, 33.6411, 35.1321, 36.6641, 38.2524] +24-11-19 20:17:28 | D | best error = [ 0.3906, 0.3906, 0.3906, 0.3906, 0.3906] +24-11-19 20:17:28 | D | + error = [0.3906] +24-11-19 20:17:28 | D | - Calibrating model.layers.1.self_attn.o_proj.weight +24-11-19 20:17:28 | D | + w: sint8 +24-11-19 20:17:28 | D | + x: None +24-11-19 20:17:28 | D | + y: None +24-11-19 20:17:28 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:17:28 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:17:28 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:17:28 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:17:28 | D | - range ratio = [ 1.0000] +24-11-19 20:17:28 | D | sum error = [ 0.1965] +24-11-19 20:17:28 | D | best error = [ 0.1965] +24-11-19 20:17:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:29 | D | sum error = [ 0.1936, 0.1951, 0.1969, 0.1994, 0.2043] +24-11-19 20:17:29 | D | best error = [ 0.1709, 0.1608, 0.1561, 0.1534, 0.1524] +24-11-19 20:17:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:29 | D | sum error = [ 0.2113, 0.2203, 0.2320, 0.2441, 0.2573] +24-11-19 20:17:29 | D | best error = [ 0.1518, 0.1514, 0.1514, 0.1513, 0.1513] +24-11-19 20:17:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:29 | D | sum error = [ 0.2714, 0.2889, 0.3084, 0.3294, 0.3507] +24-11-19 20:17:29 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:17:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:29 | D | sum error = [ 0.3744, 0.3999, 0.4273, 0.4563, 0.4857] +24-11-19 20:17:29 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:17:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:29 | D | sum error = [ 0.5169, 0.5507, 0.5858, 0.6230, 0.6620] +24-11-19 20:17:29 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:17:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:29 | D | sum error = [ 0.7030, 0.7464, 0.7909, 0.8374, 0.8870] +24-11-19 20:17:29 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:17:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:29 | D | sum error = [ 0.9382, 0.9923, 1.0491, 1.1076, 1.1698] +24-11-19 20:17:29 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:17:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:29 | D | sum error = [ 1.2346, 1.3029, 1.3743, 1.4495, 1.5282] +24-11-19 20:17:29 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:17:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:29 | D | sum error = [ 1.6111, 1.6968, 1.7874, 1.8829, 1.9818] +24-11-19 20:17:29 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:17:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:29 | D | sum error = [ 2.0868, 2.1954, 2.3100, 2.4311, 2.5569] +24-11-19 20:17:29 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:17:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:29 | D | sum error = [ 2.6892, 2.8286, 2.9733, 3.1272, 3.2879] +24-11-19 20:17:29 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:17:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:29 | D | sum error = [ 3.4566, 3.6337, 3.8203, 4.0149, 4.2215] +24-11-19 20:17:29 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:17:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:29 | D | sum error = [ 4.4377, 4.6649, 4.9037, 5.1567, 5.4231] +24-11-19 20:17:29 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:17:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:29 | D | sum error = [ 5.7039, 6.0006, 6.3127, 6.6434, 6.9920] +24-11-19 20:17:29 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:17:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:29 | D | sum error = [ 7.3615, 7.7525, 8.1672, 8.6063, 9.0705] +24-11-19 20:17:29 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:17:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:29 | D | sum error = [ 9.5634, 10.0869, 10.6435, 11.2359, 11.8669] +24-11-19 20:17:29 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:17:29 | D | + error = [0.1513] +24-11-19 20:17:29 | D | - Calibrating model.layers.1.mlp.up_proj.weight +24-11-19 20:17:29 | D | + w: sint8 +24-11-19 20:17:29 | D | + x: None +24-11-19 20:17:29 | D | + y: None +24-11-19 20:17:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:17:29 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:17:29 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:17:29 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:17:29 | D | - range ratio = [ 1.0000] +24-11-19 20:17:29 | D | sum error = [ 2.3732] +24-11-19 20:17:29 | D | best error = [ 2.3732] +24-11-19 20:17:30 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:30 | D | sum error = [ 2.3525, 2.3463, 2.3537, 2.3895, 2.4151] +24-11-19 20:17:30 | D | best error = [ 1.9926, 1.8630, 1.7962, 1.7622, 1.7429] +24-11-19 20:17:30 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:30 | D | sum error = [ 2.4724, 2.5622, 2.6752, 2.8131, 2.9391] +24-11-19 20:17:30 | D | best error = [ 1.7316, 1.7264, 1.7238, 1.7226, 1.7221] +24-11-19 20:17:30 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:30 | D | sum error = [ 3.1117, 3.3103, 3.5158, 3.7411, 4.0345] +24-11-19 20:17:30 | D | best error = [ 1.7220, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 20:17:30 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:30 | D | sum error = [ 4.3122, 4.5980, 4.9313, 5.2790, 5.6706] +24-11-19 20:17:30 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 20:17:30 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:30 | D | sum error = [ 6.0537, 6.4775, 6.9410, 7.4386, 7.9499] +24-11-19 20:17:30 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 20:17:30 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:30 | D | sum error = [ 8.4715, 9.0514, 9.6646, 10.3105, 10.9735] +24-11-19 20:17:30 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 20:17:30 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:30 | D | sum error = [ 11.7015, 12.4487, 13.2449, 14.0825, 14.9783] +24-11-19 20:17:30 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 20:17:30 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:30 | D | sum error = [ 15.8848, 16.8645, 17.8839, 18.9871, 20.1107] +24-11-19 20:17:30 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 20:17:30 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:30 | D | sum error = [ 21.3112, 22.5701, 23.8762, 25.2664, 26.7092] +24-11-19 20:17:30 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 20:17:30 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:30 | D | sum error = [ 28.2205, 29.7941, 31.4452, 33.1861, 34.9993] +24-11-19 20:17:30 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 20:17:30 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:30 | D | sum error = [ 36.8932, 38.8573, 40.9352, 43.0928, 45.3356] +24-11-19 20:17:30 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 20:17:30 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:30 | D | sum error = [ 47.6817, 50.1137, 52.6506, 55.3003, 58.0417] +24-11-19 20:17:30 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 20:17:30 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:30 | D | sum error = [ 60.8766, 63.8599, 66.9509, 70.1726, 73.4984] +24-11-19 20:17:30 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 20:17:30 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:30 | D | sum error = [ 76.9757, 80.5550, 84.2850, 88.1191, 92.1042] +24-11-19 20:17:30 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 20:17:30 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:30 | D | sum error = [ 96.2265, 100.4864, 104.8831, 109.4210, 114.0818] +24-11-19 20:17:30 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 20:17:30 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:30 | D | sum error = [ 118.9105, 123.8594, 129.0021, 134.2469, 139.6806] +24-11-19 20:17:30 | D | best error = [ 1.7219, 1.7219, 1.7219, 1.7219, 1.7219] +24-11-19 20:17:30 | D | + error = [1.7219] +24-11-19 20:17:30 | D | - Calibrating model.layers.1.mlp.gate_proj.weight +24-11-19 20:17:30 | D | + w: sint8 +24-11-19 20:17:30 | D | + x: None +24-11-19 20:17:30 | D | + y: None +24-11-19 20:17:30 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:17:30 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:17:31 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:17:31 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:17:31 | D | - range ratio = [ 1.0000] +24-11-19 20:17:31 | D | sum error = [ 2.5169] +24-11-19 20:17:31 | D | best error = [ 2.5169] +24-11-19 20:17:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:32 | D | sum error = [ 2.5048, 2.4914, 2.5117, 2.5231, 2.5655] +24-11-19 20:17:32 | D | best error = [ 2.1196, 1.9762, 1.9102, 1.8732, 1.8518] +24-11-19 20:17:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:32 | D | sum error = [ 2.6443, 2.7296, 2.8285, 2.9738, 3.1263] +24-11-19 20:17:32 | D | best error = [ 1.8396, 1.8344, 1.8315, 1.8304, 1.8300] +24-11-19 20:17:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:32 | D | sum error = [ 3.3027, 3.5055, 3.7387, 3.9765, 4.2586] +24-11-19 20:17:32 | D | best error = [ 1.8299, 1.8299, 1.8299, 1.8299, 1.8299] +24-11-19 20:17:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:32 | D | sum error = [ 4.5569, 4.8873, 5.2473, 5.6108, 6.0022] +24-11-19 20:17:32 | D | best error = [ 1.8299, 1.8299, 1.8299, 1.8299, 1.8299] +24-11-19 20:17:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:32 | D | sum error = [ 6.4578, 6.9174, 7.3972, 7.9270, 8.4841] +24-11-19 20:17:32 | D | best error = [ 1.8299, 1.8299, 1.8299, 1.8299, 1.8299] +24-11-19 20:17:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:32 | D | sum error = [ 9.0741, 9.7169, 10.3627, 11.0833, 11.8079] +24-11-19 20:17:32 | D | best error = [ 1.8299, 1.8299, 1.8299, 1.8299, 1.8299] +24-11-19 20:17:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:32 | D | sum error = [ 12.6114, 13.4358, 14.3177, 15.2528, 16.2459] +24-11-19 20:17:32 | D | best error = [ 1.8299, 1.8299, 1.8299, 1.8299, 1.8299] +24-11-19 20:17:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:32 | D | sum error = [ 17.2972, 18.4061, 19.5802, 20.8366, 22.1446] +24-11-19 20:17:32 | D | best error = [ 1.8299, 1.8299, 1.8299, 1.8299, 1.8299] +24-11-19 20:17:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:32 | D | sum error = [ 23.5426, 25.0060, 26.5528, 28.2092, 29.9578] +24-11-19 20:17:32 | D | best error = [ 1.8299, 1.8299, 1.8299, 1.8299, 1.8299] +24-11-19 20:17:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:32 | D | sum error = [ 31.7842, 33.7507, 35.8227, 37.9780, 40.2556] +24-11-19 20:17:32 | D | best error = [ 1.8299, 1.8299, 1.8299, 1.8299, 1.8299] +24-11-19 20:17:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:32 | D | sum error = [ 42.6667, 45.1848, 47.8681, 50.7179, 53.6610] +24-11-19 20:17:32 | D | best error = [ 1.8299, 1.8299, 1.8299, 1.8299, 1.8299] +24-11-19 20:17:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:32 | D | sum error = [ 56.8360, 60.1481, 63.6162, 67.2595, 71.1743] +24-11-19 20:17:32 | D | best error = [ 1.8299, 1.8299, 1.8299, 1.8299, 1.8299] +24-11-19 20:17:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:32 | D | sum error = [ 75.2311, 79.4709, 83.9538, 88.6231, 93.5289] +24-11-19 20:17:32 | D | best error = [ 1.8299, 1.8299, 1.8299, 1.8299, 1.8299] +24-11-19 20:17:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:32 | D | sum error = [ 98.6157, 103.9878, 109.5464, 115.3579, 121.4185] +24-11-19 20:17:32 | D | best error = [ 1.8299, 1.8299, 1.8299, 1.8299, 1.8299] +24-11-19 20:17:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:32 | D | sum error = [ 127.7305, 134.2908, 141.0482, 148.0354, 155.2917] +24-11-19 20:17:32 | D | best error = [ 1.8299, 1.8299, 1.8299, 1.8299, 1.8299] +24-11-19 20:17:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:32 | D | sum error = [ 162.7667, 170.4871, 178.4397, 186.6652, 195.1785] +24-11-19 20:17:32 | D | best error = [ 1.8299, 1.8299, 1.8299, 1.8299, 1.8299] +24-11-19 20:17:32 | D | + error = [1.8299] +24-11-19 20:17:32 | D | - Calibrating model.layers.1.mlp.down_proj.weight +24-11-19 20:17:32 | D | + w: sint8 +24-11-19 20:17:32 | D | + x: None +24-11-19 20:17:32 | D | + y: None +24-11-19 20:17:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:17:32 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:17:32 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:17:32 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:17:32 | D | - range ratio = [ 1.0000] +24-11-19 20:17:32 | D | sum error = [ 35.6306] +24-11-19 20:17:32 | D | best error = [ 35.6306] +24-11-19 20:17:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:33 | D | sum error = [ 35.3514, 34.8760, 34.3974, 33.9078, 33.7581] +24-11-19 20:17:33 | D | best error = [ 24.5940, 16.9724, 12.2826, 9.6107, 8.1969] +24-11-19 20:17:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:33 | D | sum error = [ 33.7350, 32.7822, 32.4168, 32.3267, 32.1456] +24-11-19 20:17:33 | D | best error = [ 7.2380, 6.5685, 6.0764, 5.6940, 5.3929] +24-11-19 20:17:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:33 | D | sum error = [ 31.5267, 31.0977, 30.7080, 30.5470, 30.1339] +24-11-19 20:17:33 | D | best error = [ 5.1202, 4.8783, 4.6584, 4.4767, 4.3335] +24-11-19 20:17:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:33 | D | sum error = [ 29.6221, 29.4096, 29.1707, 28.7152, 28.5464] +24-11-19 20:17:33 | D | best error = [ 4.2121, 4.0874, 3.9685, 3.8803, 3.8211] +24-11-19 20:17:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:33 | D | sum error = [ 28.1520, 27.5787, 27.3709, 27.5704, 26.6904] +24-11-19 20:17:33 | D | best error = [ 3.7406, 3.6221, 3.5291, 3.4476, 3.3727] +24-11-19 20:17:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:33 | D | sum error = [ 26.3861, 26.1212, 25.5771, 25.3778, 25.8732] +24-11-19 20:17:33 | D | best error = [ 3.2817, 3.2017, 3.1330, 3.0681, 3.0018] +24-11-19 20:17:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:33 | D | sum error = [ 26.4862, 29.6367, 35.1133, 42.8637, 53.5245] +24-11-19 20:17:33 | D | best error = [ 2.9399, 2.8721, 2.7932, 2.7510, 2.7044] +24-11-19 20:17:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:33 | D | sum error = [ 67.2978, 85.3563, 107.8534, 135.9016, 169.3862] +24-11-19 20:17:33 | D | best error = [ 2.6695, 2.6209, 2.5823, 2.5399, 2.5190] +24-11-19 20:17:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:33 | D | sum error = [ 208.1708, 252.4886, 302.6174, 358.4687, 420.0567] +24-11-19 20:17:33 | D | best error = [ 2.4885, 2.4737, 2.4529, 2.4427, 2.4313] +24-11-19 20:17:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:33 | D | sum error = [ 487.0142, 559.1367, 635.7220, 716.9460, 802.3419] +24-11-19 20:17:33 | D | best error = [ 2.4268, 2.4118, 2.4058, 2.4005, 2.3975] +24-11-19 20:17:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:33 | D | sum error = [ 891.1462, 983.3994, 1078.4982, 1176.1677, 1275.9976] +24-11-19 20:17:33 | D | best error = [ 2.3942, 2.3926, 2.3896, 2.3891, 2.3887] +24-11-19 20:17:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:33 | D | sum error = [ 1377.8900, 1481.3203, 1586.1519, 1692.2353, 1799.3010] +24-11-19 20:17:33 | D | best error = [ 2.3887, 2.3881, 2.3881, 2.3878, 2.3878] +24-11-19 20:17:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:33 | D | sum error = [ 1907.1090, 2015.6971, 2124.8392, 2234.4863, 2344.6072] +24-11-19 20:17:33 | D | best error = [ 2.3878, 2.3878, 2.3878, 2.3878, 2.3878] +24-11-19 20:17:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:33 | D | sum error = [ 2455.0156, 2565.7619, 2676.8788, 2788.2341, 2899.5657] +24-11-19 20:17:33 | D | best error = [ 2.3878, 2.3878, 2.3878, 2.3878, 2.3878] +24-11-19 20:17:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:33 | D | sum error = [ 3011.1597, 3122.9117, 3234.8235, 3346.8111, 3458.9283] +24-11-19 20:17:33 | D | best error = [ 2.3878, 2.3878, 2.3878, 2.3878, 2.3878] +24-11-19 20:17:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:33 | D | sum error = [ 3571.0618, 3683.3144, 3795.6627, 3908.1024, 4020.7015] +24-11-19 20:17:33 | D | best error = [ 2.3878, 2.3878, 2.3878, 2.3878, 2.3878] +24-11-19 20:17:33 | D | + error = [2.3878] +24-11-19 20:17:33 | D | - Quantizing model.layers.1.self_attn.q_proj.weight +24-11-19 20:17:35 | D | - Quantizing model.layers.1.self_attn.k_proj.weight +24-11-19 20:17:37 | D | - Quantizing model.layers.1.self_attn.v_proj.weight +24-11-19 20:17:39 | D | - Quantizing model.layers.1.self_attn.o_proj.weight +24-11-19 20:17:40 | D | - Quantizing model.layers.1.mlp.up_proj.weight +24-11-19 20:17:41 | D | - Quantizing model.layers.1.mlp.gate_proj.weight +24-11-19 20:17:42 | D | - Quantizing model.layers.1.mlp.down_proj.weight +24-11-19 20:17:51 | D | - Quantizing layer model.layers.2 +24-11-19 20:17:51 | D | - Calibrating model.layers.2.self_attn.q_proj.weight +24-11-19 20:17:51 | D | + w: sint8 +24-11-19 20:17:51 | D | + x: None +24-11-19 20:17:51 | D | + y: None +24-11-19 20:17:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:17:51 | D | + finished parsing calibration arguments, ram usage: 14.2 +24-11-19 20:17:51 | D | + finished reseting calibrator, ram usage: 14.2 +24-11-19 20:17:52 | D | + finished calculating the original outputs, ram usage: 14.2 +24-11-19 20:17:52 | D | - range ratio = [ 1.0000] +24-11-19 20:17:52 | D | sum error = [ 1.0673] +24-11-19 20:17:52 | D | best error = [ 1.0673] +24-11-19 20:18:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:05 | D | sum error = [ 1.1353, 1.0763, 1.1033, 1.0910, 1.1689] +24-11-19 20:18:05 | D | best error = [ 1.0673, 1.0673, 1.0673, 1.0673, 1.0673] +24-11-19 20:18:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:05 | D | sum error = [ 1.2319, 1.2484, 1.3069, 1.4509, 1.5502] +24-11-19 20:18:05 | D | best error = [ 1.0673, 1.0673, 1.0673, 1.0673, 1.0673] +24-11-19 20:18:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:05 | D | sum error = [ 1.7247, 1.8334, 2.0352, 2.2710, 2.5086] +24-11-19 20:18:05 | D | best error = [ 1.0673, 1.0673, 1.0673, 1.0673, 1.0673] +24-11-19 20:18:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:05 | D | sum error = [ 2.8543, 3.0886, 3.5307, 3.9406, 4.3439] +24-11-19 20:18:05 | D | best error = [ 1.0673, 1.0673, 1.0673, 1.0673, 1.0673] +24-11-19 20:18:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:05 | D | sum error = [ 4.8293, 5.4342, 6.0189, 6.6652, 7.5526] +24-11-19 20:18:05 | D | best error = [ 1.0673, 1.0673, 1.0673, 1.0673, 1.0673] +24-11-19 20:18:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:05 | D | sum error = [ 8.4543, 9.5064, 10.5827, 11.7137, 13.1925] +24-11-19 20:18:05 | D | best error = [ 1.0673, 1.0673, 1.0673, 1.0673, 1.0673] +24-11-19 20:18:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:05 | D | sum error = [ 14.4912, 16.2274, 18.0372, 20.0797, 22.1620] +24-11-19 20:18:05 | D | best error = [ 1.0673, 1.0673, 1.0673, 1.0673, 1.0673] +24-11-19 20:18:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:05 | D | sum error = [ 24.5883, 27.0314, 29.9075, 32.8994, 36.1055] +24-11-19 20:18:05 | D | best error = [ 1.0673, 1.0673, 1.0673, 1.0673, 1.0673] +24-11-19 20:18:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:05 | D | sum error = [ 39.8102, 43.6036, 47.9113, 52.6561, 57.6307] +24-11-19 20:18:05 | D | best error = [ 1.0673, 1.0673, 1.0673, 1.0673, 1.0673] +24-11-19 20:18:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:05 | D | sum error = [ 63.1132, 69.1477, 75.7011, 82.8297, 90.3757] +24-11-19 20:18:05 | D | best error = [ 1.0673, 1.0673, 1.0673, 1.0673, 1.0673] +24-11-19 20:18:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:05 | D | sum error = [ 98.6904, 107.7944, 117.5772, 128.2065, 139.7785] +24-11-19 20:18:05 | D | best error = [ 1.0673, 1.0673, 1.0673, 1.0673, 1.0673] +24-11-19 20:18:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:05 | D | sum error = [ 152.1995, 165.5679, 179.9679, 195.6929, 212.5999] +24-11-19 20:18:05 | D | best error = [ 1.0673, 1.0673, 1.0673, 1.0673, 1.0673] +24-11-19 20:18:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:05 | D | sum error = [ 231.1417, 251.3640, 273.0783, 296.8952, 322.6008] +24-11-19 20:18:05 | D | best error = [ 1.0673, 1.0673, 1.0673, 1.0673, 1.0673] +24-11-19 20:18:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:05 | D | sum error = [ 350.5972, 380.9653, 413.7281, 448.9863, 487.3136] +24-11-19 20:18:05 | D | best error = [ 1.0673, 1.0673, 1.0673, 1.0673, 1.0673] +24-11-19 20:18:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:05 | D | sum error = [ 528.4028, 572.3422, 618.8006, 668.4648, 720.8999] +24-11-19 20:18:05 | D | best error = [ 1.0673, 1.0673, 1.0673, 1.0673, 1.0673] +24-11-19 20:18:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:05 | D | sum error = [ 775.5291, 832.6064, 891.2573, 950.8157, 1011.1741] +24-11-19 20:18:05 | D | best error = [ 1.0673, 1.0673, 1.0673, 1.0673, 1.0673] +24-11-19 20:18:05 | D | + error = [1.0673] +24-11-19 20:18:06 | D | - Calibrating model.layers.2.self_attn.k_proj.weight +24-11-19 20:18:06 | D | + w: sint8 +24-11-19 20:18:06 | D | + x: None +24-11-19 20:18:06 | D | + y: None +24-11-19 20:18:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:18:06 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:18:06 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:18:06 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:18:06 | D | - range ratio = [ 1.0000] +24-11-19 20:18:06 | D | sum error = [ 1.1855] +24-11-19 20:18:06 | D | best error = [ 1.1855] +24-11-19 20:18:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:19 | D | sum error = [ 1.1767, 1.1348, 1.2161, 1.2557, 1.3864] +24-11-19 20:18:19 | D | best error = [ 1.1767, 1.1348, 1.1348, 1.1348, 1.1348] +24-11-19 20:18:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:19 | D | sum error = [ 1.3085, 1.4609, 1.4472, 1.7248, 1.9622] +24-11-19 20:18:19 | D | best error = [ 1.1348, 1.1348, 1.1348, 1.1348, 1.1348] +24-11-19 20:18:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:19 | D | sum error = [ 2.2034, 2.1446, 2.3939, 2.8413, 3.1798] +24-11-19 20:18:19 | D | best error = [ 1.1348, 1.1348, 1.1348, 1.1348, 1.1348] +24-11-19 20:18:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:19 | D | sum error = [ 3.4530, 3.8534, 4.2536, 4.8300, 5.1267] +24-11-19 20:18:19 | D | best error = [ 1.1348, 1.1348, 1.1348, 1.1348, 1.1348] +24-11-19 20:18:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:19 | D | sum error = [ 6.1196, 6.7894, 7.5924, 8.3198, 9.0933] +24-11-19 20:18:19 | D | best error = [ 1.1348, 1.1348, 1.1348, 1.1348, 1.1348] +24-11-19 20:18:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:19 | D | sum error = [ 10.2277, 11.2408, 12.6918, 13.8654, 15.1575] +24-11-19 20:18:19 | D | best error = [ 1.1348, 1.1348, 1.1348, 1.1348, 1.1348] +24-11-19 20:18:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:19 | D | sum error = [ 16.8025, 18.3401, 20.2166, 22.1728, 24.2133] +24-11-19 20:18:19 | D | best error = [ 1.1348, 1.1348, 1.1348, 1.1348, 1.1348] +24-11-19 20:18:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:19 | D | sum error = [ 26.5478, 29.1609, 31.8028, 34.8538, 38.3569] +24-11-19 20:18:19 | D | best error = [ 1.1348, 1.1348, 1.1348, 1.1348, 1.1348] +24-11-19 20:18:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:19 | D | sum error = [ 41.8695, 45.8167, 50.0211, 54.7048, 60.0802] +24-11-19 20:18:19 | D | best error = [ 1.1348, 1.1348, 1.1348, 1.1348, 1.1348] +24-11-19 20:18:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:19 | D | sum error = [ 65.3592, 71.4646, 78.0002, 84.7548, 92.0456] +24-11-19 20:18:19 | D | best error = [ 1.1348, 1.1348, 1.1348, 1.1348, 1.1348] +24-11-19 20:18:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:19 | D | sum error = [ 99.6124, 108.8712, 118.0007, 128.6167, 139.3557] +24-11-19 20:18:19 | D | best error = [ 1.1348, 1.1348, 1.1348, 1.1348, 1.1348] +24-11-19 20:18:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:19 | D | sum error = [ 152.6812, 165.8281, 180.6518, 195.8118, 213.6462] +24-11-19 20:18:19 | D | best error = [ 1.1348, 1.1348, 1.1348, 1.1348, 1.1348] +24-11-19 20:18:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:19 | D | sum error = [ 233.1453, 253.6286, 277.0636, 301.7930, 329.8204] +24-11-19 20:18:19 | D | best error = [ 1.1348, 1.1348, 1.1348, 1.1348, 1.1348] +24-11-19 20:18:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:19 | D | sum error = [ 357.7001, 391.0271, 425.3877, 461.6708, 501.5239] +24-11-19 20:18:19 | D | best error = [ 1.1348, 1.1348, 1.1348, 1.1348, 1.1348] +24-11-19 20:18:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:19 | D | sum error = [ 544.5597, 588.9715, 636.9683, 687.6420, 740.6445] +24-11-19 20:18:19 | D | best error = [ 1.1348, 1.1348, 1.1348, 1.1348, 1.1348] +24-11-19 20:18:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:19 | D | sum error = [ 796.8714, 855.5782, 913.5257, 975.0378, 1033.5504] +24-11-19 20:18:19 | D | best error = [ 1.1348, 1.1348, 1.1348, 1.1348, 1.1348] +24-11-19 20:18:19 | D | + error = [1.1348] +24-11-19 20:18:20 | D | - Calibrating model.layers.2.self_attn.v_proj.weight +24-11-19 20:18:20 | D | + w: sint8 +24-11-19 20:18:20 | D | + x: None +24-11-19 20:18:20 | D | + y: None +24-11-19 20:18:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:20 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:18:20 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:18:20 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:18:20 | D | - range ratio = [ 1.0000] +24-11-19 20:18:20 | D | sum error = [ 2.0518] +24-11-19 20:18:20 | D | best error = [ 2.0518] +24-11-19 20:18:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:20 | D | sum error = [ 2.0427, 2.0470, 2.0601, 2.0769, 2.0982] +24-11-19 20:18:20 | D | best error = [ 1.7776, 1.6932, 1.6466, 1.6217, 1.6046] +24-11-19 20:18:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:20 | D | sum error = [ 2.1663, 2.2378, 2.3240, 2.4423, 2.5627] +24-11-19 20:18:20 | D | best error = [ 1.5973, 1.5938, 1.5924, 1.5919, 1.5918] +24-11-19 20:18:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:20 | D | sum error = [ 2.7116, 2.8707, 3.0461, 3.2625, 3.4878] +24-11-19 20:18:20 | D | best error = [ 1.5917, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:18:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:20 | D | sum error = [ 3.7456, 3.9866, 4.2997, 4.6109, 4.9222] +24-11-19 20:18:20 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:18:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:20 | D | sum error = [ 5.2914, 5.6457, 6.0481, 6.4653, 6.9387] +24-11-19 20:18:20 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:18:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:20 | D | sum error = [ 7.3983, 7.9157, 8.4590, 9.0374, 9.6408] +24-11-19 20:18:20 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:18:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:20 | D | sum error = [ 10.2681, 10.9363, 11.6455, 12.4071, 13.1855] +24-11-19 20:18:20 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:18:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:20 | D | sum error = [ 14.0041, 14.8780, 15.7849, 16.7574, 17.7786] +24-11-19 20:18:20 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:18:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:20 | D | sum error = [ 18.8373, 19.9708, 21.1399, 22.3712, 23.6713] +24-11-19 20:18:20 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:18:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:20 | D | sum error = [ 25.0139, 26.4377, 27.9180, 29.4699, 31.0838] +24-11-19 20:18:20 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:18:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:20 | D | sum error = [ 32.8064, 34.5869, 36.4449, 38.4120, 40.4424] +24-11-19 20:18:20 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:18:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:20 | D | sum error = [ 42.5647, 44.8029, 47.1064, 49.5260, 52.0411] +24-11-19 20:18:20 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:18:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:20 | D | sum error = [ 54.6611, 57.3864, 60.2241, 63.1847, 66.2503] +24-11-19 20:18:20 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:18:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:20 | D | sum error = [ 69.4449, 72.7742, 76.2060, 79.7880, 83.4854] +24-11-19 20:18:20 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:18:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:20 | D | sum error = [ 87.3101, 91.2706, 95.3590, 99.5913, 103.9505] +24-11-19 20:18:20 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:18:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:20 | D | sum error = [ 108.4417, 113.0836, 117.8529, 122.7671, 127.8258] +24-11-19 20:18:20 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:18:20 | D | + error = [1.5916] +24-11-19 20:18:20 | D | - Calibrating model.layers.2.self_attn.o_proj.weight +24-11-19 20:18:20 | D | + w: sint8 +24-11-19 20:18:20 | D | + x: None +24-11-19 20:18:20 | D | + y: None +24-11-19 20:18:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:20 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:18:21 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:18:21 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:18:21 | D | - range ratio = [ 1.0000] +24-11-19 20:18:21 | D | sum error = [ 0.2226] +24-11-19 20:18:21 | D | best error = [ 0.2226] +24-11-19 20:18:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:21 | D | sum error = [ 0.2206, 0.2208, 0.2203, 0.2221, 0.2259] +24-11-19 20:18:21 | D | best error = [ 0.2102, 0.2049, 0.2017, 0.1997, 0.1986] +24-11-19 20:18:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:21 | D | sum error = [ 0.2312, 0.2388, 0.2467, 0.2577, 0.2701] +24-11-19 20:18:21 | D | best error = [ 0.1979, 0.1975, 0.1973, 0.1972, 0.1971] +24-11-19 20:18:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:21 | D | sum error = [ 0.2839, 0.3013, 0.3196, 0.3395, 0.3620] +24-11-19 20:18:21 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:18:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:21 | D | sum error = [ 0.3866, 0.4134, 0.4422, 0.4729, 0.5061] +24-11-19 20:18:21 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:18:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:21 | D | sum error = [ 0.5425, 0.5791, 0.6201, 0.6632, 0.7087] +24-11-19 20:18:21 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:18:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:21 | D | sum error = [ 0.7567, 0.8087, 0.8633, 0.9206, 0.9824] +24-11-19 20:18:21 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:18:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:21 | D | sum error = [ 1.0466, 1.1149, 1.1867, 1.2626, 1.3431] +24-11-19 20:18:21 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:18:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:21 | D | sum error = [ 1.4282, 1.5176, 1.6116, 1.7112, 1.8166] +24-11-19 20:18:21 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:18:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:21 | D | sum error = [ 1.9274, 2.0448, 2.1674, 2.2972, 2.4334] +24-11-19 20:18:21 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:18:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:21 | D | sum error = [ 2.5770, 2.7279, 2.8876, 3.0549, 3.2308] +24-11-19 20:18:21 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:18:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:21 | D | sum error = [ 3.4160, 3.6104, 3.8151, 4.0299, 4.2552] +24-11-19 20:18:21 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:18:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:21 | D | sum error = [ 4.4919, 4.7400, 5.0000, 5.2726, 5.5579] +24-11-19 20:18:21 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:18:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:21 | D | sum error = [ 5.8571, 6.1691, 6.4962, 6.8385, 7.1953] +24-11-19 20:18:21 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:18:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:21 | D | sum error = [ 7.5684, 7.9570, 8.3625, 8.7844, 9.2236] +24-11-19 20:18:21 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:18:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:21 | D | sum error = [ 9.6804, 10.1557, 10.6490, 11.1607, 11.6915] +24-11-19 20:18:21 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:18:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:21 | D | sum error = [ 12.2412, 12.8103, 13.3982, 14.0063, 14.6335] +24-11-19 20:18:21 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:18:21 | D | + error = [0.1970] +24-11-19 20:18:21 | D | - Calibrating model.layers.2.mlp.up_proj.weight +24-11-19 20:18:21 | D | + w: sint8 +24-11-19 20:18:21 | D | + x: None +24-11-19 20:18:21 | D | + y: None +24-11-19 20:18:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:21 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:18:21 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:18:22 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:18:22 | D | - range ratio = [ 1.0000] +24-11-19 20:18:22 | D | sum error = [ 3.1968] +24-11-19 20:18:22 | D | best error = [ 3.1968] +24-11-19 20:18:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:23 | D | sum error = [ 3.1534, 3.1476, 3.1665, 3.2118, 3.2477] +24-11-19 20:18:23 | D | best error = [ 2.7836, 2.6499, 2.5825, 2.5459, 2.5266] +24-11-19 20:18:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:23 | D | sum error = [ 3.3499, 3.4576, 3.5933, 3.7503, 3.9513] +24-11-19 20:18:23 | D | best error = [ 2.5164, 2.5115, 2.5096, 2.5087, 2.5083] +24-11-19 20:18:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:23 | D | sum error = [ 4.1672, 4.4456, 4.7134, 5.0278, 5.3794] +24-11-19 20:18:23 | D | best error = [ 2.5082, 2.5082, 2.5082, 2.5082, 2.5082] +24-11-19 20:18:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:23 | D | sum error = [ 5.7417, 6.1622, 6.5840, 7.0703, 7.5750] +24-11-19 20:18:23 | D | best error = [ 2.5082, 2.5082, 2.5082, 2.5082, 2.5082] +24-11-19 20:18:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:23 | D | sum error = [ 8.1089, 8.6999, 9.3043, 9.9432, 10.6336] +24-11-19 20:18:23 | D | best error = [ 2.5082, 2.5082, 2.5082, 2.5082, 2.5082] +24-11-19 20:18:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:23 | D | sum error = [ 11.3737, 12.1380, 12.9408, 13.7995, 14.6896] +24-11-19 20:18:23 | D | best error = [ 2.5082, 2.5082, 2.5082, 2.5082, 2.5082] +24-11-19 20:18:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:23 | D | sum error = [ 15.6535, 16.6402, 17.6945, 18.8004, 19.9682] +24-11-19 20:18:23 | D | best error = [ 2.5082, 2.5082, 2.5082, 2.5082, 2.5082] +24-11-19 20:18:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:23 | D | sum error = [ 21.1921, 22.4578, 23.8178, 25.2212, 26.7063] +24-11-19 20:18:23 | D | best error = [ 2.5082, 2.5082, 2.5082, 2.5082, 2.5082] +24-11-19 20:18:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:23 | D | sum error = [ 28.2311, 29.8538, 31.5541, 33.3139, 35.1811] +24-11-19 20:18:23 | D | best error = [ 2.5082, 2.5082, 2.5082, 2.5082, 2.5082] +24-11-19 20:18:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:23 | D | sum error = [ 37.1128, 39.1325, 41.2537, 43.4531, 45.7433] +24-11-19 20:18:23 | D | best error = [ 2.5082, 2.5082, 2.5082, 2.5082, 2.5082] +24-11-19 20:18:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:23 | D | sum error = [ 48.1402, 50.6151, 53.1979, 55.8860, 58.6692] +24-11-19 20:18:23 | D | best error = [ 2.5082, 2.5082, 2.5082, 2.5082, 2.5082] +24-11-19 20:18:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:23 | D | sum error = [ 61.5595, 64.5515, 67.6624, 70.8793, 74.2016] +24-11-19 20:18:23 | D | best error = [ 2.5082, 2.5082, 2.5082, 2.5082, 2.5082] +24-11-19 20:18:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:23 | D | sum error = [ 77.6479, 81.1930, 84.8692, 88.6604, 92.5807] +24-11-19 20:18:23 | D | best error = [ 2.5082, 2.5082, 2.5082, 2.5082, 2.5082] +24-11-19 20:18:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:23 | D | sum error = [ 96.6193, 100.7903, 105.0720, 109.5037, 114.0417] +24-11-19 20:18:23 | D | best error = [ 2.5082, 2.5082, 2.5082, 2.5082, 2.5082] +24-11-19 20:18:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:23 | D | sum error = [ 118.7228, 123.5452, 128.4911, 133.5863, 138.8213] +24-11-19 20:18:23 | D | best error = [ 2.5082, 2.5082, 2.5082, 2.5082, 2.5082] +24-11-19 20:18:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:23 | D | sum error = [ 144.1897, 149.7123, 155.3758, 161.1955, 167.1646] +24-11-19 20:18:23 | D | best error = [ 2.5082, 2.5082, 2.5082, 2.5082, 2.5082] +24-11-19 20:18:23 | D | + error = [2.5082] +24-11-19 20:18:23 | D | - Calibrating model.layers.2.mlp.gate_proj.weight +24-11-19 20:18:23 | D | + w: sint8 +24-11-19 20:18:23 | D | + x: None +24-11-19 20:18:23 | D | + y: None +24-11-19 20:18:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:23 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:18:23 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:18:23 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:18:23 | D | - range ratio = [ 1.0000] +24-11-19 20:18:23 | D | sum error = [ 3.4186] +24-11-19 20:18:23 | D | best error = [ 3.4186] +24-11-19 20:18:24 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:24 | D | sum error = [ 3.3799, 3.3825, 3.3908, 3.4285, 3.4885] +24-11-19 20:18:24 | D | best error = [ 2.9814, 2.8406, 2.7685, 2.7289, 2.7085] +24-11-19 20:18:24 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:24 | D | sum error = [ 3.5885, 3.7102, 3.8656, 4.0461, 4.2537] +24-11-19 20:18:24 | D | best error = [ 2.6975, 2.6923, 2.6899, 2.6892, 2.6889] +24-11-19 20:18:24 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:24 | D | sum error = [ 4.5255, 4.7818, 5.1150, 5.4591, 5.8246] +24-11-19 20:18:24 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:18:24 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:24 | D | sum error = [ 6.2414, 6.6821, 7.1540, 7.6607, 8.2201] +24-11-19 20:18:24 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:18:24 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:24 | D | sum error = [ 8.8206, 9.4339, 10.1078, 10.8003, 11.5485] +24-11-19 20:18:24 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:18:24 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:24 | D | sum error = [ 12.3448, 13.1997, 14.0726, 15.0101, 16.0109] +24-11-19 20:18:24 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:18:24 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:24 | D | sum error = [ 17.0549, 18.1555, 19.3208, 20.5680, 21.8576] +24-11-19 20:18:24 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:18:24 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:24 | D | sum error = [ 23.2260, 24.6839, 26.2142, 27.7872, 29.4698] +24-11-19 20:18:24 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:18:24 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:24 | D | sum error = [ 31.2355, 33.0859, 35.0169, 37.0536, 39.2041] +24-11-19 20:18:24 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:18:24 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:24 | D | sum error = [ 41.4297, 43.7790, 46.2290, 48.7986, 51.4890] +24-11-19 20:18:24 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:18:24 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:24 | D | sum error = [ 54.3018, 57.2512, 60.3222, 63.5163, 66.8767] +24-11-19 20:18:24 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:18:24 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:24 | D | sum error = [ 70.3456, 73.9639, 77.7371, 81.6774, 85.7601] +24-11-19 20:18:24 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:18:24 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:24 | D | sum error = [ 90.0122, 94.4263, 99.0174, 103.7747, 108.7124] +24-11-19 20:18:24 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:18:24 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:24 | D | sum error = [ 113.8400, 119.1550, 124.6343, 130.3324, 136.1978] +24-11-19 20:18:24 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:18:24 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:24 | D | sum error = [ 142.2847, 148.5751, 155.0699, 161.7797, 168.7000] +24-11-19 20:18:24 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:18:24 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:24 | D | sum error = [ 175.8384, 183.1922, 190.7575, 198.5540, 206.5657] +24-11-19 20:18:24 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:18:24 | D | + error = [2.6889] +24-11-19 20:18:24 | D | - Calibrating model.layers.2.mlp.down_proj.weight +24-11-19 20:18:24 | D | + w: sint8 +24-11-19 20:18:24 | D | + x: None +24-11-19 20:18:24 | D | + y: None +24-11-19 20:18:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:24 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:18:24 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:18:24 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:18:24 | D | - range ratio = [ 1.0000] +24-11-19 20:18:24 | D | sum error = [ 0.3957] +24-11-19 20:18:24 | D | best error = [ 0.3957] +24-11-19 20:18:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:25 | D | sum error = [ 0.3912, 0.3878, 0.3859, 0.3855, 0.3843] +24-11-19 20:18:25 | D | best error = [ 0.3663, 0.3535, 0.3464, 0.3413, 0.3375] +24-11-19 20:18:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:25 | D | sum error = [ 0.3880, 0.3912, 0.3959, 0.4065, 0.4171] +24-11-19 20:18:25 | D | best error = [ 0.3345, 0.3323, 0.3308, 0.3297, 0.3291] +24-11-19 20:18:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:25 | D | sum error = [ 0.4312, 0.4470, 0.4664, 0.4876, 0.5117] +24-11-19 20:18:25 | D | best error = [ 0.3285, 0.3282, 0.3280, 0.3279, 0.3278] +24-11-19 20:18:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:25 | D | sum error = [ 0.5384, 0.5696, 0.6036, 0.6399, 0.6820] +24-11-19 20:18:25 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 20:18:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:25 | D | sum error = [ 0.7260, 0.7756, 0.8306, 0.8901, 0.9548] +24-11-19 20:18:25 | D | best error = [ 0.3277, 0.3276, 0.3276, 0.3276, 0.3276] +24-11-19 20:18:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:25 | D | sum error = [ 1.0240, 1.0991, 1.1798, 1.2661, 1.3588] +24-11-19 20:18:25 | D | best error = [ 0.3276, 0.3276, 0.3276, 0.3276, 0.3276] +24-11-19 20:18:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:25 | D | sum error = [ 1.4588, 1.5642, 1.6773, 1.7983, 1.9266] +24-11-19 20:18:25 | D | best error = [ 0.3276, 0.3276, 0.3276, 0.3276, 0.3276] +24-11-19 20:18:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:25 | D | sum error = [ 2.0640, 2.2097, 2.3643, 2.5274, 2.6998] +24-11-19 20:18:25 | D | best error = [ 0.3276, 0.3276, 0.3276, 0.3276, 0.3276] +24-11-19 20:18:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:25 | D | sum error = [ 2.8832, 3.0772, 3.2831, 3.4996, 3.7282] +24-11-19 20:18:25 | D | best error = [ 0.3276, 0.3276, 0.3276, 0.3276, 0.3276] +24-11-19 20:18:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:25 | D | sum error = [ 3.9701, 4.2243, 4.4910, 4.7717, 5.0656] +24-11-19 20:18:25 | D | best error = [ 0.3276, 0.3276, 0.3276, 0.3276, 0.3276] +24-11-19 20:18:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:25 | D | sum error = [ 5.3739, 5.6977, 6.0372, 6.3943, 6.7680] +24-11-19 20:18:25 | D | best error = [ 0.3276, 0.3276, 0.3276, 0.3276, 0.3276] +24-11-19 20:18:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:25 | D | sum error = [ 7.1597, 7.5693, 7.9973, 8.4449, 8.9125] +24-11-19 20:18:25 | D | best error = [ 0.3276, 0.3276, 0.3276, 0.3276, 0.3276] +24-11-19 20:18:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:25 | D | sum error = [ 9.4003, 9.9087, 10.4389, 10.9913, 11.5664] +24-11-19 20:18:25 | D | best error = [ 0.3276, 0.3276, 0.3276, 0.3276, 0.3276] +24-11-19 20:18:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:25 | D | sum error = [ 12.1643, 12.7853, 13.4305, 14.1015, 14.7943] +24-11-19 20:18:25 | D | best error = [ 0.3276, 0.3276, 0.3276, 0.3276, 0.3276] +24-11-19 20:18:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:25 | D | sum error = [ 15.5139, 16.2594, 17.0311, 17.8294, 18.6552] +24-11-19 20:18:25 | D | best error = [ 0.3276, 0.3276, 0.3276, 0.3276, 0.3276] +24-11-19 20:18:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:25 | D | sum error = [ 19.5090, 20.3903, 21.3011, 22.2407, 23.2097] +24-11-19 20:18:25 | D | best error = [ 0.3276, 0.3276, 0.3276, 0.3276, 0.3276] +24-11-19 20:18:25 | D | + error = [0.3276] +24-11-19 20:18:25 | D | - Quantizing model.layers.2.self_attn.q_proj.weight +24-11-19 20:18:28 | D | - Quantizing model.layers.2.self_attn.k_proj.weight +24-11-19 20:18:29 | D | - Quantizing model.layers.2.self_attn.v_proj.weight +24-11-19 20:18:31 | D | - Quantizing model.layers.2.self_attn.o_proj.weight +24-11-19 20:18:32 | D | - Quantizing model.layers.2.mlp.up_proj.weight +24-11-19 20:18:33 | D | - Quantizing model.layers.2.mlp.gate_proj.weight +24-11-19 20:18:34 | D | - Quantizing model.layers.2.mlp.down_proj.weight +24-11-19 20:18:43 | D | - Quantizing layer model.layers.3 +24-11-19 20:18:43 | D | - Calibrating model.layers.3.self_attn.q_proj.weight +24-11-19 20:18:43 | D | + w: sint8 +24-11-19 20:18:43 | D | + x: None +24-11-19 20:18:43 | D | + y: None +24-11-19 20:18:43 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:18:43 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:18:43 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:18:44 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:18:44 | D | - range ratio = [ 1.0000] +24-11-19 20:18:44 | D | sum error = [ 2.0254] +24-11-19 20:18:44 | D | best error = [ 2.0254] +24-11-19 20:18:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:57 | D | sum error = [ 2.1131, 2.0697, 2.0795, 2.1018, 2.0961] +24-11-19 20:18:57 | D | best error = [ 2.0254, 2.0254, 2.0254, 2.0254, 2.0254] +24-11-19 20:18:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:57 | D | sum error = [ 2.1083, 2.2874, 2.3412, 2.4198, 2.6902] +24-11-19 20:18:57 | D | best error = [ 2.0254, 2.0254, 2.0254, 2.0254, 2.0254] +24-11-19 20:18:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:57 | D | sum error = [ 2.7516, 3.0533, 3.2599, 3.7012, 4.0204] +24-11-19 20:18:57 | D | best error = [ 2.0254, 2.0254, 2.0254, 2.0254, 2.0254] +24-11-19 20:18:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:57 | D | sum error = [ 4.4787, 4.6467, 5.2093, 5.8121, 6.1728] +24-11-19 20:18:57 | D | best error = [ 2.0254, 2.0254, 2.0254, 2.0254, 2.0254] +24-11-19 20:18:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:57 | D | sum error = [ 6.8919, 7.6036, 8.3776, 9.2249, 10.2233] +24-11-19 20:18:57 | D | best error = [ 2.0254, 2.0254, 2.0254, 2.0254, 2.0254] +24-11-19 20:18:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:57 | D | sum error = [ 11.1532, 12.4652, 13.8587, 15.3801, 16.9824] +24-11-19 20:18:57 | D | best error = [ 2.0254, 2.0254, 2.0254, 2.0254, 2.0254] +24-11-19 20:18:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:57 | D | sum error = [ 18.7310, 20.7678, 23.1005, 25.1744, 28.0231] +24-11-19 20:18:57 | D | best error = [ 2.0254, 2.0254, 2.0254, 2.0254, 2.0254] +24-11-19 20:18:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:57 | D | sum error = [ 30.9890, 33.9070, 37.2581, 41.1174, 45.1000] +24-11-19 20:18:57 | D | best error = [ 2.0254, 2.0254, 2.0254, 2.0254, 2.0254] +24-11-19 20:18:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:57 | D | sum error = [ 49.5678, 54.3326, 59.5173, 65.1342, 71.3038] +24-11-19 20:18:57 | D | best error = [ 2.0254, 2.0254, 2.0254, 2.0254, 2.0254] +24-11-19 20:18:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:57 | D | sum error = [ 78.1261, 85.3249, 93.0216, 101.5983, 111.2957] +24-11-19 20:18:57 | D | best error = [ 2.0254, 2.0254, 2.0254, 2.0254, 2.0254] +24-11-19 20:18:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:57 | D | sum error = [ 121.5267, 132.7201, 144.7875, 157.9867, 172.2348] +24-11-19 20:18:57 | D | best error = [ 2.0254, 2.0254, 2.0254, 2.0254, 2.0254] +24-11-19 20:18:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:57 | D | sum error = [ 187.7192, 204.7131, 222.3167, 241.9706, 262.9369] +24-11-19 20:18:57 | D | best error = [ 2.0254, 2.0254, 2.0254, 2.0254, 2.0254] +24-11-19 20:18:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:57 | D | sum error = [ 285.2998, 310.2952, 336.7539, 365.9240, 396.9891] +24-11-19 20:18:57 | D | best error = [ 2.0254, 2.0254, 2.0254, 2.0254, 2.0254] +24-11-19 20:18:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:57 | D | sum error = [ 431.0675, 467.6825, 507.3318, 550.0118, 596.2827] +24-11-19 20:18:57 | D | best error = [ 2.0254, 2.0254, 2.0254, 2.0254, 2.0254] +24-11-19 20:18:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:57 | D | sum error = [ 645.4646, 697.8588, 753.3184, 812.2425, 874.1649] +24-11-19 20:18:57 | D | best error = [ 2.0254, 2.0254, 2.0254, 2.0254, 2.0254] +24-11-19 20:18:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:57 | D | sum error = [ 939.2466, 1007.2662, 1077.6467, 1150.2598, 1223.5462] +24-11-19 20:18:57 | D | best error = [ 2.0254, 2.0254, 2.0254, 2.0254, 2.0254] +24-11-19 20:18:57 | D | + error = [2.0254] +24-11-19 20:18:57 | D | - Calibrating model.layers.3.self_attn.k_proj.weight +24-11-19 20:18:57 | D | + w: sint8 +24-11-19 20:18:57 | D | + x: None +24-11-19 20:18:57 | D | + y: None +24-11-19 20:18:57 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:18:57 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:18:57 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:18:58 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:18:58 | D | - range ratio = [ 1.0000] +24-11-19 20:18:58 | D | sum error = [ 2.3739] +24-11-19 20:18:58 | D | best error = [ 2.3739] +24-11-19 20:19:11 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:11 | D | sum error = [ 2.2972, 2.2521, 2.7491, 2.4216, 2.3906] +24-11-19 20:19:11 | D | best error = [ 2.2972, 2.2521, 2.2521, 2.2521, 2.2521] +24-11-19 20:19:11 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:11 | D | sum error = [ 2.5159, 2.4523, 2.8606, 3.2101, 3.3240] +24-11-19 20:19:11 | D | best error = [ 2.2521, 2.2521, 2.2521, 2.2521, 2.2521] +24-11-19 20:19:11 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:11 | D | sum error = [ 3.6322, 3.7729, 4.4059, 4.7863, 5.2025] +24-11-19 20:19:11 | D | best error = [ 2.2521, 2.2521, 2.2521, 2.2521, 2.2521] +24-11-19 20:19:11 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:11 | D | sum error = [ 6.2979, 6.4918, 7.0510, 7.6397, 8.5663] +24-11-19 20:19:11 | D | best error = [ 2.2521, 2.2521, 2.2521, 2.2521, 2.2521] +24-11-19 20:19:11 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:11 | D | sum error = [ 9.0246, 10.1555, 11.4659, 12.4554, 13.2354] +24-11-19 20:19:11 | D | best error = [ 2.2521, 2.2521, 2.2521, 2.2521, 2.2521] +24-11-19 20:19:11 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:11 | D | sum error = [ 14.4398, 16.0807, 17.8134, 18.7832, 20.7944] +24-11-19 20:19:11 | D | best error = [ 2.2521, 2.2521, 2.2521, 2.2521, 2.2521] +24-11-19 20:19:11 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:11 | D | sum error = [ 22.7475, 24.4851, 27.0414, 28.9417, 31.7670] +24-11-19 20:19:11 | D | best error = [ 2.2521, 2.2521, 2.2521, 2.2521, 2.2521] +24-11-19 20:19:11 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:11 | D | sum error = [ 34.3517, 37.4578, 40.5531, 43.6979, 47.0978] +24-11-19 20:19:11 | D | best error = [ 2.2521, 2.2521, 2.2521, 2.2521, 2.2521] +24-11-19 20:19:11 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:11 | D | sum error = [ 50.9942, 55.4769, 60.2801, 65.4856, 70.9003] +24-11-19 20:19:11 | D | best error = [ 2.2521, 2.2521, 2.2521, 2.2521, 2.2521] +24-11-19 20:19:11 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:11 | D | sum error = [ 77.0680, 83.8314, 91.1825, 98.8621, 107.5225] +24-11-19 20:19:11 | D | best error = [ 2.2521, 2.2521, 2.2521, 2.2521, 2.2521] +24-11-19 20:19:11 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:11 | D | sum error = [ 116.9075, 127.2248, 138.6016, 149.9234, 163.1764] +24-11-19 20:19:11 | D | best error = [ 2.2521, 2.2521, 2.2521, 2.2521, 2.2521] +24-11-19 20:19:11 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:11 | D | sum error = [ 177.1806, 192.7779, 209.2009, 227.6882, 247.7513] +24-11-19 20:19:11 | D | best error = [ 2.2521, 2.2521, 2.2521, 2.2521, 2.2521] +24-11-19 20:19:11 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:11 | D | sum error = [ 269.3024, 292.7161, 318.1666, 346.0807, 376.3248] +24-11-19 20:19:11 | D | best error = [ 2.2521, 2.2521, 2.2521, 2.2521, 2.2521] +24-11-19 20:19:11 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:11 | D | sum error = [ 408.1435, 443.1601, 481.2012, 521.6748, 567.4067] +24-11-19 20:19:11 | D | best error = [ 2.2521, 2.2521, 2.2521, 2.2521, 2.2521] +24-11-19 20:19:11 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:11 | D | sum error = [ 615.1240, 666.4130, 721.7167, 780.8098, 841.6423] +24-11-19 20:19:11 | D | best error = [ 2.2521, 2.2521, 2.2521, 2.2521, 2.2521] +24-11-19 20:19:11 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:11 | D | sum error = [ 909.3740, 977.3959, 1047.6934, 1120.5283, 1195.1438] +24-11-19 20:19:11 | D | best error = [ 2.2521, 2.2521, 2.2521, 2.2521, 2.2521] +24-11-19 20:19:11 | D | + error = [2.2521] +24-11-19 20:19:11 | D | - Calibrating model.layers.3.self_attn.v_proj.weight +24-11-19 20:19:11 | D | + w: sint8 +24-11-19 20:19:11 | D | + x: None +24-11-19 20:19:11 | D | + y: None +24-11-19 20:19:11 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:11 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:19:11 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:19:11 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:19:11 | D | - range ratio = [ 1.0000] +24-11-19 20:19:11 | D | sum error = [ 3.1708] +24-11-19 20:19:11 | D | best error = [ 3.1708] +24-11-19 20:19:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:12 | D | sum error = [ 3.1660, 3.1279, 3.1503, 3.1894, 3.2412] +24-11-19 20:19:12 | D | best error = [ 2.8480, 2.7361, 2.6847, 2.6567, 2.6407] +24-11-19 20:19:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:12 | D | sum error = [ 3.3541, 3.4515, 3.5665, 3.7337, 3.9332] +24-11-19 20:19:12 | D | best error = [ 2.6333, 2.6300, 2.6282, 2.6280, 2.6279] +24-11-19 20:19:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:12 | D | sum error = [ 4.1650, 4.4319, 4.7029, 5.0031, 5.3491] +24-11-19 20:19:12 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:19:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:12 | D | sum error = [ 5.7113, 6.1289, 6.5649, 7.0458, 7.5580] +24-11-19 20:19:12 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:19:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:12 | D | sum error = [ 8.0962, 8.6721, 9.2964, 9.9548, 10.6287] +24-11-19 20:19:12 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:19:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:12 | D | sum error = [ 11.3692, 12.1551, 12.9587, 13.8473, 14.7824] +24-11-19 20:19:12 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:19:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:12 | D | sum error = [ 15.7430, 16.7828, 17.8506, 19.0111, 20.1980] +24-11-19 20:19:12 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:19:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:12 | D | sum error = [ 21.4801, 22.8115, 24.1978, 25.6872, 27.2160] +24-11-19 20:19:12 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:19:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:12 | D | sum error = [ 28.8699, 30.5676, 32.3739, 34.2507, 36.2386] +24-11-19 20:19:12 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:19:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:12 | D | sum error = [ 38.2760, 40.4485, 42.6884, 45.0550, 47.5271] +24-11-19 20:19:12 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:19:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:12 | D | sum error = [ 50.0835, 52.7734, 55.5664, 58.4941, 61.5510] +24-11-19 20:19:12 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:19:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:12 | D | sum error = [ 64.7368, 68.0534, 71.5217, 75.1339, 78.8849] +24-11-19 20:19:12 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:19:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:12 | D | sum error = [ 82.7934, 86.8491, 91.0601, 95.4310, 99.9574] +24-11-19 20:19:12 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:19:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:12 | D | sum error = [ 104.6322, 109.4796, 114.5203, 119.7342, 125.1313] +24-11-19 20:19:12 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:19:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:12 | D | sum error = [ 130.7125, 136.4782, 142.4455, 148.6017, 154.9427] +24-11-19 20:19:12 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:19:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:12 | D | sum error = [ 161.4929, 168.2353, 175.1856, 182.3415, 189.7058] +24-11-19 20:19:12 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:19:12 | D | + error = [2.6278] +24-11-19 20:19:12 | D | - Calibrating model.layers.3.self_attn.o_proj.weight +24-11-19 20:19:12 | D | + w: sint8 +24-11-19 20:19:12 | D | + x: None +24-11-19 20:19:12 | D | + y: None +24-11-19 20:19:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:12 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:19:12 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:19:12 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:19:12 | D | - range ratio = [ 1.0000] +24-11-19 20:19:12 | D | sum error = [ 0.2488] +24-11-19 20:19:12 | D | best error = [ 0.2488] +24-11-19 20:19:13 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:13 | D | sum error = [ 0.2463, 0.2457, 0.2471, 0.2487, 0.2532] +24-11-19 20:19:13 | D | best error = [ 0.2354, 0.2293, 0.2260, 0.2240, 0.2227] +24-11-19 20:19:13 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:13 | D | sum error = [ 0.2589, 0.2666, 0.2762, 0.2870, 0.3018] +24-11-19 20:19:13 | D | best error = [ 0.2220, 0.2215, 0.2213, 0.2211, 0.2209] +24-11-19 20:19:13 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:13 | D | sum error = [ 0.3182, 0.3358, 0.3565, 0.3798, 0.4041] +24-11-19 20:19:13 | D | best error = [ 0.2209, 0.2208, 0.2207, 0.2207, 0.2207] +24-11-19 20:19:13 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:13 | D | sum error = [ 0.4315, 0.4608, 0.4929, 0.5266, 0.5639] +24-11-19 20:19:13 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:19:13 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:13 | D | sum error = [ 0.6029, 0.6450, 0.6890, 0.7372, 0.7881] +24-11-19 20:19:13 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:19:13 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:13 | D | sum error = [ 0.8411, 0.8981, 0.9579, 1.0218, 1.0890] +24-11-19 20:19:13 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:19:13 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:13 | D | sum error = [ 1.1608, 1.2361, 1.3163, 1.3999, 1.4900] +24-11-19 20:19:13 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:19:13 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:13 | D | sum error = [ 1.5826, 1.6829, 1.7868, 1.8980, 2.0141] +24-11-19 20:19:13 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:19:13 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:13 | D | sum error = [ 2.1379, 2.2672, 2.4041, 2.5480, 2.7003] +24-11-19 20:19:13 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:19:13 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:13 | D | sum error = [ 2.8612, 3.0294, 3.2077, 3.3946, 3.5916] +24-11-19 20:19:13 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:19:13 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:13 | D | sum error = [ 3.7987, 4.0170, 4.2461, 4.4868, 4.7403] +24-11-19 20:19:13 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:19:13 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:13 | D | sum error = [ 5.0062, 5.2860, 5.5789, 5.8869, 6.2101] +24-11-19 20:19:13 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:19:13 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:13 | D | sum error = [ 6.5488, 6.9039, 7.2755, 7.6645, 8.0720] +24-11-19 20:19:13 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:19:13 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:13 | D | sum error = [ 8.4983, 8.9435, 9.4091, 9.8944, 10.4022] +24-11-19 20:19:13 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:19:13 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:13 | D | sum error = [ 10.9308, 11.4814, 12.0554, 12.6526, 13.2730] +24-11-19 20:19:13 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:19:13 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:13 | D | sum error = [ 13.9168, 14.5852, 15.2774, 15.9951, 16.7371] +24-11-19 20:19:13 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:19:13 | D | + error = [0.2207] +24-11-19 20:19:13 | D | - Calibrating model.layers.3.mlp.up_proj.weight +24-11-19 20:19:13 | D | + w: sint8 +24-11-19 20:19:13 | D | + x: None +24-11-19 20:19:13 | D | + y: None +24-11-19 20:19:13 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:13 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:19:13 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:19:13 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:19:13 | D | - range ratio = [ 1.0000] +24-11-19 20:19:13 | D | sum error = [ 4.0371] +24-11-19 20:19:13 | D | best error = [ 4.0371] +24-11-19 20:19:14 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:14 | D | sum error = [ 3.9997, 3.9892, 4.0200, 4.0566, 4.1420] +24-11-19 20:19:14 | D | best error = [ 3.5555, 3.3916, 3.3174, 3.2756, 3.2531] +24-11-19 20:19:14 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:14 | D | sum error = [ 4.2349, 4.3860, 4.5690, 4.8016, 5.0211] +24-11-19 20:19:14 | D | best error = [ 3.2408, 3.2357, 3.2340, 3.2333, 3.2330] +24-11-19 20:19:14 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:14 | D | sum error = [ 5.3260, 5.6452, 6.0030, 6.4385, 6.8619] +24-11-19 20:19:14 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:19:14 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:14 | D | sum error = [ 7.3533, 7.8700, 8.4188, 9.0238, 9.6619] +24-11-19 20:19:14 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:19:14 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:14 | D | sum error = [ 10.3400, 11.0782, 11.8346, 12.6676, 13.5209] +24-11-19 20:19:14 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:19:14 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:14 | D | sum error = [ 14.4555, 15.4174, 16.4416, 17.5211, 18.6668] +24-11-19 20:19:14 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:19:14 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:14 | D | sum error = [ 19.8549, 21.1252, 22.4491, 23.8496, 25.3319] +24-11-19 20:19:14 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:19:14 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:14 | D | sum error = [ 26.8638, 28.4741, 30.1804, 31.9590, 33.8148] +24-11-19 20:19:14 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:19:14 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:14 | D | sum error = [ 35.7733, 37.8168, 39.9382, 42.1775, 44.4936] +24-11-19 20:19:14 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:19:14 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:14 | D | sum error = [ 46.9167, 49.4363, 52.0727, 54.7799, 57.6263] +24-11-19 20:19:14 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:19:14 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:14 | D | sum error = [ 60.5799, 63.6717, 66.8608, 70.1697, 73.5975] +24-11-19 20:19:14 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:19:14 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:14 | D | sum error = [ 77.1625, 80.8419, 84.6600, 88.6179, 92.6902] +24-11-19 20:19:14 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:19:14 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:14 | D | sum error = [ 96.9011, 101.2546, 105.7463, 110.3734, 115.1356] +24-11-19 20:19:14 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:19:14 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:14 | D | sum error = [ 120.0346, 125.0638, 130.2714, 135.6186, 141.1124] +24-11-19 20:19:14 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:19:14 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:14 | D | sum error = [ 146.7445, 152.5286, 158.4696, 164.5607, 170.8089] +24-11-19 20:19:14 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:19:14 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:14 | D | sum error = [ 177.2118, 183.7808, 190.5085, 197.4106, 204.4943] +24-11-19 20:19:14 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:19:14 | D | + error = [3.2330] +24-11-19 20:19:14 | D | - Calibrating model.layers.3.mlp.gate_proj.weight +24-11-19 20:19:14 | D | + w: sint8 +24-11-19 20:19:14 | D | + x: None +24-11-19 20:19:14 | D | + y: None +24-11-19 20:19:14 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:14 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:19:14 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:19:15 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:19:15 | D | - range ratio = [ 1.0000] +24-11-19 20:19:15 | D | sum error = [ 4.3527] +24-11-19 20:19:15 | D | best error = [ 4.3527] +24-11-19 20:19:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:15 | D | sum error = [ 4.3123, 4.3102, 4.3310, 4.3906, 4.4581] +24-11-19 20:19:15 | D | best error = [ 3.8365, 3.6602, 3.5782, 3.5332, 3.5095] +24-11-19 20:19:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:15 | D | sum error = [ 4.5715, 4.7274, 4.8955, 5.1578, 5.4426] +24-11-19 20:19:15 | D | best error = [ 3.4969, 3.4921, 3.4897, 3.4891, 3.4889] +24-11-19 20:19:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:15 | D | sum error = [ 5.7225, 6.0865, 6.4692, 6.8952, 7.3639] +24-11-19 20:19:15 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:19:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:15 | D | sum error = [ 7.8899, 8.4683, 9.0682, 9.7275, 10.4371] +24-11-19 20:19:15 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:19:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:15 | D | sum error = [ 11.1615, 11.9548, 12.7853, 13.7114, 14.6361] +24-11-19 20:19:15 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:19:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:15 | D | sum error = [ 15.6398, 16.7246, 17.8434, 19.0212, 20.2680] +24-11-19 20:19:15 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:19:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:15 | D | sum error = [ 21.5938, 22.9822, 24.4545, 26.0113, 27.6266] +24-11-19 20:19:15 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:19:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:15 | D | sum error = [ 29.3296, 31.1148, 33.0044, 34.9827, 37.0531] +24-11-19 20:19:15 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:19:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:15 | D | sum error = [ 39.2309, 41.4905, 43.8938, 46.3924, 49.0047] +24-11-19 20:19:15 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:19:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:15 | D | sum error = [ 51.7467, 54.6222, 57.6330, 60.7767, 64.0715] +24-11-19 20:19:15 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:19:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:15 | D | sum error = [ 67.4904, 71.0611, 74.7900, 78.6755, 82.7287] +24-11-19 20:19:15 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:19:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:15 | D | sum error = [ 86.9356, 91.3119, 95.8783, 100.6377, 105.5661] +24-11-19 20:19:15 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:19:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:15 | D | sum error = [ 110.7030, 116.0264, 121.5380, 127.2429, 133.1717] +24-11-19 20:19:15 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:19:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:15 | D | sum error = [ 139.2822, 145.5719, 152.1077, 158.8488, 165.8226] +24-11-19 20:19:15 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:19:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:15 | D | sum error = [ 173.0257, 180.4740, 188.1774, 196.1149, 204.2961] +24-11-19 20:19:15 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:19:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:15 | D | sum error = [ 212.7345, 221.4098, 230.3381, 239.5218, 248.9607] +24-11-19 20:19:15 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:19:15 | D | + error = [3.4889] +24-11-19 20:19:16 | D | - Calibrating model.layers.3.mlp.down_proj.weight +24-11-19 20:19:16 | D | + w: sint8 +24-11-19 20:19:16 | D | + x: None +24-11-19 20:19:16 | D | + y: None +24-11-19 20:19:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:16 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:19:16 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:19:16 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:19:16 | D | - range ratio = [ 1.0000] +24-11-19 20:19:16 | D | sum error = [ 0.4792] +24-11-19 20:19:16 | D | best error = [ 0.4792] +24-11-19 20:19:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:17 | D | sum error = [ 0.4748, 0.4717, 0.4686, 0.4680, 0.4671] +24-11-19 20:19:17 | D | best error = [ 0.4655, 0.4580, 0.4525, 0.4486, 0.4455] +24-11-19 20:19:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:17 | D | sum error = [ 0.4693, 0.4722, 0.4786, 0.4866, 0.4974] +24-11-19 20:19:17 | D | best error = [ 0.4431, 0.4413, 0.4400, 0.4392, 0.4387] +24-11-19 20:19:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:17 | D | sum error = [ 0.5096, 0.5257, 0.5444, 0.5669, 0.5928] +24-11-19 20:19:17 | D | best error = [ 0.4384, 0.4382, 0.4380, 0.4379, 0.4379] +24-11-19 20:19:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:17 | D | sum error = [ 0.6226, 0.6562, 0.6938, 0.7356, 0.7812] +24-11-19 20:19:17 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:19:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:17 | D | sum error = [ 0.8316, 0.8871, 0.9463, 1.0106, 1.0807] +24-11-19 20:19:17 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:19:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:17 | D | sum error = [ 1.1559, 1.2362, 1.3219, 1.4152, 1.5138] +24-11-19 20:19:17 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:19:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:17 | D | sum error = [ 1.6189, 1.7316, 1.8506, 1.9775, 2.1127] +24-11-19 20:19:17 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:19:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:17 | D | sum error = [ 2.2569, 2.4094, 2.5727, 2.7429, 2.9251] +24-11-19 20:19:17 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:19:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:17 | D | sum error = [ 3.1173, 3.3218, 3.5368, 3.7653, 4.0059] +24-11-19 20:19:17 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:19:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:17 | D | sum error = [ 4.2604, 4.5292, 4.8116, 5.1099, 5.4236] +24-11-19 20:19:17 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:19:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:17 | D | sum error = [ 5.7538, 6.1018, 6.4668, 6.8511, 7.2545] +24-11-19 20:19:17 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:19:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:17 | D | sum error = [ 7.6787, 8.1232, 8.5895, 9.0783, 9.5908] +24-11-19 20:19:17 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:19:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:17 | D | sum error = [ 10.1269, 10.6882, 11.2750, 11.8883, 12.5281] +24-11-19 20:19:17 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:19:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:17 | D | sum error = [ 13.1962, 13.8926, 14.6192, 15.3771, 16.1629] +24-11-19 20:19:17 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:19:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:17 | D | sum error = [ 16.9823, 17.8339, 18.7187, 19.6376, 20.5904] +24-11-19 20:19:17 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:19:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:17 | D | sum error = [ 21.5777, 22.6009, 23.6592, 24.7541, 25.8860] +24-11-19 20:19:17 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:19:17 | D | + error = [0.4379] +24-11-19 20:19:17 | D | - Quantizing model.layers.3.self_attn.q_proj.weight +24-11-19 20:19:19 | D | - Quantizing model.layers.3.self_attn.k_proj.weight +24-11-19 20:19:20 | D | - Quantizing model.layers.3.self_attn.v_proj.weight +24-11-19 20:19:23 | D | - Quantizing model.layers.3.self_attn.o_proj.weight +24-11-19 20:19:24 | D | - Quantizing model.layers.3.mlp.up_proj.weight +24-11-19 20:19:26 | D | - Quantizing model.layers.3.mlp.gate_proj.weight +24-11-19 20:19:27 | D | - Quantizing model.layers.3.mlp.down_proj.weight +24-11-19 20:19:36 | D | - Quantizing layer model.layers.4 +24-11-19 20:19:36 | D | - Calibrating model.layers.4.self_attn.q_proj.weight +24-11-19 20:19:36 | D | + w: sint8 +24-11-19 20:19:36 | D | + x: None +24-11-19 20:19:36 | D | + y: None +24-11-19 20:19:36 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:19:36 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:19:36 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:19:36 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:19:36 | D | - range ratio = [ 1.0000] +24-11-19 20:19:36 | D | sum error = [ 2.5247] +24-11-19 20:19:36 | D | best error = [ 2.5247] +24-11-19 20:19:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:50 | D | sum error = [ 2.5184, 2.5249, 2.4766, 2.5854, 2.6417] +24-11-19 20:19:50 | D | best error = [ 2.5184, 2.5184, 2.4766, 2.4766, 2.4766] +24-11-19 20:19:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:50 | D | sum error = [ 2.9371, 2.9482, 3.1208, 3.5527, 3.7221] +24-11-19 20:19:50 | D | best error = [ 2.4766, 2.4766, 2.4766, 2.4766, 2.4766] +24-11-19 20:19:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:50 | D | sum error = [ 3.8455, 4.5845, 5.0968, 5.6695, 6.3108] +24-11-19 20:19:50 | D | best error = [ 2.4766, 2.4766, 2.4766, 2.4766, 2.4766] +24-11-19 20:19:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:50 | D | sum error = [ 6.9436, 7.8530, 9.1054, 10.0266, 11.2103] +24-11-19 20:19:50 | D | best error = [ 2.4766, 2.4766, 2.4766, 2.4766, 2.4766] +24-11-19 20:19:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:50 | D | sum error = [ 12.5870, 13.6408, 15.1236, 16.7311, 18.5888] +24-11-19 20:19:50 | D | best error = [ 2.4766, 2.4766, 2.4766, 2.4766, 2.4766] +24-11-19 20:19:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:50 | D | sum error = [ 20.5177, 22.3319, 24.9099, 27.0311, 29.5927] +24-11-19 20:19:50 | D | best error = [ 2.4766, 2.4766, 2.4766, 2.4766, 2.4766] +24-11-19 20:19:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:50 | D | sum error = [ 32.2490, 35.2235, 38.4408, 42.3111, 45.9394] +24-11-19 20:19:50 | D | best error = [ 2.4766, 2.4766, 2.4766, 2.4766, 2.4766] +24-11-19 20:19:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:50 | D | sum error = [ 50.2420, 54.6593, 59.6742, 64.9945, 70.7622] +24-11-19 20:19:50 | D | best error = [ 2.4766, 2.4766, 2.4766, 2.4766, 2.4766] +24-11-19 20:19:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:50 | D | sum error = [ 77.1915, 83.9838, 90.9447, 98.4544, 106.7959] +24-11-19 20:19:50 | D | best error = [ 2.4766, 2.4766, 2.4766, 2.4766, 2.4766] +24-11-19 20:19:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:50 | D | sum error = [ 115.9605, 125.3818, 135.8128, 146.8937, 158.6650] +24-11-19 20:19:50 | D | best error = [ 2.4766, 2.4766, 2.4766, 2.4766, 2.4766] +24-11-19 20:19:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:50 | D | sum error = [ 171.8030, 185.1266, 200.2975, 216.3181, 233.3753] +24-11-19 20:19:50 | D | best error = [ 2.4766, 2.4766, 2.4766, 2.4766, 2.4766] +24-11-19 20:19:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:50 | D | sum error = [ 251.4556, 271.1886, 292.0636, 314.2947, 338.3539] +24-11-19 20:19:50 | D | best error = [ 2.4766, 2.4766, 2.4766, 2.4766, 2.4766] +24-11-19 20:19:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:50 | D | sum error = [ 363.9390, 391.2440, 420.7002, 452.0270, 485.2819] +24-11-19 20:19:50 | D | best error = [ 2.4766, 2.4766, 2.4766, 2.4766, 2.4766] +24-11-19 20:19:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:50 | D | sum error = [ 521.4010, 558.8608, 598.9566, 641.7646, 685.6772] +24-11-19 20:19:50 | D | best error = [ 2.4766, 2.4766, 2.4766, 2.4766, 2.4766] +24-11-19 20:19:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:50 | D | sum error = [ 732.1613, 780.1152, 830.4462, 882.7225, 937.2286] +24-11-19 20:19:50 | D | best error = [ 2.4766, 2.4766, 2.4766, 2.4766, 2.4766] +24-11-19 20:19:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:50 | D | sum error = [ 993.1157, 1050.4863, 1109.0518, 1169.1005, 1228.8982] +24-11-19 20:19:50 | D | best error = [ 2.4766, 2.4766, 2.4766, 2.4766, 2.4766] +24-11-19 20:19:50 | D | + error = [2.4766] +24-11-19 20:19:50 | D | - Calibrating model.layers.4.self_attn.k_proj.weight +24-11-19 20:19:50 | D | + w: sint8 +24-11-19 20:19:50 | D | + x: None +24-11-19 20:19:50 | D | + y: None +24-11-19 20:19:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:19:50 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:19:50 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:19:50 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:19:51 | D | - range ratio = [ 1.0000] +24-11-19 20:19:51 | D | sum error = [ 3.0503] +24-11-19 20:19:51 | D | best error = [ 3.0503] +24-11-19 20:20:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:04 | D | sum error = [ 2.7791, 2.9963, 2.9223, 2.7766, 2.8928] +24-11-19 20:20:04 | D | best error = [ 2.7791, 2.7791, 2.7791, 2.7766, 2.7766] +24-11-19 20:20:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:04 | D | sum error = [ 3.0614, 3.0733, 3.1210, 3.4602, 3.5889] +24-11-19 20:20:04 | D | best error = [ 2.7766, 2.7766, 2.7766, 2.7766, 2.7766] +24-11-19 20:20:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:04 | D | sum error = [ 3.6246, 4.0154, 4.3453, 4.4509, 5.2787] +24-11-19 20:20:04 | D | best error = [ 2.7766, 2.7766, 2.7766, 2.7766, 2.7766] +24-11-19 20:20:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:04 | D | sum error = [ 5.6471, 6.0255, 6.7055, 7.1457, 7.9674] +24-11-19 20:20:04 | D | best error = [ 2.7766, 2.7766, 2.7766, 2.7766, 2.7766] +24-11-19 20:20:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:04 | D | sum error = [ 8.7469, 9.3801, 10.4706, 11.3951, 12.3554] +24-11-19 20:20:04 | D | best error = [ 2.7766, 2.7766, 2.7766, 2.7766, 2.7766] +24-11-19 20:20:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:04 | D | sum error = [ 13.7447, 15.1471, 16.2785, 17.9404, 19.7293] +24-11-19 20:20:04 | D | best error = [ 2.7766, 2.7766, 2.7766, 2.7766, 2.7766] +24-11-19 20:20:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:04 | D | sum error = [ 21.4820, 22.9527, 25.2356, 27.8844, 29.7894] +24-11-19 20:20:04 | D | best error = [ 2.7766, 2.7766, 2.7766, 2.7766, 2.7766] +24-11-19 20:20:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:04 | D | sum error = [ 32.9226, 35.3741, 39.0889, 42.4729, 46.3019] +24-11-19 20:20:04 | D | best error = [ 2.7766, 2.7766, 2.7766, 2.7766, 2.7766] +24-11-19 20:20:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:04 | D | sum error = [ 50.1896, 54.2998, 59.4116, 64.8284, 70.9538] +24-11-19 20:20:04 | D | best error = [ 2.7766, 2.7766, 2.7766, 2.7766, 2.7766] +24-11-19 20:20:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:04 | D | sum error = [ 77.7062, 84.5500, 92.2623, 100.6216, 109.7526] +24-11-19 20:20:04 | D | best error = [ 2.7766, 2.7766, 2.7766, 2.7766, 2.7766] +24-11-19 20:20:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:04 | D | sum error = [ 118.7058, 129.5428, 140.4998, 152.4594, 165.4284] +24-11-19 20:20:04 | D | best error = [ 2.7766, 2.7766, 2.7766, 2.7766, 2.7766] +24-11-19 20:20:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:04 | D | sum error = [ 179.4801, 194.6179, 211.0948, 229.0593, 248.0708] +24-11-19 20:20:04 | D | best error = [ 2.7766, 2.7766, 2.7766, 2.7766, 2.7766] +24-11-19 20:20:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:04 | D | sum error = [ 268.2665, 290.8763, 315.4449, 341.8090, 369.2777] +24-11-19 20:20:04 | D | best error = [ 2.7766, 2.7766, 2.7766, 2.7766, 2.7766] +24-11-19 20:20:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:04 | D | sum error = [ 400.8203, 433.9046, 468.5247, 506.5521, 547.2281] +24-11-19 20:20:04 | D | best error = [ 2.7766, 2.7766, 2.7766, 2.7766, 2.7766] +24-11-19 20:20:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:04 | D | sum error = [ 588.4223, 635.1992, 684.4930, 735.0236, 789.0369] +24-11-19 20:20:04 | D | best error = [ 2.7766, 2.7766, 2.7766, 2.7766, 2.7766] +24-11-19 20:20:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:04 | D | sum error = [ 846.3769, 908.0861, 969.2253, 1034.1865, 1101.1800] +24-11-19 20:20:04 | D | best error = [ 2.7766, 2.7766, 2.7766, 2.7766, 2.7766] +24-11-19 20:20:04 | D | + error = [2.7766] +24-11-19 20:20:04 | D | - Calibrating model.layers.4.self_attn.v_proj.weight +24-11-19 20:20:04 | D | + w: sint8 +24-11-19 20:20:04 | D | + x: None +24-11-19 20:20:04 | D | + y: None +24-11-19 20:20:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:04 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:04 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:04 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:04 | D | - range ratio = [ 1.0000] +24-11-19 20:20:04 | D | sum error = [ 3.0385] +24-11-19 20:20:04 | D | best error = [ 3.0385] +24-11-19 20:20:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:04 | D | sum error = [ 3.0270, 3.0166, 3.0418, 3.0729, 3.1221] +24-11-19 20:20:04 | D | best error = [ 2.7710, 2.6786, 2.6301, 2.6048, 2.5904] +24-11-19 20:20:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:04 | D | sum error = [ 3.2046, 3.3073, 3.4543, 3.6164, 3.8044] +24-11-19 20:20:04 | D | best error = [ 2.5838, 2.5814, 2.5807, 2.5805, 2.5804] +24-11-19 20:20:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:04 | D | sum error = [ 4.0294, 4.2749, 4.5391, 4.8610, 5.2120] +24-11-19 20:20:04 | D | best error = [ 2.5804, 2.5804, 2.5804, 2.5804, 2.5804] +24-11-19 20:20:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:04 | D | sum error = [ 5.5779, 5.9705, 6.4029, 6.8547, 7.3643] +24-11-19 20:20:04 | D | best error = [ 2.5804, 2.5804, 2.5804, 2.5804, 2.5804] +24-11-19 20:20:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:04 | D | sum error = [ 7.8793, 8.4510, 9.0501, 9.6932, 10.3518] +24-11-19 20:20:04 | D | best error = [ 2.5804, 2.5804, 2.5804, 2.5804, 2.5804] +24-11-19 20:20:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:04 | D | sum error = [ 11.0568, 11.8163, 12.5975, 13.4365, 14.3397] +24-11-19 20:20:04 | D | best error = [ 2.5804, 2.5804, 2.5804, 2.5804, 2.5804] +24-11-19 20:20:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:04 | D | sum error = [ 15.2622, 16.2622, 17.2999, 18.4259, 19.5772] +24-11-19 20:20:04 | D | best error = [ 2.5804, 2.5804, 2.5804, 2.5804, 2.5804] +24-11-19 20:20:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:04 | D | sum error = [ 20.8036, 22.1006, 23.4455, 24.8737, 26.3452] +24-11-19 20:20:04 | D | best error = [ 2.5804, 2.5804, 2.5804, 2.5804, 2.5804] +24-11-19 20:20:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:04 | D | sum error = [ 27.9080, 29.5530, 31.2715, 33.0920, 34.9921] +24-11-19 20:20:04 | D | best error = [ 2.5804, 2.5804, 2.5804, 2.5804, 2.5804] +24-11-19 20:20:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:04 | D | sum error = [ 36.9779, 39.0679, 41.2552, 43.5382, 45.9260] +24-11-19 20:20:04 | D | best error = [ 2.5804, 2.5804, 2.5804, 2.5804, 2.5804] +24-11-19 20:20:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:04 | D | sum error = [ 48.4317, 51.0498, 53.7858, 56.6463, 59.6300] +24-11-19 20:20:04 | D | best error = [ 2.5804, 2.5804, 2.5804, 2.5804, 2.5804] +24-11-19 20:20:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:04 | D | sum error = [ 62.7416, 66.0028, 69.3893, 72.9162, 76.5767] +24-11-19 20:20:04 | D | best error = [ 2.5804, 2.5804, 2.5804, 2.5804, 2.5804] +24-11-19 20:20:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:04 | D | sum error = [ 80.3940, 84.3582, 88.4771, 92.7512, 97.1874] +24-11-19 20:20:04 | D | best error = [ 2.5804, 2.5804, 2.5804, 2.5804, 2.5804] +24-11-19 20:20:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:04 | D | sum error = [ 101.7909, 106.5683, 111.5172, 116.6480, 121.9538] +24-11-19 20:20:04 | D | best error = [ 2.5804, 2.5804, 2.5804, 2.5804, 2.5804] +24-11-19 20:20:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:04 | D | sum error = [ 127.4493, 133.1296, 139.0129, 145.0855, 151.3518] +24-11-19 20:20:04 | D | best error = [ 2.5804, 2.5804, 2.5804, 2.5804, 2.5804] +24-11-19 20:20:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:04 | D | sum error = [ 157.8168, 164.4661, 171.3261, 178.3840, 185.6456] +24-11-19 20:20:04 | D | best error = [ 2.5804, 2.5804, 2.5804, 2.5804, 2.5804] +24-11-19 20:20:04 | D | + error = [2.5804] +24-11-19 20:20:04 | D | - Calibrating model.layers.4.self_attn.o_proj.weight +24-11-19 20:20:04 | D | + w: sint8 +24-11-19 20:20:04 | D | + x: None +24-11-19 20:20:04 | D | + y: None +24-11-19 20:20:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:04 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:05 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:05 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:05 | D | - range ratio = [ 1.0000] +24-11-19 20:20:05 | D | sum error = [ 0.3585] +24-11-19 20:20:05 | D | best error = [ 0.3585] +24-11-19 20:20:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:05 | D | sum error = [ 0.3563, 0.3550, 0.3550, 0.3582, 0.3637] +24-11-19 20:20:05 | D | best error = [ 0.3406, 0.3319, 0.3269, 0.3237, 0.3218] +24-11-19 20:20:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:05 | D | sum error = [ 0.3715, 0.3826, 0.3958, 0.4125, 0.4323] +24-11-19 20:20:05 | D | best error = [ 0.3205, 0.3198, 0.3193, 0.3189, 0.3187] +24-11-19 20:20:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:05 | D | sum error = [ 0.4551, 0.4804, 0.5101, 0.5424, 0.5793] +24-11-19 20:20:05 | D | best error = [ 0.3186, 0.3185, 0.3184, 0.3184, 0.3184] +24-11-19 20:20:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:05 | D | sum error = [ 0.6168, 0.6603, 0.7054, 0.7551, 0.8084] +24-11-19 20:20:05 | D | best error = [ 0.3184, 0.3184, 0.3184, 0.3183, 0.3183] +24-11-19 20:20:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:05 | D | sum error = [ 0.8653, 0.9271, 0.9911, 1.0615, 1.1343] +24-11-19 20:20:05 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 20:20:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:05 | D | sum error = [ 1.2127, 1.2961, 1.3831, 1.4776, 1.5763] +24-11-19 20:20:05 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 20:20:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:05 | D | sum error = [ 1.6822, 1.7936, 1.9113, 2.0366, 2.1675] +24-11-19 20:20:05 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 20:20:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:05 | D | sum error = [ 2.3080, 2.4553, 2.6101, 2.7735, 2.9472] +24-11-19 20:20:05 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 20:20:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:05 | D | sum error = [ 3.1292, 3.3211, 3.5231, 3.7359, 3.9615] +24-11-19 20:20:05 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 20:20:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:05 | D | sum error = [ 4.1980, 4.4471, 4.7102, 4.9856, 5.2767] +24-11-19 20:20:05 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 20:20:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:05 | D | sum error = [ 5.5809, 5.9014, 6.2392, 6.5924, 6.9641] +24-11-19 20:20:05 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 20:20:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:05 | D | sum error = [ 7.3531, 7.7604, 8.1870, 8.6341, 9.1011] +24-11-19 20:20:05 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 20:20:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:05 | D | sum error = [ 9.5910, 10.1026, 10.6375, 11.1959, 11.7794] +24-11-19 20:20:05 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 20:20:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:05 | D | sum error = [ 12.3875, 13.0225, 13.6835, 14.3716, 15.0875] +24-11-19 20:20:05 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 20:20:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:05 | D | sum error = [ 15.8315, 16.6031, 17.4031, 18.2329, 19.0926] +24-11-19 20:20:05 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 20:20:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:05 | D | sum error = [ 19.9823, 20.9030, 21.8547, 22.8379, 23.8531] +24-11-19 20:20:05 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 20:20:05 | D | + error = [0.3183] +24-11-19 20:20:05 | D | - Calibrating model.layers.4.mlp.up_proj.weight +24-11-19 20:20:05 | D | + w: sint8 +24-11-19 20:20:05 | D | + x: None +24-11-19 20:20:05 | D | + y: None +24-11-19 20:20:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:05 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:05 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:06 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:06 | D | - range ratio = [ 1.0000] +24-11-19 20:20:06 | D | sum error = [ 4.3384] +24-11-19 20:20:06 | D | best error = [ 4.3384] +24-11-19 20:20:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:07 | D | sum error = [ 4.3001, 4.2761, 4.3106, 4.3731, 4.4276] +24-11-19 20:20:07 | D | best error = [ 3.8852, 3.7307, 3.6574, 3.6173, 3.5953] +24-11-19 20:20:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:07 | D | sum error = [ 4.5705, 4.7019, 4.8951, 5.1225, 5.4098] +24-11-19 20:20:07 | D | best error = [ 3.5857, 3.5817, 3.5800, 3.5794, 3.5792] +24-11-19 20:20:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:07 | D | sum error = [ 5.7091, 6.0500, 6.4233, 6.8668, 7.3466] +24-11-19 20:20:07 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:07 | D | sum error = [ 7.8606, 8.4177, 9.0018, 9.6471, 10.3321] +24-11-19 20:20:07 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:07 | D | sum error = [ 11.0813, 11.8573, 12.6783, 13.5416, 14.4909] +24-11-19 20:20:07 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:07 | D | sum error = [ 15.4648, 16.5246, 17.6270, 18.7982, 20.0248] +24-11-19 20:20:07 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:07 | D | sum error = [ 21.3293, 22.6964, 24.1358, 25.6622, 27.2493] +24-11-19 20:20:07 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:07 | D | sum error = [ 28.9358, 30.7033, 32.5699, 34.5203, 36.5490] +24-11-19 20:20:07 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:07 | D | sum error = [ 38.7021, 40.9372, 43.2843, 45.7430, 48.3015] +24-11-19 20:20:07 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:07 | D | sum error = [ 50.9633, 53.7593, 56.6605, 59.6958, 62.8778] +24-11-19 20:20:07 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:07 | D | sum error = [ 66.1851, 69.6179, 73.2069, 76.9275, 80.7890] +24-11-19 20:20:07 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:07 | D | sum error = [ 84.8013, 88.9536, 93.2565, 97.7343, 102.3539] +24-11-19 20:20:07 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:07 | D | sum error = [ 107.1415, 112.0950, 117.2191, 122.5138, 127.9860] +24-11-19 20:20:07 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:07 | D | sum error = [ 133.6377, 139.4816, 145.5195, 151.7352, 158.1538] +24-11-19 20:20:07 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:07 | D | sum error = [ 164.7761, 171.5916, 178.6155, 185.8411, 193.2765] +24-11-19 20:20:07 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:07 | D | sum error = [ 200.9259, 208.7863, 216.8722, 225.1825, 233.7195] +24-11-19 20:20:07 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:07 | D | + error = [3.5792] +24-11-19 20:20:07 | D | - Calibrating model.layers.4.mlp.gate_proj.weight +24-11-19 20:20:07 | D | + w: sint8 +24-11-19 20:20:07 | D | + x: None +24-11-19 20:20:07 | D | + y: None +24-11-19 20:20:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:07 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:07 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:07 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:07 | D | - range ratio = [ 1.0000] +24-11-19 20:20:07 | D | sum error = [ 4.7995] +24-11-19 20:20:07 | D | best error = [ 4.7995] +24-11-19 20:20:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:08 | D | sum error = [ 4.7717, 4.7539, 4.7674, 4.8343, 4.9221] +24-11-19 20:20:08 | D | best error = [ 4.2991, 4.1341, 4.0496, 4.0079, 3.9854] +24-11-19 20:20:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:08 | D | sum error = [ 5.0564, 5.2183, 5.4482, 5.6940, 6.0147] +24-11-19 20:20:08 | D | best error = [ 3.9734, 3.9683, 3.9665, 3.9660, 3.9658] +24-11-19 20:20:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:08 | D | sum error = [ 6.3445, 6.7276, 7.1694, 7.6448, 8.1802] +24-11-19 20:20:08 | D | best error = [ 3.9658, 3.9658, 3.9658, 3.9658, 3.9658] +24-11-19 20:20:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:08 | D | sum error = [ 8.7679, 9.3778, 10.0538, 10.7920, 11.5455] +24-11-19 20:20:08 | D | best error = [ 3.9658, 3.9658, 3.9658, 3.9658, 3.9658] +24-11-19 20:20:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:08 | D | sum error = [ 12.4017, 13.2770, 14.2056, 15.2078, 16.2784] +24-11-19 20:20:08 | D | best error = [ 3.9658, 3.9658, 3.9658, 3.9658, 3.9658] +24-11-19 20:20:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:08 | D | sum error = [ 17.3864, 18.5976, 19.8611, 21.1874, 22.6158] +24-11-19 20:20:08 | D | best error = [ 3.9658, 3.9658, 3.9658, 3.9658, 3.9658] +24-11-19 20:20:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:08 | D | sum error = [ 24.1066, 25.6882, 27.3473, 29.1062, 30.9624] +24-11-19 20:20:08 | D | best error = [ 3.9658, 3.9658, 3.9658, 3.9658, 3.9658] +24-11-19 20:20:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:08 | D | sum error = [ 32.9197, 34.9646, 37.1619, 39.4359, 41.8596] +24-11-19 20:20:08 | D | best error = [ 3.9658, 3.9658, 3.9658, 3.9658, 3.9658] +24-11-19 20:20:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:08 | D | sum error = [ 44.3981, 47.0780, 49.8887, 52.8188, 55.9238] +24-11-19 20:20:08 | D | best error = [ 3.9658, 3.9658, 3.9658, 3.9658, 3.9658] +24-11-19 20:20:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:08 | D | sum error = [ 59.1759, 62.5968, 66.1862, 69.9435, 73.8992] +24-11-19 20:20:08 | D | best error = [ 3.9658, 3.9658, 3.9658, 3.9658, 3.9658] +24-11-19 20:20:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:08 | D | sum error = [ 78.0219, 82.3717, 86.9186, 91.6903, 96.6692] +24-11-19 20:20:08 | D | best error = [ 3.9658, 3.9658, 3.9658, 3.9658, 3.9658] +24-11-19 20:20:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:08 | D | sum error = [ 101.8735, 107.3321, 113.0443, 118.9924, 125.1950] +24-11-19 20:20:08 | D | best error = [ 3.9658, 3.9658, 3.9658, 3.9658, 3.9658] +24-11-19 20:20:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:08 | D | sum error = [ 131.6474, 138.4162, 145.4539, 152.7812, 160.4142] +24-11-19 20:20:08 | D | best error = [ 3.9658, 3.9658, 3.9658, 3.9658, 3.9658] +24-11-19 20:20:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:08 | D | sum error = [ 168.3767, 176.6381, 185.2426, 194.1606, 203.4252] +24-11-19 20:20:08 | D | best error = [ 3.9658, 3.9658, 3.9658, 3.9658, 3.9658] +24-11-19 20:20:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:08 | D | sum error = [ 213.0498, 223.0288, 233.3551, 244.0287, 255.0500] +24-11-19 20:20:08 | D | best error = [ 3.9658, 3.9658, 3.9658, 3.9658, 3.9658] +24-11-19 20:20:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:08 | D | sum error = [ 266.4278, 278.1801, 290.2875, 302.7755, 315.6260] +24-11-19 20:20:08 | D | best error = [ 3.9658, 3.9658, 3.9658, 3.9658, 3.9658] +24-11-19 20:20:08 | D | + error = [3.9658] +24-11-19 20:20:08 | D | - Calibrating model.layers.4.mlp.down_proj.weight +24-11-19 20:20:08 | D | + w: sint8 +24-11-19 20:20:08 | D | + x: None +24-11-19 20:20:08 | D | + y: None +24-11-19 20:20:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:08 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:08 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:08 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:08 | D | - range ratio = [ 1.0000] +24-11-19 20:20:08 | D | sum error = [ 0.7611] +24-11-19 20:20:08 | D | best error = [ 0.7611] +24-11-19 20:20:09 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:09 | D | sum error = [ 0.7554, 0.7529, 0.7528, 0.7559, 0.7587] +24-11-19 20:20:09 | D | best error = [ 0.6896, 0.6605, 0.6452, 0.6345, 0.6267] +24-11-19 20:20:09 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:09 | D | sum error = [ 0.7759, 0.7886, 0.8137, 0.8392, 0.8715] +24-11-19 20:20:09 | D | best error = [ 0.6213, 0.6177, 0.6149, 0.6128, 0.6112] +24-11-19 20:20:09 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:09 | D | sum error = [ 0.9092, 0.9504, 0.9980, 1.0510, 1.1083] +24-11-19 20:20:09 | D | best error = [ 0.6102, 0.6096, 0.6093, 0.6090, 0.6089] +24-11-19 20:20:09 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:09 | D | sum error = [ 1.1738, 1.2475, 1.3172, 1.3990, 1.4895] +24-11-19 20:20:09 | D | best error = [ 0.6088, 0.6087, 0.6087, 0.6087, 0.6087] +24-11-19 20:20:09 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:09 | D | sum error = [ 1.5875, 1.6908, 1.8037, 1.9220, 2.0559] +24-11-19 20:20:09 | D | best error = [ 0.6086, 0.6086, 0.6086, 0.6086, 0.6086] +24-11-19 20:20:09 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:09 | D | sum error = [ 2.1920, 2.3428, 2.5003, 2.6669, 2.8412] +24-11-19 20:20:09 | D | best error = [ 0.6086, 0.6086, 0.6086, 0.6086, 0.6086] +24-11-19 20:20:09 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:09 | D | sum error = [ 3.0299, 3.2308, 3.4409, 3.6655, 3.9078] +24-11-19 20:20:09 | D | best error = [ 0.6086, 0.6086, 0.6086, 0.6086, 0.6086] +24-11-19 20:20:09 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:09 | D | sum error = [ 4.1624, 4.4298, 4.7138, 5.0107, 5.3308] +24-11-19 20:20:09 | D | best error = [ 0.6086, 0.6086, 0.6086, 0.6086, 0.6086] +24-11-19 20:20:09 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:09 | D | sum error = [ 5.6654, 6.0202, 6.3920, 6.7865, 7.2007] +24-11-19 20:20:09 | D | best error = [ 0.6086, 0.6086, 0.6086, 0.6086, 0.6086] +24-11-19 20:20:09 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:09 | D | sum error = [ 7.6466, 8.1083, 8.5964, 9.1107, 9.6514] +24-11-19 20:20:09 | D | best error = [ 0.6086, 0.6086, 0.6086, 0.6086, 0.6086] +24-11-19 20:20:09 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:09 | D | sum error = [ 10.2230, 10.8211, 11.4492, 12.1152, 12.8119] +24-11-19 20:20:09 | D | best error = [ 0.6086, 0.6086, 0.6086, 0.6086, 0.6086] +24-11-19 20:20:09 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:09 | D | sum error = [ 13.5442, 14.3146, 15.1210, 15.9647, 16.8544] +24-11-19 20:20:09 | D | best error = [ 0.6086, 0.6086, 0.6086, 0.6086, 0.6086] +24-11-19 20:20:09 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:09 | D | sum error = [ 17.7857, 18.7610, 19.7845, 20.8579, 21.9836] +24-11-19 20:20:09 | D | best error = [ 0.6086, 0.6086, 0.6086, 0.6086, 0.6086] +24-11-19 20:20:09 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:09 | D | sum error = [ 23.1594, 24.3874, 25.6718, 27.0126, 28.4027] +24-11-19 20:20:09 | D | best error = [ 0.6086, 0.6086, 0.6086, 0.6086, 0.6086] +24-11-19 20:20:09 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:09 | D | sum error = [ 29.8521, 31.3579, 32.9246, 34.5540, 36.2424] +24-11-19 20:20:09 | D | best error = [ 0.6086, 0.6086, 0.6086, 0.6086, 0.6086] +24-11-19 20:20:09 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:09 | D | sum error = [ 37.9928, 39.8062, 41.6847, 43.6294, 45.6400] +24-11-19 20:20:09 | D | best error = [ 0.6086, 0.6086, 0.6086, 0.6086, 0.6086] +24-11-19 20:20:09 | D | + error = [0.6086] +24-11-19 20:20:09 | D | - Quantizing model.layers.4.self_attn.q_proj.weight +24-11-19 20:20:11 | D | - Quantizing model.layers.4.self_attn.k_proj.weight +24-11-19 20:20:15 | D | - Quantizing model.layers.4.self_attn.v_proj.weight +24-11-19 20:20:17 | D | - Quantizing model.layers.4.self_attn.o_proj.weight +24-11-19 20:20:18 | D | - Quantizing model.layers.4.mlp.up_proj.weight +24-11-19 20:20:19 | D | - Quantizing model.layers.4.mlp.gate_proj.weight +24-11-19 20:20:20 | D | - Quantizing model.layers.4.mlp.down_proj.weight +24-11-19 20:20:29 | D | - Quantizing layer model.layers.5 +24-11-19 20:20:29 | D | - Calibrating model.layers.5.self_attn.q_proj.weight +24-11-19 20:20:29 | D | + w: sint8 +24-11-19 20:20:29 | D | + x: None +24-11-19 20:20:29 | D | + y: None +24-11-19 20:20:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:20:29 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:20:29 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:20:29 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:20:29 | D | - range ratio = [ 1.0000] +24-11-19 20:20:29 | D | sum error = [ 3.0166] +24-11-19 20:20:29 | D | best error = [ 3.0166] +24-11-19 20:20:43 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:43 | D | sum error = [ 2.9558, 2.8606, 2.8831, 3.0156, 2.9607] +24-11-19 20:20:43 | D | best error = [ 2.9558, 2.8606, 2.8606, 2.8606, 2.8606] +24-11-19 20:20:43 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:43 | D | sum error = [ 3.2075, 3.2500, 3.5742, 3.6068, 4.0038] +24-11-19 20:20:43 | D | best error = [ 2.8606, 2.8606, 2.8606, 2.8606, 2.8606] +24-11-19 20:20:43 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:43 | D | sum error = [ 4.2409, 4.5607, 4.9738, 5.4197, 5.8956] +24-11-19 20:20:43 | D | best error = [ 2.8606, 2.8606, 2.8606, 2.8606, 2.8606] +24-11-19 20:20:43 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:43 | D | sum error = [ 6.6337, 7.2708, 7.7457, 8.5520, 9.5658] +24-11-19 20:20:43 | D | best error = [ 2.8606, 2.8606, 2.8606, 2.8606, 2.8606] +24-11-19 20:20:43 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:43 | D | sum error = [ 10.4632, 11.4819, 12.6107, 14.0143, 14.9358] +24-11-19 20:20:43 | D | best error = [ 2.8606, 2.8606, 2.8606, 2.8606, 2.8606] +24-11-19 20:20:43 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:43 | D | sum error = [ 16.8876, 18.1799, 19.5157, 21.5412, 23.3254] +24-11-19 20:20:43 | D | best error = [ 2.8606, 2.8606, 2.8606, 2.8606, 2.8606] +24-11-19 20:20:43 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:43 | D | sum error = [ 25.6668, 27.8404, 30.3380, 33.0592, 36.0526] +24-11-19 20:20:43 | D | best error = [ 2.8606, 2.8606, 2.8606, 2.8606, 2.8606] +24-11-19 20:20:43 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:43 | D | sum error = [ 39.1662, 42.5419, 46.2258, 50.2084, 54.5972] +24-11-19 20:20:43 | D | best error = [ 2.8606, 2.8606, 2.8606, 2.8606, 2.8606] +24-11-19 20:20:43 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:43 | D | sum error = [ 59.1501, 64.2692, 69.6905, 75.7872, 81.9915] +24-11-19 20:20:43 | D | best error = [ 2.8606, 2.8606, 2.8606, 2.8606, 2.8606] +24-11-19 20:20:43 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:43 | D | sum error = [ 88.6637, 96.2943, 104.2060, 112.9431, 121.9794] +24-11-19 20:20:43 | D | best error = [ 2.8606, 2.8606, 2.8606, 2.8606, 2.8606] +24-11-19 20:20:43 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:43 | D | sum error = [ 132.1040, 142.9220, 154.4925, 167.1736, 180.7117] +24-11-19 20:20:43 | D | best error = [ 2.8606, 2.8606, 2.8606, 2.8606, 2.8606] +24-11-19 20:20:43 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:43 | D | sum error = [ 195.4135, 211.4208, 228.6974, 247.1684, 266.8784] +24-11-19 20:20:43 | D | best error = [ 2.8606, 2.8606, 2.8606, 2.8606, 2.8606] +24-11-19 20:20:43 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:43 | D | sum error = [ 288.2111, 310.6416, 335.2058, 361.5833, 389.9647] +24-11-19 20:20:43 | D | best error = [ 2.8606, 2.8606, 2.8606, 2.8606, 2.8606] +24-11-19 20:20:43 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:43 | D | sum error = [ 420.3674, 453.4694, 488.8323, 526.8522, 568.0261] +24-11-19 20:20:43 | D | best error = [ 2.8606, 2.8606, 2.8606, 2.8606, 2.8606] +24-11-19 20:20:43 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:43 | D | sum error = [ 611.9773, 659.4720, 710.1690, 764.6778, 822.5735] +24-11-19 20:20:43 | D | best error = [ 2.8606, 2.8606, 2.8606, 2.8606, 2.8606] +24-11-19 20:20:43 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:43 | D | sum error = [ 884.0967, 948.9332, 1017.1064, 1087.9102, 1161.2239] +24-11-19 20:20:43 | D | best error = [ 2.8606, 2.8606, 2.8606, 2.8606, 2.8606] +24-11-19 20:20:43 | D | + error = [2.8606] +24-11-19 20:20:43 | D | - Calibrating model.layers.5.self_attn.k_proj.weight +24-11-19 20:20:43 | D | + w: sint8 +24-11-19 20:20:43 | D | + x: None +24-11-19 20:20:43 | D | + y: None +24-11-19 20:20:43 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:20:43 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:43 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:44 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:44 | D | - range ratio = [ 1.0000] +24-11-19 20:20:44 | D | sum error = [ 3.1893] +24-11-19 20:20:44 | D | best error = [ 3.1893] +24-11-19 20:20:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:57 | D | sum error = [ 3.3275, 3.1359, 3.2791, 3.2286, 3.1367] +24-11-19 20:20:57 | D | best error = [ 3.1893, 3.1359, 3.1359, 3.1359, 3.1359] +24-11-19 20:20:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:57 | D | sum error = [ 3.3955, 3.4049, 3.7422, 3.8109, 4.1276] +24-11-19 20:20:57 | D | best error = [ 3.1359, 3.1359, 3.1359, 3.1359, 3.1359] +24-11-19 20:20:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:57 | D | sum error = [ 4.2441, 4.8247, 4.8604, 5.5444, 5.8059] +24-11-19 20:20:57 | D | best error = [ 3.1359, 3.1359, 3.1359, 3.1359, 3.1359] +24-11-19 20:20:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:57 | D | sum error = [ 6.4348, 6.7693, 7.5365, 7.9010, 8.7055] +24-11-19 20:20:57 | D | best error = [ 3.1359, 3.1359, 3.1359, 3.1359, 3.1359] +24-11-19 20:20:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:57 | D | sum error = [ 9.4353, 10.1695, 11.2904, 12.2300, 13.3809] +24-11-19 20:20:57 | D | best error = [ 3.1359, 3.1359, 3.1359, 3.1359, 3.1359] +24-11-19 20:20:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:57 | D | sum error = [ 14.2188, 15.3685, 16.8640, 18.6592, 20.0526] +24-11-19 20:20:57 | D | best error = [ 3.1359, 3.1359, 3.1359, 3.1359, 3.1359] +24-11-19 20:20:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:57 | D | sum error = [ 21.6827, 23.5946, 25.6795, 28.1914, 30.5789] +24-11-19 20:20:57 | D | best error = [ 3.1359, 3.1359, 3.1359, 3.1359, 3.1359] +24-11-19 20:20:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:57 | D | sum error = [ 33.5187, 36.5728, 40.0266, 43.5933, 47.5905] +24-11-19 20:20:57 | D | best error = [ 3.1359, 3.1359, 3.1359, 3.1359, 3.1359] +24-11-19 20:20:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:57 | D | sum error = [ 51.5287, 55.8817, 60.6042, 66.1456, 72.1071] +24-11-19 20:20:57 | D | best error = [ 3.1359, 3.1359, 3.1359, 3.1359, 3.1359] +24-11-19 20:20:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:57 | D | sum error = [ 78.0730, 84.9826, 92.3186, 100.0993, 108.9478] +24-11-19 20:20:57 | D | best error = [ 3.1359, 3.1359, 3.1359, 3.1359, 3.1359] +24-11-19 20:20:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:57 | D | sum error = [ 117.4900, 127.4727, 138.8505, 150.2225, 163.3508] +24-11-19 20:20:57 | D | best error = [ 3.1359, 3.1359, 3.1359, 3.1359, 3.1359] +24-11-19 20:20:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:57 | D | sum error = [ 176.1254, 191.1267, 206.9468, 224.9622, 243.5501] +24-11-19 20:20:57 | D | best error = [ 3.1359, 3.1359, 3.1359, 3.1359, 3.1359] +24-11-19 20:20:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:57 | D | sum error = [ 263.3753, 285.0186, 308.5425, 334.7336, 362.7294] +24-11-19 20:20:57 | D | best error = [ 3.1359, 3.1359, 3.1359, 3.1359, 3.1359] +24-11-19 20:20:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:57 | D | sum error = [ 393.0035, 424.7566, 459.9416, 496.5940, 537.4984] +24-11-19 20:20:57 | D | best error = [ 3.1359, 3.1359, 3.1359, 3.1359, 3.1359] +24-11-19 20:20:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:57 | D | sum error = [ 581.6469, 627.1161, 677.9037, 732.0817, 789.5909] +24-11-19 20:20:57 | D | best error = [ 3.1359, 3.1359, 3.1359, 3.1359, 3.1359] +24-11-19 20:20:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:57 | D | sum error = [ 851.0133, 914.5279, 982.8550, 1053.6490, 1126.6948] +24-11-19 20:20:57 | D | best error = [ 3.1359, 3.1359, 3.1359, 3.1359, 3.1359] +24-11-19 20:20:57 | D | + error = [3.1359] +24-11-19 20:20:57 | D | - Calibrating model.layers.5.self_attn.v_proj.weight +24-11-19 20:20:57 | D | + w: sint8 +24-11-19 20:20:57 | D | + x: None +24-11-19 20:20:57 | D | + y: None +24-11-19 20:20:57 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:57 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:57 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:57 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:57 | D | - range ratio = [ 1.0000] +24-11-19 20:20:57 | D | sum error = [ 3.2208] +24-11-19 20:20:57 | D | best error = [ 3.2208] +24-11-19 20:20:58 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:58 | D | sum error = [ 3.1967, 3.1902, 3.1892, 3.2318, 3.2916] +24-11-19 20:20:58 | D | best error = [ 2.9505, 2.8578, 2.8137, 2.7875, 2.7749] +24-11-19 20:20:58 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:58 | D | sum error = [ 3.3907, 3.4903, 3.6575, 3.8258, 4.0204] +24-11-19 20:20:58 | D | best error = [ 2.7691, 2.7670, 2.7664, 2.7662, 2.7661] +24-11-19 20:20:58 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:58 | D | sum error = [ 4.2644, 4.5132, 4.8045, 5.1441, 5.4983] +24-11-19 20:20:58 | D | best error = [ 2.7661, 2.7661, 2.7661, 2.7661, 2.7661] +24-11-19 20:20:58 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:58 | D | sum error = [ 5.8858, 6.2884, 6.7550, 7.2588, 7.7490] +24-11-19 20:20:58 | D | best error = [ 2.7661, 2.7661, 2.7661, 2.7661, 2.7661] +24-11-19 20:20:58 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:58 | D | sum error = [ 8.3175, 8.9078, 9.5344, 10.2068, 10.9132] +24-11-19 20:20:58 | D | best error = [ 2.7661, 2.7661, 2.7661, 2.7661, 2.7661] +24-11-19 20:20:58 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:58 | D | sum error = [ 11.6732, 12.4659, 13.3039, 14.1978, 15.1291] +24-11-19 20:20:58 | D | best error = [ 2.7661, 2.7661, 2.7661, 2.7661, 2.7661] +24-11-19 20:20:58 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:58 | D | sum error = [ 16.1118, 17.1531, 18.2547, 19.4178, 20.6278] +24-11-19 20:20:58 | D | best error = [ 2.7661, 2.7661, 2.7661, 2.7661, 2.7661] +24-11-19 20:20:58 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:58 | D | sum error = [ 21.9205, 23.2820, 24.6949, 26.1917, 27.7650] +24-11-19 20:20:58 | D | best error = [ 2.7661, 2.7661, 2.7661, 2.7661, 2.7661] +24-11-19 20:20:58 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:58 | D | sum error = [ 29.3957, 31.1205, 32.9502, 34.8588, 36.8561] +24-11-19 20:20:58 | D | best error = [ 2.7661, 2.7661, 2.7661, 2.7661, 2.7661] +24-11-19 20:20:58 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:58 | D | sum error = [ 38.9583, 41.1488, 43.4337, 45.8381, 48.3483] +24-11-19 20:20:58 | D | best error = [ 2.7661, 2.7661, 2.7661, 2.7661, 2.7661] +24-11-19 20:20:58 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:58 | D | sum error = [ 50.9693, 53.7004, 56.5461, 59.5429, 62.6486] +24-11-19 20:20:58 | D | best error = [ 2.7661, 2.7661, 2.7661, 2.7661, 2.7661] +24-11-19 20:20:58 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:58 | D | sum error = [ 65.8938, 69.2718, 72.8067, 76.4730, 80.2881] +24-11-19 20:20:58 | D | best error = [ 2.7661, 2.7661, 2.7661, 2.7661, 2.7661] +24-11-19 20:20:58 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:58 | D | sum error = [ 84.2453, 88.3657, 92.6565, 97.1063, 101.7290] +24-11-19 20:20:58 | D | best error = [ 2.7661, 2.7661, 2.7661, 2.7661, 2.7661] +24-11-19 20:20:58 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:58 | D | sum error = [ 106.5235, 111.5023, 116.6577, 121.9968, 127.5340] +24-11-19 20:20:58 | D | best error = [ 2.7661, 2.7661, 2.7661, 2.7661, 2.7661] +24-11-19 20:20:58 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:58 | D | sum error = [ 133.2529, 139.1586, 145.2611, 151.5512, 158.0391] +24-11-19 20:20:58 | D | best error = [ 2.7661, 2.7661, 2.7661, 2.7661, 2.7661] +24-11-19 20:20:58 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:58 | D | sum error = [ 164.7422, 171.6532, 178.7713, 186.1001, 193.6499] +24-11-19 20:20:58 | D | best error = [ 2.7661, 2.7661, 2.7661, 2.7661, 2.7661] +24-11-19 20:20:58 | D | + error = [2.7661] +24-11-19 20:20:58 | D | - Calibrating model.layers.5.self_attn.o_proj.weight +24-11-19 20:20:58 | D | + w: sint8 +24-11-19 20:20:58 | D | + x: None +24-11-19 20:20:58 | D | + y: None +24-11-19 20:20:58 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:58 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:58 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:58 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:58 | D | - range ratio = [ 1.0000] +24-11-19 20:20:58 | D | sum error = [ 0.5578] +24-11-19 20:20:58 | D | best error = [ 0.5578] +24-11-19 20:20:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:59 | D | sum error = [ 0.5512, 0.5490, 0.5468, 0.5503, 0.5523] +24-11-19 20:20:59 | D | best error = [ 0.5291, 0.5152, 0.5065, 0.5010, 0.4969] +24-11-19 20:20:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:59 | D | sum error = [ 0.5603, 0.5685, 0.5816, 0.5975, 0.6193] +24-11-19 20:20:59 | D | best error = [ 0.4942, 0.4923, 0.4909, 0.4899, 0.4893] +24-11-19 20:20:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:59 | D | sum error = [ 0.6423, 0.6694, 0.7015, 0.7367, 0.7781] +24-11-19 20:20:59 | D | best error = [ 0.4890, 0.4888, 0.4887, 0.4886, 0.4885] +24-11-19 20:20:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:59 | D | sum error = [ 0.8235, 0.8723, 0.9257, 0.9847, 1.0472] +24-11-19 20:20:59 | D | best error = [ 0.4884, 0.4884, 0.4884, 0.4883, 0.4883] +24-11-19 20:20:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:59 | D | sum error = [ 1.1166, 1.1899, 1.2679, 1.3516, 1.4427] +24-11-19 20:20:59 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 20:20:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:59 | D | sum error = [ 1.5390, 1.6378, 1.7476, 1.8602, 1.9824] +24-11-19 20:20:59 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 20:20:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:59 | D | sum error = [ 2.1107, 2.2479, 2.3919, 2.5428, 2.7043] +24-11-19 20:20:59 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 20:20:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:59 | D | sum error = [ 2.8738, 3.0519, 3.2401, 3.4384, 3.6483] +24-11-19 20:20:59 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 20:20:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:59 | D | sum error = [ 3.8673, 4.0985, 4.3408, 4.5962, 4.8629] +24-11-19 20:20:59 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 20:20:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:59 | D | sum error = [ 5.1452, 5.4396, 5.7483, 6.0725, 6.4138] +24-11-19 20:20:59 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 20:20:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:59 | D | sum error = [ 6.7702, 7.1439, 7.5340, 7.9426, 8.3711] +24-11-19 20:20:59 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 20:20:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:59 | D | sum error = [ 8.8182, 9.2850, 9.7745, 10.2844, 10.8170] +24-11-19 20:20:59 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 20:20:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:59 | D | sum error = [ 11.3728, 11.9522, 12.5564, 13.1856, 13.8418] +24-11-19 20:20:59 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 20:20:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:59 | D | sum error = [ 14.5248, 15.2354, 15.9752, 16.7420, 17.5412] +24-11-19 20:20:59 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 20:20:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:59 | D | sum error = [ 18.3716, 19.2353, 20.1348, 21.0682, 22.0369] +24-11-19 20:20:59 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 20:20:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:59 | D | sum error = [ 23.0446, 24.0911, 25.1781, 26.3084, 27.4824] +24-11-19 20:20:59 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 20:20:59 | D | + error = [0.4883] +24-11-19 20:20:59 | D | - Calibrating model.layers.5.mlp.up_proj.weight +24-11-19 20:20:59 | D | + w: sint8 +24-11-19 20:20:59 | D | + x: None +24-11-19 20:20:59 | D | + y: None +24-11-19 20:20:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:59 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:59 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:59 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:59 | D | - range ratio = [ 1.0000] +24-11-19 20:20:59 | D | sum error = [ 4.5863] +24-11-19 20:20:59 | D | best error = [ 4.5863] +24-11-19 20:21:00 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:00 | D | sum error = [ 4.5516, 4.5468, 4.5680, 4.6271, 4.7099] +24-11-19 20:21:00 | D | best error = [ 4.2260, 4.0969, 4.0324, 3.9955, 3.9758] +24-11-19 20:21:00 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:00 | D | sum error = [ 4.8308, 5.0019, 5.1825, 5.4277, 5.7133] +24-11-19 20:21:00 | D | best error = [ 3.9666, 3.9628, 3.9613, 3.9609, 3.9608] +24-11-19 20:21:00 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:00 | D | sum error = [ 6.0548, 6.4220, 6.8323, 7.2942, 7.7936] +24-11-19 20:21:00 | D | best error = [ 3.9608, 3.9608, 3.9608, 3.9608, 3.9608] +24-11-19 20:21:00 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:00 | D | sum error = [ 8.3414, 8.9360, 9.5832, 10.2775, 11.0013] +24-11-19 20:21:00 | D | best error = [ 3.9608, 3.9608, 3.9608, 3.9608, 3.9608] +24-11-19 20:21:00 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:00 | D | sum error = [ 11.7901, 12.6287, 13.5190, 14.4615, 15.4735] +24-11-19 20:21:00 | D | best error = [ 3.9608, 3.9608, 3.9608, 3.9608, 3.9608] +24-11-19 20:21:00 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:00 | D | sum error = [ 16.5216, 17.6452, 18.8331, 20.0864, 21.4126] +24-11-19 20:21:00 | D | best error = [ 3.9608, 3.9608, 3.9608, 3.9608, 3.9608] +24-11-19 20:21:00 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:00 | D | sum error = [ 22.8186, 24.2783, 25.8363, 27.4702, 29.1931] +24-11-19 20:21:00 | D | best error = [ 3.9608, 3.9608, 3.9608, 3.9608, 3.9608] +24-11-19 20:21:00 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:00 | D | sum error = [ 30.9872, 32.8860, 34.8655, 36.9584, 39.1433] +24-11-19 20:21:00 | D | best error = [ 3.9608, 3.9608, 3.9608, 3.9608, 3.9608] +24-11-19 20:21:00 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:00 | D | sum error = [ 41.4344, 43.8396, 46.3716, 48.9995, 51.7681] +24-11-19 20:21:00 | D | best error = [ 3.9608, 3.9608, 3.9608, 3.9608, 3.9608] +24-11-19 20:21:00 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:00 | D | sum error = [ 54.6519, 57.6801, 60.8214, 64.1217, 67.5580] +24-11-19 20:21:00 | D | best error = [ 3.9608, 3.9608, 3.9608, 3.9608, 3.9608] +24-11-19 20:21:00 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:00 | D | sum error = [ 71.1426, 74.8790, 78.7816, 82.8403, 87.0641] +24-11-19 20:21:00 | D | best error = [ 3.9608, 3.9608, 3.9608, 3.9608, 3.9608] +24-11-19 20:21:00 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:00 | D | sum error = [ 91.4715, 96.0319, 100.7921, 105.7359, 110.8513] +24-11-19 20:21:00 | D | best error = [ 3.9608, 3.9608, 3.9608, 3.9608, 3.9608] +24-11-19 20:21:00 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:00 | D | sum error = [ 116.1706, 121.6843, 127.4158, 133.3501, 139.5010] +24-11-19 20:21:00 | D | best error = [ 3.9608, 3.9608, 3.9608, 3.9608, 3.9608] +24-11-19 20:21:00 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:00 | D | sum error = [ 145.8605, 152.4447, 159.2354, 166.2599, 173.5165] +24-11-19 20:21:00 | D | best error = [ 3.9608, 3.9608, 3.9608, 3.9608, 3.9608] +24-11-19 20:21:00 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:00 | D | sum error = [ 181.0032, 188.7170, 196.6642, 204.8500, 213.2900] +24-11-19 20:21:00 | D | best error = [ 3.9608, 3.9608, 3.9608, 3.9608, 3.9608] +24-11-19 20:21:00 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:00 | D | sum error = [ 221.9856, 230.9333, 240.1248, 249.5814, 259.2957] +24-11-19 20:21:00 | D | best error = [ 3.9608, 3.9608, 3.9608, 3.9608, 3.9608] +24-11-19 20:21:00 | D | + error = [3.9608] +24-11-19 20:21:00 | D | - Calibrating model.layers.5.mlp.gate_proj.weight +24-11-19 20:21:00 | D | + w: sint8 +24-11-19 20:21:00 | D | + x: None +24-11-19 20:21:00 | D | + y: None +24-11-19 20:21:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:00 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:00 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:00 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:00 | D | - range ratio = [ 1.0000] +24-11-19 20:21:00 | D | sum error = [ 5.1223] +24-11-19 20:21:00 | D | best error = [ 5.1223] +24-11-19 20:21:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:01 | D | sum error = [ 5.0716, 5.0708, 5.1108, 5.1680, 5.2537] +24-11-19 20:21:01 | D | best error = [ 4.7115, 4.5667, 4.4943, 4.4536, 4.4336] +24-11-19 20:21:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:01 | D | sum error = [ 5.3883, 5.5705, 5.7924, 6.0719, 6.3919] +24-11-19 20:21:01 | D | best error = [ 4.4239, 4.4197, 4.4181, 4.4177, 4.4176] +24-11-19 20:21:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:01 | D | sum error = [ 6.7617, 7.1759, 7.6664, 8.1628, 8.7250] +24-11-19 20:21:01 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:01 | D | sum error = [ 9.3425, 10.0090, 10.7379, 11.5170, 12.3398] +24-11-19 20:21:01 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:01 | D | sum error = [ 13.2510, 14.1947, 15.2034, 16.2799, 17.4203] +24-11-19 20:21:01 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:01 | D | sum error = [ 18.6503, 19.9376, 21.3059, 22.7546, 24.2972] +24-11-19 20:21:01 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:01 | D | sum error = [ 25.9076, 27.6047, 29.4313, 31.3540, 33.3544] +24-11-19 20:21:01 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:01 | D | sum error = [ 35.4901, 37.7381, 40.0922, 42.6046, 45.2214] +24-11-19 20:21:01 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:01 | D | sum error = [ 47.9984, 50.9431, 54.0342, 57.2732, 60.7075] +24-11-19 20:21:01 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:01 | D | sum error = [ 64.3239, 68.1061, 72.0980, 76.2829, 80.6788] +24-11-19 20:21:01 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:01 | D | sum error = [ 85.2944, 90.1510, 95.2458, 100.5839, 106.1844] +24-11-19 20:21:01 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:01 | D | sum error = [ 112.0359, 118.1637, 124.5785, 131.2844, 138.2943] +24-11-19 20:21:01 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:01 | D | sum error = [ 145.6013, 153.2503, 161.2309, 169.5578, 178.2525] +24-11-19 20:21:01 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:01 | D | sum error = [ 187.3088, 196.7039, 206.4848, 216.6438, 227.2013] +24-11-19 20:21:01 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:01 | D | sum error = [ 238.1508, 249.5056, 261.3103, 273.5043, 286.1301] +24-11-19 20:21:01 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:01 | D | sum error = [ 299.1606, 312.6171, 326.5033, 340.8282, 355.5927] +24-11-19 20:21:01 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:01 | D | + error = [4.4176] +24-11-19 20:21:02 | D | - Calibrating model.layers.5.mlp.down_proj.weight +24-11-19 20:21:02 | D | + w: sint8 +24-11-19 20:21:02 | D | + x: None +24-11-19 20:21:02 | D | + y: None +24-11-19 20:21:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:02 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:02 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:02 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:02 | D | - range ratio = [ 1.0000] +24-11-19 20:21:02 | D | sum error = [ 0.7728] +24-11-19 20:21:02 | D | best error = [ 0.7728] +24-11-19 20:21:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:03 | D | sum error = [ 0.7662, 0.7602, 0.7551, 0.7531, 0.7533] +24-11-19 20:21:03 | D | best error = [ 0.7498, 0.7365, 0.7272, 0.7205, 0.7157] +24-11-19 20:21:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:03 | D | sum error = [ 0.7556, 0.7603, 0.7699, 0.7809, 0.7978] +24-11-19 20:21:03 | D | best error = [ 0.7118, 0.7091, 0.7073, 0.7062, 0.7054] +24-11-19 20:21:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:03 | D | sum error = [ 0.8167, 0.8429, 0.8731, 0.9091, 0.9480] +24-11-19 20:21:03 | D | best error = [ 0.7048, 0.7044, 0.7042, 0.7041, 0.7041] +24-11-19 20:21:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:03 | D | sum error = [ 0.9966, 1.0487, 1.1084, 1.1727, 1.2464] +24-11-19 20:21:03 | D | best error = [ 0.7040, 0.7040, 0.7040, 0.7040, 0.7040] +24-11-19 20:21:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:03 | D | sum error = [ 1.3244, 1.4128, 1.5072, 1.6092, 1.7185] +24-11-19 20:21:03 | D | best error = [ 0.7040, 0.7040, 0.7040, 0.7040, 0.7040] +24-11-19 20:21:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:03 | D | sum error = [ 1.8386, 1.9658, 2.1023, 2.2505, 2.4076] +24-11-19 20:21:03 | D | best error = [ 0.7040, 0.7040, 0.7040, 0.7040, 0.7040] +24-11-19 20:21:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:03 | D | sum error = [ 2.5761, 2.7548, 2.9462, 3.1496, 3.3649] +24-11-19 20:21:03 | D | best error = [ 0.7040, 0.7040, 0.7040, 0.7040, 0.7040] +24-11-19 20:21:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:03 | D | sum error = [ 3.5946, 3.8371, 4.0964, 4.3686, 4.6591] +24-11-19 20:21:03 | D | best error = [ 0.7040, 0.7040, 0.7040, 0.7040, 0.7040] +24-11-19 20:21:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:03 | D | sum error = [ 4.9655, 5.2911, 5.6350, 5.9977, 6.3802] +24-11-19 20:21:03 | D | best error = [ 0.7040, 0.7040, 0.7040, 0.7040, 0.7040] +24-11-19 20:21:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:03 | D | sum error = [ 6.7830, 7.2093, 7.6573, 8.1304, 8.6276] +24-11-19 20:21:03 | D | best error = [ 0.7040, 0.7040, 0.7040, 0.7040, 0.7040] +24-11-19 20:21:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:03 | D | sum error = [ 9.1511, 9.7010, 10.2783, 10.8858, 11.5232] +24-11-19 20:21:03 | D | best error = [ 0.7040, 0.7040, 0.7040, 0.7040, 0.7040] +24-11-19 20:21:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:03 | D | sum error = [ 12.1931, 12.8949, 13.6301, 14.4019, 15.2087] +24-11-19 20:21:03 | D | best error = [ 0.7040, 0.7040, 0.7040, 0.7040, 0.7040] +24-11-19 20:21:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:03 | D | sum error = [ 16.0534, 16.9356, 17.8566, 18.8182, 19.8224] +24-11-19 20:21:03 | D | best error = [ 0.7040, 0.7040, 0.7040, 0.7040, 0.7040] +24-11-19 20:21:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:03 | D | sum error = [ 20.8693, 21.9601, 23.0979, 24.2833, 25.5119] +24-11-19 20:21:03 | D | best error = [ 0.7040, 0.7040, 0.7040, 0.7040, 0.7040] +24-11-19 20:21:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:03 | D | sum error = [ 26.7915, 28.1206, 29.5004, 30.9320, 32.4162] +24-11-19 20:21:03 | D | best error = [ 0.7040, 0.7040, 0.7040, 0.7040, 0.7040] +24-11-19 20:21:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:03 | D | sum error = [ 33.9528, 35.5438, 37.1898, 38.8919, 40.6495] +24-11-19 20:21:03 | D | best error = [ 0.7040, 0.7040, 0.7040, 0.7040, 0.7040] +24-11-19 20:21:03 | D | + error = [0.7040] +24-11-19 20:21:03 | D | - Quantizing model.layers.5.self_attn.q_proj.weight +24-11-19 20:21:08 | D | - Quantizing model.layers.5.self_attn.k_proj.weight +24-11-19 20:21:10 | D | - Quantizing model.layers.5.self_attn.v_proj.weight +24-11-19 20:21:11 | D | - Quantizing model.layers.5.self_attn.o_proj.weight +24-11-19 20:21:12 | D | - Quantizing model.layers.5.mlp.up_proj.weight +24-11-19 20:21:13 | D | - Quantizing model.layers.5.mlp.gate_proj.weight +24-11-19 20:21:13 | D | - Quantizing model.layers.5.mlp.down_proj.weight +24-11-19 20:21:22 | D | - Quantizing layer model.layers.6 +24-11-19 20:21:22 | D | - Calibrating model.layers.6.self_attn.q_proj.weight +24-11-19 20:21:22 | D | + w: sint8 +24-11-19 20:21:22 | D | + x: None +24-11-19 20:21:22 | D | + y: None +24-11-19 20:21:22 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:21:22 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:21:22 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:21:22 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:21:23 | D | - range ratio = [ 1.0000] +24-11-19 20:21:23 | D | sum error = [ 4.7109] +24-11-19 20:21:23 | D | best error = [ 4.7109] +24-11-19 20:21:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:36 | D | sum error = [ 4.6578, 4.6713, 4.6925, 4.7836, 4.8367] +24-11-19 20:21:36 | D | best error = [ 4.6578, 4.6578, 4.6578, 4.6578, 4.6578] +24-11-19 20:21:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:36 | D | sum error = [ 5.0882, 5.1478, 5.5231, 5.7539, 5.9626] +24-11-19 20:21:36 | D | best error = [ 4.6578, 4.6578, 4.6578, 4.6578, 4.6578] +24-11-19 20:21:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:36 | D | sum error = [ 6.5174, 7.1008, 7.5102, 8.3155, 8.9999] +24-11-19 20:21:36 | D | best error = [ 4.6578, 4.6578, 4.6578, 4.6578, 4.6578] +24-11-19 20:21:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:36 | D | sum error = [ 9.7931, 10.7213, 11.5821, 12.7890, 13.9941] +24-11-19 20:21:36 | D | best error = [ 4.6578, 4.6578, 4.6578, 4.6578, 4.6578] +24-11-19 20:21:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:36 | D | sum error = [ 15.4938, 16.8538, 18.6095, 20.6075, 22.2227] +24-11-19 20:21:36 | D | best error = [ 4.6578, 4.6578, 4.6578, 4.6578, 4.6578] +24-11-19 20:21:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:36 | D | sum error = [ 24.3796, 26.7761, 29.3421, 32.1673, 35.1935] +24-11-19 20:21:36 | D | best error = [ 4.6578, 4.6578, 4.6578, 4.6578, 4.6578] +24-11-19 20:21:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:36 | D | sum error = [ 38.1897, 41.7681, 45.7574, 50.1150, 54.3368] +24-11-19 20:21:36 | D | best error = [ 4.6578, 4.6578, 4.6578, 4.6578, 4.6578] +24-11-19 20:21:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:36 | D | sum error = [ 59.2115, 64.5373, 69.9842, 76.1185, 82.7406] +24-11-19 20:21:36 | D | best error = [ 4.6578, 4.6578, 4.6578, 4.6578, 4.6578] +24-11-19 20:21:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:36 | D | sum error = [ 89.6085, 97.1817, 105.1684, 113.6251, 123.2208] +24-11-19 20:21:36 | D | best error = [ 4.6578, 4.6578, 4.6578, 4.6578, 4.6578] +24-11-19 20:21:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:36 | D | sum error = [ 133.4464, 144.1623, 155.6983, 168.1277, 181.3964] +24-11-19 20:21:36 | D | best error = [ 4.6578, 4.6578, 4.6578, 4.6578, 4.6578] +24-11-19 20:21:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:36 | D | sum error = [ 196.1722, 211.2203, 227.6395, 245.4786, 264.5134] +24-11-19 20:21:36 | D | best error = [ 4.6578, 4.6578, 4.6578, 4.6578, 4.6578] +24-11-19 20:21:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:36 | D | sum error = [ 284.9891, 307.0216, 330.4768, 355.4568, 382.6371] +24-11-19 20:21:36 | D | best error = [ 4.6578, 4.6578, 4.6578, 4.6578, 4.6578] +24-11-19 20:21:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:36 | D | sum error = [ 410.9726, 441.7013, 474.3741, 509.3946, 546.3936] +24-11-19 20:21:36 | D | best error = [ 4.6578, 4.6578, 4.6578, 4.6578, 4.6578] +24-11-19 20:21:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:36 | D | sum error = [ 586.0090, 628.2173, 673.1931, 720.7289, 771.7421] +24-11-19 20:21:36 | D | best error = [ 4.6578, 4.6578, 4.6578, 4.6578, 4.6578] +24-11-19 20:21:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:36 | D | sum error = [ 825.4669, 882.5207, 942.7846, 1005.6553, 1072.2332] +24-11-19 20:21:36 | D | best error = [ 4.6578, 4.6578, 4.6578, 4.6578, 4.6578] +24-11-19 20:21:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:36 | D | sum error = [ 1141.5268, 1213.6391, 1288.9331, 1365.8154, 1444.6723] +24-11-19 20:21:36 | D | best error = [ 4.6578, 4.6578, 4.6578, 4.6578, 4.6578] +24-11-19 20:21:36 | D | + error = [4.6578] +24-11-19 20:21:36 | D | - Calibrating model.layers.6.self_attn.k_proj.weight +24-11-19 20:21:36 | D | + w: sint8 +24-11-19 20:21:36 | D | + x: None +24-11-19 20:21:36 | D | + y: None +24-11-19 20:21:36 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:21:36 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:36 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:37 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:37 | D | - range ratio = [ 1.0000] +24-11-19 20:21:37 | D | sum error = [ 5.7349] +24-11-19 20:21:37 | D | best error = [ 5.7349] +24-11-19 20:21:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:51 | D | sum error = [ 5.4683, 5.7302, 6.2702, 5.7204, 5.5493] +24-11-19 20:21:51 | D | best error = [ 5.4683, 5.4683, 5.4683, 5.4683, 5.4683] +24-11-19 20:21:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:51 | D | sum error = [ 6.0727, 6.2643, 6.4115, 6.7886, 7.1315] +24-11-19 20:21:51 | D | best error = [ 5.4683, 5.4683, 5.4683, 5.4683, 5.4683] +24-11-19 20:21:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:51 | D | sum error = [ 7.5949, 8.2721, 8.5629, 8.8516, 10.1996] +24-11-19 20:21:51 | D | best error = [ 5.4683, 5.4683, 5.4683, 5.4683, 5.4683] +24-11-19 20:21:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:51 | D | sum error = [ 10.8092, 11.5829, 12.5106, 13.6441, 15.3276] +24-11-19 20:21:51 | D | best error = [ 5.4683, 5.4683, 5.4683, 5.4683, 5.4683] +24-11-19 20:21:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:51 | D | sum error = [ 15.9239, 17.0403, 18.3745, 20.2874, 22.1933] +24-11-19 20:21:51 | D | best error = [ 5.4683, 5.4683, 5.4683, 5.4683, 5.4683] +24-11-19 20:21:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:51 | D | sum error = [ 24.6277, 26.2069, 28.1685, 30.9960, 33.6714] +24-11-19 20:21:51 | D | best error = [ 5.4683, 5.4683, 5.4683, 5.4683, 5.4683] +24-11-19 20:21:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:51 | D | sum error = [ 37.3427, 40.3209, 43.7606, 47.4959, 52.2325] +24-11-19 20:21:51 | D | best error = [ 5.4683, 5.4683, 5.4683, 5.4683, 5.4683] +24-11-19 20:21:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:51 | D | sum error = [ 56.3315, 61.7361, 66.0143, 71.2898, 77.5428] +24-11-19 20:21:51 | D | best error = [ 5.4683, 5.4683, 5.4683, 5.4683, 5.4683] +24-11-19 20:21:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:51 | D | sum error = [ 83.2659, 90.1700, 96.9366, 104.5478, 113.2627] +24-11-19 20:21:51 | D | best error = [ 5.4683, 5.4683, 5.4683, 5.4683, 5.4683] +24-11-19 20:21:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:51 | D | sum error = [ 121.4568, 131.6725, 141.6137, 152.2308, 164.1610] +24-11-19 20:21:51 | D | best error = [ 5.4683, 5.4683, 5.4683, 5.4683, 5.4683] +24-11-19 20:21:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:51 | D | sum error = [ 177.6381, 191.6299, 205.9944, 222.4445, 238.7348] +24-11-19 20:21:51 | D | best error = [ 5.4683, 5.4683, 5.4683, 5.4683, 5.4683] +24-11-19 20:21:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:51 | D | sum error = [ 257.7906, 277.6148, 298.4702, 322.3000, 347.6441] +24-11-19 20:21:51 | D | best error = [ 5.4683, 5.4683, 5.4683, 5.4683, 5.4683] +24-11-19 20:21:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:51 | D | sum error = [ 374.6300, 403.6679, 434.5079, 470.1505, 505.2939] +24-11-19 20:21:51 | D | best error = [ 5.4683, 5.4683, 5.4683, 5.4683, 5.4683] +24-11-19 20:21:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:51 | D | sum error = [ 543.9167, 586.7003, 630.2308, 679.0097, 727.2831] +24-11-19 20:21:51 | D | best error = [ 5.4683, 5.4683, 5.4683, 5.4683, 5.4683] +24-11-19 20:21:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:51 | D | sum error = [ 782.7141, 840.0502, 901.8339, 966.3807, 1036.3131] +24-11-19 20:21:51 | D | best error = [ 5.4683, 5.4683, 5.4683, 5.4683, 5.4683] +24-11-19 20:21:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:51 | D | sum error = [ 1106.9304, 1182.3303, 1257.5277, 1336.9332, 1418.2332] +24-11-19 20:21:51 | D | best error = [ 5.4683, 5.4683, 5.4683, 5.4683, 5.4683] +24-11-19 20:21:51 | D | + error = [5.4683] +24-11-19 20:21:51 | D | - Calibrating model.layers.6.self_attn.v_proj.weight +24-11-19 20:21:51 | D | + w: sint8 +24-11-19 20:21:51 | D | + x: None +24-11-19 20:21:51 | D | + y: None +24-11-19 20:21:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:51 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:51 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:51 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:51 | D | - range ratio = [ 1.0000] +24-11-19 20:21:51 | D | sum error = [ 3.6928] +24-11-19 20:21:51 | D | best error = [ 3.6928] +24-11-19 20:21:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:52 | D | sum error = [ 3.6647, 3.6439, 3.6946, 3.7206, 3.7829] +24-11-19 20:21:52 | D | best error = [ 3.4310, 3.3331, 3.2874, 3.2599, 3.2446] +24-11-19 20:21:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:52 | D | sum error = [ 3.8904, 4.0170, 4.1882, 4.3903, 4.6268] +24-11-19 20:21:52 | D | best error = [ 3.2388, 3.2364, 3.2355, 3.2353, 3.2353] +24-11-19 20:21:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:52 | D | sum error = [ 4.9077, 5.2113, 5.5427, 5.9108, 6.3146] +24-11-19 20:21:52 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 20:21:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:52 | D | sum error = [ 6.7705, 7.2610, 7.7659, 8.3416, 8.9460] +24-11-19 20:21:52 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 20:21:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:52 | D | sum error = [ 9.5944, 10.2385, 10.9684, 11.7528, 12.5633] +24-11-19 20:21:52 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 20:21:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:52 | D | sum error = [ 13.4454, 14.3636, 15.3297, 16.3723, 17.4663] +24-11-19 20:21:52 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 20:21:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:52 | D | sum error = [ 18.6167, 19.8269, 21.1176, 22.4534, 23.8950] +24-11-19 20:21:52 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 20:21:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:52 | D | sum error = [ 25.3937, 26.9887, 28.6649, 30.4159, 32.2781] +24-11-19 20:21:52 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 20:21:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:52 | D | sum error = [ 34.2166, 36.2774, 38.4244, 40.6719, 43.0373] +24-11-19 20:21:52 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 20:21:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:52 | D | sum error = [ 45.5284, 48.1279, 50.8394, 53.7039, 56.6955] +24-11-19 20:21:52 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 20:21:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:52 | D | sum error = [ 59.8256, 63.1085, 66.5456, 70.1400, 73.9139] +24-11-19 20:21:52 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 20:21:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:52 | D | sum error = [ 77.8500, 81.9614, 86.2643, 90.7394, 95.4142] +24-11-19 20:21:52 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 20:21:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:52 | D | sum error = [ 100.2890, 105.3627, 110.6382, 116.1278, 121.8477] +24-11-19 20:21:52 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 20:21:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:52 | D | sum error = [ 127.7903, 133.9564, 140.3640, 147.0234, 153.9051] +24-11-19 20:21:52 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 20:21:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:52 | D | sum error = [ 161.0455, 168.4572, 176.1132, 184.0275, 192.2000] +24-11-19 20:21:52 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 20:21:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:52 | D | sum error = [ 200.6291, 209.3295, 218.2862, 227.5184, 237.0110] +24-11-19 20:21:52 | D | best error = [ 3.2353, 3.2353, 3.2353, 3.2353, 3.2353] +24-11-19 20:21:52 | D | + error = [3.2353] +24-11-19 20:21:52 | D | - Calibrating model.layers.6.self_attn.o_proj.weight +24-11-19 20:21:52 | D | + w: sint8 +24-11-19 20:21:52 | D | + x: None +24-11-19 20:21:52 | D | + y: None +24-11-19 20:21:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:52 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:52 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:52 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:52 | D | - range ratio = [ 1.0000] +24-11-19 20:21:52 | D | sum error = [ 0.5784] +24-11-19 20:21:52 | D | best error = [ 0.5784] +24-11-19 20:21:53 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:53 | D | sum error = [ 0.5730, 0.5701, 0.5724, 0.5767, 0.5852] +24-11-19 20:21:53 | D | best error = [ 0.5436, 0.5274, 0.5187, 0.5127, 0.5090] +24-11-19 20:21:53 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:53 | D | sum error = [ 0.5990, 0.6155, 0.6377, 0.6648, 0.6923] +24-11-19 20:21:53 | D | best error = [ 0.5065, 0.5049, 0.5039, 0.5033, 0.5028] +24-11-19 20:21:53 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:53 | D | sum error = [ 0.7300, 0.7702, 0.8167, 0.8675, 0.9229] +24-11-19 20:21:53 | D | best error = [ 0.5025, 0.5022, 0.5021, 0.5020, 0.5019] +24-11-19 20:21:53 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:53 | D | sum error = [ 0.9813, 1.0492, 1.1189, 1.1958, 1.2779] +24-11-19 20:21:53 | D | best error = [ 0.5019, 0.5018, 0.5018, 0.5018, 0.5018] +24-11-19 20:21:53 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:53 | D | sum error = [ 1.3661, 1.4609, 1.5575, 1.6628, 1.7767] +24-11-19 20:21:53 | D | best error = [ 0.5018, 0.5018, 0.5018, 0.5018, 0.5018] +24-11-19 20:21:53 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:53 | D | sum error = [ 1.8953, 2.0215, 2.1556, 2.2976, 2.4469] +24-11-19 20:21:53 | D | best error = [ 0.5018, 0.5018, 0.5018, 0.5018, 0.5018] +24-11-19 20:21:53 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:53 | D | sum error = [ 2.6050, 2.7718, 2.9483, 3.1336, 3.3278] +24-11-19 20:21:53 | D | best error = [ 0.5018, 0.5018, 0.5018, 0.5018, 0.5018] +24-11-19 20:21:53 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:53 | D | sum error = [ 3.5343, 3.7528, 3.9813, 4.2246, 4.4771] +24-11-19 20:21:53 | D | best error = [ 0.5018, 0.5018, 0.5018, 0.5018, 0.5018] +24-11-19 20:21:53 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:53 | D | sum error = [ 4.7432, 5.0241, 5.3174, 5.6263, 5.9508] +24-11-19 20:21:53 | D | best error = [ 0.5018, 0.5018, 0.5018, 0.5018, 0.5018] +24-11-19 20:21:53 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:53 | D | sum error = [ 6.2924, 6.6477, 7.0216, 7.4148, 7.8262] +24-11-19 20:21:53 | D | best error = [ 0.5018, 0.5018, 0.5018, 0.5018, 0.5018] +24-11-19 20:21:53 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:53 | D | sum error = [ 8.2574, 8.7094, 9.1823, 9.6762, 10.1943] +24-11-19 20:21:53 | D | best error = [ 0.5018, 0.5018, 0.5018, 0.5018, 0.5018] +24-11-19 20:21:53 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:53 | D | sum error = [ 10.7353, 11.2995, 11.8906, 12.5061, 13.1494] +24-11-19 20:21:53 | D | best error = [ 0.5018, 0.5018, 0.5018, 0.5018, 0.5018] +24-11-19 20:21:53 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:53 | D | sum error = [ 13.8214, 14.5216, 15.2524, 16.0129, 16.8067] +24-11-19 20:21:53 | D | best error = [ 0.5018, 0.5018, 0.5018, 0.5018, 0.5018] +24-11-19 20:21:53 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:53 | D | sum error = [ 17.6319, 18.4909, 19.3826, 20.3095, 21.2736] +24-11-19 20:21:53 | D | best error = [ 0.5018, 0.5018, 0.5018, 0.5018, 0.5018] +24-11-19 20:21:53 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:53 | D | sum error = [ 22.2730, 23.3081, 24.3841, 25.4992, 26.6555] +24-11-19 20:21:53 | D | best error = [ 0.5018, 0.5018, 0.5018, 0.5018, 0.5018] +24-11-19 20:21:53 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:53 | D | sum error = [ 27.8521, 29.0900, 30.3705, 31.6926, 33.0567] +24-11-19 20:21:53 | D | best error = [ 0.5018, 0.5018, 0.5018, 0.5018, 0.5018] +24-11-19 20:21:53 | D | + error = [0.5018] +24-11-19 20:21:53 | D | - Calibrating model.layers.6.mlp.up_proj.weight +24-11-19 20:21:53 | D | + w: sint8 +24-11-19 20:21:53 | D | + x: None +24-11-19 20:21:53 | D | + y: None +24-11-19 20:21:53 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:53 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:53 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:53 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:53 | D | - range ratio = [ 1.0000] +24-11-19 20:21:53 | D | sum error = [ 4.8870] +24-11-19 20:21:53 | D | best error = [ 4.8870] +24-11-19 20:21:54 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:54 | D | sum error = [ 4.8526, 4.8471, 4.8578, 4.9151, 5.0189] +24-11-19 20:21:54 | D | best error = [ 4.5253, 4.3952, 4.3258, 4.2899, 4.2702] +24-11-19 20:21:54 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:54 | D | sum error = [ 5.1387, 5.3008, 5.5297, 5.7891, 6.1032] +24-11-19 20:21:54 | D | best error = [ 4.2617, 4.2577, 4.2566, 4.2563, 4.2562] +24-11-19 20:21:54 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:54 | D | sum error = [ 6.4435, 6.8458, 7.3013, 7.7975, 8.3383] +24-11-19 20:21:54 | D | best error = [ 4.2562, 4.2562, 4.2562, 4.2562, 4.2562] +24-11-19 20:21:54 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:54 | D | sum error = [ 8.9147, 9.5470, 10.2416, 10.9672, 11.7433] +24-11-19 20:21:54 | D | best error = [ 4.2562, 4.2562, 4.2562, 4.2562, 4.2562] +24-11-19 20:21:54 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:54 | D | sum error = [ 12.5940, 13.4808, 14.4302, 15.4484, 16.5033] +24-11-19 20:21:54 | D | best error = [ 4.2562, 4.2562, 4.2562, 4.2562, 4.2562] +24-11-19 20:21:54 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:54 | D | sum error = [ 17.6263, 18.8278, 20.1052, 21.4232, 22.8488] +24-11-19 20:21:54 | D | best error = [ 4.2562, 4.2562, 4.2562, 4.2562, 4.2562] +24-11-19 20:21:54 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:54 | D | sum error = [ 24.3465, 25.9057, 27.5620, 29.2976, 31.1419] +24-11-19 20:21:54 | D | best error = [ 4.2562, 4.2562, 4.2562, 4.2562, 4.2562] +24-11-19 20:21:54 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:54 | D | sum error = [ 33.0722, 35.0910, 37.2346, 39.4902, 41.8290] +24-11-19 20:21:54 | D | best error = [ 4.2562, 4.2562, 4.2562, 4.2562, 4.2562] +24-11-19 20:21:54 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:54 | D | sum error = [ 44.3005, 46.8905, 49.6101, 52.4601, 55.4501] +24-11-19 20:21:54 | D | best error = [ 4.2562, 4.2562, 4.2562, 4.2562, 4.2562] +24-11-19 20:21:54 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:54 | D | sum error = [ 58.5781, 61.8502, 65.2716, 68.8477, 72.5829] +24-11-19 20:21:54 | D | best error = [ 4.2562, 4.2562, 4.2562, 4.2562, 4.2562] +24-11-19 20:21:54 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:54 | D | sum error = [ 76.4816, 80.5295, 84.7514, 89.1714, 93.7464] +24-11-19 20:21:54 | D | best error = [ 4.2562, 4.2562, 4.2562, 4.2562, 4.2562] +24-11-19 20:21:54 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:54 | D | sum error = [ 98.5147, 103.4860, 108.6496, 114.0210, 119.6070] +24-11-19 20:21:54 | D | best error = [ 4.2562, 4.2562, 4.2562, 4.2562, 4.2562] +24-11-19 20:21:54 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:54 | D | sum error = [ 125.4162, 131.4319, 137.6786, 144.1451, 150.8572] +24-11-19 20:21:54 | D | best error = [ 4.2562, 4.2562, 4.2562, 4.2562, 4.2562] +24-11-19 20:21:54 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:54 | D | sum error = [ 157.8089, 164.9994, 172.4499, 180.1517, 188.1061] +24-11-19 20:21:54 | D | best error = [ 4.2562, 4.2562, 4.2562, 4.2562, 4.2562] +24-11-19 20:21:54 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:54 | D | sum error = [ 196.3349, 204.8276, 213.5911, 222.6279, 231.9476] +24-11-19 20:21:54 | D | best error = [ 4.2562, 4.2562, 4.2562, 4.2562, 4.2562] +24-11-19 20:21:54 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:54 | D | sum error = [ 241.5490, 251.4373, 261.6224, 272.1010, 282.8743] +24-11-19 20:21:54 | D | best error = [ 4.2562, 4.2562, 4.2562, 4.2562, 4.2562] +24-11-19 20:21:54 | D | + error = [4.2562] +24-11-19 20:21:54 | D | - Calibrating model.layers.6.mlp.gate_proj.weight +24-11-19 20:21:54 | D | + w: sint8 +24-11-19 20:21:54 | D | + x: None +24-11-19 20:21:54 | D | + y: None +24-11-19 20:21:54 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:54 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:54 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:55 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:55 | D | - range ratio = [ 1.0000] +24-11-19 20:21:55 | D | sum error = [ 5.5708] +24-11-19 20:21:55 | D | best error = [ 5.5708] +24-11-19 20:21:56 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:56 | D | sum error = [ 5.5258, 5.5205, 5.5441, 5.6021, 5.7024] +24-11-19 20:21:56 | D | best error = [ 5.1658, 5.0144, 4.9351, 4.8906, 4.8681] +24-11-19 20:21:56 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:56 | D | sum error = [ 5.8673, 6.0624, 6.3066, 6.5889, 6.9534] +24-11-19 20:21:56 | D | best error = [ 4.8584, 4.8542, 4.8524, 4.8518, 4.8517] +24-11-19 20:21:56 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:56 | D | sum error = [ 7.3548, 7.8204, 8.3322, 8.9106, 9.5247] +24-11-19 20:21:56 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:21:56 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:56 | D | sum error = [ 10.2049, 10.9270, 11.7393, 12.5951, 13.4908] +24-11-19 20:21:56 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:21:56 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:56 | D | sum error = [ 14.4834, 15.5508, 16.6434, 17.8384, 19.1144] +24-11-19 20:21:56 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:21:56 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:56 | D | sum error = [ 20.4455, 21.8713, 23.3784, 24.9954, 26.6804] +24-11-19 20:21:56 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:21:56 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:56 | D | sum error = [ 28.4716, 30.3585, 32.3989, 34.5069, 36.7645] +24-11-19 20:21:56 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:21:56 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:56 | D | sum error = [ 39.1380, 41.6598, 44.3053, 47.1078, 50.0819] +24-11-19 20:21:56 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:21:56 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:56 | D | sum error = [ 53.1930, 56.4776, 59.9491, 63.6151, 67.4634] +24-11-19 20:21:56 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:21:56 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:56 | D | sum error = [ 71.5460, 75.8426, 80.3771, 85.1472, 90.1842] +24-11-19 20:21:56 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:21:56 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:56 | D | sum error = [ 95.4749, 101.0544, 106.9130, 113.0920, 119.5681] +24-11-19 20:21:56 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:21:56 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:56 | D | sum error = [ 126.3755, 133.5350, 141.0533, 148.9169, 157.1681] +24-11-19 20:21:56 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:21:56 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:56 | D | sum error = [ 165.7928, 174.8161, 184.2488, 194.0972, 204.3904] +24-11-19 20:21:56 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:21:56 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:56 | D | sum error = [ 215.1362, 226.3328, 238.0044, 250.1399, 262.7651] +24-11-19 20:21:56 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:21:56 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:56 | D | sum error = [ 275.8889, 289.5005, 303.6500, 318.2987, 333.4633] +24-11-19 20:21:56 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:21:56 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:56 | D | sum error = [ 349.1480, 365.3634, 382.1205, 399.4091, 417.2102] +24-11-19 20:21:56 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:21:56 | D | + error = [4.8517] +24-11-19 20:21:56 | D | - Calibrating model.layers.6.mlp.down_proj.weight +24-11-19 20:21:56 | D | + w: sint8 +24-11-19 20:21:56 | D | + x: None +24-11-19 20:21:56 | D | + y: None +24-11-19 20:21:56 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:56 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:56 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:56 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:56 | D | - range ratio = [ 1.0000] +24-11-19 20:21:56 | D | sum error = [ 0.9535] +24-11-19 20:21:56 | D | best error = [ 0.9535] +24-11-19 20:21:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:57 | D | sum error = [ 0.9436, 0.9375, 0.9317, 0.9282, 0.9297] +24-11-19 20:21:57 | D | best error = [ 0.9212, 0.9046, 0.8930, 0.8841, 0.8773] +24-11-19 20:21:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:57 | D | sum error = [ 0.9323, 0.9373, 0.9485, 0.9648, 0.9845] +24-11-19 20:21:57 | D | best error = [ 0.8727, 0.8694, 0.8667, 0.8649, 0.8636] +24-11-19 20:21:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:57 | D | sum error = [ 1.0103, 1.0421, 1.0786, 1.1236, 1.1752] +24-11-19 20:21:57 | D | best error = [ 0.8629, 0.8623, 0.8620, 0.8619, 0.8618] +24-11-19 20:21:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:57 | D | sum error = [ 1.2336, 1.3002, 1.3729, 1.4546, 1.5468] +24-11-19 20:21:57 | D | best error = [ 0.8618, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:21:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:57 | D | sum error = [ 1.6457, 1.7548, 1.8724, 2.0007, 2.1402] +24-11-19 20:21:57 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:21:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:57 | D | sum error = [ 2.2902, 2.4513, 2.6244, 2.8075, 3.0066] +24-11-19 20:21:57 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:21:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:57 | D | sum error = [ 3.2161, 3.4401, 3.6780, 3.9339, 4.2033] +24-11-19 20:21:57 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:21:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:57 | D | sum error = [ 4.4899, 4.7927, 5.1162, 5.4558, 5.8165] +24-11-19 20:21:57 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:21:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:57 | D | sum error = [ 6.2010, 6.6047, 7.0320, 7.4812, 7.9572] +24-11-19 20:21:57 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:21:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:57 | D | sum error = [ 8.4586, 8.9870, 9.5426, 10.1287, 10.7438] +24-11-19 20:21:57 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:21:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:57 | D | sum error = [ 11.3900, 12.0701, 12.7838, 13.5344, 14.3216] +24-11-19 20:21:57 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:21:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:57 | D | sum error = [ 15.1466, 16.0104, 16.9153, 17.8630, 18.8531] +24-11-19 20:21:57 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:21:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:57 | D | sum error = [ 19.8897, 20.9729, 22.1027, 23.2833, 24.5162] +24-11-19 20:21:57 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:21:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:57 | D | sum error = [ 25.7994, 27.1373, 28.5308, 29.9811, 31.4858] +24-11-19 20:21:57 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:21:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:57 | D | sum error = [ 33.0515, 34.6775, 36.3649, 38.1155, 39.9304] +24-11-19 20:21:57 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:21:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:57 | D | sum error = [ 41.8107, 43.7558, 45.7699, 47.8498, 49.9991] +24-11-19 20:21:57 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:21:57 | D | + error = [0.8617] +24-11-19 20:21:57 | D | - Quantizing model.layers.6.self_attn.q_proj.weight +24-11-19 20:22:02 | D | - Quantizing model.layers.6.self_attn.k_proj.weight +24-11-19 20:22:06 | D | - Quantizing model.layers.6.self_attn.v_proj.weight +24-11-19 20:22:09 | D | - Quantizing model.layers.6.self_attn.o_proj.weight +24-11-19 20:22:11 | D | - Quantizing model.layers.6.mlp.up_proj.weight +24-11-19 20:22:12 | D | - Quantizing model.layers.6.mlp.gate_proj.weight +24-11-19 20:22:13 | D | - Quantizing model.layers.6.mlp.down_proj.weight +24-11-19 20:22:21 | D | - Quantizing layer model.layers.7 +24-11-19 20:22:21 | D | - Calibrating model.layers.7.self_attn.q_proj.weight +24-11-19 20:22:21 | D | + w: sint8 +24-11-19 20:22:21 | D | + x: None +24-11-19 20:22:21 | D | + y: None +24-11-19 20:22:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:22:21 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:21 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:21 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:22 | D | - range ratio = [ 1.0000] +24-11-19 20:22:22 | D | sum error = [ 5.7766] +24-11-19 20:22:22 | D | best error = [ 5.7766] +24-11-19 20:22:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:35 | D | sum error = [ 5.7440, 5.5556, 5.6761, 5.7816, 5.8769] +24-11-19 20:22:35 | D | best error = [ 5.7440, 5.5556, 5.5556, 5.5556, 5.5556] +24-11-19 20:22:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:35 | D | sum error = [ 6.1821, 6.2345, 6.6277, 6.8625, 7.3225] +24-11-19 20:22:35 | D | best error = [ 5.5556, 5.5556, 5.5556, 5.5556, 5.5556] +24-11-19 20:22:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:35 | D | sum error = [ 7.9867, 8.4041, 9.0811, 9.7335, 10.5682] +24-11-19 20:22:35 | D | best error = [ 5.5556, 5.5556, 5.5556, 5.5556, 5.5556] +24-11-19 20:22:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:35 | D | sum error = [ 11.2892, 12.3709, 13.4458, 14.4439, 16.1216] +24-11-19 20:22:35 | D | best error = [ 5.5556, 5.5556, 5.5556, 5.5556, 5.5556] +24-11-19 20:22:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:35 | D | sum error = [ 17.4957, 18.7547, 20.5042, 22.2562, 24.3898] +24-11-19 20:22:35 | D | best error = [ 5.5556, 5.5556, 5.5556, 5.5556, 5.5556] +24-11-19 20:22:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:35 | D | sum error = [ 26.4007, 28.5562, 31.2122, 33.9746, 36.6465] +24-11-19 20:22:35 | D | best error = [ 5.5556, 5.5556, 5.5556, 5.5556, 5.5556] +24-11-19 20:22:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:35 | D | sum error = [ 39.8706, 43.0703, 46.5819, 50.7364, 54.4650] +24-11-19 20:22:35 | D | best error = [ 5.5556, 5.5556, 5.5556, 5.5556, 5.5556] +24-11-19 20:22:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:35 | D | sum error = [ 59.1188, 64.0498, 69.2256, 74.7926, 80.8231] +24-11-19 20:22:35 | D | best error = [ 5.5556, 5.5556, 5.5556, 5.5556, 5.5556] +24-11-19 20:22:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:35 | D | sum error = [ 87.0237, 93.7834, 101.0067, 108.7504, 117.2646] +24-11-19 20:22:35 | D | best error = [ 5.5556, 5.5556, 5.5556, 5.5556, 5.5556] +24-11-19 20:22:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:35 | D | sum error = [ 125.9661, 135.2442, 145.4570, 156.0470, 167.6393] +24-11-19 20:22:35 | D | best error = [ 5.5556, 5.5556, 5.5556, 5.5556, 5.5556] +24-11-19 20:22:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:35 | D | sum error = [ 179.8395, 193.1803, 207.3124, 222.5947, 239.1019] +24-11-19 20:22:35 | D | best error = [ 5.5556, 5.5556, 5.5556, 5.5556, 5.5556] +24-11-19 20:22:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:35 | D | sum error = [ 256.5447, 275.4017, 295.6936, 317.5266, 340.4887] +24-11-19 20:22:35 | D | best error = [ 5.5556, 5.5556, 5.5556, 5.5556, 5.5556] +24-11-19 20:22:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:35 | D | sum error = [ 365.0680, 391.7056, 420.0169, 450.4071, 482.6358] +24-11-19 20:22:35 | D | best error = [ 5.5556, 5.5556, 5.5556, 5.5556, 5.5556] +24-11-19 20:22:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:35 | D | sum error = [ 517.3124, 554.3284, 593.9740, 636.1322, 681.6479] +24-11-19 20:22:35 | D | best error = [ 5.5556, 5.5556, 5.5556, 5.5556, 5.5556] +24-11-19 20:22:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:35 | D | sum error = [ 730.2393, 782.6835, 838.4521, 898.2230, 961.6988] +24-11-19 20:22:35 | D | best error = [ 5.5556, 5.5556, 5.5556, 5.5556, 5.5556] +24-11-19 20:22:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:35 | D | sum error = [ 1029.1346, 1100.1977, 1175.2665, 1253.3175, 1335.0407] +24-11-19 20:22:35 | D | best error = [ 5.5556, 5.5556, 5.5556, 5.5556, 5.5556] +24-11-19 20:22:35 | D | + error = [5.5556] +24-11-19 20:22:35 | D | - Calibrating model.layers.7.self_attn.k_proj.weight +24-11-19 20:22:35 | D | + w: sint8 +24-11-19 20:22:35 | D | + x: None +24-11-19 20:22:35 | D | + y: None +24-11-19 20:22:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:22:35 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:35 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:36 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:36 | D | - range ratio = [ 1.0000] +24-11-19 20:22:36 | D | sum error = [ 6.9081] +24-11-19 20:22:36 | D | best error = [ 6.9081] +24-11-19 20:22:49 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:49 | D | sum error = [ 7.0607, 7.2102, 6.6505, 6.9217, 7.1082] +24-11-19 20:22:49 | D | best error = [ 6.9081, 6.9081, 6.6505, 6.6505, 6.6505] +24-11-19 20:22:49 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:49 | D | sum error = [ 7.0274, 7.2034, 8.2152, 8.2141, 8.5028] +24-11-19 20:22:49 | D | best error = [ 6.6505, 6.6505, 6.6505, 6.6505, 6.6505] +24-11-19 20:22:49 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:49 | D | sum error = [ 9.6987, 10.4496, 10.9027, 11.2617, 12.5979] +24-11-19 20:22:49 | D | best error = [ 6.6505, 6.6505, 6.6505, 6.6505, 6.6505] +24-11-19 20:22:49 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:49 | D | sum error = [ 13.3563, 13.8195, 14.7667, 16.1907, 17.4689] +24-11-19 20:22:49 | D | best error = [ 6.6505, 6.6505, 6.6505, 6.6505, 6.6505] +24-11-19 20:22:49 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:49 | D | sum error = [ 18.5537, 19.9708, 21.7315, 23.2496, 25.2225] +24-11-19 20:22:49 | D | best error = [ 6.6505, 6.6505, 6.6505, 6.6505, 6.6505] +24-11-19 20:22:49 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:49 | D | sum error = [ 27.1128, 29.0473, 31.7543, 34.1532, 36.9469] +24-11-19 20:22:49 | D | best error = [ 6.6505, 6.6505, 6.6505, 6.6505, 6.6505] +24-11-19 20:22:49 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:49 | D | sum error = [ 38.9833, 42.3163, 45.8870, 49.5284, 53.9073] +24-11-19 20:22:49 | D | best error = [ 6.6505, 6.6505, 6.6505, 6.6505, 6.6505] +24-11-19 20:22:49 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:49 | D | sum error = [ 57.5401, 62.1603, 66.8192, 72.0537, 77.4596] +24-11-19 20:22:49 | D | best error = [ 6.6505, 6.6505, 6.6505, 6.6505, 6.6505] +24-11-19 20:22:49 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:49 | D | sum error = [ 83.1554, 89.2480, 96.1474, 103.6923, 111.4032] +24-11-19 20:22:49 | D | best error = [ 6.6505, 6.6505, 6.6505, 6.6505, 6.6505] +24-11-19 20:22:49 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:49 | D | sum error = [ 119.8874, 128.8698, 138.9573, 149.8573, 161.1403] +24-11-19 20:22:49 | D | best error = [ 6.6505, 6.6505, 6.6505, 6.6505, 6.6505] +24-11-19 20:22:49 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:49 | D | sum error = [ 173.0704, 187.5899, 202.3862, 218.3458, 235.5284] +24-11-19 20:22:49 | D | best error = [ 6.6505, 6.6505, 6.6505, 6.6505, 6.6505] +24-11-19 20:22:49 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:49 | D | sum error = [ 253.5935, 272.6278, 293.6395, 316.5115, 339.8597] +24-11-19 20:22:49 | D | best error = [ 6.6505, 6.6505, 6.6505, 6.6505, 6.6505] +24-11-19 20:22:49 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:49 | D | sum error = [ 366.3861, 393.7200, 424.7798, 456.2421, 491.4214] +24-11-19 20:22:49 | D | best error = [ 6.6505, 6.6505, 6.6505, 6.6505, 6.6505] +24-11-19 20:22:49 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:49 | D | sum error = [ 527.8604, 566.6569, 609.9070, 655.0981, 703.5024] +24-11-19 20:22:49 | D | best error = [ 6.6505, 6.6505, 6.6505, 6.6505, 6.6505] +24-11-19 20:22:49 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:49 | D | sum error = [ 754.7363, 808.6575, 866.6750, 929.1182, 994.5263] +24-11-19 20:22:49 | D | best error = [ 6.6505, 6.6505, 6.6505, 6.6505, 6.6505] +24-11-19 20:22:49 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:49 | D | sum error = [ 1064.3165, 1134.6091, 1211.1597, 1289.6668, 1371.3090] +24-11-19 20:22:49 | D | best error = [ 6.6505, 6.6505, 6.6505, 6.6505, 6.6505] +24-11-19 20:22:49 | D | + error = [6.6505] +24-11-19 20:22:49 | D | - Calibrating model.layers.7.self_attn.v_proj.weight +24-11-19 20:22:49 | D | + w: sint8 +24-11-19 20:22:49 | D | + x: None +24-11-19 20:22:49 | D | + y: None +24-11-19 20:22:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:49 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:49 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:49 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:49 | D | - range ratio = [ 1.0000] +24-11-19 20:22:49 | D | sum error = [ 3.9003] +24-11-19 20:22:49 | D | best error = [ 3.9003] +24-11-19 20:22:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:50 | D | sum error = [ 3.8519, 3.8351, 3.8780, 3.9067, 3.9714] +24-11-19 20:22:50 | D | best error = [ 3.6236, 3.5196, 3.4709, 3.4424, 3.4285] +24-11-19 20:22:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:50 | D | sum error = [ 4.0955, 4.2104, 4.3843, 4.6033, 4.8356] +24-11-19 20:22:50 | D | best error = [ 3.4219, 3.4185, 3.4172, 3.4169, 3.4169] +24-11-19 20:22:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:50 | D | sum error = [ 5.1187, 5.4421, 5.7931, 6.1730, 6.6065] +24-11-19 20:22:50 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 20:22:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:50 | D | sum error = [ 7.0727, 7.5624, 8.1097, 8.6843, 9.3169] +24-11-19 20:22:50 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 20:22:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:50 | D | sum error = [ 9.9589, 10.6857, 11.4290, 12.2551, 13.0897] +24-11-19 20:22:50 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 20:22:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:50 | D | sum error = [ 13.9783, 14.9442, 15.9404, 17.0249, 18.1538] +24-11-19 20:22:50 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 20:22:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:50 | D | sum error = [ 19.3623, 20.6182, 21.9404, 23.3479, 24.8358] +24-11-19 20:22:50 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 20:22:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:50 | D | sum error = [ 26.3916, 28.0475, 29.7764, 31.6026, 33.5217] +24-11-19 20:22:50 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 20:22:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:50 | D | sum error = [ 35.5530, 37.6784, 39.9012, 42.2431, 44.7181] +24-11-19 20:22:50 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 20:22:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:50 | D | sum error = [ 47.3010, 50.0158, 52.8703, 55.8496, 58.9750] +24-11-19 20:22:50 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 20:22:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:50 | D | sum error = [ 62.2369, 65.6822, 69.2665, 73.0069, 76.9265] +24-11-19 20:22:50 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 20:22:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:50 | D | sum error = [ 81.0246, 85.3021, 89.7775, 94.4384, 99.2958] +24-11-19 20:22:50 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 20:22:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:50 | D | sum error = [ 104.3630, 109.6508, 115.1456, 120.8419, 126.7716] +24-11-19 20:22:50 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 20:22:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:50 | D | sum error = [ 132.9277, 139.3091, 145.9406, 152.8263, 159.9460] +24-11-19 20:22:50 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 20:22:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:50 | D | sum error = [ 167.3263, 174.9750, 182.8796, 191.0600, 199.5070] +24-11-19 20:22:50 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 20:22:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:50 | D | sum error = [ 208.2236, 217.2115, 226.4799, 236.0053, 245.8057] +24-11-19 20:22:50 | D | best error = [ 3.4169, 3.4169, 3.4169, 3.4169, 3.4169] +24-11-19 20:22:50 | D | + error = [3.4169] +24-11-19 20:22:50 | D | - Calibrating model.layers.7.self_attn.o_proj.weight +24-11-19 20:22:50 | D | + w: sint8 +24-11-19 20:22:50 | D | + x: None +24-11-19 20:22:50 | D | + y: None +24-11-19 20:22:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:50 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:50 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:50 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:50 | D | - range ratio = [ 1.0000] +24-11-19 20:22:50 | D | sum error = [ 0.6821] +24-11-19 20:22:50 | D | best error = [ 0.6821] +24-11-19 20:22:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:51 | D | sum error = [ 0.6771, 0.6733, 0.6722, 0.6736, 0.6836] +24-11-19 20:22:51 | D | best error = [ 0.6386, 0.6182, 0.6056, 0.5974, 0.5921] +24-11-19 20:22:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:51 | D | sum error = [ 0.6927, 0.7078, 0.7282, 0.7487, 0.7757] +24-11-19 20:22:51 | D | best error = [ 0.5881, 0.5850, 0.5830, 0.5815, 0.5802] +24-11-19 20:22:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:51 | D | sum error = [ 0.8115, 0.8514, 0.8949, 0.9436, 0.9985] +24-11-19 20:22:51 | D | best error = [ 0.5793, 0.5786, 0.5781, 0.5778, 0.5775] +24-11-19 20:22:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:51 | D | sum error = [ 1.0602, 1.1238, 1.1964, 1.2732, 1.3575] +24-11-19 20:22:51 | D | best error = [ 0.5772, 0.5770, 0.5768, 0.5767, 0.5765] +24-11-19 20:22:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:51 | D | sum error = [ 1.4467, 1.5425, 1.6432, 1.7526, 1.8713] +24-11-19 20:22:51 | D | best error = [ 0.5765, 0.5764, 0.5764, 0.5763, 0.5763] +24-11-19 20:22:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:51 | D | sum error = [ 1.9930, 2.1212, 2.2617, 2.4077, 2.5601] +24-11-19 20:22:51 | D | best error = [ 0.5763, 0.5763, 0.5763, 0.5762, 0.5762] +24-11-19 20:22:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:51 | D | sum error = [ 2.7267, 2.9008, 3.0798, 3.2785, 3.4794] +24-11-19 20:22:51 | D | best error = [ 0.5762, 0.5762, 0.5762, 0.5762, 0.5762] +24-11-19 20:22:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:51 | D | sum error = [ 3.6953, 3.9232, 4.1637, 4.4183, 4.6845] +24-11-19 20:22:51 | D | best error = [ 0.5762, 0.5762, 0.5762, 0.5762, 0.5762] +24-11-19 20:22:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:51 | D | sum error = [ 4.9645, 5.2607, 5.5713, 5.9004, 6.2458] +24-11-19 20:22:51 | D | best error = [ 0.5762, 0.5762, 0.5762, 0.5762, 0.5762] +24-11-19 20:22:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:51 | D | sum error = [ 6.6068, 6.9876, 7.3866, 7.8059, 8.2445] +24-11-19 20:22:51 | D | best error = [ 0.5762, 0.5762, 0.5762, 0.5762, 0.5762] +24-11-19 20:22:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:51 | D | sum error = [ 8.7052, 9.1883, 9.6934, 10.2210, 10.7739] +24-11-19 20:22:51 | D | best error = [ 0.5762, 0.5762, 0.5762, 0.5762, 0.5762] +24-11-19 20:22:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:51 | D | sum error = [ 11.3516, 11.9555, 12.5855, 13.2431, 13.9301] +24-11-19 20:22:51 | D | best error = [ 0.5762, 0.5762, 0.5762, 0.5762, 0.5762] +24-11-19 20:22:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:51 | D | sum error = [ 14.6518, 15.4010, 16.1837, 16.9997, 17.8521] +24-11-19 20:22:51 | D | best error = [ 0.5762, 0.5762, 0.5762, 0.5762, 0.5762] +24-11-19 20:22:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:51 | D | sum error = [ 18.7384, 19.6620, 20.6231, 21.6209, 22.6601] +24-11-19 20:22:51 | D | best error = [ 0.5762, 0.5762, 0.5762, 0.5762, 0.5762] +24-11-19 20:22:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:51 | D | sum error = [ 23.7412, 24.8613, 26.0255, 27.2336, 28.4868] +24-11-19 20:22:51 | D | best error = [ 0.5762, 0.5762, 0.5762, 0.5762, 0.5762] +24-11-19 20:22:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:51 | D | sum error = [ 29.7839, 31.1286, 32.5191, 33.9559, 35.4408] +24-11-19 20:22:51 | D | best error = [ 0.5762, 0.5762, 0.5762, 0.5762, 0.5762] +24-11-19 20:22:51 | D | + error = [0.5762] +24-11-19 20:22:51 | D | - Calibrating model.layers.7.mlp.up_proj.weight +24-11-19 20:22:51 | D | + w: sint8 +24-11-19 20:22:51 | D | + x: None +24-11-19 20:22:51 | D | + y: None +24-11-19 20:22:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:51 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:51 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:51 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:51 | D | - range ratio = [ 1.0000] +24-11-19 20:22:51 | D | sum error = [ 5.1920] +24-11-19 20:22:51 | D | best error = [ 5.1920] +24-11-19 20:22:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:52 | D | sum error = [ 5.1497, 5.1431, 5.1689, 5.2221, 5.3232] +24-11-19 20:22:52 | D | best error = [ 4.8322, 4.6933, 4.6240, 4.5842, 4.5644] +24-11-19 20:22:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:52 | D | sum error = [ 5.4591, 5.6338, 5.8796, 6.1609, 6.4735] +24-11-19 20:22:52 | D | best error = [ 4.5555, 4.5518, 4.5507, 4.5502, 4.5502] +24-11-19 20:22:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:52 | D | sum error = [ 6.8356, 7.2766, 7.7301, 8.2413, 8.8250] +24-11-19 20:22:52 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:22:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:52 | D | sum error = [ 9.4559, 10.1135, 10.8458, 11.6167, 12.4610] +24-11-19 20:22:52 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:22:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:52 | D | sum error = [ 13.3467, 14.2924, 15.3069, 16.3901, 17.5339] +24-11-19 20:22:52 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:22:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:52 | D | sum error = [ 18.7516, 20.0179, 21.3822, 22.8116, 24.3242] +24-11-19 20:22:52 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:22:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:52 | D | sum error = [ 25.9168, 27.5958, 29.3614, 31.2258, 33.1932] +24-11-19 20:22:52 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:22:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:52 | D | sum error = [ 35.2522, 37.4293, 39.7041, 42.1110, 44.6414] +24-11-19 20:22:52 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:22:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:52 | D | sum error = [ 47.2872, 50.0625, 52.9706, 56.0305, 59.2173] +24-11-19 20:22:52 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:22:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:52 | D | sum error = [ 62.5659, 66.0664, 69.7373, 73.5683, 77.5555] +24-11-19 20:22:52 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:22:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:52 | D | sum error = [ 81.7310, 86.0991, 90.6478, 95.3982, 100.3433] +24-11-19 20:22:52 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:22:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:52 | D | sum error = [ 105.5078, 110.8760, 116.4622, 122.2664, 128.3251] +24-11-19 20:22:52 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:22:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:52 | D | sum error = [ 134.5948, 141.1163, 147.8888, 154.9138, 162.1924] +24-11-19 20:22:52 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:22:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:52 | D | sum error = [ 169.7334, 177.5448, 185.6349, 194.0007, 202.6581] +24-11-19 20:22:52 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:22:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:52 | D | sum error = [ 211.5972, 220.8352, 230.3695, 240.2073, 250.3332] +24-11-19 20:22:52 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:22:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:52 | D | sum error = [ 260.7900, 271.5536, 282.6365, 294.0354, 305.7587] +24-11-19 20:22:52 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:22:52 | D | + error = [4.5501] +24-11-19 20:22:52 | D | - Calibrating model.layers.7.mlp.gate_proj.weight +24-11-19 20:22:52 | D | + w: sint8 +24-11-19 20:22:52 | D | + x: None +24-11-19 20:22:52 | D | + y: None +24-11-19 20:22:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:52 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:52 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:53 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:53 | D | - range ratio = [ 1.0000] +24-11-19 20:22:53 | D | sum error = [ 5.9222] +24-11-19 20:22:53 | D | best error = [ 5.9222] +24-11-19 20:22:53 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:53 | D | sum error = [ 5.8662, 5.8521, 5.8828, 5.9469, 6.0568] +24-11-19 20:22:53 | D | best error = [ 5.5034, 5.3449, 5.2635, 5.2174, 5.1946] +24-11-19 20:22:53 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:53 | D | sum error = [ 6.2013, 6.4220, 6.6793, 6.9981, 7.3551] +24-11-19 20:22:53 | D | best error = [ 5.1834, 5.1792, 5.1778, 5.1772, 5.1771] +24-11-19 20:22:53 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:53 | D | sum error = [ 7.7940, 8.2655, 8.8199, 9.3940, 10.0527] +24-11-19 20:22:53 | D | best error = [ 5.1771, 5.1771, 5.1771, 5.1771, 5.1771] +24-11-19 20:22:53 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:53 | D | sum error = [ 10.7765, 11.5587, 12.3878, 13.2941, 14.2464] +24-11-19 20:22:53 | D | best error = [ 5.1771, 5.1771, 5.1771, 5.1771, 5.1771] +24-11-19 20:22:53 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:53 | D | sum error = [ 15.2810, 16.3903, 17.5618, 18.7879, 20.1112] +24-11-19 20:22:53 | D | best error = [ 5.1771, 5.1771, 5.1771, 5.1771, 5.1771] +24-11-19 20:22:53 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:53 | D | sum error = [ 21.5265, 23.0144, 24.6232, 26.3058, 28.0824] +24-11-19 20:22:53 | D | best error = [ 5.1771, 5.1771, 5.1771, 5.1771, 5.1771] +24-11-19 20:22:53 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:53 | D | sum error = [ 29.9974, 32.0228, 34.1271, 36.3974, 38.7790] +24-11-19 20:22:53 | D | best error = [ 5.1771, 5.1771, 5.1771, 5.1771, 5.1771] +24-11-19 20:22:53 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:53 | D | sum error = [ 41.3089, 44.0001, 46.8240, 49.8116, 52.9720] +24-11-19 20:22:53 | D | best error = [ 5.1771, 5.1771, 5.1771, 5.1771, 5.1771] +24-11-19 20:22:53 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:53 | D | sum error = [ 56.3124, 59.8576, 63.5769, 67.5151, 71.6630] +24-11-19 20:22:53 | D | best error = [ 5.1771, 5.1771, 5.1771, 5.1771, 5.1771] +24-11-19 20:22:53 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:53 | D | sum error = [ 76.0435, 80.6699, 85.5239, 90.6638, 96.0772] +24-11-19 20:22:53 | D | best error = [ 5.1771, 5.1771, 5.1771, 5.1771, 5.1771] +24-11-19 20:22:53 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:53 | D | sum error = [ 101.7702, 107.7607, 114.0732, 120.7217, 127.7248] +24-11-19 20:22:53 | D | best error = [ 5.1771, 5.1771, 5.1771, 5.1771, 5.1771] +24-11-19 20:22:53 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:53 | D | sum error = [ 135.0798, 142.7956, 150.9212, 159.4416, 168.3795] +24-11-19 20:22:53 | D | best error = [ 5.1771, 5.1771, 5.1771, 5.1771, 5.1771] +24-11-19 20:22:53 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:53 | D | sum error = [ 177.7611, 187.5708, 197.8634, 208.6282, 219.8599] +24-11-19 20:22:53 | D | best error = [ 5.1771, 5.1771, 5.1771, 5.1771, 5.1771] +24-11-19 20:22:53 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:53 | D | sum error = [ 231.5757, 243.8062, 256.5834, 269.8800, 283.7004] +24-11-19 20:22:53 | D | best error = [ 5.1771, 5.1771, 5.1771, 5.1771, 5.1771] +24-11-19 20:22:53 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:53 | D | sum error = [ 298.0747, 312.9954, 328.4894, 344.5607, 361.2061] +24-11-19 20:22:53 | D | best error = [ 5.1771, 5.1771, 5.1771, 5.1771, 5.1771] +24-11-19 20:22:53 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:53 | D | sum error = [ 378.4355, 396.2508, 414.6628, 433.6622, 453.2245] +24-11-19 20:22:53 | D | best error = [ 5.1771, 5.1771, 5.1771, 5.1771, 5.1771] +24-11-19 20:22:53 | D | + error = [5.1771] +24-11-19 20:22:54 | D | - Calibrating model.layers.7.mlp.down_proj.weight +24-11-19 20:22:54 | D | + w: sint8 +24-11-19 20:22:54 | D | + x: None +24-11-19 20:22:54 | D | + y: None +24-11-19 20:22:54 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:54 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:54 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:54 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:54 | D | - range ratio = [ 1.0000] +24-11-19 20:22:54 | D | sum error = [ 1.1056] +24-11-19 20:22:54 | D | best error = [ 1.1056] +24-11-19 20:22:55 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:55 | D | sum error = [ 1.0948, 1.0876, 1.0832, 1.0788, 1.0800] +24-11-19 20:22:55 | D | best error = [ 1.0685, 1.0492, 1.0366, 1.0263, 1.0187] +24-11-19 20:22:55 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:55 | D | sum error = [ 1.0856, 1.0927, 1.1052, 1.1244, 1.1482] +24-11-19 20:22:55 | D | best error = [ 1.0130, 1.0091, 1.0062, 1.0039, 1.0027] +24-11-19 20:22:55 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:55 | D | sum error = [ 1.1787, 1.2162, 1.2603, 1.3109, 1.3695] +24-11-19 20:22:55 | D | best error = [ 1.0016, 1.0009, 1.0006, 1.0003, 1.0002] +24-11-19 20:22:55 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:55 | D | sum error = [ 1.4399, 1.5148, 1.6007, 1.6961, 1.8010] +24-11-19 20:22:55 | D | best error = [ 1.0001, 1.0001, 1.0000, 1.0000, 1.0000] +24-11-19 20:22:55 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:55 | D | sum error = [ 1.9161, 2.0421, 2.1780, 2.3252, 2.4858] +24-11-19 20:22:55 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 20:22:55 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:55 | D | sum error = [ 2.6563, 2.8411, 3.0384, 3.2494, 3.4752] +24-11-19 20:22:55 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 20:22:55 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:55 | D | sum error = [ 3.7158, 3.9733, 4.2476, 4.5372, 4.8459] +24-11-19 20:22:55 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 20:22:55 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:55 | D | sum error = [ 5.1743, 5.5216, 5.8903, 6.2799, 6.6940] +24-11-19 20:22:55 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 20:22:55 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:55 | D | sum error = [ 7.1312, 7.5931, 8.0814, 8.5969, 9.1419] +24-11-19 20:22:55 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 20:22:55 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:55 | D | sum error = [ 9.7138, 10.3180, 10.9570, 11.6288, 12.3350] +24-11-19 20:22:55 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 20:22:55 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:55 | D | sum error = [ 13.0794, 13.8614, 14.6827, 15.5458, 16.4515] +24-11-19 20:22:55 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 20:22:55 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:55 | D | sum error = [ 17.4022, 18.3980, 19.4414, 20.5339, 21.6786] +24-11-19 20:22:55 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 20:22:55 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:55 | D | sum error = [ 22.8758, 24.1268, 25.4335, 26.7962, 28.2186] +24-11-19 20:22:55 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 20:22:55 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:55 | D | sum error = [ 29.7023, 31.2475, 32.8582, 34.5365, 36.2774] +24-11-19 20:22:55 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 20:22:55 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:55 | D | sum error = [ 38.0892, 39.9717, 41.9269, 43.9536, 46.0552] +24-11-19 20:22:55 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 20:22:55 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:55 | D | sum error = [ 48.2313, 50.4843, 52.8173, 55.2301, 57.7216] +24-11-19 20:22:55 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 20:22:55 | D | + error = [1.0000] +24-11-19 20:22:55 | D | - Quantizing model.layers.7.self_attn.q_proj.weight +24-11-19 20:22:56 | D | - Quantizing model.layers.7.self_attn.k_proj.weight +24-11-19 20:22:57 | D | - Quantizing model.layers.7.self_attn.v_proj.weight +24-11-19 20:23:02 | D | - Quantizing model.layers.7.self_attn.o_proj.weight +24-11-19 20:23:03 | D | - Quantizing model.layers.7.mlp.up_proj.weight +24-11-19 20:23:04 | D | - Quantizing model.layers.7.mlp.gate_proj.weight +24-11-19 20:23:05 | D | - Quantizing model.layers.7.mlp.down_proj.weight +24-11-19 20:23:14 | D | - Quantizing layer model.layers.8 +24-11-19 20:23:14 | D | - Calibrating model.layers.8.self_attn.q_proj.weight +24-11-19 20:23:14 | D | + w: sint8 +24-11-19 20:23:14 | D | + x: None +24-11-19 20:23:14 | D | + y: None +24-11-19 20:23:14 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:23:14 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:14 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:14 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:14 | D | - range ratio = [ 1.0000] +24-11-19 20:23:14 | D | sum error = [ 6.7290] +24-11-19 20:23:14 | D | best error = [ 6.7290] +24-11-19 20:23:28 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:28 | D | sum error = [ 6.6694, 6.6121, 6.7486, 6.6965, 7.1881] +24-11-19 20:23:28 | D | best error = [ 6.6694, 6.6121, 6.6121, 6.6121, 6.6121] +24-11-19 20:23:28 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:28 | D | sum error = [ 7.1970, 7.3485, 7.5109, 8.0269, 8.3751] +24-11-19 20:23:28 | D | best error = [ 6.6121, 6.6121, 6.6121, 6.6121, 6.6121] +24-11-19 20:23:28 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:28 | D | sum error = [ 8.9486, 9.6793, 10.3990, 11.0787, 12.0867] +24-11-19 20:23:28 | D | best error = [ 6.6121, 6.6121, 6.6121, 6.6121, 6.6121] +24-11-19 20:23:28 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:28 | D | sum error = [ 12.8208, 14.2449, 15.1637, 16.4416, 17.6790] +24-11-19 20:23:28 | D | best error = [ 6.6121, 6.6121, 6.6121, 6.6121, 6.6121] +24-11-19 20:23:28 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:28 | D | sum error = [ 19.3666, 20.9146, 22.5507, 24.7022, 26.9332] +24-11-19 20:23:28 | D | best error = [ 6.6121, 6.6121, 6.6121, 6.6121, 6.6121] +24-11-19 20:23:28 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:28 | D | sum error = [ 29.2849, 31.4747, 34.4510, 37.4045, 40.5438] +24-11-19 20:23:28 | D | best error = [ 6.6121, 6.6121, 6.6121, 6.6121, 6.6121] +24-11-19 20:23:28 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:28 | D | sum error = [ 43.9130, 48.0523, 51.8515, 56.0909, 61.0542] +24-11-19 20:23:28 | D | best error = [ 6.6121, 6.6121, 6.6121, 6.6121, 6.6121] +24-11-19 20:23:28 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:28 | D | sum error = [ 65.8169, 71.3780, 76.5856, 83.0612, 89.8784] +24-11-19 20:23:28 | D | best error = [ 6.6121, 6.6121, 6.6121, 6.6121, 6.6121] +24-11-19 20:23:28 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:28 | D | sum error = [ 97.0078, 104.7030, 112.8612, 121.1513, 130.4928] +24-11-19 20:23:28 | D | best error = [ 6.6121, 6.6121, 6.6121, 6.6121, 6.6121] +24-11-19 20:23:28 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:28 | D | sum error = [ 140.6595, 151.8240, 163.0483, 175.7651, 188.9940] +24-11-19 20:23:28 | D | best error = [ 6.6121, 6.6121, 6.6121, 6.6121, 6.6121] +24-11-19 20:23:28 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:28 | D | sum error = [ 203.0858, 218.6495, 234.8468, 251.8331, 270.4230] +24-11-19 20:23:28 | D | best error = [ 6.6121, 6.6121, 6.6121, 6.6121, 6.6121] +24-11-19 20:23:28 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:28 | D | sum error = [ 290.0944, 311.1659, 333.3080, 357.1778, 382.7625] +24-11-19 20:23:28 | D | best error = [ 6.6121, 6.6121, 6.6121, 6.6121, 6.6121] +24-11-19 20:23:28 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:28 | D | sum error = [ 409.6087, 438.4389, 469.2749, 502.2857, 537.1613] +24-11-19 20:23:28 | D | best error = [ 6.6121, 6.6121, 6.6121, 6.6121, 6.6121] +24-11-19 20:23:28 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:28 | D | sum error = [ 574.2786, 614.1668, 656.4665, 701.1768, 748.7295] +24-11-19 20:23:28 | D | best error = [ 6.6121, 6.6121, 6.6121, 6.6121, 6.6121] +24-11-19 20:23:28 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:28 | D | sum error = [ 799.1650, 852.2595, 908.4042, 967.2833, 1028.8370] +24-11-19 20:23:28 | D | best error = [ 6.6121, 6.6121, 6.6121, 6.6121, 6.6121] +24-11-19 20:23:28 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:28 | D | sum error = [ 1092.9783, 1159.3736, 1227.9765, 1298.5785, 1370.7648] +24-11-19 20:23:28 | D | best error = [ 6.6121, 6.6121, 6.6121, 6.6121, 6.6121] +24-11-19 20:23:28 | D | + error = [6.6121] +24-11-19 20:23:28 | D | - Calibrating model.layers.8.self_attn.k_proj.weight +24-11-19 20:23:28 | D | + w: sint8 +24-11-19 20:23:28 | D | + x: None +24-11-19 20:23:28 | D | + y: None +24-11-19 20:23:28 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:23:28 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:28 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:29 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:29 | D | - range ratio = [ 1.0000] +24-11-19 20:23:29 | D | sum error = [ 7.5507] +24-11-19 20:23:29 | D | best error = [ 7.5507] +24-11-19 20:23:42 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:42 | D | sum error = [ 7.1784, 7.3085, 7.1985, 7.2473, 8.1274] +24-11-19 20:23:42 | D | best error = [ 7.1784, 7.1784, 7.1784, 7.1784, 7.1784] +24-11-19 20:23:42 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:42 | D | sum error = [ 7.4384, 7.8881, 8.1249, 9.3753, 9.4049] +24-11-19 20:23:42 | D | best error = [ 7.1784, 7.1784, 7.1784, 7.1784, 7.1784] +24-11-19 20:23:42 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:42 | D | sum error = [ 9.6551, 10.4897, 11.0571, 12.4337, 12.8973] +24-11-19 20:23:42 | D | best error = [ 7.1784, 7.1784, 7.1784, 7.1784, 7.1784] +24-11-19 20:23:42 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:42 | D | sum error = [ 13.8118, 14.7980, 16.3304, 17.3956, 18.7811] +24-11-19 20:23:42 | D | best error = [ 7.1784, 7.1784, 7.1784, 7.1784, 7.1784] +24-11-19 20:23:42 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:42 | D | sum error = [ 20.2764, 21.6171, 23.6175, 25.3237, 27.6940] +24-11-19 20:23:42 | D | best error = [ 7.1784, 7.1784, 7.1784, 7.1784, 7.1784] +24-11-19 20:23:42 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:42 | D | sum error = [ 30.7052, 32.5642, 35.2754, 38.9677, 41.6374] +24-11-19 20:23:42 | D | best error = [ 7.1784, 7.1784, 7.1784, 7.1784, 7.1784] +24-11-19 20:23:42 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:42 | D | sum error = [ 45.2735, 48.7923, 53.4083, 57.3874, 61.8184] +24-11-19 20:23:42 | D | best error = [ 7.1784, 7.1784, 7.1784, 7.1784, 7.1784] +24-11-19 20:23:42 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:42 | D | sum error = [ 66.6682, 71.8259, 76.5415, 82.4042, 88.8945] +24-11-19 20:23:42 | D | best error = [ 7.1784, 7.1784, 7.1784, 7.1784, 7.1784] +24-11-19 20:23:42 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:42 | D | sum error = [ 95.6425, 102.5425, 110.3283, 118.6109, 127.0456] +24-11-19 20:23:42 | D | best error = [ 7.1784, 7.1784, 7.1784, 7.1784, 7.1784] +24-11-19 20:23:42 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:42 | D | sum error = [ 137.6240, 148.0257, 159.0776, 170.7623, 183.7094] +24-11-19 20:23:42 | D | best error = [ 7.1784, 7.1784, 7.1784, 7.1784, 7.1784] +24-11-19 20:23:42 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:42 | D | sum error = [ 197.8094, 213.1470, 230.7643, 247.6034, 266.0832] +24-11-19 20:23:42 | D | best error = [ 7.1784, 7.1784, 7.1784, 7.1784, 7.1784] +24-11-19 20:23:42 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:42 | D | sum error = [ 286.4397, 308.0201, 329.8297, 354.7618, 382.4617] +24-11-19 20:23:42 | D | best error = [ 7.1784, 7.1784, 7.1784, 7.1784, 7.1784] +24-11-19 20:23:42 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:42 | D | sum error = [ 410.7827, 440.9260, 472.3453, 506.3689, 542.5343] +24-11-19 20:23:42 | D | best error = [ 7.1784, 7.1784, 7.1784, 7.1784, 7.1784] +24-11-19 20:23:42 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:42 | D | sum error = [ 580.4253, 621.3432, 665.5498, 710.9972, 759.9976] +24-11-19 20:23:42 | D | best error = [ 7.1784, 7.1784, 7.1784, 7.1784, 7.1784] +24-11-19 20:23:42 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:42 | D | sum error = [ 810.6337, 865.2668, 921.4310, 983.1696, 1045.5810] +24-11-19 20:23:42 | D | best error = [ 7.1784, 7.1784, 7.1784, 7.1784, 7.1784] +24-11-19 20:23:42 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:42 | D | sum error = [ 1111.0371, 1179.5247, 1247.3852, 1319.0906, 1391.4341] +24-11-19 20:23:42 | D | best error = [ 7.1784, 7.1784, 7.1784, 7.1784, 7.1784] +24-11-19 20:23:42 | D | + error = [7.1784] +24-11-19 20:23:42 | D | - Calibrating model.layers.8.self_attn.v_proj.weight +24-11-19 20:23:42 | D | + w: sint8 +24-11-19 20:23:42 | D | + x: None +24-11-19 20:23:42 | D | + y: None +24-11-19 20:23:42 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:42 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:42 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:43 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:43 | D | - range ratio = [ 1.0000] +24-11-19 20:23:43 | D | sum error = [ 3.9345] +24-11-19 20:23:43 | D | best error = [ 3.9345] +24-11-19 20:23:43 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:43 | D | sum error = [ 3.8925, 3.8774, 3.8875, 3.9322, 4.0104] +24-11-19 20:23:43 | D | best error = [ 3.6513, 3.5505, 3.4998, 3.4700, 3.4536] +24-11-19 20:23:43 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:43 | D | sum error = [ 4.1240, 4.2451, 4.4289, 4.6281, 4.8908] +24-11-19 20:23:43 | D | best error = [ 3.4465, 3.4442, 3.4436, 3.4435, 3.4435] +24-11-19 20:23:43 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:43 | D | sum error = [ 5.1536, 5.4629, 5.8164, 6.2127, 6.6282] +24-11-19 20:23:43 | D | best error = [ 3.4435, 3.4435, 3.4435, 3.4435, 3.4435] +24-11-19 20:23:43 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:43 | D | sum error = [ 7.1002, 7.6163, 8.1567, 8.7651, 9.3818] +24-11-19 20:23:43 | D | best error = [ 3.4435, 3.4435, 3.4435, 3.4435, 3.4435] +24-11-19 20:23:43 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:43 | D | sum error = [ 10.0547, 10.7866, 11.5489, 12.3538, 13.2216] +24-11-19 20:23:43 | D | best error = [ 3.4435, 3.4435, 3.4435, 3.4435, 3.4435] +24-11-19 20:23:43 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:43 | D | sum error = [ 14.1498, 15.1210, 16.1430, 17.2317, 18.3876] +24-11-19 20:23:43 | D | best error = [ 3.4435, 3.4435, 3.4435, 3.4435, 3.4435] +24-11-19 20:23:43 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:43 | D | sum error = [ 19.6044, 20.8935, 22.2463, 23.6881, 25.2037] +24-11-19 20:23:43 | D | best error = [ 3.4435, 3.4435, 3.4435, 3.4435, 3.4435] +24-11-19 20:23:43 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:43 | D | sum error = [ 26.7946, 28.4768, 30.2607, 32.1332, 34.0958] +24-11-19 20:23:43 | D | best error = [ 3.4435, 3.4435, 3.4435, 3.4435, 3.4435] +24-11-19 20:23:43 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:43 | D | sum error = [ 36.1607, 38.3394, 40.6260, 43.0291, 45.5561] +24-11-19 20:23:43 | D | best error = [ 3.4435, 3.4435, 3.4435, 3.4435, 3.4435] +24-11-19 20:23:43 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:43 | D | sum error = [ 48.2213, 50.9976, 53.9320, 56.9946, 60.2139] +24-11-19 20:23:43 | D | best error = [ 3.4435, 3.4435, 3.4435, 3.4435, 3.4435] +24-11-19 20:23:43 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:43 | D | sum error = [ 63.5771, 67.1118, 70.7912, 74.6490, 78.6872] +24-11-19 20:23:43 | D | best error = [ 3.4435, 3.4435, 3.4435, 3.4435, 3.4435] +24-11-19 20:23:43 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:43 | D | sum error = [ 82.9057, 87.2940, 91.8894, 96.6992, 101.7262] +24-11-19 20:23:43 | D | best error = [ 3.4435, 3.4435, 3.4435, 3.4435, 3.4435] +24-11-19 20:23:43 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:43 | D | sum error = [ 106.9600, 112.4239, 118.1164, 124.0443, 130.2289] +24-11-19 20:23:43 | D | best error = [ 3.4435, 3.4435, 3.4435, 3.4435, 3.4435] +24-11-19 20:23:43 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:43 | D | sum error = [ 136.6603, 143.3393, 150.2900, 157.5118, 164.9871] +24-11-19 20:23:43 | D | best error = [ 3.4435, 3.4435, 3.4435, 3.4435, 3.4435] +24-11-19 20:23:43 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:43 | D | sum error = [ 172.7431, 180.7699, 189.0815, 197.6752, 206.5526] +24-11-19 20:23:43 | D | best error = [ 3.4435, 3.4435, 3.4435, 3.4435, 3.4435] +24-11-19 20:23:43 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:43 | D | sum error = [ 215.7430, 225.2128, 234.9781, 245.0383, 255.3959] +24-11-19 20:23:43 | D | best error = [ 3.4435, 3.4435, 3.4435, 3.4435, 3.4435] +24-11-19 20:23:43 | D | + error = [3.4435] +24-11-19 20:23:43 | D | - Calibrating model.layers.8.self_attn.o_proj.weight +24-11-19 20:23:43 | D | + w: sint8 +24-11-19 20:23:43 | D | + x: None +24-11-19 20:23:43 | D | + y: None +24-11-19 20:23:43 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:43 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:43 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:43 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:43 | D | - range ratio = [ 1.0000] +24-11-19 20:23:43 | D | sum error = [ 0.8097] +24-11-19 20:23:43 | D | best error = [ 0.8097] +24-11-19 20:23:44 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:44 | D | sum error = [ 0.8001, 0.7996, 0.7972, 0.8014, 0.8064] +24-11-19 20:23:44 | D | best error = [ 0.7586, 0.7360, 0.7214, 0.7120, 0.7054] +24-11-19 20:23:44 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:44 | D | sum error = [ 0.8217, 0.8380, 0.8562, 0.8853, 0.9186] +24-11-19 20:23:44 | D | best error = [ 0.7013, 0.6979, 0.6958, 0.6943, 0.6933] +24-11-19 20:23:44 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:44 | D | sum error = [ 0.9598, 1.0034, 1.0573, 1.1128, 1.1828] +24-11-19 20:23:44 | D | best error = [ 0.6926, 0.6921, 0.6918, 0.6915, 0.6913] +24-11-19 20:23:44 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:44 | D | sum error = [ 1.2530, 1.3328, 1.4175, 1.5080, 1.6083] +24-11-19 20:23:44 | D | best error = [ 0.6912, 0.6910, 0.6910, 0.6909, 0.6909] +24-11-19 20:23:44 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:44 | D | sum error = [ 1.7180, 1.8307, 1.9562, 2.0894, 2.2330] +24-11-19 20:23:44 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 20:23:44 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:44 | D | sum error = [ 2.3796, 2.5406, 2.7092, 2.8880, 3.0775] +24-11-19 20:23:44 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 20:23:44 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:44 | D | sum error = [ 3.2812, 3.4932, 3.7225, 3.9592, 4.2097] +24-11-19 20:23:44 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 20:23:44 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:44 | D | sum error = [ 4.4751, 4.7536, 5.0481, 5.3598, 5.6882] +24-11-19 20:23:44 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 20:23:44 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:44 | D | sum error = [ 6.0304, 6.3920, 6.7735, 7.1750, 7.5952] +24-11-19 20:23:44 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 20:23:44 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:44 | D | sum error = [ 8.0372, 8.5024, 8.9926, 9.5048, 10.0423] +24-11-19 20:23:44 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 20:23:44 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:44 | D | sum error = [ 10.6064, 11.1958, 11.8140, 12.4595, 13.1395] +24-11-19 20:23:44 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 20:23:44 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:44 | D | sum error = [ 13.8470, 14.5863, 15.3615, 16.1683, 17.0106] +24-11-19 20:23:44 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 20:23:44 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:44 | D | sum error = [ 17.8868, 18.8027, 19.7523, 20.7406, 21.7701] +24-11-19 20:23:44 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 20:23:44 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:44 | D | sum error = [ 22.8407, 23.9522, 25.1077, 26.3062, 27.5478] +24-11-19 20:23:44 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 20:23:44 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:44 | D | sum error = [ 28.8354, 30.1691, 31.5530, 32.9850, 34.4648] +24-11-19 20:23:44 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 20:23:44 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:44 | D | sum error = [ 35.9938, 37.5730, 39.2038, 40.8864, 42.6224] +24-11-19 20:23:44 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 20:23:44 | D | + error = [0.6909] +24-11-19 20:23:44 | D | - Calibrating model.layers.8.mlp.up_proj.weight +24-11-19 20:23:44 | D | + w: sint8 +24-11-19 20:23:44 | D | + x: None +24-11-19 20:23:44 | D | + y: None +24-11-19 20:23:44 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:44 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:44 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:44 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:44 | D | - range ratio = [ 1.0000] +24-11-19 20:23:44 | D | sum error = [ 5.3774] +24-11-19 20:23:44 | D | best error = [ 5.3774] +24-11-19 20:23:45 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:45 | D | sum error = [ 5.3320, 5.3349, 5.3543, 5.3945, 5.5053] +24-11-19 20:23:45 | D | best error = [ 5.0131, 4.8725, 4.8010, 4.7574, 4.7360] +24-11-19 20:23:45 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:45 | D | sum error = [ 5.6527, 5.8391, 6.0769, 6.3601, 6.6943] +24-11-19 20:23:45 | D | best error = [ 4.7257, 4.7211, 4.7195, 4.7193, 4.7192] +24-11-19 20:23:45 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:45 | D | sum error = [ 7.0790, 7.5251, 7.9921, 8.5439, 9.1425] +24-11-19 20:23:45 | D | best error = [ 4.7192, 4.7192, 4.7192, 4.7192, 4.7192] +24-11-19 20:23:45 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:45 | D | sum error = [ 9.7789, 10.4757, 11.2245, 12.0129, 12.9016] +24-11-19 20:23:45 | D | best error = [ 4.7192, 4.7192, 4.7192, 4.7192, 4.7192] +24-11-19 20:23:45 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:45 | D | sum error = [ 13.8251, 14.7986, 15.8303, 16.9528, 18.1382] +24-11-19 20:23:45 | D | best error = [ 4.7192, 4.7192, 4.7192, 4.7192, 4.7192] +24-11-19 20:23:45 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:45 | D | sum error = [ 19.3875, 20.7025, 22.1013, 23.5769, 25.1250] +24-11-19 20:23:45 | D | best error = [ 4.7192, 4.7192, 4.7192, 4.7192, 4.7192] +24-11-19 20:23:45 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:45 | D | sum error = [ 26.7781, 28.5054, 30.3336, 32.2628, 34.2886] +24-11-19 20:23:45 | D | best error = [ 4.7192, 4.7192, 4.7192, 4.7192, 4.7192] +24-11-19 20:23:45 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:45 | D | sum error = [ 36.4274, 38.6808, 41.0497, 43.5426, 46.1707] +24-11-19 20:23:45 | D | best error = [ 4.7192, 4.7192, 4.7192, 4.7192, 4.7192] +24-11-19 20:23:45 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:45 | D | sum error = [ 48.9082, 51.7839, 54.8086, 57.9862, 61.3055] +24-11-19 20:23:45 | D | best error = [ 4.7192, 4.7192, 4.7192, 4.7192, 4.7192] +24-11-19 20:23:45 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:45 | D | sum error = [ 64.7940, 68.4413, 72.2607, 76.2756, 80.4812] +24-11-19 20:23:45 | D | best error = [ 4.7192, 4.7192, 4.7192, 4.7192, 4.7192] +24-11-19 20:23:45 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:45 | D | sum error = [ 84.8721, 89.4506, 94.2394, 99.2452, 104.4621] +24-11-19 20:23:45 | D | best error = [ 4.7192, 4.7192, 4.7192, 4.7192, 4.7192] +24-11-19 20:23:45 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:45 | D | sum error = [ 109.9076, 115.5757, 121.4900, 127.6400, 134.0402] +24-11-19 20:23:45 | D | best error = [ 4.7192, 4.7192, 4.7192, 4.7192, 4.7192] +24-11-19 20:23:45 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:45 | D | sum error = [ 140.7116, 147.6462, 154.8534, 162.3430, 170.1167] +24-11-19 20:23:45 | D | best error = [ 4.7192, 4.7192, 4.7192, 4.7192, 4.7192] +24-11-19 20:23:45 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:45 | D | sum error = [ 178.1851, 186.5529, 195.2351, 204.2238, 213.5352] +24-11-19 20:23:45 | D | best error = [ 4.7192, 4.7192, 4.7192, 4.7192, 4.7192] +24-11-19 20:23:45 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:45 | D | sum error = [ 223.1600, 233.1233, 243.4070, 254.0321, 264.9845] +24-11-19 20:23:45 | D | best error = [ 4.7192, 4.7192, 4.7192, 4.7192, 4.7192] +24-11-19 20:23:45 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:45 | D | sum error = [ 276.2905, 287.9334, 299.9319, 312.2750, 324.9855] +24-11-19 20:23:45 | D | best error = [ 4.7192, 4.7192, 4.7192, 4.7192, 4.7192] +24-11-19 20:23:45 | D | + error = [4.7192] +24-11-19 20:23:45 | D | - Calibrating model.layers.8.mlp.gate_proj.weight +24-11-19 20:23:45 | D | + w: sint8 +24-11-19 20:23:45 | D | + x: None +24-11-19 20:23:45 | D | + y: None +24-11-19 20:23:45 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:45 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:46 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:46 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:46 | D | - range ratio = [ 1.0000] +24-11-19 20:23:46 | D | sum error = [ 5.9229] +24-11-19 20:23:46 | D | best error = [ 5.9229] +24-11-19 20:23:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:47 | D | sum error = [ 5.8855, 5.8682, 5.8976, 5.9718, 6.0743] +24-11-19 20:23:47 | D | best error = [ 5.5287, 5.3734, 5.2927, 5.2480, 5.2244] +24-11-19 20:23:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:47 | D | sum error = [ 6.2319, 6.4434, 6.7127, 7.0223, 7.4130] +24-11-19 20:23:47 | D | best error = [ 5.2131, 5.2085, 5.2068, 5.2063, 5.2062] +24-11-19 20:23:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:47 | D | sum error = [ 7.8404, 8.2979, 8.8500, 9.4462, 10.1133] +24-11-19 20:23:47 | D | best error = [ 5.2062, 5.2062, 5.2062, 5.2062, 5.2062] +24-11-19 20:23:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:47 | D | sum error = [ 10.8438, 11.6140, 12.4487, 13.3601, 14.3223] +24-11-19 20:23:47 | D | best error = [ 5.2062, 5.2062, 5.2062, 5.2062, 5.2062] +24-11-19 20:23:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:47 | D | sum error = [ 15.3510, 16.4836, 17.6713, 18.9108, 20.2570] +24-11-19 20:23:47 | D | best error = [ 5.2062, 5.2062, 5.2062, 5.2062, 5.2062] +24-11-19 20:23:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:47 | D | sum error = [ 21.7035, 23.2122, 24.8293, 26.5213, 28.3552] +24-11-19 20:23:47 | D | best error = [ 5.2062, 5.2062, 5.2062, 5.2062, 5.2062] +24-11-19 20:23:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:47 | D | sum error = [ 30.2844, 32.3120, 34.4788, 36.7643, 39.1833] +24-11-19 20:23:47 | D | best error = [ 5.2062, 5.2062, 5.2062, 5.2062, 5.2062] +24-11-19 20:23:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:47 | D | sum error = [ 41.7476, 44.4482, 47.3123, 50.3339, 53.5257] +24-11-19 20:23:47 | D | best error = [ 5.2062, 5.2062, 5.2062, 5.2062, 5.2062] +24-11-19 20:23:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:47 | D | sum error = [ 56.9278, 60.5081, 64.2802, 68.2668, 72.4799] +24-11-19 20:23:47 | D | best error = [ 5.2062, 5.2062, 5.2062, 5.2062, 5.2062] +24-11-19 20:23:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:47 | D | sum error = [ 76.9082, 81.6137, 86.5464, 91.7696, 97.2713] +24-11-19 20:23:47 | D | best error = [ 5.2062, 5.2062, 5.2062, 5.2062, 5.2062] +24-11-19 20:23:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:47 | D | sum error = [ 103.0762, 109.1872, 115.5882, 122.3352, 129.4302] +24-11-19 20:23:47 | D | best error = [ 5.2062, 5.2062, 5.2062, 5.2062, 5.2062] +24-11-19 20:23:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:47 | D | sum error = [ 136.8624, 144.6863, 152.8870, 161.5086, 170.5366] +24-11-19 20:23:47 | D | best error = [ 5.2062, 5.2062, 5.2062, 5.2062, 5.2062] +24-11-19 20:23:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:47 | D | sum error = [ 180.0045, 189.8973, 200.2574, 211.0680, 222.3645] +24-11-19 20:23:47 | D | best error = [ 5.2062, 5.2062, 5.2062, 5.2062, 5.2062] +24-11-19 20:23:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:47 | D | sum error = [ 234.1730, 246.4658, 259.2925, 272.6571, 286.5585] +24-11-19 20:23:47 | D | best error = [ 5.2062, 5.2062, 5.2062, 5.2062, 5.2062] +24-11-19 20:23:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:47 | D | sum error = [ 300.9790, 315.9698, 331.5127, 347.6533, 364.3275] +24-11-19 20:23:47 | D | best error = [ 5.2062, 5.2062, 5.2062, 5.2062, 5.2062] +24-11-19 20:23:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:47 | D | sum error = [ 381.6015, 399.4374, 417.8494, 436.8509, 456.4359] +24-11-19 20:23:47 | D | best error = [ 5.2062, 5.2062, 5.2062, 5.2062, 5.2062] +24-11-19 20:23:47 | D | + error = [5.2062] +24-11-19 20:23:47 | D | - Calibrating model.layers.8.mlp.down_proj.weight +24-11-19 20:23:47 | D | + w: sint8 +24-11-19 20:23:47 | D | + x: None +24-11-19 20:23:47 | D | + y: None +24-11-19 20:23:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:47 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:47 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:47 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:47 | D | - range ratio = [ 1.0000] +24-11-19 20:23:47 | D | sum error = [ 1.2621] +24-11-19 20:23:47 | D | best error = [ 1.2621] +24-11-19 20:23:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:48 | D | sum error = [ 1.2511, 1.2410, 1.2354, 1.2297, 1.2295] +24-11-19 20:23:48 | D | best error = [ 1.2153, 1.1890, 1.1712, 1.1578, 1.1479] +24-11-19 20:23:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:48 | D | sum error = [ 1.2363, 1.2419, 1.2570, 1.2741, 1.3012] +24-11-19 20:23:48 | D | best error = [ 1.1411, 1.1357, 1.1322, 1.1298, 1.1282] +24-11-19 20:23:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:48 | D | sum error = [ 1.3331, 1.3710, 1.4174, 1.4760, 1.5384] +24-11-19 20:23:48 | D | best error = [ 1.1272, 1.1264, 1.1260, 1.1257, 1.1256] +24-11-19 20:23:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:48 | D | sum error = [ 1.6122, 1.6956, 1.7866, 1.8906, 2.0040] +24-11-19 20:23:48 | D | best error = [ 1.1255, 1.1255, 1.1254, 1.1254, 1.1254] +24-11-19 20:23:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:48 | D | sum error = [ 2.1276, 2.2644, 2.4096, 2.5704, 2.7453] +24-11-19 20:23:48 | D | best error = [ 1.1254, 1.1254, 1.1254, 1.1254, 1.1254] +24-11-19 20:23:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:48 | D | sum error = [ 2.9300, 3.1304, 3.3442, 3.5730, 3.8187] +24-11-19 20:23:48 | D | best error = [ 1.1254, 1.1254, 1.1254, 1.1254, 1.1254] +24-11-19 20:23:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:48 | D | sum error = [ 4.0814, 4.3605, 4.6614, 4.9762, 5.3145] +24-11-19 20:23:48 | D | best error = [ 1.1254, 1.1254, 1.1254, 1.1254, 1.1254] +24-11-19 20:23:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:48 | D | sum error = [ 5.6719, 6.0512, 6.4556, 6.8818, 7.3326] +24-11-19 20:23:48 | D | best error = [ 1.1254, 1.1254, 1.1254, 1.1254, 1.1254] +24-11-19 20:23:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:48 | D | sum error = [ 7.8098, 8.3167, 8.8514, 9.4152, 10.0104] +24-11-19 20:23:48 | D | best error = [ 1.1254, 1.1254, 1.1254, 1.1254, 1.1254] +24-11-19 20:23:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:48 | D | sum error = [ 10.6381, 11.3003, 11.9980, 12.7329, 13.5063] +24-11-19 20:23:48 | D | best error = [ 1.1254, 1.1254, 1.1254, 1.1254, 1.1254] +24-11-19 20:23:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:48 | D | sum error = [ 14.3180, 15.1735, 16.0692, 17.0122, 18.0005] +24-11-19 20:23:48 | D | best error = [ 1.1254, 1.1254, 1.1254, 1.1254, 1.1254] +24-11-19 20:23:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:48 | D | sum error = [ 19.0361, 20.1208, 21.2568, 22.4466, 23.6918] +24-11-19 20:23:48 | D | best error = [ 1.1254, 1.1254, 1.1254, 1.1254, 1.1254] +24-11-19 20:23:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:48 | D | sum error = [ 24.9941, 26.3553, 27.7770, 29.2625, 30.8118] +24-11-19 20:23:48 | D | best error = [ 1.1254, 1.1254, 1.1254, 1.1254, 1.1254] +24-11-19 20:23:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:48 | D | sum error = [ 32.4279, 34.1137, 35.8688, 37.7002, 39.5983] +24-11-19 20:23:48 | D | best error = [ 1.1254, 1.1254, 1.1254, 1.1254, 1.1254] +24-11-19 20:23:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:48 | D | sum error = [ 41.5763, 43.6325, 45.7692, 47.9861, 50.2884] +24-11-19 20:23:48 | D | best error = [ 1.1254, 1.1254, 1.1254, 1.1254, 1.1254] +24-11-19 20:23:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:48 | D | sum error = [ 52.6773, 55.1527, 57.7199, 60.3776, 63.1277] +24-11-19 20:23:48 | D | best error = [ 1.1254, 1.1254, 1.1254, 1.1254, 1.1254] +24-11-19 20:23:48 | D | + error = [1.1254] +24-11-19 20:23:48 | D | - Quantizing model.layers.8.self_attn.q_proj.weight +24-11-19 20:23:50 | D | - Quantizing model.layers.8.self_attn.k_proj.weight +24-11-19 20:23:51 | D | - Quantizing model.layers.8.self_attn.v_proj.weight +24-11-19 20:23:55 | D | - Quantizing model.layers.8.self_attn.o_proj.weight +24-11-19 20:23:56 | D | - Quantizing model.layers.8.mlp.up_proj.weight +24-11-19 20:23:57 | D | - Quantizing model.layers.8.mlp.gate_proj.weight +24-11-19 20:23:58 | D | - Quantizing model.layers.8.mlp.down_proj.weight +24-11-19 20:24:06 | D | - Quantizing layer model.layers.9 +24-11-19 20:24:06 | D | - Calibrating model.layers.9.self_attn.q_proj.weight +24-11-19 20:24:06 | D | + w: sint8 +24-11-19 20:24:06 | D | + x: None +24-11-19 20:24:06 | D | + y: None +24-11-19 20:24:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:24:06 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:07 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:07 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:07 | D | - range ratio = [ 1.0000] +24-11-19 20:24:07 | D | sum error = [ 7.4159] +24-11-19 20:24:07 | D | best error = [ 7.4159] +24-11-19 20:24:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:21 | D | sum error = [ 7.5081, 7.4510, 7.4772, 7.6283, 7.6733] +24-11-19 20:24:21 | D | best error = [ 7.4159, 7.4159, 7.4159, 7.4159, 7.4159] +24-11-19 20:24:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:21 | D | sum error = [ 7.9614, 8.1239, 8.3980, 8.7361, 9.5287] +24-11-19 20:24:21 | D | best error = [ 7.4159, 7.4159, 7.4159, 7.4159, 7.4159] +24-11-19 20:24:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:21 | D | sum error = [ 9.9787, 10.4953, 11.1979, 12.0716, 12.9769] +24-11-19 20:24:21 | D | best error = [ 7.4159, 7.4159, 7.4159, 7.4159, 7.4159] +24-11-19 20:24:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:21 | D | sum error = [ 13.8210, 14.9120, 16.2644, 17.5889, 18.9402] +24-11-19 20:24:21 | D | best error = [ 7.4159, 7.4159, 7.4159, 7.4159, 7.4159] +24-11-19 20:24:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:21 | D | sum error = [ 20.6171, 22.0195, 23.9093, 25.9305, 28.3465] +24-11-19 20:24:21 | D | best error = [ 7.4159, 7.4159, 7.4159, 7.4159, 7.4159] +24-11-19 20:24:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:21 | D | sum error = [ 30.4805, 33.0443, 35.7915, 38.5898, 41.6788] +24-11-19 20:24:21 | D | best error = [ 7.4159, 7.4159, 7.4159, 7.4159, 7.4159] +24-11-19 20:24:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:21 | D | sum error = [ 45.1609, 48.4730, 52.5319, 56.6597, 61.4151] +24-11-19 20:24:21 | D | best error = [ 7.4159, 7.4159, 7.4159, 7.4159, 7.4159] +24-11-19 20:24:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:21 | D | sum error = [ 66.3249, 71.2947, 77.0375, 83.0504, 89.8869] +24-11-19 20:24:21 | D | best error = [ 7.4159, 7.4159, 7.4159, 7.4159, 7.4159] +24-11-19 20:24:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:21 | D | sum error = [ 96.9473, 104.5699, 112.5520, 121.5407, 130.7435] +24-11-19 20:24:21 | D | best error = [ 7.4159, 7.4159, 7.4159, 7.4159, 7.4159] +24-11-19 20:24:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:21 | D | sum error = [ 140.8108, 151.5851, 163.3241, 175.7311, 188.9290] +24-11-19 20:24:21 | D | best error = [ 7.4159, 7.4159, 7.4159, 7.4159, 7.4159] +24-11-19 20:24:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:21 | D | sum error = [ 203.0481, 218.3254, 234.5154, 251.6624, 270.0355] +24-11-19 20:24:21 | D | best error = [ 7.4159, 7.4159, 7.4159, 7.4159, 7.4159] +24-11-19 20:24:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:21 | D | sum error = [ 289.8538, 311.1433, 334.0879, 358.5758, 384.9880] +24-11-19 20:24:21 | D | best error = [ 7.4159, 7.4159, 7.4159, 7.4159, 7.4159] +24-11-19 20:24:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:21 | D | sum error = [ 413.3725, 443.6036, 476.3311, 510.8854, 548.4209] +24-11-19 20:24:21 | D | best error = [ 7.4159, 7.4159, 7.4159, 7.4159, 7.4159] +24-11-19 20:24:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:21 | D | sum error = [ 588.6172, 631.4710, 677.4811, 726.6274, 779.1859] +24-11-19 20:24:21 | D | best error = [ 7.4159, 7.4159, 7.4159, 7.4159, 7.4159] +24-11-19 20:24:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:21 | D | sum error = [ 836.1296, 896.1567, 960.4271, 1028.4663, 1100.6249] +24-11-19 20:24:21 | D | best error = [ 7.4159, 7.4159, 7.4159, 7.4159, 7.4159] +24-11-19 20:24:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:21 | D | sum error = [ 1176.3769, 1255.6010, 1337.9937, 1423.1931, 1510.6679] +24-11-19 20:24:21 | D | best error = [ 7.4159, 7.4159, 7.4159, 7.4159, 7.4159] +24-11-19 20:24:21 | D | + error = [7.4159] +24-11-19 20:24:21 | D | - Calibrating model.layers.9.self_attn.k_proj.weight +24-11-19 20:24:21 | D | + w: sint8 +24-11-19 20:24:21 | D | + x: None +24-11-19 20:24:21 | D | + y: None +24-11-19 20:24:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:24:21 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:22 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:22 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:22 | D | - range ratio = [ 1.0000] +24-11-19 20:24:22 | D | sum error = [ 8.1119] +24-11-19 20:24:22 | D | best error = [ 8.1119] +24-11-19 20:24:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:36 | D | sum error = [ 7.7871, 7.6268, 7.9722, 7.6948, 8.1142] +24-11-19 20:24:36 | D | best error = [ 7.7871, 7.6268, 7.6268, 7.6268, 7.6268] +24-11-19 20:24:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:36 | D | sum error = [ 8.3881, 8.6446, 8.9407, 9.5361, 9.9723] +24-11-19 20:24:36 | D | best error = [ 7.6268, 7.6268, 7.6268, 7.6268, 7.6268] +24-11-19 20:24:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:36 | D | sum error = [ 10.8405, 11.3010, 12.4112, 13.3904, 13.8615] +24-11-19 20:24:36 | D | best error = [ 7.6268, 7.6268, 7.6268, 7.6268, 7.6268] +24-11-19 20:24:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:36 | D | sum error = [ 14.7848, 16.1312, 18.0682, 18.9221, 20.5070] +24-11-19 20:24:36 | D | best error = [ 7.6268, 7.6268, 7.6268, 7.6268, 7.6268] +24-11-19 20:24:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:36 | D | sum error = [ 22.3369, 24.4721, 26.3920, 28.6388, 31.5165] +24-11-19 20:24:36 | D | best error = [ 7.6268, 7.6268, 7.6268, 7.6268, 7.6268] +24-11-19 20:24:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:36 | D | sum error = [ 33.7413, 35.8151, 39.0260, 42.4044, 45.5272] +24-11-19 20:24:36 | D | best error = [ 7.6268, 7.6268, 7.6268, 7.6268, 7.6268] +24-11-19 20:24:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:36 | D | sum error = [ 49.0860, 53.4986, 57.2158, 60.8535, 65.8924] +24-11-19 20:24:36 | D | best error = [ 7.6268, 7.6268, 7.6268, 7.6268, 7.6268] +24-11-19 20:24:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:36 | D | sum error = [ 71.5558, 77.0457, 82.8220, 89.1952, 96.1136] +24-11-19 20:24:36 | D | best error = [ 7.6268, 7.6268, 7.6268, 7.6268, 7.6268] +24-11-19 20:24:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:36 | D | sum error = [ 103.8427, 111.9411, 120.5764, 130.1590, 140.0076] +24-11-19 20:24:36 | D | best error = [ 7.6268, 7.6268, 7.6268, 7.6268, 7.6268] +24-11-19 20:24:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:36 | D | sum error = [ 151.1094, 163.0682, 175.1310, 188.8772, 203.0937] +24-11-19 20:24:36 | D | best error = [ 7.6268, 7.6268, 7.6268, 7.6268, 7.6268] +24-11-19 20:24:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:36 | D | sum error = [ 217.2452, 233.1911, 249.8676, 268.1396, 287.5623] +24-11-19 20:24:36 | D | best error = [ 7.6268, 7.6268, 7.6268, 7.6268, 7.6268] +24-11-19 20:24:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:36 | D | sum error = [ 308.5866, 330.5997, 354.6416, 380.1237, 407.4523] +24-11-19 20:24:36 | D | best error = [ 7.6268, 7.6268, 7.6268, 7.6268, 7.6268] +24-11-19 20:24:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:36 | D | sum error = [ 436.4934, 467.9783, 500.8079, 535.8119, 572.3896] +24-11-19 20:24:36 | D | best error = [ 7.6268, 7.6268, 7.6268, 7.6268, 7.6268] +24-11-19 20:24:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:36 | D | sum error = [ 612.9851, 654.7458, 700.5112, 748.2353, 800.3915] +24-11-19 20:24:36 | D | best error = [ 7.6268, 7.6268, 7.6268, 7.6268, 7.6268] +24-11-19 20:24:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:36 | D | sum error = [ 857.0273, 915.0003, 978.8481, 1045.0676, 1115.8488] +24-11-19 20:24:36 | D | best error = [ 7.6268, 7.6268, 7.6268, 7.6268, 7.6268] +24-11-19 20:24:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:36 | D | sum error = [ 1189.0063, 1266.0840, 1345.4698, 1428.9945, 1514.3432] +24-11-19 20:24:36 | D | best error = [ 7.6268, 7.6268, 7.6268, 7.6268, 7.6268] +24-11-19 20:24:36 | D | + error = [7.6268] +24-11-19 20:24:36 | D | - Calibrating model.layers.9.self_attn.v_proj.weight +24-11-19 20:24:36 | D | + w: sint8 +24-11-19 20:24:36 | D | + x: None +24-11-19 20:24:36 | D | + y: None +24-11-19 20:24:36 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:36 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:36 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:36 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:36 | D | - range ratio = [ 1.0000] +24-11-19 20:24:36 | D | sum error = [ 4.1007] +24-11-19 20:24:36 | D | best error = [ 4.1007] +24-11-19 20:24:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:37 | D | sum error = [ 4.0542, 4.0666, 4.0654, 4.1176, 4.1878] +24-11-19 20:24:37 | D | best error = [ 3.8249, 3.7302, 3.6781, 3.6503, 3.6344] +24-11-19 20:24:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:37 | D | sum error = [ 4.2954, 4.4416, 4.6285, 4.8513, 5.1073] +24-11-19 20:24:37 | D | best error = [ 3.6276, 3.6243, 3.6229, 3.6226, 3.6226] +24-11-19 20:24:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:37 | D | sum error = [ 5.3817, 5.7389, 6.1031, 6.5145, 6.9541] +24-11-19 20:24:37 | D | best error = [ 3.6226, 3.6226, 3.6226, 3.6226, 3.6226] +24-11-19 20:24:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:37 | D | sum error = [ 7.4461, 7.9868, 8.5426, 9.1586, 9.8104] +24-11-19 20:24:37 | D | best error = [ 3.6226, 3.6226, 3.6226, 3.6226, 3.6226] +24-11-19 20:24:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:37 | D | sum error = [ 10.5237, 11.2661, 12.0607, 12.8949, 13.7977] +24-11-19 20:24:37 | D | best error = [ 3.6226, 3.6226, 3.6226, 3.6226, 3.6226] +24-11-19 20:24:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:37 | D | sum error = [ 14.7600, 15.7642, 16.8401, 17.9782, 19.1675] +24-11-19 20:24:37 | D | best error = [ 3.6226, 3.6226, 3.6226, 3.6226, 3.6226] +24-11-19 20:24:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:37 | D | sum error = [ 20.4467, 21.7905, 23.2134, 24.6883, 26.2662] +24-11-19 20:24:37 | D | best error = [ 3.6226, 3.6226, 3.6226, 3.6226, 3.6226] +24-11-19 20:24:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:37 | D | sum error = [ 27.9117, 29.6725, 31.5098, 33.4356, 35.4693] +24-11-19 20:24:37 | D | best error = [ 3.6226, 3.6226, 3.6226, 3.6226, 3.6226] +24-11-19 20:24:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:37 | D | sum error = [ 37.6121, 39.8583, 42.2340, 44.7193, 47.3276] +24-11-19 20:24:37 | D | best error = [ 3.6226, 3.6226, 3.6226, 3.6226, 3.6226] +24-11-19 20:24:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:37 | D | sum error = [ 50.0815, 52.9639, 55.9965, 59.1857, 62.5132] +24-11-19 20:24:37 | D | best error = [ 3.6226, 3.6226, 3.6226, 3.6226, 3.6226] +24-11-19 20:24:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:37 | D | sum error = [ 66.0167, 69.6751, 73.5067, 77.5304, 81.7247] +24-11-19 20:24:37 | D | best error = [ 3.6226, 3.6226, 3.6226, 3.6226, 3.6226] +24-11-19 20:24:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:37 | D | sum error = [ 86.0995, 90.6752, 95.4540, 100.4580, 105.6763] +24-11-19 20:24:37 | D | best error = [ 3.6226, 3.6226, 3.6226, 3.6226, 3.6226] +24-11-19 20:24:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:37 | D | sum error = [ 111.1112, 116.7688, 122.6488, 128.7624, 135.1359] +24-11-19 20:24:37 | D | best error = [ 3.6226, 3.6226, 3.6226, 3.6226, 3.6226] +24-11-19 20:24:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:37 | D | sum error = [ 141.7573, 148.6390, 155.7775, 163.1995, 170.8681] +24-11-19 20:24:37 | D | best error = [ 3.6226, 3.6226, 3.6226, 3.6226, 3.6226] +24-11-19 20:24:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:37 | D | sum error = [ 178.8278, 187.0741, 195.6001, 204.4253, 213.5486] +24-11-19 20:24:37 | D | best error = [ 3.6226, 3.6226, 3.6226, 3.6226, 3.6226] +24-11-19 20:24:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:37 | D | sum error = [ 222.9692, 232.6842, 242.7009, 253.0164, 263.6443] +24-11-19 20:24:37 | D | best error = [ 3.6226, 3.6226, 3.6226, 3.6226, 3.6226] +24-11-19 20:24:37 | D | + error = [3.6226] +24-11-19 20:24:37 | D | - Calibrating model.layers.9.self_attn.o_proj.weight +24-11-19 20:24:37 | D | + w: sint8 +24-11-19 20:24:37 | D | + x: None +24-11-19 20:24:37 | D | + y: None +24-11-19 20:24:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:37 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:37 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:37 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:37 | D | - range ratio = [ 1.0000] +24-11-19 20:24:37 | D | sum error = [ 0.9778] +24-11-19 20:24:37 | D | best error = [ 0.9778] +24-11-19 20:24:38 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:38 | D | sum error = [ 0.9670, 0.9612, 0.9570, 0.9631, 0.9681] +24-11-19 20:24:38 | D | best error = [ 0.9212, 0.8940, 0.8771, 0.8659, 0.8584] +24-11-19 20:24:38 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:38 | D | sum error = [ 0.9801, 0.9953, 1.0203, 1.0480, 1.0821] +24-11-19 20:24:38 | D | best error = [ 0.8529, 0.8488, 0.8461, 0.8439, 0.8423] +24-11-19 20:24:38 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:38 | D | sum error = [ 1.1220, 1.1697, 1.2280, 1.2909, 1.3590] +24-11-19 20:24:38 | D | best error = [ 0.8409, 0.8399, 0.8391, 0.8382, 0.8376] +24-11-19 20:24:38 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:38 | D | sum error = [ 1.4400, 1.5252, 1.6177, 1.7221, 1.8315] +24-11-19 20:24:38 | D | best error = [ 0.8372, 0.8369, 0.8366, 0.8365, 0.8364] +24-11-19 20:24:38 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:38 | D | sum error = [ 1.9514, 2.0797, 2.2218, 2.3633, 2.5202] +24-11-19 20:24:38 | D | best error = [ 0.8363, 0.8362, 0.8362, 0.8362, 0.8361] +24-11-19 20:24:38 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:38 | D | sum error = [ 2.6875, 2.8633, 3.0546, 3.2523, 3.4663] +24-11-19 20:24:38 | D | best error = [ 0.8361, 0.8361, 0.8361, 0.8361, 0.8361] +24-11-19 20:24:38 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:38 | D | sum error = [ 3.6875, 3.9283, 4.1807, 4.4494, 4.7309] +24-11-19 20:24:38 | D | best error = [ 0.8361, 0.8361, 0.8361, 0.8361, 0.8361] +24-11-19 20:24:38 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:38 | D | sum error = [ 5.0261, 5.3408, 5.6729, 6.0204, 6.3878] +24-11-19 20:24:38 | D | best error = [ 0.8361, 0.8361, 0.8361, 0.8361, 0.8361] +24-11-19 20:24:38 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:38 | D | sum error = [ 6.7756, 7.1811, 7.6084, 8.0598, 8.5290] +24-11-19 20:24:38 | D | best error = [ 0.8361, 0.8361, 0.8361, 0.8361, 0.8361] +24-11-19 20:24:38 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:38 | D | sum error = [ 9.0266, 9.5445, 10.0899, 10.6594, 11.2593] +24-11-19 20:24:38 | D | best error = [ 0.8361, 0.8361, 0.8361, 0.8361, 0.8361] +24-11-19 20:24:38 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:38 | D | sum error = [ 11.8894, 12.5446, 13.2351, 13.9537, 14.7081] +24-11-19 20:24:38 | D | best error = [ 0.8361, 0.8361, 0.8361, 0.8361, 0.8361] +24-11-19 20:24:38 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:38 | D | sum error = [ 15.4964, 16.3218, 17.1832, 18.0836, 19.0219] +24-11-19 20:24:38 | D | best error = [ 0.8361, 0.8361, 0.8361, 0.8361, 0.8361] +24-11-19 20:24:38 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:38 | D | sum error = [ 20.0027, 21.0238, 22.0881, 23.2007, 24.3589] +24-11-19 20:24:38 | D | best error = [ 0.8361, 0.8361, 0.8361, 0.8361, 0.8361] +24-11-19 20:24:38 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:38 | D | sum error = [ 25.5638, 26.8160, 28.1188, 29.4687, 30.8707] +24-11-19 20:24:38 | D | best error = [ 0.8361, 0.8361, 0.8361, 0.8361, 0.8361] +24-11-19 20:24:38 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:38 | D | sum error = [ 32.3271, 33.8385, 35.4061, 37.0303, 38.7150] +24-11-19 20:24:38 | D | best error = [ 0.8361, 0.8361, 0.8361, 0.8361, 0.8361] +24-11-19 20:24:38 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:38 | D | sum error = [ 40.4601, 42.2664, 44.1343, 46.0668, 48.0631] +24-11-19 20:24:38 | D | best error = [ 0.8361, 0.8361, 0.8361, 0.8361, 0.8361] +24-11-19 20:24:38 | D | + error = [0.8361] +24-11-19 20:24:38 | D | - Calibrating model.layers.9.mlp.up_proj.weight +24-11-19 20:24:38 | D | + w: sint8 +24-11-19 20:24:38 | D | + x: None +24-11-19 20:24:38 | D | + y: None +24-11-19 20:24:38 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:38 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:38 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:38 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:38 | D | - range ratio = [ 1.0000] +24-11-19 20:24:38 | D | sum error = [ 5.5463] +24-11-19 20:24:38 | D | best error = [ 5.5463] +24-11-19 20:24:39 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:39 | D | sum error = [ 5.4913, 5.4788, 5.5002, 5.5603, 5.6675] +24-11-19 20:24:39 | D | best error = [ 5.1786, 5.0372, 4.9621, 4.9212, 4.8999] +24-11-19 20:24:39 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:39 | D | sum error = [ 5.8179, 5.9875, 6.2358, 6.5251, 6.8829] +24-11-19 20:24:39 | D | best error = [ 4.8912, 4.8865, 4.8851, 4.8846, 4.8846] +24-11-19 20:24:39 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:39 | D | sum error = [ 7.2776, 7.7257, 8.2079, 8.7731, 9.3780] +24-11-19 20:24:39 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:39 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:39 | D | sum error = [ 10.0322, 10.7636, 11.5314, 12.3481, 13.2424] +24-11-19 20:24:39 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:39 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:39 | D | sum error = [ 14.2061, 15.2149, 16.2720, 17.4198, 18.6322] +24-11-19 20:24:39 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:39 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:39 | D | sum error = [ 19.9299, 21.2893, 22.7331, 24.2652, 25.8743] +24-11-19 20:24:39 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:39 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:39 | D | sum error = [ 27.5724, 29.3726, 31.2682, 33.2748, 35.3925] +24-11-19 20:24:39 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:39 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:39 | D | sum error = [ 37.6115, 39.9465, 42.4061, 45.0009, 47.7313] +24-11-19 20:24:39 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:39 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:39 | D | sum error = [ 50.5832, 53.5899, 56.7467, 60.0731, 63.5518] +24-11-19 20:24:39 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:39 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:39 | D | sum error = [ 67.2059, 71.0292, 75.0369, 79.2564, 83.6598] +24-11-19 20:24:39 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:39 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:39 | D | sum error = [ 88.2528, 93.0748, 98.1198, 103.3931, 108.8805] +24-11-19 20:24:39 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:39 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:39 | D | sum error = [ 114.6120, 120.5861, 126.8184, 133.3100, 140.0798] +24-11-19 20:24:39 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:39 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:39 | D | sum error = [ 147.1237, 154.4503, 162.0537, 169.9636, 178.1727] +24-11-19 20:24:39 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:39 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:39 | D | sum error = [ 186.6864, 195.5179, 204.6842, 214.1815, 224.0064] +24-11-19 20:24:39 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:39 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:39 | D | sum error = [ 234.1750, 244.6959, 255.5686, 266.8044, 278.3887] +24-11-19 20:24:39 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:39 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:39 | D | sum error = [ 290.3608, 302.6939, 315.3999, 328.4790, 341.9427] +24-11-19 20:24:39 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:39 | D | + error = [4.8846] +24-11-19 20:24:39 | D | - Calibrating model.layers.9.mlp.gate_proj.weight +24-11-19 20:24:39 | D | + w: sint8 +24-11-19 20:24:39 | D | + x: None +24-11-19 20:24:39 | D | + y: None +24-11-19 20:24:39 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:39 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:39 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:40 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:40 | D | - range ratio = [ 1.0000] +24-11-19 20:24:40 | D | sum error = [ 5.9940] +24-11-19 20:24:40 | D | best error = [ 5.9940] +24-11-19 20:24:40 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:40 | D | sum error = [ 5.9602, 5.9394, 5.9733, 6.0396, 6.1471] +24-11-19 20:24:40 | D | best error = [ 5.6099, 5.4621, 5.3851, 5.3410, 5.3187] +24-11-19 20:24:40 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:40 | D | sum error = [ 6.3049, 6.5093, 6.7855, 7.1300, 7.5131] +24-11-19 20:24:40 | D | best error = [ 5.3083, 5.3038, 5.3021, 5.3019, 5.3018] +24-11-19 20:24:40 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:40 | D | sum error = [ 7.9473, 8.4340, 8.9932, 9.6361, 10.3029] +24-11-19 20:24:40 | D | best error = [ 5.3018, 5.3018, 5.3018, 5.3018, 5.3018] +24-11-19 20:24:40 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:40 | D | sum error = [ 11.0486, 11.8557, 12.7104, 13.6572, 14.6417] +24-11-19 20:24:40 | D | best error = [ 5.3018, 5.3018, 5.3018, 5.3018, 5.3018] +24-11-19 20:24:40 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:40 | D | sum error = [ 15.7259, 16.8590, 18.0785, 19.3742, 20.7551] +24-11-19 20:24:40 | D | best error = [ 5.3018, 5.3018, 5.3018, 5.3018, 5.3018] +24-11-19 20:24:40 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:40 | D | sum error = [ 22.2078, 23.7591, 25.4186, 27.1550, 29.0129] +24-11-19 20:24:40 | D | best error = [ 5.3018, 5.3018, 5.3018, 5.3018, 5.3018] +24-11-19 20:24:40 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:40 | D | sum error = [ 30.9587, 33.0419, 35.2527, 37.5898, 40.0654] +24-11-19 20:24:40 | D | best error = [ 5.3018, 5.3018, 5.3018, 5.3018, 5.3018] +24-11-19 20:24:40 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:40 | D | sum error = [ 42.6790, 45.4516, 48.3811, 51.4693, 54.7467] +24-11-19 20:24:40 | D | best error = [ 5.3018, 5.3018, 5.3018, 5.3018, 5.3018] +24-11-19 20:24:40 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:40 | D | sum error = [ 58.2122, 61.8763, 65.7371, 69.8108, 74.1451] +24-11-19 20:24:40 | D | best error = [ 5.3018, 5.3018, 5.3018, 5.3018, 5.3018] +24-11-19 20:24:40 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:40 | D | sum error = [ 78.6873, 83.4761, 88.5458, 93.8823, 99.5046] +24-11-19 20:24:40 | D | best error = [ 5.3018, 5.3018, 5.3018, 5.3018, 5.3018] +24-11-19 20:24:40 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:40 | D | sum error = [ 105.4550, 111.7058, 118.2826, 125.2032, 132.5068] +24-11-19 20:24:40 | D | best error = [ 5.3018, 5.3018, 5.3018, 5.3018, 5.3018] +24-11-19 20:24:40 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:40 | D | sum error = [ 140.1703, 148.2123, 156.6673, 165.5240, 174.8020] +24-11-19 20:24:40 | D | best error = [ 5.3018, 5.3018, 5.3018, 5.3018, 5.3018] +24-11-19 20:24:40 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:40 | D | sum error = [ 184.5290, 194.7047, 205.3375, 216.4481, 228.0741] +24-11-19 20:24:40 | D | best error = [ 5.3018, 5.3018, 5.3018, 5.3018, 5.3018] +24-11-19 20:24:40 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:40 | D | sum error = [ 240.2189, 252.8938, 266.0994, 279.8409, 294.1321] +24-11-19 20:24:40 | D | best error = [ 5.3018, 5.3018, 5.3018, 5.3018, 5.3018] +24-11-19 20:24:40 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:40 | D | sum error = [ 308.9757, 324.4230, 340.4516, 357.0589, 374.2554] +24-11-19 20:24:40 | D | best error = [ 5.3018, 5.3018, 5.3018, 5.3018, 5.3018] +24-11-19 20:24:40 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:40 | D | sum error = [ 392.0628, 410.4849, 429.5075, 449.1264, 469.3302] +24-11-19 20:24:40 | D | best error = [ 5.3018, 5.3018, 5.3018, 5.3018, 5.3018] +24-11-19 20:24:40 | D | + error = [5.3018] +24-11-19 20:24:41 | D | - Calibrating model.layers.9.mlp.down_proj.weight +24-11-19 20:24:41 | D | + w: sint8 +24-11-19 20:24:41 | D | + x: None +24-11-19 20:24:41 | D | + y: None +24-11-19 20:24:41 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:41 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:41 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:41 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:41 | D | - range ratio = [ 1.0000] +24-11-19 20:24:41 | D | sum error = [ 1.3281] +24-11-19 20:24:41 | D | best error = [ 1.3281] +24-11-19 20:24:42 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:42 | D | sum error = [ 1.3162, 1.3049, 1.3010, 1.2971, 1.2975] +24-11-19 20:24:42 | D | best error = [ 1.2829, 1.2590, 1.2437, 1.2312, 1.2225] +24-11-19 20:24:42 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:42 | D | sum error = [ 1.3006, 1.3130, 1.3287, 1.3526, 1.3819] +24-11-19 20:24:42 | D | best error = [ 1.2159, 1.2115, 1.2086, 1.2063, 1.2050] +24-11-19 20:24:42 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:42 | D | sum error = [ 1.4181, 1.4627, 1.5168, 1.5790, 1.6507] +24-11-19 20:24:42 | D | best error = [ 1.2041, 1.2036, 1.2033, 1.2032, 1.2030] +24-11-19 20:24:42 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:42 | D | sum error = [ 1.7325, 1.8254, 1.9297, 2.0460, 2.1717] +24-11-19 20:24:42 | D | best error = [ 1.2030, 1.2029, 1.2029, 1.2029, 1.2029] +24-11-19 20:24:42 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:42 | D | sum error = [ 2.3107, 2.4588, 2.6223, 2.7965, 2.9872] +24-11-19 20:24:42 | D | best error = [ 1.2029, 1.2029, 1.2029, 1.2029, 1.2029] +24-11-19 20:24:42 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:42 | D | sum error = [ 3.1920, 3.4114, 3.6474, 3.8978, 4.1641] +24-11-19 20:24:42 | D | best error = [ 1.2029, 1.2029, 1.2029, 1.2029, 1.2029] +24-11-19 20:24:42 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:42 | D | sum error = [ 4.4488, 4.7550, 5.0772, 5.4226, 5.7887] +24-11-19 20:24:42 | D | best error = [ 1.2029, 1.2029, 1.2029, 1.2029, 1.2029] +24-11-19 20:24:42 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:42 | D | sum error = [ 6.1747, 6.5873, 7.0236, 7.4834, 7.9702] +24-11-19 20:24:42 | D | best error = [ 1.2029, 1.2029, 1.2029, 1.2029, 1.2029] +24-11-19 20:24:42 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:42 | D | sum error = [ 8.4896, 9.0352, 9.6110, 10.2198, 10.8627] +24-11-19 20:24:42 | D | best error = [ 1.2029, 1.2029, 1.2029, 1.2029, 1.2029] +24-11-19 20:24:42 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:42 | D | sum error = [ 11.5395, 12.2543, 13.0069, 13.7981, 14.6318] +24-11-19 20:24:42 | D | best error = [ 1.2029, 1.2029, 1.2029, 1.2029, 1.2029] +24-11-19 20:24:42 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:42 | D | sum error = [ 15.5064, 16.4278, 17.3932, 18.4103, 19.4751] +24-11-19 20:24:42 | D | best error = [ 1.2029, 1.2029, 1.2029, 1.2029, 1.2029] +24-11-19 20:24:42 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:42 | D | sum error = [ 20.5933, 21.7664, 22.9944, 24.2815, 25.6301] +24-11-19 20:24:42 | D | best error = [ 1.2029, 1.2029, 1.2029, 1.2029, 1.2029] +24-11-19 20:24:42 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:42 | D | sum error = [ 27.0401, 28.5149, 30.0539, 31.6602, 33.3369] +24-11-19 20:24:42 | D | best error = [ 1.2029, 1.2029, 1.2029, 1.2029, 1.2029] +24-11-19 20:24:42 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:42 | D | sum error = [ 35.0838, 36.9031, 38.7982, 40.7733, 42.8193] +24-11-19 20:24:42 | D | best error = [ 1.2029, 1.2029, 1.2029, 1.2029, 1.2029] +24-11-19 20:24:42 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:42 | D | sum error = [ 44.9495, 47.1617, 49.4570, 51.8405, 54.3105] +24-11-19 20:24:42 | D | best error = [ 1.2029, 1.2029, 1.2029, 1.2029, 1.2029] +24-11-19 20:24:42 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:42 | D | sum error = [ 56.8681, 59.5135, 62.2508, 65.0800, 68.0047] +24-11-19 20:24:42 | D | best error = [ 1.2029, 1.2029, 1.2029, 1.2029, 1.2029] +24-11-19 20:24:42 | D | + error = [1.2029] +24-11-19 20:24:42 | D | - Quantizing model.layers.9.self_attn.q_proj.weight +24-11-19 20:24:46 | D | - Quantizing model.layers.9.self_attn.k_proj.weight +24-11-19 20:24:47 | D | - Quantizing model.layers.9.self_attn.v_proj.weight +24-11-19 20:24:50 | D | - Quantizing model.layers.9.self_attn.o_proj.weight +24-11-19 20:24:51 | D | - Quantizing model.layers.9.mlp.up_proj.weight +24-11-19 20:24:52 | D | - Quantizing model.layers.9.mlp.gate_proj.weight +24-11-19 20:24:53 | D | - Quantizing model.layers.9.mlp.down_proj.weight +24-11-19 20:25:01 | D | - Quantizing layer model.layers.10 +24-11-19 20:25:01 | D | - Calibrating model.layers.10.self_attn.q_proj.weight +24-11-19 20:25:01 | D | + w: sint8 +24-11-19 20:25:01 | D | + x: None +24-11-19 20:25:01 | D | + y: None +24-11-19 20:25:01 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:25:01 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:01 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:02 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:02 | D | - range ratio = [ 1.0000] +24-11-19 20:25:02 | D | sum error = [ 8.6293] +24-11-19 20:25:02 | D | best error = [ 8.6293] +24-11-19 20:25:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:15 | D | sum error = [ 8.5127, 8.5601, 8.6643, 8.6010, 8.8178] +24-11-19 20:25:15 | D | best error = [ 8.5127, 8.5127, 8.5127, 8.5127, 8.5127] +24-11-19 20:25:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:15 | D | sum error = [ 9.1151, 9.3935, 9.8473, 10.2675, 11.0919] +24-11-19 20:25:15 | D | best error = [ 8.5127, 8.5127, 8.5127, 8.5127, 8.5127] +24-11-19 20:25:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:15 | D | sum error = [ 11.4266, 12.6290, 13.1257, 14.2354, 15.2435] +24-11-19 20:25:15 | D | best error = [ 8.5127, 8.5127, 8.5127, 8.5127, 8.5127] +24-11-19 20:25:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:15 | D | sum error = [ 16.4650, 17.7233, 19.1718, 20.5266, 22.3366] +24-11-19 20:25:15 | D | best error = [ 8.5127, 8.5127, 8.5127, 8.5127, 8.5127] +24-11-19 20:25:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:15 | D | sum error = [ 24.2274, 26.1331, 28.2506, 30.6100, 33.2445] +24-11-19 20:25:15 | D | best error = [ 8.5127, 8.5127, 8.5127, 8.5127, 8.5127] +24-11-19 20:25:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:15 | D | sum error = [ 35.4044, 38.4730, 41.7705, 44.7474, 48.2944] +24-11-19 20:25:15 | D | best error = [ 8.5127, 8.5127, 8.5127, 8.5127, 8.5127] +24-11-19 20:25:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:15 | D | sum error = [ 52.1129, 56.0225, 60.6409, 65.4765, 70.7395] +24-11-19 20:25:15 | D | best error = [ 8.5127, 8.5127, 8.5127, 8.5127, 8.5127] +24-11-19 20:25:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:15 | D | sum error = [ 75.8082, 81.9138, 88.2663, 95.0031, 101.8945] +24-11-19 20:25:15 | D | best error = [ 8.5127, 8.5127, 8.5127, 8.5127, 8.5127] +24-11-19 20:25:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:15 | D | sum error = [ 109.9823, 118.0871, 127.0046, 136.5322, 146.6377] +24-11-19 20:25:15 | D | best error = [ 8.5127, 8.5127, 8.5127, 8.5127, 8.5127] +24-11-19 20:25:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:15 | D | sum error = [ 157.7273, 169.2495, 181.8746, 195.1795, 209.5954] +24-11-19 20:25:15 | D | best error = [ 8.5127, 8.5127, 8.5127, 8.5127, 8.5127] +24-11-19 20:25:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:15 | D | sum error = [ 225.0360, 241.3981, 258.6942, 277.4248, 297.3597] +24-11-19 20:25:15 | D | best error = [ 8.5127, 8.5127, 8.5127, 8.5127, 8.5127] +24-11-19 20:25:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:15 | D | sum error = [ 318.8146, 341.5299, 365.9186, 391.6507, 419.0737] +24-11-19 20:25:15 | D | best error = [ 8.5127, 8.5127, 8.5127, 8.5127, 8.5127] +24-11-19 20:25:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:15 | D | sum error = [ 448.5148, 479.8772, 513.5654, 549.2158, 586.9666] +24-11-19 20:25:15 | D | best error = [ 8.5127, 8.5127, 8.5127, 8.5127, 8.5127] +24-11-19 20:25:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:15 | D | sum error = [ 627.1144, 669.8544, 714.6720, 762.2954, 812.2981] +24-11-19 20:25:15 | D | best error = [ 8.5127, 8.5127, 8.5127, 8.5127, 8.5127] +24-11-19 20:25:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:15 | D | sum error = [ 864.9144, 920.0343, 977.9758, 1038.1624, 1100.9440] +24-11-19 20:25:15 | D | best error = [ 8.5127, 8.5127, 8.5127, 8.5127, 8.5127] +24-11-19 20:25:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:15 | D | sum error = [ 1165.8523, 1232.5494, 1301.0441, 1371.0475, 1442.0442] +24-11-19 20:25:15 | D | best error = [ 8.5127, 8.5127, 8.5127, 8.5127, 8.5127] +24-11-19 20:25:15 | D | + error = [8.5127] +24-11-19 20:25:16 | D | - Calibrating model.layers.10.self_attn.k_proj.weight +24-11-19 20:25:16 | D | + w: sint8 +24-11-19 20:25:16 | D | + x: None +24-11-19 20:25:16 | D | + y: None +24-11-19 20:25:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:25:16 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:16 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:16 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:16 | D | - range ratio = [ 1.0000] +24-11-19 20:25:16 | D | sum error = [ 8.5675] +24-11-19 20:25:16 | D | best error = [ 8.5675] +24-11-19 20:25:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:29 | D | sum error = [ 8.8212, 8.9411, 9.1627, 9.3738, 9.7465] +24-11-19 20:25:29 | D | best error = [ 8.5675, 8.5675, 8.5675, 8.5675, 8.5675] +24-11-19 20:25:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:29 | D | sum error = [ 9.3499, 10.0914, 9.9712, 10.7336, 10.9623] +24-11-19 20:25:29 | D | best error = [ 8.5675, 8.5675, 8.5675, 8.5675, 8.5675] +24-11-19 20:25:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:29 | D | sum error = [ 12.0231, 12.4849, 13.7306, 15.0379, 15.5224] +24-11-19 20:25:29 | D | best error = [ 8.5675, 8.5675, 8.5675, 8.5675, 8.5675] +24-11-19 20:25:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:29 | D | sum error = [ 16.9450, 18.3110, 19.5788, 21.1268, 23.1915] +24-11-19 20:25:29 | D | best error = [ 8.5675, 8.5675, 8.5675, 8.5675, 8.5675] +24-11-19 20:25:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:29 | D | sum error = [ 24.8198, 27.3644, 29.2801, 31.4826, 34.8726] +24-11-19 20:25:29 | D | best error = [ 8.5675, 8.5675, 8.5675, 8.5675, 8.5675] +24-11-19 20:25:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:29 | D | sum error = [ 37.9467, 40.2849, 44.2452, 48.0232, 52.6388] +24-11-19 20:25:29 | D | best error = [ 8.5675, 8.5675, 8.5675, 8.5675, 8.5675] +24-11-19 20:25:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:29 | D | sum error = [ 57.1386, 61.9694, 67.6700, 72.9017, 80.0302] +24-11-19 20:25:29 | D | best error = [ 8.5675, 8.5675, 8.5675, 8.5675, 8.5675] +24-11-19 20:25:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:29 | D | sum error = [ 85.9354, 93.8574, 101.5206, 110.4030, 119.1288] +24-11-19 20:25:29 | D | best error = [ 8.5675, 8.5675, 8.5675, 8.5675, 8.5675] +24-11-19 20:25:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:29 | D | sum error = [ 128.8348, 139.2024, 150.0767, 162.6046, 175.5627] +24-11-19 20:25:29 | D | best error = [ 8.5675, 8.5675, 8.5675, 8.5675, 8.5675] +24-11-19 20:25:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:29 | D | sum error = [ 188.4848, 203.8216, 218.4755, 235.6491, 252.9976] +24-11-19 20:25:29 | D | best error = [ 8.5675, 8.5675, 8.5675, 8.5675, 8.5675] +24-11-19 20:25:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:29 | D | sum error = [ 270.5200, 290.1968, 310.5982, 332.2924, 355.1904] +24-11-19 20:25:29 | D | best error = [ 8.5675, 8.5675, 8.5675, 8.5675, 8.5675] +24-11-19 20:25:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:29 | D | sum error = [ 380.0201, 406.6682, 434.5669, 463.3455, 494.1296] +24-11-19 20:25:29 | D | best error = [ 8.5675, 8.5675, 8.5675, 8.5675, 8.5675] +24-11-19 20:25:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:29 | D | sum error = [ 526.5312, 560.5413, 595.1425, 632.3814, 671.9277] +24-11-19 20:25:29 | D | best error = [ 8.5675, 8.5675, 8.5675, 8.5675, 8.5675] +24-11-19 20:25:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:29 | D | sum error = [ 713.1631, 756.3324, 803.3655, 850.7021, 901.7704] +24-11-19 20:25:29 | D | best error = [ 8.5675, 8.5675, 8.5675, 8.5675, 8.5675] +24-11-19 20:25:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:29 | D | sum error = [ 955.1396, 1009.2721, 1067.3399, 1125.8868, 1186.4118] +24-11-19 20:25:29 | D | best error = [ 8.5675, 8.5675, 8.5675, 8.5675, 8.5675] +24-11-19 20:25:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:29 | D | sum error = [ 1249.9765, 1313.8233, 1379.8404, 1445.4777, 1512.8476] +24-11-19 20:25:29 | D | best error = [ 8.5675, 8.5675, 8.5675, 8.5675, 8.5675] +24-11-19 20:25:29 | D | + error = [8.5675] +24-11-19 20:25:29 | D | - Calibrating model.layers.10.self_attn.v_proj.weight +24-11-19 20:25:29 | D | + w: sint8 +24-11-19 20:25:29 | D | + x: None +24-11-19 20:25:29 | D | + y: None +24-11-19 20:25:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:29 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:29 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:30 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:30 | D | - range ratio = [ 1.0000] +24-11-19 20:25:30 | D | sum error = [ 4.0795] +24-11-19 20:25:30 | D | best error = [ 4.0795] +24-11-19 20:25:30 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:30 | D | sum error = [ 4.0372, 4.0421, 4.0606, 4.0985, 4.1819] +24-11-19 20:25:30 | D | best error = [ 3.8201, 3.7193, 3.6694, 3.6408, 3.6238] +24-11-19 20:25:30 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:30 | D | sum error = [ 4.2806, 4.4298, 4.6168, 4.8390, 5.0936] +24-11-19 20:25:30 | D | best error = [ 3.6167, 3.6141, 3.6131, 3.6126, 3.6126] +24-11-19 20:25:30 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:30 | D | sum error = [ 5.4032, 5.7123, 6.0769, 6.4941, 6.9609] +24-11-19 20:25:30 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:30 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:30 | D | sum error = [ 7.4513, 7.9761, 8.5481, 9.1515, 9.8168] +24-11-19 20:25:30 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:30 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:30 | D | sum error = [ 10.5212, 11.2585, 12.0704, 12.9258, 13.8195] +24-11-19 20:25:30 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:30 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:30 | D | sum error = [ 14.7844, 15.8085, 16.8648, 17.9983, 19.2120] +24-11-19 20:25:30 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:30 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:30 | D | sum error = [ 20.4723, 21.8125, 23.2412, 24.7244, 26.3022] +24-11-19 20:25:30 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:30 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:30 | D | sum error = [ 27.9734, 29.7231, 31.5767, 33.5133, 35.5685] +24-11-19 20:25:30 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:30 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:30 | D | sum error = [ 37.7103, 39.9982, 42.3706, 44.8752, 47.5145] +24-11-19 20:25:30 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:30 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:30 | D | sum error = [ 50.2616, 53.1818, 56.2491, 59.4633, 62.8285] +24-11-19 20:25:30 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:30 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:30 | D | sum error = [ 66.3581, 70.0647, 73.9295, 78.0041, 82.2521] +24-11-19 20:25:30 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:30 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:30 | D | sum error = [ 86.7102, 91.3611, 96.2286, 101.3120, 106.6225] +24-11-19 20:25:30 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:30 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:30 | D | sum error = [ 112.1488, 117.9147, 123.9167, 130.1681, 136.6867] +24-11-19 20:25:30 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:30 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:30 | D | sum error = [ 143.4650, 150.5248, 157.8566, 165.4758, 173.3674] +24-11-19 20:25:30 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:30 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:30 | D | sum error = [ 181.5599, 190.0381, 198.8039, 207.8721, 217.2412] +24-11-19 20:25:30 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:30 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:30 | D | sum error = [ 226.9200, 236.9114, 247.2255, 257.8471, 268.8003] +24-11-19 20:25:30 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:30 | D | + error = [3.6126] +24-11-19 20:25:30 | D | - Calibrating model.layers.10.self_attn.o_proj.weight +24-11-19 20:25:30 | D | + w: sint8 +24-11-19 20:25:30 | D | + x: None +24-11-19 20:25:30 | D | + y: None +24-11-19 20:25:30 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:30 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:30 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:30 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:30 | D | - range ratio = [ 1.0000] +24-11-19 20:25:30 | D | sum error = [ 1.1246] +24-11-19 20:25:30 | D | best error = [ 1.1246] +24-11-19 20:25:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:31 | D | sum error = [ 1.1141, 1.1089, 1.1144, 1.1145, 1.1314] +24-11-19 20:25:31 | D | best error = [ 1.0518, 1.0179, 0.9993, 0.9856, 0.9769] +24-11-19 20:25:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:31 | D | sum error = [ 1.1521, 1.1798, 1.2108, 1.2518, 1.3076] +24-11-19 20:25:31 | D | best error = [ 0.9712, 0.9677, 0.9649, 0.9630, 0.9619] +24-11-19 20:25:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:31 | D | sum error = [ 1.3719, 1.4366, 1.5177, 1.6077, 1.7035] +24-11-19 20:25:31 | D | best error = [ 0.9616, 0.9612, 0.9608, 0.9605, 0.9605] +24-11-19 20:25:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:31 | D | sum error = [ 1.8042, 1.9297, 2.0552, 2.1887, 2.3385] +24-11-19 20:25:31 | D | best error = [ 0.9604, 0.9604, 0.9604, 0.9603, 0.9603] +24-11-19 20:25:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:31 | D | sum error = [ 2.4898, 2.6554, 2.8328, 3.0264, 3.2235] +24-11-19 20:25:31 | D | best error = [ 0.9603, 0.9603, 0.9603, 0.9603, 0.9603] +24-11-19 20:25:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:31 | D | sum error = [ 3.4352, 3.6589, 3.9056, 4.1562, 4.4222] +24-11-19 20:25:31 | D | best error = [ 0.9603, 0.9603, 0.9603, 0.9603, 0.9603] +24-11-19 20:25:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:31 | D | sum error = [ 4.7124, 5.0114, 5.3254, 5.6593, 6.0097] +24-11-19 20:25:31 | D | best error = [ 0.9603, 0.9603, 0.9603, 0.9603, 0.9603] +24-11-19 20:25:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:31 | D | sum error = [ 6.3791, 6.7706, 7.1810, 7.6141, 8.0726] +24-11-19 20:25:31 | D | best error = [ 0.9603, 0.9603, 0.9603, 0.9603, 0.9603] +24-11-19 20:25:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:31 | D | sum error = [ 8.5485, 9.0543, 9.5832, 10.1376, 10.7224] +24-11-19 20:25:31 | D | best error = [ 0.9603, 0.9603, 0.9603, 0.9603, 0.9603] +24-11-19 20:25:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:31 | D | sum error = [ 11.3352, 11.9768, 12.6473, 13.3526, 14.0865] +24-11-19 20:25:31 | D | best error = [ 0.9603, 0.9603, 0.9603, 0.9603, 0.9603] +24-11-19 20:25:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:31 | D | sum error = [ 14.8637, 15.6659, 16.5124, 17.3953, 18.3172] +24-11-19 20:25:31 | D | best error = [ 0.9603, 0.9603, 0.9603, 0.9603, 0.9603] +24-11-19 20:25:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:31 | D | sum error = [ 19.2785, 20.2815, 21.3293, 22.4160, 23.5499] +24-11-19 20:25:31 | D | best error = [ 0.9603, 0.9603, 0.9603, 0.9603, 0.9603] +24-11-19 20:25:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:31 | D | sum error = [ 24.7302, 25.9588, 27.2365, 28.5675, 29.9498] +24-11-19 20:25:31 | D | best error = [ 0.9603, 0.9603, 0.9603, 0.9603, 0.9603] +24-11-19 20:25:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:31 | D | sum error = [ 31.3876, 32.8774, 34.4241, 36.0272, 37.6898] +24-11-19 20:25:31 | D | best error = [ 0.9603, 0.9603, 0.9603, 0.9603, 0.9603] +24-11-19 20:25:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:31 | D | sum error = [ 39.4133, 41.2017, 43.0535, 44.9676, 46.9477] +24-11-19 20:25:31 | D | best error = [ 0.9603, 0.9603, 0.9603, 0.9603, 0.9603] +24-11-19 20:25:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:31 | D | sum error = [ 48.9938, 51.1082, 53.2919, 55.5439, 57.8662] +24-11-19 20:25:31 | D | best error = [ 0.9603, 0.9603, 0.9603, 0.9603, 0.9603] +24-11-19 20:25:31 | D | + error = [0.9603] +24-11-19 20:25:31 | D | - Calibrating model.layers.10.mlp.up_proj.weight +24-11-19 20:25:31 | D | + w: sint8 +24-11-19 20:25:31 | D | + x: None +24-11-19 20:25:31 | D | + y: None +24-11-19 20:25:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:31 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:31 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:31 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:31 | D | - range ratio = [ 1.0000] +24-11-19 20:25:31 | D | sum error = [ 5.6645] +24-11-19 20:25:31 | D | best error = [ 5.6645] +24-11-19 20:25:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:32 | D | sum error = [ 5.6307, 5.6145, 5.6359, 5.7087, 5.8115] +24-11-19 20:25:32 | D | best error = [ 5.2987, 5.1561, 5.0793, 5.0370, 5.0154] +24-11-19 20:25:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:32 | D | sum error = [ 5.9449, 6.1656, 6.4031, 6.7125, 7.0654] +24-11-19 20:25:32 | D | best error = [ 5.0037, 4.9998, 4.9978, 4.9974, 4.9973] +24-11-19 20:25:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:32 | D | sum error = [ 7.4810, 7.9486, 8.4605, 9.0367, 9.6695] +24-11-19 20:25:32 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:32 | D | sum error = [ 10.3585, 11.0750, 11.8608, 12.7323, 13.6503] +24-11-19 20:25:32 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:32 | D | sum error = [ 14.6349, 15.6670, 16.7959, 17.9776, 19.2282] +24-11-19 20:25:32 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:32 | D | sum error = [ 20.5553, 21.9677, 23.4657, 25.0364, 26.6831] +24-11-19 20:25:32 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:32 | D | sum error = [ 28.4557, 30.3108, 32.2792, 34.3328, 36.5011] +24-11-19 20:25:32 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:32 | D | sum error = [ 38.8011, 41.1947, 43.7341, 46.3924, 49.2034] +24-11-19 20:25:32 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:32 | D | sum error = [ 52.1553, 55.2612, 58.5156, 61.9245, 65.5172] +24-11-19 20:25:32 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:32 | D | sum error = [ 69.2790, 73.1984, 77.3339, 81.6571, 86.1864] +24-11-19 20:25:32 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:32 | D | sum error = [ 90.9377, 95.8933, 101.0824, 106.5206, 112.1902] +24-11-19 20:25:32 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:32 | D | sum error = [ 118.1264, 124.3159, 130.7750, 137.5110, 144.5389] +24-11-19 20:25:32 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:32 | D | sum error = [ 151.8559, 159.4724, 167.3990, 175.6424, 184.2271] +24-11-19 20:25:32 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:32 | D | sum error = [ 193.1340, 202.3816, 211.9761, 221.9362, 232.2371] +24-11-19 20:25:32 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:32 | D | sum error = [ 242.9128, 253.9696, 265.4011, 277.2065, 289.3968] +24-11-19 20:25:32 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:32 | D | sum error = [ 301.9895, 314.9811, 328.3726, 342.1544, 356.3410] +24-11-19 20:25:32 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:32 | D | + error = [4.9972] +24-11-19 20:25:32 | D | - Calibrating model.layers.10.mlp.gate_proj.weight +24-11-19 20:25:32 | D | + w: sint8 +24-11-19 20:25:32 | D | + x: None +24-11-19 20:25:32 | D | + y: None +24-11-19 20:25:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:32 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:32 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:33 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:33 | D | - range ratio = [ 1.0000] +24-11-19 20:25:33 | D | sum error = [ 6.0751] +24-11-19 20:25:33 | D | best error = [ 6.0751] +24-11-19 20:25:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:33 | D | sum error = [ 6.0331, 6.0197, 6.0442, 6.1078, 6.2273] +24-11-19 20:25:33 | D | best error = [ 5.6863, 5.5349, 5.4516, 5.4035, 5.3797] +24-11-19 20:25:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:33 | D | sum error = [ 6.3918, 6.6095, 6.8938, 7.2043, 7.5790] +24-11-19 20:25:33 | D | best error = [ 5.3679, 5.3632, 5.3617, 5.3614, 5.3610] +24-11-19 20:25:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:33 | D | sum error = [ 8.0236, 8.5241, 9.0945, 9.7051, 10.3942] +24-11-19 20:25:33 | D | best error = [ 5.3610, 5.3610, 5.3610, 5.3610, 5.3610] +24-11-19 20:25:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:33 | D | sum error = [ 11.1269, 11.9410, 12.7868, 13.7252, 14.7153] +24-11-19 20:25:33 | D | best error = [ 5.3610, 5.3610, 5.3610, 5.3610, 5.3610] +24-11-19 20:25:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:33 | D | sum error = [ 15.7935, 16.9463, 18.1490, 19.4487, 20.8303] +24-11-19 20:25:33 | D | best error = [ 5.3610, 5.3610, 5.3610, 5.3610, 5.3610] +24-11-19 20:25:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:33 | D | sum error = [ 22.2949, 23.8643, 25.5173, 27.2901, 29.1510] +24-11-19 20:25:33 | D | best error = [ 5.3610, 5.3610, 5.3610, 5.3610, 5.3610] +24-11-19 20:25:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:33 | D | sum error = [ 31.1381, 33.2470, 35.4672, 37.8574, 40.3339] +24-11-19 20:25:33 | D | best error = [ 5.3610, 5.3610, 5.3610, 5.3610, 5.3610] +24-11-19 20:25:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:33 | D | sum error = [ 42.9916, 45.7939, 48.7839, 51.9253, 55.2580] +24-11-19 20:25:33 | D | best error = [ 5.3610, 5.3610, 5.3610, 5.3610, 5.3610] +24-11-19 20:25:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:34 | D | sum error = [ 58.8080, 62.5213, 66.4699, 70.6331, 75.0340] +24-11-19 20:25:34 | D | best error = [ 5.3610, 5.3610, 5.3610, 5.3610, 5.3610] +24-11-19 20:25:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:34 | D | sum error = [ 79.7072, 84.6111, 89.7862, 95.2747, 101.0393] +24-11-19 20:25:34 | D | best error = [ 5.3610, 5.3610, 5.3610, 5.3610, 5.3610] +24-11-19 20:25:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:34 | D | sum error = [ 107.1341, 113.5422, 120.3211, 127.4555, 134.9575] +24-11-19 20:25:34 | D | best error = [ 5.3610, 5.3610, 5.3610, 5.3610, 5.3610] +24-11-19 20:25:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:34 | D | sum error = [ 142.8326, 151.1366, 159.8316, 168.9898, 178.5827] +24-11-19 20:25:34 | D | best error = [ 5.3610, 5.3610, 5.3610, 5.3610, 5.3610] +24-11-19 20:25:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:34 | D | sum error = [ 188.6261, 199.1685, 210.1938, 221.7292, 233.8125] +24-11-19 20:25:34 | D | best error = [ 5.3610, 5.3610, 5.3610, 5.3610, 5.3610] +24-11-19 20:25:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:34 | D | sum error = [ 246.4008, 259.5209, 273.2255, 287.4956, 302.3597] +24-11-19 20:25:34 | D | best error = [ 5.3610, 5.3610, 5.3610, 5.3610, 5.3610] +24-11-19 20:25:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:34 | D | sum error = [ 317.8273, 333.8922, 350.5788, 367.8915, 385.8099] +24-11-19 20:25:34 | D | best error = [ 5.3610, 5.3610, 5.3610, 5.3610, 5.3610] +24-11-19 20:25:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:34 | D | sum error = [ 404.3679, 423.5515, 443.3611, 463.8170, 484.9028] +24-11-19 20:25:34 | D | best error = [ 5.3610, 5.3610, 5.3610, 5.3610, 5.3610] +24-11-19 20:25:34 | D | + error = [5.3610] +24-11-19 20:25:34 | D | - Calibrating model.layers.10.mlp.down_proj.weight +24-11-19 20:25:34 | D | + w: sint8 +24-11-19 20:25:34 | D | + x: None +24-11-19 20:25:34 | D | + y: None +24-11-19 20:25:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:34 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:34 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:34 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:34 | D | - range ratio = [ 1.0000] +24-11-19 20:25:34 | D | sum error = [ 1.4171] +24-11-19 20:25:34 | D | best error = [ 1.4171] +24-11-19 20:25:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:35 | D | sum error = [ 1.4054, 1.3954, 1.3867, 1.3824, 1.3823] +24-11-19 20:25:35 | D | best error = [ 1.3650, 1.3389, 1.3208, 1.3074, 1.2981] +24-11-19 20:25:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:35 | D | sum error = [ 1.3870, 1.3982, 1.4142, 1.4369, 1.4713] +24-11-19 20:25:35 | D | best error = [ 1.2903, 1.2848, 1.2812, 1.2788, 1.2771] +24-11-19 20:25:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:35 | D | sum error = [ 1.5089, 1.5593, 1.6130, 1.6793, 1.7576] +24-11-19 20:25:35 | D | best error = [ 1.2759, 1.2754, 1.2751, 1.2748, 1.2747] +24-11-19 20:25:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:35 | D | sum error = [ 1.8422, 1.9447, 2.0515, 2.1734, 2.3084] +24-11-19 20:25:35 | D | best error = [ 1.2746, 1.2746, 1.2745, 1.2745, 1.2745] +24-11-19 20:25:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:35 | D | sum error = [ 2.4557, 2.6141, 2.7895, 2.9766, 3.1786] +24-11-19 20:25:35 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 20:25:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:35 | D | sum error = [ 3.3928, 3.6281, 3.8772, 4.1462, 4.4299] +24-11-19 20:25:35 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 20:25:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:35 | D | sum error = [ 4.7340, 5.0582, 5.4025, 5.7710, 6.1608] +24-11-19 20:25:35 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 20:25:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:35 | D | sum error = [ 6.5751, 7.0124, 7.4823, 7.9735, 8.4939] +24-11-19 20:25:35 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 20:25:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:35 | D | sum error = [ 9.0454, 9.6274, 10.2456, 10.8966, 11.5826] +24-11-19 20:25:35 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 20:25:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:35 | D | sum error = [ 12.3051, 13.0650, 13.8695, 14.7138, 15.6041] +24-11-19 20:25:35 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 20:25:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:35 | D | sum error = [ 16.5355, 17.5189, 18.5462, 19.6282, 20.7678] +24-11-19 20:25:35 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 20:25:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:35 | D | sum error = [ 21.9600, 23.2100, 24.5211, 25.8914, 27.3263] +24-11-19 20:25:35 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 20:25:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:35 | D | sum error = [ 28.8296, 30.3986, 32.0396, 33.7525, 35.5381] +24-11-19 20:25:35 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 20:25:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:35 | D | sum error = [ 37.4045, 39.3459, 41.3683, 43.4779, 45.6640] +24-11-19 20:25:35 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 20:25:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:35 | D | sum error = [ 47.9385, 50.3038, 52.7572, 55.3017, 57.9402] +24-11-19 20:25:35 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 20:25:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:35 | D | sum error = [ 60.6740, 63.5034, 66.4325, 69.4596, 72.5866] +24-11-19 20:25:35 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 20:25:35 | D | + error = [1.2745] +24-11-19 20:25:35 | D | - Quantizing model.layers.10.self_attn.q_proj.weight +24-11-19 20:25:39 | D | - Quantizing model.layers.10.self_attn.k_proj.weight +24-11-19 20:25:43 | D | - Quantizing model.layers.10.self_attn.v_proj.weight +24-11-19 20:25:44 | D | - Quantizing model.layers.10.self_attn.o_proj.weight +24-11-19 20:25:45 | D | - Quantizing model.layers.10.mlp.up_proj.weight +24-11-19 20:25:46 | D | - Quantizing model.layers.10.mlp.gate_proj.weight +24-11-19 20:25:46 | D | - Quantizing model.layers.10.mlp.down_proj.weight +24-11-19 20:25:55 | D | - Quantizing layer model.layers.11 +24-11-19 20:25:55 | D | - Calibrating model.layers.11.self_attn.q_proj.weight +24-11-19 20:25:55 | D | + w: sint8 +24-11-19 20:25:55 | D | + x: None +24-11-19 20:25:55 | D | + y: None +24-11-19 20:25:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:25:55 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:55 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:55 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:55 | D | - range ratio = [ 1.0000] +24-11-19 20:25:55 | D | sum error = [ 9.6945] +24-11-19 20:25:55 | D | best error = [ 9.6945] +24-11-19 20:26:09 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:09 | D | sum error = [ 9.5867, 9.5545, 9.4543, 9.8380, 9.7947] +24-11-19 20:26:09 | D | best error = [ 9.5867, 9.5545, 9.4543, 9.4543, 9.4543] +24-11-19 20:26:09 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:09 | D | sum error = [ 10.1171, 10.6088, 10.8925, 11.5735, 12.2156] +24-11-19 20:26:09 | D | best error = [ 9.4543, 9.4543, 9.4543, 9.4543, 9.4543] +24-11-19 20:26:09 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:09 | D | sum error = [ 13.0205, 13.8893, 14.8888, 15.7929, 17.0801] +24-11-19 20:26:09 | D | best error = [ 9.4543, 9.4543, 9.4543, 9.4543, 9.4543] +24-11-19 20:26:09 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:09 | D | sum error = [ 18.5306, 20.1681, 21.6045, 23.3173, 25.7551] +24-11-19 20:26:09 | D | best error = [ 9.4543, 9.4543, 9.4543, 9.4543, 9.4543] +24-11-19 20:26:09 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:09 | D | sum error = [ 27.7569, 29.8710, 32.2609, 35.2051, 37.7151] +24-11-19 20:26:09 | D | best error = [ 9.4543, 9.4543, 9.4543, 9.4543, 9.4543] +24-11-19 20:26:09 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:09 | D | sum error = [ 40.5824, 44.1255, 47.4391, 51.7792, 56.0021] +24-11-19 20:26:09 | D | best error = [ 9.4543, 9.4543, 9.4543, 9.4543, 9.4543] +24-11-19 20:26:09 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:09 | D | sum error = [ 60.1549, 65.2055, 70.1282, 75.6173, 81.6605] +24-11-19 20:26:09 | D | best error = [ 9.4543, 9.4543, 9.4543, 9.4543, 9.4543] +24-11-19 20:26:09 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:09 | D | sum error = [ 87.6185, 94.8681, 102.0664, 109.7886, 117.7832] +24-11-19 20:26:09 | D | best error = [ 9.4543, 9.4543, 9.4543, 9.4543, 9.4543] +24-11-19 20:26:09 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:09 | D | sum error = [ 126.9925, 136.5222, 146.5580, 157.4413, 168.5470] +24-11-19 20:26:09 | D | best error = [ 9.4543, 9.4543, 9.4543, 9.4543, 9.4543] +24-11-19 20:26:09 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:09 | D | sum error = [ 180.9802, 194.2977, 208.3338, 223.4550, 239.6790] +24-11-19 20:26:09 | D | best error = [ 9.4543, 9.4543, 9.4543, 9.4543, 9.4543] +24-11-19 20:26:09 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:09 | D | sum error = [ 257.1398, 275.9386, 295.9717, 317.8796, 341.0377] +24-11-19 20:26:09 | D | best error = [ 9.4543, 9.4543, 9.4543, 9.4543, 9.4543] +24-11-19 20:26:09 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:09 | D | sum error = [ 365.8023, 392.6881, 421.4816, 452.1340, 484.9687] +24-11-19 20:26:09 | D | best error = [ 9.4543, 9.4543, 9.4543, 9.4543, 9.4543] +24-11-19 20:26:09 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:09 | D | sum error = [ 520.5219, 558.1577, 598.4416, 641.1852, 686.6427] +24-11-19 20:26:09 | D | best error = [ 9.4543, 9.4543, 9.4543, 9.4543, 9.4543] +24-11-19 20:26:09 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:09 | D | sum error = [ 735.0536, 787.2419, 842.1509, 900.4826, 961.9690] +24-11-19 20:26:09 | D | best error = [ 9.4543, 9.4543, 9.4543, 9.4543, 9.4543] +24-11-19 20:26:09 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:09 | D | sum error = [ 1026.7558, 1095.0967, 1166.8035, 1241.8539, 1319.8336] +24-11-19 20:26:09 | D | best error = [ 9.4543, 9.4543, 9.4543, 9.4543, 9.4543] +24-11-19 20:26:09 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:09 | D | sum error = [ 1400.3341, 1483.4837, 1568.4540, 1654.9746, 1742.4445] +24-11-19 20:26:09 | D | best error = [ 9.4543, 9.4543, 9.4543, 9.4543, 9.4543] +24-11-19 20:26:09 | D | + error = [9.4543] +24-11-19 20:26:09 | D | - Calibrating model.layers.11.self_attn.k_proj.weight +24-11-19 20:26:09 | D | + w: sint8 +24-11-19 20:26:09 | D | + x: None +24-11-19 20:26:09 | D | + y: None +24-11-19 20:26:09 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:26:09 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:09 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:09 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:10 | D | - range ratio = [ 1.0000] +24-11-19 20:26:10 | D | sum error = [ 9.8125] +24-11-19 20:26:10 | D | best error = [ 9.8125] +24-11-19 20:26:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:23 | D | sum error = [ 10.0663, 10.1181, 9.7926, 10.1309, 10.9685] +24-11-19 20:26:23 | D | best error = [ 9.8125, 9.8125, 9.7926, 9.7926, 9.7926] +24-11-19 20:26:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:23 | D | sum error = [ 11.2393, 11.3252, 11.9439, 12.2985, 12.9408] +24-11-19 20:26:23 | D | best error = [ 9.7926, 9.7926, 9.7926, 9.7926, 9.7926] +24-11-19 20:26:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:23 | D | sum error = [ 14.1301, 15.0237, 15.6660, 17.3590, 17.9303] +24-11-19 20:26:23 | D | best error = [ 9.7926, 9.7926, 9.7926, 9.7926, 9.7926] +24-11-19 20:26:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:23 | D | sum error = [ 19.3784, 21.4847, 23.2985, 24.1708, 25.9356] +24-11-19 20:26:23 | D | best error = [ 9.7926, 9.7926, 9.7926, 9.7926, 9.7926] +24-11-19 20:26:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:23 | D | sum error = [ 28.3083, 30.2107, 32.2335, 35.0049, 37.3903] +24-11-19 20:26:23 | D | best error = [ 9.7926, 9.7926, 9.7926, 9.7926, 9.7926] +24-11-19 20:26:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:23 | D | sum error = [ 39.9980, 43.1125, 46.4023, 49.6386, 53.5367] +24-11-19 20:26:23 | D | best error = [ 9.7926, 9.7926, 9.7926, 9.7926, 9.7926] +24-11-19 20:26:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:23 | D | sum error = [ 58.2735, 62.6322, 67.1960, 72.8485, 78.4001] +24-11-19 20:26:23 | D | best error = [ 9.7926, 9.7926, 9.7926, 9.7926, 9.7926] +24-11-19 20:26:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:23 | D | sum error = [ 83.7471, 91.0813, 96.9493, 104.1449, 112.5930] +24-11-19 20:26:23 | D | best error = [ 9.7926, 9.7926, 9.7926, 9.7926, 9.7926] +24-11-19 20:26:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:23 | D | sum error = [ 120.9452, 129.9257, 139.7416, 150.1286, 161.6014] +24-11-19 20:26:23 | D | best error = [ 9.7926, 9.7926, 9.7926, 9.7926, 9.7926] +24-11-19 20:26:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:23 | D | sum error = [ 173.6868, 186.8218, 201.0075, 216.4118, 232.6696] +24-11-19 20:26:23 | D | best error = [ 9.7926, 9.7926, 9.7926, 9.7926, 9.7926] +24-11-19 20:26:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:23 | D | sum error = [ 250.7091, 270.2623, 290.5974, 312.8536, 335.9348] +24-11-19 20:26:23 | D | best error = [ 9.7926, 9.7926, 9.7926, 9.7926, 9.7926] +24-11-19 20:26:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:23 | D | sum error = [ 361.6358, 389.6865, 419.3378, 451.0842, 484.6550] +24-11-19 20:26:23 | D | best error = [ 9.7926, 9.7926, 9.7926, 9.7926, 9.7926] +24-11-19 20:26:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:23 | D | sum error = [ 520.8795, 558.9839, 600.5931, 644.0409, 689.8122] +24-11-19 20:26:23 | D | best error = [ 9.7926, 9.7926, 9.7926, 9.7926, 9.7926] +24-11-19 20:26:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:23 | D | sum error = [ 738.5403, 790.2833, 845.6997, 903.6823, 965.8995] +24-11-19 20:26:23 | D | best error = [ 9.7926, 9.7926, 9.7926, 9.7926, 9.7926] +24-11-19 20:26:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:23 | D | sum error = [ 1031.2575, 1099.0825, 1170.8089, 1246.2281, 1324.3096] +24-11-19 20:26:23 | D | best error = [ 9.7926, 9.7926, 9.7926, 9.7926, 9.7926] +24-11-19 20:26:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:23 | D | sum error = [ 1406.6511, 1490.9551, 1575.4353, 1663.7271, 1752.5110] +24-11-19 20:26:23 | D | best error = [ 9.7926, 9.7926, 9.7926, 9.7926, 9.7926] +24-11-19 20:26:23 | D | + error = [9.7926] +24-11-19 20:26:23 | D | - Calibrating model.layers.11.self_attn.v_proj.weight +24-11-19 20:26:23 | D | + w: sint8 +24-11-19 20:26:23 | D | + x: None +24-11-19 20:26:23 | D | + y: None +24-11-19 20:26:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:23 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:23 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:23 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:23 | D | - range ratio = [ 1.0000] +24-11-19 20:26:23 | D | sum error = [ 4.6933] +24-11-19 20:26:23 | D | best error = [ 4.6933] +24-11-19 20:26:24 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:24 | D | sum error = [ 4.6470, 4.6464, 4.6590, 4.7323, 4.7966] +24-11-19 20:26:24 | D | best error = [ 4.3733, 4.2550, 4.1904, 4.1554, 4.1373] +24-11-19 20:26:24 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:24 | D | sum error = [ 4.9320, 5.0874, 5.2972, 5.5361, 5.8394] +24-11-19 20:26:24 | D | best error = [ 4.1267, 4.1229, 4.1220, 4.1219, 4.1219] +24-11-19 20:26:24 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:24 | D | sum error = [ 6.1901, 6.5666, 7.0051, 7.4607, 7.9870] +24-11-19 20:26:24 | D | best error = [ 4.1219, 4.1219, 4.1219, 4.1219, 4.1219] +24-11-19 20:26:24 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:24 | D | sum error = [ 8.5365, 9.1486, 9.8068, 10.5329, 11.2821] +24-11-19 20:26:24 | D | best error = [ 4.1219, 4.1219, 4.1219, 4.1219, 4.1219] +24-11-19 20:26:24 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:24 | D | sum error = [ 12.0978, 12.9553, 13.8604, 14.8542, 15.8850] +24-11-19 20:26:24 | D | best error = [ 4.1219, 4.1219, 4.1219, 4.1219, 4.1219] +24-11-19 20:26:24 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:24 | D | sum error = [ 16.9862, 18.1509, 19.3921, 20.6794, 22.0835] +24-11-19 20:26:24 | D | best error = [ 4.1219, 4.1219, 4.1219, 4.1219, 4.1219] +24-11-19 20:26:24 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:24 | D | sum error = [ 23.5246, 25.0771, 26.7024, 28.4194, 30.2602] +24-11-19 20:26:24 | D | best error = [ 4.1219, 4.1219, 4.1219, 4.1219, 4.1219] +24-11-19 20:26:24 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:24 | D | sum error = [ 32.1853, 34.2046, 36.3246, 38.5765, 40.9297] +24-11-19 20:26:24 | D | best error = [ 4.1219, 4.1219, 4.1219, 4.1219, 4.1219] +24-11-19 20:26:24 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:24 | D | sum error = [ 43.4225, 46.0327, 48.7891, 51.6667, 54.6928] +24-11-19 20:26:24 | D | best error = [ 4.1219, 4.1219, 4.1219, 4.1219, 4.1219] +24-11-19 20:26:24 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:24 | D | sum error = [ 57.8716, 61.2038, 64.6917, 68.3253, 72.1499] +24-11-19 20:26:24 | D | best error = [ 4.1219, 4.1219, 4.1219, 4.1219, 4.1219] +24-11-19 20:26:24 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:24 | D | sum error = [ 76.1297, 80.3110, 84.6725, 89.2499, 94.0330] +24-11-19 20:26:24 | D | best error = [ 4.1219, 4.1219, 4.1219, 4.1219, 4.1219] +24-11-19 20:26:24 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:24 | D | sum error = [ 99.0325, 104.2396, 109.6754, 115.3614, 121.2795] +24-11-19 20:26:24 | D | best error = [ 4.1219, 4.1219, 4.1219, 4.1219, 4.1219] +24-11-19 20:26:24 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:24 | D | sum error = [ 127.4581, 133.8957, 140.6019, 147.5760, 154.8179] +24-11-19 20:26:24 | D | best error = [ 4.1219, 4.1219, 4.1219, 4.1219, 4.1219] +24-11-19 20:26:24 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:24 | D | sum error = [ 162.3525, 170.1899, 178.3083, 186.7315, 195.4534] +24-11-19 20:26:24 | D | best error = [ 4.1219, 4.1219, 4.1219, 4.1219, 4.1219] +24-11-19 20:26:24 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:24 | D | sum error = [ 204.4877, 213.8389, 223.5282, 233.5333, 243.8833] +24-11-19 20:26:24 | D | best error = [ 4.1219, 4.1219, 4.1219, 4.1219, 4.1219] +24-11-19 20:26:24 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:24 | D | sum error = [ 254.5664, 265.5873, 276.9454, 288.6517, 300.7075] +24-11-19 20:26:24 | D | best error = [ 4.1219, 4.1219, 4.1219, 4.1219, 4.1219] +24-11-19 20:26:24 | D | + error = [4.1219] +24-11-19 20:26:24 | D | - Calibrating model.layers.11.self_attn.o_proj.weight +24-11-19 20:26:24 | D | + w: sint8 +24-11-19 20:26:24 | D | + x: None +24-11-19 20:26:24 | D | + y: None +24-11-19 20:26:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:24 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:24 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:24 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:24 | D | - range ratio = [ 1.0000] +24-11-19 20:26:24 | D | sum error = [ 1.0946] +24-11-19 20:26:24 | D | best error = [ 1.0946] +24-11-19 20:26:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:25 | D | sum error = [ 1.0883, 1.0824, 1.0782, 1.0814, 1.0888] +24-11-19 20:26:25 | D | best error = [ 1.0161, 0.9784, 0.9562, 0.9402, 0.9295] +24-11-19 20:26:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:25 | D | sum error = [ 1.1041, 1.1290, 1.1529, 1.1847, 1.2216] +24-11-19 20:26:25 | D | best error = [ 0.9222, 0.9166, 0.9125, 0.9098, 0.9075] +24-11-19 20:26:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:25 | D | sum error = [ 1.2738, 1.3319, 1.3955, 1.4695, 1.5439] +24-11-19 20:26:25 | D | best error = [ 0.9057, 0.9046, 0.9038, 0.9030, 0.9025] +24-11-19 20:26:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:25 | D | sum error = [ 1.6300, 1.7293, 1.8329, 1.9524, 2.0702] +24-11-19 20:26:25 | D | best error = [ 0.9020, 0.9016, 0.9013, 0.9010, 0.9008] +24-11-19 20:26:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:25 | D | sum error = [ 2.2008, 2.3435, 2.4899, 2.6471, 2.8185] +24-11-19 20:26:25 | D | best error = [ 0.9006, 0.9005, 0.9004, 0.9004, 0.9003] +24-11-19 20:26:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:25 | D | sum error = [ 3.0059, 3.1993, 3.4029, 3.6201, 3.8504] +24-11-19 20:26:25 | D | best error = [ 0.9002, 0.9002, 0.9002, 0.9002, 0.9002] +24-11-19 20:26:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:25 | D | sum error = [ 4.0986, 4.3545, 4.6318, 4.9144, 5.2237] +24-11-19 20:26:25 | D | best error = [ 0.9002, 0.9002, 0.9002, 0.9002, 0.9002] +24-11-19 20:26:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:25 | D | sum error = [ 5.5439, 5.8819, 6.2420, 6.6173, 7.0143] +24-11-19 20:26:25 | D | best error = [ 0.9002, 0.9002, 0.9002, 0.9002, 0.9002] +24-11-19 20:26:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:25 | D | sum error = [ 7.4320, 7.8694, 8.3340, 8.8178, 9.3268] +24-11-19 20:26:25 | D | best error = [ 0.9002, 0.9002, 0.9002, 0.9002, 0.9002] +24-11-19 20:26:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:25 | D | sum error = [ 9.8609, 10.4233, 11.0112, 11.6313, 12.2727] +24-11-19 20:26:25 | D | best error = [ 0.9002, 0.9002, 0.9002, 0.9002, 0.9002] +24-11-19 20:26:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:25 | D | sum error = [ 12.9515, 13.6578, 14.4009, 15.1743, 15.9837] +24-11-19 20:26:25 | D | best error = [ 0.9002, 0.9002, 0.9002, 0.9002, 0.9002] +24-11-19 20:26:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:25 | D | sum error = [ 16.8364, 17.7220, 18.6422, 19.6054, 20.6153] +24-11-19 20:26:25 | D | best error = [ 0.9002, 0.9002, 0.9002, 0.9002, 0.9002] +24-11-19 20:26:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:25 | D | sum error = [ 21.6619, 22.7523, 23.8901, 25.0679, 26.2979] +24-11-19 20:26:25 | D | best error = [ 0.9002, 0.9002, 0.9002, 0.9002, 0.9002] +24-11-19 20:26:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:25 | D | sum error = [ 27.5746, 28.9037, 30.2782, 31.7051, 33.1892] +24-11-19 20:26:25 | D | best error = [ 0.9002, 0.9002, 0.9002, 0.9002, 0.9002] +24-11-19 20:26:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:25 | D | sum error = [ 34.7262, 36.3190, 37.9705, 39.6804, 41.4489] +24-11-19 20:26:25 | D | best error = [ 0.9002, 0.9002, 0.9002, 0.9002, 0.9002] +24-11-19 20:26:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:25 | D | sum error = [ 43.2796, 45.1739, 47.1269, 49.1444, 51.2291] +24-11-19 20:26:25 | D | best error = [ 0.9002, 0.9002, 0.9002, 0.9002, 0.9002] +24-11-19 20:26:25 | D | + error = [0.9002] +24-11-19 20:26:25 | D | - Calibrating model.layers.11.mlp.up_proj.weight +24-11-19 20:26:25 | D | + w: sint8 +24-11-19 20:26:25 | D | + x: None +24-11-19 20:26:25 | D | + y: None +24-11-19 20:26:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:25 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:25 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:25 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:25 | D | - range ratio = [ 1.0000] +24-11-19 20:26:25 | D | sum error = [ 5.8968] +24-11-19 20:26:25 | D | best error = [ 5.8968] +24-11-19 20:26:26 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:26 | D | sum error = [ 5.8650, 5.8513, 5.8743, 5.9440, 6.0462] +24-11-19 20:26:26 | D | best error = [ 5.5134, 5.3594, 5.2767, 5.2300, 5.2061] +24-11-19 20:26:26 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:26 | D | sum error = [ 6.2069, 6.4161, 6.6829, 6.9984, 7.3705] +24-11-19 20:26:26 | D | best error = [ 5.1935, 5.1886, 5.1867, 5.1861, 5.1860] +24-11-19 20:26:26 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:26 | D | sum error = [ 7.8016, 8.2828, 8.8186, 9.4265, 10.0644] +24-11-19 20:26:26 | D | best error = [ 5.1859, 5.1859, 5.1859, 5.1859, 5.1859] +24-11-19 20:26:26 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:26 | D | sum error = [ 10.7817, 11.5634, 12.3790, 13.2854, 14.2258] +24-11-19 20:26:26 | D | best error = [ 5.1859, 5.1859, 5.1859, 5.1859, 5.1859] +24-11-19 20:26:26 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:26 | D | sum error = [ 15.2433, 16.3217, 17.4911, 18.7117, 20.0208] +24-11-19 20:26:26 | D | best error = [ 5.1859, 5.1859, 5.1859, 5.1859, 5.1859] +24-11-19 20:26:26 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:26 | D | sum error = [ 21.4164, 22.8783, 24.4281, 26.0772, 27.8137] +24-11-19 20:26:26 | D | best error = [ 5.1859, 5.1859, 5.1859, 5.1859, 5.1859] +24-11-19 20:26:26 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:26 | D | sum error = [ 29.6523, 31.5865, 33.6368, 35.7825, 38.0689] +24-11-19 20:26:26 | D | best error = [ 5.1859, 5.1859, 5.1859, 5.1859, 5.1859] +24-11-19 20:26:26 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:26 | D | sum error = [ 40.4626, 42.9862, 45.6295, 48.4011, 51.3435] +24-11-19 20:26:26 | D | best error = [ 5.1859, 5.1859, 5.1859, 5.1859, 5.1859] +24-11-19 20:26:26 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:26 | D | sum error = [ 54.4175, 57.6589, 61.0562, 64.6020, 68.3448] +24-11-19 20:26:26 | D | best error = [ 5.1859, 5.1859, 5.1859, 5.1859, 5.1859] +24-11-19 20:26:26 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:26 | D | sum error = [ 72.2460, 76.3634, 80.6480, 85.1423, 89.8528] +24-11-19 20:26:26 | D | best error = [ 5.1859, 5.1859, 5.1859, 5.1859, 5.1859] +24-11-19 20:26:26 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:26 | D | sum error = [ 94.7878, 99.9326, 105.3143, 110.9490, 116.8160] +24-11-19 20:26:26 | D | best error = [ 5.1859, 5.1859, 5.1859, 5.1859, 5.1859] +24-11-19 20:26:26 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:26 | D | sum error = [ 122.9551, 129.3564, 136.0345, 142.9888, 150.2254] +24-11-19 20:26:26 | D | best error = [ 5.1859, 5.1859, 5.1859, 5.1859, 5.1859] +24-11-19 20:26:26 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:26 | D | sum error = [ 157.7766, 165.6265, 173.7804, 182.2499, 191.0487] +24-11-19 20:26:26 | D | best error = [ 5.1859, 5.1859, 5.1859, 5.1859, 5.1859] +24-11-19 20:26:26 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:26 | D | sum error = [ 200.1699, 209.6422, 219.4522, 229.6337, 240.1667] +24-11-19 20:26:26 | D | best error = [ 5.1859, 5.1859, 5.1859, 5.1859, 5.1859] +24-11-19 20:26:26 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:26 | D | sum error = [ 251.0685, 262.3541, 274.0139, 286.0692, 298.4927] +24-11-19 20:26:26 | D | best error = [ 5.1859, 5.1859, 5.1859, 5.1859, 5.1859] +24-11-19 20:26:26 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:26 | D | sum error = [ 311.3393, 324.5740, 338.2199, 352.2743, 366.7366] +24-11-19 20:26:26 | D | best error = [ 5.1859, 5.1859, 5.1859, 5.1859, 5.1859] +24-11-19 20:26:26 | D | + error = [5.1859] +24-11-19 20:26:26 | D | - Calibrating model.layers.11.mlp.gate_proj.weight +24-11-19 20:26:26 | D | + w: sint8 +24-11-19 20:26:26 | D | + x: None +24-11-19 20:26:26 | D | + y: None +24-11-19 20:26:26 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:26 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:26:26 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:26:26 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:26:26 | D | - range ratio = [ 1.0000] +24-11-19 20:26:26 | D | sum error = [ 6.2444] +24-11-19 20:26:26 | D | best error = [ 6.2444] +24-11-19 20:26:27 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:27 | D | sum error = [ 6.2031, 6.1878, 6.2249, 6.2790, 6.3906] +24-11-19 20:26:27 | D | best error = [ 5.8282, 5.6706, 5.5844, 5.5342, 5.5077] +24-11-19 20:26:27 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:27 | D | sum error = [ 6.5537, 6.7828, 7.0596, 7.4142, 7.7927] +24-11-19 20:26:27 | D | best error = [ 5.4953, 5.4902, 5.4886, 5.4882, 5.4880] +24-11-19 20:26:27 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:27 | D | sum error = [ 8.2536, 8.7636, 9.3462, 9.9890, 10.6776] +24-11-19 20:26:27 | D | best error = [ 5.4880, 5.4880, 5.4880, 5.4880, 5.4880] +24-11-19 20:26:27 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:27 | D | sum error = [ 11.4498, 12.2913, 13.1845, 14.1227, 15.1669] +24-11-19 20:26:27 | D | best error = [ 5.4880, 5.4880, 5.4880, 5.4880, 5.4880] +24-11-19 20:26:27 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:27 | D | sum error = [ 16.2643, 17.4577, 18.7191, 20.0563, 21.5031] +24-11-19 20:26:27 | D | best error = [ 5.4880, 5.4880, 5.4880, 5.4880, 5.4880] +24-11-19 20:26:27 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:27 | D | sum error = [ 23.0244, 24.6573, 26.3794, 28.2338, 30.1765] +24-11-19 20:26:27 | D | best error = [ 5.4880, 5.4880, 5.4880, 5.4880, 5.4880] +24-11-19 20:26:27 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:27 | D | sum error = [ 32.2372, 34.4265, 36.7508, 39.2153, 41.7982] +24-11-19 20:26:27 | D | best error = [ 5.4880, 5.4880, 5.4880, 5.4880, 5.4880] +24-11-19 20:26:27 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:27 | D | sum error = [ 44.5803, 47.4947, 50.6060, 53.8461, 57.3444] +24-11-19 20:26:27 | D | best error = [ 5.4880, 5.4880, 5.4880, 5.4880, 5.4880] +24-11-19 20:26:27 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:27 | D | sum error = [ 60.9848, 64.8562, 68.9535, 73.2793, 77.8271] +24-11-19 20:26:27 | D | best error = [ 5.4880, 5.4880, 5.4880, 5.4880, 5.4880] +24-11-19 20:26:27 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:27 | D | sum error = [ 82.6715, 87.7624, 93.1483, 98.8137, 104.8243] +24-11-19 20:26:27 | D | best error = [ 5.4880, 5.4880, 5.4880, 5.4880, 5.4880] +24-11-19 20:26:27 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:27 | D | sum error = [ 111.1568, 117.8249, 124.8696, 132.2688, 140.0311] +24-11-19 20:26:27 | D | best error = [ 5.4880, 5.4880, 5.4880, 5.4880, 5.4880] +24-11-19 20:26:27 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:27 | D | sum error = [ 148.1953, 156.7933, 165.8133, 175.2716, 185.1961] +24-11-19 20:26:27 | D | best error = [ 5.4880, 5.4880, 5.4880, 5.4880, 5.4880] +24-11-19 20:26:27 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:27 | D | sum error = [ 195.5818, 206.4837, 217.8688, 229.8006, 242.2695] +24-11-19 20:26:27 | D | best error = [ 5.4880, 5.4880, 5.4880, 5.4880, 5.4880] +24-11-19 20:26:27 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:27 | D | sum error = [ 255.2984, 268.8695, 283.0090, 297.7371, 313.0486] +24-11-19 20:26:27 | D | best error = [ 5.4880, 5.4880, 5.4880, 5.4880, 5.4880] +24-11-19 20:26:27 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:27 | D | sum error = [ 328.9883, 345.5250, 362.6865, 380.5082, 398.9370] +24-11-19 20:26:27 | D | best error = [ 5.4880, 5.4880, 5.4880, 5.4880, 5.4880] +24-11-19 20:26:27 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:27 | D | sum error = [ 418.0164, 437.7326, 458.0958, 479.1172, 500.7893] +24-11-19 20:26:27 | D | best error = [ 5.4880, 5.4880, 5.4880, 5.4880, 5.4880] +24-11-19 20:26:27 | D | + error = [5.4880] +24-11-19 20:26:28 | D | - Calibrating model.layers.11.mlp.down_proj.weight +24-11-19 20:26:28 | D | + w: sint8 +24-11-19 20:26:28 | D | + x: None +24-11-19 20:26:28 | D | + y: None +24-11-19 20:26:28 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:28 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:26:28 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:26:28 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:26:28 | D | - range ratio = [ 1.0000] +24-11-19 20:26:28 | D | sum error = [ 1.4773] +24-11-19 20:26:28 | D | best error = [ 1.4773] +24-11-19 20:26:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:29 | D | sum error = [ 1.4650, 1.4558, 1.4490, 1.4458, 1.4460] +24-11-19 20:26:29 | D | best error = [ 1.4247, 1.3988, 1.3803, 1.3668, 1.3574] +24-11-19 20:26:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:29 | D | sum error = [ 1.4526, 1.4634, 1.4841, 1.5088, 1.5452] +24-11-19 20:26:29 | D | best error = [ 1.3498, 1.3447, 1.3410, 1.3388, 1.3374] +24-11-19 20:26:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:29 | D | sum error = [ 1.5883, 1.6346, 1.6947, 1.7676, 1.8499] +24-11-19 20:26:29 | D | best error = [ 1.3366, 1.3359, 1.3355, 1.3353, 1.3352] +24-11-19 20:26:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:29 | D | sum error = [ 1.9451, 2.0484, 2.1694, 2.2943, 2.4365] +24-11-19 20:26:29 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:29 | D | sum error = [ 2.5921, 2.7561, 2.9390, 3.1362, 3.3514] +24-11-19 20:26:29 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:29 | D | sum error = [ 3.5780, 3.8231, 4.0847, 4.3657, 4.6668] +24-11-19 20:26:29 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:29 | D | sum error = [ 4.9859, 5.3260, 5.6863, 6.0717, 6.4777] +24-11-19 20:26:29 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:29 | D | sum error = [ 6.9115, 7.3703, 7.8599, 8.3754, 8.9210] +24-11-19 20:26:29 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:29 | D | sum error = [ 9.4968, 10.1059, 10.7476, 11.4285, 12.1473] +24-11-19 20:26:29 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:29 | D | sum error = [ 12.9023, 13.6974, 14.5388, 15.4208, 16.3501] +24-11-19 20:26:29 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:29 | D | sum error = [ 17.3267, 18.3549, 19.4325, 20.5686, 21.7584] +24-11-19 20:26:29 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:29 | D | sum error = [ 23.0076, 24.3140, 25.6850, 27.1190, 28.6229] +24-11-19 20:26:29 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:29 | D | sum error = [ 30.1931, 31.8348, 33.5493, 35.3374, 37.2061] +24-11-19 20:26:29 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:29 | D | sum error = [ 39.1518, 41.1809, 43.2916, 45.4897, 47.7669] +24-11-19 20:26:29 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:29 | D | sum error = [ 50.1347, 52.5965, 55.1530, 57.8012, 60.5489] +24-11-19 20:26:29 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:29 | D | sum error = [ 63.3944, 66.3368, 69.3781, 72.5209, 75.7674] +24-11-19 20:26:29 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:29 | D | + error = [1.3351] +24-11-19 20:26:29 | D | - Quantizing model.layers.11.self_attn.q_proj.weight +24-11-19 20:26:30 | D | - Quantizing model.layers.11.self_attn.k_proj.weight +24-11-19 20:26:31 | D | - Quantizing model.layers.11.self_attn.v_proj.weight +24-11-19 20:26:33 | D | - Quantizing model.layers.11.self_attn.o_proj.weight +24-11-19 20:26:34 | D | - Quantizing model.layers.11.mlp.up_proj.weight +24-11-19 20:26:37 | D | - Quantizing model.layers.11.mlp.gate_proj.weight +24-11-19 20:26:38 | D | - Quantizing model.layers.11.mlp.down_proj.weight +24-11-19 20:26:47 | D | - Quantizing layer model.layers.12 +24-11-19 20:26:47 | D | - Calibrating model.layers.12.self_attn.q_proj.weight +24-11-19 20:26:47 | D | + w: sint8 +24-11-19 20:26:47 | D | + x: None +24-11-19 20:26:47 | D | + y: None +24-11-19 20:26:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:26:47 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:47 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:47 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:47 | D | - range ratio = [ 1.0000] +24-11-19 20:26:47 | D | sum error = [ 10.3180] +24-11-19 20:26:47 | D | best error = [ 10.3180] +24-11-19 20:27:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:01 | D | sum error = [ 10.2156, 10.2813, 10.3149, 10.3366, 10.7408] +24-11-19 20:27:01 | D | best error = [ 10.2156, 10.2156, 10.2156, 10.2156, 10.2156] +24-11-19 20:27:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:01 | D | sum error = [ 10.8833, 11.4849, 11.8846, 12.3643, 13.2922] +24-11-19 20:27:01 | D | best error = [ 10.2156, 10.2156, 10.2156, 10.2156, 10.2156] +24-11-19 20:27:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:01 | D | sum error = [ 14.2134, 14.9430, 16.0003, 17.6156, 18.6383] +24-11-19 20:27:01 | D | best error = [ 10.2156, 10.2156, 10.2156, 10.2156, 10.2156] +24-11-19 20:27:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:01 | D | sum error = [ 20.2314, 22.1950, 23.9714, 26.0809, 27.9935] +24-11-19 20:27:01 | D | best error = [ 10.2156, 10.2156, 10.2156, 10.2156, 10.2156] +24-11-19 20:27:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:01 | D | sum error = [ 30.5224, 32.6978, 36.1298, 39.1979, 41.9903] +24-11-19 20:27:01 | D | best error = [ 10.2156, 10.2156, 10.2156, 10.2156, 10.2156] +24-11-19 20:27:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:01 | D | sum error = [ 45.2304, 48.8854, 53.1362, 57.0237, 61.2853] +24-11-19 20:27:01 | D | best error = [ 10.2156, 10.2156, 10.2156, 10.2156, 10.2156] +24-11-19 20:27:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:01 | D | sum error = [ 66.2753, 71.3358, 77.0298, 83.3757, 89.3054] +24-11-19 20:27:01 | D | best error = [ 10.2156, 10.2156, 10.2156, 10.2156, 10.2156] +24-11-19 20:27:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:01 | D | sum error = [ 96.3185, 103.2885, 110.9639, 119.1696, 127.7372] +24-11-19 20:27:01 | D | best error = [ 10.2156, 10.2156, 10.2156, 10.2156, 10.2156] +24-11-19 20:27:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:01 | D | sum error = [ 137.7654, 148.2125, 159.1346, 171.3325, 184.3665] +24-11-19 20:27:01 | D | best error = [ 10.2156, 10.2156, 10.2156, 10.2156, 10.2156] +24-11-19 20:27:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:01 | D | sum error = [ 198.0718, 213.3784, 229.1936, 246.5111, 264.9831] +24-11-19 20:27:01 | D | best error = [ 10.2156, 10.2156, 10.2156, 10.2156, 10.2156] +24-11-19 20:27:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:01 | D | sum error = [ 284.9636, 305.9335, 329.3667, 353.7645, 379.3809] +24-11-19 20:27:01 | D | best error = [ 10.2156, 10.2156, 10.2156, 10.2156, 10.2156] +24-11-19 20:27:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:01 | D | sum error = [ 406.9555, 436.3145, 468.1131, 501.6405, 537.7142] +24-11-19 20:27:01 | D | best error = [ 10.2156, 10.2156, 10.2156, 10.2156, 10.2156] +24-11-19 20:27:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:01 | D | sum error = [ 576.0773, 617.3761, 661.7103, 708.0219, 757.9913] +24-11-19 20:27:01 | D | best error = [ 10.2156, 10.2156, 10.2156, 10.2156, 10.2156] +24-11-19 20:27:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:01 | D | sum error = [ 810.8553, 866.9732, 926.3581, 990.1465, 1056.6936] +24-11-19 20:27:01 | D | best error = [ 10.2156, 10.2156, 10.2156, 10.2156, 10.2156] +24-11-19 20:27:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:01 | D | sum error = [ 1127.4550, 1202.0739, 1280.0681, 1361.3131, 1446.3169] +24-11-19 20:27:01 | D | best error = [ 10.2156, 10.2156, 10.2156, 10.2156, 10.2156] +24-11-19 20:27:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:01 | D | sum error = [ 1534.5184, 1625.8497, 1718.8364, 1813.9602, 1909.7827] +24-11-19 20:27:01 | D | best error = [ 10.2156, 10.2156, 10.2156, 10.2156, 10.2156] +24-11-19 20:27:01 | D | + error = [10.2156] +24-11-19 20:27:01 | D | - Calibrating model.layers.12.self_attn.k_proj.weight +24-11-19 20:27:01 | D | + w: sint8 +24-11-19 20:27:01 | D | + x: None +24-11-19 20:27:01 | D | + y: None +24-11-19 20:27:01 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:27:01 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:27:01 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:27:01 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:27:02 | D | - range ratio = [ 1.0000] +24-11-19 20:27:02 | D | sum error = [ 10.6720] +24-11-19 20:27:02 | D | best error = [ 10.6720] +24-11-19 20:27:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:15 | D | sum error = [ 10.1358, 10.7488, 10.9434, 10.9704, 10.2688] +24-11-19 20:27:15 | D | best error = [ 10.1358, 10.1358, 10.1358, 10.1358, 10.1358] +24-11-19 20:27:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:15 | D | sum error = [ 11.4737, 11.5152, 12.3579, 12.9919, 13.2813] +24-11-19 20:27:15 | D | best error = [ 10.1358, 10.1358, 10.1358, 10.1358, 10.1358] +24-11-19 20:27:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:15 | D | sum error = [ 13.8299, 14.8177, 15.7308, 16.7498, 18.0393] +24-11-19 20:27:15 | D | best error = [ 10.1358, 10.1358, 10.1358, 10.1358, 10.1358] +24-11-19 20:27:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:15 | D | sum error = [ 19.4436, 20.8876, 23.0247, 24.2609, 26.5518] +24-11-19 20:27:15 | D | best error = [ 10.1358, 10.1358, 10.1358, 10.1358, 10.1358] +24-11-19 20:27:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:15 | D | sum error = [ 27.9508, 30.3753, 33.2516, 35.1210, 38.1178] +24-11-19 20:27:15 | D | best error = [ 10.1358, 10.1358, 10.1358, 10.1358, 10.1358] +24-11-19 20:27:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:15 | D | sum error = [ 40.4763, 43.6012, 47.2054, 51.2029, 54.0053] +24-11-19 20:27:15 | D | best error = [ 10.1358, 10.1358, 10.1358, 10.1358, 10.1358] +24-11-19 20:27:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:15 | D | sum error = [ 58.4740, 62.7040, 67.6500, 72.7841, 78.0659] +24-11-19 20:27:15 | D | best error = [ 10.1358, 10.1358, 10.1358, 10.1358, 10.1358] +24-11-19 20:27:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:15 | D | sum error = [ 83.9127, 90.8068, 97.6538, 104.8009, 113.0432] +24-11-19 20:27:15 | D | best error = [ 10.1358, 10.1358, 10.1358, 10.1358, 10.1358] +24-11-19 20:27:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:15 | D | sum error = [ 121.9547, 130.9239, 141.1861, 152.3291, 163.4382] +24-11-19 20:27:15 | D | best error = [ 10.1358, 10.1358, 10.1358, 10.1358, 10.1358] +24-11-19 20:27:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:15 | D | sum error = [ 177.2141, 191.5405, 205.6967, 220.7767, 238.3836] +24-11-19 20:27:15 | D | best error = [ 10.1358, 10.1358, 10.1358, 10.1358, 10.1358] +24-11-19 20:27:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:15 | D | sum error = [ 255.8036, 276.2228, 296.3820, 319.2443, 343.0045] +24-11-19 20:27:15 | D | best error = [ 10.1358, 10.1358, 10.1358, 10.1358, 10.1358] +24-11-19 20:27:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:15 | D | sum error = [ 369.4518, 396.6417, 426.9210, 459.7566, 493.2121] +24-11-19 20:27:15 | D | best error = [ 10.1358, 10.1358, 10.1358, 10.1358, 10.1358] +24-11-19 20:27:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:15 | D | sum error = [ 529.6482, 568.5294, 609.1559, 652.1058, 699.9004] +24-11-19 20:27:15 | D | best error = [ 10.1358, 10.1358, 10.1358, 10.1358, 10.1358] +24-11-19 20:27:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:15 | D | sum error = [ 751.1375, 804.6921, 861.9881, 924.3664, 991.1570] +24-11-19 20:27:15 | D | best error = [ 10.1358, 10.1358, 10.1358, 10.1358, 10.1358] +24-11-19 20:27:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:15 | D | sum error = [ 1062.3229, 1135.2994, 1213.0542, 1293.5901, 1379.0279] +24-11-19 20:27:15 | D | best error = [ 10.1358, 10.1358, 10.1358, 10.1358, 10.1358] +24-11-19 20:27:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:15 | D | sum error = [ 1465.3624, 1557.6447, 1652.2034, 1749.1732, 1844.8234] +24-11-19 20:27:15 | D | best error = [ 10.1358, 10.1358, 10.1358, 10.1358, 10.1358] +24-11-19 20:27:15 | D | + error = [10.1358] +24-11-19 20:27:15 | D | - Calibrating model.layers.12.self_attn.v_proj.weight +24-11-19 20:27:15 | D | + w: sint8 +24-11-19 20:27:15 | D | + x: None +24-11-19 20:27:15 | D | + y: None +24-11-19 20:27:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:15 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:27:15 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:27:15 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:27:15 | D | - range ratio = [ 1.0000] +24-11-19 20:27:15 | D | sum error = [ 4.6460] +24-11-19 20:27:15 | D | best error = [ 4.6460] +24-11-19 20:27:16 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:16 | D | sum error = [ 4.5951, 4.5832, 4.6234, 4.6631, 4.7592] +24-11-19 20:27:16 | D | best error = [ 4.3301, 4.2097, 4.1516, 4.1123, 4.0949] +24-11-19 20:27:16 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:16 | D | sum error = [ 4.8810, 5.0240, 5.2423, 5.4986, 5.7908] +24-11-19 20:27:16 | D | best error = [ 4.0869, 4.0830, 4.0818, 4.0816, 4.0815] +24-11-19 20:27:16 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:16 | D | sum error = [ 6.1179, 6.4929, 6.9257, 7.3961, 7.9224] +24-11-19 20:27:16 | D | best error = [ 4.0815, 4.0815, 4.0815, 4.0815, 4.0815] +24-11-19 20:27:16 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:16 | D | sum error = [ 8.4833, 9.0882, 9.7510, 10.4522, 11.2148] +24-11-19 20:27:16 | D | best error = [ 4.0815, 4.0815, 4.0815, 4.0815, 4.0815] +24-11-19 20:27:16 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:16 | D | sum error = [ 12.0061, 12.8747, 13.8080, 14.8002, 15.8065] +24-11-19 20:27:16 | D | best error = [ 4.0815, 4.0815, 4.0815, 4.0815, 4.0815] +24-11-19 20:27:16 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:16 | D | sum error = [ 16.9061, 18.0578, 19.2812, 20.5748, 21.9567] +24-11-19 20:27:16 | D | best error = [ 4.0815, 4.0815, 4.0815, 4.0815, 4.0815] +24-11-19 20:27:16 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:16 | D | sum error = [ 23.4131, 24.9263, 26.5569, 28.2512, 30.0624] +24-11-19 20:27:16 | D | best error = [ 4.0815, 4.0815, 4.0815, 4.0815, 4.0815] +24-11-19 20:27:16 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:16 | D | sum error = [ 31.9260, 33.9482, 36.0500, 38.2324, 40.5695] +24-11-19 20:27:16 | D | best error = [ 4.0815, 4.0815, 4.0815, 4.0815, 4.0815] +24-11-19 20:27:16 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:16 | D | sum error = [ 43.0098, 45.5928, 48.2897, 51.1404, 54.1304] +24-11-19 20:27:16 | D | best error = [ 4.0815, 4.0815, 4.0815, 4.0815, 4.0815] +24-11-19 20:27:16 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:16 | D | sum error = [ 57.2736, 60.5392, 63.9824, 67.5901, 71.3615] +24-11-19 20:27:16 | D | best error = [ 4.0815, 4.0815, 4.0815, 4.0815, 4.0815] +24-11-19 20:27:16 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:16 | D | sum error = [ 75.2950, 79.4385, 83.7500, 88.2728, 92.9957] +24-11-19 20:27:16 | D | best error = [ 4.0815, 4.0815, 4.0815, 4.0815, 4.0815] +24-11-19 20:27:16 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:16 | D | sum error = [ 97.9201, 103.0709, 108.4302, 114.0178, 119.8443] +24-11-19 20:27:16 | D | best error = [ 4.0815, 4.0815, 4.0815, 4.0815, 4.0815] +24-11-19 20:27:16 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:16 | D | sum error = [ 125.9305, 132.2545, 138.8344, 145.6705, 152.7721] +24-11-19 20:27:16 | D | best error = [ 4.0815, 4.0815, 4.0815, 4.0815, 4.0815] +24-11-19 20:27:16 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:16 | D | sum error = [ 160.1588, 167.8082, 175.7314, 183.9616, 192.4701] +24-11-19 20:27:16 | D | best error = [ 4.0815, 4.0815, 4.0815, 4.0815, 4.0815] +24-11-19 20:27:16 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:16 | D | sum error = [ 201.2919, 210.4158, 219.8473, 229.6083, 239.6799] +24-11-19 20:27:16 | D | best error = [ 4.0815, 4.0815, 4.0815, 4.0815, 4.0815] +24-11-19 20:27:16 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:16 | D | sum error = [ 250.0824, 260.8103, 271.8639, 283.2437, 294.9720] +24-11-19 20:27:16 | D | best error = [ 4.0815, 4.0815, 4.0815, 4.0815, 4.0815] +24-11-19 20:27:16 | D | + error = [4.0815] +24-11-19 20:27:16 | D | - Calibrating model.layers.12.self_attn.o_proj.weight +24-11-19 20:27:16 | D | + w: sint8 +24-11-19 20:27:16 | D | + x: None +24-11-19 20:27:16 | D | + y: None +24-11-19 20:27:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:16 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:27:16 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:27:16 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:27:16 | D | - range ratio = [ 1.0000] +24-11-19 20:27:16 | D | sum error = [ 1.1830] +24-11-19 20:27:16 | D | best error = [ 1.1830] +24-11-19 20:27:16 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:16 | D | sum error = [ 1.1708, 1.1591, 1.1589, 1.1621, 1.1669] +24-11-19 20:27:16 | D | best error = [ 1.1019, 1.0620, 1.0378, 1.0220, 1.0095] +24-11-19 20:27:16 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:16 | D | sum error = [ 1.1712, 1.1853, 1.2072, 1.2297, 1.2699] +24-11-19 20:27:16 | D | best error = [ 1.0010, 0.9940, 0.9883, 0.9838, 0.9810] +24-11-19 20:27:16 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:16 | D | sum error = [ 1.3103, 1.3594, 1.4177, 1.4816, 1.5493] +24-11-19 20:27:16 | D | best error = [ 0.9783, 0.9765, 0.9750, 0.9739, 0.9730] +24-11-19 20:27:16 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:16 | D | sum error = [ 1.6307, 1.7241, 1.8169, 1.9257, 2.0410] +24-11-19 20:27:16 | D | best error = [ 0.9725, 0.9722, 0.9718, 0.9713, 0.9712] +24-11-19 20:27:16 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:16 | D | sum error = [ 2.1685, 2.3058, 2.4536, 2.6061, 2.7788] +24-11-19 20:27:16 | D | best error = [ 0.9710, 0.9709, 0.9708, 0.9708, 0.9707] +24-11-19 20:27:16 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:16 | D | sum error = [ 2.9583, 3.1539, 3.3595, 3.5745, 3.8095] +24-11-19 20:27:16 | D | best error = [ 0.9707, 0.9707, 0.9707, 0.9707, 0.9707] +24-11-19 20:27:16 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:16 | D | sum error = [ 4.0576, 4.3172, 4.5945, 4.8904, 5.1987] +24-11-19 20:27:16 | D | best error = [ 0.9707, 0.9706, 0.9706, 0.9706, 0.9706] +24-11-19 20:27:16 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:16 | D | sum error = [ 5.5273, 5.8683, 6.2345, 6.6239, 7.0279] +24-11-19 20:27:16 | D | best error = [ 0.9706, 0.9706, 0.9706, 0.9706, 0.9706] +24-11-19 20:27:16 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:16 | D | sum error = [ 7.4588, 7.9103, 8.3835, 8.8857, 9.4143] +24-11-19 20:27:16 | D | best error = [ 0.9706, 0.9706, 0.9706, 0.9706, 0.9706] +24-11-19 20:27:16 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:16 | D | sum error = [ 9.9682, 10.5527, 11.1622, 11.8066, 12.4819] +24-11-19 20:27:16 | D | best error = [ 0.9706, 0.9706, 0.9706, 0.9706, 0.9706] +24-11-19 20:27:16 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:16 | D | sum error = [ 13.1972, 13.9407, 14.7245, 15.5442, 16.4034] +24-11-19 20:27:16 | D | best error = [ 0.9706, 0.9706, 0.9706, 0.9706, 0.9706] +24-11-19 20:27:16 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:16 | D | sum error = [ 17.3023, 18.2405, 19.2253, 20.2515, 21.3237] +24-11-19 20:27:16 | D | best error = [ 0.9706, 0.9706, 0.9706, 0.9706, 0.9706] +24-11-19 20:27:16 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:16 | D | sum error = [ 22.4462, 23.6141, 24.8381, 26.1102, 27.4364] +24-11-19 20:27:16 | D | best error = [ 0.9706, 0.9706, 0.9706, 0.9706, 0.9706] +24-11-19 20:27:16 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:16 | D | sum error = [ 28.8192, 30.2598, 31.7585, 33.3147, 34.9369] +24-11-19 20:27:16 | D | best error = [ 0.9706, 0.9706, 0.9706, 0.9706, 0.9706] +24-11-19 20:27:16 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:16 | D | sum error = [ 36.6198, 38.3655, 40.1766, 42.0548, 44.0043] +24-11-19 20:27:16 | D | best error = [ 0.9706, 0.9706, 0.9706, 0.9706, 0.9706] +24-11-19 20:27:16 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:16 | D | sum error = [ 46.0216, 48.1050, 50.2553, 52.4797, 54.7766] +24-11-19 20:27:16 | D | best error = [ 0.9706, 0.9706, 0.9706, 0.9706, 0.9706] +24-11-19 20:27:16 | D | + error = [0.9706] +24-11-19 20:27:16 | D | - Calibrating model.layers.12.mlp.up_proj.weight +24-11-19 20:27:16 | D | + w: sint8 +24-11-19 20:27:16 | D | + x: None +24-11-19 20:27:16 | D | + y: None +24-11-19 20:27:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:16 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:27:17 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:27:17 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:27:17 | D | - range ratio = [ 1.0000] +24-11-19 20:27:17 | D | sum error = [ 6.1529] +24-11-19 20:27:17 | D | best error = [ 6.1529] +24-11-19 20:27:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:18 | D | sum error = [ 6.1113, 6.0890, 6.1191, 6.1868, 6.3089] +24-11-19 20:27:18 | D | best error = [ 5.7407, 5.5776, 5.4921, 5.4429, 5.4177] +24-11-19 20:27:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:18 | D | sum error = [ 6.4505, 6.6849, 6.9268, 7.2820, 7.6472] +24-11-19 20:27:18 | D | best error = [ 5.4061, 5.4012, 5.3991, 5.3985, 5.3984] +24-11-19 20:27:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:18 | D | sum error = [ 8.0934, 8.6082, 9.1644, 9.7618, 10.4474] +24-11-19 20:27:18 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 20:27:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:18 | D | sum error = [ 11.2022, 11.9927, 12.8627, 13.7796, 14.7703] +24-11-19 20:27:18 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 20:27:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:18 | D | sum error = [ 15.8322, 16.9703, 18.1541, 19.4294, 20.7887] +24-11-19 20:27:18 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 20:27:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:18 | D | sum error = [ 22.2257, 23.7495, 25.3587, 27.0507, 28.8562] +24-11-19 20:27:18 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 20:27:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:18 | D | sum error = [ 30.7625, 32.7605, 34.8824, 37.1083, 39.4631] +24-11-19 20:27:18 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 20:27:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:18 | D | sum error = [ 41.9426, 44.5368, 47.2797, 50.1552, 53.1828] +24-11-19 20:27:18 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 20:27:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:18 | D | sum error = [ 56.3459, 59.6816, 63.1748, 66.8439, 70.7058] +24-11-19 20:27:18 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 20:27:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:18 | D | sum error = [ 74.7466, 78.9585, 83.3819, 88.0134, 92.8767] +24-11-19 20:27:18 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 20:27:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:18 | D | sum error = [ 97.9492, 103.2418, 108.7807, 114.5684, 120.6131] +24-11-19 20:27:18 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 20:27:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:18 | D | sum error = [ 126.9092, 133.4862, 140.3345, 147.4698, 154.9040] +24-11-19 20:27:18 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 20:27:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:18 | D | sum error = [ 162.6446, 170.6893, 179.0632, 187.7674, 196.8151] +24-11-19 20:27:18 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 20:27:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:18 | D | sum error = [ 206.2054, 215.9488, 226.0512, 236.5272, 247.3550] +24-11-19 20:27:18 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 20:27:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:18 | D | sum error = [ 258.5877, 270.1927, 282.1895, 294.5795, 307.3654] +24-11-19 20:27:18 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 20:27:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:18 | D | sum error = [ 320.5621, 334.1616, 348.1720, 362.5982, 377.4407] +24-11-19 20:27:18 | D | best error = [ 5.3984, 5.3984, 5.3984, 5.3984, 5.3984] +24-11-19 20:27:18 | D | + error = [5.3984] +24-11-19 20:27:18 | D | - Calibrating model.layers.12.mlp.gate_proj.weight +24-11-19 20:27:18 | D | + w: sint8 +24-11-19 20:27:18 | D | + x: None +24-11-19 20:27:18 | D | + y: None +24-11-19 20:27:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:18 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:27:18 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:27:18 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:27:18 | D | - range ratio = [ 1.0000] +24-11-19 20:27:18 | D | sum error = [ 6.4121] +24-11-19 20:27:18 | D | best error = [ 6.4121] +24-11-19 20:27:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:19 | D | sum error = [ 6.3729, 6.3466, 6.3862, 6.4430, 6.5697] +24-11-19 20:27:19 | D | best error = [ 5.9821, 5.8120, 5.7248, 5.6761, 5.6494] +24-11-19 20:27:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:19 | D | sum error = [ 6.7513, 6.9808, 7.2659, 7.6064, 8.0019] +24-11-19 20:27:19 | D | best error = [ 5.6367, 5.6310, 5.6289, 5.6283, 5.6281] +24-11-19 20:27:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:19 | D | sum error = [ 8.4809, 9.0039, 9.5971, 10.2544, 10.9897] +24-11-19 20:27:19 | D | best error = [ 5.6281, 5.6281, 5.6281, 5.6281, 5.6281] +24-11-19 20:27:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:19 | D | sum error = [ 11.7751, 12.6341, 13.5449, 14.5291, 15.5915] +24-11-19 20:27:19 | D | best error = [ 5.6281, 5.6281, 5.6281, 5.6281, 5.6281] +24-11-19 20:27:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:19 | D | sum error = [ 16.7315, 17.9440, 19.2317, 20.6146, 22.0722] +24-11-19 20:27:19 | D | best error = [ 5.6281, 5.6281, 5.6281, 5.6281, 5.6281] +24-11-19 20:27:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:19 | D | sum error = [ 23.6375, 25.3001, 27.0532, 28.9068, 30.9015] +24-11-19 20:27:19 | D | best error = [ 5.6281, 5.6281, 5.6281, 5.6281, 5.6281] +24-11-19 20:27:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:19 | D | sum error = [ 32.9750, 35.2034, 37.5529, 40.0468, 42.6939] +24-11-19 20:27:19 | D | best error = [ 5.6281, 5.6281, 5.6281, 5.6281, 5.6281] +24-11-19 20:27:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:19 | D | sum error = [ 45.5000, 48.4498, 51.5872, 54.8872, 58.3713] +24-11-19 20:27:19 | D | best error = [ 5.6281, 5.6281, 5.6281, 5.6281, 5.6281] +24-11-19 20:27:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:19 | D | sum error = [ 62.0745, 65.9894, 70.1388, 74.5005, 79.1158] +24-11-19 20:27:19 | D | best error = [ 5.6281, 5.6281, 5.6281, 5.6281, 5.6281] +24-11-19 20:27:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:19 | D | sum error = [ 83.9698, 89.1094, 94.5357, 100.2258, 106.2469] +24-11-19 20:27:19 | D | best error = [ 5.6281, 5.6281, 5.6281, 5.6281, 5.6281] +24-11-19 20:27:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:19 | D | sum error = [ 112.5875, 119.2593, 126.2836, 133.6656, 141.4286] +24-11-19 20:27:19 | D | best error = [ 5.6281, 5.6281, 5.6281, 5.6281, 5.6281] +24-11-19 20:27:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:19 | D | sum error = [ 149.5785, 158.1300, 167.0977, 176.5112, 186.3890] +24-11-19 20:27:19 | D | best error = [ 5.6281, 5.6281, 5.6281, 5.6281, 5.6281] +24-11-19 20:27:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:19 | D | sum error = [ 196.7274, 207.5537, 218.8839, 230.7356, 243.1461] +24-11-19 20:27:19 | D | best error = [ 5.6281, 5.6281, 5.6281, 5.6281, 5.6281] +24-11-19 20:27:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:19 | D | sum error = [ 256.0960, 269.6226, 283.7197, 298.4067, 313.6749] +24-11-19 20:27:19 | D | best error = [ 5.6281, 5.6281, 5.6281, 5.6281, 5.6281] +24-11-19 20:27:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:19 | D | sum error = [ 329.5681, 346.0872, 363.2230, 380.9702, 399.3640] +24-11-19 20:27:19 | D | best error = [ 5.6281, 5.6281, 5.6281, 5.6281, 5.6281] +24-11-19 20:27:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:19 | D | sum error = [ 418.4125, 438.0949, 458.4323, 479.4138, 501.0417] +24-11-19 20:27:19 | D | best error = [ 5.6281, 5.6281, 5.6281, 5.6281, 5.6281] +24-11-19 20:27:19 | D | + error = [5.6281] +24-11-19 20:27:19 | D | - Calibrating model.layers.12.mlp.down_proj.weight +24-11-19 20:27:19 | D | + w: sint8 +24-11-19 20:27:19 | D | + x: None +24-11-19 20:27:19 | D | + y: None +24-11-19 20:27:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:19 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:27:19 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:27:20 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:27:20 | D | - range ratio = [ 1.0000] +24-11-19 20:27:20 | D | sum error = [ 1.5792] +24-11-19 20:27:20 | D | best error = [ 1.5792] +24-11-19 20:27:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:21 | D | sum error = [ 1.5652, 1.5541, 1.5507, 1.5436, 1.5460] +24-11-19 20:27:21 | D | best error = [ 1.5245, 1.4961, 1.4779, 1.4644, 1.4540] +24-11-19 20:27:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:21 | D | sum error = [ 1.5534, 1.5658, 1.5870, 1.6129, 1.6502] +24-11-19 20:27:21 | D | best error = [ 1.4459, 1.4407, 1.4366, 1.4341, 1.4321] +24-11-19 20:27:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:21 | D | sum error = [ 1.6921, 1.7471, 1.8147, 1.8886, 1.9763] +24-11-19 20:27:21 | D | best error = [ 1.4308, 1.4301, 1.4296, 1.4293, 1.4292] +24-11-19 20:27:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:21 | D | sum error = [ 2.0784, 2.1866, 2.3105, 2.4468, 2.5972] +24-11-19 20:27:21 | D | best error = [ 1.4291, 1.4290, 1.4290, 1.4290, 1.4290] +24-11-19 20:27:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:21 | D | sum error = [ 2.7632, 2.9411, 3.1337, 3.3458, 3.5715] +24-11-19 20:27:21 | D | best error = [ 1.4290, 1.4290, 1.4289, 1.4289, 1.4289] +24-11-19 20:27:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:21 | D | sum error = [ 3.8094, 4.0697, 4.3495, 4.6474, 4.9628] +24-11-19 20:27:21 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 20:27:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:21 | D | sum error = [ 5.3026, 5.6600, 6.0441, 6.4514, 6.8823] +24-11-19 20:27:21 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 20:27:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:21 | D | sum error = [ 7.3408, 7.8274, 8.3449, 8.8893, 9.4649] +24-11-19 20:27:21 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 20:27:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:21 | D | sum error = [ 10.0717, 10.7163, 11.3969, 12.1158, 12.8724] +24-11-19 20:27:21 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 20:27:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:21 | D | sum error = [ 13.6713, 14.5156, 15.4050, 16.3401, 17.3199] +24-11-19 20:27:21 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 20:27:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:21 | D | sum error = [ 18.3562, 19.4422, 20.5820, 21.7799, 23.0384] +24-11-19 20:27:21 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 20:27:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:21 | D | sum error = [ 24.3570, 25.7388, 27.1876, 28.7019, 30.2873] +24-11-19 20:27:21 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 20:27:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:21 | D | sum error = [ 31.9442, 33.6756, 35.4842, 37.3717, 39.3379] +24-11-19 20:27:21 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 20:27:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:21 | D | sum error = [ 41.3903, 43.5266, 45.7519, 48.0703, 50.4720] +24-11-19 20:27:21 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 20:27:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:21 | D | sum error = [ 52.9744, 55.5702, 58.2660, 61.0583, 63.9523] +24-11-19 20:27:21 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 20:27:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:21 | D | sum error = [ 66.9517, 70.0509, 73.2585, 76.5744, 79.9973] +24-11-19 20:27:21 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 20:27:21 | D | + error = [1.4289] +24-11-19 20:27:21 | D | - Quantizing model.layers.12.self_attn.q_proj.weight +24-11-19 20:27:23 | D | - Quantizing model.layers.12.self_attn.k_proj.weight +24-11-19 20:27:25 | D | - Quantizing model.layers.12.self_attn.v_proj.weight +24-11-19 20:27:26 | D | - Quantizing model.layers.12.self_attn.o_proj.weight +24-11-19 20:27:29 | D | - Quantizing model.layers.12.mlp.up_proj.weight +24-11-19 20:27:30 | D | - Quantizing model.layers.12.mlp.gate_proj.weight +24-11-19 20:27:31 | D | - Quantizing model.layers.12.mlp.down_proj.weight +24-11-19 20:27:39 | D | - Quantizing layer model.layers.13 +24-11-19 20:27:39 | D | - Calibrating model.layers.13.self_attn.q_proj.weight +24-11-19 20:27:39 | D | + w: sint8 +24-11-19 20:27:39 | D | + x: None +24-11-19 20:27:39 | D | + y: None +24-11-19 20:27:39 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:27:39 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:27:39 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:27:40 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:27:40 | D | - range ratio = [ 1.0000] +24-11-19 20:27:40 | D | sum error = [ 10.1528] +24-11-19 20:27:40 | D | best error = [ 10.1528] +24-11-19 20:27:53 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:53 | D | sum error = [ 10.0493, 10.1120, 10.1803, 10.2111, 10.5357] +24-11-19 20:27:53 | D | best error = [ 10.0493, 10.0493, 10.0493, 10.0493, 10.0493] +24-11-19 20:27:53 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:53 | D | sum error = [ 10.9191, 11.0354, 11.5165, 12.3289, 12.9095] +24-11-19 20:27:53 | D | best error = [ 10.0493, 10.0493, 10.0493, 10.0493, 10.0493] +24-11-19 20:27:53 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:53 | D | sum error = [ 13.4529, 14.6934, 15.7267, 16.9228, 18.2481] +24-11-19 20:27:53 | D | best error = [ 10.0493, 10.0493, 10.0493, 10.0493, 10.0493] +24-11-19 20:27:53 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:53 | D | sum error = [ 19.5538, 21.1655, 23.0820, 25.2300, 27.4587] +24-11-19 20:27:53 | D | best error = [ 10.0493, 10.0493, 10.0493, 10.0493, 10.0493] +24-11-19 20:27:53 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:53 | D | sum error = [ 29.3684, 32.3996, 35.1843, 38.0179, 41.1187] +24-11-19 20:27:53 | D | best error = [ 10.0493, 10.0493, 10.0493, 10.0493, 10.0493] +24-11-19 20:27:53 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:53 | D | sum error = [ 45.1153, 49.0119, 53.5423, 57.9515, 62.9914] +24-11-19 20:27:53 | D | best error = [ 10.0493, 10.0493, 10.0493, 10.0493, 10.0493] +24-11-19 20:27:53 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:53 | D | sum error = [ 69.0684, 74.9136, 81.2400, 88.5763, 96.0382] +24-11-19 20:27:53 | D | best error = [ 10.0493, 10.0493, 10.0493, 10.0493, 10.0493] +24-11-19 20:27:53 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:53 | D | sum error = [ 104.2590, 112.9528, 122.1203, 132.0133, 142.5995] +24-11-19 20:27:53 | D | best error = [ 10.0493, 10.0493, 10.0493, 10.0493, 10.0493] +24-11-19 20:27:53 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:53 | D | sum error = [ 153.9806, 166.4617, 179.5320, 193.3330, 208.0289] +24-11-19 20:27:53 | D | best error = [ 10.0493, 10.0493, 10.0493, 10.0493, 10.0493] +24-11-19 20:27:53 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:53 | D | sum error = [ 223.7039, 240.8655, 258.7454, 278.1715, 299.3680] +24-11-19 20:27:53 | D | best error = [ 10.0493, 10.0493, 10.0493, 10.0493, 10.0493] +24-11-19 20:27:53 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:53 | D | sum error = [ 321.4943, 345.1162, 370.4524, 397.9837, 427.4495] +24-11-19 20:27:53 | D | best error = [ 10.0493, 10.0493, 10.0493, 10.0493, 10.0493] +24-11-19 20:27:53 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:53 | D | sum error = [ 458.3143, 491.6456, 527.7270, 565.5378, 606.7475] +24-11-19 20:27:53 | D | best error = [ 10.0493, 10.0493, 10.0493, 10.0493, 10.0493] +24-11-19 20:27:53 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:53 | D | sum error = [ 650.7508, 698.0127, 748.4683, 802.5140, 860.2325] +24-11-19 20:27:53 | D | best error = [ 10.0493, 10.0493, 10.0493, 10.0493, 10.0493] +24-11-19 20:27:53 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:53 | D | sum error = [ 922.1695, 988.6194, 1059.4315, 1134.7532, 1214.8362] +24-11-19 20:27:53 | D | best error = [ 10.0493, 10.0493, 10.0493, 10.0493, 10.0493] +24-11-19 20:27:53 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:53 | D | sum error = [ 1299.9984, 1391.0810, 1487.0057, 1588.0398, 1695.0472] +24-11-19 20:27:53 | D | best error = [ 10.0493, 10.0493, 10.0493, 10.0493, 10.0493] +24-11-19 20:27:53 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:53 | D | sum error = [ 1806.9905, 1923.9183, 2044.5623, 2169.0099, 2294.3559] +24-11-19 20:27:53 | D | best error = [ 10.0493, 10.0493, 10.0493, 10.0493, 10.0493] +24-11-19 20:27:53 | D | + error = [10.0493] +24-11-19 20:27:53 | D | - Calibrating model.layers.13.self_attn.k_proj.weight +24-11-19 20:27:53 | D | + w: sint8 +24-11-19 20:27:53 | D | + x: None +24-11-19 20:27:53 | D | + y: None +24-11-19 20:27:53 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:27:53 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:27:54 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:27:54 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:27:54 | D | - range ratio = [ 1.0000] +24-11-19 20:27:54 | D | sum error = [ 10.4725] +24-11-19 20:27:54 | D | best error = [ 10.4725] +24-11-19 20:28:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:07 | D | sum error = [ 10.2398, 10.4685, 10.5925, 10.7021, 11.3139] +24-11-19 20:28:07 | D | best error = [ 10.2398, 10.2398, 10.2398, 10.2398, 10.2398] +24-11-19 20:28:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:07 | D | sum error = [ 11.1215, 12.2523, 11.9387, 13.2679, 13.3789] +24-11-19 20:28:07 | D | best error = [ 10.2398, 10.2398, 10.2398, 10.2398, 10.2398] +24-11-19 20:28:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:07 | D | sum error = [ 14.7884, 15.3675, 16.9605, 18.2291, 18.4553] +24-11-19 20:28:07 | D | best error = [ 10.2398, 10.2398, 10.2398, 10.2398, 10.2398] +24-11-19 20:28:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:07 | D | sum error = [ 20.2250, 21.7495, 23.7512, 25.5481, 27.5618] +24-11-19 20:28:07 | D | best error = [ 10.2398, 10.2398, 10.2398, 10.2398, 10.2398] +24-11-19 20:28:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:07 | D | sum error = [ 29.5875, 32.2682, 34.2924, 38.1157, 41.0867] +24-11-19 20:28:07 | D | best error = [ 10.2398, 10.2398, 10.2398, 10.2398, 10.2398] +24-11-19 20:28:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:07 | D | sum error = [ 44.1088, 48.8891, 52.6246, 56.3210, 60.9478] +24-11-19 20:28:07 | D | best error = [ 10.2398, 10.2398, 10.2398, 10.2398, 10.2398] +24-11-19 20:28:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:07 | D | sum error = [ 66.0958, 71.5973, 77.9347, 84.5941, 92.2900] +24-11-19 20:28:07 | D | best error = [ 10.2398, 10.2398, 10.2398, 10.2398, 10.2398] +24-11-19 20:28:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:07 | D | sum error = [ 98.6912, 107.5931, 116.2133, 125.0222, 135.7300] +24-11-19 20:28:07 | D | best error = [ 10.2398, 10.2398, 10.2398, 10.2398, 10.2398] +24-11-19 20:28:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:07 | D | sum error = [ 147.2983, 159.1238, 171.8270, 185.4188, 199.8178] +24-11-19 20:28:07 | D | best error = [ 10.2398, 10.2398, 10.2398, 10.2398, 10.2398] +24-11-19 20:28:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:07 | D | sum error = [ 215.2987, 232.7359, 250.1040, 270.5337, 290.6378] +24-11-19 20:28:07 | D | best error = [ 10.2398, 10.2398, 10.2398, 10.2398, 10.2398] +24-11-19 20:28:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:07 | D | sum error = [ 313.5474, 336.8077, 362.9145, 389.0234, 419.3632] +24-11-19 20:28:07 | D | best error = [ 10.2398, 10.2398, 10.2398, 10.2398, 10.2398] +24-11-19 20:28:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:07 | D | sum error = [ 451.1736, 485.6692, 523.1117, 562.8668, 605.0295] +24-11-19 20:28:07 | D | best error = [ 10.2398, 10.2398, 10.2398, 10.2398, 10.2398] +24-11-19 20:28:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:07 | D | sum error = [ 651.4150, 699.5029, 752.8333, 808.8422, 869.6805] +24-11-19 20:28:07 | D | best error = [ 10.2398, 10.2398, 10.2398, 10.2398, 10.2398] +24-11-19 20:28:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:07 | D | sum error = [ 935.5877, 1006.0691, 1081.9122, 1160.3016, 1245.7423] +24-11-19 20:28:07 | D | best error = [ 10.2398, 10.2398, 10.2398, 10.2398, 10.2398] +24-11-19 20:28:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:07 | D | sum error = [ 1336.6639, 1434.8101, 1533.8459, 1639.6096, 1752.8900] +24-11-19 20:28:07 | D | best error = [ 10.2398, 10.2398, 10.2398, 10.2398, 10.2398] +24-11-19 20:28:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:07 | D | sum error = [ 1867.0960, 1987.4286, 2109.5819, 2235.0961, 2359.6572] +24-11-19 20:28:07 | D | best error = [ 10.2398, 10.2398, 10.2398, 10.2398, 10.2398] +24-11-19 20:28:07 | D | + error = [10.2398] +24-11-19 20:28:08 | D | - Calibrating model.layers.13.self_attn.v_proj.weight +24-11-19 20:28:08 | D | + w: sint8 +24-11-19 20:28:08 | D | + x: None +24-11-19 20:28:08 | D | + y: None +24-11-19 20:28:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:08 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:08 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:08 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:08 | D | - range ratio = [ 1.0000] +24-11-19 20:28:08 | D | sum error = [ 4.8723] +24-11-19 20:28:08 | D | best error = [ 4.8723] +24-11-19 20:28:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:08 | D | sum error = [ 4.8572, 4.8475, 4.8927, 4.9404, 5.0350] +24-11-19 20:28:08 | D | best error = [ 4.5667, 4.4405, 4.3757, 4.3400, 4.3215] +24-11-19 20:28:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:08 | D | sum error = [ 5.1418, 5.3158, 5.5353, 5.7934, 6.0989] +24-11-19 20:28:08 | D | best error = [ 4.3122, 4.3075, 4.3062, 4.3056, 4.3054] +24-11-19 20:28:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:08 | D | sum error = [ 6.4863, 6.8475, 7.3028, 7.8129, 8.3450] +24-11-19 20:28:08 | D | best error = [ 4.3053, 4.3053, 4.3053, 4.3053, 4.3053] +24-11-19 20:28:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:08 | D | sum error = [ 8.9099, 9.5647, 10.2552, 10.9906, 11.7626] +24-11-19 20:28:08 | D | best error = [ 4.3053, 4.3053, 4.3053, 4.3053, 4.3053] +24-11-19 20:28:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:08 | D | sum error = [ 12.6247, 13.4881, 14.4501, 15.4498, 16.5291] +24-11-19 20:28:08 | D | best error = [ 4.3053, 4.3053, 4.3053, 4.3053, 4.3053] +24-11-19 20:28:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:08 | D | sum error = [ 17.6578, 18.8804, 20.1467, 21.5060, 22.9195] +24-11-19 20:28:08 | D | best error = [ 4.3053, 4.3053, 4.3053, 4.3053, 4.3053] +24-11-19 20:28:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:08 | D | sum error = [ 24.4166, 26.0179, 27.6721, 29.4330, 31.2971] +24-11-19 20:28:08 | D | best error = [ 4.3053, 4.3053, 4.3053, 4.3053, 4.3053] +24-11-19 20:28:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:08 | D | sum error = [ 33.2407, 35.3172, 37.4806, 39.7674, 42.1664] +24-11-19 20:28:08 | D | best error = [ 4.3053, 4.3053, 4.3053, 4.3053, 4.3053] +24-11-19 20:28:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:08 | D | sum error = [ 44.6824, 47.3394, 50.1086, 53.0266, 56.1022] +24-11-19 20:28:08 | D | best error = [ 4.3053, 4.3053, 4.3053, 4.3053, 4.3053] +24-11-19 20:28:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:08 | D | sum error = [ 59.2943, 62.6705, 66.1808, 69.8463, 73.6888] +24-11-19 20:28:08 | D | best error = [ 4.3053, 4.3053, 4.3053, 4.3053, 4.3053] +24-11-19 20:28:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:08 | D | sum error = [ 77.6996, 81.8889, 86.2709, 90.8357, 95.6036] +24-11-19 20:28:08 | D | best error = [ 4.3053, 4.3053, 4.3053, 4.3053, 4.3053] +24-11-19 20:28:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:08 | D | sum error = [ 100.5853, 105.7536, 111.1545, 116.7751, 122.6124] +24-11-19 20:28:08 | D | best error = [ 4.3053, 4.3053, 4.3053, 4.3053, 4.3053] +24-11-19 20:28:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:08 | D | sum error = [ 128.7001, 135.0241, 141.5892, 148.4094, 155.4732] +24-11-19 20:28:08 | D | best error = [ 4.3053, 4.3053, 4.3053, 4.3053, 4.3053] +24-11-19 20:28:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:08 | D | sum error = [ 162.7970, 170.4017, 178.2884, 186.4414, 194.8808] +24-11-19 20:28:08 | D | best error = [ 4.3053, 4.3053, 4.3053, 4.3053, 4.3053] +24-11-19 20:28:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:08 | D | sum error = [ 203.6059, 212.6178, 221.9265, 231.5293, 241.4429] +24-11-19 20:28:08 | D | best error = [ 4.3053, 4.3053, 4.3053, 4.3053, 4.3053] +24-11-19 20:28:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:08 | D | sum error = [ 251.6552, 262.1864, 273.0400, 284.2096, 295.7077] +24-11-19 20:28:08 | D | best error = [ 4.3053, 4.3053, 4.3053, 4.3053, 4.3053] +24-11-19 20:28:08 | D | + error = [4.3053] +24-11-19 20:28:08 | D | - Calibrating model.layers.13.self_attn.o_proj.weight +24-11-19 20:28:08 | D | + w: sint8 +24-11-19 20:28:08 | D | + x: None +24-11-19 20:28:08 | D | + y: None +24-11-19 20:28:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:08 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:08 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:09 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:09 | D | - range ratio = [ 1.0000] +24-11-19 20:28:09 | D | sum error = [ 1.3072] +24-11-19 20:28:09 | D | best error = [ 1.3072] +24-11-19 20:28:09 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:09 | D | sum error = [ 1.2981, 1.2913, 1.2808, 1.2907, 1.3001] +24-11-19 20:28:09 | D | best error = [ 1.2181, 1.1783, 1.1527, 1.1367, 1.1241] +24-11-19 20:28:09 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:09 | D | sum error = [ 1.3081, 1.3286, 1.3612, 1.3943, 1.4382] +24-11-19 20:28:09 | D | best error = [ 1.1146, 1.1071, 1.1019, 1.0980, 1.0954] +24-11-19 20:28:09 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:09 | D | sum error = [ 1.4833, 1.5456, 1.6205, 1.6994, 1.7903] +24-11-19 20:28:09 | D | best error = [ 1.0932, 1.0917, 1.0903, 1.0891, 1.0885] +24-11-19 20:28:09 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:09 | D | sum error = [ 1.8816, 1.9999, 2.1176, 2.2471, 2.3891] +24-11-19 20:28:09 | D | best error = [ 1.0878, 1.0872, 1.0867, 1.0863, 1.0861] +24-11-19 20:28:09 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:09 | D | sum error = [ 2.5437, 2.7013, 2.8758, 3.0680, 3.2699] +24-11-19 20:28:09 | D | best error = [ 1.0860, 1.0859, 1.0858, 1.0857, 1.0857] +24-11-19 20:28:09 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:09 | D | sum error = [ 3.4814, 3.7086, 3.9449, 4.2047, 4.4795] +24-11-19 20:28:09 | D | best error = [ 1.0857, 1.0857, 1.0857, 1.0856, 1.0856] +24-11-19 20:28:09 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:09 | D | sum error = [ 4.7648, 5.0749, 5.3988, 5.7357, 6.1025] +24-11-19 20:28:09 | D | best error = [ 1.0856, 1.0856, 1.0856, 1.0856, 1.0856] +24-11-19 20:28:09 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:09 | D | sum error = [ 6.4849, 6.8837, 7.3098, 7.7640, 8.2353] +24-11-19 20:28:09 | D | best error = [ 1.0856, 1.0856, 1.0856, 1.0856, 1.0856] +24-11-19 20:28:09 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:09 | D | sum error = [ 8.7347, 9.2636, 9.8194, 10.4041, 11.0177] +24-11-19 20:28:09 | D | best error = [ 1.0856, 1.0856, 1.0856, 1.0856, 1.0856] +24-11-19 20:28:09 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:09 | D | sum error = [ 11.6639, 12.3435, 13.0566, 13.8086, 14.5902] +24-11-19 20:28:09 | D | best error = [ 1.0856, 1.0856, 1.0856, 1.0856, 1.0856] +24-11-19 20:28:09 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:09 | D | sum error = [ 15.4199, 16.2822, 17.1921, 18.1446, 19.1412] +24-11-19 20:28:09 | D | best error = [ 1.0856, 1.0856, 1.0856, 1.0856, 1.0856] +24-11-19 20:28:09 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:09 | D | sum error = [ 20.1821, 21.2772, 22.4199, 23.6131, 24.8632] +24-11-19 20:28:09 | D | best error = [ 1.0856, 1.0856, 1.0856, 1.0856, 1.0856] +24-11-19 20:28:09 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:09 | D | sum error = [ 26.1630, 27.5181, 28.9334, 30.4093, 31.9463] +24-11-19 20:28:09 | D | best error = [ 1.0856, 1.0856, 1.0856, 1.0856, 1.0856] +24-11-19 20:28:09 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:09 | D | sum error = [ 33.5426, 35.2102, 36.9417, 38.7360, 40.6043] +24-11-19 20:28:09 | D | best error = [ 1.0856, 1.0856, 1.0856, 1.0856, 1.0856] +24-11-19 20:28:09 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:09 | D | sum error = [ 42.5423, 44.5532, 46.6383, 48.7978, 51.0398] +24-11-19 20:28:09 | D | best error = [ 1.0856, 1.0856, 1.0856, 1.0856, 1.0856] +24-11-19 20:28:09 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:09 | D | sum error = [ 53.3609, 55.7648, 58.2500, 60.8171, 63.4716] +24-11-19 20:28:09 | D | best error = [ 1.0856, 1.0856, 1.0856, 1.0856, 1.0856] +24-11-19 20:28:09 | D | + error = [1.0856] +24-11-19 20:28:09 | D | - Calibrating model.layers.13.mlp.up_proj.weight +24-11-19 20:28:09 | D | + w: sint8 +24-11-19 20:28:09 | D | + x: None +24-11-19 20:28:09 | D | + y: None +24-11-19 20:28:09 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:09 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:09 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:09 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:09 | D | - range ratio = [ 1.0000] +24-11-19 20:28:09 | D | sum error = [ 6.4066] +24-11-19 20:28:09 | D | best error = [ 6.4066] +24-11-19 20:28:10 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:10 | D | sum error = [ 6.3675, 6.3466, 6.3547, 6.4484, 6.5661] +24-11-19 20:28:10 | D | best error = [ 5.9573, 5.7811, 5.6864, 5.6344, 5.6075] +24-11-19 20:28:10 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:10 | D | sum error = [ 6.7206, 6.9629, 7.2476, 7.6054, 7.9946] +24-11-19 20:28:10 | D | best error = [ 5.5929, 5.5868, 5.5848, 5.5843, 5.5842] +24-11-19 20:28:10 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:10 | D | sum error = [ 8.4614, 8.9806, 9.5555, 10.2155, 10.8873] +24-11-19 20:28:10 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:28:10 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:10 | D | sum error = [ 11.6764, 12.5203, 13.4126, 14.3875, 15.4175] +24-11-19 20:28:10 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:28:10 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:10 | D | sum error = [ 16.5268, 17.7118, 18.9561, 20.2975, 21.6976] +24-11-19 20:28:10 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:28:10 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:10 | D | sum error = [ 23.1991, 24.7760, 26.4661, 28.2428, 30.1136] +24-11-19 20:28:10 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:28:10 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:10 | D | sum error = [ 32.0775, 34.1968, 36.3846, 38.7118, 41.1541] +24-11-19 20:28:10 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:28:10 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:10 | D | sum error = [ 43.7446, 46.4506, 49.3080, 52.3092, 55.4622] +24-11-19 20:28:10 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:28:10 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:10 | D | sum error = [ 58.7767, 62.2599, 65.9226, 69.7801, 73.8112] +24-11-19 20:28:10 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:28:10 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:10 | D | sum error = [ 78.0370, 82.4741, 87.1184, 91.9640, 97.0540] +24-11-19 20:28:10 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:28:10 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:10 | D | sum error = [ 102.3662, 107.9250, 113.7316, 119.8129, 126.1420] +24-11-19 20:28:10 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:28:10 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:10 | D | sum error = [ 132.7427, 139.6319, 146.8204, 154.3041, 162.0921] +24-11-19 20:28:10 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:28:10 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:10 | D | sum error = [ 170.1828, 178.5957, 187.3588, 196.4421, 205.8739] +24-11-19 20:28:10 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:28:10 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:10 | D | sum error = [ 215.6820, 225.8476, 236.3898, 247.3245, 258.6240] +24-11-19 20:28:10 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:28:10 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:10 | D | sum error = [ 270.3402, 282.4511, 294.9729, 307.9022, 321.2517] +24-11-19 20:28:10 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:28:10 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:10 | D | sum error = [ 335.0158, 349.1915, 363.8154, 378.8702, 394.3512] +24-11-19 20:28:10 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:28:10 | D | + error = [5.5842] +24-11-19 20:28:10 | D | - Calibrating model.layers.13.mlp.gate_proj.weight +24-11-19 20:28:10 | D | + w: sint8 +24-11-19 20:28:10 | D | + x: None +24-11-19 20:28:10 | D | + y: None +24-11-19 20:28:10 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:10 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:11 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:11 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:11 | D | - range ratio = [ 1.0000] +24-11-19 20:28:11 | D | sum error = [ 6.5603] +24-11-19 20:28:11 | D | best error = [ 6.5603] +24-11-19 20:28:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:12 | D | sum error = [ 6.5322, 6.5093, 6.5482, 6.6247, 6.7408] +24-11-19 20:28:12 | D | best error = [ 6.1087, 5.9355, 5.8440, 5.7898, 5.7605] +24-11-19 20:28:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:12 | D | sum error = [ 6.9071, 7.1636, 7.4521, 7.7875, 8.2076] +24-11-19 20:28:12 | D | best error = [ 5.7469, 5.7411, 5.7394, 5.7387, 5.7386] +24-11-19 20:28:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:12 | D | sum error = [ 8.6916, 9.2311, 9.8408, 10.5119, 11.2331] +24-11-19 20:28:12 | D | best error = [ 5.7385, 5.7385, 5.7385, 5.7385, 5.7385] +24-11-19 20:28:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:12 | D | sum error = [ 12.0362, 12.9196, 13.8389, 14.8575, 15.9488] +24-11-19 20:28:12 | D | best error = [ 5.7385, 5.7385, 5.7385, 5.7385, 5.7385] +24-11-19 20:28:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:12 | D | sum error = [ 17.1101, 18.3272, 19.6686, 21.0846, 22.5758] +24-11-19 20:28:12 | D | best error = [ 5.7385, 5.7385, 5.7385, 5.7385, 5.7385] +24-11-19 20:28:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:12 | D | sum error = [ 24.1959, 25.9034, 27.6942, 29.6190, 31.6560] +24-11-19 20:28:12 | D | best error = [ 5.7385, 5.7385, 5.7385, 5.7385, 5.7385] +24-11-19 20:28:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:12 | D | sum error = [ 33.8161, 36.0926, 38.5154, 41.0812, 43.8117] +24-11-19 20:28:12 | D | best error = [ 5.7385, 5.7385, 5.7385, 5.7385, 5.7385] +24-11-19 20:28:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:12 | D | sum error = [ 46.6904, 49.7754, 53.0001, 56.4375, 60.0544] +24-11-19 20:28:12 | D | best error = [ 5.7385, 5.7385, 5.7385, 5.7385, 5.7385] +24-11-19 20:28:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:12 | D | sum error = [ 63.8885, 67.9146, 72.2144, 76.7289, 81.5250] +24-11-19 20:28:12 | D | best error = [ 5.7385, 5.7385, 5.7385, 5.7385, 5.7385] +24-11-19 20:28:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:12 | D | sum error = [ 86.5863, 91.9266, 97.5781, 103.5385, 109.8249] +24-11-19 20:28:12 | D | best error = [ 5.7385, 5.7385, 5.7385, 5.7385, 5.7385] +24-11-19 20:28:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:12 | D | sum error = [ 116.4267, 123.3775, 130.6981, 138.4046, 146.4954] +24-11-19 20:28:12 | D | best error = [ 5.7385, 5.7385, 5.7385, 5.7385, 5.7385] +24-11-19 20:28:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:12 | D | sum error = [ 154.9945, 163.9433, 173.3359, 183.2127, 193.5404] +24-11-19 20:28:12 | D | best error = [ 5.7385, 5.7385, 5.7385, 5.7385, 5.7385] +24-11-19 20:28:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:12 | D | sum error = [ 204.3858, 215.7238, 227.6202, 240.0454, 253.0359] +24-11-19 20:28:12 | D | best error = [ 5.7385, 5.7385, 5.7385, 5.7385, 5.7385] +24-11-19 20:28:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:12 | D | sum error = [ 266.6043, 280.7401, 295.4724, 310.8048, 326.7394] +24-11-19 20:28:12 | D | best error = [ 5.7385, 5.7385, 5.7385, 5.7385, 5.7385] +24-11-19 20:28:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:12 | D | sum error = [ 343.3040, 360.5223, 378.3804, 396.9007, 416.0960] +24-11-19 20:28:12 | D | best error = [ 5.7385, 5.7385, 5.7385, 5.7385, 5.7385] +24-11-19 20:28:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:12 | D | sum error = [ 435.9585, 456.4964, 477.7151, 499.6239, 522.2139] +24-11-19 20:28:12 | D | best error = [ 5.7385, 5.7385, 5.7385, 5.7385, 5.7385] +24-11-19 20:28:12 | D | + error = [5.7385] +24-11-19 20:28:12 | D | - Calibrating model.layers.13.mlp.down_proj.weight +24-11-19 20:28:12 | D | + w: sint8 +24-11-19 20:28:12 | D | + x: None +24-11-19 20:28:12 | D | + y: None +24-11-19 20:28:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:12 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:12 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:12 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:12 | D | - range ratio = [ 1.0000] +24-11-19 20:28:12 | D | sum error = [ 1.7328] +24-11-19 20:28:12 | D | best error = [ 1.7328] +24-11-19 20:28:13 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:13 | D | sum error = [ 1.7166, 1.7057, 1.6975, 1.6934, 1.6961] +24-11-19 20:28:13 | D | best error = [ 1.6727, 1.6405, 1.6201, 1.6053, 1.5947] +24-11-19 20:28:13 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:13 | D | sum error = [ 1.7011, 1.7140, 1.7364, 1.7667, 1.8049] +24-11-19 20:28:13 | D | best error = [ 1.5864, 1.5795, 1.5749, 1.5715, 1.5695] +24-11-19 20:28:13 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:13 | D | sum error = [ 1.8531, 1.9107, 1.9767, 2.0594, 2.1511] +24-11-19 20:28:13 | D | best error = [ 1.5680, 1.5672, 1.5666, 1.5663, 1.5662] +24-11-19 20:28:13 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:13 | D | sum error = [ 2.2551, 2.3713, 2.5022, 2.6493, 2.8104] +24-11-19 20:28:13 | D | best error = [ 1.5660, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:28:13 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:13 | D | sum error = [ 2.9810, 3.1744, 3.3794, 3.6017, 3.8425] +24-11-19 20:28:13 | D | best error = [ 1.5659, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:28:13 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:13 | D | sum error = [ 4.0996, 4.3727, 4.6693, 4.9878, 5.3256] +24-11-19 20:28:13 | D | best error = [ 1.5659, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:28:13 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:13 | D | sum error = [ 5.6843, 6.0702, 6.4768, 6.9127, 7.3742] +24-11-19 20:28:13 | D | best error = [ 1.5659, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:28:13 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:13 | D | sum error = [ 7.8656, 8.3825, 8.9359, 9.5200, 10.1361] +24-11-19 20:28:13 | D | best error = [ 1.5659, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:28:13 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:13 | D | sum error = [ 10.7868, 11.4781, 12.2108, 12.9794, 13.7918] +24-11-19 20:28:13 | D | best error = [ 1.5659, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:28:13 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:13 | D | sum error = [ 14.6507, 15.5546, 16.5083, 17.5138, 18.5734] +24-11-19 20:28:13 | D | best error = [ 1.5659, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:28:13 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:13 | D | sum error = [ 19.6845, 20.8538, 22.0850, 23.3781, 24.7336] +24-11-19 20:28:13 | D | best error = [ 1.5659, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:28:13 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:13 | D | sum error = [ 26.1591, 27.6514, 29.2168, 30.8564, 32.5731] +24-11-19 20:28:13 | D | best error = [ 1.5659, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:28:13 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:13 | D | sum error = [ 34.3684, 36.2467, 38.2086, 40.2570, 42.3945] +24-11-19 20:28:13 | D | best error = [ 1.5659, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:28:13 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:13 | D | sum error = [ 44.6264, 46.9509, 49.3733, 51.9007, 54.5216] +24-11-19 20:28:13 | D | best error = [ 1.5659, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:28:13 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:13 | D | sum error = [ 57.2521, 60.0889, 63.0358, 66.0935, 69.2644] +24-11-19 20:28:13 | D | best error = [ 1.5659, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:28:13 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:13 | D | sum error = [ 72.5495, 75.9474, 79.4620, 83.0933, 86.8512] +24-11-19 20:28:13 | D | best error = [ 1.5659, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:28:13 | D | + error = [1.5659] +24-11-19 20:28:13 | D | - Quantizing model.layers.13.self_attn.q_proj.weight +24-11-19 20:28:14 | D | - Quantizing model.layers.13.self_attn.k_proj.weight +24-11-19 20:28:15 | D | - Quantizing model.layers.13.self_attn.v_proj.weight +24-11-19 20:28:16 | D | - Quantizing model.layers.13.self_attn.o_proj.weight +24-11-19 20:28:18 | D | - Quantizing model.layers.13.mlp.up_proj.weight +24-11-19 20:28:19 | D | - Quantizing model.layers.13.mlp.gate_proj.weight +24-11-19 20:28:20 | D | - Quantizing model.layers.13.mlp.down_proj.weight +24-11-19 20:28:28 | D | - Quantizing layer model.layers.14 +24-11-19 20:28:28 | D | - Calibrating model.layers.14.self_attn.q_proj.weight +24-11-19 20:28:28 | D | + w: sint8 +24-11-19 20:28:28 | D | + x: None +24-11-19 20:28:28 | D | + y: None +24-11-19 20:28:28 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:28:28 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:28 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:29 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:29 | D | - range ratio = [ 1.0000] +24-11-19 20:28:29 | D | sum error = [ 11.6970] +24-11-19 20:28:29 | D | best error = [ 11.6970] +24-11-19 20:28:42 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:42 | D | sum error = [ 11.7472, 11.8502, 11.6997, 11.9271, 12.0598] +24-11-19 20:28:42 | D | best error = [ 11.6970, 11.6970, 11.6970, 11.6970, 11.6970] +24-11-19 20:28:42 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:42 | D | sum error = [ 12.1981, 12.7541, 13.1551, 13.7793, 14.8201] +24-11-19 20:28:42 | D | best error = [ 11.6970, 11.6970, 11.6970, 11.6970, 11.6970] +24-11-19 20:28:42 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:42 | D | sum error = [ 15.4385, 16.5889, 17.8186, 18.8674, 20.3967] +24-11-19 20:28:42 | D | best error = [ 11.6970, 11.6970, 11.6970, 11.6970, 11.6970] +24-11-19 20:28:42 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:42 | D | sum error = [ 21.6368, 23.6813, 25.3352, 27.0532, 29.0889] +24-11-19 20:28:42 | D | best error = [ 11.6970, 11.6970, 11.6970, 11.6970, 11.6970] +24-11-19 20:28:42 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:42 | D | sum error = [ 31.5611, 33.9161, 36.8134, 39.5302, 42.7986] +24-11-19 20:28:42 | D | best error = [ 11.6970, 11.6970, 11.6970, 11.6970, 11.6970] +24-11-19 20:28:42 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:42 | D | sum error = [ 45.9407, 50.0379, 53.7295, 57.7063, 62.1266] +24-11-19 20:28:42 | D | best error = [ 11.6970, 11.6970, 11.6970, 11.6970, 11.6970] +24-11-19 20:28:42 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:42 | D | sum error = [ 66.5940, 71.4311, 76.9358, 83.0032, 88.8610] +24-11-19 20:28:42 | D | best error = [ 11.6970, 11.6970, 11.6970, 11.6970, 11.6970] +24-11-19 20:28:42 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:42 | D | sum error = [ 95.4958, 101.9766, 110.0329, 118.0060, 126.8313] +24-11-19 20:28:42 | D | best error = [ 11.6970, 11.6970, 11.6970, 11.6970, 11.6970] +24-11-19 20:28:42 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:42 | D | sum error = [ 135.8679, 146.0171, 156.4948, 167.8152, 180.3085] +24-11-19 20:28:42 | D | best error = [ 11.6970, 11.6970, 11.6970, 11.6970, 11.6970] +24-11-19 20:28:42 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:42 | D | sum error = [ 193.1059, 207.2131, 222.1365, 238.5245, 255.7608] +24-11-19 20:28:42 | D | best error = [ 11.6970, 11.6970, 11.6970, 11.6970, 11.6970] +24-11-19 20:28:42 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:42 | D | sum error = [ 274.2744, 294.3929, 315.5192, 338.4097, 362.6514] +24-11-19 20:28:42 | D | best error = [ 11.6970, 11.6970, 11.6970, 11.6970, 11.6970] +24-11-19 20:28:42 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:42 | D | sum error = [ 388.6238, 416.9319, 446.5289, 478.1135, 511.8785] +24-11-19 20:28:42 | D | best error = [ 11.6970, 11.6970, 11.6970, 11.6970, 11.6970] +24-11-19 20:28:42 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:42 | D | sum error = [ 547.8934, 586.2922, 627.6013, 671.2986, 718.5592] +24-11-19 20:28:42 | D | best error = [ 11.6970, 11.6970, 11.6970, 11.6970, 11.6970] +24-11-19 20:28:42 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:42 | D | sum error = [ 768.6530, 822.3264, 879.2992, 940.4749, 1005.4979] +24-11-19 20:28:42 | D | best error = [ 11.6970, 11.6970, 11.6970, 11.6970, 11.6970] +24-11-19 20:28:42 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:42 | D | sum error = [ 1074.7231, 1148.2163, 1226.0336, 1308.1940, 1394.5212] +24-11-19 20:28:42 | D | best error = [ 11.6970, 11.6970, 11.6970, 11.6970, 11.6970] +24-11-19 20:28:42 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:42 | D | sum error = [ 1485.1345, 1579.2661, 1676.8244, 1776.8966, 1879.2367] +24-11-19 20:28:42 | D | best error = [ 11.6970, 11.6970, 11.6970, 11.6970, 11.6970] +24-11-19 20:28:42 | D | + error = [11.6970] +24-11-19 20:28:42 | D | - Calibrating model.layers.14.self_attn.k_proj.weight +24-11-19 20:28:42 | D | + w: sint8 +24-11-19 20:28:42 | D | + x: None +24-11-19 20:28:42 | D | + y: None +24-11-19 20:28:42 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:28:42 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:42 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:43 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:43 | D | - range ratio = [ 1.0000] +24-11-19 20:28:43 | D | sum error = [ 13.2752] +24-11-19 20:28:43 | D | best error = [ 13.2752] +24-11-19 20:28:56 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:56 | D | sum error = [ 11.5567, 11.4263, 11.5279, 12.3756, 12.3903] +24-11-19 20:28:56 | D | best error = [ 11.5567, 11.4263, 11.4263, 11.4263, 11.4263] +24-11-19 20:28:56 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:56 | D | sum error = [ 12.2533, 13.4854, 13.7765, 15.1161, 14.8014] +24-11-19 20:28:56 | D | best error = [ 11.4263, 11.4263, 11.4263, 11.4263, 11.4263] +24-11-19 20:28:56 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:56 | D | sum error = [ 15.9314, 16.9406, 18.2645, 19.5160, 20.3436] +24-11-19 20:28:56 | D | best error = [ 11.4263, 11.4263, 11.4263, 11.4263, 11.4263] +24-11-19 20:28:56 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:56 | D | sum error = [ 22.9752, 24.0532, 25.8047, 28.0181, 29.5232] +24-11-19 20:28:56 | D | best error = [ 11.4263, 11.4263, 11.4263, 11.4263, 11.4263] +24-11-19 20:28:56 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:56 | D | sum error = [ 32.6084, 35.0022, 37.6177, 40.7184, 44.4890] +24-11-19 20:28:56 | D | best error = [ 11.4263, 11.4263, 11.4263, 11.4263, 11.4263] +24-11-19 20:28:56 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:56 | D | sum error = [ 47.4096, 51.2383, 56.1823, 60.3647, 66.5753] +24-11-19 20:28:56 | D | best error = [ 11.4263, 11.4263, 11.4263, 11.4263, 11.4263] +24-11-19 20:28:56 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:56 | D | sum error = [ 70.5574, 75.9501, 82.0625, 89.0800, 96.5281] +24-11-19 20:28:56 | D | best error = [ 11.4263, 11.4263, 11.4263, 11.4263, 11.4263] +24-11-19 20:28:56 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:56 | D | sum error = [ 103.5884, 111.2105, 121.0231, 128.9781, 138.4720] +24-11-19 20:28:56 | D | best error = [ 11.4263, 11.4263, 11.4263, 11.4263, 11.4263] +24-11-19 20:28:56 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:56 | D | sum error = [ 148.5279, 159.6824, 171.4598, 183.2960, 196.5235] +24-11-19 20:28:56 | D | best error = [ 11.4263, 11.4263, 11.4263, 11.4263, 11.4263] +24-11-19 20:28:56 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:56 | D | sum error = [ 209.9575, 225.5252, 241.2692, 257.3563, 276.3163] +24-11-19 20:28:56 | D | best error = [ 11.4263, 11.4263, 11.4263, 11.4263, 11.4263] +24-11-19 20:28:56 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:56 | D | sum error = [ 294.4037, 315.5292, 336.7758, 360.1529, 383.0603] +24-11-19 20:28:56 | D | best error = [ 11.4263, 11.4263, 11.4263, 11.4263, 11.4263] +24-11-19 20:28:56 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:56 | D | sum error = [ 409.4722, 436.7461, 466.2640, 497.4144, 530.7572] +24-11-19 20:28:56 | D | best error = [ 11.4263, 11.4263, 11.4263, 11.4263, 11.4263] +24-11-19 20:28:56 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:56 | D | sum error = [ 564.5186, 601.7778, 641.4888, 683.6343, 729.1274] +24-11-19 20:28:56 | D | best error = [ 11.4263, 11.4263, 11.4263, 11.4263, 11.4263] +24-11-19 20:28:56 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:56 | D | sum error = [ 775.6148, 826.9154, 880.8692, 939.3378, 1000.5821] +24-11-19 20:28:56 | D | best error = [ 11.4263, 11.4263, 11.4263, 11.4263, 11.4263] +24-11-19 20:28:56 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:56 | D | sum error = [ 1068.1132, 1137.4369, 1213.7282, 1293.4196, 1377.7290] +24-11-19 20:28:56 | D | best error = [ 11.4263, 11.4263, 11.4263, 11.4263, 11.4263] +24-11-19 20:28:56 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:56 | D | sum error = [ 1465.2360, 1559.2129, 1655.8871, 1756.3659, 1858.5738] +24-11-19 20:28:56 | D | best error = [ 11.4263, 11.4263, 11.4263, 11.4263, 11.4263] +24-11-19 20:28:56 | D | + error = [11.4263] +24-11-19 20:28:56 | D | - Calibrating model.layers.14.self_attn.v_proj.weight +24-11-19 20:28:56 | D | + w: sint8 +24-11-19 20:28:56 | D | + x: None +24-11-19 20:28:56 | D | + y: None +24-11-19 20:28:56 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:56 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:56 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:56 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:56 | D | - range ratio = [ 1.0000] +24-11-19 20:28:56 | D | sum error = [ 4.9190] +24-11-19 20:28:56 | D | best error = [ 4.9190] +24-11-19 20:28:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:57 | D | sum error = [ 4.9056, 4.8908, 4.9001, 4.9577, 5.0517] +24-11-19 20:28:57 | D | best error = [ 4.5779, 4.4428, 4.3761, 4.3350, 4.3184] +24-11-19 20:28:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:57 | D | sum error = [ 5.1867, 5.3672, 5.5960, 5.8635, 6.1742] +24-11-19 20:28:57 | D | best error = [ 4.3091, 4.3038, 4.3029, 4.3026, 4.3026] +24-11-19 20:28:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:57 | D | sum error = [ 6.5323, 6.9028, 7.3726, 7.8695, 8.4094] +24-11-19 20:28:57 | D | best error = [ 4.3026, 4.3026, 4.3026, 4.3026, 4.3026] +24-11-19 20:28:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:57 | D | sum error = [ 8.9962, 9.6657, 10.3794, 11.0901, 11.9040] +24-11-19 20:28:57 | D | best error = [ 4.3026, 4.3026, 4.3026, 4.3026, 4.3026] +24-11-19 20:28:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:57 | D | sum error = [ 12.7702, 13.6653, 14.6256, 15.6658, 16.7342] +24-11-19 20:28:57 | D | best error = [ 4.3026, 4.3026, 4.3026, 4.3026, 4.3026] +24-11-19 20:28:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:57 | D | sum error = [ 17.8812, 19.0735, 20.3612, 21.7233, 23.1686] +24-11-19 20:28:57 | D | best error = [ 4.3026, 4.3026, 4.3026, 4.3026, 4.3026] +24-11-19 20:28:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:57 | D | sum error = [ 24.6603, 26.2372, 27.9261, 29.6773, 31.5417] +24-11-19 20:28:57 | D | best error = [ 4.3026, 4.3026, 4.3026, 4.3026, 4.3026] +24-11-19 20:28:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:57 | D | sum error = [ 33.5086, 35.5826, 37.7308, 40.0059, 42.4116] +24-11-19 20:28:57 | D | best error = [ 4.3026, 4.3026, 4.3026, 4.3026, 4.3026] +24-11-19 20:28:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:57 | D | sum error = [ 44.9360, 47.5714, 50.3351, 53.2530, 56.2962] +24-11-19 20:28:57 | D | best error = [ 4.3026, 4.3026, 4.3026, 4.3026, 4.3026] +24-11-19 20:28:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:57 | D | sum error = [ 59.5061, 62.8399, 66.3431, 70.0115, 73.8499] +24-11-19 20:28:57 | D | best error = [ 4.3026, 4.3026, 4.3026, 4.3026, 4.3026] +24-11-19 20:28:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:57 | D | sum error = [ 77.8687, 82.0375, 86.4080, 90.9753, 95.7312] +24-11-19 20:28:57 | D | best error = [ 4.3026, 4.3026, 4.3026, 4.3026, 4.3026] +24-11-19 20:28:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:57 | D | sum error = [ 100.6908, 105.8400, 111.2202, 116.8010, 122.6457] +24-11-19 20:28:57 | D | best error = [ 4.3026, 4.3026, 4.3026, 4.3026, 4.3026] +24-11-19 20:28:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:57 | D | sum error = [ 128.6982, 135.0119, 141.5693, 148.3809, 155.4549] +24-11-19 20:28:57 | D | best error = [ 4.3026, 4.3026, 4.3026, 4.3026, 4.3026] +24-11-19 20:28:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:57 | D | sum error = [ 162.7851, 170.3780, 178.2493, 186.4118, 194.8492] +24-11-19 20:28:57 | D | best error = [ 4.3026, 4.3026, 4.3026, 4.3026, 4.3026] +24-11-19 20:28:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:57 | D | sum error = [ 203.5769, 212.6123, 221.9468, 231.5965, 241.5490] +24-11-19 20:28:57 | D | best error = [ 4.3026, 4.3026, 4.3026, 4.3026, 4.3026] +24-11-19 20:28:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:57 | D | sum error = [ 251.8131, 262.4035, 273.3103, 284.5463, 296.0956] +24-11-19 20:28:57 | D | best error = [ 4.3026, 4.3026, 4.3026, 4.3026, 4.3026] +24-11-19 20:28:57 | D | + error = [4.3026] +24-11-19 20:28:57 | D | - Calibrating model.layers.14.self_attn.o_proj.weight +24-11-19 20:28:57 | D | + w: sint8 +24-11-19 20:28:57 | D | + x: None +24-11-19 20:28:57 | D | + y: None +24-11-19 20:28:57 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:57 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:57 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:57 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:57 | D | - range ratio = [ 1.0000] +24-11-19 20:28:57 | D | sum error = [ 1.3102] +24-11-19 20:28:57 | D | best error = [ 1.3102] +24-11-19 20:28:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:57 | D | sum error = [ 1.3044, 1.2958, 1.2961, 1.3010, 1.3102] +24-11-19 20:28:57 | D | best error = [ 1.2224, 1.1802, 1.1547, 1.1378, 1.1248] +24-11-19 20:28:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:57 | D | sum error = [ 1.3367, 1.3618, 1.3959, 1.4452, 1.4986] +24-11-19 20:28:57 | D | best error = [ 1.1172, 1.1119, 1.1088, 1.1065, 1.1050] +24-11-19 20:28:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:57 | D | sum error = [ 1.5667, 1.6428, 1.7279, 1.8186, 1.9254] +24-11-19 20:28:57 | D | best error = [ 1.1039, 1.1035, 1.1030, 1.1026, 1.1024] +24-11-19 20:28:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:57 | D | sum error = [ 2.0442, 2.1692, 2.3100, 2.4576, 2.6242] +24-11-19 20:28:57 | D | best error = [ 1.1022, 1.1021, 1.1020, 1.1019, 1.1018] +24-11-19 20:28:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:57 | D | sum error = [ 2.7949, 2.9769, 3.1742, 3.3850, 3.6099] +24-11-19 20:28:57 | D | best error = [ 1.1018, 1.1017, 1.1017, 1.1017, 1.1017] +24-11-19 20:28:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:57 | D | sum error = [ 3.8471, 4.0989, 4.3643, 4.6529, 4.9519] +24-11-19 20:28:57 | D | best error = [ 1.1017, 1.1017, 1.1017, 1.1017, 1.1017] +24-11-19 20:28:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:57 | D | sum error = [ 5.2620, 5.6010, 5.9539, 6.3208, 6.7114] +24-11-19 20:28:57 | D | best error = [ 1.1017, 1.1017, 1.1017, 1.1017, 1.1017] +24-11-19 20:28:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:57 | D | sum error = [ 7.1275, 7.5575, 8.0106, 8.4853, 8.9973] +24-11-19 20:28:57 | D | best error = [ 1.1017, 1.1017, 1.1017, 1.1017, 1.1017] +24-11-19 20:28:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:57 | D | sum error = [ 9.5189, 10.0793, 10.6640, 11.2814, 11.9293] +24-11-19 20:28:57 | D | best error = [ 1.1017, 1.1017, 1.1017, 1.1017, 1.1017] +24-11-19 20:28:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:57 | D | sum error = [ 12.6072, 13.3203, 14.0713, 14.8521, 15.6749] +24-11-19 20:28:57 | D | best error = [ 1.1017, 1.1017, 1.1017, 1.1017, 1.1017] +24-11-19 20:28:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:57 | D | sum error = [ 16.5310, 17.4301, 18.3703, 19.3507, 20.3734] +24-11-19 20:28:57 | D | best error = [ 1.1017, 1.1017, 1.1017, 1.1017, 1.1017] +24-11-19 20:28:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:57 | D | sum error = [ 21.4401, 22.5514, 23.7094, 24.9145, 26.1733] +24-11-19 20:28:57 | D | best error = [ 1.1017, 1.1017, 1.1017, 1.1017, 1.1017] +24-11-19 20:28:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:57 | D | sum error = [ 27.4834, 28.8522, 30.2692, 31.7449, 33.2797] +24-11-19 20:28:57 | D | best error = [ 1.1017, 1.1017, 1.1017, 1.1017, 1.1017] +24-11-19 20:28:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:57 | D | sum error = [ 34.8718, 36.5225, 38.2367, 40.0132, 41.8564] +24-11-19 20:28:57 | D | best error = [ 1.1017, 1.1017, 1.1017, 1.1017, 1.1017] +24-11-19 20:28:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:57 | D | sum error = [ 43.7688, 45.7488, 47.8027, 49.9310, 52.1353] +24-11-19 20:28:57 | D | best error = [ 1.1017, 1.1017, 1.1017, 1.1017, 1.1017] +24-11-19 20:28:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:57 | D | sum error = [ 54.4168, 56.7762, 59.2173, 61.7408, 64.3466] +24-11-19 20:28:57 | D | best error = [ 1.1017, 1.1017, 1.1017, 1.1017, 1.1017] +24-11-19 20:28:57 | D | + error = [1.1017] +24-11-19 20:28:57 | D | - Calibrating model.layers.14.mlp.up_proj.weight +24-11-19 20:28:57 | D | + w: sint8 +24-11-19 20:28:57 | D | + x: None +24-11-19 20:28:57 | D | + y: None +24-11-19 20:28:57 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:57 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:58 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:58 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:58 | D | - range ratio = [ 1.0000] +24-11-19 20:28:58 | D | sum error = [ 6.6596] +24-11-19 20:28:58 | D | best error = [ 6.6596] +24-11-19 20:28:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:59 | D | sum error = [ 6.6360, 6.6372, 6.6593, 6.7337, 6.8480] +24-11-19 20:28:59 | D | best error = [ 6.1985, 6.0236, 5.9275, 5.8740, 5.8451] +24-11-19 20:28:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:59 | D | sum error = [ 7.0199, 7.2543, 7.5583, 7.9125, 8.3357] +24-11-19 20:28:59 | D | best error = [ 5.8319, 5.8258, 5.8232, 5.8226, 5.8224] +24-11-19 20:28:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:59 | D | sum error = [ 8.8046, 9.3675, 9.9605, 10.6100, 11.3385] +24-11-19 20:28:59 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 20:28:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:59 | D | sum error = [ 12.1671, 13.0268, 13.9715, 14.9578, 16.0201] +24-11-19 20:28:59 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 20:28:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:59 | D | sum error = [ 17.1809, 18.4066, 19.7033, 21.0660, 22.5577] +24-11-19 20:28:59 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 20:28:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:59 | D | sum error = [ 24.1129, 25.7592, 27.5034, 29.3538, 31.2908] +24-11-19 20:28:59 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 20:28:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:59 | D | sum error = [ 33.3501, 35.5214, 37.7919, 40.2093, 42.7384] +24-11-19 20:28:59 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 20:28:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:59 | D | sum error = [ 45.4181, 48.2404, 51.2013, 54.3167, 57.6066] +24-11-19 20:28:59 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 20:28:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:59 | D | sum error = [ 61.0389, 64.6446, 68.4400, 72.3999, 76.5936] +24-11-19 20:28:59 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 20:28:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:59 | D | sum error = [ 80.9720, 85.5476, 90.3649, 95.4045, 100.6714] +24-11-19 20:28:59 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 20:28:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:59 | D | sum error = [ 106.1793, 111.9679, 117.9715, 124.2833, 130.8640] +24-11-19 20:28:59 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 20:28:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:59 | D | sum error = [ 137.7132, 144.8527, 152.3100, 160.0669, 168.1458] +24-11-19 20:28:59 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 20:28:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:59 | D | sum error = [ 176.5555, 185.2825, 194.3716, 203.7969, 213.5963] +24-11-19 20:28:59 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 20:28:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:59 | D | sum error = [ 223.7475, 234.2983, 245.2181, 256.5587, 268.2573] +24-11-19 20:28:59 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 20:28:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:59 | D | sum error = [ 280.3928, 292.9398, 305.9120, 319.3074, 333.1355] +24-11-19 20:28:59 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 20:28:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:59 | D | sum error = [ 347.3974, 362.1164, 377.2877, 392.8909, 408.9564] +24-11-19 20:28:59 | D | best error = [ 5.8224, 5.8224, 5.8224, 5.8224, 5.8224] +24-11-19 20:28:59 | D | + error = [5.8224] +24-11-19 20:28:59 | D | - Calibrating model.layers.14.mlp.gate_proj.weight +24-11-19 20:28:59 | D | + w: sint8 +24-11-19 20:28:59 | D | + x: None +24-11-19 20:28:59 | D | + y: None +24-11-19 20:28:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:59 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:59 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:59 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:59 | D | - range ratio = [ 1.0000] +24-11-19 20:28:59 | D | sum error = [ 6.8366] +24-11-19 20:28:59 | D | best error = [ 6.8366] +24-11-19 20:29:00 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:00 | D | sum error = [ 6.7900, 6.7882, 6.8273, 6.8997, 7.0229] +24-11-19 20:29:00 | D | best error = [ 6.3566, 6.1791, 6.0817, 6.0271, 5.9985] +24-11-19 20:29:00 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:00 | D | sum error = [ 7.1997, 7.4512, 7.7563, 8.1142, 8.5342] +24-11-19 20:29:00 | D | best error = [ 5.9833, 5.9764, 5.9737, 5.9730, 5.9729] +24-11-19 20:29:00 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:00 | D | sum error = [ 9.0376, 9.5978, 10.2485, 10.9295, 11.6895] +24-11-19 20:29:00 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:29:00 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:00 | D | sum error = [ 12.5093, 13.4138, 14.3819, 15.4558, 16.5636] +24-11-19 20:29:00 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:29:00 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:00 | D | sum error = [ 17.7468, 19.0357, 20.4056, 21.8778, 23.4323] +24-11-19 20:29:00 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:29:00 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:00 | D | sum error = [ 25.0953, 26.8395, 28.6960, 30.6771, 32.7712] +24-11-19 20:29:00 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:29:00 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:00 | D | sum error = [ 34.9900, 37.3382, 39.8337, 42.4631, 45.2567] +24-11-19 20:29:00 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:29:00 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:00 | D | sum error = [ 48.2020, 51.3380, 54.6383, 58.1277, 61.8085] +24-11-19 20:29:00 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:29:00 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:00 | D | sum error = [ 65.7209, 69.8090, 74.1790, 78.7958, 83.6386] +24-11-19 20:29:00 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:29:00 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:00 | D | sum error = [ 88.7688, 94.1963, 99.9155, 105.9472, 112.2886] +24-11-19 20:29:00 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:29:00 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:00 | D | sum error = [ 118.9682, 126.0237, 133.4151, 141.2139, 149.3954] +24-11-19 20:29:00 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:29:00 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:00 | D | sum error = [ 158.0032, 167.0422, 176.5294, 186.4821, 196.9478] +24-11-19 20:29:00 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:29:00 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:00 | D | sum error = [ 207.9041, 219.3757, 231.3971, 243.9683, 257.0932] +24-11-19 20:29:00 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:29:00 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:00 | D | sum error = [ 270.8091, 285.1203, 300.0440, 315.5932, 331.7657] +24-11-19 20:29:00 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:29:00 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:00 | D | sum error = [ 348.5916, 366.0325, 384.1467, 402.9240, 422.3841] +24-11-19 20:29:00 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:29:00 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:00 | D | sum error = [ 442.5126, 463.3495, 484.8287, 506.9926, 529.8647] +24-11-19 20:29:00 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:29:00 | D | + error = [5.9729] +24-11-19 20:29:00 | D | - Calibrating model.layers.14.mlp.down_proj.weight +24-11-19 20:29:00 | D | + w: sint8 +24-11-19 20:29:00 | D | + x: None +24-11-19 20:29:00 | D | + y: None +24-11-19 20:29:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:00 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:29:00 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:29:00 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:00 | D | - range ratio = [ 1.0000] +24-11-19 20:29:00 | D | sum error = [ 1.8797] +24-11-19 20:29:00 | D | best error = [ 1.8797] +24-11-19 20:29:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:01 | D | sum error = [ 1.8615, 1.8489, 1.8399, 1.8360, 1.8358] +24-11-19 20:29:01 | D | best error = [ 1.8151, 1.7824, 1.7603, 1.7439, 1.7317] +24-11-19 20:29:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:01 | D | sum error = [ 1.8432, 1.8534, 1.8779, 1.9067, 1.9519] +24-11-19 20:29:01 | D | best error = [ 1.7219, 1.7150, 1.7099, 1.7069, 1.7046] +24-11-19 20:29:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:01 | D | sum error = [ 1.9971, 2.0592, 2.1348, 2.2234, 2.3194] +24-11-19 20:29:01 | D | best error = [ 1.7032, 1.7023, 1.7017, 1.7011, 1.7009] +24-11-19 20:29:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:01 | D | sum error = [ 2.4353, 2.5617, 2.7039, 2.8624, 3.0343] +24-11-19 20:29:01 | D | best error = [ 1.7009, 1.7008, 1.7007, 1.7007, 1.7007] +24-11-19 20:29:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:01 | D | sum error = [ 3.2250, 3.4346, 3.6598, 3.9029, 4.1664] +24-11-19 20:29:01 | D | best error = [ 1.7007, 1.7006, 1.7006, 1.7006, 1.7006] +24-11-19 20:29:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:01 | D | sum error = [ 4.4472, 4.7493, 5.0745, 5.4196, 5.7950] +24-11-19 20:29:01 | D | best error = [ 1.7006, 1.7006, 1.7006, 1.7006, 1.7006] +24-11-19 20:29:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:01 | D | sum error = [ 6.1908, 6.6069, 7.0576, 7.5352, 8.0408] +24-11-19 20:29:01 | D | best error = [ 1.7006, 1.7006, 1.7006, 1.7006, 1.7006] +24-11-19 20:29:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:01 | D | sum error = [ 8.5779, 9.1521, 9.7578, 10.3953, 11.0733] +24-11-19 20:29:01 | D | best error = [ 1.7006, 1.7006, 1.7006, 1.7006, 1.7006] +24-11-19 20:29:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:01 | D | sum error = [ 11.7882, 12.5484, 13.3480, 14.1970, 15.0886] +24-11-19 20:29:01 | D | best error = [ 1.7006, 1.7006, 1.7006, 1.7006, 1.7006] +24-11-19 20:29:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:01 | D | sum error = [ 16.0275, 17.0196, 18.0660, 19.1652, 20.3242] +24-11-19 20:29:01 | D | best error = [ 1.7006, 1.7006, 1.7006, 1.7006, 1.7006] +24-11-19 20:29:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:01 | D | sum error = [ 21.5408, 22.8203, 24.1645, 25.5783, 27.0576] +24-11-19 20:29:01 | D | best error = [ 1.7006, 1.7006, 1.7006, 1.7006, 1.7006] +24-11-19 20:29:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:01 | D | sum error = [ 28.6089, 30.2360, 31.9430, 33.7262, 35.5907] +24-11-19 20:29:01 | D | best error = [ 1.7006, 1.7006, 1.7006, 1.7006, 1.7006] +24-11-19 20:29:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:01 | D | sum error = [ 37.5425, 39.5778, 41.7052, 43.9221, 46.2340] +24-11-19 20:29:01 | D | best error = [ 1.7006, 1.7006, 1.7006, 1.7006, 1.7006] +24-11-19 20:29:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:01 | D | sum error = [ 48.6476, 51.1574, 53.7705, 56.4942, 59.3171] +24-11-19 20:29:01 | D | best error = [ 1.7006, 1.7006, 1.7006, 1.7006, 1.7006] +24-11-19 20:29:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:01 | D | sum error = [ 62.2540, 65.3020, 68.4663, 71.7462, 75.1474] +24-11-19 20:29:01 | D | best error = [ 1.7006, 1.7006, 1.7006, 1.7006, 1.7006] +24-11-19 20:29:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:01 | D | sum error = [ 78.6709, 82.3149, 86.0835, 89.9809, 94.0048] +24-11-19 20:29:01 | D | best error = [ 1.7006, 1.7006, 1.7006, 1.7006, 1.7006] +24-11-19 20:29:01 | D | + error = [1.7006] +24-11-19 20:29:01 | D | - Quantizing model.layers.14.self_attn.q_proj.weight +24-11-19 20:29:02 | D | - Quantizing model.layers.14.self_attn.k_proj.weight +24-11-19 20:29:03 | D | - Quantizing model.layers.14.self_attn.v_proj.weight +24-11-19 20:29:04 | D | - Quantizing model.layers.14.self_attn.o_proj.weight +24-11-19 20:29:05 | D | - Quantizing model.layers.14.mlp.up_proj.weight +24-11-19 20:29:07 | D | - Quantizing model.layers.14.mlp.gate_proj.weight +24-11-19 20:29:07 | D | - Quantizing model.layers.14.mlp.down_proj.weight +24-11-19 20:29:16 | D | - Quantizing layer model.layers.15 +24-11-19 20:29:16 | D | - Calibrating model.layers.15.self_attn.q_proj.weight +24-11-19 20:29:16 | D | + w: sint8 +24-11-19 20:29:16 | D | + x: None +24-11-19 20:29:16 | D | + y: None +24-11-19 20:29:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:29:16 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:29:16 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:29:16 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:16 | D | - range ratio = [ 1.0000] +24-11-19 20:29:16 | D | sum error = [ 11.1344] +24-11-19 20:29:16 | D | best error = [ 11.1344] +24-11-19 20:29:30 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:30 | D | sum error = [ 11.0647, 11.0121, 11.4001, 11.2920, 11.5833] +24-11-19 20:29:30 | D | best error = [ 11.0647, 11.0121, 11.0121, 11.0121, 11.0121] +24-11-19 20:29:30 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:30 | D | sum error = [ 11.9664, 12.2790, 12.6663, 13.4482, 14.8275] +24-11-19 20:29:30 | D | best error = [ 11.0121, 11.0121, 11.0121, 11.0121, 11.0121] +24-11-19 20:29:30 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:30 | D | sum error = [ 14.9537, 15.9130, 17.2399, 18.4237, 19.6513] +24-11-19 20:29:30 | D | best error = [ 11.0121, 11.0121, 11.0121, 11.0121, 11.0121] +24-11-19 20:29:30 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:30 | D | sum error = [ 21.0445, 22.6281, 24.6721, 26.5777, 28.0939] +24-11-19 20:29:30 | D | best error = [ 11.0121, 11.0121, 11.0121, 11.0121, 11.0121] +24-11-19 20:29:30 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:30 | D | sum error = [ 30.2111, 32.8271, 35.7271, 38.2932, 41.2473] +24-11-19 20:29:30 | D | best error = [ 11.0121, 11.0121, 11.0121, 11.0121, 11.0121] +24-11-19 20:29:30 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:30 | D | sum error = [ 44.3513, 47.8105, 51.5089, 55.3865, 59.9574] +24-11-19 20:29:30 | D | best error = [ 11.0121, 11.0121, 11.0121, 11.0121, 11.0121] +24-11-19 20:29:30 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:30 | D | sum error = [ 64.5964, 69.6422, 75.2847, 80.7717, 87.0492] +24-11-19 20:29:30 | D | best error = [ 11.0121, 11.0121, 11.0121, 11.0121, 11.0121] +24-11-19 20:29:30 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:30 | D | sum error = [ 93.9630, 101.0981, 108.6503, 117.0522, 126.0298] +24-11-19 20:29:30 | D | best error = [ 11.0121, 11.0121, 11.0121, 11.0121, 11.0121] +24-11-19 20:29:30 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:30 | D | sum error = [ 135.4186, 145.8296, 156.6722, 168.7265, 181.6524] +24-11-19 20:29:30 | D | best error = [ 11.0121, 11.0121, 11.0121, 11.0121, 11.0121] +24-11-19 20:29:30 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:30 | D | sum error = [ 195.5990, 210.0716, 226.1707, 243.0960, 261.8213] +24-11-19 20:29:30 | D | best error = [ 11.0121, 11.0121, 11.0121, 11.0121, 11.0121] +24-11-19 20:29:30 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:30 | D | sum error = [ 281.2644, 301.9128, 324.3416, 348.2801, 373.7606] +24-11-19 20:29:30 | D | best error = [ 11.0121, 11.0121, 11.0121, 11.0121, 11.0121] +24-11-19 20:29:30 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:30 | D | sum error = [ 401.3143, 430.7401, 462.3397, 495.9167, 532.2789] +24-11-19 20:29:30 | D | best error = [ 11.0121, 11.0121, 11.0121, 11.0121, 11.0121] +24-11-19 20:29:30 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:30 | D | sum error = [ 571.0245, 613.0875, 658.2451, 706.2801, 757.9907] +24-11-19 20:29:30 | D | best error = [ 11.0121, 11.0121, 11.0121, 11.0121, 11.0121] +24-11-19 20:29:30 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:30 | D | sum error = [ 813.0814, 872.0043, 935.0393, 1002.3048, 1074.3765] +24-11-19 20:29:30 | D | best error = [ 11.0121, 11.0121, 11.0121, 11.0121, 11.0121] +24-11-19 20:29:30 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:30 | D | sum error = [ 1150.2604, 1230.7803, 1316.4804, 1406.3276, 1501.2307] +24-11-19 20:29:30 | D | best error = [ 11.0121, 11.0121, 11.0121, 11.0121, 11.0121] +24-11-19 20:29:30 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:30 | D | sum error = [ 1600.6755, 1704.6818, 1812.5388, 1923.6738, 2037.9052] +24-11-19 20:29:30 | D | best error = [ 11.0121, 11.0121, 11.0121, 11.0121, 11.0121] +24-11-19 20:29:30 | D | + error = [11.0121] +24-11-19 20:29:30 | D | - Calibrating model.layers.15.self_attn.k_proj.weight +24-11-19 20:29:30 | D | + w: sint8 +24-11-19 20:29:30 | D | + x: None +24-11-19 20:29:30 | D | + y: None +24-11-19 20:29:30 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:29:30 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:29:30 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:29:31 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:31 | D | - range ratio = [ 1.0000] +24-11-19 20:29:31 | D | sum error = [ 12.1573] +24-11-19 20:29:31 | D | best error = [ 12.1573] +24-11-19 20:29:44 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:44 | D | sum error = [ 11.7322, 11.9407, 11.5403, 12.0944, 11.8167] +24-11-19 20:29:44 | D | best error = [ 11.7322, 11.7322, 11.5403, 11.5403, 11.5403] +24-11-19 20:29:44 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:44 | D | sum error = [ 12.1660, 12.5361, 14.0937, 14.0045, 14.6476] +24-11-19 20:29:44 | D | best error = [ 11.5403, 11.5403, 11.5403, 11.5403, 11.5403] +24-11-19 20:29:44 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:44 | D | sum error = [ 15.6847, 16.5979, 17.3254, 18.8542, 20.2520] +24-11-19 20:29:44 | D | best error = [ 11.5403, 11.5403, 11.5403, 11.5403, 11.5403] +24-11-19 20:29:44 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:44 | D | sum error = [ 22.4736, 24.4552, 25.4907, 28.4806, 29.6038] +24-11-19 20:29:44 | D | best error = [ 11.5403, 11.5403, 11.5403, 11.5403, 11.5403] +24-11-19 20:29:44 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:44 | D | sum error = [ 33.1675, 35.2018, 37.6605, 40.8918, 43.7123] +24-11-19 20:29:44 | D | best error = [ 11.5403, 11.5403, 11.5403, 11.5403, 11.5403] +24-11-19 20:29:44 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:44 | D | sum error = [ 47.0015, 50.8080, 54.4921, 59.9627, 62.5622] +24-11-19 20:29:44 | D | best error = [ 11.5403, 11.5403, 11.5403, 11.5403, 11.5403] +24-11-19 20:29:44 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:44 | D | sum error = [ 68.5368, 74.2471, 78.7606, 84.6909, 91.4568] +24-11-19 20:29:44 | D | best error = [ 11.5403, 11.5403, 11.5403, 11.5403, 11.5403] +24-11-19 20:29:44 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:44 | D | sum error = [ 99.1960, 106.5401, 114.9033, 123.7939, 132.0639] +24-11-19 20:29:44 | D | best error = [ 11.5403, 11.5403, 11.5403, 11.5403, 11.5403] +24-11-19 20:29:44 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:44 | D | sum error = [ 140.5224, 151.0666, 163.0086, 174.7072, 188.6883] +24-11-19 20:29:44 | D | best error = [ 11.5403, 11.5403, 11.5403, 11.5403, 11.5403] +24-11-19 20:29:44 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:44 | D | sum error = [ 203.3848, 219.0993, 236.5356, 255.2691, 275.0823] +24-11-19 20:29:44 | D | best error = [ 11.5403, 11.5403, 11.5403, 11.5403, 11.5403] +24-11-19 20:29:44 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:44 | D | sum error = [ 296.2584, 319.6548, 343.4119, 369.0349, 398.0291] +24-11-19 20:29:44 | D | best error = [ 11.5403, 11.5403, 11.5403, 11.5403, 11.5403] +24-11-19 20:29:44 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:44 | D | sum error = [ 427.7610, 459.1649, 493.4328, 529.3672, 569.3835] +24-11-19 20:29:44 | D | best error = [ 11.5403, 11.5403, 11.5403, 11.5403, 11.5403] +24-11-19 20:29:44 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:44 | D | sum error = [ 611.0859, 656.9029, 704.9027, 758.3511, 812.8416] +24-11-19 20:29:44 | D | best error = [ 11.5403, 11.5403, 11.5403, 11.5403, 11.5403] +24-11-19 20:29:44 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:44 | D | sum error = [ 873.9043, 936.8125, 1002.7921, 1073.5139, 1146.0338] +24-11-19 20:29:44 | D | best error = [ 11.5403, 11.5403, 11.5403, 11.5403, 11.5403] +24-11-19 20:29:44 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:44 | D | sum error = [ 1223.6718, 1306.3903, 1391.1156, 1479.2365, 1573.5639] +24-11-19 20:29:44 | D | best error = [ 11.5403, 11.5403, 11.5403, 11.5403, 11.5403] +24-11-19 20:29:44 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:44 | D | sum error = [ 1671.7441, 1773.3305, 1877.9249, 1985.2311, 2096.4223] +24-11-19 20:29:44 | D | best error = [ 11.5403, 11.5403, 11.5403, 11.5403, 11.5403] +24-11-19 20:29:44 | D | + error = [11.5403] +24-11-19 20:29:44 | D | - Calibrating model.layers.15.self_attn.v_proj.weight +24-11-19 20:29:44 | D | + w: sint8 +24-11-19 20:29:44 | D | + x: None +24-11-19 20:29:44 | D | + y: None +24-11-19 20:29:44 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:44 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:29:45 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:29:45 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:45 | D | - range ratio = [ 1.0000] +24-11-19 20:29:45 | D | sum error = [ 5.0149] +24-11-19 20:29:45 | D | best error = [ 5.0149] +24-11-19 20:29:45 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:45 | D | sum error = [ 4.9670, 4.9391, 4.9747, 5.0359, 5.1363] +24-11-19 20:29:45 | D | best error = [ 4.6547, 4.5193, 4.4472, 4.4086, 4.3891] +24-11-19 20:29:45 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:45 | D | sum error = [ 5.2449, 5.4041, 5.6159, 5.8914, 6.2292] +24-11-19 20:29:45 | D | best error = [ 4.3790, 4.3752, 4.3738, 4.3734, 4.3734] +24-11-19 20:29:45 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:45 | D | sum error = [ 6.5700, 6.9730, 7.4192, 7.9132, 8.4605] +24-11-19 20:29:45 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 20:29:45 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:45 | D | sum error = [ 9.0726, 9.7042, 10.4124, 11.1582, 11.9757] +24-11-19 20:29:45 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 20:29:45 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:45 | D | sum error = [ 12.8112, 13.7265, 14.6956, 15.7518, 16.8182] +24-11-19 20:29:45 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 20:29:45 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:45 | D | sum error = [ 17.9799, 19.2313, 20.5213, 21.8914, 23.3512] +24-11-19 20:29:45 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 20:29:45 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:45 | D | sum error = [ 24.8862, 26.4812, 28.1892, 29.9746, 31.8837] +24-11-19 20:29:45 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 20:29:45 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:45 | D | sum error = [ 33.8859, 35.9516, 38.1689, 40.4732, 42.8972] +24-11-19 20:29:45 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 20:29:45 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:45 | D | sum error = [ 45.4744, 48.1640, 50.9810, 53.9234, 57.0228] +24-11-19 20:29:45 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 20:29:45 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:45 | D | sum error = [ 60.2677, 63.6886, 67.2310, 70.9740, 74.8773] +24-11-19 20:29:45 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 20:29:45 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:45 | D | sum error = [ 78.9436, 83.2031, 87.6573, 92.3026, 97.1614] +24-11-19 20:29:45 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 20:29:45 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:45 | D | sum error = [ 102.2362, 107.5148, 113.0437, 118.7779, 124.7601] +24-11-19 20:29:45 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 20:29:45 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:45 | D | sum error = [ 130.9766, 137.4395, 144.1704, 151.1554, 158.4102] +24-11-19 20:29:45 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 20:29:45 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:45 | D | sum error = [ 165.9116, 173.6909, 181.7492, 190.1061, 198.7709] +24-11-19 20:29:45 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 20:29:45 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:45 | D | sum error = [ 207.7251, 216.9787, 226.5482, 236.4402, 246.6373] +24-11-19 20:29:45 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 20:29:45 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:45 | D | sum error = [ 257.1546, 268.0004, 279.1551, 290.6476, 302.4724] +24-11-19 20:29:45 | D | best error = [ 4.3734, 4.3734, 4.3734, 4.3734, 4.3734] +24-11-19 20:29:45 | D | + error = [4.3734] +24-11-19 20:29:45 | D | - Calibrating model.layers.15.self_attn.o_proj.weight +24-11-19 20:29:45 | D | + w: sint8 +24-11-19 20:29:45 | D | + x: None +24-11-19 20:29:45 | D | + y: None +24-11-19 20:29:45 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:45 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:29:45 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:29:45 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:45 | D | - range ratio = [ 1.0000] +24-11-19 20:29:45 | D | sum error = [ 1.4542] +24-11-19 20:29:45 | D | best error = [ 1.4542] +24-11-19 20:29:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:46 | D | sum error = [ 1.4388, 1.4300, 1.4265, 1.4341, 1.4417] +24-11-19 20:29:46 | D | best error = [ 1.3636, 1.3224, 1.2956, 1.2784, 1.2661] +24-11-19 20:29:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:46 | D | sum error = [ 1.4527, 1.4828, 1.5147, 1.5567, 1.6121] +24-11-19 20:29:46 | D | best error = [ 1.2569, 1.2506, 1.2464, 1.2429, 1.2410] +24-11-19 20:29:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:46 | D | sum error = [ 1.6724, 1.7409, 1.8271, 1.9214, 2.0300] +24-11-19 20:29:46 | D | best error = [ 1.2395, 1.2387, 1.2380, 1.2375, 1.2370] +24-11-19 20:29:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:46 | D | sum error = [ 2.1460, 2.2762, 2.4125, 2.5628, 2.7307] +24-11-19 20:29:46 | D | best error = [ 1.2367, 1.2365, 1.2364, 1.2364, 1.2363] +24-11-19 20:29:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:46 | D | sum error = [ 2.9062, 3.0971, 3.3064, 3.5220, 3.7579] +24-11-19 20:29:46 | D | best error = [ 1.2363, 1.2363, 1.2363, 1.2362, 1.2362] +24-11-19 20:29:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:46 | D | sum error = [ 4.0050, 4.2708, 4.5541, 4.8541, 5.1688] +24-11-19 20:29:46 | D | best error = [ 1.2362, 1.2362, 1.2362, 1.2362, 1.2362] +24-11-19 20:29:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:46 | D | sum error = [ 5.5022, 5.8559, 6.2328, 6.6255, 7.0420] +24-11-19 20:29:46 | D | best error = [ 1.2362, 1.2362, 1.2362, 1.2362, 1.2362] +24-11-19 20:29:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:46 | D | sum error = [ 7.4888, 7.9552, 8.4452, 8.9646, 9.5160] +24-11-19 20:29:46 | D | best error = [ 1.2362, 1.2362, 1.2362, 1.2362, 1.2362] +24-11-19 20:29:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:46 | D | sum error = [ 10.0908, 10.7029, 11.3382, 12.0122, 12.7215] +24-11-19 20:29:46 | D | best error = [ 1.2362, 1.2362, 1.2362, 1.2362, 1.2362] +24-11-19 20:29:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:46 | D | sum error = [ 13.4723, 14.2544, 15.0771, 15.9398, 16.8462] +24-11-19 20:29:46 | D | best error = [ 1.2362, 1.2362, 1.2362, 1.2362, 1.2362] +24-11-19 20:29:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:46 | D | sum error = [ 17.7963, 18.7944, 19.8321, 20.9210, 22.0586] +24-11-19 20:29:46 | D | best error = [ 1.2362, 1.2362, 1.2362, 1.2362, 1.2362] +24-11-19 20:29:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:46 | D | sum error = [ 23.2506, 24.4992, 25.7959, 27.1538, 28.5731] +24-11-19 20:29:46 | D | best error = [ 1.2362, 1.2362, 1.2362, 1.2362, 1.2362] +24-11-19 20:29:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:46 | D | sum error = [ 30.0509, 31.5959, 33.2064, 34.8811, 36.6266] +24-11-19 20:29:46 | D | best error = [ 1.2362, 1.2362, 1.2362, 1.2362, 1.2362] +24-11-19 20:29:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:46 | D | sum error = [ 38.4447, 40.3348, 42.3003, 44.3409, 46.4633] +24-11-19 20:29:46 | D | best error = [ 1.2362, 1.2362, 1.2362, 1.2362, 1.2362] +24-11-19 20:29:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:46 | D | sum error = [ 48.6674, 50.9490, 53.3185, 55.7760, 58.3252] +24-11-19 20:29:46 | D | best error = [ 1.2362, 1.2362, 1.2362, 1.2362, 1.2362] +24-11-19 20:29:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:46 | D | sum error = [ 60.9636, 63.6994, 66.5262, 69.4496, 72.4696] +24-11-19 20:29:46 | D | best error = [ 1.2362, 1.2362, 1.2362, 1.2362, 1.2362] +24-11-19 20:29:46 | D | + error = [1.2362] +24-11-19 20:29:46 | D | - Calibrating model.layers.15.mlp.up_proj.weight +24-11-19 20:29:46 | D | + w: sint8 +24-11-19 20:29:46 | D | + x: None +24-11-19 20:29:46 | D | + y: None +24-11-19 20:29:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:46 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:29:46 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:29:46 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:46 | D | - range ratio = [ 1.0000] +24-11-19 20:29:46 | D | sum error = [ 6.9888] +24-11-19 20:29:46 | D | best error = [ 6.9888] +24-11-19 20:29:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:47 | D | sum error = [ 6.9564, 6.9153, 6.9445, 7.0244, 7.1468] +24-11-19 20:29:47 | D | best error = [ 6.4951, 6.3043, 6.2015, 6.1468, 6.1166] +24-11-19 20:29:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:47 | D | sum error = [ 7.3386, 7.5870, 7.9217, 8.2716, 8.7119] +24-11-19 20:29:47 | D | best error = [ 6.1027, 6.0971, 6.0948, 6.0941, 6.0940] +24-11-19 20:29:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:47 | D | sum error = [ 9.2199, 9.7988, 10.4476, 11.1336, 11.9182] +24-11-19 20:29:47 | D | best error = [ 6.0940, 6.0940, 6.0940, 6.0940, 6.0940] +24-11-19 20:29:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:47 | D | sum error = [ 12.7395, 13.6593, 14.6574, 15.7022, 16.8174] +24-11-19 20:29:47 | D | best error = [ 6.0940, 6.0940, 6.0940, 6.0940, 6.0940] +24-11-19 20:29:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:47 | D | sum error = [ 18.0231, 19.3104, 20.6761, 22.1369, 23.6765] +24-11-19 20:29:47 | D | best error = [ 6.0940, 6.0940, 6.0940, 6.0940, 6.0940] +24-11-19 20:29:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:47 | D | sum error = [ 25.3187, 27.0502, 28.8725, 30.8251, 32.8719] +24-11-19 20:29:47 | D | best error = [ 6.0940, 6.0940, 6.0940, 6.0940, 6.0940] +24-11-19 20:29:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:47 | D | sum error = [ 35.0518, 37.3295, 39.7548, 42.2828, 44.9627] +24-11-19 20:29:47 | D | best error = [ 6.0940, 6.0940, 6.0940, 6.0940, 6.0940] +24-11-19 20:29:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:47 | D | sum error = [ 47.7983, 50.7493, 53.8825, 57.1753, 60.6288] +24-11-19 20:29:47 | D | best error = [ 6.0940, 6.0940, 6.0940, 6.0940, 6.0940] +24-11-19 20:29:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:47 | D | sum error = [ 64.2594, 68.0807, 72.0878, 76.2937, 80.7074] +24-11-19 20:29:47 | D | best error = [ 6.0940, 6.0940, 6.0940, 6.0940, 6.0940] +24-11-19 20:29:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:47 | D | sum error = [ 85.3378, 90.1963, 95.2734, 100.6278, 106.2000] +24-11-19 20:29:47 | D | best error = [ 6.0940, 6.0940, 6.0940, 6.0940, 6.0940] +24-11-19 20:29:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:47 | D | sum error = [ 112.0581, 118.1546, 124.5182, 131.1656, 138.1196] +24-11-19 20:29:47 | D | best error = [ 6.0940, 6.0940, 6.0940, 6.0940, 6.0940] +24-11-19 20:29:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:47 | D | sum error = [ 145.3646, 152.9350, 160.8202, 169.0209, 177.5622] +24-11-19 20:29:47 | D | best error = [ 6.0940, 6.0940, 6.0940, 6.0940, 6.0940] +24-11-19 20:29:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:47 | D | sum error = [ 186.4603, 195.7088, 205.3217, 215.2954, 225.6584] +24-11-19 20:29:47 | D | best error = [ 6.0940, 6.0940, 6.0940, 6.0940, 6.0940] +24-11-19 20:29:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:47 | D | sum error = [ 236.4144, 247.5665, 259.1272, 271.1159, 283.5109] +24-11-19 20:29:47 | D | best error = [ 6.0940, 6.0940, 6.0940, 6.0940, 6.0940] +24-11-19 20:29:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:47 | D | sum error = [ 296.3481, 309.6364, 323.3702, 337.5647, 352.2219] +24-11-19 20:29:47 | D | best error = [ 6.0940, 6.0940, 6.0940, 6.0940, 6.0940] +24-11-19 20:29:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:47 | D | sum error = [ 367.3282, 382.9146, 398.9756, 415.5041, 432.5008] +24-11-19 20:29:47 | D | best error = [ 6.0940, 6.0940, 6.0940, 6.0940, 6.0940] +24-11-19 20:29:47 | D | + error = [6.0940] +24-11-19 20:29:47 | D | - Calibrating model.layers.15.mlp.gate_proj.weight +24-11-19 20:29:47 | D | + w: sint8 +24-11-19 20:29:47 | D | + x: None +24-11-19 20:29:47 | D | + y: None +24-11-19 20:29:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:47 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:29:47 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:29:47 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:47 | D | - range ratio = [ 1.0000] +24-11-19 20:29:47 | D | sum error = [ 7.1709] +24-11-19 20:29:47 | D | best error = [ 7.1709] +24-11-19 20:29:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:48 | D | sum error = [ 7.1040, 7.1006, 7.1258, 7.2033, 7.3494] +24-11-19 20:29:48 | D | best error = [ 6.6442, 6.4581, 6.3563, 6.2982, 6.2686] +24-11-19 20:29:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:48 | D | sum error = [ 7.5380, 7.7914, 8.1129, 8.4938, 8.9463] +24-11-19 20:29:48 | D | best error = [ 6.2545, 6.2477, 6.2456, 6.2452, 6.2449] +24-11-19 20:29:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:48 | D | sum error = [ 9.4641, 10.0899, 10.7238, 11.4596, 12.2416] +24-11-19 20:29:48 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:29:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:48 | D | sum error = [ 13.1169, 14.0598, 15.0826, 16.1815, 17.3476] +24-11-19 20:29:48 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:29:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:48 | D | sum error = [ 18.6096, 19.9467, 21.4049, 22.9079, 24.5510] +24-11-19 20:29:48 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:29:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:48 | D | sum error = [ 26.2961, 28.1123, 30.0754, 32.1415, 34.3262] +24-11-19 20:29:48 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:29:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:48 | D | sum error = [ 36.6662, 39.1314, 41.7667, 44.5150, 47.4413] +24-11-19 20:29:48 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:29:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:48 | D | sum error = [ 50.5500, 53.8270, 57.3001, 60.9547, 64.8489] +24-11-19 20:29:48 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:29:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:48 | D | sum error = [ 68.9413, 73.2766, 77.8382, 82.6793, 87.7440] +24-11-19 20:29:48 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:29:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:48 | D | sum error = [ 93.1184, 98.7964, 104.7799, 111.0939, 117.7812] +24-11-19 20:29:48 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:29:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:48 | D | sum error = [ 124.7913, 132.2077, 139.9990, 148.2005, 156.8025] +24-11-19 20:29:48 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:29:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:48 | D | sum error = [ 165.8658, 175.3635, 185.3436, 195.8249, 206.7959] +24-11-19 20:29:48 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:29:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:48 | D | sum error = [ 218.3114, 230.3480, 242.9170, 256.0899, 269.8580] +24-11-19 20:29:48 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:29:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:48 | D | sum error = [ 284.2224, 299.2001, 314.8097, 331.1142, 348.0093] +24-11-19 20:29:48 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:29:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:48 | D | sum error = [ 365.6222, 383.9108, 402.8912, 422.5553, 442.9553] +24-11-19 20:29:48 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:29:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:48 | D | sum error = [ 464.0749, 485.8898, 508.4140, 531.6355, 555.5715] +24-11-19 20:29:48 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:29:48 | D | + error = [6.2449] +24-11-19 20:29:48 | D | - Calibrating model.layers.15.mlp.down_proj.weight +24-11-19 20:29:48 | D | + w: sint8 +24-11-19 20:29:48 | D | + x: None +24-11-19 20:29:48 | D | + y: None +24-11-19 20:29:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:48 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:29:49 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:29:49 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:49 | D | - range ratio = [ 1.0000] +24-11-19 20:29:49 | D | sum error = [ 2.1369] +24-11-19 20:29:49 | D | best error = [ 2.1369] +24-11-19 20:29:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:50 | D | sum error = [ 2.1193, 2.1062, 2.0949, 2.0912, 2.0894] +24-11-19 20:29:50 | D | best error = [ 2.0652, 2.0283, 2.0027, 1.9851, 1.9699] +24-11-19 20:29:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:50 | D | sum error = [ 2.0955, 2.1101, 2.1357, 2.1709, 2.2162] +24-11-19 20:29:50 | D | best error = [ 1.9583, 1.9502, 1.9438, 1.9392, 1.9362] +24-11-19 20:29:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:50 | D | sum error = [ 2.2739, 2.3419, 2.4231, 2.5197, 2.6365] +24-11-19 20:29:50 | D | best error = [ 1.9347, 1.9333, 1.9323, 1.9318, 1.9314] +24-11-19 20:29:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:50 | D | sum error = [ 2.7607, 2.9062, 3.0670, 3.2433, 3.4413] +24-11-19 20:29:50 | D | best error = [ 1.9312, 1.9311, 1.9310, 1.9310, 1.9310] +24-11-19 20:29:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:50 | D | sum error = [ 3.6534, 3.8901, 4.1388, 4.4165, 4.7110] +24-11-19 20:29:50 | D | best error = [ 1.9310, 1.9310, 1.9309, 1.9309, 1.9309] +24-11-19 20:29:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:50 | D | sum error = [ 5.0255, 5.3713, 5.7321, 6.1187, 6.5394] +24-11-19 20:29:50 | D | best error = [ 1.9309, 1.9309, 1.9309, 1.9309, 1.9309] +24-11-19 20:29:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:50 | D | sum error = [ 6.9768, 7.4512, 7.9504, 8.4869, 9.0548] +24-11-19 20:29:50 | D | best error = [ 1.9309, 1.9309, 1.9309, 1.9309, 1.9309] +24-11-19 20:29:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:50 | D | sum error = [ 9.6559, 10.2957, 10.9785, 11.6919, 12.4490] +24-11-19 20:29:50 | D | best error = [ 1.9309, 1.9309, 1.9309, 1.9309, 1.9309] +24-11-19 20:29:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:50 | D | sum error = [ 13.2539, 14.1034, 15.0001, 15.9467, 16.9468] +24-11-19 20:29:50 | D | best error = [ 1.9309, 1.9309, 1.9309, 1.9309, 1.9309] +24-11-19 20:29:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:50 | D | sum error = [ 18.0012, 19.1104, 20.2823, 21.5147, 22.8113] +24-11-19 20:29:50 | D | best error = [ 1.9309, 1.9309, 1.9309, 1.9309, 1.9309] +24-11-19 20:29:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:50 | D | sum error = [ 24.1777, 25.6163, 27.1215, 28.7029, 30.3620] +24-11-19 20:29:50 | D | best error = [ 1.9309, 1.9309, 1.9309, 1.9309, 1.9309] +24-11-19 20:29:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:50 | D | sum error = [ 32.1032, 33.9305, 35.8442, 37.8472, 39.9452] +24-11-19 20:29:50 | D | best error = [ 1.9309, 1.9309, 1.9309, 1.9309, 1.9309] +24-11-19 20:29:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:50 | D | sum error = [ 42.1369, 44.4310, 46.8249, 49.3239, 51.9319] +24-11-19 20:29:50 | D | best error = [ 1.9309, 1.9309, 1.9309, 1.9309, 1.9309] +24-11-19 20:29:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:50 | D | sum error = [ 54.6552, 57.4889, 60.4402, 63.5155, 66.7059] +24-11-19 20:29:50 | D | best error = [ 1.9309, 1.9309, 1.9309, 1.9309, 1.9309] +24-11-19 20:29:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:50 | D | sum error = [ 70.0264, 73.4750, 77.0595, 80.7784, 84.6350] +24-11-19 20:29:50 | D | best error = [ 1.9309, 1.9309, 1.9309, 1.9309, 1.9309] +24-11-19 20:29:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:50 | D | sum error = [ 88.6330, 92.7716, 97.0552, 101.4890, 106.0722] +24-11-19 20:29:50 | D | best error = [ 1.9309, 1.9309, 1.9309, 1.9309, 1.9309] +24-11-19 20:29:50 | D | + error = [1.9309] +24-11-19 20:29:50 | D | - Quantizing model.layers.15.self_attn.q_proj.weight +24-11-19 20:29:51 | D | - Quantizing model.layers.15.self_attn.k_proj.weight +24-11-19 20:29:52 | D | - Quantizing model.layers.15.self_attn.v_proj.weight +24-11-19 20:29:53 | D | - Quantizing model.layers.15.self_attn.o_proj.weight +24-11-19 20:29:54 | D | - Quantizing model.layers.15.mlp.up_proj.weight +24-11-19 20:29:55 | D | - Quantizing model.layers.15.mlp.gate_proj.weight +24-11-19 20:29:56 | D | - Quantizing model.layers.15.mlp.down_proj.weight +24-11-19 20:30:04 | D | - Quantizing layer model.layers.16 +24-11-19 20:30:04 | D | - Calibrating model.layers.16.self_attn.q_proj.weight +24-11-19 20:30:04 | D | + w: sint8 +24-11-19 20:30:04 | D | + x: None +24-11-19 20:30:04 | D | + y: None +24-11-19 20:30:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:30:04 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:04 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:30:05 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:30:05 | D | - range ratio = [ 1.0000] +24-11-19 20:30:05 | D | sum error = [ 12.5600] +24-11-19 20:30:05 | D | best error = [ 12.5600] +24-11-19 20:30:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:17 | D | sum error = [ 12.5025, 12.5747, 12.5566, 12.5487, 12.8467] +24-11-19 20:30:17 | D | best error = [ 12.5025, 12.5025, 12.5025, 12.5025, 12.5025] +24-11-19 20:30:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:17 | D | sum error = [ 13.3798, 13.7473, 14.3049, 14.7643, 15.6682] +24-11-19 20:30:17 | D | best error = [ 12.5025, 12.5025, 12.5025, 12.5025, 12.5025] +24-11-19 20:30:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:17 | D | sum error = [ 16.5563, 17.6749, 18.9433, 20.6159, 21.6688] +24-11-19 20:30:17 | D | best error = [ 12.5025, 12.5025, 12.5025, 12.5025, 12.5025] +24-11-19 20:30:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:17 | D | sum error = [ 23.2052, 25.2650, 27.1644, 29.3194, 31.9120] +24-11-19 20:30:17 | D | best error = [ 12.5025, 12.5025, 12.5025, 12.5025, 12.5025] +24-11-19 20:30:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:17 | D | sum error = [ 33.9088, 36.6185, 39.6267, 42.5067, 46.0917] +24-11-19 20:30:17 | D | best error = [ 12.5025, 12.5025, 12.5025, 12.5025, 12.5025] +24-11-19 20:30:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:17 | D | sum error = [ 49.4641, 53.3164, 57.3323, 61.9432, 66.9603] +24-11-19 20:30:17 | D | best error = [ 12.5025, 12.5025, 12.5025, 12.5025, 12.5025] +24-11-19 20:30:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:17 | D | sum error = [ 71.5883, 77.4535, 83.0244, 89.1143, 96.0722] +24-11-19 20:30:17 | D | best error = [ 12.5025, 12.5025, 12.5025, 12.5025, 12.5025] +24-11-19 20:30:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:17 | D | sum error = [ 103.0509, 111.0347, 119.3156, 128.1616, 137.7517] +24-11-19 20:30:17 | D | best error = [ 12.5025, 12.5025, 12.5025, 12.5025, 12.5025] +24-11-19 20:30:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:17 | D | sum error = [ 147.7501, 158.6698, 170.4206, 183.3932, 196.6781] +24-11-19 20:30:17 | D | best error = [ 12.5025, 12.5025, 12.5025, 12.5025, 12.5025] +24-11-19 20:30:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:17 | D | sum error = [ 211.2716, 227.0415, 243.4256, 261.6174, 280.4457] +24-11-19 20:30:17 | D | best error = [ 12.5025, 12.5025, 12.5025, 12.5025, 12.5025] +24-11-19 20:30:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:17 | D | sum error = [ 300.7619, 322.8247, 346.3244, 371.4009, 398.3735] +24-11-19 20:30:17 | D | best error = [ 12.5025, 12.5025, 12.5025, 12.5025, 12.5025] +24-11-19 20:30:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:17 | D | sum error = [ 427.2299, 457.9643, 491.0635, 526.5821, 564.5883] +24-11-19 20:30:17 | D | best error = [ 12.5025, 12.5025, 12.5025, 12.5025, 12.5025] +24-11-19 20:30:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:17 | D | sum error = [ 605.2228, 649.2378, 696.2274, 746.9527, 801.1418] +24-11-19 20:30:17 | D | best error = [ 12.5025, 12.5025, 12.5025, 12.5025, 12.5025] +24-11-19 20:30:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:17 | D | sum error = [ 859.7923, 922.5129, 990.5202, 1063.9734, 1143.2278] +24-11-19 20:30:17 | D | best error = [ 12.5025, 12.5025, 12.5025, 12.5025, 12.5025] +24-11-19 20:30:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:17 | D | sum error = [ 1228.3655, 1319.7872, 1418.4362, 1523.6916, 1636.3957] +24-11-19 20:30:17 | D | best error = [ 12.5025, 12.5025, 12.5025, 12.5025, 12.5025] +24-11-19 20:30:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:17 | D | sum error = [ 1756.0428, 1883.4940, 2017.5395, 2158.6517, 2305.6459] +24-11-19 20:30:17 | D | best error = [ 12.5025, 12.5025, 12.5025, 12.5025, 12.5025] +24-11-19 20:30:17 | D | + error = [12.5025] +24-11-19 20:30:17 | D | - Calibrating model.layers.16.self_attn.k_proj.weight +24-11-19 20:30:17 | D | + w: sint8 +24-11-19 20:30:17 | D | + x: None +24-11-19 20:30:17 | D | + y: None +24-11-19 20:30:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:30:17 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:30:18 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:30:18 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:30:18 | D | - range ratio = [ 1.0000] +24-11-19 20:30:18 | D | sum error = [ 12.8463] +24-11-19 20:30:18 | D | best error = [ 12.8463] +24-11-19 20:30:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:31 | D | sum error = [ 12.4813, 12.1977, 12.7538, 13.1810, 13.1615] +24-11-19 20:30:31 | D | best error = [ 12.4813, 12.1977, 12.1977, 12.1977, 12.1977] +24-11-19 20:30:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:31 | D | sum error = [ 13.0740, 13.4931, 14.8970, 15.0069, 15.7193] +24-11-19 20:30:31 | D | best error = [ 12.1977, 12.1977, 12.1977, 12.1977, 12.1977] +24-11-19 20:30:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:31 | D | sum error = [ 16.5194, 17.8258, 20.0324, 20.4326, 22.3104] +24-11-19 20:30:31 | D | best error = [ 12.1977, 12.1977, 12.1977, 12.1977, 12.1977] +24-11-19 20:30:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:31 | D | sum error = [ 23.4175, 25.7304, 27.5961, 29.6746, 31.7100] +24-11-19 20:30:31 | D | best error = [ 12.1977, 12.1977, 12.1977, 12.1977, 12.1977] +24-11-19 20:30:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:31 | D | sum error = [ 34.9792, 37.1116, 40.2011, 43.4676, 47.1789] +24-11-19 20:30:31 | D | best error = [ 12.1977, 12.1977, 12.1977, 12.1977, 12.1977] +24-11-19 20:30:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:31 | D | sum error = [ 50.0648, 53.3754, 57.7442, 62.1220, 67.7174] +24-11-19 20:30:31 | D | best error = [ 12.1977, 12.1977, 12.1977, 12.1977, 12.1977] +24-11-19 20:30:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:31 | D | sum error = [ 72.2358, 77.3911, 83.1439, 89.9527, 96.2396] +24-11-19 20:30:31 | D | best error = [ 12.1977, 12.1977, 12.1977, 12.1977, 12.1977] +24-11-19 20:30:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:31 | D | sum error = [ 102.6789, 110.1202, 118.5583, 126.5310, 136.0100] +24-11-19 20:30:31 | D | best error = [ 12.1977, 12.1977, 12.1977, 12.1977, 12.1977] +24-11-19 20:30:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:31 | D | sum error = [ 145.8364, 156.7153, 167.4718, 179.5092, 192.9174] +24-11-19 20:30:31 | D | best error = [ 12.1977, 12.1977, 12.1977, 12.1977, 12.1977] +24-11-19 20:30:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:31 | D | sum error = [ 207.3499, 223.7543, 241.0383, 259.3145, 279.5196] +24-11-19 20:30:31 | D | best error = [ 12.1977, 12.1977, 12.1977, 12.1977, 12.1977] +24-11-19 20:30:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:31 | D | sum error = [ 301.0380, 324.6761, 349.5133, 376.3487, 405.1245] +24-11-19 20:30:31 | D | best error = [ 12.1977, 12.1977, 12.1977, 12.1977, 12.1977] +24-11-19 20:30:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:31 | D | sum error = [ 435.3228, 468.1891, 503.0541, 541.0872, 581.2265] +24-11-19 20:30:31 | D | best error = [ 12.1977, 12.1977, 12.1977, 12.1977, 12.1977] +24-11-19 20:30:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:31 | D | sum error = [ 624.1706, 669.5486, 717.4414, 770.1451, 825.7488] +24-11-19 20:30:31 | D | best error = [ 12.1977, 12.1977, 12.1977, 12.1977, 12.1977] +24-11-19 20:30:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:31 | D | sum error = [ 885.4265, 949.7729, 1018.0146, 1090.8890, 1168.3229] +24-11-19 20:30:31 | D | best error = [ 12.1977, 12.1977, 12.1977, 12.1977, 12.1977] +24-11-19 20:30:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:31 | D | sum error = [ 1251.1818, 1341.3776, 1437.5891, 1538.9482, 1648.4626] +24-11-19 20:30:31 | D | best error = [ 12.1977, 12.1977, 12.1977, 12.1977, 12.1977] +24-11-19 20:30:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:31 | D | sum error = [ 1765.7760, 1889.4731, 2020.1563, 2156.1758, 2298.6044] +24-11-19 20:30:31 | D | best error = [ 12.1977, 12.1977, 12.1977, 12.1977, 12.1977] +24-11-19 20:30:31 | D | + error = [12.1977] +24-11-19 20:30:31 | D | - Calibrating model.layers.16.self_attn.v_proj.weight +24-11-19 20:30:31 | D | + w: sint8 +24-11-19 20:30:31 | D | + x: None +24-11-19 20:30:31 | D | + y: None +24-11-19 20:30:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:31 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:31 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:30:31 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:30:31 | D | - range ratio = [ 1.0000] +24-11-19 20:30:31 | D | sum error = [ 5.3647] +24-11-19 20:30:31 | D | best error = [ 5.3647] +24-11-19 20:30:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:32 | D | sum error = [ 5.3300, 5.3273, 5.3295, 5.3943, 5.4892] +24-11-19 20:30:32 | D | best error = [ 4.9935, 4.8534, 4.7712, 4.7253, 4.7037] +24-11-19 20:30:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:32 | D | sum error = [ 5.6370, 5.8267, 6.0929, 6.3377, 6.6851] +24-11-19 20:30:32 | D | best error = [ 4.6941, 4.6899, 4.6877, 4.6869, 4.6868] +24-11-19 20:30:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:32 | D | sum error = [ 7.0378, 7.4852, 7.9770, 8.4955, 9.1010] +24-11-19 20:30:32 | D | best error = [ 4.6868, 4.6868, 4.6868, 4.6868, 4.6868] +24-11-19 20:30:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:32 | D | sum error = [ 9.7138, 10.4185, 11.1517, 11.9933, 12.8205] +24-11-19 20:30:32 | D | best error = [ 4.6868, 4.6868, 4.6868, 4.6868, 4.6868] +24-11-19 20:30:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:32 | D | sum error = [ 13.7459, 14.7339, 15.7659, 16.8739, 18.0559] +24-11-19 20:30:32 | D | best error = [ 4.6868, 4.6868, 4.6868, 4.6868, 4.6868] +24-11-19 20:30:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:32 | D | sum error = [ 19.3043, 20.6296, 22.0175, 23.4947, 25.0597] +24-11-19 20:30:32 | D | best error = [ 4.6868, 4.6868, 4.6868, 4.6868, 4.6868] +24-11-19 20:30:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:32 | D | sum error = [ 26.6932, 28.4022, 30.2486, 32.1574, 34.1823] +24-11-19 20:30:32 | D | best error = [ 4.6868, 4.6868, 4.6868, 4.6868, 4.6868] +24-11-19 20:30:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:32 | D | sum error = [ 36.3032, 38.5545, 40.8759, 43.3553, 45.9371] +24-11-19 20:30:32 | D | best error = [ 4.6868, 4.6868, 4.6868, 4.6868, 4.6868] +24-11-19 20:30:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:32 | D | sum error = [ 48.6710, 51.5212, 54.4953, 57.6243, 60.9100] +24-11-19 20:30:32 | D | best error = [ 4.6868, 4.6868, 4.6868, 4.6868, 4.6868] +24-11-19 20:30:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:32 | D | sum error = [ 64.3258, 67.9127, 71.6444, 75.5536, 79.6350] +24-11-19 20:30:32 | D | best error = [ 4.6868, 4.6868, 4.6868, 4.6868, 4.6868] +24-11-19 20:30:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:32 | D | sum error = [ 83.8989, 88.3379, 92.9854, 97.8381, 102.8834] +24-11-19 20:30:32 | D | best error = [ 4.6868, 4.6868, 4.6868, 4.6868, 4.6868] +24-11-19 20:30:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:32 | D | sum error = [ 108.1426, 113.6147, 119.3089, 125.2376, 131.4035] +24-11-19 20:30:32 | D | best error = [ 4.6868, 4.6868, 4.6868, 4.6868, 4.6868] +24-11-19 20:30:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:32 | D | sum error = [ 137.8080, 144.4692, 151.3787, 158.5236, 165.9736] +24-11-19 20:30:32 | D | best error = [ 4.6868, 4.6868, 4.6868, 4.6868, 4.6868] +24-11-19 20:30:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:32 | D | sum error = [ 173.6657, 181.6500, 189.9070, 198.4520, 207.2702] +24-11-19 20:30:32 | D | best error = [ 4.6868, 4.6868, 4.6868, 4.6868, 4.6868] +24-11-19 20:30:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:32 | D | sum error = [ 216.3916, 225.7965, 235.5213, 245.5527, 255.8924] +24-11-19 20:30:32 | D | best error = [ 4.6868, 4.6868, 4.6868, 4.6868, 4.6868] +24-11-19 20:30:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:32 | D | sum error = [ 266.5261, 277.4909, 288.7613, 300.3478, 312.2656] +24-11-19 20:30:32 | D | best error = [ 4.6868, 4.6868, 4.6868, 4.6868, 4.6868] +24-11-19 20:30:32 | D | + error = [4.6868] +24-11-19 20:30:32 | D | - Calibrating model.layers.16.self_attn.o_proj.weight +24-11-19 20:30:32 | D | + w: sint8 +24-11-19 20:30:32 | D | + x: None +24-11-19 20:30:32 | D | + y: None +24-11-19 20:30:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:32 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:32 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:30:32 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:30:32 | D | - range ratio = [ 1.0000] +24-11-19 20:30:32 | D | sum error = [ 1.6722] +24-11-19 20:30:32 | D | best error = [ 1.6722] +24-11-19 20:30:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:33 | D | sum error = [ 1.6592, 1.6519, 1.6511, 1.6611, 1.6750] +24-11-19 20:30:33 | D | best error = [ 1.5607, 1.5097, 1.4782, 1.4582, 1.4444] +24-11-19 20:30:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:33 | D | sum error = [ 1.7010, 1.7280, 1.7796, 1.8423, 1.9131] +24-11-19 20:30:33 | D | best error = [ 1.4351, 1.4287, 1.4241, 1.4218, 1.4202] +24-11-19 20:30:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:33 | D | sum error = [ 1.9965, 2.0871, 2.1925, 2.3098, 2.4444] +24-11-19 20:30:33 | D | best error = [ 1.4192, 1.4185, 1.4178, 1.4175, 1.4172] +24-11-19 20:30:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:33 | D | sum error = [ 2.6045, 2.7616, 2.9361, 3.1286, 3.3351] +24-11-19 20:30:33 | D | best error = [ 1.4169, 1.4168, 1.4167, 1.4167, 1.4167] +24-11-19 20:30:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:33 | D | sum error = [ 3.5611, 3.7920, 4.0507, 4.3177, 4.6059] +24-11-19 20:30:33 | D | best error = [ 1.4167, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 20:30:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:33 | D | sum error = [ 4.9178, 5.2496, 5.5907, 5.9587, 6.3555] +24-11-19 20:30:33 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 20:30:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:33 | D | sum error = [ 6.7661, 7.2054, 7.6636, 8.1543, 8.6689] +24-11-19 20:30:33 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 20:30:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:33 | D | sum error = [ 9.2138, 9.7905, 10.3986, 11.0382, 11.7149] +24-11-19 20:30:33 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 20:30:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:33 | D | sum error = [ 12.4217, 13.1676, 13.9460, 14.7758, 15.6388] +24-11-19 20:30:33 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 20:30:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:33 | D | sum error = [ 16.5569, 17.5130, 18.5200, 19.5834, 20.6965] +24-11-19 20:30:33 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 20:30:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:33 | D | sum error = [ 21.8647, 23.0924, 24.3761, 25.7251, 27.1339] +24-11-19 20:30:33 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 20:30:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:33 | D | sum error = [ 28.6179, 30.1690, 31.7909, 33.4837, 35.2552] +24-11-19 20:30:33 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 20:30:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:33 | D | sum error = [ 37.1078, 39.0345, 41.0547, 43.1651, 45.3649] +24-11-19 20:30:33 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 20:30:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:33 | D | sum error = [ 47.6557, 50.0359, 52.5144, 55.0957, 57.7760] +24-11-19 20:30:33 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 20:30:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:33 | D | sum error = [ 60.5623, 63.4517, 66.4508, 69.5601, 72.7870] +24-11-19 20:30:33 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 20:30:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:33 | D | sum error = [ 76.1305, 79.5928, 83.1732, 86.8755, 90.7061] +24-11-19 20:30:33 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 20:30:33 | D | + error = [1.4166] +24-11-19 20:30:33 | D | - Calibrating model.layers.16.mlp.up_proj.weight +24-11-19 20:30:33 | D | + w: sint8 +24-11-19 20:30:33 | D | + x: None +24-11-19 20:30:33 | D | + y: None +24-11-19 20:30:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:33 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:33 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:30:33 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:30:33 | D | - range ratio = [ 1.0000] +24-11-19 20:30:33 | D | sum error = [ 7.4575] +24-11-19 20:30:33 | D | best error = [ 7.4575] +24-11-19 20:30:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:34 | D | sum error = [ 7.3823, 7.3821, 7.3901, 7.4678, 7.6146] +24-11-19 20:30:34 | D | best error = [ 6.9161, 6.7103, 6.6029, 6.5384, 6.5040] +24-11-19 20:30:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:34 | D | sum error = [ 7.8014, 8.0687, 8.4295, 8.8201, 9.2559] +24-11-19 20:30:34 | D | best error = [ 6.4879, 6.4812, 6.4790, 6.4784, 6.4781] +24-11-19 20:30:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:34 | D | sum error = [ 9.8098, 10.4240, 11.0880, 11.8312, 12.6418] +24-11-19 20:30:34 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:30:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:34 | D | sum error = [ 13.5323, 14.5163, 15.5390, 16.6469, 17.8689] +24-11-19 20:30:34 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:30:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:34 | D | sum error = [ 19.1350, 20.4818, 21.9364, 23.4631, 25.0945] +24-11-19 20:30:34 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:30:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:34 | D | sum error = [ 26.8386, 28.6641, 30.6115, 32.6520, 34.8590] +24-11-19 20:30:34 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:30:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:34 | D | sum error = [ 37.1391, 39.5563, 42.1485, 44.8167, 47.6702] +24-11-19 20:30:34 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:30:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:34 | D | sum error = [ 50.6679, 53.8224, 57.1382, 60.6388, 64.3069] +24-11-19 20:30:34 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:30:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:34 | D | sum error = [ 68.1781, 72.2586, 76.5362, 81.0265, 85.7546] +24-11-19 20:30:34 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:30:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:34 | D | sum error = [ 90.6854, 95.8907, 101.3347, 107.0613, 113.0269] +24-11-19 20:30:34 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:30:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:34 | D | sum error = [ 119.2687, 125.8423, 132.6862, 139.8445, 147.3285] +24-11-19 20:30:34 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:30:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:34 | D | sum error = [ 155.1344, 163.2788, 171.8005, 180.6834, 189.9322] +24-11-19 20:30:34 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:30:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:34 | D | sum error = [ 199.5741, 209.6078, 220.0466, 230.9230, 242.2221] +24-11-19 20:30:34 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:30:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:34 | D | sum error = [ 253.9517, 266.1334, 278.7642, 291.8697, 305.4404] +24-11-19 20:30:34 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:30:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:34 | D | sum error = [ 319.4758, 333.9901, 349.0141, 364.5571, 380.6077] +24-11-19 20:30:34 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:30:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:34 | D | sum error = [ 397.1607, 414.2344, 431.8329, 449.9387, 468.5922] +24-11-19 20:30:34 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:30:34 | D | + error = [6.4781] +24-11-19 20:30:34 | D | - Calibrating model.layers.16.mlp.gate_proj.weight +24-11-19 20:30:34 | D | + w: sint8 +24-11-19 20:30:34 | D | + x: None +24-11-19 20:30:34 | D | + y: None +24-11-19 20:30:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:34 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:34 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:30:34 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:30:34 | D | - range ratio = [ 1.0000] +24-11-19 20:30:34 | D | sum error = [ 7.6659] +24-11-19 20:30:34 | D | best error = [ 7.6659] +24-11-19 20:30:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:35 | D | sum error = [ 7.6077, 7.5893, 7.6238, 7.7343, 7.8522] +24-11-19 20:30:35 | D | best error = [ 7.1297, 6.9201, 6.8046, 6.7424, 6.7084] +24-11-19 20:30:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:35 | D | sum error = [ 8.0636, 8.3361, 8.6855, 9.0863, 9.5823] +24-11-19 20:30:35 | D | best error = [ 6.6941, 6.6877, 6.6848, 6.6838, 6.6836] +24-11-19 20:30:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:35 | D | sum error = [ 10.1345, 10.7676, 11.4837, 12.2639, 13.1070] +24-11-19 20:30:35 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 20:30:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:35 | D | sum error = [ 14.0633, 15.0754, 16.1904, 17.3724, 18.6040] +24-11-19 20:30:35 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 20:30:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:35 | D | sum error = [ 19.9848, 21.4413, 22.9854, 24.6393, 26.4198] +24-11-19 20:30:35 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 20:30:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:35 | D | sum error = [ 28.2931, 30.2718, 32.3867, 34.6269, 37.0037] +24-11-19 20:30:35 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 20:30:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:35 | D | sum error = [ 39.5257, 42.2166, 45.0458, 48.0561, 51.2299] +24-11-19 20:30:35 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 20:30:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:35 | D | sum error = [ 54.5831, 58.1687, 61.9745, 65.9943, 70.2140] +24-11-19 20:30:35 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 20:30:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:35 | D | sum error = [ 74.7052, 79.4082, 84.4360, 89.6911, 95.2677] +24-11-19 20:30:35 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 20:30:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:35 | D | sum error = [ 101.1613, 107.3875, 113.9406, 120.8661, 128.2062] +24-11-19 20:30:35 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 20:30:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:35 | D | sum error = [ 135.9111, 144.0098, 152.5689, 161.5906, 171.0741] +24-11-19 20:30:35 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 20:30:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:35 | D | sum error = [ 181.0332, 191.5396, 202.5555, 214.1256, 226.2635] +24-11-19 20:30:35 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 20:30:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:35 | D | sum error = [ 238.9665, 252.2946, 266.2083, 280.7728, 295.9709] +24-11-19 20:30:35 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 20:30:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:35 | D | sum error = [ 311.8401, 328.4036, 345.6747, 363.6644, 382.3818] +24-11-19 20:30:35 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 20:30:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:35 | D | sum error = [ 401.8340, 422.0333, 443.0008, 464.7583, 487.2961] +24-11-19 20:30:35 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 20:30:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:35 | D | sum error = [ 510.5737, 534.6417, 559.4916, 585.1074, 611.4979] +24-11-19 20:30:35 | D | best error = [ 6.6836, 6.6836, 6.6836, 6.6836, 6.6836] +24-11-19 20:30:35 | D | + error = [6.6836] +24-11-19 20:30:35 | D | - Calibrating model.layers.16.mlp.down_proj.weight +24-11-19 20:30:35 | D | + w: sint8 +24-11-19 20:30:35 | D | + x: None +24-11-19 20:30:35 | D | + y: None +24-11-19 20:30:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:35 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:36 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:30:36 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:30:36 | D | - range ratio = [ 1.0000] +24-11-19 20:30:36 | D | sum error = [ 2.7203] +24-11-19 20:30:36 | D | best error = [ 2.7203] +24-11-19 20:30:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:37 | D | sum error = [ 2.7030, 2.6876, 2.6643, 2.6539, 2.6508] +24-11-19 20:30:37 | D | best error = [ 2.5824, 2.5108, 2.4638, 2.4306, 2.4046] +24-11-19 20:30:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:37 | D | sum error = [ 2.6505, 2.6692, 2.6888, 2.7267, 2.7703] +24-11-19 20:30:37 | D | best error = [ 2.3833, 2.3669, 2.3549, 2.3475, 2.3413] +24-11-19 20:30:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:37 | D | sum error = [ 2.8255, 2.9008, 2.9914, 3.0958, 3.2109] +24-11-19 20:30:37 | D | best error = [ 2.3372, 2.3343, 2.3324, 2.3310, 2.3303] +24-11-19 20:30:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:37 | D | sum error = [ 3.3525, 3.5217, 3.6989, 3.9056, 4.1390] +24-11-19 20:30:37 | D | best error = [ 2.3297, 2.3294, 2.3292, 2.3291, 2.3290] +24-11-19 20:30:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:37 | D | sum error = [ 4.3853, 4.6711, 4.9796, 5.3153, 5.6732] +24-11-19 20:30:37 | D | best error = [ 2.3290, 2.3289, 2.3289, 2.3289, 2.3289] +24-11-19 20:30:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:37 | D | sum error = [ 6.0652, 6.4922, 6.9384, 7.4292, 7.9467] +24-11-19 20:30:37 | D | best error = [ 2.3289, 2.3289, 2.3289, 2.3289, 2.3289] +24-11-19 20:30:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:37 | D | sum error = [ 8.5031, 9.0919, 9.7230, 10.3977, 11.1110] +24-11-19 20:30:37 | D | best error = [ 2.3289, 2.3289, 2.3289, 2.3289, 2.3289] +24-11-19 20:30:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:37 | D | sum error = [ 11.8685, 12.6820, 13.5426, 14.4545, 15.4256] +24-11-19 20:30:37 | D | best error = [ 2.3289, 2.3289, 2.3289, 2.3289, 2.3289] +24-11-19 20:30:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:37 | D | sum error = [ 16.4526, 17.5486, 18.7004, 19.9115, 21.1967] +24-11-19 20:30:37 | D | best error = [ 2.3289, 2.3289, 2.3289, 2.3289, 2.3289] +24-11-19 20:30:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:37 | D | sum error = [ 22.5498, 23.9765, 25.4770, 27.0568, 28.7191] +24-11-19 20:30:37 | D | best error = [ 2.3289, 2.3289, 2.3289, 2.3289, 2.3289] +24-11-19 20:30:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:37 | D | sum error = [ 30.4680, 32.3094, 34.2389, 36.2689, 38.3940] +24-11-19 20:30:37 | D | best error = [ 2.3289, 2.3289, 2.3289, 2.3289, 2.3289] +24-11-19 20:30:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:37 | D | sum error = [ 40.6317, 42.9790, 45.4336, 48.0059, 50.6873] +24-11-19 20:30:37 | D | best error = [ 2.3289, 2.3289, 2.3289, 2.3289, 2.3289] +24-11-19 20:30:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:37 | D | sum error = [ 53.5002, 56.4326, 59.4963, 62.6952, 66.0329] +24-11-19 20:30:37 | D | best error = [ 2.3289, 2.3289, 2.3289, 2.3289, 2.3289] +24-11-19 20:30:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:37 | D | sum error = [ 69.5175, 73.1466, 76.9274, 80.8663, 84.9476] +24-11-19 20:30:37 | D | best error = [ 2.3289, 2.3289, 2.3289, 2.3289, 2.3289] +24-11-19 20:30:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:37 | D | sum error = [ 89.1984, 93.6112, 98.1930, 102.9443, 107.8698] +24-11-19 20:30:37 | D | best error = [ 2.3289, 2.3289, 2.3289, 2.3289, 2.3289] +24-11-19 20:30:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:37 | D | sum error = [ 112.9740, 118.2536, 123.7153, 129.3581, 135.1912] +24-11-19 20:30:37 | D | best error = [ 2.3289, 2.3289, 2.3289, 2.3289, 2.3289] +24-11-19 20:30:37 | D | + error = [2.3289] +24-11-19 20:30:37 | D | - Quantizing model.layers.16.self_attn.q_proj.weight +24-11-19 20:30:38 | D | - Quantizing model.layers.16.self_attn.k_proj.weight +24-11-19 20:30:39 | D | - Quantizing model.layers.16.self_attn.v_proj.weight +24-11-19 20:30:39 | D | - Quantizing model.layers.16.self_attn.o_proj.weight +24-11-19 20:30:40 | D | - Quantizing model.layers.16.mlp.up_proj.weight +24-11-19 20:30:41 | D | - Quantizing model.layers.16.mlp.gate_proj.weight +24-11-19 20:30:42 | D | - Quantizing model.layers.16.mlp.down_proj.weight +24-11-19 20:30:51 | D | - Quantizing layer model.layers.17 +24-11-19 20:30:51 | D | - Calibrating model.layers.17.self_attn.q_proj.weight +24-11-19 20:30:51 | D | + w: sint8 +24-11-19 20:30:51 | D | + x: None +24-11-19 20:30:51 | D | + y: None +24-11-19 20:30:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:30:51 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:52 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:30:52 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:30:52 | D | - range ratio = [ 1.0000] +24-11-19 20:30:52 | D | sum error = [ 11.3514] +24-11-19 20:30:52 | D | best error = [ 11.3514] +24-11-19 20:31:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:04 | D | sum error = [ 11.1987, 11.2423, 11.4127, 11.4521, 11.6422] +24-11-19 20:31:04 | D | best error = [ 11.1987, 11.1987, 11.1987, 11.1987, 11.1987] +24-11-19 20:31:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:04 | D | sum error = [ 12.0357, 12.3718, 12.8500, 13.8366, 14.2769] +24-11-19 20:31:04 | D | best error = [ 11.1987, 11.1987, 11.1987, 11.1987, 11.1987] +24-11-19 20:31:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:04 | D | sum error = [ 15.0053, 16.2594, 17.1659, 18.2721, 19.4109] +24-11-19 20:31:04 | D | best error = [ 11.1987, 11.1987, 11.1987, 11.1987, 11.1987] +24-11-19 20:31:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:04 | D | sum error = [ 20.7250, 22.5606, 24.1550, 26.1861, 28.2030] +24-11-19 20:31:04 | D | best error = [ 11.1987, 11.1987, 11.1987, 11.1987, 11.1987] +24-11-19 20:31:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:04 | D | sum error = [ 30.7402, 33.2178, 35.6402, 38.8008, 41.9601] +24-11-19 20:31:04 | D | best error = [ 11.1987, 11.1987, 11.1987, 11.1987, 11.1987] +24-11-19 20:31:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:04 | D | sum error = [ 45.6152, 49.3552, 53.4441, 57.9125, 62.7152] +24-11-19 20:31:04 | D | best error = [ 11.1987, 11.1987, 11.1987, 11.1987, 11.1987] +24-11-19 20:31:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:04 | D | sum error = [ 67.6294, 73.1870, 79.4457, 86.2701, 92.9155] +24-11-19 20:31:04 | D | best error = [ 11.1987, 11.1987, 11.1987, 11.1987, 11.1987] +24-11-19 20:31:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:04 | D | sum error = [ 100.1581, 108.4283, 117.2068, 126.1531, 135.7063] +24-11-19 20:31:04 | D | best error = [ 11.1987, 11.1987, 11.1987, 11.1987, 11.1987] +24-11-19 20:31:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:04 | D | sum error = [ 145.6919, 156.6044, 168.2559, 180.7398, 194.0687] +24-11-19 20:31:04 | D | best error = [ 11.1987, 11.1987, 11.1987, 11.1987, 11.1987] +24-11-19 20:31:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:04 | D | sum error = [ 208.0041, 223.9589, 240.1157, 258.0033, 277.3499] +24-11-19 20:31:04 | D | best error = [ 11.1987, 11.1987, 11.1987, 11.1987, 11.1987] +24-11-19 20:31:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:04 | D | sum error = [ 297.7332, 320.0810, 343.8984, 369.8453, 397.7594] +24-11-19 20:31:04 | D | best error = [ 11.1987, 11.1987, 11.1987, 11.1987, 11.1987] +24-11-19 20:31:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:04 | D | sum error = [ 427.4119, 459.9737, 494.7225, 532.2983, 573.0469] +24-11-19 20:31:04 | D | best error = [ 11.1987, 11.1987, 11.1987, 11.1987, 11.1987] +24-11-19 20:31:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:04 | D | sum error = [ 617.4571, 665.3856, 717.5771, 774.2952, 835.8976] +24-11-19 20:31:04 | D | best error = [ 11.1987, 11.1987, 11.1987, 11.1987, 11.1987] +24-11-19 20:31:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:04 | D | sum error = [ 903.3216, 975.7693, 1055.8032, 1142.3073, 1237.0658] +24-11-19 20:31:04 | D | best error = [ 11.1987, 11.1987, 11.1987, 11.1987, 11.1987] +24-11-19 20:31:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:04 | D | sum error = [ 1340.5619, 1452.2205, 1574.7948, 1708.0343, 1853.2501] +24-11-19 20:31:04 | D | best error = [ 11.1987, 11.1987, 11.1987, 11.1987, 11.1987] +24-11-19 20:31:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:04 | D | sum error = [ 2009.9389, 2180.0239, 2361.3181, 2557.4498, 2764.8129] +24-11-19 20:31:04 | D | best error = [ 11.1987, 11.1987, 11.1987, 11.1987, 11.1987] +24-11-19 20:31:04 | D | + error = [11.1987] +24-11-19 20:31:05 | D | - Calibrating model.layers.17.self_attn.k_proj.weight +24-11-19 20:31:05 | D | + w: sint8 +24-11-19 20:31:05 | D | + x: None +24-11-19 20:31:05 | D | + y: None +24-11-19 20:31:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:31:05 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:31:05 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:31:05 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:31:05 | D | - range ratio = [ 1.0000] +24-11-19 20:31:05 | D | sum error = [ 11.5308] +24-11-19 20:31:05 | D | best error = [ 11.5308] +24-11-19 20:31:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:18 | D | sum error = [ 11.4765, 11.6123, 11.7705, 12.5625, 13.0510] +24-11-19 20:31:18 | D | best error = [ 11.4765, 11.4765, 11.4765, 11.4765, 11.4765] +24-11-19 20:31:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:18 | D | sum error = [ 13.2186, 13.4452, 13.5907, 15.0893, 15.1888] +24-11-19 20:31:18 | D | best error = [ 11.4765, 11.4765, 11.4765, 11.4765, 11.4765] +24-11-19 20:31:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:18 | D | sum error = [ 16.0240, 17.1468, 18.4414, 20.1109, 20.8667] +24-11-19 20:31:18 | D | best error = [ 11.4765, 11.4765, 11.4765, 11.4765, 11.4765] +24-11-19 20:31:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:18 | D | sum error = [ 23.0296, 24.8162, 26.6186, 28.7087, 30.2712] +24-11-19 20:31:18 | D | best error = [ 11.4765, 11.4765, 11.4765, 11.4765, 11.4765] +24-11-19 20:31:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:18 | D | sum error = [ 33.3261, 36.2736, 38.8628, 41.5666, 45.5054] +24-11-19 20:31:18 | D | best error = [ 11.4765, 11.4765, 11.4765, 11.4765, 11.4765] +24-11-19 20:31:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:18 | D | sum error = [ 48.8218, 52.7916, 57.0643, 61.0545, 65.3027] +24-11-19 20:31:18 | D | best error = [ 11.4765, 11.4765, 11.4765, 11.4765, 11.4765] +24-11-19 20:31:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:18 | D | sum error = [ 71.6904, 76.6335, 82.8287, 88.5760, 95.9703] +24-11-19 20:31:18 | D | best error = [ 11.4765, 11.4765, 11.4765, 11.4765, 11.4765] +24-11-19 20:31:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:18 | D | sum error = [ 102.8193, 109.5944, 118.6300, 127.9007, 137.2070] +24-11-19 20:31:18 | D | best error = [ 11.4765, 11.4765, 11.4765, 11.4765, 11.4765] +24-11-19 20:31:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:18 | D | sum error = [ 146.9663, 157.4003, 168.9143, 181.4925, 194.8158] +24-11-19 20:31:18 | D | best error = [ 11.4765, 11.4765, 11.4765, 11.4765, 11.4765] +24-11-19 20:31:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:18 | D | sum error = [ 209.0201, 224.0811, 240.5877, 258.2156, 277.0976] +24-11-19 20:31:18 | D | best error = [ 11.4765, 11.4765, 11.4765, 11.4765, 11.4765] +24-11-19 20:31:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:18 | D | sum error = [ 296.8512, 320.4739, 344.4597, 368.6254, 397.3046] +24-11-19 20:31:18 | D | best error = [ 11.4765, 11.4765, 11.4765, 11.4765, 11.4765] +24-11-19 20:31:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:18 | D | sum error = [ 426.8318, 458.9192, 495.0154, 533.1269, 575.1585] +24-11-19 20:31:18 | D | best error = [ 11.4765, 11.4765, 11.4765, 11.4765, 11.4765] +24-11-19 20:31:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:18 | D | sum error = [ 620.9609, 670.8142, 724.6682, 783.3695, 846.6816] +24-11-19 20:31:18 | D | best error = [ 11.4765, 11.4765, 11.4765, 11.4765, 11.4765] +24-11-19 20:31:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:18 | D | sum error = [ 914.1922, 990.0639, 1068.9241, 1157.6975, 1255.2240] +24-11-19 20:31:18 | D | best error = [ 11.4765, 11.4765, 11.4765, 11.4765, 11.4765] +24-11-19 20:31:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:18 | D | sum error = [ 1358.1853, 1474.9019, 1600.1055, 1736.4369, 1883.3039] +24-11-19 20:31:18 | D | best error = [ 11.4765, 11.4765, 11.4765, 11.4765, 11.4765] +24-11-19 20:31:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:18 | D | sum error = [ 2044.7496, 2216.0831, 2401.7577, 2603.0396, 2813.0114] +24-11-19 20:31:18 | D | best error = [ 11.4765, 11.4765, 11.4765, 11.4765, 11.4765] +24-11-19 20:31:18 | D | + error = [11.4765] +24-11-19 20:31:18 | D | - Calibrating model.layers.17.self_attn.v_proj.weight +24-11-19 20:31:18 | D | + w: sint8 +24-11-19 20:31:18 | D | + x: None +24-11-19 20:31:18 | D | + y: None +24-11-19 20:31:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:18 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:31:18 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:31:18 | D | + finished calculating the original outputs, ram usage: 13.4 +24-11-19 20:31:18 | D | - range ratio = [ 1.0000] +24-11-19 20:31:18 | D | sum error = [ 5.5376] +24-11-19 20:31:18 | D | best error = [ 5.5376] +24-11-19 20:31:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:19 | D | sum error = [ 5.4944, 5.4807, 5.5058, 5.5654, 5.6938] +24-11-19 20:31:19 | D | best error = [ 5.1550, 4.9954, 4.9138, 4.8717, 4.8498] +24-11-19 20:31:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:19 | D | sum error = [ 5.8228, 6.0109, 6.2413, 6.5429, 6.8832] +24-11-19 20:31:19 | D | best error = [ 4.8394, 4.8341, 4.8320, 4.8315, 4.8313] +24-11-19 20:31:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:19 | D | sum error = [ 7.2810, 7.7350, 8.2368, 8.7760, 9.3886] +24-11-19 20:31:19 | D | best error = [ 4.8313, 4.8313, 4.8313, 4.8313, 4.8313] +24-11-19 20:31:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:19 | D | sum error = [ 10.0648, 10.7882, 11.5539, 12.3651, 13.2500] +24-11-19 20:31:19 | D | best error = [ 4.8313, 4.8313, 4.8313, 4.8313, 4.8313] +24-11-19 20:31:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:19 | D | sum error = [ 14.1869, 15.2241, 16.2815, 17.4205, 18.6298] +24-11-19 20:31:19 | D | best error = [ 4.8313, 4.8313, 4.8313, 4.8313, 4.8313] +24-11-19 20:31:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:19 | D | sum error = [ 19.8908, 21.2693, 22.7062, 24.2040, 25.8056] +24-11-19 20:31:19 | D | best error = [ 4.8313, 4.8313, 4.8313, 4.8313, 4.8313] +24-11-19 20:31:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:19 | D | sum error = [ 27.5118, 29.2931, 31.1965, 33.1691, 35.2816] +24-11-19 20:31:19 | D | best error = [ 4.8313, 4.8313, 4.8313, 4.8313, 4.8313] +24-11-19 20:31:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:19 | D | sum error = [ 37.4939, 39.8295, 42.2755, 44.8392, 47.5291] +24-11-19 20:31:19 | D | best error = [ 4.8313, 4.8313, 4.8313, 4.8313, 4.8313] +24-11-19 20:31:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:19 | D | sum error = [ 50.3627, 53.3177, 56.4177, 59.6710, 63.0955] +24-11-19 20:31:19 | D | best error = [ 4.8313, 4.8313, 4.8313, 4.8313, 4.8313] +24-11-19 20:31:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:19 | D | sum error = [ 66.6626, 70.3793, 74.2850, 78.3590, 82.6274] +24-11-19 20:31:19 | D | best error = [ 4.8313, 4.8313, 4.8313, 4.8313, 4.8313] +24-11-19 20:31:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:19 | D | sum error = [ 87.0648, 91.6966, 96.5661, 101.6273, 106.9151] +24-11-19 20:31:19 | D | best error = [ 4.8313, 4.8313, 4.8313, 4.8313, 4.8313] +24-11-19 20:31:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:19 | D | sum error = [ 112.3942, 118.1176, 124.0668, 130.2594, 136.7110] +24-11-19 20:31:19 | D | best error = [ 4.8313, 4.8313, 4.8313, 4.8313, 4.8313] +24-11-19 20:31:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:19 | D | sum error = [ 143.4161, 150.3919, 157.6551, 165.1640, 172.9632] +24-11-19 20:31:19 | D | best error = [ 4.8313, 4.8313, 4.8313, 4.8313, 4.8313] +24-11-19 20:31:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:19 | D | sum error = [ 181.0322, 189.3615, 198.0048, 206.9262, 216.1651] +24-11-19 20:31:19 | D | best error = [ 4.8313, 4.8313, 4.8313, 4.8313, 4.8313] +24-11-19 20:31:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:19 | D | sum error = [ 225.7209, 235.5762, 245.7709, 256.2775, 267.1207] +24-11-19 20:31:19 | D | best error = [ 4.8313, 4.8313, 4.8313, 4.8313, 4.8313] +24-11-19 20:31:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:19 | D | sum error = [ 278.2856, 289.7918, 301.6319, 313.8298, 326.3620] +24-11-19 20:31:19 | D | best error = [ 4.8313, 4.8313, 4.8313, 4.8313, 4.8313] +24-11-19 20:31:19 | D | + error = [4.8313] +24-11-19 20:31:19 | D | - Calibrating model.layers.17.self_attn.o_proj.weight +24-11-19 20:31:19 | D | + w: sint8 +24-11-19 20:31:19 | D | + x: None +24-11-19 20:31:19 | D | + y: None +24-11-19 20:31:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:19 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:31:19 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:31:19 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:31:19 | D | - range ratio = [ 1.0000] +24-11-19 20:31:19 | D | sum error = [ 1.3724] +24-11-19 20:31:19 | D | best error = [ 1.3724] +24-11-19 20:31:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:19 | D | sum error = [ 1.3639, 1.3564, 1.3556, 1.3640, 1.3791] +24-11-19 20:31:19 | D | best error = [ 1.2852, 1.2441, 1.2186, 1.2034, 1.1922] +24-11-19 20:31:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:19 | D | sum error = [ 1.3977, 1.4286, 1.4698, 1.5179, 1.5852] +24-11-19 20:31:19 | D | best error = [ 1.1842, 1.1788, 1.1743, 1.1711, 1.1691] +24-11-19 20:31:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:19 | D | sum error = [ 1.6489, 1.7347, 1.8277, 1.9290, 2.0453] +24-11-19 20:31:19 | D | best error = [ 1.1673, 1.1660, 1.1647, 1.1639, 1.1632] +24-11-19 20:31:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:19 | D | sum error = [ 2.1722, 2.3094, 2.4597, 2.6254, 2.8004] +24-11-19 20:31:19 | D | best error = [ 1.1625, 1.1619, 1.1615, 1.1610, 1.1608] +24-11-19 20:31:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:19 | D | sum error = [ 2.9866, 3.1921, 3.4066, 3.6360, 3.8815] +24-11-19 20:31:19 | D | best error = [ 1.1606, 1.1605, 1.1604, 1.1602, 1.1600] +24-11-19 20:31:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:19 | D | sum error = [ 4.1377, 4.4123, 4.7087, 5.0191, 5.3487] +24-11-19 20:31:19 | D | best error = [ 1.1599, 1.1599, 1.1598, 1.1598, 1.1598] +24-11-19 20:31:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:19 | D | sum error = [ 5.6975, 6.0648, 6.4551, 6.8679, 7.2992] +24-11-19 20:31:19 | D | best error = [ 1.1598, 1.1598, 1.1598, 1.1598, 1.1598] +24-11-19 20:31:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:19 | D | sum error = [ 7.7605, 8.2431, 8.7552, 9.2932, 9.8587] +24-11-19 20:31:19 | D | best error = [ 1.1598, 1.1598, 1.1598, 1.1598, 1.1598] +24-11-19 20:31:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:19 | D | sum error = [ 10.4551, 11.0866, 11.7469, 12.4383, 13.1711] +24-11-19 20:31:19 | D | best error = [ 1.1597, 1.1597, 1.1597, 1.1597, 1.1597] +24-11-19 20:31:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:19 | D | sum error = [ 13.9363, 14.7393, 15.5802, 16.4618, 17.3874] +24-11-19 20:31:19 | D | best error = [ 1.1597, 1.1597, 1.1597, 1.1597, 1.1597] +24-11-19 20:31:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:19 | D | sum error = [ 18.3566, 19.3758, 20.4413, 21.5562, 22.7185] +24-11-19 20:31:19 | D | best error = [ 1.1597, 1.1597, 1.1597, 1.1597, 1.1597] +24-11-19 20:31:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:19 | D | sum error = [ 23.9322, 25.1974, 26.5215, 27.9002, 29.3346] +24-11-19 20:31:19 | D | best error = [ 1.1597, 1.1597, 1.1597, 1.1597, 1.1597] +24-11-19 20:31:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:19 | D | sum error = [ 30.8305, 32.3885, 34.0129, 35.7029, 37.4613] +24-11-19 20:31:19 | D | best error = [ 1.1597, 1.1597, 1.1597, 1.1597, 1.1597] +24-11-19 20:31:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:19 | D | sum error = [ 39.2856, 41.1806, 43.1467, 45.1880, 47.2987] +24-11-19 20:31:19 | D | best error = [ 1.1597, 1.1597, 1.1597, 1.1597, 1.1597] +24-11-19 20:31:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:19 | D | sum error = [ 49.4862, 51.7489, 54.0899, 56.5157, 59.0276] +24-11-19 20:31:19 | D | best error = [ 1.1597, 1.1597, 1.1597, 1.1597, 1.1597] +24-11-19 20:31:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:19 | D | sum error = [ 61.6205, 64.3018, 67.0713, 69.9315, 72.8784] +24-11-19 20:31:19 | D | best error = [ 1.1597, 1.1597, 1.1597, 1.1597, 1.1597] +24-11-19 20:31:19 | D | + error = [1.1597] +24-11-19 20:31:19 | D | - Calibrating model.layers.17.mlp.up_proj.weight +24-11-19 20:31:19 | D | + w: sint8 +24-11-19 20:31:19 | D | + x: None +24-11-19 20:31:19 | D | + y: None +24-11-19 20:31:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:19 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:31:20 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:31:20 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:31:20 | D | - range ratio = [ 1.0000] +24-11-19 20:31:20 | D | sum error = [ 7.8794] +24-11-19 20:31:20 | D | best error = [ 7.8794] +24-11-19 20:31:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:21 | D | sum error = [ 7.8202, 7.8244, 7.8415, 7.9089, 8.0733] +24-11-19 20:31:21 | D | best error = [ 7.3241, 7.1112, 6.9979, 6.9308, 6.8961] +24-11-19 20:31:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:21 | D | sum error = [ 8.2727, 8.5570, 8.8963, 9.3022, 9.8442] +24-11-19 20:31:21 | D | best error = [ 6.8795, 6.8725, 6.8701, 6.8696, 6.8693] +24-11-19 20:31:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:21 | D | sum error = [ 10.3899, 11.0339, 11.7505, 12.5608, 13.4178] +24-11-19 20:31:21 | D | best error = [ 6.8693, 6.8693, 6.8693, 6.8693, 6.8693] +24-11-19 20:31:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:21 | D | sum error = [ 14.3961, 15.4034, 16.5070, 17.7057, 18.9547] +24-11-19 20:31:21 | D | best error = [ 6.8693, 6.8693, 6.8693, 6.8693, 6.8693] +24-11-19 20:31:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:21 | D | sum error = [ 20.3268, 21.7516, 23.3202, 24.9172, 26.6671] +24-11-19 20:31:21 | D | best error = [ 6.8693, 6.8693, 6.8693, 6.8693, 6.8693] +24-11-19 20:31:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:21 | D | sum error = [ 28.5001, 30.4393, 32.4942, 34.6779, 36.9682] +24-11-19 20:31:21 | D | best error = [ 6.8693, 6.8693, 6.8693, 6.8693, 6.8693] +24-11-19 20:31:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:21 | D | sum error = [ 39.3954, 41.9771, 44.6609, 47.5095, 50.5238] +24-11-19 20:31:21 | D | best error = [ 6.8693, 6.8693, 6.8693, 6.8693, 6.8693] +24-11-19 20:31:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:21 | D | sum error = [ 53.6966, 57.0248, 60.5329, 64.2117, 68.0839] +24-11-19 20:31:21 | D | best error = [ 6.8693, 6.8693, 6.8693, 6.8693, 6.8693] +24-11-19 20:31:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:21 | D | sum error = [ 72.1467, 76.4344, 80.9168, 85.6097, 90.5049] +24-11-19 20:31:21 | D | best error = [ 6.8693, 6.8693, 6.8693, 6.8693, 6.8693] +24-11-19 20:31:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:21 | D | sum error = [ 95.6861, 101.0858, 106.7301, 112.6268, 118.8079] +24-11-19 20:31:21 | D | best error = [ 6.8693, 6.8693, 6.8693, 6.8693, 6.8693] +24-11-19 20:31:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:21 | D | sum error = [ 125.2802, 132.0197, 139.0492, 146.4070, 154.0898] +24-11-19 20:31:21 | D | best error = [ 6.8693, 6.8693, 6.8693, 6.8693, 6.8693] +24-11-19 20:31:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:21 | D | sum error = [ 162.1185, 170.4567, 179.1309, 188.1944, 197.6248] +24-11-19 20:31:21 | D | best error = [ 6.8693, 6.8693, 6.8693, 6.8693, 6.8693] +24-11-19 20:31:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:21 | D | sum error = [ 207.4273, 217.6194, 228.2167, 239.2182, 250.6399] +24-11-19 20:31:21 | D | best error = [ 6.8693, 6.8693, 6.8693, 6.8693, 6.8693] +24-11-19 20:31:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:21 | D | sum error = [ 262.4975, 274.7881, 287.5384, 300.7577, 314.4243] +24-11-19 20:31:21 | D | best error = [ 6.8693, 6.8693, 6.8693, 6.8693, 6.8693] +24-11-19 20:31:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:21 | D | sum error = [ 328.5860, 343.2074, 358.3027, 373.8934, 390.0018] +24-11-19 20:31:21 | D | best error = [ 6.8693, 6.8693, 6.8693, 6.8693, 6.8693] +24-11-19 20:31:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:21 | D | sum error = [ 406.6075, 423.7434, 441.3865, 459.5411, 478.2109] +24-11-19 20:31:21 | D | best error = [ 6.8693, 6.8693, 6.8693, 6.8693, 6.8693] +24-11-19 20:31:21 | D | + error = [6.8693] +24-11-19 20:31:21 | D | - Calibrating model.layers.17.mlp.gate_proj.weight +24-11-19 20:31:21 | D | + w: sint8 +24-11-19 20:31:21 | D | + x: None +24-11-19 20:31:21 | D | + y: None +24-11-19 20:31:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:21 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:31:21 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:31:21 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:31:21 | D | - range ratio = [ 1.0000] +24-11-19 20:31:21 | D | sum error = [ 8.2306] +24-11-19 20:31:21 | D | best error = [ 8.2306] +24-11-19 20:31:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:22 | D | sum error = [ 8.1932, 8.1542, 8.1854, 8.2715, 8.4389] +24-11-19 20:31:22 | D | best error = [ 7.6668, 7.4398, 7.3186, 7.2487, 7.2128] +24-11-19 20:31:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:22 | D | sum error = [ 8.6631, 8.9532, 9.3204, 9.7597, 10.2721] +24-11-19 20:31:22 | D | best error = [ 7.1942, 7.1862, 7.1836, 7.1825, 7.1822] +24-11-19 20:31:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:22 | D | sum error = [ 10.8835, 11.5594, 12.3077, 13.1654, 14.0815] +24-11-19 20:31:22 | D | best error = [ 7.1822, 7.1821, 7.1821, 7.1821, 7.1821] +24-11-19 20:31:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:22 | D | sum error = [ 15.0925, 16.1783, 17.3446, 18.5941, 19.9583] +24-11-19 20:31:22 | D | best error = [ 7.1821, 7.1821, 7.1821, 7.1821, 7.1821] +24-11-19 20:31:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:22 | D | sum error = [ 21.4032, 22.9662, 24.5873, 26.3681, 28.2498] +24-11-19 20:31:22 | D | best error = [ 7.1821, 7.1821, 7.1821, 7.1821, 7.1821] +24-11-19 20:31:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:22 | D | sum error = [ 30.2578, 32.3702, 34.6302, 37.0340, 39.5559] +24-11-19 20:31:22 | D | best error = [ 7.1821, 7.1821, 7.1821, 7.1821, 7.1821] +24-11-19 20:31:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:22 | D | sum error = [ 42.2409, 45.0809, 48.0887, 51.2753, 54.6923] +24-11-19 20:31:22 | D | best error = [ 7.1821, 7.1821, 7.1821, 7.1821, 7.1821] +24-11-19 20:31:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:22 | D | sum error = [ 58.2392, 62.0141, 66.0090, 70.2175, 74.6786] +24-11-19 20:31:22 | D | best error = [ 7.1821, 7.1821, 7.1821, 7.1821, 7.1821] +24-11-19 20:31:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:22 | D | sum error = [ 79.3875, 84.3527, 89.5689, 95.1280, 100.9766] +24-11-19 20:31:22 | D | best error = [ 7.1821, 7.1821, 7.1821, 7.1821, 7.1821] +24-11-19 20:31:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:22 | D | sum error = [ 107.1445, 113.6645, 120.5265, 127.7815, 135.4132] +24-11-19 20:31:22 | D | best error = [ 7.1821, 7.1821, 7.1821, 7.1821, 7.1821] +24-11-19 20:31:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:22 | D | sum error = [ 143.4827, 151.9881, 160.9224, 170.3161, 180.1721] +24-11-19 20:31:22 | D | best error = [ 7.1821, 7.1821, 7.1821, 7.1821, 7.1821] +24-11-19 20:31:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:22 | D | sum error = [ 190.5761, 201.4946, 212.9554, 224.9968, 237.5965] +24-11-19 20:31:22 | D | best error = [ 7.1821, 7.1821, 7.1821, 7.1821, 7.1821] +24-11-19 20:31:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:22 | D | sum error = [ 250.7871, 264.6232, 279.1238, 294.2585, 310.0638] +24-11-19 20:31:22 | D | best error = [ 7.1821, 7.1821, 7.1821, 7.1821, 7.1821] +24-11-19 20:31:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:22 | D | sum error = [ 326.5881, 343.8054, 361.7629, 380.4373, 399.8711] +24-11-19 20:31:22 | D | best error = [ 7.1821, 7.1821, 7.1821, 7.1821, 7.1821] +24-11-19 20:31:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:22 | D | sum error = [ 420.0792, 441.0667, 462.8490, 485.4143, 508.7829] +24-11-19 20:31:22 | D | best error = [ 7.1821, 7.1821, 7.1821, 7.1821, 7.1821] +24-11-19 20:31:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:22 | D | sum error = [ 532.9584, 557.9740, 583.7692, 610.3606, 637.7741] +24-11-19 20:31:22 | D | best error = [ 7.1821, 7.1821, 7.1821, 7.1821, 7.1821] +24-11-19 20:31:22 | D | + error = [7.1821] +24-11-19 20:31:22 | D | - Calibrating model.layers.17.mlp.down_proj.weight +24-11-19 20:31:22 | D | + w: sint8 +24-11-19 20:31:22 | D | + x: None +24-11-19 20:31:22 | D | + y: None +24-11-19 20:31:22 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:22 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:31:22 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:31:22 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:31:22 | D | - range ratio = [ 1.0000] +24-11-19 20:31:22 | D | sum error = [ 2.6172] +24-11-19 20:31:22 | D | best error = [ 2.6172] +24-11-19 20:31:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:23 | D | sum error = [ 2.5872, 2.5728, 2.5639, 2.5516, 2.5507] +24-11-19 20:31:23 | D | best error = [ 2.5150, 2.4674, 2.4348, 2.4083, 2.3880] +24-11-19 20:31:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:23 | D | sum error = [ 2.5639, 2.5829, 2.6088, 2.6592, 2.7127] +24-11-19 20:31:23 | D | best error = [ 2.3736, 2.3634, 2.3550, 2.3493, 2.3452] +24-11-19 20:31:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:23 | D | sum error = [ 2.7866, 2.8664, 2.9666, 3.0963, 3.2344] +24-11-19 20:31:23 | D | best error = [ 2.3426, 2.3409, 2.3397, 2.3390, 2.3384] +24-11-19 20:31:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:23 | D | sum error = [ 3.3907, 3.5706, 3.7744, 3.9967, 4.2454] +24-11-19 20:31:23 | D | best error = [ 2.3381, 2.3379, 2.3377, 2.3376, 2.3376] +24-11-19 20:31:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:23 | D | sum error = [ 4.5162, 4.8052, 5.1276, 5.4675, 5.8450] +24-11-19 20:31:23 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 20:31:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:23 | D | sum error = [ 6.2424, 6.6705, 7.1343, 7.6251, 8.1524] +24-11-19 20:31:23 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 20:31:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:23 | D | sum error = [ 8.7132, 9.3135, 9.9485, 10.6258, 11.3437] +24-11-19 20:31:23 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 20:31:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:23 | D | sum error = [ 12.1075, 12.9192, 13.7813, 14.6848, 15.6476] +24-11-19 20:31:23 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 20:31:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:23 | D | sum error = [ 16.6659, 17.7406, 18.8726, 20.0748, 21.3383] +24-11-19 20:31:23 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 20:31:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:23 | D | sum error = [ 22.6733, 24.0717, 25.5466, 27.0987, 28.7264] +24-11-19 20:31:23 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 20:31:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:23 | D | sum error = [ 30.4394, 32.2399, 34.1255, 36.1091, 38.1843] +24-11-19 20:31:23 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 20:31:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:23 | D | sum error = [ 40.3615, 42.6400, 45.0308, 47.5260, 50.1374] +24-11-19 20:31:23 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 20:31:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:23 | D | sum error = [ 52.8705, 55.7168, 58.6941, 61.7952, 65.0318] +24-11-19 20:31:23 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 20:31:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:23 | D | sum error = [ 68.3992, 71.9104, 75.5621, 79.3687, 83.3069] +24-11-19 20:31:23 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 20:31:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:23 | D | sum error = [ 87.4033, 91.6552, 96.0654, 100.6363, 105.3708] +24-11-19 20:31:23 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 20:31:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:23 | D | sum error = [ 110.2747, 115.3466, 120.5915, 126.0176, 131.6229] +24-11-19 20:31:23 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 20:31:23 | D | + error = [2.3376] +24-11-19 20:31:23 | D | - Quantizing model.layers.17.self_attn.q_proj.weight +24-11-19 20:31:24 | D | - Quantizing model.layers.17.self_attn.k_proj.weight +24-11-19 20:31:25 | D | - Quantizing model.layers.17.self_attn.v_proj.weight +24-11-19 20:31:26 | D | - Quantizing model.layers.17.self_attn.o_proj.weight +24-11-19 20:31:27 | D | - Quantizing model.layers.17.mlp.up_proj.weight +24-11-19 20:31:28 | D | - Quantizing model.layers.17.mlp.gate_proj.weight +24-11-19 20:31:29 | D | - Quantizing model.layers.17.mlp.down_proj.weight +24-11-19 20:31:37 | D | - Quantizing layer model.layers.18 +24-11-19 20:31:37 | D | - Calibrating model.layers.18.self_attn.q_proj.weight +24-11-19 20:31:37 | D | + w: sint8 +24-11-19 20:31:37 | D | + x: None +24-11-19 20:31:37 | D | + y: None +24-11-19 20:31:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:31:37 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:31:37 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:31:38 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:31:38 | D | - range ratio = [ 1.0000] +24-11-19 20:31:38 | D | sum error = [ 12.1236] +24-11-19 20:31:38 | D | best error = [ 12.1236] +24-11-19 20:31:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:51 | D | sum error = [ 11.9255, 12.1081, 12.1554, 12.3027, 12.5019] +24-11-19 20:31:51 | D | best error = [ 11.9255, 11.9255, 11.9255, 11.9255, 11.9255] +24-11-19 20:31:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:51 | D | sum error = [ 13.0596, 13.4081, 14.4051, 15.1992, 15.7794] +24-11-19 20:31:51 | D | best error = [ 11.9255, 11.9255, 11.9255, 11.9255, 11.9255] +24-11-19 20:31:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:51 | D | sum error = [ 16.7087, 17.9195, 19.1807, 20.3169, 22.0512] +24-11-19 20:31:51 | D | best error = [ 11.9255, 11.9255, 11.9255, 11.9255, 11.9255] +24-11-19 20:31:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:51 | D | sum error = [ 23.3916, 25.3414, 27.2909, 29.3307, 32.0328] +24-11-19 20:31:51 | D | best error = [ 11.9255, 11.9255, 11.9255, 11.9255, 11.9255] +24-11-19 20:31:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:51 | D | sum error = [ 34.3314, 37.5088, 40.5715, 43.8398, 47.4883] +24-11-19 20:31:51 | D | best error = [ 11.9255, 11.9255, 11.9255, 11.9255, 11.9255] +24-11-19 20:31:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:51 | D | sum error = [ 51.1475, 55.5388, 59.8452, 64.4789, 69.3460] +24-11-19 20:31:51 | D | best error = [ 11.9255, 11.9255, 11.9255, 11.9255, 11.9255] +24-11-19 20:31:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:51 | D | sum error = [ 74.8230, 80.9794, 87.0565, 93.8064, 100.8849] +24-11-19 20:31:51 | D | best error = [ 11.9255, 11.9255, 11.9255, 11.9255, 11.9255] +24-11-19 20:31:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:51 | D | sum error = [ 109.2910, 117.3905, 127.2457, 136.8878, 147.5160] +24-11-19 20:31:51 | D | best error = [ 11.9255, 11.9255, 11.9255, 11.9255, 11.9255] +24-11-19 20:31:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:51 | D | sum error = [ 159.1064, 171.7488, 184.6553, 198.6115, 213.7740] +24-11-19 20:31:51 | D | best error = [ 11.9255, 11.9255, 11.9255, 11.9255, 11.9255] +24-11-19 20:31:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:51 | D | sum error = [ 230.2060, 247.9834, 267.0707, 287.2648, 308.6670] +24-11-19 20:31:51 | D | best error = [ 11.9255, 11.9255, 11.9255, 11.9255, 11.9255] +24-11-19 20:31:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:51 | D | sum error = [ 331.9313, 356.8796, 384.2524, 413.4158, 444.8989] +24-11-19 20:31:51 | D | best error = [ 11.9255, 11.9255, 11.9255, 11.9255, 11.9255] +24-11-19 20:31:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:51 | D | sum error = [ 479.3437, 516.3971, 556.2210, 599.6268, 646.4742] +24-11-19 20:31:51 | D | best error = [ 11.9255, 11.9255, 11.9255, 11.9255, 11.9255] +24-11-19 20:31:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:51 | D | sum error = [ 698.5162, 755.1324, 817.1225, 884.7770, 959.4152] +24-11-19 20:31:51 | D | best error = [ 11.9255, 11.9255, 11.9255, 11.9255, 11.9255] +24-11-19 20:31:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:51 | D | sum error = [ 1040.8868, 1130.3421, 1227.1464, 1334.3918, 1451.6816] +24-11-19 20:31:51 | D | best error = [ 11.9255, 11.9255, 11.9255, 11.9255, 11.9255] +24-11-19 20:31:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:51 | D | sum error = [ 1582.4661, 1724.6353, 1880.8992, 2053.1013, 2241.0532] +24-11-19 20:31:51 | D | best error = [ 11.9255, 11.9255, 11.9255, 11.9255, 11.9255] +24-11-19 20:31:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:51 | D | sum error = [ 2447.0595, 2672.9890, 2915.5298, 3176.4900, 3453.4645] +24-11-19 20:31:51 | D | best error = [ 11.9255, 11.9255, 11.9255, 11.9255, 11.9255] +24-11-19 20:31:51 | D | + error = [11.9255] +24-11-19 20:31:51 | D | - Calibrating model.layers.18.self_attn.k_proj.weight +24-11-19 20:31:51 | D | + w: sint8 +24-11-19 20:31:51 | D | + x: None +24-11-19 20:31:51 | D | + y: None +24-11-19 20:31:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:31:51 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:31:51 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:31:51 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:31:51 | D | - range ratio = [ 1.0000] +24-11-19 20:31:51 | D | sum error = [ 13.5588] +24-11-19 20:31:51 | D | best error = [ 13.5588] +24-11-19 20:32:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:04 | D | sum error = [ 12.7584, 12.8120, 13.4977, 13.3799, 13.1589] +24-11-19 20:32:04 | D | best error = [ 12.7584, 12.7584, 12.7584, 12.7584, 12.7584] +24-11-19 20:32:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:04 | D | sum error = [ 14.2508, 14.0570, 16.2714, 15.4988, 16.6927] +24-11-19 20:32:04 | D | best error = [ 12.7584, 12.7584, 12.7584, 12.7584, 12.7584] +24-11-19 20:32:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:04 | D | sum error = [ 17.1676, 18.6278, 20.1455, 21.0135, 22.7554] +24-11-19 20:32:04 | D | best error = [ 12.7584, 12.7584, 12.7584, 12.7584, 12.7584] +24-11-19 20:32:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:04 | D | sum error = [ 24.0169, 26.0784, 28.4992, 31.6127, 32.4711] +24-11-19 20:32:04 | D | best error = [ 12.7584, 12.7584, 12.7584, 12.7584, 12.7584] +24-11-19 20:32:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:04 | D | sum error = [ 36.7327, 39.3345, 42.3785, 45.9888, 50.0063] +24-11-19 20:32:04 | D | best error = [ 12.7584, 12.7584, 12.7584, 12.7584, 12.7584] +24-11-19 20:32:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:04 | D | sum error = [ 53.7783, 57.7486, 61.3387, 65.8555, 70.4386] +24-11-19 20:32:04 | D | best error = [ 12.7584, 12.7584, 12.7584, 12.7584, 12.7584] +24-11-19 20:32:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:04 | D | sum error = [ 75.3094, 81.5691, 87.5829, 93.5061, 99.8902] +24-11-19 20:32:04 | D | best error = [ 12.7584, 12.7584, 12.7584, 12.7584, 12.7584] +24-11-19 20:32:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:04 | D | sum error = [ 106.4074, 114.6478, 123.2398, 131.5149, 141.2117] +24-11-19 20:32:04 | D | best error = [ 12.7584, 12.7584, 12.7584, 12.7584, 12.7584] +24-11-19 20:32:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:04 | D | sum error = [ 152.4749, 162.9553, 176.2031, 189.1419, 204.7211] +24-11-19 20:32:04 | D | best error = [ 12.7584, 12.7584, 12.7584, 12.7584, 12.7584] +24-11-19 20:32:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:04 | D | sum error = [ 221.5692, 238.8546, 257.6022, 278.8080, 301.8704] +24-11-19 20:32:04 | D | best error = [ 12.7584, 12.7584, 12.7584, 12.7584, 12.7584] +24-11-19 20:32:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:04 | D | sum error = [ 327.3172, 353.9669, 383.7602, 412.3877, 445.9097] +24-11-19 20:32:04 | D | best error = [ 12.7584, 12.7584, 12.7584, 12.7584, 12.7584] +24-11-19 20:32:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:04 | D | sum error = [ 481.1601, 520.4002, 560.0850, 603.5793, 650.8308] +24-11-19 20:32:04 | D | best error = [ 12.7584, 12.7584, 12.7584, 12.7584, 12.7584] +24-11-19 20:32:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:04 | D | sum error = [ 703.0923, 759.3020, 821.7288, 889.9583, 966.9667] +24-11-19 20:32:04 | D | best error = [ 12.7584, 12.7584, 12.7584, 12.7584, 12.7584] +24-11-19 20:32:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:04 | D | sum error = [ 1046.0983, 1134.6935, 1232.4962, 1343.3492, 1461.7699] +24-11-19 20:32:04 | D | best error = [ 12.7584, 12.7584, 12.7584, 12.7584, 12.7584] +24-11-19 20:32:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:04 | D | sum error = [ 1592.8879, 1738.1638, 1897.1463, 2074.1768, 2265.9784] +24-11-19 20:32:04 | D | best error = [ 12.7584, 12.7584, 12.7584, 12.7584, 12.7584] +24-11-19 20:32:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:04 | D | sum error = [ 2473.7243, 2701.5930, 2944.9097, 3211.6961, 3493.3776] +24-11-19 20:32:04 | D | best error = [ 12.7584, 12.7584, 12.7584, 12.7584, 12.7584] +24-11-19 20:32:04 | D | + error = [12.7584] +24-11-19 20:32:04 | D | - Calibrating model.layers.18.self_attn.v_proj.weight +24-11-19 20:32:04 | D | + w: sint8 +24-11-19 20:32:04 | D | + x: None +24-11-19 20:32:04 | D | + y: None +24-11-19 20:32:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:04 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:32:04 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:32:04 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:32:04 | D | - range ratio = [ 1.0000] +24-11-19 20:32:04 | D | sum error = [ 6.0864] +24-11-19 20:32:04 | D | best error = [ 6.0864] +24-11-19 20:32:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:05 | D | sum error = [ 6.0340, 6.0292, 6.0667, 6.1261, 6.2388] +24-11-19 20:32:05 | D | best error = [ 5.6815, 5.5201, 5.4346, 5.3879, 5.3640] +24-11-19 20:32:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:05 | D | sum error = [ 6.3995, 6.6329, 6.8717, 7.2201, 7.6198] +24-11-19 20:32:05 | D | best error = [ 5.3494, 5.3442, 5.3421, 5.3417, 5.3417] +24-11-19 20:32:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:05 | D | sum error = [ 8.0338, 8.5453, 9.1211, 9.7220, 10.4057] +24-11-19 20:32:05 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:32:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:05 | D | sum error = [ 11.1613, 11.9249, 12.7925, 13.7020, 14.6907] +24-11-19 20:32:05 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:32:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:05 | D | sum error = [ 15.7477, 16.8738, 18.0186, 19.2809, 20.6476] +24-11-19 20:32:05 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:32:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:05 | D | sum error = [ 22.0405, 23.5531, 25.1446, 26.7865, 28.5423] +24-11-19 20:32:05 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:32:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:05 | D | sum error = [ 30.4293, 32.3935, 34.4410, 36.6370, 38.9141] +24-11-19 20:32:05 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:32:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:05 | D | sum error = [ 41.3305, 43.8759, 46.5510, 49.3765, 52.3312] +24-11-19 20:32:05 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:32:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:05 | D | sum error = [ 55.4411, 58.6855, 62.0819, 65.6545, 69.3930] +24-11-19 20:32:05 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:32:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:05 | D | sum error = [ 73.3313, 77.4605, 81.7666, 86.2464, 90.9613] +24-11-19 20:32:05 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:32:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:05 | D | sum error = [ 95.8781, 100.9988, 106.3716, 111.9516, 117.7608] +24-11-19 20:32:05 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:32:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:05 | D | sum error = [ 123.8240, 130.1264, 136.6955, 143.5235, 150.6368] +24-11-19 20:32:05 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:32:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:05 | D | sum error = [ 158.0026, 165.6424, 173.5725, 181.8308, 190.3730] +24-11-19 20:32:05 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:32:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:05 | D | sum error = [ 199.2447, 208.4075, 217.8923, 227.7160, 237.8578] +24-11-19 20:32:05 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:32:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:05 | D | sum error = [ 248.3489, 259.1766, 270.3605, 281.8979, 293.8014] +24-11-19 20:32:05 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:32:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:05 | D | sum error = [ 306.0654, 318.6888, 331.6921, 345.0594, 358.8035] +24-11-19 20:32:05 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:32:05 | D | + error = [5.3416] +24-11-19 20:32:05 | D | - Calibrating model.layers.18.self_attn.o_proj.weight +24-11-19 20:32:05 | D | + w: sint8 +24-11-19 20:32:05 | D | + x: None +24-11-19 20:32:05 | D | + y: None +24-11-19 20:32:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:05 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:32:05 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:32:05 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:32:05 | D | - range ratio = [ 1.0000] +24-11-19 20:32:05 | D | sum error = [ 1.5069] +24-11-19 20:32:05 | D | best error = [ 1.5069] +24-11-19 20:32:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:06 | D | sum error = [ 1.4957, 1.4867, 1.4836, 1.4937, 1.5134] +24-11-19 20:32:06 | D | best error = [ 1.4180, 1.3751, 1.3493, 1.3327, 1.3219] +24-11-19 20:32:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:06 | D | sum error = [ 1.5353, 1.5719, 1.6156, 1.6717, 1.7380] +24-11-19 20:32:06 | D | best error = [ 1.3149, 1.3094, 1.3060, 1.3035, 1.3019] +24-11-19 20:32:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:06 | D | sum error = [ 1.8183, 1.9073, 2.0060, 2.1269, 2.2480] +24-11-19 20:32:06 | D | best error = [ 1.3006, 1.2996, 1.2988, 1.2982, 1.2977] +24-11-19 20:32:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:06 | D | sum error = [ 2.3890, 2.5436, 2.7093, 2.8909, 3.0870] +24-11-19 20:32:06 | D | best error = [ 1.2975, 1.2973, 1.2972, 1.2971, 1.2970] +24-11-19 20:32:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:06 | D | sum error = [ 3.2969, 3.5152, 3.7557, 4.0127, 4.2863] +24-11-19 20:32:06 | D | best error = [ 1.2969, 1.2969, 1.2968, 1.2968, 1.2968] +24-11-19 20:32:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:06 | D | sum error = [ 4.5713, 4.8776, 5.2071, 5.5477, 5.9179] +24-11-19 20:32:06 | D | best error = [ 1.2968, 1.2968, 1.2968, 1.2968, 1.2967] +24-11-19 20:32:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:06 | D | sum error = [ 6.3042, 6.7167, 7.1471, 7.6030, 8.0884] +24-11-19 20:32:06 | D | best error = [ 1.2967, 1.2967, 1.2967, 1.2967, 1.2967] +24-11-19 20:32:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:06 | D | sum error = [ 8.5997, 9.1401, 9.7036, 10.3003, 10.9347] +24-11-19 20:32:06 | D | best error = [ 1.2967, 1.2967, 1.2967, 1.2967, 1.2967] +24-11-19 20:32:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:06 | D | sum error = [ 11.5935, 12.2953, 13.0294, 13.7976, 14.6103] +24-11-19 20:32:06 | D | best error = [ 1.2967, 1.2967, 1.2967, 1.2967, 1.2967] +24-11-19 20:32:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:06 | D | sum error = [ 15.4606, 16.3544, 17.2924, 18.2757, 19.3087] +24-11-19 20:32:06 | D | best error = [ 1.2967, 1.2967, 1.2967, 1.2967, 1.2967] +24-11-19 20:32:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:06 | D | sum error = [ 20.3875, 21.5193, 22.7061, 23.9482, 25.2489] +24-11-19 20:32:06 | D | best error = [ 1.2967, 1.2967, 1.2967, 1.2967, 1.2967] +24-11-19 20:32:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:06 | D | sum error = [ 26.6052, 28.0230, 29.5052, 31.0527, 32.6701] +24-11-19 20:32:06 | D | best error = [ 1.2967, 1.2967, 1.2967, 1.2967, 1.2967] +24-11-19 20:32:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:06 | D | sum error = [ 34.3513, 36.1047, 37.9326, 39.8346, 41.8117] +24-11-19 20:32:06 | D | best error = [ 1.2967, 1.2967, 1.2967, 1.2967, 1.2967] +24-11-19 20:32:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:06 | D | sum error = [ 43.8698, 46.0057, 48.2276, 50.5363, 52.9280] +24-11-19 20:32:06 | D | best error = [ 1.2967, 1.2967, 1.2967, 1.2967, 1.2967] +24-11-19 20:32:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:06 | D | sum error = [ 55.4131, 57.9839, 60.6460, 63.4016, 66.2511] +24-11-19 20:32:06 | D | best error = [ 1.2967, 1.2967, 1.2967, 1.2967, 1.2967] +24-11-19 20:32:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:06 | D | sum error = [ 69.1966, 72.2384, 75.3827, 78.6299, 81.9784] +24-11-19 20:32:06 | D | best error = [ 1.2967, 1.2967, 1.2967, 1.2967, 1.2967] +24-11-19 20:32:06 | D | + error = [1.2967] +24-11-19 20:32:06 | D | - Calibrating model.layers.18.mlp.up_proj.weight +24-11-19 20:32:06 | D | + w: sint8 +24-11-19 20:32:06 | D | + x: None +24-11-19 20:32:06 | D | + y: None +24-11-19 20:32:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:06 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:32:06 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:32:06 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:32:06 | D | - range ratio = [ 1.0000] +24-11-19 20:32:06 | D | sum error = [ 8.2844] +24-11-19 20:32:06 | D | best error = [ 8.2844] +24-11-19 20:32:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:07 | D | sum error = [ 8.2269, 8.1977, 8.2435, 8.3210, 8.4733] +24-11-19 20:32:07 | D | best error = [ 7.7102, 7.4805, 7.3630, 7.2949, 7.2568] +24-11-19 20:32:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:07 | D | sum error = [ 8.6933, 8.9809, 9.3397, 9.7964, 10.2954] +24-11-19 20:32:07 | D | best error = [ 7.2389, 7.2304, 7.2279, 7.2268, 7.2266] +24-11-19 20:32:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:07 | D | sum error = [ 10.8956, 11.5479, 12.3121, 13.1347, 14.0382] +24-11-19 20:32:07 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:32:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:07 | D | sum error = [ 15.0210, 16.0826, 17.2445, 18.4577, 19.8004] +24-11-19 20:32:07 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:32:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:07 | D | sum error = [ 21.1858, 22.7118, 24.2950, 25.9928, 27.8196] +24-11-19 20:32:07 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:32:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:07 | D | sum error = [ 29.7324, 31.7577, 33.9133, 36.1796, 38.5927] +24-11-19 20:32:07 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:32:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:07 | D | sum error = [ 41.1137, 43.7738, 46.6003, 49.5581, 52.6961] +24-11-19 20:32:07 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:32:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:07 | D | sum error = [ 55.9811, 59.4739, 63.1150, 66.9605, 70.9934] +24-11-19 20:32:07 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:32:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:07 | D | sum error = [ 75.2214, 79.6633, 84.3147, 89.2119, 94.3414] +24-11-19 20:32:07 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:32:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:07 | D | sum error = [ 99.7012, 105.3106, 111.1993, 117.3497, 123.7899] +24-11-19 20:32:07 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:32:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:07 | D | sum error = [ 130.4968, 137.5311, 144.8586, 152.5441, 160.5273] +24-11-19 20:32:07 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:32:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:07 | D | sum error = [ 168.8732, 177.5588, 186.6133, 196.0291, 205.8108] +24-11-19 20:32:07 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:32:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:07 | D | sum error = [ 215.9810, 226.5494, 237.5227, 248.9137, 260.7201] +24-11-19 20:32:07 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:32:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:07 | D | sum error = [ 272.9730, 285.6835, 298.8578, 312.4886, 326.6153] +24-11-19 20:32:07 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:32:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:07 | D | sum error = [ 341.2046, 356.3034, 371.8960, 387.9989, 404.5958] +24-11-19 20:32:07 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:32:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:07 | D | sum error = [ 421.7216, 439.3662, 457.5276, 476.2241, 495.4498] +24-11-19 20:32:07 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:32:07 | D | + error = [7.2266] +24-11-19 20:32:07 | D | - Calibrating model.layers.18.mlp.gate_proj.weight +24-11-19 20:32:07 | D | + w: sint8 +24-11-19 20:32:07 | D | + x: None +24-11-19 20:32:07 | D | + y: None +24-11-19 20:32:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:07 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:32:07 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:32:07 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:32:07 | D | - range ratio = [ 1.0000] +24-11-19 20:32:07 | D | sum error = [ 8.7728] +24-11-19 20:32:07 | D | best error = [ 8.7728] +24-11-19 20:32:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:08 | D | sum error = [ 8.7093, 8.6798, 8.7034, 8.7892, 8.9786] +24-11-19 20:32:08 | D | best error = [ 8.1661, 7.9336, 7.8035, 7.7276, 7.6873] +24-11-19 20:32:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:08 | D | sum error = [ 9.2120, 9.5065, 9.9062, 10.3616, 10.9338] +24-11-19 20:32:08 | D | best error = [ 7.6674, 7.6589, 7.6561, 7.6554, 7.6551] +24-11-19 20:32:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:08 | D | sum error = [ 11.5673, 12.2638, 13.0964, 13.9563, 14.9438] +24-11-19 20:32:08 | D | best error = [ 7.6550, 7.6550, 7.6550, 7.6550, 7.6550] +24-11-19 20:32:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:08 | D | sum error = [ 16.0157, 17.1800, 18.4257, 19.7754, 21.2071] +24-11-19 20:32:08 | D | best error = [ 7.6550, 7.6550, 7.6550, 7.6550, 7.6550] +24-11-19 20:32:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:08 | D | sum error = [ 22.7690, 24.4242, 26.1826, 28.0635, 30.0138] +24-11-19 20:32:08 | D | best error = [ 7.6550, 7.6550, 7.6550, 7.6550, 7.6550] +24-11-19 20:32:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:08 | D | sum error = [ 32.1354, 34.3560, 36.7490, 39.2937, 41.9482] +24-11-19 20:32:08 | D | best error = [ 7.6550, 7.6550, 7.6550, 7.6550, 7.6550] +24-11-19 20:32:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:08 | D | sum error = [ 44.7791, 47.7659, 50.9391, 54.3018, 57.8537] +24-11-19 20:32:08 | D | best error = [ 7.6550, 7.6550, 7.6550, 7.6550, 7.6550] +24-11-19 20:32:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:08 | D | sum error = [ 61.6113, 65.5895, 69.7964, 74.2521, 78.9406] +24-11-19 20:32:08 | D | best error = [ 7.6550, 7.6550, 7.6550, 7.6550, 7.6550] +24-11-19 20:32:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:08 | D | sum error = [ 83.8766, 89.1174, 94.6722, 100.5063, 106.6557] +24-11-19 20:32:08 | D | best error = [ 7.6550, 7.6550, 7.6550, 7.6550, 7.6550] +24-11-19 20:32:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:08 | D | sum error = [ 113.1377, 119.9972, 127.2092, 134.7892, 142.8042] +24-11-19 20:32:08 | D | best error = [ 7.6550, 7.6550, 7.6550, 7.6550, 7.6550] +24-11-19 20:32:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:08 | D | sum error = [ 151.2029, 160.0132, 169.3143, 179.0642, 189.3249] +24-11-19 20:32:08 | D | best error = [ 7.6550, 7.6550, 7.6550, 7.6550, 7.6550] +24-11-19 20:32:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:08 | D | sum error = [ 200.0911, 211.4142, 223.2731, 235.7389, 248.7804] +24-11-19 20:32:08 | D | best error = [ 7.6550, 7.6550, 7.6550, 7.6550, 7.6550] +24-11-19 20:32:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:08 | D | sum error = [ 262.4426, 276.7442, 291.6969, 307.3182, 323.6220] +24-11-19 20:32:08 | D | best error = [ 7.6550, 7.6550, 7.6550, 7.6550, 7.6550] +24-11-19 20:32:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:08 | D | sum error = [ 340.6623, 358.4072, 376.8924, 396.1089, 416.0682] +24-11-19 20:32:08 | D | best error = [ 7.6550, 7.6550, 7.6550, 7.6550, 7.6550] +24-11-19 20:32:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:08 | D | sum error = [ 436.8231, 458.3699, 480.7094, 503.8481, 527.7943] +24-11-19 20:32:08 | D | best error = [ 7.6550, 7.6550, 7.6550, 7.6550, 7.6550] +24-11-19 20:32:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:08 | D | sum error = [ 552.5581, 578.1714, 604.5879, 631.8204, 659.8769] +24-11-19 20:32:08 | D | best error = [ 7.6550, 7.6550, 7.6550, 7.6550, 7.6550] +24-11-19 20:32:08 | D | + error = [7.6550] +24-11-19 20:32:08 | D | - Calibrating model.layers.18.mlp.down_proj.weight +24-11-19 20:32:08 | D | + w: sint8 +24-11-19 20:32:08 | D | + x: None +24-11-19 20:32:08 | D | + y: None +24-11-19 20:32:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:08 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:32:08 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:32:09 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:32:09 | D | - range ratio = [ 1.0000] +24-11-19 20:32:09 | D | sum error = [ 2.9066] +24-11-19 20:32:09 | D | best error = [ 2.9066] +24-11-19 20:32:10 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:10 | D | sum error = [ 2.8778, 2.8642, 2.8414, 2.8310, 2.8318] +24-11-19 20:32:10 | D | best error = [ 2.7904, 2.7320, 2.6904, 2.6615, 2.6396] +24-11-19 20:32:10 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:10 | D | sum error = [ 2.8470, 2.8707, 2.9071, 2.9591, 3.0275] +24-11-19 20:32:10 | D | best error = [ 2.6226, 2.6094, 2.6004, 2.5940, 2.5893] +24-11-19 20:32:10 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:10 | D | sum error = [ 3.1052, 3.2067, 3.3243, 3.4639, 3.6244] +24-11-19 20:32:10 | D | best error = [ 2.5855, 2.5833, 2.5822, 2.5810, 2.5806] +24-11-19 20:32:10 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:10 | D | sum error = [ 3.8153, 4.0260, 4.2537, 4.5048, 4.7869] +24-11-19 20:32:10 | D | best error = [ 2.5803, 2.5800, 2.5798, 2.5798, 2.5797] +24-11-19 20:32:10 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:10 | D | sum error = [ 5.0966, 5.4281, 5.7883, 6.1836, 6.6075] +24-11-19 20:32:10 | D | best error = [ 2.5797, 2.5797, 2.5797, 2.5797, 2.5797] +24-11-19 20:32:10 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:10 | D | sum error = [ 7.0593, 7.5455, 8.0653, 8.6297, 9.2252] +24-11-19 20:32:10 | D | best error = [ 2.5797, 2.5797, 2.5797, 2.5797, 2.5797] +24-11-19 20:32:10 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:10 | D | sum error = [ 9.8612, 10.5435, 11.2642, 12.0344, 12.8502] +24-11-19 20:32:10 | D | best error = [ 2.5797, 2.5797, 2.5797, 2.5797, 2.5797] +24-11-19 20:32:10 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:10 | D | sum error = [ 13.7153, 14.6316, 15.6089, 16.6373, 17.7306] +24-11-19 20:32:10 | D | best error = [ 2.5797, 2.5797, 2.5797, 2.5797, 2.5797] +24-11-19 20:32:10 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:10 | D | sum error = [ 18.8805, 20.1013, 21.3876, 22.7423, 24.1765] +24-11-19 20:32:10 | D | best error = [ 2.5797, 2.5797, 2.5797, 2.5797, 2.5797] +24-11-19 20:32:10 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:10 | D | sum error = [ 25.6791, 27.2674, 28.9376, 30.7026, 32.5480] +24-11-19 20:32:10 | D | best error = [ 2.5797, 2.5797, 2.5797, 2.5797, 2.5797] +24-11-19 20:32:10 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:10 | D | sum error = [ 34.4877, 36.5253, 38.6616, 40.9029, 43.2586] +24-11-19 20:32:10 | D | best error = [ 2.5797, 2.5797, 2.5797, 2.5797, 2.5797] +24-11-19 20:32:10 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:10 | D | sum error = [ 45.7200, 48.2985, 50.9981, 53.8174, 56.7709] +24-11-19 20:32:10 | D | best error = [ 2.5797, 2.5797, 2.5797, 2.5797, 2.5797] +24-11-19 20:32:10 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:10 | D | sum error = [ 59.8559, 63.0713, 66.4269, 69.9296, 73.5750] +24-11-19 20:32:10 | D | best error = [ 2.5797, 2.5797, 2.5797, 2.5797, 2.5797] +24-11-19 20:32:10 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:10 | D | sum error = [ 77.3747, 81.3251, 85.4361, 89.7120, 94.1419] +24-11-19 20:32:10 | D | best error = [ 2.5797, 2.5797, 2.5797, 2.5797, 2.5797] +24-11-19 20:32:10 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:10 | D | sum error = [ 98.7463, 103.5235, 108.4706, 113.5961, 118.9017] +24-11-19 20:32:10 | D | best error = [ 2.5797, 2.5797, 2.5797, 2.5797, 2.5797] +24-11-19 20:32:10 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:10 | D | sum error = [ 124.3913, 130.0714, 135.9451, 142.0079, 148.2673] +24-11-19 20:32:10 | D | best error = [ 2.5797, 2.5797, 2.5797, 2.5797, 2.5797] +24-11-19 20:32:10 | D | + error = [2.5797] +24-11-19 20:32:10 | D | - Quantizing model.layers.18.self_attn.q_proj.weight +24-11-19 20:32:11 | D | - Quantizing model.layers.18.self_attn.k_proj.weight +24-11-19 20:32:12 | D | - Quantizing model.layers.18.self_attn.v_proj.weight +24-11-19 20:32:12 | D | - Quantizing model.layers.18.self_attn.o_proj.weight +24-11-19 20:32:13 | D | - Quantizing model.layers.18.mlp.up_proj.weight +24-11-19 20:32:14 | D | - Quantizing model.layers.18.mlp.gate_proj.weight +24-11-19 20:32:15 | D | - Quantizing model.layers.18.mlp.down_proj.weight +24-11-19 20:32:24 | D | - Quantizing layer model.layers.19 +24-11-19 20:32:24 | D | - Calibrating model.layers.19.self_attn.q_proj.weight +24-11-19 20:32:24 | D | + w: sint8 +24-11-19 20:32:24 | D | + x: None +24-11-19 20:32:24 | D | + y: None +24-11-19 20:32:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:32:24 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:32:24 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:32:24 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:32:24 | D | - range ratio = [ 1.0000] +24-11-19 20:32:24 | D | sum error = [ 11.6314] +24-11-19 20:32:24 | D | best error = [ 11.6314] +24-11-19 20:32:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:37 | D | sum error = [ 11.4722, 11.5212, 11.8127, 11.8025, 11.8781] +24-11-19 20:32:37 | D | best error = [ 11.4722, 11.4722, 11.4722, 11.4722, 11.4722] +24-11-19 20:32:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:37 | D | sum error = [ 12.3716, 12.7963, 13.2313, 13.9115, 14.5650] +24-11-19 20:32:37 | D | best error = [ 11.4722, 11.4722, 11.4722, 11.4722, 11.4722] +24-11-19 20:32:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:37 | D | sum error = [ 15.4471, 16.2235, 17.6517, 18.5942, 19.8457] +24-11-19 20:32:37 | D | best error = [ 11.4722, 11.4722, 11.4722, 11.4722, 11.4722] +24-11-19 20:32:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:37 | D | sum error = [ 21.4369, 23.0265, 24.7298, 26.8696, 28.7164] +24-11-19 20:32:37 | D | best error = [ 11.4722, 11.4722, 11.4722, 11.4722, 11.4722] +24-11-19 20:32:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:37 | D | sum error = [ 31.0649, 33.2053, 35.8227, 38.9399, 41.7369] +24-11-19 20:32:37 | D | best error = [ 11.4722, 11.4722, 11.4722, 11.4722, 11.4722] +24-11-19 20:32:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:37 | D | sum error = [ 45.1890, 48.6732, 52.4932, 56.7549, 61.1256] +24-11-19 20:32:37 | D | best error = [ 11.4722, 11.4722, 11.4722, 11.4722, 11.4722] +24-11-19 20:32:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:37 | D | sum error = [ 65.8379, 71.0380, 76.5854, 82.4642, 88.9802] +24-11-19 20:32:37 | D | best error = [ 11.4722, 11.4722, 11.4722, 11.4722, 11.4722] +24-11-19 20:32:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:37 | D | sum error = [ 96.1493, 103.2029, 110.9963, 119.8344, 128.9688] +24-11-19 20:32:37 | D | best error = [ 11.4722, 11.4722, 11.4722, 11.4722, 11.4722] +24-11-19 20:32:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:37 | D | sum error = [ 138.7137, 149.1493, 160.2952, 172.3653, 185.6094] +24-11-19 20:32:37 | D | best error = [ 11.4722, 11.4722, 11.4722, 11.4722, 11.4722] +24-11-19 20:32:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:37 | D | sum error = [ 199.5359, 214.3677, 230.3379, 247.5024, 266.2798] +24-11-19 20:32:37 | D | best error = [ 11.4722, 11.4722, 11.4722, 11.4722, 11.4722] +24-11-19 20:32:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:37 | D | sum error = [ 286.4801, 307.4325, 330.4743, 354.7224, 381.2907] +24-11-19 20:32:37 | D | best error = [ 11.4722, 11.4722, 11.4722, 11.4722, 11.4722] +24-11-19 20:32:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:37 | D | sum error = [ 409.7859, 440.2785, 473.7262, 509.6812, 548.3559] +24-11-19 20:32:37 | D | best error = [ 11.4722, 11.4722, 11.4722, 11.4722, 11.4722] +24-11-19 20:32:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:37 | D | sum error = [ 590.6533, 636.5452, 687.0076, 741.5281, 801.5181] +24-11-19 20:32:37 | D | best error = [ 11.4722, 11.4722, 11.4722, 11.4722, 11.4722] +24-11-19 20:32:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:37 | D | sum error = [ 867.7282, 940.4285, 1020.9489, 1110.3067, 1208.7090] +24-11-19 20:32:37 | D | best error = [ 11.4722, 11.4722, 11.4722, 11.4722, 11.4722] +24-11-19 20:32:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:37 | D | sum error = [ 1316.5413, 1437.2982, 1571.3371, 1719.9737, 1884.8334] +24-11-19 20:32:37 | D | best error = [ 11.4722, 11.4722, 11.4722, 11.4722, 11.4722] +24-11-19 20:32:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:37 | D | sum error = [ 2066.5968, 2268.6725, 2488.7081, 2730.1784, 2992.2246] +24-11-19 20:32:37 | D | best error = [ 11.4722, 11.4722, 11.4722, 11.4722, 11.4722] +24-11-19 20:32:37 | D | + error = [11.4722] +24-11-19 20:32:37 | D | - Calibrating model.layers.19.self_attn.k_proj.weight +24-11-19 20:32:37 | D | + w: sint8 +24-11-19 20:32:37 | D | + x: None +24-11-19 20:32:37 | D | + y: None +24-11-19 20:32:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:32:37 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:32:37 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:32:37 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:32:38 | D | - range ratio = [ 1.0000] +24-11-19 20:32:38 | D | sum error = [ 12.6203] +24-11-19 20:32:38 | D | best error = [ 12.6203] +24-11-19 20:32:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:50 | D | sum error = [ 12.2736, 12.5789, 12.2473, 12.6142, 12.7904] +24-11-19 20:32:50 | D | best error = [ 12.2736, 12.2736, 12.2473, 12.2473, 12.2473] +24-11-19 20:32:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:50 | D | sum error = [ 13.2615, 13.5597, 14.9103, 15.1199, 17.3648] +24-11-19 20:32:50 | D | best error = [ 12.2473, 12.2473, 12.2473, 12.2473, 12.2473] +24-11-19 20:32:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:50 | D | sum error = [ 16.9832, 18.3664, 19.2287, 21.6044, 22.0547] +24-11-19 20:32:50 | D | best error = [ 12.2473, 12.2473, 12.2473, 12.2473, 12.2473] +24-11-19 20:32:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:50 | D | sum error = [ 25.2542, 25.5019, 28.1383, 30.9185, 32.5912] +24-11-19 20:32:50 | D | best error = [ 12.2473, 12.2473, 12.2473, 12.2473, 12.2473] +24-11-19 20:32:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:50 | D | sum error = [ 35.5847, 38.8338, 40.7144, 45.0065, 47.5910] +24-11-19 20:32:50 | D | best error = [ 12.2473, 12.2473, 12.2473, 12.2473, 12.2473] +24-11-19 20:32:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:50 | D | sum error = [ 52.2390, 55.9538, 59.9473, 65.0674, 68.9798] +24-11-19 20:32:50 | D | best error = [ 12.2473, 12.2473, 12.2473, 12.2473, 12.2473] +24-11-19 20:32:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:50 | D | sum error = [ 75.1849, 80.8475, 87.0607, 94.7932, 102.1909] +24-11-19 20:32:50 | D | best error = [ 12.2473, 12.2473, 12.2473, 12.2473, 12.2473] +24-11-19 20:32:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:50 | D | sum error = [ 110.3110, 118.4945, 127.1706, 137.3652, 147.0858] +24-11-19 20:32:50 | D | best error = [ 12.2473, 12.2473, 12.2473, 12.2473, 12.2473] +24-11-19 20:32:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:50 | D | sum error = [ 159.8035, 171.1197, 184.1182, 199.0874, 214.0382] +24-11-19 20:32:50 | D | best error = [ 12.2473, 12.2473, 12.2473, 12.2473, 12.2473] +24-11-19 20:32:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:50 | D | sum error = [ 229.1682, 246.8481, 265.8870, 286.0810, 307.5652] +24-11-19 20:32:50 | D | best error = [ 12.2473, 12.2473, 12.2473, 12.2473, 12.2473] +24-11-19 20:32:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:50 | D | sum error = [ 331.6864, 356.1612, 383.3028, 413.6038, 446.7017] +24-11-19 20:32:50 | D | best error = [ 12.2473, 12.2473, 12.2473, 12.2473, 12.2473] +24-11-19 20:32:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:50 | D | sum error = [ 479.6799, 517.3149, 557.5207, 600.3386, 646.4703] +24-11-19 20:32:50 | D | best error = [ 12.2473, 12.2473, 12.2473, 12.2473, 12.2473] +24-11-19 20:32:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:50 | D | sum error = [ 696.2822, 750.7956, 809.6888, 874.8233, 942.3624] +24-11-19 20:32:50 | D | best error = [ 12.2473, 12.2473, 12.2473, 12.2473, 12.2473] +24-11-19 20:32:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:50 | D | sum error = [ 1018.8190, 1102.7454, 1193.4741, 1294.4778, 1403.4891] +24-11-19 20:32:50 | D | best error = [ 12.2473, 12.2473, 12.2473, 12.2473, 12.2473] +24-11-19 20:32:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:50 | D | sum error = [ 1525.9448, 1658.1634, 1802.9085, 1965.4496, 2140.8335] +24-11-19 20:32:50 | D | best error = [ 12.2473, 12.2473, 12.2473, 12.2473, 12.2473] +24-11-19 20:32:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:50 | D | sum error = [ 2338.5571, 2544.2854, 2769.8861, 3015.2089, 3272.6558] +24-11-19 20:32:50 | D | best error = [ 12.2473, 12.2473, 12.2473, 12.2473, 12.2473] +24-11-19 20:32:50 | D | + error = [12.2473] +24-11-19 20:32:50 | D | - Calibrating model.layers.19.self_attn.v_proj.weight +24-11-19 20:32:50 | D | + w: sint8 +24-11-19 20:32:50 | D | + x: None +24-11-19 20:32:50 | D | + y: None +24-11-19 20:32:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:50 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:32:50 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:32:51 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:32:51 | D | - range ratio = [ 1.0000] +24-11-19 20:32:51 | D | sum error = [ 6.1234] +24-11-19 20:32:51 | D | best error = [ 6.1234] +24-11-19 20:32:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:51 | D | sum error = [ 6.0847, 6.0657, 6.0869, 6.1488, 6.2937] +24-11-19 20:32:51 | D | best error = [ 5.7215, 5.5622, 5.4799, 5.4270, 5.4037] +24-11-19 20:32:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:51 | D | sum error = [ 6.4281, 6.6476, 6.9059, 7.2409, 7.6318] +24-11-19 20:32:51 | D | best error = [ 5.3893, 5.3829, 5.3809, 5.3797, 5.3797] +24-11-19 20:32:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:51 | D | sum error = [ 8.0721, 8.5796, 9.1550, 9.7666, 10.4389] +24-11-19 20:32:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 20:32:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:51 | D | sum error = [ 11.1835, 11.9705, 12.8502, 13.7767, 14.7618] +24-11-19 20:32:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 20:32:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:51 | D | sum error = [ 15.7862, 16.9367, 18.1504, 19.4220, 20.7718] +24-11-19 20:32:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 20:32:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:51 | D | sum error = [ 22.1958, 23.6863, 25.3273, 27.0102, 28.7565] +24-11-19 20:32:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 20:32:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:51 | D | sum error = [ 30.6524, 32.6161, 34.7141, 36.9094, 39.2206] +24-11-19 20:32:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 20:32:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:51 | D | sum error = [ 41.6579, 44.2140, 46.8888, 49.7145, 52.6766] +24-11-19 20:32:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 20:32:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:51 | D | sum error = [ 55.7678, 59.0285, 62.4750, 66.0448, 69.7905] +24-11-19 20:32:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 20:32:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:51 | D | sum error = [ 73.7466, 77.8839, 82.2011, 86.7136, 91.4348] +24-11-19 20:32:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 20:32:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:51 | D | sum error = [ 96.3372, 101.4757, 106.8359, 112.4277, 118.2485] +24-11-19 20:32:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 20:32:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:51 | D | sum error = [ 124.3272, 130.6732, 137.2620, 144.1314, 151.2762] +24-11-19 20:32:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 20:32:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:51 | D | sum error = [ 158.6966, 166.4087, 174.4078, 182.7066, 191.3133] +24-11-19 20:32:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 20:32:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:51 | D | sum error = [ 200.2204, 209.4552, 219.0014, 228.8654, 239.0831] +24-11-19 20:32:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 20:32:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:51 | D | sum error = [ 249.6311, 260.5260, 271.7729, 283.3947, 295.3889] +24-11-19 20:32:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 20:32:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:51 | D | sum error = [ 307.7533, 320.4956, 333.6333, 347.1573, 361.0445] +24-11-19 20:32:51 | D | best error = [ 5.3796, 5.3796, 5.3796, 5.3796, 5.3796] +24-11-19 20:32:51 | D | + error = [5.3796] +24-11-19 20:32:51 | D | - Calibrating model.layers.19.self_attn.o_proj.weight +24-11-19 20:32:51 | D | + w: sint8 +24-11-19 20:32:51 | D | + x: None +24-11-19 20:32:51 | D | + y: None +24-11-19 20:32:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:51 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:32:51 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:32:51 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:32:51 | D | - range ratio = [ 1.0000] +24-11-19 20:32:51 | D | sum error = [ 1.4442] +24-11-19 20:32:51 | D | best error = [ 1.4442] +24-11-19 20:32:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:52 | D | sum error = [ 1.4344, 1.4279, 1.4233, 1.4337, 1.4452] +24-11-19 20:32:52 | D | best error = [ 1.3581, 1.3190, 1.2933, 1.2783, 1.2674] +24-11-19 20:32:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:52 | D | sum error = [ 1.4696, 1.5055, 1.5472, 1.5959, 1.6679] +24-11-19 20:32:52 | D | best error = [ 1.2605, 1.2558, 1.2527, 1.2508, 1.2497] +24-11-19 20:32:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:52 | D | sum error = [ 1.7432, 1.8306, 1.9274, 2.0374, 2.1608] +24-11-19 20:32:52 | D | best error = [ 1.2490, 1.2486, 1.2483, 1.2480, 1.2479] +24-11-19 20:32:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:52 | D | sum error = [ 2.2963, 2.4414, 2.6039, 2.7776, 2.9609] +24-11-19 20:32:52 | D | best error = [ 1.2478, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:52 | D | sum error = [ 3.1610, 3.3784, 3.6096, 3.8476, 4.1065] +24-11-19 20:32:52 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:52 | D | sum error = [ 4.3842, 4.6767, 4.9824, 5.3110, 5.6564] +24-11-19 20:32:52 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:52 | D | sum error = [ 6.0201, 6.4101, 6.8200, 7.2509, 7.7093] +24-11-19 20:32:52 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:52 | D | sum error = [ 8.1909, 8.7006, 9.2361, 9.8032, 10.3954] +24-11-19 20:32:52 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:52 | D | sum error = [ 11.0233, 11.6871, 12.3792, 13.1127, 13.8782] +24-11-19 20:32:52 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:52 | D | sum error = [ 14.6826, 15.5294, 16.4147, 17.3504, 18.3302] +24-11-19 20:32:52 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:52 | D | sum error = [ 19.3549, 20.4322, 21.5564, 22.7373, 23.9708] +24-11-19 20:32:52 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:52 | D | sum error = [ 25.2612, 26.6100, 28.0200, 29.4973, 31.0361] +24-11-19 20:32:52 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:52 | D | sum error = [ 32.6465, 34.3200, 36.0695, 37.8876, 39.7849] +24-11-19 20:32:52 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:52 | D | sum error = [ 41.7594, 43.8085, 45.9352, 48.1450, 50.4406] +24-11-19 20:32:52 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:52 | D | sum error = [ 52.8228, 55.2918, 57.8511, 60.4996, 63.2413] +24-11-19 20:32:52 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:52 | D | sum error = [ 66.0759, 69.0012, 72.0218, 75.1483, 78.3739] +24-11-19 20:32:52 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:52 | D | + error = [1.2477] +24-11-19 20:32:52 | D | - Calibrating model.layers.19.mlp.up_proj.weight +24-11-19 20:32:52 | D | + w: sint8 +24-11-19 20:32:52 | D | + x: None +24-11-19 20:32:52 | D | + y: None +24-11-19 20:32:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:52 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:32:52 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:32:52 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:32:52 | D | - range ratio = [ 1.0000] +24-11-19 20:32:52 | D | sum error = [ 8.5689] +24-11-19 20:32:52 | D | best error = [ 8.5689] +24-11-19 20:32:53 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:53 | D | sum error = [ 8.4892, 8.4579, 8.4863, 8.6028, 8.7570] +24-11-19 20:32:53 | D | best error = [ 7.9733, 7.7404, 7.6125, 7.5437, 7.5083] +24-11-19 20:32:53 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:53 | D | sum error = [ 8.9984, 9.2995, 9.6525, 10.1222, 10.6438] +24-11-19 20:32:53 | D | best error = [ 7.4898, 7.4822, 7.4797, 7.4790, 7.4787] +24-11-19 20:32:53 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:53 | D | sum error = [ 11.2535, 11.9661, 12.7167, 13.6163, 14.5495] +24-11-19 20:32:53 | D | best error = [ 7.4787, 7.4787, 7.4787, 7.4787, 7.4787] +24-11-19 20:32:53 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:53 | D | sum error = [ 15.5718, 16.6999, 17.8664, 19.1548, 20.5485] +24-11-19 20:32:53 | D | best error = [ 7.4787, 7.4787, 7.4787, 7.4787, 7.4787] +24-11-19 20:32:53 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:53 | D | sum error = [ 22.0095, 23.5564, 25.2413, 27.0080, 28.8850] +24-11-19 20:32:53 | D | best error = [ 7.4787, 7.4787, 7.4787, 7.4787, 7.4787] +24-11-19 20:32:53 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:53 | D | sum error = [ 30.8389, 32.9887, 35.2019, 37.5530, 40.0535] +24-11-19 20:32:53 | D | best error = [ 7.4787, 7.4787, 7.4787, 7.4787, 7.4787] +24-11-19 20:32:53 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:53 | D | sum error = [ 42.6628, 45.4303, 48.3517, 51.4131, 54.6615] +24-11-19 20:32:53 | D | best error = [ 7.4787, 7.4787, 7.4787, 7.4787, 7.4787] +24-11-19 20:32:53 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:53 | D | sum error = [ 58.0756, 61.6827, 65.4552, 69.4130, 73.5954] +24-11-19 20:32:53 | D | best error = [ 7.4787, 7.4787, 7.4787, 7.4787, 7.4787] +24-11-19 20:32:53 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:53 | D | sum error = [ 77.9743, 82.5543, 87.3699, 92.4232, 97.6954] +24-11-19 20:32:53 | D | best error = [ 7.4787, 7.4787, 7.4787, 7.4787, 7.4787] +24-11-19 20:32:53 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:53 | D | sum error = [ 103.2490, 109.0561, 115.1457, 121.5041, 128.1709] +24-11-19 20:32:53 | D | best error = [ 7.4787, 7.4787, 7.4787, 7.4787, 7.4787] +24-11-19 20:32:53 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:53 | D | sum error = [ 135.1357, 142.4189, 150.0236, 157.9662, 166.2380] +24-11-19 20:32:53 | D | best error = [ 7.4787, 7.4787, 7.4787, 7.4787, 7.4787] +24-11-19 20:32:53 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:53 | D | sum error = [ 174.8829, 183.8776, 193.2441, 202.9951, 213.1211] +24-11-19 20:32:53 | D | best error = [ 7.4787, 7.4787, 7.4787, 7.4787, 7.4787] +24-11-19 20:32:53 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:53 | D | sum error = [ 223.6552, 234.6085, 245.9691, 257.7603, 269.9796] +24-11-19 20:32:53 | D | best error = [ 7.4787, 7.4787, 7.4787, 7.4787, 7.4787] +24-11-19 20:32:53 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:53 | D | sum error = [ 282.6456, 295.7730, 309.3686, 323.4517, 338.0031] +24-11-19 20:32:53 | D | best error = [ 7.4787, 7.4787, 7.4787, 7.4787, 7.4787] +24-11-19 20:32:53 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:53 | D | sum error = [ 353.0518, 368.6061, 384.6839, 401.2785, 418.3963] +24-11-19 20:32:53 | D | best error = [ 7.4787, 7.4787, 7.4787, 7.4787, 7.4787] +24-11-19 20:32:53 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:53 | D | sum error = [ 436.0444, 454.2460, 473.0035, 492.3127, 512.1725] +24-11-19 20:32:53 | D | best error = [ 7.4787, 7.4787, 7.4787, 7.4787, 7.4787] +24-11-19 20:32:53 | D | + error = [7.4787] +24-11-19 20:32:53 | D | - Calibrating model.layers.19.mlp.gate_proj.weight +24-11-19 20:32:53 | D | + w: sint8 +24-11-19 20:32:53 | D | + x: None +24-11-19 20:32:53 | D | + y: None +24-11-19 20:32:53 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:53 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:32:53 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:32:53 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:32:53 | D | - range ratio = [ 1.0000] +24-11-19 20:32:53 | D | sum error = [ 9.0827] +24-11-19 20:32:53 | D | best error = [ 9.0827] +24-11-19 20:32:54 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:54 | D | sum error = [ 9.0302, 8.9884, 9.0399, 9.1341, 9.3228] +24-11-19 20:32:54 | D | best error = [ 8.4721, 8.2227, 8.0920, 8.0194, 7.9828] +24-11-19 20:32:54 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:54 | D | sum error = [ 9.5323, 9.8616, 10.2888, 10.7680, 11.3341] +24-11-19 20:32:54 | D | best error = [ 7.9640, 7.9558, 7.9528, 7.9518, 7.9515] +24-11-19 20:32:54 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:54 | D | sum error = [ 11.9796, 12.7090, 13.5281, 14.4876, 15.4840] +24-11-19 20:32:54 | D | best error = [ 7.9515, 7.9515, 7.9515, 7.9515, 7.9515] +24-11-19 20:32:54 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:54 | D | sum error = [ 16.5747, 17.7595, 19.0575, 20.4220, 21.9248] +24-11-19 20:32:54 | D | best error = [ 7.9515, 7.9515, 7.9515, 7.9515, 7.9515] +24-11-19 20:32:54 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:54 | D | sum error = [ 23.4891, 25.1805, 26.9975, 28.9028, 30.9530] +24-11-19 20:32:54 | D | best error = [ 7.9515, 7.9515, 7.9515, 7.9515, 7.9515] +24-11-19 20:32:54 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:54 | D | sum error = [ 33.1295, 35.4128, 37.8687, 40.4579, 43.1801] +24-11-19 20:32:54 | D | best error = [ 7.9515, 7.9515, 7.9515, 7.9515, 7.9515] +24-11-19 20:32:54 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:54 | D | sum error = [ 46.0685, 49.1558, 52.4048, 55.8277, 59.4571] +24-11-19 20:32:54 | D | best error = [ 7.9515, 7.9515, 7.9515, 7.9515, 7.9515] +24-11-19 20:32:54 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:54 | D | sum error = [ 63.2709, 67.3117, 71.5997, 76.0797, 80.8520] +24-11-19 20:32:54 | D | best error = [ 7.9515, 7.9515, 7.9515, 7.9515, 7.9515] +24-11-19 20:32:54 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:54 | D | sum error = [ 85.8823, 91.1827, 96.8016, 102.6810, 108.9123] +24-11-19 20:32:54 | D | best error = [ 7.9515, 7.9515, 7.9515, 7.9515, 7.9515] +24-11-19 20:32:54 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:54 | D | sum error = [ 115.4791, 122.3773, 129.6343, 137.2885, 145.3355] +24-11-19 20:32:54 | D | best error = [ 7.9515, 7.9515, 7.9515, 7.9515, 7.9515] +24-11-19 20:32:54 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:54 | D | sum error = [ 153.7736, 162.6536, 171.9716, 181.7464, 192.0398] +24-11-19 20:32:54 | D | best error = [ 7.9515, 7.9515, 7.9515, 7.9515, 7.9515] +24-11-19 20:32:54 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:54 | D | sum error = [ 202.7878, 214.0909, 225.9248, 238.3164, 251.2914] +24-11-19 20:32:54 | D | best error = [ 7.9515, 7.9515, 7.9515, 7.9515, 7.9515] +24-11-19 20:32:54 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:54 | D | sum error = [ 264.8826, 279.0399, 293.8322, 309.2634, 325.3688] +24-11-19 20:32:54 | D | best error = [ 7.9515, 7.9515, 7.9515, 7.9515, 7.9515] +24-11-19 20:32:54 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:54 | D | sum error = [ 342.1568, 359.6492, 377.8756, 396.8479, 416.5648] +24-11-19 20:32:54 | D | best error = [ 7.9515, 7.9515, 7.9515, 7.9515, 7.9515] +24-11-19 20:32:54 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:54 | D | sum error = [ 437.0418, 458.2745, 480.2783, 503.0535, 526.6425] +24-11-19 20:32:54 | D | best error = [ 7.9515, 7.9515, 7.9515, 7.9515, 7.9515] +24-11-19 20:32:54 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:54 | D | sum error = [ 550.9698, 576.1531, 602.1326, 628.9369, 656.5331] +24-11-19 20:32:54 | D | best error = [ 7.9515, 7.9515, 7.9515, 7.9515, 7.9515] +24-11-19 20:32:54 | D | + error = [7.9515] +24-11-19 20:32:54 | D | - Calibrating model.layers.19.mlp.down_proj.weight +24-11-19 20:32:54 | D | + w: sint8 +24-11-19 20:32:54 | D | + x: None +24-11-19 20:32:54 | D | + y: None +24-11-19 20:32:54 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:54 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:32:54 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:32:55 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:32:55 | D | - range ratio = [ 1.0000] +24-11-19 20:32:55 | D | sum error = [ 3.1574] +24-11-19 20:32:55 | D | best error = [ 3.1574] +24-11-19 20:32:55 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:55 | D | sum error = [ 3.1301, 3.1111, 3.0919, 3.0961, 3.1011] +24-11-19 20:32:55 | D | best error = [ 3.0239, 2.9600, 2.9147, 2.8819, 2.8583] +24-11-19 20:32:55 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:55 | D | sum error = [ 3.1157, 3.1496, 3.1976, 3.2597, 3.3496] +24-11-19 20:32:55 | D | best error = [ 2.8369, 2.8209, 2.8101, 2.8024, 2.7970] +24-11-19 20:32:55 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:55 | D | sum error = [ 3.4448, 3.5695, 3.7103, 3.8779, 4.0653] +24-11-19 20:32:55 | D | best error = [ 2.7931, 2.7903, 2.7887, 2.7874, 2.7868] +24-11-19 20:32:55 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:55 | D | sum error = [ 4.2743, 4.5097, 4.7709, 5.0539, 5.3664] +24-11-19 20:32:55 | D | best error = [ 2.7863, 2.7859, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:55 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:55 | D | sum error = [ 5.7124, 6.0804, 6.4812, 6.9122, 7.3715] +24-11-19 20:32:55 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:55 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:55 | D | sum error = [ 7.8768, 8.4042, 8.9708, 9.5872, 10.2357] +24-11-19 20:32:55 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:55 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:55 | D | sum error = [ 10.9317, 11.6662, 12.4538, 13.2901, 14.1804] +24-11-19 20:32:55 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:55 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:55 | D | sum error = [ 15.1188, 16.1225, 17.1844, 18.3056, 19.4930] +24-11-19 20:32:55 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:55 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:55 | D | sum error = [ 20.7459, 22.0743, 23.4710, 24.9496, 26.5059] +24-11-19 20:32:55 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:55 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:55 | D | sum error = [ 28.1442, 29.8719, 31.6914, 33.6071, 35.6156] +24-11-19 20:32:55 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:55 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:55 | D | sum error = [ 37.7394, 39.9566, 42.2847, 44.7270, 47.2881] +24-11-19 20:32:55 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:55 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:55 | D | sum error = [ 49.9681, 52.7746, 55.7143, 58.7857, 61.9962] +24-11-19 20:32:55 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:55 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:55 | D | sum error = [ 65.3506, 68.8490, 72.4997, 76.3062, 80.2726] +24-11-19 20:32:55 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:55 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:55 | D | sum error = [ 84.4116, 88.7125, 93.2003, 97.8758, 102.7106] +24-11-19 20:32:55 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:55 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:55 | D | sum error = [ 107.7453, 112.9643, 118.3756, 123.9862, 129.7993] +24-11-19 20:32:55 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:55 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:55 | D | sum error = [ 135.8190, 142.0462, 148.4856, 155.1436, 162.0176] +24-11-19 20:32:55 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:55 | D | + error = [2.7857] +24-11-19 20:32:56 | D | - Quantizing model.layers.19.self_attn.q_proj.weight +24-11-19 20:32:57 | D | - Quantizing model.layers.19.self_attn.k_proj.weight +24-11-19 20:32:58 | D | - Quantizing model.layers.19.self_attn.v_proj.weight +24-11-19 20:32:59 | D | - Quantizing model.layers.19.self_attn.o_proj.weight +24-11-19 20:32:59 | D | - Quantizing model.layers.19.mlp.up_proj.weight +24-11-19 20:33:00 | D | - Quantizing model.layers.19.mlp.gate_proj.weight +24-11-19 20:33:01 | D | - Quantizing model.layers.19.mlp.down_proj.weight +24-11-19 20:33:10 | D | - Quantizing layer model.layers.20 +24-11-19 20:33:10 | D | - Calibrating model.layers.20.self_attn.q_proj.weight +24-11-19 20:33:10 | D | + w: sint8 +24-11-19 20:33:10 | D | + x: None +24-11-19 20:33:10 | D | + y: None +24-11-19 20:33:10 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:33:10 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:33:10 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:33:10 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:33:10 | D | - range ratio = [ 1.0000] +24-11-19 20:33:10 | D | sum error = [ 11.9287] +24-11-19 20:33:10 | D | best error = [ 11.9287] +24-11-19 20:33:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:23 | D | sum error = [ 11.8993, 11.7535, 11.9042, 12.1813, 12.1911] +24-11-19 20:33:23 | D | best error = [ 11.8993, 11.7535, 11.7535, 11.7535, 11.7535] +24-11-19 20:33:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:23 | D | sum error = [ 12.9636, 13.1611, 13.4962, 14.4127, 15.1301] +24-11-19 20:33:23 | D | best error = [ 11.7535, 11.7535, 11.7535, 11.7535, 11.7535] +24-11-19 20:33:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:23 | D | sum error = [ 15.8258, 17.0073, 17.9686, 19.2883, 20.7587] +24-11-19 20:33:23 | D | best error = [ 11.7535, 11.7535, 11.7535, 11.7535, 11.7535] +24-11-19 20:33:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:23 | D | sum error = [ 22.2436, 24.0098, 25.6734, 28.0745, 30.1774] +24-11-19 20:33:23 | D | best error = [ 11.7535, 11.7535, 11.7535, 11.7535, 11.7535] +24-11-19 20:33:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:23 | D | sum error = [ 32.6051, 35.2063, 38.3860, 40.9441, 44.6909] +24-11-19 20:33:23 | D | best error = [ 11.7535, 11.7535, 11.7535, 11.7535, 11.7535] +24-11-19 20:33:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:23 | D | sum error = [ 48.2513, 51.8129, 55.8351, 60.2219, 65.1764] +24-11-19 20:33:23 | D | best error = [ 11.7535, 11.7535, 11.7535, 11.7535, 11.7535] +24-11-19 20:33:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:23 | D | sum error = [ 70.0884, 75.0035, 81.0192, 87.1278, 93.9602] +24-11-19 20:33:23 | D | best error = [ 11.7535, 11.7535, 11.7535, 11.7535, 11.7535] +24-11-19 20:33:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:23 | D | sum error = [ 100.8883, 108.4514, 116.3459, 125.1906, 134.4357] +24-11-19 20:33:23 | D | best error = [ 11.7535, 11.7535, 11.7535, 11.7535, 11.7535] +24-11-19 20:33:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:23 | D | sum error = [ 144.5097, 154.9618, 166.4281, 178.6094, 191.2510] +24-11-19 20:33:23 | D | best error = [ 11.7535, 11.7535, 11.7535, 11.7535, 11.7535] +24-11-19 20:33:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:23 | D | sum error = [ 205.4475, 220.4149, 236.0923, 253.4933, 271.8690] +24-11-19 20:33:23 | D | best error = [ 11.7535, 11.7535, 11.7535, 11.7535, 11.7535] +24-11-19 20:33:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:23 | D | sum error = [ 291.5604, 312.8284, 335.9787, 360.4771, 386.8351] +24-11-19 20:33:23 | D | best error = [ 11.7535, 11.7535, 11.7535, 11.7535, 11.7535] +24-11-19 20:33:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:23 | D | sum error = [ 415.3480, 445.5089, 477.8287, 512.8896, 550.1025] +24-11-19 20:33:23 | D | best error = [ 11.7535, 11.7535, 11.7535, 11.7535, 11.7535] +24-11-19 20:33:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:23 | D | sum error = [ 590.3808, 633.8544, 681.1426, 732.3339, 788.6447] +24-11-19 20:33:23 | D | best error = [ 11.7535, 11.7535, 11.7535, 11.7535, 11.7535] +24-11-19 20:33:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:23 | D | sum error = [ 849.6935, 916.4989, 988.9849, 1068.6652, 1155.9267] +24-11-19 20:33:23 | D | best error = [ 11.7535, 11.7535, 11.7535, 11.7535, 11.7535] +24-11-19 20:33:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:23 | D | sum error = [ 1251.7667, 1356.7727, 1472.6323, 1600.7116, 1741.5914] +24-11-19 20:33:23 | D | best error = [ 11.7535, 11.7535, 11.7535, 11.7535, 11.7535] +24-11-19 20:33:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:23 | D | sum error = [ 1897.0282, 2069.0677, 2258.3481, 2467.7776, 2698.6674] +24-11-19 20:33:23 | D | best error = [ 11.7535, 11.7535, 11.7535, 11.7535, 11.7535] +24-11-19 20:33:23 | D | + error = [11.7535] +24-11-19 20:33:24 | D | - Calibrating model.layers.20.self_attn.k_proj.weight +24-11-19 20:33:24 | D | + w: sint8 +24-11-19 20:33:24 | D | + x: None +24-11-19 20:33:24 | D | + y: None +24-11-19 20:33:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:33:24 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:33:24 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:33:24 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:33:24 | D | - range ratio = [ 1.0000] +24-11-19 20:33:24 | D | sum error = [ 13.5100] +24-11-19 20:33:24 | D | best error = [ 13.5100] +24-11-19 20:33:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:37 | D | sum error = [ 13.6388, 13.4743, 14.0808, 12.4049, 14.5242] +24-11-19 20:33:37 | D | best error = [ 13.5100, 13.4743, 13.4743, 12.4049, 12.4049] +24-11-19 20:33:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:37 | D | sum error = [ 14.0696, 14.2687, 15.0477, 16.0722, 16.5904] +24-11-19 20:33:37 | D | best error = [ 12.4049, 12.4049, 12.4049, 12.4049, 12.4049] +24-11-19 20:33:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:37 | D | sum error = [ 17.4752, 18.2098, 19.9701, 20.9895, 23.6076] +24-11-19 20:33:37 | D | best error = [ 12.4049, 12.4049, 12.4049, 12.4049, 12.4049] +24-11-19 20:33:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:37 | D | sum error = [ 23.9142, 27.2382, 29.0418, 31.0118, 33.6902] +24-11-19 20:33:37 | D | best error = [ 12.4049, 12.4049, 12.4049, 12.4049, 12.4049] +24-11-19 20:33:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:37 | D | sum error = [ 35.8296, 39.9149, 42.0127, 45.8607, 49.8759] +24-11-19 20:33:37 | D | best error = [ 12.4049, 12.4049, 12.4049, 12.4049, 12.4049] +24-11-19 20:33:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:37 | D | sum error = [ 53.5800, 58.7731, 63.6154, 68.0603, 74.5052] +24-11-19 20:33:37 | D | best error = [ 12.4049, 12.4049, 12.4049, 12.4049, 12.4049] +24-11-19 20:33:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:37 | D | sum error = [ 79.0257, 85.6115, 92.2650, 100.3617, 109.4574] +24-11-19 20:33:37 | D | best error = [ 12.4049, 12.4049, 12.4049, 12.4049, 12.4049] +24-11-19 20:33:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:37 | D | sum error = [ 118.0984, 127.4402, 136.2396, 147.9341, 160.2241] +24-11-19 20:33:37 | D | best error = [ 12.4049, 12.4049, 12.4049, 12.4049, 12.4049] +24-11-19 20:33:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:37 | D | sum error = [ 173.0197, 186.5974, 200.1803, 214.7584, 229.7047] +24-11-19 20:33:37 | D | best error = [ 12.4049, 12.4049, 12.4049, 12.4049, 12.4049] +24-11-19 20:33:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:37 | D | sum error = [ 246.3684, 263.4344, 282.2786, 303.3032, 325.2447] +24-11-19 20:33:37 | D | best error = [ 12.4049, 12.4049, 12.4049, 12.4049, 12.4049] +24-11-19 20:33:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:37 | D | sum error = [ 348.4615, 374.8763, 401.8435, 432.0206, 463.7684] +24-11-19 20:33:37 | D | best error = [ 12.4049, 12.4049, 12.4049, 12.4049, 12.4049] +24-11-19 20:33:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:37 | D | sum error = [ 498.0871, 534.0006, 572.1778, 613.3184, 657.4057] +24-11-19 20:33:37 | D | best error = [ 12.4049, 12.4049, 12.4049, 12.4049, 12.4049] +24-11-19 20:33:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:37 | D | sum error = [ 705.9674, 759.3836, 819.1022, 882.5383, 952.5269] +24-11-19 20:33:37 | D | best error = [ 12.4049, 12.4049, 12.4049, 12.4049, 12.4049] +24-11-19 20:33:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:37 | D | sum error = [ 1027.1605, 1109.2339, 1196.3816, 1295.3194, 1405.0380] +24-11-19 20:33:37 | D | best error = [ 12.4049, 12.4049, 12.4049, 12.4049, 12.4049] +24-11-19 20:33:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:37 | D | sum error = [ 1523.5647, 1653.1489, 1794.4536, 1951.3739, 2122.2937] +24-11-19 20:33:37 | D | best error = [ 12.4049, 12.4049, 12.4049, 12.4049, 12.4049] +24-11-19 20:33:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:37 | D | sum error = [ 2308.5957, 2510.9357, 2733.8658, 2976.3179, 3232.2211] +24-11-19 20:33:37 | D | best error = [ 12.4049, 12.4049, 12.4049, 12.4049, 12.4049] +24-11-19 20:33:37 | D | + error = [12.4049] +24-11-19 20:33:37 | D | - Calibrating model.layers.20.self_attn.v_proj.weight +24-11-19 20:33:37 | D | + w: sint8 +24-11-19 20:33:37 | D | + x: None +24-11-19 20:33:37 | D | + y: None +24-11-19 20:33:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:37 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:33:37 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:33:37 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:33:37 | D | - range ratio = [ 1.0000] +24-11-19 20:33:37 | D | sum error = [ 6.2684] +24-11-19 20:33:37 | D | best error = [ 6.2684] +24-11-19 20:33:38 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:38 | D | sum error = [ 6.2184, 6.1894, 6.2650, 6.2987, 6.4249] +24-11-19 20:33:38 | D | best error = [ 5.8547, 5.6913, 5.6085, 5.5548, 5.5272] +24-11-19 20:33:38 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:38 | D | sum error = [ 6.5900, 6.7914, 7.0917, 7.4224, 7.7914] +24-11-19 20:33:38 | D | best error = [ 5.5144, 5.5088, 5.5070, 5.5063, 5.5060] +24-11-19 20:33:38 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:38 | D | sum error = [ 8.2302, 8.7554, 9.3383, 9.9468, 10.6288] +24-11-19 20:33:38 | D | best error = [ 5.5059, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 20:33:38 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:38 | D | sum error = [ 11.3716, 12.1929, 13.0445, 13.9738, 14.9413] +24-11-19 20:33:38 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 20:33:38 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:38 | D | sum error = [ 16.0622, 17.1488, 18.3729, 19.6298, 20.9818] +24-11-19 20:33:38 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 20:33:38 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:38 | D | sum error = [ 22.4530, 23.9498, 25.5790, 27.2779, 29.0743] +24-11-19 20:33:38 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 20:33:38 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:38 | D | sum error = [ 30.9799, 32.9659, 35.1012, 37.3396, 39.6674] +24-11-19 20:33:38 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 20:33:38 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:38 | D | sum error = [ 42.1293, 44.7226, 47.4432, 50.3076, 53.3087] +24-11-19 20:33:38 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 20:33:38 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:38 | D | sum error = [ 56.4382, 59.7399, 63.1946, 66.7975, 70.5889] +24-11-19 20:33:38 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 20:33:38 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:38 | D | sum error = [ 74.5435, 78.6967, 83.0209, 87.5472, 92.2677] +24-11-19 20:33:38 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 20:33:38 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:38 | D | sum error = [ 97.2040, 102.3675, 107.7532, 113.3446, 119.1765] +24-11-19 20:33:38 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 20:33:38 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:38 | D | sum error = [ 125.2444, 131.5574, 138.1334, 144.9617, 152.0462] +24-11-19 20:33:38 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 20:33:38 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:38 | D | sum error = [ 159.4228, 167.0627, 175.0069, 183.2256, 191.7368] +24-11-19 20:33:38 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 20:33:38 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:38 | D | sum error = [ 200.5666, 209.6957, 219.1354, 228.8941, 238.9694] +24-11-19 20:33:38 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 20:33:38 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:38 | D | sum error = [ 249.3727, 260.1035, 271.1810, 282.6117, 294.4017] +24-11-19 20:33:38 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 20:33:38 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:38 | D | sum error = [ 306.5356, 319.0706, 331.9557, 345.2145, 358.8657] +24-11-19 20:33:38 | D | best error = [ 5.5058, 5.5058, 5.5058, 5.5058, 5.5058] +24-11-19 20:33:38 | D | + error = [5.5058] +24-11-19 20:33:38 | D | - Calibrating model.layers.20.self_attn.o_proj.weight +24-11-19 20:33:38 | D | + w: sint8 +24-11-19 20:33:38 | D | + x: None +24-11-19 20:33:38 | D | + y: None +24-11-19 20:33:38 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:38 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:33:38 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:33:38 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:33:38 | D | - range ratio = [ 1.0000] +24-11-19 20:33:38 | D | sum error = [ 1.6048] +24-11-19 20:33:38 | D | best error = [ 1.6048] +24-11-19 20:33:38 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:38 | D | sum error = [ 1.5926, 1.5806, 1.5858, 1.6035, 1.6210] +24-11-19 20:33:38 | D | best error = [ 1.4783, 1.4200, 1.3869, 1.3672, 1.3520] +24-11-19 20:33:38 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:38 | D | sum error = [ 1.6512, 1.6911, 1.7531, 1.8247, 1.9039] +24-11-19 20:33:38 | D | best error = [ 1.3414, 1.3342, 1.3288, 1.3256, 1.3229] +24-11-19 20:33:38 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:38 | D | sum error = [ 2.0027, 2.1191, 2.2476, 2.3784, 2.5336] +24-11-19 20:33:38 | D | best error = [ 1.3207, 1.3194, 1.3188, 1.3181, 1.3175] +24-11-19 20:33:38 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:38 | D | sum error = [ 2.7062, 2.8771, 3.0774, 3.2925, 3.5152] +24-11-19 20:33:38 | D | best error = [ 1.3173, 1.3170, 1.3167, 1.3166, 1.3165] +24-11-19 20:33:38 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:38 | D | sum error = [ 3.7617, 4.0189, 4.2989, 4.5888, 4.9026] +24-11-19 20:33:38 | D | best error = [ 1.3165, 1.3164, 1.3163, 1.3162, 1.3162] +24-11-19 20:33:38 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:38 | D | sum error = [ 5.2414, 5.5911, 5.9710, 6.3672, 6.7924] +24-11-19 20:33:38 | D | best error = [ 1.3162, 1.3162, 1.3162, 1.3162, 1.3162] +24-11-19 20:33:38 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:38 | D | sum error = [ 7.2345, 7.7008, 8.1992, 8.7280, 9.2768] +24-11-19 20:33:38 | D | best error = [ 1.3162, 1.3162, 1.3162, 1.3162, 1.3162] +24-11-19 20:33:38 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:38 | D | sum error = [ 9.8625, 10.4838, 11.1298, 11.8106, 12.5255] +24-11-19 20:33:38 | D | best error = [ 1.3162, 1.3162, 1.3162, 1.3162, 1.3162] +24-11-19 20:33:38 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:38 | D | sum error = [ 13.2876, 14.0778, 14.9121, 15.7921, 16.7140] +24-11-19 20:33:38 | D | best error = [ 1.3162, 1.3162, 1.3162, 1.3162, 1.3162] +24-11-19 20:33:38 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:38 | D | sum error = [ 17.6804, 18.6900, 19.7533, 20.8743, 22.0459] +24-11-19 20:33:38 | D | best error = [ 1.3162, 1.3162, 1.3162, 1.3162, 1.3162] +24-11-19 20:33:38 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:38 | D | sum error = [ 23.2743, 24.5703, 25.9197, 27.3421, 28.8260] +24-11-19 20:33:38 | D | best error = [ 1.3162, 1.3162, 1.3162, 1.3162, 1.3162] +24-11-19 20:33:38 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:38 | D | sum error = [ 30.3806, 32.0108, 33.7130, 35.4939, 37.3480] +24-11-19 20:33:38 | D | best error = [ 1.3162, 1.3162, 1.3162, 1.3162, 1.3162] +24-11-19 20:33:38 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:38 | D | sum error = [ 39.2914, 41.3178, 43.4330, 45.6442, 47.9454] +24-11-19 20:33:38 | D | best error = [ 1.3162, 1.3162, 1.3162, 1.3162, 1.3162] +24-11-19 20:33:38 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:38 | D | sum error = [ 50.3393, 52.8262, 55.4069, 58.0940, 60.8793] +24-11-19 20:33:38 | D | best error = [ 1.3162, 1.3162, 1.3162, 1.3162, 1.3162] +24-11-19 20:33:38 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:38 | D | sum error = [ 63.7686, 66.7681, 69.8791, 73.1021, 76.4407] +24-11-19 20:33:38 | D | best error = [ 1.3162, 1.3162, 1.3162, 1.3162, 1.3162] +24-11-19 20:33:38 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:38 | D | sum error = [ 79.8947, 83.4649, 87.1556, 90.9611, 94.8952] +24-11-19 20:33:38 | D | best error = [ 1.3162, 1.3162, 1.3162, 1.3162, 1.3162] +24-11-19 20:33:38 | D | + error = [1.3162] +24-11-19 20:33:38 | D | - Calibrating model.layers.20.mlp.up_proj.weight +24-11-19 20:33:38 | D | + w: sint8 +24-11-19 20:33:38 | D | + x: None +24-11-19 20:33:38 | D | + y: None +24-11-19 20:33:38 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:38 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:33:39 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:33:39 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:33:39 | D | - range ratio = [ 1.0000] +24-11-19 20:33:39 | D | sum error = [ 8.8652] +24-11-19 20:33:39 | D | best error = [ 8.8652] +24-11-19 20:33:40 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:40 | D | sum error = [ 8.7908, 8.7811, 8.7994, 8.8912, 9.0735] +24-11-19 20:33:40 | D | best error = [ 8.2411, 8.0057, 7.8698, 7.7957, 7.7558] +24-11-19 20:33:40 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:40 | D | sum error = [ 9.3097, 9.6131, 9.9978, 10.4631, 11.0298] +24-11-19 20:33:40 | D | best error = [ 7.7356, 7.7269, 7.7236, 7.7223, 7.7221] +24-11-19 20:33:40 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:40 | D | sum error = [ 11.6514, 12.3827, 13.1597, 14.0527, 15.0231] +24-11-19 20:33:40 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:33:40 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:40 | D | sum error = [ 16.0745, 17.2033, 18.4510, 19.7852, 21.1863] +24-11-19 20:33:40 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:33:40 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:40 | D | sum error = [ 22.7063, 24.3036, 26.0144, 27.8597, 29.7862] +24-11-19 20:33:40 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:33:40 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:40 | D | sum error = [ 31.8366, 34.0227, 36.3281, 38.7614, 41.3223] +24-11-19 20:33:40 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:33:40 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:40 | D | sum error = [ 44.0567, 46.9201, 49.9453, 53.1461, 56.5015] +24-11-19 20:33:40 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:33:40 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:40 | D | sum error = [ 60.0357, 63.7925, 67.7204, 71.8454, 76.2302] +24-11-19 20:33:40 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:33:40 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:40 | D | sum error = [ 80.7661, 85.5907, 90.6184, 95.8912, 101.4194] +24-11-19 20:33:40 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:33:40 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:40 | D | sum error = [ 107.2223, 113.2945, 119.6499, 126.3208, 133.2851] +24-11-19 20:33:40 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:33:40 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:40 | D | sum error = [ 140.5749, 148.1899, 156.1293, 164.4446, 173.1075] +24-11-19 20:33:40 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:33:40 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:40 | D | sum error = [ 182.1467, 191.5567, 201.3937, 211.6279, 222.2925] +24-11-19 20:33:40 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:33:40 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:40 | D | sum error = [ 233.3484, 244.8610, 256.8226, 269.2518, 282.1513] +24-11-19 20:33:40 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:33:40 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:40 | D | sum error = [ 295.5089, 309.3656, 323.7315, 338.6110, 353.9896] +24-11-19 20:33:40 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:33:40 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:40 | D | sum error = [ 369.9065, 386.3702, 403.3696, 420.9419, 439.0775] +24-11-19 20:33:40 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:33:40 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:40 | D | sum error = [ 457.7670, 477.0342, 496.8800, 517.3182, 538.3213] +24-11-19 20:33:40 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:33:40 | D | + error = [7.7219] +24-11-19 20:33:40 | D | - Calibrating model.layers.20.mlp.gate_proj.weight +24-11-19 20:33:40 | D | + w: sint8 +24-11-19 20:33:40 | D | + x: None +24-11-19 20:33:40 | D | + y: None +24-11-19 20:33:40 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:40 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:33:40 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:33:40 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:33:40 | D | - range ratio = [ 1.0000] +24-11-19 20:33:40 | D | sum error = [ 9.4608] +24-11-19 20:33:40 | D | best error = [ 9.4608] +24-11-19 20:33:41 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:41 | D | sum error = [ 9.3632, 9.3593, 9.3920, 9.5032, 9.6869] +24-11-19 20:33:41 | D | best error = [ 8.7996, 8.5406, 8.3998, 8.3217, 8.2798] +24-11-19 20:33:41 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:41 | D | sum error = [ 9.9493, 10.2755, 10.6808, 11.2231, 11.8115] +24-11-19 20:33:41 | D | best error = [ 8.2573, 8.2478, 8.2441, 8.2433, 8.2431] +24-11-19 20:33:41 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:41 | D | sum error = [ 12.4920, 13.2899, 14.1574, 15.0827, 16.1448] +24-11-19 20:33:41 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 20:33:41 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:41 | D | sum error = [ 17.2953, 18.5223, 19.8822, 21.3322, 22.8647] +24-11-19 20:33:41 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 20:33:41 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:41 | D | sum error = [ 24.5386, 26.3138, 28.1777, 30.2015, 32.3299] +24-11-19 20:33:41 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 20:33:41 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:41 | D | sum error = [ 34.5727, 36.9750, 39.5277, 42.2338, 45.0653] +24-11-19 20:33:41 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 20:33:41 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:41 | D | sum error = [ 48.1019, 51.2754, 54.6579, 58.2593, 62.0039] +24-11-19 20:33:41 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 20:33:41 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:41 | D | sum error = [ 66.0279, 70.2287, 74.6919, 79.4057, 84.3932] +24-11-19 20:33:41 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 20:33:41 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:41 | D | sum error = [ 89.6649, 95.2224, 101.0852, 107.2616, 113.7670] +24-11-19 20:33:41 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 20:33:41 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:41 | D | sum error = [ 120.6069, 127.8135, 135.3857, 143.3568, 151.7418] +24-11-19 20:33:41 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 20:33:41 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:41 | D | sum error = [ 160.5819, 169.8465, 179.5972, 189.8461, 200.6101] +24-11-19 20:33:41 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 20:33:41 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:41 | D | sum error = [ 211.8566, 223.6740, 236.0653, 249.0030, 262.5654] +24-11-19 20:33:41 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 20:33:41 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:41 | D | sum error = [ 276.7378, 291.5807, 307.0664, 323.2564, 340.1275] +24-11-19 20:33:41 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 20:33:41 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:41 | D | sum error = [ 357.7378, 376.1207, 395.2591, 415.1439, 435.8718] +24-11-19 20:33:41 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 20:33:41 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:41 | D | sum error = [ 457.3809, 479.6842, 502.8022, 526.7731, 551.6063] +24-11-19 20:33:41 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 20:33:41 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:41 | D | sum error = [ 577.2852, 603.8299, 631.2157, 659.4646, 688.5775] +24-11-19 20:33:41 | D | best error = [ 8.2430, 8.2430, 8.2430, 8.2430, 8.2430] +24-11-19 20:33:41 | D | + error = [8.2430] +24-11-19 20:33:41 | D | - Calibrating model.layers.20.mlp.down_proj.weight +24-11-19 20:33:41 | D | + w: sint8 +24-11-19 20:33:41 | D | + x: None +24-11-19 20:33:41 | D | + y: None +24-11-19 20:33:41 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:41 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:33:41 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:33:41 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:33:41 | D | - range ratio = [ 1.0000] +24-11-19 20:33:41 | D | sum error = [ 3.4711] +24-11-19 20:33:41 | D | best error = [ 3.4711] +24-11-19 20:33:42 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:42 | D | sum error = [ 3.4366, 3.4106, 3.3994, 3.3892, 3.3956] +24-11-19 20:33:42 | D | best error = [ 3.3105, 3.2335, 3.1800, 3.1415, 3.1137] +24-11-19 20:33:42 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:42 | D | sum error = [ 3.4134, 3.4468, 3.4996, 3.5598, 3.6440] +24-11-19 20:33:42 | D | best error = [ 3.0928, 3.0766, 3.0651, 3.0556, 3.0490] +24-11-19 20:33:42 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:42 | D | sum error = [ 3.7660, 3.8948, 4.0478, 4.2461, 4.4465] +24-11-19 20:33:42 | D | best error = [ 3.0447, 3.0411, 3.0393, 3.0381, 3.0374] +24-11-19 20:33:42 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:42 | D | sum error = [ 4.6807, 4.9449, 5.2507, 5.5608, 5.9165] +24-11-19 20:33:42 | D | best error = [ 3.0368, 3.0363, 3.0361, 3.0360, 3.0359] +24-11-19 20:33:42 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:42 | D | sum error = [ 6.3006, 6.7242, 7.1722, 7.6594, 8.1867] +24-11-19 20:33:42 | D | best error = [ 3.0359, 3.0359, 3.0359, 3.0359, 3.0359] +24-11-19 20:33:42 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:42 | D | sum error = [ 8.7454, 9.3428, 9.9804, 10.6713, 11.4034] +24-11-19 20:33:42 | D | best error = [ 3.0359, 3.0359, 3.0359, 3.0359, 3.0359] +24-11-19 20:33:42 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:42 | D | sum error = [ 12.1886, 13.0141, 13.8940, 14.8301, 15.8192] +24-11-19 20:33:42 | D | best error = [ 3.0359, 3.0359, 3.0359, 3.0359, 3.0359] +24-11-19 20:33:42 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:42 | D | sum error = [ 16.8840, 17.9872, 19.1786, 20.4167, 21.7399] +24-11-19 20:33:42 | D | best error = [ 3.0359, 3.0359, 3.0359, 3.0359, 3.0359] +24-11-19 20:33:42 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:42 | D | sum error = [ 23.1411, 24.6173, 26.1694, 27.8129, 29.5464] +24-11-19 20:33:42 | D | best error = [ 3.0359, 3.0359, 3.0359, 3.0359, 3.0359] +24-11-19 20:33:42 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:42 | D | sum error = [ 31.3730, 33.2928, 35.3176, 37.4513, 39.6859] +24-11-19 20:33:42 | D | best error = [ 3.0359, 3.0359, 3.0359, 3.0359, 3.0359] +24-11-19 20:33:42 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:42 | D | sum error = [ 42.0408, 44.5115, 47.1036, 49.8316, 52.6808] +24-11-19 20:33:42 | D | best error = [ 3.0359, 3.0359, 3.0359, 3.0359, 3.0359] +24-11-19 20:33:42 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:42 | D | sum error = [ 55.6738, 58.8089, 62.0850, 65.5185, 69.1150] +24-11-19 20:33:42 | D | best error = [ 3.0359, 3.0359, 3.0359, 3.0359, 3.0359] +24-11-19 20:33:42 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:42 | D | sum error = [ 72.8677, 76.7954, 80.8817, 85.1472, 89.5971] +24-11-19 20:33:42 | D | best error = [ 3.0359, 3.0359, 3.0359, 3.0359, 3.0359] +24-11-19 20:33:42 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:42 | D | sum error = [ 94.2242, 99.0466, 104.0605, 109.2801, 114.6953] +24-11-19 20:33:42 | D | best error = [ 3.0359, 3.0359, 3.0359, 3.0359, 3.0359] +24-11-19 20:33:42 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:42 | D | sum error = [ 120.3353, 126.1814, 132.2523, 138.5448, 145.0583] +24-11-19 20:33:42 | D | best error = [ 3.0359, 3.0359, 3.0359, 3.0359, 3.0359] +24-11-19 20:33:42 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:42 | D | sum error = [ 151.7970, 158.7685, 165.9756, 173.4220, 181.1059] +24-11-19 20:33:42 | D | best error = [ 3.0359, 3.0359, 3.0359, 3.0359, 3.0359] +24-11-19 20:33:42 | D | + error = [3.0359] +24-11-19 20:33:43 | D | - Quantizing model.layers.20.self_attn.q_proj.weight +24-11-19 20:33:43 | D | - Quantizing model.layers.20.self_attn.k_proj.weight +24-11-19 20:33:44 | D | - Quantizing model.layers.20.self_attn.v_proj.weight +24-11-19 20:33:45 | D | - Quantizing model.layers.20.self_attn.o_proj.weight +24-11-19 20:33:46 | D | - Quantizing model.layers.20.mlp.up_proj.weight +24-11-19 20:33:47 | D | - Quantizing model.layers.20.mlp.gate_proj.weight +24-11-19 20:33:48 | D | - Quantizing model.layers.20.mlp.down_proj.weight +24-11-19 20:33:57 | D | - Quantizing layer model.layers.21 +24-11-19 20:33:57 | D | - Calibrating model.layers.21.self_attn.q_proj.weight +24-11-19 20:33:57 | D | + w: sint8 +24-11-19 20:33:57 | D | + x: None +24-11-19 20:33:57 | D | + y: None +24-11-19 20:33:57 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:33:57 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:33:57 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:33:57 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:33:57 | D | - range ratio = [ 1.0000] +24-11-19 20:33:57 | D | sum error = [ 12.0076] +24-11-19 20:33:57 | D | best error = [ 12.0076] +24-11-19 20:34:10 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:10 | D | sum error = [ 11.8694, 11.7605, 11.8092, 11.9552, 12.2033] +24-11-19 20:34:10 | D | best error = [ 11.8694, 11.7605, 11.7605, 11.7605, 11.7605] +24-11-19 20:34:10 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:10 | D | sum error = [ 12.5282, 13.0427, 13.5959, 14.2528, 15.0334] +24-11-19 20:34:10 | D | best error = [ 11.7605, 11.7605, 11.7605, 11.7605, 11.7605] +24-11-19 20:34:10 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:10 | D | sum error = [ 15.9806, 17.0563, 18.1663, 19.4974, 20.8140] +24-11-19 20:34:10 | D | best error = [ 11.7605, 11.7605, 11.7605, 11.7605, 11.7605] +24-11-19 20:34:10 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:10 | D | sum error = [ 22.7552, 24.3189, 26.1197, 28.0628, 30.3619] +24-11-19 20:34:10 | D | best error = [ 11.7605, 11.7605, 11.7605, 11.7605, 11.7605] +24-11-19 20:34:10 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:10 | D | sum error = [ 32.6829, 35.3840, 38.1394, 41.1939, 44.0403] +24-11-19 20:34:10 | D | best error = [ 11.7605, 11.7605, 11.7605, 11.7605, 11.7605] +24-11-19 20:34:10 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:10 | D | sum error = [ 47.4313, 51.1084, 55.2352, 59.4012, 63.9000] +24-11-19 20:34:10 | D | best error = [ 11.7605, 11.7605, 11.7605, 11.7605, 11.7605] +24-11-19 20:34:10 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:10 | D | sum error = [ 68.7660, 73.8983, 79.3264, 85.5972, 92.3924] +24-11-19 20:34:10 | D | best error = [ 11.7605, 11.7605, 11.7605, 11.7605, 11.7605] +24-11-19 20:34:10 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:10 | D | sum error = [ 99.1136, 106.8317, 114.6947, 123.6962, 132.6762] +24-11-19 20:34:10 | D | best error = [ 11.7605, 11.7605, 11.7605, 11.7605, 11.7605] +24-11-19 20:34:10 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:10 | D | sum error = [ 143.0158, 153.9652, 165.4963, 178.3566, 191.7901] +24-11-19 20:34:10 | D | best error = [ 11.7605, 11.7605, 11.7605, 11.7605, 11.7605] +24-11-19 20:34:10 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:10 | D | sum error = [ 206.7296, 222.3625, 239.9819, 258.6524, 278.9016] +24-11-19 20:34:10 | D | best error = [ 11.7605, 11.7605, 11.7605, 11.7605, 11.7605] +24-11-19 20:34:10 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:10 | D | sum error = [ 301.2258, 324.3300, 350.1227, 377.2628, 407.4238] +24-11-19 20:34:10 | D | best error = [ 11.7605, 11.7605, 11.7605, 11.7605, 11.7605] +24-11-19 20:34:10 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:10 | D | sum error = [ 438.6757, 473.7730, 511.3024, 553.1008, 597.7327] +24-11-19 20:34:10 | D | best error = [ 11.7605, 11.7605, 11.7605, 11.7605, 11.7605] +24-11-19 20:34:10 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:10 | D | sum error = [ 647.2800, 701.2629, 759.9378, 824.4671, 893.8724] +24-11-19 20:34:10 | D | best error = [ 11.7605, 11.7605, 11.7605, 11.7605, 11.7605] +24-11-19 20:34:10 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:10 | D | sum error = [ 971.4197, 1055.3494, 1147.7538, 1250.1527, 1361.6555] +24-11-19 20:34:10 | D | best error = [ 11.7605, 11.7605, 11.7605, 11.7605, 11.7605] +24-11-19 20:34:10 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:10 | D | sum error = [ 1485.8121, 1622.0233, 1772.3712, 1938.7515, 2122.0165] +24-11-19 20:34:10 | D | best error = [ 11.7605, 11.7605, 11.7605, 11.7605, 11.7605] +24-11-19 20:34:10 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:10 | D | sum error = [ 2322.7520, 2543.5111, 2782.5686, 3043.0470, 3322.7173] +24-11-19 20:34:10 | D | best error = [ 11.7605, 11.7605, 11.7605, 11.7605, 11.7605] +24-11-19 20:34:10 | D | + error = [11.7605] +24-11-19 20:34:10 | D | - Calibrating model.layers.21.self_attn.k_proj.weight +24-11-19 20:34:10 | D | + w: sint8 +24-11-19 20:34:10 | D | + x: None +24-11-19 20:34:10 | D | + y: None +24-11-19 20:34:10 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:34:10 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:34:10 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:34:11 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:34:11 | D | - range ratio = [ 1.0000] +24-11-19 20:34:11 | D | sum error = [ 13.8685] +24-11-19 20:34:11 | D | best error = [ 13.8685] +24-11-19 20:34:24 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:24 | D | sum error = [ 13.9606, 13.1606, 13.8612, 14.1760, 14.1218] +24-11-19 20:34:24 | D | best error = [ 13.8685, 13.1606, 13.1606, 13.1606, 13.1606] +24-11-19 20:34:24 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:24 | D | sum error = [ 15.6242, 14.9765, 15.6818, 16.4445, 16.9863] +24-11-19 20:34:24 | D | best error = [ 13.1606, 13.1606, 13.1606, 13.1606, 13.1606] +24-11-19 20:34:24 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:24 | D | sum error = [ 18.6135, 19.8605, 21.0561, 23.1818, 24.4490] +24-11-19 20:34:24 | D | best error = [ 13.1606, 13.1606, 13.1606, 13.1606, 13.1606] +24-11-19 20:34:24 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:24 | D | sum error = [ 26.3998, 28.6650, 29.8501, 33.9452, 35.9393] +24-11-19 20:34:24 | D | best error = [ 13.1606, 13.1606, 13.1606, 13.1606, 13.1606] +24-11-19 20:34:24 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:24 | D | sum error = [ 37.3355, 40.8856, 45.6663, 48.0309, 52.3772] +24-11-19 20:34:24 | D | best error = [ 13.1606, 13.1606, 13.1606, 13.1606, 13.1606] +24-11-19 20:34:24 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:24 | D | sum error = [ 55.9116, 59.8576, 65.3541, 68.7738, 73.4762] +24-11-19 20:34:24 | D | best error = [ 13.1606, 13.1606, 13.1606, 13.1606, 13.1606] +24-11-19 20:34:24 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:24 | D | sum error = [ 79.6741, 86.2568, 92.1992, 98.8519, 106.6077] +24-11-19 20:34:24 | D | best error = [ 13.1606, 13.1606, 13.1606, 13.1606, 13.1606] +24-11-19 20:34:24 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:24 | D | sum error = [ 113.6336, 122.3220, 131.5176, 141.7806, 151.6629] +24-11-19 20:34:24 | D | best error = [ 13.1606, 13.1606, 13.1606, 13.1606, 13.1606] +24-11-19 20:34:24 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:24 | D | sum error = [ 162.0714, 175.7307, 188.4071, 200.3234, 215.7312] +24-11-19 20:34:24 | D | best error = [ 13.1606, 13.1606, 13.1606, 13.1606, 13.1606] +24-11-19 20:34:24 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:24 | D | sum error = [ 232.2787, 248.6613, 267.0125, 286.5713, 307.9995] +24-11-19 20:34:24 | D | best error = [ 13.1606, 13.1606, 13.1606, 13.1606, 13.1606] +24-11-19 20:34:24 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:24 | D | sum error = [ 331.8908, 355.0986, 382.0216, 409.8162, 441.4417] +24-11-19 20:34:24 | D | best error = [ 13.1606, 13.1606, 13.1606, 13.1606, 13.1606] +24-11-19 20:34:24 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:24 | D | sum error = [ 476.1375, 512.8209, 552.4908, 596.3825, 642.1285] +24-11-19 20:34:24 | D | best error = [ 13.1606, 13.1606, 13.1606, 13.1606, 13.1606] +24-11-19 20:34:24 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:24 | D | sum error = [ 693.3075, 749.7695, 810.4361, 875.0164, 948.0396] +24-11-19 20:34:24 | D | best error = [ 13.1606, 13.1606, 13.1606, 13.1606, 13.1606] +24-11-19 20:34:24 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:24 | D | sum error = [ 1027.3918, 1114.0370, 1208.7981, 1316.3439, 1431.3612] +24-11-19 20:34:24 | D | best error = [ 13.1606, 13.1606, 13.1606, 13.1606, 13.1606] +24-11-19 20:34:24 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:24 | D | sum error = [ 1555.3839, 1696.4410, 1850.5465, 2022.7077, 2210.1454] +24-11-19 20:34:24 | D | best error = [ 13.1606, 13.1606, 13.1606, 13.1606, 13.1606] +24-11-19 20:34:24 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:24 | D | sum error = [ 2416.5258, 2642.0327, 2888.0918, 3154.5412, 3437.5643] +24-11-19 20:34:24 | D | best error = [ 13.1606, 13.1606, 13.1606, 13.1606, 13.1606] +24-11-19 20:34:24 | D | + error = [13.1606] +24-11-19 20:34:24 | D | - Calibrating model.layers.21.self_attn.v_proj.weight +24-11-19 20:34:24 | D | + w: sint8 +24-11-19 20:34:24 | D | + x: None +24-11-19 20:34:24 | D | + y: None +24-11-19 20:34:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:24 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:34:24 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:34:24 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:34:24 | D | - range ratio = [ 1.0000] +24-11-19 20:34:24 | D | sum error = [ 6.8641] +24-11-19 20:34:24 | D | best error = [ 6.8641] +24-11-19 20:34:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:25 | D | sum error = [ 6.7998, 6.8018, 6.8284, 6.8791, 7.0114] +24-11-19 20:34:25 | D | best error = [ 6.4108, 6.2229, 6.1236, 6.0671, 6.0379] +24-11-19 20:34:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:25 | D | sum error = [ 7.1784, 7.4558, 7.7361, 8.0921, 8.5120] +24-11-19 20:34:25 | D | best error = [ 6.0212, 6.0134, 6.0105, 6.0093, 6.0092] +24-11-19 20:34:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:25 | D | sum error = [ 9.0162, 9.5806, 10.1961, 10.9042, 11.6104] +24-11-19 20:34:25 | D | best error = [ 6.0091, 6.0091, 6.0091, 6.0091, 6.0091] +24-11-19 20:34:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:25 | D | sum error = [ 12.4521, 13.3139, 14.2449, 15.2726, 16.3759] +24-11-19 20:34:25 | D | best error = [ 6.0091, 6.0091, 6.0091, 6.0091, 6.0091] +24-11-19 20:34:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:25 | D | sum error = [ 17.5314, 18.7746, 20.1113, 21.5346, 23.0038] +24-11-19 20:34:25 | D | best error = [ 6.0091, 6.0091, 6.0091, 6.0091, 6.0091] +24-11-19 20:34:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:25 | D | sum error = [ 24.5830, 26.2310, 27.9943, 29.8756, 31.8155] +24-11-19 20:34:25 | D | best error = [ 6.0091, 6.0091, 6.0091, 6.0091, 6.0091] +24-11-19 20:34:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:25 | D | sum error = [ 33.8866, 36.0869, 38.3477, 40.7739, 43.3330] +24-11-19 20:34:25 | D | best error = [ 6.0091, 6.0091, 6.0091, 6.0091, 6.0091] +24-11-19 20:34:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:25 | D | sum error = [ 45.9979, 48.8277, 51.7795, 54.8834, 58.1194] +24-11-19 20:34:25 | D | best error = [ 6.0091, 6.0091, 6.0091, 6.0091, 6.0091] +24-11-19 20:34:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:25 | D | sum error = [ 61.5667, 65.1573, 68.9271, 72.8473, 76.9740] +24-11-19 20:34:25 | D | best error = [ 6.0091, 6.0091, 6.0091, 6.0091, 6.0091] +24-11-19 20:34:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:25 | D | sum error = [ 81.2855, 85.7945, 90.5045, 95.4154, 100.5745] +24-11-19 20:34:25 | D | best error = [ 6.0091, 6.0091, 6.0091, 6.0091, 6.0091] +24-11-19 20:34:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:25 | D | sum error = [ 105.9158, 111.5174, 117.3639, 123.4390, 129.7787] +24-11-19 20:34:25 | D | best error = [ 6.0091, 6.0091, 6.0091, 6.0091, 6.0091] +24-11-19 20:34:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:25 | D | sum error = [ 136.3735, 143.2211, 150.3606, 157.7693, 165.4505] +24-11-19 20:34:25 | D | best error = [ 6.0091, 6.0091, 6.0091, 6.0091, 6.0091] +24-11-19 20:34:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:25 | D | sum error = [ 173.4312, 181.7036, 190.2696, 199.1545, 208.3559] +24-11-19 20:34:25 | D | best error = [ 6.0091, 6.0091, 6.0091, 6.0091, 6.0091] +24-11-19 20:34:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:25 | D | sum error = [ 217.8720, 227.7346, 237.9243, 248.4659, 259.3356] +24-11-19 20:34:25 | D | best error = [ 6.0091, 6.0091, 6.0091, 6.0091, 6.0091] +24-11-19 20:34:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:25 | D | sum error = [ 270.5357, 282.0938, 294.0296, 306.3206, 318.9770] +24-11-19 20:34:25 | D | best error = [ 6.0091, 6.0091, 6.0091, 6.0091, 6.0091] +24-11-19 20:34:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:25 | D | sum error = [ 332.0042, 345.4057, 359.1903, 373.3683, 387.9345] +24-11-19 20:34:25 | D | best error = [ 6.0091, 6.0091, 6.0091, 6.0091, 6.0091] +24-11-19 20:34:25 | D | + error = [6.0091] +24-11-19 20:34:25 | D | - Calibrating model.layers.21.self_attn.o_proj.weight +24-11-19 20:34:25 | D | + w: sint8 +24-11-19 20:34:25 | D | + x: None +24-11-19 20:34:25 | D | + y: None +24-11-19 20:34:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:25 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:34:25 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:34:25 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:34:25 | D | - range ratio = [ 1.0000] +24-11-19 20:34:25 | D | sum error = [ 1.3077] +24-11-19 20:34:25 | D | best error = [ 1.3077] +24-11-19 20:34:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:25 | D | sum error = [ 1.2976, 1.2920, 1.2941, 1.2998, 1.3197] +24-11-19 20:34:25 | D | best error = [ 1.2231, 1.1853, 1.1624, 1.1470, 1.1378] +24-11-19 20:34:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:25 | D | sum error = [ 1.3549, 1.3892, 1.4382, 1.4958, 1.5668] +24-11-19 20:34:25 | D | best error = [ 1.1319, 1.1279, 1.1251, 1.1235, 1.1223] +24-11-19 20:34:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:25 | D | sum error = [ 1.6502, 1.7423, 1.8440, 1.9683, 2.0886] +24-11-19 20:34:25 | D | best error = [ 1.1215, 1.1211, 1.1209, 1.1207, 1.1206] +24-11-19 20:34:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:25 | D | sum error = [ 2.2325, 2.3762, 2.5518, 2.7314, 2.9161] +24-11-19 20:34:25 | D | best error = [ 1.1205, 1.1204, 1.1204, 1.1203, 1.1203] +24-11-19 20:34:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:25 | D | sum error = [ 3.1256, 3.3389, 3.5658, 3.8168, 4.0796] +24-11-19 20:34:25 | D | best error = [ 1.1203, 1.1203, 1.1203, 1.1203, 1.1203] +24-11-19 20:34:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:25 | D | sum error = [ 4.3559, 4.6543, 4.9698, 5.2995, 5.6494] +24-11-19 20:34:25 | D | best error = [ 1.1203, 1.1203, 1.1203, 1.1203, 1.1203] +24-11-19 20:34:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:25 | D | sum error = [ 6.0196, 6.4123, 6.8311, 7.2692, 7.7298] +24-11-19 20:34:25 | D | best error = [ 1.1203, 1.1203, 1.1203, 1.1203, 1.1203] +24-11-19 20:34:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:25 | D | sum error = [ 8.2138, 8.7276, 9.2704, 9.8404, 10.4435] +24-11-19 20:34:25 | D | best error = [ 1.1203, 1.1203, 1.1203, 1.1203, 1.1203] +24-11-19 20:34:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:25 | D | sum error = [ 11.0722, 11.7340, 12.4330, 13.1676, 13.9358] +24-11-19 20:34:25 | D | best error = [ 1.1203, 1.1203, 1.1203, 1.1203, 1.1203] +24-11-19 20:34:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:25 | D | sum error = [ 14.7437, 15.5917, 16.4780, 17.4160, 18.3941] +24-11-19 20:34:25 | D | best error = [ 1.1203, 1.1203, 1.1203, 1.1203, 1.1203] +24-11-19 20:34:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:25 | D | sum error = [ 19.4120, 20.4829, 21.6018, 22.7706, 23.9941] +24-11-19 20:34:25 | D | best error = [ 1.1203, 1.1203, 1.1203, 1.1203, 1.1203] +24-11-19 20:34:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:25 | D | sum error = [ 25.2710, 26.6043, 27.9963, 29.4483, 30.9621] +24-11-19 20:34:25 | D | best error = [ 1.1203, 1.1203, 1.1203, 1.1203, 1.1203] +24-11-19 20:34:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:25 | D | sum error = [ 32.5413, 34.1854, 35.9012, 37.6800, 39.5320] +24-11-19 20:34:25 | D | best error = [ 1.1203, 1.1203, 1.1203, 1.1203, 1.1203] +24-11-19 20:34:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:25 | D | sum error = [ 41.4564, 43.4576, 45.5338, 47.6914, 49.9214] +24-11-19 20:34:25 | D | best error = [ 1.1203, 1.1203, 1.1203, 1.1203, 1.1203] +24-11-19 20:34:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:25 | D | sum error = [ 52.2386, 54.6362, 57.1214, 59.6876, 62.3393] +24-11-19 20:34:25 | D | best error = [ 1.1203, 1.1203, 1.1203, 1.1203, 1.1203] +24-11-19 20:34:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:25 | D | sum error = [ 65.0792, 67.9083, 70.8308, 73.8432, 76.9493] +24-11-19 20:34:25 | D | best error = [ 1.1203, 1.1203, 1.1203, 1.1203, 1.1203] +24-11-19 20:34:25 | D | + error = [1.1203] +24-11-19 20:34:26 | D | - Calibrating model.layers.21.mlp.up_proj.weight +24-11-19 20:34:26 | D | + w: sint8 +24-11-19 20:34:26 | D | + x: None +24-11-19 20:34:26 | D | + y: None +24-11-19 20:34:26 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:26 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:34:26 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:34:26 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:34:26 | D | - range ratio = [ 1.0000] +24-11-19 20:34:26 | D | sum error = [ 9.1195] +24-11-19 20:34:26 | D | best error = [ 9.1195] +24-11-19 20:34:27 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:27 | D | sum error = [ 9.0836, 9.0516, 9.0975, 9.1814, 9.3563] +24-11-19 20:34:27 | D | best error = [ 8.5040, 8.2543, 8.1232, 8.0428, 7.9982] +24-11-19 20:34:27 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:27 | D | sum error = [ 9.6170, 9.9372, 10.3389, 10.8012, 11.3553] +24-11-19 20:34:27 | D | best error = [ 7.9771, 7.9678, 7.9638, 7.9623, 7.9621] +24-11-19 20:34:27 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:27 | D | sum error = [ 12.0437, 12.7856, 13.6291, 14.5402, 15.5513] +24-11-19 20:34:27 | D | best error = [ 7.9621, 7.9620, 7.9620, 7.9620, 7.9620] +24-11-19 20:34:27 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:27 | D | sum error = [ 16.6609, 17.8373, 19.1384, 20.4914, 21.9807] +24-11-19 20:34:27 | D | best error = [ 7.9620, 7.9620, 7.9620, 7.9620, 7.9620] +24-11-19 20:34:27 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:27 | D | sum error = [ 23.5637, 25.2181, 26.9869, 28.8988, 30.9347] +24-11-19 20:34:27 | D | best error = [ 7.9620, 7.9620, 7.9620, 7.9620, 7.9620] +24-11-19 20:34:27 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:27 | D | sum error = [ 33.0462, 35.2860, 37.6701, 40.1972, 42.8540] +24-11-19 20:34:27 | D | best error = [ 7.9620, 7.9620, 7.9620, 7.9620, 7.9620] +24-11-19 20:34:27 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:27 | D | sum error = [ 45.6567, 48.6105, 51.7281, 55.0169, 58.4977] +24-11-19 20:34:27 | D | best error = [ 7.9620, 7.9620, 7.9620, 7.9620, 7.9620] +24-11-19 20:34:27 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:27 | D | sum error = [ 62.1341, 65.9477, 69.9992, 74.2600, 78.7268] +24-11-19 20:34:27 | D | best error = [ 7.9620, 7.9620, 7.9620, 7.9620, 7.9620] +24-11-19 20:34:27 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:27 | D | sum error = [ 83.4108, 88.3312, 93.4762, 98.9134, 104.6085] +24-11-19 20:34:27 | D | best error = [ 7.9620, 7.9620, 7.9620, 7.9620, 7.9620] +24-11-19 20:34:27 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:27 | D | sum error = [ 110.5565, 116.8093, 123.3358, 130.1743, 137.3206] +24-11-19 20:34:27 | D | best error = [ 7.9620, 7.9620, 7.9620, 7.9620, 7.9620] +24-11-19 20:34:27 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:27 | D | sum error = [ 144.7676, 152.5847, 160.7211, 169.2187, 178.0566] +24-11-19 20:34:27 | D | best error = [ 7.9620, 7.9620, 7.9620, 7.9620, 7.9620] +24-11-19 20:34:27 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:27 | D | sum error = [ 187.3027, 196.9315, 206.9480, 217.3835, 228.2509] +24-11-19 20:34:27 | D | best error = [ 7.9620, 7.9620, 7.9620, 7.9620, 7.9620] +24-11-19 20:34:27 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:27 | D | sum error = [ 239.5390, 251.2720, 263.4633, 276.1193, 289.2520] +24-11-19 20:34:27 | D | best error = [ 7.9620, 7.9620, 7.9620, 7.9620, 7.9620] +24-11-19 20:34:27 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:27 | D | sum error = [ 302.8744, 316.9892, 331.6058, 346.7416, 362.3972] +24-11-19 20:34:27 | D | best error = [ 7.9620, 7.9620, 7.9620, 7.9620, 7.9620] +24-11-19 20:34:27 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:27 | D | sum error = [ 378.5928, 395.3343, 412.6014, 430.4175, 448.7778] +24-11-19 20:34:27 | D | best error = [ 7.9620, 7.9620, 7.9620, 7.9620, 7.9620] +24-11-19 20:34:27 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:27 | D | sum error = [ 467.7066, 487.1861, 507.2484, 527.8792, 549.1047] +24-11-19 20:34:27 | D | best error = [ 7.9620, 7.9620, 7.9620, 7.9620, 7.9620] +24-11-19 20:34:27 | D | + error = [7.9620] +24-11-19 20:34:27 | D | - Calibrating model.layers.21.mlp.gate_proj.weight +24-11-19 20:34:27 | D | + w: sint8 +24-11-19 20:34:27 | D | + x: None +24-11-19 20:34:27 | D | + y: None +24-11-19 20:34:27 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:27 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:34:27 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:34:27 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:34:27 | D | - range ratio = [ 1.0000] +24-11-19 20:34:27 | D | sum error = [ 9.8574] +24-11-19 20:34:27 | D | best error = [ 9.8574] +24-11-19 20:34:28 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:28 | D | sum error = [ 9.7582, 9.7539, 9.7944, 9.8987, 10.0859] +24-11-19 20:34:28 | D | best error = [ 9.1684, 8.9012, 8.7466, 8.6637, 8.6183] +24-11-19 20:34:28 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:28 | D | sum error = [ 10.3643, 10.7091, 11.1389, 11.6684, 12.2970] +24-11-19 20:34:28 | D | best error = [ 8.5954, 8.5853, 8.5815, 8.5800, 8.5794] +24-11-19 20:34:28 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:28 | D | sum error = [ 13.0141, 13.7865, 14.7242, 15.7217, 16.8084] +24-11-19 20:34:28 | D | best error = [ 8.5792, 8.5791, 8.5791, 8.5791, 8.5791] +24-11-19 20:34:28 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:28 | D | sum error = [ 18.0289, 19.3381, 20.7016, 22.2033, 23.7936] +24-11-19 20:34:28 | D | best error = [ 8.5791, 8.5791, 8.5791, 8.5791, 8.5791] +24-11-19 20:34:28 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:28 | D | sum error = [ 25.5310, 27.3885, 29.3228, 31.3946, 33.6075] +24-11-19 20:34:28 | D | best error = [ 8.5791, 8.5791, 8.5791, 8.5791, 8.5791] +24-11-19 20:34:28 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:28 | D | sum error = [ 35.9341, 38.4193, 41.0609, 43.8496, 46.8176] +24-11-19 20:34:28 | D | best error = [ 8.5791, 8.5791, 8.5791, 8.5791, 8.5791] +24-11-19 20:34:28 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:28 | D | sum error = [ 49.9493, 53.2131, 56.7297, 60.4158, 64.3276] +24-11-19 20:34:28 | D | best error = [ 8.5791, 8.5791, 8.5791, 8.5791, 8.5791] +24-11-19 20:34:28 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:28 | D | sum error = [ 68.4500, 72.7787, 77.3715, 82.2296, 87.3259] +24-11-19 20:34:28 | D | best error = [ 8.5791, 8.5791, 8.5791, 8.5791, 8.5791] +24-11-19 20:34:28 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:28 | D | sum error = [ 92.7396, 98.4141, 104.4262, 110.7296, 117.3709] +24-11-19 20:34:28 | D | best error = [ 8.5791, 8.5791, 8.5791, 8.5791, 8.5791] +24-11-19 20:34:28 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:28 | D | sum error = [ 124.3546, 131.7215, 139.4458, 147.5717, 156.1297] +24-11-19 20:34:28 | D | best error = [ 8.5791, 8.5791, 8.5791, 8.5791, 8.5791] +24-11-19 20:34:28 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:28 | D | sum error = [ 165.1132, 174.5645, 184.4537, 194.8509, 205.7486] +24-11-19 20:34:28 | D | best error = [ 8.5791, 8.5791, 8.5791, 8.5791, 8.5791] +24-11-19 20:34:28 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:28 | D | sum error = [ 217.1630, 229.1186, 241.6564, 254.7692, 268.5019] +24-11-19 20:34:28 | D | best error = [ 8.5791, 8.5791, 8.5791, 8.5791, 8.5791] +24-11-19 20:34:28 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:28 | D | sum error = [ 282.8421, 297.8339, 313.4916, 329.8100, 346.8054] +24-11-19 20:34:28 | D | best error = [ 8.5791, 8.5791, 8.5791, 8.5791, 8.5791] +24-11-19 20:34:28 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:28 | D | sum error = [ 364.5397, 382.9854, 402.1746, 422.1408, 442.8906] +24-11-19 20:34:28 | D | best error = [ 8.5791, 8.5791, 8.5791, 8.5791, 8.5791] +24-11-19 20:34:28 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:28 | D | sum error = [ 464.4083, 486.7306, 509.8726, 533.8227, 558.6136] +24-11-19 20:34:28 | D | best error = [ 8.5791, 8.5791, 8.5791, 8.5791, 8.5791] +24-11-19 20:34:28 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:28 | D | sum error = [ 584.2238, 610.6857, 637.9804, 666.1287, 695.1019] +24-11-19 20:34:28 | D | best error = [ 8.5791, 8.5791, 8.5791, 8.5791, 8.5791] +24-11-19 20:34:28 | D | + error = [8.5791] +24-11-19 20:34:28 | D | - Calibrating model.layers.21.mlp.down_proj.weight +24-11-19 20:34:28 | D | + w: sint8 +24-11-19 20:34:28 | D | + x: None +24-11-19 20:34:28 | D | + y: None +24-11-19 20:34:28 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:28 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:34:28 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:34:28 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:34:29 | D | - range ratio = [ 1.0000] +24-11-19 20:34:29 | D | sum error = [ 3.5337] +24-11-19 20:34:29 | D | best error = [ 3.5337] +24-11-19 20:34:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:29 | D | sum error = [ 3.5091, 3.4772, 3.4575, 3.4539, 3.4519] +24-11-19 20:34:29 | D | best error = [ 3.3742, 3.2958, 3.2416, 3.2035, 3.1737] +24-11-19 20:34:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:29 | D | sum error = [ 3.4712, 3.4930, 3.5501, 3.6075, 3.6866] +24-11-19 20:34:29 | D | best error = [ 3.1519, 3.1335, 3.1214, 3.1121, 3.1053] +24-11-19 20:34:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:29 | D | sum error = [ 3.7920, 3.9186, 4.0713, 4.2428, 4.4386] +24-11-19 20:34:29 | D | best error = [ 3.1014, 3.0985, 3.0965, 3.0954, 3.0944] +24-11-19 20:34:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:29 | D | sum error = [ 4.6678, 4.9251, 5.2205, 5.5263, 5.8772] +24-11-19 20:34:29 | D | best error = [ 3.0938, 3.0936, 3.0935, 3.0934, 3.0933] +24-11-19 20:34:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:29 | D | sum error = [ 6.2605, 6.6664, 7.1180, 7.6077, 8.1330] +24-11-19 20:34:29 | D | best error = [ 3.0933, 3.0933, 3.0933, 3.0933, 3.0933] +24-11-19 20:34:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:29 | D | sum error = [ 8.6822, 9.2912, 9.9265, 10.6186, 11.3488] +24-11-19 20:34:29 | D | best error = [ 3.0933, 3.0933, 3.0933, 3.0933, 3.0933] +24-11-19 20:34:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:29 | D | sum error = [ 12.1378, 12.9735, 13.8656, 14.8122, 15.8170] +24-11-19 20:34:29 | D | best error = [ 3.0933, 3.0933, 3.0933, 3.0933, 3.0933] +24-11-19 20:34:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:29 | D | sum error = [ 16.8932, 18.0303, 19.2428, 20.5126, 21.8668] +24-11-19 20:34:29 | D | best error = [ 3.0933, 3.0933, 3.0933, 3.0933, 3.0933] +24-11-19 20:34:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:29 | D | sum error = [ 23.2933, 24.8026, 26.4003, 28.0850, 29.8580] +24-11-19 20:34:29 | D | best error = [ 3.0933, 3.0933, 3.0933, 3.0933, 3.0933] +24-11-19 20:34:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:29 | D | sum error = [ 31.7306, 33.6978, 35.7745, 37.9582, 40.2502] +24-11-19 20:34:29 | D | best error = [ 3.0933, 3.0933, 3.0933, 3.0933, 3.0933] +24-11-19 20:34:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:29 | D | sum error = [ 42.6604, 45.1948, 47.8500, 50.6440, 53.5606] +24-11-19 20:34:29 | D | best error = [ 3.0933, 3.0933, 3.0933, 3.0933, 3.0933] +24-11-19 20:34:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:29 | D | sum error = [ 56.6255, 59.8247, 63.1843, 66.6918, 70.3526] +24-11-19 20:34:29 | D | best error = [ 3.0933, 3.0933, 3.0933, 3.0933, 3.0933] +24-11-19 20:34:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:29 | D | sum error = [ 74.1837, 78.1756, 82.3487, 86.6896, 91.2248] +24-11-19 20:34:29 | D | best error = [ 3.0933, 3.0933, 3.0933, 3.0933, 3.0933] +24-11-19 20:34:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:29 | D | sum error = [ 95.9412, 100.8534, 105.9622, 111.2871, 116.7908] +24-11-19 20:34:29 | D | best error = [ 3.0933, 3.0933, 3.0933, 3.0933, 3.0933] +24-11-19 20:34:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:29 | D | sum error = [ 122.5124, 128.4487, 134.6113, 140.9900, 147.5963] +24-11-19 20:34:29 | D | best error = [ 3.0933, 3.0933, 3.0933, 3.0933, 3.0933] +24-11-19 20:34:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:29 | D | sum error = [ 154.4309, 161.4983, 168.7965, 176.3353, 184.1081] +24-11-19 20:34:29 | D | best error = [ 3.0933, 3.0933, 3.0933, 3.0933, 3.0933] +24-11-19 20:34:29 | D | + error = [3.0933] +24-11-19 20:34:30 | D | - Quantizing model.layers.21.self_attn.q_proj.weight +24-11-19 20:34:30 | D | - Quantizing model.layers.21.self_attn.k_proj.weight +24-11-19 20:34:31 | D | - Quantizing model.layers.21.self_attn.v_proj.weight +24-11-19 20:34:32 | D | - Quantizing model.layers.21.self_attn.o_proj.weight +24-11-19 20:34:33 | D | - Quantizing model.layers.21.mlp.up_proj.weight +24-11-19 20:34:34 | D | - Quantizing model.layers.21.mlp.gate_proj.weight +24-11-19 20:34:35 | D | - Quantizing model.layers.21.mlp.down_proj.weight +24-11-19 20:34:43 | D | - Quantizing layer model.layers.22 +24-11-19 20:34:43 | D | - Calibrating model.layers.22.self_attn.q_proj.weight +24-11-19 20:34:44 | D | + w: sint8 +24-11-19 20:34:44 | D | + x: None +24-11-19 20:34:44 | D | + y: None +24-11-19 20:34:44 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:34:44 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:34:44 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:34:44 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:34:44 | D | - range ratio = [ 1.0000] +24-11-19 20:34:44 | D | sum error = [ 13.7348] +24-11-19 20:34:44 | D | best error = [ 13.7348] +24-11-19 20:34:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:57 | D | sum error = [ 13.3712, 13.5492, 13.5456, 13.7549, 13.7850] +24-11-19 20:34:57 | D | best error = [ 13.3712, 13.3712, 13.3712, 13.3712, 13.3712] +24-11-19 20:34:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:57 | D | sum error = [ 14.3704, 14.7225, 15.5003, 16.1729, 17.3101] +24-11-19 20:34:57 | D | best error = [ 13.3712, 13.3712, 13.3712, 13.3712, 13.3712] +24-11-19 20:34:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:57 | D | sum error = [ 17.9825, 19.0767, 20.7505, 21.7285, 23.4161] +24-11-19 20:34:57 | D | best error = [ 13.3712, 13.3712, 13.3712, 13.3712, 13.3712] +24-11-19 20:34:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:57 | D | sum error = [ 24.9661, 26.9159, 29.0113, 31.2943, 33.9868] +24-11-19 20:34:57 | D | best error = [ 13.3712, 13.3712, 13.3712, 13.3712, 13.3712] +24-11-19 20:34:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:57 | D | sum error = [ 36.4683, 39.7440, 42.4579, 45.9450, 49.5627] +24-11-19 20:34:57 | D | best error = [ 13.3712, 13.3712, 13.3712, 13.3712, 13.3712] +24-11-19 20:34:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:57 | D | sum error = [ 53.6589, 57.8289, 62.3123, 67.4183, 72.2407] +24-11-19 20:34:57 | D | best error = [ 13.3712, 13.3712, 13.3712, 13.3712, 13.3712] +24-11-19 20:34:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:57 | D | sum error = [ 78.3402, 84.5078, 91.0189, 98.4271, 105.8545] +24-11-19 20:34:57 | D | best error = [ 13.3712, 13.3712, 13.3712, 13.3712, 13.3712] +24-11-19 20:34:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:57 | D | sum error = [ 114.5127, 123.2162, 132.4854, 143.3371, 154.1454] +24-11-19 20:34:57 | D | best error = [ 13.3712, 13.3712, 13.3712, 13.3712, 13.3712] +24-11-19 20:34:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:57 | D | sum error = [ 166.1830, 178.7890, 192.9555, 207.6704, 223.7783] +24-11-19 20:34:57 | D | best error = [ 13.3712, 13.3712, 13.3712, 13.3712, 13.3712] +24-11-19 20:34:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:57 | D | sum error = [ 240.5806, 259.3477, 279.2883, 300.2857, 323.4263] +24-11-19 20:34:57 | D | best error = [ 13.3712, 13.3712, 13.3712, 13.3712, 13.3712] +24-11-19 20:34:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:57 | D | sum error = [ 347.9111, 374.4129, 403.4745, 434.3944, 468.1475] +24-11-19 20:34:57 | D | best error = [ 13.3712, 13.3712, 13.3712, 13.3712, 13.3712] +24-11-19 20:34:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:57 | D | sum error = [ 504.9562, 543.5854, 586.5740, 632.3375, 682.0635] +24-11-19 20:34:57 | D | best error = [ 13.3712, 13.3712, 13.3712, 13.3712, 13.3712] +24-11-19 20:34:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:57 | D | sum error = [ 736.4081, 795.8459, 861.8150, 931.7003, 1008.4029] +24-11-19 20:34:57 | D | best error = [ 13.3712, 13.3712, 13.3712, 13.3712, 13.3712] +24-11-19 20:34:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:57 | D | sum error = [ 1094.3495, 1186.5377, 1289.5485, 1401.5647, 1525.2005] +24-11-19 20:34:57 | D | best error = [ 13.3712, 13.3712, 13.3712, 13.3712, 13.3712] +24-11-19 20:34:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:57 | D | sum error = [ 1660.6728, 1809.7143, 1973.0561, 2154.2264, 2351.7752] +24-11-19 20:34:57 | D | best error = [ 13.3712, 13.3712, 13.3712, 13.3712, 13.3712] +24-11-19 20:34:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:57 | D | sum error = [ 2568.0004, 2806.6609, 3065.2292, 3345.6564, 3648.3762] +24-11-19 20:34:57 | D | best error = [ 13.3712, 13.3712, 13.3712, 13.3712, 13.3712] +24-11-19 20:34:57 | D | + error = [13.3712] +24-11-19 20:34:58 | D | - Calibrating model.layers.22.self_attn.k_proj.weight +24-11-19 20:34:58 | D | + w: sint8 +24-11-19 20:34:58 | D | + x: None +24-11-19 20:34:58 | D | + y: None +24-11-19 20:34:58 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:34:58 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:34:58 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:34:58 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:34:58 | D | - range ratio = [ 1.0000] +24-11-19 20:34:58 | D | sum error = [ 16.7022] +24-11-19 20:34:58 | D | best error = [ 16.7022] +24-11-19 20:35:11 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:11 | D | sum error = [ 18.1688, 17.0652, 16.8696, 17.6860, 20.3037] +24-11-19 20:35:11 | D | best error = [ 16.7022, 16.7022, 16.7022, 16.7022, 16.7022] +24-11-19 20:35:11 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:11 | D | sum error = [ 17.4969, 19.1032, 17.5879, 18.5293, 22.0761] +24-11-19 20:35:11 | D | best error = [ 16.7022, 16.7022, 16.7022, 16.7022, 16.7022] +24-11-19 20:35:11 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:11 | D | sum error = [ 20.7951, 24.6765, 23.7006, 25.8292, 28.2592] +24-11-19 20:35:11 | D | best error = [ 16.7022, 16.7022, 16.7022, 16.7022, 16.7022] +24-11-19 20:35:11 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:11 | D | sum error = [ 31.0403, 32.7589, 34.8498, 37.8360, 42.0666] +24-11-19 20:35:11 | D | best error = [ 16.7022, 16.7022, 16.7022, 16.7022, 16.7022] +24-11-19 20:35:11 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:11 | D | sum error = [ 43.2988, 48.3168, 48.9299, 53.7624, 57.9465] +24-11-19 20:35:11 | D | best error = [ 16.7022, 16.7022, 16.7022, 16.7022, 16.7022] +24-11-19 20:35:11 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:11 | D | sum error = [ 63.1243, 66.5130, 72.1951, 78.8501, 81.7454] +24-11-19 20:35:11 | D | best error = [ 16.7022, 16.7022, 16.7022, 16.7022, 16.7022] +24-11-19 20:35:11 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:11 | D | sum error = [ 89.9690, 94.9480, 102.2905, 112.9044, 120.4775] +24-11-19 20:35:11 | D | best error = [ 16.7022, 16.7022, 16.7022, 16.7022, 16.7022] +24-11-19 20:35:11 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:11 | D | sum error = [ 129.6574, 138.7846, 150.3781, 162.7346, 173.6761] +24-11-19 20:35:11 | D | best error = [ 16.7022, 16.7022, 16.7022, 16.7022, 16.7022] +24-11-19 20:35:11 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:11 | D | sum error = [ 192.9765, 206.6594, 222.8275, 239.2756, 257.3859] +24-11-19 20:35:11 | D | best error = [ 16.7022, 16.7022, 16.7022, 16.7022, 16.7022] +24-11-19 20:35:11 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:11 | D | sum error = [ 275.5377, 298.0049, 318.4938, 346.0899, 373.6568] +24-11-19 20:35:11 | D | best error = [ 16.7022, 16.7022, 16.7022, 16.7022, 16.7022] +24-11-19 20:35:11 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:11 | D | sum error = [ 403.2795, 437.4974, 470.4606, 507.0950, 544.7067] +24-11-19 20:35:11 | D | best error = [ 16.7022, 16.7022, 16.7022, 16.7022, 16.7022] +24-11-19 20:35:11 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:11 | D | sum error = [ 586.0642, 635.3962, 685.6470, 738.7096, 800.2898] +24-11-19 20:35:11 | D | best error = [ 16.7022, 16.7022, 16.7022, 16.7022, 16.7022] +24-11-19 20:35:11 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:11 | D | sum error = [ 861.9973, 935.2919, 1007.1308, 1087.5363, 1176.6116] +24-11-19 20:35:11 | D | best error = [ 16.7022, 16.7022, 16.7022, 16.7022, 16.7022] +24-11-19 20:35:11 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:11 | D | sum error = [ 1270.2415, 1377.7513, 1491.0435, 1620.9179, 1760.7452] +24-11-19 20:35:11 | D | best error = [ 16.7022, 16.7022, 16.7022, 16.7022, 16.7022] +24-11-19 20:35:11 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:11 | D | sum error = [ 1914.6753, 2074.8281, 2256.7754, 2449.8715, 2648.7595] +24-11-19 20:35:11 | D | best error = [ 16.7022, 16.7022, 16.7022, 16.7022, 16.7022] +24-11-19 20:35:11 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:11 | D | sum error = [ 2875.7815, 3115.9586, 3376.7917, 3648.3262, 3942.1498] +24-11-19 20:35:11 | D | best error = [ 16.7022, 16.7022, 16.7022, 16.7022, 16.7022] +24-11-19 20:35:11 | D | + error = [16.7022] +24-11-19 20:35:11 | D | - Calibrating model.layers.22.self_attn.v_proj.weight +24-11-19 20:35:11 | D | + w: sint8 +24-11-19 20:35:11 | D | + x: None +24-11-19 20:35:11 | D | + y: None +24-11-19 20:35:11 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:11 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:11 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:11 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:11 | D | - range ratio = [ 1.0000] +24-11-19 20:35:11 | D | sum error = [ 6.9744] +24-11-19 20:35:11 | D | best error = [ 6.9744] +24-11-19 20:35:11 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:11 | D | sum error = [ 6.9370, 6.9066, 6.9611, 7.0471, 7.1696] +24-11-19 20:35:11 | D | best error = [ 6.5128, 6.3256, 6.2210, 6.1611, 6.1256] +24-11-19 20:35:11 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:11 | D | sum error = [ 7.3340, 7.6016, 7.8552, 8.2550, 8.7079] +24-11-19 20:35:11 | D | best error = [ 6.1094, 6.1023, 6.0997, 6.0981, 6.0979] +24-11-19 20:35:11 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:11 | D | sum error = [ 9.1970, 9.7553, 10.3968, 11.0715, 11.8427] +24-11-19 20:35:11 | D | best error = [ 6.0978, 6.0978, 6.0978, 6.0978, 6.0978] +24-11-19 20:35:11 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:11 | D | sum error = [ 12.6840, 13.6031, 14.5733, 15.6218, 16.7603] +24-11-19 20:35:11 | D | best error = [ 6.0978, 6.0978, 6.0978, 6.0978, 6.0978] +24-11-19 20:35:11 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:11 | D | sum error = [ 17.9540, 19.2457, 20.5264, 21.9816, 23.5128] +24-11-19 20:35:11 | D | best error = [ 6.0978, 6.0978, 6.0978, 6.0978, 6.0978] +24-11-19 20:35:11 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:11 | D | sum error = [ 25.1404, 26.8286, 28.6330, 30.5460, 32.5348] +24-11-19 20:35:11 | D | best error = [ 6.0978, 6.0978, 6.0978, 6.0978, 6.0978] +24-11-19 20:35:11 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:11 | D | sum error = [ 34.6668, 36.8682, 39.2090, 41.7110, 44.2933] +24-11-19 20:35:11 | D | best error = [ 6.0978, 6.0978, 6.0978, 6.0978, 6.0978] +24-11-19 20:35:11 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:11 | D | sum error = [ 47.0481, 49.9110, 52.9480, 56.0983, 59.4391] +24-11-19 20:35:11 | D | best error = [ 6.0978, 6.0978, 6.0978, 6.0978, 6.0978] +24-11-19 20:35:11 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:11 | D | sum error = [ 62.9374, 66.6008, 70.4845, 74.5042, 78.7120] +24-11-19 20:35:11 | D | best error = [ 6.0978, 6.0978, 6.0978, 6.0978, 6.0978] +24-11-19 20:35:11 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:11 | D | sum error = [ 83.1477, 87.7771, 92.5997, 97.6679, 102.9379] +24-11-19 20:35:11 | D | best error = [ 6.0978, 6.0978, 6.0978, 6.0978, 6.0978] +24-11-19 20:35:11 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:11 | D | sum error = [ 108.4258, 114.1935, 120.1808, 126.4459, 132.9662] +24-11-19 20:35:11 | D | best error = [ 6.0978, 6.0978, 6.0978, 6.0978, 6.0978] +24-11-19 20:35:11 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:11 | D | sum error = [ 139.7468, 146.7832, 154.1303, 161.7537, 169.6378] +24-11-19 20:35:11 | D | best error = [ 6.0978, 6.0978, 6.0978, 6.0978, 6.0978] +24-11-19 20:35:11 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:11 | D | sum error = [ 177.8571, 186.3549, 195.2021, 204.3419, 213.8211] +24-11-19 20:35:11 | D | best error = [ 6.0978, 6.0978, 6.0978, 6.0978, 6.0978] +24-11-19 20:35:11 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:11 | D | sum error = [ 223.6200, 233.7804, 244.2856, 255.1574, 266.3598] +24-11-19 20:35:11 | D | best error = [ 6.0978, 6.0978, 6.0978, 6.0978, 6.0978] +24-11-19 20:35:11 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:11 | D | sum error = [ 277.9607, 289.8909, 302.2143, 314.9025, 327.9778] +24-11-19 20:35:11 | D | best error = [ 6.0978, 6.0978, 6.0978, 6.0978, 6.0978] +24-11-19 20:35:11 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:11 | D | sum error = [ 341.4278, 355.2741, 369.5286, 384.2012, 399.2655] +24-11-19 20:35:11 | D | best error = [ 6.0978, 6.0978, 6.0978, 6.0978, 6.0978] +24-11-19 20:35:11 | D | + error = [6.0978] +24-11-19 20:35:12 | D | - Calibrating model.layers.22.self_attn.o_proj.weight +24-11-19 20:35:12 | D | + w: sint8 +24-11-19 20:35:12 | D | + x: None +24-11-19 20:35:12 | D | + y: None +24-11-19 20:35:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:12 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:12 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:12 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:12 | D | - range ratio = [ 1.0000] +24-11-19 20:35:12 | D | sum error = [ 1.5649] +24-11-19 20:35:12 | D | best error = [ 1.5649] +24-11-19 20:35:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:12 | D | sum error = [ 1.5487, 1.5493, 1.5549, 1.5659, 1.5863] +24-11-19 20:35:12 | D | best error = [ 1.4816, 1.4436, 1.4211, 1.4076, 1.3987] +24-11-19 20:35:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:12 | D | sum error = [ 1.6229, 1.6736, 1.7314, 1.8047, 1.8894] +24-11-19 20:35:12 | D | best error = [ 1.3929, 1.3889, 1.3865, 1.3847, 1.3836] +24-11-19 20:35:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:12 | D | sum error = [ 1.9908, 2.1010, 2.2263, 2.3723, 2.5231] +24-11-19 20:35:12 | D | best error = [ 1.3829, 1.3823, 1.3819, 1.3816, 1.3814] +24-11-19 20:35:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:12 | D | sum error = [ 2.6909, 2.8738, 3.0651, 3.2760, 3.5009] +24-11-19 20:35:12 | D | best error = [ 1.3813, 1.3813, 1.3811, 1.3810, 1.3810] +24-11-19 20:35:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:12 | D | sum error = [ 3.7470, 4.0011, 4.2804, 4.5666, 4.8725] +24-11-19 20:35:12 | D | best error = [ 1.3810, 1.3810, 1.3809, 1.3809, 1.3809] +24-11-19 20:35:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:12 | D | sum error = [ 5.2002, 5.5506, 5.9166, 6.3054, 6.7184] +24-11-19 20:35:12 | D | best error = [ 1.3809, 1.3809, 1.3809, 1.3809, 1.3809] +24-11-19 20:35:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:12 | D | sum error = [ 7.1496, 7.6134, 8.1007, 8.6083, 9.1511] +24-11-19 20:35:12 | D | best error = [ 1.3809, 1.3809, 1.3809, 1.3809, 1.3809] +24-11-19 20:35:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:12 | D | sum error = [ 9.7218, 10.3216, 10.9522, 11.6184, 12.3201] +24-11-19 20:35:12 | D | best error = [ 1.3809, 1.3809, 1.3809, 1.3809, 1.3809] +24-11-19 20:35:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:12 | D | sum error = [ 13.0563, 13.8359, 14.6508, 15.5109, 16.4147] +24-11-19 20:35:12 | D | best error = [ 1.3809, 1.3809, 1.3809, 1.3809, 1.3809] +24-11-19 20:35:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:12 | D | sum error = [ 17.3624, 18.3645, 19.4140, 20.5160, 21.6736] +24-11-19 20:35:12 | D | best error = [ 1.3809, 1.3809, 1.3809, 1.3809, 1.3809] +24-11-19 20:35:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:12 | D | sum error = [ 22.8850, 24.1652, 25.5025, 26.9062, 28.3796] +24-11-19 20:35:12 | D | best error = [ 1.3809, 1.3809, 1.3809, 1.3809, 1.3809] +24-11-19 20:35:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:12 | D | sum error = [ 29.9249, 31.5457, 33.2357, 35.0064, 36.8623] +24-11-19 20:35:12 | D | best error = [ 1.3809, 1.3809, 1.3809, 1.3809, 1.3809] +24-11-19 20:35:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:12 | D | sum error = [ 38.8027, 40.8309, 42.9510, 45.1668, 47.4778] +24-11-19 20:35:12 | D | best error = [ 1.3809, 1.3809, 1.3809, 1.3809, 1.3809] +24-11-19 20:35:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:12 | D | sum error = [ 49.8847, 52.3959, 55.0089, 57.7355, 60.5652] +24-11-19 20:35:12 | D | best error = [ 1.3809, 1.3809, 1.3809, 1.3809, 1.3809] +24-11-19 20:35:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:12 | D | sum error = [ 63.5102, 66.5734, 69.7467, 73.0423, 76.4599] +24-11-19 20:35:12 | D | best error = [ 1.3809, 1.3809, 1.3809, 1.3809, 1.3809] +24-11-19 20:35:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:12 | D | sum error = [ 79.9994, 83.6675, 87.4626, 91.3873, 95.4446] +24-11-19 20:35:12 | D | best error = [ 1.3809, 1.3809, 1.3809, 1.3809, 1.3809] +24-11-19 20:35:12 | D | + error = [1.3809] +24-11-19 20:35:12 | D | - Calibrating model.layers.22.mlp.up_proj.weight +24-11-19 20:35:12 | D | + w: sint8 +24-11-19 20:35:12 | D | + x: None +24-11-19 20:35:12 | D | + y: None +24-11-19 20:35:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:12 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:12 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:13 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:13 | D | - range ratio = [ 1.0000] +24-11-19 20:35:13 | D | sum error = [ 9.4733] +24-11-19 20:35:13 | D | best error = [ 9.4733] +24-11-19 20:35:13 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:13 | D | sum error = [ 9.4110, 9.3690, 9.4097, 9.5209, 9.7018] +24-11-19 20:35:13 | D | best error = [ 8.8006, 8.5261, 8.3838, 8.3009, 8.2560] +24-11-19 20:35:13 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:13 | D | sum error = [ 9.9501, 10.2578, 10.6997, 11.1984, 11.8110] +24-11-19 20:35:13 | D | best error = [ 8.2315, 8.2222, 8.2183, 8.2172, 8.2168] +24-11-19 20:35:13 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:13 | D | sum error = [ 12.4641, 13.2181, 14.1027, 15.0293, 16.0581] +24-11-19 20:35:13 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:35:13 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:13 | D | sum error = [ 17.2242, 18.4275, 19.7746, 21.1736, 22.6690] +24-11-19 20:35:13 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:35:13 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:13 | D | sum error = [ 24.2973, 26.0039, 27.8558, 29.7835, 31.8876] +24-11-19 20:35:13 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:35:13 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:13 | D | sum error = [ 34.0587, 36.3667, 38.8450, 41.4109, 44.1697] +24-11-19 20:35:13 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:35:13 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:13 | D | sum error = [ 47.0674, 50.0998, 53.3182, 56.7303, 60.2904] +24-11-19 20:35:13 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:35:13 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:13 | D | sum error = [ 64.0570, 67.9974, 72.1487, 76.5488, 81.1409] +24-11-19 20:35:13 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:35:13 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:13 | D | sum error = [ 85.9580, 91.0350, 96.3387, 101.9176, 107.7507] +24-11-19 20:35:13 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:35:13 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:13 | D | sum error = [ 113.8724, 120.2701, 127.0044, 134.0133, 141.3319] +24-11-19 20:35:13 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:35:13 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:13 | D | sum error = [ 149.0101, 156.9922, 165.3545, 174.0826, 183.1705] +24-11-19 20:35:13 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:35:13 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:13 | D | sum error = [ 192.6482, 202.5280, 212.8131, 223.5199, 234.6503] +24-11-19 20:35:13 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:35:13 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:13 | D | sum error = [ 246.2210, 258.2449, 270.7469, 283.7191, 297.1907] +24-11-19 20:35:13 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:35:13 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:13 | D | sum error = [ 311.1550, 325.6184, 340.5957, 356.1017, 372.1389] +24-11-19 20:35:13 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:35:13 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:13 | D | sum error = [ 388.7160, 405.8522, 423.5700, 441.8247, 460.6790] +24-11-19 20:35:13 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:35:13 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:13 | D | sum error = [ 480.1038, 500.1358, 520.7782, 541.9991, 563.8370] +24-11-19 20:35:13 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:35:13 | D | + error = [8.2167] +24-11-19 20:35:14 | D | - Calibrating model.layers.22.mlp.gate_proj.weight +24-11-19 20:35:14 | D | + w: sint8 +24-11-19 20:35:14 | D | + x: None +24-11-19 20:35:14 | D | + y: None +24-11-19 20:35:14 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:14 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:14 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:14 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:14 | D | - range ratio = [ 1.0000] +24-11-19 20:35:14 | D | sum error = [ 10.2655] +24-11-19 20:35:14 | D | best error = [ 10.2655] +24-11-19 20:35:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:15 | D | sum error = [ 10.1790, 10.1786, 10.2408, 10.3557, 10.5124] +24-11-19 20:35:15 | D | best error = [ 9.5289, 9.2422, 9.0877, 9.0037, 8.9502] +24-11-19 20:35:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:15 | D | sum error = [ 10.8136, 11.1442, 11.5999, 12.1646, 12.7847] +24-11-19 20:35:15 | D | best error = [ 8.9249, 8.9149, 8.9103, 8.9087, 8.9083] +24-11-19 20:35:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:15 | D | sum error = [ 13.5205, 14.3707, 15.2989, 16.3625, 17.4736] +24-11-19 20:35:15 | D | best error = [ 8.9082, 8.9081, 8.9081, 8.9081, 8.9081] +24-11-19 20:35:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:15 | D | sum error = [ 18.7215, 20.0606, 21.5007, 23.0411, 24.7250] +24-11-19 20:35:15 | D | best error = [ 8.9081, 8.9081, 8.9081, 8.9081, 8.9081] +24-11-19 20:35:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:15 | D | sum error = [ 26.4990, 28.4078, 30.3993, 32.5352, 34.8315] +24-11-19 20:35:15 | D | best error = [ 8.9081, 8.9081, 8.9081, 8.9081, 8.9081] +24-11-19 20:35:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:15 | D | sum error = [ 37.2514, 39.7903, 42.5503, 45.4050, 48.4722] +24-11-19 20:35:15 | D | best error = [ 8.9081, 8.9081, 8.9081, 8.9081, 8.9081] +24-11-19 20:35:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:15 | D | sum error = [ 51.7213, 55.1190, 58.7321, 62.5564, 66.5914] +24-11-19 20:35:15 | D | best error = [ 8.9081, 8.9081, 8.9081, 8.9081, 8.9081] +24-11-19 20:35:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:15 | D | sum error = [ 70.8196, 75.3306, 80.0522, 85.0598, 90.3145] +24-11-19 20:35:15 | D | best error = [ 8.9081, 8.9081, 8.9081, 8.9081, 8.9081] +24-11-19 20:35:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:15 | D | sum error = [ 95.8625, 101.7168, 107.9118, 114.3949, 121.2392] +24-11-19 20:35:15 | D | best error = [ 8.9081, 8.9081, 8.9081, 8.9081, 8.9081] +24-11-19 20:35:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:15 | D | sum error = [ 128.3898, 135.9644, 143.9185, 152.2476, 161.0638] +24-11-19 20:35:15 | D | best error = [ 8.9081, 8.9081, 8.9081, 8.9081, 8.9081] +24-11-19 20:35:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:15 | D | sum error = [ 170.2309, 179.9137, 190.0618, 200.6747, 211.8230] +24-11-19 20:35:15 | D | best error = [ 8.9081, 8.9081, 8.9081, 8.9081, 8.9081] +24-11-19 20:35:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:15 | D | sum error = [ 223.4701, 235.6821, 248.4542, 261.8310, 275.7976] +24-11-19 20:35:15 | D | best error = [ 8.9081, 8.9081, 8.9081, 8.9081, 8.9081] +24-11-19 20:35:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:15 | D | sum error = [ 290.4173, 305.6241, 321.5442, 338.1146, 355.3794] +24-11-19 20:35:15 | D | best error = [ 8.9081, 8.9081, 8.9081, 8.9081, 8.9081] +24-11-19 20:35:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:15 | D | sum error = [ 373.3603, 392.0497, 411.5183, 431.7445, 452.7443] +24-11-19 20:35:15 | D | best error = [ 8.9081, 8.9081, 8.9081, 8.9081, 8.9081] +24-11-19 20:35:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:15 | D | sum error = [ 474.5165, 497.0591, 520.4457, 544.6493, 569.7032] +24-11-19 20:35:15 | D | best error = [ 8.9081, 8.9081, 8.9081, 8.9081, 8.9081] +24-11-19 20:35:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:15 | D | sum error = [ 595.5663, 622.2998, 649.8799, 678.3293, 707.6429] +24-11-19 20:35:15 | D | best error = [ 8.9081, 8.9081, 8.9081, 8.9081, 8.9081] +24-11-19 20:35:15 | D | + error = [8.9081] +24-11-19 20:35:15 | D | - Calibrating model.layers.22.mlp.down_proj.weight +24-11-19 20:35:15 | D | + w: sint8 +24-11-19 20:35:15 | D | + x: None +24-11-19 20:35:15 | D | + y: None +24-11-19 20:35:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:15 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:15 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:15 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:15 | D | - range ratio = [ 1.0000] +24-11-19 20:35:15 | D | sum error = [ 3.6774] +24-11-19 20:35:15 | D | best error = [ 3.6774] +24-11-19 20:35:16 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:16 | D | sum error = [ 3.6483, 3.6173, 3.5999, 3.5987, 3.6022] +24-11-19 20:35:16 | D | best error = [ 3.5216, 3.4388, 3.3822, 3.3442, 3.3175] +24-11-19 20:35:16 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:16 | D | sum error = [ 3.6189, 3.6419, 3.6960, 3.7576, 3.8573] +24-11-19 20:35:16 | D | best error = [ 3.2963, 3.2793, 3.2678, 3.2586, 3.2522] +24-11-19 20:35:16 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:16 | D | sum error = [ 3.9577, 4.0862, 4.2414, 4.4238, 4.6363] +24-11-19 20:35:16 | D | best error = [ 3.2478, 3.2445, 3.2427, 3.2413, 3.2406] +24-11-19 20:35:16 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:16 | D | sum error = [ 4.8711, 5.1511, 5.4473, 5.7777, 6.1470] +24-11-19 20:35:16 | D | best error = [ 3.2402, 3.2400, 3.2399, 3.2399, 3.2398] +24-11-19 20:35:16 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:16 | D | sum error = [ 6.5546, 6.9869, 7.4680, 7.9737, 8.5379] +24-11-19 20:35:16 | D | best error = [ 3.2397, 3.2397, 3.2397, 3.2397, 3.2397] +24-11-19 20:35:16 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:16 | D | sum error = [ 9.1218, 9.7590, 10.4460, 11.1767, 11.9488] +24-11-19 20:35:16 | D | best error = [ 3.2397, 3.2397, 3.2397, 3.2397, 3.2397] +24-11-19 20:35:16 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:16 | D | sum error = [ 12.7728, 13.6600, 14.5993, 15.6007, 16.6567] +24-11-19 20:35:16 | D | best error = [ 3.2397, 3.2397, 3.2397, 3.2397, 3.2397] +24-11-19 20:35:16 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:16 | D | sum error = [ 17.7763, 18.9676, 20.2274, 21.5534, 22.9657] +24-11-19 20:35:16 | D | best error = [ 3.2397, 3.2397, 3.2397, 3.2397, 3.2397] +24-11-19 20:35:16 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:16 | D | sum error = [ 24.4583, 26.0261, 27.6920, 29.4489, 31.2927] +24-11-19 20:35:16 | D | best error = [ 3.2397, 3.2397, 3.2397, 3.2397, 3.2397] +24-11-19 20:35:16 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:16 | D | sum error = [ 33.2478, 35.2974, 37.4588, 39.7355, 42.1254] +24-11-19 20:35:16 | D | best error = [ 3.2397, 3.2397, 3.2397, 3.2397, 3.2397] +24-11-19 20:35:16 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:16 | D | sum error = [ 44.6361, 47.2704, 50.0287, 52.9339, 55.9657] +24-11-19 20:35:16 | D | best error = [ 3.2397, 3.2397, 3.2397, 3.2397, 3.2397] +24-11-19 20:35:16 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:16 | D | sum error = [ 59.1544, 62.4875, 65.9792, 69.6330, 73.4502] +24-11-19 20:35:16 | D | best error = [ 3.2397, 3.2397, 3.2397, 3.2397, 3.2397] +24-11-19 20:35:16 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:16 | D | sum error = [ 77.4372, 81.6041, 85.9497, 90.4812, 95.1961] +24-11-19 20:35:16 | D | best error = [ 3.2397, 3.2397, 3.2397, 3.2397, 3.2397] +24-11-19 20:35:16 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:16 | D | sum error = [ 100.1138, 105.2215, 110.5354, 116.0733, 121.8054] +24-11-19 20:35:16 | D | best error = [ 3.2397, 3.2397, 3.2397, 3.2397, 3.2397] +24-11-19 20:35:16 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:16 | D | sum error = [ 127.7658, 133.9506, 140.3579, 146.9968, 153.8673] +24-11-19 20:35:16 | D | best error = [ 3.2397, 3.2397, 3.2397, 3.2397, 3.2397] +24-11-19 20:35:16 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:16 | D | sum error = [ 160.9829, 168.3375, 175.9405, 183.7922, 191.8949] +24-11-19 20:35:16 | D | best error = [ 3.2397, 3.2397, 3.2397, 3.2397, 3.2397] +24-11-19 20:35:16 | D | + error = [3.2397] +24-11-19 20:35:16 | D | - Quantizing model.layers.22.self_attn.q_proj.weight +24-11-19 20:35:17 | D | - Quantizing model.layers.22.self_attn.k_proj.weight +24-11-19 20:35:18 | D | - Quantizing model.layers.22.self_attn.v_proj.weight +24-11-19 20:35:19 | D | - Quantizing model.layers.22.self_attn.o_proj.weight +24-11-19 20:35:20 | D | - Quantizing model.layers.22.mlp.up_proj.weight +24-11-19 20:35:21 | D | - Quantizing model.layers.22.mlp.gate_proj.weight +24-11-19 20:35:21 | D | - Quantizing model.layers.22.mlp.down_proj.weight +24-11-19 20:35:30 | D | - Quantizing layer model.layers.23 +24-11-19 20:35:30 | D | - Calibrating model.layers.23.self_attn.q_proj.weight +24-11-19 20:35:30 | D | + w: sint8 +24-11-19 20:35:30 | D | + x: None +24-11-19 20:35:30 | D | + y: None +24-11-19 20:35:30 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:35:30 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:30 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:30 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:30 | D | - range ratio = [ 1.0000] +24-11-19 20:35:30 | D | sum error = [ 12.8129] +24-11-19 20:35:30 | D | best error = [ 12.8129] +24-11-19 20:35:43 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:43 | D | sum error = [ 12.8409, 12.6040, 12.6082, 12.8151, 13.0984] +24-11-19 20:35:43 | D | best error = [ 12.8129, 12.6040, 12.6040, 12.6040, 12.6040] +24-11-19 20:35:43 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:43 | D | sum error = [ 13.3812, 13.6284, 14.1433, 15.2528, 15.9915] +24-11-19 20:35:43 | D | best error = [ 12.6040, 12.6040, 12.6040, 12.6040, 12.6040] +24-11-19 20:35:43 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:43 | D | sum error = [ 16.6326, 17.7785, 19.2011, 20.7666, 22.0747] +24-11-19 20:35:43 | D | best error = [ 12.6040, 12.6040, 12.6040, 12.6040, 12.6040] +24-11-19 20:35:43 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:43 | D | sum error = [ 23.7857, 25.3693, 27.5112, 30.0433, 32.6214] +24-11-19 20:35:43 | D | best error = [ 12.6040, 12.6040, 12.6040, 12.6040, 12.6040] +24-11-19 20:35:43 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:43 | D | sum error = [ 34.9054, 37.8086, 40.9857, 44.4470, 47.4404] +24-11-19 20:35:43 | D | best error = [ 12.6040, 12.6040, 12.6040, 12.6040, 12.6040] +24-11-19 20:35:43 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:43 | D | sum error = [ 51.1555, 55.4638, 59.8164, 64.5979, 69.5869] +24-11-19 20:35:43 | D | best error = [ 12.6040, 12.6040, 12.6040, 12.6040, 12.6040] +24-11-19 20:35:43 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:43 | D | sum error = [ 75.0073, 81.2156, 87.3101, 93.9388, 101.1547] +24-11-19 20:35:43 | D | best error = [ 12.6040, 12.6040, 12.6040, 12.6040, 12.6040] +24-11-19 20:35:43 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:43 | D | sum error = [ 108.1949, 116.5611, 125.2739, 134.3587, 144.2129] +24-11-19 20:35:43 | D | best error = [ 12.6040, 12.6040, 12.6040, 12.6040, 12.6040] +24-11-19 20:35:43 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:43 | D | sum error = [ 155.2400, 167.0566, 179.7383, 193.3166, 208.2633] +24-11-19 20:35:43 | D | best error = [ 12.6040, 12.6040, 12.6040, 12.6040, 12.6040] +24-11-19 20:35:43 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:43 | D | sum error = [ 224.2761, 241.1776, 258.8739, 278.0759, 299.4532] +24-11-19 20:35:43 | D | best error = [ 12.6040, 12.6040, 12.6040, 12.6040, 12.6040] +24-11-19 20:35:43 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:43 | D | sum error = [ 321.6129, 346.1961, 372.7566, 401.2508, 432.2611] +24-11-19 20:35:43 | D | best error = [ 12.6040, 12.6040, 12.6040, 12.6040, 12.6040] +24-11-19 20:35:43 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:43 | D | sum error = [ 465.8570, 502.3351, 541.2510, 583.5811, 629.1685] +24-11-19 20:35:43 | D | best error = [ 12.6040, 12.6040, 12.6040, 12.6040, 12.6040] +24-11-19 20:35:43 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:43 | D | sum error = [ 679.5166, 733.9248, 793.1998, 857.5532, 928.1319] +24-11-19 20:35:43 | D | best error = [ 12.6040, 12.6040, 12.6040, 12.6040, 12.6040] +24-11-19 20:35:43 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:43 | D | sum error = [ 1005.6069, 1090.7689, 1183.9596, 1286.3809, 1398.8191] +24-11-19 20:35:43 | D | best error = [ 12.6040, 12.6040, 12.6040, 12.6040, 12.6040] +24-11-19 20:35:43 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:43 | D | sum error = [ 1524.3725, 1660.7142, 1812.3349, 1978.7770, 2161.1177] +24-11-19 20:35:43 | D | best error = [ 12.6040, 12.6040, 12.6040, 12.6040, 12.6040] +24-11-19 20:35:43 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:43 | D | sum error = [ 2360.4989, 2580.0031, 2818.3006, 3077.7713, 3356.1564] +24-11-19 20:35:43 | D | best error = [ 12.6040, 12.6040, 12.6040, 12.6040, 12.6040] +24-11-19 20:35:43 | D | + error = [12.6040] +24-11-19 20:35:43 | D | - Calibrating model.layers.23.self_attn.k_proj.weight +24-11-19 20:35:43 | D | + w: sint8 +24-11-19 20:35:43 | D | + x: None +24-11-19 20:35:43 | D | + y: None +24-11-19 20:35:43 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:35:43 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:35:43 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:35:44 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:35:44 | D | - range ratio = [ 1.0000] +24-11-19 20:35:44 | D | sum error = [ 15.1166] +24-11-19 20:35:44 | D | best error = [ 15.1166] +24-11-19 20:35:56 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:56 | D | sum error = [ 14.9529, 14.6473, 14.4146, 15.1761, 15.0106] +24-11-19 20:35:56 | D | best error = [ 14.9529, 14.6473, 14.4146, 14.4146, 14.4146] +24-11-19 20:35:56 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:56 | D | sum error = [ 15.3409, 16.0503, 16.5679, 17.8073, 18.4645] +24-11-19 20:35:56 | D | best error = [ 14.4146, 14.4146, 14.4146, 14.4146, 14.4146] +24-11-19 20:35:56 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:56 | D | sum error = [ 19.8286, 21.1456, 23.1546, 24.7205, 25.7257] +24-11-19 20:35:56 | D | best error = [ 14.4146, 14.4146, 14.4146, 14.4146, 14.4146] +24-11-19 20:35:56 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:56 | D | sum error = [ 27.9314, 29.2805, 32.2419, 33.8634, 37.0439] +24-11-19 20:35:56 | D | best error = [ 14.4146, 14.4146, 14.4146, 14.4146, 14.4146] +24-11-19 20:35:56 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:56 | D | sum error = [ 40.6151, 43.6759, 47.6764, 51.0588, 55.3055] +24-11-19 20:35:56 | D | best error = [ 14.4146, 14.4146, 14.4146, 14.4146, 14.4146] +24-11-19 20:35:56 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:56 | D | sum error = [ 59.0606, 64.6632, 69.3529, 74.0755, 79.1971] +24-11-19 20:35:56 | D | best error = [ 14.4146, 14.4146, 14.4146, 14.4146, 14.4146] +24-11-19 20:35:56 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:56 | D | sum error = [ 84.5244, 91.4953, 99.0028, 105.1780, 112.9264] +24-11-19 20:35:56 | D | best error = [ 14.4146, 14.4146, 14.4146, 14.4146, 14.4146] +24-11-19 20:35:56 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:56 | D | sum error = [ 121.0840, 130.4680, 141.0223, 151.9831, 163.3864] +24-11-19 20:35:56 | D | best error = [ 14.4146, 14.4146, 14.4146, 14.4146, 14.4146] +24-11-19 20:35:56 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:56 | D | sum error = [ 176.4571, 190.0943, 204.0845, 220.3414, 237.6995] +24-11-19 20:35:56 | D | best error = [ 14.4146, 14.4146, 14.4146, 14.4146, 14.4146] +24-11-19 20:35:56 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:56 | D | sum error = [ 256.7642, 275.5870, 296.7975, 319.4366, 343.8826] +24-11-19 20:35:56 | D | best error = [ 14.4146, 14.4146, 14.4146, 14.4146, 14.4146] +24-11-19 20:35:56 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:56 | D | sum error = [ 369.4519, 397.7610, 428.5525, 460.6337, 496.2173] +24-11-19 20:35:56 | D | best error = [ 14.4146, 14.4146, 14.4146, 14.4146, 14.4146] +24-11-19 20:35:56 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:56 | D | sum error = [ 534.6916, 575.3982, 621.5472, 668.9343, 721.4330] +24-11-19 20:35:56 | D | best error = [ 14.4146, 14.4146, 14.4146, 14.4146, 14.4146] +24-11-19 20:35:56 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:56 | D | sum error = [ 777.6849, 841.1761, 908.6619, 980.9831, 1062.4710] +24-11-19 20:35:56 | D | best error = [ 14.4146, 14.4146, 14.4146, 14.4146, 14.4146] +24-11-19 20:35:56 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:56 | D | sum error = [ 1150.2186, 1244.1493, 1347.5572, 1460.4809, 1581.0287] +24-11-19 20:35:56 | D | best error = [ 14.4146, 14.4146, 14.4146, 14.4146, 14.4146] +24-11-19 20:35:56 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:56 | D | sum error = [ 1716.6689, 1862.1850, 2024.2814, 2201.5288, 2392.3305] +24-11-19 20:35:56 | D | best error = [ 14.4146, 14.4146, 14.4146, 14.4146, 14.4146] +24-11-19 20:35:56 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:56 | D | sum error = [ 2601.7511, 2827.3538, 3071.7047, 3329.5642, 3606.1316] +24-11-19 20:35:56 | D | best error = [ 14.4146, 14.4146, 14.4146, 14.4146, 14.4146] +24-11-19 20:35:56 | D | + error = [14.4146] +24-11-19 20:35:57 | D | - Calibrating model.layers.23.self_attn.v_proj.weight +24-11-19 20:35:57 | D | + w: sint8 +24-11-19 20:35:57 | D | + x: None +24-11-19 20:35:57 | D | + y: None +24-11-19 20:35:57 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:57 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:57 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:57 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:57 | D | - range ratio = [ 1.0000] +24-11-19 20:35:57 | D | sum error = [ 7.7980] +24-11-19 20:35:57 | D | best error = [ 7.7980] +24-11-19 20:35:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:57 | D | sum error = [ 7.7396, 7.7078, 7.7646, 7.8594, 7.9750] +24-11-19 20:35:57 | D | best error = [ 7.2650, 7.0370, 6.9212, 6.8553, 6.8184] +24-11-19 20:35:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:57 | D | sum error = [ 8.1977, 8.4918, 8.8039, 9.2441, 9.6932] +24-11-19 20:35:57 | D | best error = [ 6.7995, 6.7919, 6.7889, 6.7882, 6.7880] +24-11-19 20:35:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:57 | D | sum error = [ 10.2610, 10.9176, 11.6065, 12.3645, 13.2645] +24-11-19 20:35:57 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:57 | D | sum error = [ 14.1702, 15.1787, 16.2431, 17.4004, 18.6635] +24-11-19 20:35:57 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:57 | D | sum error = [ 19.9808, 21.4089, 22.8943, 24.5184, 26.2247] +24-11-19 20:35:57 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:57 | D | sum error = [ 27.9854, 29.9186, 31.9535, 34.0517, 36.3120] +24-11-19 20:35:57 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:57 | D | sum error = [ 38.6629, 41.1819, 43.8081, 46.5525, 49.4590] +24-11-19 20:35:57 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:57 | D | sum error = [ 52.4985, 55.6957, 59.0821, 62.5961, 66.3361] +24-11-19 20:35:57 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:57 | D | sum error = [ 70.2253, 74.2969, 78.5761, 83.0533, 87.7656] +24-11-19 20:35:57 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:57 | D | sum error = [ 92.6646, 97.8049, 103.1712, 108.7866, 114.6477] +24-11-19 20:35:57 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:57 | D | sum error = [ 120.7481, 127.1282, 133.7160, 140.6246, 147.8058] +24-11-19 20:35:57 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:57 | D | sum error = [ 155.3015, 163.0705, 171.1395, 179.5132, 188.2137] +24-11-19 20:35:57 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:57 | D | sum error = [ 197.2486, 206.6379, 216.3630, 226.4354, 236.8853] +24-11-19 20:35:57 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:57 | D | sum error = [ 247.6792, 258.8415, 270.3805, 282.3154, 294.6108] +24-11-19 20:35:57 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:57 | D | sum error = [ 307.3159, 320.4301, 333.9411, 347.8336, 362.1336] +24-11-19 20:35:57 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:57 | D | sum error = [ 376.8562, 391.9998, 407.5657, 423.5860, 440.0720] +24-11-19 20:35:57 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:57 | D | + error = [6.7879] +24-11-19 20:35:57 | D | - Calibrating model.layers.23.self_attn.o_proj.weight +24-11-19 20:35:57 | D | + w: sint8 +24-11-19 20:35:57 | D | + x: None +24-11-19 20:35:57 | D | + y: None +24-11-19 20:35:57 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:57 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:58 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:58 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:58 | D | - range ratio = [ 1.0000] +24-11-19 20:35:58 | D | sum error = [ 1.4846] +24-11-19 20:35:58 | D | best error = [ 1.4846] +24-11-19 20:35:58 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:58 | D | sum error = [ 1.4771, 1.4676, 1.4727, 1.4863, 1.5074] +24-11-19 20:35:58 | D | best error = [ 1.4110, 1.3748, 1.3534, 1.3401, 1.3318] +24-11-19 20:35:58 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:58 | D | sum error = [ 1.5426, 1.5859, 1.6347, 1.7014, 1.7800] +24-11-19 20:35:58 | D | best error = [ 1.3267, 1.3233, 1.3214, 1.3201, 1.3193] +24-11-19 20:35:58 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:58 | D | sum error = [ 1.8741, 1.9772, 2.0930, 2.2217, 2.3635] +24-11-19 20:35:58 | D | best error = [ 1.3189, 1.3186, 1.3184, 1.3183, 1.3181] +24-11-19 20:35:58 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:58 | D | sum error = [ 2.5184, 2.6882, 2.8669, 3.0639, 3.2749] +24-11-19 20:35:58 | D | best error = [ 1.3180, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 20:35:58 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:58 | D | sum error = [ 3.4903, 3.7278, 3.9839, 4.2499, 4.5330] +24-11-19 20:35:58 | D | best error = [ 1.3179, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 20:35:58 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:58 | D | sum error = [ 4.8344, 5.1534, 5.4910, 5.8496, 6.2236] +24-11-19 20:35:58 | D | best error = [ 1.3179, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 20:35:58 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:58 | D | sum error = [ 6.6228, 7.0410, 7.4829, 7.9519, 8.4385] +24-11-19 20:35:58 | D | best error = [ 1.3179, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 20:35:58 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:58 | D | sum error = [ 8.9557, 9.5006, 10.0749, 10.6717, 11.3088] +24-11-19 20:35:58 | D | best error = [ 1.3179, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 20:35:58 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:58 | D | sum error = [ 11.9803, 12.6751, 13.4122, 14.1830, 14.9927] +24-11-19 20:35:58 | D | best error = [ 1.3179, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 20:35:58 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:58 | D | sum error = [ 15.8427, 16.7320, 17.6656, 18.6425, 19.6651] +24-11-19 20:35:58 | D | best error = [ 1.3179, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 20:35:58 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:58 | D | sum error = [ 20.7354, 21.8574, 23.0296, 24.2566, 25.5435] +24-11-19 20:35:58 | D | best error = [ 1.3179, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 20:35:58 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:58 | D | sum error = [ 26.8849, 28.2854, 29.7511, 31.2769, 32.8705] +24-11-19 20:35:58 | D | best error = [ 1.3179, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 20:35:58 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:58 | D | sum error = [ 34.5292, 36.2572, 38.0573, 39.9337, 41.8889] +24-11-19 20:35:58 | D | best error = [ 1.3179, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 20:35:58 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:58 | D | sum error = [ 43.9214, 46.0387, 48.2358, 50.5251, 52.8964] +24-11-19 20:35:58 | D | best error = [ 1.3179, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 20:35:58 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:58 | D | sum error = [ 55.3608, 57.9175, 60.5699, 63.3135, 66.1563] +24-11-19 20:35:58 | D | best error = [ 1.3179, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 20:35:58 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:58 | D | sum error = [ 69.0956, 72.1371, 75.2809, 78.5315, 81.8864] +24-11-19 20:35:58 | D | best error = [ 1.3179, 1.3179, 1.3179, 1.3179, 1.3179] +24-11-19 20:35:58 | D | + error = [1.3179] +24-11-19 20:35:58 | D | - Calibrating model.layers.23.mlp.up_proj.weight +24-11-19 20:35:58 | D | + w: sint8 +24-11-19 20:35:58 | D | + x: None +24-11-19 20:35:58 | D | + y: None +24-11-19 20:35:58 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:58 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:58 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:58 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:58 | D | - range ratio = [ 1.0000] +24-11-19 20:35:58 | D | sum error = [ 9.8258] +24-11-19 20:35:58 | D | best error = [ 9.8258] +24-11-19 20:35:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:59 | D | sum error = [ 9.7550, 9.7361, 9.7549, 9.8671, 10.0538] +24-11-19 20:35:59 | D | best error = [ 9.1277, 8.8528, 8.7000, 8.6134, 8.5642] +24-11-19 20:35:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:59 | D | sum error = [ 10.2793, 10.6346, 11.0885, 11.5907, 12.1701] +24-11-19 20:35:59 | D | best error = [ 8.5397, 8.5280, 8.5240, 8.5224, 8.5219] +24-11-19 20:35:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:59 | D | sum error = [ 12.8760, 13.6922, 14.5474, 15.5264, 16.6080] +24-11-19 20:35:59 | D | best error = [ 8.5218, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 20:35:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:59 | D | sum error = [ 17.7951, 19.0285, 20.3872, 21.8497, 23.4165] +24-11-19 20:35:59 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 20:35:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:59 | D | sum error = [ 25.0713, 26.8809, 28.7447, 30.7729, 32.9187] +24-11-19 20:35:59 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 20:35:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:59 | D | sum error = [ 35.1863, 37.5837, 40.1244, 42.8175, 45.6548] +24-11-19 20:35:59 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 20:35:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:59 | D | sum error = [ 48.6415, 51.7908, 55.1055, 58.5983, 62.2625] +24-11-19 20:35:59 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 20:35:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:59 | D | sum error = [ 66.1294, 70.2001, 74.4540, 78.9548, 83.6560] +24-11-19 20:35:59 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 20:35:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:59 | D | sum error = [ 88.6140, 93.8008, 99.2560, 104.9304, 110.9216] +24-11-19 20:35:59 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 20:35:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:59 | D | sum error = [ 117.1656, 123.7220, 130.5776, 137.7428, 145.1950] +24-11-19 20:35:59 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 20:35:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:59 | D | sum error = [ 153.0223, 161.1801, 169.6923, 178.5603, 187.8251] +24-11-19 20:35:59 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 20:35:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:59 | D | sum error = [ 197.4831, 207.5079, 217.9626, 228.8318, 240.1382] +24-11-19 20:35:59 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 20:35:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:59 | D | sum error = [ 251.9084, 264.1196, 276.8060, 289.9453, 303.5847] +24-11-19 20:35:59 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 20:35:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:59 | D | sum error = [ 317.7191, 332.3501, 347.4858, 363.1297, 379.3219] +24-11-19 20:35:59 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 20:35:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:59 | D | sum error = [ 396.0543, 413.3405, 431.2033, 449.6161, 468.6251] +24-11-19 20:35:59 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 20:35:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:59 | D | sum error = [ 488.2025, 508.3647, 529.1073, 550.4454, 572.3897] +24-11-19 20:35:59 | D | best error = [ 8.5217, 8.5217, 8.5217, 8.5217, 8.5217] +24-11-19 20:35:59 | D | + error = [8.5217] +24-11-19 20:36:00 | D | - Calibrating model.layers.23.mlp.gate_proj.weight +24-11-19 20:36:00 | D | + w: sint8 +24-11-19 20:36:00 | D | + x: None +24-11-19 20:36:00 | D | + y: None +24-11-19 20:36:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:00 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:36:00 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:36:00 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:36:00 | D | - range ratio = [ 1.0000] +24-11-19 20:36:00 | D | sum error = [ 10.5800] +24-11-19 20:36:00 | D | best error = [ 10.5800] +24-11-19 20:36:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:01 | D | sum error = [ 10.4923, 10.4795, 10.5359, 10.6543, 10.8388] +24-11-19 20:36:01 | D | best error = [ 9.8185, 9.5221, 9.3598, 9.2694, 9.2152] +24-11-19 20:36:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:01 | D | sum error = [ 11.1484, 11.4905, 11.9715, 12.5280, 13.1557] +24-11-19 20:36:01 | D | best error = [ 9.1914, 9.1795, 9.1759, 9.1748, 9.1745] +24-11-19 20:36:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:01 | D | sum error = [ 13.9366, 14.7882, 15.7767, 16.8211, 18.0015] +24-11-19 20:36:01 | D | best error = [ 9.1745, 9.1745, 9.1745, 9.1745, 9.1745] +24-11-19 20:36:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:01 | D | sum error = [ 19.2700, 20.6379, 22.1343, 23.7195, 25.4411] +24-11-19 20:36:01 | D | best error = [ 9.1745, 9.1745, 9.1745, 9.1745, 9.1745] +24-11-19 20:36:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:01 | D | sum error = [ 27.2432, 29.1692, 31.2740, 33.4756, 35.8267] +24-11-19 20:36:01 | D | best error = [ 9.1745, 9.1745, 9.1745, 9.1745, 9.1745] +24-11-19 20:36:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:01 | D | sum error = [ 38.3223, 40.9617, 43.7763, 46.7293, 49.8915] +24-11-19 20:36:01 | D | best error = [ 9.1745, 9.1745, 9.1745, 9.1745, 9.1745] +24-11-19 20:36:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:01 | D | sum error = [ 53.1863, 56.7060, 60.3903, 64.3074, 68.4364] +24-11-19 20:36:01 | D | best error = [ 9.1745, 9.1745, 9.1745, 9.1745, 9.1745] +24-11-19 20:36:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:01 | D | sum error = [ 72.7874, 77.3853, 82.1982, 87.2885, 92.6531] +24-11-19 20:36:01 | D | best error = [ 9.1745, 9.1745, 9.1745, 9.1745, 9.1745] +24-11-19 20:36:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:01 | D | sum error = [ 98.3011, 104.2509, 110.5288, 117.0997, 124.0444] +24-11-19 20:36:01 | D | best error = [ 9.1745, 9.1745, 9.1745, 9.1745, 9.1745] +24-11-19 20:36:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:01 | D | sum error = [ 131.3331, 138.9841, 147.0441, 155.4820, 164.3398] +24-11-19 20:36:01 | D | best error = [ 9.1745, 9.1745, 9.1745, 9.1745, 9.1745] +24-11-19 20:36:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:01 | D | sum error = [ 173.6305, 183.3488, 193.5540, 204.2357, 215.4629] +24-11-19 20:36:01 | D | best error = [ 9.1745, 9.1745, 9.1745, 9.1745, 9.1745] +24-11-19 20:36:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:01 | D | sum error = [ 227.1643, 239.4222, 252.2239, 265.5799, 279.5441] +24-11-19 20:36:01 | D | best error = [ 9.1745, 9.1745, 9.1745, 9.1745, 9.1745] +24-11-19 20:36:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:01 | D | sum error = [ 294.1125, 309.2928, 325.1086, 341.5979, 358.7573] +24-11-19 20:36:01 | D | best error = [ 9.1745, 9.1745, 9.1745, 9.1745, 9.1745] +24-11-19 20:36:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:01 | D | sum error = [ 376.6160, 395.2066, 414.5144, 434.5788, 455.3841] +24-11-19 20:36:01 | D | best error = [ 9.1745, 9.1745, 9.1745, 9.1745, 9.1745] +24-11-19 20:36:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:01 | D | sum error = [ 476.9589, 499.3137, 522.4515, 546.4021, 571.2025] +24-11-19 20:36:01 | D | best error = [ 9.1745, 9.1745, 9.1745, 9.1745, 9.1745] +24-11-19 20:36:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:01 | D | sum error = [ 596.7633, 623.1838, 650.4279, 678.5203, 707.4457] +24-11-19 20:36:01 | D | best error = [ 9.1745, 9.1745, 9.1745, 9.1745, 9.1745] +24-11-19 20:36:01 | D | + error = [9.1745] +24-11-19 20:36:01 | D | - Calibrating model.layers.23.mlp.down_proj.weight +24-11-19 20:36:01 | D | + w: sint8 +24-11-19 20:36:01 | D | + x: None +24-11-19 20:36:01 | D | + y: None +24-11-19 20:36:01 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:01 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:36:01 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:36:01 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:36:01 | D | - range ratio = [ 1.0000] +24-11-19 20:36:01 | D | sum error = [ 3.8379] +24-11-19 20:36:01 | D | best error = [ 3.8379] +24-11-19 20:36:02 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:02 | D | sum error = [ 3.7954, 3.7729, 3.7509, 3.7441, 3.7602] +24-11-19 20:36:02 | D | best error = [ 3.6766, 3.5964, 3.5432, 3.5018, 3.4736] +24-11-19 20:36:02 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:02 | D | sum error = [ 3.7767, 3.8179, 3.8669, 3.9414, 4.0336] +24-11-19 20:36:02 | D | best error = [ 3.4526, 3.4372, 3.4247, 3.4156, 3.4107] +24-11-19 20:36:02 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:02 | D | sum error = [ 4.1594, 4.2996, 4.4627, 4.6613, 4.8931] +24-11-19 20:36:02 | D | best error = [ 3.4067, 3.4044, 3.4022, 3.4011, 3.4006] +24-11-19 20:36:02 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:02 | D | sum error = [ 5.1556, 5.4442, 5.7617, 6.1162, 6.5145] +24-11-19 20:36:02 | D | best error = [ 3.4001, 3.3999, 3.3998, 3.3997, 3.3997] +24-11-19 20:36:02 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:02 | D | sum error = [ 6.9463, 7.4088, 7.8998, 8.4457, 9.0283] +24-11-19 20:36:02 | D | best error = [ 3.3996, 3.3996, 3.3996, 3.3996, 3.3996] +24-11-19 20:36:02 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:02 | D | sum error = [ 9.6554, 10.3366, 11.0570, 11.8279, 12.6447] +24-11-19 20:36:02 | D | best error = [ 3.3996, 3.3996, 3.3996, 3.3996, 3.3996] +24-11-19 20:36:02 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:02 | D | sum error = [ 13.5212, 14.4464, 15.4498, 16.4961, 17.6101] +24-11-19 20:36:02 | D | best error = [ 3.3996, 3.3996, 3.3996, 3.3996, 3.3996] +24-11-19 20:36:02 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:02 | D | sum error = [ 18.7995, 20.0560, 21.3874, 22.7911, 24.2801] +24-11-19 20:36:02 | D | best error = [ 3.3996, 3.3996, 3.3996, 3.3996, 3.3996] +24-11-19 20:36:02 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:02 | D | sum error = [ 25.8466, 27.5079, 29.2537, 31.1128, 33.0570] +24-11-19 20:36:02 | D | best error = [ 3.3996, 3.3996, 3.3996, 3.3996, 3.3996] +24-11-19 20:36:02 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:02 | D | sum error = [ 35.1063, 37.2663, 39.5352, 41.9203, 44.4215] +24-11-19 20:36:02 | D | best error = [ 3.3996, 3.3996, 3.3996, 3.3996, 3.3996] +24-11-19 20:36:02 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:02 | D | sum error = [ 47.0549, 49.8128, 52.6991, 55.7359, 58.9149] +24-11-19 20:36:02 | D | best error = [ 3.3996, 3.3996, 3.3996, 3.3996, 3.3996] +24-11-19 20:36:02 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:02 | D | sum error = [ 62.2388, 65.7177, 69.3528, 73.1644, 77.1380] +24-11-19 20:36:02 | D | best error = [ 3.3996, 3.3996, 3.3996, 3.3996, 3.3996] +24-11-19 20:36:02 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:02 | D | sum error = [ 81.2879, 85.6141, 90.1275, 94.8293, 99.7175] +24-11-19 20:36:02 | D | best error = [ 3.3996, 3.3996, 3.3996, 3.3996, 3.3996] +24-11-19 20:36:02 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:02 | D | sum error = [ 104.8123, 110.0999, 115.6007, 121.3222, 127.2491] +24-11-19 20:36:02 | D | best error = [ 3.3996, 3.3996, 3.3996, 3.3996, 3.3996] +24-11-19 20:36:02 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:02 | D | sum error = [ 133.4109, 139.7947, 146.4200, 153.2722, 160.3734] +24-11-19 20:36:02 | D | best error = [ 3.3996, 3.3996, 3.3996, 3.3996, 3.3996] +24-11-19 20:36:02 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:02 | D | sum error = [ 167.7142, 175.2981, 183.1395, 191.2298, 199.5811] +24-11-19 20:36:02 | D | best error = [ 3.3996, 3.3996, 3.3996, 3.3996, 3.3996] +24-11-19 20:36:02 | D | + error = [3.3996] +24-11-19 20:36:02 | D | - Quantizing model.layers.23.self_attn.q_proj.weight +24-11-19 20:36:03 | D | - Quantizing model.layers.23.self_attn.k_proj.weight +24-11-19 20:36:04 | D | - Quantizing model.layers.23.self_attn.v_proj.weight +24-11-19 20:36:05 | D | - Quantizing model.layers.23.self_attn.o_proj.weight +24-11-19 20:36:06 | D | - Quantizing model.layers.23.mlp.up_proj.weight +24-11-19 20:36:07 | D | - Quantizing model.layers.23.mlp.gate_proj.weight +24-11-19 20:36:08 | D | - Quantizing model.layers.23.mlp.down_proj.weight +24-11-19 20:36:16 | D | - Quantizing layer model.layers.24 +24-11-19 20:36:16 | D | - Calibrating model.layers.24.self_attn.q_proj.weight +24-11-19 20:36:16 | D | + w: sint8 +24-11-19 20:36:16 | D | + x: None +24-11-19 20:36:16 | D | + y: None +24-11-19 20:36:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:36:16 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:36:16 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:36:16 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:36:16 | D | - range ratio = [ 1.0000] +24-11-19 20:36:16 | D | sum error = [ 15.6393] +24-11-19 20:36:16 | D | best error = [ 15.6393] +24-11-19 20:36:30 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:30 | D | sum error = [ 15.3587, 15.3345, 15.4868, 15.7388, 16.3210] +24-11-19 20:36:30 | D | best error = [ 15.3587, 15.3345, 15.3345, 15.3345, 15.3345] +24-11-19 20:36:30 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:30 | D | sum error = [ 16.4341, 17.3818, 17.8221, 18.8072, 21.1483] +24-11-19 20:36:30 | D | best error = [ 15.3345, 15.3345, 15.3345, 15.3345, 15.3345] +24-11-19 20:36:30 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:30 | D | sum error = [ 21.9482, 23.0665, 24.8478, 26.7380, 29.0945] +24-11-19 20:36:30 | D | best error = [ 15.3345, 15.3345, 15.3345, 15.3345, 15.3345] +24-11-19 20:36:30 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:30 | D | sum error = [ 30.8028, 33.4834, 35.4575, 39.2637, 42.2314] +24-11-19 20:36:30 | D | best error = [ 15.3345, 15.3345, 15.3345, 15.3345, 15.3345] +24-11-19 20:36:30 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:30 | D | sum error = [ 46.5558, 49.7349, 52.6374, 57.5693, 61.8135] +24-11-19 20:36:30 | D | best error = [ 15.3345, 15.3345, 15.3345, 15.3345, 15.3345] +24-11-19 20:36:30 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:30 | D | sum error = [ 66.8888, 71.8934, 78.2452, 82.7966, 89.2830] +24-11-19 20:36:30 | D | best error = [ 15.3345, 15.3345, 15.3345, 15.3345, 15.3345] +24-11-19 20:36:30 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:30 | D | sum error = [ 96.6298, 104.2348, 111.7329, 120.4028, 128.8365] +24-11-19 20:36:30 | D | best error = [ 15.3345, 15.3345, 15.3345, 15.3345, 15.3345] +24-11-19 20:36:30 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:30 | D | sum error = [ 139.9617, 149.9731, 161.7180, 173.4238, 185.9551] +24-11-19 20:36:30 | D | best error = [ 15.3345, 15.3345, 15.3345, 15.3345, 15.3345] +24-11-19 20:36:30 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:30 | D | sum error = [ 201.1063, 215.3250, 230.5677, 248.2256, 266.2329] +24-11-19 20:36:30 | D | best error = [ 15.3345, 15.3345, 15.3345, 15.3345, 15.3345] +24-11-19 20:36:30 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:30 | D | sum error = [ 285.5509, 305.5789, 327.7280, 352.5070, 377.2007] +24-11-19 20:36:30 | D | best error = [ 15.3345, 15.3345, 15.3345, 15.3345, 15.3345] +24-11-19 20:36:30 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:30 | D | sum error = [ 403.8233, 431.5468, 461.8980, 494.1353, 528.0784] +24-11-19 20:36:30 | D | best error = [ 15.3345, 15.3345, 15.3345, 15.3345, 15.3345] +24-11-19 20:36:30 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:30 | D | sum error = [ 565.5596, 605.5306, 647.2603, 693.0264, 742.7298] +24-11-19 20:36:30 | D | best error = [ 15.3345, 15.3345, 15.3345, 15.3345, 15.3345] +24-11-19 20:36:30 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:30 | D | sum error = [ 795.1778, 852.9194, 914.4080, 981.0884, 1055.0674] +24-11-19 20:36:30 | D | best error = [ 15.3345, 15.3345, 15.3345, 15.3345, 15.3345] +24-11-19 20:36:30 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:30 | D | sum error = [ 1133.5081, 1220.1558, 1314.1733, 1417.8470, 1527.9779] +24-11-19 20:36:30 | D | best error = [ 15.3345, 15.3345, 15.3345, 15.3345, 15.3345] +24-11-19 20:36:30 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:30 | D | sum error = [ 1650.3079, 1782.3647, 1926.7419, 2085.8016, 2258.0866] +24-11-19 20:36:30 | D | best error = [ 15.3345, 15.3345, 15.3345, 15.3345, 15.3345] +24-11-19 20:36:30 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:30 | D | sum error = [ 2447.5338, 2654.8657, 2877.4881, 3116.1142, 3372.8968] +24-11-19 20:36:30 | D | best error = [ 15.3345, 15.3345, 15.3345, 15.3345, 15.3345] +24-11-19 20:36:30 | D | + error = [15.3345] +24-11-19 20:36:30 | D | - Calibrating model.layers.24.self_attn.k_proj.weight +24-11-19 20:36:30 | D | + w: sint8 +24-11-19 20:36:30 | D | + x: None +24-11-19 20:36:30 | D | + y: None +24-11-19 20:36:30 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:36:30 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:36:30 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:36:31 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:36:31 | D | - range ratio = [ 1.0000] +24-11-19 20:36:31 | D | sum error = [ 19.6612] +24-11-19 20:36:31 | D | best error = [ 19.6612] +24-11-19 20:36:44 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:44 | D | sum error = [ 18.7800, 19.5191, 17.9717, 17.7818, 19.0473] +24-11-19 20:36:44 | D | best error = [ 18.7800, 18.7800, 17.9717, 17.7818, 17.7818] +24-11-19 20:36:44 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:44 | D | sum error = [ 20.1760, 21.4053, 20.9366, 22.5987, 23.0447] +24-11-19 20:36:44 | D | best error = [ 17.7818, 17.7818, 17.7818, 17.7818, 17.7818] +24-11-19 20:36:44 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:44 | D | sum error = [ 25.1813, 26.4179, 27.6379, 31.6704, 31.3791] +24-11-19 20:36:44 | D | best error = [ 17.7818, 17.7818, 17.7818, 17.7818, 17.7818] +24-11-19 20:36:44 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:44 | D | sum error = [ 33.7376, 36.6793, 38.6667, 42.7295, 46.7944] +24-11-19 20:36:44 | D | best error = [ 17.7818, 17.7818, 17.7818, 17.7818, 17.7818] +24-11-19 20:36:44 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:44 | D | sum error = [ 49.5477, 52.6153, 55.9405, 61.0503, 66.4805] +24-11-19 20:36:44 | D | best error = [ 17.7818, 17.7818, 17.7818, 17.7818, 17.7818] +24-11-19 20:36:44 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:44 | D | sum error = [ 69.8544, 78.0085, 81.9411, 86.9206, 93.4846] +24-11-19 20:36:44 | D | best error = [ 17.7818, 17.7818, 17.7818, 17.7818, 17.7818] +24-11-19 20:36:44 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:44 | D | sum error = [ 99.7000, 107.7443, 115.5603, 124.7701, 136.4279] +24-11-19 20:36:44 | D | best error = [ 17.7818, 17.7818, 17.7818, 17.7818, 17.7818] +24-11-19 20:36:44 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:44 | D | sum error = [ 144.4053, 155.2996, 167.7235, 182.0729, 193.9343] +24-11-19 20:36:44 | D | best error = [ 17.7818, 17.7818, 17.7818, 17.7818, 17.7818] +24-11-19 20:36:44 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:44 | D | sum error = [ 206.8858, 224.4513, 240.9721, 258.6183, 277.1611] +24-11-19 20:36:44 | D | best error = [ 17.7818, 17.7818, 17.7818, 17.7818, 17.7818] +24-11-19 20:36:44 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:44 | D | sum error = [ 296.7921, 316.2086, 339.9365, 363.1897, 388.3788] +24-11-19 20:36:44 | D | best error = [ 17.7818, 17.7818, 17.7818, 17.7818, 17.7818] +24-11-19 20:36:44 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:44 | D | sum error = [ 416.8184, 444.3678, 478.1766, 506.8693, 541.4200] +24-11-19 20:36:44 | D | best error = [ 17.7818, 17.7818, 17.7818, 17.7818, 17.7818] +24-11-19 20:36:44 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:44 | D | sum error = [ 579.4763, 618.9849, 661.5429, 709.1046, 761.9796] +24-11-19 20:36:44 | D | best error = [ 17.7818, 17.7818, 17.7818, 17.7818, 17.7818] +24-11-19 20:36:44 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:44 | D | sum error = [ 818.4742, 878.0621, 942.0481, 1012.3946, 1089.1607] +24-11-19 20:36:44 | D | best error = [ 17.7818, 17.7818, 17.7818, 17.7818, 17.7818] +24-11-19 20:36:44 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:44 | D | sum error = [ 1171.6528, 1263.0273, 1358.8209, 1466.0460, 1582.3761] +24-11-19 20:36:44 | D | best error = [ 17.7818, 17.7818, 17.7818, 17.7818, 17.7818] +24-11-19 20:36:44 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:44 | D | sum error = [ 1713.4802, 1856.5628, 2010.1187, 2185.8573, 2365.0710] +24-11-19 20:36:44 | D | best error = [ 17.7818, 17.7818, 17.7818, 17.7818, 17.7818] +24-11-19 20:36:44 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:44 | D | sum error = [ 2561.1878, 2771.7798, 3000.0477, 3242.6878, 3503.4343] +24-11-19 20:36:44 | D | best error = [ 17.7818, 17.7818, 17.7818, 17.7818, 17.7818] +24-11-19 20:36:44 | D | + error = [17.7818] +24-11-19 20:36:44 | D | - Calibrating model.layers.24.self_attn.v_proj.weight +24-11-19 20:36:44 | D | + w: sint8 +24-11-19 20:36:44 | D | + x: None +24-11-19 20:36:44 | D | + y: None +24-11-19 20:36:44 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:44 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:36:44 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:36:44 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:36:44 | D | - range ratio = [ 1.0000] +24-11-19 20:36:44 | D | sum error = [ 7.5830] +24-11-19 20:36:44 | D | best error = [ 7.5830] +24-11-19 20:36:44 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:44 | D | sum error = [ 7.4948, 7.4980, 7.5469, 7.6342, 7.7739] +24-11-19 20:36:44 | D | best error = [ 7.0514, 6.8502, 6.7476, 6.6821, 6.6460] +24-11-19 20:36:44 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:44 | D | sum error = [ 7.9658, 8.2178, 8.5667, 8.9477, 9.4384] +24-11-19 20:36:44 | D | best error = [ 6.6286, 6.6209, 6.6179, 6.6164, 6.6164] +24-11-19 20:36:44 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:44 | D | sum error = [ 10.0046, 10.5969, 11.2812, 12.0596, 12.8549] +24-11-19 20:36:44 | D | best error = [ 6.6163, 6.6163, 6.6163, 6.6163, 6.6163] +24-11-19 20:36:44 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:44 | D | sum error = [ 13.7971, 14.7656, 15.8220, 16.9398, 18.1523] +24-11-19 20:36:44 | D | best error = [ 6.6163, 6.6163, 6.6163, 6.6163, 6.6163] +24-11-19 20:36:44 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:44 | D | sum error = [ 19.4641, 20.8264, 22.3029, 23.8333, 25.4943] +24-11-19 20:36:44 | D | best error = [ 6.6163, 6.6163, 6.6163, 6.6163, 6.6163] +24-11-19 20:36:44 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:44 | D | sum error = [ 27.2448, 29.0678, 31.0167, 33.1077, 35.2635] +24-11-19 20:36:44 | D | best error = [ 6.6163, 6.6163, 6.6163, 6.6163, 6.6163] +24-11-19 20:36:44 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:44 | D | sum error = [ 37.5320, 39.9561, 42.5059, 45.1705, 47.9822] +24-11-19 20:36:44 | D | best error = [ 6.6163, 6.6163, 6.6163, 6.6163, 6.6163] +24-11-19 20:36:44 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:44 | D | sum error = [ 50.9508, 54.0658, 57.3358, 60.7352, 64.3621] +24-11-19 20:36:44 | D | best error = [ 6.6163, 6.6163, 6.6163, 6.6163, 6.6163] +24-11-19 20:36:44 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:44 | D | sum error = [ 68.1362, 72.1079, 76.2861, 80.5923, 85.1690] +24-11-19 20:36:44 | D | best error = [ 6.6163, 6.6163, 6.6163, 6.6163, 6.6163] +24-11-19 20:36:44 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:44 | D | sum error = [ 89.9192, 94.9047, 100.1079, 105.5362, 111.2277] +24-11-19 20:36:44 | D | best error = [ 6.6163, 6.6163, 6.6163, 6.6163, 6.6163] +24-11-19 20:36:44 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:44 | D | sum error = [ 117.1257, 123.3117, 129.7349, 136.4517, 143.4206] +24-11-19 20:36:44 | D | best error = [ 6.6163, 6.6163, 6.6163, 6.6163, 6.6163] +24-11-19 20:36:44 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:44 | D | sum error = [ 150.6837, 158.2027, 166.0578, 174.1692, 182.6122] +24-11-19 20:36:44 | D | best error = [ 6.6163, 6.6163, 6.6163, 6.6163, 6.6163] +24-11-19 20:36:44 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:44 | D | sum error = [ 191.3755, 200.4568, 209.8687, 219.6421, 229.7508] +24-11-19 20:36:44 | D | best error = [ 6.6163, 6.6163, 6.6163, 6.6163, 6.6163] +24-11-19 20:36:44 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:44 | D | sum error = [ 240.2089, 251.0323, 262.2170, 273.7909, 285.7111] +24-11-19 20:36:44 | D | best error = [ 6.6163, 6.6163, 6.6163, 6.6163, 6.6163] +24-11-19 20:36:44 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:44 | D | sum error = [ 298.0135, 310.7097, 323.7942, 337.2677, 351.1611] +24-11-19 20:36:44 | D | best error = [ 6.6163, 6.6163, 6.6163, 6.6163, 6.6163] +24-11-19 20:36:44 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:44 | D | sum error = [ 365.4424, 380.1419, 395.2746, 410.8474, 426.8680] +24-11-19 20:36:44 | D | best error = [ 6.6163, 6.6163, 6.6163, 6.6163, 6.6163] +24-11-19 20:36:44 | D | + error = [6.6163] +24-11-19 20:36:44 | D | - Calibrating model.layers.24.self_attn.o_proj.weight +24-11-19 20:36:44 | D | + w: sint8 +24-11-19 20:36:44 | D | + x: None +24-11-19 20:36:44 | D | + y: None +24-11-19 20:36:44 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:44 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:36:45 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:36:45 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:36:45 | D | - range ratio = [ 1.0000] +24-11-19 20:36:45 | D | sum error = [ 1.6953] +24-11-19 20:36:45 | D | best error = [ 1.6953] +24-11-19 20:36:45 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:45 | D | sum error = [ 1.6807, 1.6694, 1.6710, 1.6757, 1.6906] +24-11-19 20:36:45 | D | best error = [ 1.5744, 1.5195, 1.4884, 1.4671, 1.4519] +24-11-19 20:36:45 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:45 | D | sum error = [ 1.7202, 1.7566, 1.8016, 1.8590, 1.9346] +24-11-19 20:36:45 | D | best error = [ 1.4422, 1.4341, 1.4291, 1.4255, 1.4234] +24-11-19 20:36:45 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:45 | D | sum error = [ 2.0275, 2.1277, 2.2327, 2.3608, 2.5033] +24-11-19 20:36:45 | D | best error = [ 1.4218, 1.4208, 1.4200, 1.4195, 1.4191] +24-11-19 20:36:45 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:45 | D | sum error = [ 2.6604, 2.8323, 3.0168, 3.2225, 3.4414] +24-11-19 20:36:45 | D | best error = [ 1.4190, 1.4188, 1.4186, 1.4185, 1.4185] +24-11-19 20:36:45 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:45 | D | sum error = [ 3.6850, 3.9413, 4.2101, 4.4977, 4.8086] +24-11-19 20:36:45 | D | best error = [ 1.4184, 1.4184, 1.4184, 1.4184, 1.4184] +24-11-19 20:36:45 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:45 | D | sum error = [ 5.1364, 5.4920, 5.8586, 6.2471, 6.6671] +24-11-19 20:36:45 | D | best error = [ 1.4184, 1.4184, 1.4184, 1.4184, 1.4184] +24-11-19 20:36:45 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:45 | D | sum error = [ 7.1174, 7.5852, 8.0776, 8.6037, 9.1574] +24-11-19 20:36:45 | D | best error = [ 1.4184, 1.4184, 1.4184, 1.4184, 1.4184] +24-11-19 20:36:45 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:45 | D | sum error = [ 9.7465, 10.3736, 11.0283, 11.7265, 12.4602] +24-11-19 20:36:45 | D | best error = [ 1.4184, 1.4184, 1.4184, 1.4184, 1.4184] +24-11-19 20:36:45 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:45 | D | sum error = [ 13.2347, 14.0558, 14.9235, 15.8381, 16.7985] +24-11-19 20:36:45 | D | best error = [ 1.4184, 1.4184, 1.4184, 1.4184, 1.4184] +24-11-19 20:36:45 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:45 | D | sum error = [ 17.8124, 18.8808, 19.9998, 21.1794, 22.4241] +24-11-19 20:36:45 | D | best error = [ 1.4184, 1.4184, 1.4184, 1.4184, 1.4184] +24-11-19 20:36:45 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:45 | D | sum error = [ 23.7275, 25.1057, 26.5469, 28.0613, 29.6553] +24-11-19 20:36:45 | D | best error = [ 1.4184, 1.4184, 1.4184, 1.4184, 1.4184] +24-11-19 20:36:45 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:45 | D | sum error = [ 31.3219, 33.0724, 34.9121, 36.8418, 38.8643] +24-11-19 20:36:45 | D | best error = [ 1.4184, 1.4184, 1.4184, 1.4184, 1.4184] +24-11-19 20:36:45 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:45 | D | sum error = [ 40.9783, 43.1889, 45.5070, 47.9286, 50.4568] +24-11-19 20:36:45 | D | best error = [ 1.4184, 1.4184, 1.4184, 1.4184, 1.4184] +24-11-19 20:36:45 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:45 | D | sum error = [ 53.0974, 55.8501, 58.7240, 61.7210, 64.8267] +24-11-19 20:36:45 | D | best error = [ 1.4184, 1.4184, 1.4184, 1.4184, 1.4184] +24-11-19 20:36:45 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:45 | D | sum error = [ 68.0572, 71.4179, 74.8999, 78.5140, 82.2635] +24-11-19 20:36:45 | D | best error = [ 1.4184, 1.4184, 1.4184, 1.4184, 1.4184] +24-11-19 20:36:45 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:45 | D | sum error = [ 86.1475, 90.1826, 94.3574, 98.6794, 103.1510] +24-11-19 20:36:45 | D | best error = [ 1.4184, 1.4184, 1.4184, 1.4184, 1.4184] +24-11-19 20:36:45 | D | + error = [1.4184] +24-11-19 20:36:45 | D | - Calibrating model.layers.24.mlp.up_proj.weight +24-11-19 20:36:45 | D | + w: sint8 +24-11-19 20:36:45 | D | + x: None +24-11-19 20:36:45 | D | + y: None +24-11-19 20:36:45 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:45 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:36:45 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:36:45 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:36:46 | D | - range ratio = [ 1.0000] +24-11-19 20:36:46 | D | sum error = [ 10.1795] +24-11-19 20:36:46 | D | best error = [ 10.1795] +24-11-19 20:36:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:46 | D | sum error = [ 10.0910, 10.0499, 10.0861, 10.2409, 10.3964] +24-11-19 20:36:46 | D | best error = [ 9.4023, 9.1065, 8.9462, 8.8595, 8.8090] +24-11-19 20:36:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:46 | D | sum error = [ 10.6639, 11.0446, 11.4702, 12.0138, 12.6394] +24-11-19 20:36:46 | D | best error = [ 8.7846, 8.7731, 8.7682, 8.7667, 8.7664] +24-11-19 20:36:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:46 | D | sum error = [ 13.3529, 14.2022, 15.0932, 16.1366, 17.2342] +24-11-19 20:36:46 | D | best error = [ 8.7664, 8.7664, 8.7664, 8.7664, 8.7664] +24-11-19 20:36:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:46 | D | sum error = [ 18.4309, 19.7369, 21.1777, 22.6627, 24.2799] +24-11-19 20:36:46 | D | best error = [ 8.7664, 8.7664, 8.7664, 8.7664, 8.7664] +24-11-19 20:36:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:46 | D | sum error = [ 26.0479, 27.8856, 29.8479, 31.9226, 34.1463] +24-11-19 20:36:46 | D | best error = [ 8.7664, 8.7664, 8.7664, 8.7664, 8.7664] +24-11-19 20:36:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:46 | D | sum error = [ 36.4885, 38.9604, 41.5910, 44.3363, 47.2608] +24-11-19 20:36:46 | D | best error = [ 8.7664, 8.7664, 8.7664, 8.7664, 8.7664] +24-11-19 20:36:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:46 | D | sum error = [ 50.3604, 53.5841, 57.0059, 60.6048, 64.4000] +24-11-19 20:36:46 | D | best error = [ 8.7664, 8.7664, 8.7664, 8.7664, 8.7664] +24-11-19 20:36:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:46 | D | sum error = [ 68.3631, 72.5928, 76.9905, 81.6378, 86.4941] +24-11-19 20:36:46 | D | best error = [ 8.7664, 8.7664, 8.7664, 8.7664, 8.7664] +24-11-19 20:36:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:46 | D | sum error = [ 91.6059, 96.9664, 102.5994, 108.4740, 114.6401] +24-11-19 20:36:46 | D | best error = [ 8.7664, 8.7664, 8.7664, 8.7664, 8.7664] +24-11-19 20:36:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:46 | D | sum error = [ 121.1263, 127.8743, 134.9558, 142.3323, 150.0545] +24-11-19 20:36:46 | D | best error = [ 8.7664, 8.7664, 8.7664, 8.7664, 8.7664] +24-11-19 20:36:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:46 | D | sum error = [ 158.1164, 166.5091, 175.2684, 184.4024, 193.9127] +24-11-19 20:36:46 | D | best error = [ 8.7664, 8.7664, 8.7664, 8.7664, 8.7664] +24-11-19 20:36:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:46 | D | sum error = [ 203.8136, 214.1278, 224.8459, 235.9989, 247.5711] +24-11-19 20:36:46 | D | best error = [ 8.7664, 8.7664, 8.7664, 8.7664, 8.7664] +24-11-19 20:36:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:46 | D | sum error = [ 259.5905, 272.0710, 285.0220, 298.4292, 312.3332] +24-11-19 20:36:46 | D | best error = [ 8.7664, 8.7664, 8.7664, 8.7664, 8.7664] +24-11-19 20:36:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:46 | D | sum error = [ 326.7241, 341.6386, 357.0577, 372.9933, 389.4690] +24-11-19 20:36:46 | D | best error = [ 8.7664, 8.7664, 8.7664, 8.7664, 8.7664] +24-11-19 20:36:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:46 | D | sum error = [ 406.4871, 424.0423, 442.1523, 460.8255, 480.0774] +24-11-19 20:36:46 | D | best error = [ 8.7664, 8.7664, 8.7664, 8.7664, 8.7664] +24-11-19 20:36:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:46 | D | sum error = [ 499.8643, 520.2679, 541.2364, 562.8000, 584.9595] +24-11-19 20:36:46 | D | best error = [ 8.7664, 8.7664, 8.7664, 8.7664, 8.7664] +24-11-19 20:36:46 | D | + error = [8.7664] +24-11-19 20:36:47 | D | - Calibrating model.layers.24.mlp.gate_proj.weight +24-11-19 20:36:47 | D | + w: sint8 +24-11-19 20:36:47 | D | + x: None +24-11-19 20:36:47 | D | + y: None +24-11-19 20:36:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:47 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:36:47 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:36:47 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:36:47 | D | - range ratio = [ 1.0000] +24-11-19 20:36:47 | D | sum error = [ 10.9378] +24-11-19 20:36:47 | D | best error = [ 10.9378] +24-11-19 20:36:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:48 | D | sum error = [ 10.8679, 10.8292, 10.8482, 10.9821, 11.1959] +24-11-19 20:36:48 | D | best error = [ 10.1234, 9.8019, 9.6278, 9.5264, 9.4697] +24-11-19 20:36:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:48 | D | sum error = [ 11.4689, 11.8782, 12.3430, 12.9485, 13.6202] +24-11-19 20:36:48 | D | best error = [ 9.4416, 9.4300, 9.4248, 9.4232, 9.4228] +24-11-19 20:36:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:48 | D | sum error = [ 14.4039, 15.2861, 16.3278, 17.4119, 18.6367] +24-11-19 20:36:48 | D | best error = [ 9.4228, 9.4228, 9.4228, 9.4228, 9.4228] +24-11-19 20:36:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:48 | D | sum error = [ 19.9511, 21.3941, 22.9412, 24.6145, 26.4160] +24-11-19 20:36:48 | D | best error = [ 9.4228, 9.4228, 9.4228, 9.4228, 9.4228] +24-11-19 20:36:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:48 | D | sum error = [ 28.3298, 30.3531, 32.4962, 34.8235, 37.2552] +24-11-19 20:36:48 | D | best error = [ 9.4228, 9.4228, 9.4228, 9.4228, 9.4228] +24-11-19 20:36:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:48 | D | sum error = [ 39.8651, 42.5908, 45.5257, 48.6078, 51.8860] +24-11-19 20:36:48 | D | best error = [ 9.4228, 9.4228, 9.4228, 9.4228, 9.4228] +24-11-19 20:36:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:48 | D | sum error = [ 55.3161, 58.9605, 62.7989, 66.8479, 71.1101] +24-11-19 20:36:48 | D | best error = [ 9.4228, 9.4228, 9.4228, 9.4228, 9.4228] +24-11-19 20:36:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:48 | D | sum error = [ 75.6204, 80.3600, 85.3463, 90.6182, 96.1442] +24-11-19 20:36:48 | D | best error = [ 9.4228, 9.4228, 9.4228, 9.4228, 9.4228] +24-11-19 20:36:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:48 | D | sum error = [ 102.0065, 108.0832, 114.5329, 121.2581, 128.3413] +24-11-19 20:36:48 | D | best error = [ 9.4228, 9.4228, 9.4228, 9.4228, 9.4228] +24-11-19 20:36:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:48 | D | sum error = [ 135.8363, 143.7012, 151.8970, 160.5529, 169.5837] +24-11-19 20:36:48 | D | best error = [ 9.4228, 9.4228, 9.4228, 9.4228, 9.4228] +24-11-19 20:36:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:48 | D | sum error = [ 179.0515, 189.0084, 199.4301, 210.3216, 221.7231] +24-11-19 20:36:48 | D | best error = [ 9.4228, 9.4228, 9.4228, 9.4228, 9.4228] +24-11-19 20:36:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:48 | D | sum error = [ 233.6553, 246.1305, 259.1499, 272.7186, 286.8741] +24-11-19 20:36:48 | D | best error = [ 9.4228, 9.4228, 9.4228, 9.4228, 9.4228] +24-11-19 20:36:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:48 | D | sum error = [ 301.6689, 317.0784, 333.1396, 349.8223, 367.2016] +24-11-19 20:36:48 | D | best error = [ 9.4228, 9.4228, 9.4228, 9.4228, 9.4228] +24-11-19 20:36:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:48 | D | sum error = [ 385.2614, 404.0702, 423.5873, 443.8486, 464.8465] +24-11-19 20:36:48 | D | best error = [ 9.4228, 9.4228, 9.4228, 9.4228, 9.4228] +24-11-19 20:36:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:48 | D | sum error = [ 486.5891, 509.1024, 532.4105, 556.4965, 581.4189] +24-11-19 20:36:48 | D | best error = [ 9.4228, 9.4228, 9.4228, 9.4228, 9.4228] +24-11-19 20:36:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:48 | D | sum error = [ 607.1399, 633.6951, 661.0592, 689.2516, 718.2964] +24-11-19 20:36:48 | D | best error = [ 9.4228, 9.4228, 9.4228, 9.4228, 9.4228] +24-11-19 20:36:48 | D | + error = [9.4228] +24-11-19 20:36:48 | D | - Calibrating model.layers.24.mlp.down_proj.weight +24-11-19 20:36:48 | D | + w: sint8 +24-11-19 20:36:48 | D | + x: None +24-11-19 20:36:48 | D | + y: None +24-11-19 20:36:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:48 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:36:48 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:36:48 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:36:48 | D | - range ratio = [ 1.0000] +24-11-19 20:36:48 | D | sum error = [ 3.9007] +24-11-19 20:36:48 | D | best error = [ 3.9007] +24-11-19 20:36:49 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:49 | D | sum error = [ 3.8707, 3.8527, 3.8229, 3.8141, 3.8162] +24-11-19 20:36:49 | D | best error = [ 3.7466, 3.6720, 3.6179, 3.5794, 3.5513] +24-11-19 20:36:49 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:49 | D | sum error = [ 3.8300, 3.8645, 3.9238, 3.9860, 4.0875] +24-11-19 20:36:49 | D | best error = [ 3.5301, 3.5138, 3.5023, 3.4938, 3.4878] +24-11-19 20:36:49 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:49 | D | sum error = [ 4.2028, 4.3397, 4.5058, 4.6969, 4.9250] +24-11-19 20:36:49 | D | best error = [ 3.4834, 3.4812, 3.4796, 3.4785, 3.4779] +24-11-19 20:36:49 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:49 | D | sum error = [ 5.1786, 5.4659, 5.7800, 6.1234, 6.5193] +24-11-19 20:36:49 | D | best error = [ 3.4777, 3.4775, 3.4774, 3.4774, 3.4773] +24-11-19 20:36:49 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:49 | D | sum error = [ 6.9446, 7.4020, 7.9029, 8.4358, 9.0152] +24-11-19 20:36:49 | D | best error = [ 3.4773, 3.4773, 3.4773, 3.4773, 3.4773] +24-11-19 20:36:49 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:49 | D | sum error = [ 9.6427, 10.3146, 11.0312, 11.8065, 12.6213] +24-11-19 20:36:49 | D | best error = [ 3.4773, 3.4773, 3.4773, 3.4773, 3.4773] +24-11-19 20:36:49 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:49 | D | sum error = [ 13.4956, 14.4266, 15.4200, 16.4682, 17.5921] +24-11-19 20:36:49 | D | best error = [ 3.4773, 3.4773, 3.4773, 3.4773, 3.4773] +24-11-19 20:36:49 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:49 | D | sum error = [ 18.7880, 20.0428, 21.3879, 22.7989, 24.2953] +24-11-19 20:36:49 | D | best error = [ 3.4773, 3.4773, 3.4773, 3.4773, 3.4773] +24-11-19 20:36:49 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:49 | D | sum error = [ 25.8736, 27.5507, 29.3138, 31.1695, 33.1257] +24-11-19 20:36:49 | D | best error = [ 3.4773, 3.4773, 3.4773, 3.4773, 3.4773] +24-11-19 20:36:49 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:49 | D | sum error = [ 35.1930, 37.3697, 39.6545, 42.0536, 44.5905] +24-11-19 20:36:49 | D | best error = [ 3.4773, 3.4773, 3.4773, 3.4773, 3.4773] +24-11-19 20:36:49 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:49 | D | sum error = [ 47.2417, 50.0339, 52.9559, 56.0246, 59.2334] +24-11-19 20:36:49 | D | best error = [ 3.4773, 3.4773, 3.4773, 3.4773, 3.4773] +24-11-19 20:36:49 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:49 | D | sum error = [ 62.5999, 66.1192, 69.8072, 73.6580, 77.6838] +24-11-19 20:36:49 | D | best error = [ 3.4773, 3.4773, 3.4773, 3.4773, 3.4773] +24-11-19 20:36:49 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:49 | D | sum error = [ 81.8802, 86.2509, 90.8207, 95.5789, 100.5351] +24-11-19 20:36:49 | D | best error = [ 3.4773, 3.4773, 3.4773, 3.4773, 3.4773] +24-11-19 20:36:49 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:49 | D | sum error = [ 105.6946, 111.0637, 116.6498, 122.4582, 128.4641] +24-11-19 20:36:49 | D | best error = [ 3.4773, 3.4773, 3.4773, 3.4773, 3.4773] +24-11-19 20:36:49 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:49 | D | sum error = [ 134.7067, 141.1812, 147.8938, 154.8484, 162.0470] +24-11-19 20:36:49 | D | best error = [ 3.4773, 3.4773, 3.4773, 3.4773, 3.4773] +24-11-19 20:36:49 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:49 | D | sum error = [ 169.4957, 177.1947, 185.1519, 193.3740, 201.8533] +24-11-19 20:36:49 | D | best error = [ 3.4773, 3.4773, 3.4773, 3.4773, 3.4773] +24-11-19 20:36:49 | D | + error = [3.4773] +24-11-19 20:36:49 | D | - Quantizing model.layers.24.self_attn.q_proj.weight +24-11-19 20:36:50 | D | - Quantizing model.layers.24.self_attn.k_proj.weight +24-11-19 20:36:51 | D | - Quantizing model.layers.24.self_attn.v_proj.weight +24-11-19 20:36:52 | D | - Quantizing model.layers.24.self_attn.o_proj.weight +24-11-19 20:36:53 | D | - Quantizing model.layers.24.mlp.up_proj.weight +24-11-19 20:36:54 | D | - Quantizing model.layers.24.mlp.gate_proj.weight +24-11-19 20:36:55 | D | - Quantizing model.layers.24.mlp.down_proj.weight +24-11-19 20:37:02 | D | - Quantizing layer model.layers.25 +24-11-19 20:37:02 | D | - Calibrating model.layers.25.self_attn.q_proj.weight +24-11-19 20:37:02 | D | + w: sint8 +24-11-19 20:37:02 | D | + x: None +24-11-19 20:37:02 | D | + y: None +24-11-19 20:37:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:37:02 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:03 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:03 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:03 | D | - range ratio = [ 1.0000] +24-11-19 20:37:03 | D | sum error = [ 13.9630] +24-11-19 20:37:03 | D | best error = [ 13.9630] +24-11-19 20:37:16 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:16 | D | sum error = [ 13.6003, 14.0157, 13.9121, 14.0004, 14.3711] +24-11-19 20:37:16 | D | best error = [ 13.6003, 13.6003, 13.6003, 13.6003, 13.6003] +24-11-19 20:37:16 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:16 | D | sum error = [ 14.8528, 15.1481, 15.8374, 16.7600, 17.2106] +24-11-19 20:37:16 | D | best error = [ 13.6003, 13.6003, 13.6003, 13.6003, 13.6003] +24-11-19 20:37:16 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:16 | D | sum error = [ 18.3017, 19.4955, 21.0785, 22.2361, 24.0384] +24-11-19 20:37:16 | D | best error = [ 13.6003, 13.6003, 13.6003, 13.6003, 13.6003] +24-11-19 20:37:16 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:16 | D | sum error = [ 25.6940, 27.8877, 30.0183, 32.0850, 34.8568] +24-11-19 20:37:16 | D | best error = [ 13.6003, 13.6003, 13.6003, 13.6003, 13.6003] +24-11-19 20:37:16 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:16 | D | sum error = [ 37.4809, 40.4620, 43.9070, 46.9949, 50.5368] +24-11-19 20:37:16 | D | best error = [ 13.6003, 13.6003, 13.6003, 13.6003, 13.6003] +24-11-19 20:37:16 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:16 | D | sum error = [ 54.7109, 58.6533, 63.8345, 68.3684, 73.5355] +24-11-19 20:37:16 | D | best error = [ 13.6003, 13.6003, 13.6003, 13.6003, 13.6003] +24-11-19 20:37:16 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:16 | D | sum error = [ 79.0725, 85.2634, 91.3360, 97.9992, 105.2129] +24-11-19 20:37:16 | D | best error = [ 13.6003, 13.6003, 13.6003, 13.6003, 13.6003] +24-11-19 20:37:16 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:16 | D | sum error = [ 113.0748, 121.5438, 130.4155, 140.0911, 150.4796] +24-11-19 20:37:16 | D | best error = [ 13.6003, 13.6003, 13.6003, 13.6003, 13.6003] +24-11-19 20:37:16 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:16 | D | sum error = [ 161.2085, 173.1931, 186.2244, 199.7200, 214.2698] +24-11-19 20:37:16 | D | best error = [ 13.6003, 13.6003, 13.6003, 13.6003, 13.6003] +24-11-19 20:37:16 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:16 | D | sum error = [ 230.2282, 246.9558, 265.3520, 285.0976, 306.0214] +24-11-19 20:37:16 | D | best error = [ 13.6003, 13.6003, 13.6003, 13.6003, 13.6003] +24-11-19 20:37:16 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:16 | D | sum error = [ 328.9467, 353.8631, 380.4930, 409.6032, 441.4122] +24-11-19 20:37:16 | D | best error = [ 13.6003, 13.6003, 13.6003, 13.6003, 13.6003] +24-11-19 20:37:16 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:16 | D | sum error = [ 475.2561, 512.2166, 553.4573, 597.8428, 646.1566] +24-11-19 20:37:16 | D | best error = [ 13.6003, 13.6003, 13.6003, 13.6003, 13.6003] +24-11-19 20:37:16 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:16 | D | sum error = [ 700.2515, 758.6866, 823.5389, 894.8786, 973.7554] +24-11-19 20:37:16 | D | best error = [ 13.6003, 13.6003, 13.6003, 13.6003, 13.6003] +24-11-19 20:37:16 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:16 | D | sum error = [ 1060.3939, 1156.3196, 1262.2647, 1379.3803, 1508.5793] +24-11-19 20:37:16 | D | best error = [ 13.6003, 13.6003, 13.6003, 13.6003, 13.6003] +24-11-19 20:37:16 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:16 | D | sum error = [ 1652.3174, 1812.9858, 1990.7465, 2189.4024, 2411.3451] +24-11-19 20:37:16 | D | best error = [ 13.6003, 13.6003, 13.6003, 13.6003, 13.6003] +24-11-19 20:37:16 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:16 | D | sum error = [ 2658.1977, 2932.4587, 3235.2822, 3571.6584, 3939.9637] +24-11-19 20:37:16 | D | best error = [ 13.6003, 13.6003, 13.6003, 13.6003, 13.6003] +24-11-19 20:37:16 | D | + error = [13.6003] +24-11-19 20:37:16 | D | - Calibrating model.layers.25.self_attn.k_proj.weight +24-11-19 20:37:16 | D | + w: sint8 +24-11-19 20:37:16 | D | + x: None +24-11-19 20:37:16 | D | + y: None +24-11-19 20:37:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:37:16 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:16 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:17 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:37:17 | D | - range ratio = [ 1.0000] +24-11-19 20:37:17 | D | sum error = [ 17.6516] +24-11-19 20:37:17 | D | best error = [ 17.6516] +24-11-19 20:37:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:31 | D | sum error = [ 16.8522, 16.1306, 16.2356, 17.3749, 16.8998] +24-11-19 20:37:31 | D | best error = [ 16.8522, 16.1306, 16.1306, 16.1306, 16.1306] +24-11-19 20:37:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:31 | D | sum error = [ 16.7023, 18.1171, 18.3456, 19.3988, 20.4616] +24-11-19 20:37:31 | D | best error = [ 16.1306, 16.1306, 16.1306, 16.1306, 16.1306] +24-11-19 20:37:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:31 | D | sum error = [ 23.0468, 23.9402, 25.8109, 26.6882, 28.4217] +24-11-19 20:37:31 | D | best error = [ 16.1306, 16.1306, 16.1306, 16.1306, 16.1306] +24-11-19 20:37:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:31 | D | sum error = [ 32.0729, 34.7279, 36.4361, 38.5396, 42.2336] +24-11-19 20:37:31 | D | best error = [ 16.1306, 16.1306, 16.1306, 16.1306, 16.1306] +24-11-19 20:37:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:31 | D | sum error = [ 45.1814, 48.2715, 52.2672, 55.8215, 59.9124] +24-11-19 20:37:31 | D | best error = [ 16.1306, 16.1306, 16.1306, 16.1306, 16.1306] +24-11-19 20:37:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:31 | D | sum error = [ 64.0049, 68.7581, 73.4944, 79.4936, 85.5581] +24-11-19 20:37:31 | D | best error = [ 16.1306, 16.1306, 16.1306, 16.1306, 16.1306] +24-11-19 20:37:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:31 | D | sum error = [ 91.6550, 98.4556, 105.9927, 114.3140, 122.2939] +24-11-19 20:37:31 | D | best error = [ 16.1306, 16.1306, 16.1306, 16.1306, 16.1306] +24-11-19 20:37:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:31 | D | sum error = [ 131.3540, 140.2124, 151.9442, 163.1716, 174.2377] +24-11-19 20:37:31 | D | best error = [ 16.1306, 16.1306, 16.1306, 16.1306, 16.1306] +24-11-19 20:37:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:31 | D | sum error = [ 187.4882, 200.5156, 214.8058, 230.1169, 246.4894] +24-11-19 20:37:31 | D | best error = [ 16.1306, 16.1306, 16.1306, 16.1306, 16.1306] +24-11-19 20:37:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:31 | D | sum error = [ 263.5160, 283.6033, 303.5307, 327.0136, 351.6480] +24-11-19 20:37:31 | D | best error = [ 16.1306, 16.1306, 16.1306, 16.1306, 16.1306] +24-11-19 20:37:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:31 | D | sum error = [ 377.7993, 407.2654, 438.4918, 472.6746, 509.5271] +24-11-19 20:37:31 | D | best error = [ 16.1306, 16.1306, 16.1306, 16.1306, 16.1306] +24-11-19 20:37:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:31 | D | sum error = [ 550.0053, 592.7307, 641.4026, 692.0976, 747.1914] +24-11-19 20:37:31 | D | best error = [ 16.1306, 16.1306, 16.1306, 16.1306, 16.1306] +24-11-19 20:37:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:31 | D | sum error = [ 808.9869, 874.1432, 948.3116, 1027.0766, 1113.6380] +24-11-19 20:37:31 | D | best error = [ 16.1306, 16.1306, 16.1306, 16.1306, 16.1306] +24-11-19 20:37:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:31 | D | sum error = [ 1209.7667, 1315.8341, 1430.2408, 1558.9695, 1700.4848] +24-11-19 20:37:31 | D | best error = [ 16.1306, 16.1306, 16.1306, 16.1306, 16.1306] +24-11-19 20:37:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:31 | D | sum error = [ 1854.6067, 2028.7077, 2218.0848, 2422.5271, 2652.6835] +24-11-19 20:37:31 | D | best error = [ 16.1306, 16.1306, 16.1306, 16.1306, 16.1306] +24-11-19 20:37:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:31 | D | sum error = [ 2909.6213, 3192.0680, 3502.6354, 3841.0294, 4212.5190] +24-11-19 20:37:31 | D | best error = [ 16.1306, 16.1306, 16.1306, 16.1306, 16.1306] +24-11-19 20:37:31 | D | + error = [16.1306] +24-11-19 20:37:31 | D | - Calibrating model.layers.25.self_attn.v_proj.weight +24-11-19 20:37:31 | D | + w: sint8 +24-11-19 20:37:31 | D | + x: None +24-11-19 20:37:31 | D | + y: None +24-11-19 20:37:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:31 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:37:31 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:37:31 | D | + finished calculating the original outputs, ram usage: 13.2 +24-11-19 20:37:31 | D | - range ratio = [ 1.0000] +24-11-19 20:37:31 | D | sum error = [ 8.5743] +24-11-19 20:37:31 | D | best error = [ 8.5743] +24-11-19 20:37:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:32 | D | sum error = [ 8.4820, 8.4723, 8.5309, 8.6382, 8.7933] +24-11-19 20:37:32 | D | best error = [ 7.9246, 7.6887, 7.5641, 7.4926, 7.4524] +24-11-19 20:37:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:32 | D | sum error = [ 8.9693, 9.2974, 9.7191, 10.0967, 10.6745] +24-11-19 20:37:32 | D | best error = [ 7.4291, 7.4192, 7.4158, 7.4143, 7.4139] +24-11-19 20:37:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:32 | D | sum error = [ 11.2797, 11.9377, 12.7633, 13.6023, 14.4911] +24-11-19 20:37:32 | D | best error = [ 7.4139, 7.4138, 7.4138, 7.4138, 7.4138] +24-11-19 20:37:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:32 | D | sum error = [ 15.5425, 16.6421, 17.8070, 19.1457, 20.4844] +24-11-19 20:37:32 | D | best error = [ 7.4138, 7.4138, 7.4138, 7.4138, 7.4138] +24-11-19 20:37:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:32 | D | sum error = [ 21.9515, 23.4849, 25.1718, 26.9277, 28.7703] +24-11-19 20:37:32 | D | best error = [ 7.4138, 7.4138, 7.4138, 7.4138, 7.4138] +24-11-19 20:37:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:32 | D | sum error = [ 30.7712, 32.8924, 35.0736, 37.4046, 39.8243] +24-11-19 20:37:32 | D | best error = [ 7.4138, 7.4138, 7.4138, 7.4138, 7.4138] +24-11-19 20:37:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:32 | D | sum error = [ 42.4566, 45.2094, 48.0895, 51.1662, 54.3845] +24-11-19 20:37:32 | D | best error = [ 7.4138, 7.4138, 7.4138, 7.4138, 7.4138] +24-11-19 20:37:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:32 | D | sum error = [ 57.7064, 61.2840, 64.9775, 68.8679, 72.9806] +24-11-19 20:37:32 | D | best error = [ 7.4138, 7.4138, 7.4138, 7.4138, 7.4138] +24-11-19 20:37:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:32 | D | sum error = [ 77.2656, 81.7377, 86.4264, 91.3561, 96.5016] +24-11-19 20:37:32 | D | best error = [ 7.4138, 7.4138, 7.4138, 7.4138, 7.4138] +24-11-19 20:37:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:32 | D | sum error = [ 101.9031, 107.5086, 113.3869, 119.5111, 125.8780] +24-11-19 20:37:32 | D | best error = [ 7.4138, 7.4138, 7.4138, 7.4138, 7.4138] +24-11-19 20:37:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:32 | D | sum error = [ 132.5437, 139.4634, 146.6955, 154.2135, 162.0267] +24-11-19 20:37:32 | D | best error = [ 7.4138, 7.4138, 7.4138, 7.4138, 7.4138] +24-11-19 20:37:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:32 | D | sum error = [ 170.1403, 178.5912, 187.3744, 196.4739, 205.8987] +24-11-19 20:37:32 | D | best error = [ 7.4138, 7.4138, 7.4138, 7.4138, 7.4138] +24-11-19 20:37:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:32 | D | sum error = [ 215.6869, 225.8273, 236.3324, 247.1890, 258.4298] +24-11-19 20:37:32 | D | best error = [ 7.4138, 7.4138, 7.4138, 7.4138, 7.4138] +24-11-19 20:37:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:32 | D | sum error = [ 270.0371, 282.0440, 294.4412, 307.2729, 320.5048] +24-11-19 20:37:32 | D | best error = [ 7.4138, 7.4138, 7.4138, 7.4138, 7.4138] +24-11-19 20:37:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:32 | D | sum error = [ 334.1700, 348.2863, 362.8333, 377.8285, 393.2599] +24-11-19 20:37:32 | D | best error = [ 7.4138, 7.4138, 7.4138, 7.4138, 7.4138] +24-11-19 20:37:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:32 | D | sum error = [ 409.1220, 425.4257, 442.1722, 459.3830, 477.0668] +24-11-19 20:37:32 | D | best error = [ 7.4138, 7.4138, 7.4138, 7.4138, 7.4138] +24-11-19 20:37:32 | D | + error = [7.4138] +24-11-19 20:37:32 | D | - Calibrating model.layers.25.self_attn.o_proj.weight +24-11-19 20:37:32 | D | + w: sint8 +24-11-19 20:37:32 | D | + x: None +24-11-19 20:37:32 | D | + y: None +24-11-19 20:37:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:32 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:37:32 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:37:32 | D | + finished calculating the original outputs, ram usage: 13.3 +24-11-19 20:37:32 | D | - range ratio = [ 1.0000] +24-11-19 20:37:32 | D | sum error = [ 1.6134] +24-11-19 20:37:32 | D | best error = [ 1.6134] +24-11-19 20:37:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:33 | D | sum error = [ 1.5965, 1.5916, 1.5985, 1.6190, 1.6445] +24-11-19 20:37:33 | D | best error = [ 1.5112, 1.4668, 1.4403, 1.4230, 1.4133] +24-11-19 20:37:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:33 | D | sum error = [ 1.6770, 1.7241, 1.7902, 1.8667, 1.9577] +24-11-19 20:37:33 | D | best error = [ 1.4058, 1.4004, 1.3966, 1.3937, 1.3912] +24-11-19 20:37:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:33 | D | sum error = [ 2.0622, 2.1802, 2.3105, 2.4598, 2.6197] +24-11-19 20:37:33 | D | best error = [ 1.3898, 1.3888, 1.3881, 1.3875, 1.3871] +24-11-19 20:37:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:33 | D | sum error = [ 2.7982, 2.9910, 3.2041, 3.4234, 3.6670] +24-11-19 20:37:33 | D | best error = [ 1.3867, 1.3865, 1.3863, 1.3863, 1.3862] +24-11-19 20:37:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:33 | D | sum error = [ 3.9174, 4.1975, 4.4830, 4.7990, 5.1234] +24-11-19 20:37:33 | D | best error = [ 1.3861, 1.3860, 1.3859, 1.3858, 1.3858] +24-11-19 20:37:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:33 | D | sum error = [ 5.4770, 5.8452, 6.2314, 6.6517, 7.0934] +24-11-19 20:37:33 | D | best error = [ 1.3857, 1.3857, 1.3857, 1.3856, 1.3856] +24-11-19 20:37:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:33 | D | sum error = [ 7.5535, 8.0381, 8.5550, 9.0919, 9.6688] +24-11-19 20:37:33 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 20:37:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:33 | D | sum error = [ 10.2706, 10.9069, 11.5830, 12.2761, 13.0195] +24-11-19 20:37:33 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 20:37:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:33 | D | sum error = [ 13.7996, 14.6132, 15.4738, 16.3684, 17.3091] +24-11-19 20:37:33 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 20:37:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:33 | D | sum error = [ 18.2950, 19.3329, 20.4146, 21.5442, 22.7300] +24-11-19 20:37:33 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 20:37:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:33 | D | sum error = [ 23.9686, 25.2681, 26.6248, 28.0399, 29.5153] +24-11-19 20:37:33 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 20:37:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:33 | D | sum error = [ 31.0625, 32.6737, 34.3510, 36.1030, 37.9317] +24-11-19 20:37:33 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 20:37:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:33 | D | sum error = [ 39.8376, 41.8194, 43.8826, 46.0275, 48.2578] +24-11-19 20:37:33 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 20:37:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:33 | D | sum error = [ 50.5749, 52.9738, 55.4682, 58.0593, 60.7379] +24-11-19 20:37:33 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 20:37:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:33 | D | sum error = [ 63.5139, 66.3838, 69.3592, 72.4336, 75.6097] +24-11-19 20:37:33 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 20:37:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:33 | D | sum error = [ 78.8869, 82.2670, 85.7628, 89.3657, 93.0779] +24-11-19 20:37:33 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 20:37:33 | D | + error = [1.3856] +24-11-19 20:37:33 | D | - Calibrating model.layers.25.mlp.up_proj.weight +24-11-19 20:37:33 | D | + w: sint8 +24-11-19 20:37:33 | D | + x: None +24-11-19 20:37:33 | D | + y: None +24-11-19 20:37:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:33 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:37:33 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:37:33 | D | + finished calculating the original outputs, ram usage: 13.4 +24-11-19 20:37:33 | D | - range ratio = [ 1.0000] +24-11-19 20:37:33 | D | sum error = [ 10.5095] +24-11-19 20:37:33 | D | best error = [ 10.5095] +24-11-19 20:37:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:34 | D | sum error = [ 10.4077, 10.4053, 10.4463, 10.5561, 10.7383] +24-11-19 20:37:34 | D | best error = [ 9.7087, 9.4011, 9.2415, 9.1458, 9.0933] +24-11-19 20:37:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:34 | D | sum error = [ 11.0325, 11.4181, 11.8612, 12.3913, 13.0590] +24-11-19 20:37:34 | D | best error = [ 9.0676, 9.0562, 9.0522, 9.0503, 9.0498] +24-11-19 20:37:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:34 | D | sum error = [ 13.7899, 14.6641, 15.5809, 16.6115, 17.7901] +24-11-19 20:37:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:37:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:34 | D | sum error = [ 19.0041, 20.3932, 21.8161, 23.4095, 25.0683] +24-11-19 20:37:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:37:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:34 | D | sum error = [ 26.8445, 28.7651, 30.7785, 32.9081, 35.2139] +24-11-19 20:37:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:37:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:34 | D | sum error = [ 37.6372, 40.2098, 42.9049, 45.7590, 48.7722] +24-11-19 20:37:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:37:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:34 | D | sum error = [ 51.9368, 55.3021, 58.8295, 62.5597, 66.4799] +24-11-19 20:37:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:37:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:34 | D | sum error = [ 70.6030, 74.9643, 79.5020, 84.2855, 89.3072] +24-11-19 20:37:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:37:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:34 | D | sum error = [ 94.5642, 100.0764, 105.8854, 111.9773, 118.3133] +24-11-19 20:37:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:37:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:34 | D | sum error = [ 124.9899, 131.9431, 139.2522, 146.8563, 154.8019] +24-11-19 20:37:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:37:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:34 | D | sum error = [ 163.1180, 171.7674, 180.7950, 190.1983, 200.0221] +24-11-19 20:37:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:37:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:34 | D | sum error = [ 210.2097, 220.8365, 231.8718, 243.3294, 255.2538] +24-11-19 20:37:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:37:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:34 | D | sum error = [ 267.6232, 280.4548, 293.7839, 307.5590, 321.8490] +24-11-19 20:37:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:37:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:34 | D | sum error = [ 336.6554, 351.9730, 367.8413, 384.2127, 401.1617] +24-11-19 20:37:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:37:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:34 | D | sum error = [ 418.6264, 436.6565, 455.2768, 474.4827, 494.2908] +24-11-19 20:37:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:37:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:34 | D | sum error = [ 514.6824, 535.6796, 557.2717, 579.4641, 602.2744] +24-11-19 20:37:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:37:34 | D | + error = [9.0497] +24-11-19 20:37:34 | D | - Calibrating model.layers.25.mlp.gate_proj.weight +24-11-19 20:37:34 | D | + w: sint8 +24-11-19 20:37:34 | D | + x: None +24-11-19 20:37:34 | D | + y: None +24-11-19 20:37:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:34 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:37:34 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:37:34 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:37:34 | D | - range ratio = [ 1.0000] +24-11-19 20:37:34 | D | sum error = [ 11.2779] +24-11-19 20:37:34 | D | best error = [ 11.2779] +24-11-19 20:37:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:35 | D | sum error = [ 11.1932, 11.1399, 11.2194, 11.3304, 11.5483] +24-11-19 20:37:35 | D | best error = [ 10.4329, 10.0913, 9.9252, 9.8239, 9.7684] +24-11-19 20:37:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:35 | D | sum error = [ 11.8265, 12.2420, 12.7221, 13.3282, 14.0440] +24-11-19 20:37:35 | D | best error = [ 9.7395, 9.7283, 9.7231, 9.7221, 9.7217] +24-11-19 20:37:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:35 | D | sum error = [ 14.8762, 15.7784, 16.8498, 17.9841, 19.2626] +24-11-19 20:37:35 | D | best error = [ 9.7216, 9.7216, 9.7216, 9.7216, 9.7216] +24-11-19 20:37:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:35 | D | sum error = [ 20.5967, 22.1060, 23.6764, 25.3889, 27.2387] +24-11-19 20:37:35 | D | best error = [ 9.7216, 9.7216, 9.7216, 9.7216, 9.7216] +24-11-19 20:37:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:35 | D | sum error = [ 29.1926, 31.2892, 33.4775, 35.8705, 38.3590] +24-11-19 20:37:35 | D | best error = [ 9.7216, 9.7216, 9.7216, 9.7216, 9.7216] +24-11-19 20:37:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:35 | D | sum error = [ 40.9960, 43.8139, 46.8112, 49.9566, 53.2929] +24-11-19 20:37:35 | D | best error = [ 9.7216, 9.7216, 9.7216, 9.7216, 9.7216] +24-11-19 20:37:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:35 | D | sum error = [ 56.8359, 60.5512, 64.5197, 68.6785, 73.0715] +24-11-19 20:37:35 | D | best error = [ 9.7216, 9.7216, 9.7216, 9.7216, 9.7216] +24-11-19 20:37:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:35 | D | sum error = [ 77.7080, 82.6091, 87.7402, 93.1398, 98.8506] +24-11-19 20:37:35 | D | best error = [ 9.7216, 9.7216, 9.7216, 9.7216, 9.7216] +24-11-19 20:37:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:35 | D | sum error = [ 104.8553, 111.2118, 117.8507, 124.8177, 132.1633] +24-11-19 20:37:35 | D | best error = [ 9.7216, 9.7216, 9.7216, 9.7216, 9.7216] +24-11-19 20:37:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:35 | D | sum error = [ 139.9021, 147.9754, 156.4538, 165.3547, 174.6826] +24-11-19 20:37:35 | D | best error = [ 9.7216, 9.7216, 9.7216, 9.7216, 9.7216] +24-11-19 20:37:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:35 | D | sum error = [ 184.4608, 194.7164, 205.4244, 216.6699, 228.4039] +24-11-19 20:37:35 | D | best error = [ 9.7216, 9.7216, 9.7216, 9.7216, 9.7216] +24-11-19 20:37:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:35 | D | sum error = [ 240.7038, 253.5412, 266.9419, 280.9282, 295.5265] +24-11-19 20:37:35 | D | best error = [ 9.7216, 9.7216, 9.7216, 9.7216, 9.7216] +24-11-19 20:37:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:35 | D | sum error = [ 310.7524, 326.5903, 343.1574, 360.3742, 378.2725] +24-11-19 20:37:35 | D | best error = [ 9.7216, 9.7216, 9.7216, 9.7216, 9.7216] +24-11-19 20:37:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:35 | D | sum error = [ 396.8706, 416.1949, 436.2411, 457.0846, 478.6726] +24-11-19 20:37:35 | D | best error = [ 9.7216, 9.7216, 9.7216, 9.7216, 9.7216] +24-11-19 20:37:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:35 | D | sum error = [ 501.0616, 524.2631, 548.2432, 573.0209, 598.6516] +24-11-19 20:37:35 | D | best error = [ 9.7216, 9.7216, 9.7216, 9.7216, 9.7216] +24-11-19 20:37:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:35 | D | sum error = [ 625.0530, 652.3657, 680.5161, 709.5475, 739.4247] +24-11-19 20:37:35 | D | best error = [ 9.7216, 9.7216, 9.7216, 9.7216, 9.7216] +24-11-19 20:37:35 | D | + error = [9.7216] +24-11-19 20:37:35 | D | - Calibrating model.layers.25.mlp.down_proj.weight +24-11-19 20:37:35 | D | + w: sint8 +24-11-19 20:37:35 | D | + x: None +24-11-19 20:37:35 | D | + y: None +24-11-19 20:37:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:35 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:37:35 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:37:36 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:37:36 | D | - range ratio = [ 1.0000] +24-11-19 20:37:36 | D | sum error = [ 3.9734] +24-11-19 20:37:36 | D | best error = [ 3.9734] +24-11-19 20:37:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:36 | D | sum error = [ 3.9439, 3.9206, 3.8896, 3.8831, 3.8787] +24-11-19 20:37:36 | D | best error = [ 3.8246, 3.7471, 3.6927, 3.6561, 3.6244] +24-11-19 20:37:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:36 | D | sum error = [ 3.9029, 3.9302, 3.9877, 4.0518, 4.1290] +24-11-19 20:37:36 | D | best error = [ 3.6032, 3.5884, 3.5789, 3.5715, 3.5659] +24-11-19 20:37:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:36 | D | sum error = [ 4.2430, 4.3762, 4.5363, 4.7223, 4.9493] +24-11-19 20:37:36 | D | best error = [ 3.5625, 3.5601, 3.5584, 3.5578, 3.5575] +24-11-19 20:37:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:36 | D | sum error = [ 5.1932, 5.4764, 5.7921, 6.1461, 6.5314] +24-11-19 20:37:36 | D | best error = [ 3.5571, 3.5568, 3.5568, 3.5567, 3.5566] +24-11-19 20:37:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:36 | D | sum error = [ 6.9502, 7.4085, 7.9109, 8.4412, 9.0253] +24-11-19 20:37:36 | D | best error = [ 3.5566, 3.5566, 3.5566, 3.5566, 3.5566] +24-11-19 20:37:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:36 | D | sum error = [ 9.6519, 10.3221, 11.0428, 11.8155, 12.6324] +24-11-19 20:37:36 | D | best error = [ 3.5566, 3.5566, 3.5566, 3.5566, 3.5566] +24-11-19 20:37:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:36 | D | sum error = [ 13.5150, 14.4471, 15.4418, 16.4962, 17.6253] +24-11-19 20:37:36 | D | best error = [ 3.5566, 3.5566, 3.5566, 3.5566, 3.5566] +24-11-19 20:37:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:36 | D | sum error = [ 18.8171, 20.0824, 21.4207, 22.8296, 24.3251] +24-11-19 20:37:36 | D | best error = [ 3.5566, 3.5566, 3.5566, 3.5566, 3.5566] +24-11-19 20:37:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:36 | D | sum error = [ 25.9148, 27.5857, 29.3448, 31.2094, 33.1661] +24-11-19 20:37:36 | D | best error = [ 3.5566, 3.5566, 3.5566, 3.5566, 3.5566] +24-11-19 20:37:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:36 | D | sum error = [ 35.2359, 37.4188, 39.7132, 42.1234, 44.6606] +24-11-19 20:37:36 | D | best error = [ 3.5566, 3.5566, 3.5566, 3.5566, 3.5566] +24-11-19 20:37:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:36 | D | sum error = [ 47.3297, 50.1232, 53.0554, 56.1305, 59.3487] +24-11-19 20:37:36 | D | best error = [ 3.5566, 3.5566, 3.5566, 3.5566, 3.5566] +24-11-19 20:37:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:36 | D | sum error = [ 62.7245, 66.2580, 69.9518, 73.8125, 77.8544] +24-11-19 20:37:36 | D | best error = [ 3.5566, 3.5566, 3.5566, 3.5566, 3.5566] +24-11-19 20:37:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:36 | D | sum error = [ 82.0742, 86.4823, 91.0757, 95.8641, 100.8463] +24-11-19 20:37:36 | D | best error = [ 3.5566, 3.5566, 3.5566, 3.5566, 3.5566] +24-11-19 20:37:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:36 | D | sum error = [ 106.0395, 111.4447, 117.0709, 122.9176, 128.9703] +24-11-19 20:37:36 | D | best error = [ 3.5566, 3.5566, 3.5566, 3.5566, 3.5566] +24-11-19 20:37:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:36 | D | sum error = [ 135.2606, 141.7735, 148.5330, 155.5269, 162.7772] +24-11-19 20:37:36 | D | best error = [ 3.5566, 3.5566, 3.5566, 3.5566, 3.5566] +24-11-19 20:37:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:36 | D | sum error = [ 170.2814, 178.0309, 186.0454, 194.3230, 202.8686] +24-11-19 20:37:36 | D | best error = [ 3.5566, 3.5566, 3.5566, 3.5566, 3.5566] +24-11-19 20:37:36 | D | + error = [3.5566] +24-11-19 20:37:37 | D | - Quantizing model.layers.25.self_attn.q_proj.weight +24-11-19 20:37:37 | D | - Quantizing model.layers.25.self_attn.k_proj.weight +24-11-19 20:37:38 | D | - Quantizing model.layers.25.self_attn.v_proj.weight +24-11-19 20:37:39 | D | - Quantizing model.layers.25.self_attn.o_proj.weight +24-11-19 20:37:40 | D | - Quantizing model.layers.25.mlp.up_proj.weight +24-11-19 20:37:41 | D | - Quantizing model.layers.25.mlp.gate_proj.weight +24-11-19 20:37:42 | D | - Quantizing model.layers.25.mlp.down_proj.weight +24-11-19 20:37:50 | D | - Quantizing layer model.layers.26 +24-11-19 20:37:50 | D | - Calibrating model.layers.26.self_attn.q_proj.weight +24-11-19 20:37:50 | D | + w: sint8 +24-11-19 20:37:50 | D | + x: None +24-11-19 20:37:50 | D | + y: None +24-11-19 20:37:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:37:50 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:50 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:50 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:51 | D | - range ratio = [ 1.0000] +24-11-19 20:37:51 | D | sum error = [ 17.6095] +24-11-19 20:37:51 | D | best error = [ 17.6095] +24-11-19 20:38:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:04 | D | sum error = [ 17.6294, 17.7939, 17.6968, 17.4362, 18.2361] +24-11-19 20:38:04 | D | best error = [ 17.6095, 17.6095, 17.6095, 17.4362, 17.4362] +24-11-19 20:38:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:04 | D | sum error = [ 18.4658, 19.2892, 20.0550, 20.7455, 21.8307] +24-11-19 20:38:04 | D | best error = [ 17.4362, 17.4362, 17.4362, 17.4362, 17.4362] +24-11-19 20:38:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:04 | D | sum error = [ 23.4547, 24.5785, 26.3805, 28.5468, 30.5921] +24-11-19 20:38:04 | D | best error = [ 17.4362, 17.4362, 17.4362, 17.4362, 17.4362] +24-11-19 20:38:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:04 | D | sum error = [ 32.5588, 34.7851, 37.3744, 40.6262, 43.5454] +24-11-19 20:38:04 | D | best error = [ 17.4362, 17.4362, 17.4362, 17.4362, 17.4362] +24-11-19 20:38:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:04 | D | sum error = [ 47.1154, 50.8425, 54.7520, 58.7463, 63.1198] +24-11-19 20:38:04 | D | best error = [ 17.4362, 17.4362, 17.4362, 17.4362, 17.4362] +24-11-19 20:38:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:04 | D | sum error = [ 68.8348, 73.4640, 79.7832, 85.9307, 92.6020] +24-11-19 20:38:04 | D | best error = [ 17.4362, 17.4362, 17.4362, 17.4362, 17.4362] +24-11-19 20:38:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:04 | D | sum error = [ 100.1906, 107.5462, 115.6677, 124.0055, 133.3275] +24-11-19 20:38:04 | D | best error = [ 17.4362, 17.4362, 17.4362, 17.4362, 17.4362] +24-11-19 20:38:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:04 | D | sum error = [ 143.5743, 154.8761, 166.1826, 178.0288, 190.9540] +24-11-19 20:38:04 | D | best error = [ 17.4362, 17.4362, 17.4362, 17.4362, 17.4362] +24-11-19 20:38:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:04 | D | sum error = [ 205.1242, 219.8998, 236.2638, 253.6902, 271.4139] +24-11-19 20:38:04 | D | best error = [ 17.4362, 17.4362, 17.4362, 17.4362, 17.4362] +24-11-19 20:38:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:04 | D | sum error = [ 290.9090, 312.4295, 335.3765, 359.5178, 386.0379] +24-11-19 20:38:04 | D | best error = [ 17.4362, 17.4362, 17.4362, 17.4362, 17.4362] +24-11-19 20:38:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:04 | D | sum error = [ 414.1339, 445.2635, 477.4140, 512.8739, 550.5004] +24-11-19 20:38:04 | D | best error = [ 17.4362, 17.4362, 17.4362, 17.4362, 17.4362] +24-11-19 20:38:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:04 | D | sum error = [ 591.3992, 636.3317, 684.2816, 736.6016, 791.9592] +24-11-19 20:38:04 | D | best error = [ 17.4362, 17.4362, 17.4362, 17.4362, 17.4362] +24-11-19 20:38:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:04 | D | sum error = [ 852.7868, 918.4295, 989.0127, 1065.8857, 1148.0816] +24-11-19 20:38:04 | D | best error = [ 17.4362, 17.4362, 17.4362, 17.4362, 17.4362] +24-11-19 20:38:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:04 | D | sum error = [ 1238.6267, 1336.7114, 1442.1780, 1557.9348, 1683.9583] +24-11-19 20:38:04 | D | best error = [ 17.4362, 17.4362, 17.4362, 17.4362, 17.4362] +24-11-19 20:38:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:04 | D | sum error = [ 1820.5723, 1967.9516, 2127.4117, 2300.6483, 2488.8517] +24-11-19 20:38:04 | D | best error = [ 17.4362, 17.4362, 17.4362, 17.4362, 17.4362] +24-11-19 20:38:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:04 | D | sum error = [ 2691.4566, 2910.4622, 3143.9919, 3393.4366, 3658.0339] +24-11-19 20:38:04 | D | best error = [ 17.4362, 17.4362, 17.4362, 17.4362, 17.4362] +24-11-19 20:38:04 | D | + error = [17.4362] +24-11-19 20:38:04 | D | - Calibrating model.layers.26.self_attn.k_proj.weight +24-11-19 20:38:04 | D | + w: sint8 +24-11-19 20:38:04 | D | + x: None +24-11-19 20:38:04 | D | + y: None +24-11-19 20:38:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:38:04 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:04 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:05 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:05 | D | - range ratio = [ 1.0000] +24-11-19 20:38:05 | D | sum error = [ 22.2345] +24-11-19 20:38:05 | D | best error = [ 22.2345] +24-11-19 20:38:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:18 | D | sum error = [ 20.8874, 20.9288, 21.8363, 20.9148, 25.1428] +24-11-19 20:38:18 | D | best error = [ 20.8874, 20.8874, 20.8874, 20.8874, 20.8874] +24-11-19 20:38:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:18 | D | sum error = [ 21.1708, 22.3927, 25.3851, 25.8496, 30.2617] +24-11-19 20:38:18 | D | best error = [ 20.8874, 20.8874, 20.8874, 20.8874, 20.8874] +24-11-19 20:38:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:18 | D | sum error = [ 28.2913, 31.6685, 30.9459, 34.0895, 34.8831] +24-11-19 20:38:18 | D | best error = [ 20.8874, 20.8874, 20.8874, 20.8874, 20.8874] +24-11-19 20:38:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:18 | D | sum error = [ 37.3608, 43.1023, 45.7359, 46.6888, 49.9174] +24-11-19 20:38:18 | D | best error = [ 20.8874, 20.8874, 20.8874, 20.8874, 20.8874] +24-11-19 20:38:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:18 | D | sum error = [ 53.7446, 58.9610, 62.7082, 68.4256, 74.0123] +24-11-19 20:38:18 | D | best error = [ 20.8874, 20.8874, 20.8874, 20.8874, 20.8874] +24-11-19 20:38:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:18 | D | sum error = [ 79.4088, 88.6316, 96.4598, 104.7112, 116.8367] +24-11-19 20:38:18 | D | best error = [ 20.8874, 20.8874, 20.8874, 20.8874, 20.8874] +24-11-19 20:38:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:18 | D | sum error = [ 124.3160, 134.2609, 144.2808, 158.8034, 170.8933] +24-11-19 20:38:18 | D | best error = [ 20.8874, 20.8874, 20.8874, 20.8874, 20.8874] +24-11-19 20:38:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:18 | D | sum error = [ 180.5942, 198.6637, 209.4090, 222.0407, 237.2796] +24-11-19 20:38:18 | D | best error = [ 20.8874, 20.8874, 20.8874, 20.8874, 20.8874] +24-11-19 20:38:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:18 | D | sum error = [ 249.0749, 264.5757, 279.7707, 298.9325, 318.7860] +24-11-19 20:38:18 | D | best error = [ 20.8874, 20.8874, 20.8874, 20.8874, 20.8874] +24-11-19 20:38:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:18 | D | sum error = [ 337.2845, 359.3745, 380.2347, 403.4296, 427.8611] +24-11-19 20:38:18 | D | best error = [ 20.8874, 20.8874, 20.8874, 20.8874, 20.8874] +24-11-19 20:38:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:18 | D | sum error = [ 454.5165, 486.2959, 518.5499, 553.2874, 589.7068] +24-11-19 20:38:18 | D | best error = [ 20.8874, 20.8874, 20.8874, 20.8874, 20.8874] +24-11-19 20:38:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:18 | D | sum error = [ 629.2507, 672.9882, 721.3759, 771.6985, 829.1533] +24-11-19 20:38:18 | D | best error = [ 20.8874, 20.8874, 20.8874, 20.8874, 20.8874] +24-11-19 20:38:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:18 | D | sum error = [ 890.0409, 957.2467, 1027.7111, 1105.2868, 1190.2163] +24-11-19 20:38:18 | D | best error = [ 20.8874, 20.8874, 20.8874, 20.8874, 20.8874] +24-11-19 20:38:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:18 | D | sum error = [ 1282.3095, 1385.6514, 1494.7853, 1612.7546, 1742.9850] +24-11-19 20:38:18 | D | best error = [ 20.8874, 20.8874, 20.8874, 20.8874, 20.8874] +24-11-19 20:38:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:18 | D | sum error = [ 1879.8222, 2029.6838, 2192.8102, 2365.6170, 2551.9297] +24-11-19 20:38:18 | D | best error = [ 20.8874, 20.8874, 20.8874, 20.8874, 20.8874] +24-11-19 20:38:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:18 | D | sum error = [ 2754.2534, 2975.2020, 3209.5741, 3459.3651, 3728.0327] +24-11-19 20:38:18 | D | best error = [ 20.8874, 20.8874, 20.8874, 20.8874, 20.8874] +24-11-19 20:38:18 | D | + error = [20.8874] +24-11-19 20:38:18 | D | - Calibrating model.layers.26.self_attn.v_proj.weight +24-11-19 20:38:18 | D | + w: sint8 +24-11-19 20:38:18 | D | + x: None +24-11-19 20:38:18 | D | + y: None +24-11-19 20:38:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:18 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:18 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:19 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:19 | D | - range ratio = [ 1.0000] +24-11-19 20:38:19 | D | sum error = [ 8.4098] +24-11-19 20:38:19 | D | best error = [ 8.4098] +24-11-19 20:38:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:19 | D | sum error = [ 8.3899, 8.3298, 8.3668, 8.4867, 8.6151] +24-11-19 20:38:19 | D | best error = [ 7.8146, 7.5707, 7.4436, 7.3744, 7.3339] +24-11-19 20:38:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:19 | D | sum error = [ 8.8435, 9.0996, 9.5170, 9.9570, 10.4810] +24-11-19 20:38:19 | D | best error = [ 7.3150, 7.3070, 7.3029, 7.3020, 7.3019] +24-11-19 20:38:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:19 | D | sum error = [ 11.0353, 11.7494, 12.5417, 13.3414, 14.2716] +24-11-19 20:38:19 | D | best error = [ 7.3017, 7.3017, 7.3017, 7.3017, 7.3017] +24-11-19 20:38:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:19 | D | sum error = [ 15.2832, 16.3259, 17.5311, 18.7883, 20.1169] +24-11-19 20:38:19 | D | best error = [ 7.3017, 7.3017, 7.3017, 7.3017, 7.3017] +24-11-19 20:38:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:19 | D | sum error = [ 21.5030, 23.0617, 24.6872, 26.4027, 28.1867] +24-11-19 20:38:19 | D | best error = [ 7.3017, 7.3017, 7.3017, 7.3017, 7.3017] +24-11-19 20:38:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:19 | D | sum error = [ 30.1014, 32.1638, 34.3242, 36.6444, 38.9714] +24-11-19 20:38:19 | D | best error = [ 7.3017, 7.3017, 7.3017, 7.3017, 7.3017] +24-11-19 20:38:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:19 | D | sum error = [ 41.5277, 44.1542, 46.9513, 49.9193, 53.0303] +24-11-19 20:38:19 | D | best error = [ 7.3017, 7.3017, 7.3017, 7.3017, 7.3017] +24-11-19 20:38:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:19 | D | sum error = [ 56.2952, 59.7353, 63.3445, 67.1230, 71.1217] +24-11-19 20:38:19 | D | best error = [ 7.3017, 7.3017, 7.3017, 7.3017, 7.3017] +24-11-19 20:38:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:19 | D | sum error = [ 75.2596, 79.6241, 84.2220, 88.9922, 93.9813] +24-11-19 20:38:19 | D | best error = [ 7.3017, 7.3017, 7.3017, 7.3017, 7.3017] +24-11-19 20:38:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:19 | D | sum error = [ 99.2157, 104.6938, 110.4115, 116.3506, 122.5721] +24-11-19 20:38:19 | D | best error = [ 7.3017, 7.3017, 7.3017, 7.3017, 7.3017] +24-11-19 20:38:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:19 | D | sum error = [ 129.0490, 135.7695, 142.7755, 150.0797, 157.6378] +24-11-19 20:38:19 | D | best error = [ 7.3017, 7.3017, 7.3017, 7.3017, 7.3017] +24-11-19 20:38:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:19 | D | sum error = [ 165.5227, 173.6770, 182.1599, 190.9392, 200.0590] +24-11-19 20:38:19 | D | best error = [ 7.3017, 7.3017, 7.3017, 7.3017, 7.3017] +24-11-19 20:38:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:19 | D | sum error = [ 209.5065, 219.2991, 229.4327, 239.9362, 250.8212] +24-11-19 20:38:19 | D | best error = [ 7.3017, 7.3017, 7.3017, 7.3017, 7.3017] +24-11-19 20:38:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:19 | D | sum error = [ 262.0618, 273.6945, 285.7011, 298.1049, 310.8626] +24-11-19 20:38:19 | D | best error = [ 7.3017, 7.3017, 7.3017, 7.3017, 7.3017] +24-11-19 20:38:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:19 | D | sum error = [ 324.0677, 337.6788, 351.6774, 366.1009, 380.9611] +24-11-19 20:38:19 | D | best error = [ 7.3017, 7.3017, 7.3017, 7.3017, 7.3017] +24-11-19 20:38:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:19 | D | sum error = [ 396.2505, 411.9774, 428.1355, 444.7243, 461.7635] +24-11-19 20:38:19 | D | best error = [ 7.3017, 7.3017, 7.3017, 7.3017, 7.3017] +24-11-19 20:38:19 | D | + error = [7.3017] +24-11-19 20:38:19 | D | - Calibrating model.layers.26.self_attn.o_proj.weight +24-11-19 20:38:19 | D | + w: sint8 +24-11-19 20:38:19 | D | + x: None +24-11-19 20:38:19 | D | + y: None +24-11-19 20:38:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:19 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:19 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:38:19 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:38:19 | D | - range ratio = [ 1.0000] +24-11-19 20:38:19 | D | sum error = [ 2.2268] +24-11-19 20:38:19 | D | best error = [ 2.2268] +24-11-19 20:38:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:20 | D | sum error = [ 2.2029, 2.1796, 2.1742, 2.1641, 2.1500] +24-11-19 20:38:20 | D | best error = [ 2.0791, 2.0089, 1.9658, 1.9325, 1.9071] +24-11-19 20:38:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:20 | D | sum error = [ 2.1590, 2.1694, 2.1775, 2.1970, 2.2288] +24-11-19 20:38:20 | D | best error = [ 1.8865, 1.8707, 1.8577, 1.8455, 1.8356] +24-11-19 20:38:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:20 | D | sum error = [ 2.2543, 2.2985, 2.3569, 2.4229, 2.4988] +24-11-19 20:38:20 | D | best error = [ 1.8267, 1.8191, 1.8126, 1.8069, 1.8019] +24-11-19 20:38:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:20 | D | sum error = [ 2.5911, 2.6852, 2.7966, 2.9373, 3.0592] +24-11-19 20:38:20 | D | best error = [ 1.7975, 1.7939, 1.7905, 1.7877, 1.7858] +24-11-19 20:38:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:20 | D | sum error = [ 3.2267, 3.3943, 3.5858, 3.7908, 4.0110] +24-11-19 20:38:20 | D | best error = [ 1.7839, 1.7828, 1.7819, 1.7811, 1.7807] +24-11-19 20:38:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:20 | D | sum error = [ 4.2501, 4.5119, 4.7790, 5.0739, 5.3947] +24-11-19 20:38:20 | D | best error = [ 1.7802, 1.7793, 1.7791, 1.7790, 1.7788] +24-11-19 20:38:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:20 | D | sum error = [ 5.7423, 6.1028, 6.4915, 6.9058, 7.3355] +24-11-19 20:38:20 | D | best error = [ 1.7785, 1.7785, 1.7783, 1.7782, 1.7782] +24-11-19 20:38:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:20 | D | sum error = [ 7.8109, 8.3063, 8.8365, 9.3992, 10.0082] +24-11-19 20:38:20 | D | best error = [ 1.7781, 1.7780, 1.7780, 1.7779, 1.7779] +24-11-19 20:38:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:20 | D | sum error = [ 10.6437, 11.3291, 12.0491, 12.8066, 13.6204] +24-11-19 20:38:20 | D | best error = [ 1.7778, 1.7778, 1.7778, 1.7778, 1.7778] +24-11-19 20:38:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:20 | D | sum error = [ 14.4860, 15.3969, 16.3682, 17.3919, 18.4763] +24-11-19 20:38:20 | D | best error = [ 1.7778, 1.7778, 1.7778, 1.7778, 1.7778] +24-11-19 20:38:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:20 | D | sum error = [ 19.6176, 20.8294, 22.1200, 23.4724, 24.9032] +24-11-19 20:38:20 | D | best error = [ 1.7778, 1.7778, 1.7778, 1.7778, 1.7778] +24-11-19 20:38:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:20 | D | sum error = [ 26.4125, 28.0040, 29.6813, 31.4592, 33.3314] +24-11-19 20:38:20 | D | best error = [ 1.7778, 1.7778, 1.7778, 1.7778, 1.7778] +24-11-19 20:38:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:20 | D | sum error = [ 35.2960, 37.3658, 39.5493, 41.8460, 44.2568] +24-11-19 20:38:20 | D | best error = [ 1.7778, 1.7778, 1.7778, 1.7778, 1.7778] +24-11-19 20:38:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:20 | D | sum error = [ 46.7785, 49.4308, 52.2079, 55.1235, 58.1775] +24-11-19 20:38:20 | D | best error = [ 1.7778, 1.7778, 1.7778, 1.7778, 1.7778] +24-11-19 20:38:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:20 | D | sum error = [ 61.3755, 64.7170, 68.2220, 71.8784, 75.6985] +24-11-19 20:38:20 | D | best error = [ 1.7778, 1.7778, 1.7778, 1.7778, 1.7778] +24-11-19 20:38:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:20 | D | sum error = [ 79.6865, 83.8459, 88.1794, 92.6873, 97.3817] +24-11-19 20:38:20 | D | best error = [ 1.7778, 1.7778, 1.7778, 1.7778, 1.7778] +24-11-19 20:38:20 | D | + error = [1.7778] +24-11-19 20:38:20 | D | - Calibrating model.layers.26.mlp.up_proj.weight +24-11-19 20:38:20 | D | + w: sint8 +24-11-19 20:38:20 | D | + x: None +24-11-19 20:38:20 | D | + y: None +24-11-19 20:38:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:20 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:38:20 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:38:20 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:38:20 | D | - range ratio = [ 1.0000] +24-11-19 20:38:20 | D | sum error = [ 10.8623] +24-11-19 20:38:20 | D | best error = [ 10.8623] +24-11-19 20:38:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:21 | D | sum error = [ 10.7834, 10.7700, 10.8014, 10.9306, 11.1499] +24-11-19 20:38:21 | D | best error = [ 10.0299, 9.7114, 9.5459, 9.4501, 9.3986] +24-11-19 20:38:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:21 | D | sum error = [ 11.4085, 11.8118, 12.2581, 12.8783, 13.5507] +24-11-19 20:38:21 | D | best error = [ 9.3699, 9.3576, 9.3535, 9.3521, 9.3516] +24-11-19 20:38:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:21 | D | sum error = [ 14.2928, 15.2032, 16.1922, 17.2659, 18.4674] +24-11-19 20:38:21 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:38:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:21 | D | sum error = [ 19.7563, 21.1553, 22.6964, 24.3036, 26.0352] +24-11-19 20:38:21 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:38:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:21 | D | sum error = [ 27.8848, 29.8421, 31.9633, 34.1574, 36.6063] +24-11-19 20:38:21 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:38:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:21 | D | sum error = [ 39.0766, 41.7263, 44.5191, 47.5144, 50.6346] +24-11-19 20:38:21 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:38:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:21 | D | sum error = [ 53.9347, 57.4318, 61.1436, 65.0085, 69.0964] +24-11-19 20:38:21 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:38:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:21 | D | sum error = [ 73.4051, 77.9119, 82.6543, 87.6406, 92.8796] +24-11-19 20:38:21 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:38:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:21 | D | sum error = [ 98.3907, 104.1510, 110.2061, 116.5281, 123.1573] +24-11-19 20:38:21 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:38:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:21 | D | sum error = [ 130.1183, 137.3724, 144.9792, 152.9240, 161.2279] +24-11-19 20:38:21 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:38:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:21 | D | sum error = [ 169.9203, 178.9555, 188.4204, 198.2642, 208.5301] +24-11-19 20:38:21 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:38:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:21 | D | sum error = [ 219.2252, 230.3614, 241.9205, 253.9625, 266.4954] +24-11-19 20:38:21 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:38:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:21 | D | sum error = [ 279.4893, 292.9896, 306.9946, 321.5181, 336.5771] +24-11-19 20:38:21 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:38:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:21 | D | sum error = [ 352.1885, 368.3339, 385.0662, 402.3520, 420.2293] +24-11-19 20:38:21 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:38:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:21 | D | sum error = [ 438.6779, 457.7492, 477.4256, 497.7195, 518.6493] +24-11-19 20:38:21 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:38:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:21 | D | sum error = [ 540.1852, 562.3861, 585.2028, 608.6682, 632.7959] +24-11-19 20:38:21 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:38:21 | D | + error = [9.3515] +24-11-19 20:38:21 | D | - Calibrating model.layers.26.mlp.gate_proj.weight +24-11-19 20:38:21 | D | + w: sint8 +24-11-19 20:38:21 | D | + x: None +24-11-19 20:38:21 | D | + y: None +24-11-19 20:38:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:21 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:38:21 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:38:21 | D | + finished calculating the original outputs, ram usage: 13.3 +24-11-19 20:38:21 | D | - range ratio = [ 1.0000] +24-11-19 20:38:21 | D | sum error = [ 11.6638] +24-11-19 20:38:21 | D | best error = [ 11.6638] +24-11-19 20:38:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:22 | D | sum error = [ 11.6070, 11.5727, 11.6082, 11.7385, 11.9192] +24-11-19 20:38:22 | D | best error = [ 10.7955, 10.4510, 10.2605, 10.1529, 10.0943] +24-11-19 20:38:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:22 | D | sum error = [ 12.2270, 12.6306, 13.1443, 13.8048, 14.5257] +24-11-19 20:38:22 | D | best error = [ 10.0662, 10.0530, 10.0470, 10.0456, 10.0453] +24-11-19 20:38:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:22 | D | sum error = [ 15.3564, 16.2924, 17.3649, 18.5526, 19.8591] +24-11-19 20:38:22 | D | best error = [ 10.0451, 10.0451, 10.0451, 10.0451, 10.0451] +24-11-19 20:38:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:22 | D | sum error = [ 21.2624, 22.7822, 24.4261, 26.1932, 28.0698] +24-11-19 20:38:22 | D | best error = [ 10.0451, 10.0451, 10.0451, 10.0451, 10.0451] +24-11-19 20:38:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:22 | D | sum error = [ 30.0904, 32.2493, 34.5621, 37.0180, 39.6220] +24-11-19 20:38:22 | D | best error = [ 10.0451, 10.0451, 10.0451, 10.0451, 10.0451] +24-11-19 20:38:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:22 | D | sum error = [ 42.3645, 45.2710, 48.3772, 51.6289, 55.0972] +24-11-19 20:38:22 | D | best error = [ 10.0451, 10.0451, 10.0451, 10.0451, 10.0451] +24-11-19 20:38:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:22 | D | sum error = [ 58.7803, 62.6470, 66.7402, 71.0780, 75.6870] +24-11-19 20:38:22 | D | best error = [ 10.0451, 10.0451, 10.0451, 10.0451, 10.0451] +24-11-19 20:38:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:22 | D | sum error = [ 80.5195, 85.6085, 90.9949, 96.6548, 102.6079] +24-11-19 20:38:22 | D | best error = [ 10.0451, 10.0451, 10.0451, 10.0451, 10.0451] +24-11-19 20:38:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:22 | D | sum error = [ 108.9188, 115.5099, 122.4501, 129.7468, 137.4359] +24-11-19 20:38:22 | D | best error = [ 10.0451, 10.0451, 10.0451, 10.0451, 10.0451] +24-11-19 20:38:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:22 | D | sum error = [ 145.4664, 153.9621, 162.8656, 172.2114, 182.0138] +24-11-19 20:38:22 | D | best error = [ 10.0451, 10.0451, 10.0451, 10.0451, 10.0451] +24-11-19 20:38:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:22 | D | sum error = [ 192.2942, 203.0947, 214.4182, 226.2774, 238.6690] +24-11-19 20:38:22 | D | best error = [ 10.0451, 10.0451, 10.0451, 10.0451, 10.0451] +24-11-19 20:38:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:22 | D | sum error = [ 251.6529, 265.2389, 279.4059, 294.2433, 309.7511] +24-11-19 20:38:22 | D | best error = [ 10.0451, 10.0451, 10.0451, 10.0451, 10.0451] +24-11-19 20:38:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:22 | D | sum error = [ 325.9314, 342.7883, 360.3718, 378.7133, 397.8172] +24-11-19 20:38:22 | D | best error = [ 10.0451, 10.0451, 10.0451, 10.0451, 10.0451] +24-11-19 20:38:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:22 | D | sum error = [ 417.7036, 438.3599, 459.8041, 482.0771, 505.1619] +24-11-19 20:38:22 | D | best error = [ 10.0451, 10.0451, 10.0451, 10.0451, 10.0451] +24-11-19 20:38:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:22 | D | sum error = [ 529.1197, 553.9237, 579.6154, 606.1933, 633.6744] +24-11-19 20:38:22 | D | best error = [ 10.0451, 10.0451, 10.0451, 10.0451, 10.0451] +24-11-19 20:38:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:22 | D | sum error = [ 662.0310, 691.3016, 721.4733, 752.5834, 784.5888] +24-11-19 20:38:22 | D | best error = [ 10.0451, 10.0451, 10.0451, 10.0451, 10.0451] +24-11-19 20:38:22 | D | + error = [10.0451] +24-11-19 20:38:23 | D | - Calibrating model.layers.26.mlp.down_proj.weight +24-11-19 20:38:23 | D | + w: sint8 +24-11-19 20:38:23 | D | + x: None +24-11-19 20:38:23 | D | + y: None +24-11-19 20:38:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:23 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:38:23 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:38:23 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:38:23 | D | - range ratio = [ 1.0000] +24-11-19 20:38:23 | D | sum error = [ 4.1821] +24-11-19 20:38:23 | D | best error = [ 4.1821] +24-11-19 20:38:24 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:24 | D | sum error = [ 4.1419, 4.1120, 4.0801, 4.0877, 4.0872] +24-11-19 20:38:24 | D | best error = [ 4.0138, 3.9314, 3.8715, 3.8344, 3.8062] +24-11-19 20:38:24 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:24 | D | sum error = [ 4.0922, 4.1323, 4.1916, 4.2558, 4.3429] +24-11-19 20:38:24 | D | best error = [ 3.7833, 3.7677, 3.7586, 3.7509, 3.7444] +24-11-19 20:38:24 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:24 | D | sum error = [ 4.4598, 4.5983, 4.7633, 4.9671, 5.1986] +24-11-19 20:38:24 | D | best error = [ 3.7411, 3.7385, 3.7370, 3.7362, 3.7355] +24-11-19 20:38:24 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:24 | D | sum error = [ 5.4592, 5.7537, 6.0771, 6.4398, 6.8431] +24-11-19 20:38:24 | D | best error = [ 3.7353, 3.7350, 3.7348, 3.7348, 3.7347] +24-11-19 20:38:24 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:24 | D | sum error = [ 7.2904, 7.7649, 8.2803, 8.8484, 9.4561] +24-11-19 20:38:24 | D | best error = [ 3.7347, 3.7347, 3.7347, 3.7347, 3.7347] +24-11-19 20:38:24 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:24 | D | sum error = [ 10.1136, 10.8093, 11.5655, 12.3778, 13.2401] +24-11-19 20:38:24 | D | best error = [ 3.7347, 3.7347, 3.7347, 3.7347, 3.7347] +24-11-19 20:38:24 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:24 | D | sum error = [ 14.1588, 15.1375, 16.1694, 17.2824, 18.4597] +24-11-19 20:38:24 | D | best error = [ 3.7347, 3.7347, 3.7347, 3.7347, 3.7347] +24-11-19 20:38:24 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:24 | D | sum error = [ 19.7074, 21.0104, 22.4215, 23.8983, 25.4657] +24-11-19 20:38:24 | D | best error = [ 3.7347, 3.7347, 3.7347, 3.7347, 3.7347] +24-11-19 20:38:24 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:24 | D | sum error = [ 27.1226, 28.8663, 30.7144, 32.6668, 34.7243] +24-11-19 20:38:24 | D | best error = [ 3.7347, 3.7347, 3.7347, 3.7347, 3.7347] +24-11-19 20:38:24 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:24 | D | sum error = [ 36.8904, 39.1667, 41.5666, 44.0850, 46.7378] +24-11-19 20:38:24 | D | best error = [ 3.7347, 3.7347, 3.7347, 3.7347, 3.7347] +24-11-19 20:38:24 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:24 | D | sum error = [ 49.5197, 52.4408, 55.5111, 58.7221, 62.0880] +24-11-19 20:38:24 | D | best error = [ 3.7347, 3.7347, 3.7347, 3.7347, 3.7347] +24-11-19 20:38:24 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:24 | D | sum error = [ 65.6160, 69.3044, 73.1718, 77.2093, 81.4384] +24-11-19 20:38:24 | D | best error = [ 3.7347, 3.7347, 3.7347, 3.7347, 3.7347] +24-11-19 20:38:24 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:24 | D | sum error = [ 85.8471, 90.4415, 95.2402, 100.2377, 105.4465] +24-11-19 20:38:24 | D | best error = [ 3.7347, 3.7347, 3.7347, 3.7347, 3.7347] +24-11-19 20:38:24 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:24 | D | sum error = [ 110.8678, 116.5108, 122.3783, 128.4893, 134.8066] +24-11-19 20:38:24 | D | best error = [ 3.7347, 3.7347, 3.7347, 3.7347, 3.7347] +24-11-19 20:38:24 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:24 | D | sum error = [ 141.3807, 148.1951, 155.2657, 162.5884, 170.1639] +24-11-19 20:38:24 | D | best error = [ 3.7347, 3.7347, 3.7347, 3.7347, 3.7347] +24-11-19 20:38:24 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:24 | D | sum error = [ 178.0057, 186.1077, 194.4799, 203.1303, 212.0605] +24-11-19 20:38:24 | D | best error = [ 3.7347, 3.7347, 3.7347, 3.7347, 3.7347] +24-11-19 20:38:24 | D | + error = [3.7347] +24-11-19 20:38:24 | D | - Quantizing model.layers.26.self_attn.q_proj.weight +24-11-19 20:38:25 | D | - Quantizing model.layers.26.self_attn.k_proj.weight +24-11-19 20:38:26 | D | - Quantizing model.layers.26.self_attn.v_proj.weight +24-11-19 20:38:26 | D | - Quantizing model.layers.26.self_attn.o_proj.weight +24-11-19 20:38:27 | D | - Quantizing model.layers.26.mlp.up_proj.weight +24-11-19 20:38:28 | D | - Quantizing model.layers.26.mlp.gate_proj.weight +24-11-19 20:38:29 | D | - Quantizing model.layers.26.mlp.down_proj.weight +24-11-19 20:38:37 | D | - Quantizing layer model.layers.27 +24-11-19 20:38:37 | D | - Calibrating model.layers.27.self_attn.q_proj.weight +24-11-19 20:38:37 | D | + w: sint8 +24-11-19 20:38:37 | D | + x: None +24-11-19 20:38:37 | D | + y: None +24-11-19 20:38:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:38:37 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:38 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:38 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:38 | D | - range ratio = [ 1.0000] +24-11-19 20:38:38 | D | sum error = [ 16.9834] +24-11-19 20:38:38 | D | best error = [ 16.9834] +24-11-19 20:38:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:51 | D | sum error = [ 16.9219, 16.5613, 16.8430, 16.9936, 17.3837] +24-11-19 20:38:51 | D | best error = [ 16.9219, 16.5613, 16.5613, 16.5613, 16.5613] +24-11-19 20:38:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:51 | D | sum error = [ 17.8453, 18.4108, 19.6305, 20.4380, 21.4873] +24-11-19 20:38:51 | D | best error = [ 16.5613, 16.5613, 16.5613, 16.5613, 16.5613] +24-11-19 20:38:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:51 | D | sum error = [ 22.6851, 25.0416, 26.2090, 28.3173, 30.4924] +24-11-19 20:38:51 | D | best error = [ 16.5613, 16.5613, 16.5613, 16.5613, 16.5613] +24-11-19 20:38:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:51 | D | sum error = [ 32.1192, 34.9263, 37.4466, 40.3357, 43.7034] +24-11-19 20:38:51 | D | best error = [ 16.5613, 16.5613, 16.5613, 16.5613, 16.5613] +24-11-19 20:38:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:51 | D | sum error = [ 47.4655, 51.2352, 56.1004, 59.3440, 63.3413] +24-11-19 20:38:51 | D | best error = [ 16.5613, 16.5613, 16.5613, 16.5613, 16.5613] +24-11-19 20:38:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:51 | D | sum error = [ 68.8267, 73.9820, 79.8349, 85.8127, 91.7827] +24-11-19 20:38:51 | D | best error = [ 16.5613, 16.5613, 16.5613, 16.5613, 16.5613] +24-11-19 20:38:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:51 | D | sum error = [ 98.3167, 105.7363, 112.9351, 121.3664, 130.4764] +24-11-19 20:38:51 | D | best error = [ 16.5613, 16.5613, 16.5613, 16.5613, 16.5613] +24-11-19 20:38:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:51 | D | sum error = [ 140.1167, 149.7287, 160.7007, 172.5249, 185.5326] +24-11-19 20:38:51 | D | best error = [ 16.5613, 16.5613, 16.5613, 16.5613, 16.5613] +24-11-19 20:38:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:51 | D | sum error = [ 199.6255, 214.2242, 230.1364, 247.4517, 266.5308] +24-11-19 20:38:51 | D | best error = [ 16.5613, 16.5613, 16.5613, 16.5613, 16.5613] +24-11-19 20:38:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:51 | D | sum error = [ 286.2293, 307.5369, 330.6780, 355.0057, 381.1497] +24-11-19 20:38:51 | D | best error = [ 16.5613, 16.5613, 16.5613, 16.5613, 16.5613] +24-11-19 20:38:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:51 | D | sum error = [ 409.6155, 439.7716, 472.9832, 509.0001, 547.3848] +24-11-19 20:38:51 | D | best error = [ 16.5613, 16.5613, 16.5613, 16.5613, 16.5613] +24-11-19 20:38:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:51 | D | sum error = [ 589.4839, 635.3342, 684.4897, 737.2688, 795.3082] +24-11-19 20:38:51 | D | best error = [ 16.5613, 16.5613, 16.5613, 16.5613, 16.5613] +24-11-19 20:38:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:51 | D | sum error = [ 858.6144, 927.1244, 1001.2936, 1083.4080, 1173.1835] +24-11-19 20:38:51 | D | best error = [ 16.5613, 16.5613, 16.5613, 16.5613, 16.5613] +24-11-19 20:38:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:51 | D | sum error = [ 1271.2778, 1379.1210, 1498.9096, 1629.4643, 1772.9749] +24-11-19 20:38:51 | D | best error = [ 16.5613, 16.5613, 16.5613, 16.5613, 16.5613] +24-11-19 20:38:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:51 | D | sum error = [ 1931.2264, 2104.5812, 2297.5715, 2508.7664, 2741.3200] +24-11-19 20:38:51 | D | best error = [ 16.5613, 16.5613, 16.5613, 16.5613, 16.5613] +24-11-19 20:38:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:51 | D | sum error = [ 2999.1239, 3284.4590, 3597.7272, 3941.1445, 4312.5371] +24-11-19 20:38:51 | D | best error = [ 16.5613, 16.5613, 16.5613, 16.5613, 16.5613] +24-11-19 20:38:51 | D | + error = [16.5613] +24-11-19 20:38:51 | D | - Calibrating model.layers.27.self_attn.k_proj.weight +24-11-19 20:38:51 | D | + w: sint8 +24-11-19 20:38:51 | D | + x: None +24-11-19 20:38:51 | D | + y: None +24-11-19 20:38:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:38:51 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:51 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:52 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:52 | D | - range ratio = [ 1.0000] +24-11-19 20:38:52 | D | sum error = [ 19.9863] +24-11-19 20:38:52 | D | best error = [ 19.9863] +24-11-19 20:39:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:05 | D | sum error = [ 19.6078, 19.4891, 19.0769, 19.9338, 20.0403] +24-11-19 20:39:05 | D | best error = [ 19.6078, 19.4891, 19.0769, 19.0769, 19.0769] +24-11-19 20:39:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:05 | D | sum error = [ 21.7110, 21.4498, 22.1061, 22.8466, 24.8794] +24-11-19 20:39:05 | D | best error = [ 19.0769, 19.0769, 19.0769, 19.0769, 19.0769] +24-11-19 20:39:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:05 | D | sum error = [ 26.8017, 27.0767, 29.4165, 32.8150, 34.4903] +24-11-19 20:39:05 | D | best error = [ 19.0769, 19.0769, 19.0769, 19.0769, 19.0769] +24-11-19 20:39:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:05 | D | sum error = [ 36.5572, 37.8789, 41.5372, 44.7043, 49.5011] +24-11-19 20:39:05 | D | best error = [ 19.0769, 19.0769, 19.0769, 19.0769, 19.0769] +24-11-19 20:39:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:05 | D | sum error = [ 52.6802, 58.7934, 63.4889, 68.5208, 73.9847] +24-11-19 20:39:05 | D | best error = [ 19.0769, 19.0769, 19.0769, 19.0769, 19.0769] +24-11-19 20:39:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:05 | D | sum error = [ 80.9988, 87.5354, 94.5834, 102.9937, 112.6883] +24-11-19 20:39:05 | D | best error = [ 19.0769, 19.0769, 19.0769, 19.0769, 19.0769] +24-11-19 20:39:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:05 | D | sum error = [ 119.6644, 131.3289, 141.0598, 152.7730, 164.3827] +24-11-19 20:39:05 | D | best error = [ 19.0769, 19.0769, 19.0769, 19.0769, 19.0769] +24-11-19 20:39:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:05 | D | sum error = [ 179.8063, 194.8988, 205.6906, 219.9517, 236.3916] +24-11-19 20:39:05 | D | best error = [ 19.0769, 19.0769, 19.0769, 19.0769, 19.0769] +24-11-19 20:39:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:05 | D | sum error = [ 254.0335, 273.5216, 291.2570, 311.4044, 335.1219] +24-11-19 20:39:05 | D | best error = [ 19.0769, 19.0769, 19.0769, 19.0769, 19.0769] +24-11-19 20:39:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:05 | D | sum error = [ 356.8977, 379.8076, 404.3832, 430.1921, 456.4605] +24-11-19 20:39:05 | D | best error = [ 19.0769, 19.0769, 19.0769, 19.0769, 19.0769] +24-11-19 20:39:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:05 | D | sum error = [ 486.2552, 516.9104, 549.7111, 586.6580, 624.5900] +24-11-19 20:39:05 | D | best error = [ 19.0769, 19.0769, 19.0769, 19.0769, 19.0769] +24-11-19 20:39:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:05 | D | sum error = [ 666.9134, 713.1236, 763.6150, 818.2231, 879.3886] +24-11-19 20:39:05 | D | best error = [ 19.0769, 19.0769, 19.0769, 19.0769, 19.0769] +24-11-19 20:39:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:05 | D | sum error = [ 944.9533, 1013.9369, 1087.4427, 1169.4160, 1258.2775] +24-11-19 20:39:05 | D | best error = [ 19.0769, 19.0769, 19.0769, 19.0769, 19.0769] +24-11-19 20:39:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:05 | D | sum error = [ 1355.5908, 1461.8006, 1577.4806, 1702.8000, 1842.3469] +24-11-19 20:39:05 | D | best error = [ 19.0769, 19.0769, 19.0769, 19.0769, 19.0769] +24-11-19 20:39:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:05 | D | sum error = [ 1995.8142, 2165.2726, 2352.3257, 2565.3536, 2795.5761] +24-11-19 20:39:05 | D | best error = [ 19.0769, 19.0769, 19.0769, 19.0769, 19.0769] +24-11-19 20:39:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:05 | D | sum error = [ 3046.8272, 3334.0939, 3643.1633, 3981.5383, 4348.2327] +24-11-19 20:39:05 | D | best error = [ 19.0769, 19.0769, 19.0769, 19.0769, 19.0769] +24-11-19 20:39:05 | D | + error = [19.0769] +24-11-19 20:39:05 | D | - Calibrating model.layers.27.self_attn.v_proj.weight +24-11-19 20:39:05 | D | + w: sint8 +24-11-19 20:39:05 | D | + x: None +24-11-19 20:39:05 | D | + y: None +24-11-19 20:39:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:05 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:39:05 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:39:05 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:39:05 | D | - range ratio = [ 1.0000] +24-11-19 20:39:05 | D | sum error = [ 8.7442] +24-11-19 20:39:05 | D | best error = [ 8.7442] +24-11-19 20:39:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:06 | D | sum error = [ 8.6580, 8.6659, 8.6783, 8.8057, 8.9231] +24-11-19 20:39:06 | D | best error = [ 8.0866, 7.8397, 7.7000, 7.6217, 7.5782] +24-11-19 20:39:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:06 | D | sum error = [ 9.1533, 9.5019, 9.8707, 10.3350, 10.8674] +24-11-19 20:39:06 | D | best error = [ 7.5574, 7.5479, 7.5446, 7.5437, 7.5433] +24-11-19 20:39:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:06 | D | sum error = [ 11.5042, 12.1960, 13.0164, 13.8875, 14.8565] +24-11-19 20:39:06 | D | best error = [ 7.5433, 7.5433, 7.5433, 7.5433, 7.5433] +24-11-19 20:39:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:06 | D | sum error = [ 15.8716, 17.0337, 18.2335, 19.5205, 20.9624] +24-11-19 20:39:06 | D | best error = [ 7.5433, 7.5433, 7.5433, 7.5433, 7.5433] +24-11-19 20:39:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:06 | D | sum error = [ 22.4892, 24.0736, 25.7135, 27.5121, 29.4367] +24-11-19 20:39:06 | D | best error = [ 7.5433, 7.5433, 7.5433, 7.5433, 7.5433] +24-11-19 20:39:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:06 | D | sum error = [ 31.4859, 33.5723, 35.8794, 38.2556, 40.7684] +24-11-19 20:39:06 | D | best error = [ 7.5433, 7.5433, 7.5433, 7.5433, 7.5433] +24-11-19 20:39:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:06 | D | sum error = [ 43.4490, 46.2161, 49.1456, 52.2399, 55.4834] +24-11-19 20:39:06 | D | best error = [ 7.5433, 7.5433, 7.5433, 7.5433, 7.5433] +24-11-19 20:39:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:06 | D | sum error = [ 58.9227, 62.5105, 66.3164, 70.3132, 74.4911] +24-11-19 20:39:06 | D | best error = [ 7.5433, 7.5433, 7.5433, 7.5433, 7.5433] +24-11-19 20:39:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:06 | D | sum error = [ 78.9189, 83.4971, 88.3043, 93.3384, 98.6262] +24-11-19 20:39:06 | D | best error = [ 7.5433, 7.5433, 7.5433, 7.5433, 7.5433] +24-11-19 20:39:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:06 | D | sum error = [ 104.1349, 109.8947, 115.9312, 122.2566, 128.8206] +24-11-19 20:39:06 | D | best error = [ 7.5433, 7.5433, 7.5433, 7.5433, 7.5433] +24-11-19 20:39:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:06 | D | sum error = [ 135.6481, 142.7542, 150.1509, 157.8392, 165.8254] +24-11-19 20:39:06 | D | best error = [ 7.5433, 7.5433, 7.5433, 7.5433, 7.5433] +24-11-19 20:39:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:06 | D | sum error = [ 174.1017, 182.7243, 191.6912, 200.9852, 210.6419] +24-11-19 20:39:06 | D | best error = [ 7.5433, 7.5433, 7.5433, 7.5433, 7.5433] +24-11-19 20:39:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:06 | D | sum error = [ 220.6460, 231.0152, 241.7357, 252.8515, 264.3552] +24-11-19 20:39:06 | D | best error = [ 7.5433, 7.5433, 7.5433, 7.5433, 7.5433] +24-11-19 20:39:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:06 | D | sum error = [ 276.2465, 288.5525, 301.2395, 314.3584, 327.8692] +24-11-19 20:39:06 | D | best error = [ 7.5433, 7.5433, 7.5433, 7.5433, 7.5433] +24-11-19 20:39:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:06 | D | sum error = [ 341.7881, 356.1583, 370.9730, 386.2260, 401.9053] +24-11-19 20:39:06 | D | best error = [ 7.5433, 7.5433, 7.5433, 7.5433, 7.5433] +24-11-19 20:39:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:06 | D | sum error = [ 418.0711, 434.6754, 451.7513, 469.3286, 487.4073] +24-11-19 20:39:06 | D | best error = [ 7.5433, 7.5433, 7.5433, 7.5433, 7.5433] +24-11-19 20:39:06 | D | + error = [7.5433] +24-11-19 20:39:06 | D | - Calibrating model.layers.27.self_attn.o_proj.weight +24-11-19 20:39:06 | D | + w: sint8 +24-11-19 20:39:06 | D | + x: None +24-11-19 20:39:06 | D | + y: None +24-11-19 20:39:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:06 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:39:06 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:39:06 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:39:06 | D | - range ratio = [ 1.0000] +24-11-19 20:39:06 | D | sum error = [ 2.1055] +24-11-19 20:39:06 | D | best error = [ 2.1055] +24-11-19 20:39:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:07 | D | sum error = [ 2.0875, 2.0795, 2.0815, 2.0925, 2.1133] +24-11-19 20:39:07 | D | best error = [ 1.9901, 1.9376, 1.9067, 1.8864, 1.8731] +24-11-19 20:39:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:07 | D | sum error = [ 2.1474, 2.1905, 2.2635, 2.3378, 2.4320] +24-11-19 20:39:07 | D | best error = [ 1.8648, 1.8584, 1.8546, 1.8522, 1.8509] +24-11-19 20:39:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:07 | D | sum error = [ 2.5406, 2.6759, 2.8155, 2.9756, 3.1544] +24-11-19 20:39:07 | D | best error = [ 1.8500, 1.8496, 1.8492, 1.8491, 1.8488] +24-11-19 20:39:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:07 | D | sum error = [ 3.3479, 3.5668, 3.8067, 4.0556, 4.3280] +24-11-19 20:39:07 | D | best error = [ 1.8487, 1.8487, 1.8486, 1.8486, 1.8486] +24-11-19 20:39:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:07 | D | sum error = [ 4.6235, 4.9389, 5.2668, 5.6298, 6.0047] +24-11-19 20:39:07 | D | best error = [ 1.8486, 1.8486, 1.8486, 1.8486, 1.8486] +24-11-19 20:39:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:07 | D | sum error = [ 6.4130, 6.8400, 7.2914, 7.7712, 8.2903] +24-11-19 20:39:07 | D | best error = [ 1.8486, 1.8486, 1.8486, 1.8486, 1.8486] +24-11-19 20:39:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:07 | D | sum error = [ 8.8260, 9.4014, 10.0011, 10.6436, 11.3228] +24-11-19 20:39:07 | D | best error = [ 1.8486, 1.8486, 1.8486, 1.8486, 1.8486] +24-11-19 20:39:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:07 | D | sum error = [ 12.0326, 12.7896, 13.5791, 14.4143, 15.2970] +24-11-19 20:39:07 | D | best error = [ 1.8486, 1.8486, 1.8486, 1.8486, 1.8486] +24-11-19 20:39:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:07 | D | sum error = [ 16.2277, 17.2033, 18.2337, 19.3157, 20.4588] +24-11-19 20:39:07 | D | best error = [ 1.8486, 1.8486, 1.8486, 1.8486, 1.8486] +24-11-19 20:39:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:07 | D | sum error = [ 21.6529, 22.9070, 24.2294, 25.6175, 27.0806] +24-11-19 20:39:07 | D | best error = [ 1.8486, 1.8486, 1.8486, 1.8486, 1.8486] +24-11-19 20:39:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:07 | D | sum error = [ 28.6116, 30.2146, 31.9001, 33.6591, 35.5037] +24-11-19 20:39:07 | D | best error = [ 1.8486, 1.8486, 1.8486, 1.8486, 1.8486] +24-11-19 20:39:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:07 | D | sum error = [ 37.4359, 39.4563, 41.5710, 43.7815, 46.0953] +24-11-19 20:39:07 | D | best error = [ 1.8486, 1.8486, 1.8486, 1.8486, 1.8486] +24-11-19 20:39:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:07 | D | sum error = [ 48.5054, 51.0255, 53.6560, 56.3990, 59.2531] +24-11-19 20:39:07 | D | best error = [ 1.8486, 1.8486, 1.8486, 1.8486, 1.8486] +24-11-19 20:39:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:07 | D | sum error = [ 62.2299, 65.3308, 68.5553, 71.9215, 75.4046] +24-11-19 20:39:07 | D | best error = [ 1.8486, 1.8486, 1.8486, 1.8486, 1.8486] +24-11-19 20:39:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:07 | D | sum error = [ 79.0300, 82.7949, 86.6988, 90.7526, 94.9517] +24-11-19 20:39:07 | D | best error = [ 1.8486, 1.8486, 1.8486, 1.8486, 1.8486] +24-11-19 20:39:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:07 | D | sum error = [ 99.2956, 103.7905, 108.4347, 113.2384, 118.1946] +24-11-19 20:39:07 | D | best error = [ 1.8486, 1.8486, 1.8486, 1.8486, 1.8486] +24-11-19 20:39:07 | D | + error = [1.8486] +24-11-19 20:39:07 | D | - Calibrating model.layers.27.mlp.up_proj.weight +24-11-19 20:39:07 | D | + w: sint8 +24-11-19 20:39:07 | D | + x: None +24-11-19 20:39:07 | D | + y: None +24-11-19 20:39:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:07 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:39:07 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:39:07 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:39:07 | D | - range ratio = [ 1.0000] +24-11-19 20:39:07 | D | sum error = [ 11.2418] +24-11-19 20:39:07 | D | best error = [ 11.2418] +24-11-19 20:39:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:08 | D | sum error = [ 11.1657, 11.1361, 11.1451, 11.2843, 11.5235] +24-11-19 20:39:08 | D | best error = [ 10.3591, 10.0243, 9.8466, 9.7478, 9.6964] +24-11-19 20:39:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:08 | D | sum error = [ 11.7887, 12.1965, 12.7035, 13.3105, 13.9734] +24-11-19 20:39:08 | D | best error = [ 9.6671, 9.6548, 9.6502, 9.6487, 9.6481] +24-11-19 20:39:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:08 | D | sum error = [ 14.8392, 15.7336, 16.7928, 17.8973, 19.1482] +24-11-19 20:39:08 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:39:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:08 | D | sum error = [ 20.4978, 21.9685, 23.5245, 25.1947, 27.0139] +24-11-19 20:39:08 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:39:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:08 | D | sum error = [ 28.9431, 30.9784, 33.1772, 35.5040, 37.9645] +24-11-19 20:39:08 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:39:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:08 | D | sum error = [ 40.5499, 43.3590, 46.2453, 49.3193, 52.6027] +24-11-19 20:39:08 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:39:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:08 | D | sum error = [ 56.0305, 59.6609, 63.4967, 67.5424, 71.7762] +24-11-19 20:39:08 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:39:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:08 | D | sum error = [ 76.2758, 80.9826, 85.9450, 91.1868, 96.6707] +24-11-19 20:39:08 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:39:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:08 | D | sum error = [ 102.4305, 108.4662, 114.8239, 121.4551, 128.4150] +24-11-19 20:39:08 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:39:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:08 | D | sum error = [ 135.6964, 143.3268, 151.2951, 159.6272, 168.3642] +24-11-19 20:39:08 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:39:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:08 | D | sum error = [ 177.4641, 186.9878, 196.9341, 207.3029, 218.1221] +24-11-19 20:39:08 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:39:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:08 | D | sum error = [ 229.4137, 241.1602, 253.3857, 266.1076, 279.3927] +24-11-19 20:39:08 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:39:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:08 | D | sum error = [ 293.1860, 307.4885, 322.3752, 337.8102, 353.8461] +24-11-19 20:39:08 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:39:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:08 | D | sum error = [ 370.4902, 387.7429, 405.6195, 424.1325, 443.2534] +24-11-19 20:39:08 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:39:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:08 | D | sum error = [ 463.0578, 483.5180, 504.6276, 526.4304, 548.9183] +24-11-19 20:39:08 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:39:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:08 | D | sum error = [ 572.0742, 595.9692, 620.5619, 645.8722, 671.9238] +24-11-19 20:39:08 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:39:08 | D | + error = [9.6481] +24-11-19 20:39:08 | D | - Calibrating model.layers.27.mlp.gate_proj.weight +24-11-19 20:39:08 | D | + w: sint8 +24-11-19 20:39:08 | D | + x: None +24-11-19 20:39:08 | D | + y: None +24-11-19 20:39:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:08 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:39:08 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:39:08 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:39:08 | D | - range ratio = [ 1.0000] +24-11-19 20:39:08 | D | sum error = [ 12.0688] +24-11-19 20:39:08 | D | best error = [ 12.0688] +24-11-19 20:39:09 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:09 | D | sum error = [ 11.9304, 11.9407, 11.9773, 12.1406, 12.3586] +24-11-19 20:39:09 | D | best error = [ 11.1053, 10.7479, 10.5560, 10.4541, 10.3976] +24-11-19 20:39:09 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:09 | D | sum error = [ 12.6526, 13.0557, 13.6236, 14.2592, 14.9614] +24-11-19 20:39:09 | D | best error = [ 10.3719, 10.3601, 10.3552, 10.3534, 10.3530] +24-11-19 20:39:09 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:09 | D | sum error = [ 15.8356, 16.8167, 17.9052, 19.1340, 20.4399] +24-11-19 20:39:09 | D | best error = [ 10.3529, 10.3529, 10.3529, 10.3529, 10.3529] +24-11-19 20:39:09 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:09 | D | sum error = [ 21.8923, 23.4590, 25.1331, 26.9725, 28.8839] +24-11-19 20:39:09 | D | best error = [ 10.3529, 10.3529, 10.3529, 10.3529, 10.3529] +24-11-19 20:39:09 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:09 | D | sum error = [ 30.9766, 33.2313, 35.5690, 38.0759, 40.7257] +24-11-19 20:39:09 | D | best error = [ 10.3529, 10.3529, 10.3529, 10.3529, 10.3529] +24-11-19 20:39:09 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:09 | D | sum error = [ 43.5919, 46.6034, 49.7449, 53.1151, 56.7196] +24-11-19 20:39:09 | D | best error = [ 10.3529, 10.3529, 10.3529, 10.3529, 10.3529] +24-11-19 20:39:09 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:09 | D | sum error = [ 60.4949, 64.4560, 68.6605, 73.0819, 77.7716] +24-11-19 20:39:09 | D | best error = [ 10.3529, 10.3529, 10.3529, 10.3529, 10.3529] +24-11-19 20:39:09 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:09 | D | sum error = [ 82.7486, 88.0163, 93.5060, 99.3636, 105.5204] +24-11-19 20:39:09 | D | best error = [ 10.3529, 10.3529, 10.3529, 10.3529, 10.3529] +24-11-19 20:39:09 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:09 | D | sum error = [ 111.9760, 118.7970, 125.9751, 133.5242, 141.4696] +24-11-19 20:39:09 | D | best error = [ 10.3529, 10.3529, 10.3529, 10.3529, 10.3529] +24-11-19 20:39:09 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:09 | D | sum error = [ 149.8222, 158.5528, 167.7746, 177.4309, 187.5834] +24-11-19 20:39:09 | D | best error = [ 10.3529, 10.3529, 10.3529, 10.3529, 10.3529] +24-11-19 20:39:09 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:09 | D | sum error = [ 198.2417, 209.4165, 221.1221, 233.3881, 246.2965] +24-11-19 20:39:09 | D | best error = [ 10.3529, 10.3529, 10.3529, 10.3529, 10.3529] +24-11-19 20:39:09 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:09 | D | sum error = [ 259.7909, 273.8856, 288.6481, 304.1246, 320.2439] +24-11-19 20:39:09 | D | best error = [ 10.3529, 10.3529, 10.3529, 10.3529, 10.3529] +24-11-19 20:39:09 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:09 | D | sum error = [ 337.1500, 354.7670, 373.1188, 392.2480, 412.2178] +24-11-19 20:39:09 | D | best error = [ 10.3529, 10.3529, 10.3529, 10.3529, 10.3529] +24-11-19 20:39:09 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:09 | D | sum error = [ 433.0145, 454.6281, 477.1514, 500.5286, 524.7756] +24-11-19 20:39:09 | D | best error = [ 10.3529, 10.3529, 10.3529, 10.3529, 10.3529] +24-11-19 20:39:09 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:09 | D | sum error = [ 549.9644, 576.0972, 603.1708, 631.2666, 660.3292] +24-11-19 20:39:09 | D | best error = [ 10.3529, 10.3529, 10.3529, 10.3529, 10.3529] +24-11-19 20:39:09 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:09 | D | sum error = [ 690.3732, 721.3693, 753.3298, 786.2900, 820.2720] +24-11-19 20:39:09 | D | best error = [ 10.3529, 10.3529, 10.3529, 10.3529, 10.3529] +24-11-19 20:39:09 | D | + error = [10.3529] +24-11-19 20:39:09 | D | - Calibrating model.layers.27.mlp.down_proj.weight +24-11-19 20:39:09 | D | + w: sint8 +24-11-19 20:39:09 | D | + x: None +24-11-19 20:39:09 | D | + y: None +24-11-19 20:39:09 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:09 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:39:10 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:39:10 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:39:10 | D | - range ratio = [ 1.0000] +24-11-19 20:39:10 | D | sum error = [ 4.5001] +24-11-19 20:39:10 | D | best error = [ 4.5001] +24-11-19 20:39:11 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:11 | D | sum error = [ 4.4561, 4.4264, 4.4098, 4.3946, 4.3928] +24-11-19 20:39:11 | D | best error = [ 4.3070, 4.2165, 4.1579, 4.1140, 4.0836] +24-11-19 20:39:11 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:11 | D | sum error = [ 4.4068, 4.4391, 4.4814, 4.5615, 4.6529] +24-11-19 20:39:11 | D | best error = [ 4.0591, 4.0418, 4.0266, 4.0170, 4.0106] +24-11-19 20:39:11 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:11 | D | sum error = [ 4.7683, 4.8991, 5.0862, 5.2859, 5.5161] +24-11-19 20:39:11 | D | best error = [ 4.0060, 4.0028, 4.0014, 3.9999, 3.9992] +24-11-19 20:39:11 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:11 | D | sum error = [ 5.7899, 6.0882, 6.4211, 6.8012, 7.2023] +24-11-19 20:39:11 | D | best error = [ 3.9988, 3.9985, 3.9982, 3.9981, 3.9981] +24-11-19 20:39:11 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:11 | D | sum error = [ 7.6524, 8.1410, 8.6885, 9.2666, 9.8916] +24-11-19 20:39:11 | D | best error = [ 3.9981, 3.9981, 3.9981, 3.9981, 3.9981] +24-11-19 20:39:11 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:11 | D | sum error = [ 10.5805, 11.2972, 12.0745, 12.9168, 13.8004] +24-11-19 20:39:11 | D | best error = [ 3.9981, 3.9981, 3.9981, 3.9981, 3.9981] +24-11-19 20:39:11 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:11 | D | sum error = [ 14.7533, 15.7731, 16.8507, 18.0013, 19.2160] +24-11-19 20:39:11 | D | best error = [ 3.9981, 3.9981, 3.9981, 3.9981, 3.9981] +24-11-19 20:39:11 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:11 | D | sum error = [ 20.5173, 21.8881, 23.3551, 24.8823, 26.5218] +24-11-19 20:39:11 | D | best error = [ 3.9981, 3.9981, 3.9981, 3.9981, 3.9981] +24-11-19 20:39:11 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:11 | D | sum error = [ 28.2457, 30.0634, 31.9942, 34.0180, 36.1630] +24-11-19 20:39:11 | D | best error = [ 3.9981, 3.9981, 3.9981, 3.9981, 3.9981] +24-11-19 20:39:11 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:11 | D | sum error = [ 38.4271, 40.7975, 43.3070, 45.9422, 48.7173] +24-11-19 20:39:11 | D | best error = [ 3.9981, 3.9981, 3.9981, 3.9981, 3.9981] +24-11-19 20:39:11 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:11 | D | sum error = [ 51.6315, 54.6843, 57.8959, 61.2689, 64.7932] +24-11-19 20:39:11 | D | best error = [ 3.9981, 3.9981, 3.9981, 3.9981, 3.9981] +24-11-19 20:39:11 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:11 | D | sum error = [ 68.4943, 72.3744, 76.4318, 80.6729, 85.1094] +24-11-19 20:39:11 | D | best error = [ 3.9981, 3.9981, 3.9981, 3.9981, 3.9981] +24-11-19 20:39:11 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:11 | D | sum error = [ 89.7546, 94.5951, 99.6501, 104.9164, 110.4073] +24-11-19 20:39:11 | D | best error = [ 3.9981, 3.9981, 3.9981, 3.9981, 3.9981] +24-11-19 20:39:11 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:11 | D | sum error = [ 116.1223, 122.0786, 128.2777, 134.7262, 141.4024] +24-11-19 20:39:11 | D | best error = [ 3.9981, 3.9981, 3.9981, 3.9981, 3.9981] +24-11-19 20:39:11 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:11 | D | sum error = [ 148.3444, 155.5441, 163.0117, 170.7505, 178.7645] +24-11-19 20:39:11 | D | best error = [ 3.9981, 3.9981, 3.9981, 3.9981, 3.9981] +24-11-19 20:39:11 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:11 | D | sum error = [ 187.0552, 195.6347, 204.4949, 213.6552, 223.1086] +24-11-19 20:39:11 | D | best error = [ 3.9981, 3.9981, 3.9981, 3.9981, 3.9981] +24-11-19 20:39:11 | D | + error = [3.9981] +24-11-19 20:39:11 | D | - Quantizing model.layers.27.self_attn.q_proj.weight +24-11-19 20:39:12 | D | - Quantizing model.layers.27.self_attn.k_proj.weight +24-11-19 20:39:13 | D | - Quantizing model.layers.27.self_attn.v_proj.weight +24-11-19 20:39:14 | D | - Quantizing model.layers.27.self_attn.o_proj.weight +24-11-19 20:39:14 | D | - Quantizing model.layers.27.mlp.up_proj.weight +24-11-19 20:39:15 | D | - Quantizing model.layers.27.mlp.gate_proj.weight +24-11-19 20:39:16 | D | - Quantizing model.layers.27.mlp.down_proj.weight +24-11-19 20:39:25 | D | - Quantizing layer model.layers.28 +24-11-19 20:39:25 | D | - Calibrating model.layers.28.self_attn.q_proj.weight +24-11-19 20:39:25 | D | + w: sint8 +24-11-19 20:39:25 | D | + x: None +24-11-19 20:39:25 | D | + y: None +24-11-19 20:39:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:39:25 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:39:25 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:39:25 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:39:25 | D | - range ratio = [ 1.0000] +24-11-19 20:39:25 | D | sum error = [ 18.8607] +24-11-19 20:39:25 | D | best error = [ 18.8607] +24-11-19 20:39:39 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:39 | D | sum error = [ 18.8465, 18.9613, 19.0418, 18.9491, 19.2373] +24-11-19 20:39:39 | D | best error = [ 18.8465, 18.8465, 18.8465, 18.8465, 18.8465] +24-11-19 20:39:39 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:39 | D | sum error = [ 20.2978, 20.4933, 22.1330, 22.4939, 24.0132] +24-11-19 20:39:39 | D | best error = [ 18.8465, 18.8465, 18.8465, 18.8465, 18.8465] +24-11-19 20:39:39 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:39 | D | sum error = [ 25.6712, 26.5061, 28.5934, 30.1318, 32.7833] +24-11-19 20:39:39 | D | best error = [ 18.8465, 18.8465, 18.8465, 18.8465, 18.8465] +24-11-19 20:39:39 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:39 | D | sum error = [ 34.7456, 37.6746, 41.0816, 43.4569, 47.0924] +24-11-19 20:39:39 | D | best error = [ 18.8465, 18.8465, 18.8465, 18.8465, 18.8465] +24-11-19 20:39:39 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:39 | D | sum error = [ 50.3981, 54.9542, 59.0270, 63.8521, 67.5441] +24-11-19 20:39:39 | D | best error = [ 18.8465, 18.8465, 18.8465, 18.8465, 18.8465] +24-11-19 20:39:39 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:39 | D | sum error = [ 73.7314, 79.5219, 85.6230, 93.0967, 100.0820] +24-11-19 20:39:39 | D | best error = [ 18.8465, 18.8465, 18.8465, 18.8465, 18.8465] +24-11-19 20:39:39 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:39 | D | sum error = [ 107.7980, 116.1191, 125.0845, 135.7523, 145.4021] +24-11-19 20:39:39 | D | best error = [ 18.8465, 18.8465, 18.8465, 18.8465, 18.8465] +24-11-19 20:39:39 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:39 | D | sum error = [ 156.7854, 168.5996, 181.9263, 194.2466, 209.2532] +24-11-19 20:39:39 | D | best error = [ 18.8465, 18.8465, 18.8465, 18.8465, 18.8465] +24-11-19 20:39:39 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:39 | D | sum error = [ 224.7208, 240.6212, 257.6552, 277.2963, 296.3654] +24-11-19 20:39:39 | D | best error = [ 18.8465, 18.8465, 18.8465, 18.8465, 18.8465] +24-11-19 20:39:39 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:39 | D | sum error = [ 318.4175, 342.1666, 367.1826, 394.3674, 423.8066] +24-11-19 20:39:39 | D | best error = [ 18.8465, 18.8465, 18.8465, 18.8465, 18.8465] +24-11-19 20:39:39 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:39 | D | sum error = [ 454.1915, 487.5876, 523.1367, 560.9809, 602.8846] +24-11-19 20:39:39 | D | best error = [ 18.8465, 18.8465, 18.8465, 18.8465, 18.8465] +24-11-19 20:39:39 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:39 | D | sum error = [ 646.8178, 694.9454, 745.3233, 801.0626, 860.4369] +24-11-19 20:39:39 | D | best error = [ 18.8465, 18.8465, 18.8465, 18.8465, 18.8465] +24-11-19 20:39:39 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:39 | D | sum error = [ 924.9762, 994.7930, 1071.4286, 1153.9539, 1243.6811] +24-11-19 20:39:39 | D | best error = [ 18.8465, 18.8465, 18.8465, 18.8465, 18.8465] +24-11-19 20:39:39 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:39 | D | sum error = [ 1341.2646, 1449.7291, 1568.3610, 1698.3987, 1841.8316] +24-11-19 20:39:39 | D | best error = [ 18.8465, 18.8465, 18.8465, 18.8465, 18.8465] +24-11-19 20:39:39 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:39 | D | sum error = [ 1998.8899, 2173.0198, 2366.6599, 2578.7731, 2814.1848] +24-11-19 20:39:39 | D | best error = [ 18.8465, 18.8465, 18.8465, 18.8465, 18.8465] +24-11-19 20:39:39 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:39 | D | sum error = [ 3074.7504, 3362.9013, 3680.3405, 4028.8251, 4410.3118] +24-11-19 20:39:39 | D | best error = [ 18.8465, 18.8465, 18.8465, 18.8465, 18.8465] +24-11-19 20:39:39 | D | + error = [18.8465] +24-11-19 20:39:39 | D | - Calibrating model.layers.28.self_attn.k_proj.weight +24-11-19 20:39:39 | D | + w: sint8 +24-11-19 20:39:39 | D | + x: None +24-11-19 20:39:39 | D | + y: None +24-11-19 20:39:39 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:39:39 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:39:39 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:39:39 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:39:39 | D | - range ratio = [ 1.0000] +24-11-19 20:39:39 | D | sum error = [ 23.5714] +24-11-19 20:39:39 | D | best error = [ 23.5714] +24-11-19 20:39:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:52 | D | sum error = [ 21.5028, 21.7660, 21.4084, 22.7339, 24.7673] +24-11-19 20:39:52 | D | best error = [ 21.5028, 21.5028, 21.4084, 21.4084, 21.4084] +24-11-19 20:39:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:52 | D | sum error = [ 23.3417, 25.2889, 26.8202, 26.4107, 28.1382] +24-11-19 20:39:52 | D | best error = [ 21.4084, 21.4084, 21.4084, 21.4084, 21.4084] +24-11-19 20:39:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:52 | D | sum error = [ 29.8371, 33.1920, 32.7359, 37.5708, 40.3278] +24-11-19 20:39:52 | D | best error = [ 21.4084, 21.4084, 21.4084, 21.4084, 21.4084] +24-11-19 20:39:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:52 | D | sum error = [ 42.7757, 45.0317, 48.4312, 54.2495, 57.7048] +24-11-19 20:39:52 | D | best error = [ 21.4084, 21.4084, 21.4084, 21.4084, 21.4084] +24-11-19 20:39:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:52 | D | sum error = [ 61.3548, 66.2431, 70.6304, 75.3536, 81.3234] +24-11-19 20:39:52 | D | best error = [ 21.4084, 21.4084, 21.4084, 21.4084, 21.4084] +24-11-19 20:39:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:52 | D | sum error = [ 86.9124, 92.0584, 97.9648, 106.4076, 113.2177] +24-11-19 20:39:52 | D | best error = [ 21.4084, 21.4084, 21.4084, 21.4084, 21.4084] +24-11-19 20:39:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:52 | D | sum error = [ 120.8912, 129.8893, 138.3240, 148.6062, 156.9000] +24-11-19 20:39:52 | D | best error = [ 21.4084, 21.4084, 21.4084, 21.4084, 21.4084] +24-11-19 20:39:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:52 | D | sum error = [ 169.0332, 179.5429, 193.9550, 207.0658, 222.2695] +24-11-19 20:39:52 | D | best error = [ 21.4084, 21.4084, 21.4084, 21.4084, 21.4084] +24-11-19 20:39:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:52 | D | sum error = [ 238.1889, 254.7340, 271.9541, 291.2540, 312.6731] +24-11-19 20:39:52 | D | best error = [ 21.4084, 21.4084, 21.4084, 21.4084, 21.4084] +24-11-19 20:39:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:52 | D | sum error = [ 334.9963, 358.7131, 382.4342, 408.6495, 437.5912] +24-11-19 20:39:52 | D | best error = [ 21.4084, 21.4084, 21.4084, 21.4084, 21.4084] +24-11-19 20:39:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:52 | D | sum error = [ 468.9223, 502.9002, 539.7539, 579.5080, 623.2976] +24-11-19 20:39:52 | D | best error = [ 21.4084, 21.4084, 21.4084, 21.4084, 21.4084] +24-11-19 20:39:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:52 | D | sum error = [ 669.9163, 720.5945, 775.2043, 834.0449, 901.8837] +24-11-19 20:39:52 | D | best error = [ 21.4084, 21.4084, 21.4084, 21.4084, 21.4084] +24-11-19 20:39:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:52 | D | sum error = [ 972.6172, 1049.2740, 1133.4221, 1228.3027, 1329.3182] +24-11-19 20:39:52 | D | best error = [ 21.4084, 21.4084, 21.4084, 21.4084, 21.4084] +24-11-19 20:39:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:52 | D | sum error = [ 1440.8950, 1560.4602, 1690.9950, 1833.1933, 1986.8612] +24-11-19 20:39:52 | D | best error = [ 21.4084, 21.4084, 21.4084, 21.4084, 21.4084] +24-11-19 20:39:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:52 | D | sum error = [ 2154.4157, 2336.9553, 2541.1887, 2762.1174, 3006.2176] +24-11-19 20:39:52 | D | best error = [ 21.4084, 21.4084, 21.4084, 21.4084, 21.4084] +24-11-19 20:39:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:52 | D | sum error = [ 3272.3863, 3560.3031, 3883.7390, 4239.2929, 4629.6531] +24-11-19 20:39:52 | D | best error = [ 21.4084, 21.4084, 21.4084, 21.4084, 21.4084] +24-11-19 20:39:52 | D | + error = [21.4084] +24-11-19 20:39:52 | D | - Calibrating model.layers.28.self_attn.v_proj.weight +24-11-19 20:39:52 | D | + w: sint8 +24-11-19 20:39:52 | D | + x: None +24-11-19 20:39:52 | D | + y: None +24-11-19 20:39:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:52 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:39:52 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:39:52 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:39:52 | D | - range ratio = [ 1.0000] +24-11-19 20:39:52 | D | sum error = [ 9.1232] +24-11-19 20:39:52 | D | best error = [ 9.1232] +24-11-19 20:39:53 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:53 | D | sum error = [ 9.0496, 9.0801, 9.1000, 9.2264, 9.3537] +24-11-19 20:39:53 | D | best error = [ 8.4568, 8.2024, 8.0670, 7.9893, 7.9514] +24-11-19 20:39:53 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:53 | D | sum error = [ 9.5992, 9.9030, 10.3094, 10.8336, 11.3576] +24-11-19 20:39:53 | D | best error = [ 7.9326, 7.9232, 7.9185, 7.9178, 7.9177] +24-11-19 20:39:53 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:53 | D | sum error = [ 12.0497, 12.7902, 13.6460, 14.5239, 15.4966] +24-11-19 20:39:53 | D | best error = [ 7.9177, 7.9177, 7.9177, 7.9177, 7.9177] +24-11-19 20:39:53 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:53 | D | sum error = [ 16.6177, 17.7945, 19.0560, 20.3889, 21.8789] +24-11-19 20:39:53 | D | best error = [ 7.9177, 7.9177, 7.9177, 7.9177, 7.9177] +24-11-19 20:39:53 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:53 | D | sum error = [ 23.3693, 25.0745, 26.8442, 28.6720, 30.6264] +24-11-19 20:39:53 | D | best error = [ 7.9177, 7.9177, 7.9177, 7.9177, 7.9177] +24-11-19 20:39:53 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:53 | D | sum error = [ 32.7450, 34.9027, 37.2536, 39.7405, 42.3425] +24-11-19 20:39:53 | D | best error = [ 7.9177, 7.9177, 7.9177, 7.9177, 7.9177] +24-11-19 20:39:53 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:53 | D | sum error = [ 45.1072, 47.9737, 51.0477, 54.2787, 57.6558] +24-11-19 20:39:53 | D | best error = [ 7.9177, 7.9177, 7.9177, 7.9177, 7.9177] +24-11-19 20:39:53 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:53 | D | sum error = [ 61.2645, 64.9602, 68.8848, 73.0158, 77.3679] +24-11-19 20:39:53 | D | best error = [ 7.9177, 7.9177, 7.9177, 7.9177, 7.9177] +24-11-19 20:39:53 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:53 | D | sum error = [ 81.9137, 86.6921, 91.7234, 96.9426, 102.4276] +24-11-19 20:39:53 | D | best error = [ 7.9177, 7.9177, 7.9177, 7.9177, 7.9177] +24-11-19 20:39:53 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:53 | D | sum error = [ 108.1510, 114.1752, 120.4243, 126.9888, 133.8491] +24-11-19 20:39:53 | D | best error = [ 7.9177, 7.9177, 7.9177, 7.9177, 7.9177] +24-11-19 20:39:53 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:53 | D | sum error = [ 141.0042, 148.4580, 156.2054, 164.2970, 172.6729] +24-11-19 20:39:53 | D | best error = [ 7.9177, 7.9177, 7.9177, 7.9177, 7.9177] +24-11-19 20:39:53 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:53 | D | sum error = [ 181.4358, 190.5566, 199.9945, 209.7779, 219.9338] +24-11-19 20:39:53 | D | best error = [ 7.9177, 7.9177, 7.9177, 7.9177, 7.9177] +24-11-19 20:39:53 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:53 | D | sum error = [ 230.5035, 241.4299, 252.7358, 264.4530, 276.5886] +24-11-19 20:39:53 | D | best error = [ 7.9177, 7.9177, 7.9177, 7.9177, 7.9177] +24-11-19 20:39:53 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:53 | D | sum error = [ 289.1344, 302.1484, 315.5951, 329.4748, 343.7895] +24-11-19 20:39:53 | D | best error = [ 7.9177, 7.9177, 7.9177, 7.9177, 7.9177] +24-11-19 20:39:53 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:53 | D | sum error = [ 358.5381, 373.7348, 389.4023, 405.5667, 422.2053] +24-11-19 20:39:53 | D | best error = [ 7.9177, 7.9177, 7.9177, 7.9177, 7.9177] +24-11-19 20:39:53 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:53 | D | sum error = [ 439.3433, 456.9946, 475.1446, 493.8315, 513.0228] +24-11-19 20:39:53 | D | best error = [ 7.9177, 7.9177, 7.9177, 7.9177, 7.9177] +24-11-19 20:39:53 | D | + error = [7.9177] +24-11-19 20:39:53 | D | - Calibrating model.layers.28.self_attn.o_proj.weight +24-11-19 20:39:53 | D | + w: sint8 +24-11-19 20:39:53 | D | + x: None +24-11-19 20:39:53 | D | + y: None +24-11-19 20:39:53 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:53 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:39:53 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:39:53 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:39:53 | D | - range ratio = [ 1.0000] +24-11-19 20:39:53 | D | sum error = [ 2.1611] +24-11-19 20:39:53 | D | best error = [ 2.1611] +24-11-19 20:39:54 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:54 | D | sum error = [ 2.1410, 2.1421, 2.1588, 2.1941, 2.2390] +24-11-19 20:39:54 | D | best error = [ 2.0367, 1.9845, 1.9551, 1.9367, 1.9250] +24-11-19 20:39:54 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:54 | D | sum error = [ 2.3026, 2.3917, 2.4968, 2.6190, 2.7691] +24-11-19 20:39:54 | D | best error = [ 1.9166, 1.9108, 1.9073, 1.9047, 1.9029] +24-11-19 20:39:54 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:54 | D | sum error = [ 2.9363, 3.1243, 3.3327, 3.5539, 3.8006] +24-11-19 20:39:54 | D | best error = [ 1.9018, 1.9011, 1.9007, 1.9006, 1.9005] +24-11-19 20:39:54 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:54 | D | sum error = [ 4.0563, 4.3484, 4.6496, 4.9743, 5.3086] +24-11-19 20:39:54 | D | best error = [ 1.9004, 1.9004, 1.9003, 1.9003, 1.9003] +24-11-19 20:39:54 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:54 | D | sum error = [ 5.6814, 6.0735, 6.4763, 6.9212, 7.3742] +24-11-19 20:39:54 | D | best error = [ 1.9003, 1.9003, 1.9003, 1.9003, 1.9003] +24-11-19 20:39:54 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:54 | D | sum error = [ 7.8645, 8.3617, 8.9047, 9.4678, 10.0669] +24-11-19 20:39:54 | D | best error = [ 1.9003, 1.9003, 1.9003, 1.9003, 1.9003] +24-11-19 20:39:54 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:54 | D | sum error = [ 10.6878, 11.3419, 12.0321, 12.7699, 13.5362] +24-11-19 20:39:54 | D | best error = [ 1.9003, 1.9003, 1.9003, 1.9003, 1.9003] +24-11-19 20:39:54 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:54 | D | sum error = [ 14.3364, 15.1928, 16.0800, 17.0153, 17.9943] +24-11-19 20:39:54 | D | best error = [ 1.9003, 1.9003, 1.9003, 1.9003, 1.9003] +24-11-19 20:39:54 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:54 | D | sum error = [ 19.0260, 20.1119, 21.2394, 22.4337, 23.6829] +24-11-19 20:39:54 | D | best error = [ 1.9003, 1.9003, 1.9003, 1.9003, 1.9003] +24-11-19 20:39:54 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:54 | D | sum error = [ 24.9953, 26.3808, 27.8248, 29.3415, 30.9265] +24-11-19 20:39:54 | D | best error = [ 1.9003, 1.9003, 1.9003, 1.9003, 1.9003] +24-11-19 20:39:54 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:54 | D | sum error = [ 32.5920, 34.3403, 36.1729, 38.0890, 40.0946] +24-11-19 20:39:54 | D | best error = [ 1.9003, 1.9003, 1.9003, 1.9003, 1.9003] +24-11-19 20:39:54 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:54 | D | sum error = [ 42.1864, 44.3778, 46.6657, 49.0577, 51.5595] +24-11-19 20:39:54 | D | best error = [ 1.9003, 1.9003, 1.9003, 1.9003, 1.9003] +24-11-19 20:39:54 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:54 | D | sum error = [ 54.1675, 56.8902, 59.7361, 62.7050, 65.7971] +24-11-19 20:39:54 | D | best error = [ 1.9003, 1.9003, 1.9003, 1.9003, 1.9003] +24-11-19 20:39:54 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:54 | D | sum error = [ 69.0147, 72.3644, 75.8613, 79.4971, 83.2699] +24-11-19 20:39:54 | D | best error = [ 1.9003, 1.9003, 1.9003, 1.9003, 1.9003] +24-11-19 20:39:54 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:54 | D | sum error = [ 87.1948, 91.2769, 95.5172, 99.9190, 104.4755] +24-11-19 20:39:54 | D | best error = [ 1.9003, 1.9003, 1.9003, 1.9003, 1.9003] +24-11-19 20:39:54 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:54 | D | sum error = [ 109.1969, 114.0845, 119.1390, 124.3599, 129.7522] +24-11-19 20:39:54 | D | best error = [ 1.9003, 1.9003, 1.9003, 1.9003, 1.9003] +24-11-19 20:39:54 | D | + error = [1.9003] +24-11-19 20:39:54 | D | - Calibrating model.layers.28.mlp.up_proj.weight +24-11-19 20:39:54 | D | + w: sint8 +24-11-19 20:39:54 | D | + x: None +24-11-19 20:39:54 | D | + y: None +24-11-19 20:39:54 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:54 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:39:54 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:39:54 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:39:54 | D | - range ratio = [ 1.0000] +24-11-19 20:39:54 | D | sum error = [ 11.5523] +24-11-19 20:39:54 | D | best error = [ 11.5523] +24-11-19 20:39:55 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:55 | D | sum error = [ 11.4991, 11.4881, 11.4806, 11.6241, 11.8440] +24-11-19 20:39:55 | D | best error = [ 10.6639, 10.3165, 10.1307, 10.0301, 9.9769] +24-11-19 20:39:55 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:55 | D | sum error = [ 12.1668, 12.5576, 13.0444, 13.6596, 14.4295] +24-11-19 20:39:55 | D | best error = [ 9.9487, 9.9360, 9.9308, 9.9298, 9.9293] +24-11-19 20:39:55 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:55 | D | sum error = [ 15.2425, 16.1698, 17.2356, 18.4154, 19.7337] +24-11-19 20:39:55 | D | best error = [ 9.9293, 9.9293, 9.9293, 9.9293, 9.9293] +24-11-19 20:39:55 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:55 | D | sum error = [ 21.0857, 22.5845, 24.2391, 25.9614, 27.8958] +24-11-19 20:39:55 | D | best error = [ 9.9293, 9.9293, 9.9293, 9.9293, 9.9293] +24-11-19 20:39:55 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:55 | D | sum error = [ 29.8690, 31.9745, 34.2612, 36.6413, 39.1873] +24-11-19 20:39:55 | D | best error = [ 9.9293, 9.9293, 9.9293, 9.9293, 9.9293] +24-11-19 20:39:55 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:55 | D | sum error = [ 41.8969, 44.7937, 47.8086, 51.0446, 54.4059] +24-11-19 20:39:55 | D | best error = [ 9.9293, 9.9293, 9.9293, 9.9293, 9.9293] +24-11-19 20:39:55 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:55 | D | sum error = [ 58.0057, 61.7829, 65.7989, 70.0256, 74.4741] +24-11-19 20:39:55 | D | best error = [ 9.9293, 9.9293, 9.9293, 9.9293, 9.9293] +24-11-19 20:39:55 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:55 | D | sum error = [ 79.1452, 84.0907, 89.2641, 94.6930, 100.4560] +24-11-19 20:39:55 | D | best error = [ 9.9293, 9.9293, 9.9293, 9.9293, 9.9293] +24-11-19 20:39:55 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:55 | D | sum error = [ 106.5133, 112.8467, 119.5344, 126.5223, 133.8715] +24-11-19 20:39:55 | D | best error = [ 9.9293, 9.9293, 9.9293, 9.9293, 9.9293] +24-11-19 20:39:55 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:55 | D | sum error = [ 141.5796, 149.6582, 158.1260, 166.9826, 176.2937] +24-11-19 20:39:55 | D | best error = [ 9.9293, 9.9293, 9.9293, 9.9293, 9.9293] +24-11-19 20:39:55 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:55 | D | sum error = [ 185.9950, 196.1717, 206.8157, 217.9418, 229.5418] +24-11-19 20:39:55 | D | best error = [ 9.9293, 9.9293, 9.9293, 9.9293, 9.9293] +24-11-19 20:39:55 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:55 | D | sum error = [ 241.6795, 254.3213, 267.5252, 281.3402, 295.7061] +24-11-19 20:39:55 | D | best error = [ 9.9293, 9.9293, 9.9293, 9.9293, 9.9293] +24-11-19 20:39:55 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:55 | D | sum error = [ 310.7049, 326.2999, 342.5295, 359.4277, 376.9899] +24-11-19 20:39:55 | D | best error = [ 9.9293, 9.9293, 9.9293, 9.9293, 9.9293] +24-11-19 20:39:55 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:55 | D | sum error = [ 395.2533, 414.2293, 433.9081, 454.3393, 475.5195] +24-11-19 20:39:55 | D | best error = [ 9.9293, 9.9293, 9.9293, 9.9293, 9.9293] +24-11-19 20:39:55 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:55 | D | sum error = [ 497.4383, 520.1494, 543.6188, 567.8972, 593.0248] +24-11-19 20:39:55 | D | best error = [ 9.9293, 9.9293, 9.9293, 9.9293, 9.9293] +24-11-19 20:39:55 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:55 | D | sum error = [ 618.9493, 645.7092, 673.3019, 701.7374, 731.0273] +24-11-19 20:39:55 | D | best error = [ 9.9293, 9.9293, 9.9293, 9.9293, 9.9293] +24-11-19 20:39:55 | D | + error = [9.9293] +24-11-19 20:39:55 | D | - Calibrating model.layers.28.mlp.gate_proj.weight +24-11-19 20:39:55 | D | + w: sint8 +24-11-19 20:39:55 | D | + x: None +24-11-19 20:39:55 | D | + y: None +24-11-19 20:39:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:55 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:39:55 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:39:55 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:39:55 | D | - range ratio = [ 1.0000] +24-11-19 20:39:55 | D | sum error = [ 12.2295] +24-11-19 20:39:55 | D | best error = [ 12.2295] +24-11-19 20:39:56 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:56 | D | sum error = [ 12.1352, 12.1054, 12.1747, 12.3343, 12.4890] +24-11-19 20:39:56 | D | best error = [ 11.2760, 10.9069, 10.7141, 10.6116, 10.5495] +24-11-19 20:39:56 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:56 | D | sum error = [ 12.8239, 13.2973, 13.8469, 14.5020, 15.2520] +24-11-19 20:39:56 | D | best error = [ 10.5199, 10.5071, 10.5019, 10.5006, 10.5003] +24-11-19 20:39:56 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:56 | D | sum error = [ 16.1094, 17.1343, 18.2084, 19.4977, 20.8530] +24-11-19 20:39:56 | D | best error = [ 10.5001, 10.5001, 10.5001, 10.5001, 10.5001] +24-11-19 20:39:56 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:56 | D | sum error = [ 22.3267, 23.9266, 25.6240, 27.4705, 29.4939] +24-11-19 20:39:56 | D | best error = [ 10.5001, 10.5001, 10.5001, 10.5001, 10.5001] +24-11-19 20:39:56 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:56 | D | sum error = [ 31.6156, 33.8630, 36.2840, 38.8756, 41.6290] +24-11-19 20:39:56 | D | best error = [ 10.5001, 10.5001, 10.5001, 10.5001, 10.5001] +24-11-19 20:39:56 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:56 | D | sum error = [ 44.5289, 47.6234, 50.9098, 54.3289, 58.0160] +24-11-19 20:39:56 | D | best error = [ 10.5001, 10.5001, 10.5001, 10.5001, 10.5001] +24-11-19 20:39:56 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:56 | D | sum error = [ 61.8520, 65.9764, 70.3054, 74.9014, 79.7879] +24-11-19 20:39:56 | D | best error = [ 10.5001, 10.5001, 10.5001, 10.5001, 10.5001] +24-11-19 20:39:56 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:56 | D | sum error = [ 84.8981, 90.2631, 96.0003, 102.0173, 108.3332] +24-11-19 20:39:56 | D | best error = [ 10.5001, 10.5001, 10.5001, 10.5001, 10.5001] +24-11-19 20:39:56 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:56 | D | sum error = [ 115.0974, 122.1227, 129.5780, 137.4142, 145.6679] +24-11-19 20:39:56 | D | best error = [ 10.5001, 10.5001, 10.5001, 10.5001, 10.5001] +24-11-19 20:39:56 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:56 | D | sum error = [ 154.3366, 163.4701, 173.0644, 183.1777, 193.7780] +24-11-19 20:39:56 | D | best error = [ 10.5001, 10.5001, 10.5001, 10.5001, 10.5001] +24-11-19 20:39:56 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:56 | D | sum error = [ 204.8925, 216.5090, 228.7047, 241.5398, 254.9449] +24-11-19 20:39:56 | D | best error = [ 10.5001, 10.5001, 10.5001, 10.5001, 10.5001] +24-11-19 20:39:56 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:56 | D | sum error = [ 269.0489, 283.7607, 299.2005, 315.3347, 332.1947] +24-11-19 20:39:56 | D | best error = [ 10.5001, 10.5001, 10.5001, 10.5001, 10.5001] +24-11-19 20:39:56 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:56 | D | sum error = [ 349.8651, 368.2365, 387.4863, 407.5664, 428.4835] +24-11-19 20:39:56 | D | best error = [ 10.5001, 10.5001, 10.5001, 10.5001, 10.5001] +24-11-19 20:39:56 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:56 | D | sum error = [ 450.2652, 472.9027, 496.4673, 520.9621, 546.3821] +24-11-19 20:39:56 | D | best error = [ 10.5001, 10.5001, 10.5001, 10.5001, 10.5001] +24-11-19 20:39:56 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:56 | D | sum error = [ 572.7650, 600.1174, 628.4553, 657.8118, 688.2359] +24-11-19 20:39:56 | D | best error = [ 10.5001, 10.5001, 10.5001, 10.5001, 10.5001] +24-11-19 20:39:56 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:56 | D | sum error = [ 719.6868, 752.1765, 785.7053, 820.2435, 855.7762] +24-11-19 20:39:56 | D | best error = [ 10.5001, 10.5001, 10.5001, 10.5001, 10.5001] +24-11-19 20:39:56 | D | + error = [10.5001] +24-11-19 20:39:56 | D | - Calibrating model.layers.28.mlp.down_proj.weight +24-11-19 20:39:56 | D | + w: sint8 +24-11-19 20:39:56 | D | + x: None +24-11-19 20:39:56 | D | + y: None +24-11-19 20:39:56 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:56 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:39:56 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:39:57 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:39:57 | D | - range ratio = [ 1.0000] +24-11-19 20:39:57 | D | sum error = [ 5.0247] +24-11-19 20:39:57 | D | best error = [ 5.0247] +24-11-19 20:39:58 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:58 | D | sum error = [ 4.9761, 4.9390, 4.9120, 4.8926, 4.8765] +24-11-19 20:39:58 | D | best error = [ 4.7569, 4.6339, 4.5635, 4.5109, 4.4692] +24-11-19 20:39:58 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:58 | D | sum error = [ 4.8936, 4.9179, 4.9501, 5.0176, 5.1061] +24-11-19 20:39:58 | D | best error = [ 4.4397, 4.4179, 4.4025, 4.3911, 4.3820] +24-11-19 20:39:58 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:58 | D | sum error = [ 5.2137, 5.3504, 5.5051, 5.7101, 5.9409] +24-11-19 20:39:58 | D | best error = [ 4.3777, 4.3737, 4.3711, 4.3699, 4.3690] +24-11-19 20:39:58 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:58 | D | sum error = [ 6.2028, 6.5101, 6.8546, 7.2270, 7.6536] +24-11-19 20:39:58 | D | best error = [ 4.3685, 4.3681, 4.3679, 4.3679, 4.3678] +24-11-19 20:39:58 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:58 | D | sum error = [ 8.1227, 8.6213, 9.1865, 9.7937, 10.4478] +24-11-19 20:39:58 | D | best error = [ 4.3678, 4.3678, 4.3677, 4.3677, 4.3677] +24-11-19 20:39:58 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:58 | D | sum error = [ 11.1621, 11.9210, 12.7449, 13.6054, 14.5564] +24-11-19 20:39:58 | D | best error = [ 4.3677, 4.3677, 4.3677, 4.3677, 4.3677] +24-11-19 20:39:58 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:58 | D | sum error = [ 15.5530, 16.6298, 17.7757, 18.9856, 20.2780] +24-11-19 20:39:58 | D | best error = [ 4.3677, 4.3677, 4.3677, 4.3677, 4.3677] +24-11-19 20:39:58 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:58 | D | sum error = [ 21.6445, 23.0988, 24.6538, 26.2967, 28.0238] +24-11-19 20:39:58 | D | best error = [ 4.3677, 4.3677, 4.3677, 4.3677, 4.3677] +24-11-19 20:39:58 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:58 | D | sum error = [ 29.8562, 31.7905, 33.8471, 36.0099, 38.3158] +24-11-19 20:39:58 | D | best error = [ 4.3677, 4.3677, 4.3677, 4.3677, 4.3677] +24-11-19 20:39:58 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:58 | D | sum error = [ 40.7193, 43.2758, 45.9592, 48.7788, 51.7564] +24-11-19 20:39:58 | D | best error = [ 4.3677, 4.3677, 4.3677, 4.3677, 4.3677] +24-11-19 20:39:58 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:58 | D | sum error = [ 54.8681, 58.1622, 61.6158, 65.2422, 69.0458] +24-11-19 20:39:58 | D | best error = [ 4.3677, 4.3677, 4.3677, 4.3677, 4.3677] +24-11-19 20:39:58 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:58 | D | sum error = [ 73.0374, 77.2279, 81.6091, 86.2062, 91.0163] +24-11-19 20:39:58 | D | best error = [ 4.3677, 4.3677, 4.3677, 4.3677, 4.3677] +24-11-19 20:39:58 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:58 | D | sum error = [ 96.0428, 101.3021, 106.7995, 112.5257, 118.5145] +24-11-19 20:39:58 | D | best error = [ 4.3677, 4.3677, 4.3677, 4.3677, 4.3677] +24-11-19 20:39:58 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:58 | D | sum error = [ 124.7559, 131.2664, 138.0454, 145.1109, 152.4404] +24-11-19 20:39:58 | D | best error = [ 4.3677, 4.3677, 4.3677, 4.3677, 4.3677] +24-11-19 20:39:58 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:58 | D | sum error = [ 160.0729, 168.0038, 176.2403, 184.7870, 193.6528] +24-11-19 20:39:58 | D | best error = [ 4.3677, 4.3677, 4.3677, 4.3677, 4.3677] +24-11-19 20:39:58 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:58 | D | sum error = [ 202.8363, 212.3485, 222.1915, 232.3704, 242.8939] +24-11-19 20:39:58 | D | best error = [ 4.3677, 4.3677, 4.3677, 4.3677, 4.3677] +24-11-19 20:39:58 | D | + error = [4.3677] +24-11-19 20:39:58 | D | - Quantizing model.layers.28.self_attn.q_proj.weight +24-11-19 20:39:59 | D | - Quantizing model.layers.28.self_attn.k_proj.weight +24-11-19 20:40:00 | D | - Quantizing model.layers.28.self_attn.v_proj.weight +24-11-19 20:40:01 | D | - Quantizing model.layers.28.self_attn.o_proj.weight +24-11-19 20:40:02 | D | - Quantizing model.layers.28.mlp.up_proj.weight +24-11-19 20:40:03 | D | - Quantizing model.layers.28.mlp.gate_proj.weight +24-11-19 20:40:04 | D | - Quantizing model.layers.28.mlp.down_proj.weight +24-11-19 20:40:13 | D | - Quantizing layer model.layers.29 +24-11-19 20:40:13 | D | - Calibrating model.layers.29.self_attn.q_proj.weight +24-11-19 20:40:13 | D | + w: sint8 +24-11-19 20:40:13 | D | + x: None +24-11-19 20:40:13 | D | + y: None +24-11-19 20:40:13 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:40:13 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:40:13 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:40:13 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:14 | D | - range ratio = [ 1.0000] +24-11-19 20:40:14 | D | sum error = [ 18.6514] +24-11-19 20:40:14 | D | best error = [ 18.6514] +24-11-19 20:40:28 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:28 | D | sum error = [ 18.7327, 18.7196, 18.6419, 18.7916, 19.3029] +24-11-19 20:40:28 | D | best error = [ 18.6514, 18.6514, 18.6419, 18.6419, 18.6419] +24-11-19 20:40:28 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:28 | D | sum error = [ 19.8032, 21.2494, 21.0879, 22.7903, 23.9461] +24-11-19 20:40:28 | D | best error = [ 18.6419, 18.6419, 18.6419, 18.6419, 18.6419] +24-11-19 20:40:28 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:28 | D | sum error = [ 25.4638, 26.4612, 28.4766, 30.4578, 33.2852] +24-11-19 20:40:28 | D | best error = [ 18.6419, 18.6419, 18.6419, 18.6419, 18.6419] +24-11-19 20:40:28 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:28 | D | sum error = [ 35.6932, 38.5056, 41.9272, 44.8823, 48.4642] +24-11-19 20:40:28 | D | best error = [ 18.6419, 18.6419, 18.6419, 18.6419, 18.6419] +24-11-19 20:40:28 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:28 | D | sum error = [ 52.4767, 57.1727, 62.2696, 67.0680, 72.4865] +24-11-19 20:40:28 | D | best error = [ 18.6419, 18.6419, 18.6419, 18.6419, 18.6419] +24-11-19 20:40:28 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:28 | D | sum error = [ 78.2093, 84.3514, 91.9223, 99.3484, 107.2308] +24-11-19 20:40:28 | D | best error = [ 18.6419, 18.6419, 18.6419, 18.6419, 18.6419] +24-11-19 20:40:28 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:28 | D | sum error = [ 115.6818, 125.2377, 135.2585, 146.1244, 156.8055] +24-11-19 20:40:28 | D | best error = [ 18.6419, 18.6419, 18.6419, 18.6419, 18.6419] +24-11-19 20:40:28 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:28 | D | sum error = [ 169.4109, 182.5594, 196.5091, 212.1676, 228.8539] +24-11-19 20:40:28 | D | best error = [ 18.6419, 18.6419, 18.6419, 18.6419, 18.6419] +24-11-19 20:40:28 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:28 | D | sum error = [ 246.9036, 265.7560, 285.0231, 307.5846, 331.0338] +24-11-19 20:40:28 | D | best error = [ 18.6419, 18.6419, 18.6419, 18.6419, 18.6419] +24-11-19 20:40:28 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:28 | D | sum error = [ 357.0056, 383.7344, 412.7096, 443.7898, 476.5052] +24-11-19 20:40:28 | D | best error = [ 18.6419, 18.6419, 18.6419, 18.6419, 18.6419] +24-11-19 20:40:28 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:28 | D | sum error = [ 511.8151, 548.6608, 588.9264, 631.5053, 677.4081] +24-11-19 20:40:28 | D | best error = [ 18.6419, 18.6419, 18.6419, 18.6419, 18.6419] +24-11-19 20:40:28 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:28 | D | sum error = [ 726.9510, 779.1219, 835.9733, 896.9150, 962.2559] +24-11-19 20:40:28 | D | best error = [ 18.6419, 18.6419, 18.6419, 18.6419, 18.6419] +24-11-19 20:40:28 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:28 | D | sum error = [ 1032.6509, 1108.3891, 1190.2359, 1279.3662, 1375.0331] +24-11-19 20:40:28 | D | best error = [ 18.6419, 18.6419, 18.6419, 18.6419, 18.6419] +24-11-19 20:40:28 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:28 | D | sum error = [ 1479.3438, 1592.7020, 1714.6889, 1848.9863, 1994.0171] +24-11-19 20:40:28 | D | best error = [ 18.6419, 18.6419, 18.6419, 18.6419, 18.6419] +24-11-19 20:40:28 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:28 | D | sum error = [ 2152.1842, 2321.1273, 2506.4692, 2707.5145, 2924.4316] +24-11-19 20:40:28 | D | best error = [ 18.6419, 18.6419, 18.6419, 18.6419, 18.6419] +24-11-19 20:40:28 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:28 | D | sum error = [ 3156.2975, 3406.6222, 3675.7783, 3961.8088, 4266.1784] +24-11-19 20:40:28 | D | best error = [ 18.6419, 18.6419, 18.6419, 18.6419, 18.6419] +24-11-19 20:40:28 | D | + error = [18.6419] +24-11-19 20:40:28 | D | - Calibrating model.layers.29.self_attn.k_proj.weight +24-11-19 20:40:28 | D | + w: sint8 +24-11-19 20:40:28 | D | + x: None +24-11-19 20:40:28 | D | + y: None +24-11-19 20:40:28 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:40:28 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:40:28 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:40:28 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:40:29 | D | - range ratio = [ 1.0000] +24-11-19 20:40:29 | D | sum error = [ 21.7100] +24-11-19 20:40:29 | D | best error = [ 21.7100] +24-11-19 20:40:42 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:42 | D | sum error = [ 23.6832, 21.5139, 21.6148, 22.6391, 21.9710] +24-11-19 20:40:42 | D | best error = [ 21.7100, 21.5139, 21.5139, 21.5139, 21.5139] +24-11-19 20:40:42 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:42 | D | sum error = [ 22.2727, 23.8615, 25.6713, 25.7200, 26.7697] +24-11-19 20:40:42 | D | best error = [ 21.5139, 21.5139, 21.5139, 21.5139, 21.5139] +24-11-19 20:40:42 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:42 | D | sum error = [ 28.0210, 30.8054, 31.8217, 36.3536, 37.9358] +24-11-19 20:40:42 | D | best error = [ 21.5139, 21.5139, 21.5139, 21.5139, 21.5139] +24-11-19 20:40:42 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:42 | D | sum error = [ 39.9785, 45.0367, 48.9814, 52.2274, 60.0039] +24-11-19 20:40:42 | D | best error = [ 21.5139, 21.5139, 21.5139, 21.5139, 21.5139] +24-11-19 20:40:42 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:42 | D | sum error = [ 62.6644, 68.4411, 72.2631, 77.3486, 83.0873] +24-11-19 20:40:42 | D | best error = [ 21.5139, 21.5139, 21.5139, 21.5139, 21.5139] +24-11-19 20:40:42 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:42 | D | sum error = [ 89.6442, 98.6000, 103.4858, 112.1083, 119.2609] +24-11-19 20:40:42 | D | best error = [ 21.5139, 21.5139, 21.5139, 21.5139, 21.5139] +24-11-19 20:40:42 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:42 | D | sum error = [ 127.9911, 139.6411, 149.8711, 161.1276, 174.5097] +24-11-19 20:40:42 | D | best error = [ 21.5139, 21.5139, 21.5139, 21.5139, 21.5139] +24-11-19 20:40:42 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:42 | D | sum error = [ 186.4758, 200.9325, 217.2929, 232.9223, 250.6776] +24-11-19 20:40:42 | D | best error = [ 21.5139, 21.5139, 21.5139, 21.5139, 21.5139] +24-11-19 20:40:42 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:42 | D | sum error = [ 268.3978, 287.6326, 304.7426, 326.8732, 348.4372] +24-11-19 20:40:42 | D | best error = [ 21.5139, 21.5139, 21.5139, 21.5139, 21.5139] +24-11-19 20:40:42 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:42 | D | sum error = [ 371.6944, 396.8885, 423.3588, 450.8197, 480.9291] +24-11-19 20:40:42 | D | best error = [ 21.5139, 21.5139, 21.5139, 21.5139, 21.5139] +24-11-19 20:40:42 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:42 | D | sum error = [ 515.0846, 550.2158, 586.8998, 627.5633, 669.4471] +24-11-19 20:40:42 | D | best error = [ 21.5139, 21.5139, 21.5139, 21.5139, 21.5139] +24-11-19 20:40:42 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:42 | D | sum error = [ 715.3068, 765.1958, 817.9107, 875.0196, 937.9946] +24-11-19 20:40:42 | D | best error = [ 21.5139, 21.5139, 21.5139, 21.5139, 21.5139] +24-11-19 20:40:42 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:42 | D | sum error = [ 1005.6155, 1077.8076, 1155.0003, 1238.6670, 1329.0229] +24-11-19 20:40:42 | D | best error = [ 21.5139, 21.5139, 21.5139, 21.5139, 21.5139] +24-11-19 20:40:42 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:42 | D | sum error = [ 1424.2177, 1527.1937, 1643.6148, 1765.7639, 1901.4579] +24-11-19 20:40:42 | D | best error = [ 21.5139, 21.5139, 21.5139, 21.5139, 21.5139] +24-11-19 20:40:42 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:42 | D | sum error = [ 2046.8532, 2205.4402, 2380.2796, 2572.2493, 2777.9078] +24-11-19 20:40:42 | D | best error = [ 21.5139, 21.5139, 21.5139, 21.5139, 21.5139] +24-11-19 20:40:42 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:42 | D | sum error = [ 3001.5145, 3247.5745, 3507.2665, 3797.8348, 4095.9817] +24-11-19 20:40:42 | D | best error = [ 21.5139, 21.5139, 21.5139, 21.5139, 21.5139] +24-11-19 20:40:42 | D | + error = [21.5139] +24-11-19 20:40:42 | D | - Calibrating model.layers.29.self_attn.v_proj.weight +24-11-19 20:40:42 | D | + w: sint8 +24-11-19 20:40:42 | D | + x: None +24-11-19 20:40:42 | D | + y: None +24-11-19 20:40:42 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:42 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:40:42 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:40:43 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:43 | D | - range ratio = [ 1.0000] +24-11-19 20:40:43 | D | sum error = [ 8.9299] +24-11-19 20:40:43 | D | best error = [ 8.9299] +24-11-19 20:40:43 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:43 | D | sum error = [ 8.8425, 8.8173, 8.8612, 8.9814, 9.1411] +24-11-19 20:40:43 | D | best error = [ 8.2218, 7.9539, 7.8107, 7.7366, 7.6946] +24-11-19 20:40:43 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:43 | D | sum error = [ 9.3800, 9.6650, 10.0276, 10.5652, 11.0968] +24-11-19 20:40:43 | D | best error = [ 7.6743, 7.6646, 7.6621, 7.6606, 7.6604] +24-11-19 20:40:43 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:43 | D | sum error = [ 11.7374, 12.4420, 13.2534, 14.1653, 15.1476] +24-11-19 20:40:43 | D | best error = [ 7.6604, 7.6604, 7.6604, 7.6604, 7.6604] +24-11-19 20:40:43 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:43 | D | sum error = [ 16.2388, 17.4154, 18.6273, 19.9433, 21.3438] +24-11-19 20:40:43 | D | best error = [ 7.6604, 7.6604, 7.6604, 7.6604, 7.6604] +24-11-19 20:40:43 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:43 | D | sum error = [ 22.8224, 24.4786, 26.1952, 27.9887, 29.8985] +24-11-19 20:40:43 | D | best error = [ 7.6604, 7.6604, 7.6604, 7.6604, 7.6604] +24-11-19 20:40:43 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:43 | D | sum error = [ 31.9563, 34.1238, 36.3697, 38.8128, 41.4055] +24-11-19 20:40:43 | D | best error = [ 7.6604, 7.6604, 7.6604, 7.6604, 7.6604] +24-11-19 20:40:43 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:43 | D | sum error = [ 44.0448, 46.8781, 49.8572, 52.9805, 56.3173] +24-11-19 20:40:43 | D | best error = [ 7.6604, 7.6604, 7.6604, 7.6604, 7.6604] +24-11-19 20:40:43 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:43 | D | sum error = [ 59.7737, 63.4687, 67.2620, 71.2833, 75.4942] +24-11-19 20:40:43 | D | best error = [ 7.6604, 7.6604, 7.6604, 7.6604, 7.6604] +24-11-19 20:40:43 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:43 | D | sum error = [ 79.9249, 84.5196, 89.3963, 94.5099, 99.7966] +24-11-19 20:40:43 | D | best error = [ 7.6604, 7.6604, 7.6604, 7.6604, 7.6604] +24-11-19 20:40:43 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:43 | D | sum error = [ 105.3359, 111.1016, 117.1609, 123.4596, 130.0232] +24-11-19 20:40:43 | D | best error = [ 7.6604, 7.6604, 7.6604, 7.6604, 7.6604] +24-11-19 20:40:43 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:43 | D | sum error = [ 136.8519, 143.9924, 151.4013, 159.1095, 167.1375] +24-11-19 20:40:43 | D | best error = [ 7.6604, 7.6604, 7.6604, 7.6604, 7.6604] +24-11-19 20:40:43 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:43 | D | sum error = [ 175.4695, 184.1447, 193.1258, 202.3849, 211.9914] +24-11-19 20:40:43 | D | best error = [ 7.6604, 7.6604, 7.6604, 7.6604, 7.6604] +24-11-19 20:40:43 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:43 | D | sum error = [ 221.9935, 232.3168, 243.0247, 254.1141, 265.5893] +24-11-19 20:40:43 | D | best error = [ 7.6604, 7.6604, 7.6604, 7.6604, 7.6604] +24-11-19 20:40:43 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:43 | D | sum error = [ 277.4575, 289.6892, 302.3275, 315.3774, 328.8159] +24-11-19 20:40:43 | D | best error = [ 7.6604, 7.6604, 7.6604, 7.6604, 7.6604] +24-11-19 20:40:43 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:43 | D | sum error = [ 342.6765, 356.9379, 371.6929, 386.8495, 402.4433] +24-11-19 20:40:43 | D | best error = [ 7.6604, 7.6604, 7.6604, 7.6604, 7.6604] +24-11-19 20:40:43 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:43 | D | sum error = [ 418.4817, 434.9786, 451.9334, 469.3349, 487.2001] +24-11-19 20:40:43 | D | best error = [ 7.6604, 7.6604, 7.6604, 7.6604, 7.6604] +24-11-19 20:40:43 | D | + error = [7.6604] +24-11-19 20:40:43 | D | - Calibrating model.layers.29.self_attn.o_proj.weight +24-11-19 20:40:43 | D | + w: sint8 +24-11-19 20:40:43 | D | + x: None +24-11-19 20:40:43 | D | + y: None +24-11-19 20:40:43 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:43 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:40:43 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:40:43 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:43 | D | - range ratio = [ 1.0000] +24-11-19 20:40:43 | D | sum error = [ 2.0423] +24-11-19 20:40:43 | D | best error = [ 2.0423] +24-11-19 20:40:44 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:44 | D | sum error = [ 2.0305, 2.0285, 2.0448, 2.0708, 2.1251] +24-11-19 20:40:44 | D | best error = [ 1.9218, 1.8661, 1.8334, 1.8138, 1.8034] +24-11-19 20:40:44 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:44 | D | sum error = [ 2.1946, 2.2772, 2.3880, 2.5031, 2.6593] +24-11-19 20:40:44 | D | best error = [ 1.7960, 1.7915, 1.7889, 1.7866, 1.7853] +24-11-19 20:40:44 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:44 | D | sum error = [ 2.8231, 2.9978, 3.2020, 3.4219, 3.6673] +24-11-19 20:40:44 | D | best error = [ 1.7843, 1.7836, 1.7833, 1.7829, 1.7827] +24-11-19 20:40:44 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:44 | D | sum error = [ 3.9408, 4.2192, 4.5200, 4.8424, 5.1798] +24-11-19 20:40:44 | D | best error = [ 1.7826, 1.7826, 1.7826, 1.7826, 1.7825] +24-11-19 20:40:44 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:44 | D | sum error = [ 5.5556, 5.9385, 6.3601, 6.7878, 7.2523] +24-11-19 20:40:44 | D | best error = [ 1.7825, 1.7825, 1.7824, 1.7824, 1.7824] +24-11-19 20:40:44 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:44 | D | sum error = [ 7.7446, 8.2565, 8.8158, 9.3739, 9.9847] +24-11-19 20:40:44 | D | best error = [ 1.7824, 1.7824, 1.7824, 1.7824, 1.7824] +24-11-19 20:40:44 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:44 | D | sum error = [ 10.6183, 11.2993, 12.0023, 12.7470, 13.5374] +24-11-19 20:40:44 | D | best error = [ 1.7824, 1.7824, 1.7824, 1.7824, 1.7824] +24-11-19 20:40:44 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:44 | D | sum error = [ 14.3677, 15.2407, 16.1551, 17.1273, 18.1367] +24-11-19 20:40:44 | D | best error = [ 1.7824, 1.7824, 1.7824, 1.7824, 1.7824] +24-11-19 20:40:44 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:44 | D | sum error = [ 19.2024, 20.3194, 21.4984, 22.7304, 24.0274] +24-11-19 20:40:44 | D | best error = [ 1.7824, 1.7824, 1.7824, 1.7824, 1.7824] +24-11-19 20:40:44 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:44 | D | sum error = [ 25.3904, 26.8124, 28.3010, 29.8687, 31.5105] +24-11-19 20:40:44 | D | best error = [ 1.7824, 1.7824, 1.7824, 1.7824, 1.7824] +24-11-19 20:40:44 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:44 | D | sum error = [ 33.2326, 35.0330, 36.9135, 38.8945, 40.9502] +24-11-19 20:40:44 | D | best error = [ 1.7824, 1.7824, 1.7824, 1.7824, 1.7824] +24-11-19 20:40:44 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:44 | D | sum error = [ 43.1042, 45.3515, 47.6996, 50.1576, 52.7208] +24-11-19 20:40:44 | D | best error = [ 1.7824, 1.7824, 1.7824, 1.7824, 1.7824] +24-11-19 20:40:44 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:44 | D | sum error = [ 55.3836, 58.1613, 61.0547, 64.0653, 67.1998] +24-11-19 20:40:44 | D | best error = [ 1.7824, 1.7824, 1.7824, 1.7824, 1.7824] +24-11-19 20:40:44 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:44 | D | sum error = [ 70.4620, 73.8621, 77.3909, 81.0659, 84.8714] +24-11-19 20:40:44 | D | best error = [ 1.7824, 1.7824, 1.7824, 1.7824, 1.7824] +24-11-19 20:40:44 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:44 | D | sum error = [ 88.8259, 92.9206, 97.1646, 101.5555, 106.1058] +24-11-19 20:40:44 | D | best error = [ 1.7824, 1.7824, 1.7824, 1.7824, 1.7824] +24-11-19 20:40:44 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:44 | D | sum error = [ 110.8103, 115.6758, 120.7003, 125.8819, 131.2286] +24-11-19 20:40:44 | D | best error = [ 1.7824, 1.7824, 1.7824, 1.7824, 1.7824] +24-11-19 20:40:44 | D | + error = [1.7824] +24-11-19 20:40:44 | D | - Calibrating model.layers.29.mlp.up_proj.weight +24-11-19 20:40:44 | D | + w: sint8 +24-11-19 20:40:44 | D | + x: None +24-11-19 20:40:44 | D | + y: None +24-11-19 20:40:44 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:44 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:40:44 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:40:44 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:44 | D | - range ratio = [ 1.0000] +24-11-19 20:40:44 | D | sum error = [ 12.0014] +24-11-19 20:40:44 | D | best error = [ 12.0014] +24-11-19 20:40:45 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:45 | D | sum error = [ 11.9180, 11.8740, 11.9713, 12.0803, 12.3129] +24-11-19 20:40:45 | D | best error = [ 10.9816, 10.6101, 10.4214, 10.3157, 10.2544] +24-11-19 20:40:45 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:45 | D | sum error = [ 12.6097, 13.0406, 13.5656, 14.2106, 14.9810] +24-11-19 20:40:45 | D | best error = [ 10.2257, 10.2117, 10.2058, 10.2042, 10.2035] +24-11-19 20:40:45 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:45 | D | sum error = [ 15.8365, 16.8000, 17.9158, 19.1456, 20.4466] +24-11-19 20:40:45 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 20:40:45 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:45 | D | sum error = [ 21.8674, 23.4372, 25.1408, 26.9110, 28.8531] +24-11-19 20:40:45 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 20:40:45 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:45 | D | sum error = [ 30.9382, 33.1494, 35.4664, 37.9384, 40.5994] +24-11-19 20:40:45 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 20:40:45 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:45 | D | sum error = [ 43.4074, 46.3444, 49.5867, 52.8545, 56.4133] +24-11-19 20:40:45 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 20:40:45 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:45 | D | sum error = [ 60.1637, 64.1053, 68.3474, 72.7430, 77.4484] +24-11-19 20:40:45 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 20:40:45 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:45 | D | sum error = [ 82.3635, 87.5972, 93.0832, 98.8569, 104.9263] +24-11-19 20:40:45 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 20:40:45 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:45 | D | sum error = [ 111.3535, 118.0718, 125.1964, 132.6835, 140.5810] +24-11-19 20:40:45 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 20:40:45 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:45 | D | sum error = [ 148.8447, 157.6362, 166.7908, 176.4210, 186.4641] +24-11-19 20:40:45 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 20:40:45 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:45 | D | sum error = [ 197.0897, 208.1908, 219.7911, 232.0196, 244.8274] +24-11-19 20:40:45 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 20:40:45 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:45 | D | sum error = [ 258.1971, 272.2238, 286.8476, 302.1768, 318.2399] +24-11-19 20:40:45 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 20:40:45 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:45 | D | sum error = [ 334.8976, 352.3148, 370.5314, 389.5042, 409.2241] +24-11-19 20:40:45 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 20:40:45 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:45 | D | sum error = [ 429.7856, 451.1871, 473.3823, 496.4013, 520.2899] +24-11-19 20:40:45 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 20:40:45 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:45 | D | sum error = [ 545.1449, 570.8270, 597.4256, 624.9681, 653.5031] +24-11-19 20:40:45 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 20:40:45 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:45 | D | sum error = [ 682.9196, 713.2814, 744.6012, 776.9236, 810.2187] +24-11-19 20:40:45 | D | best error = [ 10.2035, 10.2035, 10.2035, 10.2035, 10.2035] +24-11-19 20:40:45 | D | + error = [10.2035] +24-11-19 20:40:45 | D | - Calibrating model.layers.29.mlp.gate_proj.weight +24-11-19 20:40:45 | D | + w: sint8 +24-11-19 20:40:45 | D | + x: None +24-11-19 20:40:45 | D | + y: None +24-11-19 20:40:45 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:45 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:40:45 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:40:46 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:46 | D | - range ratio = [ 1.0000] +24-11-19 20:40:46 | D | sum error = [ 12.5805] +24-11-19 20:40:46 | D | best error = [ 12.5805] +24-11-19 20:40:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:46 | D | sum error = [ 12.4591, 12.4590, 12.4853, 12.6734, 12.9048] +24-11-19 20:40:46 | D | best error = [ 11.5088, 11.1216, 10.9162, 10.8051, 10.7432] +24-11-19 20:40:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:46 | D | sum error = [ 13.2264, 13.6932, 14.2552, 14.8513, 15.7032] +24-11-19 20:40:46 | D | best error = [ 10.7128, 10.6979, 10.6928, 10.6911, 10.6908] +24-11-19 20:40:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:46 | D | sum error = [ 16.6672, 17.6764, 18.8303, 20.0792, 21.5188] +24-11-19 20:40:46 | D | best error = [ 10.6907, 10.6907, 10.6907, 10.6907, 10.6907] +24-11-19 20:40:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:46 | D | sum error = [ 23.0476, 24.6958, 26.5315, 28.3987, 30.4926] +24-11-19 20:40:46 | D | best error = [ 10.6907, 10.6907, 10.6907, 10.6907, 10.6907] +24-11-19 20:40:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:46 | D | sum error = [ 32.6787, 35.0848, 37.5537, 40.2973, 43.0554] +24-11-19 20:40:46 | D | best error = [ 10.6907, 10.6907, 10.6907, 10.6907, 10.6907] +24-11-19 20:40:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:46 | D | sum error = [ 46.1185, 49.3481, 52.7247, 56.3487, 60.1037] +24-11-19 20:40:46 | D | best error = [ 10.6907, 10.6907, 10.6907, 10.6907, 10.6907] +24-11-19 20:40:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:46 | D | sum error = [ 64.1690, 68.4320, 72.9630, 77.6764, 82.7229] +24-11-19 20:40:46 | D | best error = [ 10.6907, 10.6907, 10.6907, 10.6907, 10.6907] +24-11-19 20:40:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:46 | D | sum error = [ 88.0706, 93.6787, 99.6443, 105.8944, 112.5241] +24-11-19 20:40:46 | D | best error = [ 10.6907, 10.6907, 10.6907, 10.6907, 10.6907] +24-11-19 20:40:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:46 | D | sum error = [ 119.5122, 126.8591, 134.6111, 142.7921, 151.3728] +24-11-19 20:40:46 | D | best error = [ 10.6907, 10.6907, 10.6907, 10.6907, 10.6907] +24-11-19 20:40:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:46 | D | sum error = [ 160.4417, 169.9612, 180.0178, 190.5210, 201.6644] +24-11-19 20:40:46 | D | best error = [ 10.6907, 10.6907, 10.6907, 10.6907, 10.6907] +24-11-19 20:40:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:46 | D | sum error = [ 213.3225, 225.5490, 238.4413, 251.9407, 266.1247] +24-11-19 20:40:46 | D | best error = [ 10.6907, 10.6907, 10.6907, 10.6907, 10.6907] +24-11-19 20:40:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:46 | D | sum error = [ 280.9431, 296.4271, 312.6826, 329.7244, 347.4887] +24-11-19 20:40:46 | D | best error = [ 10.6907, 10.6907, 10.6907, 10.6907, 10.6907] +24-11-19 20:40:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:46 | D | sum error = [ 366.0902, 385.5110, 405.7758, 426.9448, 449.0061] +24-11-19 20:40:46 | D | best error = [ 10.6907, 10.6907, 10.6907, 10.6907, 10.6907] +24-11-19 20:40:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:46 | D | sum error = [ 472.0189, 495.9464, 520.8386, 546.7566, 573.6171] +24-11-19 20:40:46 | D | best error = [ 10.6907, 10.6907, 10.6907, 10.6907, 10.6907] +24-11-19 20:40:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:46 | D | sum error = [ 601.4992, 630.4344, 660.3618, 691.3550, 723.4356] +24-11-19 20:40:46 | D | best error = [ 10.6907, 10.6907, 10.6907, 10.6907, 10.6907] +24-11-19 20:40:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:46 | D | sum error = [ 756.5189, 790.7587, 826.0346, 862.3885, 899.7814] +24-11-19 20:40:46 | D | best error = [ 10.6907, 10.6907, 10.6907, 10.6907, 10.6907] +24-11-19 20:40:46 | D | + error = [10.6907] +24-11-19 20:40:47 | D | - Calibrating model.layers.29.mlp.down_proj.weight +24-11-19 20:40:47 | D | + w: sint8 +24-11-19 20:40:47 | D | + x: None +24-11-19 20:40:47 | D | + y: None +24-11-19 20:40:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:47 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:40:47 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:40:47 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:47 | D | - range ratio = [ 1.0000] +24-11-19 20:40:47 | D | sum error = [ 5.7944] +24-11-19 20:40:47 | D | best error = [ 5.7944] +24-11-19 20:40:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:48 | D | sum error = [ 5.8186, 6.0098, 6.3352, 6.8270, 7.4215] +24-11-19 20:40:48 | D | best error = [ 5.4537, 5.3266, 5.2435, 5.1869, 5.1413] +24-11-19 20:40:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:48 | D | sum error = [ 8.1025, 8.8830, 9.7038, 10.5914, 11.5100] +24-11-19 20:40:48 | D | best error = [ 5.1060, 5.0821, 5.0643, 5.0494, 5.0380] +24-11-19 20:40:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:48 | D | sum error = [ 12.4870, 13.4807, 14.5147, 15.5758, 16.6731] +24-11-19 20:40:48 | D | best error = [ 5.0306, 5.0251, 5.0219, 5.0198, 5.0184] +24-11-19 20:40:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:48 | D | sum error = [ 17.7961, 18.9370, 20.1158, 21.3304, 22.5593] +24-11-19 20:40:48 | D | best error = [ 5.0174, 5.0171, 5.0168, 5.0165, 5.0164] +24-11-19 20:40:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:48 | D | sum error = [ 23.8136, 25.1167, 26.4374, 27.7983, 29.1954] +24-11-19 20:40:48 | D | best error = [ 5.0164, 5.0163, 5.0163, 5.0163, 5.0163] +24-11-19 20:40:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:48 | D | sum error = [ 30.6203, 32.0941, 33.6025, 35.1562, 36.7568] +24-11-19 20:40:48 | D | best error = [ 5.0163, 5.0163, 5.0163, 5.0163, 5.0163] +24-11-19 20:40:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:48 | D | sum error = [ 38.3979, 40.0843, 41.8262, 43.6315, 45.4776] +24-11-19 20:40:48 | D | best error = [ 5.0163, 5.0163, 5.0163, 5.0163, 5.0163] +24-11-19 20:40:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:48 | D | sum error = [ 47.3936, 49.3822, 51.4436, 53.5724, 55.7821] +24-11-19 20:40:48 | D | best error = [ 5.0163, 5.0163, 5.0163, 5.0163, 5.0163] +24-11-19 20:40:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:48 | D | sum error = [ 58.0727, 60.4608, 62.9459, 65.5235, 68.2137] +24-11-19 20:40:48 | D | best error = [ 5.0163, 5.0163, 5.0163, 5.0163, 5.0163] +24-11-19 20:40:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:48 | D | sum error = [ 71.0065, 73.9269, 76.9702, 80.1446, 83.4549] +24-11-19 20:40:48 | D | best error = [ 5.0163, 5.0163, 5.0163, 5.0163, 5.0163] +24-11-19 20:40:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:48 | D | sum error = [ 86.9191, 90.5409, 94.3168, 98.2621, 102.3880] +24-11-19 20:40:48 | D | best error = [ 5.0163, 5.0163, 5.0163, 5.0163, 5.0163] +24-11-19 20:40:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:48 | D | sum error = [ 106.7088, 111.2297, 115.9479, 120.8874, 126.0536] +24-11-19 20:40:48 | D | best error = [ 5.0163, 5.0163, 5.0163, 5.0163, 5.0163] +24-11-19 20:40:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:48 | D | sum error = [ 131.4607, 137.1145, 143.0263, 149.2040, 155.6629] +24-11-19 20:40:48 | D | best error = [ 5.0163, 5.0163, 5.0163, 5.0163, 5.0163] +24-11-19 20:40:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:48 | D | sum error = [ 162.4052, 169.4515, 176.7809, 184.4575, 192.4300] +24-11-19 20:40:48 | D | best error = [ 5.0163, 5.0163, 5.0163, 5.0163, 5.0163] +24-11-19 20:40:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:48 | D | sum error = [ 200.7348, 209.3853, 218.3895, 227.7719, 237.5281] +24-11-19 20:40:48 | D | best error = [ 5.0163, 5.0163, 5.0163, 5.0163, 5.0163] +24-11-19 20:40:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:48 | D | sum error = [ 247.6587, 258.1858, 269.1221, 280.4541, 292.2006] +24-11-19 20:40:48 | D | best error = [ 5.0163, 5.0163, 5.0163, 5.0163, 5.0163] +24-11-19 20:40:48 | D | + error = [5.0163] +24-11-19 20:40:48 | D | - Quantizing model.layers.29.self_attn.q_proj.weight +24-11-19 20:40:49 | D | - Quantizing model.layers.29.self_attn.k_proj.weight +24-11-19 20:40:50 | D | - Quantizing model.layers.29.self_attn.v_proj.weight +24-11-19 20:40:51 | D | - Quantizing model.layers.29.self_attn.o_proj.weight +24-11-19 20:40:52 | D | - Quantizing model.layers.29.mlp.up_proj.weight +24-11-19 20:40:53 | D | - Quantizing model.layers.29.mlp.gate_proj.weight +24-11-19 20:40:54 | D | - Quantizing model.layers.29.mlp.down_proj.weight +24-11-19 20:41:03 | D | - Quantizing layer model.layers.30 +24-11-19 20:41:03 | D | - Calibrating model.layers.30.self_attn.q_proj.weight +24-11-19 20:41:03 | D | + w: sint8 +24-11-19 20:41:03 | D | + x: None +24-11-19 20:41:03 | D | + y: None +24-11-19 20:41:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:41:03 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:41:03 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:41:03 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:41:03 | D | - range ratio = [ 1.0000] +24-11-19 20:41:03 | D | sum error = [ 18.2796] +24-11-19 20:41:03 | D | best error = [ 18.2796] +24-11-19 20:41:16 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:16 | D | sum error = [ 18.7410, 18.5153, 18.7168, 19.8199, 19.4012] +24-11-19 20:41:16 | D | best error = [ 18.2796, 18.2796, 18.2796, 18.2796, 18.2796] +24-11-19 20:41:16 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:16 | D | sum error = [ 19.8934, 20.5274, 22.2398, 22.4545, 23.9540] +24-11-19 20:41:16 | D | best error = [ 18.2796, 18.2796, 18.2796, 18.2796, 18.2796] +24-11-19 20:41:16 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:16 | D | sum error = [ 25.1320, 26.6608, 29.9870, 30.8157, 32.8061] +24-11-19 20:41:16 | D | best error = [ 18.2796, 18.2796, 18.2796, 18.2796, 18.2796] +24-11-19 20:41:16 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:16 | D | sum error = [ 35.3922, 38.8770, 41.0929, 44.0386, 47.4752] +24-11-19 20:41:16 | D | best error = [ 18.2796, 18.2796, 18.2796, 18.2796, 18.2796] +24-11-19 20:41:16 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:16 | D | sum error = [ 51.3311, 55.9415, 60.1019, 64.8250, 70.3370] +24-11-19 20:41:16 | D | best error = [ 18.2796, 18.2796, 18.2796, 18.2796, 18.2796] +24-11-19 20:41:16 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:16 | D | sum error = [ 76.3578, 82.0490, 89.3528, 95.6589, 104.1473] +24-11-19 20:41:16 | D | best error = [ 18.2796, 18.2796, 18.2796, 18.2796, 18.2796] +24-11-19 20:41:16 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:16 | D | sum error = [ 112.3337, 121.8263, 131.4522, 142.7184, 154.3318] +24-11-19 20:41:16 | D | best error = [ 18.2796, 18.2796, 18.2796, 18.2796, 18.2796] +24-11-19 20:41:16 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:16 | D | sum error = [ 166.1383, 178.5669, 194.1169, 210.8515, 228.3114] +24-11-19 20:41:16 | D | best error = [ 18.2796, 18.2796, 18.2796, 18.2796, 18.2796] +24-11-19 20:41:16 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:16 | D | sum error = [ 245.6944, 266.3045, 288.3633, 311.6711, 336.9367] +24-11-19 20:41:16 | D | best error = [ 18.2796, 18.2796, 18.2796, 18.2796, 18.2796] +24-11-19 20:41:16 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:16 | D | sum error = [ 362.6610, 391.8011, 423.6075, 457.5158, 494.6717] +24-11-19 20:41:16 | D | best error = [ 18.2796, 18.2796, 18.2796, 18.2796, 18.2796] +24-11-19 20:41:16 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:16 | D | sum error = [ 534.7384, 578.8441, 625.2521, 677.0158, 732.0659] +24-11-19 20:41:16 | D | best error = [ 18.2796, 18.2796, 18.2796, 18.2796, 18.2796] +24-11-19 20:41:16 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:16 | D | sum error = [ 791.7194, 857.4897, 928.5319, 1004.9939, 1088.3081] +24-11-19 20:41:16 | D | best error = [ 18.2796, 18.2796, 18.2796, 18.2796, 18.2796] +24-11-19 20:41:16 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:16 | D | sum error = [ 1177.2639, 1274.4339, 1380.4820, 1493.9600, 1619.4147] +24-11-19 20:41:16 | D | best error = [ 18.2796, 18.2796, 18.2796, 18.2796, 18.2796] +24-11-19 20:41:16 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:16 | D | sum error = [ 1756.7271, 1905.2169, 2068.5026, 2248.1879, 2443.7784] +24-11-19 20:41:16 | D | best error = [ 18.2796, 18.2796, 18.2796, 18.2796, 18.2796] +24-11-19 20:41:16 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:16 | D | sum error = [ 2657.5577, 2890.8909, 3146.8831, 3428.2873, 3735.1313] +24-11-19 20:41:16 | D | best error = [ 18.2796, 18.2796, 18.2796, 18.2796, 18.2796] +24-11-19 20:41:16 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:16 | D | sum error = [ 4068.5708, 4434.0706, 4830.3184, 5258.4789, 5719.3902] +24-11-19 20:41:16 | D | best error = [ 18.2796, 18.2796, 18.2796, 18.2796, 18.2796] +24-11-19 20:41:16 | D | + error = [18.2796] +24-11-19 20:41:16 | D | - Calibrating model.layers.30.self_attn.k_proj.weight +24-11-19 20:41:16 | D | + w: sint8 +24-11-19 20:41:16 | D | + x: None +24-11-19 20:41:16 | D | + y: None +24-11-19 20:41:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:41:16 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:41:17 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:41:17 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:41:17 | D | - range ratio = [ 1.0000] +24-11-19 20:41:17 | D | sum error = [ 21.5713] +24-11-19 20:41:17 | D | best error = [ 21.5713] +24-11-19 20:41:30 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:30 | D | sum error = [ 21.7370, 22.4732, 22.7378, 22.2036, 23.7874] +24-11-19 20:41:30 | D | best error = [ 21.5713, 21.5713, 21.5713, 21.5713, 21.5713] +24-11-19 20:41:30 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:30 | D | sum error = [ 23.4601, 25.8509, 24.6390, 26.9577, 30.1491] +24-11-19 20:41:30 | D | best error = [ 21.5713, 21.5713, 21.5713, 21.5713, 21.5713] +24-11-19 20:41:30 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:30 | D | sum error = [ 29.4981, 33.6519, 35.8596, 38.0735, 43.1574] +24-11-19 20:41:30 | D | best error = [ 21.5713, 21.5713, 21.5713, 21.5713, 21.5713] +24-11-19 20:41:30 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:30 | D | sum error = [ 43.3104, 45.7285, 50.3815, 52.8845, 57.8231] +24-11-19 20:41:30 | D | best error = [ 21.5713, 21.5713, 21.5713, 21.5713, 21.5713] +24-11-19 20:41:30 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:30 | D | sum error = [ 59.7663, 67.4500, 71.7871, 76.2849, 80.1549] +24-11-19 20:41:30 | D | best error = [ 21.5713, 21.5713, 21.5713, 21.5713, 21.5713] +24-11-19 20:41:30 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:30 | D | sum error = [ 87.9770, 96.0034, 104.8789, 112.2664, 119.0130] +24-11-19 20:41:30 | D | best error = [ 21.5713, 21.5713, 21.5713, 21.5713, 21.5713] +24-11-19 20:41:30 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:30 | D | sum error = [ 129.6791, 140.2616, 150.6262, 160.5490, 173.1123] +24-11-19 20:41:30 | D | best error = [ 21.5713, 21.5713, 21.5713, 21.5713, 21.5713] +24-11-19 20:41:30 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:30 | D | sum error = [ 186.3642, 201.8242, 214.4207, 232.0164, 248.5550] +24-11-19 20:41:30 | D | best error = [ 21.5713, 21.5713, 21.5713, 21.5713, 21.5713] +24-11-19 20:41:30 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:30 | D | sum error = [ 266.4504, 289.1357, 311.3950, 335.4552, 360.4434] +24-11-19 20:41:30 | D | best error = [ 21.5713, 21.5713, 21.5713, 21.5713, 21.5713] +24-11-19 20:41:30 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:30 | D | sum error = [ 388.0678, 419.3524, 450.1868, 484.8688, 524.9027] +24-11-19 20:41:30 | D | best error = [ 21.5713, 21.5713, 21.5713, 21.5713, 21.5713] +24-11-19 20:41:30 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:30 | D | sum error = [ 564.4870, 607.1741, 654.5735, 709.0445, 763.8514] +24-11-19 20:41:30 | D | best error = [ 21.5713, 21.5713, 21.5713, 21.5713, 21.5713] +24-11-19 20:41:30 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:30 | D | sum error = [ 822.7383, 887.7568, 958.0307, 1032.9774, 1112.5366] +24-11-19 20:41:30 | D | best error = [ 21.5713, 21.5713, 21.5713, 21.5713, 21.5713] +24-11-19 20:41:30 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:30 | D | sum error = [ 1202.7138, 1295.2277, 1395.4819, 1505.0085, 1627.9049] +24-11-19 20:41:30 | D | best error = [ 21.5713, 21.5713, 21.5713, 21.5713, 21.5713] +24-11-19 20:41:30 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:30 | D | sum error = [ 1764.9673, 1908.7798, 2065.9376, 2241.3311, 2430.6991] +24-11-19 20:41:30 | D | best error = [ 21.5713, 21.5713, 21.5713, 21.5713, 21.5713] +24-11-19 20:41:30 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:30 | D | sum error = [ 2636.1168, 2857.1197, 3095.5513, 3359.5803, 3637.0386] +24-11-19 20:41:30 | D | best error = [ 21.5713, 21.5713, 21.5713, 21.5713, 21.5713] +24-11-19 20:41:30 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:30 | D | sum error = [ 3943.6838, 4278.4436, 4648.0022, 5044.6800, 5464.4670] +24-11-19 20:41:30 | D | best error = [ 21.5713, 21.5713, 21.5713, 21.5713, 21.5713] +24-11-19 20:41:30 | D | + error = [21.5713] +24-11-19 20:41:30 | D | - Calibrating model.layers.30.self_attn.v_proj.weight +24-11-19 20:41:30 | D | + w: sint8 +24-11-19 20:41:30 | D | + x: None +24-11-19 20:41:30 | D | + y: None +24-11-19 20:41:30 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:30 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:41:30 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:41:31 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:41:31 | D | - range ratio = [ 1.0000] +24-11-19 20:41:31 | D | sum error = [ 9.5461] +24-11-19 20:41:31 | D | best error = [ 9.5461] +24-11-19 20:41:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:31 | D | sum error = [ 9.4695, 9.4376, 9.4999, 9.5574, 9.7634] +24-11-19 20:41:31 | D | best error = [ 8.7479, 8.4663, 8.3195, 8.2333, 8.1870] +24-11-19 20:41:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:31 | D | sum error = [ 10.0510, 10.3482, 10.7464, 11.2844, 11.8345] +24-11-19 20:41:31 | D | best error = [ 8.1663, 8.1559, 8.1527, 8.1517, 8.1516] +24-11-19 20:41:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:31 | D | sum error = [ 12.5300, 13.2983, 14.1317, 15.1046, 16.1398] +24-11-19 20:41:31 | D | best error = [ 8.1516, 8.1516, 8.1516, 8.1516, 8.1516] +24-11-19 20:41:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:31 | D | sum error = [ 17.2536, 18.4392, 19.7519, 21.1645, 22.6934] +24-11-19 20:41:31 | D | best error = [ 8.1516, 8.1516, 8.1516, 8.1516, 8.1516] +24-11-19 20:41:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:31 | D | sum error = [ 24.2957, 25.9902, 27.7824, 29.7242, 31.8004] +24-11-19 20:41:31 | D | best error = [ 8.1516, 8.1516, 8.1516, 8.1516, 8.1516] +24-11-19 20:41:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:31 | D | sum error = [ 34.0007, 36.2801, 38.7417, 41.2805, 43.9641] +24-11-19 20:41:31 | D | best error = [ 8.1516, 8.1516, 8.1516, 8.1516, 8.1516] +24-11-19 20:41:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:31 | D | sum error = [ 46.8258, 49.9102, 53.1174, 56.4666, 59.9708] +24-11-19 20:41:31 | D | best error = [ 8.1516, 8.1516, 8.1516, 8.1516, 8.1516] +24-11-19 20:41:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:31 | D | sum error = [ 63.7425, 67.6544, 71.7299, 76.0516, 80.5505] +24-11-19 20:41:31 | D | best error = [ 8.1516, 8.1516, 8.1516, 8.1516, 8.1516] +24-11-19 20:41:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:31 | D | sum error = [ 85.2359, 90.1965, 95.3683, 100.7918, 106.4844] +24-11-19 20:41:31 | D | best error = [ 8.1516, 8.1516, 8.1516, 8.1516, 8.1516] +24-11-19 20:41:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:31 | D | sum error = [ 112.4325, 118.5884, 125.0928, 131.8881, 138.9845] +24-11-19 20:41:31 | D | best error = [ 8.1516, 8.1516, 8.1516, 8.1516, 8.1516] +24-11-19 20:41:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:31 | D | sum error = [ 146.3606, 154.0480, 162.0891, 170.4682, 179.1707] +24-11-19 20:41:31 | D | best error = [ 8.1516, 8.1516, 8.1516, 8.1516, 8.1516] +24-11-19 20:41:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:31 | D | sum error = [ 188.2530, 197.6968, 207.5109, 217.6982, 228.2829] +24-11-19 20:41:31 | D | best error = [ 8.1516, 8.1516, 8.1516, 8.1516, 8.1516] +24-11-19 20:41:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:31 | D | sum error = [ 239.2721, 250.7135, 262.5394, 274.7984, 287.4830] +24-11-19 20:41:31 | D | best error = [ 8.1516, 8.1516, 8.1516, 8.1516, 8.1516] +24-11-19 20:41:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:31 | D | sum error = [ 300.6039, 314.1700, 328.2196, 342.7222, 357.7008] +24-11-19 20:41:31 | D | best error = [ 8.1516, 8.1516, 8.1516, 8.1516, 8.1516] +24-11-19 20:41:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:31 | D | sum error = [ 373.1796, 389.0893, 405.4830, 422.3678, 439.7413] +24-11-19 20:41:31 | D | best error = [ 8.1516, 8.1516, 8.1516, 8.1516, 8.1516] +24-11-19 20:41:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:31 | D | sum error = [ 457.6248, 476.0239, 494.9605, 514.4404, 534.4483] +24-11-19 20:41:31 | D | best error = [ 8.1516, 8.1516, 8.1516, 8.1516, 8.1516] +24-11-19 20:41:31 | D | + error = [8.1516] +24-11-19 20:41:31 | D | - Calibrating model.layers.30.self_attn.o_proj.weight +24-11-19 20:41:31 | D | + w: sint8 +24-11-19 20:41:31 | D | + x: None +24-11-19 20:41:31 | D | + y: None +24-11-19 20:41:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:31 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:41:31 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:41:31 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:41:31 | D | - range ratio = [ 1.0000] +24-11-19 20:41:31 | D | sum error = [ 2.6061] +24-11-19 20:41:31 | D | best error = [ 2.6061] +24-11-19 20:41:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:32 | D | sum error = [ 2.5897, 2.5785, 2.5844, 2.6160, 2.6581] +24-11-19 20:41:32 | D | best error = [ 2.4314, 2.3504, 2.3035, 2.2756, 2.2551] +24-11-19 20:41:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:32 | D | sum error = [ 2.7084, 2.7933, 2.8917, 3.0158, 3.1567] +24-11-19 20:41:32 | D | best error = [ 2.2409, 2.2314, 2.2243, 2.2195, 2.2160] +24-11-19 20:41:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:32 | D | sum error = [ 3.3319, 3.5241, 3.7426, 3.9757, 4.2401] +24-11-19 20:41:32 | D | best error = [ 2.2131, 2.2104, 2.2089, 2.2077, 2.2067] +24-11-19 20:41:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:32 | D | sum error = [ 4.5241, 4.8443, 5.1826, 5.5376, 5.9341] +24-11-19 20:41:32 | D | best error = [ 2.2058, 2.2052, 2.2047, 2.2042, 2.2040] +24-11-19 20:41:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:32 | D | sum error = [ 6.3419, 6.7900, 7.2721, 7.7742, 8.3064] +24-11-19 20:41:32 | D | best error = [ 2.2039, 2.2039, 2.2039, 2.2038, 2.2037] +24-11-19 20:41:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:32 | D | sum error = [ 8.8687, 9.4678, 10.1196, 10.7972, 11.5126] +24-11-19 20:41:32 | D | best error = [ 2.2037, 2.2036, 2.2035, 2.2035, 2.2034] +24-11-19 20:41:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:32 | D | sum error = [ 12.2762, 13.0868, 13.9246, 14.8143, 15.7785] +24-11-19 20:41:32 | D | best error = [ 2.2034, 2.2034, 2.2034, 2.2034, 2.2034] +24-11-19 20:41:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:32 | D | sum error = [ 16.7855, 17.8427, 18.9669, 20.1410, 21.4067] +24-11-19 20:41:32 | D | best error = [ 2.2034, 2.2034, 2.2034, 2.2034, 2.2034] +24-11-19 20:41:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:32 | D | sum error = [ 22.7326, 24.1194, 25.5990, 27.1613, 28.7971] +24-11-19 20:41:32 | D | best error = [ 2.2034, 2.2034, 2.2034, 2.2034, 2.2034] +24-11-19 20:41:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:32 | D | sum error = [ 30.5263, 32.3526, 34.2728, 36.2947, 38.4194] +24-11-19 20:41:32 | D | best error = [ 2.2034, 2.2034, 2.2034, 2.2034, 2.2034] +24-11-19 20:41:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:32 | D | sum error = [ 40.6547, 42.9975, 45.4630, 48.0484, 50.7809] +24-11-19 20:41:32 | D | best error = [ 2.2034, 2.2034, 2.2034, 2.2034, 2.2034] +24-11-19 20:41:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:32 | D | sum error = [ 53.6384, 56.6357, 59.7757, 63.0718, 66.5184] +24-11-19 20:41:32 | D | best error = [ 2.2034, 2.2034, 2.2034, 2.2034, 2.2034] +24-11-19 20:41:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:32 | D | sum error = [ 70.1241, 73.9014, 77.8341, 81.9471, 86.2412] +24-11-19 20:41:32 | D | best error = [ 2.2034, 2.2034, 2.2034, 2.2034, 2.2034] +24-11-19 20:41:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:32 | D | sum error = [ 90.7135, 95.3815, 100.2446, 105.3197, 110.5868] +24-11-19 20:41:32 | D | best error = [ 2.2034, 2.2034, 2.2034, 2.2034, 2.2034] +24-11-19 20:41:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:32 | D | sum error = [ 116.0731, 121.7643, 127.6679, 133.7850, 140.1320] +24-11-19 20:41:32 | D | best error = [ 2.2034, 2.2034, 2.2034, 2.2034, 2.2034] +24-11-19 20:41:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:32 | D | sum error = [ 146.7004, 153.4980, 160.5232, 167.7672, 175.2492] +24-11-19 20:41:32 | D | best error = [ 2.2034, 2.2034, 2.2034, 2.2034, 2.2034] +24-11-19 20:41:32 | D | + error = [2.2034] +24-11-19 20:41:32 | D | - Calibrating model.layers.30.mlp.up_proj.weight +24-11-19 20:41:32 | D | + w: sint8 +24-11-19 20:41:32 | D | + x: None +24-11-19 20:41:32 | D | + y: None +24-11-19 20:41:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:32 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:41:32 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:41:32 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:41:32 | D | - range ratio = [ 1.0000] +24-11-19 20:41:32 | D | sum error = [ 12.3254] +24-11-19 20:41:32 | D | best error = [ 12.3254] +24-11-19 20:41:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:33 | D | sum error = [ 12.3258, 12.1778, 12.2712, 12.3676, 12.6244] +24-11-19 20:41:33 | D | best error = [ 11.2607, 10.8271, 10.6262, 10.4960, 10.4371] +24-11-19 20:41:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:33 | D | sum error = [ 12.9356, 13.3300, 13.9028, 14.5368, 15.3053] +24-11-19 20:41:33 | D | best error = [ 10.4098, 10.3956, 10.3901, 10.3884, 10.3877] +24-11-19 20:41:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:33 | D | sum error = [ 16.1747, 17.1680, 18.2495, 19.5097, 20.9492] +24-11-19 20:41:33 | D | best error = [ 10.3877, 10.3877, 10.3877, 10.3877, 10.3877] +24-11-19 20:41:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:33 | D | sum error = [ 22.3874, 23.9450, 25.7357, 27.5712, 29.6246] +24-11-19 20:41:33 | D | best error = [ 10.3877, 10.3877, 10.3877, 10.3877, 10.3877] +24-11-19 20:41:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:33 | D | sum error = [ 31.7315, 34.0598, 36.5039, 39.0719, 41.8401] +24-11-19 20:41:33 | D | best error = [ 10.3877, 10.3877, 10.3877, 10.3877, 10.3877] +24-11-19 20:41:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:33 | D | sum error = [ 44.7342, 47.9183, 51.1982, 54.7294, 58.4897] +24-11-19 20:41:33 | D | best error = [ 10.3877, 10.3877, 10.3877, 10.3877, 10.3877] +24-11-19 20:41:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:33 | D | sum error = [ 62.4581, 66.7305, 71.2292, 75.9164, 80.9355] +24-11-19 20:41:33 | D | best error = [ 10.3877, 10.3877, 10.3877, 10.3877, 10.3877] +24-11-19 20:41:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:33 | D | sum error = [ 86.2921, 91.8689, 97.8750, 104.1069, 110.7960] +24-11-19 20:41:33 | D | best error = [ 10.3877, 10.3877, 10.3877, 10.3877, 10.3877] +24-11-19 20:41:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:33 | D | sum error = [ 117.7860, 125.2079, 133.1725, 141.4889, 150.3930] +24-11-19 20:41:33 | D | best error = [ 10.3877, 10.3877, 10.3877, 10.3877, 10.3877] +24-11-19 20:41:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:33 | D | sum error = [ 159.7076, 169.6295, 179.9976, 191.0918, 202.7762] +24-11-19 20:41:33 | D | best error = [ 10.3877, 10.3877, 10.3877, 10.3877, 10.3877] +24-11-19 20:41:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:33 | D | sum error = [ 215.1805, 228.2249, 242.0367, 256.5144, 271.7894] +24-11-19 20:41:33 | D | best error = [ 10.3877, 10.3877, 10.3877, 10.3877, 10.3877] +24-11-19 20:41:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:33 | D | sum error = [ 288.1174, 305.3019, 323.1948, 342.0541, 361.9264] +24-11-19 20:41:33 | D | best error = [ 10.3877, 10.3877, 10.3877, 10.3877, 10.3877] +24-11-19 20:41:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:33 | D | sum error = [ 382.7584, 404.5910, 427.6722, 451.6511, 476.8255] +24-11-19 20:41:33 | D | best error = [ 10.3877, 10.3877, 10.3877, 10.3877, 10.3877] +24-11-19 20:41:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:33 | D | sum error = [ 502.9704, 530.7712, 559.5312, 589.2930, 620.1003] +24-11-19 20:41:33 | D | best error = [ 10.3877, 10.3877, 10.3877, 10.3877, 10.3877] +24-11-19 20:41:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:33 | D | sum error = [ 652.5059, 685.9617, 720.9391, 756.9282, 794.3349] +24-11-19 20:41:33 | D | best error = [ 10.3877, 10.3877, 10.3877, 10.3877, 10.3877] +24-11-19 20:41:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:33 | D | sum error = [ 832.7423, 872.5123, 913.7443, 956.1584, 1000.0885] +24-11-19 20:41:33 | D | best error = [ 10.3877, 10.3877, 10.3877, 10.3877, 10.3877] +24-11-19 20:41:33 | D | + error = [10.3877] +24-11-19 20:41:33 | D | - Calibrating model.layers.30.mlp.gate_proj.weight +24-11-19 20:41:33 | D | + w: sint8 +24-11-19 20:41:33 | D | + x: None +24-11-19 20:41:33 | D | + y: None +24-11-19 20:41:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:33 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:41:33 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:41:33 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:41:33 | D | - range ratio = [ 1.0000] +24-11-19 20:41:33 | D | sum error = [ 12.9615] +24-11-19 20:41:33 | D | best error = [ 12.9615] +24-11-19 20:41:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:34 | D | sum error = [ 12.8898, 12.7871, 12.8981, 13.0753, 13.3501] +24-11-19 20:41:34 | D | best error = [ 11.8088, 11.3865, 11.1627, 11.0519, 10.9909] +24-11-19 20:41:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:34 | D | sum error = [ 13.6194, 14.1134, 14.6520, 15.4752, 16.1487] +24-11-19 20:41:34 | D | best error = [ 10.9600, 10.9444, 10.9395, 10.9382, 10.9377] +24-11-19 20:41:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:34 | D | sum error = [ 17.1037, 18.2060, 19.3757, 20.7468, 22.1570] +24-11-19 20:41:34 | D | best error = [ 10.9376, 10.9376, 10.9376, 10.9376, 10.9376] +24-11-19 20:41:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:34 | D | sum error = [ 23.7378, 25.4030, 27.2492, 29.2136, 31.3503] +24-11-19 20:41:34 | D | best error = [ 10.9376, 10.9376, 10.9376, 10.9376, 10.9376] +24-11-19 20:41:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:34 | D | sum error = [ 33.6442, 36.0674, 38.6098, 41.3947, 44.2975] +24-11-19 20:41:34 | D | best error = [ 10.9376, 10.9376, 10.9376, 10.9376, 10.9376] +24-11-19 20:41:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:34 | D | sum error = [ 47.5010, 50.7658, 54.4198, 58.1748, 62.1452] +24-11-19 20:41:34 | D | best error = [ 10.9376, 10.9376, 10.9376, 10.9376, 10.9376] +24-11-19 20:41:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:34 | D | sum error = [ 66.2925, 70.9246, 75.6606, 80.7565, 86.1106] +24-11-19 20:41:34 | D | best error = [ 10.9376, 10.9376, 10.9376, 10.9376, 10.9376] +24-11-19 20:41:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:34 | D | sum error = [ 91.7600, 97.7386, 104.0813, 110.7891, 117.9186] +24-11-19 20:41:34 | D | best error = [ 10.9376, 10.9376, 10.9376, 10.9376, 10.9376] +24-11-19 20:41:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:34 | D | sum error = [ 125.5227, 133.4355, 141.7930, 150.8231, 160.3221] +24-11-19 20:41:34 | D | best error = [ 10.9376, 10.9376, 10.9376, 10.9376, 10.9376] +24-11-19 20:41:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:34 | D | sum error = [ 170.3152, 180.9865, 192.1414, 204.0155, 216.5558] +24-11-19 20:41:34 | D | best error = [ 10.9376, 10.9376, 10.9376, 10.9376, 10.9376] +24-11-19 20:41:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:34 | D | sum error = [ 229.8288, 243.8634, 258.7907, 274.4572, 290.9992] +24-11-19 20:41:34 | D | best error = [ 10.9376, 10.9376, 10.9376, 10.9376, 10.9376] +24-11-19 20:41:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:34 | D | sum error = [ 308.5537, 327.0087, 346.0620, 366.4761, 387.8500] +24-11-19 20:41:34 | D | best error = [ 10.9376, 10.9376, 10.9376, 10.9376, 10.9376] +24-11-19 20:41:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:34 | D | sum error = [ 410.3845, 433.7884, 458.5556, 484.1242, 510.9740] +24-11-19 20:41:34 | D | best error = [ 10.9376, 10.9376, 10.9376, 10.9376, 10.9376] +24-11-19 20:41:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:34 | D | sum error = [ 539.1204, 568.4780, 598.8121, 630.8829, 664.3154] +24-11-19 20:41:34 | D | best error = [ 10.9376, 10.9376, 10.9376, 10.9376, 10.9376] +24-11-19 20:41:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:34 | D | sum error = [ 699.1024, 735.3211, 772.7387, 811.4151, 851.4607] +24-11-19 20:41:34 | D | best error = [ 10.9376, 10.9376, 10.9376, 10.9376, 10.9376] +24-11-19 20:41:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:34 | D | sum error = [ 893.0210, 935.7484, 980.2168, 1026.0544, 1073.1205] +24-11-19 20:41:34 | D | best error = [ 10.9376, 10.9376, 10.9376, 10.9376, 10.9376] +24-11-19 20:41:34 | D | + error = [10.9376] +24-11-19 20:41:35 | D | - Calibrating model.layers.30.mlp.down_proj.weight +24-11-19 20:41:35 | D | + w: sint8 +24-11-19 20:41:35 | D | + x: None +24-11-19 20:41:35 | D | + y: None +24-11-19 20:41:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:35 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:41:35 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:41:35 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:41:35 | D | - range ratio = [ 1.0000] +24-11-19 20:41:35 | D | sum error = [ 32.8963] +24-11-19 20:41:35 | D | best error = [ 32.8963] +24-11-19 20:41:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:36 | D | sum error = [ 32.9600, 32.3472, 32.4913, 31.9617, 32.3592] +24-11-19 20:41:36 | D | best error = [ 22.0453, 17.6669, 15.1545, 13.3139, 12.0942] +24-11-19 20:41:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:36 | D | sum error = [ 31.3371, 30.5218, 30.4290, 29.7577, 29.7040] +24-11-19 20:41:36 | D | best error = [ 11.0646, 10.3035, 9.7446, 9.3059, 8.9667] +24-11-19 20:41:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:36 | D | sum error = [ 29.8929, 29.0698, 29.0910, 28.9834, 28.4279] +24-11-19 20:41:36 | D | best error = [ 8.7895, 8.6009, 8.4581, 8.3584, 8.2513] +24-11-19 20:41:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:36 | D | sum error = [ 28.4155, 28.4063, 27.8320, 27.8466, 27.6461] +24-11-19 20:41:36 | D | best error = [ 8.1832, 8.1269, 8.0880, 8.0520, 8.0233] +24-11-19 20:41:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:36 | D | sum error = [ 27.5765, 27.6031, 26.9706, 26.9249, 27.0273] +24-11-19 20:41:36 | D | best error = [ 8.0045, 7.9939, 7.9825, 7.9729, 7.9675] +24-11-19 20:41:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:36 | D | sum error = [ 27.3031, 27.5363, 27.6356, 27.9660, 27.8262] +24-11-19 20:41:36 | D | best error = [ 7.9650, 7.9627, 7.9611, 7.9607, 7.9605] +24-11-19 20:41:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:36 | D | sum error = [ 28.3927, 29.2133, 29.4981, 30.3100, 31.1084] +24-11-19 20:41:36 | D | best error = [ 7.9596, 7.9594, 7.9593, 7.9593, 7.9593] +24-11-19 20:41:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:36 | D | sum error = [ 32.1308, 32.9385, 34.4179, 35.5998, 37.1928] +24-11-19 20:41:36 | D | best error = [ 7.9593, 7.9590, 7.9590, 7.9590, 7.9590] +24-11-19 20:41:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:36 | D | sum error = [ 39.0135, 40.7851, 42.9130, 45.2802, 48.0509] +24-11-19 20:41:36 | D | best error = [ 7.9590, 7.9590, 7.9590, 7.9590, 7.9590] +24-11-19 20:41:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:36 | D | sum error = [ 51.4306, 55.6467, 61.0372, 68.1166, 77.1445] +24-11-19 20:41:36 | D | best error = [ 7.9590, 7.9590, 7.9590, 7.9590, 7.9590] +24-11-19 20:41:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:36 | D | sum error = [ 89.5696, 105.0920, 125.2428, 150.7012, 182.8323] +24-11-19 20:41:36 | D | best error = [ 7.9590, 7.9590, 7.9590, 7.9590, 7.9590] +24-11-19 20:41:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:36 | D | sum error = [ 222.2956, 270.3398, 327.2717, 392.8769, 467.3647] +24-11-19 20:41:36 | D | best error = [ 7.9590, 7.9590, 7.9590, 7.9590, 7.9590] +24-11-19 20:41:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:36 | D | sum error = [ 550.7997, 642.6372, 742.2299, 848.9757, 961.8554] +24-11-19 20:41:36 | D | best error = [ 7.9590, 7.9590, 7.9590, 7.9590, 7.9590] +24-11-19 20:41:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:36 | D | sum error = [ 1079.8172, 1202.5805, 1329.2061, 1459.0327, 1591.0249] +24-11-19 20:41:36 | D | best error = [ 7.9590, 7.9590, 7.9590, 7.9590, 7.9590] +24-11-19 20:41:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:36 | D | sum error = [ 1725.2106, 1861.2021, 1998.5507, 2137.0906, 2276.6474] +24-11-19 20:41:36 | D | best error = [ 7.9590, 7.9590, 7.9590, 7.9590, 7.9590] +24-11-19 20:41:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:36 | D | sum error = [ 2417.1318, 2558.3631, 2700.3012, 2842.7519, 2985.8469] +24-11-19 20:41:36 | D | best error = [ 7.9590, 7.9590, 7.9590, 7.9590, 7.9590] +24-11-19 20:41:36 | D | + error = [7.9590] +24-11-19 20:41:36 | D | - Quantizing model.layers.30.self_attn.q_proj.weight +24-11-19 20:41:37 | D | - Quantizing model.layers.30.self_attn.k_proj.weight +24-11-19 20:41:38 | D | - Quantizing model.layers.30.self_attn.v_proj.weight +24-11-19 20:41:39 | D | - Quantizing model.layers.30.self_attn.o_proj.weight +24-11-19 20:41:40 | D | - Quantizing model.layers.30.mlp.up_proj.weight +24-11-19 20:41:41 | D | - Quantizing model.layers.30.mlp.gate_proj.weight +24-11-19 20:41:42 | D | - Quantizing model.layers.30.mlp.down_proj.weight +24-11-19 20:41:50 | D | - Quantizing layer model.layers.31 +24-11-19 20:41:50 | D | - Calibrating model.layers.31.self_attn.q_proj.weight +24-11-19 20:41:50 | D | + w: sint8 +24-11-19 20:41:50 | D | + x: None +24-11-19 20:41:50 | D | + y: None +24-11-19 20:41:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:41:50 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:41:50 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:41:51 | D | + finished calculating the original outputs, ram usage: 13.2 +24-11-19 20:41:51 | D | - range ratio = [ 1.0000] +24-11-19 20:41:51 | D | sum error = [ 15.2204] +24-11-19 20:41:51 | D | best error = [ 15.2204] +24-11-19 20:42:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:42:04 | D | sum error = [ 15.1735, 15.0683, 15.5503, 15.9918, 15.6623] +24-11-19 20:42:04 | D | best error = [ 15.1735, 15.0683, 15.0683, 15.0683, 15.0683] +24-11-19 20:42:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:42:04 | D | sum error = [ 16.4812, 17.7243, 17.6739, 19.8125, 22.1824] +24-11-19 20:42:04 | D | best error = [ 15.0683, 15.0683, 15.0683, 15.0683, 15.0683] +24-11-19 20:42:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:42:04 | D | sum error = [ 23.2931, 24.0895, 27.8287, 29.7030, 31.6188] +24-11-19 20:42:04 | D | best error = [ 15.0683, 15.0683, 15.0683, 15.0683, 15.0683] +24-11-19 20:42:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:42:04 | D | sum error = [ 36.3195, 39.7834, 42.3161, 46.5922, 52.1867] +24-11-19 20:42:04 | D | best error = [ 15.0683, 15.0683, 15.0683, 15.0683, 15.0683] +24-11-19 20:42:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:42:04 | D | sum error = [ 56.3757, 61.8991, 65.4634, 72.4412, 78.4763] +24-11-19 20:42:04 | D | best error = [ 15.0683, 15.0683, 15.0683, 15.0683, 15.0683] +24-11-19 20:42:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:42:04 | D | sum error = [ 85.1964, 92.9267, 99.6549, 106.6693, 115.6736] +24-11-19 20:42:04 | D | best error = [ 15.0683, 15.0683, 15.0683, 15.0683, 15.0683] +24-11-19 20:42:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:42:04 | D | sum error = [ 123.6973, 133.0302, 142.6329, 152.7277, 165.4779] +24-11-19 20:42:04 | D | best error = [ 15.0683, 15.0683, 15.0683, 15.0683, 15.0683] +24-11-19 20:42:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:42:04 | D | sum error = [ 178.4679, 191.1073, 206.2322, 221.2052, 238.7598] +24-11-19 20:42:04 | D | best error = [ 15.0683, 15.0683, 15.0683, 15.0683, 15.0683] +24-11-19 20:42:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:42:04 | D | sum error = [ 256.7454, 276.6023, 298.2234, 322.5441, 347.3127] +24-11-19 20:42:04 | D | best error = [ 15.0683, 15.0683, 15.0683, 15.0683, 15.0683] +24-11-19 20:42:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:42:04 | D | sum error = [ 374.0340, 403.3903, 433.9638, 466.6470, 501.0093] +24-11-19 20:42:04 | D | best error = [ 15.0683, 15.0683, 15.0683, 15.0683, 15.0683] +24-11-19 20:42:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:42:04 | D | sum error = [ 539.0946, 578.4623, 620.3977, 667.4746, 716.8239] +24-11-19 20:42:04 | D | best error = [ 15.0683, 15.0683, 15.0683, 15.0683, 15.0683] +24-11-19 20:42:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:42:04 | D | sum error = [ 769.4769, 826.7143, 886.9315, 952.6406, 1020.7873] +24-11-19 20:42:04 | D | best error = [ 15.0683, 15.0683, 15.0683, 15.0683, 15.0683] +24-11-19 20:42:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:42:04 | D | sum error = [ 1096.4682, 1176.4382, 1262.1691, 1353.9791, 1454.2703] +24-11-19 20:42:04 | D | best error = [ 15.0683, 15.0683, 15.0683, 15.0683, 15.0683] +24-11-19 20:42:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:42:04 | D | sum error = [ 1561.2737, 1675.5398, 1799.6451, 1932.5445, 2074.5910] +24-11-19 20:42:04 | D | best error = [ 15.0683, 15.0683, 15.0683, 15.0683, 15.0683] +24-11-19 20:42:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:42:04 | D | sum error = [ 2226.1703, 2387.8319, 2560.8140, 2746.3476, 2944.6750] +24-11-19 20:42:04 | D | best error = [ 15.0683, 15.0683, 15.0683, 15.0683, 15.0683] +24-11-19 20:42:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:42:04 | D | sum error = [ 3157.3410, 3384.9601, 3627.9821, 3888.4887, 4165.8449] +24-11-19 20:42:04 | D | best error = [ 15.0683, 15.0683, 15.0683, 15.0683, 15.0683] +24-11-19 20:42:04 | D | + error = [15.0683] +24-11-19 20:42:04 | D | - Calibrating model.layers.31.self_attn.k_proj.weight +24-11-19 20:42:04 | D | + w: sint8 +24-11-19 20:42:04 | D | + x: None +24-11-19 20:42:04 | D | + y: None +24-11-19 20:42:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:42:04 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:42:04 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:42:04 | D | + finished calculating the original outputs, ram usage: 13.4 +24-11-19 20:42:05 | D | - range ratio = [ 1.0000] +24-11-19 20:42:05 | D | sum error = [ 19.6212] +24-11-19 20:42:05 | D | best error = [ 19.6212] +24-11-19 20:42:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:42:17 | D | sum error = [ 22.0381, 20.5294, 19.5076, 19.3915, 22.4782] +24-11-19 20:42:17 | D | best error = [ 19.6212, 19.6212, 19.5076, 19.3915, 19.3915] +24-11-19 20:42:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:42:17 | D | sum error = [ 20.0321, 22.5132, 21.6057, 23.8498, 27.4203] +24-11-19 20:42:17 | D | best error = [ 19.3915, 19.3915, 19.3915, 19.3915, 19.3915] +24-11-19 20:42:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:42:17 | D | sum error = [ 30.4753, 29.8109, 29.5689, 32.7965, 42.4151] +24-11-19 20:42:17 | D | best error = [ 19.3915, 19.3915, 19.3915, 19.3915, 19.3915] +24-11-19 20:42:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:42:17 | D | sum error = [ 39.1304, 46.9454, 51.2095, 52.5934, 60.4609] +24-11-19 20:42:17 | D | best error = [ 19.3915, 19.3915, 19.3915, 19.3915, 19.3915] +24-11-19 20:42:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:42:17 | D | sum error = [ 64.4050, 69.2313, 72.9479, 82.2522, 91.8004] +24-11-19 20:42:17 | D | best error = [ 19.3915, 19.3915, 19.3915, 19.3915, 19.3915] +24-11-19 20:42:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:42:17 | D | sum error = [ 98.2079, 104.9407, 112.7722, 121.0145, 128.5054] +24-11-19 20:42:17 | D | best error = [ 19.3915, 19.3915, 19.3915, 19.3915, 19.3915] +24-11-19 20:42:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:42:17 | D | sum error = [ 138.2161, 145.3185, 158.7642, 169.7905, 180.3145] +24-11-19 20:42:17 | D | best error = [ 19.3915, 19.3915, 19.3915, 19.3915, 19.3915] +24-11-19 20:42:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:42:17 | D | sum error = [ 191.1937, 205.8961, 220.2297, 235.4357, 253.9832] +24-11-19 20:42:17 | D | best error = [ 19.3915, 19.3915, 19.3915, 19.3915, 19.3915] +24-11-19 20:42:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:42:17 | D | sum error = [ 270.6346, 286.3046, 304.6731, 321.6596, 343.6976] +24-11-19 20:42:17 | D | best error = [ 19.3915, 19.3915, 19.3915, 19.3915, 19.3915] +24-11-19 20:42:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:42:17 | D | sum error = [ 366.4176, 391.4450, 421.3351, 448.7821, 479.9540] +24-11-19 20:42:17 | D | best error = [ 19.3915, 19.3915, 19.3915, 19.3915, 19.3915] +24-11-19 20:42:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:42:17 | D | sum error = [ 513.5513, 550.3292, 592.0204, 634.5501, 683.3161] +24-11-19 20:42:17 | D | best error = [ 19.3915, 19.3915, 19.3915, 19.3915, 19.3915] +24-11-19 20:42:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:42:17 | D | sum error = [ 734.1171, 789.4574, 849.0942, 910.9957, 978.0773] +24-11-19 20:42:17 | D | best error = [ 19.3915, 19.3915, 19.3915, 19.3915, 19.3915] +24-11-19 20:42:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:42:17 | D | sum error = [ 1050.1139, 1127.6796, 1209.5642, 1302.8946, 1401.1080] +24-11-19 20:42:17 | D | best error = [ 19.3915, 19.3915, 19.3915, 19.3915, 19.3915] +24-11-19 20:42:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:42:17 | D | sum error = [ 1511.6496, 1626.3482, 1750.6432, 1885.7417, 2032.3393] +24-11-19 20:42:17 | D | best error = [ 19.3915, 19.3915, 19.3915, 19.3915, 19.3915] +24-11-19 20:42:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:42:17 | D | sum error = [ 2188.3722, 2361.3335, 2542.1017, 2739.4764, 2950.2261] +24-11-19 20:42:17 | D | best error = [ 19.3915, 19.3915, 19.3915, 19.3915, 19.3915] +24-11-19 20:42:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:42:17 | D | sum error = [ 3177.8696, 3418.2127, 3680.8825, 3958.3658, 4255.0389] +24-11-19 20:42:17 | D | best error = [ 19.3915, 19.3915, 19.3915, 19.3915, 19.3915] +24-11-19 20:42:17 | D | + error = [19.3915] +24-11-19 20:42:17 | D | - Calibrating model.layers.31.self_attn.v_proj.weight +24-11-19 20:42:17 | D | + w: sint8 +24-11-19 20:42:17 | D | + x: None +24-11-19 20:42:17 | D | + y: None +24-11-19 20:42:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:42:17 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:42:17 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:42:18 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:42:18 | D | - range ratio = [ 1.0000] +24-11-19 20:42:18 | D | sum error = [ 7.1425] +24-11-19 20:42:18 | D | best error = [ 7.1425] +24-11-19 20:42:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:42:18 | D | sum error = [ 7.0746, 7.0772, 7.1226, 7.1757, 7.3251] +24-11-19 20:42:18 | D | best error = [ 6.5573, 6.3478, 6.2429, 6.1819, 6.1502] +24-11-19 20:42:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:42:18 | D | sum error = [ 7.4906, 7.7635, 8.0272, 8.4426, 8.8785] +24-11-19 20:42:18 | D | best error = [ 6.1348, 6.1276, 6.1245, 6.1236, 6.1235] +24-11-19 20:42:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:42:18 | D | sum error = [ 9.3645, 9.9784, 10.5790, 11.2913, 12.0628] +24-11-19 20:42:18 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:42:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:42:18 | D | sum error = [ 12.9323, 13.8333, 14.8188, 15.8855, 17.0363] +24-11-19 20:42:18 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:42:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:42:18 | D | sum error = [ 18.2383, 19.5468, 20.8744, 22.3206, 23.8820] +24-11-19 20:42:18 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:42:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:42:18 | D | sum error = [ 25.4862, 27.2183, 29.0511, 30.9617, 32.9830] +24-11-19 20:42:18 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:42:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:42:18 | D | sum error = [ 35.1293, 37.4131, 39.8031, 42.3105, 44.9297] +24-11-19 20:42:18 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:42:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:42:18 | D | sum error = [ 47.7155, 50.6461, 53.7065, 56.9330, 60.3290] +24-11-19 20:42:18 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:42:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:42:18 | D | sum error = [ 63.8696, 67.6162, 71.5237, 75.6106, 79.8987] +24-11-19 20:42:18 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:42:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:42:18 | D | sum error = [ 84.3826, 89.0943, 94.0279, 99.1452, 104.5056] +24-11-19 20:42:18 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:42:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:42:18 | D | sum error = [ 110.1022, 115.9356, 121.9911, 128.3106, 134.9472] +24-11-19 20:42:18 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:42:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:42:18 | D | sum error = [ 141.8061, 148.9298, 156.3558, 164.0508, 172.0323] +24-11-19 20:42:18 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:42:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:42:18 | D | sum error = [ 180.3181, 188.9340, 197.8609, 207.0752, 216.6351] +24-11-19 20:42:18 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:42:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:42:18 | D | sum error = [ 226.4945, 236.6881, 247.2244, 258.1079, 269.3415] +24-11-19 20:42:18 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:42:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:42:18 | D | sum error = [ 280.9379, 292.8798, 305.2135, 317.8905, 330.9918] +24-11-19 20:42:18 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:42:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:42:18 | D | sum error = [ 344.4591, 358.3471, 372.6138, 387.2948, 402.3751] +24-11-19 20:42:18 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:42:18 | D | + error = [6.1235] +24-11-19 20:42:18 | D | - Calibrating model.layers.31.self_attn.o_proj.weight +24-11-19 20:42:18 | D | + w: sint8 +24-11-19 20:42:18 | D | + x: None +24-11-19 20:42:18 | D | + y: None +24-11-19 20:42:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:42:18 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:42:18 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:42:18 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:42:18 | D | - range ratio = [ 1.0000] +24-11-19 20:42:18 | D | sum error = [ 3.3448] +24-11-19 20:42:18 | D | best error = [ 3.3448] +24-11-19 20:42:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:42:19 | D | sum error = [ 3.2880, 3.3090, 3.3390, 3.3741, 3.4702] +24-11-19 20:42:19 | D | best error = [ 3.0139, 2.8867, 2.8128, 2.7657, 2.7319] +24-11-19 20:42:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:42:19 | D | sum error = [ 3.5938, 3.7294, 3.9174, 4.1601, 4.4181] +24-11-19 20:42:19 | D | best error = [ 2.7108, 2.6919, 2.6785, 2.6697, 2.6631] +24-11-19 20:42:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:42:19 | D | sum error = [ 4.7299, 5.0625, 5.4483, 5.8597, 6.3171] +24-11-19 20:42:19 | D | best error = [ 2.6591, 2.6560, 2.6539, 2.6522, 2.6509] +24-11-19 20:42:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:42:19 | D | sum error = [ 6.8210, 7.3389, 7.9472, 8.6024, 9.2781] +24-11-19 20:42:19 | D | best error = [ 2.6503, 2.6498, 2.6494, 2.6490, 2.6486] +24-11-19 20:42:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:42:19 | D | sum error = [ 10.0510, 10.8336, 11.7198, 12.6403, 13.6620] +24-11-19 20:42:19 | D | best error = [ 2.6485, 2.6483, 2.6483, 2.6482, 2.6482] +24-11-19 20:42:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:42:19 | D | sum error = [ 14.7200, 15.8607, 17.1200, 18.4489, 19.9117] +24-11-19 20:42:19 | D | best error = [ 2.6481, 2.6481, 2.6481, 2.6481, 2.6481] +24-11-19 20:42:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:42:19 | D | sum error = [ 21.4403, 23.1041, 24.8785, 26.7988, 28.8468] +24-11-19 20:42:19 | D | best error = [ 2.6481, 2.6481, 2.6481, 2.6481, 2.6481] +24-11-19 20:42:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:42:19 | D | sum error = [ 31.0492, 33.3761, 35.9040, 38.5658, 41.4535] +24-11-19 20:42:19 | D | best error = [ 2.6481, 2.6481, 2.6481, 2.6481, 2.6481] +24-11-19 20:42:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:42:19 | D | sum error = [ 44.5260, 47.7894, 51.2778, 54.9870, 58.9659] +24-11-19 20:42:19 | D | best error = [ 2.6481, 2.6481, 2.6481, 2.6481, 2.6481] +24-11-19 20:42:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:42:19 | D | sum error = [ 63.1969, 67.6950, 72.4635, 77.5434, 82.9279] +24-11-19 20:42:19 | D | best error = [ 2.6481, 2.6481, 2.6481, 2.6481, 2.6481] +24-11-19 20:42:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:42:19 | D | sum error = [ 88.6428, 94.6810, 101.0777, 107.8369, 115.0007] +24-11-19 20:42:19 | D | best error = [ 2.6481, 2.6481, 2.6481, 2.6481, 2.6481] +24-11-19 20:42:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:42:19 | D | sum error = [ 122.5493, 130.5249, 138.9382, 147.8055, 157.1402] +24-11-19 20:42:19 | D | best error = [ 2.6481, 2.6481, 2.6481, 2.6481, 2.6481] +24-11-19 20:42:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:42:19 | D | sum error = [ 166.9635, 177.3029, 188.1358, 199.4900, 211.3780] +24-11-19 20:42:19 | D | best error = [ 2.6481, 2.6481, 2.6481, 2.6481, 2.6481] +24-11-19 20:42:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:42:19 | D | sum error = [ 223.8271, 236.8338, 250.4045, 264.5771, 279.2996] +24-11-19 20:42:19 | D | best error = [ 2.6481, 2.6481, 2.6481, 2.6481, 2.6481] +24-11-19 20:42:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:42:19 | D | sum error = [ 294.6285, 310.5808, 327.1232, 344.2833, 362.0896] +24-11-19 20:42:19 | D | best error = [ 2.6481, 2.6481, 2.6481, 2.6481, 2.6481] +24-11-19 20:42:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:42:19 | D | sum error = [ 380.5206, 399.5967, 419.3157, 439.6837, 460.6854] +24-11-19 20:42:19 | D | best error = [ 2.6481, 2.6481, 2.6481, 2.6481, 2.6481] +24-11-19 20:42:19 | D | + error = [2.6481] +24-11-19 20:42:19 | D | - Calibrating model.layers.31.mlp.up_proj.weight +24-11-19 20:42:19 | D | + w: sint8 +24-11-19 20:42:19 | D | + x: None +24-11-19 20:42:19 | D | + y: None +24-11-19 20:42:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:42:19 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:42:19 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:42:19 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:42:19 | D | - range ratio = [ 1.0000] +24-11-19 20:42:19 | D | sum error = [ 11.4365] +24-11-19 20:42:19 | D | best error = [ 11.4365] +24-11-19 20:42:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:42:20 | D | sum error = [ 11.3794, 11.3383, 11.3949, 11.5100, 11.7402] +24-11-19 20:42:20 | D | best error = [ 10.4752, 10.1288, 9.9467, 9.8414, 9.7829] +24-11-19 20:42:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:42:20 | D | sum error = [ 12.0194, 12.4803, 12.9889, 13.5759, 14.3248] +24-11-19 20:42:20 | D | best error = [ 9.7556, 9.7436, 9.7391, 9.7376, 9.7373] +24-11-19 20:42:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:42:20 | D | sum error = [ 15.1346, 16.1378, 17.1919, 18.3540, 19.6634] +24-11-19 20:42:20 | D | best error = [ 9.7373, 9.7371, 9.7371, 9.7371, 9.7371] +24-11-19 20:42:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:42:20 | D | sum error = [ 21.0816, 22.6084, 24.2972, 26.1387, 28.0548] +24-11-19 20:42:20 | D | best error = [ 9.7371, 9.7371, 9.7371, 9.7371, 9.7371] +24-11-19 20:42:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:42:20 | D | sum error = [ 30.1312, 32.3248, 34.7177, 37.2659, 40.0397] +24-11-19 20:42:20 | D | best error = [ 9.7371, 9.7371, 9.7371, 9.7371, 9.7371] +24-11-19 20:42:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:42:20 | D | sum error = [ 42.9122, 46.0280, 49.3462, 52.8249, 56.6086] +24-11-19 20:42:20 | D | best error = [ 9.7371, 9.7371, 9.7371, 9.7371, 9.7371] +24-11-19 20:42:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:42:20 | D | sum error = [ 60.6306, 64.8824, 69.4923, 74.2720, 79.3570] +24-11-19 20:42:20 | D | best error = [ 9.7371, 9.7371, 9.7371, 9.7371, 9.7371] +24-11-19 20:42:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:42:20 | D | sum error = [ 84.7704, 90.6680, 96.8714, 103.4119, 110.4614] +24-11-19 20:42:20 | D | best error = [ 9.7371, 9.7371, 9.7371, 9.7371, 9.7371] +24-11-19 20:42:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:42:20 | D | sum error = [ 117.9611, 125.8732, 134.3411, 143.2961, 152.8243] +24-11-19 20:42:20 | D | best error = [ 9.7371, 9.7371, 9.7371, 9.7371, 9.7371] +24-11-19 20:42:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:42:20 | D | sum error = [ 163.0088, 173.7659, 185.1843, 197.3209, 210.1769] +24-11-19 20:42:20 | D | best error = [ 9.7371, 9.7371, 9.7371, 9.7371, 9.7371] +24-11-19 20:42:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:42:20 | D | sum error = [ 223.8595, 238.2737, 253.5414, 269.7521, 286.8774] +24-11-19 20:42:20 | D | best error = [ 9.7371, 9.7371, 9.7371, 9.7371, 9.7371] +24-11-19 20:42:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:42:20 | D | sum error = [ 305.0052, 324.1630, 344.3284, 365.5849, 388.0416] +24-11-19 20:42:20 | D | best error = [ 9.7371, 9.7371, 9.7371, 9.7371, 9.7371] +24-11-19 20:42:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:42:20 | D | sum error = [ 411.6650, 436.4128, 462.5451, 489.9228, 518.6242] +24-11-19 20:42:20 | D | best error = [ 9.7371, 9.7371, 9.7371, 9.7371, 9.7371] +24-11-19 20:42:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:42:20 | D | sum error = [ 548.7199, 580.1769, 613.1435, 647.5482, 683.3823] +24-11-19 20:42:20 | D | best error = [ 9.7371, 9.7371, 9.7371, 9.7371, 9.7371] +24-11-19 20:42:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:42:20 | D | sum error = [ 720.8461, 759.8791, 800.5169, 842.7235, 886.5321] +24-11-19 20:42:20 | D | best error = [ 9.7371, 9.7371, 9.7371, 9.7371, 9.7371] +24-11-19 20:42:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:42:20 | D | sum error = [ 931.9327, 979.0450, 1027.7390, 1078.0729, 1130.0133] +24-11-19 20:42:20 | D | best error = [ 9.7371, 9.7371, 9.7371, 9.7371, 9.7371] +24-11-19 20:42:20 | D | + error = [9.7371] +24-11-19 20:42:20 | D | - Calibrating model.layers.31.mlp.gate_proj.weight +24-11-19 20:42:20 | D | + w: sint8 +24-11-19 20:42:20 | D | + x: None +24-11-19 20:42:20 | D | + y: None +24-11-19 20:42:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:42:20 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:42:20 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:42:20 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:42:20 | D | - range ratio = [ 1.0000] +24-11-19 20:42:20 | D | sum error = [ 12.1305] +24-11-19 20:42:20 | D | best error = [ 12.1305] +24-11-19 20:42:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:42:21 | D | sum error = [ 12.0055, 11.9940, 12.0402, 12.2101, 12.4273] +24-11-19 20:42:21 | D | best error = [ 11.0941, 10.7180, 10.5280, 10.4183, 10.3638] +24-11-19 20:42:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:42:21 | D | sum error = [ 12.7492, 13.2095, 13.7160, 14.3700, 15.1644] +24-11-19 20:42:21 | D | best error = [ 10.3361, 10.3238, 10.3187, 10.3170, 10.3169] +24-11-19 20:42:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:42:21 | D | sum error = [ 16.0517, 17.0458, 18.1590, 19.5128, 20.8498] +24-11-19 20:42:21 | D | best error = [ 10.3168, 10.3168, 10.3168, 10.3168, 10.3168] +24-11-19 20:42:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:42:21 | D | sum error = [ 22.3873, 24.0355, 25.8343, 27.7364, 29.8160] +24-11-19 20:42:21 | D | best error = [ 10.3168, 10.3168, 10.3168, 10.3168, 10.3168] +24-11-19 20:42:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:42:21 | D | sum error = [ 32.0526, 34.4052, 37.0354, 39.7629, 42.6565] +24-11-19 20:42:21 | D | best error = [ 10.3168, 10.3168, 10.3168, 10.3168, 10.3168] +24-11-19 20:42:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:42:21 | D | sum error = [ 45.7456, 49.0975, 52.6130, 56.2882, 60.3415] +24-11-19 20:42:21 | D | best error = [ 10.3168, 10.3168, 10.3168, 10.3168, 10.3168] +24-11-19 20:42:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:42:21 | D | sum error = [ 64.5855, 69.0620, 73.8511, 78.9249, 84.3776] +24-11-19 20:42:21 | D | best error = [ 10.3168, 10.3168, 10.3168, 10.3168, 10.3168] +24-11-19 20:42:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:42:21 | D | sum error = [ 90.1027, 96.2198, 102.7133, 109.5840, 116.9499] +24-11-19 20:42:21 | D | best error = [ 10.3168, 10.3168, 10.3168, 10.3168, 10.3168] +24-11-19 20:42:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:42:21 | D | sum error = [ 124.7798, 133.0852, 141.8766, 151.3138, 161.2274] +24-11-19 20:42:21 | D | best error = [ 10.3168, 10.3168, 10.3168, 10.3168, 10.3168] +24-11-19 20:42:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:42:21 | D | sum error = [ 171.8606, 183.1125, 195.0699, 207.7798, 221.2470] +24-11-19 20:42:21 | D | best error = [ 10.3168, 10.3168, 10.3168, 10.3168, 10.3168] +24-11-19 20:42:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:42:21 | D | sum error = [ 235.4817, 250.6909, 266.7370, 283.7256, 301.6951] +24-11-19 20:42:21 | D | best error = [ 10.3168, 10.3168, 10.3168, 10.3168, 10.3168] +24-11-19 20:42:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:42:21 | D | sum error = [ 320.6507, 340.7267, 361.8239, 384.1038, 407.4989] +24-11-19 20:42:21 | D | best error = [ 10.3168, 10.3168, 10.3168, 10.3168, 10.3168] +24-11-19 20:42:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:42:21 | D | sum error = [ 432.2017, 458.0942, 485.3556, 513.9492, 543.9666] +24-11-19 20:42:21 | D | best error = [ 10.3168, 10.3168, 10.3168, 10.3168, 10.3168] +24-11-19 20:42:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:42:21 | D | sum error = [ 575.4339, 608.4002, 642.7392, 678.5867, 716.0666] +24-11-19 20:42:21 | D | best error = [ 10.3168, 10.3168, 10.3168, 10.3168, 10.3168] +24-11-19 20:42:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:42:21 | D | sum error = [ 755.1122, 795.7046, 837.9817, 881.8340, 927.3398] +24-11-19 20:42:21 | D | best error = [ 10.3168, 10.3168, 10.3168, 10.3168, 10.3168] +24-11-19 20:42:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:42:21 | D | sum error = [ 974.3948, 1023.0745, 1073.3960, 1125.3139, 1178.8357] +24-11-19 20:42:21 | D | best error = [ 10.3168, 10.3168, 10.3168, 10.3168, 10.3168] +24-11-19 20:42:21 | D | + error = [10.3168] +24-11-19 20:42:21 | D | - Calibrating model.layers.31.mlp.down_proj.weight +24-11-19 20:42:21 | D | + w: sint8 +24-11-19 20:42:21 | D | + x: None +24-11-19 20:42:21 | D | + y: None +24-11-19 20:42:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:42:21 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:42:22 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:42:22 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:42:22 | D | - range ratio = [ 1.0000] +24-11-19 20:42:22 | D | sum error = [ 16.3837] +24-11-19 20:42:22 | D | best error = [ 16.3837] +24-11-19 20:42:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:42:23 | D | sum error = [ 16.2078, 15.9895, 15.8525, 15.7853, 15.5108] +24-11-19 20:42:23 | D | best error = [ 14.4999, 13.7480, 13.2792, 12.9795, 12.7379] +24-11-19 20:42:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:42:23 | D | sum error = [ 15.4281, 15.3097, 15.2463, 15.0511, 14.8326] +24-11-19 20:42:23 | D | best error = [ 12.5493, 12.3798, 12.2452, 12.1236, 12.0079] +24-11-19 20:42:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:42:23 | D | sum error = [ 14.8768, 14.8840, 14.7524, 14.7282, 14.8245] +24-11-19 20:42:23 | D | best error = [ 11.9105, 11.8183, 11.7319, 11.6586, 11.5955] +24-11-19 20:42:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:42:23 | D | sum error = [ 14.6985, 14.6694, 14.8959, 14.9791, 15.0439] +24-11-19 20:42:23 | D | best error = [ 11.5398, 11.4993, 11.4663, 11.4405, 11.4108] +24-11-19 20:42:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:42:23 | D | sum error = [ 15.3753, 15.6147, 16.0405, 16.4434, 16.8740] +24-11-19 20:42:23 | D | best error = [ 11.3910, 11.3779, 11.3649, 11.3548, 11.3465] +24-11-19 20:42:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:42:23 | D | sum error = [ 17.5219, 18.1300, 18.8935, 19.7694, 20.6994] +24-11-19 20:42:23 | D | best error = [ 11.3423, 11.3363, 11.3344, 11.3320, 11.3300] +24-11-19 20:42:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:42:23 | D | sum error = [ 21.7738, 22.9280, 24.2374, 25.6661, 27.2460] +24-11-19 20:42:23 | D | best error = [ 11.3293, 11.3283, 11.3282, 11.3282, 11.3280] +24-11-19 20:42:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:42:23 | D | sum error = [ 28.9889, 30.8872, 32.8870, 35.1127, 37.5511] +24-11-19 20:42:23 | D | best error = [ 11.3280, 11.3277, 11.3277, 11.3276, 11.3276] +24-11-19 20:42:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:42:23 | D | sum error = [ 40.1515, 42.9997, 46.0949, 49.3546, 52.9455] +24-11-19 20:42:23 | D | best error = [ 11.3276, 11.3274, 11.3274, 11.3274, 11.3274] +24-11-19 20:42:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:42:23 | D | sum error = [ 56.7596, 60.9169, 65.4328, 70.2986, 75.5259] +24-11-19 20:42:23 | D | best error = [ 11.3274, 11.3274, 11.3274, 11.3274, 11.3274] +24-11-19 20:42:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:42:23 | D | sum error = [ 81.2350, 87.3116, 93.9715, 101.2349, 109.0219] +24-11-19 20:42:23 | D | best error = [ 11.3274, 11.3274, 11.3274, 11.3274, 11.3274] +24-11-19 20:42:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:42:23 | D | sum error = [ 117.5065, 126.7842, 136.9164, 147.8667, 159.8438] +24-11-19 20:42:23 | D | best error = [ 11.3274, 11.3274, 11.3274, 11.3274, 11.3274] +24-11-19 20:42:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:42:23 | D | sum error = [ 172.9510, 187.0875, 202.5635, 219.4365, 237.7642] +24-11-19 20:42:23 | D | best error = [ 11.3274, 11.3274, 11.3274, 11.3274, 11.3274] +24-11-19 20:42:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:42:23 | D | sum error = [ 257.6644, 279.2056, 302.6104, 327.8024, 355.0250] +24-11-19 20:42:23 | D | best error = [ 11.3274, 11.3274, 11.3274, 11.3274, 11.3274] +24-11-19 20:42:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:42:23 | D | sum error = [ 384.4654, 416.1861, 450.3329, 486.9427, 526.2527] +24-11-19 20:42:23 | D | best error = [ 11.3274, 11.3274, 11.3274, 11.3274, 11.3274] +24-11-19 20:42:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:42:23 | D | sum error = [ 568.3629, 613.4341, 661.5867, 712.8869, 767.5746] +24-11-19 20:42:23 | D | best error = [ 11.3274, 11.3274, 11.3274, 11.3274, 11.3274] +24-11-19 20:42:23 | D | + error = [11.3274] +24-11-19 20:42:23 | D | - Quantizing model.layers.31.self_attn.q_proj.weight +24-11-19 20:42:24 | D | - Quantizing model.layers.31.self_attn.k_proj.weight +24-11-19 20:42:25 | D | - Quantizing model.layers.31.self_attn.v_proj.weight +24-11-19 20:42:26 | D | - Quantizing model.layers.31.self_attn.o_proj.weight +24-11-19 20:42:26 | D | - Quantizing model.layers.31.mlp.up_proj.weight +24-11-19 20:42:27 | D | - Quantizing model.layers.31.mlp.gate_proj.weight +24-11-19 20:42:28 | D | - Quantizing model.layers.31.mlp.down_proj.weight +24-11-19 20:42:31 | I | - Saving weight quantizer settings to runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-2-7b-instruct-together-32k.pt +24-11-19 20:42:31 | I | - Linking weight quantizer settings to runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200727.RUNNING/model/wgts.pt +24-11-19 20:42:31 | I | - Saving model checkpoint to runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200727.RUNNING/model +24-11-19 20:42:47 | I | * Quantizing activations +24-11-19 20:42:47 | I | - Generating activation quantizer settings +24-11-19 20:42:47 | D | Starting new HTTPS connection (7): huggingface.co:443 +24-11-19 20:42:53 | D | Starting new HTTPS connection (8): huggingface.co:443 +24-11-19 20:43:05 | D | Starting new HTTPS connection (3): s3.amazonaws.com:443 +24-11-19 20:43:17 | W | Repo card metadata block was not found. Setting CardData to empty. +24-11-19 20:43:17 | D | Starting new HTTPS connection (9): huggingface.co:443 +24-11-19 20:43:29 | W | Using the latest cached version of the dataset since mit-han-lab/pile-val-backup couldn't be found on the Hugging Face Hub +24-11-19 20:43:29 | W | Found the latest cached dataset configuration 'default' at /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4 (last modified on Tue Oct 8 18:58:39 2024). +24-11-19 20:43:29 | D | Attempting to acquire lock 23437939640272 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:43:29 | D | Lock 23437939640272 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:43:29 | D | open file: /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4/dataset_info.json +24-11-19 20:43:29 | D | Attempting to release lock 23437939640272 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:43:29 | D | Lock 23437939640272 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:43:43 | D | - Quantizing layer model.layers.0 +24-11-19 20:43:43 | D | - Calibrating model.layers.0.self_attn.v_proj.input +24-11-19 20:43:43 | D | - Calibrating model.layers.0.self_attn.k_rotary_emb.output +24-11-19 20:43:43 | D | + w: None +24-11-19 20:43:43 | D | + x: None +24-11-19 20:43:43 | D | + y: sint8 +24-11-19 20:43:43 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:43 | D | + finished parsing calibration arguments, ram usage: 14.1 +24-11-19 20:43:43 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:43:44 | D | - range ratio = [ 1.0000] +24-11-19 20:43:44 | D | sum error = [ 1.1624] +24-11-19 20:43:44 | D | best error = [ 1.1624] +24-11-19 20:43:44 | D | + error = [1.1624] +24-11-19 20:43:44 | D | - Calibrating model.layers.0.self_attn.v_proj.output +24-11-19 20:43:44 | D | + w: None +24-11-19 20:43:44 | D | + x: None +24-11-19 20:43:44 | D | + y: sint8 +24-11-19 20:43:44 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:44 | D | + finished parsing calibration arguments, ram usage: 14.1 +24-11-19 20:43:45 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:43:45 | D | - range ratio = [ 1.0000] +24-11-19 20:43:45 | D | sum error = [ 2.0073] +24-11-19 20:43:45 | D | best error = [ 2.0073] +24-11-19 20:43:45 | D | + error = [2.0073] +24-11-19 20:43:45 | D | - Calibrating model.layers.0.self_attn.o_proj.input +24-11-19 20:43:45 | D | - Calibrating model.layers.0.mlp.up_proj.input +24-11-19 20:43:45 | D | - Calibrating model.layers.0.mlp.down_proj.input +24-11-19 20:43:45 | D | - Quantizing model.layers.0.self_attn.q_proj (inputs) +24-11-19 20:43:45 | D | - Quantizing model.layers.0.self_attn.k_proj (inputs) +24-11-19 20:43:45 | D | - Quantizing model.layers.0.self_attn.v_proj (inputs and outputs) +24-11-19 20:43:45 | D | - Quantizing model.layers.0.self_attn.o_proj (inputs) +24-11-19 20:43:45 | D | - Quantizing model.layers.0.self_attn.k_rotary_emb (outputs) +24-11-19 20:43:45 | D | - Quantizing model.layers.0.mlp.gate_proj (inputs) +24-11-19 20:43:45 | D | - Quantizing model.layers.0.mlp.up_proj (inputs) +24-11-19 20:43:45 | D | - Quantizing model.layers.0.mlp.down_proj (inputs) +24-11-19 20:43:53 | D | - Quantizing layer model.layers.1 +24-11-19 20:43:53 | D | - Calibrating model.layers.1.self_attn.v_proj.input +24-11-19 20:43:53 | D | - Calibrating model.layers.1.self_attn.k_rotary_emb.output +24-11-19 20:43:53 | D | + w: None +24-11-19 20:43:53 | D | + x: None +24-11-19 20:43:53 | D | + y: sint8 +24-11-19 20:43:53 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:53 | D | + finished parsing calibration arguments, ram usage: 14.1 +24-11-19 20:43:53 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:43:54 | D | - range ratio = [ 1.0000] +24-11-19 20:43:54 | D | sum error = [ 5.7322] +24-11-19 20:43:54 | D | best error = [ 5.7322] +24-11-19 20:43:54 | D | + error = [5.7322] +24-11-19 20:43:54 | D | - Calibrating model.layers.1.self_attn.v_proj.output +24-11-19 20:43:54 | D | + w: None +24-11-19 20:43:54 | D | + x: None +24-11-19 20:43:54 | D | + y: sint8 +24-11-19 20:43:54 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:54 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:43:55 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:43:55 | D | - range ratio = [ 1.0000] +24-11-19 20:43:55 | D | sum error = [ 6.5769] +24-11-19 20:43:55 | D | best error = [ 6.5769] +24-11-19 20:43:55 | D | + error = [6.5769] +24-11-19 20:43:55 | D | - Calibrating model.layers.1.self_attn.o_proj.input +24-11-19 20:43:55 | D | - Calibrating model.layers.1.mlp.up_proj.input +24-11-19 20:43:55 | D | - Calibrating model.layers.1.mlp.down_proj.input +24-11-19 20:43:55 | D | - Quantizing model.layers.1.self_attn.q_proj (inputs) +24-11-19 20:43:55 | D | - Quantizing model.layers.1.self_attn.k_proj (inputs) +24-11-19 20:43:55 | D | - Quantizing model.layers.1.self_attn.v_proj (inputs and outputs) +24-11-19 20:43:55 | D | - Quantizing model.layers.1.self_attn.o_proj (inputs) +24-11-19 20:43:55 | D | - Quantizing model.layers.1.self_attn.k_rotary_emb (outputs) +24-11-19 20:43:55 | D | - Quantizing model.layers.1.mlp.gate_proj (inputs) +24-11-19 20:43:55 | D | - Quantizing model.layers.1.mlp.up_proj (inputs) +24-11-19 20:43:55 | D | - Quantizing model.layers.1.mlp.down_proj (inputs) +24-11-19 20:44:02 | D | - Quantizing layer model.layers.2 +24-11-19 20:44:02 | D | - Calibrating model.layers.2.self_attn.v_proj.input +24-11-19 20:44:03 | D | - Calibrating model.layers.2.self_attn.k_rotary_emb.output +24-11-19 20:44:03 | D | + w: None +24-11-19 20:44:03 | D | + x: None +24-11-19 20:44:03 | D | + y: sint8 +24-11-19 20:44:03 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:03 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:44:03 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:44:04 | D | - range ratio = [ 1.0000] +24-11-19 20:44:04 | D | sum error = [ 19.7251] +24-11-19 20:44:04 | D | best error = [ 19.7251] +24-11-19 20:44:04 | D | + error = [19.7251] +24-11-19 20:44:04 | D | - Calibrating model.layers.2.self_attn.v_proj.output +24-11-19 20:44:04 | D | + w: None +24-11-19 20:44:04 | D | + x: None +24-11-19 20:44:04 | D | + y: sint8 +24-11-19 20:44:04 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:04 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:44:05 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:44:05 | D | - range ratio = [ 1.0000] +24-11-19 20:44:05 | D | sum error = [ 54.5305] +24-11-19 20:44:05 | D | best error = [ 54.5305] +24-11-19 20:44:05 | D | + error = [54.5305] +24-11-19 20:44:05 | D | - Calibrating model.layers.2.self_attn.o_proj.input +24-11-19 20:44:05 | D | - Calibrating model.layers.2.mlp.up_proj.input +24-11-19 20:44:05 | D | - Calibrating model.layers.2.mlp.down_proj.input +24-11-19 20:44:06 | D | - Quantizing model.layers.2.self_attn.q_proj (inputs) +24-11-19 20:44:06 | D | - Quantizing model.layers.2.self_attn.k_proj (inputs) +24-11-19 20:44:06 | D | - Quantizing model.layers.2.self_attn.v_proj (inputs and outputs) +24-11-19 20:44:06 | D | - Quantizing model.layers.2.self_attn.o_proj (inputs) +24-11-19 20:44:06 | D | - Quantizing model.layers.2.self_attn.k_rotary_emb (outputs) +24-11-19 20:44:06 | D | - Quantizing model.layers.2.mlp.gate_proj (inputs) +24-11-19 20:44:06 | D | - Quantizing model.layers.2.mlp.up_proj (inputs) +24-11-19 20:44:06 | D | - Quantizing model.layers.2.mlp.down_proj (inputs) +24-11-19 20:44:12 | D | - Quantizing layer model.layers.3 +24-11-19 20:44:12 | D | - Calibrating model.layers.3.self_attn.v_proj.input +24-11-19 20:44:13 | D | - Calibrating model.layers.3.self_attn.k_rotary_emb.output +24-11-19 20:44:13 | D | + w: None +24-11-19 20:44:13 | D | + x: None +24-11-19 20:44:13 | D | + y: sint8 +24-11-19 20:44:13 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:13 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:44:13 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:44:14 | D | - range ratio = [ 1.0000] +24-11-19 20:44:14 | D | sum error = [ 22.8888] +24-11-19 20:44:14 | D | best error = [ 22.8888] +24-11-19 20:44:14 | D | + error = [22.8888] +24-11-19 20:44:14 | D | - Calibrating model.layers.3.self_attn.v_proj.output +24-11-19 20:44:14 | D | + w: None +24-11-19 20:44:14 | D | + x: None +24-11-19 20:44:14 | D | + y: sint8 +24-11-19 20:44:14 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:14 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:44:14 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:44:15 | D | - range ratio = [ 1.0000] +24-11-19 20:44:15 | D | sum error = [ 78.5281] +24-11-19 20:44:15 | D | best error = [ 78.5281] +24-11-19 20:44:15 | D | + error = [78.5281] +24-11-19 20:44:15 | D | - Calibrating model.layers.3.self_attn.o_proj.input +24-11-19 20:44:15 | D | - Calibrating model.layers.3.mlp.up_proj.input +24-11-19 20:44:15 | D | - Calibrating model.layers.3.mlp.down_proj.input +24-11-19 20:44:15 | D | - Quantizing model.layers.3.self_attn.q_proj (inputs) +24-11-19 20:44:15 | D | - Quantizing model.layers.3.self_attn.k_proj (inputs) +24-11-19 20:44:15 | D | - Quantizing model.layers.3.self_attn.v_proj (inputs and outputs) +24-11-19 20:44:15 | D | - Quantizing model.layers.3.self_attn.o_proj (inputs) +24-11-19 20:44:15 | D | - Quantizing model.layers.3.self_attn.k_rotary_emb (outputs) +24-11-19 20:44:15 | D | - Quantizing model.layers.3.mlp.gate_proj (inputs) +24-11-19 20:44:15 | D | - Quantizing model.layers.3.mlp.up_proj (inputs) +24-11-19 20:44:15 | D | - Quantizing model.layers.3.mlp.down_proj (inputs) +24-11-19 20:44:23 | D | - Quantizing layer model.layers.4 +24-11-19 20:44:23 | D | - Calibrating model.layers.4.self_attn.v_proj.input +24-11-19 20:44:23 | D | - Calibrating model.layers.4.self_attn.k_rotary_emb.output +24-11-19 20:44:23 | D | + w: None +24-11-19 20:44:23 | D | + x: None +24-11-19 20:44:23 | D | + y: sint8 +24-11-19 20:44:23 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:23 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:44:24 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:44:24 | D | - range ratio = [ 1.0000] +24-11-19 20:44:24 | D | sum error = [ 33.3361] +24-11-19 20:44:24 | D | best error = [ 33.3361] +24-11-19 20:44:24 | D | + error = [33.3361] +24-11-19 20:44:24 | D | - Calibrating model.layers.4.self_attn.v_proj.output +24-11-19 20:44:24 | D | + w: None +24-11-19 20:44:24 | D | + x: None +24-11-19 20:44:24 | D | + y: sint8 +24-11-19 20:44:24 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:24 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:44:25 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:44:25 | D | - range ratio = [ 1.0000] +24-11-19 20:44:25 | D | sum error = [ 120.1565] +24-11-19 20:44:25 | D | best error = [ 120.1565] +24-11-19 20:44:25 | D | + error = [120.1565] +24-11-19 20:44:25 | D | - Calibrating model.layers.4.self_attn.o_proj.input +24-11-19 20:44:25 | D | - Calibrating model.layers.4.mlp.up_proj.input +24-11-19 20:44:25 | D | - Calibrating model.layers.4.mlp.down_proj.input +24-11-19 20:44:25 | D | - Quantizing model.layers.4.self_attn.q_proj (inputs) +24-11-19 20:44:25 | D | - Quantizing model.layers.4.self_attn.k_proj (inputs) +24-11-19 20:44:25 | D | - Quantizing model.layers.4.self_attn.v_proj (inputs and outputs) +24-11-19 20:44:25 | D | - Quantizing model.layers.4.self_attn.o_proj (inputs) +24-11-19 20:44:25 | D | - Quantizing model.layers.4.self_attn.k_rotary_emb (outputs) +24-11-19 20:44:25 | D | - Quantizing model.layers.4.mlp.gate_proj (inputs) +24-11-19 20:44:25 | D | - Quantizing model.layers.4.mlp.up_proj (inputs) +24-11-19 20:44:25 | D | - Quantizing model.layers.4.mlp.down_proj (inputs) +24-11-19 20:44:33 | D | - Quantizing layer model.layers.5 +24-11-19 20:44:33 | D | - Calibrating model.layers.5.self_attn.v_proj.input +24-11-19 20:44:33 | D | - Calibrating model.layers.5.self_attn.k_rotary_emb.output +24-11-19 20:44:33 | D | + w: None +24-11-19 20:44:33 | D | + x: None +24-11-19 20:44:33 | D | + y: sint8 +24-11-19 20:44:33 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:33 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:44:33 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:44:34 | D | - range ratio = [ 1.0000] +24-11-19 20:44:34 | D | sum error = [ 36.5805] +24-11-19 20:44:34 | D | best error = [ 36.5805] +24-11-19 20:44:34 | D | + error = [36.5805] +24-11-19 20:44:34 | D | - Calibrating model.layers.5.self_attn.v_proj.output +24-11-19 20:44:34 | D | + w: None +24-11-19 20:44:34 | D | + x: None +24-11-19 20:44:34 | D | + y: sint8 +24-11-19 20:44:34 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:34 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:44:34 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:44:35 | D | - range ratio = [ 1.0000] +24-11-19 20:44:35 | D | sum error = [ 95.4317] +24-11-19 20:44:35 | D | best error = [ 95.4317] +24-11-19 20:44:35 | D | + error = [95.4317] +24-11-19 20:44:35 | D | - Calibrating model.layers.5.self_attn.o_proj.input +24-11-19 20:44:35 | D | - Calibrating model.layers.5.mlp.up_proj.input +24-11-19 20:44:35 | D | - Calibrating model.layers.5.mlp.down_proj.input +24-11-19 20:44:35 | D | - Quantizing model.layers.5.self_attn.q_proj (inputs) +24-11-19 20:44:35 | D | - Quantizing model.layers.5.self_attn.k_proj (inputs) +24-11-19 20:44:35 | D | - Quantizing model.layers.5.self_attn.v_proj (inputs and outputs) +24-11-19 20:44:35 | D | - Quantizing model.layers.5.self_attn.o_proj (inputs) +24-11-19 20:44:35 | D | - Quantizing model.layers.5.self_attn.k_rotary_emb (outputs) +24-11-19 20:44:35 | D | - Quantizing model.layers.5.mlp.gate_proj (inputs) +24-11-19 20:44:35 | D | - Quantizing model.layers.5.mlp.up_proj (inputs) +24-11-19 20:44:35 | D | - Quantizing model.layers.5.mlp.down_proj (inputs) +24-11-19 20:44:42 | D | - Quantizing layer model.layers.6 +24-11-19 20:44:42 | D | - Calibrating model.layers.6.self_attn.v_proj.input +24-11-19 20:44:42 | D | - Calibrating model.layers.6.self_attn.k_rotary_emb.output +24-11-19 20:44:42 | D | + w: None +24-11-19 20:44:42 | D | + x: None +24-11-19 20:44:42 | D | + y: sint8 +24-11-19 20:44:42 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:42 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:44:43 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:44:43 | D | - range ratio = [ 1.0000] +24-11-19 20:44:43 | D | sum error = [ 41.0774] +24-11-19 20:44:43 | D | best error = [ 41.0774] +24-11-19 20:44:43 | D | + error = [41.0774] +24-11-19 20:44:43 | D | - Calibrating model.layers.6.self_attn.v_proj.output +24-11-19 20:44:43 | D | + w: None +24-11-19 20:44:43 | D | + x: None +24-11-19 20:44:43 | D | + y: sint8 +24-11-19 20:44:43 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:43 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:44:44 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:44:44 | D | - range ratio = [ 1.0000] +24-11-19 20:44:44 | D | sum error = [ 80.6056] +24-11-19 20:44:44 | D | best error = [ 80.6056] +24-11-19 20:44:44 | D | + error = [80.6056] +24-11-19 20:44:44 | D | - Calibrating model.layers.6.self_attn.o_proj.input +24-11-19 20:44:45 | D | - Calibrating model.layers.6.mlp.up_proj.input +24-11-19 20:44:45 | D | - Calibrating model.layers.6.mlp.down_proj.input +24-11-19 20:44:45 | D | - Quantizing model.layers.6.self_attn.q_proj (inputs) +24-11-19 20:44:45 | D | - Quantizing model.layers.6.self_attn.k_proj (inputs) +24-11-19 20:44:45 | D | - Quantizing model.layers.6.self_attn.v_proj (inputs and outputs) +24-11-19 20:44:45 | D | - Quantizing model.layers.6.self_attn.o_proj (inputs) +24-11-19 20:44:45 | D | - Quantizing model.layers.6.self_attn.k_rotary_emb (outputs) +24-11-19 20:44:45 | D | - Quantizing model.layers.6.mlp.gate_proj (inputs) +24-11-19 20:44:45 | D | - Quantizing model.layers.6.mlp.up_proj (inputs) +24-11-19 20:44:45 | D | - Quantizing model.layers.6.mlp.down_proj (inputs) +24-11-19 20:44:51 | D | - Quantizing layer model.layers.7 +24-11-19 20:44:51 | D | - Calibrating model.layers.7.self_attn.v_proj.input +24-11-19 20:44:51 | D | - Calibrating model.layers.7.self_attn.k_rotary_emb.output +24-11-19 20:44:51 | D | + w: None +24-11-19 20:44:51 | D | + x: None +24-11-19 20:44:51 | D | + y: sint8 +24-11-19 20:44:51 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:51 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:44:52 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:44:52 | D | - range ratio = [ 1.0000] +24-11-19 20:44:52 | D | sum error = [ 45.7415] +24-11-19 20:44:52 | D | best error = [ 45.7415] +24-11-19 20:44:52 | D | + error = [45.7415] +24-11-19 20:44:52 | D | - Calibrating model.layers.7.self_attn.v_proj.output +24-11-19 20:44:52 | D | + w: None +24-11-19 20:44:52 | D | + x: None +24-11-19 20:44:52 | D | + y: sint8 +24-11-19 20:44:52 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:52 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:44:53 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:44:53 | D | - range ratio = [ 1.0000] +24-11-19 20:44:53 | D | sum error = [ 89.4377] +24-11-19 20:44:53 | D | best error = [ 89.4377] +24-11-19 20:44:53 | D | + error = [89.4377] +24-11-19 20:44:53 | D | - Calibrating model.layers.7.self_attn.o_proj.input +24-11-19 20:44:54 | D | - Calibrating model.layers.7.mlp.up_proj.input +24-11-19 20:44:54 | D | - Calibrating model.layers.7.mlp.down_proj.input +24-11-19 20:44:54 | D | - Quantizing model.layers.7.self_attn.q_proj (inputs) +24-11-19 20:44:54 | D | - Quantizing model.layers.7.self_attn.k_proj (inputs) +24-11-19 20:44:54 | D | - Quantizing model.layers.7.self_attn.v_proj (inputs and outputs) +24-11-19 20:44:54 | D | - Quantizing model.layers.7.self_attn.o_proj (inputs) +24-11-19 20:44:54 | D | - Quantizing model.layers.7.self_attn.k_rotary_emb (outputs) +24-11-19 20:44:54 | D | - Quantizing model.layers.7.mlp.gate_proj (inputs) +24-11-19 20:44:54 | D | - Quantizing model.layers.7.mlp.up_proj (inputs) +24-11-19 20:44:54 | D | - Quantizing model.layers.7.mlp.down_proj (inputs) +24-11-19 20:45:01 | D | - Quantizing layer model.layers.8 +24-11-19 20:45:01 | D | - Calibrating model.layers.8.self_attn.v_proj.input +24-11-19 20:45:01 | D | - Calibrating model.layers.8.self_attn.k_rotary_emb.output +24-11-19 20:45:01 | D | + w: None +24-11-19 20:45:01 | D | + x: None +24-11-19 20:45:01 | D | + y: sint8 +24-11-19 20:45:01 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:01 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:45:01 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:45:02 | D | - range ratio = [ 1.0000] +24-11-19 20:45:02 | D | sum error = [ 55.1264] +24-11-19 20:45:02 | D | best error = [ 55.1264] +24-11-19 20:45:02 | D | + error = [55.1264] +24-11-19 20:45:02 | D | - Calibrating model.layers.8.self_attn.v_proj.output +24-11-19 20:45:02 | D | + w: None +24-11-19 20:45:02 | D | + x: None +24-11-19 20:45:02 | D | + y: sint8 +24-11-19 20:45:02 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:02 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:45:02 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:45:03 | D | - range ratio = [ 1.0000] +24-11-19 20:45:03 | D | sum error = [ 80.1731] +24-11-19 20:45:03 | D | best error = [ 80.1731] +24-11-19 20:45:03 | D | + error = [80.1731] +24-11-19 20:45:03 | D | - Calibrating model.layers.8.self_attn.o_proj.input +24-11-19 20:45:03 | D | - Calibrating model.layers.8.mlp.up_proj.input +24-11-19 20:45:03 | D | - Calibrating model.layers.8.mlp.down_proj.input +24-11-19 20:45:03 | D | - Quantizing model.layers.8.self_attn.q_proj (inputs) +24-11-19 20:45:03 | D | - Quantizing model.layers.8.self_attn.k_proj (inputs) +24-11-19 20:45:03 | D | - Quantizing model.layers.8.self_attn.v_proj (inputs and outputs) +24-11-19 20:45:03 | D | - Quantizing model.layers.8.self_attn.o_proj (inputs) +24-11-19 20:45:03 | D | - Quantizing model.layers.8.self_attn.k_rotary_emb (outputs) +24-11-19 20:45:03 | D | - Quantizing model.layers.8.mlp.gate_proj (inputs) +24-11-19 20:45:03 | D | - Quantizing model.layers.8.mlp.up_proj (inputs) +24-11-19 20:45:03 | D | - Quantizing model.layers.8.mlp.down_proj (inputs) +24-11-19 20:45:10 | D | - Quantizing layer model.layers.9 +24-11-19 20:45:10 | D | - Calibrating model.layers.9.self_attn.v_proj.input +24-11-19 20:45:10 | D | - Calibrating model.layers.9.self_attn.k_rotary_emb.output +24-11-19 20:45:10 | D | + w: None +24-11-19 20:45:10 | D | + x: None +24-11-19 20:45:10 | D | + y: sint8 +24-11-19 20:45:10 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:10 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:45:10 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:45:11 | D | - range ratio = [ 1.0000] +24-11-19 20:45:11 | D | sum error = [ 65.0993] +24-11-19 20:45:11 | D | best error = [ 65.0993] +24-11-19 20:45:11 | D | + error = [65.0993] +24-11-19 20:45:11 | D | - Calibrating model.layers.9.self_attn.v_proj.output +24-11-19 20:45:11 | D | + w: None +24-11-19 20:45:11 | D | + x: None +24-11-19 20:45:11 | D | + y: sint8 +24-11-19 20:45:11 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:11 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:45:11 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:45:12 | D | - range ratio = [ 1.0000] +24-11-19 20:45:12 | D | sum error = [ 128.0213] +24-11-19 20:45:12 | D | best error = [ 128.0213] +24-11-19 20:45:12 | D | + error = [128.0213] +24-11-19 20:45:12 | D | - Calibrating model.layers.9.self_attn.o_proj.input +24-11-19 20:45:12 | D | - Calibrating model.layers.9.mlp.up_proj.input +24-11-19 20:45:12 | D | - Calibrating model.layers.9.mlp.down_proj.input +24-11-19 20:45:12 | D | - Quantizing model.layers.9.self_attn.q_proj (inputs) +24-11-19 20:45:12 | D | - Quantizing model.layers.9.self_attn.k_proj (inputs) +24-11-19 20:45:12 | D | - Quantizing model.layers.9.self_attn.v_proj (inputs and outputs) +24-11-19 20:45:12 | D | - Quantizing model.layers.9.self_attn.o_proj (inputs) +24-11-19 20:45:12 | D | - Quantizing model.layers.9.self_attn.k_rotary_emb (outputs) +24-11-19 20:45:12 | D | - Quantizing model.layers.9.mlp.gate_proj (inputs) +24-11-19 20:45:12 | D | - Quantizing model.layers.9.mlp.up_proj (inputs) +24-11-19 20:45:12 | D | - Quantizing model.layers.9.mlp.down_proj (inputs) +24-11-19 20:45:19 | D | - Quantizing layer model.layers.10 +24-11-19 20:45:19 | D | - Calibrating model.layers.10.self_attn.v_proj.input +24-11-19 20:45:19 | D | - Calibrating model.layers.10.self_attn.k_rotary_emb.output +24-11-19 20:45:19 | D | + w: None +24-11-19 20:45:19 | D | + x: None +24-11-19 20:45:19 | D | + y: sint8 +24-11-19 20:45:19 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:19 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:45:20 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:45:20 | D | - range ratio = [ 1.0000] +24-11-19 20:45:20 | D | sum error = [ 68.4544] +24-11-19 20:45:20 | D | best error = [ 68.4544] +24-11-19 20:45:20 | D | + error = [68.4544] +24-11-19 20:45:20 | D | - Calibrating model.layers.10.self_attn.v_proj.output +24-11-19 20:45:20 | D | + w: None +24-11-19 20:45:20 | D | + x: None +24-11-19 20:45:20 | D | + y: sint8 +24-11-19 20:45:20 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:20 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:45:21 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:45:21 | D | - range ratio = [ 1.0000] +24-11-19 20:45:21 | D | sum error = [ 149.3623] +24-11-19 20:45:21 | D | best error = [ 149.3623] +24-11-19 20:45:21 | D | + error = [149.3623] +24-11-19 20:45:22 | D | - Calibrating model.layers.10.self_attn.o_proj.input +24-11-19 20:45:22 | D | - Calibrating model.layers.10.mlp.up_proj.input +24-11-19 20:45:22 | D | - Calibrating model.layers.10.mlp.down_proj.input +24-11-19 20:45:22 | D | - Quantizing model.layers.10.self_attn.q_proj (inputs) +24-11-19 20:45:22 | D | - Quantizing model.layers.10.self_attn.k_proj (inputs) +24-11-19 20:45:22 | D | - Quantizing model.layers.10.self_attn.v_proj (inputs and outputs) +24-11-19 20:45:22 | D | - Quantizing model.layers.10.self_attn.o_proj (inputs) +24-11-19 20:45:22 | D | - Quantizing model.layers.10.self_attn.k_rotary_emb (outputs) +24-11-19 20:45:22 | D | - Quantizing model.layers.10.mlp.gate_proj (inputs) +24-11-19 20:45:22 | D | - Quantizing model.layers.10.mlp.up_proj (inputs) +24-11-19 20:45:22 | D | - Quantizing model.layers.10.mlp.down_proj (inputs) +24-11-19 20:45:29 | D | - Quantizing layer model.layers.11 +24-11-19 20:45:29 | D | - Calibrating model.layers.11.self_attn.v_proj.input +24-11-19 20:45:29 | D | - Calibrating model.layers.11.self_attn.k_rotary_emb.output +24-11-19 20:45:29 | D | + w: None +24-11-19 20:45:29 | D | + x: None +24-11-19 20:45:29 | D | + y: sint8 +24-11-19 20:45:29 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:29 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:45:29 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:45:30 | D | - range ratio = [ 1.0000] +24-11-19 20:45:30 | D | sum error = [ 62.5850] +24-11-19 20:45:30 | D | best error = [ 62.5850] +24-11-19 20:45:30 | D | + error = [62.5850] +24-11-19 20:45:30 | D | - Calibrating model.layers.11.self_attn.v_proj.output +24-11-19 20:45:30 | D | + w: None +24-11-19 20:45:30 | D | + x: None +24-11-19 20:45:30 | D | + y: sint8 +24-11-19 20:45:30 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:30 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:45:31 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:45:31 | D | - range ratio = [ 1.0000] +24-11-19 20:45:31 | D | sum error = [ 168.2423] +24-11-19 20:45:31 | D | best error = [ 168.2423] +24-11-19 20:45:31 | D | + error = [168.2423] +24-11-19 20:45:31 | D | - Calibrating model.layers.11.self_attn.o_proj.input +24-11-19 20:45:31 | D | - Calibrating model.layers.11.mlp.up_proj.input +24-11-19 20:45:31 | D | - Calibrating model.layers.11.mlp.down_proj.input +24-11-19 20:45:31 | D | - Quantizing model.layers.11.self_attn.q_proj (inputs) +24-11-19 20:45:31 | D | - Quantizing model.layers.11.self_attn.k_proj (inputs) +24-11-19 20:45:31 | D | - Quantizing model.layers.11.self_attn.v_proj (inputs and outputs) +24-11-19 20:45:31 | D | - Quantizing model.layers.11.self_attn.o_proj (inputs) +24-11-19 20:45:31 | D | - Quantizing model.layers.11.self_attn.k_rotary_emb (outputs) +24-11-19 20:45:31 | D | - Quantizing model.layers.11.mlp.gate_proj (inputs) +24-11-19 20:45:31 | D | - Quantizing model.layers.11.mlp.up_proj (inputs) +24-11-19 20:45:31 | D | - Quantizing model.layers.11.mlp.down_proj (inputs) +24-11-19 20:45:39 | D | - Quantizing layer model.layers.12 +24-11-19 20:45:39 | D | - Calibrating model.layers.12.self_attn.v_proj.input +24-11-19 20:45:39 | D | - Calibrating model.layers.12.self_attn.k_rotary_emb.output +24-11-19 20:45:39 | D | + w: None +24-11-19 20:45:39 | D | + x: None +24-11-19 20:45:39 | D | + y: sint8 +24-11-19 20:45:39 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:39 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:45:39 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:45:40 | D | - range ratio = [ 1.0000] +24-11-19 20:45:40 | D | sum error = [ 72.9855] +24-11-19 20:45:40 | D | best error = [ 72.9855] +24-11-19 20:45:40 | D | + error = [72.9855] +24-11-19 20:45:40 | D | - Calibrating model.layers.12.self_attn.v_proj.output +24-11-19 20:45:40 | D | + w: None +24-11-19 20:45:40 | D | + x: None +24-11-19 20:45:40 | D | + y: sint8 +24-11-19 20:45:40 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:40 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:45:40 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:45:41 | D | - range ratio = [ 1.0000] +24-11-19 20:45:41 | D | sum error = [ 153.0065] +24-11-19 20:45:41 | D | best error = [ 153.0065] +24-11-19 20:45:41 | D | + error = [153.0065] +24-11-19 20:45:41 | D | - Calibrating model.layers.12.self_attn.o_proj.input +24-11-19 20:45:41 | D | - Calibrating model.layers.12.mlp.up_proj.input +24-11-19 20:45:41 | D | - Calibrating model.layers.12.mlp.down_proj.input +24-11-19 20:45:41 | D | - Quantizing model.layers.12.self_attn.q_proj (inputs) +24-11-19 20:45:41 | D | - Quantizing model.layers.12.self_attn.k_proj (inputs) +24-11-19 20:45:41 | D | - Quantizing model.layers.12.self_attn.v_proj (inputs and outputs) +24-11-19 20:45:41 | D | - Quantizing model.layers.12.self_attn.o_proj (inputs) +24-11-19 20:45:41 | D | - Quantizing model.layers.12.self_attn.k_rotary_emb (outputs) +24-11-19 20:45:41 | D | - Quantizing model.layers.12.mlp.gate_proj (inputs) +24-11-19 20:45:41 | D | - Quantizing model.layers.12.mlp.up_proj (inputs) +24-11-19 20:45:41 | D | - Quantizing model.layers.12.mlp.down_proj (inputs) +24-11-19 20:45:48 | D | - Quantizing layer model.layers.13 +24-11-19 20:45:48 | D | - Calibrating model.layers.13.self_attn.v_proj.input +24-11-19 20:45:48 | D | - Calibrating model.layers.13.self_attn.k_rotary_emb.output +24-11-19 20:45:48 | D | + w: None +24-11-19 20:45:48 | D | + x: None +24-11-19 20:45:48 | D | + y: sint8 +24-11-19 20:45:48 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:48 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:45:48 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:45:49 | D | - range ratio = [ 1.0000] +24-11-19 20:45:49 | D | sum error = [ 73.5571] +24-11-19 20:45:49 | D | best error = [ 73.5571] +24-11-19 20:45:49 | D | + error = [73.5571] +24-11-19 20:45:49 | D | - Calibrating model.layers.13.self_attn.v_proj.output +24-11-19 20:45:49 | D | + w: None +24-11-19 20:45:49 | D | + x: None +24-11-19 20:45:49 | D | + y: sint8 +24-11-19 20:45:49 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:49 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:45:50 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:45:50 | D | - range ratio = [ 1.0000] +24-11-19 20:45:50 | D | sum error = [ 120.7414] +24-11-19 20:45:50 | D | best error = [ 120.7414] +24-11-19 20:45:50 | D | + error = [120.7414] +24-11-19 20:45:50 | D | - Calibrating model.layers.13.self_attn.o_proj.input +24-11-19 20:45:50 | D | - Calibrating model.layers.13.mlp.up_proj.input +24-11-19 20:45:50 | D | - Calibrating model.layers.13.mlp.down_proj.input +24-11-19 20:45:51 | D | - Quantizing model.layers.13.self_attn.q_proj (inputs) +24-11-19 20:45:51 | D | - Quantizing model.layers.13.self_attn.k_proj (inputs) +24-11-19 20:45:51 | D | - Quantizing model.layers.13.self_attn.v_proj (inputs and outputs) +24-11-19 20:45:51 | D | - Quantizing model.layers.13.self_attn.o_proj (inputs) +24-11-19 20:45:51 | D | - Quantizing model.layers.13.self_attn.k_rotary_emb (outputs) +24-11-19 20:45:51 | D | - Quantizing model.layers.13.mlp.gate_proj (inputs) +24-11-19 20:45:51 | D | - Quantizing model.layers.13.mlp.up_proj (inputs) +24-11-19 20:45:51 | D | - Quantizing model.layers.13.mlp.down_proj (inputs) +24-11-19 20:45:57 | D | - Quantizing layer model.layers.14 +24-11-19 20:45:57 | D | - Calibrating model.layers.14.self_attn.v_proj.input +24-11-19 20:45:57 | D | - Calibrating model.layers.14.self_attn.k_rotary_emb.output +24-11-19 20:45:57 | D | + w: None +24-11-19 20:45:57 | D | + x: None +24-11-19 20:45:57 | D | + y: sint8 +24-11-19 20:45:57 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:57 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:45:58 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:45:58 | D | - range ratio = [ 1.0000] +24-11-19 20:45:58 | D | sum error = [ 75.6866] +24-11-19 20:45:58 | D | best error = [ 75.6866] +24-11-19 20:45:58 | D | + error = [75.6866] +24-11-19 20:45:59 | D | - Calibrating model.layers.14.self_attn.v_proj.output +24-11-19 20:45:59 | D | + w: None +24-11-19 20:45:59 | D | + x: None +24-11-19 20:45:59 | D | + y: sint8 +24-11-19 20:45:59 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:59 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:45:59 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:46:00 | D | - range ratio = [ 1.0000] +24-11-19 20:46:00 | D | sum error = [ 120.0770] +24-11-19 20:46:00 | D | best error = [ 120.0770] +24-11-19 20:46:00 | D | + error = [120.0770] +24-11-19 20:46:00 | D | - Calibrating model.layers.14.self_attn.o_proj.input +24-11-19 20:46:00 | D | - Calibrating model.layers.14.mlp.up_proj.input +24-11-19 20:46:00 | D | - Calibrating model.layers.14.mlp.down_proj.input +24-11-19 20:46:00 | D | - Quantizing model.layers.14.self_attn.q_proj (inputs) +24-11-19 20:46:00 | D | - Quantizing model.layers.14.self_attn.k_proj (inputs) +24-11-19 20:46:00 | D | - Quantizing model.layers.14.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:00 | D | - Quantizing model.layers.14.self_attn.o_proj (inputs) +24-11-19 20:46:00 | D | - Quantizing model.layers.14.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:00 | D | - Quantizing model.layers.14.mlp.gate_proj (inputs) +24-11-19 20:46:00 | D | - Quantizing model.layers.14.mlp.up_proj (inputs) +24-11-19 20:46:00 | D | - Quantizing model.layers.14.mlp.down_proj (inputs) +24-11-19 20:46:07 | D | - Quantizing layer model.layers.15 +24-11-19 20:46:07 | D | - Calibrating model.layers.15.self_attn.v_proj.input +24-11-19 20:46:07 | D | - Calibrating model.layers.15.self_attn.k_rotary_emb.output +24-11-19 20:46:07 | D | + w: None +24-11-19 20:46:07 | D | + x: None +24-11-19 20:46:07 | D | + y: sint8 +24-11-19 20:46:07 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:07 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:46:08 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:46:08 | D | - range ratio = [ 1.0000] +24-11-19 20:46:08 | D | sum error = [ 79.9031] +24-11-19 20:46:08 | D | best error = [ 79.9031] +24-11-19 20:46:08 | D | + error = [79.9031] +24-11-19 20:46:08 | D | - Calibrating model.layers.15.self_attn.v_proj.output +24-11-19 20:46:08 | D | + w: None +24-11-19 20:46:08 | D | + x: None +24-11-19 20:46:08 | D | + y: sint8 +24-11-19 20:46:08 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:08 | D | + finished parsing calibration arguments, ram usage: 13.1 +24-11-19 20:46:09 | D | + finished reseting calibrator, ram usage: 13.1 +24-11-19 20:46:09 | D | - range ratio = [ 1.0000] +24-11-19 20:46:09 | D | sum error = [ 126.2782] +24-11-19 20:46:09 | D | best error = [ 126.2782] +24-11-19 20:46:09 | D | + error = [126.2782] +24-11-19 20:46:09 | D | - Calibrating model.layers.15.self_attn.o_proj.input +24-11-19 20:46:09 | D | - Calibrating model.layers.15.mlp.up_proj.input +24-11-19 20:46:10 | D | - Calibrating model.layers.15.mlp.down_proj.input +24-11-19 20:46:10 | D | - Quantizing model.layers.15.self_attn.q_proj (inputs) +24-11-19 20:46:10 | D | - Quantizing model.layers.15.self_attn.k_proj (inputs) +24-11-19 20:46:10 | D | - Quantizing model.layers.15.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:10 | D | - Quantizing model.layers.15.self_attn.o_proj (inputs) +24-11-19 20:46:10 | D | - Quantizing model.layers.15.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:10 | D | - Quantizing model.layers.15.mlp.gate_proj (inputs) +24-11-19 20:46:10 | D | - Quantizing model.layers.15.mlp.up_proj (inputs) +24-11-19 20:46:10 | D | - Quantizing model.layers.15.mlp.down_proj (inputs) +24-11-19 20:46:16 | D | - Quantizing layer model.layers.16 +24-11-19 20:46:16 | D | - Calibrating model.layers.16.self_attn.v_proj.input +24-11-19 20:46:16 | D | - Calibrating model.layers.16.self_attn.k_rotary_emb.output +24-11-19 20:46:16 | D | + w: None +24-11-19 20:46:16 | D | + x: None +24-11-19 20:46:16 | D | + y: sint8 +24-11-19 20:46:16 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:16 | D | + finished parsing calibration arguments, ram usage: 13.0 +24-11-19 20:46:17 | D | + finished reseting calibrator, ram usage: 13.1 +24-11-19 20:46:17 | D | - range ratio = [ 1.0000] +24-11-19 20:46:17 | D | sum error = [ 88.4118] +24-11-19 20:46:17 | D | best error = [ 88.4118] +24-11-19 20:46:17 | D | + error = [88.4118] +24-11-19 20:46:17 | D | - Calibrating model.layers.16.self_attn.v_proj.output +24-11-19 20:46:17 | D | + w: None +24-11-19 20:46:17 | D | + x: None +24-11-19 20:46:17 | D | + y: sint8 +24-11-19 20:46:17 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:17 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:46:18 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:46:19 | D | - range ratio = [ 1.0000] +24-11-19 20:46:19 | D | sum error = [ 130.8961] +24-11-19 20:46:19 | D | best error = [ 130.8961] +24-11-19 20:46:19 | D | + error = [130.8961] +24-11-19 20:46:19 | D | - Calibrating model.layers.16.self_attn.o_proj.input +24-11-19 20:46:19 | D | - Calibrating model.layers.16.mlp.up_proj.input +24-11-19 20:46:19 | D | - Calibrating model.layers.16.mlp.down_proj.input +24-11-19 20:46:19 | D | - Quantizing model.layers.16.self_attn.q_proj (inputs) +24-11-19 20:46:19 | D | - Quantizing model.layers.16.self_attn.k_proj (inputs) +24-11-19 20:46:19 | D | - Quantizing model.layers.16.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:19 | D | - Quantizing model.layers.16.self_attn.o_proj (inputs) +24-11-19 20:46:19 | D | - Quantizing model.layers.16.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:19 | D | - Quantizing model.layers.16.mlp.gate_proj (inputs) +24-11-19 20:46:19 | D | - Quantizing model.layers.16.mlp.up_proj (inputs) +24-11-19 20:46:19 | D | - Quantizing model.layers.16.mlp.down_proj (inputs) +24-11-19 20:46:26 | D | - Quantizing layer model.layers.17 +24-11-19 20:46:26 | D | - Calibrating model.layers.17.self_attn.v_proj.input +24-11-19 20:46:26 | D | - Calibrating model.layers.17.self_attn.k_rotary_emb.output +24-11-19 20:46:26 | D | + w: None +24-11-19 20:46:26 | D | + x: None +24-11-19 20:46:26 | D | + y: sint8 +24-11-19 20:46:26 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:26 | D | + finished parsing calibration arguments, ram usage: 13.1 +24-11-19 20:46:27 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:46:27 | D | - range ratio = [ 1.0000] +24-11-19 20:46:27 | D | sum error = [ 90.9454] +24-11-19 20:46:27 | D | best error = [ 90.9454] +24-11-19 20:46:27 | D | + error = [90.9454] +24-11-19 20:46:27 | D | - Calibrating model.layers.17.self_attn.v_proj.output +24-11-19 20:46:27 | D | + w: None +24-11-19 20:46:27 | D | + x: None +24-11-19 20:46:27 | D | + y: sint8 +24-11-19 20:46:27 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:27 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:46:28 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:46:28 | D | - range ratio = [ 1.0000] +24-11-19 20:46:28 | D | sum error = [ 148.1910] +24-11-19 20:46:28 | D | best error = [ 148.1910] +24-11-19 20:46:28 | D | + error = [148.1910] +24-11-19 20:46:28 | D | - Calibrating model.layers.17.self_attn.o_proj.input +24-11-19 20:46:28 | D | - Calibrating model.layers.17.mlp.up_proj.input +24-11-19 20:46:28 | D | - Calibrating model.layers.17.mlp.down_proj.input +24-11-19 20:46:28 | D | - Quantizing model.layers.17.self_attn.q_proj (inputs) +24-11-19 20:46:28 | D | - Quantizing model.layers.17.self_attn.k_proj (inputs) +24-11-19 20:46:28 | D | - Quantizing model.layers.17.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:28 | D | - Quantizing model.layers.17.self_attn.o_proj (inputs) +24-11-19 20:46:28 | D | - Quantizing model.layers.17.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:28 | D | - Quantizing model.layers.17.mlp.gate_proj (inputs) +24-11-19 20:46:28 | D | - Quantizing model.layers.17.mlp.up_proj (inputs) +24-11-19 20:46:28 | D | - Quantizing model.layers.17.mlp.down_proj (inputs) +24-11-19 20:46:35 | D | - Quantizing layer model.layers.18 +24-11-19 20:46:35 | D | - Calibrating model.layers.18.self_attn.v_proj.input +24-11-19 20:46:35 | D | - Calibrating model.layers.18.self_attn.k_rotary_emb.output +24-11-19 20:46:35 | D | + w: None +24-11-19 20:46:35 | D | + x: None +24-11-19 20:46:35 | D | + y: sint8 +24-11-19 20:46:35 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:35 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:46:36 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:46:36 | D | - range ratio = [ 1.0000] +24-11-19 20:46:36 | D | sum error = [ 95.1550] +24-11-19 20:46:36 | D | best error = [ 95.1550] +24-11-19 20:46:36 | D | + error = [95.1550] +24-11-19 20:46:37 | D | - Calibrating model.layers.18.self_attn.v_proj.output +24-11-19 20:46:37 | D | + w: None +24-11-19 20:46:37 | D | + x: None +24-11-19 20:46:37 | D | + y: sint8 +24-11-19 20:46:37 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:37 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:46:37 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:46:38 | D | - range ratio = [ 1.0000] +24-11-19 20:46:38 | D | sum error = [ 168.6270] +24-11-19 20:46:38 | D | best error = [ 168.6270] +24-11-19 20:46:38 | D | + error = [168.6270] +24-11-19 20:46:38 | D | - Calibrating model.layers.18.self_attn.o_proj.input +24-11-19 20:46:38 | D | - Calibrating model.layers.18.mlp.up_proj.input +24-11-19 20:46:38 | D | - Calibrating model.layers.18.mlp.down_proj.input +24-11-19 20:46:38 | D | - Quantizing model.layers.18.self_attn.q_proj (inputs) +24-11-19 20:46:38 | D | - Quantizing model.layers.18.self_attn.k_proj (inputs) +24-11-19 20:46:38 | D | - Quantizing model.layers.18.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:38 | D | - Quantizing model.layers.18.self_attn.o_proj (inputs) +24-11-19 20:46:38 | D | - Quantizing model.layers.18.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:38 | D | - Quantizing model.layers.18.mlp.gate_proj (inputs) +24-11-19 20:46:38 | D | - Quantizing model.layers.18.mlp.up_proj (inputs) +24-11-19 20:46:38 | D | - Quantizing model.layers.18.mlp.down_proj (inputs) +24-11-19 20:46:45 | D | - Quantizing layer model.layers.19 +24-11-19 20:46:45 | D | - Calibrating model.layers.19.self_attn.v_proj.input +24-11-19 20:46:45 | D | - Calibrating model.layers.19.self_attn.k_rotary_emb.output +24-11-19 20:46:45 | D | + w: None +24-11-19 20:46:45 | D | + x: None +24-11-19 20:46:45 | D | + y: sint8 +24-11-19 20:46:45 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:45 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:46:46 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:46:46 | D | - range ratio = [ 1.0000] +24-11-19 20:46:46 | D | sum error = [ 88.7428] +24-11-19 20:46:46 | D | best error = [ 88.7428] +24-11-19 20:46:46 | D | + error = [88.7428] +24-11-19 20:46:46 | D | - Calibrating model.layers.19.self_attn.v_proj.output +24-11-19 20:46:46 | D | + w: None +24-11-19 20:46:46 | D | + x: None +24-11-19 20:46:46 | D | + y: sint8 +24-11-19 20:46:46 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:46 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:46:47 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:46:47 | D | - range ratio = [ 1.0000] +24-11-19 20:46:47 | D | sum error = [ 157.6726] +24-11-19 20:46:47 | D | best error = [ 157.6726] +24-11-19 20:46:47 | D | + error = [157.6726] +24-11-19 20:46:48 | D | - Calibrating model.layers.19.self_attn.o_proj.input +24-11-19 20:46:48 | D | - Calibrating model.layers.19.mlp.up_proj.input +24-11-19 20:46:48 | D | - Calibrating model.layers.19.mlp.down_proj.input +24-11-19 20:46:48 | D | - Quantizing model.layers.19.self_attn.q_proj (inputs) +24-11-19 20:46:48 | D | - Quantizing model.layers.19.self_attn.k_proj (inputs) +24-11-19 20:46:48 | D | - Quantizing model.layers.19.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:48 | D | - Quantizing model.layers.19.self_attn.o_proj (inputs) +24-11-19 20:46:48 | D | - Quantizing model.layers.19.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:48 | D | - Quantizing model.layers.19.mlp.gate_proj (inputs) +24-11-19 20:46:48 | D | - Quantizing model.layers.19.mlp.up_proj (inputs) +24-11-19 20:46:48 | D | - Quantizing model.layers.19.mlp.down_proj (inputs) +24-11-19 20:46:55 | D | - Quantizing layer model.layers.20 +24-11-19 20:46:55 | D | - Calibrating model.layers.20.self_attn.v_proj.input +24-11-19 20:46:55 | D | - Calibrating model.layers.20.self_attn.k_rotary_emb.output +24-11-19 20:46:55 | D | + w: None +24-11-19 20:46:55 | D | + x: None +24-11-19 20:46:55 | D | + y: sint8 +24-11-19 20:46:55 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:55 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:46:56 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:46:56 | D | - range ratio = [ 1.0000] +24-11-19 20:46:56 | D | sum error = [ 88.4419] +24-11-19 20:46:56 | D | best error = [ 88.4419] +24-11-19 20:46:56 | D | + error = [88.4419] +24-11-19 20:46:56 | D | - Calibrating model.layers.20.self_attn.v_proj.output +24-11-19 20:46:56 | D | + w: None +24-11-19 20:46:56 | D | + x: None +24-11-19 20:46:56 | D | + y: sint8 +24-11-19 20:46:56 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:56 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:46:57 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:46:57 | D | - range ratio = [ 1.0000] +24-11-19 20:46:57 | D | sum error = [ 183.3839] +24-11-19 20:46:57 | D | best error = [ 183.3839] +24-11-19 20:46:57 | D | + error = [183.3839] +24-11-19 20:46:57 | D | - Calibrating model.layers.20.self_attn.o_proj.input +24-11-19 20:46:57 | D | - Calibrating model.layers.20.mlp.up_proj.input +24-11-19 20:46:57 | D | - Calibrating model.layers.20.mlp.down_proj.input +24-11-19 20:46:57 | D | - Quantizing model.layers.20.self_attn.q_proj (inputs) +24-11-19 20:46:57 | D | - Quantizing model.layers.20.self_attn.k_proj (inputs) +24-11-19 20:46:57 | D | - Quantizing model.layers.20.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:57 | D | - Quantizing model.layers.20.self_attn.o_proj (inputs) +24-11-19 20:46:57 | D | - Quantizing model.layers.20.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:57 | D | - Quantizing model.layers.20.mlp.gate_proj (inputs) +24-11-19 20:46:57 | D | - Quantizing model.layers.20.mlp.up_proj (inputs) +24-11-19 20:46:57 | D | - Quantizing model.layers.20.mlp.down_proj (inputs) +24-11-19 20:47:04 | D | - Quantizing layer model.layers.21 +24-11-19 20:47:04 | D | - Calibrating model.layers.21.self_attn.v_proj.input +24-11-19 20:47:05 | D | - Calibrating model.layers.21.self_attn.k_rotary_emb.output +24-11-19 20:47:05 | D | + w: None +24-11-19 20:47:05 | D | + x: None +24-11-19 20:47:05 | D | + y: sint8 +24-11-19 20:47:05 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:05 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:47:05 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:47:06 | D | - range ratio = [ 1.0000] +24-11-19 20:47:06 | D | sum error = [ 91.9793] +24-11-19 20:47:06 | D | best error = [ 91.9793] +24-11-19 20:47:06 | D | + error = [91.9793] +24-11-19 20:47:06 | D | - Calibrating model.layers.21.self_attn.v_proj.output +24-11-19 20:47:06 | D | + w: None +24-11-19 20:47:06 | D | + x: None +24-11-19 20:47:06 | D | + y: sint8 +24-11-19 20:47:06 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:06 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:47:06 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:47:07 | D | - range ratio = [ 1.0000] +24-11-19 20:47:07 | D | sum error = [ 200.0000] +24-11-19 20:47:07 | D | best error = [ 200.0000] +24-11-19 20:47:07 | D | + error = [200.0000] +24-11-19 20:47:07 | D | - Calibrating model.layers.21.self_attn.o_proj.input +24-11-19 20:47:07 | D | - Calibrating model.layers.21.mlp.up_proj.input +24-11-19 20:47:07 | D | - Calibrating model.layers.21.mlp.down_proj.input +24-11-19 20:47:07 | D | - Quantizing model.layers.21.self_attn.q_proj (inputs) +24-11-19 20:47:07 | D | - Quantizing model.layers.21.self_attn.k_proj (inputs) +24-11-19 20:47:07 | D | - Quantizing model.layers.21.self_attn.v_proj (inputs and outputs) +24-11-19 20:47:07 | D | - Quantizing model.layers.21.self_attn.o_proj (inputs) +24-11-19 20:47:07 | D | - Quantizing model.layers.21.self_attn.k_rotary_emb (outputs) +24-11-19 20:47:07 | D | - Quantizing model.layers.21.mlp.gate_proj (inputs) +24-11-19 20:47:07 | D | - Quantizing model.layers.21.mlp.up_proj (inputs) +24-11-19 20:47:07 | D | - Quantizing model.layers.21.mlp.down_proj (inputs) +24-11-19 20:47:14 | D | - Quantizing layer model.layers.22 +24-11-19 20:47:14 | D | - Calibrating model.layers.22.self_attn.v_proj.input +24-11-19 20:47:14 | D | - Calibrating model.layers.22.self_attn.k_rotary_emb.output +24-11-19 20:47:14 | D | + w: None +24-11-19 20:47:14 | D | + x: None +24-11-19 20:47:14 | D | + y: sint8 +24-11-19 20:47:14 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:14 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:47:15 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:47:15 | D | - range ratio = [ 1.0000] +24-11-19 20:47:15 | D | sum error = [ 125.4327] +24-11-19 20:47:15 | D | best error = [ 125.4327] +24-11-19 20:47:15 | D | + error = [125.4327] +24-11-19 20:47:15 | D | - Calibrating model.layers.22.self_attn.v_proj.output +24-11-19 20:47:15 | D | + w: None +24-11-19 20:47:15 | D | + x: None +24-11-19 20:47:15 | D | + y: sint8 +24-11-19 20:47:15 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:15 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:47:16 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:47:16 | D | - range ratio = [ 1.0000] +24-11-19 20:47:16 | D | sum error = [ 193.4577] +24-11-19 20:47:16 | D | best error = [ 193.4577] +24-11-19 20:47:16 | D | + error = [193.4577] +24-11-19 20:47:16 | D | - Calibrating model.layers.22.self_attn.o_proj.input +24-11-19 20:47:16 | D | - Calibrating model.layers.22.mlp.up_proj.input +24-11-19 20:47:16 | D | - Calibrating model.layers.22.mlp.down_proj.input +24-11-19 20:47:17 | D | - Quantizing model.layers.22.self_attn.q_proj (inputs) +24-11-19 20:47:17 | D | - Quantizing model.layers.22.self_attn.k_proj (inputs) +24-11-19 20:47:17 | D | - Quantizing model.layers.22.self_attn.v_proj (inputs and outputs) +24-11-19 20:47:17 | D | - Quantizing model.layers.22.self_attn.o_proj (inputs) +24-11-19 20:47:17 | D | - Quantizing model.layers.22.self_attn.k_rotary_emb (outputs) +24-11-19 20:47:17 | D | - Quantizing model.layers.22.mlp.gate_proj (inputs) +24-11-19 20:47:17 | D | - Quantizing model.layers.22.mlp.up_proj (inputs) +24-11-19 20:47:17 | D | - Quantizing model.layers.22.mlp.down_proj (inputs) +24-11-19 20:47:24 | D | - Quantizing layer model.layers.23 +24-11-19 20:47:24 | D | - Calibrating model.layers.23.self_attn.v_proj.input +24-11-19 20:47:24 | D | - Calibrating model.layers.23.self_attn.k_rotary_emb.output +24-11-19 20:47:24 | D | + w: None +24-11-19 20:47:24 | D | + x: None +24-11-19 20:47:24 | D | + y: sint8 +24-11-19 20:47:24 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:24 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:47:25 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:47:25 | D | - range ratio = [ 1.0000] +24-11-19 20:47:25 | D | sum error = [ 109.9908] +24-11-19 20:47:25 | D | best error = [ 109.9908] +24-11-19 20:47:25 | D | + error = [109.9908] +24-11-19 20:47:25 | D | - Calibrating model.layers.23.self_attn.v_proj.output +24-11-19 20:47:25 | D | + w: None +24-11-19 20:47:25 | D | + x: None +24-11-19 20:47:25 | D | + y: sint8 +24-11-19 20:47:25 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:25 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:47:26 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:47:26 | D | - range ratio = [ 1.0000] +24-11-19 20:47:26 | D | sum error = [ 259.7072] +24-11-19 20:47:26 | D | best error = [ 259.7072] +24-11-19 20:47:26 | D | + error = [259.7072] +24-11-19 20:47:27 | D | - Calibrating model.layers.23.self_attn.o_proj.input +24-11-19 20:47:27 | D | - Calibrating model.layers.23.mlp.up_proj.input +24-11-19 20:47:27 | D | - Calibrating model.layers.23.mlp.down_proj.input +24-11-19 20:47:27 | D | - Quantizing model.layers.23.self_attn.q_proj (inputs) +24-11-19 20:47:27 | D | - Quantizing model.layers.23.self_attn.k_proj (inputs) +24-11-19 20:47:27 | D | - Quantizing model.layers.23.self_attn.v_proj (inputs and outputs) +24-11-19 20:47:27 | D | - Quantizing model.layers.23.self_attn.o_proj (inputs) +24-11-19 20:47:27 | D | - Quantizing model.layers.23.self_attn.k_rotary_emb (outputs) +24-11-19 20:47:27 | D | - Quantizing model.layers.23.mlp.gate_proj (inputs) +24-11-19 20:47:27 | D | - Quantizing model.layers.23.mlp.up_proj (inputs) +24-11-19 20:47:27 | D | - Quantizing model.layers.23.mlp.down_proj (inputs) +24-11-19 20:47:34 | D | - Quantizing layer model.layers.24 +24-11-19 20:47:34 | D | - Calibrating model.layers.24.self_attn.v_proj.input +24-11-19 20:47:34 | D | - Calibrating model.layers.24.self_attn.k_rotary_emb.output +24-11-19 20:47:34 | D | + w: None +24-11-19 20:47:34 | D | + x: None +24-11-19 20:47:34 | D | + y: sint8 +24-11-19 20:47:34 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:34 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:47:34 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:47:35 | D | - range ratio = [ 1.0000] +24-11-19 20:47:35 | D | sum error = [ 120.6430] +24-11-19 20:47:35 | D | best error = [ 120.6430] +24-11-19 20:47:35 | D | + error = [120.6430] +24-11-19 20:47:35 | D | - Calibrating model.layers.24.self_attn.v_proj.output +24-11-19 20:47:35 | D | + w: None +24-11-19 20:47:35 | D | + x: None +24-11-19 20:47:35 | D | + y: sint8 +24-11-19 20:47:35 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:35 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:47:36 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:47:37 | D | - range ratio = [ 1.0000] +24-11-19 20:47:37 | D | sum error = [ 235.6821] +24-11-19 20:47:37 | D | best error = [ 235.6821] +24-11-19 20:47:37 | D | + error = [235.6821] +24-11-19 20:47:37 | D | - Calibrating model.layers.24.self_attn.o_proj.input +24-11-19 20:47:37 | D | - Calibrating model.layers.24.mlp.up_proj.input +24-11-19 20:47:37 | D | - Calibrating model.layers.24.mlp.down_proj.input +24-11-19 20:47:37 | D | - Quantizing model.layers.24.self_attn.q_proj (inputs) +24-11-19 20:47:37 | D | - Quantizing model.layers.24.self_attn.k_proj (inputs) +24-11-19 20:47:37 | D | - Quantizing model.layers.24.self_attn.v_proj (inputs and outputs) +24-11-19 20:47:37 | D | - Quantizing model.layers.24.self_attn.o_proj (inputs) +24-11-19 20:47:37 | D | - Quantizing model.layers.24.self_attn.k_rotary_emb (outputs) +24-11-19 20:47:37 | D | - Quantizing model.layers.24.mlp.gate_proj (inputs) +24-11-19 20:47:37 | D | - Quantizing model.layers.24.mlp.up_proj (inputs) +24-11-19 20:47:37 | D | - Quantizing model.layers.24.mlp.down_proj (inputs) +24-11-19 20:47:44 | D | - Quantizing layer model.layers.25 +24-11-19 20:47:44 | D | - Calibrating model.layers.25.self_attn.v_proj.input +24-11-19 20:47:44 | D | - Calibrating model.layers.25.self_attn.k_rotary_emb.output +24-11-19 20:47:44 | D | + w: None +24-11-19 20:47:44 | D | + x: None +24-11-19 20:47:44 | D | + y: sint8 +24-11-19 20:47:44 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:44 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:47:45 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:47:45 | D | - range ratio = [ 1.0000] +24-11-19 20:47:45 | D | sum error = [ 100.3470] +24-11-19 20:47:45 | D | best error = [ 100.3470] +24-11-19 20:47:45 | D | + error = [100.3470] +24-11-19 20:47:45 | D | - Calibrating model.layers.25.self_attn.v_proj.output +24-11-19 20:47:45 | D | + w: None +24-11-19 20:47:45 | D | + x: None +24-11-19 20:47:45 | D | + y: sint8 +24-11-19 20:47:45 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:45 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:47:46 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:47:46 | D | - range ratio = [ 1.0000] +24-11-19 20:47:46 | D | sum error = [ 244.6742] +24-11-19 20:47:46 | D | best error = [ 244.6742] +24-11-19 20:47:46 | D | + error = [244.6742] +24-11-19 20:47:47 | D | - Calibrating model.layers.25.self_attn.o_proj.input +24-11-19 20:47:47 | D | - Calibrating model.layers.25.mlp.up_proj.input +24-11-19 20:47:47 | D | - Calibrating model.layers.25.mlp.down_proj.input +24-11-19 20:47:47 | D | - Quantizing model.layers.25.self_attn.q_proj (inputs) +24-11-19 20:47:47 | D | - Quantizing model.layers.25.self_attn.k_proj (inputs) +24-11-19 20:47:47 | D | - Quantizing model.layers.25.self_attn.v_proj (inputs and outputs) +24-11-19 20:47:47 | D | - Quantizing model.layers.25.self_attn.o_proj (inputs) +24-11-19 20:47:47 | D | - Quantizing model.layers.25.self_attn.k_rotary_emb (outputs) +24-11-19 20:47:47 | D | - Quantizing model.layers.25.mlp.gate_proj (inputs) +24-11-19 20:47:47 | D | - Quantizing model.layers.25.mlp.up_proj (inputs) +24-11-19 20:47:47 | D | - Quantizing model.layers.25.mlp.down_proj (inputs) +24-11-19 20:47:54 | D | - Quantizing layer model.layers.26 +24-11-19 20:47:54 | D | - Calibrating model.layers.26.self_attn.v_proj.input +24-11-19 20:47:54 | D | - Calibrating model.layers.26.self_attn.k_rotary_emb.output +24-11-19 20:47:54 | D | + w: None +24-11-19 20:47:54 | D | + x: None +24-11-19 20:47:54 | D | + y: sint8 +24-11-19 20:47:54 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:54 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:47:54 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:47:55 | D | - range ratio = [ 1.0000] +24-11-19 20:47:55 | D | sum error = [ 135.5828] +24-11-19 20:47:55 | D | best error = [ 135.5828] +24-11-19 20:47:55 | D | + error = [135.5828] +24-11-19 20:47:55 | D | - Calibrating model.layers.26.self_attn.v_proj.output +24-11-19 20:47:55 | D | + w: None +24-11-19 20:47:55 | D | + x: None +24-11-19 20:47:55 | D | + y: sint8 +24-11-19 20:47:55 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:55 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:47:55 | D | + finished reseting calibrator, ram usage: 13.0 +24-11-19 20:47:56 | D | - range ratio = [ 1.0000] +24-11-19 20:47:56 | D | sum error = [ 262.6941] +24-11-19 20:47:56 | D | best error = [ 262.6941] +24-11-19 20:47:56 | D | + error = [262.6941] +24-11-19 20:47:56 | D | - Calibrating model.layers.26.self_attn.o_proj.input +24-11-19 20:47:56 | D | - Calibrating model.layers.26.mlp.up_proj.input +24-11-19 20:47:56 | D | - Calibrating model.layers.26.mlp.down_proj.input +24-11-19 20:47:56 | D | - Quantizing model.layers.26.self_attn.q_proj (inputs) +24-11-19 20:47:56 | D | - Quantizing model.layers.26.self_attn.k_proj (inputs) +24-11-19 20:47:56 | D | - Quantizing model.layers.26.self_attn.v_proj (inputs and outputs) +24-11-19 20:47:56 | D | - Quantizing model.layers.26.self_attn.o_proj (inputs) +24-11-19 20:47:56 | D | - Quantizing model.layers.26.self_attn.k_rotary_emb (outputs) +24-11-19 20:47:56 | D | - Quantizing model.layers.26.mlp.gate_proj (inputs) +24-11-19 20:47:56 | D | - Quantizing model.layers.26.mlp.up_proj (inputs) +24-11-19 20:47:56 | D | - Quantizing model.layers.26.mlp.down_proj (inputs) +24-11-19 20:48:03 | D | - Quantizing layer model.layers.27 +24-11-19 20:48:03 | D | - Calibrating model.layers.27.self_attn.v_proj.input +24-11-19 20:48:03 | D | - Calibrating model.layers.27.self_attn.k_rotary_emb.output +24-11-19 20:48:03 | D | + w: None +24-11-19 20:48:03 | D | + x: None +24-11-19 20:48:03 | D | + y: sint8 +24-11-19 20:48:03 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:03 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:48:04 | D | + finished reseting calibrator, ram usage: 13.1 +24-11-19 20:48:04 | D | - range ratio = [ 1.0000] +24-11-19 20:48:04 | D | sum error = [ 148.3797] +24-11-19 20:48:04 | D | best error = [ 148.3797] +24-11-19 20:48:04 | D | + error = [148.3797] +24-11-19 20:48:04 | D | - Calibrating model.layers.27.self_attn.v_proj.output +24-11-19 20:48:04 | D | + w: None +24-11-19 20:48:04 | D | + x: None +24-11-19 20:48:04 | D | + y: sint8 +24-11-19 20:48:04 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:04 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:48:05 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:48:05 | D | - range ratio = [ 1.0000] +24-11-19 20:48:05 | D | sum error = [ 324.9978] +24-11-19 20:48:05 | D | best error = [ 324.9978] +24-11-19 20:48:05 | D | + error = [324.9978] +24-11-19 20:48:05 | D | - Calibrating model.layers.27.self_attn.o_proj.input +24-11-19 20:48:05 | D | - Calibrating model.layers.27.mlp.up_proj.input +24-11-19 20:48:06 | D | - Calibrating model.layers.27.mlp.down_proj.input +24-11-19 20:48:06 | D | - Quantizing model.layers.27.self_attn.q_proj (inputs) +24-11-19 20:48:06 | D | - Quantizing model.layers.27.self_attn.k_proj (inputs) +24-11-19 20:48:06 | D | - Quantizing model.layers.27.self_attn.v_proj (inputs and outputs) +24-11-19 20:48:06 | D | - Quantizing model.layers.27.self_attn.o_proj (inputs) +24-11-19 20:48:06 | D | - Quantizing model.layers.27.self_attn.k_rotary_emb (outputs) +24-11-19 20:48:06 | D | - Quantizing model.layers.27.mlp.gate_proj (inputs) +24-11-19 20:48:06 | D | - Quantizing model.layers.27.mlp.up_proj (inputs) +24-11-19 20:48:06 | D | - Quantizing model.layers.27.mlp.down_proj (inputs) +24-11-19 20:48:13 | D | - Quantizing layer model.layers.28 +24-11-19 20:48:13 | D | - Calibrating model.layers.28.self_attn.v_proj.input +24-11-19 20:48:13 | D | - Calibrating model.layers.28.self_attn.k_rotary_emb.output +24-11-19 20:48:13 | D | + w: None +24-11-19 20:48:13 | D | + x: None +24-11-19 20:48:13 | D | + y: sint8 +24-11-19 20:48:13 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:13 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:48:13 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:48:14 | D | - range ratio = [ 1.0000] +24-11-19 20:48:14 | D | sum error = [ 139.9464] +24-11-19 20:48:14 | D | best error = [ 139.9464] +24-11-19 20:48:14 | D | + error = [139.9464] +24-11-19 20:48:14 | D | - Calibrating model.layers.28.self_attn.v_proj.output +24-11-19 20:48:14 | D | + w: None +24-11-19 20:48:14 | D | + x: None +24-11-19 20:48:14 | D | + y: sint8 +24-11-19 20:48:14 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:14 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:48:14 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:48:15 | D | - range ratio = [ 1.0000] +24-11-19 20:48:15 | D | sum error = [ 290.3549] +24-11-19 20:48:15 | D | best error = [ 290.3549] +24-11-19 20:48:15 | D | + error = [290.3549] +24-11-19 20:48:15 | D | - Calibrating model.layers.28.self_attn.o_proj.input +24-11-19 20:48:15 | D | - Calibrating model.layers.28.mlp.up_proj.input +24-11-19 20:48:15 | D | - Calibrating model.layers.28.mlp.down_proj.input +24-11-19 20:48:15 | D | - Quantizing model.layers.28.self_attn.q_proj (inputs) +24-11-19 20:48:15 | D | - Quantizing model.layers.28.self_attn.k_proj (inputs) +24-11-19 20:48:15 | D | - Quantizing model.layers.28.self_attn.v_proj (inputs and outputs) +24-11-19 20:48:15 | D | - Quantizing model.layers.28.self_attn.o_proj (inputs) +24-11-19 20:48:15 | D | - Quantizing model.layers.28.self_attn.k_rotary_emb (outputs) +24-11-19 20:48:15 | D | - Quantizing model.layers.28.mlp.gate_proj (inputs) +24-11-19 20:48:15 | D | - Quantizing model.layers.28.mlp.up_proj (inputs) +24-11-19 20:48:15 | D | - Quantizing model.layers.28.mlp.down_proj (inputs) +24-11-19 20:48:23 | D | - Quantizing layer model.layers.29 +24-11-19 20:48:23 | D | - Calibrating model.layers.29.self_attn.v_proj.input +24-11-19 20:48:23 | D | - Calibrating model.layers.29.self_attn.k_rotary_emb.output +24-11-19 20:48:23 | D | + w: None +24-11-19 20:48:23 | D | + x: None +24-11-19 20:48:23 | D | + y: sint8 +24-11-19 20:48:23 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:23 | D | + finished parsing calibration arguments, ram usage: 13.0 +24-11-19 20:48:23 | D | + finished reseting calibrator, ram usage: 13.1 +24-11-19 20:48:24 | D | - range ratio = [ 1.0000] +24-11-19 20:48:24 | D | sum error = [ 154.1468] +24-11-19 20:48:24 | D | best error = [ 154.1468] +24-11-19 20:48:24 | D | + error = [154.1468] +24-11-19 20:48:24 | D | - Calibrating model.layers.29.self_attn.v_proj.output +24-11-19 20:48:24 | D | + w: None +24-11-19 20:48:24 | D | + x: None +24-11-19 20:48:24 | D | + y: sint8 +24-11-19 20:48:24 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:24 | D | + finished parsing calibration arguments, ram usage: 13.1 +24-11-19 20:48:24 | D | + finished reseting calibrator, ram usage: 13.1 +24-11-19 20:48:25 | D | - range ratio = [ 1.0000] +24-11-19 20:48:25 | D | sum error = [ 337.3955] +24-11-19 20:48:25 | D | best error = [ 337.3955] +24-11-19 20:48:25 | D | + error = [337.3955] +24-11-19 20:48:25 | D | - Calibrating model.layers.29.self_attn.o_proj.input +24-11-19 20:48:25 | D | - Calibrating model.layers.29.mlp.up_proj.input +24-11-19 20:48:25 | D | - Calibrating model.layers.29.mlp.down_proj.input +24-11-19 20:48:25 | D | - Quantizing model.layers.29.self_attn.q_proj (inputs) +24-11-19 20:48:25 | D | - Quantizing model.layers.29.self_attn.k_proj (inputs) +24-11-19 20:48:25 | D | - Quantizing model.layers.29.self_attn.v_proj (inputs and outputs) +24-11-19 20:48:25 | D | - Quantizing model.layers.29.self_attn.o_proj (inputs) +24-11-19 20:48:25 | D | - Quantizing model.layers.29.self_attn.k_rotary_emb (outputs) +24-11-19 20:48:25 | D | - Quantizing model.layers.29.mlp.gate_proj (inputs) +24-11-19 20:48:25 | D | - Quantizing model.layers.29.mlp.up_proj (inputs) +24-11-19 20:48:25 | D | - Quantizing model.layers.29.mlp.down_proj (inputs) +24-11-19 20:48:32 | D | - Quantizing layer model.layers.30 +24-11-19 20:48:32 | D | - Calibrating model.layers.30.self_attn.v_proj.input +24-11-19 20:48:32 | D | - Calibrating model.layers.30.self_attn.k_rotary_emb.output +24-11-19 20:48:32 | D | + w: None +24-11-19 20:48:32 | D | + x: None +24-11-19 20:48:32 | D | + y: sint8 +24-11-19 20:48:32 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:32 | D | + finished parsing calibration arguments, ram usage: 13.0 +24-11-19 20:48:33 | D | + finished reseting calibrator, ram usage: 12.8 +24-11-19 20:48:33 | D | - range ratio = [ 1.0000] +24-11-19 20:48:33 | D | sum error = [ 151.7990] +24-11-19 20:48:33 | D | best error = [ 151.7990] +24-11-19 20:48:33 | D | + error = [151.7990] +24-11-19 20:48:33 | D | - Calibrating model.layers.30.self_attn.v_proj.output +24-11-19 20:48:33 | D | + w: None +24-11-19 20:48:33 | D | + x: None +24-11-19 20:48:33 | D | + y: sint8 +24-11-19 20:48:33 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:33 | D | + finished parsing calibration arguments, ram usage: 12.9 +24-11-19 20:48:34 | D | + finished reseting calibrator, ram usage: 12.9 +24-11-19 20:48:34 | D | - range ratio = [ 1.0000] +24-11-19 20:48:34 | D | sum error = [ 330.3534] +24-11-19 20:48:34 | D | best error = [ 330.3534] +24-11-19 20:48:34 | D | + error = [330.3534] +24-11-19 20:48:35 | D | - Calibrating model.layers.30.self_attn.o_proj.input +24-11-19 20:48:35 | D | - Calibrating model.layers.30.mlp.up_proj.input +24-11-19 20:48:35 | D | - Calibrating model.layers.30.mlp.down_proj.input +24-11-19 20:48:35 | D | - Quantizing model.layers.30.self_attn.q_proj (inputs) +24-11-19 20:48:35 | D | - Quantizing model.layers.30.self_attn.k_proj (inputs) +24-11-19 20:48:35 | D | - Quantizing model.layers.30.self_attn.v_proj (inputs and outputs) +24-11-19 20:48:35 | D | - Quantizing model.layers.30.self_attn.o_proj (inputs) +24-11-19 20:48:35 | D | - Quantizing model.layers.30.self_attn.k_rotary_emb (outputs) +24-11-19 20:48:35 | D | - Quantizing model.layers.30.mlp.gate_proj (inputs) +24-11-19 20:48:35 | D | - Quantizing model.layers.30.mlp.up_proj (inputs) +24-11-19 20:48:35 | D | - Quantizing model.layers.30.mlp.down_proj (inputs) diff --git a/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.201608/config-241119.201608.yaml b/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.201608/config-241119.201608.yaml new file mode 100644 index 0000000000000000000000000000000000000000..cbc22de6e0b8fdf6576baa8e3871fe015ea37bf1 --- /dev/null +++ b/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.201608/config-241119.201608.yaml @@ -0,0 +1,129 @@ +cache: + root: runs/shang + path: + rotation: runs/shang/llm/cache/quant/rotation/hadamard/llama-2-7b-instruct-together-32k.pt + reorder: '' + smooth: '' + wgts: runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-2-7b-instruct-together-32k.pt + acts: runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-2-7b-instruct-together-32k.pt +output: + root: runs/shang + dirname: skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0] + job: run +model: + name: llama-2-7b-instruct-together-32k + family: llama-2 + path: /home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k + root: '' + local_path: /home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k + local_root: /home/yujunlin/models + dtype: torch.float16 +eval: + num_gpus: 1 + batch_size: 8 + tasks: + - wikitext + max_seq_length: -4096 + evaluators: + - gptq +quant: + wgts: + dtype: sint8 + zero_point: null + group_shapes: + - - 1 + - -1 + - -1 + scale_dtypes: + - torch.float16 + intermediate_dtypes: [] + intermediate_levels: [] + needs_dequant_saturation: false + skips: [] + enable_kernel_gptq: true + kernel_gptq: + damp_percentage: 0.01 + block_size: 128 + num_inv_tries: 250 + hessian_block_size: 512 + enable_calib_range: true + calib_range: + degree: 2 + objective: OutputsError + strategy: GridSearch + granularity: Group + element_batch_size: 64 + sample_batch_size: -1 + element_size: 512 + sample_size: -1 + pre_reshape: true + outputs_device: cpu + ratio: 1.0 + max_shrink: 0.2 + max_expand: 1.0 + num_grids: 80 + allow_scale: false + skips: [] + ipts: + dtype: sint8 + zero_point: null + group_shapes: + - - 1 + - -1 + - -1 + scale_dtypes: + - torch.float16 + skips: [] + static: false + enable_calib_range: false + opts: + dtype: sint8 + zero_point: null + group_shapes: + - - -1 + - -1 + - -1 + scale_dtypes: + - torch.float16 + skips: + - attn_q + static: true + enable_calib_range: true + calib_range: + degree: 2 + objective: OutputsError + strategy: Manual + granularity: Layer + element_batch_size: -1 + sample_batch_size: -1 + element_size: -1 + sample_size: -1 + pre_reshape: true + outputs_device: cpu + ratio: 1.0 + max_shrink: 0.2 + max_expand: 1.0 + num_grids: 80 + allow_scale: false + skips: [] + calib: + data: pileval + num_samples: 128 + path: mit-han-lab/pile-val-backup + seq_length: 1024 + min_seq_length: 0 + max_seq_length: 0 + local_path: '' + enable_rotation: true + rotation: + random: false + transforms: + - out_proj + enable_reorder: false + enable_smooth: false + develop_dtype: torch.float32 +seed: 12345 +skip_eval: false +load_from: '' +save_model: 'true' +copy_on_save: false diff --git a/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.201608/model/acts.pt b/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.201608/model/acts.pt new file mode 100644 index 0000000000000000000000000000000000000000..c0cac1428be2c5b71753dcb0316dbf1b8926fed7 --- /dev/null +++ b/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.201608/model/acts.pt @@ -0,0 +1,3 @@ +version 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a/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.201608/run-241119.201608.log b/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.201608/run-241119.201608.log new file mode 100644 index 0000000000000000000000000000000000000000..0ee7277b3228eeec2cda7af0fa3cef84e19c7ea2 --- /dev/null +++ b/runs/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.201608/run-241119.201608.log @@ -0,0 +1,15508 @@ +24-11-19 20:16:08 | I | === Configurations === +24-11-19 20:16:08 | I | LlmPtqRunConfig( +24-11-19 20:16:08 | I | cache=LlmCacheConfig( +24-11-19 20:16:08 | I | root=runs/shang, +24-11-19 20:16:08 | I | dirpath=LlmQuantCacheConfig( +24-11-19 20:16:08 | I | rotation=runs/shang/llm/cache/quant/rotation/hadamard, +24-11-19 20:16:08 | I | reorder=, +24-11-19 20:16:08 | I | smooth=, +24-11-19 20:16:08 | I | wgts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[], +24-11-19 20:16:08 | I | acts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]), +24-11-19 20:16:08 | I | path=LlmQuantCacheConfig( +24-11-19 20:16:08 | I | rotation=runs/shang/llm/cache/quant/rotation/hadamard/llama-2-7b-instruct-together-32k.pt, +24-11-19 20:16:08 | I | reorder=, +24-11-19 20:16:08 | I | smooth=, +24-11-19 20:16:08 | I | wgts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-2-7b-instruct-together-32k.pt, +24-11-19 20:16:08 | I | acts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-2-7b-instruct-together-32k.pt)), +24-11-19 20:16:08 | I | output=OutputConfig( +24-11-19 20:16:08 | I | root=runs/shang, +24-11-19 20:16:08 | I | dirname=skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0], +24-11-19 20:16:08 | I | job=run, +24-11-19 20:16:08 | I | dirpath=runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0], +24-11-19 20:16:08 | I | timestamp=241119.201608), +24-11-19 20:16:08 | I | model=LlmModelConfig( +24-11-19 20:16:08 | I | name=llama-2-7b-instruct-together-32k, +24-11-19 20:16:08 | I | family=llama-2, +24-11-19 20:16:08 | I | path=/home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k, +24-11-19 20:16:08 | I | root=, +24-11-19 20:16:08 | I | local_path=/home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k, +24-11-19 20:16:08 | I | local_root=/home/yujunlin/models, +24-11-19 20:16:08 | I | size=7.0, +24-11-19 20:16:08 | I | variant=instruct-together-32k, +24-11-19 20:16:08 | I | dtype=torch.float16, +24-11-19 20:16:08 | I | orig_dtype=torch.float16), +24-11-19 20:16:08 | I | eval=LlmEvalConfig( +24-11-19 20:16:08 | I | num_gpus=1, +24-11-19 20:16:08 | I | batch_size=8, +24-11-19 20:16:08 | I | tasks=['wikitext'], +24-11-19 20:16:08 | I | max_seq_length=-4096, +24-11-19 20:16:08 | I | evaluators=['gptq']), +24-11-19 20:16:08 | I | quant=LlmQuantConfig( +24-11-19 20:16:08 | I | wgts=LlmWeightQuantizerConfig( +24-11-19 20:16:08 | I | dtype=sint8, +24-11-19 20:16:08 | I | zero_point=None, +24-11-19 20:16:08 | I | group_shapes=((1, -1, -1),), +24-11-19 20:16:08 | I | scale_dtypes=(torch.float16,), +24-11-19 20:16:08 | I | intermediate_dtypes=(), +24-11-19 20:16:08 | I | intermediate_levels=(), +24-11-19 20:16:08 | I | needs_dequant_saturation=False, +24-11-19 20:16:08 | I | skips=[], +24-11-19 20:16:08 | I | static=True, +24-11-19 20:16:08 | I | kernel_gptq=QuantGptqConfig( +24-11-19 20:16:08 | I | damp_percentage=0.01, +24-11-19 20:16:08 | I | block_size=128, +24-11-19 20:16:08 | I | num_inv_tries=250, +24-11-19 20:16:08 | I | hessian_block_size=512), +24-11-19 20:16:08 | I | calib_range=SkipBasedDynamicRangeCalibConfig( +24-11-19 20:16:08 | I | degree=2, +24-11-19 20:16:08 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 20:16:08 | I | strategy=SearchBasedCalibStrategy.GridSearch, +24-11-19 20:16:08 | I | granularity=SearchBasedCalibGranularity.Group, +24-11-19 20:16:08 | I | element_batch_size=64, +24-11-19 20:16:08 | I | sample_batch_size=-1, +24-11-19 20:16:08 | I | element_size=512, +24-11-19 20:16:08 | I | sample_size=-1, +24-11-19 20:16:08 | I | pre_reshape=True, +24-11-19 20:16:08 | I | outputs_device=cpu, +24-11-19 20:16:08 | I | ratio=1.0, +24-11-19 20:16:08 | I | max_shrink=0.2, +24-11-19 20:16:08 | I | max_expand=1.0, +24-11-19 20:16:08 | I | num_grids=80, +24-11-19 20:16:08 | I | allow_scale=False, +24-11-19 20:16:08 | I | skips=[])), +24-11-19 20:16:08 | I | ipts=LlmActivationQuantizerConfig( +24-11-19 20:16:08 | I | dtype=sint8, +24-11-19 20:16:08 | I | zero_point=None, +24-11-19 20:16:08 | I | group_shapes=((1, -1, -1),), +24-11-19 20:16:08 | I | scale_dtypes=(torch.float16,), +24-11-19 20:16:08 | I | intermediate_dtypes=(), +24-11-19 20:16:08 | I | intermediate_levels=(), +24-11-19 20:16:08 | I | needs_dequant_saturation=False, +24-11-19 20:16:08 | I | skips=[], +24-11-19 20:16:08 | I | static=False, +24-11-19 20:16:08 | I | kernel_gptq=None, +24-11-19 20:16:08 | I | calib_range=None), +24-11-19 20:16:08 | I | opts=LlmActivationQuantizerConfig( +24-11-19 20:16:08 | I | dtype=sint8, +24-11-19 20:16:08 | I | zero_point=None, +24-11-19 20:16:08 | I | group_shapes=((-1, -1, -1),), +24-11-19 20:16:08 | I | scale_dtypes=(torch.float16,), +24-11-19 20:16:08 | I | intermediate_dtypes=(), +24-11-19 20:16:08 | I | intermediate_levels=(), +24-11-19 20:16:08 | I | needs_dequant_saturation=False, +24-11-19 20:16:08 | I | skips=['attn_q'], +24-11-19 20:16:08 | I | static=True, +24-11-19 20:16:08 | I | kernel_gptq=None, +24-11-19 20:16:08 | I | calib_range=SkipBasedDynamicRangeCalibConfig( +24-11-19 20:16:08 | I | degree=2, +24-11-19 20:16:08 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 20:16:08 | I | strategy=SearchBasedCalibStrategy.Manual, +24-11-19 20:16:08 | I | granularity=SearchBasedCalibGranularity.Layer, +24-11-19 20:16:08 | I | element_batch_size=-1, +24-11-19 20:16:08 | I | sample_batch_size=-1, +24-11-19 20:16:08 | I | element_size=-1, +24-11-19 20:16:08 | I | sample_size=-1, +24-11-19 20:16:08 | I | pre_reshape=True, +24-11-19 20:16:08 | I | outputs_device=cpu, +24-11-19 20:16:08 | I | ratio=1.0, +24-11-19 20:16:08 | I | max_shrink=0.2, +24-11-19 20:16:08 | I | max_expand=1.0, +24-11-19 20:16:08 | I | num_grids=80, +24-11-19 20:16:08 | I | allow_scale=False, +24-11-19 20:16:08 | I | skips=[])), +24-11-19 20:16:08 | I | calib=LlmCalibDataLoaderConfig( +24-11-19 20:16:08 | I | data=pileval, +24-11-19 20:16:08 | I | num_samples=128, +24-11-19 20:16:08 | I | batch_size=1, +24-11-19 20:16:08 | I | path=mit-han-lab/pile-val-backup, +24-11-19 20:16:08 | I | seq_length=1024, +24-11-19 20:16:08 | I | min_seq_length=0, +24-11-19 20:16:08 | I | max_seq_length=0, +24-11-19 20:16:08 | I | local_path=), +24-11-19 20:16:08 | I | rotation=QuantRotationConfig( +24-11-19 20:16:08 | I | random=False, +24-11-19 20:16:08 | I | transforms=['out_proj']), +24-11-19 20:16:08 | I | reorder=None, +24-11-19 20:16:08 | I | smooth=None, +24-11-19 20:16:08 | I | develop_dtype=torch.float32), +24-11-19 20:16:08 | I | seed=12345, +24-11-19 20:16:08 | I | skip_eval=False, +24-11-19 20:16:08 | I | load_from=, +24-11-19 20:16:08 | I | save_model=true, +24-11-19 20:16:08 | I | copy_on_save=False) +24-11-19 20:16:08 | I | === Dumped Configurations === +24-11-19 20:16:08 | I | { 'cache': { 'path': { 'acts': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-2-7b-instruct-together-32k.pt', +24-11-19 20:16:08 | I | 'reorder': '', +24-11-19 20:16:08 | I | 'rotation': 'runs/shang/llm/cache/quant/rotation/hadamard/llama-2-7b-instruct-together-32k.pt', +24-11-19 20:16:08 | I | 'smooth': '', +24-11-19 20:16:08 | I | 'wgts': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-2-7b-instruct-together-32k.pt'}, +24-11-19 20:16:08 | I | 'root': 'runs/shang'}, +24-11-19 20:16:08 | I | 'copy_on_save': False, +24-11-19 20:16:08 | I | 'eval': {'batch_size': 8, 'evaluators': ['gptq'], 'max_seq_length': -4096, 'num_gpus': 1, 'tasks': ['wikitext']}, +24-11-19 20:16:08 | I | 'load_from': '', +24-11-19 20:16:08 | I | 'model': { 'dtype': 'torch.float16', +24-11-19 20:16:08 | I | 'family': 'llama-2', +24-11-19 20:16:08 | I | 'local_path': '/home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k', +24-11-19 20:16:08 | I | 'local_root': '/home/yujunlin/models', +24-11-19 20:16:08 | I | 'name': 'llama-2-7b-instruct-together-32k', +24-11-19 20:16:08 | I | 'path': '/home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k', +24-11-19 20:16:08 | I | 'root': ''}, +24-11-19 20:16:08 | I | 'output': { 'dirname': 'skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]', +24-11-19 20:16:08 | I | 'job': 'run', +24-11-19 20:16:08 | I | 'root': 'runs/shang'}, +24-11-19 20:16:08 | I | 'quant': { 'calib': { 'data': 'pileval', +24-11-19 20:16:08 | I | 'local_path': '', +24-11-19 20:16:08 | I | 'max_seq_length': 0, +24-11-19 20:16:08 | I | 'min_seq_length': 0, +24-11-19 20:16:08 | I | 'num_samples': 128, +24-11-19 20:16:08 | I | 'path': 'mit-han-lab/pile-val-backup', +24-11-19 20:16:08 | I | 'seq_length': 1024}, +24-11-19 20:16:08 | I | 'develop_dtype': 'torch.float32', +24-11-19 20:16:08 | I | 'enable_reorder': False, +24-11-19 20:16:08 | I | 'enable_rotation': True, +24-11-19 20:16:08 | I | 'enable_smooth': False, +24-11-19 20:16:08 | I | 'ipts': { 'dtype': 'sint8', +24-11-19 20:16:08 | I | 'enable_calib_range': False, +24-11-19 20:16:08 | I | 'group_shapes': [[1, -1, -1]], +24-11-19 20:16:08 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 20:16:08 | I | 'skips': [], +24-11-19 20:16:08 | I | 'static': False, +24-11-19 20:16:08 | I | 'zero_point': None}, +24-11-19 20:16:08 | I | 'opts': { 'calib_range': { 'allow_scale': False, +24-11-19 20:16:08 | I | 'degree': 2, +24-11-19 20:16:08 | I | 'element_batch_size': -1, +24-11-19 20:16:08 | I | 'element_size': -1, +24-11-19 20:16:08 | I | 'granularity': 'Layer', +24-11-19 20:16:08 | I | 'max_expand': 1.0, +24-11-19 20:16:08 | I | 'max_shrink': 0.2, +24-11-19 20:16:08 | I | 'num_grids': 80, +24-11-19 20:16:08 | I | 'objective': 'OutputsError', +24-11-19 20:16:08 | I | 'outputs_device': 'cpu', +24-11-19 20:16:08 | I | 'pre_reshape': True, +24-11-19 20:16:08 | I | 'ratio': 1.0, +24-11-19 20:16:08 | I | 'sample_batch_size': -1, +24-11-19 20:16:08 | I | 'sample_size': -1, +24-11-19 20:16:08 | I | 'skips': [], +24-11-19 20:16:08 | I | 'strategy': 'Manual'}, +24-11-19 20:16:08 | I | 'dtype': 'sint8', +24-11-19 20:16:08 | I | 'enable_calib_range': True, +24-11-19 20:16:08 | I | 'group_shapes': [[-1, -1, -1]], +24-11-19 20:16:08 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 20:16:08 | I | 'skips': ['attn_q'], +24-11-19 20:16:08 | I | 'static': True, +24-11-19 20:16:08 | I | 'zero_point': None}, +24-11-19 20:16:08 | I | 'rotation': {'random': False, 'transforms': ['out_proj']}, +24-11-19 20:16:08 | I | 'wgts': { 'calib_range': { 'allow_scale': False, +24-11-19 20:16:08 | I | 'degree': 2, +24-11-19 20:16:08 | I | 'element_batch_size': 64, +24-11-19 20:16:08 | I | 'element_size': 512, +24-11-19 20:16:08 | I | 'granularity': 'Group', +24-11-19 20:16:08 | I | 'max_expand': 1.0, +24-11-19 20:16:08 | I | 'max_shrink': 0.2, +24-11-19 20:16:08 | I | 'num_grids': 80, +24-11-19 20:16:08 | I | 'objective': 'OutputsError', +24-11-19 20:16:08 | I | 'outputs_device': 'cpu', +24-11-19 20:16:08 | I | 'pre_reshape': True, +24-11-19 20:16:08 | I | 'ratio': 1.0, +24-11-19 20:16:08 | I | 'sample_batch_size': -1, +24-11-19 20:16:08 | I | 'sample_size': -1, +24-11-19 20:16:08 | I | 'skips': [], +24-11-19 20:16:08 | I | 'strategy': 'GridSearch'}, +24-11-19 20:16:08 | I | 'dtype': 'sint8', +24-11-19 20:16:08 | I | 'enable_calib_range': True, +24-11-19 20:16:08 | I | 'enable_kernel_gptq': True, +24-11-19 20:16:08 | I | 'group_shapes': [[1, -1, -1]], +24-11-19 20:16:08 | I | 'intermediate_dtypes': [], +24-11-19 20:16:08 | I | 'intermediate_levels': [], +24-11-19 20:16:08 | I | 'kernel_gptq': { 'block_size': 128, +24-11-19 20:16:08 | I | 'damp_percentage': 0.01, +24-11-19 20:16:08 | I | 'hessian_block_size': 512, +24-11-19 20:16:08 | I | 'num_inv_tries': 250}, +24-11-19 20:16:08 | I | 'needs_dequant_saturation': False, +24-11-19 20:16:08 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 20:16:08 | I | 'skips': [], +24-11-19 20:16:08 | I | 'zero_point': None}}, +24-11-19 20:16:08 | I | 'save_model': 'true', +24-11-19 20:16:08 | I | 'seed': 12345, +24-11-19 20:16:08 | I | 'skip_eval': False} +24-11-19 20:16:08 | I | === Output Directory === +24-11-19 20:16:08 | I | runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.201608 +24-11-19 20:16:08 | I | === Start Evaluating === +24-11-19 20:16:08 | I | * Building model llama-2-7b-instruct-together-32k from /home/yujunlin/models/llama-2/llama-2-7b-instruct-together-32k +24-11-19 20:16:08 | I | We will use 90% of the memory on device 0 for storing the model, and 10% for the buffer to avoid OOM. You can set `max_memory` in to a higher value to use more memory (at your own risk). +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.0.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.1.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.2.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.3.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.4.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.5.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.6.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.7.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.8.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.9.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.10.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.11.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.12.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.13.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.14.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.15.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.16.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.17.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.18.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.19.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.20.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.21.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.22.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.23.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.24.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.25.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.26.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.27.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.28.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.29.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.30.self_attn +24-11-19 20:16:17 | I | - Patching LlamaSdpaAttention.forward in model.layers.31.self_attn +24-11-19 20:16:17 | I | * Rotating model +24-11-19 20:16:17 | I | - Loading rotation from runs/shang/llm/cache/quant/rotation/hadamard/llama-2-7b-instruct-together-32k.pt +24-11-19 20:16:17 | D | - Transforming norm and linear in model.layers.0 +24-11-19 20:16:17 | D | - Transforming norm and linear in model.layers.1 +24-11-19 20:16:17 | D | - Transforming norm and linear in model.layers.2 +24-11-19 20:16:17 | D | - Transforming norm and linear in model.layers.3 +24-11-19 20:16:17 | D | - Transforming norm and linear in model.layers.4 +24-11-19 20:16:17 | D | - Transforming norm and linear in model.layers.5 +24-11-19 20:16:17 | D | - Transforming norm and linear in model.layers.6 +24-11-19 20:16:17 | D | - Transforming norm and linear in model.layers.7 +24-11-19 20:16:18 | D | - Transforming norm and linear in model.layers.8 +24-11-19 20:16:18 | D | - Transforming norm and linear in model.layers.9 +24-11-19 20:16:18 | D | - Transforming norm and linear in model.layers.10 +24-11-19 20:16:18 | D | - Transforming norm and linear in model.layers.11 +24-11-19 20:16:18 | D | - Transforming norm and linear in model.layers.12 +24-11-19 20:16:18 | D | - Transforming norm and linear in model.layers.13 +24-11-19 20:16:18 | D | - Transforming norm and linear in model.layers.14 +24-11-19 20:16:18 | D | - Transforming norm and linear in model.layers.15 +24-11-19 20:16:18 | D | - Transforming norm and linear in model.layers.16 +24-11-19 20:16:18 | D | - Transforming norm and linear in model.layers.17 +24-11-19 20:16:18 | D | - Transforming norm and linear in model.layers.18 +24-11-19 20:16:18 | D | - Transforming norm and linear in model.layers.19 +24-11-19 20:16:19 | D | - Transforming norm and linear in model.layers.20 +24-11-19 20:16:19 | D | - Transforming norm and linear in model.layers.21 +24-11-19 20:16:19 | D | - Transforming norm and linear in model.layers.22 +24-11-19 20:16:19 | D | - Transforming norm and linear in model.layers.23 +24-11-19 20:16:19 | D | - Transforming norm and linear in model.layers.24 +24-11-19 20:16:19 | D | - Transforming norm and linear in model.layers.25 +24-11-19 20:16:19 | D | - Transforming norm and linear in model.layers.26 +24-11-19 20:16:19 | D | - Transforming norm and linear in model.layers.27 +24-11-19 20:16:19 | D | - Transforming norm and linear in model.layers.28 +24-11-19 20:16:19 | D | - Transforming norm and linear in model.layers.29 +24-11-19 20:16:19 | D | - Transforming norm and linear in model.layers.30 +24-11-19 20:16:20 | D | - Transforming norm and linear in model.layers.31 +24-11-19 20:16:20 | D | - Transforming model.norm +24-11-19 20:16:20 | D | - Rotating model.embed_tokens +24-11-19 20:16:20 | D | - Rotating model.layers.0 +24-11-19 20:16:20 | D | - Rotating model.layers.0.self_attn.q_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.0.self_attn.k_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.0.self_attn.v_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.0.self_attn.o_proj (out) +24-11-19 20:16:20 | D | - Rotating model.layers.0.self_attn.v_proj (out) +24-11-19 20:16:20 | D | - Rotating model.layers.0.self_attn.o_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.0.mlp.up_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.0.mlp.gate_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.0.mlp.down_proj (out) +24-11-19 20:16:20 | D | - Rotating model.layers.1 +24-11-19 20:16:20 | D | - Rotating model.layers.1.self_attn.q_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.1.self_attn.k_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.1.self_attn.v_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.1.self_attn.o_proj (out) +24-11-19 20:16:20 | D | - Rotating model.layers.1.self_attn.v_proj (out) +24-11-19 20:16:20 | D | - Rotating model.layers.1.self_attn.o_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.1.mlp.up_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.1.mlp.gate_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.1.mlp.down_proj (out) +24-11-19 20:16:20 | D | - Rotating model.layers.2 +24-11-19 20:16:20 | D | - Rotating model.layers.2.self_attn.q_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.2.self_attn.k_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.2.self_attn.v_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.2.self_attn.o_proj (out) +24-11-19 20:16:20 | D | - Rotating model.layers.2.self_attn.v_proj (out) +24-11-19 20:16:20 | D | - Rotating model.layers.2.self_attn.o_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.2.mlp.up_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.2.mlp.gate_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.2.mlp.down_proj (out) +24-11-19 20:16:20 | D | - Rotating model.layers.3 +24-11-19 20:16:20 | D | - Rotating model.layers.3.self_attn.q_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.3.self_attn.k_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.3.self_attn.v_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.3.self_attn.o_proj (out) +24-11-19 20:16:20 | D | - Rotating model.layers.3.self_attn.v_proj (out) +24-11-19 20:16:20 | D | - Rotating model.layers.3.self_attn.o_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.3.mlp.up_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.3.mlp.gate_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.3.mlp.down_proj (out) +24-11-19 20:16:20 | D | - Rotating model.layers.4 +24-11-19 20:16:20 | D | - Rotating model.layers.4.self_attn.q_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.4.self_attn.k_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.4.self_attn.v_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.4.self_attn.o_proj (out) +24-11-19 20:16:20 | D | - Rotating model.layers.4.self_attn.v_proj (out) +24-11-19 20:16:20 | D | - Rotating model.layers.4.self_attn.o_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.4.mlp.up_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.4.mlp.gate_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.4.mlp.down_proj (out) +24-11-19 20:16:20 | D | - Rotating model.layers.5 +24-11-19 20:16:20 | D | - Rotating model.layers.5.self_attn.q_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.5.self_attn.k_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.5.self_attn.v_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.5.self_attn.o_proj (out) +24-11-19 20:16:20 | D | - Rotating model.layers.5.self_attn.v_proj (out) +24-11-19 20:16:20 | D | - Rotating model.layers.5.self_attn.o_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.5.mlp.up_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.5.mlp.gate_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.5.mlp.down_proj (out) +24-11-19 20:16:20 | D | - Rotating model.layers.6 +24-11-19 20:16:20 | D | - Rotating model.layers.6.self_attn.q_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.6.self_attn.k_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.6.self_attn.v_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.6.self_attn.o_proj (out) +24-11-19 20:16:20 | D | - Rotating model.layers.6.self_attn.v_proj (out) +24-11-19 20:16:20 | D | - Rotating model.layers.6.self_attn.o_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.6.mlp.up_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.6.mlp.gate_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.6.mlp.down_proj (out) +24-11-19 20:16:20 | D | - Rotating model.layers.7 +24-11-19 20:16:20 | D | - Rotating model.layers.7.self_attn.q_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.7.self_attn.k_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.7.self_attn.v_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.7.self_attn.o_proj (out) +24-11-19 20:16:20 | D | - Rotating model.layers.7.self_attn.v_proj (out) +24-11-19 20:16:20 | D | - Rotating model.layers.7.self_attn.o_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.7.mlp.up_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.7.mlp.gate_proj (in) +24-11-19 20:16:20 | D | - Rotating model.layers.7.mlp.down_proj (out) +24-11-19 20:16:21 | D | - Rotating model.layers.8 +24-11-19 20:16:21 | D | - Rotating model.layers.8.self_attn.q_proj (in) +24-11-19 20:16:21 | D | - 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Rotating model.layers.30.self_attn.v_proj (out) +24-11-19 20:16:23 | D | - Rotating model.layers.30.self_attn.o_proj (in) +24-11-19 20:16:23 | D | - Rotating model.layers.30.mlp.up_proj (in) +24-11-19 20:16:23 | D | - Rotating model.layers.30.mlp.gate_proj (in) +24-11-19 20:16:23 | D | - Rotating model.layers.30.mlp.down_proj (out) +24-11-19 20:16:23 | D | - Rotating model.layers.31 +24-11-19 20:16:23 | D | - Rotating model.layers.31.self_attn.q_proj (in) +24-11-19 20:16:23 | D | - Rotating model.layers.31.self_attn.k_proj (in) +24-11-19 20:16:23 | D | - Rotating model.layers.31.self_attn.v_proj (in) +24-11-19 20:16:23 | D | - Rotating model.layers.31.self_attn.o_proj (out) +24-11-19 20:16:23 | D | - Rotating model.layers.31.self_attn.v_proj (out) +24-11-19 20:16:23 | D | - Rotating model.layers.31.self_attn.o_proj (in) +24-11-19 20:16:23 | D | - Rotating model.layers.31.mlp.up_proj (in) +24-11-19 20:16:23 | D | - Rotating model.layers.31.mlp.gate_proj (in) +24-11-19 20:16:23 | D | - Rotating model.layers.31.mlp.down_proj (out) +24-11-19 20:16:23 | D | - Rotating lm_head (in) +24-11-19 20:16:23 | I | - Linking rotation to runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.201608.RUNNING/model/rotation.pt +24-11-19 20:16:23 | I | * Development dtype is torch.float32 +24-11-19 20:16:23 | I | * Quantizing weights +24-11-19 20:16:23 | I | - Generating weight quantizer settings +24-11-19 20:16:23 | D | Starting new HTTPS connection (1): huggingface.co:443 +24-11-19 20:16:29 | D | Starting new HTTPS connection (2): huggingface.co:443 +24-11-19 20:16:42 | D | Starting new HTTPS connection (1): s3.amazonaws.com:443 +24-11-19 20:16:54 | W | Repo card metadata block was not found. Setting CardData to empty. +24-11-19 20:16:54 | D | Starting new HTTPS connection (3): huggingface.co:443 +24-11-19 20:17:06 | W | Using the latest cached version of the dataset since mit-han-lab/pile-val-backup couldn't be found on the Hugging Face Hub +24-11-19 20:17:06 | W | Found the latest cached dataset configuration 'default' at /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4 (last modified on Tue Oct 8 18:58:39 2024). +24-11-19 20:17:06 | D | Attempting to acquire lock 23438951254544 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:17:06 | D | Lock 23438951254544 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:17:06 | D | open file: /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4/dataset_info.json +24-11-19 20:17:06 | D | Attempting to release lock 23438951254544 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:17:06 | D | Lock 23438951254544 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:17:20 | D | - Quantizing layer model.layers.0 +24-11-19 20:17:20 | D | - Calibrating model.layers.0.self_attn.q_proj.weight +24-11-19 20:17:20 | D | + w: sint8 +24-11-19 20:17:20 | D | + x: None +24-11-19 20:17:20 | D | + y: None +24-11-19 20:17:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:17:20 | D | + finished parsing calibration arguments, ram usage: 38.5 +24-11-19 20:17:20 | D | + finished reseting calibrator, ram usage: 38.5 +24-11-19 20:17:21 | D | + finished calculating the original outputs, ram usage: 38.5 +24-11-19 20:17:21 | D | - range ratio = [ 1.0000] +24-11-19 20:17:21 | D | sum error = [ 0.1422] +24-11-19 20:17:21 | D | best error = [ 0.1422] +24-11-19 20:17:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:33 | D | sum error = [ 0.1421, 0.1442, 0.1479, 0.1561, 0.1705] +24-11-19 20:17:33 | D | best error = [ 0.1421, 0.1421, 0.1421, 0.1421, 0.1421] +24-11-19 20:17:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:33 | D | sum error = [ 0.1839, 0.2066, 0.2299, 0.2553, 0.2846] +24-11-19 20:17:33 | D | best error = [ 0.1421, 0.1421, 0.1421, 0.1421, 0.1421] +24-11-19 20:17:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:33 | D | sum error = [ 0.3305, 0.3739, 0.4225, 0.4834, 0.5537] +24-11-19 20:17:33 | D | best error = [ 0.1421, 0.1421, 0.1421, 0.1421, 0.1421] +24-11-19 20:17:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:33 | D | sum error = [ 0.6341, 0.7233, 0.8091, 0.9207, 1.0457] +24-11-19 20:17:33 | D | best error = [ 0.1421, 0.1421, 0.1421, 0.1421, 0.1421] +24-11-19 20:17:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:33 | D | sum error = [ 1.1665, 1.3184, 1.4767, 1.6646, 1.8676] +24-11-19 20:17:33 | D | best error = [ 0.1421, 0.1421, 0.1421, 0.1421, 0.1421] +24-11-19 20:17:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:33 | D | sum error = [ 2.0880, 2.3286, 2.5953, 2.8969, 3.2220] +24-11-19 20:17:33 | D | best error = [ 0.1421, 0.1421, 0.1421, 0.1421, 0.1421] +24-11-19 20:17:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:33 | D | sum error = [ 3.5778, 3.9578, 4.3828, 4.8501, 5.3466] +24-11-19 20:17:33 | D | best error = [ 0.1421, 0.1421, 0.1421, 0.1421, 0.1421] +24-11-19 20:17:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:33 | D | sum error = [ 5.8912, 6.4889, 7.1377, 7.8378, 8.5946] +24-11-19 20:17:33 | D | best error = [ 0.1421, 0.1421, 0.1421, 0.1421, 0.1421] +24-11-19 20:17:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:33 | D | sum error = [ 9.4211, 10.2941, 11.2388, 12.2649, 13.3677] +24-11-19 20:17:33 | D | best error = [ 0.1421, 0.1421, 0.1421, 0.1421, 0.1421] +24-11-19 20:17:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:33 | D | sum error = [ 14.5416, 15.7919, 17.1426, 18.5836, 20.1033] +24-11-19 20:17:33 | D | best error = [ 0.1421, 0.1421, 0.1421, 0.1421, 0.1421] +24-11-19 20:17:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:33 | D | sum error = [ 21.7355, 23.4416, 25.2821, 27.2392, 29.3136] +24-11-19 20:17:33 | D | best error = [ 0.1421, 0.1421, 0.1421, 0.1421, 0.1421] +24-11-19 20:17:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:33 | D | sum error = [ 31.4910, 33.8246, 36.2556, 38.8380, 41.5717] +24-11-19 20:17:33 | D | best error = [ 0.1421, 0.1421, 0.1421, 0.1421, 0.1421] +24-11-19 20:17:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:33 | D | sum error = [ 44.4471, 47.4761, 50.6536, 54.0172, 57.5154] +24-11-19 20:17:33 | D | best error = [ 0.1421, 0.1421, 0.1421, 0.1421, 0.1421] +24-11-19 20:17:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:33 | D | sum error = [ 61.2105, 65.0537, 69.1092, 73.3653, 77.8061] +24-11-19 20:17:33 | D | best error = [ 0.1421, 0.1421, 0.1421, 0.1421, 0.1421] +24-11-19 20:17:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:33 | D | sum error = [ 82.4584, 87.3412, 92.4192, 97.7520, 103.3197] +24-11-19 20:17:33 | D | best error = [ 0.1421, 0.1421, 0.1421, 0.1421, 0.1421] +24-11-19 20:17:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:33 | D | sum error = [ 109.1227, 115.1751, 121.5195, 128.1301, 135.0025] +24-11-19 20:17:33 | D | best error = [ 0.1421, 0.1421, 0.1421, 0.1421, 0.1421] +24-11-19 20:17:33 | D | + error = [0.1421] +24-11-19 20:17:34 | D | - Calibrating model.layers.0.self_attn.k_proj.weight +24-11-19 20:17:34 | D | + w: sint8 +24-11-19 20:17:34 | D | + x: None +24-11-19 20:17:34 | D | + y: None +24-11-19 20:17:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:17:34 | D | + finished parsing calibration arguments, ram usage: 38.5 +24-11-19 20:17:34 | D | + finished reseting calibrator, ram usage: 38.5 +24-11-19 20:17:34 | D | + finished calculating the original outputs, ram usage: 38.5 +24-11-19 20:17:34 | D | - range ratio = [ 1.0000] +24-11-19 20:17:34 | D | sum error = [ 0.1475] +24-11-19 20:17:34 | D | best error = [ 0.1475] +24-11-19 20:17:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:47 | D | sum error = [ 0.1501, 0.1562, 0.1575, 0.1563, 0.1705] +24-11-19 20:17:47 | D | best error = [ 0.1475, 0.1475, 0.1475, 0.1475, 0.1475] +24-11-19 20:17:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:47 | D | sum error = [ 0.1866, 0.2161, 0.2377, 0.2715, 0.2963] +24-11-19 20:17:47 | D | best error = [ 0.1475, 0.1475, 0.1475, 0.1475, 0.1475] +24-11-19 20:17:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:47 | D | sum error = [ 0.3447, 0.3597, 0.4186, 0.4764, 0.5412] +24-11-19 20:17:47 | D | best error = [ 0.1475, 0.1475, 0.1475, 0.1475, 0.1475] +24-11-19 20:17:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:47 | D | sum error = [ 0.6109, 0.6845, 0.7886, 0.8690, 0.9844] +24-11-19 20:17:47 | D | best error = [ 0.1475, 0.1475, 0.1475, 0.1475, 0.1475] +24-11-19 20:17:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:47 | D | sum error = [ 1.1269, 1.2490, 1.3703, 1.5572, 1.7039] +24-11-19 20:17:47 | D | best error = [ 0.1475, 0.1475, 0.1475, 0.1475, 0.1475] +24-11-19 20:17:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:47 | D | sum error = [ 1.9078, 2.1253, 2.3734, 2.6751, 2.9831] +24-11-19 20:17:47 | D | best error = [ 0.1475, 0.1475, 0.1475, 0.1475, 0.1475] +24-11-19 20:17:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:47 | D | sum error = [ 3.3177, 3.6907, 4.1139, 4.5674, 5.0646] +24-11-19 20:17:47 | D | best error = [ 0.1475, 0.1475, 0.1475, 0.1475, 0.1475] +24-11-19 20:17:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:47 | D | sum error = [ 5.5623, 6.1137, 6.7121, 7.3639, 8.0625] +24-11-19 20:17:47 | D | best error = [ 0.1475, 0.1475, 0.1475, 0.1475, 0.1475] +24-11-19 20:17:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:47 | D | sum error = [ 8.8260, 9.6103, 10.5211, 11.4757, 12.5123] +24-11-19 20:17:47 | D | best error = [ 0.1475, 0.1475, 0.1475, 0.1475, 0.1475] +24-11-19 20:17:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:47 | D | sum error = [ 13.6385, 14.7792, 16.0570, 17.3788, 18.7937] +24-11-19 20:17:47 | D | best error = [ 0.1475, 0.1475, 0.1475, 0.1475, 0.1475] +24-11-19 20:17:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:47 | D | sum error = [ 20.3172, 21.9228, 23.6172, 25.4239, 27.3262] +24-11-19 20:17:47 | D | best error = [ 0.1475, 0.1475, 0.1475, 0.1475, 0.1475] +24-11-19 20:17:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:47 | D | sum error = [ 29.3699, 31.4931, 33.7367, 36.1569, 38.6874] +24-11-19 20:17:47 | D | best error = [ 0.1475, 0.1475, 0.1475, 0.1475, 0.1475] +24-11-19 20:17:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:47 | D | sum error = [ 41.3844, 44.1983, 47.1579, 50.2985, 53.5820] +24-11-19 20:17:47 | D | best error = [ 0.1475, 0.1475, 0.1475, 0.1475, 0.1475] +24-11-19 20:17:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:47 | D | sum error = [ 57.0639, 60.7205, 64.5450, 68.5669, 72.8054] +24-11-19 20:17:47 | D | best error = [ 0.1475, 0.1475, 0.1475, 0.1475, 0.1475] +24-11-19 20:17:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:47 | D | sum error = [ 77.2499, 81.9084, 86.8228, 91.9509, 97.3517] +24-11-19 20:17:47 | D | best error = [ 0.1475, 0.1475, 0.1475, 0.1475, 0.1475] +24-11-19 20:17:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:47 | D | sum error = [ 102.9970, 108.9394, 115.1394, 121.6820, 128.4961] +24-11-19 20:17:47 | D | best error = [ 0.1475, 0.1475, 0.1475, 0.1475, 0.1475] +24-11-19 20:17:47 | D | + error = [0.1475] +24-11-19 20:17:47 | D | - Calibrating model.layers.0.self_attn.v_proj.weight +24-11-19 20:17:47 | D | + w: sint8 +24-11-19 20:17:47 | D | + x: None +24-11-19 20:17:47 | D | + y: None +24-11-19 20:17:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:17:47 | D | + finished parsing calibration arguments, ram usage: 38.5 +24-11-19 20:17:47 | D | + finished reseting calibrator, ram usage: 38.5 +24-11-19 20:17:47 | D | + finished calculating the original outputs, ram usage: 38.5 +24-11-19 20:17:47 | D | - range ratio = [ 1.0000] +24-11-19 20:17:47 | D | sum error = [ 0.1651] +24-11-19 20:17:47 | D | best error = [ 0.1651] +24-11-19 20:17:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:48 | D | sum error = [ 0.1647, 0.1643, 0.1650, 0.1667, 0.1701] +24-11-19 20:17:48 | D | best error = [ 0.1588, 0.1555, 0.1537, 0.1526, 0.1520] +24-11-19 20:17:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:48 | D | sum error = [ 0.1745, 0.1805, 0.1884, 0.1978, 0.2083] +24-11-19 20:17:48 | D | best error = [ 0.1518, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:17:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:48 | D | sum error = [ 0.2216, 0.2363, 0.2523, 0.2711, 0.2914] +24-11-19 20:17:48 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:17:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:48 | D | sum error = [ 0.3135, 0.3375, 0.3639, 0.3929, 0.4232] +24-11-19 20:17:48 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:17:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:48 | D | sum error = [ 0.4577, 0.4936, 0.5329, 0.5751, 0.6201] +24-11-19 20:17:48 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:17:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:48 | D | sum error = [ 0.6685, 0.7205, 0.7772, 0.8383, 0.9034] +24-11-19 20:17:48 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:17:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:48 | D | sum error = [ 0.9723, 1.0473, 1.1282, 1.2155, 1.3080] +24-11-19 20:17:48 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:17:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:48 | D | sum error = [ 1.4062, 1.5131, 1.6266, 1.7496, 1.8799] +24-11-19 20:17:48 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:17:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:48 | D | sum error = [ 2.0190, 2.1704, 2.3298, 2.5019, 2.6858] +24-11-19 20:17:48 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:17:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:48 | D | sum error = [ 2.8805, 3.0913, 3.3127, 3.5499, 3.8043] +24-11-19 20:17:48 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:17:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:48 | D | sum error = [ 4.0728, 4.3559, 4.6612, 4.9893, 5.3296] +24-11-19 20:17:48 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:17:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:48 | D | sum error = [ 5.6925, 6.0727, 6.4826, 6.9085, 7.3523] +24-11-19 20:17:48 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:17:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:48 | D | sum error = [ 7.8266, 8.3350, 8.8687, 9.4163, 9.9942] +24-11-19 20:17:48 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:17:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:48 | D | sum error = [ 10.6022, 11.2399, 11.9030, 12.5901, 13.3304] +24-11-19 20:17:48 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:17:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:48 | D | sum error = [ 14.0796, 14.8659, 15.6744, 16.5281, 17.3983] +24-11-19 20:17:48 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:17:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:48 | D | sum error = [ 18.3058, 19.2532, 20.2299, 21.2235, 22.2691] +24-11-19 20:17:48 | D | best error = [ 0.1517, 0.1517, 0.1517, 0.1517, 0.1517] +24-11-19 20:17:48 | D | + error = [0.1517] +24-11-19 20:17:48 | D | - Calibrating model.layers.0.self_attn.o_proj.weight +24-11-19 20:17:48 | D | + w: sint8 +24-11-19 20:17:48 | D | + x: None +24-11-19 20:17:48 | D | + y: None +24-11-19 20:17:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:17:48 | D | + finished parsing calibration arguments, ram usage: 38.5 +24-11-19 20:17:48 | D | + finished reseting calibrator, ram usage: 38.5 +24-11-19 20:17:48 | D | + finished calculating the original outputs, ram usage: 38.5 +24-11-19 20:17:48 | D | - range ratio = [ 1.0000] +24-11-19 20:17:48 | D | sum error = [ 0.1585] +24-11-19 20:17:48 | D | best error = [ 0.1585] +24-11-19 20:17:49 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:49 | D | sum error = [ 0.1591, 0.1617, 0.1624, 0.1693, 0.1741] +24-11-19 20:17:49 | D | best error = [ 0.1245, 0.1112, 0.1047, 0.1010, 0.0989] +24-11-19 20:17:49 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:49 | D | sum error = [ 0.1799, 0.1878, 0.2007, 0.2118, 0.2274] +24-11-19 20:17:49 | D | best error = [ 0.0979, 0.0974, 0.0971, 0.0969, 0.0968] +24-11-19 20:17:49 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:49 | D | sum error = [ 0.2414, 0.2578, 0.2752, 0.2941, 0.3122] +24-11-19 20:17:49 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:17:49 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:49 | D | sum error = [ 0.3338, 0.3557, 0.3783, 0.4041, 0.4267] +24-11-19 20:17:49 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:17:49 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:49 | D | sum error = [ 0.4520, 0.4809, 0.5094, 0.5403, 0.5700] +24-11-19 20:17:49 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:17:49 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:49 | D | sum error = [ 0.6029, 0.6375, 0.6712, 0.7089, 0.7474] +24-11-19 20:17:49 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:17:49 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:49 | D | sum error = [ 0.7874, 0.8281, 0.8726, 0.9187, 0.9661] +24-11-19 20:17:49 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:17:49 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:49 | D | sum error = [ 1.0138, 1.0659, 1.1194, 1.1759, 1.2330] +24-11-19 20:17:49 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:17:49 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:49 | D | sum error = [ 1.2957, 1.3596, 1.4265, 1.4964, 1.5682] +24-11-19 20:17:49 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:17:49 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:49 | D | sum error = [ 1.6440, 1.7248, 1.8089, 1.8963, 1.9871] +24-11-19 20:17:49 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:17:49 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:49 | D | sum error = [ 2.0834, 2.1848, 2.2893, 2.4001, 2.5167] +24-11-19 20:17:49 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:17:49 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:49 | D | sum error = [ 2.6383, 2.7670, 2.9031, 3.0450, 3.1961] +24-11-19 20:17:49 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:17:49 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:49 | D | sum error = [ 3.3544, 3.5217, 3.6982, 3.8857, 4.0827] +24-11-19 20:17:49 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:17:49 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:49 | D | sum error = [ 4.2919, 4.5125, 4.7458, 4.9922, 5.2527] +24-11-19 20:17:49 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:17:49 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:49 | D | sum error = [ 5.5272, 5.8189, 6.1279, 6.4531, 6.7987] +24-11-19 20:17:49 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:17:49 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:49 | D | sum error = [ 7.1634, 7.5504, 7.9601, 8.3933, 8.8510] +24-11-19 20:17:49 | D | best error = [ 0.0968, 0.0968, 0.0968, 0.0968, 0.0968] +24-11-19 20:17:49 | D | + error = [0.0968] +24-11-19 20:17:49 | D | - Calibrating model.layers.0.mlp.up_proj.weight +24-11-19 20:17:49 | D | + w: sint8 +24-11-19 20:17:49 | D | + x: None +24-11-19 20:17:49 | D | + y: None +24-11-19 20:17:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:17:49 | D | + finished parsing calibration arguments, ram usage: 38.5 +24-11-19 20:17:49 | D | + finished reseting calibrator, ram usage: 38.5 +24-11-19 20:17:49 | D | + finished calculating the original outputs, ram usage: 38.5 +24-11-19 20:17:49 | D | - range ratio = [ 1.0000] +24-11-19 20:17:49 | D | sum error = [ 1.1910] +24-11-19 20:17:49 | D | best error = [ 1.1910] +24-11-19 20:17:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:50 | D | sum error = [ 1.1895, 1.1912, 1.1942, 1.2135, 1.2268] +24-11-19 20:17:50 | D | best error = [ 0.9638, 0.8905, 0.8553, 0.8368, 0.8267] +24-11-19 20:17:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:50 | D | sum error = [ 1.2651, 1.3033, 1.3597, 1.4171, 1.4855] +24-11-19 20:17:50 | D | best error = [ 0.8211, 0.8183, 0.8168, 0.8163, 0.8160] +24-11-19 20:17:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:50 | D | sum error = [ 1.5698, 1.6663, 1.7880, 1.9086, 2.0377] +24-11-19 20:17:50 | D | best error = [ 0.8160, 0.8160, 0.8160, 0.8160, 0.8160] +24-11-19 20:17:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:50 | D | sum error = [ 2.1845, 2.3469, 2.5103, 2.6824, 2.8712] +24-11-19 20:17:50 | D | best error = [ 0.8160, 0.8160, 0.8160, 0.8160, 0.8160] +24-11-19 20:17:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:50 | D | sum error = [ 3.0858, 3.2954, 3.5312, 3.7806, 4.0482] +24-11-19 20:17:50 | D | best error = [ 0.8160, 0.8160, 0.8160, 0.8160, 0.8160] +24-11-19 20:17:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:50 | D | sum error = [ 4.3288, 4.6241, 4.9415, 5.2807, 5.6338] +24-11-19 20:17:50 | D | best error = [ 0.8160, 0.8160, 0.8160, 0.8160, 0.8160] +24-11-19 20:17:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:50 | D | sum error = [ 6.0131, 6.4133, 6.8432, 7.2954, 7.7747] +24-11-19 20:17:50 | D | best error = [ 0.8160, 0.8160, 0.8160, 0.8160, 0.8160] +24-11-19 20:17:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:50 | D | sum error = [ 8.2771, 8.8130, 9.3706, 9.9703, 10.5992] +24-11-19 20:17:50 | D | best error = [ 0.8160, 0.8160, 0.8160, 0.8160, 0.8160] +24-11-19 20:17:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:50 | D | sum error = [ 11.2583, 11.9630, 12.6926, 13.4808, 14.3066] +24-11-19 20:17:50 | D | best error = [ 0.8160, 0.8160, 0.8160, 0.8160, 0.8160] +24-11-19 20:17:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:50 | D | sum error = [ 15.1676, 16.0742, 17.0266, 18.0282, 19.0876] +24-11-19 20:17:50 | D | best error = [ 0.8160, 0.8160, 0.8160, 0.8160, 0.8160] +24-11-19 20:17:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:50 | D | sum error = [ 20.2075, 21.3659, 22.5881, 23.8657, 25.2197] +24-11-19 20:17:50 | D | best error = [ 0.8160, 0.8160, 0.8160, 0.8160, 0.8160] +24-11-19 20:17:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:50 | D | sum error = [ 26.6283, 28.1045, 29.6637, 31.2890, 32.9748] +24-11-19 20:17:50 | D | best error = [ 0.8160, 0.8160, 0.8160, 0.8160, 0.8160] +24-11-19 20:17:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:50 | D | sum error = [ 34.7493, 36.6032, 38.5300, 40.5537, 42.6552] +24-11-19 20:17:50 | D | best error = [ 0.8160, 0.8160, 0.8160, 0.8160, 0.8160] +24-11-19 20:17:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:50 | D | sum error = [ 44.8414, 47.1221, 49.4934, 51.9612, 54.5278] +24-11-19 20:17:50 | D | best error = [ 0.8160, 0.8160, 0.8160, 0.8160, 0.8160] +24-11-19 20:17:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:50 | D | sum error = [ 57.1925, 59.9486, 62.8100, 65.7719, 68.8488] +24-11-19 20:17:50 | D | best error = [ 0.8160, 0.8160, 0.8160, 0.8160, 0.8160] +24-11-19 20:17:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:50 | D | sum error = [ 72.0004, 75.2733, 78.6429, 82.1055, 85.6962] +24-11-19 20:17:50 | D | best error = [ 0.8160, 0.8160, 0.8160, 0.8160, 0.8160] +24-11-19 20:17:50 | D | + error = [0.8160] +24-11-19 20:17:50 | D | - Calibrating model.layers.0.mlp.gate_proj.weight +24-11-19 20:17:50 | D | + w: sint8 +24-11-19 20:17:50 | D | + x: None +24-11-19 20:17:50 | D | + y: None +24-11-19 20:17:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:17:50 | D | + finished parsing calibration arguments, ram usage: 38.5 +24-11-19 20:17:50 | D | + finished reseting calibrator, ram usage: 38.5 +24-11-19 20:17:50 | D | + finished calculating the original outputs, ram usage: 38.5 +24-11-19 20:17:50 | D | - range ratio = [ 1.0000] +24-11-19 20:17:50 | D | sum error = [ 1.2260] +24-11-19 20:17:50 | D | best error = [ 1.2260] +24-11-19 20:17:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:51 | D | sum error = [ 1.2229, 1.2239, 1.2226, 1.2215, 1.2576] +24-11-19 20:17:51 | D | best error = [ 0.9923, 0.9161, 0.8771, 0.8572, 0.8462] +24-11-19 20:17:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:51 | D | sum error = [ 1.2903, 1.3259, 1.3903, 1.4514, 1.5393] +24-11-19 20:17:51 | D | best error = [ 0.8404, 0.8373, 0.8359, 0.8355, 0.8353] +24-11-19 20:17:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:51 | D | sum error = [ 1.6162, 1.7165, 1.8486, 1.9557, 2.1089] +24-11-19 20:17:51 | D | best error = [ 0.8352, 0.8352, 0.8352, 0.8352, 0.8352] +24-11-19 20:17:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:51 | D | sum error = [ 2.2724, 2.4345, 2.6098, 2.8143, 3.0235] +24-11-19 20:17:51 | D | best error = [ 0.8352, 0.8352, 0.8352, 0.8352, 0.8352] +24-11-19 20:17:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:51 | D | sum error = [ 3.2488, 3.4874, 3.7394, 4.0346, 4.3167] +24-11-19 20:17:51 | D | best error = [ 0.8352, 0.8352, 0.8352, 0.8352, 0.8352] +24-11-19 20:17:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:51 | D | sum error = [ 4.6387, 4.9653, 5.3253, 5.7067, 6.1136] +24-11-19 20:17:51 | D | best error = [ 0.8352, 0.8352, 0.8352, 0.8352, 0.8352] +24-11-19 20:17:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:51 | D | sum error = [ 6.5312, 6.9941, 7.4755, 7.9900, 8.5412] +24-11-19 20:17:51 | D | best error = [ 0.8352, 0.8352, 0.8352, 0.8352, 0.8352] +24-11-19 20:17:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:51 | D | sum error = [ 9.1274, 9.7506, 10.3936, 11.0987, 11.8281] +24-11-19 20:17:51 | D | best error = [ 0.8352, 0.8352, 0.8352, 0.8352, 0.8352] +24-11-19 20:17:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:51 | D | sum error = [ 12.6095, 13.4420, 14.3234, 15.2498, 16.2556] +24-11-19 20:17:51 | D | best error = [ 0.8352, 0.8352, 0.8352, 0.8352, 0.8352] +24-11-19 20:17:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:51 | D | sum error = [ 17.3042, 18.4118, 19.5852, 20.8203, 22.1309] +24-11-19 20:17:51 | D | best error = [ 0.8352, 0.8352, 0.8352, 0.8352, 0.8352] +24-11-19 20:17:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:51 | D | sum error = [ 23.5212, 24.9773, 26.5301, 28.1434, 29.8595] +24-11-19 20:17:51 | D | best error = [ 0.8352, 0.8352, 0.8352, 0.8352, 0.8352] +24-11-19 20:17:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:51 | D | sum error = [ 31.6601, 33.5639, 35.5501, 37.6381, 39.8410] +24-11-19 20:17:51 | D | best error = [ 0.8352, 0.8352, 0.8352, 0.8352, 0.8352] +24-11-19 20:17:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:51 | D | sum error = [ 42.1554, 44.5896, 47.1309, 49.7893, 52.5747] +24-11-19 20:17:51 | D | best error = [ 0.8352, 0.8352, 0.8352, 0.8352, 0.8352] +24-11-19 20:17:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:51 | D | sum error = [ 55.4885, 58.5542, 61.7176, 65.0343, 68.5021] +24-11-19 20:17:51 | D | best error = [ 0.8352, 0.8352, 0.8352, 0.8352, 0.8352] +24-11-19 20:17:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:51 | D | sum error = [ 72.0880, 75.8163, 79.6826, 83.6827, 87.8501] +24-11-19 20:17:51 | D | best error = [ 0.8352, 0.8352, 0.8352, 0.8352, 0.8352] +24-11-19 20:17:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:51 | D | sum error = [ 92.1096, 96.5678, 101.1452, 105.8576, 110.7467] +24-11-19 20:17:51 | D | best error = [ 0.8352, 0.8352, 0.8352, 0.8352, 0.8352] +24-11-19 20:17:51 | D | + error = [0.8352] +24-11-19 20:17:51 | D | - Calibrating model.layers.0.mlp.down_proj.weight +24-11-19 20:17:51 | D | + w: sint8 +24-11-19 20:17:51 | D | + x: None +24-11-19 20:17:51 | D | + y: None +24-11-19 20:17:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:17:51 | D | + finished parsing calibration arguments, ram usage: 38.5 +24-11-19 20:17:51 | D | + finished reseting calibrator, ram usage: 38.5 +24-11-19 20:17:52 | D | + finished calculating the original outputs, ram usage: 38.5 +24-11-19 20:17:52 | D | - range ratio = [ 1.0000] +24-11-19 20:17:52 | D | sum error = [ 0.1969] +24-11-19 20:17:52 | D | best error = [ 0.1969] +24-11-19 20:17:53 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:53 | D | sum error = [ 0.1958, 0.1934, 0.1939, 0.1917, 0.1926] +24-11-19 20:17:53 | D | best error = [ 0.1723, 0.1613, 0.1548, 0.1501, 0.1468] +24-11-19 20:17:53 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:53 | D | sum error = [ 0.1940, 0.1927, 0.1943, 0.1959, 0.2003] +24-11-19 20:17:53 | D | best error = [ 0.1439, 0.1416, 0.1397, 0.1383, 0.1370] +24-11-19 20:17:53 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:53 | D | sum error = [ 0.2050, 0.2100, 0.2159, 0.2226, 0.2311] +24-11-19 20:17:53 | D | best error = [ 0.1359, 0.1351, 0.1343, 0.1336, 0.1331] +24-11-19 20:17:53 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:53 | D | sum error = [ 0.2425, 0.2537, 0.2670, 0.2824, 0.2989] +24-11-19 20:17:53 | D | best error = [ 0.1327, 0.1324, 0.1321, 0.1319, 0.1318] +24-11-19 20:17:53 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:53 | D | sum error = [ 0.3182, 0.3375, 0.3597, 0.3831, 0.4069] +24-11-19 20:17:53 | D | best error = [ 0.1317, 0.1316, 0.1316, 0.1315, 0.1315] +24-11-19 20:17:53 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:53 | D | sum error = [ 0.4339, 0.4634, 0.4937, 0.5284, 0.5645] +24-11-19 20:17:53 | D | best error = [ 0.1315, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 20:17:53 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:53 | D | sum error = [ 0.6028, 0.6435, 0.6870, 0.7323, 0.7808] +24-11-19 20:17:53 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 20:17:53 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:53 | D | sum error = [ 0.8318, 0.8867, 0.9467, 1.0089, 1.0749] +24-11-19 20:17:53 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 20:17:53 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:53 | D | sum error = [ 1.1466, 1.2227, 1.3037, 1.3909, 1.4844] +24-11-19 20:17:53 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 20:17:53 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:53 | D | sum error = [ 1.5837, 1.6905, 1.8034, 1.9263, 2.0549] +24-11-19 20:17:53 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 20:17:53 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:53 | D | sum error = [ 2.1937, 2.3409, 2.4986, 2.6667, 2.8447] +24-11-19 20:17:53 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 20:17:53 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:53 | D | sum error = [ 3.0351, 3.2381, 3.4543, 3.6836, 3.9284] +24-11-19 20:17:53 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 20:17:53 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:53 | D | sum error = [ 4.1887, 4.4645, 4.7576, 5.0692, 5.3995] +24-11-19 20:17:53 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 20:17:53 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:53 | D | sum error = [ 5.7502, 6.1222, 6.5159, 6.9326, 7.3720] +24-11-19 20:17:53 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 20:17:53 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:53 | D | sum error = [ 7.8355, 8.3248, 8.8397, 9.3799, 9.9484] +24-11-19 20:17:53 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 20:17:53 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:53 | D | sum error = [ 10.5436, 11.1683, 11.8217, 12.5044, 13.2162] +24-11-19 20:17:53 | D | best error = [ 0.1314, 0.1314, 0.1314, 0.1314, 0.1314] +24-11-19 20:17:53 | D | + error = [0.1314] +24-11-19 20:17:53 | D | - Quantizing model.layers.0.self_attn.q_proj.weight +24-11-19 20:17:54 | D | - Quantizing model.layers.0.self_attn.k_proj.weight +24-11-19 20:17:55 | D | - Quantizing model.layers.0.self_attn.v_proj.weight +24-11-19 20:17:55 | D | - Quantizing model.layers.0.self_attn.o_proj.weight +24-11-19 20:17:56 | D | - Quantizing model.layers.0.mlp.up_proj.weight +24-11-19 20:17:57 | D | - Quantizing model.layers.0.mlp.gate_proj.weight +24-11-19 20:17:58 | D | - Quantizing model.layers.0.mlp.down_proj.weight +24-11-19 20:18:06 | D | - Quantizing layer model.layers.1 +24-11-19 20:18:06 | D | - Calibrating model.layers.1.self_attn.q_proj.weight +24-11-19 20:18:06 | D | + w: sint8 +24-11-19 20:18:06 | D | + x: None +24-11-19 20:18:06 | D | + y: None +24-11-19 20:18:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:18:06 | D | + finished parsing calibration arguments, ram usage: 38.5 +24-11-19 20:18:06 | D | + finished reseting calibrator, ram usage: 38.5 +24-11-19 20:18:06 | D | + finished calculating the original outputs, ram usage: 38.5 +24-11-19 20:18:07 | D | - range ratio = [ 1.0000] +24-11-19 20:18:07 | D | sum error = [ 0.4068] +24-11-19 20:18:07 | D | best error = [ 0.4068] +24-11-19 20:18:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:19 | D | sum error = [ 0.4122, 0.4204, 0.4213, 0.4316, 0.4565] +24-11-19 20:18:19 | D | best error = [ 0.4068, 0.4068, 0.4068, 0.4068, 0.4068] +24-11-19 20:18:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:19 | D | sum error = [ 0.4467, 0.4989, 0.4833, 0.5379, 0.5503] +24-11-19 20:18:19 | D | best error = [ 0.4068, 0.4068, 0.4068, 0.4068, 0.4068] +24-11-19 20:18:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:19 | D | sum error = [ 0.6514, 0.6724, 0.7812, 0.8227, 0.9073] +24-11-19 20:18:19 | D | best error = [ 0.4068, 0.4068, 0.4068, 0.4068, 0.4068] +24-11-19 20:18:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:19 | D | sum error = [ 1.0179, 1.1311, 1.2177, 1.3942, 1.5536] +24-11-19 20:18:19 | D | best error = [ 0.4068, 0.4068, 0.4068, 0.4068, 0.4068] +24-11-19 20:18:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:19 | D | sum error = [ 1.7598, 1.9443, 2.1749, 2.4236, 2.7113] +24-11-19 20:18:19 | D | best error = [ 0.4068, 0.4068, 0.4068, 0.4068, 0.4068] +24-11-19 20:18:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:19 | D | sum error = [ 3.0237, 3.3738, 3.7460, 4.1343, 4.5931] +24-11-19 20:18:19 | D | best error = [ 0.4068, 0.4068, 0.4068, 0.4068, 0.4068] +24-11-19 20:18:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:19 | D | sum error = [ 5.1654, 5.6836, 6.3331, 7.0070, 7.7333] +24-11-19 20:18:19 | D | best error = [ 0.4068, 0.4068, 0.4068, 0.4068, 0.4068] +24-11-19 20:18:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:19 | D | sum error = [ 8.5065, 9.3425, 10.2917, 11.3050, 12.4009] +24-11-19 20:18:19 | D | best error = [ 0.4068, 0.4068, 0.4068, 0.4068, 0.4068] +24-11-19 20:18:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:19 | D | sum error = [ 13.5805, 14.8649, 16.2394, 17.8015, 19.4301] +24-11-19 20:18:19 | D | best error = [ 0.4068, 0.4068, 0.4068, 0.4068, 0.4068] +24-11-19 20:18:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:19 | D | sum error = [ 21.1964, 23.0443, 25.1421, 27.3187, 29.6635] +24-11-19 20:18:19 | D | best error = [ 0.4068, 0.4068, 0.4068, 0.4068, 0.4068] +24-11-19 20:18:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:19 | D | sum error = [ 32.1928, 34.8959, 37.8014, 40.8682, 44.0766] +24-11-19 20:18:19 | D | best error = [ 0.4068, 0.4068, 0.4068, 0.4068, 0.4068] +24-11-19 20:18:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:19 | D | sum error = [ 47.5773, 51.2454, 55.1418, 59.3484, 63.7415] +24-11-19 20:18:19 | D | best error = [ 0.4068, 0.4068, 0.4068, 0.4068, 0.4068] +24-11-19 20:18:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:19 | D | sum error = [ 68.4288, 73.3176, 78.5219, 84.0232, 89.8461] +24-11-19 20:18:19 | D | best error = [ 0.4068, 0.4068, 0.4068, 0.4068, 0.4068] +24-11-19 20:18:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:19 | D | sum error = [ 95.8220, 102.2540, 109.0527, 116.0769, 123.5617] +24-11-19 20:18:19 | D | best error = [ 0.4068, 0.4068, 0.4068, 0.4068, 0.4068] +24-11-19 20:18:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:19 | D | sum error = [ 131.4197, 139.5976, 148.0433, 156.8853, 166.2906] +24-11-19 20:18:19 | D | best error = [ 0.4068, 0.4068, 0.4068, 0.4068, 0.4068] +24-11-19 20:18:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:19 | D | sum error = [ 175.9499, 185.9845, 196.4307, 207.0913, 218.3932] +24-11-19 20:18:19 | D | best error = [ 0.4068, 0.4068, 0.4068, 0.4068, 0.4068] +24-11-19 20:18:19 | D | + error = [0.4068] +24-11-19 20:18:19 | D | - Calibrating model.layers.1.self_attn.k_proj.weight +24-11-19 20:18:19 | D | + w: sint8 +24-11-19 20:18:19 | D | + x: None +24-11-19 20:18:19 | D | + y: None +24-11-19 20:18:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:18:19 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:18:19 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:18:19 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:18:20 | D | - range ratio = [ 1.0000] +24-11-19 20:18:20 | D | sum error = [ 0.4773] +24-11-19 20:18:20 | D | best error = [ 0.4773] +24-11-19 20:18:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:32 | D | sum error = [ 0.4992, 0.5072, 0.5106, 0.5035, 0.5172] +24-11-19 20:18:32 | D | best error = [ 0.4773, 0.4773, 0.4773, 0.4773, 0.4773] +24-11-19 20:18:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:32 | D | sum error = [ 0.5979, 0.5783, 0.6169, 0.6233, 0.6780] +24-11-19 20:18:32 | D | best error = [ 0.4773, 0.4773, 0.4773, 0.4773, 0.4773] +24-11-19 20:18:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:32 | D | sum error = [ 0.7196, 0.7860, 0.8346, 0.9674, 1.1212] +24-11-19 20:18:32 | D | best error = [ 0.4773, 0.4773, 0.4773, 0.4773, 0.4773] +24-11-19 20:18:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:32 | D | sum error = [ 1.2147, 1.3382, 1.4721, 1.6283, 1.7866] +24-11-19 20:18:32 | D | best error = [ 0.4773, 0.4773, 0.4773, 0.4773, 0.4773] +24-11-19 20:18:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:32 | D | sum error = [ 2.0017, 2.2464, 2.4587, 2.7786, 2.9980] +24-11-19 20:18:32 | D | best error = [ 0.4773, 0.4773, 0.4773, 0.4773, 0.4773] +24-11-19 20:18:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:32 | D | sum error = [ 3.3731, 3.7175, 4.1497, 4.6676, 5.0750] +24-11-19 20:18:32 | D | best error = [ 0.4773, 0.4773, 0.4773, 0.4773, 0.4773] +24-11-19 20:18:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:32 | D | sum error = [ 5.6147, 6.1996, 6.8615, 7.5286, 8.3052] +24-11-19 20:18:32 | D | best error = [ 0.4773, 0.4773, 0.4773, 0.4773, 0.4773] +24-11-19 20:18:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:32 | D | sum error = [ 9.1349, 10.0396, 11.0267, 12.0536, 13.1880] +24-11-19 20:18:32 | D | best error = [ 0.4773, 0.4773, 0.4773, 0.4773, 0.4773] +24-11-19 20:18:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:32 | D | sum error = [ 14.4531, 15.7982, 17.2496, 18.8385, 20.5552] +24-11-19 20:18:32 | D | best error = [ 0.4773, 0.4773, 0.4773, 0.4773, 0.4773] +24-11-19 20:18:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:32 | D | sum error = [ 22.3912, 24.2949, 26.3320, 28.5225, 30.9711] +24-11-19 20:18:32 | D | best error = [ 0.4773, 0.4773, 0.4773, 0.4773, 0.4773] +24-11-19 20:18:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:32 | D | sum error = [ 33.5339, 36.2997, 39.2265, 42.3671, 45.7222] +24-11-19 20:18:32 | D | best error = [ 0.4773, 0.4773, 0.4773, 0.4773, 0.4773] +24-11-19 20:18:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:32 | D | sum error = [ 49.2395, 52.9928, 56.9856, 61.2649, 65.7235] +24-11-19 20:18:32 | D | best error = [ 0.4773, 0.4773, 0.4773, 0.4773, 0.4773] +24-11-19 20:18:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:32 | D | sum error = [ 70.4348, 75.4174, 80.7551, 86.3108, 92.2363] +24-11-19 20:18:32 | D | best error = [ 0.4773, 0.4773, 0.4773, 0.4773, 0.4773] +24-11-19 20:18:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:32 | D | sum error = [ 98.3371, 104.7923, 111.6115, 118.6619, 126.0659] +24-11-19 20:18:32 | D | best error = [ 0.4773, 0.4773, 0.4773, 0.4773, 0.4773] +24-11-19 20:18:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:32 | D | sum error = [ 133.8572, 142.0117, 150.4756, 159.2863, 168.5092] +24-11-19 20:18:32 | D | best error = [ 0.4773, 0.4773, 0.4773, 0.4773, 0.4773] +24-11-19 20:18:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:32 | D | sum error = [ 178.1354, 187.9794, 198.4249, 209.1354, 220.2330] +24-11-19 20:18:32 | D | best error = [ 0.4773, 0.4773, 0.4773, 0.4773, 0.4773] +24-11-19 20:18:32 | D | + error = [0.4773] +24-11-19 20:18:32 | D | - Calibrating model.layers.1.self_attn.v_proj.weight +24-11-19 20:18:32 | D | + w: sint8 +24-11-19 20:18:32 | D | + x: None +24-11-19 20:18:32 | D | + y: None +24-11-19 20:18:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:32 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:18:32 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:18:32 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:18:32 | D | - range ratio = [ 1.0000] +24-11-19 20:18:32 | D | sum error = [ 0.5679] +24-11-19 20:18:32 | D | best error = [ 0.5679] +24-11-19 20:18:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:33 | D | sum error = [ 0.5627, 0.5602, 0.5617, 0.5667, 0.5797] +24-11-19 20:18:33 | D | best error = [ 0.4618, 0.4274, 0.4105, 0.4014, 0.3963] +24-11-19 20:18:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:33 | D | sum error = [ 0.6023, 0.6175, 0.6359, 0.6753, 0.7081] +24-11-19 20:18:33 | D | best error = [ 0.3935, 0.3918, 0.3911, 0.3907, 0.3906] +24-11-19 20:18:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:33 | D | sum error = [ 0.7568, 0.7966, 0.8521, 0.9004, 0.9724] +24-11-19 20:18:33 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 20:18:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:33 | D | sum error = [ 1.0363, 1.1098, 1.1928, 1.2775, 1.3714] +24-11-19 20:18:33 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 20:18:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:33 | D | sum error = [ 1.4677, 1.5680, 1.6871, 1.8023, 1.9202] +24-11-19 20:18:33 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 20:18:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:33 | D | sum error = [ 2.0587, 2.1934, 2.3487, 2.5043, 2.6680] +24-11-19 20:18:33 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 20:18:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:33 | D | sum error = [ 2.8503, 3.0405, 3.2322, 3.4504, 3.6688] +24-11-19 20:18:33 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 20:18:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:33 | D | sum error = [ 3.9027, 4.1470, 4.4098, 4.6826, 4.9729] +24-11-19 20:18:33 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 20:18:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:33 | D | sum error = [ 5.2767, 5.6024, 5.9407, 6.2933, 6.6711] +24-11-19 20:18:33 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 20:18:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:33 | D | sum error = [ 7.0604, 7.4788, 7.9150, 8.3674, 8.8420] +24-11-19 20:18:33 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 20:18:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:33 | D | sum error = [ 9.3425, 9.8636, 10.4107, 10.9836, 11.5830] +24-11-19 20:18:33 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 20:18:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:33 | D | sum error = [ 12.2013, 12.8571, 13.5404, 14.2493, 15.0003] +24-11-19 20:18:33 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 20:18:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:33 | D | sum error = [ 15.7840, 16.6028, 17.4596, 18.3438, 19.2688] +24-11-19 20:18:33 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 20:18:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:33 | D | sum error = [ 20.2356, 21.2378, 22.2769, 23.3616, 24.4909] +24-11-19 20:18:33 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 20:18:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:33 | D | sum error = [ 25.6676, 26.8771, 28.1364, 29.4455, 30.8037] +24-11-19 20:18:33 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 20:18:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:33 | D | sum error = [ 32.1979, 33.6414, 35.1324, 36.6645, 38.2527] +24-11-19 20:18:33 | D | best error = [ 0.3905, 0.3905, 0.3905, 0.3905, 0.3905] +24-11-19 20:18:33 | D | + error = [0.3905] +24-11-19 20:18:33 | D | - Calibrating model.layers.1.self_attn.o_proj.weight +24-11-19 20:18:33 | D | + w: sint8 +24-11-19 20:18:33 | D | + x: None +24-11-19 20:18:33 | D | + y: None +24-11-19 20:18:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:33 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:18:33 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:18:33 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:18:33 | D | - range ratio = [ 1.0000] +24-11-19 20:18:33 | D | sum error = [ 0.1966] +24-11-19 20:18:33 | D | best error = [ 0.1966] +24-11-19 20:18:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:34 | D | sum error = [ 0.1936, 0.1951, 0.1969, 0.1994, 0.2043] +24-11-19 20:18:34 | D | best error = [ 0.1709, 0.1608, 0.1561, 0.1534, 0.1524] +24-11-19 20:18:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:34 | D | sum error = [ 0.2113, 0.2203, 0.2320, 0.2441, 0.2573] +24-11-19 20:18:34 | D | best error = [ 0.1518, 0.1514, 0.1514, 0.1513, 0.1513] +24-11-19 20:18:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:34 | D | sum error = [ 0.2714, 0.2889, 0.3084, 0.3294, 0.3507] +24-11-19 20:18:34 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:18:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:34 | D | sum error = [ 0.3744, 0.3999, 0.4273, 0.4563, 0.4857] +24-11-19 20:18:34 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:18:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:34 | D | sum error = [ 0.5169, 0.5507, 0.5858, 0.6230, 0.6620] +24-11-19 20:18:34 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:18:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:34 | D | sum error = [ 0.7030, 0.7464, 0.7909, 0.8374, 0.8871] +24-11-19 20:18:34 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:18:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:34 | D | sum error = [ 0.9382, 0.9923, 1.0491, 1.1076, 1.1698] +24-11-19 20:18:34 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:18:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:34 | D | sum error = [ 1.2346, 1.3029, 1.3743, 1.4495, 1.5282] +24-11-19 20:18:34 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:18:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:34 | D | sum error = [ 1.6112, 1.6968, 1.7874, 1.8830, 1.9819] +24-11-19 20:18:34 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:18:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:34 | D | sum error = [ 2.0868, 2.1955, 2.3100, 2.4311, 2.5569] +24-11-19 20:18:34 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:18:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:34 | D | sum error = [ 2.6893, 2.8286, 2.9733, 3.1273, 3.2880] +24-11-19 20:18:34 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:18:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:34 | D | sum error = [ 3.4566, 3.6338, 3.8203, 4.0150, 4.2215] +24-11-19 20:18:34 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:18:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:34 | D | sum error = [ 4.4377, 4.6650, 4.9038, 5.1568, 5.4232] +24-11-19 20:18:34 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:18:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:34 | D | sum error = [ 5.7040, 6.0007, 6.3128, 6.6435, 6.9921] +24-11-19 20:18:34 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:18:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:34 | D | sum error = [ 7.3616, 7.7526, 8.1673, 8.6064, 9.0706] +24-11-19 20:18:34 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:18:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:34 | D | sum error = [ 9.5635, 10.0870, 10.6436, 11.2360, 11.8670] +24-11-19 20:18:34 | D | best error = [ 0.1513, 0.1513, 0.1513, 0.1513, 0.1513] +24-11-19 20:18:34 | D | + error = [0.1513] +24-11-19 20:18:34 | D | - Calibrating model.layers.1.mlp.up_proj.weight +24-11-19 20:18:34 | D | + w: sint8 +24-11-19 20:18:34 | D | + x: None +24-11-19 20:18:34 | D | + y: None +24-11-19 20:18:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:34 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:18:34 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:18:34 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:18:34 | D | - range ratio = [ 1.0000] +24-11-19 20:18:34 | D | sum error = [ 2.3733] +24-11-19 20:18:34 | D | best error = [ 2.3733] +24-11-19 20:18:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:35 | D | sum error = [ 2.3522, 2.3463, 2.3536, 2.3893, 2.4148] +24-11-19 20:18:35 | D | best error = [ 1.9923, 1.8627, 1.7961, 1.7621, 1.7428] +24-11-19 20:18:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:35 | D | sum error = [ 2.4724, 2.5623, 2.6752, 2.8130, 2.9391] +24-11-19 20:18:35 | D | best error = [ 1.7314, 1.7262, 1.7237, 1.7225, 1.7220] +24-11-19 20:18:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:35 | D | sum error = [ 3.1117, 3.3104, 3.5158, 3.7411, 4.0346] +24-11-19 20:18:35 | D | best error = [ 1.7219, 1.7218, 1.7218, 1.7218, 1.7218] +24-11-19 20:18:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:35 | D | sum error = [ 4.3122, 4.5981, 4.9314, 5.2790, 5.6705] +24-11-19 20:18:35 | D | best error = [ 1.7218, 1.7218, 1.7218, 1.7218, 1.7218] +24-11-19 20:18:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:35 | D | sum error = [ 6.0540, 6.4773, 6.9410, 7.4388, 7.9501] +24-11-19 20:18:35 | D | best error = [ 1.7218, 1.7218, 1.7218, 1.7218, 1.7218] +24-11-19 20:18:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:35 | D | sum error = [ 8.4715, 9.0514, 9.6647, 10.3107, 10.9737] +24-11-19 20:18:35 | D | best error = [ 1.7218, 1.7218, 1.7218, 1.7218, 1.7218] +24-11-19 20:18:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:35 | D | sum error = [ 11.7019, 12.4486, 13.2453, 14.0829, 14.9801] +24-11-19 20:18:35 | D | best error = [ 1.7218, 1.7218, 1.7218, 1.7218, 1.7218] +24-11-19 20:18:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:35 | D | sum error = [ 15.8852, 16.8652, 17.8842, 18.9895, 20.1116] +24-11-19 20:18:35 | D | best error = [ 1.7218, 1.7218, 1.7218, 1.7218, 1.7218] +24-11-19 20:18:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:35 | D | sum error = [ 21.3123, 22.5705, 23.8770, 25.2674, 26.7103] +24-11-19 20:18:35 | D | best error = [ 1.7218, 1.7218, 1.7218, 1.7218, 1.7218] +24-11-19 20:18:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:35 | D | sum error = [ 28.2221, 29.7952, 31.4464, 33.1871, 35.0006] +24-11-19 20:18:35 | D | best error = [ 1.7218, 1.7218, 1.7218, 1.7218, 1.7218] +24-11-19 20:18:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:35 | D | sum error = [ 36.8947, 38.8599, 40.9379, 43.0947, 45.3369] +24-11-19 20:18:35 | D | best error = [ 1.7218, 1.7218, 1.7218, 1.7218, 1.7218] +24-11-19 20:18:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:35 | D | sum error = [ 47.6846, 50.1149, 52.6515, 55.3010, 58.0441] +24-11-19 20:18:35 | D | best error = [ 1.7218, 1.7218, 1.7218, 1.7218, 1.7218] +24-11-19 20:18:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:35 | D | sum error = [ 60.8783, 63.8618, 66.9531, 70.1749, 73.5013] +24-11-19 20:18:35 | D | best error = [ 1.7218, 1.7218, 1.7218, 1.7218, 1.7218] +24-11-19 20:18:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:35 | D | sum error = [ 76.9786, 80.5568, 84.2890, 88.1219, 92.1074] +24-11-19 20:18:35 | D | best error = [ 1.7218, 1.7218, 1.7218, 1.7218, 1.7218] +24-11-19 20:18:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:35 | D | sum error = [ 96.2286, 100.4895, 104.8843, 109.4242, 114.0871] +24-11-19 20:18:35 | D | best error = [ 1.7218, 1.7218, 1.7218, 1.7218, 1.7218] +24-11-19 20:18:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:35 | D | sum error = [ 118.9159, 123.8637, 129.0033, 134.2499, 139.6843] +24-11-19 20:18:35 | D | best error = [ 1.7218, 1.7218, 1.7218, 1.7218, 1.7218] +24-11-19 20:18:35 | D | + error = [1.7218] +24-11-19 20:18:35 | D | - Calibrating model.layers.1.mlp.gate_proj.weight +24-11-19 20:18:35 | D | + w: sint8 +24-11-19 20:18:35 | D | + x: None +24-11-19 20:18:35 | D | + y: None +24-11-19 20:18:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:35 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:18:35 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:18:35 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:18:35 | D | - range ratio = [ 1.0000] +24-11-19 20:18:35 | D | sum error = [ 2.5171] +24-11-19 20:18:35 | D | best error = [ 2.5171] +24-11-19 20:18:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:36 | D | sum error = [ 2.5044, 2.4911, 2.5113, 2.5238, 2.5651] +24-11-19 20:18:36 | D | best error = [ 2.1194, 1.9758, 1.9097, 1.8737, 1.8524] +24-11-19 20:18:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:36 | D | sum error = [ 2.6447, 2.7294, 2.8284, 2.9743, 3.1263] +24-11-19 20:18:36 | D | best error = [ 1.8398, 1.8346, 1.8317, 1.8306, 1.8302] +24-11-19 20:18:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:36 | D | sum error = [ 3.3029, 3.5052, 3.7391, 3.9765, 4.2589] +24-11-19 20:18:36 | D | best error = [ 1.8301, 1.8301, 1.8301, 1.8301, 1.8301] +24-11-19 20:18:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:36 | D | sum error = [ 4.5569, 4.8874, 5.2471, 5.6110, 6.0022] +24-11-19 20:18:36 | D | best error = [ 1.8301, 1.8301, 1.8301, 1.8301, 1.8301] +24-11-19 20:18:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:36 | D | sum error = [ 6.4580, 6.9174, 7.3972, 7.9277, 8.4843] +24-11-19 20:18:36 | D | best error = [ 1.8301, 1.8301, 1.8301, 1.8301, 1.8301] +24-11-19 20:18:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:36 | D | sum error = [ 9.0743, 9.7165, 10.3630, 11.0837, 11.8085] +24-11-19 20:18:36 | D | best error = [ 1.8301, 1.8301, 1.8301, 1.8301, 1.8301] +24-11-19 20:18:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:36 | D | sum error = [ 12.6124, 13.4360, 14.3180, 15.2529, 16.2459] +24-11-19 20:18:36 | D | best error = [ 1.8301, 1.8301, 1.8301, 1.8301, 1.8301] +24-11-19 20:18:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:36 | D | sum error = [ 17.2982, 18.4071, 19.5815, 20.8358, 22.1454] +24-11-19 20:18:36 | D | best error = [ 1.8301, 1.8301, 1.8301, 1.8301, 1.8301] +24-11-19 20:18:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:36 | D | sum error = [ 23.5438, 25.0065, 26.5545, 28.2100, 29.9587] +24-11-19 20:18:36 | D | best error = [ 1.8301, 1.8301, 1.8301, 1.8301, 1.8301] +24-11-19 20:18:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:36 | D | sum error = [ 31.7854, 33.7523, 35.8232, 37.9810, 40.2586] +24-11-19 20:18:36 | D | best error = [ 1.8301, 1.8301, 1.8301, 1.8301, 1.8301] +24-11-19 20:18:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:36 | D | sum error = [ 42.6687, 45.1889, 47.8715, 50.7205, 53.6646] +24-11-19 20:18:36 | D | best error = [ 1.8301, 1.8301, 1.8301, 1.8301, 1.8301] +24-11-19 20:18:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:36 | D | sum error = [ 56.8387, 60.1517, 63.6212, 67.2632, 71.1772] +24-11-19 20:18:36 | D | best error = [ 1.8301, 1.8301, 1.8301, 1.8301, 1.8301] +24-11-19 20:18:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:36 | D | sum error = [ 75.2333, 79.4744, 83.9595, 88.6296, 93.5316] +24-11-19 20:18:36 | D | best error = [ 1.8301, 1.8301, 1.8301, 1.8301, 1.8301] +24-11-19 20:18:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:36 | D | sum error = [ 98.6175, 103.9944, 109.5519, 115.3628, 121.4230] +24-11-19 20:18:36 | D | best error = [ 1.8301, 1.8301, 1.8301, 1.8301, 1.8301] +24-11-19 20:18:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:36 | D | sum error = [ 127.7369, 134.2977, 141.0524, 148.0409, 155.2980] +24-11-19 20:18:36 | D | best error = [ 1.8301, 1.8301, 1.8301, 1.8301, 1.8301] +24-11-19 20:18:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:36 | D | sum error = [ 162.7739, 170.4927, 178.4476, 186.6735, 195.1869] +24-11-19 20:18:36 | D | best error = [ 1.8301, 1.8301, 1.8301, 1.8301, 1.8301] +24-11-19 20:18:36 | D | + error = [1.8301] +24-11-19 20:18:36 | D | - Calibrating model.layers.1.mlp.down_proj.weight +24-11-19 20:18:36 | D | + w: sint8 +24-11-19 20:18:36 | D | + x: None +24-11-19 20:18:36 | D | + y: None +24-11-19 20:18:36 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:36 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:18:36 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:18:37 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:18:37 | D | - range ratio = [ 1.0000] +24-11-19 20:18:37 | D | sum error = [ 35.6320] +24-11-19 20:18:37 | D | best error = [ 35.6320] +24-11-19 20:18:38 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:38 | D | sum error = [ 35.3511, 34.8754, 34.3995, 33.9112, 33.7600] +24-11-19 20:18:38 | D | best error = [ 24.5926, 16.9711, 12.2855, 9.6147, 8.2009] +24-11-19 20:18:38 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:38 | D | sum error = [ 33.7399, 32.7834, 32.4180, 32.3361, 32.1470] +24-11-19 20:18:38 | D | best error = [ 7.2422, 6.5753, 6.0846, 5.7005, 5.3987] +24-11-19 20:18:38 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:38 | D | sum error = [ 31.5283, 31.0955, 30.7076, 30.5502, 30.1326] +24-11-19 20:18:38 | D | best error = [ 5.1254, 4.8846, 4.6653, 4.4839, 4.3405] +24-11-19 20:18:38 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:38 | D | sum error = [ 29.6275, 29.4128, 29.1681, 28.7119, 28.5492] +24-11-19 20:18:38 | D | best error = [ 4.2192, 4.0945, 3.9747, 3.8872, 3.8282] +24-11-19 20:18:38 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:38 | D | sum error = [ 28.1529, 27.5770, 27.3720, 27.5769, 26.6896] +24-11-19 20:18:38 | D | best error = [ 3.7461, 3.6258, 3.5312, 3.4492, 3.3742] +24-11-19 20:18:38 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:38 | D | sum error = [ 26.3857, 26.1276, 25.5775, 25.3857, 25.8769] +24-11-19 20:18:38 | D | best error = [ 3.2822, 3.2025, 3.1335, 3.0695, 3.0041] +24-11-19 20:18:38 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:38 | D | sum error = [ 26.4873, 29.6406, 35.1177, 42.8668, 53.5283] +24-11-19 20:18:38 | D | best error = [ 2.9428, 2.8759, 2.7943, 2.7520, 2.7051] +24-11-19 20:18:38 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:38 | D | sum error = [ 67.2991, 85.3664, 107.8596, 135.9093, 169.3932] +24-11-19 20:18:38 | D | best error = [ 2.6692, 2.6205, 2.5820, 2.5404, 2.5192] +24-11-19 20:18:38 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:38 | D | sum error = [ 208.1840, 252.5016, 302.6367, 358.4903, 420.0702] +24-11-19 20:18:38 | D | best error = [ 2.4884, 2.4736, 2.4527, 2.4430, 2.4317] +24-11-19 20:18:38 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:38 | D | sum error = [ 487.0364, 559.1607, 635.7500, 716.9787, 802.3769] +24-11-19 20:18:38 | D | best error = [ 2.4272, 2.4130, 2.4071, 2.4012, 2.3982] +24-11-19 20:18:38 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:38 | D | sum error = [ 891.1881, 983.4428, 1078.5478, 1176.2204, 1276.0566] +24-11-19 20:18:38 | D | best error = [ 2.3949, 2.3933, 2.3903, 2.3897, 2.3894] +24-11-19 20:18:38 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:38 | D | sum error = [ 1377.9471, 1481.3876, 1586.2271, 1692.3104, 1799.3833] +24-11-19 20:18:38 | D | best error = [ 2.3894, 2.3887, 2.3887, 2.3884, 2.3884] +24-11-19 20:18:38 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:38 | D | sum error = [ 1907.1944, 2015.7856, 2124.9322, 2234.5814, 2344.7102] +24-11-19 20:18:38 | D | best error = [ 2.3884, 2.3884, 2.3884, 2.3884, 2.3884] +24-11-19 20:18:38 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:38 | D | sum error = [ 2455.1212, 2565.8722, 2676.9970, 2788.3534, 2899.6911] +24-11-19 20:18:38 | D | best error = [ 2.3884, 2.3884, 2.3884, 2.3884, 2.3884] +24-11-19 20:18:38 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:38 | D | sum error = [ 3011.2883, 3123.0453, 3234.9657, 3346.9564, 3459.0757] +24-11-19 20:18:38 | D | best error = [ 2.3884, 2.3884, 2.3884, 2.3884, 2.3884] +24-11-19 20:18:38 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:38 | D | sum error = [ 3571.2147, 3683.4736, 3795.8280, 3908.2698, 4020.8745] +24-11-19 20:18:38 | D | best error = [ 2.3884, 2.3884, 2.3884, 2.3884, 2.3884] +24-11-19 20:18:38 | D | + error = [2.3884] +24-11-19 20:18:38 | D | - Quantizing model.layers.1.self_attn.q_proj.weight +24-11-19 20:18:38 | D | - Quantizing model.layers.1.self_attn.k_proj.weight +24-11-19 20:18:39 | D | - Quantizing model.layers.1.self_attn.v_proj.weight +24-11-19 20:18:40 | D | - Quantizing model.layers.1.self_attn.o_proj.weight +24-11-19 20:18:41 | D | - Quantizing model.layers.1.mlp.up_proj.weight +24-11-19 20:18:42 | D | - Quantizing model.layers.1.mlp.gate_proj.weight +24-11-19 20:18:43 | D | - Quantizing model.layers.1.mlp.down_proj.weight +24-11-19 20:18:51 | D | - Quantizing layer model.layers.2 +24-11-19 20:18:51 | D | - Calibrating model.layers.2.self_attn.q_proj.weight +24-11-19 20:18:51 | D | + w: sint8 +24-11-19 20:18:51 | D | + x: None +24-11-19 20:18:51 | D | + y: None +24-11-19 20:18:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:18:51 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:18:51 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:18:51 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:18:51 | D | - range ratio = [ 1.0000] +24-11-19 20:18:51 | D | sum error = [ 1.0825] +24-11-19 20:18:51 | D | best error = [ 1.0825] +24-11-19 20:19:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:04 | D | sum error = [ 1.1602, 1.1086, 1.1228, 1.1229, 1.1714] +24-11-19 20:19:04 | D | best error = [ 1.0825, 1.0825, 1.0825, 1.0825, 1.0825] +24-11-19 20:19:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:04 | D | sum error = [ 1.2267, 1.2372, 1.3027, 1.4601, 1.5561] +24-11-19 20:19:04 | D | best error = [ 1.0825, 1.0825, 1.0825, 1.0825, 1.0825] +24-11-19 20:19:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:04 | D | sum error = [ 1.7145, 1.7951, 2.0212, 2.2637, 2.5378] +24-11-19 20:19:04 | D | best error = [ 1.0825, 1.0825, 1.0825, 1.0825, 1.0825] +24-11-19 20:19:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:04 | D | sum error = [ 2.8376, 3.0952, 3.5145, 3.9483, 4.3604] +24-11-19 20:19:04 | D | best error = [ 1.0825, 1.0825, 1.0825, 1.0825, 1.0825] +24-11-19 20:19:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:04 | D | sum error = [ 4.8543, 5.4070, 6.0155, 6.6616, 7.5266] +24-11-19 20:19:04 | D | best error = [ 1.0825, 1.0825, 1.0825, 1.0825, 1.0825] +24-11-19 20:19:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:04 | D | sum error = [ 8.4743, 9.5180, 10.5613, 11.7535, 13.2273] +24-11-19 20:19:04 | D | best error = [ 1.0825, 1.0825, 1.0825, 1.0825, 1.0825] +24-11-19 20:19:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:04 | D | sum error = [ 14.5267, 16.1881, 18.0941, 20.1354, 22.1573] +24-11-19 20:19:04 | D | best error = [ 1.0825, 1.0825, 1.0825, 1.0825, 1.0825] +24-11-19 20:19:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:04 | D | sum error = [ 24.6048, 27.0535, 29.9065, 32.8858, 36.1552] +24-11-19 20:19:04 | D | best error = [ 1.0825, 1.0825, 1.0825, 1.0825, 1.0825] +24-11-19 20:19:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:04 | D | sum error = [ 39.8324, 43.5545, 47.9178, 52.6520, 57.6552] +24-11-19 20:19:04 | D | best error = [ 1.0825, 1.0825, 1.0825, 1.0825, 1.0825] +24-11-19 20:19:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:04 | D | sum error = [ 63.1075, 69.2248, 75.7354, 82.8391, 90.3738] +24-11-19 20:19:04 | D | best error = [ 1.0825, 1.0825, 1.0825, 1.0825, 1.0825] +24-11-19 20:19:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:04 | D | sum error = [ 98.7845, 107.8417, 117.5070, 128.2616, 139.6671] +24-11-19 20:19:04 | D | best error = [ 1.0825, 1.0825, 1.0825, 1.0825, 1.0825] +24-11-19 20:19:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:04 | D | sum error = [ 152.3019, 165.3809, 179.9043, 195.7468, 212.8671] +24-11-19 20:19:04 | D | best error = [ 1.0825, 1.0825, 1.0825, 1.0825, 1.0825] +24-11-19 20:19:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:04 | D | sum error = [ 231.0642, 251.2525, 273.1370, 296.9427, 322.4959] +24-11-19 20:19:04 | D | best error = [ 1.0825, 1.0825, 1.0825, 1.0825, 1.0825] +24-11-19 20:19:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:04 | D | sum error = [ 350.5782, 381.0973, 413.7322, 449.2763, 487.5229] +24-11-19 20:19:04 | D | best error = [ 1.0825, 1.0825, 1.0825, 1.0825, 1.0825] +24-11-19 20:19:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:04 | D | sum error = [ 528.7281, 572.3925, 618.7795, 668.1375, 721.1067] +24-11-19 20:19:04 | D | best error = [ 1.0825, 1.0825, 1.0825, 1.0825, 1.0825] +24-11-19 20:19:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:04 | D | sum error = [ 775.3300, 832.6199, 891.0751, 951.1278, 1011.1006] +24-11-19 20:19:04 | D | best error = [ 1.0825, 1.0825, 1.0825, 1.0825, 1.0825] +24-11-19 20:19:04 | D | + error = [1.0825] +24-11-19 20:19:04 | D | - Calibrating model.layers.2.self_attn.k_proj.weight +24-11-19 20:19:04 | D | + w: sint8 +24-11-19 20:19:04 | D | + x: None +24-11-19 20:19:04 | D | + y: None +24-11-19 20:19:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:19:04 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:19:04 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:19:04 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:19:04 | D | - range ratio = [ 1.0000] +24-11-19 20:19:04 | D | sum error = [ 1.1711] +24-11-19 20:19:04 | D | best error = [ 1.1711] +24-11-19 20:19:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:17 | D | sum error = [ 1.1756, 1.1166, 1.2182, 1.3476, 1.3235] +24-11-19 20:19:17 | D | best error = [ 1.1711, 1.1166, 1.1166, 1.1166, 1.1166] +24-11-19 20:19:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:17 | D | sum error = [ 1.2796, 1.4818, 1.4356, 1.7180, 1.8937] +24-11-19 20:19:17 | D | best error = [ 1.1166, 1.1166, 1.1166, 1.1166, 1.1166] +24-11-19 20:19:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:17 | D | sum error = [ 2.1699, 2.1095, 2.3661, 2.8676, 3.2033] +24-11-19 20:19:17 | D | best error = [ 1.1166, 1.1166, 1.1166, 1.1166, 1.1166] +24-11-19 20:19:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:17 | D | sum error = [ 3.4666, 3.7809, 4.2237, 4.8796, 5.2180] +24-11-19 20:19:17 | D | best error = [ 1.1166, 1.1166, 1.1166, 1.1166, 1.1166] +24-11-19 20:19:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:17 | D | sum error = [ 5.9981, 6.7548, 7.5301, 8.3089, 9.0424] +24-11-19 20:19:17 | D | best error = [ 1.1166, 1.1166, 1.1166, 1.1166, 1.1166] +24-11-19 20:19:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:17 | D | sum error = [ 10.2552, 11.2328, 12.7231, 13.7779, 15.1333] +24-11-19 20:19:17 | D | best error = [ 1.1166, 1.1166, 1.1166, 1.1166, 1.1166] +24-11-19 20:19:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:17 | D | sum error = [ 16.7862, 18.2745, 20.1945, 22.3066, 24.3340] +24-11-19 20:19:17 | D | best error = [ 1.1166, 1.1166, 1.1166, 1.1166, 1.1166] +24-11-19 20:19:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:17 | D | sum error = [ 26.5564, 29.0563, 31.9220, 34.8639, 38.2446] +24-11-19 20:19:17 | D | best error = [ 1.1166, 1.1166, 1.1166, 1.1166, 1.1166] +24-11-19 20:19:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:17 | D | sum error = [ 41.8914, 45.7804, 50.0947, 54.7232, 59.9507] +24-11-19 20:19:17 | D | best error = [ 1.1166, 1.1166, 1.1166, 1.1166, 1.1166] +24-11-19 20:19:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:17 | D | sum error = [ 65.6129, 71.2773, 77.5686, 84.4353, 91.8176] +24-11-19 20:19:17 | D | best error = [ 1.1166, 1.1166, 1.1166, 1.1166, 1.1166] +24-11-19 20:19:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:17 | D | sum error = [ 99.7300, 108.6249, 118.1394, 128.6895, 139.9775] +24-11-19 20:19:17 | D | best error = [ 1.1166, 1.1166, 1.1166, 1.1166, 1.1166] +24-11-19 20:19:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:17 | D | sum error = [ 152.4131, 165.9339, 180.3456, 196.4975, 213.8776] +24-11-19 20:19:17 | D | best error = [ 1.1166, 1.1166, 1.1166, 1.1166, 1.1166] +24-11-19 20:19:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:17 | D | sum error = [ 232.6323, 254.0010, 277.1950, 301.8362, 329.4309] +24-11-19 20:19:17 | D | best error = [ 1.1166, 1.1166, 1.1166, 1.1166, 1.1166] +24-11-19 20:19:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:17 | D | sum error = [ 358.8541, 390.2421, 424.9054, 461.8178, 501.2176] +24-11-19 20:19:17 | D | best error = [ 1.1166, 1.1166, 1.1166, 1.1166, 1.1166] +24-11-19 20:19:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:17 | D | sum error = [ 544.0438, 589.2553, 637.3062, 687.7087, 741.4171] +24-11-19 20:19:17 | D | best error = [ 1.1166, 1.1166, 1.1166, 1.1166, 1.1166] +24-11-19 20:19:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:17 | D | sum error = [ 796.8344, 854.9906, 913.9815, 973.6476, 1034.6463] +24-11-19 20:19:17 | D | best error = [ 1.1166, 1.1166, 1.1166, 1.1166, 1.1166] +24-11-19 20:19:17 | D | + error = [1.1166] +24-11-19 20:19:17 | D | - Calibrating model.layers.2.self_attn.v_proj.weight +24-11-19 20:19:17 | D | + w: sint8 +24-11-19 20:19:17 | D | + x: None +24-11-19 20:19:17 | D | + y: None +24-11-19 20:19:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:17 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:19:17 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:19:17 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:19:17 | D | - range ratio = [ 1.0000] +24-11-19 20:19:17 | D | sum error = [ 2.0518] +24-11-19 20:19:17 | D | best error = [ 2.0518] +24-11-19 20:19:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:17 | D | sum error = [ 2.0428, 2.0470, 2.0600, 2.0770, 2.0982] +24-11-19 20:19:17 | D | best error = [ 1.7778, 1.6933, 1.6466, 1.6217, 1.6046] +24-11-19 20:19:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:17 | D | sum error = [ 2.1663, 2.2377, 2.3241, 2.4423, 2.5628] +24-11-19 20:19:17 | D | best error = [ 1.5972, 1.5938, 1.5924, 1.5919, 1.5918] +24-11-19 20:19:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:17 | D | sum error = [ 2.7116, 2.8707, 3.0460, 3.2626, 3.4878] +24-11-19 20:19:17 | D | best error = [ 1.5917, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:19:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:17 | D | sum error = [ 3.7456, 3.9866, 4.2996, 4.6109, 4.9223] +24-11-19 20:19:17 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:19:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:17 | D | sum error = [ 5.2914, 5.6457, 6.0480, 6.4653, 6.9388] +24-11-19 20:19:17 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:19:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:17 | D | sum error = [ 7.3983, 7.9156, 8.4591, 9.0374, 9.6407] +24-11-19 20:19:17 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:19:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:17 | D | sum error = [ 10.2681, 10.9364, 11.6455, 12.4072, 13.1856] +24-11-19 20:19:17 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:19:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:17 | D | sum error = [ 14.0041, 14.8780, 15.7847, 16.7573, 17.7786] +24-11-19 20:19:17 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:19:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:17 | D | sum error = [ 18.8374, 19.9709, 21.1399, 22.3712, 23.6713] +24-11-19 20:19:17 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:19:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:17 | D | sum error = [ 25.0139, 26.4377, 27.9180, 29.4699, 31.0839] +24-11-19 20:19:17 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:19:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:17 | D | sum error = [ 32.8063, 34.5869, 36.4450, 38.4119, 40.4424] +24-11-19 20:19:17 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:19:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:17 | D | sum error = [ 42.5647, 44.8028, 47.1064, 49.5259, 52.0410] +24-11-19 20:19:17 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:19:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:17 | D | sum error = [ 54.6609, 57.3863, 60.2241, 63.1847, 66.2502] +24-11-19 20:19:17 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:19:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:17 | D | sum error = [ 69.4448, 72.7742, 76.2060, 79.7879, 83.4853] +24-11-19 20:19:17 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:19:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:17 | D | sum error = [ 87.3100, 91.2705, 95.3589, 99.5913, 103.9503] +24-11-19 20:19:17 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:19:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:17 | D | sum error = [ 108.4415, 113.0834, 117.8526, 122.7668, 127.8255] +24-11-19 20:19:17 | D | best error = [ 1.5916, 1.5916, 1.5916, 1.5916, 1.5916] +24-11-19 20:19:17 | D | + error = [1.5916] +24-11-19 20:19:18 | D | - Calibrating model.layers.2.self_attn.o_proj.weight +24-11-19 20:19:18 | D | + w: sint8 +24-11-19 20:19:18 | D | + x: None +24-11-19 20:19:18 | D | + y: None +24-11-19 20:19:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:18 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:19:18 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:19:18 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:19:18 | D | - range ratio = [ 1.0000] +24-11-19 20:19:18 | D | sum error = [ 0.2226] +24-11-19 20:19:18 | D | best error = [ 0.2226] +24-11-19 20:19:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:18 | D | sum error = [ 0.2207, 0.2208, 0.2203, 0.2222, 0.2259] +24-11-19 20:19:18 | D | best error = [ 0.2102, 0.2049, 0.2017, 0.1997, 0.1986] +24-11-19 20:19:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:18 | D | sum error = [ 0.2312, 0.2389, 0.2467, 0.2577, 0.2701] +24-11-19 20:19:18 | D | best error = [ 0.1979, 0.1975, 0.1973, 0.1971, 0.1971] +24-11-19 20:19:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:18 | D | sum error = [ 0.2839, 0.3014, 0.3196, 0.3396, 0.3621] +24-11-19 20:19:18 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:19:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:18 | D | sum error = [ 0.3866, 0.4135, 0.4423, 0.4729, 0.5061] +24-11-19 20:19:18 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:19:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:18 | D | sum error = [ 0.5425, 0.5791, 0.6202, 0.6632, 0.7087] +24-11-19 20:19:18 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:19:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:18 | D | sum error = [ 0.7567, 0.8087, 0.8633, 0.9206, 0.9825] +24-11-19 20:19:18 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:19:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:18 | D | sum error = [ 1.0467, 1.1150, 1.1868, 1.2626, 1.3432] +24-11-19 20:19:18 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:19:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:18 | D | sum error = [ 1.4282, 1.5177, 1.6117, 1.7113, 1.8167] +24-11-19 20:19:18 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:19:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:18 | D | sum error = [ 1.9275, 2.0449, 2.1675, 2.2973, 2.4335] +24-11-19 20:19:18 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:19:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:18 | D | sum error = [ 2.5771, 2.7281, 2.8877, 3.0551, 3.2309] +24-11-19 20:19:18 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:19:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:18 | D | sum error = [ 3.4161, 3.6106, 3.8152, 4.0300, 4.2554] +24-11-19 20:19:18 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:19:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:18 | D | sum error = [ 4.4921, 4.7402, 5.0003, 5.2728, 5.5581] +24-11-19 20:19:18 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:19:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:18 | D | sum error = [ 5.8573, 6.1693, 6.4965, 6.8388, 7.1957] +24-11-19 20:19:18 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:19:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:18 | D | sum error = [ 7.5687, 7.9573, 8.3629, 8.7848, 9.2240] +24-11-19 20:19:18 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:19:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:18 | D | sum error = [ 9.6808, 10.1561, 10.6495, 11.1612, 11.6920] +24-11-19 20:19:18 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:19:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:18 | D | sum error = [ 12.2418, 12.8109, 13.3988, 14.0069, 14.6342] +24-11-19 20:19:18 | D | best error = [ 0.1970, 0.1970, 0.1970, 0.1970, 0.1970] +24-11-19 20:19:18 | D | + error = [0.1970] +24-11-19 20:19:18 | D | - Calibrating model.layers.2.mlp.up_proj.weight +24-11-19 20:19:18 | D | + w: sint8 +24-11-19 20:19:18 | D | + x: None +24-11-19 20:19:18 | D | + y: None +24-11-19 20:19:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:18 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:19:18 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:19:19 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:19:19 | D | - range ratio = [ 1.0000] +24-11-19 20:19:19 | D | sum error = [ 3.1968] +24-11-19 20:19:19 | D | best error = [ 3.1968] +24-11-19 20:19:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:20 | D | sum error = [ 3.1533, 3.1476, 3.1666, 3.2118, 3.2477] +24-11-19 20:19:20 | D | best error = [ 2.7835, 2.6499, 2.5824, 2.5458, 2.5265] +24-11-19 20:19:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:20 | D | sum error = [ 3.3500, 3.4577, 3.5933, 3.7504, 3.9512] +24-11-19 20:19:20 | D | best error = [ 2.5164, 2.5115, 2.5095, 2.5086, 2.5082] +24-11-19 20:19:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:20 | D | sum error = [ 4.1672, 4.4456, 4.7134, 5.0279, 5.3794] +24-11-19 20:19:20 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 20:19:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:20 | D | sum error = [ 5.7417, 6.1622, 6.5841, 7.0703, 7.5751] +24-11-19 20:19:20 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 20:19:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:20 | D | sum error = [ 8.1089, 8.6999, 9.3043, 9.9432, 10.6336] +24-11-19 20:19:20 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 20:19:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:20 | D | sum error = [ 11.3737, 12.1380, 12.9408, 13.7994, 14.6897] +24-11-19 20:19:20 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 20:19:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:20 | D | sum error = [ 15.6535, 16.6402, 17.6946, 18.8005, 19.9683] +24-11-19 20:19:20 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 20:19:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:20 | D | sum error = [ 21.1920, 22.4579, 23.8180, 25.2213, 26.7065] +24-11-19 20:19:20 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 20:19:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:20 | D | sum error = [ 28.2312, 29.8538, 31.5542, 33.3140, 35.1813] +24-11-19 20:19:20 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 20:19:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:20 | D | sum error = [ 37.1128, 39.1327, 41.2538, 43.4532, 45.7434] +24-11-19 20:19:20 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 20:19:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:20 | D | sum error = [ 48.1403, 50.6152, 53.1979, 55.8861, 58.6692] +24-11-19 20:19:20 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 20:19:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:20 | D | sum error = [ 61.5596, 64.5517, 67.6625, 70.8793, 74.2016] +24-11-19 20:19:20 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 20:19:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:20 | D | sum error = [ 77.6479, 81.1930, 84.8692, 88.6605, 92.5806] +24-11-19 20:19:20 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 20:19:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:20 | D | sum error = [ 96.6193, 100.7903, 105.0719, 109.5037, 114.0416] +24-11-19 20:19:20 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 20:19:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:20 | D | sum error = [ 118.7227, 123.5451, 128.4909, 133.5861, 138.8211] +24-11-19 20:19:20 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 20:19:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:20 | D | sum error = [ 144.1896, 149.7120, 155.3756, 161.1953, 167.1643] +24-11-19 20:19:20 | D | best error = [ 2.5081, 2.5081, 2.5081, 2.5081, 2.5081] +24-11-19 20:19:20 | D | + error = [2.5081] +24-11-19 20:19:20 | D | - Calibrating model.layers.2.mlp.gate_proj.weight +24-11-19 20:19:20 | D | + w: sint8 +24-11-19 20:19:20 | D | + x: None +24-11-19 20:19:20 | D | + y: None +24-11-19 20:19:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:20 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:19:20 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:19:20 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:19:20 | D | - range ratio = [ 1.0000] +24-11-19 20:19:20 | D | sum error = [ 3.4186] +24-11-19 20:19:20 | D | best error = [ 3.4186] +24-11-19 20:19:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:21 | D | sum error = [ 3.3799, 3.3824, 3.3910, 3.4286, 3.4884] +24-11-19 20:19:21 | D | best error = [ 2.9815, 2.8406, 2.7686, 2.7290, 2.7085] +24-11-19 20:19:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:21 | D | sum error = [ 3.5885, 3.7104, 3.8656, 4.0461, 4.2538] +24-11-19 20:19:21 | D | best error = [ 2.6974, 2.6922, 2.6898, 2.6892, 2.6889] +24-11-19 20:19:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:21 | D | sum error = [ 4.5257, 4.7819, 5.1150, 5.4591, 5.8247] +24-11-19 20:19:21 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:19:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:21 | D | sum error = [ 6.2415, 6.6822, 7.1540, 7.6607, 8.2202] +24-11-19 20:19:21 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:19:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:21 | D | sum error = [ 8.8206, 9.4340, 10.1079, 10.8005, 11.5487] +24-11-19 20:19:21 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:19:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:21 | D | sum error = [ 12.3449, 13.1998, 14.0725, 15.0102, 16.0109] +24-11-19 20:19:21 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:19:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:21 | D | sum error = [ 17.0550, 18.1557, 19.3210, 20.5681, 21.8576] +24-11-19 20:19:21 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:19:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:21 | D | sum error = [ 23.2260, 24.6841, 26.2144, 27.7874, 29.4699] +24-11-19 20:19:21 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:19:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:21 | D | sum error = [ 31.2357, 33.0859, 35.0171, 37.0538, 39.2042] +24-11-19 20:19:21 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:19:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:21 | D | sum error = [ 41.4298, 43.7790, 46.2292, 48.7986, 51.4889] +24-11-19 20:19:21 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:19:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:21 | D | sum error = [ 54.3018, 57.2514, 60.3222, 63.5162, 66.8768] +24-11-19 20:19:21 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:19:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:21 | D | sum error = [ 70.3456, 73.9640, 77.7370, 81.6775, 85.7600] +24-11-19 20:19:21 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:19:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:21 | D | sum error = [ 90.0122, 94.4263, 99.0174, 103.7748, 108.7124] +24-11-19 20:19:21 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:19:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:21 | D | sum error = [ 113.8399, 119.1549, 124.6344, 130.3323, 136.1976] +24-11-19 20:19:21 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:19:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:21 | D | sum error = [ 142.2845, 148.5750, 155.0699, 161.7798, 168.7000] +24-11-19 20:19:21 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:19:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:21 | D | sum error = [ 175.8385, 183.1922, 190.7575, 198.5536, 206.5657] +24-11-19 20:19:21 | D | best error = [ 2.6889, 2.6889, 2.6889, 2.6889, 2.6889] +24-11-19 20:19:21 | D | + error = [2.6889] +24-11-19 20:19:21 | D | - Calibrating model.layers.2.mlp.down_proj.weight +24-11-19 20:19:21 | D | + w: sint8 +24-11-19 20:19:21 | D | + x: None +24-11-19 20:19:21 | D | + y: None +24-11-19 20:19:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:21 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:19:21 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:19:21 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:19:21 | D | - range ratio = [ 1.0000] +24-11-19 20:19:21 | D | sum error = [ 0.3957] +24-11-19 20:19:21 | D | best error = [ 0.3957] +24-11-19 20:19:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:22 | D | sum error = [ 0.3912, 0.3878, 0.3860, 0.3855, 0.3843] +24-11-19 20:19:22 | D | best error = [ 0.3664, 0.3536, 0.3464, 0.3413, 0.3375] +24-11-19 20:19:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:22 | D | sum error = [ 0.3880, 0.3912, 0.3959, 0.4065, 0.4171] +24-11-19 20:19:22 | D | best error = [ 0.3346, 0.3323, 0.3308, 0.3298, 0.3291] +24-11-19 20:19:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:22 | D | sum error = [ 0.4312, 0.4470, 0.4664, 0.4876, 0.5117] +24-11-19 20:19:22 | D | best error = [ 0.3286, 0.3282, 0.3281, 0.3279, 0.3278] +24-11-19 20:19:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:22 | D | sum error = [ 0.5384, 0.5696, 0.6036, 0.6399, 0.6820] +24-11-19 20:19:22 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 20:19:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:22 | D | sum error = [ 0.7260, 0.7756, 0.8306, 0.8901, 0.9548] +24-11-19 20:19:22 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 20:19:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:22 | D | sum error = [ 1.0240, 1.0991, 1.1798, 1.2661, 1.3589] +24-11-19 20:19:22 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 20:19:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:22 | D | sum error = [ 1.4588, 1.5642, 1.6774, 1.7984, 1.9267] +24-11-19 20:19:22 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 20:19:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:22 | D | sum error = [ 2.0641, 2.2098, 2.3643, 2.5275, 2.6999] +24-11-19 20:19:22 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 20:19:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:22 | D | sum error = [ 2.8833, 3.0772, 3.2832, 3.4997, 3.7283] +24-11-19 20:19:22 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 20:19:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:22 | D | sum error = [ 3.9702, 4.2243, 4.4910, 4.7718, 5.0657] +24-11-19 20:19:22 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 20:19:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:22 | D | sum error = [ 5.3740, 5.6978, 6.0373, 6.3944, 6.7682] +24-11-19 20:19:22 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 20:19:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:22 | D | sum error = [ 7.1598, 7.5694, 7.9975, 8.4451, 8.9126] +24-11-19 20:19:22 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 20:19:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:22 | D | sum error = [ 9.4005, 9.9089, 10.4391, 10.9916, 11.5666] +24-11-19 20:19:22 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 20:19:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:22 | D | sum error = [ 12.1645, 12.7855, 13.4307, 14.1017, 14.7945] +24-11-19 20:19:22 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 20:19:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:22 | D | sum error = [ 15.5141, 16.2597, 17.0314, 17.8297, 18.6555] +24-11-19 20:19:22 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 20:19:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:22 | D | sum error = [ 19.5093, 20.3906, 21.3014, 22.2411, 23.2100] +24-11-19 20:19:22 | D | best error = [ 0.3277, 0.3277, 0.3277, 0.3277, 0.3277] +24-11-19 20:19:22 | D | + error = [0.3277] +24-11-19 20:19:22 | D | - Quantizing model.layers.2.self_attn.q_proj.weight +24-11-19 20:19:23 | D | - Quantizing model.layers.2.self_attn.k_proj.weight +24-11-19 20:19:24 | D | - Quantizing model.layers.2.self_attn.v_proj.weight +24-11-19 20:19:25 | D | - Quantizing model.layers.2.self_attn.o_proj.weight +24-11-19 20:19:25 | D | - Quantizing model.layers.2.mlp.up_proj.weight +24-11-19 20:19:26 | D | - Quantizing model.layers.2.mlp.gate_proj.weight +24-11-19 20:19:27 | D | - Quantizing model.layers.2.mlp.down_proj.weight +24-11-19 20:19:35 | D | - Quantizing layer model.layers.3 +24-11-19 20:19:35 | D | - Calibrating model.layers.3.self_attn.q_proj.weight +24-11-19 20:19:35 | D | + w: sint8 +24-11-19 20:19:35 | D | + x: None +24-11-19 20:19:35 | D | + y: None +24-11-19 20:19:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:19:35 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:19:35 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:19:35 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:19:36 | D | - range ratio = [ 1.0000] +24-11-19 20:19:36 | D | sum error = [ 2.0287] +24-11-19 20:19:36 | D | best error = [ 2.0287] +24-11-19 20:19:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:48 | D | sum error = [ 2.1425, 2.0662, 2.0784, 2.0949, 2.1328] +24-11-19 20:19:48 | D | best error = [ 2.0287, 2.0287, 2.0287, 2.0287, 2.0287] +24-11-19 20:19:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:48 | D | sum error = [ 2.1051, 2.2540, 2.3397, 2.4320, 2.6689] +24-11-19 20:19:48 | D | best error = [ 2.0287, 2.0287, 2.0287, 2.0287, 2.0287] +24-11-19 20:19:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:48 | D | sum error = [ 2.7371, 3.0791, 3.2678, 3.6901, 4.0746] +24-11-19 20:19:48 | D | best error = [ 2.0287, 2.0287, 2.0287, 2.0287, 2.0287] +24-11-19 20:19:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:48 | D | sum error = [ 4.4616, 4.6567, 5.1327, 5.7340, 6.1604] +24-11-19 20:19:48 | D | best error = [ 2.0287, 2.0287, 2.0287, 2.0287, 2.0287] +24-11-19 20:19:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:48 | D | sum error = [ 6.9177, 7.5875, 8.4345, 9.2859, 10.1836] +24-11-19 20:19:48 | D | best error = [ 2.0287, 2.0287, 2.0287, 2.0287, 2.0287] +24-11-19 20:19:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:48 | D | sum error = [ 11.1094, 12.4240, 13.8513, 15.4556, 16.9226] +24-11-19 20:19:48 | D | best error = [ 2.0287, 2.0287, 2.0287, 2.0287, 2.0287] +24-11-19 20:19:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:48 | D | sum error = [ 18.8336, 20.7404, 23.1317, 25.2010, 27.9659] +24-11-19 20:19:48 | D | best error = [ 2.0287, 2.0287, 2.0287, 2.0287, 2.0287] +24-11-19 20:19:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:48 | D | sum error = [ 30.9405, 33.8392, 37.2285, 41.1492, 45.1488] +24-11-19 20:19:48 | D | best error = [ 2.0287, 2.0287, 2.0287, 2.0287, 2.0287] +24-11-19 20:19:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:48 | D | sum error = [ 49.5037, 54.2828, 59.5275, 65.1886, 71.3165] +24-11-19 20:19:48 | D | best error = [ 2.0287, 2.0287, 2.0287, 2.0287, 2.0287] +24-11-19 20:19:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:48 | D | sum error = [ 78.1659, 85.1892, 92.9693, 101.6381, 111.3345] +24-11-19 20:19:48 | D | best error = [ 2.0287, 2.0287, 2.0287, 2.0287, 2.0287] +24-11-19 20:19:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:48 | D | sum error = [ 121.4071, 132.7627, 144.7651, 157.8853, 172.2798] +24-11-19 20:19:48 | D | best error = [ 2.0287, 2.0287, 2.0287, 2.0287, 2.0287] +24-11-19 20:19:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:48 | D | sum error = [ 187.7940, 204.7184, 222.3435, 241.8852, 262.7890] +24-11-19 20:19:48 | D | best error = [ 2.0287, 2.0287, 2.0287, 2.0287, 2.0287] +24-11-19 20:19:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:48 | D | sum error = [ 285.6174, 310.1223, 336.7313, 365.6266, 397.0767] +24-11-19 20:19:48 | D | best error = [ 2.0287, 2.0287, 2.0287, 2.0287, 2.0287] +24-11-19 20:19:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:48 | D | sum error = [ 430.6958, 467.4610, 507.0977, 550.1275, 596.2700] +24-11-19 20:19:48 | D | best error = [ 2.0287, 2.0287, 2.0287, 2.0287, 2.0287] +24-11-19 20:19:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:48 | D | sum error = [ 645.5758, 697.1371, 753.1615, 812.1357, 873.9922] +24-11-19 20:19:48 | D | best error = [ 2.0287, 2.0287, 2.0287, 2.0287, 2.0287] +24-11-19 20:19:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:48 | D | sum error = [ 939.3041, 1007.3153, 1078.2378, 1150.3509, 1223.1571] +24-11-19 20:19:48 | D | best error = [ 2.0287, 2.0287, 2.0287, 2.0287, 2.0287] +24-11-19 20:19:48 | D | + error = [2.0287] +24-11-19 20:19:48 | D | - Calibrating model.layers.3.self_attn.k_proj.weight +24-11-19 20:19:48 | D | + w: sint8 +24-11-19 20:19:48 | D | + x: None +24-11-19 20:19:48 | D | + y: None +24-11-19 20:19:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:19:48 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:19:48 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:19:49 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:19:49 | D | - range ratio = [ 1.0000] +24-11-19 20:19:49 | D | sum error = [ 2.4166] +24-11-19 20:19:49 | D | best error = [ 2.4166] +24-11-19 20:20:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:01 | D | sum error = [ 2.2938, 2.2375, 2.7453, 2.3867, 2.3181] +24-11-19 20:20:01 | D | best error = [ 2.2938, 2.2375, 2.2375, 2.2375, 2.2375] +24-11-19 20:20:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:01 | D | sum error = [ 2.5364, 2.5296, 2.9554, 3.2754, 3.4305] +24-11-19 20:20:01 | D | best error = [ 2.2375, 2.2375, 2.2375, 2.2375, 2.2375] +24-11-19 20:20:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:01 | D | sum error = [ 3.5790, 3.8184, 4.4946, 4.8233, 5.2900] +24-11-19 20:20:01 | D | best error = [ 2.2375, 2.2375, 2.2375, 2.2375, 2.2375] +24-11-19 20:20:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:01 | D | sum error = [ 6.2261, 6.5868, 7.1446, 7.6790, 8.6654] +24-11-19 20:20:01 | D | best error = [ 2.2375, 2.2375, 2.2375, 2.2375, 2.2375] +24-11-19 20:20:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:01 | D | sum error = [ 8.9933, 10.2477, 11.3130, 12.3708, 13.3186] +24-11-19 20:20:01 | D | best error = [ 2.2375, 2.2375, 2.2375, 2.2375, 2.2375] +24-11-19 20:20:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:01 | D | sum error = [ 14.4670, 16.2061, 17.8433, 18.8397, 20.7667] +24-11-19 20:20:01 | D | best error = [ 2.2375, 2.2375, 2.2375, 2.2375, 2.2375] +24-11-19 20:20:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:01 | D | sum error = [ 22.7479, 24.4313, 27.2438, 28.8480, 31.7976] +24-11-19 20:20:01 | D | best error = [ 2.2375, 2.2375, 2.2375, 2.2375, 2.2375] +24-11-19 20:20:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:01 | D | sum error = [ 34.3681, 37.4378, 40.5500, 43.6745, 47.0274] +24-11-19 20:20:01 | D | best error = [ 2.2375, 2.2375, 2.2375, 2.2375, 2.2375] +24-11-19 20:20:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:01 | D | sum error = [ 50.9775, 55.4157, 60.0832, 65.4092, 70.8163] +24-11-19 20:20:01 | D | best error = [ 2.2375, 2.2375, 2.2375, 2.2375, 2.2375] +24-11-19 20:20:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:01 | D | sum error = [ 76.9947, 83.7676, 91.1229, 98.7580, 107.6444] +24-11-19 20:20:01 | D | best error = [ 2.2375, 2.2375, 2.2375, 2.2375, 2.2375] +24-11-19 20:20:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:01 | D | sum error = [ 117.1203, 127.1883, 138.4931, 149.8921, 163.3088] +24-11-19 20:20:01 | D | best error = [ 2.2375, 2.2375, 2.2375, 2.2375, 2.2375] +24-11-19 20:20:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:01 | D | sum error = [ 177.4098, 192.6361, 209.0906, 227.7028, 247.8607] +24-11-19 20:20:01 | D | best error = [ 2.2375, 2.2375, 2.2375, 2.2375, 2.2375] +24-11-19 20:20:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:01 | D | sum error = [ 269.3275, 293.0680, 318.0406, 345.4770, 375.7175] +24-11-19 20:20:01 | D | best error = [ 2.2375, 2.2375, 2.2375, 2.2375, 2.2375] +24-11-19 20:20:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:01 | D | sum error = [ 407.8931, 443.1822, 481.6032, 522.2379, 566.9276] +24-11-19 20:20:01 | D | best error = [ 2.2375, 2.2375, 2.2375, 2.2375, 2.2375] +24-11-19 20:20:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:01 | D | sum error = [ 615.0197, 667.0802, 722.2951, 780.9276, 844.0187] +24-11-19 20:20:01 | D | best error = [ 2.2375, 2.2375, 2.2375, 2.2375, 2.2375] +24-11-19 20:20:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:01 | D | sum error = [ 908.9916, 977.3311, 1048.3208, 1120.9207, 1194.0791] +24-11-19 20:20:01 | D | best error = [ 2.2375, 2.2375, 2.2375, 2.2375, 2.2375] +24-11-19 20:20:01 | D | + error = [2.2375] +24-11-19 20:20:01 | D | - Calibrating model.layers.3.self_attn.v_proj.weight +24-11-19 20:20:01 | D | + w: sint8 +24-11-19 20:20:01 | D | + x: None +24-11-19 20:20:01 | D | + y: None +24-11-19 20:20:01 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:01 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:20:02 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:20:02 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:20:02 | D | - range ratio = [ 1.0000] +24-11-19 20:20:02 | D | sum error = [ 3.1706] +24-11-19 20:20:02 | D | best error = [ 3.1706] +24-11-19 20:20:02 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:02 | D | sum error = [ 3.1659, 3.1278, 3.1504, 3.1894, 3.2410] +24-11-19 20:20:02 | D | best error = [ 2.8479, 2.7360, 2.6847, 2.6567, 2.6407] +24-11-19 20:20:02 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:02 | D | sum error = [ 3.3542, 3.4515, 3.5666, 3.7337, 3.9333] +24-11-19 20:20:02 | D | best error = [ 2.6334, 2.6300, 2.6283, 2.6280, 2.6279] +24-11-19 20:20:02 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:02 | D | sum error = [ 4.1649, 4.4321, 4.7029, 5.0032, 5.3494] +24-11-19 20:20:02 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:20:02 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:02 | D | sum error = [ 5.7114, 6.1290, 6.5651, 7.0457, 7.5580] +24-11-19 20:20:02 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:20:02 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:02 | D | sum error = [ 8.0963, 8.6722, 9.2964, 9.9548, 10.6288] +24-11-19 20:20:02 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:20:02 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:02 | D | sum error = [ 11.3692, 12.1552, 12.9588, 13.8473, 14.7824] +24-11-19 20:20:02 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:20:02 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:02 | D | sum error = [ 15.7429, 16.7829, 17.8507, 19.0112, 20.1979] +24-11-19 20:20:02 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:20:02 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:02 | D | sum error = [ 21.4800, 22.8116, 24.1978, 25.6871, 27.2159] +24-11-19 20:20:02 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:20:02 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:02 | D | sum error = [ 28.8699, 30.5675, 32.3739, 34.2507, 36.2386] +24-11-19 20:20:02 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:20:02 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:02 | D | sum error = [ 38.2760, 40.4485, 42.6884, 45.0550, 47.5271] +24-11-19 20:20:02 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:20:02 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:02 | D | sum error = [ 50.0835, 52.7733, 55.5664, 58.4941, 61.5510] +24-11-19 20:20:02 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:20:02 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:02 | D | sum error = [ 64.7368, 68.0532, 71.5216, 75.1339, 78.8849] +24-11-19 20:20:02 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:20:02 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:02 | D | sum error = [ 82.7932, 86.8489, 91.0597, 95.4307, 99.9571] +24-11-19 20:20:02 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:20:02 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:02 | D | sum error = [ 104.6319, 109.4792, 114.5200, 119.7338, 125.1311] +24-11-19 20:20:02 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:20:02 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:02 | D | sum error = [ 130.7122, 136.4777, 142.4452, 148.6014, 154.9424] +24-11-19 20:20:02 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:20:02 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:02 | D | sum error = [ 161.4924, 168.2349, 175.1851, 182.3412, 189.7053] +24-11-19 20:20:02 | D | best error = [ 2.6278, 2.6278, 2.6278, 2.6278, 2.6278] +24-11-19 20:20:02 | D | + error = [2.6278] +24-11-19 20:20:02 | D | - Calibrating model.layers.3.self_attn.o_proj.weight +24-11-19 20:20:02 | D | + w: sint8 +24-11-19 20:20:02 | D | + x: None +24-11-19 20:20:02 | D | + y: None +24-11-19 20:20:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:02 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:20:02 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:20:02 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:20:02 | D | - range ratio = [ 1.0000] +24-11-19 20:20:02 | D | sum error = [ 0.2488] +24-11-19 20:20:02 | D | best error = [ 0.2488] +24-11-19 20:20:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:03 | D | sum error = [ 0.2462, 0.2457, 0.2470, 0.2486, 0.2532] +24-11-19 20:20:03 | D | best error = [ 0.2354, 0.2293, 0.2260, 0.2240, 0.2227] +24-11-19 20:20:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:03 | D | sum error = [ 0.2589, 0.2665, 0.2761, 0.2869, 0.3018] +24-11-19 20:20:03 | D | best error = [ 0.2219, 0.2215, 0.2212, 0.2210, 0.2209] +24-11-19 20:20:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:03 | D | sum error = [ 0.3182, 0.3358, 0.3564, 0.3797, 0.4041] +24-11-19 20:20:03 | D | best error = [ 0.2208, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:20:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:03 | D | sum error = [ 0.4314, 0.4607, 0.4929, 0.5265, 0.5638] +24-11-19 20:20:03 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:20:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:03 | D | sum error = [ 0.6028, 0.6449, 0.6888, 0.7371, 0.7880] +24-11-19 20:20:03 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:20:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:03 | D | sum error = [ 0.8410, 0.8980, 0.9578, 1.0217, 1.0888] +24-11-19 20:20:03 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:20:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:03 | D | sum error = [ 1.1607, 1.2360, 1.3161, 1.3997, 1.4898] +24-11-19 20:20:03 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:20:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:03 | D | sum error = [ 1.5824, 1.6827, 1.7865, 1.8978, 2.0139] +24-11-19 20:20:03 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:20:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:03 | D | sum error = [ 2.1377, 2.2669, 2.4038, 2.5477, 2.6999] +24-11-19 20:20:03 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:20:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:03 | D | sum error = [ 2.8609, 3.0290, 3.2073, 3.3941, 3.5911] +24-11-19 20:20:03 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:20:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:03 | D | sum error = [ 3.7982, 4.0165, 4.2456, 4.4862, 4.7397] +24-11-19 20:20:03 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:20:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:03 | D | sum error = [ 5.0056, 5.2854, 5.5782, 5.8861, 6.2093] +24-11-19 20:20:03 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:20:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:03 | D | sum error = [ 6.5480, 6.9030, 7.2745, 7.6636, 8.0710] +24-11-19 20:20:03 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:20:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:03 | D | sum error = [ 8.4973, 8.9424, 9.4079, 9.8932, 10.4010] +24-11-19 20:20:03 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:20:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:03 | D | sum error = [ 10.9294, 11.4800, 12.0539, 12.6511, 13.2714] +24-11-19 20:20:03 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:20:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:03 | D | sum error = [ 13.9151, 14.5835, 15.2756, 15.9932, 16.7351] +24-11-19 20:20:03 | D | best error = [ 0.2207, 0.2207, 0.2207, 0.2207, 0.2207] +24-11-19 20:20:03 | D | + error = [0.2207] +24-11-19 20:20:03 | D | - Calibrating model.layers.3.mlp.up_proj.weight +24-11-19 20:20:03 | D | + w: sint8 +24-11-19 20:20:03 | D | + x: None +24-11-19 20:20:03 | D | + y: None +24-11-19 20:20:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:03 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:20:03 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:20:03 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:20:03 | D | - range ratio = [ 1.0000] +24-11-19 20:20:03 | D | sum error = [ 4.0370] +24-11-19 20:20:03 | D | best error = [ 4.0370] +24-11-19 20:20:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:04 | D | sum error = [ 3.9998, 3.9891, 4.0198, 4.0566, 4.1421] +24-11-19 20:20:04 | D | best error = [ 3.5555, 3.3916, 3.3174, 3.2756, 3.2530] +24-11-19 20:20:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:04 | D | sum error = [ 4.2349, 4.3860, 4.5689, 4.8016, 5.0211] +24-11-19 20:20:04 | D | best error = [ 3.2408, 3.2357, 3.2339, 3.2333, 3.2330] +24-11-19 20:20:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:04 | D | sum error = [ 5.3260, 5.6452, 6.0029, 6.4385, 6.8619] +24-11-19 20:20:04 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:20:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:04 | D | sum error = [ 7.3532, 7.8700, 8.4187, 9.0236, 9.6618] +24-11-19 20:20:04 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:20:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:04 | D | sum error = [ 10.3401, 11.0781, 11.8346, 12.6675, 13.5209] +24-11-19 20:20:04 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:20:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:04 | D | sum error = [ 14.4555, 15.4174, 16.4416, 17.5209, 18.6667] +24-11-19 20:20:04 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:20:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:04 | D | sum error = [ 19.8548, 21.1250, 22.4491, 23.8495, 25.3318] +24-11-19 20:20:04 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:20:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:04 | D | sum error = [ 26.8636, 28.4741, 30.1802, 31.9589, 33.8147] +24-11-19 20:20:04 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:20:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:04 | D | sum error = [ 35.7731, 37.8166, 39.9381, 42.1774, 44.4935] +24-11-19 20:20:04 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:20:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:04 | D | sum error = [ 46.9165, 49.4362, 52.0725, 54.7797, 57.6262] +24-11-19 20:20:04 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:20:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:04 | D | sum error = [ 60.5798, 63.6716, 66.8606, 70.1694, 73.5973] +24-11-19 20:20:04 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:20:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:04 | D | sum error = [ 77.1623, 80.8417, 84.6597, 88.6177, 92.6898] +24-11-19 20:20:04 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:20:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:04 | D | sum error = [ 96.9009, 101.2543, 105.7459, 110.3730, 115.1352] +24-11-19 20:20:04 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:20:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:04 | D | sum error = [ 120.0342, 125.0632, 130.2709, 135.6180, 141.1118] +24-11-19 20:20:04 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:20:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:04 | D | sum error = [ 146.7439, 152.5279, 158.4690, 164.5600, 170.8083] +24-11-19 20:20:04 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:20:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:04 | D | sum error = [ 177.2109, 183.7800, 190.5077, 197.4097, 204.4933] +24-11-19 20:20:04 | D | best error = [ 3.2330, 3.2330, 3.2330, 3.2330, 3.2330] +24-11-19 20:20:04 | D | + error = [3.2330] +24-11-19 20:20:04 | D | - Calibrating model.layers.3.mlp.gate_proj.weight +24-11-19 20:20:04 | D | + w: sint8 +24-11-19 20:20:04 | D | + x: None +24-11-19 20:20:04 | D | + y: None +24-11-19 20:20:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:04 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:20:04 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:20:05 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:20:05 | D | - range ratio = [ 1.0000] +24-11-19 20:20:05 | D | sum error = [ 4.3526] +24-11-19 20:20:05 | D | best error = [ 4.3526] +24-11-19 20:20:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:06 | D | sum error = [ 4.3122, 4.3102, 4.3309, 4.3907, 4.4581] +24-11-19 20:20:06 | D | best error = [ 3.8364, 3.6601, 3.5782, 3.5333, 3.5096] +24-11-19 20:20:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:06 | D | sum error = [ 4.5714, 4.7274, 4.8956, 5.1579, 5.4426] +24-11-19 20:20:06 | D | best error = [ 3.4970, 3.4921, 3.4898, 3.4891, 3.4890] +24-11-19 20:20:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:06 | D | sum error = [ 5.7226, 6.0866, 6.4694, 6.8953, 7.3639] +24-11-19 20:20:06 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:20:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:06 | D | sum error = [ 7.8899, 8.4682, 9.0682, 9.7275, 10.4371] +24-11-19 20:20:06 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:20:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:06 | D | sum error = [ 11.1614, 11.9548, 12.7853, 13.7114, 14.6360] +24-11-19 20:20:06 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:20:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:06 | D | sum error = [ 15.6397, 16.7247, 17.8433, 19.0212, 20.2680] +24-11-19 20:20:06 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:20:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:06 | D | sum error = [ 21.5937, 22.9822, 24.4545, 26.0112, 27.6265] +24-11-19 20:20:06 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:20:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:06 | D | sum error = [ 29.3295, 31.1147, 33.0042, 34.9825, 37.0528] +24-11-19 20:20:06 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:20:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:06 | D | sum error = [ 39.2307, 41.4905, 43.8937, 46.3922, 49.0047] +24-11-19 20:20:06 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:20:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:06 | D | sum error = [ 51.7466, 54.6220, 57.6329, 60.7764, 64.0714] +24-11-19 20:20:06 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:20:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:06 | D | sum error = [ 67.4902, 71.0607, 74.7897, 78.6751, 82.7281] +24-11-19 20:20:06 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:20:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:06 | D | sum error = [ 86.9350, 91.3115, 95.8778, 100.6369, 105.5655] +24-11-19 20:20:06 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:20:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:06 | D | sum error = [ 110.7024, 116.0255, 121.5371, 127.2419, 133.1707] +24-11-19 20:20:06 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:20:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:06 | D | sum error = [ 139.2812, 145.5707, 152.1066, 158.8474, 165.8211] +24-11-19 20:20:06 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:20:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:06 | D | sum error = [ 173.0241, 180.4723, 188.1756, 196.1130, 204.2939] +24-11-19 20:20:06 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:20:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:06 | D | sum error = [ 212.7321, 221.4073, 230.3355, 239.5191, 248.9578] +24-11-19 20:20:06 | D | best error = [ 3.4889, 3.4889, 3.4889, 3.4889, 3.4889] +24-11-19 20:20:06 | D | + error = [3.4889] +24-11-19 20:20:06 | D | - Calibrating model.layers.3.mlp.down_proj.weight +24-11-19 20:20:06 | D | + w: sint8 +24-11-19 20:20:06 | D | + x: None +24-11-19 20:20:06 | D | + y: None +24-11-19 20:20:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:06 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:20:06 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:20:06 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:20:06 | D | - range ratio = [ 1.0000] +24-11-19 20:20:06 | D | sum error = [ 0.4792] +24-11-19 20:20:06 | D | best error = [ 0.4792] +24-11-19 20:20:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:07 | D | sum error = [ 0.4748, 0.4716, 0.4686, 0.4679, 0.4671] +24-11-19 20:20:07 | D | best error = [ 0.4655, 0.4580, 0.4525, 0.4486, 0.4455] +24-11-19 20:20:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:07 | D | sum error = [ 0.4693, 0.4722, 0.4786, 0.4866, 0.4974] +24-11-19 20:20:07 | D | best error = [ 0.4431, 0.4413, 0.4400, 0.4392, 0.4387] +24-11-19 20:20:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:07 | D | sum error = [ 0.5096, 0.5257, 0.5444, 0.5669, 0.5928] +24-11-19 20:20:07 | D | best error = [ 0.4384, 0.4382, 0.4380, 0.4379, 0.4379] +24-11-19 20:20:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:07 | D | sum error = [ 0.6225, 0.6562, 0.6937, 0.7355, 0.7811] +24-11-19 20:20:07 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:20:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:07 | D | sum error = [ 0.8315, 0.8871, 0.9463, 1.0106, 1.0806] +24-11-19 20:20:07 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:20:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:07 | D | sum error = [ 1.1559, 1.2362, 1.3218, 1.4151, 1.5138] +24-11-19 20:20:07 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:20:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:07 | D | sum error = [ 1.6188, 1.7316, 1.8506, 1.9774, 2.1126] +24-11-19 20:20:07 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:20:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:07 | D | sum error = [ 2.2568, 2.4093, 2.5726, 2.7428, 2.9250] +24-11-19 20:20:07 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:20:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:07 | D | sum error = [ 3.1173, 3.3217, 3.5367, 3.7652, 4.0059] +24-11-19 20:20:07 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:20:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:07 | D | sum error = [ 4.2603, 4.5291, 4.8116, 5.1098, 5.4236] +24-11-19 20:20:07 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:20:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:07 | D | sum error = [ 5.7537, 6.1017, 6.4667, 6.8510, 7.2544] +24-11-19 20:20:07 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:20:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:07 | D | sum error = [ 7.6786, 8.1230, 8.5894, 9.0781, 9.5906] +24-11-19 20:20:07 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:20:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:07 | D | sum error = [ 10.1268, 10.6880, 11.2747, 11.8881, 12.5279] +24-11-19 20:20:07 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:20:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:07 | D | sum error = [ 13.1959, 13.8923, 14.6189, 15.3768, 16.1626] +24-11-19 20:20:07 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:20:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:07 | D | sum error = [ 16.9819, 17.8336, 18.7184, 19.6372, 20.5900] +24-11-19 20:20:07 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:20:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:07 | D | sum error = [ 21.5773, 22.6005, 23.6587, 24.7536, 25.8855] +24-11-19 20:20:07 | D | best error = [ 0.4379, 0.4379, 0.4379, 0.4379, 0.4379] +24-11-19 20:20:07 | D | + error = [0.4379] +24-11-19 20:20:07 | D | - Quantizing model.layers.3.self_attn.q_proj.weight +24-11-19 20:20:08 | D | - Quantizing model.layers.3.self_attn.k_proj.weight +24-11-19 20:20:09 | D | - Quantizing model.layers.3.self_attn.v_proj.weight +24-11-19 20:20:09 | D | - Quantizing model.layers.3.self_attn.o_proj.weight +24-11-19 20:20:10 | D | - Quantizing model.layers.3.mlp.up_proj.weight +24-11-19 20:20:11 | D | - Quantizing model.layers.3.mlp.gate_proj.weight +24-11-19 20:20:12 | D | - Quantizing model.layers.3.mlp.down_proj.weight +24-11-19 20:20:20 | D | - Quantizing layer model.layers.4 +24-11-19 20:20:20 | D | - Calibrating model.layers.4.self_attn.q_proj.weight +24-11-19 20:20:20 | D | + w: sint8 +24-11-19 20:20:20 | D | + x: None +24-11-19 20:20:20 | D | + y: None +24-11-19 20:20:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:20:20 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:20:20 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:20:20 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:20:20 | D | - range ratio = [ 1.0000] +24-11-19 20:20:20 | D | sum error = [ 2.5572] +24-11-19 20:20:20 | D | best error = [ 2.5572] +24-11-19 20:20:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:33 | D | sum error = [ 2.4640, 2.5561, 2.5047, 2.6148, 2.6626] +24-11-19 20:20:33 | D | best error = [ 2.4640, 2.4640, 2.4640, 2.4640, 2.4640] +24-11-19 20:20:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:33 | D | sum error = [ 2.9028, 2.9652, 3.1652, 3.5245, 3.6498] +24-11-19 20:20:33 | D | best error = [ 2.4640, 2.4640, 2.4640, 2.4640, 2.4640] +24-11-19 20:20:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:33 | D | sum error = [ 3.8595, 4.5755, 5.0644, 5.7013, 6.2316] +24-11-19 20:20:33 | D | best error = [ 2.4640, 2.4640, 2.4640, 2.4640, 2.4640] +24-11-19 20:20:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:33 | D | sum error = [ 6.9969, 7.7723, 9.1923, 9.9504, 11.1872] +24-11-19 20:20:33 | D | best error = [ 2.4640, 2.4640, 2.4640, 2.4640, 2.4640] +24-11-19 20:20:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:33 | D | sum error = [ 12.5927, 13.7096, 15.1294, 16.7233, 18.4953] +24-11-19 20:20:33 | D | best error = [ 2.4640, 2.4640, 2.4640, 2.4640, 2.4640] +24-11-19 20:20:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:33 | D | sum error = [ 20.6143, 22.2936, 24.8900, 26.9965, 29.5665] +24-11-19 20:20:33 | D | best error = [ 2.4640, 2.4640, 2.4640, 2.4640, 2.4640] +24-11-19 20:20:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:33 | D | sum error = [ 32.2610, 35.2435, 38.4467, 42.3139, 46.0364] +24-11-19 20:20:33 | D | best error = [ 2.4640, 2.4640, 2.4640, 2.4640, 2.4640] +24-11-19 20:20:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:33 | D | sum error = [ 50.2704, 54.5445, 59.5446, 65.0675, 70.7963] +24-11-19 20:20:33 | D | best error = [ 2.4640, 2.4640, 2.4640, 2.4640, 2.4640] +24-11-19 20:20:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:33 | D | sum error = [ 77.0809, 83.8873, 90.9795, 98.5268, 106.8245] +24-11-19 20:20:33 | D | best error = [ 2.4640, 2.4640, 2.4640, 2.4640, 2.4640] +24-11-19 20:20:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:33 | D | sum error = [ 116.1286, 125.4762, 135.8183, 146.8897, 158.7871] +24-11-19 20:20:33 | D | best error = [ 2.4640, 2.4640, 2.4640, 2.4640, 2.4640] +24-11-19 20:20:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:33 | D | sum error = [ 171.7812, 185.2307, 200.4759, 216.1053, 233.3152] +24-11-19 20:20:33 | D | best error = [ 2.4640, 2.4640, 2.4640, 2.4640, 2.4640] +24-11-19 20:20:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:33 | D | sum error = [ 251.4829, 271.0411, 291.8237, 314.1443, 338.1226] +24-11-19 20:20:33 | D | best error = [ 2.4640, 2.4640, 2.4640, 2.4640, 2.4640] +24-11-19 20:20:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:33 | D | sum error = [ 364.0069, 391.2442, 420.0904, 452.3835, 485.9130] +24-11-19 20:20:33 | D | best error = [ 2.4640, 2.4640, 2.4640, 2.4640, 2.4640] +24-11-19 20:20:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:33 | D | sum error = [ 520.8465, 558.9338, 599.0647, 641.6332, 685.4558] +24-11-19 20:20:33 | D | best error = [ 2.4640, 2.4640, 2.4640, 2.4640, 2.4640] +24-11-19 20:20:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:33 | D | sum error = [ 732.4399, 780.3931, 829.9800, 883.0846, 937.4858] +24-11-19 20:20:33 | D | best error = [ 2.4640, 2.4640, 2.4640, 2.4640, 2.4640] +24-11-19 20:20:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:33 | D | sum error = [ 993.0115, 1050.1295, 1109.0361, 1168.6235, 1228.9340] +24-11-19 20:20:33 | D | best error = [ 2.4640, 2.4640, 2.4640, 2.4640, 2.4640] +24-11-19 20:20:33 | D | + error = [2.4640] +24-11-19 20:20:33 | D | - Calibrating model.layers.4.self_attn.k_proj.weight +24-11-19 20:20:33 | D | + w: sint8 +24-11-19 20:20:33 | D | + x: None +24-11-19 20:20:33 | D | + y: None +24-11-19 20:20:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:20:33 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:20:33 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:20:33 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:20:34 | D | - range ratio = [ 1.0000] +24-11-19 20:20:34 | D | sum error = [ 3.0707] +24-11-19 20:20:34 | D | best error = [ 3.0707] +24-11-19 20:20:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:46 | D | sum error = [ 2.8729, 2.9890, 2.8631, 2.8425, 2.9218] +24-11-19 20:20:46 | D | best error = [ 2.8729, 2.8729, 2.8631, 2.8425, 2.8425] +24-11-19 20:20:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:46 | D | sum error = [ 3.1479, 3.0471, 3.1507, 3.4162, 3.5367] +24-11-19 20:20:46 | D | best error = [ 2.8425, 2.8425, 2.8425, 2.8425, 2.8425] +24-11-19 20:20:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:46 | D | sum error = [ 3.6514, 4.0466, 4.3917, 4.4873, 5.2773] +24-11-19 20:20:46 | D | best error = [ 2.8425, 2.8425, 2.8425, 2.8425, 2.8425] +24-11-19 20:20:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:46 | D | sum error = [ 5.7011, 6.0711, 6.7194, 7.2071, 7.9570] +24-11-19 20:20:46 | D | best error = [ 2.8425, 2.8425, 2.8425, 2.8425, 2.8425] +24-11-19 20:20:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:46 | D | sum error = [ 8.8354, 9.3801, 10.4367, 11.4474, 12.4779] +24-11-19 20:20:46 | D | best error = [ 2.8425, 2.8425, 2.8425, 2.8425, 2.8425] +24-11-19 20:20:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:46 | D | sum error = [ 13.7066, 15.0879, 16.2723, 17.8017, 19.7305] +24-11-19 20:20:46 | D | best error = [ 2.8425, 2.8425, 2.8425, 2.8425, 2.8425] +24-11-19 20:20:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:46 | D | sum error = [ 21.3938, 23.0088, 25.3943, 27.8744, 29.8283] +24-11-19 20:20:46 | D | best error = [ 2.8425, 2.8425, 2.8425, 2.8425, 2.8425] +24-11-19 20:20:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:46 | D | sum error = [ 32.8386, 35.4345, 39.0272, 42.5111, 46.3916] +24-11-19 20:20:46 | D | best error = [ 2.8425, 2.8425, 2.8425, 2.8425, 2.8425] +24-11-19 20:20:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:46 | D | sum error = [ 50.0774, 54.4053, 59.1382, 64.8737, 71.0373] +24-11-19 20:20:46 | D | best error = [ 2.8425, 2.8425, 2.8425, 2.8425, 2.8425] +24-11-19 20:20:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:46 | D | sum error = [ 77.5588, 84.5110, 92.2140, 100.4495, 109.6007] +24-11-19 20:20:46 | D | best error = [ 2.8425, 2.8425, 2.8425, 2.8425, 2.8425] +24-11-19 20:20:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:46 | D | sum error = [ 118.7929, 129.6082, 140.3154, 152.3856, 165.4830] +24-11-19 20:20:46 | D | best error = [ 2.8425, 2.8425, 2.8425, 2.8425, 2.8425] +24-11-19 20:20:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:46 | D | sum error = [ 179.2914, 194.7455, 210.4448, 228.7995, 247.8982] +24-11-19 20:20:46 | D | best error = [ 2.8425, 2.8425, 2.8425, 2.8425, 2.8425] +24-11-19 20:20:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:46 | D | sum error = [ 268.5980, 291.2628, 315.1508, 341.2652, 369.8966] +24-11-19 20:20:46 | D | best error = [ 2.8425, 2.8425, 2.8425, 2.8425, 2.8425] +24-11-19 20:20:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:46 | D | sum error = [ 400.6799, 433.3889, 468.7046, 506.4089, 546.2733] +24-11-19 20:20:46 | D | best error = [ 2.8425, 2.8425, 2.8425, 2.8425, 2.8425] +24-11-19 20:20:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:46 | D | sum error = [ 589.9666, 635.3067, 683.7241, 734.8402, 788.6883] +24-11-19 20:20:46 | D | best error = [ 2.8425, 2.8425, 2.8425, 2.8425, 2.8425] +24-11-19 20:20:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:46 | D | sum error = [ 846.0424, 906.7563, 969.3053, 1034.1080, 1099.8231] +24-11-19 20:20:46 | D | best error = [ 2.8425, 2.8425, 2.8425, 2.8425, 2.8425] +24-11-19 20:20:46 | D | + error = [2.8425] +24-11-19 20:20:46 | D | - Calibrating model.layers.4.self_attn.v_proj.weight +24-11-19 20:20:46 | D | + w: sint8 +24-11-19 20:20:46 | D | + x: None +24-11-19 20:20:46 | D | + y: None +24-11-19 20:20:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:46 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:20:47 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:20:47 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:20:47 | D | - range ratio = [ 1.0000] +24-11-19 20:20:47 | D | sum error = [ 3.0382] +24-11-19 20:20:47 | D | best error = [ 3.0382] +24-11-19 20:20:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:47 | D | sum error = [ 3.0269, 3.0165, 3.0419, 3.0730, 3.1221] +24-11-19 20:20:47 | D | best error = [ 2.7708, 2.6785, 2.6299, 2.6046, 2.5902] +24-11-19 20:20:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:47 | D | sum error = [ 3.2047, 3.3074, 3.4541, 3.6162, 3.8043] +24-11-19 20:20:47 | D | best error = [ 2.5836, 2.5812, 2.5805, 2.5803, 2.5802] +24-11-19 20:20:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:47 | D | sum error = [ 4.0295, 4.2748, 4.5390, 4.8611, 5.2119] +24-11-19 20:20:47 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 20:20:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:47 | D | sum error = [ 5.5778, 5.9704, 6.4029, 6.8546, 7.3643] +24-11-19 20:20:47 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 20:20:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:47 | D | sum error = [ 7.8791, 8.4510, 9.0501, 9.6931, 10.3518] +24-11-19 20:20:47 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 20:20:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:47 | D | sum error = [ 11.0565, 11.8161, 12.5972, 13.4364, 14.3395] +24-11-19 20:20:47 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 20:20:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:47 | D | sum error = [ 15.2620, 16.2620, 17.2998, 18.4258, 19.5770] +24-11-19 20:20:47 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 20:20:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:47 | D | sum error = [ 20.8035, 22.1004, 23.4454, 24.8736, 26.3450] +24-11-19 20:20:47 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 20:20:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:47 | D | sum error = [ 27.9079, 29.5526, 31.2713, 33.0916, 34.9918] +24-11-19 20:20:47 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 20:20:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:47 | D | sum error = [ 36.9777, 39.0679, 41.2549, 43.5380, 45.9258] +24-11-19 20:20:47 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 20:20:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:47 | D | sum error = [ 48.4313, 51.0497, 53.7855, 56.6461, 59.6297] +24-11-19 20:20:47 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 20:20:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:47 | D | sum error = [ 62.7415, 66.0027, 69.3891, 72.9159, 76.5764] +24-11-19 20:20:47 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 20:20:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:47 | D | sum error = [ 80.3937, 84.3580, 88.4769, 92.7510, 97.1873] +24-11-19 20:20:47 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 20:20:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:47 | D | sum error = [ 101.7907, 106.5681, 111.5172, 116.6478, 121.9537] +24-11-19 20:20:47 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 20:20:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:47 | D | sum error = [ 127.4490, 133.1294, 139.0126, 145.0853, 151.3517] +24-11-19 20:20:47 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 20:20:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:47 | D | sum error = [ 157.8167, 164.4661, 171.3260, 178.3838, 185.6455] +24-11-19 20:20:47 | D | best error = [ 2.5802, 2.5802, 2.5802, 2.5802, 2.5802] +24-11-19 20:20:47 | D | + error = [2.5802] +24-11-19 20:20:47 | D | - Calibrating model.layers.4.self_attn.o_proj.weight +24-11-19 20:20:47 | D | + w: sint8 +24-11-19 20:20:47 | D | + x: None +24-11-19 20:20:47 | D | + y: None +24-11-19 20:20:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:47 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:20:47 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:20:47 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:20:47 | D | - range ratio = [ 1.0000] +24-11-19 20:20:47 | D | sum error = [ 0.3585] +24-11-19 20:20:47 | D | best error = [ 0.3585] +24-11-19 20:20:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:48 | D | sum error = [ 0.3563, 0.3550, 0.3550, 0.3582, 0.3637] +24-11-19 20:20:48 | D | best error = [ 0.3406, 0.3319, 0.3269, 0.3237, 0.3218] +24-11-19 20:20:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:48 | D | sum error = [ 0.3715, 0.3826, 0.3958, 0.4125, 0.4322] +24-11-19 20:20:48 | D | best error = [ 0.3205, 0.3198, 0.3193, 0.3189, 0.3187] +24-11-19 20:20:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:48 | D | sum error = [ 0.4551, 0.4804, 0.5101, 0.5424, 0.5793] +24-11-19 20:20:48 | D | best error = [ 0.3186, 0.3185, 0.3184, 0.3184, 0.3184] +24-11-19 20:20:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:48 | D | sum error = [ 0.6168, 0.6602, 0.7053, 0.7550, 0.8084] +24-11-19 20:20:48 | D | best error = [ 0.3184, 0.3184, 0.3184, 0.3183, 0.3183] +24-11-19 20:20:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:48 | D | sum error = [ 0.8652, 0.9271, 0.9910, 1.0615, 1.1343] +24-11-19 20:20:48 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 20:20:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:48 | D | sum error = [ 1.2126, 1.2961, 1.3831, 1.4776, 1.5762] +24-11-19 20:20:48 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 20:20:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:48 | D | sum error = [ 1.6821, 1.7936, 1.9112, 2.0366, 2.1674] +24-11-19 20:20:48 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 20:20:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:48 | D | sum error = [ 2.3079, 2.4552, 2.6100, 2.7734, 2.9471] +24-11-19 20:20:48 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 20:20:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:48 | D | sum error = [ 3.1290, 3.3210, 3.5230, 3.7358, 3.9614] +24-11-19 20:20:48 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 20:20:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:48 | D | sum error = [ 4.1979, 4.4469, 4.7100, 4.9854, 5.2765] +24-11-19 20:20:48 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 20:20:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:48 | D | sum error = [ 5.5807, 5.9012, 6.2390, 6.5922, 6.9639] +24-11-19 20:20:48 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 20:20:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:48 | D | sum error = [ 7.3529, 7.7602, 8.1868, 8.6339, 9.1009] +24-11-19 20:20:48 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 20:20:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:48 | D | sum error = [ 9.5908, 10.1024, 10.6374, 11.1957, 11.7792] +24-11-19 20:20:48 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 20:20:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:48 | D | sum error = [ 12.3873, 13.0223, 13.6834, 14.3714, 15.0874] +24-11-19 20:20:48 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 20:20:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:48 | D | sum error = [ 15.8314, 16.6030, 17.4030, 18.2328, 19.0925] +24-11-19 20:20:48 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 20:20:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:48 | D | sum error = [ 19.9822, 20.9029, 21.8546, 22.8379, 23.8531] +24-11-19 20:20:48 | D | best error = [ 0.3183, 0.3183, 0.3183, 0.3183, 0.3183] +24-11-19 20:20:48 | D | + error = [0.3183] +24-11-19 20:20:48 | D | - Calibrating model.layers.4.mlp.up_proj.weight +24-11-19 20:20:48 | D | + w: sint8 +24-11-19 20:20:48 | D | + x: None +24-11-19 20:20:48 | D | + y: None +24-11-19 20:20:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:48 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:20:48 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:20:48 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:20:48 | D | - range ratio = [ 1.0000] +24-11-19 20:20:48 | D | sum error = [ 4.3383] +24-11-19 20:20:48 | D | best error = [ 4.3383] +24-11-19 20:20:49 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:49 | D | sum error = [ 4.3001, 4.2761, 4.3107, 4.3731, 4.4277] +24-11-19 20:20:49 | D | best error = [ 3.8851, 3.7306, 3.6573, 3.6172, 3.5953] +24-11-19 20:20:49 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:49 | D | sum error = [ 4.5705, 4.7019, 4.8952, 5.1225, 5.4097] +24-11-19 20:20:49 | D | best error = [ 3.5857, 3.5816, 3.5799, 3.5794, 3.5792] +24-11-19 20:20:49 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:49 | D | sum error = [ 5.7089, 6.0500, 6.4233, 6.8669, 7.3466] +24-11-19 20:20:49 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:49 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:49 | D | sum error = [ 7.8604, 8.4177, 9.0018, 9.6470, 10.3319] +24-11-19 20:20:49 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:49 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:49 | D | sum error = [ 11.0811, 11.8573, 12.6782, 13.5416, 14.4910] +24-11-19 20:20:49 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:49 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:49 | D | sum error = [ 15.4648, 16.5244, 17.6269, 18.7983, 20.0247] +24-11-19 20:20:49 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:49 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:49 | D | sum error = [ 21.3292, 22.6963, 24.1357, 25.6622, 27.2492] +24-11-19 20:20:49 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:49 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:49 | D | sum error = [ 28.9358, 30.7032, 32.5698, 34.5203, 36.5489] +24-11-19 20:20:49 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:49 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:49 | D | sum error = [ 38.7020, 40.9370, 43.2842, 45.7430, 48.3014] +24-11-19 20:20:49 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:49 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:49 | D | sum error = [ 50.9633, 53.7592, 56.6604, 59.6957, 62.8777] +24-11-19 20:20:49 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:49 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:49 | D | sum error = [ 66.1850, 69.6177, 73.2068, 76.9273, 80.7888] +24-11-19 20:20:49 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:49 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:49 | D | sum error = [ 84.8014, 88.9535, 93.2563, 97.7341, 102.3535] +24-11-19 20:20:49 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:49 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:49 | D | sum error = [ 107.1412, 112.0947, 117.2187, 122.5134, 127.9855] +24-11-19 20:20:49 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:49 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:49 | D | sum error = [ 133.6372, 139.4811, 145.5189, 151.7347, 158.1532] +24-11-19 20:20:49 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:49 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:49 | D | sum error = [ 164.7753, 171.5909, 178.6147, 185.8402, 193.2757] +24-11-19 20:20:49 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:49 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:49 | D | sum error = [ 200.9248, 208.7852, 216.8708, 225.1812, 233.7179] +24-11-19 20:20:49 | D | best error = [ 3.5792, 3.5792, 3.5792, 3.5792, 3.5792] +24-11-19 20:20:49 | D | + error = [3.5792] +24-11-19 20:20:49 | D | - Calibrating model.layers.4.mlp.gate_proj.weight +24-11-19 20:20:49 | D | + w: sint8 +24-11-19 20:20:49 | D | + x: None +24-11-19 20:20:49 | D | + y: None +24-11-19 20:20:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:49 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:20:49 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:20:49 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:20:49 | D | - range ratio = [ 1.0000] +24-11-19 20:20:49 | D | sum error = [ 4.7995] +24-11-19 20:20:49 | D | best error = [ 4.7995] +24-11-19 20:20:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:50 | D | sum error = [ 4.7717, 4.7537, 4.7676, 4.8341, 4.9219] +24-11-19 20:20:50 | D | best error = [ 4.2993, 4.1342, 4.0496, 4.0080, 3.9855] +24-11-19 20:20:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:50 | D | sum error = [ 5.0562, 5.2183, 5.4483, 5.6938, 6.0147] +24-11-19 20:20:50 | D | best error = [ 3.9735, 3.9684, 3.9665, 3.9660, 3.9659] +24-11-19 20:20:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:50 | D | sum error = [ 6.3445, 6.7274, 7.1695, 7.6447, 8.1802] +24-11-19 20:20:50 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 20:20:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:50 | D | sum error = [ 8.7679, 9.3777, 10.0536, 10.7920, 11.5454] +24-11-19 20:20:50 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 20:20:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:50 | D | sum error = [ 12.4016, 13.2769, 14.2056, 15.2078, 16.2783] +24-11-19 20:20:50 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 20:20:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:50 | D | sum error = [ 17.3865, 18.5976, 19.8611, 21.1873, 22.6158] +24-11-19 20:20:50 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 20:20:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:50 | D | sum error = [ 24.1066, 25.6881, 27.3474, 29.1062, 30.9624] +24-11-19 20:20:50 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 20:20:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:50 | D | sum error = [ 32.9195, 34.9647, 37.1620, 39.4358, 41.8594] +24-11-19 20:20:50 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 20:20:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:50 | D | sum error = [ 44.3980, 47.0780, 49.8888, 52.8186, 55.9236] +24-11-19 20:20:50 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 20:20:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:50 | D | sum error = [ 59.1756, 62.5965, 66.1862, 69.9433, 73.8991] +24-11-19 20:20:50 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 20:20:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:50 | D | sum error = [ 78.0218, 82.3713, 86.9185, 91.6896, 96.6688] +24-11-19 20:20:50 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 20:20:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:50 | D | sum error = [ 101.8734, 107.3317, 113.0438, 118.9917, 125.1945] +24-11-19 20:20:50 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 20:20:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:50 | D | sum error = [ 131.6468, 138.4157, 145.4530, 152.7803, 160.4138] +24-11-19 20:20:50 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 20:20:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:50 | D | sum error = [ 168.3758, 176.6374, 185.2416, 194.1595, 203.4243] +24-11-19 20:20:50 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 20:20:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:50 | D | sum error = [ 213.0488, 223.0277, 233.3543, 244.0274, 255.0488] +24-11-19 20:20:50 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 20:20:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:50 | D | sum error = [ 266.4262, 278.1786, 290.2861, 302.7739, 315.6242] +24-11-19 20:20:50 | D | best error = [ 3.9659, 3.9659, 3.9659, 3.9659, 3.9659] +24-11-19 20:20:50 | D | + error = [3.9659] +24-11-19 20:20:50 | D | - Calibrating model.layers.4.mlp.down_proj.weight +24-11-19 20:20:50 | D | + w: sint8 +24-11-19 20:20:50 | D | + x: None +24-11-19 20:20:50 | D | + y: None +24-11-19 20:20:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:50 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:20:51 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:20:51 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:20:51 | D | - range ratio = [ 1.0000] +24-11-19 20:20:51 | D | sum error = [ 0.7610] +24-11-19 20:20:51 | D | best error = [ 0.7610] +24-11-19 20:20:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:52 | D | sum error = [ 0.7554, 0.7529, 0.7528, 0.7558, 0.7587] +24-11-19 20:20:52 | D | best error = [ 0.6896, 0.6605, 0.6452, 0.6345, 0.6267] +24-11-19 20:20:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:52 | D | sum error = [ 0.7759, 0.7886, 0.8137, 0.8392, 0.8715] +24-11-19 20:20:52 | D | best error = [ 0.6213, 0.6177, 0.6149, 0.6128, 0.6112] +24-11-19 20:20:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:52 | D | sum error = [ 0.9092, 0.9504, 0.9979, 1.0510, 1.1083] +24-11-19 20:20:52 | D | best error = [ 0.6102, 0.6096, 0.6093, 0.6090, 0.6089] +24-11-19 20:20:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:52 | D | sum error = [ 1.1738, 1.2474, 1.3172, 1.3990, 1.4895] +24-11-19 20:20:52 | D | best error = [ 0.6088, 0.6087, 0.6087, 0.6087, 0.6087] +24-11-19 20:20:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:52 | D | sum error = [ 1.5875, 1.6907, 1.8037, 1.9220, 2.0559] +24-11-19 20:20:52 | D | best error = [ 0.6086, 0.6086, 0.6086, 0.6086, 0.6086] +24-11-19 20:20:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:52 | D | sum error = [ 2.1921, 2.3428, 2.5004, 2.6669, 2.8411] +24-11-19 20:20:52 | D | best error = [ 0.6086, 0.6086, 0.6086, 0.6086, 0.6086] +24-11-19 20:20:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:52 | D | sum error = [ 3.0298, 3.2308, 3.4409, 3.6655, 3.9078] +24-11-19 20:20:52 | D | best error = [ 0.6086, 0.6086, 0.6086, 0.6086, 0.6086] +24-11-19 20:20:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:52 | D | sum error = [ 4.1624, 4.4299, 4.7138, 5.0108, 5.3308] +24-11-19 20:20:52 | D | best error = [ 0.6086, 0.6086, 0.6086, 0.6086, 0.6086] +24-11-19 20:20:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:52 | D | sum error = [ 5.6655, 6.0202, 6.3921, 6.7865, 7.2008] +24-11-19 20:20:52 | D | best error = [ 0.6086, 0.6086, 0.6086, 0.6086, 0.6086] +24-11-19 20:20:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:52 | D | sum error = [ 7.6467, 8.1084, 8.5965, 9.1107, 9.6515] +24-11-19 20:20:52 | D | best error = [ 0.6086, 0.6086, 0.6086, 0.6086, 0.6086] +24-11-19 20:20:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:52 | D | sum error = [ 10.2231, 10.8212, 11.4493, 12.1153, 12.8120] +24-11-19 20:20:52 | D | best error = [ 0.6086, 0.6086, 0.6086, 0.6086, 0.6086] +24-11-19 20:20:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:52 | D | sum error = [ 13.5443, 14.3147, 15.1211, 15.9649, 16.8546] +24-11-19 20:20:52 | D | best error = [ 0.6086, 0.6086, 0.6086, 0.6086, 0.6086] +24-11-19 20:20:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:52 | D | sum error = [ 17.7858, 18.7611, 19.7846, 20.8581, 21.9838] +24-11-19 20:20:52 | D | best error = [ 0.6086, 0.6086, 0.6086, 0.6086, 0.6086] +24-11-19 20:20:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:52 | D | sum error = [ 23.1596, 24.3877, 25.6720, 27.0129, 28.4030] +24-11-19 20:20:52 | D | best error = [ 0.6086, 0.6086, 0.6086, 0.6086, 0.6086] +24-11-19 20:20:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:52 | D | sum error = [ 29.8524, 31.3582, 32.9249, 34.5543, 36.2428] +24-11-19 20:20:52 | D | best error = [ 0.6086, 0.6086, 0.6086, 0.6086, 0.6086] +24-11-19 20:20:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:52 | D | sum error = [ 37.9932, 39.8066, 41.6851, 43.6298, 45.6404] +24-11-19 20:20:52 | D | best error = [ 0.6086, 0.6086, 0.6086, 0.6086, 0.6086] +24-11-19 20:20:52 | D | + error = [0.6086] +24-11-19 20:20:52 | D | - Quantizing model.layers.4.self_attn.q_proj.weight +24-11-19 20:20:53 | D | - Quantizing model.layers.4.self_attn.k_proj.weight +24-11-19 20:20:53 | D | - Quantizing model.layers.4.self_attn.v_proj.weight +24-11-19 20:20:54 | D | - Quantizing model.layers.4.self_attn.o_proj.weight +24-11-19 20:20:55 | D | - Quantizing model.layers.4.mlp.up_proj.weight +24-11-19 20:20:56 | D | - Quantizing model.layers.4.mlp.gate_proj.weight +24-11-19 20:20:57 | D | - Quantizing model.layers.4.mlp.down_proj.weight +24-11-19 20:21:05 | D | - Quantizing layer model.layers.5 +24-11-19 20:21:05 | D | - Calibrating model.layers.5.self_attn.q_proj.weight +24-11-19 20:21:05 | D | + w: sint8 +24-11-19 20:21:05 | D | + x: None +24-11-19 20:21:05 | D | + y: None +24-11-19 20:21:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:21:05 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:21:05 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:21:05 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:21:05 | D | - range ratio = [ 1.0000] +24-11-19 20:21:05 | D | sum error = [ 2.9438] +24-11-19 20:21:05 | D | best error = [ 2.9438] +24-11-19 20:21:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:18 | D | sum error = [ 2.9702, 2.8730, 2.8835, 3.0460, 2.9560] +24-11-19 20:21:18 | D | best error = [ 2.9438, 2.8730, 2.8730, 2.8730, 2.8730] +24-11-19 20:21:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:18 | D | sum error = [ 3.2000, 3.2908, 3.5480, 3.6253, 3.9716] +24-11-19 20:21:18 | D | best error = [ 2.8730, 2.8730, 2.8730, 2.8730, 2.8730] +24-11-19 20:21:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:18 | D | sum error = [ 4.2769, 4.6104, 5.0236, 5.4319, 5.9599] +24-11-19 20:21:18 | D | best error = [ 2.8730, 2.8730, 2.8730, 2.8730, 2.8730] +24-11-19 20:21:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:18 | D | sum error = [ 6.6108, 7.2546, 7.7442, 8.6824, 9.5811] +24-11-19 20:21:18 | D | best error = [ 2.8730, 2.8730, 2.8730, 2.8730, 2.8730] +24-11-19 20:21:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:18 | D | sum error = [ 10.4232, 11.4038, 12.6057, 13.9893, 14.9680] +24-11-19 20:21:18 | D | best error = [ 2.8730, 2.8730, 2.8730, 2.8730, 2.8730] +24-11-19 20:21:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:18 | D | sum error = [ 16.8656, 18.1810, 19.5265, 21.4513, 23.3091] +24-11-19 20:21:18 | D | best error = [ 2.8730, 2.8730, 2.8730, 2.8730, 2.8730] +24-11-19 20:21:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:18 | D | sum error = [ 25.7100, 27.8150, 30.3887, 33.0506, 36.0936] +24-11-19 20:21:18 | D | best error = [ 2.8730, 2.8730, 2.8730, 2.8730, 2.8730] +24-11-19 20:21:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:18 | D | sum error = [ 39.0301, 42.4896, 46.2886, 50.2422, 54.5726] +24-11-19 20:21:18 | D | best error = [ 2.8730, 2.8730, 2.8730, 2.8730, 2.8730] +24-11-19 20:21:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:18 | D | sum error = [ 59.1991, 64.2578, 69.7674, 75.7969, 81.9414] +24-11-19 20:21:18 | D | best error = [ 2.8730, 2.8730, 2.8730, 2.8730, 2.8730] +24-11-19 20:21:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:18 | D | sum error = [ 88.6863, 96.3123, 104.2228, 113.0082, 121.9604] +24-11-19 20:21:18 | D | best error = [ 2.8730, 2.8730, 2.8730, 2.8730, 2.8730] +24-11-19 20:21:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:18 | D | sum error = [ 132.0678, 142.7851, 154.5784, 167.0609, 180.7760] +24-11-19 20:21:18 | D | best error = [ 2.8730, 2.8730, 2.8730, 2.8730, 2.8730] +24-11-19 20:21:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:18 | D | sum error = [ 195.5101, 211.4726, 228.7163, 247.4210, 266.8202] +24-11-19 20:21:18 | D | best error = [ 2.8730, 2.8730, 2.8730, 2.8730, 2.8730] +24-11-19 20:21:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:18 | D | sum error = [ 288.0917, 310.9020, 335.2656, 361.6329, 389.8982] +24-11-19 20:21:18 | D | best error = [ 2.8730, 2.8730, 2.8730, 2.8730, 2.8730] +24-11-19 20:21:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:18 | D | sum error = [ 420.5137, 453.4406, 488.7573, 526.6822, 568.0429] +24-11-19 20:21:18 | D | best error = [ 2.8730, 2.8730, 2.8730, 2.8730, 2.8730] +24-11-19 20:21:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:18 | D | sum error = [ 611.9839, 659.3436, 710.3509, 764.8920, 822.4494] +24-11-19 20:21:18 | D | best error = [ 2.8730, 2.8730, 2.8730, 2.8730, 2.8730] +24-11-19 20:21:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:18 | D | sum error = [ 883.8890, 949.0585, 1017.0689, 1087.7809, 1160.8271] +24-11-19 20:21:18 | D | best error = [ 2.8730, 2.8730, 2.8730, 2.8730, 2.8730] +24-11-19 20:21:18 | D | + error = [2.8730] +24-11-19 20:21:18 | D | - Calibrating model.layers.5.self_attn.k_proj.weight +24-11-19 20:21:18 | D | + w: sint8 +24-11-19 20:21:18 | D | + x: None +24-11-19 20:21:18 | D | + y: None +24-11-19 20:21:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:21:18 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:21:18 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:21:18 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:21:18 | D | - range ratio = [ 1.0000] +24-11-19 20:21:18 | D | sum error = [ 3.1031] +24-11-19 20:21:18 | D | best error = [ 3.1031] +24-11-19 20:21:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:31 | D | sum error = [ 3.2811, 3.1379, 3.3234, 3.2297, 3.0925] +24-11-19 20:21:31 | D | best error = [ 3.1031, 3.1031, 3.1031, 3.1031, 3.0925] +24-11-19 20:21:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:31 | D | sum error = [ 3.3329, 3.4614, 3.6950, 3.8064, 4.2454] +24-11-19 20:21:31 | D | best error = [ 3.0925, 3.0925, 3.0925, 3.0925, 3.0925] +24-11-19 20:21:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:31 | D | sum error = [ 4.1719, 4.8266, 4.8404, 5.5869, 5.7862] +24-11-19 20:21:31 | D | best error = [ 3.0925, 3.0925, 3.0925, 3.0925, 3.0925] +24-11-19 20:21:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:31 | D | sum error = [ 6.2838, 6.8132, 7.5603, 7.9032, 8.8458] +24-11-19 20:21:31 | D | best error = [ 3.0925, 3.0925, 3.0925, 3.0925, 3.0925] +24-11-19 20:21:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:31 | D | sum error = [ 9.4108, 10.1074, 11.2709, 12.0795, 13.3358] +24-11-19 20:21:31 | D | best error = [ 3.0925, 3.0925, 3.0925, 3.0925, 3.0925] +24-11-19 20:21:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:31 | D | sum error = [ 14.2216, 15.4278, 16.8508, 18.5808, 20.0956] +24-11-19 20:21:31 | D | best error = [ 3.0925, 3.0925, 3.0925, 3.0925, 3.0925] +24-11-19 20:21:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:31 | D | sum error = [ 21.6974, 23.6352, 25.5240, 28.1132, 30.4894] +24-11-19 20:21:31 | D | best error = [ 3.0925, 3.0925, 3.0925, 3.0925, 3.0925] +24-11-19 20:21:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:31 | D | sum error = [ 33.4523, 36.5133, 39.9811, 43.5995, 47.3705] +24-11-19 20:21:31 | D | best error = [ 3.0925, 3.0925, 3.0925, 3.0925, 3.0925] +24-11-19 20:21:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:31 | D | sum error = [ 51.5483, 55.9031, 60.6638, 66.2326, 71.9504] +24-11-19 20:21:31 | D | best error = [ 3.0925, 3.0925, 3.0925, 3.0925, 3.0925] +24-11-19 20:21:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:31 | D | sum error = [ 78.2549, 84.7710, 92.0971, 99.9733, 108.4659] +24-11-19 20:21:31 | D | best error = [ 3.0925, 3.0925, 3.0925, 3.0925, 3.0925] +24-11-19 20:21:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:31 | D | sum error = [ 117.9025, 127.6083, 138.7884, 150.1318, 163.1128] +24-11-19 20:21:31 | D | best error = [ 3.0925, 3.0925, 3.0925, 3.0925, 3.0925] +24-11-19 20:21:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:31 | D | sum error = [ 176.5023, 191.0984, 207.0197, 224.8472, 243.4237] +24-11-19 20:21:31 | D | best error = [ 3.0925, 3.0925, 3.0925, 3.0925, 3.0925] +24-11-19 20:21:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:31 | D | sum error = [ 263.5805, 285.5515, 308.9458, 334.8194, 362.4461] +24-11-19 20:21:31 | D | best error = [ 3.0925, 3.0925, 3.0925, 3.0925, 3.0925] +24-11-19 20:21:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:31 | D | sum error = [ 392.5289, 424.7274, 459.6625, 496.7890, 537.3706] +24-11-19 20:21:31 | D | best error = [ 3.0925, 3.0925, 3.0925, 3.0925, 3.0925] +24-11-19 20:21:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:31 | D | sum error = [ 580.8906, 627.9846, 677.8848, 732.0590, 789.6204] +24-11-19 20:21:31 | D | best error = [ 3.0925, 3.0925, 3.0925, 3.0925, 3.0925] +24-11-19 20:21:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:31 | D | sum error = [ 850.5786, 915.2542, 982.9153, 1052.8133, 1126.2116] +24-11-19 20:21:31 | D | best error = [ 3.0925, 3.0925, 3.0925, 3.0925, 3.0925] +24-11-19 20:21:31 | D | + error = [3.0925] +24-11-19 20:21:31 | D | - Calibrating model.layers.5.self_attn.v_proj.weight +24-11-19 20:21:31 | D | + w: sint8 +24-11-19 20:21:31 | D | + x: None +24-11-19 20:21:31 | D | + y: None +24-11-19 20:21:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:31 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:21:31 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:21:31 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:21:31 | D | - range ratio = [ 1.0000] +24-11-19 20:21:31 | D | sum error = [ 3.2207] +24-11-19 20:21:31 | D | best error = [ 3.2207] +24-11-19 20:21:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:32 | D | sum error = [ 3.1969, 3.1903, 3.1891, 3.2316, 3.2918] +24-11-19 20:21:32 | D | best error = [ 2.9506, 2.8579, 2.8138, 2.7875, 2.7750] +24-11-19 20:21:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:32 | D | sum error = [ 3.3910, 3.4902, 3.6576, 3.8258, 4.0203] +24-11-19 20:21:32 | D | best error = [ 2.7691, 2.7670, 2.7665, 2.7662, 2.7662] +24-11-19 20:21:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:32 | D | sum error = [ 4.2643, 4.5132, 4.8044, 5.1439, 5.4981] +24-11-19 20:21:32 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 20:21:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:32 | D | sum error = [ 5.8855, 6.2884, 6.7550, 7.2586, 7.7489] +24-11-19 20:21:32 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 20:21:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:32 | D | sum error = [ 8.3174, 8.9075, 9.5343, 10.2067, 10.9130] +24-11-19 20:21:32 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 20:21:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:32 | D | sum error = [ 11.6731, 12.4656, 13.3038, 14.1977, 15.1289] +24-11-19 20:21:32 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 20:21:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:32 | D | sum error = [ 16.1116, 17.1530, 18.2547, 19.4176, 20.6276] +24-11-19 20:21:32 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 20:21:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:32 | D | sum error = [ 21.9203, 23.2819, 24.6947, 26.1917, 27.7647] +24-11-19 20:21:32 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 20:21:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:32 | D | sum error = [ 29.3955, 31.1204, 32.9500, 34.8586, 36.8560] +24-11-19 20:21:32 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 20:21:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:32 | D | sum error = [ 38.9583, 41.1485, 43.4334, 45.8379, 48.3479] +24-11-19 20:21:32 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 20:21:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:32 | D | sum error = [ 50.9692, 53.7002, 56.5458, 59.5427, 62.6484] +24-11-19 20:21:32 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 20:21:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:32 | D | sum error = [ 65.8933, 69.2716, 72.8064, 76.4728, 80.2877] +24-11-19 20:21:32 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 20:21:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:32 | D | sum error = [ 84.2449, 88.3653, 92.6560, 97.1057, 101.7284] +24-11-19 20:21:32 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 20:21:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:32 | D | sum error = [ 106.5229, 111.5017, 116.6573, 121.9962, 127.5332] +24-11-19 20:21:32 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 20:21:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:32 | D | sum error = [ 133.2522, 139.1576, 145.2601, 151.5501, 158.0380] +24-11-19 20:21:32 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 20:21:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:32 | D | sum error = [ 164.7409, 171.6519, 178.7697, 186.0984, 193.6482] +24-11-19 20:21:32 | D | best error = [ 2.7662, 2.7662, 2.7662, 2.7662, 2.7662] +24-11-19 20:21:32 | D | + error = [2.7662] +24-11-19 20:21:32 | D | - Calibrating model.layers.5.self_attn.o_proj.weight +24-11-19 20:21:32 | D | + w: sint8 +24-11-19 20:21:32 | D | + x: None +24-11-19 20:21:32 | D | + y: None +24-11-19 20:21:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:32 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:21:32 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:21:32 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:21:32 | D | - range ratio = [ 1.0000] +24-11-19 20:21:32 | D | sum error = [ 0.5578] +24-11-19 20:21:32 | D | best error = [ 0.5578] +24-11-19 20:21:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:32 | D | sum error = [ 0.5512, 0.5490, 0.5468, 0.5503, 0.5523] +24-11-19 20:21:32 | D | best error = [ 0.5290, 0.5152, 0.5064, 0.5009, 0.4969] +24-11-19 20:21:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:32 | D | sum error = [ 0.5603, 0.5685, 0.5816, 0.5975, 0.6193] +24-11-19 20:21:32 | D | best error = [ 0.4942, 0.4922, 0.4909, 0.4899, 0.4893] +24-11-19 20:21:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:32 | D | sum error = [ 0.6422, 0.6693, 0.7014, 0.7367, 0.7781] +24-11-19 20:21:32 | D | best error = [ 0.4890, 0.4888, 0.4887, 0.4886, 0.4885] +24-11-19 20:21:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:32 | D | sum error = [ 0.8235, 0.8722, 0.9257, 0.9847, 1.0471] +24-11-19 20:21:32 | D | best error = [ 0.4884, 0.4884, 0.4883, 0.4883, 0.4883] +24-11-19 20:21:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:32 | D | sum error = [ 1.1166, 1.1899, 1.2679, 1.3516, 1.4426] +24-11-19 20:21:32 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 20:21:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:32 | D | sum error = [ 1.5390, 1.6377, 1.7476, 1.8601, 1.9824] +24-11-19 20:21:32 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 20:21:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:32 | D | sum error = [ 2.1106, 2.2478, 2.3918, 2.5427, 2.7042] +24-11-19 20:21:32 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 20:21:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:32 | D | sum error = [ 2.8737, 3.0518, 3.2399, 3.4383, 3.6482] +24-11-19 20:21:32 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 20:21:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:32 | D | sum error = [ 3.8672, 4.0983, 4.3406, 4.5960, 4.8627] +24-11-19 20:21:32 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 20:21:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:32 | D | sum error = [ 5.1450, 5.4393, 5.7480, 6.0723, 6.4136] +24-11-19 20:21:32 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 20:21:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:32 | D | sum error = [ 6.7699, 7.1436, 7.5337, 7.9423, 8.3707] +24-11-19 20:21:32 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 20:21:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:32 | D | sum error = [ 8.8178, 9.2846, 9.7741, 10.2839, 10.8165] +24-11-19 20:21:32 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 20:21:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:32 | D | sum error = [ 11.3722, 11.9516, 12.5558, 13.1850, 13.8411] +24-11-19 20:21:32 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 20:21:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:32 | D | sum error = [ 14.5241, 15.2346, 15.9743, 16.7411, 17.5404] +24-11-19 20:21:32 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 20:21:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:32 | D | sum error = [ 18.3707, 19.2344, 20.1338, 21.0671, 22.0357] +24-11-19 20:21:32 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 20:21:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:32 | D | sum error = [ 23.0434, 24.0899, 25.1768, 26.3070, 27.4810] +24-11-19 20:21:32 | D | best error = [ 0.4883, 0.4883, 0.4883, 0.4883, 0.4883] +24-11-19 20:21:32 | D | + error = [0.4883] +24-11-19 20:21:33 | D | - Calibrating model.layers.5.mlp.up_proj.weight +24-11-19 20:21:33 | D | + w: sint8 +24-11-19 20:21:33 | D | + x: None +24-11-19 20:21:33 | D | + y: None +24-11-19 20:21:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:33 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:21:33 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:21:33 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:21:33 | D | - range ratio = [ 1.0000] +24-11-19 20:21:33 | D | sum error = [ 4.5862] +24-11-19 20:21:33 | D | best error = [ 4.5862] +24-11-19 20:21:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:34 | D | sum error = [ 4.5516, 4.5467, 4.5680, 4.6272, 4.7099] +24-11-19 20:21:34 | D | best error = [ 4.2259, 4.0967, 4.0322, 3.9953, 3.9756] +24-11-19 20:21:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:34 | D | sum error = [ 4.8310, 5.0019, 5.1824, 5.4277, 5.7134] +24-11-19 20:21:34 | D | best error = [ 3.9664, 3.9626, 3.9611, 3.9607, 3.9606] +24-11-19 20:21:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:34 | D | sum error = [ 6.0547, 6.4220, 6.8324, 7.2941, 7.7936] +24-11-19 20:21:34 | D | best error = [ 3.9606, 3.9606, 3.9606, 3.9606, 3.9606] +24-11-19 20:21:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:34 | D | sum error = [ 8.3413, 8.9361, 9.5831, 10.2775, 11.0012] +24-11-19 20:21:34 | D | best error = [ 3.9606, 3.9606, 3.9606, 3.9606, 3.9606] +24-11-19 20:21:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:34 | D | sum error = [ 11.7902, 12.6287, 13.5190, 14.4614, 15.4734] +24-11-19 20:21:34 | D | best error = [ 3.9606, 3.9606, 3.9606, 3.9606, 3.9606] +24-11-19 20:21:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:34 | D | sum error = [ 16.5215, 17.6451, 18.8331, 20.0863, 21.4126] +24-11-19 20:21:34 | D | best error = [ 3.9606, 3.9606, 3.9606, 3.9606, 3.9606] +24-11-19 20:21:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:34 | D | sum error = [ 22.8186, 24.2783, 25.8361, 27.4702, 29.1931] +24-11-19 20:21:34 | D | best error = [ 3.9606, 3.9606, 3.9606, 3.9606, 3.9606] +24-11-19 20:21:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:34 | D | sum error = [ 30.9872, 32.8861, 34.8655, 36.9584, 39.1432] +24-11-19 20:21:34 | D | best error = [ 3.9606, 3.9606, 3.9606, 3.9606, 3.9606] +24-11-19 20:21:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:34 | D | sum error = [ 41.4343, 43.8397, 46.3717, 48.9995, 51.7681] +24-11-19 20:21:34 | D | best error = [ 3.9606, 3.9606, 3.9606, 3.9606, 3.9606] +24-11-19 20:21:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:34 | D | sum error = [ 54.6517, 57.6799, 60.8214, 64.1214, 67.5579] +24-11-19 20:21:34 | D | best error = [ 3.9606, 3.9606, 3.9606, 3.9606, 3.9606] +24-11-19 20:21:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:34 | D | sum error = [ 71.1425, 74.8789, 78.7812, 82.8400, 87.0639] +24-11-19 20:21:34 | D | best error = [ 3.9606, 3.9606, 3.9606, 3.9606, 3.9606] +24-11-19 20:21:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:34 | D | sum error = [ 91.4712, 96.0316, 100.7918, 105.7355, 110.8508] +24-11-19 20:21:34 | D | best error = [ 3.9606, 3.9606, 3.9606, 3.9606, 3.9606] +24-11-19 20:21:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:34 | D | sum error = [ 116.1701, 121.6836, 127.4152, 133.3493, 139.5002] +24-11-19 20:21:34 | D | best error = [ 3.9606, 3.9606, 3.9606, 3.9606, 3.9606] +24-11-19 20:21:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:34 | D | sum error = [ 145.8597, 152.4438, 159.2344, 166.2588, 173.5154] +24-11-19 20:21:34 | D | best error = [ 3.9606, 3.9606, 3.9606, 3.9606, 3.9606] +24-11-19 20:21:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:34 | D | sum error = [ 181.0018, 188.7156, 196.6628, 204.8482, 213.2882] +24-11-19 20:21:34 | D | best error = [ 3.9606, 3.9606, 3.9606, 3.9606, 3.9606] +24-11-19 20:21:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:34 | D | sum error = [ 221.9836, 230.9312, 240.1225, 249.5789, 259.2932] +24-11-19 20:21:34 | D | best error = [ 3.9606, 3.9606, 3.9606, 3.9606, 3.9606] +24-11-19 20:21:34 | D | + error = [3.9606] +24-11-19 20:21:34 | D | - Calibrating model.layers.5.mlp.gate_proj.weight +24-11-19 20:21:34 | D | + w: sint8 +24-11-19 20:21:34 | D | + x: None +24-11-19 20:21:34 | D | + y: None +24-11-19 20:21:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:34 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:21:34 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:21:34 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:21:34 | D | - range ratio = [ 1.0000] +24-11-19 20:21:34 | D | sum error = [ 5.1223] +24-11-19 20:21:34 | D | best error = [ 5.1223] +24-11-19 20:21:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:35 | D | sum error = [ 5.0716, 5.0709, 5.1107, 5.1681, 5.2537] +24-11-19 20:21:35 | D | best error = [ 4.7114, 4.5667, 4.4944, 4.4537, 4.4336] +24-11-19 20:21:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:35 | D | sum error = [ 5.3884, 5.5705, 5.7926, 6.0721, 6.3918] +24-11-19 20:21:35 | D | best error = [ 4.4239, 4.4197, 4.4182, 4.4178, 4.4177] +24-11-19 20:21:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:35 | D | sum error = [ 6.7617, 7.1759, 7.6664, 8.1629, 8.7250] +24-11-19 20:21:35 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:35 | D | sum error = [ 9.3425, 10.0090, 10.7380, 11.5170, 12.3399] +24-11-19 20:21:35 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:35 | D | sum error = [ 13.2510, 14.1947, 15.2034, 16.2798, 17.4202] +24-11-19 20:21:35 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:35 | D | sum error = [ 18.6503, 19.9376, 21.3058, 22.7547, 24.2971] +24-11-19 20:21:35 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:35 | D | sum error = [ 25.9075, 27.6046, 29.4311, 31.3538, 33.3543] +24-11-19 20:21:35 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:35 | D | sum error = [ 35.4899, 37.7378, 40.0919, 42.6042, 45.2209] +24-11-19 20:21:35 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:35 | D | sum error = [ 47.9978, 50.9427, 54.0336, 57.2726, 60.7066] +24-11-19 20:21:35 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:35 | D | sum error = [ 64.3231, 68.1054, 72.0969, 76.2818, 80.6776] +24-11-19 20:21:35 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:35 | D | sum error = [ 85.2932, 90.1497, 95.2442, 100.5823, 106.1826] +24-11-19 20:21:35 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:35 | D | sum error = [ 112.0340, 118.1615, 124.5764, 131.2820, 138.2915] +24-11-19 20:21:35 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:35 | D | sum error = [ 145.5983, 153.2472, 161.2276, 169.5542, 178.2486] +24-11-19 20:21:35 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:35 | D | sum error = [ 187.3046, 196.6994, 206.4796, 216.6385, 227.1956] +24-11-19 20:21:35 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:35 | D | sum error = [ 238.1446, 249.4987, 261.3030, 273.4964, 286.1217] +24-11-19 20:21:35 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:35 | D | sum error = [ 299.1518, 312.6075, 326.4931, 340.8173, 355.5813] +24-11-19 20:21:35 | D | best error = [ 4.4176, 4.4176, 4.4176, 4.4176, 4.4176] +24-11-19 20:21:35 | D | + error = [4.4176] +24-11-19 20:21:35 | D | - Calibrating model.layers.5.mlp.down_proj.weight +24-11-19 20:21:35 | D | + w: sint8 +24-11-19 20:21:35 | D | + x: None +24-11-19 20:21:35 | D | + y: None +24-11-19 20:21:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:35 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:21:35 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:21:35 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:21:35 | D | - range ratio = [ 1.0000] +24-11-19 20:21:35 | D | sum error = [ 0.7727] +24-11-19 20:21:35 | D | best error = [ 0.7727] +24-11-19 20:21:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:36 | D | sum error = [ 0.7662, 0.7601, 0.7551, 0.7531, 0.7533] +24-11-19 20:21:36 | D | best error = [ 0.7498, 0.7365, 0.7272, 0.7205, 0.7157] +24-11-19 20:21:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:36 | D | sum error = [ 0.7556, 0.7603, 0.7699, 0.7808, 0.7977] +24-11-19 20:21:36 | D | best error = [ 0.7118, 0.7091, 0.7073, 0.7061, 0.7054] +24-11-19 20:21:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:36 | D | sum error = [ 0.8166, 0.8428, 0.8730, 0.9090, 0.9479] +24-11-19 20:21:36 | D | best error = [ 0.7048, 0.7044, 0.7042, 0.7041, 0.7040] +24-11-19 20:21:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:36 | D | sum error = [ 0.9965, 1.0487, 1.1083, 1.1726, 1.2463] +24-11-19 20:21:36 | D | best error = [ 0.7040, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 20:21:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:36 | D | sum error = [ 1.3243, 1.4128, 1.5071, 1.6092, 1.7184] +24-11-19 20:21:36 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 20:21:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:36 | D | sum error = [ 1.8386, 1.9658, 2.1023, 2.2504, 2.4075] +24-11-19 20:21:36 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 20:21:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:36 | D | sum error = [ 2.5760, 2.7547, 2.9461, 3.1495, 3.3648] +24-11-19 20:21:36 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 20:21:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:36 | D | sum error = [ 3.5945, 3.8369, 4.0962, 4.3685, 4.6590] +24-11-19 20:21:36 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 20:21:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:36 | D | sum error = [ 4.9653, 5.2909, 5.6348, 5.9975, 6.3800] +24-11-19 20:21:36 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 20:21:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:36 | D | sum error = [ 6.7827, 7.2090, 7.6570, 8.1301, 8.6272] +24-11-19 20:21:36 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 20:21:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:36 | D | sum error = [ 9.1507, 9.7005, 10.2779, 10.8853, 11.5227] +24-11-19 20:21:36 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 20:21:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:36 | D | sum error = [ 12.1925, 12.8944, 13.6296, 14.4013, 15.2081] +24-11-19 20:21:36 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 20:21:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:36 | D | sum error = [ 16.0527, 16.9348, 17.8558, 18.8174, 19.8216] +24-11-19 20:21:36 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 20:21:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:36 | D | sum error = [ 20.8685, 21.9592, 23.0969, 24.2823, 25.5107] +24-11-19 20:21:36 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 20:21:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:36 | D | sum error = [ 26.7904, 28.1194, 29.4991, 30.9307, 32.4149] +24-11-19 20:21:36 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 20:21:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:36 | D | sum error = [ 33.9513, 35.5423, 37.1882, 38.8902, 40.6477] +24-11-19 20:21:36 | D | best error = [ 0.7039, 0.7039, 0.7039, 0.7039, 0.7039] +24-11-19 20:21:36 | D | + error = [0.7039] +24-11-19 20:21:36 | D | - Quantizing model.layers.5.self_attn.q_proj.weight +24-11-19 20:21:37 | D | - Quantizing model.layers.5.self_attn.k_proj.weight +24-11-19 20:21:38 | D | - Quantizing model.layers.5.self_attn.v_proj.weight +24-11-19 20:21:39 | D | - Quantizing model.layers.5.self_attn.o_proj.weight +24-11-19 20:21:40 | D | - Quantizing model.layers.5.mlp.up_proj.weight +24-11-19 20:21:41 | D | - Quantizing model.layers.5.mlp.gate_proj.weight +24-11-19 20:21:42 | D | - Quantizing model.layers.5.mlp.down_proj.weight +24-11-19 20:21:49 | D | - Quantizing layer model.layers.6 +24-11-19 20:21:49 | D | - Calibrating model.layers.6.self_attn.q_proj.weight +24-11-19 20:21:49 | D | + w: sint8 +24-11-19 20:21:49 | D | + x: None +24-11-19 20:21:49 | D | + y: None +24-11-19 20:21:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:21:49 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:21:50 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:21:50 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:21:50 | D | - range ratio = [ 1.0000] +24-11-19 20:21:50 | D | sum error = [ 4.7409] +24-11-19 20:21:50 | D | best error = [ 4.7409] +24-11-19 20:22:02 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:02 | D | sum error = [ 4.7019, 4.7398, 4.6935, 4.8281, 4.8530] +24-11-19 20:22:02 | D | best error = [ 4.7019, 4.7019, 4.6935, 4.6935, 4.6935] +24-11-19 20:22:02 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:02 | D | sum error = [ 5.0592, 5.1996, 5.5431, 5.7182, 5.9517] +24-11-19 20:22:02 | D | best error = [ 4.6935, 4.6935, 4.6935, 4.6935, 4.6935] +24-11-19 20:22:02 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:02 | D | sum error = [ 6.4853, 7.1281, 7.5293, 8.2800, 9.0003] +24-11-19 20:22:02 | D | best error = [ 4.6935, 4.6935, 4.6935, 4.6935, 4.6935] +24-11-19 20:22:02 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:02 | D | sum error = [ 9.7609, 10.7417, 11.5957, 12.8504, 13.9817] +24-11-19 20:22:02 | D | best error = [ 4.6935, 4.6935, 4.6935, 4.6935, 4.6935] +24-11-19 20:22:02 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:02 | D | sum error = [ 15.5404, 16.9200, 18.5442, 20.5962, 22.2574] +24-11-19 20:22:02 | D | best error = [ 4.6935, 4.6935, 4.6935, 4.6935, 4.6935] +24-11-19 20:22:02 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:02 | D | sum error = [ 24.3725, 26.8613, 29.3420, 32.1652, 35.2461] +24-11-19 20:22:02 | D | best error = [ 4.6935, 4.6935, 4.6935, 4.6935, 4.6935] +24-11-19 20:22:02 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:02 | D | sum error = [ 38.1862, 41.7652, 45.7889, 50.0381, 54.2661] +24-11-19 20:22:02 | D | best error = [ 4.6935, 4.6935, 4.6935, 4.6935, 4.6935] +24-11-19 20:22:02 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:02 | D | sum error = [ 59.2514, 64.6065, 69.9418, 76.0847, 82.6846] +24-11-19 20:22:02 | D | best error = [ 4.6935, 4.6935, 4.6935, 4.6935, 4.6935] +24-11-19 20:22:02 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:02 | D | sum error = [ 89.6681, 97.2134, 105.0552, 113.6726, 123.2190] +24-11-19 20:22:02 | D | best error = [ 4.6935, 4.6935, 4.6935, 4.6935, 4.6935] +24-11-19 20:22:02 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:02 | D | sum error = [ 133.3529, 144.2577, 155.7964, 168.1810, 181.2658] +24-11-19 20:22:02 | D | best error = [ 4.6935, 4.6935, 4.6935, 4.6935, 4.6935] +24-11-19 20:22:02 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:02 | D | sum error = [ 196.0176, 211.2731, 227.5498, 245.6979, 264.6926] +24-11-19 20:22:02 | D | best error = [ 4.6935, 4.6935, 4.6935, 4.6935, 4.6935] +24-11-19 20:22:02 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:02 | D | sum error = [ 284.7346, 307.0405, 330.8325, 355.6089, 382.4431] +24-11-19 20:22:02 | D | best error = [ 4.6935, 4.6935, 4.6935, 4.6935, 4.6935] +24-11-19 20:22:02 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:02 | D | sum error = [ 411.2506, 442.0384, 474.4732, 509.5295, 546.5677] +24-11-19 20:22:02 | D | best error = [ 4.6935, 4.6935, 4.6935, 4.6935, 4.6935] +24-11-19 20:22:02 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:02 | D | sum error = [ 586.0178, 628.1296, 673.6901, 720.8816, 771.7239] +24-11-19 20:22:02 | D | best error = [ 4.6935, 4.6935, 4.6935, 4.6935, 4.6935] +24-11-19 20:22:02 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:02 | D | sum error = [ 825.7537, 882.7352, 942.6687, 1005.9083, 1072.3464] +24-11-19 20:22:02 | D | best error = [ 4.6935, 4.6935, 4.6935, 4.6935, 4.6935] +24-11-19 20:22:02 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:02 | D | sum error = [ 1141.2587, 1213.7320, 1288.7508, 1365.5758, 1444.3381] +24-11-19 20:22:02 | D | best error = [ 4.6935, 4.6935, 4.6935, 4.6935, 4.6935] +24-11-19 20:22:02 | D | + error = [4.6935] +24-11-19 20:22:03 | D | - Calibrating model.layers.6.self_attn.k_proj.weight +24-11-19 20:22:03 | D | + w: sint8 +24-11-19 20:22:03 | D | + x: None +24-11-19 20:22:03 | D | + y: None +24-11-19 20:22:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:22:03 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:22:03 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:22:03 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:22:03 | D | - range ratio = [ 1.0000] +24-11-19 20:22:03 | D | sum error = [ 5.7295] +24-11-19 20:22:03 | D | best error = [ 5.7295] +24-11-19 20:22:16 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:16 | D | sum error = [ 5.4169, 5.6051, 6.2521, 5.6571, 5.5808] +24-11-19 20:22:16 | D | best error = [ 5.4169, 5.4169, 5.4169, 5.4169, 5.4169] +24-11-19 20:22:16 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:16 | D | sum error = [ 6.1001, 6.2207, 6.2813, 6.7664, 7.1645] +24-11-19 20:22:16 | D | best error = [ 5.4169, 5.4169, 5.4169, 5.4169, 5.4169] +24-11-19 20:22:16 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:16 | D | sum error = [ 7.6391, 8.4037, 8.5780, 8.9168, 10.2391] +24-11-19 20:22:16 | D | best error = [ 5.4169, 5.4169, 5.4169, 5.4169, 5.4169] +24-11-19 20:22:16 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:16 | D | sum error = [ 10.7864, 11.6368, 12.4775, 13.5886, 15.1869] +24-11-19 20:22:16 | D | best error = [ 5.4169, 5.4169, 5.4169, 5.4169, 5.4169] +24-11-19 20:22:16 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:16 | D | sum error = [ 16.0397, 17.2036, 18.6018, 20.2509, 22.1221] +24-11-19 20:22:16 | D | best error = [ 5.4169, 5.4169, 5.4169, 5.4169, 5.4169] +24-11-19 20:22:16 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:16 | D | sum error = [ 24.6929, 26.3694, 28.3959, 31.3177, 33.7572] +24-11-19 20:22:16 | D | best error = [ 5.4169, 5.4169, 5.4169, 5.4169, 5.4169] +24-11-19 20:22:16 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:16 | D | sum error = [ 37.3435, 40.2859, 44.0383, 47.3925, 52.3870] +24-11-19 20:22:16 | D | best error = [ 5.4169, 5.4169, 5.4169, 5.4169, 5.4169] +24-11-19 20:22:16 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:16 | D | sum error = [ 56.2139, 61.5985, 65.9685, 71.3600, 77.4411] +24-11-19 20:22:16 | D | best error = [ 5.4169, 5.4169, 5.4169, 5.4169, 5.4169] +24-11-19 20:22:16 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:16 | D | sum error = [ 83.3365, 90.2814, 96.8860, 104.4980, 113.3260] +24-11-19 20:22:16 | D | best error = [ 5.4169, 5.4169, 5.4169, 5.4169, 5.4169] +24-11-19 20:22:16 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:16 | D | sum error = [ 121.9933, 131.7974, 141.7604, 152.4378, 164.2503] +24-11-19 20:22:16 | D | best error = [ 5.4169, 5.4169, 5.4169, 5.4169, 5.4169] +24-11-19 20:22:16 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:16 | D | sum error = [ 177.4631, 191.5909, 206.0685, 222.1993, 239.0679] +24-11-19 20:22:16 | D | best error = [ 5.4169, 5.4169, 5.4169, 5.4169, 5.4169] +24-11-19 20:22:16 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:16 | D | sum error = [ 257.4266, 277.3824, 298.8422, 322.1250, 347.3017] +24-11-19 20:22:16 | D | best error = [ 5.4169, 5.4169, 5.4169, 5.4169, 5.4169] +24-11-19 20:22:16 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:16 | D | sum error = [ 374.3422, 403.8148, 435.2001, 469.5779, 505.2675] +24-11-19 20:22:16 | D | best error = [ 5.4169, 5.4169, 5.4169, 5.4169, 5.4169] +24-11-19 20:22:16 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:16 | D | sum error = [ 544.4182, 585.8974, 630.2342, 677.4390, 727.6172] +24-11-19 20:22:16 | D | best error = [ 5.4169, 5.4169, 5.4169, 5.4169, 5.4169] +24-11-19 20:22:16 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:16 | D | sum error = [ 782.4732, 839.7180, 901.2910, 966.3315, 1035.2964] +24-11-19 20:22:16 | D | best error = [ 5.4169, 5.4169, 5.4169, 5.4169, 5.4169] +24-11-19 20:22:16 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:16 | D | sum error = [ 1106.5692, 1181.1644, 1258.5108, 1337.1065, 1417.9897] +24-11-19 20:22:16 | D | best error = [ 5.4169, 5.4169, 5.4169, 5.4169, 5.4169] +24-11-19 20:22:16 | D | + error = [5.4169] +24-11-19 20:22:16 | D | - Calibrating model.layers.6.self_attn.v_proj.weight +24-11-19 20:22:16 | D | + w: sint8 +24-11-19 20:22:16 | D | + x: None +24-11-19 20:22:16 | D | + y: None +24-11-19 20:22:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:16 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:22:16 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:22:16 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:22:16 | D | - range ratio = [ 1.0000] +24-11-19 20:22:16 | D | sum error = [ 3.6930] +24-11-19 20:22:16 | D | best error = [ 3.6930] +24-11-19 20:22:16 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:16 | D | sum error = [ 3.6649, 3.6436, 3.6946, 3.7204, 3.7829] +24-11-19 20:22:16 | D | best error = [ 3.4312, 3.3332, 3.2876, 3.2600, 3.2448] +24-11-19 20:22:16 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:16 | D | sum error = [ 3.8904, 4.0170, 4.1881, 4.3906, 4.6270] +24-11-19 20:22:16 | D | best error = [ 3.2389, 3.2364, 3.2356, 3.2354, 3.2354] +24-11-19 20:22:16 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:16 | D | sum error = [ 4.9079, 5.2114, 5.5428, 5.9107, 6.3147] +24-11-19 20:22:16 | D | best error = [ 3.2354, 3.2354, 3.2354, 3.2354, 3.2354] +24-11-19 20:22:16 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:16 | D | sum error = [ 6.7705, 7.2611, 7.7659, 8.3416, 8.9461] +24-11-19 20:22:16 | D | best error = [ 3.2354, 3.2354, 3.2354, 3.2354, 3.2354] +24-11-19 20:22:16 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:16 | D | sum error = [ 9.5944, 10.2385, 10.9685, 11.7527, 12.5629] +24-11-19 20:22:16 | D | best error = [ 3.2354, 3.2354, 3.2354, 3.2354, 3.2354] +24-11-19 20:22:16 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:16 | D | sum error = [ 13.4453, 14.3634, 15.3295, 16.3724, 17.4661] +24-11-19 20:22:16 | D | best error = [ 3.2354, 3.2354, 3.2354, 3.2354, 3.2354] +24-11-19 20:22:16 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:16 | D | sum error = [ 18.6166, 19.8266, 21.1175, 22.4532, 23.8948] +24-11-19 20:22:16 | D | best error = [ 3.2354, 3.2354, 3.2354, 3.2354, 3.2354] +24-11-19 20:22:16 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:16 | D | sum error = [ 25.3935, 26.9887, 28.6647, 30.4160, 32.2779] +24-11-19 20:22:16 | D | best error = [ 3.2354, 3.2354, 3.2354, 3.2354, 3.2354] +24-11-19 20:22:16 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:16 | D | sum error = [ 34.2165, 36.2772, 38.4244, 40.6716, 43.0373] +24-11-19 20:22:16 | D | best error = [ 3.2354, 3.2354, 3.2354, 3.2354, 3.2354] +24-11-19 20:22:16 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:16 | D | sum error = [ 45.5281, 48.1278, 50.8392, 53.7037, 56.6951] +24-11-19 20:22:16 | D | best error = [ 3.2354, 3.2354, 3.2354, 3.2354, 3.2354] +24-11-19 20:22:16 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:16 | D | sum error = [ 59.8254, 63.1080, 66.5453, 70.1398, 73.9136] +24-11-19 20:22:16 | D | best error = [ 3.2354, 3.2354, 3.2354, 3.2354, 3.2354] +24-11-19 20:22:16 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:16 | D | sum error = [ 77.8499, 81.9611, 86.2641, 90.7389, 95.4137] +24-11-19 20:22:16 | D | best error = [ 3.2354, 3.2354, 3.2354, 3.2354, 3.2354] +24-11-19 20:22:16 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:16 | D | sum error = [ 100.2886, 105.3621, 110.6378, 116.1274, 121.8472] +24-11-19 20:22:16 | D | best error = [ 3.2354, 3.2354, 3.2354, 3.2354, 3.2354] +24-11-19 20:22:16 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:16 | D | sum error = [ 127.7894, 133.9556, 140.3634, 147.0226, 153.9043] +24-11-19 20:22:16 | D | best error = [ 3.2354, 3.2354, 3.2354, 3.2354, 3.2354] +24-11-19 20:22:16 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:16 | D | sum error = [ 161.0445, 168.4564, 176.1122, 184.0263, 192.1990] +24-11-19 20:22:16 | D | best error = [ 3.2354, 3.2354, 3.2354, 3.2354, 3.2354] +24-11-19 20:22:16 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:16 | D | sum error = [ 200.6278, 209.3280, 218.2847, 227.5165, 237.0095] +24-11-19 20:22:16 | D | best error = [ 3.2354, 3.2354, 3.2354, 3.2354, 3.2354] +24-11-19 20:22:16 | D | + error = [3.2354] +24-11-19 20:22:17 | D | - Calibrating model.layers.6.self_attn.o_proj.weight +24-11-19 20:22:17 | D | + w: sint8 +24-11-19 20:22:17 | D | + x: None +24-11-19 20:22:17 | D | + y: None +24-11-19 20:22:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:17 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:22:17 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:22:17 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:22:17 | D | - range ratio = [ 1.0000] +24-11-19 20:22:17 | D | sum error = [ 0.5783] +24-11-19 20:22:17 | D | best error = [ 0.5783] +24-11-19 20:22:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:17 | D | sum error = [ 0.5729, 0.5700, 0.5723, 0.5766, 0.5852] +24-11-19 20:22:17 | D | best error = [ 0.5436, 0.5273, 0.5186, 0.5126, 0.5089] +24-11-19 20:22:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:17 | D | sum error = [ 0.5990, 0.6154, 0.6377, 0.6647, 0.6923] +24-11-19 20:22:17 | D | best error = [ 0.5064, 0.5048, 0.5039, 0.5032, 0.5027] +24-11-19 20:22:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:17 | D | sum error = [ 0.7299, 0.7702, 0.8167, 0.8674, 0.9228] +24-11-19 20:22:17 | D | best error = [ 0.5024, 0.5021, 0.5020, 0.5019, 0.5018] +24-11-19 20:22:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:17 | D | sum error = [ 0.9812, 1.0492, 1.1188, 1.1957, 1.2779] +24-11-19 20:22:17 | D | best error = [ 0.5018, 0.5018, 0.5017, 0.5017, 0.5017] +24-11-19 20:22:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:17 | D | sum error = [ 1.3660, 1.4609, 1.5574, 1.6627, 1.7766] +24-11-19 20:22:17 | D | best error = [ 0.5017, 0.5017, 0.5017, 0.5017, 0.5017] +24-11-19 20:22:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:17 | D | sum error = [ 1.8952, 2.0214, 2.1555, 2.2975, 2.4468] +24-11-19 20:22:17 | D | best error = [ 0.5017, 0.5017, 0.5017, 0.5017, 0.5017] +24-11-19 20:22:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:17 | D | sum error = [ 2.6049, 2.7716, 2.9481, 3.1334, 3.3275] +24-11-19 20:22:17 | D | best error = [ 0.5017, 0.5017, 0.5017, 0.5017, 0.5017] +24-11-19 20:22:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:17 | D | sum error = [ 3.5340, 3.7525, 3.9811, 4.2243, 4.4768] +24-11-19 20:22:17 | D | best error = [ 0.5017, 0.5017, 0.5017, 0.5017, 0.5017] +24-11-19 20:22:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:17 | D | sum error = [ 4.7428, 5.0238, 5.3170, 5.6259, 5.9504] +24-11-19 20:22:17 | D | best error = [ 0.5017, 0.5017, 0.5017, 0.5017, 0.5017] +24-11-19 20:22:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:17 | D | sum error = [ 6.2919, 6.6472, 7.0211, 7.4143, 7.8257] +24-11-19 20:22:17 | D | best error = [ 0.5017, 0.5017, 0.5017, 0.5017, 0.5017] +24-11-19 20:22:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:17 | D | sum error = [ 8.2567, 8.7088, 9.1816, 9.6754, 10.1935] +24-11-19 20:22:17 | D | best error = [ 0.5017, 0.5017, 0.5017, 0.5017, 0.5017] +24-11-19 20:22:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:17 | D | sum error = [ 10.7345, 11.2986, 11.8897, 12.5051, 13.1484] +24-11-19 20:22:17 | D | best error = [ 0.5017, 0.5017, 0.5017, 0.5017, 0.5017] +24-11-19 20:22:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:17 | D | sum error = [ 13.8203, 14.5204, 15.2511, 16.0116, 16.8052] +24-11-19 20:22:17 | D | best error = [ 0.5017, 0.5017, 0.5017, 0.5017, 0.5017] +24-11-19 20:22:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:17 | D | sum error = [ 17.6304, 18.4893, 19.3809, 20.3077, 21.2717] +24-11-19 20:22:17 | D | best error = [ 0.5017, 0.5017, 0.5017, 0.5017, 0.5017] +24-11-19 20:22:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:17 | D | sum error = [ 22.2710, 23.3060, 24.3819, 25.4969, 26.6530] +24-11-19 20:22:17 | D | best error = [ 0.5017, 0.5017, 0.5017, 0.5017, 0.5017] +24-11-19 20:22:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:17 | D | sum error = [ 27.8495, 29.0872, 30.3676, 31.6895, 33.0535] +24-11-19 20:22:17 | D | best error = [ 0.5017, 0.5017, 0.5017, 0.5017, 0.5017] +24-11-19 20:22:17 | D | + error = [0.5017] +24-11-19 20:22:17 | D | - Calibrating model.layers.6.mlp.up_proj.weight +24-11-19 20:22:17 | D | + w: sint8 +24-11-19 20:22:17 | D | + x: None +24-11-19 20:22:17 | D | + y: None +24-11-19 20:22:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:17 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:22:17 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:22:18 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:22:18 | D | - range ratio = [ 1.0000] +24-11-19 20:22:18 | D | sum error = [ 4.8868] +24-11-19 20:22:18 | D | best error = [ 4.8868] +24-11-19 20:22:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:19 | D | sum error = [ 4.8526, 4.8472, 4.8578, 4.9151, 5.0190] +24-11-19 20:22:19 | D | best error = [ 4.5252, 4.3950, 4.3255, 4.2897, 4.2699] +24-11-19 20:22:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:19 | D | sum error = [ 5.1387, 5.3010, 5.5297, 5.7892, 6.1032] +24-11-19 20:22:19 | D | best error = [ 4.2614, 4.2574, 4.2563, 4.2561, 4.2560] +24-11-19 20:22:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:19 | D | sum error = [ 6.4435, 6.8461, 7.3014, 7.7975, 8.3383] +24-11-19 20:22:19 | D | best error = [ 4.2560, 4.2560, 4.2560, 4.2560, 4.2560] +24-11-19 20:22:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:19 | D | sum error = [ 8.9147, 9.5471, 10.2417, 10.9671, 11.7434] +24-11-19 20:22:19 | D | best error = [ 4.2560, 4.2560, 4.2560, 4.2560, 4.2560] +24-11-19 20:22:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:19 | D | sum error = [ 12.5941, 13.4807, 14.4303, 15.4485, 16.5032] +24-11-19 20:22:19 | D | best error = [ 4.2560, 4.2560, 4.2560, 4.2560, 4.2560] +24-11-19 20:22:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:19 | D | sum error = [ 17.6262, 18.8278, 20.1052, 21.4231, 22.8487] +24-11-19 20:22:19 | D | best error = [ 4.2560, 4.2560, 4.2560, 4.2560, 4.2560] +24-11-19 20:22:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:19 | D | sum error = [ 24.3466, 25.9058, 27.5620, 29.2975, 31.1419] +24-11-19 20:22:19 | D | best error = [ 4.2560, 4.2560, 4.2560, 4.2560, 4.2560] +24-11-19 20:22:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:19 | D | sum error = [ 33.0721, 35.0909, 37.2345, 39.4900, 41.8289] +24-11-19 20:22:19 | D | best error = [ 4.2560, 4.2560, 4.2560, 4.2560, 4.2560] +24-11-19 20:22:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:19 | D | sum error = [ 44.3004, 46.8903, 49.6099, 52.4600, 55.4501] +24-11-19 20:22:19 | D | best error = [ 4.2560, 4.2560, 4.2560, 4.2560, 4.2560] +24-11-19 20:22:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:19 | D | sum error = [ 58.5780, 61.8500, 65.2716, 68.8477, 72.5829] +24-11-19 20:22:19 | D | best error = [ 4.2560, 4.2560, 4.2560, 4.2560, 4.2560] +24-11-19 20:22:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:19 | D | sum error = [ 76.4814, 80.5294, 84.7512, 89.1713, 93.7460] +24-11-19 20:22:19 | D | best error = [ 4.2560, 4.2560, 4.2560, 4.2560, 4.2560] +24-11-19 20:22:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:19 | D | sum error = [ 98.5143, 103.4855, 108.6491, 114.0205, 119.6064] +24-11-19 20:22:19 | D | best error = [ 4.2560, 4.2560, 4.2560, 4.2560, 4.2560] +24-11-19 20:22:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:19 | D | sum error = [ 125.4155, 131.4310, 137.6777, 144.1441, 150.8561] +24-11-19 20:22:19 | D | best error = [ 4.2560, 4.2560, 4.2560, 4.2560, 4.2560] +24-11-19 20:22:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:19 | D | sum error = [ 157.8077, 164.9982, 172.4485, 180.1502, 188.1046] +24-11-19 20:22:19 | D | best error = [ 4.2560, 4.2560, 4.2560, 4.2560, 4.2560] +24-11-19 20:22:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:19 | D | sum error = [ 196.3328, 204.8256, 213.5889, 222.6256, 231.9451] +24-11-19 20:22:19 | D | best error = [ 4.2560, 4.2560, 4.2560, 4.2560, 4.2560] +24-11-19 20:22:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:19 | D | sum error = [ 241.5463, 251.4345, 261.6193, 272.0978, 282.8709] +24-11-19 20:22:19 | D | best error = [ 4.2560, 4.2560, 4.2560, 4.2560, 4.2560] +24-11-19 20:22:19 | D | + error = [4.2560] +24-11-19 20:22:19 | D | - Calibrating model.layers.6.mlp.gate_proj.weight +24-11-19 20:22:19 | D | + w: sint8 +24-11-19 20:22:19 | D | + x: None +24-11-19 20:22:19 | D | + y: None +24-11-19 20:22:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:19 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:22:19 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:22:19 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:22:19 | D | - range ratio = [ 1.0000] +24-11-19 20:22:19 | D | sum error = [ 5.5707] +24-11-19 20:22:19 | D | best error = [ 5.5707] +24-11-19 20:22:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:20 | D | sum error = [ 5.5254, 5.5205, 5.5440, 5.6019, 5.7026] +24-11-19 20:22:20 | D | best error = [ 5.1654, 5.0140, 4.9349, 4.8904, 4.8680] +24-11-19 20:22:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:20 | D | sum error = [ 5.8672, 6.0627, 6.3067, 6.5890, 6.9529] +24-11-19 20:22:20 | D | best error = [ 4.8583, 4.8541, 4.8523, 4.8517, 4.8517] +24-11-19 20:22:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:20 | D | sum error = [ 7.3547, 7.8204, 8.3321, 8.9105, 9.5247] +24-11-19 20:22:20 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:22:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:20 | D | sum error = [ 10.2047, 10.9269, 11.7396, 12.5952, 13.4910] +24-11-19 20:22:20 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:22:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:20 | D | sum error = [ 14.4834, 15.5510, 16.6435, 17.8386, 19.1145] +24-11-19 20:22:20 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:22:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:20 | D | sum error = [ 20.4456, 21.8713, 23.3787, 24.9958, 26.6804] +24-11-19 20:22:20 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:22:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:20 | D | sum error = [ 28.4716, 30.3585, 32.3990, 34.5067, 36.7643] +24-11-19 20:22:20 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:22:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:20 | D | sum error = [ 39.1378, 41.6597, 44.3052, 47.1081, 50.0818] +24-11-19 20:22:20 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:22:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:20 | D | sum error = [ 53.1929, 56.4774, 59.9488, 63.6147, 67.4631] +24-11-19 20:22:20 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:22:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:20 | D | sum error = [ 71.5453, 75.8420, 80.3764, 85.1467, 90.1833] +24-11-19 20:22:20 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:22:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:20 | D | sum error = [ 95.4741, 101.0533, 106.9119, 113.0910, 119.5666] +24-11-19 20:22:20 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:22:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:20 | D | sum error = [ 126.3740, 133.5334, 141.0513, 148.9148, 157.1657] +24-11-19 20:22:20 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:22:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:20 | D | sum error = [ 165.7903, 174.8128, 184.2455, 194.0939, 204.3867] +24-11-19 20:22:20 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:22:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:20 | D | sum error = [ 215.1320, 226.3283, 237.9995, 250.1346, 262.7594] +24-11-19 20:22:20 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:22:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:20 | D | sum error = [ 275.8828, 289.4940, 303.6430, 318.2910, 333.4552] +24-11-19 20:22:20 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:22:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:20 | D | sum error = [ 349.1392, 365.3541, 382.1106, 399.3984, 417.1990] +24-11-19 20:22:20 | D | best error = [ 4.8517, 4.8517, 4.8517, 4.8517, 4.8517] +24-11-19 20:22:20 | D | + error = [4.8517] +24-11-19 20:22:20 | D | - Calibrating model.layers.6.mlp.down_proj.weight +24-11-19 20:22:20 | D | + w: sint8 +24-11-19 20:22:20 | D | + x: None +24-11-19 20:22:20 | D | + y: None +24-11-19 20:22:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:20 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:22:20 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:22:20 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:22:20 | D | - range ratio = [ 1.0000] +24-11-19 20:22:20 | D | sum error = [ 0.9536] +24-11-19 20:22:20 | D | best error = [ 0.9536] +24-11-19 20:22:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:21 | D | sum error = [ 0.9436, 0.9375, 0.9316, 0.9281, 0.9297] +24-11-19 20:22:21 | D | best error = [ 0.9212, 0.9046, 0.8930, 0.8841, 0.8773] +24-11-19 20:22:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:21 | D | sum error = [ 0.9322, 0.9372, 0.9485, 0.9647, 0.9844] +24-11-19 20:22:21 | D | best error = [ 0.8727, 0.8693, 0.8666, 0.8649, 0.8636] +24-11-19 20:22:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:21 | D | sum error = [ 1.0102, 1.0420, 1.0785, 1.1235, 1.1752] +24-11-19 20:22:21 | D | best error = [ 0.8628, 0.8622, 0.8619, 0.8618, 0.8618] +24-11-19 20:22:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:21 | D | sum error = [ 1.2335, 1.3002, 1.3728, 1.4545, 1.5467] +24-11-19 20:22:21 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:22:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:21 | D | sum error = [ 1.6456, 1.7547, 1.8723, 2.0006, 2.1402] +24-11-19 20:22:21 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:22:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:21 | D | sum error = [ 2.2901, 2.4512, 2.6243, 2.8074, 3.0064] +24-11-19 20:22:21 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:22:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:21 | D | sum error = [ 3.2160, 3.4400, 3.6778, 3.9338, 4.2032] +24-11-19 20:22:21 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:22:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:21 | D | sum error = [ 4.4897, 4.7925, 5.1161, 5.4555, 5.8162] +24-11-19 20:22:21 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:22:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:21 | D | sum error = [ 6.2008, 6.6045, 7.0318, 7.4810, 7.9569] +24-11-19 20:22:21 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:22:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:21 | D | sum error = [ 8.4582, 8.9867, 9.5423, 10.1284, 10.7434] +24-11-19 20:22:21 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:22:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:21 | D | sum error = [ 11.3896, 12.0697, 12.7834, 13.5339, 14.3210] +24-11-19 20:22:21 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:22:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:21 | D | sum error = [ 15.1461, 16.0098, 16.9147, 17.8623, 18.8524] +24-11-19 20:22:21 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:22:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:21 | D | sum error = [ 19.8889, 20.9721, 22.1018, 23.2824, 24.5153] +24-11-19 20:22:21 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:22:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:21 | D | sum error = [ 25.7984, 27.1362, 28.5297, 29.9800, 31.4847] +24-11-19 20:22:21 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:22:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:21 | D | sum error = [ 33.0502, 34.6761, 36.3635, 38.1140, 39.9288] +24-11-19 20:22:21 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:22:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:21 | D | sum error = [ 41.8091, 43.7541, 45.7681, 47.8480, 49.9971] +24-11-19 20:22:21 | D | best error = [ 0.8617, 0.8617, 0.8617, 0.8617, 0.8617] +24-11-19 20:22:21 | D | + error = [0.8617] +24-11-19 20:22:21 | D | - Quantizing model.layers.6.self_attn.q_proj.weight +24-11-19 20:22:22 | D | - Quantizing model.layers.6.self_attn.k_proj.weight +24-11-19 20:22:23 | D | - Quantizing model.layers.6.self_attn.v_proj.weight +24-11-19 20:22:24 | D | - Quantizing model.layers.6.self_attn.o_proj.weight +24-11-19 20:22:25 | D | - Quantizing model.layers.6.mlp.up_proj.weight +24-11-19 20:22:25 | D | - Quantizing model.layers.6.mlp.gate_proj.weight +24-11-19 20:22:26 | D | - Quantizing model.layers.6.mlp.down_proj.weight +24-11-19 20:22:34 | D | - Quantizing layer model.layers.7 +24-11-19 20:22:34 | D | - Calibrating model.layers.7.self_attn.q_proj.weight +24-11-19 20:22:34 | D | + w: sint8 +24-11-19 20:22:34 | D | + x: None +24-11-19 20:22:34 | D | + y: None +24-11-19 20:22:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:22:34 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:22:34 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:22:35 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:22:35 | D | - range ratio = [ 1.0000] +24-11-19 20:22:35 | D | sum error = [ 5.7286] +24-11-19 20:22:35 | D | best error = [ 5.7286] +24-11-19 20:22:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:47 | D | sum error = [ 5.7707, 5.5519, 5.6226, 5.7661, 5.8725] +24-11-19 20:22:47 | D | best error = [ 5.7286, 5.5519, 5.5519, 5.5519, 5.5519] +24-11-19 20:22:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:47 | D | sum error = [ 6.1913, 6.2720, 6.7454, 6.9004, 7.4318] +24-11-19 20:22:47 | D | best error = [ 5.5519, 5.5519, 5.5519, 5.5519, 5.5519] +24-11-19 20:22:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:47 | D | sum error = [ 7.9486, 8.3582, 9.0564, 9.7658, 10.5277] +24-11-19 20:22:47 | D | best error = [ 5.5519, 5.5519, 5.5519, 5.5519, 5.5519] +24-11-19 20:22:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:47 | D | sum error = [ 11.3007, 12.3754, 13.5141, 14.4244, 16.1249] +24-11-19 20:22:47 | D | best error = [ 5.5519, 5.5519, 5.5519, 5.5519, 5.5519] +24-11-19 20:22:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:47 | D | sum error = [ 17.5062, 18.7966, 20.6149, 22.3324, 24.4055] +24-11-19 20:22:47 | D | best error = [ 5.5519, 5.5519, 5.5519, 5.5519, 5.5519] +24-11-19 20:22:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:47 | D | sum error = [ 26.3248, 28.5948, 31.2382, 34.0389, 36.7022] +24-11-19 20:22:47 | D | best error = [ 5.5519, 5.5519, 5.5519, 5.5519, 5.5519] +24-11-19 20:22:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:47 | D | sum error = [ 39.8655, 43.0552, 46.5004, 50.7153, 54.6225] +24-11-19 20:22:47 | D | best error = [ 5.5519, 5.5519, 5.5519, 5.5519, 5.5519] +24-11-19 20:22:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:47 | D | sum error = [ 59.1614, 64.0346, 69.2520, 74.7719, 80.7960] +24-11-19 20:22:47 | D | best error = [ 5.5519, 5.5519, 5.5519, 5.5519, 5.5519] +24-11-19 20:22:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:47 | D | sum error = [ 87.0442, 93.7954, 101.0410, 108.7421, 117.2643] +24-11-19 20:22:47 | D | best error = [ 5.5519, 5.5519, 5.5519, 5.5519, 5.5519] +24-11-19 20:22:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:47 | D | sum error = [ 125.9926, 135.3025, 145.5932, 155.9867, 167.7125] +24-11-19 20:22:47 | D | best error = [ 5.5519, 5.5519, 5.5519, 5.5519, 5.5519] +24-11-19 20:22:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:47 | D | sum error = [ 179.9229, 193.2532, 207.3025, 222.6183, 239.0825] +24-11-19 20:22:47 | D | best error = [ 5.5519, 5.5519, 5.5519, 5.5519, 5.5519] +24-11-19 20:22:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:47 | D | sum error = [ 256.3440, 275.3585, 295.9404, 317.6855, 340.4749] +24-11-19 20:22:47 | D | best error = [ 5.5519, 5.5519, 5.5519, 5.5519, 5.5519] +24-11-19 20:22:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:47 | D | sum error = [ 365.4761, 391.7155, 419.8291, 450.4237, 482.8495] +24-11-19 20:22:47 | D | best error = [ 5.5519, 5.5519, 5.5519, 5.5519, 5.5519] +24-11-19 20:22:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:47 | D | sum error = [ 517.2275, 554.1774, 593.9597, 636.1278, 681.5387] +24-11-19 20:22:47 | D | best error = [ 5.5519, 5.5519, 5.5519, 5.5519, 5.5519] +24-11-19 20:22:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:47 | D | sum error = [ 730.3294, 782.8561, 838.5431, 898.4032, 961.8593] +24-11-19 20:22:47 | D | best error = [ 5.5519, 5.5519, 5.5519, 5.5519, 5.5519] +24-11-19 20:22:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:47 | D | sum error = [ 1029.2103, 1100.3040, 1175.2374, 1253.4371, 1334.9127] +24-11-19 20:22:47 | D | best error = [ 5.5519, 5.5519, 5.5519, 5.5519, 5.5519] +24-11-19 20:22:47 | D | + error = [5.5519] +24-11-19 20:22:47 | D | - Calibrating model.layers.7.self_attn.k_proj.weight +24-11-19 20:22:47 | D | + w: sint8 +24-11-19 20:22:47 | D | + x: None +24-11-19 20:22:47 | D | + y: None +24-11-19 20:22:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:22:47 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:22:47 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:22:48 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:22:48 | D | - range ratio = [ 1.0000] +24-11-19 20:22:48 | D | sum error = [ 6.8134] +24-11-19 20:22:48 | D | best error = [ 6.8134] +24-11-19 20:23:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:01 | D | sum error = [ 6.7313, 7.1333, 6.9481, 6.9282, 7.0923] +24-11-19 20:23:01 | D | best error = [ 6.7313, 6.7313, 6.7313, 6.7313, 6.7313] +24-11-19 20:23:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:01 | D | sum error = [ 7.1686, 7.2068, 7.9989, 8.5373, 8.4070] +24-11-19 20:23:01 | D | best error = [ 6.7313, 6.7313, 6.7313, 6.7313, 6.7313] +24-11-19 20:23:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:01 | D | sum error = [ 9.7576, 10.6410, 10.9275, 11.2563, 12.7058] +24-11-19 20:23:01 | D | best error = [ 6.7313, 6.7313, 6.7313, 6.7313, 6.7313] +24-11-19 20:23:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:01 | D | sum error = [ 13.2867, 13.6849, 14.6838, 16.1102, 17.4206] +24-11-19 20:23:01 | D | best error = [ 6.7313, 6.7313, 6.7313, 6.7313, 6.7313] +24-11-19 20:23:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:01 | D | sum error = [ 18.5930, 20.1258, 21.6373, 23.2852, 25.2099] +24-11-19 20:23:01 | D | best error = [ 6.7313, 6.7313, 6.7313, 6.7313, 6.7313] +24-11-19 20:23:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:01 | D | sum error = [ 27.0980, 29.3616, 31.6917, 34.0932, 37.0828] +24-11-19 20:23:01 | D | best error = [ 6.7313, 6.7313, 6.7313, 6.7313, 6.7313] +24-11-19 20:23:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:01 | D | sum error = [ 38.8750, 42.3299, 45.9733, 49.6314, 53.8397] +24-11-19 20:23:01 | D | best error = [ 6.7313, 6.7313, 6.7313, 6.7313, 6.7313] +24-11-19 20:23:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:01 | D | sum error = [ 57.4788, 62.1491, 66.6443, 71.9338, 77.3732] +24-11-19 20:23:01 | D | best error = [ 6.7313, 6.7313, 6.7313, 6.7313, 6.7313] +24-11-19 20:23:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:01 | D | sum error = [ 83.0520, 89.1922, 96.0796, 103.8592, 111.0726] +24-11-19 20:23:01 | D | best error = [ 6.7313, 6.7313, 6.7313, 6.7313, 6.7313] +24-11-19 20:23:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:01 | D | sum error = [ 119.9177, 129.1519, 139.0183, 149.7456, 161.0827] +24-11-19 20:23:01 | D | best error = [ 6.7313, 6.7313, 6.7313, 6.7313, 6.7313] +24-11-19 20:23:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:01 | D | sum error = [ 173.3316, 187.6350, 202.5485, 218.2650, 235.1849] +24-11-19 20:23:01 | D | best error = [ 6.7313, 6.7313, 6.7313, 6.7313, 6.7313] +24-11-19 20:23:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:01 | D | sum error = [ 253.4732, 272.6193, 293.6209, 316.1583, 340.3589] +24-11-19 20:23:01 | D | best error = [ 6.7313, 6.7313, 6.7313, 6.7313, 6.7313] +24-11-19 20:23:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:01 | D | sum error = [ 366.5853, 394.4186, 424.9175, 456.9515, 491.3877] +24-11-19 20:23:01 | D | best error = [ 6.7313, 6.7313, 6.7313, 6.7313, 6.7313] +24-11-19 20:23:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:01 | D | sum error = [ 527.5777, 567.4664, 609.7833, 654.4118, 702.0806] +24-11-19 20:23:01 | D | best error = [ 6.7313, 6.7313, 6.7313, 6.7313, 6.7313] +24-11-19 20:23:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:01 | D | sum error = [ 753.8382, 808.7006, 866.8345, 928.8484, 994.2500] +24-11-19 20:23:01 | D | best error = [ 6.7313, 6.7313, 6.7313, 6.7313, 6.7313] +24-11-19 20:23:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:01 | D | sum error = [ 1063.2638, 1135.7489, 1211.7343, 1290.2709, 1371.9236] +24-11-19 20:23:01 | D | best error = [ 6.7313, 6.7313, 6.7313, 6.7313, 6.7313] +24-11-19 20:23:01 | D | + error = [6.7313] +24-11-19 20:23:01 | D | - Calibrating model.layers.7.self_attn.v_proj.weight +24-11-19 20:23:01 | D | + w: sint8 +24-11-19 20:23:01 | D | + x: None +24-11-19 20:23:01 | D | + y: None +24-11-19 20:23:01 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:01 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:23:01 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:23:01 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:23:01 | D | - range ratio = [ 1.0000] +24-11-19 20:23:01 | D | sum error = [ 3.9002] +24-11-19 20:23:01 | D | best error = [ 3.9002] +24-11-19 20:23:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:01 | D | sum error = [ 3.8518, 3.8352, 3.8778, 3.9066, 3.9715] +24-11-19 20:23:01 | D | best error = [ 3.6235, 3.5196, 3.4707, 3.4421, 3.4284] +24-11-19 20:23:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:01 | D | sum error = [ 4.0955, 4.2104, 4.3844, 4.6033, 4.8356] +24-11-19 20:23:01 | D | best error = [ 3.4217, 3.4183, 3.4170, 3.4167, 3.4167] +24-11-19 20:23:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:01 | D | sum error = [ 5.1188, 5.4420, 5.7931, 6.1731, 6.6066] +24-11-19 20:23:01 | D | best error = [ 3.4167, 3.4167, 3.4167, 3.4167, 3.4167] +24-11-19 20:23:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:01 | D | sum error = [ 7.0728, 7.5624, 8.1097, 8.6842, 9.3167] +24-11-19 20:23:01 | D | best error = [ 3.4167, 3.4167, 3.4167, 3.4167, 3.4167] +24-11-19 20:23:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:01 | D | sum error = [ 9.9590, 10.6858, 11.4289, 12.2552, 13.0898] +24-11-19 20:23:01 | D | best error = [ 3.4167, 3.4167, 3.4167, 3.4167, 3.4167] +24-11-19 20:23:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:01 | D | sum error = [ 13.9782, 14.9444, 15.9404, 17.0249, 18.1538] +24-11-19 20:23:01 | D | best error = [ 3.4167, 3.4167, 3.4167, 3.4167, 3.4167] +24-11-19 20:23:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:01 | D | sum error = [ 19.3622, 20.6182, 21.9405, 23.3480, 24.8357] +24-11-19 20:23:01 | D | best error = [ 3.4167, 3.4167, 3.4167, 3.4167, 3.4167] +24-11-19 20:23:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:01 | D | sum error = [ 26.3915, 28.0476, 29.7763, 31.6026, 33.5215] +24-11-19 20:23:01 | D | best error = [ 3.4167, 3.4167, 3.4167, 3.4167, 3.4167] +24-11-19 20:23:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:01 | D | sum error = [ 35.5527, 37.6781, 39.9011, 42.2427, 44.7178] +24-11-19 20:23:01 | D | best error = [ 3.4167, 3.4167, 3.4167, 3.4167, 3.4167] +24-11-19 20:23:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:01 | D | sum error = [ 47.3009, 50.0153, 52.8698, 55.8494, 58.9747] +24-11-19 20:23:01 | D | best error = [ 3.4167, 3.4167, 3.4167, 3.4167, 3.4167] +24-11-19 20:23:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:01 | D | sum error = [ 62.2365, 65.6818, 69.2661, 73.0066, 76.9260] +24-11-19 20:23:01 | D | best error = [ 3.4167, 3.4167, 3.4167, 3.4167, 3.4167] +24-11-19 20:23:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:01 | D | sum error = [ 81.0241, 85.3016, 89.7770, 94.4379, 99.2952] +24-11-19 20:23:01 | D | best error = [ 3.4167, 3.4167, 3.4167, 3.4167, 3.4167] +24-11-19 20:23:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:01 | D | sum error = [ 104.3624, 109.6500, 115.1450, 120.8410, 126.7707] +24-11-19 20:23:01 | D | best error = [ 3.4167, 3.4167, 3.4167, 3.4167, 3.4167] +24-11-19 20:23:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:01 | D | sum error = [ 132.9268, 139.3080, 145.9395, 152.8249, 159.9448] +24-11-19 20:23:01 | D | best error = [ 3.4167, 3.4167, 3.4167, 3.4167, 3.4167] +24-11-19 20:23:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:01 | D | sum error = [ 167.3248, 174.9736, 182.8780, 191.0583, 199.5052] +24-11-19 20:23:01 | D | best error = [ 3.4167, 3.4167, 3.4167, 3.4167, 3.4167] +24-11-19 20:23:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:01 | D | sum error = [ 208.2218, 217.2092, 226.4778, 236.0029, 245.8031] +24-11-19 20:23:01 | D | best error = [ 3.4167, 3.4167, 3.4167, 3.4167, 3.4167] +24-11-19 20:23:01 | D | + error = [3.4167] +24-11-19 20:23:01 | D | - Calibrating model.layers.7.self_attn.o_proj.weight +24-11-19 20:23:01 | D | + w: sint8 +24-11-19 20:23:01 | D | + x: None +24-11-19 20:23:01 | D | + y: None +24-11-19 20:23:01 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:01 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:23:02 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:23:02 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:23:02 | D | - range ratio = [ 1.0000] +24-11-19 20:23:02 | D | sum error = [ 0.6821] +24-11-19 20:23:02 | D | best error = [ 0.6821] +24-11-19 20:23:02 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:02 | D | sum error = [ 0.6771, 0.6733, 0.6721, 0.6736, 0.6836] +24-11-19 20:23:02 | D | best error = [ 0.6386, 0.6182, 0.6055, 0.5974, 0.5920] +24-11-19 20:23:02 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:02 | D | sum error = [ 0.6927, 0.7078, 0.7282, 0.7488, 0.7757] +24-11-19 20:23:02 | D | best error = [ 0.5881, 0.5850, 0.5830, 0.5815, 0.5802] +24-11-19 20:23:02 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:02 | D | sum error = [ 0.8115, 0.8514, 0.8949, 0.9436, 0.9985] +24-11-19 20:23:02 | D | best error = [ 0.5792, 0.5786, 0.5781, 0.5777, 0.5774] +24-11-19 20:23:02 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:02 | D | sum error = [ 1.0602, 1.1238, 1.1964, 1.2732, 1.3575] +24-11-19 20:23:02 | D | best error = [ 0.5772, 0.5769, 0.5768, 0.5766, 0.5765] +24-11-19 20:23:02 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:02 | D | sum error = [ 1.4466, 1.5425, 1.6432, 1.7525, 1.8713] +24-11-19 20:23:02 | D | best error = [ 0.5764, 0.5764, 0.5763, 0.5763, 0.5763] +24-11-19 20:23:02 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:02 | D | sum error = [ 1.9930, 2.1212, 2.2616, 2.4077, 2.5601] +24-11-19 20:23:02 | D | best error = [ 0.5763, 0.5762, 0.5762, 0.5762, 0.5762] +24-11-19 20:23:02 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:02 | D | sum error = [ 2.7267, 2.9008, 3.0797, 3.2784, 3.4794] +24-11-19 20:23:02 | D | best error = [ 0.5762, 0.5762, 0.5762, 0.5762, 0.5762] +24-11-19 20:23:02 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:02 | D | sum error = [ 3.6953, 3.9231, 4.1636, 4.4183, 4.6844] +24-11-19 20:23:02 | D | best error = [ 0.5762, 0.5762, 0.5762, 0.5762, 0.5762] +24-11-19 20:23:02 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:02 | D | sum error = [ 4.9644, 5.2606, 5.5712, 5.9003, 6.2458] +24-11-19 20:23:02 | D | best error = [ 0.5762, 0.5762, 0.5762, 0.5762, 0.5762] +24-11-19 20:23:02 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:02 | D | sum error = [ 6.6067, 6.9875, 7.3865, 7.8058, 8.2444] +24-11-19 20:23:02 | D | best error = [ 0.5762, 0.5762, 0.5762, 0.5762, 0.5762] +24-11-19 20:23:02 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:02 | D | sum error = [ 8.7050, 9.1881, 9.6933, 10.2208, 10.7737] +24-11-19 20:23:02 | D | best error = [ 0.5762, 0.5762, 0.5762, 0.5762, 0.5762] +24-11-19 20:23:02 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:02 | D | sum error = [ 11.3514, 11.9554, 12.5853, 13.2430, 13.9299] +24-11-19 20:23:02 | D | best error = [ 0.5762, 0.5762, 0.5762, 0.5762, 0.5762] +24-11-19 20:23:02 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:02 | D | sum error = [ 14.6515, 15.4007, 16.1834, 16.9994, 17.8518] +24-11-19 20:23:02 | D | best error = [ 0.5762, 0.5762, 0.5762, 0.5762, 0.5762] +24-11-19 20:23:02 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:02 | D | sum error = [ 18.7381, 19.6616, 20.6227, 21.6206, 22.6597] +24-11-19 20:23:02 | D | best error = [ 0.5762, 0.5762, 0.5762, 0.5762, 0.5762] +24-11-19 20:23:02 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:02 | D | sum error = [ 23.7408, 24.8609, 26.0251, 27.2332, 28.4864] +24-11-19 20:23:02 | D | best error = [ 0.5762, 0.5762, 0.5762, 0.5762, 0.5762] +24-11-19 20:23:02 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:02 | D | sum error = [ 29.7834, 31.1280, 32.5185, 33.9553, 35.4401] +24-11-19 20:23:02 | D | best error = [ 0.5762, 0.5762, 0.5762, 0.5762, 0.5762] +24-11-19 20:23:02 | D | + error = [0.5762] +24-11-19 20:23:02 | D | - Calibrating model.layers.7.mlp.up_proj.weight +24-11-19 20:23:02 | D | + w: sint8 +24-11-19 20:23:02 | D | + x: None +24-11-19 20:23:02 | D | + y: None +24-11-19 20:23:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:02 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:23:02 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:23:02 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:23:02 | D | - range ratio = [ 1.0000] +24-11-19 20:23:02 | D | sum error = [ 5.1919] +24-11-19 20:23:02 | D | best error = [ 5.1919] +24-11-19 20:23:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:03 | D | sum error = [ 5.1498, 5.1432, 5.1689, 5.2221, 5.3233] +24-11-19 20:23:03 | D | best error = [ 4.8322, 4.6933, 4.6240, 4.5843, 4.5645] +24-11-19 20:23:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:03 | D | sum error = [ 5.4592, 5.6338, 5.8797, 6.1611, 6.4735] +24-11-19 20:23:03 | D | best error = [ 4.5556, 4.5518, 4.5507, 4.5502, 4.5502] +24-11-19 20:23:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:03 | D | sum error = [ 6.8357, 7.2765, 7.7299, 8.2412, 8.8248] +24-11-19 20:23:03 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:23:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:03 | D | sum error = [ 9.4560, 10.1133, 10.8457, 11.6167, 12.4610] +24-11-19 20:23:03 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:23:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:03 | D | sum error = [ 13.3465, 14.2923, 15.3069, 16.3901, 17.5339] +24-11-19 20:23:03 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:23:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:03 | D | sum error = [ 18.7517, 20.0177, 21.3822, 22.8116, 24.3242] +24-11-19 20:23:03 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:23:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:03 | D | sum error = [ 25.9170, 27.5958, 29.3613, 31.2258, 33.1933] +24-11-19 20:23:03 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:23:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:03 | D | sum error = [ 35.2521, 37.4294, 39.7042, 42.1110, 44.6416] +24-11-19 20:23:03 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:23:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:03 | D | sum error = [ 47.2872, 50.0623, 52.9705, 56.0305, 59.2173] +24-11-19 20:23:03 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:23:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:03 | D | sum error = [ 62.5660, 66.0664, 69.7373, 73.5684, 77.5553] +24-11-19 20:23:03 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:23:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:03 | D | sum error = [ 81.7309, 86.0989, 90.6477, 95.3980, 100.3431] +24-11-19 20:23:03 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:23:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:03 | D | sum error = [ 105.5076, 110.8757, 116.4619, 122.2660, 128.3246] +24-11-19 20:23:03 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:23:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:03 | D | sum error = [ 134.5945, 141.1159, 147.8885, 154.9133, 162.1919] +24-11-19 20:23:03 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:23:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:03 | D | sum error = [ 169.7328, 177.5441, 185.6343, 194.0000, 202.6573] +24-11-19 20:23:03 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:23:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:03 | D | sum error = [ 211.5964, 220.8346, 230.3686, 240.2063, 250.3320] +24-11-19 20:23:03 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:23:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:03 | D | sum error = [ 260.7889, 271.5525, 282.6353, 294.0340, 305.7570] +24-11-19 20:23:03 | D | best error = [ 4.5501, 4.5501, 4.5501, 4.5501, 4.5501] +24-11-19 20:23:03 | D | + error = [4.5501] +24-11-19 20:23:04 | D | - Calibrating model.layers.7.mlp.gate_proj.weight +24-11-19 20:23:04 | D | + w: sint8 +24-11-19 20:23:04 | D | + x: None +24-11-19 20:23:04 | D | + y: None +24-11-19 20:23:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:04 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:23:04 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:23:04 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:23:04 | D | - range ratio = [ 1.0000] +24-11-19 20:23:04 | D | sum error = [ 5.9223] +24-11-19 20:23:04 | D | best error = [ 5.9223] +24-11-19 20:23:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:05 | D | sum error = [ 5.8661, 5.8521, 5.8828, 5.9467, 6.0569] +24-11-19 20:23:05 | D | best error = [ 5.5034, 5.3449, 5.2634, 5.2172, 5.1943] +24-11-19 20:23:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:05 | D | sum error = [ 6.2014, 6.4219, 6.6795, 6.9982, 7.3552] +24-11-19 20:23:05 | D | best error = [ 5.1833, 5.1791, 5.1776, 5.1771, 5.1770] +24-11-19 20:23:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:05 | D | sum error = [ 7.7940, 8.2657, 8.8200, 9.3941, 10.0525] +24-11-19 20:23:05 | D | best error = [ 5.1770, 5.1770, 5.1770, 5.1770, 5.1770] +24-11-19 20:23:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:05 | D | sum error = [ 10.7764, 11.5587, 12.3878, 13.2942, 14.2464] +24-11-19 20:23:05 | D | best error = [ 5.1770, 5.1770, 5.1770, 5.1770, 5.1770] +24-11-19 20:23:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:05 | D | sum error = [ 15.2810, 16.3903, 17.5615, 18.7878, 20.1114] +24-11-19 20:23:05 | D | best error = [ 5.1770, 5.1770, 5.1770, 5.1770, 5.1770] +24-11-19 20:23:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:05 | D | sum error = [ 21.5266, 23.0143, 24.6231, 26.3056, 28.0824] +24-11-19 20:23:05 | D | best error = [ 5.1770, 5.1770, 5.1770, 5.1770, 5.1770] +24-11-19 20:23:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:05 | D | sum error = [ 29.9974, 32.0230, 34.1272, 36.3978, 38.7791] +24-11-19 20:23:05 | D | best error = [ 5.1770, 5.1770, 5.1770, 5.1770, 5.1770] +24-11-19 20:23:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:05 | D | sum error = [ 41.3090, 44.0000, 46.8241, 49.8117, 52.9721] +24-11-19 20:23:05 | D | best error = [ 5.1770, 5.1770, 5.1770, 5.1770, 5.1770] +24-11-19 20:23:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:05 | D | sum error = [ 56.3122, 59.8575, 63.5769, 67.5152, 71.6632] +24-11-19 20:23:05 | D | best error = [ 5.1770, 5.1770, 5.1770, 5.1770, 5.1770] +24-11-19 20:23:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:05 | D | sum error = [ 76.0433, 80.6699, 85.5237, 90.6639, 96.0770] +24-11-19 20:23:05 | D | best error = [ 5.1770, 5.1770, 5.1770, 5.1770, 5.1770] +24-11-19 20:23:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:05 | D | sum error = [ 101.7702, 107.7605, 114.0730, 120.7215, 127.7246] +24-11-19 20:23:05 | D | best error = [ 5.1770, 5.1770, 5.1770, 5.1770, 5.1770] +24-11-19 20:23:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:05 | D | sum error = [ 135.0797, 142.7957, 150.9212, 159.4416, 168.3790] +24-11-19 20:23:05 | D | best error = [ 5.1770, 5.1770, 5.1770, 5.1770, 5.1770] +24-11-19 20:23:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:05 | D | sum error = [ 177.7607, 187.5707, 197.8629, 208.6275, 219.8592] +24-11-19 20:23:05 | D | best error = [ 5.1770, 5.1770, 5.1770, 5.1770, 5.1770] +24-11-19 20:23:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:05 | D | sum error = [ 231.5750, 243.8054, 256.5825, 269.8794, 283.6996] +24-11-19 20:23:05 | D | best error = [ 5.1770, 5.1770, 5.1770, 5.1770, 5.1770] +24-11-19 20:23:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:05 | D | sum error = [ 298.0739, 312.9944, 328.4881, 344.5592, 361.2046] +24-11-19 20:23:05 | D | best error = [ 5.1770, 5.1770, 5.1770, 5.1770, 5.1770] +24-11-19 20:23:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:05 | D | sum error = [ 378.4340, 396.2489, 414.6610, 433.6603, 453.2222] +24-11-19 20:23:05 | D | best error = [ 5.1770, 5.1770, 5.1770, 5.1770, 5.1770] +24-11-19 20:23:05 | D | + error = [5.1770] +24-11-19 20:23:05 | D | - Calibrating model.layers.7.mlp.down_proj.weight +24-11-19 20:23:05 | D | + w: sint8 +24-11-19 20:23:05 | D | + x: None +24-11-19 20:23:05 | D | + y: None +24-11-19 20:23:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:05 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:23:05 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:23:05 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:23:05 | D | - range ratio = [ 1.0000] +24-11-19 20:23:05 | D | sum error = [ 1.1057] +24-11-19 20:23:05 | D | best error = [ 1.1057] +24-11-19 20:23:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:06 | D | sum error = [ 1.0948, 1.0875, 1.0832, 1.0787, 1.0800] +24-11-19 20:23:06 | D | best error = [ 1.0685, 1.0492, 1.0366, 1.0263, 1.0187] +24-11-19 20:23:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:06 | D | sum error = [ 1.0856, 1.0927, 1.1052, 1.1243, 1.1482] +24-11-19 20:23:06 | D | best error = [ 1.0130, 1.0091, 1.0062, 1.0039, 1.0027] +24-11-19 20:23:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:06 | D | sum error = [ 1.1787, 1.2162, 1.2603, 1.3109, 1.3694] +24-11-19 20:23:06 | D | best error = [ 1.0016, 1.0009, 1.0006, 1.0003, 1.0002] +24-11-19 20:23:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:06 | D | sum error = [ 1.4399, 1.5148, 1.6007, 1.6961, 1.8010] +24-11-19 20:23:06 | D | best error = [ 1.0001, 1.0001, 1.0001, 1.0000, 1.0000] +24-11-19 20:23:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:06 | D | sum error = [ 1.9161, 2.0421, 2.1780, 2.3252, 2.4857] +24-11-19 20:23:06 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 20:23:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:06 | D | sum error = [ 2.6563, 2.8411, 3.0383, 3.2494, 3.4752] +24-11-19 20:23:06 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 20:23:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:06 | D | sum error = [ 3.7158, 3.9733, 4.2476, 4.5372, 4.8458] +24-11-19 20:23:06 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 20:23:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:06 | D | sum error = [ 5.1743, 5.5215, 5.8902, 6.2798, 6.6940] +24-11-19 20:23:06 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 20:23:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:06 | D | sum error = [ 7.1312, 7.5930, 8.0813, 8.5968, 9.1418] +24-11-19 20:23:06 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 20:23:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:06 | D | sum error = [ 9.7136, 10.3179, 10.9569, 11.6286, 12.3348] +24-11-19 20:23:06 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 20:23:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:06 | D | sum error = [ 13.0792, 13.8612, 14.6825, 15.5455, 16.4512] +24-11-19 20:23:06 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 20:23:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:06 | D | sum error = [ 17.4019, 18.3977, 19.4411, 20.5336, 21.6782] +24-11-19 20:23:06 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 20:23:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:06 | D | sum error = [ 22.8755, 24.1264, 25.4331, 26.7958, 28.2180] +24-11-19 20:23:06 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 20:23:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:06 | D | sum error = [ 29.7018, 31.2470, 32.8577, 34.5359, 36.2768] +24-11-19 20:23:06 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 20:23:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:06 | D | sum error = [ 38.0886, 39.9711, 41.9262, 43.9528, 46.0545] +24-11-19 20:23:06 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 20:23:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:06 | D | sum error = [ 48.2305, 50.4834, 52.8163, 55.2292, 57.7205] +24-11-19 20:23:06 | D | best error = [ 1.0000, 1.0000, 1.0000, 1.0000, 1.0000] +24-11-19 20:23:06 | D | + error = [1.0000] +24-11-19 20:23:06 | D | - Quantizing model.layers.7.self_attn.q_proj.weight +24-11-19 20:23:07 | D | - Quantizing model.layers.7.self_attn.k_proj.weight +24-11-19 20:23:08 | D | - Quantizing model.layers.7.self_attn.v_proj.weight +24-11-19 20:23:09 | D | - Quantizing model.layers.7.self_attn.o_proj.weight +24-11-19 20:23:10 | D | - Quantizing model.layers.7.mlp.up_proj.weight +24-11-19 20:23:10 | D | - Quantizing model.layers.7.mlp.gate_proj.weight +24-11-19 20:23:11 | D | - Quantizing model.layers.7.mlp.down_proj.weight +24-11-19 20:23:19 | D | - Quantizing layer model.layers.8 +24-11-19 20:23:19 | D | - Calibrating model.layers.8.self_attn.q_proj.weight +24-11-19 20:23:19 | D | + w: sint8 +24-11-19 20:23:19 | D | + x: None +24-11-19 20:23:19 | D | + y: None +24-11-19 20:23:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:23:19 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:23:19 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:23:20 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:23:20 | D | - range ratio = [ 1.0000] +24-11-19 20:23:20 | D | sum error = [ 6.6670] +24-11-19 20:23:20 | D | best error = [ 6.6670] +24-11-19 20:23:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:32 | D | sum error = [ 6.7387, 6.5965, 6.6816, 6.7549, 7.0999] +24-11-19 20:23:32 | D | best error = [ 6.6670, 6.5965, 6.5965, 6.5965, 6.5965] +24-11-19 20:23:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:32 | D | sum error = [ 7.1725, 7.3532, 7.5143, 8.0390, 8.3465] +24-11-19 20:23:32 | D | best error = [ 6.5965, 6.5965, 6.5965, 6.5965, 6.5965] +24-11-19 20:23:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:32 | D | sum error = [ 8.9683, 9.6710, 10.3810, 11.0718, 12.0346] +24-11-19 20:23:32 | D | best error = [ 6.5965, 6.5965, 6.5965, 6.5965, 6.5965] +24-11-19 20:23:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:32 | D | sum error = [ 12.8113, 14.2900, 15.1306, 16.3935, 17.6408] +24-11-19 20:23:32 | D | best error = [ 6.5965, 6.5965, 6.5965, 6.5965, 6.5965] +24-11-19 20:23:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:32 | D | sum error = [ 19.3250, 20.8692, 22.7082, 24.7426, 26.9448] +24-11-19 20:23:32 | D | best error = [ 6.5965, 6.5965, 6.5965, 6.5965, 6.5965] +24-11-19 20:23:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:32 | D | sum error = [ 29.2305, 31.4541, 34.4307, 37.3891, 40.5749] +24-11-19 20:23:32 | D | best error = [ 6.5965, 6.5965, 6.5965, 6.5965, 6.5965] +24-11-19 20:23:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:32 | D | sum error = [ 43.9530, 48.0272, 51.7571, 56.1409, 61.0500] +24-11-19 20:23:32 | D | best error = [ 6.5965, 6.5965, 6.5965, 6.5965, 6.5965] +24-11-19 20:23:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:32 | D | sum error = [ 65.8275, 71.3643, 76.6634, 83.1313, 90.0030] +24-11-19 20:23:32 | D | best error = [ 6.5965, 6.5965, 6.5965, 6.5965, 6.5965] +24-11-19 20:23:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:32 | D | sum error = [ 96.9795, 104.6323, 112.8503, 121.2078, 130.4463] +24-11-19 20:23:32 | D | best error = [ 6.5965, 6.5965, 6.5965, 6.5965, 6.5965] +24-11-19 20:23:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:32 | D | sum error = [ 140.5395, 151.7507, 162.9999, 175.8177, 188.9727] +24-11-19 20:23:32 | D | best error = [ 6.5965, 6.5965, 6.5965, 6.5965, 6.5965] +24-11-19 20:23:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:32 | D | sum error = [ 203.1941, 218.5249, 234.8124, 251.6994, 270.4608] +24-11-19 20:23:32 | D | best error = [ 6.5965, 6.5965, 6.5965, 6.5965, 6.5965] +24-11-19 20:23:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:32 | D | sum error = [ 290.0946, 311.0450, 333.5479, 356.8050, 382.8410] +24-11-19 20:23:32 | D | best error = [ 6.5965, 6.5965, 6.5965, 6.5965, 6.5965] +24-11-19 20:23:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:32 | D | sum error = [ 409.6972, 438.4771, 468.8963, 502.1892, 537.1318] +24-11-19 20:23:32 | D | best error = [ 6.5965, 6.5965, 6.5965, 6.5965, 6.5965] +24-11-19 20:23:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:32 | D | sum error = [ 574.3278, 614.0051, 656.4722, 701.1605, 748.9327] +24-11-19 20:23:32 | D | best error = [ 6.5965, 6.5965, 6.5965, 6.5965, 6.5965] +24-11-19 20:23:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:32 | D | sum error = [ 798.9803, 852.1011, 908.4900, 967.2688, 1028.6897] +24-11-19 20:23:32 | D | best error = [ 6.5965, 6.5965, 6.5965, 6.5965, 6.5965] +24-11-19 20:23:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:32 | D | sum error = [ 1093.0923, 1159.3875, 1227.9228, 1298.5224, 1370.6742] +24-11-19 20:23:32 | D | best error = [ 6.5965, 6.5965, 6.5965, 6.5965, 6.5965] +24-11-19 20:23:32 | D | + error = [6.5965] +24-11-19 20:23:32 | D | - Calibrating model.layers.8.self_attn.k_proj.weight +24-11-19 20:23:32 | D | + w: sint8 +24-11-19 20:23:32 | D | + x: None +24-11-19 20:23:32 | D | + y: None +24-11-19 20:23:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:23:32 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:23:32 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:23:33 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:23:33 | D | - range ratio = [ 1.0000] +24-11-19 20:23:33 | D | sum error = [ 7.5538] +24-11-19 20:23:33 | D | best error = [ 7.5538] +24-11-19 20:23:45 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:45 | D | sum error = [ 7.0349, 7.2551, 7.1568, 7.2092, 8.2048] +24-11-19 20:23:45 | D | best error = [ 7.0349, 7.0349, 7.0349, 7.0349, 7.0349] +24-11-19 20:23:45 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:45 | D | sum error = [ 7.3485, 7.9056, 8.0955, 9.2721, 9.3372] +24-11-19 20:23:45 | D | best error = [ 7.0349, 7.0349, 7.0349, 7.0349, 7.0349] +24-11-19 20:23:45 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:45 | D | sum error = [ 9.8283, 10.6651, 10.8874, 12.0156, 12.9257] +24-11-19 20:23:45 | D | best error = [ 7.0349, 7.0349, 7.0349, 7.0349, 7.0349] +24-11-19 20:23:45 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:45 | D | sum error = [ 13.8446, 14.7109, 16.2334, 17.5693, 18.8532] +24-11-19 20:23:45 | D | best error = [ 7.0349, 7.0349, 7.0349, 7.0349, 7.0349] +24-11-19 20:23:45 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:45 | D | sum error = [ 20.2903, 21.8760, 23.8941, 25.7385, 27.6698] +24-11-19 20:23:45 | D | best error = [ 7.0349, 7.0349, 7.0349, 7.0349, 7.0349] +24-11-19 20:23:45 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:45 | D | sum error = [ 30.6977, 32.4049, 35.0772, 38.7113, 41.6619] +24-11-19 20:23:45 | D | best error = [ 7.0349, 7.0349, 7.0349, 7.0349, 7.0349] +24-11-19 20:23:45 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:45 | D | sum error = [ 45.0187, 48.7189, 53.3777, 57.3422, 61.6984] +24-11-19 20:23:45 | D | best error = [ 7.0349, 7.0349, 7.0349, 7.0349, 7.0349] +24-11-19 20:23:45 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:45 | D | sum error = [ 66.7987, 71.7499, 76.6020, 82.4049, 88.8789] +24-11-19 20:23:45 | D | best error = [ 7.0349, 7.0349, 7.0349, 7.0349, 7.0349] +24-11-19 20:23:45 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:45 | D | sum error = [ 95.5254, 102.3938, 110.0037, 118.9285, 127.4035] +24-11-19 20:23:45 | D | best error = [ 7.0349, 7.0349, 7.0349, 7.0349, 7.0349] +24-11-19 20:23:45 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:45 | D | sum error = [ 137.3999, 147.8098, 159.0712, 170.8907, 183.5795] +24-11-19 20:23:45 | D | best error = [ 7.0349, 7.0349, 7.0349, 7.0349, 7.0349] +24-11-19 20:23:45 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:45 | D | sum error = [ 197.9559, 213.4594, 230.1244, 247.8476, 265.8905] +24-11-19 20:23:45 | D | best error = [ 7.0349, 7.0349, 7.0349, 7.0349, 7.0349] +24-11-19 20:23:45 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:45 | D | sum error = [ 286.6836, 308.3658, 330.2837, 355.3209, 382.5764] +24-11-19 20:23:45 | D | best error = [ 7.0349, 7.0349, 7.0349, 7.0349, 7.0349] +24-11-19 20:23:45 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:45 | D | sum error = [ 410.2731, 440.6616, 472.5040, 506.4706, 542.8730] +24-11-19 20:23:45 | D | best error = [ 7.0349, 7.0349, 7.0349, 7.0349, 7.0349] +24-11-19 20:23:45 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:45 | D | sum error = [ 580.7476, 621.5636, 664.8852, 710.4512, 759.3488] +24-11-19 20:23:45 | D | best error = [ 7.0349, 7.0349, 7.0349, 7.0349, 7.0349] +24-11-19 20:23:45 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:45 | D | sum error = [ 810.8913, 865.2421, 922.5218, 983.2216, 1045.5580] +24-11-19 20:23:45 | D | best error = [ 7.0349, 7.0349, 7.0349, 7.0349, 7.0349] +24-11-19 20:23:45 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:45 | D | sum error = [ 1111.0781, 1178.5024, 1247.8856, 1319.3586, 1392.0598] +24-11-19 20:23:45 | D | best error = [ 7.0349, 7.0349, 7.0349, 7.0349, 7.0349] +24-11-19 20:23:45 | D | + error = [7.0349] +24-11-19 20:23:46 | D | - Calibrating model.layers.8.self_attn.v_proj.weight +24-11-19 20:23:46 | D | + w: sint8 +24-11-19 20:23:46 | D | + x: None +24-11-19 20:23:46 | D | + y: None +24-11-19 20:23:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:46 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:23:46 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:23:46 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:23:46 | D | - range ratio = [ 1.0000] +24-11-19 20:23:46 | D | sum error = [ 3.9344] +24-11-19 20:23:46 | D | best error = [ 3.9344] +24-11-19 20:23:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:46 | D | sum error = [ 3.8926, 3.8772, 3.8873, 3.9323, 4.0105] +24-11-19 20:23:46 | D | best error = [ 3.6512, 3.5504, 3.4997, 3.4698, 3.4534] +24-11-19 20:23:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:46 | D | sum error = [ 4.1242, 4.2454, 4.4286, 4.6279, 4.8907] +24-11-19 20:23:46 | D | best error = [ 3.4463, 3.4440, 3.4434, 3.4433, 3.4433] +24-11-19 20:23:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:46 | D | sum error = [ 5.1537, 5.4629, 5.8161, 6.2122, 6.6280] +24-11-19 20:23:46 | D | best error = [ 3.4433, 3.4433, 3.4433, 3.4433, 3.4433] +24-11-19 20:23:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:46 | D | sum error = [ 7.1002, 7.6162, 8.1569, 8.7652, 9.3818] +24-11-19 20:23:46 | D | best error = [ 3.4433, 3.4433, 3.4433, 3.4433, 3.4433] +24-11-19 20:23:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:46 | D | sum error = [ 10.0546, 10.7865, 11.5488, 12.3538, 13.2216] +24-11-19 20:23:46 | D | best error = [ 3.4433, 3.4433, 3.4433, 3.4433, 3.4433] +24-11-19 20:23:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:46 | D | sum error = [ 14.1499, 15.1211, 16.1432, 17.2317, 18.3876] +24-11-19 20:23:46 | D | best error = [ 3.4433, 3.4433, 3.4433, 3.4433, 3.4433] +24-11-19 20:23:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:46 | D | sum error = [ 19.6046, 20.8939, 22.2465, 23.6882, 25.2040] +24-11-19 20:23:46 | D | best error = [ 3.4433, 3.4433, 3.4433, 3.4433, 3.4433] +24-11-19 20:23:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:46 | D | sum error = [ 26.7948, 28.4768, 30.2610, 32.1332, 34.0960] +24-11-19 20:23:46 | D | best error = [ 3.4433, 3.4433, 3.4433, 3.4433, 3.4433] +24-11-19 20:23:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:46 | D | sum error = [ 36.1610, 38.3397, 40.6262, 43.0293, 45.5564] +24-11-19 20:23:46 | D | best error = [ 3.4433, 3.4433, 3.4433, 3.4433, 3.4433] +24-11-19 20:23:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:46 | D | sum error = [ 48.2214, 50.9976, 53.9322, 56.9945, 60.2138] +24-11-19 20:23:46 | D | best error = [ 3.4433, 3.4433, 3.4433, 3.4433, 3.4433] +24-11-19 20:23:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:46 | D | sum error = [ 63.5773, 67.1119, 70.7912, 74.6487, 78.6868] +24-11-19 20:23:46 | D | best error = [ 3.4433, 3.4433, 3.4433, 3.4433, 3.4433] +24-11-19 20:23:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:46 | D | sum error = [ 82.9054, 87.2939, 91.8891, 96.6989, 101.7260] +24-11-19 20:23:46 | D | best error = [ 3.4433, 3.4433, 3.4433, 3.4433, 3.4433] +24-11-19 20:23:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:46 | D | sum error = [ 106.9595, 112.4235, 118.1161, 124.0438, 130.2284] +24-11-19 20:23:46 | D | best error = [ 3.4433, 3.4433, 3.4433, 3.4433, 3.4433] +24-11-19 20:23:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:46 | D | sum error = [ 136.6597, 143.3385, 150.2893, 157.5106, 164.9862] +24-11-19 20:23:46 | D | best error = [ 3.4433, 3.4433, 3.4433, 3.4433, 3.4433] +24-11-19 20:23:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:46 | D | sum error = [ 172.7420, 180.7684, 189.0803, 197.6736, 206.5512] +24-11-19 20:23:46 | D | best error = [ 3.4433, 3.4433, 3.4433, 3.4433, 3.4433] +24-11-19 20:23:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:46 | D | sum error = [ 215.7414, 225.2109, 234.9762, 245.0361, 255.3936] +24-11-19 20:23:46 | D | best error = [ 3.4433, 3.4433, 3.4433, 3.4433, 3.4433] +24-11-19 20:23:46 | D | + error = [3.4433] +24-11-19 20:23:46 | D | - Calibrating model.layers.8.self_attn.o_proj.weight +24-11-19 20:23:46 | D | + w: sint8 +24-11-19 20:23:46 | D | + x: None +24-11-19 20:23:46 | D | + y: None +24-11-19 20:23:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:46 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:23:46 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:23:46 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:23:47 | D | - range ratio = [ 1.0000] +24-11-19 20:23:47 | D | sum error = [ 0.8096] +24-11-19 20:23:47 | D | best error = [ 0.8096] +24-11-19 20:23:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:47 | D | sum error = [ 0.8000, 0.7995, 0.7971, 0.8013, 0.8064] +24-11-19 20:23:47 | D | best error = [ 0.7585, 0.7359, 0.7214, 0.7120, 0.7054] +24-11-19 20:23:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:47 | D | sum error = [ 0.8217, 0.8379, 0.8561, 0.8852, 0.9185] +24-11-19 20:23:47 | D | best error = [ 0.7013, 0.6979, 0.6958, 0.6943, 0.6933] +24-11-19 20:23:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:47 | D | sum error = [ 0.9598, 1.0034, 1.0572, 1.1127, 1.1827] +24-11-19 20:23:47 | D | best error = [ 0.6926, 0.6921, 0.6918, 0.6915, 0.6913] +24-11-19 20:23:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:47 | D | sum error = [ 1.2529, 1.3327, 1.4174, 1.5079, 1.6082] +24-11-19 20:23:47 | D | best error = [ 0.6912, 0.6910, 0.6910, 0.6909, 0.6909] +24-11-19 20:23:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:47 | D | sum error = [ 1.7179, 1.8306, 1.9561, 2.0893, 2.2328] +24-11-19 20:23:47 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 20:23:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:47 | D | sum error = [ 2.3795, 2.5404, 2.7091, 2.8878, 3.0774] +24-11-19 20:23:47 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 20:23:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:47 | D | sum error = [ 3.2810, 3.4930, 3.7223, 3.9590, 4.2095] +24-11-19 20:23:47 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 20:23:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:47 | D | sum error = [ 4.4749, 4.7533, 5.0477, 5.3595, 5.6879] +24-11-19 20:23:47 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 20:23:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:47 | D | sum error = [ 6.0301, 6.3916, 6.7731, 7.1746, 7.5948] +24-11-19 20:23:47 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 20:23:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:47 | D | sum error = [ 8.0367, 8.5019, 8.9922, 9.5043, 10.0418] +24-11-19 20:23:47 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 20:23:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:47 | D | sum error = [ 10.6058, 11.1952, 11.8134, 12.4589, 13.1388] +24-11-19 20:23:47 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 20:23:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:47 | D | sum error = [ 13.8464, 14.5855, 15.3607, 16.1674, 17.0097] +24-11-19 20:23:47 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 20:23:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:47 | D | sum error = [ 17.8858, 18.8016, 19.7513, 20.7394, 21.7689] +24-11-19 20:23:47 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 20:23:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:47 | D | sum error = [ 22.8394, 23.9508, 25.1062, 26.3046, 27.5461] +24-11-19 20:23:47 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 20:23:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:47 | D | sum error = [ 28.8337, 30.1673, 31.5511, 32.9831, 34.4627] +24-11-19 20:23:47 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 20:23:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:47 | D | sum error = [ 35.9916, 37.5708, 39.2014, 40.8839, 42.6198] +24-11-19 20:23:47 | D | best error = [ 0.6909, 0.6909, 0.6909, 0.6909, 0.6909] +24-11-19 20:23:47 | D | + error = [0.6909] +24-11-19 20:23:47 | D | - Calibrating model.layers.8.mlp.up_proj.weight +24-11-19 20:23:47 | D | + w: sint8 +24-11-19 20:23:47 | D | + x: None +24-11-19 20:23:47 | D | + y: None +24-11-19 20:23:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:47 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:23:47 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:23:47 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:23:47 | D | - range ratio = [ 1.0000] +24-11-19 20:23:47 | D | sum error = [ 5.3774] +24-11-19 20:23:47 | D | best error = [ 5.3774] +24-11-19 20:23:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:48 | D | sum error = [ 5.3321, 5.3351, 5.3543, 5.3946, 5.5052] +24-11-19 20:23:48 | D | best error = [ 5.0132, 4.8726, 4.8012, 4.7576, 4.7363] +24-11-19 20:23:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:48 | D | sum error = [ 5.6527, 5.8393, 6.0768, 6.3601, 6.6944] +24-11-19 20:23:48 | D | best error = [ 4.7260, 4.7213, 4.7198, 4.7195, 4.7195] +24-11-19 20:23:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:48 | D | sum error = [ 7.0789, 7.5251, 7.9921, 8.5439, 9.1425] +24-11-19 20:23:48 | D | best error = [ 4.7195, 4.7195, 4.7195, 4.7195, 4.7195] +24-11-19 20:23:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:48 | D | sum error = [ 9.7790, 10.4757, 11.2245, 12.0130, 12.9017] +24-11-19 20:23:48 | D | best error = [ 4.7195, 4.7195, 4.7195, 4.7195, 4.7195] +24-11-19 20:23:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:48 | D | sum error = [ 13.8250, 14.7986, 15.8302, 16.9527, 18.1381] +24-11-19 20:23:48 | D | best error = [ 4.7195, 4.7195, 4.7195, 4.7195, 4.7195] +24-11-19 20:23:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:48 | D | sum error = [ 19.3876, 20.7024, 22.1010, 23.5768, 25.1249] +24-11-19 20:23:48 | D | best error = [ 4.7195, 4.7195, 4.7195, 4.7195, 4.7195] +24-11-19 20:23:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:48 | D | sum error = [ 26.7780, 28.5054, 30.3336, 32.2627, 34.2886] +24-11-19 20:23:48 | D | best error = [ 4.7195, 4.7195, 4.7195, 4.7195, 4.7195] +24-11-19 20:23:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:48 | D | sum error = [ 36.4272, 38.6808, 41.0497, 43.5426, 46.1707] +24-11-19 20:23:48 | D | best error = [ 4.7195, 4.7195, 4.7195, 4.7195, 4.7195] +24-11-19 20:23:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:48 | D | sum error = [ 48.9082, 51.7839, 54.8086, 57.9861, 61.3056] +24-11-19 20:23:48 | D | best error = [ 4.7195, 4.7195, 4.7195, 4.7195, 4.7195] +24-11-19 20:23:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:48 | D | sum error = [ 64.7940, 68.4412, 72.2610, 76.2755, 80.4812] +24-11-19 20:23:48 | D | best error = [ 4.7195, 4.7195, 4.7195, 4.7195, 4.7195] +24-11-19 20:23:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:48 | D | sum error = [ 84.8724, 89.4507, 94.2394, 99.2453, 104.4623] +24-11-19 20:23:48 | D | best error = [ 4.7195, 4.7195, 4.7195, 4.7195, 4.7195] +24-11-19 20:23:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:48 | D | sum error = [ 109.9075, 115.5758, 121.4902, 127.6400, 134.0403] +24-11-19 20:23:48 | D | best error = [ 4.7195, 4.7195, 4.7195, 4.7195, 4.7195] +24-11-19 20:23:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:48 | D | sum error = [ 140.7117, 147.6461, 154.8535, 162.3430, 170.1166] +24-11-19 20:23:48 | D | best error = [ 4.7195, 4.7195, 4.7195, 4.7195, 4.7195] +24-11-19 20:23:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:48 | D | sum error = [ 178.1850, 186.5528, 195.2350, 204.2236, 213.5350] +24-11-19 20:23:48 | D | best error = [ 4.7195, 4.7195, 4.7195, 4.7195, 4.7195] +24-11-19 20:23:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:48 | D | sum error = [ 223.1598, 233.1233, 243.4068, 254.0320, 264.9842] +24-11-19 20:23:48 | D | best error = [ 4.7195, 4.7195, 4.7195, 4.7195, 4.7195] +24-11-19 20:23:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:48 | D | sum error = [ 276.2902, 287.9332, 299.9316, 312.2749, 324.9851] +24-11-19 20:23:48 | D | best error = [ 4.7195, 4.7195, 4.7195, 4.7195, 4.7195] +24-11-19 20:23:48 | D | + error = [4.7195] +24-11-19 20:23:48 | D | - Calibrating model.layers.8.mlp.gate_proj.weight +24-11-19 20:23:48 | D | + w: sint8 +24-11-19 20:23:48 | D | + x: None +24-11-19 20:23:48 | D | + y: None +24-11-19 20:23:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:48 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:23:48 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:23:49 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:23:49 | D | - range ratio = [ 1.0000] +24-11-19 20:23:49 | D | sum error = [ 5.9226] +24-11-19 20:23:49 | D | best error = [ 5.9226] +24-11-19 20:23:49 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:49 | D | sum error = [ 5.8856, 5.8680, 5.8978, 5.9719, 6.0745] +24-11-19 20:23:49 | D | best error = [ 5.5284, 5.3734, 5.2927, 5.2481, 5.2243] +24-11-19 20:23:49 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:49 | D | sum error = [ 6.2320, 6.4435, 6.7129, 7.0226, 7.4131] +24-11-19 20:23:49 | D | best error = [ 5.2130, 5.2084, 5.2066, 5.2061, 5.2060] +24-11-19 20:23:49 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:49 | D | sum error = [ 7.8404, 8.2978, 8.8501, 9.4462, 10.1134] +24-11-19 20:23:49 | D | best error = [ 5.2060, 5.2060, 5.2060, 5.2060, 5.2060] +24-11-19 20:23:49 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:49 | D | sum error = [ 10.8437, 11.6138, 12.4487, 13.3600, 14.3225] +24-11-19 20:23:49 | D | best error = [ 5.2060, 5.2060, 5.2060, 5.2060, 5.2060] +24-11-19 20:23:49 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:49 | D | sum error = [ 15.3508, 16.4837, 17.6711, 18.9111, 20.2572] +24-11-19 20:23:49 | D | best error = [ 5.2060, 5.2060, 5.2060, 5.2060, 5.2060] +24-11-19 20:23:49 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:49 | D | sum error = [ 21.7036, 23.2121, 24.8293, 26.5213, 28.3554] +24-11-19 20:23:49 | D | best error = [ 5.2060, 5.2060, 5.2060, 5.2060, 5.2060] +24-11-19 20:23:49 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:49 | D | sum error = [ 30.2847, 32.3119, 34.4789, 36.7643, 39.1834] +24-11-19 20:23:49 | D | best error = [ 5.2060, 5.2060, 5.2060, 5.2060, 5.2060] +24-11-19 20:23:49 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:49 | D | sum error = [ 41.7477, 44.4481, 47.3121, 50.3336, 53.5255] +24-11-19 20:23:49 | D | best error = [ 5.2060, 5.2060, 5.2060, 5.2060, 5.2060] +24-11-19 20:23:49 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:49 | D | sum error = [ 56.9278, 60.5081, 64.2799, 68.2671, 72.4799] +24-11-19 20:23:49 | D | best error = [ 5.2060, 5.2060, 5.2060, 5.2060, 5.2060] +24-11-19 20:23:49 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:49 | D | sum error = [ 76.9080, 81.6135, 86.5463, 91.7696, 97.2709] +24-11-19 20:23:49 | D | best error = [ 5.2060, 5.2060, 5.2060, 5.2060, 5.2060] +24-11-19 20:23:49 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:49 | D | sum error = [ 103.0761, 109.1873, 115.5879, 122.3349, 129.4302] +24-11-19 20:23:49 | D | best error = [ 5.2060, 5.2060, 5.2060, 5.2060, 5.2060] +24-11-19 20:23:49 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:49 | D | sum error = [ 136.8621, 144.6860, 152.8868, 161.5085, 170.5361] +24-11-19 20:23:49 | D | best error = [ 5.2060, 5.2060, 5.2060, 5.2060, 5.2060] +24-11-19 20:23:49 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:49 | D | sum error = [ 180.0041, 189.8967, 200.2570, 211.0673, 222.3638] +24-11-19 20:23:49 | D | best error = [ 5.2060, 5.2060, 5.2060, 5.2060, 5.2060] +24-11-19 20:23:49 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:49 | D | sum error = [ 234.1723, 246.4649, 259.2914, 272.6558, 286.5571] +24-11-19 20:23:49 | D | best error = [ 5.2060, 5.2060, 5.2060, 5.2060, 5.2060] +24-11-19 20:23:49 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:49 | D | sum error = [ 300.9777, 315.9683, 331.5113, 347.6517, 364.3256] +24-11-19 20:23:49 | D | best error = [ 5.2060, 5.2060, 5.2060, 5.2060, 5.2060] +24-11-19 20:23:49 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:49 | D | sum error = [ 381.5997, 399.4357, 417.8474, 436.8490, 456.4338] +24-11-19 20:23:49 | D | best error = [ 5.2060, 5.2060, 5.2060, 5.2060, 5.2060] +24-11-19 20:23:49 | D | + error = [5.2060] +24-11-19 20:23:50 | D | - Calibrating model.layers.8.mlp.down_proj.weight +24-11-19 20:23:50 | D | + w: sint8 +24-11-19 20:23:50 | D | + x: None +24-11-19 20:23:50 | D | + y: None +24-11-19 20:23:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:50 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:23:50 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:23:50 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:23:50 | D | - range ratio = [ 1.0000] +24-11-19 20:23:50 | D | sum error = [ 1.2621] +24-11-19 20:23:50 | D | best error = [ 1.2621] +24-11-19 20:23:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:51 | D | sum error = [ 1.2512, 1.2411, 1.2355, 1.2297, 1.2296] +24-11-19 20:23:51 | D | best error = [ 1.2154, 1.1891, 1.1712, 1.1578, 1.1480] +24-11-19 20:23:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:51 | D | sum error = [ 1.2363, 1.2419, 1.2570, 1.2741, 1.3012] +24-11-19 20:23:51 | D | best error = [ 1.1412, 1.1357, 1.1322, 1.1299, 1.1283] +24-11-19 20:23:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:51 | D | sum error = [ 1.3331, 1.3710, 1.4174, 1.4760, 1.5384] +24-11-19 20:23:51 | D | best error = [ 1.1273, 1.1265, 1.1260, 1.1258, 1.1256] +24-11-19 20:23:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:51 | D | sum error = [ 1.6121, 1.6956, 1.7865, 1.8906, 2.0041] +24-11-19 20:23:51 | D | best error = [ 1.1256, 1.1255, 1.1255, 1.1255, 1.1255] +24-11-19 20:23:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:51 | D | sum error = [ 2.1276, 2.2644, 2.4096, 2.5703, 2.7453] +24-11-19 20:23:51 | D | best error = [ 1.1255, 1.1255, 1.1255, 1.1255, 1.1255] +24-11-19 20:23:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:51 | D | sum error = [ 2.9300, 3.1303, 3.3441, 3.5729, 3.8186] +24-11-19 20:23:51 | D | best error = [ 1.1255, 1.1255, 1.1255, 1.1255, 1.1255] +24-11-19 20:23:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:51 | D | sum error = [ 4.0813, 4.3604, 4.6614, 4.9761, 5.3145] +24-11-19 20:23:51 | D | best error = [ 1.1255, 1.1255, 1.1255, 1.1255, 1.1255] +24-11-19 20:23:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:51 | D | sum error = [ 5.6718, 6.0512, 6.4556, 6.8817, 7.3325] +24-11-19 20:23:51 | D | best error = [ 1.1255, 1.1255, 1.1255, 1.1255, 1.1255] +24-11-19 20:23:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:51 | D | sum error = [ 7.8097, 8.3166, 8.8513, 9.4151, 10.0103] +24-11-19 20:23:51 | D | best error = [ 1.1255, 1.1255, 1.1255, 1.1255, 1.1255] +24-11-19 20:23:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:51 | D | sum error = [ 10.6381, 11.3001, 11.9980, 12.7328, 13.5062] +24-11-19 20:23:51 | D | best error = [ 1.1255, 1.1255, 1.1255, 1.1255, 1.1255] +24-11-19 20:23:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:51 | D | sum error = [ 14.3180, 15.1734, 16.0691, 17.0121, 18.0003] +24-11-19 20:23:51 | D | best error = [ 1.1255, 1.1255, 1.1255, 1.1255, 1.1255] +24-11-19 20:23:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:51 | D | sum error = [ 19.0360, 20.1207, 21.2567, 22.4465, 23.6917] +24-11-19 20:23:51 | D | best error = [ 1.1255, 1.1255, 1.1255, 1.1255, 1.1255] +24-11-19 20:23:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:51 | D | sum error = [ 24.9940, 26.3552, 27.7769, 29.2625, 30.8117] +24-11-19 20:23:51 | D | best error = [ 1.1255, 1.1255, 1.1255, 1.1255, 1.1255] +24-11-19 20:23:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:51 | D | sum error = [ 32.4279, 34.1137, 35.8687, 37.7001, 39.5982] +24-11-19 20:23:51 | D | best error = [ 1.1255, 1.1255, 1.1255, 1.1255, 1.1255] +24-11-19 20:23:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:51 | D | sum error = [ 41.5762, 43.6324, 45.7691, 47.9861, 50.2883] +24-11-19 20:23:51 | D | best error = [ 1.1255, 1.1255, 1.1255, 1.1255, 1.1255] +24-11-19 20:23:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:51 | D | sum error = [ 52.6772, 55.1526, 57.7198, 60.3775, 63.1276] +24-11-19 20:23:51 | D | best error = [ 1.1255, 1.1255, 1.1255, 1.1255, 1.1255] +24-11-19 20:23:51 | D | + error = [1.1255] +24-11-19 20:23:51 | D | - Quantizing model.layers.8.self_attn.q_proj.weight +24-11-19 20:23:52 | D | - Quantizing model.layers.8.self_attn.k_proj.weight +24-11-19 20:23:52 | D | - Quantizing model.layers.8.self_attn.v_proj.weight +24-11-19 20:23:53 | D | - Quantizing model.layers.8.self_attn.o_proj.weight +24-11-19 20:23:54 | D | - Quantizing model.layers.8.mlp.up_proj.weight +24-11-19 20:23:55 | D | - Quantizing model.layers.8.mlp.gate_proj.weight +24-11-19 20:23:56 | D | - Quantizing model.layers.8.mlp.down_proj.weight +24-11-19 20:24:04 | D | - Quantizing layer model.layers.9 +24-11-19 20:24:04 | D | - Calibrating model.layers.9.self_attn.q_proj.weight +24-11-19 20:24:04 | D | + w: sint8 +24-11-19 20:24:04 | D | + x: None +24-11-19 20:24:04 | D | + y: None +24-11-19 20:24:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:24:04 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:24:04 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:24:05 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:24:05 | D | - range ratio = [ 1.0000] +24-11-19 20:24:05 | D | sum error = [ 7.4218] +24-11-19 20:24:05 | D | best error = [ 7.4218] +24-11-19 20:24:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:18 | D | sum error = [ 7.4708, 7.4525, 7.4522, 7.5914, 7.6734] +24-11-19 20:24:18 | D | best error = [ 7.4218, 7.4218, 7.4218, 7.4218, 7.4218] +24-11-19 20:24:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:18 | D | sum error = [ 7.9913, 8.1983, 8.3881, 8.7187, 9.5399] +24-11-19 20:24:18 | D | best error = [ 7.4218, 7.4218, 7.4218, 7.4218, 7.4218] +24-11-19 20:24:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:18 | D | sum error = [ 10.0188, 10.5231, 11.1675, 12.0988, 13.0028] +24-11-19 20:24:18 | D | best error = [ 7.4218, 7.4218, 7.4218, 7.4218, 7.4218] +24-11-19 20:24:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:18 | D | sum error = [ 13.8816, 14.8788, 16.2821, 17.5822, 18.9381] +24-11-19 20:24:18 | D | best error = [ 7.4218, 7.4218, 7.4218, 7.4218, 7.4218] +24-11-19 20:24:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:18 | D | sum error = [ 20.5473, 21.9550, 23.8946, 26.0335, 28.3067] +24-11-19 20:24:18 | D | best error = [ 7.4218, 7.4218, 7.4218, 7.4218, 7.4218] +24-11-19 20:24:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:18 | D | sum error = [ 30.5142, 33.0544, 35.8049, 38.6123, 41.6819] +24-11-19 20:24:18 | D | best error = [ 7.4218, 7.4218, 7.4218, 7.4218, 7.4218] +24-11-19 20:24:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:18 | D | sum error = [ 45.1897, 48.5350, 52.5486, 56.7447, 61.4053] +24-11-19 20:24:18 | D | best error = [ 7.4218, 7.4218, 7.4218, 7.4218, 7.4218] +24-11-19 20:24:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:18 | D | sum error = [ 66.3372, 71.3105, 77.0905, 83.1222, 90.0021] +24-11-19 20:24:18 | D | best error = [ 7.4218, 7.4218, 7.4218, 7.4218, 7.4218] +24-11-19 20:24:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:18 | D | sum error = [ 96.9643, 104.4030, 112.4875, 121.5289, 130.7441] +24-11-19 20:24:18 | D | best error = [ 7.4218, 7.4218, 7.4218, 7.4218, 7.4218] +24-11-19 20:24:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:18 | D | sum error = [ 140.8014, 151.5231, 163.3329, 175.7705, 188.9109] +24-11-19 20:24:18 | D | best error = [ 7.4218, 7.4218, 7.4218, 7.4218, 7.4218] +24-11-19 20:24:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:18 | D | sum error = [ 203.1534, 218.3303, 234.5835, 251.6294, 270.0638] +24-11-19 20:24:18 | D | best error = [ 7.4218, 7.4218, 7.4218, 7.4218, 7.4218] +24-11-19 20:24:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:18 | D | sum error = [ 290.0499, 311.1369, 334.1209, 358.5894, 384.9480] +24-11-19 20:24:18 | D | best error = [ 7.4218, 7.4218, 7.4218, 7.4218, 7.4218] +24-11-19 20:24:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:18 | D | sum error = [ 413.3450, 443.8457, 476.2676, 510.9313, 548.6008] +24-11-19 20:24:18 | D | best error = [ 7.4218, 7.4218, 7.4218, 7.4218, 7.4218] +24-11-19 20:24:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:18 | D | sum error = [ 588.8095, 631.4823, 677.5074, 726.8661, 779.2267] +24-11-19 20:24:18 | D | best error = [ 7.4218, 7.4218, 7.4218, 7.4218, 7.4218] +24-11-19 20:24:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:18 | D | sum error = [ 836.0413, 896.3237, 960.3898, 1028.6359, 1100.5856] +24-11-19 20:24:18 | D | best error = [ 7.4218, 7.4218, 7.4218, 7.4218, 7.4218] +24-11-19 20:24:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:18 | D | sum error = [ 1176.4007, 1255.7426, 1338.0136, 1423.2120, 1510.7755] +24-11-19 20:24:18 | D | best error = [ 7.4218, 7.4218, 7.4218, 7.4218, 7.4218] +24-11-19 20:24:18 | D | + error = [7.4218] +24-11-19 20:24:18 | D | - Calibrating model.layers.9.self_attn.k_proj.weight +24-11-19 20:24:18 | D | + w: sint8 +24-11-19 20:24:18 | D | + x: None +24-11-19 20:24:18 | D | + y: None +24-11-19 20:24:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:24:18 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:24:18 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:24:18 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:24:18 | D | - range ratio = [ 1.0000] +24-11-19 20:24:18 | D | sum error = [ 7.9994] +24-11-19 20:24:18 | D | best error = [ 7.9994] +24-11-19 20:24:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:31 | D | sum error = [ 7.5959, 7.6786, 7.9913, 7.8110, 8.3627] +24-11-19 20:24:31 | D | best error = [ 7.5959, 7.5959, 7.5959, 7.5959, 7.5959] +24-11-19 20:24:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:31 | D | sum error = [ 8.4679, 8.6291, 8.9151, 9.5048, 10.0295] +24-11-19 20:24:31 | D | best error = [ 7.5959, 7.5959, 7.5959, 7.5959, 7.5959] +24-11-19 20:24:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:31 | D | sum error = [ 10.8329, 11.5551, 12.3763, 13.3372, 13.8185] +24-11-19 20:24:31 | D | best error = [ 7.5959, 7.5959, 7.5959, 7.5959, 7.5959] +24-11-19 20:24:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:31 | D | sum error = [ 14.8246, 16.1155, 18.0890, 18.9447, 20.6560] +24-11-19 20:24:31 | D | best error = [ 7.5959, 7.5959, 7.5959, 7.5959, 7.5959] +24-11-19 20:24:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:31 | D | sum error = [ 22.2896, 24.5781, 26.3438, 28.6899, 31.2669] +24-11-19 20:24:31 | D | best error = [ 7.5959, 7.5959, 7.5959, 7.5959, 7.5959] +24-11-19 20:24:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:31 | D | sum error = [ 33.7983, 35.8481, 38.8487, 42.5881, 45.7411] +24-11-19 20:24:31 | D | best error = [ 7.5959, 7.5959, 7.5959, 7.5959, 7.5959] +24-11-19 20:24:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:31 | D | sum error = [ 48.9445, 53.4579, 57.3948, 60.6302, 65.7452] +24-11-19 20:24:31 | D | best error = [ 7.5959, 7.5959, 7.5959, 7.5959, 7.5959] +24-11-19 20:24:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:31 | D | sum error = [ 71.7429, 76.6828, 83.1273, 89.0481, 95.9671] +24-11-19 20:24:31 | D | best error = [ 7.5959, 7.5959, 7.5959, 7.5959, 7.5959] +24-11-19 20:24:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:31 | D | sum error = [ 103.9268, 112.0290, 120.8340, 130.0873, 139.7642] +24-11-19 20:24:31 | D | best error = [ 7.5959, 7.5959, 7.5959, 7.5959, 7.5959] +24-11-19 20:24:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:31 | D | sum error = [ 151.0097, 162.9781, 175.1293, 189.1117, 203.1573] +24-11-19 20:24:31 | D | best error = [ 7.5959, 7.5959, 7.5959, 7.5959, 7.5959] +24-11-19 20:24:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:31 | D | sum error = [ 217.7694, 233.3906, 249.9013, 268.1772, 287.5252] +24-11-19 20:24:31 | D | best error = [ 7.5959, 7.5959, 7.5959, 7.5959, 7.5959] +24-11-19 20:24:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:31 | D | sum error = [ 308.5992, 330.8078, 354.9692, 380.1110, 407.3462] +24-11-19 20:24:31 | D | best error = [ 7.5959, 7.5959, 7.5959, 7.5959, 7.5959] +24-11-19 20:24:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:31 | D | sum error = [ 436.4670, 467.5222, 500.4957, 535.9497, 573.0511] +24-11-19 20:24:31 | D | best error = [ 7.5959, 7.5959, 7.5959, 7.5959, 7.5959] +24-11-19 20:24:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:31 | D | sum error = [ 612.7960, 654.9865, 700.2673, 748.9166, 800.6188] +24-11-19 20:24:31 | D | best error = [ 7.5959, 7.5959, 7.5959, 7.5959, 7.5959] +24-11-19 20:24:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:31 | D | sum error = [ 856.2611, 915.5276, 978.7937, 1045.5753, 1115.5834] +24-11-19 20:24:31 | D | best error = [ 7.5959, 7.5959, 7.5959, 7.5959, 7.5959] +24-11-19 20:24:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:31 | D | sum error = [ 1188.6584, 1265.6257, 1345.7485, 1429.0412, 1514.5918] +24-11-19 20:24:31 | D | best error = [ 7.5959, 7.5959, 7.5959, 7.5959, 7.5959] +24-11-19 20:24:31 | D | + error = [7.5959] +24-11-19 20:24:31 | D | - Calibrating model.layers.9.self_attn.v_proj.weight +24-11-19 20:24:31 | D | + w: sint8 +24-11-19 20:24:31 | D | + x: None +24-11-19 20:24:31 | D | + y: None +24-11-19 20:24:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:31 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:24:31 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:24:31 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:24:31 | D | - range ratio = [ 1.0000] +24-11-19 20:24:31 | D | sum error = [ 4.1008] +24-11-19 20:24:31 | D | best error = [ 4.1008] +24-11-19 20:24:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:32 | D | sum error = [ 4.0543, 4.0669, 4.0653, 4.1175, 4.1877] +24-11-19 20:24:32 | D | best error = [ 3.8249, 3.7303, 3.6782, 3.6503, 3.6344] +24-11-19 20:24:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:32 | D | sum error = [ 4.2953, 4.4418, 4.6285, 4.8514, 5.1078] +24-11-19 20:24:32 | D | best error = [ 3.6275, 3.6243, 3.6229, 3.6226, 3.6225] +24-11-19 20:24:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:32 | D | sum error = [ 5.3817, 5.7390, 6.1032, 6.5148, 6.9543] +24-11-19 20:24:32 | D | best error = [ 3.6225, 3.6225, 3.6225, 3.6225, 3.6225] +24-11-19 20:24:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:32 | D | sum error = [ 7.4459, 7.9869, 8.5428, 9.1589, 9.8105] +24-11-19 20:24:32 | D | best error = [ 3.6225, 3.6225, 3.6225, 3.6225, 3.6225] +24-11-19 20:24:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:32 | D | sum error = [ 10.5238, 11.2663, 12.0609, 12.8951, 13.7977] +24-11-19 20:24:32 | D | best error = [ 3.6225, 3.6225, 3.6225, 3.6225, 3.6225] +24-11-19 20:24:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:32 | D | sum error = [ 14.7601, 15.7645, 16.8402, 17.9784, 19.1674] +24-11-19 20:24:32 | D | best error = [ 3.6225, 3.6225, 3.6225, 3.6225, 3.6225] +24-11-19 20:24:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:32 | D | sum error = [ 20.4467, 21.7905, 23.2136, 24.6884, 26.2662] +24-11-19 20:24:32 | D | best error = [ 3.6225, 3.6225, 3.6225, 3.6225, 3.6225] +24-11-19 20:24:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:32 | D | sum error = [ 27.9118, 29.6725, 31.5097, 33.4357, 35.4692] +24-11-19 20:24:32 | D | best error = [ 3.6225, 3.6225, 3.6225, 3.6225, 3.6225] +24-11-19 20:24:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:32 | D | sum error = [ 37.6122, 39.8584, 42.2342, 44.7193, 47.3275] +24-11-19 20:24:32 | D | best error = [ 3.6225, 3.6225, 3.6225, 3.6225, 3.6225] +24-11-19 20:24:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:32 | D | sum error = [ 50.0813, 52.9641, 55.9967, 59.1859, 62.5130] +24-11-19 20:24:32 | D | best error = [ 3.6225, 3.6225, 3.6225, 3.6225, 3.6225] +24-11-19 20:24:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:32 | D | sum error = [ 66.0167, 69.6753, 73.5065, 77.5307, 81.7249] +24-11-19 20:24:32 | D | best error = [ 3.6225, 3.6225, 3.6225, 3.6225, 3.6225] +24-11-19 20:24:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:32 | D | sum error = [ 86.0994, 90.6753, 95.4541, 100.4583, 105.6767] +24-11-19 20:24:32 | D | best error = [ 3.6225, 3.6225, 3.6225, 3.6225, 3.6225] +24-11-19 20:24:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:32 | D | sum error = [ 111.1114, 116.7688, 122.6490, 128.7627, 135.1363] +24-11-19 20:24:32 | D | best error = [ 3.6225, 3.6225, 3.6225, 3.6225, 3.6225] +24-11-19 20:24:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:32 | D | sum error = [ 141.7575, 148.6393, 155.7780, 163.1998, 170.8684] +24-11-19 20:24:32 | D | best error = [ 3.6225, 3.6225, 3.6225, 3.6225, 3.6225] +24-11-19 20:24:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:32 | D | sum error = [ 178.8282, 187.0745, 195.6004, 204.4255, 213.5486] +24-11-19 20:24:32 | D | best error = [ 3.6225, 3.6225, 3.6225, 3.6225, 3.6225] +24-11-19 20:24:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:32 | D | sum error = [ 222.9695, 232.6845, 242.7011, 253.0165, 263.6445] +24-11-19 20:24:32 | D | best error = [ 3.6225, 3.6225, 3.6225, 3.6225, 3.6225] +24-11-19 20:24:32 | D | + error = [3.6225] +24-11-19 20:24:32 | D | - Calibrating model.layers.9.self_attn.o_proj.weight +24-11-19 20:24:32 | D | + w: sint8 +24-11-19 20:24:32 | D | + x: None +24-11-19 20:24:32 | D | + y: None +24-11-19 20:24:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:32 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:24:32 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:24:32 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:24:32 | D | - range ratio = [ 1.0000] +24-11-19 20:24:32 | D | sum error = [ 0.9777] +24-11-19 20:24:32 | D | best error = [ 0.9777] +24-11-19 20:24:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:32 | D | sum error = [ 0.9669, 0.9611, 0.9569, 0.9631, 0.9681] +24-11-19 20:24:32 | D | best error = [ 0.9211, 0.8939, 0.8770, 0.8658, 0.8583] +24-11-19 20:24:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:32 | D | sum error = [ 0.9801, 0.9952, 1.0202, 1.0480, 1.0820] +24-11-19 20:24:32 | D | best error = [ 0.8528, 0.8487, 0.8460, 0.8438, 0.8422] +24-11-19 20:24:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:32 | D | sum error = [ 1.1219, 1.1696, 1.2279, 1.2908, 1.3590] +24-11-19 20:24:32 | D | best error = [ 0.8408, 0.8398, 0.8389, 0.8381, 0.8375] +24-11-19 20:24:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:32 | D | sum error = [ 1.4399, 1.5252, 1.6176, 1.7220, 1.8314] +24-11-19 20:24:32 | D | best error = [ 0.8371, 0.8368, 0.8365, 0.8364, 0.8363] +24-11-19 20:24:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:32 | D | sum error = [ 1.9513, 2.0796, 2.2216, 2.3632, 2.5201] +24-11-19 20:24:32 | D | best error = [ 0.8362, 0.8361, 0.8361, 0.8360, 0.8360] +24-11-19 20:24:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:32 | D | sum error = [ 2.6873, 2.8631, 3.0544, 3.2521, 3.4660] +24-11-19 20:24:32 | D | best error = [ 0.8360, 0.8360, 0.8360, 0.8360, 0.8360] +24-11-19 20:24:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:32 | D | sum error = [ 3.6873, 3.9280, 4.1804, 4.4491, 4.7306] +24-11-19 20:24:32 | D | best error = [ 0.8360, 0.8360, 0.8360, 0.8360, 0.8360] +24-11-19 20:24:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:32 | D | sum error = [ 5.0258, 5.3404, 5.6725, 6.0199, 6.3873] +24-11-19 20:24:32 | D | best error = [ 0.8360, 0.8360, 0.8360, 0.8360, 0.8360] +24-11-19 20:24:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:32 | D | sum error = [ 6.7752, 7.1806, 7.6079, 8.0593, 8.5285] +24-11-19 20:24:32 | D | best error = [ 0.8360, 0.8360, 0.8360, 0.8360, 0.8360] +24-11-19 20:24:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:32 | D | sum error = [ 9.0260, 9.5438, 10.0892, 10.6587, 11.2586] +24-11-19 20:24:32 | D | best error = [ 0.8360, 0.8360, 0.8360, 0.8360, 0.8360] +24-11-19 20:24:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:32 | D | sum error = [ 11.8886, 12.5438, 13.2342, 13.9528, 14.7071] +24-11-19 20:24:32 | D | best error = [ 0.8360, 0.8360, 0.8360, 0.8360, 0.8360] +24-11-19 20:24:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:32 | D | sum error = [ 15.4954, 16.3208, 17.1821, 18.0824, 19.0207] +24-11-19 20:24:32 | D | best error = [ 0.8360, 0.8360, 0.8360, 0.8360, 0.8360] +24-11-19 20:24:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:32 | D | sum error = [ 20.0014, 21.0224, 22.0867, 23.1993, 24.3573] +24-11-19 20:24:32 | D | best error = [ 0.8360, 0.8360, 0.8360, 0.8360, 0.8360] +24-11-19 20:24:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:32 | D | sum error = [ 25.5622, 26.8144, 28.1171, 29.4669, 30.8689] +24-11-19 20:24:32 | D | best error = [ 0.8360, 0.8360, 0.8360, 0.8360, 0.8360] +24-11-19 20:24:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:32 | D | sum error = [ 32.3252, 33.8365, 35.4040, 37.0280, 38.7127] +24-11-19 20:24:32 | D | best error = [ 0.8360, 0.8360, 0.8360, 0.8360, 0.8360] +24-11-19 20:24:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:32 | D | sum error = [ 40.4577, 42.2639, 44.1318, 46.0642, 48.0603] +24-11-19 20:24:32 | D | best error = [ 0.8360, 0.8360, 0.8360, 0.8360, 0.8360] +24-11-19 20:24:32 | D | + error = [0.8360] +24-11-19 20:24:32 | D | - Calibrating model.layers.9.mlp.up_proj.weight +24-11-19 20:24:32 | D | + w: sint8 +24-11-19 20:24:32 | D | + x: None +24-11-19 20:24:32 | D | + y: None +24-11-19 20:24:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:32 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:24:33 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:24:33 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:24:33 | D | - range ratio = [ 1.0000] +24-11-19 20:24:33 | D | sum error = [ 5.5465] +24-11-19 20:24:33 | D | best error = [ 5.5465] +24-11-19 20:24:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:34 | D | sum error = [ 5.4913, 5.4790, 5.5001, 5.5604, 5.6675] +24-11-19 20:24:34 | D | best error = [ 5.1786, 5.0372, 4.9621, 4.9212, 4.9000] +24-11-19 20:24:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:34 | D | sum error = [ 5.8178, 5.9875, 6.2359, 6.5251, 6.8829] +24-11-19 20:24:34 | D | best error = [ 4.8912, 4.8866, 4.8851, 4.8847, 4.8846] +24-11-19 20:24:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:34 | D | sum error = [ 7.2775, 7.7255, 8.2078, 8.7731, 9.3779] +24-11-19 20:24:34 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:34 | D | sum error = [ 10.0321, 10.7637, 11.5313, 12.3481, 13.2424] +24-11-19 20:24:34 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:34 | D | sum error = [ 14.2061, 15.2147, 16.2720, 17.4196, 18.6322] +24-11-19 20:24:34 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:34 | D | sum error = [ 19.9300, 21.2892, 22.7330, 24.2651, 25.8743] +24-11-19 20:24:34 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:34 | D | sum error = [ 27.5725, 29.3725, 31.2683, 33.2747, 35.3925] +24-11-19 20:24:34 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:34 | D | sum error = [ 37.6115, 39.9464, 42.4062, 45.0011, 47.7314] +24-11-19 20:24:34 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:34 | D | sum error = [ 50.5833, 53.5900, 56.7469, 60.0730, 63.5519] +24-11-19 20:24:34 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:34 | D | sum error = [ 67.2061, 71.0293, 75.0370, 79.2565, 83.6597] +24-11-19 20:24:34 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:34 | D | sum error = [ 88.2529, 93.0749, 98.1198, 103.3932, 108.8806] +24-11-19 20:24:34 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:34 | D | sum error = [ 114.6121, 120.5861, 126.8184, 133.3101, 140.0799] +24-11-19 20:24:34 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:34 | D | sum error = [ 147.1237, 154.4504, 162.0536, 169.9637, 178.1728] +24-11-19 20:24:34 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:34 | D | sum error = [ 186.6865, 195.5178, 204.6842, 214.1816, 224.0065] +24-11-19 20:24:34 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:34 | D | sum error = [ 234.1749, 244.6958, 255.5682, 266.8043, 278.3886] +24-11-19 20:24:34 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:34 | D | sum error = [ 290.3607, 302.6937, 315.3996, 328.4786, 341.9423] +24-11-19 20:24:34 | D | best error = [ 4.8846, 4.8846, 4.8846, 4.8846, 4.8846] +24-11-19 20:24:34 | D | + error = [4.8846] +24-11-19 20:24:34 | D | - Calibrating model.layers.9.mlp.gate_proj.weight +24-11-19 20:24:34 | D | + w: sint8 +24-11-19 20:24:34 | D | + x: None +24-11-19 20:24:34 | D | + y: None +24-11-19 20:24:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:34 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:24:34 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:24:34 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:24:34 | D | - range ratio = [ 1.0000] +24-11-19 20:24:34 | D | sum error = [ 5.9938] +24-11-19 20:24:34 | D | best error = [ 5.9938] +24-11-19 20:24:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:35 | D | sum error = [ 5.9602, 5.9394, 5.9732, 6.0396, 6.1471] +24-11-19 20:24:35 | D | best error = [ 5.6098, 5.4622, 5.3851, 5.3408, 5.3185] +24-11-19 20:24:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:35 | D | sum error = [ 6.3048, 6.5091, 6.7852, 7.1299, 7.5130] +24-11-19 20:24:35 | D | best error = [ 5.3081, 5.3037, 5.3020, 5.3017, 5.3016] +24-11-19 20:24:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:35 | D | sum error = [ 7.9474, 8.4342, 8.9930, 9.6363, 10.3031] +24-11-19 20:24:35 | D | best error = [ 5.3016, 5.3016, 5.3016, 5.3016, 5.3016] +24-11-19 20:24:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:35 | D | sum error = [ 11.0487, 11.8557, 12.7106, 13.6571, 14.6418] +24-11-19 20:24:35 | D | best error = [ 5.3016, 5.3016, 5.3016, 5.3016, 5.3016] +24-11-19 20:24:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:35 | D | sum error = [ 15.7261, 16.8591, 18.0786, 19.3743, 20.7548] +24-11-19 20:24:35 | D | best error = [ 5.3016, 5.3016, 5.3016, 5.3016, 5.3016] +24-11-19 20:24:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:35 | D | sum error = [ 22.2079, 23.7595, 25.4189, 27.1550, 29.0131] +24-11-19 20:24:35 | D | best error = [ 5.3016, 5.3016, 5.3016, 5.3016, 5.3016] +24-11-19 20:24:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:35 | D | sum error = [ 30.9590, 33.0418, 35.2524, 37.5897, 40.0654] +24-11-19 20:24:35 | D | best error = [ 5.3016, 5.3016, 5.3016, 5.3016, 5.3016] +24-11-19 20:24:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:35 | D | sum error = [ 42.6790, 45.4518, 48.3814, 51.4690, 54.7469] +24-11-19 20:24:35 | D | best error = [ 5.3016, 5.3016, 5.3016, 5.3016, 5.3016] +24-11-19 20:24:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:35 | D | sum error = [ 58.2121, 61.8762, 65.7368, 69.8109, 74.1452] +24-11-19 20:24:35 | D | best error = [ 5.3016, 5.3016, 5.3016, 5.3016, 5.3016] +24-11-19 20:24:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:35 | D | sum error = [ 78.6873, 83.4762, 88.5460, 93.8822, 99.5047] +24-11-19 20:24:35 | D | best error = [ 5.3016, 5.3016, 5.3016, 5.3016, 5.3016] +24-11-19 20:24:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:35 | D | sum error = [ 105.4549, 111.7055, 118.2824, 125.2031, 132.5069] +24-11-19 20:24:35 | D | best error = [ 5.3016, 5.3016, 5.3016, 5.3016, 5.3016] +24-11-19 20:24:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:35 | D | sum error = [ 140.1702, 148.2118, 156.6669, 165.5237, 174.8016] +24-11-19 20:24:35 | D | best error = [ 5.3016, 5.3016, 5.3016, 5.3016, 5.3016] +24-11-19 20:24:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:35 | D | sum error = [ 184.5285, 194.7040, 205.3364, 216.4471, 228.0730] +24-11-19 20:24:35 | D | best error = [ 5.3016, 5.3016, 5.3016, 5.3016, 5.3016] +24-11-19 20:24:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:35 | D | sum error = [ 240.2175, 252.8922, 266.0981, 279.8394, 294.1302] +24-11-19 20:24:35 | D | best error = [ 5.3016, 5.3016, 5.3016, 5.3016, 5.3016] +24-11-19 20:24:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:35 | D | sum error = [ 308.9739, 324.4210, 340.4493, 357.0566, 374.2527] +24-11-19 20:24:35 | D | best error = [ 5.3016, 5.3016, 5.3016, 5.3016, 5.3016] +24-11-19 20:24:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:35 | D | sum error = [ 392.0600, 410.4819, 429.5042, 449.1226, 469.3264] +24-11-19 20:24:35 | D | best error = [ 5.3016, 5.3016, 5.3016, 5.3016, 5.3016] +24-11-19 20:24:35 | D | + error = [5.3016] +24-11-19 20:24:35 | D | - Calibrating model.layers.9.mlp.down_proj.weight +24-11-19 20:24:35 | D | + w: sint8 +24-11-19 20:24:35 | D | + x: None +24-11-19 20:24:35 | D | + y: None +24-11-19 20:24:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:35 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:24:35 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:24:35 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:24:35 | D | - range ratio = [ 1.0000] +24-11-19 20:24:35 | D | sum error = [ 1.3282] +24-11-19 20:24:35 | D | best error = [ 1.3282] +24-11-19 20:24:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:36 | D | sum error = [ 1.3163, 1.3049, 1.3010, 1.2970, 1.2975] +24-11-19 20:24:36 | D | best error = [ 1.2830, 1.2590, 1.2436, 1.2311, 1.2224] +24-11-19 20:24:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:36 | D | sum error = [ 1.3007, 1.3130, 1.3288, 1.3527, 1.3819] +24-11-19 20:24:36 | D | best error = [ 1.2158, 1.2114, 1.2085, 1.2063, 1.2049] +24-11-19 20:24:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:36 | D | sum error = [ 1.4182, 1.4627, 1.5168, 1.5791, 1.6508] +24-11-19 20:24:36 | D | best error = [ 1.2041, 1.2036, 1.2033, 1.2031, 1.2029] +24-11-19 20:24:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:36 | D | sum error = [ 1.7325, 1.8254, 1.9297, 2.0461, 2.1717] +24-11-19 20:24:36 | D | best error = [ 1.2029, 1.2029, 1.2028, 1.2028, 1.2028] +24-11-19 20:24:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:36 | D | sum error = [ 2.3107, 2.4589, 2.6224, 2.7966, 2.9873] +24-11-19 20:24:36 | D | best error = [ 1.2028, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 20:24:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:36 | D | sum error = [ 3.1921, 3.4114, 3.6474, 3.8980, 4.1642] +24-11-19 20:24:36 | D | best error = [ 1.2028, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 20:24:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:36 | D | sum error = [ 4.4489, 4.7551, 5.0772, 5.4227, 5.7889] +24-11-19 20:24:36 | D | best error = [ 1.2028, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 20:24:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:36 | D | sum error = [ 6.1748, 6.5875, 7.0237, 7.4836, 7.9703] +24-11-19 20:24:36 | D | best error = [ 1.2028, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 20:24:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:36 | D | sum error = [ 8.4897, 9.0353, 9.6111, 10.2199, 10.8628] +24-11-19 20:24:36 | D | best error = [ 1.2028, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 20:24:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:36 | D | sum error = [ 11.5396, 12.2543, 13.0070, 13.7981, 14.6318] +24-11-19 20:24:36 | D | best error = [ 1.2028, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 20:24:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:36 | D | sum error = [ 15.5064, 16.4278, 17.3932, 18.4104, 19.4750] +24-11-19 20:24:36 | D | best error = [ 1.2028, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 20:24:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:36 | D | sum error = [ 20.5932, 21.7664, 22.9944, 24.2815, 25.6301] +24-11-19 20:24:36 | D | best error = [ 1.2028, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 20:24:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:36 | D | sum error = [ 27.0401, 28.5149, 30.0539, 31.6601, 33.3368] +24-11-19 20:24:36 | D | best error = [ 1.2028, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 20:24:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:36 | D | sum error = [ 35.0837, 36.9030, 38.7982, 40.7731, 42.8191] +24-11-19 20:24:36 | D | best error = [ 1.2028, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 20:24:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:36 | D | sum error = [ 44.9494, 47.1615, 49.4569, 51.8403, 54.3104] +24-11-19 20:24:36 | D | best error = [ 1.2028, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 20:24:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:36 | D | sum error = [ 56.8678, 59.5133, 62.2505, 65.0797, 68.0044] +24-11-19 20:24:36 | D | best error = [ 1.2028, 1.2028, 1.2028, 1.2028, 1.2028] +24-11-19 20:24:36 | D | + error = [1.2028] +24-11-19 20:24:36 | D | - Quantizing model.layers.9.self_attn.q_proj.weight +24-11-19 20:24:37 | D | - Quantizing model.layers.9.self_attn.k_proj.weight +24-11-19 20:24:38 | D | - Quantizing model.layers.9.self_attn.v_proj.weight +24-11-19 20:24:39 | D | - Quantizing model.layers.9.self_attn.o_proj.weight +24-11-19 20:24:40 | D | - Quantizing model.layers.9.mlp.up_proj.weight +24-11-19 20:24:41 | D | - Quantizing model.layers.9.mlp.gate_proj.weight +24-11-19 20:24:42 | D | - Quantizing model.layers.9.mlp.down_proj.weight +24-11-19 20:24:50 | D | - Quantizing layer model.layers.10 +24-11-19 20:24:50 | D | - Calibrating model.layers.10.self_attn.q_proj.weight +24-11-19 20:24:50 | D | + w: sint8 +24-11-19 20:24:50 | D | + x: None +24-11-19 20:24:50 | D | + y: None +24-11-19 20:24:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:24:50 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:24:50 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:24:50 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:24:51 | D | - range ratio = [ 1.0000] +24-11-19 20:24:51 | D | sum error = [ 8.6256] +24-11-19 20:24:51 | D | best error = [ 8.6256] +24-11-19 20:25:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:03 | D | sum error = [ 8.5512, 8.5483, 8.6615, 8.6210, 8.8747] +24-11-19 20:25:03 | D | best error = [ 8.5512, 8.5483, 8.5483, 8.5483, 8.5483] +24-11-19 20:25:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:03 | D | sum error = [ 9.0986, 9.4020, 9.7969, 10.2453, 11.0483] +24-11-19 20:25:03 | D | best error = [ 8.5483, 8.5483, 8.5483, 8.5483, 8.5483] +24-11-19 20:25:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:03 | D | sum error = [ 11.4323, 12.6241, 13.1448, 14.2273, 15.2207] +24-11-19 20:25:03 | D | best error = [ 8.5483, 8.5483, 8.5483, 8.5483, 8.5483] +24-11-19 20:25:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:03 | D | sum error = [ 16.4941, 17.6624, 19.2010, 20.5793, 22.3484] +24-11-19 20:25:03 | D | best error = [ 8.5483, 8.5483, 8.5483, 8.5483, 8.5483] +24-11-19 20:25:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:03 | D | sum error = [ 24.2464, 26.1633, 28.2500, 30.6419, 33.2631] +24-11-19 20:25:03 | D | best error = [ 8.5483, 8.5483, 8.5483, 8.5483, 8.5483] +24-11-19 20:25:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:03 | D | sum error = [ 35.4068, 38.4394, 41.7853, 44.8606, 48.2160] +24-11-19 20:25:03 | D | best error = [ 8.5483, 8.5483, 8.5483, 8.5483, 8.5483] +24-11-19 20:25:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:03 | D | sum error = [ 52.1703, 56.0359, 60.5829, 65.3942, 70.7502] +24-11-19 20:25:03 | D | best error = [ 8.5483, 8.5483, 8.5483, 8.5483, 8.5483] +24-11-19 20:25:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:03 | D | sum error = [ 75.7899, 81.9785, 88.2431, 95.0336, 101.9279] +24-11-19 20:25:03 | D | best error = [ 8.5483, 8.5483, 8.5483, 8.5483, 8.5483] +24-11-19 20:25:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:03 | D | sum error = [ 109.8655, 118.1409, 126.8961, 136.5834, 146.6906] +24-11-19 20:25:03 | D | best error = [ 8.5483, 8.5483, 8.5483, 8.5483, 8.5483] +24-11-19 20:25:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:03 | D | sum error = [ 157.6956, 169.1694, 181.8816, 195.2941, 209.5093] +24-11-19 20:25:03 | D | best error = [ 8.5483, 8.5483, 8.5483, 8.5483, 8.5483] +24-11-19 20:25:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:03 | D | sum error = [ 224.9873, 241.4657, 258.7790, 277.4617, 297.3817] +24-11-19 20:25:03 | D | best error = [ 8.5483, 8.5483, 8.5483, 8.5483, 8.5483] +24-11-19 20:25:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:03 | D | sum error = [ 318.8392, 341.5566, 365.9670, 391.6957, 419.1246] +24-11-19 20:25:03 | D | best error = [ 8.5483, 8.5483, 8.5483, 8.5483, 8.5483] +24-11-19 20:25:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:03 | D | sum error = [ 448.5316, 479.8773, 513.4175, 548.9683, 587.0887] +24-11-19 20:25:03 | D | best error = [ 8.5483, 8.5483, 8.5483, 8.5483, 8.5483] +24-11-19 20:25:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:03 | D | sum error = [ 627.1254, 669.6201, 714.8415, 762.2703, 812.4790] +24-11-19 20:25:03 | D | best error = [ 8.5483, 8.5483, 8.5483, 8.5483, 8.5483] +24-11-19 20:25:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:03 | D | sum error = [ 864.8836, 919.9843, 978.0443, 1038.0407, 1101.1637] +24-11-19 20:25:03 | D | best error = [ 8.5483, 8.5483, 8.5483, 8.5483, 8.5483] +24-11-19 20:25:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:03 | D | sum error = [ 1165.8866, 1232.4240, 1301.1540, 1371.0383, 1441.8948] +24-11-19 20:25:03 | D | best error = [ 8.5483, 8.5483, 8.5483, 8.5483, 8.5483] +24-11-19 20:25:03 | D | + error = [8.5483] +24-11-19 20:25:04 | D | - Calibrating model.layers.10.self_attn.k_proj.weight +24-11-19 20:25:04 | D | + w: sint8 +24-11-19 20:25:04 | D | + x: None +24-11-19 20:25:04 | D | + y: None +24-11-19 20:25:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:25:04 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:25:04 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:25:04 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:25:04 | D | - range ratio = [ 1.0000] +24-11-19 20:25:04 | D | sum error = [ 8.6637] +24-11-19 20:25:04 | D | best error = [ 8.6637] +24-11-19 20:25:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:17 | D | sum error = [ 8.7512, 8.8514, 9.1384, 9.0557, 9.5329] +24-11-19 20:25:17 | D | best error = [ 8.6637, 8.6637, 8.6637, 8.6637, 8.6637] +24-11-19 20:25:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:17 | D | sum error = [ 9.4430, 10.0161, 10.1280, 10.6175, 11.0424] +24-11-19 20:25:17 | D | best error = [ 8.6637, 8.6637, 8.6637, 8.6637, 8.6637] +24-11-19 20:25:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:17 | D | sum error = [ 12.2254, 12.4892, 13.8007, 15.1753, 15.5326] +24-11-19 20:25:17 | D | best error = [ 8.6637, 8.6637, 8.6637, 8.6637, 8.6637] +24-11-19 20:25:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:17 | D | sum error = [ 17.0132, 18.1731, 19.5877, 21.2523, 23.0597] +24-11-19 20:25:17 | D | best error = [ 8.6637, 8.6637, 8.6637, 8.6637, 8.6637] +24-11-19 20:25:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:17 | D | sum error = [ 24.8026, 27.3730, 29.5846, 31.6482, 34.3949] +24-11-19 20:25:17 | D | best error = [ 8.6637, 8.6637, 8.6637, 8.6637, 8.6637] +24-11-19 20:25:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:17 | D | sum error = [ 37.7991, 40.0772, 44.0634, 48.1990, 52.9064] +24-11-19 20:25:17 | D | best error = [ 8.6637, 8.6637, 8.6637, 8.6637, 8.6637] +24-11-19 20:25:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:17 | D | sum error = [ 57.1990, 61.8819, 67.6876, 73.0731, 80.0011] +24-11-19 20:25:17 | D | best error = [ 8.6637, 8.6637, 8.6637, 8.6637, 8.6637] +24-11-19 20:25:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:17 | D | sum error = [ 85.9202, 94.1535, 101.7702, 110.4106, 119.1358] +24-11-19 20:25:17 | D | best error = [ 8.6637, 8.6637, 8.6637, 8.6637, 8.6637] +24-11-19 20:25:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:17 | D | sum error = [ 128.7276, 139.2087, 150.1453, 162.5568, 175.5993] +24-11-19 20:25:17 | D | best error = [ 8.6637, 8.6637, 8.6637, 8.6637, 8.6637] +24-11-19 20:25:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:17 | D | sum error = [ 188.7124, 203.7853, 218.5252, 235.4058, 252.9568] +24-11-19 20:25:17 | D | best error = [ 8.6637, 8.6637, 8.6637, 8.6637, 8.6637] +24-11-19 20:25:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:17 | D | sum error = [ 270.8442, 290.3567, 310.8301, 331.9249, 355.3573] +24-11-19 20:25:17 | D | best error = [ 8.6637, 8.6637, 8.6637, 8.6637, 8.6637] +24-11-19 20:25:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:17 | D | sum error = [ 380.3073, 406.3799, 434.7127, 463.8159, 494.3050] +24-11-19 20:25:17 | D | best error = [ 8.6637, 8.6637, 8.6637, 8.6637, 8.6637] +24-11-19 20:25:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:17 | D | sum error = [ 526.3110, 560.0915, 595.2614, 632.6758, 671.8358] +24-11-19 20:25:17 | D | best error = [ 8.6637, 8.6637, 8.6637, 8.6637, 8.6637] +24-11-19 20:25:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:17 | D | sum error = [ 712.9732, 756.4059, 802.5089, 850.6485, 901.5764] +24-11-19 20:25:17 | D | best error = [ 8.6637, 8.6637, 8.6637, 8.6637, 8.6637] +24-11-19 20:25:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:17 | D | sum error = [ 954.5436, 1009.9982, 1067.2411, 1125.8668, 1186.9163] +24-11-19 20:25:17 | D | best error = [ 8.6637, 8.6637, 8.6637, 8.6637, 8.6637] +24-11-19 20:25:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:17 | D | sum error = [ 1249.5406, 1313.8621, 1379.3851, 1445.6458, 1512.2614] +24-11-19 20:25:17 | D | best error = [ 8.6637, 8.6637, 8.6637, 8.6637, 8.6637] +24-11-19 20:25:17 | D | + error = [8.6637] +24-11-19 20:25:17 | D | - Calibrating model.layers.10.self_attn.v_proj.weight +24-11-19 20:25:17 | D | + w: sint8 +24-11-19 20:25:17 | D | + x: None +24-11-19 20:25:17 | D | + y: None +24-11-19 20:25:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:17 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:25:17 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:25:17 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:25:17 | D | - range ratio = [ 1.0000] +24-11-19 20:25:17 | D | sum error = [ 4.0795] +24-11-19 20:25:17 | D | best error = [ 4.0795] +24-11-19 20:25:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:18 | D | sum error = [ 4.0371, 4.0422, 4.0606, 4.0984, 4.1819] +24-11-19 20:25:18 | D | best error = [ 3.8202, 3.7195, 3.6694, 3.6407, 3.6237] +24-11-19 20:25:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:18 | D | sum error = [ 4.2805, 4.4296, 4.6169, 4.8386, 5.0936] +24-11-19 20:25:18 | D | best error = [ 3.6166, 3.6141, 3.6130, 3.6126, 3.6126] +24-11-19 20:25:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:18 | D | sum error = [ 5.4029, 5.7122, 6.0765, 6.4940, 6.9610] +24-11-19 20:25:18 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:18 | D | sum error = [ 7.4511, 7.9758, 8.5480, 9.1515, 9.8169] +24-11-19 20:25:18 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:18 | D | sum error = [ 10.5212, 11.2586, 12.0706, 12.9258, 13.8194] +24-11-19 20:25:18 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:18 | D | sum error = [ 14.7842, 15.8084, 16.8649, 17.9983, 19.2122] +24-11-19 20:25:18 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:18 | D | sum error = [ 20.4721, 21.8125, 23.2412, 24.7245, 26.3020] +24-11-19 20:25:18 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:18 | D | sum error = [ 27.9737, 29.7231, 31.5769, 33.5135, 35.5685] +24-11-19 20:25:18 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:18 | D | sum error = [ 37.7104, 39.9983, 42.3707, 44.8752, 47.5147] +24-11-19 20:25:18 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:18 | D | sum error = [ 50.2616, 53.1818, 56.2491, 59.4634, 62.8287] +24-11-19 20:25:18 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:18 | D | sum error = [ 66.3583, 70.0647, 73.9296, 78.0041, 82.2521] +24-11-19 20:25:18 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:18 | D | sum error = [ 86.7102, 91.3616, 96.2286, 101.3121, 106.6227] +24-11-19 20:25:18 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:18 | D | sum error = [ 112.1490, 117.9149, 123.9169, 130.1681, 136.6869] +24-11-19 20:25:18 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:18 | D | sum error = [ 143.4653, 150.5252, 157.8563, 165.4760, 173.3675] +24-11-19 20:25:18 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:18 | D | sum error = [ 181.5601, 190.0384, 198.8041, 207.8722, 217.2414] +24-11-19 20:25:18 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:18 | D | sum error = [ 226.9199, 236.9117, 247.2256, 257.8472, 268.8002] +24-11-19 20:25:18 | D | best error = [ 3.6126, 3.6126, 3.6126, 3.6126, 3.6126] +24-11-19 20:25:18 | D | + error = [3.6126] +24-11-19 20:25:18 | D | - Calibrating model.layers.10.self_attn.o_proj.weight +24-11-19 20:25:18 | D | + w: sint8 +24-11-19 20:25:18 | D | + x: None +24-11-19 20:25:18 | D | + y: None +24-11-19 20:25:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:18 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:25:18 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:25:18 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:25:18 | D | - range ratio = [ 1.0000] +24-11-19 20:25:18 | D | sum error = [ 1.1246] +24-11-19 20:25:18 | D | best error = [ 1.1246] +24-11-19 20:25:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:18 | D | sum error = [ 1.1141, 1.1089, 1.1144, 1.1146, 1.1314] +24-11-19 20:25:18 | D | best error = [ 1.0518, 1.0179, 0.9993, 0.9857, 0.9770] +24-11-19 20:25:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:18 | D | sum error = [ 1.1521, 1.1798, 1.2108, 1.2516, 1.3075] +24-11-19 20:25:18 | D | best error = [ 0.9712, 0.9678, 0.9650, 0.9631, 0.9620] +24-11-19 20:25:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:18 | D | sum error = [ 1.3718, 1.4366, 1.5177, 1.6076, 1.7034] +24-11-19 20:25:18 | D | best error = [ 0.9616, 0.9612, 0.9609, 0.9606, 0.9605] +24-11-19 20:25:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:18 | D | sum error = [ 1.8041, 1.9297, 2.0552, 2.1886, 2.3383] +24-11-19 20:25:18 | D | best error = [ 0.9605, 0.9604, 0.9604, 0.9604, 0.9604] +24-11-19 20:25:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:18 | D | sum error = [ 2.4896, 2.6553, 2.8326, 3.0263, 3.2233] +24-11-19 20:25:18 | D | best error = [ 0.9604, 0.9604, 0.9604, 0.9604, 0.9604] +24-11-19 20:25:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:18 | D | sum error = [ 3.4350, 3.6587, 3.9054, 4.1560, 4.4220] +24-11-19 20:25:18 | D | best error = [ 0.9604, 0.9604, 0.9604, 0.9604, 0.9604] +24-11-19 20:25:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:18 | D | sum error = [ 4.7121, 5.0111, 5.3251, 5.6590, 6.0094] +24-11-19 20:25:18 | D | best error = [ 0.9604, 0.9604, 0.9604, 0.9604, 0.9604] +24-11-19 20:25:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:18 | D | sum error = [ 6.3787, 6.7703, 7.1807, 7.6137, 8.0723] +24-11-19 20:25:18 | D | best error = [ 0.9604, 0.9604, 0.9604, 0.9604, 0.9604] +24-11-19 20:25:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:18 | D | sum error = [ 8.5481, 9.0539, 9.5828, 10.1371, 10.7219] +24-11-19 20:25:18 | D | best error = [ 0.9604, 0.9604, 0.9604, 0.9604, 0.9604] +24-11-19 20:25:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:18 | D | sum error = [ 11.3347, 11.9763, 12.6468, 13.3520, 14.0860] +24-11-19 20:25:18 | D | best error = [ 0.9604, 0.9604, 0.9604, 0.9604, 0.9604] +24-11-19 20:25:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:18 | D | sum error = [ 14.8630, 15.6652, 16.5118, 17.3947, 18.3164] +24-11-19 20:25:18 | D | best error = [ 0.9604, 0.9604, 0.9604, 0.9604, 0.9604] +24-11-19 20:25:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:18 | D | sum error = [ 19.2777, 20.2807, 21.3285, 22.4152, 23.5491] +24-11-19 20:25:18 | D | best error = [ 0.9604, 0.9604, 0.9604, 0.9604, 0.9604] +24-11-19 20:25:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:18 | D | sum error = [ 24.7294, 25.9579, 27.2356, 28.5666, 29.9489] +24-11-19 20:25:18 | D | best error = [ 0.9604, 0.9604, 0.9604, 0.9604, 0.9604] +24-11-19 20:25:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:18 | D | sum error = [ 31.3867, 32.8765, 34.4233, 36.0263, 37.6889] +24-11-19 20:25:18 | D | best error = [ 0.9604, 0.9604, 0.9604, 0.9604, 0.9604] +24-11-19 20:25:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:18 | D | sum error = [ 39.4124, 41.2009, 43.0526, 44.9666, 46.9468] +24-11-19 20:25:18 | D | best error = [ 0.9604, 0.9604, 0.9604, 0.9604, 0.9604] +24-11-19 20:25:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:18 | D | sum error = [ 48.9929, 51.1073, 53.2910, 55.5430, 57.8653] +24-11-19 20:25:18 | D | best error = [ 0.9604, 0.9604, 0.9604, 0.9604, 0.9604] +24-11-19 20:25:18 | D | + error = [0.9604] +24-11-19 20:25:18 | D | - Calibrating model.layers.10.mlp.up_proj.weight +24-11-19 20:25:18 | D | + w: sint8 +24-11-19 20:25:18 | D | + x: None +24-11-19 20:25:18 | D | + y: None +24-11-19 20:25:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:18 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:25:19 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:25:19 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:25:19 | D | - range ratio = [ 1.0000] +24-11-19 20:25:19 | D | sum error = [ 5.6644] +24-11-19 20:25:19 | D | best error = [ 5.6644] +24-11-19 20:25:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:20 | D | sum error = [ 5.6305, 5.6145, 5.6357, 5.7088, 5.8115] +24-11-19 20:25:20 | D | best error = [ 5.2986, 5.1559, 5.0792, 5.0369, 5.0153] +24-11-19 20:25:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:20 | D | sum error = [ 5.9448, 6.1653, 6.4029, 6.7123, 7.0652] +24-11-19 20:25:20 | D | best error = [ 5.0036, 4.9997, 4.9977, 4.9973, 4.9972] +24-11-19 20:25:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:20 | D | sum error = [ 7.4810, 7.9485, 8.4604, 9.0366, 9.6692] +24-11-19 20:25:20 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:20 | D | sum error = [ 10.3584, 11.0747, 11.8604, 12.7321, 13.6499] +24-11-19 20:25:20 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:20 | D | sum error = [ 14.6346, 15.6671, 16.7957, 17.9774, 19.2280] +24-11-19 20:25:20 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:20 | D | sum error = [ 20.5552, 21.9676, 23.4654, 25.0363, 26.6830] +24-11-19 20:25:20 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:20 | D | sum error = [ 28.4555, 30.3106, 32.2789, 34.3327, 36.5009] +24-11-19 20:25:20 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:20 | D | sum error = [ 38.8008, 41.1944, 43.7339, 46.3921, 49.2032] +24-11-19 20:25:20 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:20 | D | sum error = [ 52.1550, 55.2609, 58.5152, 61.9244, 65.5168] +24-11-19 20:25:20 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:20 | D | sum error = [ 69.2786, 73.1982, 77.3336, 81.6568, 86.1862] +24-11-19 20:25:20 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:20 | D | sum error = [ 90.9373, 95.8927, 101.0818, 106.5200, 112.1896] +24-11-19 20:25:20 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:20 | D | sum error = [ 118.1255, 124.3152, 130.7742, 137.5101, 144.5381] +24-11-19 20:25:20 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:20 | D | sum error = [ 151.8549, 159.4715, 167.3976, 175.6412, 184.2258] +24-11-19 20:25:20 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:20 | D | sum error = [ 193.1326, 202.3802, 211.9747, 221.9346, 232.2355] +24-11-19 20:25:20 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:20 | D | sum error = [ 242.9107, 253.9677, 265.3990, 277.2040, 289.3945] +24-11-19 20:25:20 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:20 | D | sum error = [ 301.9872, 314.9783, 328.3698, 342.1513, 356.3379] +24-11-19 20:25:20 | D | best error = [ 4.9972, 4.9972, 4.9972, 4.9972, 4.9972] +24-11-19 20:25:20 | D | + error = [4.9972] +24-11-19 20:25:20 | D | - Calibrating model.layers.10.mlp.gate_proj.weight +24-11-19 20:25:20 | D | + w: sint8 +24-11-19 20:25:20 | D | + x: None +24-11-19 20:25:20 | D | + y: None +24-11-19 20:25:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:20 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:25:20 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:25:20 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:25:20 | D | - range ratio = [ 1.0000] +24-11-19 20:25:20 | D | sum error = [ 6.0749] +24-11-19 20:25:20 | D | best error = [ 6.0749] +24-11-19 20:25:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:21 | D | sum error = [ 6.0327, 6.0196, 6.0440, 6.1076, 6.2269] +24-11-19 20:25:21 | D | best error = [ 5.6860, 5.5346, 5.4514, 5.4034, 5.3795] +24-11-19 20:25:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:21 | D | sum error = [ 6.3917, 6.6093, 6.8935, 7.2040, 7.5787] +24-11-19 20:25:21 | D | best error = [ 5.3677, 5.3630, 5.3615, 5.3611, 5.3607] +24-11-19 20:25:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:21 | D | sum error = [ 8.0233, 8.5241, 9.0943, 9.7046, 10.3942] +24-11-19 20:25:21 | D | best error = [ 5.3607, 5.3607, 5.3607, 5.3607, 5.3607] +24-11-19 20:25:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:21 | D | sum error = [ 11.1267, 11.9412, 12.7866, 13.7247, 14.7150] +24-11-19 20:25:21 | D | best error = [ 5.3607, 5.3607, 5.3607, 5.3607, 5.3607] +24-11-19 20:25:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:21 | D | sum error = [ 15.7929, 16.9458, 18.1485, 19.4479, 20.8301] +24-11-19 20:25:21 | D | best error = [ 5.3607, 5.3607, 5.3607, 5.3607, 5.3607] +24-11-19 20:25:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:21 | D | sum error = [ 22.2943, 23.8642, 25.5169, 27.2894, 29.1506] +24-11-19 20:25:21 | D | best error = [ 5.3607, 5.3607, 5.3607, 5.3607, 5.3607] +24-11-19 20:25:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:21 | D | sum error = [ 31.1375, 33.2464, 35.4670, 37.8571, 40.3333] +24-11-19 20:25:21 | D | best error = [ 5.3607, 5.3607, 5.3607, 5.3607, 5.3607] +24-11-19 20:25:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:21 | D | sum error = [ 42.9914, 45.7936, 48.7834, 51.9251, 55.2576] +24-11-19 20:25:21 | D | best error = [ 5.3607, 5.3607, 5.3607, 5.3607, 5.3607] +24-11-19 20:25:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:21 | D | sum error = [ 58.8077, 62.5206, 66.4698, 70.6327, 75.0334] +24-11-19 20:25:21 | D | best error = [ 5.3607, 5.3607, 5.3607, 5.3607, 5.3607] +24-11-19 20:25:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:21 | D | sum error = [ 79.7067, 84.6110, 89.7856, 95.2741, 101.0388] +24-11-19 20:25:21 | D | best error = [ 5.3607, 5.3607, 5.3607, 5.3607, 5.3607] +24-11-19 20:25:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:21 | D | sum error = [ 107.1334, 113.5417, 120.3202, 127.4549, 134.9570] +24-11-19 20:25:21 | D | best error = [ 5.3607, 5.3607, 5.3607, 5.3607, 5.3607] +24-11-19 20:25:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:21 | D | sum error = [ 142.8318, 151.1359, 159.8307, 168.9887, 178.5816] +24-11-19 20:25:21 | D | best error = [ 5.3607, 5.3607, 5.3607, 5.3607, 5.3607] +24-11-19 20:25:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:21 | D | sum error = [ 188.6249, 199.1671, 210.1919, 221.7274, 233.8107] +24-11-19 20:25:21 | D | best error = [ 5.3607, 5.3607, 5.3607, 5.3607, 5.3607] +24-11-19 20:25:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:21 | D | sum error = [ 246.3989, 259.5185, 273.2231, 287.4930, 302.3569] +24-11-19 20:25:21 | D | best error = [ 5.3607, 5.3607, 5.3607, 5.3607, 5.3607] +24-11-19 20:25:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:21 | D | sum error = [ 317.8241, 333.8892, 350.5754, 367.8874, 385.8057] +24-11-19 20:25:21 | D | best error = [ 5.3607, 5.3607, 5.3607, 5.3607, 5.3607] +24-11-19 20:25:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:21 | D | sum error = [ 404.3635, 423.5472, 443.3564, 463.8120, 484.8974] +24-11-19 20:25:21 | D | best error = [ 5.3607, 5.3607, 5.3607, 5.3607, 5.3607] +24-11-19 20:25:21 | D | + error = [5.3607] +24-11-19 20:25:21 | D | - Calibrating model.layers.10.mlp.down_proj.weight +24-11-19 20:25:21 | D | + w: sint8 +24-11-19 20:25:21 | D | + x: None +24-11-19 20:25:21 | D | + y: None +24-11-19 20:25:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:21 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:25:21 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:25:21 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:25:21 | D | - range ratio = [ 1.0000] +24-11-19 20:25:21 | D | sum error = [ 1.4170] +24-11-19 20:25:21 | D | best error = [ 1.4170] +24-11-19 20:25:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:22 | D | sum error = [ 1.4053, 1.3954, 1.3866, 1.3824, 1.3823] +24-11-19 20:25:22 | D | best error = [ 1.3650, 1.3389, 1.3207, 1.3074, 1.2980] +24-11-19 20:25:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:22 | D | sum error = [ 1.3870, 1.3981, 1.4141, 1.4368, 1.4713] +24-11-19 20:25:22 | D | best error = [ 1.2902, 1.2847, 1.2811, 1.2787, 1.2770] +24-11-19 20:25:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:22 | D | sum error = [ 1.5089, 1.5593, 1.6129, 1.6792, 1.7576] +24-11-19 20:25:22 | D | best error = [ 1.2759, 1.2753, 1.2750, 1.2748, 1.2746] +24-11-19 20:25:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:22 | D | sum error = [ 1.8422, 1.9446, 2.0513, 2.1733, 2.3083] +24-11-19 20:25:22 | D | best error = [ 1.2745, 1.2745, 1.2745, 1.2745, 1.2745] +24-11-19 20:25:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:22 | D | sum error = [ 2.4557, 2.6141, 2.7895, 2.9765, 3.1785] +24-11-19 20:25:22 | D | best error = [ 1.2745, 1.2745, 1.2744, 1.2744, 1.2744] +24-11-19 20:25:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:22 | D | sum error = [ 3.3927, 3.6280, 3.8771, 4.1460, 4.4298] +24-11-19 20:25:22 | D | best error = [ 1.2744, 1.2744, 1.2744, 1.2744, 1.2744] +24-11-19 20:25:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:22 | D | sum error = [ 4.7339, 5.0580, 5.4023, 5.7709, 6.1606] +24-11-19 20:25:22 | D | best error = [ 1.2744, 1.2744, 1.2744, 1.2744, 1.2744] +24-11-19 20:25:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:22 | D | sum error = [ 6.5750, 7.0123, 7.4821, 7.9734, 8.4937] +24-11-19 20:25:22 | D | best error = [ 1.2744, 1.2744, 1.2744, 1.2744, 1.2744] +24-11-19 20:25:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:22 | D | sum error = [ 9.0452, 9.6272, 10.2455, 10.8964, 11.5824] +24-11-19 20:25:22 | D | best error = [ 1.2744, 1.2744, 1.2744, 1.2744, 1.2744] +24-11-19 20:25:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:22 | D | sum error = [ 12.3049, 13.0648, 13.8692, 14.7136, 15.6038] +24-11-19 20:25:22 | D | best error = [ 1.2744, 1.2744, 1.2744, 1.2744, 1.2744] +24-11-19 20:25:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:22 | D | sum error = [ 16.5352, 17.5186, 18.5459, 19.6279, 20.7674] +24-11-19 20:25:22 | D | best error = [ 1.2744, 1.2744, 1.2744, 1.2744, 1.2744] +24-11-19 20:25:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:22 | D | sum error = [ 21.9597, 23.2096, 24.5207, 25.8910, 27.3259] +24-11-19 20:25:22 | D | best error = [ 1.2744, 1.2744, 1.2744, 1.2744, 1.2744] +24-11-19 20:25:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:22 | D | sum error = [ 28.8291, 30.3981, 32.0391, 33.7521, 35.5375] +24-11-19 20:25:22 | D | best error = [ 1.2744, 1.2744, 1.2744, 1.2744, 1.2744] +24-11-19 20:25:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:22 | D | sum error = [ 37.4039, 39.3453, 41.3676, 43.4772, 45.6632] +24-11-19 20:25:22 | D | best error = [ 1.2744, 1.2744, 1.2744, 1.2744, 1.2744] +24-11-19 20:25:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:22 | D | sum error = [ 47.9377, 50.3031, 52.7564, 55.3009, 57.9392] +24-11-19 20:25:22 | D | best error = [ 1.2744, 1.2744, 1.2744, 1.2744, 1.2744] +24-11-19 20:25:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:22 | D | sum error = [ 60.6730, 63.5023, 66.4314, 69.4584, 72.5854] +24-11-19 20:25:22 | D | best error = [ 1.2744, 1.2744, 1.2744, 1.2744, 1.2744] +24-11-19 20:25:22 | D | + error = [1.2744] +24-11-19 20:25:22 | D | - Quantizing model.layers.10.self_attn.q_proj.weight +24-11-19 20:25:23 | D | - Quantizing model.layers.10.self_attn.k_proj.weight +24-11-19 20:25:24 | D | - Quantizing model.layers.10.self_attn.v_proj.weight +24-11-19 20:25:25 | D | - Quantizing model.layers.10.self_attn.o_proj.weight +24-11-19 20:25:26 | D | - Quantizing model.layers.10.mlp.up_proj.weight +24-11-19 20:25:26 | D | - Quantizing model.layers.10.mlp.gate_proj.weight +24-11-19 20:25:27 | D | - Quantizing model.layers.10.mlp.down_proj.weight +24-11-19 20:25:35 | D | - Quantizing layer model.layers.11 +24-11-19 20:25:35 | D | - Calibrating model.layers.11.self_attn.q_proj.weight +24-11-19 20:25:35 | D | + w: sint8 +24-11-19 20:25:35 | D | + x: None +24-11-19 20:25:35 | D | + y: None +24-11-19 20:25:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:25:35 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:25:35 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:25:36 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:25:36 | D | - range ratio = [ 1.0000] +24-11-19 20:25:36 | D | sum error = [ 9.6307] +24-11-19 20:25:36 | D | best error = [ 9.6307] +24-11-19 20:25:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:48 | D | sum error = [ 9.5759, 9.5980, 9.4677, 9.8242, 9.7202] +24-11-19 20:25:48 | D | best error = [ 9.5759, 9.5759, 9.4677, 9.4677, 9.4677] +24-11-19 20:25:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:48 | D | sum error = [ 10.0713, 10.6802, 10.8724, 11.6673, 12.2803] +24-11-19 20:25:48 | D | best error = [ 9.4677, 9.4677, 9.4677, 9.4677, 9.4677] +24-11-19 20:25:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:48 | D | sum error = [ 12.9559, 13.8099, 14.8305, 15.7703, 17.0769] +24-11-19 20:25:48 | D | best error = [ 9.4677, 9.4677, 9.4677, 9.4677, 9.4677] +24-11-19 20:25:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:48 | D | sum error = [ 18.5316, 20.1722, 21.4971, 23.3016, 25.6549] +24-11-19 20:25:48 | D | best error = [ 9.4677, 9.4677, 9.4677, 9.4677, 9.4677] +24-11-19 20:25:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:48 | D | sum error = [ 27.7544, 29.9302, 32.2291, 35.1657, 37.6713] +24-11-19 20:25:48 | D | best error = [ 9.4677, 9.4677, 9.4677, 9.4677, 9.4677] +24-11-19 20:25:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:48 | D | sum error = [ 40.5879, 44.0380, 47.4597, 51.8367, 56.0212] +24-11-19 20:25:48 | D | best error = [ 9.4677, 9.4677, 9.4677, 9.4677, 9.4677] +24-11-19 20:25:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:48 | D | sum error = [ 60.2470, 65.2932, 70.0478, 75.7511, 81.5762] +24-11-19 20:25:48 | D | best error = [ 9.4677, 9.4677, 9.4677, 9.4677, 9.4677] +24-11-19 20:25:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:48 | D | sum error = [ 87.6100, 94.8839, 101.9646, 109.7916, 117.9435] +24-11-19 20:25:48 | D | best error = [ 9.4677, 9.4677, 9.4677, 9.4677, 9.4677] +24-11-19 20:25:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:48 | D | sum error = [ 127.0127, 136.5590, 146.6843, 157.6161, 168.6560] +24-11-19 20:25:48 | D | best error = [ 9.4677, 9.4677, 9.4677, 9.4677, 9.4677] +24-11-19 20:25:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:48 | D | sum error = [ 181.0638, 194.3291, 208.3657, 223.7030, 239.7366] +24-11-19 20:25:48 | D | best error = [ 9.4677, 9.4677, 9.4677, 9.4677, 9.4677] +24-11-19 20:25:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:48 | D | sum error = [ 257.1969, 276.0187, 296.0569, 317.9401, 341.1658] +24-11-19 20:25:48 | D | best error = [ 9.4677, 9.4677, 9.4677, 9.4677, 9.4677] +24-11-19 20:25:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:48 | D | sum error = [ 365.8221, 392.8569, 421.3883, 452.1719, 485.0397] +24-11-19 20:25:48 | D | best error = [ 9.4677, 9.4677, 9.4677, 9.4677, 9.4677] +24-11-19 20:25:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:48 | D | sum error = [ 520.5566, 558.2014, 598.6696, 641.2406, 686.9361] +24-11-19 20:25:48 | D | best error = [ 9.4677, 9.4677, 9.4677, 9.4677, 9.4677] +24-11-19 20:25:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:48 | D | sum error = [ 735.3126, 787.3127, 842.1820, 900.6271, 961.9030] +24-11-19 20:25:48 | D | best error = [ 9.4677, 9.4677, 9.4677, 9.4677, 9.4677] +24-11-19 20:25:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:48 | D | sum error = [ 1026.7772, 1095.2553, 1166.8622, 1241.8914, 1319.9645] +24-11-19 20:25:48 | D | best error = [ 9.4677, 9.4677, 9.4677, 9.4677, 9.4677] +24-11-19 20:25:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:48 | D | sum error = [ 1400.4404, 1483.5478, 1568.4488, 1655.0850, 1742.5009] +24-11-19 20:25:48 | D | best error = [ 9.4677, 9.4677, 9.4677, 9.4677, 9.4677] +24-11-19 20:25:48 | D | + error = [9.4677] +24-11-19 20:25:49 | D | - Calibrating model.layers.11.self_attn.k_proj.weight +24-11-19 20:25:49 | D | + w: sint8 +24-11-19 20:25:49 | D | + x: None +24-11-19 20:25:49 | D | + y: None +24-11-19 20:25:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:25:49 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:25:49 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:25:49 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:25:49 | D | - range ratio = [ 1.0000] +24-11-19 20:25:49 | D | sum error = [ 9.7722] +24-11-19 20:25:49 | D | best error = [ 9.7722] +24-11-19 20:26:02 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:02 | D | sum error = [ 10.2088, 10.0167, 9.7887, 10.1044, 11.2168] +24-11-19 20:26:02 | D | best error = [ 9.7722, 9.7722, 9.7722, 9.7722, 9.7722] +24-11-19 20:26:02 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:02 | D | sum error = [ 10.9360, 11.1890, 11.7602, 12.3875, 12.8845] +24-11-19 20:26:02 | D | best error = [ 9.7722, 9.7722, 9.7722, 9.7722, 9.7722] +24-11-19 20:26:02 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:02 | D | sum error = [ 14.0766, 14.9402, 15.5084, 17.3486, 18.1391] +24-11-19 20:26:02 | D | best error = [ 9.7722, 9.7722, 9.7722, 9.7722, 9.7722] +24-11-19 20:26:02 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:02 | D | sum error = [ 19.3544, 21.3193, 23.0897, 24.0829, 25.9028] +24-11-19 20:26:02 | D | best error = [ 9.7722, 9.7722, 9.7722, 9.7722, 9.7722] +24-11-19 20:26:02 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:02 | D | sum error = [ 28.2536, 30.2314, 32.2112, 34.9505, 37.3446] +24-11-19 20:26:02 | D | best error = [ 9.7722, 9.7722, 9.7722, 9.7722, 9.7722] +24-11-19 20:26:02 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:02 | D | sum error = [ 40.1437, 43.1671, 46.3780, 49.7127, 53.5140] +24-11-19 20:26:02 | D | best error = [ 9.7722, 9.7722, 9.7722, 9.7722, 9.7722] +24-11-19 20:26:02 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:02 | D | sum error = [ 58.1770, 62.8765, 67.1338, 72.6646, 78.6875] +24-11-19 20:26:02 | D | best error = [ 9.7722, 9.7722, 9.7722, 9.7722, 9.7722] +24-11-19 20:26:02 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:02 | D | sum error = [ 83.8050, 91.0706, 97.0678, 104.1750, 112.7729] +24-11-19 20:26:02 | D | best error = [ 9.7722, 9.7722, 9.7722, 9.7722, 9.7722] +24-11-19 20:26:02 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:02 | D | sum error = [ 121.1464, 130.0286, 139.7213, 150.3581, 161.7012] +24-11-19 20:26:02 | D | best error = [ 9.7722, 9.7722, 9.7722, 9.7722, 9.7722] +24-11-19 20:26:02 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:02 | D | sum error = [ 173.7090, 186.9867, 200.8758, 216.2480, 232.5205] +24-11-19 20:26:02 | D | best error = [ 9.7722, 9.7722, 9.7722, 9.7722, 9.7722] +24-11-19 20:26:02 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:02 | D | sum error = [ 250.6166, 270.1548, 290.5776, 313.0573, 336.2652] +24-11-19 20:26:02 | D | best error = [ 9.7722, 9.7722, 9.7722, 9.7722, 9.7722] +24-11-19 20:26:02 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:02 | D | sum error = [ 362.0020, 390.0803, 419.1683, 451.0283, 484.9923] +24-11-19 20:26:02 | D | best error = [ 9.7722, 9.7722, 9.7722, 9.7722, 9.7722] +24-11-19 20:26:02 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:02 | D | sum error = [ 520.8319, 559.2627, 600.2189, 644.1941, 690.0633] +24-11-19 20:26:02 | D | best error = [ 9.7722, 9.7722, 9.7722, 9.7722, 9.7722] +24-11-19 20:26:02 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:02 | D | sum error = [ 738.4419, 790.0557, 846.2736, 904.2565, 965.9119] +24-11-19 20:26:02 | D | best error = [ 9.7722, 9.7722, 9.7722, 9.7722, 9.7722] +24-11-19 20:26:02 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:02 | D | sum error = [ 1031.1342, 1099.2058, 1170.9236, 1246.0395, 1324.9253] +24-11-19 20:26:02 | D | best error = [ 9.7722, 9.7722, 9.7722, 9.7722, 9.7722] +24-11-19 20:26:02 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:02 | D | sum error = [ 1406.7466, 1490.1441, 1575.9854, 1663.7501, 1752.5939] +24-11-19 20:26:02 | D | best error = [ 9.7722, 9.7722, 9.7722, 9.7722, 9.7722] +24-11-19 20:26:02 | D | + error = [9.7722] +24-11-19 20:26:02 | D | - Calibrating model.layers.11.self_attn.v_proj.weight +24-11-19 20:26:02 | D | + w: sint8 +24-11-19 20:26:02 | D | + x: None +24-11-19 20:26:02 | D | + y: None +24-11-19 20:26:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:02 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:26:02 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:26:02 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:26:02 | D | - range ratio = [ 1.0000] +24-11-19 20:26:02 | D | sum error = [ 4.6933] +24-11-19 20:26:02 | D | best error = [ 4.6933] +24-11-19 20:26:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:03 | D | sum error = [ 4.6471, 4.6466, 4.6588, 4.7325, 4.7964] +24-11-19 20:26:03 | D | best error = [ 4.3732, 4.2550, 4.1906, 4.1555, 4.1375] +24-11-19 20:26:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:03 | D | sum error = [ 4.9320, 5.0873, 5.2972, 5.5362, 5.8397] +24-11-19 20:26:03 | D | best error = [ 4.1270, 4.1231, 4.1223, 4.1222, 4.1222] +24-11-19 20:26:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:03 | D | sum error = [ 6.1904, 6.5664, 7.0054, 7.4606, 7.9870] +24-11-19 20:26:03 | D | best error = [ 4.1222, 4.1222, 4.1222, 4.1222, 4.1222] +24-11-19 20:26:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:03 | D | sum error = [ 8.5366, 9.1487, 9.8068, 10.5328, 11.2821] +24-11-19 20:26:03 | D | best error = [ 4.1222, 4.1222, 4.1222, 4.1222, 4.1222] +24-11-19 20:26:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:03 | D | sum error = [ 12.0978, 12.9554, 13.8607, 14.8544, 15.8851] +24-11-19 20:26:03 | D | best error = [ 4.1222, 4.1222, 4.1222, 4.1222, 4.1222] +24-11-19 20:26:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:03 | D | sum error = [ 16.9862, 18.1512, 19.3922, 20.6797, 22.0835] +24-11-19 20:26:03 | D | best error = [ 4.1222, 4.1222, 4.1222, 4.1222, 4.1222] +24-11-19 20:26:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:03 | D | sum error = [ 23.5248, 25.0772, 26.7027, 28.4194, 30.2603] +24-11-19 20:26:03 | D | best error = [ 4.1222, 4.1222, 4.1222, 4.1222, 4.1222] +24-11-19 20:26:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:03 | D | sum error = [ 32.1853, 34.2047, 36.3248, 38.5767, 40.9299] +24-11-19 20:26:03 | D | best error = [ 4.1222, 4.1222, 4.1222, 4.1222, 4.1222] +24-11-19 20:26:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:03 | D | sum error = [ 43.4227, 46.0331, 48.7892, 51.6668, 54.6930] +24-11-19 20:26:03 | D | best error = [ 4.1222, 4.1222, 4.1222, 4.1222, 4.1222] +24-11-19 20:26:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:03 | D | sum error = [ 57.8716, 61.2040, 64.6917, 68.3258, 72.1502] +24-11-19 20:26:03 | D | best error = [ 4.1222, 4.1222, 4.1222, 4.1222, 4.1222] +24-11-19 20:26:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:03 | D | sum error = [ 76.1299, 80.3113, 84.6728, 89.2504, 94.0334] +24-11-19 20:26:03 | D | best error = [ 4.1222, 4.1222, 4.1222, 4.1222, 4.1222] +24-11-19 20:26:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:03 | D | sum error = [ 99.0328, 104.2400, 109.6753, 115.3614, 121.2795] +24-11-19 20:26:03 | D | best error = [ 4.1222, 4.1222, 4.1222, 4.1222, 4.1222] +24-11-19 20:26:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:03 | D | sum error = [ 127.4582, 133.8957, 140.6021, 147.5761, 154.8180] +24-11-19 20:26:03 | D | best error = [ 4.1222, 4.1222, 4.1222, 4.1222, 4.1222] +24-11-19 20:26:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:03 | D | sum error = [ 162.3525, 170.1899, 178.3081, 186.7315, 195.4531] +24-11-19 20:26:03 | D | best error = [ 4.1222, 4.1222, 4.1222, 4.1222, 4.1222] +24-11-19 20:26:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:03 | D | sum error = [ 204.4874, 213.8386, 223.5279, 233.5331, 243.8830] +24-11-19 20:26:03 | D | best error = [ 4.1222, 4.1222, 4.1222, 4.1222, 4.1222] +24-11-19 20:26:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:03 | D | sum error = [ 254.5660, 265.5871, 276.9451, 288.6513, 300.7073] +24-11-19 20:26:03 | D | best error = [ 4.1222, 4.1222, 4.1222, 4.1222, 4.1222] +24-11-19 20:26:03 | D | + error = [4.1222] +24-11-19 20:26:03 | D | - Calibrating model.layers.11.self_attn.o_proj.weight +24-11-19 20:26:03 | D | + w: sint8 +24-11-19 20:26:03 | D | + x: None +24-11-19 20:26:03 | D | + y: None +24-11-19 20:26:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:03 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:26:03 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:26:03 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:26:03 | D | - range ratio = [ 1.0000] +24-11-19 20:26:03 | D | sum error = [ 1.0946] +24-11-19 20:26:03 | D | best error = [ 1.0946] +24-11-19 20:26:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:03 | D | sum error = [ 1.0882, 1.0824, 1.0783, 1.0814, 1.0888] +24-11-19 20:26:03 | D | best error = [ 1.0160, 0.9784, 0.9562, 0.9401, 0.9294] +24-11-19 20:26:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:03 | D | sum error = [ 1.1041, 1.1290, 1.1529, 1.1848, 1.2217] +24-11-19 20:26:03 | D | best error = [ 0.9221, 0.9166, 0.9125, 0.9097, 0.9074] +24-11-19 20:26:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:03 | D | sum error = [ 1.2738, 1.3320, 1.3954, 1.4695, 1.5439] +24-11-19 20:26:03 | D | best error = [ 0.9057, 0.9046, 0.9037, 0.9030, 0.9025] +24-11-19 20:26:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:03 | D | sum error = [ 1.6300, 1.7294, 1.8329, 1.9525, 2.0703] +24-11-19 20:26:03 | D | best error = [ 0.9019, 0.9015, 0.9012, 0.9009, 0.9008] +24-11-19 20:26:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:03 | D | sum error = [ 2.2008, 2.3436, 2.4899, 2.6471, 2.8185] +24-11-19 20:26:03 | D | best error = [ 0.9006, 0.9005, 0.9003, 0.9003, 0.9003] +24-11-19 20:26:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:03 | D | sum error = [ 3.0060, 3.1994, 3.4030, 3.6202, 3.8505] +24-11-19 20:26:03 | D | best error = [ 0.9002, 0.9001, 0.9001, 0.9001, 0.9001] +24-11-19 20:26:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:03 | D | sum error = [ 4.0986, 4.3545, 4.6318, 4.9145, 5.2237] +24-11-19 20:26:03 | D | best error = [ 0.9001, 0.9001, 0.9001, 0.9001, 0.9001] +24-11-19 20:26:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:03 | D | sum error = [ 5.5439, 5.8818, 6.2420, 6.6172, 7.0143] +24-11-19 20:26:03 | D | best error = [ 0.9001, 0.9001, 0.9001, 0.9001, 0.9001] +24-11-19 20:26:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:03 | D | sum error = [ 7.4319, 7.8694, 8.3339, 8.8177, 9.3267] +24-11-19 20:26:03 | D | best error = [ 0.9001, 0.9001, 0.9001, 0.9001, 0.9001] +24-11-19 20:26:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:03 | D | sum error = [ 9.8608, 10.4232, 11.0111, 11.6312, 12.2725] +24-11-19 20:26:03 | D | best error = [ 0.9001, 0.9001, 0.9001, 0.9001, 0.9001] +24-11-19 20:26:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:03 | D | sum error = [ 12.9514, 13.6576, 14.4007, 15.1741, 15.9835] +24-11-19 20:26:03 | D | best error = [ 0.9001, 0.9001, 0.9001, 0.9001, 0.9001] +24-11-19 20:26:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:03 | D | sum error = [ 16.8362, 17.7217, 18.6420, 19.6052, 20.6150] +24-11-19 20:26:03 | D | best error = [ 0.9001, 0.9001, 0.9001, 0.9001, 0.9001] +24-11-19 20:26:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:03 | D | sum error = [ 21.6616, 22.7520, 23.8898, 25.0675, 26.2975] +24-11-19 20:26:03 | D | best error = [ 0.9001, 0.9001, 0.9001, 0.9001, 0.9001] +24-11-19 20:26:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:03 | D | sum error = [ 27.5742, 28.9033, 30.2777, 31.7046, 33.1888] +24-11-19 20:26:03 | D | best error = [ 0.9001, 0.9001, 0.9001, 0.9001, 0.9001] +24-11-19 20:26:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:03 | D | sum error = [ 34.7257, 36.3185, 37.9700, 39.6799, 41.4484] +24-11-19 20:26:03 | D | best error = [ 0.9001, 0.9001, 0.9001, 0.9001, 0.9001] +24-11-19 20:26:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:03 | D | sum error = [ 43.2791, 45.1734, 47.1264, 49.1439, 51.2286] +24-11-19 20:26:03 | D | best error = [ 0.9001, 0.9001, 0.9001, 0.9001, 0.9001] +24-11-19 20:26:03 | D | + error = [0.9001] +24-11-19 20:26:03 | D | - Calibrating model.layers.11.mlp.up_proj.weight +24-11-19 20:26:03 | D | + w: sint8 +24-11-19 20:26:03 | D | + x: None +24-11-19 20:26:03 | D | + y: None +24-11-19 20:26:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:03 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:26:04 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:26:04 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:26:04 | D | - range ratio = [ 1.0000] +24-11-19 20:26:04 | D | sum error = [ 5.8968] +24-11-19 20:26:04 | D | best error = [ 5.8968] +24-11-19 20:26:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:05 | D | sum error = [ 5.8648, 5.8512, 5.8744, 5.9440, 6.0464] +24-11-19 20:26:05 | D | best error = [ 5.5133, 5.3593, 5.2766, 5.2299, 5.2059] +24-11-19 20:26:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:05 | D | sum error = [ 6.2069, 6.4160, 6.6831, 6.9984, 7.3707] +24-11-19 20:26:05 | D | best error = [ 5.1934, 5.1884, 5.1865, 5.1859, 5.1858] +24-11-19 20:26:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:05 | D | sum error = [ 7.8015, 8.2826, 8.8186, 9.4265, 10.0645] +24-11-19 20:26:05 | D | best error = [ 5.1857, 5.1857, 5.1857, 5.1857, 5.1857] +24-11-19 20:26:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:05 | D | sum error = [ 10.7819, 11.5635, 12.3790, 13.2853, 14.2258] +24-11-19 20:26:05 | D | best error = [ 5.1857, 5.1857, 5.1857, 5.1857, 5.1857] +24-11-19 20:26:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:05 | D | sum error = [ 15.2434, 16.3216, 17.4914, 18.7119, 20.0209] +24-11-19 20:26:05 | D | best error = [ 5.1857, 5.1857, 5.1857, 5.1857, 5.1857] +24-11-19 20:26:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:05 | D | sum error = [ 21.4164, 22.8784, 24.4280, 26.0774, 27.8139] +24-11-19 20:26:05 | D | best error = [ 5.1857, 5.1857, 5.1857, 5.1857, 5.1857] +24-11-19 20:26:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:05 | D | sum error = [ 29.6522, 31.5865, 33.6369, 35.7828, 38.0690] +24-11-19 20:26:05 | D | best error = [ 5.1857, 5.1857, 5.1857, 5.1857, 5.1857] +24-11-19 20:26:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:05 | D | sum error = [ 40.4625, 42.9863, 45.6296, 48.4012, 51.3437] +24-11-19 20:26:05 | D | best error = [ 5.1857, 5.1857, 5.1857, 5.1857, 5.1857] +24-11-19 20:26:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:05 | D | sum error = [ 54.4175, 57.6587, 61.0560, 64.6021, 68.3445] +24-11-19 20:26:05 | D | best error = [ 5.1857, 5.1857, 5.1857, 5.1857, 5.1857] +24-11-19 20:26:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:05 | D | sum error = [ 72.2460, 76.3632, 80.6481, 85.1422, 89.8528] +24-11-19 20:26:05 | D | best error = [ 5.1857, 5.1857, 5.1857, 5.1857, 5.1857] +24-11-19 20:26:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:05 | D | sum error = [ 94.7878, 99.9325, 105.3140, 110.9490, 116.8159] +24-11-19 20:26:05 | D | best error = [ 5.1857, 5.1857, 5.1857, 5.1857, 5.1857] +24-11-19 20:26:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:05 | D | sum error = [ 122.9547, 129.3560, 136.0342, 142.9886, 150.2252] +24-11-19 20:26:05 | D | best error = [ 5.1857, 5.1857, 5.1857, 5.1857, 5.1857] +24-11-19 20:26:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:05 | D | sum error = [ 157.7762, 165.6260, 173.7798, 182.2493, 191.0478] +24-11-19 20:26:05 | D | best error = [ 5.1857, 5.1857, 5.1857, 5.1857, 5.1857] +24-11-19 20:26:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:05 | D | sum error = [ 200.1690, 209.6412, 219.4516, 229.6326, 240.1655] +24-11-19 20:26:05 | D | best error = [ 5.1857, 5.1857, 5.1857, 5.1857, 5.1857] +24-11-19 20:26:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:05 | D | sum error = [ 251.0674, 262.3529, 274.0126, 286.0677, 298.4910] +24-11-19 20:26:05 | D | best error = [ 5.1857, 5.1857, 5.1857, 5.1857, 5.1857] +24-11-19 20:26:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:05 | D | sum error = [ 311.3375, 324.5722, 338.2180, 352.2722, 366.7342] +24-11-19 20:26:05 | D | best error = [ 5.1857, 5.1857, 5.1857, 5.1857, 5.1857] +24-11-19 20:26:05 | D | + error = [5.1857] +24-11-19 20:26:05 | D | - Calibrating model.layers.11.mlp.gate_proj.weight +24-11-19 20:26:05 | D | + w: sint8 +24-11-19 20:26:05 | D | + x: None +24-11-19 20:26:05 | D | + y: None +24-11-19 20:26:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:05 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:26:05 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:26:05 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:26:05 | D | - range ratio = [ 1.0000] +24-11-19 20:26:05 | D | sum error = [ 6.2441] +24-11-19 20:26:05 | D | best error = [ 6.2441] +24-11-19 20:26:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:06 | D | sum error = [ 6.2030, 6.1876, 6.2250, 6.2789, 6.3904] +24-11-19 20:26:06 | D | best error = [ 5.8277, 5.6704, 5.5842, 5.5339, 5.5075] +24-11-19 20:26:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:06 | D | sum error = [ 6.5534, 6.7827, 7.0596, 7.4140, 7.7926] +24-11-19 20:26:06 | D | best error = [ 5.4950, 5.4899, 5.4882, 5.4878, 5.4876] +24-11-19 20:26:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:06 | D | sum error = [ 8.2536, 8.7638, 9.3459, 9.9888, 10.6777] +24-11-19 20:26:06 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 20:26:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:06 | D | sum error = [ 11.4497, 12.2914, 13.1843, 14.1227, 15.1669] +24-11-19 20:26:06 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 20:26:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:06 | D | sum error = [ 16.2643, 17.4575, 18.7192, 20.0563, 21.5031] +24-11-19 20:26:06 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 20:26:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:06 | D | sum error = [ 23.0239, 24.6570, 26.3791, 28.2335, 30.1765] +24-11-19 20:26:06 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 20:26:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:06 | D | sum error = [ 32.2370, 34.4260, 36.7506, 39.2152, 41.7980] +24-11-19 20:26:06 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 20:26:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:06 | D | sum error = [ 44.5799, 47.4941, 50.6055, 53.8459, 57.3435] +24-11-19 20:26:06 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 20:26:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:06 | D | sum error = [ 60.9845, 64.8556, 68.9530, 73.2790, 77.8271] +24-11-19 20:26:06 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 20:26:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:06 | D | sum error = [ 82.6709, 87.7616, 93.1481, 98.8127, 104.8237] +24-11-19 20:26:06 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 20:26:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:06 | D | sum error = [ 111.1557, 117.8242, 124.8689, 132.2678, 140.0305] +24-11-19 20:26:06 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 20:26:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:06 | D | sum error = [ 148.1941, 156.7923, 165.8121, 175.2705, 185.1950] +24-11-19 20:26:06 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 20:26:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:06 | D | sum error = [ 195.5803, 206.4820, 217.8674, 229.7988, 242.2675] +24-11-19 20:26:06 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 20:26:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:06 | D | sum error = [ 255.2965, 268.8668, 283.0067, 297.7344, 313.0456] +24-11-19 20:26:06 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 20:26:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:06 | D | sum error = [ 328.9851, 345.5214, 362.6826, 380.5041, 398.9328] +24-11-19 20:26:06 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 20:26:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:06 | D | sum error = [ 418.0120, 437.7279, 458.0911, 479.1119, 500.7838] +24-11-19 20:26:06 | D | best error = [ 5.4876, 5.4876, 5.4876, 5.4876, 5.4876] +24-11-19 20:26:06 | D | + error = [5.4876] +24-11-19 20:26:06 | D | - Calibrating model.layers.11.mlp.down_proj.weight +24-11-19 20:26:06 | D | + w: sint8 +24-11-19 20:26:06 | D | + x: None +24-11-19 20:26:06 | D | + y: None +24-11-19 20:26:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:06 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:26:06 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:26:06 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:26:06 | D | - range ratio = [ 1.0000] +24-11-19 20:26:06 | D | sum error = [ 1.4773] +24-11-19 20:26:06 | D | best error = [ 1.4773] +24-11-19 20:26:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:07 | D | sum error = [ 1.4650, 1.4557, 1.4490, 1.4458, 1.4461] +24-11-19 20:26:07 | D | best error = [ 1.4246, 1.3987, 1.3803, 1.3668, 1.3573] +24-11-19 20:26:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:07 | D | sum error = [ 1.4525, 1.4634, 1.4841, 1.5089, 1.5451] +24-11-19 20:26:07 | D | best error = [ 1.3499, 1.3447, 1.3411, 1.3388, 1.3374] +24-11-19 20:26:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:07 | D | sum error = [ 1.5883, 1.6345, 1.6948, 1.7676, 1.8499] +24-11-19 20:26:07 | D | best error = [ 1.3366, 1.3359, 1.3355, 1.3353, 1.3352] +24-11-19 20:26:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:07 | D | sum error = [ 1.9451, 2.0484, 2.1694, 2.2943, 2.4366] +24-11-19 20:26:07 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:07 | D | sum error = [ 2.5920, 2.7562, 2.9390, 3.1361, 3.3514] +24-11-19 20:26:07 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:07 | D | sum error = [ 3.5780, 3.8231, 4.0847, 4.3657, 4.6668] +24-11-19 20:26:07 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:07 | D | sum error = [ 4.9859, 5.3260, 5.6863, 6.0716, 6.4776] +24-11-19 20:26:07 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:07 | D | sum error = [ 6.9114, 7.3702, 7.8598, 8.3753, 8.9209] +24-11-19 20:26:07 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:07 | D | sum error = [ 9.4967, 10.1057, 10.7474, 11.4283, 12.1471] +24-11-19 20:26:07 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:07 | D | sum error = [ 12.9020, 13.6972, 14.5385, 15.4205, 16.3498] +24-11-19 20:26:07 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:07 | D | sum error = [ 17.3264, 18.3546, 19.4323, 20.5683, 21.7581] +24-11-19 20:26:07 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:07 | D | sum error = [ 23.0074, 24.3137, 25.6847, 27.1187, 28.6226] +24-11-19 20:26:07 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:07 | D | sum error = [ 30.1927, 31.8344, 33.5488, 35.3369, 37.2056] +24-11-19 20:26:07 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:07 | D | sum error = [ 39.1513, 41.1803, 43.2909, 45.4892, 47.7662] +24-11-19 20:26:07 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:07 | D | sum error = [ 50.1341, 52.5958, 55.1523, 57.8004, 60.5480] +24-11-19 20:26:07 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:07 | D | sum error = [ 63.3936, 66.3359, 69.3772, 72.5200, 75.7664] +24-11-19 20:26:07 | D | best error = [ 1.3351, 1.3351, 1.3351, 1.3351, 1.3351] +24-11-19 20:26:07 | D | + error = [1.3351] +24-11-19 20:26:07 | D | - Quantizing model.layers.11.self_attn.q_proj.weight +24-11-19 20:26:08 | D | - Quantizing model.layers.11.self_attn.k_proj.weight +24-11-19 20:26:09 | D | - Quantizing model.layers.11.self_attn.v_proj.weight +24-11-19 20:26:10 | D | - Quantizing model.layers.11.self_attn.o_proj.weight +24-11-19 20:26:10 | D | - Quantizing model.layers.11.mlp.up_proj.weight +24-11-19 20:26:11 | D | - Quantizing model.layers.11.mlp.gate_proj.weight +24-11-19 20:26:12 | D | - Quantizing model.layers.11.mlp.down_proj.weight +24-11-19 20:26:20 | D | - Quantizing layer model.layers.12 +24-11-19 20:26:20 | D | - Calibrating model.layers.12.self_attn.q_proj.weight +24-11-19 20:26:20 | D | + w: sint8 +24-11-19 20:26:20 | D | + x: None +24-11-19 20:26:20 | D | + y: None +24-11-19 20:26:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:26:20 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:26:20 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:26:20 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:26:21 | D | - range ratio = [ 1.0000] +24-11-19 20:26:21 | D | sum error = [ 10.3319] +24-11-19 20:26:21 | D | best error = [ 10.3319] +24-11-19 20:26:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:33 | D | sum error = [ 10.2096, 10.3005, 10.2823, 10.3087, 10.7213] +24-11-19 20:26:33 | D | best error = [ 10.2096, 10.2096, 10.2096, 10.2096, 10.2096] +24-11-19 20:26:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:33 | D | sum error = [ 10.9134, 11.4015, 11.8333, 12.4572, 13.3307] +24-11-19 20:26:33 | D | best error = [ 10.2096, 10.2096, 10.2096, 10.2096, 10.2096] +24-11-19 20:26:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:33 | D | sum error = [ 14.2640, 14.9033, 16.0238, 17.5741, 18.6040] +24-11-19 20:26:33 | D | best error = [ 10.2096, 10.2096, 10.2096, 10.2096, 10.2096] +24-11-19 20:26:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:33 | D | sum error = [ 20.3091, 22.2514, 23.9767, 25.9816, 27.9500] +24-11-19 20:26:33 | D | best error = [ 10.2096, 10.2096, 10.2096, 10.2096, 10.2096] +24-11-19 20:26:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:33 | D | sum error = [ 30.4012, 32.8047, 36.0624, 39.2472, 41.9984] +24-11-19 20:26:33 | D | best error = [ 10.2096, 10.2096, 10.2096, 10.2096, 10.2096] +24-11-19 20:26:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:33 | D | sum error = [ 45.2233, 48.9934, 53.2031, 57.1214, 61.3127] +24-11-19 20:26:33 | D | best error = [ 10.2096, 10.2096, 10.2096, 10.2096, 10.2096] +24-11-19 20:26:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:33 | D | sum error = [ 66.2595, 71.2995, 77.0547, 83.3200, 89.2096] +24-11-19 20:26:33 | D | best error = [ 10.2096, 10.2096, 10.2096, 10.2096, 10.2096] +24-11-19 20:26:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:33 | D | sum error = [ 96.3699, 103.2694, 110.8643, 119.2362, 127.8695] +24-11-19 20:26:33 | D | best error = [ 10.2096, 10.2096, 10.2096, 10.2096, 10.2096] +24-11-19 20:26:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:33 | D | sum error = [ 137.7908, 148.1837, 159.1815, 171.2633, 184.6596] +24-11-19 20:26:33 | D | best error = [ 10.2096, 10.2096, 10.2096, 10.2096, 10.2096] +24-11-19 20:26:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:33 | D | sum error = [ 197.9723, 213.5054, 229.2664, 246.3996, 265.1303] +24-11-19 20:26:33 | D | best error = [ 10.2096, 10.2096, 10.2096, 10.2096, 10.2096] +24-11-19 20:26:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:33 | D | sum error = [ 285.1169, 306.0366, 329.2635, 353.8719, 379.5894] +24-11-19 20:26:33 | D | best error = [ 10.2096, 10.2096, 10.2096, 10.2096, 10.2096] +24-11-19 20:26:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:33 | D | sum error = [ 407.0489, 436.6239, 467.9467, 501.6480, 537.7100] +24-11-19 20:26:33 | D | best error = [ 10.2096, 10.2096, 10.2096, 10.2096, 10.2096] +24-11-19 20:26:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:33 | D | sum error = [ 576.2943, 617.6695, 661.9841, 708.0756, 758.1195] +24-11-19 20:26:33 | D | best error = [ 10.2096, 10.2096, 10.2096, 10.2096, 10.2096] +24-11-19 20:26:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:33 | D | sum error = [ 811.1377, 866.9813, 926.5109, 990.0554, 1057.1147] +24-11-19 20:26:33 | D | best error = [ 10.2096, 10.2096, 10.2096, 10.2096, 10.2096] +24-11-19 20:26:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:33 | D | sum error = [ 1127.7637, 1202.1177, 1280.1345, 1361.5776, 1446.5280] +24-11-19 20:26:33 | D | best error = [ 10.2096, 10.2096, 10.2096, 10.2096, 10.2096] +24-11-19 20:26:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:33 | D | sum error = [ 1534.9241, 1625.9353, 1719.1883, 1813.6215, 1910.1812] +24-11-19 20:26:33 | D | best error = [ 10.2096, 10.2096, 10.2096, 10.2096, 10.2096] +24-11-19 20:26:33 | D | + error = [10.2096] +24-11-19 20:26:33 | D | - Calibrating model.layers.12.self_attn.k_proj.weight +24-11-19 20:26:33 | D | + w: sint8 +24-11-19 20:26:33 | D | + x: None +24-11-19 20:26:33 | D | + y: None +24-11-19 20:26:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:26:33 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:26:33 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:26:34 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:26:34 | D | - range ratio = [ 1.0000] +24-11-19 20:26:34 | D | sum error = [ 10.8503] +24-11-19 20:26:34 | D | best error = [ 10.8503] +24-11-19 20:26:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:47 | D | sum error = [ 10.1512, 10.6094, 10.9688, 11.0263, 10.4243] +24-11-19 20:26:47 | D | best error = [ 10.1512, 10.1512, 10.1512, 10.1512, 10.1512] +24-11-19 20:26:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:47 | D | sum error = [ 11.4154, 11.7446, 12.3259, 13.0518, 13.3238] +24-11-19 20:26:47 | D | best error = [ 10.1512, 10.1512, 10.1512, 10.1512, 10.1512] +24-11-19 20:26:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:47 | D | sum error = [ 13.7617, 14.5058, 15.9113, 16.9509, 18.0018] +24-11-19 20:26:47 | D | best error = [ 10.1512, 10.1512, 10.1512, 10.1512, 10.1512] +24-11-19 20:26:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:47 | D | sum error = [ 19.2409, 20.9093, 22.9125, 24.4511, 26.3488] +24-11-19 20:26:47 | D | best error = [ 10.1512, 10.1512, 10.1512, 10.1512, 10.1512] +24-11-19 20:26:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:47 | D | sum error = [ 27.9268, 30.4239, 33.2047, 35.2505, 38.2080] +24-11-19 20:26:47 | D | best error = [ 10.1512, 10.1512, 10.1512, 10.1512, 10.1512] +24-11-19 20:26:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:47 | D | sum error = [ 40.4187, 43.5324, 47.3204, 51.1653, 54.2953] +24-11-19 20:26:47 | D | best error = [ 10.1512, 10.1512, 10.1512, 10.1512, 10.1512] +24-11-19 20:26:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:47 | D | sum error = [ 58.5728, 62.8760, 67.6250, 72.7139, 78.3199] +24-11-19 20:26:47 | D | best error = [ 10.1512, 10.1512, 10.1512, 10.1512, 10.1512] +24-11-19 20:26:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:47 | D | sum error = [ 83.7682, 90.6421, 97.8479, 105.0313, 112.8586] +24-11-19 20:26:47 | D | best error = [ 10.1512, 10.1512, 10.1512, 10.1512, 10.1512] +24-11-19 20:26:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:47 | D | sum error = [ 121.5890, 130.8263, 141.3139, 152.3997, 163.6555] +24-11-19 20:26:47 | D | best error = [ 10.1512, 10.1512, 10.1512, 10.1512, 10.1512] +24-11-19 20:26:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:47 | D | sum error = [ 177.1535, 191.2247, 205.4597, 221.0710, 238.4046] +24-11-19 20:26:47 | D | best error = [ 10.1512, 10.1512, 10.1512, 10.1512, 10.1512] +24-11-19 20:26:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:47 | D | sum error = [ 256.3888, 275.7742, 296.5317, 319.0743, 343.1340] +24-11-19 20:26:47 | D | best error = [ 10.1512, 10.1512, 10.1512, 10.1512, 10.1512] +24-11-19 20:26:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:47 | D | sum error = [ 369.6883, 396.6256, 427.2836, 459.0196, 493.0136] +24-11-19 20:26:47 | D | best error = [ 10.1512, 10.1512, 10.1512, 10.1512, 10.1512] +24-11-19 20:26:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:47 | D | sum error = [ 529.7479, 567.3782, 609.6688, 652.6548, 699.8483] +24-11-19 20:26:47 | D | best error = [ 10.1512, 10.1512, 10.1512, 10.1512, 10.1512] +24-11-19 20:26:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:47 | D | sum error = [ 750.8141, 804.2522, 862.0317, 924.8383, 991.8958] +24-11-19 20:26:47 | D | best error = [ 10.1512, 10.1512, 10.1512, 10.1512, 10.1512] +24-11-19 20:26:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:47 | D | sum error = [ 1061.5588, 1135.8874, 1213.0550, 1293.8945, 1378.6918] +24-11-19 20:26:47 | D | best error = [ 10.1512, 10.1512, 10.1512, 10.1512, 10.1512] +24-11-19 20:26:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:47 | D | sum error = [ 1466.9018, 1558.1072, 1651.9625, 1747.9451, 1845.2047] +24-11-19 20:26:47 | D | best error = [ 10.1512, 10.1512, 10.1512, 10.1512, 10.1512] +24-11-19 20:26:47 | D | + error = [10.1512] +24-11-19 20:26:47 | D | - Calibrating model.layers.12.self_attn.v_proj.weight +24-11-19 20:26:47 | D | + w: sint8 +24-11-19 20:26:47 | D | + x: None +24-11-19 20:26:47 | D | + y: None +24-11-19 20:26:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:47 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:26:47 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:26:47 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:26:47 | D | - range ratio = [ 1.0000] +24-11-19 20:26:47 | D | sum error = [ 4.6460] +24-11-19 20:26:47 | D | best error = [ 4.6460] +24-11-19 20:26:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:47 | D | sum error = [ 4.5952, 4.5831, 4.6238, 4.6632, 4.7590] +24-11-19 20:26:47 | D | best error = [ 4.3300, 4.2094, 4.1515, 4.1121, 4.0946] +24-11-19 20:26:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:47 | D | sum error = [ 4.8810, 5.0238, 5.2422, 5.4988, 5.7909] +24-11-19 20:26:47 | D | best error = [ 4.0866, 4.0827, 4.0815, 4.0813, 4.0813] +24-11-19 20:26:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:47 | D | sum error = [ 6.1181, 6.4929, 6.9256, 7.3965, 7.9223] +24-11-19 20:26:47 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 20:26:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:47 | D | sum error = [ 8.4833, 9.0882, 9.7510, 10.4522, 11.2147] +24-11-19 20:26:47 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 20:26:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:47 | D | sum error = [ 12.0061, 12.8747, 13.8079, 14.8003, 15.8065] +24-11-19 20:26:47 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 20:26:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:47 | D | sum error = [ 16.9062, 18.0576, 19.2812, 20.5750, 21.9568] +24-11-19 20:26:47 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 20:26:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:47 | D | sum error = [ 23.4132, 24.9266, 26.5569, 28.2512, 30.0627] +24-11-19 20:26:47 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 20:26:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:47 | D | sum error = [ 31.9264, 33.9483, 36.0498, 38.2325, 40.5696] +24-11-19 20:26:47 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 20:26:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:47 | D | sum error = [ 43.0097, 45.5931, 48.2898, 51.1402, 54.1306] +24-11-19 20:26:47 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 20:26:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:47 | D | sum error = [ 57.2738, 60.5393, 63.9824, 67.5902, 71.3618] +24-11-19 20:26:47 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 20:26:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:47 | D | sum error = [ 75.2951, 79.4385, 83.7503, 88.2727, 92.9956] +24-11-19 20:26:47 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 20:26:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:47 | D | sum error = [ 97.9200, 103.0707, 108.4301, 114.0175, 119.8443] +24-11-19 20:26:47 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 20:26:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:47 | D | sum error = [ 125.9304, 132.2545, 138.8342, 145.6706, 152.7721] +24-11-19 20:26:47 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 20:26:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:47 | D | sum error = [ 160.1588, 167.8083, 175.7313, 183.9614, 192.4699] +24-11-19 20:26:47 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 20:26:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:47 | D | sum error = [ 201.2917, 210.4159, 219.8474, 229.6086, 239.6801] +24-11-19 20:26:47 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 20:26:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:47 | D | sum error = [ 250.0827, 260.8105, 271.8638, 283.2437, 294.9720] +24-11-19 20:26:47 | D | best error = [ 4.0813, 4.0813, 4.0813, 4.0813, 4.0813] +24-11-19 20:26:47 | D | + error = [4.0813] +24-11-19 20:26:47 | D | - Calibrating model.layers.12.self_attn.o_proj.weight +24-11-19 20:26:47 | D | + w: sint8 +24-11-19 20:26:47 | D | + x: None +24-11-19 20:26:47 | D | + y: None +24-11-19 20:26:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:47 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:26:47 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:26:48 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:26:48 | D | - range ratio = [ 1.0000] +24-11-19 20:26:48 | D | sum error = [ 1.1831] +24-11-19 20:26:48 | D | best error = [ 1.1831] +24-11-19 20:26:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:48 | D | sum error = [ 1.1709, 1.1591, 1.1589, 1.1621, 1.1669] +24-11-19 20:26:48 | D | best error = [ 1.1020, 1.0621, 1.0378, 1.0220, 1.0095] +24-11-19 20:26:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:48 | D | sum error = [ 1.1712, 1.1854, 1.2072, 1.2296, 1.2699] +24-11-19 20:26:48 | D | best error = [ 1.0010, 0.9940, 0.9883, 0.9838, 0.9809] +24-11-19 20:26:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:48 | D | sum error = [ 1.3103, 1.3595, 1.4177, 1.4816, 1.5492] +24-11-19 20:26:48 | D | best error = [ 0.9783, 0.9765, 0.9750, 0.9739, 0.9730] +24-11-19 20:26:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:48 | D | sum error = [ 1.6306, 1.7240, 1.8168, 1.9255, 2.0409] +24-11-19 20:26:48 | D | best error = [ 0.9725, 0.9722, 0.9718, 0.9713, 0.9712] +24-11-19 20:26:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:48 | D | sum error = [ 2.1684, 2.3058, 2.4535, 2.6060, 2.7787] +24-11-19 20:26:48 | D | best error = [ 0.9710, 0.9709, 0.9708, 0.9708, 0.9707] +24-11-19 20:26:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:48 | D | sum error = [ 2.9583, 3.1538, 3.3594, 3.5744, 3.8095] +24-11-19 20:26:48 | D | best error = [ 0.9707, 0.9707, 0.9707, 0.9707, 0.9707] +24-11-19 20:26:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:48 | D | sum error = [ 4.0575, 4.3171, 4.5945, 4.8904, 5.1986] +24-11-19 20:26:48 | D | best error = [ 0.9707, 0.9706, 0.9706, 0.9706, 0.9706] +24-11-19 20:26:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:48 | D | sum error = [ 5.5272, 5.8682, 6.2344, 6.6238, 7.0279] +24-11-19 20:26:48 | D | best error = [ 0.9706, 0.9706, 0.9706, 0.9706, 0.9706] +24-11-19 20:26:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:48 | D | sum error = [ 7.4587, 7.9103, 8.3835, 8.8857, 9.4143] +24-11-19 20:26:48 | D | best error = [ 0.9706, 0.9706, 0.9706, 0.9706, 0.9706] +24-11-19 20:26:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:48 | D | sum error = [ 9.9682, 10.5527, 11.1622, 11.8066, 12.4819] +24-11-19 20:26:48 | D | best error = [ 0.9706, 0.9706, 0.9706, 0.9706, 0.9706] +24-11-19 20:26:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:48 | D | sum error = [ 13.1973, 13.9408, 14.7246, 15.5442, 16.4034] +24-11-19 20:26:48 | D | best error = [ 0.9706, 0.9706, 0.9706, 0.9706, 0.9706] +24-11-19 20:26:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:48 | D | sum error = [ 17.3023, 18.2406, 19.2255, 20.2517, 21.3238] +24-11-19 20:26:48 | D | best error = [ 0.9706, 0.9706, 0.9706, 0.9706, 0.9706] +24-11-19 20:26:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:48 | D | sum error = [ 22.4464, 23.6143, 24.8384, 26.1105, 27.4367] +24-11-19 20:26:48 | D | best error = [ 0.9706, 0.9706, 0.9706, 0.9706, 0.9706] +24-11-19 20:26:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:48 | D | sum error = [ 28.8196, 30.2602, 31.7590, 33.3152, 34.9375] +24-11-19 20:26:48 | D | best error = [ 0.9706, 0.9706, 0.9706, 0.9706, 0.9706] +24-11-19 20:26:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:48 | D | sum error = [ 36.6204, 38.3661, 40.1773, 42.0555, 44.0052] +24-11-19 20:26:48 | D | best error = [ 0.9706, 0.9706, 0.9706, 0.9706, 0.9706] +24-11-19 20:26:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:48 | D | sum error = [ 46.0225, 48.1061, 50.2564, 52.4809, 54.7779] +24-11-19 20:26:48 | D | best error = [ 0.9706, 0.9706, 0.9706, 0.9706, 0.9706] +24-11-19 20:26:48 | D | + error = [0.9706] +24-11-19 20:26:48 | D | - Calibrating model.layers.12.mlp.up_proj.weight +24-11-19 20:26:48 | D | + w: sint8 +24-11-19 20:26:48 | D | + x: None +24-11-19 20:26:48 | D | + y: None +24-11-19 20:26:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:48 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:26:48 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:26:48 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:26:48 | D | - range ratio = [ 1.0000] +24-11-19 20:26:48 | D | sum error = [ 6.1530] +24-11-19 20:26:48 | D | best error = [ 6.1530] +24-11-19 20:26:49 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:49 | D | sum error = [ 6.1111, 6.0891, 6.1190, 6.1870, 6.3088] +24-11-19 20:26:49 | D | best error = [ 5.7406, 5.5774, 5.4920, 5.4429, 5.4177] +24-11-19 20:26:49 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:49 | D | sum error = [ 6.4505, 6.6849, 6.9269, 7.2823, 7.6472] +24-11-19 20:26:49 | D | best error = [ 5.4062, 5.4013, 5.3992, 5.3986, 5.3986] +24-11-19 20:26:49 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:49 | D | sum error = [ 8.0934, 8.6084, 9.1645, 9.7618, 10.4475] +24-11-19 20:26:49 | D | best error = [ 5.3985, 5.3985, 5.3985, 5.3985, 5.3985] +24-11-19 20:26:49 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:49 | D | sum error = [ 11.2024, 11.9929, 12.8628, 13.7795, 14.7704] +24-11-19 20:26:49 | D | best error = [ 5.3985, 5.3985, 5.3985, 5.3985, 5.3985] +24-11-19 20:26:49 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:49 | D | sum error = [ 15.8322, 16.9705, 18.1541, 19.4296, 20.7887] +24-11-19 20:26:49 | D | best error = [ 5.3985, 5.3985, 5.3985, 5.3985, 5.3985] +24-11-19 20:26:49 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:49 | D | sum error = [ 22.2259, 23.7497, 25.3588, 27.0508, 28.8562] +24-11-19 20:26:49 | D | best error = [ 5.3985, 5.3985, 5.3985, 5.3985, 5.3985] +24-11-19 20:26:49 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:49 | D | sum error = [ 30.7627, 32.7605, 34.8826, 37.1080, 39.4630] +24-11-19 20:26:49 | D | best error = [ 5.3985, 5.3985, 5.3985, 5.3985, 5.3985] +24-11-19 20:26:49 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:49 | D | sum error = [ 41.9426, 44.5367, 47.2798, 50.1552, 53.1827] +24-11-19 20:26:49 | D | best error = [ 5.3985, 5.3985, 5.3985, 5.3985, 5.3985] +24-11-19 20:26:49 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:49 | D | sum error = [ 56.3458, 59.6814, 63.1748, 66.8437, 70.7058] +24-11-19 20:26:49 | D | best error = [ 5.3985, 5.3985, 5.3985, 5.3985, 5.3985] +24-11-19 20:26:49 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:49 | D | sum error = [ 74.7464, 78.9585, 83.3820, 88.0132, 92.8766] +24-11-19 20:26:49 | D | best error = [ 5.3985, 5.3985, 5.3985, 5.3985, 5.3985] +24-11-19 20:26:49 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:49 | D | sum error = [ 97.9490, 103.2414, 108.7804, 114.5681, 120.6128] +24-11-19 20:26:49 | D | best error = [ 5.3985, 5.3985, 5.3985, 5.3985, 5.3985] +24-11-19 20:26:49 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:49 | D | sum error = [ 126.9087, 133.4857, 140.3340, 147.4690, 154.9033] +24-11-19 20:26:49 | D | best error = [ 5.3985, 5.3985, 5.3985, 5.3985, 5.3985] +24-11-19 20:26:49 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:49 | D | sum error = [ 162.6438, 170.6884, 179.0623, 187.7663, 196.8140] +24-11-19 20:26:49 | D | best error = [ 5.3985, 5.3985, 5.3985, 5.3985, 5.3985] +24-11-19 20:26:49 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:49 | D | sum error = [ 206.2042, 215.9477, 226.0497, 236.5257, 247.3535] +24-11-19 20:26:49 | D | best error = [ 5.3985, 5.3985, 5.3985, 5.3985, 5.3985] +24-11-19 20:26:49 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:49 | D | sum error = [ 258.5859, 270.1910, 282.1877, 294.5775, 307.3633] +24-11-19 20:26:49 | D | best error = [ 5.3985, 5.3985, 5.3985, 5.3985, 5.3985] +24-11-19 20:26:49 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:49 | D | sum error = [ 320.5600, 334.1590, 348.1693, 362.5954, 377.4376] +24-11-19 20:26:49 | D | best error = [ 5.3985, 5.3985, 5.3985, 5.3985, 5.3985] +24-11-19 20:26:49 | D | + error = [5.3985] +24-11-19 20:26:49 | D | - Calibrating model.layers.12.mlp.gate_proj.weight +24-11-19 20:26:49 | D | + w: sint8 +24-11-19 20:26:49 | D | + x: None +24-11-19 20:26:49 | D | + y: None +24-11-19 20:26:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:49 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:26:49 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:26:50 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:26:50 | D | - range ratio = [ 1.0000] +24-11-19 20:26:50 | D | sum error = [ 6.4117] +24-11-19 20:26:50 | D | best error = [ 6.4117] +24-11-19 20:26:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:50 | D | sum error = [ 6.3731, 6.3465, 6.3861, 6.4430, 6.5694] +24-11-19 20:26:50 | D | best error = [ 5.9818, 5.8118, 5.7244, 5.6757, 5.6491] +24-11-19 20:26:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:50 | D | sum error = [ 6.7513, 6.9807, 7.2659, 7.6067, 8.0020] +24-11-19 20:26:50 | D | best error = [ 5.6365, 5.6309, 5.6288, 5.6282, 5.6280] +24-11-19 20:26:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:50 | D | sum error = [ 8.4810, 9.0034, 9.5973, 10.2540, 10.9897] +24-11-19 20:26:50 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 20:26:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:50 | D | sum error = [ 11.7747, 12.6334, 13.5450, 14.5290, 15.5914] +24-11-19 20:26:50 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 20:26:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:50 | D | sum error = [ 16.7317, 17.9438, 19.2314, 20.6148, 22.0722] +24-11-19 20:26:50 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 20:26:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:50 | D | sum error = [ 23.6373, 25.3001, 27.0530, 28.9068, 30.9012] +24-11-19 20:26:50 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 20:26:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:50 | D | sum error = [ 32.9748, 35.2033, 37.5526, 40.0467, 42.6936] +24-11-19 20:26:50 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 20:26:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:50 | D | sum error = [ 45.4998, 48.4497, 51.5866, 54.8867, 58.3711] +24-11-19 20:26:50 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 20:26:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:50 | D | sum error = [ 62.0741, 65.9888, 70.1382, 74.5001, 79.1156] +24-11-19 20:26:50 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 20:26:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:50 | D | sum error = [ 83.9692, 89.1089, 94.5352, 100.2252, 106.2462] +24-11-19 20:26:50 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 20:26:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:50 | D | sum error = [ 112.5869, 119.2588, 126.2828, 133.6648, 141.4275] +24-11-19 20:26:50 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 20:26:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:50 | D | sum error = [ 149.5774, 158.1289, 167.0970, 176.5102, 186.3878] +24-11-19 20:26:50 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 20:26:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:50 | D | sum error = [ 196.7262, 207.5517, 218.8822, 230.7340, 243.1441] +24-11-19 20:26:50 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 20:26:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:50 | D | sum error = [ 256.0943, 269.6204, 283.7174, 298.4043, 313.6724] +24-11-19 20:26:50 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 20:26:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:50 | D | sum error = [ 329.5653, 346.0841, 363.2200, 380.9670, 399.3606] +24-11-19 20:26:50 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 20:26:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:50 | D | sum error = [ 418.4088, 438.0910, 458.4281, 479.4096, 501.0371] +24-11-19 20:26:50 | D | best error = [ 5.6280, 5.6280, 5.6280, 5.6280, 5.6280] +24-11-19 20:26:50 | D | + error = [5.6280] +24-11-19 20:26:51 | D | - Calibrating model.layers.12.mlp.down_proj.weight +24-11-19 20:26:51 | D | + w: sint8 +24-11-19 20:26:51 | D | + x: None +24-11-19 20:26:51 | D | + y: None +24-11-19 20:26:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:51 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:26:51 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:26:51 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:26:51 | D | - range ratio = [ 1.0000] +24-11-19 20:26:51 | D | sum error = [ 1.5791] +24-11-19 20:26:51 | D | best error = [ 1.5791] +24-11-19 20:26:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:52 | D | sum error = [ 1.5651, 1.5540, 1.5507, 1.5436, 1.5459] +24-11-19 20:26:52 | D | best error = [ 1.5245, 1.4961, 1.4779, 1.4643, 1.4538] +24-11-19 20:26:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:52 | D | sum error = [ 1.5533, 1.5657, 1.5870, 1.6128, 1.6502] +24-11-19 20:26:52 | D | best error = [ 1.4458, 1.4406, 1.4365, 1.4340, 1.4320] +24-11-19 20:26:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:52 | D | sum error = [ 1.6921, 1.7470, 1.8146, 1.8885, 1.9763] +24-11-19 20:26:52 | D | best error = [ 1.4307, 1.4300, 1.4296, 1.4293, 1.4292] +24-11-19 20:26:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:52 | D | sum error = [ 2.0784, 2.1866, 2.3104, 2.4467, 2.5972] +24-11-19 20:26:52 | D | best error = [ 1.4291, 1.4290, 1.4289, 1.4289, 1.4289] +24-11-19 20:26:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:52 | D | sum error = [ 2.7629, 2.9411, 3.1336, 3.3457, 3.5714] +24-11-19 20:26:52 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 20:26:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:52 | D | sum error = [ 3.8092, 4.0696, 4.3494, 4.6473, 4.9627] +24-11-19 20:26:52 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 20:26:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:52 | D | sum error = [ 5.3024, 5.6599, 6.0439, 6.4512, 6.8822] +24-11-19 20:26:52 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 20:26:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:52 | D | sum error = [ 7.3406, 7.8272, 8.3447, 8.8891, 9.4646] +24-11-19 20:26:52 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 20:26:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:52 | D | sum error = [ 10.0714, 10.7161, 11.3965, 12.1155, 12.8721] +24-11-19 20:26:52 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 20:26:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:52 | D | sum error = [ 13.6709, 14.5152, 15.4046, 16.3397, 17.3196] +24-11-19 20:26:52 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 20:26:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:52 | D | sum error = [ 18.3557, 19.4419, 20.5815, 21.7795, 23.0379] +24-11-19 20:26:52 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 20:26:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:52 | D | sum error = [ 24.3565, 25.7384, 27.1872, 28.7014, 30.2868] +24-11-19 20:26:52 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 20:26:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:52 | D | sum error = [ 31.9436, 33.6749, 35.4836, 37.3710, 39.3372] +24-11-19 20:26:52 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 20:26:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:52 | D | sum error = [ 41.3896, 43.5258, 45.7510, 48.0695, 50.4712] +24-11-19 20:26:52 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 20:26:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:52 | D | sum error = [ 52.9735, 55.5694, 58.2651, 61.0574, 63.9514] +24-11-19 20:26:52 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 20:26:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:52 | D | sum error = [ 66.9507, 70.0499, 73.2574, 76.5733, 79.9962] +24-11-19 20:26:52 | D | best error = [ 1.4289, 1.4289, 1.4289, 1.4289, 1.4289] +24-11-19 20:26:52 | D | + error = [1.4289] +24-11-19 20:26:52 | D | - Quantizing model.layers.12.self_attn.q_proj.weight +24-11-19 20:26:53 | D | - Quantizing model.layers.12.self_attn.k_proj.weight +24-11-19 20:26:53 | D | - Quantizing model.layers.12.self_attn.v_proj.weight +24-11-19 20:26:54 | D | - Quantizing model.layers.12.self_attn.o_proj.weight +24-11-19 20:26:55 | D | - Quantizing model.layers.12.mlp.up_proj.weight +24-11-19 20:26:56 | D | - Quantizing model.layers.12.mlp.gate_proj.weight +24-11-19 20:26:57 | D | - Quantizing model.layers.12.mlp.down_proj.weight +24-11-19 20:27:05 | D | - Quantizing layer model.layers.13 +24-11-19 20:27:05 | D | - Calibrating model.layers.13.self_attn.q_proj.weight +24-11-19 20:27:05 | D | + w: sint8 +24-11-19 20:27:05 | D | + x: None +24-11-19 20:27:05 | D | + y: None +24-11-19 20:27:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:27:05 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:27:05 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:27:05 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:27:05 | D | - range ratio = [ 1.0000] +24-11-19 20:27:05 | D | sum error = [ 10.1654] +24-11-19 20:27:05 | D | best error = [ 10.1654] +24-11-19 20:27:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:18 | D | sum error = [ 10.0590, 10.0943, 10.1634, 10.1993, 10.5859] +24-11-19 20:27:18 | D | best error = [ 10.0590, 10.0590, 10.0590, 10.0590, 10.0590] +24-11-19 20:27:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:18 | D | sum error = [ 10.9038, 11.0465, 11.5621, 12.3685, 12.9039] +24-11-19 20:27:18 | D | best error = [ 10.0590, 10.0590, 10.0590, 10.0590, 10.0590] +24-11-19 20:27:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:18 | D | sum error = [ 13.5234, 14.7089, 15.6851, 16.9344, 18.3144] +24-11-19 20:27:18 | D | best error = [ 10.0590, 10.0590, 10.0590, 10.0590, 10.0590] +24-11-19 20:27:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:18 | D | sum error = [ 19.5742, 21.1102, 23.1604, 25.2549, 27.4160] +24-11-19 20:27:18 | D | best error = [ 10.0590, 10.0590, 10.0590, 10.0590, 10.0590] +24-11-19 20:27:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:18 | D | sum error = [ 29.4357, 32.3793, 35.0972, 37.9228, 41.1649] +24-11-19 20:27:18 | D | best error = [ 10.0590, 10.0590, 10.0590, 10.0590, 10.0590] +24-11-19 20:27:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:18 | D | sum error = [ 45.0608, 48.9400, 53.5547, 57.8489, 63.0658] +24-11-19 20:27:18 | D | best error = [ 10.0590, 10.0590, 10.0590, 10.0590, 10.0590] +24-11-19 20:27:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:18 | D | sum error = [ 69.0850, 74.8961, 81.2178, 88.5638, 96.0770] +24-11-19 20:27:18 | D | best error = [ 10.0590, 10.0590, 10.0590, 10.0590, 10.0590] +24-11-19 20:27:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:18 | D | sum error = [ 104.2432, 112.9946, 122.2112, 131.8033, 142.6973] +24-11-19 20:27:18 | D | best error = [ 10.0590, 10.0590, 10.0590, 10.0590, 10.0590] +24-11-19 20:27:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:18 | D | sum error = [ 153.9976, 166.4230, 179.4554, 193.3578, 208.1615] +24-11-19 20:27:18 | D | best error = [ 10.0590, 10.0590, 10.0590, 10.0590, 10.0590] +24-11-19 20:27:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:18 | D | sum error = [ 223.6179, 240.9247, 258.8702, 278.1944, 299.1680] +24-11-19 20:27:18 | D | best error = [ 10.0590, 10.0590, 10.0590, 10.0590, 10.0590] +24-11-19 20:27:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:18 | D | sum error = [ 321.5461, 345.4226, 370.5346, 397.8168, 427.2707] +24-11-19 20:27:18 | D | best error = [ 10.0590, 10.0590, 10.0590, 10.0590, 10.0590] +24-11-19 20:27:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:18 | D | sum error = [ 458.2469, 491.5655, 527.4621, 565.7382, 606.6620] +24-11-19 20:27:18 | D | best error = [ 10.0590, 10.0590, 10.0590, 10.0590, 10.0590] +24-11-19 20:27:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:18 | D | sum error = [ 650.3138, 697.9554, 748.3567, 802.3365, 860.2103] +24-11-19 20:27:18 | D | best error = [ 10.0590, 10.0590, 10.0590, 10.0590, 10.0590] +24-11-19 20:27:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:18 | D | sum error = [ 922.5869, 988.5678, 1059.5291, 1134.9686, 1214.7710] +24-11-19 20:27:18 | D | best error = [ 10.0590, 10.0590, 10.0590, 10.0590, 10.0590] +24-11-19 20:27:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:18 | D | sum error = [ 1300.4472, 1390.8278, 1486.3931, 1587.9905, 1695.0691] +24-11-19 20:27:18 | D | best error = [ 10.0590, 10.0590, 10.0590, 10.0590, 10.0590] +24-11-19 20:27:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:18 | D | sum error = [ 1806.8282, 1923.6264, 2044.4770, 2168.8804, 2294.1744] +24-11-19 20:27:18 | D | best error = [ 10.0590, 10.0590, 10.0590, 10.0590, 10.0590] +24-11-19 20:27:18 | D | + error = [10.0590] +24-11-19 20:27:18 | D | - Calibrating model.layers.13.self_attn.k_proj.weight +24-11-19 20:27:18 | D | + w: sint8 +24-11-19 20:27:18 | D | + x: None +24-11-19 20:27:18 | D | + y: None +24-11-19 20:27:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:27:18 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:27:18 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:27:18 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:27:18 | D | - range ratio = [ 1.0000] +24-11-19 20:27:18 | D | sum error = [ 10.6845] +24-11-19 20:27:18 | D | best error = [ 10.6845] +24-11-19 20:27:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:31 | D | sum error = [ 10.5396, 10.5468, 10.6495, 10.9145, 11.4504] +24-11-19 20:27:31 | D | best error = [ 10.5396, 10.5396, 10.5396, 10.5396, 10.5396] +24-11-19 20:27:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:31 | D | sum error = [ 11.1740, 11.8668, 12.0634, 13.2254, 13.3922] +24-11-19 20:27:31 | D | best error = [ 10.5396, 10.5396, 10.5396, 10.5396, 10.5396] +24-11-19 20:27:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:31 | D | sum error = [ 15.1007, 15.2214, 16.9854, 18.3108, 18.4110] +24-11-19 20:27:31 | D | best error = [ 10.5396, 10.5396, 10.5396, 10.5396, 10.5396] +24-11-19 20:27:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:31 | D | sum error = [ 20.4294, 21.4637, 23.6874, 25.5696, 27.3435] +24-11-19 20:27:31 | D | best error = [ 10.5396, 10.5396, 10.5396, 10.5396, 10.5396] +24-11-19 20:27:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:31 | D | sum error = [ 29.6178, 32.0963, 34.4501, 38.2941, 41.1765] +24-11-19 20:27:31 | D | best error = [ 10.5396, 10.5396, 10.5396, 10.5396, 10.5396] +24-11-19 20:27:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:31 | D | sum error = [ 44.1987, 48.7046, 52.6922, 56.0167, 61.1085] +24-11-19 20:27:31 | D | best error = [ 10.5396, 10.5396, 10.5396, 10.5396, 10.5396] +24-11-19 20:27:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:31 | D | sum error = [ 66.3532, 71.6871, 77.7892, 84.5723, 92.2407] +24-11-19 20:27:31 | D | best error = [ 10.5396, 10.5396, 10.5396, 10.5396, 10.5396] +24-11-19 20:27:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:31 | D | sum error = [ 98.5396, 107.5710, 116.1005, 125.2056, 135.7125] +24-11-19 20:27:31 | D | best error = [ 10.5396, 10.5396, 10.5396, 10.5396, 10.5396] +24-11-19 20:27:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:31 | D | sum error = [ 146.8440, 159.0217, 172.1245, 185.3575, 200.1475] +24-11-19 20:27:31 | D | best error = [ 10.5396, 10.5396, 10.5396, 10.5396, 10.5396] +24-11-19 20:27:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:31 | D | sum error = [ 215.6877, 232.7600, 250.7473, 270.1736, 290.2525] +24-11-19 20:27:31 | D | best error = [ 10.5396, 10.5396, 10.5396, 10.5396, 10.5396] +24-11-19 20:27:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:31 | D | sum error = [ 313.3045, 337.3123, 362.6090, 389.1968, 419.2608] +24-11-19 20:27:31 | D | best error = [ 10.5396, 10.5396, 10.5396, 10.5396, 10.5396] +24-11-19 20:27:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:31 | D | sum error = [ 451.2418, 485.0466, 523.2424, 563.3219, 604.9204] +24-11-19 20:27:31 | D | best error = [ 10.5396, 10.5396, 10.5396, 10.5396, 10.5396] +24-11-19 20:27:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:31 | D | sum error = [ 651.0977, 699.4428, 752.4532, 808.9954, 870.1013] +24-11-19 20:27:31 | D | best error = [ 10.5396, 10.5396, 10.5396, 10.5396, 10.5396] +24-11-19 20:27:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:31 | D | sum error = [ 935.7304, 1006.2076, 1080.6435, 1160.7023, 1246.2511] +24-11-19 20:27:31 | D | best error = [ 10.5396, 10.5396, 10.5396, 10.5396, 10.5396] +24-11-19 20:27:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:31 | D | sum error = [ 1336.9937, 1432.6076, 1535.0471, 1641.0821, 1751.7720] +24-11-19 20:27:31 | D | best error = [ 10.5396, 10.5396, 10.5396, 10.5396, 10.5396] +24-11-19 20:27:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:31 | D | sum error = [ 1869.2753, 1987.8667, 2110.8794, 2235.4379, 2361.5986] +24-11-19 20:27:31 | D | best error = [ 10.5396, 10.5396, 10.5396, 10.5396, 10.5396] +24-11-19 20:27:31 | D | + error = [10.5396] +24-11-19 20:27:31 | D | - Calibrating model.layers.13.self_attn.v_proj.weight +24-11-19 20:27:31 | D | + w: sint8 +24-11-19 20:27:31 | D | + x: None +24-11-19 20:27:31 | D | + y: None +24-11-19 20:27:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:31 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:27:31 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:27:31 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:27:31 | D | - range ratio = [ 1.0000] +24-11-19 20:27:31 | D | sum error = [ 4.8721] +24-11-19 20:27:31 | D | best error = [ 4.8721] +24-11-19 20:27:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:31 | D | sum error = [ 4.8574, 4.8477, 4.8927, 4.9403, 5.0353] +24-11-19 20:27:31 | D | best error = [ 4.5665, 4.4406, 4.3757, 4.3400, 4.3215] +24-11-19 20:27:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:31 | D | sum error = [ 5.1419, 5.3159, 5.5353, 5.7932, 6.0991] +24-11-19 20:27:31 | D | best error = [ 4.3122, 4.3076, 4.3062, 4.3057, 4.3054] +24-11-19 20:27:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:31 | D | sum error = [ 6.4862, 6.8474, 7.3025, 7.8126, 8.3449] +24-11-19 20:27:31 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 20:27:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:31 | D | sum error = [ 8.9100, 9.5646, 10.2550, 10.9905, 11.7625] +24-11-19 20:27:31 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 20:27:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:31 | D | sum error = [ 12.6246, 13.4881, 14.4503, 15.4498, 16.5292] +24-11-19 20:27:31 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 20:27:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:31 | D | sum error = [ 17.6578, 18.8803, 20.1466, 21.5061, 22.9194] +24-11-19 20:27:31 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 20:27:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:31 | D | sum error = [ 24.4166, 26.0181, 27.6723, 29.4331, 31.2973] +24-11-19 20:27:31 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 20:27:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:31 | D | sum error = [ 33.2409, 35.3174, 37.4805, 39.7675, 42.1664] +24-11-19 20:27:31 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 20:27:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:31 | D | sum error = [ 44.6826, 47.3392, 50.1089, 53.0268, 56.1020] +24-11-19 20:27:31 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 20:27:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:31 | D | sum error = [ 59.2945, 62.6708, 66.1809, 69.8464, 73.6891] +24-11-19 20:27:31 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 20:27:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:31 | D | sum error = [ 77.7000, 81.8892, 86.2713, 90.8360, 95.6039] +24-11-19 20:27:31 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 20:27:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:31 | D | sum error = [ 100.5855, 105.7537, 111.1549, 116.7756, 122.6130] +24-11-19 20:27:31 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 20:27:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:31 | D | sum error = [ 128.7006, 135.0246, 141.5898, 148.4096, 155.4739] +24-11-19 20:27:31 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 20:27:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:31 | D | sum error = [ 162.7976, 170.4024, 178.2889, 186.4417, 194.8815] +24-11-19 20:27:31 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 20:27:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:31 | D | sum error = [ 203.6062, 212.6183, 221.9271, 231.5299, 241.4438] +24-11-19 20:27:31 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 20:27:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:31 | D | sum error = [ 251.6561, 262.1873, 273.0409, 284.2104, 295.7086] +24-11-19 20:27:31 | D | best error = [ 4.3054, 4.3054, 4.3054, 4.3054, 4.3054] +24-11-19 20:27:31 | D | + error = [4.3054] +24-11-19 20:27:32 | D | - Calibrating model.layers.13.self_attn.o_proj.weight +24-11-19 20:27:32 | D | + w: sint8 +24-11-19 20:27:32 | D | + x: None +24-11-19 20:27:32 | D | + y: None +24-11-19 20:27:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:32 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:27:32 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:27:32 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:27:32 | D | - range ratio = [ 1.0000] +24-11-19 20:27:32 | D | sum error = [ 1.3070] +24-11-19 20:27:32 | D | best error = [ 1.3070] +24-11-19 20:27:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:32 | D | sum error = [ 1.2980, 1.2914, 1.2807, 1.2906, 1.3000] +24-11-19 20:27:32 | D | best error = [ 1.2180, 1.1782, 1.1526, 1.1366, 1.1241] +24-11-19 20:27:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:32 | D | sum error = [ 1.3080, 1.3285, 1.3612, 1.3943, 1.4381] +24-11-19 20:27:32 | D | best error = [ 1.1145, 1.1071, 1.1018, 1.0979, 1.0954] +24-11-19 20:27:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:32 | D | sum error = [ 1.4832, 1.5456, 1.6204, 1.6994, 1.7903] +24-11-19 20:27:32 | D | best error = [ 1.0932, 1.0917, 1.0903, 1.0890, 1.0885] +24-11-19 20:27:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:32 | D | sum error = [ 1.8816, 1.9999, 2.1176, 2.2471, 2.3890] +24-11-19 20:27:32 | D | best error = [ 1.0878, 1.0871, 1.0866, 1.0863, 1.0860] +24-11-19 20:27:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:32 | D | sum error = [ 2.5436, 2.7013, 2.8758, 3.0680, 3.2699] +24-11-19 20:27:32 | D | best error = [ 1.0859, 1.0858, 1.0857, 1.0856, 1.0856] +24-11-19 20:27:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:32 | D | sum error = [ 3.4814, 3.7086, 3.9449, 4.2047, 4.4795] +24-11-19 20:27:32 | D | best error = [ 1.0856, 1.0856, 1.0856, 1.0856, 1.0856] +24-11-19 20:27:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:32 | D | sum error = [ 4.7647, 5.0749, 5.3988, 5.7357, 6.1025] +24-11-19 20:27:32 | D | best error = [ 1.0855, 1.0855, 1.0855, 1.0855, 1.0855] +24-11-19 20:27:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:32 | D | sum error = [ 6.4849, 6.8837, 7.3097, 7.7640, 8.2352] +24-11-19 20:27:32 | D | best error = [ 1.0855, 1.0855, 1.0855, 1.0855, 1.0855] +24-11-19 20:27:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:32 | D | sum error = [ 8.7347, 9.2636, 9.8193, 10.4041, 11.0176] +24-11-19 20:27:32 | D | best error = [ 1.0855, 1.0855, 1.0855, 1.0855, 1.0855] +24-11-19 20:27:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:32 | D | sum error = [ 11.6638, 12.3433, 13.0564, 13.8084, 14.5901] +24-11-19 20:27:32 | D | best error = [ 1.0855, 1.0855, 1.0855, 1.0855, 1.0855] +24-11-19 20:27:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:32 | D | sum error = [ 15.4197, 16.2820, 17.1918, 18.1443, 19.1408] +24-11-19 20:27:32 | D | best error = [ 1.0855, 1.0855, 1.0855, 1.0855, 1.0855] +24-11-19 20:27:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:32 | D | sum error = [ 20.1818, 21.2769, 22.4194, 23.6127, 24.8628] +24-11-19 20:27:32 | D | best error = [ 1.0855, 1.0855, 1.0855, 1.0855, 1.0855] +24-11-19 20:27:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:32 | D | sum error = [ 26.1625, 27.5176, 28.9328, 30.4086, 31.9456] +24-11-19 20:27:32 | D | best error = [ 1.0855, 1.0855, 1.0855, 1.0855, 1.0855] +24-11-19 20:27:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:32 | D | sum error = [ 33.5418, 35.2094, 36.9408, 38.7350, 40.6032] +24-11-19 20:27:32 | D | best error = [ 1.0855, 1.0855, 1.0855, 1.0855, 1.0855] +24-11-19 20:27:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:32 | D | sum error = [ 42.5411, 44.5519, 46.6369, 48.7964, 51.0382] +24-11-19 20:27:32 | D | best error = [ 1.0855, 1.0855, 1.0855, 1.0855, 1.0855] +24-11-19 20:27:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:32 | D | sum error = [ 53.3593, 55.7631, 58.2482, 60.8152, 63.4696] +24-11-19 20:27:32 | D | best error = [ 1.0855, 1.0855, 1.0855, 1.0855, 1.0855] +24-11-19 20:27:32 | D | + error = [1.0855] +24-11-19 20:27:32 | D | - Calibrating model.layers.13.mlp.up_proj.weight +24-11-19 20:27:32 | D | + w: sint8 +24-11-19 20:27:32 | D | + x: None +24-11-19 20:27:32 | D | + y: None +24-11-19 20:27:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:32 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:27:32 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:27:32 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:27:32 | D | - range ratio = [ 1.0000] +24-11-19 20:27:32 | D | sum error = [ 6.4067] +24-11-19 20:27:32 | D | best error = [ 6.4067] +24-11-19 20:27:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:33 | D | sum error = [ 6.3675, 6.3465, 6.3547, 6.4482, 6.5663] +24-11-19 20:27:33 | D | best error = [ 5.9573, 5.7809, 5.6865, 5.6344, 5.6075] +24-11-19 20:27:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:33 | D | sum error = [ 6.7206, 6.9630, 7.2475, 7.6053, 7.9945] +24-11-19 20:27:33 | D | best error = [ 5.5929, 5.5868, 5.5848, 5.5843, 5.5842] +24-11-19 20:27:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:33 | D | sum error = [ 8.4613, 8.9805, 9.5554, 10.2155, 10.8873] +24-11-19 20:27:33 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:27:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:33 | D | sum error = [ 11.6765, 12.5201, 13.4125, 14.3875, 15.4176] +24-11-19 20:27:33 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:27:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:33 | D | sum error = [ 16.5269, 17.7120, 18.9561, 20.2975, 21.6976] +24-11-19 20:27:33 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:27:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:33 | D | sum error = [ 23.1993, 24.7762, 26.4663, 28.2427, 30.1136] +24-11-19 20:27:33 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:27:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:33 | D | sum error = [ 32.0778, 34.1969, 36.3847, 38.7119, 41.1540] +24-11-19 20:27:33 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:27:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:33 | D | sum error = [ 43.7446, 46.4506, 49.3081, 52.3092, 55.4621] +24-11-19 20:27:33 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:27:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:33 | D | sum error = [ 58.7768, 62.2599, 65.9227, 69.7801, 73.8114] +24-11-19 20:27:33 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:27:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:33 | D | sum error = [ 78.0369, 82.4739, 87.1182, 91.9638, 97.0539] +24-11-19 20:27:33 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:27:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:33 | D | sum error = [ 102.3662, 107.9249, 113.7316, 119.8127, 126.1416] +24-11-19 20:27:33 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:27:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:33 | D | sum error = [ 132.7423, 139.6316, 146.8201, 154.3039, 162.0919] +24-11-19 20:27:33 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:27:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:33 | D | sum error = [ 170.1822, 178.5953, 187.3582, 196.4418, 205.8733] +24-11-19 20:27:33 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:27:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:33 | D | sum error = [ 215.6813, 225.8469, 236.3890, 247.3238, 258.6232] +24-11-19 20:27:33 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:27:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:33 | D | sum error = [ 270.3393, 282.4501, 294.9718, 307.9013, 321.2507] +24-11-19 20:27:33 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:27:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:33 | D | sum error = [ 335.0145, 349.1902, 363.8139, 378.8687, 394.3496] +24-11-19 20:27:33 | D | best error = [ 5.5842, 5.5842, 5.5842, 5.5842, 5.5842] +24-11-19 20:27:33 | D | + error = [5.5842] +24-11-19 20:27:33 | D | - Calibrating model.layers.13.mlp.gate_proj.weight +24-11-19 20:27:33 | D | + w: sint8 +24-11-19 20:27:33 | D | + x: None +24-11-19 20:27:33 | D | + y: None +24-11-19 20:27:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:33 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:27:34 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:27:34 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:27:34 | D | - range ratio = [ 1.0000] +24-11-19 20:27:34 | D | sum error = [ 6.5604] +24-11-19 20:27:34 | D | best error = [ 6.5604] +24-11-19 20:27:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:35 | D | sum error = [ 6.5324, 6.5093, 6.5484, 6.6245, 6.7408] +24-11-19 20:27:35 | D | best error = [ 6.1089, 5.9359, 5.8444, 5.7901, 5.7607] +24-11-19 20:27:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:35 | D | sum error = [ 6.9069, 7.1637, 7.4519, 7.7874, 8.2076] +24-11-19 20:27:35 | D | best error = [ 5.7470, 5.7412, 5.7396, 5.7389, 5.7388] +24-11-19 20:27:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:35 | D | sum error = [ 8.6919, 9.2310, 9.8411, 10.5116, 11.2331] +24-11-19 20:27:35 | D | best error = [ 5.7387, 5.7387, 5.7387, 5.7387, 5.7387] +24-11-19 20:27:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:35 | D | sum error = [ 12.0361, 12.9195, 13.8392, 14.8576, 15.9485] +24-11-19 20:27:35 | D | best error = [ 5.7387, 5.7387, 5.7387, 5.7387, 5.7387] +24-11-19 20:27:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:35 | D | sum error = [ 17.1101, 18.3274, 19.6688, 21.0845, 22.5760] +24-11-19 20:27:35 | D | best error = [ 5.7387, 5.7387, 5.7387, 5.7387, 5.7387] +24-11-19 20:27:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:35 | D | sum error = [ 24.1960, 25.9036, 27.6940, 29.6192, 31.6561] +24-11-19 20:27:35 | D | best error = [ 5.7387, 5.7387, 5.7387, 5.7387, 5.7387] +24-11-19 20:27:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:35 | D | sum error = [ 33.8161, 36.0930, 38.5156, 41.0812, 43.8118] +24-11-19 20:27:35 | D | best error = [ 5.7387, 5.7387, 5.7387, 5.7387, 5.7387] +24-11-19 20:27:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:35 | D | sum error = [ 46.6908, 49.7754, 53.0003, 56.4376, 60.0546] +24-11-19 20:27:35 | D | best error = [ 5.7387, 5.7387, 5.7387, 5.7387, 5.7387] +24-11-19 20:27:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:35 | D | sum error = [ 63.8888, 67.9150, 72.2144, 76.7292, 81.5248] +24-11-19 20:27:35 | D | best error = [ 5.7387, 5.7387, 5.7387, 5.7387, 5.7387] +24-11-19 20:27:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:35 | D | sum error = [ 86.5865, 91.9270, 97.5788, 103.5386, 109.8252] +24-11-19 20:27:35 | D | best error = [ 5.7387, 5.7387, 5.7387, 5.7387, 5.7387] +24-11-19 20:27:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:35 | D | sum error = [ 116.4273, 123.3778, 130.6983, 138.4050, 146.4957] +24-11-19 20:27:35 | D | best error = [ 5.7387, 5.7387, 5.7387, 5.7387, 5.7387] +24-11-19 20:27:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:35 | D | sum error = [ 154.9948, 163.9434, 173.3360, 183.2128, 193.5412] +24-11-19 20:27:35 | D | best error = [ 5.7387, 5.7387, 5.7387, 5.7387, 5.7387] +24-11-19 20:27:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:35 | D | sum error = [ 204.3867, 215.7243, 227.6204, 240.0462, 253.0364] +24-11-19 20:27:35 | D | best error = [ 5.7387, 5.7387, 5.7387, 5.7387, 5.7387] +24-11-19 20:27:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:35 | D | sum error = [ 266.6049, 280.7406, 295.4727, 310.8053, 326.7404] +24-11-19 20:27:35 | D | best error = [ 5.7387, 5.7387, 5.7387, 5.7387, 5.7387] +24-11-19 20:27:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:35 | D | sum error = [ 343.3049, 360.5231, 378.3813, 396.9018, 416.0971] +24-11-19 20:27:35 | D | best error = [ 5.7387, 5.7387, 5.7387, 5.7387, 5.7387] +24-11-19 20:27:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:35 | D | sum error = [ 435.9592, 456.4975, 477.7159, 499.6248, 522.2147] +24-11-19 20:27:35 | D | best error = [ 5.7387, 5.7387, 5.7387, 5.7387, 5.7387] +24-11-19 20:27:35 | D | + error = [5.7387] +24-11-19 20:27:35 | D | - Calibrating model.layers.13.mlp.down_proj.weight +24-11-19 20:27:35 | D | + w: sint8 +24-11-19 20:27:35 | D | + x: None +24-11-19 20:27:35 | D | + y: None +24-11-19 20:27:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:35 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:27:35 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:27:35 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:27:35 | D | - range ratio = [ 1.0000] +24-11-19 20:27:35 | D | sum error = [ 1.7328] +24-11-19 20:27:35 | D | best error = [ 1.7328] +24-11-19 20:27:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:36 | D | sum error = [ 1.7166, 1.7056, 1.6973, 1.6934, 1.6961] +24-11-19 20:27:36 | D | best error = [ 1.6726, 1.6404, 1.6201, 1.6053, 1.5948] +24-11-19 20:27:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:36 | D | sum error = [ 1.7011, 1.7141, 1.7365, 1.7667, 1.8049] +24-11-19 20:27:36 | D | best error = [ 1.5864, 1.5796, 1.5750, 1.5716, 1.5696] +24-11-19 20:27:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:36 | D | sum error = [ 1.8531, 1.9107, 1.9766, 2.0594, 2.1511] +24-11-19 20:27:36 | D | best error = [ 1.5681, 1.5672, 1.5667, 1.5664, 1.5662] +24-11-19 20:27:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:36 | D | sum error = [ 2.2551, 2.3714, 2.5022, 2.6494, 2.8103] +24-11-19 20:27:36 | D | best error = [ 1.5661, 1.5660, 1.5660, 1.5660, 1.5659] +24-11-19 20:27:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:36 | D | sum error = [ 2.9810, 3.1744, 3.3794, 3.6016, 3.8425] +24-11-19 20:27:36 | D | best error = [ 1.5659, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:27:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:36 | D | sum error = [ 4.0996, 4.3728, 4.6694, 4.9877, 5.3256] +24-11-19 20:27:36 | D | best error = [ 1.5659, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:27:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:36 | D | sum error = [ 5.6843, 6.0702, 6.4769, 6.9127, 7.3743] +24-11-19 20:27:36 | D | best error = [ 1.5659, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:27:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:36 | D | sum error = [ 7.8656, 8.3826, 8.9360, 9.5200, 10.1363] +24-11-19 20:27:36 | D | best error = [ 1.5659, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:27:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:36 | D | sum error = [ 10.7869, 11.4782, 12.2108, 12.9796, 13.7919] +24-11-19 20:27:36 | D | best error = [ 1.5659, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:27:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:36 | D | sum error = [ 14.6508, 15.5548, 16.5086, 17.5140, 18.5737] +24-11-19 20:27:36 | D | best error = [ 1.5659, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:27:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:36 | D | sum error = [ 19.6847, 20.8541, 22.0853, 23.3784, 24.7339] +24-11-19 20:27:36 | D | best error = [ 1.5659, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:27:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:36 | D | sum error = [ 26.1595, 27.6518, 29.2171, 30.8567, 32.5735] +24-11-19 20:27:36 | D | best error = [ 1.5659, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:27:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:36 | D | sum error = [ 34.3689, 36.2472, 38.2090, 40.2575, 42.3950] +24-11-19 20:27:36 | D | best error = [ 1.5659, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:27:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:36 | D | sum error = [ 44.6269, 46.9514, 49.3739, 51.9012, 54.5221] +24-11-19 20:27:36 | D | best error = [ 1.5659, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:27:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:36 | D | sum error = [ 57.2526, 60.0896, 63.0365, 66.0942, 69.2652] +24-11-19 20:27:36 | D | best error = [ 1.5659, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:27:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:36 | D | sum error = [ 72.5503, 75.9482, 79.4628, 83.0941, 86.8521] +24-11-19 20:27:36 | D | best error = [ 1.5659, 1.5659, 1.5659, 1.5659, 1.5659] +24-11-19 20:27:36 | D | + error = [1.5659] +24-11-19 20:27:36 | D | - Quantizing model.layers.13.self_attn.q_proj.weight +24-11-19 20:27:37 | D | - Quantizing model.layers.13.self_attn.k_proj.weight +24-11-19 20:27:38 | D | - Quantizing model.layers.13.self_attn.v_proj.weight +24-11-19 20:27:38 | D | - Quantizing model.layers.13.self_attn.o_proj.weight +24-11-19 20:27:39 | D | - Quantizing model.layers.13.mlp.up_proj.weight +24-11-19 20:27:40 | D | - Quantizing model.layers.13.mlp.gate_proj.weight +24-11-19 20:27:41 | D | - Quantizing model.layers.13.mlp.down_proj.weight +24-11-19 20:27:50 | D | - Quantizing layer model.layers.14 +24-11-19 20:27:50 | D | - Calibrating model.layers.14.self_attn.q_proj.weight +24-11-19 20:27:50 | D | + w: sint8 +24-11-19 20:27:50 | D | + x: None +24-11-19 20:27:50 | D | + y: None +24-11-19 20:27:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:27:50 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:27:50 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:27:50 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:27:50 | D | - range ratio = [ 1.0000] +24-11-19 20:27:50 | D | sum error = [ 11.6680] +24-11-19 20:27:50 | D | best error = [ 11.6680] +24-11-19 20:28:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:03 | D | sum error = [ 11.8323, 11.9171, 11.7629, 11.8936, 12.1663] +24-11-19 20:28:03 | D | best error = [ 11.6680, 11.6680, 11.6680, 11.6680, 11.6680] +24-11-19 20:28:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:03 | D | sum error = [ 12.2779, 12.7035, 13.1483, 13.8250, 14.8139] +24-11-19 20:28:03 | D | best error = [ 11.6680, 11.6680, 11.6680, 11.6680, 11.6680] +24-11-19 20:28:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:03 | D | sum error = [ 15.3823, 16.5934, 17.8558, 18.8337, 20.4023] +24-11-19 20:28:03 | D | best error = [ 11.6680, 11.6680, 11.6680, 11.6680, 11.6680] +24-11-19 20:28:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:03 | D | sum error = [ 21.6573, 23.5156, 25.3802, 26.9556, 29.2265] +24-11-19 20:28:03 | D | best error = [ 11.6680, 11.6680, 11.6680, 11.6680, 11.6680] +24-11-19 20:28:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:03 | D | sum error = [ 31.5766, 33.9668, 36.8614, 39.6624, 42.7093] +24-11-19 20:28:03 | D | best error = [ 11.6680, 11.6680, 11.6680, 11.6680, 11.6680] +24-11-19 20:28:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:03 | D | sum error = [ 46.1142, 50.1057, 53.7878, 57.6502, 62.0854] +24-11-19 20:28:03 | D | best error = [ 11.6680, 11.6680, 11.6680, 11.6680, 11.6680] +24-11-19 20:28:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:03 | D | sum error = [ 66.6185, 71.4583, 76.9771, 83.0708, 88.8693] +24-11-19 20:28:03 | D | best error = [ 11.6680, 11.6680, 11.6680, 11.6680, 11.6680] +24-11-19 20:28:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:03 | D | sum error = [ 95.4259, 102.0089, 109.9460, 117.9585, 126.8040] +24-11-19 20:28:03 | D | best error = [ 11.6680, 11.6680, 11.6680, 11.6680, 11.6680] +24-11-19 20:28:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:03 | D | sum error = [ 135.7852, 146.0941, 156.3726, 167.7679, 180.2882] +24-11-19 20:28:03 | D | best error = [ 11.6680, 11.6680, 11.6680, 11.6680, 11.6680] +24-11-19 20:28:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:03 | D | sum error = [ 193.0367, 207.0666, 222.0488, 238.4885, 255.8523] +24-11-19 20:28:03 | D | best error = [ 11.6680, 11.6680, 11.6680, 11.6680, 11.6680] +24-11-19 20:28:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:03 | D | sum error = [ 274.1471, 294.3906, 315.5125, 338.3499, 362.5401] +24-11-19 20:28:03 | D | best error = [ 11.6680, 11.6680, 11.6680, 11.6680, 11.6680] +24-11-19 20:28:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:03 | D | sum error = [ 388.5667, 416.7283, 446.4069, 477.9749, 511.9507] +24-11-19 20:28:03 | D | best error = [ 11.6680, 11.6680, 11.6680, 11.6680, 11.6680] +24-11-19 20:28:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:03 | D | sum error = [ 547.8814, 586.3588, 627.4584, 671.3585, 718.4801] +24-11-19 20:28:03 | D | best error = [ 11.6680, 11.6680, 11.6680, 11.6680, 11.6680] +24-11-19 20:28:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:03 | D | sum error = [ 768.5984, 822.3811, 879.4867, 940.3010, 1005.4989] +24-11-19 20:28:03 | D | best error = [ 11.6680, 11.6680, 11.6680, 11.6680, 11.6680] +24-11-19 20:28:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:03 | D | sum error = [ 1074.8448, 1148.1499, 1226.0424, 1308.3505, 1394.4052] +24-11-19 20:28:03 | D | best error = [ 11.6680, 11.6680, 11.6680, 11.6680, 11.6680] +24-11-19 20:28:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:03 | D | sum error = [ 1485.1855, 1579.4607, 1676.8646, 1777.0326, 1878.9536] +24-11-19 20:28:03 | D | best error = [ 11.6680, 11.6680, 11.6680, 11.6680, 11.6680] +24-11-19 20:28:03 | D | + error = [11.6680] +24-11-19 20:28:03 | D | - Calibrating model.layers.14.self_attn.k_proj.weight +24-11-19 20:28:03 | D | + w: sint8 +24-11-19 20:28:03 | D | + x: None +24-11-19 20:28:03 | D | + y: None +24-11-19 20:28:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:28:03 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:28:04 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:28:04 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:28:04 | D | - range ratio = [ 1.0000] +24-11-19 20:28:04 | D | sum error = [ 12.9358] +24-11-19 20:28:04 | D | best error = [ 12.9358] +24-11-19 20:28:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:17 | D | sum error = [ 11.5957, 11.5367, 11.5857, 12.5477, 12.5895] +24-11-19 20:28:17 | D | best error = [ 11.5957, 11.5367, 11.5367, 11.5367, 11.5367] +24-11-19 20:28:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:17 | D | sum error = [ 12.3411, 13.4979, 13.9190, 14.9271, 15.2167] +24-11-19 20:28:17 | D | best error = [ 11.5367, 11.5367, 11.5367, 11.5367, 11.5367] +24-11-19 20:28:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:17 | D | sum error = [ 16.0546, 16.9225, 18.2861, 19.2671, 20.2049] +24-11-19 20:28:17 | D | best error = [ 11.5367, 11.5367, 11.5367, 11.5367, 11.5367] +24-11-19 20:28:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:17 | D | sum error = [ 22.9107, 23.9697, 25.8938, 27.8828, 29.4411] +24-11-19 20:28:17 | D | best error = [ 11.5367, 11.5367, 11.5367, 11.5367, 11.5367] +24-11-19 20:28:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:17 | D | sum error = [ 32.6059, 35.0675, 37.5559, 40.9471, 44.3374] +24-11-19 20:28:17 | D | best error = [ 11.5367, 11.5367, 11.5367, 11.5367, 11.5367] +24-11-19 20:28:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:17 | D | sum error = [ 47.6739, 51.1029, 55.9793, 60.7088, 66.2132] +24-11-19 20:28:17 | D | best error = [ 11.5367, 11.5367, 11.5367, 11.5367, 11.5367] +24-11-19 20:28:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:17 | D | sum error = [ 70.6058, 76.2997, 82.1278, 89.4299, 96.4789] +24-11-19 20:28:17 | D | best error = [ 11.5367, 11.5367, 11.5367, 11.5367, 11.5367] +24-11-19 20:28:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:17 | D | sum error = [ 103.6404, 111.2120, 120.9344, 128.5949, 138.7163] +24-11-19 20:28:17 | D | best error = [ 11.5367, 11.5367, 11.5367, 11.5367, 11.5367] +24-11-19 20:28:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:17 | D | sum error = [ 148.3909, 159.7117, 171.7983, 183.1924, 196.3190] +24-11-19 20:28:17 | D | best error = [ 11.5367, 11.5367, 11.5367, 11.5367, 11.5367] +24-11-19 20:28:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:17 | D | sum error = [ 210.0665, 225.4890, 241.6381, 257.4496, 276.3125] +24-11-19 20:28:17 | D | best error = [ 11.5367, 11.5367, 11.5367, 11.5367, 11.5367] +24-11-19 20:28:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:17 | D | sum error = [ 294.3982, 315.3748, 336.7530, 360.5708, 383.4054] +24-11-19 20:28:17 | D | best error = [ 11.5367, 11.5367, 11.5367, 11.5367, 11.5367] +24-11-19 20:28:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:17 | D | sum error = [ 409.2043, 436.9751, 466.4680, 497.3465, 529.9768] +24-11-19 20:28:17 | D | best error = [ 11.5367, 11.5367, 11.5367, 11.5367, 11.5367] +24-11-19 20:28:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:17 | D | sum error = [ 564.5986, 601.6307, 641.1886, 683.7361, 728.6858] +24-11-19 20:28:17 | D | best error = [ 11.5367, 11.5367, 11.5367, 11.5367, 11.5367] +24-11-19 20:28:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:17 | D | sum error = [ 775.4637, 826.5535, 880.9275, 938.4063, 1000.7065] +24-11-19 20:28:17 | D | best error = [ 11.5367, 11.5367, 11.5367, 11.5367, 11.5367] +24-11-19 20:28:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:17 | D | sum error = [ 1067.5185, 1138.7654, 1213.8120, 1293.6021, 1377.5218] +24-11-19 20:28:17 | D | best error = [ 11.5367, 11.5367, 11.5367, 11.5367, 11.5367] +24-11-19 20:28:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:17 | D | sum error = [ 1465.9874, 1558.8640, 1655.7301, 1755.8059, 1858.7223] +24-11-19 20:28:17 | D | best error = [ 11.5367, 11.5367, 11.5367, 11.5367, 11.5367] +24-11-19 20:28:17 | D | + error = [11.5367] +24-11-19 20:28:17 | D | - Calibrating model.layers.14.self_attn.v_proj.weight +24-11-19 20:28:17 | D | + w: sint8 +24-11-19 20:28:17 | D | + x: None +24-11-19 20:28:17 | D | + y: None +24-11-19 20:28:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:17 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:28:17 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:28:17 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:28:17 | D | - range ratio = [ 1.0000] +24-11-19 20:28:17 | D | sum error = [ 4.9189] +24-11-19 20:28:17 | D | best error = [ 4.9189] +24-11-19 20:28:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:18 | D | sum error = [ 4.9057, 4.8907, 4.9002, 4.9577, 5.0519] +24-11-19 20:28:18 | D | best error = [ 4.5777, 4.4426, 4.3759, 4.3347, 4.3181] +24-11-19 20:28:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:18 | D | sum error = [ 5.1867, 5.3672, 5.5956, 5.8633, 6.1739] +24-11-19 20:28:18 | D | best error = [ 4.3089, 4.3036, 4.3027, 4.3024, 4.3024] +24-11-19 20:28:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:18 | D | sum error = [ 6.5323, 6.9029, 7.3726, 7.8693, 8.4093] +24-11-19 20:28:18 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 20:28:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:18 | D | sum error = [ 8.9963, 9.6657, 10.3796, 11.0901, 11.9039] +24-11-19 20:28:18 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 20:28:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:18 | D | sum error = [ 12.7701, 13.6650, 14.6255, 15.6658, 16.7343] +24-11-19 20:28:18 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 20:28:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:18 | D | sum error = [ 17.8812, 19.0733, 20.3612, 21.7233, 23.1687] +24-11-19 20:28:18 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 20:28:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:18 | D | sum error = [ 24.6603, 26.2372, 27.9261, 29.6772, 31.5418] +24-11-19 20:28:18 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 20:28:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:18 | D | sum error = [ 33.5087, 35.5828, 37.7307, 40.0058, 42.4119] +24-11-19 20:28:18 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 20:28:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:18 | D | sum error = [ 44.9360, 47.5717, 50.3349, 53.2531, 56.2964] +24-11-19 20:28:18 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 20:28:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:18 | D | sum error = [ 59.5063, 62.8400, 66.3431, 70.0113, 73.8500] +24-11-19 20:28:18 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 20:28:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:18 | D | sum error = [ 77.8688, 82.0377, 86.4084, 90.9752, 95.7309] +24-11-19 20:28:18 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 20:28:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:18 | D | sum error = [ 100.6909, 105.8400, 111.2202, 116.8011, 122.6461] +24-11-19 20:28:18 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 20:28:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:18 | D | sum error = [ 128.6983, 135.0120, 141.5696, 148.3808, 155.4549] +24-11-19 20:28:18 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 20:28:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:18 | D | sum error = [ 162.7851, 170.3781, 178.2494, 186.4119, 194.8492] +24-11-19 20:28:18 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 20:28:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:18 | D | sum error = [ 203.5769, 212.6122, 221.9468, 231.5968, 241.5493] +24-11-19 20:28:18 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 20:28:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:18 | D | sum error = [ 251.8134, 262.4035, 273.3104, 284.5462, 296.0957] +24-11-19 20:28:18 | D | best error = [ 4.3024, 4.3024, 4.3024, 4.3024, 4.3024] +24-11-19 20:28:18 | D | + error = [4.3024] +24-11-19 20:28:18 | D | - Calibrating model.layers.14.self_attn.o_proj.weight +24-11-19 20:28:18 | D | + w: sint8 +24-11-19 20:28:18 | D | + x: None +24-11-19 20:28:18 | D | + y: None +24-11-19 20:28:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:18 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:28:18 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:28:18 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:28:18 | D | - range ratio = [ 1.0000] +24-11-19 20:28:18 | D | sum error = [ 1.3102] +24-11-19 20:28:18 | D | best error = [ 1.3102] +24-11-19 20:28:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:19 | D | sum error = [ 1.3044, 1.2959, 1.2962, 1.3011, 1.3103] +24-11-19 20:28:19 | D | best error = [ 1.2224, 1.1802, 1.1547, 1.1378, 1.1248] +24-11-19 20:28:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:19 | D | sum error = [ 1.3367, 1.3619, 1.3960, 1.4453, 1.4987] +24-11-19 20:28:19 | D | best error = [ 1.1172, 1.1120, 1.1089, 1.1065, 1.1050] +24-11-19 20:28:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:19 | D | sum error = [ 1.5668, 1.6429, 1.7279, 1.8185, 1.9254] +24-11-19 20:28:19 | D | best error = [ 1.1039, 1.1035, 1.1031, 1.1026, 1.1024] +24-11-19 20:28:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:19 | D | sum error = [ 2.0443, 2.1692, 2.3100, 2.4576, 2.6242] +24-11-19 20:28:19 | D | best error = [ 1.1023, 1.1021, 1.1020, 1.1019, 1.1018] +24-11-19 20:28:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:19 | D | sum error = [ 2.7950, 2.9770, 3.1742, 3.3851, 3.6100] +24-11-19 20:28:19 | D | best error = [ 1.1018, 1.1017, 1.1017, 1.1017, 1.1017] +24-11-19 20:28:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:19 | D | sum error = [ 3.8471, 4.0990, 4.3643, 4.6529, 4.9518] +24-11-19 20:28:19 | D | best error = [ 1.1017, 1.1017, 1.1017, 1.1017, 1.1017] +24-11-19 20:28:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:19 | D | sum error = [ 5.2619, 5.6010, 5.9539, 6.3208, 6.7114] +24-11-19 20:28:19 | D | best error = [ 1.1017, 1.1017, 1.1017, 1.1017, 1.1017] +24-11-19 20:28:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:19 | D | sum error = [ 7.1275, 7.5576, 8.0106, 8.4853, 8.9973] +24-11-19 20:28:19 | D | best error = [ 1.1017, 1.1017, 1.1017, 1.1017, 1.1017] +24-11-19 20:28:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:19 | D | sum error = [ 9.5189, 10.0792, 10.6641, 11.2815, 11.9293] +24-11-19 20:28:19 | D | best error = [ 1.1017, 1.1017, 1.1017, 1.1017, 1.1017] +24-11-19 20:28:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:19 | D | sum error = [ 12.6073, 13.3204, 14.0714, 14.8522, 15.6750] +24-11-19 20:28:19 | D | best error = [ 1.1017, 1.1017, 1.1017, 1.1017, 1.1017] +24-11-19 20:28:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:19 | D | sum error = [ 16.5312, 17.4303, 18.3705, 19.3510, 20.3737] +24-11-19 20:28:19 | D | best error = [ 1.1017, 1.1017, 1.1017, 1.1017, 1.1017] +24-11-19 20:28:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:19 | D | sum error = [ 21.4405, 22.5518, 23.7098, 24.9149, 26.1738] +24-11-19 20:28:19 | D | best error = [ 1.1017, 1.1017, 1.1017, 1.1017, 1.1017] +24-11-19 20:28:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:19 | D | sum error = [ 27.4840, 28.8527, 30.2698, 31.7456, 33.2805] +24-11-19 20:28:19 | D | best error = [ 1.1017, 1.1017, 1.1017, 1.1017, 1.1017] +24-11-19 20:28:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:19 | D | sum error = [ 34.8727, 36.5235, 38.2377, 40.0143, 41.8576] +24-11-19 20:28:19 | D | best error = [ 1.1017, 1.1017, 1.1017, 1.1017, 1.1017] +24-11-19 20:28:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:19 | D | sum error = [ 43.7701, 45.7502, 47.8042, 49.9325, 52.1371] +24-11-19 20:28:19 | D | best error = [ 1.1017, 1.1017, 1.1017, 1.1017, 1.1017] +24-11-19 20:28:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:19 | D | sum error = [ 54.4185, 56.7781, 59.2195, 61.7431, 64.3491] +24-11-19 20:28:19 | D | best error = [ 1.1017, 1.1017, 1.1017, 1.1017, 1.1017] +24-11-19 20:28:19 | D | + error = [1.1017] +24-11-19 20:28:19 | D | - Calibrating model.layers.14.mlp.up_proj.weight +24-11-19 20:28:19 | D | + w: sint8 +24-11-19 20:28:19 | D | + x: None +24-11-19 20:28:19 | D | + y: None +24-11-19 20:28:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:19 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:28:19 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:28:19 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:28:19 | D | - range ratio = [ 1.0000] +24-11-19 20:28:19 | D | sum error = [ 6.6596] +24-11-19 20:28:19 | D | best error = [ 6.6596] +24-11-19 20:28:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:20 | D | sum error = [ 6.6362, 6.6373, 6.6592, 6.7336, 6.8477] +24-11-19 20:28:20 | D | best error = [ 6.1987, 6.0237, 5.9276, 5.8741, 5.8453] +24-11-19 20:28:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:20 | D | sum error = [ 7.0198, 7.2539, 7.5582, 7.9123, 8.3357] +24-11-19 20:28:20 | D | best error = [ 5.8320, 5.8259, 5.8234, 5.8227, 5.8226] +24-11-19 20:28:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:20 | D | sum error = [ 8.8044, 9.3674, 9.9604, 10.6098, 11.3384] +24-11-19 20:28:20 | D | best error = [ 5.8225, 5.8225, 5.8225, 5.8225, 5.8225] +24-11-19 20:28:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:20 | D | sum error = [ 12.1669, 13.0267, 13.9711, 14.9575, 16.0199] +24-11-19 20:28:20 | D | best error = [ 5.8225, 5.8225, 5.8225, 5.8225, 5.8225] +24-11-19 20:28:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:20 | D | sum error = [ 17.1808, 18.4063, 19.7031, 21.0660, 22.5574] +24-11-19 20:28:20 | D | best error = [ 5.8225, 5.8225, 5.8225, 5.8225, 5.8225] +24-11-19 20:28:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:20 | D | sum error = [ 24.1128, 25.7589, 27.5031, 29.3537, 31.2905] +24-11-19 20:28:20 | D | best error = [ 5.8225, 5.8225, 5.8225, 5.8225, 5.8225] +24-11-19 20:28:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:20 | D | sum error = [ 33.3500, 35.5211, 37.7917, 40.2090, 42.7382] +24-11-19 20:28:20 | D | best error = [ 5.8225, 5.8225, 5.8225, 5.8225, 5.8225] +24-11-19 20:28:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:20 | D | sum error = [ 45.4177, 48.2401, 51.2008, 54.3163, 57.6064] +24-11-19 20:28:20 | D | best error = [ 5.8225, 5.8225, 5.8225, 5.8225, 5.8225] +24-11-19 20:28:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:20 | D | sum error = [ 61.0387, 64.6445, 68.4395, 72.3995, 76.5932] +24-11-19 20:28:20 | D | best error = [ 5.8225, 5.8225, 5.8225, 5.8225, 5.8225] +24-11-19 20:28:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:20 | D | sum error = [ 80.9716, 85.5473, 90.3645, 95.4042, 100.6711] +24-11-19 20:28:20 | D | best error = [ 5.8225, 5.8225, 5.8225, 5.8225, 5.8225] +24-11-19 20:28:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:20 | D | sum error = [ 106.1788, 111.9676, 117.9711, 124.2829, 130.8637] +24-11-19 20:28:20 | D | best error = [ 5.8225, 5.8225, 5.8225, 5.8225, 5.8225] +24-11-19 20:28:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:20 | D | sum error = [ 137.7130, 144.8523, 152.3097, 160.0667, 168.1456] +24-11-19 20:28:20 | D | best error = [ 5.8225, 5.8225, 5.8225, 5.8225, 5.8225] +24-11-19 20:28:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:20 | D | sum error = [ 176.5555, 185.2825, 194.3715, 203.7967, 213.5961] +24-11-19 20:28:20 | D | best error = [ 5.8225, 5.8225, 5.8225, 5.8225, 5.8225] +24-11-19 20:28:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:20 | D | sum error = [ 223.7474, 234.2981, 245.2179, 256.5588, 268.2572] +24-11-19 20:28:20 | D | best error = [ 5.8225, 5.8225, 5.8225, 5.8225, 5.8225] +24-11-19 20:28:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:20 | D | sum error = [ 280.3927, 292.9397, 305.9119, 319.3076, 333.1354] +24-11-19 20:28:20 | D | best error = [ 5.8225, 5.8225, 5.8225, 5.8225, 5.8225] +24-11-19 20:28:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:20 | D | sum error = [ 347.3975, 362.1164, 377.2877, 392.8910, 408.9560] +24-11-19 20:28:20 | D | best error = [ 5.8225, 5.8225, 5.8225, 5.8225, 5.8225] +24-11-19 20:28:20 | D | + error = [5.8225] +24-11-19 20:28:20 | D | - Calibrating model.layers.14.mlp.gate_proj.weight +24-11-19 20:28:20 | D | + w: sint8 +24-11-19 20:28:20 | D | + x: None +24-11-19 20:28:20 | D | + y: None +24-11-19 20:28:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:20 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:28:20 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:28:20 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:28:20 | D | - range ratio = [ 1.0000] +24-11-19 20:28:20 | D | sum error = [ 6.8368] +24-11-19 20:28:20 | D | best error = [ 6.8368] +24-11-19 20:28:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:21 | D | sum error = [ 6.7901, 6.7881, 6.8270, 6.9000, 7.0230] +24-11-19 20:28:21 | D | best error = [ 6.3567, 6.1791, 6.0815, 6.0271, 5.9984] +24-11-19 20:28:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:21 | D | sum error = [ 7.1996, 7.4513, 7.7564, 8.1143, 8.5344] +24-11-19 20:28:21 | D | best error = [ 5.9833, 5.9763, 5.9737, 5.9730, 5.9729] +24-11-19 20:28:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:21 | D | sum error = [ 9.0378, 9.5979, 10.2481, 10.9296, 11.6898] +24-11-19 20:28:21 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:28:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:21 | D | sum error = [ 12.5096, 13.4142, 14.3821, 15.4558, 16.5636] +24-11-19 20:28:21 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:28:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:21 | D | sum error = [ 17.7470, 19.0362, 20.4058, 21.8784, 23.4325] +24-11-19 20:28:21 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:28:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:21 | D | sum error = [ 25.0956, 26.8393, 28.6964, 30.6774, 32.7713] +24-11-19 20:28:21 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:28:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:21 | D | sum error = [ 34.9903, 37.3386, 39.8335, 42.4631, 45.2569] +24-11-19 20:28:21 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:28:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:21 | D | sum error = [ 48.2022, 51.3380, 54.6386, 58.1280, 61.8089] +24-11-19 20:28:21 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:28:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:21 | D | sum error = [ 65.7208, 69.8091, 74.1792, 78.7961, 83.6387] +24-11-19 20:28:21 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:28:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:21 | D | sum error = [ 88.7691, 94.1964, 99.9157, 105.9477, 112.2891] +24-11-19 20:28:21 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:28:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:21 | D | sum error = [ 118.9683, 126.0239, 133.4157, 141.2138, 149.3958] +24-11-19 20:28:21 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:28:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:21 | D | sum error = [ 158.0034, 167.0424, 176.5295, 186.4825, 196.9480] +24-11-19 20:28:21 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:28:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:21 | D | sum error = [ 207.9048, 219.3762, 231.3973, 243.9690, 257.0934] +24-11-19 20:28:21 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:28:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:21 | D | sum error = [ 270.8094, 285.1208, 300.0443, 315.5934, 331.7658] +24-11-19 20:28:21 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:28:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:21 | D | sum error = [ 348.5918, 366.0329, 384.1473, 402.9243, 422.3845] +24-11-19 20:28:21 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:28:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:21 | D | sum error = [ 442.5131, 463.3495, 484.8291, 506.9929, 529.8649] +24-11-19 20:28:21 | D | best error = [ 5.9729, 5.9729, 5.9729, 5.9729, 5.9729] +24-11-19 20:28:21 | D | + error = [5.9729] +24-11-19 20:28:21 | D | - Calibrating model.layers.14.mlp.down_proj.weight +24-11-19 20:28:21 | D | + w: sint8 +24-11-19 20:28:21 | D | + x: None +24-11-19 20:28:21 | D | + y: None +24-11-19 20:28:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:21 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:28:21 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:28:21 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:28:21 | D | - range ratio = [ 1.0000] +24-11-19 20:28:21 | D | sum error = [ 1.8796] +24-11-19 20:28:21 | D | best error = [ 1.8796] +24-11-19 20:28:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:22 | D | sum error = [ 1.8615, 1.8488, 1.8398, 1.8361, 1.8358] +24-11-19 20:28:22 | D | best error = [ 1.8151, 1.7824, 1.7604, 1.7439, 1.7318] +24-11-19 20:28:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:22 | D | sum error = [ 1.8432, 1.8534, 1.8778, 1.9068, 1.9519] +24-11-19 20:28:22 | D | best error = [ 1.7220, 1.7151, 1.7099, 1.7069, 1.7047] +24-11-19 20:28:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:22 | D | sum error = [ 1.9972, 2.0592, 2.1349, 2.2234, 2.3195] +24-11-19 20:28:22 | D | best error = [ 1.7032, 1.7024, 1.7017, 1.7012, 1.7010] +24-11-19 20:28:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:22 | D | sum error = [ 2.4354, 2.5619, 2.7040, 2.8625, 3.0343] +24-11-19 20:28:22 | D | best error = [ 1.7010, 1.7009, 1.7008, 1.7008, 1.7008] +24-11-19 20:28:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:22 | D | sum error = [ 3.2250, 3.4346, 3.6598, 3.9029, 4.1666] +24-11-19 20:28:22 | D | best error = [ 1.7007, 1.7007, 1.7007, 1.7007, 1.7007] +24-11-19 20:28:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:22 | D | sum error = [ 4.4473, 4.7494, 5.0746, 5.4197, 5.7951] +24-11-19 20:28:22 | D | best error = [ 1.7007, 1.7007, 1.7007, 1.7007, 1.7007] +24-11-19 20:28:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:22 | D | sum error = [ 6.1909, 6.6070, 7.0577, 7.5353, 8.0408] +24-11-19 20:28:22 | D | best error = [ 1.7007, 1.7007, 1.7007, 1.7007, 1.7007] +24-11-19 20:28:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:22 | D | sum error = [ 8.5779, 9.1521, 9.7578, 10.3954, 11.0733] +24-11-19 20:28:22 | D | best error = [ 1.7007, 1.7007, 1.7007, 1.7007, 1.7007] +24-11-19 20:28:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:22 | D | sum error = [ 11.7884, 12.5485, 13.3482, 14.1970, 15.0888] +24-11-19 20:28:22 | D | best error = [ 1.7007, 1.7007, 1.7007, 1.7007, 1.7007] +24-11-19 20:28:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:22 | D | sum error = [ 16.0277, 17.0198, 18.0662, 19.1654, 20.3243] +24-11-19 20:28:22 | D | best error = [ 1.7007, 1.7007, 1.7007, 1.7007, 1.7007] +24-11-19 20:28:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:22 | D | sum error = [ 21.5409, 22.8204, 24.1646, 25.5786, 27.0578] +24-11-19 20:28:22 | D | best error = [ 1.7007, 1.7007, 1.7007, 1.7007, 1.7007] +24-11-19 20:28:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:22 | D | sum error = [ 28.6090, 30.2361, 31.9433, 33.7265, 35.5909] +24-11-19 20:28:22 | D | best error = [ 1.7007, 1.7007, 1.7007, 1.7007, 1.7007] +24-11-19 20:28:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:22 | D | sum error = [ 37.5427, 39.5780, 41.7055, 43.9224, 46.2344] +24-11-19 20:28:22 | D | best error = [ 1.7007, 1.7007, 1.7007, 1.7007, 1.7007] +24-11-19 20:28:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:22 | D | sum error = [ 48.6479, 51.1578, 53.7710, 56.4945, 59.3174] +24-11-19 20:28:22 | D | best error = [ 1.7007, 1.7007, 1.7007, 1.7007, 1.7007] +24-11-19 20:28:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:22 | D | sum error = [ 62.2543, 65.3025, 68.4666, 71.7465, 75.1477] +24-11-19 20:28:22 | D | best error = [ 1.7007, 1.7007, 1.7007, 1.7007, 1.7007] +24-11-19 20:28:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:22 | D | sum error = [ 78.6713, 82.3154, 86.0840, 89.9814, 94.0054] +24-11-19 20:28:22 | D | best error = [ 1.7007, 1.7007, 1.7007, 1.7007, 1.7007] +24-11-19 20:28:22 | D | + error = [1.7007] +24-11-19 20:28:22 | D | - Quantizing model.layers.14.self_attn.q_proj.weight +24-11-19 20:28:23 | D | - Quantizing model.layers.14.self_attn.k_proj.weight +24-11-19 20:28:24 | D | - Quantizing model.layers.14.self_attn.v_proj.weight +24-11-19 20:28:25 | D | - Quantizing model.layers.14.self_attn.o_proj.weight +24-11-19 20:28:26 | D | - Quantizing model.layers.14.mlp.up_proj.weight +24-11-19 20:28:26 | D | - Quantizing model.layers.14.mlp.gate_proj.weight +24-11-19 20:28:27 | D | - Quantizing model.layers.14.mlp.down_proj.weight +24-11-19 20:28:35 | D | - Quantizing layer model.layers.15 +24-11-19 20:28:35 | D | - Calibrating model.layers.15.self_attn.q_proj.weight +24-11-19 20:28:35 | D | + w: sint8 +24-11-19 20:28:35 | D | + x: None +24-11-19 20:28:35 | D | + y: None +24-11-19 20:28:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:28:35 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:28:35 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:28:36 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:28:36 | D | - range ratio = [ 1.0000] +24-11-19 20:28:36 | D | sum error = [ 11.1471] +24-11-19 20:28:36 | D | best error = [ 11.1471] +24-11-19 20:28:49 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:49 | D | sum error = [ 11.1056, 10.9997, 11.3483, 11.2537, 11.6113] +24-11-19 20:28:49 | D | best error = [ 11.1056, 10.9997, 10.9997, 10.9997, 10.9997] +24-11-19 20:28:49 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:49 | D | sum error = [ 12.0493, 12.2840, 12.6707, 13.3325, 14.7476] +24-11-19 20:28:49 | D | best error = [ 10.9997, 10.9997, 10.9997, 10.9997, 10.9997] +24-11-19 20:28:49 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:49 | D | sum error = [ 14.9536, 15.9276, 17.3635, 18.4313, 19.7750] +24-11-19 20:28:49 | D | best error = [ 10.9997, 10.9997, 10.9997, 10.9997, 10.9997] +24-11-19 20:28:49 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:49 | D | sum error = [ 21.0111, 22.5916, 24.5933, 26.6021, 28.0787] +24-11-19 20:28:49 | D | best error = [ 10.9997, 10.9997, 10.9997, 10.9997, 10.9997] +24-11-19 20:28:49 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:49 | D | sum error = [ 30.2382, 32.8558, 35.6960, 38.3181, 41.2664] +24-11-19 20:28:49 | D | best error = [ 10.9997, 10.9997, 10.9997, 10.9997, 10.9997] +24-11-19 20:28:49 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:49 | D | sum error = [ 44.4568, 47.7576, 51.4747, 55.4300, 59.9922] +24-11-19 20:28:49 | D | best error = [ 10.9997, 10.9997, 10.9997, 10.9997, 10.9997] +24-11-19 20:28:49 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:49 | D | sum error = [ 64.4491, 69.6413, 75.2159, 80.8153, 86.9832] +24-11-19 20:28:49 | D | best error = [ 10.9997, 10.9997, 10.9997, 10.9997, 10.9997] +24-11-19 20:28:49 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:49 | D | sum error = [ 93.8755, 101.1573, 108.6408, 116.9211, 125.9206] +24-11-19 20:28:49 | D | best error = [ 10.9997, 10.9997, 10.9997, 10.9997, 10.9997] +24-11-19 20:28:49 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:49 | D | sum error = [ 135.5182, 145.8368, 156.7902, 168.7988, 181.6411] +24-11-19 20:28:49 | D | best error = [ 10.9997, 10.9997, 10.9997, 10.9997, 10.9997] +24-11-19 20:28:49 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:49 | D | sum error = [ 195.5007, 209.9713, 226.1164, 243.0849, 261.7722] +24-11-19 20:28:49 | D | best error = [ 10.9997, 10.9997, 10.9997, 10.9997, 10.9997] +24-11-19 20:28:49 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:49 | D | sum error = [ 281.1749, 301.8730, 324.4693, 348.1811, 373.5727] +24-11-19 20:28:49 | D | best error = [ 10.9997, 10.9997, 10.9997, 10.9997, 10.9997] +24-11-19 20:28:49 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:49 | D | sum error = [ 401.2969, 430.7209, 462.0546, 495.9829, 532.2929] +24-11-19 20:28:49 | D | best error = [ 10.9997, 10.9997, 10.9997, 10.9997, 10.9997] +24-11-19 20:28:49 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:49 | D | sum error = [ 571.0567, 612.9328, 658.2766, 706.4396, 757.8200] +24-11-19 20:28:49 | D | best error = [ 10.9997, 10.9997, 10.9997, 10.9997, 10.9997] +24-11-19 20:28:49 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:49 | D | sum error = [ 812.8007, 871.8597, 935.2354, 1002.0949, 1074.4500] +24-11-19 20:28:49 | D | best error = [ 10.9997, 10.9997, 10.9997, 10.9997, 10.9997] +24-11-19 20:28:49 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:49 | D | sum error = [ 1150.0332, 1230.9414, 1316.1799, 1406.4555, 1501.2591] +24-11-19 20:28:49 | D | best error = [ 10.9997, 10.9997, 10.9997, 10.9997, 10.9997] +24-11-19 20:28:49 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:49 | D | sum error = [ 1600.4599, 1704.6244, 1812.5270, 1923.4914, 2038.0559] +24-11-19 20:28:49 | D | best error = [ 10.9997, 10.9997, 10.9997, 10.9997, 10.9997] +24-11-19 20:28:49 | D | + error = [10.9997] +24-11-19 20:28:49 | D | - Calibrating model.layers.15.self_attn.k_proj.weight +24-11-19 20:28:49 | D | + w: sint8 +24-11-19 20:28:49 | D | + x: None +24-11-19 20:28:49 | D | + y: None +24-11-19 20:28:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:28:49 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:28:49 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:28:49 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:28:50 | D | - range ratio = [ 1.0000] +24-11-19 20:28:50 | D | sum error = [ 12.1152] +24-11-19 20:28:50 | D | best error = [ 12.1152] +24-11-19 20:29:02 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:02 | D | sum error = [ 12.0194, 12.1105, 11.5910, 12.0440, 11.7950] +24-11-19 20:29:02 | D | best error = [ 12.0194, 12.0194, 11.5910, 11.5910, 11.5910] +24-11-19 20:29:02 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:02 | D | sum error = [ 12.2611, 12.7665, 14.1928, 14.0892, 14.8187] +24-11-19 20:29:02 | D | best error = [ 11.5910, 11.5910, 11.5910, 11.5910, 11.5910] +24-11-19 20:29:02 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:02 | D | sum error = [ 15.6360, 16.5736, 17.2128, 19.1262, 20.2484] +24-11-19 20:29:02 | D | best error = [ 11.5910, 11.5910, 11.5910, 11.5910, 11.5910] +24-11-19 20:29:02 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:02 | D | sum error = [ 22.4900, 24.2732, 25.7017, 28.6102, 29.6399] +24-11-19 20:29:02 | D | best error = [ 11.5910, 11.5910, 11.5910, 11.5910, 11.5910] +24-11-19 20:29:02 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:02 | D | sum error = [ 32.9430, 34.8748, 37.7702, 40.6030, 43.5626] +24-11-19 20:29:02 | D | best error = [ 11.5910, 11.5910, 11.5910, 11.5910, 11.5910] +24-11-19 20:29:02 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:02 | D | sum error = [ 46.8633, 50.8080, 54.4619, 60.0160, 62.4667] +24-11-19 20:29:02 | D | best error = [ 11.5910, 11.5910, 11.5910, 11.5910, 11.5910] +24-11-19 20:29:02 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:02 | D | sum error = [ 68.5576, 74.1836, 78.6394, 84.5200, 91.1367] +24-11-19 20:29:02 | D | best error = [ 11.5910, 11.5910, 11.5910, 11.5910, 11.5910] +24-11-19 20:29:02 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:02 | D | sum error = [ 99.0543, 106.9258, 114.7609, 123.6170, 132.0884] +24-11-19 20:29:02 | D | best error = [ 11.5910, 11.5910, 11.5910, 11.5910, 11.5910] +24-11-19 20:29:02 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:02 | D | sum error = [ 140.9293, 150.8296, 162.9393, 174.9426, 188.8026] +24-11-19 20:29:02 | D | best error = [ 11.5910, 11.5910, 11.5910, 11.5910, 11.5910] +24-11-19 20:29:02 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:02 | D | sum error = [ 203.2244, 218.8942, 236.2513, 254.8091, 275.5018] +24-11-19 20:29:02 | D | best error = [ 11.5910, 11.5910, 11.5910, 11.5910, 11.5910] +24-11-19 20:29:02 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:02 | D | sum error = [ 296.4330, 319.5250, 343.6070, 369.1426, 397.6754] +24-11-19 20:29:02 | D | best error = [ 11.5910, 11.5910, 11.5910, 11.5910, 11.5910] +24-11-19 20:29:02 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:02 | D | sum error = [ 427.2278, 459.1235, 493.0421, 529.7366, 569.2402] +24-11-19 20:29:02 | D | best error = [ 11.5910, 11.5910, 11.5910, 11.5910, 11.5910] +24-11-19 20:29:02 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:02 | D | sum error = [ 611.2453, 656.6112, 704.7331, 757.9103, 814.3537] +24-11-19 20:29:02 | D | best error = [ 11.5910, 11.5910, 11.5910, 11.5910, 11.5910] +24-11-19 20:29:02 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:02 | D | sum error = [ 873.8661, 936.6415, 1002.7299, 1072.9485, 1145.7184] +24-11-19 20:29:02 | D | best error = [ 11.5910, 11.5910, 11.5910, 11.5910, 11.5910] +24-11-19 20:29:02 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:02 | D | sum error = [ 1223.6181, 1305.3240, 1390.7804, 1479.5673, 1573.6055] +24-11-19 20:29:02 | D | best error = [ 11.5910, 11.5910, 11.5910, 11.5910, 11.5910] +24-11-19 20:29:02 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:02 | D | sum error = [ 1671.1813, 1772.5943, 1877.6592, 1985.4264, 2095.7583] +24-11-19 20:29:02 | D | best error = [ 11.5910, 11.5910, 11.5910, 11.5910, 11.5910] +24-11-19 20:29:02 | D | + error = [11.5910] +24-11-19 20:29:02 | D | - Calibrating model.layers.15.self_attn.v_proj.weight +24-11-19 20:29:02 | D | + w: sint8 +24-11-19 20:29:02 | D | + x: None +24-11-19 20:29:02 | D | + y: None +24-11-19 20:29:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:02 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:29:02 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:29:03 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:29:03 | D | - range ratio = [ 1.0000] +24-11-19 20:29:03 | D | sum error = [ 5.0147] +24-11-19 20:29:03 | D | best error = [ 5.0147] +24-11-19 20:29:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:03 | D | sum error = [ 4.9667, 4.9391, 4.9746, 5.0358, 5.1365] +24-11-19 20:29:03 | D | best error = [ 4.6546, 4.5191, 4.4471, 4.4084, 4.3890] +24-11-19 20:29:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:03 | D | sum error = [ 5.2450, 5.4041, 5.6159, 5.8912, 6.2292] +24-11-19 20:29:03 | D | best error = [ 4.3790, 4.3751, 4.3737, 4.3734, 4.3733] +24-11-19 20:29:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:03 | D | sum error = [ 6.5701, 6.9728, 7.4193, 7.9130, 8.4606] +24-11-19 20:29:03 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:29:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:03 | D | sum error = [ 9.0725, 9.7041, 10.4123, 11.1582, 11.9755] +24-11-19 20:29:03 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:29:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:03 | D | sum error = [ 12.8112, 13.7265, 14.6954, 15.7519, 16.8181] +24-11-19 20:29:03 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:29:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:03 | D | sum error = [ 17.9801, 19.2315, 20.5211, 21.8915, 23.3511] +24-11-19 20:29:03 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:29:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:03 | D | sum error = [ 24.8865, 26.4814, 28.1891, 29.9749, 31.8839] +24-11-19 20:29:03 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:29:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:03 | D | sum error = [ 33.8861, 35.9518, 38.1690, 40.4732, 42.8973] +24-11-19 20:29:03 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:29:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:03 | D | sum error = [ 45.4744, 48.1642, 50.9811, 53.9234, 57.0231] +24-11-19 20:29:03 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:29:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:03 | D | sum error = [ 60.2679, 63.6888, 67.2312, 70.9743, 74.8775] +24-11-19 20:29:03 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:29:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:03 | D | sum error = [ 78.9438, 83.2033, 87.6576, 92.3030, 97.1618] +24-11-19 20:29:03 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:29:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:03 | D | sum error = [ 102.2366, 107.5154, 113.0442, 118.7785, 124.7605] +24-11-19 20:29:03 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:29:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:03 | D | sum error = [ 130.9771, 137.4403, 144.1708, 151.1561, 158.4108] +24-11-19 20:29:03 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:29:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:03 | D | sum error = [ 165.9124, 173.6918, 181.7503, 190.1069, 198.7718] +24-11-19 20:29:03 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:29:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:03 | D | sum error = [ 207.7260, 216.9802, 226.5492, 236.4412, 246.6388] +24-11-19 20:29:03 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:29:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:03 | D | sum error = [ 257.1562, 268.0016, 279.1563, 290.6490, 302.4740] +24-11-19 20:29:03 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:29:03 | D | + error = [4.3733] +24-11-19 20:29:03 | D | - Calibrating model.layers.15.self_attn.o_proj.weight +24-11-19 20:29:03 | D | + w: sint8 +24-11-19 20:29:03 | D | + x: None +24-11-19 20:29:03 | D | + y: None +24-11-19 20:29:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:03 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:29:03 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:29:03 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:29:03 | D | - range ratio = [ 1.0000] +24-11-19 20:29:03 | D | sum error = [ 1.4542] +24-11-19 20:29:03 | D | best error = [ 1.4542] +24-11-19 20:29:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:04 | D | sum error = [ 1.4388, 1.4300, 1.4265, 1.4340, 1.4417] +24-11-19 20:29:04 | D | best error = [ 1.3636, 1.3224, 1.2956, 1.2785, 1.2661] +24-11-19 20:29:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:04 | D | sum error = [ 1.4527, 1.4828, 1.5147, 1.5567, 1.6122] +24-11-19 20:29:04 | D | best error = [ 1.2569, 1.2506, 1.2464, 1.2429, 1.2410] +24-11-19 20:29:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:04 | D | sum error = [ 1.6725, 1.7409, 1.8272, 1.9215, 2.0301] +24-11-19 20:29:04 | D | best error = [ 1.2395, 1.2386, 1.2380, 1.2375, 1.2370] +24-11-19 20:29:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:04 | D | sum error = [ 2.1461, 2.2763, 2.4126, 2.5629, 2.7308] +24-11-19 20:29:04 | D | best error = [ 1.2367, 1.2365, 1.2364, 1.2364, 1.2363] +24-11-19 20:29:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:04 | D | sum error = [ 2.9063, 3.0972, 3.3066, 3.5222, 3.7580] +24-11-19 20:29:04 | D | best error = [ 1.2363, 1.2363, 1.2362, 1.2362, 1.2362] +24-11-19 20:29:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:04 | D | sum error = [ 4.0051, 4.2710, 4.5543, 4.8542, 5.1690] +24-11-19 20:29:04 | D | best error = [ 1.2362, 1.2362, 1.2362, 1.2362, 1.2362] +24-11-19 20:29:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:04 | D | sum error = [ 5.5023, 5.8562, 6.2331, 6.6257, 7.0422] +24-11-19 20:29:04 | D | best error = [ 1.2362, 1.2362, 1.2362, 1.2362, 1.2362] +24-11-19 20:29:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:04 | D | sum error = [ 7.4891, 7.9556, 8.4456, 8.9649, 9.5164] +24-11-19 20:29:04 | D | best error = [ 1.2362, 1.2362, 1.2362, 1.2362, 1.2362] +24-11-19 20:29:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:04 | D | sum error = [ 10.0912, 10.7032, 11.3386, 12.0126, 12.7220] +24-11-19 20:29:04 | D | best error = [ 1.2362, 1.2362, 1.2362, 1.2362, 1.2362] +24-11-19 20:29:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:04 | D | sum error = [ 13.4728, 14.2548, 15.0776, 15.9403, 16.8467] +24-11-19 20:29:04 | D | best error = [ 1.2362, 1.2362, 1.2362, 1.2362, 1.2362] +24-11-19 20:29:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:04 | D | sum error = [ 17.7968, 18.7949, 19.8325, 20.9216, 22.0591] +24-11-19 20:29:04 | D | best error = [ 1.2362, 1.2362, 1.2362, 1.2362, 1.2362] +24-11-19 20:29:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:04 | D | sum error = [ 23.2512, 24.4998, 25.7964, 27.1544, 28.5737] +24-11-19 20:29:04 | D | best error = [ 1.2362, 1.2362, 1.2362, 1.2362, 1.2362] +24-11-19 20:29:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:04 | D | sum error = [ 30.0515, 31.5965, 33.2070, 34.8816, 36.6273] +24-11-19 20:29:04 | D | best error = [ 1.2362, 1.2362, 1.2362, 1.2362, 1.2362] +24-11-19 20:29:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:04 | D | sum error = [ 38.4452, 40.3354, 42.3009, 44.3415, 46.4639] +24-11-19 20:29:04 | D | best error = [ 1.2362, 1.2362, 1.2362, 1.2362, 1.2362] +24-11-19 20:29:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:04 | D | sum error = [ 48.6679, 50.9496, 53.3191, 55.7766, 58.3258] +24-11-19 20:29:04 | D | best error = [ 1.2362, 1.2362, 1.2362, 1.2362, 1.2362] +24-11-19 20:29:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:04 | D | sum error = [ 60.9641, 63.7000, 66.5267, 69.4502, 72.4700] +24-11-19 20:29:04 | D | best error = [ 1.2362, 1.2362, 1.2362, 1.2362, 1.2362] +24-11-19 20:29:04 | D | + error = [1.2362] +24-11-19 20:29:04 | D | - Calibrating model.layers.15.mlp.up_proj.weight +24-11-19 20:29:04 | D | + w: sint8 +24-11-19 20:29:04 | D | + x: None +24-11-19 20:29:04 | D | + y: None +24-11-19 20:29:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:04 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:29:04 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:29:04 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:29:04 | D | - range ratio = [ 1.0000] +24-11-19 20:29:04 | D | sum error = [ 6.9889] +24-11-19 20:29:04 | D | best error = [ 6.9889] +24-11-19 20:29:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:05 | D | sum error = [ 6.9561, 6.9154, 6.9445, 7.0244, 7.1470] +24-11-19 20:29:05 | D | best error = [ 6.4948, 6.3043, 6.2016, 6.1467, 6.1166] +24-11-19 20:29:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:05 | D | sum error = [ 7.3387, 7.5870, 7.9216, 8.2716, 8.7120] +24-11-19 20:29:05 | D | best error = [ 6.1026, 6.0971, 6.0948, 6.0940, 6.0940] +24-11-19 20:29:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:05 | D | sum error = [ 9.2201, 9.7988, 10.4476, 11.1337, 11.9180] +24-11-19 20:29:05 | D | best error = [ 6.0939, 6.0939, 6.0939, 6.0939, 6.0939] +24-11-19 20:29:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:05 | D | sum error = [ 12.7393, 13.6591, 14.6572, 15.7022, 16.8175] +24-11-19 20:29:05 | D | best error = [ 6.0939, 6.0939, 6.0939, 6.0939, 6.0939] +24-11-19 20:29:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:05 | D | sum error = [ 18.0234, 19.3105, 20.6762, 22.1370, 23.6763] +24-11-19 20:29:05 | D | best error = [ 6.0939, 6.0939, 6.0939, 6.0939, 6.0939] +24-11-19 20:29:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:05 | D | sum error = [ 25.3186, 27.0500, 28.8722, 30.8248, 32.8720] +24-11-19 20:29:05 | D | best error = [ 6.0939, 6.0939, 6.0939, 6.0939, 6.0939] +24-11-19 20:29:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:05 | D | sum error = [ 35.0516, 37.3293, 39.7546, 42.2827, 44.9628] +24-11-19 20:29:05 | D | best error = [ 6.0939, 6.0939, 6.0939, 6.0939, 6.0939] +24-11-19 20:29:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:05 | D | sum error = [ 47.7981, 50.7491, 53.8822, 57.1753, 60.6288] +24-11-19 20:29:05 | D | best error = [ 6.0939, 6.0939, 6.0939, 6.0939, 6.0939] +24-11-19 20:29:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:05 | D | sum error = [ 64.2594, 68.0808, 72.0875, 76.2934, 80.7073] +24-11-19 20:29:05 | D | best error = [ 6.0939, 6.0939, 6.0939, 6.0939, 6.0939] +24-11-19 20:29:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:05 | D | sum error = [ 85.3375, 90.1960, 95.2731, 100.6274, 106.1995] +24-11-19 20:29:05 | D | best error = [ 6.0939, 6.0939, 6.0939, 6.0939, 6.0939] +24-11-19 20:29:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:05 | D | sum error = [ 112.0578, 118.1546, 124.5178, 131.1649, 138.1190] +24-11-19 20:29:05 | D | best error = [ 6.0939, 6.0939, 6.0939, 6.0939, 6.0939] +24-11-19 20:29:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:05 | D | sum error = [ 145.3641, 152.9345, 160.8195, 169.0203, 177.5617] +24-11-19 20:29:05 | D | best error = [ 6.0939, 6.0939, 6.0939, 6.0939, 6.0939] +24-11-19 20:29:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:05 | D | sum error = [ 186.4594, 195.7082, 205.3211, 215.2946, 225.6579] +24-11-19 20:29:05 | D | best error = [ 6.0939, 6.0939, 6.0939, 6.0939, 6.0939] +24-11-19 20:29:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:05 | D | sum error = [ 236.4134, 247.5656, 259.1264, 271.1152, 283.5101] +24-11-19 20:29:05 | D | best error = [ 6.0939, 6.0939, 6.0939, 6.0939, 6.0939] +24-11-19 20:29:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:05 | D | sum error = [ 296.3470, 309.6351, 323.3691, 337.5636, 352.2206] +24-11-19 20:29:05 | D | best error = [ 6.0939, 6.0939, 6.0939, 6.0939, 6.0939] +24-11-19 20:29:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:05 | D | sum error = [ 367.3268, 382.9134, 398.9742, 415.5029, 432.4994] +24-11-19 20:29:05 | D | best error = [ 6.0939, 6.0939, 6.0939, 6.0939, 6.0939] +24-11-19 20:29:05 | D | + error = [6.0939] +24-11-19 20:29:05 | D | - Calibrating model.layers.15.mlp.gate_proj.weight +24-11-19 20:29:05 | D | + w: sint8 +24-11-19 20:29:05 | D | + x: None +24-11-19 20:29:05 | D | + y: None +24-11-19 20:29:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:05 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:29:05 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:29:05 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:29:05 | D | - range ratio = [ 1.0000] +24-11-19 20:29:05 | D | sum error = [ 7.1708] +24-11-19 20:29:05 | D | best error = [ 7.1708] +24-11-19 20:29:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:06 | D | sum error = [ 7.1040, 7.1008, 7.1257, 7.2035, 7.3490] +24-11-19 20:29:06 | D | best error = [ 6.6444, 6.4585, 6.3564, 6.2985, 6.2690] +24-11-19 20:29:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:06 | D | sum error = [ 7.5379, 7.7913, 8.1127, 8.4940, 8.9460] +24-11-19 20:29:06 | D | best error = [ 6.2549, 6.2480, 6.2459, 6.2455, 6.2452] +24-11-19 20:29:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:06 | D | sum error = [ 9.4640, 10.0898, 10.7237, 11.4596, 12.2412] +24-11-19 20:29:06 | D | best error = [ 6.2452, 6.2452, 6.2452, 6.2452, 6.2452] +24-11-19 20:29:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:06 | D | sum error = [ 13.1165, 14.0597, 15.0824, 16.1817, 17.3477] +24-11-19 20:29:06 | D | best error = [ 6.2452, 6.2452, 6.2452, 6.2452, 6.2452] +24-11-19 20:29:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:06 | D | sum error = [ 18.6093, 19.9464, 21.4045, 22.9079, 24.5507] +24-11-19 20:29:06 | D | best error = [ 6.2452, 6.2452, 6.2452, 6.2452, 6.2452] +24-11-19 20:29:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:06 | D | sum error = [ 26.2957, 28.1119, 30.0752, 32.1413, 34.3256] +24-11-19 20:29:06 | D | best error = [ 6.2452, 6.2452, 6.2452, 6.2452, 6.2452] +24-11-19 20:29:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:06 | D | sum error = [ 36.6660, 39.1313, 41.7665, 44.5148, 47.4413] +24-11-19 20:29:06 | D | best error = [ 6.2452, 6.2452, 6.2452, 6.2452, 6.2452] +24-11-19 20:29:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:06 | D | sum error = [ 50.5500, 53.8273, 57.3001, 60.9543, 64.8490] +24-11-19 20:29:06 | D | best error = [ 6.2452, 6.2452, 6.2452, 6.2452, 6.2452] +24-11-19 20:29:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:06 | D | sum error = [ 68.9412, 73.2764, 77.8380, 82.6793, 87.7441] +24-11-19 20:29:06 | D | best error = [ 6.2452, 6.2452, 6.2452, 6.2452, 6.2452] +24-11-19 20:29:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:06 | D | sum error = [ 93.1181, 98.7959, 104.7796, 111.0940, 117.7808] +24-11-19 20:29:06 | D | best error = [ 6.2452, 6.2452, 6.2452, 6.2452, 6.2452] +24-11-19 20:29:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:06 | D | sum error = [ 124.7910, 132.2074, 139.9987, 148.2007, 156.8022] +24-11-19 20:29:06 | D | best error = [ 6.2452, 6.2452, 6.2452, 6.2452, 6.2452] +24-11-19 20:29:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:06 | D | sum error = [ 165.8657, 175.3636, 185.3435, 195.8245, 206.7959] +24-11-19 20:29:06 | D | best error = [ 6.2452, 6.2452, 6.2452, 6.2452, 6.2452] +24-11-19 20:29:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:06 | D | sum error = [ 218.3102, 230.3477, 242.9166, 256.0894, 269.8576] +24-11-19 20:29:06 | D | best error = [ 6.2452, 6.2452, 6.2452, 6.2452, 6.2452] +24-11-19 20:29:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:06 | D | sum error = [ 284.2222, 299.1995, 314.8091, 331.1137, 348.0086] +24-11-19 20:29:06 | D | best error = [ 6.2452, 6.2452, 6.2452, 6.2452, 6.2452] +24-11-19 20:29:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:06 | D | sum error = [ 365.6216, 383.9099, 402.8907, 422.5546, 442.9543] +24-11-19 20:29:06 | D | best error = [ 6.2452, 6.2452, 6.2452, 6.2452, 6.2452] +24-11-19 20:29:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:06 | D | sum error = [ 464.0741, 485.8889, 508.4127, 531.6343, 555.5705] +24-11-19 20:29:06 | D | best error = [ 6.2452, 6.2452, 6.2452, 6.2452, 6.2452] +24-11-19 20:29:06 | D | + error = [6.2452] +24-11-19 20:29:06 | D | - Calibrating model.layers.15.mlp.down_proj.weight +24-11-19 20:29:06 | D | + w: sint8 +24-11-19 20:29:06 | D | + x: None +24-11-19 20:29:06 | D | + y: None +24-11-19 20:29:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:06 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:29:06 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:29:07 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:29:07 | D | - range ratio = [ 1.0000] +24-11-19 20:29:07 | D | sum error = [ 2.1370] +24-11-19 20:29:07 | D | best error = [ 2.1370] +24-11-19 20:29:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:07 | D | sum error = [ 2.1193, 2.1061, 2.0949, 2.0911, 2.0895] +24-11-19 20:29:07 | D | best error = [ 2.0653, 2.0283, 2.0027, 1.9850, 1.9699] +24-11-19 20:29:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:07 | D | sum error = [ 2.0954, 2.1101, 2.1357, 2.1708, 2.2163] +24-11-19 20:29:07 | D | best error = [ 1.9582, 1.9500, 1.9437, 1.9391, 1.9360] +24-11-19 20:29:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:07 | D | sum error = [ 2.2739, 2.3419, 2.4230, 2.5197, 2.6365] +24-11-19 20:29:07 | D | best error = [ 1.9344, 1.9331, 1.9321, 1.9316, 1.9313] +24-11-19 20:29:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:07 | D | sum error = [ 2.7608, 2.9062, 3.0670, 3.2432, 3.4412] +24-11-19 20:29:07 | D | best error = [ 1.9310, 1.9309, 1.9309, 1.9308, 1.9308] +24-11-19 20:29:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:07 | D | sum error = [ 3.6534, 3.8901, 4.1390, 4.4166, 4.7110] +24-11-19 20:29:07 | D | best error = [ 1.9308, 1.9308, 1.9308, 1.9307, 1.9307] +24-11-19 20:29:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:07 | D | sum error = [ 5.0255, 5.3714, 5.7321, 6.1187, 6.5395] +24-11-19 20:29:07 | D | best error = [ 1.9307, 1.9307, 1.9307, 1.9307, 1.9307] +24-11-19 20:29:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:07 | D | sum error = [ 6.9770, 7.4513, 7.9504, 8.4871, 9.0549] +24-11-19 20:29:07 | D | best error = [ 1.9307, 1.9307, 1.9307, 1.9307, 1.9307] +24-11-19 20:29:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:07 | D | sum error = [ 9.6560, 10.2958, 10.9786, 11.6921, 12.4492] +24-11-19 20:29:07 | D | best error = [ 1.9307, 1.9307, 1.9307, 1.9307, 1.9307] +24-11-19 20:29:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:07 | D | sum error = [ 13.2540, 14.1034, 15.0002, 15.9467, 16.9470] +24-11-19 20:29:07 | D | best error = [ 1.9307, 1.9307, 1.9307, 1.9307, 1.9307] +24-11-19 20:29:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:07 | D | sum error = [ 18.0013, 19.1106, 20.2824, 21.5148, 22.8114] +24-11-19 20:29:07 | D | best error = [ 1.9307, 1.9307, 1.9307, 1.9307, 1.9307] +24-11-19 20:29:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:07 | D | sum error = [ 24.1778, 25.6164, 27.1216, 28.7030, 30.3621] +24-11-19 20:29:07 | D | best error = [ 1.9307, 1.9307, 1.9307, 1.9307, 1.9307] +24-11-19 20:29:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:07 | D | sum error = [ 32.1033, 33.9307, 35.8443, 37.8473, 39.9454] +24-11-19 20:29:07 | D | best error = [ 1.9307, 1.9307, 1.9307, 1.9307, 1.9307] +24-11-19 20:29:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:07 | D | sum error = [ 42.1371, 44.4312, 46.8251, 49.3241, 51.9321] +24-11-19 20:29:07 | D | best error = [ 1.9307, 1.9307, 1.9307, 1.9307, 1.9307] +24-11-19 20:29:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:07 | D | sum error = [ 54.6555, 57.4891, 60.4406, 63.5158, 66.7061] +24-11-19 20:29:07 | D | best error = [ 1.9307, 1.9307, 1.9307, 1.9307, 1.9307] +24-11-19 20:29:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:07 | D | sum error = [ 70.0267, 73.4754, 77.0600, 80.7788, 84.6354] +24-11-19 20:29:07 | D | best error = [ 1.9307, 1.9307, 1.9307, 1.9307, 1.9307] +24-11-19 20:29:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:07 | D | sum error = [ 88.6335, 92.7721, 97.0557, 101.4894, 106.0728] +24-11-19 20:29:07 | D | best error = [ 1.9307, 1.9307, 1.9307, 1.9307, 1.9307] +24-11-19 20:29:07 | D | + error = [1.9307] +24-11-19 20:29:08 | D | - Quantizing model.layers.15.self_attn.q_proj.weight +24-11-19 20:29:08 | D | - Quantizing model.layers.15.self_attn.k_proj.weight +24-11-19 20:29:09 | D | - Quantizing model.layers.15.self_attn.v_proj.weight +24-11-19 20:29:10 | D | - Quantizing model.layers.15.self_attn.o_proj.weight +24-11-19 20:29:11 | D | - Quantizing model.layers.15.mlp.up_proj.weight +24-11-19 20:29:12 | D | - Quantizing model.layers.15.mlp.gate_proj.weight +24-11-19 20:29:13 | D | - Quantizing model.layers.15.mlp.down_proj.weight +24-11-19 20:29:21 | D | - Quantizing layer model.layers.16 +24-11-19 20:29:21 | D | - Calibrating model.layers.16.self_attn.q_proj.weight +24-11-19 20:29:21 | D | + w: sint8 +24-11-19 20:29:21 | D | + x: None +24-11-19 20:29:21 | D | + y: None +24-11-19 20:29:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:29:21 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:29:21 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:29:21 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:29:21 | D | - range ratio = [ 1.0000] +24-11-19 20:29:21 | D | sum error = [ 12.6092] +24-11-19 20:29:21 | D | best error = [ 12.6092] +24-11-19 20:29:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:34 | D | sum error = [ 12.5453, 12.6281, 12.4824, 12.5469, 12.7935] +24-11-19 20:29:34 | D | best error = [ 12.5453, 12.5453, 12.4824, 12.4824, 12.4824] +24-11-19 20:29:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:34 | D | sum error = [ 13.3932, 13.7781, 14.3521, 14.7775, 15.6714] +24-11-19 20:29:34 | D | best error = [ 12.4824, 12.4824, 12.4824, 12.4824, 12.4824] +24-11-19 20:29:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:34 | D | sum error = [ 16.5836, 17.7090, 19.0145, 20.5546, 21.6274] +24-11-19 20:29:34 | D | best error = [ 12.4824, 12.4824, 12.4824, 12.4824, 12.4824] +24-11-19 20:29:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:34 | D | sum error = [ 23.2803, 25.2109, 27.0891, 29.2580, 31.9973] +24-11-19 20:29:34 | D | best error = [ 12.4824, 12.4824, 12.4824, 12.4824, 12.4824] +24-11-19 20:29:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:34 | D | sum error = [ 33.8616, 36.6639, 39.5169, 42.5594, 45.9955] +24-11-19 20:29:34 | D | best error = [ 12.4824, 12.4824, 12.4824, 12.4824, 12.4824] +24-11-19 20:29:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:34 | D | sum error = [ 49.4606, 53.3484, 57.3762, 61.8817, 66.9250] +24-11-19 20:29:34 | D | best error = [ 12.4824, 12.4824, 12.4824, 12.4824, 12.4824] +24-11-19 20:29:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:34 | D | sum error = [ 71.6414, 77.2938, 83.0878, 89.1582, 96.0205] +24-11-19 20:29:34 | D | best error = [ 12.4824, 12.4824, 12.4824, 12.4824, 12.4824] +24-11-19 20:29:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:34 | D | sum error = [ 103.0222, 111.0467, 119.3809, 128.2042, 137.6938] +24-11-19 20:29:34 | D | best error = [ 12.4824, 12.4824, 12.4824, 12.4824, 12.4824] +24-11-19 20:29:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:34 | D | sum error = [ 147.8773, 158.8253, 170.4470, 183.3367, 196.6018] +24-11-19 20:29:34 | D | best error = [ 12.4824, 12.4824, 12.4824, 12.4824, 12.4824] +24-11-19 20:29:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:34 | D | sum error = [ 211.2171, 226.9974, 243.4394, 261.5265, 280.4031] +24-11-19 20:29:34 | D | best error = [ 12.4824, 12.4824, 12.4824, 12.4824, 12.4824] +24-11-19 20:29:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:34 | D | sum error = [ 300.7978, 322.9011, 346.2840, 371.4214, 398.2918] +24-11-19 20:29:34 | D | best error = [ 12.4824, 12.4824, 12.4824, 12.4824, 12.4824] +24-11-19 20:29:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:34 | D | sum error = [ 427.2451, 457.9702, 491.0490, 526.6491, 564.3990] +24-11-19 20:29:34 | D | best error = [ 12.4824, 12.4824, 12.4824, 12.4824, 12.4824] +24-11-19 20:29:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:34 | D | sum error = [ 605.3658, 649.1323, 696.3209, 746.9670, 801.2221] +24-11-19 20:29:34 | D | best error = [ 12.4824, 12.4824, 12.4824, 12.4824, 12.4824] +24-11-19 20:29:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:34 | D | sum error = [ 859.6259, 922.7039, 990.5974, 1063.9998, 1143.2361] +24-11-19 20:29:34 | D | best error = [ 12.4824, 12.4824, 12.4824, 12.4824, 12.4824] +24-11-19 20:29:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:34 | D | sum error = [ 1228.6282, 1320.0611, 1418.4000, 1523.7905, 1636.4680] +24-11-19 20:29:34 | D | best error = [ 12.4824, 12.4824, 12.4824, 12.4824, 12.4824] +24-11-19 20:29:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:34 | D | sum error = [ 1756.2400, 1883.2788, 2017.6395, 2158.5053, 2305.6380] +24-11-19 20:29:34 | D | best error = [ 12.4824, 12.4824, 12.4824, 12.4824, 12.4824] +24-11-19 20:29:34 | D | + error = [12.4824] +24-11-19 20:29:34 | D | - Calibrating model.layers.16.self_attn.k_proj.weight +24-11-19 20:29:34 | D | + w: sint8 +24-11-19 20:29:34 | D | + x: None +24-11-19 20:29:34 | D | + y: None +24-11-19 20:29:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:29:34 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:29:34 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:29:34 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:29:34 | D | - range ratio = [ 1.0000] +24-11-19 20:29:34 | D | sum error = [ 12.7790] +24-11-19 20:29:34 | D | best error = [ 12.7790] +24-11-19 20:29:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:47 | D | sum error = [ 12.4174, 12.0928, 12.7273, 13.1086, 13.2538] +24-11-19 20:29:47 | D | best error = [ 12.4174, 12.0928, 12.0928, 12.0928, 12.0928] +24-11-19 20:29:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:47 | D | sum error = [ 13.2297, 13.5572, 14.7633, 15.1420, 15.6795] +24-11-19 20:29:47 | D | best error = [ 12.0928, 12.0928, 12.0928, 12.0928, 12.0928] +24-11-19 20:29:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:47 | D | sum error = [ 16.5198, 17.9310, 19.8711, 20.2034, 22.1907] +24-11-19 20:29:47 | D | best error = [ 12.0928, 12.0928, 12.0928, 12.0928, 12.0928] +24-11-19 20:29:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:47 | D | sum error = [ 23.6186, 25.7896, 27.6106, 29.6359, 31.7534] +24-11-19 20:29:47 | D | best error = [ 12.0928, 12.0928, 12.0928, 12.0928, 12.0928] +24-11-19 20:29:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:47 | D | sum error = [ 35.2310, 37.1147, 40.2894, 43.6778, 47.3252] +24-11-19 20:29:47 | D | best error = [ 12.0928, 12.0928, 12.0928, 12.0928, 12.0928] +24-11-19 20:29:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:47 | D | sum error = [ 49.9278, 53.4997, 57.8243, 62.0014, 67.4181] +24-11-19 20:29:47 | D | best error = [ 12.0928, 12.0928, 12.0928, 12.0928, 12.0928] +24-11-19 20:29:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:47 | D | sum error = [ 72.2437, 77.4805, 82.8727, 89.8836, 95.9762] +24-11-19 20:29:47 | D | best error = [ 12.0928, 12.0928, 12.0928, 12.0928, 12.0928] +24-11-19 20:29:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:47 | D | sum error = [ 102.8718, 110.0562, 118.2963, 126.4043, 136.0361] +24-11-19 20:29:47 | D | best error = [ 12.0928, 12.0928, 12.0928, 12.0928, 12.0928] +24-11-19 20:29:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:47 | D | sum error = [ 145.8670, 156.7339, 167.2126, 179.5702, 192.7963] +24-11-19 20:29:47 | D | best error = [ 12.0928, 12.0928, 12.0928, 12.0928, 12.0928] +24-11-19 20:29:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:47 | D | sum error = [ 207.5924, 223.2114, 240.8011, 259.0435, 279.4834] +24-11-19 20:29:47 | D | best error = [ 12.0928, 12.0928, 12.0928, 12.0928, 12.0928] +24-11-19 20:29:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:47 | D | sum error = [ 300.9560, 324.3237, 349.2494, 376.2160, 405.4020] +24-11-19 20:29:47 | D | best error = [ 12.0928, 12.0928, 12.0928, 12.0928, 12.0928] +24-11-19 20:29:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:47 | D | sum error = [ 435.2688, 467.9917, 503.0171, 540.9337, 581.0817] +24-11-19 20:29:47 | D | best error = [ 12.0928, 12.0928, 12.0928, 12.0928, 12.0928] +24-11-19 20:29:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:47 | D | sum error = [ 624.3059, 669.6469, 718.0247, 770.0081, 825.2548] +24-11-19 20:29:47 | D | best error = [ 12.0928, 12.0928, 12.0928, 12.0928, 12.0928] +24-11-19 20:29:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:47 | D | sum error = [ 885.6403, 949.6527, 1017.7792, 1090.6293, 1168.1665] +24-11-19 20:29:47 | D | best error = [ 12.0928, 12.0928, 12.0928, 12.0928, 12.0928] +24-11-19 20:29:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:47 | D | sum error = [ 1251.8632, 1341.6746, 1437.0629, 1539.0669, 1648.0673] +24-11-19 20:29:47 | D | best error = [ 12.0928, 12.0928, 12.0928, 12.0928, 12.0928] +24-11-19 20:29:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:47 | D | sum error = [ 1765.2936, 1888.9782, 2019.9130, 2156.1614, 2298.3431] +24-11-19 20:29:47 | D | best error = [ 12.0928, 12.0928, 12.0928, 12.0928, 12.0928] +24-11-19 20:29:47 | D | + error = [12.0928] +24-11-19 20:29:47 | D | - Calibrating model.layers.16.self_attn.v_proj.weight +24-11-19 20:29:47 | D | + w: sint8 +24-11-19 20:29:47 | D | + x: None +24-11-19 20:29:47 | D | + y: None +24-11-19 20:29:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:47 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:29:47 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:29:48 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:29:48 | D | - range ratio = [ 1.0000] +24-11-19 20:29:48 | D | sum error = [ 5.3645] +24-11-19 20:29:48 | D | best error = [ 5.3645] +24-11-19 20:29:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:48 | D | sum error = [ 5.3299, 5.3270, 5.3295, 5.3941, 5.4895] +24-11-19 20:29:48 | D | best error = [ 4.9930, 4.8529, 4.7709, 4.7249, 4.7033] +24-11-19 20:29:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:48 | D | sum error = [ 5.6367, 5.8265, 6.0926, 6.3376, 6.6850] +24-11-19 20:29:48 | D | best error = [ 4.6937, 4.6895, 4.6874, 4.6866, 4.6865] +24-11-19 20:29:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:48 | D | sum error = [ 7.0380, 7.4850, 7.9770, 8.4952, 9.1009] +24-11-19 20:29:48 | D | best error = [ 4.6865, 4.6865, 4.6865, 4.6865, 4.6865] +24-11-19 20:29:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:48 | D | sum error = [ 9.7138, 10.4187, 11.1517, 11.9937, 12.8204] +24-11-19 20:29:48 | D | best error = [ 4.6865, 4.6865, 4.6865, 4.6865, 4.6865] +24-11-19 20:29:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:48 | D | sum error = [ 13.7456, 14.7340, 15.7659, 16.8738, 18.0561] +24-11-19 20:29:48 | D | best error = [ 4.6865, 4.6865, 4.6865, 4.6865, 4.6865] +24-11-19 20:29:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:48 | D | sum error = [ 19.3044, 20.6296, 22.0176, 23.4947, 25.0599] +24-11-19 20:29:48 | D | best error = [ 4.6865, 4.6865, 4.6865, 4.6865, 4.6865] +24-11-19 20:29:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:48 | D | sum error = [ 26.6933, 28.4022, 30.2486, 32.1576, 34.1823] +24-11-19 20:29:48 | D | best error = [ 4.6865, 4.6865, 4.6865, 4.6865, 4.6865] +24-11-19 20:29:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:48 | D | sum error = [ 36.3034, 38.5546, 40.8761, 43.3555, 45.9372] +24-11-19 20:29:48 | D | best error = [ 4.6865, 4.6865, 4.6865, 4.6865, 4.6865] +24-11-19 20:29:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:48 | D | sum error = [ 48.6712, 51.5214, 54.4954, 57.6243, 60.9101] +24-11-19 20:29:48 | D | best error = [ 4.6865, 4.6865, 4.6865, 4.6865, 4.6865] +24-11-19 20:29:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:48 | D | sum error = [ 64.3259, 67.9130, 71.6446, 75.5538, 79.6353] +24-11-19 20:29:48 | D | best error = [ 4.6865, 4.6865, 4.6865, 4.6865, 4.6865] +24-11-19 20:29:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:48 | D | sum error = [ 83.8992, 88.3380, 92.9854, 97.8381, 102.8837] +24-11-19 20:29:48 | D | best error = [ 4.6865, 4.6865, 4.6865, 4.6865, 4.6865] +24-11-19 20:29:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:48 | D | sum error = [ 108.1428, 113.6149, 119.3089, 125.2378, 131.4033] +24-11-19 20:29:48 | D | best error = [ 4.6865, 4.6865, 4.6865, 4.6865, 4.6865] +24-11-19 20:29:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:48 | D | sum error = [ 137.8084, 144.4691, 151.3784, 158.5237, 165.9737] +24-11-19 20:29:48 | D | best error = [ 4.6865, 4.6865, 4.6865, 4.6865, 4.6865] +24-11-19 20:29:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:48 | D | sum error = [ 173.6659, 181.6496, 189.9067, 198.4518, 207.2699] +24-11-19 20:29:48 | D | best error = [ 4.6865, 4.6865, 4.6865, 4.6865, 4.6865] +24-11-19 20:29:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:48 | D | sum error = [ 216.3913, 225.7960, 235.5208, 245.5520, 255.8915] +24-11-19 20:29:48 | D | best error = [ 4.6865, 4.6865, 4.6865, 4.6865, 4.6865] +24-11-19 20:29:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:48 | D | sum error = [ 266.5256, 277.4900, 288.7606, 300.3469, 312.2645] +24-11-19 20:29:48 | D | best error = [ 4.6865, 4.6865, 4.6865, 4.6865, 4.6865] +24-11-19 20:29:48 | D | + error = [4.6865] +24-11-19 20:29:48 | D | - Calibrating model.layers.16.self_attn.o_proj.weight +24-11-19 20:29:48 | D | + w: sint8 +24-11-19 20:29:48 | D | + x: None +24-11-19 20:29:48 | D | + y: None +24-11-19 20:29:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:48 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:29:48 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:29:48 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:29:48 | D | - range ratio = [ 1.0000] +24-11-19 20:29:48 | D | sum error = [ 1.6721] +24-11-19 20:29:48 | D | best error = [ 1.6721] +24-11-19 20:29:49 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:49 | D | sum error = [ 1.6591, 1.6518, 1.6509, 1.6610, 1.6748] +24-11-19 20:29:49 | D | best error = [ 1.5607, 1.5097, 1.4781, 1.4580, 1.4443] +24-11-19 20:29:49 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:49 | D | sum error = [ 1.7010, 1.7279, 1.7795, 1.8422, 1.9129] +24-11-19 20:29:49 | D | best error = [ 1.4349, 1.4286, 1.4240, 1.4217, 1.4201] +24-11-19 20:29:49 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:49 | D | sum error = [ 1.9964, 2.0870, 2.1924, 2.3096, 2.4443] +24-11-19 20:29:49 | D | best error = [ 1.4191, 1.4184, 1.4177, 1.4175, 1.4171] +24-11-19 20:29:49 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:49 | D | sum error = [ 2.6044, 2.7615, 2.9360, 3.1284, 3.3350] +24-11-19 20:29:49 | D | best error = [ 1.4168, 1.4167, 1.4166, 1.4166, 1.4166] +24-11-19 20:29:49 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:49 | D | sum error = [ 3.5610, 3.7919, 4.0504, 4.3176, 4.6057] +24-11-19 20:29:49 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 20:29:49 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:49 | D | sum error = [ 4.9176, 5.2494, 5.5905, 5.9584, 6.3552] +24-11-19 20:29:49 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 20:29:49 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:49 | D | sum error = [ 6.7657, 7.2051, 7.6633, 8.1539, 8.6685] +24-11-19 20:29:49 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 20:29:49 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:49 | D | sum error = [ 9.2134, 9.7900, 10.3981, 11.0377, 11.7143] +24-11-19 20:29:49 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 20:29:49 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:49 | D | sum error = [ 12.4211, 13.1669, 13.9453, 14.7751, 15.6379] +24-11-19 20:29:49 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 20:29:49 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:49 | D | sum error = [ 16.5561, 17.5121, 18.5190, 19.5825, 20.6954] +24-11-19 20:29:49 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 20:29:49 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:49 | D | sum error = [ 21.8636, 23.0913, 24.3748, 25.7238, 27.1326] +24-11-19 20:29:49 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 20:29:49 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:49 | D | sum error = [ 28.6164, 30.1674, 31.7893, 33.4818, 35.2534] +24-11-19 20:29:49 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 20:29:49 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:49 | D | sum error = [ 37.1059, 39.0325, 41.0527, 43.1629, 45.3625] +24-11-19 20:29:49 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 20:29:49 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:49 | D | sum error = [ 47.6532, 50.0332, 52.5116, 55.0928, 57.7730] +24-11-19 20:29:49 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 20:29:49 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:49 | D | sum error = [ 60.5592, 63.4483, 66.4473, 69.5565, 72.7832] +24-11-19 20:29:49 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 20:29:49 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:49 | D | sum error = [ 76.1264, 79.5885, 83.1687, 86.8708, 90.7011] +24-11-19 20:29:49 | D | best error = [ 1.4166, 1.4166, 1.4166, 1.4166, 1.4166] +24-11-19 20:29:49 | D | + error = [1.4166] +24-11-19 20:29:49 | D | - Calibrating model.layers.16.mlp.up_proj.weight +24-11-19 20:29:49 | D | + w: sint8 +24-11-19 20:29:49 | D | + x: None +24-11-19 20:29:49 | D | + y: None +24-11-19 20:29:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:49 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:29:49 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:29:49 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:29:49 | D | - range ratio = [ 1.0000] +24-11-19 20:29:49 | D | sum error = [ 7.4574] +24-11-19 20:29:49 | D | best error = [ 7.4574] +24-11-19 20:29:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:50 | D | sum error = [ 7.3824, 7.3822, 7.3901, 7.4680, 7.6147] +24-11-19 20:29:50 | D | best error = [ 6.9161, 6.7102, 6.6028, 6.5384, 6.5041] +24-11-19 20:29:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:50 | D | sum error = [ 7.8015, 8.0685, 8.4292, 8.8203, 9.2559] +24-11-19 20:29:50 | D | best error = [ 6.4880, 6.4812, 6.4790, 6.4784, 6.4781] +24-11-19 20:29:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:50 | D | sum error = [ 9.8095, 10.4238, 11.0877, 11.8312, 12.6416] +24-11-19 20:29:50 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:29:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:50 | D | sum error = [ 13.5321, 14.5160, 15.5388, 16.6466, 17.8686] +24-11-19 20:29:50 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:29:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:50 | D | sum error = [ 19.1347, 20.4816, 21.9363, 23.4630, 25.0942] +24-11-19 20:29:50 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:29:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:50 | D | sum error = [ 26.8384, 28.6638, 30.6114, 32.6516, 34.8586] +24-11-19 20:29:50 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:29:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:50 | D | sum error = [ 37.1389, 39.5560, 42.1480, 44.8167, 47.6700] +24-11-19 20:29:50 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:29:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:50 | D | sum error = [ 50.6679, 53.8220, 57.1378, 60.6382, 64.3063] +24-11-19 20:29:50 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:29:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:50 | D | sum error = [ 68.1776, 72.2583, 76.5359, 81.0260, 85.7542] +24-11-19 20:29:50 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:29:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:50 | D | sum error = [ 90.6850, 95.8900, 101.3344, 107.0607, 113.0261] +24-11-19 20:29:50 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:29:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:50 | D | sum error = [ 119.2684, 125.8417, 132.6857, 139.8441, 147.3277] +24-11-19 20:29:50 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:29:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:50 | D | sum error = [ 155.1339, 163.2781, 171.7995, 180.6831, 189.9312] +24-11-19 20:29:50 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:29:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:50 | D | sum error = [ 199.5732, 209.6069, 220.0460, 230.9219, 242.2209] +24-11-19 20:29:50 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:29:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:50 | D | sum error = [ 253.9506, 266.1325, 278.7632, 291.8685, 305.4391] +24-11-19 20:29:50 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:29:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:50 | D | sum error = [ 319.4748, 333.9887, 349.0129, 364.5555, 380.6063] +24-11-19 20:29:50 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:29:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:50 | D | sum error = [ 397.1590, 414.2329, 431.8313, 449.9371, 468.5906] +24-11-19 20:29:50 | D | best error = [ 6.4781, 6.4781, 6.4781, 6.4781, 6.4781] +24-11-19 20:29:50 | D | + error = [6.4781] +24-11-19 20:29:50 | D | - Calibrating model.layers.16.mlp.gate_proj.weight +24-11-19 20:29:50 | D | + w: sint8 +24-11-19 20:29:50 | D | + x: None +24-11-19 20:29:50 | D | + y: None +24-11-19 20:29:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:50 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:29:50 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:29:50 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:29:50 | D | - range ratio = [ 1.0000] +24-11-19 20:29:50 | D | sum error = [ 7.6660] +24-11-19 20:29:50 | D | best error = [ 7.6660] +24-11-19 20:29:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:51 | D | sum error = [ 7.6077, 7.5892, 7.6236, 7.7346, 7.8520] +24-11-19 20:29:51 | D | best error = [ 7.1298, 6.9201, 6.8046, 6.7425, 6.7086] +24-11-19 20:29:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:51 | D | sum error = [ 8.0633, 8.3359, 8.6855, 9.0859, 9.5821] +24-11-19 20:29:51 | D | best error = [ 6.6940, 6.6875, 6.6846, 6.6836, 6.6835] +24-11-19 20:29:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:51 | D | sum error = [ 10.1345, 10.7673, 11.4834, 12.2640, 13.1064] +24-11-19 20:29:51 | D | best error = [ 6.6834, 6.6834, 6.6834, 6.6834, 6.6834] +24-11-19 20:29:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:51 | D | sum error = [ 14.0633, 15.0756, 16.1900, 17.3719, 18.6039] +24-11-19 20:29:51 | D | best error = [ 6.6834, 6.6834, 6.6834, 6.6834, 6.6834] +24-11-19 20:29:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:51 | D | sum error = [ 19.9845, 21.4409, 22.9854, 24.6392, 26.4199] +24-11-19 20:29:51 | D | best error = [ 6.6834, 6.6834, 6.6834, 6.6834, 6.6834] +24-11-19 20:29:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:51 | D | sum error = [ 28.2929, 30.2718, 32.3869, 34.6267, 37.0037] +24-11-19 20:29:51 | D | best error = [ 6.6834, 6.6834, 6.6834, 6.6834, 6.6834] +24-11-19 20:29:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:51 | D | sum error = [ 39.5259, 42.2165, 45.0457, 48.0560, 51.2298] +24-11-19 20:29:51 | D | best error = [ 6.6834, 6.6834, 6.6834, 6.6834, 6.6834] +24-11-19 20:29:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:51 | D | sum error = [ 54.5831, 58.1685, 61.9739, 65.9944, 70.2138] +24-11-19 20:29:51 | D | best error = [ 6.6834, 6.6834, 6.6834, 6.6834, 6.6834] +24-11-19 20:29:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:51 | D | sum error = [ 74.7047, 79.4084, 84.4363, 89.6911, 95.2673] +24-11-19 20:29:51 | D | best error = [ 6.6834, 6.6834, 6.6834, 6.6834, 6.6834] +24-11-19 20:29:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:51 | D | sum error = [ 101.1610, 107.3874, 113.9407, 120.8659, 128.2058] +24-11-19 20:29:51 | D | best error = [ 6.6834, 6.6834, 6.6834, 6.6834, 6.6834] +24-11-19 20:29:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:51 | D | sum error = [ 135.9109, 144.0097, 152.5683, 161.5901, 171.0735] +24-11-19 20:29:51 | D | best error = [ 6.6834, 6.6834, 6.6834, 6.6834, 6.6834] +24-11-19 20:29:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:51 | D | sum error = [ 181.0332, 191.5390, 202.5553, 214.1252, 226.2638] +24-11-19 20:29:51 | D | best error = [ 6.6834, 6.6834, 6.6834, 6.6834, 6.6834] +24-11-19 20:29:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:51 | D | sum error = [ 238.9662, 252.2942, 266.2077, 280.7723, 295.9704] +24-11-19 20:29:51 | D | best error = [ 6.6834, 6.6834, 6.6834, 6.6834, 6.6834] +24-11-19 20:29:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:51 | D | sum error = [ 311.8390, 328.4026, 345.6737, 363.6634, 382.3806] +24-11-19 20:29:51 | D | best error = [ 6.6834, 6.6834, 6.6834, 6.6834, 6.6834] +24-11-19 20:29:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:51 | D | sum error = [ 401.8332, 422.0320, 442.9996, 464.7569, 487.2948] +24-11-19 20:29:51 | D | best error = [ 6.6834, 6.6834, 6.6834, 6.6834, 6.6834] +24-11-19 20:29:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:51 | D | sum error = [ 510.5721, 534.6403, 559.4902, 585.1057, 611.4965] +24-11-19 20:29:51 | D | best error = [ 6.6834, 6.6834, 6.6834, 6.6834, 6.6834] +24-11-19 20:29:51 | D | + error = [6.6834] +24-11-19 20:29:51 | D | - Calibrating model.layers.16.mlp.down_proj.weight +24-11-19 20:29:51 | D | + w: sint8 +24-11-19 20:29:51 | D | + x: None +24-11-19 20:29:51 | D | + y: None +24-11-19 20:29:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:51 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:29:51 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:29:52 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:29:52 | D | - range ratio = [ 1.0000] +24-11-19 20:29:52 | D | sum error = [ 2.7201] +24-11-19 20:29:52 | D | best error = [ 2.7201] +24-11-19 20:29:53 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:53 | D | sum error = [ 2.7031, 2.6875, 2.6643, 2.6538, 2.6506] +24-11-19 20:29:53 | D | best error = [ 2.5823, 2.5106, 2.4637, 2.4305, 2.4044] +24-11-19 20:29:53 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:53 | D | sum error = [ 2.6505, 2.6690, 2.6886, 2.7266, 2.7701] +24-11-19 20:29:53 | D | best error = [ 2.3832, 2.3667, 2.3547, 2.3473, 2.3412] +24-11-19 20:29:53 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:53 | D | sum error = [ 2.8254, 2.9006, 2.9912, 3.0957, 3.2108] +24-11-19 20:29:53 | D | best error = [ 2.3371, 2.3342, 2.3323, 2.3309, 2.3303] +24-11-19 20:29:53 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:53 | D | sum error = [ 3.3522, 3.5215, 3.6988, 3.9054, 4.1387] +24-11-19 20:29:53 | D | best error = [ 2.3296, 2.3293, 2.3291, 2.3290, 2.3289] +24-11-19 20:29:53 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:53 | D | sum error = [ 4.3852, 4.6709, 4.9793, 5.3150, 5.6729] +24-11-19 20:29:53 | D | best error = [ 2.3288, 2.3288, 2.3288, 2.3288, 2.3288] +24-11-19 20:29:53 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:53 | D | sum error = [ 6.0647, 6.4918, 6.9380, 7.4289, 7.9463] +24-11-19 20:29:53 | D | best error = [ 2.3288, 2.3288, 2.3288, 2.3288, 2.3288] +24-11-19 20:29:53 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:53 | D | sum error = [ 8.5026, 9.0914, 9.7226, 10.3972, 11.1105] +24-11-19 20:29:53 | D | best error = [ 2.3288, 2.3288, 2.3288, 2.3288, 2.3288] +24-11-19 20:29:53 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:53 | D | sum error = [ 11.8679, 12.6816, 13.5422, 14.4540, 15.4250] +24-11-19 20:29:53 | D | best error = [ 2.3288, 2.3288, 2.3288, 2.3288, 2.3288] +24-11-19 20:29:53 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:53 | D | sum error = [ 16.4519, 17.5482, 18.6997, 19.9109, 21.1961] +24-11-19 20:29:53 | D | best error = [ 2.3288, 2.3288, 2.3288, 2.3288, 2.3288] +24-11-19 20:29:53 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:53 | D | sum error = [ 22.5491, 23.9758, 25.4764, 27.0559, 28.7183] +24-11-19 20:29:53 | D | best error = [ 2.3288, 2.3288, 2.3288, 2.3288, 2.3288] +24-11-19 20:29:53 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:53 | D | sum error = [ 30.4672, 32.3085, 34.2381, 36.2679, 38.3929] +24-11-19 20:29:53 | D | best error = [ 2.3288, 2.3288, 2.3288, 2.3288, 2.3288] +24-11-19 20:29:53 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:53 | D | sum error = [ 40.6306, 42.9779, 45.4324, 48.0047, 50.6861] +24-11-19 20:29:53 | D | best error = [ 2.3288, 2.3288, 2.3288, 2.3288, 2.3288] +24-11-19 20:29:53 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:53 | D | sum error = [ 53.4988, 56.4313, 59.4949, 62.6939, 66.0315] +24-11-19 20:29:53 | D | best error = [ 2.3288, 2.3288, 2.3288, 2.3288, 2.3288] +24-11-19 20:29:53 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:53 | D | sum error = [ 69.5160, 73.1452, 76.9258, 80.8647, 84.9459] +24-11-19 20:29:53 | D | best error = [ 2.3288, 2.3288, 2.3288, 2.3288, 2.3288] +24-11-19 20:29:53 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:53 | D | sum error = [ 89.1966, 93.6093, 98.1911, 102.9421, 107.8678] +24-11-19 20:29:53 | D | best error = [ 2.3288, 2.3288, 2.3288, 2.3288, 2.3288] +24-11-19 20:29:53 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:53 | D | sum error = [ 112.9718, 118.2514, 123.7129, 129.3557, 135.1887] +24-11-19 20:29:53 | D | best error = [ 2.3288, 2.3288, 2.3288, 2.3288, 2.3288] +24-11-19 20:29:53 | D | + error = [2.3288] +24-11-19 20:29:53 | D | - Quantizing model.layers.16.self_attn.q_proj.weight +24-11-19 20:29:53 | D | - Quantizing model.layers.16.self_attn.k_proj.weight +24-11-19 20:29:54 | D | - Quantizing model.layers.16.self_attn.v_proj.weight +24-11-19 20:29:55 | D | - Quantizing model.layers.16.self_attn.o_proj.weight +24-11-19 20:29:56 | D | - Quantizing model.layers.16.mlp.up_proj.weight +24-11-19 20:29:57 | D | - Quantizing model.layers.16.mlp.gate_proj.weight +24-11-19 20:29:58 | D | - Quantizing model.layers.16.mlp.down_proj.weight +24-11-19 20:30:06 | D | - Quantizing layer model.layers.17 +24-11-19 20:30:06 | D | - Calibrating model.layers.17.self_attn.q_proj.weight +24-11-19 20:30:06 | D | + w: sint8 +24-11-19 20:30:06 | D | + x: None +24-11-19 20:30:06 | D | + y: None +24-11-19 20:30:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:30:06 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:30:06 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:30:06 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:30:06 | D | - range ratio = [ 1.0000] +24-11-19 20:30:06 | D | sum error = [ 11.2874] +24-11-19 20:30:06 | D | best error = [ 11.2874] +24-11-19 20:30:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:19 | D | sum error = [ 11.1776, 11.2499, 11.3871, 11.3689, 11.6749] +24-11-19 20:30:19 | D | best error = [ 11.1776, 11.1776, 11.1776, 11.1776, 11.1776] +24-11-19 20:30:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:19 | D | sum error = [ 11.9869, 12.3483, 12.9324, 13.7605, 14.2206] +24-11-19 20:30:19 | D | best error = [ 11.1776, 11.1776, 11.1776, 11.1776, 11.1776] +24-11-19 20:30:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:19 | D | sum error = [ 14.9806, 16.3399, 17.1178, 18.2580, 19.4232] +24-11-19 20:30:19 | D | best error = [ 11.1776, 11.1776, 11.1776, 11.1776, 11.1776] +24-11-19 20:30:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:19 | D | sum error = [ 20.7758, 22.6103, 24.0887, 26.2143, 28.2621] +24-11-19 20:30:19 | D | best error = [ 11.1776, 11.1776, 11.1776, 11.1776, 11.1776] +24-11-19 20:30:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:19 | D | sum error = [ 30.6814, 33.3217, 35.6103, 38.8176, 41.8950] +24-11-19 20:30:19 | D | best error = [ 11.1776, 11.1776, 11.1776, 11.1776, 11.1776] +24-11-19 20:30:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:19 | D | sum error = [ 45.5449, 49.1863, 53.4176, 57.8631, 62.7246] +24-11-19 20:30:19 | D | best error = [ 11.1776, 11.1776, 11.1776, 11.1776, 11.1776] +24-11-19 20:30:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:19 | D | sum error = [ 67.6571, 73.1398, 79.4108, 86.1634, 92.8336] +24-11-19 20:30:19 | D | best error = [ 11.1776, 11.1776, 11.1776, 11.1776, 11.1776] +24-11-19 20:30:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:19 | D | sum error = [ 100.1084, 108.4538, 117.2673, 126.1947, 135.6519] +24-11-19 20:30:19 | D | best error = [ 11.1776, 11.1776, 11.1776, 11.1776, 11.1776] +24-11-19 20:30:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:19 | D | sum error = [ 145.6564, 156.5424, 168.2035, 180.7309, 193.8584] +24-11-19 20:30:19 | D | best error = [ 11.1776, 11.1776, 11.1776, 11.1776, 11.1776] +24-11-19 20:30:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:19 | D | sum error = [ 208.0298, 223.9479, 240.2456, 257.9807, 277.3614] +24-11-19 20:30:19 | D | best error = [ 11.1776, 11.1776, 11.1776, 11.1776, 11.1776] +24-11-19 20:30:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:19 | D | sum error = [ 297.8958, 320.0291, 343.9172, 369.6460, 397.4245] +24-11-19 20:30:19 | D | best error = [ 11.1776, 11.1776, 11.1776, 11.1776, 11.1776] +24-11-19 20:30:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:19 | D | sum error = [ 427.3848, 459.9165, 494.5339, 532.1839, 573.3037] +24-11-19 20:30:19 | D | best error = [ 11.1776, 11.1776, 11.1776, 11.1776, 11.1776] +24-11-19 20:30:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:19 | D | sum error = [ 617.1843, 665.3869, 718.0088, 774.3614, 835.8561] +24-11-19 20:30:19 | D | best error = [ 11.1776, 11.1776, 11.1776, 11.1776, 11.1776] +24-11-19 20:30:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:19 | D | sum error = [ 903.0269, 976.0589, 1055.7581, 1142.0788, 1237.4037] +24-11-19 20:30:19 | D | best error = [ 11.1776, 11.1776, 11.1776, 11.1776, 11.1776] +24-11-19 20:30:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:19 | D | sum error = [ 1340.3415, 1452.7009, 1574.4484, 1708.0670, 1852.9775] +24-11-19 20:30:19 | D | best error = [ 11.1776, 11.1776, 11.1776, 11.1776, 11.1776] +24-11-19 20:30:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:19 | D | sum error = [ 2009.6413, 2179.2593, 2361.5221, 2556.5227, 2764.7359] +24-11-19 20:30:19 | D | best error = [ 11.1776, 11.1776, 11.1776, 11.1776, 11.1776] +24-11-19 20:30:19 | D | + error = [11.1776] +24-11-19 20:30:19 | D | - Calibrating model.layers.17.self_attn.k_proj.weight +24-11-19 20:30:19 | D | + w: sint8 +24-11-19 20:30:19 | D | + x: None +24-11-19 20:30:19 | D | + y: None +24-11-19 20:30:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:30:19 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:30:19 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:30:20 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:30:20 | D | - range ratio = [ 1.0000] +24-11-19 20:30:20 | D | sum error = [ 11.5115] +24-11-19 20:30:20 | D | best error = [ 11.5115] +24-11-19 20:30:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:33 | D | sum error = [ 11.4713, 11.5427, 11.5970, 12.5601, 13.1356] +24-11-19 20:30:33 | D | best error = [ 11.4713, 11.4713, 11.4713, 11.4713, 11.4713] +24-11-19 20:30:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:33 | D | sum error = [ 13.1653, 13.3931, 13.9081, 14.7352, 15.3763] +24-11-19 20:30:33 | D | best error = [ 11.4713, 11.4713, 11.4713, 11.4713, 11.4713] +24-11-19 20:30:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:33 | D | sum error = [ 16.2156, 17.0981, 18.8132, 20.0809, 20.6817] +24-11-19 20:30:33 | D | best error = [ 11.4713, 11.4713, 11.4713, 11.4713, 11.4713] +24-11-19 20:30:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:33 | D | sum error = [ 22.8647, 24.9363, 26.6753, 28.7623, 30.0737] +24-11-19 20:30:33 | D | best error = [ 11.4713, 11.4713, 11.4713, 11.4713, 11.4713] +24-11-19 20:30:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:33 | D | sum error = [ 33.3790, 36.4493, 38.9320, 41.7189, 45.5670] +24-11-19 20:30:33 | D | best error = [ 11.4713, 11.4713, 11.4713, 11.4713, 11.4713] +24-11-19 20:30:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:33 | D | sum error = [ 48.7793, 53.1256, 57.5315, 60.9966, 65.4193] +24-11-19 20:30:33 | D | best error = [ 11.4713, 11.4713, 11.4713, 11.4713, 11.4713] +24-11-19 20:30:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:33 | D | sum error = [ 71.6099, 76.8302, 82.7116, 88.8434, 96.1728] +24-11-19 20:30:33 | D | best error = [ 11.4713, 11.4713, 11.4713, 11.4713, 11.4713] +24-11-19 20:30:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:33 | D | sum error = [ 102.5632, 109.8083, 118.9124, 127.7869, 137.1972] +24-11-19 20:30:33 | D | best error = [ 11.4713, 11.4713, 11.4713, 11.4713, 11.4713] +24-11-19 20:30:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:33 | D | sum error = [ 146.8873, 157.8360, 169.2998, 181.5698, 194.9879] +24-11-19 20:30:33 | D | best error = [ 11.4713, 11.4713, 11.4713, 11.4713, 11.4713] +24-11-19 20:30:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:33 | D | sum error = [ 209.1758, 224.0654, 240.6750, 258.1257, 277.5317] +24-11-19 20:30:33 | D | best error = [ 11.4713, 11.4713, 11.4713, 11.4713, 11.4713] +24-11-19 20:30:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:33 | D | sum error = [ 296.8130, 320.4343, 344.8229, 369.0005, 396.4470] +24-11-19 20:30:33 | D | best error = [ 11.4713, 11.4713, 11.4713, 11.4713, 11.4713] +24-11-19 20:30:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:33 | D | sum error = [ 426.7383, 458.6665, 494.2636, 533.2152, 575.2851] +24-11-19 20:30:33 | D | best error = [ 11.4713, 11.4713, 11.4713, 11.4713, 11.4713] +24-11-19 20:30:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:33 | D | sum error = [ 621.0039, 670.1560, 724.4733, 783.2981, 847.2089] +24-11-19 20:30:33 | D | best error = [ 11.4713, 11.4713, 11.4713, 11.4713, 11.4713] +24-11-19 20:30:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:33 | D | sum error = [ 914.9411, 989.0549, 1069.3509, 1158.0939, 1253.4571] +24-11-19 20:30:33 | D | best error = [ 11.4713, 11.4713, 11.4713, 11.4713, 11.4713] +24-11-19 20:30:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:33 | D | sum error = [ 1359.1110, 1475.1148, 1600.6228, 1736.4621, 1883.5112] +24-11-19 20:30:33 | D | best error = [ 11.4713, 11.4713, 11.4713, 11.4713, 11.4713] +24-11-19 20:30:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:33 | D | sum error = [ 2043.3726, 2217.2402, 2403.4450, 2603.6178, 2814.5836] +24-11-19 20:30:33 | D | best error = [ 11.4713, 11.4713, 11.4713, 11.4713, 11.4713] +24-11-19 20:30:33 | D | + error = [11.4713] +24-11-19 20:30:33 | D | - Calibrating model.layers.17.self_attn.v_proj.weight +24-11-19 20:30:33 | D | + w: sint8 +24-11-19 20:30:33 | D | + x: None +24-11-19 20:30:33 | D | + y: None +24-11-19 20:30:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:33 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:30:33 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:30:33 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:30:33 | D | - range ratio = [ 1.0000] +24-11-19 20:30:33 | D | sum error = [ 5.5376] +24-11-19 20:30:33 | D | best error = [ 5.5376] +24-11-19 20:30:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:33 | D | sum error = [ 5.4942, 5.4806, 5.5061, 5.5651, 5.6937] +24-11-19 20:30:33 | D | best error = [ 5.1550, 4.9954, 4.9141, 4.8718, 4.8497] +24-11-19 20:30:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:33 | D | sum error = [ 5.8229, 6.0110, 6.2412, 6.5428, 6.8833] +24-11-19 20:30:33 | D | best error = [ 4.8392, 4.8340, 4.8318, 4.8313, 4.8311] +24-11-19 20:30:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:33 | D | sum error = [ 7.2811, 7.7348, 8.2370, 8.7762, 9.3884] +24-11-19 20:30:33 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 20:30:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:33 | D | sum error = [ 10.0648, 10.7883, 11.5539, 12.3650, 13.2501] +24-11-19 20:30:33 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 20:30:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:33 | D | sum error = [ 14.1868, 15.2240, 16.2815, 17.4210, 18.6297] +24-11-19 20:30:33 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 20:30:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:33 | D | sum error = [ 19.8908, 21.2694, 22.7062, 24.2039, 25.8055] +24-11-19 20:30:33 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 20:30:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:33 | D | sum error = [ 27.5117, 29.2931, 31.1964, 33.1693, 35.2812] +24-11-19 20:30:33 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 20:30:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:33 | D | sum error = [ 37.4938, 39.8293, 42.2756, 44.8394, 47.5291] +24-11-19 20:30:33 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 20:30:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:33 | D | sum error = [ 50.3626, 53.3174, 56.4177, 59.6706, 63.0953] +24-11-19 20:30:33 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 20:30:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:33 | D | sum error = [ 66.6625, 70.3791, 74.2846, 78.3590, 82.6270] +24-11-19 20:30:33 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 20:30:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:33 | D | sum error = [ 87.0645, 91.6963, 96.5658, 101.6270, 106.9146] +24-11-19 20:30:33 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 20:30:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:33 | D | sum error = [ 112.3937, 118.1172, 124.0664, 130.2589, 136.7106] +24-11-19 20:30:33 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 20:30:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:33 | D | sum error = [ 143.4157, 150.3915, 157.6544, 165.1637, 172.9629] +24-11-19 20:30:33 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 20:30:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:33 | D | sum error = [ 181.0316, 189.3609, 198.0042, 206.9254, 216.1645] +24-11-19 20:30:33 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 20:30:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:33 | D | sum error = [ 225.7201, 235.5756, 245.7698, 256.2766, 267.1200] +24-11-19 20:30:33 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 20:30:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:33 | D | sum error = [ 278.2846, 289.7909, 301.6311, 313.8290, 326.3607] +24-11-19 20:30:33 | D | best error = [ 4.8310, 4.8310, 4.8310, 4.8310, 4.8310] +24-11-19 20:30:33 | D | + error = [4.8310] +24-11-19 20:30:33 | D | - Calibrating model.layers.17.self_attn.o_proj.weight +24-11-19 20:30:33 | D | + w: sint8 +24-11-19 20:30:33 | D | + x: None +24-11-19 20:30:33 | D | + y: None +24-11-19 20:30:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:33 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:30:34 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:30:34 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:30:34 | D | - range ratio = [ 1.0000] +24-11-19 20:30:34 | D | sum error = [ 1.3725] +24-11-19 20:30:34 | D | best error = [ 1.3725] +24-11-19 20:30:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:34 | D | sum error = [ 1.3638, 1.3564, 1.3555, 1.3639, 1.3790] +24-11-19 20:30:34 | D | best error = [ 1.2851, 1.2440, 1.2185, 1.2033, 1.1921] +24-11-19 20:30:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:34 | D | sum error = [ 1.3976, 1.4286, 1.4697, 1.5178, 1.5851] +24-11-19 20:30:34 | D | best error = [ 1.1842, 1.1787, 1.1743, 1.1711, 1.1691] +24-11-19 20:30:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:34 | D | sum error = [ 1.6488, 1.7345, 1.8277, 1.9289, 2.0453] +24-11-19 20:30:34 | D | best error = [ 1.1673, 1.1659, 1.1646, 1.1638, 1.1631] +24-11-19 20:30:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:34 | D | sum error = [ 2.1721, 2.3093, 2.4597, 2.6253, 2.8003] +24-11-19 20:30:34 | D | best error = [ 1.1624, 1.1618, 1.1614, 1.1610, 1.1607] +24-11-19 20:30:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:34 | D | sum error = [ 2.9865, 3.1919, 3.4064, 3.6358, 3.8814] +24-11-19 20:30:34 | D | best error = [ 1.1605, 1.1604, 1.1603, 1.1601, 1.1599] +24-11-19 20:30:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:34 | D | sum error = [ 4.1375, 4.4122, 4.7086, 5.0189, 5.3484] +24-11-19 20:30:34 | D | best error = [ 1.1599, 1.1598, 1.1598, 1.1597, 1.1597] +24-11-19 20:30:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:34 | D | sum error = [ 5.6973, 6.0646, 6.4549, 6.8677, 7.2989] +24-11-19 20:30:34 | D | best error = [ 1.1597, 1.1597, 1.1597, 1.1597, 1.1597] +24-11-19 20:30:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:34 | D | sum error = [ 7.7603, 8.2427, 8.7549, 9.2929, 9.8584] +24-11-19 20:30:34 | D | best error = [ 1.1597, 1.1597, 1.1597, 1.1597, 1.1597] +24-11-19 20:30:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:34 | D | sum error = [ 10.4548, 11.0862, 11.7465, 12.4379, 13.1708] +24-11-19 20:30:34 | D | best error = [ 1.1597, 1.1597, 1.1597, 1.1597, 1.1597] +24-11-19 20:30:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:34 | D | sum error = [ 13.9359, 14.7389, 15.5798, 16.4613, 17.3869] +24-11-19 20:30:34 | D | best error = [ 1.1597, 1.1597, 1.1597, 1.1597, 1.1597] +24-11-19 20:30:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:34 | D | sum error = [ 18.3561, 19.3754, 20.4408, 21.5557, 22.7179] +24-11-19 20:30:34 | D | best error = [ 1.1597, 1.1597, 1.1597, 1.1597, 1.1597] +24-11-19 20:30:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:34 | D | sum error = [ 23.9317, 25.1968, 26.5210, 27.8995, 29.3340] +24-11-19 20:30:34 | D | best error = [ 1.1597, 1.1597, 1.1597, 1.1597, 1.1597] +24-11-19 20:30:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:34 | D | sum error = [ 30.8299, 32.3879, 34.0123, 35.7023, 37.4608] +24-11-19 20:30:34 | D | best error = [ 1.1597, 1.1597, 1.1597, 1.1597, 1.1597] +24-11-19 20:30:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:34 | D | sum error = [ 39.2849, 41.1800, 43.1460, 45.1873, 47.2981] +24-11-19 20:30:34 | D | best error = [ 1.1597, 1.1597, 1.1597, 1.1597, 1.1597] +24-11-19 20:30:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:34 | D | sum error = [ 49.4856, 51.7482, 54.0892, 56.5150, 59.0270] +24-11-19 20:30:34 | D | best error = [ 1.1597, 1.1597, 1.1597, 1.1597, 1.1597] +24-11-19 20:30:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:34 | D | sum error = [ 61.6199, 64.3012, 67.0707, 69.9310, 72.8778] +24-11-19 20:30:34 | D | best error = [ 1.1597, 1.1597, 1.1597, 1.1597, 1.1597] +24-11-19 20:30:34 | D | + error = [1.1597] +24-11-19 20:30:34 | D | - Calibrating model.layers.17.mlp.up_proj.weight +24-11-19 20:30:34 | D | + w: sint8 +24-11-19 20:30:34 | D | + x: None +24-11-19 20:30:34 | D | + y: None +24-11-19 20:30:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:34 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:30:34 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:30:34 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:30:34 | D | - range ratio = [ 1.0000] +24-11-19 20:30:34 | D | sum error = [ 7.8793] +24-11-19 20:30:34 | D | best error = [ 7.8793] +24-11-19 20:30:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:35 | D | sum error = [ 7.8203, 7.8244, 7.8414, 7.9088, 8.0735] +24-11-19 20:30:35 | D | best error = [ 7.3242, 7.1114, 6.9980, 6.9309, 6.8962] +24-11-19 20:30:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:35 | D | sum error = [ 8.2727, 8.5572, 8.8967, 9.3023, 9.8444] +24-11-19 20:30:35 | D | best error = [ 6.8796, 6.8726, 6.8702, 6.8697, 6.8695] +24-11-19 20:30:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:35 | D | sum error = [ 10.3899, 11.0342, 11.7506, 12.5610, 13.4180] +24-11-19 20:30:35 | D | best error = [ 6.8694, 6.8694, 6.8694, 6.8694, 6.8694] +24-11-19 20:30:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:35 | D | sum error = [ 14.3965, 15.4035, 16.5072, 17.7056, 18.9548] +24-11-19 20:30:35 | D | best error = [ 6.8694, 6.8694, 6.8694, 6.8694, 6.8694] +24-11-19 20:30:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:35 | D | sum error = [ 20.3272, 21.7517, 23.3202, 24.9175, 26.6673] +24-11-19 20:30:35 | D | best error = [ 6.8694, 6.8694, 6.8694, 6.8694, 6.8694] +24-11-19 20:30:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:35 | D | sum error = [ 28.5003, 30.4396, 32.4944, 34.6782, 36.9683] +24-11-19 20:30:35 | D | best error = [ 6.8694, 6.8694, 6.8694, 6.8694, 6.8694] +24-11-19 20:30:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:35 | D | sum error = [ 39.3953, 41.9773, 44.6612, 47.5101, 50.5242] +24-11-19 20:30:35 | D | best error = [ 6.8694, 6.8694, 6.8694, 6.8694, 6.8694] +24-11-19 20:30:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:35 | D | sum error = [ 53.6970, 57.0252, 60.5334, 64.2121, 68.0841] +24-11-19 20:30:35 | D | best error = [ 6.8694, 6.8694, 6.8694, 6.8694, 6.8694] +24-11-19 20:30:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:35 | D | sum error = [ 72.1469, 76.4348, 80.9171, 85.6104, 90.5052] +24-11-19 20:30:35 | D | best error = [ 6.8694, 6.8694, 6.8694, 6.8694, 6.8694] +24-11-19 20:30:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:35 | D | sum error = [ 95.6863, 101.0862, 106.7305, 112.6271, 118.8085] +24-11-19 20:30:35 | D | best error = [ 6.8694, 6.8694, 6.8694, 6.8694, 6.8694] +24-11-19 20:30:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:35 | D | sum error = [ 125.2804, 132.0199, 139.0490, 146.4069, 154.0897] +24-11-19 20:30:35 | D | best error = [ 6.8694, 6.8694, 6.8694, 6.8694, 6.8694] +24-11-19 20:30:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:35 | D | sum error = [ 162.1183, 170.4566, 179.1309, 188.1943, 197.6249] +24-11-19 20:30:35 | D | best error = [ 6.8694, 6.8694, 6.8694, 6.8694, 6.8694] +24-11-19 20:30:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:35 | D | sum error = [ 207.4272, 217.6192, 228.2165, 239.2179, 250.6392] +24-11-19 20:30:35 | D | best error = [ 6.8694, 6.8694, 6.8694, 6.8694, 6.8694] +24-11-19 20:30:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:35 | D | sum error = [ 262.4970, 274.7874, 287.5379, 300.7570, 314.4238] +24-11-19 20:30:35 | D | best error = [ 6.8694, 6.8694, 6.8694, 6.8694, 6.8694] +24-11-19 20:30:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:35 | D | sum error = [ 328.5854, 343.2067, 358.3020, 373.8925, 390.0011] +24-11-19 20:30:35 | D | best error = [ 6.8694, 6.8694, 6.8694, 6.8694, 6.8694] +24-11-19 20:30:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:35 | D | sum error = [ 406.6065, 423.7422, 441.3852, 459.5397, 478.2092] +24-11-19 20:30:35 | D | best error = [ 6.8694, 6.8694, 6.8694, 6.8694, 6.8694] +24-11-19 20:30:35 | D | + error = [6.8694] +24-11-19 20:30:35 | D | - Calibrating model.layers.17.mlp.gate_proj.weight +24-11-19 20:30:35 | D | + w: sint8 +24-11-19 20:30:35 | D | + x: None +24-11-19 20:30:35 | D | + y: None +24-11-19 20:30:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:35 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:30:36 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:30:36 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:30:36 | D | - range ratio = [ 1.0000] +24-11-19 20:30:36 | D | sum error = [ 8.2312] +24-11-19 20:30:36 | D | best error = [ 8.2312] +24-11-19 20:30:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:37 | D | sum error = [ 8.1933, 8.1539, 8.1854, 8.2712, 8.4389] +24-11-19 20:30:37 | D | best error = [ 7.6672, 7.4398, 7.3181, 7.2480, 7.2122] +24-11-19 20:30:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:37 | D | sum error = [ 8.6628, 8.9529, 9.3201, 9.7596, 10.2717] +24-11-19 20:30:37 | D | best error = [ 7.1937, 7.1856, 7.1830, 7.1819, 7.1816] +24-11-19 20:30:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:37 | D | sum error = [ 10.8831, 11.5594, 12.3074, 13.1651, 14.0808] +24-11-19 20:30:37 | D | best error = [ 7.1816, 7.1816, 7.1816, 7.1816, 7.1816] +24-11-19 20:30:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:37 | D | sum error = [ 15.0922, 16.1779, 17.3444, 18.5933, 19.9577] +24-11-19 20:30:37 | D | best error = [ 7.1816, 7.1816, 7.1816, 7.1816, 7.1816] +24-11-19 20:30:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:37 | D | sum error = [ 21.4022, 22.9657, 24.5870, 26.3676, 28.2494] +24-11-19 20:30:37 | D | best error = [ 7.1816, 7.1816, 7.1816, 7.1816, 7.1816] +24-11-19 20:30:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:37 | D | sum error = [ 30.2571, 32.3700, 34.6297, 37.0334, 39.5556] +24-11-19 20:30:37 | D | best error = [ 7.1816, 7.1816, 7.1816, 7.1816, 7.1816] +24-11-19 20:30:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:37 | D | sum error = [ 42.2400, 45.0808, 48.0881, 51.2753, 54.6917] +24-11-19 20:30:37 | D | best error = [ 7.1816, 7.1816, 7.1816, 7.1816, 7.1816] +24-11-19 20:30:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:37 | D | sum error = [ 58.2387, 62.0137, 66.0087, 70.2172, 74.6780] +24-11-19 20:30:37 | D | best error = [ 7.1816, 7.1816, 7.1816, 7.1816, 7.1816] +24-11-19 20:30:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:37 | D | sum error = [ 79.3871, 84.3518, 89.5681, 95.1276, 100.9759] +24-11-19 20:30:37 | D | best error = [ 7.1816, 7.1816, 7.1816, 7.1816, 7.1816] +24-11-19 20:30:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:37 | D | sum error = [ 107.1444, 113.6638, 120.5260, 127.7810, 135.4124] +24-11-19 20:30:37 | D | best error = [ 7.1816, 7.1816, 7.1816, 7.1816, 7.1816] +24-11-19 20:30:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:37 | D | sum error = [ 143.4819, 151.9871, 160.9214, 170.3154, 180.1710] +24-11-19 20:30:37 | D | best error = [ 7.1816, 7.1816, 7.1816, 7.1816, 7.1816] +24-11-19 20:30:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:37 | D | sum error = [ 190.5750, 201.4928, 212.9537, 224.9952, 237.5945] +24-11-19 20:30:37 | D | best error = [ 7.1816, 7.1816, 7.1816, 7.1816, 7.1816] +24-11-19 20:30:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:37 | D | sum error = [ 250.7850, 264.6212, 279.1211, 294.2559, 310.0608] +24-11-19 20:30:37 | D | best error = [ 7.1816, 7.1816, 7.1816, 7.1816, 7.1816] +24-11-19 20:30:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:37 | D | sum error = [ 326.5850, 343.8023, 361.7597, 380.4338, 399.8674] +24-11-19 20:30:37 | D | best error = [ 7.1816, 7.1816, 7.1816, 7.1816, 7.1816] +24-11-19 20:30:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:37 | D | sum error = [ 420.0749, 441.0621, 462.8436, 485.4087, 508.7772] +24-11-19 20:30:37 | D | best error = [ 7.1816, 7.1816, 7.1816, 7.1816, 7.1816] +24-11-19 20:30:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:37 | D | sum error = [ 532.9526, 557.9680, 583.7628, 610.3536, 637.7668] +24-11-19 20:30:37 | D | best error = [ 7.1816, 7.1816, 7.1816, 7.1816, 7.1816] +24-11-19 20:30:37 | D | + error = [7.1816] +24-11-19 20:30:37 | D | - Calibrating model.layers.17.mlp.down_proj.weight +24-11-19 20:30:37 | D | + w: sint8 +24-11-19 20:30:37 | D | + x: None +24-11-19 20:30:37 | D | + y: None +24-11-19 20:30:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:37 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:30:37 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:30:37 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:30:37 | D | - range ratio = [ 1.0000] +24-11-19 20:30:37 | D | sum error = [ 2.6173] +24-11-19 20:30:37 | D | best error = [ 2.6173] +24-11-19 20:30:38 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:38 | D | sum error = [ 2.5871, 2.5730, 2.5638, 2.5515, 2.5507] +24-11-19 20:30:38 | D | best error = [ 2.5151, 2.4675, 2.4349, 2.4083, 2.3880] +24-11-19 20:30:38 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:38 | D | sum error = [ 2.5638, 2.5829, 2.6087, 2.6592, 2.7126] +24-11-19 20:30:38 | D | best error = [ 2.3736, 2.3634, 2.3550, 2.3494, 2.3452] +24-11-19 20:30:38 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:38 | D | sum error = [ 2.7865, 2.8663, 2.9666, 3.0961, 3.2343] +24-11-19 20:30:38 | D | best error = [ 2.3426, 2.3409, 2.3397, 2.3390, 2.3385] +24-11-19 20:30:38 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:38 | D | sum error = [ 3.3906, 3.5706, 3.7743, 3.9966, 4.2453] +24-11-19 20:30:38 | D | best error = [ 2.3381, 2.3379, 2.3377, 2.3377, 2.3376] +24-11-19 20:30:38 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:38 | D | sum error = [ 4.5161, 4.8051, 5.1277, 5.4675, 5.8449] +24-11-19 20:30:38 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 20:30:38 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:38 | D | sum error = [ 6.2423, 6.6704, 7.1342, 7.6249, 8.1523] +24-11-19 20:30:38 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 20:30:38 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:38 | D | sum error = [ 8.7130, 9.3134, 9.9484, 10.6255, 11.3435] +24-11-19 20:30:38 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 20:30:38 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:38 | D | sum error = [ 12.1073, 12.9191, 13.7810, 14.6846, 15.6473] +24-11-19 20:30:38 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 20:30:38 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:38 | D | sum error = [ 16.6656, 17.7404, 18.8722, 20.0745, 21.3380] +24-11-19 20:30:38 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 20:30:38 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:38 | D | sum error = [ 22.6729, 24.0712, 25.5459, 27.0983, 28.7259] +24-11-19 20:30:38 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 20:30:38 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:38 | D | sum error = [ 30.4390, 32.2393, 34.1250, 36.1084, 38.1836] +24-11-19 20:30:38 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 20:30:38 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:38 | D | sum error = [ 40.3607, 42.6393, 45.0299, 47.5250, 50.1365] +24-11-19 20:30:38 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 20:30:38 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:38 | D | sum error = [ 52.8695, 55.7157, 58.6930, 61.7940, 65.0305] +24-11-19 20:30:38 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 20:30:38 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:38 | D | sum error = [ 68.3979, 71.9088, 75.5605, 79.3669, 83.3050] +24-11-19 20:30:38 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 20:30:38 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:38 | D | sum error = [ 87.4014, 91.6531, 96.0630, 100.6338, 105.3683] +24-11-19 20:30:38 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 20:30:38 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:38 | D | sum error = [ 110.2719, 115.3438, 120.5885, 126.0144, 131.6194] +24-11-19 20:30:38 | D | best error = [ 2.3376, 2.3376, 2.3376, 2.3376, 2.3376] +24-11-19 20:30:38 | D | + error = [2.3376] +24-11-19 20:30:38 | D | - Quantizing model.layers.17.self_attn.q_proj.weight +24-11-19 20:30:39 | D | - Quantizing model.layers.17.self_attn.k_proj.weight +24-11-19 20:30:40 | D | - Quantizing model.layers.17.self_attn.v_proj.weight +24-11-19 20:30:41 | D | - Quantizing model.layers.17.self_attn.o_proj.weight +24-11-19 20:30:41 | D | - Quantizing model.layers.17.mlp.up_proj.weight +24-11-19 20:30:42 | D | - Quantizing model.layers.17.mlp.gate_proj.weight +24-11-19 20:30:43 | D | - Quantizing model.layers.17.mlp.down_proj.weight +24-11-19 20:30:51 | D | - Quantizing layer model.layers.18 +24-11-19 20:30:51 | D | - Calibrating model.layers.18.self_attn.q_proj.weight +24-11-19 20:30:51 | D | + w: sint8 +24-11-19 20:30:51 | D | + x: None +24-11-19 20:30:51 | D | + y: None +24-11-19 20:30:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:30:51 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:30:51 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:30:52 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:30:52 | D | - range ratio = [ 1.0000] +24-11-19 20:30:52 | D | sum error = [ 12.1187] +24-11-19 20:30:52 | D | best error = [ 12.1187] +24-11-19 20:31:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:04 | D | sum error = [ 11.9866, 12.1137, 12.1000, 12.2165, 12.4994] +24-11-19 20:31:04 | D | best error = [ 11.9866, 11.9866, 11.9866, 11.9866, 11.9866] +24-11-19 20:31:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:04 | D | sum error = [ 13.0800, 13.3954, 14.3088, 15.2991, 15.8525] +24-11-19 20:31:04 | D | best error = [ 11.9866, 11.9866, 11.9866, 11.9866, 11.9866] +24-11-19 20:31:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:04 | D | sum error = [ 16.5898, 17.9994, 19.1405, 20.3459, 22.0594] +24-11-19 20:31:04 | D | best error = [ 11.9866, 11.9866, 11.9866, 11.9866, 11.9866] +24-11-19 20:31:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:04 | D | sum error = [ 23.3450, 25.4156, 27.2632, 29.2974, 32.0064] +24-11-19 20:31:04 | D | best error = [ 11.9866, 11.9866, 11.9866, 11.9866, 11.9866] +24-11-19 20:31:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:04 | D | sum error = [ 34.3123, 37.6560, 40.6379, 43.9115, 47.3948] +24-11-19 20:31:04 | D | best error = [ 11.9866, 11.9866, 11.9866, 11.9866, 11.9866] +24-11-19 20:31:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:04 | D | sum error = [ 51.0474, 55.4959, 59.8253, 64.4161, 69.1905] +24-11-19 20:31:04 | D | best error = [ 11.9866, 11.9866, 11.9866, 11.9866, 11.9866] +24-11-19 20:31:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:04 | D | sum error = [ 74.6774, 80.9432, 87.0107, 93.7345, 100.9552] +24-11-19 20:31:04 | D | best error = [ 11.9866, 11.9866, 11.9866, 11.9866, 11.9866] +24-11-19 20:31:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:04 | D | sum error = [ 109.1409, 117.5174, 127.3997, 136.9722, 147.6918] +24-11-19 20:31:04 | D | best error = [ 11.9866, 11.9866, 11.9866, 11.9866, 11.9866] +24-11-19 20:31:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:04 | D | sum error = [ 159.2855, 171.6619, 184.7332, 198.5931, 213.8481] +24-11-19 20:31:04 | D | best error = [ 11.9866, 11.9866, 11.9866, 11.9866, 11.9866] +24-11-19 20:31:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:04 | D | sum error = [ 230.2760, 247.8567, 266.9481, 287.1515, 308.7076] +24-11-19 20:31:04 | D | best error = [ 11.9866, 11.9866, 11.9866, 11.9866, 11.9866] +24-11-19 20:31:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:04 | D | sum error = [ 331.9490, 357.0971, 384.2677, 413.7673, 445.0944] +24-11-19 20:31:04 | D | best error = [ 11.9866, 11.9866, 11.9866, 11.9866, 11.9866] +24-11-19 20:31:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:04 | D | sum error = [ 479.6162, 516.2103, 556.1150, 600.0734, 646.8749] +24-11-19 20:31:04 | D | best error = [ 11.9866, 11.9866, 11.9866, 11.9866, 11.9866] +24-11-19 20:31:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:04 | D | sum error = [ 698.9466, 755.4048, 817.5110, 884.7068, 959.1561] +24-11-19 20:31:04 | D | best error = [ 11.9866, 11.9866, 11.9866, 11.9866, 11.9866] +24-11-19 20:31:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:04 | D | sum error = [ 1040.8525, 1130.8658, 1226.6398, 1334.4759, 1452.3388] +24-11-19 20:31:04 | D | best error = [ 11.9866, 11.9866, 11.9866, 11.9866, 11.9866] +24-11-19 20:31:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:04 | D | sum error = [ 1582.2858, 1725.4370, 1880.9159, 2052.7840, 2240.8964] +24-11-19 20:31:04 | D | best error = [ 11.9866, 11.9866, 11.9866, 11.9866, 11.9866] +24-11-19 20:31:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:04 | D | sum error = [ 2447.9875, 2672.8452, 2915.5349, 3176.7210, 3454.5674] +24-11-19 20:31:04 | D | best error = [ 11.9866, 11.9866, 11.9866, 11.9866, 11.9866] +24-11-19 20:31:04 | D | + error = [11.9866] +24-11-19 20:31:05 | D | - Calibrating model.layers.18.self_attn.k_proj.weight +24-11-19 20:31:05 | D | + w: sint8 +24-11-19 20:31:05 | D | + x: None +24-11-19 20:31:05 | D | + y: None +24-11-19 20:31:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:31:05 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:31:05 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:31:05 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:31:05 | D | - range ratio = [ 1.0000] +24-11-19 20:31:05 | D | sum error = [ 13.6475] +24-11-19 20:31:05 | D | best error = [ 13.6475] +24-11-19 20:31:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:18 | D | sum error = [ 13.1390, 12.7666, 13.4902, 13.2758, 13.3516] +24-11-19 20:31:18 | D | best error = [ 13.1390, 12.7666, 12.7666, 12.7666, 12.7666] +24-11-19 20:31:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:18 | D | sum error = [ 14.1378, 13.8120, 16.2789, 15.4789, 16.4827] +24-11-19 20:31:18 | D | best error = [ 12.7666, 12.7666, 12.7666, 12.7666, 12.7666] +24-11-19 20:31:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:18 | D | sum error = [ 17.0921, 18.7076, 20.3318, 20.9506, 22.4322] +24-11-19 20:31:18 | D | best error = [ 12.7666, 12.7666, 12.7666, 12.7666, 12.7666] +24-11-19 20:31:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:18 | D | sum error = [ 24.2554, 26.1090, 28.5386, 31.1394, 32.7010] +24-11-19 20:31:18 | D | best error = [ 12.7666, 12.7666, 12.7666, 12.7666, 12.7666] +24-11-19 20:31:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:18 | D | sum error = [ 36.4812, 39.6252, 42.4504, 46.1373, 49.7365] +24-11-19 20:31:18 | D | best error = [ 12.7666, 12.7666, 12.7666, 12.7666, 12.7666] +24-11-19 20:31:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:18 | D | sum error = [ 53.6755, 57.5758, 61.5408, 65.3708, 70.3446] +24-11-19 20:31:18 | D | best error = [ 12.7666, 12.7666, 12.7666, 12.7666, 12.7666] +24-11-19 20:31:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:18 | D | sum error = [ 75.2154, 81.3653, 87.2812, 93.5302, 99.5447] +24-11-19 20:31:18 | D | best error = [ 12.7666, 12.7666, 12.7666, 12.7666, 12.7666] +24-11-19 20:31:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:18 | D | sum error = [ 106.3788, 114.9597, 123.1649, 131.2965, 140.7017] +24-11-19 20:31:18 | D | best error = [ 12.7666, 12.7666, 12.7666, 12.7666, 12.7666] +24-11-19 20:31:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:18 | D | sum error = [ 152.1049, 162.6131, 175.9407, 188.9904, 204.2952] +24-11-19 20:31:18 | D | best error = [ 12.7666, 12.7666, 12.7666, 12.7666, 12.7666] +24-11-19 20:31:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:18 | D | sum error = [ 221.4246, 238.5254, 257.8629, 278.7431, 302.1197] +24-11-19 20:31:18 | D | best error = [ 12.7666, 12.7666, 12.7666, 12.7666, 12.7666] +24-11-19 20:31:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:18 | D | sum error = [ 326.8275, 353.2168, 382.9253, 412.1327, 444.8309] +24-11-19 20:31:18 | D | best error = [ 12.7666, 12.7666, 12.7666, 12.7666, 12.7666] +24-11-19 20:31:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:18 | D | sum error = [ 480.6465, 519.5437, 559.8955, 603.6103, 651.0126] +24-11-19 20:31:18 | D | best error = [ 12.7666, 12.7666, 12.7666, 12.7666, 12.7666] +24-11-19 20:31:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:18 | D | sum error = [ 704.4244, 759.7623, 821.5061, 889.6639, 965.2814] +24-11-19 20:31:18 | D | best error = [ 12.7666, 12.7666, 12.7666, 12.7666, 12.7666] +24-11-19 20:31:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:18 | D | sum error = [ 1044.4634, 1133.5428, 1231.7447, 1340.9123, 1460.2742] +24-11-19 20:31:18 | D | best error = [ 12.7666, 12.7666, 12.7666, 12.7666, 12.7666] +24-11-19 20:31:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:18 | D | sum error = [ 1591.4114, 1737.5120, 1898.5186, 2075.4561, 2265.6054] +24-11-19 20:31:18 | D | best error = [ 12.7666, 12.7666, 12.7666, 12.7666, 12.7666] +24-11-19 20:31:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:18 | D | sum error = [ 2473.6343, 2700.1456, 2944.5217, 3210.1847, 3491.9728] +24-11-19 20:31:18 | D | best error = [ 12.7666, 12.7666, 12.7666, 12.7666, 12.7666] +24-11-19 20:31:18 | D | + error = [12.7666] +24-11-19 20:31:18 | D | - Calibrating model.layers.18.self_attn.v_proj.weight +24-11-19 20:31:18 | D | + w: sint8 +24-11-19 20:31:18 | D | + x: None +24-11-19 20:31:18 | D | + y: None +24-11-19 20:31:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:18 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:31:18 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:31:18 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:31:18 | D | - range ratio = [ 1.0000] +24-11-19 20:31:18 | D | sum error = [ 6.0866] +24-11-19 20:31:18 | D | best error = [ 6.0866] +24-11-19 20:31:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:19 | D | sum error = [ 6.0342, 6.0291, 6.0671, 6.1263, 6.2388] +24-11-19 20:31:19 | D | best error = [ 5.6818, 5.5202, 5.4348, 5.3879, 5.3640] +24-11-19 20:31:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:19 | D | sum error = [ 6.3997, 6.6333, 6.8715, 7.2200, 7.6201] +24-11-19 20:31:19 | D | best error = [ 5.3495, 5.3444, 5.3422, 5.3417, 5.3417] +24-11-19 20:31:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:19 | D | sum error = [ 8.0337, 8.5452, 9.1213, 9.7220, 10.4058] +24-11-19 20:31:19 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:31:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:19 | D | sum error = [ 11.1612, 11.9249, 12.7925, 13.7019, 14.6903] +24-11-19 20:31:19 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:31:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:19 | D | sum error = [ 15.7474, 16.8738, 18.0185, 19.2813, 20.6475] +24-11-19 20:31:19 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:31:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:19 | D | sum error = [ 22.0405, 23.5527, 25.1445, 26.7865, 28.5424] +24-11-19 20:31:19 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:31:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:19 | D | sum error = [ 30.4294, 32.3933, 34.4412, 36.6369, 38.9143] +24-11-19 20:31:19 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:31:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:19 | D | sum error = [ 41.3303, 43.8757, 46.5508, 49.3767, 52.3310] +24-11-19 20:31:19 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:31:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:19 | D | sum error = [ 55.4406, 58.6854, 62.0819, 65.6542, 69.3928] +24-11-19 20:31:19 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:31:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:19 | D | sum error = [ 73.3313, 77.4604, 81.7664, 86.2465, 90.9615] +24-11-19 20:31:19 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:31:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:19 | D | sum error = [ 95.8779, 100.9986, 106.3714, 111.9517, 117.7610] +24-11-19 20:31:19 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:31:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:19 | D | sum error = [ 123.8242, 130.1268, 136.6958, 143.5236, 150.6368] +24-11-19 20:31:19 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:31:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:19 | D | sum error = [ 158.0031, 165.6426, 173.5729, 181.8310, 190.3731] +24-11-19 20:31:19 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:31:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:19 | D | sum error = [ 199.2449, 208.4081, 217.8925, 227.7165, 237.8582] +24-11-19 20:31:19 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:31:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:19 | D | sum error = [ 248.3494, 259.1772, 270.3611, 281.8984, 293.8020] +24-11-19 20:31:19 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:31:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:19 | D | sum error = [ 306.0658, 318.6889, 331.6925, 345.0595, 358.8038] +24-11-19 20:31:19 | D | best error = [ 5.3416, 5.3416, 5.3416, 5.3416, 5.3416] +24-11-19 20:31:19 | D | + error = [5.3416] +24-11-19 20:31:19 | D | - Calibrating model.layers.18.self_attn.o_proj.weight +24-11-19 20:31:19 | D | + w: sint8 +24-11-19 20:31:19 | D | + x: None +24-11-19 20:31:19 | D | + y: None +24-11-19 20:31:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:19 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:31:19 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:31:19 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:31:19 | D | - range ratio = [ 1.0000] +24-11-19 20:31:19 | D | sum error = [ 1.5069] +24-11-19 20:31:19 | D | best error = [ 1.5069] +24-11-19 20:31:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:19 | D | sum error = [ 1.4956, 1.4866, 1.4836, 1.4936, 1.5133] +24-11-19 20:31:19 | D | best error = [ 1.4179, 1.3751, 1.3492, 1.3327, 1.3218] +24-11-19 20:31:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:19 | D | sum error = [ 1.5351, 1.5718, 1.6156, 1.6715, 1.7379] +24-11-19 20:31:19 | D | best error = [ 1.3149, 1.3094, 1.3060, 1.3035, 1.3018] +24-11-19 20:31:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:19 | D | sum error = [ 1.8182, 1.9072, 2.0058, 2.1268, 2.2479] +24-11-19 20:31:19 | D | best error = [ 1.3005, 1.2996, 1.2988, 1.2981, 1.2977] +24-11-19 20:31:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:19 | D | sum error = [ 2.3889, 2.5434, 2.7091, 2.8907, 3.0868] +24-11-19 20:31:19 | D | best error = [ 1.2975, 1.2973, 1.2971, 1.2971, 1.2970] +24-11-19 20:31:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:19 | D | sum error = [ 3.2966, 3.5149, 3.7554, 4.0125, 4.2859] +24-11-19 20:31:19 | D | best error = [ 1.2969, 1.2968, 1.2968, 1.2967, 1.2967] +24-11-19 20:31:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:19 | D | sum error = [ 4.5709, 4.8771, 5.2067, 5.5474, 5.9174] +24-11-19 20:31:19 | D | best error = [ 1.2967, 1.2967, 1.2967, 1.2967, 1.2967] +24-11-19 20:31:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:19 | D | sum error = [ 6.3037, 6.7162, 7.1466, 7.6023, 8.0877] +24-11-19 20:31:19 | D | best error = [ 1.2967, 1.2967, 1.2967, 1.2967, 1.2967] +24-11-19 20:31:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:19 | D | sum error = [ 8.5990, 9.1393, 9.7028, 10.2995, 10.9338] +24-11-19 20:31:19 | D | best error = [ 1.2967, 1.2967, 1.2967, 1.2967, 1.2967] +24-11-19 20:31:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:19 | D | sum error = [ 11.5926, 12.2943, 13.0284, 13.7964, 14.6091] +24-11-19 20:31:19 | D | best error = [ 1.2967, 1.2967, 1.2967, 1.2967, 1.2967] +24-11-19 20:31:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:19 | D | sum error = [ 15.4593, 16.3531, 17.2910, 18.2743, 19.3072] +24-11-19 20:31:19 | D | best error = [ 1.2967, 1.2967, 1.2967, 1.2967, 1.2967] +24-11-19 20:31:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:19 | D | sum error = [ 20.3858, 21.5175, 22.7043, 23.9462, 25.2469] +24-11-19 20:31:19 | D | best error = [ 1.2967, 1.2967, 1.2967, 1.2967, 1.2967] +24-11-19 20:31:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:19 | D | sum error = [ 26.6030, 28.0207, 29.5029, 31.0503, 32.6675] +24-11-19 20:31:19 | D | best error = [ 1.2967, 1.2967, 1.2967, 1.2967, 1.2967] +24-11-19 20:31:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:19 | D | sum error = [ 34.3486, 36.1018, 37.9295, 39.8314, 41.8084] +24-11-19 20:31:19 | D | best error = [ 1.2967, 1.2967, 1.2967, 1.2967, 1.2967] +24-11-19 20:31:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:19 | D | sum error = [ 43.8663, 46.0021, 48.2237, 50.5322, 52.9238] +24-11-19 20:31:19 | D | best error = [ 1.2967, 1.2967, 1.2967, 1.2967, 1.2967] +24-11-19 20:31:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:19 | D | sum error = [ 55.4087, 57.9793, 60.6412, 63.3966, 66.2459] +24-11-19 20:31:19 | D | best error = [ 1.2967, 1.2967, 1.2967, 1.2967, 1.2967] +24-11-19 20:31:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:19 | D | sum error = [ 69.1912, 72.2328, 75.3768, 78.6238, 81.9721] +24-11-19 20:31:19 | D | best error = [ 1.2967, 1.2967, 1.2967, 1.2967, 1.2967] +24-11-19 20:31:19 | D | + error = [1.2967] +24-11-19 20:31:19 | D | - Calibrating model.layers.18.mlp.up_proj.weight +24-11-19 20:31:19 | D | + w: sint8 +24-11-19 20:31:19 | D | + x: None +24-11-19 20:31:19 | D | + y: None +24-11-19 20:31:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:19 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:31:19 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:31:20 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:31:20 | D | - range ratio = [ 1.0000] +24-11-19 20:31:20 | D | sum error = [ 8.2844] +24-11-19 20:31:20 | D | best error = [ 8.2844] +24-11-19 20:31:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:21 | D | sum error = [ 8.2267, 8.1978, 8.2434, 8.3212, 8.4733] +24-11-19 20:31:21 | D | best error = [ 7.7101, 7.4805, 7.3631, 7.2950, 7.2569] +24-11-19 20:31:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:21 | D | sum error = [ 8.6932, 8.9808, 9.3397, 9.7962, 10.2957] +24-11-19 20:31:21 | D | best error = [ 7.2389, 7.2305, 7.2280, 7.2268, 7.2266] +24-11-19 20:31:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:21 | D | sum error = [ 10.8957, 11.5480, 12.3120, 13.1350, 14.0383] +24-11-19 20:31:21 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:31:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:21 | D | sum error = [ 15.0213, 16.0826, 17.2448, 18.4578, 19.8005] +24-11-19 20:31:21 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:31:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:21 | D | sum error = [ 21.1859, 22.7119, 24.2951, 25.9930, 27.8194] +24-11-19 20:31:21 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:31:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:21 | D | sum error = [ 29.7322, 31.7577, 33.9132, 36.1797, 38.5928] +24-11-19 20:31:21 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:31:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:21 | D | sum error = [ 41.1137, 43.7736, 46.6004, 49.5582, 52.6961] +24-11-19 20:31:21 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:31:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:21 | D | sum error = [ 55.9811, 59.4738, 63.1151, 66.9604, 70.9934] +24-11-19 20:31:21 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:31:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:21 | D | sum error = [ 75.2213, 79.6634, 84.3145, 89.2121, 94.3414] +24-11-19 20:31:21 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:31:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:21 | D | sum error = [ 99.7013, 105.3106, 111.1992, 117.3500, 123.7898] +24-11-19 20:31:21 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:31:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:21 | D | sum error = [ 130.4966, 137.5309, 144.8584, 152.5443, 160.5271] +24-11-19 20:31:21 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:31:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:21 | D | sum error = [ 168.8732, 177.5589, 186.6132, 196.0291, 205.8105] +24-11-19 20:31:21 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:31:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:21 | D | sum error = [ 215.9806, 226.5492, 237.5224, 248.9135, 260.7200] +24-11-19 20:31:21 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:31:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:21 | D | sum error = [ 272.9727, 285.6830, 298.8574, 312.4881, 326.6145] +24-11-19 20:31:21 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:31:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:21 | D | sum error = [ 341.2037, 356.3025, 371.8952, 387.9979, 404.5947] +24-11-19 20:31:21 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:31:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:21 | D | sum error = [ 421.7203, 439.3647, 457.5263, 476.2225, 495.4483] +24-11-19 20:31:21 | D | best error = [ 7.2266, 7.2266, 7.2266, 7.2266, 7.2266] +24-11-19 20:31:21 | D | + error = [7.2266] +24-11-19 20:31:21 | D | - Calibrating model.layers.18.mlp.gate_proj.weight +24-11-19 20:31:21 | D | + w: sint8 +24-11-19 20:31:21 | D | + x: None +24-11-19 20:31:21 | D | + y: None +24-11-19 20:31:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:21 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:31:21 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:31:21 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:31:21 | D | - range ratio = [ 1.0000] +24-11-19 20:31:21 | D | sum error = [ 8.7726] +24-11-19 20:31:21 | D | best error = [ 8.7726] +24-11-19 20:31:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:22 | D | sum error = [ 8.7090, 8.6796, 8.7033, 8.7893, 8.9787] +24-11-19 20:31:22 | D | best error = [ 8.1659, 7.9330, 7.8033, 7.7278, 7.6872] +24-11-19 20:31:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:22 | D | sum error = [ 9.2119, 9.5062, 9.9063, 10.3619, 10.9341] +24-11-19 20:31:22 | D | best error = [ 7.6671, 7.6586, 7.6558, 7.6551, 7.6548] +24-11-19 20:31:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:22 | D | sum error = [ 11.5673, 12.2641, 13.0970, 13.9565, 14.9439] +24-11-19 20:31:22 | D | best error = [ 7.6547, 7.6547, 7.6547, 7.6547, 7.6547] +24-11-19 20:31:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:22 | D | sum error = [ 16.0159, 17.1804, 18.4262, 19.7756, 21.2078] +24-11-19 20:31:22 | D | best error = [ 7.6547, 7.6547, 7.6547, 7.6547, 7.6547] +24-11-19 20:31:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:22 | D | sum error = [ 22.7690, 24.4243, 26.1829, 28.0644, 30.0139] +24-11-19 20:31:22 | D | best error = [ 7.6547, 7.6547, 7.6547, 7.6547, 7.6547] +24-11-19 20:31:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:22 | D | sum error = [ 32.1359, 34.3562, 36.7493, 39.2939, 41.9486] +24-11-19 20:31:22 | D | best error = [ 7.6547, 7.6547, 7.6547, 7.6547, 7.6547] +24-11-19 20:31:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:22 | D | sum error = [ 44.7792, 47.7658, 50.9396, 54.3018, 57.8539] +24-11-19 20:31:22 | D | best error = [ 7.6547, 7.6547, 7.6547, 7.6547, 7.6547] +24-11-19 20:31:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:22 | D | sum error = [ 61.6117, 65.5900, 69.7965, 74.2522, 78.9408] +24-11-19 20:31:22 | D | best error = [ 7.6547, 7.6547, 7.6547, 7.6547, 7.6547] +24-11-19 20:31:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:22 | D | sum error = [ 83.8764, 89.1179, 94.6718, 100.5060, 106.6555] +24-11-19 20:31:22 | D | best error = [ 7.6547, 7.6547, 7.6547, 7.6547, 7.6547] +24-11-19 20:31:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:22 | D | sum error = [ 113.1377, 119.9967, 127.2087, 134.7888, 142.8036] +24-11-19 20:31:22 | D | best error = [ 7.6547, 7.6547, 7.6547, 7.6547, 7.6547] +24-11-19 20:31:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:22 | D | sum error = [ 151.2023, 160.0126, 169.3136, 179.0636, 189.3241] +24-11-19 20:31:22 | D | best error = [ 7.6547, 7.6547, 7.6547, 7.6547, 7.6547] +24-11-19 20:31:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:22 | D | sum error = [ 200.0902, 211.4130, 223.2719, 235.7378, 248.7792] +24-11-19 20:31:22 | D | best error = [ 7.6547, 7.6547, 7.6547, 7.6547, 7.6547] +24-11-19 20:31:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:22 | D | sum error = [ 262.4407, 276.7421, 291.6946, 307.3157, 323.6194] +24-11-19 20:31:22 | D | best error = [ 7.6547, 7.6547, 7.6547, 7.6547, 7.6547] +24-11-19 20:31:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:22 | D | sum error = [ 340.6595, 358.4039, 376.8891, 396.1058, 416.0649] +24-11-19 20:31:22 | D | best error = [ 7.6547, 7.6547, 7.6547, 7.6547, 7.6547] +24-11-19 20:31:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:22 | D | sum error = [ 436.8197, 458.3660, 480.7050, 503.8432, 527.7896] +24-11-19 20:31:22 | D | best error = [ 7.6547, 7.6547, 7.6547, 7.6547, 7.6547] +24-11-19 20:31:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:22 | D | sum error = [ 552.5529, 578.1664, 604.5823, 631.8146, 659.8707] +24-11-19 20:31:22 | D | best error = [ 7.6547, 7.6547, 7.6547, 7.6547, 7.6547] +24-11-19 20:31:22 | D | + error = [7.6547] +24-11-19 20:31:22 | D | - Calibrating model.layers.18.mlp.down_proj.weight +24-11-19 20:31:22 | D | + w: sint8 +24-11-19 20:31:22 | D | + x: None +24-11-19 20:31:22 | D | + y: None +24-11-19 20:31:22 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:22 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:31:22 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:31:22 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:31:22 | D | - range ratio = [ 1.0000] +24-11-19 20:31:22 | D | sum error = [ 2.9066] +24-11-19 20:31:22 | D | best error = [ 2.9066] +24-11-19 20:31:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:23 | D | sum error = [ 2.8779, 2.8642, 2.8413, 2.8310, 2.8317] +24-11-19 20:31:23 | D | best error = [ 2.7906, 2.7321, 2.6905, 2.6615, 2.6397] +24-11-19 20:31:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:23 | D | sum error = [ 2.8470, 2.8706, 2.9070, 2.9590, 3.0274] +24-11-19 20:31:23 | D | best error = [ 2.6227, 2.6095, 2.6004, 2.5940, 2.5893] +24-11-19 20:31:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:23 | D | sum error = [ 3.1050, 3.2067, 3.3243, 3.4639, 3.6243] +24-11-19 20:31:23 | D | best error = [ 2.5855, 2.5833, 2.5821, 2.5810, 2.5805] +24-11-19 20:31:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:23 | D | sum error = [ 3.8153, 4.0260, 4.2538, 4.5048, 4.7869] +24-11-19 20:31:23 | D | best error = [ 2.5802, 2.5800, 2.5797, 2.5797, 2.5797] +24-11-19 20:31:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:23 | D | sum error = [ 5.0966, 5.4281, 5.7881, 6.1835, 6.6075] +24-11-19 20:31:23 | D | best error = [ 2.5797, 2.5797, 2.5797, 2.5797, 2.5797] +24-11-19 20:31:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:23 | D | sum error = [ 7.0593, 7.5454, 8.0652, 8.6297, 9.2253] +24-11-19 20:31:23 | D | best error = [ 2.5797, 2.5797, 2.5797, 2.5797, 2.5797] +24-11-19 20:31:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:23 | D | sum error = [ 9.8611, 10.5434, 11.2643, 12.0344, 12.8501] +24-11-19 20:31:23 | D | best error = [ 2.5797, 2.5797, 2.5797, 2.5797, 2.5797] +24-11-19 20:31:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:23 | D | sum error = [ 13.7152, 14.6317, 15.6089, 16.6372, 17.7305] +24-11-19 20:31:23 | D | best error = [ 2.5797, 2.5797, 2.5797, 2.5797, 2.5797] +24-11-19 20:31:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:23 | D | sum error = [ 18.8805, 20.1013, 21.3876, 22.7423, 24.1766] +24-11-19 20:31:23 | D | best error = [ 2.5797, 2.5797, 2.5797, 2.5797, 2.5797] +24-11-19 20:31:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:23 | D | sum error = [ 25.6792, 27.2675, 28.9376, 30.7026, 32.5481] +24-11-19 20:31:23 | D | best error = [ 2.5797, 2.5797, 2.5797, 2.5797, 2.5797] +24-11-19 20:31:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:23 | D | sum error = [ 34.4876, 36.5252, 38.6615, 40.9030, 43.2586] +24-11-19 20:31:23 | D | best error = [ 2.5797, 2.5797, 2.5797, 2.5797, 2.5797] +24-11-19 20:31:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:23 | D | sum error = [ 45.7199, 48.2984, 50.9980, 53.8171, 56.7707] +24-11-19 20:31:23 | D | best error = [ 2.5797, 2.5797, 2.5797, 2.5797, 2.5797] +24-11-19 20:31:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:23 | D | sum error = [ 59.8557, 63.0711, 66.4267, 69.9293, 73.5747] +24-11-19 20:31:23 | D | best error = [ 2.5797, 2.5797, 2.5797, 2.5797, 2.5797] +24-11-19 20:31:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:23 | D | sum error = [ 77.3744, 81.3248, 85.4357, 89.7115, 94.1415] +24-11-19 20:31:23 | D | best error = [ 2.5797, 2.5797, 2.5797, 2.5797, 2.5797] +24-11-19 20:31:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:23 | D | sum error = [ 98.7457, 103.5230, 108.4700, 113.5953, 118.9010] +24-11-19 20:31:23 | D | best error = [ 2.5797, 2.5797, 2.5797, 2.5797, 2.5797] +24-11-19 20:31:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:23 | D | sum error = [ 124.3904, 130.0706, 135.9442, 142.0069, 148.2664] +24-11-19 20:31:23 | D | best error = [ 2.5797, 2.5797, 2.5797, 2.5797, 2.5797] +24-11-19 20:31:23 | D | + error = [2.5797] +24-11-19 20:31:23 | D | - Quantizing model.layers.18.self_attn.q_proj.weight +24-11-19 20:31:24 | D | - Quantizing model.layers.18.self_attn.k_proj.weight +24-11-19 20:31:25 | D | - Quantizing model.layers.18.self_attn.v_proj.weight +24-11-19 20:31:26 | D | - Quantizing model.layers.18.self_attn.o_proj.weight +24-11-19 20:31:26 | D | - Quantizing model.layers.18.mlp.up_proj.weight +24-11-19 20:31:27 | D | - Quantizing model.layers.18.mlp.gate_proj.weight +24-11-19 20:31:28 | D | - Quantizing model.layers.18.mlp.down_proj.weight +24-11-19 20:31:36 | D | - Quantizing layer model.layers.19 +24-11-19 20:31:36 | D | - Calibrating model.layers.19.self_attn.q_proj.weight +24-11-19 20:31:36 | D | + w: sint8 +24-11-19 20:31:36 | D | + x: None +24-11-19 20:31:36 | D | + y: None +24-11-19 20:31:36 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:31:36 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:31:36 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:31:37 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:31:37 | D | - range ratio = [ 1.0000] +24-11-19 20:31:37 | D | sum error = [ 11.5747] +24-11-19 20:31:37 | D | best error = [ 11.5747] +24-11-19 20:31:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:50 | D | sum error = [ 11.4891, 11.5475, 11.8410, 11.8341, 11.7840] +24-11-19 20:31:50 | D | best error = [ 11.4891, 11.4891, 11.4891, 11.4891, 11.4891] +24-11-19 20:31:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:50 | D | sum error = [ 12.2857, 12.7053, 13.3110, 13.9502, 14.5915] +24-11-19 20:31:50 | D | best error = [ 11.4891, 11.4891, 11.4891, 11.4891, 11.4891] +24-11-19 20:31:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:50 | D | sum error = [ 15.5433, 16.3284, 17.5897, 18.5484, 19.7929] +24-11-19 20:31:50 | D | best error = [ 11.4891, 11.4891, 11.4891, 11.4891, 11.4891] +24-11-19 20:31:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:50 | D | sum error = [ 21.3788, 23.0851, 24.7500, 26.8810, 28.7081] +24-11-19 20:31:50 | D | best error = [ 11.4891, 11.4891, 11.4891, 11.4891, 11.4891] +24-11-19 20:31:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:50 | D | sum error = [ 31.1248, 33.1887, 35.8143, 38.8753, 41.7248] +24-11-19 20:31:50 | D | best error = [ 11.4891, 11.4891, 11.4891, 11.4891, 11.4891] +24-11-19 20:31:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:50 | D | sum error = [ 45.1877, 48.6461, 52.6110, 56.7660, 61.2123] +24-11-19 20:31:50 | D | best error = [ 11.4891, 11.4891, 11.4891, 11.4891, 11.4891] +24-11-19 20:31:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:50 | D | sum error = [ 65.8495, 71.0139, 76.5436, 82.5302, 88.8971] +24-11-19 20:31:50 | D | best error = [ 11.4891, 11.4891, 11.4891, 11.4891, 11.4891] +24-11-19 20:31:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:50 | D | sum error = [ 95.9974, 103.1921, 111.0509, 119.8244, 129.0590] +24-11-19 20:31:50 | D | best error = [ 11.4891, 11.4891, 11.4891, 11.4891, 11.4891] +24-11-19 20:31:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:50 | D | sum error = [ 138.6011, 149.1988, 160.4527, 172.4162, 185.5037] +24-11-19 20:31:50 | D | best error = [ 11.4891, 11.4891, 11.4891, 11.4891, 11.4891] +24-11-19 20:31:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:50 | D | sum error = [ 199.5099, 214.3783, 230.4647, 247.5605, 266.1884] +24-11-19 20:31:50 | D | best error = [ 11.4891, 11.4891, 11.4891, 11.4891, 11.4891] +24-11-19 20:31:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:50 | D | sum error = [ 286.4135, 307.5049, 330.3942, 354.8407, 381.2647] +24-11-19 20:31:50 | D | best error = [ 11.4891, 11.4891, 11.4891, 11.4891, 11.4891] +24-11-19 20:31:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:50 | D | sum error = [ 409.6971, 440.2825, 473.7783, 509.6941, 548.3223] +24-11-19 20:31:50 | D | best error = [ 11.4891, 11.4891, 11.4891, 11.4891, 11.4891] +24-11-19 20:31:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:50 | D | sum error = [ 590.5922, 636.4896, 686.7741, 741.5079, 801.6893] +24-11-19 20:31:50 | D | best error = [ 11.4891, 11.4891, 11.4891, 11.4891, 11.4891] +24-11-19 20:31:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:50 | D | sum error = [ 867.8470, 940.6996, 1020.7127, 1109.9676, 1208.4484] +24-11-19 20:31:50 | D | best error = [ 11.4891, 11.4891, 11.4891, 11.4891, 11.4891] +24-11-19 20:31:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:50 | D | sum error = [ 1316.7729, 1437.0278, 1571.9309, 1720.0291, 1884.7615] +24-11-19 20:31:50 | D | best error = [ 11.4891, 11.4891, 11.4891, 11.4891, 11.4891] +24-11-19 20:31:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:50 | D | sum error = [ 2066.9821, 2268.2920, 2489.2232, 2730.0701, 2992.8121] +24-11-19 20:31:50 | D | best error = [ 11.4891, 11.4891, 11.4891, 11.4891, 11.4891] +24-11-19 20:31:50 | D | + error = [11.4891] +24-11-19 20:31:50 | D | - Calibrating model.layers.19.self_attn.k_proj.weight +24-11-19 20:31:50 | D | + w: sint8 +24-11-19 20:31:50 | D | + x: None +24-11-19 20:31:50 | D | + y: None +24-11-19 20:31:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:31:50 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:31:50 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:31:50 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:31:50 | D | - range ratio = [ 1.0000] +24-11-19 20:31:50 | D | sum error = [ 13.0176] +24-11-19 20:31:50 | D | best error = [ 13.0176] +24-11-19 20:32:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:03 | D | sum error = [ 12.3141, 12.4126, 12.1058, 12.4851, 12.4041] +24-11-19 20:32:03 | D | best error = [ 12.3141, 12.3141, 12.1058, 12.1058, 12.1058] +24-11-19 20:32:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:03 | D | sum error = [ 13.5465, 13.5421, 14.9618, 15.1120, 17.2595] +24-11-19 20:32:03 | D | best error = [ 12.1058, 12.1058, 12.1058, 12.1058, 12.1058] +24-11-19 20:32:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:03 | D | sum error = [ 17.1213, 18.1242, 19.2803, 21.4803, 22.2965] +24-11-19 20:32:03 | D | best error = [ 12.1058, 12.1058, 12.1058, 12.1058, 12.1058] +24-11-19 20:32:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:03 | D | sum error = [ 24.9982, 25.2347, 28.3616, 31.0330, 32.5066] +24-11-19 20:32:03 | D | best error = [ 12.1058, 12.1058, 12.1058, 12.1058, 12.1058] +24-11-19 20:32:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:03 | D | sum error = [ 35.7373, 38.5954, 40.6402, 44.9572, 47.6001] +24-11-19 20:32:03 | D | best error = [ 12.1058, 12.1058, 12.1058, 12.1058, 12.1058] +24-11-19 20:32:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:03 | D | sum error = [ 51.9894, 56.1784, 59.8344, 65.1370, 68.7496] +24-11-19 20:32:03 | D | best error = [ 12.1058, 12.1058, 12.1058, 12.1058, 12.1058] +24-11-19 20:32:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:03 | D | sum error = [ 75.1904, 80.7589, 86.8025, 95.0374, 102.2826] +24-11-19 20:32:03 | D | best error = [ 12.1058, 12.1058, 12.1058, 12.1058, 12.1058] +24-11-19 20:32:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:03 | D | sum error = [ 110.3576, 118.2552, 127.7486, 137.8276, 147.3306] +24-11-19 20:32:03 | D | best error = [ 12.1058, 12.1058, 12.1058, 12.1058, 12.1058] +24-11-19 20:32:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:03 | D | sum error = [ 159.6022, 170.9606, 184.2044, 199.1843, 213.9601] +24-11-19 20:32:03 | D | best error = [ 12.1058, 12.1058, 12.1058, 12.1058, 12.1058] +24-11-19 20:32:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:03 | D | sum error = [ 229.3772, 247.2853, 265.7317, 286.3774, 307.6453] +24-11-19 20:32:03 | D | best error = [ 12.1058, 12.1058, 12.1058, 12.1058, 12.1058] +24-11-19 20:32:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:03 | D | sum error = [ 331.4360, 355.8535, 383.0856, 413.9460, 446.4892] +24-11-19 20:32:03 | D | best error = [ 12.1058, 12.1058, 12.1058, 12.1058, 12.1058] +24-11-19 20:32:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:03 | D | sum error = [ 479.9665, 517.4265, 557.4084, 600.0667, 645.9961] +24-11-19 20:32:03 | D | best error = [ 12.1058, 12.1058, 12.1058, 12.1058, 12.1058] +24-11-19 20:32:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:03 | D | sum error = [ 696.1332, 750.9315, 809.5317, 874.1943, 941.5166] +24-11-19 20:32:03 | D | best error = [ 12.1058, 12.1058, 12.1058, 12.1058, 12.1058] +24-11-19 20:32:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:03 | D | sum error = [ 1018.8054, 1102.2053, 1194.0137, 1294.5673, 1405.0819] +24-11-19 20:32:03 | D | best error = [ 12.1058, 12.1058, 12.1058, 12.1058, 12.1058] +24-11-19 20:32:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:03 | D | sum error = [ 1525.7318, 1658.4853, 1803.4944, 1965.4002, 2142.4218] +24-11-19 20:32:03 | D | best error = [ 12.1058, 12.1058, 12.1058, 12.1058, 12.1058] +24-11-19 20:32:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:03 | D | sum error = [ 2335.3107, 2542.8765, 2768.6962, 3011.4769, 3271.2881] +24-11-19 20:32:03 | D | best error = [ 12.1058, 12.1058, 12.1058, 12.1058, 12.1058] +24-11-19 20:32:03 | D | + error = [12.1058] +24-11-19 20:32:03 | D | - Calibrating model.layers.19.self_attn.v_proj.weight +24-11-19 20:32:03 | D | + w: sint8 +24-11-19 20:32:03 | D | + x: None +24-11-19 20:32:03 | D | + y: None +24-11-19 20:32:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:03 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:32:03 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:32:03 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:32:03 | D | - range ratio = [ 1.0000] +24-11-19 20:32:03 | D | sum error = [ 6.1233] +24-11-19 20:32:03 | D | best error = [ 6.1233] +24-11-19 20:32:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:04 | D | sum error = [ 6.0845, 6.0659, 6.0867, 6.1491, 6.2935] +24-11-19 20:32:04 | D | best error = [ 5.7213, 5.5621, 5.4798, 5.4269, 5.4035] +24-11-19 20:32:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:04 | D | sum error = [ 6.4279, 6.6476, 6.9058, 7.2412, 7.6320] +24-11-19 20:32:04 | D | best error = [ 5.3891, 5.3827, 5.3807, 5.3796, 5.3795] +24-11-19 20:32:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:04 | D | sum error = [ 8.0722, 8.5798, 9.1548, 9.7667, 10.4388] +24-11-19 20:32:04 | D | best error = [ 5.3795, 5.3795, 5.3795, 5.3795, 5.3795] +24-11-19 20:32:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:04 | D | sum error = [ 11.1838, 11.9707, 12.8504, 13.7770, 14.7617] +24-11-19 20:32:04 | D | best error = [ 5.3795, 5.3795, 5.3795, 5.3795, 5.3795] +24-11-19 20:32:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:04 | D | sum error = [ 15.7864, 16.9367, 18.1507, 19.4224, 20.7722] +24-11-19 20:32:04 | D | best error = [ 5.3795, 5.3795, 5.3795, 5.3795, 5.3795] +24-11-19 20:32:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:04 | D | sum error = [ 22.1961, 23.6865, 25.3272, 27.0102, 28.7566] +24-11-19 20:32:04 | D | best error = [ 5.3795, 5.3795, 5.3795, 5.3795, 5.3795] +24-11-19 20:32:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:04 | D | sum error = [ 30.6524, 32.6164, 34.7141, 36.9094, 39.2204] +24-11-19 20:32:04 | D | best error = [ 5.3795, 5.3795, 5.3795, 5.3795, 5.3795] +24-11-19 20:32:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:04 | D | sum error = [ 41.6579, 44.2141, 46.8888, 49.7144, 52.6768] +24-11-19 20:32:04 | D | best error = [ 5.3795, 5.3795, 5.3795, 5.3795, 5.3795] +24-11-19 20:32:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:04 | D | sum error = [ 55.7678, 59.0285, 62.4747, 66.0448, 69.7902] +24-11-19 20:32:04 | D | best error = [ 5.3795, 5.3795, 5.3795, 5.3795, 5.3795] +24-11-19 20:32:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:04 | D | sum error = [ 73.7466, 77.8836, 82.2010, 86.7137, 91.4346] +24-11-19 20:32:04 | D | best error = [ 5.3795, 5.3795, 5.3795, 5.3795, 5.3795] +24-11-19 20:32:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:04 | D | sum error = [ 96.3370, 101.4756, 106.8357, 112.4276, 118.2483] +24-11-19 20:32:04 | D | best error = [ 5.3795, 5.3795, 5.3795, 5.3795, 5.3795] +24-11-19 20:32:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:04 | D | sum error = [ 124.3268, 130.6731, 137.2617, 144.1314, 151.2758] +24-11-19 20:32:04 | D | best error = [ 5.3795, 5.3795, 5.3795, 5.3795, 5.3795] +24-11-19 20:32:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:04 | D | sum error = [ 158.6964, 166.4085, 174.4076, 182.7062, 191.3130] +24-11-19 20:32:04 | D | best error = [ 5.3795, 5.3795, 5.3795, 5.3795, 5.3795] +24-11-19 20:32:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:04 | D | sum error = [ 200.2200, 209.4550, 219.0011, 228.8654, 239.0829] +24-11-19 20:32:04 | D | best error = [ 5.3795, 5.3795, 5.3795, 5.3795, 5.3795] +24-11-19 20:32:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:04 | D | sum error = [ 249.6311, 260.5257, 271.7726, 283.3943, 295.3888] +24-11-19 20:32:04 | D | best error = [ 5.3795, 5.3795, 5.3795, 5.3795, 5.3795] +24-11-19 20:32:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:04 | D | sum error = [ 307.7530, 320.4953, 333.6333, 347.1570, 361.0443] +24-11-19 20:32:04 | D | best error = [ 5.3795, 5.3795, 5.3795, 5.3795, 5.3795] +24-11-19 20:32:04 | D | + error = [5.3795] +24-11-19 20:32:04 | D | - Calibrating model.layers.19.self_attn.o_proj.weight +24-11-19 20:32:04 | D | + w: sint8 +24-11-19 20:32:04 | D | + x: None +24-11-19 20:32:04 | D | + y: None +24-11-19 20:32:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:04 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:32:04 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:32:04 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:32:04 | D | - range ratio = [ 1.0000] +24-11-19 20:32:04 | D | sum error = [ 1.4442] +24-11-19 20:32:04 | D | best error = [ 1.4442] +24-11-19 20:32:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:04 | D | sum error = [ 1.4345, 1.4280, 1.4233, 1.4338, 1.4451] +24-11-19 20:32:04 | D | best error = [ 1.3582, 1.3190, 1.2933, 1.2784, 1.2674] +24-11-19 20:32:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:04 | D | sum error = [ 1.4696, 1.5054, 1.5473, 1.5958, 1.6678] +24-11-19 20:32:04 | D | best error = [ 1.2605, 1.2558, 1.2527, 1.2508, 1.2497] +24-11-19 20:32:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:04 | D | sum error = [ 1.7432, 1.8306, 1.9273, 2.0375, 2.1608] +24-11-19 20:32:04 | D | best error = [ 1.2490, 1.2487, 1.2483, 1.2480, 1.2479] +24-11-19 20:32:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:04 | D | sum error = [ 2.2963, 2.4414, 2.6038, 2.7777, 2.9609] +24-11-19 20:32:04 | D | best error = [ 1.2478, 1.2478, 1.2478, 1.2477, 1.2477] +24-11-19 20:32:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:04 | D | sum error = [ 3.1610, 3.3784, 3.6097, 3.8476, 4.1066] +24-11-19 20:32:04 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:04 | D | sum error = [ 4.3842, 4.6767, 4.9825, 5.3110, 5.6565] +24-11-19 20:32:04 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:04 | D | sum error = [ 6.0202, 6.4101, 6.8200, 7.2510, 7.7093] +24-11-19 20:32:04 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:04 | D | sum error = [ 8.1909, 8.7006, 9.2361, 9.8032, 10.3954] +24-11-19 20:32:04 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:04 | D | sum error = [ 11.0233, 11.6870, 12.3792, 13.1126, 13.8781] +24-11-19 20:32:04 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:04 | D | sum error = [ 14.6826, 15.5293, 16.4146, 17.3503, 18.3301] +24-11-19 20:32:04 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:04 | D | sum error = [ 19.3548, 20.4321, 21.5562, 22.7371, 23.9705] +24-11-19 20:32:04 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:04 | D | sum error = [ 25.2610, 26.6098, 28.0197, 29.4969, 31.0358] +24-11-19 20:32:04 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:04 | D | sum error = [ 32.6462, 34.3195, 36.0691, 37.8872, 39.7842] +24-11-19 20:32:04 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:04 | D | sum error = [ 41.7588, 43.8079, 45.9346, 48.1444, 50.4400] +24-11-19 20:32:04 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:04 | D | sum error = [ 52.8222, 55.2911, 57.8504, 60.4989, 63.2406] +24-11-19 20:32:04 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:04 | D | sum error = [ 66.0751, 69.0004, 72.0210, 75.1474, 78.3730] +24-11-19 20:32:04 | D | best error = [ 1.2477, 1.2477, 1.2477, 1.2477, 1.2477] +24-11-19 20:32:04 | D | + error = [1.2477] +24-11-19 20:32:05 | D | - Calibrating model.layers.19.mlp.up_proj.weight +24-11-19 20:32:05 | D | + w: sint8 +24-11-19 20:32:05 | D | + x: None +24-11-19 20:32:05 | D | + y: None +24-11-19 20:32:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:05 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:32:05 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:32:05 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:32:05 | D | - range ratio = [ 1.0000] +24-11-19 20:32:05 | D | sum error = [ 8.5688] +24-11-19 20:32:05 | D | best error = [ 8.5688] +24-11-19 20:32:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:06 | D | sum error = [ 8.4890, 8.4581, 8.4860, 8.6027, 8.7571] +24-11-19 20:32:06 | D | best error = [ 7.9733, 7.7406, 7.6124, 7.5434, 7.5081] +24-11-19 20:32:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:06 | D | sum error = [ 8.9986, 9.2997, 9.6522, 10.1223, 10.6439] +24-11-19 20:32:06 | D | best error = [ 7.4897, 7.4822, 7.4797, 7.4789, 7.4786] +24-11-19 20:32:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:06 | D | sum error = [ 11.2534, 11.9662, 12.7168, 13.6162, 14.5496] +24-11-19 20:32:06 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 20:32:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:06 | D | sum error = [ 15.5718, 16.7000, 17.8665, 19.1549, 20.5486] +24-11-19 20:32:06 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 20:32:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:06 | D | sum error = [ 22.0098, 23.5563, 25.2414, 27.0081, 28.8852] +24-11-19 20:32:06 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 20:32:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:06 | D | sum error = [ 30.8389, 32.9888, 35.2017, 37.5531, 40.0533] +24-11-19 20:32:06 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 20:32:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:06 | D | sum error = [ 42.6627, 45.4301, 48.3516, 51.4131, 54.6612] +24-11-19 20:32:06 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 20:32:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:06 | D | sum error = [ 58.0755, 61.6824, 65.4553, 69.4129, 73.5951] +24-11-19 20:32:06 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 20:32:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:06 | D | sum error = [ 77.9742, 82.5544, 87.3696, 92.4232, 97.6952] +24-11-19 20:32:06 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 20:32:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:06 | D | sum error = [ 103.2489, 109.0557, 115.1454, 121.5037, 128.1709] +24-11-19 20:32:06 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 20:32:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:06 | D | sum error = [ 135.1354, 142.4183, 150.0233, 157.9658, 166.2377] +24-11-19 20:32:06 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 20:32:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:06 | D | sum error = [ 174.8824, 183.8773, 193.2438, 202.9948, 213.1206] +24-11-19 20:32:06 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 20:32:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:06 | D | sum error = [ 223.6544, 234.6079, 245.9683, 257.7599, 269.9790] +24-11-19 20:32:06 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 20:32:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:06 | D | sum error = [ 282.6448, 295.7721, 309.3677, 323.4507, 338.0016] +24-11-19 20:32:06 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 20:32:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:06 | D | sum error = [ 353.0505, 368.6047, 384.6824, 401.2770, 418.3946] +24-11-19 20:32:06 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 20:32:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:06 | D | sum error = [ 436.0426, 454.2440, 473.0015, 492.3105, 512.1702] +24-11-19 20:32:06 | D | best error = [ 7.4786, 7.4786, 7.4786, 7.4786, 7.4786] +24-11-19 20:32:06 | D | + error = [7.4786] +24-11-19 20:32:06 | D | - Calibrating model.layers.19.mlp.gate_proj.weight +24-11-19 20:32:06 | D | + w: sint8 +24-11-19 20:32:06 | D | + x: None +24-11-19 20:32:06 | D | + y: None +24-11-19 20:32:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:06 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:32:06 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:32:06 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:32:06 | D | - range ratio = [ 1.0000] +24-11-19 20:32:06 | D | sum error = [ 9.0831] +24-11-19 20:32:06 | D | best error = [ 9.0831] +24-11-19 20:32:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:07 | D | sum error = [ 9.0299, 8.9881, 9.0397, 9.1343, 9.3226] +24-11-19 20:32:07 | D | best error = [ 8.4721, 8.2229, 8.0920, 8.0194, 7.9828] +24-11-19 20:32:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:07 | D | sum error = [ 9.5314, 9.8616, 10.2886, 10.7678, 11.3341] +24-11-19 20:32:07 | D | best error = [ 7.9640, 7.9559, 7.9528, 7.9518, 7.9515] +24-11-19 20:32:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:07 | D | sum error = [ 11.9796, 12.7092, 13.5279, 14.4875, 15.4842] +24-11-19 20:32:07 | D | best error = [ 7.9515, 7.9514, 7.9514, 7.9514, 7.9514] +24-11-19 20:32:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:07 | D | sum error = [ 16.5750, 17.7593, 19.0572, 20.4221, 21.9245] +24-11-19 20:32:07 | D | best error = [ 7.9514, 7.9514, 7.9514, 7.9514, 7.9514] +24-11-19 20:32:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:07 | D | sum error = [ 23.4891, 25.1805, 26.9975, 28.9029, 30.9529] +24-11-19 20:32:07 | D | best error = [ 7.9514, 7.9514, 7.9514, 7.9514, 7.9514] +24-11-19 20:32:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:07 | D | sum error = [ 33.1293, 35.4128, 37.8687, 40.4576, 43.1800] +24-11-19 20:32:07 | D | best error = [ 7.9514, 7.9514, 7.9514, 7.9514, 7.9514] +24-11-19 20:32:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:07 | D | sum error = [ 46.0683, 49.1554, 52.4044, 55.8280, 59.4570] +24-11-19 20:32:07 | D | best error = [ 7.9514, 7.9514, 7.9514, 7.9514, 7.9514] +24-11-19 20:32:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:07 | D | sum error = [ 63.2708, 67.3114, 71.5999, 76.0794, 80.8520] +24-11-19 20:32:07 | D | best error = [ 7.9514, 7.9514, 7.9514, 7.9514, 7.9514] +24-11-19 20:32:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:07 | D | sum error = [ 85.8820, 91.1827, 96.8012, 102.6806, 108.9118] +24-11-19 20:32:07 | D | best error = [ 7.9514, 7.9514, 7.9514, 7.9514, 7.9514] +24-11-19 20:32:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:07 | D | sum error = [ 115.4789, 122.3769, 129.6338, 137.2880, 145.3352] +24-11-19 20:32:07 | D | best error = [ 7.9514, 7.9514, 7.9514, 7.9514, 7.9514] +24-11-19 20:32:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:07 | D | sum error = [ 153.7726, 162.6530, 171.9702, 181.7451, 192.0388] +24-11-19 20:32:07 | D | best error = [ 7.9514, 7.9514, 7.9514, 7.9514, 7.9514] +24-11-19 20:32:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:07 | D | sum error = [ 202.7870, 214.0894, 225.9238, 238.3146, 251.2891] +24-11-19 20:32:07 | D | best error = [ 7.9514, 7.9514, 7.9514, 7.9514, 7.9514] +24-11-19 20:32:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:07 | D | sum error = [ 264.8805, 279.0374, 293.8296, 309.2605, 325.3655] +24-11-19 20:32:07 | D | best error = [ 7.9514, 7.9514, 7.9514, 7.9514, 7.9514] +24-11-19 20:32:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:07 | D | sum error = [ 342.1531, 359.6452, 377.8718, 396.8438, 416.5601] +24-11-19 20:32:07 | D | best error = [ 7.9514, 7.9514, 7.9514, 7.9514, 7.9514] +24-11-19 20:32:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:07 | D | sum error = [ 437.0371, 458.2693, 480.2725, 503.0471, 526.6358] +24-11-19 20:32:07 | D | best error = [ 7.9514, 7.9514, 7.9514, 7.9514, 7.9514] +24-11-19 20:32:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:07 | D | sum error = [ 550.9626, 576.1453, 602.1242, 628.9280, 656.5236] +24-11-19 20:32:07 | D | best error = [ 7.9514, 7.9514, 7.9514, 7.9514, 7.9514] +24-11-19 20:32:07 | D | + error = [7.9514] +24-11-19 20:32:07 | D | - Calibrating model.layers.19.mlp.down_proj.weight +24-11-19 20:32:07 | D | + w: sint8 +24-11-19 20:32:07 | D | + x: None +24-11-19 20:32:07 | D | + y: None +24-11-19 20:32:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:07 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:32:07 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:32:07 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:32:07 | D | - range ratio = [ 1.0000] +24-11-19 20:32:07 | D | sum error = [ 3.1572] +24-11-19 20:32:07 | D | best error = [ 3.1572] +24-11-19 20:32:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:08 | D | sum error = [ 3.1302, 3.1110, 3.0918, 3.0961, 3.1010] +24-11-19 20:32:08 | D | best error = [ 3.0239, 2.9600, 2.9146, 2.8818, 2.8582] +24-11-19 20:32:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:08 | D | sum error = [ 3.1156, 3.1496, 3.1977, 3.2596, 3.3496] +24-11-19 20:32:08 | D | best error = [ 2.8368, 2.8209, 2.8101, 2.8025, 2.7970] +24-11-19 20:32:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:08 | D | sum error = [ 3.4448, 3.5697, 3.7102, 3.8778, 4.0652] +24-11-19 20:32:08 | D | best error = [ 2.7931, 2.7903, 2.7887, 2.7874, 2.7868] +24-11-19 20:32:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:08 | D | sum error = [ 4.2744, 4.5097, 4.7710, 5.0538, 5.3665] +24-11-19 20:32:08 | D | best error = [ 2.7863, 2.7859, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:08 | D | sum error = [ 5.7125, 6.0802, 6.4812, 6.9123, 7.3715] +24-11-19 20:32:08 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:08 | D | sum error = [ 7.8768, 8.4042, 8.9709, 9.5872, 10.2355] +24-11-19 20:32:08 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:08 | D | sum error = [ 10.9315, 11.6661, 12.4536, 13.2901, 14.1804] +24-11-19 20:32:08 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:08 | D | sum error = [ 15.1187, 16.1223, 17.1841, 18.3054, 19.4926] +24-11-19 20:32:08 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:08 | D | sum error = [ 20.7455, 22.0739, 23.4705, 24.9491, 26.5053] +24-11-19 20:32:08 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:08 | D | sum error = [ 28.1438, 29.8714, 31.6908, 33.6065, 35.6150] +24-11-19 20:32:08 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:08 | D | sum error = [ 37.7385, 39.9560, 42.2838, 44.7261, 47.2871] +24-11-19 20:32:08 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:08 | D | sum error = [ 49.9670, 52.7736, 55.7133, 58.7844, 61.9949] +24-11-19 20:32:08 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:08 | D | sum error = [ 65.3492, 68.8476, 72.4981, 76.3045, 80.2709] +24-11-19 20:32:08 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:08 | D | sum error = [ 84.4096, 88.7104, 93.1983, 97.8738, 102.7083] +24-11-19 20:32:08 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:08 | D | sum error = [ 107.7428, 112.9618, 118.3730, 123.9835, 129.7966] +24-11-19 20:32:08 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:08 | D | sum error = [ 135.8160, 142.0432, 148.4824, 155.1401, 162.0140] +24-11-19 20:32:08 | D | best error = [ 2.7857, 2.7857, 2.7857, 2.7857, 2.7857] +24-11-19 20:32:08 | D | + error = [2.7857] +24-11-19 20:32:09 | D | - Quantizing model.layers.19.self_attn.q_proj.weight +24-11-19 20:32:09 | D | - Quantizing model.layers.19.self_attn.k_proj.weight +24-11-19 20:32:10 | D | - Quantizing model.layers.19.self_attn.v_proj.weight +24-11-19 20:32:11 | D | - Quantizing model.layers.19.self_attn.o_proj.weight +24-11-19 20:32:12 | D | - Quantizing model.layers.19.mlp.up_proj.weight +24-11-19 20:32:13 | D | - Quantizing model.layers.19.mlp.gate_proj.weight +24-11-19 20:32:14 | D | - Quantizing model.layers.19.mlp.down_proj.weight +24-11-19 20:32:22 | D | - Quantizing layer model.layers.20 +24-11-19 20:32:22 | D | - Calibrating model.layers.20.self_attn.q_proj.weight +24-11-19 20:32:22 | D | + w: sint8 +24-11-19 20:32:22 | D | + x: None +24-11-19 20:32:22 | D | + y: None +24-11-19 20:32:22 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:32:22 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:32:22 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:32:22 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:32:22 | D | - range ratio = [ 1.0000] +24-11-19 20:32:22 | D | sum error = [ 11.9652] +24-11-19 20:32:22 | D | best error = [ 11.9652] +24-11-19 20:32:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:35 | D | sum error = [ 11.9626, 11.7150, 11.8451, 12.1155, 12.1653] +24-11-19 20:32:35 | D | best error = [ 11.9626, 11.7150, 11.7150, 11.7150, 11.7150] +24-11-19 20:32:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:35 | D | sum error = [ 12.8144, 13.1733, 13.5101, 14.3792, 15.0502] +24-11-19 20:32:35 | D | best error = [ 11.7150, 11.7150, 11.7150, 11.7150, 11.7150] +24-11-19 20:32:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:35 | D | sum error = [ 15.8349, 16.9708, 17.9468, 19.2938, 20.7166] +24-11-19 20:32:35 | D | best error = [ 11.7150, 11.7150, 11.7150, 11.7150, 11.7150] +24-11-19 20:32:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:35 | D | sum error = [ 22.2673, 23.9592, 25.6391, 28.0169, 30.1946] +24-11-19 20:32:35 | D | best error = [ 11.7150, 11.7150, 11.7150, 11.7150, 11.7150] +24-11-19 20:32:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:35 | D | sum error = [ 32.5252, 35.2367, 38.3723, 40.9538, 44.6121] +24-11-19 20:32:35 | D | best error = [ 11.7150, 11.7150, 11.7150, 11.7150, 11.7150] +24-11-19 20:32:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:35 | D | sum error = [ 48.2095, 51.6751, 55.9444, 60.2528, 65.1060] +24-11-19 20:32:35 | D | best error = [ 11.7150, 11.7150, 11.7150, 11.7150, 11.7150] +24-11-19 20:32:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:35 | D | sum error = [ 70.0926, 75.0366, 81.0231, 87.0662, 93.9638] +24-11-19 20:32:35 | D | best error = [ 11.7150, 11.7150, 11.7150, 11.7150, 11.7150] +24-11-19 20:32:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:35 | D | sum error = [ 100.8611, 108.4518, 116.4145, 125.2037, 134.4272] +24-11-19 20:32:35 | D | best error = [ 11.7150, 11.7150, 11.7150, 11.7150, 11.7150] +24-11-19 20:32:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:35 | D | sum error = [ 144.3987, 154.8903, 166.2869, 178.5300, 191.1827] +24-11-19 20:32:35 | D | best error = [ 11.7150, 11.7150, 11.7150, 11.7150, 11.7150] +24-11-19 20:32:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:35 | D | sum error = [ 205.3493, 220.3377, 236.0486, 253.5243, 271.8225] +24-11-19 20:32:35 | D | best error = [ 11.7150, 11.7150, 11.7150, 11.7150, 11.7150] +24-11-19 20:32:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:35 | D | sum error = [ 291.5044, 312.7900, 336.0462, 360.3692, 386.8093] +24-11-19 20:32:35 | D | best error = [ 11.7150, 11.7150, 11.7150, 11.7150, 11.7150] +24-11-19 20:32:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:35 | D | sum error = [ 415.1259, 445.5399, 477.8641, 512.8398, 549.9177] +24-11-19 20:32:35 | D | best error = [ 11.7150, 11.7150, 11.7150, 11.7150, 11.7150] +24-11-19 20:32:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:35 | D | sum error = [ 590.1662, 633.7571, 681.0077, 732.3638, 788.3859] +24-11-19 20:32:35 | D | best error = [ 11.7150, 11.7150, 11.7150, 11.7150, 11.7150] +24-11-19 20:32:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:35 | D | sum error = [ 849.6922, 916.2882, 988.6400, 1068.6530, 1155.6283] +24-11-19 20:32:35 | D | best error = [ 11.7150, 11.7150, 11.7150, 11.7150, 11.7150] +24-11-19 20:32:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:35 | D | sum error = [ 1251.2523, 1356.3134, 1472.3868, 1600.2426, 1741.1634] +24-11-19 20:32:35 | D | best error = [ 11.7150, 11.7150, 11.7150, 11.7150, 11.7150] +24-11-19 20:32:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:35 | D | sum error = [ 1896.8143, 2068.1690, 2257.9792, 2468.0000, 2697.8490] +24-11-19 20:32:35 | D | best error = [ 11.7150, 11.7150, 11.7150, 11.7150, 11.7150] +24-11-19 20:32:35 | D | + error = [11.7150] +24-11-19 20:32:35 | D | - Calibrating model.layers.20.self_attn.k_proj.weight +24-11-19 20:32:35 | D | + w: sint8 +24-11-19 20:32:35 | D | + x: None +24-11-19 20:32:35 | D | + y: None +24-11-19 20:32:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:32:35 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:32:35 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:32:36 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:32:36 | D | - range ratio = [ 1.0000] +24-11-19 20:32:36 | D | sum error = [ 13.4083] +24-11-19 20:32:36 | D | best error = [ 13.4083] +24-11-19 20:32:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:48 | D | sum error = [ 13.7117, 13.3905, 13.7129, 12.3819, 14.4308] +24-11-19 20:32:48 | D | best error = [ 13.4083, 13.3905, 13.3905, 12.3819, 12.3819] +24-11-19 20:32:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:48 | D | sum error = [ 14.1646, 14.4623, 15.0945, 16.1269, 16.4213] +24-11-19 20:32:48 | D | best error = [ 12.3819, 12.3819, 12.3819, 12.3819, 12.3819] +24-11-19 20:32:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:48 | D | sum error = [ 17.2460, 18.0715, 19.9032, 20.8521, 23.4265] +24-11-19 20:32:48 | D | best error = [ 12.3819, 12.3819, 12.3819, 12.3819, 12.3819] +24-11-19 20:32:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:48 | D | sum error = [ 23.9892, 27.0171, 29.0059, 30.8553, 33.9371] +24-11-19 20:32:48 | D | best error = [ 12.3819, 12.3819, 12.3819, 12.3819, 12.3819] +24-11-19 20:32:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:48 | D | sum error = [ 36.0536, 39.6762, 41.8658, 46.2917, 49.5616] +24-11-19 20:32:48 | D | best error = [ 12.3819, 12.3819, 12.3819, 12.3819, 12.3819] +24-11-19 20:32:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:48 | D | sum error = [ 53.5125, 58.9674, 63.1494, 68.5720, 74.0964] +24-11-19 20:32:48 | D | best error = [ 12.3819, 12.3819, 12.3819, 12.3819, 12.3819] +24-11-19 20:32:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:48 | D | sum error = [ 78.8933, 86.1702, 92.5812, 100.7706, 109.3566] +24-11-19 20:32:48 | D | best error = [ 12.3819, 12.3819, 12.3819, 12.3819, 12.3819] +24-11-19 20:32:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:48 | D | sum error = [ 118.4176, 128.1775, 135.9387, 148.5448, 160.3424] +24-11-19 20:32:48 | D | best error = [ 12.3819, 12.3819, 12.3819, 12.3819, 12.3819] +24-11-19 20:32:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:48 | D | sum error = [ 173.0505, 186.0233, 200.3076, 214.9663, 229.3574] +24-11-19 20:32:48 | D | best error = [ 12.3819, 12.3819, 12.3819, 12.3819, 12.3819] +24-11-19 20:32:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:48 | D | sum error = [ 245.8593, 263.4686, 282.2976, 303.2681, 325.3217] +24-11-19 20:32:48 | D | best error = [ 12.3819, 12.3819, 12.3819, 12.3819, 12.3819] +24-11-19 20:32:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:48 | D | sum error = [ 348.6843, 374.7935, 401.4439, 431.7925, 463.8352] +24-11-19 20:32:48 | D | best error = [ 12.3819, 12.3819, 12.3819, 12.3819, 12.3819] +24-11-19 20:32:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:48 | D | sum error = [ 498.4874, 534.7418, 572.2202, 612.6162, 657.1146] +24-11-19 20:32:48 | D | best error = [ 12.3819, 12.3819, 12.3819, 12.3819, 12.3819] +24-11-19 20:32:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:48 | D | sum error = [ 705.4253, 758.5279, 817.8758, 882.4280, 951.3094] +24-11-19 20:32:48 | D | best error = [ 12.3819, 12.3819, 12.3819, 12.3819, 12.3819] +24-11-19 20:32:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:48 | D | sum error = [ 1026.0442, 1108.0006, 1197.0628, 1295.1531, 1404.2911] +24-11-19 20:32:48 | D | best error = [ 12.3819, 12.3819, 12.3819, 12.3819, 12.3819] +24-11-19 20:32:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:48 | D | sum error = [ 1522.4622, 1652.3226, 1793.2774, 1950.0067, 2120.5271] +24-11-19 20:32:48 | D | best error = [ 12.3819, 12.3819, 12.3819, 12.3819, 12.3819] +24-11-19 20:32:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:48 | D | sum error = [ 2307.1337, 2510.2552, 2734.1811, 2973.3930, 3230.9618] +24-11-19 20:32:48 | D | best error = [ 12.3819, 12.3819, 12.3819, 12.3819, 12.3819] +24-11-19 20:32:48 | D | + error = [12.3819] +24-11-19 20:32:49 | D | - Calibrating model.layers.20.self_attn.v_proj.weight +24-11-19 20:32:49 | D | + w: sint8 +24-11-19 20:32:49 | D | + x: None +24-11-19 20:32:49 | D | + y: None +24-11-19 20:32:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:49 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:32:49 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:32:49 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:32:49 | D | - range ratio = [ 1.0000] +24-11-19 20:32:49 | D | sum error = [ 6.2685] +24-11-19 20:32:49 | D | best error = [ 6.2685] +24-11-19 20:32:49 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:49 | D | sum error = [ 6.2183, 6.1893, 6.2650, 6.2987, 6.4248] +24-11-19 20:32:49 | D | best error = [ 5.8547, 5.6913, 5.6085, 5.5549, 5.5271] +24-11-19 20:32:49 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:49 | D | sum error = [ 6.5902, 6.7917, 7.0915, 7.4223, 7.7917] +24-11-19 20:32:49 | D | best error = [ 5.5144, 5.5088, 5.5070, 5.5064, 5.5061] +24-11-19 20:32:49 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:49 | D | sum error = [ 8.2305, 8.7552, 9.3387, 9.9472, 10.6291] +24-11-19 20:32:49 | D | best error = [ 5.5059, 5.5059, 5.5059, 5.5059, 5.5059] +24-11-19 20:32:49 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:49 | D | sum error = [ 11.3717, 12.1932, 13.0446, 13.9742, 14.9415] +24-11-19 20:32:49 | D | best error = [ 5.5059, 5.5059, 5.5059, 5.5059, 5.5059] +24-11-19 20:32:49 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:49 | D | sum error = [ 16.0624, 17.1490, 18.3731, 19.6302, 20.9820] +24-11-19 20:32:49 | D | best error = [ 5.5059, 5.5059, 5.5059, 5.5059, 5.5059] +24-11-19 20:32:49 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:49 | D | sum error = [ 22.4535, 23.9498, 25.5790, 27.2780, 29.0746] +24-11-19 20:32:49 | D | best error = [ 5.5059, 5.5059, 5.5059, 5.5059, 5.5059] +24-11-19 20:32:49 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:49 | D | sum error = [ 30.9798, 32.9662, 35.1016, 37.3400, 39.6678] +24-11-19 20:32:49 | D | best error = [ 5.5059, 5.5059, 5.5059, 5.5059, 5.5059] +24-11-19 20:32:49 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:49 | D | sum error = [ 42.1296, 44.7228, 47.4432, 50.3080, 53.3088] +24-11-19 20:32:49 | D | best error = [ 5.5059, 5.5059, 5.5059, 5.5059, 5.5059] +24-11-19 20:32:49 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:49 | D | sum error = [ 56.4382, 59.7399, 63.1949, 66.7972, 70.5892] +24-11-19 20:32:49 | D | best error = [ 5.5059, 5.5059, 5.5059, 5.5059, 5.5059] +24-11-19 20:32:49 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:49 | D | sum error = [ 74.5435, 78.6966, 83.0211, 87.5471, 92.2678] +24-11-19 20:32:49 | D | best error = [ 5.5059, 5.5059, 5.5059, 5.5059, 5.5059] +24-11-19 20:32:49 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:49 | D | sum error = [ 97.2037, 102.3674, 107.7531, 113.3443, 119.1764] +24-11-19 20:32:49 | D | best error = [ 5.5059, 5.5059, 5.5059, 5.5059, 5.5059] +24-11-19 20:32:49 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:49 | D | sum error = [ 125.2442, 131.5572, 138.1329, 144.9614, 152.0460] +24-11-19 20:32:49 | D | best error = [ 5.5059, 5.5059, 5.5059, 5.5059, 5.5059] +24-11-19 20:32:49 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:49 | D | sum error = [ 159.4225, 167.0623, 175.0066, 183.2254, 191.7363] +24-11-19 20:32:49 | D | best error = [ 5.5059, 5.5059, 5.5059, 5.5059, 5.5059] +24-11-19 20:32:49 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:49 | D | sum error = [ 200.5660, 209.6955, 219.1349, 228.8941, 238.9689] +24-11-19 20:32:49 | D | best error = [ 5.5059, 5.5059, 5.5059, 5.5059, 5.5059] +24-11-19 20:32:49 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:49 | D | sum error = [ 249.3722, 260.1035, 271.1806, 282.6116, 294.4014] +24-11-19 20:32:49 | D | best error = [ 5.5059, 5.5059, 5.5059, 5.5059, 5.5059] +24-11-19 20:32:49 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:49 | D | sum error = [ 306.5353, 319.0702, 331.9549, 345.2141, 358.8654] +24-11-19 20:32:49 | D | best error = [ 5.5059, 5.5059, 5.5059, 5.5059, 5.5059] +24-11-19 20:32:49 | D | + error = [5.5059] +24-11-19 20:32:49 | D | - Calibrating model.layers.20.self_attn.o_proj.weight +24-11-19 20:32:49 | D | + w: sint8 +24-11-19 20:32:49 | D | + x: None +24-11-19 20:32:49 | D | + y: None +24-11-19 20:32:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:49 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:32:49 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:32:49 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:32:49 | D | - range ratio = [ 1.0000] +24-11-19 20:32:49 | D | sum error = [ 1.6047] +24-11-19 20:32:49 | D | best error = [ 1.6047] +24-11-19 20:32:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:50 | D | sum error = [ 1.5926, 1.5806, 1.5856, 1.6034, 1.6210] +24-11-19 20:32:50 | D | best error = [ 1.4783, 1.4200, 1.3869, 1.3671, 1.3519] +24-11-19 20:32:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:50 | D | sum error = [ 1.6511, 1.6911, 1.7531, 1.8247, 1.9038] +24-11-19 20:32:50 | D | best error = [ 1.3413, 1.3341, 1.3287, 1.3255, 1.3228] +24-11-19 20:32:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:50 | D | sum error = [ 2.0028, 2.1191, 2.2477, 2.3784, 2.5336] +24-11-19 20:32:50 | D | best error = [ 1.3206, 1.3193, 1.3187, 1.3181, 1.3174] +24-11-19 20:32:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:50 | D | sum error = [ 2.7063, 2.8773, 3.0775, 3.2926, 3.5154] +24-11-19 20:32:50 | D | best error = [ 1.3172, 1.3169, 1.3166, 1.3165, 1.3164] +24-11-19 20:32:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:50 | D | sum error = [ 3.7619, 4.0191, 4.2992, 4.5890, 4.9028] +24-11-19 20:32:50 | D | best error = [ 1.3163, 1.3163, 1.3161, 1.3161, 1.3161] +24-11-19 20:32:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:50 | D | sum error = [ 5.2417, 5.5913, 5.9712, 6.3675, 6.7928] +24-11-19 20:32:50 | D | best error = [ 1.3161, 1.3161, 1.3161, 1.3161, 1.3161] +24-11-19 20:32:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:50 | D | sum error = [ 7.2349, 7.7012, 8.1997, 8.7283, 9.2773] +24-11-19 20:32:50 | D | best error = [ 1.3161, 1.3161, 1.3161, 1.3161, 1.3161] +24-11-19 20:32:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:50 | D | sum error = [ 9.8629, 10.4843, 11.1303, 11.8111, 12.5261] +24-11-19 20:32:50 | D | best error = [ 1.3161, 1.3161, 1.3161, 1.3161, 1.3161] +24-11-19 20:32:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:50 | D | sum error = [ 13.2882, 14.0785, 14.9128, 15.7928, 16.7147] +24-11-19 20:32:50 | D | best error = [ 1.3161, 1.3161, 1.3161, 1.3161, 1.3161] +24-11-19 20:32:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:50 | D | sum error = [ 17.6812, 18.6909, 19.7542, 20.8753, 22.0469] +24-11-19 20:32:50 | D | best error = [ 1.3161, 1.3161, 1.3161, 1.3161, 1.3161] +24-11-19 20:32:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:50 | D | sum error = [ 23.2752, 24.5711, 25.9207, 27.3431, 28.8271] +24-11-19 20:32:50 | D | best error = [ 1.3161, 1.3161, 1.3161, 1.3161, 1.3161] +24-11-19 20:32:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:50 | D | sum error = [ 30.3818, 32.0121, 33.7141, 35.4952, 37.3494] +24-11-19 20:32:50 | D | best error = [ 1.3161, 1.3161, 1.3161, 1.3161, 1.3161] +24-11-19 20:32:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:50 | D | sum error = [ 39.2927, 41.3191, 43.4343, 45.6457, 47.9468] +24-11-19 20:32:50 | D | best error = [ 1.3161, 1.3161, 1.3161, 1.3161, 1.3161] +24-11-19 20:32:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:50 | D | sum error = [ 50.3408, 52.8277, 55.4086, 58.0955, 60.8810] +24-11-19 20:32:50 | D | best error = [ 1.3161, 1.3161, 1.3161, 1.3161, 1.3161] +24-11-19 20:32:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:50 | D | sum error = [ 63.7701, 66.7697, 69.8807, 73.1038, 76.4424] +24-11-19 20:32:50 | D | best error = [ 1.3161, 1.3161, 1.3161, 1.3161, 1.3161] +24-11-19 20:32:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:50 | D | sum error = [ 79.8965, 83.4667, 87.1574, 90.9630, 94.8970] +24-11-19 20:32:50 | D | best error = [ 1.3161, 1.3161, 1.3161, 1.3161, 1.3161] +24-11-19 20:32:50 | D | + error = [1.3161] +24-11-19 20:32:50 | D | - Calibrating model.layers.20.mlp.up_proj.weight +24-11-19 20:32:50 | D | + w: sint8 +24-11-19 20:32:50 | D | + x: None +24-11-19 20:32:50 | D | + y: None +24-11-19 20:32:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:50 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:32:50 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:32:50 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:32:50 | D | - range ratio = [ 1.0000] +24-11-19 20:32:50 | D | sum error = [ 8.8652] +24-11-19 20:32:50 | D | best error = [ 8.8652] +24-11-19 20:32:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:51 | D | sum error = [ 8.7905, 8.7809, 8.7994, 8.8916, 9.0732] +24-11-19 20:32:51 | D | best error = [ 8.2409, 8.0054, 7.8696, 7.7956, 7.7557] +24-11-19 20:32:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:51 | D | sum error = [ 9.3095, 9.6131, 9.9981, 10.4632, 11.0299] +24-11-19 20:32:51 | D | best error = [ 7.7355, 7.7268, 7.7236, 7.7223, 7.7220] +24-11-19 20:32:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:51 | D | sum error = [ 11.6515, 12.3829, 13.1598, 14.0526, 15.0231] +24-11-19 20:32:51 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:32:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:51 | D | sum error = [ 16.0747, 17.2032, 18.4510, 19.7852, 21.1864] +24-11-19 20:32:51 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:32:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:51 | D | sum error = [ 22.7063, 24.3036, 26.0147, 27.8598, 29.7860] +24-11-19 20:32:51 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:32:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:51 | D | sum error = [ 31.8367, 34.0226, 36.3281, 38.7613, 41.3223] +24-11-19 20:32:51 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:32:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:51 | D | sum error = [ 44.0567, 46.9200, 49.9451, 53.1462, 56.5013] +24-11-19 20:32:51 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:32:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:51 | D | sum error = [ 60.0355, 63.7922, 67.7206, 71.8454, 76.2303] +24-11-19 20:32:51 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:32:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:51 | D | sum error = [ 80.7661, 85.5905, 90.6185, 95.8913, 101.4189] +24-11-19 20:32:51 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:32:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:51 | D | sum error = [ 107.2223, 113.2944, 119.6501, 126.3206, 133.2850] +24-11-19 20:32:51 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:32:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:51 | D | sum error = [ 140.5746, 148.1895, 156.1293, 164.4445, 173.1074] +24-11-19 20:32:51 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:32:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:51 | D | sum error = [ 182.1464, 191.5566, 201.3938, 211.6277, 222.2925] +24-11-19 20:32:51 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:32:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:51 | D | sum error = [ 233.3481, 244.8608, 256.8228, 269.2520, 282.1510] +24-11-19 20:32:51 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:32:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:51 | D | sum error = [ 295.5086, 309.3653, 323.7314, 338.6105, 353.9892] +24-11-19 20:32:51 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:32:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:51 | D | sum error = [ 369.9061, 386.3700, 403.3692, 420.9413, 439.0771] +24-11-19 20:32:51 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:32:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:51 | D | sum error = [ 457.7665, 477.0336, 496.8793, 517.3178, 538.3206] +24-11-19 20:32:51 | D | best error = [ 7.7219, 7.7219, 7.7219, 7.7219, 7.7219] +24-11-19 20:32:51 | D | + error = [7.7219] +24-11-19 20:32:51 | D | - Calibrating model.layers.20.mlp.gate_proj.weight +24-11-19 20:32:51 | D | + w: sint8 +24-11-19 20:32:51 | D | + x: None +24-11-19 20:32:51 | D | + y: None +24-11-19 20:32:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:51 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:32:51 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:32:51 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:32:51 | D | - range ratio = [ 1.0000] +24-11-19 20:32:51 | D | sum error = [ 9.4608] +24-11-19 20:32:51 | D | best error = [ 9.4608] +24-11-19 20:32:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:52 | D | sum error = [ 9.3634, 9.3591, 9.3920, 9.5034, 9.6873] +24-11-19 20:32:52 | D | best error = [ 8.7997, 8.5409, 8.4000, 8.3218, 8.2801] +24-11-19 20:32:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:52 | D | sum error = [ 9.9493, 10.2753, 10.6811, 11.2229, 11.8117] +24-11-19 20:32:52 | D | best error = [ 8.2576, 8.2480, 8.2444, 8.2436, 8.2433] +24-11-19 20:32:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:52 | D | sum error = [ 12.4918, 13.2895, 14.1572, 15.0823, 16.1449] +24-11-19 20:32:52 | D | best error = [ 8.2433, 8.2433, 8.2433, 8.2433, 8.2433] +24-11-19 20:32:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:52 | D | sum error = [ 17.2951, 18.5221, 19.8818, 21.3320, 22.8645] +24-11-19 20:32:52 | D | best error = [ 8.2433, 8.2433, 8.2433, 8.2433, 8.2433] +24-11-19 20:32:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:52 | D | sum error = [ 24.5387, 26.3137, 28.1777, 30.2010, 32.3299] +24-11-19 20:32:52 | D | best error = [ 8.2433, 8.2433, 8.2433, 8.2433, 8.2433] +24-11-19 20:32:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:52 | D | sum error = [ 34.5725, 36.9748, 39.5279, 42.2334, 45.0651] +24-11-19 20:32:52 | D | best error = [ 8.2433, 8.2433, 8.2433, 8.2433, 8.2433] +24-11-19 20:32:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:52 | D | sum error = [ 48.1018, 51.2751, 54.6577, 58.2590, 62.0034] +24-11-19 20:32:52 | D | best error = [ 8.2433, 8.2433, 8.2433, 8.2433, 8.2433] +24-11-19 20:32:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:52 | D | sum error = [ 66.0274, 70.2284, 74.6916, 79.4053, 84.3928] +24-11-19 20:32:52 | D | best error = [ 8.2433, 8.2433, 8.2433, 8.2433, 8.2433] +24-11-19 20:32:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:52 | D | sum error = [ 89.6645, 95.2218, 101.0849, 107.2611, 113.7665] +24-11-19 20:32:52 | D | best error = [ 8.2433, 8.2433, 8.2433, 8.2433, 8.2433] +24-11-19 20:32:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:52 | D | sum error = [ 120.6072, 127.8130, 135.3854, 143.3565, 151.7414] +24-11-19 20:32:52 | D | best error = [ 8.2433, 8.2433, 8.2433, 8.2433, 8.2433] +24-11-19 20:32:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:52 | D | sum error = [ 160.5817, 169.8460, 179.5969, 189.8458, 200.6096] +24-11-19 20:32:52 | D | best error = [ 8.2433, 8.2433, 8.2433, 8.2433, 8.2433] +24-11-19 20:32:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:52 | D | sum error = [ 211.8559, 223.6729, 236.0644, 249.0014, 262.5647] +24-11-19 20:32:52 | D | best error = [ 8.2433, 8.2433, 8.2433, 8.2433, 8.2433] +24-11-19 20:32:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:52 | D | sum error = [ 276.7363, 291.5793, 307.0648, 323.2548, 340.1263] +24-11-19 20:32:52 | D | best error = [ 8.2433, 8.2433, 8.2433, 8.2433, 8.2433] +24-11-19 20:32:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:52 | D | sum error = [ 357.7361, 376.1187, 395.2570, 415.1422, 435.8698] +24-11-19 20:32:52 | D | best error = [ 8.2433, 8.2433, 8.2433, 8.2433, 8.2433] +24-11-19 20:32:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:52 | D | sum error = [ 457.3788, 479.6821, 502.7996, 526.7703, 551.6033] +24-11-19 20:32:52 | D | best error = [ 8.2433, 8.2433, 8.2433, 8.2433, 8.2433] +24-11-19 20:32:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:52 | D | sum error = [ 577.2820, 603.8265, 631.2121, 659.4608, 688.5733] +24-11-19 20:32:52 | D | best error = [ 8.2433, 8.2433, 8.2433, 8.2433, 8.2433] +24-11-19 20:32:52 | D | + error = [8.2433] +24-11-19 20:32:52 | D | - Calibrating model.layers.20.mlp.down_proj.weight +24-11-19 20:32:52 | D | + w: sint8 +24-11-19 20:32:52 | D | + x: None +24-11-19 20:32:52 | D | + y: None +24-11-19 20:32:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:52 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:32:53 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:32:53 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:32:53 | D | - range ratio = [ 1.0000] +24-11-19 20:32:53 | D | sum error = [ 3.4711] +24-11-19 20:32:53 | D | best error = [ 3.4711] +24-11-19 20:32:54 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:54 | D | sum error = [ 3.4366, 3.4104, 3.3994, 3.3893, 3.3953] +24-11-19 20:32:54 | D | best error = [ 3.3106, 3.2335, 3.1800, 3.1414, 3.1137] +24-11-19 20:32:54 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:54 | D | sum error = [ 3.4134, 3.4469, 3.4994, 3.5596, 3.6437] +24-11-19 20:32:54 | D | best error = [ 3.0927, 3.0765, 3.0650, 3.0554, 3.0489] +24-11-19 20:32:54 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:54 | D | sum error = [ 3.7659, 3.8949, 4.0479, 4.2459, 4.4462] +24-11-19 20:32:54 | D | best error = [ 3.0446, 3.0410, 3.0392, 3.0380, 3.0373] +24-11-19 20:32:54 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:54 | D | sum error = [ 4.6807, 4.9446, 5.2503, 5.5606, 5.9164] +24-11-19 20:32:54 | D | best error = [ 3.0367, 3.0362, 3.0360, 3.0359, 3.0359] +24-11-19 20:32:54 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:54 | D | sum error = [ 6.3005, 6.7241, 7.1721, 7.6591, 8.1865] +24-11-19 20:32:54 | D | best error = [ 3.0358, 3.0358, 3.0358, 3.0358, 3.0358] +24-11-19 20:32:54 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:54 | D | sum error = [ 8.7450, 9.3425, 9.9802, 10.6711, 11.4031] +24-11-19 20:32:54 | D | best error = [ 3.0358, 3.0358, 3.0358, 3.0358, 3.0358] +24-11-19 20:32:54 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:54 | D | sum error = [ 12.1882, 13.0137, 13.8938, 14.8296, 15.8186] +24-11-19 20:32:54 | D | best error = [ 3.0358, 3.0358, 3.0358, 3.0358, 3.0358] +24-11-19 20:32:54 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:54 | D | sum error = [ 16.8835, 17.9867, 19.1782, 20.4162, 21.7394] +24-11-19 20:32:54 | D | best error = [ 3.0358, 3.0358, 3.0358, 3.0358, 3.0358] +24-11-19 20:32:54 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:54 | D | sum error = [ 23.1408, 24.6166, 26.1686, 27.8123, 29.5458] +24-11-19 20:32:54 | D | best error = [ 3.0358, 3.0358, 3.0358, 3.0358, 3.0358] +24-11-19 20:32:54 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:54 | D | sum error = [ 31.3721, 33.2920, 35.3167, 37.4506, 39.6849] +24-11-19 20:32:54 | D | best error = [ 3.0358, 3.0358, 3.0358, 3.0358, 3.0358] +24-11-19 20:32:54 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:54 | D | sum error = [ 42.0399, 44.5106, 47.1026, 49.8306, 52.6796] +24-11-19 20:32:54 | D | best error = [ 3.0358, 3.0358, 3.0358, 3.0358, 3.0358] +24-11-19 20:32:54 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:54 | D | sum error = [ 55.6726, 58.8076, 62.0836, 65.5170, 69.1134] +24-11-19 20:32:54 | D | best error = [ 3.0358, 3.0358, 3.0358, 3.0358, 3.0358] +24-11-19 20:32:54 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:54 | D | sum error = [ 72.8659, 76.7936, 80.8798, 85.1452, 89.5948] +24-11-19 20:32:54 | D | best error = [ 3.0358, 3.0358, 3.0358, 3.0358, 3.0358] +24-11-19 20:32:54 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:54 | D | sum error = [ 94.2220, 99.0442, 104.0581, 109.2774, 114.6926] +24-11-19 20:32:54 | D | best error = [ 3.0358, 3.0358, 3.0358, 3.0358, 3.0358] +24-11-19 20:32:54 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:54 | D | sum error = [ 120.3326, 126.1783, 132.2492, 138.5415, 145.0549] +24-11-19 20:32:54 | D | best error = [ 3.0358, 3.0358, 3.0358, 3.0358, 3.0358] +24-11-19 20:32:54 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:54 | D | sum error = [ 151.7934, 158.7648, 165.9716, 173.4180, 181.1017] +24-11-19 20:32:54 | D | best error = [ 3.0358, 3.0358, 3.0358, 3.0358, 3.0358] +24-11-19 20:32:54 | D | + error = [3.0358] +24-11-19 20:32:54 | D | - Quantizing model.layers.20.self_attn.q_proj.weight +24-11-19 20:32:55 | D | - Quantizing model.layers.20.self_attn.k_proj.weight +24-11-19 20:32:55 | D | - Quantizing model.layers.20.self_attn.v_proj.weight +24-11-19 20:32:56 | D | - Quantizing model.layers.20.self_attn.o_proj.weight +24-11-19 20:32:57 | D | - Quantizing model.layers.20.mlp.up_proj.weight +24-11-19 20:32:58 | D | - Quantizing model.layers.20.mlp.gate_proj.weight +24-11-19 20:32:59 | D | - Quantizing model.layers.20.mlp.down_proj.weight +24-11-19 20:33:07 | D | - Quantizing layer model.layers.21 +24-11-19 20:33:07 | D | - Calibrating model.layers.21.self_attn.q_proj.weight +24-11-19 20:33:07 | D | + w: sint8 +24-11-19 20:33:07 | D | + x: None +24-11-19 20:33:07 | D | + y: None +24-11-19 20:33:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:33:07 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:33:07 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:33:07 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:33:07 | D | - range ratio = [ 1.0000] +24-11-19 20:33:07 | D | sum error = [ 12.0186] +24-11-19 20:33:07 | D | best error = [ 12.0186] +24-11-19 20:33:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:20 | D | sum error = [ 11.7856, 11.8214, 11.7766, 12.0277, 12.2959] +24-11-19 20:33:20 | D | best error = [ 11.7856, 11.7856, 11.7766, 11.7766, 11.7766] +24-11-19 20:33:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:20 | D | sum error = [ 12.5558, 13.0341, 13.7637, 14.3179, 14.9818] +24-11-19 20:33:20 | D | best error = [ 11.7766, 11.7766, 11.7766, 11.7766, 11.7766] +24-11-19 20:33:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:20 | D | sum error = [ 15.9521, 17.1145, 18.1903, 19.4876, 20.8020] +24-11-19 20:33:20 | D | best error = [ 11.7766, 11.7766, 11.7766, 11.7766, 11.7766] +24-11-19 20:33:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:20 | D | sum error = [ 22.8318, 24.3513, 26.0785, 28.0143, 30.3578] +24-11-19 20:33:20 | D | best error = [ 11.7766, 11.7766, 11.7766, 11.7766, 11.7766] +24-11-19 20:33:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:20 | D | sum error = [ 32.7085, 35.3874, 38.0911, 41.0970, 44.0017] +24-11-19 20:33:20 | D | best error = [ 11.7766, 11.7766, 11.7766, 11.7766, 11.7766] +24-11-19 20:33:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:20 | D | sum error = [ 47.4987, 51.1562, 55.2268, 59.3839, 63.9335] +24-11-19 20:33:20 | D | best error = [ 11.7766, 11.7766, 11.7766, 11.7766, 11.7766] +24-11-19 20:33:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:20 | D | sum error = [ 68.7969, 73.8533, 79.3746, 85.7263, 92.4352] +24-11-19 20:33:20 | D | best error = [ 11.7766, 11.7766, 11.7766, 11.7766, 11.7766] +24-11-19 20:33:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:20 | D | sum error = [ 99.1618, 106.7845, 114.7535, 123.7822, 132.7100] +24-11-19 20:33:20 | D | best error = [ 11.7766, 11.7766, 11.7766, 11.7766, 11.7766] +24-11-19 20:33:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:20 | D | sum error = [ 143.0115, 153.9287, 165.5677, 178.4183, 191.7212] +24-11-19 20:33:20 | D | best error = [ 11.7766, 11.7766, 11.7766, 11.7766, 11.7766] +24-11-19 20:33:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:20 | D | sum error = [ 206.7920, 222.5609, 240.0371, 258.4808, 278.9630] +24-11-19 20:33:20 | D | best error = [ 11.7766, 11.7766, 11.7766, 11.7766, 11.7766] +24-11-19 20:33:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:20 | D | sum error = [ 301.2844, 324.6172, 349.9852, 377.2125, 407.5917] +24-11-19 20:33:20 | D | best error = [ 11.7766, 11.7766, 11.7766, 11.7766, 11.7766] +24-11-19 20:33:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:20 | D | sum error = [ 439.1525, 473.7692, 511.4554, 553.4044, 598.2832] +24-11-19 20:33:20 | D | best error = [ 11.7766, 11.7766, 11.7766, 11.7766, 11.7766] +24-11-19 20:33:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:20 | D | sum error = [ 647.0749, 700.8424, 759.7493, 824.4402, 894.2326] +24-11-19 20:33:20 | D | best error = [ 11.7766, 11.7766, 11.7766, 11.7766, 11.7766] +24-11-19 20:33:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:20 | D | sum error = [ 971.7360, 1056.0179, 1147.9609, 1250.2400, 1361.8758] +24-11-19 20:33:20 | D | best error = [ 11.7766, 11.7766, 11.7766, 11.7766, 11.7766] +24-11-19 20:33:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:20 | D | sum error = [ 1485.9823, 1621.8162, 1772.9199, 1939.4417, 2122.9056] +24-11-19 20:33:20 | D | best error = [ 11.7766, 11.7766, 11.7766, 11.7766, 11.7766] +24-11-19 20:33:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:20 | D | sum error = [ 2323.3069, 2543.5392, 2783.9318, 3044.1514, 3323.5454] +24-11-19 20:33:20 | D | best error = [ 11.7766, 11.7766, 11.7766, 11.7766, 11.7766] +24-11-19 20:33:20 | D | + error = [11.7766] +24-11-19 20:33:20 | D | - Calibrating model.layers.21.self_attn.k_proj.weight +24-11-19 20:33:20 | D | + w: sint8 +24-11-19 20:33:20 | D | + x: None +24-11-19 20:33:20 | D | + y: None +24-11-19 20:33:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:33:20 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:33:20 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:33:20 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:33:20 | D | - range ratio = [ 1.0000] +24-11-19 20:33:20 | D | sum error = [ 13.7392] +24-11-19 20:33:20 | D | best error = [ 13.7392] +24-11-19 20:33:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:33 | D | sum error = [ 13.9753, 13.0848, 13.7309, 14.1340, 13.8546] +24-11-19 20:33:33 | D | best error = [ 13.7392, 13.0848, 13.0848, 13.0848, 13.0848] +24-11-19 20:33:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:33 | D | sum error = [ 16.1105, 14.9337, 15.4642, 16.2878, 16.8745] +24-11-19 20:33:33 | D | best error = [ 13.0848, 13.0848, 13.0848, 13.0848, 13.0848] +24-11-19 20:33:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:33 | D | sum error = [ 18.6828, 19.5935, 20.7701, 23.4144, 24.2932] +24-11-19 20:33:33 | D | best error = [ 13.0848, 13.0848, 13.0848, 13.0848, 13.0848] +24-11-19 20:33:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:33 | D | sum error = [ 26.3583, 28.5258, 30.0242, 34.0582, 35.5995] +24-11-19 20:33:33 | D | best error = [ 13.0848, 13.0848, 13.0848, 13.0848, 13.0848] +24-11-19 20:33:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:33 | D | sum error = [ 37.1760, 40.8155, 45.4984, 47.9843, 52.4152] +24-11-19 20:33:33 | D | best error = [ 13.0848, 13.0848, 13.0848, 13.0848, 13.0848] +24-11-19 20:33:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:33 | D | sum error = [ 56.0265, 59.7732, 65.3029, 68.8639, 73.5491] +24-11-19 20:33:33 | D | best error = [ 13.0848, 13.0848, 13.0848, 13.0848, 13.0848] +24-11-19 20:33:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:33 | D | sum error = [ 79.9145, 86.1247, 92.1425, 98.3449, 106.0935] +24-11-19 20:33:33 | D | best error = [ 13.0848, 13.0848, 13.0848, 13.0848, 13.0848] +24-11-19 20:33:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:33 | D | sum error = [ 113.7962, 122.4277, 131.2855, 141.9022, 151.7561] +24-11-19 20:33:33 | D | best error = [ 13.0848, 13.0848, 13.0848, 13.0848, 13.0848] +24-11-19 20:33:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:33 | D | sum error = [ 161.8520, 175.6861, 188.4198, 200.7319, 215.6764] +24-11-19 20:33:33 | D | best error = [ 13.0848, 13.0848, 13.0848, 13.0848, 13.0848] +24-11-19 20:33:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:33 | D | sum error = [ 232.3243, 248.3686, 266.6611, 286.6054, 307.8618] +24-11-19 20:33:33 | D | best error = [ 13.0848, 13.0848, 13.0848, 13.0848, 13.0848] +24-11-19 20:33:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:33 | D | sum error = [ 331.4963, 354.7452, 381.9185, 409.9812, 441.2766] +24-11-19 20:33:33 | D | best error = [ 13.0848, 13.0848, 13.0848, 13.0848, 13.0848] +24-11-19 20:33:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:33 | D | sum error = [ 475.9864, 512.3333, 552.7402, 596.3588, 642.4970] +24-11-19 20:33:33 | D | best error = [ 13.0848, 13.0848, 13.0848, 13.0848, 13.0848] +24-11-19 20:33:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:33 | D | sum error = [ 693.4230, 749.6845, 810.3676, 876.3787, 948.3467] +24-11-19 20:33:33 | D | best error = [ 13.0848, 13.0848, 13.0848, 13.0848, 13.0848] +24-11-19 20:33:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:33 | D | sum error = [ 1026.9581, 1113.8680, 1209.1768, 1314.9987, 1431.5000] +24-11-19 20:33:33 | D | best error = [ 13.0848, 13.0848, 13.0848, 13.0848, 13.0848] +24-11-19 20:33:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:33 | D | sum error = [ 1557.2497, 1696.8752, 1851.2536, 2022.8978, 2210.6612] +24-11-19 20:33:33 | D | best error = [ 13.0848, 13.0848, 13.0848, 13.0848, 13.0848] +24-11-19 20:33:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:33 | D | sum error = [ 2417.9013, 2643.2671, 2889.6377, 3154.0117, 3437.5832] +24-11-19 20:33:33 | D | best error = [ 13.0848, 13.0848, 13.0848, 13.0848, 13.0848] +24-11-19 20:33:33 | D | + error = [13.0848] +24-11-19 20:33:33 | D | - Calibrating model.layers.21.self_attn.v_proj.weight +24-11-19 20:33:33 | D | + w: sint8 +24-11-19 20:33:33 | D | + x: None +24-11-19 20:33:33 | D | + y: None +24-11-19 20:33:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:33 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:33:33 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:33:33 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:33:33 | D | - range ratio = [ 1.0000] +24-11-19 20:33:33 | D | sum error = [ 6.8642] +24-11-19 20:33:33 | D | best error = [ 6.8642] +24-11-19 20:33:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:33 | D | sum error = [ 6.7998, 6.8018, 6.8284, 6.8795, 7.0118] +24-11-19 20:33:33 | D | best error = [ 6.4111, 6.2229, 6.1234, 6.0670, 6.0377] +24-11-19 20:33:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:33 | D | sum error = [ 7.1786, 7.4563, 7.7366, 8.0925, 8.5119] +24-11-19 20:33:33 | D | best error = [ 6.0212, 6.0134, 6.0105, 6.0093, 6.0092] +24-11-19 20:33:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:33 | D | sum error = [ 9.0163, 9.5814, 10.1963, 10.9049, 11.6108] +24-11-19 20:33:33 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 20:33:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:33 | D | sum error = [ 12.4525, 13.3142, 14.2451, 15.2729, 16.3763] +24-11-19 20:33:33 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 20:33:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:33 | D | sum error = [ 17.5317, 18.7749, 20.1113, 21.5344, 23.0043] +24-11-19 20:33:33 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 20:33:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:33 | D | sum error = [ 24.5832, 26.2314, 27.9949, 29.8758, 31.8156] +24-11-19 20:33:33 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 20:33:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:33 | D | sum error = [ 33.8870, 36.0874, 38.3479, 40.7742, 43.3334] +24-11-19 20:33:33 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 20:33:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:33 | D | sum error = [ 45.9984, 48.8283, 51.7799, 54.8836, 58.1195] +24-11-19 20:33:33 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 20:33:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:33 | D | sum error = [ 61.5670, 65.1575, 68.9273, 72.8474, 76.9742] +24-11-19 20:33:33 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 20:33:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:33 | D | sum error = [ 81.2857, 85.7948, 90.5047, 95.4160, 100.5747] +24-11-19 20:33:33 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 20:33:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:33 | D | sum error = [ 105.9161, 111.5179, 117.3640, 123.4392, 129.7789] +24-11-19 20:33:33 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 20:33:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:33 | D | sum error = [ 136.3738, 143.2212, 150.3608, 157.7695, 165.4506] +24-11-19 20:33:33 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 20:33:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:33 | D | sum error = [ 173.4315, 181.7037, 190.2698, 199.1548, 208.3558] +24-11-19 20:33:33 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 20:33:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:33 | D | sum error = [ 217.8718, 227.7351, 237.9245, 248.4661, 259.3356] +24-11-19 20:33:33 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 20:33:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:33 | D | sum error = [ 270.5359, 282.0940, 294.0298, 306.3209, 318.9775] +24-11-19 20:33:33 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 20:33:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:33 | D | sum error = [ 332.0044, 345.4063, 359.1905, 373.3684, 387.9352] +24-11-19 20:33:33 | D | best error = [ 6.0092, 6.0092, 6.0092, 6.0092, 6.0092] +24-11-19 20:33:33 | D | + error = [6.0092] +24-11-19 20:33:34 | D | - Calibrating model.layers.21.self_attn.o_proj.weight +24-11-19 20:33:34 | D | + w: sint8 +24-11-19 20:33:34 | D | + x: None +24-11-19 20:33:34 | D | + y: None +24-11-19 20:33:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:34 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:33:34 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:33:34 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:33:34 | D | - range ratio = [ 1.0000] +24-11-19 20:33:34 | D | sum error = [ 1.3077] +24-11-19 20:33:34 | D | best error = [ 1.3077] +24-11-19 20:33:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:34 | D | sum error = [ 1.2976, 1.2920, 1.2940, 1.2998, 1.3198] +24-11-19 20:33:34 | D | best error = [ 1.2231, 1.1853, 1.1624, 1.1470, 1.1379] +24-11-19 20:33:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:34 | D | sum error = [ 1.3549, 1.3892, 1.4382, 1.4959, 1.5669] +24-11-19 20:33:34 | D | best error = [ 1.1319, 1.1279, 1.1251, 1.1236, 1.1224] +24-11-19 20:33:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:34 | D | sum error = [ 1.6502, 1.7423, 1.8440, 1.9682, 2.0886] +24-11-19 20:33:34 | D | best error = [ 1.1217, 1.1212, 1.1210, 1.1208, 1.1207] +24-11-19 20:33:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:34 | D | sum error = [ 2.2325, 2.3763, 2.5518, 2.7315, 2.9162] +24-11-19 20:33:34 | D | best error = [ 1.1206, 1.1205, 1.1205, 1.1204, 1.1204] +24-11-19 20:33:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:34 | D | sum error = [ 3.1258, 3.3390, 3.5660, 3.8169, 4.0797] +24-11-19 20:33:34 | D | best error = [ 1.1204, 1.1204, 1.1204, 1.1204, 1.1204] +24-11-19 20:33:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:34 | D | sum error = [ 4.3560, 4.6545, 4.9700, 5.2996, 5.6496] +24-11-19 20:33:34 | D | best error = [ 1.1204, 1.1204, 1.1204, 1.1204, 1.1204] +24-11-19 20:33:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:34 | D | sum error = [ 6.0199, 6.4125, 6.8314, 7.2693, 7.7300] +24-11-19 20:33:34 | D | best error = [ 1.1204, 1.1204, 1.1204, 1.1204, 1.1204] +24-11-19 20:33:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:34 | D | sum error = [ 8.2140, 8.7277, 9.2705, 9.8407, 10.4436] +24-11-19 20:33:34 | D | best error = [ 1.1204, 1.1204, 1.1204, 1.1204, 1.1204] +24-11-19 20:33:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:34 | D | sum error = [ 11.0723, 11.7342, 12.4332, 13.1677, 13.9359] +24-11-19 20:33:34 | D | best error = [ 1.1204, 1.1204, 1.1204, 1.1204, 1.1204] +24-11-19 20:33:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:34 | D | sum error = [ 14.7438, 15.5918, 16.4783, 17.4162, 18.3944] +24-11-19 20:33:34 | D | best error = [ 1.1204, 1.1204, 1.1204, 1.1204, 1.1204] +24-11-19 20:33:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:34 | D | sum error = [ 19.4121, 20.4831, 21.6019, 22.7707, 23.9942] +24-11-19 20:33:34 | D | best error = [ 1.1204, 1.1204, 1.1204, 1.1204, 1.1204] +24-11-19 20:33:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:34 | D | sum error = [ 25.2711, 26.6044, 27.9964, 29.4483, 30.9621] +24-11-19 20:33:34 | D | best error = [ 1.1204, 1.1204, 1.1204, 1.1204, 1.1204] +24-11-19 20:33:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:34 | D | sum error = [ 32.5413, 34.1853, 35.9012, 37.6800, 39.5319] +24-11-19 20:33:34 | D | best error = [ 1.1204, 1.1204, 1.1204, 1.1204, 1.1204] +24-11-19 20:33:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:34 | D | sum error = [ 41.4563, 43.4574, 45.5336, 47.6912, 49.9212] +24-11-19 20:33:34 | D | best error = [ 1.1204, 1.1204, 1.1204, 1.1204, 1.1204] +24-11-19 20:33:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:34 | D | sum error = [ 52.2383, 54.6358, 57.1210, 59.6870, 62.3387] +24-11-19 20:33:34 | D | best error = [ 1.1204, 1.1204, 1.1204, 1.1204, 1.1204] +24-11-19 20:33:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:34 | D | sum error = [ 65.0787, 67.9075, 70.8301, 73.8425, 76.9484] +24-11-19 20:33:34 | D | best error = [ 1.1204, 1.1204, 1.1204, 1.1204, 1.1204] +24-11-19 20:33:34 | D | + error = [1.1204] +24-11-19 20:33:34 | D | - Calibrating model.layers.21.mlp.up_proj.weight +24-11-19 20:33:34 | D | + w: sint8 +24-11-19 20:33:34 | D | + x: None +24-11-19 20:33:34 | D | + y: None +24-11-19 20:33:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:34 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:33:34 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:33:34 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:33:34 | D | - range ratio = [ 1.0000] +24-11-19 20:33:34 | D | sum error = [ 9.1194] +24-11-19 20:33:34 | D | best error = [ 9.1194] +24-11-19 20:33:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:35 | D | sum error = [ 9.0836, 9.0518, 9.0977, 9.1813, 9.3564] +24-11-19 20:33:35 | D | best error = [ 8.5041, 8.2546, 8.1236, 8.0431, 7.9983] +24-11-19 20:33:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:35 | D | sum error = [ 9.6171, 9.9371, 10.3388, 10.8011, 11.3554] +24-11-19 20:33:35 | D | best error = [ 7.9773, 7.9679, 7.9638, 7.9624, 7.9622] +24-11-19 20:33:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:35 | D | sum error = [ 12.0436, 12.7854, 13.6289, 14.5399, 15.5510] +24-11-19 20:33:35 | D | best error = [ 7.9622, 7.9621, 7.9621, 7.9621, 7.9621] +24-11-19 20:33:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:35 | D | sum error = [ 16.6606, 17.8371, 19.1382, 20.4913, 21.9806] +24-11-19 20:33:35 | D | best error = [ 7.9621, 7.9621, 7.9621, 7.9621, 7.9621] +24-11-19 20:33:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:35 | D | sum error = [ 23.5636, 25.2178, 26.9869, 28.8987, 30.9346] +24-11-19 20:33:35 | D | best error = [ 7.9621, 7.9621, 7.9621, 7.9621, 7.9621] +24-11-19 20:33:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:35 | D | sum error = [ 33.0464, 35.2860, 37.6700, 40.1972, 42.8538] +24-11-19 20:33:35 | D | best error = [ 7.9621, 7.9621, 7.9621, 7.9621, 7.9621] +24-11-19 20:33:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:35 | D | sum error = [ 45.6567, 48.6105, 51.7278, 55.0167, 58.4979] +24-11-19 20:33:35 | D | best error = [ 7.9621, 7.9621, 7.9621, 7.9621, 7.9621] +24-11-19 20:33:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:35 | D | sum error = [ 62.1340, 65.9478, 69.9993, 74.2599, 78.7270] +24-11-19 20:33:35 | D | best error = [ 7.9621, 7.9621, 7.9621, 7.9621, 7.9621] +24-11-19 20:33:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:35 | D | sum error = [ 83.4113, 88.3313, 93.4766, 98.9136, 104.6088] +24-11-19 20:33:35 | D | best error = [ 7.9621, 7.9621, 7.9621, 7.9621, 7.9621] +24-11-19 20:33:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:35 | D | sum error = [ 110.5565, 116.8094, 123.3362, 130.1743, 137.3207] +24-11-19 20:33:35 | D | best error = [ 7.9621, 7.9621, 7.9621, 7.9621, 7.9621] +24-11-19 20:33:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:35 | D | sum error = [ 144.7677, 152.5851, 160.7212, 169.2188, 178.0565] +24-11-19 20:33:35 | D | best error = [ 7.9621, 7.9621, 7.9621, 7.9621, 7.9621] +24-11-19 20:33:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:35 | D | sum error = [ 187.3028, 196.9317, 206.9481, 217.3836, 228.2512] +24-11-19 20:33:35 | D | best error = [ 7.9621, 7.9621, 7.9621, 7.9621, 7.9621] +24-11-19 20:33:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:35 | D | sum error = [ 239.5390, 251.2720, 263.4637, 276.1197, 289.2526] +24-11-19 20:33:35 | D | best error = [ 7.9621, 7.9621, 7.9621, 7.9621, 7.9621] +24-11-19 20:33:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:35 | D | sum error = [ 302.8748, 316.9896, 331.6057, 346.7422, 362.3980] +24-11-19 20:33:35 | D | best error = [ 7.9621, 7.9621, 7.9621, 7.9621, 7.9621] +24-11-19 20:33:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:35 | D | sum error = [ 378.5932, 395.3345, 412.6017, 430.4180, 448.7781] +24-11-19 20:33:35 | D | best error = [ 7.9621, 7.9621, 7.9621, 7.9621, 7.9621] +24-11-19 20:33:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:35 | D | sum error = [ 467.7074, 487.1868, 507.2490, 527.8800, 549.1058] +24-11-19 20:33:35 | D | best error = [ 7.9621, 7.9621, 7.9621, 7.9621, 7.9621] +24-11-19 20:33:35 | D | + error = [7.9621] +24-11-19 20:33:35 | D | - Calibrating model.layers.21.mlp.gate_proj.weight +24-11-19 20:33:35 | D | + w: sint8 +24-11-19 20:33:35 | D | + x: None +24-11-19 20:33:35 | D | + y: None +24-11-19 20:33:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:35 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:33:36 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:33:36 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:33:36 | D | - range ratio = [ 1.0000] +24-11-19 20:33:36 | D | sum error = [ 9.8574] +24-11-19 20:33:36 | D | best error = [ 9.8574] +24-11-19 20:33:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:37 | D | sum error = [ 9.7579, 9.7541, 9.7943, 9.8992, 10.0854] +24-11-19 20:33:37 | D | best error = [ 9.1679, 8.9011, 8.7466, 8.6639, 8.6184] +24-11-19 20:33:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:37 | D | sum error = [ 10.3640, 10.7093, 11.1397, 11.6686, 12.2971] +24-11-19 20:33:37 | D | best error = [ 8.5953, 8.5854, 8.5817, 8.5800, 8.5794] +24-11-19 20:33:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:37 | D | sum error = [ 13.0143, 13.7866, 14.7245, 15.7216, 16.8089] +24-11-19 20:33:37 | D | best error = [ 8.5793, 8.5792, 8.5792, 8.5792, 8.5792] +24-11-19 20:33:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:37 | D | sum error = [ 18.0294, 19.3382, 20.7015, 22.2035, 23.7942] +24-11-19 20:33:37 | D | best error = [ 8.5792, 8.5792, 8.5792, 8.5792, 8.5792] +24-11-19 20:33:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:37 | D | sum error = [ 25.5314, 27.3885, 29.3228, 31.3948, 33.6079] +24-11-19 20:33:37 | D | best error = [ 8.5792, 8.5792, 8.5792, 8.5792, 8.5792] +24-11-19 20:33:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:37 | D | sum error = [ 35.9343, 38.4197, 41.0614, 43.8494, 46.8179] +24-11-19 20:33:37 | D | best error = [ 8.5792, 8.5792, 8.5792, 8.5792, 8.5792] +24-11-19 20:33:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:37 | D | sum error = [ 49.9499, 53.2131, 56.7301, 60.4158, 64.3276] +24-11-19 20:33:37 | D | best error = [ 8.5792, 8.5792, 8.5792, 8.5792, 8.5792] +24-11-19 20:33:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:37 | D | sum error = [ 68.4500, 72.7786, 77.3718, 82.2299, 87.3260] +24-11-19 20:33:37 | D | best error = [ 8.5792, 8.5792, 8.5792, 8.5792, 8.5792] +24-11-19 20:33:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:37 | D | sum error = [ 92.7399, 98.4140, 104.4262, 110.7292, 117.3709] +24-11-19 20:33:37 | D | best error = [ 8.5792, 8.5792, 8.5792, 8.5792, 8.5792] +24-11-19 20:33:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:37 | D | sum error = [ 124.3542, 131.7211, 139.4452, 147.5714, 156.1295] +24-11-19 20:33:37 | D | best error = [ 8.5792, 8.5792, 8.5792, 8.5792, 8.5792] +24-11-19 20:33:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:37 | D | sum error = [ 165.1129, 174.5640, 184.4532, 194.8503, 205.7481] +24-11-19 20:33:37 | D | best error = [ 8.5792, 8.5792, 8.5792, 8.5792, 8.5792] +24-11-19 20:33:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:37 | D | sum error = [ 217.1622, 229.1182, 241.6556, 254.7684, 268.5012] +24-11-19 20:33:37 | D | best error = [ 8.5792, 8.5792, 8.5792, 8.5792, 8.5792] +24-11-19 20:33:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:37 | D | sum error = [ 282.8416, 297.8324, 313.4905, 329.8087, 346.8040] +24-11-19 20:33:37 | D | best error = [ 8.5792, 8.5792, 8.5792, 8.5792, 8.5792] +24-11-19 20:33:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:37 | D | sum error = [ 364.5386, 382.9841, 402.1731, 422.1388, 442.8888] +24-11-19 20:33:37 | D | best error = [ 8.5792, 8.5792, 8.5792, 8.5792, 8.5792] +24-11-19 20:33:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:37 | D | sum error = [ 464.4060, 486.7286, 509.8701, 533.8203, 558.6109] +24-11-19 20:33:37 | D | best error = [ 8.5792, 8.5792, 8.5792, 8.5792, 8.5792] +24-11-19 20:33:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:37 | D | sum error = [ 584.2204, 610.6826, 637.9772, 666.1253, 695.0983] +24-11-19 20:33:37 | D | best error = [ 8.5792, 8.5792, 8.5792, 8.5792, 8.5792] +24-11-19 20:33:37 | D | + error = [8.5792] +24-11-19 20:33:37 | D | - Calibrating model.layers.21.mlp.down_proj.weight +24-11-19 20:33:37 | D | + w: sint8 +24-11-19 20:33:37 | D | + x: None +24-11-19 20:33:37 | D | + y: None +24-11-19 20:33:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:37 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:33:37 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:33:37 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:33:37 | D | - range ratio = [ 1.0000] +24-11-19 20:33:37 | D | sum error = [ 3.5337] +24-11-19 20:33:37 | D | best error = [ 3.5337] +24-11-19 20:33:38 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:38 | D | sum error = [ 3.5092, 3.4774, 3.4575, 3.4540, 3.4520] +24-11-19 20:33:38 | D | best error = [ 3.3741, 3.2957, 3.2415, 3.2035, 3.1737] +24-11-19 20:33:38 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:38 | D | sum error = [ 3.4713, 3.4931, 3.5500, 3.6074, 3.6865] +24-11-19 20:33:38 | D | best error = [ 3.1519, 3.1336, 3.1215, 3.1123, 3.1054] +24-11-19 20:33:38 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:38 | D | sum error = [ 3.7920, 3.9185, 4.0714, 4.2427, 4.4385] +24-11-19 20:33:38 | D | best error = [ 3.1015, 3.0986, 3.0966, 3.0955, 3.0944] +24-11-19 20:33:38 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:38 | D | sum error = [ 4.6678, 4.9251, 5.2203, 5.5262, 5.8770] +24-11-19 20:33:38 | D | best error = [ 3.0939, 3.0936, 3.0936, 3.0935, 3.0934] +24-11-19 20:33:38 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:38 | D | sum error = [ 6.2603, 6.6666, 7.1181, 7.6078, 8.1329] +24-11-19 20:33:38 | D | best error = [ 3.0934, 3.0934, 3.0934, 3.0934, 3.0934] +24-11-19 20:33:38 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:38 | D | sum error = [ 8.6823, 9.2912, 9.9264, 10.6187, 11.3488] +24-11-19 20:33:38 | D | best error = [ 3.0934, 3.0934, 3.0934, 3.0934, 3.0934] +24-11-19 20:33:38 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:38 | D | sum error = [ 12.1378, 12.9735, 13.8657, 14.8124, 15.8172] +24-11-19 20:33:38 | D | best error = [ 3.0934, 3.0934, 3.0934, 3.0934, 3.0934] +24-11-19 20:33:38 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:38 | D | sum error = [ 16.8935, 18.0305, 19.2429, 20.5129, 21.8671] +24-11-19 20:33:38 | D | best error = [ 3.0934, 3.0934, 3.0934, 3.0934, 3.0934] +24-11-19 20:33:38 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:38 | D | sum error = [ 23.2936, 24.8031, 26.4008, 28.0856, 29.8585] +24-11-19 20:33:38 | D | best error = [ 3.0934, 3.0934, 3.0934, 3.0934, 3.0934] +24-11-19 20:33:38 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:38 | D | sum error = [ 31.7313, 33.6984, 35.7753, 37.9590, 40.2510] +24-11-19 20:33:38 | D | best error = [ 3.0934, 3.0934, 3.0934, 3.0934, 3.0934] +24-11-19 20:33:38 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:38 | D | sum error = [ 42.6613, 45.1957, 47.8509, 50.6453, 53.5618] +24-11-19 20:33:38 | D | best error = [ 3.0934, 3.0934, 3.0934, 3.0934, 3.0934] +24-11-19 20:33:38 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:38 | D | sum error = [ 56.6268, 59.8263, 63.1856, 66.6934, 70.3544] +24-11-19 20:33:38 | D | best error = [ 3.0934, 3.0934, 3.0934, 3.0934, 3.0934] +24-11-19 20:33:38 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:38 | D | sum error = [ 74.1855, 78.1776, 82.3510, 86.6919, 91.2275] +24-11-19 20:33:38 | D | best error = [ 3.0934, 3.0934, 3.0934, 3.0934, 3.0934] +24-11-19 20:33:38 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:38 | D | sum error = [ 95.9437, 100.8561, 105.9651, 111.2901, 116.7938] +24-11-19 20:33:38 | D | best error = [ 3.0934, 3.0934, 3.0934, 3.0934, 3.0934] +24-11-19 20:33:38 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:38 | D | sum error = [ 122.5158, 128.4521, 134.6151, 140.9939, 147.6003] +24-11-19 20:33:38 | D | best error = [ 3.0934, 3.0934, 3.0934, 3.0934, 3.0934] +24-11-19 20:33:38 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:38 | D | sum error = [ 154.4351, 161.5029, 168.8013, 176.3404, 184.1133] +24-11-19 20:33:38 | D | best error = [ 3.0934, 3.0934, 3.0934, 3.0934, 3.0934] +24-11-19 20:33:38 | D | + error = [3.0934] +24-11-19 20:33:38 | D | - Quantizing model.layers.21.self_attn.q_proj.weight +24-11-19 20:33:39 | D | - Quantizing model.layers.21.self_attn.k_proj.weight +24-11-19 20:33:40 | D | - Quantizing model.layers.21.self_attn.v_proj.weight +24-11-19 20:33:40 | D | - Quantizing model.layers.21.self_attn.o_proj.weight +24-11-19 20:33:41 | D | - Quantizing model.layers.21.mlp.up_proj.weight +24-11-19 20:33:42 | D | - Quantizing model.layers.21.mlp.gate_proj.weight +24-11-19 20:33:43 | D | - Quantizing model.layers.21.mlp.down_proj.weight +24-11-19 20:33:51 | D | - Quantizing layer model.layers.22 +24-11-19 20:33:51 | D | - Calibrating model.layers.22.self_attn.q_proj.weight +24-11-19 20:33:51 | D | + w: sint8 +24-11-19 20:33:51 | D | + x: None +24-11-19 20:33:51 | D | + y: None +24-11-19 20:33:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:33:51 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:33:51 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:33:51 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:33:51 | D | - range ratio = [ 1.0000] +24-11-19 20:33:51 | D | sum error = [ 13.7691] +24-11-19 20:33:51 | D | best error = [ 13.7691] +24-11-19 20:34:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:04 | D | sum error = [ 13.3560, 13.5656, 13.5527, 13.8466, 13.7478] +24-11-19 20:34:04 | D | best error = [ 13.3560, 13.3560, 13.3560, 13.3560, 13.3560] +24-11-19 20:34:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:04 | D | sum error = [ 14.3307, 14.6610, 15.4008, 16.1914, 17.2189] +24-11-19 20:34:04 | D | best error = [ 13.3560, 13.3560, 13.3560, 13.3560, 13.3560] +24-11-19 20:34:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:04 | D | sum error = [ 17.9701, 19.0466, 20.6760, 21.7790, 23.3363] +24-11-19 20:34:04 | D | best error = [ 13.3560, 13.3560, 13.3560, 13.3560, 13.3560] +24-11-19 20:34:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:04 | D | sum error = [ 24.8212, 26.9761, 28.9315, 31.2586, 34.1519] +24-11-19 20:34:04 | D | best error = [ 13.3560, 13.3560, 13.3560, 13.3560, 13.3560] +24-11-19 20:34:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:04 | D | sum error = [ 36.3752, 39.6328, 42.4847, 45.8313, 49.5507] +24-11-19 20:34:04 | D | best error = [ 13.3560, 13.3560, 13.3560, 13.3560, 13.3560] +24-11-19 20:34:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:04 | D | sum error = [ 53.6049, 57.8586, 62.2808, 67.3441, 72.4165] +24-11-19 20:34:04 | D | best error = [ 13.3560, 13.3560, 13.3560, 13.3560, 13.3560] +24-11-19 20:34:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:04 | D | sum error = [ 78.1799, 84.5835, 91.0649, 98.6789, 105.9410] +24-11-19 20:34:04 | D | best error = [ 13.3560, 13.3560, 13.3560, 13.3560, 13.3560] +24-11-19 20:34:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:04 | D | sum error = [ 114.5802, 123.1734, 132.5715, 143.4059, 154.2328] +24-11-19 20:34:04 | D | best error = [ 13.3560, 13.3560, 13.3560, 13.3560, 13.3560] +24-11-19 20:34:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:04 | D | sum error = [ 166.0402, 178.8062, 192.9473, 207.6452, 223.8016] +24-11-19 20:34:04 | D | best error = [ 13.3560, 13.3560, 13.3560, 13.3560, 13.3560] +24-11-19 20:34:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:04 | D | sum error = [ 240.7831, 259.3630, 279.4266, 300.5634, 323.5522] +24-11-19 20:34:04 | D | best error = [ 13.3560, 13.3560, 13.3560, 13.3560, 13.3560] +24-11-19 20:34:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:04 | D | sum error = [ 347.9490, 374.2322, 403.4449, 434.6560, 467.9251] +24-11-19 20:34:04 | D | best error = [ 13.3560, 13.3560, 13.3560, 13.3560, 13.3560] +24-11-19 20:34:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:04 | D | sum error = [ 505.0657, 543.6526, 586.1924, 632.2546, 681.8677] +24-11-19 20:34:04 | D | best error = [ 13.3560, 13.3560, 13.3560, 13.3560, 13.3560] +24-11-19 20:34:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:04 | D | sum error = [ 736.9756, 795.7351, 861.3404, 931.5105, 1008.6998] +24-11-19 20:34:04 | D | best error = [ 13.3560, 13.3560, 13.3560, 13.3560, 13.3560] +24-11-19 20:34:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:04 | D | sum error = [ 1093.7432, 1187.4501, 1288.7611, 1401.8239, 1524.5657] +24-11-19 20:34:04 | D | best error = [ 13.3560, 13.3560, 13.3560, 13.3560, 13.3560] +24-11-19 20:34:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:04 | D | sum error = [ 1661.1356, 1809.9046, 1972.7481, 2153.8553, 2352.3813] +24-11-19 20:34:04 | D | best error = [ 13.3560, 13.3560, 13.3560, 13.3560, 13.3560] +24-11-19 20:34:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:04 | D | sum error = [ 2568.4863, 2806.3108, 3064.5642, 3344.5831, 3648.8241] +24-11-19 20:34:04 | D | best error = [ 13.3560, 13.3560, 13.3560, 13.3560, 13.3560] +24-11-19 20:34:04 | D | + error = [13.3560] +24-11-19 20:34:04 | D | - Calibrating model.layers.22.self_attn.k_proj.weight +24-11-19 20:34:04 | D | + w: sint8 +24-11-19 20:34:04 | D | + x: None +24-11-19 20:34:04 | D | + y: None +24-11-19 20:34:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:34:04 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:34:04 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:34:04 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:34:05 | D | - range ratio = [ 1.0000] +24-11-19 20:34:05 | D | sum error = [ 16.1740] +24-11-19 20:34:05 | D | best error = [ 16.1740] +24-11-19 20:34:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:17 | D | sum error = [ 17.9390, 16.6958, 17.5377, 17.5652, 19.4801] +24-11-19 20:34:17 | D | best error = [ 16.1740, 16.1740, 16.1740, 16.1740, 16.1740] +24-11-19 20:34:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:17 | D | sum error = [ 17.4735, 19.0322, 17.5633, 18.8829, 23.1048] +24-11-19 20:34:17 | D | best error = [ 16.1740, 16.1740, 16.1740, 16.1740, 16.1740] +24-11-19 20:34:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:17 | D | sum error = [ 20.9536, 24.1310, 24.0594, 26.1908, 28.1675] +24-11-19 20:34:17 | D | best error = [ 16.1740, 16.1740, 16.1740, 16.1740, 16.1740] +24-11-19 20:34:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:17 | D | sum error = [ 30.7507, 32.7337, 34.6091, 38.3579, 42.0004] +24-11-19 20:34:17 | D | best error = [ 16.1740, 16.1740, 16.1740, 16.1740, 16.1740] +24-11-19 20:34:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:17 | D | sum error = [ 43.3917, 48.4958, 49.3602, 54.3945, 58.0590] +24-11-19 20:34:17 | D | best error = [ 16.1740, 16.1740, 16.1740, 16.1740, 16.1740] +24-11-19 20:34:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:17 | D | sum error = [ 62.6291, 66.2995, 71.8107, 79.0687, 82.1675] +24-11-19 20:34:17 | D | best error = [ 16.1740, 16.1740, 16.1740, 16.1740, 16.1740] +24-11-19 20:34:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:17 | D | sum error = [ 89.4309, 95.1248, 102.6643, 113.1502, 120.7035] +24-11-19 20:34:17 | D | best error = [ 16.1740, 16.1740, 16.1740, 16.1740, 16.1740] +24-11-19 20:34:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:17 | D | sum error = [ 128.2731, 138.4886, 149.4947, 162.5053, 173.2641] +24-11-19 20:34:17 | D | best error = [ 16.1740, 16.1740, 16.1740, 16.1740, 16.1740] +24-11-19 20:34:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:17 | D | sum error = [ 192.4125, 206.7729, 222.9504, 239.5462, 257.4265] +24-11-19 20:34:17 | D | best error = [ 16.1740, 16.1740, 16.1740, 16.1740, 16.1740] +24-11-19 20:34:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:17 | D | sum error = [ 276.3278, 297.4210, 319.3205, 346.3570, 373.4574] +24-11-19 20:34:17 | D | best error = [ 16.1740, 16.1740, 16.1740, 16.1740, 16.1740] +24-11-19 20:34:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:17 | D | sum error = [ 402.9258, 436.2964, 470.5923, 507.1976, 545.0121] +24-11-19 20:34:17 | D | best error = [ 16.1740, 16.1740, 16.1740, 16.1740, 16.1740] +24-11-19 20:34:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:17 | D | sum error = [ 586.3532, 635.8428, 684.8536, 739.7433, 799.0301] +24-11-19 20:34:17 | D | best error = [ 16.1740, 16.1740, 16.1740, 16.1740, 16.1740] +24-11-19 20:34:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:17 | D | sum error = [ 863.7911, 932.1413, 1006.6084, 1088.1605, 1176.0254] +24-11-19 20:34:17 | D | best error = [ 16.1740, 16.1740, 16.1740, 16.1740, 16.1740] +24-11-19 20:34:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:17 | D | sum error = [ 1269.7993, 1378.2561, 1493.0147, 1619.7279, 1761.4514] +24-11-19 20:34:17 | D | best error = [ 16.1740, 16.1740, 16.1740, 16.1740, 16.1740] +24-11-19 20:34:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:17 | D | sum error = [ 1912.2916, 2075.9640, 2253.3695, 2444.1630, 2650.6846] +24-11-19 20:34:17 | D | best error = [ 16.1740, 16.1740, 16.1740, 16.1740, 16.1740] +24-11-19 20:34:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:17 | D | sum error = [ 2874.3884, 3119.0191, 3378.3082, 3650.1731, 3941.1757] +24-11-19 20:34:17 | D | best error = [ 16.1740, 16.1740, 16.1740, 16.1740, 16.1740] +24-11-19 20:34:17 | D | + error = [16.1740] +24-11-19 20:34:18 | D | - Calibrating model.layers.22.self_attn.v_proj.weight +24-11-19 20:34:18 | D | + w: sint8 +24-11-19 20:34:18 | D | + x: None +24-11-19 20:34:18 | D | + y: None +24-11-19 20:34:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:18 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:34:18 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:34:18 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:34:18 | D | - range ratio = [ 1.0000] +24-11-19 20:34:18 | D | sum error = [ 6.9745] +24-11-19 20:34:18 | D | best error = [ 6.9745] +24-11-19 20:34:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:18 | D | sum error = [ 6.9371, 6.9066, 6.9608, 7.0469, 7.1696] +24-11-19 20:34:18 | D | best error = [ 6.5132, 6.3258, 6.2211, 6.1613, 6.1258] +24-11-19 20:34:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:18 | D | sum error = [ 7.3338, 7.6013, 7.8552, 8.2550, 8.7077] +24-11-19 20:34:18 | D | best error = [ 6.1096, 6.1025, 6.0999, 6.0983, 6.0980] +24-11-19 20:34:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:18 | D | sum error = [ 9.1970, 9.7549, 10.3967, 11.0712, 11.8424] +24-11-19 20:34:18 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 20:34:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:18 | D | sum error = [ 12.6838, 13.6030, 14.5729, 15.6212, 16.7604] +24-11-19 20:34:18 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 20:34:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:18 | D | sum error = [ 17.9535, 19.2457, 20.5263, 21.9813, 23.5128] +24-11-19 20:34:18 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 20:34:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:18 | D | sum error = [ 25.1400, 26.8285, 28.6326, 30.5458, 32.5346] +24-11-19 20:34:18 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 20:34:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:18 | D | sum error = [ 34.6662, 36.8680, 39.2088, 41.7110, 44.2932] +24-11-19 20:34:18 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 20:34:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:18 | D | sum error = [ 47.0480, 49.9110, 52.9479, 56.0983, 59.4389] +24-11-19 20:34:18 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 20:34:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:18 | D | sum error = [ 62.9375, 66.6009, 70.4841, 74.5041, 78.7117] +24-11-19 20:34:18 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 20:34:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:18 | D | sum error = [ 83.1477, 87.7771, 92.5996, 97.6677, 102.9379] +24-11-19 20:34:18 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 20:34:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:18 | D | sum error = [ 108.4256, 114.1937, 120.1808, 126.4460, 132.9662] +24-11-19 20:34:18 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 20:34:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:18 | D | sum error = [ 139.7467, 146.7832, 154.1300, 161.7538, 169.6376] +24-11-19 20:34:18 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 20:34:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:18 | D | sum error = [ 177.8568, 186.3549, 195.2018, 204.3418, 213.8211] +24-11-19 20:34:18 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 20:34:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:18 | D | sum error = [ 223.6199, 233.7806, 244.2858, 255.1577, 266.3596] +24-11-19 20:34:18 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 20:34:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:18 | D | sum error = [ 277.9607, 289.8907, 302.2147, 314.9025, 327.9780] +24-11-19 20:34:18 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 20:34:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:18 | D | sum error = [ 341.4283, 355.2746, 369.5290, 384.2015, 399.2660] +24-11-19 20:34:18 | D | best error = [ 6.0980, 6.0980, 6.0980, 6.0980, 6.0980] +24-11-19 20:34:18 | D | + error = [6.0980] +24-11-19 20:34:18 | D | - Calibrating model.layers.22.self_attn.o_proj.weight +24-11-19 20:34:18 | D | + w: sint8 +24-11-19 20:34:18 | D | + x: None +24-11-19 20:34:18 | D | + y: None +24-11-19 20:34:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:18 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:34:18 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:34:18 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:34:18 | D | - range ratio = [ 1.0000] +24-11-19 20:34:18 | D | sum error = [ 1.5648] +24-11-19 20:34:18 | D | best error = [ 1.5648] +24-11-19 20:34:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:19 | D | sum error = [ 1.5486, 1.5491, 1.5550, 1.5658, 1.5862] +24-11-19 20:34:19 | D | best error = [ 1.4815, 1.4435, 1.4210, 1.4075, 1.3987] +24-11-19 20:34:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:19 | D | sum error = [ 1.6228, 1.6735, 1.7313, 1.8046, 1.8892] +24-11-19 20:34:19 | D | best error = [ 1.3929, 1.3888, 1.3864, 1.3846, 1.3835] +24-11-19 20:34:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:19 | D | sum error = [ 1.9908, 2.1010, 2.2260, 2.3721, 2.5228] +24-11-19 20:34:19 | D | best error = [ 1.3828, 1.3822, 1.3818, 1.3815, 1.3813] +24-11-19 20:34:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:19 | D | sum error = [ 2.6907, 2.8736, 3.0648, 3.2758, 3.5006] +24-11-19 20:34:19 | D | best error = [ 1.3813, 1.3812, 1.3810, 1.3810, 1.3809] +24-11-19 20:34:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:19 | D | sum error = [ 3.7468, 4.0006, 4.2801, 4.5661, 4.8720] +24-11-19 20:34:19 | D | best error = [ 1.3809, 1.3809, 1.3809, 1.3808, 1.3808] +24-11-19 20:34:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:19 | D | sum error = [ 5.1999, 5.5501, 5.9161, 6.3049, 6.7178] +24-11-19 20:34:19 | D | best error = [ 1.3808, 1.3808, 1.3808, 1.3808, 1.3808] +24-11-19 20:34:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:19 | D | sum error = [ 7.1490, 7.6128, 8.0999, 8.6075, 9.1502] +24-11-19 20:34:19 | D | best error = [ 1.3808, 1.3808, 1.3808, 1.3808, 1.3808] +24-11-19 20:34:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:19 | D | sum error = [ 9.7210, 10.3206, 10.9513, 11.6173, 12.3190] +24-11-19 20:34:19 | D | best error = [ 1.3808, 1.3808, 1.3808, 1.3808, 1.3808] +24-11-19 20:34:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:19 | D | sum error = [ 13.0551, 13.8347, 14.6496, 15.5095, 16.4132] +24-11-19 20:34:19 | D | best error = [ 1.3808, 1.3808, 1.3808, 1.3808, 1.3808] +24-11-19 20:34:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:19 | D | sum error = [ 17.3610, 18.3629, 19.4123, 20.5143, 21.6718] +24-11-19 20:34:19 | D | best error = [ 1.3808, 1.3808, 1.3808, 1.3808, 1.3808] +24-11-19 20:34:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:19 | D | sum error = [ 22.8830, 24.1631, 25.5004, 26.9039, 28.3771] +24-11-19 20:34:19 | D | best error = [ 1.3808, 1.3808, 1.3808, 1.3808, 1.3808] +24-11-19 20:34:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:19 | D | sum error = [ 29.9224, 31.5431, 33.2330, 35.0035, 36.8593] +24-11-19 20:34:19 | D | best error = [ 1.3808, 1.3808, 1.3808, 1.3808, 1.3808] +24-11-19 20:34:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:19 | D | sum error = [ 38.7996, 40.8275, 42.9476, 45.1631, 47.4741] +24-11-19 20:34:19 | D | best error = [ 1.3808, 1.3808, 1.3808, 1.3808, 1.3808] +24-11-19 20:34:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:19 | D | sum error = [ 49.8808, 52.3918, 55.0047, 57.7311, 60.5606] +24-11-19 20:34:19 | D | best error = [ 1.3808, 1.3808, 1.3808, 1.3808, 1.3808] +24-11-19 20:34:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:19 | D | sum error = [ 63.5053, 66.5684, 69.7416, 73.0370, 76.4544] +24-11-19 20:34:19 | D | best error = [ 1.3808, 1.3808, 1.3808, 1.3808, 1.3808] +24-11-19 20:34:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:19 | D | sum error = [ 79.9937, 83.6616, 87.4564, 91.3810, 95.4381] +24-11-19 20:34:19 | D | best error = [ 1.3808, 1.3808, 1.3808, 1.3808, 1.3808] +24-11-19 20:34:19 | D | + error = [1.3808] +24-11-19 20:34:19 | D | - Calibrating model.layers.22.mlp.up_proj.weight +24-11-19 20:34:19 | D | + w: sint8 +24-11-19 20:34:19 | D | + x: None +24-11-19 20:34:19 | D | + y: None +24-11-19 20:34:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:19 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:34:19 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:34:19 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:34:19 | D | - range ratio = [ 1.0000] +24-11-19 20:34:19 | D | sum error = [ 9.4734] +24-11-19 20:34:19 | D | best error = [ 9.4734] +24-11-19 20:34:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:20 | D | sum error = [ 9.4109, 9.3689, 9.4094, 9.5209, 9.7016] +24-11-19 20:34:20 | D | best error = [ 8.8007, 8.5261, 8.3836, 8.3009, 8.2560] +24-11-19 20:34:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:20 | D | sum error = [ 9.9501, 10.2579, 10.6996, 11.1983, 11.8109] +24-11-19 20:34:20 | D | best error = [ 8.2315, 8.2222, 8.2183, 8.2172, 8.2168] +24-11-19 20:34:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:20 | D | sum error = [ 12.4641, 13.2186, 14.1030, 15.0294, 16.0582] +24-11-19 20:34:20 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:34:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:20 | D | sum error = [ 17.2242, 18.4278, 19.7746, 21.1738, 22.6691] +24-11-19 20:34:20 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:34:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:20 | D | sum error = [ 24.2974, 26.0043, 27.8561, 29.7835, 31.8878] +24-11-19 20:34:20 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:34:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:20 | D | sum error = [ 34.0587, 36.3669, 38.8451, 41.4110, 44.1699] +24-11-19 20:34:20 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:34:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:20 | D | sum error = [ 47.0676, 50.0997, 53.3182, 56.7304, 60.2905] +24-11-19 20:34:20 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:34:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:20 | D | sum error = [ 64.0570, 67.9975, 72.1485, 76.5489, 81.1411] +24-11-19 20:34:20 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:34:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:20 | D | sum error = [ 85.9578, 91.0350, 96.3389, 101.9176, 107.7507] +24-11-19 20:34:20 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:34:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:20 | D | sum error = [ 113.8726, 120.2702, 127.0047, 134.0137, 141.3319] +24-11-19 20:34:20 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:34:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:20 | D | sum error = [ 149.0106, 156.9920, 165.3547, 174.0829, 183.1705] +24-11-19 20:34:20 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:34:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:20 | D | sum error = [ 192.6488, 202.5283, 212.8135, 223.5200, 234.6508] +24-11-19 20:34:20 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:34:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:20 | D | sum error = [ 246.2216, 258.2456, 270.7473, 283.7196, 297.1914] +24-11-19 20:34:20 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:34:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:20 | D | sum error = [ 311.1555, 325.6192, 340.5964, 356.1026, 372.1396] +24-11-19 20:34:20 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:34:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:20 | D | sum error = [ 388.7167, 405.8529, 423.5709, 441.8250, 460.6796] +24-11-19 20:34:20 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:34:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:20 | D | sum error = [ 480.1046, 500.1366, 520.7789, 541.9999, 563.8380] +24-11-19 20:34:20 | D | best error = [ 8.2167, 8.2167, 8.2167, 8.2167, 8.2167] +24-11-19 20:34:20 | D | + error = [8.2167] +24-11-19 20:34:20 | D | - Calibrating model.layers.22.mlp.gate_proj.weight +24-11-19 20:34:20 | D | + w: sint8 +24-11-19 20:34:20 | D | + x: None +24-11-19 20:34:20 | D | + y: None +24-11-19 20:34:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:20 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:34:20 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:34:20 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:34:20 | D | - range ratio = [ 1.0000] +24-11-19 20:34:20 | D | sum error = [ 10.2653] +24-11-19 20:34:20 | D | best error = [ 10.2653] +24-11-19 20:34:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:21 | D | sum error = [ 10.1790, 10.1786, 10.2409, 10.3557, 10.5122] +24-11-19 20:34:21 | D | best error = [ 9.5288, 9.2420, 9.0875, 9.0037, 8.9502] +24-11-19 20:34:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:21 | D | sum error = [ 10.8136, 11.1442, 11.5998, 12.1647, 12.7851] +24-11-19 20:34:21 | D | best error = [ 8.9248, 8.9147, 8.9102, 8.9086, 8.9082] +24-11-19 20:34:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:21 | D | sum error = [ 13.5202, 14.3705, 15.2988, 16.3625, 17.4732] +24-11-19 20:34:21 | D | best error = [ 8.9081, 8.9080, 8.9080, 8.9080, 8.9080] +24-11-19 20:34:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:21 | D | sum error = [ 18.7212, 20.0602, 21.5002, 23.0409, 24.7246] +24-11-19 20:34:21 | D | best error = [ 8.9080, 8.9080, 8.9080, 8.9080, 8.9080] +24-11-19 20:34:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:21 | D | sum error = [ 26.4988, 28.4073, 30.3986, 32.5349, 34.8314] +24-11-19 20:34:21 | D | best error = [ 8.9080, 8.9080, 8.9080, 8.9080, 8.9080] +24-11-19 20:34:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:21 | D | sum error = [ 37.2510, 39.7900, 42.5502, 45.4048, 48.4718] +24-11-19 20:34:21 | D | best error = [ 8.9080, 8.9080, 8.9080, 8.9080, 8.9080] +24-11-19 20:34:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:21 | D | sum error = [ 51.7212, 55.1183, 58.7320, 62.5564, 66.5912] +24-11-19 20:34:21 | D | best error = [ 8.9080, 8.9080, 8.9080, 8.9080, 8.9080] +24-11-19 20:34:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:21 | D | sum error = [ 70.8189, 75.3307, 80.0525, 85.0597, 90.3145] +24-11-19 20:34:21 | D | best error = [ 8.9080, 8.9080, 8.9080, 8.9080, 8.9080] +24-11-19 20:34:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:21 | D | sum error = [ 95.8622, 101.7167, 107.9112, 114.3949, 121.2389] +24-11-19 20:34:21 | D | best error = [ 8.9080, 8.9080, 8.9080, 8.9080, 8.9080] +24-11-19 20:34:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:21 | D | sum error = [ 128.3893, 135.9640, 143.9182, 152.2471, 161.0630] +24-11-19 20:34:21 | D | best error = [ 8.9080, 8.9080, 8.9080, 8.9080, 8.9080] +24-11-19 20:34:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:21 | D | sum error = [ 170.2304, 179.9132, 190.0614, 200.6742, 211.8224] +24-11-19 20:34:21 | D | best error = [ 8.9080, 8.9080, 8.9080, 8.9080, 8.9080] +24-11-19 20:34:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:21 | D | sum error = [ 223.4693, 235.6816, 248.4535, 261.8296, 275.7966] +24-11-19 20:34:21 | D | best error = [ 8.9080, 8.9080, 8.9080, 8.9080, 8.9080] +24-11-19 20:34:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:21 | D | sum error = [ 290.4161, 305.6232, 321.5427, 338.1135, 355.3777] +24-11-19 20:34:21 | D | best error = [ 8.9080, 8.9080, 8.9080, 8.9080, 8.9080] +24-11-19 20:34:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:21 | D | sum error = [ 373.3586, 392.0476, 411.5164, 431.7425, 452.7420] +24-11-19 20:34:21 | D | best error = [ 8.9080, 8.9080, 8.9080, 8.9080, 8.9080] +24-11-19 20:34:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:21 | D | sum error = [ 474.5141, 497.0572, 520.4432, 544.6472, 569.7003] +24-11-19 20:34:21 | D | best error = [ 8.9080, 8.9080, 8.9080, 8.9080, 8.9080] +24-11-19 20:34:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:21 | D | sum error = [ 595.5630, 622.2965, 649.8760, 678.3254, 707.6387] +24-11-19 20:34:21 | D | best error = [ 8.9080, 8.9080, 8.9080, 8.9080, 8.9080] +24-11-19 20:34:21 | D | + error = [8.9080] +24-11-19 20:34:21 | D | - Calibrating model.layers.22.mlp.down_proj.weight +24-11-19 20:34:21 | D | + w: sint8 +24-11-19 20:34:21 | D | + x: None +24-11-19 20:34:21 | D | + y: None +24-11-19 20:34:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:21 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:34:22 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:34:22 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:34:22 | D | - range ratio = [ 1.0000] +24-11-19 20:34:22 | D | sum error = [ 3.6774] +24-11-19 20:34:22 | D | best error = [ 3.6774] +24-11-19 20:34:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:23 | D | sum error = [ 3.6482, 3.6173, 3.6001, 3.5988, 3.6024] +24-11-19 20:34:23 | D | best error = [ 3.5214, 3.4387, 3.3822, 3.3442, 3.3174] +24-11-19 20:34:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:23 | D | sum error = [ 3.6188, 3.6417, 3.6959, 3.7576, 3.8573] +24-11-19 20:34:23 | D | best error = [ 3.2963, 3.2792, 3.2676, 3.2586, 3.2522] +24-11-19 20:34:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:23 | D | sum error = [ 3.9578, 4.0865, 4.2415, 4.4238, 4.6363] +24-11-19 20:34:23 | D | best error = [ 3.2478, 3.2446, 3.2427, 3.2413, 3.2407] +24-11-19 20:34:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:23 | D | sum error = [ 4.8712, 5.1509, 5.4474, 5.7777, 6.1472] +24-11-19 20:34:23 | D | best error = [ 3.2403, 3.2400, 3.2399, 3.2399, 3.2398] +24-11-19 20:34:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:23 | D | sum error = [ 6.5547, 6.9869, 7.4679, 7.9738, 8.5381] +24-11-19 20:34:23 | D | best error = [ 3.2397, 3.2397, 3.2397, 3.2397, 3.2397] +24-11-19 20:34:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:23 | D | sum error = [ 9.1218, 9.7590, 10.4461, 11.1767, 11.9488] +24-11-19 20:34:23 | D | best error = [ 3.2397, 3.2397, 3.2397, 3.2397, 3.2397] +24-11-19 20:34:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:23 | D | sum error = [ 12.7729, 13.6600, 14.5996, 15.6009, 16.6569] +24-11-19 20:34:23 | D | best error = [ 3.2397, 3.2397, 3.2397, 3.2397, 3.2397] +24-11-19 20:34:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:23 | D | sum error = [ 17.7765, 18.9677, 20.2276, 21.5532, 22.9658] +24-11-19 20:34:23 | D | best error = [ 3.2397, 3.2397, 3.2397, 3.2397, 3.2397] +24-11-19 20:34:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:23 | D | sum error = [ 24.4583, 26.0263, 27.6920, 29.4488, 31.2927] +24-11-19 20:34:23 | D | best error = [ 3.2397, 3.2397, 3.2397, 3.2397, 3.2397] +24-11-19 20:34:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:23 | D | sum error = [ 33.2478, 35.2975, 37.4587, 39.7356, 42.1255] +24-11-19 20:34:23 | D | best error = [ 3.2397, 3.2397, 3.2397, 3.2397, 3.2397] +24-11-19 20:34:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:23 | D | sum error = [ 44.6361, 47.2704, 50.0287, 52.9339, 55.9655] +24-11-19 20:34:23 | D | best error = [ 3.2397, 3.2397, 3.2397, 3.2397, 3.2397] +24-11-19 20:34:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:23 | D | sum error = [ 59.1544, 62.4876, 65.9793, 69.6330, 73.4501] +24-11-19 20:34:23 | D | best error = [ 3.2397, 3.2397, 3.2397, 3.2397, 3.2397] +24-11-19 20:34:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:23 | D | sum error = [ 77.4371, 81.6041, 85.9496, 90.4813, 95.1962] +24-11-19 20:34:23 | D | best error = [ 3.2397, 3.2397, 3.2397, 3.2397, 3.2397] +24-11-19 20:34:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:23 | D | sum error = [ 100.1137, 105.2215, 110.5353, 116.0733, 121.8054] +24-11-19 20:34:23 | D | best error = [ 3.2397, 3.2397, 3.2397, 3.2397, 3.2397] +24-11-19 20:34:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:23 | D | sum error = [ 127.7655, 133.9505, 140.3581, 146.9969, 153.8674] +24-11-19 20:34:23 | D | best error = [ 3.2397, 3.2397, 3.2397, 3.2397, 3.2397] +24-11-19 20:34:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:23 | D | sum error = [ 160.9830, 168.3374, 175.9405, 183.7922, 191.8948] +24-11-19 20:34:23 | D | best error = [ 3.2397, 3.2397, 3.2397, 3.2397, 3.2397] +24-11-19 20:34:23 | D | + error = [3.2397] +24-11-19 20:34:23 | D | - Quantizing model.layers.22.self_attn.q_proj.weight +24-11-19 20:34:24 | D | - Quantizing model.layers.22.self_attn.k_proj.weight +24-11-19 20:34:24 | D | - Quantizing model.layers.22.self_attn.v_proj.weight +24-11-19 20:34:25 | D | - Quantizing model.layers.22.self_attn.o_proj.weight +24-11-19 20:34:26 | D | - Quantizing model.layers.22.mlp.up_proj.weight +24-11-19 20:34:27 | D | - Quantizing model.layers.22.mlp.gate_proj.weight +24-11-19 20:34:28 | D | - Quantizing model.layers.22.mlp.down_proj.weight +24-11-19 20:34:36 | D | - Quantizing layer model.layers.23 +24-11-19 20:34:36 | D | - Calibrating model.layers.23.self_attn.q_proj.weight +24-11-19 20:34:36 | D | + w: sint8 +24-11-19 20:34:36 | D | + x: None +24-11-19 20:34:36 | D | + y: None +24-11-19 20:34:36 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:34:36 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:34:36 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:34:36 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:34:36 | D | - range ratio = [ 1.0000] +24-11-19 20:34:36 | D | sum error = [ 12.8688] +24-11-19 20:34:36 | D | best error = [ 12.8688] +24-11-19 20:34:49 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:49 | D | sum error = [ 12.8287, 12.5288, 12.6507, 12.8485, 13.0293] +24-11-19 20:34:49 | D | best error = [ 12.8287, 12.5288, 12.5288, 12.5288, 12.5288] +24-11-19 20:34:49 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:49 | D | sum error = [ 13.4262, 13.5857, 14.1560, 15.1535, 16.0119] +24-11-19 20:34:49 | D | best error = [ 12.5288, 12.5288, 12.5288, 12.5288, 12.5288] +24-11-19 20:34:49 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:49 | D | sum error = [ 16.6313, 17.6993, 19.1473, 20.8253, 22.0354] +24-11-19 20:34:49 | D | best error = [ 12.5288, 12.5288, 12.5288, 12.5288, 12.5288] +24-11-19 20:34:49 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:49 | D | sum error = [ 23.8209, 25.3807, 27.5012, 30.0591, 32.5077] +24-11-19 20:34:49 | D | best error = [ 12.5288, 12.5288, 12.5288, 12.5288, 12.5288] +24-11-19 20:34:49 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:49 | D | sum error = [ 34.9022, 37.7504, 40.9857, 44.2710, 47.3836] +24-11-19 20:34:49 | D | best error = [ 12.5288, 12.5288, 12.5288, 12.5288, 12.5288] +24-11-19 20:34:49 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:49 | D | sum error = [ 51.1129, 55.4801, 59.7873, 64.5442, 69.6675] +24-11-19 20:34:49 | D | best error = [ 12.5288, 12.5288, 12.5288, 12.5288, 12.5288] +24-11-19 20:34:49 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:49 | D | sum error = [ 75.1291, 81.1073, 87.1819, 93.8755, 101.1253] +24-11-19 20:34:49 | D | best error = [ 12.5288, 12.5288, 12.5288, 12.5288, 12.5288] +24-11-19 20:34:49 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:49 | D | sum error = [ 108.1443, 116.6198, 125.3108, 134.3195, 144.2581] +24-11-19 20:34:49 | D | best error = [ 12.5288, 12.5288, 12.5288, 12.5288, 12.5288] +24-11-19 20:34:49 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:49 | D | sum error = [ 155.2820, 167.1163, 179.6711, 193.3099, 208.2048] +24-11-19 20:34:49 | D | best error = [ 12.5288, 12.5288, 12.5288, 12.5288, 12.5288] +24-11-19 20:34:49 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:49 | D | sum error = [ 224.1444, 241.1711, 259.0461, 277.9967, 299.2766] +24-11-19 20:34:49 | D | best error = [ 12.5288, 12.5288, 12.5288, 12.5288, 12.5288] +24-11-19 20:34:49 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:49 | D | sum error = [ 321.7191, 346.4645, 372.4920, 401.1396, 432.4303] +24-11-19 20:34:49 | D | best error = [ 12.5288, 12.5288, 12.5288, 12.5288, 12.5288] +24-11-19 20:34:49 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:49 | D | sum error = [ 465.9604, 502.2073, 541.2997, 583.3216, 629.0221] +24-11-19 20:34:49 | D | best error = [ 12.5288, 12.5288, 12.5288, 12.5288, 12.5288] +24-11-19 20:34:49 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:49 | D | sum error = [ 679.4393, 733.9027, 793.1666, 857.6179, 927.9196] +24-11-19 20:34:49 | D | best error = [ 12.5288, 12.5288, 12.5288, 12.5288, 12.5288] +24-11-19 20:34:49 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:49 | D | sum error = [ 1005.3445, 1090.3774, 1183.5807, 1286.4407, 1399.0287] +24-11-19 20:34:49 | D | best error = [ 12.5288, 12.5288, 12.5288, 12.5288, 12.5288] +24-11-19 20:34:49 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:49 | D | sum error = [ 1524.0935, 1660.8517, 1812.0890, 1978.1670, 2160.8336] +24-11-19 20:34:49 | D | best error = [ 12.5288, 12.5288, 12.5288, 12.5288, 12.5288] +24-11-19 20:34:49 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:49 | D | sum error = [ 2360.7077, 2579.1676, 2818.2605, 3077.8499, 3355.6928] +24-11-19 20:34:49 | D | best error = [ 12.5288, 12.5288, 12.5288, 12.5288, 12.5288] +24-11-19 20:34:49 | D | + error = [12.5288] +24-11-19 20:34:49 | D | - Calibrating model.layers.23.self_attn.k_proj.weight +24-11-19 20:34:49 | D | + w: sint8 +24-11-19 20:34:49 | D | + x: None +24-11-19 20:34:49 | D | + y: None +24-11-19 20:34:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:34:49 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:34:49 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:34:49 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:34:49 | D | - range ratio = [ 1.0000] +24-11-19 20:34:49 | D | sum error = [ 15.0083] +24-11-19 20:34:49 | D | best error = [ 15.0083] +24-11-19 20:35:02 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:02 | D | sum error = [ 14.7118, 14.7808, 14.3214, 15.0978, 15.2247] +24-11-19 20:35:02 | D | best error = [ 14.7118, 14.7118, 14.3214, 14.3214, 14.3214] +24-11-19 20:35:02 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:02 | D | sum error = [ 15.4061, 16.4665, 16.5619, 17.9618, 18.3151] +24-11-19 20:35:02 | D | best error = [ 14.3214, 14.3214, 14.3214, 14.3214, 14.3214] +24-11-19 20:35:02 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:02 | D | sum error = [ 20.1203, 21.2218, 23.2957, 24.7401, 26.2797] +24-11-19 20:35:02 | D | best error = [ 14.3214, 14.3214, 14.3214, 14.3214, 14.3214] +24-11-19 20:35:02 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:02 | D | sum error = [ 28.0592, 29.4124, 32.0166, 34.2570, 37.3511] +24-11-19 20:35:02 | D | best error = [ 14.3214, 14.3214, 14.3214, 14.3214, 14.3214] +24-11-19 20:35:02 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:02 | D | sum error = [ 40.6830, 44.1763, 47.5255, 51.0623, 55.2452] +24-11-19 20:35:02 | D | best error = [ 14.3214, 14.3214, 14.3214, 14.3214, 14.3214] +24-11-19 20:35:02 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:02 | D | sum error = [ 59.2195, 64.9073, 69.7236, 74.2713, 79.4919] +24-11-19 20:35:02 | D | best error = [ 14.3214, 14.3214, 14.3214, 14.3214, 14.3214] +24-11-19 20:35:02 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:02 | D | sum error = [ 84.6177, 91.6387, 99.0967, 104.9905, 112.8281] +24-11-19 20:35:02 | D | best error = [ 14.3214, 14.3214, 14.3214, 14.3214, 14.3214] +24-11-19 20:35:02 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:02 | D | sum error = [ 120.9322, 130.4031, 141.0216, 151.9038, 163.3717] +24-11-19 20:35:02 | D | best error = [ 14.3214, 14.3214, 14.3214, 14.3214, 14.3214] +24-11-19 20:35:02 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:02 | D | sum error = [ 176.2520, 189.9766, 204.3405, 220.0764, 237.4620] +24-11-19 20:35:02 | D | best error = [ 14.3214, 14.3214, 14.3214, 14.3214, 14.3214] +24-11-19 20:35:02 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:02 | D | sum error = [ 256.6530, 275.8640, 297.1558, 319.3839, 343.5932] +24-11-19 20:35:02 | D | best error = [ 14.3214, 14.3214, 14.3214, 14.3214, 14.3214] +24-11-19 20:35:02 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:02 | D | sum error = [ 370.0130, 397.6344, 428.3747, 460.5776, 496.1722] +24-11-19 20:35:02 | D | best error = [ 14.3214, 14.3214, 14.3214, 14.3214, 14.3214] +24-11-19 20:35:02 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:02 | D | sum error = [ 534.3796, 574.8643, 620.5421, 669.6726, 721.2885] +24-11-19 20:35:02 | D | best error = [ 14.3214, 14.3214, 14.3214, 14.3214, 14.3214] +24-11-19 20:35:02 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:02 | D | sum error = [ 777.8806, 840.8049, 908.1750, 980.9489, 1061.9953] +24-11-19 20:35:02 | D | best error = [ 14.3214, 14.3214, 14.3214, 14.3214, 14.3214] +24-11-19 20:35:02 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:02 | D | sum error = [ 1149.6594, 1243.7496, 1347.9752, 1459.0792, 1582.3541] +24-11-19 20:35:02 | D | best error = [ 14.3214, 14.3214, 14.3214, 14.3214, 14.3214] +24-11-19 20:35:02 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:02 | D | sum error = [ 1716.8770, 1862.6522, 2024.5496, 2199.8514, 2393.8036] +24-11-19 20:35:02 | D | best error = [ 14.3214, 14.3214, 14.3214, 14.3214, 14.3214] +24-11-19 20:35:02 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:02 | D | sum error = [ 2601.6211, 2826.6902, 3069.4794, 3330.7507, 3606.4585] +24-11-19 20:35:02 | D | best error = [ 14.3214, 14.3214, 14.3214, 14.3214, 14.3214] +24-11-19 20:35:02 | D | + error = [14.3214] +24-11-19 20:35:02 | D | - Calibrating model.layers.23.self_attn.v_proj.weight +24-11-19 20:35:02 | D | + w: sint8 +24-11-19 20:35:02 | D | + x: None +24-11-19 20:35:02 | D | + y: None +24-11-19 20:35:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:02 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:35:02 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:35:02 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:35:02 | D | - range ratio = [ 1.0000] +24-11-19 20:35:02 | D | sum error = [ 7.7981] +24-11-19 20:35:02 | D | best error = [ 7.7981] +24-11-19 20:35:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:03 | D | sum error = [ 7.7398, 7.7081, 7.7647, 7.8596, 7.9754] +24-11-19 20:35:03 | D | best error = [ 7.2653, 7.0372, 6.9213, 6.8553, 6.8184] +24-11-19 20:35:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:03 | D | sum error = [ 8.1974, 8.4917, 8.8041, 9.2439, 9.6929] +24-11-19 20:35:03 | D | best error = [ 6.7995, 6.7918, 6.7888, 6.7882, 6.7880] +24-11-19 20:35:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:03 | D | sum error = [ 10.2608, 10.9182, 11.6065, 12.3650, 13.2648] +24-11-19 20:35:03 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:03 | D | sum error = [ 14.1702, 15.1787, 16.2432, 17.4007, 18.6635] +24-11-19 20:35:03 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:03 | D | sum error = [ 19.9809, 21.4091, 22.8945, 24.5181, 26.2249] +24-11-19 20:35:03 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:03 | D | sum error = [ 27.9854, 29.9182, 31.9536, 34.0517, 36.3117] +24-11-19 20:35:03 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:03 | D | sum error = [ 38.6631, 41.1821, 43.8080, 46.5524, 49.4589] +24-11-19 20:35:03 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:03 | D | sum error = [ 52.4983, 55.6957, 59.0821, 62.5960, 66.3361] +24-11-19 20:35:03 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:03 | D | sum error = [ 70.2253, 74.2967, 78.5761, 83.0531, 87.7654] +24-11-19 20:35:03 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:03 | D | sum error = [ 92.6647, 97.8046, 103.1713, 108.7868, 114.6476] +24-11-19 20:35:03 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:03 | D | sum error = [ 120.7478, 127.1278, 133.7158, 140.6244, 147.8058] +24-11-19 20:35:03 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:03 | D | sum error = [ 155.3014, 163.0702, 171.1393, 179.5131, 188.2134] +24-11-19 20:35:03 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:03 | D | sum error = [ 197.2482, 206.6380, 216.3631, 226.4352, 236.8853] +24-11-19 20:35:03 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:03 | D | sum error = [ 247.6794, 258.8418, 270.3805, 282.3153, 294.6109] +24-11-19 20:35:03 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:03 | D | sum error = [ 307.3160, 320.4301, 333.9413, 347.8339, 362.1335] +24-11-19 20:35:03 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:03 | D | sum error = [ 376.8564, 392.0001, 407.5656, 423.5858, 440.0720] +24-11-19 20:35:03 | D | best error = [ 6.7879, 6.7879, 6.7879, 6.7879, 6.7879] +24-11-19 20:35:03 | D | + error = [6.7879] +24-11-19 20:35:03 | D | - Calibrating model.layers.23.self_attn.o_proj.weight +24-11-19 20:35:03 | D | + w: sint8 +24-11-19 20:35:03 | D | + x: None +24-11-19 20:35:03 | D | + y: None +24-11-19 20:35:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:03 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:35:03 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:35:03 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:35:03 | D | - range ratio = [ 1.0000] +24-11-19 20:35:03 | D | sum error = [ 1.4847] +24-11-19 20:35:03 | D | best error = [ 1.4847] +24-11-19 20:35:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:04 | D | sum error = [ 1.4771, 1.4677, 1.4728, 1.4862, 1.5074] +24-11-19 20:35:04 | D | best error = [ 1.4111, 1.3749, 1.3536, 1.3401, 1.3318] +24-11-19 20:35:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:04 | D | sum error = [ 1.5426, 1.5860, 1.6348, 1.7013, 1.7800] +24-11-19 20:35:04 | D | best error = [ 1.3267, 1.3234, 1.3215, 1.3202, 1.3194] +24-11-19 20:35:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:04 | D | sum error = [ 1.8741, 1.9771, 2.0930, 2.2218, 2.3635] +24-11-19 20:35:04 | D | best error = [ 1.3190, 1.3186, 1.3184, 1.3183, 1.3182] +24-11-19 20:35:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:04 | D | sum error = [ 2.5186, 2.6882, 2.8670, 3.0639, 3.2749] +24-11-19 20:35:04 | D | best error = [ 1.3181, 1.3180, 1.3180, 1.3180, 1.3180] +24-11-19 20:35:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:04 | D | sum error = [ 3.4903, 3.7278, 3.9841, 4.2500, 4.5331] +24-11-19 20:35:04 | D | best error = [ 1.3180, 1.3180, 1.3180, 1.3180, 1.3180] +24-11-19 20:35:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:04 | D | sum error = [ 4.8345, 5.1535, 5.4912, 5.8497, 6.2237] +24-11-19 20:35:04 | D | best error = [ 1.3180, 1.3180, 1.3180, 1.3180, 1.3180] +24-11-19 20:35:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:04 | D | sum error = [ 6.6229, 7.0412, 7.4832, 7.9522, 8.4387] +24-11-19 20:35:04 | D | best error = [ 1.3180, 1.3180, 1.3180, 1.3180, 1.3180] +24-11-19 20:35:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:04 | D | sum error = [ 8.9559, 9.5009, 10.0752, 10.6721, 11.3092] +24-11-19 20:35:04 | D | best error = [ 1.3180, 1.3180, 1.3180, 1.3180, 1.3180] +24-11-19 20:35:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:04 | D | sum error = [ 11.9807, 12.6755, 13.4127, 14.1835, 14.9932] +24-11-19 20:35:04 | D | best error = [ 1.3180, 1.3180, 1.3180, 1.3180, 1.3180] +24-11-19 20:35:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:04 | D | sum error = [ 15.8432, 16.7326, 17.6662, 18.6433, 19.6659] +24-11-19 20:35:04 | D | best error = [ 1.3180, 1.3180, 1.3180, 1.3180, 1.3180] +24-11-19 20:35:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:04 | D | sum error = [ 20.7362, 21.8582, 23.0305, 24.2576, 25.5445] +24-11-19 20:35:04 | D | best error = [ 1.3180, 1.3180, 1.3180, 1.3180, 1.3180] +24-11-19 20:35:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:04 | D | sum error = [ 26.8859, 28.2864, 29.7523, 31.2781, 32.8717] +24-11-19 20:35:04 | D | best error = [ 1.3180, 1.3180, 1.3180, 1.3180, 1.3180] +24-11-19 20:35:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:04 | D | sum error = [ 34.5305, 36.2586, 38.0588, 39.9352, 41.8905] +24-11-19 20:35:04 | D | best error = [ 1.3180, 1.3180, 1.3180, 1.3180, 1.3180] +24-11-19 20:35:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:04 | D | sum error = [ 43.9230, 46.0404, 48.2375, 50.5270, 52.8983] +24-11-19 20:35:04 | D | best error = [ 1.3180, 1.3180, 1.3180, 1.3180, 1.3180] +24-11-19 20:35:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:04 | D | sum error = [ 55.3627, 57.9196, 60.5721, 63.3158, 66.1587] +24-11-19 20:35:04 | D | best error = [ 1.3180, 1.3180, 1.3180, 1.3180, 1.3180] +24-11-19 20:35:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:04 | D | sum error = [ 69.0981, 72.1398, 75.2837, 78.5344, 81.8894] +24-11-19 20:35:04 | D | best error = [ 1.3180, 1.3180, 1.3180, 1.3180, 1.3180] +24-11-19 20:35:04 | D | + error = [1.3180] +24-11-19 20:35:04 | D | - Calibrating model.layers.23.mlp.up_proj.weight +24-11-19 20:35:04 | D | + w: sint8 +24-11-19 20:35:04 | D | + x: None +24-11-19 20:35:04 | D | + y: None +24-11-19 20:35:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:04 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:35:04 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:35:04 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:35:04 | D | - range ratio = [ 1.0000] +24-11-19 20:35:04 | D | sum error = [ 9.8254] +24-11-19 20:35:04 | D | best error = [ 9.8254] +24-11-19 20:35:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:05 | D | sum error = [ 9.7548, 9.7358, 9.7546, 9.8672, 10.0536] +24-11-19 20:35:05 | D | best error = [ 9.1276, 8.8528, 8.7000, 8.6133, 8.5643] +24-11-19 20:35:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:05 | D | sum error = [ 10.2795, 10.6346, 11.0885, 11.5907, 12.1702] +24-11-19 20:35:05 | D | best error = [ 8.5397, 8.5280, 8.5241, 8.5225, 8.5219] +24-11-19 20:35:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:05 | D | sum error = [ 12.8761, 13.6924, 14.5476, 15.5264, 16.6079] +24-11-19 20:35:05 | D | best error = [ 8.5219, 8.5218, 8.5218, 8.5218, 8.5218] +24-11-19 20:35:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:05 | D | sum error = [ 17.7954, 19.0284, 20.3871, 21.8496, 23.4165] +24-11-19 20:35:05 | D | best error = [ 8.5218, 8.5218, 8.5218, 8.5218, 8.5218] +24-11-19 20:35:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:05 | D | sum error = [ 25.0715, 26.8810, 28.7445, 30.7733, 32.9187] +24-11-19 20:35:05 | D | best error = [ 8.5218, 8.5218, 8.5218, 8.5218, 8.5218] +24-11-19 20:35:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:05 | D | sum error = [ 35.1865, 37.5837, 40.1243, 42.8178, 45.6548] +24-11-19 20:35:05 | D | best error = [ 8.5218, 8.5218, 8.5218, 8.5218, 8.5218] +24-11-19 20:35:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:05 | D | sum error = [ 48.6417, 51.7910, 55.1059, 58.5984, 62.2626] +24-11-19 20:35:05 | D | best error = [ 8.5218, 8.5218, 8.5218, 8.5218, 8.5218] +24-11-19 20:35:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:05 | D | sum error = [ 66.1295, 70.2004, 74.4546, 78.9550, 83.6565] +24-11-19 20:35:05 | D | best error = [ 8.5218, 8.5218, 8.5218, 8.5218, 8.5218] +24-11-19 20:35:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:05 | D | sum error = [ 88.6143, 93.8011, 99.2563, 104.9308, 110.9220] +24-11-19 20:35:05 | D | best error = [ 8.5218, 8.5218, 8.5218, 8.5218, 8.5218] +24-11-19 20:35:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:05 | D | sum error = [ 117.1659, 123.7221, 130.5776, 137.7430, 145.1953] +24-11-19 20:35:05 | D | best error = [ 8.5218, 8.5218, 8.5218, 8.5218, 8.5218] +24-11-19 20:35:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:05 | D | sum error = [ 153.0225, 161.1805, 169.6929, 178.5609, 187.8254] +24-11-19 20:35:05 | D | best error = [ 8.5218, 8.5218, 8.5218, 8.5218, 8.5218] +24-11-19 20:35:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:05 | D | sum error = [ 197.4836, 207.5085, 217.9637, 228.8329, 240.1392] +24-11-19 20:35:05 | D | best error = [ 8.5218, 8.5218, 8.5218, 8.5218, 8.5218] +24-11-19 20:35:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:05 | D | sum error = [ 251.9094, 264.1210, 276.8075, 289.9464, 303.5863] +24-11-19 20:35:05 | D | best error = [ 8.5218, 8.5218, 8.5218, 8.5218, 8.5218] +24-11-19 20:35:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:05 | D | sum error = [ 317.7204, 332.3518, 347.4878, 363.1321, 379.3240] +24-11-19 20:35:05 | D | best error = [ 8.5218, 8.5218, 8.5218, 8.5218, 8.5218] +24-11-19 20:35:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:05 | D | sum error = [ 396.0568, 413.3427, 431.2056, 449.6190, 468.6282] +24-11-19 20:35:05 | D | best error = [ 8.5218, 8.5218, 8.5218, 8.5218, 8.5218] +24-11-19 20:35:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:05 | D | sum error = [ 488.2054, 508.3680, 529.1105, 550.4489, 572.3935] +24-11-19 20:35:05 | D | best error = [ 8.5218, 8.5218, 8.5218, 8.5218, 8.5218] +24-11-19 20:35:05 | D | + error = [8.5218] +24-11-19 20:35:05 | D | - Calibrating model.layers.23.mlp.gate_proj.weight +24-11-19 20:35:05 | D | + w: sint8 +24-11-19 20:35:05 | D | + x: None +24-11-19 20:35:05 | D | + y: None +24-11-19 20:35:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:05 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:35:05 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:35:05 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:35:05 | D | - range ratio = [ 1.0000] +24-11-19 20:35:05 | D | sum error = [ 10.5801] +24-11-19 20:35:05 | D | best error = [ 10.5801] +24-11-19 20:35:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:06 | D | sum error = [ 10.4923, 10.4797, 10.5360, 10.6544, 10.8388] +24-11-19 20:35:06 | D | best error = [ 9.8184, 9.5222, 9.3601, 9.2697, 9.2154] +24-11-19 20:35:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:06 | D | sum error = [ 11.1489, 11.4901, 11.9718, 12.5281, 13.1558] +24-11-19 20:35:06 | D | best error = [ 9.1916, 9.1798, 9.1760, 9.1750, 9.1747] +24-11-19 20:35:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:06 | D | sum error = [ 13.9370, 14.7884, 15.7770, 16.8211, 18.0019] +24-11-19 20:35:06 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 20:35:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:06 | D | sum error = [ 19.2701, 20.6382, 22.1344, 23.7197, 25.4416] +24-11-19 20:35:06 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 20:35:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:06 | D | sum error = [ 27.2436, 29.1696, 31.2743, 33.4760, 35.8269] +24-11-19 20:35:06 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 20:35:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:06 | D | sum error = [ 38.3227, 40.9619, 43.7768, 46.7295, 49.8919] +24-11-19 20:35:06 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 20:35:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:06 | D | sum error = [ 53.1866, 56.7061, 60.3906, 64.3074, 68.4367] +24-11-19 20:35:06 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 20:35:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:06 | D | sum error = [ 72.7879, 77.3855, 82.1985, 87.2892, 92.6529] +24-11-19 20:35:06 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 20:35:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:06 | D | sum error = [ 98.3017, 104.2509, 110.5285, 117.0998, 124.0445] +24-11-19 20:35:06 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 20:35:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:06 | D | sum error = [ 131.3336, 138.9838, 147.0439, 155.4827, 164.3399] +24-11-19 20:35:06 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 20:35:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:06 | D | sum error = [ 173.6307, 183.3486, 193.5541, 204.2362, 215.4632] +24-11-19 20:35:06 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 20:35:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:06 | D | sum error = [ 227.1642, 239.4219, 252.2239, 265.5802, 279.5441] +24-11-19 20:35:06 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 20:35:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:06 | D | sum error = [ 294.1126, 309.2929, 325.1090, 341.5978, 358.7575] +24-11-19 20:35:06 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 20:35:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:06 | D | sum error = [ 376.6165, 395.2070, 414.5141, 434.5788, 455.3839] +24-11-19 20:35:06 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 20:35:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:06 | D | sum error = [ 476.9583, 499.3132, 522.4514, 546.4014, 571.2020] +24-11-19 20:35:06 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 20:35:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:06 | D | sum error = [ 596.7628, 623.1835, 650.4275, 678.5195, 707.4451] +24-11-19 20:35:06 | D | best error = [ 9.1746, 9.1746, 9.1746, 9.1746, 9.1746] +24-11-19 20:35:06 | D | + error = [9.1746] +24-11-19 20:35:06 | D | - Calibrating model.layers.23.mlp.down_proj.weight +24-11-19 20:35:06 | D | + w: sint8 +24-11-19 20:35:06 | D | + x: None +24-11-19 20:35:06 | D | + y: None +24-11-19 20:35:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:06 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:35:06 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:35:06 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:35:06 | D | - range ratio = [ 1.0000] +24-11-19 20:35:06 | D | sum error = [ 3.8380] +24-11-19 20:35:06 | D | best error = [ 3.8380] +24-11-19 20:35:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:07 | D | sum error = [ 3.7953, 3.7726, 3.7508, 3.7439, 3.7600] +24-11-19 20:35:07 | D | best error = [ 3.6766, 3.5964, 3.5432, 3.5018, 3.4734] +24-11-19 20:35:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:07 | D | sum error = [ 3.7770, 3.8178, 3.8667, 3.9412, 4.0338] +24-11-19 20:35:07 | D | best error = [ 3.4525, 3.4371, 3.4247, 3.4155, 3.4107] +24-11-19 20:35:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:07 | D | sum error = [ 4.1594, 4.2995, 4.4627, 4.6610, 4.8932] +24-11-19 20:35:07 | D | best error = [ 3.4066, 3.4043, 3.4021, 3.4010, 3.4005] +24-11-19 20:35:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:07 | D | sum error = [ 5.1556, 5.4441, 5.7615, 6.1159, 6.5144] +24-11-19 20:35:07 | D | best error = [ 3.4000, 3.3998, 3.3996, 3.3996, 3.3995] +24-11-19 20:35:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:07 | D | sum error = [ 6.9462, 7.4087, 7.8998, 8.4459, 9.0284] +24-11-19 20:35:07 | D | best error = [ 3.3995, 3.3995, 3.3995, 3.3995, 3.3995] +24-11-19 20:35:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:07 | D | sum error = [ 9.6554, 10.3364, 11.0572, 11.8277, 12.6446] +24-11-19 20:35:07 | D | best error = [ 3.3995, 3.3995, 3.3995, 3.3995, 3.3995] +24-11-19 20:35:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:07 | D | sum error = [ 13.5212, 14.4463, 15.4496, 16.4960, 17.6100] +24-11-19 20:35:07 | D | best error = [ 3.3995, 3.3995, 3.3995, 3.3995, 3.3995] +24-11-19 20:35:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:07 | D | sum error = [ 18.7993, 20.0557, 21.3871, 22.7911, 24.2801] +24-11-19 20:35:07 | D | best error = [ 3.3995, 3.3995, 3.3995, 3.3995, 3.3995] +24-11-19 20:35:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:07 | D | sum error = [ 25.8465, 27.5076, 29.2535, 31.1124, 33.0569] +24-11-19 20:35:07 | D | best error = [ 3.3995, 3.3995, 3.3995, 3.3995, 3.3995] +24-11-19 20:35:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:07 | D | sum error = [ 35.1061, 37.2661, 39.5352, 41.9199, 44.4214] +24-11-19 20:35:07 | D | best error = [ 3.3995, 3.3995, 3.3995, 3.3995, 3.3995] +24-11-19 20:35:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:07 | D | sum error = [ 47.0547, 49.8127, 52.6988, 55.7357, 58.9145] +24-11-19 20:35:07 | D | best error = [ 3.3995, 3.3995, 3.3995, 3.3995, 3.3995] +24-11-19 20:35:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:07 | D | sum error = [ 62.2387, 65.7174, 69.3524, 73.1642, 77.1378] +24-11-19 20:35:07 | D | best error = [ 3.3995, 3.3995, 3.3995, 3.3995, 3.3995] +24-11-19 20:35:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:07 | D | sum error = [ 81.2877, 85.6138, 90.1273, 94.8291, 99.7173] +24-11-19 20:35:07 | D | best error = [ 3.3995, 3.3995, 3.3995, 3.3995, 3.3995] +24-11-19 20:35:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:07 | D | sum error = [ 104.8120, 110.0999, 115.6003, 121.3218, 127.2487] +24-11-19 20:35:07 | D | best error = [ 3.3995, 3.3995, 3.3995, 3.3995, 3.3995] +24-11-19 20:35:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:07 | D | sum error = [ 133.4108, 139.7943, 146.4197, 153.2720, 160.3731] +24-11-19 20:35:07 | D | best error = [ 3.3995, 3.3995, 3.3995, 3.3995, 3.3995] +24-11-19 20:35:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:07 | D | sum error = [ 167.7138, 175.2978, 183.1389, 191.2291, 199.5806] +24-11-19 20:35:07 | D | best error = [ 3.3995, 3.3995, 3.3995, 3.3995, 3.3995] +24-11-19 20:35:07 | D | + error = [3.3995] +24-11-19 20:35:07 | D | - Quantizing model.layers.23.self_attn.q_proj.weight +24-11-19 20:35:08 | D | - Quantizing model.layers.23.self_attn.k_proj.weight +24-11-19 20:35:09 | D | - Quantizing model.layers.23.self_attn.v_proj.weight +24-11-19 20:35:10 | D | - Quantizing model.layers.23.self_attn.o_proj.weight +24-11-19 20:35:11 | D | - Quantizing model.layers.23.mlp.up_proj.weight +24-11-19 20:35:12 | D | - Quantizing model.layers.23.mlp.gate_proj.weight +24-11-19 20:35:12 | D | - Quantizing model.layers.23.mlp.down_proj.weight +24-11-19 20:35:20 | D | - Quantizing layer model.layers.24 +24-11-19 20:35:20 | D | - Calibrating model.layers.24.self_attn.q_proj.weight +24-11-19 20:35:20 | D | + w: sint8 +24-11-19 20:35:20 | D | + x: None +24-11-19 20:35:20 | D | + y: None +24-11-19 20:35:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:35:20 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:35:20 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:35:20 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:35:21 | D | - range ratio = [ 1.0000] +24-11-19 20:35:21 | D | sum error = [ 15.5906] +24-11-19 20:35:21 | D | best error = [ 15.5906] +24-11-19 20:35:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:33 | D | sum error = [ 15.2628, 15.4208, 15.4958, 15.7516, 16.1632] +24-11-19 20:35:33 | D | best error = [ 15.2628, 15.2628, 15.2628, 15.2628, 15.2628] +24-11-19 20:35:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:33 | D | sum error = [ 16.4562, 17.3153, 17.7855, 18.8291, 20.9894] +24-11-19 20:35:33 | D | best error = [ 15.2628, 15.2628, 15.2628, 15.2628, 15.2628] +24-11-19 20:35:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:33 | D | sum error = [ 21.6372, 23.1975, 24.4989, 26.7840, 28.9262] +24-11-19 20:35:33 | D | best error = [ 15.2628, 15.2628, 15.2628, 15.2628, 15.2628] +24-11-19 20:35:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:33 | D | sum error = [ 30.7192, 33.5336, 35.6346, 39.2661, 42.2896] +24-11-19 20:35:33 | D | best error = [ 15.2628, 15.2628, 15.2628, 15.2628, 15.2628] +24-11-19 20:35:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:33 | D | sum error = [ 46.2078, 49.6828, 52.5231, 57.2144, 61.4638] +24-11-19 20:35:33 | D | best error = [ 15.2628, 15.2628, 15.2628, 15.2628, 15.2628] +24-11-19 20:35:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:33 | D | sum error = [ 66.8514, 71.7068, 78.3269, 82.8824, 89.0926] +24-11-19 20:35:33 | D | best error = [ 15.2628, 15.2628, 15.2628, 15.2628, 15.2628] +24-11-19 20:35:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:33 | D | sum error = [ 96.5184, 104.1372, 111.5644, 120.5996, 128.5743] +24-11-19 20:35:33 | D | best error = [ 15.2628, 15.2628, 15.2628, 15.2628, 15.2628] +24-11-19 20:35:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:33 | D | sum error = [ 139.6409, 150.1591, 161.4979, 173.4528, 185.9453] +24-11-19 20:35:33 | D | best error = [ 15.2628, 15.2628, 15.2628, 15.2628, 15.2628] +24-11-19 20:35:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:33 | D | sum error = [ 200.9022, 215.1571, 230.5306, 248.2130, 266.5794] +24-11-19 20:35:33 | D | best error = [ 15.2628, 15.2628, 15.2628, 15.2628, 15.2628] +24-11-19 20:35:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:33 | D | sum error = [ 285.6565, 305.6343, 327.7598, 352.3387, 377.3906] +24-11-19 20:35:33 | D | best error = [ 15.2628, 15.2628, 15.2628, 15.2628, 15.2628] +24-11-19 20:35:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:33 | D | sum error = [ 404.0642, 431.8573, 461.4786, 493.9081, 528.2816] +24-11-19 20:35:33 | D | best error = [ 15.2628, 15.2628, 15.2628, 15.2628, 15.2628] +24-11-19 20:35:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:33 | D | sum error = [ 565.4567, 605.5569, 647.1422, 693.3067, 742.6918] +24-11-19 20:35:33 | D | best error = [ 15.2628, 15.2628, 15.2628, 15.2628, 15.2628] +24-11-19 20:35:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:33 | D | sum error = [ 794.9890, 853.1949, 914.1967, 981.1929, 1054.3089] +24-11-19 20:35:33 | D | best error = [ 15.2628, 15.2628, 15.2628, 15.2628, 15.2628] +24-11-19 20:35:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:33 | D | sum error = [ 1133.3709, 1220.0136, 1313.7416, 1417.6690, 1527.6218] +24-11-19 20:35:33 | D | best error = [ 15.2628, 15.2628, 15.2628, 15.2628, 15.2628] +24-11-19 20:35:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:33 | D | sum error = [ 1650.0494, 1782.6496, 1926.6169, 2085.1077, 2257.7024] +24-11-19 20:35:33 | D | best error = [ 15.2628, 15.2628, 15.2628, 15.2628, 15.2628] +24-11-19 20:35:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:33 | D | sum error = [ 2447.9673, 2654.6673, 2877.5013, 3116.5309, 3372.1100] +24-11-19 20:35:33 | D | best error = [ 15.2628, 15.2628, 15.2628, 15.2628, 15.2628] +24-11-19 20:35:33 | D | + error = [15.2628] +24-11-19 20:35:33 | D | - Calibrating model.layers.24.self_attn.k_proj.weight +24-11-19 20:35:33 | D | + w: sint8 +24-11-19 20:35:33 | D | + x: None +24-11-19 20:35:33 | D | + y: None +24-11-19 20:35:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:35:33 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:35:33 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:35:34 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:35:34 | D | - range ratio = [ 1.0000] +24-11-19 20:35:34 | D | sum error = [ 19.2124] +24-11-19 20:35:34 | D | best error = [ 19.2124] +24-11-19 20:35:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:46 | D | sum error = [ 19.6450, 19.5519, 18.3381, 17.9091, 19.1060] +24-11-19 20:35:46 | D | best error = [ 19.2124, 19.2124, 18.3381, 17.9091, 17.9091] +24-11-19 20:35:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:46 | D | sum error = [ 20.2946, 20.7679, 21.0829, 21.9278, 22.8766] +24-11-19 20:35:46 | D | best error = [ 17.9091, 17.9091, 17.9091, 17.9091, 17.9091] +24-11-19 20:35:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:46 | D | sum error = [ 25.8217, 26.5718, 27.6052, 31.8298, 31.2687] +24-11-19 20:35:46 | D | best error = [ 17.9091, 17.9091, 17.9091, 17.9091, 17.9091] +24-11-19 20:35:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:46 | D | sum error = [ 33.5078, 36.2827, 38.5431, 42.5549, 46.3238] +24-11-19 20:35:46 | D | best error = [ 17.9091, 17.9091, 17.9091, 17.9091, 17.9091] +24-11-19 20:35:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:46 | D | sum error = [ 49.5133, 52.5064, 55.8599, 60.8661, 66.4606] +24-11-19 20:35:46 | D | best error = [ 17.9091, 17.9091, 17.9091, 17.9091, 17.9091] +24-11-19 20:35:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:46 | D | sum error = [ 69.6604, 77.2801, 82.5611, 86.3946, 93.3591] +24-11-19 20:35:46 | D | best error = [ 17.9091, 17.9091, 17.9091, 17.9091, 17.9091] +24-11-19 20:35:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:46 | D | sum error = [ 99.2590, 107.2253, 115.3872, 124.3094, 136.4571] +24-11-19 20:35:46 | D | best error = [ 17.9091, 17.9091, 17.9091, 17.9091, 17.9091] +24-11-19 20:35:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:46 | D | sum error = [ 144.8933, 155.5908, 166.9320, 182.3820, 194.4938] +24-11-19 20:35:46 | D | best error = [ 17.9091, 17.9091, 17.9091, 17.9091, 17.9091] +24-11-19 20:35:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:46 | D | sum error = [ 207.3038, 225.0832, 241.4947, 258.7635, 277.5702] +24-11-19 20:35:46 | D | best error = [ 17.9091, 17.9091, 17.9091, 17.9091, 17.9091] +24-11-19 20:35:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:46 | D | sum error = [ 297.3084, 316.1946, 340.1894, 363.8483, 388.5687] +24-11-19 20:35:46 | D | best error = [ 17.9091, 17.9091, 17.9091, 17.9091, 17.9091] +24-11-19 20:35:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:46 | D | sum error = [ 416.5675, 444.6606, 477.2376, 508.0496, 541.6653] +24-11-19 20:35:46 | D | best error = [ 17.9091, 17.9091, 17.9091, 17.9091, 17.9091] +24-11-19 20:35:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:46 | D | sum error = [ 579.9998, 618.8984, 660.9322, 708.9968, 761.1053] +24-11-19 20:35:46 | D | best error = [ 17.9091, 17.9091, 17.9091, 17.9091, 17.9091] +24-11-19 20:35:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:46 | D | sum error = [ 818.8658, 878.7264, 942.9862, 1012.2236, 1089.2838] +24-11-19 20:35:46 | D | best error = [ 17.9091, 17.9091, 17.9091, 17.9091, 17.9091] +24-11-19 20:35:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:46 | D | sum error = [ 1171.3288, 1261.9102, 1358.7077, 1466.6769, 1583.2171] +24-11-19 20:35:46 | D | best error = [ 17.9091, 17.9091, 17.9091, 17.9091, 17.9091] +24-11-19 20:35:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:46 | D | sum error = [ 1712.8108, 1855.3694, 2010.2191, 2181.8185, 2365.1746] +24-11-19 20:35:46 | D | best error = [ 17.9091, 17.9091, 17.9091, 17.9091, 17.9091] +24-11-19 20:35:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:46 | D | sum error = [ 2563.2851, 2772.5196, 2999.8867, 3242.7188, 3499.6860] +24-11-19 20:35:46 | D | best error = [ 17.9091, 17.9091, 17.9091, 17.9091, 17.9091] +24-11-19 20:35:46 | D | + error = [17.9091] +24-11-19 20:35:46 | D | - Calibrating model.layers.24.self_attn.v_proj.weight +24-11-19 20:35:46 | D | + w: sint8 +24-11-19 20:35:46 | D | + x: None +24-11-19 20:35:46 | D | + y: None +24-11-19 20:35:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:46 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:35:47 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:35:47 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:35:47 | D | - range ratio = [ 1.0000] +24-11-19 20:35:47 | D | sum error = [ 7.5829] +24-11-19 20:35:47 | D | best error = [ 7.5829] +24-11-19 20:35:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:47 | D | sum error = [ 7.4951, 7.4978, 7.5469, 7.6344, 7.7740] +24-11-19 20:35:47 | D | best error = [ 7.0516, 6.8502, 6.7480, 6.6824, 6.6462] +24-11-19 20:35:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:47 | D | sum error = [ 7.9663, 8.2179, 8.5665, 8.9477, 9.4382] +24-11-19 20:35:47 | D | best error = [ 6.6289, 6.6212, 6.6181, 6.6167, 6.6167] +24-11-19 20:35:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:47 | D | sum error = [ 10.0043, 10.5967, 11.2808, 12.0596, 12.8546] +24-11-19 20:35:47 | D | best error = [ 6.6166, 6.6166, 6.6166, 6.6166, 6.6166] +24-11-19 20:35:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:47 | D | sum error = [ 13.7972, 14.7657, 15.8222, 16.9396, 18.1522] +24-11-19 20:35:47 | D | best error = [ 6.6166, 6.6166, 6.6166, 6.6166, 6.6166] +24-11-19 20:35:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:47 | D | sum error = [ 19.4638, 20.8265, 22.3028, 23.8332, 25.4946] +24-11-19 20:35:47 | D | best error = [ 6.6166, 6.6166, 6.6166, 6.6166, 6.6166] +24-11-19 20:35:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:47 | D | sum error = [ 27.2448, 29.0675, 31.0165, 33.1079, 35.2634] +24-11-19 20:35:47 | D | best error = [ 6.6166, 6.6166, 6.6166, 6.6166, 6.6166] +24-11-19 20:35:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:47 | D | sum error = [ 37.5318, 39.9560, 42.5059, 45.1701, 47.9824] +24-11-19 20:35:47 | D | best error = [ 6.6166, 6.6166, 6.6166, 6.6166, 6.6166] +24-11-19 20:35:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:47 | D | sum error = [ 50.9511, 54.0655, 57.3359, 60.7353, 64.3624] +24-11-19 20:35:47 | D | best error = [ 6.6166, 6.6166, 6.6166, 6.6166, 6.6166] +24-11-19 20:35:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:47 | D | sum error = [ 68.1363, 72.1078, 76.2861, 80.5923, 85.1687] +24-11-19 20:35:47 | D | best error = [ 6.6166, 6.6166, 6.6166, 6.6166, 6.6166] +24-11-19 20:35:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:47 | D | sum error = [ 89.9192, 94.9049, 100.1075, 105.5365, 111.2278] +24-11-19 20:35:47 | D | best error = [ 6.6166, 6.6166, 6.6166, 6.6166, 6.6166] +24-11-19 20:35:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:47 | D | sum error = [ 117.1258, 123.3114, 129.7352, 136.4520, 143.4208] +24-11-19 20:35:47 | D | best error = [ 6.6166, 6.6166, 6.6166, 6.6166, 6.6166] +24-11-19 20:35:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:47 | D | sum error = [ 150.6841, 158.2030, 166.0576, 174.1693, 182.6120] +24-11-19 20:35:47 | D | best error = [ 6.6166, 6.6166, 6.6166, 6.6166, 6.6166] +24-11-19 20:35:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:47 | D | sum error = [ 191.3757, 200.4572, 209.8687, 219.6417, 229.7503] +24-11-19 20:35:47 | D | best error = [ 6.6166, 6.6166, 6.6166, 6.6166, 6.6166] +24-11-19 20:35:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:47 | D | sum error = [ 240.2088, 251.0317, 262.2167, 273.7904, 285.7109] +24-11-19 20:35:47 | D | best error = [ 6.6166, 6.6166, 6.6166, 6.6166, 6.6166] +24-11-19 20:35:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:47 | D | sum error = [ 298.0130, 310.7090, 323.7934, 337.2671, 351.1603] +24-11-19 20:35:47 | D | best error = [ 6.6166, 6.6166, 6.6166, 6.6166, 6.6166] +24-11-19 20:35:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:47 | D | sum error = [ 365.4416, 380.1409, 395.2736, 410.8464, 426.8662] +24-11-19 20:35:47 | D | best error = [ 6.6166, 6.6166, 6.6166, 6.6166, 6.6166] +24-11-19 20:35:47 | D | + error = [6.6166] +24-11-19 20:35:47 | D | - Calibrating model.layers.24.self_attn.o_proj.weight +24-11-19 20:35:47 | D | + w: sint8 +24-11-19 20:35:47 | D | + x: None +24-11-19 20:35:47 | D | + y: None +24-11-19 20:35:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:47 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:35:47 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:35:47 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:35:47 | D | - range ratio = [ 1.0000] +24-11-19 20:35:47 | D | sum error = [ 1.6953] +24-11-19 20:35:47 | D | best error = [ 1.6953] +24-11-19 20:35:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:48 | D | sum error = [ 1.6807, 1.6692, 1.6710, 1.6756, 1.6907] +24-11-19 20:35:48 | D | best error = [ 1.5744, 1.5195, 1.4883, 1.4671, 1.4519] +24-11-19 20:35:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:48 | D | sum error = [ 1.7202, 1.7567, 1.8015, 1.8590, 1.9346] +24-11-19 20:35:48 | D | best error = [ 1.4422, 1.4342, 1.4291, 1.4255, 1.4234] +24-11-19 20:35:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:48 | D | sum error = [ 2.0275, 2.1277, 2.2327, 2.3608, 2.5033] +24-11-19 20:35:48 | D | best error = [ 1.4218, 1.4208, 1.4200, 1.4195, 1.4191] +24-11-19 20:35:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:48 | D | sum error = [ 2.6604, 2.8324, 3.0168, 3.2226, 3.4416] +24-11-19 20:35:48 | D | best error = [ 1.4190, 1.4188, 1.4186, 1.4185, 1.4185] +24-11-19 20:35:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:48 | D | sum error = [ 3.6850, 3.9415, 4.2103, 4.4979, 4.8089] +24-11-19 20:35:48 | D | best error = [ 1.4184, 1.4184, 1.4184, 1.4184, 1.4184] +24-11-19 20:35:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:48 | D | sum error = [ 5.1366, 5.4922, 5.8588, 6.2471, 6.6673] +24-11-19 20:35:48 | D | best error = [ 1.4184, 1.4184, 1.4184, 1.4184, 1.4184] +24-11-19 20:35:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:48 | D | sum error = [ 7.1176, 7.5853, 8.0778, 8.6038, 9.1576] +24-11-19 20:35:48 | D | best error = [ 1.4184, 1.4184, 1.4184, 1.4184, 1.4184] +24-11-19 20:35:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:48 | D | sum error = [ 9.7467, 10.3739, 11.0287, 11.7267, 12.4605] +24-11-19 20:35:48 | D | best error = [ 1.4184, 1.4184, 1.4184, 1.4184, 1.4184] +24-11-19 20:35:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:48 | D | sum error = [ 13.2349, 14.0560, 14.9236, 15.8384, 16.7988] +24-11-19 20:35:48 | D | best error = [ 1.4184, 1.4184, 1.4184, 1.4184, 1.4184] +24-11-19 20:35:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:48 | D | sum error = [ 17.8126, 18.8810, 20.0000, 21.1796, 22.4244] +24-11-19 20:35:48 | D | best error = [ 1.4184, 1.4184, 1.4184, 1.4184, 1.4184] +24-11-19 20:35:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:48 | D | sum error = [ 23.7278, 25.1060, 26.5470, 28.0614, 29.6555] +24-11-19 20:35:48 | D | best error = [ 1.4184, 1.4184, 1.4184, 1.4184, 1.4184] +24-11-19 20:35:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:48 | D | sum error = [ 31.3219, 33.0725, 34.9122, 36.8417, 38.8643] +24-11-19 20:35:48 | D | best error = [ 1.4184, 1.4184, 1.4184, 1.4184, 1.4184] +24-11-19 20:35:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:48 | D | sum error = [ 40.9782, 43.1887, 45.5067, 47.9282, 50.4566] +24-11-19 20:35:48 | D | best error = [ 1.4184, 1.4184, 1.4184, 1.4184, 1.4184] +24-11-19 20:35:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:48 | D | sum error = [ 53.0969, 55.8498, 58.7234, 61.7204, 64.8260] +24-11-19 20:35:48 | D | best error = [ 1.4184, 1.4184, 1.4184, 1.4184, 1.4184] +24-11-19 20:35:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:48 | D | sum error = [ 68.0564, 71.4170, 74.8989, 78.5130, 82.2624] +24-11-19 20:35:48 | D | best error = [ 1.4184, 1.4184, 1.4184, 1.4184, 1.4184] +24-11-19 20:35:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:48 | D | sum error = [ 86.1461, 90.1811, 94.3558, 98.6777, 103.1491] +24-11-19 20:35:48 | D | best error = [ 1.4184, 1.4184, 1.4184, 1.4184, 1.4184] +24-11-19 20:35:48 | D | + error = [1.4184] +24-11-19 20:35:48 | D | - Calibrating model.layers.24.mlp.up_proj.weight +24-11-19 20:35:48 | D | + w: sint8 +24-11-19 20:35:48 | D | + x: None +24-11-19 20:35:48 | D | + y: None +24-11-19 20:35:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:48 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:35:48 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:35:48 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:35:48 | D | - range ratio = [ 1.0000] +24-11-19 20:35:48 | D | sum error = [ 10.1791] +24-11-19 20:35:48 | D | best error = [ 10.1791] +24-11-19 20:35:49 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:49 | D | sum error = [ 10.0908, 10.0502, 10.0860, 10.2411, 10.3963] +24-11-19 20:35:49 | D | best error = [ 9.4022, 9.1066, 8.9462, 8.8597, 8.8092] +24-11-19 20:35:49 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:49 | D | sum error = [ 10.6641, 11.0446, 11.4701, 12.0139, 12.6391] +24-11-19 20:35:49 | D | best error = [ 8.7847, 8.7732, 8.7683, 8.7668, 8.7666] +24-11-19 20:35:49 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:49 | D | sum error = [ 13.3529, 14.2020, 15.0936, 16.1366, 17.2343] +24-11-19 20:35:49 | D | best error = [ 8.7665, 8.7665, 8.7665, 8.7665, 8.7665] +24-11-19 20:35:49 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:49 | D | sum error = [ 18.4307, 19.7368, 21.1774, 22.6624, 24.2799] +24-11-19 20:35:49 | D | best error = [ 8.7665, 8.7665, 8.7665, 8.7665, 8.7665] +24-11-19 20:35:49 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:49 | D | sum error = [ 26.0479, 27.8856, 29.8480, 31.9226, 34.1463] +24-11-19 20:35:49 | D | best error = [ 8.7665, 8.7665, 8.7665, 8.7665, 8.7665] +24-11-19 20:35:49 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:49 | D | sum error = [ 36.4885, 38.9603, 41.5909, 44.3361, 47.2608] +24-11-19 20:35:49 | D | best error = [ 8.7665, 8.7665, 8.7665, 8.7665, 8.7665] +24-11-19 20:35:49 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:49 | D | sum error = [ 50.3604, 53.5841, 57.0061, 60.6048, 64.4001] +24-11-19 20:35:49 | D | best error = [ 8.7665, 8.7665, 8.7665, 8.7665, 8.7665] +24-11-19 20:35:49 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:49 | D | sum error = [ 68.3630, 72.5931, 76.9909, 81.6382, 86.4943] +24-11-19 20:35:49 | D | best error = [ 8.7665, 8.7665, 8.7665, 8.7665, 8.7665] +24-11-19 20:35:49 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:49 | D | sum error = [ 91.6059, 96.9667, 102.5996, 108.4744, 114.6405] +24-11-19 20:35:49 | D | best error = [ 8.7665, 8.7665, 8.7665, 8.7665, 8.7665] +24-11-19 20:35:49 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:49 | D | sum error = [ 121.1268, 127.8748, 134.9563, 142.3329, 150.0550] +24-11-19 20:35:49 | D | best error = [ 8.7665, 8.7665, 8.7665, 8.7665, 8.7665] +24-11-19 20:35:49 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:49 | D | sum error = [ 158.1173, 166.5097, 175.2689, 184.4032, 193.9136] +24-11-19 20:35:49 | D | best error = [ 8.7665, 8.7665, 8.7665, 8.7665, 8.7665] +24-11-19 20:35:49 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:49 | D | sum error = [ 203.8143, 214.1291, 224.8468, 235.9999, 247.5719] +24-11-19 20:35:49 | D | best error = [ 8.7665, 8.7665, 8.7665, 8.7665, 8.7665] +24-11-19 20:35:49 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:49 | D | sum error = [ 259.5917, 272.0719, 285.0232, 298.4304, 312.3346] +24-11-19 20:35:49 | D | best error = [ 8.7665, 8.7665, 8.7665, 8.7665, 8.7665] +24-11-19 20:35:49 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:49 | D | sum error = [ 326.7256, 341.6401, 357.0594, 372.9949, 389.4706] +24-11-19 20:35:49 | D | best error = [ 8.7665, 8.7665, 8.7665, 8.7665, 8.7665] +24-11-19 20:35:49 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:49 | D | sum error = [ 406.4890, 424.0442, 442.1544, 460.8277, 480.0800] +24-11-19 20:35:49 | D | best error = [ 8.7665, 8.7665, 8.7665, 8.7665, 8.7665] +24-11-19 20:35:49 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:49 | D | sum error = [ 499.8668, 520.2706, 541.2392, 562.8031, 584.9627] +24-11-19 20:35:49 | D | best error = [ 8.7665, 8.7665, 8.7665, 8.7665, 8.7665] +24-11-19 20:35:49 | D | + error = [8.7665] +24-11-19 20:35:49 | D | - Calibrating model.layers.24.mlp.gate_proj.weight +24-11-19 20:35:49 | D | + w: sint8 +24-11-19 20:35:49 | D | + x: None +24-11-19 20:35:49 | D | + y: None +24-11-19 20:35:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:49 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:35:49 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:35:49 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:35:49 | D | - range ratio = [ 1.0000] +24-11-19 20:35:49 | D | sum error = [ 10.9379] +24-11-19 20:35:49 | D | best error = [ 10.9379] +24-11-19 20:35:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:50 | D | sum error = [ 10.8679, 10.8293, 10.8485, 10.9824, 11.1961] +24-11-19 20:35:50 | D | best error = [ 10.1232, 9.8019, 9.6280, 9.5268, 9.4700] +24-11-19 20:35:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:50 | D | sum error = [ 11.4689, 11.8784, 12.3428, 12.9484, 13.6203] +24-11-19 20:35:50 | D | best error = [ 9.4418, 9.4301, 9.4249, 9.4233, 9.4229] +24-11-19 20:35:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:50 | D | sum error = [ 14.4038, 15.2862, 16.3278, 17.4114, 18.6367] +24-11-19 20:35:50 | D | best error = [ 9.4229, 9.4229, 9.4229, 9.4229, 9.4229] +24-11-19 20:35:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:50 | D | sum error = [ 19.9513, 21.3942, 22.9407, 24.6144, 26.4159] +24-11-19 20:35:50 | D | best error = [ 9.4229, 9.4229, 9.4229, 9.4229, 9.4229] +24-11-19 20:35:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:50 | D | sum error = [ 28.3298, 30.3529, 32.4965, 34.8235, 37.2553] +24-11-19 20:35:50 | D | best error = [ 9.4229, 9.4229, 9.4229, 9.4229, 9.4229] +24-11-19 20:35:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:50 | D | sum error = [ 39.8650, 42.5905, 45.5256, 48.6072, 51.8859] +24-11-19 20:35:50 | D | best error = [ 9.4229, 9.4229, 9.4229, 9.4229, 9.4229] +24-11-19 20:35:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:50 | D | sum error = [ 55.3159, 58.9604, 62.7986, 66.8479, 71.1094] +24-11-19 20:35:50 | D | best error = [ 9.4229, 9.4229, 9.4229, 9.4229, 9.4229] +24-11-19 20:35:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:50 | D | sum error = [ 75.6203, 80.3595, 85.3461, 90.6174, 96.1441] +24-11-19 20:35:50 | D | best error = [ 9.4229, 9.4229, 9.4229, 9.4229, 9.4229] +24-11-19 20:35:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:50 | D | sum error = [ 102.0065, 108.0829, 114.5327, 121.2575, 128.3411] +24-11-19 20:35:50 | D | best error = [ 9.4229, 9.4229, 9.4229, 9.4229, 9.4229] +24-11-19 20:35:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:50 | D | sum error = [ 135.8355, 143.7010, 151.8971, 160.5525, 169.5831] +24-11-19 20:35:50 | D | best error = [ 9.4229, 9.4229, 9.4229, 9.4229, 9.4229] +24-11-19 20:35:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:50 | D | sum error = [ 179.0505, 189.0076, 199.4300, 210.3216, 221.7229] +24-11-19 20:35:50 | D | best error = [ 9.4229, 9.4229, 9.4229, 9.4229, 9.4229] +24-11-19 20:35:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:50 | D | sum error = [ 233.6553, 246.1302, 259.1490, 272.7186, 286.8734] +24-11-19 20:35:50 | D | best error = [ 9.4229, 9.4229, 9.4229, 9.4229, 9.4229] +24-11-19 20:35:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:50 | D | sum error = [ 301.6679, 317.0782, 333.1388, 349.8219, 367.2012] +24-11-19 20:35:50 | D | best error = [ 9.4229, 9.4229, 9.4229, 9.4229, 9.4229] +24-11-19 20:35:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:50 | D | sum error = [ 385.2609, 404.0695, 423.5862, 443.8482, 464.8458] +24-11-19 20:35:50 | D | best error = [ 9.4229, 9.4229, 9.4229, 9.4229, 9.4229] +24-11-19 20:35:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:50 | D | sum error = [ 486.5882, 509.1019, 532.4095, 556.4954, 581.4177] +24-11-19 20:35:50 | D | best error = [ 9.4229, 9.4229, 9.4229, 9.4229, 9.4229] +24-11-19 20:35:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:50 | D | sum error = [ 607.1388, 633.6943, 661.0583, 689.2504, 718.2950] +24-11-19 20:35:50 | D | best error = [ 9.4229, 9.4229, 9.4229, 9.4229, 9.4229] +24-11-19 20:35:50 | D | + error = [9.4229] +24-11-19 20:35:50 | D | - Calibrating model.layers.24.mlp.down_proj.weight +24-11-19 20:35:50 | D | + w: sint8 +24-11-19 20:35:50 | D | + x: None +24-11-19 20:35:50 | D | + y: None +24-11-19 20:35:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:50 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:35:51 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:35:51 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:35:51 | D | - range ratio = [ 1.0000] +24-11-19 20:35:51 | D | sum error = [ 3.9004] +24-11-19 20:35:51 | D | best error = [ 3.9004] +24-11-19 20:35:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:52 | D | sum error = [ 3.8709, 3.8526, 3.8229, 3.8143, 3.8163] +24-11-19 20:35:52 | D | best error = [ 3.7467, 3.6719, 3.6178, 3.5794, 3.5513] +24-11-19 20:35:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:52 | D | sum error = [ 3.8302, 3.8643, 3.9240, 3.9861, 4.0877] +24-11-19 20:35:52 | D | best error = [ 3.5301, 3.5138, 3.5022, 3.4937, 3.4877] +24-11-19 20:35:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:52 | D | sum error = [ 4.2029, 4.3397, 4.5060, 4.6970, 4.9251] +24-11-19 20:35:52 | D | best error = [ 3.4834, 3.4812, 3.4795, 3.4784, 3.4779] +24-11-19 20:35:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:52 | D | sum error = [ 5.1787, 5.4660, 5.7802, 6.1235, 6.5194] +24-11-19 20:35:52 | D | best error = [ 3.4776, 3.4774, 3.4774, 3.4773, 3.4773] +24-11-19 20:35:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:52 | D | sum error = [ 6.9447, 7.4024, 7.9030, 8.4360, 9.0153] +24-11-19 20:35:52 | D | best error = [ 3.4772, 3.4772, 3.4772, 3.4772, 3.4772] +24-11-19 20:35:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:52 | D | sum error = [ 9.6430, 10.3148, 11.0313, 11.8068, 12.6216] +24-11-19 20:35:52 | D | best error = [ 3.4772, 3.4772, 3.4772, 3.4772, 3.4772] +24-11-19 20:35:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:52 | D | sum error = [ 13.4959, 14.4270, 15.4203, 16.4688, 17.5924] +24-11-19 20:35:52 | D | best error = [ 3.4772, 3.4772, 3.4772, 3.4772, 3.4772] +24-11-19 20:35:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:52 | D | sum error = [ 18.7885, 20.0433, 21.3884, 22.7994, 24.2957] +24-11-19 20:35:52 | D | best error = [ 3.4772, 3.4772, 3.4772, 3.4772, 3.4772] +24-11-19 20:35:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:52 | D | sum error = [ 25.8742, 27.5513, 29.3146, 31.1702, 33.1265] +24-11-19 20:35:52 | D | best error = [ 3.4772, 3.4772, 3.4772, 3.4772, 3.4772] +24-11-19 20:35:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:52 | D | sum error = [ 35.1935, 37.3706, 39.6554, 42.0544, 44.5915] +24-11-19 20:35:52 | D | best error = [ 3.4772, 3.4772, 3.4772, 3.4772, 3.4772] +24-11-19 20:35:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:52 | D | sum error = [ 47.2427, 50.0347, 52.9569, 56.0259, 59.2348] +24-11-19 20:35:52 | D | best error = [ 3.4772, 3.4772, 3.4772, 3.4772, 3.4772] +24-11-19 20:35:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:52 | D | sum error = [ 62.6010, 66.1204, 69.8085, 73.6595, 77.6853] +24-11-19 20:35:52 | D | best error = [ 3.4772, 3.4772, 3.4772, 3.4772, 3.4772] +24-11-19 20:35:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:52 | D | sum error = [ 81.8816, 86.2525, 90.8222, 95.5809, 100.5370] +24-11-19 20:35:52 | D | best error = [ 3.4772, 3.4772, 3.4772, 3.4772, 3.4772] +24-11-19 20:35:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:52 | D | sum error = [ 105.6964, 111.0660, 116.6519, 122.4604, 128.4665] +24-11-19 20:35:52 | D | best error = [ 3.4772, 3.4772, 3.4772, 3.4772, 3.4772] +24-11-19 20:35:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:52 | D | sum error = [ 134.7093, 141.1841, 147.8965, 154.8514, 162.0500] +24-11-19 20:35:52 | D | best error = [ 3.4772, 3.4772, 3.4772, 3.4772, 3.4772] +24-11-19 20:35:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:52 | D | sum error = [ 169.4990, 177.1980, 185.1556, 193.3779, 201.8572] +24-11-19 20:35:52 | D | best error = [ 3.4772, 3.4772, 3.4772, 3.4772, 3.4772] +24-11-19 20:35:52 | D | + error = [3.4772] +24-11-19 20:35:52 | D | - Quantizing model.layers.24.self_attn.q_proj.weight +24-11-19 20:35:53 | D | - Quantizing model.layers.24.self_attn.k_proj.weight +24-11-19 20:35:53 | D | - Quantizing model.layers.24.self_attn.v_proj.weight +24-11-19 20:35:54 | D | - Quantizing model.layers.24.self_attn.o_proj.weight +24-11-19 20:35:55 | D | - Quantizing model.layers.24.mlp.up_proj.weight +24-11-19 20:35:56 | D | - Quantizing model.layers.24.mlp.gate_proj.weight +24-11-19 20:35:57 | D | - Quantizing model.layers.24.mlp.down_proj.weight +24-11-19 20:36:05 | D | - Quantizing layer model.layers.25 +24-11-19 20:36:05 | D | - Calibrating model.layers.25.self_attn.q_proj.weight +24-11-19 20:36:05 | D | + w: sint8 +24-11-19 20:36:05 | D | + x: None +24-11-19 20:36:05 | D | + y: None +24-11-19 20:36:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:36:05 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:36:05 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:36:05 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:36:05 | D | - range ratio = [ 1.0000] +24-11-19 20:36:05 | D | sum error = [ 13.9573] +24-11-19 20:36:05 | D | best error = [ 13.9573] +24-11-19 20:36:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:18 | D | sum error = [ 13.6064, 14.0959, 13.9452, 13.9980, 14.4116] +24-11-19 20:36:18 | D | best error = [ 13.6064, 13.6064, 13.6064, 13.6064, 13.6064] +24-11-19 20:36:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:18 | D | sum error = [ 14.8636, 15.2551, 15.7882, 16.6642, 17.2530] +24-11-19 20:36:18 | D | best error = [ 13.6064, 13.6064, 13.6064, 13.6064, 13.6064] +24-11-19 20:36:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:18 | D | sum error = [ 18.3255, 19.5537, 21.1212, 22.3088, 24.0448] +24-11-19 20:36:18 | D | best error = [ 13.6064, 13.6064, 13.6064, 13.6064, 13.6064] +24-11-19 20:36:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:18 | D | sum error = [ 25.7450, 27.8817, 29.9765, 32.0682, 34.8310] +24-11-19 20:36:18 | D | best error = [ 13.6064, 13.6064, 13.6064, 13.6064, 13.6064] +24-11-19 20:36:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:18 | D | sum error = [ 37.3812, 40.5475, 43.7891, 46.9568, 50.6423] +24-11-19 20:36:18 | D | best error = [ 13.6064, 13.6064, 13.6064, 13.6064, 13.6064] +24-11-19 20:36:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:18 | D | sum error = [ 54.7712, 58.6578, 63.7998, 68.4301, 73.6261] +24-11-19 20:36:18 | D | best error = [ 13.6064, 13.6064, 13.6064, 13.6064, 13.6064] +24-11-19 20:36:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:18 | D | sum error = [ 79.0547, 85.3053, 91.2839, 98.0434, 105.3366] +24-11-19 20:36:18 | D | best error = [ 13.6064, 13.6064, 13.6064, 13.6064, 13.6064] +24-11-19 20:36:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:18 | D | sum error = [ 113.1220, 121.5202, 130.2844, 139.9914, 150.4144] +24-11-19 20:36:18 | D | best error = [ 13.6064, 13.6064, 13.6064, 13.6064, 13.6064] +24-11-19 20:36:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:18 | D | sum error = [ 161.1832, 173.1188, 186.1605, 199.5669, 214.1450] +24-11-19 20:36:18 | D | best error = [ 13.6064, 13.6064, 13.6064, 13.6064, 13.6064] +24-11-19 20:36:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:18 | D | sum error = [ 230.2868, 247.1394, 265.1450, 285.0789, 306.2021] +24-11-19 20:36:18 | D | best error = [ 13.6064, 13.6064, 13.6064, 13.6064, 13.6064] +24-11-19 20:36:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:18 | D | sum error = [ 329.0599, 353.8785, 380.3929, 409.5721, 441.4543] +24-11-19 20:36:18 | D | best error = [ 13.6064, 13.6064, 13.6064, 13.6064, 13.6064] +24-11-19 20:36:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:18 | D | sum error = [ 475.3271, 512.2732, 553.2434, 597.7118, 646.2942] +24-11-19 20:36:18 | D | best error = [ 13.6064, 13.6064, 13.6064, 13.6064, 13.6064] +24-11-19 20:36:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:18 | D | sum error = [ 700.0988, 758.8234, 823.7833, 894.9259, 973.5911] +24-11-19 20:36:18 | D | best error = [ 13.6064, 13.6064, 13.6064, 13.6064, 13.6064] +24-11-19 20:36:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:18 | D | sum error = [ 1060.3842, 1155.8782, 1262.0243, 1379.0855, 1508.6595] +24-11-19 20:36:18 | D | best error = [ 13.6064, 13.6064, 13.6064, 13.6064, 13.6064] +24-11-19 20:36:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:18 | D | sum error = [ 1652.8584, 1812.1759, 1990.9751, 2189.1340, 2411.5649] +24-11-19 20:36:18 | D | best error = [ 13.6064, 13.6064, 13.6064, 13.6064, 13.6064] +24-11-19 20:36:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:18 | D | sum error = [ 2658.1323, 2931.5985, 3235.4301, 3570.4369, 3939.6486] +24-11-19 20:36:18 | D | best error = [ 13.6064, 13.6064, 13.6064, 13.6064, 13.6064] +24-11-19 20:36:18 | D | + error = [13.6064] +24-11-19 20:36:18 | D | - Calibrating model.layers.25.self_attn.k_proj.weight +24-11-19 20:36:18 | D | + w: sint8 +24-11-19 20:36:18 | D | + x: None +24-11-19 20:36:18 | D | + y: None +24-11-19 20:36:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:36:18 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:36:18 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:36:18 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:36:19 | D | - range ratio = [ 1.0000] +24-11-19 20:36:19 | D | sum error = [ 16.9980] +24-11-19 20:36:19 | D | best error = [ 16.9980] +24-11-19 20:36:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:31 | D | sum error = [ 16.5453, 16.0707, 16.1792, 17.6235, 16.9088] +24-11-19 20:36:31 | D | best error = [ 16.5453, 16.0707, 16.0707, 16.0707, 16.0707] +24-11-19 20:36:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:31 | D | sum error = [ 16.5880, 17.9870, 18.6401, 19.4442, 20.9672] +24-11-19 20:36:31 | D | best error = [ 16.0707, 16.0707, 16.0707, 16.0707, 16.0707] +24-11-19 20:36:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:31 | D | sum error = [ 22.6834, 24.3899, 26.0339, 26.6760, 28.3923] +24-11-19 20:36:31 | D | best error = [ 16.0707, 16.0707, 16.0707, 16.0707, 16.0707] +24-11-19 20:36:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:31 | D | sum error = [ 31.7848, 34.6542, 36.5506, 38.0735, 41.9986] +24-11-19 20:36:31 | D | best error = [ 16.0707, 16.0707, 16.0707, 16.0707, 16.0707] +24-11-19 20:36:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:31 | D | sum error = [ 45.0345, 48.1163, 52.4302, 56.1062, 59.6121] +24-11-19 20:36:31 | D | best error = [ 16.0707, 16.0707, 16.0707, 16.0707, 16.0707] +24-11-19 20:36:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:31 | D | sum error = [ 64.2670, 68.3951, 73.4678, 79.7193, 85.5648] +24-11-19 20:36:31 | D | best error = [ 16.0707, 16.0707, 16.0707, 16.0707, 16.0707] +24-11-19 20:36:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:31 | D | sum error = [ 91.5863, 98.4838, 106.2243, 113.8307, 122.4683] +24-11-19 20:36:31 | D | best error = [ 16.0707, 16.0707, 16.0707, 16.0707, 16.0707] +24-11-19 20:36:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:31 | D | sum error = [ 131.1205, 140.2394, 151.7448, 162.9328, 173.7709] +24-11-19 20:36:31 | D | best error = [ 16.0707, 16.0707, 16.0707, 16.0707, 16.0707] +24-11-19 20:36:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:31 | D | sum error = [ 187.0102, 200.4873, 214.5669, 230.3942, 246.0891] +24-11-19 20:36:31 | D | best error = [ 16.0707, 16.0707, 16.0707, 16.0707, 16.0707] +24-11-19 20:36:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:31 | D | sum error = [ 263.2496, 283.6493, 303.7863, 326.6316, 351.5731] +24-11-19 20:36:31 | D | best error = [ 16.0707, 16.0707, 16.0707, 16.0707, 16.0707] +24-11-19 20:36:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:31 | D | sum error = [ 377.7394, 407.6256, 438.2145, 473.2446, 509.6145] +24-11-19 20:36:31 | D | best error = [ 16.0707, 16.0707, 16.0707, 16.0707, 16.0707] +24-11-19 20:36:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:31 | D | sum error = [ 549.6376, 593.1352, 641.0238, 691.8055, 747.8070] +24-11-19 20:36:31 | D | best error = [ 16.0707, 16.0707, 16.0707, 16.0707, 16.0707] +24-11-19 20:36:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:31 | D | sum error = [ 808.7667, 874.7803, 948.2405, 1026.4922, 1113.0489] +24-11-19 20:36:31 | D | best error = [ 16.0707, 16.0707, 16.0707, 16.0707, 16.0707] +24-11-19 20:36:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:31 | D | sum error = [ 1209.1961, 1313.9585, 1430.9520, 1558.4678, 1700.8701] +24-11-19 20:36:31 | D | best error = [ 16.0707, 16.0707, 16.0707, 16.0707, 16.0707] +24-11-19 20:36:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:31 | D | sum error = [ 1856.7373, 2028.0616, 2216.0023, 2423.7795, 2652.6589] +24-11-19 20:36:31 | D | best error = [ 16.0707, 16.0707, 16.0707, 16.0707, 16.0707] +24-11-19 20:36:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:31 | D | sum error = [ 2908.8874, 3189.4046, 3501.1807, 3840.3073, 4212.4549] +24-11-19 20:36:31 | D | best error = [ 16.0707, 16.0707, 16.0707, 16.0707, 16.0707] +24-11-19 20:36:31 | D | + error = [16.0707] +24-11-19 20:36:31 | D | - Calibrating model.layers.25.self_attn.v_proj.weight +24-11-19 20:36:31 | D | + w: sint8 +24-11-19 20:36:31 | D | + x: None +24-11-19 20:36:31 | D | + y: None +24-11-19 20:36:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:31 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:36:31 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:36:32 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:36:32 | D | - range ratio = [ 1.0000] +24-11-19 20:36:32 | D | sum error = [ 8.5745] +24-11-19 20:36:32 | D | best error = [ 8.5745] +24-11-19 20:36:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:32 | D | sum error = [ 8.4818, 8.4725, 8.5308, 8.6382, 8.7934] +24-11-19 20:36:32 | D | best error = [ 7.9243, 7.6883, 7.5637, 7.4925, 7.4521] +24-11-19 20:36:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:32 | D | sum error = [ 8.9694, 9.2972, 9.7189, 10.0965, 10.6749] +24-11-19 20:36:32 | D | best error = [ 7.4289, 7.4192, 7.4158, 7.4143, 7.4139] +24-11-19 20:36:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:32 | D | sum error = [ 11.2797, 11.9380, 12.7636, 13.6022, 14.4914] +24-11-19 20:36:32 | D | best error = [ 7.4139, 7.4139, 7.4139, 7.4139, 7.4139] +24-11-19 20:36:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:32 | D | sum error = [ 15.5426, 16.6425, 17.8074, 19.1458, 20.4841] +24-11-19 20:36:32 | D | best error = [ 7.4139, 7.4139, 7.4139, 7.4139, 7.4139] +24-11-19 20:36:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:32 | D | sum error = [ 21.9520, 23.4855, 25.1723, 26.9283, 28.7704] +24-11-19 20:36:32 | D | best error = [ 7.4139, 7.4139, 7.4139, 7.4139, 7.4139] +24-11-19 20:36:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:32 | D | sum error = [ 30.7717, 32.8927, 35.0741, 37.4049, 39.8245] +24-11-19 20:36:32 | D | best error = [ 7.4139, 7.4139, 7.4139, 7.4139, 7.4139] +24-11-19 20:36:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:32 | D | sum error = [ 42.4569, 45.2100, 48.0897, 51.1662, 54.3848] +24-11-19 20:36:32 | D | best error = [ 7.4139, 7.4139, 7.4139, 7.4139, 7.4139] +24-11-19 20:36:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:32 | D | sum error = [ 57.7066, 61.2848, 64.9779, 68.8681, 72.9809] +24-11-19 20:36:32 | D | best error = [ 7.4139, 7.4139, 7.4139, 7.4139, 7.4139] +24-11-19 20:36:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:32 | D | sum error = [ 77.2656, 81.7377, 86.4269, 91.3563, 96.5022] +24-11-19 20:36:32 | D | best error = [ 7.4139, 7.4139, 7.4139, 7.4139, 7.4139] +24-11-19 20:36:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:32 | D | sum error = [ 101.9030, 107.5089, 113.3874, 119.5115, 125.8782] +24-11-19 20:36:32 | D | best error = [ 7.4139, 7.4139, 7.4139, 7.4139, 7.4139] +24-11-19 20:36:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:32 | D | sum error = [ 132.5443, 139.4639, 146.6959, 154.2137, 162.0272] +24-11-19 20:36:32 | D | best error = [ 7.4139, 7.4139, 7.4139, 7.4139, 7.4139] +24-11-19 20:36:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:32 | D | sum error = [ 170.1404, 178.5914, 187.3748, 196.4745, 205.8989] +24-11-19 20:36:32 | D | best error = [ 7.4139, 7.4139, 7.4139, 7.4139, 7.4139] +24-11-19 20:36:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:32 | D | sum error = [ 215.6871, 225.8277, 236.3327, 247.1893, 258.4304] +24-11-19 20:36:32 | D | best error = [ 7.4139, 7.4139, 7.4139, 7.4139, 7.4139] +24-11-19 20:36:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:32 | D | sum error = [ 270.0379, 282.0444, 294.4418, 307.2735, 320.5058] +24-11-19 20:36:32 | D | best error = [ 7.4139, 7.4139, 7.4139, 7.4139, 7.4139] +24-11-19 20:36:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:32 | D | sum error = [ 334.1707, 348.2872, 362.8339, 377.8293, 393.2608] +24-11-19 20:36:32 | D | best error = [ 7.4139, 7.4139, 7.4139, 7.4139, 7.4139] +24-11-19 20:36:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:32 | D | sum error = [ 409.1226, 425.4267, 442.1733, 459.3839, 477.0678] +24-11-19 20:36:32 | D | best error = [ 7.4139, 7.4139, 7.4139, 7.4139, 7.4139] +24-11-19 20:36:32 | D | + error = [7.4139] +24-11-19 20:36:32 | D | - Calibrating model.layers.25.self_attn.o_proj.weight +24-11-19 20:36:32 | D | + w: sint8 +24-11-19 20:36:32 | D | + x: None +24-11-19 20:36:32 | D | + y: None +24-11-19 20:36:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:32 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:36:32 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:36:32 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:36:32 | D | - range ratio = [ 1.0000] +24-11-19 20:36:32 | D | sum error = [ 1.6134] +24-11-19 20:36:32 | D | best error = [ 1.6134] +24-11-19 20:36:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:33 | D | sum error = [ 1.5965, 1.5917, 1.5986, 1.6190, 1.6445] +24-11-19 20:36:33 | D | best error = [ 1.5113, 1.4667, 1.4403, 1.4230, 1.4133] +24-11-19 20:36:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:33 | D | sum error = [ 1.6770, 1.7241, 1.7904, 1.8668, 1.9577] +24-11-19 20:36:33 | D | best error = [ 1.4057, 1.4004, 1.3966, 1.3937, 1.3912] +24-11-19 20:36:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:33 | D | sum error = [ 2.0623, 2.1802, 2.3106, 2.4599, 2.6197] +24-11-19 20:36:33 | D | best error = [ 1.3898, 1.3888, 1.3881, 1.3875, 1.3871] +24-11-19 20:36:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:33 | D | sum error = [ 2.7984, 2.9910, 3.2042, 3.4235, 3.6671] +24-11-19 20:36:33 | D | best error = [ 1.3867, 1.3864, 1.3863, 1.3862, 1.3862] +24-11-19 20:36:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:33 | D | sum error = [ 3.9174, 4.1975, 4.4830, 4.7989, 5.1235] +24-11-19 20:36:33 | D | best error = [ 1.3860, 1.3859, 1.3858, 1.3858, 1.3857] +24-11-19 20:36:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:33 | D | sum error = [ 5.4772, 5.8454, 6.2315, 6.6518, 7.0936] +24-11-19 20:36:33 | D | best error = [ 1.3857, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 20:36:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:33 | D | sum error = [ 7.5537, 8.0383, 8.5551, 9.0919, 9.6690] +24-11-19 20:36:33 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 20:36:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:33 | D | sum error = [ 10.2706, 10.9070, 11.5831, 12.2763, 13.0197] +24-11-19 20:36:33 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 20:36:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:33 | D | sum error = [ 13.7998, 14.6134, 15.4740, 16.3686, 17.3094] +24-11-19 20:36:33 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 20:36:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:33 | D | sum error = [ 18.2953, 19.3331, 20.4149, 21.5446, 22.7302] +24-11-19 20:36:33 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 20:36:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:33 | D | sum error = [ 23.9689, 25.2684, 26.6252, 28.0402, 29.5156] +24-11-19 20:36:33 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 20:36:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:33 | D | sum error = [ 31.0629, 32.6740, 34.3513, 36.1034, 37.9321] +24-11-19 20:36:33 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 20:36:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:33 | D | sum error = [ 39.8380, 41.8198, 43.8830, 46.0279, 48.2581] +24-11-19 20:36:33 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 20:36:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:33 | D | sum error = [ 50.5752, 52.9742, 55.4686, 58.0597, 60.7383] +24-11-19 20:36:33 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 20:36:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:33 | D | sum error = [ 63.5143, 66.3842, 69.3595, 72.4340, 75.6101] +24-11-19 20:36:33 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 20:36:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:33 | D | sum error = [ 78.8873, 82.2674, 85.7631, 89.3662, 93.0783] +24-11-19 20:36:33 | D | best error = [ 1.3856, 1.3856, 1.3856, 1.3856, 1.3856] +24-11-19 20:36:33 | D | + error = [1.3856] +24-11-19 20:36:33 | D | - Calibrating model.layers.25.mlp.up_proj.weight +24-11-19 20:36:33 | D | + w: sint8 +24-11-19 20:36:33 | D | + x: None +24-11-19 20:36:33 | D | + y: None +24-11-19 20:36:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:33 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:36:33 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:36:33 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:36:33 | D | - range ratio = [ 1.0000] +24-11-19 20:36:33 | D | sum error = [ 10.5096] +24-11-19 20:36:33 | D | best error = [ 10.5096] +24-11-19 20:36:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:34 | D | sum error = [ 10.4076, 10.4051, 10.4460, 10.5560, 10.7385] +24-11-19 20:36:34 | D | best error = [ 9.7089, 9.4011, 9.2414, 9.1457, 9.0932] +24-11-19 20:36:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:34 | D | sum error = [ 11.0327, 11.4179, 11.8612, 12.3913, 13.0593] +24-11-19 20:36:34 | D | best error = [ 9.0676, 9.0561, 9.0522, 9.0502, 9.0497] +24-11-19 20:36:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:34 | D | sum error = [ 13.7901, 14.6639, 15.5811, 16.6115, 17.7900] +24-11-19 20:36:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:36:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:34 | D | sum error = [ 19.0044, 20.3931, 21.8164, 23.4096, 25.0686] +24-11-19 20:36:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:36:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:34 | D | sum error = [ 26.8445, 28.7655, 30.7788, 32.9082, 35.2138] +24-11-19 20:36:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:36:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:34 | D | sum error = [ 37.6376, 40.2103, 42.9050, 45.7591, 48.7723] +24-11-19 20:36:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:36:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:34 | D | sum error = [ 51.9370, 55.3024, 58.8298, 62.5598, 66.4800] +24-11-19 20:36:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:36:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:34 | D | sum error = [ 70.6033, 74.9646, 79.5022, 84.2859, 89.3074] +24-11-19 20:36:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:36:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:34 | D | sum error = [ 94.5644, 100.0765, 105.8858, 111.9776, 118.3135] +24-11-19 20:36:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:36:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:34 | D | sum error = [ 124.9902, 131.9433, 139.2528, 146.8566, 154.8027] +24-11-19 20:36:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:36:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:34 | D | sum error = [ 163.1184, 171.7678, 180.7958, 190.1990, 200.0230] +24-11-19 20:36:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:36:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:34 | D | sum error = [ 210.2103, 220.8374, 231.8729, 243.3306, 255.2552] +24-11-19 20:36:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:36:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:34 | D | sum error = [ 267.6245, 280.4562, 293.7850, 307.5603, 321.8504] +24-11-19 20:36:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:36:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:34 | D | sum error = [ 336.6574, 351.9748, 367.8433, 384.2145, 401.1640] +24-11-19 20:36:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:36:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:34 | D | sum error = [ 418.6287, 436.6589, 455.2793, 474.4852, 494.2936] +24-11-19 20:36:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:36:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:34 | D | sum error = [ 514.6851, 535.6826, 557.2744, 579.4676, 602.2778] +24-11-19 20:36:34 | D | best error = [ 9.0497, 9.0497, 9.0497, 9.0497, 9.0497] +24-11-19 20:36:34 | D | + error = [9.0497] +24-11-19 20:36:34 | D | - Calibrating model.layers.25.mlp.gate_proj.weight +24-11-19 20:36:34 | D | + w: sint8 +24-11-19 20:36:34 | D | + x: None +24-11-19 20:36:34 | D | + y: None +24-11-19 20:36:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:34 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:36:34 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:36:34 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:36:34 | D | - range ratio = [ 1.0000] +24-11-19 20:36:34 | D | sum error = [ 11.2783] +24-11-19 20:36:34 | D | best error = [ 11.2783] +24-11-19 20:36:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:35 | D | sum error = [ 11.1931, 11.1401, 11.2187, 11.3303, 11.5478] +24-11-19 20:36:35 | D | best error = [ 10.4329, 10.0912, 9.9251, 9.8237, 9.7680] +24-11-19 20:36:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:35 | D | sum error = [ 11.8264, 12.2421, 12.7219, 13.3280, 14.0439] +24-11-19 20:36:35 | D | best error = [ 9.7390, 9.7279, 9.7227, 9.7216, 9.7212] +24-11-19 20:36:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:35 | D | sum error = [ 14.8764, 15.7784, 16.8496, 17.9841, 19.2627] +24-11-19 20:36:35 | D | best error = [ 9.7212, 9.7212, 9.7212, 9.7212, 9.7212] +24-11-19 20:36:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:35 | D | sum error = [ 20.5964, 22.1063, 23.6767, 25.3889, 27.2388] +24-11-19 20:36:35 | D | best error = [ 9.7212, 9.7212, 9.7212, 9.7212, 9.7212] +24-11-19 20:36:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:35 | D | sum error = [ 29.1925, 31.2891, 33.4774, 35.8706, 38.3593] +24-11-19 20:36:35 | D | best error = [ 9.7212, 9.7212, 9.7212, 9.7212, 9.7212] +24-11-19 20:36:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:35 | D | sum error = [ 40.9963, 43.8140, 46.8116, 49.9569, 53.2934] +24-11-19 20:36:35 | D | best error = [ 9.7212, 9.7212, 9.7212, 9.7212, 9.7212] +24-11-19 20:36:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:35 | D | sum error = [ 56.8359, 60.5512, 64.5195, 68.6790, 73.0718] +24-11-19 20:36:35 | D | best error = [ 9.7212, 9.7212, 9.7212, 9.7212, 9.7212] +24-11-19 20:36:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:35 | D | sum error = [ 77.7080, 82.6093, 87.7407, 93.1402, 98.8507] +24-11-19 20:36:35 | D | best error = [ 9.7212, 9.7212, 9.7212, 9.7212, 9.7212] +24-11-19 20:36:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:35 | D | sum error = [ 104.8556, 111.2121, 117.8506, 124.8176, 132.1631] +24-11-19 20:36:35 | D | best error = [ 9.7212, 9.7212, 9.7212, 9.7212, 9.7212] +24-11-19 20:36:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:35 | D | sum error = [ 139.9023, 147.9754, 156.4542, 165.3552, 174.6830] +24-11-19 20:36:35 | D | best error = [ 9.7212, 9.7212, 9.7212, 9.7212, 9.7212] +24-11-19 20:36:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:35 | D | sum error = [ 184.4608, 194.7158, 205.4243, 216.6699, 228.4033] +24-11-19 20:36:35 | D | best error = [ 9.7212, 9.7212, 9.7212, 9.7212, 9.7212] +24-11-19 20:36:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:35 | D | sum error = [ 240.7041, 253.5415, 266.9417, 280.9283, 295.5267] +24-11-19 20:36:35 | D | best error = [ 9.7212, 9.7212, 9.7212, 9.7212, 9.7212] +24-11-19 20:36:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:35 | D | sum error = [ 310.7525, 326.5896, 343.1567, 360.3740, 378.2724] +24-11-19 20:36:35 | D | best error = [ 9.7212, 9.7212, 9.7212, 9.7212, 9.7212] +24-11-19 20:36:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:35 | D | sum error = [ 396.8705, 416.1951, 436.2411, 457.0843, 478.6720] +24-11-19 20:36:35 | D | best error = [ 9.7212, 9.7212, 9.7212, 9.7212, 9.7212] +24-11-19 20:36:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:35 | D | sum error = [ 501.0610, 524.2628, 548.2425, 573.0203, 598.6510] +24-11-19 20:36:35 | D | best error = [ 9.7212, 9.7212, 9.7212, 9.7212, 9.7212] +24-11-19 20:36:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:35 | D | sum error = [ 625.0522, 652.3647, 680.5148, 709.5462, 739.4236] +24-11-19 20:36:35 | D | best error = [ 9.7212, 9.7212, 9.7212, 9.7212, 9.7212] +24-11-19 20:36:35 | D | + error = [9.7212] +24-11-19 20:36:35 | D | - Calibrating model.layers.25.mlp.down_proj.weight +24-11-19 20:36:35 | D | + w: sint8 +24-11-19 20:36:35 | D | + x: None +24-11-19 20:36:35 | D | + y: None +24-11-19 20:36:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:35 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:36:35 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:36:36 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:36:36 | D | - range ratio = [ 1.0000] +24-11-19 20:36:36 | D | sum error = [ 3.9736] +24-11-19 20:36:36 | D | best error = [ 3.9736] +24-11-19 20:36:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:36 | D | sum error = [ 3.9443, 3.9207, 3.8897, 3.8831, 3.8788] +24-11-19 20:36:36 | D | best error = [ 3.8250, 3.7474, 3.6927, 3.6560, 3.6243] +24-11-19 20:36:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:36 | D | sum error = [ 3.9031, 3.9301, 3.9878, 4.0519, 4.1293] +24-11-19 20:36:36 | D | best error = [ 3.6032, 3.5885, 3.5789, 3.5715, 3.5658] +24-11-19 20:36:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:36 | D | sum error = [ 4.2433, 4.3763, 4.5363, 4.7223, 4.9494] +24-11-19 20:36:36 | D | best error = [ 3.5625, 3.5601, 3.5584, 3.5577, 3.5574] +24-11-19 20:36:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:36 | D | sum error = [ 5.1934, 5.4767, 5.7924, 6.1464, 6.5317] +24-11-19 20:36:36 | D | best error = [ 3.5570, 3.5568, 3.5567, 3.5567, 3.5566] +24-11-19 20:36:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:36 | D | sum error = [ 6.9507, 7.4087, 7.9113, 8.4416, 9.0255] +24-11-19 20:36:36 | D | best error = [ 3.5566, 3.5566, 3.5566, 3.5566, 3.5566] +24-11-19 20:36:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:36 | D | sum error = [ 9.6522, 10.3225, 11.0432, 11.8160, 12.6329] +24-11-19 20:36:36 | D | best error = [ 3.5566, 3.5566, 3.5566, 3.5566, 3.5566] +24-11-19 20:36:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:36 | D | sum error = [ 13.5155, 14.4475, 15.4423, 16.4966, 17.6259] +24-11-19 20:36:36 | D | best error = [ 3.5566, 3.5566, 3.5566, 3.5566, 3.5566] +24-11-19 20:36:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:36 | D | sum error = [ 18.8174, 20.0830, 21.4213, 22.8304, 24.3257] +24-11-19 20:36:36 | D | best error = [ 3.5566, 3.5566, 3.5566, 3.5566, 3.5566] +24-11-19 20:36:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:36 | D | sum error = [ 25.9156, 27.5864, 29.3457, 31.2101, 33.1670] +24-11-19 20:36:36 | D | best error = [ 3.5566, 3.5566, 3.5566, 3.5566, 3.5566] +24-11-19 20:36:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:36 | D | sum error = [ 35.2368, 37.4197, 39.7143, 42.1245, 44.6615] +24-11-19 20:36:36 | D | best error = [ 3.5566, 3.5566, 3.5566, 3.5566, 3.5566] +24-11-19 20:36:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:36 | D | sum error = [ 47.3309, 50.1244, 53.0566, 56.1319, 59.3501] +24-11-19 20:36:36 | D | best error = [ 3.5566, 3.5566, 3.5566, 3.5566, 3.5566] +24-11-19 20:36:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:36 | D | sum error = [ 62.7261, 66.2595, 69.9534, 73.8141, 77.8561] +24-11-19 20:36:36 | D | best error = [ 3.5566, 3.5566, 3.5566, 3.5566, 3.5566] +24-11-19 20:36:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:36 | D | sum error = [ 82.0760, 86.4842, 91.0777, 95.8661, 100.8484] +24-11-19 20:36:36 | D | best error = [ 3.5566, 3.5566, 3.5566, 3.5566, 3.5566] +24-11-19 20:36:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:36 | D | sum error = [ 106.0416, 111.4469, 117.0732, 122.9199, 128.9727] +24-11-19 20:36:36 | D | best error = [ 3.5566, 3.5566, 3.5566, 3.5566, 3.5566] +24-11-19 20:36:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:36 | D | sum error = [ 135.2631, 141.7761, 148.5358, 155.5299, 162.7800] +24-11-19 20:36:36 | D | best error = [ 3.5566, 3.5566, 3.5566, 3.5566, 3.5566] +24-11-19 20:36:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:36 | D | sum error = [ 170.2847, 178.0342, 186.0486, 194.3262, 202.8720] +24-11-19 20:36:36 | D | best error = [ 3.5566, 3.5566, 3.5566, 3.5566, 3.5566] +24-11-19 20:36:36 | D | + error = [3.5566] +24-11-19 20:36:37 | D | - Quantizing model.layers.25.self_attn.q_proj.weight +24-11-19 20:36:37 | D | - Quantizing model.layers.25.self_attn.k_proj.weight +24-11-19 20:36:38 | D | - Quantizing model.layers.25.self_attn.v_proj.weight +24-11-19 20:36:39 | D | - Quantizing model.layers.25.self_attn.o_proj.weight +24-11-19 20:36:40 | D | - Quantizing model.layers.25.mlp.up_proj.weight +24-11-19 20:36:41 | D | - Quantizing model.layers.25.mlp.gate_proj.weight +24-11-19 20:36:42 | D | - Quantizing model.layers.25.mlp.down_proj.weight +24-11-19 20:36:49 | D | - Quantizing layer model.layers.26 +24-11-19 20:36:49 | D | - Calibrating model.layers.26.self_attn.q_proj.weight +24-11-19 20:36:49 | D | + w: sint8 +24-11-19 20:36:49 | D | + x: None +24-11-19 20:36:49 | D | + y: None +24-11-19 20:36:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:36:49 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:36:49 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:36:50 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:36:50 | D | - range ratio = [ 1.0000] +24-11-19 20:36:50 | D | sum error = [ 17.6043] +24-11-19 20:36:50 | D | best error = [ 17.6043] +24-11-19 20:37:02 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:02 | D | sum error = [ 17.6089, 17.7531, 17.8704, 17.3868, 18.1764] +24-11-19 20:37:02 | D | best error = [ 17.6043, 17.6043, 17.6043, 17.3868, 17.3868] +24-11-19 20:37:02 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:02 | D | sum error = [ 18.5774, 19.3512, 20.0146, 20.6211, 21.7593] +24-11-19 20:37:02 | D | best error = [ 17.3868, 17.3868, 17.3868, 17.3868, 17.3868] +24-11-19 20:37:02 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:02 | D | sum error = [ 23.4967, 24.6670, 26.3899, 28.6945, 30.5504] +24-11-19 20:37:02 | D | best error = [ 17.3868, 17.3868, 17.3868, 17.3868, 17.3868] +24-11-19 20:37:02 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:02 | D | sum error = [ 32.7131, 34.6922, 37.4260, 40.5938, 43.6460] +24-11-19 20:37:02 | D | best error = [ 17.3868, 17.3868, 17.3868, 17.3868, 17.3868] +24-11-19 20:37:02 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:02 | D | sum error = [ 46.9756, 50.9483, 54.9826, 58.6346, 63.0331] +24-11-19 20:37:02 | D | best error = [ 17.3868, 17.3868, 17.3868, 17.3868, 17.3868] +24-11-19 20:37:02 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:02 | D | sum error = [ 68.6520, 73.3475, 79.8335, 86.0922, 92.6284] +24-11-19 20:37:02 | D | best error = [ 17.3868, 17.3868, 17.3868, 17.3868, 17.3868] +24-11-19 20:37:02 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:02 | D | sum error = [ 100.1831, 107.2734, 115.3433, 124.0915, 133.3759] +24-11-19 20:37:02 | D | best error = [ 17.3868, 17.3868, 17.3868, 17.3868, 17.3868] +24-11-19 20:37:02 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:02 | D | sum error = [ 143.4225, 155.0243, 166.3590, 178.1377, 190.7309] +24-11-19 20:37:02 | D | best error = [ 17.3868, 17.3868, 17.3868, 17.3868, 17.3868] +24-11-19 20:37:02 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:02 | D | sum error = [ 205.1984, 219.9324, 236.4680, 253.5242, 271.3686] +24-11-19 20:37:02 | D | best error = [ 17.3868, 17.3868, 17.3868, 17.3868, 17.3868] +24-11-19 20:37:02 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:02 | D | sum error = [ 291.0246, 312.5210, 335.3812, 359.6798, 386.2071] +24-11-19 20:37:02 | D | best error = [ 17.3868, 17.3868, 17.3868, 17.3868, 17.3868] +24-11-19 20:37:02 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:02 | D | sum error = [ 414.1988, 445.3276, 477.3304, 512.9706, 550.3850] +24-11-19 20:37:02 | D | best error = [ 17.3868, 17.3868, 17.3868, 17.3868, 17.3868] +24-11-19 20:37:02 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:02 | D | sum error = [ 591.6472, 636.3345, 684.5849, 736.6365, 791.8107] +24-11-19 20:37:02 | D | best error = [ 17.3868, 17.3868, 17.3868, 17.3868, 17.3868] +24-11-19 20:37:02 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:02 | D | sum error = [ 853.1367, 918.2803, 988.7322, 1065.9488, 1148.2876] +24-11-19 20:37:02 | D | best error = [ 17.3868, 17.3868, 17.3868, 17.3868, 17.3868] +24-11-19 20:37:02 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:02 | D | sum error = [ 1238.7584, 1335.9739, 1442.1346, 1558.3250, 1683.9312] +24-11-19 20:37:02 | D | best error = [ 17.3868, 17.3868, 17.3868, 17.3868, 17.3868] +24-11-19 20:37:02 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:02 | D | sum error = [ 1821.0304, 1967.1921, 2127.6988, 2300.8466, 2489.3762] +24-11-19 20:37:02 | D | best error = [ 17.3868, 17.3868, 17.3868, 17.3868, 17.3868] +24-11-19 20:37:02 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:02 | D | sum error = [ 2691.4857, 2910.5515, 3144.4796, 3394.0329, 3657.8650] +24-11-19 20:37:02 | D | best error = [ 17.3868, 17.3868, 17.3868, 17.3868, 17.3868] +24-11-19 20:37:02 | D | + error = [17.3868] +24-11-19 20:37:03 | D | - Calibrating model.layers.26.self_attn.k_proj.weight +24-11-19 20:37:03 | D | + w: sint8 +24-11-19 20:37:03 | D | + x: None +24-11-19 20:37:03 | D | + y: None +24-11-19 20:37:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:37:03 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:37:03 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:37:03 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:37:03 | D | - range ratio = [ 1.0000] +24-11-19 20:37:03 | D | sum error = [ 21.1860] +24-11-19 20:37:03 | D | best error = [ 21.1860] +24-11-19 20:37:16 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:16 | D | sum error = [ 20.5539, 20.5474, 21.4758, 21.1181, 25.7897] +24-11-19 20:37:16 | D | best error = [ 20.5539, 20.5474, 20.5474, 20.5474, 20.5474] +24-11-19 20:37:16 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:16 | D | sum error = [ 21.7343, 22.7562, 25.0062, 25.6672, 30.8480] +24-11-19 20:37:16 | D | best error = [ 20.5474, 20.5474, 20.5474, 20.5474, 20.5474] +24-11-19 20:37:16 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:16 | D | sum error = [ 28.8114, 31.9348, 30.5569, 33.8713, 35.2988] +24-11-19 20:37:16 | D | best error = [ 20.5474, 20.5474, 20.5474, 20.5474, 20.5474] +24-11-19 20:37:16 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:16 | D | sum error = [ 37.5352, 43.0767, 45.5124, 46.8030, 49.5302] +24-11-19 20:37:16 | D | best error = [ 20.5474, 20.5474, 20.5474, 20.5474, 20.5474] +24-11-19 20:37:16 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:16 | D | sum error = [ 53.6369, 59.5564, 62.7573, 68.3659, 73.1169] +24-11-19 20:37:16 | D | best error = [ 20.5474, 20.5474, 20.5474, 20.5474, 20.5474] +24-11-19 20:37:16 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:16 | D | sum error = [ 80.2350, 87.6642, 96.5276, 103.7545, 117.0298] +24-11-19 20:37:16 | D | best error = [ 20.5474, 20.5474, 20.5474, 20.5474, 20.5474] +24-11-19 20:37:16 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:16 | D | sum error = [ 125.3882, 134.1787, 144.7152, 158.5644, 171.7031] +24-11-19 20:37:16 | D | best error = [ 20.5474, 20.5474, 20.5474, 20.5474, 20.5474] +24-11-19 20:37:16 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:16 | D | sum error = [ 181.3282, 199.0750, 209.7952, 222.0106, 236.9966] +24-11-19 20:37:16 | D | best error = [ 20.5474, 20.5474, 20.5474, 20.5474, 20.5474] +24-11-19 20:37:16 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:16 | D | sum error = [ 250.3975, 264.0392, 279.9137, 298.7018, 320.0756] +24-11-19 20:37:16 | D | best error = [ 20.5474, 20.5474, 20.5474, 20.5474, 20.5474] +24-11-19 20:37:16 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:16 | D | sum error = [ 337.4990, 358.9486, 380.1145, 403.8416, 427.9698] +24-11-19 20:37:16 | D | best error = [ 20.5474, 20.5474, 20.5474, 20.5474, 20.5474] +24-11-19 20:37:16 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:16 | D | sum error = [ 455.1278, 486.4566, 518.3879, 553.7334, 590.2639] +24-11-19 20:37:16 | D | best error = [ 20.5474, 20.5474, 20.5474, 20.5474, 20.5474] +24-11-19 20:37:16 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:16 | D | sum error = [ 629.1916, 672.4505, 721.0018, 771.9773, 828.6572] +24-11-19 20:37:16 | D | best error = [ 20.5474, 20.5474, 20.5474, 20.5474, 20.5474] +24-11-19 20:37:16 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:16 | D | sum error = [ 891.0502, 957.3948, 1027.6899, 1106.0180, 1189.8188] +24-11-19 20:37:16 | D | best error = [ 20.5474, 20.5474, 20.5474, 20.5474, 20.5474] +24-11-19 20:37:16 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:16 | D | sum error = [ 1282.9314, 1385.1652, 1494.8721, 1614.4124, 1741.7254] +24-11-19 20:37:16 | D | best error = [ 20.5474, 20.5474, 20.5474, 20.5474, 20.5474] +24-11-19 20:37:16 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:16 | D | sum error = [ 1880.1503, 2030.5553, 2191.5931, 2365.0862, 2552.0601] +24-11-19 20:37:16 | D | best error = [ 20.5474, 20.5474, 20.5474, 20.5474, 20.5474] +24-11-19 20:37:16 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:16 | D | sum error = [ 2755.2441, 2974.3198, 3210.8413, 3461.3044, 3727.0677] +24-11-19 20:37:16 | D | best error = [ 20.5474, 20.5474, 20.5474, 20.5474, 20.5474] +24-11-19 20:37:16 | D | + error = [20.5474] +24-11-19 20:37:16 | D | - Calibrating model.layers.26.self_attn.v_proj.weight +24-11-19 20:37:16 | D | + w: sint8 +24-11-19 20:37:16 | D | + x: None +24-11-19 20:37:16 | D | + y: None +24-11-19 20:37:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:16 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:37:16 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:37:16 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:37:16 | D | - range ratio = [ 1.0000] +24-11-19 20:37:16 | D | sum error = [ 8.4096] +24-11-19 20:37:16 | D | best error = [ 8.4096] +24-11-19 20:37:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:17 | D | sum error = [ 8.3901, 8.3301, 8.3668, 8.4865, 8.6153] +24-11-19 20:37:17 | D | best error = [ 7.8146, 7.5707, 7.4436, 7.3739, 7.3334] +24-11-19 20:37:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:17 | D | sum error = [ 8.8433, 9.0994, 9.5168, 9.9569, 10.4812] +24-11-19 20:37:17 | D | best error = [ 7.3146, 7.3068, 7.3026, 7.3017, 7.3016] +24-11-19 20:37:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:17 | D | sum error = [ 11.0352, 11.7497, 12.5423, 13.3417, 14.2718] +24-11-19 20:37:17 | D | best error = [ 7.3014, 7.3014, 7.3014, 7.3014, 7.3014] +24-11-19 20:37:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:17 | D | sum error = [ 15.2833, 16.3259, 17.5315, 18.7889, 20.1167] +24-11-19 20:37:17 | D | best error = [ 7.3014, 7.3014, 7.3014, 7.3014, 7.3014] +24-11-19 20:37:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:17 | D | sum error = [ 21.5032, 23.0617, 24.6874, 26.4025, 28.1867] +24-11-19 20:37:17 | D | best error = [ 7.3014, 7.3014, 7.3014, 7.3014, 7.3014] +24-11-19 20:37:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:17 | D | sum error = [ 30.1018, 32.1639, 34.3244, 36.6443, 38.9717] +24-11-19 20:37:17 | D | best error = [ 7.3014, 7.3014, 7.3014, 7.3014, 7.3014] +24-11-19 20:37:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:17 | D | sum error = [ 41.5279, 44.1546, 46.9514, 49.9193, 53.0303] +24-11-19 20:37:17 | D | best error = [ 7.3014, 7.3014, 7.3014, 7.3014, 7.3014] +24-11-19 20:37:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:17 | D | sum error = [ 56.2955, 59.7355, 63.3446, 67.1227, 71.1220] +24-11-19 20:37:17 | D | best error = [ 7.3014, 7.3014, 7.3014, 7.3014, 7.3014] +24-11-19 20:37:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:17 | D | sum error = [ 75.2595, 79.6244, 84.2223, 88.9922, 93.9813] +24-11-19 20:37:17 | D | best error = [ 7.3014, 7.3014, 7.3014, 7.3014, 7.3014] +24-11-19 20:37:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:17 | D | sum error = [ 99.2157, 104.6940, 110.4121, 116.3510, 122.5723] +24-11-19 20:37:17 | D | best error = [ 7.3014, 7.3014, 7.3014, 7.3014, 7.3014] +24-11-19 20:37:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:17 | D | sum error = [ 129.0490, 135.7701, 142.7755, 150.0802, 157.6384] +24-11-19 20:37:17 | D | best error = [ 7.3014, 7.3014, 7.3014, 7.3014, 7.3014] +24-11-19 20:37:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:17 | D | sum error = [ 165.5229, 173.6773, 182.1600, 190.9395, 200.0596] +24-11-19 20:37:17 | D | best error = [ 7.3014, 7.3014, 7.3014, 7.3014, 7.3014] +24-11-19 20:37:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:17 | D | sum error = [ 209.5067, 219.2994, 229.4334, 239.9366, 250.8220] +24-11-19 20:37:17 | D | best error = [ 7.3014, 7.3014, 7.3014, 7.3014, 7.3014] +24-11-19 20:37:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:17 | D | sum error = [ 262.0624, 273.6949, 285.7017, 298.1061, 310.8634] +24-11-19 20:37:17 | D | best error = [ 7.3014, 7.3014, 7.3014, 7.3014, 7.3014] +24-11-19 20:37:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:17 | D | sum error = [ 324.0686, 337.6796, 351.6783, 366.1023, 380.9621] +24-11-19 20:37:17 | D | best error = [ 7.3014, 7.3014, 7.3014, 7.3014, 7.3014] +24-11-19 20:37:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:17 | D | sum error = [ 396.2517, 411.9789, 428.1368, 444.7262, 461.7651] +24-11-19 20:37:17 | D | best error = [ 7.3014, 7.3014, 7.3014, 7.3014, 7.3014] +24-11-19 20:37:17 | D | + error = [7.3014] +24-11-19 20:37:17 | D | - Calibrating model.layers.26.self_attn.o_proj.weight +24-11-19 20:37:17 | D | + w: sint8 +24-11-19 20:37:17 | D | + x: None +24-11-19 20:37:17 | D | + y: None +24-11-19 20:37:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:17 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:37:17 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:37:17 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:37:17 | D | - range ratio = [ 1.0000] +24-11-19 20:37:17 | D | sum error = [ 2.2268] +24-11-19 20:37:17 | D | best error = [ 2.2268] +24-11-19 20:37:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:17 | D | sum error = [ 2.2029, 2.1797, 2.1743, 2.1641, 2.1501] +24-11-19 20:37:17 | D | best error = [ 2.0791, 2.0089, 1.9659, 1.9325, 1.9072] +24-11-19 20:37:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:17 | D | sum error = [ 2.1590, 2.1695, 2.1776, 2.1971, 2.2289] +24-11-19 20:37:17 | D | best error = [ 1.8865, 1.8707, 1.8577, 1.8455, 1.8356] +24-11-19 20:37:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:17 | D | sum error = [ 2.2543, 2.2986, 2.3570, 2.4229, 2.4990] +24-11-19 20:37:17 | D | best error = [ 1.8267, 1.8191, 1.8126, 1.8069, 1.8020] +24-11-19 20:37:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:17 | D | sum error = [ 2.5911, 2.6854, 2.7968, 2.9374, 3.0593] +24-11-19 20:37:17 | D | best error = [ 1.7976, 1.7940, 1.7906, 1.7878, 1.7859] +24-11-19 20:37:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:17 | D | sum error = [ 3.2269, 3.3945, 3.5859, 3.7910, 4.0112] +24-11-19 20:37:17 | D | best error = [ 1.7840, 1.7829, 1.7820, 1.7812, 1.7808] +24-11-19 20:37:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:17 | D | sum error = [ 4.2503, 4.5122, 4.7793, 5.0741, 5.3949] +24-11-19 20:37:17 | D | best error = [ 1.7803, 1.7795, 1.7793, 1.7791, 1.7789] +24-11-19 20:37:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:17 | D | sum error = [ 5.7425, 6.1030, 6.4918, 6.9062, 7.3358] +24-11-19 20:37:17 | D | best error = [ 1.7787, 1.7786, 1.7784, 1.7784, 1.7783] +24-11-19 20:37:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:17 | D | sum error = [ 7.8113, 8.3070, 8.8371, 9.3999, 10.0087] +24-11-19 20:37:17 | D | best error = [ 1.7782, 1.7782, 1.7781, 1.7780, 1.7780] +24-11-19 20:37:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:17 | D | sum error = [ 10.6445, 11.3299, 12.0499, 12.8075, 13.6213] +24-11-19 20:37:17 | D | best error = [ 1.7780, 1.7780, 1.7780, 1.7780, 1.7780] +24-11-19 20:37:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:17 | D | sum error = [ 14.4871, 15.3978, 16.3693, 17.3931, 18.4775] +24-11-19 20:37:17 | D | best error = [ 1.7780, 1.7780, 1.7780, 1.7780, 1.7780] +24-11-19 20:37:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:17 | D | sum error = [ 19.6190, 20.8309, 22.1215, 23.4740, 24.9049] +24-11-19 20:37:17 | D | best error = [ 1.7780, 1.7780, 1.7780, 1.7780, 1.7780] +24-11-19 20:37:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:17 | D | sum error = [ 26.4143, 28.0058, 29.6832, 31.4613, 33.3335] +24-11-19 20:37:17 | D | best error = [ 1.7780, 1.7780, 1.7780, 1.7780, 1.7780] +24-11-19 20:37:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:17 | D | sum error = [ 35.2983, 37.3682, 39.5519, 41.8486, 44.2596] +24-11-19 20:37:17 | D | best error = [ 1.7780, 1.7780, 1.7780, 1.7780, 1.7780] +24-11-19 20:37:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:17 | D | sum error = [ 46.7814, 49.4338, 52.2110, 55.1268, 58.1809] +24-11-19 20:37:17 | D | best error = [ 1.7780, 1.7780, 1.7780, 1.7780, 1.7780] +24-11-19 20:37:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:17 | D | sum error = [ 61.3791, 64.7208, 68.2260, 71.8827, 75.7031] +24-11-19 20:37:17 | D | best error = [ 1.7780, 1.7780, 1.7780, 1.7780, 1.7780] +24-11-19 20:37:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:17 | D | sum error = [ 79.6913, 83.8510, 88.1847, 92.6927, 97.3875] +24-11-19 20:37:17 | D | best error = [ 1.7780, 1.7780, 1.7780, 1.7780, 1.7780] +24-11-19 20:37:17 | D | + error = [1.7780] +24-11-19 20:37:17 | D | - Calibrating model.layers.26.mlp.up_proj.weight +24-11-19 20:37:17 | D | + w: sint8 +24-11-19 20:37:17 | D | + x: None +24-11-19 20:37:17 | D | + y: None +24-11-19 20:37:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:17 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:37:18 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:37:18 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:37:18 | D | - range ratio = [ 1.0000] +24-11-19 20:37:18 | D | sum error = [ 10.8622] +24-11-19 20:37:18 | D | best error = [ 10.8622] +24-11-19 20:37:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:19 | D | sum error = [ 10.7829, 10.7698, 10.8017, 10.9310, 11.1502] +24-11-19 20:37:19 | D | best error = [ 10.0298, 9.7113, 9.5461, 9.4502, 9.3987] +24-11-19 20:37:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:19 | D | sum error = [ 11.4088, 11.8119, 12.2582, 12.8788, 13.5506] +24-11-19 20:37:19 | D | best error = [ 9.3700, 9.3576, 9.3536, 9.3521, 9.3517] +24-11-19 20:37:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:19 | D | sum error = [ 14.2931, 15.2036, 16.1922, 17.2664, 18.4679] +24-11-19 20:37:19 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:37:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:19 | D | sum error = [ 19.7564, 21.1554, 22.6965, 24.3037, 26.0353] +24-11-19 20:37:19 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:37:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:19 | D | sum error = [ 27.8852, 29.8423, 31.9637, 34.1578, 36.6065] +24-11-19 20:37:19 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:37:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:19 | D | sum error = [ 39.0767, 41.7267, 44.5193, 47.5147, 50.6348] +24-11-19 20:37:19 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:37:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:19 | D | sum error = [ 53.9348, 57.4320, 61.1438, 65.0089, 69.0969] +24-11-19 20:37:19 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:37:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:19 | D | sum error = [ 73.4054, 77.9122, 82.6545, 87.6408, 92.8798] +24-11-19 20:37:19 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:37:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:19 | D | sum error = [ 98.3909, 104.1514, 110.2061, 116.5282, 123.1579] +24-11-19 20:37:19 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:37:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:19 | D | sum error = [ 130.1190, 137.3726, 144.9796, 152.9247, 161.2285] +24-11-19 20:37:19 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:37:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:19 | D | sum error = [ 169.9211, 178.9563, 188.4213, 198.2651, 208.5310] +24-11-19 20:37:19 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:37:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:19 | D | sum error = [ 219.2261, 230.3625, 241.9219, 253.9640, 266.4965] +24-11-19 20:37:19 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:37:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:19 | D | sum error = [ 279.4905, 292.9906, 306.9963, 321.5199, 336.5792] +24-11-19 20:37:19 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:37:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:19 | D | sum error = [ 352.1906, 368.3362, 385.0682, 402.3542, 420.2318] +24-11-19 20:37:19 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:37:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:19 | D | sum error = [ 438.6808, 457.7517, 477.4287, 497.7220, 518.6524] +24-11-19 20:37:19 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:37:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:19 | D | sum error = [ 540.1885, 562.3893, 585.2062, 608.6721, 632.7998] +24-11-19 20:37:19 | D | best error = [ 9.3515, 9.3515, 9.3515, 9.3515, 9.3515] +24-11-19 20:37:19 | D | + error = [9.3515] +24-11-19 20:37:19 | D | - Calibrating model.layers.26.mlp.gate_proj.weight +24-11-19 20:37:19 | D | + w: sint8 +24-11-19 20:37:19 | D | + x: None +24-11-19 20:37:19 | D | + y: None +24-11-19 20:37:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:19 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:37:19 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:37:19 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:37:19 | D | - range ratio = [ 1.0000] +24-11-19 20:37:19 | D | sum error = [ 11.6637] +24-11-19 20:37:19 | D | best error = [ 11.6637] +24-11-19 20:37:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:20 | D | sum error = [ 11.6071, 11.5722, 11.6087, 11.7383, 11.9191] +24-11-19 20:37:20 | D | best error = [ 10.7956, 10.4508, 10.2602, 10.1526, 10.0942] +24-11-19 20:37:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:20 | D | sum error = [ 12.2266, 12.6299, 13.1435, 13.8044, 14.5256] +24-11-19 20:37:20 | D | best error = [ 10.0660, 10.0529, 10.0469, 10.0455, 10.0451] +24-11-19 20:37:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:20 | D | sum error = [ 15.3563, 16.2917, 17.3648, 18.5520, 19.8584] +24-11-19 20:37:20 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 20:37:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:20 | D | sum error = [ 21.2619, 22.7817, 24.4261, 26.1930, 28.0691] +24-11-19 20:37:20 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 20:37:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:20 | D | sum error = [ 30.0906, 32.2480, 34.5612, 37.0173, 39.6213] +24-11-19 20:37:20 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 20:37:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:20 | D | sum error = [ 42.3639, 45.2703, 48.3766, 51.6285, 55.0966] +24-11-19 20:37:20 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 20:37:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:20 | D | sum error = [ 58.7801, 62.6464, 66.7397, 71.0775, 75.6861] +24-11-19 20:37:20 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 20:37:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:20 | D | sum error = [ 80.5189, 85.6081, 90.9945, 96.6549, 102.6081] +24-11-19 20:37:20 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 20:37:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:20 | D | sum error = [ 108.9187, 115.5094, 122.4500, 129.7469, 137.4359] +24-11-19 20:37:20 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 20:37:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:20 | D | sum error = [ 145.4661, 153.9621, 162.8654, 172.2117, 182.0130] +24-11-19 20:37:20 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 20:37:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:20 | D | sum error = [ 192.2937, 203.0945, 214.4180, 226.2767, 238.6691] +24-11-19 20:37:20 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 20:37:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:20 | D | sum error = [ 251.6532, 265.2388, 279.4055, 294.2433, 309.7510] +24-11-19 20:37:20 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 20:37:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:20 | D | sum error = [ 325.9313, 342.7885, 360.3722, 378.7132, 397.8178] +24-11-19 20:37:20 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 20:37:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:20 | D | sum error = [ 417.7040, 438.3598, 459.8045, 482.0776, 505.1621] +24-11-19 20:37:20 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 20:37:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:20 | D | sum error = [ 529.1202, 553.9241, 579.6165, 606.1938, 633.6749] +24-11-19 20:37:20 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 20:37:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:20 | D | sum error = [ 662.0314, 691.3021, 721.4740, 752.5841, 784.5898] +24-11-19 20:37:20 | D | best error = [ 10.0450, 10.0450, 10.0450, 10.0450, 10.0450] +24-11-19 20:37:20 | D | + error = [10.0450] +24-11-19 20:37:20 | D | - Calibrating model.layers.26.mlp.down_proj.weight +24-11-19 20:37:20 | D | + w: sint8 +24-11-19 20:37:20 | D | + x: None +24-11-19 20:37:20 | D | + y: None +24-11-19 20:37:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:20 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:37:20 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:37:20 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:37:20 | D | - range ratio = [ 1.0000] +24-11-19 20:37:20 | D | sum error = [ 4.1822] +24-11-19 20:37:20 | D | best error = [ 4.1822] +24-11-19 20:37:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:21 | D | sum error = [ 4.1421, 4.1120, 4.0802, 4.0878, 4.0871] +24-11-19 20:37:21 | D | best error = [ 4.0139, 3.9315, 3.8716, 3.8346, 3.8063] +24-11-19 20:37:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:21 | D | sum error = [ 4.0923, 4.1322, 4.1914, 4.2560, 4.3429] +24-11-19 20:37:21 | D | best error = [ 3.7835, 3.7680, 3.7588, 3.7511, 3.7445] +24-11-19 20:37:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:21 | D | sum error = [ 4.4598, 4.5981, 4.7634, 4.9671, 5.1986] +24-11-19 20:37:21 | D | best error = [ 3.7412, 3.7386, 3.7372, 3.7364, 3.7357] +24-11-19 20:37:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:21 | D | sum error = [ 5.4591, 5.7536, 6.0770, 6.4397, 6.8432] +24-11-19 20:37:21 | D | best error = [ 3.7355, 3.7352, 3.7350, 3.7350, 3.7349] +24-11-19 20:37:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:21 | D | sum error = [ 7.2905, 7.7650, 8.2804, 8.8485, 9.4562] +24-11-19 20:37:21 | D | best error = [ 3.7349, 3.7349, 3.7349, 3.7349, 3.7349] +24-11-19 20:37:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:21 | D | sum error = [ 10.1136, 10.8094, 11.5656, 12.3779, 13.2402] +24-11-19 20:37:21 | D | best error = [ 3.7349, 3.7349, 3.7349, 3.7349, 3.7349] +24-11-19 20:37:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:21 | D | sum error = [ 14.1589, 15.1377, 16.1696, 17.2825, 18.4601] +24-11-19 20:37:21 | D | best error = [ 3.7349, 3.7349, 3.7349, 3.7349, 3.7349] +24-11-19 20:37:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:21 | D | sum error = [ 19.7076, 21.0106, 22.4216, 23.8985, 25.4660] +24-11-19 20:37:21 | D | best error = [ 3.7349, 3.7349, 3.7349, 3.7349, 3.7349] +24-11-19 20:37:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:21 | D | sum error = [ 27.1228, 28.8667, 30.7147, 32.6671, 34.7247] +24-11-19 20:37:21 | D | best error = [ 3.7349, 3.7349, 3.7349, 3.7349, 3.7349] +24-11-19 20:37:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:21 | D | sum error = [ 36.8909, 39.1670, 41.5667, 44.0852, 46.7381] +24-11-19 20:37:21 | D | best error = [ 3.7349, 3.7349, 3.7349, 3.7349, 3.7349] +24-11-19 20:37:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:21 | D | sum error = [ 49.5200, 52.4411, 55.5114, 58.7226, 62.0886] +24-11-19 20:37:21 | D | best error = [ 3.7349, 3.7349, 3.7349, 3.7349, 3.7349] +24-11-19 20:37:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:21 | D | sum error = [ 65.6163, 69.3050, 73.1723, 77.2098, 81.4390] +24-11-19 20:37:21 | D | best error = [ 3.7349, 3.7349, 3.7349, 3.7349, 3.7349] +24-11-19 20:37:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:21 | D | sum error = [ 85.8477, 90.4423, 95.2407, 100.2387, 105.4474] +24-11-19 20:37:21 | D | best error = [ 3.7349, 3.7349, 3.7349, 3.7349, 3.7349] +24-11-19 20:37:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:21 | D | sum error = [ 110.8687, 116.5116, 122.3793, 128.4902, 134.8077] +24-11-19 20:37:21 | D | best error = [ 3.7349, 3.7349, 3.7349, 3.7349, 3.7349] +24-11-19 20:37:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:21 | D | sum error = [ 141.3819, 148.1964, 155.2671, 162.5900, 170.1656] +24-11-19 20:37:21 | D | best error = [ 3.7349, 3.7349, 3.7349, 3.7349, 3.7349] +24-11-19 20:37:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:21 | D | sum error = [ 178.0076, 186.1096, 194.4817, 203.1322, 212.0624] +24-11-19 20:37:21 | D | best error = [ 3.7349, 3.7349, 3.7349, 3.7349, 3.7349] +24-11-19 20:37:21 | D | + error = [3.7349] +24-11-19 20:37:21 | D | - Quantizing model.layers.26.self_attn.q_proj.weight +24-11-19 20:37:22 | D | - Quantizing model.layers.26.self_attn.k_proj.weight +24-11-19 20:37:23 | D | - Quantizing model.layers.26.self_attn.v_proj.weight +24-11-19 20:37:24 | D | - Quantizing model.layers.26.self_attn.o_proj.weight +24-11-19 20:37:24 | D | - Quantizing model.layers.26.mlp.up_proj.weight +24-11-19 20:37:25 | D | - Quantizing model.layers.26.mlp.gate_proj.weight +24-11-19 20:37:26 | D | - Quantizing model.layers.26.mlp.down_proj.weight +24-11-19 20:37:34 | D | - Quantizing layer model.layers.27 +24-11-19 20:37:34 | D | - Calibrating model.layers.27.self_attn.q_proj.weight +24-11-19 20:37:34 | D | + w: sint8 +24-11-19 20:37:34 | D | + x: None +24-11-19 20:37:34 | D | + y: None +24-11-19 20:37:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:37:34 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:37:34 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:37:34 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:37:35 | D | - range ratio = [ 1.0000] +24-11-19 20:37:35 | D | sum error = [ 16.8352] +24-11-19 20:37:35 | D | best error = [ 16.8352] +24-11-19 20:37:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:47 | D | sum error = [ 16.9372, 16.5315, 16.9096, 16.9346, 17.2794] +24-11-19 20:37:47 | D | best error = [ 16.8352, 16.5315, 16.5315, 16.5315, 16.5315] +24-11-19 20:37:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:47 | D | sum error = [ 17.8178, 18.3844, 19.6120, 20.1931, 21.6013] +24-11-19 20:37:47 | D | best error = [ 16.5315, 16.5315, 16.5315, 16.5315, 16.5315] +24-11-19 20:37:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:47 | D | sum error = [ 22.5368, 25.1880, 26.1491, 28.4278, 30.4463] +24-11-19 20:37:47 | D | best error = [ 16.5315, 16.5315, 16.5315, 16.5315, 16.5315] +24-11-19 20:37:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:47 | D | sum error = [ 32.2668, 34.9072, 37.5112, 40.3996, 43.7680] +24-11-19 20:37:47 | D | best error = [ 16.5315, 16.5315, 16.5315, 16.5315, 16.5315] +24-11-19 20:37:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:47 | D | sum error = [ 47.4257, 51.4218, 56.1582, 59.5312, 63.3486] +24-11-19 20:37:47 | D | best error = [ 16.5315, 16.5315, 16.5315, 16.5315, 16.5315] +24-11-19 20:37:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:47 | D | sum error = [ 68.7524, 74.1724, 79.7319, 85.6778, 91.7659] +24-11-19 20:37:47 | D | best error = [ 16.5315, 16.5315, 16.5315, 16.5315, 16.5315] +24-11-19 20:37:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:47 | D | sum error = [ 98.2390, 105.8276, 113.0695, 121.5320, 130.1520] +24-11-19 20:37:47 | D | best error = [ 16.5315, 16.5315, 16.5315, 16.5315, 16.5315] +24-11-19 20:37:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:47 | D | sum error = [ 140.0326, 149.7848, 160.7059, 172.6574, 185.5939] +24-11-19 20:37:47 | D | best error = [ 16.5315, 16.5315, 16.5315, 16.5315, 16.5315] +24-11-19 20:37:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:47 | D | sum error = [ 199.6230, 214.0177, 230.3098, 247.5801, 266.6064] +24-11-19 20:37:47 | D | best error = [ 16.5315, 16.5315, 16.5315, 16.5315, 16.5315] +24-11-19 20:37:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:47 | D | sum error = [ 286.3757, 307.6690, 331.0945, 354.9713, 381.1657] +24-11-19 20:37:47 | D | best error = [ 16.5315, 16.5315, 16.5315, 16.5315, 16.5315] +24-11-19 20:37:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:47 | D | sum error = [ 409.5941, 440.0490, 472.9174, 509.0253, 547.4915] +24-11-19 20:37:47 | D | best error = [ 16.5315, 16.5315, 16.5315, 16.5315, 16.5315] +24-11-19 20:37:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:47 | D | sum error = [ 589.7578, 634.9588, 685.0495, 737.5802, 795.5112] +24-11-19 20:37:47 | D | best error = [ 16.5315, 16.5315, 16.5315, 16.5315, 16.5315] +24-11-19 20:37:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:47 | D | sum error = [ 858.9877, 927.0860, 1001.6248, 1083.6078, 1173.0448] +24-11-19 20:37:47 | D | best error = [ 16.5315, 16.5315, 16.5315, 16.5315, 16.5315] +24-11-19 20:37:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:47 | D | sum error = [ 1271.4536, 1379.4642, 1498.5819, 1629.7335, 1773.0687] +24-11-19 20:37:47 | D | best error = [ 16.5315, 16.5315, 16.5315, 16.5315, 16.5315] +24-11-19 20:37:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:47 | D | sum error = [ 1930.9648, 2105.6494, 2296.9175, 2508.8907, 2741.2610] +24-11-19 20:37:47 | D | best error = [ 16.5315, 16.5315, 16.5315, 16.5315, 16.5315] +24-11-19 20:37:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:47 | D | sum error = [ 2999.5435, 3283.9555, 3596.8508, 3941.5170, 4313.1096] +24-11-19 20:37:47 | D | best error = [ 16.5315, 16.5315, 16.5315, 16.5315, 16.5315] +24-11-19 20:37:47 | D | + error = [16.5315] +24-11-19 20:37:47 | D | - Calibrating model.layers.27.self_attn.k_proj.weight +24-11-19 20:37:47 | D | + w: sint8 +24-11-19 20:37:47 | D | + x: None +24-11-19 20:37:47 | D | + y: None +24-11-19 20:37:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:37:47 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:37:47 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:37:47 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:37:48 | D | - range ratio = [ 1.0000] +24-11-19 20:37:48 | D | sum error = [ 20.0287] +24-11-19 20:37:48 | D | best error = [ 20.0287] +24-11-19 20:38:00 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:00 | D | sum error = [ 19.0406, 19.5089, 19.7507, 20.1274, 20.0650] +24-11-19 20:38:00 | D | best error = [ 19.0406, 19.0406, 19.0406, 19.0406, 19.0406] +24-11-19 20:38:00 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:00 | D | sum error = [ 21.3809, 21.7017, 22.3121, 22.7162, 25.0766] +24-11-19 20:38:00 | D | best error = [ 19.0406, 19.0406, 19.0406, 19.0406, 19.0406] +24-11-19 20:38:00 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:00 | D | sum error = [ 26.8921, 27.0083, 29.5781, 32.6312, 34.2483] +24-11-19 20:38:00 | D | best error = [ 19.0406, 19.0406, 19.0406, 19.0406, 19.0406] +24-11-19 20:38:00 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:00 | D | sum error = [ 36.5577, 38.4349, 41.8435, 44.9898, 49.8216] +24-11-19 20:38:00 | D | best error = [ 19.0406, 19.0406, 19.0406, 19.0406, 19.0406] +24-11-19 20:38:00 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:00 | D | sum error = [ 52.4216, 58.2008, 62.7610, 68.6995, 74.1153] +24-11-19 20:38:00 | D | best error = [ 19.0406, 19.0406, 19.0406, 19.0406, 19.0406] +24-11-19 20:38:00 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:00 | D | sum error = [ 81.3135, 86.8294, 94.1410, 102.5751, 112.6531] +24-11-19 20:38:00 | D | best error = [ 19.0406, 19.0406, 19.0406, 19.0406, 19.0406] +24-11-19 20:38:00 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:00 | D | sum error = [ 120.7284, 131.7084, 141.0910, 153.1501, 164.4205] +24-11-19 20:38:00 | D | best error = [ 19.0406, 19.0406, 19.0406, 19.0406, 19.0406] +24-11-19 20:38:00 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:00 | D | sum error = [ 179.4399, 194.0208, 205.9056, 220.2425, 236.7119] +24-11-19 20:38:00 | D | best error = [ 19.0406, 19.0406, 19.0406, 19.0406, 19.0406] +24-11-19 20:38:00 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:00 | D | sum error = [ 254.4828, 273.6140, 290.6199, 311.4146, 333.9635] +24-11-19 20:38:00 | D | best error = [ 19.0406, 19.0406, 19.0406, 19.0406, 19.0406] +24-11-19 20:38:00 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:00 | D | sum error = [ 356.7808, 380.2542, 404.0246, 431.0008, 455.7434] +24-11-19 20:38:00 | D | best error = [ 19.0406, 19.0406, 19.0406, 19.0406, 19.0406] +24-11-19 20:38:00 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:00 | D | sum error = [ 486.5482, 516.3114, 548.6817, 585.9579, 624.9424] +24-11-19 20:38:00 | D | best error = [ 19.0406, 19.0406, 19.0406, 19.0406, 19.0406] +24-11-19 20:38:00 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:00 | D | sum error = [ 667.3194, 713.8092, 763.4154, 818.2394, 880.4869] +24-11-19 20:38:00 | D | best error = [ 19.0406, 19.0406, 19.0406, 19.0406, 19.0406] +24-11-19 20:38:00 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:00 | D | sum error = [ 944.3944, 1012.6900, 1087.0090, 1169.5029, 1259.0731] +24-11-19 20:38:00 | D | best error = [ 19.0406, 19.0406, 19.0406, 19.0406, 19.0406] +24-11-19 20:38:00 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:00 | D | sum error = [ 1357.1332, 1462.1245, 1576.3031, 1703.2303, 1841.4449] +24-11-19 20:38:00 | D | best error = [ 19.0406, 19.0406, 19.0406, 19.0406, 19.0406] +24-11-19 20:38:00 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:00 | D | sum error = [ 1995.3593, 2165.3467, 2352.6089, 2562.7154, 2792.9889] +24-11-19 20:38:00 | D | best error = [ 19.0406, 19.0406, 19.0406, 19.0406, 19.0406] +24-11-19 20:38:00 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:00 | D | sum error = [ 3049.5008, 3332.5534, 3643.5889, 3982.4815, 4348.2070] +24-11-19 20:38:00 | D | best error = [ 19.0406, 19.0406, 19.0406, 19.0406, 19.0406] +24-11-19 20:38:00 | D | + error = [19.0406] +24-11-19 20:38:00 | D | - Calibrating model.layers.27.self_attn.v_proj.weight +24-11-19 20:38:00 | D | + w: sint8 +24-11-19 20:38:00 | D | + x: None +24-11-19 20:38:00 | D | + y: None +24-11-19 20:38:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:00 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:38:00 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:38:00 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:38:00 | D | - range ratio = [ 1.0000] +24-11-19 20:38:00 | D | sum error = [ 8.7446] +24-11-19 20:38:00 | D | best error = [ 8.7446] +24-11-19 20:38:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:01 | D | sum error = [ 8.6579, 8.6659, 8.6783, 8.8059, 8.9231] +24-11-19 20:38:01 | D | best error = [ 8.0867, 7.8396, 7.6999, 7.6217, 7.5783] +24-11-19 20:38:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:01 | D | sum error = [ 9.1532, 9.5016, 9.8701, 10.3347, 10.8673] +24-11-19 20:38:01 | D | best error = [ 7.5574, 7.5479, 7.5446, 7.5437, 7.5434] +24-11-19 20:38:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:01 | D | sum error = [ 11.5039, 12.1960, 13.0162, 13.8870, 14.8562] +24-11-19 20:38:01 | D | best error = [ 7.5434, 7.5434, 7.5434, 7.5434, 7.5434] +24-11-19 20:38:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:01 | D | sum error = [ 15.8717, 17.0340, 18.2333, 19.5205, 20.9624] +24-11-19 20:38:01 | D | best error = [ 7.5434, 7.5434, 7.5434, 7.5434, 7.5434] +24-11-19 20:38:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:01 | D | sum error = [ 22.4892, 24.0738, 25.7139, 27.5123, 29.4369] +24-11-19 20:38:01 | D | best error = [ 7.5434, 7.5434, 7.5434, 7.5434, 7.5434] +24-11-19 20:38:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:01 | D | sum error = [ 31.4860, 33.5723, 35.8793, 38.2558, 40.7687] +24-11-19 20:38:01 | D | best error = [ 7.5434, 7.5434, 7.5434, 7.5434, 7.5434] +24-11-19 20:38:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:01 | D | sum error = [ 43.4490, 46.2162, 49.1460, 52.2402, 55.4842] +24-11-19 20:38:01 | D | best error = [ 7.5434, 7.5434, 7.5434, 7.5434, 7.5434] +24-11-19 20:38:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:01 | D | sum error = [ 58.9229, 62.5107, 66.3164, 70.3133, 74.4915] +24-11-19 20:38:01 | D | best error = [ 7.5434, 7.5434, 7.5434, 7.5434, 7.5434] +24-11-19 20:38:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:01 | D | sum error = [ 78.9189, 83.4973, 88.3045, 93.3386, 98.6261] +24-11-19 20:38:01 | D | best error = [ 7.5434, 7.5434, 7.5434, 7.5434, 7.5434] +24-11-19 20:38:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:01 | D | sum error = [ 104.1350, 109.8947, 115.9310, 122.2568, 128.8207] +24-11-19 20:38:01 | D | best error = [ 7.5434, 7.5434, 7.5434, 7.5434, 7.5434] +24-11-19 20:38:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:01 | D | sum error = [ 135.6477, 142.7543, 150.1510, 157.8390, 165.8255] +24-11-19 20:38:01 | D | best error = [ 7.5434, 7.5434, 7.5434, 7.5434, 7.5434] +24-11-19 20:38:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:01 | D | sum error = [ 174.1018, 182.7247, 191.6912, 200.9851, 210.6423] +24-11-19 20:38:01 | D | best error = [ 7.5434, 7.5434, 7.5434, 7.5434, 7.5434] +24-11-19 20:38:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:01 | D | sum error = [ 220.6464, 231.0149, 241.7362, 252.8523, 264.3557] +24-11-19 20:38:01 | D | best error = [ 7.5434, 7.5434, 7.5434, 7.5434, 7.5434] +24-11-19 20:38:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:01 | D | sum error = [ 276.2469, 288.5527, 301.2402, 314.3592, 327.8700] +24-11-19 20:38:01 | D | best error = [ 7.5434, 7.5434, 7.5434, 7.5434, 7.5434] +24-11-19 20:38:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:01 | D | sum error = [ 341.7890, 356.1591, 370.9739, 386.2273, 401.9064] +24-11-19 20:38:01 | D | best error = [ 7.5434, 7.5434, 7.5434, 7.5434, 7.5434] +24-11-19 20:38:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:01 | D | sum error = [ 418.0726, 434.6764, 451.7522, 469.3295, 487.4090] +24-11-19 20:38:01 | D | best error = [ 7.5434, 7.5434, 7.5434, 7.5434, 7.5434] +24-11-19 20:38:01 | D | + error = [7.5434] +24-11-19 20:38:01 | D | - Calibrating model.layers.27.self_attn.o_proj.weight +24-11-19 20:38:01 | D | + w: sint8 +24-11-19 20:38:01 | D | + x: None +24-11-19 20:38:01 | D | + y: None +24-11-19 20:38:01 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:01 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:38:01 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:38:01 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:38:01 | D | - range ratio = [ 1.0000] +24-11-19 20:38:01 | D | sum error = [ 2.1056] +24-11-19 20:38:01 | D | best error = [ 2.1056] +24-11-19 20:38:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:01 | D | sum error = [ 2.0877, 2.0797, 2.0814, 2.0927, 2.1133] +24-11-19 20:38:01 | D | best error = [ 1.9902, 1.9377, 1.9066, 1.8863, 1.8731] +24-11-19 20:38:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:01 | D | sum error = [ 2.1475, 2.1906, 2.2634, 2.3378, 2.4320] +24-11-19 20:38:01 | D | best error = [ 1.8649, 1.8585, 1.8546, 1.8522, 1.8509] +24-11-19 20:38:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:01 | D | sum error = [ 2.5408, 2.6761, 2.8157, 2.9758, 3.1547] +24-11-19 20:38:01 | D | best error = [ 1.8500, 1.8496, 1.8492, 1.8491, 1.8488] +24-11-19 20:38:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:01 | D | sum error = [ 3.3482, 3.5671, 3.8070, 4.0558, 4.3284] +24-11-19 20:38:01 | D | best error = [ 1.8487, 1.8487, 1.8486, 1.8486, 1.8486] +24-11-19 20:38:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:01 | D | sum error = [ 4.6238, 4.9394, 5.2672, 5.6303, 6.0052] +24-11-19 20:38:01 | D | best error = [ 1.8486, 1.8486, 1.8486, 1.8486, 1.8486] +24-11-19 20:38:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:01 | D | sum error = [ 6.4136, 6.8406, 7.2919, 7.7717, 8.2908] +24-11-19 20:38:01 | D | best error = [ 1.8486, 1.8486, 1.8486, 1.8486, 1.8486] +24-11-19 20:38:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:01 | D | sum error = [ 8.8266, 9.4021, 10.0019, 10.6444, 11.3235] +24-11-19 20:38:01 | D | best error = [ 1.8486, 1.8486, 1.8486, 1.8486, 1.8486] +24-11-19 20:38:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:01 | D | sum error = [ 12.0334, 12.7904, 13.5800, 14.4151, 15.2979] +24-11-19 20:38:01 | D | best error = [ 1.8486, 1.8486, 1.8486, 1.8486, 1.8486] +24-11-19 20:38:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:01 | D | sum error = [ 16.2287, 17.2043, 18.2348, 19.3168, 20.4599] +24-11-19 20:38:01 | D | best error = [ 1.8486, 1.8486, 1.8486, 1.8486, 1.8486] +24-11-19 20:38:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:01 | D | sum error = [ 21.6542, 22.9084, 24.2308, 25.6191, 27.0822] +24-11-19 20:38:01 | D | best error = [ 1.8486, 1.8486, 1.8486, 1.8486, 1.8486] +24-11-19 20:38:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:01 | D | sum error = [ 28.6134, 30.2163, 31.9020, 33.6612, 35.5058] +24-11-19 20:38:01 | D | best error = [ 1.8486, 1.8486, 1.8486, 1.8486, 1.8486] +24-11-19 20:38:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:01 | D | sum error = [ 37.4380, 39.4586, 41.5733, 43.7841, 46.0980] +24-11-19 20:38:01 | D | best error = [ 1.8486, 1.8486, 1.8486, 1.8486, 1.8486] +24-11-19 20:38:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:01 | D | sum error = [ 48.5082, 51.0286, 53.6592, 56.4023, 59.2566] +24-11-19 20:38:01 | D | best error = [ 1.8486, 1.8486, 1.8486, 1.8486, 1.8486] +24-11-19 20:38:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:01 | D | sum error = [ 62.2337, 65.3346, 68.5595, 71.9258, 75.4090] +24-11-19 20:38:01 | D | best error = [ 1.8486, 1.8486, 1.8486, 1.8486, 1.8486] +24-11-19 20:38:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:01 | D | sum error = [ 79.0348, 82.7998, 86.7041, 90.7582, 94.9575] +24-11-19 20:38:01 | D | best error = [ 1.8486, 1.8486, 1.8486, 1.8486, 1.8486] +24-11-19 20:38:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:01 | D | sum error = [ 99.3016, 103.7967, 108.4413, 113.2453, 118.2018] +24-11-19 20:38:01 | D | best error = [ 1.8486, 1.8486, 1.8486, 1.8486, 1.8486] +24-11-19 20:38:01 | D | + error = [1.8486] +24-11-19 20:38:02 | D | - Calibrating model.layers.27.mlp.up_proj.weight +24-11-19 20:38:02 | D | + w: sint8 +24-11-19 20:38:02 | D | + x: None +24-11-19 20:38:02 | D | + y: None +24-11-19 20:38:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:02 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:38:02 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:38:02 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:38:02 | D | - range ratio = [ 1.0000] +24-11-19 20:38:02 | D | sum error = [ 11.2416] +24-11-19 20:38:02 | D | best error = [ 11.2416] +24-11-19 20:38:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:03 | D | sum error = [ 11.1654, 11.1359, 11.1450, 11.2843, 11.5235] +24-11-19 20:38:03 | D | best error = [ 10.3592, 10.0242, 9.8465, 9.7476, 9.6964] +24-11-19 20:38:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:03 | D | sum error = [ 11.7884, 12.1965, 12.7037, 13.3109, 13.9740] +24-11-19 20:38:03 | D | best error = [ 9.6671, 9.6548, 9.6502, 9.6488, 9.6482] +24-11-19 20:38:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:03 | D | sum error = [ 14.8393, 15.7341, 16.7935, 17.8975, 19.1484] +24-11-19 20:38:03 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:38:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:03 | D | sum error = [ 20.4979, 21.9689, 23.5250, 25.1947, 27.0143] +24-11-19 20:38:03 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:38:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:03 | D | sum error = [ 28.9432, 30.9788, 33.1775, 35.5042, 37.9648] +24-11-19 20:38:03 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:38:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:03 | D | sum error = [ 40.5500, 43.3586, 46.2456, 49.3195, 52.6023] +24-11-19 20:38:03 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:38:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:03 | D | sum error = [ 56.0309, 59.6607, 63.4965, 67.5425, 71.7763] +24-11-19 20:38:03 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:38:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:03 | D | sum error = [ 76.2756, 80.9827, 85.9449, 91.1870, 96.6709] +24-11-19 20:38:03 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:38:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:03 | D | sum error = [ 102.4303, 108.4664, 114.8241, 121.4552, 128.4151] +24-11-19 20:38:03 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:38:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:03 | D | sum error = [ 135.6965, 143.3267, 151.2949, 159.6274, 168.3646] +24-11-19 20:38:03 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:38:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:03 | D | sum error = [ 177.4639, 186.9878, 196.9340, 207.3028, 218.1222] +24-11-19 20:38:03 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:38:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:03 | D | sum error = [ 229.4136, 241.1601, 253.3856, 266.1075, 279.3927] +24-11-19 20:38:03 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:38:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:03 | D | sum error = [ 293.1856, 307.4887, 322.3751, 337.8101, 353.8462] +24-11-19 20:38:03 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:38:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:03 | D | sum error = [ 370.4899, 387.7429, 405.6194, 424.1323, 443.2528] +24-11-19 20:38:03 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:38:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:03 | D | sum error = [ 463.0575, 483.5174, 504.6268, 526.4302, 548.9175] +24-11-19 20:38:03 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:38:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:03 | D | sum error = [ 572.0736, 595.9685, 620.5614, 645.8721, 671.9233] +24-11-19 20:38:03 | D | best error = [ 9.6481, 9.6481, 9.6481, 9.6481, 9.6481] +24-11-19 20:38:03 | D | + error = [9.6481] +24-11-19 20:38:03 | D | - Calibrating model.layers.27.mlp.gate_proj.weight +24-11-19 20:38:03 | D | + w: sint8 +24-11-19 20:38:03 | D | + x: None +24-11-19 20:38:03 | D | + y: None +24-11-19 20:38:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:03 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:38:03 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:38:03 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:38:03 | D | - range ratio = [ 1.0000] +24-11-19 20:38:03 | D | sum error = [ 12.0688] +24-11-19 20:38:03 | D | best error = [ 12.0688] +24-11-19 20:38:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:04 | D | sum error = [ 11.9304, 11.9411, 11.9769, 12.1409, 12.3583] +24-11-19 20:38:04 | D | best error = [ 11.1053, 10.7478, 10.5554, 10.4535, 10.3969] +24-11-19 20:38:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:04 | D | sum error = [ 12.6528, 13.0551, 13.6235, 14.2596, 14.9617] +24-11-19 20:38:04 | D | best error = [ 10.3712, 10.3595, 10.3546, 10.3528, 10.3525] +24-11-19 20:38:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:04 | D | sum error = [ 15.8355, 16.8168, 17.9052, 19.1345, 20.4406] +24-11-19 20:38:04 | D | best error = [ 10.3524, 10.3524, 10.3524, 10.3524, 10.3524] +24-11-19 20:38:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:04 | D | sum error = [ 21.8926, 23.4590, 25.1338, 26.9729, 28.8843] +24-11-19 20:38:04 | D | best error = [ 10.3524, 10.3524, 10.3524, 10.3524, 10.3524] +24-11-19 20:38:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:04 | D | sum error = [ 30.9766, 33.2320, 35.5692, 38.0760, 40.7257] +24-11-19 20:38:04 | D | best error = [ 10.3524, 10.3524, 10.3524, 10.3524, 10.3524] +24-11-19 20:38:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:04 | D | sum error = [ 43.5922, 46.6035, 49.7453, 53.1151, 56.7201] +24-11-19 20:38:04 | D | best error = [ 10.3524, 10.3524, 10.3524, 10.3524, 10.3524] +24-11-19 20:38:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:04 | D | sum error = [ 60.4956, 64.4563, 68.6613, 73.0822, 77.7716] +24-11-19 20:38:04 | D | best error = [ 10.3524, 10.3524, 10.3524, 10.3524, 10.3524] +24-11-19 20:38:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:04 | D | sum error = [ 82.7493, 88.0164, 93.5066, 99.3638, 105.5205] +24-11-19 20:38:04 | D | best error = [ 10.3524, 10.3524, 10.3524, 10.3524, 10.3524] +24-11-19 20:38:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:04 | D | sum error = [ 111.9762, 118.7970, 125.9756, 133.5244, 141.4697] +24-11-19 20:38:04 | D | best error = [ 10.3524, 10.3524, 10.3524, 10.3524, 10.3524] +24-11-19 20:38:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:04 | D | sum error = [ 149.8225, 158.5526, 167.7755, 177.4314, 187.5831] +24-11-19 20:38:04 | D | best error = [ 10.3524, 10.3524, 10.3524, 10.3524, 10.3524] +24-11-19 20:38:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:04 | D | sum error = [ 198.2415, 209.4164, 221.1220, 233.3884, 246.2959] +24-11-19 20:38:04 | D | best error = [ 10.3524, 10.3524, 10.3524, 10.3524, 10.3524] +24-11-19 20:38:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:04 | D | sum error = [ 259.7911, 273.8851, 288.6477, 304.1246, 320.2432] +24-11-19 20:38:04 | D | best error = [ 10.3524, 10.3524, 10.3524, 10.3524, 10.3524] +24-11-19 20:38:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:04 | D | sum error = [ 337.1496, 354.7671, 373.1186, 392.2482, 412.2175] +24-11-19 20:38:04 | D | best error = [ 10.3524, 10.3524, 10.3524, 10.3524, 10.3524] +24-11-19 20:38:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:04 | D | sum error = [ 433.0139, 454.6276, 477.1514, 500.5283, 524.7754] +24-11-19 20:38:04 | D | best error = [ 10.3524, 10.3524, 10.3524, 10.3524, 10.3524] +24-11-19 20:38:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:04 | D | sum error = [ 549.9638, 576.0966, 603.1703, 631.2660, 660.3292] +24-11-19 20:38:04 | D | best error = [ 10.3524, 10.3524, 10.3524, 10.3524, 10.3524] +24-11-19 20:38:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:04 | D | sum error = [ 690.3725, 721.3693, 753.3291, 786.2897, 820.2715] +24-11-19 20:38:04 | D | best error = [ 10.3524, 10.3524, 10.3524, 10.3524, 10.3524] +24-11-19 20:38:04 | D | + error = [10.3524] +24-11-19 20:38:04 | D | - Calibrating model.layers.27.mlp.down_proj.weight +24-11-19 20:38:04 | D | + w: sint8 +24-11-19 20:38:04 | D | + x: None +24-11-19 20:38:04 | D | + y: None +24-11-19 20:38:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:04 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:38:04 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:38:04 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:38:04 | D | - range ratio = [ 1.0000] +24-11-19 20:38:04 | D | sum error = [ 4.5002] +24-11-19 20:38:04 | D | best error = [ 4.5002] +24-11-19 20:38:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:05 | D | sum error = [ 4.4560, 4.4263, 4.4098, 4.3946, 4.3926] +24-11-19 20:38:05 | D | best error = [ 4.3071, 4.2167, 4.1580, 4.1141, 4.0836] +24-11-19 20:38:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:05 | D | sum error = [ 4.4067, 4.4389, 4.4814, 4.5612, 4.6529] +24-11-19 20:38:05 | D | best error = [ 4.0591, 4.0417, 4.0264, 4.0168, 4.0104] +24-11-19 20:38:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:05 | D | sum error = [ 4.7681, 4.8990, 5.0862, 5.2859, 5.5160] +24-11-19 20:38:05 | D | best error = [ 4.0058, 4.0026, 4.0012, 3.9997, 3.9990] +24-11-19 20:38:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:05 | D | sum error = [ 5.7897, 6.0881, 6.4209, 6.8010, 7.2025] +24-11-19 20:38:05 | D | best error = [ 3.9986, 3.9983, 3.9981, 3.9979, 3.9979] +24-11-19 20:38:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:05 | D | sum error = [ 7.6524, 8.1408, 8.6882, 9.2665, 9.8915] +24-11-19 20:38:05 | D | best error = [ 3.9979, 3.9979, 3.9979, 3.9979, 3.9979] +24-11-19 20:38:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:05 | D | sum error = [ 10.5803, 11.2969, 12.0744, 12.9166, 13.8003] +24-11-19 20:38:05 | D | best error = [ 3.9979, 3.9979, 3.9979, 3.9979, 3.9979] +24-11-19 20:38:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:05 | D | sum error = [ 14.7531, 15.7728, 16.8504, 18.0011, 19.2157] +24-11-19 20:38:05 | D | best error = [ 3.9979, 3.9979, 3.9979, 3.9979, 3.9979] +24-11-19 20:38:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:05 | D | sum error = [ 20.5172, 21.8876, 23.3549, 24.8821, 26.5214] +24-11-19 20:38:05 | D | best error = [ 3.9979, 3.9979, 3.9979, 3.9979, 3.9979] +24-11-19 20:38:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:05 | D | sum error = [ 28.2452, 30.0631, 31.9937, 34.0177, 36.1629] +24-11-19 20:38:05 | D | best error = [ 3.9979, 3.9979, 3.9979, 3.9979, 3.9979] +24-11-19 20:38:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:05 | D | sum error = [ 38.4266, 40.7973, 43.3066, 45.9418, 48.7168] +24-11-19 20:38:05 | D | best error = [ 3.9979, 3.9979, 3.9979, 3.9979, 3.9979] +24-11-19 20:38:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:05 | D | sum error = [ 51.6310, 54.6839, 57.8955, 61.2685, 64.7930] +24-11-19 20:38:05 | D | best error = [ 3.9979, 3.9979, 3.9979, 3.9979, 3.9979] +24-11-19 20:38:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:05 | D | sum error = [ 68.4938, 72.3739, 76.4312, 80.6723, 85.1089] +24-11-19 20:38:05 | D | best error = [ 3.9979, 3.9979, 3.9979, 3.9979, 3.9979] +24-11-19 20:38:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:05 | D | sum error = [ 89.7544, 94.5948, 99.6496, 104.9158, 110.4067] +24-11-19 20:38:05 | D | best error = [ 3.9979, 3.9979, 3.9979, 3.9979, 3.9979] +24-11-19 20:38:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:05 | D | sum error = [ 116.1215, 122.0782, 128.2771, 134.7255, 141.4017] +24-11-19 20:38:05 | D | best error = [ 3.9979, 3.9979, 3.9979, 3.9979, 3.9979] +24-11-19 20:38:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:05 | D | sum error = [ 148.3436, 155.5431, 163.0109, 170.7498, 178.7638] +24-11-19 20:38:05 | D | best error = [ 3.9979, 3.9979, 3.9979, 3.9979, 3.9979] +24-11-19 20:38:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:05 | D | sum error = [ 187.0542, 195.6338, 204.4937, 213.6541, 223.1072] +24-11-19 20:38:05 | D | best error = [ 3.9979, 3.9979, 3.9979, 3.9979, 3.9979] +24-11-19 20:38:05 | D | + error = [3.9979] +24-11-19 20:38:05 | D | - Quantizing model.layers.27.self_attn.q_proj.weight +24-11-19 20:38:06 | D | - Quantizing model.layers.27.self_attn.k_proj.weight +24-11-19 20:38:07 | D | - Quantizing model.layers.27.self_attn.v_proj.weight +24-11-19 20:38:08 | D | - Quantizing model.layers.27.self_attn.o_proj.weight +24-11-19 20:38:09 | D | - Quantizing model.layers.27.mlp.up_proj.weight +24-11-19 20:38:10 | D | - Quantizing model.layers.27.mlp.gate_proj.weight +24-11-19 20:38:10 | D | - Quantizing model.layers.27.mlp.down_proj.weight +24-11-19 20:38:18 | D | - Quantizing layer model.layers.28 +24-11-19 20:38:18 | D | - Calibrating model.layers.28.self_attn.q_proj.weight +24-11-19 20:38:18 | D | + w: sint8 +24-11-19 20:38:18 | D | + x: None +24-11-19 20:38:18 | D | + y: None +24-11-19 20:38:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:38:18 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:38:18 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:38:18 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:38:18 | D | - range ratio = [ 1.0000] +24-11-19 20:38:18 | D | sum error = [ 18.8695] +24-11-19 20:38:18 | D | best error = [ 18.8695] +24-11-19 20:38:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:31 | D | sum error = [ 18.8422, 18.7897, 18.8394, 18.9064, 19.3220] +24-11-19 20:38:31 | D | best error = [ 18.8422, 18.7897, 18.7897, 18.7897, 18.7897] +24-11-19 20:38:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:31 | D | sum error = [ 20.2492, 20.5475, 22.1514, 22.6627, 24.3493] +24-11-19 20:38:31 | D | best error = [ 18.7897, 18.7897, 18.7897, 18.7897, 18.7897] +24-11-19 20:38:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:31 | D | sum error = [ 25.5174, 26.4337, 28.6373, 30.1413, 32.8629] +24-11-19 20:38:31 | D | best error = [ 18.7897, 18.7897, 18.7897, 18.7897, 18.7897] +24-11-19 20:38:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:31 | D | sum error = [ 34.7079, 37.9195, 41.0372, 43.3863, 46.9380] +24-11-19 20:38:31 | D | best error = [ 18.7897, 18.7897, 18.7897, 18.7897, 18.7897] +24-11-19 20:38:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:31 | D | sum error = [ 50.4597, 54.7136, 59.1046, 63.6442, 67.6229] +24-11-19 20:38:31 | D | best error = [ 18.7897, 18.7897, 18.7897, 18.7897, 18.7897] +24-11-19 20:38:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:31 | D | sum error = [ 73.6934, 79.2924, 85.6159, 93.1702, 100.3148] +24-11-19 20:38:31 | D | best error = [ 18.7897, 18.7897, 18.7897, 18.7897, 18.7897] +24-11-19 20:38:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:31 | D | sum error = [ 107.5537, 116.2730, 125.2133, 135.7499, 145.2253] +24-11-19 20:38:31 | D | best error = [ 18.7897, 18.7897, 18.7897, 18.7897, 18.7897] +24-11-19 20:38:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:31 | D | sum error = [ 156.6266, 168.8368, 181.6987, 194.0090, 209.3818] +24-11-19 20:38:31 | D | best error = [ 18.7897, 18.7897, 18.7897, 18.7897, 18.7897] +24-11-19 20:38:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:31 | D | sum error = [ 224.8300, 240.8680, 257.4688, 277.4120, 296.6240] +24-11-19 20:38:31 | D | best error = [ 18.7897, 18.7897, 18.7897, 18.7897, 18.7897] +24-11-19 20:38:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:31 | D | sum error = [ 318.1235, 342.2050, 367.3344, 394.3440, 423.7871] +24-11-19 20:38:31 | D | best error = [ 18.7897, 18.7897, 18.7897, 18.7897, 18.7897] +24-11-19 20:38:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:31 | D | sum error = [ 454.3520, 487.5797, 523.0613, 561.4079, 602.6728] +24-11-19 20:38:31 | D | best error = [ 18.7897, 18.7897, 18.7897, 18.7897, 18.7897] +24-11-19 20:38:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:31 | D | sum error = [ 646.9131, 694.8640, 745.6627, 800.9460, 860.1566] +24-11-19 20:38:31 | D | best error = [ 18.7897, 18.7897, 18.7897, 18.7897, 18.7897] +24-11-19 20:38:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:31 | D | sum error = [ 924.9532, 994.7625, 1071.6978, 1153.8389, 1243.7349] +24-11-19 20:38:31 | D | best error = [ 18.7897, 18.7897, 18.7897, 18.7897, 18.7897] +24-11-19 20:38:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:31 | D | sum error = [ 1341.2826, 1449.4244, 1568.2147, 1697.8473, 1841.7112] +24-11-19 20:38:31 | D | best error = [ 18.7897, 18.7897, 18.7897, 18.7897, 18.7897] +24-11-19 20:38:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:31 | D | sum error = [ 1999.6600, 2173.2437, 2365.8357, 2579.0306, 2813.7881] +24-11-19 20:38:31 | D | best error = [ 18.7897, 18.7897, 18.7897, 18.7897, 18.7897] +24-11-19 20:38:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:31 | D | sum error = [ 3075.6141, 3363.2264, 3680.2429, 4030.0962, 4409.9796] +24-11-19 20:38:31 | D | best error = [ 18.7897, 18.7897, 18.7897, 18.7897, 18.7897] +24-11-19 20:38:31 | D | + error = [18.7897] +24-11-19 20:38:31 | D | - Calibrating model.layers.28.self_attn.k_proj.weight +24-11-19 20:38:31 | D | + w: sint8 +24-11-19 20:38:31 | D | + x: None +24-11-19 20:38:31 | D | + y: None +24-11-19 20:38:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:38:31 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:38:31 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:38:31 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:38:32 | D | - range ratio = [ 1.0000] +24-11-19 20:38:32 | D | sum error = [ 23.2260] +24-11-19 20:38:32 | D | best error = [ 23.2260] +24-11-19 20:38:44 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:44 | D | sum error = [ 21.6464, 22.2327, 21.4085, 22.2571, 24.0536] +24-11-19 20:38:44 | D | best error = [ 21.6464, 21.6464, 21.4085, 21.4085, 21.4085] +24-11-19 20:38:44 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:44 | D | sum error = [ 23.2916, 25.3266, 26.6458, 26.6115, 27.9995] +24-11-19 20:38:44 | D | best error = [ 21.4085, 21.4085, 21.4085, 21.4085, 21.4085] +24-11-19 20:38:44 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:44 | D | sum error = [ 29.4943, 32.5944, 33.0207, 37.1543, 40.0048] +24-11-19 20:38:44 | D | best error = [ 21.4085, 21.4085, 21.4085, 21.4085, 21.4085] +24-11-19 20:38:44 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:44 | D | sum error = [ 42.1501, 45.6813, 48.2725, 54.3297, 57.7143] +24-11-19 20:38:44 | D | best error = [ 21.4085, 21.4085, 21.4085, 21.4085, 21.4085] +24-11-19 20:38:44 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:44 | D | sum error = [ 61.2543, 65.8589, 70.4708, 75.3767, 81.8376] +24-11-19 20:38:44 | D | best error = [ 21.4085, 21.4085, 21.4085, 21.4085, 21.4085] +24-11-19 20:38:44 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:44 | D | sum error = [ 86.9752, 92.0433, 98.0294, 105.9557, 113.1679] +24-11-19 20:38:44 | D | best error = [ 21.4085, 21.4085, 21.4085, 21.4085, 21.4085] +24-11-19 20:38:44 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:44 | D | sum error = [ 121.5300, 129.8473, 137.9698, 148.1966, 157.4156] +24-11-19 20:38:44 | D | best error = [ 21.4085, 21.4085, 21.4085, 21.4085, 21.4085] +24-11-19 20:38:44 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:44 | D | sum error = [ 169.3371, 179.5497, 193.4505, 206.9801, 222.0390] +24-11-19 20:38:44 | D | best error = [ 21.4085, 21.4085, 21.4085, 21.4085, 21.4085] +24-11-19 20:38:44 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:44 | D | sum error = [ 237.8236, 254.9637, 271.7804, 291.5194, 312.9869] +24-11-19 20:38:44 | D | best error = [ 21.4085, 21.4085, 21.4085, 21.4085, 21.4085] +24-11-19 20:38:44 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:44 | D | sum error = [ 334.9131, 358.5398, 382.6482, 408.0653, 437.4366] +24-11-19 20:38:44 | D | best error = [ 21.4085, 21.4085, 21.4085, 21.4085, 21.4085] +24-11-19 20:38:44 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:44 | D | sum error = [ 468.8752, 502.8292, 540.1740, 579.9803, 623.3446] +24-11-19 20:38:44 | D | best error = [ 21.4085, 21.4085, 21.4085, 21.4085, 21.4085] +24-11-19 20:38:44 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:44 | D | sum error = [ 669.6359, 720.8726, 775.2763, 834.0672, 901.5059] +24-11-19 20:38:44 | D | best error = [ 21.4085, 21.4085, 21.4085, 21.4085, 21.4085] +24-11-19 20:38:44 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:44 | D | sum error = [ 972.8322, 1049.4153, 1133.9831, 1228.1772, 1329.4417] +24-11-19 20:38:44 | D | best error = [ 21.4085, 21.4085, 21.4085, 21.4085, 21.4085] +24-11-19 20:38:44 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:44 | D | sum error = [ 1441.3713, 1562.2545, 1691.7953, 1832.9830, 1987.1840] +24-11-19 20:38:44 | D | best error = [ 21.4085, 21.4085, 21.4085, 21.4085, 21.4085] +24-11-19 20:38:44 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:44 | D | sum error = [ 2154.9840, 2339.9429, 2541.4467, 2762.5765, 3005.9982] +24-11-19 20:38:44 | D | best error = [ 21.4085, 21.4085, 21.4085, 21.4085, 21.4085] +24-11-19 20:38:44 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:44 | D | sum error = [ 3272.5094, 3566.4304, 3885.3843, 4236.9211, 4623.6016] +24-11-19 20:38:44 | D | best error = [ 21.4085, 21.4085, 21.4085, 21.4085, 21.4085] +24-11-19 20:38:44 | D | + error = [21.4085] +24-11-19 20:38:44 | D | - Calibrating model.layers.28.self_attn.v_proj.weight +24-11-19 20:38:44 | D | + w: sint8 +24-11-19 20:38:44 | D | + x: None +24-11-19 20:38:44 | D | + y: None +24-11-19 20:38:44 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:44 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:38:44 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:38:44 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:38:44 | D | - range ratio = [ 1.0000] +24-11-19 20:38:44 | D | sum error = [ 9.1232] +24-11-19 20:38:44 | D | best error = [ 9.1232] +24-11-19 20:38:45 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:45 | D | sum error = [ 9.0495, 9.0799, 9.1002, 9.2266, 9.3540] +24-11-19 20:38:45 | D | best error = [ 8.4567, 8.2021, 8.0668, 7.9890, 7.9511] +24-11-19 20:38:45 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:45 | D | sum error = [ 9.5991, 9.9026, 10.3096, 10.8337, 11.3577] +24-11-19 20:38:45 | D | best error = [ 7.9322, 7.9229, 7.9182, 7.9176, 7.9174] +24-11-19 20:38:45 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:45 | D | sum error = [ 12.0495, 12.7903, 13.6459, 14.5239, 15.4966] +24-11-19 20:38:45 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 20:38:45 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:45 | D | sum error = [ 16.6178, 17.7946, 19.0560, 20.3887, 21.8793] +24-11-19 20:38:45 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 20:38:45 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:45 | D | sum error = [ 23.3693, 25.0746, 26.8448, 28.6718, 30.6267] +24-11-19 20:38:45 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 20:38:45 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:45 | D | sum error = [ 32.7448, 34.9029, 37.2536, 39.7408, 42.3419] +24-11-19 20:38:45 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 20:38:45 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:45 | D | sum error = [ 45.1072, 47.9738, 51.0477, 54.2785, 57.6559] +24-11-19 20:38:45 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 20:38:45 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:45 | D | sum error = [ 61.2641, 64.9602, 68.8847, 73.0159, 77.3675] +24-11-19 20:38:45 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 20:38:45 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:45 | D | sum error = [ 81.9139, 86.6916, 91.7238, 96.9427, 102.4276] +24-11-19 20:38:45 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 20:38:45 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:45 | D | sum error = [ 108.1511, 114.1756, 120.4245, 126.9888, 133.8494] +24-11-19 20:38:45 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 20:38:45 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:45 | D | sum error = [ 141.0042, 148.4582, 156.2058, 164.2968, 172.6733] +24-11-19 20:38:45 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 20:38:45 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:45 | D | sum error = [ 181.4359, 190.5571, 199.9948, 209.7781, 219.9343] +24-11-19 20:38:45 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 20:38:45 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:45 | D | sum error = [ 230.5040, 241.4305, 252.7365, 264.4539, 276.5890] +24-11-19 20:38:45 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 20:38:45 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:45 | D | sum error = [ 289.1353, 302.1490, 315.5956, 329.4748, 343.7897] +24-11-19 20:38:45 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 20:38:45 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:45 | D | sum error = [ 358.5384, 373.7350, 389.4026, 405.5669, 422.2053] +24-11-19 20:38:45 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 20:38:45 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:45 | D | sum error = [ 439.3432, 456.9945, 475.1445, 493.8316, 513.0224] +24-11-19 20:38:45 | D | best error = [ 7.9174, 7.9174, 7.9174, 7.9174, 7.9174] +24-11-19 20:38:45 | D | + error = [7.9174] +24-11-19 20:38:45 | D | - Calibrating model.layers.28.self_attn.o_proj.weight +24-11-19 20:38:45 | D | + w: sint8 +24-11-19 20:38:45 | D | + x: None +24-11-19 20:38:45 | D | + y: None +24-11-19 20:38:45 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:45 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:38:45 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:38:45 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:38:45 | D | - range ratio = [ 1.0000] +24-11-19 20:38:45 | D | sum error = [ 2.1611] +24-11-19 20:38:45 | D | best error = [ 2.1611] +24-11-19 20:38:45 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:45 | D | sum error = [ 2.1409, 2.1420, 2.1588, 2.1941, 2.2390] +24-11-19 20:38:45 | D | best error = [ 2.0369, 1.9845, 1.9551, 1.9368, 1.9250] +24-11-19 20:38:45 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:45 | D | sum error = [ 2.3026, 2.3917, 2.4969, 2.6191, 2.7694] +24-11-19 20:38:45 | D | best error = [ 1.9167, 1.9109, 1.9074, 1.9048, 1.9030] +24-11-19 20:38:45 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:45 | D | sum error = [ 2.9364, 3.1244, 3.3329, 3.5541, 3.8007] +24-11-19 20:38:45 | D | best error = [ 1.9018, 1.9012, 1.9008, 1.9007, 1.9006] +24-11-19 20:38:45 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:45 | D | sum error = [ 4.0564, 4.3485, 4.6497, 4.9746, 5.3087] +24-11-19 20:38:45 | D | best error = [ 1.9005, 1.9005, 1.9004, 1.9004, 1.9004] +24-11-19 20:38:45 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:45 | D | sum error = [ 5.6816, 6.0737, 6.4765, 6.9215, 7.3743] +24-11-19 20:38:45 | D | best error = [ 1.9004, 1.9004, 1.9004, 1.9004, 1.9004] +24-11-19 20:38:45 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:45 | D | sum error = [ 7.8645, 8.3619, 8.9049, 9.4680, 10.0670] +24-11-19 20:38:45 | D | best error = [ 1.9004, 1.9004, 1.9004, 1.9004, 1.9004] +24-11-19 20:38:45 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:45 | D | sum error = [ 10.6880, 11.3419, 12.0323, 12.7700, 13.5364] +24-11-19 20:38:45 | D | best error = [ 1.9004, 1.9004, 1.9004, 1.9004, 1.9004] +24-11-19 20:38:45 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:45 | D | sum error = [ 14.3366, 15.1930, 16.0802, 17.0154, 17.9943] +24-11-19 20:38:45 | D | best error = [ 1.9004, 1.9004, 1.9004, 1.9004, 1.9004] +24-11-19 20:38:45 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:45 | D | sum error = [ 19.0261, 20.1120, 21.2396, 22.4336, 23.6829] +24-11-19 20:38:45 | D | best error = [ 1.9004, 1.9004, 1.9004, 1.9004, 1.9004] +24-11-19 20:38:45 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:45 | D | sum error = [ 24.9957, 26.3810, 27.8248, 29.3417, 30.9268] +24-11-19 20:38:45 | D | best error = [ 1.9004, 1.9004, 1.9004, 1.9004, 1.9004] +24-11-19 20:38:45 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:45 | D | sum error = [ 32.5921, 34.3407, 36.1730, 38.0892, 40.0947] +24-11-19 20:38:45 | D | best error = [ 1.9004, 1.9004, 1.9004, 1.9004, 1.9004] +24-11-19 20:38:45 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:45 | D | sum error = [ 42.1864, 44.3780, 46.6657, 49.0579, 51.5595] +24-11-19 20:38:45 | D | best error = [ 1.9004, 1.9004, 1.9004, 1.9004, 1.9004] +24-11-19 20:38:45 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:45 | D | sum error = [ 54.1676, 56.8903, 59.7361, 62.7049, 65.7971] +24-11-19 20:38:45 | D | best error = [ 1.9004, 1.9004, 1.9004, 1.9004, 1.9004] +24-11-19 20:38:45 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:45 | D | sum error = [ 69.0146, 72.3645, 75.8613, 79.4970, 83.2698] +24-11-19 20:38:45 | D | best error = [ 1.9004, 1.9004, 1.9004, 1.9004, 1.9004] +24-11-19 20:38:45 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:45 | D | sum error = [ 87.1946, 91.2768, 95.5170, 99.9188, 104.4752] +24-11-19 20:38:45 | D | best error = [ 1.9004, 1.9004, 1.9004, 1.9004, 1.9004] +24-11-19 20:38:45 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:45 | D | sum error = [ 109.1966, 114.0842, 119.1386, 124.3597, 129.7521] +24-11-19 20:38:45 | D | best error = [ 1.9004, 1.9004, 1.9004, 1.9004, 1.9004] +24-11-19 20:38:45 | D | + error = [1.9004] +24-11-19 20:38:45 | D | - Calibrating model.layers.28.mlp.up_proj.weight +24-11-19 20:38:45 | D | + w: sint8 +24-11-19 20:38:45 | D | + x: None +24-11-19 20:38:45 | D | + y: None +24-11-19 20:38:45 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:45 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:38:46 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:38:46 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:38:46 | D | - range ratio = [ 1.0000] +24-11-19 20:38:46 | D | sum error = [ 11.5525] +24-11-19 20:38:46 | D | best error = [ 11.5525] +24-11-19 20:38:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:47 | D | sum error = [ 11.4992, 11.4880, 11.4806, 11.6243, 11.8435] +24-11-19 20:38:47 | D | best error = [ 10.6637, 10.3164, 10.1307, 10.0302, 9.9771] +24-11-19 20:38:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:47 | D | sum error = [ 12.1669, 12.5576, 13.0447, 13.6596, 14.4298] +24-11-19 20:38:47 | D | best error = [ 9.9490, 9.9363, 9.9311, 9.9301, 9.9296] +24-11-19 20:38:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:47 | D | sum error = [ 15.2428, 16.1699, 17.2359, 18.4158, 19.7339] +24-11-19 20:38:47 | D | best error = [ 9.9296, 9.9296, 9.9296, 9.9296, 9.9296] +24-11-19 20:38:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:47 | D | sum error = [ 21.0857, 22.5846, 24.2393, 25.9612, 27.8957] +24-11-19 20:38:47 | D | best error = [ 9.9296, 9.9296, 9.9296, 9.9296, 9.9296] +24-11-19 20:38:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:47 | D | sum error = [ 29.8694, 31.9747, 34.2618, 36.6414, 39.1874] +24-11-19 20:38:47 | D | best error = [ 9.9296, 9.9296, 9.9296, 9.9296, 9.9296] +24-11-19 20:38:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:47 | D | sum error = [ 41.8973, 44.7938, 47.8091, 51.0445, 54.4062] +24-11-19 20:38:47 | D | best error = [ 9.9296, 9.9296, 9.9296, 9.9296, 9.9296] +24-11-19 20:38:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:47 | D | sum error = [ 58.0062, 61.7831, 65.7992, 70.0255, 74.4741] +24-11-19 20:38:47 | D | best error = [ 9.9296, 9.9296, 9.9296, 9.9296, 9.9296] +24-11-19 20:38:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:47 | D | sum error = [ 79.1456, 84.0906, 89.2640, 94.6928, 100.4561] +24-11-19 20:38:47 | D | best error = [ 9.9296, 9.9296, 9.9296, 9.9296, 9.9296] +24-11-19 20:38:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:47 | D | sum error = [ 106.5132, 112.8469, 119.5342, 126.5222, 133.8720] +24-11-19 20:38:47 | D | best error = [ 9.9296, 9.9296, 9.9296, 9.9296, 9.9296] +24-11-19 20:38:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:47 | D | sum error = [ 141.5795, 149.6584, 158.1263, 166.9824, 176.2933] +24-11-19 20:38:47 | D | best error = [ 9.9296, 9.9296, 9.9296, 9.9296, 9.9296] +24-11-19 20:38:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:47 | D | sum error = [ 185.9951, 196.1718, 206.8158, 217.9416, 229.5411] +24-11-19 20:38:47 | D | best error = [ 9.9296, 9.9296, 9.9296, 9.9296, 9.9296] +24-11-19 20:38:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:47 | D | sum error = [ 241.6793, 254.3214, 267.5252, 281.3398, 295.7054] +24-11-19 20:38:47 | D | best error = [ 9.9296, 9.9296, 9.9296, 9.9296, 9.9296] +24-11-19 20:38:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:47 | D | sum error = [ 310.7044, 326.2994, 342.5293, 359.4273, 376.9891] +24-11-19 20:38:47 | D | best error = [ 9.9296, 9.9296, 9.9296, 9.9296, 9.9296] +24-11-19 20:38:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:47 | D | sum error = [ 395.2527, 414.2283, 433.9074, 454.3386, 475.5186] +24-11-19 20:38:47 | D | best error = [ 9.9296, 9.9296, 9.9296, 9.9296, 9.9296] +24-11-19 20:38:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:47 | D | sum error = [ 497.4377, 520.1486, 543.6175, 567.8963, 593.0232] +24-11-19 20:38:47 | D | best error = [ 9.9296, 9.9296, 9.9296, 9.9296, 9.9296] +24-11-19 20:38:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:47 | D | sum error = [ 618.9481, 645.7075, 673.3003, 701.7351, 731.0246] +24-11-19 20:38:47 | D | best error = [ 9.9296, 9.9296, 9.9296, 9.9296, 9.9296] +24-11-19 20:38:47 | D | + error = [9.9296] +24-11-19 20:38:47 | D | - Calibrating model.layers.28.mlp.gate_proj.weight +24-11-19 20:38:47 | D | + w: sint8 +24-11-19 20:38:47 | D | + x: None +24-11-19 20:38:47 | D | + y: None +24-11-19 20:38:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:47 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:38:47 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:38:47 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:38:47 | D | - range ratio = [ 1.0000] +24-11-19 20:38:47 | D | sum error = [ 12.2297] +24-11-19 20:38:47 | D | best error = [ 12.2297] +24-11-19 20:38:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:48 | D | sum error = [ 12.1356, 12.1054, 12.1751, 12.3346, 12.4889] +24-11-19 20:38:48 | D | best error = [ 11.2767, 10.9073, 10.7143, 10.6117, 10.5497] +24-11-19 20:38:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:48 | D | sum error = [ 12.8242, 13.2973, 13.8474, 14.5021, 15.2515] +24-11-19 20:38:48 | D | best error = [ 10.5202, 10.5074, 10.5022, 10.5009, 10.5006] +24-11-19 20:38:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:48 | D | sum error = [ 16.1097, 17.1344, 18.2089, 19.4974, 20.8530] +24-11-19 20:38:48 | D | best error = [ 10.5003, 10.5003, 10.5003, 10.5003, 10.5003] +24-11-19 20:38:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:48 | D | sum error = [ 22.3265, 23.9264, 25.6240, 27.4703, 29.4942] +24-11-19 20:38:48 | D | best error = [ 10.5003, 10.5003, 10.5003, 10.5003, 10.5003] +24-11-19 20:38:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:48 | D | sum error = [ 31.6160, 33.8628, 36.2842, 38.8759, 41.6290] +24-11-19 20:38:48 | D | best error = [ 10.5003, 10.5003, 10.5003, 10.5003, 10.5003] +24-11-19 20:38:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:48 | D | sum error = [ 44.5291, 47.6231, 50.9098, 54.3293, 58.0162] +24-11-19 20:38:48 | D | best error = [ 10.5003, 10.5003, 10.5003, 10.5003, 10.5003] +24-11-19 20:38:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:48 | D | sum error = [ 61.8526, 65.9773, 70.3056, 74.9020, 79.7885] +24-11-19 20:38:48 | D | best error = [ 10.5003, 10.5003, 10.5003, 10.5003, 10.5003] +24-11-19 20:38:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:48 | D | sum error = [ 84.8984, 90.2634, 96.0004, 102.0176, 108.3333] +24-11-19 20:38:48 | D | best error = [ 10.5003, 10.5003, 10.5003, 10.5003, 10.5003] +24-11-19 20:38:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:48 | D | sum error = [ 115.0977, 122.1229, 129.5783, 137.4141, 145.6682] +24-11-19 20:38:48 | D | best error = [ 10.5003, 10.5003, 10.5003, 10.5003, 10.5003] +24-11-19 20:38:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:48 | D | sum error = [ 154.3369, 163.4704, 173.0648, 183.1779, 193.7784] +24-11-19 20:38:48 | D | best error = [ 10.5003, 10.5003, 10.5003, 10.5003, 10.5003] +24-11-19 20:38:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:48 | D | sum error = [ 204.8924, 216.5090, 228.7055, 241.5400, 254.9454] +24-11-19 20:38:48 | D | best error = [ 10.5003, 10.5003, 10.5003, 10.5003, 10.5003] +24-11-19 20:38:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:48 | D | sum error = [ 269.0485, 283.7605, 299.2004, 315.3344, 332.1949] +24-11-19 20:38:48 | D | best error = [ 10.5003, 10.5003, 10.5003, 10.5003, 10.5003] +24-11-19 20:38:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:48 | D | sum error = [ 349.8645, 368.2367, 387.4863, 407.5658, 428.4827] +24-11-19 20:38:48 | D | best error = [ 10.5003, 10.5003, 10.5003, 10.5003, 10.5003] +24-11-19 20:38:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:48 | D | sum error = [ 450.2646, 472.9021, 496.4660, 520.9617, 546.3816] +24-11-19 20:38:48 | D | best error = [ 10.5003, 10.5003, 10.5003, 10.5003, 10.5003] +24-11-19 20:38:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:48 | D | sum error = [ 572.7638, 600.1165, 628.4542, 657.8109, 688.2351] +24-11-19 20:38:48 | D | best error = [ 10.5003, 10.5003, 10.5003, 10.5003, 10.5003] +24-11-19 20:38:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:48 | D | sum error = [ 719.6856, 752.1750, 785.7039, 820.2421, 855.7752] +24-11-19 20:38:48 | D | best error = [ 10.5003, 10.5003, 10.5003, 10.5003, 10.5003] +24-11-19 20:38:48 | D | + error = [10.5003] +24-11-19 20:38:48 | D | - Calibrating model.layers.28.mlp.down_proj.weight +24-11-19 20:38:48 | D | + w: sint8 +24-11-19 20:38:48 | D | + x: None +24-11-19 20:38:48 | D | + y: None +24-11-19 20:38:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:48 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:38:48 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:38:48 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:38:48 | D | - range ratio = [ 1.0000] +24-11-19 20:38:48 | D | sum error = [ 5.0248] +24-11-19 20:38:48 | D | best error = [ 5.0248] +24-11-19 20:38:49 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:49 | D | sum error = [ 4.9761, 4.9391, 4.9122, 4.8924, 4.8761] +24-11-19 20:38:49 | D | best error = [ 4.7567, 4.6340, 4.5635, 4.5109, 4.4690] +24-11-19 20:38:49 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:49 | D | sum error = [ 4.8934, 4.9177, 4.9499, 5.0175, 5.1061] +24-11-19 20:38:49 | D | best error = [ 4.4394, 4.4177, 4.4023, 4.3909, 4.3819] +24-11-19 20:38:49 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:49 | D | sum error = [ 5.2136, 5.3504, 5.5051, 5.7099, 5.9412] +24-11-19 20:38:49 | D | best error = [ 4.3775, 4.3735, 4.3710, 4.3698, 4.3689] +24-11-19 20:38:49 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:49 | D | sum error = [ 6.2030, 6.5098, 6.8546, 7.2269, 7.6537] +24-11-19 20:38:49 | D | best error = [ 4.3684, 4.3680, 4.3678, 4.3678, 4.3677] +24-11-19 20:38:49 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:49 | D | sum error = [ 8.1228, 8.6212, 9.1862, 9.7937, 10.4479] +24-11-19 20:38:49 | D | best error = [ 4.3676, 4.3676, 4.3676, 4.3676, 4.3676] +24-11-19 20:38:49 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:49 | D | sum error = [ 11.1619, 11.9208, 12.7449, 13.6054, 14.5563] +24-11-19 20:38:49 | D | best error = [ 4.3676, 4.3676, 4.3676, 4.3676, 4.3676] +24-11-19 20:38:49 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:49 | D | sum error = [ 15.5528, 16.6297, 17.7755, 18.9857, 20.2783] +24-11-19 20:38:49 | D | best error = [ 4.3676, 4.3676, 4.3676, 4.3676, 4.3676] +24-11-19 20:38:49 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:49 | D | sum error = [ 21.6445, 23.0987, 24.6536, 26.2967, 28.0236] +24-11-19 20:38:49 | D | best error = [ 4.3676, 4.3676, 4.3676, 4.3676, 4.3676] +24-11-19 20:38:49 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:49 | D | sum error = [ 29.8561, 31.7904, 33.8471, 36.0099, 38.3157] +24-11-19 20:38:49 | D | best error = [ 4.3676, 4.3676, 4.3676, 4.3676, 4.3676] +24-11-19 20:38:49 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:49 | D | sum error = [ 40.7192, 43.2759, 45.9589, 48.7786, 51.7563] +24-11-19 20:38:49 | D | best error = [ 4.3676, 4.3676, 4.3676, 4.3676, 4.3676] +24-11-19 20:38:49 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:49 | D | sum error = [ 54.8679, 58.1621, 61.6159, 65.2420, 69.0455] +24-11-19 20:38:49 | D | best error = [ 4.3676, 4.3676, 4.3676, 4.3676, 4.3676] +24-11-19 20:38:49 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:49 | D | sum error = [ 73.0372, 77.2276, 81.6089, 86.2059, 91.0161] +24-11-19 20:38:49 | D | best error = [ 4.3676, 4.3676, 4.3676, 4.3676, 4.3676] +24-11-19 20:38:49 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:49 | D | sum error = [ 96.0424, 101.3017, 106.7993, 112.5255, 118.5142] +24-11-19 20:38:49 | D | best error = [ 4.3676, 4.3676, 4.3676, 4.3676, 4.3676] +24-11-19 20:38:49 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:49 | D | sum error = [ 124.7553, 131.2658, 138.0448, 145.1103, 152.4399] +24-11-19 20:38:49 | D | best error = [ 4.3676, 4.3676, 4.3676, 4.3676, 4.3676] +24-11-19 20:38:49 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:49 | D | sum error = [ 160.0722, 168.0031, 176.2397, 184.7865, 193.6521] +24-11-19 20:38:49 | D | best error = [ 4.3676, 4.3676, 4.3676, 4.3676, 4.3676] +24-11-19 20:38:49 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:49 | D | sum error = [ 202.8356, 212.3478, 222.1905, 232.3696, 242.8928] +24-11-19 20:38:49 | D | best error = [ 4.3676, 4.3676, 4.3676, 4.3676, 4.3676] +24-11-19 20:38:49 | D | + error = [4.3676] +24-11-19 20:38:49 | D | - Quantizing model.layers.28.self_attn.q_proj.weight +24-11-19 20:38:50 | D | - Quantizing model.layers.28.self_attn.k_proj.weight +24-11-19 20:38:51 | D | - Quantizing model.layers.28.self_attn.v_proj.weight +24-11-19 20:38:52 | D | - Quantizing model.layers.28.self_attn.o_proj.weight +24-11-19 20:38:52 | D | - Quantizing model.layers.28.mlp.up_proj.weight +24-11-19 20:38:53 | D | - Quantizing model.layers.28.mlp.gate_proj.weight +24-11-19 20:38:54 | D | - Quantizing model.layers.28.mlp.down_proj.weight +24-11-19 20:39:02 | D | - Quantizing layer model.layers.29 +24-11-19 20:39:02 | D | - Calibrating model.layers.29.self_attn.q_proj.weight +24-11-19 20:39:02 | D | + w: sint8 +24-11-19 20:39:02 | D | + x: None +24-11-19 20:39:02 | D | + y: None +24-11-19 20:39:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:39:02 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:39:02 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:39:02 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:39:03 | D | - range ratio = [ 1.0000] +24-11-19 20:39:03 | D | sum error = [ 18.8028] +24-11-19 20:39:03 | D | best error = [ 18.8028] +24-11-19 20:39:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:15 | D | sum error = [ 18.6694, 18.7847, 18.7503, 18.7167, 19.4341] +24-11-19 20:39:15 | D | best error = [ 18.6694, 18.6694, 18.6694, 18.6694, 18.6694] +24-11-19 20:39:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:15 | D | sum error = [ 19.8614, 21.0803, 21.0630, 22.5629, 23.9113] +24-11-19 20:39:15 | D | best error = [ 18.6694, 18.6694, 18.6694, 18.6694, 18.6694] +24-11-19 20:39:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:15 | D | sum error = [ 25.4856, 26.4715, 28.7665, 30.5536, 33.2671] +24-11-19 20:39:15 | D | best error = [ 18.6694, 18.6694, 18.6694, 18.6694, 18.6694] +24-11-19 20:39:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:15 | D | sum error = [ 35.4909, 38.0591, 41.7318, 44.9349, 48.2868] +24-11-19 20:39:15 | D | best error = [ 18.6694, 18.6694, 18.6694, 18.6694, 18.6694] +24-11-19 20:39:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:15 | D | sum error = [ 52.4324, 57.1638, 62.3620, 67.1333, 72.4293] +24-11-19 20:39:15 | D | best error = [ 18.6694, 18.6694, 18.6694, 18.6694, 18.6694] +24-11-19 20:39:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:15 | D | sum error = [ 78.0498, 84.4657, 91.7857, 99.3647, 107.3036] +24-11-19 20:39:15 | D | best error = [ 18.6694, 18.6694, 18.6694, 18.6694, 18.6694] +24-11-19 20:39:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:15 | D | sum error = [ 115.7722, 125.2471, 135.0910, 146.3667, 156.7622] +24-11-19 20:39:15 | D | best error = [ 18.6694, 18.6694, 18.6694, 18.6694, 18.6694] +24-11-19 20:39:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:15 | D | sum error = [ 169.1805, 182.5170, 196.6192, 212.1287, 228.7125] +24-11-19 20:39:15 | D | best error = [ 18.6694, 18.6694, 18.6694, 18.6694, 18.6694] +24-11-19 20:39:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:15 | D | sum error = [ 246.7040, 265.3892, 284.7977, 307.7289, 330.9024] +24-11-19 20:39:15 | D | best error = [ 18.6694, 18.6694, 18.6694, 18.6694, 18.6694] +24-11-19 20:39:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:15 | D | sum error = [ 357.2598, 383.8438, 412.4705, 444.3363, 476.5826] +24-11-19 20:39:15 | D | best error = [ 18.6694, 18.6694, 18.6694, 18.6694, 18.6694] +24-11-19 20:39:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:15 | D | sum error = [ 511.7212, 548.9916, 589.0581, 631.7053, 677.7588] +24-11-19 20:39:15 | D | best error = [ 18.6694, 18.6694, 18.6694, 18.6694, 18.6694] +24-11-19 20:39:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:15 | D | sum error = [ 726.9972, 779.5603, 836.2920, 897.0648, 962.4844] +24-11-19 20:39:15 | D | best error = [ 18.6694, 18.6694, 18.6694, 18.6694, 18.6694] +24-11-19 20:39:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:15 | D | sum error = [ 1033.0023, 1108.8306, 1190.5182, 1279.3780, 1374.9605] +24-11-19 20:39:15 | D | best error = [ 18.6694, 18.6694, 18.6694, 18.6694, 18.6694] +24-11-19 20:39:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:15 | D | sum error = [ 1480.4418, 1592.8257, 1715.1711, 1849.2428, 1993.9797] +24-11-19 20:39:15 | D | best error = [ 18.6694, 18.6694, 18.6694, 18.6694, 18.6694] +24-11-19 20:39:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:15 | D | sum error = [ 2152.2908, 2321.7857, 2506.8550, 2707.5493, 2924.9048] +24-11-19 20:39:15 | D | best error = [ 18.6694, 18.6694, 18.6694, 18.6694, 18.6694] +24-11-19 20:39:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:15 | D | sum error = [ 3157.3764, 3406.3949, 3676.7238, 3962.6211, 4266.3788] +24-11-19 20:39:15 | D | best error = [ 18.6694, 18.6694, 18.6694, 18.6694, 18.6694] +24-11-19 20:39:15 | D | + error = [18.6694] +24-11-19 20:39:15 | D | - Calibrating model.layers.29.self_attn.k_proj.weight +24-11-19 20:39:15 | D | + w: sint8 +24-11-19 20:39:15 | D | + x: None +24-11-19 20:39:15 | D | + y: None +24-11-19 20:39:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:39:15 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:39:15 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:39:15 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:39:16 | D | - range ratio = [ 1.0000] +24-11-19 20:39:16 | D | sum error = [ 22.1355] +24-11-19 20:39:16 | D | best error = [ 22.1355] +24-11-19 20:39:28 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:28 | D | sum error = [ 24.3648, 21.4375, 21.6556, 22.7834, 21.7425] +24-11-19 20:39:28 | D | best error = [ 22.1355, 21.4375, 21.4375, 21.4375, 21.4375] +24-11-19 20:39:28 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:28 | D | sum error = [ 22.6352, 23.7316, 25.4448, 25.7781, 26.9631] +24-11-19 20:39:28 | D | best error = [ 21.4375, 21.4375, 21.4375, 21.4375, 21.4375] +24-11-19 20:39:28 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:28 | D | sum error = [ 28.6764, 30.4799, 31.6233, 35.7881, 37.9134] +24-11-19 20:39:28 | D | best error = [ 21.4375, 21.4375, 21.4375, 21.4375, 21.4375] +24-11-19 20:39:28 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:28 | D | sum error = [ 40.3704, 44.3183, 49.1976, 52.1417, 59.2904] +24-11-19 20:39:28 | D | best error = [ 21.4375, 21.4375, 21.4375, 21.4375, 21.4375] +24-11-19 20:39:28 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:28 | D | sum error = [ 62.5593, 68.1703, 73.4686, 77.7799, 83.1794] +24-11-19 20:39:28 | D | best error = [ 21.4375, 21.4375, 21.4375, 21.4375, 21.4375] +24-11-19 20:39:28 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:28 | D | sum error = [ 89.3413, 98.0979, 103.2280, 112.4556, 119.1483] +24-11-19 20:39:28 | D | best error = [ 21.4375, 21.4375, 21.4375, 21.4375, 21.4375] +24-11-19 20:39:28 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:28 | D | sum error = [ 127.9297, 139.5470, 149.8716, 161.1478, 175.0107] +24-11-19 20:39:28 | D | best error = [ 21.4375, 21.4375, 21.4375, 21.4375, 21.4375] +24-11-19 20:39:28 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:28 | D | sum error = [ 186.1045, 199.8362, 217.2536, 233.2960, 249.8954] +24-11-19 20:39:28 | D | best error = [ 21.4375, 21.4375, 21.4375, 21.4375, 21.4375] +24-11-19 20:39:28 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:28 | D | sum error = [ 269.2330, 287.6047, 305.7090, 326.8041, 348.1070] +24-11-19 20:39:28 | D | best error = [ 21.4375, 21.4375, 21.4375, 21.4375, 21.4375] +24-11-19 20:39:28 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:28 | D | sum error = [ 371.5480, 395.6895, 423.9494, 450.0319, 480.9826] +24-11-19 20:39:28 | D | best error = [ 21.4375, 21.4375, 21.4375, 21.4375, 21.4375] +24-11-19 20:39:28 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:28 | D | sum error = [ 514.4516, 550.4148, 587.0915, 626.9587, 669.5816] +24-11-19 20:39:28 | D | best error = [ 21.4375, 21.4375, 21.4375, 21.4375, 21.4375] +24-11-19 20:39:28 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:28 | D | sum error = [ 714.3602, 764.9928, 816.8073, 875.8878, 937.4144] +24-11-19 20:39:28 | D | best error = [ 21.4375, 21.4375, 21.4375, 21.4375, 21.4375] +24-11-19 20:39:28 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:28 | D | sum error = [ 1005.1365, 1077.5680, 1154.2919, 1238.6503, 1328.0710] +24-11-19 20:39:28 | D | best error = [ 21.4375, 21.4375, 21.4375, 21.4375, 21.4375] +24-11-19 20:39:28 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:28 | D | sum error = [ 1425.2353, 1528.3429, 1643.4712, 1765.1589, 1900.1668] +24-11-19 20:39:28 | D | best error = [ 21.4375, 21.4375, 21.4375, 21.4375, 21.4375] +24-11-19 20:39:28 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:28 | D | sum error = [ 2045.6053, 2205.3190, 2379.0182, 2570.4221, 2776.3381] +24-11-19 20:39:28 | D | best error = [ 21.4375, 21.4375, 21.4375, 21.4375, 21.4375] +24-11-19 20:39:28 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:28 | D | sum error = [ 3001.3104, 3245.2541, 3508.2860, 3792.3452, 4099.3056] +24-11-19 20:39:28 | D | best error = [ 21.4375, 21.4375, 21.4375, 21.4375, 21.4375] +24-11-19 20:39:28 | D | + error = [21.4375] +24-11-19 20:39:28 | D | - Calibrating model.layers.29.self_attn.v_proj.weight +24-11-19 20:39:28 | D | + w: sint8 +24-11-19 20:39:28 | D | + x: None +24-11-19 20:39:28 | D | + y: None +24-11-19 20:39:28 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:28 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:39:28 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:39:28 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:39:28 | D | - range ratio = [ 1.0000] +24-11-19 20:39:28 | D | sum error = [ 8.9297] +24-11-19 20:39:28 | D | best error = [ 8.9297] +24-11-19 20:39:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:29 | D | sum error = [ 8.8427, 8.8175, 8.8617, 8.9818, 9.1412] +24-11-19 20:39:29 | D | best error = [ 8.2220, 7.9542, 7.8112, 7.7368, 7.6946] +24-11-19 20:39:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:29 | D | sum error = [ 9.3798, 9.6651, 10.0278, 10.5651, 11.0971] +24-11-19 20:39:29 | D | best error = [ 7.6743, 7.6647, 7.6622, 7.6607, 7.6605] +24-11-19 20:39:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:29 | D | sum error = [ 11.7378, 12.4422, 13.2536, 14.1654, 15.1473] +24-11-19 20:39:29 | D | best error = [ 7.6605, 7.6605, 7.6605, 7.6605, 7.6605] +24-11-19 20:39:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:29 | D | sum error = [ 16.2385, 17.4149, 18.6279, 19.9432, 21.3437] +24-11-19 20:39:29 | D | best error = [ 7.6605, 7.6605, 7.6605, 7.6605, 7.6605] +24-11-19 20:39:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:29 | D | sum error = [ 22.8224, 24.4789, 26.1955, 27.9891, 29.8989] +24-11-19 20:39:29 | D | best error = [ 7.6605, 7.6605, 7.6605, 7.6605, 7.6605] +24-11-19 20:39:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:29 | D | sum error = [ 31.9565, 34.1241, 36.3701, 38.8133, 41.4057] +24-11-19 20:39:29 | D | best error = [ 7.6605, 7.6605, 7.6605, 7.6605, 7.6605] +24-11-19 20:39:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:29 | D | sum error = [ 44.0450, 46.8788, 49.8576, 52.9808, 56.3175] +24-11-19 20:39:29 | D | best error = [ 7.6605, 7.6605, 7.6605, 7.6605, 7.6605] +24-11-19 20:39:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:29 | D | sum error = [ 59.7742, 63.4689, 67.2626, 71.2835, 75.4950] +24-11-19 20:39:29 | D | best error = [ 7.6605, 7.6605, 7.6605, 7.6605, 7.6605] +24-11-19 20:39:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:29 | D | sum error = [ 79.9254, 84.5202, 89.3967, 94.5101, 99.7970] +24-11-19 20:39:29 | D | best error = [ 7.6605, 7.6605, 7.6605, 7.6605, 7.6605] +24-11-19 20:39:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:29 | D | sum error = [ 105.3361, 111.1021, 117.1613, 123.4599, 130.0234] +24-11-19 20:39:29 | D | best error = [ 7.6605, 7.6605, 7.6605, 7.6605, 7.6605] +24-11-19 20:39:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:29 | D | sum error = [ 136.8521, 143.9927, 151.4019, 159.1100, 167.1377] +24-11-19 20:39:29 | D | best error = [ 7.6605, 7.6605, 7.6605, 7.6605, 7.6605] +24-11-19 20:39:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:29 | D | sum error = [ 175.4696, 184.1453, 193.1261, 202.3851, 211.9920] +24-11-19 20:39:29 | D | best error = [ 7.6605, 7.6605, 7.6605, 7.6605, 7.6605] +24-11-19 20:39:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:29 | D | sum error = [ 221.9942, 232.3173, 243.0254, 254.1146, 265.5898] +24-11-19 20:39:29 | D | best error = [ 7.6605, 7.6605, 7.6605, 7.6605, 7.6605] +24-11-19 20:39:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:29 | D | sum error = [ 277.4583, 289.6898, 302.3283, 315.3784, 328.8165] +24-11-19 20:39:29 | D | best error = [ 7.6605, 7.6605, 7.6605, 7.6605, 7.6605] +24-11-19 20:39:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:29 | D | sum error = [ 342.6771, 356.9389, 371.6940, 386.8506, 402.4444] +24-11-19 20:39:29 | D | best error = [ 7.6605, 7.6605, 7.6605, 7.6605, 7.6605] +24-11-19 20:39:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:29 | D | sum error = [ 418.4829, 434.9797, 451.9343, 469.3361, 487.2017] +24-11-19 20:39:29 | D | best error = [ 7.6605, 7.6605, 7.6605, 7.6605, 7.6605] +24-11-19 20:39:29 | D | + error = [7.6605] +24-11-19 20:39:29 | D | - Calibrating model.layers.29.self_attn.o_proj.weight +24-11-19 20:39:29 | D | + w: sint8 +24-11-19 20:39:29 | D | + x: None +24-11-19 20:39:29 | D | + y: None +24-11-19 20:39:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:29 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:39:29 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:39:29 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:39:29 | D | - range ratio = [ 1.0000] +24-11-19 20:39:29 | D | sum error = [ 2.0425] +24-11-19 20:39:29 | D | best error = [ 2.0425] +24-11-19 20:39:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:29 | D | sum error = [ 2.0305, 2.0287, 2.0450, 2.0711, 2.1253] +24-11-19 20:39:29 | D | best error = [ 1.9219, 1.8662, 1.8335, 1.8138, 1.8036] +24-11-19 20:39:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:29 | D | sum error = [ 2.1947, 2.2773, 2.3880, 2.5032, 2.6595] +24-11-19 20:39:29 | D | best error = [ 1.7961, 1.7916, 1.7891, 1.7867, 1.7854] +24-11-19 20:39:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:29 | D | sum error = [ 2.8232, 2.9978, 3.2023, 3.4223, 3.6675] +24-11-19 20:39:29 | D | best error = [ 1.7844, 1.7836, 1.7833, 1.7830, 1.7827] +24-11-19 20:39:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:29 | D | sum error = [ 3.9409, 4.2195, 4.5202, 4.8427, 5.1800] +24-11-19 20:39:29 | D | best error = [ 1.7827, 1.7826, 1.7826, 1.7826, 1.7826] +24-11-19 20:39:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:29 | D | sum error = [ 5.5559, 5.9387, 6.3606, 6.7883, 7.2527] +24-11-19 20:39:29 | D | best error = [ 1.7825, 1.7825, 1.7825, 1.7825, 1.7825] +24-11-19 20:39:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:29 | D | sum error = [ 7.7449, 8.2570, 8.8163, 9.3746, 9.9854] +24-11-19 20:39:29 | D | best error = [ 1.7825, 1.7825, 1.7825, 1.7825, 1.7825] +24-11-19 20:39:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:29 | D | sum error = [ 10.6190, 11.3001, 12.0030, 12.7478, 13.5382] +24-11-19 20:39:29 | D | best error = [ 1.7825, 1.7825, 1.7825, 1.7825, 1.7825] +24-11-19 20:39:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:29 | D | sum error = [ 14.3685, 15.2414, 16.1560, 17.1283, 18.1377] +24-11-19 20:39:29 | D | best error = [ 1.7825, 1.7825, 1.7825, 1.7825, 1.7825] +24-11-19 20:39:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:29 | D | sum error = [ 19.2036, 20.3206, 21.4996, 22.7315, 24.0287] +24-11-19 20:39:29 | D | best error = [ 1.7825, 1.7825, 1.7825, 1.7825, 1.7825] +24-11-19 20:39:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:29 | D | sum error = [ 25.3918, 26.8138, 28.3025, 29.8702, 31.5122] +24-11-19 20:39:29 | D | best error = [ 1.7825, 1.7825, 1.7825, 1.7825, 1.7825] +24-11-19 20:39:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:29 | D | sum error = [ 33.2343, 35.0348, 36.9154, 38.8965, 40.9523] +24-11-19 20:39:29 | D | best error = [ 1.7825, 1.7825, 1.7825, 1.7825, 1.7825] +24-11-19 20:39:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:29 | D | sum error = [ 43.1065, 45.3536, 47.7021, 50.1601, 52.7234] +24-11-19 20:39:29 | D | best error = [ 1.7825, 1.7825, 1.7825, 1.7825, 1.7825] +24-11-19 20:39:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:29 | D | sum error = [ 55.3863, 58.1641, 61.0577, 64.0683, 67.2029] +24-11-19 20:39:29 | D | best error = [ 1.7825, 1.7825, 1.7825, 1.7825, 1.7825] +24-11-19 20:39:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:29 | D | sum error = [ 70.4652, 73.8653, 77.3943, 81.0693, 84.8751] +24-11-19 20:39:29 | D | best error = [ 1.7825, 1.7825, 1.7825, 1.7825, 1.7825] +24-11-19 20:39:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:29 | D | sum error = [ 88.8296, 92.9245, 97.1687, 101.5597, 106.1102] +24-11-19 20:39:29 | D | best error = [ 1.7825, 1.7825, 1.7825, 1.7825, 1.7825] +24-11-19 20:39:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:29 | D | sum error = [ 110.8147, 115.6805, 120.7052, 125.8866, 131.2336] +24-11-19 20:39:29 | D | best error = [ 1.7825, 1.7825, 1.7825, 1.7825, 1.7825] +24-11-19 20:39:29 | D | + error = [1.7825] +24-11-19 20:39:30 | D | - Calibrating model.layers.29.mlp.up_proj.weight +24-11-19 20:39:30 | D | + w: sint8 +24-11-19 20:39:30 | D | + x: None +24-11-19 20:39:30 | D | + y: None +24-11-19 20:39:30 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:30 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:39:30 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:39:30 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:39:30 | D | - range ratio = [ 1.0000] +24-11-19 20:39:30 | D | sum error = [ 12.0013] +24-11-19 20:39:30 | D | best error = [ 12.0013] +24-11-19 20:39:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:31 | D | sum error = [ 11.9179, 11.8739, 11.9716, 12.0804, 12.3124] +24-11-19 20:39:31 | D | best error = [ 10.9816, 10.6098, 10.4209, 10.3152, 10.2543] +24-11-19 20:39:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:31 | D | sum error = [ 12.6097, 13.0410, 13.5660, 14.2108, 14.9817] +24-11-19 20:39:31 | D | best error = [ 10.2257, 10.2120, 10.2060, 10.2044, 10.2037] +24-11-19 20:39:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:31 | D | sum error = [ 15.8368, 16.7999, 17.9159, 19.1454, 20.4471] +24-11-19 20:39:31 | D | best error = [ 10.2037, 10.2037, 10.2037, 10.2037, 10.2037] +24-11-19 20:39:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:31 | D | sum error = [ 21.8670, 23.4378, 25.1414, 26.9110, 28.8534] +24-11-19 20:39:31 | D | best error = [ 10.2037, 10.2037, 10.2037, 10.2037, 10.2037] +24-11-19 20:39:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:31 | D | sum error = [ 30.9383, 33.1497, 35.4662, 37.9385, 40.5992] +24-11-19 20:39:31 | D | best error = [ 10.2037, 10.2037, 10.2037, 10.2037, 10.2037] +24-11-19 20:39:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:31 | D | sum error = [ 43.4074, 46.3443, 49.5869, 52.8545, 56.4132] +24-11-19 20:39:31 | D | best error = [ 10.2037, 10.2037, 10.2037, 10.2037, 10.2037] +24-11-19 20:39:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:31 | D | sum error = [ 60.1636, 64.1054, 68.3472, 72.7426, 77.4481] +24-11-19 20:39:31 | D | best error = [ 10.2037, 10.2037, 10.2037, 10.2037, 10.2037] +24-11-19 20:39:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:31 | D | sum error = [ 82.3636, 87.5969, 93.0824, 98.8567, 104.9259] +24-11-19 20:39:31 | D | best error = [ 10.2037, 10.2037, 10.2037, 10.2037, 10.2037] +24-11-19 20:39:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:31 | D | sum error = [ 111.3530, 118.0712, 125.1960, 132.6829, 140.5809] +24-11-19 20:39:31 | D | best error = [ 10.2037, 10.2037, 10.2037, 10.2037, 10.2037] +24-11-19 20:39:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:31 | D | sum error = [ 148.8441, 157.6357, 166.7905, 176.4205, 186.4633] +24-11-19 20:39:31 | D | best error = [ 10.2037, 10.2037, 10.2037, 10.2037, 10.2037] +24-11-19 20:39:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:31 | D | sum error = [ 197.0892, 208.1906, 219.7910, 232.0192, 244.8269] +24-11-19 20:39:31 | D | best error = [ 10.2037, 10.2037, 10.2037, 10.2037, 10.2037] +24-11-19 20:39:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:31 | D | sum error = [ 258.1963, 272.2232, 286.8473, 302.1765, 318.2389] +24-11-19 20:39:31 | D | best error = [ 10.2037, 10.2037, 10.2037, 10.2037, 10.2037] +24-11-19 20:39:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:31 | D | sum error = [ 334.8964, 352.3139, 370.5295, 389.5033, 409.2233] +24-11-19 20:39:31 | D | best error = [ 10.2037, 10.2037, 10.2037, 10.2037, 10.2037] +24-11-19 20:39:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:31 | D | sum error = [ 429.7846, 451.1863, 473.3816, 496.4005, 520.2896] +24-11-19 20:39:31 | D | best error = [ 10.2037, 10.2037, 10.2037, 10.2037, 10.2037] +24-11-19 20:39:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:31 | D | sum error = [ 545.1443, 570.8257, 597.4247, 624.9670, 653.5015] +24-11-19 20:39:31 | D | best error = [ 10.2037, 10.2037, 10.2037, 10.2037, 10.2037] +24-11-19 20:39:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:31 | D | sum error = [ 682.9182, 713.2803, 744.6003, 776.9230, 810.2177] +24-11-19 20:39:31 | D | best error = [ 10.2037, 10.2037, 10.2037, 10.2037, 10.2037] +24-11-19 20:39:31 | D | + error = [10.2037] +24-11-19 20:39:31 | D | - Calibrating model.layers.29.mlp.gate_proj.weight +24-11-19 20:39:31 | D | + w: sint8 +24-11-19 20:39:31 | D | + x: None +24-11-19 20:39:31 | D | + y: None +24-11-19 20:39:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:31 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:39:31 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:39:31 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:39:31 | D | - range ratio = [ 1.0000] +24-11-19 20:39:31 | D | sum error = [ 12.5805] +24-11-19 20:39:31 | D | best error = [ 12.5805] +24-11-19 20:39:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:32 | D | sum error = [ 12.4593, 12.4585, 12.4849, 12.6731, 12.9043] +24-11-19 20:39:32 | D | best error = [ 11.5091, 11.1214, 10.9161, 10.8045, 10.7426] +24-11-19 20:39:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:32 | D | sum error = [ 13.2260, 13.6926, 14.2545, 14.8514, 15.7027] +24-11-19 20:39:32 | D | best error = [ 10.7123, 10.6975, 10.6924, 10.6909, 10.6906] +24-11-19 20:39:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:32 | D | sum error = [ 16.6667, 17.6754, 18.8303, 20.0797, 21.5183] +24-11-19 20:39:32 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 20:39:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:32 | D | sum error = [ 23.0477, 24.6955, 26.5311, 28.3981, 30.4921] +24-11-19 20:39:32 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 20:39:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:32 | D | sum error = [ 32.6782, 35.0840, 37.5537, 40.2966, 43.0547] +24-11-19 20:39:32 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 20:39:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:32 | D | sum error = [ 46.1186, 49.3474, 52.7241, 56.3489, 60.1035] +24-11-19 20:39:32 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 20:39:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:32 | D | sum error = [ 64.1687, 68.4312, 72.9626, 77.6761, 82.7226] +24-11-19 20:39:32 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 20:39:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:32 | D | sum error = [ 88.0695, 93.6773, 99.6435, 105.8934, 112.5235] +24-11-19 20:39:32 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 20:39:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:32 | D | sum error = [ 119.5112, 126.8585, 134.6099, 142.7908, 151.3712] +24-11-19 20:39:32 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 20:39:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:32 | D | sum error = [ 160.4405, 169.9608, 180.0175, 190.5193, 201.6637] +24-11-19 20:39:32 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 20:39:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:32 | D | sum error = [ 213.3215, 225.5483, 238.4410, 251.9409, 266.1249] +24-11-19 20:39:32 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 20:39:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:32 | D | sum error = [ 280.9431, 296.4271, 312.6828, 329.7256, 347.4890] +24-11-19 20:39:32 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 20:39:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:32 | D | sum error = [ 366.0914, 385.5114, 405.7753, 426.9455, 449.0071] +24-11-19 20:39:32 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 20:39:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:32 | D | sum error = [ 472.0207, 495.9479, 520.8401, 546.7581, 573.6187] +24-11-19 20:39:32 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 20:39:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:32 | D | sum error = [ 601.5006, 630.4363, 660.3646, 691.3585, 723.4388] +24-11-19 20:39:32 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 20:39:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:32 | D | sum error = [ 756.5218, 790.7625, 826.0384, 862.3924, 899.7857] +24-11-19 20:39:32 | D | best error = [ 10.6905, 10.6905, 10.6905, 10.6905, 10.6905] +24-11-19 20:39:32 | D | + error = [10.6905] +24-11-19 20:39:32 | D | - Calibrating model.layers.29.mlp.down_proj.weight +24-11-19 20:39:32 | D | + w: sint8 +24-11-19 20:39:32 | D | + x: None +24-11-19 20:39:32 | D | + y: None +24-11-19 20:39:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:32 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:39:32 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:39:32 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:39:32 | D | - range ratio = [ 1.0000] +24-11-19 20:39:32 | D | sum error = [ 5.7945] +24-11-19 20:39:32 | D | best error = [ 5.7945] +24-11-19 20:39:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:33 | D | sum error = [ 5.8182, 6.0094, 6.3352, 6.8270, 7.4213] +24-11-19 20:39:33 | D | best error = [ 5.4537, 5.3264, 5.2433, 5.1866, 5.1410] +24-11-19 20:39:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:33 | D | sum error = [ 8.1029, 8.8836, 9.7049, 10.5917, 11.5110] +24-11-19 20:39:33 | D | best error = [ 5.1055, 5.0816, 5.0640, 5.0492, 5.0378] +24-11-19 20:39:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:33 | D | sum error = [ 12.4885, 13.4815, 14.5155, 15.5776, 16.6742] +24-11-19 20:39:33 | D | best error = [ 5.0304, 5.0249, 5.0217, 5.0196, 5.0182] +24-11-19 20:39:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:33 | D | sum error = [ 17.7980, 18.9385, 20.1178, 21.3328, 22.5613] +24-11-19 20:39:33 | D | best error = [ 5.0171, 5.0169, 5.0166, 5.0162, 5.0162] +24-11-19 20:39:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:33 | D | sum error = [ 23.8161, 25.1190, 26.4402, 27.8012, 29.1984] +24-11-19 20:39:33 | D | best error = [ 5.0162, 5.0161, 5.0161, 5.0161, 5.0161] +24-11-19 20:39:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:33 | D | sum error = [ 30.6231, 32.0974, 33.6058, 35.1598, 36.7599] +24-11-19 20:39:33 | D | best error = [ 5.0161, 5.0161, 5.0161, 5.0161, 5.0161] +24-11-19 20:39:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:33 | D | sum error = [ 38.4014, 40.0880, 41.8302, 43.6358, 45.4818] +24-11-19 20:39:33 | D | best error = [ 5.0161, 5.0161, 5.0161, 5.0161, 5.0161] +24-11-19 20:39:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:33 | D | sum error = [ 47.3978, 49.3867, 51.4487, 53.5770, 55.7866] +24-11-19 20:39:33 | D | best error = [ 5.0161, 5.0161, 5.0161, 5.0161, 5.0161] +24-11-19 20:39:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:33 | D | sum error = [ 58.0776, 60.4656, 62.9509, 65.5287, 68.2190] +24-11-19 20:39:33 | D | best error = [ 5.0161, 5.0161, 5.0161, 5.0161, 5.0161] +24-11-19 20:39:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:33 | D | sum error = [ 71.0122, 73.9325, 76.9757, 80.1506, 83.4609] +24-11-19 20:39:33 | D | best error = [ 5.0161, 5.0161, 5.0161, 5.0161, 5.0161] +24-11-19 20:39:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:33 | D | sum error = [ 86.9252, 90.5470, 94.3229, 98.2683, 102.3944] +24-11-19 20:39:33 | D | best error = [ 5.0161, 5.0161, 5.0161, 5.0161, 5.0161] +24-11-19 20:39:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:33 | D | sum error = [ 106.7150, 111.2363, 115.9544, 120.8944, 126.0603] +24-11-19 20:39:33 | D | best error = [ 5.0161, 5.0161, 5.0161, 5.0161, 5.0161] +24-11-19 20:39:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:33 | D | sum error = [ 131.4673, 137.1211, 143.0331, 149.2105, 155.6700] +24-11-19 20:39:33 | D | best error = [ 5.0161, 5.0161, 5.0161, 5.0161, 5.0161] +24-11-19 20:39:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:33 | D | sum error = [ 162.4122, 169.4585, 176.7878, 184.4644, 192.4370] +24-11-19 20:39:33 | D | best error = [ 5.0161, 5.0161, 5.0161, 5.0161, 5.0161] +24-11-19 20:39:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:33 | D | sum error = [ 200.7414, 209.3921, 218.3962, 227.7790, 237.5346] +24-11-19 20:39:33 | D | best error = [ 5.0161, 5.0161, 5.0161, 5.0161, 5.0161] +24-11-19 20:39:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:33 | D | sum error = [ 247.6657, 258.1926, 269.1286, 280.4606, 292.2071] +24-11-19 20:39:33 | D | best error = [ 5.0161, 5.0161, 5.0161, 5.0161, 5.0161] +24-11-19 20:39:33 | D | + error = [5.0161] +24-11-19 20:39:33 | D | - Quantizing model.layers.29.self_attn.q_proj.weight +24-11-19 20:39:34 | D | - Quantizing model.layers.29.self_attn.k_proj.weight +24-11-19 20:39:35 | D | - Quantizing model.layers.29.self_attn.v_proj.weight +24-11-19 20:39:36 | D | - Quantizing model.layers.29.self_attn.o_proj.weight +24-11-19 20:39:37 | D | - Quantizing model.layers.29.mlp.up_proj.weight +24-11-19 20:39:37 | D | - Quantizing model.layers.29.mlp.gate_proj.weight +24-11-19 20:39:38 | D | - Quantizing model.layers.29.mlp.down_proj.weight +24-11-19 20:39:47 | D | - Quantizing layer model.layers.30 +24-11-19 20:39:47 | D | - Calibrating model.layers.30.self_attn.q_proj.weight +24-11-19 20:39:47 | D | + w: sint8 +24-11-19 20:39:47 | D | + x: None +24-11-19 20:39:47 | D | + y: None +24-11-19 20:39:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:39:47 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:39:47 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:39:48 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:39:48 | D | - range ratio = [ 1.0000] +24-11-19 20:39:48 | D | sum error = [ 18.1859] +24-11-19 20:39:48 | D | best error = [ 18.1859] +24-11-19 20:40:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:01 | D | sum error = [ 18.8800, 18.3616, 18.6723, 19.6762, 19.3009] +24-11-19 20:40:01 | D | best error = [ 18.1859, 18.1859, 18.1859, 18.1859, 18.1859] +24-11-19 20:40:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:01 | D | sum error = [ 19.9292, 20.6156, 22.0051, 22.4952, 24.0192] +24-11-19 20:40:01 | D | best error = [ 18.1859, 18.1859, 18.1859, 18.1859, 18.1859] +24-11-19 20:40:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:01 | D | sum error = [ 25.0879, 26.6310, 29.8705, 30.8757, 32.6828] +24-11-19 20:40:01 | D | best error = [ 18.1859, 18.1859, 18.1859, 18.1859, 18.1859] +24-11-19 20:40:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:01 | D | sum error = [ 35.5503, 38.7911, 40.9198, 44.1769, 47.5806] +24-11-19 20:40:01 | D | best error = [ 18.1859, 18.1859, 18.1859, 18.1859, 18.1859] +24-11-19 20:40:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:01 | D | sum error = [ 51.3845, 56.1662, 60.0471, 64.8966, 70.4583] +24-11-19 20:40:01 | D | best error = [ 18.1859, 18.1859, 18.1859, 18.1859, 18.1859] +24-11-19 20:40:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:01 | D | sum error = [ 76.3757, 81.9392, 89.3545, 95.7398, 103.7695] +24-11-19 20:40:01 | D | best error = [ 18.1859, 18.1859, 18.1859, 18.1859, 18.1859] +24-11-19 20:40:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:01 | D | sum error = [ 112.6334, 121.7762, 131.7367, 142.5201, 154.4974] +24-11-19 20:40:01 | D | best error = [ 18.1859, 18.1859, 18.1859, 18.1859, 18.1859] +24-11-19 20:40:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:01 | D | sum error = [ 166.1837, 178.8226, 193.9117, 210.8031, 227.9884] +24-11-19 20:40:01 | D | best error = [ 18.1859, 18.1859, 18.1859, 18.1859, 18.1859] +24-11-19 20:40:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:01 | D | sum error = [ 245.2909, 265.8487, 288.4192, 311.6416, 336.7612] +24-11-19 20:40:01 | D | best error = [ 18.1859, 18.1859, 18.1859, 18.1859, 18.1859] +24-11-19 20:40:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:01 | D | sum error = [ 362.6636, 391.8842, 423.5230, 457.2129, 494.8003] +24-11-19 20:40:01 | D | best error = [ 18.1859, 18.1859, 18.1859, 18.1859, 18.1859] +24-11-19 20:40:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:01 | D | sum error = [ 534.9843, 579.4057, 625.1986, 676.9639, 732.3208] +24-11-19 20:40:01 | D | best error = [ 18.1859, 18.1859, 18.1859, 18.1859, 18.1859] +24-11-19 20:40:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:01 | D | sum error = [ 791.9103, 857.6058, 928.3110, 1005.0678, 1088.2990] +24-11-19 20:40:01 | D | best error = [ 18.1859, 18.1859, 18.1859, 18.1859, 18.1859] +24-11-19 20:40:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:01 | D | sum error = [ 1177.9471, 1275.2045, 1380.0505, 1494.8345, 1620.1803] +24-11-19 20:40:01 | D | best error = [ 18.1859, 18.1859, 18.1859, 18.1859, 18.1859] +24-11-19 20:40:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:01 | D | sum error = [ 1756.4343, 1905.0243, 2069.0927, 2248.9313, 2442.9380] +24-11-19 20:40:01 | D | best error = [ 18.1859, 18.1859, 18.1859, 18.1859, 18.1859] +24-11-19 20:40:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:01 | D | sum error = [ 2657.5186, 2891.1071, 3147.2766, 3428.1543, 3735.0119] +24-11-19 20:40:01 | D | best error = [ 18.1859, 18.1859, 18.1859, 18.1859, 18.1859] +24-11-19 20:40:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:01 | D | sum error = [ 4068.4393, 4434.4894, 4831.4561, 5259.1033, 5719.1800] +24-11-19 20:40:01 | D | best error = [ 18.1859, 18.1859, 18.1859, 18.1859, 18.1859] +24-11-19 20:40:01 | D | + error = [18.1859] +24-11-19 20:40:01 | D | - Calibrating model.layers.30.self_attn.k_proj.weight +24-11-19 20:40:01 | D | + w: sint8 +24-11-19 20:40:01 | D | + x: None +24-11-19 20:40:01 | D | + y: None +24-11-19 20:40:01 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:40:01 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:40:01 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:40:01 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:40:02 | D | - range ratio = [ 1.0000] +24-11-19 20:40:02 | D | sum error = [ 21.8169] +24-11-19 20:40:02 | D | best error = [ 21.8169] +24-11-19 20:40:14 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:14 | D | sum error = [ 21.4127, 22.3766, 22.5542, 22.6159, 24.1290] +24-11-19 20:40:14 | D | best error = [ 21.4127, 21.4127, 21.4127, 21.4127, 21.4127] +24-11-19 20:40:14 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:14 | D | sum error = [ 23.3059, 25.8009, 25.0222, 27.4958, 30.5663] +24-11-19 20:40:14 | D | best error = [ 21.4127, 21.4127, 21.4127, 21.4127, 21.4127] +24-11-19 20:40:14 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:14 | D | sum error = [ 29.9733, 32.8808, 35.8706, 38.5439, 43.1604] +24-11-19 20:40:14 | D | best error = [ 21.4127, 21.4127, 21.4127, 21.4127, 21.4127] +24-11-19 20:40:14 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:14 | D | sum error = [ 43.0705, 45.4830, 50.8411, 52.7114, 57.8590] +24-11-19 20:40:14 | D | best error = [ 21.4127, 21.4127, 21.4127, 21.4127, 21.4127] +24-11-19 20:40:14 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:14 | D | sum error = [ 59.5377, 67.1069, 72.0300, 76.1085, 80.6789] +24-11-19 20:40:14 | D | best error = [ 21.4127, 21.4127, 21.4127, 21.4127, 21.4127] +24-11-19 20:40:14 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:14 | D | sum error = [ 87.5657, 96.2359, 104.4901, 111.3491, 119.2831] +24-11-19 20:40:14 | D | best error = [ 21.4127, 21.4127, 21.4127, 21.4127, 21.4127] +24-11-19 20:40:14 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:14 | D | sum error = [ 130.7644, 141.2964, 150.4541, 160.7450, 173.2418] +24-11-19 20:40:14 | D | best error = [ 21.4127, 21.4127, 21.4127, 21.4127, 21.4127] +24-11-19 20:40:14 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:14 | D | sum error = [ 186.6727, 202.3199, 214.3733, 232.4106, 248.1138] +24-11-19 20:40:14 | D | best error = [ 21.4127, 21.4127, 21.4127, 21.4127, 21.4127] +24-11-19 20:40:14 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:14 | D | sum error = [ 266.7319, 288.7261, 310.9440, 335.3271, 360.7195] +24-11-19 20:40:14 | D | best error = [ 21.4127, 21.4127, 21.4127, 21.4127, 21.4127] +24-11-19 20:40:14 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:14 | D | sum error = [ 387.2832, 419.1848, 450.4653, 485.3509, 525.0651] +24-11-19 20:40:14 | D | best error = [ 21.4127, 21.4127, 21.4127, 21.4127, 21.4127] +24-11-19 20:40:14 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:14 | D | sum error = [ 564.6602, 608.0566, 655.2967, 708.6855, 765.0254] +24-11-19 20:40:14 | D | best error = [ 21.4127, 21.4127, 21.4127, 21.4127, 21.4127] +24-11-19 20:40:14 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:14 | D | sum error = [ 823.3668, 887.5698, 957.0848, 1033.3492, 1112.6670] +24-11-19 20:40:14 | D | best error = [ 21.4127, 21.4127, 21.4127, 21.4127, 21.4127] +24-11-19 20:40:14 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:14 | D | sum error = [ 1202.7241, 1294.1424, 1395.4681, 1505.5192, 1627.8730] +24-11-19 20:40:14 | D | best error = [ 21.4127, 21.4127, 21.4127, 21.4127, 21.4127] +24-11-19 20:40:14 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:14 | D | sum error = [ 1763.3224, 1907.9199, 2065.8492, 2241.0170, 2429.1476] +24-11-19 20:40:14 | D | best error = [ 21.4127, 21.4127, 21.4127, 21.4127, 21.4127] +24-11-19 20:40:14 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:14 | D | sum error = [ 2634.4756, 2858.1380, 3096.5668, 3357.0293, 3637.9475] +24-11-19 20:40:14 | D | best error = [ 21.4127, 21.4127, 21.4127, 21.4127, 21.4127] +24-11-19 20:40:14 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:14 | D | sum error = [ 3945.2599, 4279.4009, 4646.3947, 5041.3562, 5463.6310] +24-11-19 20:40:14 | D | best error = [ 21.4127, 21.4127, 21.4127, 21.4127, 21.4127] +24-11-19 20:40:14 | D | + error = [21.4127] +24-11-19 20:40:15 | D | - Calibrating model.layers.30.self_attn.v_proj.weight +24-11-19 20:40:15 | D | + w: sint8 +24-11-19 20:40:15 | D | + x: None +24-11-19 20:40:15 | D | + y: None +24-11-19 20:40:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:15 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:40:15 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:40:15 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:40:15 | D | - range ratio = [ 1.0000] +24-11-19 20:40:15 | D | sum error = [ 9.5461] +24-11-19 20:40:15 | D | best error = [ 9.5461] +24-11-19 20:40:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:15 | D | sum error = [ 9.4696, 9.4379, 9.4999, 9.5575, 9.7636] +24-11-19 20:40:15 | D | best error = [ 8.7481, 8.4664, 8.3196, 8.2333, 8.1871] +24-11-19 20:40:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:15 | D | sum error = [ 10.0507, 10.3478, 10.7464, 11.2839, 11.8346] +24-11-19 20:40:15 | D | best error = [ 8.1664, 8.1560, 8.1528, 8.1519, 8.1518] +24-11-19 20:40:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:15 | D | sum error = [ 12.5296, 13.2980, 14.1315, 15.1045, 16.1400] +24-11-19 20:40:15 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 20:40:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:15 | D | sum error = [ 17.2535, 18.4391, 19.7514, 21.1642, 22.6931] +24-11-19 20:40:15 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 20:40:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:15 | D | sum error = [ 24.2955, 25.9902, 27.7819, 29.7242, 31.7998] +24-11-19 20:40:15 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 20:40:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:15 | D | sum error = [ 34.0004, 36.2799, 38.7410, 41.2800, 43.9640] +24-11-19 20:40:15 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 20:40:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:15 | D | sum error = [ 46.8254, 49.9100, 53.1169, 56.4660, 59.9709] +24-11-19 20:40:15 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 20:40:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:15 | D | sum error = [ 63.7424, 67.6544, 71.7302, 76.0514, 80.5506] +24-11-19 20:40:15 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 20:40:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:15 | D | sum error = [ 85.2361, 90.1960, 95.3682, 100.7918, 106.4843] +24-11-19 20:40:15 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 20:40:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:15 | D | sum error = [ 112.4326, 118.5882, 125.0926, 131.8876, 138.9843] +24-11-19 20:40:15 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 20:40:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:15 | D | sum error = [ 146.3604, 154.0479, 162.0886, 170.4678, 179.1706] +24-11-19 20:40:15 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 20:40:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:15 | D | sum error = [ 188.2525, 197.6967, 207.5106, 217.6976, 228.2820] +24-11-19 20:40:15 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 20:40:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:15 | D | sum error = [ 239.2714, 250.7128, 262.5387, 274.7975, 287.4820] +24-11-19 20:40:15 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 20:40:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:15 | D | sum error = [ 300.6031, 314.1688, 328.2184, 342.7216, 357.7000] +24-11-19 20:40:15 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 20:40:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:15 | D | sum error = [ 373.1790, 389.0887, 405.4823, 422.3678, 439.7411] +24-11-19 20:40:15 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 20:40:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:15 | D | sum error = [ 457.6245, 476.0235, 494.9600, 514.4400, 534.4477] +24-11-19 20:40:15 | D | best error = [ 8.1517, 8.1517, 8.1517, 8.1517, 8.1517] +24-11-19 20:40:15 | D | + error = [8.1517] +24-11-19 20:40:15 | D | - Calibrating model.layers.30.self_attn.o_proj.weight +24-11-19 20:40:15 | D | + w: sint8 +24-11-19 20:40:15 | D | + x: None +24-11-19 20:40:15 | D | + y: None +24-11-19 20:40:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:15 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:40:15 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:40:16 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:40:16 | D | - range ratio = [ 1.0000] +24-11-19 20:40:16 | D | sum error = [ 2.6061] +24-11-19 20:40:16 | D | best error = [ 2.6061] +24-11-19 20:40:16 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:16 | D | sum error = [ 2.5900, 2.5787, 2.5841, 2.6159, 2.6582] +24-11-19 20:40:16 | D | best error = [ 2.4314, 2.3505, 2.3034, 2.2755, 2.2550] +24-11-19 20:40:16 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:16 | D | sum error = [ 2.7085, 2.7932, 2.8921, 3.0157, 3.1569] +24-11-19 20:40:16 | D | best error = [ 2.2410, 2.2316, 2.2244, 2.2196, 2.2161] +24-11-19 20:40:16 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:16 | D | sum error = [ 3.3321, 3.5243, 3.7426, 3.9756, 4.2402] +24-11-19 20:40:16 | D | best error = [ 2.2132, 2.2105, 2.2090, 2.2078, 2.2067] +24-11-19 20:40:16 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:16 | D | sum error = [ 4.5243, 4.8444, 5.1829, 5.5376, 5.9341] +24-11-19 20:40:16 | D | best error = [ 2.2059, 2.2053, 2.2048, 2.2043, 2.2041] +24-11-19 20:40:16 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:16 | D | sum error = [ 6.3420, 6.7901, 7.2722, 7.7742, 8.3065] +24-11-19 20:40:16 | D | best error = [ 2.2040, 2.2040, 2.2040, 2.2039, 2.2038] +24-11-19 20:40:16 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:16 | D | sum error = [ 8.8688, 9.4676, 10.1197, 10.7974, 11.5127] +24-11-19 20:40:16 | D | best error = [ 2.2038, 2.2037, 2.2036, 2.2036, 2.2035] +24-11-19 20:40:16 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:16 | D | sum error = [ 12.2763, 13.0868, 13.9249, 14.8146, 15.7786] +24-11-19 20:40:16 | D | best error = [ 2.2035, 2.2035, 2.2035, 2.2035, 2.2035] +24-11-19 20:40:16 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:16 | D | sum error = [ 16.7856, 17.8429, 18.9672, 20.1414, 21.4071] +24-11-19 20:40:16 | D | best error = [ 2.2035, 2.2035, 2.2035, 2.2035, 2.2035] +24-11-19 20:40:16 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:16 | D | sum error = [ 22.7327, 24.1197, 25.5992, 27.1614, 28.7974] +24-11-19 20:40:16 | D | best error = [ 2.2035, 2.2035, 2.2035, 2.2035, 2.2035] +24-11-19 20:40:16 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:16 | D | sum error = [ 30.5266, 32.3528, 34.2728, 36.2951, 38.4197] +24-11-19 20:40:16 | D | best error = [ 2.2035, 2.2035, 2.2035, 2.2035, 2.2035] +24-11-19 20:40:16 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:16 | D | sum error = [ 40.6550, 42.9976, 45.4635, 48.0488, 50.7816] +24-11-19 20:40:16 | D | best error = [ 2.2035, 2.2035, 2.2035, 2.2035, 2.2035] +24-11-19 20:40:16 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:16 | D | sum error = [ 53.6389, 56.6364, 59.7760, 63.0721, 66.5189] +24-11-19 20:40:16 | D | best error = [ 2.2035, 2.2035, 2.2035, 2.2035, 2.2035] +24-11-19 20:40:16 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:16 | D | sum error = [ 70.1244, 73.9016, 77.8346, 81.9476, 86.2416] +24-11-19 20:40:16 | D | best error = [ 2.2035, 2.2035, 2.2035, 2.2035, 2.2035] +24-11-19 20:40:16 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:16 | D | sum error = [ 90.7137, 95.3820, 100.2449, 105.3198, 110.5871] +24-11-19 20:40:16 | D | best error = [ 2.2035, 2.2035, 2.2035, 2.2035, 2.2035] +24-11-19 20:40:16 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:16 | D | sum error = [ 116.0733, 121.7647, 127.6683, 133.7852, 140.1323] +24-11-19 20:40:16 | D | best error = [ 2.2035, 2.2035, 2.2035, 2.2035, 2.2035] +24-11-19 20:40:16 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:16 | D | sum error = [ 146.7004, 153.4981, 160.5233, 167.7676, 175.2492] +24-11-19 20:40:16 | D | best error = [ 2.2035, 2.2035, 2.2035, 2.2035, 2.2035] +24-11-19 20:40:16 | D | + error = [2.2035] +24-11-19 20:40:16 | D | - Calibrating model.layers.30.mlp.up_proj.weight +24-11-19 20:40:16 | D | + w: sint8 +24-11-19 20:40:16 | D | + x: None +24-11-19 20:40:16 | D | + y: None +24-11-19 20:40:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:16 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:40:16 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:40:16 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:40:16 | D | - range ratio = [ 1.0000] +24-11-19 20:40:16 | D | sum error = [ 12.3242] +24-11-19 20:40:16 | D | best error = [ 12.3242] +24-11-19 20:40:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:17 | D | sum error = [ 12.3252, 12.1767, 12.2689, 12.3683, 12.6233] +24-11-19 20:40:17 | D | best error = [ 11.2597, 10.8274, 10.6266, 10.4980, 10.4392] +24-11-19 20:40:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:17 | D | sum error = [ 12.9360, 13.3305, 13.9003, 14.5379, 15.3050] +24-11-19 20:40:17 | D | best error = [ 10.4119, 10.3977, 10.3922, 10.3905, 10.3898] +24-11-19 20:40:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:17 | D | sum error = [ 16.1750, 17.1666, 18.2483, 19.5097, 20.9477] +24-11-19 20:40:17 | D | best error = [ 10.3897, 10.3897, 10.3897, 10.3897, 10.3897] +24-11-19 20:40:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:17 | D | sum error = [ 22.3847, 23.9440, 25.7347, 27.5715, 29.6224] +24-11-19 20:40:17 | D | best error = [ 10.3897, 10.3897, 10.3897, 10.3897, 10.3897] +24-11-19 20:40:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:17 | D | sum error = [ 31.7302, 34.0583, 36.5025, 39.0721, 41.8412] +24-11-19 20:40:17 | D | best error = [ 10.3897, 10.3897, 10.3897, 10.3897, 10.3897] +24-11-19 20:40:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:17 | D | sum error = [ 44.7324, 47.9173, 51.1977, 54.7289, 58.4877] +24-11-19 20:40:17 | D | best error = [ 10.3897, 10.3897, 10.3897, 10.3897, 10.3897] +24-11-19 20:40:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:17 | D | sum error = [ 62.4566, 66.7301, 71.2294, 75.9134, 80.9335] +24-11-19 20:40:17 | D | best error = [ 10.3897, 10.3897, 10.3897, 10.3897, 10.3897] +24-11-19 20:40:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:17 | D | sum error = [ 86.2908, 91.8678, 97.8706, 104.1038, 110.7916] +24-11-19 20:40:17 | D | best error = [ 10.3897, 10.3897, 10.3897, 10.3897, 10.3897] +24-11-19 20:40:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:17 | D | sum error = [ 117.7827, 125.2061, 133.1683, 141.4855, 150.3866] +24-11-19 20:40:17 | D | best error = [ 10.3897, 10.3897, 10.3897, 10.3897, 10.3897] +24-11-19 20:40:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:17 | D | sum error = [ 159.7057, 169.6264, 179.9948, 191.0866, 202.7729] +24-11-19 20:40:17 | D | best error = [ 10.3897, 10.3897, 10.3897, 10.3897, 10.3897] +24-11-19 20:40:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:17 | D | sum error = [ 215.1772, 228.2208, 242.0312, 256.5091, 271.7828] +24-11-19 20:40:17 | D | best error = [ 10.3897, 10.3897, 10.3897, 10.3897, 10.3897] +24-11-19 20:40:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:17 | D | sum error = [ 288.1099, 305.2952, 323.1873, 342.0463, 361.9223] +24-11-19 20:40:17 | D | best error = [ 10.3897, 10.3897, 10.3897, 10.3897, 10.3897] +24-11-19 20:40:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:17 | D | sum error = [ 382.7501, 404.5839, 427.6644, 451.6443, 476.8166] +24-11-19 20:40:17 | D | best error = [ 10.3897, 10.3897, 10.3897, 10.3897, 10.3897] +24-11-19 20:40:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:17 | D | sum error = [ 502.9643, 530.7632, 559.5224, 589.2847, 620.0893] +24-11-19 20:40:17 | D | best error = [ 10.3897, 10.3897, 10.3897, 10.3897, 10.3897] +24-11-19 20:40:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:17 | D | sum error = [ 652.4968, 685.9521, 720.9297, 756.9156, 794.3259] +24-11-19 20:40:17 | D | best error = [ 10.3897, 10.3897, 10.3897, 10.3897, 10.3897] +24-11-19 20:40:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:17 | D | sum error = [ 832.7328, 872.5033, 913.7334, 956.1493, 1000.0784] +24-11-19 20:40:17 | D | best error = [ 10.3897, 10.3897, 10.3897, 10.3897, 10.3897] +24-11-19 20:40:17 | D | + error = [10.3897] +24-11-19 20:40:17 | D | - Calibrating model.layers.30.mlp.gate_proj.weight +24-11-19 20:40:17 | D | + w: sint8 +24-11-19 20:40:17 | D | + x: None +24-11-19 20:40:17 | D | + y: None +24-11-19 20:40:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:17 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:40:17 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:40:17 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:40:17 | D | - range ratio = [ 1.0000] +24-11-19 20:40:17 | D | sum error = [ 12.9603] +24-11-19 20:40:17 | D | best error = [ 12.9603] +24-11-19 20:40:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:18 | D | sum error = [ 12.8875, 12.7886, 12.8969, 13.0745, 13.3489] +24-11-19 20:40:18 | D | best error = [ 11.8081, 11.3882, 11.1639, 11.0530, 10.9921] +24-11-19 20:40:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:18 | D | sum error = [ 13.6185, 14.1123, 14.6523, 15.4776, 16.1459] +24-11-19 20:40:18 | D | best error = [ 10.9611, 10.9454, 10.9406, 10.9392, 10.9388] +24-11-19 20:40:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:18 | D | sum error = [ 17.1039, 18.2066, 19.3744, 20.7485, 22.1548] +24-11-19 20:40:18 | D | best error = [ 10.9387, 10.9387, 10.9387, 10.9387, 10.9387] +24-11-19 20:40:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:18 | D | sum error = [ 23.7389, 25.4037, 27.2486, 29.2128, 31.3503] +24-11-19 20:40:18 | D | best error = [ 10.9387, 10.9387, 10.9387, 10.9387, 10.9387] +24-11-19 20:40:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:18 | D | sum error = [ 33.6432, 36.0671, 38.6114, 41.3945, 44.2976] +24-11-19 20:40:18 | D | best error = [ 10.9387, 10.9387, 10.9387, 10.9387, 10.9387] +24-11-19 20:40:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:18 | D | sum error = [ 47.5015, 50.7653, 54.4209, 58.1746, 62.1447] +24-11-19 20:40:18 | D | best error = [ 10.9387, 10.9387, 10.9387, 10.9387, 10.9387] +24-11-19 20:40:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:18 | D | sum error = [ 66.2923, 70.9244, 75.6617, 80.7577, 86.1100] +24-11-19 20:40:18 | D | best error = [ 10.9387, 10.9387, 10.9387, 10.9387, 10.9387] +24-11-19 20:40:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:18 | D | sum error = [ 91.7596, 97.7387, 104.0788, 110.7900, 117.9180] +24-11-19 20:40:18 | D | best error = [ 10.9387, 10.9387, 10.9387, 10.9387, 10.9387] +24-11-19 20:40:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:18 | D | sum error = [ 125.5229, 133.4358, 141.7953, 150.8251, 160.3218] +24-11-19 20:40:18 | D | best error = [ 10.9387, 10.9387, 10.9387, 10.9387, 10.9387] +24-11-19 20:40:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:18 | D | sum error = [ 170.3156, 180.9884, 192.1407, 204.0177, 216.5600] +24-11-19 20:40:18 | D | best error = [ 10.9387, 10.9387, 10.9387, 10.9387, 10.9387] +24-11-19 20:40:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:18 | D | sum error = [ 229.8288, 243.8650, 258.7934, 274.4648, 291.0073] +24-11-19 20:40:18 | D | best error = [ 10.9387, 10.9387, 10.9387, 10.9387, 10.9387] +24-11-19 20:40:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:18 | D | sum error = [ 308.5570, 327.0028, 346.0669, 366.4767, 387.8517] +24-11-19 20:40:18 | D | best error = [ 10.9387, 10.9387, 10.9387, 10.9387, 10.9387] +24-11-19 20:40:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:18 | D | sum error = [ 410.3856, 433.7867, 458.5576, 484.1233, 510.9755] +24-11-19 20:40:18 | D | best error = [ 10.9387, 10.9387, 10.9387, 10.9387, 10.9387] +24-11-19 20:40:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:18 | D | sum error = [ 539.1226, 568.4818, 598.8122, 630.8868, 664.3230] +24-11-19 20:40:18 | D | best error = [ 10.9387, 10.9387, 10.9387, 10.9387, 10.9387] +24-11-19 20:40:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:18 | D | sum error = [ 699.1024, 735.3248, 772.7415, 811.4176, 851.4620] +24-11-19 20:40:18 | D | best error = [ 10.9387, 10.9387, 10.9387, 10.9387, 10.9387] +24-11-19 20:40:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:18 | D | sum error = [ 893.0247, 935.7489, 980.2202, 1026.0596, 1073.1305] +24-11-19 20:40:18 | D | best error = [ 10.9387, 10.9387, 10.9387, 10.9387, 10.9387] +24-11-19 20:40:18 | D | + error = [10.9387] +24-11-19 20:40:19 | D | - Calibrating model.layers.30.mlp.down_proj.weight +24-11-19 20:40:19 | D | + w: sint8 +24-11-19 20:40:19 | D | + x: None +24-11-19 20:40:19 | D | + y: None +24-11-19 20:40:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:19 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:40:19 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:40:19 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:40:19 | D | - range ratio = [ 1.0000] +24-11-19 20:40:19 | D | sum error = [ 32.8978] +24-11-19 20:40:19 | D | best error = [ 32.8978] +24-11-19 20:40:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:20 | D | sum error = [ 32.9690, 32.3607, 32.4943, 31.9701, 32.3439] +24-11-19 20:40:20 | D | best error = [ 22.0486, 17.6657, 15.1497, 13.3116, 12.0917] +24-11-19 20:40:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:20 | D | sum error = [ 31.3452, 30.5339, 30.4174, 29.7758, 29.6996] +24-11-19 20:40:20 | D | best error = [ 11.0594, 10.2998, 9.7456, 9.3140, 8.9732] +24-11-19 20:40:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:20 | D | sum error = [ 29.8893, 29.0795, 29.0871, 28.9878, 28.4300] +24-11-19 20:40:20 | D | best error = [ 8.7931, 8.6060, 8.4592, 8.3573, 8.2532] +24-11-19 20:40:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:20 | D | sum error = [ 28.4205, 28.4123, 27.8240, 27.8570, 27.6374] +24-11-19 20:40:20 | D | best error = [ 8.1850, 8.1290, 8.0915, 8.0531, 8.0235] +24-11-19 20:40:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:20 | D | sum error = [ 27.5663, 27.6019, 26.9745, 26.9319, 27.0187] +24-11-19 20:40:20 | D | best error = [ 8.0040, 7.9930, 7.9820, 7.9738, 7.9681] +24-11-19 20:40:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:20 | D | sum error = [ 27.3168, 27.5247, 27.6386, 27.9657, 27.8252] +24-11-19 20:40:20 | D | best error = [ 7.9655, 7.9630, 7.9615, 7.9608, 7.9608] +24-11-19 20:40:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:20 | D | sum error = [ 28.3964, 29.2196, 29.5049, 30.3171, 31.1041] +24-11-19 20:40:20 | D | best error = [ 7.9599, 7.9595, 7.9593, 7.9593, 7.9593] +24-11-19 20:40:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:20 | D | sum error = [ 32.1273, 32.9382, 34.4205, 35.6016, 37.1954] +24-11-19 20:40:20 | D | best error = [ 7.9593, 7.9589, 7.9589, 7.9589, 7.9589] +24-11-19 20:40:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:20 | D | sum error = [ 39.0219, 40.7876, 42.9147, 45.2821, 48.0451] +24-11-19 20:40:20 | D | best error = [ 7.9589, 7.9589, 7.9589, 7.9589, 7.9589] +24-11-19 20:40:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:20 | D | sum error = [ 51.4196, 55.6446, 61.0299, 68.1186, 77.1280] +24-11-19 20:40:20 | D | best error = [ 7.9589, 7.9589, 7.9589, 7.9589, 7.9589] +24-11-19 20:40:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:20 | D | sum error = [ 89.5592, 105.0866, 125.2469, 150.7279, 182.8427] +24-11-19 20:40:20 | D | best error = [ 7.9589, 7.9589, 7.9589, 7.9589, 7.9589] +24-11-19 20:40:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:20 | D | sum error = [ 222.3174, 270.3638, 327.3151, 392.9133, 467.4097] +24-11-19 20:40:20 | D | best error = [ 7.9589, 7.9589, 7.9589, 7.9589, 7.9589] +24-11-19 20:40:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:20 | D | sum error = [ 550.8609, 642.7022, 742.3136, 849.0750, 961.9444] +24-11-19 20:40:20 | D | best error = [ 7.9589, 7.9589, 7.9589, 7.9589, 7.9589] +24-11-19 20:40:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:20 | D | sum error = [ 1079.9285, 1202.7164, 1329.3425, 1459.1750, 1591.1760] +24-11-19 20:40:20 | D | best error = [ 7.9589, 7.9589, 7.9589, 7.9589, 7.9589] +24-11-19 20:40:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:20 | D | sum error = [ 1725.3889, 1861.3800, 1998.7443, 2137.2997, 2276.8676] +24-11-19 20:40:20 | D | best error = [ 7.9589, 7.9589, 7.9589, 7.9589, 7.9589] +24-11-19 20:40:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:20 | D | sum error = [ 2417.3596, 2558.6107, 2700.5554, 2843.0277, 2986.1260] +24-11-19 20:40:20 | D | best error = [ 7.9589, 7.9589, 7.9589, 7.9589, 7.9589] +24-11-19 20:40:20 | D | + error = [7.9589] +24-11-19 20:40:20 | D | - Quantizing model.layers.30.self_attn.q_proj.weight +24-11-19 20:40:21 | D | - Quantizing model.layers.30.self_attn.k_proj.weight +24-11-19 20:40:21 | D | - Quantizing model.layers.30.self_attn.v_proj.weight +24-11-19 20:40:22 | D | - Quantizing model.layers.30.self_attn.o_proj.weight +24-11-19 20:40:23 | D | - Quantizing model.layers.30.mlp.up_proj.weight +24-11-19 20:40:24 | D | - Quantizing model.layers.30.mlp.gate_proj.weight +24-11-19 20:40:25 | D | - Quantizing model.layers.30.mlp.down_proj.weight +24-11-19 20:40:33 | D | - Quantizing layer model.layers.31 +24-11-19 20:40:33 | D | - Calibrating model.layers.31.self_attn.q_proj.weight +24-11-19 20:40:33 | D | + w: sint8 +24-11-19 20:40:33 | D | + x: None +24-11-19 20:40:33 | D | + y: None +24-11-19 20:40:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:40:33 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:40:33 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:40:33 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:40:34 | D | - range ratio = [ 1.0000] +24-11-19 20:40:34 | D | sum error = [ 15.2371] +24-11-19 20:40:34 | D | best error = [ 15.2371] +24-11-19 20:40:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:46 | D | sum error = [ 15.1539, 14.8553, 15.4217, 15.8780, 15.7386] +24-11-19 20:40:46 | D | best error = [ 15.1539, 14.8553, 14.8553, 14.8553, 14.8553] +24-11-19 20:40:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:46 | D | sum error = [ 16.4910, 17.5876, 17.5219, 20.1505, 21.8811] +24-11-19 20:40:46 | D | best error = [ 14.8553, 14.8553, 14.8553, 14.8553, 14.8553] +24-11-19 20:40:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:46 | D | sum error = [ 23.1651, 24.2956, 27.6677, 29.2359, 31.9046] +24-11-19 20:40:46 | D | best error = [ 14.8553, 14.8553, 14.8553, 14.8553, 14.8553] +24-11-19 20:40:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:46 | D | sum error = [ 36.0807, 39.7034, 41.9633, 46.7785, 51.9896] +24-11-19 20:40:46 | D | best error = [ 14.8553, 14.8553, 14.8553, 14.8553, 14.8553] +24-11-19 20:40:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:46 | D | sum error = [ 56.2202, 61.8591, 65.4054, 72.0158, 78.5694] +24-11-19 20:40:46 | D | best error = [ 14.8553, 14.8553, 14.8553, 14.8553, 14.8553] +24-11-19 20:40:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:46 | D | sum error = [ 85.2659, 92.7227, 100.1210, 106.4871, 115.9498] +24-11-19 20:40:46 | D | best error = [ 14.8553, 14.8553, 14.8553, 14.8553, 14.8553] +24-11-19 20:40:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:46 | D | sum error = [ 123.6041, 133.1311, 143.0763, 152.9122, 165.8797] +24-11-19 20:40:46 | D | best error = [ 14.8553, 14.8553, 14.8553, 14.8553, 14.8553] +24-11-19 20:40:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:46 | D | sum error = [ 177.9261, 191.1900, 206.0952, 221.0014, 238.6195] +24-11-19 20:40:46 | D | best error = [ 14.8553, 14.8553, 14.8553, 14.8553, 14.8553] +24-11-19 20:40:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:46 | D | sum error = [ 257.2141, 276.7253, 298.1929, 322.3401, 347.2082] +24-11-19 20:40:46 | D | best error = [ 14.8553, 14.8553, 14.8553, 14.8553, 14.8553] +24-11-19 20:40:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:46 | D | sum error = [ 374.3973, 403.3427, 433.8748, 466.6563, 501.0349] +24-11-19 20:40:46 | D | best error = [ 14.8553, 14.8553, 14.8553, 14.8553, 14.8553] +24-11-19 20:40:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:46 | D | sum error = [ 538.6956, 578.3721, 620.6976, 667.5261, 716.7906] +24-11-19 20:40:46 | D | best error = [ 14.8553, 14.8553, 14.8553, 14.8553, 14.8553] +24-11-19 20:40:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:46 | D | sum error = [ 769.6959, 826.8786, 886.6662, 952.7809, 1021.1696] +24-11-19 20:40:46 | D | best error = [ 14.8553, 14.8553, 14.8553, 14.8553, 14.8553] +24-11-19 20:40:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:46 | D | sum error = [ 1096.4732, 1176.4942, 1261.9662, 1354.2801, 1453.8634] +24-11-19 20:40:46 | D | best error = [ 14.8553, 14.8553, 14.8553, 14.8553, 14.8553] +24-11-19 20:40:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:46 | D | sum error = [ 1561.2716, 1675.6964, 1799.6947, 1932.4988, 2074.5172] +24-11-19 20:40:46 | D | best error = [ 14.8553, 14.8553, 14.8553, 14.8553, 14.8553] +24-11-19 20:40:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:46 | D | sum error = [ 2226.5417, 2387.7612, 2560.9725, 2746.2707, 2944.9837] +24-11-19 20:40:46 | D | best error = [ 14.8553, 14.8553, 14.8553, 14.8553, 14.8553] +24-11-19 20:40:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:46 | D | sum error = [ 3157.3441, 3385.0069, 3628.1477, 3888.5128, 4166.6161] +24-11-19 20:40:46 | D | best error = [ 14.8553, 14.8553, 14.8553, 14.8553, 14.8553] +24-11-19 20:40:46 | D | + error = [14.8553] +24-11-19 20:40:47 | D | - Calibrating model.layers.31.self_attn.k_proj.weight +24-11-19 20:40:47 | D | + w: sint8 +24-11-19 20:40:47 | D | + x: None +24-11-19 20:40:47 | D | + y: None +24-11-19 20:40:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:40:47 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:40:47 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:40:47 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:40:47 | D | - range ratio = [ 1.0000] +24-11-19 20:40:47 | D | sum error = [ 19.7682] +24-11-19 20:40:47 | D | best error = [ 19.7682] +24-11-19 20:41:00 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:00 | D | sum error = [ 21.5936, 20.4607, 19.5901, 19.7116, 21.7477] +24-11-19 20:41:00 | D | best error = [ 19.7682, 19.7682, 19.5901, 19.5901, 19.5901] +24-11-19 20:41:00 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:00 | D | sum error = [ 20.4767, 22.8913, 21.6609, 24.1928, 26.6987] +24-11-19 20:41:00 | D | best error = [ 19.5901, 19.5901, 19.5901, 19.5901, 19.5901] +24-11-19 20:41:00 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:00 | D | sum error = [ 30.1640, 29.7762, 30.0072, 32.6615, 41.6155] +24-11-19 20:41:00 | D | best error = [ 19.5901, 19.5901, 19.5901, 19.5901, 19.5901] +24-11-19 20:41:00 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:00 | D | sum error = [ 40.2324, 46.5775, 50.0245, 53.9867, 60.4884] +24-11-19 20:41:00 | D | best error = [ 19.5901, 19.5901, 19.5901, 19.5901, 19.5901] +24-11-19 20:41:00 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:00 | D | sum error = [ 64.7885, 68.2641, 73.8083, 81.4244, 93.9287] +24-11-19 20:41:00 | D | best error = [ 19.5901, 19.5901, 19.5901, 19.5901, 19.5901] +24-11-19 20:41:00 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:00 | D | sum error = [ 98.0316, 105.2030, 112.4923, 121.4477, 129.0696] +24-11-19 20:41:00 | D | best error = [ 19.5901, 19.5901, 19.5901, 19.5901, 19.5901] +24-11-19 20:41:00 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:00 | D | sum error = [ 139.5876, 145.5448, 159.3276, 169.6346, 179.8258] +24-11-19 20:41:00 | D | best error = [ 19.5901, 19.5901, 19.5901, 19.5901, 19.5901] +24-11-19 20:41:00 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:00 | D | sum error = [ 191.2198, 203.6664, 220.0498, 236.0932, 253.2902] +24-11-19 20:41:00 | D | best error = [ 19.5901, 19.5901, 19.5901, 19.5901, 19.5901] +24-11-19 20:41:00 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:00 | D | sum error = [ 270.2614, 286.3589, 305.5289, 322.5137, 343.6233] +24-11-19 20:41:00 | D | best error = [ 19.5901, 19.5901, 19.5901, 19.5901, 19.5901] +24-11-19 20:41:00 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:00 | D | sum error = [ 366.4474, 390.9312, 421.1095, 448.8965, 480.0136] +24-11-19 20:41:00 | D | best error = [ 19.5901, 19.5901, 19.5901, 19.5901, 19.5901] +24-11-19 20:41:00 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:00 | D | sum error = [ 514.0959, 550.7839, 592.0377, 634.0556, 682.9305] +24-11-19 20:41:00 | D | best error = [ 19.5901, 19.5901, 19.5901, 19.5901, 19.5901] +24-11-19 20:41:00 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:00 | D | sum error = [ 734.6198, 789.2446, 848.0200, 911.6553, 978.8802] +24-11-19 20:41:00 | D | best error = [ 19.5901, 19.5901, 19.5901, 19.5901, 19.5901] +24-11-19 20:41:00 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:00 | D | sum error = [ 1050.7932, 1127.8801, 1210.2576, 1303.0715, 1401.3590] +24-11-19 20:41:00 | D | best error = [ 19.5901, 19.5901, 19.5901, 19.5901, 19.5901] +24-11-19 20:41:00 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:00 | D | sum error = [ 1510.6155, 1627.7828, 1750.6241, 1886.7760, 2031.8477] +24-11-19 20:41:00 | D | best error = [ 19.5901, 19.5901, 19.5901, 19.5901, 19.5901] +24-11-19 20:41:00 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:00 | D | sum error = [ 2189.4333, 2360.6211, 2543.2664, 2738.9984, 2951.6538] +24-11-19 20:41:00 | D | best error = [ 19.5901, 19.5901, 19.5901, 19.5901, 19.5901] +24-11-19 20:41:00 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:00 | D | sum error = [ 3176.6325, 3419.4973, 3680.2242, 3959.9780, 4254.9519] +24-11-19 20:41:00 | D | best error = [ 19.5901, 19.5901, 19.5901, 19.5901, 19.5901] +24-11-19 20:41:00 | D | + error = [19.5901] +24-11-19 20:41:00 | D | - Calibrating model.layers.31.self_attn.v_proj.weight +24-11-19 20:41:00 | D | + w: sint8 +24-11-19 20:41:00 | D | + x: None +24-11-19 20:41:00 | D | + y: None +24-11-19 20:41:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:00 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:41:00 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:41:00 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:41:00 | D | - range ratio = [ 1.0000] +24-11-19 20:41:00 | D | sum error = [ 7.1424] +24-11-19 20:41:00 | D | best error = [ 7.1424] +24-11-19 20:41:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:01 | D | sum error = [ 7.0744, 7.0773, 7.1224, 7.1759, 7.3251] +24-11-19 20:41:01 | D | best error = [ 6.5571, 6.3479, 6.2429, 6.1820, 6.1502] +24-11-19 20:41:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:01 | D | sum error = [ 7.4905, 7.7636, 8.0270, 8.4424, 8.8788] +24-11-19 20:41:01 | D | best error = [ 6.1349, 6.1277, 6.1246, 6.1237, 6.1236] +24-11-19 20:41:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:01 | D | sum error = [ 9.3645, 9.9785, 10.5790, 11.2911, 12.0628] +24-11-19 20:41:01 | D | best error = [ 6.1236, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:41:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:01 | D | sum error = [ 12.9323, 13.8330, 14.8188, 15.8854, 17.0364] +24-11-19 20:41:01 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:41:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:01 | D | sum error = [ 18.2383, 19.5469, 20.8742, 22.3204, 23.8822] +24-11-19 20:41:01 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:41:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:01 | D | sum error = [ 25.4860, 27.2179, 29.0509, 30.9616, 32.9825] +24-11-19 20:41:01 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:41:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:01 | D | sum error = [ 35.1288, 37.4126, 39.8029, 42.3101, 44.9295] +24-11-19 20:41:01 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:41:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:01 | D | sum error = [ 47.7153, 50.6458, 53.7063, 56.9327, 60.3290] +24-11-19 20:41:01 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:41:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:01 | D | sum error = [ 63.8692, 67.6154, 71.5235, 75.6103, 79.8985] +24-11-19 20:41:01 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:41:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:01 | D | sum error = [ 84.3821, 89.0937, 94.0277, 99.1445, 104.5051] +24-11-19 20:41:01 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:41:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:01 | D | sum error = [ 110.1022, 115.9349, 121.9910, 128.3107, 134.9469] +24-11-19 20:41:01 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:41:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:01 | D | sum error = [ 141.8059, 148.9295, 156.3556, 164.0506, 172.0322] +24-11-19 20:41:01 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:41:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:01 | D | sum error = [ 180.3179, 188.9339, 197.8604, 207.0748, 216.6350] +24-11-19 20:41:01 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:41:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:01 | D | sum error = [ 226.4944, 236.6879, 247.2242, 258.1079, 269.3416] +24-11-19 20:41:01 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:41:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:01 | D | sum error = [ 280.9380, 292.8799, 305.2137, 317.8902, 330.9914] +24-11-19 20:41:01 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:41:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:01 | D | sum error = [ 344.4592, 358.3469, 372.6139, 387.2950, 402.3754] +24-11-19 20:41:01 | D | best error = [ 6.1235, 6.1235, 6.1235, 6.1235, 6.1235] +24-11-19 20:41:01 | D | + error = [6.1235] +24-11-19 20:41:01 | D | - Calibrating model.layers.31.self_attn.o_proj.weight +24-11-19 20:41:01 | D | + w: sint8 +24-11-19 20:41:01 | D | + x: None +24-11-19 20:41:01 | D | + y: None +24-11-19 20:41:01 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:01 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:41:01 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:41:01 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:41:01 | D | - range ratio = [ 1.0000] +24-11-19 20:41:01 | D | sum error = [ 3.3449] +24-11-19 20:41:01 | D | best error = [ 3.3449] +24-11-19 20:41:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:01 | D | sum error = [ 3.2880, 3.3084, 3.3384, 3.3735, 3.4694] +24-11-19 20:41:01 | D | best error = [ 3.0144, 2.8869, 2.8132, 2.7661, 2.7321] +24-11-19 20:41:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:01 | D | sum error = [ 3.5928, 3.7290, 3.9168, 4.1598, 4.4175] +24-11-19 20:41:01 | D | best error = [ 2.7110, 2.6920, 2.6784, 2.6697, 2.6629] +24-11-19 20:41:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:01 | D | sum error = [ 4.7292, 5.0611, 5.4465, 5.8580, 6.3157] +24-11-19 20:41:01 | D | best error = [ 2.6590, 2.6559, 2.6537, 2.6520, 2.6508] +24-11-19 20:41:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:01 | D | sum error = [ 6.8184, 7.3365, 7.9452, 8.6000, 9.2753] +24-11-19 20:41:01 | D | best error = [ 2.6501, 2.6496, 2.6492, 2.6488, 2.6484] +24-11-19 20:41:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:01 | D | sum error = [ 10.0464, 10.8303, 11.7164, 12.6362, 13.6574] +24-11-19 20:41:01 | D | best error = [ 2.6483, 2.6481, 2.6481, 2.6480, 2.6480] +24-11-19 20:41:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:01 | D | sum error = [ 14.7154, 15.8551, 17.1138, 18.4421, 19.9039] +24-11-19 20:41:01 | D | best error = [ 2.6480, 2.6480, 2.6480, 2.6480, 2.6480] +24-11-19 20:41:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:01 | D | sum error = [ 21.4330, 23.0953, 24.8684, 26.7891, 28.8358] +24-11-19 20:41:01 | D | best error = [ 2.6480, 2.6480, 2.6480, 2.6480, 2.6480] +24-11-19 20:41:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:01 | D | sum error = [ 31.0379, 33.3637, 35.8903, 38.5515, 41.4380] +24-11-19 20:41:01 | D | best error = [ 2.6480, 2.6480, 2.6480, 2.6480, 2.6480] +24-11-19 20:41:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:01 | D | sum error = [ 44.5095, 47.7720, 51.2593, 54.9660, 58.9441] +24-11-19 20:41:01 | D | best error = [ 2.6480, 2.6480, 2.6480, 2.6480, 2.6480] +24-11-19 20:41:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:01 | D | sum error = [ 63.1728, 67.6697, 72.4368, 77.5149, 82.8970] +24-11-19 20:41:01 | D | best error = [ 2.6480, 2.6480, 2.6480, 2.6480, 2.6480] +24-11-19 20:41:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:01 | D | sum error = [ 88.6103, 94.6450, 101.0399, 107.7961, 114.9569] +24-11-19 20:41:01 | D | best error = [ 2.6480, 2.6480, 2.6480, 2.6480, 2.6480] +24-11-19 20:41:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:01 | D | sum error = [ 122.5029, 130.4750, 138.8858, 147.7503, 157.0813] +24-11-19 20:41:01 | D | best error = [ 2.6480, 2.6480, 2.6480, 2.6480, 2.6480] +24-11-19 20:41:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:01 | D | sum error = [ 166.9002, 177.2356, 188.0648, 199.4146, 211.2985] +24-11-19 20:41:01 | D | best error = [ 2.6480, 2.6480, 2.6480, 2.6480, 2.6480] +24-11-19 20:41:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:01 | D | sum error = [ 223.7428, 236.7446, 250.3111, 264.4778, 279.1946] +24-11-19 20:41:01 | D | best error = [ 2.6480, 2.6480, 2.6480, 2.6480, 2.6480] +24-11-19 20:41:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:01 | D | sum error = [ 294.5179, 310.4643, 327.0009, 344.1544, 361.9548] +24-11-19 20:41:01 | D | best error = [ 2.6480, 2.6480, 2.6480, 2.6480, 2.6480] +24-11-19 20:41:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:01 | D | sum error = [ 380.3790, 399.4486, 419.1604, 439.5211, 460.5157] +24-11-19 20:41:01 | D | best error = [ 2.6480, 2.6480, 2.6480, 2.6480, 2.6480] +24-11-19 20:41:01 | D | + error = [2.6480] +24-11-19 20:41:01 | D | - Calibrating model.layers.31.mlp.up_proj.weight +24-11-19 20:41:01 | D | + w: sint8 +24-11-19 20:41:01 | D | + x: None +24-11-19 20:41:01 | D | + y: None +24-11-19 20:41:01 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:01 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:41:01 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:41:02 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:41:02 | D | - range ratio = [ 1.0000] +24-11-19 20:41:02 | D | sum error = [ 11.4362] +24-11-19 20:41:02 | D | best error = [ 11.4362] +24-11-19 20:41:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:03 | D | sum error = [ 11.3801, 11.3373, 11.3944, 11.5109, 11.7399] +24-11-19 20:41:03 | D | best error = [ 10.4755, 10.1291, 9.9467, 9.8412, 9.7828] +24-11-19 20:41:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:03 | D | sum error = [ 12.0181, 12.4805, 12.9880, 13.5757, 14.3252] +24-11-19 20:41:03 | D | best error = [ 9.7557, 9.7435, 9.7389, 9.7374, 9.7371] +24-11-19 20:41:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:03 | D | sum error = [ 15.1336, 16.1375, 17.1925, 18.3537, 19.6643] +24-11-19 20:41:03 | D | best error = [ 9.7371, 9.7369, 9.7369, 9.7369, 9.7369] +24-11-19 20:41:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:03 | D | sum error = [ 21.0823, 22.6088, 24.2968, 26.1390, 28.0552] +24-11-19 20:41:03 | D | best error = [ 9.7369, 9.7369, 9.7369, 9.7369, 9.7369] +24-11-19 20:41:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:03 | D | sum error = [ 30.1305, 32.3244, 34.7170, 37.2659, 40.0404] +24-11-19 20:41:03 | D | best error = [ 9.7369, 9.7369, 9.7369, 9.7369, 9.7369] +24-11-19 20:41:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:03 | D | sum error = [ 42.9118, 46.0273, 49.3455, 52.8253, 56.6084] +24-11-19 20:41:03 | D | best error = [ 9.7369, 9.7369, 9.7369, 9.7369, 9.7369] +24-11-19 20:41:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:03 | D | sum error = [ 60.6301, 64.8815, 69.4927, 74.2719, 79.3567] +24-11-19 20:41:03 | D | best error = [ 9.7369, 9.7369, 9.7369, 9.7369, 9.7369] +24-11-19 20:41:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:03 | D | sum error = [ 84.7713, 90.6695, 96.8729, 103.4131, 110.4608] +24-11-19 20:41:03 | D | best error = [ 9.7369, 9.7369, 9.7369, 9.7369, 9.7369] +24-11-19 20:41:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:03 | D | sum error = [ 117.9619, 125.8754, 134.3420, 143.2978, 152.8258] +24-11-19 20:41:03 | D | best error = [ 9.7369, 9.7369, 9.7369, 9.7369, 9.7369] +24-11-19 20:41:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:03 | D | sum error = [ 163.0102, 173.7662, 185.1849, 197.3238, 210.1791] +24-11-19 20:41:03 | D | best error = [ 9.7369, 9.7369, 9.7369, 9.7369, 9.7369] +24-11-19 20:41:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:03 | D | sum error = [ 223.8615, 238.2732, 253.5430, 269.7557, 286.8808] +24-11-19 20:41:03 | D | best error = [ 9.7369, 9.7369, 9.7369, 9.7369, 9.7369] +24-11-19 20:41:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:03 | D | sum error = [ 305.0076, 324.1650, 344.3322, 365.5898, 388.0438] +24-11-19 20:41:03 | D | best error = [ 9.7369, 9.7369, 9.7369, 9.7369, 9.7369] +24-11-19 20:41:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:03 | D | sum error = [ 411.6698, 436.4165, 462.5494, 489.9278, 518.6309] +24-11-19 20:41:03 | D | best error = [ 9.7369, 9.7369, 9.7369, 9.7369, 9.7369] +24-11-19 20:41:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:03 | D | sum error = [ 548.7249, 580.1833, 613.1517, 647.5569, 683.3905] +24-11-19 20:41:03 | D | best error = [ 9.7369, 9.7369, 9.7369, 9.7369, 9.7369] +24-11-19 20:41:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:03 | D | sum error = [ 720.8566, 759.8903, 800.5257, 842.7346, 886.5449] +24-11-19 20:41:03 | D | best error = [ 9.7369, 9.7369, 9.7369, 9.7369, 9.7369] +24-11-19 20:41:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:03 | D | sum error = [ 931.9450, 979.0582, 1027.7541, 1078.0879, 1130.0295] +24-11-19 20:41:03 | D | best error = [ 9.7369, 9.7369, 9.7369, 9.7369, 9.7369] +24-11-19 20:41:03 | D | + error = [9.7369] +24-11-19 20:41:03 | D | - Calibrating model.layers.31.mlp.gate_proj.weight +24-11-19 20:41:03 | D | + w: sint8 +24-11-19 20:41:03 | D | + x: None +24-11-19 20:41:03 | D | + y: None +24-11-19 20:41:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:03 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:41:03 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:41:03 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:41:03 | D | - range ratio = [ 1.0000] +24-11-19 20:41:03 | D | sum error = [ 12.1307] +24-11-19 20:41:03 | D | best error = [ 12.1307] +24-11-19 20:41:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:04 | D | sum error = [ 12.0060, 11.9939, 12.0392, 12.2104, 12.4274] +24-11-19 20:41:04 | D | best error = [ 11.0944, 10.7178, 10.5276, 10.4182, 10.3636] +24-11-19 20:41:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:04 | D | sum error = [ 12.7498, 13.2101, 13.7165, 14.3704, 15.1647] +24-11-19 20:41:04 | D | best error = [ 10.3360, 10.3237, 10.3185, 10.3169, 10.3168] +24-11-19 20:41:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:04 | D | sum error = [ 16.0521, 17.0469, 18.1591, 19.5131, 20.8492] +24-11-19 20:41:04 | D | best error = [ 10.3168, 10.3167, 10.3167, 10.3167, 10.3167] +24-11-19 20:41:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:04 | D | sum error = [ 22.3880, 24.0358, 25.8354, 27.7377, 29.8159] +24-11-19 20:41:04 | D | best error = [ 10.3167, 10.3167, 10.3167, 10.3167, 10.3167] +24-11-19 20:41:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:04 | D | sum error = [ 32.0539, 34.4056, 37.0357, 39.7634, 42.6579] +24-11-19 20:41:04 | D | best error = [ 10.3167, 10.3167, 10.3167, 10.3167, 10.3167] +24-11-19 20:41:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:04 | D | sum error = [ 45.7445, 49.0990, 52.6145, 56.2893, 60.3421] +24-11-19 20:41:04 | D | best error = [ 10.3167, 10.3167, 10.3167, 10.3167, 10.3167] +24-11-19 20:41:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:04 | D | sum error = [ 64.5849, 69.0634, 73.8517, 78.9261, 84.3786] +24-11-19 20:41:04 | D | best error = [ 10.3167, 10.3167, 10.3167, 10.3167, 10.3167] +24-11-19 20:41:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:04 | D | sum error = [ 90.1025, 96.2208, 102.7144, 109.5851, 116.9501] +24-11-19 20:41:04 | D | best error = [ 10.3167, 10.3167, 10.3167, 10.3167, 10.3167] +24-11-19 20:41:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:04 | D | sum error = [ 124.7798, 133.0861, 141.8784, 151.3133, 161.2278] +24-11-19 20:41:04 | D | best error = [ 10.3167, 10.3167, 10.3167, 10.3167, 10.3167] +24-11-19 20:41:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:04 | D | sum error = [ 171.8630, 183.1146, 195.0721, 207.7823, 221.2471] +24-11-19 20:41:04 | D | best error = [ 10.3167, 10.3167, 10.3167, 10.3167, 10.3167] +24-11-19 20:41:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:04 | D | sum error = [ 235.4832, 250.6927, 266.7387, 283.7276, 301.6990] +24-11-19 20:41:04 | D | best error = [ 10.3167, 10.3167, 10.3167, 10.3167, 10.3167] +24-11-19 20:41:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:04 | D | sum error = [ 320.6541, 340.7290, 361.8278, 384.1081, 407.5042] +24-11-19 20:41:04 | D | best error = [ 10.3167, 10.3167, 10.3167, 10.3167, 10.3167] +24-11-19 20:41:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:04 | D | sum error = [ 432.2061, 458.0983, 485.3620, 513.9551, 543.9751] +24-11-19 20:41:04 | D | best error = [ 10.3167, 10.3167, 10.3167, 10.3167, 10.3167] +24-11-19 20:41:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:04 | D | sum error = [ 575.4402, 608.4092, 642.7482, 678.5965, 716.0775] +24-11-19 20:41:04 | D | best error = [ 10.3167, 10.3167, 10.3167, 10.3167, 10.3167] +24-11-19 20:41:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:04 | D | sum error = [ 755.1239, 795.7149, 837.9932, 881.8479, 927.3544] +24-11-19 20:41:04 | D | best error = [ 10.3167, 10.3167, 10.3167, 10.3167, 10.3167] +24-11-19 20:41:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:04 | D | sum error = [ 974.4099, 1023.0917, 1073.4140, 1125.3335, 1178.8549] +24-11-19 20:41:04 | D | best error = [ 10.3167, 10.3167, 10.3167, 10.3167, 10.3167] +24-11-19 20:41:04 | D | + error = [10.3167] +24-11-19 20:41:04 | D | - Calibrating model.layers.31.mlp.down_proj.weight +24-11-19 20:41:04 | D | + w: sint8 +24-11-19 20:41:04 | D | + x: None +24-11-19 20:41:04 | D | + y: None +24-11-19 20:41:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:04 | D | + finished parsing calibration arguments, ram usage: 38.6 +24-11-19 20:41:04 | D | + finished reseting calibrator, ram usage: 38.6 +24-11-19 20:41:04 | D | + finished calculating the original outputs, ram usage: 38.6 +24-11-19 20:41:04 | D | - range ratio = [ 1.0000] +24-11-19 20:41:04 | D | sum error = [ 16.3835] +24-11-19 20:41:04 | D | best error = [ 16.3835] +24-11-19 20:41:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:05 | D | sum error = [ 16.2094, 15.9903, 15.8524, 15.7856, 15.5113] +24-11-19 20:41:05 | D | best error = [ 14.5014, 13.7495, 13.2804, 12.9802, 12.7382] +24-11-19 20:41:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:05 | D | sum error = [ 15.4306, 15.3098, 15.2456, 15.0519, 14.8328] +24-11-19 20:41:05 | D | best error = [ 12.5498, 12.3805, 12.2459, 12.1247, 12.0089] +24-11-19 20:41:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:05 | D | sum error = [ 14.8775, 14.8836, 14.7519, 14.7281, 14.8264] +24-11-19 20:41:05 | D | best error = [ 11.9109, 11.8185, 11.7318, 11.6582, 11.5955] +24-11-19 20:41:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:05 | D | sum error = [ 14.6994, 14.6707, 14.8970, 14.9792, 15.0449] +24-11-19 20:41:05 | D | best error = [ 11.5401, 11.4997, 11.4671, 11.4408, 11.4108] +24-11-19 20:41:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:05 | D | sum error = [ 15.3778, 15.6149, 16.0407, 16.4447, 16.8750] +24-11-19 20:41:05 | D | best error = [ 11.3911, 11.3779, 11.3650, 11.3551, 11.3469] +24-11-19 20:41:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:05 | D | sum error = [ 17.5235, 18.1309, 18.8945, 19.7706, 20.7008] +24-11-19 20:41:05 | D | best error = [ 11.3428, 11.3368, 11.3349, 11.3324, 11.3305] +24-11-19 20:41:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:05 | D | sum error = [ 21.7752, 22.9283, 24.2380, 25.6676, 27.2480] +24-11-19 20:41:05 | D | best error = [ 11.3297, 11.3287, 11.3286, 11.3285, 11.3284] +24-11-19 20:41:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:05 | D | sum error = [ 28.9904, 30.8888, 32.8893, 35.1153, 37.5538] +24-11-19 20:41:05 | D | best error = [ 11.3284, 11.3281, 11.3281, 11.3280, 11.3280] +24-11-19 20:41:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:05 | D | sum error = [ 40.1533, 43.0014, 46.0978, 49.3571, 52.9468] +24-11-19 20:41:05 | D | best error = [ 11.3280, 11.3277, 11.3277, 11.3277, 11.3277] +24-11-19 20:41:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:05 | D | sum error = [ 56.7611, 60.9189, 65.4354, 70.3009, 75.5276] +24-11-19 20:41:05 | D | best error = [ 11.3277, 11.3277, 11.3277, 11.3277, 11.3277] +24-11-19 20:41:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:05 | D | sum error = [ 81.2379, 87.3157, 93.9750, 101.2386, 109.0256] +24-11-19 20:41:05 | D | best error = [ 11.3277, 11.3277, 11.3277, 11.3277, 11.3277] +24-11-19 20:41:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:05 | D | sum error = [ 117.5112, 126.7874, 136.9220, 147.8714, 159.8490] +24-11-19 20:41:05 | D | best error = [ 11.3277, 11.3277, 11.3277, 11.3277, 11.3277] +24-11-19 20:41:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:05 | D | sum error = [ 172.9562, 187.0931, 202.5697, 219.4414, 237.7707] +24-11-19 20:41:05 | D | best error = [ 11.3277, 11.3277, 11.3277, 11.3277, 11.3277] +24-11-19 20:41:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:05 | D | sum error = [ 257.6714, 279.2117, 302.6179, 327.8104, 355.0336] +24-11-19 20:41:05 | D | best error = [ 11.3277, 11.3277, 11.3277, 11.3277, 11.3277] +24-11-19 20:41:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:05 | D | sum error = [ 384.4737, 416.1944, 450.3415, 486.9515, 526.2646] +24-11-19 20:41:05 | D | best error = [ 11.3277, 11.3277, 11.3277, 11.3277, 11.3277] +24-11-19 20:41:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:05 | D | sum error = [ 568.3728, 613.4461, 661.5994, 712.9002, 767.5885] +24-11-19 20:41:05 | D | best error = [ 11.3277, 11.3277, 11.3277, 11.3277, 11.3277] +24-11-19 20:41:05 | D | + error = [11.3277] +24-11-19 20:41:05 | D | - Quantizing model.layers.31.self_attn.q_proj.weight +24-11-19 20:41:06 | D | - Quantizing model.layers.31.self_attn.k_proj.weight +24-11-19 20:41:07 | D | - Quantizing model.layers.31.self_attn.v_proj.weight +24-11-19 20:41:08 | D | - Quantizing model.layers.31.self_attn.o_proj.weight +24-11-19 20:41:08 | D | - Quantizing model.layers.31.mlp.up_proj.weight +24-11-19 20:41:09 | D | - Quantizing model.layers.31.mlp.gate_proj.weight +24-11-19 20:41:10 | D | - Quantizing model.layers.31.mlp.down_proj.weight +24-11-19 20:41:13 | I | - Saving weight quantizer settings to runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-2-7b-instruct-together-32k.pt +24-11-19 20:41:13 | I | - Linking weight quantizer settings to runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.201608.RUNNING/model/wgts.pt +24-11-19 20:41:13 | I | - Saving model checkpoint to runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.201608.RUNNING/model +24-11-19 20:41:28 | I | * Quantizing activations +24-11-19 20:41:28 | I | - Generating activation quantizer settings +24-11-19 20:41:28 | D | Starting new HTTPS connection (4): huggingface.co:443 +24-11-19 20:41:34 | D | Starting new HTTPS connection (5): huggingface.co:443 +24-11-19 20:41:46 | D | Starting new HTTPS connection (2): s3.amazonaws.com:443 +24-11-19 20:41:58 | W | Repo card metadata block was not found. Setting CardData to empty. +24-11-19 20:41:58 | D | Starting new HTTPS connection (6): huggingface.co:443 +24-11-19 20:42:10 | W | Using the latest cached version of the dataset since mit-han-lab/pile-val-backup couldn't be found on the Hugging Face Hub +24-11-19 20:42:10 | W | Found the latest cached dataset configuration 'default' at /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4 (last modified on Tue Oct 8 18:58:39 2024). +24-11-19 20:42:10 | D | Attempting to acquire lock 23438672412944 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:42:10 | D | Lock 23438672412944 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:42:10 | D | open file: /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4/dataset_info.json +24-11-19 20:42:10 | D | Attempting to release lock 23438672412944 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:42:10 | D | Lock 23438672412944 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:42:23 | D | - Quantizing layer model.layers.0 +24-11-19 20:42:23 | D | - Calibrating model.layers.0.self_attn.v_proj.input +24-11-19 20:42:23 | D | - Calibrating model.layers.0.self_attn.k_rotary_emb.output +24-11-19 20:42:23 | D | + w: None +24-11-19 20:42:23 | D | + x: None +24-11-19 20:42:23 | D | + y: sint8 +24-11-19 20:42:23 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:42:23 | D | + finished parsing calibration arguments, ram usage: 38.8 +24-11-19 20:42:24 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:42:24 | D | - range ratio = [ 1.0000] +24-11-19 20:42:24 | D | sum error = [ 1.7409] +24-11-19 20:42:24 | D | best error = [ 1.7409] +24-11-19 20:42:24 | D | + error = [1.7409] +24-11-19 20:42:24 | D | - Calibrating model.layers.0.self_attn.v_proj.output +24-11-19 20:42:24 | D | + w: None +24-11-19 20:42:24 | D | + x: None +24-11-19 20:42:24 | D | + y: sint8 +24-11-19 20:42:24 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:42:24 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:42:25 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:42:25 | D | - range ratio = [ 1.0000] +24-11-19 20:42:25 | D | sum error = [ 2.0075] +24-11-19 20:42:25 | D | best error = [ 2.0075] +24-11-19 20:42:25 | D | + error = [2.0075] +24-11-19 20:42:25 | D | - Calibrating model.layers.0.self_attn.o_proj.input +24-11-19 20:42:25 | D | - Calibrating model.layers.0.mlp.up_proj.input +24-11-19 20:42:25 | D | - Calibrating model.layers.0.mlp.down_proj.input +24-11-19 20:42:26 | D | - Quantizing model.layers.0.self_attn.q_proj (inputs) +24-11-19 20:42:26 | D | - Quantizing model.layers.0.self_attn.k_proj (inputs) +24-11-19 20:42:26 | D | - Quantizing model.layers.0.self_attn.v_proj (inputs and outputs) +24-11-19 20:42:26 | D | - Quantizing model.layers.0.self_attn.o_proj (inputs) +24-11-19 20:42:26 | D | - Quantizing model.layers.0.self_attn.k_rotary_emb (outputs) +24-11-19 20:42:26 | D | - Quantizing model.layers.0.mlp.gate_proj (inputs) +24-11-19 20:42:26 | D | - Quantizing model.layers.0.mlp.up_proj (inputs) +24-11-19 20:42:26 | D | - Quantizing model.layers.0.mlp.down_proj (inputs) +24-11-19 20:42:33 | D | - Quantizing layer model.layers.1 +24-11-19 20:42:33 | D | - Calibrating model.layers.1.self_attn.v_proj.input +24-11-19 20:42:33 | D | - Calibrating model.layers.1.self_attn.k_rotary_emb.output +24-11-19 20:42:33 | D | + w: None +24-11-19 20:42:33 | D | + x: None +24-11-19 20:42:33 | D | + y: sint8 +24-11-19 20:42:33 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:42:33 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:42:33 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:42:34 | D | - range ratio = [ 1.0000] +24-11-19 20:42:34 | D | sum error = [ 7.9433] +24-11-19 20:42:34 | D | best error = [ 7.9433] +24-11-19 20:42:34 | D | + error = [7.9433] +24-11-19 20:42:34 | D | - Calibrating model.layers.1.self_attn.v_proj.output +24-11-19 20:42:34 | D | + w: None +24-11-19 20:42:34 | D | + x: None +24-11-19 20:42:34 | D | + y: sint8 +24-11-19 20:42:34 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:42:34 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:42:34 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:42:35 | D | - range ratio = [ 1.0000] +24-11-19 20:42:35 | D | sum error = [ 6.5824] +24-11-19 20:42:35 | D | best error = [ 6.5824] +24-11-19 20:42:35 | D | + error = [6.5824] +24-11-19 20:42:35 | D | - Calibrating model.layers.1.self_attn.o_proj.input +24-11-19 20:42:35 | D | - Calibrating model.layers.1.mlp.up_proj.input +24-11-19 20:42:35 | D | - Calibrating model.layers.1.mlp.down_proj.input +24-11-19 20:42:35 | D | - Quantizing model.layers.1.self_attn.q_proj (inputs) +24-11-19 20:42:35 | D | - Quantizing model.layers.1.self_attn.k_proj (inputs) +24-11-19 20:42:35 | D | - Quantizing model.layers.1.self_attn.v_proj (inputs and outputs) +24-11-19 20:42:35 | D | - Quantizing model.layers.1.self_attn.o_proj (inputs) +24-11-19 20:42:35 | D | - Quantizing model.layers.1.self_attn.k_rotary_emb (outputs) +24-11-19 20:42:35 | D | - Quantizing model.layers.1.mlp.gate_proj (inputs) +24-11-19 20:42:35 | D | - Quantizing model.layers.1.mlp.up_proj (inputs) +24-11-19 20:42:35 | D | - Quantizing model.layers.1.mlp.down_proj (inputs) +24-11-19 20:42:42 | D | - Quantizing layer model.layers.2 +24-11-19 20:42:42 | D | - Calibrating model.layers.2.self_attn.v_proj.input +24-11-19 20:42:42 | D | - Calibrating model.layers.2.self_attn.k_rotary_emb.output +24-11-19 20:42:42 | D | + w: None +24-11-19 20:42:42 | D | + x: None +24-11-19 20:42:42 | D | + y: sint8 +24-11-19 20:42:42 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:42:42 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:42:43 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:42:43 | D | - range ratio = [ 1.0000] +24-11-19 20:42:43 | D | sum error = [ 30.9935] +24-11-19 20:42:43 | D | best error = [ 30.9935] +24-11-19 20:42:43 | D | + error = [30.9935] +24-11-19 20:42:43 | D | - Calibrating model.layers.2.self_attn.v_proj.output +24-11-19 20:42:43 | D | + w: None +24-11-19 20:42:43 | D | + x: None +24-11-19 20:42:43 | D | + y: sint8 +24-11-19 20:42:43 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:42:43 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:42:44 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:42:44 | D | - range ratio = [ 1.0000] +24-11-19 20:42:44 | D | sum error = [ 54.3443] +24-11-19 20:42:44 | D | best error = [ 54.3443] +24-11-19 20:42:44 | D | + error = [54.3443] +24-11-19 20:42:44 | D | - Calibrating model.layers.2.self_attn.o_proj.input +24-11-19 20:42:44 | D | - Calibrating model.layers.2.mlp.up_proj.input +24-11-19 20:42:44 | D | - Calibrating model.layers.2.mlp.down_proj.input +24-11-19 20:42:45 | D | - Quantizing model.layers.2.self_attn.q_proj (inputs) +24-11-19 20:42:45 | D | - Quantizing model.layers.2.self_attn.k_proj (inputs) +24-11-19 20:42:45 | D | - Quantizing model.layers.2.self_attn.v_proj (inputs and outputs) +24-11-19 20:42:45 | D | - Quantizing model.layers.2.self_attn.o_proj (inputs) +24-11-19 20:42:45 | D | - Quantizing model.layers.2.self_attn.k_rotary_emb (outputs) +24-11-19 20:42:45 | D | - Quantizing model.layers.2.mlp.gate_proj (inputs) +24-11-19 20:42:45 | D | - Quantizing model.layers.2.mlp.up_proj (inputs) +24-11-19 20:42:45 | D | - Quantizing model.layers.2.mlp.down_proj (inputs) +24-11-19 20:42:51 | D | - Quantizing layer model.layers.3 +24-11-19 20:42:51 | D | - Calibrating model.layers.3.self_attn.v_proj.input +24-11-19 20:42:51 | D | - Calibrating model.layers.3.self_attn.k_rotary_emb.output +24-11-19 20:42:51 | D | + w: None +24-11-19 20:42:51 | D | + x: None +24-11-19 20:42:51 | D | + y: sint8 +24-11-19 20:42:51 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:42:51 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:42:52 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:42:52 | D | - range ratio = [ 1.0000] +24-11-19 20:42:52 | D | sum error = [ 35.8843] +24-11-19 20:42:52 | D | best error = [ 35.8843] +24-11-19 20:42:52 | D | + error = [35.8843] +24-11-19 20:42:52 | D | - Calibrating model.layers.3.self_attn.v_proj.output +24-11-19 20:42:52 | D | + w: None +24-11-19 20:42:52 | D | + x: None +24-11-19 20:42:52 | D | + y: sint8 +24-11-19 20:42:52 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:42:52 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:42:53 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:42:53 | D | - range ratio = [ 1.0000] +24-11-19 20:42:53 | D | sum error = [ 78.7585] +24-11-19 20:42:53 | D | best error = [ 78.7585] +24-11-19 20:42:53 | D | + error = [78.7585] +24-11-19 20:42:53 | D | - Calibrating model.layers.3.self_attn.o_proj.input +24-11-19 20:42:53 | D | - Calibrating model.layers.3.mlp.up_proj.input +24-11-19 20:42:54 | D | - Calibrating model.layers.3.mlp.down_proj.input +24-11-19 20:42:54 | D | - Quantizing model.layers.3.self_attn.q_proj (inputs) +24-11-19 20:42:54 | D | - Quantizing model.layers.3.self_attn.k_proj (inputs) +24-11-19 20:42:54 | D | - Quantizing model.layers.3.self_attn.v_proj (inputs and outputs) +24-11-19 20:42:54 | D | - Quantizing model.layers.3.self_attn.o_proj (inputs) +24-11-19 20:42:54 | D | - Quantizing model.layers.3.self_attn.k_rotary_emb (outputs) +24-11-19 20:42:54 | D | - Quantizing model.layers.3.mlp.gate_proj (inputs) +24-11-19 20:42:54 | D | - Quantizing model.layers.3.mlp.up_proj (inputs) +24-11-19 20:42:54 | D | - Quantizing model.layers.3.mlp.down_proj (inputs) +24-11-19 20:43:00 | D | - Quantizing layer model.layers.4 +24-11-19 20:43:00 | D | - Calibrating model.layers.4.self_attn.v_proj.input +24-11-19 20:43:00 | D | - Calibrating model.layers.4.self_attn.k_rotary_emb.output +24-11-19 20:43:00 | D | + w: None +24-11-19 20:43:00 | D | + x: None +24-11-19 20:43:00 | D | + y: sint8 +24-11-19 20:43:00 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:00 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:43:01 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:43:01 | D | - range ratio = [ 1.0000] +24-11-19 20:43:01 | D | sum error = [ 53.2453] +24-11-19 20:43:01 | D | best error = [ 53.2453] +24-11-19 20:43:01 | D | + error = [53.2453] +24-11-19 20:43:01 | D | - Calibrating model.layers.4.self_attn.v_proj.output +24-11-19 20:43:01 | D | + w: None +24-11-19 20:43:01 | D | + x: None +24-11-19 20:43:01 | D | + y: sint8 +24-11-19 20:43:01 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:01 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:43:02 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:43:02 | D | - range ratio = [ 1.0000] +24-11-19 20:43:02 | D | sum error = [ 120.3323] +24-11-19 20:43:02 | D | best error = [ 120.3323] +24-11-19 20:43:02 | D | + error = [120.3323] +24-11-19 20:43:03 | D | - Calibrating model.layers.4.self_attn.o_proj.input +24-11-19 20:43:03 | D | - Calibrating model.layers.4.mlp.up_proj.input +24-11-19 20:43:03 | D | - Calibrating model.layers.4.mlp.down_proj.input +24-11-19 20:43:03 | D | - Quantizing model.layers.4.self_attn.q_proj (inputs) +24-11-19 20:43:03 | D | - Quantizing model.layers.4.self_attn.k_proj (inputs) +24-11-19 20:43:03 | D | - Quantizing model.layers.4.self_attn.v_proj (inputs and outputs) +24-11-19 20:43:03 | D | - Quantizing model.layers.4.self_attn.o_proj (inputs) +24-11-19 20:43:03 | D | - Quantizing model.layers.4.self_attn.k_rotary_emb (outputs) +24-11-19 20:43:03 | D | - Quantizing model.layers.4.mlp.gate_proj (inputs) +24-11-19 20:43:03 | D | - Quantizing model.layers.4.mlp.up_proj (inputs) +24-11-19 20:43:03 | D | - Quantizing model.layers.4.mlp.down_proj (inputs) +24-11-19 20:43:09 | D | - Quantizing layer model.layers.5 +24-11-19 20:43:09 | D | - Calibrating model.layers.5.self_attn.v_proj.input +24-11-19 20:43:09 | D | - Calibrating model.layers.5.self_attn.k_rotary_emb.output +24-11-19 20:43:09 | D | + w: None +24-11-19 20:43:09 | D | + x: None +24-11-19 20:43:09 | D | + y: sint8 +24-11-19 20:43:09 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:09 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:43:10 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:43:10 | D | - range ratio = [ 1.0000] +24-11-19 20:43:10 | D | sum error = [ 56.6263] +24-11-19 20:43:10 | D | best error = [ 56.6263] +24-11-19 20:43:10 | D | + error = [56.6263] +24-11-19 20:43:10 | D | - Calibrating model.layers.5.self_attn.v_proj.output +24-11-19 20:43:10 | D | + w: None +24-11-19 20:43:10 | D | + x: None +24-11-19 20:43:10 | D | + y: sint8 +24-11-19 20:43:10 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:10 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:43:11 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:43:11 | D | - range ratio = [ 1.0000] +24-11-19 20:43:11 | D | sum error = [ 95.8392] +24-11-19 20:43:11 | D | best error = [ 95.8392] +24-11-19 20:43:11 | D | + error = [95.8392] +24-11-19 20:43:11 | D | - Calibrating model.layers.5.self_attn.o_proj.input +24-11-19 20:43:12 | D | - Calibrating model.layers.5.mlp.up_proj.input +24-11-19 20:43:12 | D | - Calibrating model.layers.5.mlp.down_proj.input +24-11-19 20:43:12 | D | - Quantizing model.layers.5.self_attn.q_proj (inputs) +24-11-19 20:43:12 | D | - Quantizing model.layers.5.self_attn.k_proj (inputs) +24-11-19 20:43:12 | D | - Quantizing model.layers.5.self_attn.v_proj (inputs and outputs) +24-11-19 20:43:12 | D | - Quantizing model.layers.5.self_attn.o_proj (inputs) +24-11-19 20:43:12 | D | - Quantizing model.layers.5.self_attn.k_rotary_emb (outputs) +24-11-19 20:43:12 | D | - Quantizing model.layers.5.mlp.gate_proj (inputs) +24-11-19 20:43:12 | D | - Quantizing model.layers.5.mlp.up_proj (inputs) +24-11-19 20:43:12 | D | - Quantizing model.layers.5.mlp.down_proj (inputs) +24-11-19 20:43:18 | D | - Quantizing layer model.layers.6 +24-11-19 20:43:18 | D | - Calibrating model.layers.6.self_attn.v_proj.input +24-11-19 20:43:18 | D | - Calibrating model.layers.6.self_attn.k_rotary_emb.output +24-11-19 20:43:18 | D | + w: None +24-11-19 20:43:18 | D | + x: None +24-11-19 20:43:18 | D | + y: sint8 +24-11-19 20:43:18 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:18 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:43:19 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:43:19 | D | - range ratio = [ 1.0000] +24-11-19 20:43:19 | D | sum error = [ 57.9241] +24-11-19 20:43:19 | D | best error = [ 57.9241] +24-11-19 20:43:19 | D | + error = [57.9241] +24-11-19 20:43:19 | D | - Calibrating model.layers.6.self_attn.v_proj.output +24-11-19 20:43:19 | D | + w: None +24-11-19 20:43:19 | D | + x: None +24-11-19 20:43:19 | D | + y: sint8 +24-11-19 20:43:19 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:19 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:43:20 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:43:20 | D | - range ratio = [ 1.0000] +24-11-19 20:43:20 | D | sum error = [ 80.4585] +24-11-19 20:43:20 | D | best error = [ 80.4585] +24-11-19 20:43:20 | D | + error = [80.4585] +24-11-19 20:43:20 | D | - Calibrating model.layers.6.self_attn.o_proj.input +24-11-19 20:43:21 | D | - Calibrating model.layers.6.mlp.up_proj.input +24-11-19 20:43:21 | D | - Calibrating model.layers.6.mlp.down_proj.input +24-11-19 20:43:21 | D | - Quantizing model.layers.6.self_attn.q_proj (inputs) +24-11-19 20:43:21 | D | - Quantizing model.layers.6.self_attn.k_proj (inputs) +24-11-19 20:43:21 | D | - Quantizing model.layers.6.self_attn.v_proj (inputs and outputs) +24-11-19 20:43:21 | D | - Quantizing model.layers.6.self_attn.o_proj (inputs) +24-11-19 20:43:21 | D | - Quantizing model.layers.6.self_attn.k_rotary_emb (outputs) +24-11-19 20:43:21 | D | - Quantizing model.layers.6.mlp.gate_proj (inputs) +24-11-19 20:43:21 | D | - Quantizing model.layers.6.mlp.up_proj (inputs) +24-11-19 20:43:21 | D | - Quantizing model.layers.6.mlp.down_proj (inputs) +24-11-19 20:43:27 | D | - Quantizing layer model.layers.7 +24-11-19 20:43:27 | D | - Calibrating model.layers.7.self_attn.v_proj.input +24-11-19 20:43:27 | D | - Calibrating model.layers.7.self_attn.k_rotary_emb.output +24-11-19 20:43:27 | D | + w: None +24-11-19 20:43:27 | D | + x: None +24-11-19 20:43:27 | D | + y: sint8 +24-11-19 20:43:27 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:27 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:43:27 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:43:28 | D | - range ratio = [ 1.0000] +24-11-19 20:43:28 | D | sum error = [ 66.9550] +24-11-19 20:43:28 | D | best error = [ 66.9550] +24-11-19 20:43:28 | D | + error = [66.9550] +24-11-19 20:43:28 | D | - Calibrating model.layers.7.self_attn.v_proj.output +24-11-19 20:43:28 | D | + w: None +24-11-19 20:43:28 | D | + x: None +24-11-19 20:43:28 | D | + y: sint8 +24-11-19 20:43:28 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:28 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:43:29 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:43:29 | D | - range ratio = [ 1.0000] +24-11-19 20:43:29 | D | sum error = [ 90.4935] +24-11-19 20:43:29 | D | best error = [ 90.4935] +24-11-19 20:43:29 | D | + error = [90.4935] +24-11-19 20:43:29 | D | - Calibrating model.layers.7.self_attn.o_proj.input +24-11-19 20:43:29 | D | - Calibrating model.layers.7.mlp.up_proj.input +24-11-19 20:43:29 | D | - Calibrating model.layers.7.mlp.down_proj.input +24-11-19 20:43:29 | D | - Quantizing model.layers.7.self_attn.q_proj (inputs) +24-11-19 20:43:29 | D | - Quantizing model.layers.7.self_attn.k_proj (inputs) +24-11-19 20:43:29 | D | - Quantizing model.layers.7.self_attn.v_proj (inputs and outputs) +24-11-19 20:43:29 | D | - Quantizing model.layers.7.self_attn.o_proj (inputs) +24-11-19 20:43:29 | D | - Quantizing model.layers.7.self_attn.k_rotary_emb (outputs) +24-11-19 20:43:29 | D | - Quantizing model.layers.7.mlp.gate_proj (inputs) +24-11-19 20:43:29 | D | - Quantizing model.layers.7.mlp.up_proj (inputs) +24-11-19 20:43:29 | D | - Quantizing model.layers.7.mlp.down_proj (inputs) +24-11-19 20:43:36 | D | - Quantizing layer model.layers.8 +24-11-19 20:43:36 | D | - Calibrating model.layers.8.self_attn.v_proj.input +24-11-19 20:43:36 | D | - Calibrating model.layers.8.self_attn.k_rotary_emb.output +24-11-19 20:43:36 | D | + w: None +24-11-19 20:43:36 | D | + x: None +24-11-19 20:43:36 | D | + y: sint8 +24-11-19 20:43:36 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:36 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:43:37 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:43:37 | D | - range ratio = [ 1.0000] +24-11-19 20:43:37 | D | sum error = [ 76.5372] +24-11-19 20:43:37 | D | best error = [ 76.5372] +24-11-19 20:43:37 | D | + error = [76.5372] +24-11-19 20:43:37 | D | - Calibrating model.layers.8.self_attn.v_proj.output +24-11-19 20:43:37 | D | + w: None +24-11-19 20:43:37 | D | + x: None +24-11-19 20:43:37 | D | + y: sint8 +24-11-19 20:43:37 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:37 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:43:38 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:43:38 | D | - range ratio = [ 1.0000] +24-11-19 20:43:38 | D | sum error = [ 79.7578] +24-11-19 20:43:38 | D | best error = [ 79.7578] +24-11-19 20:43:38 | D | + error = [79.7578] +24-11-19 20:43:39 | D | - Calibrating model.layers.8.self_attn.o_proj.input +24-11-19 20:43:39 | D | - Calibrating model.layers.8.mlp.up_proj.input +24-11-19 20:43:39 | D | - Calibrating model.layers.8.mlp.down_proj.input +24-11-19 20:43:39 | D | - Quantizing model.layers.8.self_attn.q_proj (inputs) +24-11-19 20:43:39 | D | - Quantizing model.layers.8.self_attn.k_proj (inputs) +24-11-19 20:43:39 | D | - Quantizing model.layers.8.self_attn.v_proj (inputs and outputs) +24-11-19 20:43:39 | D | - Quantizing model.layers.8.self_attn.o_proj (inputs) +24-11-19 20:43:39 | D | - Quantizing model.layers.8.self_attn.k_rotary_emb (outputs) +24-11-19 20:43:39 | D | - Quantizing model.layers.8.mlp.gate_proj (inputs) +24-11-19 20:43:39 | D | - Quantizing model.layers.8.mlp.up_proj (inputs) +24-11-19 20:43:39 | D | - Quantizing model.layers.8.mlp.down_proj (inputs) +24-11-19 20:43:45 | D | - Quantizing layer model.layers.9 +24-11-19 20:43:45 | D | - Calibrating model.layers.9.self_attn.v_proj.input +24-11-19 20:43:45 | D | - Calibrating model.layers.9.self_attn.k_rotary_emb.output +24-11-19 20:43:45 | D | + w: None +24-11-19 20:43:45 | D | + x: None +24-11-19 20:43:45 | D | + y: sint8 +24-11-19 20:43:45 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:45 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:43:46 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:43:46 | D | - range ratio = [ 1.0000] +24-11-19 20:43:46 | D | sum error = [ 92.4531] +24-11-19 20:43:46 | D | best error = [ 92.4531] +24-11-19 20:43:46 | D | + error = [92.4531] +24-11-19 20:43:46 | D | - Calibrating model.layers.9.self_attn.v_proj.output +24-11-19 20:43:46 | D | + w: None +24-11-19 20:43:46 | D | + x: None +24-11-19 20:43:46 | D | + y: sint8 +24-11-19 20:43:46 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:46 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:43:47 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:43:47 | D | - range ratio = [ 1.0000] +24-11-19 20:43:47 | D | sum error = [ 128.2043] +24-11-19 20:43:47 | D | best error = [ 128.2043] +24-11-19 20:43:47 | D | + error = [128.2043] +24-11-19 20:43:47 | D | - Calibrating model.layers.9.self_attn.o_proj.input +24-11-19 20:43:47 | D | - Calibrating model.layers.9.mlp.up_proj.input +24-11-19 20:43:48 | D | - Calibrating model.layers.9.mlp.down_proj.input +24-11-19 20:43:48 | D | - Quantizing model.layers.9.self_attn.q_proj (inputs) +24-11-19 20:43:48 | D | - Quantizing model.layers.9.self_attn.k_proj (inputs) +24-11-19 20:43:48 | D | - Quantizing model.layers.9.self_attn.v_proj (inputs and outputs) +24-11-19 20:43:48 | D | - Quantizing model.layers.9.self_attn.o_proj (inputs) +24-11-19 20:43:48 | D | - Quantizing model.layers.9.self_attn.k_rotary_emb (outputs) +24-11-19 20:43:48 | D | - Quantizing model.layers.9.mlp.gate_proj (inputs) +24-11-19 20:43:48 | D | - Quantizing model.layers.9.mlp.up_proj (inputs) +24-11-19 20:43:48 | D | - Quantizing model.layers.9.mlp.down_proj (inputs) +24-11-19 20:43:54 | D | - Quantizing layer model.layers.10 +24-11-19 20:43:54 | D | - Calibrating model.layers.10.self_attn.v_proj.input +24-11-19 20:43:54 | D | - Calibrating model.layers.10.self_attn.k_rotary_emb.output +24-11-19 20:43:54 | D | + w: None +24-11-19 20:43:54 | D | + x: None +24-11-19 20:43:54 | D | + y: sint8 +24-11-19 20:43:54 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:54 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:43:55 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:43:56 | D | - range ratio = [ 1.0000] +24-11-19 20:43:56 | D | sum error = [ 93.3313] +24-11-19 20:43:56 | D | best error = [ 93.3313] +24-11-19 20:43:56 | D | + error = [93.3313] +24-11-19 20:43:56 | D | - Calibrating model.layers.10.self_attn.v_proj.output +24-11-19 20:43:56 | D | + w: None +24-11-19 20:43:56 | D | + x: None +24-11-19 20:43:56 | D | + y: sint8 +24-11-19 20:43:56 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:56 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:43:56 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:43:57 | D | - range ratio = [ 1.0000] +24-11-19 20:43:57 | D | sum error = [ 148.6232] +24-11-19 20:43:57 | D | best error = [ 148.6232] +24-11-19 20:43:57 | D | + error = [148.6232] +24-11-19 20:43:57 | D | - Calibrating model.layers.10.self_attn.o_proj.input +24-11-19 20:43:57 | D | - Calibrating model.layers.10.mlp.up_proj.input +24-11-19 20:43:57 | D | - Calibrating model.layers.10.mlp.down_proj.input +24-11-19 20:43:57 | D | - Quantizing model.layers.10.self_attn.q_proj (inputs) +24-11-19 20:43:57 | D | - Quantizing model.layers.10.self_attn.k_proj (inputs) +24-11-19 20:43:57 | D | - Quantizing model.layers.10.self_attn.v_proj (inputs and outputs) +24-11-19 20:43:57 | D | - Quantizing model.layers.10.self_attn.o_proj (inputs) +24-11-19 20:43:57 | D | - Quantizing model.layers.10.self_attn.k_rotary_emb (outputs) +24-11-19 20:43:57 | D | - Quantizing model.layers.10.mlp.gate_proj (inputs) +24-11-19 20:43:57 | D | - Quantizing model.layers.10.mlp.up_proj (inputs) +24-11-19 20:43:57 | D | - Quantizing model.layers.10.mlp.down_proj (inputs) +24-11-19 20:44:04 | D | - Quantizing layer model.layers.11 +24-11-19 20:44:04 | D | - Calibrating model.layers.11.self_attn.v_proj.input +24-11-19 20:44:04 | D | - Calibrating model.layers.11.self_attn.k_rotary_emb.output +24-11-19 20:44:04 | D | + w: None +24-11-19 20:44:04 | D | + x: None +24-11-19 20:44:04 | D | + y: sint8 +24-11-19 20:44:04 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:04 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:44:04 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:44:05 | D | - range ratio = [ 1.0000] +24-11-19 20:44:05 | D | sum error = [ 83.1552] +24-11-19 20:44:05 | D | best error = [ 83.1552] +24-11-19 20:44:05 | D | + error = [83.1552] +24-11-19 20:44:05 | D | - Calibrating model.layers.11.self_attn.v_proj.output +24-11-19 20:44:05 | D | + w: None +24-11-19 20:44:05 | D | + x: None +24-11-19 20:44:05 | D | + y: sint8 +24-11-19 20:44:05 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:05 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:44:05 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:44:06 | D | - range ratio = [ 1.0000] +24-11-19 20:44:06 | D | sum error = [ 169.9493] +24-11-19 20:44:06 | D | best error = [ 169.9493] +24-11-19 20:44:06 | D | + error = [169.9493] +24-11-19 20:44:06 | D | - Calibrating model.layers.11.self_attn.o_proj.input +24-11-19 20:44:06 | D | - Calibrating model.layers.11.mlp.up_proj.input +24-11-19 20:44:06 | D | - Calibrating model.layers.11.mlp.down_proj.input +24-11-19 20:44:06 | D | - Quantizing model.layers.11.self_attn.q_proj (inputs) +24-11-19 20:44:06 | D | - Quantizing model.layers.11.self_attn.k_proj (inputs) +24-11-19 20:44:06 | D | - Quantizing model.layers.11.self_attn.v_proj (inputs and outputs) +24-11-19 20:44:06 | D | - Quantizing model.layers.11.self_attn.o_proj (inputs) +24-11-19 20:44:06 | D | - Quantizing model.layers.11.self_attn.k_rotary_emb (outputs) +24-11-19 20:44:06 | D | - Quantizing model.layers.11.mlp.gate_proj (inputs) +24-11-19 20:44:06 | D | - Quantizing model.layers.11.mlp.up_proj (inputs) +24-11-19 20:44:06 | D | - Quantizing model.layers.11.mlp.down_proj (inputs) +24-11-19 20:44:13 | D | - Quantizing layer model.layers.12 +24-11-19 20:44:13 | D | - Calibrating model.layers.12.self_attn.v_proj.input +24-11-19 20:44:13 | D | - Calibrating model.layers.12.self_attn.k_rotary_emb.output +24-11-19 20:44:13 | D | + w: None +24-11-19 20:44:13 | D | + x: None +24-11-19 20:44:13 | D | + y: sint8 +24-11-19 20:44:13 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:13 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:44:13 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:44:14 | D | - range ratio = [ 1.0000] +24-11-19 20:44:14 | D | sum error = [ 99.6637] +24-11-19 20:44:14 | D | best error = [ 99.6637] +24-11-19 20:44:14 | D | + error = [99.6637] +24-11-19 20:44:14 | D | - Calibrating model.layers.12.self_attn.v_proj.output +24-11-19 20:44:14 | D | + w: None +24-11-19 20:44:14 | D | + x: None +24-11-19 20:44:14 | D | + y: sint8 +24-11-19 20:44:14 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:14 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:44:14 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:44:15 | D | - range ratio = [ 1.0000] +24-11-19 20:44:15 | D | sum error = [ 152.2722] +24-11-19 20:44:15 | D | best error = [ 152.2722] +24-11-19 20:44:15 | D | + error = [152.2722] +24-11-19 20:44:15 | D | - Calibrating model.layers.12.self_attn.o_proj.input +24-11-19 20:44:15 | D | - Calibrating model.layers.12.mlp.up_proj.input +24-11-19 20:44:15 | D | - Calibrating model.layers.12.mlp.down_proj.input +24-11-19 20:44:15 | D | - Quantizing model.layers.12.self_attn.q_proj (inputs) +24-11-19 20:44:15 | D | - Quantizing model.layers.12.self_attn.k_proj (inputs) +24-11-19 20:44:15 | D | - Quantizing model.layers.12.self_attn.v_proj (inputs and outputs) +24-11-19 20:44:15 | D | - Quantizing model.layers.12.self_attn.o_proj (inputs) +24-11-19 20:44:15 | D | - Quantizing model.layers.12.self_attn.k_rotary_emb (outputs) +24-11-19 20:44:15 | D | - Quantizing model.layers.12.mlp.gate_proj (inputs) +24-11-19 20:44:15 | D | - Quantizing model.layers.12.mlp.up_proj (inputs) +24-11-19 20:44:15 | D | - Quantizing model.layers.12.mlp.down_proj (inputs) +24-11-19 20:44:22 | D | - Quantizing layer model.layers.13 +24-11-19 20:44:22 | D | - Calibrating model.layers.13.self_attn.v_proj.input +24-11-19 20:44:22 | D | - Calibrating model.layers.13.self_attn.k_rotary_emb.output +24-11-19 20:44:22 | D | + w: None +24-11-19 20:44:22 | D | + x: None +24-11-19 20:44:22 | D | + y: sint8 +24-11-19 20:44:22 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:22 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:44:22 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:44:23 | D | - range ratio = [ 1.0000] +24-11-19 20:44:23 | D | sum error = [ 99.8154] +24-11-19 20:44:23 | D | best error = [ 99.8154] +24-11-19 20:44:23 | D | + error = [99.8154] +24-11-19 20:44:23 | D | - Calibrating model.layers.13.self_attn.v_proj.output +24-11-19 20:44:23 | D | + w: None +24-11-19 20:44:23 | D | + x: None +24-11-19 20:44:23 | D | + y: sint8 +24-11-19 20:44:23 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:23 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:44:24 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:44:24 | D | - range ratio = [ 1.0000] +24-11-19 20:44:24 | D | sum error = [ 120.0966] +24-11-19 20:44:24 | D | best error = [ 120.0966] +24-11-19 20:44:24 | D | + error = [120.0966] +24-11-19 20:44:24 | D | - Calibrating model.layers.13.self_attn.o_proj.input +24-11-19 20:44:24 | D | - Calibrating model.layers.13.mlp.up_proj.input +24-11-19 20:44:24 | D | - Calibrating model.layers.13.mlp.down_proj.input +24-11-19 20:44:24 | D | - Quantizing model.layers.13.self_attn.q_proj (inputs) +24-11-19 20:44:24 | D | - Quantizing model.layers.13.self_attn.k_proj (inputs) +24-11-19 20:44:24 | D | - Quantizing model.layers.13.self_attn.v_proj (inputs and outputs) +24-11-19 20:44:24 | D | - Quantizing model.layers.13.self_attn.o_proj (inputs) +24-11-19 20:44:24 | D | - Quantizing model.layers.13.self_attn.k_rotary_emb (outputs) +24-11-19 20:44:24 | D | - Quantizing model.layers.13.mlp.gate_proj (inputs) +24-11-19 20:44:24 | D | - Quantizing model.layers.13.mlp.up_proj (inputs) +24-11-19 20:44:24 | D | - Quantizing model.layers.13.mlp.down_proj (inputs) +24-11-19 20:44:31 | D | - Quantizing layer model.layers.14 +24-11-19 20:44:31 | D | - Calibrating model.layers.14.self_attn.v_proj.input +24-11-19 20:44:31 | D | - Calibrating model.layers.14.self_attn.k_rotary_emb.output +24-11-19 20:44:31 | D | + w: None +24-11-19 20:44:31 | D | + x: None +24-11-19 20:44:31 | D | + y: sint8 +24-11-19 20:44:31 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:31 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:44:32 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:44:32 | D | - range ratio = [ 1.0000] +24-11-19 20:44:32 | D | sum error = [ 101.0657] +24-11-19 20:44:32 | D | best error = [ 101.0657] +24-11-19 20:44:32 | D | + error = [101.0657] +24-11-19 20:44:32 | D | - Calibrating model.layers.14.self_attn.v_proj.output +24-11-19 20:44:32 | D | + w: None +24-11-19 20:44:32 | D | + x: None +24-11-19 20:44:32 | D | + y: sint8 +24-11-19 20:44:32 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:32 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:44:33 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:44:33 | D | - range ratio = [ 1.0000] +24-11-19 20:44:33 | D | sum error = [ 120.0294] +24-11-19 20:44:33 | D | best error = [ 120.0294] +24-11-19 20:44:33 | D | + error = [120.0294] +24-11-19 20:44:33 | D | - Calibrating model.layers.14.self_attn.o_proj.input +24-11-19 20:44:33 | D | - Calibrating model.layers.14.mlp.up_proj.input +24-11-19 20:44:33 | D | - Calibrating model.layers.14.mlp.down_proj.input +24-11-19 20:44:34 | D | - Quantizing model.layers.14.self_attn.q_proj (inputs) +24-11-19 20:44:34 | D | - Quantizing model.layers.14.self_attn.k_proj (inputs) +24-11-19 20:44:34 | D | - Quantizing model.layers.14.self_attn.v_proj (inputs and outputs) +24-11-19 20:44:34 | D | - Quantizing model.layers.14.self_attn.o_proj (inputs) +24-11-19 20:44:34 | D | - Quantizing model.layers.14.self_attn.k_rotary_emb (outputs) +24-11-19 20:44:34 | D | - Quantizing model.layers.14.mlp.gate_proj (inputs) +24-11-19 20:44:34 | D | - Quantizing model.layers.14.mlp.up_proj (inputs) +24-11-19 20:44:34 | D | - Quantizing model.layers.14.mlp.down_proj (inputs) +24-11-19 20:44:40 | D | - Quantizing layer model.layers.15 +24-11-19 20:44:40 | D | - Calibrating model.layers.15.self_attn.v_proj.input +24-11-19 20:44:40 | D | - Calibrating model.layers.15.self_attn.k_rotary_emb.output +24-11-19 20:44:40 | D | + w: None +24-11-19 20:44:40 | D | + x: None +24-11-19 20:44:40 | D | + y: sint8 +24-11-19 20:44:40 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:40 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:44:41 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:44:41 | D | - range ratio = [ 1.0000] +24-11-19 20:44:41 | D | sum error = [ 104.7727] +24-11-19 20:44:41 | D | best error = [ 104.7727] +24-11-19 20:44:41 | D | + error = [104.7727] +24-11-19 20:44:41 | D | - Calibrating model.layers.15.self_attn.v_proj.output +24-11-19 20:44:41 | D | + w: None +24-11-19 20:44:41 | D | + x: None +24-11-19 20:44:41 | D | + y: sint8 +24-11-19 20:44:41 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:41 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:44:42 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:44:42 | D | - range ratio = [ 1.0000] +24-11-19 20:44:42 | D | sum error = [ 126.2651] +24-11-19 20:44:42 | D | best error = [ 126.2651] +24-11-19 20:44:42 | D | + error = [126.2651] +24-11-19 20:44:42 | D | - Calibrating model.layers.15.self_attn.o_proj.input +24-11-19 20:44:42 | D | - Calibrating model.layers.15.mlp.up_proj.input +24-11-19 20:44:43 | D | - Calibrating model.layers.15.mlp.down_proj.input +24-11-19 20:44:43 | D | - Quantizing model.layers.15.self_attn.q_proj (inputs) +24-11-19 20:44:43 | D | - Quantizing model.layers.15.self_attn.k_proj (inputs) +24-11-19 20:44:43 | D | - Quantizing model.layers.15.self_attn.v_proj (inputs and outputs) +24-11-19 20:44:43 | D | - Quantizing model.layers.15.self_attn.o_proj (inputs) +24-11-19 20:44:43 | D | - Quantizing model.layers.15.self_attn.k_rotary_emb (outputs) +24-11-19 20:44:43 | D | - Quantizing model.layers.15.mlp.gate_proj (inputs) +24-11-19 20:44:43 | D | - Quantizing model.layers.15.mlp.up_proj (inputs) +24-11-19 20:44:43 | D | - Quantizing model.layers.15.mlp.down_proj (inputs) +24-11-19 20:44:49 | D | - Quantizing layer model.layers.16 +24-11-19 20:44:49 | D | - Calibrating model.layers.16.self_attn.v_proj.input +24-11-19 20:44:49 | D | - Calibrating model.layers.16.self_attn.k_rotary_emb.output +24-11-19 20:44:49 | D | + w: None +24-11-19 20:44:49 | D | + x: None +24-11-19 20:44:49 | D | + y: sint8 +24-11-19 20:44:49 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:49 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:44:50 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:44:50 | D | - range ratio = [ 1.0000] +24-11-19 20:44:50 | D | sum error = [ 114.5176] +24-11-19 20:44:50 | D | best error = [ 114.5176] +24-11-19 20:44:50 | D | + error = [114.5176] +24-11-19 20:44:50 | D | - Calibrating model.layers.16.self_attn.v_proj.output +24-11-19 20:44:50 | D | + w: None +24-11-19 20:44:50 | D | + x: None +24-11-19 20:44:50 | D | + y: sint8 +24-11-19 20:44:50 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:50 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:44:51 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:44:51 | D | - range ratio = [ 1.0000] +24-11-19 20:44:51 | D | sum error = [ 130.5890] +24-11-19 20:44:51 | D | best error = [ 130.5890] +24-11-19 20:44:51 | D | + error = [130.5890] +24-11-19 20:44:52 | D | - Calibrating model.layers.16.self_attn.o_proj.input +24-11-19 20:44:52 | D | - Calibrating model.layers.16.mlp.up_proj.input +24-11-19 20:44:52 | D | - Calibrating model.layers.16.mlp.down_proj.input +24-11-19 20:44:52 | D | - Quantizing model.layers.16.self_attn.q_proj (inputs) +24-11-19 20:44:52 | D | - Quantizing model.layers.16.self_attn.k_proj (inputs) +24-11-19 20:44:52 | D | - Quantizing model.layers.16.self_attn.v_proj (inputs and outputs) +24-11-19 20:44:52 | D | - Quantizing model.layers.16.self_attn.o_proj (inputs) +24-11-19 20:44:52 | D | - Quantizing model.layers.16.self_attn.k_rotary_emb (outputs) +24-11-19 20:44:52 | D | - Quantizing model.layers.16.mlp.gate_proj (inputs) +24-11-19 20:44:52 | D | - Quantizing model.layers.16.mlp.up_proj (inputs) +24-11-19 20:44:52 | D | - Quantizing model.layers.16.mlp.down_proj (inputs) +24-11-19 20:44:58 | D | - Quantizing layer model.layers.17 +24-11-19 20:44:58 | D | - Calibrating model.layers.17.self_attn.v_proj.input +24-11-19 20:44:58 | D | - Calibrating model.layers.17.self_attn.k_rotary_emb.output +24-11-19 20:44:58 | D | + w: None +24-11-19 20:44:58 | D | + x: None +24-11-19 20:44:58 | D | + y: sint8 +24-11-19 20:44:58 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:58 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:44:59 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:44:59 | D | - range ratio = [ 1.0000] +24-11-19 20:44:59 | D | sum error = [ 134.9787] +24-11-19 20:44:59 | D | best error = [ 134.9787] +24-11-19 20:44:59 | D | + error = [134.9787] +24-11-19 20:45:00 | D | - Calibrating model.layers.17.self_attn.v_proj.output +24-11-19 20:45:00 | D | + w: None +24-11-19 20:45:00 | D | + x: None +24-11-19 20:45:00 | D | + y: sint8 +24-11-19 20:45:00 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:00 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:45:00 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:45:01 | D | - range ratio = [ 1.0000] +24-11-19 20:45:01 | D | sum error = [ 147.4821] +24-11-19 20:45:01 | D | best error = [ 147.4821] +24-11-19 20:45:01 | D | + error = [147.4821] +24-11-19 20:45:01 | D | - Calibrating model.layers.17.self_attn.o_proj.input +24-11-19 20:45:01 | D | - Calibrating model.layers.17.mlp.up_proj.input +24-11-19 20:45:01 | D | - Calibrating model.layers.17.mlp.down_proj.input +24-11-19 20:45:01 | D | - Quantizing model.layers.17.self_attn.q_proj (inputs) +24-11-19 20:45:01 | D | - Quantizing model.layers.17.self_attn.k_proj (inputs) +24-11-19 20:45:01 | D | - Quantizing model.layers.17.self_attn.v_proj (inputs and outputs) +24-11-19 20:45:01 | D | - Quantizing model.layers.17.self_attn.o_proj (inputs) +24-11-19 20:45:01 | D | - Quantizing model.layers.17.self_attn.k_rotary_emb (outputs) +24-11-19 20:45:01 | D | - Quantizing model.layers.17.mlp.gate_proj (inputs) +24-11-19 20:45:01 | D | - Quantizing model.layers.17.mlp.up_proj (inputs) +24-11-19 20:45:01 | D | - Quantizing model.layers.17.mlp.down_proj (inputs) +24-11-19 20:45:08 | D | - Quantizing layer model.layers.18 +24-11-19 20:45:08 | D | - Calibrating model.layers.18.self_attn.v_proj.input +24-11-19 20:45:08 | D | - Calibrating model.layers.18.self_attn.k_rotary_emb.output +24-11-19 20:45:08 | D | + w: None +24-11-19 20:45:08 | D | + x: None +24-11-19 20:45:08 | D | + y: sint8 +24-11-19 20:45:08 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:08 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:45:08 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:45:09 | D | - range ratio = [ 1.0000] +24-11-19 20:45:09 | D | sum error = [ 125.6382] +24-11-19 20:45:09 | D | best error = [ 125.6382] +24-11-19 20:45:09 | D | + error = [125.6382] +24-11-19 20:45:09 | D | - Calibrating model.layers.18.self_attn.v_proj.output +24-11-19 20:45:09 | D | + w: None +24-11-19 20:45:09 | D | + x: None +24-11-19 20:45:09 | D | + y: sint8 +24-11-19 20:45:09 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:09 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:45:09 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:45:10 | D | - range ratio = [ 1.0000] +24-11-19 20:45:10 | D | sum error = [ 168.5833] +24-11-19 20:45:10 | D | best error = [ 168.5833] +24-11-19 20:45:10 | D | + error = [168.5833] +24-11-19 20:45:10 | D | - Calibrating model.layers.18.self_attn.o_proj.input +24-11-19 20:45:10 | D | - Calibrating model.layers.18.mlp.up_proj.input +24-11-19 20:45:10 | D | - Calibrating model.layers.18.mlp.down_proj.input +24-11-19 20:45:10 | D | - Quantizing model.layers.18.self_attn.q_proj (inputs) +24-11-19 20:45:10 | D | - Quantizing model.layers.18.self_attn.k_proj (inputs) +24-11-19 20:45:10 | D | - Quantizing model.layers.18.self_attn.v_proj (inputs and outputs) +24-11-19 20:45:10 | D | - Quantizing model.layers.18.self_attn.o_proj (inputs) +24-11-19 20:45:10 | D | - Quantizing model.layers.18.self_attn.k_rotary_emb (outputs) +24-11-19 20:45:10 | D | - Quantizing model.layers.18.mlp.gate_proj (inputs) +24-11-19 20:45:10 | D | - Quantizing model.layers.18.mlp.up_proj (inputs) +24-11-19 20:45:10 | D | - Quantizing model.layers.18.mlp.down_proj (inputs) +24-11-19 20:45:17 | D | - Quantizing layer model.layers.19 +24-11-19 20:45:17 | D | - Calibrating model.layers.19.self_attn.v_proj.input +24-11-19 20:45:17 | D | - Calibrating model.layers.19.self_attn.k_rotary_emb.output +24-11-19 20:45:17 | D | + w: None +24-11-19 20:45:17 | D | + x: None +24-11-19 20:45:17 | D | + y: sint8 +24-11-19 20:45:17 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:17 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:45:17 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:45:18 | D | - range ratio = [ 1.0000] +24-11-19 20:45:18 | D | sum error = [ 119.5127] +24-11-19 20:45:18 | D | best error = [ 119.5127] +24-11-19 20:45:18 | D | + error = [119.5127] +24-11-19 20:45:18 | D | - Calibrating model.layers.19.self_attn.v_proj.output +24-11-19 20:45:18 | D | + w: None +24-11-19 20:45:18 | D | + x: None +24-11-19 20:45:18 | D | + y: sint8 +24-11-19 20:45:18 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:18 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:45:18 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:45:19 | D | - range ratio = [ 1.0000] +24-11-19 20:45:19 | D | sum error = [ 157.8358] +24-11-19 20:45:19 | D | best error = [ 157.8358] +24-11-19 20:45:19 | D | + error = [157.8358] +24-11-19 20:45:19 | D | - Calibrating model.layers.19.self_attn.o_proj.input +24-11-19 20:45:19 | D | - Calibrating model.layers.19.mlp.up_proj.input +24-11-19 20:45:19 | D | - Calibrating model.layers.19.mlp.down_proj.input +24-11-19 20:45:19 | D | - Quantizing model.layers.19.self_attn.q_proj (inputs) +24-11-19 20:45:19 | D | - Quantizing model.layers.19.self_attn.k_proj (inputs) +24-11-19 20:45:19 | D | - Quantizing model.layers.19.self_attn.v_proj (inputs and outputs) +24-11-19 20:45:19 | D | - Quantizing model.layers.19.self_attn.o_proj (inputs) +24-11-19 20:45:19 | D | - Quantizing model.layers.19.self_attn.k_rotary_emb (outputs) +24-11-19 20:45:19 | D | - Quantizing model.layers.19.mlp.gate_proj (inputs) +24-11-19 20:45:19 | D | - Quantizing model.layers.19.mlp.up_proj (inputs) +24-11-19 20:45:19 | D | - Quantizing model.layers.19.mlp.down_proj (inputs) +24-11-19 20:45:26 | D | - Quantizing layer model.layers.20 +24-11-19 20:45:26 | D | - Calibrating model.layers.20.self_attn.v_proj.input +24-11-19 20:45:26 | D | - Calibrating model.layers.20.self_attn.k_rotary_emb.output +24-11-19 20:45:26 | D | + w: None +24-11-19 20:45:26 | D | + x: None +24-11-19 20:45:26 | D | + y: sint8 +24-11-19 20:45:26 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:26 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:45:26 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:45:27 | D | - range ratio = [ 1.0000] +24-11-19 20:45:27 | D | sum error = [ 114.1178] +24-11-19 20:45:27 | D | best error = [ 114.1178] +24-11-19 20:45:27 | D | + error = [114.1178] +24-11-19 20:45:27 | D | - Calibrating model.layers.20.self_attn.v_proj.output +24-11-19 20:45:27 | D | + w: None +24-11-19 20:45:27 | D | + x: None +24-11-19 20:45:27 | D | + y: sint8 +24-11-19 20:45:27 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:27 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:45:27 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:45:28 | D | - range ratio = [ 1.0000] +24-11-19 20:45:28 | D | sum error = [ 184.0207] +24-11-19 20:45:28 | D | best error = [ 184.0207] +24-11-19 20:45:28 | D | + error = [184.0207] +24-11-19 20:45:28 | D | - Calibrating model.layers.20.self_attn.o_proj.input +24-11-19 20:45:28 | D | - Calibrating model.layers.20.mlp.up_proj.input +24-11-19 20:45:28 | D | - Calibrating model.layers.20.mlp.down_proj.input +24-11-19 20:45:28 | D | - Quantizing model.layers.20.self_attn.q_proj (inputs) +24-11-19 20:45:28 | D | - Quantizing model.layers.20.self_attn.k_proj (inputs) +24-11-19 20:45:28 | D | - Quantizing model.layers.20.self_attn.v_proj (inputs and outputs) +24-11-19 20:45:28 | D | - Quantizing model.layers.20.self_attn.o_proj (inputs) +24-11-19 20:45:28 | D | - Quantizing model.layers.20.self_attn.k_rotary_emb (outputs) +24-11-19 20:45:28 | D | - Quantizing model.layers.20.mlp.gate_proj (inputs) +24-11-19 20:45:28 | D | - Quantizing model.layers.20.mlp.up_proj (inputs) +24-11-19 20:45:28 | D | - Quantizing model.layers.20.mlp.down_proj (inputs) +24-11-19 20:45:34 | D | - Quantizing layer model.layers.21 +24-11-19 20:45:34 | D | - Calibrating model.layers.21.self_attn.v_proj.input +24-11-19 20:45:35 | D | - Calibrating model.layers.21.self_attn.k_rotary_emb.output +24-11-19 20:45:35 | D | + w: None +24-11-19 20:45:35 | D | + x: None +24-11-19 20:45:35 | D | + y: sint8 +24-11-19 20:45:35 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:35 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:45:35 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:45:35 | D | - range ratio = [ 1.0000] +24-11-19 20:45:35 | D | sum error = [ 121.2750] +24-11-19 20:45:35 | D | best error = [ 121.2750] +24-11-19 20:45:35 | D | + error = [121.2750] +24-11-19 20:45:36 | D | - Calibrating model.layers.21.self_attn.v_proj.output +24-11-19 20:45:36 | D | + w: None +24-11-19 20:45:36 | D | + x: None +24-11-19 20:45:36 | D | + y: sint8 +24-11-19 20:45:36 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:36 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:45:36 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:45:37 | D | - range ratio = [ 1.0000] +24-11-19 20:45:37 | D | sum error = [ 199.9881] +24-11-19 20:45:37 | D | best error = [ 199.9881] +24-11-19 20:45:37 | D | + error = [199.9881] +24-11-19 20:45:37 | D | - Calibrating model.layers.21.self_attn.o_proj.input +24-11-19 20:45:37 | D | - Calibrating model.layers.21.mlp.up_proj.input +24-11-19 20:45:37 | D | - Calibrating model.layers.21.mlp.down_proj.input +24-11-19 20:45:37 | D | - Quantizing model.layers.21.self_attn.q_proj (inputs) +24-11-19 20:45:37 | D | - Quantizing model.layers.21.self_attn.k_proj (inputs) +24-11-19 20:45:37 | D | - Quantizing model.layers.21.self_attn.v_proj (inputs and outputs) +24-11-19 20:45:37 | D | - Quantizing model.layers.21.self_attn.o_proj (inputs) +24-11-19 20:45:37 | D | - Quantizing model.layers.21.self_attn.k_rotary_emb (outputs) +24-11-19 20:45:37 | D | - Quantizing model.layers.21.mlp.gate_proj (inputs) +24-11-19 20:45:37 | D | - Quantizing model.layers.21.mlp.up_proj (inputs) +24-11-19 20:45:37 | D | - Quantizing model.layers.21.mlp.down_proj (inputs) +24-11-19 20:45:44 | D | - Quantizing layer model.layers.22 +24-11-19 20:45:44 | D | - Calibrating model.layers.22.self_attn.v_proj.input +24-11-19 20:45:44 | D | - Calibrating model.layers.22.self_attn.k_rotary_emb.output +24-11-19 20:45:44 | D | + w: None +24-11-19 20:45:44 | D | + x: None +24-11-19 20:45:44 | D | + y: sint8 +24-11-19 20:45:44 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:44 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:45:44 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:45:45 | D | - range ratio = [ 1.0000] +24-11-19 20:45:45 | D | sum error = [ 159.1454] +24-11-19 20:45:45 | D | best error = [ 159.1454] +24-11-19 20:45:45 | D | + error = [159.1454] +24-11-19 20:45:45 | D | - Calibrating model.layers.22.self_attn.v_proj.output +24-11-19 20:45:45 | D | + w: None +24-11-19 20:45:45 | D | + x: None +24-11-19 20:45:45 | D | + y: sint8 +24-11-19 20:45:45 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:45 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:45:45 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:45:46 | D | - range ratio = [ 1.0000] +24-11-19 20:45:46 | D | sum error = [ 193.3962] +24-11-19 20:45:46 | D | best error = [ 193.3962] +24-11-19 20:45:46 | D | + error = [193.3962] +24-11-19 20:45:46 | D | - Calibrating model.layers.22.self_attn.o_proj.input +24-11-19 20:45:46 | D | - Calibrating model.layers.22.mlp.up_proj.input +24-11-19 20:45:46 | D | - Calibrating model.layers.22.mlp.down_proj.input +24-11-19 20:45:46 | D | - Quantizing model.layers.22.self_attn.q_proj (inputs) +24-11-19 20:45:46 | D | - Quantizing model.layers.22.self_attn.k_proj (inputs) +24-11-19 20:45:46 | D | - Quantizing model.layers.22.self_attn.v_proj (inputs and outputs) +24-11-19 20:45:46 | D | - Quantizing model.layers.22.self_attn.o_proj (inputs) +24-11-19 20:45:46 | D | - Quantizing model.layers.22.self_attn.k_rotary_emb (outputs) +24-11-19 20:45:46 | D | - Quantizing model.layers.22.mlp.gate_proj (inputs) +24-11-19 20:45:46 | D | - Quantizing model.layers.22.mlp.up_proj (inputs) +24-11-19 20:45:46 | D | - Quantizing model.layers.22.mlp.down_proj (inputs) +24-11-19 20:45:53 | D | - Quantizing layer model.layers.23 +24-11-19 20:45:53 | D | - Calibrating model.layers.23.self_attn.v_proj.input +24-11-19 20:45:53 | D | - Calibrating model.layers.23.self_attn.k_rotary_emb.output +24-11-19 20:45:53 | D | + w: None +24-11-19 20:45:53 | D | + x: None +24-11-19 20:45:53 | D | + y: sint8 +24-11-19 20:45:53 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:53 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:45:53 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:45:54 | D | - range ratio = [ 1.0000] +24-11-19 20:45:54 | D | sum error = [ 140.0098] +24-11-19 20:45:54 | D | best error = [ 140.0098] +24-11-19 20:45:54 | D | + error = [140.0098] +24-11-19 20:45:54 | D | - Calibrating model.layers.23.self_attn.v_proj.output +24-11-19 20:45:54 | D | + w: None +24-11-19 20:45:54 | D | + x: None +24-11-19 20:45:54 | D | + y: sint8 +24-11-19 20:45:54 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:54 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:45:54 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:45:55 | D | - range ratio = [ 1.0000] +24-11-19 20:45:55 | D | sum error = [ 260.7649] +24-11-19 20:45:55 | D | best error = [ 260.7649] +24-11-19 20:45:55 | D | + error = [260.7649] +24-11-19 20:45:55 | D | - Calibrating model.layers.23.self_attn.o_proj.input +24-11-19 20:45:55 | D | - Calibrating model.layers.23.mlp.up_proj.input +24-11-19 20:45:55 | D | - Calibrating model.layers.23.mlp.down_proj.input +24-11-19 20:45:55 | D | - Quantizing model.layers.23.self_attn.q_proj (inputs) +24-11-19 20:45:55 | D | - Quantizing model.layers.23.self_attn.k_proj (inputs) +24-11-19 20:45:55 | D | - Quantizing model.layers.23.self_attn.v_proj (inputs and outputs) +24-11-19 20:45:55 | D | - Quantizing model.layers.23.self_attn.o_proj (inputs) +24-11-19 20:45:55 | D | - Quantizing model.layers.23.self_attn.k_rotary_emb (outputs) +24-11-19 20:45:55 | D | - Quantizing model.layers.23.mlp.gate_proj (inputs) +24-11-19 20:45:55 | D | - Quantizing model.layers.23.mlp.up_proj (inputs) +24-11-19 20:45:55 | D | - Quantizing model.layers.23.mlp.down_proj (inputs) +24-11-19 20:46:02 | D | - Quantizing layer model.layers.24 +24-11-19 20:46:02 | D | - Calibrating model.layers.24.self_attn.v_proj.input +24-11-19 20:46:02 | D | - Calibrating model.layers.24.self_attn.k_rotary_emb.output +24-11-19 20:46:02 | D | + w: None +24-11-19 20:46:02 | D | + x: None +24-11-19 20:46:02 | D | + y: sint8 +24-11-19 20:46:02 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:02 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:46:03 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:46:03 | D | - range ratio = [ 1.0000] +24-11-19 20:46:03 | D | sum error = [ 166.7006] +24-11-19 20:46:03 | D | best error = [ 166.7006] +24-11-19 20:46:03 | D | + error = [166.7006] +24-11-19 20:46:03 | D | - Calibrating model.layers.24.self_attn.v_proj.output +24-11-19 20:46:03 | D | + w: None +24-11-19 20:46:03 | D | + x: None +24-11-19 20:46:03 | D | + y: sint8 +24-11-19 20:46:03 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:03 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:46:04 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:46:04 | D | - range ratio = [ 1.0000] +24-11-19 20:46:04 | D | sum error = [ 235.7953] +24-11-19 20:46:04 | D | best error = [ 235.7953] +24-11-19 20:46:04 | D | + error = [235.7953] +24-11-19 20:46:04 | D | - Calibrating model.layers.24.self_attn.o_proj.input +24-11-19 20:46:04 | D | - Calibrating model.layers.24.mlp.up_proj.input +24-11-19 20:46:04 | D | - Calibrating model.layers.24.mlp.down_proj.input +24-11-19 20:46:04 | D | - Quantizing model.layers.24.self_attn.q_proj (inputs) +24-11-19 20:46:04 | D | - Quantizing model.layers.24.self_attn.k_proj (inputs) +24-11-19 20:46:04 | D | - Quantizing model.layers.24.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:04 | D | - Quantizing model.layers.24.self_attn.o_proj (inputs) +24-11-19 20:46:04 | D | - Quantizing model.layers.24.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:04 | D | - Quantizing model.layers.24.mlp.gate_proj (inputs) +24-11-19 20:46:04 | D | - Quantizing model.layers.24.mlp.up_proj (inputs) +24-11-19 20:46:04 | D | - Quantizing model.layers.24.mlp.down_proj (inputs) +24-11-19 20:46:11 | D | - Quantizing layer model.layers.25 +24-11-19 20:46:11 | D | - Calibrating model.layers.25.self_attn.v_proj.input +24-11-19 20:46:11 | D | - Calibrating model.layers.25.self_attn.k_rotary_emb.output +24-11-19 20:46:11 | D | + w: None +24-11-19 20:46:11 | D | + x: None +24-11-19 20:46:11 | D | + y: sint8 +24-11-19 20:46:11 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:11 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:46:11 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:46:12 | D | - range ratio = [ 1.0000] +24-11-19 20:46:12 | D | sum error = [ 132.4638] +24-11-19 20:46:12 | D | best error = [ 132.4638] +24-11-19 20:46:12 | D | + error = [132.4638] +24-11-19 20:46:12 | D | - Calibrating model.layers.25.self_attn.v_proj.output +24-11-19 20:46:12 | D | + w: None +24-11-19 20:46:12 | D | + x: None +24-11-19 20:46:12 | D | + y: sint8 +24-11-19 20:46:12 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:12 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:46:13 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:46:13 | D | - range ratio = [ 1.0000] +24-11-19 20:46:13 | D | sum error = [ 244.7589] +24-11-19 20:46:13 | D | best error = [ 244.7589] +24-11-19 20:46:13 | D | + error = [244.7589] +24-11-19 20:46:13 | D | - Calibrating model.layers.25.self_attn.o_proj.input +24-11-19 20:46:13 | D | - Calibrating model.layers.25.mlp.up_proj.input +24-11-19 20:46:13 | D | - Calibrating model.layers.25.mlp.down_proj.input +24-11-19 20:46:13 | D | - Quantizing model.layers.25.self_attn.q_proj (inputs) +24-11-19 20:46:13 | D | - Quantizing model.layers.25.self_attn.k_proj (inputs) +24-11-19 20:46:13 | D | - Quantizing model.layers.25.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:13 | D | - Quantizing model.layers.25.self_attn.o_proj (inputs) +24-11-19 20:46:13 | D | - Quantizing model.layers.25.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:13 | D | - Quantizing model.layers.25.mlp.gate_proj (inputs) +24-11-19 20:46:13 | D | - Quantizing model.layers.25.mlp.up_proj (inputs) +24-11-19 20:46:13 | D | - Quantizing model.layers.25.mlp.down_proj (inputs) +24-11-19 20:46:20 | D | - Quantizing layer model.layers.26 +24-11-19 20:46:20 | D | - Calibrating model.layers.26.self_attn.v_proj.input +24-11-19 20:46:20 | D | - Calibrating model.layers.26.self_attn.k_rotary_emb.output +24-11-19 20:46:20 | D | + w: None +24-11-19 20:46:20 | D | + x: None +24-11-19 20:46:20 | D | + y: sint8 +24-11-19 20:46:20 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:20 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:46:21 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:46:21 | D | - range ratio = [ 1.0000] +24-11-19 20:46:21 | D | sum error = [ 184.2645] +24-11-19 20:46:21 | D | best error = [ 184.2645] +24-11-19 20:46:21 | D | + error = [184.2645] +24-11-19 20:46:21 | D | - Calibrating model.layers.26.self_attn.v_proj.output +24-11-19 20:46:21 | D | + w: None +24-11-19 20:46:21 | D | + x: None +24-11-19 20:46:21 | D | + y: sint8 +24-11-19 20:46:21 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:21 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:46:22 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:46:22 | D | - range ratio = [ 1.0000] +24-11-19 20:46:22 | D | sum error = [ 264.4401] +24-11-19 20:46:22 | D | best error = [ 264.4401] +24-11-19 20:46:22 | D | + error = [264.4401] +24-11-19 20:46:22 | D | - Calibrating model.layers.26.self_attn.o_proj.input +24-11-19 20:46:22 | D | - Calibrating model.layers.26.mlp.up_proj.input +24-11-19 20:46:22 | D | - Calibrating model.layers.26.mlp.down_proj.input +24-11-19 20:46:22 | D | - Quantizing model.layers.26.self_attn.q_proj (inputs) +24-11-19 20:46:22 | D | - Quantizing model.layers.26.self_attn.k_proj (inputs) +24-11-19 20:46:22 | D | - Quantizing model.layers.26.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:22 | D | - Quantizing model.layers.26.self_attn.o_proj (inputs) +24-11-19 20:46:22 | D | - Quantizing model.layers.26.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:22 | D | - Quantizing model.layers.26.mlp.gate_proj (inputs) +24-11-19 20:46:22 | D | - Quantizing model.layers.26.mlp.up_proj (inputs) +24-11-19 20:46:22 | D | - Quantizing model.layers.26.mlp.down_proj (inputs) +24-11-19 20:46:29 | D | - Quantizing layer model.layers.27 +24-11-19 20:46:29 | D | - Calibrating model.layers.27.self_attn.v_proj.input +24-11-19 20:46:29 | D | - Calibrating model.layers.27.self_attn.k_rotary_emb.output +24-11-19 20:46:29 | D | + w: None +24-11-19 20:46:29 | D | + x: None +24-11-19 20:46:29 | D | + y: sint8 +24-11-19 20:46:29 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:29 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:46:30 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:46:30 | D | - range ratio = [ 1.0000] +24-11-19 20:46:30 | D | sum error = [ 195.2632] +24-11-19 20:46:30 | D | best error = [ 195.2632] +24-11-19 20:46:30 | D | + error = [195.2632] +24-11-19 20:46:30 | D | - Calibrating model.layers.27.self_attn.v_proj.output +24-11-19 20:46:30 | D | + w: None +24-11-19 20:46:30 | D | + x: None +24-11-19 20:46:30 | D | + y: sint8 +24-11-19 20:46:30 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:30 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:46:31 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:46:31 | D | - range ratio = [ 1.0000] +24-11-19 20:46:31 | D | sum error = [ 325.3341] +24-11-19 20:46:31 | D | best error = [ 325.3341] +24-11-19 20:46:31 | D | + error = [325.3341] +24-11-19 20:46:31 | D | - Calibrating model.layers.27.self_attn.o_proj.input +24-11-19 20:46:31 | D | - Calibrating model.layers.27.mlp.up_proj.input +24-11-19 20:46:31 | D | - Calibrating model.layers.27.mlp.down_proj.input +24-11-19 20:46:32 | D | - Quantizing model.layers.27.self_attn.q_proj (inputs) +24-11-19 20:46:32 | D | - Quantizing model.layers.27.self_attn.k_proj (inputs) +24-11-19 20:46:32 | D | - Quantizing model.layers.27.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:32 | D | - Quantizing model.layers.27.self_attn.o_proj (inputs) +24-11-19 20:46:32 | D | - Quantizing model.layers.27.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:32 | D | - Quantizing model.layers.27.mlp.gate_proj (inputs) +24-11-19 20:46:32 | D | - Quantizing model.layers.27.mlp.up_proj (inputs) +24-11-19 20:46:32 | D | - Quantizing model.layers.27.mlp.down_proj (inputs) +24-11-19 20:46:38 | D | - Quantizing layer model.layers.28 +24-11-19 20:46:38 | D | - Calibrating model.layers.28.self_attn.v_proj.input +24-11-19 20:46:38 | D | - Calibrating model.layers.28.self_attn.k_rotary_emb.output +24-11-19 20:46:38 | D | + w: None +24-11-19 20:46:38 | D | + x: None +24-11-19 20:46:38 | D | + y: sint8 +24-11-19 20:46:38 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:38 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:46:39 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:46:39 | D | - range ratio = [ 1.0000] +24-11-19 20:46:39 | D | sum error = [ 185.3058] +24-11-19 20:46:39 | D | best error = [ 185.3058] +24-11-19 20:46:39 | D | + error = [185.3058] +24-11-19 20:46:39 | D | - Calibrating model.layers.28.self_attn.v_proj.output +24-11-19 20:46:39 | D | + w: None +24-11-19 20:46:39 | D | + x: None +24-11-19 20:46:39 | D | + y: sint8 +24-11-19 20:46:39 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:39 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:46:40 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:46:40 | D | - range ratio = [ 1.0000] +24-11-19 20:46:40 | D | sum error = [ 289.9868] +24-11-19 20:46:40 | D | best error = [ 289.9868] +24-11-19 20:46:40 | D | + error = [289.9868] +24-11-19 20:46:40 | D | - Calibrating model.layers.28.self_attn.o_proj.input +24-11-19 20:46:41 | D | - Calibrating model.layers.28.mlp.up_proj.input +24-11-19 20:46:41 | D | - Calibrating model.layers.28.mlp.down_proj.input +24-11-19 20:46:41 | D | - Quantizing model.layers.28.self_attn.q_proj (inputs) +24-11-19 20:46:41 | D | - Quantizing model.layers.28.self_attn.k_proj (inputs) +24-11-19 20:46:41 | D | - Quantizing model.layers.28.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:41 | D | - Quantizing model.layers.28.self_attn.o_proj (inputs) +24-11-19 20:46:41 | D | - Quantizing model.layers.28.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:41 | D | - Quantizing model.layers.28.mlp.gate_proj (inputs) +24-11-19 20:46:41 | D | - Quantizing model.layers.28.mlp.up_proj (inputs) +24-11-19 20:46:41 | D | - Quantizing model.layers.28.mlp.down_proj (inputs) +24-11-19 20:46:47 | D | - Quantizing layer model.layers.29 +24-11-19 20:46:47 | D | - Calibrating model.layers.29.self_attn.v_proj.input +24-11-19 20:46:47 | D | - Calibrating model.layers.29.self_attn.k_rotary_emb.output +24-11-19 20:46:47 | D | + w: None +24-11-19 20:46:47 | D | + x: None +24-11-19 20:46:47 | D | + y: sint8 +24-11-19 20:46:47 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:47 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:46:48 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:46:48 | D | - range ratio = [ 1.0000] +24-11-19 20:46:48 | D | sum error = [ 215.9063] +24-11-19 20:46:48 | D | best error = [ 215.9063] +24-11-19 20:46:48 | D | + error = [215.9063] +24-11-19 20:46:48 | D | - Calibrating model.layers.29.self_attn.v_proj.output +24-11-19 20:46:48 | D | + w: None +24-11-19 20:46:48 | D | + x: None +24-11-19 20:46:48 | D | + y: sint8 +24-11-19 20:46:48 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:48 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:46:49 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:46:49 | D | - range ratio = [ 1.0000] +24-11-19 20:46:49 | D | sum error = [ 334.9527] +24-11-19 20:46:49 | D | best error = [ 334.9527] +24-11-19 20:46:49 | D | + error = [334.9527] +24-11-19 20:46:49 | D | - Calibrating model.layers.29.self_attn.o_proj.input +24-11-19 20:46:49 | D | - Calibrating model.layers.29.mlp.up_proj.input +24-11-19 20:46:49 | D | - Calibrating model.layers.29.mlp.down_proj.input +24-11-19 20:46:50 | D | - Quantizing model.layers.29.self_attn.q_proj (inputs) +24-11-19 20:46:50 | D | - Quantizing model.layers.29.self_attn.k_proj (inputs) +24-11-19 20:46:50 | D | - Quantizing model.layers.29.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:50 | D | - Quantizing model.layers.29.self_attn.o_proj (inputs) +24-11-19 20:46:50 | D | - Quantizing model.layers.29.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:50 | D | - Quantizing model.layers.29.mlp.gate_proj (inputs) +24-11-19 20:46:50 | D | - Quantizing model.layers.29.mlp.up_proj (inputs) +24-11-19 20:46:50 | D | - Quantizing model.layers.29.mlp.down_proj (inputs) +24-11-19 20:46:56 | D | - Quantizing layer model.layers.30 +24-11-19 20:46:56 | D | - Calibrating model.layers.30.self_attn.v_proj.input +24-11-19 20:46:56 | D | - Calibrating model.layers.30.self_attn.k_rotary_emb.output +24-11-19 20:46:56 | D | + w: None +24-11-19 20:46:56 | D | + x: None +24-11-19 20:46:56 | D | + y: sint8 +24-11-19 20:46:56 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:56 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:46:57 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:46:57 | D | - range ratio = [ 1.0000] +24-11-19 20:46:57 | D | sum error = [ 200.2183] +24-11-19 20:46:57 | D | best error = [ 200.2183] +24-11-19 20:46:57 | D | + error = [200.2183] +24-11-19 20:46:57 | D | - Calibrating model.layers.30.self_attn.v_proj.output +24-11-19 20:46:57 | D | + w: None +24-11-19 20:46:57 | D | + x: None +24-11-19 20:46:57 | D | + y: sint8 +24-11-19 20:46:57 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:57 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:46:58 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:46:59 | D | - range ratio = [ 1.0000] +24-11-19 20:46:59 | D | sum error = [ 330.7124] +24-11-19 20:46:59 | D | best error = [ 330.7124] +24-11-19 20:46:59 | D | + error = [330.7124] +24-11-19 20:46:59 | D | - Calibrating model.layers.30.self_attn.o_proj.input +24-11-19 20:46:59 | D | - Calibrating model.layers.30.mlp.up_proj.input +24-11-19 20:46:59 | D | - Calibrating model.layers.30.mlp.down_proj.input +24-11-19 20:46:59 | D | - Quantizing model.layers.30.self_attn.q_proj (inputs) +24-11-19 20:46:59 | D | - Quantizing model.layers.30.self_attn.k_proj (inputs) +24-11-19 20:46:59 | D | - Quantizing model.layers.30.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:59 | D | - Quantizing model.layers.30.self_attn.o_proj (inputs) +24-11-19 20:46:59 | D | - Quantizing model.layers.30.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:59 | D | - Quantizing model.layers.30.mlp.gate_proj (inputs) +24-11-19 20:46:59 | D | - Quantizing model.layers.30.mlp.up_proj (inputs) +24-11-19 20:46:59 | D | - Quantizing model.layers.30.mlp.down_proj (inputs) +24-11-19 20:47:05 | D | - Quantizing layer model.layers.31 +24-11-19 20:47:05 | D | - Calibrating model.layers.31.self_attn.v_proj.input +24-11-19 20:47:05 | D | - Calibrating model.layers.31.self_attn.k_rotary_emb.output +24-11-19 20:47:05 | D | + w: None +24-11-19 20:47:05 | D | + x: None +24-11-19 20:47:05 | D | + y: sint8 +24-11-19 20:47:05 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:05 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:47:06 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:47:06 | D | - range ratio = [ 1.0000] +24-11-19 20:47:06 | D | sum error = [ 258.9879] +24-11-19 20:47:06 | D | best error = [ 258.9879] +24-11-19 20:47:06 | D | + error = [258.9879] +24-11-19 20:47:06 | D | - Calibrating model.layers.31.self_attn.v_proj.output +24-11-19 20:47:06 | D | + w: None +24-11-19 20:47:06 | D | + x: None +24-11-19 20:47:06 | D | + y: sint8 +24-11-19 20:47:06 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:06 | D | + finished parsing calibration arguments, ram usage: 38.7 +24-11-19 20:47:07 | D | + finished reseting calibrator, ram usage: 38.7 +24-11-19 20:47:07 | D | - range ratio = [ 1.0000] +24-11-19 20:47:07 | D | sum error = [ 347.5068] +24-11-19 20:47:07 | D | best error = [ 347.5068] +24-11-19 20:47:07 | D | + error = [347.5068] +24-11-19 20:47:07 | D | - Calibrating model.layers.31.self_attn.o_proj.input +24-11-19 20:47:08 | D | - Calibrating model.layers.31.mlp.up_proj.input +24-11-19 20:47:08 | D | - Calibrating model.layers.31.mlp.down_proj.input +24-11-19 20:47:08 | D | - Quantizing model.layers.31.self_attn.q_proj (inputs) +24-11-19 20:47:08 | D | - Quantizing model.layers.31.self_attn.k_proj (inputs) +24-11-19 20:47:08 | D | - Quantizing model.layers.31.self_attn.v_proj (inputs and outputs) +24-11-19 20:47:08 | D | - Quantizing model.layers.31.self_attn.o_proj (inputs) +24-11-19 20:47:08 | D | - Quantizing model.layers.31.self_attn.k_rotary_emb (outputs) +24-11-19 20:47:08 | D | - Quantizing model.layers.31.mlp.gate_proj (inputs) +24-11-19 20:47:08 | D | - Quantizing model.layers.31.mlp.up_proj (inputs) +24-11-19 20:47:08 | D | - Quantizing model.layers.31.mlp.down_proj (inputs) +24-11-19 20:47:08 | I | - Saving activation quantizer settings to runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-2-7b-instruct-together-32k.pt +24-11-19 20:47:08 | I | - Linking activation quantizer settings to runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.201608.RUNNING/model/acts.pt +24-11-19 20:47:08 | I | * Evaluating model +24-11-19 20:47:08 | W | `pretrained` model kwarg is not of type `str`. Many other model arguments may be ignored. Please do not launch via accelerate or use `parallelize=True` if passing an existing model this way. +24-11-19 20:47:08 | I | Using model type 'default' +24-11-19 20:47:08 | W | Passed an already-initialized model through `pretrained`, assuming single-process call to evaluate() or custom distributed integration +24-11-19 20:47:08 | I | - Evaluator: gptq +24-11-19 20:47:08 | I | - Tasks: ['wikitext'] +24-11-19 20:47:08 | I | - Batch_size: 8 +24-11-19 20:47:08 | I | + Max_seq_length: 2048 +24-11-19 20:47:08 | D | Starting new HTTPS connection (7): huggingface.co:443 +24-11-19 20:47:14 | W | Using the latest cached version of the dataset since wikitext couldn't be found on the Hugging Face Hub +24-11-19 20:47:14 | W | Found the latest cached dataset configuration 'wikitext-2-raw-v1' at /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3 (last modified on Tue Oct 8 19:51:38 2024). +24-11-19 20:47:14 | D | Attempting to acquire lock 23438671659520 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:47:14 | D | Lock 23438671659520 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:47:14 | D | open file: /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3/dataset_info.json +24-11-19 20:47:14 | D | Attempting to release lock 23438671659520 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:47:14 | D | Lock 23438671659520 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:47:51 | I | - Results: +24-11-19 20:47:51 | I | | Task |Version| Metric |Value | |Stderr| +24-11-19 20:47:51 | I | |--------|------:|---------------|-----:|---|-----:| +24-11-19 20:47:51 | I | |wikitext| 1|word_perplexity|6.5098|± |6.5098| +24-11-19 20:47:51 | I | +24-11-19 20:47:51 | I | + Max_seq_length: 4096 +24-11-19 20:47:51 | D | Starting new HTTPS connection (8): huggingface.co:443 +24-11-19 20:47:57 | W | Using the latest cached version of the dataset since wikitext couldn't be found on the Hugging Face Hub +24-11-19 20:47:57 | W | Found the latest cached dataset configuration 'wikitext-2-raw-v1' at /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3 (last modified on Tue Oct 8 19:51:38 2024). +24-11-19 20:47:57 | D | Attempting to acquire lock 23438241875056 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:47:57 | D | Lock 23438241875056 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:47:57 | D | open file: /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3/dataset_info.json +24-11-19 20:47:57 | D | Attempting to release lock 23438241875056 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:47:57 | D | Lock 23438241875056 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:48:28 | I | - Results: +24-11-19 20:48:29 | I | | Task |Version| Metric |Value | |Stderr| +24-11-19 20:48:29 | I | |--------|------:|---------------|-----:|---|-----:| +24-11-19 20:48:29 | I | |wikitext| 1|word_perplexity|6.0176|± |6.0176| +24-11-19 20:48:29 | I | +24-11-19 20:48:29 | I | * Saving results to runs/shang/llm/llama-2/llama-2-7b-instruct-together-32k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.201608 diff --git a/runs/llama-3-8b-instruct-gradient-1048k/w.16-x.16-y.16/w.fp16-x.fp16-y.fp16/w.tnsr.fp16-x.tnsr.fp16-y.tnsr.fp16/default-pileval.128x1024.[0-0]/run-241119.172947/config-241119.172947.yaml b/runs/llama-3-8b-instruct-gradient-1048k/w.16-x.16-y.16/w.fp16-x.fp16-y.fp16/w.tnsr.fp16-x.tnsr.fp16-y.tnsr.fp16/default-pileval.128x1024.[0-0]/run-241119.172947/config-241119.172947.yaml new file mode 100644 index 0000000000000000000000000000000000000000..aaf6164e0f91b0a9abef898a9d3156ab454e2496 --- /dev/null +++ b/runs/llama-3-8b-instruct-gradient-1048k/w.16-x.16-y.16/w.fp16-x.fp16-y.fp16/w.tnsr.fp16-x.tnsr.fp16-y.tnsr.fp16/default-pileval.128x1024.[0-0]/run-241119.172947/config-241119.172947.yaml @@ -0,0 +1,85 @@ +cache: + root: runs/shang + path: + rotation: '' + reorder: '' + smooth: '' + wgts: '' + acts: '' +output: + root: runs/shang + dirname: default-pileval.128x1024.[0-0] + job: run +model: + name: llama-3-8b-instruct-gradient-1048k + family: llama-3 + path: /home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k + root: '' + local_path: /home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k + local_root: /home/yujunlin/models + dtype: torch.float16 +eval: + num_gpus: 1 + batch_size: 8 + tasks: + - wikitext + max_seq_length: -4096 + evaluators: + - gptq +quant: + wgts: + dtype: null + zero_point: null + group_shapes: + - - -1 + - -1 + - -1 + scale_dtypes: + - null + intermediate_dtypes: [] + intermediate_levels: [] + needs_dequant_saturation: false + skips: [] + enable_kernel_gptq: false + enable_calib_range: false + ipts: + dtype: null + zero_point: null + group_shapes: + - - -1 + - -1 + - -1 + scale_dtypes: + - null + skips: [] + static: false + enable_calib_range: false + opts: + dtype: null + zero_point: null + group_shapes: + - - -1 + - -1 + - -1 + scale_dtypes: + - null + skips: [] + static: false + enable_calib_range: false + calib: + data: pileval + num_samples: 128 + path: mit-han-lab/pile-val-backup + seq_length: 1024 + min_seq_length: 0 + max_seq_length: 0 + local_path: '' + enable_rotation: false + enable_reorder: false + enable_smooth: false + develop_dtype: torch.float32 +seed: 12345 +skip_eval: false +load_from: '' +save_model: false +copy_on_save: false diff --git a/runs/llama-3-8b-instruct-gradient-1048k/w.16-x.16-y.16/w.fp16-x.fp16-y.fp16/w.tnsr.fp16-x.tnsr.fp16-y.tnsr.fp16/default-pileval.128x1024.[0-0]/run-241119.172947/results-241119.172947.json b/runs/llama-3-8b-instruct-gradient-1048k/w.16-x.16-y.16/w.fp16-x.fp16-y.fp16/w.tnsr.fp16-x.tnsr.fp16-y.tnsr.fp16/default-pileval.128x1024.[0-0]/run-241119.172947/results-241119.172947.json new file mode 100644 index 0000000000000000000000000000000000000000..b4e07c37ced1e163002a55c5a00774e6381a03cf --- /dev/null +++ b/runs/llama-3-8b-instruct-gradient-1048k/w.16-x.16-y.16/w.fp16-x.fp16-y.fp16/w.tnsr.fp16-x.tnsr.fp16-y.tnsr.fp16/default-pileval.128x1024.[0-0]/run-241119.172947/results-241119.172947.json @@ -0,0 +1,32 @@ +{ + "gptq": { + "2048": { + "results": { + "wikitext": { + "word_perplexity": 7.833065190604292 + } + }, + "versions": { + "wikitext": 1 + }, + "config": { + "model": "llama-3-8b-instruct-gradient-1048k" + }, + "model": "llama-3-8b-instruct-gradient-1048k" + }, + "4096": { + "results": { + "wikitext": { + "word_perplexity": 7.261800992411218 + } + }, + "versions": { + "wikitext": 1 + }, + "config": { + "model": "llama-3-8b-instruct-gradient-1048k" + }, + "model": "llama-3-8b-instruct-gradient-1048k" + } + } +} \ No newline at end of file diff --git a/runs/llama-3-8b-instruct-gradient-1048k/w.16-x.16-y.16/w.fp16-x.fp16-y.fp16/w.tnsr.fp16-x.tnsr.fp16-y.tnsr.fp16/default-pileval.128x1024.[0-0]/run-241119.172947/run-241119.172947.log b/runs/llama-3-8b-instruct-gradient-1048k/w.16-x.16-y.16/w.fp16-x.fp16-y.fp16/w.tnsr.fp16-x.tnsr.fp16-y.tnsr.fp16/default-pileval.128x1024.[0-0]/run-241119.172947/run-241119.172947.log new file mode 100644 index 0000000000000000000000000000000000000000..467d774ca6dc230303fa78e52ebbcc8f2b992619 --- /dev/null +++ b/runs/llama-3-8b-instruct-gradient-1048k/w.16-x.16-y.16/w.fp16-x.fp16-y.fp16/w.tnsr.fp16-x.tnsr.fp16-y.tnsr.fp16/default-pileval.128x1024.[0-0]/run-241119.172947/run-241119.172947.log @@ -0,0 +1,219 @@ +24-11-19 17:29:47 | I | === Configurations === +24-11-19 17:29:47 | I | LlmPtqRunConfig( +24-11-19 17:29:47 | I | cache=LlmCacheConfig( +24-11-19 17:29:47 | I | root=runs/shang, +24-11-19 17:29:47 | I | dirpath=LlmQuantCacheConfig( +24-11-19 17:29:47 | I | rotation=, +24-11-19 17:29:47 | I | reorder=, +24-11-19 17:29:47 | I | smooth=, +24-11-19 17:29:47 | I | wgts=, +24-11-19 17:29:47 | I | acts=), +24-11-19 17:29:47 | I | path=LlmQuantCacheConfig( +24-11-19 17:29:47 | I | rotation=, +24-11-19 17:29:47 | I | reorder=, +24-11-19 17:29:47 | I | smooth=, +24-11-19 17:29:47 | I | wgts=, +24-11-19 17:29:47 | I | acts=)), +24-11-19 17:29:47 | I | output=OutputConfig( +24-11-19 17:29:47 | I | root=runs/shang, +24-11-19 17:29:47 | I | dirname=default-pileval.128x1024.[0-0], +24-11-19 17:29:47 | I | job=run, +24-11-19 17:29:47 | I | dirpath=runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.16-x.16-y.16/w.fp16-x.fp16-y.fp16/w.tnsr.fp16-x.tnsr.fp16-y.tnsr.fp16/default-pileval.128x1024.[0-0], +24-11-19 17:29:47 | I | timestamp=241119.172947), +24-11-19 17:29:47 | I | model=LlmModelConfig( +24-11-19 17:29:47 | I | name=llama-3-8b-instruct-gradient-1048k, +24-11-19 17:29:47 | I | family=llama-3, +24-11-19 17:29:47 | I | path=/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k, +24-11-19 17:29:47 | I | root=, +24-11-19 17:29:47 | I | local_path=/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k, +24-11-19 17:29:47 | I | local_root=/home/yujunlin/models, +24-11-19 17:29:47 | I | size=8.0, +24-11-19 17:29:47 | I | variant=instruct-gradient-1048k, +24-11-19 17:29:47 | I | dtype=torch.float16, +24-11-19 17:29:47 | I | orig_dtype=torch.bfloat16), +24-11-19 17:29:47 | I | eval=LlmEvalConfig( +24-11-19 17:29:47 | I | num_gpus=1, +24-11-19 17:29:47 | I | batch_size=8, +24-11-19 17:29:47 | I | tasks=['wikitext'], +24-11-19 17:29:47 | I | max_seq_length=-4096, +24-11-19 17:29:47 | I | evaluators=['gptq']), +24-11-19 17:29:47 | I | quant=LlmQuantConfig( +24-11-19 17:29:47 | I | wgts=LlmWeightQuantizerConfig( +24-11-19 17:29:47 | I | dtype=None, +24-11-19 17:29:47 | I | zero_point=None, +24-11-19 17:29:47 | I | group_shapes=((-1, -1, -1),), +24-11-19 17:29:47 | I | scale_dtypes=(None,), +24-11-19 17:29:47 | I | intermediate_dtypes=(), +24-11-19 17:29:47 | I | intermediate_levels=(), +24-11-19 17:29:47 | I | needs_dequant_saturation=False, +24-11-19 17:29:47 | I | skips=[], +24-11-19 17:29:47 | I | static=False, +24-11-19 17:29:47 | I | kernel_gptq=None, +24-11-19 17:29:47 | I | calib_range=None), +24-11-19 17:29:47 | I | ipts=LlmActivationQuantizerConfig( +24-11-19 17:29:47 | I | dtype=None, +24-11-19 17:29:47 | I | zero_point=None, +24-11-19 17:29:47 | I | group_shapes=((-1, -1, -1),), +24-11-19 17:29:47 | I | scale_dtypes=(None,), +24-11-19 17:29:47 | I | intermediate_dtypes=(), +24-11-19 17:29:47 | I | intermediate_levels=(), +24-11-19 17:29:47 | I | needs_dequant_saturation=False, +24-11-19 17:29:47 | I | skips=[], +24-11-19 17:29:47 | I | static=False, +24-11-19 17:29:47 | I | kernel_gptq=None, +24-11-19 17:29:47 | I | calib_range=None), +24-11-19 17:29:47 | I | opts=LlmActivationQuantizerConfig( +24-11-19 17:29:47 | I | dtype=None, +24-11-19 17:29:47 | I | zero_point=None, +24-11-19 17:29:47 | I | group_shapes=((-1, -1, -1),), +24-11-19 17:29:47 | I | scale_dtypes=(None,), +24-11-19 17:29:47 | I | intermediate_dtypes=(), +24-11-19 17:29:47 | I | intermediate_levels=(), +24-11-19 17:29:47 | I | needs_dequant_saturation=False, +24-11-19 17:29:47 | I | skips=[], +24-11-19 17:29:47 | I | static=False, +24-11-19 17:29:47 | I | kernel_gptq=None, +24-11-19 17:29:47 | I | calib_range=None), +24-11-19 17:29:47 | I | calib=LlmCalibDataLoaderConfig( +24-11-19 17:29:47 | I | data=pileval, +24-11-19 17:29:47 | I | num_samples=128, +24-11-19 17:29:47 | I | batch_size=1, +24-11-19 17:29:47 | I | path=mit-han-lab/pile-val-backup, +24-11-19 17:29:47 | I | seq_length=1024, +24-11-19 17:29:47 | I | min_seq_length=0, +24-11-19 17:29:47 | I | max_seq_length=0, +24-11-19 17:29:47 | I | local_path=), +24-11-19 17:29:47 | I | rotation=None, +24-11-19 17:29:47 | I | reorder=None, +24-11-19 17:29:47 | I | smooth=None, +24-11-19 17:29:47 | I | develop_dtype=torch.float32), +24-11-19 17:29:47 | I | seed=12345, +24-11-19 17:29:47 | I | skip_eval=False, +24-11-19 17:29:47 | I | load_from=, +24-11-19 17:29:47 | I | save_model=False, +24-11-19 17:29:47 | I | copy_on_save=False) +24-11-19 17:29:47 | I | === Dumped Configurations === +24-11-19 17:29:47 | I | { 'cache': {'path': {'acts': '', 'reorder': '', 'rotation': '', 'smooth': '', 'wgts': ''}, 'root': 'runs/shang'}, +24-11-19 17:29:47 | I | 'copy_on_save': False, +24-11-19 17:29:47 | I | 'eval': {'batch_size': 8, 'evaluators': ['gptq'], 'max_seq_length': -4096, 'num_gpus': 1, 'tasks': ['wikitext']}, +24-11-19 17:29:47 | I | 'load_from': '', +24-11-19 17:29:47 | I | 'model': { 'dtype': 'torch.float16', +24-11-19 17:29:47 | I | 'family': 'llama-3', +24-11-19 17:29:47 | I | 'local_path': '/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k', +24-11-19 17:29:47 | I | 'local_root': '/home/yujunlin/models', +24-11-19 17:29:47 | I | 'name': 'llama-3-8b-instruct-gradient-1048k', +24-11-19 17:29:47 | I | 'path': '/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k', +24-11-19 17:29:47 | I | 'root': ''}, +24-11-19 17:29:47 | I | 'output': {'dirname': 'default-pileval.128x1024.[0-0]', 'job': 'run', 'root': 'runs/shang'}, +24-11-19 17:29:47 | I | 'quant': { 'calib': { 'data': 'pileval', +24-11-19 17:29:47 | I | 'local_path': '', +24-11-19 17:29:47 | I | 'max_seq_length': 0, +24-11-19 17:29:47 | I | 'min_seq_length': 0, +24-11-19 17:29:47 | I | 'num_samples': 128, +24-11-19 17:29:47 | I | 'path': 'mit-han-lab/pile-val-backup', +24-11-19 17:29:47 | I | 'seq_length': 1024}, +24-11-19 17:29:47 | I | 'develop_dtype': 'torch.float32', +24-11-19 17:29:47 | I | 'enable_reorder': False, +24-11-19 17:29:47 | I | 'enable_rotation': False, +24-11-19 17:29:47 | I | 'enable_smooth': False, +24-11-19 17:29:47 | I | 'ipts': { 'dtype': None, +24-11-19 17:29:47 | I | 'enable_calib_range': False, +24-11-19 17:29:47 | I | 'group_shapes': [[-1, -1, -1]], +24-11-19 17:29:47 | I | 'scale_dtypes': [None], +24-11-19 17:29:47 | I | 'skips': [], +24-11-19 17:29:47 | I | 'static': False, +24-11-19 17:29:47 | I | 'zero_point': None}, +24-11-19 17:29:47 | I | 'opts': { 'dtype': None, +24-11-19 17:29:47 | I | 'enable_calib_range': False, +24-11-19 17:29:47 | I | 'group_shapes': [[-1, -1, -1]], +24-11-19 17:29:47 | I | 'scale_dtypes': [None], +24-11-19 17:29:47 | I | 'skips': [], +24-11-19 17:29:47 | I | 'static': False, +24-11-19 17:29:47 | I | 'zero_point': None}, +24-11-19 17:29:47 | I | 'wgts': { 'dtype': None, +24-11-19 17:29:47 | I | 'enable_calib_range': False, +24-11-19 17:29:47 | I | 'enable_kernel_gptq': False, +24-11-19 17:29:47 | I | 'group_shapes': [[-1, -1, -1]], +24-11-19 17:29:47 | I | 'intermediate_dtypes': [], +24-11-19 17:29:47 | I | 'intermediate_levels': [], +24-11-19 17:29:47 | I | 'needs_dequant_saturation': False, +24-11-19 17:29:47 | I | 'scale_dtypes': [None], +24-11-19 17:29:47 | I | 'skips': [], +24-11-19 17:29:47 | I | 'zero_point': None}}, +24-11-19 17:29:47 | I | 'save_model': False, +24-11-19 17:29:47 | I | 'seed': 12345, +24-11-19 17:29:47 | I | 'skip_eval': False} +24-11-19 17:29:47 | I | === Output Directory === +24-11-19 17:29:47 | I | runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.16-x.16-y.16/w.fp16-x.fp16-y.fp16/w.tnsr.fp16-x.tnsr.fp16-y.tnsr.fp16/default-pileval.128x1024.[0-0]/run-241119.172947 +24-11-19 17:29:47 | I | === Start Evaluating === +24-11-19 17:29:47 | I | * Building model llama-3-8b-instruct-gradient-1048k from /home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k +24-11-19 17:29:48 | I | We will use 90% of the memory on device 0 for storing the model, and 10% for the buffer to avoid OOM. You can set `max_memory` in to a higher value to use more memory (at your own risk). +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.0.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.1.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.2.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.3.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.4.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.5.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.6.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.7.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.8.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.9.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.10.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.11.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.12.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.13.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.14.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.15.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.16.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.17.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.18.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.19.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.20.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.21.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.22.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.23.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.24.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.25.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.26.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.27.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.28.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.29.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.30.self_attn +24-11-19 17:29:56 | I | - Patching LlamaSdpaAttention.forward in model.layers.31.self_attn +24-11-19 17:29:56 | I | * Development dtype is torch.float32 +24-11-19 17:29:56 | I | * Evaluating model +24-11-19 17:29:56 | W | `pretrained` model kwarg is not of type `str`. Many other model arguments may be ignored. Please do not launch via accelerate or use `parallelize=True` if passing an existing model this way. +24-11-19 17:29:56 | I | Using model type 'default' +24-11-19 17:29:56 | W | Passed an already-initialized model through `pretrained`, assuming single-process call to evaluate() or custom distributed integration +24-11-19 17:29:56 | I | - Evaluator: gptq +24-11-19 17:29:56 | I | - Tasks: ['wikitext'] +24-11-19 17:29:56 | I | - Batch_size: 8 +24-11-19 17:29:56 | I | + Max_seq_length: 2048 +24-11-19 17:29:56 | D | Starting new HTTPS connection (1): huggingface.co:443 +24-11-19 17:30:03 | W | Using the latest cached version of the dataset since wikitext couldn't be found on the Hugging Face Hub +24-11-19 17:30:03 | W | Found the latest cached dataset configuration 'wikitext-2-raw-v1' at /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3 (last modified on Tue Oct 8 19:51:38 2024). +24-11-19 17:30:03 | D | Attempting to acquire lock 23438954666640 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 17:30:03 | D | Lock 23438954666640 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 17:30:03 | D | open file: /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3/dataset_info.json +24-11-19 17:30:03 | D | Attempting to release lock 23438954666640 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 17:30:03 | D | Lock 23438954666640 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 17:30:15 | I | - Results: +24-11-19 17:30:15 | I | | Task |Version| Metric |Value | |Stderr| +24-11-19 17:30:15 | I | |--------|------:|---------------|-----:|---|-----:| +24-11-19 17:30:15 | I | |wikitext| 1|word_perplexity|7.8331|± |7.8331| +24-11-19 17:30:15 | I | +24-11-19 17:30:15 | I | + Max_seq_length: 4096 +24-11-19 17:30:15 | D | Starting new HTTPS connection (2): huggingface.co:443 +24-11-19 17:30:21 | W | Using the latest cached version of the dataset since wikitext couldn't be found on the Hugging Face Hub +24-11-19 17:30:21 | W | Found the latest cached dataset configuration 'wikitext-2-raw-v1' at /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3 (last modified on Tue Oct 8 19:51:38 2024). +24-11-19 17:30:21 | D | Attempting to acquire lock 23438952840800 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 17:30:21 | D | Lock 23438952840800 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 17:30:21 | D | open file: /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3/dataset_info.json +24-11-19 17:30:21 | D | Attempting to release lock 23438952840800 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 17:30:21 | D | Lock 23438952840800 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 17:30:32 | I | - Results: +24-11-19 17:30:32 | I | | Task |Version| Metric |Value | |Stderr| +24-11-19 17:30:32 | I | |--------|------:|---------------|-----:|---|-----:| +24-11-19 17:30:32 | I | |wikitext| 1|word_perplexity|7.2618|± |7.2618| +24-11-19 17:30:32 | I | +24-11-19 17:30:32 | I | * Saving results to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.16-x.16-y.16/w.fp16-x.fp16-y.fp16/w.tnsr.fp16-x.tnsr.fp16-y.tnsr.fp16/default-pileval.128x1024.[0-0]/run-241119.172947 diff --git a/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200545/config-241119.200545.yaml b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200545/config-241119.200545.yaml new file mode 100644 index 0000000000000000000000000000000000000000..47b4c53eb98d79e23deaf9f8a39870bdfd702365 --- /dev/null +++ b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200545/config-241119.200545.yaml @@ -0,0 +1,146 @@ +cache: + root: runs/shang + path: + rotation: runs/shang/llm/cache/quant/rotation/hadamard/llama-3-8b-instruct-gradient-1048k.pt + reorder: '' + smooth: runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/llama-3-8b-instruct-gradient-1048k.pt + wgts: runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt + acts: runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt +output: + root: runs/shang + dirname: skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0] + job: run +model: + name: llama-3-8b-instruct-gradient-1048k + family: llama-3 + path: /home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k + root: '' + local_path: /home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k + local_root: /home/yujunlin/models + dtype: torch.float16 +eval: + num_gpus: 1 + batch_size: 8 + tasks: + - wikitext + max_seq_length: -4096 + evaluators: + - gptq +quant: + wgts: + dtype: sint8 + zero_point: null + group_shapes: + - - 1 + - -1 + - -1 + scale_dtypes: + - torch.float16 + intermediate_dtypes: [] + intermediate_levels: [] + needs_dequant_saturation: false + skips: [] + enable_kernel_gptq: true + kernel_gptq: + damp_percentage: 0.01 + block_size: 128 + num_inv_tries: 250 + hessian_block_size: 512 + enable_calib_range: true + calib_range: + degree: 2 + objective: OutputsError + strategy: GridSearch + granularity: Group + element_batch_size: 64 + sample_batch_size: -1 + element_size: 512 + sample_size: -1 + pre_reshape: true + outputs_device: cpu + ratio: 1.0 + max_shrink: 0.2 + max_expand: 1.0 + num_grids: 80 + allow_scale: false + skips: [] + ipts: + dtype: sint8 + zero_point: null + group_shapes: + - - 1 + - -1 + - -1 + scale_dtypes: + - torch.float16 + skips: [] + static: false + enable_calib_range: false + opts: + dtype: sint8 + zero_point: null + group_shapes: + - - -1 + - -1 + - -1 + scale_dtypes: + - torch.float16 + skips: + - attn_q + static: true + enable_calib_range: true + calib_range: + degree: 2 + objective: OutputsError + strategy: Manual + granularity: Layer + element_batch_size: -1 + sample_batch_size: -1 + element_size: -1 + sample_size: -1 + pre_reshape: true + outputs_device: cpu + ratio: 1.0 + max_shrink: 0.2 + max_expand: 1.0 + num_grids: 80 + allow_scale: false + skips: [] + calib: + data: pileval + num_samples: 128 + path: mit-han-lab/pile-val-backup + seq_length: 1024 + min_seq_length: 0 + max_seq_length: 0 + local_path: '' + enable_rotation: true + rotation: + random: false + transforms: + - out_proj + enable_reorder: false + enable_smooth: true + smooth: + enable_proj: false + enable_attn: true + attn: + degree: 2 + strategy: GridSearch + sample_batch_size: -1 + sample_size: -1 + outputs_device: cpu + allow_a_quant: true + allow_b_quant: true + spans: + - - AbsMax + - AbsMax + alpha: 0.5 + beta: -2 + num_grids: 20 + 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a/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200545/results-241119.200545.json b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200545/results-241119.200545.json new file mode 100644 index 0000000000000000000000000000000000000000..049f1a78d4d52679e5b116f3426fe69dc27174e4 --- /dev/null +++ b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200545/results-241119.200545.json @@ -0,0 +1,32 @@ +{ + "gptq": { + "2048": { + "results": { + "wikitext": { + "word_perplexity": 7.989659368184836 + } + }, + "versions": { + "wikitext": 1 + }, + "config": { + "model": "llama-3-8b-instruct-gradient-1048k" + }, + "model": "llama-3-8b-instruct-gradient-1048k" + }, + "4096": { + "results": { + "wikitext": { + "word_perplexity": 7.396661695312681 + } + }, + "versions": { + "wikitext": 1 + }, + "config": { + "model": "llama-3-8b-instruct-gradient-1048k" + }, + "model": "llama-3-8b-instruct-gradient-1048k" + } + } +} \ No newline at end of file diff --git a/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200545/run-241119.183745.log b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200545/run-241119.183745.log new file mode 100644 index 0000000000000000000000000000000000000000..aa98ea5ab86fc203e57ab445478f1a4817bfdd0f --- /dev/null +++ b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200545/run-241119.183745.log @@ -0,0 +1,15947 @@ +24-11-19 18:37:45 | I | === Configurations === +24-11-19 18:37:45 | I | LlmPtqRunConfig( +24-11-19 18:37:45 | I | cache=LlmCacheConfig( +24-11-19 18:37:45 | I | root=runs/shang, +24-11-19 18:37:45 | I | dirpath=LlmQuantCacheConfig( +24-11-19 18:37:45 | I | rotation=runs/shang/llm/cache/quant/rotation/hadamard, +24-11-19 18:37:45 | I | reorder=, +24-11-19 18:37:45 | I | smooth=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2, +24-11-19 18:37:45 | I | wgts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[], +24-11-19 18:37:45 | I | acts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]), +24-11-19 18:37:45 | I | path=LlmQuantCacheConfig( +24-11-19 18:37:45 | I | rotation=runs/shang/llm/cache/quant/rotation/hadamard/llama-3-8b-instruct-gradient-1048k.pt, +24-11-19 18:37:45 | I | reorder=, +24-11-19 18:37:45 | I | smooth=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/llama-3-8b-instruct-gradient-1048k.pt, +24-11-19 18:37:45 | I | wgts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt, +24-11-19 18:37:45 | I | acts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt)), +24-11-19 18:37:45 | I | output=OutputConfig( +24-11-19 18:37:45 | I | root=runs/shang, +24-11-19 18:37:45 | I | dirname=skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0], +24-11-19 18:37:45 | I | job=run, +24-11-19 18:37:45 | I | dirpath=runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0], +24-11-19 18:37:45 | I | timestamp=241119.183745), +24-11-19 18:37:45 | I | model=LlmModelConfig( +24-11-19 18:37:45 | I | name=llama-3-8b-instruct-gradient-1048k, +24-11-19 18:37:45 | I | family=llama-3, +24-11-19 18:37:45 | I | path=/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k, +24-11-19 18:37:45 | I | root=, +24-11-19 18:37:45 | I | local_path=/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k, +24-11-19 18:37:45 | I | local_root=/home/yujunlin/models, +24-11-19 18:37:45 | I | size=8.0, +24-11-19 18:37:45 | I | variant=instruct-gradient-1048k, +24-11-19 18:37:45 | I | dtype=torch.float16, +24-11-19 18:37:45 | I | orig_dtype=torch.bfloat16), +24-11-19 18:37:45 | I | eval=LlmEvalConfig( +24-11-19 18:37:45 | I | num_gpus=1, +24-11-19 18:37:45 | I | batch_size=8, +24-11-19 18:37:45 | I | tasks=['wikitext'], +24-11-19 18:37:45 | I | max_seq_length=-4096, +24-11-19 18:37:45 | I | evaluators=['gptq']), +24-11-19 18:37:45 | I | quant=LlmQuantConfig( +24-11-19 18:37:45 | I | wgts=LlmWeightQuantizerConfig( +24-11-19 18:37:45 | I | dtype=sint8, +24-11-19 18:37:45 | I | zero_point=None, +24-11-19 18:37:45 | I | group_shapes=((1, -1, -1),), +24-11-19 18:37:45 | I | scale_dtypes=(torch.float16,), +24-11-19 18:37:45 | I | intermediate_dtypes=(), +24-11-19 18:37:45 | I | intermediate_levels=(), +24-11-19 18:37:45 | I | needs_dequant_saturation=False, +24-11-19 18:37:45 | I | skips=[], +24-11-19 18:37:45 | I | static=True, +24-11-19 18:37:45 | I | kernel_gptq=QuantGptqConfig( +24-11-19 18:37:45 | I | damp_percentage=0.01, +24-11-19 18:37:45 | I | block_size=128, +24-11-19 18:37:45 | I | num_inv_tries=250, +24-11-19 18:37:45 | I | hessian_block_size=512), +24-11-19 18:37:45 | I | calib_range=SkipBasedDynamicRangeCalibConfig( +24-11-19 18:37:45 | I | degree=2, +24-11-19 18:37:45 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 18:37:45 | I | strategy=SearchBasedCalibStrategy.GridSearch, +24-11-19 18:37:45 | I | granularity=SearchBasedCalibGranularity.Group, +24-11-19 18:37:45 | I | element_batch_size=64, +24-11-19 18:37:45 | I | sample_batch_size=-1, +24-11-19 18:37:45 | I | element_size=512, +24-11-19 18:37:45 | I | sample_size=-1, +24-11-19 18:37:45 | I | pre_reshape=True, +24-11-19 18:37:45 | I | outputs_device=cpu, +24-11-19 18:37:45 | I | ratio=1.0, +24-11-19 18:37:45 | I | max_shrink=0.2, +24-11-19 18:37:45 | I | max_expand=1.0, +24-11-19 18:37:45 | I | num_grids=80, +24-11-19 18:37:45 | I | allow_scale=False, +24-11-19 18:37:45 | I | skips=[])), +24-11-19 18:37:45 | I | ipts=LlmActivationQuantizerConfig( +24-11-19 18:37:45 | I | dtype=sint8, +24-11-19 18:37:45 | I | zero_point=None, +24-11-19 18:37:45 | I | group_shapes=((1, -1, -1),), +24-11-19 18:37:45 | I | scale_dtypes=(torch.float16,), +24-11-19 18:37:45 | I | intermediate_dtypes=(), +24-11-19 18:37:45 | I | intermediate_levels=(), +24-11-19 18:37:45 | I | needs_dequant_saturation=False, +24-11-19 18:37:45 | I | skips=[], +24-11-19 18:37:45 | I | static=False, +24-11-19 18:37:45 | I | kernel_gptq=None, +24-11-19 18:37:45 | I | calib_range=None), +24-11-19 18:37:45 | I | opts=LlmActivationQuantizerConfig( +24-11-19 18:37:45 | I | dtype=sint8, +24-11-19 18:37:45 | I | zero_point=None, +24-11-19 18:37:45 | I | group_shapes=((-1, -1, -1),), +24-11-19 18:37:45 | I | scale_dtypes=(torch.float16,), +24-11-19 18:37:45 | I | intermediate_dtypes=(), +24-11-19 18:37:45 | I | intermediate_levels=(), +24-11-19 18:37:45 | I | needs_dequant_saturation=False, +24-11-19 18:37:45 | I | skips=['attn_q'], +24-11-19 18:37:45 | I | static=True, +24-11-19 18:37:45 | I | kernel_gptq=None, +24-11-19 18:37:45 | I | calib_range=SkipBasedDynamicRangeCalibConfig( +24-11-19 18:37:45 | I | degree=2, +24-11-19 18:37:45 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 18:37:45 | I | strategy=SearchBasedCalibStrategy.Manual, +24-11-19 18:37:45 | I | granularity=SearchBasedCalibGranularity.Layer, +24-11-19 18:37:45 | I | element_batch_size=-1, +24-11-19 18:37:45 | I | sample_batch_size=-1, +24-11-19 18:37:45 | I | element_size=-1, +24-11-19 18:37:45 | I | sample_size=-1, +24-11-19 18:37:45 | I | pre_reshape=True, +24-11-19 18:37:45 | I | outputs_device=cpu, +24-11-19 18:37:45 | I | ratio=1.0, +24-11-19 18:37:45 | I | max_shrink=0.2, +24-11-19 18:37:45 | I | max_expand=1.0, +24-11-19 18:37:45 | I | num_grids=80, +24-11-19 18:37:45 | I | allow_scale=False, +24-11-19 18:37:45 | I | skips=[])), +24-11-19 18:37:45 | I | calib=LlmCalibDataLoaderConfig( +24-11-19 18:37:45 | I | data=pileval, +24-11-19 18:37:45 | I | num_samples=128, +24-11-19 18:37:45 | I | batch_size=1, +24-11-19 18:37:45 | I | path=mit-han-lab/pile-val-backup, +24-11-19 18:37:45 | I | seq_length=1024, +24-11-19 18:37:45 | I | min_seq_length=0, +24-11-19 18:37:45 | I | max_seq_length=0, +24-11-19 18:37:45 | I | local_path=), +24-11-19 18:37:45 | I | rotation=QuantRotationConfig( +24-11-19 18:37:45 | I | random=False, +24-11-19 18:37:45 | I | transforms=['out_proj']), +24-11-19 18:37:45 | I | reorder=None, +24-11-19 18:37:45 | I | smooth=SmoothTransfomerConfig( +24-11-19 18:37:45 | I | proj=None, +24-11-19 18:37:45 | I | attn=SmoothAttentionCalibConfig( +24-11-19 18:37:45 | I | degree=2, +24-11-19 18:37:45 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 18:37:45 | I | strategy=SearchBasedCalibStrategy.GridSearch, +24-11-19 18:37:45 | I | granularity=SearchBasedCalibGranularity.Layer, +24-11-19 18:37:45 | I | element_batch_size=-1, +24-11-19 18:37:45 | I | sample_batch_size=-1, +24-11-19 18:37:45 | I | element_size=-1, +24-11-19 18:37:45 | I | sample_size=-1, +24-11-19 18:37:45 | I | pre_reshape=True, +24-11-19 18:37:45 | I | outputs_device=cpu, +24-11-19 18:37:45 | I | allow_a_quant=True, +24-11-19 18:37:45 | I | allow_b_quant=True, +24-11-19 18:37:45 | I | spans=[(, )], +24-11-19 18:37:45 | I | a_spans=[], +24-11-19 18:37:45 | I | b_spans=[], +24-11-19 18:37:45 | I | alpha=0.5, +24-11-19 18:37:45 | I | beta=-2, +24-11-19 18:37:45 | I | num_grids=20, +24-11-19 18:37:45 | I | allow_low_rank=False)), +24-11-19 18:37:45 | I | develop_dtype=torch.float32), +24-11-19 18:37:45 | I | seed=12345, +24-11-19 18:37:45 | I | skip_eval=False, +24-11-19 18:37:45 | I | load_from=, +24-11-19 18:37:45 | I | save_model=False, +24-11-19 18:37:45 | I | copy_on_save=False) +24-11-19 18:37:45 | I | === Dumped Configurations === +24-11-19 18:37:45 | I | { 'cache': { 'path': { 'acts': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt', +24-11-19 18:37:45 | I | 'reorder': '', +24-11-19 18:37:45 | I | 'rotation': 'runs/shang/llm/cache/quant/rotation/hadamard/llama-3-8b-instruct-gradient-1048k.pt', +24-11-19 18:37:45 | I | 'smooth': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/llama-3-8b-instruct-gradient-1048k.pt', +24-11-19 18:37:45 | I | 'wgts': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt'}, +24-11-19 18:37:45 | I | 'root': 'runs/shang'}, +24-11-19 18:37:45 | I | 'copy_on_save': False, +24-11-19 18:37:45 | I | 'eval': {'batch_size': 8, 'evaluators': ['gptq'], 'max_seq_length': -4096, 'num_gpus': 1, 'tasks': ['wikitext']}, +24-11-19 18:37:45 | I | 'load_from': '', +24-11-19 18:37:45 | I | 'model': { 'dtype': 'torch.float16', +24-11-19 18:37:45 | I | 'family': 'llama-3', +24-11-19 18:37:45 | I | 'local_path': '/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k', +24-11-19 18:37:45 | I | 'local_root': '/home/yujunlin/models', +24-11-19 18:37:45 | I | 'name': 'llama-3-8b-instruct-gradient-1048k', +24-11-19 18:37:45 | I | 'path': '/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k', +24-11-19 18:37:45 | I | 'root': ''}, +24-11-19 18:37:45 | I | 'output': { 'dirname': 'skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]', +24-11-19 18:37:45 | I | 'job': 'run', +24-11-19 18:37:45 | I | 'root': 'runs/shang'}, +24-11-19 18:37:45 | I | 'quant': { 'calib': { 'data': 'pileval', +24-11-19 18:37:45 | I | 'local_path': '', +24-11-19 18:37:45 | I | 'max_seq_length': 0, +24-11-19 18:37:45 | I | 'min_seq_length': 0, +24-11-19 18:37:45 | I | 'num_samples': 128, +24-11-19 18:37:45 | I | 'path': 'mit-han-lab/pile-val-backup', +24-11-19 18:37:45 | I | 'seq_length': 1024}, +24-11-19 18:37:45 | I | 'develop_dtype': 'torch.float32', +24-11-19 18:37:45 | I | 'enable_reorder': False, +24-11-19 18:37:45 | I | 'enable_rotation': True, +24-11-19 18:37:45 | I | 'enable_smooth': True, +24-11-19 18:37:45 | I | 'ipts': { 'dtype': 'sint8', +24-11-19 18:37:45 | I | 'enable_calib_range': False, +24-11-19 18:37:45 | I | 'group_shapes': [[1, -1, -1]], +24-11-19 18:37:45 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 18:37:45 | I | 'skips': [], +24-11-19 18:37:45 | I | 'static': False, +24-11-19 18:37:45 | I | 'zero_point': None}, +24-11-19 18:37:45 | I | 'opts': { 'calib_range': { 'allow_scale': False, +24-11-19 18:37:45 | I | 'degree': 2, +24-11-19 18:37:45 | I | 'element_batch_size': -1, +24-11-19 18:37:45 | I | 'element_size': -1, +24-11-19 18:37:45 | I | 'granularity': 'Layer', +24-11-19 18:37:45 | I | 'max_expand': 1.0, +24-11-19 18:37:45 | I | 'max_shrink': 0.2, +24-11-19 18:37:45 | I | 'num_grids': 80, +24-11-19 18:37:45 | I | 'objective': 'OutputsError', +24-11-19 18:37:45 | I | 'outputs_device': 'cpu', +24-11-19 18:37:45 | I | 'pre_reshape': True, +24-11-19 18:37:45 | I | 'ratio': 1.0, +24-11-19 18:37:45 | I | 'sample_batch_size': -1, +24-11-19 18:37:45 | I | 'sample_size': -1, +24-11-19 18:37:45 | I | 'skips': [], +24-11-19 18:37:45 | I | 'strategy': 'Manual'}, +24-11-19 18:37:45 | I | 'dtype': 'sint8', +24-11-19 18:37:45 | I | 'enable_calib_range': True, +24-11-19 18:37:45 | I | 'group_shapes': [[-1, -1, -1]], +24-11-19 18:37:45 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 18:37:45 | I | 'skips': ['attn_q'], +24-11-19 18:37:45 | I | 'static': True, +24-11-19 18:37:45 | I | 'zero_point': None}, +24-11-19 18:37:45 | I | 'rotation': {'random': False, 'transforms': ['out_proj']}, +24-11-19 18:37:45 | I | 'smooth': { 'attn': { 'allow_a_quant': True, +24-11-19 18:37:45 | I | 'allow_b_quant': True, +24-11-19 18:37:45 | I | 'alpha': 0.5, +24-11-19 18:37:45 | I | 'beta': -2, +24-11-19 18:37:45 | I | 'degree': 2, +24-11-19 18:37:45 | I | 'num_grids': 20, +24-11-19 18:37:45 | I | 'outputs_device': 'cpu', +24-11-19 18:37:45 | I | 'sample_batch_size': -1, +24-11-19 18:37:45 | I | 'sample_size': -1, +24-11-19 18:37:45 | I | 'spans': [['AbsMax', 'AbsMax']], +24-11-19 18:37:45 | I | 'strategy': 'GridSearch'}, +24-11-19 18:37:45 | I | 'enable_attn': True, +24-11-19 18:37:45 | I | 'enable_proj': False}, +24-11-19 18:37:45 | I | 'wgts': { 'calib_range': { 'allow_scale': False, +24-11-19 18:37:45 | I | 'degree': 2, +24-11-19 18:37:45 | I | 'element_batch_size': 64, +24-11-19 18:37:45 | I | 'element_size': 512, +24-11-19 18:37:45 | I | 'granularity': 'Group', +24-11-19 18:37:45 | I | 'max_expand': 1.0, +24-11-19 18:37:45 | I | 'max_shrink': 0.2, +24-11-19 18:37:45 | I | 'num_grids': 80, +24-11-19 18:37:45 | I | 'objective': 'OutputsError', +24-11-19 18:37:45 | I | 'outputs_device': 'cpu', +24-11-19 18:37:45 | I | 'pre_reshape': True, +24-11-19 18:37:45 | I | 'ratio': 1.0, +24-11-19 18:37:45 | I | 'sample_batch_size': -1, +24-11-19 18:37:45 | I | 'sample_size': -1, +24-11-19 18:37:45 | I | 'skips': [], +24-11-19 18:37:45 | I | 'strategy': 'GridSearch'}, +24-11-19 18:37:45 | I | 'dtype': 'sint8', +24-11-19 18:37:45 | I | 'enable_calib_range': True, +24-11-19 18:37:45 | I | 'enable_kernel_gptq': True, +24-11-19 18:37:45 | I | 'group_shapes': [[1, -1, -1]], +24-11-19 18:37:45 | I | 'intermediate_dtypes': [], +24-11-19 18:37:45 | I | 'intermediate_levels': [], +24-11-19 18:37:45 | I | 'kernel_gptq': { 'block_size': 128, +24-11-19 18:37:45 | I | 'damp_percentage': 0.01, +24-11-19 18:37:45 | I | 'hessian_block_size': 512, +24-11-19 18:37:45 | I | 'num_inv_tries': 250}, +24-11-19 18:37:45 | I | 'needs_dequant_saturation': False, +24-11-19 18:37:45 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 18:37:45 | I | 'skips': [], +24-11-19 18:37:45 | I | 'zero_point': None}}, +24-11-19 18:37:45 | I | 'save_model': False, +24-11-19 18:37:45 | I | 'seed': 12345, +24-11-19 18:37:45 | I | 'skip_eval': False} +24-11-19 18:37:45 | I | === Output Directory === +24-11-19 18:37:45 | I | runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.183745 +24-11-19 18:37:45 | I | === Start Evaluating === +24-11-19 18:37:45 | I | * Building model llama-3-8b-instruct-gradient-1048k from /home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k +24-11-19 18:37:46 | I | We will use 90% of the memory on device 0 for storing the model, and 10% for the buffer to avoid OOM. You can set `max_memory` in to a higher value to use more memory (at your own risk). +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.0.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.1.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.2.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.3.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.4.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.5.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.6.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.7.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.8.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.9.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.10.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.11.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.12.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.13.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.14.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.15.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.16.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.17.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.18.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.19.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.20.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.21.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.22.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.23.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.24.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.25.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.26.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.27.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.28.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.29.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.30.self_attn +24-11-19 18:37:52 | I | - Patching LlamaSdpaAttention.forward in model.layers.31.self_attn +24-11-19 18:37:52 | I | * Rotating model +24-11-19 18:37:52 | I | - Generating rotation +24-11-19 18:37:52 | D | - Transforming norm and linear in model.layers.0 +24-11-19 18:37:53 | D | - Transforming norm and linear in model.layers.1 +24-11-19 18:37:53 | D | - Transforming norm and linear in model.layers.2 +24-11-19 18:37:53 | D | - Transforming norm and linear in model.layers.3 +24-11-19 18:37:53 | D | - Transforming norm and linear in model.layers.4 +24-11-19 18:37:53 | D | - Transforming norm and linear in model.layers.5 +24-11-19 18:37:53 | D | - Transforming norm and linear in model.layers.6 +24-11-19 18:37:53 | D | - Transforming norm and linear in model.layers.7 +24-11-19 18:37:53 | D | - Transforming norm and linear in model.layers.8 +24-11-19 18:37:53 | D | - Transforming norm and linear in model.layers.9 +24-11-19 18:37:53 | D | - Transforming norm and linear in model.layers.10 +24-11-19 18:37:53 | D | - Transforming norm and linear in model.layers.11 +24-11-19 18:37:53 | D | - Transforming norm and linear in model.layers.12 +24-11-19 18:37:54 | D | - Transforming norm and linear in model.layers.13 +24-11-19 18:37:54 | D | - Transforming norm and linear in model.layers.14 +24-11-19 18:37:54 | D | - Transforming norm and linear in model.layers.15 +24-11-19 18:37:54 | D | - Transforming norm and linear in model.layers.16 +24-11-19 18:37:54 | D | - Transforming norm and linear in model.layers.17 +24-11-19 18:37:54 | D | - Transforming norm and linear in model.layers.18 +24-11-19 18:37:54 | D | - Transforming norm and linear in model.layers.19 +24-11-19 18:37:54 | D | - Transforming norm and linear in model.layers.20 +24-11-19 18:37:54 | D | - Transforming norm and linear in model.layers.21 +24-11-19 18:37:54 | D | - Transforming norm and linear in model.layers.22 +24-11-19 18:37:54 | D | - Transforming norm and linear in model.layers.23 +24-11-19 18:37:54 | D | - Transforming norm and linear in model.layers.24 +24-11-19 18:37:54 | D | - Transforming norm and linear in model.layers.25 +24-11-19 18:37:55 | D | - Transforming norm and linear in model.layers.26 +24-11-19 18:37:55 | D | - Transforming norm and linear in model.layers.27 +24-11-19 18:37:55 | D | - Transforming norm and linear in model.layers.28 +24-11-19 18:37:55 | D | - Transforming norm and linear in model.layers.29 +24-11-19 18:37:55 | D | - Transforming norm and linear in model.layers.30 +24-11-19 18:37:55 | D | - Transforming norm and linear in model.layers.31 +24-11-19 18:37:55 | D | - Transforming model.norm +24-11-19 18:37:55 | D | - Rotating model.embed_tokens +24-11-19 18:37:55 | D | - Rotating model.layers.0 +24-11-19 18:37:55 | D | - Rotating model.layers.0.self_attn.q_proj (in) +24-11-19 18:37:55 | D | - Rotating model.layers.0.self_attn.k_proj (in) +24-11-19 18:37:55 | D | - Rotating model.layers.0.self_attn.v_proj (in) +24-11-19 18:37:55 | D | - Rotating model.layers.0.self_attn.o_proj (out) +24-11-19 18:37:55 | D | - Rotating model.layers.0.self_attn.v_proj (out) +24-11-19 18:37:55 | D | - Rotating model.layers.0.self_attn.o_proj (in) +24-11-19 18:37:55 | D | - Rotating model.layers.0.mlp.up_proj (in) +24-11-19 18:37:55 | D | - Rotating model.layers.0.mlp.gate_proj (in) +24-11-19 18:37:55 | D | - Rotating model.layers.0.mlp.down_proj (out) +24-11-19 18:37:55 | D | - Rotating model.layers.1 +24-11-19 18:37:55 | D | - Rotating model.layers.1.self_attn.q_proj (in) +24-11-19 18:37:55 | D | - Rotating model.layers.1.self_attn.k_proj (in) +24-11-19 18:37:55 | D | - Rotating model.layers.1.self_attn.v_proj (in) +24-11-19 18:37:55 | D | - Rotating model.layers.1.self_attn.o_proj (out) +24-11-19 18:37:55 | D | - Rotating model.layers.1.self_attn.v_proj (out) +24-11-19 18:37:55 | D | - Rotating model.layers.1.self_attn.o_proj (in) +24-11-19 18:37:55 | D | - Rotating model.layers.1.mlp.up_proj (in) +24-11-19 18:37:55 | D | - Rotating model.layers.1.mlp.gate_proj (in) +24-11-19 18:37:55 | D | - Rotating model.layers.1.mlp.down_proj (out) +24-11-19 18:37:55 | D | - Rotating model.layers.2 +24-11-19 18:37:55 | D | - Rotating model.layers.2.self_attn.q_proj (in) +24-11-19 18:37:55 | D | - Rotating model.layers.2.self_attn.k_proj (in) +24-11-19 18:37:55 | D | - Rotating model.layers.2.self_attn.v_proj (in) +24-11-19 18:37:55 | D | - Rotating model.layers.2.self_attn.o_proj (out) +24-11-19 18:37:55 | D | - Rotating model.layers.2.self_attn.v_proj (out) +24-11-19 18:37:55 | D | - Rotating model.layers.2.self_attn.o_proj (in) +24-11-19 18:37:55 | D | - Rotating model.layers.2.mlp.up_proj (in) +24-11-19 18:37:55 | D | - Rotating model.layers.2.mlp.gate_proj (in) +24-11-19 18:37:55 | D | - Rotating model.layers.2.mlp.down_proj (out) +24-11-19 18:37:56 | D | - Rotating model.layers.3 +24-11-19 18:37:56 | D | - Rotating model.layers.3.self_attn.q_proj (in) +24-11-19 18:37:56 | D | - Rotating model.layers.3.self_attn.k_proj (in) +24-11-19 18:37:56 | D | - Rotating model.layers.3.self_attn.v_proj (in) +24-11-19 18:37:56 | D | - Rotating model.layers.3.self_attn.o_proj (out) +24-11-19 18:37:56 | D | - Rotating model.layers.3.self_attn.v_proj (out) +24-11-19 18:37:56 | D | - Rotating model.layers.3.self_attn.o_proj (in) +24-11-19 18:37:56 | D | - Rotating model.layers.3.mlp.up_proj (in) +24-11-19 18:37:56 | D | - Rotating model.layers.3.mlp.gate_proj (in) +24-11-19 18:37:56 | D | - Rotating model.layers.3.mlp.down_proj (out) +24-11-19 18:37:56 | D | - Rotating model.layers.4 +24-11-19 18:37:56 | D | - Rotating model.layers.4.self_attn.q_proj (in) +24-11-19 18:37:56 | D | - Rotating model.layers.4.self_attn.k_proj (in) +24-11-19 18:37:56 | D | - Rotating model.layers.4.self_attn.v_proj (in) +24-11-19 18:37:56 | D | - Rotating model.layers.4.self_attn.o_proj (out) +24-11-19 18:37:56 | D | - Rotating model.layers.4.self_attn.v_proj (out) +24-11-19 18:37:56 | D | - Rotating model.layers.4.self_attn.o_proj (in) +24-11-19 18:37:56 | D | - Rotating model.layers.4.mlp.up_proj (in) +24-11-19 18:37:56 | D | - Rotating model.layers.4.mlp.gate_proj (in) +24-11-19 18:37:56 | D | - Rotating model.layers.4.mlp.down_proj (out) +24-11-19 18:37:56 | D | - Rotating model.layers.5 +24-11-19 18:37:56 | D | - Rotating model.layers.5.self_attn.q_proj (in) +24-11-19 18:37:56 | D | - Rotating model.layers.5.self_attn.k_proj (in) +24-11-19 18:37:56 | D | - 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Rotating model.layers.26 +24-11-19 18:37:57 | D | - Rotating model.layers.26.self_attn.q_proj (in) +24-11-19 18:37:57 | D | - Rotating model.layers.26.self_attn.k_proj (in) +24-11-19 18:37:57 | D | - Rotating model.layers.26.self_attn.v_proj (in) +24-11-19 18:37:57 | D | - Rotating model.layers.26.self_attn.o_proj (out) +24-11-19 18:37:57 | D | - Rotating model.layers.26.self_attn.v_proj (out) +24-11-19 18:37:57 | D | - Rotating model.layers.26.self_attn.o_proj (in) +24-11-19 18:37:57 | D | - Rotating model.layers.26.mlp.up_proj (in) +24-11-19 18:37:57 | D | - Rotating model.layers.26.mlp.gate_proj (in) +24-11-19 18:37:57 | D | - Rotating model.layers.26.mlp.down_proj (out) +24-11-19 18:37:57 | D | - Rotating model.layers.27 +24-11-19 18:37:57 | D | - Rotating model.layers.27.self_attn.q_proj (in) +24-11-19 18:37:57 | D | - Rotating model.layers.27.self_attn.k_proj (in) +24-11-19 18:37:57 | D | - Rotating model.layers.27.self_attn.v_proj (in) +24-11-19 18:37:57 | D | - Rotating model.layers.27.self_attn.o_proj (out) +24-11-19 18:37:57 | D | - Rotating model.layers.27.self_attn.v_proj (out) +24-11-19 18:37:57 | D | - Rotating model.layers.27.self_attn.o_proj (in) +24-11-19 18:37:57 | D | - Rotating model.layers.27.mlp.up_proj (in) +24-11-19 18:37:57 | D | - Rotating model.layers.27.mlp.gate_proj (in) +24-11-19 18:37:57 | D | - Rotating model.layers.27.mlp.down_proj (out) +24-11-19 18:37:58 | D | - Rotating model.layers.28 +24-11-19 18:37:58 | D | - Rotating model.layers.28.self_attn.q_proj (in) +24-11-19 18:37:58 | D | - Rotating model.layers.28.self_attn.k_proj (in) +24-11-19 18:37:58 | D | - Rotating model.layers.28.self_attn.v_proj (in) +24-11-19 18:37:58 | D | - Rotating model.layers.28.self_attn.o_proj (out) +24-11-19 18:37:58 | D | - Rotating model.layers.28.self_attn.v_proj (out) +24-11-19 18:37:58 | D | - Rotating model.layers.28.self_attn.o_proj (in) +24-11-19 18:37:58 | D | - Rotating model.layers.28.mlp.up_proj (in) +24-11-19 18:37:58 | D | - Rotating model.layers.28.mlp.gate_proj (in) +24-11-19 18:37:58 | D | - Rotating model.layers.28.mlp.down_proj (out) +24-11-19 18:37:58 | D | - Rotating model.layers.29 +24-11-19 18:37:58 | D | - Rotating model.layers.29.self_attn.q_proj (in) +24-11-19 18:37:58 | D | - Rotating model.layers.29.self_attn.k_proj (in) +24-11-19 18:37:58 | D | - Rotating model.layers.29.self_attn.v_proj (in) +24-11-19 18:37:58 | D | - Rotating model.layers.29.self_attn.o_proj (out) +24-11-19 18:37:58 | D | - Rotating model.layers.29.self_attn.v_proj (out) +24-11-19 18:37:58 | D | - Rotating model.layers.29.self_attn.o_proj (in) +24-11-19 18:37:58 | D | - Rotating model.layers.29.mlp.up_proj (in) +24-11-19 18:37:58 | D | - Rotating model.layers.29.mlp.gate_proj (in) +24-11-19 18:37:58 | D | - Rotating model.layers.29.mlp.down_proj (out) +24-11-19 18:37:58 | D | - Rotating model.layers.30 +24-11-19 18:37:58 | D | - Rotating model.layers.30.self_attn.q_proj (in) +24-11-19 18:37:58 | D | - Rotating model.layers.30.self_attn.k_proj (in) +24-11-19 18:37:58 | D | - Rotating model.layers.30.self_attn.v_proj (in) +24-11-19 18:37:58 | D | - Rotating model.layers.30.self_attn.o_proj (out) +24-11-19 18:37:58 | D | - Rotating model.layers.30.self_attn.v_proj (out) +24-11-19 18:37:58 | D | - Rotating model.layers.30.self_attn.o_proj (in) +24-11-19 18:37:58 | D | - Rotating model.layers.30.mlp.up_proj (in) +24-11-19 18:37:58 | D | - Rotating model.layers.30.mlp.gate_proj (in) +24-11-19 18:37:58 | D | - Rotating model.layers.30.mlp.down_proj (out) +24-11-19 18:37:58 | D | - Rotating model.layers.31 +24-11-19 18:37:58 | D | - Rotating model.layers.31.self_attn.q_proj (in) +24-11-19 18:37:58 | D | - Rotating model.layers.31.self_attn.k_proj (in) +24-11-19 18:37:58 | D | - Rotating model.layers.31.self_attn.v_proj (in) +24-11-19 18:37:58 | D | - Rotating model.layers.31.self_attn.o_proj (out) +24-11-19 18:37:58 | D | - Rotating model.layers.31.self_attn.v_proj (out) +24-11-19 18:37:58 | D | - Rotating model.layers.31.self_attn.o_proj (in) +24-11-19 18:37:58 | D | - Rotating model.layers.31.mlp.up_proj (in) +24-11-19 18:37:58 | D | - Rotating model.layers.31.mlp.gate_proj (in) +24-11-19 18:37:58 | D | - Rotating model.layers.31.mlp.down_proj (out) +24-11-19 18:37:58 | D | - Rotating lm_head (in) +24-11-19 18:37:58 | I | - Saving rotation to runs/shang/llm/cache/quant/rotation/hadamard/llama-3-8b-instruct-gradient-1048k.pt +24-11-19 18:37:58 | I | - Linking rotation to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.183745.RUNNING/cache/rotation.pt +24-11-19 18:37:58 | I | * Development dtype is torch.float32 +24-11-19 18:37:58 | I | * Smoothing model for quantization +24-11-19 18:37:58 | I | - Generating smooth scales +24-11-19 18:37:58 | D | Starting new HTTPS connection (1): huggingface.co:443 +24-11-19 18:38:05 | D | Starting new HTTPS connection (2): huggingface.co:443 +24-11-19 18:38:17 | D | Starting new HTTPS connection (1): s3.amazonaws.com:443 +24-11-19 18:38:29 | W | Repo card metadata block was not found. Setting CardData to empty. +24-11-19 18:38:29 | D | Starting new HTTPS connection (3): huggingface.co:443 +24-11-19 18:38:41 | W | Using the latest cached version of the dataset since mit-han-lab/pile-val-backup couldn't be found on the Hugging Face Hub +24-11-19 18:38:41 | W | Found the latest cached dataset configuration 'default' at /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4 (last modified on Tue Oct 8 18:58:39 2024). +24-11-19 18:38:41 | D | Attempting to acquire lock 23438919150640 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 18:38:41 | D | Lock 23438919150640 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 18:38:41 | D | open file: /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4/dataset_info.json +24-11-19 18:38:41 | D | Attempting to release lock 23438919150640 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 18:38:41 | D | Lock 23438919150640 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 18:38:55 | D | - Smoothing model.layers.0 +24-11-19 18:38:55 | D | - model.layers.0.self_attn.attn_k +24-11-19 18:38:55 | D | + w: None +24-11-19 18:38:55 | D | + x: None +24-11-19 18:38:55 | D | + y: sint8 +24-11-19 18:38:55 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:38:55 | D | + finished parsing calibration arguments, ram usage: 11.5 +24-11-19 18:38:55 | D | + x - AbsMax +24-11-19 18:38:55 | D | + x = [min=1.3467, max=18.0000] +24-11-19 18:38:55 | D | + y - AbsMax +24-11-19 18:38:55 | D | + y = [min=1.5479, max=18.6094] +24-11-19 18:38:55 | D | + finished reseting calibrator, ram usage: 11.5 +24-11-19 18:39:01 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:39:01 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:39:01 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:39:01 | D | - sum error = [ 4.3130, 4.2756, 3.8838, 3.8293, 3.4933] +24-11-19 18:39:01 | D | - best error = [ 4.3130, 4.2756, 3.8838, 3.8293, 3.4933] +24-11-19 18:39:01 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:39:01 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:39:01 | D | - sum error = [ 3.3341, 3.3426, 3.0915, 2.8786, 2.8685] +24-11-19 18:39:01 | D | - best error = [ 3.3341, 3.3341, 3.0915, 2.8786, 2.8685] +24-11-19 18:39:01 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:39:01 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:39:01 | D | - sum error = [ 2.7568, 2.5314, 2.5127, 2.2802, 2.2286] +24-11-19 18:39:01 | D | - best error = [ 2.7568, 2.5314, 2.5127, 2.2802, 2.2286] +24-11-19 18:39:01 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:39:01 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:39:01 | D | - sum error = [ 2.1337, 2.0306, 1.9838, 1.9255, 1.7867] +24-11-19 18:39:01 | D | - best error = [ 2.1337, 2.0306, 1.9838, 1.9255, 1.7867] +24-11-19 18:39:01 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:39:01 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:39:01 | D | - sum error = [ 8.5024, 7.7012, 6.9279, 6.0653, 5.4443] +24-11-19 18:39:01 | D | - best error = [ 1.7867, 1.7867, 1.7867, 1.7867, 1.7867] +24-11-19 18:39:01 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:39:01 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:39:01 | D | - sum error = [ 5.0477, 4.4980, 4.0051, 3.6670, 3.3360] +24-11-19 18:39:01 | D | - best error = [ 1.7867, 1.7867, 1.7867, 1.7867, 1.7867] +24-11-19 18:39:01 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:39:01 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:39:01 | D | - sum error = [ 3.1704, 2.9671, 2.6540, 2.5056, 2.3484] +24-11-19 18:39:01 | D | - best error = [ 1.7867, 1.7867, 1.7867, 1.7867, 1.7867] +24-11-19 18:39:01 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:39:01 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:39:01 | D | - sum error = [ 2.2074, 2.0618, 1.9387, 1.8251] +24-11-19 18:39:01 | D | - best error = [ 1.7867, 1.7867, 1.7867, 1.7867] +24-11-19 18:39:01 | D | + error = 1.7867 +24-11-19 18:39:01 | D | + scale = [min=1.5144, max=16.0785] +24-11-19 18:39:08 | D | - Smoothing model.layers.1 +24-11-19 18:39:08 | D | - model.layers.1.self_attn.attn_k +24-11-19 18:39:08 | D | + w: None +24-11-19 18:39:08 | D | + x: None +24-11-19 18:39:08 | D | + y: sint8 +24-11-19 18:39:08 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:39:08 | D | + finished parsing calibration arguments, ram usage: 11.5 +24-11-19 18:39:09 | D | + x - AbsMax +24-11-19 18:39:09 | D | + x = [min=2.2598, max=14.4688] +24-11-19 18:39:09 | D | + y - AbsMax +24-11-19 18:39:09 | D | + y = [min=2.4453, max=17.8125] +24-11-19 18:39:09 | D | + finished reseting calibrator, ram usage: 11.5 +24-11-19 18:39:15 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:39:15 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:39:15 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:39:15 | D | - sum error = [ 11.3022, 10.6862, 10.2100, 9.8338, 9.3304] +24-11-19 18:39:15 | D | - best error = [ 11.3022, 10.6862, 10.2100, 9.8338, 9.3304] +24-11-19 18:39:15 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:39:15 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:39:15 | D | - sum error = [ 8.8558, 8.5838, 8.2442, 7.8983, 7.5492] +24-11-19 18:39:15 | D | - best error = [ 8.8558, 8.5838, 8.2442, 7.8983, 7.5492] +24-11-19 18:39:15 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:39:15 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:39:15 | D | - sum error = [ 7.1286, 6.7859, 6.6481, 6.3896, 6.1402] +24-11-19 18:39:15 | D | - best error = [ 7.1286, 6.7859, 6.6481, 6.3896, 6.1402] +24-11-19 18:39:15 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:39:15 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:39:15 | D | - sum error = [ 5.9742, 5.7331, 5.6128, 5.3917, 5.1841] +24-11-19 18:39:15 | D | - best error = [ 5.9742, 5.7331, 5.6128, 5.3917, 5.1841] +24-11-19 18:39:15 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:39:15 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:39:15 | D | - sum error = [ 16.5291, 15.0478, 13.7415, 12.8160, 11.9685] +24-11-19 18:39:15 | D | - best error = [ 5.1841, 5.1841, 5.1841, 5.1841, 5.1841] +24-11-19 18:39:15 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:39:15 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:39:15 | D | - sum error = [ 11.0745, 9.9252, 9.4580, 8.6899, 8.1854] +24-11-19 18:39:15 | D | - best error = [ 5.1841, 5.1841, 5.1841, 5.1841, 5.1841] +24-11-19 18:39:15 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:39:15 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:39:15 | D | - sum error = [ 7.8079, 7.2042, 6.7778, 6.3648, 6.0961] +24-11-19 18:39:15 | D | - best error = [ 5.1841, 5.1841, 5.1841, 5.1841, 5.1841] +24-11-19 18:39:15 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:39:15 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:39:15 | D | - sum error = [ 5.9570, 5.6813, 5.4382, 5.2450] +24-11-19 18:39:15 | D | - best error = [ 5.1841, 5.1841, 5.1841, 5.1841] +24-11-19 18:39:15 | D | + error = 5.1841 +24-11-19 18:39:15 | D | + scale = [min=2.3384, max=15.4237] +24-11-19 18:39:22 | D | - Smoothing model.layers.2 +24-11-19 18:39:22 | D | - model.layers.2.self_attn.attn_k +24-11-19 18:39:22 | D | + w: None +24-11-19 18:39:22 | D | + x: None +24-11-19 18:39:22 | D | + y: sint8 +24-11-19 18:39:22 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:39:22 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:39:22 | D | + x - AbsMax +24-11-19 18:39:22 | D | + x = [min=1.4365, max=15.0547] +24-11-19 18:39:22 | D | + y - AbsMax +24-11-19 18:39:22 | D | + y = [min=1.2695, max=21.7812] +24-11-19 18:39:22 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:39:28 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:39:28 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:39:28 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:39:28 | D | - sum error = [ 10.0993, 9.8351, 10.6674, 11.5021, 9.8022] +24-11-19 18:39:28 | D | - best error = [ 10.0993, 9.8351, 9.8351, 9.8351, 9.8022] +24-11-19 18:39:28 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:39:28 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:39:28 | D | - sum error = [ 9.6427, 8.4623, 8.0726, 8.8569, 8.0026] +24-11-19 18:39:28 | D | - best error = [ 9.6427, 8.4623, 8.0726, 8.0726, 8.0026] +24-11-19 18:39:28 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:39:28 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:39:28 | D | - sum error = [ 7.3559, 8.3227, 6.9004, 8.8324, 7.1838] +24-11-19 18:39:28 | D | - best error = [ 7.3559, 7.3559, 6.9004, 6.9004, 6.9004] +24-11-19 18:39:28 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:39:28 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:39:28 | D | - sum error = [ 7.4677, 7.4056, 6.2429, 6.4605, 6.7088] +24-11-19 18:39:28 | D | - best error = [ 6.9004, 6.9004, 6.2429, 6.2429, 6.2429] +24-11-19 18:39:28 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:39:28 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:39:28 | D | - sum error = [ 17.9271, 14.9788, 16.3584, 13.8585, 12.7827] +24-11-19 18:39:28 | D | - best error = [ 6.2429, 6.2429, 6.2429, 6.2429, 6.2429] +24-11-19 18:39:28 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:39:28 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:39:28 | D | - sum error = [ 14.1076, 10.9522, 9.5972, 9.1000, 8.6356] +24-11-19 18:39:28 | D | - best error = [ 6.2429, 6.2429, 6.2429, 6.2429, 6.2429] +24-11-19 18:39:28 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:39:28 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:39:28 | D | - sum error = [ 8.3475, 8.8639, 7.3109, 8.2463, 7.3629] +24-11-19 18:39:28 | D | - best error = [ 6.2429, 6.2429, 6.2429, 6.2429, 6.2429] +24-11-19 18:39:28 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:39:28 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:39:28 | D | - sum error = [ 6.5924, 7.1105, 8.0991, 6.1601] +24-11-19 18:39:28 | D | - best error = [ 6.2429, 6.2429, 6.2429, 6.1601] +24-11-19 18:39:28 | D | + error = 6.1601 +24-11-19 18:39:28 | D | + scale = [min=1.2224, max=16.5051] +24-11-19 18:39:35 | D | - Smoothing model.layers.3 +24-11-19 18:39:35 | D | - model.layers.3.self_attn.attn_k +24-11-19 18:39:35 | D | + w: None +24-11-19 18:39:35 | D | + x: None +24-11-19 18:39:35 | D | + y: sint8 +24-11-19 18:39:35 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:39:35 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:39:35 | D | + x - AbsMax +24-11-19 18:39:35 | D | + x = [min=2.4746, max=15.6016] +24-11-19 18:39:35 | D | + y - AbsMax +24-11-19 18:39:35 | D | + y = [min=3.0293, max=23.3438] +24-11-19 18:39:35 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:39:41 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:39:41 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:39:41 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:39:41 | D | - sum error = [ 16.3366, 16.7010, 13.9156, 14.6210, 14.7456] +24-11-19 18:39:41 | D | - best error = [ 16.3366, 16.3366, 13.9156, 13.9156, 13.9156] +24-11-19 18:39:41 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:39:41 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:39:41 | D | - sum error = [ 13.7603, 13.4267, 12.9478, 11.6983, 13.3297] +24-11-19 18:39:41 | D | - best error = [ 13.7603, 13.4267, 12.9478, 11.6983, 11.6983] +24-11-19 18:39:41 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:39:41 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:39:41 | D | - sum error = [ 11.2295, 11.3618, 11.3753, 10.5742, 9.4624] +24-11-19 18:39:41 | D | - best error = [ 11.2295, 11.2295, 11.2295, 10.5742, 9.4624] +24-11-19 18:39:41 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:39:41 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:39:41 | D | - sum error = [ 8.9573, 9.8012, 8.5908, 8.4784, 8.3098] +24-11-19 18:39:41 | D | - best error = [ 8.9573, 8.9573, 8.5908, 8.4784, 8.3098] +24-11-19 18:39:41 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:39:41 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:39:41 | D | - sum error = [ 30.4996, 29.4152, 23.6254, 28.0312, 19.7890] +24-11-19 18:39:41 | D | - best error = [ 8.3098, 8.3098, 8.3098, 8.3098, 8.3098] +24-11-19 18:39:41 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:39:41 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:39:41 | D | - sum error = [ 19.9734, 19.8287, 15.4566, 15.1217, 16.2987] +24-11-19 18:39:41 | D | - best error = [ 8.3098, 8.3098, 8.3098, 8.3098, 8.3098] +24-11-19 18:39:41 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:39:41 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:39:41 | D | - sum error = [ 13.6280, 12.5966, 12.3417, 11.2137, 10.0505] +24-11-19 18:39:41 | D | - best error = [ 8.3098, 8.3098, 8.3098, 8.3098, 8.3098] +24-11-19 18:39:41 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:39:41 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:39:41 | D | - sum error = [ 10.4266, 8.8768, 9.8944, 8.4754] +24-11-19 18:39:41 | D | - best error = [ 8.3098, 8.3098, 8.3098, 8.3098] +24-11-19 18:39:41 | D | + error = 8.3098 +24-11-19 18:39:41 | D | + scale = [min=2.8660, max=19.9417] +24-11-19 18:39:47 | D | - Smoothing model.layers.4 +24-11-19 18:39:47 | D | - model.layers.4.self_attn.attn_k +24-11-19 18:39:47 | D | + w: None +24-11-19 18:39:47 | D | + x: None +24-11-19 18:39:47 | D | + y: sint8 +24-11-19 18:39:47 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:39:47 | D | + finished parsing calibration arguments, ram usage: 11.5 +24-11-19 18:39:47 | D | + x - AbsMax +24-11-19 18:39:47 | D | + x = [min=2.1934, max=15.2812] +24-11-19 18:39:47 | D | + y - AbsMax +24-11-19 18:39:47 | D | + y = [min=3.4199, max=24.3125] +24-11-19 18:39:47 | D | + finished reseting calibrator, ram usage: 11.5 +24-11-19 18:39:53 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:39:53 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:39:53 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:39:53 | D | - sum error = [ 26.4180, 23.3620, 24.1818, 22.9937, 21.8562] +24-11-19 18:39:53 | D | - best error = [ 26.4180, 23.3620, 23.3620, 22.9937, 21.8562] +24-11-19 18:39:53 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:39:53 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:39:53 | D | - sum error = [ 20.1541, 18.6427, 21.8045, 19.2961, 17.1159] +24-11-19 18:39:53 | D | - best error = [ 20.1541, 18.6427, 18.6427, 18.6427, 17.1159] +24-11-19 18:39:53 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:39:53 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:39:53 | D | - sum error = [ 20.4703, 16.8949, 17.3045, 15.2317, 16.1951] +24-11-19 18:39:53 | D | - best error = [ 17.1159, 16.8949, 16.8949, 15.2317, 15.2317] +24-11-19 18:39:53 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:39:53 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:39:53 | D | - sum error = [ 19.0278, 14.5752, 15.4224, 12.9177, 14.6967] +24-11-19 18:39:53 | D | - best error = [ 15.2317, 14.5752, 14.5752, 12.9177, 12.9177] +24-11-19 18:39:53 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:39:53 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:39:53 | D | - sum error = [ 39.2466, 38.7443, 32.4899, 28.3823, 28.7719] +24-11-19 18:39:53 | D | - best error = [ 12.9177, 12.9177, 12.9177, 12.9177, 12.9177] +24-11-19 18:39:53 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:39:53 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:39:53 | D | - sum error = [ 25.5926, 24.3230, 20.5793, 22.7627, 17.5121] +24-11-19 18:39:53 | D | - best error = [ 12.9177, 12.9177, 12.9177, 12.9177, 12.9177] +24-11-19 18:39:53 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:39:53 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:39:53 | D | - sum error = [ 18.8690, 17.4450, 17.3721, 15.0492, 16.9480] +24-11-19 18:39:53 | D | - best error = [ 12.9177, 12.9177, 12.9177, 12.9177, 12.9177] +24-11-19 18:39:53 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:39:53 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:39:53 | D | - sum error = [ 17.2736, 17.5634, 14.8244, 13.8495] +24-11-19 18:39:53 | D | - best error = [ 12.9177, 12.9177, 12.9177, 12.9177] +24-11-19 18:39:53 | D | + error = 12.9177 +24-11-19 18:39:53 | D | + scale = [min=3.0242, max=17.6704] +24-11-19 18:40:00 | D | - Smoothing model.layers.5 +24-11-19 18:40:00 | D | - model.layers.5.self_attn.attn_k +24-11-19 18:40:00 | D | + w: None +24-11-19 18:40:00 | D | + x: None +24-11-19 18:40:00 | D | + y: sint8 +24-11-19 18:40:00 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:40:00 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:40:00 | D | + x - AbsMax +24-11-19 18:40:00 | D | + x = [min=2.9180, max=18.8281] +24-11-19 18:40:00 | D | + y - AbsMax +24-11-19 18:40:00 | D | + y = [min=2.4434, max=27.2812] +24-11-19 18:40:00 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:40:06 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:40:06 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:40:06 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:40:06 | D | - sum error = [ 27.1517, 25.4816, 23.5039, 21.7445, 25.9823] +24-11-19 18:40:06 | D | - best error = [ 27.1517, 25.4816, 23.5039, 21.7445, 21.7445] +24-11-19 18:40:06 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:40:06 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:40:06 | D | - sum error = [ 22.2799, 21.0292, 20.0088, 20.5225, 19.9985] +24-11-19 18:40:06 | D | - best error = [ 21.7445, 21.0292, 20.0088, 20.0088, 19.9985] +24-11-19 18:40:06 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:40:06 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:40:06 | D | - sum error = [ 19.7660, 20.4908, 17.0625, 17.8040, 16.1847] +24-11-19 18:40:06 | D | - best error = [ 19.7660, 19.7660, 17.0625, 17.0625, 16.1847] +24-11-19 18:40:06 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:40:06 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:40:06 | D | - sum error = [ 17.2002, 15.5329, 14.3459, 16.5048, 13.6060] +24-11-19 18:40:06 | D | - best error = [ 16.1847, 15.5329, 14.3459, 14.3459, 13.6060] +24-11-19 18:40:06 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:40:06 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:40:06 | D | - sum error = [ 48.0090, 44.8583, 37.8915, 37.6662, 31.2861] +24-11-19 18:40:06 | D | - best error = [ 13.6060, 13.6060, 13.6060, 13.6060, 13.6060] +24-11-19 18:40:06 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:40:06 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:40:06 | D | - sum error = [ 34.0286, 28.9405, 24.8074, 23.4880, 22.3893] +24-11-19 18:40:06 | D | - best error = [ 13.6060, 13.6060, 13.6060, 13.6060, 13.6060] +24-11-19 18:40:06 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:40:06 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:40:06 | D | - sum error = [ 21.9641, 20.0147, 20.2605, 19.8026, 17.2462] +24-11-19 18:40:06 | D | - best error = [ 13.6060, 13.6060, 13.6060, 13.6060, 13.6060] +24-11-19 18:40:06 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:40:06 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:40:06 | D | - sum error = [ 16.8498, 17.3905, 15.4714, 15.4429] +24-11-19 18:40:06 | D | - best error = [ 13.6060, 13.6060, 13.6060, 13.6060] +24-11-19 18:40:06 | D | + error = 13.6060 +24-11-19 18:40:06 | D | + scale = [min=2.3366, max=23.1244] +24-11-19 18:40:13 | D | - Smoothing model.layers.6 +24-11-19 18:40:13 | D | - model.layers.6.self_attn.attn_k +24-11-19 18:40:13 | D | + w: None +24-11-19 18:40:13 | D | + x: None +24-11-19 18:40:13 | D | + y: sint8 +24-11-19 18:40:13 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:40:13 | D | + finished parsing calibration arguments, ram usage: 11.5 +24-11-19 18:40:13 | D | + x - AbsMax +24-11-19 18:40:13 | D | + x = [min=2.4512, max=18.4844] +24-11-19 18:40:13 | D | + y - AbsMax +24-11-19 18:40:13 | D | + y = [min=3.5645, max=22.1094] +24-11-19 18:40:13 | D | + finished reseting calibrator, ram usage: 11.5 +24-11-19 18:40:19 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:40:19 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:40:19 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:40:19 | D | - sum error = [ 23.9308, 23.2757, 24.0716, 23.8867, 22.0313] +24-11-19 18:40:19 | D | - best error = [ 23.9308, 23.2757, 23.2757, 23.2757, 22.0313] +24-11-19 18:40:19 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:40:19 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:40:19 | D | - sum error = [ 18.9395, 22.6747, 19.6582, 19.7498, 20.2179] +24-11-19 18:40:19 | D | - best error = [ 18.9395, 18.9395, 18.9395, 18.9395, 18.9395] +24-11-19 18:40:19 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:40:19 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:40:19 | D | - sum error = [ 18.1268, 19.2679, 18.7790, 16.9481, 17.3420] +24-11-19 18:40:19 | D | - best error = [ 18.1268, 18.1268, 18.1268, 16.9481, 16.9481] +24-11-19 18:40:19 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:40:19 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:40:19 | D | - sum error = [ 20.4201, 18.1934, 19.2963, 18.2755, 16.1636] +24-11-19 18:40:19 | D | - best error = [ 16.9481, 16.9481, 16.9481, 16.9481, 16.1636] +24-11-19 18:40:19 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:40:19 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:40:19 | D | - sum error = [ 51.6831, 42.6431, 36.9191, 37.9299, 34.2942] +24-11-19 18:40:19 | D | - best error = [ 16.1636, 16.1636, 16.1636, 16.1636, 16.1636] +24-11-19 18:40:19 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:40:19 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:40:19 | D | - sum error = [ 34.2759, 29.7117, 27.3872, 24.3080, 24.4482] +24-11-19 18:40:19 | D | - best error = [ 16.1636, 16.1636, 16.1636, 16.1636, 16.1636] +24-11-19 18:40:19 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:40:19 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:40:19 | D | - sum error = [ 20.8335, 24.0936, 21.5683, 19.4415, 19.3777] +24-11-19 18:40:19 | D | - best error = [ 16.1636, 16.1636, 16.1636, 16.1636, 16.1636] +24-11-19 18:40:19 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:40:19 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:40:19 | D | - sum error = [ 18.0544, 15.4663, 18.6958, 18.4269] +24-11-19 18:40:19 | D | - best error = [ 16.1636, 15.4663, 15.4663, 15.4663] +24-11-19 18:40:19 | D | + error = 15.4663 +24-11-19 18:40:19 | D | + scale = [min=2.4451, max=9.4385] +24-11-19 18:40:25 | D | - Smoothing model.layers.7 +24-11-19 18:40:25 | D | - model.layers.7.self_attn.attn_k +24-11-19 18:40:25 | D | + w: None +24-11-19 18:40:25 | D | + x: None +24-11-19 18:40:25 | D | + y: sint8 +24-11-19 18:40:25 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:40:25 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:40:26 | D | + x - AbsMax +24-11-19 18:40:26 | D | + x = [min=2.7207, max=17.5469] +24-11-19 18:40:26 | D | + y - AbsMax +24-11-19 18:40:26 | D | + y = [min=3.4629, max=23.9844] +24-11-19 18:40:26 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:40:32 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:40:32 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:40:32 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:40:32 | D | - sum error = [ 31.4706, 32.6667, 30.4724, 33.8385, 31.4502] +24-11-19 18:40:32 | D | - best error = [ 31.4706, 31.4706, 30.4724, 30.4724, 30.4724] +24-11-19 18:40:32 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:40:32 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:40:32 | D | - sum error = [ 29.3631, 27.8309, 29.0893, 28.3829, 25.0293] +24-11-19 18:40:32 | D | - best error = [ 29.3631, 27.8309, 27.8309, 27.8309, 25.0293] +24-11-19 18:40:32 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:40:32 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:40:32 | D | - sum error = [ 25.4320, 23.8808, 24.7272, 27.7494, 27.0241] +24-11-19 18:40:32 | D | - best error = [ 25.0293, 23.8808, 23.8808, 23.8808, 23.8808] +24-11-19 18:40:32 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:40:32 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:40:32 | D | - sum error = [ 23.6623, 21.5847, 22.2585, 26.1266, 22.4083] +24-11-19 18:40:32 | D | - best error = [ 23.6623, 21.5847, 21.5847, 21.5847, 21.5847] +24-11-19 18:40:32 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:40:32 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:40:32 | D | - sum error = [ 53.8295, 46.2339, 43.7831, 43.1015, 37.9882] +24-11-19 18:40:32 | D | - best error = [ 21.5847, 21.5847, 21.5847, 21.5847, 21.5847] +24-11-19 18:40:32 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:40:32 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:40:32 | D | - sum error = [ 35.7466, 36.6016, 31.9315, 28.1794, 27.3651] +24-11-19 18:40:32 | D | - best error = [ 21.5847, 21.5847, 21.5847, 21.5847, 21.5847] +24-11-19 18:40:32 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:40:32 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:40:32 | D | - sum error = [ 28.3289, 29.0870, 28.6164, 27.4058, 25.7668] +24-11-19 18:40:32 | D | - best error = [ 21.5847, 21.5847, 21.5847, 21.5847, 21.5847] +24-11-19 18:40:32 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:40:32 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:40:32 | D | - sum error = [ 24.0739, 24.5334, 24.4049, 23.3444] +24-11-19 18:40:32 | D | - best error = [ 21.5847, 21.5847, 21.5847, 21.5847] +24-11-19 18:40:32 | D | + error = 21.5847 +24-11-19 18:40:32 | D | + scale = [min=2.7012, max=12.7041] +24-11-19 18:40:38 | D | - Smoothing model.layers.8 +24-11-19 18:40:38 | D | - model.layers.8.self_attn.attn_k +24-11-19 18:40:38 | D | + w: None +24-11-19 18:40:38 | D | + x: None +24-11-19 18:40:38 | D | + y: sint8 +24-11-19 18:40:38 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:40:38 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:40:38 | D | + x - AbsMax +24-11-19 18:40:38 | D | + x = [min=2.5527, max=19.6406] +24-11-19 18:40:38 | D | + y - AbsMax +24-11-19 18:40:38 | D | + y = [min=2.7891, max=23.6719] +24-11-19 18:40:38 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:40:45 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:40:45 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:40:45 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:40:45 | D | - sum error = [ 27.9102, 31.9682, 26.7007, 25.7901, 25.9988] +24-11-19 18:40:45 | D | - best error = [ 27.9102, 27.9102, 26.7007, 25.7901, 25.7901] +24-11-19 18:40:45 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:40:45 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:40:45 | D | - sum error = [ 24.0665, 24.0304, 25.6819, 23.0984, 23.4911] +24-11-19 18:40:45 | D | - best error = [ 24.0665, 24.0304, 24.0304, 23.0984, 23.0984] +24-11-19 18:40:45 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:40:45 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:40:45 | D | - sum error = [ 21.6155, 21.4487, 21.5819, 19.9092, 18.4513] +24-11-19 18:40:45 | D | - best error = [ 21.6155, 21.4487, 21.4487, 19.9092, 18.4513] +24-11-19 18:40:45 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:40:45 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:40:45 | D | - sum error = [ 19.3013, 18.5948, 19.6082, 17.6498, 17.2464] +24-11-19 18:40:45 | D | - best error = [ 18.4513, 18.4513, 18.4513, 17.6498, 17.2464] +24-11-19 18:40:45 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:40:45 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:40:45 | D | - sum error = [ 60.8828, 53.1553, 49.8769, 46.2990, 40.3415] +24-11-19 18:40:45 | D | - best error = [ 17.2464, 17.2464, 17.2464, 17.2464, 17.2464] +24-11-19 18:40:45 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:40:45 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:40:45 | D | - sum error = [ 38.7726, 35.1459, 33.3425, 30.2487, 27.7743] +24-11-19 18:40:45 | D | - best error = [ 17.2464, 17.2464, 17.2464, 17.2464, 17.2464] +24-11-19 18:40:45 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:40:45 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:40:45 | D | - sum error = [ 27.3476, 24.0843, 23.3423, 21.9374, 20.4819] +24-11-19 18:40:45 | D | - best error = [ 17.2464, 17.2464, 17.2464, 17.2464, 17.2464] +24-11-19 18:40:45 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:40:45 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:40:45 | D | - sum error = [ 20.3244, 19.1243, 19.0773, 18.6373] +24-11-19 18:40:45 | D | - best error = [ 17.2464, 17.2464, 17.2464, 17.2464] +24-11-19 18:40:45 | D | + error = 17.2464 +24-11-19 18:40:45 | D | + scale = [min=2.6496, max=20.2079] +24-11-19 18:40:51 | D | - Smoothing model.layers.9 +24-11-19 18:40:51 | D | - model.layers.9.self_attn.attn_k +24-11-19 18:40:51 | D | + w: None +24-11-19 18:40:51 | D | + x: None +24-11-19 18:40:51 | D | + y: sint8 +24-11-19 18:40:51 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:40:51 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:40:51 | D | + x - AbsMax +24-11-19 18:40:51 | D | + x = [min=2.4062, max=15.3125] +24-11-19 18:40:51 | D | + y - AbsMax +24-11-19 18:40:51 | D | + y = [min=3.0723, max=25.1562] +24-11-19 18:40:51 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:40:57 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:40:57 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:40:57 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:40:57 | D | - sum error = [ 33.7289, 33.2497, 30.4901, 32.0686, 30.9633] +24-11-19 18:40:57 | D | - best error = [ 33.7289, 33.2497, 30.4901, 30.4901, 30.4901] +24-11-19 18:40:57 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:40:57 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:40:57 | D | - sum error = [ 27.7688, 26.2281, 27.3425, 23.5923, 24.2986] +24-11-19 18:40:57 | D | - best error = [ 27.7688, 26.2281, 26.2281, 23.5923, 23.5923] +24-11-19 18:40:57 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:40:57 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:40:57 | D | - sum error = [ 22.4573, 24.5350, 23.0917, 20.9470, 21.8851] +24-11-19 18:40:57 | D | - best error = [ 22.4573, 22.4573, 22.4573, 20.9470, 20.9470] +24-11-19 18:40:57 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:40:57 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:40:57 | D | - sum error = [ 19.5837, 20.3113, 19.9093, 19.6440, 16.9186] +24-11-19 18:40:57 | D | - best error = [ 19.5837, 19.5837, 19.5837, 19.5837, 16.9186] +24-11-19 18:40:57 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:40:57 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:40:57 | D | - sum error = [ 66.6836, 66.6265, 60.0851, 52.9642, 43.2529] +24-11-19 18:40:57 | D | - best error = [ 16.9186, 16.9186, 16.9186, 16.9186, 16.9186] +24-11-19 18:40:57 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:40:57 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:40:57 | D | - sum error = [ 40.1277, 36.6514, 36.5449, 36.9710, 33.4277] +24-11-19 18:40:57 | D | - best error = [ 16.9186, 16.9186, 16.9186, 16.9186, 16.9186] +24-11-19 18:40:57 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:40:57 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:40:57 | D | - sum error = [ 31.1947, 26.9364, 30.0226, 25.0586, 22.2656] +24-11-19 18:40:57 | D | - best error = [ 16.9186, 16.9186, 16.9186, 16.9186, 16.9186] +24-11-19 18:40:57 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:40:57 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:40:57 | D | - sum error = [ 21.3659, 21.3657, 18.5638, 19.5323] +24-11-19 18:40:57 | D | - best error = [ 16.9186, 16.9186, 16.9186, 16.9186] +24-11-19 18:40:57 | D | + error = 16.9186 +24-11-19 18:40:57 | D | + scale = [min=2.9046, max=21.4098] +24-11-19 18:41:03 | D | - Smoothing model.layers.10 +24-11-19 18:41:03 | D | - model.layers.10.self_attn.attn_k +24-11-19 18:41:03 | D | + w: None +24-11-19 18:41:03 | D | + x: None +24-11-19 18:41:03 | D | + y: sint8 +24-11-19 18:41:03 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:41:03 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:41:03 | D | + x - AbsMax +24-11-19 18:41:03 | D | + x = [min=2.7832, max=16.7969] +24-11-19 18:41:03 | D | + y - AbsMax +24-11-19 18:41:03 | D | + y = [min=3.5762, max=23.3750] +24-11-19 18:41:03 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:41:09 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:41:09 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:41:09 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:41:09 | D | - sum error = [ 29.0194, 26.2716, 28.1552, 26.4109, 26.9005] +24-11-19 18:41:09 | D | - best error = [ 29.0194, 26.2716, 26.2716, 26.2716, 26.2716] +24-11-19 18:41:09 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:41:09 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:41:09 | D | - sum error = [ 27.2829, 25.5716, 24.2359, 23.0337, 23.4623] +24-11-19 18:41:09 | D | - best error = [ 26.2716, 25.5716, 24.2359, 23.0337, 23.0337] +24-11-19 18:41:09 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:41:09 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:41:09 | D | - sum error = [ 19.7481, 19.7647, 21.6039, 19.5886, 18.2835] +24-11-19 18:41:09 | D | - best error = [ 19.7481, 19.7481, 19.7481, 19.5886, 18.2835] +24-11-19 18:41:09 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:41:09 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:41:09 | D | - sum error = [ 18.8733, 18.5238, 19.0058, 17.7739, 16.7766] +24-11-19 18:41:09 | D | - best error = [ 18.2835, 18.2835, 18.2835, 17.7739, 16.7766] +24-11-19 18:41:09 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:41:09 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:41:09 | D | - sum error = [ 61.2661, 55.9057, 50.2575, 45.1080, 42.4466] +24-11-19 18:41:09 | D | - best error = [ 16.7766, 16.7766, 16.7766, 16.7766, 16.7766] +24-11-19 18:41:09 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:41:09 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:41:09 | D | - sum error = [ 37.1820, 39.0036, 34.1307, 31.4384, 30.6290] +24-11-19 18:41:09 | D | - best error = [ 16.7766, 16.7766, 16.7766, 16.7766, 16.7766] +24-11-19 18:41:09 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:41:09 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:41:09 | D | - sum error = [ 25.6504, 25.3192, 28.4872, 26.6923, 20.1167] +24-11-19 18:41:09 | D | - best error = [ 16.7766, 16.7766, 16.7766, 16.7766, 16.7766] +24-11-19 18:41:09 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:41:09 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:41:09 | D | - sum error = [ 19.5810, 19.2372, 18.1946, 16.8559] +24-11-19 18:41:09 | D | - best error = [ 16.7766, 16.7766, 16.7766, 16.7766] +24-11-19 18:41:09 | D | + error = 16.7766 +24-11-19 18:41:09 | D | + scale = [min=3.3554, max=19.9671] +24-11-19 18:41:16 | D | - Smoothing model.layers.11 +24-11-19 18:41:16 | D | - model.layers.11.self_attn.attn_k +24-11-19 18:41:16 | D | + w: None +24-11-19 18:41:16 | D | + x: None +24-11-19 18:41:16 | D | + y: sint8 +24-11-19 18:41:16 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:41:16 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:41:16 | D | + x - AbsMax +24-11-19 18:41:16 | D | + x = [min=2.3789, max=15.8125] +24-11-19 18:41:16 | D | + y - AbsMax +24-11-19 18:41:16 | D | + y = [min=3.2129, max=26.1406] +24-11-19 18:41:16 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:41:22 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:41:22 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:41:22 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:41:22 | D | - sum error = [ 33.8501, 32.2029, 32.0886, 30.4229, 31.0411] +24-11-19 18:41:22 | D | - best error = [ 33.8501, 32.2029, 32.0886, 30.4229, 30.4229] +24-11-19 18:41:22 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:41:22 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:41:22 | D | - sum error = [ 31.3995, 28.0928, 30.3285, 29.9048, 30.1724] +24-11-19 18:41:22 | D | - best error = [ 30.4229, 28.0928, 28.0928, 28.0928, 28.0928] +24-11-19 18:41:22 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:41:22 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:41:22 | D | - sum error = [ 24.0137, 23.3708, 25.7934, 25.0424, 23.1192] +24-11-19 18:41:22 | D | - best error = [ 24.0137, 23.3708, 23.3708, 23.3708, 23.1192] +24-11-19 18:41:22 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:41:22 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:41:22 | D | - sum error = [ 22.0978, 22.4191, 24.9844, 20.1585, 21.5677] +24-11-19 18:41:22 | D | - best error = [ 22.0978, 22.0978, 22.0978, 20.1585, 20.1585] +24-11-19 18:41:22 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:41:22 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:41:22 | D | - sum error = [ 60.5358, 53.6791, 55.5766, 47.0431, 42.7085] +24-11-19 18:41:22 | D | - best error = [ 20.1585, 20.1585, 20.1585, 20.1585, 20.1585] +24-11-19 18:41:22 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:41:22 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:41:22 | D | - sum error = [ 43.1091, 37.9036, 33.4480, 32.0073, 32.0714] +24-11-19 18:41:22 | D | - best error = [ 20.1585, 20.1585, 20.1585, 20.1585, 20.1585] +24-11-19 18:41:22 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:41:22 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:41:22 | D | - sum error = [ 27.3505, 28.5079, 26.3469, 28.2733, 26.4772] +24-11-19 18:41:22 | D | - best error = [ 20.1585, 20.1585, 20.1585, 20.1585, 20.1585] +24-11-19 18:41:22 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:41:22 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:41:22 | D | - sum error = [ 24.3824, 22.3383, 22.3382, 18.6195] +24-11-19 18:41:22 | D | - best error = [ 20.1585, 20.1585, 20.1585, 18.6195] +24-11-19 18:41:22 | D | + error = 18.6195 +24-11-19 18:41:22 | D | + scale = [min=2.8178, max=19.5218] +24-11-19 18:41:28 | D | - Smoothing model.layers.12 +24-11-19 18:41:28 | D | - model.layers.12.self_attn.attn_k +24-11-19 18:41:28 | D | + w: None +24-11-19 18:41:28 | D | + x: None +24-11-19 18:41:28 | D | + y: sint8 +24-11-19 18:41:28 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:41:28 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:41:29 | D | + x - AbsMax +24-11-19 18:41:29 | D | + x = [min=2.6582, max=21.0625] +24-11-19 18:41:29 | D | + y - AbsMax +24-11-19 18:41:29 | D | + y = [min=3.4844, max=25.3594] +24-11-19 18:41:29 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:41:35 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:41:35 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:41:35 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:41:35 | D | - sum error = [ 41.5660, 42.1655, 40.0990, 40.5716, 37.3839] +24-11-19 18:41:35 | D | - best error = [ 41.5660, 41.5660, 40.0990, 40.0990, 37.3839] +24-11-19 18:41:35 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:41:35 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:41:35 | D | - sum error = [ 36.5638, 34.7830, 35.6264, 32.7895, 34.1203] +24-11-19 18:41:35 | D | - best error = [ 36.5638, 34.7830, 34.7830, 32.7895, 32.7895] +24-11-19 18:41:35 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:41:35 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:41:35 | D | - sum error = [ 32.7301, 30.5264, 31.3039, 29.3953, 29.5828] +24-11-19 18:41:35 | D | - best error = [ 32.7301, 30.5264, 30.5264, 29.3953, 29.3953] +24-11-19 18:41:35 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:41:35 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:41:35 | D | - sum error = [ 29.0574, 28.2732, 26.9362, 27.0414, 27.2275] +24-11-19 18:41:35 | D | - best error = [ 29.0574, 28.2732, 26.9362, 26.9362, 26.9362] +24-11-19 18:41:35 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:41:35 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:41:35 | D | - sum error = [ 117.0205, 105.8680, 96.1963, 83.5715, 73.2900] +24-11-19 18:41:35 | D | - best error = [ 26.9362, 26.9362, 26.9362, 26.9362, 26.9362] +24-11-19 18:41:35 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:41:35 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:41:35 | D | - sum error = [ 69.9847, 60.8832, 56.9455, 49.9288, 45.1651] +24-11-19 18:41:35 | D | - best error = [ 26.9362, 26.9362, 26.9362, 26.9362, 26.9362] +24-11-19 18:41:35 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:41:35 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:41:35 | D | - sum error = [ 41.2601, 43.4255, 40.7736, 37.1588, 31.8205] +24-11-19 18:41:35 | D | - best error = [ 26.9362, 26.9362, 26.9362, 26.9362, 26.9362] +24-11-19 18:41:35 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:41:35 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:41:35 | D | - sum error = [ 33.8957, 29.5154, 29.7290, 28.8040] +24-11-19 18:41:35 | D | - best error = [ 26.9362, 26.9362, 26.9362, 26.9362] +24-11-19 18:41:35 | D | + error = 26.9362 +24-11-19 18:41:35 | D | + scale = [min=2.8894, max=15.6141] +24-11-19 18:41:41 | D | - Smoothing model.layers.13 +24-11-19 18:41:41 | D | - model.layers.13.self_attn.attn_k +24-11-19 18:41:41 | D | + w: None +24-11-19 18:41:41 | D | + x: None +24-11-19 18:41:41 | D | + y: sint8 +24-11-19 18:41:41 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:41:41 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:41:41 | D | + x - AbsMax +24-11-19 18:41:41 | D | + x = [min=2.3457, max=18.3906] +24-11-19 18:41:41 | D | + y - AbsMax +24-11-19 18:41:41 | D | + y = [min=2.7832, max=23.2812] +24-11-19 18:41:41 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:41:47 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:41:47 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:41:47 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:41:47 | D | - sum error = [ 35.8022, 30.6970, 31.8450, 32.2445, 28.5813] +24-11-19 18:41:47 | D | - best error = [ 35.8022, 30.6970, 30.6970, 30.6970, 28.5813] +24-11-19 18:41:47 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:41:47 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:41:47 | D | - sum error = [ 27.4213, 26.8843, 29.7396, 25.5865, 25.4846] +24-11-19 18:41:47 | D | - best error = [ 27.4213, 26.8843, 26.8843, 25.5865, 25.4846] +24-11-19 18:41:47 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:41:47 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:41:47 | D | - sum error = [ 25.4453, 24.6203, 22.2619, 23.9087, 25.2574] +24-11-19 18:41:47 | D | - best error = [ 25.4453, 24.6203, 22.2619, 22.2619, 22.2619] +24-11-19 18:41:47 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:41:47 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:41:47 | D | - sum error = [ 21.4129, 21.4095, 19.5735, 20.2430, 20.5431] +24-11-19 18:41:47 | D | - best error = [ 21.4129, 21.4095, 19.5735, 19.5735, 19.5735] +24-11-19 18:41:47 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:41:47 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:41:47 | D | - sum error = [ 74.9509, 68.3134, 62.4132, 55.9784, 50.3419] +24-11-19 18:41:47 | D | - best error = [ 19.5735, 19.5735, 19.5735, 19.5735, 19.5735] +24-11-19 18:41:47 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:41:47 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:41:47 | D | - sum error = [ 48.2272, 43.3472, 38.9786, 40.2175, 36.2273] +24-11-19 18:41:47 | D | - best error = [ 19.5735, 19.5735, 19.5735, 19.5735, 19.5735] +24-11-19 18:41:47 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:41:47 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:41:47 | D | - sum error = [ 36.0474, 30.8868, 27.8253, 30.2394, 25.8557] +24-11-19 18:41:47 | D | - best error = [ 19.5735, 19.5735, 19.5735, 19.5735, 19.5735] +24-11-19 18:41:47 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:41:47 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:41:47 | D | - sum error = [ 22.6712, 24.6404, 22.1334, 21.5753] +24-11-19 18:41:47 | D | - best error = [ 19.5735, 19.5735, 19.5735, 19.5735] +24-11-19 18:41:47 | D | + error = 19.5735 +24-11-19 18:41:47 | D | + scale = [min=2.3871, max=14.5196] +24-11-19 18:41:53 | D | - Smoothing model.layers.14 +24-11-19 18:41:53 | D | - model.layers.14.self_attn.attn_k +24-11-19 18:41:53 | D | + w: None +24-11-19 18:41:53 | D | + x: None +24-11-19 18:41:53 | D | + y: sint8 +24-11-19 18:41:53 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:41:53 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:41:53 | D | + x - AbsMax +24-11-19 18:41:53 | D | + x = [min=2.2734, max=16.0781] +24-11-19 18:41:53 | D | + y - AbsMax +24-11-19 18:41:53 | D | + y = [min=2.9512, max=25.4531] +24-11-19 18:41:53 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:42:00 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:42:00 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:42:00 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:42:00 | D | - sum error = [ 44.3933, 45.1293, 42.6719, 37.2829, 36.5966] +24-11-19 18:42:00 | D | - best error = [ 44.3933, 44.3933, 42.6719, 37.2829, 36.5966] +24-11-19 18:42:00 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:42:00 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:42:00 | D | - sum error = [ 36.0495, 38.1060, 36.7833, 35.1087, 31.5539] +24-11-19 18:42:00 | D | - best error = [ 36.0495, 36.0495, 36.0495, 35.1087, 31.5539] +24-11-19 18:42:00 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:42:00 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:42:00 | D | - sum error = [ 30.6803, 32.4976, 29.8508, 31.3182, 27.9157] +24-11-19 18:42:00 | D | - best error = [ 30.6803, 30.6803, 29.8508, 29.8508, 27.9157] +24-11-19 18:42:00 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:42:00 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:42:00 | D | - sum error = [ 29.2394, 26.1243, 25.8644, 25.2316, 25.9546] +24-11-19 18:42:00 | D | - best error = [ 27.9157, 26.1243, 25.8644, 25.2316, 25.2316] +24-11-19 18:42:00 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:42:00 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:42:00 | D | - sum error = [ 82.7295, 74.1895, 70.1282, 61.3622, 60.3586] +24-11-19 18:42:00 | D | - best error = [ 25.2316, 25.2316, 25.2316, 25.2316, 25.2316] +24-11-19 18:42:00 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:42:00 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:42:00 | D | - sum error = [ 53.2419, 49.1991, 44.3800, 47.0597, 37.6337] +24-11-19 18:42:00 | D | - best error = [ 25.2316, 25.2316, 25.2316, 25.2316, 25.2316] +24-11-19 18:42:00 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:42:00 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:42:00 | D | - sum error = [ 35.3101, 37.8431, 33.3907, 31.7219, 30.3589] +24-11-19 18:42:00 | D | - best error = [ 25.2316, 25.2316, 25.2316, 25.2316, 25.2316] +24-11-19 18:42:00 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:42:00 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:42:00 | D | - sum error = [ 29.7508, 28.5511, 27.6246, 26.7521] +24-11-19 18:42:00 | D | - best error = [ 25.2316, 25.2316, 25.2316, 25.2316] +24-11-19 18:42:00 | D | + error = 25.2316 +24-11-19 18:42:00 | D | + scale = [min=2.6485, max=18.4148] +24-11-19 18:42:06 | D | - Smoothing model.layers.15 +24-11-19 18:42:06 | D | - model.layers.15.self_attn.attn_k +24-11-19 18:42:06 | D | + w: None +24-11-19 18:42:06 | D | + x: None +24-11-19 18:42:06 | D | + y: sint8 +24-11-19 18:42:06 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:42:06 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:42:06 | D | + x - AbsMax +24-11-19 18:42:06 | D | + x = [min=2.6152, max=18.0625] +24-11-19 18:42:06 | D | + y - AbsMax +24-11-19 18:42:06 | D | + y = [min=3.1660, max=24.4531] +24-11-19 18:42:06 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:42:12 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:42:12 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:42:12 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:42:12 | D | - sum error = [ 39.1834, 39.9294, 37.8002, 35.5435, 34.5503] +24-11-19 18:42:12 | D | - best error = [ 39.1834, 39.1834, 37.8002, 35.5435, 34.5503] +24-11-19 18:42:12 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:42:12 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:42:12 | D | - sum error = [ 37.6996, 32.0305, 33.8328, 35.1301, 31.1262] +24-11-19 18:42:12 | D | - best error = [ 34.5503, 32.0305, 32.0305, 32.0305, 31.1262] +24-11-19 18:42:12 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:42:12 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:42:12 | D | - sum error = [ 29.8959, 28.5940, 28.7403, 30.2517, 28.6175] +24-11-19 18:42:12 | D | - best error = [ 29.8959, 28.5940, 28.5940, 28.5940, 28.5940] +24-11-19 18:42:12 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:42:12 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:42:12 | D | - sum error = [ 28.2511, 27.1377, 27.4290, 26.7957, 26.7750] +24-11-19 18:42:12 | D | - best error = [ 28.2511, 27.1377, 27.1377, 26.7957, 26.7750] +24-11-19 18:42:12 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:42:12 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:42:12 | D | - sum error = [ 83.7776, 75.8851, 69.6491, 61.0682, 58.9339] +24-11-19 18:42:12 | D | - best error = [ 26.7750, 26.7750, 26.7750, 26.7750, 26.7750] +24-11-19 18:42:12 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:42:12 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:42:12 | D | - sum error = [ 54.5545, 54.1891, 43.8804, 39.8017, 37.8192] +24-11-19 18:42:12 | D | - best error = [ 26.7750, 26.7750, 26.7750, 26.7750, 26.7750] +24-11-19 18:42:12 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:42:12 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:42:12 | D | - sum error = [ 36.0985, 35.7527, 30.7538, 32.6226, 30.8616] +24-11-19 18:42:12 | D | - best error = [ 26.7750, 26.7750, 26.7750, 26.7750, 26.7750] +24-11-19 18:42:12 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:42:12 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:42:12 | D | - sum error = [ 29.5035, 28.0302, 26.9566, 26.8767] +24-11-19 18:42:12 | D | - best error = [ 26.7750, 26.7750, 26.7750, 26.7750] +24-11-19 18:42:12 | D | + error = 26.7750 +24-11-19 18:42:12 | D | + scale = [min=2.9887, max=20.8410] +24-11-19 18:42:18 | D | - Smoothing model.layers.16 +24-11-19 18:42:18 | D | - model.layers.16.self_attn.attn_k +24-11-19 18:42:18 | D | + w: None +24-11-19 18:42:18 | D | + x: None +24-11-19 18:42:18 | D | + y: sint8 +24-11-19 18:42:18 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:42:18 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:42:18 | D | + x - AbsMax +24-11-19 18:42:18 | D | + x = [min=2.5508, max=19.0781] +24-11-19 18:42:18 | D | + y - AbsMax +24-11-19 18:42:18 | D | + y = [min=2.6094, max=25.7656] +24-11-19 18:42:18 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:42:24 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:42:24 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:42:24 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:42:24 | D | - sum error = [ 49.0091, 44.6158, 40.4091, 42.9589, 42.0679] +24-11-19 18:42:24 | D | - best error = [ 49.0091, 44.6158, 40.4091, 40.4091, 40.4091] +24-11-19 18:42:24 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:42:24 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:42:24 | D | - sum error = [ 37.2238, 34.7578, 37.8537, 35.7836, 34.1485] +24-11-19 18:42:24 | D | - best error = [ 37.2238, 34.7578, 34.7578, 34.7578, 34.1485] +24-11-19 18:42:24 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:42:24 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:42:24 | D | - sum error = [ 34.2738, 34.3162, 30.5869, 31.0727, 29.7999] +24-11-19 18:42:24 | D | - best error = [ 34.1485, 34.1485, 30.5869, 30.5869, 29.7999] +24-11-19 18:42:24 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:42:24 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:42:24 | D | - sum error = [ 28.2078, 30.5756, 28.2274, 29.0973, 28.4525] +24-11-19 18:42:24 | D | - best error = [ 28.2078, 28.2078, 28.2078, 28.2078, 28.2078] +24-11-19 18:42:24 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:42:24 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:42:24 | D | - sum error = [ 92.1397, 84.6659, 73.5645, 73.5955, 61.9554] +24-11-19 18:42:24 | D | - best error = [ 28.2078, 28.2078, 28.2078, 28.2078, 28.2078] +24-11-19 18:42:24 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:42:24 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:42:24 | D | - sum error = [ 57.2880, 53.0676, 45.0255, 46.5353, 44.4149] +24-11-19 18:42:24 | D | - best error = [ 28.2078, 28.2078, 28.2078, 28.2078, 28.2078] +24-11-19 18:42:24 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:42:24 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:42:24 | D | - sum error = [ 38.9311, 36.8337, 35.0764, 35.6108, 30.3776] +24-11-19 18:42:24 | D | - best error = [ 28.2078, 28.2078, 28.2078, 28.2078, 28.2078] +24-11-19 18:42:24 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:42:24 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:42:24 | D | - sum error = [ 28.9612, 33.0469, 30.1502, 29.7810] +24-11-19 18:42:24 | D | - best error = [ 28.2078, 28.2078, 28.2078, 28.2078] +24-11-19 18:42:24 | D | + error = 28.2078 +24-11-19 18:42:24 | D | + scale = [min=2.0531, max=11.4362] +24-11-19 18:42:31 | D | - Smoothing model.layers.17 +24-11-19 18:42:31 | D | - model.layers.17.self_attn.attn_k +24-11-19 18:42:31 | D | + w: None +24-11-19 18:42:31 | D | + x: None +24-11-19 18:42:31 | D | + y: sint8 +24-11-19 18:42:31 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:42:31 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:42:31 | D | + x - AbsMax +24-11-19 18:42:31 | D | + x = [min=2.8594, max=18.2969] +24-11-19 18:42:31 | D | + y - AbsMax +24-11-19 18:42:31 | D | + y = [min=2.9941, max=23.2031] +24-11-19 18:42:31 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:42:37 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:42:37 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:42:37 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:42:37 | D | - sum error = [ 39.5416, 36.0503, 36.8088, 36.3417, 35.2969] +24-11-19 18:42:37 | D | - best error = [ 39.5416, 36.0503, 36.0503, 36.0503, 35.2969] +24-11-19 18:42:37 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:42:37 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:42:37 | D | - sum error = [ 30.4491, 33.2754, 30.3800, 35.1771, 29.1957] +24-11-19 18:42:37 | D | - best error = [ 30.4491, 30.4491, 30.3800, 30.3800, 29.1957] +24-11-19 18:42:37 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:42:37 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:42:37 | D | - sum error = [ 29.4680, 32.3240, 30.6921, 26.9627, 27.0066] +24-11-19 18:42:37 | D | - best error = [ 29.1957, 29.1957, 29.1957, 26.9627, 26.9627] +24-11-19 18:42:37 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:42:37 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:42:37 | D | - sum error = [ 25.4299, 24.8745, 24.1767, 24.0610, 22.7845] +24-11-19 18:42:37 | D | - best error = [ 25.4299, 24.8745, 24.1767, 24.0610, 22.7845] +24-11-19 18:42:37 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:42:37 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:42:37 | D | - sum error = [ 71.2353, 66.3185, 62.0239, 56.6115, 49.9739] +24-11-19 18:42:37 | D | - best error = [ 22.7845, 22.7845, 22.7845, 22.7845, 22.7845] +24-11-19 18:42:37 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:42:37 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:42:37 | D | - sum error = [ 49.2724, 44.7736, 39.5001, 37.7336, 35.0104] +24-11-19 18:42:37 | D | - best error = [ 22.7845, 22.7845, 22.7845, 22.7845, 22.7845] +24-11-19 18:42:37 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:42:37 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:42:37 | D | - sum error = [ 33.8796, 33.3357, 31.9860, 30.1948, 31.7117] +24-11-19 18:42:37 | D | - best error = [ 22.7845, 22.7845, 22.7845, 22.7845, 22.7845] +24-11-19 18:42:37 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:42:37 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:42:37 | D | - sum error = [ 26.9996, 27.3901, 23.8675, 23.1488] +24-11-19 18:42:37 | D | - best error = [ 22.7845, 22.7845, 22.7845, 22.7845] +24-11-19 18:42:37 | D | + error = 22.7845 +24-11-19 18:42:37 | D | + scale = [min=2.8344, max=19.8276] +24-11-19 18:42:43 | D | - Smoothing model.layers.18 +24-11-19 18:42:43 | D | - model.layers.18.self_attn.attn_k +24-11-19 18:42:43 | D | + w: None +24-11-19 18:42:43 | D | + x: None +24-11-19 18:42:43 | D | + y: sint8 +24-11-19 18:42:43 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:42:43 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:42:44 | D | + x - AbsMax +24-11-19 18:42:44 | D | + x = [min=2.8047, max=17.0000] +24-11-19 18:42:44 | D | + y - AbsMax +24-11-19 18:42:44 | D | + y = [min=2.9727, max=22.5000] +24-11-19 18:42:44 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:42:49 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:42:49 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:42:49 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:42:49 | D | - sum error = [ 32.8755, 30.2864, 28.0168, 30.4286, 29.6792] +24-11-19 18:42:49 | D | - best error = [ 32.8755, 30.2864, 28.0168, 28.0168, 28.0168] +24-11-19 18:42:49 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:42:49 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:42:49 | D | - sum error = [ 26.4237, 26.6500, 26.0011, 26.8933, 26.0118] +24-11-19 18:42:49 | D | - best error = [ 26.4237, 26.4237, 26.0011, 26.0011, 26.0011] +24-11-19 18:42:49 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:42:49 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:42:49 | D | - sum error = [ 23.9080, 22.9070, 23.3172, 24.0404, 21.7786] +24-11-19 18:42:49 | D | - best error = [ 23.9080, 22.9070, 22.9070, 22.9070, 21.7786] +24-11-19 18:42:49 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:42:49 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:42:49 | D | - sum error = [ 21.7733, 22.7193, 20.0073, 20.9117, 20.6036] +24-11-19 18:42:49 | D | - best error = [ 21.7733, 21.7733, 20.0073, 20.0073, 20.0073] +24-11-19 18:42:49 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:42:49 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:42:49 | D | - sum error = [ 54.9711, 51.5559, 48.7474, 42.7085, 40.1480] +24-11-19 18:42:49 | D | - best error = [ 20.0073, 20.0073, 20.0073, 20.0073, 20.0073] +24-11-19 18:42:49 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:42:49 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:42:49 | D | - sum error = [ 39.3467, 40.8228, 34.8477, 33.6653, 27.7715] +24-11-19 18:42:49 | D | - best error = [ 20.0073, 20.0073, 20.0073, 20.0073, 20.0073] +24-11-19 18:42:49 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:42:49 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:42:49 | D | - sum error = [ 30.7702, 27.1900, 25.7083, 24.1991, 22.2940] +24-11-19 18:42:49 | D | - best error = [ 20.0073, 20.0073, 20.0073, 20.0073, 20.0073] +24-11-19 18:42:49 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:42:49 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:42:49 | D | - sum error = [ 21.6180, 21.4417, 21.8944, 20.0790] +24-11-19 18:42:49 | D | - best error = [ 20.0073, 20.0073, 20.0073, 20.0073] +24-11-19 18:42:49 | D | + error = 20.0073 +24-11-19 18:42:49 | D | + scale = [min=2.5245, max=14.1044] +24-11-19 18:42:56 | D | - Smoothing model.layers.19 +24-11-19 18:42:56 | D | - model.layers.19.self_attn.attn_k +24-11-19 18:42:56 | D | + w: None +24-11-19 18:42:56 | D | + x: None +24-11-19 18:42:56 | D | + y: sint8 +24-11-19 18:42:56 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:42:56 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:42:56 | D | + x - AbsMax +24-11-19 18:42:56 | D | + x = [min=1.6318, max=18.2500] +24-11-19 18:42:56 | D | + y - AbsMax +24-11-19 18:42:56 | D | + y = [min=3.8086, max=22.5469] +24-11-19 18:42:56 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:43:02 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:43:02 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:43:02 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:43:02 | D | - sum error = [ 26.3885, 26.7398, 27.1696, 25.8924, 26.7660] +24-11-19 18:43:02 | D | - best error = [ 26.3885, 26.3885, 26.3885, 25.8924, 25.8924] +24-11-19 18:43:02 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:43:02 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:43:02 | D | - sum error = [ 22.7850, 24.8956, 25.4633, 21.6831, 22.7140] +24-11-19 18:43:02 | D | - best error = [ 22.7850, 22.7850, 22.7850, 21.6831, 21.6831] +24-11-19 18:43:02 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:43:02 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:43:02 | D | - sum error = [ 22.1298, 19.9071, 22.3282, 21.3050, 19.5095] +24-11-19 18:43:02 | D | - best error = [ 21.6831, 19.9071, 19.9071, 19.9071, 19.5095] +24-11-19 18:43:02 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:43:02 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:43:02 | D | - sum error = [ 18.7145, 18.9940, 18.0602, 18.1548, 19.9352] +24-11-19 18:43:02 | D | - best error = [ 18.7145, 18.7145, 18.0602, 18.0602, 18.0602] +24-11-19 18:43:02 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:43:02 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:43:02 | D | - sum error = [ 50.3362, 46.9444, 42.2280, 41.6752, 36.8873] +24-11-19 18:43:02 | D | - best error = [ 18.0602, 18.0602, 18.0602, 18.0602, 18.0602] +24-11-19 18:43:02 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:43:02 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:43:02 | D | - sum error = [ 35.0925, 32.8369, 29.7740, 28.4212, 28.0043] +24-11-19 18:43:02 | D | - best error = [ 18.0602, 18.0602, 18.0602, 18.0602, 18.0602] +24-11-19 18:43:02 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:43:02 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:43:02 | D | - sum error = [ 24.3863, 24.7816, 22.0049, 24.9197, 20.4578] +24-11-19 18:43:02 | D | - best error = [ 18.0602, 18.0602, 18.0602, 18.0602, 18.0602] +24-11-19 18:43:02 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:43:02 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:43:02 | D | - sum error = [ 19.0211, 19.6267, 18.9204, 18.6553] +24-11-19 18:43:02 | D | - best error = [ 18.0602, 18.0602, 18.0602, 18.0602] +24-11-19 18:43:02 | D | + error = 18.0602 +24-11-19 18:43:02 | D | + scale = [min=3.1164, max=14.1294] +24-11-19 18:43:08 | D | - Smoothing model.layers.20 +24-11-19 18:43:08 | D | - model.layers.20.self_attn.attn_k +24-11-19 18:43:08 | D | + w: None +24-11-19 18:43:08 | D | + x: None +24-11-19 18:43:08 | D | + y: sint8 +24-11-19 18:43:08 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:43:08 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:43:08 | D | + x - AbsMax +24-11-19 18:43:08 | D | + x = [min=1.7852, max=18.7500] +24-11-19 18:43:08 | D | + y - AbsMax +24-11-19 18:43:08 | D | + y = [min=3.3359, max=21.0312] +24-11-19 18:43:08 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:43:14 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:43:14 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:43:14 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:43:14 | D | - sum error = [ 29.6178, 24.9845, 25.2321, 24.1858, 23.3117] +24-11-19 18:43:14 | D | - best error = [ 29.6178, 24.9845, 24.9845, 24.1858, 23.3117] +24-11-19 18:43:14 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:43:14 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:43:14 | D | - sum error = [ 23.5119, 24.9696, 23.0933, 22.2845, 22.4294] +24-11-19 18:43:14 | D | - best error = [ 23.3117, 23.3117, 23.0933, 22.2845, 22.2845] +24-11-19 18:43:14 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:43:14 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:43:14 | D | - sum error = [ 20.8735, 21.5412, 23.4842, 18.6311, 20.6820] +24-11-19 18:43:14 | D | - best error = [ 20.8735, 20.8735, 20.8735, 18.6311, 18.6311] +24-11-19 18:43:14 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:43:14 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:43:14 | D | - sum error = [ 19.8338, 20.6652, 22.7479, 18.8847, 19.5135] +24-11-19 18:43:14 | D | - best error = [ 18.6311, 18.6311, 18.6311, 18.6311, 18.6311] +24-11-19 18:43:14 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:43:14 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:43:14 | D | - sum error = [ 62.9948, 55.5878, 47.8615, 48.9218, 43.4627] +24-11-19 18:43:14 | D | - best error = [ 18.6311, 18.6311, 18.6311, 18.6311, 18.6311] +24-11-19 18:43:14 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:43:14 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:43:14 | D | - sum error = [ 43.9225, 35.5346, 34.1949, 34.7903, 33.0614] +24-11-19 18:43:14 | D | - best error = [ 18.6311, 18.6311, 18.6311, 18.6311, 18.6311] +24-11-19 18:43:14 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:43:14 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:43:14 | D | - sum error = [ 29.0231, 27.3085, 24.5269, 22.1962, 24.3537] +24-11-19 18:43:14 | D | - best error = [ 18.6311, 18.6311, 18.6311, 18.6311, 18.6311] +24-11-19 18:43:14 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:43:14 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:43:14 | D | - sum error = [ 22.2771, 22.1063, 21.1875, 20.9516] +24-11-19 18:43:14 | D | - best error = [ 18.6311, 18.6311, 18.6311, 18.6311] +24-11-19 18:43:14 | D | + error = 18.6311 +24-11-19 18:43:14 | D | + scale = [min=2.1882, max=7.2421] +24-11-19 18:43:19 | D | - Smoothing model.layers.21 +24-11-19 18:43:19 | D | - model.layers.21.self_attn.attn_k +24-11-19 18:43:19 | D | + w: None +24-11-19 18:43:19 | D | + x: None +24-11-19 18:43:19 | D | + y: sint8 +24-11-19 18:43:19 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:43:19 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:43:19 | D | + x - AbsMax +24-11-19 18:43:19 | D | + x = [min=2.5195, max=22.7344] +24-11-19 18:43:19 | D | + y - AbsMax +24-11-19 18:43:19 | D | + y = [min=3.4102, max=26.6094] +24-11-19 18:43:19 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:43:25 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:43:25 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:43:25 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:43:25 | D | - sum error = [ 47.7779, 47.8361, 44.1869, 42.6190, 42.0479] +24-11-19 18:43:25 | D | - best error = [ 47.7779, 47.7779, 44.1869, 42.6190, 42.0479] +24-11-19 18:43:25 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:43:25 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:43:25 | D | - sum error = [ 38.9243, 39.5416, 35.4249, 34.0211, 36.4722] +24-11-19 18:43:25 | D | - best error = [ 38.9243, 38.9243, 35.4249, 34.0211, 34.0211] +24-11-19 18:43:25 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:43:25 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:43:25 | D | - sum error = [ 35.7271, 32.6482, 32.6825, 32.9102, 30.8764] +24-11-19 18:43:25 | D | - best error = [ 34.0211, 32.6482, 32.6482, 32.6482, 30.8764] +24-11-19 18:43:25 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:43:25 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:43:25 | D | - sum error = [ 28.4706, 29.8967, 29.8923, 27.3472, 27.3028] +24-11-19 18:43:25 | D | - best error = [ 28.4706, 28.4706, 28.4706, 27.3472, 27.3028] +24-11-19 18:43:25 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:43:25 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:43:25 | D | - sum error = [ 90.4298, 83.4059, 69.4941, 62.7764, 61.6921] +24-11-19 18:43:25 | D | - best error = [ 27.3028, 27.3028, 27.3028, 27.3028, 27.3028] +24-11-19 18:43:25 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:43:25 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:43:25 | D | - sum error = [ 54.4117, 49.5031, 49.1064, 49.3540, 36.4542] +24-11-19 18:43:25 | D | - best error = [ 27.3028, 27.3028, 27.3028, 27.3028, 27.3028] +24-11-19 18:43:25 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:43:25 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:43:25 | D | - sum error = [ 36.4036, 34.4276, 34.9758, 31.6718, 31.6411] +24-11-19 18:43:25 | D | - best error = [ 27.3028, 27.3028, 27.3028, 27.3028, 27.3028] +24-11-19 18:43:25 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:43:25 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:43:25 | D | - sum error = [ 31.2569, 29.0907, 31.3019, 28.4189] +24-11-19 18:43:25 | D | - best error = [ 27.3028, 27.3028, 27.3028, 27.3028] +24-11-19 18:43:25 | D | + error = 27.3028 +24-11-19 18:43:25 | D | + scale = [min=3.2073, max=22.5831] +24-11-19 18:43:31 | D | - Smoothing model.layers.22 +24-11-19 18:43:31 | D | - model.layers.22.self_attn.attn_k +24-11-19 18:43:31 | D | + w: None +24-11-19 18:43:31 | D | + x: None +24-11-19 18:43:31 | D | + y: sint8 +24-11-19 18:43:31 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:43:31 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:43:31 | D | + x - AbsMax +24-11-19 18:43:31 | D | + x = [min=2.2441, max=22.4375] +24-11-19 18:43:31 | D | + y - AbsMax +24-11-19 18:43:31 | D | + y = [min=3.7188, max=24.7969] +24-11-19 18:43:31 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:43:37 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:43:37 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:43:37 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:43:37 | D | - sum error = [ 37.0293, 33.6389, 33.7255, 33.6681, 33.0408] +24-11-19 18:43:37 | D | - best error = [ 37.0293, 33.6389, 33.6389, 33.6389, 33.0408] +24-11-19 18:43:37 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:43:37 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:43:37 | D | - sum error = [ 30.2467, 30.1160, 29.7480, 28.4296, 28.6480] +24-11-19 18:43:37 | D | - best error = [ 30.2467, 30.1160, 29.7480, 28.4296, 28.4296] +24-11-19 18:43:37 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:43:37 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:43:37 | D | - sum error = [ 27.8256, 25.4112, 23.7863, 27.8390, 24.6003] +24-11-19 18:43:37 | D | - best error = [ 27.8256, 25.4112, 23.7863, 23.7863, 23.7863] +24-11-19 18:43:37 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:43:37 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:43:37 | D | - sum error = [ 23.8495, 22.0821, 22.4311, 23.1707, 21.0018] +24-11-19 18:43:37 | D | - best error = [ 23.7863, 22.0821, 22.0821, 22.0821, 21.0018] +24-11-19 18:43:37 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:43:37 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:43:37 | D | - sum error = [ 67.9268, 57.9732, 53.2294, 46.7290, 48.9339] +24-11-19 18:43:37 | D | - best error = [ 21.0018, 21.0018, 21.0018, 21.0018, 21.0018] +24-11-19 18:43:37 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:43:37 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:43:37 | D | - sum error = [ 41.1997, 41.3739, 36.1092, 32.5250, 33.1952] +24-11-19 18:43:37 | D | - best error = [ 21.0018, 21.0018, 21.0018, 21.0018, 21.0018] +24-11-19 18:43:37 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:43:37 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:43:37 | D | - sum error = [ 30.9025, 26.4920, 28.4248, 25.2389, 26.7958] +24-11-19 18:43:37 | D | - best error = [ 21.0018, 21.0018, 21.0018, 21.0018, 21.0018] +24-11-19 18:43:37 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:43:37 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:43:37 | D | - sum error = [ 23.3584, 23.8766, 21.2474, 24.2100] +24-11-19 18:43:37 | D | - best error = [ 21.0018, 21.0018, 21.0018, 21.0018] +24-11-19 18:43:37 | D | + error = 21.0018 +24-11-19 18:43:37 | D | + scale = [min=3.4824, max=21.1192] +24-11-19 18:43:43 | D | - Smoothing model.layers.23 +24-11-19 18:43:43 | D | - model.layers.23.self_attn.attn_k +24-11-19 18:43:43 | D | + w: None +24-11-19 18:43:43 | D | + x: None +24-11-19 18:43:43 | D | + y: sint8 +24-11-19 18:43:43 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:43:43 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:43:43 | D | + x - AbsMax +24-11-19 18:43:43 | D | + x = [min=2.4004, max=21.9688] +24-11-19 18:43:43 | D | + y - AbsMax +24-11-19 18:43:43 | D | + y = [min=3.2637, max=23.6719] +24-11-19 18:43:43 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:43:49 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:43:49 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:43:49 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:43:49 | D | - sum error = [ 37.8705, 37.9131, 36.4608, 35.0184, 36.5458] +24-11-19 18:43:49 | D | - best error = [ 37.8705, 37.8705, 36.4608, 35.0184, 35.0184] +24-11-19 18:43:49 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:43:49 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:43:49 | D | - sum error = [ 30.9832, 31.3936, 29.2710, 30.0660, 30.7508] +24-11-19 18:43:49 | D | - best error = [ 30.9832, 30.9832, 29.2710, 29.2710, 29.2710] +24-11-19 18:43:49 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:43:49 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:43:49 | D | - sum error = [ 29.4462, 25.0367, 28.2503, 27.6115, 27.0534] +24-11-19 18:43:49 | D | - best error = [ 29.2710, 25.0367, 25.0367, 25.0367, 25.0367] +24-11-19 18:43:49 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:43:49 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:43:49 | D | - sum error = [ 27.2260, 25.9493, 26.0842, 25.3295, 22.8366] +24-11-19 18:43:49 | D | - best error = [ 25.0367, 25.0367, 25.0367, 25.0367, 22.8366] +24-11-19 18:43:49 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:43:49 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:43:49 | D | - sum error = [ 78.8664, 75.1408, 75.9639, 59.3407, 55.8637] +24-11-19 18:43:49 | D | - best error = [ 22.8366, 22.8366, 22.8366, 22.8366, 22.8366] +24-11-19 18:43:49 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:43:49 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:43:49 | D | - sum error = [ 49.0533, 43.8393, 47.7408, 36.6799, 36.2134] +24-11-19 18:43:49 | D | - best error = [ 22.8366, 22.8366, 22.8366, 22.8366, 22.8366] +24-11-19 18:43:49 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:43:49 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:43:49 | D | - sum error = [ 43.4143, 36.1481, 29.7859, 31.2776, 28.1747] +24-11-19 18:43:49 | D | - best error = [ 22.8366, 22.8366, 22.8366, 22.8366, 22.8366] +24-11-19 18:43:49 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:43:49 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:43:49 | D | - sum error = [ 26.1386, 30.5276, 26.0848, 26.2282] +24-11-19 18:43:49 | D | - best error = [ 22.8366, 22.8366, 22.8366, 22.8366] +24-11-19 18:43:49 | D | + error = 22.8366 +24-11-19 18:43:49 | D | + scale = [min=3.0762, max=20.2079] +24-11-19 18:43:54 | D | - Smoothing model.layers.24 +24-11-19 18:43:54 | D | - model.layers.24.self_attn.attn_k +24-11-19 18:43:54 | D | + w: None +24-11-19 18:43:54 | D | + x: None +24-11-19 18:43:54 | D | + y: sint8 +24-11-19 18:43:54 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:43:54 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:43:54 | D | + x - AbsMax +24-11-19 18:43:54 | D | + x = [min=2.2500, max=25.5156] +24-11-19 18:43:54 | D | + y - AbsMax +24-11-19 18:43:54 | D | + y = [min=3.3730, max=24.4688] +24-11-19 18:43:54 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:44:00 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:44:00 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:44:00 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:44:00 | D | - sum error = [ 44.9535, 39.5444, 42.7933, 37.9541, 34.7093] +24-11-19 18:44:00 | D | - best error = [ 44.9535, 39.5444, 39.5444, 37.9541, 34.7093] +24-11-19 18:44:00 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:44:00 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:44:00 | D | - sum error = [ 36.9525, 33.4936, 33.9545, 32.2360, 34.3910] +24-11-19 18:44:00 | D | - best error = [ 34.7093, 33.4936, 33.4936, 32.2360, 32.2360] +24-11-19 18:44:00 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:44:00 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:44:00 | D | - sum error = [ 29.6528, 28.8387, 28.9508, 29.6005, 29.0767] +24-11-19 18:44:00 | D | - best error = [ 29.6528, 28.8387, 28.8387, 28.8387, 28.8387] +24-11-19 18:44:00 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:44:00 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:44:00 | D | - sum error = [ 27.2806, 26.1905, 26.2671, 26.8261, 27.6270] +24-11-19 18:44:00 | D | - best error = [ 27.2806, 26.1905, 26.1905, 26.1905, 26.1905] +24-11-19 18:44:00 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:44:00 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:44:00 | D | - sum error = [ 103.1724, 87.1527, 82.0144, 73.2518, 63.3276] +24-11-19 18:44:00 | D | - best error = [ 26.1905, 26.1905, 26.1905, 26.1905, 26.1905] +24-11-19 18:44:00 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:44:00 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:44:00 | D | - sum error = [ 56.6879, 53.5064, 51.4434, 44.4673, 41.9058] +24-11-19 18:44:00 | D | - best error = [ 26.1905, 26.1905, 26.1905, 26.1905, 26.1905] +24-11-19 18:44:00 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:44:00 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:44:00 | D | - sum error = [ 38.1252, 36.5551, 34.7282, 30.6221, 30.3691] +24-11-19 18:44:00 | D | - best error = [ 26.1905, 26.1905, 26.1905, 26.1905, 26.1905] +24-11-19 18:44:00 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:44:00 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:44:00 | D | - sum error = [ 30.7933, 28.0278, 27.7770, 25.7868] +24-11-19 18:44:00 | D | - best error = [ 26.1905, 26.1905, 26.1905, 25.7868] +24-11-19 18:44:00 | D | + error = 25.7868 +24-11-19 18:44:00 | D | + scale = [min=2.8958, max=18.0033] +24-11-19 18:44:06 | D | - Smoothing model.layers.25 +24-11-19 18:44:06 | D | - model.layers.25.self_attn.attn_k +24-11-19 18:44:06 | D | + w: None +24-11-19 18:44:06 | D | + x: None +24-11-19 18:44:06 | D | + y: sint8 +24-11-19 18:44:06 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:44:06 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:44:07 | D | + x - AbsMax +24-11-19 18:44:07 | D | + x = [min=1.5195, max=26.2656] +24-11-19 18:44:07 | D | + y - AbsMax +24-11-19 18:44:07 | D | + y = [min=2.8398, max=25.7812] +24-11-19 18:44:07 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:44:13 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:44:13 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:44:13 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:44:13 | D | - sum error = [ 57.7032, 57.1721, 56.2357, 54.0036, 55.7897] +24-11-19 18:44:13 | D | - best error = [ 57.7032, 57.1721, 56.2357, 54.0036, 54.0036] +24-11-19 18:44:13 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:44:13 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:44:13 | D | - sum error = [ 48.0470, 54.1307, 47.7555, 45.4708, 42.2805] +24-11-19 18:44:13 | D | - best error = [ 48.0470, 48.0470, 47.7555, 45.4708, 42.2805] +24-11-19 18:44:13 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:44:13 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:44:13 | D | - sum error = [ 43.2213, 38.1664, 40.5182, 38.0043, 36.5850] +24-11-19 18:44:13 | D | - best error = [ 42.2805, 38.1664, 38.1664, 38.0043, 36.5850] +24-11-19 18:44:13 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:44:13 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:44:13 | D | - sum error = [ 35.3431, 35.4267, 34.4973, 34.2925, 34.9680] +24-11-19 18:44:13 | D | - best error = [ 35.3431, 35.3431, 34.4973, 34.2925, 34.2925] +24-11-19 18:44:13 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:44:13 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:44:13 | D | - sum error = [ 127.6303, 115.7825, 94.9046, 91.9465, 83.6754] +24-11-19 18:44:13 | D | - best error = [ 34.2925, 34.2925, 34.2925, 34.2925, 34.2925] +24-11-19 18:44:13 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:44:13 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:44:13 | D | - sum error = [ 72.3856, 67.5490, 60.6275, 52.8906, 54.8740] +24-11-19 18:44:13 | D | - best error = [ 34.2925, 34.2925, 34.2925, 34.2925, 34.2925] +24-11-19 18:44:13 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:44:13 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:44:13 | D | - sum error = [ 52.0243, 49.9649, 48.4007, 42.9284, 40.9811] +24-11-19 18:44:13 | D | - best error = [ 34.2925, 34.2925, 34.2925, 34.2925, 34.2925] +24-11-19 18:44:13 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:44:13 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:44:13 | D | - sum error = [ 40.9166, 36.5250, 34.0471, 32.6970] +24-11-19 18:44:13 | D | - best error = [ 34.2925, 34.2925, 34.0471, 32.6970] +24-11-19 18:44:13 | D | + error = 32.6970 +24-11-19 18:44:13 | D | + scale = [min=2.5614, max=19.2324] +24-11-19 18:44:19 | D | - Smoothing model.layers.26 +24-11-19 18:44:19 | D | - model.layers.26.self_attn.attn_k +24-11-19 18:44:19 | D | + w: None +24-11-19 18:44:19 | D | + x: None +24-11-19 18:44:19 | D | + y: sint8 +24-11-19 18:44:19 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:44:19 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:44:19 | D | + x - AbsMax +24-11-19 18:44:19 | D | + x = [min=1.6602, max=24.8750] +24-11-19 18:44:19 | D | + y - AbsMax +24-11-19 18:44:19 | D | + y = [min=2.8652, max=25.5156] +24-11-19 18:44:19 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:44:25 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:44:25 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:44:25 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:44:25 | D | - sum error = [ 55.2434, 50.9596, 47.4489, 48.6079, 46.1570] +24-11-19 18:44:25 | D | - best error = [ 55.2434, 50.9596, 47.4489, 47.4489, 46.1570] +24-11-19 18:44:25 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:44:25 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:44:25 | D | - sum error = [ 47.0429, 42.5282, 39.3749, 37.2645, 35.4746] +24-11-19 18:44:25 | D | - best error = [ 46.1570, 42.5282, 39.3749, 37.2645, 35.4746] +24-11-19 18:44:25 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:44:25 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:44:25 | D | - sum error = [ 36.3745, 38.0936, 37.8405, 36.9386, 34.8691] +24-11-19 18:44:25 | D | - best error = [ 35.4746, 35.4746, 35.4746, 35.4746, 34.8691] +24-11-19 18:44:25 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:44:25 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:44:25 | D | - sum error = [ 35.7195, 33.2072, 33.1612, 32.9672, 29.2773] +24-11-19 18:44:25 | D | - best error = [ 34.8691, 33.2072, 33.1612, 32.9672, 29.2773] +24-11-19 18:44:25 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:44:25 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:44:25 | D | - sum error = [ 105.1371, 95.8721, 81.4498, 74.5289, 72.3198] +24-11-19 18:44:25 | D | - best error = [ 29.2773, 29.2773, 29.2773, 29.2773, 29.2773] +24-11-19 18:44:25 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:44:25 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:44:25 | D | - sum error = [ 69.0296, 61.6723, 59.9982, 51.6316, 48.2022] +24-11-19 18:44:25 | D | - best error = [ 29.2773, 29.2773, 29.2773, 29.2773, 29.2773] +24-11-19 18:44:25 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:44:25 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:44:25 | D | - sum error = [ 49.4358, 45.1893, 44.9580, 38.2817, 35.9764] +24-11-19 18:44:25 | D | - best error = [ 29.2773, 29.2773, 29.2773, 29.2773, 29.2773] +24-11-19 18:44:25 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:44:25 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:44:25 | D | - sum error = [ 33.8707, 36.2410, 32.3333, 31.8889] +24-11-19 18:44:25 | D | - best error = [ 29.2773, 29.2773, 29.2773, 29.2773] +24-11-19 18:44:25 | D | + error = 29.2773 +24-11-19 18:44:25 | D | + scale = [min=2.7183, max=21.7003] +24-11-19 18:44:31 | D | - Smoothing model.layers.27 +24-11-19 18:44:31 | D | - model.layers.27.self_attn.attn_k +24-11-19 18:44:31 | D | + w: None +24-11-19 18:44:31 | D | + x: None +24-11-19 18:44:31 | D | + y: sint8 +24-11-19 18:44:31 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:44:31 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:44:31 | D | + x - AbsMax +24-11-19 18:44:31 | D | + x = [min=2.0391, max=24.8750] +24-11-19 18:44:31 | D | + y - AbsMax +24-11-19 18:44:31 | D | + y = [min=2.9277, max=23.4844] +24-11-19 18:44:31 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:44:37 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:44:37 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:44:37 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:44:37 | D | - sum error = [ 57.1492, 55.2568, 49.2634, 53.2408, 49.0191] +24-11-19 18:44:37 | D | - best error = [ 57.1492, 55.2568, 49.2634, 49.2634, 49.0191] +24-11-19 18:44:37 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:44:37 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:44:37 | D | - sum error = [ 46.8792, 44.7638, 44.4421, 43.8167, 42.5690] +24-11-19 18:44:37 | D | - best error = [ 46.8792, 44.7638, 44.4421, 43.8167, 42.5690] +24-11-19 18:44:37 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:44:37 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:44:37 | D | - sum error = [ 41.1900, 40.4850, 38.1825, 38.5332, 37.9403] +24-11-19 18:44:37 | D | - best error = [ 41.1900, 40.4850, 38.1825, 38.1825, 37.9403] +24-11-19 18:44:37 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:44:37 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:44:37 | D | - sum error = [ 37.1782, 37.0944, 36.3430, 34.3950, 34.9419] +24-11-19 18:44:37 | D | - best error = [ 37.1782, 37.0944, 36.3430, 34.3950, 34.3950] +24-11-19 18:44:37 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:44:37 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:44:37 | D | - sum error = [ 112.6126, 103.3610, 94.1851, 87.6063, 81.2018] +24-11-19 18:44:37 | D | - best error = [ 34.3950, 34.3950, 34.3950, 34.3950, 34.3950] +24-11-19 18:44:37 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:44:37 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:44:37 | D | - sum error = [ 69.5150, 66.8113, 60.5170, 58.8107, 51.8878] +24-11-19 18:44:37 | D | - best error = [ 34.3950, 34.3950, 34.3950, 34.3950, 34.3950] +24-11-19 18:44:37 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:44:37 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:44:37 | D | - sum error = [ 53.0158, 48.4843, 42.0345, 44.8433, 42.8174] +24-11-19 18:44:37 | D | - best error = [ 34.3950, 34.3950, 34.3950, 34.3950, 34.3950] +24-11-19 18:44:37 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:44:37 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:44:37 | D | - sum error = [ 38.7227, 40.1827, 36.1350, 36.1793] +24-11-19 18:44:37 | D | - best error = [ 34.3950, 34.3950, 34.3950, 34.3950] +24-11-19 18:44:37 | D | + error = 34.3950 +24-11-19 18:44:37 | D | + scale = [min=2.6295, max=17.1278] +24-11-19 18:44:42 | D | - Smoothing model.layers.28 +24-11-19 18:44:42 | D | - model.layers.28.self_attn.attn_k +24-11-19 18:44:42 | D | + w: None +24-11-19 18:44:42 | D | + x: None +24-11-19 18:44:42 | D | + y: sint8 +24-11-19 18:44:42 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:44:42 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:44:43 | D | + x - AbsMax +24-11-19 18:44:43 | D | + x = [min=2.9023, max=21.4062] +24-11-19 18:44:43 | D | + y - AbsMax +24-11-19 18:44:43 | D | + y = [min=3.2109, max=25.6094] +24-11-19 18:44:43 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:44:49 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:44:49 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:44:49 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:44:49 | D | - sum error = [ 72.9161, 71.2311, 69.4744, 66.9924, 58.8306] +24-11-19 18:44:49 | D | - best error = [ 72.9161, 71.2311, 69.4744, 66.9924, 58.8306] +24-11-19 18:44:49 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:44:49 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:44:49 | D | - sum error = [ 64.1621, 59.4511, 58.5528, 56.7439, 55.4980] +24-11-19 18:44:49 | D | - best error = [ 58.8306, 58.8306, 58.5528, 56.7439, 55.4980] +24-11-19 18:44:49 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:44:49 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:44:49 | D | - sum error = [ 52.4741, 52.6351, 48.2149, 49.6962, 48.8641] +24-11-19 18:44:49 | D | - best error = [ 52.4741, 52.4741, 48.2149, 48.2149, 48.2149] +24-11-19 18:44:49 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:44:49 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:44:49 | D | - sum error = [ 50.7111, 47.2439, 43.8657, 43.9270, 40.9340] +24-11-19 18:44:49 | D | - best error = [ 48.2149, 47.2439, 43.8657, 43.8657, 40.9340] +24-11-19 18:44:49 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:44:49 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:44:49 | D | - sum error = [ 165.2127, 130.6847, 123.8375, 112.6714, 101.1005] +24-11-19 18:44:49 | D | - best error = [ 40.9340, 40.9340, 40.9340, 40.9340, 40.9340] +24-11-19 18:44:49 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:44:49 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:44:49 | D | - sum error = [ 92.9471, 81.5421, 77.7521, 73.6795, 67.5009] +24-11-19 18:44:49 | D | - best error = [ 40.9340, 40.9340, 40.9340, 40.9340, 40.9340] +24-11-19 18:44:49 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:44:49 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:44:49 | D | - sum error = [ 66.9187, 61.5133, 64.2566, 57.7528, 59.3974] +24-11-19 18:44:49 | D | - best error = [ 40.9340, 40.9340, 40.9340, 40.9340, 40.9340] +24-11-19 18:44:49 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:44:49 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:44:49 | D | - sum error = [ 53.4327, 50.8114, 46.7953, 42.5964] +24-11-19 18:44:49 | D | - best error = [ 40.9340, 40.9340, 40.9340, 40.9340] +24-11-19 18:44:49 | D | + error = 40.9340 +24-11-19 18:44:49 | D | + scale = [min=3.0290, max=21.7760] +24-11-19 18:44:54 | D | - Smoothing model.layers.29 +24-11-19 18:44:54 | D | - model.layers.29.self_attn.attn_k +24-11-19 18:44:54 | D | + w: None +24-11-19 18:44:54 | D | + x: None +24-11-19 18:44:54 | D | + y: sint8 +24-11-19 18:44:54 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:44:54 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:44:54 | D | + x - AbsMax +24-11-19 18:44:54 | D | + x = [min=2.5352, max=18.3125] +24-11-19 18:44:54 | D | + y - AbsMax +24-11-19 18:44:54 | D | + y = [min=2.8203, max=41.7812] +24-11-19 18:44:54 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:45:00 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:45:00 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:45:00 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:45:00 | D | - sum error = [ 118.6755, 107.6552, 99.8410, 101.4621, 88.9902] +24-11-19 18:45:00 | D | - best error = [ 118.6755, 107.6552, 99.8410, 99.8410, 88.9902] +24-11-19 18:45:00 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:45:00 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:45:00 | D | - sum error = [ 97.9288, 93.3254, 91.3481, 85.0054, 79.8957] +24-11-19 18:45:00 | D | - best error = [ 88.9902, 88.9902, 88.9902, 85.0054, 79.8957] +24-11-19 18:45:00 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:45:00 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:45:00 | D | - sum error = [ 72.9680, 61.7562, 61.4569, 59.3357, 60.6234] +24-11-19 18:45:00 | D | - best error = [ 72.9680, 61.7562, 61.4569, 59.3357, 59.3357] +24-11-19 18:45:00 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:45:00 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:45:00 | D | - sum error = [ 67.6862, 64.0833, 60.8343, 59.0108, 51.6767] +24-11-19 18:45:00 | D | - best error = [ 59.3357, 59.3357, 59.3357, 59.0108, 51.6767] +24-11-19 18:45:00 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:45:00 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:45:00 | D | - sum error = [ 195.7876, 150.6826, 127.5638, 117.0140, 118.6813] +24-11-19 18:45:00 | D | - best error = [ 51.6767, 51.6767, 51.6767, 51.6767, 51.6767] +24-11-19 18:45:00 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:45:00 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:45:00 | D | - sum error = [ 98.8616, 107.9640, 89.0795, 85.7018, 77.8273] +24-11-19 18:45:00 | D | - best error = [ 51.6767, 51.6767, 51.6767, 51.6767, 51.6767] +24-11-19 18:45:00 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:45:00 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:45:00 | D | - sum error = [ 71.6512, 68.8834, 61.9162, 65.6579, 59.5476] +24-11-19 18:45:00 | D | - best error = [ 51.6767, 51.6767, 51.6767, 51.6767, 51.6767] +24-11-19 18:45:00 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:45:00 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:45:00 | D | - sum error = [ 59.9162, 56.4198, 50.9165, 47.4433] +24-11-19 18:45:00 | D | - best error = [ 51.6767, 51.6767, 50.9165, 47.4433] +24-11-19 18:45:00 | D | + error = 47.4433 +24-11-19 18:45:00 | D | + scale = [min=2.4823, max=30.8969] +24-11-19 18:45:06 | D | - Smoothing model.layers.30 +24-11-19 18:45:06 | D | - model.layers.30.self_attn.attn_k +24-11-19 18:45:06 | D | + w: None +24-11-19 18:45:06 | D | + x: None +24-11-19 18:45:06 | D | + y: sint8 +24-11-19 18:45:06 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:45:06 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:45:06 | D | + x - AbsMax +24-11-19 18:45:06 | D | + x = [min=2.7656, max=21.4531] +24-11-19 18:45:06 | D | + y - AbsMax +24-11-19 18:45:06 | D | + y = [min=2.6582, max=24.0781] +24-11-19 18:45:06 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:45:13 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:45:13 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:45:13 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:45:13 | D | - sum error = [ 93.9706, 95.4933, 89.5127, 86.4917, 81.9394] +24-11-19 18:45:13 | D | - best error = [ 93.9706, 93.9706, 89.5127, 86.4917, 81.9394] +24-11-19 18:45:13 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:45:13 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:45:13 | D | - sum error = [ 83.8899, 84.4102, 78.5190, 78.9425, 68.0551] +24-11-19 18:45:13 | D | - best error = [ 81.9394, 81.9394, 78.5190, 78.5190, 68.0551] +24-11-19 18:45:13 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:45:13 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:45:13 | D | - sum error = [ 72.0842, 65.5686, 70.5535, 67.0314, 65.8160] +24-11-19 18:45:13 | D | - best error = [ 68.0551, 65.5686, 65.5686, 65.5686, 65.5686] +24-11-19 18:45:13 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:45:13 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:45:13 | D | - sum error = [ 60.6445, 60.7329, 58.1828, 59.6789, 55.7241] +24-11-19 18:45:13 | D | - best error = [ 60.6445, 60.6445, 58.1828, 58.1828, 55.7241] +24-11-19 18:45:13 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:45:13 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:45:13 | D | - sum error = [ 193.8917, 185.5132, 172.8113, 149.3771, 130.1122] +24-11-19 18:45:13 | D | - best error = [ 55.7241, 55.7241, 55.7241, 55.7241, 55.7241] +24-11-19 18:45:13 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:45:13 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:45:13 | D | - sum error = [ 123.6302, 116.1902, 104.3370, 104.5951, 93.8908] +24-11-19 18:45:13 | D | - best error = [ 55.7241, 55.7241, 55.7241, 55.7241, 55.7241] +24-11-19 18:45:13 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:45:13 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:45:13 | D | - sum error = [ 91.2649, 89.5281, 80.5987, 80.2383, 76.3177] +24-11-19 18:45:13 | D | - best error = [ 55.7241, 55.7241, 55.7241, 55.7241, 55.7241] +24-11-19 18:45:13 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:45:13 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:45:13 | D | - sum error = [ 67.7390, 66.5357, 62.3294, 57.4964] +24-11-19 18:45:13 | D | - best error = [ 55.7241, 55.7241, 55.7241, 55.7241] +24-11-19 18:45:13 | D | + error = 55.7241 +24-11-19 18:45:13 | D | + scale = [min=2.5314, max=20.5372] +24-11-19 18:45:19 | D | - Smoothing model.layers.31 +24-11-19 18:45:19 | D | - model.layers.31.self_attn.attn_k +24-11-19 18:45:19 | D | + w: None +24-11-19 18:45:19 | D | + x: None +24-11-19 18:45:19 | D | + y: sint8 +24-11-19 18:45:19 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:45:19 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:45:19 | D | + x - AbsMax +24-11-19 18:45:19 | D | + x = [min=2.5547, max=34.0000] +24-11-19 18:45:19 | D | + y - AbsMax +24-11-19 18:45:19 | D | + y = [min=3.4902, max=25.7031] +24-11-19 18:45:19 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:45:25 | D | - x / w range = AbsMax / AbsMax +24-11-19 18:45:25 | D | - alpha = [ 0.0000, 0.0500, 0.1000, 0.1500, 0.2000] +24-11-19 18:45:25 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:45:25 | D | - sum error = [ 137.8191, 123.4061, 124.7137, 120.6580, 113.5695] +24-11-19 18:45:25 | D | - best error = [ 137.8191, 123.4061, 123.4061, 120.6580, 113.5695] +24-11-19 18:45:25 | D | - alpha = [ 0.2500, 0.3000, 0.3500, 0.4000, 0.4500] +24-11-19 18:45:25 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:45:25 | D | - sum error = [ 110.2195, 105.5729, 103.4481, 98.0909, 90.2200] +24-11-19 18:45:25 | D | - best error = [ 110.2195, 105.5729, 103.4481, 98.0909, 90.2200] +24-11-19 18:45:25 | D | - alpha = [ 0.5000, 0.5500, 0.6000, 0.6500, 0.7000] +24-11-19 18:45:25 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:45:25 | D | - sum error = [ 92.1100, 98.7218, 91.7037, 89.6155, 92.1457] +24-11-19 18:45:25 | D | - best error = [ 90.2200, 90.2200, 90.2200, 89.6155, 89.6155] +24-11-19 18:45:25 | D | - alpha = [ 0.7500, 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:45:25 | D | - beta = [ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000] +24-11-19 18:45:25 | D | - sum error = [ 85.5720, 87.9986, 79.2025, 80.7396, 82.0906] +24-11-19 18:45:25 | D | - best error = [ 85.5720, 85.5720, 79.2025, 79.2025, 79.2025] +24-11-19 18:45:25 | D | - alpha = [ 0.0500, 0.1000, 0.1500, 0.2000, 0.2500] +24-11-19 18:45:25 | D | - beta = [ 0.9500, 0.9000, 0.8500, 0.8000, 0.7500] +24-11-19 18:45:25 | D | - sum error = [ 360.2199, 319.5865, 286.7635, 240.0873, 227.9176] +24-11-19 18:45:25 | D | - best error = [ 79.2025, 79.2025, 79.2025, 79.2025, 79.2025] +24-11-19 18:45:25 | D | - alpha = [ 0.3000, 0.3500, 0.4000, 0.4500, 0.5000] +24-11-19 18:45:25 | D | - beta = [ 0.7000, 0.6500, 0.6000, 0.5500, 0.5000] +24-11-19 18:45:25 | D | - sum error = [ 200.1083, 178.3037, 156.5951, 148.0537, 132.9592] +24-11-19 18:45:25 | D | - best error = [ 79.2025, 79.2025, 79.2025, 79.2025, 79.2025] +24-11-19 18:45:25 | D | - alpha = [ 0.5500, 0.6000, 0.6500, 0.7000, 0.7500] +24-11-19 18:45:25 | D | - beta = [ 0.4500, 0.4000, 0.3500, 0.3000, 0.2500] +24-11-19 18:45:25 | D | - sum error = [ 124.6687, 111.6365, 102.8073, 97.8803, 103.3949] +24-11-19 18:45:25 | D | - best error = [ 79.2025, 79.2025, 79.2025, 79.2025, 79.2025] +24-11-19 18:45:25 | D | - alpha = [ 0.8000, 0.8500, 0.9000, 0.9500] +24-11-19 18:45:25 | D | - beta = [ 0.2000, 0.1500, 0.1000, 0.0500] +24-11-19 18:45:25 | D | - sum error = [ 86.2436, 94.0562, 92.0590, 83.8967] +24-11-19 18:45:25 | D | - best error = [ 79.2025, 79.2025, 79.2025, 79.2025] +24-11-19 18:45:25 | D | + error = 79.2025 +24-11-19 18:45:25 | D | + scale = [min=2.8935, max=15.7939] +24-11-19 18:45:26 | I | - Saving smooth scales to runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/llama-3-8b-instruct-gradient-1048k.pt +24-11-19 18:45:26 | I | - Linking smooth scales to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.183745.RUNNING/cache/smooth.pt +24-11-19 18:45:26 | I | * Quantizing weights +24-11-19 18:45:26 | I | - Generating weight quantizer settings +24-11-19 18:45:26 | D | Starting new HTTPS connection (4): huggingface.co:443 +24-11-19 18:45:32 | D | Starting new HTTPS connection (5): huggingface.co:443 +24-11-19 18:45:44 | D | Starting new HTTPS connection (2): s3.amazonaws.com:443 +24-11-19 18:45:56 | W | Repo card metadata block was not found. Setting CardData to empty. +24-11-19 18:45:56 | D | Starting new HTTPS connection (6): huggingface.co:443 +24-11-19 18:46:08 | W | Using the latest cached version of the dataset since mit-han-lab/pile-val-backup couldn't be found on the Hugging Face Hub +24-11-19 18:46:08 | W | Found the latest cached dataset configuration 'default' at /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4 (last modified on Tue Oct 8 18:58:39 2024). +24-11-19 18:46:08 | D | Attempting to acquire lock 23438703707296 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 18:46:08 | D | Lock 23438703707296 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 18:46:08 | D | open file: /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4/dataset_info.json +24-11-19 18:46:08 | D | Attempting to release lock 23438703707296 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 18:46:08 | D | Lock 23438703707296 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 18:46:20 | D | - Quantizing layer model.layers.0 +24-11-19 18:46:20 | D | - Calibrating model.layers.0.self_attn.q_proj.weight +24-11-19 18:46:20 | D | + w: sint8 +24-11-19 18:46:20 | D | + x: None +24-11-19 18:46:20 | D | + y: None +24-11-19 18:46:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:46:20 | D | + finished parsing calibration arguments, ram usage: 11.5 +24-11-19 18:46:20 | D | + finished reseting calibrator, ram usage: 11.5 +24-11-19 18:46:21 | D | + finished calculating the original outputs, ram usage: 11.5 +24-11-19 18:46:21 | D | - range ratio = [ 1.0000] +24-11-19 18:46:21 | D | sum error = [ 0.1837] +24-11-19 18:46:21 | D | best error = [ 0.1837] +24-11-19 18:46:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:46:33 | D | sum error = [ 0.1860, 0.1831, 0.1893, 0.1887, 0.1941] +24-11-19 18:46:33 | D | best error = [ 0.1837, 0.1831, 0.1831, 0.1831, 0.1831] +24-11-19 18:46:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:46:33 | D | sum error = [ 0.2066, 0.2203, 0.2243, 0.2500, 0.2625] +24-11-19 18:46:33 | D | best error = [ 0.1831, 0.1831, 0.1831, 0.1831, 0.1831] +24-11-19 18:46:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:46:33 | D | sum error = [ 0.2852, 0.3080, 0.3307, 0.3697, 0.4066] +24-11-19 18:46:33 | D | best error = [ 0.1831, 0.1831, 0.1831, 0.1831, 0.1831] +24-11-19 18:46:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:46:33 | D | sum error = [ 0.4471, 0.4879, 0.5351, 0.6007, 0.6568] +24-11-19 18:46:33 | D | best error = [ 0.1831, 0.1831, 0.1831, 0.1831, 0.1831] +24-11-19 18:46:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:46:33 | D | sum error = [ 0.7279, 0.8046, 0.8809, 0.9610, 1.0524] +24-11-19 18:46:33 | D | best error = [ 0.1831, 0.1831, 0.1831, 0.1831, 0.1831] +24-11-19 18:46:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:46:33 | D | sum error = [ 1.1545, 1.2621, 1.3761, 1.5152, 1.6581] +24-11-19 18:46:33 | D | best error = [ 0.1831, 0.1831, 0.1831, 0.1831, 0.1831] +24-11-19 18:46:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:46:33 | D | sum error = [ 1.8235, 1.9925, 2.1825, 2.3876, 2.6078] +24-11-19 18:46:33 | D | best error = [ 0.1831, 0.1831, 0.1831, 0.1831, 0.1831] +24-11-19 18:46:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:46:33 | D | sum error = [ 2.8493, 3.1065, 3.3807, 3.6910, 4.0192] +24-11-19 18:46:33 | D | best error = [ 0.1831, 0.1831, 0.1831, 0.1831, 0.1831] +24-11-19 18:46:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:46:33 | D | sum error = [ 4.3777, 4.7569, 5.1683, 5.6203, 6.0942] +24-11-19 18:46:33 | D | best error = [ 0.1831, 0.1831, 0.1831, 0.1831, 0.1831] +24-11-19 18:46:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:46:33 | D | sum error = [ 6.6165, 7.1724, 7.7652, 8.4078, 9.1144] +24-11-19 18:46:33 | D | best error = [ 0.1831, 0.1831, 0.1831, 0.1831, 0.1831] +24-11-19 18:46:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:46:33 | D | sum error = [ 9.8612, 10.6462, 11.5137, 12.4288, 13.4171] +24-11-19 18:46:33 | D | best error = [ 0.1831, 0.1831, 0.1831, 0.1831, 0.1831] +24-11-19 18:46:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:46:33 | D | sum error = [ 14.4697, 15.5908, 16.7935, 18.0779, 19.4469] +24-11-19 18:46:33 | D | best error = [ 0.1831, 0.1831, 0.1831, 0.1831, 0.1831] +24-11-19 18:46:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:46:33 | D | sum error = [ 20.9050, 22.4552, 24.1002, 25.8550, 27.7184] +24-11-19 18:46:33 | D | best error = [ 0.1831, 0.1831, 0.1831, 0.1831, 0.1831] +24-11-19 18:46:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:46:33 | D | sum error = [ 29.7012, 31.8038, 34.0313, 36.3931, 38.8919] +24-11-19 18:46:33 | D | best error = [ 0.1831, 0.1831, 0.1831, 0.1831, 0.1831] +24-11-19 18:46:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:46:33 | D | sum error = [ 41.5329, 44.3203, 47.2487, 50.3469, 53.5924] +24-11-19 18:46:33 | D | best error = [ 0.1831, 0.1831, 0.1831, 0.1831, 0.1831] +24-11-19 18:46:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:46:33 | D | sum error = [ 56.9983, 60.5512, 64.2421, 68.0600, 72.0200] +24-11-19 18:46:33 | D | best error = [ 0.1831, 0.1831, 0.1831, 0.1831, 0.1831] +24-11-19 18:46:33 | D | + error = [0.1831] +24-11-19 18:46:33 | D | - Calibrating model.layers.0.self_attn.k_proj.weight +24-11-19 18:46:33 | D | + w: sint8 +24-11-19 18:46:33 | D | + x: None +24-11-19 18:46:33 | D | + y: None +24-11-19 18:46:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:46:33 | D | + finished parsing calibration arguments, ram usage: 11.5 +24-11-19 18:46:33 | D | + finished reseting calibrator, ram usage: 11.5 +24-11-19 18:46:34 | D | + finished calculating the original outputs, ram usage: 11.5 +24-11-19 18:46:34 | D | - range ratio = [ 1.0000] +24-11-19 18:46:34 | D | sum error = [ 0.2643] +24-11-19 18:46:34 | D | best error = [ 0.2643] +24-11-19 18:46:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:46:46 | D | sum error = [ 0.2536, 0.2576, 0.2570, 0.2701, 0.2628] +24-11-19 18:46:46 | D | best error = [ 0.2536, 0.2536, 0.2536, 0.2536, 0.2536] +24-11-19 18:46:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:46:46 | D | sum error = [ 0.2612, 0.2832, 0.2868, 0.3153, 0.3301] +24-11-19 18:46:46 | D | best error = [ 0.2536, 0.2536, 0.2536, 0.2536, 0.2536] +24-11-19 18:46:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:46:46 | D | sum error = [ 0.3490, 0.3731, 0.3931, 0.4344, 0.4703] +24-11-19 18:46:46 | D | best error = [ 0.2536, 0.2536, 0.2536, 0.2536, 0.2536] +24-11-19 18:46:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:46:46 | D | sum error = [ 0.4934, 0.5403, 0.5769, 0.6214, 0.6838] +24-11-19 18:46:46 | D | best error = [ 0.2536, 0.2536, 0.2536, 0.2536, 0.2536] +24-11-19 18:46:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:46:46 | D | sum error = [ 0.7407, 0.7968, 0.8761, 0.9414, 1.0084] +24-11-19 18:46:46 | D | best error = [ 0.2536, 0.2536, 0.2536, 0.2536, 0.2536] +24-11-19 18:46:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:46:46 | D | sum error = [ 1.0963, 1.1805, 1.2889, 1.3944, 1.5319] +24-11-19 18:46:46 | D | best error = [ 0.2536, 0.2536, 0.2536, 0.2536, 0.2536] +24-11-19 18:46:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:46:46 | D | sum error = [ 1.6443, 1.7897, 1.9500, 2.1149, 2.2933] +24-11-19 18:46:46 | D | best error = [ 0.2536, 0.2536, 0.2536, 0.2536, 0.2536] +24-11-19 18:46:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:46:46 | D | sum error = [ 2.4959, 2.7047, 2.9396, 3.1927, 3.4793] +24-11-19 18:46:46 | D | best error = [ 0.2536, 0.2536, 0.2536, 0.2536, 0.2536] +24-11-19 18:46:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:46:46 | D | sum error = [ 3.7709, 4.0971, 4.4546, 4.8414, 5.2621] +24-11-19 18:46:46 | D | best error = [ 0.2536, 0.2536, 0.2536, 0.2536, 0.2536] +24-11-19 18:46:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:46:46 | D | sum error = [ 5.7142, 6.2046, 6.7299, 7.3081, 7.9368] +24-11-19 18:46:46 | D | best error = [ 0.2536, 0.2536, 0.2536, 0.2536, 0.2536] +24-11-19 18:46:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:46:46 | D | sum error = [ 8.5947, 9.3064, 10.0897, 10.9261, 11.8201] +24-11-19 18:46:46 | D | best error = [ 0.2536, 0.2536, 0.2536, 0.2536, 0.2536] +24-11-19 18:46:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:46:46 | D | sum error = [ 12.8008, 13.8286, 14.9594, 16.1794, 17.4409] +24-11-19 18:46:46 | D | best error = [ 0.2536, 0.2536, 0.2536, 0.2536, 0.2536] +24-11-19 18:46:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:46:46 | D | sum error = [ 18.8588, 20.3153, 21.9409, 23.6411, 25.4796] +24-11-19 18:46:46 | D | best error = [ 0.2536, 0.2536, 0.2536, 0.2536, 0.2536] +24-11-19 18:46:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:46:46 | D | sum error = [ 27.4329, 29.4993, 31.7163, 34.0693, 36.5733] +24-11-19 18:46:46 | D | best error = [ 0.2536, 0.2536, 0.2536, 0.2536, 0.2536] +24-11-19 18:46:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:46:46 | D | sum error = [ 39.2567, 42.1082, 45.0565, 48.2241, 51.5115] +24-11-19 18:46:46 | D | best error = [ 0.2536, 0.2536, 0.2536, 0.2536, 0.2536] +24-11-19 18:46:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:46:46 | D | sum error = [ 55.0036, 58.6991, 62.4726, 66.5005, 70.6387] +24-11-19 18:46:46 | D | best error = [ 0.2536, 0.2536, 0.2536, 0.2536, 0.2536] +24-11-19 18:46:46 | D | + error = [0.2536] +24-11-19 18:46:46 | D | - Calibrating model.layers.0.self_attn.v_proj.weight +24-11-19 18:46:46 | D | + w: sint8 +24-11-19 18:46:46 | D | + x: None +24-11-19 18:46:46 | D | + y: None +24-11-19 18:46:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:46:46 | D | + finished parsing calibration arguments, ram usage: 11.5 +24-11-19 18:46:46 | D | + finished reseting calibrator, ram usage: 11.5 +24-11-19 18:46:46 | D | + finished calculating the original outputs, ram usage: 11.5 +24-11-19 18:46:46 | D | - range ratio = [ 1.0000] +24-11-19 18:46:46 | D | sum error = [ 0.2193] +24-11-19 18:46:46 | D | best error = [ 0.2193] +24-11-19 18:46:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:46:46 | D | sum error = [ 0.2178, 0.2165, 0.2172, 0.2209, 0.2241] +24-11-19 18:46:46 | D | best error = [ 0.2060, 0.2008, 0.1982, 0.1969, 0.1960] +24-11-19 18:46:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:46:46 | D | sum error = [ 0.2293, 0.2382, 0.2481, 0.2593, 0.2738] +24-11-19 18:46:46 | D | best error = [ 0.1956, 0.1954, 0.1954, 0.1953, 0.1953] +24-11-19 18:46:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:46:46 | D | sum error = [ 0.2899, 0.3096, 0.3280, 0.3501, 0.3750] +24-11-19 18:46:46 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 18:46:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:46:46 | D | sum error = [ 0.4020, 0.4313, 0.4606, 0.4962, 0.5293] +24-11-19 18:46:46 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 18:46:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:46:46 | D | sum error = [ 0.5675, 0.6087, 0.6506, 0.6965, 0.7455] +24-11-19 18:46:46 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 18:46:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:46:46 | D | sum error = [ 0.7961, 0.8488, 0.9054, 0.9655, 1.0301] +24-11-19 18:46:46 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 18:46:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:46:46 | D | sum error = [ 1.0968, 1.1670, 1.2410, 1.3205, 1.4035] +24-11-19 18:46:46 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 18:46:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:46:46 | D | sum error = [ 1.4913, 1.5827, 1.6815, 1.7853, 1.8956] +24-11-19 18:46:46 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 18:46:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:46:46 | D | sum error = [ 2.0087, 2.1281, 2.2525, 2.3848, 2.5248] +24-11-19 18:46:46 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 18:46:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:46:46 | D | sum error = [ 2.6681, 2.8214, 2.9810, 3.1454, 3.3203] +24-11-19 18:46:46 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 18:46:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:46:46 | D | sum error = [ 3.5019, 3.6937, 3.8935, 4.1018, 4.3188] +24-11-19 18:46:46 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 18:46:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:46:46 | D | sum error = [ 4.5428, 4.7796, 5.0255, 5.2814, 5.5463] +24-11-19 18:46:46 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 18:46:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:46:46 | D | sum error = [ 5.8234, 6.1121, 6.4115, 6.7200, 7.0420] +24-11-19 18:46:46 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 18:46:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:46:46 | D | sum error = [ 7.3753, 7.7223, 8.0823, 8.4551, 8.8431] +24-11-19 18:46:46 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 18:46:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:46:46 | D | sum error = [ 9.2382, 9.6566, 10.0822, 10.5254, 10.9777] +24-11-19 18:46:46 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 18:46:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:46:46 | D | sum error = [ 11.4473, 11.9355, 12.4371, 12.9462, 13.4751] +24-11-19 18:46:46 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 18:46:46 | D | + error = [0.1953] +24-11-19 18:46:46 | D | - Calibrating model.layers.0.self_attn.o_proj.weight +24-11-19 18:46:46 | D | + w: sint8 +24-11-19 18:46:46 | D | + x: None +24-11-19 18:46:46 | D | + y: None +24-11-19 18:46:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:46:46 | D | + finished parsing calibration arguments, ram usage: 11.5 +24-11-19 18:46:46 | D | + finished reseting calibrator, ram usage: 11.5 +24-11-19 18:46:46 | D | + finished calculating the original outputs, ram usage: 11.5 +24-11-19 18:46:46 | D | - range ratio = [ 1.0000] +24-11-19 18:46:46 | D | sum error = [ 0.1014] +24-11-19 18:46:46 | D | best error = [ 0.1014] +24-11-19 18:46:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:46:47 | D | sum error = [ 0.1011, 0.1009, 0.1004, 0.1013, 0.1026] +24-11-19 18:46:47 | D | best error = [ 0.0902, 0.0859, 0.0834, 0.0820, 0.0811] +24-11-19 18:46:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:46:47 | D | sum error = [ 0.1056, 0.1081, 0.1115, 0.1154, 0.1205] +24-11-19 18:46:47 | D | best error = [ 0.0806, 0.0803, 0.0801, 0.0799, 0.0798] +24-11-19 18:46:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:46:47 | D | sum error = [ 0.1252, 0.1319, 0.1386, 0.1464, 0.1553] +24-11-19 18:46:47 | D | best error = [ 0.0798, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 18:46:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:46:47 | D | sum error = [ 0.1643, 0.1749, 0.1849, 0.1957, 0.2081] +24-11-19 18:46:47 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 18:46:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:46:47 | D | sum error = [ 0.2214, 0.2347, 0.2486, 0.2639, 0.2794] +24-11-19 18:46:47 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 18:46:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:46:47 | D | sum error = [ 0.2963, 0.3145, 0.3331, 0.3528, 0.3731] +24-11-19 18:46:47 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 18:46:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:46:47 | D | sum error = [ 0.3947, 0.4176, 0.4414, 0.4663, 0.4933] +24-11-19 18:46:47 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 18:46:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:46:47 | D | sum error = [ 0.5207, 0.5495, 0.5802, 0.6122, 0.6453] +24-11-19 18:46:47 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 18:46:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:46:47 | D | sum error = [ 0.6803, 0.7163, 0.7551, 0.7950, 0.8371] +24-11-19 18:46:47 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 18:46:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:46:47 | D | sum error = [ 0.8808, 0.9269, 0.9751, 1.0255, 1.0783] +24-11-19 18:46:47 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 18:46:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:46:47 | D | sum error = [ 1.1342, 1.1925, 1.2527, 1.3168, 1.3839] +24-11-19 18:46:47 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 18:46:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:46:47 | D | sum error = [ 1.4544, 1.5281, 1.6059, 1.6874, 1.7732] +24-11-19 18:46:47 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 18:46:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:46:47 | D | sum error = [ 1.8639, 1.9588, 2.0590, 2.1650, 2.2763] +24-11-19 18:46:47 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 18:46:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:46:47 | D | sum error = [ 2.3937, 2.5177, 2.6487, 2.7875, 2.9339] +24-11-19 18:46:47 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 18:46:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:46:47 | D | sum error = [ 3.0887, 3.2524, 3.4252, 3.6073, 3.8000] +24-11-19 18:46:47 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 18:46:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:46:47 | D | sum error = [ 4.0033, 4.2181, 4.4442, 4.6817, 4.9316] +24-11-19 18:46:47 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 18:46:47 | D | + error = [0.0797] +24-11-19 18:46:47 | D | - Calibrating model.layers.0.mlp.up_proj.weight +24-11-19 18:46:47 | D | + w: sint8 +24-11-19 18:46:47 | D | + x: None +24-11-19 18:46:47 | D | + y: None +24-11-19 18:46:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:46:47 | D | + finished parsing calibration arguments, ram usage: 11.5 +24-11-19 18:46:47 | D | + finished reseting calibrator, ram usage: 11.5 +24-11-19 18:46:47 | D | + finished calculating the original outputs, ram usage: 11.5 +24-11-19 18:46:47 | D | - range ratio = [ 1.0000] +24-11-19 18:46:47 | D | sum error = [ 2.2606] +24-11-19 18:46:47 | D | best error = [ 2.2606] +24-11-19 18:46:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:46:48 | D | sum error = [ 2.2440, 2.2534, 2.2473, 2.2776, 2.3220] +24-11-19 18:46:48 | D | best error = [ 1.9587, 1.8600, 1.8120, 1.7874, 1.7745] +24-11-19 18:46:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:46:48 | D | sum error = [ 2.3844, 2.4639, 2.5580, 2.6769, 2.8203] +24-11-19 18:46:48 | D | best error = [ 1.7677, 1.7644, 1.7632, 1.7627, 1.7626] +24-11-19 18:46:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:46:48 | D | sum error = [ 2.9755, 3.1721, 3.3687, 3.5980, 3.8508] +24-11-19 18:46:48 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 18:46:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:46:48 | D | sum error = [ 4.1289, 4.4220, 4.7278, 5.0683, 5.4289] +24-11-19 18:46:48 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 18:46:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:46:48 | D | sum error = [ 5.8146, 6.2320, 6.6839, 7.1387, 7.6263] +24-11-19 18:46:48 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 18:46:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:46:48 | D | sum error = [ 8.1391, 8.6967, 9.2717, 9.8850, 10.5353] +24-11-19 18:46:48 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 18:46:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:46:48 | D | sum error = [ 11.2253, 11.9461, 12.7076, 13.5005, 14.3488] +24-11-19 18:46:48 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 18:46:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:46:48 | D | sum error = [ 15.2349, 16.1825, 17.1606, 18.1984, 19.2827] +24-11-19 18:46:48 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 18:46:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:46:48 | D | sum error = [ 20.4207, 21.6123, 22.8676, 24.1704, 25.5445] +24-11-19 18:46:48 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 18:46:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:46:48 | D | sum error = [ 26.9862, 28.4909, 30.0510, 31.6862, 33.3914] +24-11-19 18:46:48 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 18:46:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:46:48 | D | sum error = [ 35.1696, 37.0370, 38.9715, 40.9964, 43.1047] +24-11-19 18:46:48 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 18:46:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:46:48 | D | sum error = [ 45.2971, 47.5756, 49.9515, 52.4044, 54.9502] +24-11-19 18:46:48 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 18:46:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:46:48 | D | sum error = [ 57.5901, 60.3275, 63.1578, 66.0883, 69.1155] +24-11-19 18:46:48 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 18:46:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:46:48 | D | sum error = [ 72.2658, 75.5222, 78.8807, 82.3588, 85.9552] +24-11-19 18:46:48 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 18:46:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:46:48 | D | sum error = [ 89.6679, 93.5025, 97.4544, 101.5237, 105.7318] +24-11-19 18:46:48 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 18:46:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:46:48 | D | sum error = [ 110.0648, 114.5185, 119.0958, 123.8127, 128.6630] +24-11-19 18:46:48 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 18:46:48 | D | + error = [1.7625] +24-11-19 18:46:48 | D | - Calibrating model.layers.0.mlp.gate_proj.weight +24-11-19 18:46:48 | D | + w: sint8 +24-11-19 18:46:48 | D | + x: None +24-11-19 18:46:48 | D | + y: None +24-11-19 18:46:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:46:48 | D | + finished parsing calibration arguments, ram usage: 11.5 +24-11-19 18:46:49 | D | + finished reseting calibrator, ram usage: 11.5 +24-11-19 18:46:49 | D | + finished calculating the original outputs, ram usage: 11.5 +24-11-19 18:46:49 | D | - range ratio = [ 1.0000] +24-11-19 18:46:49 | D | sum error = [ 2.4925] +24-11-19 18:46:49 | D | best error = [ 2.4925] +24-11-19 18:46:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:46:50 | D | sum error = [ 2.4685, 2.4669, 2.4705, 2.5084, 2.5609] +24-11-19 18:46:50 | D | best error = [ 2.1586, 2.0455, 1.9930, 1.9666, 1.9526] +24-11-19 18:46:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:46:50 | D | sum error = [ 2.6194, 2.7142, 2.8166, 2.9524, 3.1187] +24-11-19 18:46:50 | D | best error = [ 1.9451, 1.9417, 1.9406, 1.9400, 1.9399] +24-11-19 18:46:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:46:50 | D | sum error = [ 3.3007, 3.5003, 3.7487, 3.9832, 4.2776] +24-11-19 18:46:50 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 18:46:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:46:50 | D | sum error = [ 4.5814, 4.9088, 5.2640, 5.6560, 6.0630] +24-11-19 18:46:50 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 18:46:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:46:50 | D | sum error = [ 6.4869, 6.9653, 7.4493, 7.9752, 8.5342] +24-11-19 18:46:50 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 18:46:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:46:50 | D | sum error = [ 9.1347, 9.7686, 10.4226, 11.1435, 11.8854] +24-11-19 18:46:50 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 18:46:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:46:50 | D | sum error = [ 12.6731, 13.5071, 14.3957, 15.3215, 16.3074] +24-11-19 18:46:50 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 18:46:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:46:50 | D | sum error = [ 17.3393, 18.4393, 19.5982, 20.8128, 22.1063] +24-11-19 18:46:50 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 18:46:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:46:50 | D | sum error = [ 23.4630, 24.9016, 26.4145, 27.9974, 29.6842] +24-11-19 18:46:50 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 18:46:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:46:50 | D | sum error = [ 31.4595, 33.3230, 35.2820, 37.3383, 39.4903] +24-11-19 18:46:50 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 18:46:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:46:50 | D | sum error = [ 41.7521, 44.1281, 46.6129, 49.2286, 51.9737] +24-11-19 18:46:50 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 18:46:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:46:50 | D | sum error = [ 54.8395, 57.8361, 60.9741, 64.2671, 67.6998] +24-11-19 18:46:50 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 18:46:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:46:50 | D | sum error = [ 71.2954, 75.0443, 78.9598, 83.0351, 87.2865] +24-11-19 18:46:50 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 18:46:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:46:50 | D | sum error = [ 91.6985, 96.2938, 101.0750, 106.0364, 111.1839] +24-11-19 18:46:50 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 18:46:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:46:50 | D | sum error = [ 116.5351, 122.0650, 127.7921, 133.7295, 139.8644] +24-11-19 18:46:50 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 18:46:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:46:50 | D | sum error = [ 146.2084, 152.7497, 159.5057, 166.4499, 173.5979] +24-11-19 18:46:50 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 18:46:50 | D | + error = [1.9398] +24-11-19 18:46:50 | D | - Calibrating model.layers.0.mlp.down_proj.weight +24-11-19 18:46:50 | D | + w: sint8 +24-11-19 18:46:50 | D | + x: None +24-11-19 18:46:50 | D | + y: None +24-11-19 18:46:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:46:50 | D | + finished parsing calibration arguments, ram usage: 11.5 +24-11-19 18:46:50 | D | + finished reseting calibrator, ram usage: 11.5 +24-11-19 18:46:50 | D | + finished calculating the original outputs, ram usage: 11.5 +24-11-19 18:46:50 | D | - range ratio = [ 1.0000] +24-11-19 18:46:50 | D | sum error = [ 0.1641] +24-11-19 18:46:50 | D | best error = [ 0.1641] +24-11-19 18:46:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:46:51 | D | sum error = [ 0.1636, 0.1663, 0.1712, 0.1798, 0.1903] +24-11-19 18:46:51 | D | best error = [ 0.1496, 0.1434, 0.1397, 0.1370, 0.1349] +24-11-19 18:46:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:46:51 | D | sum error = [ 0.2039, 0.2198, 0.2368, 0.2570, 0.2792] +24-11-19 18:46:51 | D | best error = [ 0.1333, 0.1321, 0.1310, 0.1301, 0.1294] +24-11-19 18:46:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:46:51 | D | sum error = [ 0.3030, 0.3301, 0.3569, 0.3863, 0.4184] +24-11-19 18:46:51 | D | best error = [ 0.1289, 0.1285, 0.1281, 0.1278, 0.1277] +24-11-19 18:46:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:46:51 | D | sum error = [ 0.4517, 0.4873, 0.5258, 0.5652, 0.6072] +24-11-19 18:46:51 | D | best error = [ 0.1275, 0.1274, 0.1273, 0.1273, 0.1272] +24-11-19 18:46:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:46:51 | D | sum error = [ 0.6517, 0.6995, 0.7485, 0.8007, 0.8544] +24-11-19 18:46:51 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 18:46:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:46:51 | D | sum error = [ 0.9124, 0.9722, 1.0356, 1.1028, 1.1735] +24-11-19 18:46:51 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 18:46:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:46:51 | D | sum error = [ 1.2474, 1.3250, 1.4057, 1.4919, 1.5835] +24-11-19 18:46:51 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 18:46:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:46:51 | D | sum error = [ 1.6789, 1.7790, 1.8840, 1.9953, 2.1114] +24-11-19 18:46:51 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 18:46:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:46:51 | D | sum error = [ 2.2333, 2.3602, 2.4940, 2.6353, 2.7823] +24-11-19 18:46:51 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 18:46:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:46:51 | D | sum error = [ 2.9372, 3.0986, 3.2685, 3.4469, 3.6331] +24-11-19 18:46:51 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 18:46:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:46:51 | D | sum error = [ 3.8271, 4.0309, 4.2440, 4.4677, 4.7012] +24-11-19 18:46:51 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 18:46:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:46:51 | D | sum error = [ 4.9451, 5.1996, 5.4651, 5.7416, 6.0311] +24-11-19 18:46:51 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 18:46:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:46:51 | D | sum error = [ 6.3321, 6.6462, 6.9736, 7.3146, 7.6690] +24-11-19 18:46:51 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 18:46:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:46:51 | D | sum error = [ 8.0381, 8.4220, 8.8204, 9.2342, 9.6632] +24-11-19 18:46:51 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 18:46:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:46:51 | D | sum error = [ 10.1082, 10.5688, 11.0461, 11.5404, 12.0510] +24-11-19 18:46:51 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 18:46:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:46:51 | D | sum error = [ 12.5789, 13.1239, 13.6868, 14.2677, 14.8656] +24-11-19 18:46:51 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 18:46:51 | D | + error = [0.1272] +24-11-19 18:46:52 | D | - Quantizing model.layers.0.self_attn.q_proj.weight +24-11-19 18:46:52 | D | - Quantizing model.layers.0.self_attn.k_proj.weight +24-11-19 18:46:53 | D | - Quantizing model.layers.0.self_attn.v_proj.weight +24-11-19 18:46:54 | D | - Quantizing model.layers.0.self_attn.o_proj.weight +24-11-19 18:46:55 | D | - Quantizing model.layers.0.mlp.up_proj.weight +24-11-19 18:46:56 | D | - Quantizing model.layers.0.mlp.gate_proj.weight +24-11-19 18:46:57 | D | - Quantizing model.layers.0.mlp.down_proj.weight +24-11-19 18:47:06 | D | - Quantizing layer model.layers.1 +24-11-19 18:47:06 | D | - Calibrating model.layers.1.self_attn.q_proj.weight +24-11-19 18:47:06 | D | + w: sint8 +24-11-19 18:47:06 | D | + x: None +24-11-19 18:47:06 | D | + y: None +24-11-19 18:47:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:47:06 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:47:06 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:47:07 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:47:07 | D | - range ratio = [ 1.0000] +24-11-19 18:47:07 | D | sum error = [ 0.4266] +24-11-19 18:47:07 | D | best error = [ 0.4266] +24-11-19 18:47:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:47:18 | D | sum error = [ 0.4330, 0.4297, 0.4230, 0.4402, 0.4759] +24-11-19 18:47:18 | D | best error = [ 0.4266, 0.4266, 0.4230, 0.4230, 0.4230] +24-11-19 18:47:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:47:18 | D | sum error = [ 0.4747, 0.4779, 0.5172, 0.5407, 0.5931] +24-11-19 18:47:18 | D | best error = [ 0.4230, 0.4230, 0.4230, 0.4230, 0.4230] +24-11-19 18:47:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:47:18 | D | sum error = [ 0.6514, 0.6989, 0.7900, 0.8853, 1.0257] +24-11-19 18:47:18 | D | best error = [ 0.4230, 0.4230, 0.4230, 0.4230, 0.4230] +24-11-19 18:47:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:47:18 | D | sum error = [ 1.0944, 1.2176, 1.3608, 1.5048, 1.6533] +24-11-19 18:47:18 | D | best error = [ 0.4230, 0.4230, 0.4230, 0.4230, 0.4230] +24-11-19 18:47:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:47:18 | D | sum error = [ 1.9276, 2.1475, 2.3307, 2.6260, 2.9117] +24-11-19 18:47:18 | D | best error = [ 0.4230, 0.4230, 0.4230, 0.4230, 0.4230] +24-11-19 18:47:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:47:18 | D | sum error = [ 3.2629, 3.5505, 3.9445, 4.3399, 4.8291] +24-11-19 18:47:18 | D | best error = [ 0.4230, 0.4230, 0.4230, 0.4230, 0.4230] +24-11-19 18:47:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:47:18 | D | sum error = [ 5.2638, 5.7129, 6.2691, 6.8826, 7.4814] +24-11-19 18:47:18 | D | best error = [ 0.4230, 0.4230, 0.4230, 0.4230, 0.4230] +24-11-19 18:47:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:47:18 | D | sum error = [ 8.1162, 8.7938, 9.5158, 10.2961, 11.1600] +24-11-19 18:47:18 | D | best error = [ 0.4230, 0.4230, 0.4230, 0.4230, 0.4230] +24-11-19 18:47:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:47:18 | D | sum error = [ 12.0606, 13.0561, 14.1115, 15.2376, 16.4325] +24-11-19 18:47:18 | D | best error = [ 0.4230, 0.4230, 0.4230, 0.4230, 0.4230] +24-11-19 18:47:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:47:18 | D | sum error = [ 17.7361, 19.1397, 20.6435, 22.2798, 24.0799] +24-11-19 18:47:18 | D | best error = [ 0.4230, 0.4230, 0.4230, 0.4230, 0.4230] +24-11-19 18:47:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:47:18 | D | sum error = [ 25.9334, 27.9992, 30.1044, 32.4840, 34.9297] +24-11-19 18:47:18 | D | best error = [ 0.4230, 0.4230, 0.4230, 0.4230, 0.4230] +24-11-19 18:47:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:47:18 | D | sum error = [ 37.5326, 40.3651, 43.3129, 46.4962, 49.8228] +24-11-19 18:47:18 | D | best error = [ 0.4230, 0.4230, 0.4230, 0.4230, 0.4230] +24-11-19 18:47:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:47:18 | D | sum error = [ 53.4072, 57.2224, 61.2886, 65.5614, 70.2332] +24-11-19 18:47:18 | D | best error = [ 0.4230, 0.4230, 0.4230, 0.4230, 0.4230] +24-11-19 18:47:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:47:18 | D | sum error = [ 75.1124, 80.2868, 85.9009, 91.7631, 98.0879] +24-11-19 18:47:18 | D | best error = [ 0.4230, 0.4230, 0.4230, 0.4230, 0.4230] +24-11-19 18:47:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:47:18 | D | sum error = [ 104.7127, 111.7878, 119.2658, 127.0507, 135.3181] +24-11-19 18:47:18 | D | best error = [ 0.4230, 0.4230, 0.4230, 0.4230, 0.4230] +24-11-19 18:47:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:47:18 | D | sum error = [ 143.9916, 153.0182, 162.4135, 172.1805, 182.2930] +24-11-19 18:47:18 | D | best error = [ 0.4230, 0.4230, 0.4230, 0.4230, 0.4230] +24-11-19 18:47:18 | D | + error = [0.4230] +24-11-19 18:47:19 | D | - Calibrating model.layers.1.self_attn.k_proj.weight +24-11-19 18:47:19 | D | + w: sint8 +24-11-19 18:47:19 | D | + x: None +24-11-19 18:47:19 | D | + y: None +24-11-19 18:47:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:47:19 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:47:19 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:47:19 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:47:19 | D | - range ratio = [ 1.0000] +24-11-19 18:47:19 | D | sum error = [ 0.5264] +24-11-19 18:47:19 | D | best error = [ 0.5264] +24-11-19 18:47:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:47:31 | D | sum error = [ 0.5148, 0.5271, 0.5065, 0.5378, 0.5403] +24-11-19 18:47:31 | D | best error = [ 0.5148, 0.5148, 0.5065, 0.5065, 0.5065] +24-11-19 18:47:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:47:31 | D | sum error = [ 0.5932, 0.5511, 0.6385, 0.6193, 0.6771] +24-11-19 18:47:31 | D | best error = [ 0.5065, 0.5065, 0.5065, 0.5065, 0.5065] +24-11-19 18:47:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:47:31 | D | sum error = [ 0.7165, 0.7326, 0.8229, 0.8949, 0.9583] +24-11-19 18:47:31 | D | best error = [ 0.5065, 0.5065, 0.5065, 0.5065, 0.5065] +24-11-19 18:47:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:47:31 | D | sum error = [ 1.1482, 1.2381, 1.3462, 1.4848, 1.6316] +24-11-19 18:47:31 | D | best error = [ 0.5065, 0.5065, 0.5065, 0.5065, 0.5065] +24-11-19 18:47:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:47:31 | D | sum error = [ 1.9417, 2.0625, 2.4167, 2.6217, 2.8730] +24-11-19 18:47:31 | D | best error = [ 0.5065, 0.5065, 0.5065, 0.5065, 0.5065] +24-11-19 18:47:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:47:31 | D | sum error = [ 2.9799, 3.4568, 3.8593, 4.2956, 4.6514] +24-11-19 18:47:31 | D | best error = [ 0.5065, 0.5065, 0.5065, 0.5065, 0.5065] +24-11-19 18:47:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:47:31 | D | sum error = [ 5.3027, 5.6494, 6.3134, 6.8232, 7.5788] +24-11-19 18:47:31 | D | best error = [ 0.5065, 0.5065, 0.5065, 0.5065, 0.5065] +24-11-19 18:47:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:47:31 | D | sum error = [ 8.2592, 9.0908, 9.7826, 10.7619, 11.4028] +24-11-19 18:47:31 | D | best error = [ 0.5065, 0.5065, 0.5065, 0.5065, 0.5065] +24-11-19 18:47:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:47:31 | D | sum error = [ 12.3404, 13.5457, 14.5584, 15.6328, 16.7750] +24-11-19 18:47:31 | D | best error = [ 0.5065, 0.5065, 0.5065, 0.5065, 0.5065] +24-11-19 18:47:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:47:31 | D | sum error = [ 17.8792, 19.0870, 20.8356, 22.1453, 23.8383] +24-11-19 18:47:31 | D | best error = [ 0.5065, 0.5065, 0.5065, 0.5065, 0.5065] +24-11-19 18:47:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:47:31 | D | sum error = [ 25.7846, 27.4852, 29.5831, 31.9769, 34.0782] +24-11-19 18:47:31 | D | best error = [ 0.5065, 0.5065, 0.5065, 0.5065, 0.5065] +24-11-19 18:47:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:47:31 | D | sum error = [ 36.8409, 39.2521, 42.5035, 45.3798, 49.0209] +24-11-19 18:47:31 | D | best error = [ 0.5065, 0.5065, 0.5065, 0.5065, 0.5065] +24-11-19 18:47:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:47:31 | D | sum error = [ 53.0950, 56.6739, 60.6381, 65.7954, 70.6241] +24-11-19 18:47:31 | D | best error = [ 0.5065, 0.5065, 0.5065, 0.5065, 0.5065] +24-11-19 18:47:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:47:31 | D | sum error = [ 75.0748, 81.1026, 86.3994, 91.9236, 98.1349] +24-11-19 18:47:31 | D | best error = [ 0.5065, 0.5065, 0.5065, 0.5065, 0.5065] +24-11-19 18:47:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:47:31 | D | sum error = [ 104.8521, 111.5700, 119.1212, 126.8878, 134.6104] +24-11-19 18:47:31 | D | best error = [ 0.5065, 0.5065, 0.5065, 0.5065, 0.5065] +24-11-19 18:47:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:47:31 | D | sum error = [ 143.5315, 152.6800, 161.1167, 171.7059, 181.5728] +24-11-19 18:47:31 | D | best error = [ 0.5065, 0.5065, 0.5065, 0.5065, 0.5065] +24-11-19 18:47:31 | D | + error = [0.5065] +24-11-19 18:47:31 | D | - Calibrating model.layers.1.self_attn.v_proj.weight +24-11-19 18:47:31 | D | + w: sint8 +24-11-19 18:47:31 | D | + x: None +24-11-19 18:47:31 | D | + y: None +24-11-19 18:47:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:47:31 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:47:31 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:47:31 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:47:31 | D | - range ratio = [ 1.0000] +24-11-19 18:47:31 | D | sum error = [ 0.3294] +24-11-19 18:47:31 | D | best error = [ 0.3294] +24-11-19 18:47:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:47:31 | D | sum error = [ 0.3318, 0.3363, 0.3407, 0.3381, 0.3455] +24-11-19 18:47:31 | D | best error = [ 0.2895, 0.2763, 0.2705, 0.2663, 0.2638] +24-11-19 18:47:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:47:31 | D | sum error = [ 0.3512, 0.3679, 0.3774, 0.3980, 0.4161] +24-11-19 18:47:31 | D | best error = [ 0.2624, 0.2621, 0.2618, 0.2618, 0.2618] +24-11-19 18:47:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:47:31 | D | sum error = [ 0.4412, 0.4761, 0.5048, 0.5370, 0.5741] +24-11-19 18:47:31 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 18:47:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:47:31 | D | sum error = [ 0.6138, 0.6649, 0.7099, 0.7621, 0.8185] +24-11-19 18:47:31 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 18:47:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:47:31 | D | sum error = [ 0.8748, 0.9379, 1.0041, 1.0734, 1.1491] +24-11-19 18:47:31 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 18:47:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:47:31 | D | sum error = [ 1.2320, 1.3188, 1.4054, 1.5045, 1.6055] +24-11-19 18:47:31 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 18:47:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:47:31 | D | sum error = [ 1.7072, 1.8264, 1.9491, 2.0751, 2.2106] +24-11-19 18:47:31 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 18:47:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:47:31 | D | sum error = [ 2.3531, 2.5026, 2.6662, 2.8296, 3.0075] +24-11-19 18:47:31 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 18:47:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:47:31 | D | sum error = [ 3.1903, 3.3819, 3.5857, 3.8012, 4.0309] +24-11-19 18:47:31 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 18:47:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:47:31 | D | sum error = [ 4.2656, 4.5187, 4.7817, 5.0580, 5.3496] +24-11-19 18:47:31 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 18:47:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:47:31 | D | sum error = [ 5.6503, 5.9666, 6.2939, 6.6413, 7.0047] +24-11-19 18:47:31 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 18:47:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:47:31 | D | sum error = [ 7.3769, 7.7712, 8.1822, 8.6119, 9.0603] +24-11-19 18:47:31 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 18:47:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:47:31 | D | sum error = [ 9.5292, 10.0163, 10.5322, 11.0698, 11.6274] +24-11-19 18:47:31 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 18:47:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:47:31 | D | sum error = [ 12.2053, 12.8132, 13.4399, 14.0968, 14.7771] +24-11-19 18:47:31 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 18:47:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:47:31 | D | sum error = [ 15.4821, 16.2135, 16.9706, 17.7526, 18.5686] +24-11-19 18:47:31 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 18:47:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:47:31 | D | sum error = [ 19.4044, 20.2756, 21.1660, 22.0940, 23.0469] +24-11-19 18:47:31 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 18:47:31 | D | + error = [0.2618] +24-11-19 18:47:31 | D | - Calibrating model.layers.1.self_attn.o_proj.weight +24-11-19 18:47:31 | D | + w: sint8 +24-11-19 18:47:31 | D | + x: None +24-11-19 18:47:31 | D | + y: None +24-11-19 18:47:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:47:31 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:47:31 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:47:31 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:47:31 | D | - range ratio = [ 1.0000] +24-11-19 18:47:31 | D | sum error = [ 0.1715] +24-11-19 18:47:31 | D | best error = [ 0.1715] +24-11-19 18:47:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:47:32 | D | sum error = [ 0.1714, 0.1715, 0.1711, 0.1736, 0.1769] +24-11-19 18:47:32 | D | best error = [ 0.1451, 0.1357, 0.1307, 0.1276, 0.1256] +24-11-19 18:47:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:47:32 | D | sum error = [ 0.1834, 0.1906, 0.1981, 0.2086, 0.2177] +24-11-19 18:47:32 | D | best error = [ 0.1242, 0.1233, 0.1226, 0.1221, 0.1218] +24-11-19 18:47:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:47:32 | D | sum error = [ 0.2321, 0.2444, 0.2620, 0.2816, 0.2976] +24-11-19 18:47:32 | D | best error = [ 0.1215, 0.1213, 0.1212, 0.1212, 0.1211] +24-11-19 18:47:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:47:32 | D | sum error = [ 0.3189, 0.3423, 0.3661, 0.3919, 0.4202] +24-11-19 18:47:32 | D | best error = [ 0.1211, 0.1211, 0.1210, 0.1210, 0.1210] +24-11-19 18:47:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:47:32 | D | sum error = [ 0.4477, 0.4783, 0.5106, 0.5460, 0.5800] +24-11-19 18:47:32 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 18:47:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:47:32 | D | sum error = [ 0.6194, 0.6581, 0.6998, 0.7448, 0.7923] +24-11-19 18:47:32 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 18:47:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:47:32 | D | sum error = [ 0.8393, 0.8907, 0.9449, 1.0029, 1.0619] +24-11-19 18:47:32 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 18:47:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:47:32 | D | sum error = [ 1.1270, 1.1929, 1.2632, 1.3355, 1.4128] +24-11-19 18:47:32 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 18:47:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:47:32 | D | sum error = [ 1.4944, 1.5789, 1.6669, 1.7620, 1.8595] +24-11-19 18:47:32 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 18:47:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:47:32 | D | sum error = [ 1.9630, 2.0718, 2.1844, 2.3028, 2.4295] +24-11-19 18:47:32 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 18:47:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:47:32 | D | sum error = [ 2.5585, 2.6951, 2.8373, 2.9860, 3.1410] +24-11-19 18:47:32 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 18:47:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:47:32 | D | sum error = [ 3.3036, 3.4725, 3.6491, 3.8322, 4.0236] +24-11-19 18:47:32 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 18:47:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:47:32 | D | sum error = [ 4.2247, 4.4349, 4.6525, 4.8814, 5.1192] +24-11-19 18:47:32 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 18:47:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:47:32 | D | sum error = [ 5.3671, 5.6261, 5.8959, 6.1753, 6.4658] +24-11-19 18:47:32 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 18:47:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:47:32 | D | sum error = [ 6.7680, 7.0804, 7.4045, 7.7410, 8.0899] +24-11-19 18:47:32 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 18:47:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:47:32 | D | sum error = [ 8.4525, 8.8289, 9.2179, 9.6206, 10.0361] +24-11-19 18:47:32 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 18:47:32 | D | + error = [0.1210] +24-11-19 18:47:32 | D | - Calibrating model.layers.1.mlp.up_proj.weight +24-11-19 18:47:32 | D | + w: sint8 +24-11-19 18:47:32 | D | + x: None +24-11-19 18:47:32 | D | + y: None +24-11-19 18:47:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:47:32 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:47:32 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:47:32 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:47:32 | D | - range ratio = [ 1.0000] +24-11-19 18:47:32 | D | sum error = [ 2.8587] +24-11-19 18:47:32 | D | best error = [ 2.8587] +24-11-19 18:47:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:47:33 | D | sum error = [ 2.8478, 2.8403, 2.8455, 2.8714, 2.9348] +24-11-19 18:47:33 | D | best error = [ 2.5600, 2.4592, 2.4095, 2.3818, 2.3678] +24-11-19 18:47:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:47:33 | D | sum error = [ 3.0035, 3.1014, 3.2269, 3.3767, 3.5564] +24-11-19 18:47:33 | D | best error = [ 2.3599, 2.3564, 2.3550, 2.3545, 2.3543] +24-11-19 18:47:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:47:33 | D | sum error = [ 3.7697, 3.9968, 4.2592, 4.5401, 4.8493] +24-11-19 18:47:33 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 18:47:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:47:33 | D | sum error = [ 5.1894, 5.5658, 5.9570, 6.3827, 6.8402] +24-11-19 18:47:33 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 18:47:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:47:33 | D | sum error = [ 7.3233, 7.8433, 8.4096, 8.9832, 9.6155] +24-11-19 18:47:33 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 18:47:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:47:33 | D | sum error = [ 10.2823, 10.9748, 11.7283, 12.5027, 13.3356] +24-11-19 18:47:33 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 18:47:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:47:33 | D | sum error = [ 14.2070, 15.1243, 16.0843, 17.1077, 18.1667] +24-11-19 18:47:33 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 18:47:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:47:33 | D | sum error = [ 19.3034, 20.4810, 21.7155, 23.0216, 24.3950] +24-11-19 18:47:33 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 18:47:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:47:33 | D | sum error = [ 25.8040, 27.2999, 28.8618, 30.4906, 32.1956] +24-11-19 18:47:33 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 18:47:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:47:33 | D | sum error = [ 33.9886, 35.8464, 37.7940, 39.8152, 41.9159] +24-11-19 18:47:33 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 18:47:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:47:33 | D | sum error = [ 44.1047, 46.3848, 48.7580, 51.2120, 53.7624] +24-11-19 18:47:33 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 18:47:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:47:33 | D | sum error = [ 56.4084, 59.1605, 62.0054, 64.9515, 68.0061] +24-11-19 18:47:33 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 18:47:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:47:33 | D | sum error = [ 71.1715, 74.4235, 77.7935, 81.2795, 84.8690] +24-11-19 18:47:33 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 18:47:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:47:33 | D | sum error = [ 88.5754, 92.4037, 96.3343, 100.3833, 104.5504] +24-11-19 18:47:33 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 18:47:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:47:33 | D | sum error = [ 108.8207, 113.2285, 117.7605, 122.4094, 127.1847] +24-11-19 18:47:33 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 18:47:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:47:33 | D | sum error = [ 132.1107, 137.1536, 142.3304, 147.6304, 153.0661] +24-11-19 18:47:33 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 18:47:33 | D | + error = [2.3543] +24-11-19 18:47:33 | D | - Calibrating model.layers.1.mlp.gate_proj.weight +24-11-19 18:47:33 | D | + w: sint8 +24-11-19 18:47:33 | D | + x: None +24-11-19 18:47:33 | D | + y: None +24-11-19 18:47:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:47:33 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:47:33 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:47:33 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:47:33 | D | - range ratio = [ 1.0000] +24-11-19 18:47:33 | D | sum error = [ 3.1407] +24-11-19 18:47:33 | D | best error = [ 3.1407] +24-11-19 18:47:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:47:35 | D | sum error = [ 3.1194, 3.1115, 3.1216, 3.1556, 3.2210] +24-11-19 18:47:35 | D | best error = [ 2.8113, 2.7001, 2.6439, 2.6124, 2.5956] +24-11-19 18:47:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:47:35 | D | sum error = [ 3.2958, 3.4250, 3.5639, 3.7060, 3.9122] +24-11-19 18:47:35 | D | best error = [ 2.5874, 2.5834, 2.5818, 2.5813, 2.5812] +24-11-19 18:47:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:47:35 | D | sum error = [ 4.1398, 4.3993, 4.6881, 5.0054, 5.3382] +24-11-19 18:47:35 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 18:47:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:47:35 | D | sum error = [ 5.7277, 6.1403, 6.5766, 7.0422, 7.5545] +24-11-19 18:47:35 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 18:47:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:47:35 | D | sum error = [ 8.1074, 8.6789, 9.2919, 9.9557, 10.6587] +24-11-19 18:47:35 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 18:47:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:47:35 | D | sum error = [ 11.3907, 12.1812, 13.0135, 13.8805, 14.8351] +24-11-19 18:47:35 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 18:47:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:47:35 | D | sum error = [ 15.8138, 16.8597, 17.9430, 19.1224, 20.3502] +24-11-19 18:47:35 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 18:47:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:47:35 | D | sum error = [ 21.6437, 23.0060, 24.4404, 25.9433, 27.5297] +24-11-19 18:47:35 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 18:47:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:47:35 | D | sum error = [ 29.2007, 30.9575, 32.7994, 34.7381, 36.7919] +24-11-19 18:47:35 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 18:47:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:47:35 | D | sum error = [ 38.8924, 41.1365, 43.4846, 45.9333, 48.5119] +24-11-19 18:47:35 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 18:47:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:47:35 | D | sum error = [ 51.1918, 54.0083, 56.9475, 60.0054, 63.2196] +24-11-19 18:47:35 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 18:47:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:47:35 | D | sum error = [ 66.5702, 70.0563, 73.7002, 77.4979, 81.4439] +24-11-19 18:47:35 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 18:47:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:47:35 | D | sum error = [ 85.5654, 89.8638, 94.3492, 98.9857, 103.8039] +24-11-19 18:47:35 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 18:47:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:47:35 | D | sum error = [ 108.8117, 113.9946, 119.3791, 124.9658, 130.7152] +24-11-19 18:47:35 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 18:47:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:47:35 | D | sum error = [ 136.7068, 142.8795, 149.2639, 155.8615, 162.6906] +24-11-19 18:47:35 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 18:47:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:47:35 | D | sum error = [ 169.6949, 176.9067, 184.3563, 192.0177, 199.8928] +24-11-19 18:47:35 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 18:47:35 | D | + error = [2.5811] +24-11-19 18:47:35 | D | - Calibrating model.layers.1.mlp.down_proj.weight +24-11-19 18:47:35 | D | + w: sint8 +24-11-19 18:47:35 | D | + x: None +24-11-19 18:47:35 | D | + y: None +24-11-19 18:47:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:47:35 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:47:35 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:47:35 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:47:35 | D | - range ratio = [ 1.0000] +24-11-19 18:47:35 | D | sum error = [ 7.9591] +24-11-19 18:47:35 | D | best error = [ 7.9591] +24-11-19 18:47:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:47:36 | D | sum error = [ 7.9157, 7.8600, 7.6944, 7.6240, 7.6451] +24-11-19 18:47:36 | D | best error = [ 5.3061, 3.5582, 2.5455, 2.0893, 1.8233] +24-11-19 18:47:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:47:36 | D | sum error = [ 7.4927, 7.4259, 7.3341, 7.2715, 7.1535] +24-11-19 18:47:36 | D | best error = [ 1.6384, 1.4977, 1.3851, 1.2995, 1.2109] +24-11-19 18:47:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:47:36 | D | sum error = [ 7.1480, 7.0531, 6.9486, 6.9361, 6.8553] +24-11-19 18:47:36 | D | best error = [ 1.1280, 1.0696, 1.0201, 0.9718, 0.9320] +24-11-19 18:47:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:47:36 | D | sum error = [ 6.6392, 6.5877, 6.6797, 6.4963, 6.3144] +24-11-19 18:47:36 | D | best error = [ 0.9013, 0.8758, 0.8497, 0.8245, 0.8024] +24-11-19 18:47:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:47:36 | D | sum error = [ 6.3767, 6.2338, 6.1571, 6.0932, 6.0145] +24-11-19 18:47:36 | D | best error = [ 0.7824, 0.7623, 0.7422, 0.7270, 0.7084] +24-11-19 18:47:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:47:36 | D | sum error = [ 5.9206, 5.8803, 5.8285, 5.7613, 5.7062] +24-11-19 18:47:36 | D | best error = [ 0.6922, 0.6758, 0.6603, 0.6468, 0.6383] +24-11-19 18:47:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:47:36 | D | sum error = [ 5.8050, 6.0816, 6.5824, 7.5586, 9.0175] +24-11-19 18:47:36 | D | best error = [ 0.6261, 0.6182, 0.6088, 0.6042, 0.5984] +24-11-19 18:47:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:47:36 | D | sum error = [ 10.9590, 13.4600, 16.6624, 20.6222, 25.3745] +24-11-19 18:47:36 | D | best error = [ 0.5931, 0.5879, 0.5845, 0.5819, 0.5809] +24-11-19 18:47:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:47:36 | D | sum error = [ 30.9930, 37.6028, 45.2574, 53.9781, 63.7948] +24-11-19 18:47:36 | D | best error = [ 0.5778, 0.5774, 0.5771, 0.5763, 0.5760] +24-11-19 18:47:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:47:36 | D | sum error = [ 74.6279, 86.4621, 99.1837, 112.7870, 127.1712] +24-11-19 18:47:36 | D | best error = [ 0.5760, 0.5757, 0.5757, 0.5757, 0.5757] +24-11-19 18:47:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:47:36 | D | sum error = [ 142.2490, 157.9393, 174.1446, 190.7974, 207.8472] +24-11-19 18:47:36 | D | best error = [ 0.5756, 0.5755, 0.5755, 0.5754, 0.5754] +24-11-19 18:47:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:47:36 | D | sum error = [ 225.2549, 242.9607, 260.9119, 279.0856, 297.4546] +24-11-19 18:47:36 | D | best error = [ 0.5754, 0.5754, 0.5754, 0.5754, 0.5754] +24-11-19 18:47:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:47:36 | D | sum error = [ 315.9476, 334.5793, 353.3324, 372.1834, 391.1233] +24-11-19 18:47:36 | D | best error = [ 0.5754, 0.5754, 0.5754, 0.5754, 0.5754] +24-11-19 18:47:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:47:36 | D | sum error = [ 410.1312, 429.2203, 448.3491, 467.5552, 486.7728] +24-11-19 18:47:36 | D | best error = [ 0.5754, 0.5754, 0.5754, 0.5754, 0.5754] +24-11-19 18:47:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:47:36 | D | sum error = [ 506.0567, 525.3800, 544.7496, 564.1900, 583.7210] +24-11-19 18:47:36 | D | best error = [ 0.5754, 0.5754, 0.5754, 0.5754, 0.5754] +24-11-19 18:47:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:47:36 | D | sum error = [ 603.3769, 623.1961, 643.2531, 663.6215, 684.3780] +24-11-19 18:47:36 | D | best error = [ 0.5754, 0.5754, 0.5754, 0.5754, 0.5754] +24-11-19 18:47:36 | D | + error = [0.5754] +24-11-19 18:47:36 | D | - Quantizing model.layers.1.self_attn.q_proj.weight +24-11-19 18:47:37 | D | - Quantizing model.layers.1.self_attn.k_proj.weight +24-11-19 18:47:38 | D | - Quantizing model.layers.1.self_attn.v_proj.weight +24-11-19 18:47:39 | D | - Quantizing model.layers.1.self_attn.o_proj.weight +24-11-19 18:47:39 | D | - Quantizing model.layers.1.mlp.up_proj.weight +24-11-19 18:47:40 | D | - Quantizing model.layers.1.mlp.gate_proj.weight +24-11-19 18:47:41 | D | - Quantizing model.layers.1.mlp.down_proj.weight +24-11-19 18:47:51 | D | - Quantizing layer model.layers.2 +24-11-19 18:47:51 | D | - Calibrating model.layers.2.self_attn.q_proj.weight +24-11-19 18:47:51 | D | + w: sint8 +24-11-19 18:47:51 | D | + x: None +24-11-19 18:47:51 | D | + y: None +24-11-19 18:47:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:47:51 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:47:51 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:47:51 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:47:51 | D | - range ratio = [ 1.0000] +24-11-19 18:47:51 | D | sum error = [ 0.7872] +24-11-19 18:47:51 | D | best error = [ 0.7872] +24-11-19 18:48:02 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:48:02 | D | sum error = [ 0.7799, 0.7831, 0.7819, 0.7924, 0.8282] +24-11-19 18:48:02 | D | best error = [ 0.7799, 0.7799, 0.7799, 0.7799, 0.7799] +24-11-19 18:48:02 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:48:02 | D | sum error = [ 0.8473, 0.8786, 0.9412, 1.0017, 1.0785] +24-11-19 18:48:02 | D | best error = [ 0.7799, 0.7799, 0.7799, 0.7799, 0.7799] +24-11-19 18:48:02 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:48:02 | D | sum error = [ 1.1228, 1.2059, 1.3314, 1.4574, 1.5944] +24-11-19 18:48:02 | D | best error = [ 0.7799, 0.7799, 0.7799, 0.7799, 0.7799] +24-11-19 18:48:02 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:48:02 | D | sum error = [ 1.7280, 1.9323, 2.1191, 2.3317, 2.5383] +24-11-19 18:48:02 | D | best error = [ 0.7799, 0.7799, 0.7799, 0.7799, 0.7799] +24-11-19 18:48:02 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:48:02 | D | sum error = [ 2.7341, 3.0036, 3.2309, 3.5987, 3.9400] +24-11-19 18:48:02 | D | best error = [ 0.7799, 0.7799, 0.7799, 0.7799, 0.7799] +24-11-19 18:48:02 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:48:02 | D | sum error = [ 4.3968, 4.7272, 5.1604, 5.6446, 6.1470] +24-11-19 18:48:02 | D | best error = [ 0.7799, 0.7799, 0.7799, 0.7799, 0.7799] +24-11-19 18:48:02 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:48:02 | D | sum error = [ 6.7647, 7.3601, 8.0433, 8.7873, 9.6653] +24-11-19 18:48:02 | D | best error = [ 0.7799, 0.7799, 0.7799, 0.7799, 0.7799] +24-11-19 18:48:02 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:48:02 | D | sum error = [ 10.5201, 11.4888, 12.6537, 13.7510, 14.9966] +24-11-19 18:48:02 | D | best error = [ 0.7799, 0.7799, 0.7799, 0.7799, 0.7799] +24-11-19 18:48:02 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:48:02 | D | sum error = [ 16.4523, 17.9469, 19.5581, 21.3401, 23.2940] +24-11-19 18:48:02 | D | best error = [ 0.7799, 0.7799, 0.7799, 0.7799, 0.7799] +24-11-19 18:48:02 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:48:02 | D | sum error = [ 25.4143, 27.7114, 30.2351, 33.0766, 36.0457] +24-11-19 18:48:02 | D | best error = [ 0.7799, 0.7799, 0.7799, 0.7799, 0.7799] +24-11-19 18:48:02 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:48:02 | D | sum error = [ 39.2941, 42.8190, 46.6830, 50.9319, 55.5417] +24-11-19 18:48:02 | D | best error = [ 0.7799, 0.7799, 0.7799, 0.7799, 0.7799] +24-11-19 18:48:02 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:48:02 | D | sum error = [ 60.4591, 65.8111, 71.6724, 78.0926, 85.0026] +24-11-19 18:48:02 | D | best error = [ 0.7799, 0.7799, 0.7799, 0.7799, 0.7799] +24-11-19 18:48:02 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:48:02 | D | sum error = [ 92.3389, 100.5416, 109.3045, 118.7961, 128.9879] +24-11-19 18:48:02 | D | best error = [ 0.7799, 0.7799, 0.7799, 0.7799, 0.7799] +24-11-19 18:48:02 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:48:02 | D | sum error = [ 140.0009, 151.9112, 164.7315, 178.5680, 193.4107] +24-11-19 18:48:02 | D | best error = [ 0.7799, 0.7799, 0.7799, 0.7799, 0.7799] +24-11-19 18:48:02 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:48:02 | D | sum error = [ 209.2949, 226.5625, 245.0492, 264.8945, 286.4684] +24-11-19 18:48:02 | D | best error = [ 0.7799, 0.7799, 0.7799, 0.7799, 0.7799] +24-11-19 18:48:02 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:48:02 | D | sum error = [ 309.5795, 334.4103, 360.9391, 389.0870, 419.0588] +24-11-19 18:48:02 | D | best error = [ 0.7799, 0.7799, 0.7799, 0.7799, 0.7799] +24-11-19 18:48:02 | D | + error = [0.7799] +24-11-19 18:48:03 | D | - Calibrating model.layers.2.self_attn.k_proj.weight +24-11-19 18:48:03 | D | + w: sint8 +24-11-19 18:48:03 | D | + x: None +24-11-19 18:48:03 | D | + y: None +24-11-19 18:48:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:48:03 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:48:03 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:48:03 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:48:03 | D | - range ratio = [ 1.0000] +24-11-19 18:48:03 | D | sum error = [ 1.0426] +24-11-19 18:48:03 | D | best error = [ 1.0426] +24-11-19 18:48:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:48:15 | D | sum error = [ 0.9297, 0.9455, 0.8374, 1.0698, 1.0896] +24-11-19 18:48:15 | D | best error = [ 0.9297, 0.9297, 0.8374, 0.8374, 0.8374] +24-11-19 18:48:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:48:15 | D | sum error = [ 1.0907, 0.9775, 1.1896, 1.0759, 1.2531] +24-11-19 18:48:15 | D | best error = [ 0.8374, 0.8374, 0.8374, 0.8374, 0.8374] +24-11-19 18:48:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:48:15 | D | sum error = [ 1.1689, 1.3007, 1.5391, 1.7668, 1.8947] +24-11-19 18:48:15 | D | best error = [ 0.8374, 0.8374, 0.8374, 0.8374, 0.8374] +24-11-19 18:48:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:48:15 | D | sum error = [ 1.8366, 2.1183, 2.3954, 2.4673, 2.5685] +24-11-19 18:48:15 | D | best error = [ 0.8374, 0.8374, 0.8374, 0.8374, 0.8374] +24-11-19 18:48:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:48:15 | D | sum error = [ 2.8108, 3.0239, 3.3426, 3.4736, 3.9054] +24-11-19 18:48:15 | D | best error = [ 0.8374, 0.8374, 0.8374, 0.8374, 0.8374] +24-11-19 18:48:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:48:15 | D | sum error = [ 4.2091, 4.4858, 4.8163, 5.3162, 5.7647] +24-11-19 18:48:15 | D | best error = [ 0.8374, 0.8374, 0.8374, 0.8374, 0.8374] +24-11-19 18:48:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:48:15 | D | sum error = [ 6.5831, 7.0530, 7.5232, 8.2321, 9.1064] +24-11-19 18:48:15 | D | best error = [ 0.8374, 0.8374, 0.8374, 0.8374, 0.8374] +24-11-19 18:48:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:48:15 | D | sum error = [ 10.1768, 11.0331, 11.8799, 13.0729, 14.2310] +24-11-19 18:48:15 | D | best error = [ 0.8374, 0.8374, 0.8374, 0.8374, 0.8374] +24-11-19 18:48:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:48:15 | D | sum error = [ 15.3785, 16.9128, 18.6032, 20.2856, 22.0268] +24-11-19 18:48:15 | D | best error = [ 0.8374, 0.8374, 0.8374, 0.8374, 0.8374] +24-11-19 18:48:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:48:15 | D | sum error = [ 24.4833, 26.7527, 29.7930, 31.9254, 34.5385] +24-11-19 18:48:15 | D | best error = [ 0.8374, 0.8374, 0.8374, 0.8374, 0.8374] +24-11-19 18:48:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:48:15 | D | sum error = [ 37.8659, 41.7956, 45.2164, 49.7488, 54.5230] +24-11-19 18:48:15 | D | best error = [ 0.8374, 0.8374, 0.8374, 0.8374, 0.8374] +24-11-19 18:48:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:48:15 | D | sum error = [ 57.7041, 64.0814, 69.8846, 77.3744, 82.2563] +24-11-19 18:48:15 | D | best error = [ 0.8374, 0.8374, 0.8374, 0.8374, 0.8374] +24-11-19 18:48:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:48:15 | D | sum error = [ 89.9416, 98.5133, 107.1170, 115.6278, 126.4247] +24-11-19 18:48:15 | D | best error = [ 0.8374, 0.8374, 0.8374, 0.8374, 0.8374] +24-11-19 18:48:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:48:15 | D | sum error = [ 138.7820, 151.7107, 163.2626, 175.9941, 193.8172] +24-11-19 18:48:15 | D | best error = [ 0.8374, 0.8374, 0.8374, 0.8374, 0.8374] +24-11-19 18:48:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:48:15 | D | sum error = [ 209.9457, 226.8088, 246.6081, 267.3023, 292.8066] +24-11-19 18:48:15 | D | best error = [ 0.8374, 0.8374, 0.8374, 0.8374, 0.8374] +24-11-19 18:48:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:48:15 | D | sum error = [ 313.9391, 342.9074, 368.0371, 395.8599, 427.3318] +24-11-19 18:48:15 | D | best error = [ 0.8374, 0.8374, 0.8374, 0.8374, 0.8374] +24-11-19 18:48:15 | D | + error = [0.8374] +24-11-19 18:48:15 | D | - Calibrating model.layers.2.self_attn.v_proj.weight +24-11-19 18:48:15 | D | + w: sint8 +24-11-19 18:48:15 | D | + x: None +24-11-19 18:48:15 | D | + y: None +24-11-19 18:48:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:48:15 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:48:15 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:48:15 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:48:15 | D | - range ratio = [ 1.0000] +24-11-19 18:48:15 | D | sum error = [ 0.8205] +24-11-19 18:48:15 | D | best error = [ 0.8205] +24-11-19 18:48:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:48:15 | D | sum error = [ 0.8166, 0.8109, 0.8089, 0.8218, 0.8328] +24-11-19 18:48:15 | D | best error = [ 0.7553, 0.7305, 0.7184, 0.7126, 0.7094] +24-11-19 18:48:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:48:15 | D | sum error = [ 0.8653, 0.8976, 0.9325, 0.9728, 1.0204] +24-11-19 18:48:15 | D | best error = [ 0.7072, 0.7067, 0.7066, 0.7066, 0.7065] +24-11-19 18:48:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:48:15 | D | sum error = [ 1.0814, 1.1516, 1.2346, 1.3097, 1.4000] +24-11-19 18:48:15 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 18:48:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:48:15 | D | sum error = [ 1.5128, 1.6153, 1.7231, 1.8517, 1.9805] +24-11-19 18:48:15 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 18:48:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:48:15 | D | sum error = [ 2.1150, 2.2709, 2.4384, 2.6099, 2.7959] +24-11-19 18:48:15 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 18:48:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:48:15 | D | sum error = [ 2.9916, 3.2027, 3.4188, 3.6549, 3.8907] +24-11-19 18:48:15 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 18:48:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:48:15 | D | sum error = [ 4.1589, 4.4351, 4.7180, 5.0183, 5.3427] +24-11-19 18:48:15 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 18:48:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:48:15 | D | sum error = [ 5.6892, 6.0510, 6.4313, 6.8304, 7.2528] +24-11-19 18:48:15 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 18:48:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:48:15 | D | sum error = [ 7.6969, 8.1623, 8.6491, 9.1593, 9.6983] +24-11-19 18:48:15 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 18:48:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:48:15 | D | sum error = [ 10.2620, 10.8530, 11.4770, 12.1217, 12.7997] +24-11-19 18:48:15 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 18:48:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:48:15 | D | sum error = [ 13.5131, 14.2653, 15.0476, 15.8720, 16.7312] +24-11-19 18:48:15 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 18:48:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:48:15 | D | sum error = [ 17.6222, 18.5602, 19.5330, 20.5604, 21.6281] +24-11-19 18:48:15 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 18:48:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:48:15 | D | sum error = [ 22.7467, 23.9115, 25.1174, 26.3842, 27.6976] +24-11-19 18:48:15 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 18:48:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:48:15 | D | sum error = [ 29.0596, 30.4782, 31.9561, 33.4868, 35.0699] +24-11-19 18:48:15 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 18:48:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:48:15 | D | sum error = [ 36.7136, 38.4198, 40.1865, 42.0148, 43.9057] +24-11-19 18:48:15 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 18:48:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:48:15 | D | sum error = [ 45.8631, 47.8863, 49.9769, 52.1390, 54.3618] +24-11-19 18:48:15 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 18:48:15 | D | + error = [0.7065] +24-11-19 18:48:15 | D | - Calibrating model.layers.2.self_attn.o_proj.weight +24-11-19 18:48:15 | D | + w: sint8 +24-11-19 18:48:15 | D | + x: None +24-11-19 18:48:15 | D | + y: None +24-11-19 18:48:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:48:15 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:48:15 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:48:15 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:48:15 | D | - range ratio = [ 1.0000] +24-11-19 18:48:15 | D | sum error = [ 0.1002] +24-11-19 18:48:15 | D | best error = [ 0.1002] +24-11-19 18:48:16 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:48:16 | D | sum error = [ 0.0992, 0.0991, 0.1001, 0.1004, 0.1026] +24-11-19 18:48:16 | D | best error = [ 0.0890, 0.0846, 0.0822, 0.0806, 0.0797] +24-11-19 18:48:16 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:48:16 | D | sum error = [ 0.1048, 0.1082, 0.1122, 0.1169, 0.1233] +24-11-19 18:48:16 | D | best error = [ 0.0790, 0.0786, 0.0783, 0.0781, 0.0780] +24-11-19 18:48:16 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:48:16 | D | sum error = [ 0.1288, 0.1373, 0.1450, 0.1545, 0.1648] +24-11-19 18:48:16 | D | best error = [ 0.0780, 0.0779, 0.0779, 0.0778, 0.0778] +24-11-19 18:48:16 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:48:16 | D | sum error = [ 0.1759, 0.1872, 0.1997, 0.2131, 0.2281] +24-11-19 18:48:16 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 18:48:16 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:48:16 | D | sum error = [ 0.2434, 0.2598, 0.2767, 0.2957, 0.3145] +24-11-19 18:48:16 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 18:48:16 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:48:16 | D | sum error = [ 0.3351, 0.3569, 0.3797, 0.4039, 0.4310] +24-11-19 18:48:16 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 18:48:16 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:48:16 | D | sum error = [ 0.4577, 0.4860, 0.5156, 0.5474, 0.5809] +24-11-19 18:48:16 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 18:48:16 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:48:16 | D | sum error = [ 0.6154, 0.6525, 0.6915, 0.7328, 0.7752] +24-11-19 18:48:16 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 18:48:16 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:48:16 | D | sum error = [ 0.8208, 0.8675, 0.9184, 0.9711, 1.0260] +24-11-19 18:48:16 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 18:48:16 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:48:16 | D | sum error = [ 1.0843, 1.1459, 1.2097, 1.2769, 1.3476] +24-11-19 18:48:16 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 18:48:16 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:48:16 | D | sum error = [ 1.4208, 1.4989, 1.5797, 1.6651, 1.7541] +24-11-19 18:48:16 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 18:48:16 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:48:16 | D | sum error = [ 1.8478, 1.9454, 2.0481, 2.1552, 2.2673] +24-11-19 18:48:16 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 18:48:16 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:48:16 | D | sum error = [ 2.3841, 2.5066, 2.6348, 2.7691, 2.9084] +24-11-19 18:48:16 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 18:48:16 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:48:16 | D | sum error = [ 3.0548, 3.2072, 3.3670, 3.5327, 3.7055] +24-11-19 18:48:16 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 18:48:16 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:48:16 | D | sum error = [ 3.8850, 4.0720, 4.2668, 4.4692, 4.6799] +24-11-19 18:48:16 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 18:48:16 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:48:16 | D | sum error = [ 4.8981, 5.1250, 5.3604, 5.6050, 5.8589] +24-11-19 18:48:16 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 18:48:16 | D | + error = [0.0778] +24-11-19 18:48:16 | D | - Calibrating model.layers.2.mlp.up_proj.weight +24-11-19 18:48:16 | D | + w: sint8 +24-11-19 18:48:16 | D | + x: None +24-11-19 18:48:16 | D | + y: None +24-11-19 18:48:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:48:16 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:48:16 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:48:16 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:48:16 | D | - range ratio = [ 1.0000] +24-11-19 18:48:16 | D | sum error = [ 3.5337] +24-11-19 18:48:16 | D | best error = [ 3.5337] +24-11-19 18:48:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:48:17 | D | sum error = [ 3.5089, 3.5032, 3.5199, 3.5563, 3.6225] +24-11-19 18:48:17 | D | best error = [ 3.2474, 3.1425, 3.0916, 3.0633, 3.0486] +24-11-19 18:48:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:48:17 | D | sum error = [ 3.7037, 3.8343, 3.9768, 4.1717, 4.3847] +24-11-19 18:48:17 | D | best error = [ 3.0412, 3.0384, 3.0374, 3.0371, 3.0370] +24-11-19 18:48:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:48:17 | D | sum error = [ 4.6433, 4.9324, 5.2461, 5.5985, 5.9849] +24-11-19 18:48:17 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 18:48:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:48:17 | D | sum error = [ 6.4008, 6.8539, 7.3394, 7.8677, 8.4220] +24-11-19 18:48:17 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 18:48:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:48:17 | D | sum error = [ 9.0258, 9.6695, 10.3381, 11.0431, 11.8103] +24-11-19 18:48:17 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 18:48:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:48:17 | D | sum error = [ 12.6105, 13.4655, 14.3594, 15.3058, 16.2943] +24-11-19 18:48:17 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 18:48:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:48:17 | D | sum error = [ 17.3484, 18.4572, 19.6120, 20.8389, 22.1252] +24-11-19 18:48:17 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 18:48:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:48:17 | D | sum error = [ 23.4742, 24.8924, 26.3867, 27.9375, 29.5722] +24-11-19 18:48:17 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 18:48:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:48:17 | D | sum error = [ 31.2823, 33.0531, 34.9261, 36.8739, 38.8967] +24-11-19 18:48:17 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 18:48:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:48:17 | D | sum error = [ 41.0085, 43.2169, 45.5107, 47.8899, 50.3836] +24-11-19 18:48:17 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 18:48:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:48:17 | D | sum error = [ 52.9506, 55.6317, 58.4028, 61.2821, 64.2637] +24-11-19 18:48:17 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 18:48:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:48:17 | D | sum error = [ 67.3503, 70.5509, 73.8494, 77.2642, 80.7885] +24-11-19 18:48:17 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 18:48:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:48:17 | D | sum error = [ 84.4279, 88.1788, 92.0527, 96.0416, 100.1533] +24-11-19 18:48:17 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 18:48:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:48:17 | D | sum error = [ 104.3754, 108.7304, 113.1857, 117.7816, 122.4812] +24-11-19 18:48:17 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 18:48:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:48:17 | D | sum error = [ 127.3143, 132.2702, 137.3482, 142.5575, 147.8891] +24-11-19 18:48:17 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 18:48:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:48:17 | D | sum error = [ 153.3612, 158.9580, 164.7023, 170.5794, 176.6045] +24-11-19 18:48:17 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 18:48:17 | D | + error = [3.0370] +24-11-19 18:48:17 | D | - Calibrating model.layers.2.mlp.gate_proj.weight +24-11-19 18:48:17 | D | + w: sint8 +24-11-19 18:48:17 | D | + x: None +24-11-19 18:48:17 | D | + y: None +24-11-19 18:48:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:48:17 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:48:17 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:48:18 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:48:18 | D | - range ratio = [ 1.0000] +24-11-19 18:48:18 | D | sum error = [ 3.9980] +24-11-19 18:48:18 | D | best error = [ 3.9980] +24-11-19 18:48:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:48:19 | D | sum error = [ 3.9786, 3.9603, 3.9846, 4.0198, 4.0982] +24-11-19 18:48:19 | D | best error = [ 3.6791, 3.5607, 3.5039, 3.4719, 3.4547] +24-11-19 18:48:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:48:19 | D | sum error = [ 4.2017, 4.3490, 4.5203, 4.7271, 4.9827] +24-11-19 18:48:19 | D | best error = [ 3.4469, 3.4437, 3.4427, 3.4424, 3.4424] +24-11-19 18:48:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:48:19 | D | sum error = [ 5.2611, 5.5997, 5.9432, 6.3509, 6.7835] +24-11-19 18:48:19 | D | best error = [ 3.4424, 3.4424, 3.4424, 3.4424, 3.4424] +24-11-19 18:48:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:48:19 | D | sum error = [ 7.2726, 7.7934, 8.3510, 8.9396, 9.5742] +24-11-19 18:48:19 | D | best error = [ 3.4424, 3.4424, 3.4424, 3.4424, 3.4424] +24-11-19 18:48:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:48:19 | D | sum error = [ 10.2557, 10.9924, 11.7530, 12.5645, 13.4402] +24-11-19 18:48:19 | D | best error = [ 3.4424, 3.4424, 3.4424, 3.4424, 3.4424] +24-11-19 18:48:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:48:19 | D | sum error = [ 14.3533, 15.3234, 16.3636, 17.4521, 18.5963] +24-11-19 18:48:19 | D | best error = [ 3.4424, 3.4424, 3.4424, 3.4424, 3.4424] +24-11-19 18:48:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:48:19 | D | sum error = [ 19.8088, 21.0840, 22.4182, 23.8392, 25.3311] +24-11-19 18:48:19 | D | best error = [ 3.4424, 3.4424, 3.4424, 3.4424, 3.4424] +24-11-19 18:48:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:48:19 | D | sum error = [ 26.9097, 28.5593, 30.2878, 32.1126, 34.0179] +24-11-19 18:48:19 | D | best error = [ 3.4424, 3.4424, 3.4424, 3.4424, 3.4424] +24-11-19 18:48:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:48:19 | D | sum error = [ 36.0199, 38.1137, 40.3158, 42.6219, 45.0295] +24-11-19 18:48:19 | D | best error = [ 3.4424, 3.4424, 3.4424, 3.4424, 3.4424] +24-11-19 18:48:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:48:19 | D | sum error = [ 47.5567, 50.2097, 52.9696, 55.8776, 58.8923] +24-11-19 18:48:19 | D | best error = [ 3.4424, 3.4424, 3.4424, 3.4424, 3.4424] +24-11-19 18:48:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:48:19 | D | sum error = [ 62.0533, 65.3524, 68.7917, 72.3745, 76.0953] +24-11-19 18:48:19 | D | best error = [ 3.4424, 3.4424, 3.4424, 3.4424, 3.4424] +24-11-19 18:48:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:48:19 | D | sum error = [ 79.9831, 84.0263, 88.2231, 92.5850, 97.1228] +24-11-19 18:48:19 | D | best error = [ 3.4424, 3.4424, 3.4424, 3.4424, 3.4424] +24-11-19 18:48:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:48:19 | D | sum error = [ 101.8324, 106.7275, 111.7992, 117.0725, 122.5205] +24-11-19 18:48:19 | D | best error = [ 3.4424, 3.4424, 3.4424, 3.4424, 3.4424] +24-11-19 18:48:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:48:19 | D | sum error = [ 128.1648, 134.0268, 140.0554, 146.3135, 152.7692] +24-11-19 18:48:19 | D | best error = [ 3.4424, 3.4424, 3.4424, 3.4424, 3.4424] +24-11-19 18:48:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:48:19 | D | sum error = [ 159.4398, 166.3244, 173.4319, 180.7560, 188.3028] +24-11-19 18:48:19 | D | best error = [ 3.4424, 3.4424, 3.4424, 3.4424, 3.4424] +24-11-19 18:48:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:48:19 | D | sum error = [ 196.0696, 204.0770, 212.3093, 220.7742, 229.4770] +24-11-19 18:48:19 | D | best error = [ 3.4424, 3.4424, 3.4424, 3.4424, 3.4424] +24-11-19 18:48:19 | D | + error = [3.4424] +24-11-19 18:48:19 | D | - Calibrating model.layers.2.mlp.down_proj.weight +24-11-19 18:48:19 | D | + w: sint8 +24-11-19 18:48:19 | D | + x: None +24-11-19 18:48:19 | D | + y: None +24-11-19 18:48:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:48:19 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:48:19 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:48:19 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:48:19 | D | - range ratio = [ 1.0000] +24-11-19 18:48:19 | D | sum error = [ 0.2097] +24-11-19 18:48:19 | D | best error = [ 0.2097] +24-11-19 18:48:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:48:20 | D | sum error = [ 0.2077, 0.2059, 0.2046, 0.2036, 0.2034] +24-11-19 18:48:20 | D | best error = [ 0.2027, 0.1990, 0.1964, 0.1945, 0.1930] +24-11-19 18:48:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:48:20 | D | sum error = [ 0.2029, 0.2035, 0.2046, 0.2068, 0.2094] +24-11-19 18:48:20 | D | best error = [ 0.1916, 0.1905, 0.1896, 0.1889, 0.1884] +24-11-19 18:48:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:48:20 | D | sum error = [ 0.2133, 0.2179, 0.2240, 0.2308, 0.2392] +24-11-19 18:48:20 | D | best error = [ 0.1880, 0.1878, 0.1876, 0.1874, 0.1873] +24-11-19 18:48:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:48:20 | D | sum error = [ 0.2496, 0.2608, 0.2740, 0.2886, 0.3048] +24-11-19 18:48:20 | D | best error = [ 0.1872, 0.1872, 0.1871, 0.1871, 0.1871] +24-11-19 18:48:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:48:20 | D | sum error = [ 0.3229, 0.3431, 0.3651, 0.3891, 0.4153] +24-11-19 18:48:20 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 18:48:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:48:20 | D | sum error = [ 0.4439, 0.4744, 0.5074, 0.5433, 0.5813] +24-11-19 18:48:20 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 18:48:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:48:20 | D | sum error = [ 0.6226, 0.6662, 0.7134, 0.7634, 0.8170] +24-11-19 18:48:20 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 18:48:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:48:20 | D | sum error = [ 0.8739, 0.9347, 0.9994, 1.0678, 1.1406] +24-11-19 18:48:20 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 18:48:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:48:20 | D | sum error = [ 1.2180, 1.2998, 1.3866, 1.4784, 1.5758] +24-11-19 18:48:20 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 18:48:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:48:20 | D | sum error = [ 1.6789, 1.7876, 1.9025, 2.0236, 2.1516] +24-11-19 18:48:20 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 18:48:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:48:20 | D | sum error = [ 2.2862, 2.4284, 2.5776, 2.7348, 2.9003] +24-11-19 18:48:20 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 18:48:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:48:20 | D | sum error = [ 3.0740, 3.2563, 3.4476, 3.6480, 3.8589] +24-11-19 18:48:20 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 18:48:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:48:20 | D | sum error = [ 4.0792, 4.3101, 4.5521, 4.8053, 5.0701] +24-11-19 18:48:20 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 18:48:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:48:20 | D | sum error = [ 5.3471, 5.6362, 5.9380, 6.2532, 6.5808] +24-11-19 18:48:20 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 18:48:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:48:20 | D | sum error = [ 6.9224, 7.2777, 7.6475, 8.0317, 8.4307] +24-11-19 18:48:20 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 18:48:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:48:20 | D | sum error = [ 8.8447, 9.2737, 9.7181, 10.1777, 10.6534] +24-11-19 18:48:20 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 18:48:20 | D | + error = [0.1871] +24-11-19 18:48:20 | D | - Quantizing model.layers.2.self_attn.q_proj.weight +24-11-19 18:48:21 | D | - Quantizing model.layers.2.self_attn.k_proj.weight +24-11-19 18:48:22 | D | - Quantizing model.layers.2.self_attn.v_proj.weight +24-11-19 18:48:23 | D | - Quantizing model.layers.2.self_attn.o_proj.weight +24-11-19 18:48:23 | D | - Quantizing model.layers.2.mlp.up_proj.weight +24-11-19 18:48:24 | D | - Quantizing model.layers.2.mlp.gate_proj.weight +24-11-19 18:48:25 | D | - Quantizing model.layers.2.mlp.down_proj.weight +24-11-19 18:48:35 | D | - Quantizing layer model.layers.3 +24-11-19 18:48:35 | D | - Calibrating model.layers.3.self_attn.q_proj.weight +24-11-19 18:48:35 | D | + w: sint8 +24-11-19 18:48:35 | D | + x: None +24-11-19 18:48:35 | D | + y: None +24-11-19 18:48:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:48:35 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:48:35 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:48:35 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:48:35 | D | - range ratio = [ 1.0000] +24-11-19 18:48:35 | D | sum error = [ 1.1027] +24-11-19 18:48:35 | D | best error = [ 1.1027] +24-11-19 18:48:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:48:47 | D | sum error = [ 1.0952, 1.0850, 1.0849, 1.1123, 1.1382] +24-11-19 18:48:47 | D | best error = [ 1.0952, 1.0850, 1.0849, 1.0849, 1.0849] +24-11-19 18:48:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:48:47 | D | sum error = [ 1.1429, 1.2442, 1.2863, 1.3849, 1.4816] +24-11-19 18:48:47 | D | best error = [ 1.0849, 1.0849, 1.0849, 1.0849, 1.0849] +24-11-19 18:48:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:48:47 | D | sum error = [ 1.6279, 1.6922, 1.9386, 2.1103, 2.2847] +24-11-19 18:48:47 | D | best error = [ 1.0849, 1.0849, 1.0849, 1.0849, 1.0849] +24-11-19 18:48:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:48:47 | D | sum error = [ 2.5188, 2.8200, 3.1229, 3.5049, 3.8024] +24-11-19 18:48:47 | D | best error = [ 1.0849, 1.0849, 1.0849, 1.0849, 1.0849] +24-11-19 18:48:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:48:47 | D | sum error = [ 4.2974, 4.6188, 5.1609, 5.7187, 6.4265] +24-11-19 18:48:47 | D | best error = [ 1.0849, 1.0849, 1.0849, 1.0849, 1.0849] +24-11-19 18:48:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:48:47 | D | sum error = [ 7.0759, 7.8105, 8.6081, 9.5726, 10.4739] +24-11-19 18:48:47 | D | best error = [ 1.0849, 1.0849, 1.0849, 1.0849, 1.0849] +24-11-19 18:48:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:48:47 | D | sum error = [ 11.4927, 12.6517, 13.9464, 15.4556, 16.9147] +24-11-19 18:48:47 | D | best error = [ 1.0849, 1.0849, 1.0849, 1.0849, 1.0849] +24-11-19 18:48:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:48:47 | D | sum error = [ 18.6812, 20.5860, 22.5187, 24.8258, 27.2160] +24-11-19 18:48:47 | D | best error = [ 1.0849, 1.0849, 1.0849, 1.0849, 1.0849] +24-11-19 18:48:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:48:47 | D | sum error = [ 29.9532, 32.8830, 35.9509, 39.4100, 43.0538] +24-11-19 18:48:47 | D | best error = [ 1.0849, 1.0849, 1.0849, 1.0849, 1.0849] +24-11-19 18:48:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:48:47 | D | sum error = [ 46.9612, 51.2011, 55.7279, 60.6476, 65.9234] +24-11-19 18:48:47 | D | best error = [ 1.0849, 1.0849, 1.0849, 1.0849, 1.0849] +24-11-19 18:48:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:48:47 | D | sum error = [ 71.6340, 77.7097, 84.3183, 91.1999, 98.5852] +24-11-19 18:48:47 | D | best error = [ 1.0849, 1.0849, 1.0849, 1.0849, 1.0849] +24-11-19 18:48:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:48:47 | D | sum error = [ 106.7158, 115.3769, 124.5292, 134.5562, 145.2751] +24-11-19 18:48:47 | D | best error = [ 1.0849, 1.0849, 1.0849, 1.0849, 1.0849] +24-11-19 18:48:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:48:47 | D | sum error = [ 156.5921, 168.5082, 181.3592, 195.1467, 209.7081] +24-11-19 18:48:47 | D | best error = [ 1.0849, 1.0849, 1.0849, 1.0849, 1.0849] +24-11-19 18:48:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:48:47 | D | sum error = [ 225.0032, 241.4940, 258.8469, 277.2865, 296.7499] +24-11-19 18:48:47 | D | best error = [ 1.0849, 1.0849, 1.0849, 1.0849, 1.0849] +24-11-19 18:48:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:48:47 | D | sum error = [ 317.4827, 338.9449, 361.5810, 384.9970, 409.3185] +24-11-19 18:48:47 | D | best error = [ 1.0849, 1.0849, 1.0849, 1.0849, 1.0849] +24-11-19 18:48:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:48:47 | D | sum error = [ 434.3921, 460.0406, 486.0892, 512.3652, 539.0823] +24-11-19 18:48:47 | D | best error = [ 1.0849, 1.0849, 1.0849, 1.0849, 1.0849] +24-11-19 18:48:47 | D | + error = [1.0849] +24-11-19 18:48:47 | D | - Calibrating model.layers.3.self_attn.k_proj.weight +24-11-19 18:48:47 | D | + w: sint8 +24-11-19 18:48:47 | D | + x: None +24-11-19 18:48:47 | D | + y: None +24-11-19 18:48:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:48:47 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:48:47 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:48:47 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:48:48 | D | - range ratio = [ 1.0000] +24-11-19 18:48:48 | D | sum error = [ 1.3016] +24-11-19 18:48:48 | D | best error = [ 1.3016] +24-11-19 18:48:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:48:59 | D | sum error = [ 1.2757, 1.2997, 1.3490, 1.2540, 1.2290] +24-11-19 18:48:59 | D | best error = [ 1.2757, 1.2757, 1.2757, 1.2540, 1.2290] +24-11-19 18:48:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:48:59 | D | sum error = [ 1.4142, 1.4771, 1.4951, 1.6186, 1.6498] +24-11-19 18:48:59 | D | best error = [ 1.2290, 1.2290, 1.2290, 1.2290, 1.2290] +24-11-19 18:48:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:48:59 | D | sum error = [ 1.7214, 2.1662, 2.3012, 2.5442, 2.6864] +24-11-19 18:48:59 | D | best error = [ 1.2290, 1.2290, 1.2290, 1.2290, 1.2290] +24-11-19 18:48:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:48:59 | D | sum error = [ 3.1714, 3.5700, 3.7745, 4.1473, 4.4361] +24-11-19 18:48:59 | D | best error = [ 1.2290, 1.2290, 1.2290, 1.2290, 1.2290] +24-11-19 18:48:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:48:59 | D | sum error = [ 5.0447, 5.7634, 6.2063, 6.7244, 7.4469] +24-11-19 18:48:59 | D | best error = [ 1.2290, 1.2290, 1.2290, 1.2290, 1.2290] +24-11-19 18:48:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:48:59 | D | sum error = [ 8.0979, 8.6414, 9.5315, 10.2296, 11.5162] +24-11-19 18:48:59 | D | best error = [ 1.2290, 1.2290, 1.2290, 1.2290, 1.2290] +24-11-19 18:48:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:48:59 | D | sum error = [ 12.6014, 13.4620, 15.0335, 16.5685, 18.3154] +24-11-19 18:48:59 | D | best error = [ 1.2290, 1.2290, 1.2290, 1.2290, 1.2290] +24-11-19 18:48:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:48:59 | D | sum error = [ 19.9014, 21.3793, 23.5459, 25.7096, 28.0573] +24-11-19 18:48:59 | D | best error = [ 1.2290, 1.2290, 1.2290, 1.2290, 1.2290] +24-11-19 18:48:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:48:59 | D | sum error = [ 31.1638, 33.5268, 36.3238, 39.9736, 43.2629] +24-11-19 18:48:59 | D | best error = [ 1.2290, 1.2290, 1.2290, 1.2290, 1.2290] +24-11-19 18:48:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:48:59 | D | sum error = [ 47.8118, 52.5263, 56.6963, 61.8475, 68.0917] +24-11-19 18:48:59 | D | best error = [ 1.2290, 1.2290, 1.2290, 1.2290, 1.2290] +24-11-19 18:48:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:48:59 | D | sum error = [ 73.2797, 80.6862, 87.7632, 96.8248, 103.2527] +24-11-19 18:48:59 | D | best error = [ 1.2290, 1.2290, 1.2290, 1.2290, 1.2290] +24-11-19 18:48:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:48:59 | D | sum error = [ 113.1271, 123.9572, 132.6762, 144.4913, 158.3413] +24-11-19 18:48:59 | D | best error = [ 1.2290, 1.2290, 1.2290, 1.2290, 1.2290] +24-11-19 18:48:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:48:59 | D | sum error = [ 167.8307, 182.9578, 195.2656, 210.0420, 227.0480] +24-11-19 18:48:59 | D | best error = [ 1.2290, 1.2290, 1.2290, 1.2290, 1.2290] +24-11-19 18:48:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:48:59 | D | sum error = [ 245.4828, 261.7707, 279.5105, 299.4093, 320.9242] +24-11-19 18:48:59 | D | best error = [ 1.2290, 1.2290, 1.2290, 1.2290, 1.2290] +24-11-19 18:48:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:48:59 | D | sum error = [ 344.5161, 371.1920, 391.2953, 413.0704, 441.7831] +24-11-19 18:48:59 | D | best error = [ 1.2290, 1.2290, 1.2290, 1.2290, 1.2290] +24-11-19 18:48:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:48:59 | D | sum error = [ 468.4740, 495.9897, 520.4383, 544.3620, 570.6186] +24-11-19 18:48:59 | D | best error = [ 1.2290, 1.2290, 1.2290, 1.2290, 1.2290] +24-11-19 18:48:59 | D | + error = [1.2290] +24-11-19 18:48:59 | D | - Calibrating model.layers.3.self_attn.v_proj.weight +24-11-19 18:48:59 | D | + w: sint8 +24-11-19 18:48:59 | D | + x: None +24-11-19 18:48:59 | D | + y: None +24-11-19 18:48:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:48:59 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:48:59 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:48:59 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:48:59 | D | - range ratio = [ 1.0000] +24-11-19 18:48:59 | D | sum error = [ 1.1201] +24-11-19 18:48:59 | D | best error = [ 1.1201] +24-11-19 18:49:00 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:49:00 | D | sum error = [ 1.1038, 1.1016, 1.1164, 1.1283, 1.1469] +24-11-19 18:49:00 | D | best error = [ 1.0294, 0.9987, 0.9838, 0.9764, 0.9715] +24-11-19 18:49:00 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:49:00 | D | sum error = [ 1.1881, 1.2075, 1.2721, 1.3148, 1.3861] +24-11-19 18:49:00 | D | best error = [ 0.9689, 0.9682, 0.9676, 0.9675, 0.9675] +24-11-19 18:49:00 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:49:00 | D | sum error = [ 1.4581, 1.5489, 1.6522, 1.7699, 1.8787] +24-11-19 18:49:00 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 18:49:00 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:49:00 | D | sum error = [ 2.0078, 2.1547, 2.2972, 2.4628, 2.6344] +24-11-19 18:49:00 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 18:49:00 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:49:00 | D | sum error = [ 2.8179, 3.0160, 3.2291, 3.4557, 3.6961] +24-11-19 18:49:00 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 18:49:00 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:49:00 | D | sum error = [ 3.9542, 4.2225, 4.5091, 4.8164, 5.1365] +24-11-19 18:49:00 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 18:49:00 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:49:00 | D | sum error = [ 5.4757, 5.8410, 6.2142, 6.6093, 7.0352] +24-11-19 18:49:00 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 18:49:00 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:49:00 | D | sum error = [ 7.4762, 7.9477, 8.4231, 8.9330, 9.4623] +24-11-19 18:49:00 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 18:49:00 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:49:00 | D | sum error = [ 10.0352, 10.6159, 11.2390, 11.8919, 12.5845] +24-11-19 18:49:00 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 18:49:00 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:49:00 | D | sum error = [ 13.3005, 14.0561, 14.8525, 15.6792, 16.5375] +24-11-19 18:49:00 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 18:49:00 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:49:00 | D | sum error = [ 17.4495, 18.3952, 19.3821, 20.4121, 21.4902] +24-11-19 18:49:00 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 18:49:00 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:49:00 | D | sum error = [ 22.6145, 23.7927, 25.0133, 26.2966, 27.6234] +24-11-19 18:49:00 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 18:49:00 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:49:00 | D | sum error = [ 29.0141, 30.4528, 31.9530, 33.5151, 35.1378] +24-11-19 18:49:00 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 18:49:00 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:49:00 | D | sum error = [ 36.8227, 38.5734, 40.3789, 42.2525, 44.1977] +24-11-19 18:49:00 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 18:49:00 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:49:00 | D | sum error = [ 46.2040, 48.2850, 50.4313, 52.6451, 54.9222] +24-11-19 18:49:00 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 18:49:00 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:49:00 | D | sum error = [ 57.2729, 59.6950, 62.1825, 64.7455, 67.3940] +24-11-19 18:49:00 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 18:49:00 | D | + error = [0.9675] +24-11-19 18:49:00 | D | - Calibrating model.layers.3.self_attn.o_proj.weight +24-11-19 18:49:00 | D | + w: sint8 +24-11-19 18:49:00 | D | + x: None +24-11-19 18:49:00 | D | + y: None +24-11-19 18:49:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:49:00 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:49:00 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:49:00 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:49:00 | D | - range ratio = [ 1.0000] +24-11-19 18:49:00 | D | sum error = [ 0.1798] +24-11-19 18:49:00 | D | best error = [ 0.1798] +24-11-19 18:49:00 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:49:00 | D | sum error = [ 0.1783, 0.1778, 0.1777, 0.1781, 0.1803] +24-11-19 18:49:00 | D | best error = [ 0.1673, 0.1617, 0.1581, 0.1558, 0.1542] +24-11-19 18:49:00 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:49:00 | D | sum error = [ 0.1819, 0.1861, 0.1906, 0.1969, 0.2034] +24-11-19 18:49:00 | D | best error = [ 0.1530, 0.1522, 0.1517, 0.1513, 0.1511] +24-11-19 18:49:00 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:49:00 | D | sum error = [ 0.2122, 0.2227, 0.2331, 0.2460, 0.2596] +24-11-19 18:49:00 | D | best error = [ 0.1509, 0.1508, 0.1507, 0.1506, 0.1506] +24-11-19 18:49:00 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:49:00 | D | sum error = [ 0.2748, 0.2923, 0.3100, 0.3300, 0.3510] +24-11-19 18:49:00 | D | best error = [ 0.1505, 0.1505, 0.1505, 0.1505, 0.1505] +24-11-19 18:49:00 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:49:00 | D | sum error = [ 0.3739, 0.3982, 0.4252, 0.4533, 0.4832] +24-11-19 18:49:00 | D | best error = [ 0.1505, 0.1505, 0.1505, 0.1505, 0.1505] +24-11-19 18:49:00 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:49:00 | D | sum error = [ 0.5151, 0.5486, 0.5843, 0.6230, 0.6643] +24-11-19 18:49:00 | D | best error = [ 0.1505, 0.1505, 0.1505, 0.1505, 0.1505] +24-11-19 18:49:00 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:49:00 | D | sum error = [ 0.7066, 0.7526, 0.8002, 0.8511, 0.9047] +24-11-19 18:49:00 | D | best error = [ 0.1505, 0.1505, 0.1505, 0.1505, 0.1505] +24-11-19 18:49:00 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:49:00 | D | sum error = [ 0.9614, 1.0209, 1.0848, 1.1516, 1.2216] +24-11-19 18:49:00 | D | best error = [ 0.1505, 0.1505, 0.1505, 0.1505, 0.1505] +24-11-19 18:49:00 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:49:00 | D | sum error = [ 1.2951, 1.3730, 1.4555, 1.5425, 1.6335] +24-11-19 18:49:00 | D | best error = [ 0.1505, 0.1505, 0.1505, 0.1505, 0.1505] +24-11-19 18:49:00 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:49:00 | D | sum error = [ 1.7298, 1.8312, 1.9373, 2.0492, 2.1675] +24-11-19 18:49:00 | D | best error = [ 0.1505, 0.1505, 0.1505, 0.1505, 0.1505] +24-11-19 18:49:00 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:49:00 | D | sum error = [ 2.2902, 2.4206, 2.5570, 2.7001, 2.8501] +24-11-19 18:49:00 | D | best error = [ 0.1505, 0.1505, 0.1505, 0.1505, 0.1505] +24-11-19 18:49:00 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:49:00 | D | sum error = [ 3.0074, 3.1717, 3.3445, 3.5253, 3.7146] +24-11-19 18:49:00 | D | best error = [ 0.1505, 0.1505, 0.1505, 0.1505, 0.1505] +24-11-19 18:49:00 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:49:00 | D | sum error = [ 3.9122, 4.1194, 4.3361, 4.5616, 4.7973] +24-11-19 18:49:00 | D | best error = [ 0.1505, 0.1505, 0.1505, 0.1505, 0.1505] +24-11-19 18:49:00 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:49:00 | D | sum error = [ 5.0428, 5.2991, 5.5660, 5.8447, 6.1344] +24-11-19 18:49:00 | D | best error = [ 0.1505, 0.1505, 0.1505, 0.1505, 0.1505] +24-11-19 18:49:00 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:49:00 | D | sum error = [ 6.4368, 6.7508, 7.0774, 7.4168, 7.7690] +24-11-19 18:49:00 | D | best error = [ 0.1505, 0.1505, 0.1505, 0.1505, 0.1505] +24-11-19 18:49:00 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:49:00 | D | sum error = [ 8.1335, 8.5116, 8.9032, 9.3084, 9.7275] +24-11-19 18:49:00 | D | best error = [ 0.1505, 0.1505, 0.1505, 0.1505, 0.1505] +24-11-19 18:49:00 | D | + error = [0.1505] +24-11-19 18:49:00 | D | - Calibrating model.layers.3.mlp.up_proj.weight +24-11-19 18:49:00 | D | + w: sint8 +24-11-19 18:49:00 | D | + x: None +24-11-19 18:49:00 | D | + y: None +24-11-19 18:49:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:49:00 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:49:00 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:49:01 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:49:01 | D | - range ratio = [ 1.0000] +24-11-19 18:49:01 | D | sum error = [ 3.8858] +24-11-19 18:49:01 | D | best error = [ 3.8858] +24-11-19 18:49:02 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:49:02 | D | sum error = [ 3.8494, 3.8297, 3.8439, 3.9054, 3.9737] +24-11-19 18:49:02 | D | best error = [ 3.5704, 3.4571, 3.4000, 3.3709, 3.3551] +24-11-19 18:49:02 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:49:02 | D | sum error = [ 4.0746, 4.2113, 4.3825, 4.5749, 4.8264] +24-11-19 18:49:02 | D | best error = [ 3.3479, 3.3448, 3.3439, 3.3436, 3.3435] +24-11-19 18:49:02 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:49:02 | D | sum error = [ 5.1139, 5.4050, 5.7598, 6.1635, 6.5767] +24-11-19 18:49:02 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 18:49:02 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:49:02 | D | sum error = [ 7.0282, 7.5319, 8.0674, 8.6492, 9.2538] +24-11-19 18:49:02 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 18:49:02 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:49:02 | D | sum error = [ 9.9231, 10.6268, 11.3770, 12.1681, 12.9936] +24-11-19 18:49:02 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 18:49:02 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:49:02 | D | sum error = [ 13.8948, 14.8314, 15.8233, 16.8648, 17.9756] +24-11-19 18:49:02 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 18:49:02 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:49:02 | D | sum error = [ 19.1255, 20.3587, 21.6464, 23.0089, 24.4220] +24-11-19 18:49:02 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 18:49:02 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:49:02 | D | sum error = [ 25.9167, 27.5022, 29.1572, 30.8859, 32.7119] +24-11-19 18:49:02 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 18:49:02 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:49:02 | D | sum error = [ 34.6084, 36.5925, 38.6802, 40.8625, 43.1336] +24-11-19 18:49:02 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 18:49:02 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:49:02 | D | sum error = [ 45.5008, 47.9881, 50.5668, 53.2687, 56.0744] +24-11-19 18:49:02 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 18:49:02 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:49:02 | D | sum error = [ 58.9896, 62.0308, 65.2004, 68.4726, 71.8891] +24-11-19 18:49:02 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 18:49:02 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:49:02 | D | sum error = [ 75.4251, 79.0981, 82.8959, 86.8380, 90.9216] +24-11-19 18:49:02 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 18:49:02 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:49:02 | D | sum error = [ 95.1530, 99.5304, 104.0589, 108.7456, 113.5775] +24-11-19 18:49:02 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 18:49:02 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:49:02 | D | sum error = [ 118.5648, 123.7175, 129.0113, 134.4881, 140.1180] +24-11-19 18:49:02 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 18:49:02 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:49:02 | D | sum error = [ 145.9285, 151.9060, 158.0578, 164.3831, 170.8900] +24-11-19 18:49:02 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 18:49:02 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:49:02 | D | sum error = [ 177.5816, 184.4600, 191.5209, 198.7813, 206.2378] +24-11-19 18:49:02 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 18:49:02 | D | + error = [3.3435] +24-11-19 18:49:02 | D | - Calibrating model.layers.3.mlp.gate_proj.weight +24-11-19 18:49:02 | D | + w: sint8 +24-11-19 18:49:02 | D | + x: None +24-11-19 18:49:02 | D | + y: None +24-11-19 18:49:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:49:02 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:49:02 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:49:02 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:49:02 | D | - range ratio = [ 1.0000] +24-11-19 18:49:02 | D | sum error = [ 4.7581] +24-11-19 18:49:02 | D | best error = [ 4.7581] +24-11-19 18:49:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:49:03 | D | sum error = [ 4.7183, 4.7077, 4.7268, 4.7780, 4.8631] +24-11-19 18:49:03 | D | best error = [ 4.3768, 4.2407, 4.1709, 4.1338, 4.1129] +24-11-19 18:49:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:49:03 | D | sum error = [ 4.9953, 5.1655, 5.3742, 5.6178, 5.9282] +24-11-19 18:49:03 | D | best error = [ 4.1044, 4.1003, 4.0991, 4.0988, 4.0987] +24-11-19 18:49:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:49:03 | D | sum error = [ 6.2572, 6.6472, 7.0701, 7.5707, 8.0796] +24-11-19 18:49:03 | D | best error = [ 4.0987, 4.0987, 4.0987, 4.0987, 4.0987] +24-11-19 18:49:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:49:03 | D | sum error = [ 8.6597, 9.2767, 9.9358, 10.6677, 11.4209] +24-11-19 18:49:03 | D | best error = [ 4.0987, 4.0987, 4.0987, 4.0987, 4.0987] +24-11-19 18:49:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:49:03 | D | sum error = [ 12.2457, 13.1138, 14.0547, 15.0400, 16.0881] +24-11-19 18:49:03 | D | best error = [ 4.0987, 4.0987, 4.0987, 4.0987, 4.0987] +24-11-19 18:49:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:49:03 | D | sum error = [ 17.1968, 18.3754, 19.6289, 20.9565, 22.3442] +24-11-19 18:49:03 | D | best error = [ 4.0987, 4.0987, 4.0987, 4.0987, 4.0987] +24-11-19 18:49:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:49:03 | D | sum error = [ 23.8260, 25.3893, 27.0402, 28.7880, 30.6370] +24-11-19 18:49:03 | D | best error = [ 4.0987, 4.0987, 4.0987, 4.0987, 4.0987] +24-11-19 18:49:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:49:03 | D | sum error = [ 32.5808, 34.6028, 36.7706, 39.0539, 41.4399] +24-11-19 18:49:03 | D | best error = [ 4.0987, 4.0987, 4.0987, 4.0987, 4.0987] +24-11-19 18:49:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:49:03 | D | sum error = [ 43.9658, 46.6411, 49.4272, 52.3523, 55.4591] +24-11-19 18:49:03 | D | best error = [ 4.0987, 4.0987, 4.0987, 4.0987, 4.0987] +24-11-19 18:49:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:49:03 | D | sum error = [ 58.7169, 62.1331, 65.7028, 69.4859, 73.4449] +24-11-19 18:49:03 | D | best error = [ 4.0987, 4.0987, 4.0987, 4.0987, 4.0987] +24-11-19 18:49:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:49:03 | D | sum error = [ 77.5851, 81.9394, 86.5073, 91.2887, 96.2990] +24-11-19 18:49:03 | D | best error = [ 4.0987, 4.0987, 4.0987, 4.0987, 4.0987] +24-11-19 18:49:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:49:03 | D | sum error = [ 101.5226, 107.0083, 112.7259, 118.7104, 124.9538] +24-11-19 18:49:03 | D | best error = [ 4.0987, 4.0987, 4.0987, 4.0987, 4.0987] +24-11-19 18:49:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:49:03 | D | sum error = [ 131.4743, 138.2550, 145.3397, 152.7078, 160.3869] +24-11-19 18:49:03 | D | best error = [ 4.0987, 4.0987, 4.0987, 4.0987, 4.0987] +24-11-19 18:49:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:49:03 | D | sum error = [ 168.3571, 176.6449, 185.2637, 194.2100, 203.5002] +24-11-19 18:49:03 | D | best error = [ 4.0987, 4.0987, 4.0987, 4.0987, 4.0987] +24-11-19 18:49:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:49:03 | D | sum error = [ 213.1312, 223.1197, 233.4638, 244.1818, 255.2456] +24-11-19 18:49:03 | D | best error = [ 4.0987, 4.0987, 4.0987, 4.0987, 4.0987] +24-11-19 18:49:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:49:03 | D | sum error = [ 266.6868, 278.4904, 290.6540, 303.1826, 316.0851] +24-11-19 18:49:03 | D | best error = [ 4.0987, 4.0987, 4.0987, 4.0987, 4.0987] +24-11-19 18:49:03 | D | + error = [4.0987] +24-11-19 18:49:03 | D | - Calibrating model.layers.3.mlp.down_proj.weight +24-11-19 18:49:03 | D | + w: sint8 +24-11-19 18:49:03 | D | + x: None +24-11-19 18:49:03 | D | + y: None +24-11-19 18:49:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:49:03 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:49:03 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:49:04 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:49:04 | D | - range ratio = [ 1.0000] +24-11-19 18:49:04 | D | sum error = [ 0.2974] +24-11-19 18:49:04 | D | best error = [ 0.2974] +24-11-19 18:49:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:49:05 | D | sum error = [ 0.2938, 0.2916, 0.2897, 0.2884, 0.2877] +24-11-19 18:49:05 | D | best error = [ 0.2869, 0.2814, 0.2776, 0.2749, 0.2726] +24-11-19 18:49:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:49:05 | D | sum error = [ 0.2869, 0.2877, 0.2891, 0.2921, 0.2957] +24-11-19 18:49:05 | D | best error = [ 0.2705, 0.2689, 0.2676, 0.2667, 0.2660] +24-11-19 18:49:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:49:05 | D | sum error = [ 0.3008, 0.3074, 0.3158, 0.3259, 0.3375] +24-11-19 18:49:05 | D | best error = [ 0.2655, 0.2652, 0.2650, 0.2648, 0.2647] +24-11-19 18:49:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:49:05 | D | sum error = [ 0.3516, 0.3679, 0.3867, 0.4074, 0.4306] +24-11-19 18:49:05 | D | best error = [ 0.2646, 0.2646, 0.2645, 0.2645, 0.2645] +24-11-19 18:49:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:49:05 | D | sum error = [ 0.4566, 0.4854, 0.5165, 0.5507, 0.5888] +24-11-19 18:49:05 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 18:49:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:49:05 | D | sum error = [ 0.6297, 0.6735, 0.7208, 0.7715, 0.8260] +24-11-19 18:49:05 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 18:49:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:49:05 | D | sum error = [ 0.8843, 0.9476, 1.0139, 1.0859, 1.1614] +24-11-19 18:49:05 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 18:49:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:49:05 | D | sum error = [ 1.2423, 1.3283, 1.4192, 1.5161, 1.6185] +24-11-19 18:49:05 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 18:49:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:49:05 | D | sum error = [ 1.7274, 1.8431, 1.9650, 2.0948, 2.2321] +24-11-19 18:49:05 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 18:49:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:49:05 | D | sum error = [ 2.3769, 2.5299, 2.6910, 2.8612, 3.0405] +24-11-19 18:49:05 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 18:49:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:49:05 | D | sum error = [ 3.2294, 3.4287, 3.6386, 3.8596, 4.0910] +24-11-19 18:49:05 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 18:49:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:49:05 | D | sum error = [ 4.3352, 4.5908, 4.8595, 5.1417, 5.4366] +24-11-19 18:49:05 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 18:49:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:49:05 | D | sum error = [ 5.7459, 6.0700, 6.4089, 6.7634, 7.1343] +24-11-19 18:49:05 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 18:49:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:49:05 | D | sum error = [ 7.5212, 7.9261, 8.3475, 8.7879, 9.2453] +24-11-19 18:49:05 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 18:49:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:49:05 | D | sum error = [ 9.7220, 10.2179, 10.7339, 11.2700, 11.8268] +24-11-19 18:49:05 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 18:49:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:49:05 | D | sum error = [ 12.4042, 13.0029, 13.6231, 14.2646, 14.9289] +24-11-19 18:49:05 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 18:49:05 | D | + error = [0.2645] +24-11-19 18:49:05 | D | - Quantizing model.layers.3.self_attn.q_proj.weight +24-11-19 18:49:06 | D | - Quantizing model.layers.3.self_attn.k_proj.weight +24-11-19 18:49:06 | D | - Quantizing model.layers.3.self_attn.v_proj.weight +24-11-19 18:49:07 | D | - Quantizing model.layers.3.self_attn.o_proj.weight +24-11-19 18:49:08 | D | - Quantizing model.layers.3.mlp.up_proj.weight +24-11-19 18:49:09 | D | - Quantizing model.layers.3.mlp.gate_proj.weight +24-11-19 18:49:10 | D | - Quantizing model.layers.3.mlp.down_proj.weight +24-11-19 18:49:19 | D | - Quantizing layer model.layers.4 +24-11-19 18:49:19 | D | - Calibrating model.layers.4.self_attn.q_proj.weight +24-11-19 18:49:19 | D | + w: sint8 +24-11-19 18:49:19 | D | + x: None +24-11-19 18:49:19 | D | + y: None +24-11-19 18:49:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:49:19 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:49:19 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:49:20 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:49:20 | D | - range ratio = [ 1.0000] +24-11-19 18:49:20 | D | sum error = [ 1.4157] +24-11-19 18:49:20 | D | best error = [ 1.4157] +24-11-19 18:49:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:49:31 | D | sum error = [ 1.4216, 1.4330, 1.4320, 1.4534, 1.4777] +24-11-19 18:49:31 | D | best error = [ 1.4157, 1.4157, 1.4157, 1.4157, 1.4157] +24-11-19 18:49:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:49:31 | D | sum error = [ 1.5058, 1.5998, 1.7003, 1.7572, 1.9418] +24-11-19 18:49:31 | D | best error = [ 1.4157, 1.4157, 1.4157, 1.4157, 1.4157] +24-11-19 18:49:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:49:31 | D | sum error = [ 1.9778, 2.2123, 2.3980, 2.6075, 2.9186] +24-11-19 18:49:31 | D | best error = [ 1.4157, 1.4157, 1.4157, 1.4157, 1.4157] +24-11-19 18:49:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:49:31 | D | sum error = [ 3.2615, 3.4589, 3.9945, 4.3828, 4.8314] +24-11-19 18:49:31 | D | best error = [ 1.4157, 1.4157, 1.4157, 1.4157, 1.4157] +24-11-19 18:49:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:49:31 | D | sum error = [ 5.3994, 6.0241, 6.8613, 7.6027, 8.3551] +24-11-19 18:49:31 | D | best error = [ 1.4157, 1.4157, 1.4157, 1.4157, 1.4157] +24-11-19 18:49:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:49:31 | D | sum error = [ 9.3029, 10.5062, 11.7628, 13.1084, 14.6402] +24-11-19 18:49:31 | D | best error = [ 1.4157, 1.4157, 1.4157, 1.4157, 1.4157] +24-11-19 18:49:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:49:31 | D | sum error = [ 16.2403, 17.8882, 19.8878, 21.9897, 24.1059] +24-11-19 18:49:31 | D | best error = [ 1.4157, 1.4157, 1.4157, 1.4157, 1.4157] +24-11-19 18:49:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:49:31 | D | sum error = [ 26.5403, 29.2032, 31.9015, 34.8309, 38.0126] +24-11-19 18:49:31 | D | best error = [ 1.4157, 1.4157, 1.4157, 1.4157, 1.4157] +24-11-19 18:49:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:49:31 | D | sum error = [ 41.2525, 44.8795, 48.6986, 52.9286, 57.1365] +24-11-19 18:49:31 | D | best error = [ 1.4157, 1.4157, 1.4157, 1.4157, 1.4157] +24-11-19 18:49:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:49:31 | D | sum error = [ 62.0612, 67.3205, 72.8026, 78.6605, 84.9993] +24-11-19 18:49:31 | D | best error = [ 1.4157, 1.4157, 1.4157, 1.4157, 1.4157] +24-11-19 18:49:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:49:31 | D | sum error = [ 91.3884, 98.4493, 105.9371, 113.7740, 122.0180] +24-11-19 18:49:31 | D | best error = [ 1.4157, 1.4157, 1.4157, 1.4157, 1.4157] +24-11-19 18:49:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:49:31 | D | sum error = [ 131.0507, 140.4200, 150.4581, 161.0670, 172.2139] +24-11-19 18:49:31 | D | best error = [ 1.4157, 1.4157, 1.4157, 1.4157, 1.4157] +24-11-19 18:49:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:49:31 | D | sum error = [ 184.2555, 196.7024, 209.9692, 224.0762, 238.8058] +24-11-19 18:49:31 | D | best error = [ 1.4157, 1.4157, 1.4157, 1.4157, 1.4157] +24-11-19 18:49:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:49:31 | D | sum error = [ 254.1518, 270.3463, 287.1181, 304.7384, 322.8873] +24-11-19 18:49:31 | D | best error = [ 1.4157, 1.4157, 1.4157, 1.4157, 1.4157] +24-11-19 18:49:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:49:31 | D | sum error = [ 341.6376, 361.2949, 381.2758, 402.1394, 423.3521] +24-11-19 18:49:31 | D | best error = [ 1.4157, 1.4157, 1.4157, 1.4157, 1.4157] +24-11-19 18:49:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:49:31 | D | sum error = [ 445.1685, 467.5620, 490.3540, 513.3554, 536.5623] +24-11-19 18:49:31 | D | best error = [ 1.4157, 1.4157, 1.4157, 1.4157, 1.4157] +24-11-19 18:49:31 | D | + error = [1.4157] +24-11-19 18:49:32 | D | - Calibrating model.layers.4.self_attn.k_proj.weight +24-11-19 18:49:32 | D | + w: sint8 +24-11-19 18:49:32 | D | + x: None +24-11-19 18:49:32 | D | + y: None +24-11-19 18:49:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:49:32 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:49:32 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:49:32 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:49:32 | D | - range ratio = [ 1.0000] +24-11-19 18:49:32 | D | sum error = [ 1.5312] +24-11-19 18:49:32 | D | best error = [ 1.5312] +24-11-19 18:49:44 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:49:44 | D | sum error = [ 1.4637, 1.4500, 1.6563, 1.5827, 1.5317] +24-11-19 18:49:44 | D | best error = [ 1.4637, 1.4500, 1.4500, 1.4500, 1.4500] +24-11-19 18:49:44 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:49:44 | D | sum error = [ 1.5793, 1.8788, 1.8869, 1.8114, 2.0820] +24-11-19 18:49:44 | D | best error = [ 1.4500, 1.4500, 1.4500, 1.4500, 1.4500] +24-11-19 18:49:44 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:49:44 | D | sum error = [ 2.0660, 2.2421, 2.8258, 2.8554, 3.2169] +24-11-19 18:49:44 | D | best error = [ 1.4500, 1.4500, 1.4500, 1.4500, 1.4500] +24-11-19 18:49:44 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:49:44 | D | sum error = [ 3.6955, 3.9322, 4.6119, 5.0187, 5.2691] +24-11-19 18:49:44 | D | best error = [ 1.4500, 1.4500, 1.4500, 1.4500, 1.4500] +24-11-19 18:49:44 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:49:44 | D | sum error = [ 5.8363, 6.7108, 7.3439, 8.3358, 8.8824] +24-11-19 18:49:44 | D | best error = [ 1.4500, 1.4500, 1.4500, 1.4500, 1.4500] +24-11-19 18:49:44 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:49:44 | D | sum error = [ 10.0624, 10.9092, 11.7254, 13.0273, 14.1776] +24-11-19 18:49:44 | D | best error = [ 1.4500, 1.4500, 1.4500, 1.4500, 1.4500] +24-11-19 18:49:44 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:49:44 | D | sum error = [ 16.0864, 17.0902, 19.7292, 21.6267, 23.0028] +24-11-19 18:49:44 | D | best error = [ 1.4500, 1.4500, 1.4500, 1.4500, 1.4500] +24-11-19 18:49:44 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:49:44 | D | sum error = [ 25.3294, 28.2691, 30.1780, 33.0822, 35.8805] +24-11-19 18:49:44 | D | best error = [ 1.4500, 1.4500, 1.4500, 1.4500, 1.4500] +24-11-19 18:49:44 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:49:44 | D | sum error = [ 39.5250, 42.0537, 46.0490, 49.8839, 53.1496] +24-11-19 18:49:44 | D | best error = [ 1.4500, 1.4500, 1.4500, 1.4500, 1.4500] +24-11-19 18:49:44 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:49:44 | D | sum error = [ 57.8560, 63.1171, 69.1660, 73.2785, 79.3174] +24-11-19 18:49:44 | D | best error = [ 1.4500, 1.4500, 1.4500, 1.4500, 1.4500] +24-11-19 18:49:44 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:49:44 | D | sum error = [ 86.8200, 93.8053, 98.9834, 107.6794, 115.3787] +24-11-19 18:49:44 | D | best error = [ 1.4500, 1.4500, 1.4500, 1.4500, 1.4500] +24-11-19 18:49:44 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:49:44 | D | sum error = [ 123.9288, 133.9649, 144.5681, 156.6511, 165.8206] +24-11-19 18:49:44 | D | best error = [ 1.4500, 1.4500, 1.4500, 1.4500, 1.4500] +24-11-19 18:49:44 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:49:44 | D | sum error = [ 178.2425, 190.3983, 202.5939, 218.4909, 233.1570] +24-11-19 18:49:44 | D | best error = [ 1.4500, 1.4500, 1.4500, 1.4500, 1.4500] +24-11-19 18:49:44 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:49:44 | D | sum error = [ 250.6131, 264.0243, 280.9980, 301.1635, 315.7542] +24-11-19 18:49:44 | D | best error = [ 1.4500, 1.4500, 1.4500, 1.4500, 1.4500] +24-11-19 18:49:44 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:49:44 | D | sum error = [ 337.6028, 358.0520, 379.1698, 400.6195, 421.5007] +24-11-19 18:49:44 | D | best error = [ 1.4500, 1.4500, 1.4500, 1.4500, 1.4500] +24-11-19 18:49:44 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:49:44 | D | sum error = [ 448.3580, 467.5404, 491.5822, 516.7878, 540.9376] +24-11-19 18:49:44 | D | best error = [ 1.4500, 1.4500, 1.4500, 1.4500, 1.4500] +24-11-19 18:49:44 | D | + error = [1.4500] +24-11-19 18:49:44 | D | - Calibrating model.layers.4.self_attn.v_proj.weight +24-11-19 18:49:44 | D | + w: sint8 +24-11-19 18:49:44 | D | + x: None +24-11-19 18:49:44 | D | + y: None +24-11-19 18:49:44 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:49:44 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:49:44 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:49:44 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:49:44 | D | - range ratio = [ 1.0000] +24-11-19 18:49:44 | D | sum error = [ 1.0560] +24-11-19 18:49:44 | D | best error = [ 1.0560] +24-11-19 18:49:44 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:49:44 | D | sum error = [ 1.0357, 1.0335, 1.0433, 1.0470, 1.0659] +24-11-19 18:49:44 | D | best error = [ 0.9714, 0.9430, 0.9296, 0.9224, 0.9185] +24-11-19 18:49:44 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:49:44 | D | sum error = [ 1.0973, 1.1391, 1.1875, 1.2496, 1.3196] +24-11-19 18:49:44 | D | best error = [ 0.9168, 0.9161, 0.9158, 0.9158, 0.9158] +24-11-19 18:49:44 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:49:44 | D | sum error = [ 1.3911, 1.4979, 1.5854, 1.7004, 1.8229] +24-11-19 18:49:44 | D | best error = [ 0.9158, 0.9158, 0.9158, 0.9158, 0.9158] +24-11-19 18:49:44 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:49:44 | D | sum error = [ 1.9658, 2.0959, 2.2570, 2.4120, 2.5985] +24-11-19 18:49:44 | D | best error = [ 0.9158, 0.9158, 0.9158, 0.9158, 0.9158] +24-11-19 18:49:44 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:49:44 | D | sum error = [ 2.7799, 2.9868, 3.1973, 3.4212, 3.6610] +24-11-19 18:49:44 | D | best error = [ 0.9158, 0.9158, 0.9158, 0.9158, 0.9158] +24-11-19 18:49:44 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:49:44 | D | sum error = [ 3.9063, 4.1848, 4.4680, 4.7677, 5.0880] +24-11-19 18:49:44 | D | best error = [ 0.9158, 0.9158, 0.9158, 0.9158, 0.9158] +24-11-19 18:49:44 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:49:44 | D | sum error = [ 5.4304, 5.7680, 6.1445, 6.5421, 6.9583] +24-11-19 18:49:44 | D | best error = [ 0.9158, 0.9158, 0.9158, 0.9158, 0.9158] +24-11-19 18:49:44 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:49:44 | D | sum error = [ 7.3821, 7.8468, 8.3164, 8.8234, 9.3476] +24-11-19 18:49:44 | D | best error = [ 0.9158, 0.9158, 0.9158, 0.9158, 0.9158] +24-11-19 18:49:44 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:49:44 | D | sum error = [ 9.9035, 10.4906, 11.1055, 11.7554, 12.4313] +24-11-19 18:49:44 | D | best error = [ 0.9158, 0.9158, 0.9158, 0.9158, 0.9158] +24-11-19 18:49:44 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:49:44 | D | sum error = [ 13.1424, 13.8891, 14.6719, 15.5029, 16.3635] +24-11-19 18:49:44 | D | best error = [ 0.9158, 0.9158, 0.9158, 0.9158, 0.9158] +24-11-19 18:49:44 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:49:44 | D | sum error = [ 17.2650, 18.2129, 19.1939, 20.2227, 21.3006] +24-11-19 18:49:44 | D | best error = [ 0.9158, 0.9158, 0.9158, 0.9158, 0.9158] +24-11-19 18:49:44 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:49:44 | D | sum error = [ 22.4255, 23.6093, 24.8413, 26.1334, 27.4703] +24-11-19 18:49:44 | D | best error = [ 0.9158, 0.9158, 0.9158, 0.9158, 0.9158] +24-11-19 18:49:44 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:49:44 | D | sum error = [ 28.8628, 30.3236, 31.8371, 33.4093, 35.0452] +24-11-19 18:49:44 | D | best error = [ 0.9158, 0.9158, 0.9158, 0.9158, 0.9158] +24-11-19 18:49:44 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:49:44 | D | sum error = [ 36.7507, 38.5107, 40.3456, 42.2488, 44.2114] +24-11-19 18:49:44 | D | best error = [ 0.9158, 0.9158, 0.9158, 0.9158, 0.9158] +24-11-19 18:49:44 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:49:44 | D | sum error = [ 46.2456, 48.3502, 50.5301, 52.7811, 55.1036] +24-11-19 18:49:44 | D | best error = [ 0.9158, 0.9158, 0.9158, 0.9158, 0.9158] +24-11-19 18:49:44 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:49:44 | D | sum error = [ 57.4954, 59.9633, 62.5066, 65.1162, 67.8064] +24-11-19 18:49:44 | D | best error = [ 0.9158, 0.9158, 0.9158, 0.9158, 0.9158] +24-11-19 18:49:44 | D | + error = [0.9158] +24-11-19 18:49:44 | D | - Calibrating model.layers.4.self_attn.o_proj.weight +24-11-19 18:49:44 | D | + w: sint8 +24-11-19 18:49:44 | D | + x: None +24-11-19 18:49:44 | D | + y: None +24-11-19 18:49:44 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:49:44 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:49:44 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:49:44 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:49:44 | D | - range ratio = [ 1.0000] +24-11-19 18:49:44 | D | sum error = [ 0.2424] +24-11-19 18:49:44 | D | best error = [ 0.2424] +24-11-19 18:49:45 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:49:45 | D | sum error = [ 0.2397, 0.2394, 0.2387, 0.2408, 0.2439] +24-11-19 18:49:45 | D | best error = [ 0.2238, 0.2157, 0.2109, 0.2080, 0.2060] +24-11-19 18:49:45 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:49:45 | D | sum error = [ 0.2474, 0.2528, 0.2607, 0.2704, 0.2811] +24-11-19 18:49:45 | D | best error = [ 0.2045, 0.2035, 0.2029, 0.2025, 0.2022] +24-11-19 18:49:45 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:49:45 | D | sum error = [ 0.2929, 0.3088, 0.3251, 0.3436, 0.3637] +24-11-19 18:49:45 | D | best error = [ 0.2020, 0.2018, 0.2017, 0.2016, 0.2016] +24-11-19 18:49:45 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:49:45 | D | sum error = [ 0.3861, 0.4096, 0.4356, 0.4635, 0.4936] +24-11-19 18:49:45 | D | best error = [ 0.2016, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 18:49:45 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:49:45 | D | sum error = [ 0.5252, 0.5593, 0.5951, 0.6347, 0.6748] +24-11-19 18:49:45 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 18:49:45 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:49:45 | D | sum error = [ 0.7187, 0.7639, 0.8129, 0.8634, 0.9179] +24-11-19 18:49:45 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 18:49:45 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:49:45 | D | sum error = [ 0.9744, 1.0344, 1.0979, 1.1651, 1.2353] +24-11-19 18:49:45 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 18:49:45 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:49:45 | D | sum error = [ 1.3105, 1.3882, 1.4719, 1.5583, 1.6490] +24-11-19 18:49:45 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 18:49:45 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:49:45 | D | sum error = [ 1.7450, 1.8458, 1.9511, 2.0618, 2.1790] +24-11-19 18:49:45 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 18:49:45 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:49:45 | D | sum error = [ 2.3018, 2.4298, 2.5638, 2.7042, 2.8523] +24-11-19 18:49:45 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 18:49:45 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:49:45 | D | sum error = [ 3.0068, 3.1691, 3.3395, 3.5172, 3.7033] +24-11-19 18:49:45 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 18:49:45 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:49:45 | D | sum error = [ 3.8978, 4.0998, 4.3120, 4.5341, 4.7661] +24-11-19 18:49:45 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 18:49:45 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:49:45 | D | sum error = [ 5.0075, 5.2594, 5.5219, 5.7951, 6.0801] +24-11-19 18:49:45 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 18:49:45 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:49:45 | D | sum error = [ 6.3769, 6.6851, 7.0063, 7.3414, 7.6886] +24-11-19 18:49:45 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 18:49:45 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:49:45 | D | sum error = [ 8.0495, 8.4244, 8.8140, 9.2182, 9.6366] +24-11-19 18:49:45 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 18:49:45 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:49:45 | D | sum error = [ 10.0699, 10.5187, 10.9848, 11.4663, 11.9641] +24-11-19 18:49:45 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 18:49:45 | D | + error = [0.2015] +24-11-19 18:49:45 | D | - Calibrating model.layers.4.mlp.up_proj.weight +24-11-19 18:49:45 | D | + w: sint8 +24-11-19 18:49:45 | D | + x: None +24-11-19 18:49:45 | D | + y: None +24-11-19 18:49:45 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:49:45 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:49:45 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:49:45 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:49:45 | D | - range ratio = [ 1.0000] +24-11-19 18:49:45 | D | sum error = [ 4.1357] +24-11-19 18:49:45 | D | best error = [ 4.1357] +24-11-19 18:49:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:49:46 | D | sum error = [ 4.1022, 4.0974, 4.1086, 4.1658, 4.2359] +24-11-19 18:49:46 | D | best error = [ 3.8270, 3.7159, 3.6587, 3.6278, 3.6107] +24-11-19 18:49:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:49:46 | D | sum error = [ 4.3392, 4.4969, 4.6753, 4.9023, 5.1582] +24-11-19 18:49:46 | D | best error = [ 3.6026, 3.5994, 3.5982, 3.5980, 3.5979] +24-11-19 18:49:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:49:46 | D | sum error = [ 5.4483, 5.7922, 6.1834, 6.5923, 7.0500] +24-11-19 18:49:46 | D | best error = [ 3.5979, 3.5979, 3.5979, 3.5979, 3.5979] +24-11-19 18:49:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:49:46 | D | sum error = [ 7.5437, 8.0814, 8.6601, 9.2840, 9.9546] +24-11-19 18:49:46 | D | best error = [ 3.5979, 3.5979, 3.5979, 3.5979, 3.5979] +24-11-19 18:49:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:49:46 | D | sum error = [ 10.6533, 11.4022, 12.2030, 13.0591, 13.9610] +24-11-19 18:49:46 | D | best error = [ 3.5979, 3.5979, 3.5979, 3.5979, 3.5979] +24-11-19 18:49:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:49:46 | D | sum error = [ 14.9062, 15.9094, 16.9848, 18.1103, 19.3025] +24-11-19 18:49:46 | D | best error = [ 3.5979, 3.5979, 3.5979, 3.5979, 3.5979] +24-11-19 18:49:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:49:46 | D | sum error = [ 20.5504, 21.8651, 23.2474, 24.7098, 26.2476] +24-11-19 18:49:46 | D | best error = [ 3.5979, 3.5979, 3.5979, 3.5979, 3.5979] +24-11-19 18:49:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:49:46 | D | sum error = [ 27.8627, 29.5584, 31.3394, 33.2040, 35.1702] +24-11-19 18:49:46 | D | best error = [ 3.5979, 3.5979, 3.5979, 3.5979, 3.5979] +24-11-19 18:49:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:49:46 | D | sum error = [ 37.2257, 39.3769, 41.6458, 44.0019, 46.4749] +24-11-19 18:49:46 | D | best error = [ 3.5979, 3.5979, 3.5979, 3.5979, 3.5979] +24-11-19 18:49:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:49:46 | D | sum error = [ 49.0542, 51.7582, 54.5819, 57.5211, 60.6015] +24-11-19 18:49:46 | D | best error = [ 3.5979, 3.5979, 3.5979, 3.5979, 3.5979] +24-11-19 18:49:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:49:46 | D | sum error = [ 63.8101, 67.1504, 70.6424, 74.2486, 78.0203] +24-11-19 18:49:46 | D | best error = [ 3.5979, 3.5979, 3.5979, 3.5979, 3.5979] +24-11-19 18:49:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:49:46 | D | sum error = [ 81.9274, 85.9962, 90.2176, 94.5901, 99.1324] +24-11-19 18:49:46 | D | best error = [ 3.5979, 3.5979, 3.5979, 3.5979, 3.5979] +24-11-19 18:49:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:49:46 | D | sum error = [ 103.8337, 108.7011, 113.7400, 118.9548, 124.3432] +24-11-19 18:49:46 | D | best error = [ 3.5979, 3.5979, 3.5979, 3.5979, 3.5979] +24-11-19 18:49:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:49:46 | D | sum error = [ 129.9158, 135.6816, 141.6160, 147.7636, 154.0975] +24-11-19 18:49:46 | D | best error = [ 3.5979, 3.5979, 3.5979, 3.5979, 3.5979] +24-11-19 18:49:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:49:46 | D | sum error = [ 160.6367, 167.3651, 174.3042, 181.4473, 188.7961] +24-11-19 18:49:46 | D | best error = [ 3.5979, 3.5979, 3.5979, 3.5979, 3.5979] +24-11-19 18:49:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:49:46 | D | sum error = [ 196.3656, 204.1532, 212.1558, 220.3834, 228.8309] +24-11-19 18:49:46 | D | best error = [ 3.5979, 3.5979, 3.5979, 3.5979, 3.5979] +24-11-19 18:49:46 | D | + error = [3.5979] +24-11-19 18:49:46 | D | - Calibrating model.layers.4.mlp.gate_proj.weight +24-11-19 18:49:46 | D | + w: sint8 +24-11-19 18:49:46 | D | + x: None +24-11-19 18:49:46 | D | + y: None +24-11-19 18:49:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:49:46 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:49:46 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:49:47 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:49:47 | D | - range ratio = [ 1.0000] +24-11-19 18:49:47 | D | sum error = [ 5.4961] +24-11-19 18:49:47 | D | best error = [ 5.4961] +24-11-19 18:49:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:49:48 | D | sum error = [ 5.4530, 5.4445, 5.4726, 5.5371, 5.6338] +24-11-19 18:49:48 | D | best error = [ 5.0891, 4.9442, 4.8681, 4.8259, 4.8045] +24-11-19 18:49:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:49:48 | D | sum error = [ 5.7897, 5.9669, 6.2185, 6.5255, 6.8787] +24-11-19 18:49:48 | D | best error = [ 4.7950, 4.7908, 4.7897, 4.7893, 4.7892] +24-11-19 18:49:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:49:48 | D | sum error = [ 7.2651, 7.7114, 8.2112, 8.7682, 9.3670] +24-11-19 18:49:48 | D | best error = [ 4.7892, 4.7892, 4.7892, 4.7892, 4.7892] +24-11-19 18:49:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:49:48 | D | sum error = [ 10.0430, 10.7753, 11.5434, 12.3932, 13.2799] +24-11-19 18:49:48 | D | best error = [ 4.7892, 4.7892, 4.7892, 4.7892, 4.7892] +24-11-19 18:49:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:49:48 | D | sum error = [ 14.2490, 15.2754, 16.3796, 17.5404, 18.7774] +24-11-19 18:49:48 | D | best error = [ 4.7892, 4.7892, 4.7892, 4.7892, 4.7892] +24-11-19 18:49:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:49:48 | D | sum error = [ 20.1102, 21.5071, 22.9975, 24.5689, 26.2362] +24-11-19 18:49:48 | D | best error = [ 4.7892, 4.7892, 4.7892, 4.7892, 4.7892] +24-11-19 18:49:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:49:48 | D | sum error = [ 27.9980, 29.8765, 31.8543, 33.9416, 36.1605] +24-11-19 18:49:48 | D | best error = [ 4.7892, 4.7892, 4.7892, 4.7892, 4.7892] +24-11-19 18:49:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:49:48 | D | sum error = [ 38.4972, 40.9797, 43.5954, 46.3713, 49.2888] +24-11-19 18:49:48 | D | best error = [ 4.7892, 4.7892, 4.7892, 4.7892, 4.7892] +24-11-19 18:49:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:49:48 | D | sum error = [ 52.3768, 55.6447, 59.0772, 62.7131, 66.5538] +24-11-19 18:49:48 | D | best error = [ 4.7892, 4.7892, 4.7892, 4.7892, 4.7892] +24-11-19 18:49:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:49:48 | D | sum error = [ 70.5948, 74.8498, 79.3296, 84.0488, 89.0131] +24-11-19 18:49:48 | D | best error = [ 4.7892, 4.7892, 4.7892, 4.7892, 4.7892] +24-11-19 18:49:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:49:48 | D | sum error = [ 94.2480, 99.7559, 105.5390, 111.6305, 118.0201] +24-11-19 18:49:48 | D | best error = [ 4.7892, 4.7892, 4.7892, 4.7892, 4.7892] +24-11-19 18:49:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:49:48 | D | sum error = [ 124.7403, 131.7840, 139.1707, 146.9195, 155.0245] +24-11-19 18:49:48 | D | best error = [ 4.7892, 4.7892, 4.7892, 4.7892, 4.7892] +24-11-19 18:49:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:49:48 | D | sum error = [ 163.5205, 172.4032, 181.6857, 191.3822, 201.4960] +24-11-19 18:49:48 | D | best error = [ 4.7892, 4.7892, 4.7892, 4.7892, 4.7892] +24-11-19 18:49:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:49:48 | D | sum error = [ 212.0449, 223.0348, 234.4950, 246.4319, 258.8295] +24-11-19 18:49:48 | D | best error = [ 4.7892, 4.7892, 4.7892, 4.7892, 4.7892] +24-11-19 18:49:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:49:48 | D | sum error = [ 271.7244, 285.1318, 299.0048, 313.4164, 328.3331] +24-11-19 18:49:48 | D | best error = [ 4.7892, 4.7892, 4.7892, 4.7892, 4.7892] +24-11-19 18:49:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:49:48 | D | sum error = [ 343.7604, 359.6825, 376.1245, 393.0872, 410.5684] +24-11-19 18:49:48 | D | best error = [ 4.7892, 4.7892, 4.7892, 4.7892, 4.7892] +24-11-19 18:49:48 | D | + error = [4.7892] +24-11-19 18:49:48 | D | - Calibrating model.layers.4.mlp.down_proj.weight +24-11-19 18:49:48 | D | + w: sint8 +24-11-19 18:49:48 | D | + x: None +24-11-19 18:49:48 | D | + y: None +24-11-19 18:49:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:49:48 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:49:48 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:49:48 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:49:48 | D | - range ratio = [ 1.0000] +24-11-19 18:49:48 | D | sum error = [ 0.3828] +24-11-19 18:49:48 | D | best error = [ 0.3828] +24-11-19 18:49:49 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:49:49 | D | sum error = [ 0.3789, 0.3753, 0.3732, 0.3716, 0.3704] +24-11-19 18:49:49 | D | best error = [ 0.3693, 0.3621, 0.3570, 0.3534, 0.3505] +24-11-19 18:49:49 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:49:49 | D | sum error = [ 0.3710, 0.3719, 0.3746, 0.3787, 0.3835] +24-11-19 18:49:49 | D | best error = [ 0.3483, 0.3464, 0.3450, 0.3438, 0.3431] +24-11-19 18:49:49 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:49:49 | D | sum error = [ 0.3914, 0.4003, 0.4116, 0.4250, 0.4411] +24-11-19 18:49:49 | D | best error = [ 0.3426, 0.3422, 0.3419, 0.3417, 0.3416] +24-11-19 18:49:49 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:49:49 | D | sum error = [ 0.4600, 0.4816, 0.5051, 0.5331, 0.5626] +24-11-19 18:49:49 | D | best error = [ 0.3415, 0.3414, 0.3414, 0.3414, 0.3414] +24-11-19 18:49:49 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:49:49 | D | sum error = [ 0.5973, 0.6337, 0.6747, 0.7197, 0.7675] +24-11-19 18:49:49 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 18:49:49 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:49:49 | D | sum error = [ 0.8193, 0.8765, 0.9372, 1.0021, 1.0723] +24-11-19 18:49:49 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 18:49:49 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:49:49 | D | sum error = [ 1.1481, 1.2279, 1.3142, 1.4060, 1.5038] +24-11-19 18:49:49 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 18:49:49 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:49:49 | D | sum error = [ 1.6080, 1.7187, 1.8374, 1.9618, 2.0954] +24-11-19 18:49:49 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 18:49:49 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:49:49 | D | sum error = [ 2.2365, 2.3857, 2.5443, 2.7117, 2.8887] +24-11-19 18:49:49 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 18:49:49 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:49:49 | D | sum error = [ 3.0759, 3.2734, 3.4809, 3.7004, 3.9318] +24-11-19 18:49:49 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 18:49:49 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:49:49 | D | sum error = [ 4.1763, 4.4329, 4.7024, 4.9859, 5.2834] +24-11-19 18:49:49 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 18:49:49 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:49:49 | D | sum error = [ 5.5954, 5.9232, 6.2669, 6.6266, 7.0038] +24-11-19 18:49:49 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 18:49:49 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:49:49 | D | sum error = [ 7.3983, 7.8113, 8.2431, 8.6942, 9.1656] +24-11-19 18:49:49 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 18:49:49 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:49:49 | D | sum error = [ 9.6568, 10.1693, 10.7034, 11.2605, 11.8381] +24-11-19 18:49:49 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 18:49:49 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:49:49 | D | sum error = [ 12.4399, 13.0651, 13.7146, 14.3894, 15.0890] +24-11-19 18:49:49 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 18:49:49 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:49:49 | D | sum error = [ 15.8141, 16.5644, 17.3417, 18.1450, 18.9758] +24-11-19 18:49:49 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 18:49:49 | D | + error = [0.3413] +24-11-19 18:49:49 | D | - Quantizing model.layers.4.self_attn.q_proj.weight +24-11-19 18:49:50 | D | - Quantizing model.layers.4.self_attn.k_proj.weight +24-11-19 18:49:51 | D | - Quantizing model.layers.4.self_attn.v_proj.weight +24-11-19 18:49:52 | D | - Quantizing model.layers.4.self_attn.o_proj.weight +24-11-19 18:49:53 | D | - Quantizing model.layers.4.mlp.up_proj.weight +24-11-19 18:49:53 | D | - Quantizing model.layers.4.mlp.gate_proj.weight +24-11-19 18:49:54 | D | - Quantizing model.layers.4.mlp.down_proj.weight +24-11-19 18:50:04 | D | - Quantizing layer model.layers.5 +24-11-19 18:50:04 | D | - Calibrating model.layers.5.self_attn.q_proj.weight +24-11-19 18:50:04 | D | + w: sint8 +24-11-19 18:50:04 | D | + x: None +24-11-19 18:50:04 | D | + y: None +24-11-19 18:50:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:50:04 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:50:04 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:50:04 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:50:04 | D | - range ratio = [ 1.0000] +24-11-19 18:50:04 | D | sum error = [ 2.0444] +24-11-19 18:50:04 | D | best error = [ 2.0444] +24-11-19 18:50:16 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:50:16 | D | sum error = [ 2.1625, 2.0389, 2.0675, 2.0355, 2.0766] +24-11-19 18:50:16 | D | best error = [ 2.0444, 2.0389, 2.0389, 2.0355, 2.0355] +24-11-19 18:50:16 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:50:16 | D | sum error = [ 2.1370, 2.2421, 2.3186, 2.5151, 2.4964] +24-11-19 18:50:16 | D | best error = [ 2.0355, 2.0355, 2.0355, 2.0355, 2.0355] +24-11-19 18:50:16 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:50:16 | D | sum error = [ 2.6965, 2.8953, 3.1002, 3.4375, 3.7068] +24-11-19 18:50:16 | D | best error = [ 2.0355, 2.0355, 2.0355, 2.0355, 2.0355] +24-11-19 18:50:16 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:50:16 | D | sum error = [ 3.8762, 4.1836, 4.6941, 5.0352, 5.5091] +24-11-19 18:50:16 | D | best error = [ 2.0355, 2.0355, 2.0355, 2.0355, 2.0355] +24-11-19 18:50:16 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:50:16 | D | sum error = [ 5.8759, 6.3906, 7.0458, 7.5893, 8.1133] +24-11-19 18:50:16 | D | best error = [ 2.0355, 2.0355, 2.0355, 2.0355, 2.0355] +24-11-19 18:50:16 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:50:16 | D | sum error = [ 8.7859, 9.6899, 10.5660, 11.5547, 12.4746] +24-11-19 18:50:16 | D | best error = [ 2.0355, 2.0355, 2.0355, 2.0355, 2.0355] +24-11-19 18:50:16 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:50:16 | D | sum error = [ 13.6025, 14.6923, 16.1300, 17.5667, 19.1623] +24-11-19 18:50:16 | D | best error = [ 2.0355, 2.0355, 2.0355, 2.0355, 2.0355] +24-11-19 18:50:16 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:50:16 | D | sum error = [ 20.8529, 22.7106, 24.8025, 26.9223, 29.2827] +24-11-19 18:50:16 | D | best error = [ 2.0355, 2.0355, 2.0355, 2.0355, 2.0355] +24-11-19 18:50:16 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:50:16 | D | sum error = [ 31.8940, 34.7337, 37.5235, 40.6916, 44.0351] +24-11-19 18:50:16 | D | best error = [ 2.0355, 2.0355, 2.0355, 2.0355, 2.0355] +24-11-19 18:50:16 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:50:16 | D | sum error = [ 47.8054, 51.8145, 55.9649, 60.5818, 65.4938] +24-11-19 18:50:16 | D | best error = [ 2.0355, 2.0355, 2.0355, 2.0355, 2.0355] +24-11-19 18:50:16 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:50:16 | D | sum error = [ 70.9703, 76.4120, 82.4174, 88.8334, 95.6980] +24-11-19 18:50:16 | D | best error = [ 2.0355, 2.0355, 2.0355, 2.0355, 2.0355] +24-11-19 18:50:16 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:50:16 | D | sum error = [ 102.9835, 110.7916, 119.2021, 128.1475, 137.6875] +24-11-19 18:50:16 | D | best error = [ 2.0355, 2.0355, 2.0355, 2.0355, 2.0355] +24-11-19 18:50:16 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:50:16 | D | sum error = [ 147.9316, 158.7708, 170.2712, 182.4699, 195.3227] +24-11-19 18:50:16 | D | best error = [ 2.0355, 2.0355, 2.0355, 2.0355, 2.0355] +24-11-19 18:50:16 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:50:16 | D | sum error = [ 208.8951, 223.3425, 238.6541, 254.7731, 271.6306] +24-11-19 18:50:16 | D | best error = [ 2.0355, 2.0355, 2.0355, 2.0355, 2.0355] +24-11-19 18:50:16 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:50:16 | D | sum error = [ 289.3976, 307.9777, 327.3298, 347.3678, 368.1493] +24-11-19 18:50:16 | D | best error = [ 2.0355, 2.0355, 2.0355, 2.0355, 2.0355] +24-11-19 18:50:16 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:50:16 | D | sum error = [ 389.4028, 411.1734, 433.4491, 456.1219, 479.1059] +24-11-19 18:50:16 | D | best error = [ 2.0355, 2.0355, 2.0355, 2.0355, 2.0355] +24-11-19 18:50:16 | D | + error = [2.0355] +24-11-19 18:50:16 | D | - Calibrating model.layers.5.self_attn.k_proj.weight +24-11-19 18:50:16 | D | + w: sint8 +24-11-19 18:50:16 | D | + x: None +24-11-19 18:50:16 | D | + y: None +24-11-19 18:50:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:50:16 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:50:16 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:50:16 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:50:17 | D | - range ratio = [ 1.0000] +24-11-19 18:50:17 | D | sum error = [ 2.2469] +24-11-19 18:50:17 | D | best error = [ 2.2469] +24-11-19 18:50:28 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:50:28 | D | sum error = [ 2.2132, 2.1535, 2.0362, 2.1405, 2.0797] +24-11-19 18:50:28 | D | best error = [ 2.2132, 2.1535, 2.0362, 2.0362, 2.0362] +24-11-19 18:50:28 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:50:28 | D | sum error = [ 2.1237, 2.3031, 2.2924, 2.5899, 2.9032] +24-11-19 18:50:28 | D | best error = [ 2.0362, 2.0362, 2.0362, 2.0362, 2.0362] +24-11-19 18:50:28 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:50:28 | D | sum error = [ 2.9739, 3.3811, 3.9649, 4.1093, 4.3863] +24-11-19 18:50:28 | D | best error = [ 2.0362, 2.0362, 2.0362, 2.0362, 2.0362] +24-11-19 18:50:28 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:50:28 | D | sum error = [ 4.9182, 5.2795, 6.2419, 5.9114, 7.3072] +24-11-19 18:50:28 | D | best error = [ 2.0362, 2.0362, 2.0362, 2.0362, 2.0362] +24-11-19 18:50:28 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:50:28 | D | sum error = [ 7.2845, 8.6508, 9.5265, 9.8376, 10.4995] +24-11-19 18:50:28 | D | best error = [ 2.0362, 2.0362, 2.0362, 2.0362, 2.0362] +24-11-19 18:50:28 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:50:28 | D | sum error = [ 11.5261, 12.7913, 13.7314, 14.6344, 16.3874] +24-11-19 18:50:28 | D | best error = [ 2.0362, 2.0362, 2.0362, 2.0362, 2.0362] +24-11-19 18:50:28 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:50:28 | D | sum error = [ 17.5414, 18.8494, 20.7590, 22.3197, 24.7393] +24-11-19 18:50:28 | D | best error = [ 2.0362, 2.0362, 2.0362, 2.0362, 2.0362] +24-11-19 18:50:28 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:50:28 | D | sum error = [ 26.1545, 28.2492, 30.8089, 33.6560, 36.0955] +24-11-19 18:50:28 | D | best error = [ 2.0362, 2.0362, 2.0362, 2.0362, 2.0362] +24-11-19 18:50:28 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:50:28 | D | sum error = [ 38.6534, 41.9996, 44.8245, 48.6606, 52.3887] +24-11-19 18:50:28 | D | best error = [ 2.0362, 2.0362, 2.0362, 2.0362, 2.0362] +24-11-19 18:50:28 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:50:28 | D | sum error = [ 56.9167, 60.7532, 65.2736, 70.6551, 75.6268] +24-11-19 18:50:28 | D | best error = [ 2.0362, 2.0362, 2.0362, 2.0362, 2.0362] +24-11-19 18:50:28 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:50:28 | D | sum error = [ 81.9315, 88.2409, 94.9859, 102.4064, 110.9856] +24-11-19 18:50:28 | D | best error = [ 2.0362, 2.0362, 2.0362, 2.0362, 2.0362] +24-11-19 18:50:28 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:50:28 | D | sum error = [ 119.1781, 126.8793, 136.9280, 145.9495, 155.8997] +24-11-19 18:50:28 | D | best error = [ 2.0362, 2.0362, 2.0362, 2.0362, 2.0362] +24-11-19 18:50:28 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:50:28 | D | sum error = [ 168.3732, 178.5525, 191.0507, 204.0370, 217.8984] +24-11-19 18:50:28 | D | best error = [ 2.0362, 2.0362, 2.0362, 2.0362, 2.0362] +24-11-19 18:50:28 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:50:28 | D | sum error = [ 231.6973, 246.3962, 263.6295, 278.4859, 296.2557] +24-11-19 18:50:28 | D | best error = [ 2.0362, 2.0362, 2.0362, 2.0362, 2.0362] +24-11-19 18:50:28 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:50:28 | D | sum error = [ 315.6544, 334.0621, 354.1268, 373.7132, 396.0064] +24-11-19 18:50:28 | D | best error = [ 2.0362, 2.0362, 2.0362, 2.0362, 2.0362] +24-11-19 18:50:28 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:50:28 | D | sum error = [ 417.1062, 438.1367, 459.5185, 482.0071, 505.3020] +24-11-19 18:50:28 | D | best error = [ 2.0362, 2.0362, 2.0362, 2.0362, 2.0362] +24-11-19 18:50:28 | D | + error = [2.0362] +24-11-19 18:50:28 | D | - Calibrating model.layers.5.self_attn.v_proj.weight +24-11-19 18:50:28 | D | + w: sint8 +24-11-19 18:50:28 | D | + x: None +24-11-19 18:50:28 | D | + y: None +24-11-19 18:50:28 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:50:28 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:50:28 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:50:28 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:50:28 | D | - range ratio = [ 1.0000] +24-11-19 18:50:28 | D | sum error = [ 1.0033] +24-11-19 18:50:28 | D | best error = [ 1.0033] +24-11-19 18:50:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:50:29 | D | sum error = [ 1.0005, 0.9913, 1.0059, 1.0056, 1.0222] +24-11-19 18:50:29 | D | best error = [ 0.9389, 0.9115, 0.8993, 0.8917, 0.8878] +24-11-19 18:50:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:50:29 | D | sum error = [ 1.0523, 1.0929, 1.1406, 1.1925, 1.2559] +24-11-19 18:50:29 | D | best error = [ 0.8860, 0.8852, 0.8851, 0.8850, 0.8850] +24-11-19 18:50:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:50:29 | D | sum error = [ 1.3233, 1.4095, 1.4920, 1.5863, 1.7087] +24-11-19 18:50:29 | D | best error = [ 0.8850, 0.8850, 0.8850, 0.8850, 0.8850] +24-11-19 18:50:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:50:29 | D | sum error = [ 1.8306, 1.9485, 2.0877, 2.2412, 2.4037] +24-11-19 18:50:29 | D | best error = [ 0.8850, 0.8850, 0.8850, 0.8850, 0.8850] +24-11-19 18:50:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:50:29 | D | sum error = [ 2.5822, 2.7649, 2.9591, 3.1654, 3.3877] +24-11-19 18:50:29 | D | best error = [ 0.8850, 0.8850, 0.8850, 0.8850, 0.8850] +24-11-19 18:50:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:50:29 | D | sum error = [ 3.6183, 3.8645, 4.1259, 4.4100, 4.6895] +24-11-19 18:50:29 | D | best error = [ 0.8850, 0.8850, 0.8850, 0.8850, 0.8850] +24-11-19 18:50:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:50:29 | D | sum error = [ 5.0081, 5.3381, 5.6819, 6.0541, 6.4474] +24-11-19 18:50:29 | D | best error = [ 0.8850, 0.8850, 0.8850, 0.8850, 0.8850] +24-11-19 18:50:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:50:29 | D | sum error = [ 6.8520, 7.2900, 7.7407, 8.2281, 8.7239] +24-11-19 18:50:29 | D | best error = [ 0.8850, 0.8850, 0.8850, 0.8850, 0.8850] +24-11-19 18:50:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:50:29 | D | sum error = [ 9.2691, 9.8240, 10.4281, 11.0487, 11.7095] +24-11-19 18:50:29 | D | best error = [ 0.8850, 0.8850, 0.8850, 0.8850, 0.8850] +24-11-19 18:50:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:50:29 | D | sum error = [ 12.4024, 13.1275, 13.8908, 14.6910, 15.5339] +24-11-19 18:50:29 | D | best error = [ 0.8850, 0.8850, 0.8850, 0.8850, 0.8850] +24-11-19 18:50:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:50:29 | D | sum error = [ 16.4191, 17.3479, 18.3219, 19.3400, 20.4082] +24-11-19 18:50:29 | D | best error = [ 0.8850, 0.8850, 0.8850, 0.8850, 0.8850] +24-11-19 18:50:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:50:29 | D | sum error = [ 21.5172, 22.6809, 23.8931, 25.1673, 26.4874] +24-11-19 18:50:29 | D | best error = [ 0.8850, 0.8850, 0.8850, 0.8850, 0.8850] +24-11-19 18:50:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:50:29 | D | sum error = [ 27.8733, 29.3124, 30.8161, 32.3774, 34.0150] +24-11-19 18:50:29 | D | best error = [ 0.8850, 0.8850, 0.8850, 0.8850, 0.8850] +24-11-19 18:50:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:50:29 | D | sum error = [ 35.7089, 37.4731, 39.3028, 41.2053, 43.1681] +24-11-19 18:50:29 | D | best error = [ 0.8850, 0.8850, 0.8850, 0.8850, 0.8850] +24-11-19 18:50:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:50:29 | D | sum error = [ 45.2112, 47.3153, 49.5047, 51.7682, 54.1000] +24-11-19 18:50:29 | D | best error = [ 0.8850, 0.8850, 0.8850, 0.8850, 0.8850] +24-11-19 18:50:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:50:29 | D | sum error = [ 56.5213, 59.0153, 61.5929, 64.2504, 66.9856] +24-11-19 18:50:29 | D | best error = [ 0.8850, 0.8850, 0.8850, 0.8850, 0.8850] +24-11-19 18:50:29 | D | + error = [0.8850] +24-11-19 18:50:29 | D | - Calibrating model.layers.5.self_attn.o_proj.weight +24-11-19 18:50:29 | D | + w: sint8 +24-11-19 18:50:29 | D | + x: None +24-11-19 18:50:29 | D | + y: None +24-11-19 18:50:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:50:29 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:50:29 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:50:29 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:50:29 | D | - range ratio = [ 1.0000] +24-11-19 18:50:29 | D | sum error = [ 0.2897] +24-11-19 18:50:29 | D | best error = [ 0.2897] +24-11-19 18:50:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:50:29 | D | sum error = [ 0.2875, 0.2868, 0.2866, 0.2898, 0.2925] +24-11-19 18:50:29 | D | best error = [ 0.2659, 0.2556, 0.2493, 0.2453, 0.2425] +24-11-19 18:50:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:50:29 | D | sum error = [ 0.2993, 0.3056, 0.3168, 0.3281, 0.3434] +24-11-19 18:50:29 | D | best error = [ 0.2406, 0.2393, 0.2385, 0.2378, 0.2374] +24-11-19 18:50:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:50:29 | D | sum error = [ 0.3585, 0.3782, 0.3980, 0.4194, 0.4461] +24-11-19 18:50:29 | D | best error = [ 0.2371, 0.2369, 0.2368, 0.2367, 0.2366] +24-11-19 18:50:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:50:29 | D | sum error = [ 0.4731, 0.5006, 0.5320, 0.5664, 0.6014] +24-11-19 18:50:29 | D | best error = [ 0.2366, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 18:50:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:50:29 | D | sum error = [ 0.6403, 0.6803, 0.7235, 0.7705, 0.8181] +24-11-19 18:50:29 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 18:50:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:50:29 | D | sum error = [ 0.8684, 0.9218, 0.9799, 1.0391, 1.1031] +24-11-19 18:50:29 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 18:50:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:50:29 | D | sum error = [ 1.1676, 1.2365, 1.3110, 1.3864, 1.4684] +24-11-19 18:50:29 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 18:50:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:50:29 | D | sum error = [ 1.5532, 1.6416, 1.7354, 1.8317, 1.9357] +24-11-19 18:50:29 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 18:50:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:50:29 | D | sum error = [ 2.0425, 2.1546, 2.2726, 2.3962, 2.5254] +24-11-19 18:50:29 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 18:50:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:50:29 | D | sum error = [ 2.6604, 2.8013, 2.9487, 3.1041, 3.2668] +24-11-19 18:50:29 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 18:50:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:50:29 | D | sum error = [ 3.4362, 3.6131, 3.7995, 3.9935, 4.1962] +24-11-19 18:50:29 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 18:50:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:50:29 | D | sum error = [ 4.4072, 4.6287, 4.8578, 5.0955, 5.3437] +24-11-19 18:50:29 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 18:50:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:50:29 | D | sum error = [ 5.6021, 5.8708, 6.1488, 6.4382, 6.7386] +24-11-19 18:50:29 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 18:50:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:50:29 | D | sum error = [ 7.0513, 7.3754, 7.7104, 8.0585, 8.4180] +24-11-19 18:50:29 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 18:50:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:50:29 | D | sum error = [ 8.7913, 9.1774, 9.5773, 9.9928, 10.4220] +24-11-19 18:50:29 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 18:50:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:50:29 | D | sum error = [ 10.8659, 11.3251, 11.7998, 12.2903, 12.7971] +24-11-19 18:50:29 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 18:50:29 | D | + error = [0.2365] +24-11-19 18:50:29 | D | - Calibrating model.layers.5.mlp.up_proj.weight +24-11-19 18:50:29 | D | + w: sint8 +24-11-19 18:50:29 | D | + x: None +24-11-19 18:50:29 | D | + y: None +24-11-19 18:50:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:50:29 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:50:29 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:50:29 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:50:30 | D | - range ratio = [ 1.0000] +24-11-19 18:50:30 | D | sum error = [ 4.4835] +24-11-19 18:50:30 | D | best error = [ 4.4835] +24-11-19 18:50:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:50:31 | D | sum error = [ 4.4296, 4.4432, 4.4538, 4.4915, 4.5817] +24-11-19 18:50:31 | D | best error = [ 4.1859, 4.0784, 4.0202, 3.9870, 3.9701] +24-11-19 18:50:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:50:31 | D | sum error = [ 4.6996, 4.8572, 5.0468, 5.2860, 5.5556] +24-11-19 18:50:31 | D | best error = [ 3.9621, 3.9586, 3.9576, 3.9573, 3.9572] +24-11-19 18:50:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:50:31 | D | sum error = [ 5.8674, 6.2452, 6.6416, 7.0830, 7.5658] +24-11-19 18:50:31 | D | best error = [ 3.9572, 3.9572, 3.9572, 3.9572, 3.9572] +24-11-19 18:50:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:50:31 | D | sum error = [ 8.1035, 8.6712, 9.2791, 9.9441, 10.6449] +24-11-19 18:50:31 | D | best error = [ 3.9572, 3.9572, 3.9572, 3.9572, 3.9572] +24-11-19 18:50:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:50:31 | D | sum error = [ 11.4114, 12.2051, 13.0636, 13.9665, 14.9325] +24-11-19 18:50:31 | D | best error = [ 3.9572, 3.9572, 3.9572, 3.9572, 3.9572] +24-11-19 18:50:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:50:31 | D | sum error = [ 15.9642, 17.0384, 18.1930, 19.4042, 20.6869] +24-11-19 18:50:31 | D | best error = [ 3.9572, 3.9572, 3.9572, 3.9572, 3.9572] +24-11-19 18:50:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:50:31 | D | sum error = [ 22.0293, 23.4578, 24.9634, 26.5502, 28.2242] +24-11-19 18:50:31 | D | best error = [ 3.9572, 3.9572, 3.9572, 3.9572, 3.9572] +24-11-19 18:50:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:50:31 | D | sum error = [ 29.9743, 31.8221, 33.7587, 35.8043, 37.9417] +24-11-19 18:50:31 | D | best error = [ 3.9572, 3.9572, 3.9572, 3.9572, 3.9572] +24-11-19 18:50:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:50:31 | D | sum error = [ 40.1805, 42.5377, 45.0027, 47.5841, 50.2884] +24-11-19 18:50:31 | D | best error = [ 3.9572, 3.9572, 3.9572, 3.9572, 3.9572] +24-11-19 18:50:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:50:31 | D | sum error = [ 53.1228, 56.0695, 59.1724, 62.4035, 65.7716] +24-11-19 18:50:31 | D | best error = [ 3.9572, 3.9572, 3.9572, 3.9572, 3.9572] +24-11-19 18:50:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:50:31 | D | sum error = [ 69.2913, 72.9595, 76.7916, 80.7708, 84.9218] +24-11-19 18:50:31 | D | best error = [ 3.9572, 3.9572, 3.9572, 3.9572, 3.9572] +24-11-19 18:50:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:50:31 | D | sum error = [ 89.2351, 93.7337, 98.4066, 103.2592, 108.3026] +24-11-19 18:50:31 | D | best error = [ 3.9572, 3.9572, 3.9572, 3.9572, 3.9572] +24-11-19 18:50:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:50:31 | D | sum error = [ 113.5285, 118.9537, 124.5640, 130.3860, 136.4151] +24-11-19 18:50:31 | D | best error = [ 3.9572, 3.9572, 3.9572, 3.9572, 3.9572] +24-11-19 18:50:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:50:31 | D | sum error = [ 142.6509, 149.0963, 155.7785, 162.6752, 169.7918] +24-11-19 18:50:31 | D | best error = [ 3.9572, 3.9572, 3.9572, 3.9572, 3.9572] +24-11-19 18:50:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:50:31 | D | sum error = [ 177.1428, 184.7289, 192.5323, 200.5880, 208.8754] +24-11-19 18:50:31 | D | best error = [ 3.9572, 3.9572, 3.9572, 3.9572, 3.9572] +24-11-19 18:50:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:50:31 | D | sum error = [ 217.4280, 226.2184, 235.2700, 244.5800, 254.1506] +24-11-19 18:50:31 | D | best error = [ 3.9572, 3.9572, 3.9572, 3.9572, 3.9572] +24-11-19 18:50:31 | D | + error = [3.9572] +24-11-19 18:50:31 | D | - Calibrating model.layers.5.mlp.gate_proj.weight +24-11-19 18:50:31 | D | + w: sint8 +24-11-19 18:50:31 | D | + x: None +24-11-19 18:50:31 | D | + y: None +24-11-19 18:50:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:50:31 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:50:31 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:50:31 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:50:31 | D | - range ratio = [ 1.0000] +24-11-19 18:50:31 | D | sum error = [ 5.8952] +24-11-19 18:50:31 | D | best error = [ 5.8952] +24-11-19 18:50:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:50:32 | D | sum error = [ 5.8588, 5.8435, 5.8619, 5.9249, 6.0496] +24-11-19 18:50:32 | D | best error = [ 5.5166, 5.3717, 5.2952, 5.2503, 5.2285] +24-11-19 18:50:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:50:32 | D | sum error = [ 6.2003, 6.4092, 6.6709, 6.9730, 7.3502] +24-11-19 18:50:32 | D | best error = [ 5.2189, 5.2144, 5.2134, 5.2131, 5.2131] +24-11-19 18:50:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:50:32 | D | sum error = [ 7.7802, 8.2689, 8.7929, 9.3940, 10.0414] +24-11-19 18:50:32 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 18:50:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:50:32 | D | sum error = [ 10.7527, 11.5324, 12.3634, 13.2523, 14.2210] +24-11-19 18:50:32 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 18:50:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:50:32 | D | sum error = [ 15.2586, 16.3515, 17.5426, 18.7957, 20.1324] +24-11-19 18:50:32 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 18:50:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:50:32 | D | sum error = [ 21.5500, 23.0594, 24.6702, 26.3764, 28.1796] +24-11-19 18:50:32 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 18:50:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:50:32 | D | sum error = [ 30.0817, 32.1203, 34.2573, 36.5255, 38.9358] +24-11-19 18:50:32 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 18:50:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:50:32 | D | sum error = [ 41.4822, 44.1633, 47.0024, 50.0169, 53.1954] +24-11-19 18:50:32 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 18:50:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:50:32 | D | sum error = [ 56.5626, 60.1217, 63.8759, 67.8484, 72.0171] +24-11-19 18:50:32 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 18:50:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:50:32 | D | sum error = [ 76.4412, 81.1111, 86.0155, 91.2037, 96.6456] +24-11-19 18:50:32 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 18:50:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:50:32 | D | sum error = [ 102.4077, 108.4404, 114.8111, 121.5281, 128.5539] +24-11-19 18:50:32 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 18:50:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:50:32 | D | sum error = [ 135.9608, 143.7146, 151.8728, 160.4018, 169.3447] +24-11-19 18:50:32 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 18:50:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:50:32 | D | sum error = [ 178.7246, 188.5375, 198.7988, 209.5440, 220.7658] +24-11-19 18:50:32 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 18:50:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:50:32 | D | sum error = [ 232.4653, 244.6641, 257.3853, 270.6631, 284.4643] +24-11-19 18:50:32 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 18:50:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:50:32 | D | sum error = [ 298.8109, 313.7125, 329.2012, 345.2363, 361.8442] +24-11-19 18:50:32 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 18:50:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:50:32 | D | sum error = [ 379.0455, 396.7981, 415.1367, 434.0557, 453.5674] +24-11-19 18:50:32 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 18:50:32 | D | + error = [5.2131] +24-11-19 18:50:32 | D | - Calibrating model.layers.5.mlp.down_proj.weight +24-11-19 18:50:32 | D | + w: sint8 +24-11-19 18:50:32 | D | + x: None +24-11-19 18:50:32 | D | + y: None +24-11-19 18:50:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:50:32 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:50:32 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:50:32 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:50:32 | D | - range ratio = [ 1.0000] +24-11-19 18:50:32 | D | sum error = [ 0.4632] +24-11-19 18:50:32 | D | best error = [ 0.4632] +24-11-19 18:50:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:50:34 | D | sum error = [ 0.4583, 0.4555, 0.4528, 0.4524, 0.4521] +24-11-19 18:50:34 | D | best error = [ 0.4462, 0.4376, 0.4317, 0.4274, 0.4240] +24-11-19 18:50:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:50:34 | D | sum error = [ 0.4550, 0.4578, 0.4633, 0.4711, 0.4809] +24-11-19 18:50:34 | D | best error = [ 0.4215, 0.4196, 0.4179, 0.4168, 0.4160] +24-11-19 18:50:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:50:34 | D | sum error = [ 0.4947, 0.5096, 0.5273, 0.5487, 0.5717] +24-11-19 18:50:34 | D | best error = [ 0.4155, 0.4151, 0.4149, 0.4147, 0.4146] +24-11-19 18:50:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:50:34 | D | sum error = [ 0.6009, 0.6317, 0.6670, 0.7054, 0.7477] +24-11-19 18:50:34 | D | best error = [ 0.4146, 0.4145, 0.4145, 0.4145, 0.4145] +24-11-19 18:50:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:50:34 | D | sum error = [ 0.7937, 0.8448, 0.8999, 0.9614, 1.0254] +24-11-19 18:50:34 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 18:50:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:50:34 | D | sum error = [ 1.0949, 1.1684, 1.2492, 1.3341, 1.4255] +24-11-19 18:50:34 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 18:50:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:50:34 | D | sum error = [ 1.5224, 1.6265, 1.7377, 1.8541, 1.9790] +24-11-19 18:50:34 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 18:50:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:50:34 | D | sum error = [ 2.1116, 2.2521, 2.4018, 2.5597, 2.7275] +24-11-19 18:50:34 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 18:50:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:50:34 | D | sum error = [ 2.9048, 3.0922, 3.2907, 3.5011, 3.7226] +24-11-19 18:50:34 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 18:50:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:50:34 | D | sum error = [ 3.9570, 4.2033, 4.4628, 4.7361, 5.0243] +24-11-19 18:50:34 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 18:50:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:50:34 | D | sum error = [ 5.3273, 5.6452, 5.9798, 6.3317, 6.7009] +24-11-19 18:50:34 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 18:50:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:50:34 | D | sum error = [ 7.0886, 7.4945, 7.9192, 8.3638, 8.8295] +24-11-19 18:50:34 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 18:50:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:50:34 | D | sum error = [ 9.3159, 9.8248, 10.3573, 10.9132, 11.4935] +24-11-19 18:50:34 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 18:50:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:50:34 | D | sum error = [ 12.0973, 12.7263, 13.3813, 14.0634, 14.7708] +24-11-19 18:50:34 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 18:50:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:50:34 | D | sum error = [ 15.5072, 16.2717, 17.0651, 17.8877, 18.7400] +24-11-19 18:50:34 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 18:50:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:50:34 | D | sum error = [ 19.6233, 20.5374, 21.4833, 22.4610, 23.4710] +24-11-19 18:50:34 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 18:50:34 | D | + error = [0.4144] +24-11-19 18:50:34 | D | - Quantizing model.layers.5.self_attn.q_proj.weight +24-11-19 18:50:35 | D | - Quantizing model.layers.5.self_attn.k_proj.weight +24-11-19 18:50:35 | D | - Quantizing model.layers.5.self_attn.v_proj.weight +24-11-19 18:50:36 | D | - Quantizing model.layers.5.self_attn.o_proj.weight +24-11-19 18:50:37 | D | - Quantizing model.layers.5.mlp.up_proj.weight +24-11-19 18:50:38 | D | - Quantizing model.layers.5.mlp.gate_proj.weight +24-11-19 18:50:39 | D | - Quantizing model.layers.5.mlp.down_proj.weight +24-11-19 18:50:48 | D | - Quantizing layer model.layers.6 +24-11-19 18:50:48 | D | - Calibrating model.layers.6.self_attn.q_proj.weight +24-11-19 18:50:48 | D | + w: sint8 +24-11-19 18:50:48 | D | + x: None +24-11-19 18:50:48 | D | + y: None +24-11-19 18:50:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:50:48 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:50:48 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:50:49 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:50:49 | D | - range ratio = [ 1.0000] +24-11-19 18:50:49 | D | sum error = [ 2.4387] +24-11-19 18:50:49 | D | best error = [ 2.4387] +24-11-19 18:51:00 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:51:00 | D | sum error = [ 2.3927, 2.3965, 2.4891, 2.4171, 2.5453] +24-11-19 18:51:00 | D | best error = [ 2.3927, 2.3927, 2.3927, 2.3927, 2.3927] +24-11-19 18:51:00 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:51:00 | D | sum error = [ 2.5632, 2.7533, 2.8179, 2.8897, 3.0653] +24-11-19 18:51:00 | D | best error = [ 2.3927, 2.3927, 2.3927, 2.3927, 2.3927] +24-11-19 18:51:00 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:51:00 | D | sum error = [ 3.2225, 3.5490, 3.7818, 4.1697, 4.4296] +24-11-19 18:51:00 | D | best error = [ 2.3927, 2.3927, 2.3927, 2.3927, 2.3927] +24-11-19 18:51:00 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:51:00 | D | sum error = [ 4.8512, 5.1731, 5.6938, 6.1607, 6.6643] +24-11-19 18:51:00 | D | best error = [ 2.3927, 2.3927, 2.3927, 2.3927, 2.3927] +24-11-19 18:51:00 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:51:00 | D | sum error = [ 7.3038, 7.9417, 8.7912, 9.4925, 10.3231] +24-11-19 18:51:00 | D | best error = [ 2.3927, 2.3927, 2.3927, 2.3927, 2.3927] +24-11-19 18:51:00 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:51:00 | D | sum error = [ 11.3363, 12.2333, 13.3068, 14.3740, 15.7442] +24-11-19 18:51:00 | D | best error = [ 2.3927, 2.3927, 2.3927, 2.3927, 2.3927] +24-11-19 18:51:00 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:51:00 | D | sum error = [ 16.9532, 18.5101, 19.8948, 21.6102, 23.3376] +24-11-19 18:51:00 | D | best error = [ 2.3927, 2.3927, 2.3927, 2.3927, 2.3927] +24-11-19 18:51:00 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:51:00 | D | sum error = [ 25.2405, 27.2846, 29.5400, 31.8860, 34.4628] +24-11-19 18:51:00 | D | best error = [ 2.3927, 2.3927, 2.3927, 2.3927, 2.3927] +24-11-19 18:51:00 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:51:00 | D | sum error = [ 37.0586, 40.0615, 43.0387, 46.2370, 49.7954] +24-11-19 18:51:00 | D | best error = [ 2.3927, 2.3927, 2.3927, 2.3927, 2.3927] +24-11-19 18:51:00 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:51:00 | D | sum error = [ 53.4247, 57.2927, 61.3071, 65.8399, 70.5732] +24-11-19 18:51:00 | D | best error = [ 2.3927, 2.3927, 2.3927, 2.3927, 2.3927] +24-11-19 18:51:00 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:51:00 | D | sum error = [ 75.4918, 80.6749, 86.3129, 92.2319, 98.6045] +24-11-19 18:51:00 | D | best error = [ 2.3927, 2.3927, 2.3927, 2.3927, 2.3927] +24-11-19 18:51:00 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:51:00 | D | sum error = [ 105.4909, 112.6437, 120.3088, 128.4948, 137.0932] +24-11-19 18:51:00 | D | best error = [ 2.3927, 2.3927, 2.3927, 2.3927, 2.3927] +24-11-19 18:51:00 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:51:00 | D | sum error = [ 146.3338, 156.1922, 166.5677, 177.7480, 189.3948] +24-11-19 18:51:00 | D | best error = [ 2.3927, 2.3927, 2.3927, 2.3927, 2.3927] +24-11-19 18:51:00 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:51:00 | D | sum error = [ 201.8243, 215.0628, 228.8449, 243.4253, 259.0399] +24-11-19 18:51:00 | D | best error = [ 2.3927, 2.3927, 2.3927, 2.3927, 2.3927] +24-11-19 18:51:00 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:51:00 | D | sum error = [ 275.4223, 292.6241, 310.7396, 329.5729, 349.2627] +24-11-19 18:51:00 | D | best error = [ 2.3927, 2.3927, 2.3927, 2.3927, 2.3927] +24-11-19 18:51:00 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:51:00 | D | sum error = [ 369.6569, 390.7271, 412.4473, 434.5909, 457.2742] +24-11-19 18:51:00 | D | best error = [ 2.3927, 2.3927, 2.3927, 2.3927, 2.3927] +24-11-19 18:51:00 | D | + error = [2.3927] +24-11-19 18:51:00 | D | - Calibrating model.layers.6.self_attn.k_proj.weight +24-11-19 18:51:00 | D | + w: sint8 +24-11-19 18:51:00 | D | + x: None +24-11-19 18:51:00 | D | + y: None +24-11-19 18:51:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:51:00 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:51:00 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:51:01 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:51:01 | D | - range ratio = [ 1.0000] +24-11-19 18:51:01 | D | sum error = [ 2.1934] +24-11-19 18:51:01 | D | best error = [ 2.1934] +24-11-19 18:51:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:51:12 | D | sum error = [ 2.3776, 2.3656, 2.3760, 2.4788, 2.6241] +24-11-19 18:51:12 | D | best error = [ 2.1934, 2.1934, 2.1934, 2.1934, 2.1934] +24-11-19 18:51:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:51:12 | D | sum error = [ 2.4477, 3.0336, 2.7388, 2.9050, 3.0362] +24-11-19 18:51:12 | D | best error = [ 2.1934, 2.1934, 2.1934, 2.1934, 2.1934] +24-11-19 18:51:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:51:12 | D | sum error = [ 3.4355, 3.6132, 3.7426, 4.0079, 4.8009] +24-11-19 18:51:12 | D | best error = [ 2.1934, 2.1934, 2.1934, 2.1934, 2.1934] +24-11-19 18:51:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:51:12 | D | sum error = [ 4.8189, 5.0886, 5.5230, 6.1531, 6.3471] +24-11-19 18:51:12 | D | best error = [ 2.1934, 2.1934, 2.1934, 2.1934, 2.1934] +24-11-19 18:51:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:51:12 | D | sum error = [ 6.4194, 7.7100, 7.8638, 8.3196, 9.5510] +24-11-19 18:51:12 | D | best error = [ 2.1934, 2.1934, 2.1934, 2.1934, 2.1934] +24-11-19 18:51:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:51:12 | D | sum error = [ 10.2143, 10.6825, 11.6841, 12.7884, 13.6771] +24-11-19 18:51:12 | D | best error = [ 2.1934, 2.1934, 2.1934, 2.1934, 2.1934] +24-11-19 18:51:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:51:12 | D | sum error = [ 15.0462, 16.1404, 17.6225, 18.9574, 20.5987] +24-11-19 18:51:12 | D | best error = [ 2.1934, 2.1934, 2.1934, 2.1934, 2.1934] +24-11-19 18:51:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:51:12 | D | sum error = [ 22.4341, 24.1851, 26.3272, 28.1891, 30.6707] +24-11-19 18:51:12 | D | best error = [ 2.1934, 2.1934, 2.1934, 2.1934, 2.1934] +24-11-19 18:51:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:51:12 | D | sum error = [ 32.6443, 35.6009, 38.1824, 41.2102, 44.8066] +24-11-19 18:51:12 | D | best error = [ 2.1934, 2.1934, 2.1934, 2.1934, 2.1934] +24-11-19 18:51:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:51:12 | D | sum error = [ 48.3541, 52.4011, 56.0904, 60.3169, 64.7892] +24-11-19 18:51:12 | D | best error = [ 2.1934, 2.1934, 2.1934, 2.1934, 2.1934] +24-11-19 18:51:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:51:12 | D | sum error = [ 69.6735, 74.2099, 80.4079, 86.1310, 92.0992] +24-11-19 18:51:12 | D | best error = [ 2.1934, 2.1934, 2.1934, 2.1934, 2.1934] +24-11-19 18:51:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:51:12 | D | sum error = [ 98.8934, 105.8972, 113.9999, 121.5651, 130.1900] +24-11-19 18:51:12 | D | best error = [ 2.1934, 2.1934, 2.1934, 2.1934, 2.1934] +24-11-19 18:51:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:51:12 | D | sum error = [ 139.0477, 149.8431, 159.1655, 171.1356, 183.3393] +24-11-19 18:51:12 | D | best error = [ 2.1934, 2.1934, 2.1934, 2.1934, 2.1934] +24-11-19 18:51:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:51:12 | D | sum error = [ 195.6888, 209.0863, 223.0189, 239.1600, 254.8618] +24-11-19 18:51:12 | D | best error = [ 2.1934, 2.1934, 2.1934, 2.1934, 2.1934] +24-11-19 18:51:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:51:12 | D | sum error = [ 272.4194, 289.4477, 308.9898, 328.7755, 348.0312] +24-11-19 18:51:12 | D | best error = [ 2.1934, 2.1934, 2.1934, 2.1934, 2.1934] +24-11-19 18:51:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:51:12 | D | sum error = [ 370.3496, 391.5896, 414.6023, 436.4967, 459.8174] +24-11-19 18:51:12 | D | best error = [ 2.1934, 2.1934, 2.1934, 2.1934, 2.1934] +24-11-19 18:51:12 | D | + error = [2.1934] +24-11-19 18:51:12 | D | - Calibrating model.layers.6.self_attn.v_proj.weight +24-11-19 18:51:12 | D | + w: sint8 +24-11-19 18:51:12 | D | + x: None +24-11-19 18:51:12 | D | + y: None +24-11-19 18:51:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:51:12 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:51:12 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:51:12 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:51:12 | D | - range ratio = [ 1.0000] +24-11-19 18:51:12 | D | sum error = [ 1.1028] +24-11-19 18:51:12 | D | best error = [ 1.1028] +24-11-19 18:51:13 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:51:13 | D | sum error = [ 1.0957, 1.0915, 1.1007, 1.1122, 1.1424] +24-11-19 18:51:13 | D | best error = [ 1.0285, 0.9992, 0.9848, 0.9777, 0.9747] +24-11-19 18:51:13 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:51:13 | D | sum error = [ 1.1567, 1.1925, 1.2335, 1.2966, 1.3712] +24-11-19 18:51:13 | D | best error = [ 0.9729, 0.9724, 0.9719, 0.9718, 0.9717] +24-11-19 18:51:13 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:51:13 | D | sum error = [ 1.4550, 1.5435, 1.6493, 1.7468, 1.8753] +24-11-19 18:51:13 | D | best error = [ 0.9717, 0.9717, 0.9717, 0.9717, 0.9717] +24-11-19 18:51:13 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:51:13 | D | sum error = [ 2.0071, 2.1595, 2.3008, 2.4727, 2.6496] +24-11-19 18:51:13 | D | best error = [ 0.9717, 0.9717, 0.9717, 0.9717, 0.9717] +24-11-19 18:51:13 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:51:13 | D | sum error = [ 2.8290, 3.0311, 3.2430, 3.4693, 3.7042] +24-11-19 18:51:13 | D | best error = [ 0.9717, 0.9717, 0.9717, 0.9717, 0.9717] +24-11-19 18:51:13 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:51:13 | D | sum error = [ 3.9608, 4.2310, 4.5137, 4.8199, 5.1323] +24-11-19 18:51:13 | D | best error = [ 0.9717, 0.9717, 0.9717, 0.9717, 0.9717] +24-11-19 18:51:13 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:51:13 | D | sum error = [ 5.4729, 5.8235, 6.2010, 6.6021, 7.0158] +24-11-19 18:51:13 | D | best error = [ 0.9717, 0.9717, 0.9717, 0.9717, 0.9717] +24-11-19 18:51:13 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:51:13 | D | sum error = [ 7.4625, 7.9123, 8.4073, 8.9199, 9.4699] +24-11-19 18:51:13 | D | best error = [ 0.9717, 0.9717, 0.9717, 0.9717, 0.9717] +24-11-19 18:51:13 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:51:13 | D | sum error = [ 10.0319, 10.6439, 11.2715, 11.9378, 12.6385] +24-11-19 18:51:13 | D | best error = [ 0.9717, 0.9717, 0.9717, 0.9717, 0.9717] +24-11-19 18:51:13 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:51:13 | D | sum error = [ 13.3784, 14.1471, 14.9640, 15.8142, 16.7033] +24-11-19 18:51:13 | D | best error = [ 0.9717, 0.9717, 0.9717, 0.9717, 0.9717] +24-11-19 18:51:13 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:51:13 | D | sum error = [ 17.6405, 18.6223, 19.6393, 20.7172, 21.8291] +24-11-19 18:51:13 | D | best error = [ 0.9717, 0.9717, 0.9717, 0.9717, 0.9717] +24-11-19 18:51:13 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:51:13 | D | sum error = [ 23.0082, 24.2281, 25.5064, 26.8482, 28.2398] +24-11-19 18:51:13 | D | best error = [ 0.9717, 0.9717, 0.9717, 0.9717, 0.9717] +24-11-19 18:51:13 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:51:13 | D | sum error = [ 29.6964, 31.2190, 32.7921, 34.4423, 36.1520] +24-11-19 18:51:13 | D | best error = [ 0.9717, 0.9717, 0.9717, 0.9717, 0.9717] +24-11-19 18:51:13 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:51:13 | D | sum error = [ 37.9292, 39.7692, 41.6833, 43.6622, 45.7145] +24-11-19 18:51:13 | D | best error = [ 0.9717, 0.9717, 0.9717, 0.9717, 0.9717] +24-11-19 18:51:13 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:51:13 | D | sum error = [ 47.8500, 50.0513, 52.3322, 54.6946, 57.1376] +24-11-19 18:51:13 | D | best error = [ 0.9717, 0.9717, 0.9717, 0.9717, 0.9717] +24-11-19 18:51:13 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:51:13 | D | sum error = [ 59.6512, 62.2523, 64.9285, 67.6874, 70.5326] +24-11-19 18:51:13 | D | best error = [ 0.9717, 0.9717, 0.9717, 0.9717, 0.9717] +24-11-19 18:51:13 | D | + error = [0.9717] +24-11-19 18:51:13 | D | - Calibrating model.layers.6.self_attn.o_proj.weight +24-11-19 18:51:13 | D | + w: sint8 +24-11-19 18:51:13 | D | + x: None +24-11-19 18:51:13 | D | + y: None +24-11-19 18:51:13 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:51:13 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:51:13 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:51:13 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:51:13 | D | - range ratio = [ 1.0000] +24-11-19 18:51:13 | D | sum error = [ 0.3657] +24-11-19 18:51:13 | D | best error = [ 0.3657] +24-11-19 18:51:13 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:51:13 | D | sum error = [ 0.3632, 0.3644, 0.3643, 0.3695, 0.3754] +24-11-19 18:51:13 | D | best error = [ 0.3373, 0.3256, 0.3186, 0.3142, 0.3114] +24-11-19 18:51:13 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:51:13 | D | sum error = [ 0.3849, 0.3964, 0.4123, 0.4311, 0.4512] +24-11-19 18:51:13 | D | best error = [ 0.3099, 0.3088, 0.3082, 0.3076, 0.3073] +24-11-19 18:51:13 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:51:13 | D | sum error = [ 0.4776, 0.5028, 0.5314, 0.5618, 0.6004] +24-11-19 18:51:13 | D | best error = [ 0.3070, 0.3068, 0.3066, 0.3065, 0.3064] +24-11-19 18:51:13 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:51:13 | D | sum error = [ 0.6388, 0.6786, 0.7214, 0.7687, 0.8186] +24-11-19 18:51:13 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 18:51:13 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:51:13 | D | sum error = [ 0.8699, 0.9265, 0.9853, 1.0466, 1.1118] +24-11-19 18:51:13 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 18:51:13 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:51:13 | D | sum error = [ 1.1816, 1.2511, 1.3273, 1.4066, 1.4905] +24-11-19 18:51:13 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 18:51:13 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:51:13 | D | sum error = [ 1.5768, 1.6684, 1.7645, 1.8650, 1.9705] +24-11-19 18:51:13 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 18:51:13 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:51:13 | D | sum error = [ 2.0795, 2.1948, 2.3160, 2.4401, 2.5726] +24-11-19 18:51:13 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 18:51:13 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:51:13 | D | sum error = [ 2.7096, 2.8545, 3.0061, 3.1644, 3.3294] +24-11-19 18:51:13 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 18:51:13 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:51:13 | D | sum error = [ 3.5035, 3.6842, 3.8733, 4.0717, 4.2773] +24-11-19 18:51:13 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 18:51:13 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:51:13 | D | sum error = [ 4.4927, 4.7169, 4.9498, 5.1919, 5.4448] +24-11-19 18:51:13 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 18:51:13 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:51:13 | D | sum error = [ 5.7068, 5.9800, 6.2653, 6.5606, 6.8688] +24-11-19 18:51:13 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 18:51:13 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:51:13 | D | sum error = [ 7.1897, 7.5221, 7.8670, 8.2251, 8.5959] +24-11-19 18:51:13 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 18:51:13 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:51:13 | D | sum error = [ 8.9815, 9.3797, 9.7935, 10.2221, 10.6637] +24-11-19 18:51:13 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 18:51:13 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:51:13 | D | sum error = [ 11.1228, 11.5963, 12.0858, 12.5922, 13.1160] +24-11-19 18:51:13 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 18:51:13 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:51:13 | D | sum error = [ 13.6574, 14.2168, 14.7948, 15.3920, 16.0085] +24-11-19 18:51:13 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 18:51:13 | D | + error = [0.3064] +24-11-19 18:51:13 | D | - Calibrating model.layers.6.mlp.up_proj.weight +24-11-19 18:51:13 | D | + w: sint8 +24-11-19 18:51:13 | D | + x: None +24-11-19 18:51:13 | D | + y: None +24-11-19 18:51:13 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:51:13 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:51:13 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:51:14 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:51:14 | D | - range ratio = [ 1.0000] +24-11-19 18:51:14 | D | sum error = [ 4.6048] +24-11-19 18:51:14 | D | best error = [ 4.6048] +24-11-19 18:51:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:51:15 | D | sum error = [ 4.5751, 4.5580, 4.5794, 4.6401, 4.7251] +24-11-19 18:51:15 | D | best error = [ 4.3022, 4.1883, 4.1246, 4.0898, 4.0725] +24-11-19 18:51:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:51:15 | D | sum error = [ 4.8312, 4.9963, 5.2097, 5.4389, 5.7219] +24-11-19 18:51:15 | D | best error = [ 4.0634, 4.0602, 4.0591, 4.0587, 4.0586] +24-11-19 18:51:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:51:15 | D | sum error = [ 6.0576, 6.4312, 6.8528, 7.3134, 7.8158] +24-11-19 18:51:15 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 18:51:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:51:15 | D | sum error = [ 8.3581, 8.9582, 9.5980, 10.2743, 11.0164] +24-11-19 18:51:15 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 18:51:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:51:15 | D | sum error = [ 11.7991, 12.6288, 13.5297, 14.4737, 15.4769] +24-11-19 18:51:15 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 18:51:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:51:15 | D | sum error = [ 16.5437, 17.6615, 18.8577, 20.1142, 21.4433] +24-11-19 18:51:15 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 18:51:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:51:15 | D | sum error = [ 22.8483, 24.3300, 25.9015, 27.5468, 29.2706] +24-11-19 18:51:15 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 18:51:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:51:15 | D | sum error = [ 31.1017, 33.0176, 35.0289, 37.1580, 39.3904] +24-11-19 18:51:15 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 18:51:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:51:15 | D | sum error = [ 41.7212, 44.1767, 46.7497, 49.4545, 52.2793] +24-11-19 18:51:15 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 18:51:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:51:15 | D | sum error = [ 55.2353, 58.3297, 61.5646, 64.9538, 68.5032] +24-11-19 18:51:15 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 18:51:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:51:15 | D | sum error = [ 72.1967, 76.0594, 80.0946, 84.3044, 88.6975] +24-11-19 18:51:15 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 18:51:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:51:15 | D | sum error = [ 93.2652, 98.0226, 102.9740, 108.1382, 113.4872] +24-11-19 18:51:15 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 18:51:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:51:15 | D | sum error = [ 119.0551, 124.8396, 130.8429, 137.0711, 143.5290] +24-11-19 18:51:15 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 18:51:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:51:15 | D | sum error = [ 150.2348, 157.1655, 164.3636, 171.8044, 179.4999] +24-11-19 18:51:15 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 18:51:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:51:15 | D | sum error = [ 187.4450, 195.6493, 204.1088, 212.8559, 221.8642] +24-11-19 18:51:15 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 18:51:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:51:15 | D | sum error = [ 231.1573, 240.7254, 250.5824, 260.7121, 271.1350] +24-11-19 18:51:15 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 18:51:15 | D | + error = [4.0586] +24-11-19 18:51:15 | D | - Calibrating model.layers.6.mlp.gate_proj.weight +24-11-19 18:51:15 | D | + w: sint8 +24-11-19 18:51:15 | D | + x: None +24-11-19 18:51:15 | D | + y: None +24-11-19 18:51:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:51:15 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:51:15 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:51:15 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:51:15 | D | - range ratio = [ 1.0000] +24-11-19 18:51:15 | D | sum error = [ 6.1107] +24-11-19 18:51:15 | D | best error = [ 6.1107] +24-11-19 18:51:16 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:51:16 | D | sum error = [ 6.0622, 6.0486, 6.0677, 6.1399, 6.2553] +24-11-19 18:51:16 | D | best error = [ 5.7027, 5.5489, 5.4699, 5.4240, 5.4018] +24-11-19 18:51:16 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:51:16 | D | sum error = [ 6.4338, 6.6374, 6.9192, 7.2440, 7.6375] +24-11-19 18:51:16 | D | best error = [ 5.3908, 5.3863, 5.3852, 5.3847, 5.3846] +24-11-19 18:51:16 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:51:16 | D | sum error = [ 8.0797, 8.5823, 9.1400, 9.7949, 10.4627] +24-11-19 18:51:16 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 18:51:16 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:51:16 | D | sum error = [ 11.2296, 12.0336, 12.9127, 13.8543, 14.8838] +24-11-19 18:51:16 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 18:51:16 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:51:16 | D | sum error = [ 15.9821, 17.1479, 18.3855, 19.7277, 21.1393] +24-11-19 18:51:16 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 18:51:16 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:51:16 | D | sum error = [ 22.6416, 24.2584, 25.9560, 27.7583, 29.6805] +24-11-19 18:51:16 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 18:51:16 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:51:16 | D | sum error = [ 31.7298, 33.9134, 36.1994, 38.6388, 41.2393] +24-11-19 18:51:16 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 18:51:16 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:51:16 | D | sum error = [ 43.9905, 46.8854, 49.9794, 53.2406, 56.7033] +24-11-19 18:51:16 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 18:51:16 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:51:16 | D | sum error = [ 60.3784, 64.2663, 68.3710, 72.7398, 77.3368] +24-11-19 18:51:16 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 18:51:16 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:51:16 | D | sum error = [ 82.2104, 87.3825, 92.8332, 98.5993, 104.6895] +24-11-19 18:51:16 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 18:51:16 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:51:16 | D | sum error = [ 111.1076, 117.8935, 125.0377, 132.5804, 140.5079] +24-11-19 18:51:16 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 18:51:16 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:51:16 | D | sum error = [ 148.8487, 157.6312, 166.8876, 176.5952, 186.7930] +24-11-19 18:51:16 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 18:51:16 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:51:16 | D | sum error = [ 197.4965, 208.7061, 220.4482, 232.7421, 245.6060] +24-11-19 18:51:16 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 18:51:16 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:51:16 | D | sum error = [ 259.0374, 273.0669, 287.7073, 302.9660, 318.8660] +24-11-19 18:51:16 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 18:51:16 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:51:16 | D | sum error = [ 335.4081, 352.5926, 370.4426, 388.9548, 408.1235] +24-11-19 18:51:16 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 18:51:16 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:51:16 | D | sum error = [ 427.9944, 448.5497, 469.7912, 491.7075, 514.3044] +24-11-19 18:51:16 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 18:51:16 | D | + error = [5.3846] +24-11-19 18:51:16 | D | - Calibrating model.layers.6.mlp.down_proj.weight +24-11-19 18:51:16 | D | + w: sint8 +24-11-19 18:51:16 | D | + x: None +24-11-19 18:51:16 | D | + y: None +24-11-19 18:51:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:51:16 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:51:16 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:51:16 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:51:17 | D | - range ratio = [ 1.0000] +24-11-19 18:51:17 | D | sum error = [ 0.5203] +24-11-19 18:51:17 | D | best error = [ 0.5203] +24-11-19 18:51:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:51:18 | D | sum error = [ 0.5157, 0.5110, 0.5083, 0.5064, 0.5061] +24-11-19 18:51:18 | D | best error = [ 0.5010, 0.4908, 0.4842, 0.4790, 0.4752] +24-11-19 18:51:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:51:18 | D | sum error = [ 0.5071, 0.5091, 0.5140, 0.5193, 0.5295] +24-11-19 18:51:18 | D | best error = [ 0.4724, 0.4700, 0.4683, 0.4672, 0.4663] +24-11-19 18:51:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:51:18 | D | sum error = [ 0.5416, 0.5557, 0.5747, 0.5952, 0.6194] +24-11-19 18:51:18 | D | best error = [ 0.4657, 0.4653, 0.4649, 0.4647, 0.4646] +24-11-19 18:51:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:51:18 | D | sum error = [ 0.6469, 0.6784, 0.7146, 0.7549, 0.7996] +24-11-19 18:51:18 | D | best error = [ 0.4645, 0.4645, 0.4645, 0.4644, 0.4644] +24-11-19 18:51:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:51:18 | D | sum error = [ 0.8483, 0.9028, 0.9611, 1.0242, 1.0937] +24-11-19 18:51:18 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 18:51:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:51:18 | D | sum error = [ 1.1684, 1.2488, 1.3351, 1.4275, 1.5264] +24-11-19 18:51:18 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 18:51:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:51:18 | D | sum error = [ 1.6315, 1.7449, 1.8667, 1.9947, 2.1321] +24-11-19 18:51:18 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 18:51:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:51:18 | D | sum error = [ 2.2766, 2.4320, 2.5962, 2.7693, 2.9537] +24-11-19 18:51:18 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 18:51:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:51:18 | D | sum error = [ 3.1490, 3.3558, 3.5751, 3.8062, 4.0506] +24-11-19 18:51:18 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 18:51:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:51:18 | D | sum error = [ 4.3089, 4.5809, 4.8683, 5.1705, 5.4897] +24-11-19 18:51:18 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 18:51:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:51:18 | D | sum error = [ 5.8258, 6.1782, 6.5496, 6.9397, 7.3491] +24-11-19 18:51:18 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 18:51:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:51:18 | D | sum error = [ 7.7793, 8.2313, 8.7039, 9.1986, 9.7164] +24-11-19 18:51:18 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 18:51:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:51:18 | D | sum error = [ 10.2584, 10.8250, 11.4173, 12.0356, 12.6804] +24-11-19 18:51:18 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 18:51:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:51:18 | D | sum error = [ 13.3532, 14.0539, 14.7837, 15.5436, 16.3323] +24-11-19 18:51:18 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 18:51:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:51:18 | D | sum error = [ 17.1531, 18.0047, 18.8891, 19.8065, 20.7574] +24-11-19 18:51:18 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 18:51:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:51:18 | D | sum error = [ 21.7423, 22.7622, 23.8177, 24.9096, 26.0373] +24-11-19 18:51:18 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 18:51:18 | D | + error = [0.4644] +24-11-19 18:51:18 | D | - Quantizing model.layers.6.self_attn.q_proj.weight +24-11-19 18:51:19 | D | - Quantizing model.layers.6.self_attn.k_proj.weight +24-11-19 18:51:19 | D | - Quantizing model.layers.6.self_attn.v_proj.weight +24-11-19 18:51:20 | D | - Quantizing model.layers.6.self_attn.o_proj.weight +24-11-19 18:51:21 | D | - Quantizing model.layers.6.mlp.up_proj.weight +24-11-19 18:51:22 | D | - Quantizing model.layers.6.mlp.gate_proj.weight +24-11-19 18:51:23 | D | - Quantizing model.layers.6.mlp.down_proj.weight +24-11-19 18:51:32 | D | - Quantizing layer model.layers.7 +24-11-19 18:51:32 | D | - Calibrating model.layers.7.self_attn.q_proj.weight +24-11-19 18:51:32 | D | + w: sint8 +24-11-19 18:51:32 | D | + x: None +24-11-19 18:51:32 | D | + y: None +24-11-19 18:51:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:51:32 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:51:32 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:51:32 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:51:33 | D | - range ratio = [ 1.0000] +24-11-19 18:51:33 | D | sum error = [ 2.9788] +24-11-19 18:51:33 | D | best error = [ 2.9788] +24-11-19 18:51:44 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:51:44 | D | sum error = [ 3.0692, 3.0338, 3.0385, 3.0570, 3.1461] +24-11-19 18:51:44 | D | best error = [ 2.9788, 2.9788, 2.9788, 2.9788, 2.9788] +24-11-19 18:51:44 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:51:44 | D | sum error = [ 3.1970, 3.3690, 3.4196, 3.8060, 4.0083] +24-11-19 18:51:44 | D | best error = [ 2.9788, 2.9788, 2.9788, 2.9788, 2.9788] +24-11-19 18:51:44 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:51:44 | D | sum error = [ 4.0743, 4.3405, 4.7645, 5.0920, 5.5746] +24-11-19 18:51:44 | D | best error = [ 2.9788, 2.9788, 2.9788, 2.9788, 2.9788] +24-11-19 18:51:44 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:51:44 | D | sum error = [ 5.9516, 6.4565, 7.0043, 7.7348, 8.5433] +24-11-19 18:51:44 | D | best error = [ 2.9788, 2.9788, 2.9788, 2.9788, 2.9788] +24-11-19 18:51:44 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:51:44 | D | sum error = [ 9.2917, 10.3680, 11.5016, 12.6219, 13.5825] +24-11-19 18:51:44 | D | best error = [ 2.9788, 2.9788, 2.9788, 2.9788, 2.9788] +24-11-19 18:51:44 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:51:44 | D | sum error = [ 15.1890, 16.4347, 17.9679, 20.0528, 21.6400] +24-11-19 18:51:44 | D | best error = [ 2.9788, 2.9788, 2.9788, 2.9788, 2.9788] +24-11-19 18:51:44 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:51:44 | D | sum error = [ 23.7590, 25.8617, 28.4159, 31.0291, 33.7949] +24-11-19 18:51:44 | D | best error = [ 2.9788, 2.9788, 2.9788, 2.9788, 2.9788] +24-11-19 18:51:44 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:51:44 | D | sum error = [ 36.9449, 40.1347, 43.6232, 47.1532, 51.1399] +24-11-19 18:51:44 | D | best error = [ 2.9788, 2.9788, 2.9788, 2.9788, 2.9788] +24-11-19 18:51:44 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:51:44 | D | sum error = [ 55.4035, 59.6883, 64.1459, 69.2741, 74.6876] +24-11-19 18:51:44 | D | best error = [ 2.9788, 2.9788, 2.9788, 2.9788, 2.9788] +24-11-19 18:51:44 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:51:44 | D | sum error = [ 80.3876, 86.1639, 92.2973, 98.7863, 105.5949] +24-11-19 18:51:44 | D | best error = [ 2.9788, 2.9788, 2.9788, 2.9788, 2.9788] +24-11-19 18:51:44 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:51:44 | D | sum error = [ 112.9157, 120.7436, 128.5963, 136.9374, 145.8465] +24-11-19 18:51:44 | D | best error = [ 2.9788, 2.9788, 2.9788, 2.9788, 2.9788] +24-11-19 18:51:44 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:51:44 | D | sum error = [ 155.4403, 165.2758, 175.6146, 186.4694, 197.7698] +24-11-19 18:51:44 | D | best error = [ 2.9788, 2.9788, 2.9788, 2.9788, 2.9788] +24-11-19 18:51:44 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:51:44 | D | sum error = [ 209.4912, 221.8932, 234.6705, 247.6768, 261.7081] +24-11-19 18:51:44 | D | best error = [ 2.9788, 2.9788, 2.9788, 2.9788, 2.9788] +24-11-19 18:51:44 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:51:44 | D | sum error = [ 275.8102, 290.1705, 305.1911, 320.7085, 336.6223] +24-11-19 18:51:44 | D | best error = [ 2.9788, 2.9788, 2.9788, 2.9788, 2.9788] +24-11-19 18:51:44 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:51:44 | D | sum error = [ 352.9655, 369.5416, 386.9568, 404.7324, 422.7534] +24-11-19 18:51:44 | D | best error = [ 2.9788, 2.9788, 2.9788, 2.9788, 2.9788] +24-11-19 18:51:44 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:51:44 | D | sum error = [ 441.4783, 460.2793, 479.6390, 499.3704, 519.5028] +24-11-19 18:51:44 | D | best error = [ 2.9788, 2.9788, 2.9788, 2.9788, 2.9788] +24-11-19 18:51:44 | D | + error = [2.9788] +24-11-19 18:51:45 | D | - Calibrating model.layers.7.self_attn.k_proj.weight +24-11-19 18:51:45 | D | + w: sint8 +24-11-19 18:51:45 | D | + x: None +24-11-19 18:51:45 | D | + y: None +24-11-19 18:51:45 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:51:45 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:51:45 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:51:45 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:51:45 | D | - range ratio = [ 1.0000] +24-11-19 18:51:45 | D | sum error = [ 3.3390] +24-11-19 18:51:45 | D | best error = [ 3.3390] +24-11-19 18:51:56 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:51:56 | D | sum error = [ 2.7685, 3.1014, 3.1887, 2.7444, 3.2076] +24-11-19 18:51:56 | D | best error = [ 2.7685, 2.7685, 2.7685, 2.7444, 2.7444] +24-11-19 18:51:56 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:51:56 | D | sum error = [ 3.0483, 3.4073, 3.4245, 3.7703, 3.6732] +24-11-19 18:51:56 | D | best error = [ 2.7444, 2.7444, 2.7444, 2.7444, 2.7444] +24-11-19 18:51:56 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:51:56 | D | sum error = [ 3.8687, 3.9579, 4.6786, 4.8011, 5.2843] +24-11-19 18:51:56 | D | best error = [ 2.7444, 2.7444, 2.7444, 2.7444, 2.7444] +24-11-19 18:51:56 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:51:56 | D | sum error = [ 5.4675, 6.0787, 6.2442, 7.1381, 7.9206] +24-11-19 18:51:56 | D | best error = [ 2.7444, 2.7444, 2.7444, 2.7444, 2.7444] +24-11-19 18:51:56 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:51:56 | D | sum error = [ 8.5584, 9.3966, 9.9219, 10.7944, 11.4850] +24-11-19 18:51:56 | D | best error = [ 2.7444, 2.7444, 2.7444, 2.7444, 2.7444] +24-11-19 18:51:56 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:51:56 | D | sum error = [ 12.7105, 13.7125, 14.4453, 16.1442, 17.1795] +24-11-19 18:51:56 | D | best error = [ 2.7444, 2.7444, 2.7444, 2.7444, 2.7444] +24-11-19 18:51:56 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:51:56 | D | sum error = [ 18.8344, 20.6900, 22.7743, 24.4350, 26.1104] +24-11-19 18:51:56 | D | best error = [ 2.7444, 2.7444, 2.7444, 2.7444, 2.7444] +24-11-19 18:51:56 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:51:56 | D | sum error = [ 28.6715, 31.6038, 34.5907, 37.7588, 40.8597] +24-11-19 18:51:56 | D | best error = [ 2.7444, 2.7444, 2.7444, 2.7444, 2.7444] +24-11-19 18:51:56 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:51:56 | D | sum error = [ 44.8229, 48.9943, 53.9130, 57.8483, 61.6154] +24-11-19 18:51:56 | D | best error = [ 2.7444, 2.7444, 2.7444, 2.7444, 2.7444] +24-11-19 18:51:56 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:51:56 | D | sum error = [ 67.2811, 72.8144, 78.1499, 84.6502, 91.5250] +24-11-19 18:51:56 | D | best error = [ 2.7444, 2.7444, 2.7444, 2.7444, 2.7444] +24-11-19 18:51:56 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:51:56 | D | sum error = [ 98.4195, 106.0523, 112.9080, 121.2928, 129.8483] +24-11-19 18:51:56 | D | best error = [ 2.7444, 2.7444, 2.7444, 2.7444, 2.7444] +24-11-19 18:51:56 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:51:56 | D | sum error = [ 138.6711, 147.9275, 157.4017, 167.3812, 176.7688] +24-11-19 18:51:56 | D | best error = [ 2.7444, 2.7444, 2.7444, 2.7444, 2.7444] +24-11-19 18:51:56 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:51:56 | D | sum error = [ 187.3699, 197.8032, 209.4392, 222.7751, 234.4352] +24-11-19 18:51:56 | D | best error = [ 2.7444, 2.7444, 2.7444, 2.7444, 2.7444] +24-11-19 18:51:56 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:51:56 | D | sum error = [ 248.2991, 263.3869, 279.3065, 294.8049, 312.1491] +24-11-19 18:51:56 | D | best error = [ 2.7444, 2.7444, 2.7444, 2.7444, 2.7444] +24-11-19 18:51:56 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:51:56 | D | sum error = [ 330.0315, 346.6506, 366.9059, 387.0579, 405.6211] +24-11-19 18:51:56 | D | best error = [ 2.7444, 2.7444, 2.7444, 2.7444, 2.7444] +24-11-19 18:51:56 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:51:56 | D | sum error = [ 426.7381, 446.6183, 468.9951, 489.9612, 511.8970] +24-11-19 18:51:56 | D | best error = [ 2.7444, 2.7444, 2.7444, 2.7444, 2.7444] +24-11-19 18:51:56 | D | + error = [2.7444] +24-11-19 18:51:56 | D | - Calibrating model.layers.7.self_attn.v_proj.weight +24-11-19 18:51:56 | D | + w: sint8 +24-11-19 18:51:56 | D | + x: None +24-11-19 18:51:56 | D | + y: None +24-11-19 18:51:56 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:51:56 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:51:57 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:51:57 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:51:57 | D | - range ratio = [ 1.0000] +24-11-19 18:51:57 | D | sum error = [ 1.1250] +24-11-19 18:51:57 | D | best error = [ 1.1250] +24-11-19 18:51:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:51:57 | D | sum error = [ 1.1199, 1.1085, 1.1298, 1.1321, 1.1591] +24-11-19 18:51:57 | D | best error = [ 1.0515, 1.0210, 1.0085, 1.0001, 0.9957] +24-11-19 18:51:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:51:57 | D | sum error = [ 1.1907, 1.2354, 1.2746, 1.3361, 1.4066] +24-11-19 18:51:57 | D | best error = [ 0.9935, 0.9925, 0.9922, 0.9921, 0.9921] +24-11-19 18:51:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:51:57 | D | sum error = [ 1.4879, 1.5790, 1.6868, 1.8055, 1.9353] +24-11-19 18:51:57 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 18:51:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:51:57 | D | sum error = [ 2.0685, 2.2238, 2.3759, 2.5632, 2.7579] +24-11-19 18:51:57 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 18:51:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:51:57 | D | sum error = [ 2.9356, 3.1513, 3.3772, 3.6220, 3.8687] +24-11-19 18:51:57 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 18:51:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:51:57 | D | sum error = [ 4.1492, 4.4319, 4.7419, 5.0630, 5.3927] +24-11-19 18:51:57 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 18:51:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:51:57 | D | sum error = [ 5.7567, 6.1291, 6.5345, 6.9568, 7.4034] +24-11-19 18:51:57 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 18:51:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:51:57 | D | sum error = [ 7.8809, 8.3781, 8.8992, 9.4552, 10.0462] +24-11-19 18:51:57 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 18:51:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:51:57 | D | sum error = [ 10.6642, 11.3072, 11.9923, 12.7134, 13.4619] +24-11-19 18:51:57 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 18:51:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:51:57 | D | sum error = [ 14.2609, 15.0906, 15.9593, 16.8740, 17.8271] +24-11-19 18:51:57 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 18:51:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:51:57 | D | sum error = [ 18.8384, 19.8928, 21.0053, 22.1703, 23.3844] +24-11-19 18:51:57 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 18:51:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:51:57 | D | sum error = [ 24.6595, 25.9892, 27.3875, 28.8503, 30.3808] +24-11-19 18:51:57 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 18:51:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:51:57 | D | sum error = [ 31.9762, 33.6432, 35.3720, 37.1796, 39.0546] +24-11-19 18:51:57 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 18:51:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:51:57 | D | sum error = [ 40.9993, 43.0164, 45.1192, 47.3036, 49.5732] +24-11-19 18:51:57 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 18:51:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:51:57 | D | sum error = [ 51.9221, 54.3650, 56.8915, 59.5156, 62.2243] +24-11-19 18:51:57 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 18:51:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:51:57 | D | sum error = [ 65.0232, 67.9192, 70.9076, 73.9888, 77.1604] +24-11-19 18:51:57 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 18:51:57 | D | + error = [0.9921] +24-11-19 18:51:57 | D | - Calibrating model.layers.7.self_attn.o_proj.weight +24-11-19 18:51:57 | D | + w: sint8 +24-11-19 18:51:57 | D | + x: None +24-11-19 18:51:57 | D | + y: None +24-11-19 18:51:57 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:51:57 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:51:57 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:51:57 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:51:57 | D | - range ratio = [ 1.0000] +24-11-19 18:51:57 | D | sum error = [ 0.4496] +24-11-19 18:51:57 | D | best error = [ 0.4496] +24-11-19 18:51:58 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:51:58 | D | sum error = [ 0.4475, 0.4437, 0.4447, 0.4467, 0.4540] +24-11-19 18:51:58 | D | best error = [ 0.4121, 0.3951, 0.3850, 0.3786, 0.3743] +24-11-19 18:51:58 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:51:58 | D | sum error = [ 0.4631, 0.4731, 0.4871, 0.5047, 0.5263] +24-11-19 18:51:58 | D | best error = [ 0.3719, 0.3702, 0.3692, 0.3684, 0.3680] +24-11-19 18:51:58 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:51:58 | D | sum error = [ 0.5504, 0.5750, 0.6075, 0.6399, 0.6770] +24-11-19 18:51:58 | D | best error = [ 0.3677, 0.3675, 0.3675, 0.3674, 0.3674] +24-11-19 18:51:58 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:51:58 | D | sum error = [ 0.7182, 0.7624, 0.8106, 0.8605, 0.9133] +24-11-19 18:51:58 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 18:51:58 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:51:58 | D | sum error = [ 0.9709, 1.0342, 1.0967, 1.1679, 1.2399] +24-11-19 18:51:58 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 18:51:58 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:51:58 | D | sum error = [ 1.3157, 1.3972, 1.4839, 1.5729, 1.6664] +24-11-19 18:51:58 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 18:51:58 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:51:58 | D | sum error = [ 1.7681, 1.8730, 1.9829, 2.1017, 2.2250] +24-11-19 18:51:58 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 18:51:58 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:51:58 | D | sum error = [ 2.3553, 2.4906, 2.6324, 2.7810, 2.9376] +24-11-19 18:51:58 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 18:51:58 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:51:58 | D | sum error = [ 3.1023, 3.2735, 3.4525, 3.6410, 3.8385] +24-11-19 18:51:58 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 18:51:58 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:51:58 | D | sum error = [ 4.0454, 4.2623, 4.4850, 4.7201, 4.9681] +24-11-19 18:51:58 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 18:51:58 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:51:58 | D | sum error = [ 5.2258, 5.4940, 5.7739, 6.0663, 6.3704] +24-11-19 18:51:58 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 18:51:58 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:51:58 | D | sum error = [ 6.6887, 7.0197, 7.3627, 7.7216, 8.0942] +24-11-19 18:51:58 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 18:51:58 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:51:58 | D | sum error = [ 8.4822, 8.8859, 9.3067, 9.7436, 10.1956] +24-11-19 18:51:58 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 18:51:58 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:51:58 | D | sum error = [ 10.6668, 11.1530, 11.6599, 12.1860, 12.7274] +24-11-19 18:51:58 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 18:51:58 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:51:58 | D | sum error = [ 13.2908, 13.8738, 14.4778, 15.1042, 15.7533] +24-11-19 18:51:58 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 18:51:58 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:51:58 | D | sum error = [ 16.4249, 17.1172, 17.8337, 18.5735, 19.3379] +24-11-19 18:51:58 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 18:51:58 | D | + error = [0.3674] +24-11-19 18:51:58 | D | - Calibrating model.layers.7.mlp.up_proj.weight +24-11-19 18:51:58 | D | + w: sint8 +24-11-19 18:51:58 | D | + x: None +24-11-19 18:51:58 | D | + y: None +24-11-19 18:51:58 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:51:58 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:51:58 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:51:58 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:51:58 | D | - range ratio = [ 1.0000] +24-11-19 18:51:58 | D | sum error = [ 4.6658] +24-11-19 18:51:58 | D | best error = [ 4.6658] +24-11-19 18:51:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:51:59 | D | sum error = [ 4.6409, 4.6287, 4.6487, 4.7028, 4.7906] +24-11-19 18:51:59 | D | best error = [ 4.3839, 4.2702, 4.2086, 4.1743, 4.1571] +24-11-19 18:51:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:51:59 | D | sum error = [ 4.9143, 5.0769, 5.2802, 5.5319, 5.8070] +24-11-19 18:51:59 | D | best error = [ 4.1483, 4.1449, 4.1437, 4.1434, 4.1433] +24-11-19 18:51:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:51:59 | D | sum error = [ 6.1499, 6.5394, 6.9590, 7.4257, 7.9269] +24-11-19 18:51:59 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 18:51:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:51:59 | D | sum error = [ 8.4883, 9.0836, 9.7308, 10.4403, 11.1904] +24-11-19 18:51:59 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 18:51:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:51:59 | D | sum error = [ 11.9937, 12.8414, 13.7437, 14.7060, 15.7194] +24-11-19 18:51:59 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 18:51:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:51:59 | D | sum error = [ 16.8098, 17.9550, 19.1694, 20.4580, 21.8142] +24-11-19 18:51:59 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 18:51:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:51:59 | D | sum error = [ 23.2597, 24.7711, 26.3566, 28.0515, 29.8227] +24-11-19 18:51:59 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 18:51:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:51:59 | D | sum error = [ 31.6940, 33.6672, 35.7286, 37.8949, 40.1758] +24-11-19 18:51:59 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 18:51:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:51:59 | D | sum error = [ 42.5690, 45.0947, 47.7307, 50.5203, 53.4215] +24-11-19 18:51:59 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 18:51:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:51:59 | D | sum error = [ 56.4784, 59.6829, 63.0381, 66.5535, 70.2262] +24-11-19 18:51:59 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 18:51:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:51:59 | D | sum error = [ 74.0738, 78.0890, 82.3028, 86.6833, 91.2685] +24-11-19 18:51:59 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 18:51:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:51:59 | D | sum error = [ 96.0454, 101.0304, 106.2237, 111.6368, 117.2758] +24-11-19 18:51:59 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 18:51:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:51:59 | D | sum error = [ 123.1397, 129.2439, 135.5741, 142.1657, 148.9997] +24-11-19 18:51:59 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 18:51:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:51:59 | D | sum error = [ 156.0914, 163.4441, 171.0840, 178.9951, 187.1838] +24-11-19 18:51:59 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 18:51:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:51:59 | D | sum error = [ 195.6616, 204.4336, 213.4939, 222.8616, 232.5275] +24-11-19 18:51:59 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 18:51:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:51:59 | D | sum error = [ 242.4952, 252.7703, 263.3609, 274.2513, 285.4620] +24-11-19 18:51:59 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 18:51:59 | D | + error = [4.1433] +24-11-19 18:51:59 | D | - Calibrating model.layers.7.mlp.gate_proj.weight +24-11-19 18:51:59 | D | + w: sint8 +24-11-19 18:51:59 | D | + x: None +24-11-19 18:51:59 | D | + y: None +24-11-19 18:51:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:51:59 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:51:59 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:51:59 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:51:59 | D | - range ratio = [ 1.0000] +24-11-19 18:51:59 | D | sum error = [ 6.0135] +24-11-19 18:51:59 | D | best error = [ 6.0135] +24-11-19 18:52:00 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:52:00 | D | sum error = [ 5.9720, 5.9571, 5.9817, 6.0588, 6.1473] +24-11-19 18:52:00 | D | best error = [ 5.6381, 5.4906, 5.4113, 5.3685, 5.3456] +24-11-19 18:52:00 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:52:00 | D | sum error = [ 6.3127, 6.5433, 6.7939, 7.1167, 7.4979] +24-11-19 18:52:00 | D | best error = [ 5.3350, 5.3304, 5.3294, 5.3291, 5.3290] +24-11-19 18:52:00 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:52:00 | D | sum error = [ 7.9409, 8.4337, 8.9925, 9.6053, 10.2925] +24-11-19 18:52:00 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 18:52:00 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:52:00 | D | sum error = [ 11.0288, 11.8165, 12.6931, 13.6233, 14.6305] +24-11-19 18:52:00 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 18:52:00 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:52:00 | D | sum error = [ 15.6925, 16.8489, 18.0865, 19.3967, 20.7882] +24-11-19 18:52:00 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 18:52:00 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:52:00 | D | sum error = [ 22.2775, 23.8774, 25.5591, 27.3552, 29.2763] +24-11-19 18:52:00 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 18:52:00 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:52:00 | D | sum error = [ 31.3047, 33.4660, 35.7555, 38.1829, 40.7695] +24-11-19 18:52:00 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 18:52:00 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:52:00 | D | sum error = [ 43.5167, 46.4229, 49.4958, 52.7675, 56.2435] +24-11-19 18:52:00 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 18:52:00 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:52:00 | D | sum error = [ 59.9274, 63.8432, 67.9820, 72.3717, 77.0272] +24-11-19 18:52:00 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 18:52:00 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:52:00 | D | sum error = [ 81.9553, 87.1748, 92.6880, 98.5311, 104.7034] +24-11-19 18:52:00 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 18:52:00 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:52:00 | D | sum error = [ 111.2082, 118.1069, 125.3714, 133.0608, 141.1502] +24-11-19 18:52:00 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 18:52:00 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:52:00 | D | sum error = [ 149.6863, 158.6733, 168.1147, 178.0504, 188.5082] +24-11-19 18:52:00 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 18:52:00 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:52:00 | D | sum error = [ 199.4850, 211.0123, 223.0997, 235.7602, 249.0291] +24-11-19 18:52:00 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 18:52:00 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:52:00 | D | sum error = [ 262.8892, 277.3906, 292.5259, 308.3247, 324.7759] +24-11-19 18:52:00 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 18:52:00 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:52:00 | D | sum error = [ 341.8893, 359.7152, 378.2390, 397.4480, 417.3565] +24-11-19 18:52:00 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 18:52:00 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:52:00 | D | sum error = [ 438.0118, 459.3633, 481.4650, 504.2506, 527.7298] +24-11-19 18:52:00 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 18:52:00 | D | + error = [5.3290] +24-11-19 18:52:01 | D | - Calibrating model.layers.7.mlp.down_proj.weight +24-11-19 18:52:01 | D | + w: sint8 +24-11-19 18:52:01 | D | + x: None +24-11-19 18:52:01 | D | + y: None +24-11-19 18:52:01 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:52:01 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:52:01 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:52:01 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:52:01 | D | - range ratio = [ 1.0000] +24-11-19 18:52:01 | D | sum error = [ 0.5477] +24-11-19 18:52:01 | D | best error = [ 0.5477] +24-11-19 18:52:02 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:52:02 | D | sum error = [ 0.5423, 0.5389, 0.5358, 0.5344, 0.5340] +24-11-19 18:52:02 | D | best error = [ 0.5264, 0.5161, 0.5092, 0.5042, 0.5002] +24-11-19 18:52:02 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:52:02 | D | sum error = [ 0.5346, 0.5376, 0.5441, 0.5521, 0.5620] +24-11-19 18:52:02 | D | best error = [ 0.4972, 0.4948, 0.4932, 0.4921, 0.4912] +24-11-19 18:52:02 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:52:02 | D | sum error = [ 0.5759, 0.5915, 0.6106, 0.6344, 0.6613] +24-11-19 18:52:02 | D | best error = [ 0.4907, 0.4903, 0.4900, 0.4898, 0.4897] +24-11-19 18:52:02 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:52:02 | D | sum error = [ 0.6919, 0.7247, 0.7638, 0.8063, 0.8534] +24-11-19 18:52:02 | D | best error = [ 0.4896, 0.4895, 0.4895, 0.4894, 0.4894] +24-11-19 18:52:02 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:52:02 | D | sum error = [ 0.9053, 0.9627, 1.0258, 1.0910, 1.1641] +24-11-19 18:52:02 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 18:52:02 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:52:02 | D | sum error = [ 1.2417, 1.3266, 1.4166, 1.5130, 1.6179] +24-11-19 18:52:02 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 18:52:02 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:52:02 | D | sum error = [ 1.7285, 1.8457, 1.9722, 2.1071, 2.2487] +24-11-19 18:52:02 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 18:52:02 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:52:02 | D | sum error = [ 2.4005, 2.5624, 2.7322, 2.9128, 3.1034] +24-11-19 18:52:02 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 18:52:02 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:52:02 | D | sum error = [ 3.3059, 3.5205, 3.7456, 3.9850, 4.2381] +24-11-19 18:52:02 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 18:52:02 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:52:02 | D | sum error = [ 4.5051, 4.7864, 5.0837, 5.3967, 5.7258] +24-11-19 18:52:02 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 18:52:02 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:52:02 | D | sum error = [ 6.0722, 6.4367, 6.8198, 7.2218, 7.6440] +24-11-19 18:52:02 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 18:52:02 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:52:02 | D | sum error = [ 8.0865, 8.5511, 9.0367, 9.5450, 10.0762] +24-11-19 18:52:02 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 18:52:02 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:52:02 | D | sum error = [ 10.6319, 11.2134, 11.8196, 12.4532, 13.1138] +24-11-19 18:52:02 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 18:52:02 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:52:02 | D | sum error = [ 13.8025, 14.5204, 15.2672, 16.0446, 16.8512] +24-11-19 18:52:02 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 18:52:02 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:52:02 | D | sum error = [ 17.6902, 18.5608, 19.4646, 20.4023, 21.3734] +24-11-19 18:52:02 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 18:52:02 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:52:02 | D | sum error = [ 22.3797, 23.4208, 24.4967, 25.6100, 26.7586] +24-11-19 18:52:02 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 18:52:02 | D | + error = [0.4894] +24-11-19 18:52:02 | D | - Quantizing model.layers.7.self_attn.q_proj.weight +24-11-19 18:52:03 | D | - Quantizing model.layers.7.self_attn.k_proj.weight +24-11-19 18:52:04 | D | - Quantizing model.layers.7.self_attn.v_proj.weight +24-11-19 18:52:04 | D | - Quantizing model.layers.7.self_attn.o_proj.weight +24-11-19 18:52:05 | D | - Quantizing model.layers.7.mlp.up_proj.weight +24-11-19 18:52:06 | D | - Quantizing model.layers.7.mlp.gate_proj.weight +24-11-19 18:52:07 | D | - Quantizing model.layers.7.mlp.down_proj.weight +24-11-19 18:52:16 | D | - Quantizing layer model.layers.8 +24-11-19 18:52:16 | D | - Calibrating model.layers.8.self_attn.q_proj.weight +24-11-19 18:52:16 | D | + w: sint8 +24-11-19 18:52:16 | D | + x: None +24-11-19 18:52:16 | D | + y: None +24-11-19 18:52:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:52:16 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:52:16 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:52:17 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:52:17 | D | - range ratio = [ 1.0000] +24-11-19 18:52:17 | D | sum error = [ 3.4754] +24-11-19 18:52:17 | D | best error = [ 3.4754] +24-11-19 18:52:28 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:52:28 | D | sum error = [ 3.5359, 3.5062, 3.6386, 3.4259, 3.5756] +24-11-19 18:52:28 | D | best error = [ 3.4754, 3.4754, 3.4754, 3.4259, 3.4259] +24-11-19 18:52:28 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:52:28 | D | sum error = [ 3.5994, 3.7697, 3.9865, 4.2141, 4.3763] +24-11-19 18:52:28 | D | best error = [ 3.4259, 3.4259, 3.4259, 3.4259, 3.4259] +24-11-19 18:52:28 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:52:28 | D | sum error = [ 4.7410, 4.9171, 5.3376, 5.6255, 6.0029] +24-11-19 18:52:28 | D | best error = [ 3.4259, 3.4259, 3.4259, 3.4259, 3.4259] +24-11-19 18:52:28 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:52:28 | D | sum error = [ 6.4268, 6.9575, 7.6478, 8.1569, 8.7528] +24-11-19 18:52:28 | D | best error = [ 3.4259, 3.4259, 3.4259, 3.4259, 3.4259] +24-11-19 18:52:28 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:52:28 | D | sum error = [ 9.3634, 10.3193, 10.9762, 11.9235, 12.7979] +24-11-19 18:52:28 | D | best error = [ 3.4259, 3.4259, 3.4259, 3.4259, 3.4259] +24-11-19 18:52:28 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:52:28 | D | sum error = [ 13.9180, 14.8958, 16.1946, 17.6098, 19.0292] +24-11-19 18:52:28 | D | best error = [ 3.4259, 3.4259, 3.4259, 3.4259, 3.4259] +24-11-19 18:52:28 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:52:28 | D | sum error = [ 20.4419, 22.1852, 24.0352, 26.0261, 28.3293] +24-11-19 18:52:28 | D | best error = [ 3.4259, 3.4259, 3.4259, 3.4259, 3.4259] +24-11-19 18:52:28 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:52:28 | D | sum error = [ 30.5660, 33.0189, 35.7436, 38.6417, 41.5840] +24-11-19 18:52:28 | D | best error = [ 3.4259, 3.4259, 3.4259, 3.4259, 3.4259] +24-11-19 18:52:28 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:52:28 | D | sum error = [ 44.8485, 48.2537, 51.9125, 55.8954, 60.1206] +24-11-19 18:52:28 | D | best error = [ 3.4259, 3.4259, 3.4259, 3.4259, 3.4259] +24-11-19 18:52:28 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:52:28 | D | sum error = [ 64.6411, 69.2874, 74.2535, 79.5357, 85.0061] +24-11-19 18:52:28 | D | best error = [ 3.4259, 3.4259, 3.4259, 3.4259, 3.4259] +24-11-19 18:52:28 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:52:28 | D | sum error = [ 91.1539, 97.2740, 103.9205, 110.9933, 118.5528] +24-11-19 18:52:28 | D | best error = [ 3.4259, 3.4259, 3.4259, 3.4259, 3.4259] +24-11-19 18:52:28 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:52:28 | D | sum error = [ 126.5224, 134.8157, 143.6543, 152.8640, 162.7643] +24-11-19 18:52:28 | D | best error = [ 3.4259, 3.4259, 3.4259, 3.4259, 3.4259] +24-11-19 18:52:28 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:52:28 | D | sum error = [ 173.2371, 184.2419, 195.7488, 207.8826, 220.5514] +24-11-19 18:52:28 | D | best error = [ 3.4259, 3.4259, 3.4259, 3.4259, 3.4259] +24-11-19 18:52:28 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:52:28 | D | sum error = [ 233.7523, 247.6665, 262.0157, 276.9822, 292.4070] +24-11-19 18:52:28 | D | best error = [ 3.4259, 3.4259, 3.4259, 3.4259, 3.4259] +24-11-19 18:52:28 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:52:28 | D | sum error = [ 308.4042, 324.9505, 341.9351, 359.2576, 377.1307] +24-11-19 18:52:28 | D | best error = [ 3.4259, 3.4259, 3.4259, 3.4259, 3.4259] +24-11-19 18:52:28 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:52:28 | D | sum error = [ 395.2802, 413.8060, 432.5481, 451.3062, 470.1928] +24-11-19 18:52:28 | D | best error = [ 3.4259, 3.4259, 3.4259, 3.4259, 3.4259] +24-11-19 18:52:28 | D | + error = [3.4259] +24-11-19 18:52:29 | D | - Calibrating model.layers.8.self_attn.k_proj.weight +24-11-19 18:52:29 | D | + w: sint8 +24-11-19 18:52:29 | D | + x: None +24-11-19 18:52:29 | D | + y: None +24-11-19 18:52:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:52:29 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:52:29 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:52:29 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:52:29 | D | - range ratio = [ 1.0000] +24-11-19 18:52:29 | D | sum error = [ 3.0592] +24-11-19 18:52:29 | D | best error = [ 3.0592] +24-11-19 18:52:40 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:52:40 | D | sum error = [ 3.2533, 2.9532, 2.8766, 2.8525, 3.0564] +24-11-19 18:52:40 | D | best error = [ 3.0592, 2.9532, 2.8766, 2.8525, 2.8525] +24-11-19 18:52:40 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:52:40 | D | sum error = [ 3.3794, 3.3688, 3.1667, 3.4620, 3.4685] +24-11-19 18:52:40 | D | best error = [ 2.8525, 2.8525, 2.8525, 2.8525, 2.8525] +24-11-19 18:52:40 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:52:40 | D | sum error = [ 4.0223, 4.3764, 4.5486, 4.8376, 5.5430] +24-11-19 18:52:40 | D | best error = [ 2.8525, 2.8525, 2.8525, 2.8525, 2.8525] +24-11-19 18:52:40 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:52:40 | D | sum error = [ 5.7091, 6.0721, 6.3024, 6.8718, 7.5328] +24-11-19 18:52:40 | D | best error = [ 2.8525, 2.8525, 2.8525, 2.8525, 2.8525] +24-11-19 18:52:40 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:52:40 | D | sum error = [ 8.1734, 8.8845, 9.9759, 10.5483, 11.3413] +24-11-19 18:52:40 | D | best error = [ 2.8525, 2.8525, 2.8525, 2.8525, 2.8525] +24-11-19 18:52:40 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:52:40 | D | sum error = [ 12.0071, 12.9896, 13.9769, 15.1371, 16.3188] +24-11-19 18:52:40 | D | best error = [ 2.8525, 2.8525, 2.8525, 2.8525, 2.8525] +24-11-19 18:52:40 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:52:40 | D | sum error = [ 17.5949, 19.0375, 20.3207, 22.4306, 24.3002] +24-11-19 18:52:40 | D | best error = [ 2.8525, 2.8525, 2.8525, 2.8525, 2.8525] +24-11-19 18:52:40 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:52:40 | D | sum error = [ 26.3606, 28.6525, 31.1583, 33.3451, 36.3412] +24-11-19 18:52:40 | D | best error = [ 2.8525, 2.8525, 2.8525, 2.8525, 2.8525] +24-11-19 18:52:40 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:52:40 | D | sum error = [ 39.4061, 42.2818, 46.5351, 49.8818, 53.9820] +24-11-19 18:52:40 | D | best error = [ 2.8525, 2.8525, 2.8525, 2.8525, 2.8525] +24-11-19 18:52:40 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:52:40 | D | sum error = [ 58.4800, 63.7052, 69.1080, 74.4207, 80.0229] +24-11-19 18:52:40 | D | best error = [ 2.8525, 2.8525, 2.8525, 2.8525, 2.8525] +24-11-19 18:52:40 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:52:40 | D | sum error = [ 86.3221, 93.6958, 100.7485, 107.7523, 115.0891] +24-11-19 18:52:40 | D | best error = [ 2.8525, 2.8525, 2.8525, 2.8525, 2.8525] +24-11-19 18:52:40 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:52:40 | D | sum error = [ 123.0518, 131.8845, 141.0030, 151.0691, 161.4570] +24-11-19 18:52:40 | D | best error = [ 2.8525, 2.8525, 2.8525, 2.8525, 2.8525] +24-11-19 18:52:40 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:52:40 | D | sum error = [ 172.0606, 182.6335, 194.1402, 206.4182, 219.0872] +24-11-19 18:52:40 | D | best error = [ 2.8525, 2.8525, 2.8525, 2.8525, 2.8525] +24-11-19 18:52:40 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:52:40 | D | sum error = [ 233.1051, 246.9123, 260.4861, 275.4066, 291.7037] +24-11-19 18:52:40 | D | best error = [ 2.8525, 2.8525, 2.8525, 2.8525, 2.8525] +24-11-19 18:52:40 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:52:40 | D | sum error = [ 308.6663, 324.9987, 342.2329, 358.9461, 375.7507] +24-11-19 18:52:40 | D | best error = [ 2.8525, 2.8525, 2.8525, 2.8525, 2.8525] +24-11-19 18:52:40 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:52:40 | D | sum error = [ 394.5227, 412.3994, 431.3887, 449.1629, 467.5872] +24-11-19 18:52:40 | D | best error = [ 2.8525, 2.8525, 2.8525, 2.8525, 2.8525] +24-11-19 18:52:40 | D | + error = [2.8525] +24-11-19 18:52:41 | D | - Calibrating model.layers.8.self_attn.v_proj.weight +24-11-19 18:52:41 | D | + w: sint8 +24-11-19 18:52:41 | D | + x: None +24-11-19 18:52:41 | D | + y: None +24-11-19 18:52:41 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:52:41 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:52:41 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:52:41 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:52:41 | D | - range ratio = [ 1.0000] +24-11-19 18:52:41 | D | sum error = [ 1.2606] +24-11-19 18:52:41 | D | best error = [ 1.2606] +24-11-19 18:52:41 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:52:41 | D | sum error = [ 1.2597, 1.2429, 1.2569, 1.2737, 1.2947] +24-11-19 18:52:41 | D | best error = [ 1.1819, 1.1479, 1.1322, 1.1226, 1.1172] +24-11-19 18:52:41 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:52:41 | D | sum error = [ 1.3298, 1.3728, 1.4204, 1.4853, 1.5743] +24-11-19 18:52:41 | D | best error = [ 1.1152, 1.1138, 1.1134, 1.1134, 1.1134] +24-11-19 18:52:41 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:52:41 | D | sum error = [ 1.6740, 1.7801, 1.8900, 2.0184, 2.1590] +24-11-19 18:52:41 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 18:52:41 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:52:41 | D | sum error = [ 2.3206, 2.4870, 2.6690, 2.8542, 3.0664] +24-11-19 18:52:41 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 18:52:41 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:52:41 | D | sum error = [ 3.2911, 3.5228, 3.7752, 4.0314, 4.3187] +24-11-19 18:52:41 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 18:52:41 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:52:41 | D | sum error = [ 4.6191, 4.9183, 5.2776, 5.6322, 6.0146] +24-11-19 18:52:41 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 18:52:41 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:52:41 | D | sum error = [ 6.4039, 6.8142, 7.2586, 7.7247, 8.2196] +24-11-19 18:52:41 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 18:52:41 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:52:41 | D | sum error = [ 8.7292, 9.2842, 9.8474, 10.4479, 11.1001] +24-11-19 18:52:41 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 18:52:41 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:52:41 | D | sum error = [ 11.7586, 12.4681, 13.1999, 13.9764, 14.7856] +24-11-19 18:52:41 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 18:52:41 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:52:41 | D | sum error = [ 15.6335, 16.5240, 17.4429, 18.4144, 19.4272] +24-11-19 18:52:41 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 18:52:41 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:52:41 | D | sum error = [ 20.4905, 21.5898, 22.7625, 23.9679, 25.2324] +24-11-19 18:52:41 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 18:52:41 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:52:41 | D | sum error = [ 26.5501, 27.9252, 29.3590, 30.8574, 32.4197] +24-11-19 18:52:41 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 18:52:41 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:52:41 | D | sum error = [ 34.0433, 35.7379, 37.4992, 39.3452, 41.2520] +24-11-19 18:52:41 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 18:52:41 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:52:41 | D | sum error = [ 43.2341, 45.3028, 47.4335, 49.6527, 51.9438] +24-11-19 18:52:41 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 18:52:41 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:52:41 | D | sum error = [ 54.3175, 56.7630, 59.2939, 61.9129, 64.6103] +24-11-19 18:52:41 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 18:52:41 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:52:41 | D | sum error = [ 67.4023, 70.2788, 73.2410, 76.2901, 79.4227] +24-11-19 18:52:41 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 18:52:41 | D | + error = [1.1134] +24-11-19 18:52:41 | D | - Calibrating model.layers.8.self_attn.o_proj.weight +24-11-19 18:52:41 | D | + w: sint8 +24-11-19 18:52:41 | D | + x: None +24-11-19 18:52:41 | D | + y: None +24-11-19 18:52:41 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:52:41 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:52:41 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:52:41 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:52:41 | D | - range ratio = [ 1.0000] +24-11-19 18:52:41 | D | sum error = [ 0.5011] +24-11-19 18:52:41 | D | best error = [ 0.5011] +24-11-19 18:52:42 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:52:42 | D | sum error = [ 0.4978, 0.4973, 0.4996, 0.5024, 0.5113] +24-11-19 18:52:42 | D | best error = [ 0.4565, 0.4378, 0.4271, 0.4201, 0.4153] +24-11-19 18:52:42 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:52:42 | D | sum error = [ 0.5200, 0.5387, 0.5551, 0.5763, 0.6056] +24-11-19 18:52:42 | D | best error = [ 0.4121, 0.4103, 0.4092, 0.4084, 0.4080] +24-11-19 18:52:42 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:52:42 | D | sum error = [ 0.6366, 0.6694, 0.7043, 0.7466, 0.7908] +24-11-19 18:52:42 | D | best error = [ 0.4078, 0.4076, 0.4075, 0.4074, 0.4074] +24-11-19 18:52:42 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:52:42 | D | sum error = [ 0.8441, 0.8941, 0.9510, 1.0105, 1.0713] +24-11-19 18:52:42 | D | best error = [ 0.4074, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 18:52:42 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:52:42 | D | sum error = [ 1.1388, 1.2093, 1.2863, 1.3631, 1.4494] +24-11-19 18:52:42 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 18:52:42 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:52:42 | D | sum error = [ 1.5361, 1.6307, 1.7281, 1.8294, 1.9360] +24-11-19 18:52:42 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 18:52:42 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:52:42 | D | sum error = [ 2.0506, 2.1689, 2.2938, 2.4236, 2.5601] +24-11-19 18:52:42 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 18:52:42 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:52:42 | D | sum error = [ 2.7059, 2.8533, 3.0125, 3.1735, 3.3437] +24-11-19 18:52:42 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 18:52:42 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:52:42 | D | sum error = [ 3.5234, 3.7093, 3.9019, 4.1039, 4.3116] +24-11-19 18:52:42 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 18:52:42 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:52:42 | D | sum error = [ 4.5289, 4.7529, 4.9866, 5.2312, 5.4856] +24-11-19 18:52:42 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 18:52:42 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:52:42 | D | sum error = [ 5.7470, 6.0195, 6.3027, 6.5977, 6.8997] +24-11-19 18:52:42 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 18:52:42 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:52:42 | D | sum error = [ 7.2124, 7.5405, 7.8777, 8.2250, 8.5849] +24-11-19 18:52:42 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 18:52:42 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:52:42 | D | sum error = [ 8.9556, 9.3382, 9.7332, 10.1429, 10.5621] +24-11-19 18:52:42 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 18:52:42 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:52:42 | D | sum error = [ 10.9939, 11.4382, 11.8945, 12.3658, 12.8473] +24-11-19 18:52:42 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 18:52:42 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:52:42 | D | sum error = [ 13.3430, 13.8512, 14.3750, 14.9134, 15.4694] +24-11-19 18:52:42 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 18:52:42 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:52:42 | D | sum error = [ 16.0424, 16.6319, 17.2390, 17.8632, 18.5067] +24-11-19 18:52:42 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 18:52:42 | D | + error = [0.4073] +24-11-19 18:52:42 | D | - Calibrating model.layers.8.mlp.up_proj.weight +24-11-19 18:52:42 | D | + w: sint8 +24-11-19 18:52:42 | D | + x: None +24-11-19 18:52:42 | D | + y: None +24-11-19 18:52:42 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:52:42 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:52:42 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:52:42 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:52:42 | D | - range ratio = [ 1.0000] +24-11-19 18:52:42 | D | sum error = [ 4.7245] +24-11-19 18:52:42 | D | best error = [ 4.7245] +24-11-19 18:52:43 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:52:43 | D | sum error = [ 4.6830, 4.6832, 4.6900, 4.7490, 4.8348] +24-11-19 18:52:43 | D | best error = [ 4.4205, 4.3041, 4.2399, 4.2055, 4.1863] +24-11-19 18:52:43 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:52:43 | D | sum error = [ 4.9590, 5.1385, 5.3332, 5.5917, 5.8828] +24-11-19 18:52:43 | D | best error = [ 4.1773, 4.1736, 4.1723, 4.1719, 4.1719] +24-11-19 18:52:43 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:52:43 | D | sum error = [ 6.2149, 6.6078, 7.0392, 7.5051, 8.0219] +24-11-19 18:52:43 | D | best error = [ 4.1718, 4.1718, 4.1718, 4.1718, 4.1718] +24-11-19 18:52:43 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:52:43 | D | sum error = [ 8.5910, 9.2104, 9.8581, 10.5697, 11.3240] +24-11-19 18:52:43 | D | best error = [ 4.1718, 4.1718, 4.1718, 4.1718, 4.1718] +24-11-19 18:52:43 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:52:43 | D | sum error = [ 12.1384, 12.9841, 13.9022, 14.8785, 15.9156] +24-11-19 18:52:43 | D | best error = [ 4.1718, 4.1718, 4.1718, 4.1718, 4.1718] +24-11-19 18:52:43 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:52:43 | D | sum error = [ 17.0043, 18.1634, 19.3983, 20.6971, 22.0697] +24-11-19 18:52:43 | D | best error = [ 4.1718, 4.1718, 4.1718, 4.1718, 4.1718] +24-11-19 18:52:43 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:52:43 | D | sum error = [ 23.5188, 25.0558, 26.6594, 28.3694, 30.1571] +24-11-19 18:52:43 | D | best error = [ 4.1718, 4.1718, 4.1718, 4.1718, 4.1718] +24-11-19 18:52:43 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:52:43 | D | sum error = [ 32.0380, 34.0269, 36.1228, 38.3206, 40.6332] +24-11-19 18:52:43 | D | best error = [ 4.1718, 4.1718, 4.1718, 4.1718, 4.1718] +24-11-19 18:52:43 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:52:43 | D | sum error = [ 43.0629, 45.6115, 48.2900, 51.0959, 54.0432] +24-11-19 18:52:43 | D | best error = [ 4.1718, 4.1718, 4.1718, 4.1718, 4.1718] +24-11-19 18:52:43 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:52:43 | D | sum error = [ 57.1202, 60.3408, 63.7242, 67.2589, 70.9497] +24-11-19 18:52:43 | D | best error = [ 4.1718, 4.1718, 4.1718, 4.1718, 4.1718] +24-11-19 18:52:43 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:52:43 | D | sum error = [ 74.8220, 78.8664, 83.0936, 87.5120, 92.1224] +24-11-19 18:52:43 | D | best error = [ 4.1718, 4.1718, 4.1718, 4.1718, 4.1718] +24-11-19 18:52:43 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:52:43 | D | sum error = [ 96.9356, 101.9604, 107.1873, 112.6402, 118.3250] +24-11-19 18:52:43 | D | best error = [ 4.1718, 4.1718, 4.1718, 4.1718, 4.1718] +24-11-19 18:52:43 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:52:43 | D | sum error = [ 124.2256, 130.3567, 136.7403, 143.3704, 150.2442] +24-11-19 18:52:43 | D | best error = [ 4.1718, 4.1718, 4.1718, 4.1718, 4.1718] +24-11-19 18:52:43 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:52:43 | D | sum error = [ 157.3717, 164.7542, 172.4192, 180.3575, 188.5589] +24-11-19 18:52:43 | D | best error = [ 4.1718, 4.1718, 4.1718, 4.1718, 4.1718] +24-11-19 18:52:43 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:52:43 | D | sum error = [ 197.0476, 205.8201, 214.8853, 224.2431, 233.8976] +24-11-19 18:52:43 | D | best error = [ 4.1718, 4.1718, 4.1718, 4.1718, 4.1718] +24-11-19 18:52:43 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:52:43 | D | sum error = [ 243.8639, 254.1379, 264.7255, 275.6267, 286.8454] +24-11-19 18:52:43 | D | best error = [ 4.1718, 4.1718, 4.1718, 4.1718, 4.1718] +24-11-19 18:52:43 | D | + error = [4.1718] +24-11-19 18:52:43 | D | - Calibrating model.layers.8.mlp.gate_proj.weight +24-11-19 18:52:43 | D | + w: sint8 +24-11-19 18:52:43 | D | + x: None +24-11-19 18:52:43 | D | + y: None +24-11-19 18:52:43 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:52:43 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:52:43 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:52:43 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:52:43 | D | - range ratio = [ 1.0000] +24-11-19 18:52:43 | D | sum error = [ 6.1288] +24-11-19 18:52:43 | D | best error = [ 6.1288] +24-11-19 18:52:45 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:52:45 | D | sum error = [ 6.0859, 6.0774, 6.1028, 6.1626, 6.2800] +24-11-19 18:52:45 | D | best error = [ 5.7421, 5.5909, 5.5096, 5.4645, 5.4405] +24-11-19 18:52:45 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:52:45 | D | sum error = [ 6.4481, 6.6751, 6.9504, 7.2788, 7.6643] +24-11-19 18:52:45 | D | best error = [ 5.4296, 5.4248, 5.4234, 5.4230, 5.4228] +24-11-19 18:52:45 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:52:45 | D | sum error = [ 8.1258, 8.6346, 9.2143, 9.8370, 10.5511] +24-11-19 18:52:45 | D | best error = [ 5.4228, 5.4228, 5.4228, 5.4228, 5.4228] +24-11-19 18:52:45 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:52:45 | D | sum error = [ 11.3024, 12.1308, 13.0150, 13.9840, 15.0101] +24-11-19 18:52:45 | D | best error = [ 5.4228, 5.4228, 5.4228, 5.4228, 5.4228] +24-11-19 18:52:45 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:52:45 | D | sum error = [ 16.1113, 17.2971, 18.5569, 19.8999, 21.3596] +24-11-19 18:52:45 | D | best error = [ 5.4228, 5.4228, 5.4228, 5.4228, 5.4228] +24-11-19 18:52:45 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:52:45 | D | sum error = [ 22.8985, 24.5248, 26.2569, 28.1087, 30.0802] +24-11-19 18:52:45 | D | best error = [ 5.4228, 5.4228, 5.4228, 5.4228, 5.4228] +24-11-19 18:52:45 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:52:45 | D | sum error = [ 32.1602, 34.3815, 36.7390, 39.2422, 41.8947] +24-11-19 18:52:45 | D | best error = [ 5.4228, 5.4228, 5.4228, 5.4228, 5.4228] +24-11-19 18:52:45 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:52:45 | D | sum error = [ 44.7358, 47.7097, 50.9053, 54.2686, 57.8396] +24-11-19 18:52:45 | D | best error = [ 5.4228, 5.4228, 5.4228, 5.4228, 5.4228] +24-11-19 18:52:45 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:52:45 | D | sum error = [ 61.6332, 65.6645, 69.9375, 74.4657, 79.2617] +24-11-19 18:52:45 | D | best error = [ 5.4228, 5.4228, 5.4228, 5.4228, 5.4228] +24-11-19 18:52:45 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:52:45 | D | sum error = [ 84.3353, 89.7313, 95.4258, 101.4561, 107.8268] +24-11-19 18:52:45 | D | best error = [ 5.4228, 5.4228, 5.4228, 5.4228, 5.4228] +24-11-19 18:52:45 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:52:45 | D | sum error = [ 114.5843, 121.6896, 129.2193, 137.1756, 145.5415] +24-11-19 18:52:45 | D | best error = [ 5.4228, 5.4228, 5.4228, 5.4228, 5.4228] +24-11-19 18:52:45 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:52:45 | D | sum error = [ 154.3885, 163.6889, 173.4853, 183.7946, 194.6378] +24-11-19 18:52:45 | D | best error = [ 5.4228, 5.4228, 5.4228, 5.4228, 5.4228] +24-11-19 18:52:45 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:52:45 | D | sum error = [ 206.0234, 217.9777, 230.5203, 243.6517, 257.3986] +24-11-19 18:52:45 | D | best error = [ 5.4228, 5.4228, 5.4228, 5.4228, 5.4228] +24-11-19 18:52:45 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:52:45 | D | sum error = [ 271.7765, 286.8044, 302.4859, 318.8435, 335.9049] +24-11-19 18:52:45 | D | best error = [ 5.4228, 5.4228, 5.4228, 5.4228, 5.4228] +24-11-19 18:52:45 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:52:45 | D | sum error = [ 353.6817, 372.1551, 391.3374, 411.2569, 431.8618] +24-11-19 18:52:45 | D | best error = [ 5.4228, 5.4228, 5.4228, 5.4228, 5.4228] +24-11-19 18:52:45 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:52:45 | D | sum error = [ 453.2212, 475.2958, 498.1239, 521.6641, 545.9372] +24-11-19 18:52:45 | D | best error = [ 5.4228, 5.4228, 5.4228, 5.4228, 5.4228] +24-11-19 18:52:45 | D | + error = [5.4228] +24-11-19 18:52:45 | D | - Calibrating model.layers.8.mlp.down_proj.weight +24-11-19 18:52:45 | D | + w: sint8 +24-11-19 18:52:45 | D | + x: None +24-11-19 18:52:45 | D | + y: None +24-11-19 18:52:45 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:52:45 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:52:45 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:52:45 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:52:45 | D | - range ratio = [ 1.0000] +24-11-19 18:52:45 | D | sum error = [ 0.5646] +24-11-19 18:52:45 | D | best error = [ 0.5646] +24-11-19 18:52:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:52:46 | D | sum error = [ 0.5582, 0.5557, 0.5521, 0.5519, 0.5525] +24-11-19 18:52:46 | D | best error = [ 0.5424, 0.5320, 0.5248, 0.5195, 0.5155] +24-11-19 18:52:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:52:46 | D | sum error = [ 0.5541, 0.5590, 0.5674, 0.5761, 0.5904] +24-11-19 18:52:46 | D | best error = [ 0.5127, 0.5103, 0.5087, 0.5074, 0.5066] +24-11-19 18:52:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:52:46 | D | sum error = [ 0.6063, 0.6261, 0.6493, 0.6756, 0.7062] +24-11-19 18:52:46 | D | best error = [ 0.5061, 0.5056, 0.5054, 0.5052, 0.5051] +24-11-19 18:52:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:52:46 | D | sum error = [ 0.7415, 0.7806, 0.8257, 0.8750, 0.9275] +24-11-19 18:52:46 | D | best error = [ 0.5050, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 18:52:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:52:46 | D | sum error = [ 0.9858, 1.0478, 1.1167, 1.1918, 1.2707] +24-11-19 18:52:46 | D | best error = [ 0.5049, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 18:52:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:52:46 | D | sum error = [ 1.3547, 1.4467, 1.5439, 1.6491, 1.7596] +24-11-19 18:52:46 | D | best error = [ 0.5049, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 18:52:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:52:46 | D | sum error = [ 1.8791, 2.0057, 2.1387, 2.2819, 2.4335] +24-11-19 18:52:46 | D | best error = [ 0.5049, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 18:52:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:52:46 | D | sum error = [ 2.5939, 2.7652, 2.9457, 3.1363, 3.3385] +24-11-19 18:52:46 | D | best error = [ 0.5049, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 18:52:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:52:46 | D | sum error = [ 3.5518, 3.7771, 4.0158, 4.2669, 4.5323] +24-11-19 18:52:46 | D | best error = [ 0.5049, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 18:52:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:52:46 | D | sum error = [ 4.8130, 5.1070, 5.4166, 5.7438, 6.0874] +24-11-19 18:52:46 | D | best error = [ 0.5049, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 18:52:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:52:46 | D | sum error = [ 6.4498, 6.8289, 7.2274, 7.6472, 8.0866] +24-11-19 18:52:46 | D | best error = [ 0.5049, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 18:52:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:52:46 | D | sum error = [ 8.5466, 9.0300, 9.5350, 10.0632, 10.6155] +24-11-19 18:52:46 | D | best error = [ 0.5049, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 18:52:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:52:46 | D | sum error = [ 11.1937, 11.7979, 12.4284, 13.0857, 13.7710] +24-11-19 18:52:46 | D | best error = [ 0.5049, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 18:52:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:52:46 | D | sum error = [ 14.4852, 15.2290, 16.0029, 16.8076, 17.6436] +24-11-19 18:52:46 | D | best error = [ 0.5049, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 18:52:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:52:46 | D | sum error = [ 18.5137, 19.4165, 20.3539, 21.3263, 22.3341] +24-11-19 18:52:46 | D | best error = [ 0.5049, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 18:52:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:52:46 | D | sum error = [ 23.3780, 24.4577, 25.5750, 26.7284, 27.9195] +24-11-19 18:52:46 | D | best error = [ 0.5049, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 18:52:46 | D | + error = [0.5049] +24-11-19 18:52:46 | D | - Quantizing model.layers.8.self_attn.q_proj.weight +24-11-19 18:52:47 | D | - Quantizing model.layers.8.self_attn.k_proj.weight +24-11-19 18:52:48 | D | - Quantizing model.layers.8.self_attn.v_proj.weight +24-11-19 18:52:49 | D | - Quantizing model.layers.8.self_attn.o_proj.weight +24-11-19 18:52:49 | D | - Quantizing model.layers.8.mlp.up_proj.weight +24-11-19 18:52:50 | D | - Quantizing model.layers.8.mlp.gate_proj.weight +24-11-19 18:52:51 | D | - Quantizing model.layers.8.mlp.down_proj.weight +24-11-19 18:53:00 | D | - Quantizing layer model.layers.9 +24-11-19 18:53:00 | D | - Calibrating model.layers.9.self_attn.q_proj.weight +24-11-19 18:53:00 | D | + w: sint8 +24-11-19 18:53:00 | D | + x: None +24-11-19 18:53:00 | D | + y: None +24-11-19 18:53:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:53:00 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:53:01 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:53:01 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:53:01 | D | - range ratio = [ 1.0000] +24-11-19 18:53:01 | D | sum error = [ 3.9276] +24-11-19 18:53:01 | D | best error = [ 3.9276] +24-11-19 18:53:13 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:53:13 | D | sum error = [ 3.8231, 3.9017, 3.8443, 3.8733, 3.9296] +24-11-19 18:53:13 | D | best error = [ 3.8231, 3.8231, 3.8231, 3.8231, 3.8231] +24-11-19 18:53:13 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:53:13 | D | sum error = [ 4.1120, 4.2483, 4.4195, 4.6500, 5.0264] +24-11-19 18:53:13 | D | best error = [ 3.8231, 3.8231, 3.8231, 3.8231, 3.8231] +24-11-19 18:53:13 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:53:13 | D | sum error = [ 5.2865, 5.5046, 6.0757, 6.5288, 7.0853] +24-11-19 18:53:13 | D | best error = [ 3.8231, 3.8231, 3.8231, 3.8231, 3.8231] +24-11-19 18:53:13 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:53:13 | D | sum error = [ 7.7170, 8.1283, 8.7633, 9.4860, 10.2042] +24-11-19 18:53:13 | D | best error = [ 3.8231, 3.8231, 3.8231, 3.8231, 3.8231] +24-11-19 18:53:13 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:53:13 | D | sum error = [ 11.2517, 11.9368, 13.0497, 14.1444, 15.9152] +24-11-19 18:53:13 | D | best error = [ 3.8231, 3.8231, 3.8231, 3.8231, 3.8231] +24-11-19 18:53:13 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:53:13 | D | sum error = [ 16.8099, 18.2149, 19.9486, 21.4598, 23.2577] +24-11-19 18:53:13 | D | best error = [ 3.8231, 3.8231, 3.8231, 3.8231, 3.8231] +24-11-19 18:53:13 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:53:13 | D | sum error = [ 25.2505, 27.1740, 29.2503, 31.5923, 34.1872] +24-11-19 18:53:13 | D | best error = [ 3.8231, 3.8231, 3.8231, 3.8231, 3.8231] +24-11-19 18:53:13 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:53:13 | D | sum error = [ 37.0075, 40.0923, 43.3503, 46.5416, 50.3361] +24-11-19 18:53:13 | D | best error = [ 3.8231, 3.8231, 3.8231, 3.8231, 3.8231] +24-11-19 18:53:13 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:53:13 | D | sum error = [ 54.2550, 58.4660, 62.8205, 67.5913, 72.7994] +24-11-19 18:53:13 | D | best error = [ 3.8231, 3.8231, 3.8231, 3.8231, 3.8231] +24-11-19 18:53:13 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:53:13 | D | sum error = [ 78.3861, 84.4492, 90.6110, 97.4874, 104.6961] +24-11-19 18:53:13 | D | best error = [ 3.8231, 3.8231, 3.8231, 3.8231, 3.8231] +24-11-19 18:53:13 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:53:13 | D | sum error = [ 112.5026, 120.4287, 129.1212, 138.2277, 148.2652] +24-11-19 18:53:13 | D | best error = [ 3.8231, 3.8231, 3.8231, 3.8231, 3.8231] +24-11-19 18:53:13 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:53:13 | D | sum error = [ 158.6338, 169.5015, 181.0070, 192.7040, 205.1851] +24-11-19 18:53:13 | D | best error = [ 3.8231, 3.8231, 3.8231, 3.8231, 3.8231] +24-11-19 18:53:13 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:53:13 | D | sum error = [ 218.5319, 232.3143, 246.5294, 261.5364, 277.0139] +24-11-19 18:53:13 | D | best error = [ 3.8231, 3.8231, 3.8231, 3.8231, 3.8231] +24-11-19 18:53:13 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:53:13 | D | sum error = [ 293.3183, 310.2482, 327.7238, 345.8549, 364.6167] +24-11-19 18:53:13 | D | best error = [ 3.8231, 3.8231, 3.8231, 3.8231, 3.8231] +24-11-19 18:53:13 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:53:13 | D | sum error = [ 383.8021, 403.5589, 423.9397, 444.4992, 465.0752] +24-11-19 18:53:13 | D | best error = [ 3.8231, 3.8231, 3.8231, 3.8231, 3.8231] +24-11-19 18:53:13 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:53:13 | D | sum error = [ 485.9718, 506.8390, 527.8337, 548.9045, 569.8572] +24-11-19 18:53:13 | D | best error = [ 3.8231, 3.8231, 3.8231, 3.8231, 3.8231] +24-11-19 18:53:13 | D | + error = [3.8231] +24-11-19 18:53:13 | D | - Calibrating model.layers.9.self_attn.k_proj.weight +24-11-19 18:53:13 | D | + w: sint8 +24-11-19 18:53:13 | D | + x: None +24-11-19 18:53:13 | D | + y: None +24-11-19 18:53:13 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:53:13 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:53:13 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:53:13 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:53:13 | D | - range ratio = [ 1.0000] +24-11-19 18:53:13 | D | sum error = [ 3.1283] +24-11-19 18:53:13 | D | best error = [ 3.1283] +24-11-19 18:53:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:53:25 | D | sum error = [ 3.2059, 3.0277, 3.2569, 3.2275, 3.3148] +24-11-19 18:53:25 | D | best error = [ 3.1283, 3.0277, 3.0277, 3.0277, 3.0277] +24-11-19 18:53:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:53:25 | D | sum error = [ 3.3004, 3.4727, 3.5933, 3.8225, 4.5562] +24-11-19 18:53:25 | D | best error = [ 3.0277, 3.0277, 3.0277, 3.0277, 3.0277] +24-11-19 18:53:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:53:25 | D | sum error = [ 4.0641, 5.0504, 5.3982, 5.9065, 6.5492] +24-11-19 18:53:25 | D | best error = [ 3.0277, 3.0277, 3.0277, 3.0277, 3.0277] +24-11-19 18:53:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:53:25 | D | sum error = [ 6.6166, 7.3176, 7.7538, 8.9517, 8.8904] +24-11-19 18:53:25 | D | best error = [ 3.0277, 3.0277, 3.0277, 3.0277, 3.0277] +24-11-19 18:53:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:53:25 | D | sum error = [ 10.1062, 11.0738, 12.0426, 13.0872, 14.1728] +24-11-19 18:53:25 | D | best error = [ 3.0277, 3.0277, 3.0277, 3.0277, 3.0277] +24-11-19 18:53:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:53:25 | D | sum error = [ 15.2888, 16.7120, 17.9494, 19.4433, 20.9033] +24-11-19 18:53:25 | D | best error = [ 3.0277, 3.0277, 3.0277, 3.0277, 3.0277] +24-11-19 18:53:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:53:25 | D | sum error = [ 22.3020, 24.7829, 26.7137, 28.1731, 30.9785] +24-11-19 18:53:25 | D | best error = [ 3.0277, 3.0277, 3.0277, 3.0277, 3.0277] +24-11-19 18:53:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:53:25 | D | sum error = [ 33.4293, 36.1838, 39.7119, 42.9570, 46.0746] +24-11-19 18:53:25 | D | best error = [ 3.0277, 3.0277, 3.0277, 3.0277, 3.0277] +24-11-19 18:53:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:53:25 | D | sum error = [ 49.3156, 53.2148, 57.7484, 61.7962, 66.4403] +24-11-19 18:53:25 | D | best error = [ 3.0277, 3.0277, 3.0277, 3.0277, 3.0277] +24-11-19 18:53:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:53:25 | D | sum error = [ 72.0521, 77.1685, 82.6379, 89.2656, 95.8069] +24-11-19 18:53:25 | D | best error = [ 3.0277, 3.0277, 3.0277, 3.0277, 3.0277] +24-11-19 18:53:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:53:25 | D | sum error = [ 104.1956, 109.7783, 117.8907, 127.1386, 135.6707] +24-11-19 18:53:25 | D | best error = [ 3.0277, 3.0277, 3.0277, 3.0277, 3.0277] +24-11-19 18:53:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:53:25 | D | sum error = [ 146.5315, 156.9886, 167.3511, 179.5042, 189.2088] +24-11-19 18:53:25 | D | best error = [ 3.0277, 3.0277, 3.0277, 3.0277, 3.0277] +24-11-19 18:53:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:53:25 | D | sum error = [ 202.9488, 217.2884, 230.8877, 246.3601, 261.9505] +24-11-19 18:53:25 | D | best error = [ 3.0277, 3.0277, 3.0277, 3.0277, 3.0277] +24-11-19 18:53:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:53:25 | D | sum error = [ 277.1901, 296.9622, 314.5515, 327.4379, 348.2352] +24-11-19 18:53:25 | D | best error = [ 3.0277, 3.0277, 3.0277, 3.0277, 3.0277] +24-11-19 18:53:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:53:25 | D | sum error = [ 367.3437, 388.4407, 409.1373, 429.4546, 451.9214] +24-11-19 18:53:25 | D | best error = [ 3.0277, 3.0277, 3.0277, 3.0277, 3.0277] +24-11-19 18:53:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:53:25 | D | sum error = [ 474.3825, 495.6092, 515.5973, 537.9058, 560.6258] +24-11-19 18:53:25 | D | best error = [ 3.0277, 3.0277, 3.0277, 3.0277, 3.0277] +24-11-19 18:53:25 | D | + error = [3.0277] +24-11-19 18:53:25 | D | - Calibrating model.layers.9.self_attn.v_proj.weight +24-11-19 18:53:25 | D | + w: sint8 +24-11-19 18:53:25 | D | + x: None +24-11-19 18:53:25 | D | + y: None +24-11-19 18:53:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:53:25 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:53:25 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:53:25 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:53:25 | D | - range ratio = [ 1.0000] +24-11-19 18:53:25 | D | sum error = [ 1.5155] +24-11-19 18:53:25 | D | best error = [ 1.5155] +24-11-19 18:53:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:53:25 | D | sum error = [ 1.4846, 1.4869, 1.4861, 1.5136, 1.5481] +24-11-19 18:53:25 | D | best error = [ 1.3918, 1.3497, 1.3305, 1.3182, 1.3128] +24-11-19 18:53:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:53:25 | D | sum error = [ 1.5734, 1.6196, 1.6909, 1.7683, 1.8770] +24-11-19 18:53:25 | D | best error = [ 1.3100, 1.3089, 1.3083, 1.3079, 1.3079] +24-11-19 18:53:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:53:25 | D | sum error = [ 1.9685, 2.0880, 2.2213, 2.3689, 2.5329] +24-11-19 18:53:25 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 18:53:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:53:25 | D | sum error = [ 2.7143, 2.9169, 3.1262, 3.3473, 3.5933] +24-11-19 18:53:25 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 18:53:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:53:25 | D | sum error = [ 3.8468, 4.1142, 4.4017, 4.7178, 5.0319] +24-11-19 18:53:25 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 18:53:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:53:25 | D | sum error = [ 5.3654, 5.7428, 6.1359, 6.5293, 6.9686] +24-11-19 18:53:25 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 18:53:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:53:25 | D | sum error = [ 7.4178, 7.9069, 8.4136, 8.9446, 9.5171] +24-11-19 18:53:25 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 18:53:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:53:25 | D | sum error = [ 10.1043, 10.7327, 11.3957, 12.0977, 12.8040] +24-11-19 18:53:25 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 18:53:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:53:25 | D | sum error = [ 13.5730, 14.3842, 15.2318, 16.1326, 17.0589] +24-11-19 18:53:25 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 18:53:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:53:25 | D | sum error = [ 18.0458, 19.0806, 20.1647, 21.3047, 22.4921] +24-11-19 18:53:25 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 18:53:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:53:25 | D | sum error = [ 23.7517, 25.0505, 26.4222, 27.8445, 29.3258] +24-11-19 18:53:25 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 18:53:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:53:25 | D | sum error = [ 30.8811, 32.4900, 34.1791, 35.9361, 37.7563] +24-11-19 18:53:25 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 18:53:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:53:25 | D | sum error = [ 39.6576, 41.6314, 43.6692, 45.7923, 48.0012] +24-11-19 18:53:25 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 18:53:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:53:25 | D | sum error = [ 50.2933, 52.6618, 55.1277, 57.6746, 60.3189] +24-11-19 18:53:25 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 18:53:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:53:25 | D | sum error = [ 63.0727, 65.9145, 68.8617, 71.9142, 75.0673] +24-11-19 18:53:25 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 18:53:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:53:25 | D | sum error = [ 78.3037, 81.6619, 85.1176, 88.6774, 92.3427] +24-11-19 18:53:25 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 18:53:25 | D | + error = [1.3079] +24-11-19 18:53:25 | D | - Calibrating model.layers.9.self_attn.o_proj.weight +24-11-19 18:53:25 | D | + w: sint8 +24-11-19 18:53:25 | D | + x: None +24-11-19 18:53:25 | D | + y: None +24-11-19 18:53:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:53:25 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:53:25 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:53:25 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:53:25 | D | - range ratio = [ 1.0000] +24-11-19 18:53:25 | D | sum error = [ 0.5988] +24-11-19 18:53:25 | D | best error = [ 0.5988] +24-11-19 18:53:26 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:53:26 | D | sum error = [ 0.5930, 0.5906, 0.5868, 0.5880, 0.5964] +24-11-19 18:53:26 | D | best error = [ 0.5446, 0.5202, 0.5060, 0.4950, 0.4882] +24-11-19 18:53:26 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:53:26 | D | sum error = [ 0.5957, 0.6081, 0.6182, 0.6324, 0.6502] +24-11-19 18:53:26 | D | best error = [ 0.4828, 0.4790, 0.4763, 0.4744, 0.4728] +24-11-19 18:53:26 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:53:26 | D | sum error = [ 0.6711, 0.6960, 0.7226, 0.7538, 0.7841] +24-11-19 18:53:26 | D | best error = [ 0.4718, 0.4711, 0.4706, 0.4703, 0.4700] +24-11-19 18:53:26 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:53:26 | D | sum error = [ 0.8265, 0.8686, 0.9099, 0.9582, 1.0101] +24-11-19 18:53:26 | D | best error = [ 0.4698, 0.4696, 0.4695, 0.4693, 0.4692] +24-11-19 18:53:26 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:53:26 | D | sum error = [ 1.0622, 1.1208, 1.1835, 1.2483, 1.3158] +24-11-19 18:53:26 | D | best error = [ 0.4691, 0.4691, 0.4690, 0.4690, 0.4690] +24-11-19 18:53:26 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:53:26 | D | sum error = [ 1.3890, 1.4621, 1.5436, 1.6302, 1.7199] +24-11-19 18:53:26 | D | best error = [ 0.4690, 0.4690, 0.4689, 0.4689, 0.4689] +24-11-19 18:53:26 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:53:26 | D | sum error = [ 1.8137, 1.9098, 2.0154, 2.1217, 2.2345] +24-11-19 18:53:26 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 18:53:26 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:53:26 | D | sum error = [ 2.3530, 2.4802, 2.6102, 2.7485, 2.8942] +24-11-19 18:53:26 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 18:53:26 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:53:26 | D | sum error = [ 3.0425, 3.2010, 3.3631, 3.5379, 3.7172] +24-11-19 18:53:26 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 18:53:26 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:53:26 | D | sum error = [ 3.9093, 4.1079, 4.3168, 4.5313, 4.7594] +24-11-19 18:53:26 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 18:53:26 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:53:26 | D | sum error = [ 4.9992, 5.2464, 5.5025, 5.7740, 6.0577] +24-11-19 18:53:26 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 18:53:26 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:53:26 | D | sum error = [ 6.3518, 6.6595, 6.9776, 7.3092, 7.6533] +24-11-19 18:53:26 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 18:53:26 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:53:26 | D | sum error = [ 8.0123, 8.3840, 8.7703, 9.1733, 9.5953] +24-11-19 18:53:26 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 18:53:26 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:53:26 | D | sum error = [ 10.0306, 10.4825, 10.9524, 11.4374, 11.9388] +24-11-19 18:53:26 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 18:53:26 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:53:26 | D | sum error = [ 12.4578, 12.9968, 13.5532, 14.1286, 14.7245] +24-11-19 18:53:26 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 18:53:26 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:53:26 | D | sum error = [ 15.3433, 15.9825, 16.6458, 17.3310, 18.0444] +24-11-19 18:53:26 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 18:53:26 | D | + error = [0.4689] +24-11-19 18:53:26 | D | - Calibrating model.layers.9.mlp.up_proj.weight +24-11-19 18:53:26 | D | + w: sint8 +24-11-19 18:53:26 | D | + x: None +24-11-19 18:53:26 | D | + y: None +24-11-19 18:53:26 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:53:26 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:53:26 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:53:26 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:53:26 | D | - range ratio = [ 1.0000] +24-11-19 18:53:26 | D | sum error = [ 4.7746] +24-11-19 18:53:26 | D | best error = [ 4.7746] +24-11-19 18:53:27 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:53:27 | D | sum error = [ 4.7424, 4.7342, 4.7440, 4.8013, 4.8915] +24-11-19 18:53:27 | D | best error = [ 4.4661, 4.3420, 4.2771, 4.2399, 4.2209] +24-11-19 18:53:27 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:53:27 | D | sum error = [ 5.0194, 5.1865, 5.3997, 5.6576, 5.9478] +24-11-19 18:53:27 | D | best error = [ 4.2112, 4.2073, 4.2059, 4.2056, 4.2055] +24-11-19 18:53:27 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:53:27 | D | sum error = [ 6.2993, 6.6832, 7.1240, 7.6001, 8.1243] +24-11-19 18:53:27 | D | best error = [ 4.2055, 4.2055, 4.2055, 4.2055, 4.2055] +24-11-19 18:53:27 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:53:27 | D | sum error = [ 8.7105, 9.3195, 9.9950, 10.7216, 11.4886] +24-11-19 18:53:27 | D | best error = [ 4.2055, 4.2055, 4.2055, 4.2055, 4.2055] +24-11-19 18:53:27 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:53:27 | D | sum error = [ 12.3061, 13.1881, 14.1296, 15.1215, 16.1703] +24-11-19 18:53:27 | D | best error = [ 4.2055, 4.2055, 4.2055, 4.2055, 4.2055] +24-11-19 18:53:27 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:53:27 | D | sum error = [ 17.2906, 18.4731, 19.7167, 21.0499, 22.4502] +24-11-19 18:53:27 | D | best error = [ 4.2055, 4.2055, 4.2055, 4.2055, 4.2055] +24-11-19 18:53:27 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:53:27 | D | sum error = [ 23.9185, 25.4793, 27.1248, 28.8546, 30.6935] +24-11-19 18:53:27 | D | best error = [ 4.2055, 4.2055, 4.2055, 4.2055, 4.2055] +24-11-19 18:53:27 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:53:27 | D | sum error = [ 32.6198, 34.6458, 36.7790, 39.0267, 41.3949] +24-11-19 18:53:27 | D | best error = [ 4.2055, 4.2055, 4.2055, 4.2055, 4.2055] +24-11-19 18:53:27 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:53:27 | D | sum error = [ 43.8678, 46.4697, 49.2044, 52.0636, 55.0688] +24-11-19 18:53:27 | D | best error = [ 4.2055, 4.2055, 4.2055, 4.2055, 4.2055] +24-11-19 18:53:27 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:53:27 | D | sum error = [ 58.2143, 61.5233, 64.9818, 68.6119, 72.3988] +24-11-19 18:53:27 | D | best error = [ 4.2055, 4.2055, 4.2055, 4.2055, 4.2055] +24-11-19 18:53:27 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:53:27 | D | sum error = [ 76.3670, 80.5079, 84.8474, 89.3708, 94.0963] +24-11-19 18:53:27 | D | best error = [ 4.2055, 4.2055, 4.2055, 4.2055, 4.2055] +24-11-19 18:53:27 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:53:27 | D | sum error = [ 99.0337, 104.1808, 109.5500, 115.1399, 120.9544] +24-11-19 18:53:27 | D | best error = [ 4.2055, 4.2055, 4.2055, 4.2055, 4.2055] +24-11-19 18:53:27 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:53:27 | D | sum error = [ 127.0115, 133.3020, 139.8464, 146.6478, 153.7145] +24-11-19 18:53:27 | D | best error = [ 4.2055, 4.2055, 4.2055, 4.2055, 4.2055] +24-11-19 18:53:27 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:53:27 | D | sum error = [ 161.0384, 168.6391, 176.5260, 184.6944, 193.1480] +24-11-19 18:53:27 | D | best error = [ 4.2055, 4.2055, 4.2055, 4.2055, 4.2055] +24-11-19 18:53:27 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:53:27 | D | sum error = [ 201.8978, 210.9445, 220.2862, 229.9428, 239.9122] +24-11-19 18:53:27 | D | best error = [ 4.2055, 4.2055, 4.2055, 4.2055, 4.2055] +24-11-19 18:53:27 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:53:27 | D | sum error = [ 250.1809, 260.7686, 271.6711, 282.9068, 294.4776] +24-11-19 18:53:27 | D | best error = [ 4.2055, 4.2055, 4.2055, 4.2055, 4.2055] +24-11-19 18:53:27 | D | + error = [4.2055] +24-11-19 18:53:27 | D | - Calibrating model.layers.9.mlp.gate_proj.weight +24-11-19 18:53:27 | D | + w: sint8 +24-11-19 18:53:27 | D | + x: None +24-11-19 18:53:27 | D | + y: None +24-11-19 18:53:27 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:53:27 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:53:27 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:53:27 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:53:28 | D | - range ratio = [ 1.0000] +24-11-19 18:53:28 | D | sum error = [ 6.2402] +24-11-19 18:53:28 | D | best error = [ 6.2402] +24-11-19 18:53:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:53:29 | D | sum error = [ 6.1804, 6.1856, 6.1931, 6.2769, 6.3897] +24-11-19 18:53:29 | D | best error = [ 5.8299, 5.6704, 5.5855, 5.5367, 5.5108] +24-11-19 18:53:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:53:29 | D | sum error = [ 6.5547, 6.7607, 7.0566, 7.3731, 7.7654] +24-11-19 18:53:29 | D | best error = [ 5.4997, 5.4946, 5.4927, 5.4921, 5.4920] +24-11-19 18:53:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:53:29 | D | sum error = [ 8.2378, 8.7373, 9.3239, 9.9537, 10.6554] +24-11-19 18:53:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 18:53:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:53:29 | D | sum error = [ 11.4140, 12.2596, 13.1528, 14.1179, 15.1730] +24-11-19 18:53:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 18:53:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:53:29 | D | sum error = [ 16.2879, 17.4940, 18.7591, 20.1425, 21.6191] +24-11-19 18:53:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 18:53:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:53:29 | D | sum error = [ 23.1739, 24.8240, 26.5891, 28.4722, 30.4690] +24-11-19 18:53:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 18:53:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:53:29 | D | sum error = [ 32.5953, 34.8542, 37.2693, 39.8202, 42.5352] +24-11-19 18:53:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 18:53:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:53:29 | D | sum error = [ 45.4095, 48.4702, 51.7206, 55.1498, 58.8194] +24-11-19 18:53:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 18:53:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:53:29 | D | sum error = [ 62.6896, 66.8307, 71.1778, 75.8116, 80.7244] +24-11-19 18:53:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 18:53:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:53:29 | D | sum error = [ 85.9324, 91.4572, 97.3011, 103.4903, 110.0270] +24-11-19 18:53:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 18:53:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:53:29 | D | sum error = [ 116.9505, 124.2696, 132.0084, 140.1769, 148.7802] +24-11-19 18:53:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 18:53:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:53:29 | D | sum error = [ 157.8645, 167.4476, 177.5322, 188.1372, 199.2885] +24-11-19 18:53:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 18:53:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:53:29 | D | sum error = [ 211.0232, 223.3295, 236.2446, 249.7951, 263.9968] +24-11-19 18:53:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 18:53:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:53:29 | D | sum error = [ 278.8269, 294.3405, 310.5633, 327.4672, 345.1035] +24-11-19 18:53:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 18:53:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:53:29 | D | sum error = [ 363.4495, 382.5660, 402.4161, 423.0445, 444.4282] +24-11-19 18:53:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 18:53:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:53:29 | D | sum error = [ 466.5684, 489.4831, 513.1534, 537.5890, 562.7781] +24-11-19 18:53:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 18:53:29 | D | + error = [5.4920] +24-11-19 18:53:29 | D | - Calibrating model.layers.9.mlp.down_proj.weight +24-11-19 18:53:29 | D | + w: sint8 +24-11-19 18:53:29 | D | + x: None +24-11-19 18:53:29 | D | + y: None +24-11-19 18:53:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:53:29 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:53:29 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:53:29 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:53:29 | D | - range ratio = [ 1.0000] +24-11-19 18:53:29 | D | sum error = [ 0.5906] +24-11-19 18:53:29 | D | best error = [ 0.5906] +24-11-19 18:53:30 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:53:30 | D | sum error = [ 0.5843, 0.5794, 0.5773, 0.5767, 0.5766] +24-11-19 18:53:30 | D | best error = [ 0.5655, 0.5529, 0.5446, 0.5387, 0.5345] +24-11-19 18:53:30 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:53:30 | D | sum error = [ 0.5784, 0.5848, 0.5915, 0.6025, 0.6150] +24-11-19 18:53:30 | D | best error = [ 0.5312, 0.5286, 0.5269, 0.5258, 0.5249] +24-11-19 18:53:30 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:53:30 | D | sum error = [ 0.6326, 0.6527, 0.6753, 0.7029, 0.7342] +24-11-19 18:53:30 | D | best error = [ 0.5243, 0.5240, 0.5237, 0.5235, 0.5234] +24-11-19 18:53:30 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:53:30 | D | sum error = [ 0.7701, 0.8111, 0.8554, 0.9045, 0.9571] +24-11-19 18:53:30 | D | best error = [ 0.5233, 0.5233, 0.5233, 0.5233, 0.5233] +24-11-19 18:53:30 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:53:30 | D | sum error = [ 1.0170, 1.0821, 1.1512, 1.2273, 1.3080] +24-11-19 18:53:30 | D | best error = [ 0.5232, 0.5232, 0.5232, 0.5232, 0.5232] +24-11-19 18:53:30 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:53:30 | D | sum error = [ 1.3949, 1.4878, 1.5881, 1.6948, 1.8084] +24-11-19 18:53:30 | D | best error = [ 0.5232, 0.5232, 0.5232, 0.5232, 0.5232] +24-11-19 18:53:30 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:53:30 | D | sum error = [ 1.9320, 2.0598, 2.1987, 2.3447, 2.5002] +24-11-19 18:53:30 | D | best error = [ 0.5232, 0.5232, 0.5232, 0.5232, 0.5232] +24-11-19 18:53:30 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:53:30 | D | sum error = [ 2.6672, 2.8422, 3.0299, 3.2269, 3.4356] +24-11-19 18:53:30 | D | best error = [ 0.5232, 0.5232, 0.5232, 0.5232, 0.5232] +24-11-19 18:53:30 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:53:30 | D | sum error = [ 3.6575, 3.8907, 4.1383, 4.3992, 4.6732] +24-11-19 18:53:30 | D | best error = [ 0.5232, 0.5232, 0.5232, 0.5232, 0.5232] +24-11-19 18:53:30 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:53:30 | D | sum error = [ 4.9638, 5.2675, 5.5895, 5.9273, 6.2842] +24-11-19 18:53:30 | D | best error = [ 0.5232, 0.5232, 0.5232, 0.5232, 0.5232] +24-11-19 18:53:30 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:53:30 | D | sum error = [ 6.6586, 7.0521, 7.4642, 7.8970, 8.3497] +24-11-19 18:53:30 | D | best error = [ 0.5232, 0.5232, 0.5232, 0.5232, 0.5232] +24-11-19 18:53:30 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:53:30 | D | sum error = [ 8.8254, 9.3237, 9.8449, 10.3902, 10.9602] +24-11-19 18:53:30 | D | best error = [ 0.5232, 0.5232, 0.5232, 0.5232, 0.5232] +24-11-19 18:53:30 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:53:30 | D | sum error = [ 11.5569, 12.1801, 12.8314, 13.5100, 14.2185] +24-11-19 18:53:30 | D | best error = [ 0.5232, 0.5232, 0.5232, 0.5232, 0.5232] +24-11-19 18:53:30 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:53:30 | D | sum error = [ 14.9567, 15.7247, 16.5234, 17.3544, 18.2172] +24-11-19 18:53:30 | D | best error = [ 0.5232, 0.5232, 0.5232, 0.5232, 0.5232] +24-11-19 18:53:30 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:53:30 | D | sum error = [ 19.1140, 20.0446, 21.0107, 22.0110, 23.0490] +24-11-19 18:53:30 | D | best error = [ 0.5232, 0.5232, 0.5232, 0.5232, 0.5232] +24-11-19 18:53:30 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:53:30 | D | sum error = [ 24.1232, 25.2355, 26.3864, 27.5763, 28.8051] +24-11-19 18:53:30 | D | best error = [ 0.5232, 0.5232, 0.5232, 0.5232, 0.5232] +24-11-19 18:53:30 | D | + error = [0.5232] +24-11-19 18:53:30 | D | - Quantizing model.layers.9.self_attn.q_proj.weight +24-11-19 18:53:31 | D | - Quantizing model.layers.9.self_attn.k_proj.weight +24-11-19 18:53:32 | D | - Quantizing model.layers.9.self_attn.v_proj.weight +24-11-19 18:53:33 | D | - Quantizing model.layers.9.self_attn.o_proj.weight +24-11-19 18:53:33 | D | - Quantizing model.layers.9.mlp.up_proj.weight +24-11-19 18:53:34 | D | - Quantizing model.layers.9.mlp.gate_proj.weight +24-11-19 18:53:35 | D | - Quantizing model.layers.9.mlp.down_proj.weight +24-11-19 18:53:44 | D | - Quantizing layer model.layers.10 +24-11-19 18:53:44 | D | - Calibrating model.layers.10.self_attn.q_proj.weight +24-11-19 18:53:44 | D | + w: sint8 +24-11-19 18:53:44 | D | + x: None +24-11-19 18:53:44 | D | + y: None +24-11-19 18:53:44 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:53:44 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:53:45 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:53:45 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:53:45 | D | - range ratio = [ 1.0000] +24-11-19 18:53:45 | D | sum error = [ 4.0879] +24-11-19 18:53:45 | D | best error = [ 4.0879] +24-11-19 18:53:56 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:53:56 | D | sum error = [ 4.0329, 4.0882, 4.0857, 4.1941, 4.2349] +24-11-19 18:53:56 | D | best error = [ 4.0329, 4.0329, 4.0329, 4.0329, 4.0329] +24-11-19 18:53:56 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:53:56 | D | sum error = [ 4.3592, 4.4326, 4.5086, 5.0093, 5.1154] +24-11-19 18:53:56 | D | best error = [ 4.0329, 4.0329, 4.0329, 4.0329, 4.0329] +24-11-19 18:53:56 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:53:56 | D | sum error = [ 5.5141, 5.9249, 6.3329, 6.8851, 7.5639] +24-11-19 18:53:56 | D | best error = [ 4.0329, 4.0329, 4.0329, 4.0329, 4.0329] +24-11-19 18:53:56 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:53:56 | D | sum error = [ 8.0433, 8.5833, 9.6830, 10.4089, 11.1725] +24-11-19 18:53:56 | D | best error = [ 4.0329, 4.0329, 4.0329, 4.0329, 4.0329] +24-11-19 18:53:56 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:53:56 | D | sum error = [ 12.1165, 13.3682, 14.3741, 15.4795, 17.0118] +24-11-19 18:53:56 | D | best error = [ 4.0329, 4.0329, 4.0329, 4.0329, 4.0329] +24-11-19 18:53:56 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:53:56 | D | sum error = [ 17.8832, 19.5181, 20.7958, 22.4057, 24.1053] +24-11-19 18:53:56 | D | best error = [ 4.0329, 4.0329, 4.0329, 4.0329, 4.0329] +24-11-19 18:53:56 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:53:56 | D | sum error = [ 25.9754, 28.0382, 29.7599, 32.0133, 34.3901] +24-11-19 18:53:56 | D | best error = [ 4.0329, 4.0329, 4.0329, 4.0329, 4.0329] +24-11-19 18:53:56 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:53:56 | D | sum error = [ 36.9010, 39.9769, 42.9978, 46.3945, 49.6694] +24-11-19 18:53:56 | D | best error = [ 4.0329, 4.0329, 4.0329, 4.0329, 4.0329] +24-11-19 18:53:56 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:53:56 | D | sum error = [ 53.0131, 57.2556, 60.8862, 65.1799, 69.5785] +24-11-19 18:53:56 | D | best error = [ 4.0329, 4.0329, 4.0329, 4.0329, 4.0329] +24-11-19 18:53:56 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:53:56 | D | sum error = [ 74.1777, 79.1065, 84.5235, 90.3146, 96.3320] +24-11-19 18:53:56 | D | best error = [ 4.0329, 4.0329, 4.0329, 4.0329, 4.0329] +24-11-19 18:53:56 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:53:56 | D | sum error = [ 103.0811, 109.7138, 117.0448, 124.8618, 133.0985] +24-11-19 18:53:56 | D | best error = [ 4.0329, 4.0329, 4.0329, 4.0329, 4.0329] +24-11-19 18:53:56 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:53:56 | D | sum error = [ 141.5626, 150.8747, 160.4883, 170.6857, 181.3746] +24-11-19 18:53:56 | D | best error = [ 4.0329, 4.0329, 4.0329, 4.0329, 4.0329] +24-11-19 18:53:56 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:53:56 | D | sum error = [ 192.6943, 204.6720, 217.4024, 230.6656, 244.5663] +24-11-19 18:53:56 | D | best error = [ 4.0329, 4.0329, 4.0329, 4.0329, 4.0329] +24-11-19 18:53:56 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:53:56 | D | sum error = [ 259.2962, 274.7589, 290.9247, 307.9883, 325.8814] +24-11-19 18:53:56 | D | best error = [ 4.0329, 4.0329, 4.0329, 4.0329, 4.0329] +24-11-19 18:53:56 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:53:56 | D | sum error = [ 344.4455, 363.8167, 383.8681, 404.3485, 425.5849] +24-11-19 18:53:56 | D | best error = [ 4.0329, 4.0329, 4.0329, 4.0329, 4.0329] +24-11-19 18:53:56 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:53:56 | D | sum error = [ 447.3480, 469.5811, 492.1465, 514.9801, 537.9216] +24-11-19 18:53:56 | D | best error = [ 4.0329, 4.0329, 4.0329, 4.0329, 4.0329] +24-11-19 18:53:56 | D | + error = [4.0329] +24-11-19 18:53:56 | D | - Calibrating model.layers.10.self_attn.k_proj.weight +24-11-19 18:53:56 | D | + w: sint8 +24-11-19 18:53:56 | D | + x: None +24-11-19 18:53:56 | D | + y: None +24-11-19 18:53:56 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:53:56 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:53:57 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:53:57 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:53:57 | D | - range ratio = [ 1.0000] +24-11-19 18:53:57 | D | sum error = [ 3.5643] +24-11-19 18:53:57 | D | best error = [ 3.5643] +24-11-19 18:54:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:54:08 | D | sum error = [ 3.4414, 3.4357, 3.4359, 3.4938, 3.5756] +24-11-19 18:54:08 | D | best error = [ 3.4414, 3.4357, 3.4357, 3.4357, 3.4357] +24-11-19 18:54:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:54:08 | D | sum error = [ 4.0361, 3.7136, 3.9716, 4.6864, 4.7093] +24-11-19 18:54:08 | D | best error = [ 3.4357, 3.4357, 3.4357, 3.4357, 3.4357] +24-11-19 18:54:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:54:08 | D | sum error = [ 5.4218, 6.4537, 6.2428, 6.5909, 7.6554] +24-11-19 18:54:08 | D | best error = [ 3.4357, 3.4357, 3.4357, 3.4357, 3.4357] +24-11-19 18:54:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:54:08 | D | sum error = [ 7.6183, 9.0441, 10.1563, 9.8582, 11.5873] +24-11-19 18:54:08 | D | best error = [ 3.4357, 3.4357, 3.4357, 3.4357, 3.4357] +24-11-19 18:54:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:54:08 | D | sum error = [ 13.3556, 13.6351, 15.1255, 16.4649, 17.9233] +24-11-19 18:54:08 | D | best error = [ 3.4357, 3.4357, 3.4357, 3.4357, 3.4357] +24-11-19 18:54:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:54:08 | D | sum error = [ 18.1766, 21.1448, 22.0071, 22.6781, 23.6929] +24-11-19 18:54:08 | D | best error = [ 3.4357, 3.4357, 3.4357, 3.4357, 3.4357] +24-11-19 18:54:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:54:08 | D | sum error = [ 26.4613, 28.0637, 30.1533, 32.4967, 34.7961] +24-11-19 18:54:08 | D | best error = [ 3.4357, 3.4357, 3.4357, 3.4357, 3.4357] +24-11-19 18:54:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:54:08 | D | sum error = [ 37.3969, 41.0435, 43.4376, 47.9487, 50.0027] +24-11-19 18:54:08 | D | best error = [ 3.4357, 3.4357, 3.4357, 3.4357, 3.4357] +24-11-19 18:54:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:54:08 | D | sum error = [ 53.6643, 58.0649, 61.4339, 65.6757, 70.4329] +24-11-19 18:54:08 | D | best error = [ 3.4357, 3.4357, 3.4357, 3.4357, 3.4357] +24-11-19 18:54:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:54:08 | D | sum error = [ 74.3859, 79.5067, 84.4890, 90.2830, 97.0291] +24-11-19 18:54:08 | D | best error = [ 3.4357, 3.4357, 3.4357, 3.4357, 3.4357] +24-11-19 18:54:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:54:08 | D | sum error = [ 102.9083, 109.3571, 116.7600, 124.2990, 132.8473] +24-11-19 18:54:08 | D | best error = [ 3.4357, 3.4357, 3.4357, 3.4357, 3.4357] +24-11-19 18:54:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:54:08 | D | sum error = [ 140.1818, 150.3962, 159.9664, 169.5133, 179.6956] +24-11-19 18:54:08 | D | best error = [ 3.4357, 3.4357, 3.4357, 3.4357, 3.4357] +24-11-19 18:54:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:54:08 | D | sum error = [ 191.5246, 202.6044, 214.3195, 227.3797, 239.8555] +24-11-19 18:54:08 | D | best error = [ 3.4357, 3.4357, 3.4357, 3.4357, 3.4357] +24-11-19 18:54:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:54:08 | D | sum error = [ 253.7598, 268.1913, 284.5001, 301.1061, 318.0629] +24-11-19 18:54:08 | D | best error = [ 3.4357, 3.4357, 3.4357, 3.4357, 3.4357] +24-11-19 18:54:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:54:08 | D | sum error = [ 336.3084, 355.2300, 375.7488, 397.8293, 418.7320] +24-11-19 18:54:08 | D | best error = [ 3.4357, 3.4357, 3.4357, 3.4357, 3.4357] +24-11-19 18:54:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:54:08 | D | sum error = [ 441.1474, 463.5495, 484.6664, 508.7868, 532.2415] +24-11-19 18:54:08 | D | best error = [ 3.4357, 3.4357, 3.4357, 3.4357, 3.4357] +24-11-19 18:54:08 | D | + error = [3.4357] +24-11-19 18:54:08 | D | - Calibrating model.layers.10.self_attn.v_proj.weight +24-11-19 18:54:08 | D | + w: sint8 +24-11-19 18:54:08 | D | + x: None +24-11-19 18:54:08 | D | + y: None +24-11-19 18:54:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:54:08 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:54:08 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:54:09 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:54:09 | D | - range ratio = [ 1.0000] +24-11-19 18:54:09 | D | sum error = [ 1.2931] +24-11-19 18:54:09 | D | best error = [ 1.2931] +24-11-19 18:54:09 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:54:09 | D | sum error = [ 1.3015, 1.2853, 1.2940, 1.3082, 1.3242] +24-11-19 18:54:09 | D | best error = [ 1.2037, 1.1669, 1.1482, 1.1377, 1.1307] +24-11-19 18:54:09 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:54:09 | D | sum error = [ 1.3687, 1.4235, 1.4743, 1.5509, 1.6300] +24-11-19 18:54:09 | D | best error = [ 1.1289, 1.1278, 1.1274, 1.1273, 1.1273] +24-11-19 18:54:09 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:54:09 | D | sum error = [ 1.7165, 1.8473, 1.9671, 2.1094, 2.2625] +24-11-19 18:54:09 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 18:54:09 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:54:09 | D | sum error = [ 2.4045, 2.5821, 2.7853, 2.9851, 3.2138] +24-11-19 18:54:09 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 18:54:09 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:54:09 | D | sum error = [ 3.4368, 3.6794, 3.9365, 4.2031, 4.4993] +24-11-19 18:54:09 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 18:54:09 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:54:09 | D | sum error = [ 4.8142, 5.1414, 5.4713, 5.8592, 6.2332] +24-11-19 18:54:09 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 18:54:09 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:54:09 | D | sum error = [ 6.6528, 7.0762, 7.5334, 8.0242, 8.5343] +24-11-19 18:54:09 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 18:54:09 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:54:09 | D | sum error = [ 9.0835, 9.6664, 10.2537, 10.8891, 11.5512] +24-11-19 18:54:09 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 18:54:09 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:54:09 | D | sum error = [ 12.2462, 12.9689, 13.7457, 14.5355, 15.3966] +24-11-19 18:54:09 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 18:54:09 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:54:09 | D | sum error = [ 16.2799, 17.2093, 18.1887, 19.2065, 20.2794] +24-11-19 18:54:09 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 18:54:09 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:54:09 | D | sum error = [ 21.4050, 22.5716, 23.8083, 25.0863, 26.4301] +24-11-19 18:54:09 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 18:54:09 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:54:09 | D | sum error = [ 27.8278, 29.2909, 30.8202, 32.4154, 34.0767] +24-11-19 18:54:09 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 18:54:09 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:54:09 | D | sum error = [ 35.8105, 37.6032, 39.4812, 41.4298, 43.4509] +24-11-19 18:54:09 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 18:54:09 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:54:09 | D | sum error = [ 45.5512, 47.7220, 49.9756, 52.3183, 54.7266] +24-11-19 18:54:09 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 18:54:09 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:54:09 | D | sum error = [ 57.2288, 59.8198, 62.4901, 65.2596, 68.1086] +24-11-19 18:54:09 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 18:54:09 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:54:09 | D | sum error = [ 71.0433, 74.0726, 77.1897, 80.4100, 83.7218] +24-11-19 18:54:09 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 18:54:09 | D | + error = [1.1273] +24-11-19 18:54:09 | D | - Calibrating model.layers.10.self_attn.o_proj.weight +24-11-19 18:54:09 | D | + w: sint8 +24-11-19 18:54:09 | D | + x: None +24-11-19 18:54:09 | D | + y: None +24-11-19 18:54:09 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:54:09 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:54:09 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:54:09 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:54:09 | D | - range ratio = [ 1.0000] +24-11-19 18:54:09 | D | sum error = [ 0.5436] +24-11-19 18:54:09 | D | best error = [ 0.5436] +24-11-19 18:54:09 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:54:09 | D | sum error = [ 0.5385, 0.5361, 0.5382, 0.5383, 0.5443] +24-11-19 18:54:09 | D | best error = [ 0.4867, 0.4644, 0.4507, 0.4419, 0.4359] +24-11-19 18:54:09 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:54:09 | D | sum error = [ 0.5546, 0.5647, 0.5830, 0.6030, 0.6261] +24-11-19 18:54:09 | D | best error = [ 0.4318, 0.4284, 0.4264, 0.4250, 0.4240] +24-11-19 18:54:09 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:54:09 | D | sum error = [ 0.6535, 0.6809, 0.7134, 0.7492, 0.7945] +24-11-19 18:54:09 | D | best error = [ 0.4232, 0.4226, 0.4222, 0.4218, 0.4216] +24-11-19 18:54:09 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:54:09 | D | sum error = [ 0.8386, 0.8856, 0.9349, 0.9937, 1.0503] +24-11-19 18:54:09 | D | best error = [ 0.4215, 0.4213, 0.4212, 0.4211, 0.4210] +24-11-19 18:54:09 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:54:09 | D | sum error = [ 1.1143, 1.1827, 1.2535, 1.3300, 1.4098] +24-11-19 18:54:09 | D | best error = [ 0.4209, 0.4209, 0.4208, 0.4208, 0.4208] +24-11-19 18:54:09 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:54:09 | D | sum error = [ 1.4934, 1.5853, 1.6739, 1.7752, 1.8758] +24-11-19 18:54:09 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 18:54:09 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:54:09 | D | sum error = [ 1.9881, 2.0994, 2.2158, 2.3413, 2.4731] +24-11-19 18:54:09 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 18:54:09 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:54:09 | D | sum error = [ 2.6108, 2.7539, 2.9056, 3.0638, 3.2276] +24-11-19 18:54:09 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 18:54:09 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:54:09 | D | sum error = [ 3.4020, 3.5791, 3.7715, 3.9679, 4.1738] +24-11-19 18:54:09 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 18:54:09 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:54:09 | D | sum error = [ 4.3873, 4.6124, 4.8454, 5.0891, 5.3396] +24-11-19 18:54:09 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 18:54:09 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:54:09 | D | sum error = [ 5.6038, 5.8785, 6.1634, 6.4558, 6.7656] +24-11-19 18:54:09 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 18:54:09 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:54:09 | D | sum error = [ 7.0844, 7.4162, 7.7590, 8.1180, 8.4863] +24-11-19 18:54:09 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 18:54:09 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:54:09 | D | sum error = [ 8.8700, 9.2649, 9.6759, 10.1025, 10.5401] +24-11-19 18:54:09 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 18:54:09 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:54:09 | D | sum error = [ 10.9963, 11.4648, 11.9481, 12.4485, 12.9627] +24-11-19 18:54:09 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 18:54:09 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:54:09 | D | sum error = [ 13.4945, 14.0398, 14.6026, 15.1834, 15.7805] +24-11-19 18:54:09 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 18:54:09 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:54:09 | D | sum error = [ 16.3942, 17.0258, 17.6754, 18.3412, 19.0258] +24-11-19 18:54:09 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 18:54:09 | D | + error = [0.4208] +24-11-19 18:54:10 | D | - Calibrating model.layers.10.mlp.up_proj.weight +24-11-19 18:54:10 | D | + w: sint8 +24-11-19 18:54:10 | D | + x: None +24-11-19 18:54:10 | D | + y: None +24-11-19 18:54:10 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:54:10 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:54:10 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:54:10 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:54:10 | D | - range ratio = [ 1.0000] +24-11-19 18:54:10 | D | sum error = [ 4.9257] +24-11-19 18:54:10 | D | best error = [ 4.9257] +24-11-19 18:54:11 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:54:11 | D | sum error = [ 4.8766, 4.8760, 4.8901, 4.9433, 5.0448] +24-11-19 18:54:11 | D | best error = [ 4.5814, 4.4533, 4.3839, 4.3444, 4.3234] +24-11-19 18:54:11 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:54:11 | D | sum error = [ 5.1680, 5.3505, 5.5600, 5.8195, 6.1360] +24-11-19 18:54:11 | D | best error = [ 4.3138, 4.3092, 4.3078, 4.3073, 4.3072] +24-11-19 18:54:11 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:54:11 | D | sum error = [ 6.4730, 6.8698, 7.3242, 7.8104, 8.3545] +24-11-19 18:54:11 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 18:54:11 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:54:11 | D | sum error = [ 8.9463, 9.5742, 10.2651, 11.0111, 11.7875] +24-11-19 18:54:11 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 18:54:11 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:54:11 | D | sum error = [ 12.6273, 13.5351, 14.4927, 15.4918, 16.5715] +24-11-19 18:54:11 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 18:54:11 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:54:11 | D | sum error = [ 17.7116, 18.9210, 20.2035, 21.5576, 22.9871] +24-11-19 18:54:11 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 18:54:11 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:54:11 | D | sum error = [ 24.5017, 26.0886, 27.7731, 29.5385, 31.4141] +24-11-19 18:54:11 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 18:54:11 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:54:11 | D | sum error = [ 33.3780, 35.4478, 37.6244, 39.9139, 42.3249] +24-11-19 18:54:11 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 18:54:11 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:54:11 | D | sum error = [ 44.8556, 47.5184, 50.3072, 53.2326, 56.3012] +24-11-19 18:54:11 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 18:54:11 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:54:11 | D | sum error = [ 59.5176, 62.8781, 66.4106, 70.1054, 73.9589] +24-11-19 18:54:11 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 18:54:11 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:54:11 | D | sum error = [ 78.0032, 82.2119, 86.6240, 91.2111, 96.0238] +24-11-19 18:54:11 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 18:54:11 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:54:11 | D | sum error = [ 101.0316, 106.2511, 111.6930, 117.3445, 123.2296] +24-11-19 18:54:11 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 18:54:11 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:54:11 | D | sum error = [ 129.3549, 135.7186, 142.3155, 149.1912, 156.3224] +24-11-19 18:54:11 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 18:54:11 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:54:11 | D | sum error = [ 163.7153, 171.3853, 179.3333, 187.5796, 196.1065] +24-11-19 18:54:11 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 18:54:11 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:54:11 | D | sum error = [ 204.9244, 214.0356, 223.4639, 233.1963, 243.2492] +24-11-19 18:54:11 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 18:54:11 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:54:11 | D | sum error = [ 253.6034, 264.2857, 275.2826, 286.6055, 298.2632] +24-11-19 18:54:11 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 18:54:11 | D | + error = [4.3072] +24-11-19 18:54:11 | D | - Calibrating model.layers.10.mlp.gate_proj.weight +24-11-19 18:54:11 | D | + w: sint8 +24-11-19 18:54:11 | D | + x: None +24-11-19 18:54:11 | D | + y: None +24-11-19 18:54:11 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:54:11 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:54:11 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:54:11 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:54:11 | D | - range ratio = [ 1.0000] +24-11-19 18:54:11 | D | sum error = [ 6.1663] +24-11-19 18:54:11 | D | best error = [ 6.1663] +24-11-19 18:54:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:54:12 | D | sum error = [ 6.1189, 6.1047, 6.1384, 6.2018, 6.3050] +24-11-19 18:54:12 | D | best error = [ 5.7390, 5.5778, 5.4917, 5.4430, 5.4164] +24-11-19 18:54:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:54:12 | D | sum error = [ 6.4838, 6.7024, 6.9802, 7.3146, 7.7033] +24-11-19 18:54:12 | D | best error = [ 5.4035, 5.3983, 5.3963, 5.3958, 5.3957] +24-11-19 18:54:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:54:12 | D | sum error = [ 8.1572, 8.6705, 9.2523, 9.8716, 10.5725] +24-11-19 18:54:12 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 18:54:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:54:12 | D | sum error = [ 11.3336, 12.1449, 13.0658, 14.0114, 15.0401] +24-11-19 18:54:12 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 18:54:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:54:12 | D | sum error = [ 16.1731, 17.3327, 18.6217, 19.9744, 21.4163] +24-11-19 18:54:12 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 18:54:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:54:12 | D | sum error = [ 22.9594, 24.5746, 26.3320, 28.1759, 30.1367] +24-11-19 18:54:12 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 18:54:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:54:12 | D | sum error = [ 32.2085, 34.4485, 36.8157, 39.3135, 41.9888] +24-11-19 18:54:12 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 18:54:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:54:12 | D | sum error = [ 44.7979, 47.7951, 50.9898, 54.3595, 57.9665] +24-11-19 18:54:12 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 18:54:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:54:12 | D | sum error = [ 61.7551, 65.7836, 70.0652, 74.6027, 79.3901] +24-11-19 18:54:12 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 18:54:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:54:12 | D | sum error = [ 84.4635, 89.8591, 95.5745, 101.5874, 107.9738] +24-11-19 18:54:12 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 18:54:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:54:12 | D | sum error = [ 114.7145, 121.8331, 129.3426, 137.3149, 145.6753] +24-11-19 18:54:12 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 18:54:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:54:12 | D | sum error = [ 154.5142, 163.8238, 173.6209, 183.9282, 194.7675] +24-11-19 18:54:12 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 18:54:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:54:12 | D | sum error = [ 206.1163, 218.0469, 230.5673, 243.6619, 257.3773] +24-11-19 18:54:12 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 18:54:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:54:12 | D | sum error = [ 271.7440, 286.7198, 302.3933, 318.7527, 335.7862] +24-11-19 18:54:12 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 18:54:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:54:12 | D | sum error = [ 353.5474, 372.0112, 391.1902, 411.1101, 431.7624] +24-11-19 18:54:12 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 18:54:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:54:12 | D | sum error = [ 453.1857, 475.3205, 498.1978, 521.7886, 546.1163] +24-11-19 18:54:12 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 18:54:12 | D | + error = [5.3957] +24-11-19 18:54:12 | D | - Calibrating model.layers.10.mlp.down_proj.weight +24-11-19 18:54:12 | D | + w: sint8 +24-11-19 18:54:12 | D | + x: None +24-11-19 18:54:12 | D | + y: None +24-11-19 18:54:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:54:12 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:54:12 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:54:13 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:54:13 | D | - range ratio = [ 1.0000] +24-11-19 18:54:13 | D | sum error = [ 0.6022] +24-11-19 18:54:13 | D | best error = [ 0.6022] +24-11-19 18:54:14 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:54:14 | D | sum error = [ 0.5983, 0.5935, 0.5899, 0.5876, 0.5882] +24-11-19 18:54:14 | D | best error = [ 0.5786, 0.5662, 0.5583, 0.5522, 0.5474] +24-11-19 18:54:14 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:54:14 | D | sum error = [ 0.5915, 0.5948, 0.6016, 0.6101, 0.6227] +24-11-19 18:54:14 | D | best error = [ 0.5441, 0.5415, 0.5396, 0.5385, 0.5377] +24-11-19 18:54:14 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:54:14 | D | sum error = [ 0.6379, 0.6553, 0.6760, 0.7041, 0.7337] +24-11-19 18:54:14 | D | best error = [ 0.5372, 0.5368, 0.5366, 0.5364, 0.5362] +24-11-19 18:54:14 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:54:14 | D | sum error = [ 0.7680, 0.8067, 0.8510, 0.8989, 0.9513] +24-11-19 18:54:14 | D | best error = [ 0.5361, 0.5361, 0.5361, 0.5361, 0.5361] +24-11-19 18:54:14 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:54:14 | D | sum error = [ 1.0104, 1.0755, 1.1448, 1.2214, 1.3018] +24-11-19 18:54:14 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 18:54:14 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:54:14 | D | sum error = [ 1.3894, 1.4834, 1.5836, 1.6911, 1.8071] +24-11-19 18:54:14 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 18:54:14 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:54:14 | D | sum error = [ 1.9296, 2.0618, 2.2013, 2.3503, 2.5064] +24-11-19 18:54:14 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 18:54:14 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:54:14 | D | sum error = [ 2.6741, 2.8526, 3.0418, 3.2392, 3.4492] +24-11-19 18:54:14 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 18:54:14 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:54:14 | D | sum error = [ 3.6727, 3.9069, 4.1549, 4.4172, 4.6936] +24-11-19 18:54:14 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 18:54:14 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:54:14 | D | sum error = [ 4.9852, 5.2918, 5.6156, 5.9561, 6.3144] +24-11-19 18:54:14 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 18:54:14 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:54:14 | D | sum error = [ 6.6906, 7.0874, 7.5026, 7.9391, 8.3964] +24-11-19 18:54:14 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 18:54:14 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:54:14 | D | sum error = [ 8.8747, 9.3763, 9.9006, 10.4495, 11.0221] +24-11-19 18:54:14 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 18:54:14 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:54:14 | D | sum error = [ 11.6207, 12.2446, 12.8977, 13.5776, 14.2863] +24-11-19 18:54:14 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 18:54:14 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:54:14 | D | sum error = [ 15.0247, 15.7935, 16.5936, 17.4264, 18.2908] +24-11-19 18:54:14 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 18:54:14 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:54:14 | D | sum error = [ 19.1888, 20.1208, 21.0875, 22.0900, 23.1292] +24-11-19 18:54:14 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 18:54:14 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:54:14 | D | sum error = [ 24.2049, 25.3184, 26.4706, 27.6610, 28.8917] +24-11-19 18:54:14 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 18:54:14 | D | + error = [0.5360] +24-11-19 18:54:14 | D | - Quantizing model.layers.10.self_attn.q_proj.weight +24-11-19 18:54:15 | D | - Quantizing model.layers.10.self_attn.k_proj.weight +24-11-19 18:54:15 | D | - Quantizing model.layers.10.self_attn.v_proj.weight +24-11-19 18:54:18 | D | - Quantizing model.layers.10.self_attn.o_proj.weight +24-11-19 18:54:18 | D | - Quantizing model.layers.10.mlp.up_proj.weight +24-11-19 18:54:19 | D | - Quantizing model.layers.10.mlp.gate_proj.weight +24-11-19 18:54:20 | D | - Quantizing model.layers.10.mlp.down_proj.weight +24-11-19 18:54:29 | D | - Quantizing layer model.layers.11 +24-11-19 18:54:29 | D | - Calibrating model.layers.11.self_attn.q_proj.weight +24-11-19 18:54:29 | D | + w: sint8 +24-11-19 18:54:29 | D | + x: None +24-11-19 18:54:29 | D | + y: None +24-11-19 18:54:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:54:29 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:54:30 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:54:30 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:54:30 | D | - range ratio = [ 1.0000] +24-11-19 18:54:30 | D | sum error = [ 4.5199] +24-11-19 18:54:30 | D | best error = [ 4.5199] +24-11-19 18:54:42 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:54:42 | D | sum error = [ 4.3721, 4.3768, 4.4174, 4.4510, 4.5456] +24-11-19 18:54:42 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 18:54:42 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:54:42 | D | sum error = [ 4.6729, 4.9438, 5.0193, 5.3301, 5.6263] +24-11-19 18:54:42 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 18:54:42 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:54:42 | D | sum error = [ 6.0035, 6.3489, 6.8737, 7.2317, 7.6584] +24-11-19 18:54:42 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 18:54:42 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:54:42 | D | sum error = [ 8.5496, 8.9742, 9.6222, 10.4436, 11.4344] +24-11-19 18:54:42 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 18:54:42 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:54:42 | D | sum error = [ 12.3133, 13.2258, 14.5721, 15.9762, 17.5238] +24-11-19 18:54:42 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 18:54:42 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:54:42 | D | sum error = [ 19.1325, 20.5395, 22.4454, 24.1765, 26.5560] +24-11-19 18:54:42 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 18:54:42 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:54:42 | D | sum error = [ 28.7120, 31.3016, 33.4259, 36.1172, 38.7716] +24-11-19 18:54:42 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 18:54:42 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:54:42 | D | sum error = [ 41.6522, 44.5342, 47.8689, 51.2850, 54.7550] +24-11-19 18:54:42 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 18:54:42 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:54:42 | D | sum error = [ 58.6213, 62.6558, 66.7674, 70.9962, 75.7002] +24-11-19 18:54:42 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 18:54:42 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:54:42 | D | sum error = [ 80.7153, 85.9032, 91.5539, 97.1990, 103.2243] +24-11-19 18:54:42 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 18:54:42 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:54:42 | D | sum error = [ 109.5686, 115.9063, 123.1006, 130.4579, 138.2360] +24-11-19 18:54:42 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 18:54:42 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:54:42 | D | sum error = [ 146.2699, 154.8672, 163.7865, 173.0149, 182.8001] +24-11-19 18:54:42 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 18:54:42 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:54:42 | D | sum error = [ 192.8215, 203.4819, 214.5904, 226.2604, 238.2083] +24-11-19 18:54:42 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 18:54:42 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:54:42 | D | sum error = [ 250.6082, 263.6146, 277.2938, 291.2336, 305.9762] +24-11-19 18:54:42 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 18:54:42 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:54:42 | D | sum error = [ 321.3295, 337.0221, 353.5857, 370.5917, 388.0751] +24-11-19 18:54:42 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 18:54:42 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:54:42 | D | sum error = [ 406.0692, 424.8017, 443.8989, 463.4661, 483.4130] +24-11-19 18:54:42 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 18:54:42 | D | + error = [4.3721] +24-11-19 18:54:42 | D | - Calibrating model.layers.11.self_attn.k_proj.weight +24-11-19 18:54:42 | D | + w: sint8 +24-11-19 18:54:42 | D | + x: None +24-11-19 18:54:42 | D | + y: None +24-11-19 18:54:42 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:54:42 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:54:42 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:54:42 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:54:42 | D | - range ratio = [ 1.0000] +24-11-19 18:54:42 | D | sum error = [ 3.7533] +24-11-19 18:54:42 | D | best error = [ 3.7533] +24-11-19 18:54:54 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:54:54 | D | sum error = [ 3.6009, 3.8263, 3.6105, 3.7792, 3.9549] +24-11-19 18:54:54 | D | best error = [ 3.6009, 3.6009, 3.6009, 3.6009, 3.6009] +24-11-19 18:54:54 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:54:54 | D | sum error = [ 4.2522, 3.7429, 4.6950, 5.0002, 4.6554] +24-11-19 18:54:54 | D | best error = [ 3.6009, 3.6009, 3.6009, 3.6009, 3.6009] +24-11-19 18:54:54 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:54:54 | D | sum error = [ 4.5752, 4.6955, 5.4867, 5.8339, 6.6710] +24-11-19 18:54:54 | D | best error = [ 3.6009, 3.6009, 3.6009, 3.6009, 3.6009] +24-11-19 18:54:54 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:54:54 | D | sum error = [ 6.2763, 7.1151, 7.4053, 8.4776, 9.1405] +24-11-19 18:54:54 | D | best error = [ 3.6009, 3.6009, 3.6009, 3.6009, 3.6009] +24-11-19 18:54:54 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:54:54 | D | sum error = [ 9.7453, 10.7543, 11.4197, 11.9932, 13.6404] +24-11-19 18:54:54 | D | best error = [ 3.6009, 3.6009, 3.6009, 3.6009, 3.6009] +24-11-19 18:54:54 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:54:54 | D | sum error = [ 14.8212, 15.2977, 16.6620, 17.5329, 18.9441] +24-11-19 18:54:54 | D | best error = [ 3.6009, 3.6009, 3.6009, 3.6009, 3.6009] +24-11-19 18:54:54 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:54:54 | D | sum error = [ 20.2362, 21.5258, 23.0643, 23.8859, 26.1665] +24-11-19 18:54:54 | D | best error = [ 3.6009, 3.6009, 3.6009, 3.6009, 3.6009] +24-11-19 18:54:54 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:54:54 | D | sum error = [ 27.7685, 29.8864, 32.7217, 35.3273, 38.3496] +24-11-19 18:54:54 | D | best error = [ 3.6009, 3.6009, 3.6009, 3.6009, 3.6009] +24-11-19 18:54:54 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:54:54 | D | sum error = [ 40.6984, 44.1216, 47.2657, 51.1159, 55.1069] +24-11-19 18:54:54 | D | best error = [ 3.6009, 3.6009, 3.6009, 3.6009, 3.6009] +24-11-19 18:54:54 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:54:54 | D | sum error = [ 59.2493, 63.5208, 67.7154, 73.6333, 78.0105] +24-11-19 18:54:54 | D | best error = [ 3.6009, 3.6009, 3.6009, 3.6009, 3.6009] +24-11-19 18:54:54 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:54:54 | D | sum error = [ 82.9360, 89.0891, 95.5928, 101.2025, 109.2038] +24-11-19 18:54:54 | D | best error = [ 3.6009, 3.6009, 3.6009, 3.6009, 3.6009] +24-11-19 18:54:54 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:54:54 | D | sum error = [ 116.4295, 125.4303, 134.0907, 143.3600, 153.3210] +24-11-19 18:54:54 | D | best error = [ 3.6009, 3.6009, 3.6009, 3.6009, 3.6009] +24-11-19 18:54:54 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:54:54 | D | sum error = [ 163.9089, 174.3004, 186.1120, 198.7862, 210.6645] +24-11-19 18:54:54 | D | best error = [ 3.6009, 3.6009, 3.6009, 3.6009, 3.6009] +24-11-19 18:54:54 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:54:54 | D | sum error = [ 224.5560, 239.3011, 252.9382, 267.4479, 283.1126] +24-11-19 18:54:54 | D | best error = [ 3.6009, 3.6009, 3.6009, 3.6009, 3.6009] +24-11-19 18:54:54 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:54:54 | D | sum error = [ 299.7319, 316.2547, 334.3750, 352.4472, 372.0403] +24-11-19 18:54:54 | D | best error = [ 3.6009, 3.6009, 3.6009, 3.6009, 3.6009] +24-11-19 18:54:54 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:54:54 | D | sum error = [ 391.0196, 411.9611, 432.7126, 453.6924, 475.0458] +24-11-19 18:54:54 | D | best error = [ 3.6009, 3.6009, 3.6009, 3.6009, 3.6009] +24-11-19 18:54:54 | D | + error = [3.6009] +24-11-19 18:54:54 | D | - Calibrating model.layers.11.self_attn.v_proj.weight +24-11-19 18:54:54 | D | + w: sint8 +24-11-19 18:54:54 | D | + x: None +24-11-19 18:54:54 | D | + y: None +24-11-19 18:54:54 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:54:54 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:54:54 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:54:54 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:54:54 | D | - range ratio = [ 1.0000] +24-11-19 18:54:54 | D | sum error = [ 1.3219] +24-11-19 18:54:54 | D | best error = [ 1.3219] +24-11-19 18:54:54 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:54:54 | D | sum error = [ 1.3345, 1.3231, 1.3282, 1.3424, 1.3748] +24-11-19 18:54:54 | D | best error = [ 1.2337, 1.1990, 1.1796, 1.1687, 1.1630] +24-11-19 18:54:54 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:54:54 | D | sum error = [ 1.4015, 1.4425, 1.5051, 1.5766, 1.6627] +24-11-19 18:54:54 | D | best error = [ 1.1606, 1.1596, 1.1594, 1.1593, 1.1593] +24-11-19 18:54:54 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:54:54 | D | sum error = [ 1.7673, 1.8566, 1.9720, 2.1077, 2.2687] +24-11-19 18:54:54 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 18:54:54 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:54:54 | D | sum error = [ 2.4104, 2.5891, 2.7743, 2.9767, 3.1839] +24-11-19 18:54:54 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 18:54:54 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:54:54 | D | sum error = [ 3.4143, 3.6699, 3.9296, 4.2133, 4.5068] +24-11-19 18:54:54 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 18:54:54 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:54:54 | D | sum error = [ 4.8199, 5.1587, 5.5152, 5.8746, 6.2908] +24-11-19 18:54:54 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 18:54:54 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:54:54 | D | sum error = [ 6.7136, 7.1528, 7.6380, 8.1287, 8.6428] +24-11-19 18:54:54 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 18:54:54 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:54:54 | D | sum error = [ 9.1915, 9.7821, 10.3852, 11.0339, 11.7097] +24-11-19 18:54:54 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 18:54:54 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:54:54 | D | sum error = [ 12.4336, 13.1913, 13.9876, 14.8250, 15.7179] +24-11-19 18:54:54 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 18:54:54 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:54:54 | D | sum error = [ 16.6361, 17.6123, 18.6211, 19.6839, 20.8004] +24-11-19 18:54:54 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 18:54:54 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:54:54 | D | sum error = [ 21.9703, 23.1892, 24.4650, 25.8168, 27.2142] +24-11-19 18:54:54 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 18:54:54 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:54:54 | D | sum error = [ 28.6794, 30.2064, 31.8129, 33.4811, 35.2097] +24-11-19 18:54:54 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 18:54:54 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:54:54 | D | sum error = [ 37.0241, 38.9127, 40.8814, 42.9277, 45.0581] +24-11-19 18:54:54 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 18:54:54 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:54:54 | D | sum error = [ 47.2750, 49.5776, 51.9752, 54.4575, 57.0347] +24-11-19 18:54:54 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 18:54:54 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:54:54 | D | sum error = [ 59.7057, 62.4858, 65.3575, 68.3337, 71.4036] +24-11-19 18:54:54 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 18:54:54 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:54:54 | D | sum error = [ 74.5721, 77.8485, 81.2238, 84.7115, 88.2925] +24-11-19 18:54:54 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 18:54:54 | D | + error = [1.1593] +24-11-19 18:54:55 | D | - Calibrating model.layers.11.self_attn.o_proj.weight +24-11-19 18:54:55 | D | + w: sint8 +24-11-19 18:54:55 | D | + x: None +24-11-19 18:54:55 | D | + y: None +24-11-19 18:54:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:54:55 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:54:55 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:54:55 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:54:55 | D | - range ratio = [ 1.0000] +24-11-19 18:54:55 | D | sum error = [ 0.5878] +24-11-19 18:54:55 | D | best error = [ 0.5878] +24-11-19 18:54:55 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:54:55 | D | sum error = [ 0.5827, 0.5814, 0.5757, 0.5830, 0.5843] +24-11-19 18:54:55 | D | best error = [ 0.5158, 0.4886, 0.4726, 0.4630, 0.4556] +24-11-19 18:54:55 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:54:55 | D | sum error = [ 0.5924, 0.6013, 0.6144, 0.6290, 0.6509] +24-11-19 18:54:55 | D | best error = [ 0.4504, 0.4463, 0.4428, 0.4403, 0.4385] +24-11-19 18:54:55 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:54:55 | D | sum error = [ 0.6713, 0.7039, 0.7310, 0.7717, 0.8036] +24-11-19 18:54:55 | D | best error = [ 0.4372, 0.4359, 0.4351, 0.4344, 0.4340] +24-11-19 18:54:55 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:54:55 | D | sum error = [ 0.8513, 0.8954, 0.9500, 1.0031, 1.0674] +24-11-19 18:54:55 | D | best error = [ 0.4336, 0.4333, 0.4329, 0.4326, 0.4324] +24-11-19 18:54:55 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:54:55 | D | sum error = [ 1.1290, 1.1941, 1.2662, 1.3500, 1.4292] +24-11-19 18:54:55 | D | best error = [ 0.4322, 0.4321, 0.4320, 0.4319, 0.4319] +24-11-19 18:54:55 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:54:55 | D | sum error = [ 1.5191, 1.6134, 1.7064, 1.8167, 1.9240] +24-11-19 18:54:55 | D | best error = [ 0.4318, 0.4318, 0.4317, 0.4317, 0.4317] +24-11-19 18:54:55 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:54:55 | D | sum error = [ 2.0390, 2.1607, 2.2902, 2.4260, 2.5694] +24-11-19 18:54:55 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 18:54:55 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:54:55 | D | sum error = [ 2.7165, 2.8716, 3.0333, 3.2051, 3.3805] +24-11-19 18:54:55 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 18:54:55 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:54:55 | D | sum error = [ 3.5674, 3.7593, 3.9608, 4.1712, 4.3928] +24-11-19 18:54:55 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 18:54:55 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:54:55 | D | sum error = [ 4.6183, 4.8549, 5.1028, 5.3601, 5.6298] +24-11-19 18:54:55 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 18:54:55 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:54:55 | D | sum error = [ 5.9099, 6.2019, 6.5039, 6.8136, 7.1409] +24-11-19 18:54:55 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 18:54:55 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:54:55 | D | sum error = [ 7.4725, 7.8195, 8.1780, 8.5487, 8.9276] +24-11-19 18:54:55 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 18:54:55 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:54:55 | D | sum error = [ 9.3239, 9.7288, 10.1461, 10.5735, 11.0149] +24-11-19 18:54:55 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 18:54:55 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:54:55 | D | sum error = [ 11.4714, 11.9356, 12.4137, 12.9031, 13.4039] +24-11-19 18:54:55 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 18:54:55 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:54:55 | D | sum error = [ 13.9175, 14.4441, 14.9840, 15.5361, 16.1025] +24-11-19 18:54:55 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 18:54:55 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:54:55 | D | sum error = [ 16.6822, 17.2713, 17.8727, 18.4905, 19.1222] +24-11-19 18:54:55 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 18:54:55 | D | + error = [0.4316] +24-11-19 18:54:55 | D | - Calibrating model.layers.11.mlp.up_proj.weight +24-11-19 18:54:55 | D | + w: sint8 +24-11-19 18:54:55 | D | + x: None +24-11-19 18:54:55 | D | + y: None +24-11-19 18:54:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:54:55 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:54:55 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:54:55 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:54:55 | D | - range ratio = [ 1.0000] +24-11-19 18:54:55 | D | sum error = [ 5.0178] +24-11-19 18:54:55 | D | best error = [ 5.0178] +24-11-19 18:54:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:54:57 | D | sum error = [ 4.9834, 4.9685, 4.9860, 5.0472, 5.1333] +24-11-19 18:54:57 | D | best error = [ 4.6583, 4.5243, 4.4524, 4.4121, 4.3904] +24-11-19 18:54:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:54:57 | D | sum error = [ 5.2573, 5.4363, 5.6594, 5.9256, 6.2306] +24-11-19 18:54:57 | D | best error = [ 4.3801, 4.3754, 4.3741, 4.3735, 4.3735] +24-11-19 18:54:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:54:57 | D | sum error = [ 6.5901, 7.0043, 7.4497, 7.9337, 8.4848] +24-11-19 18:54:57 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 18:54:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:54:57 | D | sum error = [ 9.0888, 9.7390, 10.4356, 11.1645, 11.9761] +24-11-19 18:54:57 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 18:54:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:54:57 | D | sum error = [ 12.8368, 13.7471, 14.7185, 15.7465, 16.8466] +24-11-19 18:54:57 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 18:54:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:54:57 | D | sum error = [ 18.0052, 19.2370, 20.5262, 21.9090, 23.3588] +24-11-19 18:54:57 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 18:54:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:54:57 | D | sum error = [ 24.8955, 26.5062, 28.2088, 30.0088, 31.8980] +24-11-19 18:54:57 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 18:54:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:54:57 | D | sum error = [ 33.8798, 35.9791, 38.1846, 40.5027, 42.9370] +24-11-19 18:54:57 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 18:54:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:54:57 | D | sum error = [ 45.4985, 48.1838, 51.0101, 53.9740, 57.0842] +24-11-19 18:54:57 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 18:54:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:54:57 | D | sum error = [ 60.3490, 63.7614, 67.3445, 71.0805, 74.9929] +24-11-19 18:54:57 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 18:54:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:54:57 | D | sum error = [ 79.0939, 83.3859, 87.8560, 92.5314, 97.4124] +24-11-19 18:54:57 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 18:54:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:54:57 | D | sum error = [ 102.4934, 107.7967, 113.3142, 119.0642, 125.0503] +24-11-19 18:54:57 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 18:54:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:54:57 | D | sum error = [ 131.2736, 137.7481, 144.4711, 151.4670, 158.7291] +24-11-19 18:54:57 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 18:54:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:54:57 | D | sum error = [ 166.2487, 174.0592, 182.1667, 190.5738, 199.2771] +24-11-19 18:54:57 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 18:54:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:54:57 | D | sum error = [ 208.2938, 217.5974, 227.2258, 237.1690, 247.4230] +24-11-19 18:54:57 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 18:54:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:54:57 | D | sum error = [ 258.0118, 268.9313, 280.1780, 291.7532, 303.6726] +24-11-19 18:54:57 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 18:54:57 | D | + error = [4.3735] +24-11-19 18:54:57 | D | - Calibrating model.layers.11.mlp.gate_proj.weight +24-11-19 18:54:57 | D | + w: sint8 +24-11-19 18:54:57 | D | + x: None +24-11-19 18:54:57 | D | + y: None +24-11-19 18:54:57 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:54:57 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:54:57 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:54:57 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:54:57 | D | - range ratio = [ 1.0000] +24-11-19 18:54:57 | D | sum error = [ 6.1489] +24-11-19 18:54:57 | D | best error = [ 6.1489] +24-11-19 18:54:58 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:54:58 | D | sum error = [ 6.1071, 6.0889, 6.1146, 6.1729, 6.3095] +24-11-19 18:54:58 | D | best error = [ 5.7142, 5.5461, 5.4577, 5.4068, 5.3802] +24-11-19 18:54:58 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:54:58 | D | sum error = [ 6.4717, 6.6796, 6.9562, 7.2927, 7.6668] +24-11-19 18:54:58 | D | best error = [ 5.3679, 5.3624, 5.3608, 5.3603, 5.3602] +24-11-19 18:54:58 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:54:58 | D | sum error = [ 8.1324, 8.6424, 9.2207, 9.8342, 10.5397] +24-11-19 18:54:58 | D | best error = [ 5.3601, 5.3601, 5.3601, 5.3601, 5.3601] +24-11-19 18:54:58 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:54:58 | D | sum error = [ 11.3231, 12.1333, 13.0343, 14.0031, 15.0362] +24-11-19 18:54:58 | D | best error = [ 5.3601, 5.3601, 5.3601, 5.3601, 5.3601] +24-11-19 18:54:58 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:54:58 | D | sum error = [ 16.1513, 17.3471, 18.6203, 19.9623, 21.4347] +24-11-19 18:54:58 | D | best error = [ 5.3601, 5.3601, 5.3601, 5.3601, 5.3601] +24-11-19 18:54:58 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:54:58 | D | sum error = [ 22.9689, 24.6141, 26.3813, 28.2286, 30.2035] +24-11-19 18:54:58 | D | best error = [ 5.3601, 5.3601, 5.3601, 5.3601, 5.3601] +24-11-19 18:54:58 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:54:58 | D | sum error = [ 32.3124, 34.5556, 36.9238, 39.4514, 42.1417] +24-11-19 18:54:58 | D | best error = [ 5.3601, 5.3601, 5.3601, 5.3601, 5.3601] +24-11-19 18:54:58 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:54:58 | D | sum error = [ 44.9869, 48.0104, 51.2226, 54.6454, 58.2444] +24-11-19 18:54:58 | D | best error = [ 5.3601, 5.3601, 5.3601, 5.3601, 5.3601] +24-11-19 18:54:58 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:54:58 | D | sum error = [ 62.0633, 66.1358, 70.4297, 75.0014, 79.8364] +24-11-19 18:54:58 | D | best error = [ 5.3601, 5.3601, 5.3601, 5.3601, 5.3601] +24-11-19 18:54:58 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:54:58 | D | sum error = [ 84.9549, 90.3966, 96.1314, 102.2123, 108.6538] +24-11-19 18:54:58 | D | best error = [ 5.3601, 5.3601, 5.3601, 5.3601, 5.3601] +24-11-19 18:54:58 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:54:58 | D | sum error = [ 115.4956, 122.6845, 130.3048, 138.3661, 146.8427] +24-11-19 18:54:58 | D | best error = [ 5.3601, 5.3601, 5.3601, 5.3601, 5.3601] +24-11-19 18:54:58 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:54:58 | D | sum error = [ 155.7902, 165.2409, 175.1991, 185.6495, 196.6605] +24-11-19 18:54:58 | D | best error = [ 5.3601, 5.3601, 5.3601, 5.3601, 5.3601] +24-11-19 18:54:58 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:54:58 | D | sum error = [ 208.2399, 220.3811, 233.1354, 246.4879, 260.4767] +24-11-19 18:54:58 | D | best error = [ 5.3601, 5.3601, 5.3601, 5.3601, 5.3601] +24-11-19 18:54:58 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:54:58 | D | sum error = [ 275.1108, 290.4099, 306.3804, 323.0688, 340.4758] +24-11-19 18:54:58 | D | best error = [ 5.3601, 5.3601, 5.3601, 5.3601, 5.3601] +24-11-19 18:54:58 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:54:58 | D | sum error = [ 358.5700, 377.4145, 396.9943, 417.3196, 438.3877] +24-11-19 18:54:58 | D | best error = [ 5.3601, 5.3601, 5.3601, 5.3601, 5.3601] +24-11-19 18:54:58 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:54:58 | D | sum error = [ 460.2231, 482.8102, 506.1780, 530.2585, 555.1144] +24-11-19 18:54:58 | D | best error = [ 5.3601, 5.3601, 5.3601, 5.3601, 5.3601] +24-11-19 18:54:58 | D | + error = [5.3601] +24-11-19 18:54:58 | D | - Calibrating model.layers.11.mlp.down_proj.weight +24-11-19 18:54:58 | D | + w: sint8 +24-11-19 18:54:58 | D | + x: None +24-11-19 18:54:58 | D | + y: None +24-11-19 18:54:58 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:54:58 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:54:58 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:54:58 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:54:58 | D | - range ratio = [ 1.0000] +24-11-19 18:54:58 | D | sum error = [ 0.6148] +24-11-19 18:54:58 | D | best error = [ 0.6148] +24-11-19 18:55:00 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:55:00 | D | sum error = [ 0.6082, 0.6049, 0.6005, 0.5996, 0.5999] +24-11-19 18:55:00 | D | best error = [ 0.5873, 0.5755, 0.5671, 0.5611, 0.5565] +24-11-19 18:55:00 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:55:00 | D | sum error = [ 0.6031, 0.6090, 0.6170, 0.6286, 0.6416] +24-11-19 18:55:00 | D | best error = [ 0.5535, 0.5514, 0.5496, 0.5486, 0.5479] +24-11-19 18:55:00 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:55:00 | D | sum error = [ 0.6594, 0.6810, 0.7079, 0.7371, 0.7700] +24-11-19 18:55:00 | D | best error = [ 0.5473, 0.5470, 0.5467, 0.5465, 0.5465] +24-11-19 18:55:00 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:55:00 | D | sum error = [ 0.8069, 0.8506, 0.8969, 0.9485, 1.0060] +24-11-19 18:55:00 | D | best error = [ 0.5464, 0.5464, 0.5464, 0.5463, 0.5463] +24-11-19 18:55:00 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:55:00 | D | sum error = [ 1.0688, 1.1349, 1.2098, 1.2879, 1.3720] +24-11-19 18:55:00 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 18:55:00 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:55:00 | D | sum error = [ 1.4635, 1.5609, 1.6646, 1.7754, 1.8951] +24-11-19 18:55:00 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 18:55:00 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:55:00 | D | sum error = [ 2.0213, 2.1564, 2.3001, 2.4528, 2.6154] +24-11-19 18:55:00 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 18:55:00 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:55:00 | D | sum error = [ 2.7870, 2.9690, 3.1609, 3.3640, 3.5800] +24-11-19 18:55:00 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 18:55:00 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:55:00 | D | sum error = [ 3.8077, 4.0473, 4.3023, 4.5701, 4.8527] +24-11-19 18:55:00 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 18:55:00 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:55:00 | D | sum error = [ 5.1499, 5.4633, 5.7928, 6.1401, 6.5051] +24-11-19 18:55:00 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 18:55:00 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:55:00 | D | sum error = [ 6.8895, 7.2933, 7.7163, 8.1622, 8.6282] +24-11-19 18:55:00 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 18:55:00 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:55:00 | D | sum error = [ 9.1167, 9.6285, 10.1646, 10.7235, 11.3090] +24-11-19 18:55:00 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 18:55:00 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:55:00 | D | sum error = [ 11.9201, 12.5587, 13.2246, 13.9198, 14.6459] +24-11-19 18:55:00 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 18:55:00 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:55:00 | D | sum error = [ 15.4031, 16.1921, 17.0119, 17.8668, 18.7541] +24-11-19 18:55:00 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 18:55:00 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:55:00 | D | sum error = [ 19.6774, 20.6346, 21.6295, 22.6617, 23.7317] +24-11-19 18:55:00 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 18:55:00 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:55:00 | D | sum error = [ 24.8399, 25.9877, 27.1745, 28.4020, 29.6694] +24-11-19 18:55:00 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 18:55:00 | D | + error = [0.5463] +24-11-19 18:55:00 | D | - Quantizing model.layers.11.self_attn.q_proj.weight +24-11-19 18:55:00 | D | - Quantizing model.layers.11.self_attn.k_proj.weight +24-11-19 18:55:01 | D | - Quantizing model.layers.11.self_attn.v_proj.weight +24-11-19 18:55:02 | D | - Quantizing model.layers.11.self_attn.o_proj.weight +24-11-19 18:55:03 | D | - Quantizing model.layers.11.mlp.up_proj.weight +24-11-19 18:55:04 | D | - Quantizing model.layers.11.mlp.gate_proj.weight +24-11-19 18:55:05 | D | - Quantizing model.layers.11.mlp.down_proj.weight +24-11-19 18:55:14 | D | - Quantizing layer model.layers.12 +24-11-19 18:55:14 | D | - Calibrating model.layers.12.self_attn.q_proj.weight +24-11-19 18:55:14 | D | + w: sint8 +24-11-19 18:55:14 | D | + x: None +24-11-19 18:55:14 | D | + y: None +24-11-19 18:55:14 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:55:14 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:55:14 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:55:14 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:55:14 | D | - range ratio = [ 1.0000] +24-11-19 18:55:14 | D | sum error = [ 3.9519] +24-11-19 18:55:14 | D | best error = [ 3.9519] +24-11-19 18:55:26 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:55:26 | D | sum error = [ 3.8738, 3.8948, 3.8338, 3.9715, 4.0721] +24-11-19 18:55:26 | D | best error = [ 3.8738, 3.8738, 3.8338, 3.8338, 3.8338] +24-11-19 18:55:26 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:55:26 | D | sum error = [ 4.2229, 4.3497, 4.5555, 4.6573, 5.0972] +24-11-19 18:55:26 | D | best error = [ 3.8338, 3.8338, 3.8338, 3.8338, 3.8338] +24-11-19 18:55:26 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:55:26 | D | sum error = [ 5.2559, 5.6130, 6.0129, 6.4927, 6.9609] +24-11-19 18:55:26 | D | best error = [ 3.8338, 3.8338, 3.8338, 3.8338, 3.8338] +24-11-19 18:55:26 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:55:26 | D | sum error = [ 7.5260, 8.1701, 8.7727, 9.6013, 10.3662] +24-11-19 18:55:26 | D | best error = [ 3.8338, 3.8338, 3.8338, 3.8338, 3.8338] +24-11-19 18:55:26 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:55:26 | D | sum error = [ 11.2771, 12.3666, 13.5329, 14.8035, 16.2340] +24-11-19 18:55:26 | D | best error = [ 3.8338, 3.8338, 3.8338, 3.8338, 3.8338] +24-11-19 18:55:26 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:55:26 | D | sum error = [ 17.4959, 19.1835, 20.8233, 22.7598, 24.3956] +24-11-19 18:55:26 | D | best error = [ 3.8338, 3.8338, 3.8338, 3.8338, 3.8338] +24-11-19 18:55:26 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:55:26 | D | sum error = [ 26.7177, 28.6174, 30.9008, 33.3312, 35.9528] +24-11-19 18:55:26 | D | best error = [ 3.8338, 3.8338, 3.8338, 3.8338, 3.8338] +24-11-19 18:55:26 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:55:26 | D | sum error = [ 38.9855, 41.8148, 44.8614, 48.2179, 51.9529] +24-11-19 18:55:26 | D | best error = [ 3.8338, 3.8338, 3.8338, 3.8338, 3.8338] +24-11-19 18:55:26 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:55:26 | D | sum error = [ 55.6251, 59.6255, 63.7629, 68.4501, 73.0757] +24-11-19 18:55:26 | D | best error = [ 3.8338, 3.8338, 3.8338, 3.8338, 3.8338] +24-11-19 18:55:26 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:55:26 | D | sum error = [ 78.1027, 83.4414, 89.1584, 95.1043, 101.3102] +24-11-19 18:55:26 | D | best error = [ 3.8338, 3.8338, 3.8338, 3.8338, 3.8338] +24-11-19 18:55:26 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:55:26 | D | sum error = [ 107.8306, 114.6745, 122.0204, 129.4562, 137.4119] +24-11-19 18:55:26 | D | best error = [ 3.8338, 3.8338, 3.8338, 3.8338, 3.8338] +24-11-19 18:55:26 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:55:26 | D | sum error = [ 145.6891, 154.4135, 163.4462, 172.8937, 182.9265] +24-11-19 18:55:26 | D | best error = [ 3.8338, 3.8338, 3.8338, 3.8338, 3.8338] +24-11-19 18:55:26 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:55:26 | D | sum error = [ 193.0849, 204.0024, 215.3806, 227.2658, 239.8145] +24-11-19 18:55:26 | D | best error = [ 3.8338, 3.8338, 3.8338, 3.8338, 3.8338] +24-11-19 18:55:26 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:55:26 | D | sum error = [ 253.1082, 267.0357, 281.8644, 297.4369, 313.8486] +24-11-19 18:55:26 | D | best error = [ 3.8338, 3.8338, 3.8338, 3.8338, 3.8338] +24-11-19 18:55:26 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:55:26 | D | sum error = [ 331.1504, 349.3070, 368.2123, 388.1301, 408.7182] +24-11-19 18:55:26 | D | best error = [ 3.8338, 3.8338, 3.8338, 3.8338, 3.8338] +24-11-19 18:55:26 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:55:26 | D | sum error = [ 430.2635, 452.4685, 475.5212, 499.1286, 523.2331] +24-11-19 18:55:26 | D | best error = [ 3.8338, 3.8338, 3.8338, 3.8338, 3.8338] +24-11-19 18:55:26 | D | + error = [3.8338] +24-11-19 18:55:26 | D | - Calibrating model.layers.12.self_attn.k_proj.weight +24-11-19 18:55:26 | D | + w: sint8 +24-11-19 18:55:26 | D | + x: None +24-11-19 18:55:26 | D | + y: None +24-11-19 18:55:26 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:55:26 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:55:26 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:55:27 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:55:27 | D | - range ratio = [ 1.0000] +24-11-19 18:55:27 | D | sum error = [ 3.7909] +24-11-19 18:55:27 | D | best error = [ 3.7909] +24-11-19 18:55:38 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:55:38 | D | sum error = [ 3.5853, 3.6875, 4.0494, 3.9816, 3.8444] +24-11-19 18:55:38 | D | best error = [ 3.5853, 3.5853, 3.5853, 3.5853, 3.5853] +24-11-19 18:55:38 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:55:38 | D | sum error = [ 4.0863, 3.9690, 4.0391, 4.5299, 4.9410] +24-11-19 18:55:38 | D | best error = [ 3.5853, 3.5853, 3.5853, 3.5853, 3.5853] +24-11-19 18:55:38 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:55:38 | D | sum error = [ 4.9514, 5.4117, 5.5246, 5.7017, 6.4012] +24-11-19 18:55:38 | D | best error = [ 3.5853, 3.5853, 3.5853, 3.5853, 3.5853] +24-11-19 18:55:38 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:55:38 | D | sum error = [ 7.0613, 6.9320, 8.2366, 8.5444, 9.1797] +24-11-19 18:55:38 | D | best error = [ 3.5853, 3.5853, 3.5853, 3.5853, 3.5853] +24-11-19 18:55:38 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:55:38 | D | sum error = [ 9.7759, 10.9689, 11.9733, 12.6019, 13.7523] +24-11-19 18:55:38 | D | best error = [ 3.5853, 3.5853, 3.5853, 3.5853, 3.5853] +24-11-19 18:55:38 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:55:38 | D | sum error = [ 14.2564, 16.4194, 17.5845, 18.7961, 20.6784] +24-11-19 18:55:38 | D | best error = [ 3.5853, 3.5853, 3.5853, 3.5853, 3.5853] +24-11-19 18:55:38 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:55:38 | D | sum error = [ 22.2589, 23.4584, 25.8841, 27.6800, 30.1102] +24-11-19 18:55:38 | D | best error = [ 3.5853, 3.5853, 3.5853, 3.5853, 3.5853] +24-11-19 18:55:38 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:55:38 | D | sum error = [ 32.3757, 34.8867, 38.5455, 40.8467, 44.0453] +24-11-19 18:55:38 | D | best error = [ 3.5853, 3.5853, 3.5853, 3.5853, 3.5853] +24-11-19 18:55:38 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:55:38 | D | sum error = [ 47.2554, 51.4105, 54.5302, 58.2802, 62.5259] +24-11-19 18:55:38 | D | best error = [ 3.5853, 3.5853, 3.5853, 3.5853, 3.5853] +24-11-19 18:55:38 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:55:38 | D | sum error = [ 67.2402, 71.6429, 76.5303, 82.2174, 87.2881] +24-11-19 18:55:38 | D | best error = [ 3.5853, 3.5853, 3.5853, 3.5853, 3.5853] +24-11-19 18:55:38 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:55:38 | D | sum error = [ 93.1046, 99.4558, 105.8798, 113.4557, 120.8864] +24-11-19 18:55:38 | D | best error = [ 3.5853, 3.5853, 3.5853, 3.5853, 3.5853] +24-11-19 18:55:38 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:55:38 | D | sum error = [ 128.7910, 137.8116, 146.5152, 157.3191, 167.0552] +24-11-19 18:55:38 | D | best error = [ 3.5853, 3.5853, 3.5853, 3.5853, 3.5853] +24-11-19 18:55:38 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:55:38 | D | sum error = [ 177.3245, 188.9351, 200.5599, 212.7435, 226.6056] +24-11-19 18:55:38 | D | best error = [ 3.5853, 3.5853, 3.5853, 3.5853, 3.5853] +24-11-19 18:55:38 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:55:38 | D | sum error = [ 241.9393, 257.1265, 273.1420, 290.6175, 307.2682] +24-11-19 18:55:38 | D | best error = [ 3.5853, 3.5853, 3.5853, 3.5853, 3.5853] +24-11-19 18:55:38 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:55:38 | D | sum error = [ 325.7628, 345.8276, 363.7132, 386.1116, 406.8728] +24-11-19 18:55:38 | D | best error = [ 3.5853, 3.5853, 3.5853, 3.5853, 3.5853] +24-11-19 18:55:38 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:55:38 | D | sum error = [ 429.1013, 451.3497, 474.8569, 500.1662, 522.7682] +24-11-19 18:55:38 | D | best error = [ 3.5853, 3.5853, 3.5853, 3.5853, 3.5853] +24-11-19 18:55:38 | D | + error = [3.5853] +24-11-19 18:55:38 | D | - Calibrating model.layers.12.self_attn.v_proj.weight +24-11-19 18:55:38 | D | + w: sint8 +24-11-19 18:55:38 | D | + x: None +24-11-19 18:55:38 | D | + y: None +24-11-19 18:55:38 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:55:38 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:55:39 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:55:39 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:55:39 | D | - range ratio = [ 1.0000] +24-11-19 18:55:39 | D | sum error = [ 1.4829] +24-11-19 18:55:39 | D | best error = [ 1.4829] +24-11-19 18:55:39 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:55:39 | D | sum error = [ 1.4766, 1.4614, 1.4629, 1.4769, 1.5103] +24-11-19 18:55:39 | D | best error = [ 1.3705, 1.3279, 1.3040, 1.2913, 1.2851] +24-11-19 18:55:39 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:55:39 | D | sum error = [ 1.5586, 1.6066, 1.6758, 1.7463, 1.8507] +24-11-19 18:55:39 | D | best error = [ 1.2827, 1.2817, 1.2813, 1.2813, 1.2813] +24-11-19 18:55:39 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:55:39 | D | sum error = [ 1.9547, 2.0595, 2.2076, 2.3607, 2.5322] +24-11-19 18:55:39 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 18:55:39 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:55:39 | D | sum error = [ 2.6900, 2.8792, 3.0993, 3.3178, 3.5564] +24-11-19 18:55:39 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 18:55:39 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:55:39 | D | sum error = [ 3.8150, 4.1025, 4.3672, 4.6763, 4.9913] +24-11-19 18:55:39 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 18:55:39 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:55:39 | D | sum error = [ 5.3541, 5.6954, 6.0709, 6.4642, 6.8867] +24-11-19 18:55:39 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 18:55:39 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:55:39 | D | sum error = [ 7.3192, 7.7913, 8.2879, 8.8145, 9.3729] +24-11-19 18:55:39 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 18:55:39 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:55:39 | D | sum error = [ 9.9517, 10.5887, 11.2226, 11.9154, 12.6188] +24-11-19 18:55:39 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 18:55:39 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:55:39 | D | sum error = [ 13.3742, 14.1611, 14.9864, 15.8653, 16.7671] +24-11-19 18:55:39 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 18:55:39 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:55:39 | D | sum error = [ 17.7346, 18.7318, 19.7907, 20.9008, 22.0485] +24-11-19 18:55:39 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 18:55:39 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:55:39 | D | sum error = [ 23.2562, 24.5112, 25.8255, 27.2024, 28.6387] +24-11-19 18:55:39 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 18:55:39 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:55:39 | D | sum error = [ 30.1280, 31.6757, 33.2885, 34.9687, 36.7127] +24-11-19 18:55:39 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 18:55:39 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:55:39 | D | sum error = [ 38.5216, 40.3988, 42.3433, 44.3634, 46.4458] +24-11-19 18:55:39 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 18:55:39 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:55:39 | D | sum error = [ 48.6077, 50.8597, 53.1746, 55.5876, 58.0889] +24-11-19 18:55:39 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 18:55:39 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:55:39 | D | sum error = [ 60.6729, 63.3413, 66.1046, 68.9450, 71.8763] +24-11-19 18:55:39 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 18:55:39 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:55:39 | D | sum error = [ 74.9025, 78.0125, 81.2212, 84.5215, 87.9258] +24-11-19 18:55:39 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 18:55:39 | D | + error = [1.2813] +24-11-19 18:55:39 | D | - Calibrating model.layers.12.self_attn.o_proj.weight +24-11-19 18:55:39 | D | + w: sint8 +24-11-19 18:55:39 | D | + x: None +24-11-19 18:55:39 | D | + y: None +24-11-19 18:55:39 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:55:39 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:55:39 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:55:39 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:55:39 | D | - range ratio = [ 1.0000] +24-11-19 18:55:39 | D | sum error = [ 0.6289] +24-11-19 18:55:39 | D | best error = [ 0.6289] +24-11-19 18:55:40 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:55:40 | D | sum error = [ 0.6250, 0.6200, 0.6215, 0.6243, 0.6330] +24-11-19 18:55:40 | D | best error = [ 0.5732, 0.5483, 0.5347, 0.5259, 0.5200] +24-11-19 18:55:40 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:55:40 | D | sum error = [ 0.6442, 0.6590, 0.6755, 0.6963, 0.7224] +24-11-19 18:55:40 | D | best error = [ 0.5164, 0.5137, 0.5122, 0.5111, 0.5104] +24-11-19 18:55:40 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:55:40 | D | sum error = [ 0.7579, 0.7926, 0.8321, 0.8776, 0.9335] +24-11-19 18:55:40 | D | best error = [ 0.5100, 0.5098, 0.5096, 0.5096, 0.5095] +24-11-19 18:55:40 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:55:40 | D | sum error = [ 0.9845, 1.0463, 1.1124, 1.1852, 1.2639] +24-11-19 18:55:40 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 18:55:40 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:55:40 | D | sum error = [ 1.3422, 1.4332, 1.5256, 1.6274, 1.7308] +24-11-19 18:55:40 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 18:55:40 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:55:40 | D | sum error = [ 1.8446, 1.9603, 2.0878, 2.2212, 2.3595] +24-11-19 18:55:40 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 18:55:40 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:55:40 | D | sum error = [ 2.5072, 2.6611, 2.8227, 2.9967, 3.1770] +24-11-19 18:55:40 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 18:55:40 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:55:40 | D | sum error = [ 3.3625, 3.5630, 3.7722, 3.9892, 4.2194] +24-11-19 18:55:40 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 18:55:40 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:55:40 | D | sum error = [ 4.4533, 4.7080, 4.9696, 5.2450, 5.5312] +24-11-19 18:55:40 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 18:55:40 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:55:40 | D | sum error = [ 5.8293, 6.1455, 6.4713, 6.8133, 7.1666] +24-11-19 18:55:40 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 18:55:40 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:55:40 | D | sum error = [ 7.5353, 7.9201, 8.3153, 8.7279, 9.1563] +24-11-19 18:55:40 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 18:55:40 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:55:40 | D | sum error = [ 9.5973, 10.0583, 10.5332, 11.0280, 11.5383] +24-11-19 18:55:40 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 18:55:40 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:55:40 | D | sum error = [ 12.0652, 12.6100, 13.1717, 13.7517, 14.3504] +24-11-19 18:55:40 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 18:55:40 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:55:40 | D | sum error = [ 14.9626, 15.5948, 16.2468, 16.9156, 17.6015] +24-11-19 18:55:40 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 18:55:40 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:55:40 | D | sum error = [ 18.3063, 19.0291, 19.7715, 20.5326, 21.3137] +24-11-19 18:55:40 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 18:55:40 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:55:40 | D | sum error = [ 22.1187, 22.9431, 23.7848, 24.6463, 25.5304] +24-11-19 18:55:40 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 18:55:40 | D | + error = [0.5095] +24-11-19 18:55:40 | D | - Calibrating model.layers.12.mlp.up_proj.weight +24-11-19 18:55:40 | D | + w: sint8 +24-11-19 18:55:40 | D | + x: None +24-11-19 18:55:40 | D | + y: None +24-11-19 18:55:40 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:55:40 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:55:40 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:55:40 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:55:40 | D | - range ratio = [ 1.0000] +24-11-19 18:55:40 | D | sum error = [ 5.0366] +24-11-19 18:55:40 | D | best error = [ 5.0366] +24-11-19 18:55:41 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:55:41 | D | sum error = [ 4.9990, 4.9829, 5.0032, 5.0551, 5.1623] +24-11-19 18:55:41 | D | best error = [ 4.6633, 4.5225, 4.4471, 4.4068, 4.3856] +24-11-19 18:55:41 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:55:41 | D | sum error = [ 5.2902, 5.4587, 5.6778, 5.9661, 6.2834] +24-11-19 18:55:41 | D | best error = [ 4.3743, 4.3696, 4.3676, 4.3671, 4.3669] +24-11-19 18:55:41 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:55:41 | D | sum error = [ 6.6254, 7.0489, 7.5112, 8.0191, 8.5750] +24-11-19 18:55:41 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 18:55:41 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:55:41 | D | sum error = [ 9.1852, 9.8435, 10.5495, 11.3057, 12.1206] +24-11-19 18:55:41 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 18:55:41 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:55:41 | D | sum error = [ 12.9943, 13.9324, 14.9022, 15.9494, 17.0561] +24-11-19 18:55:41 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 18:55:41 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:55:41 | D | sum error = [ 18.2418, 19.4998, 20.8227, 22.2129, 23.7030] +24-11-19 18:55:41 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 18:55:41 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:55:41 | D | sum error = [ 25.2611, 26.9169, 28.6585, 30.4928, 32.4459] +24-11-19 18:55:41 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 18:55:41 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:55:41 | D | sum error = [ 34.4733, 36.6296, 38.9024, 41.2865, 43.7983] +24-11-19 18:55:41 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 18:55:41 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:55:41 | D | sum error = [ 46.4297, 49.2229, 52.1410, 55.2072, 58.4337] +24-11-19 18:55:41 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 18:55:41 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:55:41 | D | sum error = [ 61.8130, 65.3607, 69.0856, 72.9905, 77.0849] +24-11-19 18:55:41 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 18:55:41 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:55:41 | D | sum error = [ 81.3674, 85.8481, 90.5391, 95.4257, 100.5474] +24-11-19 18:55:41 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 18:55:41 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:55:41 | D | sum error = [ 105.8818, 111.4639, 117.2826, 123.3515, 129.6897] +24-11-19 18:55:41 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 18:55:41 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:55:41 | D | sum error = [ 136.2835, 143.1556, 150.3000, 157.7283, 165.4539] +24-11-19 18:55:41 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 18:55:41 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:55:41 | D | sum error = [ 173.4755, 181.8205, 190.4647, 199.4480, 208.7624] +24-11-19 18:55:41 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 18:55:41 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:55:41 | D | sum error = [ 218.3993, 228.3969, 238.7241, 249.4067, 260.4220] +24-11-19 18:55:41 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 18:55:41 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:55:41 | D | sum error = [ 271.7965, 283.5390, 295.6542, 308.1387, 320.9904] +24-11-19 18:55:41 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 18:55:41 | D | + error = [4.3669] +24-11-19 18:55:41 | D | - Calibrating model.layers.12.mlp.gate_proj.weight +24-11-19 18:55:41 | D | + w: sint8 +24-11-19 18:55:41 | D | + x: None +24-11-19 18:55:41 | D | + y: None +24-11-19 18:55:41 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:55:41 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:55:41 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:55:41 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:55:41 | D | - range ratio = [ 1.0000] +24-11-19 18:55:41 | D | sum error = [ 5.9746] +24-11-19 18:55:41 | D | best error = [ 5.9746] +24-11-19 18:55:42 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:55:42 | D | sum error = [ 5.9571, 5.9284, 5.9471, 6.0204, 6.1548] +24-11-19 18:55:42 | D | best error = [ 5.5443, 5.3803, 5.2911, 5.2421, 5.2175] +24-11-19 18:55:42 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:55:42 | D | sum error = [ 6.3064, 6.5198, 6.7917, 7.1285, 7.4829] +24-11-19 18:55:42 | D | best error = [ 5.2052, 5.2000, 5.1980, 5.1975, 5.1974] +24-11-19 18:55:42 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:55:42 | D | sum error = [ 7.9523, 8.4357, 9.0025, 9.6157, 10.3268] +24-11-19 18:55:42 | D | best error = [ 5.1974, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 18:55:42 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:55:42 | D | sum error = [ 11.0722, 11.8820, 12.7617, 13.7102, 14.7450] +24-11-19 18:55:42 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 18:55:42 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:55:42 | D | sum error = [ 15.8365, 17.0185, 18.2573, 19.6102, 21.0406] +24-11-19 18:55:42 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 18:55:42 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:55:42 | D | sum error = [ 22.5982, 24.2123, 25.9551, 27.8389, 29.8088] +24-11-19 18:55:42 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 18:55:42 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:55:42 | D | sum error = [ 31.9261, 34.1830, 36.5887, 39.1221, 41.8435] +24-11-19 18:55:42 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 18:55:42 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:55:42 | D | sum error = [ 44.7140, 47.7778, 51.0600, 54.5143, 58.2046] +24-11-19 18:55:42 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 18:55:42 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:55:42 | D | sum error = [ 62.1233, 66.2846, 70.6880, 75.4191, 80.3985] +24-11-19 18:55:43 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 18:55:43 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:55:43 | D | sum error = [ 85.6789, 91.3065, 97.2582, 103.5576, 110.2590] +24-11-19 18:55:43 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 18:55:43 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:55:43 | D | sum error = [ 117.3567, 124.8380, 132.7874, 141.1950, 150.0761] +24-11-19 18:55:43 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 18:55:43 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:55:43 | D | sum error = [ 159.4487, 169.3104, 179.6967, 190.6575, 202.1763] +24-11-19 18:55:43 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 18:55:43 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:55:43 | D | sum error = [ 214.2935, 227.0681, 240.4557, 254.5151, 269.2138] +24-11-19 18:55:43 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 18:55:43 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:55:43 | D | sum error = [ 284.5930, 300.7050, 317.5240, 335.0883, 353.3951] +24-11-19 18:55:43 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 18:55:43 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:55:43 | D | sum error = [ 372.4592, 392.2688, 412.8755, 434.2710, 456.4597] +24-11-19 18:55:43 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 18:55:43 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:55:43 | D | sum error = [ 479.4513, 503.2026, 527.7654, 553.1017, 579.2451] +24-11-19 18:55:43 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 18:55:43 | D | + error = [5.1973] +24-11-19 18:55:43 | D | - Calibrating model.layers.12.mlp.down_proj.weight +24-11-19 18:55:43 | D | + w: sint8 +24-11-19 18:55:43 | D | + x: None +24-11-19 18:55:43 | D | + y: None +24-11-19 18:55:43 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:55:43 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:55:43 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:55:43 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:55:43 | D | - range ratio = [ 1.0000] +24-11-19 18:55:43 | D | sum error = [ 0.6718] +24-11-19 18:55:43 | D | best error = [ 0.6718] +24-11-19 18:55:44 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:55:44 | D | sum error = [ 0.6655, 0.6621, 0.6577, 0.6568, 0.6570] +24-11-19 18:55:44 | D | best error = [ 0.6427, 0.6294, 0.6205, 0.6136, 0.6089] +24-11-19 18:55:44 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:55:44 | D | sum error = [ 0.6588, 0.6633, 0.6711, 0.6818, 0.6945] +24-11-19 18:55:44 | D | best error = [ 0.6053, 0.6023, 0.6004, 0.5992, 0.5980] +24-11-19 18:55:44 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:55:44 | D | sum error = [ 0.7111, 0.7315, 0.7555, 0.7835, 0.8156] +24-11-19 18:55:44 | D | best error = [ 0.5974, 0.5970, 0.5966, 0.5964, 0.5962] +24-11-19 18:55:44 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:55:44 | D | sum error = [ 0.8549, 0.8959, 0.9423, 0.9943, 1.0517] +24-11-19 18:55:44 | D | best error = [ 0.5961, 0.5961, 0.5960, 0.5960, 0.5960] +24-11-19 18:55:44 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:55:44 | D | sum error = [ 1.1159, 1.1819, 1.2567, 1.3387, 1.4232] +24-11-19 18:55:44 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 18:55:44 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:55:44 | D | sum error = [ 1.5141, 1.6153, 1.7216, 1.8351, 1.9585] +24-11-19 18:55:44 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 18:55:44 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:55:44 | D | sum error = [ 2.0885, 2.2276, 2.3749, 2.5319, 2.6980] +24-11-19 18:55:44 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 18:55:44 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:55:44 | D | sum error = [ 2.8758, 3.0634, 3.2631, 3.4736, 3.6964] +24-11-19 18:55:44 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 18:55:44 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:55:44 | D | sum error = [ 3.9332, 4.1819, 4.4466, 4.7255, 5.0211] +24-11-19 18:55:44 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 18:55:44 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:55:44 | D | sum error = [ 5.3305, 5.6588, 6.0037, 6.3687, 6.7518] +24-11-19 18:55:44 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 18:55:44 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:55:44 | D | sum error = [ 7.1550, 7.5798, 8.0252, 8.4943, 8.9852] +24-11-19 18:55:44 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 18:55:44 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:55:44 | D | sum error = [ 9.5012, 10.0422, 10.6073, 11.2004, 11.8205] +24-11-19 18:55:44 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 18:55:44 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:55:44 | D | sum error = [ 12.4705, 13.1506, 13.8622, 14.6033, 15.3779] +24-11-19 18:55:44 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 18:55:44 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:55:44 | D | sum error = [ 16.1862, 17.0293, 17.9081, 18.8244, 19.7753] +24-11-19 18:55:44 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 18:55:44 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:55:44 | D | sum error = [ 20.7673, 21.7987, 22.8696, 23.9827, 25.1384] +24-11-19 18:55:44 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 18:55:44 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:55:44 | D | sum error = [ 26.3362, 27.5773, 28.8618, 30.1930, 31.5687] +24-11-19 18:55:44 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 18:55:44 | D | + error = [0.5960] +24-11-19 18:55:44 | D | - Quantizing model.layers.12.self_attn.q_proj.weight +24-11-19 18:55:45 | D | - Quantizing model.layers.12.self_attn.k_proj.weight +24-11-19 18:55:46 | D | - Quantizing model.layers.12.self_attn.v_proj.weight +24-11-19 18:55:46 | D | - Quantizing model.layers.12.self_attn.o_proj.weight +24-11-19 18:55:47 | D | - Quantizing model.layers.12.mlp.up_proj.weight +24-11-19 18:55:48 | D | - Quantizing model.layers.12.mlp.gate_proj.weight +24-11-19 18:55:49 | D | - Quantizing model.layers.12.mlp.down_proj.weight +24-11-19 18:55:58 | D | - Quantizing layer model.layers.13 +24-11-19 18:55:58 | D | - Calibrating model.layers.13.self_attn.q_proj.weight +24-11-19 18:55:58 | D | + w: sint8 +24-11-19 18:55:58 | D | + x: None +24-11-19 18:55:58 | D | + y: None +24-11-19 18:55:58 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:55:58 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:55:58 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:55:59 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:55:59 | D | - range ratio = [ 1.0000] +24-11-19 18:55:59 | D | sum error = [ 5.3038] +24-11-19 18:55:59 | D | best error = [ 5.3038] +24-11-19 18:56:10 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:56:10 | D | sum error = [ 5.3981, 5.4006, 5.5628, 5.5630, 5.3853] +24-11-19 18:56:10 | D | best error = [ 5.3038, 5.3038, 5.3038, 5.3038, 5.3038] +24-11-19 18:56:10 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:56:10 | D | sum error = [ 5.6512, 6.0032, 5.9108, 6.3012, 6.7945] +24-11-19 18:56:10 | D | best error = [ 5.3038, 5.3038, 5.3038, 5.3038, 5.3038] +24-11-19 18:56:10 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:56:10 | D | sum error = [ 7.1401, 7.4213, 8.0908, 8.7587, 9.4481] +24-11-19 18:56:10 | D | best error = [ 5.3038, 5.3038, 5.3038, 5.3038, 5.3038] +24-11-19 18:56:10 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:56:10 | D | sum error = [ 9.9619, 10.6890, 11.5783, 12.4593, 13.2183] +24-11-19 18:56:10 | D | best error = [ 5.3038, 5.3038, 5.3038, 5.3038, 5.3038] +24-11-19 18:56:10 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:56:10 | D | sum error = [ 14.5959, 15.3804, 16.9637, 18.2317, 19.6758] +24-11-19 18:56:10 | D | best error = [ 5.3038, 5.3038, 5.3038, 5.3038, 5.3038] +24-11-19 18:56:10 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:56:10 | D | sum error = [ 21.2346, 22.8051, 24.7511, 26.4788, 28.5414] +24-11-19 18:56:10 | D | best error = [ 5.3038, 5.3038, 5.3038, 5.3038, 5.3038] +24-11-19 18:56:10 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:56:10 | D | sum error = [ 30.8450, 33.3110, 35.9532, 38.6176, 41.5174] +24-11-19 18:56:10 | D | best error = [ 5.3038, 5.3038, 5.3038, 5.3038, 5.3038] +24-11-19 18:56:10 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:56:10 | D | sum error = [ 44.4594, 47.6464, 51.1563, 54.7477, 58.7640] +24-11-19 18:56:10 | D | best error = [ 5.3038, 5.3038, 5.3038, 5.3038, 5.3038] +24-11-19 18:56:10 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:56:10 | D | sum error = [ 62.6809, 67.0492, 71.7697, 76.6263, 81.7066] +24-11-19 18:56:10 | D | best error = [ 5.3038, 5.3038, 5.3038, 5.3038, 5.3038] +24-11-19 18:56:10 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:56:10 | D | sum error = [ 87.1238, 92.7970, 98.7183, 105.0406, 111.6306] +24-11-19 18:56:10 | D | best error = [ 5.3038, 5.3038, 5.3038, 5.3038, 5.3038] +24-11-19 18:56:10 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:56:10 | D | sum error = [ 118.4758, 125.9109, 133.7735, 141.9214, 150.6158] +24-11-19 18:56:10 | D | best error = [ 5.3038, 5.3038, 5.3038, 5.3038, 5.3038] +24-11-19 18:56:10 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:56:10 | D | sum error = [ 159.4323, 169.1017, 179.0343, 189.5533, 200.6008] +24-11-19 18:56:10 | D | best error = [ 5.3038, 5.3038, 5.3038, 5.3038, 5.3038] +24-11-19 18:56:10 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:56:10 | D | sum error = [ 211.9362, 223.8820, 236.4099, 249.4446, 262.9132] +24-11-19 18:56:10 | D | best error = [ 5.3038, 5.3038, 5.3038, 5.3038, 5.3038] +24-11-19 18:56:10 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:56:10 | D | sum error = [ 277.1951, 291.9312, 307.2506, 323.1073, 339.6848] +24-11-19 18:56:10 | D | best error = [ 5.3038, 5.3038, 5.3038, 5.3038, 5.3038] +24-11-19 18:56:10 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:56:10 | D | sum error = [ 356.7316, 374.4578, 392.7356, 411.5135, 430.7887] +24-11-19 18:56:10 | D | best error = [ 5.3038, 5.3038, 5.3038, 5.3038, 5.3038] +24-11-19 18:56:10 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:56:10 | D | sum error = [ 450.5989, 470.9079, 491.6017, 512.6168, 533.9838] +24-11-19 18:56:10 | D | best error = [ 5.3038, 5.3038, 5.3038, 5.3038, 5.3038] +24-11-19 18:56:10 | D | + error = [5.3038] +24-11-19 18:56:10 | D | - Calibrating model.layers.13.self_attn.k_proj.weight +24-11-19 18:56:10 | D | + w: sint8 +24-11-19 18:56:10 | D | + x: None +24-11-19 18:56:10 | D | + y: None +24-11-19 18:56:10 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:56:10 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:56:10 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:56:11 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:56:11 | D | - range ratio = [ 1.0000] +24-11-19 18:56:11 | D | sum error = [ 4.4387] +24-11-19 18:56:11 | D | best error = [ 4.4387] +24-11-19 18:56:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:56:22 | D | sum error = [ 4.1029, 4.0080, 4.2150, 4.3383, 4.3855] +24-11-19 18:56:22 | D | best error = [ 4.1029, 4.0080, 4.0080, 4.0080, 4.0080] +24-11-19 18:56:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:56:22 | D | sum error = [ 4.4124, 4.6053, 4.7580, 4.9809, 5.0823] +24-11-19 18:56:22 | D | best error = [ 4.0080, 4.0080, 4.0080, 4.0080, 4.0080] +24-11-19 18:56:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:56:22 | D | sum error = [ 5.5889, 5.7283, 6.1720, 6.3595, 7.2249] +24-11-19 18:56:22 | D | best error = [ 4.0080, 4.0080, 4.0080, 4.0080, 4.0080] +24-11-19 18:56:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:56:22 | D | sum error = [ 7.6801, 8.2844, 8.7435, 9.2481, 10.1532] +24-11-19 18:56:22 | D | best error = [ 4.0080, 4.0080, 4.0080, 4.0080, 4.0080] +24-11-19 18:56:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:56:22 | D | sum error = [ 11.2961, 11.8572, 13.0089, 14.1579, 15.2324] +24-11-19 18:56:22 | D | best error = [ 4.0080, 4.0080, 4.0080, 4.0080, 4.0080] +24-11-19 18:56:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:56:22 | D | sum error = [ 16.1760, 17.5284, 19.2622, 21.0974, 23.1835] +24-11-19 18:56:22 | D | best error = [ 4.0080, 4.0080, 4.0080, 4.0080, 4.0080] +24-11-19 18:56:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:56:22 | D | sum error = [ 24.1710, 26.6480, 28.6510, 31.1216, 34.0607] +24-11-19 18:56:22 | D | best error = [ 4.0080, 4.0080, 4.0080, 4.0080, 4.0080] +24-11-19 18:56:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:56:22 | D | sum error = [ 36.3209, 40.0826, 43.5316, 46.9012, 49.9913] +24-11-19 18:56:22 | D | best error = [ 4.0080, 4.0080, 4.0080, 4.0080, 4.0080] +24-11-19 18:56:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:56:22 | D | sum error = [ 54.2593, 57.9007, 62.6759, 67.6794, 72.7168] +24-11-19 18:56:22 | D | best error = [ 4.0080, 4.0080, 4.0080, 4.0080, 4.0080] +24-11-19 18:56:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:56:22 | D | sum error = [ 77.9984, 84.2466, 90.2570, 96.9479, 103.7203] +24-11-19 18:56:22 | D | best error = [ 4.0080, 4.0080, 4.0080, 4.0080, 4.0080] +24-11-19 18:56:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:56:22 | D | sum error = [ 111.0081, 119.3575, 127.8148, 136.2514, 144.8006] +24-11-19 18:56:22 | D | best error = [ 4.0080, 4.0080, 4.0080, 4.0080, 4.0080] +24-11-19 18:56:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:56:22 | D | sum error = [ 153.9723, 163.5844, 173.8525, 184.8140, 195.8745] +24-11-19 18:56:22 | D | best error = [ 4.0080, 4.0080, 4.0080, 4.0080, 4.0080] +24-11-19 18:56:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:56:22 | D | sum error = [ 207.9184, 219.5990, 231.5497, 243.8893, 256.4903] +24-11-19 18:56:22 | D | best error = [ 4.0080, 4.0080, 4.0080, 4.0080, 4.0080] +24-11-19 18:56:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:56:22 | D | sum error = [ 270.5943, 285.1681, 299.4824, 313.7993, 328.6859] +24-11-19 18:56:22 | D | best error = [ 4.0080, 4.0080, 4.0080, 4.0080, 4.0080] +24-11-19 18:56:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:56:22 | D | sum error = [ 345.0849, 361.4082, 379.1264, 397.7535, 415.8113] +24-11-19 18:56:22 | D | best error = [ 4.0080, 4.0080, 4.0080, 4.0080, 4.0080] +24-11-19 18:56:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:56:22 | D | sum error = [ 434.9063, 454.4729, 475.0996, 496.2528, 518.1765] +24-11-19 18:56:22 | D | best error = [ 4.0080, 4.0080, 4.0080, 4.0080, 4.0080] +24-11-19 18:56:22 | D | + error = [4.0080] +24-11-19 18:56:22 | D | - Calibrating model.layers.13.self_attn.v_proj.weight +24-11-19 18:56:22 | D | + w: sint8 +24-11-19 18:56:22 | D | + x: None +24-11-19 18:56:22 | D | + y: None +24-11-19 18:56:22 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:56:22 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:56:23 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:56:23 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:56:23 | D | - range ratio = [ 1.0000] +24-11-19 18:56:23 | D | sum error = [ 1.5429] +24-11-19 18:56:23 | D | best error = [ 1.5429] +24-11-19 18:56:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:56:23 | D | sum error = [ 1.5350, 1.5290, 1.5368, 1.5639, 1.5954] +24-11-19 18:56:23 | D | best error = [ 1.4093, 1.3642, 1.3425, 1.3299, 1.3238] +24-11-19 18:56:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:56:23 | D | sum error = [ 1.6296, 1.6694, 1.7427, 1.8536, 1.9289] +24-11-19 18:56:23 | D | best error = [ 1.3197, 1.3181, 1.3178, 1.3177, 1.3177] +24-11-19 18:56:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:56:23 | D | sum error = [ 2.0451, 2.1628, 2.3128, 2.4615, 2.6435] +24-11-19 18:56:23 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 18:56:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:56:23 | D | sum error = [ 2.8114, 3.0145, 3.2200, 3.4621, 3.6950] +24-11-19 18:56:23 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 18:56:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:56:23 | D | sum error = [ 3.9478, 4.2212, 4.5173, 4.8290, 5.1521] +24-11-19 18:56:23 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 18:56:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:56:23 | D | sum error = [ 5.4972, 5.8585, 6.2739, 6.6815, 7.1183] +24-11-19 18:56:23 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 18:56:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:56:23 | D | sum error = [ 7.5799, 8.0737, 8.6016, 9.1444, 9.7151] +24-11-19 18:56:23 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 18:56:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:56:23 | D | sum error = [ 10.3166, 10.9586, 11.6357, 12.3359, 13.0785] +24-11-19 18:56:23 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 18:56:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:56:23 | D | sum error = [ 13.8629, 14.6678, 15.5410, 16.4329, 17.3832] +24-11-19 18:56:23 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 18:56:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:56:23 | D | sum error = [ 18.3756, 19.4148, 20.4995, 21.6436, 22.8292] +24-11-19 18:56:23 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 18:56:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:56:23 | D | sum error = [ 24.0745, 25.3791, 26.7424, 28.1612, 29.6329] +24-11-19 18:56:23 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 18:56:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:56:23 | D | sum error = [ 31.1733, 32.7542, 34.4259, 36.1649, 37.9658] +24-11-19 18:56:23 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 18:56:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:56:23 | D | sum error = [ 39.8514, 41.8059, 43.8316, 45.9401, 48.1339] +24-11-19 18:56:23 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 18:56:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:56:23 | D | sum error = [ 50.3988, 52.7430, 55.1722, 57.6815, 60.2809] +24-11-19 18:56:23 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 18:56:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:56:23 | D | sum error = [ 62.9655, 65.7383, 68.6042, 71.5639, 74.6215] +24-11-19 18:56:23 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 18:56:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:56:23 | D | sum error = [ 77.7620, 81.0098, 84.3464, 87.7824, 91.3219] +24-11-19 18:56:23 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 18:56:23 | D | + error = [1.3177] +24-11-19 18:56:23 | D | - Calibrating model.layers.13.self_attn.o_proj.weight +24-11-19 18:56:23 | D | + w: sint8 +24-11-19 18:56:23 | D | + x: None +24-11-19 18:56:23 | D | + y: None +24-11-19 18:56:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:56:23 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:56:23 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:56:23 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:56:23 | D | - range ratio = [ 1.0000] +24-11-19 18:56:23 | D | sum error = [ 0.6588] +24-11-19 18:56:23 | D | best error = [ 0.6588] +24-11-19 18:56:24 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:56:24 | D | sum error = [ 0.6568, 0.6514, 0.6565, 0.6617, 0.6734] +24-11-19 18:56:24 | D | best error = [ 0.5910, 0.5594, 0.5430, 0.5318, 0.5248] +24-11-19 18:56:24 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:56:24 | D | sum error = [ 0.6896, 0.7039, 0.7348, 0.7634, 0.7994] +24-11-19 18:56:24 | D | best error = [ 0.5198, 0.5166, 0.5144, 0.5129, 0.5119] +24-11-19 18:56:24 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:56:24 | D | sum error = [ 0.8402, 0.8837, 0.9338, 0.9910, 1.0525] +24-11-19 18:56:24 | D | best error = [ 0.5114, 0.5110, 0.5107, 0.5106, 0.5105] +24-11-19 18:56:24 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:56:24 | D | sum error = [ 1.1177, 1.1877, 1.2632, 1.3458, 1.4343] +24-11-19 18:56:24 | D | best error = [ 0.5105, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 18:56:24 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:56:24 | D | sum error = [ 1.5245, 1.6276, 1.7294, 1.8399, 1.9527] +24-11-19 18:56:24 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 18:56:24 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:56:24 | D | sum error = [ 2.0768, 2.2061, 2.3416, 2.4839, 2.6291] +24-11-19 18:56:24 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 18:56:24 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:56:24 | D | sum error = [ 2.7886, 2.9508, 3.1279, 3.3051, 3.4927] +24-11-19 18:56:24 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 18:56:24 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:56:24 | D | sum error = [ 3.6904, 3.8974, 4.1133, 4.3375, 4.5716] +24-11-19 18:56:24 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 18:56:24 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:56:24 | D | sum error = [ 4.8163, 5.0719, 5.3363, 5.6192, 5.9095] +24-11-19 18:56:24 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 18:56:24 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:56:24 | D | sum error = [ 6.2093, 6.5236, 6.8500, 7.1834, 7.5352] +24-11-19 18:56:24 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 18:56:24 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:56:24 | D | sum error = [ 7.8951, 8.2698, 8.6552, 9.0568, 9.4680] +24-11-19 18:56:24 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 18:56:24 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:56:24 | D | sum error = [ 9.8942, 10.3319, 10.7807, 11.2484, 11.7246] +24-11-19 18:56:24 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 18:56:24 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:56:24 | D | sum error = [ 12.2156, 12.7226, 13.2430, 13.7808, 14.3283] +24-11-19 18:56:24 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 18:56:24 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:56:24 | D | sum error = [ 14.8914, 15.4735, 16.0661, 16.6792, 17.3051] +24-11-19 18:56:24 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 18:56:24 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:56:24 | D | sum error = [ 17.9511, 18.6125, 19.2887, 19.9897, 20.7109] +24-11-19 18:56:24 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 18:56:24 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:56:24 | D | sum error = [ 21.4516, 22.2132, 22.9957, 23.8033, 24.6391] +24-11-19 18:56:24 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 18:56:24 | D | + error = [0.5104] +24-11-19 18:56:24 | D | - Calibrating model.layers.13.mlp.up_proj.weight +24-11-19 18:56:24 | D | + w: sint8 +24-11-19 18:56:24 | D | + x: None +24-11-19 18:56:24 | D | + y: None +24-11-19 18:56:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:56:24 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:56:24 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:56:24 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:56:24 | D | - range ratio = [ 1.0000] +24-11-19 18:56:24 | D | sum error = [ 5.2102] +24-11-19 18:56:24 | D | best error = [ 5.2102] +24-11-19 18:56:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:56:25 | D | sum error = [ 5.1758, 5.1702, 5.2003, 5.2598, 5.3390] +24-11-19 18:56:25 | D | best error = [ 4.8357, 4.6922, 4.6136, 4.5708, 4.5482] +24-11-19 18:56:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:56:25 | D | sum error = [ 5.4806, 5.6726, 5.9000, 6.1787, 6.5039] +24-11-19 18:56:25 | D | best error = [ 4.5359, 4.5308, 4.5291, 4.5284, 4.5282] +24-11-19 18:56:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:56:25 | D | sum error = [ 6.8674, 7.3069, 7.7922, 8.3069, 8.8931] +24-11-19 18:56:25 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 18:56:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:56:25 | D | sum error = [ 9.4960, 10.1876, 10.9180, 11.6992, 12.5266] +24-11-19 18:56:25 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 18:56:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:56:25 | D | sum error = [ 13.4339, 14.3896, 15.4123, 16.5008, 17.6429] +24-11-19 18:56:25 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 18:56:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:56:25 | D | sum error = [ 18.8569, 20.1547, 21.5269, 22.9633, 24.4981] +24-11-19 18:56:25 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 18:56:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:56:25 | D | sum error = [ 26.0932, 27.8183, 29.6190, 31.4963, 33.5095] +24-11-19 18:56:25 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 18:56:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:56:25 | D | sum error = [ 35.6122, 37.8439, 40.1722, 42.6393, 45.2255] +24-11-19 18:56:25 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 18:56:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:56:25 | D | sum error = [ 47.9564, 50.8041, 53.8127, 56.9847, 60.2812] +24-11-19 18:56:25 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 18:56:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:56:25 | D | sum error = [ 63.7635, 67.4108, 71.2418, 75.2470, 79.4447] +24-11-19 18:56:25 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 18:56:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:56:25 | D | sum error = [ 83.8205, 88.4225, 93.2233, 98.2381, 103.4799] +24-11-19 18:56:25 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 18:56:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:56:25 | D | sum error = [ 108.9464, 114.6504, 120.6141, 126.8270, 133.3027] +24-11-19 18:56:25 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 18:56:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:56:25 | D | sum error = [ 140.0322, 147.0576, 154.3504, 161.9396, 169.8329] +24-11-19 18:56:25 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 18:56:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:56:25 | D | sum error = [ 178.0237, 186.5369, 195.3642, 204.5080, 213.9904] +24-11-19 18:56:25 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 18:56:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:56:25 | D | sum error = [ 223.8040, 233.9642, 244.4656, 255.3158, 266.5171] +24-11-19 18:56:25 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 18:56:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:56:25 | D | sum error = [ 278.0772, 290.0024, 302.3057, 314.9910, 328.0301] +24-11-19 18:56:25 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 18:56:25 | D | + error = [4.5282] +24-11-19 18:56:25 | D | - Calibrating model.layers.13.mlp.gate_proj.weight +24-11-19 18:56:25 | D | + w: sint8 +24-11-19 18:56:25 | D | + x: None +24-11-19 18:56:25 | D | + y: None +24-11-19 18:56:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:56:25 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:56:25 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:56:25 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:56:25 | D | - range ratio = [ 1.0000] +24-11-19 18:56:25 | D | sum error = [ 6.2251] +24-11-19 18:56:25 | D | best error = [ 6.2251] +24-11-19 18:56:27 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:56:27 | D | sum error = [ 6.1723, 6.1683, 6.2014, 6.2660, 6.3768] +24-11-19 18:56:27 | D | best error = [ 5.7641, 5.5894, 5.4985, 5.4462, 5.4179] +24-11-19 18:56:27 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:56:27 | D | sum error = [ 6.5523, 6.7687, 7.0503, 7.3910, 7.7925] +24-11-19 18:56:27 | D | best error = [ 5.4040, 5.3982, 5.3957, 5.3952, 5.3950] +24-11-19 18:56:27 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:56:27 | D | sum error = [ 8.2577, 8.7634, 9.3525, 10.0051, 10.7003] +24-11-19 18:56:27 | D | best error = [ 5.3949, 5.3949, 5.3949, 5.3949, 5.3949] +24-11-19 18:56:27 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:56:27 | D | sum error = [ 11.4827, 12.3220, 13.2169, 14.2106, 15.2751] +24-11-19 18:56:27 | D | best error = [ 5.3949, 5.3949, 5.3949, 5.3949, 5.3949] +24-11-19 18:56:27 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:56:27 | D | sum error = [ 16.4005, 17.5904, 18.8915, 20.2942, 21.7735] +24-11-19 18:56:27 | D | best error = [ 5.3949, 5.3949, 5.3949, 5.3949, 5.3949] +24-11-19 18:56:27 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:56:27 | D | sum error = [ 23.3566, 25.0217, 26.8342, 28.7316, 30.7819] +24-11-19 18:56:27 | D | best error = [ 5.3949, 5.3949, 5.3949, 5.3949, 5.3949] +24-11-19 18:56:27 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:56:27 | D | sum error = [ 32.9636, 35.2703, 37.7539, 40.3762, 43.1596] +24-11-19 18:56:27 | D | best error = [ 5.3949, 5.3949, 5.3949, 5.3949, 5.3949] +24-11-19 18:56:27 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:56:27 | D | sum error = [ 46.1526, 49.3273, 52.7176, 56.3079, 60.1296] +24-11-19 18:56:27 | D | best error = [ 5.3949, 5.3949, 5.3949, 5.3949, 5.3949] +24-11-19 18:56:27 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:56:27 | D | sum error = [ 64.2194, 68.5706, 73.1549, 78.0800, 83.2820] +24-11-19 18:56:27 | D | best error = [ 5.3949, 5.3949, 5.3949, 5.3949, 5.3949] +24-11-19 18:56:27 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:56:27 | D | sum error = [ 88.8147, 94.7358, 100.9637, 107.6051, 114.6458] +24-11-19 18:56:27 | D | best error = [ 5.3949, 5.3949, 5.3949, 5.3949, 5.3949] +24-11-19 18:56:27 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:56:27 | D | sum error = [ 122.0924, 129.9975, 138.3405, 147.1863, 156.5571] +24-11-19 18:56:27 | D | best error = [ 5.3949, 5.3949, 5.3949, 5.3949, 5.3949] +24-11-19 18:56:27 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:56:27 | D | sum error = [ 166.4357, 176.8694, 187.8705, 199.4856, 211.7042] +24-11-19 18:56:27 | D | best error = [ 5.3949, 5.3949, 5.3949, 5.3949, 5.3949] +24-11-19 18:56:27 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:56:27 | D | sum error = [ 224.5575, 238.0970, 252.3138, 267.2375, 282.8820] +24-11-19 18:56:27 | D | best error = [ 5.3949, 5.3949, 5.3949, 5.3949, 5.3949] +24-11-19 18:56:27 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:56:27 | D | sum error = [ 299.2774, 316.4116, 334.3222, 352.9916, 372.4699] +24-11-19 18:56:27 | D | best error = [ 5.3949, 5.3949, 5.3949, 5.3949, 5.3949] +24-11-19 18:56:27 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:56:27 | D | sum error = [ 392.7614, 413.8571, 435.8225, 458.5879, 482.2116] +24-11-19 18:56:27 | D | best error = [ 5.3949, 5.3949, 5.3949, 5.3949, 5.3949] +24-11-19 18:56:27 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:56:27 | D | sum error = [ 506.6651, 531.9860, 558.1123, 585.0571, 612.8567] +24-11-19 18:56:27 | D | best error = [ 5.3949, 5.3949, 5.3949, 5.3949, 5.3949] +24-11-19 18:56:27 | D | + error = [5.3949] +24-11-19 18:56:27 | D | - Calibrating model.layers.13.mlp.down_proj.weight +24-11-19 18:56:27 | D | + w: sint8 +24-11-19 18:56:27 | D | + x: None +24-11-19 18:56:27 | D | + y: None +24-11-19 18:56:27 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:56:27 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:56:27 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:56:27 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:56:27 | D | - range ratio = [ 1.0000] +24-11-19 18:56:27 | D | sum error = [ 0.7254] +24-11-19 18:56:27 | D | best error = [ 0.7254] +24-11-19 18:56:28 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:56:28 | D | sum error = [ 0.7192, 0.7146, 0.7102, 0.7098, 0.7082] +24-11-19 18:56:28 | D | best error = [ 0.6907, 0.6752, 0.6646, 0.6575, 0.6519] +24-11-19 18:56:28 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:56:28 | D | sum error = [ 0.7093, 0.7155, 0.7196, 0.7296, 0.7448] +24-11-19 18:56:28 | D | best error = [ 0.6480, 0.6447, 0.6422, 0.6405, 0.6394] +24-11-19 18:56:28 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:56:28 | D | sum error = [ 0.7647, 0.7823, 0.8085, 0.8381, 0.8746] +24-11-19 18:56:28 | D | best error = [ 0.6386, 0.6381, 0.6377, 0.6374, 0.6372] +24-11-19 18:56:28 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:56:28 | D | sum error = [ 0.9123, 0.9562, 1.0070, 1.0631, 1.1251] +24-11-19 18:56:28 | D | best error = [ 0.6371, 0.6370, 0.6370, 0.6369, 0.6369] +24-11-19 18:56:28 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:56:28 | D | sum error = [ 1.1921, 1.2647, 1.3460, 1.4341, 1.5275] +24-11-19 18:56:28 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 18:56:28 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:56:28 | D | sum error = [ 1.6281, 1.7397, 1.8549, 1.9804, 2.1134] +24-11-19 18:56:28 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 18:56:28 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:56:28 | D | sum error = [ 2.2568, 2.4085, 2.5715, 2.7445, 2.9283] +24-11-19 18:56:28 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 18:56:28 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:56:28 | D | sum error = [ 3.1222, 3.3280, 3.5468, 3.7791, 4.0240] +24-11-19 18:56:28 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 18:56:28 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:56:28 | D | sum error = [ 4.2826, 4.5580, 4.8473, 5.1518, 5.4752] +24-11-19 18:56:28 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 18:56:28 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:56:28 | D | sum error = [ 5.8154, 6.1744, 6.5526, 6.9505, 7.3688] +24-11-19 18:56:28 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 18:56:28 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:56:28 | D | sum error = [ 7.8083, 8.2707, 8.7601, 9.2692, 9.8057] +24-11-19 18:56:28 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 18:56:28 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:56:28 | D | sum error = [ 10.3667, 10.9554, 11.5725, 12.2183, 12.8948] +24-11-19 18:56:28 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 18:56:28 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:56:28 | D | sum error = [ 13.6020, 14.3385, 15.1090, 15.9131, 16.7516] +24-11-19 18:56:28 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 18:56:28 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:56:28 | D | sum error = [ 17.6263, 18.5389, 19.4880, 20.4773, 21.5059] +24-11-19 18:56:28 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 18:56:28 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:56:28 | D | sum error = [ 22.5744, 23.6864, 24.8397, 26.0345, 27.2732] +24-11-19 18:56:28 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 18:56:28 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:56:28 | D | sum error = [ 28.5544, 29.8807, 31.2529, 32.6707, 34.1344] +24-11-19 18:56:28 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 18:56:28 | D | + error = [0.6369] +24-11-19 18:56:28 | D | - Quantizing model.layers.13.self_attn.q_proj.weight +24-11-19 18:56:29 | D | - Quantizing model.layers.13.self_attn.k_proj.weight +24-11-19 18:56:30 | D | - Quantizing model.layers.13.self_attn.v_proj.weight +24-11-19 18:56:30 | D | - Quantizing model.layers.13.self_attn.o_proj.weight +24-11-19 18:56:31 | D | - Quantizing model.layers.13.mlp.up_proj.weight +24-11-19 18:56:32 | D | - Quantizing model.layers.13.mlp.gate_proj.weight +24-11-19 18:56:33 | D | - Quantizing model.layers.13.mlp.down_proj.weight +24-11-19 18:56:42 | D | - Quantizing layer model.layers.14 +24-11-19 18:56:42 | D | - Calibrating model.layers.14.self_attn.q_proj.weight +24-11-19 18:56:42 | D | + w: sint8 +24-11-19 18:56:42 | D | + x: None +24-11-19 18:56:42 | D | + y: None +24-11-19 18:56:42 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:56:42 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:56:42 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:56:43 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:56:43 | D | - range ratio = [ 1.0000] +24-11-19 18:56:43 | D | sum error = [ 5.6111] +24-11-19 18:56:43 | D | best error = [ 5.6111] +24-11-19 18:56:54 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:56:54 | D | sum error = [ 5.4014, 5.3813, 5.5717, 5.5683, 5.6150] +24-11-19 18:56:54 | D | best error = [ 5.4014, 5.3813, 5.3813, 5.3813, 5.3813] +24-11-19 18:56:54 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:56:54 | D | sum error = [ 5.8998, 5.9547, 6.1773, 6.5401, 6.9792] +24-11-19 18:56:54 | D | best error = [ 5.3813, 5.3813, 5.3813, 5.3813, 5.3813] +24-11-19 18:56:54 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:56:54 | D | sum error = [ 7.3891, 7.6953, 8.3489, 9.2088, 9.8451] +24-11-19 18:56:54 | D | best error = [ 5.3813, 5.3813, 5.3813, 5.3813, 5.3813] +24-11-19 18:56:54 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:56:54 | D | sum error = [ 10.1053, 10.9755, 11.9259, 12.7782, 13.9147] +24-11-19 18:56:54 | D | best error = [ 5.3813, 5.3813, 5.3813, 5.3813, 5.3813] +24-11-19 18:56:54 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:56:54 | D | sum error = [ 15.0960, 16.5069, 17.6462, 19.1201, 20.5094] +24-11-19 18:56:54 | D | best error = [ 5.3813, 5.3813, 5.3813, 5.3813, 5.3813] +24-11-19 18:56:54 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:56:54 | D | sum error = [ 22.1587, 24.0780, 25.6984, 27.4993, 30.0439] +24-11-19 18:56:54 | D | best error = [ 5.3813, 5.3813, 5.3813, 5.3813, 5.3813] +24-11-19 18:56:54 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:56:54 | D | sum error = [ 32.4122, 34.7453, 37.1093, 40.0502, 42.6314] +24-11-19 18:56:54 | D | best error = [ 5.3813, 5.3813, 5.3813, 5.3813, 5.3813] +24-11-19 18:56:54 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:56:54 | D | sum error = [ 45.5032, 48.9969, 52.3630, 55.9802, 59.5885] +24-11-19 18:56:54 | D | best error = [ 5.3813, 5.3813, 5.3813, 5.3813, 5.3813] +24-11-19 18:56:54 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:56:54 | D | sum error = [ 63.5765, 68.1188, 72.4540, 77.1453, 82.0491] +24-11-19 18:56:54 | D | best error = [ 5.3813, 5.3813, 5.3813, 5.3813, 5.3813] +24-11-19 18:56:54 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:56:54 | D | sum error = [ 87.1327, 92.5585, 97.8791, 103.7211, 109.9035] +24-11-19 18:56:54 | D | best error = [ 5.3813, 5.3813, 5.3813, 5.3813, 5.3813] +24-11-19 18:56:54 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:56:54 | D | sum error = [ 116.1118, 122.7966, 129.6247, 136.9509, 144.5504] +24-11-19 18:56:54 | D | best error = [ 5.3813, 5.3813, 5.3813, 5.3813, 5.3813] +24-11-19 18:56:54 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:56:54 | D | sum error = [ 152.0679, 160.3002, 168.9740, 178.1889, 187.8535] +24-11-19 18:56:54 | D | best error = [ 5.3813, 5.3813, 5.3813, 5.3813, 5.3813] +24-11-19 18:56:54 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:56:54 | D | sum error = [ 198.1310, 209.0024, 220.4640, 232.5272, 245.1718] +24-11-19 18:56:54 | D | best error = [ 5.3813, 5.3813, 5.3813, 5.3813, 5.3813] +24-11-19 18:56:54 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:56:54 | D | sum error = [ 258.7759, 273.0274, 288.2411, 304.1564, 321.1497] +24-11-19 18:56:54 | D | best error = [ 5.3813, 5.3813, 5.3813, 5.3813, 5.3813] +24-11-19 18:56:54 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:56:54 | D | sum error = [ 339.0667, 358.0172, 377.8824, 399.0825, 421.2239] +24-11-19 18:56:54 | D | best error = [ 5.3813, 5.3813, 5.3813, 5.3813, 5.3813] +24-11-19 18:56:54 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:56:54 | D | sum error = [ 444.4518, 468.7360, 494.3196, 521.0026, 548.8147] +24-11-19 18:56:54 | D | best error = [ 5.3813, 5.3813, 5.3813, 5.3813, 5.3813] +24-11-19 18:56:54 | D | + error = [5.3813] +24-11-19 18:56:55 | D | - Calibrating model.layers.14.self_attn.k_proj.weight +24-11-19 18:56:55 | D | + w: sint8 +24-11-19 18:56:55 | D | + x: None +24-11-19 18:56:55 | D | + y: None +24-11-19 18:56:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:56:55 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:56:55 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:56:55 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:56:55 | D | - range ratio = [ 1.0000] +24-11-19 18:56:55 | D | sum error = [ 4.3701] +24-11-19 18:56:55 | D | best error = [ 4.3701] +24-11-19 18:57:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:57:07 | D | sum error = [ 4.4955, 4.3097, 4.5723, 4.3650, 5.0455] +24-11-19 18:57:07 | D | best error = [ 4.3701, 4.3097, 4.3097, 4.3097, 4.3097] +24-11-19 18:57:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:57:07 | D | sum error = [ 4.9314, 4.5811, 5.8917, 5.0530, 5.5143] +24-11-19 18:57:07 | D | best error = [ 4.3097, 4.3097, 4.3097, 4.3097, 4.3097] +24-11-19 18:57:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:57:07 | D | sum error = [ 6.4586, 6.6418, 7.0218, 8.8157, 8.3483] +24-11-19 18:57:07 | D | best error = [ 4.3097, 4.3097, 4.3097, 4.3097, 4.3097] +24-11-19 18:57:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:57:07 | D | sum error = [ 8.6419, 9.5916, 10.1296, 11.9891, 11.8937] +24-11-19 18:57:07 | D | best error = [ 4.3097, 4.3097, 4.3097, 4.3097, 4.3097] +24-11-19 18:57:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:57:07 | D | sum error = [ 14.0719, 14.3644, 16.0512, 16.9049, 18.0257] +24-11-19 18:57:07 | D | best error = [ 4.3097, 4.3097, 4.3097, 4.3097, 4.3097] +24-11-19 18:57:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:57:07 | D | sum error = [ 19.1538, 20.9728, 23.1256, 25.2782, 26.3509] +24-11-19 18:57:07 | D | best error = [ 4.3097, 4.3097, 4.3097, 4.3097, 4.3097] +24-11-19 18:57:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:57:07 | D | sum error = [ 28.6109, 31.0152, 33.6197, 36.0794, 39.0674] +24-11-19 18:57:07 | D | best error = [ 4.3097, 4.3097, 4.3097, 4.3097, 4.3097] +24-11-19 18:57:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:57:07 | D | sum error = [ 41.7453, 44.4463, 48.3525, 51.8914, 55.1604] +24-11-19 18:57:07 | D | best error = [ 4.3097, 4.3097, 4.3097, 4.3097, 4.3097] +24-11-19 18:57:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:57:07 | D | sum error = [ 59.3391, 64.0391, 68.8167, 73.8031, 79.4903] +24-11-19 18:57:07 | D | best error = [ 4.3097, 4.3097, 4.3097, 4.3097, 4.3097] +24-11-19 18:57:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:57:07 | D | sum error = [ 84.3694, 90.0761, 95.8236, 102.4762, 109.8069] +24-11-19 18:57:07 | D | best error = [ 4.3097, 4.3097, 4.3097, 4.3097, 4.3097] +24-11-19 18:57:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:57:07 | D | sum error = [ 116.7547, 123.7214, 132.0118, 140.0602, 148.8361] +24-11-19 18:57:07 | D | best error = [ 4.3097, 4.3097, 4.3097, 4.3097, 4.3097] +24-11-19 18:57:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:57:07 | D | sum error = [ 157.1927, 168.2826, 178.8806, 190.0644, 201.3537] +24-11-19 18:57:07 | D | best error = [ 4.3097, 4.3097, 4.3097, 4.3097, 4.3097] +24-11-19 18:57:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:57:07 | D | sum error = [ 212.7312, 224.9237, 237.3854, 250.2167, 264.0265] +24-11-19 18:57:07 | D | best error = [ 4.3097, 4.3097, 4.3097, 4.3097, 4.3097] +24-11-19 18:57:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:57:07 | D | sum error = [ 278.4124, 294.1821, 309.7555, 325.6339, 343.1860] +24-11-19 18:57:07 | D | best error = [ 4.3097, 4.3097, 4.3097, 4.3097, 4.3097] +24-11-19 18:57:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:57:07 | D | sum error = [ 359.4120, 378.5070, 396.6076, 417.5146, 436.9898] +24-11-19 18:57:07 | D | best error = [ 4.3097, 4.3097, 4.3097, 4.3097, 4.3097] +24-11-19 18:57:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:57:07 | D | sum error = [ 459.6550, 482.3930, 506.3701, 531.1458, 557.6028] +24-11-19 18:57:07 | D | best error = [ 4.3097, 4.3097, 4.3097, 4.3097, 4.3097] +24-11-19 18:57:07 | D | + error = [4.3097] +24-11-19 18:57:07 | D | - Calibrating model.layers.14.self_attn.v_proj.weight +24-11-19 18:57:07 | D | + w: sint8 +24-11-19 18:57:07 | D | + x: None +24-11-19 18:57:07 | D | + y: None +24-11-19 18:57:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:57:07 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:57:07 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:57:07 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:57:07 | D | - range ratio = [ 1.0000] +24-11-19 18:57:07 | D | sum error = [ 1.4941] +24-11-19 18:57:07 | D | best error = [ 1.4941] +24-11-19 18:57:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:57:07 | D | sum error = [ 1.4891, 1.4769, 1.4870, 1.5100, 1.5456] +24-11-19 18:57:07 | D | best error = [ 1.3700, 1.3223, 1.3004, 1.2852, 1.2788] +24-11-19 18:57:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:57:07 | D | sum error = [ 1.5669, 1.6263, 1.6987, 1.7781, 1.8660] +24-11-19 18:57:07 | D | best error = [ 1.2745, 1.2732, 1.2725, 1.2724, 1.2723] +24-11-19 18:57:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:57:07 | D | sum error = [ 1.9870, 2.1071, 2.2512, 2.3752, 2.5735] +24-11-19 18:57:07 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 18:57:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:57:07 | D | sum error = [ 2.7605, 2.9326, 3.1611, 3.4007, 3.6390] +24-11-19 18:57:07 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 18:57:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:57:07 | D | sum error = [ 3.9003, 4.1942, 4.4886, 4.8095, 5.1388] +24-11-19 18:57:07 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 18:57:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:57:07 | D | sum error = [ 5.4926, 5.8660, 6.2688, 6.6845, 7.1314] +24-11-19 18:57:07 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 18:57:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:57:07 | D | sum error = [ 7.6036, 8.0843, 8.6039, 9.1469, 9.7343] +24-11-19 18:57:07 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 18:57:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:57:07 | D | sum error = [ 10.3429, 10.9812, 11.6503, 12.3594, 13.1074] +24-11-19 18:57:07 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 18:57:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:57:07 | D | sum error = [ 13.8899, 14.7083, 15.5774, 16.4893, 17.4256] +24-11-19 18:57:07 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 18:57:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:57:07 | D | sum error = [ 18.4274, 19.4652, 20.5695, 21.7078, 22.9092] +24-11-19 18:57:07 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 18:57:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:57:07 | D | sum error = [ 24.1582, 25.4724, 26.8391, 28.2720, 29.7670] +24-11-19 18:57:07 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 18:57:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:57:07 | D | sum error = [ 31.3248, 32.9410, 34.6349, 36.3934, 38.2184] +24-11-19 18:57:07 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 18:57:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:57:07 | D | sum error = [ 40.1051, 42.0847, 44.1340, 46.2823, 48.5119] +24-11-19 18:57:07 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 18:57:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:57:07 | D | sum error = [ 50.8349, 53.2300, 55.7143, 58.2847, 60.9373] +24-11-19 18:57:07 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 18:57:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:57:07 | D | sum error = [ 63.6856, 66.5352, 69.4735, 72.5206, 75.6744] +24-11-19 18:57:07 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 18:57:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:57:07 | D | sum error = [ 78.9118, 82.2571, 85.6905, 89.2238, 92.8594] +24-11-19 18:57:07 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 18:57:07 | D | + error = [1.2723] +24-11-19 18:57:07 | D | - Calibrating model.layers.14.self_attn.o_proj.weight +24-11-19 18:57:07 | D | + w: sint8 +24-11-19 18:57:07 | D | + x: None +24-11-19 18:57:07 | D | + y: None +24-11-19 18:57:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:57:07 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:57:07 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:57:07 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:57:07 | D | - range ratio = [ 1.0000] +24-11-19 18:57:07 | D | sum error = [ 0.6814] +24-11-19 18:57:07 | D | best error = [ 0.6814] +24-11-19 18:57:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:57:08 | D | sum error = [ 0.6728, 0.6722, 0.6699, 0.6736, 0.6789] +24-11-19 18:57:08 | D | best error = [ 0.6234, 0.5987, 0.5839, 0.5745, 0.5675] +24-11-19 18:57:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:57:08 | D | sum error = [ 0.6881, 0.7001, 0.7138, 0.7333, 0.7589] +24-11-19 18:57:08 | D | best error = [ 0.5632, 0.5599, 0.5578, 0.5566, 0.5558] +24-11-19 18:57:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:57:08 | D | sum error = [ 0.7888, 0.8182, 0.8608, 0.9040, 0.9496] +24-11-19 18:57:08 | D | best error = [ 0.5554, 0.5551, 0.5549, 0.5548, 0.5547] +24-11-19 18:57:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:57:08 | D | sum error = [ 0.9995, 1.0547, 1.1155, 1.1833, 1.2500] +24-11-19 18:57:08 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 18:57:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:57:08 | D | sum error = [ 1.3238, 1.4026, 1.4869, 1.5779, 1.6707] +24-11-19 18:57:08 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 18:57:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:57:08 | D | sum error = [ 1.7684, 1.8766, 1.9895, 2.1054, 2.2274] +24-11-19 18:57:08 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 18:57:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:57:08 | D | sum error = [ 2.3598, 2.4979, 2.6418, 2.7925, 2.9504] +24-11-19 18:57:08 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 18:57:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:57:08 | D | sum error = [ 3.1172, 3.2940, 3.4803, 3.6715, 3.8763] +24-11-19 18:57:08 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 18:57:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:57:08 | D | sum error = [ 4.0929, 4.3130, 4.5477, 4.7930, 5.0462] +24-11-19 18:57:08 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 18:57:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:57:08 | D | sum error = [ 5.3170, 5.5951, 5.8887, 6.1932, 6.5098] +24-11-19 18:57:08 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 18:57:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:57:08 | D | sum error = [ 6.8453, 7.1880, 7.5484, 7.9237, 8.3166] +24-11-19 18:57:08 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 18:57:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:57:08 | D | sum error = [ 8.7221, 9.1495, 9.5915, 10.0528, 10.5314] +24-11-19 18:57:08 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 18:57:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:57:08 | D | sum error = [ 11.0303, 11.5513, 12.0894, 12.6497, 13.2304] +24-11-19 18:57:08 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 18:57:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:57:08 | D | sum error = [ 13.8371, 14.4638, 15.1173, 15.7928, 16.4945] +24-11-19 18:57:08 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 18:57:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:57:08 | D | sum error = [ 17.2231, 17.9786, 18.7628, 19.5729, 20.4108] +24-11-19 18:57:08 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 18:57:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:57:08 | D | sum error = [ 21.2807, 22.1796, 23.1107, 24.0747, 25.0728] +24-11-19 18:57:08 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 18:57:08 | D | + error = [0.5546] +24-11-19 18:57:08 | D | - Calibrating model.layers.14.mlp.up_proj.weight +24-11-19 18:57:08 | D | + w: sint8 +24-11-19 18:57:08 | D | + x: None +24-11-19 18:57:08 | D | + y: None +24-11-19 18:57:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:57:08 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:57:08 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:57:08 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:57:08 | D | - range ratio = [ 1.0000] +24-11-19 18:57:08 | D | sum error = [ 5.4713] +24-11-19 18:57:08 | D | best error = [ 5.4713] +24-11-19 18:57:09 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:57:09 | D | sum error = [ 5.4285, 5.4062, 5.4441, 5.5010, 5.6021] +24-11-19 18:57:09 | D | best error = [ 5.0522, 4.8931, 4.8126, 4.7669, 4.7418] +24-11-19 18:57:09 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:57:09 | D | sum error = [ 5.7422, 5.9334, 6.1673, 6.4544, 6.7961] +24-11-19 18:57:09 | D | best error = [ 4.7298, 4.7247, 4.7227, 4.7220, 4.7218] +24-11-19 18:57:09 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:57:09 | D | sum error = [ 7.2130, 7.6293, 8.1356, 8.6843, 9.2915] +24-11-19 18:57:09 | D | best error = [ 4.7218, 4.7218, 4.7218, 4.7218, 4.7218] +24-11-19 18:57:09 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:57:09 | D | sum error = [ 9.9632, 10.6479, 11.4122, 12.2493, 13.1185] +24-11-19 18:57:09 | D | best error = [ 4.7218, 4.7218, 4.7218, 4.7218, 4.7218] +24-11-19 18:57:09 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:57:09 | D | sum error = [ 14.0544, 15.0452, 16.1229, 17.2528, 18.4524] +24-11-19 18:57:09 | D | best error = [ 4.7218, 4.7218, 4.7218, 4.7218, 4.7218] +24-11-19 18:57:09 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:57:09 | D | sum error = [ 19.7204, 21.0743, 22.5068, 24.0191, 25.6118] +24-11-19 18:57:09 | D | best error = [ 4.7218, 4.7218, 4.7218, 4.7218, 4.7218] +24-11-19 18:57:09 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:57:09 | D | sum error = [ 27.3111, 29.0917, 30.9650, 32.9490, 35.0385] +24-11-19 18:57:09 | D | best error = [ 4.7218, 4.7218, 4.7218, 4.7218, 4.7218] +24-11-19 18:57:09 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:57:09 | D | sum error = [ 37.2332, 39.5531, 41.9857, 44.5405, 47.2272] +24-11-19 18:57:09 | D | best error = [ 4.7218, 4.7218, 4.7218, 4.7218, 4.7218] +24-11-19 18:57:09 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:57:09 | D | sum error = [ 50.0476, 53.0074, 56.1213, 59.3901, 62.8002] +24-11-19 18:57:09 | D | best error = [ 4.7218, 4.7218, 4.7218, 4.7218, 4.7218] +24-11-19 18:57:09 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:57:09 | D | sum error = [ 66.3882, 70.1549, 74.0946, 78.2198, 82.5280] +24-11-19 18:57:09 | D | best error = [ 4.7218, 4.7218, 4.7218, 4.7218, 4.7218] +24-11-19 18:57:09 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:57:09 | D | sum error = [ 87.0291, 91.7348, 96.6582, 101.8011, 107.1620] +24-11-19 18:57:09 | D | best error = [ 4.7218, 4.7218, 4.7218, 4.7218, 4.7218] +24-11-19 18:57:09 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:57:09 | D | sum error = [ 112.7459, 118.5820, 124.6627, 130.9889, 137.5846] +24-11-19 18:57:09 | D | best error = [ 4.7218, 4.7218, 4.7218, 4.7218, 4.7218] +24-11-19 18:57:09 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:57:09 | D | sum error = [ 144.4481, 151.5826, 158.9912, 166.6976, 174.6853] +24-11-19 18:57:09 | D | best error = [ 4.7218, 4.7218, 4.7218, 4.7218, 4.7218] +24-11-19 18:57:09 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:57:09 | D | sum error = [ 182.9792, 191.5774, 200.4672, 209.6801, 219.2082] +24-11-19 18:57:09 | D | best error = [ 4.7218, 4.7218, 4.7218, 4.7218, 4.7218] +24-11-19 18:57:09 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:57:09 | D | sum error = [ 229.0636, 239.2478, 249.7688, 260.6150, 271.8069] +24-11-19 18:57:09 | D | best error = [ 4.7218, 4.7218, 4.7218, 4.7218, 4.7218] +24-11-19 18:57:09 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:57:09 | D | sum error = [ 283.3690, 295.2684, 307.5415, 320.1644, 333.1533] +24-11-19 18:57:09 | D | best error = [ 4.7218, 4.7218, 4.7218, 4.7218, 4.7218] +24-11-19 18:57:09 | D | + error = [4.7218] +24-11-19 18:57:09 | D | - Calibrating model.layers.14.mlp.gate_proj.weight +24-11-19 18:57:09 | D | + w: sint8 +24-11-19 18:57:09 | D | + x: None +24-11-19 18:57:09 | D | + y: None +24-11-19 18:57:09 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:57:09 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:57:09 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:57:10 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:57:10 | D | - range ratio = [ 1.0000] +24-11-19 18:57:10 | D | sum error = [ 6.6986] +24-11-19 18:57:10 | D | best error = [ 6.6986] +24-11-19 18:57:11 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:57:11 | D | sum error = [ 6.6451, 6.6273, 6.6653, 6.7275, 6.8619] +24-11-19 18:57:11 | D | best error = [ 6.1865, 5.9963, 5.9018, 5.8453, 5.8149] +24-11-19 18:57:11 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:57:11 | D | sum error = [ 7.0479, 7.2757, 7.5619, 7.9342, 8.3582] +24-11-19 18:57:11 | D | best error = [ 5.8009, 5.7954, 5.7934, 5.7929, 5.7927] +24-11-19 18:57:11 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:57:11 | D | sum error = [ 8.8600, 9.4086, 10.0453, 10.7452, 11.4982] +24-11-19 18:57:11 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 18:57:11 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:57:11 | D | sum error = [ 12.3330, 13.2528, 14.2241, 15.2831, 16.4133] +24-11-19 18:57:11 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 18:57:11 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:57:11 | D | sum error = [ 17.6522, 18.9548, 20.3690, 21.8567, 23.4709] +24-11-19 18:57:11 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 18:57:11 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:57:11 | D | sum error = [ 25.1933, 27.0393, 28.9803, 31.0708, 33.3149] +24-11-19 18:57:11 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 18:57:11 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:57:11 | D | sum error = [ 35.6803, 38.1954, 40.8965, 43.7552, 46.8113] +24-11-19 18:57:11 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 18:57:11 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:57:11 | D | sum error = [ 50.0831, 53.5213, 57.2137, 61.1109, 65.3054] +24-11-19 18:57:11 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 18:57:11 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:57:11 | D | sum error = [ 69.7510, 74.4774, 79.4973, 84.8455, 90.5535] +24-11-19 18:57:11 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 18:57:11 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:57:11 | D | sum error = [ 96.5861, 103.0196, 109.8244, 117.0297, 124.7098] +24-11-19 18:57:11 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 18:57:11 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:57:11 | D | sum error = [ 132.8430, 141.4376, 150.5262, 160.1743, 170.3527] +24-11-19 18:57:11 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 18:57:11 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:57:11 | D | sum error = [ 181.1364, 192.5211, 204.5370, 217.1867, 230.5170] +24-11-19 18:57:11 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 18:57:11 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:57:11 | D | sum error = [ 244.5671, 259.3032, 274.7835, 291.0174, 308.0535] +24-11-19 18:57:11 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 18:57:11 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:57:11 | D | sum error = [ 325.9059, 344.5712, 364.0845, 384.4814, 405.7402] +24-11-19 18:57:11 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 18:57:11 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:57:11 | D | sum error = [ 427.9148, 451.0096, 475.0147, 499.9380, 525.8021] +24-11-19 18:57:11 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 18:57:11 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:57:11 | D | sum error = [ 552.6129, 580.3601, 609.0459, 638.6742, 669.2205] +24-11-19 18:57:11 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 18:57:11 | D | + error = [5.7927] +24-11-19 18:57:11 | D | - Calibrating model.layers.14.mlp.down_proj.weight +24-11-19 18:57:11 | D | + w: sint8 +24-11-19 18:57:11 | D | + x: None +24-11-19 18:57:11 | D | + y: None +24-11-19 18:57:11 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:57:11 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:57:11 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:57:11 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:57:11 | D | - range ratio = [ 1.0000] +24-11-19 18:57:11 | D | sum error = [ 0.7967] +24-11-19 18:57:11 | D | best error = [ 0.7967] +24-11-19 18:57:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:57:12 | D | sum error = [ 0.7888, 0.7836, 0.7789, 0.7753, 0.7746] +24-11-19 18:57:12 | D | best error = [ 0.7628, 0.7467, 0.7364, 0.7289, 0.7230] +24-11-19 18:57:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:57:12 | D | sum error = [ 0.7773, 0.7802, 0.7861, 0.7968, 0.8095] +24-11-19 18:57:12 | D | best error = [ 0.7185, 0.7150, 0.7123, 0.7103, 0.7089] +24-11-19 18:57:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:57:12 | D | sum error = [ 0.8278, 0.8489, 0.8761, 0.9062, 0.9401] +24-11-19 18:57:12 | D | best error = [ 0.7076, 0.7070, 0.7063, 0.7060, 0.7055] +24-11-19 18:57:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:57:12 | D | sum error = [ 0.9830, 1.0299, 1.0806, 1.1377, 1.2048] +24-11-19 18:57:12 | D | best error = [ 0.7053, 0.7052, 0.7050, 0.7049, 0.7049] +24-11-19 18:57:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:57:12 | D | sum error = [ 1.2745, 1.3528, 1.4373, 1.5264, 1.6271] +24-11-19 18:57:12 | D | best error = [ 0.7048, 0.7048, 0.7047, 0.7047, 0.7047] +24-11-19 18:57:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:57:12 | D | sum error = [ 1.7338, 1.8484, 1.9716, 2.1024, 2.2433] +24-11-19 18:57:12 | D | best error = [ 0.7047, 0.7046, 0.7046, 0.7046, 0.7046] +24-11-19 18:57:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:57:12 | D | sum error = [ 2.3945, 2.5550, 2.7242, 2.9064, 3.1010] +24-11-19 18:57:12 | D | best error = [ 0.7046, 0.7046, 0.7046, 0.7046, 0.7046] +24-11-19 18:57:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:57:12 | D | sum error = [ 3.3055, 3.5246, 3.7551, 3.9997, 4.2570] +24-11-19 18:57:12 | D | best error = [ 0.7046, 0.7046, 0.7046, 0.7046, 0.7046] +24-11-19 18:57:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:57:12 | D | sum error = [ 4.5311, 4.8196, 5.1265, 5.4495, 5.7911] +24-11-19 18:57:12 | D | best error = [ 0.7046, 0.7046, 0.7046, 0.7046, 0.7046] +24-11-19 18:57:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:57:12 | D | sum error = [ 6.1519, 6.5303, 6.9297, 7.3517, 7.7943] +24-11-19 18:57:12 | D | best error = [ 0.7046, 0.7046, 0.7046, 0.7046, 0.7046] +24-11-19 18:57:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:57:12 | D | sum error = [ 8.2606, 8.7511, 9.2663, 9.8065, 10.3742] +24-11-19 18:57:12 | D | best error = [ 0.7046, 0.7046, 0.7046, 0.7046, 0.7046] +24-11-19 18:57:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:57:12 | D | sum error = [ 10.9703, 11.5949, 12.2506, 12.9365, 13.6556] +24-11-19 18:57:12 | D | best error = [ 0.7046, 0.7046, 0.7046, 0.7046, 0.7046] +24-11-19 18:57:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:57:12 | D | sum error = [ 14.4068, 15.1929, 16.0137, 16.8723, 17.7684] +24-11-19 18:57:12 | D | best error = [ 0.7046, 0.7046, 0.7046, 0.7046, 0.7046] +24-11-19 18:57:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:57:12 | D | sum error = [ 18.7034, 19.6780, 20.6936, 21.7530, 22.8540] +24-11-19 18:57:12 | D | best error = [ 0.7046, 0.7046, 0.7046, 0.7046, 0.7046] +24-11-19 18:57:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:57:12 | D | sum error = [ 24.0008, 25.1903, 26.4257, 27.7090, 29.0399] +24-11-19 18:57:12 | D | best error = [ 0.7046, 0.7046, 0.7046, 0.7046, 0.7046] +24-11-19 18:57:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:57:12 | D | sum error = [ 30.4197, 31.8483, 33.3289, 34.8586, 36.4413] +24-11-19 18:57:12 | D | best error = [ 0.7046, 0.7046, 0.7046, 0.7046, 0.7046] +24-11-19 18:57:12 | D | + error = [0.7046] +24-11-19 18:57:12 | D | - Quantizing model.layers.14.self_attn.q_proj.weight +24-11-19 18:57:13 | D | - Quantizing model.layers.14.self_attn.k_proj.weight +24-11-19 18:57:14 | D | - Quantizing model.layers.14.self_attn.v_proj.weight +24-11-19 18:57:15 | D | - Quantizing model.layers.14.self_attn.o_proj.weight +24-11-19 18:57:16 | D | - Quantizing model.layers.14.mlp.up_proj.weight +24-11-19 18:57:16 | D | - Quantizing model.layers.14.mlp.gate_proj.weight +24-11-19 18:57:17 | D | - Quantizing model.layers.14.mlp.down_proj.weight +24-11-19 18:57:27 | D | - Quantizing layer model.layers.15 +24-11-19 18:57:27 | D | - Calibrating model.layers.15.self_attn.q_proj.weight +24-11-19 18:57:27 | D | + w: sint8 +24-11-19 18:57:27 | D | + x: None +24-11-19 18:57:27 | D | + y: None +24-11-19 18:57:27 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:57:27 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:57:27 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:57:27 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:57:27 | D | - range ratio = [ 1.0000] +24-11-19 18:57:27 | D | sum error = [ 4.3708] +24-11-19 18:57:27 | D | best error = [ 4.3708] +24-11-19 18:57:39 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:57:39 | D | sum error = [ 4.4225, 4.3483, 4.3680, 4.4767, 4.4974] +24-11-19 18:57:39 | D | best error = [ 4.3708, 4.3483, 4.3483, 4.3483, 4.3483] +24-11-19 18:57:39 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:57:39 | D | sum error = [ 4.6904, 4.7661, 4.9037, 5.2502, 5.4583] +24-11-19 18:57:39 | D | best error = [ 4.3483, 4.3483, 4.3483, 4.3483, 4.3483] +24-11-19 18:57:39 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:57:39 | D | sum error = [ 5.8780, 6.2633, 6.6465, 7.1043, 7.7263] +24-11-19 18:57:39 | D | best error = [ 4.3483, 4.3483, 4.3483, 4.3483, 4.3483] +24-11-19 18:57:39 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:57:39 | D | sum error = [ 8.3536, 9.0489, 9.5913, 10.4912, 11.3346] +24-11-19 18:57:39 | D | best error = [ 4.3483, 4.3483, 4.3483, 4.3483, 4.3483] +24-11-19 18:57:39 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:57:39 | D | sum error = [ 12.3104, 13.2148, 14.3036, 15.5829, 16.6964] +24-11-19 18:57:39 | D | best error = [ 4.3483, 4.3483, 4.3483, 4.3483, 4.3483] +24-11-19 18:57:39 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:57:39 | D | sum error = [ 18.1923, 19.5570, 21.0876, 22.6303, 24.3175] +24-11-19 18:57:39 | D | best error = [ 4.3483, 4.3483, 4.3483, 4.3483, 4.3483] +24-11-19 18:57:39 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:57:39 | D | sum error = [ 26.2656, 28.0552, 30.0934, 32.3286, 34.7710] +24-11-19 18:57:39 | D | best error = [ 4.3483, 4.3483, 4.3483, 4.3483, 4.3483] +24-11-19 18:57:39 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:57:39 | D | sum error = [ 37.3372, 40.1615, 42.9734, 46.1454, 49.6435] +24-11-19 18:57:39 | D | best error = [ 4.3483, 4.3483, 4.3483, 4.3483, 4.3483] +24-11-19 18:57:39 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:57:39 | D | sum error = [ 53.0885, 56.8955, 61.1469, 65.6117, 70.2104] +24-11-19 18:57:39 | D | best error = [ 4.3483, 4.3483, 4.3483, 4.3483, 4.3483] +24-11-19 18:57:39 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:57:39 | D | sum error = [ 75.3505, 80.7608, 86.7128, 92.8191, 99.6723] +24-11-19 18:57:39 | D | best error = [ 4.3483, 4.3483, 4.3483, 4.3483, 4.3483] +24-11-19 18:57:39 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:57:39 | D | sum error = [ 106.6695, 114.4875, 122.8895, 131.8308, 141.2274] +24-11-19 18:57:39 | D | best error = [ 4.3483, 4.3483, 4.3483, 4.3483, 4.3483] +24-11-19 18:57:39 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:57:39 | D | sum error = [ 151.0988, 161.8370, 173.2012, 185.5563, 198.4071] +24-11-19 18:57:39 | D | best error = [ 4.3483, 4.3483, 4.3483, 4.3483, 4.3483] +24-11-19 18:57:39 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:57:39 | D | sum error = [ 212.4031, 227.2605, 242.8052, 259.6748, 277.5665] +24-11-19 18:57:39 | D | best error = [ 4.3483, 4.3483, 4.3483, 4.3483, 4.3483] +24-11-19 18:57:39 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:57:39 | D | sum error = [ 296.1670, 315.7913, 336.8027, 358.8034, 382.0797] +24-11-19 18:57:39 | D | best error = [ 4.3483, 4.3483, 4.3483, 4.3483, 4.3483] +24-11-19 18:57:39 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:57:39 | D | sum error = [ 406.6405, 432.2816, 459.2033, 487.3542, 516.9366] +24-11-19 18:57:39 | D | best error = [ 4.3483, 4.3483, 4.3483, 4.3483, 4.3483] +24-11-19 18:57:39 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:57:39 | D | sum error = [ 547.5473, 579.3272, 611.9257, 645.7134, 680.0518] +24-11-19 18:57:39 | D | best error = [ 4.3483, 4.3483, 4.3483, 4.3483, 4.3483] +24-11-19 18:57:39 | D | + error = [4.3483] +24-11-19 18:57:39 | D | - Calibrating model.layers.15.self_attn.k_proj.weight +24-11-19 18:57:39 | D | + w: sint8 +24-11-19 18:57:39 | D | + x: None +24-11-19 18:57:39 | D | + y: None +24-11-19 18:57:39 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:57:39 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:57:39 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:57:39 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:57:39 | D | - range ratio = [ 1.0000] +24-11-19 18:57:39 | D | sum error = [ 4.0264] +24-11-19 18:57:39 | D | best error = [ 4.0264] +24-11-19 18:57:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:57:51 | D | sum error = [ 4.4213, 4.6134, 4.0913, 3.9434, 4.4064] +24-11-19 18:57:51 | D | best error = [ 4.0264, 4.0264, 4.0264, 3.9434, 3.9434] +24-11-19 18:57:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:57:51 | D | sum error = [ 4.4557, 4.3555, 4.5012, 5.1624, 5.3392] +24-11-19 18:57:51 | D | best error = [ 3.9434, 3.9434, 3.9434, 3.9434, 3.9434] +24-11-19 18:57:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:57:51 | D | sum error = [ 5.7869, 5.6253, 6.1759, 6.5939, 7.1391] +24-11-19 18:57:51 | D | best error = [ 3.9434, 3.9434, 3.9434, 3.9434, 3.9434] +24-11-19 18:57:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:57:51 | D | sum error = [ 8.0505, 8.1697, 9.0435, 10.0214, 10.0295] +24-11-19 18:57:51 | D | best error = [ 3.9434, 3.9434, 3.9434, 3.9434, 3.9434] +24-11-19 18:57:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:57:51 | D | sum error = [ 11.1370, 11.8626, 12.2092, 13.9603, 14.5343] +24-11-19 18:57:51 | D | best error = [ 3.9434, 3.9434, 3.9434, 3.9434, 3.9434] +24-11-19 18:57:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:57:51 | D | sum error = [ 15.6594, 16.4695, 17.1380, 18.4499, 20.0672] +24-11-19 18:57:51 | D | best error = [ 3.9434, 3.9434, 3.9434, 3.9434, 3.9434] +24-11-19 18:57:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:57:51 | D | sum error = [ 20.7420, 22.3223, 23.9739, 25.7944, 27.6716] +24-11-19 18:57:51 | D | best error = [ 3.9434, 3.9434, 3.9434, 3.9434, 3.9434] +24-11-19 18:57:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:57:51 | D | sum error = [ 29.5655, 32.0443, 34.2596, 36.8307, 39.5395] +24-11-19 18:57:51 | D | best error = [ 3.9434, 3.9434, 3.9434, 3.9434, 3.9434] +24-11-19 18:57:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:57:51 | D | sum error = [ 42.6839, 46.0824, 49.9230, 53.7425, 57.9146] +24-11-19 18:57:51 | D | best error = [ 3.9434, 3.9434, 3.9434, 3.9434, 3.9434] +24-11-19 18:57:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:57:51 | D | sum error = [ 62.4463, 67.2895, 72.9587, 78.8350, 85.3743] +24-11-19 18:57:51 | D | best error = [ 3.9434, 3.9434, 3.9434, 3.9434, 3.9434] +24-11-19 18:57:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:57:51 | D | sum error = [ 92.0656, 99.3623, 107.3182, 115.1234, 123.9823] +24-11-19 18:57:51 | D | best error = [ 3.9434, 3.9434, 3.9434, 3.9434, 3.9434] +24-11-19 18:57:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:57:51 | D | sum error = [ 132.7364, 143.3510, 153.0563, 164.5840, 175.9669] +24-11-19 18:57:51 | D | best error = [ 3.9434, 3.9434, 3.9434, 3.9434, 3.9434] +24-11-19 18:57:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:57:51 | D | sum error = [ 188.3558, 202.9371, 216.8424, 232.2284, 248.5010] +24-11-19 18:57:51 | D | best error = [ 3.9434, 3.9434, 3.9434, 3.9434, 3.9434] +24-11-19 18:57:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:57:51 | D | sum error = [ 265.9432, 285.8595, 304.4213, 326.3799, 348.8571] +24-11-19 18:57:51 | D | best error = [ 3.9434, 3.9434, 3.9434, 3.9434, 3.9434] +24-11-19 18:57:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:57:51 | D | sum error = [ 373.6686, 400.8443, 426.6206, 456.4986, 485.5914] +24-11-19 18:57:51 | D | best error = [ 3.9434, 3.9434, 3.9434, 3.9434, 3.9434] +24-11-19 18:57:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:57:51 | D | sum error = [ 520.2289, 553.3418, 590.2113, 626.2444, 663.2963] +24-11-19 18:57:51 | D | best error = [ 3.9434, 3.9434, 3.9434, 3.9434, 3.9434] +24-11-19 18:57:51 | D | + error = [3.9434] +24-11-19 18:57:51 | D | - Calibrating model.layers.15.self_attn.v_proj.weight +24-11-19 18:57:51 | D | + w: sint8 +24-11-19 18:57:51 | D | + x: None +24-11-19 18:57:51 | D | + y: None +24-11-19 18:57:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:57:51 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:57:51 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:57:51 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:57:51 | D | - range ratio = [ 1.0000] +24-11-19 18:57:51 | D | sum error = [ 1.6270] +24-11-19 18:57:51 | D | best error = [ 1.6270] +24-11-19 18:57:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:57:51 | D | sum error = [ 1.6117, 1.6157, 1.6031, 1.6550, 1.6608] +24-11-19 18:57:51 | D | best error = [ 1.4883, 1.4404, 1.4182, 1.4064, 1.3979] +24-11-19 18:57:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:57:51 | D | sum error = [ 1.7147, 1.7674, 1.8275, 1.9185, 2.0203] +24-11-19 18:57:51 | D | best error = [ 1.3947, 1.3927, 1.3925, 1.3922, 1.3922] +24-11-19 18:57:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:57:51 | D | sum error = [ 2.1383, 2.2737, 2.4184, 2.5748, 2.7640] +24-11-19 18:57:51 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 18:57:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:57:51 | D | sum error = [ 2.9467, 3.1334, 3.3821, 3.6242, 3.8718] +24-11-19 18:57:51 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 18:57:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:57:51 | D | sum error = [ 4.1295, 4.4245, 4.7319, 5.0639, 5.4102] +24-11-19 18:57:51 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 18:57:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:57:51 | D | sum error = [ 5.7769, 6.1667, 6.5721, 7.0212, 7.4689] +24-11-19 18:57:51 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 18:57:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:57:51 | D | sum error = [ 7.9480, 8.4473, 8.9870, 9.5614, 10.1468] +24-11-19 18:57:51 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 18:57:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:57:51 | D | sum error = [ 10.7618, 11.4239, 12.1077, 12.8198, 13.5861] +24-11-19 18:57:51 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 18:57:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:57:51 | D | sum error = [ 14.3774, 15.2067, 16.0878, 16.9971, 17.9612] +24-11-19 18:57:51 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 18:57:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:57:51 | D | sum error = [ 18.9555, 20.0103, 21.1109, 22.2542, 23.4667] +24-11-19 18:57:51 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 18:57:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:57:51 | D | sum error = [ 24.7296, 26.0378, 27.4132, 28.8243, 30.3043] +24-11-19 18:57:51 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 18:57:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:57:51 | D | sum error = [ 31.8422, 33.4486, 35.1209, 36.8534, 38.6460] +24-11-19 18:57:51 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 18:57:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:57:51 | D | sum error = [ 40.5168, 42.4489, 44.4637, 46.5266, 48.6572] +24-11-19 18:57:51 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 18:57:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:57:51 | D | sum error = [ 50.8755, 53.1591, 55.5144, 57.9431, 60.4429] +24-11-19 18:57:51 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 18:57:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:57:51 | D | sum error = [ 63.0288, 65.6856, 68.4208, 71.2315, 74.1319] +24-11-19 18:57:51 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 18:57:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:57:51 | D | sum error = [ 77.1190, 80.1985, 83.3722, 86.6235, 89.9684] +24-11-19 18:57:51 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 18:57:51 | D | + error = [1.3922] +24-11-19 18:57:51 | D | - Calibrating model.layers.15.self_attn.o_proj.weight +24-11-19 18:57:51 | D | + w: sint8 +24-11-19 18:57:51 | D | + x: None +24-11-19 18:57:51 | D | + y: None +24-11-19 18:57:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:57:51 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:57:51 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:57:52 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:57:52 | D | - range ratio = [ 1.0000] +24-11-19 18:57:52 | D | sum error = [ 0.6806] +24-11-19 18:57:52 | D | best error = [ 0.6806] +24-11-19 18:57:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:57:52 | D | sum error = [ 0.6759, 0.6693, 0.6703, 0.6746, 0.6771] +24-11-19 18:57:52 | D | best error = [ 0.6259, 0.6001, 0.5850, 0.5755, 0.5683] +24-11-19 18:57:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:57:52 | D | sum error = [ 0.6902, 0.6962, 0.7136, 0.7314, 0.7520] +24-11-19 18:57:52 | D | best error = [ 0.5632, 0.5589, 0.5557, 0.5533, 0.5516] +24-11-19 18:57:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:57:52 | D | sum error = [ 0.7802, 0.8061, 0.8438, 0.8830, 0.9297] +24-11-19 18:57:52 | D | best error = [ 0.5498, 0.5486, 0.5476, 0.5467, 0.5460] +24-11-19 18:57:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:57:52 | D | sum error = [ 0.9743, 1.0238, 1.0824, 1.1405, 1.2041] +24-11-19 18:57:52 | D | best error = [ 0.5453, 0.5449, 0.5446, 0.5443, 0.5441] +24-11-19 18:57:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:57:52 | D | sum error = [ 1.2729, 1.3532, 1.4273, 1.5110, 1.5986] +24-11-19 18:57:52 | D | best error = [ 0.5439, 0.5437, 0.5436, 0.5436, 0.5435] +24-11-19 18:57:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:57:52 | D | sum error = [ 1.6909, 1.7875, 1.8895, 1.9986, 2.1131] +24-11-19 18:57:52 | D | best error = [ 0.5434, 0.5434, 0.5433, 0.5433, 0.5432] +24-11-19 18:57:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:57:52 | D | sum error = [ 2.2339, 2.3583, 2.4899, 2.6302, 2.7733] +24-11-19 18:57:52 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 18:57:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:57:52 | D | sum error = [ 2.9256, 3.0846, 3.2514, 3.4292, 3.6125] +24-11-19 18:57:52 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 18:57:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:57:52 | D | sum error = [ 3.8035, 4.0034, 4.2156, 4.4354, 4.6666] +24-11-19 18:57:52 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 18:57:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:57:52 | D | sum error = [ 4.9062, 5.1536, 5.4141, 5.6853, 5.9666] +24-11-19 18:57:52 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 18:57:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:57:52 | D | sum error = [ 6.2588, 6.5654, 6.8825, 7.2131, 7.5559] +24-11-19 18:57:52 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 18:57:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:57:52 | D | sum error = [ 7.9123, 8.2843, 8.6685, 9.0670, 9.4823] +24-11-19 18:57:52 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 18:57:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:57:52 | D | sum error = [ 9.9118, 10.3585, 10.8228, 11.3052, 11.8046] +24-11-19 18:57:52 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 18:57:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:57:52 | D | sum error = [ 12.3233, 12.8636, 13.4248, 14.0060, 14.6092] +24-11-19 18:57:52 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 18:57:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:57:52 | D | sum error = [ 15.2355, 15.8848, 16.5573, 17.2545, 17.9784] +24-11-19 18:57:52 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 18:57:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:57:52 | D | sum error = [ 18.7282, 19.5079, 20.3209, 21.1669, 22.0479] +24-11-19 18:57:52 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 18:57:52 | D | + error = [0.5432] +24-11-19 18:57:52 | D | - Calibrating model.layers.15.mlp.up_proj.weight +24-11-19 18:57:52 | D | + w: sint8 +24-11-19 18:57:52 | D | + x: None +24-11-19 18:57:52 | D | + y: None +24-11-19 18:57:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:57:52 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:57:52 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:57:52 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:57:52 | D | - range ratio = [ 1.0000] +24-11-19 18:57:52 | D | sum error = [ 5.6795] +24-11-19 18:57:52 | D | best error = [ 5.6795] +24-11-19 18:57:53 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:57:53 | D | sum error = [ 5.6420, 5.6327, 5.6514, 5.7001, 5.8242] +24-11-19 18:57:53 | D | best error = [ 5.2615, 5.1044, 5.0214, 4.9749, 4.9506] +24-11-19 18:57:53 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:57:53 | D | sum error = [ 5.9815, 6.1770, 6.4276, 6.7260, 7.0821] +24-11-19 18:57:53 | D | best error = [ 4.9389, 4.9338, 4.9321, 4.9313, 4.9311] +24-11-19 18:57:53 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:57:53 | D | sum error = [ 7.4985, 7.9564, 8.4572, 9.0274, 9.6645] +24-11-19 18:57:53 | D | best error = [ 4.9311, 4.9311, 4.9311, 4.9311, 4.9311] +24-11-19 18:57:53 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:57:53 | D | sum error = [ 10.3479, 11.0877, 11.8821, 12.7242, 13.6446] +24-11-19 18:57:53 | D | best error = [ 4.9311, 4.9311, 4.9311, 4.9311, 4.9311] +24-11-19 18:57:53 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:57:53 | D | sum error = [ 14.6131, 15.6529, 16.7528, 17.9255, 19.1710] +24-11-19 18:57:53 | D | best error = [ 4.9311, 4.9311, 4.9311, 4.9311, 4.9311] +24-11-19 18:57:53 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:57:53 | D | sum error = [ 20.4746, 21.8763, 23.3466, 24.9341, 26.5649] +24-11-19 18:57:53 | D | best error = [ 4.9311, 4.9311, 4.9311, 4.9311, 4.9311] +24-11-19 18:57:53 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:57:53 | D | sum error = [ 28.3121, 30.1530, 32.0846, 34.1314, 36.2846] +24-11-19 18:57:53 | D | best error = [ 4.9311, 4.9311, 4.9311, 4.9311, 4.9311] +24-11-19 18:57:53 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:57:53 | D | sum error = [ 38.5422, 40.9324, 43.4414, 46.0674, 48.8435] +24-11-19 18:57:53 | D | best error = [ 4.9311, 4.9311, 4.9311, 4.9311, 4.9311] +24-11-19 18:57:53 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:57:53 | D | sum error = [ 51.7538, 54.8031, 58.0003, 61.3771, 64.8931] +24-11-19 18:57:53 | D | best error = [ 4.9311, 4.9311, 4.9311, 4.9311, 4.9311] +24-11-19 18:57:53 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:57:53 | D | sum error = [ 68.5859, 72.4614, 76.5100, 80.7602, 85.2009] +24-11-19 18:57:53 | D | best error = [ 4.9311, 4.9311, 4.9311, 4.9311, 4.9311] +24-11-19 18:57:53 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:57:53 | D | sum error = [ 89.8357, 94.6837, 99.7464, 105.0362, 110.5355] +24-11-19 18:57:53 | D | best error = [ 4.9311, 4.9311, 4.9311, 4.9311, 4.9311] +24-11-19 18:57:53 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:57:53 | D | sum error = [ 116.2793, 122.2546, 128.4774, 134.9594, 141.6935] +24-11-19 18:57:53 | D | best error = [ 4.9311, 4.9311, 4.9311, 4.9311, 4.9311] +24-11-19 18:57:53 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:57:53 | D | sum error = [ 148.6994, 155.9755, 163.5391, 171.3897, 179.5342] +24-11-19 18:57:53 | D | best error = [ 4.9311, 4.9311, 4.9311, 4.9311, 4.9311] +24-11-19 18:57:53 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:57:53 | D | sum error = [ 187.9853, 196.7374, 205.8032, 215.1802, 224.8935] +24-11-19 18:57:53 | D | best error = [ 4.9311, 4.9311, 4.9311, 4.9311, 4.9311] +24-11-19 18:57:53 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:57:53 | D | sum error = [ 234.9410, 245.3144, 256.0429, 267.1292, 278.5645] +24-11-19 18:57:53 | D | best error = [ 4.9311, 4.9311, 4.9311, 4.9311, 4.9311] +24-11-19 18:57:53 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:57:53 | D | sum error = [ 290.3537, 302.5085, 315.0439, 327.9395, 341.2186] +24-11-19 18:57:53 | D | best error = [ 4.9311, 4.9311, 4.9311, 4.9311, 4.9311] +24-11-19 18:57:53 | D | + error = [4.9311] +24-11-19 18:57:54 | D | - Calibrating model.layers.15.mlp.gate_proj.weight +24-11-19 18:57:54 | D | + w: sint8 +24-11-19 18:57:54 | D | + x: None +24-11-19 18:57:54 | D | + y: None +24-11-19 18:57:54 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:57:54 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:57:54 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:57:54 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:57:54 | D | - range ratio = [ 1.0000] +24-11-19 18:57:54 | D | sum error = [ 7.1843] +24-11-19 18:57:54 | D | best error = [ 7.1843] +24-11-19 18:57:55 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:57:55 | D | sum error = [ 7.1496, 7.1244, 7.1603, 7.2401, 7.3490] +24-11-19 18:57:55 | D | best error = [ 6.6701, 6.4708, 6.3636, 6.3019, 6.2714] +24-11-19 18:57:55 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:57:55 | D | sum error = [ 7.5750, 7.8293, 8.1451, 8.5285, 8.9878] +24-11-19 18:57:55 | D | best error = [ 6.2561, 6.2493, 6.2467, 6.2458, 6.2456] +24-11-19 18:57:55 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:57:55 | D | sum error = [ 9.5117, 10.1129, 10.7901, 11.5533, 12.3676] +24-11-19 18:57:55 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 18:57:55 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:57:55 | D | sum error = [ 13.2789, 14.2455, 15.3036, 16.4568, 17.6659] +24-11-19 18:57:55 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 18:57:55 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:57:55 | D | sum error = [ 19.0045, 20.4020, 21.9024, 23.5480, 25.2954] +24-11-19 18:57:55 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 18:57:55 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:57:55 | D | sum error = [ 27.1375, 29.1173, 31.2306, 33.4960, 35.8765] +24-11-19 18:57:55 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 18:57:55 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:57:55 | D | sum error = [ 38.4357, 41.1518, 44.0489, 47.1414, 50.4286] +24-11-19 18:57:55 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 18:57:55 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:57:55 | D | sum error = [ 53.9734, 57.6985, 61.6758, 65.8972, 70.4032] +24-11-19 18:57:55 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 18:57:55 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:57:55 | D | sum error = [ 75.1970, 80.2868, 85.7062, 91.4983, 97.6332] +24-11-19 18:57:55 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 18:57:55 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:57:55 | D | sum error = [ 104.1997, 111.1449, 118.5271, 126.3840, 134.6781] +24-11-19 18:57:55 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 18:57:55 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:57:55 | D | sum error = [ 143.4933, 152.8101, 162.6891, 173.1642, 184.2230] +24-11-19 18:57:55 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 18:57:55 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:57:55 | D | sum error = [ 195.9147, 208.3205, 221.3933, 235.1808, 249.6866] +24-11-19 18:57:55 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 18:57:55 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:57:55 | D | sum error = [ 265.0069, 281.0931, 298.0266, 315.7816, 334.4523] +24-11-19 18:57:55 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 18:57:55 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:57:55 | D | sum error = [ 354.0119, 374.4739, 395.8723, 418.2430, 441.5471] +24-11-19 18:57:55 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 18:57:55 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:57:55 | D | sum error = [ 465.8538, 491.1500, 517.4462, 544.7416, 573.0559] +24-11-19 18:57:55 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 18:57:55 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:57:55 | D | sum error = [ 602.3892, 632.7451, 664.1395, 696.5270, 729.9136] +24-11-19 18:57:55 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 18:57:55 | D | + error = [6.2456] +24-11-19 18:57:55 | D | - Calibrating model.layers.15.mlp.down_proj.weight +24-11-19 18:57:55 | D | + w: sint8 +24-11-19 18:57:55 | D | + x: None +24-11-19 18:57:55 | D | + y: None +24-11-19 18:57:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:57:55 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:57:55 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:57:55 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:57:55 | D | - range ratio = [ 1.0000] +24-11-19 18:57:55 | D | sum error = [ 0.8764] +24-11-19 18:57:55 | D | best error = [ 0.8764] +24-11-19 18:57:56 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:57:56 | D | sum error = [ 0.8669, 0.8618, 0.8584, 0.8541, 0.8515] +24-11-19 18:57:56 | D | best error = [ 0.8409, 0.8240, 0.8125, 0.8034, 0.7968] +24-11-19 18:57:56 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:57:56 | D | sum error = [ 0.8562, 0.8597, 0.8678, 0.8780, 0.8916] +24-11-19 18:57:56 | D | best error = [ 0.7917, 0.7879, 0.7853, 0.7835, 0.7817] +24-11-19 18:57:56 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:57:56 | D | sum error = [ 0.9122, 0.9356, 0.9651, 0.9993, 1.0381] +24-11-19 18:57:56 | D | best error = [ 0.7807, 0.7799, 0.7795, 0.7791, 0.7788] +24-11-19 18:57:56 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:57:56 | D | sum error = [ 1.0854, 1.1377, 1.1940, 1.2615, 1.3334] +24-11-19 18:57:56 | D | best error = [ 0.7787, 0.7787, 0.7786, 0.7785, 0.7785] +24-11-19 18:57:56 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:57:56 | D | sum error = [ 1.4112, 1.4983, 1.5953, 1.6979, 1.8089] +24-11-19 18:57:56 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 18:57:56 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:57:56 | D | sum error = [ 1.9289, 2.0588, 2.1980, 2.3471, 2.5059] +24-11-19 18:57:56 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 18:57:56 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:57:56 | D | sum error = [ 2.6767, 2.8583, 3.0519, 3.2575, 3.4737] +24-11-19 18:57:56 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 18:57:56 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:57:56 | D | sum error = [ 3.7082, 3.9551, 4.2175, 4.4949, 4.7877] +24-11-19 18:57:56 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 18:57:56 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:57:56 | D | sum error = [ 5.0991, 5.4285, 5.7776, 6.1455, 6.5350] +24-11-19 18:57:56 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 18:57:56 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:57:56 | D | sum error = [ 6.9446, 7.3760, 7.8329, 8.3136, 8.8178] +24-11-19 18:57:56 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 18:57:56 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:57:56 | D | sum error = [ 9.3493, 9.9089, 10.4959, 11.1139, 11.7620] +24-11-19 18:57:56 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 18:57:56 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:57:56 | D | sum error = [ 12.4420, 13.1554, 13.9029, 14.6868, 15.5067] +24-11-19 18:57:56 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 18:57:56 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:57:56 | D | sum error = [ 16.3642, 17.2605, 18.1964, 19.1739, 20.1933] +24-11-19 18:57:56 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 18:57:56 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:57:56 | D | sum error = [ 21.2577, 22.3671, 23.5228, 24.7257, 25.9748] +24-11-19 18:57:56 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 18:57:56 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:57:56 | D | sum error = [ 27.2746, 28.6263, 30.0280, 31.4823, 32.9913] +24-11-19 18:57:56 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 18:57:56 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:57:56 | D | sum error = [ 34.5555, 36.1762, 37.8516, 39.5845, 41.3758] +24-11-19 18:57:56 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 18:57:56 | D | + error = [0.7784] +24-11-19 18:57:57 | D | - Quantizing model.layers.15.self_attn.q_proj.weight +24-11-19 18:57:57 | D | - Quantizing model.layers.15.self_attn.k_proj.weight +24-11-19 18:57:58 | D | - Quantizing model.layers.15.self_attn.v_proj.weight +24-11-19 18:57:59 | D | - Quantizing model.layers.15.self_attn.o_proj.weight +24-11-19 18:58:00 | D | - Quantizing model.layers.15.mlp.up_proj.weight +24-11-19 18:58:00 | D | - Quantizing model.layers.15.mlp.gate_proj.weight +24-11-19 18:58:01 | D | - Quantizing model.layers.15.mlp.down_proj.weight +24-11-19 18:58:11 | D | - Quantizing layer model.layers.16 +24-11-19 18:58:11 | D | - Calibrating model.layers.16.self_attn.q_proj.weight +24-11-19 18:58:11 | D | + w: sint8 +24-11-19 18:58:11 | D | + x: None +24-11-19 18:58:11 | D | + y: None +24-11-19 18:58:11 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:58:11 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:58:11 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:58:11 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:58:11 | D | - range ratio = [ 1.0000] +24-11-19 18:58:11 | D | sum error = [ 4.4705] +24-11-19 18:58:11 | D | best error = [ 4.4705] +24-11-19 18:58:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:58:23 | D | sum error = [ 4.3564, 4.3693, 4.4899, 4.5321, 4.5161] +24-11-19 18:58:23 | D | best error = [ 4.3564, 4.3564, 4.3564, 4.3564, 4.3564] +24-11-19 18:58:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:58:23 | D | sum error = [ 4.7753, 4.9324, 5.0324, 5.3495, 5.6852] +24-11-19 18:58:23 | D | best error = [ 4.3564, 4.3564, 4.3564, 4.3564, 4.3564] +24-11-19 18:58:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:58:23 | D | sum error = [ 5.9609, 6.5192, 7.0185, 7.5814, 8.2049] +24-11-19 18:58:23 | D | best error = [ 4.3564, 4.3564, 4.3564, 4.3564, 4.3564] +24-11-19 18:58:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:58:23 | D | sum error = [ 9.1758, 9.7593, 10.6242, 11.6976, 12.5592] +24-11-19 18:58:23 | D | best error = [ 4.3564, 4.3564, 4.3564, 4.3564, 4.3564] +24-11-19 18:58:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:58:23 | D | sum error = [ 13.6101, 15.0898, 16.4919, 17.9442, 19.4634] +24-11-19 18:58:23 | D | best error = [ 4.3564, 4.3564, 4.3564, 4.3564, 4.3564] +24-11-19 18:58:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:58:23 | D | sum error = [ 21.1384, 23.2207, 25.0593, 27.4561, 30.1101] +24-11-19 18:58:23 | D | best error = [ 4.3564, 4.3564, 4.3564, 4.3564, 4.3564] +24-11-19 18:58:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:58:23 | D | sum error = [ 32.5186, 35.4585, 38.5199, 42.0236, 45.7762] +24-11-19 18:58:23 | D | best error = [ 4.3564, 4.3564, 4.3564, 4.3564, 4.3564] +24-11-19 18:58:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:58:23 | D | sum error = [ 49.6198, 53.7043, 58.0448, 62.5824, 67.6834] +24-11-19 18:58:23 | D | best error = [ 4.3564, 4.3564, 4.3564, 4.3564, 4.3564] +24-11-19 18:58:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:58:23 | D | sum error = [ 72.8611, 78.4729, 83.9428, 90.3075, 97.1400] +24-11-19 18:58:23 | D | best error = [ 4.3564, 4.3564, 4.3564, 4.3564, 4.3564] +24-11-19 18:58:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:58:23 | D | sum error = [ 104.1354, 111.6316, 119.4094, 128.0702, 137.1962] +24-11-19 18:58:23 | D | best error = [ 4.3564, 4.3564, 4.3564, 4.3564, 4.3564] +24-11-19 18:58:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:58:23 | D | sum error = [ 146.8974, 157.1093, 168.1694, 179.7681, 192.1595] +24-11-19 18:58:23 | D | best error = [ 4.3564, 4.3564, 4.3564, 4.3564, 4.3564] +24-11-19 18:58:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:58:23 | D | sum error = [ 205.4733, 219.3108, 233.8042, 249.4001, 265.4476] +24-11-19 18:58:23 | D | best error = [ 4.3564, 4.3564, 4.3564, 4.3564, 4.3564] +24-11-19 18:58:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:58:23 | D | sum error = [ 282.7885, 301.1469, 320.2860, 340.8680, 362.1580] +24-11-19 18:58:23 | D | best error = [ 4.3564, 4.3564, 4.3564, 4.3564, 4.3564] +24-11-19 18:58:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:58:23 | D | sum error = [ 384.7322, 408.1881, 433.0290, 459.4698, 486.7848] +24-11-19 18:58:23 | D | best error = [ 4.3564, 4.3564, 4.3564, 4.3564, 4.3564] +24-11-19 18:58:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:58:23 | D | sum error = [ 515.4070, 545.2183, 575.9198, 608.2490, 641.5259] +24-11-19 18:58:23 | D | best error = [ 4.3564, 4.3564, 4.3564, 4.3564, 4.3564] +24-11-19 18:58:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:58:23 | D | sum error = [ 675.6906, 710.6442, 746.6006, 783.0666, 820.1154] +24-11-19 18:58:23 | D | best error = [ 4.3564, 4.3564, 4.3564, 4.3564, 4.3564] +24-11-19 18:58:23 | D | + error = [4.3564] +24-11-19 18:58:23 | D | - Calibrating model.layers.16.self_attn.k_proj.weight +24-11-19 18:58:23 | D | + w: sint8 +24-11-19 18:58:23 | D | + x: None +24-11-19 18:58:23 | D | + y: None +24-11-19 18:58:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:58:23 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:58:23 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:58:24 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:58:24 | D | - range ratio = [ 1.0000] +24-11-19 18:58:24 | D | sum error = [ 4.0634] +24-11-19 18:58:24 | D | best error = [ 4.0634] +24-11-19 18:58:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:58:35 | D | sum error = [ 4.3795, 4.2465, 4.3459, 4.1041, 3.9818] +24-11-19 18:58:35 | D | best error = [ 4.0634, 4.0634, 4.0634, 4.0634, 3.9818] +24-11-19 18:58:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:58:35 | D | sum error = [ 4.5656, 4.6488, 4.3839, 4.5494, 5.7436] +24-11-19 18:58:35 | D | best error = [ 3.9818, 3.9818, 3.9818, 3.9818, 3.9818] +24-11-19 18:58:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:58:35 | D | sum error = [ 5.2761, 5.8331, 5.7623, 6.2936, 6.7324] +24-11-19 18:58:35 | D | best error = [ 3.9818, 3.9818, 3.9818, 3.9818, 3.9818] +24-11-19 18:58:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:58:35 | D | sum error = [ 7.1504, 7.7966, 8.0762, 8.8141, 9.4171] +24-11-19 18:58:35 | D | best error = [ 3.9818, 3.9818, 3.9818, 3.9818, 3.9818] +24-11-19 18:58:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:58:35 | D | sum error = [ 9.9461, 10.6830, 12.0595, 12.5927, 13.3490] +24-11-19 18:58:35 | D | best error = [ 3.9818, 3.9818, 3.9818, 3.9818, 3.9818] +24-11-19 18:58:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:58:35 | D | sum error = [ 14.6601, 15.4735, 17.2817, 18.6320, 20.4053] +24-11-19 18:58:35 | D | best error = [ 3.9818, 3.9818, 3.9818, 3.9818, 3.9818] +24-11-19 18:58:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:58:35 | D | sum error = [ 21.8671, 23.8259, 25.1349, 27.0977, 29.6511] +24-11-19 18:58:35 | D | best error = [ 3.9818, 3.9818, 3.9818, 3.9818, 3.9818] +24-11-19 18:58:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:58:35 | D | sum error = [ 31.6061, 34.5975, 36.6618, 39.7854, 42.7332] +24-11-19 18:58:35 | D | best error = [ 3.9818, 3.9818, 3.9818, 3.9818, 3.9818] +24-11-19 18:58:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:58:35 | D | sum error = [ 45.4031, 48.6512, 51.3134, 55.4041, 59.5732] +24-11-19 18:58:35 | D | best error = [ 3.9818, 3.9818, 3.9818, 3.9818, 3.9818] +24-11-19 18:58:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:58:35 | D | sum error = [ 63.9344, 69.1045, 74.6457, 81.3124, 87.8004] +24-11-19 18:58:35 | D | best error = [ 3.9818, 3.9818, 3.9818, 3.9818, 3.9818] +24-11-19 18:58:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:58:35 | D | sum error = [ 95.7580, 103.7011, 113.2111, 122.2259, 134.6000] +24-11-19 18:58:35 | D | best error = [ 3.9818, 3.9818, 3.9818, 3.9818, 3.9818] +24-11-19 18:58:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:58:35 | D | sum error = [ 146.2769, 158.4629, 172.7739, 187.2288, 203.6425] +24-11-19 18:58:35 | D | best error = [ 3.9818, 3.9818, 3.9818, 3.9818, 3.9818] +24-11-19 18:58:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:58:35 | D | sum error = [ 218.3637, 236.5539, 254.9636, 275.8859, 295.4862] +24-11-19 18:58:35 | D | best error = [ 3.9818, 3.9818, 3.9818, 3.9818, 3.9818] +24-11-19 18:58:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:58:35 | D | sum error = [ 319.3258, 342.3507, 370.6074, 394.7310, 424.0677] +24-11-19 18:58:35 | D | best error = [ 3.9818, 3.9818, 3.9818, 3.9818, 3.9818] +24-11-19 18:58:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:58:35 | D | sum error = [ 452.3215, 487.8081, 518.8578, 553.0028, 587.0677] +24-11-19 18:58:35 | D | best error = [ 3.9818, 3.9818, 3.9818, 3.9818, 3.9818] +24-11-19 18:58:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:58:35 | D | sum error = [ 624.9061, 664.8777, 704.6253, 743.9764, 784.1887] +24-11-19 18:58:35 | D | best error = [ 3.9818, 3.9818, 3.9818, 3.9818, 3.9818] +24-11-19 18:58:35 | D | + error = [3.9818] +24-11-19 18:58:36 | D | - Calibrating model.layers.16.self_attn.v_proj.weight +24-11-19 18:58:36 | D | + w: sint8 +24-11-19 18:58:36 | D | + x: None +24-11-19 18:58:36 | D | + y: None +24-11-19 18:58:36 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:58:36 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:58:36 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:58:36 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:58:36 | D | - range ratio = [ 1.0000] +24-11-19 18:58:36 | D | sum error = [ 1.4683] +24-11-19 18:58:36 | D | best error = [ 1.4683] +24-11-19 18:58:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:58:36 | D | sum error = [ 1.4494, 1.4512, 1.4634, 1.4704, 1.4986] +24-11-19 18:58:36 | D | best error = [ 1.3528, 1.3116, 1.2902, 1.2772, 1.2715] +24-11-19 18:58:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:58:36 | D | sum error = [ 1.5349, 1.5795, 1.6524, 1.7302, 1.8124] +24-11-19 18:58:36 | D | best error = [ 1.2680, 1.2667, 1.2663, 1.2662, 1.2662] +24-11-19 18:58:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:58:36 | D | sum error = [ 1.9113, 2.0449, 2.1737, 2.3227, 2.4733] +24-11-19 18:58:36 | D | best error = [ 1.2662, 1.2662, 1.2662, 1.2662, 1.2662] +24-11-19 18:58:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:58:36 | D | sum error = [ 2.6628, 2.8524, 3.0447, 3.2737, 3.5263] +24-11-19 18:58:36 | D | best error = [ 1.2662, 1.2662, 1.2662, 1.2662, 1.2662] +24-11-19 18:58:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:58:36 | D | sum error = [ 3.7740, 4.0546, 4.3472, 4.6352, 4.9616] +24-11-19 18:58:36 | D | best error = [ 1.2662, 1.2662, 1.2662, 1.2662, 1.2662] +24-11-19 18:58:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:58:36 | D | sum error = [ 5.3260, 5.6922, 6.0860, 6.4864, 6.9204] +24-11-19 18:58:36 | D | best error = [ 1.2662, 1.2662, 1.2662, 1.2662, 1.2662] +24-11-19 18:58:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:58:36 | D | sum error = [ 7.3764, 7.8677, 8.3754, 8.9042, 9.4809] +24-11-19 18:58:36 | D | best error = [ 1.2662, 1.2662, 1.2662, 1.2662, 1.2662] +24-11-19 18:58:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:58:36 | D | sum error = [ 10.0832, 10.7144, 11.3798, 12.0821, 12.8088] +24-11-19 18:58:36 | D | best error = [ 1.2662, 1.2662, 1.2662, 1.2662, 1.2662] +24-11-19 18:58:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:58:36 | D | sum error = [ 13.5889, 14.4032, 15.2501, 16.1474, 17.0876] +24-11-19 18:58:36 | D | best error = [ 1.2662, 1.2662, 1.2662, 1.2662, 1.2662] +24-11-19 18:58:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:58:36 | D | sum error = [ 18.0691, 19.1064, 20.1732, 21.3052, 22.4920] +24-11-19 18:58:36 | D | best error = [ 1.2662, 1.2662, 1.2662, 1.2662, 1.2662] +24-11-19 18:58:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:58:36 | D | sum error = [ 23.7133, 24.9920, 26.3368, 27.7390, 29.1911] +24-11-19 18:58:36 | D | best error = [ 1.2662, 1.2662, 1.2662, 1.2662, 1.2662] +24-11-19 18:58:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:58:36 | D | sum error = [ 30.7102, 32.2967, 33.9404, 35.6499, 37.4312] +24-11-19 18:58:36 | D | best error = [ 1.2662, 1.2662, 1.2662, 1.2662, 1.2662] +24-11-19 18:58:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:58:36 | D | sum error = [ 39.2880, 41.2214, 43.2282, 45.3211, 47.4846] +24-11-19 18:58:36 | D | best error = [ 1.2662, 1.2662, 1.2662, 1.2662, 1.2662] +24-11-19 18:58:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:58:36 | D | sum error = [ 49.7327, 52.0636, 54.4682, 56.9737, 59.5748] +24-11-19 18:58:36 | D | best error = [ 1.2662, 1.2662, 1.2662, 1.2662, 1.2662] +24-11-19 18:58:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:58:36 | D | sum error = [ 62.2570, 65.0299, 67.8949, 70.8477, 73.8975] +24-11-19 18:58:36 | D | best error = [ 1.2662, 1.2662, 1.2662, 1.2662, 1.2662] +24-11-19 18:58:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:58:36 | D | sum error = [ 77.0443, 80.2900, 83.6487, 87.1052, 90.6604] +24-11-19 18:58:36 | D | best error = [ 1.2662, 1.2662, 1.2662, 1.2662, 1.2662] +24-11-19 18:58:36 | D | + error = [1.2662] +24-11-19 18:58:36 | D | - Calibrating model.layers.16.self_attn.o_proj.weight +24-11-19 18:58:36 | D | + w: sint8 +24-11-19 18:58:36 | D | + x: None +24-11-19 18:58:36 | D | + y: None +24-11-19 18:58:36 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:58:36 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:58:36 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:58:36 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:58:36 | D | - range ratio = [ 1.0000] +24-11-19 18:58:36 | D | sum error = [ 0.6276] +24-11-19 18:58:36 | D | best error = [ 0.6276] +24-11-19 18:58:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:58:37 | D | sum error = [ 0.6227, 0.6200, 0.6188, 0.6152, 0.6179] +24-11-19 18:58:37 | D | best error = [ 0.5784, 0.5565, 0.5427, 0.5331, 0.5259] +24-11-19 18:58:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:58:37 | D | sum error = [ 0.6236, 0.6278, 0.6366, 0.6483, 0.6660] +24-11-19 18:58:37 | D | best error = [ 0.5206, 0.5156, 0.5123, 0.5092, 0.5071] +24-11-19 18:58:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:58:37 | D | sum error = [ 0.6838, 0.7058, 0.7314, 0.7625, 0.7972] +24-11-19 18:58:37 | D | best error = [ 0.5050, 0.5035, 0.5023, 0.5010, 0.5002] +24-11-19 18:58:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:58:37 | D | sum error = [ 0.8354, 0.8743, 0.9233, 0.9754, 1.0309] +24-11-19 18:58:37 | D | best error = [ 0.4996, 0.4988, 0.4983, 0.4980, 0.4976] +24-11-19 18:58:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:58:37 | D | sum error = [ 1.0906, 1.1553, 1.2242, 1.3003, 1.3816] +24-11-19 18:58:37 | D | best error = [ 0.4975, 0.4973, 0.4971, 0.4970, 0.4970] +24-11-19 18:58:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:58:37 | D | sum error = [ 1.4690, 1.5600, 1.6580, 1.7618, 1.8732] +24-11-19 18:58:37 | D | best error = [ 0.4970, 0.4969, 0.4968, 0.4968, 0.4968] +24-11-19 18:58:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:58:37 | D | sum error = [ 1.9893, 2.1160, 2.2463, 2.3871, 2.5319] +24-11-19 18:58:37 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 18:58:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:58:37 | D | sum error = [ 2.6883, 2.8543, 3.0266, 3.2088, 3.4013] +24-11-19 18:58:37 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 18:58:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:58:37 | D | sum error = [ 3.6051, 3.8181, 4.0471, 4.2824, 4.5332] +24-11-19 18:58:37 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 18:58:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:58:37 | D | sum error = [ 4.7985, 5.0753, 5.3646, 5.6734, 5.9939] +24-11-19 18:58:37 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 18:58:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:58:37 | D | sum error = [ 6.3282, 6.6781, 7.0469, 7.4304, 7.8318] +24-11-19 18:58:37 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 18:58:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:58:37 | D | sum error = [ 8.2511, 8.6887, 9.1465, 9.6245, 10.1220] +24-11-19 18:58:37 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 18:58:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:58:37 | D | sum error = [ 10.6422, 11.1849, 11.7515, 12.3416, 12.9568] +24-11-19 18:58:37 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 18:58:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:58:37 | D | sum error = [ 13.5989, 14.2674, 14.9612, 15.6854, 16.4335] +24-11-19 18:58:37 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 18:58:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:58:37 | D | sum error = [ 17.2113, 18.0207, 18.8620, 19.7348, 20.6405] +24-11-19 18:58:37 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 18:58:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:58:37 | D | sum error = [ 21.5766, 22.5500, 23.5562, 24.5988, 25.6799] +24-11-19 18:58:37 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 18:58:37 | D | + error = [0.4968] +24-11-19 18:58:37 | D | - Calibrating model.layers.16.mlp.up_proj.weight +24-11-19 18:58:37 | D | + w: sint8 +24-11-19 18:58:37 | D | + x: None +24-11-19 18:58:37 | D | + y: None +24-11-19 18:58:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:58:37 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:58:37 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:58:37 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:58:37 | D | - range ratio = [ 1.0000] +24-11-19 18:58:37 | D | sum error = [ 5.9253] +24-11-19 18:58:37 | D | best error = [ 5.9253] +24-11-19 18:58:38 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:58:38 | D | sum error = [ 5.8708, 5.8619, 5.8930, 5.9624, 6.0603] +24-11-19 18:58:38 | D | best error = [ 5.5094, 5.3477, 5.2630, 5.2148, 5.1900] +24-11-19 18:58:38 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:58:38 | D | sum error = [ 6.2224, 6.4194, 6.6829, 7.0001, 7.3701] +24-11-19 18:58:38 | D | best error = [ 5.1772, 5.1717, 5.1697, 5.1693, 5.1691] +24-11-19 18:58:38 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:58:38 | D | sum error = [ 7.7781, 8.2706, 8.7926, 9.3919, 10.0396] +24-11-19 18:58:38 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 18:58:38 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:58:38 | D | sum error = [ 10.7521, 11.4993, 12.3187, 13.2022, 14.1519] +24-11-19 18:58:38 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 18:58:38 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:58:38 | D | sum error = [ 15.1579, 16.2353, 17.3723, 18.6016, 19.8786] +24-11-19 18:58:38 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 18:58:38 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:58:38 | D | sum error = [ 21.2458, 22.6768, 24.2182, 25.8338, 27.5515] +24-11-19 18:58:38 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 18:58:38 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:58:38 | D | sum error = [ 29.3300, 31.2321, 33.2263, 35.3340, 37.5413] +24-11-19 18:58:38 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 18:58:38 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:58:38 | D | sum error = [ 39.8757, 42.3320, 44.9101, 47.5981, 50.4524] +24-11-19 18:58:38 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 18:58:38 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:58:38 | D | sum error = [ 53.4531, 56.5861, 59.8765, 63.3221, 66.9337] +24-11-19 18:58:38 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 18:58:38 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:58:38 | D | sum error = [ 70.7162, 74.6735, 78.8160, 83.1517, 87.6797] +24-11-19 18:58:38 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 18:58:38 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:58:38 | D | sum error = [ 92.4029, 97.3333, 102.4842, 107.8561, 113.4467] +24-11-19 18:58:38 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 18:58:38 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:58:38 | D | sum error = [ 119.2693, 125.3227, 131.6334, 138.1889, 144.9928] +24-11-19 18:58:38 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 18:58:38 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:58:38 | D | sum error = [ 152.0714, 159.4077, 167.0237, 174.9066, 183.0957] +24-11-19 18:58:38 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 18:58:38 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:58:38 | D | sum error = [ 191.5718, 200.3570, 209.4575, 218.8559, 228.5875] +24-11-19 18:58:38 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 18:58:38 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:58:38 | D | sum error = [ 238.6405, 249.0251, 259.7442, 270.8129, 282.2093] +24-11-19 18:58:38 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 18:58:38 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:58:38 | D | sum error = [ 293.9688, 306.0799, 318.5251, 331.3475, 344.5256] +24-11-19 18:58:38 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 18:58:38 | D | + error = [5.1691] +24-11-19 18:58:38 | D | - Calibrating model.layers.16.mlp.gate_proj.weight +24-11-19 18:58:38 | D | + w: sint8 +24-11-19 18:58:38 | D | + x: None +24-11-19 18:58:38 | D | + y: None +24-11-19 18:58:38 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:58:38 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:58:38 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:58:38 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:58:38 | D | - range ratio = [ 1.0000] +24-11-19 18:58:38 | D | sum error = [ 7.7746] +24-11-19 18:58:38 | D | best error = [ 7.7746] +24-11-19 18:58:40 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:58:40 | D | sum error = [ 7.6986, 7.6781, 7.7142, 7.8137, 7.9644] +24-11-19 18:58:40 | D | best error = [ 7.2199, 7.0129, 6.9003, 6.8396, 6.8057] +24-11-19 18:58:40 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:58:40 | D | sum error = [ 8.1478, 8.4546, 8.7970, 9.2113, 9.7071] +24-11-19 18:58:40 | D | best error = [ 6.7888, 6.7826, 6.7798, 6.7789, 6.7788] +24-11-19 18:58:40 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:58:40 | D | sum error = [ 10.2836, 10.9304, 11.6471, 12.4713, 13.3164] +24-11-19 18:58:40 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 18:58:40 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:58:40 | D | sum error = [ 14.2945, 15.3542, 16.4903, 17.6991, 19.0174] +24-11-19 18:58:40 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 18:58:40 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:58:40 | D | sum error = [ 20.4309, 21.9272, 23.5460, 25.2745, 27.0735] +24-11-19 18:58:40 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 18:58:40 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:58:40 | D | sum error = [ 29.0322, 31.1104, 33.3445, 35.6832, 38.2193] +24-11-19 18:58:40 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 18:58:40 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:58:40 | D | sum error = [ 40.8815, 43.7111, 46.7525, 49.9637, 53.4074] +24-11-19 18:58:40 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 18:58:40 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:58:40 | D | sum error = [ 57.0385, 60.9149, 65.0289, 69.3943, 74.0130] +24-11-19 18:58:40 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 18:58:40 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:58:40 | D | sum error = [ 78.9320, 84.1709, 89.7121, 95.5792, 101.8126] +24-11-19 18:58:40 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 18:58:40 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:58:40 | D | sum error = [ 108.4312, 115.4376, 122.8693, 130.7481, 139.0904] +24-11-19 18:58:40 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 18:58:40 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:58:40 | D | sum error = [ 147.9029, 157.2409, 167.1268, 177.5687, 188.5808] +24-11-19 18:58:40 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 18:58:40 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:58:40 | D | sum error = [ 200.1923, 212.4593, 225.3846, 238.9773, 253.2893] +24-11-19 18:58:40 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 18:58:40 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:58:40 | D | sum error = [ 268.3423, 284.1573, 300.7339, 318.1416, 336.3844] +24-11-19 18:58:40 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 18:58:40 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:58:40 | D | sum error = [ 355.4720, 375.4353, 396.2878, 418.0804, 440.7418] +24-11-19 18:58:40 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 18:58:40 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:58:40 | D | sum error = [ 464.3744, 488.9632, 514.5017, 541.0129, 568.5225] +24-11-19 18:58:40 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 18:58:40 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:58:40 | D | sum error = [ 597.0205, 626.5177, 656.9850, 688.4447, 720.9083] +24-11-19 18:58:40 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 18:58:40 | D | + error = [6.7787] +24-11-19 18:58:40 | D | - Calibrating model.layers.16.mlp.down_proj.weight +24-11-19 18:58:40 | D | + w: sint8 +24-11-19 18:58:40 | D | + x: None +24-11-19 18:58:40 | D | + y: None +24-11-19 18:58:40 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:58:40 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:58:40 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:58:40 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:58:40 | D | - range ratio = [ 1.0000] +24-11-19 18:58:40 | D | sum error = [ 0.8971] +24-11-19 18:58:40 | D | best error = [ 0.8971] +24-11-19 18:58:41 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:58:41 | D | sum error = [ 0.8890, 0.8830, 0.8789, 0.8765, 0.8738] +24-11-19 18:58:41 | D | best error = [ 0.8583, 0.8395, 0.8280, 0.8193, 0.8126] +24-11-19 18:58:41 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:58:41 | D | sum error = [ 0.8759, 0.8810, 0.8906, 0.9009, 0.9184] +24-11-19 18:58:41 | D | best error = [ 0.8075, 0.8033, 0.8002, 0.7978, 0.7959] +24-11-19 18:58:41 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:58:41 | D | sum error = [ 0.9361, 0.9633, 0.9941, 1.0290, 1.0697] +24-11-19 18:58:41 | D | best error = [ 0.7945, 0.7937, 0.7930, 0.7926, 0.7924] +24-11-19 18:58:41 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:58:41 | D | sum error = [ 1.1145, 1.1710, 1.2314, 1.2985, 1.3710] +24-11-19 18:58:41 | D | best error = [ 0.7922, 0.7921, 0.7920, 0.7919, 0.7919] +24-11-19 18:58:41 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:58:41 | D | sum error = [ 1.4532, 1.5433, 1.6404, 1.7469, 1.8601] +24-11-19 18:58:41 | D | best error = [ 0.7919, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 18:58:41 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:58:41 | D | sum error = [ 1.9867, 2.1193, 2.2619, 2.4164, 2.5809] +24-11-19 18:58:41 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 18:58:41 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:58:41 | D | sum error = [ 2.7563, 2.9440, 3.1432, 3.3572, 3.5835] +24-11-19 18:58:41 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 18:58:41 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:58:41 | D | sum error = [ 3.8251, 4.0816, 4.3527, 4.6396, 4.9454] +24-11-19 18:58:41 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 18:58:41 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:58:41 | D | sum error = [ 5.2686, 5.6108, 5.9708, 6.3514, 6.7546] +24-11-19 18:58:41 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 18:58:41 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:58:41 | D | sum error = [ 7.1801, 7.6278, 8.1001, 8.5963, 9.1212] +24-11-19 18:58:41 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 18:58:41 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:58:41 | D | sum error = [ 9.6717, 10.2510, 10.8602, 11.5009, 12.1737] +24-11-19 18:58:41 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 18:58:41 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:58:41 | D | sum error = [ 12.8821, 13.6241, 14.4026, 15.2176, 16.0715] +24-11-19 18:58:41 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 18:58:41 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:58:41 | D | sum error = [ 16.9657, 17.9004, 18.8789, 19.9011, 20.9689] +24-11-19 18:58:41 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 18:58:41 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:58:41 | D | sum error = [ 22.0825, 23.2439, 24.4539, 25.7146, 27.0243] +24-11-19 18:58:41 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 18:58:41 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:58:41 | D | sum error = [ 28.3883, 29.8077, 31.2843, 32.8169, 34.4083] +24-11-19 18:58:41 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 18:58:41 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:58:41 | D | sum error = [ 36.0587, 37.7663, 39.5342, 41.3628, 43.2511] +24-11-19 18:58:41 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 18:58:41 | D | + error = [0.7918] +24-11-19 18:58:41 | D | - Quantizing model.layers.16.self_attn.q_proj.weight +24-11-19 18:58:42 | D | - Quantizing model.layers.16.self_attn.k_proj.weight +24-11-19 18:58:43 | D | - Quantizing model.layers.16.self_attn.v_proj.weight +24-11-19 18:58:43 | D | - Quantizing model.layers.16.self_attn.o_proj.weight +24-11-19 18:58:44 | D | - Quantizing model.layers.16.mlp.up_proj.weight +24-11-19 18:58:45 | D | - Quantizing model.layers.16.mlp.gate_proj.weight +24-11-19 18:58:46 | D | - Quantizing model.layers.16.mlp.down_proj.weight +24-11-19 18:58:55 | D | - Quantizing layer model.layers.17 +24-11-19 18:58:55 | D | - Calibrating model.layers.17.self_attn.q_proj.weight +24-11-19 18:58:55 | D | + w: sint8 +24-11-19 18:58:55 | D | + x: None +24-11-19 18:58:55 | D | + y: None +24-11-19 18:58:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:58:55 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:58:55 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:58:56 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:58:56 | D | - range ratio = [ 1.0000] +24-11-19 18:58:56 | D | sum error = [ 4.1677] +24-11-19 18:58:56 | D | best error = [ 4.1677] +24-11-19 18:59:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:59:07 | D | sum error = [ 4.1763, 4.1251, 4.1589, 4.2163, 4.3692] +24-11-19 18:59:07 | D | best error = [ 4.1677, 4.1251, 4.1251, 4.1251, 4.1251] +24-11-19 18:59:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:59:07 | D | sum error = [ 4.3695, 4.6548, 4.9741, 4.9874, 5.3721] +24-11-19 18:59:07 | D | best error = [ 4.1251, 4.1251, 4.1251, 4.1251, 4.1251] +24-11-19 18:59:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:59:07 | D | sum error = [ 5.5328, 5.9748, 6.5668, 6.9072, 7.5381] +24-11-19 18:59:07 | D | best error = [ 4.1251, 4.1251, 4.1251, 4.1251, 4.1251] +24-11-19 18:59:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:59:07 | D | sum error = [ 8.1465, 8.8595, 9.5552, 10.3668, 11.0868] +24-11-19 18:59:07 | D | best error = [ 4.1251, 4.1251, 4.1251, 4.1251, 4.1251] +24-11-19 18:59:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:59:07 | D | sum error = [ 11.9565, 13.0032, 13.9658, 15.2697, 16.5079] +24-11-19 18:59:07 | D | best error = [ 4.1251, 4.1251, 4.1251, 4.1251, 4.1251] +24-11-19 18:59:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:59:07 | D | sum error = [ 17.9451, 19.3961, 21.0786, 22.6028, 24.6022] +24-11-19 18:59:07 | D | best error = [ 4.1251, 4.1251, 4.1251, 4.1251, 4.1251] +24-11-19 18:59:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:59:07 | D | sum error = [ 26.6550, 28.8305, 31.1724, 33.6542, 36.5436] +24-11-19 18:59:07 | D | best error = [ 4.1251, 4.1251, 4.1251, 4.1251, 4.1251] +24-11-19 18:59:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:59:07 | D | sum error = [ 39.3090, 42.5338, 45.8861, 49.5900, 53.8657] +24-11-19 18:59:07 | D | best error = [ 4.1251, 4.1251, 4.1251, 4.1251, 4.1251] +24-11-19 18:59:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:59:07 | D | sum error = [ 57.9881, 62.4411, 67.5848, 72.7818, 78.4296] +24-11-19 18:59:07 | D | best error = [ 4.1251, 4.1251, 4.1251, 4.1251, 4.1251] +24-11-19 18:59:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:59:07 | D | sum error = [ 84.4996, 90.8274, 97.7102, 105.2591, 113.1752] +24-11-19 18:59:07 | D | best error = [ 4.1251, 4.1251, 4.1251, 4.1251, 4.1251] +24-11-19 18:59:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:59:07 | D | sum error = [ 121.8942, 131.3256, 141.3400, 152.0505, 163.6871] +24-11-19 18:59:07 | D | best error = [ 4.1251, 4.1251, 4.1251, 4.1251, 4.1251] +24-11-19 18:59:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:59:07 | D | sum error = [ 175.8999, 189.0385, 203.0853, 218.2432, 234.5037] +24-11-19 18:59:07 | D | best error = [ 4.1251, 4.1251, 4.1251, 4.1251, 4.1251] +24-11-19 18:59:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:59:07 | D | sum error = [ 251.9025, 270.5117, 290.5048, 311.9330, 334.9509] +24-11-19 18:59:07 | D | best error = [ 4.1251, 4.1251, 4.1251, 4.1251, 4.1251] +24-11-19 18:59:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:59:07 | D | sum error = [ 359.5513, 386.0808, 414.3377, 444.4799, 476.5059] +24-11-19 18:59:08 | D | best error = [ 4.1251, 4.1251, 4.1251, 4.1251, 4.1251] +24-11-19 18:59:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:59:08 | D | sum error = [ 510.0899, 545.1419, 582.1395, 621.0567, 661.6420] +24-11-19 18:59:08 | D | best error = [ 4.1251, 4.1251, 4.1251, 4.1251, 4.1251] +24-11-19 18:59:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:59:08 | D | sum error = [ 703.3908, 746.7286, 791.0804, 836.0423, 881.2569] +24-11-19 18:59:08 | D | best error = [ 4.1251, 4.1251, 4.1251, 4.1251, 4.1251] +24-11-19 18:59:08 | D | + error = [4.1251] +24-11-19 18:59:08 | D | - Calibrating model.layers.17.self_attn.k_proj.weight +24-11-19 18:59:08 | D | + w: sint8 +24-11-19 18:59:08 | D | + x: None +24-11-19 18:59:08 | D | + y: None +24-11-19 18:59:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:59:08 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:59:08 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:59:08 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:59:08 | D | - range ratio = [ 1.0000] +24-11-19 18:59:08 | D | sum error = [ 3.6958] +24-11-19 18:59:08 | D | best error = [ 3.6958] +24-11-19 18:59:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:59:20 | D | sum error = [ 3.5531, 3.8438, 3.8701, 3.9193, 4.3567] +24-11-19 18:59:20 | D | best error = [ 3.5531, 3.5531, 3.5531, 3.5531, 3.5531] +24-11-19 18:59:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:59:20 | D | sum error = [ 3.9356, 4.3269, 4.6774, 4.5418, 4.6746] +24-11-19 18:59:20 | D | best error = [ 3.5531, 3.5531, 3.5531, 3.5531, 3.5531] +24-11-19 18:59:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:59:20 | D | sum error = [ 4.9337, 6.0991, 5.6725, 5.9226, 7.2860] +24-11-19 18:59:20 | D | best error = [ 3.5531, 3.5531, 3.5531, 3.5531, 3.5531] +24-11-19 18:59:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:59:20 | D | sum error = [ 7.1945, 8.0023, 8.3038, 9.1605, 9.5001] +24-11-19 18:59:20 | D | best error = [ 3.5531, 3.5531, 3.5531, 3.5531, 3.5531] +24-11-19 18:59:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:59:20 | D | sum error = [ 10.2673, 11.6845, 11.9811, 13.4146, 14.3044] +24-11-19 18:59:20 | D | best error = [ 3.5531, 3.5531, 3.5531, 3.5531, 3.5531] +24-11-19 18:59:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:59:20 | D | sum error = [ 15.5818, 17.0458, 17.9555, 19.8148, 21.7097] +24-11-19 18:59:20 | D | best error = [ 3.5531, 3.5531, 3.5531, 3.5531, 3.5531] +24-11-19 18:59:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:59:20 | D | sum error = [ 22.7319, 25.0220, 27.2130, 28.9530, 31.1591] +24-11-19 18:59:20 | D | best error = [ 3.5531, 3.5531, 3.5531, 3.5531, 3.5531] +24-11-19 18:59:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:59:20 | D | sum error = [ 33.4563, 36.0615, 38.3112, 41.1069, 44.6737] +24-11-19 18:59:20 | D | best error = [ 3.5531, 3.5531, 3.5531, 3.5531, 3.5531] +24-11-19 18:59:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:59:20 | D | sum error = [ 48.2480, 51.8062, 55.7157, 59.6896, 63.9140] +24-11-19 18:59:20 | D | best error = [ 3.5531, 3.5531, 3.5531, 3.5531, 3.5531] +24-11-19 18:59:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:59:20 | D | sum error = [ 68.9413, 74.2545, 79.2464, 84.2051, 90.2869] +24-11-19 18:59:20 | D | best error = [ 3.5531, 3.5531, 3.5531, 3.5531, 3.5531] +24-11-19 18:59:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:59:20 | D | sum error = [ 96.4855, 103.2323, 111.3281, 119.7501, 129.2662] +24-11-19 18:59:20 | D | best error = [ 3.5531, 3.5531, 3.5531, 3.5531, 3.5531] +24-11-19 18:59:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:59:20 | D | sum error = [ 138.3925, 148.9623, 161.5498, 174.6269, 188.9129] +24-11-19 18:59:20 | D | best error = [ 3.5531, 3.5531, 3.5531, 3.5531, 3.5531] +24-11-19 18:59:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:59:20 | D | sum error = [ 203.6685, 219.9403, 238.8819, 256.7007, 279.7373] +24-11-19 18:59:20 | D | best error = [ 3.5531, 3.5531, 3.5531, 3.5531, 3.5531] +24-11-19 18:59:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:59:20 | D | sum error = [ 303.1298, 326.6591, 354.3517, 380.9401, 411.1489] +24-11-19 18:59:20 | D | best error = [ 3.5531, 3.5531, 3.5531, 3.5531, 3.5531] +24-11-19 18:59:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:59:20 | D | sum error = [ 443.7360, 477.0185, 513.9877, 552.6220, 590.6656] +24-11-19 18:59:20 | D | best error = [ 3.5531, 3.5531, 3.5531, 3.5531, 3.5531] +24-11-19 18:59:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:59:20 | D | sum error = [ 634.6253, 675.3557, 724.0991, 770.6098, 818.6277] +24-11-19 18:59:20 | D | best error = [ 3.5531, 3.5531, 3.5531, 3.5531, 3.5531] +24-11-19 18:59:20 | D | + error = [3.5531] +24-11-19 18:59:20 | D | - Calibrating model.layers.17.self_attn.v_proj.weight +24-11-19 18:59:20 | D | + w: sint8 +24-11-19 18:59:20 | D | + x: None +24-11-19 18:59:20 | D | + y: None +24-11-19 18:59:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:59:20 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:59:20 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:59:20 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:59:20 | D | - range ratio = [ 1.0000] +24-11-19 18:59:20 | D | sum error = [ 1.6667] +24-11-19 18:59:20 | D | best error = [ 1.6667] +24-11-19 18:59:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:59:20 | D | sum error = [ 1.6654, 1.6563, 1.6656, 1.6858, 1.7151] +24-11-19 18:59:20 | D | best error = [ 1.5438, 1.4956, 1.4716, 1.4580, 1.4507] +24-11-19 18:59:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:59:20 | D | sum error = [ 1.7560, 1.8144, 1.8830, 1.9786, 2.0719] +24-11-19 18:59:20 | D | best error = [ 1.4459, 1.4437, 1.4433, 1.4432, 1.4432] +24-11-19 18:59:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:59:20 | D | sum error = [ 2.2085, 2.3453, 2.4996, 2.6597, 2.8358] +24-11-19 18:59:20 | D | best error = [ 1.4432, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 18:59:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:59:20 | D | sum error = [ 3.0481, 3.2493, 3.4911, 3.7507, 4.0037] +24-11-19 18:59:20 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 18:59:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:59:20 | D | sum error = [ 4.2903, 4.5823, 4.9049, 5.2600, 5.6158] +24-11-19 18:59:20 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 18:59:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:59:20 | D | sum error = [ 5.9927, 6.3970, 6.8403, 7.2728, 7.7410] +24-11-19 18:59:20 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 18:59:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:59:20 | D | sum error = [ 8.2470, 8.7804, 9.3371, 9.9353, 10.5505] +24-11-19 18:59:20 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 18:59:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:59:20 | D | sum error = [ 11.2153, 11.8871, 12.6127, 13.3553, 14.1363] +24-11-19 18:59:20 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 18:59:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:59:20 | D | sum error = [ 14.9728, 15.8467, 16.7660, 17.7242, 18.7273] +24-11-19 18:59:20 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 18:59:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:59:20 | D | sum error = [ 19.7846, 20.8916, 22.0462, 23.2527, 24.5139] +24-11-19 18:59:20 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 18:59:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:59:20 | D | sum error = [ 25.8141, 27.1848, 28.5964, 30.0768, 31.6221] +24-11-19 18:59:20 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 18:59:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:59:20 | D | sum error = [ 33.2170, 34.8803, 36.6093, 38.3841, 40.2370] +24-11-19 18:59:20 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 18:59:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:59:20 | D | sum error = [ 42.1580, 44.1558, 46.2217, 48.3619, 50.5675] +24-11-19 18:59:20 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 18:59:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:59:20 | D | sum error = [ 52.8627, 55.2301, 57.6863, 60.2424, 62.8704] +24-11-19 18:59:20 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 18:59:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:59:20 | D | sum error = [ 65.5969, 68.3814, 71.2622, 74.2332, 77.2796] +24-11-19 18:59:20 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 18:59:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:59:20 | D | sum error = [ 80.4268, 83.6591, 86.9893, 90.4007, 93.9029] +24-11-19 18:59:20 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 18:59:20 | D | + error = [1.4431] +24-11-19 18:59:20 | D | - Calibrating model.layers.17.self_attn.o_proj.weight +24-11-19 18:59:20 | D | + w: sint8 +24-11-19 18:59:20 | D | + x: None +24-11-19 18:59:20 | D | + y: None +24-11-19 18:59:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:59:20 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:59:20 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:59:21 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:59:21 | D | - range ratio = [ 1.0000] +24-11-19 18:59:21 | D | sum error = [ 0.6015] +24-11-19 18:59:21 | D | best error = [ 0.6015] +24-11-19 18:59:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:59:21 | D | sum error = [ 0.5980, 0.5916, 0.5862, 0.5857, 0.5807] +24-11-19 18:59:21 | D | best error = [ 0.5533, 0.5312, 0.5166, 0.5056, 0.4978] +24-11-19 18:59:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:59:21 | D | sum error = [ 0.5811, 0.5844, 0.5822, 0.5896, 0.5960] +24-11-19 18:59:21 | D | best error = [ 0.4915, 0.4865, 0.4824, 0.4789, 0.4762] +24-11-19 18:59:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:59:21 | D | sum error = [ 0.6033, 0.6144, 0.6274, 0.6404, 0.6582] +24-11-19 18:59:21 | D | best error = [ 0.4740, 0.4723, 0.4710, 0.4698, 0.4688] +24-11-19 18:59:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:59:21 | D | sum error = [ 0.6765, 0.6999, 0.7225, 0.7510, 0.7822] +24-11-19 18:59:21 | D | best error = [ 0.4678, 0.4670, 0.4663, 0.4658, 0.4654] +24-11-19 18:59:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:59:21 | D | sum error = [ 0.8122, 0.8503, 0.8868, 0.9303, 0.9775] +24-11-19 18:59:21 | D | best error = [ 0.4652, 0.4648, 0.4646, 0.4643, 0.4641] +24-11-19 18:59:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:59:21 | D | sum error = [ 1.0246, 1.0743, 1.1328, 1.1914, 1.2509] +24-11-19 18:59:21 | D | best error = [ 0.4640, 0.4639, 0.4637, 0.4636, 0.4636] +24-11-19 18:59:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:59:21 | D | sum error = [ 1.3212, 1.3886, 1.4616, 1.5411, 1.6243] +24-11-19 18:59:21 | D | best error = [ 0.4635, 0.4635, 0.4635, 0.4634, 0.4634] +24-11-19 18:59:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:59:21 | D | sum error = [ 1.7122, 1.8070, 1.9071, 2.0102, 2.1212] +24-11-19 18:59:21 | D | best error = [ 0.4634, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 18:59:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:59:21 | D | sum error = [ 2.2380, 2.3621, 2.4937, 2.6331, 2.7805] +24-11-19 18:59:21 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 18:59:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:59:21 | D | sum error = [ 2.9381, 3.1037, 3.2777, 3.4625, 3.6597] +24-11-19 18:59:21 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 18:59:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:59:21 | D | sum error = [ 3.8685, 4.0878, 4.3217, 4.5686, 4.8313] +24-11-19 18:59:21 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 18:59:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:59:21 | D | sum error = [ 5.1074, 5.4031, 5.7119, 6.0388, 6.3840] +24-11-19 18:59:21 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 18:59:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:59:21 | D | sum error = [ 6.7482, 7.1345, 7.5413, 7.9702, 8.4228] +24-11-19 18:59:21 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 18:59:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:59:21 | D | sum error = [ 8.8974, 9.3978, 9.9230, 10.4795, 11.0620] +24-11-19 18:59:21 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 18:59:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:59:21 | D | sum error = [ 11.6758, 12.3184, 12.9951, 13.7046, 14.4474] +24-11-19 18:59:21 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 18:59:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:59:21 | D | sum error = [ 15.2263, 16.0402, 16.8895, 17.7779, 18.7065] +24-11-19 18:59:21 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 18:59:21 | D | + error = [0.4633] +24-11-19 18:59:21 | D | - Calibrating model.layers.17.mlp.up_proj.weight +24-11-19 18:59:21 | D | + w: sint8 +24-11-19 18:59:21 | D | + x: None +24-11-19 18:59:21 | D | + y: None +24-11-19 18:59:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:59:21 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:59:21 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:59:21 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:59:21 | D | - range ratio = [ 1.0000] +24-11-19 18:59:21 | D | sum error = [ 6.0977] +24-11-19 18:59:21 | D | best error = [ 6.0977] +24-11-19 18:59:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:59:22 | D | sum error = [ 6.0668, 6.0417, 6.0689, 6.1281, 6.2541] +24-11-19 18:59:22 | D | best error = [ 5.6622, 5.4882, 5.3961, 5.3445, 5.3192] +24-11-19 18:59:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:59:22 | D | sum error = [ 6.3969, 6.6281, 6.8993, 7.2203, 7.5989] +24-11-19 18:59:22 | D | best error = [ 5.3065, 5.3008, 5.2987, 5.2980, 5.2978] +24-11-19 18:59:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:59:22 | D | sum error = [ 8.0353, 8.5257, 9.0861, 9.7059, 10.3663] +24-11-19 18:59:22 | D | best error = [ 5.2978, 5.2978, 5.2978, 5.2978, 5.2978] +24-11-19 18:59:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:59:22 | D | sum error = [ 11.0906, 11.8835, 12.7066, 13.6187, 14.5913] +24-11-19 18:59:22 | D | best error = [ 5.2978, 5.2978, 5.2978, 5.2978, 5.2978] +24-11-19 18:59:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:59:22 | D | sum error = [ 15.6320, 16.7420, 17.9372, 19.1723, 20.5082] +24-11-19 18:59:22 | D | best error = [ 5.2978, 5.2978, 5.2978, 5.2978, 5.2978] +24-11-19 18:59:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:59:22 | D | sum error = [ 21.9067, 23.3930, 24.9702, 26.6360, 28.3784] +24-11-19 18:59:22 | D | best error = [ 5.2978, 5.2978, 5.2978, 5.2978, 5.2978] +24-11-19 18:59:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:59:22 | D | sum error = [ 30.2427, 32.2074, 34.2559, 36.4167, 38.7194] +24-11-19 18:59:22 | D | best error = [ 5.2978, 5.2978, 5.2978, 5.2978, 5.2978] +24-11-19 18:59:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:59:22 | D | sum error = [ 41.1257, 43.6417, 46.3233, 49.1313, 52.0686] +24-11-19 18:59:22 | D | best error = [ 5.2978, 5.2978, 5.2978, 5.2978, 5.2978] +24-11-19 18:59:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:59:22 | D | sum error = [ 55.1759, 58.4011, 61.8026, 65.3776, 69.1105] +24-11-19 18:59:22 | D | best error = [ 5.2978, 5.2978, 5.2978, 5.2978, 5.2978] +24-11-19 18:59:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:59:22 | D | sum error = [ 73.0132, 77.0928, 81.3643, 85.8296, 90.4989] +24-11-19 18:59:22 | D | best error = [ 5.2978, 5.2978, 5.2978, 5.2978, 5.2978] +24-11-19 18:59:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:59:22 | D | sum error = [ 95.3876, 100.4849, 105.8083, 111.3570, 117.1533] +24-11-19 18:59:22 | D | best error = [ 5.2978, 5.2978, 5.2978, 5.2978, 5.2978] +24-11-19 18:59:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:59:22 | D | sum error = [ 123.1836, 129.4657, 136.0115, 142.8227, 149.8898] +24-11-19 18:59:22 | D | best error = [ 5.2978, 5.2978, 5.2978, 5.2978, 5.2978] +24-11-19 18:59:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:59:22 | D | sum error = [ 157.2302, 164.8667, 172.7779, 180.9874, 189.5033] +24-11-19 18:59:22 | D | best error = [ 5.2978, 5.2978, 5.2978, 5.2978, 5.2978] +24-11-19 18:59:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:59:22 | D | sum error = [ 198.3231, 207.4464, 216.8887, 226.6484, 236.7514] +24-11-19 18:59:22 | D | best error = [ 5.2978, 5.2978, 5.2978, 5.2978, 5.2978] +24-11-19 18:59:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:59:22 | D | sum error = [ 247.1858, 257.9706, 269.0973, 280.5802, 292.4143] +24-11-19 18:59:22 | D | best error = [ 5.2978, 5.2978, 5.2978, 5.2978, 5.2978] +24-11-19 18:59:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:59:22 | D | sum error = [ 304.6240, 317.1972, 330.1523, 343.4717, 357.1617] +24-11-19 18:59:22 | D | best error = [ 5.2978, 5.2978, 5.2978, 5.2978, 5.2978] +24-11-19 18:59:22 | D | + error = [5.2978] +24-11-19 18:59:22 | D | - Calibrating model.layers.17.mlp.gate_proj.weight +24-11-19 18:59:22 | D | + w: sint8 +24-11-19 18:59:22 | D | + x: None +24-11-19 18:59:22 | D | + y: None +24-11-19 18:59:22 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:59:22 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:59:23 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:59:23 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:59:23 | D | - range ratio = [ 1.0000] +24-11-19 18:59:23 | D | sum error = [ 8.1034] +24-11-19 18:59:23 | D | best error = [ 8.1034] +24-11-19 18:59:24 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:59:24 | D | sum error = [ 8.0414, 8.0434, 8.0744, 8.1552, 8.3147] +24-11-19 18:59:24 | D | best error = [ 7.5236, 7.3035, 7.1847, 7.1157, 7.0807] +24-11-19 18:59:24 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:59:24 | D | sum error = [ 8.5183, 8.8325, 9.1862, 9.6500, 10.1426] +24-11-19 18:59:24 | D | best error = [ 7.0625, 7.0548, 7.0517, 7.0507, 7.0503] +24-11-19 18:59:24 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:59:24 | D | sum error = [ 10.7629, 11.4112, 12.1669, 13.0055, 13.9312] +24-11-19 18:59:24 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 18:59:24 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:59:24 | D | sum error = [ 14.9106, 16.0050, 17.2014, 18.4815, 19.8113] +24-11-19 18:59:24 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 18:59:24 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:59:24 | D | sum error = [ 21.2876, 22.8190, 24.4993, 26.2931, 28.1671] +24-11-19 18:59:24 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 18:59:24 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:59:24 | D | sum error = [ 30.2011, 32.3551, 34.6345, 37.0816, 39.6794] +24-11-19 18:59:24 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 18:59:24 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:59:24 | D | sum error = [ 42.4143, 45.3529, 48.4812, 51.7916, 55.2986] +24-11-19 18:59:24 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 18:59:24 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:59:24 | D | sum error = [ 59.0569, 62.9986, 67.2526, 71.7088, 76.4469] +24-11-19 18:59:24 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 18:59:24 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:59:24 | D | sum error = [ 81.4745, 86.8458, 92.5186, 98.5228, 104.8836] +24-11-19 18:59:24 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 18:59:24 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:59:24 | D | sum error = [ 111.6583, 118.8265, 126.3904, 134.4066, 142.8904] +24-11-19 18:59:24 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 18:59:24 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:59:24 | D | sum error = [ 151.8769, 161.3702, 171.3998, 181.9979, 193.1677] +24-11-19 18:59:24 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 18:59:24 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:59:24 | D | sum error = [ 204.9812, 217.4541, 230.5700, 244.3772, 258.8788] +24-11-19 18:59:24 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 18:59:24 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:59:24 | D | sum error = [ 274.1372, 290.1681, 306.9588, 324.5922, 343.0618] +24-11-19 18:59:24 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 18:59:24 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:59:24 | D | sum error = [ 362.3365, 382.5153, 403.5864, 425.5652, 448.4634] +24-11-19 18:59:24 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 18:59:24 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:59:24 | D | sum error = [ 472.3348, 497.1540, 522.9651, 549.7292, 577.4924] +24-11-19 18:59:24 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 18:59:24 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:59:24 | D | sum error = [ 606.2655, 636.0329, 666.7866, 698.5310, 731.2575] +24-11-19 18:59:24 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 18:59:24 | D | + error = [7.0503] +24-11-19 18:59:24 | D | - Calibrating model.layers.17.mlp.down_proj.weight +24-11-19 18:59:24 | D | + w: sint8 +24-11-19 18:59:24 | D | + x: None +24-11-19 18:59:24 | D | + y: None +24-11-19 18:59:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 18:59:24 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:59:24 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:59:24 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:59:24 | D | - range ratio = [ 1.0000] +24-11-19 18:59:24 | D | sum error = [ 0.9949] +24-11-19 18:59:24 | D | best error = [ 0.9949] +24-11-19 18:59:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:59:25 | D | sum error = [ 0.9832, 0.9783, 0.9725, 0.9662, 0.9666] +24-11-19 18:59:25 | D | best error = [ 0.9523, 0.9320, 0.9183, 0.9080, 0.9003] +24-11-19 18:59:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:59:25 | D | sum error = [ 0.9665, 0.9705, 0.9799, 0.9882, 1.0059] +24-11-19 18:59:25 | D | best error = [ 0.8938, 0.8891, 0.8853, 0.8821, 0.8800] +24-11-19 18:59:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:59:25 | D | sum error = [ 1.0266, 1.0534, 1.0836, 1.1229, 1.1695] +24-11-19 18:59:25 | D | best error = [ 0.8784, 0.8773, 0.8766, 0.8761, 0.8757] +24-11-19 18:59:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:59:25 | D | sum error = [ 1.2186, 1.2781, 1.3443, 1.4174, 1.4990] +24-11-19 18:59:25 | D | best error = [ 0.8754, 0.8753, 0.8752, 0.8751, 0.8750] +24-11-19 18:59:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:59:25 | D | sum error = [ 1.5919, 1.6893, 1.8002, 1.9181, 2.0455] +24-11-19 18:59:25 | D | best error = [ 0.8750, 0.8750, 0.8750, 0.8749, 0.8749] +24-11-19 18:59:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:59:25 | D | sum error = [ 2.1852, 2.3335, 2.4936, 2.6648, 2.8494] +24-11-19 18:59:25 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 18:59:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:59:25 | D | sum error = [ 3.0460, 3.2541, 3.4794, 3.7215, 3.9739] +24-11-19 18:59:25 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 18:59:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:59:25 | D | sum error = [ 4.2437, 4.5291, 4.8359, 5.1590, 5.5009] +24-11-19 18:59:25 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 18:59:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:59:25 | D | sum error = [ 5.8645, 6.2494, 6.6562, 7.0843, 7.5388] +24-11-19 18:59:25 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 18:59:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:59:25 | D | sum error = [ 8.0188, 8.5255, 9.0590, 9.6208, 10.2106] +24-11-19 18:59:25 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 18:59:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:59:25 | D | sum error = [ 10.8315, 11.4868, 12.1774, 12.8983, 13.6588] +24-11-19 18:59:25 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 18:59:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:59:25 | D | sum error = [ 14.4563, 15.2921, 16.1690, 17.0847, 18.0445] +24-11-19 18:59:25 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 18:59:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:59:25 | D | sum error = [ 19.0475, 20.0963, 21.1899, 22.3323, 23.5266] +24-11-19 18:59:25 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 18:59:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:59:25 | D | sum error = [ 24.7679, 26.0602, 27.4093, 28.8113, 30.2658] +24-11-19 18:59:25 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 18:59:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:59:25 | D | sum error = [ 31.7807, 33.3529, 34.9831, 36.6757, 38.4287] +24-11-19 18:59:25 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 18:59:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:59:25 | D | sum error = [ 40.2425, 42.1204, 44.0595, 46.0645, 48.1343] +24-11-19 18:59:25 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 18:59:25 | D | + error = [0.8749] +24-11-19 18:59:25 | D | - Quantizing model.layers.17.self_attn.q_proj.weight +24-11-19 18:59:26 | D | - Quantizing model.layers.17.self_attn.k_proj.weight +24-11-19 18:59:27 | D | - Quantizing model.layers.17.self_attn.v_proj.weight +24-11-19 18:59:28 | D | - Quantizing model.layers.17.self_attn.o_proj.weight +24-11-19 18:59:29 | D | - Quantizing model.layers.17.mlp.up_proj.weight +24-11-19 18:59:29 | D | - Quantizing model.layers.17.mlp.gate_proj.weight +24-11-19 18:59:30 | D | - Quantizing model.layers.17.mlp.down_proj.weight +24-11-19 18:59:40 | D | - Quantizing layer model.layers.18 +24-11-19 18:59:40 | D | - Calibrating model.layers.18.self_attn.q_proj.weight +24-11-19 18:59:40 | D | + w: sint8 +24-11-19 18:59:40 | D | + x: None +24-11-19 18:59:40 | D | + y: None +24-11-19 18:59:40 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:59:40 | D | + finished parsing calibration arguments, ram usage: 11.6 +24-11-19 18:59:40 | D | + finished reseting calibrator, ram usage: 11.6 +24-11-19 18:59:40 | D | + finished calculating the original outputs, ram usage: 11.6 +24-11-19 18:59:40 | D | - range ratio = [ 1.0000] +24-11-19 18:59:40 | D | sum error = [ 3.9081] +24-11-19 18:59:40 | D | best error = [ 3.9081] +24-11-19 18:59:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 18:59:52 | D | sum error = [ 3.9604, 3.8425, 3.8595, 4.1440, 4.0562] +24-11-19 18:59:52 | D | best error = [ 3.9081, 3.8425, 3.8425, 3.8425, 3.8425] +24-11-19 18:59:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 18:59:52 | D | sum error = [ 4.1891, 4.3360, 4.5645, 4.7717, 5.1368] +24-11-19 18:59:52 | D | best error = [ 3.8425, 3.8425, 3.8425, 3.8425, 3.8425] +24-11-19 18:59:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 18:59:52 | D | sum error = [ 5.3439, 5.7700, 6.2126, 6.6834, 7.1925] +24-11-19 18:59:52 | D | best error = [ 3.8425, 3.8425, 3.8425, 3.8425, 3.8425] +24-11-19 18:59:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 18:59:52 | D | sum error = [ 7.8022, 8.3445, 9.1283, 9.9066, 10.7616] +24-11-19 18:59:52 | D | best error = [ 3.8425, 3.8425, 3.8425, 3.8425, 3.8425] +24-11-19 18:59:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 18:59:52 | D | sum error = [ 11.6408, 12.5376, 13.7711, 14.8342, 16.0767] +24-11-19 18:59:52 | D | best error = [ 3.8425, 3.8425, 3.8425, 3.8425, 3.8425] +24-11-19 18:59:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 18:59:52 | D | sum error = [ 17.5634, 19.0650, 20.7598, 22.5122, 24.4928] +24-11-19 18:59:52 | D | best error = [ 3.8425, 3.8425, 3.8425, 3.8425, 3.8425] +24-11-19 18:59:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 18:59:52 | D | sum error = [ 26.5810, 28.8085, 31.3528, 34.1379, 37.1769] +24-11-19 18:59:52 | D | best error = [ 3.8425, 3.8425, 3.8425, 3.8425, 3.8425] +24-11-19 18:59:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 18:59:52 | D | sum error = [ 40.3373, 43.8388, 47.3704, 51.1739, 55.4625] +24-11-19 18:59:52 | D | best error = [ 3.8425, 3.8425, 3.8425, 3.8425, 3.8425] +24-11-19 18:59:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 18:59:52 | D | sum error = [ 60.0454, 64.8728, 70.2235, 75.6988, 82.2500] +24-11-19 18:59:52 | D | best error = [ 3.8425, 3.8425, 3.8425, 3.8425, 3.8425] +24-11-19 18:59:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 18:59:52 | D | sum error = [ 88.6329, 95.7987, 103.2549, 111.1762, 119.9088] +24-11-19 18:59:52 | D | best error = [ 3.8425, 3.8425, 3.8425, 3.8425, 3.8425] +24-11-19 18:59:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 18:59:52 | D | sum error = [ 129.2754, 139.4293, 150.2039, 162.0651, 174.5507] +24-11-19 18:59:52 | D | best error = [ 3.8425, 3.8425, 3.8425, 3.8425, 3.8425] +24-11-19 18:59:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 18:59:52 | D | sum error = [ 187.8918, 202.8713, 218.9545, 236.2798, 255.2154] +24-11-19 18:59:52 | D | best error = [ 3.8425, 3.8425, 3.8425, 3.8425, 3.8425] +24-11-19 18:59:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 18:59:52 | D | sum error = [ 275.8418, 298.5370, 323.0988, 349.8771, 379.2915] +24-11-19 18:59:52 | D | best error = [ 3.8425, 3.8425, 3.8425, 3.8425, 3.8425] +24-11-19 18:59:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 18:59:52 | D | sum error = [ 411.1042, 446.4648, 485.1419, 527.6177, 574.2261] +24-11-19 18:59:52 | D | best error = [ 3.8425, 3.8425, 3.8425, 3.8425, 3.8425] +24-11-19 18:59:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 18:59:52 | D | sum error = [ 625.4081, 680.3935, 741.1483, 806.8175, 877.2631] +24-11-19 18:59:52 | D | best error = [ 3.8425, 3.8425, 3.8425, 3.8425, 3.8425] +24-11-19 18:59:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 18:59:52 | D | sum error = [ 952.9229, 1032.9595, 1117.1705, 1205.2790, 1294.7796] +24-11-19 18:59:52 | D | best error = [ 3.8425, 3.8425, 3.8425, 3.8425, 3.8425] +24-11-19 18:59:52 | D | + error = [3.8425] +24-11-19 18:59:53 | D | - Calibrating model.layers.18.self_attn.k_proj.weight +24-11-19 18:59:53 | D | + w: sint8 +24-11-19 18:59:53 | D | + x: None +24-11-19 18:59:53 | D | + y: None +24-11-19 18:59:53 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 18:59:53 | D | + finished parsing calibration arguments, ram usage: 11.7 +24-11-19 18:59:53 | D | + finished reseting calibrator, ram usage: 11.7 +24-11-19 18:59:53 | D | + finished calculating the original outputs, ram usage: 11.7 +24-11-19 18:59:53 | D | - range ratio = [ 1.0000] +24-11-19 18:59:53 | D | sum error = [ 4.0113] +24-11-19 18:59:53 | D | best error = [ 4.0113] +24-11-19 19:00:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:00:05 | D | sum error = [ 3.3768, 3.6811, 3.4167, 3.4830, 3.5623] +24-11-19 19:00:05 | D | best error = [ 3.3768, 3.3768, 3.3768, 3.3768, 3.3768] +24-11-19 19:00:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:00:05 | D | sum error = [ 4.6185, 4.2871, 3.8946, 4.1510, 4.6963] +24-11-19 19:00:05 | D | best error = [ 3.3768, 3.3768, 3.3768, 3.3768, 3.3768] +24-11-19 19:00:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:00:05 | D | sum error = [ 5.1201, 5.1711, 5.3603, 5.9955, 5.7717] +24-11-19 19:00:05 | D | best error = [ 3.3768, 3.3768, 3.3768, 3.3768, 3.3768] +24-11-19 19:00:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:00:05 | D | sum error = [ 6.5193, 7.2147, 7.6516, 8.0233, 9.3403] +24-11-19 19:00:05 | D | best error = [ 3.3768, 3.3768, 3.3768, 3.3768, 3.3768] +24-11-19 19:00:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:00:05 | D | sum error = [ 10.0265, 10.5412, 11.1421, 11.5912, 12.8894] +24-11-19 19:00:05 | D | best error = [ 3.3768, 3.3768, 3.3768, 3.3768, 3.3768] +24-11-19 19:00:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:00:05 | D | sum error = [ 13.7975, 14.9514, 15.9963, 17.4088, 18.1740] +24-11-19 19:00:05 | D | best error = [ 3.3768, 3.3768, 3.3768, 3.3768, 3.3768] +24-11-19 19:00:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:00:05 | D | sum error = [ 19.9651, 21.3877, 22.9674, 25.5266, 27.5879] +24-11-19 19:00:05 | D | best error = [ 3.3768, 3.3768, 3.3768, 3.3768, 3.3768] +24-11-19 19:00:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:00:05 | D | sum error = [ 29.5995, 31.9430, 34.4872, 37.1008, 40.3571] +24-11-19 19:00:05 | D | best error = [ 3.3768, 3.3768, 3.3768, 3.3768, 3.3768] +24-11-19 19:00:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:00:05 | D | sum error = [ 43.5417, 46.6001, 50.5752, 53.9349, 57.8203] +24-11-19 19:00:05 | D | best error = [ 3.3768, 3.3768, 3.3768, 3.3768, 3.3768] +24-11-19 19:00:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:00:05 | D | sum error = [ 62.4523, 67.3130, 71.9458, 77.5924, 83.7799] +24-11-19 19:00:05 | D | best error = [ 3.3768, 3.3768, 3.3768, 3.3768, 3.3768] +24-11-19 19:00:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:00:05 | D | sum error = [ 89.6355, 97.4616, 104.3754, 113.2423, 122.3416] +24-11-19 19:00:05 | D | best error = [ 3.3768, 3.3768, 3.3768, 3.3768, 3.3768] +24-11-19 19:00:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:00:05 | D | sum error = [ 132.4750, 142.9669, 156.0725, 168.8500, 182.9184] +24-11-19 19:00:05 | D | best error = [ 3.3768, 3.3768, 3.3768, 3.3768, 3.3768] +24-11-19 19:00:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:00:05 | D | sum error = [ 198.7934, 216.7105, 235.3795, 255.6808, 280.0539] +24-11-19 19:00:05 | D | best error = [ 3.3768, 3.3768, 3.3768, 3.3768, 3.3768] +24-11-19 19:00:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:00:05 | D | sum error = [ 306.6304, 335.8287, 367.6962, 401.1720, 444.0934] +24-11-19 19:00:05 | D | best error = [ 3.3768, 3.3768, 3.3768, 3.3768, 3.3768] +24-11-19 19:00:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:00:05 | D | sum error = [ 489.6293, 533.4302, 592.1024, 647.4379, 717.6870] +24-11-19 19:00:05 | D | best error = [ 3.3768, 3.3768, 3.3768, 3.3768, 3.3768] +24-11-19 19:00:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:00:05 | D | sum error = [ 790.8908, 862.3397, 954.3270, 1039.0969, 1134.2214] +24-11-19 19:00:05 | D | best error = [ 3.3768, 3.3768, 3.3768, 3.3768, 3.3768] +24-11-19 19:00:05 | D | + error = [3.3768] +24-11-19 19:00:05 | D | - Calibrating model.layers.18.self_attn.v_proj.weight +24-11-19 19:00:05 | D | + w: sint8 +24-11-19 19:00:05 | D | + x: None +24-11-19 19:00:05 | D | + y: None +24-11-19 19:00:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:00:05 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:00:05 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:00:06 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:00:06 | D | - range ratio = [ 1.0000] +24-11-19 19:00:06 | D | sum error = [ 1.5762] +24-11-19 19:00:06 | D | best error = [ 1.5762] +24-11-19 19:00:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:00:06 | D | sum error = [ 1.5520, 1.5676, 1.5642, 1.5788, 1.6104] +24-11-19 19:00:06 | D | best error = [ 1.4569, 1.4122, 1.3884, 1.3755, 1.3671] +24-11-19 19:00:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:00:06 | D | sum error = [ 1.6403, 1.7143, 1.7713, 1.8551, 1.9489] +24-11-19 19:00:06 | D | best error = [ 1.3635, 1.3622, 1.3618, 1.3616, 1.3615] +24-11-19 19:00:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:00:06 | D | sum error = [ 2.0696, 2.1984, 2.3499, 2.5076, 2.6850] +24-11-19 19:00:06 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 19:00:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:00:06 | D | sum error = [ 2.8743, 3.0854, 3.2999, 3.5297, 3.7866] +24-11-19 19:00:06 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 19:00:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:00:06 | D | sum error = [ 4.0744, 4.3587, 4.6779, 4.9984, 5.3414] +24-11-19 19:00:06 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 19:00:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:00:06 | D | sum error = [ 5.7191, 6.1081, 6.5258, 6.9653, 7.4331] +24-11-19 19:00:06 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 19:00:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:00:06 | D | sum error = [ 7.9337, 8.4678, 8.9966, 9.5805, 10.1707] +24-11-19 19:00:06 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 19:00:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:00:06 | D | sum error = [ 10.8141, 11.4666, 12.1675, 12.9108, 13.6725] +24-11-19 19:00:06 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 19:00:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:00:06 | D | sum error = [ 14.4917, 15.3349, 16.2348, 17.1732, 18.1451] +24-11-19 19:00:06 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 19:00:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:00:06 | D | sum error = [ 19.1743, 20.2642, 21.3816, 22.5694, 23.8085] +24-11-19 19:00:06 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 19:00:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:00:06 | D | sum error = [ 25.0940, 26.4393, 27.8539, 29.3362, 30.8825] +24-11-19 19:00:06 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 19:00:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:00:06 | D | sum error = [ 32.4827, 34.1576, 35.8988, 37.7082, 39.5933] +24-11-19 19:00:06 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 19:00:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:00:06 | D | sum error = [ 41.5579, 43.5933, 45.7138, 47.9122, 50.1969] +24-11-19 19:00:06 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 19:00:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:00:06 | D | sum error = [ 52.5763, 55.0435, 57.6051, 60.2507, 63.0127] +24-11-19 19:00:06 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 19:00:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:00:06 | D | sum error = [ 65.8640, 68.8145, 71.8666, 75.0191, 78.2795] +24-11-19 19:00:06 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 19:00:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:00:06 | D | sum error = [ 81.6533, 85.1184, 88.6886, 92.3592, 96.1321] +24-11-19 19:00:06 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 19:00:06 | D | + error = [1.3615] +24-11-19 19:00:06 | D | - Calibrating model.layers.18.self_attn.o_proj.weight +24-11-19 19:00:06 | D | + w: sint8 +24-11-19 19:00:06 | D | + x: None +24-11-19 19:00:06 | D | + y: None +24-11-19 19:00:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:00:06 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:00:06 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:00:06 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:00:06 | D | - range ratio = [ 1.0000] +24-11-19 19:00:06 | D | sum error = [ 0.4923] +24-11-19 19:00:06 | D | best error = [ 0.4923] +24-11-19 19:00:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:00:06 | D | sum error = [ 0.4870, 0.4853, 0.4819, 0.4841, 0.4836] +24-11-19 19:00:06 | D | best error = [ 0.4556, 0.4386, 0.4283, 0.4213, 0.4159] +24-11-19 19:00:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:00:06 | D | sum error = [ 0.4870, 0.4951, 0.5034, 0.5113, 0.5268] +24-11-19 19:00:06 | D | best error = [ 0.4119, 0.4089, 0.4067, 0.4051, 0.4042] +24-11-19 19:00:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:00:06 | D | sum error = [ 0.5403, 0.5584, 0.5781, 0.5977, 0.6243] +24-11-19 19:00:06 | D | best error = [ 0.4034, 0.4029, 0.4025, 0.4023, 0.4022] +24-11-19 19:00:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:00:06 | D | sum error = [ 0.6484, 0.6799, 0.7123, 0.7448, 0.7832] +24-11-19 19:00:06 | D | best error = [ 0.4020, 0.4020, 0.4020, 0.4020, 0.4019] +24-11-19 19:00:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:00:06 | D | sum error = [ 0.8232, 0.8658, 0.9089, 0.9588, 1.0084] +24-11-19 19:00:06 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 19:00:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:00:06 | D | sum error = [ 1.0614, 1.1190, 1.1801, 1.2435, 1.3120] +24-11-19 19:00:06 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 19:00:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:00:06 | D | sum error = [ 1.3825, 1.4564, 1.5381, 1.6194, 1.7082] +24-11-19 19:00:06 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 19:00:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:00:06 | D | sum error = [ 1.7986, 1.8983, 2.0010, 2.1087, 2.2233] +24-11-19 19:00:06 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 19:00:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:00:06 | D | sum error = [ 2.3414, 2.4685, 2.6021, 2.7451, 2.8930] +24-11-19 19:00:06 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 19:00:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:00:06 | D | sum error = [ 3.0508, 3.2165, 3.3932, 3.5779, 3.7738] +24-11-19 19:00:06 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 19:00:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:00:06 | D | sum error = [ 3.9790, 4.1973, 4.4246, 4.6664, 4.9199] +24-11-19 19:00:06 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 19:00:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:00:06 | D | sum error = [ 5.1899, 5.4734, 5.7722, 6.0867, 6.4184] +24-11-19 19:00:06 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 19:00:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:00:06 | D | sum error = [ 6.7678, 7.1368, 7.5222, 7.9295, 8.3567] +24-11-19 19:00:06 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 19:00:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:00:06 | D | sum error = [ 8.8050, 9.2743, 9.7674, 10.2855, 10.8280] +24-11-19 19:00:06 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 19:00:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:00:06 | D | sum error = [ 11.3962, 11.9898, 12.6097, 13.2569, 13.9334] +24-11-19 19:00:06 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 19:00:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:00:06 | D | sum error = [ 14.6399, 15.3772, 16.1460, 16.9481, 17.7818] +24-11-19 19:00:06 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 19:00:06 | D | + error = [0.4019] +24-11-19 19:00:07 | D | - Calibrating model.layers.18.mlp.up_proj.weight +24-11-19 19:00:07 | D | + w: sint8 +24-11-19 19:00:07 | D | + x: None +24-11-19 19:00:07 | D | + y: None +24-11-19 19:00:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:00:07 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:00:07 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:00:07 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:00:07 | D | - range ratio = [ 1.0000] +24-11-19 19:00:07 | D | sum error = [ 6.3108] +24-11-19 19:00:07 | D | best error = [ 6.3108] +24-11-19 19:00:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:00:08 | D | sum error = [ 6.2590, 6.2430, 6.2805, 6.3584, 6.4696] +24-11-19 19:00:08 | D | best error = [ 5.8604, 5.6852, 5.5973, 5.5462, 5.5186] +24-11-19 19:00:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:00:08 | D | sum error = [ 6.6285, 6.8763, 7.1337, 7.4649, 7.8847] +24-11-19 19:00:08 | D | best error = [ 5.5040, 5.4982, 5.4959, 5.4952, 5.4951] +24-11-19 19:00:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:00:08 | D | sum error = [ 8.3327, 8.8270, 9.3983, 10.0469, 10.7477] +24-11-19 19:00:08 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 19:00:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:00:08 | D | sum error = [ 11.4970, 12.3174, 13.1834, 14.1326, 15.1609] +24-11-19 19:00:08 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 19:00:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:00:08 | D | sum error = [ 16.2362, 17.3901, 18.6229, 19.9074, 21.2778] +24-11-19 19:00:08 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 19:00:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:00:08 | D | sum error = [ 22.7555, 24.2899, 25.9268, 27.6547, 29.4779] +24-11-19 19:00:08 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 19:00:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:00:08 | D | sum error = [ 31.3950, 33.4325, 35.5667, 37.8132, 40.1955] +24-11-19 19:00:08 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 19:00:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:00:08 | D | sum error = [ 42.6686, 45.2979, 48.0397, 50.9333, 53.9672] +24-11-19 19:00:08 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 19:00:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:00:08 | D | sum error = [ 57.1427, 60.4671, 63.9745, 67.6199, 71.4618] +24-11-19 19:00:08 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 19:00:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:00:08 | D | sum error = [ 75.4638, 79.6723, 84.0533, 88.6380, 93.4305] +24-11-19 19:00:08 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 19:00:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:00:08 | D | sum error = [ 98.4244, 103.6244, 109.0506, 114.7144, 120.5888] +24-11-19 19:00:08 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 19:00:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:00:08 | D | sum error = [ 126.7218, 133.0849, 139.7146, 146.6134, 153.7644] +24-11-19 19:00:08 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 19:00:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:00:08 | D | sum error = [ 161.2017, 168.9018, 176.8858, 185.1652, 193.7454] +24-11-19 19:00:08 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 19:00:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:00:08 | D | sum error = [ 202.6145, 211.7987, 221.2998, 231.1167, 241.2685] +24-11-19 19:00:08 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 19:00:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:00:08 | D | sum error = [ 251.7280, 262.5307, 273.6692, 285.1478, 296.9604] +24-11-19 19:00:08 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 19:00:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:00:08 | D | sum error = [ 309.1590, 321.6956, 334.6017, 347.8680, 361.5139] +24-11-19 19:00:08 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 19:00:08 | D | + error = [5.4950] +24-11-19 19:00:08 | D | - Calibrating model.layers.18.mlp.gate_proj.weight +24-11-19 19:00:08 | D | + w: sint8 +24-11-19 19:00:08 | D | + x: None +24-11-19 19:00:08 | D | + y: None +24-11-19 19:00:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:00:08 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:00:08 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:00:08 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:00:08 | D | - range ratio = [ 1.0000] +24-11-19 19:00:08 | D | sum error = [ 8.4719] +24-11-19 19:00:08 | D | best error = [ 8.4719] +24-11-19 19:00:09 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:00:09 | D | sum error = [ 8.4298, 8.3632, 8.3987, 8.5097, 8.6754] +24-11-19 19:00:09 | D | best error = [ 7.8774, 7.6401, 7.5132, 7.4432, 7.4052] +24-11-19 19:00:09 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:00:09 | D | sum error = [ 8.8910, 9.2041, 9.5659, 10.0268, 10.5291] +24-11-19 19:00:09 | D | best error = [ 7.3862, 7.3782, 7.3750, 7.3742, 7.3740] +24-11-19 19:00:09 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:00:09 | D | sum error = [ 11.1571, 11.8446, 12.6262, 13.4752, 14.4324] +24-11-19 19:00:09 | D | best error = [ 7.3740, 7.3740, 7.3740, 7.3740, 7.3740] +24-11-19 19:00:09 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:00:09 | D | sum error = [ 15.4653, 16.5582, 17.7397, 19.0474, 20.4237] +24-11-19 19:00:09 | D | best error = [ 7.3740, 7.3740, 7.3740, 7.3740, 7.3740] +24-11-19 19:00:09 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:00:09 | D | sum error = [ 21.9181, 23.5210, 25.2372, 27.0553, 28.9860] +24-11-19 19:00:09 | D | best error = [ 7.3740, 7.3740, 7.3740, 7.3740, 7.3740] +24-11-19 19:00:09 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:00:09 | D | sum error = [ 31.0400, 33.2395, 35.5834, 38.0451, 40.6927] +24-11-19 19:00:09 | D | best error = [ 7.3740, 7.3740, 7.3740, 7.3740, 7.3740] +24-11-19 19:00:09 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:00:09 | D | sum error = [ 43.4828, 46.4610, 49.6081, 52.9474, 56.5108] +24-11-19 19:00:09 | D | best error = [ 7.3740, 7.3740, 7.3740, 7.3740, 7.3740] +24-11-19 19:00:09 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:00:09 | D | sum error = [ 60.2399, 64.2197, 68.4702, 72.9322, 77.7117] +24-11-19 19:00:09 | D | best error = [ 7.3740, 7.3740, 7.3740, 7.3740, 7.3740] +24-11-19 19:00:09 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:00:09 | D | sum error = [ 82.7275, 88.0458, 93.6816, 99.6520, 105.9330] +24-11-19 19:00:09 | D | best error = [ 7.3740, 7.3740, 7.3740, 7.3740, 7.3740] +24-11-19 19:00:09 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:00:09 | D | sum error = [ 112.5558, 119.5936, 127.0264, 134.8444, 143.1157] +24-11-19 19:00:09 | D | best error = [ 7.3740, 7.3740, 7.3740, 7.3740, 7.3740] +24-11-19 19:00:09 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:00:09 | D | sum error = [ 151.8418, 161.0627, 170.7576, 181.0164, 191.7686] +24-11-19 19:00:09 | D | best error = [ 7.3740, 7.3740, 7.3740, 7.3740, 7.3740] +24-11-19 19:00:09 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:00:09 | D | sum error = [ 203.1198, 215.0893, 227.6150, 240.8246, 254.6591] +24-11-19 19:00:09 | D | best error = [ 7.3740, 7.3740, 7.3740, 7.3740, 7.3740] +24-11-19 19:00:09 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:00:09 | D | sum error = [ 269.2359, 284.5168, 300.5071, 317.2482, 334.7649] +24-11-19 19:00:09 | D | best error = [ 7.3740, 7.3740, 7.3740, 7.3740, 7.3740] +24-11-19 19:00:09 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:00:09 | D | sum error = [ 353.0719, 372.1786, 392.1369, 412.9434, 434.5865] +24-11-19 19:00:09 | D | best error = [ 7.3740, 7.3740, 7.3740, 7.3740, 7.3740] +24-11-19 19:00:09 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:00:09 | D | sum error = [ 457.1205, 480.5485, 504.8526, 530.0574, 556.1799] +24-11-19 19:00:09 | D | best error = [ 7.3740, 7.3740, 7.3740, 7.3740, 7.3740] +24-11-19 19:00:09 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:00:09 | D | sum error = [ 583.2217, 611.2053, 640.0795, 669.8736, 700.6145] +24-11-19 19:00:09 | D | best error = [ 7.3740, 7.3740, 7.3740, 7.3740, 7.3740] +24-11-19 19:00:09 | D | + error = [7.3740] +24-11-19 19:00:10 | D | - Calibrating model.layers.18.mlp.down_proj.weight +24-11-19 19:00:10 | D | + w: sint8 +24-11-19 19:00:10 | D | + x: None +24-11-19 19:00:10 | D | + y: None +24-11-19 19:00:10 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:00:10 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:00:10 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:00:10 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:00:10 | D | - range ratio = [ 1.0000] +24-11-19 19:00:10 | D | sum error = [ 0.9852] +24-11-19 19:00:10 | D | best error = [ 0.9852] +24-11-19 19:00:11 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:00:11 | D | sum error = [ 0.9770, 0.9692, 0.9631, 0.9602, 0.9584] +24-11-19 19:00:11 | D | best error = [ 0.9447, 0.9247, 0.9109, 0.9009, 0.8926] +24-11-19 19:00:11 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:00:11 | D | sum error = [ 0.9584, 0.9624, 0.9671, 0.9800, 0.9953] +24-11-19 19:00:11 | D | best error = [ 0.8861, 0.8810, 0.8770, 0.8740, 0.8719] +24-11-19 19:00:11 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:00:11 | D | sum error = [ 1.0133, 1.0375, 1.0677, 1.1057, 1.1471] +24-11-19 19:00:11 | D | best error = [ 0.8703, 0.8689, 0.8681, 0.8675, 0.8670] +24-11-19 19:00:11 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:00:11 | D | sum error = [ 1.1962, 1.2553, 1.3167, 1.3887, 1.4723] +24-11-19 19:00:11 | D | best error = [ 0.8668, 0.8666, 0.8665, 0.8664, 0.8663] +24-11-19 19:00:11 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:00:11 | D | sum error = [ 1.5593, 1.6580, 1.7640, 1.8811, 2.0079] +24-11-19 19:00:11 | D | best error = [ 0.8663, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 19:00:11 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:00:11 | D | sum error = [ 2.1449, 2.2956, 2.4525, 2.6249, 2.8092] +24-11-19 19:00:11 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 19:00:11 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:00:11 | D | sum error = [ 3.0041, 3.2152, 3.4364, 3.6758, 3.9290] +24-11-19 19:00:11 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 19:00:11 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:00:11 | D | sum error = [ 4.2011, 4.4881, 4.7924, 5.1170, 5.4614] +24-11-19 19:00:11 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 19:00:11 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:00:11 | D | sum error = [ 5.8251, 6.2097, 6.6177, 7.0477, 7.5030] +24-11-19 19:00:11 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 19:00:11 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:00:11 | D | sum error = [ 7.9832, 8.4888, 9.0215, 9.5827, 10.1729] +24-11-19 19:00:11 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 19:00:11 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:00:11 | D | sum error = [ 10.7941, 11.4458, 12.1301, 12.8510, 13.6061] +24-11-19 19:00:11 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 19:00:11 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:00:11 | D | sum error = [ 14.3990, 15.2321, 16.1037, 17.0131, 17.9707] +24-11-19 19:00:11 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 19:00:11 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:00:11 | D | sum error = [ 18.9681, 20.0131, 21.1045, 22.2448, 23.4326] +24-11-19 19:00:11 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 19:00:11 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:00:11 | D | sum error = [ 24.6706, 25.9596, 27.3021, 28.7002, 30.1522] +24-11-19 19:00:11 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 19:00:11 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:00:11 | D | sum error = [ 31.6608, 33.2278, 34.8534, 36.5392, 38.2853] +24-11-19 19:00:11 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 19:00:11 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:00:11 | D | sum error = [ 40.0916, 41.9609, 43.8942, 45.8903, 47.9505] +24-11-19 19:00:11 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 19:00:11 | D | + error = [0.8662] +24-11-19 19:00:11 | D | - Quantizing model.layers.18.self_attn.q_proj.weight +24-11-19 19:00:12 | D | - Quantizing model.layers.18.self_attn.k_proj.weight +24-11-19 19:00:13 | D | - Quantizing model.layers.18.self_attn.v_proj.weight +24-11-19 19:00:14 | D | - Quantizing model.layers.18.self_attn.o_proj.weight +24-11-19 19:00:14 | D | - Quantizing model.layers.18.mlp.up_proj.weight +24-11-19 19:00:15 | D | - Quantizing model.layers.18.mlp.gate_proj.weight +24-11-19 19:00:16 | D | - Quantizing model.layers.18.mlp.down_proj.weight +24-11-19 19:00:26 | D | - Quantizing layer model.layers.19 +24-11-19 19:00:26 | D | - Calibrating model.layers.19.self_attn.q_proj.weight +24-11-19 19:00:26 | D | + w: sint8 +24-11-19 19:00:26 | D | + x: None +24-11-19 19:00:26 | D | + y: None +24-11-19 19:00:26 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:00:26 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:00:26 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:00:26 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:00:26 | D | - range ratio = [ 1.0000] +24-11-19 19:00:26 | D | sum error = [ 3.5058] +24-11-19 19:00:26 | D | best error = [ 3.5058] +24-11-19 19:00:38 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:00:38 | D | sum error = [ 3.4877, 3.4378, 3.5227, 3.5352, 3.5689] +24-11-19 19:00:38 | D | best error = [ 3.4877, 3.4378, 3.4378, 3.4378, 3.4378] +24-11-19 19:00:38 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:00:38 | D | sum error = [ 3.7226, 3.9482, 4.0259, 4.2809, 4.6491] +24-11-19 19:00:38 | D | best error = [ 3.4378, 3.4378, 3.4378, 3.4378, 3.4378] +24-11-19 19:00:38 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:00:38 | D | sum error = [ 4.9949, 5.3615, 5.8403, 6.3172, 6.8340] +24-11-19 19:00:38 | D | best error = [ 3.4378, 3.4378, 3.4378, 3.4378, 3.4378] +24-11-19 19:00:38 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:00:38 | D | sum error = [ 7.4449, 8.1269, 8.9685, 9.7814, 10.6251] +24-11-19 19:00:38 | D | best error = [ 3.4378, 3.4378, 3.4378, 3.4378, 3.4378] +24-11-19 19:00:38 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:00:38 | D | sum error = [ 11.8279, 12.8682, 14.0961, 15.4823, 16.8984] +24-11-19 19:00:38 | D | best error = [ 3.4378, 3.4378, 3.4378, 3.4378, 3.4378] +24-11-19 19:00:38 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:00:38 | D | sum error = [ 18.6892, 20.5607, 22.6584, 24.7882, 27.1914] +24-11-19 19:00:38 | D | best error = [ 3.4378, 3.4378, 3.4378, 3.4378, 3.4378] +24-11-19 19:00:38 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:00:38 | D | sum error = [ 29.8177, 32.6616, 35.9089, 39.0710, 42.9372] +24-11-19 19:00:38 | D | best error = [ 3.4378, 3.4378, 3.4378, 3.4378, 3.4378] +24-11-19 19:00:38 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:00:38 | D | sum error = [ 46.6396, 51.2487, 55.9464, 61.3387, 66.8520] +24-11-19 19:00:38 | D | best error = [ 3.4378, 3.4378, 3.4378, 3.4378, 3.4378] +24-11-19 19:00:38 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:00:38 | D | sum error = [ 73.1013, 79.9804, 86.9410, 94.8311, 103.1736] +24-11-19 19:00:38 | D | best error = [ 3.4378, 3.4378, 3.4378, 3.4378, 3.4378] +24-11-19 19:00:38 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:00:38 | D | sum error = [ 112.3517, 122.3243, 132.8257, 144.5895, 157.1375] +24-11-19 19:00:38 | D | best error = [ 3.4378, 3.4378, 3.4378, 3.4378, 3.4378] +24-11-19 19:00:38 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:00:38 | D | sum error = [ 171.0707, 185.4711, 201.9855, 219.3057, 238.3623] +24-11-19 19:00:38 | D | best error = [ 3.4378, 3.4378, 3.4378, 3.4378, 3.4378] +24-11-19 19:00:38 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:00:38 | D | sum error = [ 258.9414, 281.5291, 305.8786, 332.8400, 362.2321] +24-11-19 19:00:38 | D | best error = [ 3.4378, 3.4378, 3.4378, 3.4378, 3.4378] +24-11-19 19:00:38 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:00:38 | D | sum error = [ 394.4902, 429.4345, 468.3905, 510.4737, 556.7147] +24-11-19 19:00:38 | D | best error = [ 3.4378, 3.4378, 3.4378, 3.4378, 3.4378] +24-11-19 19:00:38 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:00:38 | D | sum error = [ 606.9380, 661.8521, 722.2892, 787.4537, 859.1186] +24-11-19 19:00:38 | D | best error = [ 3.4378, 3.4378, 3.4378, 3.4378, 3.4378] +24-11-19 19:00:38 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:00:38 | D | sum error = [ 936.3092, 1018.7246, 1107.8972, 1201.6296, 1300.7106] +24-11-19 19:00:38 | D | best error = [ 3.4378, 3.4378, 3.4378, 3.4378, 3.4378] +24-11-19 19:00:38 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:00:38 | D | sum error = [ 1404.1576, 1511.8859, 1621.2035, 1732.4988, 1843.8290] +24-11-19 19:00:38 | D | best error = [ 3.4378, 3.4378, 3.4378, 3.4378, 3.4378] +24-11-19 19:00:38 | D | + error = [3.4378] +24-11-19 19:00:38 | D | - Calibrating model.layers.19.self_attn.k_proj.weight +24-11-19 19:00:38 | D | + w: sint8 +24-11-19 19:00:38 | D | + x: None +24-11-19 19:00:38 | D | + y: None +24-11-19 19:00:38 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:00:38 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:00:38 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:00:39 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:00:39 | D | - range ratio = [ 1.0000] +24-11-19 19:00:39 | D | sum error = [ 3.4343] +24-11-19 19:00:39 | D | best error = [ 3.4343] +24-11-19 19:00:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:00:51 | D | sum error = [ 3.1547, 3.3218, 3.3957, 3.5746, 3.7939] +24-11-19 19:00:51 | D | best error = [ 3.1547, 3.1547, 3.1547, 3.1547, 3.1547] +24-11-19 19:00:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:00:51 | D | sum error = [ 3.6236, 4.1477, 4.2285, 4.2285, 4.0516] +24-11-19 19:00:51 | D | best error = [ 3.1547, 3.1547, 3.1547, 3.1547, 3.1547] +24-11-19 19:00:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:00:51 | D | sum error = [ 4.7023, 5.0188, 5.1386, 5.7722, 6.3227] +24-11-19 19:00:51 | D | best error = [ 3.1547, 3.1547, 3.1547, 3.1547, 3.1547] +24-11-19 19:00:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:00:51 | D | sum error = [ 6.3713, 7.0948, 7.8162, 8.2897, 9.1874] +24-11-19 19:00:51 | D | best error = [ 3.1547, 3.1547, 3.1547, 3.1547, 3.1547] +24-11-19 19:00:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:00:51 | D | sum error = [ 9.7228, 10.4635, 11.8910, 13.1617, 13.8082] +24-11-19 19:00:51 | D | best error = [ 3.1547, 3.1547, 3.1547, 3.1547, 3.1547] +24-11-19 19:00:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:00:51 | D | sum error = [ 15.4216, 16.5605, 17.5939, 19.3614, 21.5222] +24-11-19 19:00:51 | D | best error = [ 3.1547, 3.1547, 3.1547, 3.1547, 3.1547] +24-11-19 19:00:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:00:51 | D | sum error = [ 23.0260, 25.0211, 27.3176, 28.6258, 31.5584] +24-11-19 19:00:51 | D | best error = [ 3.1547, 3.1547, 3.1547, 3.1547, 3.1547] +24-11-19 19:00:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:00:51 | D | sum error = [ 34.0368, 36.9784, 40.6894, 43.6002, 46.8737] +24-11-19 19:00:51 | D | best error = [ 3.1547, 3.1547, 3.1547, 3.1547, 3.1547] +24-11-19 19:00:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:00:51 | D | sum error = [ 50.6219, 54.9610, 58.8597, 63.4457, 68.1221] +24-11-19 19:00:51 | D | best error = [ 3.1547, 3.1547, 3.1547, 3.1547, 3.1547] +24-11-19 19:00:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:00:51 | D | sum error = [ 72.7287, 78.8150, 84.7766, 91.8923, 98.9246] +24-11-19 19:00:51 | D | best error = [ 3.1547, 3.1547, 3.1547, 3.1547, 3.1547] +24-11-19 19:00:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:00:51 | D | sum error = [ 107.0032, 115.3562, 125.1037, 135.8594, 147.2959] +24-11-19 19:00:51 | D | best error = [ 3.1547, 3.1547, 3.1547, 3.1547, 3.1547] +24-11-19 19:00:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:00:51 | D | sum error = [ 160.2231, 174.2449, 189.9409, 207.8807, 226.4112] +24-11-19 19:00:51 | D | best error = [ 3.1547, 3.1547, 3.1547, 3.1547, 3.1547] +24-11-19 19:00:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:00:51 | D | sum error = [ 248.3942, 273.0747, 299.2878, 327.6425, 362.4528] +24-11-19 19:00:51 | D | best error = [ 3.1547, 3.1547, 3.1547, 3.1547, 3.1547] +24-11-19 19:00:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:00:51 | D | sum error = [ 396.5239, 437.5780, 478.1574, 528.2443, 581.8539] +24-11-19 19:00:51 | D | best error = [ 3.1547, 3.1547, 3.1547, 3.1547, 3.1547] +24-11-19 19:00:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:00:51 | D | sum error = [ 635.7420, 701.1527, 769.6217, 844.3331, 927.9111] +24-11-19 19:00:51 | D | best error = [ 3.1547, 3.1547, 3.1547, 3.1547, 3.1547] +24-11-19 19:00:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:00:51 | D | sum error = [ 1027.0809, 1125.7710, 1237.9758, 1361.8906, 1475.7371] +24-11-19 19:00:51 | D | best error = [ 3.1547, 3.1547, 3.1547, 3.1547, 3.1547] +24-11-19 19:00:51 | D | + error = [3.1547] +24-11-19 19:00:51 | D | - Calibrating model.layers.19.self_attn.v_proj.weight +24-11-19 19:00:51 | D | + w: sint8 +24-11-19 19:00:51 | D | + x: None +24-11-19 19:00:51 | D | + y: None +24-11-19 19:00:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:00:51 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:00:51 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:00:51 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:00:51 | D | - range ratio = [ 1.0000] +24-11-19 19:00:51 | D | sum error = [ 1.6692] +24-11-19 19:00:51 | D | best error = [ 1.6692] +24-11-19 19:00:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:00:51 | D | sum error = [ 1.6538, 1.6520, 1.6486, 1.6798, 1.7039] +24-11-19 19:00:51 | D | best error = [ 1.5518, 1.5043, 1.4782, 1.4636, 1.4568] +24-11-19 19:00:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:00:51 | D | sum error = [ 1.7583, 1.8325, 1.8980, 1.9813, 2.0894] +24-11-19 19:00:51 | D | best error = [ 1.4535, 1.4517, 1.4508, 1.4508, 1.4508] +24-11-19 19:00:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:00:51 | D | sum error = [ 2.2062, 2.3504, 2.5087, 2.6761, 2.8682] +24-11-19 19:00:51 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 19:00:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:00:51 | D | sum error = [ 3.0666, 3.2979, 3.5263, 3.7767, 4.0503] +24-11-19 19:00:51 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 19:00:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:00:51 | D | sum error = [ 4.3568, 4.6812, 5.0113, 5.3734, 5.7395] +24-11-19 19:00:51 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 19:00:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:00:51 | D | sum error = [ 6.1462, 6.5612, 7.0236, 7.4914, 7.9802] +24-11-19 19:00:51 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 19:00:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:00:51 | D | sum error = [ 8.5145, 9.1003, 9.6885, 10.2946, 10.9647] +24-11-19 19:00:51 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 19:00:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:00:51 | D | sum error = [ 11.6565, 12.3896, 13.1799, 13.9666, 14.8151] +24-11-19 19:00:51 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 19:00:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:00:51 | D | sum error = [ 15.7022, 16.6455, 17.6163, 18.6358, 19.7231] +24-11-19 19:00:51 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 19:00:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:00:51 | D | sum error = [ 20.8676, 22.0525, 23.3050, 24.5919, 25.9614] +24-11-19 19:00:51 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 19:00:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:00:51 | D | sum error = [ 27.3883, 28.8894, 30.4526, 32.0713, 33.7827] +24-11-19 19:00:51 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 19:00:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:00:51 | D | sum error = [ 35.5501, 37.3871, 39.3071, 41.3036, 43.3823] +24-11-19 19:00:51 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 19:00:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:00:51 | D | sum error = [ 45.5445, 47.7912, 50.1313, 52.5603, 55.0914] +24-11-19 19:00:51 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 19:00:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:00:51 | D | sum error = [ 57.7119, 60.4460, 63.2682, 66.1918, 69.2189] +24-11-19 19:00:51 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 19:00:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:00:51 | D | sum error = [ 72.3492, 75.5811, 78.9191, 82.3741, 85.9294] +24-11-19 19:00:51 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 19:00:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:00:51 | D | sum error = [ 89.6069, 93.3907, 97.2977, 101.3108, 105.4422] +24-11-19 19:00:51 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 19:00:51 | D | + error = [1.4508] +24-11-19 19:00:51 | D | - Calibrating model.layers.19.self_attn.o_proj.weight +24-11-19 19:00:51 | D | + w: sint8 +24-11-19 19:00:51 | D | + x: None +24-11-19 19:00:51 | D | + y: None +24-11-19 19:00:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:00:51 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:00:51 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:00:51 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:00:51 | D | - range ratio = [ 1.0000] +24-11-19 19:00:51 | D | sum error = [ 0.3769] +24-11-19 19:00:51 | D | best error = [ 0.3769] +24-11-19 19:00:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:00:52 | D | sum error = [ 0.3739, 0.3729, 0.3743, 0.3756, 0.3788] +24-11-19 19:00:52 | D | best error = [ 0.3528, 0.3422, 0.3355, 0.3311, 0.3277] +24-11-19 19:00:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:00:52 | D | sum error = [ 0.3877, 0.3978, 0.4103, 0.4241, 0.4425] +24-11-19 19:00:52 | D | best error = [ 0.3256, 0.3239, 0.3227, 0.3217, 0.3209] +24-11-19 19:00:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:00:52 | D | sum error = [ 0.4619, 0.4867, 0.5129, 0.5426, 0.5725] +24-11-19 19:00:52 | D | best error = [ 0.3204, 0.3199, 0.3196, 0.3193, 0.3191] +24-11-19 19:00:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:00:52 | D | sum error = [ 0.6093, 0.6461, 0.6862, 0.7302, 0.7759] +24-11-19 19:00:52 | D | best error = [ 0.3190, 0.3189, 0.3188, 0.3188, 0.3188] +24-11-19 19:00:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:00:52 | D | sum error = [ 0.8266, 0.8794, 0.9358, 0.9960, 1.0572] +24-11-19 19:00:52 | D | best error = [ 0.3187, 0.3187, 0.3187, 0.3187, 0.3187] +24-11-19 19:00:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:00:52 | D | sum error = [ 1.1250, 1.1945, 1.2702, 1.3491, 1.4311] +24-11-19 19:00:52 | D | best error = [ 0.3187, 0.3187, 0.3187, 0.3187, 0.3187] +24-11-19 19:00:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:00:52 | D | sum error = [ 1.5200, 1.6123, 1.7080, 1.8098, 1.9179] +24-11-19 19:00:52 | D | best error = [ 0.3187, 0.3187, 0.3187, 0.3187, 0.3187] +24-11-19 19:00:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:00:52 | D | sum error = [ 2.0296, 2.1472, 2.2701, 2.3991, 2.5339] +24-11-19 19:00:52 | D | best error = [ 0.3187, 0.3187, 0.3187, 0.3187, 0.3187] +24-11-19 19:00:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:00:52 | D | sum error = [ 2.6770, 2.8268, 2.9833, 3.1481, 3.3202] +24-11-19 19:00:52 | D | best error = [ 0.3187, 0.3187, 0.3187, 0.3187, 0.3187] +24-11-19 19:00:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:00:52 | D | sum error = [ 3.5016, 3.6919, 3.8899, 4.0979, 4.3150] +24-11-19 19:00:52 | D | best error = [ 0.3187, 0.3187, 0.3187, 0.3187, 0.3187] +24-11-19 19:00:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:00:52 | D | sum error = [ 4.5427, 4.7808, 5.0285, 5.2881, 5.5587] +24-11-19 19:00:52 | D | best error = [ 0.3187, 0.3187, 0.3187, 0.3187, 0.3187] +24-11-19 19:00:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:00:52 | D | sum error = [ 5.8412, 6.1361, 6.4446, 6.7647, 7.0999] +24-11-19 19:00:52 | D | best error = [ 0.3187, 0.3187, 0.3187, 0.3187, 0.3187] +24-11-19 19:00:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:00:52 | D | sum error = [ 7.4474, 7.8105, 8.1864, 8.5771, 8.9827] +24-11-19 19:00:52 | D | best error = [ 0.3187, 0.3187, 0.3187, 0.3187, 0.3187] +24-11-19 19:00:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:00:52 | D | sum error = [ 9.4041, 9.8412, 10.2949, 10.7666, 11.2542] +24-11-19 19:00:52 | D | best error = [ 0.3187, 0.3187, 0.3187, 0.3187, 0.3187] +24-11-19 19:00:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:00:52 | D | sum error = [ 11.7600, 12.2840, 12.8268, 13.3886, 13.9696] +24-11-19 19:00:52 | D | best error = [ 0.3187, 0.3187, 0.3187, 0.3187, 0.3187] +24-11-19 19:00:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:00:52 | D | sum error = [ 14.5694, 15.1898, 15.8292, 16.4905, 17.1724] +24-11-19 19:00:52 | D | best error = [ 0.3187, 0.3187, 0.3187, 0.3187, 0.3187] +24-11-19 19:00:52 | D | + error = [0.3187] +24-11-19 19:00:52 | D | - Calibrating model.layers.19.mlp.up_proj.weight +24-11-19 19:00:52 | D | + w: sint8 +24-11-19 19:00:52 | D | + x: None +24-11-19 19:00:52 | D | + y: None +24-11-19 19:00:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:00:52 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:00:52 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:00:52 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:00:52 | D | - range ratio = [ 1.0000] +24-11-19 19:00:52 | D | sum error = [ 6.5165] +24-11-19 19:00:52 | D | best error = [ 6.5165] +24-11-19 19:00:53 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:00:53 | D | sum error = [ 6.4672, 6.4596, 6.4681, 6.5433, 6.6677] +24-11-19 19:00:53 | D | best error = [ 6.0329, 5.8510, 5.7551, 5.7001, 5.6706] +24-11-19 19:00:53 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:00:53 | D | sum error = [ 6.8281, 7.0455, 7.3503, 7.6848, 8.0798] +24-11-19 19:00:53 | D | best error = [ 5.6568, 5.6505, 5.6477, 5.6469, 5.6468] +24-11-19 19:00:53 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:00:53 | D | sum error = [ 8.5415, 9.0687, 9.6612, 10.3071, 11.0191] +24-11-19 19:00:53 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 19:00:53 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:00:53 | D | sum error = [ 11.7936, 12.6167, 13.5121, 14.4817, 15.5122] +24-11-19 19:00:53 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 19:00:53 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:00:53 | D | sum error = [ 16.5966, 17.7793, 19.0325, 20.3632, 21.7691] +24-11-19 19:00:53 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 19:00:53 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:00:53 | D | sum error = [ 23.2454, 24.8389, 26.4932, 28.2685, 30.1317] +24-11-19 19:00:53 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 19:00:53 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:00:53 | D | sum error = [ 32.0830, 34.1470, 36.3173, 38.6050, 41.0202] +24-11-19 19:00:53 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 19:00:53 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:00:53 | D | sum error = [ 43.5601, 46.2148, 49.0193, 51.9462, 55.0224] +24-11-19 19:00:53 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 19:00:53 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:00:53 | D | sum error = [ 58.2601, 61.6452, 65.1931, 68.8988, 72.7872] +24-11-19 19:00:53 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 19:00:53 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:00:53 | D | sum error = [ 76.8570, 81.1146, 85.5695, 90.2008, 95.0508] +24-11-19 19:00:53 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 19:00:53 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:00:53 | D | sum error = [ 100.0966, 105.3692, 110.8627, 116.5770, 122.5243] +24-11-19 19:00:53 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 19:00:53 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:00:53 | D | sum error = [ 128.7041, 135.1230, 141.8095, 148.7412, 155.9260] +24-11-19 19:00:53 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 19:00:53 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:00:53 | D | sum error = [ 163.3883, 171.1225, 179.1347, 187.4351, 196.0244] +24-11-19 19:00:53 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 19:00:53 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:00:53 | D | sum error = [ 204.9075, 214.0933, 223.5835, 233.4018, 243.5249] +24-11-19 19:00:53 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 19:00:53 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:00:53 | D | sum error = [ 253.9667, 264.7419, 275.8380, 287.2759, 299.0452] +24-11-19 19:00:53 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 19:00:53 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:00:53 | D | sum error = [ 311.1845, 323.6742, 336.5217, 349.7249, 363.2882] +24-11-19 19:00:53 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 19:00:53 | D | + error = [5.6467] +24-11-19 19:00:53 | D | - Calibrating model.layers.19.mlp.gate_proj.weight +24-11-19 19:00:53 | D | + w: sint8 +24-11-19 19:00:53 | D | + x: None +24-11-19 19:00:53 | D | + y: None +24-11-19 19:00:53 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:00:54 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:00:54 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:00:54 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:00:54 | D | - range ratio = [ 1.0000] +24-11-19 19:00:54 | D | sum error = [ 8.7899] +24-11-19 19:00:54 | D | best error = [ 8.7899] +24-11-19 19:00:55 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:00:55 | D | sum error = [ 8.7251, 8.7156, 8.7480, 8.8185, 9.0157] +24-11-19 19:00:55 | D | best error = [ 8.1414, 7.9018, 7.7734, 7.7010, 7.6611] +24-11-19 19:00:55 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:00:55 | D | sum error = [ 9.2218, 9.5534, 9.9450, 10.4356, 10.9775] +24-11-19 19:00:55 | D | best error = [ 7.6409, 7.6329, 7.6298, 7.6291, 7.6289] +24-11-19 19:00:55 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:00:55 | D | sum error = [ 11.6514, 12.3518, 13.1933, 14.0684, 15.0734] +24-11-19 19:00:55 | D | best error = [ 7.6289, 7.6289, 7.6289, 7.6289, 7.6289] +24-11-19 19:00:55 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:00:55 | D | sum error = [ 16.1477, 17.3154, 18.5728, 19.9121, 21.3775] +24-11-19 19:00:55 | D | best error = [ 7.6289, 7.6289, 7.6289, 7.6289, 7.6289] +24-11-19 19:00:55 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:00:55 | D | sum error = [ 22.9254, 24.6111, 26.3695, 28.2314, 30.2432] +24-11-19 19:00:55 | D | best error = [ 7.6289, 7.6289, 7.6289, 7.6289, 7.6289] +24-11-19 19:00:55 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:00:55 | D | sum error = [ 32.3739, 34.6330, 37.0572, 39.5941, 42.3189] +24-11-19 19:00:55 | D | best error = [ 7.6289, 7.6289, 7.6289, 7.6289, 7.6289] +24-11-19 19:00:55 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:00:55 | D | sum error = [ 45.1771, 48.2119, 51.4340, 54.8725, 58.4748] +24-11-19 19:00:55 | D | best error = [ 7.6289, 7.6289, 7.6289, 7.6289, 7.6289] +24-11-19 19:00:55 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:00:55 | D | sum error = [ 62.3059, 66.3515, 70.6754, 75.2014, 80.0120] +24-11-19 19:00:55 | D | best error = [ 7.6289, 7.6289, 7.6289, 7.6289, 7.6289] +24-11-19 19:00:55 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:00:55 | D | sum error = [ 85.0875, 90.4900, 96.1737, 102.2025, 108.5780] +24-11-19 19:00:55 | D | best error = [ 7.6289, 7.6289, 7.6289, 7.6289, 7.6289] +24-11-19 19:00:55 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:00:55 | D | sum error = [ 115.2923, 122.4208, 129.8785, 137.7788, 146.1051] +24-11-19 19:00:55 | D | best error = [ 7.6289, 7.6289, 7.6289, 7.6289, 7.6289] +24-11-19 19:00:55 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:00:55 | D | sum error = [ 154.8552, 164.0638, 173.7661, 184.0217, 194.7750] +24-11-19 19:00:55 | D | best error = [ 7.6289, 7.6289, 7.6289, 7.6289, 7.6289] +24-11-19 19:00:55 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:00:55 | D | sum error = [ 206.0436, 217.9107, 230.3620, 243.4271, 257.1208] +24-11-19 19:00:55 | D | best error = [ 7.6289, 7.6289, 7.6289, 7.6289, 7.6289] +24-11-19 19:00:55 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:00:55 | D | sum error = [ 271.4771, 286.4874, 302.2060, 318.6268, 335.7859] +24-11-19 19:00:55 | D | best error = [ 7.6289, 7.6289, 7.6289, 7.6289, 7.6289] +24-11-19 19:00:55 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:00:55 | D | sum error = [ 353.7419, 372.4614, 391.9792, 412.3473, 433.5226] +24-11-19 19:00:55 | D | best error = [ 7.6289, 7.6289, 7.6289, 7.6289, 7.6289] +24-11-19 19:00:55 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:00:55 | D | sum error = [ 455.5800, 478.4815, 502.2455, 526.8746, 552.4140] +24-11-19 19:00:55 | D | best error = [ 7.6289, 7.6289, 7.6289, 7.6289, 7.6289] +24-11-19 19:00:55 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:00:55 | D | sum error = [ 578.7895, 606.0565, 634.2175, 663.2334, 693.1630] +24-11-19 19:00:55 | D | best error = [ 7.6289, 7.6289, 7.6289, 7.6289, 7.6289] +24-11-19 19:00:55 | D | + error = [7.6289] +24-11-19 19:00:55 | D | - Calibrating model.layers.19.mlp.down_proj.weight +24-11-19 19:00:55 | D | + w: sint8 +24-11-19 19:00:55 | D | + x: None +24-11-19 19:00:55 | D | + y: None +24-11-19 19:00:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:00:55 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:00:55 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:00:55 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:00:55 | D | - range ratio = [ 1.0000] +24-11-19 19:00:55 | D | sum error = [ 0.9893] +24-11-19 19:00:55 | D | best error = [ 0.9893] +24-11-19 19:00:56 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:00:56 | D | sum error = [ 0.9835, 0.9754, 0.9692, 0.9637, 0.9633] +24-11-19 19:00:56 | D | best error = [ 0.9520, 0.9325, 0.9196, 0.9091, 0.9011] +24-11-19 19:00:56 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:00:56 | D | sum error = [ 0.9638, 0.9674, 0.9747, 0.9846, 0.9998] +24-11-19 19:00:56 | D | best error = [ 0.8951, 0.8900, 0.8860, 0.8832, 0.8809] +24-11-19 19:00:56 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:00:56 | D | sum error = [ 1.0199, 1.0462, 1.0778, 1.1125, 1.1565] +24-11-19 19:00:56 | D | best error = [ 0.8792, 0.8780, 0.8775, 0.8769, 0.8766] +24-11-19 19:00:56 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:00:56 | D | sum error = [ 1.2058, 1.2615, 1.3247, 1.3957, 1.4770] +24-11-19 19:00:56 | D | best error = [ 0.8763, 0.8762, 0.8761, 0.8760, 0.8760] +24-11-19 19:00:56 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:00:56 | D | sum error = [ 1.5649, 1.6606, 1.7651, 1.8797, 2.0054] +24-11-19 19:00:56 | D | best error = [ 0.8760, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 19:00:56 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:00:56 | D | sum error = [ 2.1372, 2.2858, 2.4423, 2.6090, 2.7918] +24-11-19 19:00:56 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 19:00:56 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:00:56 | D | sum error = [ 2.9842, 3.1908, 3.4138, 3.6485, 3.9003] +24-11-19 19:00:56 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 19:00:56 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:00:56 | D | sum error = [ 4.1663, 4.4508, 4.7537, 5.0750, 5.4137] +24-11-19 19:00:56 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 19:00:56 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:00:56 | D | sum error = [ 5.7747, 6.1567, 6.5608, 6.9886, 7.4418] +24-11-19 19:00:56 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 19:00:56 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:00:56 | D | sum error = [ 7.9199, 8.4233, 8.9566, 9.5167, 10.1085] +24-11-19 19:00:56 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 19:00:56 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:00:56 | D | sum error = [ 10.7301, 11.3871, 12.0746, 12.7994, 13.5581] +24-11-19 19:00:56 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 19:00:56 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:00:56 | D | sum error = [ 14.3566, 15.1944, 16.0726, 16.9917, 17.9538] +24-11-19 19:00:56 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 19:00:56 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:00:56 | D | sum error = [ 18.9604, 20.0147, 21.1154, 22.2631, 23.4604] +24-11-19 19:00:56 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 19:00:56 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:00:56 | D | sum error = [ 24.7086, 26.0095, 27.3621, 28.7709, 30.2335] +24-11-19 19:00:56 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 19:00:56 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:00:56 | D | sum error = [ 31.7533, 33.3332, 34.9727, 36.6728, 38.4355] +24-11-19 19:00:56 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 19:00:56 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:00:56 | D | sum error = [ 40.2618, 42.1521, 44.1077, 46.1276, 48.2115] +24-11-19 19:00:56 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 19:00:56 | D | + error = [0.8759] +24-11-19 19:00:57 | D | - Quantizing model.layers.19.self_attn.q_proj.weight +24-11-19 19:00:57 | D | - Quantizing model.layers.19.self_attn.k_proj.weight +24-11-19 19:00:58 | D | - Quantizing model.layers.19.self_attn.v_proj.weight +24-11-19 19:00:59 | D | - Quantizing model.layers.19.self_attn.o_proj.weight +24-11-19 19:01:00 | D | - Quantizing model.layers.19.mlp.up_proj.weight +24-11-19 19:01:01 | D | - Quantizing model.layers.19.mlp.gate_proj.weight +24-11-19 19:01:02 | D | - Quantizing model.layers.19.mlp.down_proj.weight +24-11-19 19:01:11 | D | - Quantizing layer model.layers.20 +24-11-19 19:01:11 | D | - Calibrating model.layers.20.self_attn.q_proj.weight +24-11-19 19:01:11 | D | + w: sint8 +24-11-19 19:01:11 | D | + x: None +24-11-19 19:01:11 | D | + y: None +24-11-19 19:01:11 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:01:11 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:01:11 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:01:12 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:01:12 | D | - range ratio = [ 1.0000] +24-11-19 19:01:12 | D | sum error = [ 3.8876] +24-11-19 19:01:12 | D | best error = [ 3.8876] +24-11-19 19:01:24 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:01:24 | D | sum error = [ 3.8332, 3.8452, 3.8523, 3.9365, 3.9898] +24-11-19 19:01:24 | D | best error = [ 3.8332, 3.8332, 3.8332, 3.8332, 3.8332] +24-11-19 19:01:24 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:01:24 | D | sum error = [ 4.1030, 4.3147, 4.4450, 4.6628, 4.8763] +24-11-19 19:01:24 | D | best error = [ 3.8332, 3.8332, 3.8332, 3.8332, 3.8332] +24-11-19 19:01:24 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:01:24 | D | sum error = [ 5.1391, 5.4766, 5.9863, 6.4666, 7.0303] +24-11-19 19:01:24 | D | best error = [ 3.8332, 3.8332, 3.8332, 3.8332, 3.8332] +24-11-19 19:01:24 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:01:24 | D | sum error = [ 7.7344, 8.1971, 8.8373, 10.0256, 10.7699] +24-11-19 19:01:24 | D | best error = [ 3.8332, 3.8332, 3.8332, 3.8332, 3.8332] +24-11-19 19:01:24 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:01:24 | D | sum error = [ 11.8670, 13.2121, 14.5375, 16.1096, 17.3969] +24-11-19 19:01:24 | D | best error = [ 3.8332, 3.8332, 3.8332, 3.8332, 3.8332] +24-11-19 19:01:24 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:01:24 | D | sum error = [ 19.3326, 21.4387, 23.5265, 25.7685, 28.5547] +24-11-19 19:01:24 | D | best error = [ 3.8332, 3.8332, 3.8332, 3.8332, 3.8332] +24-11-19 19:01:24 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:01:24 | D | sum error = [ 31.2030, 34.4129, 37.8154, 41.5930, 45.7464] +24-11-19 19:01:24 | D | best error = [ 3.8332, 3.8332, 3.8332, 3.8332, 3.8332] +24-11-19 19:01:24 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:01:24 | D | sum error = [ 50.6557, 55.6318, 61.2479, 67.5029, 74.3612] +24-11-19 19:01:24 | D | best error = [ 3.8332, 3.8332, 3.8332, 3.8332, 3.8332] +24-11-19 19:01:24 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:01:24 | D | sum error = [ 81.6114, 89.5035, 98.4856, 107.1832, 117.6868] +24-11-19 19:01:24 | D | best error = [ 3.8332, 3.8332, 3.8332, 3.8332, 3.8332] +24-11-19 19:01:24 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:01:24 | D | sum error = [ 129.3590, 141.6191, 155.9553, 170.8480, 187.4404] +24-11-19 19:01:24 | D | best error = [ 3.8332, 3.8332, 3.8332, 3.8332, 3.8332] +24-11-19 19:01:24 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:01:24 | D | sum error = [ 205.6359, 226.4329, 247.9940, 272.1835, 299.1896] +24-11-19 19:01:24 | D | best error = [ 3.8332, 3.8332, 3.8332, 3.8332, 3.8332] +24-11-19 19:01:24 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:01:24 | D | sum error = [ 328.3000, 360.6359, 396.8730, 436.5728, 480.3876] +24-11-19 19:01:24 | D | best error = [ 3.8332, 3.8332, 3.8332, 3.8332, 3.8332] +24-11-19 19:01:24 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:01:24 | D | sum error = [ 529.1299, 582.9179, 641.8571, 709.0922, 781.6383] +24-11-19 19:01:24 | D | best error = [ 3.8332, 3.8332, 3.8332, 3.8332, 3.8332] +24-11-19 19:01:24 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:01:24 | D | sum error = [ 862.8207, 950.8718, 1048.9571, 1155.4436, 1270.6406] +24-11-19 19:01:24 | D | best error = [ 3.8332, 3.8332, 3.8332, 3.8332, 3.8332] +24-11-19 19:01:24 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:01:24 | D | sum error = [ 1397.7511, 1536.0063, 1684.2224, 1842.5239, 2011.6516] +24-11-19 19:01:24 | D | best error = [ 3.8332, 3.8332, 3.8332, 3.8332, 3.8332] +24-11-19 19:01:24 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:01:24 | D | sum error = [ 2186.7045, 2364.9074, 2546.8049, 2727.6446, 2905.6259] +24-11-19 19:01:24 | D | best error = [ 3.8332, 3.8332, 3.8332, 3.8332, 3.8332] +24-11-19 19:01:24 | D | + error = [3.8332] +24-11-19 19:01:24 | D | - Calibrating model.layers.20.self_attn.k_proj.weight +24-11-19 19:01:24 | D | + w: sint8 +24-11-19 19:01:24 | D | + x: None +24-11-19 19:01:24 | D | + y: None +24-11-19 19:01:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:01:24 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:01:24 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:01:24 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:01:24 | D | - range ratio = [ 1.0000] +24-11-19 19:01:24 | D | sum error = [ 3.9182] +24-11-19 19:01:24 | D | best error = [ 3.9182] +24-11-19 19:01:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:01:36 | D | sum error = [ 3.8892, 3.8192, 3.9948, 3.7042, 3.9100] +24-11-19 19:01:36 | D | best error = [ 3.8892, 3.8192, 3.8192, 3.7042, 3.7042] +24-11-19 19:01:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:01:36 | D | sum error = [ 4.0549, 4.5596, 4.6236, 4.9815, 5.8555] +24-11-19 19:01:36 | D | best error = [ 3.7042, 3.7042, 3.7042, 3.7042, 3.7042] +24-11-19 19:01:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:01:36 | D | sum error = [ 5.3344, 6.5960, 7.6250, 7.3420, 9.6270] +24-11-19 19:01:36 | D | best error = [ 3.7042, 3.7042, 3.7042, 3.7042, 3.7042] +24-11-19 19:01:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:01:36 | D | sum error = [ 9.1379, 9.8977, 11.1011, 13.0930, 11.8288] +24-11-19 19:01:36 | D | best error = [ 3.7042, 3.7042, 3.7042, 3.7042, 3.7042] +24-11-19 19:01:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:01:36 | D | sum error = [ 14.0667, 14.4908, 16.4779, 17.2621, 18.3539] +24-11-19 19:01:36 | D | best error = [ 3.7042, 3.7042, 3.7042, 3.7042, 3.7042] +24-11-19 19:01:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:01:36 | D | sum error = [ 19.2690, 20.4684, 21.8447, 24.3991, 26.8319] +24-11-19 19:01:36 | D | best error = [ 3.7042, 3.7042, 3.7042, 3.7042, 3.7042] +24-11-19 19:01:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:01:36 | D | sum error = [ 29.9138, 33.0773, 37.0641, 38.8151, 41.8896] +24-11-19 19:01:36 | D | best error = [ 3.7042, 3.7042, 3.7042, 3.7042, 3.7042] +24-11-19 19:01:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:01:36 | D | sum error = [ 47.8965, 51.7216, 55.2994, 59.8164, 65.7461] +24-11-19 19:01:36 | D | best error = [ 3.7042, 3.7042, 3.7042, 3.7042, 3.7042] +24-11-19 19:01:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:01:36 | D | sum error = [ 70.0347, 75.6270, 83.4162, 90.4330, 99.0258] +24-11-19 19:01:36 | D | best error = [ 3.7042, 3.7042, 3.7042, 3.7042, 3.7042] +24-11-19 19:01:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:01:36 | D | sum error = [ 107.9685, 117.5471, 129.6091, 140.4962, 153.7462] +24-11-19 19:01:36 | D | best error = [ 3.7042, 3.7042, 3.7042, 3.7042, 3.7042] +24-11-19 19:01:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:01:36 | D | sum error = [ 168.2359, 184.9960, 203.0848, 222.4920, 244.8478] +24-11-19 19:01:36 | D | best error = [ 3.7042, 3.7042, 3.7042, 3.7042, 3.7042] +24-11-19 19:01:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:01:36 | D | sum error = [ 268.5875, 295.6119, 325.6173, 357.4713, 396.2916] +24-11-19 19:01:36 | D | best error = [ 3.7042, 3.7042, 3.7042, 3.7042, 3.7042] +24-11-19 19:01:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:01:36 | D | sum error = [ 438.0960, 486.0836, 537.7151, 597.2336, 668.5144] +24-11-19 19:01:36 | D | best error = [ 3.7042, 3.7042, 3.7042, 3.7042, 3.7042] +24-11-19 19:01:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:01:36 | D | sum error = [ 739.8350, 825.3620, 918.4486, 1015.4144, 1131.6977] +24-11-19 19:01:36 | D | best error = [ 3.7042, 3.7042, 3.7042, 3.7042, 3.7042] +24-11-19 19:01:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:01:36 | D | sum error = [ 1255.0451, 1390.7462, 1535.6328, 1688.1453, 1850.7039] +24-11-19 19:01:36 | D | best error = [ 3.7042, 3.7042, 3.7042, 3.7042, 3.7042] +24-11-19 19:01:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:01:36 | D | sum error = [ 2033.2753, 2221.4441, 2406.9605, 2587.8197, 2773.8585] +24-11-19 19:01:36 | D | best error = [ 3.7042, 3.7042, 3.7042, 3.7042, 3.7042] +24-11-19 19:01:36 | D | + error = [3.7042] +24-11-19 19:01:36 | D | - Calibrating model.layers.20.self_attn.v_proj.weight +24-11-19 19:01:36 | D | + w: sint8 +24-11-19 19:01:36 | D | + x: None +24-11-19 19:01:36 | D | + y: None +24-11-19 19:01:36 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:01:36 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:01:36 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:01:36 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:01:36 | D | - range ratio = [ 1.0000] +24-11-19 19:01:36 | D | sum error = [ 1.7734] +24-11-19 19:01:36 | D | best error = [ 1.7734] +24-11-19 19:01:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:01:36 | D | sum error = [ 1.7581, 1.7438, 1.7642, 1.7670, 1.8085] +24-11-19 19:01:36 | D | best error = [ 1.6386, 1.5846, 1.5591, 1.5451, 1.5364] +24-11-19 19:01:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:01:36 | D | sum error = [ 1.8774, 1.9164, 2.0073, 2.0976, 2.2089] +24-11-19 19:01:36 | D | best error = [ 1.5332, 1.5322, 1.5313, 1.5309, 1.5309] +24-11-19 19:01:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:01:36 | D | sum error = [ 2.3411, 2.5019, 2.6577, 2.8426, 3.0288] +24-11-19 19:01:36 | D | best error = [ 1.5309, 1.5309, 1.5309, 1.5309, 1.5309] +24-11-19 19:01:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:01:36 | D | sum error = [ 3.2549, 3.4785, 3.7390, 4.0024, 4.3063] +24-11-19 19:01:36 | D | best error = [ 1.5309, 1.5309, 1.5309, 1.5309, 1.5309] +24-11-19 19:01:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:01:36 | D | sum error = [ 4.5965, 4.9113, 5.2878, 5.6585, 6.0506] +24-11-19 19:01:36 | D | best error = [ 1.5309, 1.5309, 1.5309, 1.5309, 1.5309] +24-11-19 19:01:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:01:36 | D | sum error = [ 6.4593, 6.9312, 7.3973, 7.8912, 8.4277] +24-11-19 19:01:36 | D | best error = [ 1.5309, 1.5309, 1.5309, 1.5309, 1.5309] +24-11-19 19:01:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:01:36 | D | sum error = [ 8.9734, 9.5765, 10.1879, 10.8319, 11.5142] +24-11-19 19:01:36 | D | best error = [ 1.5309, 1.5309, 1.5309, 1.5309, 1.5309] +24-11-19 19:01:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:01:36 | D | sum error = [ 12.2358, 13.0084, 13.7885, 14.6184, 15.4933] +24-11-19 19:01:36 | D | best error = [ 1.5309, 1.5309, 1.5309, 1.5309, 1.5309] +24-11-19 19:01:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:01:36 | D | sum error = [ 16.4090, 17.3815, 18.3991, 19.4508, 20.5692] +24-11-19 19:01:36 | D | best error = [ 1.5309, 1.5309, 1.5309, 1.5309, 1.5309] +24-11-19 19:01:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:01:36 | D | sum error = [ 21.7318, 22.9575, 24.2358, 25.5712, 26.9723] +24-11-19 19:01:36 | D | best error = [ 1.5309, 1.5309, 1.5309, 1.5309, 1.5309] +24-11-19 19:01:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:01:36 | D | sum error = [ 28.4515, 29.9865, 31.5790, 33.2401, 34.9746] +24-11-19 19:01:36 | D | best error = [ 1.5309, 1.5309, 1.5309, 1.5309, 1.5309] +24-11-19 19:01:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:01:36 | D | sum error = [ 36.7753, 38.6536, 40.6086, 42.6396, 44.7586] +24-11-19 19:01:36 | D | best error = [ 1.5309, 1.5309, 1.5309, 1.5309, 1.5309] +24-11-19 19:01:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:01:36 | D | sum error = [ 46.9633, 49.2417, 51.6177, 54.0614, 56.6112] +24-11-19 19:01:36 | D | best error = [ 1.5309, 1.5309, 1.5309, 1.5309, 1.5309] +24-11-19 19:01:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:01:36 | D | sum error = [ 59.2582, 61.9888, 64.8259, 67.7660, 70.8089] +24-11-19 19:01:36 | D | best error = [ 1.5309, 1.5309, 1.5309, 1.5309, 1.5309] +24-11-19 19:01:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:01:36 | D | sum error = [ 73.9648, 77.2173, 80.5846, 84.0489, 87.6264] +24-11-19 19:01:36 | D | best error = [ 1.5309, 1.5309, 1.5309, 1.5309, 1.5309] +24-11-19 19:01:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:01:36 | D | sum error = [ 91.3160, 95.0974, 98.9974, 102.9924, 107.1096] +24-11-19 19:01:36 | D | best error = [ 1.5309, 1.5309, 1.5309, 1.5309, 1.5309] +24-11-19 19:01:36 | D | + error = [1.5309] +24-11-19 19:01:36 | D | - Calibrating model.layers.20.self_attn.o_proj.weight +24-11-19 19:01:36 | D | + w: sint8 +24-11-19 19:01:36 | D | + x: None +24-11-19 19:01:36 | D | + y: None +24-11-19 19:01:36 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:01:36 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:01:37 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:01:37 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:01:37 | D | - range ratio = [ 1.0000] +24-11-19 19:01:37 | D | sum error = [ 0.3942] +24-11-19 19:01:37 | D | best error = [ 0.3942] +24-11-19 19:01:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:01:37 | D | sum error = [ 0.3909, 0.3897, 0.3907, 0.3927, 0.3999] +24-11-19 19:01:37 | D | best error = [ 0.3712, 0.3608, 0.3546, 0.3502, 0.3477] +24-11-19 19:01:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:01:37 | D | sum error = [ 0.4069, 0.4172, 0.4312, 0.4465, 0.4671] +24-11-19 19:01:37 | D | best error = [ 0.3459, 0.3447, 0.3439, 0.3432, 0.3428] +24-11-19 19:01:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:01:37 | D | sum error = [ 0.4899, 0.5137, 0.5443, 0.5763, 0.6105] +24-11-19 19:01:37 | D | best error = [ 0.3426, 0.3424, 0.3423, 0.3422, 0.3422] +24-11-19 19:01:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:01:37 | D | sum error = [ 0.6510, 0.6930, 0.7384, 0.7868, 0.8398] +24-11-19 19:01:37 | D | best error = [ 0.3421, 0.3421, 0.3421, 0.3420, 0.3420] +24-11-19 19:01:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:01:37 | D | sum error = [ 0.8961, 0.9556, 1.0189, 1.0869, 1.1585] +24-11-19 19:01:37 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 19:01:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:01:37 | D | sum error = [ 1.2344, 1.3140, 1.3992, 1.4895, 1.5835] +24-11-19 19:01:37 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 19:01:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:01:37 | D | sum error = [ 1.6841, 1.7883, 1.9002, 2.0169, 2.1411] +24-11-19 19:01:37 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 19:01:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:01:37 | D | sum error = [ 2.2701, 2.4064, 2.5504, 2.7023, 2.8603] +24-11-19 19:01:37 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 19:01:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:01:37 | D | sum error = [ 3.0276, 3.2009, 3.3839, 3.5761, 3.7783] +24-11-19 19:01:37 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 19:01:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:01:37 | D | sum error = [ 3.9885, 4.2090, 4.4408, 4.6820, 4.9354] +24-11-19 19:01:37 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 19:01:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:01:37 | D | sum error = [ 5.1999, 5.4766, 5.7644, 6.0661, 6.3809] +24-11-19 19:01:37 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 19:01:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:01:37 | D | sum error = [ 6.7103, 7.0530, 7.4101, 7.7828, 8.1707] +24-11-19 19:01:37 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 19:01:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:01:37 | D | sum error = [ 8.5758, 8.9964, 9.4341, 9.8904, 10.3638] +24-11-19 19:01:37 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 19:01:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:01:37 | D | sum error = [ 10.8554, 11.3656, 11.8949, 12.4446, 13.0126] +24-11-19 19:01:37 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 19:01:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:01:37 | D | sum error = [ 13.6006, 14.2093, 14.8390, 15.4908, 16.1644] +24-11-19 19:01:37 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 19:01:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:01:37 | D | sum error = [ 16.8610, 17.5809, 18.3234, 19.0894, 19.8787] +24-11-19 19:01:37 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 19:01:37 | D | + error = [0.3420] +24-11-19 19:01:37 | D | - Calibrating model.layers.20.mlp.up_proj.weight +24-11-19 19:01:37 | D | + w: sint8 +24-11-19 19:01:37 | D | + x: None +24-11-19 19:01:37 | D | + y: None +24-11-19 19:01:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:01:37 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:01:37 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:01:37 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:01:37 | D | - range ratio = [ 1.0000] +24-11-19 19:01:37 | D | sum error = [ 6.7130] +24-11-19 19:01:37 | D | best error = [ 6.7130] +24-11-19 19:01:39 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:01:39 | D | sum error = [ 6.6596, 6.6498, 6.6917, 6.7609, 6.8796] +24-11-19 19:01:39 | D | best error = [ 6.2415, 6.0588, 5.9609, 5.9070, 5.8777] +24-11-19 19:01:39 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:01:39 | D | sum error = [ 7.0657, 7.3001, 7.6011, 7.9472, 8.3616] +24-11-19 19:01:39 | D | best error = [ 5.8637, 5.8577, 5.8559, 5.8554, 5.8553] +24-11-19 19:01:39 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:01:39 | D | sum error = [ 8.8514, 9.3928, 9.9933, 10.6768, 11.4227] +24-11-19 19:01:39 | D | best error = [ 5.8553, 5.8553, 5.8553, 5.8553, 5.8553] +24-11-19 19:01:39 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:01:39 | D | sum error = [ 12.2096, 13.0857, 14.0369, 15.0242, 16.1101] +24-11-19 19:01:39 | D | best error = [ 5.8553, 5.8553, 5.8553, 5.8553, 5.8553] +24-11-19 19:01:39 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:01:39 | D | sum error = [ 17.2630, 18.4870, 19.7820, 21.1575, 22.6246] +24-11-19 19:01:39 | D | best error = [ 5.8553, 5.8553, 5.8553, 5.8553, 5.8553] +24-11-19 19:01:39 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:01:39 | D | sum error = [ 24.1823, 25.8154, 27.5715, 29.3924, 31.3219] +24-11-19 19:01:39 | D | best error = [ 5.8553, 5.8553, 5.8553, 5.8553, 5.8553] +24-11-19 19:01:39 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:01:39 | D | sum error = [ 33.3658, 35.5101, 37.7794, 40.1736, 42.6909] +24-11-19 19:01:39 | D | best error = [ 5.8553, 5.8553, 5.8553, 5.8553, 5.8553] +24-11-19 19:01:39 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:01:39 | D | sum error = [ 45.3058, 48.0826, 50.9989, 54.0418, 57.2413] +24-11-19 19:01:39 | D | best error = [ 5.8553, 5.8553, 5.8553, 5.8553, 5.8553] +24-11-19 19:01:39 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:01:39 | D | sum error = [ 60.5992, 64.1207, 67.7983, 71.6575, 75.7003] +24-11-19 19:01:39 | D | best error = [ 5.8553, 5.8553, 5.8553, 5.8553, 5.8553] +24-11-19 19:01:39 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:01:39 | D | sum error = [ 79.9194, 84.3377, 88.9364, 93.7347, 98.7489] +24-11-19 19:01:39 | D | best error = [ 5.8553, 5.8553, 5.8553, 5.8553, 5.8553] +24-11-19 19:01:39 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:01:39 | D | sum error = [ 103.9692, 109.4227, 115.0949, 121.0242, 127.1723] +24-11-19 19:01:39 | D | best error = [ 5.8553, 5.8553, 5.8553, 5.8553, 5.8553] +24-11-19 19:01:39 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:01:39 | D | sum error = [ 133.5755, 140.2179, 147.1306, 154.2761, 161.7121] +24-11-19 19:01:39 | D | best error = [ 5.8553, 5.8553, 5.8553, 5.8553, 5.8553] +24-11-19 19:01:39 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:01:39 | D | sum error = [ 169.4178, 177.4102, 185.6889, 194.2585, 203.1353] +24-11-19 19:01:39 | D | best error = [ 5.8553, 5.8553, 5.8553, 5.8553, 5.8553] +24-11-19 19:01:39 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:01:39 | D | sum error = [ 212.2989, 221.7831, 231.5746, 241.6946, 252.1263] +24-11-19 19:01:39 | D | best error = [ 5.8553, 5.8553, 5.8553, 5.8553, 5.8553] +24-11-19 19:01:39 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:01:39 | D | sum error = [ 262.9022, 274.0066, 285.4524, 297.2414, 309.3824] +24-11-19 19:01:39 | D | best error = [ 5.8553, 5.8553, 5.8553, 5.8553, 5.8553] +24-11-19 19:01:39 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:01:39 | D | sum error = [ 321.8855, 334.7485, 347.9761, 361.5689, 375.5350] +24-11-19 19:01:39 | D | best error = [ 5.8553, 5.8553, 5.8553, 5.8553, 5.8553] +24-11-19 19:01:39 | D | + error = [5.8553] +24-11-19 19:01:39 | D | - Calibrating model.layers.20.mlp.gate_proj.weight +24-11-19 19:01:39 | D | + w: sint8 +24-11-19 19:01:39 | D | + x: None +24-11-19 19:01:39 | D | + y: None +24-11-19 19:01:39 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:01:39 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:01:39 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:01:39 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:01:39 | D | - range ratio = [ 1.0000] +24-11-19 19:01:39 | D | sum error = [ 9.0699] +24-11-19 19:01:39 | D | best error = [ 9.0699] +24-11-19 19:01:40 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:01:40 | D | sum error = [ 8.9872, 8.9780, 9.0108, 9.1164, 9.2856] +24-11-19 19:01:40 | D | best error = [ 8.4128, 8.1688, 8.0398, 7.9666, 7.9271] +24-11-19 19:01:40 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:01:40 | D | sum error = [ 9.5323, 9.8504, 10.2555, 10.7275, 11.3057] +24-11-19 19:01:40 | D | best error = [ 7.9087, 7.9010, 7.8980, 7.8969, 7.8966] +24-11-19 19:01:40 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:01:40 | D | sum error = [ 11.9359, 12.6701, 13.5204, 14.4279, 15.4428] +24-11-19 19:01:40 | D | best error = [ 7.8966, 7.8966, 7.8966, 7.8966, 7.8966] +24-11-19 19:01:40 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:01:40 | D | sum error = [ 16.5344, 17.7013, 19.0071, 20.3584, 21.8506] +24-11-19 19:01:40 | D | best error = [ 7.8966, 7.8966, 7.8966, 7.8966, 7.8966] +24-11-19 19:01:40 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:01:40 | D | sum error = [ 23.4203, 25.0953, 26.9035, 28.8105, 30.8713] +24-11-19 19:01:40 | D | best error = [ 7.8966, 7.8966, 7.8966, 7.8966, 7.8966] +24-11-19 19:01:40 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:01:40 | D | sum error = [ 33.0290, 35.3436, 37.7804, 40.3978, 43.1419] +24-11-19 19:01:40 | D | best error = [ 7.8966, 7.8966, 7.8966, 7.8966, 7.8966] +24-11-19 19:01:40 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:01:40 | D | sum error = [ 46.0813, 49.2018, 52.4725, 55.9556, 59.6396] +24-11-19 19:01:40 | D | best error = [ 7.8966, 7.8966, 7.8966, 7.8966, 7.8966] +24-11-19 19:01:40 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:01:40 | D | sum error = [ 63.5450, 67.6753, 72.0345, 76.6629, 81.5510] +24-11-19 19:01:40 | D | best error = [ 7.8966, 7.8966, 7.8966, 7.8966, 7.8966] +24-11-19 19:01:40 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:01:40 | D | sum error = [ 86.7035, 92.1716, 97.9536, 104.0569, 110.4899] +24-11-19 19:01:40 | D | best error = [ 7.8966, 7.8966, 7.8966, 7.8966, 7.8966] +24-11-19 19:01:40 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:01:40 | D | sum error = [ 117.2960, 124.4795, 132.0229, 139.9723, 148.3736] +24-11-19 19:01:40 | D | best error = [ 7.8966, 7.8966, 7.8966, 7.8966, 7.8966] +24-11-19 19:01:40 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:01:40 | D | sum error = [ 157.2034, 166.4977, 176.2494, 186.5423, 197.3468] +24-11-19 19:01:40 | D | best error = [ 7.8966, 7.8966, 7.8966, 7.8966, 7.8966] +24-11-19 19:01:40 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:01:40 | D | sum error = [ 208.6606, 220.5610, 233.0890, 246.1919, 259.9389] +24-11-19 19:01:40 | D | best error = [ 7.8966, 7.8966, 7.8966, 7.8966, 7.8966] +24-11-19 19:01:40 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:01:40 | D | sum error = [ 274.3422, 289.3712, 305.1308, 321.5877, 338.7869] +24-11-19 19:01:40 | D | best error = [ 7.8966, 7.8966, 7.8966, 7.8966, 7.8966] +24-11-19 19:01:40 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:01:40 | D | sum error = [ 356.7539, 375.4865, 395.0030, 415.3112, 436.4232] +24-11-19 19:01:40 | D | best error = [ 7.8966, 7.8966, 7.8966, 7.8966, 7.8966] +24-11-19 19:01:40 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:01:40 | D | sum error = [ 458.3662, 481.1698, 504.8430, 529.3762, 554.7920] +24-11-19 19:01:40 | D | best error = [ 7.8966, 7.8966, 7.8966, 7.8966, 7.8966] +24-11-19 19:01:40 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:01:40 | D | sum error = [ 581.0556, 608.2157, 636.2634, 665.2253, 695.0729] +24-11-19 19:01:40 | D | best error = [ 7.8966, 7.8966, 7.8966, 7.8966, 7.8966] +24-11-19 19:01:40 | D | + error = [7.8966] +24-11-19 19:01:40 | D | - Calibrating model.layers.20.mlp.down_proj.weight +24-11-19 19:01:40 | D | + w: sint8 +24-11-19 19:01:40 | D | + x: None +24-11-19 19:01:40 | D | + y: None +24-11-19 19:01:40 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:01:40 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:01:40 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:01:40 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:01:41 | D | - range ratio = [ 1.0000] +24-11-19 19:01:41 | D | sum error = [ 1.0446] +24-11-19 19:01:41 | D | best error = [ 1.0446] +24-11-19 19:01:42 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:01:42 | D | sum error = [ 1.0353, 1.0262, 1.0177, 1.0130, 1.0125] +24-11-19 19:01:42 | D | best error = [ 1.0019, 0.9806, 0.9655, 0.9548, 0.9461] +24-11-19 19:01:42 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:01:42 | D | sum error = [ 1.0127, 1.0173, 1.0231, 1.0326, 1.0463] +24-11-19 19:01:42 | D | best error = [ 0.9390, 0.9335, 0.9291, 0.9257, 0.9229] +24-11-19 19:01:42 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:01:42 | D | sum error = [ 1.0693, 1.0918, 1.1249, 1.1632, 1.2052] +24-11-19 19:01:42 | D | best error = [ 0.9213, 0.9201, 0.9193, 0.9187, 0.9184] +24-11-19 19:01:42 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:01:42 | D | sum error = [ 1.2558, 1.3140, 1.3809, 1.4551, 1.5368] +24-11-19 19:01:42 | D | best error = [ 0.9180, 0.9179, 0.9179, 0.9178, 0.9178] +24-11-19 19:01:42 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:01:42 | D | sum error = [ 1.6304, 1.7329, 1.8441, 1.9642, 2.0996] +24-11-19 19:01:42 | D | best error = [ 0.9178, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 19:01:42 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:01:42 | D | sum error = [ 2.2418, 2.3991, 2.5661, 2.7460, 2.9385] +24-11-19 19:01:42 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 19:01:42 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:01:42 | D | sum error = [ 3.1432, 3.3639, 3.6002, 3.8499, 4.1184] +24-11-19 19:01:42 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 19:01:42 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:01:42 | D | sum error = [ 4.4010, 4.7032, 5.0230, 5.3621, 5.7212] +24-11-19 19:01:42 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 19:01:42 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:01:42 | D | sum error = [ 6.1033, 6.5042, 6.9303, 7.3818, 7.8593] +24-11-19 19:01:42 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 19:01:42 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:01:42 | D | sum error = [ 8.3595, 8.8881, 9.4476, 10.0362, 10.6567] +24-11-19 19:01:42 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 19:01:42 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:01:42 | D | sum error = [ 11.3094, 11.9970, 12.7190, 13.4772, 14.2733] +24-11-19 19:01:42 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 19:01:42 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:01:42 | D | sum error = [ 15.1089, 15.9858, 16.9031, 17.8627, 18.8681] +24-11-19 19:01:42 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 19:01:42 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:01:42 | D | sum error = [ 19.9178, 21.0170, 22.1648, 23.3622, 24.6124] +24-11-19 19:01:42 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 19:01:42 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:01:42 | D | sum error = [ 25.9160, 27.2718, 28.6869, 30.1585, 31.6873] +24-11-19 19:01:42 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 19:01:42 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:01:42 | D | sum error = [ 33.2771, 34.9297, 36.6458, 38.4269, 40.2721] +24-11-19 19:01:42 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 19:01:42 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:01:42 | D | sum error = [ 42.1868, 44.1683, 46.2184, 48.3396, 50.5315] +24-11-19 19:01:42 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 19:01:42 | D | + error = [0.9177] +24-11-19 19:01:42 | D | - Quantizing model.layers.20.self_attn.q_proj.weight +24-11-19 19:01:43 | D | - Quantizing model.layers.20.self_attn.k_proj.weight +24-11-19 19:01:43 | D | - Quantizing model.layers.20.self_attn.v_proj.weight +24-11-19 19:01:44 | D | - Quantizing model.layers.20.self_attn.o_proj.weight +24-11-19 19:01:45 | D | - Quantizing model.layers.20.mlp.up_proj.weight +24-11-19 19:01:46 | D | - Quantizing model.layers.20.mlp.gate_proj.weight +24-11-19 19:01:47 | D | - Quantizing model.layers.20.mlp.down_proj.weight +24-11-19 19:01:57 | D | - Quantizing layer model.layers.21 +24-11-19 19:01:57 | D | - Calibrating model.layers.21.self_attn.q_proj.weight +24-11-19 19:01:57 | D | + w: sint8 +24-11-19 19:01:57 | D | + x: None +24-11-19 19:01:57 | D | + y: None +24-11-19 19:01:57 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:01:57 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:01:57 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:01:57 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:01:57 | D | - range ratio = [ 1.0000] +24-11-19 19:01:57 | D | sum error = [ 4.4470] +24-11-19 19:01:57 | D | best error = [ 4.4470] +24-11-19 19:02:09 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:02:09 | D | sum error = [ 4.4607, 4.3336, 4.4376, 4.4878, 4.5609] +24-11-19 19:02:09 | D | best error = [ 4.4470, 4.3336, 4.3336, 4.3336, 4.3336] +24-11-19 19:02:09 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:02:09 | D | sum error = [ 4.6100, 4.7426, 5.1457, 5.3217, 5.5755] +24-11-19 19:02:09 | D | best error = [ 4.3336, 4.3336, 4.3336, 4.3336, 4.3336] +24-11-19 19:02:09 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:02:09 | D | sum error = [ 5.9242, 6.2520, 6.6999, 7.1765, 7.7871] +24-11-19 19:02:09 | D | best error = [ 4.3336, 4.3336, 4.3336, 4.3336, 4.3336] +24-11-19 19:02:09 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:02:09 | D | sum error = [ 8.3523, 9.1612, 9.9084, 10.5548, 11.7010] +24-11-19 19:02:09 | D | best error = [ 4.3336, 4.3336, 4.3336, 4.3336, 4.3336] +24-11-19 19:02:09 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:02:09 | D | sum error = [ 12.7082, 13.8558, 15.0429, 16.3647, 17.8246] +24-11-19 19:02:09 | D | best error = [ 4.3336, 4.3336, 4.3336, 4.3336, 4.3336] +24-11-19 19:02:09 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:02:09 | D | sum error = [ 19.3575, 20.9974, 22.6028, 24.3804, 26.4085] +24-11-19 19:02:09 | D | best error = [ 4.3336, 4.3336, 4.3336, 4.3336, 4.3336] +24-11-19 19:02:09 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:02:09 | D | sum error = [ 28.5337, 30.9197, 33.2110, 35.9477, 38.8681] +24-11-19 19:02:09 | D | best error = [ 4.3336, 4.3336, 4.3336, 4.3336, 4.3336] +24-11-19 19:02:09 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:02:09 | D | sum error = [ 41.9836, 45.4376, 49.0337, 53.2414, 57.3668] +24-11-19 19:02:09 | D | best error = [ 4.3336, 4.3336, 4.3336, 4.3336, 4.3336] +24-11-19 19:02:09 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:02:09 | D | sum error = [ 61.8230, 67.1531, 72.5409, 78.4968, 84.9428] +24-11-19 19:02:09 | D | best error = [ 4.3336, 4.3336, 4.3336, 4.3336, 4.3336] +24-11-19 19:02:09 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:02:09 | D | sum error = [ 91.7990, 99.5794, 107.8567, 116.9239, 126.7693] +24-11-19 19:02:09 | D | best error = [ 4.3336, 4.3336, 4.3336, 4.3336, 4.3336] +24-11-19 19:02:09 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:02:09 | D | sum error = [ 137.2054, 148.6543, 161.0101, 174.4489, 188.7785] +24-11-19 19:02:09 | D | best error = [ 4.3336, 4.3336, 4.3336, 4.3336, 4.3336] +24-11-19 19:02:09 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:02:09 | D | sum error = [ 204.4020, 221.5670, 239.7852, 259.7694, 281.4601] +24-11-19 19:02:09 | D | best error = [ 4.3336, 4.3336, 4.3336, 4.3336, 4.3336] +24-11-19 19:02:09 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:02:09 | D | sum error = [ 305.4016, 330.9919, 358.7626, 388.6821, 421.3901] +24-11-19 19:02:09 | D | best error = [ 4.3336, 4.3336, 4.3336, 4.3336, 4.3336] +24-11-19 19:02:09 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:02:09 | D | sum error = [ 456.6179, 494.9377, 536.6309, 581.7456, 630.5681] +24-11-19 19:02:09 | D | best error = [ 4.3336, 4.3336, 4.3336, 4.3336, 4.3336] +24-11-19 19:02:09 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:02:09 | D | sum error = [ 683.6576, 740.3932, 801.5021, 866.7712, 936.7974] +24-11-19 19:02:09 | D | best error = [ 4.3336, 4.3336, 4.3336, 4.3336, 4.3336] +24-11-19 19:02:09 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:02:09 | D | sum error = [ 1010.7827, 1088.6598, 1169.5570, 1253.1549, 1338.0862] +24-11-19 19:02:09 | D | best error = [ 4.3336, 4.3336, 4.3336, 4.3336, 4.3336] +24-11-19 19:02:09 | D | + error = [4.3336] +24-11-19 19:02:09 | D | - Calibrating model.layers.21.self_attn.k_proj.weight +24-11-19 19:02:09 | D | + w: sint8 +24-11-19 19:02:09 | D | + x: None +24-11-19 19:02:09 | D | + y: None +24-11-19 19:02:09 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:02:09 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:02:09 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:02:09 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:02:09 | D | - range ratio = [ 1.0000] +24-11-19 19:02:09 | D | sum error = [ 4.9073] +24-11-19 19:02:09 | D | best error = [ 4.9073] +24-11-19 19:02:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:02:21 | D | sum error = [ 4.1705, 4.1612, 4.2819, 4.7729, 4.9195] +24-11-19 19:02:21 | D | best error = [ 4.1705, 4.1612, 4.1612, 4.1612, 4.1612] +24-11-19 19:02:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:02:21 | D | sum error = [ 4.3795, 4.7711, 4.8804, 5.4963, 5.9130] +24-11-19 19:02:21 | D | best error = [ 4.1612, 4.1612, 4.1612, 4.1612, 4.1612] +24-11-19 19:02:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:02:21 | D | sum error = [ 6.8707, 6.1837, 6.6008, 6.8484, 7.2472] +24-11-19 19:02:21 | D | best error = [ 4.1612, 4.1612, 4.1612, 4.1612, 4.1612] +24-11-19 19:02:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:02:21 | D | sum error = [ 8.1130, 8.8815, 9.7096, 11.1428, 11.6788] +24-11-19 19:02:21 | D | best error = [ 4.1612, 4.1612, 4.1612, 4.1612, 4.1612] +24-11-19 19:02:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:02:21 | D | sum error = [ 12.9123, 13.7918, 15.4973, 16.9487, 17.8594] +24-11-19 19:02:21 | D | best error = [ 4.1612, 4.1612, 4.1612, 4.1612, 4.1612] +24-11-19 19:02:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:02:21 | D | sum error = [ 19.5214, 22.8256, 24.7067, 26.7512, 29.3531] +24-11-19 19:02:21 | D | best error = [ 4.1612, 4.1612, 4.1612, 4.1612, 4.1612] +24-11-19 19:02:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:02:21 | D | sum error = [ 32.4348, 35.1175, 37.8610, 41.2452, 44.6282] +24-11-19 19:02:21 | D | best error = [ 4.1612, 4.1612, 4.1612, 4.1612, 4.1612] +24-11-19 19:02:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:02:21 | D | sum error = [ 47.7545, 53.2645, 57.4604, 61.9778, 68.3834] +24-11-19 19:02:21 | D | best error = [ 4.1612, 4.1612, 4.1612, 4.1612, 4.1612] +24-11-19 19:02:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:02:21 | D | sum error = [ 74.0750, 79.9070, 86.3747, 93.6017, 101.6019] +24-11-19 19:02:21 | D | best error = [ 4.1612, 4.1612, 4.1612, 4.1612, 4.1612] +24-11-19 19:02:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:02:21 | D | sum error = [ 108.9737, 117.5615, 125.6720, 135.1182, 144.2530] +24-11-19 19:02:21 | D | best error = [ 4.1612, 4.1612, 4.1612, 4.1612, 4.1612] +24-11-19 19:02:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:02:21 | D | sum error = [ 154.7762, 165.2161, 177.5536, 190.4868, 205.6022] +24-11-19 19:02:21 | D | best error = [ 4.1612, 4.1612, 4.1612, 4.1612, 4.1612] +24-11-19 19:02:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:02:21 | D | sum error = [ 220.8356, 239.1063, 255.9762, 276.9136, 299.5027] +24-11-19 19:02:21 | D | best error = [ 4.1612, 4.1612, 4.1612, 4.1612, 4.1612] +24-11-19 19:02:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:02:21 | D | sum error = [ 323.2532, 347.7700, 376.2874, 407.5392, 439.7165] +24-11-19 19:02:21 | D | best error = [ 4.1612, 4.1612, 4.1612, 4.1612, 4.1612] +24-11-19 19:02:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:02:21 | D | sum error = [ 477.4934, 516.2208, 555.5607, 599.7295, 650.6507] +24-11-19 19:02:21 | D | best error = [ 4.1612, 4.1612, 4.1612, 4.1612, 4.1612] +24-11-19 19:02:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:02:21 | D | sum error = [ 703.1790, 757.3184, 822.8280, 886.7006, 957.7282] +24-11-19 19:02:21 | D | best error = [ 4.1612, 4.1612, 4.1612, 4.1612, 4.1612] +24-11-19 19:02:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:02:21 | D | sum error = [ 1031.4401, 1106.7504, 1185.4182, 1268.3044, 1351.6912] +24-11-19 19:02:21 | D | best error = [ 4.1612, 4.1612, 4.1612, 4.1612, 4.1612] +24-11-19 19:02:21 | D | + error = [4.1612] +24-11-19 19:02:21 | D | - Calibrating model.layers.21.self_attn.v_proj.weight +24-11-19 19:02:21 | D | + w: sint8 +24-11-19 19:02:21 | D | + x: None +24-11-19 19:02:21 | D | + y: None +24-11-19 19:02:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:02:21 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:02:21 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:02:21 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:02:21 | D | - range ratio = [ 1.0000] +24-11-19 19:02:21 | D | sum error = [ 1.7953] +24-11-19 19:02:21 | D | best error = [ 1.7953] +24-11-19 19:02:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:02:21 | D | sum error = [ 1.7841, 1.7697, 1.7838, 1.8132, 1.8351] +24-11-19 19:02:21 | D | best error = [ 1.6671, 1.6124, 1.5853, 1.5722, 1.5642] +24-11-19 19:02:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:02:21 | D | sum error = [ 1.8772, 1.9553, 2.0486, 2.1259, 2.2459] +24-11-19 19:02:21 | D | best error = [ 1.5595, 1.5577, 1.5572, 1.5571, 1.5571] +24-11-19 19:02:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:02:21 | D | sum error = [ 2.3628, 2.5210, 2.7044, 2.8830, 3.0898] +24-11-19 19:02:21 | D | best error = [ 1.5571, 1.5571, 1.5571, 1.5571, 1.5571] +24-11-19 19:02:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:02:21 | D | sum error = [ 3.3169, 3.5498, 3.7951, 4.0694, 4.3748] +24-11-19 19:02:21 | D | best error = [ 1.5571, 1.5571, 1.5571, 1.5571, 1.5571] +24-11-19 19:02:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:02:21 | D | sum error = [ 4.6695, 4.9905, 5.3455, 5.7352, 6.1224] +24-11-19 19:02:21 | D | best error = [ 1.5571, 1.5571, 1.5571, 1.5571, 1.5571] +24-11-19 19:02:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:02:21 | D | sum error = [ 6.5549, 6.9931, 7.4680, 7.9595, 8.4737] +24-11-19 19:02:21 | D | best error = [ 1.5571, 1.5571, 1.5571, 1.5571, 1.5571] +24-11-19 19:02:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:02:21 | D | sum error = [ 9.0382, 9.6168, 10.2157, 10.8763, 11.5570] +24-11-19 19:02:21 | D | best error = [ 1.5571, 1.5571, 1.5571, 1.5571, 1.5571] +24-11-19 19:02:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:02:21 | D | sum error = [ 12.2718, 13.0220, 13.8284, 14.6553, 15.5374] +24-11-19 19:02:21 | D | best error = [ 1.5571, 1.5571, 1.5571, 1.5571, 1.5571] +24-11-19 19:02:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:02:21 | D | sum error = [ 16.4430, 17.4097, 18.4023, 19.4824, 20.5836] +24-11-19 19:02:21 | D | best error = [ 1.5571, 1.5571, 1.5571, 1.5571, 1.5571] +24-11-19 19:02:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:02:21 | D | sum error = [ 21.7568, 22.9694, 24.2458, 25.5767, 26.9629] +24-11-19 19:02:21 | D | best error = [ 1.5571, 1.5571, 1.5571, 1.5571, 1.5571] +24-11-19 19:02:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:02:21 | D | sum error = [ 28.4142, 29.9334, 31.5160, 33.1607, 34.8902] +24-11-19 19:02:21 | D | best error = [ 1.5571, 1.5571, 1.5571, 1.5571, 1.5571] +24-11-19 19:02:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:02:21 | D | sum error = [ 36.6780, 38.5566, 40.5079, 42.5255, 44.6413] +24-11-19 19:02:21 | D | best error = [ 1.5571, 1.5571, 1.5571, 1.5571, 1.5571] +24-11-19 19:02:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:02:21 | D | sum error = [ 46.8312, 49.1080, 51.4668, 53.9306, 56.4730] +24-11-19 19:02:21 | D | best error = [ 1.5571, 1.5571, 1.5571, 1.5571, 1.5571] +24-11-19 19:02:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:02:21 | D | sum error = [ 59.1212, 61.8585, 64.6891, 67.6320, 70.6686] +24-11-19 19:02:21 | D | best error = [ 1.5571, 1.5571, 1.5571, 1.5571, 1.5571] +24-11-19 19:02:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:02:21 | D | sum error = [ 73.8126, 77.0548, 80.4005, 83.8614, 87.4367] +24-11-19 19:02:21 | D | best error = [ 1.5571, 1.5571, 1.5571, 1.5571, 1.5571] +24-11-19 19:02:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:02:21 | D | sum error = [ 91.1149, 94.9229, 98.8395, 102.8746, 107.0252] +24-11-19 19:02:21 | D | best error = [ 1.5571, 1.5571, 1.5571, 1.5571, 1.5571] +24-11-19 19:02:21 | D | + error = [1.5571] +24-11-19 19:02:22 | D | - Calibrating model.layers.21.self_attn.o_proj.weight +24-11-19 19:02:22 | D | + w: sint8 +24-11-19 19:02:22 | D | + x: None +24-11-19 19:02:22 | D | + y: None +24-11-19 19:02:22 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:02:22 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:02:22 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:02:22 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:02:22 | D | - range ratio = [ 1.0000] +24-11-19 19:02:22 | D | sum error = [ 0.5899] +24-11-19 19:02:22 | D | best error = [ 0.5899] +24-11-19 19:02:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:02:22 | D | sum error = [ 0.5811, 0.5813, 0.5785, 0.5789, 0.5814] +24-11-19 19:02:22 | D | best error = [ 0.5376, 0.5165, 0.5027, 0.4939, 0.4874] +24-11-19 19:02:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:02:22 | D | sum error = [ 0.5869, 0.5925, 0.6038, 0.6166, 0.6325] +24-11-19 19:02:22 | D | best error = [ 0.4827, 0.4789, 0.4761, 0.4739, 0.4724] +24-11-19 19:02:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:02:22 | D | sum error = [ 0.6551, 0.6750, 0.7017, 0.7346, 0.7694] +24-11-19 19:02:22 | D | best error = [ 0.4712, 0.4703, 0.4696, 0.4690, 0.4686] +24-11-19 19:02:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:02:22 | D | sum error = [ 0.8087, 0.8539, 0.9035, 0.9549, 1.0132] +24-11-19 19:02:22 | D | best error = [ 0.4682, 0.4680, 0.4678, 0.4677, 0.4676] +24-11-19 19:02:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:02:22 | D | sum error = [ 1.0761, 1.1467, 1.2197, 1.2984, 1.3859] +24-11-19 19:02:22 | D | best error = [ 0.4675, 0.4674, 0.4673, 0.4673, 0.4672] +24-11-19 19:02:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:02:22 | D | sum error = [ 1.4738, 1.5696, 1.6724, 1.7828, 1.8996] +24-11-19 19:02:22 | D | best error = [ 0.4672, 0.4672, 0.4672, 0.4672, 0.4672] +24-11-19 19:02:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:02:22 | D | sum error = [ 2.0225, 2.1526, 2.2932, 2.4417, 2.5941] +24-11-19 19:02:22 | D | best error = [ 0.4672, 0.4672, 0.4671, 0.4671, 0.4671] +24-11-19 19:02:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:02:22 | D | sum error = [ 2.7570, 2.9296, 3.1148, 3.3086, 3.5107] +24-11-19 19:02:22 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 19:02:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:02:22 | D | sum error = [ 3.7286, 3.9552, 4.1944, 4.4462, 4.7116] +24-11-19 19:02:22 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 19:02:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:02:22 | D | sum error = [ 4.9924, 5.2889, 5.5989, 5.9255, 6.2664] +24-11-19 19:02:22 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 19:02:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:02:22 | D | sum error = [ 6.6274, 7.0028, 7.4007, 7.8171, 8.2531] +24-11-19 19:02:22 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 19:02:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:02:22 | D | sum error = [ 8.7109, 9.1887, 9.6905, 10.2147, 10.7646] +24-11-19 19:02:22 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 19:02:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:02:22 | D | sum error = [ 11.3362, 11.9325, 12.5550, 13.2026, 13.8778] +24-11-19 19:02:22 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 19:02:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:02:22 | D | sum error = [ 14.5822, 15.3138, 16.0750, 16.8669, 17.6863] +24-11-19 19:02:22 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 19:02:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:02:22 | D | sum error = [ 18.5379, 19.4221, 20.3368, 21.2852, 22.2673] +24-11-19 19:02:22 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 19:02:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:02:22 | D | sum error = [ 23.2839, 24.3365, 25.4255, 26.5496, 27.7139] +24-11-19 19:02:22 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 19:02:22 | D | + error = [0.4671] +24-11-19 19:02:22 | D | - Calibrating model.layers.21.mlp.up_proj.weight +24-11-19 19:02:22 | D | + w: sint8 +24-11-19 19:02:22 | D | + x: None +24-11-19 19:02:22 | D | + y: None +24-11-19 19:02:22 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:02:22 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:02:22 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:02:23 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:02:23 | D | - range ratio = [ 1.0000] +24-11-19 19:02:23 | D | sum error = [ 7.0072] +24-11-19 19:02:23 | D | best error = [ 7.0072] +24-11-19 19:02:24 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:02:24 | D | sum error = [ 6.9546, 6.9441, 6.9953, 7.0736, 7.1956] +24-11-19 19:02:24 | D | best error = [ 6.4870, 6.2844, 6.1807, 6.1225, 6.0909] +24-11-19 19:02:24 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:02:24 | D | sum error = [ 7.3758, 7.6330, 7.9266, 8.3272, 8.7637] +24-11-19 19:02:24 | D | best error = [ 6.0740, 6.0674, 6.0647, 6.0640, 6.0638] +24-11-19 19:02:24 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:02:24 | D | sum error = [ 9.2650, 9.8229, 10.4797, 11.1772, 11.9632] +24-11-19 19:02:24 | D | best error = [ 6.0637, 6.0637, 6.0637, 6.0637, 6.0637] +24-11-19 19:02:24 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:02:24 | D | sum error = [ 12.7782, 13.6960, 14.6623, 15.7111, 16.8587] +24-11-19 19:02:24 | D | best error = [ 6.0637, 6.0637, 6.0637, 6.0637, 6.0637] +24-11-19 19:02:24 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:02:24 | D | sum error = [ 18.0487, 19.3101, 20.6825, 22.1230, 23.6501] +24-11-19 19:02:24 | D | best error = [ 6.0637, 6.0637, 6.0637, 6.0637, 6.0637] +24-11-19 19:02:24 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:02:24 | D | sum error = [ 25.2579, 26.9903, 28.7860, 30.7265, 32.7190] +24-11-19 19:02:24 | D | best error = [ 6.0637, 6.0637, 6.0637, 6.0637, 6.0637] +24-11-19 19:02:24 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:02:24 | D | sum error = [ 34.8506, 37.1046, 39.4742, 41.9732, 44.5935] +24-11-19 19:02:24 | D | best error = [ 6.0637, 6.0637, 6.0637, 6.0637, 6.0637] +24-11-19 19:02:24 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:02:24 | D | sum error = [ 47.3343, 50.2476, 53.2815, 56.4822, 59.8298] +24-11-19 19:02:24 | D | best error = [ 6.0637, 6.0637, 6.0637, 6.0637, 6.0637] +24-11-19 19:02:24 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:02:24 | D | sum error = [ 63.3375, 67.0037, 70.8603, 74.8808, 79.1134] +24-11-19 19:02:24 | D | best error = [ 6.0637, 6.0637, 6.0637, 6.0637, 6.0637] +24-11-19 19:02:24 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:02:24 | D | sum error = [ 83.5329, 88.1413, 92.9643, 97.9966, 103.2612] +24-11-19 19:02:24 | D | best error = [ 6.0637, 6.0637, 6.0637, 6.0637, 6.0637] +24-11-19 19:02:24 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:02:24 | D | sum error = [ 108.7428, 114.4462, 120.3993, 126.5973, 133.0641] +24-11-19 19:02:24 | D | best error = [ 6.0637, 6.0637, 6.0637, 6.0637, 6.0637] +24-11-19 19:02:24 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:02:24 | D | sum error = [ 139.7749, 146.7378, 153.9855, 161.4998, 169.3065] +24-11-19 19:02:24 | D | best error = [ 6.0637, 6.0637, 6.0637, 6.0637, 6.0637] +24-11-19 19:02:24 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:02:24 | D | sum error = [ 177.3774, 185.7583, 194.4449, 203.4412, 212.7448] +24-11-19 19:02:24 | D | best error = [ 6.0637, 6.0637, 6.0637, 6.0637, 6.0637] +24-11-19 19:02:24 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:02:24 | D | sum error = [ 222.3830, 232.3279, 242.5874, 253.2068, 264.1276] +24-11-19 19:02:24 | D | best error = [ 6.0637, 6.0637, 6.0637, 6.0637, 6.0637] +24-11-19 19:02:24 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:02:24 | D | sum error = [ 275.4138, 287.0455, 299.0459, 311.4119, 324.1322] +24-11-19 19:02:24 | D | best error = [ 6.0637, 6.0637, 6.0637, 6.0637, 6.0637] +24-11-19 19:02:24 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:02:24 | D | sum error = [ 337.2185, 350.6936, 364.5640, 378.8195, 393.4856] +24-11-19 19:02:24 | D | best error = [ 6.0637, 6.0637, 6.0637, 6.0637, 6.0637] +24-11-19 19:02:24 | D | + error = [6.0637] +24-11-19 19:02:24 | D | - Calibrating model.layers.21.mlp.gate_proj.weight +24-11-19 19:02:24 | D | + w: sint8 +24-11-19 19:02:24 | D | + x: None +24-11-19 19:02:24 | D | + y: None +24-11-19 19:02:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:02:24 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:02:24 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:02:24 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:02:24 | D | - range ratio = [ 1.0000] +24-11-19 19:02:24 | D | sum error = [ 9.5250] +24-11-19 19:02:24 | D | best error = [ 9.5250] +24-11-19 19:02:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:02:25 | D | sum error = [ 9.4763, 9.4153, 9.4594, 9.5682, 9.7495] +24-11-19 19:02:25 | D | best error = [ 8.8078, 8.5320, 8.3854, 8.3075, 8.2613] +24-11-19 19:02:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:02:25 | D | sum error = [ 10.0180, 10.3435, 10.7743, 11.2849, 11.8733] +24-11-19 19:02:25 | D | best error = [ 8.2399, 8.2298, 8.2261, 8.2250, 8.2248] +24-11-19 19:02:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:02:25 | D | sum error = [ 12.5653, 13.3104, 14.1924, 15.1484, 16.2133] +24-11-19 19:02:25 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 19:02:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:02:25 | D | sum error = [ 17.3587, 18.6171, 19.9742, 21.4336, 22.9991] +24-11-19 19:02:25 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 19:02:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:02:25 | D | sum error = [ 24.6499, 26.4255, 28.3499, 30.3494, 32.5221] +24-11-19 19:02:25 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 19:02:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:02:25 | D | sum error = [ 34.8217, 37.2309, 39.8487, 42.5561, 45.4572] +24-11-19 19:02:25 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 19:02:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:02:25 | D | sum error = [ 48.5474, 51.7943, 55.2516, 58.9098, 62.7665] +24-11-19 19:02:25 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 19:02:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:02:25 | D | sum error = [ 66.8650, 71.1808, 75.7475, 80.5587, 85.6904] +24-11-19 19:02:25 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 19:02:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:02:25 | D | sum error = [ 91.0888, 96.7909, 102.8374, 109.1872, 115.9332] +24-11-19 19:02:25 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 19:02:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:02:25 | D | sum error = [ 123.0382, 130.5096, 138.4358, 146.7585, 155.5338] +24-11-19 19:02:25 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 19:02:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:02:25 | D | sum error = [ 164.7493, 174.4871, 184.7419, 195.5120, 206.8520] +24-11-19 19:02:25 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 19:02:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:02:25 | D | sum error = [ 218.7783, 231.2743, 244.3832, 258.0926, 272.5141] +24-11-19 19:02:25 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 19:02:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:02:25 | D | sum error = [ 287.6062, 303.3942, 319.9112, 337.2234, 355.2653] +24-11-19 19:02:25 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 19:02:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:02:25 | D | sum error = [ 374.1248, 393.7712, 414.2299, 435.5322, 457.7039] +24-11-19 19:02:25 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 19:02:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:02:25 | D | sum error = [ 480.7460, 504.6494, 529.4845, 555.1753, 581.7733] +24-11-19 19:02:25 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 19:02:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:02:25 | D | sum error = [ 609.3088, 637.7250, 667.0643, 697.3603, 728.5572] +24-11-19 19:02:25 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 19:02:25 | D | + error = [8.2247] +24-11-19 19:02:25 | D | - Calibrating model.layers.21.mlp.down_proj.weight +24-11-19 19:02:25 | D | + w: sint8 +24-11-19 19:02:25 | D | + x: None +24-11-19 19:02:25 | D | + y: None +24-11-19 19:02:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:02:25 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:02:25 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:02:26 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:02:26 | D | - range ratio = [ 1.0000] +24-11-19 19:02:26 | D | sum error = [ 1.1579] +24-11-19 19:02:26 | D | best error = [ 1.1579] +24-11-19 19:02:27 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:02:27 | D | sum error = [ 1.1479, 1.1366, 1.1266, 1.1219, 1.1182] +24-11-19 19:02:27 | D | best error = [ 1.1097, 1.0841, 1.0671, 1.0546, 1.0443] +24-11-19 19:02:27 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:02:27 | D | sum error = [ 1.1174, 1.1200, 1.1255, 1.1350, 1.1494] +24-11-19 19:02:27 | D | best error = [ 1.0363, 1.0299, 1.0245, 1.0206, 1.0177] +24-11-19 19:02:27 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:02:27 | D | sum error = [ 1.1705, 1.1955, 1.2249, 1.2642, 1.3085] +24-11-19 19:02:27 | D | best error = [ 1.0155, 1.0138, 1.0128, 1.0120, 1.0114] +24-11-19 19:02:27 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:02:27 | D | sum error = [ 1.3597, 1.4241, 1.4943, 1.5699, 1.6587] +24-11-19 19:02:27 | D | best error = [ 1.0110, 1.0108, 1.0106, 1.0104, 1.0103] +24-11-19 19:02:27 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:02:27 | D | sum error = [ 1.7567, 1.8645, 1.9854, 2.1139, 2.2553] +24-11-19 19:02:27 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 19:02:27 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:02:27 | D | sum error = [ 2.4066, 2.5746, 2.7528, 2.9443, 3.1521] +24-11-19 19:02:27 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 19:02:27 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:02:27 | D | sum error = [ 3.3720, 3.6112, 3.8626, 4.1340, 4.4209] +24-11-19 19:02:27 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 19:02:27 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:02:27 | D | sum error = [ 4.7282, 5.0534, 5.4002, 5.7671, 6.1559] +24-11-19 19:02:27 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 19:02:27 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:02:27 | D | sum error = [ 6.5657, 7.0030, 7.4656, 7.9551, 8.4706] +24-11-19 19:02:27 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 19:02:27 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:02:27 | D | sum error = [ 9.0155, 9.5950, 10.2040, 10.8463, 11.5219] +24-11-19 19:02:27 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 19:02:27 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:02:27 | D | sum error = [ 12.2358, 12.9858, 13.7747, 14.6048, 15.4708] +24-11-19 19:02:27 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 19:02:27 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:02:27 | D | sum error = [ 16.3863, 17.3461, 18.3492, 19.4043, 20.5052] +24-11-19 19:02:27 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 19:02:27 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:02:27 | D | sum error = [ 21.6601, 22.8677, 24.1311, 25.4529, 26.8321] +24-11-19 19:02:27 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 19:02:27 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:02:27 | D | sum error = [ 28.2717, 29.7754, 31.3417, 32.9772, 34.6766] +24-11-19 19:02:27 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 19:02:27 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:02:27 | D | sum error = [ 36.4495, 38.2924, 40.2094, 42.1974, 44.2603] +24-11-19 19:02:27 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 19:02:27 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:02:27 | D | sum error = [ 46.4006, 48.6194, 50.9200, 53.3015, 55.7664] +24-11-19 19:02:27 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 19:02:27 | D | + error = [1.0102] +24-11-19 19:02:27 | D | - Quantizing model.layers.21.self_attn.q_proj.weight +24-11-19 19:02:28 | D | - Quantizing model.layers.21.self_attn.k_proj.weight +24-11-19 19:02:28 | D | - Quantizing model.layers.21.self_attn.v_proj.weight +24-11-19 19:02:29 | D | - Quantizing model.layers.21.self_attn.o_proj.weight +24-11-19 19:02:30 | D | - Quantizing model.layers.21.mlp.up_proj.weight +24-11-19 19:02:31 | D | - Quantizing model.layers.21.mlp.gate_proj.weight +24-11-19 19:02:32 | D | - Quantizing model.layers.21.mlp.down_proj.weight +24-11-19 19:02:41 | D | - Quantizing layer model.layers.22 +24-11-19 19:02:41 | D | - Calibrating model.layers.22.self_attn.q_proj.weight +24-11-19 19:02:41 | D | + w: sint8 +24-11-19 19:02:41 | D | + x: None +24-11-19 19:02:41 | D | + y: None +24-11-19 19:02:41 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:02:41 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:02:41 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:02:42 | D | + finished calculating the original outputs, ram usage: 12.1 +24-11-19 19:02:42 | D | - range ratio = [ 1.0000] +24-11-19 19:02:42 | D | sum error = [ 4.6307] +24-11-19 19:02:42 | D | best error = [ 4.6307] +24-11-19 19:02:53 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:02:53 | D | sum error = [ 4.5864, 4.5750, 4.5598, 4.6012, 4.6964] +24-11-19 19:02:53 | D | best error = [ 4.5864, 4.5750, 4.5598, 4.5598, 4.5598] +24-11-19 19:02:53 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:02:53 | D | sum error = [ 4.7895, 4.9994, 5.2785, 5.5214, 5.8310] +24-11-19 19:02:53 | D | best error = [ 4.5598, 4.5598, 4.5598, 4.5598, 4.5598] +24-11-19 19:02:53 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:02:53 | D | sum error = [ 6.2923, 6.6734, 7.4840, 7.7338, 8.3402] +24-11-19 19:02:53 | D | best error = [ 4.5598, 4.5598, 4.5598, 4.5598, 4.5598] +24-11-19 19:02:53 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:02:53 | D | sum error = [ 8.9805, 9.8098, 10.6449, 11.5569, 12.4025] +24-11-19 19:02:53 | D | best error = [ 4.5598, 4.5598, 4.5598, 4.5598, 4.5598] +24-11-19 19:02:53 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:02:53 | D | sum error = [ 13.5280, 14.9772, 16.1818, 17.5058, 18.8616] +24-11-19 19:02:53 | D | best error = [ 4.5598, 4.5598, 4.5598, 4.5598, 4.5598] +24-11-19 19:02:53 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:02:53 | D | sum error = [ 20.5159, 22.3938, 24.2626, 26.1846, 28.4635] +24-11-19 19:02:53 | D | best error = [ 4.5598, 4.5598, 4.5598, 4.5598, 4.5598] +24-11-19 19:02:53 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:02:53 | D | sum error = [ 31.0953, 33.5249, 36.5521, 39.4487, 42.9839] +24-11-19 19:02:53 | D | best error = [ 4.5598, 4.5598, 4.5598, 4.5598, 4.5598] +24-11-19 19:02:53 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:02:53 | D | sum error = [ 46.3162, 50.3497, 54.4477, 59.2304, 64.0966] +24-11-19 19:02:53 | D | best error = [ 4.5598, 4.5598, 4.5598, 4.5598, 4.5598] +24-11-19 19:02:53 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:02:53 | D | sum error = [ 69.6559, 75.2766, 81.6949, 88.5367, 95.9278] +24-11-19 19:02:53 | D | best error = [ 4.5598, 4.5598, 4.5598, 4.5598, 4.5598] +24-11-19 19:02:53 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:02:53 | D | sum error = [ 104.1939, 113.1522, 122.9920, 133.6446, 145.2288] +24-11-19 19:02:53 | D | best error = [ 4.5598, 4.5598, 4.5598, 4.5598, 4.5598] +24-11-19 19:02:53 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:02:53 | D | sum error = [ 157.4473, 171.2405, 185.6932, 201.9298, 219.2250] +24-11-19 19:02:53 | D | best error = [ 4.5598, 4.5598, 4.5598, 4.5598, 4.5598] +24-11-19 19:02:53 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:02:53 | D | sum error = [ 238.7608, 259.5244, 282.5916, 308.3842, 335.6200] +24-11-19 19:02:53 | D | best error = [ 4.5598, 4.5598, 4.5598, 4.5598, 4.5598] +24-11-19 19:02:53 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:02:53 | D | sum error = [ 366.0345, 399.7501, 437.5030, 479.1223, 525.0442] +24-11-19 19:02:53 | D | best error = [ 4.5598, 4.5598, 4.5598, 4.5598, 4.5598] +24-11-19 19:02:53 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:02:53 | D | sum error = [ 576.0612, 634.2888, 698.3185, 767.1498, 844.2688] +24-11-19 19:02:53 | D | best error = [ 4.5598, 4.5598, 4.5598, 4.5598, 4.5598] +24-11-19 19:02:53 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:02:53 | D | sum error = [ 929.6348, 1022.3551, 1123.6528, 1232.5065, 1348.2294] +24-11-19 19:02:53 | D | best error = [ 4.5598, 4.5598, 4.5598, 4.5598, 4.5598] +24-11-19 19:02:53 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:02:53 | D | sum error = [ 1471.3613, 1601.0342, 1736.0130, 1871.9203, 2010.4182] +24-11-19 19:02:53 | D | best error = [ 4.5598, 4.5598, 4.5598, 4.5598, 4.5598] +24-11-19 19:02:53 | D | + error = [4.5598] +24-11-19 19:02:53 | D | - Calibrating model.layers.22.self_attn.k_proj.weight +24-11-19 19:02:53 | D | + w: sint8 +24-11-19 19:02:53 | D | + x: None +24-11-19 19:02:53 | D | + y: None +24-11-19 19:02:53 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:02:53 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:02:54 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:02:54 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:02:54 | D | - range ratio = [ 1.0000] +24-11-19 19:02:54 | D | sum error = [ 4.7668] +24-11-19 19:02:54 | D | best error = [ 4.7668] +24-11-19 19:03:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:03:06 | D | sum error = [ 4.0851, 4.0218, 4.0883, 4.6373, 5.2618] +24-11-19 19:03:06 | D | best error = [ 4.0851, 4.0218, 4.0218, 4.0218, 4.0218] +24-11-19 19:03:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:03:06 | D | sum error = [ 4.6449, 4.6454, 5.9633, 5.6433, 6.4993] +24-11-19 19:03:06 | D | best error = [ 4.0218, 4.0218, 4.0218, 4.0218, 4.0218] +24-11-19 19:03:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:03:06 | D | sum error = [ 7.3682, 8.2597, 8.1559, 9.4377, 9.6863] +24-11-19 19:03:06 | D | best error = [ 4.0218, 4.0218, 4.0218, 4.0218, 4.0218] +24-11-19 19:03:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:03:06 | D | sum error = [ 10.9718, 12.4284, 12.8556, 16.3871, 16.4978] +24-11-19 19:03:06 | D | best error = [ 4.0218, 4.0218, 4.0218, 4.0218, 4.0218] +24-11-19 19:03:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:03:06 | D | sum error = [ 19.3216, 19.5406, 21.5662, 23.9079, 26.1531] +24-11-19 19:03:06 | D | best error = [ 4.0218, 4.0218, 4.0218, 4.0218, 4.0218] +24-11-19 19:03:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:03:06 | D | sum error = [ 27.7023, 29.7482, 31.7481, 34.6257, 36.8283] +24-11-19 19:03:06 | D | best error = [ 4.0218, 4.0218, 4.0218, 4.0218, 4.0218] +24-11-19 19:03:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:03:06 | D | sum error = [ 39.9229, 43.5181, 46.3863, 50.0083, 54.9997] +24-11-19 19:03:06 | D | best error = [ 4.0218, 4.0218, 4.0218, 4.0218, 4.0218] +24-11-19 19:03:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:03:06 | D | sum error = [ 58.9468, 63.3681, 69.4771, 75.2325, 81.6665] +24-11-19 19:03:06 | D | best error = [ 4.0218, 4.0218, 4.0218, 4.0218, 4.0218] +24-11-19 19:03:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:03:06 | D | sum error = [ 87.0433, 94.0304, 101.4190, 108.1789, 117.0847] +24-11-19 19:03:06 | D | best error = [ 4.0218, 4.0218, 4.0218, 4.0218, 4.0218] +24-11-19 19:03:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:03:06 | D | sum error = [ 126.3631, 137.3271, 146.7097, 160.4191, 171.2520] +24-11-19 19:03:06 | D | best error = [ 4.0218, 4.0218, 4.0218, 4.0218, 4.0218] +24-11-19 19:03:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:03:06 | D | sum error = [ 184.6851, 198.9749, 216.8077, 233.4797, 252.6683] +24-11-19 19:03:06 | D | best error = [ 4.0218, 4.0218, 4.0218, 4.0218, 4.0218] +24-11-19 19:03:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:03:06 | D | sum error = [ 271.4206, 297.1170, 323.8713, 349.9417, 381.5153] +24-11-19 19:03:06 | D | best error = [ 4.0218, 4.0218, 4.0218, 4.0218, 4.0218] +24-11-19 19:03:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:03:06 | D | sum error = [ 426.6337, 463.7351, 502.0656, 545.9290, 609.9119] +24-11-19 19:03:06 | D | best error = [ 4.0218, 4.0218, 4.0218, 4.0218, 4.0218] +24-11-19 19:03:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:03:06 | D | sum error = [ 663.7777, 722.7461, 800.6975, 880.6626, 951.5493] +24-11-19 19:03:06 | D | best error = [ 4.0218, 4.0218, 4.0218, 4.0218, 4.0218] +24-11-19 19:03:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:03:06 | D | sum error = [ 1044.0696, 1171.3670, 1273.4732, 1386.8352, 1498.6657] +24-11-19 19:03:06 | D | best error = [ 4.0218, 4.0218, 4.0218, 4.0218, 4.0218] +24-11-19 19:03:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:03:06 | D | sum error = [ 1663.7740, 1775.3637, 1915.3265, 2034.6626, 2200.2373] +24-11-19 19:03:06 | D | best error = [ 4.0218, 4.0218, 4.0218, 4.0218, 4.0218] +24-11-19 19:03:06 | D | + error = [4.0218] +24-11-19 19:03:06 | D | - Calibrating model.layers.22.self_attn.v_proj.weight +24-11-19 19:03:06 | D | + w: sint8 +24-11-19 19:03:06 | D | + x: None +24-11-19 19:03:06 | D | + y: None +24-11-19 19:03:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:03:06 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:03:06 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:03:06 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:03:06 | D | - range ratio = [ 1.0000] +24-11-19 19:03:06 | D | sum error = [ 1.9819] +24-11-19 19:03:06 | D | best error = [ 1.9819] +24-11-19 19:03:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:03:06 | D | sum error = [ 1.9627, 1.9530, 1.9638, 2.0062, 2.0229] +24-11-19 19:03:06 | D | best error = [ 1.8301, 1.7729, 1.7420, 1.7255, 1.7149] +24-11-19 19:03:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:03:06 | D | sum error = [ 2.0776, 2.1478, 2.2106, 2.3220, 2.4459] +24-11-19 19:03:06 | D | best error = [ 1.7117, 1.7099, 1.7094, 1.7092, 1.7091] +24-11-19 19:03:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:03:06 | D | sum error = [ 2.5803, 2.7699, 2.9190, 3.1388, 3.3631] +24-11-19 19:03:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 19:03:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:03:06 | D | sum error = [ 3.6046, 3.8516, 4.1133, 4.4081, 4.7147] +24-11-19 19:03:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 19:03:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:03:06 | D | sum error = [ 5.0483, 5.4195, 5.8138, 6.1998, 6.6479] +24-11-19 19:03:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 19:03:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:03:06 | D | sum error = [ 7.0998, 7.5798, 8.1036, 8.6460, 9.2122] +24-11-19 19:03:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 19:03:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:03:06 | D | sum error = [ 9.8087, 10.4524, 11.1151, 11.8064, 12.5573] +24-11-19 19:03:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 19:03:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:03:06 | D | sum error = [ 13.3256, 14.1327, 14.9954, 15.8898, 16.8350] +24-11-19 19:03:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 19:03:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:03:06 | D | sum error = [ 17.8260, 18.8587, 19.9603, 21.1010, 22.3025] +24-11-19 19:03:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 19:03:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:03:06 | D | sum error = [ 23.5549, 24.8744, 26.2562, 27.6743, 29.1490] +24-11-19 19:03:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 19:03:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:03:06 | D | sum error = [ 30.7127, 32.3297, 33.9993, 35.7502, 37.5700] +24-11-19 19:03:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 19:03:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:03:06 | D | sum error = [ 39.4627, 41.4358, 43.4862, 45.6304, 47.8658] +24-11-19 19:03:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 19:03:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:03:06 | D | sum error = [ 50.1932, 52.6119, 55.1129, 57.7105, 60.4097] +24-11-19 19:03:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 19:03:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:03:06 | D | sum error = [ 63.2120, 66.1029, 69.1031, 72.2085, 75.4142] +24-11-19 19:03:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 19:03:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:03:06 | D | sum error = [ 78.7075, 82.1051, 85.6129, 89.2247, 92.9544] +24-11-19 19:03:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 19:03:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:03:06 | D | sum error = [ 96.7854, 100.7274, 104.7826, 108.9560, 113.2414] +24-11-19 19:03:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 19:03:06 | D | + error = [1.7091] +24-11-19 19:03:06 | D | - Calibrating model.layers.22.self_attn.o_proj.weight +24-11-19 19:03:06 | D | + w: sint8 +24-11-19 19:03:06 | D | + x: None +24-11-19 19:03:06 | D | + y: None +24-11-19 19:03:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:03:06 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:03:07 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:03:07 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:03:07 | D | - range ratio = [ 1.0000] +24-11-19 19:03:07 | D | sum error = [ 0.4521] +24-11-19 19:03:07 | D | best error = [ 0.4521] +24-11-19 19:03:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:03:07 | D | sum error = [ 0.4463, 0.4463, 0.4499, 0.4541, 0.4648] +24-11-19 19:03:07 | D | best error = [ 0.4190, 0.4053, 0.3975, 0.3927, 0.3900] +24-11-19 19:03:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:03:07 | D | sum error = [ 0.4754, 0.4901, 0.5115, 0.5335, 0.5614] +24-11-19 19:03:07 | D | best error = [ 0.3881, 0.3868, 0.3860, 0.3855, 0.3851] +24-11-19 19:03:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:03:07 | D | sum error = [ 0.5918, 0.6273, 0.6662, 0.7091, 0.7571] +24-11-19 19:03:07 | D | best error = [ 0.3849, 0.3847, 0.3846, 0.3845, 0.3845] +24-11-19 19:03:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:03:07 | D | sum error = [ 0.8046, 0.8604, 0.9180, 0.9810, 1.0458] +24-11-19 19:03:07 | D | best error = [ 0.3845, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 19:03:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:03:07 | D | sum error = [ 1.1163, 1.1911, 1.2712, 1.3522, 1.4396] +24-11-19 19:03:07 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 19:03:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:03:07 | D | sum error = [ 1.5324, 1.6322, 1.7359, 1.8422, 1.9597] +24-11-19 19:03:07 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 19:03:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:03:07 | D | sum error = [ 2.0797, 2.2069, 2.3397, 2.4788, 2.6272] +24-11-19 19:03:07 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 19:03:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:03:07 | D | sum error = [ 2.7820, 2.9428, 3.1131, 3.2902, 3.4762] +24-11-19 19:03:07 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 19:03:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:03:07 | D | sum error = [ 3.6724, 3.8758, 4.0892, 4.3114, 4.5452] +24-11-19 19:03:07 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 19:03:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:03:07 | D | sum error = [ 4.7890, 5.0449, 5.3102, 5.5882, 5.8796] +24-11-19 19:03:07 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 19:03:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:03:07 | D | sum error = [ 6.1822, 6.4971, 6.8245, 7.1663, 7.5222] +24-11-19 19:03:07 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 19:03:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:03:07 | D | sum error = [ 7.8931, 8.2770, 8.6776, 9.0926, 9.5241] +24-11-19 19:03:07 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 19:03:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:03:07 | D | sum error = [ 9.9720, 10.4358, 10.9171, 11.4146, 11.9310] +24-11-19 19:03:07 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 19:03:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:03:07 | D | sum error = [ 12.4653, 13.0178, 13.5891, 14.1807, 14.7909] +24-11-19 19:03:07 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 19:03:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:03:07 | D | sum error = [ 15.4211, 16.0720, 16.7428, 17.4354, 18.1494] +24-11-19 19:03:07 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 19:03:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:03:07 | D | sum error = [ 18.8847, 19.6430, 20.4219, 21.2232, 22.0479] +24-11-19 19:03:07 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 19:03:07 | D | + error = [0.3844] +24-11-19 19:03:07 | D | - Calibrating model.layers.22.mlp.up_proj.weight +24-11-19 19:03:07 | D | + w: sint8 +24-11-19 19:03:07 | D | + x: None +24-11-19 19:03:07 | D | + y: None +24-11-19 19:03:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:03:07 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:03:07 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:03:07 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:03:07 | D | - range ratio = [ 1.0000] +24-11-19 19:03:07 | D | sum error = [ 7.2488] +24-11-19 19:03:07 | D | best error = [ 7.2488] +24-11-19 19:03:09 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:03:09 | D | sum error = [ 7.2062, 7.1656, 7.2085, 7.2907, 7.4430] +24-11-19 19:03:09 | D | best error = [ 6.6943, 6.4776, 6.3681, 6.3079, 6.2741] +24-11-19 19:03:09 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:03:09 | D | sum error = [ 7.6009, 7.8749, 8.1861, 8.5720, 9.0194] +24-11-19 19:03:09 | D | best error = [ 6.2563, 6.2490, 6.2461, 6.2453, 6.2450] +24-11-19 19:03:09 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:03:09 | D | sum error = [ 9.5497, 10.1528, 10.8176, 11.5275, 12.3283] +24-11-19 19:03:09 | D | best error = [ 6.2450, 6.2450, 6.2450, 6.2450, 6.2450] +24-11-19 19:03:09 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:03:09 | D | sum error = [ 13.2066, 14.1500, 15.1713, 16.2532, 17.4111] +24-11-19 19:03:09 | D | best error = [ 6.2450, 6.2450, 6.2450, 6.2450, 6.2450] +24-11-19 19:03:09 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:03:09 | D | sum error = [ 18.6463, 19.9752, 21.3904, 22.8680, 24.4253] +24-11-19 19:03:09 | D | best error = [ 6.2450, 6.2450, 6.2450, 6.2450, 6.2450] +24-11-19 19:03:09 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:03:09 | D | sum error = [ 26.1040, 27.8939, 29.7410, 31.7124, 33.7919] +24-11-19 19:03:09 | D | best error = [ 6.2450, 6.2450, 6.2450, 6.2450, 6.2450] +24-11-19 19:03:09 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:03:09 | D | sum error = [ 35.9943, 38.2950, 40.7239, 43.2770, 45.9722] +24-11-19 19:03:09 | D | best error = [ 6.2450, 6.2450, 6.2450, 6.2450, 6.2450] +24-11-19 19:03:09 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:03:09 | D | sum error = [ 48.7991, 51.7918, 54.9268, 58.1935, 61.6214] +24-11-19 19:03:09 | D | best error = [ 6.2450, 6.2450, 6.2450, 6.2450, 6.2450] +24-11-19 19:03:09 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:03:09 | D | sum error = [ 65.2326, 69.0075, 72.9695, 77.1035, 81.4245] +24-11-19 19:03:09 | D | best error = [ 6.2450, 6.2450, 6.2450, 6.2450, 6.2450] +24-11-19 19:03:09 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:03:09 | D | sum error = [ 85.9536, 90.6647, 95.5954, 100.7365, 106.1131] +24-11-19 19:03:09 | D | best error = [ 6.2450, 6.2450, 6.2450, 6.2450, 6.2450] +24-11-19 19:03:09 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:03:09 | D | sum error = [ 111.6971, 117.5242, 123.5699, 129.8741, 136.4215] +24-11-19 19:03:09 | D | best error = [ 6.2450, 6.2450, 6.2450, 6.2450, 6.2450] +24-11-19 19:03:09 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:03:09 | D | sum error = [ 143.2221, 150.3068, 157.6557, 165.2781, 173.1811] +24-11-19 19:03:09 | D | best error = [ 6.2450, 6.2450, 6.2450, 6.2450, 6.2450] +24-11-19 19:03:09 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:03:09 | D | sum error = [ 181.3657, 189.8624, 198.6462, 207.7263, 217.1301] +24-11-19 19:03:09 | D | best error = [ 6.2450, 6.2450, 6.2450, 6.2450, 6.2450] +24-11-19 19:03:09 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:03:09 | D | sum error = [ 226.8349, 236.8681, 247.2132, 257.9117, 268.9023] +24-11-19 19:03:09 | D | best error = [ 6.2450, 6.2450, 6.2450, 6.2450, 6.2450] +24-11-19 19:03:09 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:03:09 | D | sum error = [ 280.2518, 291.9364, 303.9810, 316.3792, 329.1234] +24-11-19 19:03:09 | D | best error = [ 6.2450, 6.2450, 6.2450, 6.2450, 6.2450] +24-11-19 19:03:09 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:03:09 | D | sum error = [ 342.2276, 355.6981, 369.5556, 383.7869, 398.3986] +24-11-19 19:03:09 | D | best error = [ 6.2450, 6.2450, 6.2450, 6.2450, 6.2450] +24-11-19 19:03:09 | D | + error = [6.2450] +24-11-19 19:03:09 | D | - Calibrating model.layers.22.mlp.gate_proj.weight +24-11-19 19:03:09 | D | + w: sint8 +24-11-19 19:03:09 | D | + x: None +24-11-19 19:03:09 | D | + y: None +24-11-19 19:03:09 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:03:09 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:03:09 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:03:09 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:03:09 | D | - range ratio = [ 1.0000] +24-11-19 19:03:09 | D | sum error = [ 9.7713] +24-11-19 19:03:09 | D | best error = [ 9.7713] +24-11-19 19:03:10 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:03:10 | D | sum error = [ 9.7380, 9.6910, 9.7717, 9.8511, 10.0472] +24-11-19 19:03:10 | D | best error = [ 9.0477, 8.7670, 8.6196, 8.5345, 8.4874] +24-11-19 19:03:10 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:03:10 | D | sum error = [ 10.2750, 10.6284, 11.0620, 11.6109, 12.2281] +24-11-19 19:03:10 | D | best error = [ 8.4643, 8.4546, 8.4507, 8.4496, 8.4495] +24-11-19 19:03:10 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:03:10 | D | sum error = [ 12.9505, 13.7050, 14.6157, 15.6298, 16.7242] +24-11-19 19:03:10 | D | best error = [ 8.4494, 8.4494, 8.4494, 8.4494, 8.4494] +24-11-19 19:03:10 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:03:10 | D | sum error = [ 17.9076, 19.1771, 20.5846, 22.0675, 23.6585] +24-11-19 19:03:10 | D | best error = [ 8.4494, 8.4494, 8.4494, 8.4494, 8.4494] +24-11-19 19:03:10 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:03:10 | D | sum error = [ 25.3931, 27.2236, 29.1696, 31.2626, 33.4642] +24-11-19 19:03:10 | D | best error = [ 8.4494, 8.4494, 8.4494, 8.4494, 8.4494] +24-11-19 19:03:10 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:03:10 | D | sum error = [ 35.7989, 38.2849, 40.9292, 43.7492, 46.7193] +24-11-19 19:03:10 | D | best error = [ 8.4494, 8.4494, 8.4494, 8.4494, 8.4494] +24-11-19 19:03:10 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:03:10 | D | sum error = [ 49.8715, 53.2280, 56.7207, 60.4683, 64.4044] +24-11-19 19:03:10 | D | best error = [ 8.4494, 8.4494, 8.4494, 8.4494, 8.4494] +24-11-19 19:03:10 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:03:10 | D | sum error = [ 68.5299, 72.9325, 77.5692, 82.4700, 87.6510] +24-11-19 19:03:10 | D | best error = [ 8.4494, 8.4494, 8.4494, 8.4494, 8.4494] +24-11-19 19:03:10 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:03:10 | D | sum error = [ 93.1064, 98.8713, 104.9349, 111.3339, 118.0844] +24-11-19 19:03:10 | D | best error = [ 8.4494, 8.4494, 8.4494, 8.4494, 8.4494] +24-11-19 19:03:10 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:03:10 | D | sum error = [ 125.2008, 132.6831, 140.5661, 148.8570, 157.5873] +24-11-19 19:03:10 | D | best error = [ 8.4494, 8.4494, 8.4494, 8.4494, 8.4494] +24-11-19 19:03:10 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:03:10 | D | sum error = [ 166.7892, 176.4116, 186.5604, 197.2002, 208.3700] +24-11-19 19:03:10 | D | best error = [ 8.4494, 8.4494, 8.4494, 8.4494, 8.4494] +24-11-19 19:03:10 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:03:10 | D | sum error = [ 220.0814, 232.3665, 245.2370, 258.7129, 272.8273] +24-11-19 19:03:10 | D | best error = [ 8.4494, 8.4494, 8.4494, 8.4494, 8.4494] +24-11-19 19:03:10 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:03:10 | D | sum error = [ 287.5669, 302.9935, 319.1397, 335.9651, 353.5409] +24-11-19 19:03:10 | D | best error = [ 8.4494, 8.4494, 8.4494, 8.4494, 8.4494] +24-11-19 19:03:10 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:03:10 | D | sum error = [ 371.8712, 390.9650, 410.8560, 431.5263, 453.0232] +24-11-19 19:03:10 | D | best error = [ 8.4494, 8.4494, 8.4494, 8.4494, 8.4494] +24-11-19 19:03:10 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:03:10 | D | sum error = [ 475.3348, 498.5043, 522.5285, 547.3610, 573.1071] +24-11-19 19:03:10 | D | best error = [ 8.4494, 8.4494, 8.4494, 8.4494, 8.4494] +24-11-19 19:03:10 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:03:10 | D | sum error = [ 599.7052, 627.1781, 655.5070, 684.7163, 714.8295] +24-11-19 19:03:10 | D | best error = [ 8.4494, 8.4494, 8.4494, 8.4494, 8.4494] +24-11-19 19:03:10 | D | + error = [8.4494] +24-11-19 19:03:10 | D | - Calibrating model.layers.22.mlp.down_proj.weight +24-11-19 19:03:10 | D | + w: sint8 +24-11-19 19:03:10 | D | + x: None +24-11-19 19:03:10 | D | + y: None +24-11-19 19:03:10 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:03:10 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:03:10 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:03:10 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:03:10 | D | - range ratio = [ 1.0000] +24-11-19 19:03:10 | D | sum error = [ 1.1781] +24-11-19 19:03:10 | D | best error = [ 1.1781] +24-11-19 19:03:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:03:12 | D | sum error = [ 1.1659, 1.1550, 1.1480, 1.1417, 1.1408] +24-11-19 19:03:12 | D | best error = [ 1.1238, 1.0968, 1.0792, 1.0661, 1.0557] +24-11-19 19:03:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:03:12 | D | sum error = [ 1.1382, 1.1428, 1.1505, 1.1579, 1.1756] +24-11-19 19:03:12 | D | best error = [ 1.0478, 1.0408, 1.0356, 1.0314, 1.0287] +24-11-19 19:03:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:03:12 | D | sum error = [ 1.1969, 1.2221, 1.2579, 1.2957, 1.3447] +24-11-19 19:03:12 | D | best error = [ 1.0264, 1.0245, 1.0234, 1.0225, 1.0218] +24-11-19 19:03:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:03:12 | D | sum error = [ 1.4011, 1.4650, 1.5420, 1.6232, 1.7123] +24-11-19 19:03:12 | D | best error = [ 1.0214, 1.0212, 1.0211, 1.0210, 1.0209] +24-11-19 19:03:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:03:12 | D | sum error = [ 1.8170, 1.9316, 2.0574, 2.1934, 2.3410] +24-11-19 19:03:12 | D | best error = [ 1.0209, 1.0209, 1.0209, 1.0209, 1.0209] +24-11-19 19:03:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:03:12 | D | sum error = [ 2.4998, 2.6761, 2.8611, 3.0611, 3.2786] +24-11-19 19:03:12 | D | best error = [ 1.0209, 1.0209, 1.0209, 1.0209, 1.0209] +24-11-19 19:03:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:03:12 | D | sum error = [ 3.5083, 3.7535, 4.0167, 4.2976, 4.5971] +24-11-19 19:03:12 | D | best error = [ 1.0209, 1.0209, 1.0209, 1.0209, 1.0209] +24-11-19 19:03:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:03:12 | D | sum error = [ 4.9143, 5.2535, 5.6148, 5.9944, 6.4010] +24-11-19 19:03:12 | D | best error = [ 1.0209, 1.0209, 1.0209, 1.0209, 1.0209] +24-11-19 19:03:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:03:12 | D | sum error = [ 6.8312, 7.2876, 7.7733, 8.2825, 8.8221] +24-11-19 19:03:12 | D | best error = [ 1.0209, 1.0209, 1.0209, 1.0209, 1.0209] +24-11-19 19:03:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:03:12 | D | sum error = [ 9.3917, 9.9940, 10.6284, 11.2974, 12.0007] +24-11-19 19:03:12 | D | best error = [ 1.0209, 1.0209, 1.0209, 1.0209, 1.0209] +24-11-19 19:03:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:03:12 | D | sum error = [ 12.7422, 13.5241, 14.3453, 15.2068, 16.1126] +24-11-19 19:03:12 | D | best error = [ 1.0209, 1.0209, 1.0209, 1.0209, 1.0209] +24-11-19 19:03:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:03:12 | D | sum error = [ 17.0628, 18.0604, 19.1066, 20.2026, 21.3517] +24-11-19 19:03:12 | D | best error = [ 1.0209, 1.0209, 1.0209, 1.0209, 1.0209] +24-11-19 19:03:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:03:12 | D | sum error = [ 22.5551, 23.8152, 25.1332, 26.5111, 27.9458] +24-11-19 19:03:12 | D | best error = [ 1.0209, 1.0209, 1.0209, 1.0209, 1.0209] +24-11-19 19:03:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:03:12 | D | sum error = [ 29.4449, 31.0069, 32.6351, 34.3333, 36.0965] +24-11-19 19:03:12 | D | best error = [ 1.0209, 1.0209, 1.0209, 1.0209, 1.0209] +24-11-19 19:03:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:03:12 | D | sum error = [ 37.9326, 39.8386, 41.8188, 43.8720, 46.0008] +24-11-19 19:03:12 | D | best error = [ 1.0209, 1.0209, 1.0209, 1.0209, 1.0209] +24-11-19 19:03:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:03:12 | D | sum error = [ 48.2082, 50.4936, 52.8605, 55.3084, 57.8374] +24-11-19 19:03:12 | D | best error = [ 1.0209, 1.0209, 1.0209, 1.0209, 1.0209] +24-11-19 19:03:12 | D | + error = [1.0209] +24-11-19 19:03:12 | D | - Quantizing model.layers.22.self_attn.q_proj.weight +24-11-19 19:03:13 | D | - Quantizing model.layers.22.self_attn.k_proj.weight +24-11-19 19:03:13 | D | - Quantizing model.layers.22.self_attn.v_proj.weight +24-11-19 19:03:14 | D | - Quantizing model.layers.22.self_attn.o_proj.weight +24-11-19 19:03:15 | D | - Quantizing model.layers.22.mlp.up_proj.weight +24-11-19 19:03:16 | D | - Quantizing model.layers.22.mlp.gate_proj.weight +24-11-19 19:03:17 | D | - Quantizing model.layers.22.mlp.down_proj.weight +24-11-19 19:03:26 | D | - Quantizing layer model.layers.23 +24-11-19 19:03:26 | D | - Calibrating model.layers.23.self_attn.q_proj.weight +24-11-19 19:03:26 | D | + w: sint8 +24-11-19 19:03:26 | D | + x: None +24-11-19 19:03:26 | D | + y: None +24-11-19 19:03:26 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:03:26 | D | + finished parsing calibration arguments, ram usage: 12.0 +24-11-19 19:03:26 | D | + finished reseting calibrator, ram usage: 11.9 +24-11-19 19:03:27 | D | + finished calculating the original outputs, ram usage: 11.9 +24-11-19 19:03:27 | D | - range ratio = [ 1.0000] +24-11-19 19:03:27 | D | sum error = [ 4.1375] +24-11-19 19:03:27 | D | best error = [ 4.1375] +24-11-19 19:03:39 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:03:39 | D | sum error = [ 4.1499, 4.1850, 4.1313, 4.2527, 4.3752] +24-11-19 19:03:39 | D | best error = [ 4.1375, 4.1375, 4.1313, 4.1313, 4.1313] +24-11-19 19:03:39 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:03:39 | D | sum error = [ 4.3837, 4.6407, 4.8731, 5.1561, 5.6645] +24-11-19 19:03:39 | D | best error = [ 4.1313, 4.1313, 4.1313, 4.1313, 4.1313] +24-11-19 19:03:39 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:03:39 | D | sum error = [ 5.8214, 6.4526, 6.7826, 7.3113, 8.1756] +24-11-19 19:03:39 | D | best error = [ 4.1313, 4.1313, 4.1313, 4.1313, 4.1313] +24-11-19 19:03:39 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:03:39 | D | sum error = [ 9.0649, 9.7444, 10.6114, 11.4513, 12.6383] +24-11-19 19:03:39 | D | best error = [ 4.1313, 4.1313, 4.1313, 4.1313, 4.1313] +24-11-19 19:03:39 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:03:39 | D | sum error = [ 13.6950, 14.9898, 16.3643, 18.0415, 19.7604] +24-11-19 19:03:39 | D | best error = [ 4.1313, 4.1313, 4.1313, 4.1313, 4.1313] +24-11-19 19:03:39 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:03:39 | D | sum error = [ 21.4577, 23.8205, 25.9196, 28.2188, 30.8105] +24-11-19 19:03:39 | D | best error = [ 4.1313, 4.1313, 4.1313, 4.1313, 4.1313] +24-11-19 19:03:39 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:03:39 | D | sum error = [ 33.5364, 36.5652, 39.8106, 43.0069, 46.9160] +24-11-19 19:03:39 | D | best error = [ 4.1313, 4.1313, 4.1313, 4.1313, 4.1313] +24-11-19 19:03:39 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:03:39 | D | sum error = [ 51.2237, 55.8557, 60.7017, 65.5341, 71.5222] +24-11-19 19:03:39 | D | best error = [ 4.1313, 4.1313, 4.1313, 4.1313, 4.1313] +24-11-19 19:03:39 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:03:39 | D | sum error = [ 77.6681, 84.3593, 91.1532, 99.1754, 107.4514] +24-11-19 19:03:39 | D | best error = [ 4.1313, 4.1313, 4.1313, 4.1313, 4.1313] +24-11-19 19:03:39 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:03:39 | D | sum error = [ 116.3055, 125.6076, 136.3258, 147.4895, 159.8475] +24-11-19 19:03:39 | D | best error = [ 4.1313, 4.1313, 4.1313, 4.1313, 4.1313] +24-11-19 19:03:39 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:03:39 | D | sum error = [ 173.0903, 187.6940, 203.0381, 220.3450, 239.1192] +24-11-19 19:03:39 | D | best error = [ 4.1313, 4.1313, 4.1313, 4.1313, 4.1313] +24-11-19 19:03:39 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:03:39 | D | sum error = [ 259.6940, 281.9613, 306.0890, 333.1492, 362.3238] +24-11-19 19:03:39 | D | best error = [ 4.1313, 4.1313, 4.1313, 4.1313, 4.1313] +24-11-19 19:03:39 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:03:39 | D | sum error = [ 394.0530, 428.8081, 467.0267, 508.8621, 554.7732] +24-11-19 19:03:39 | D | best error = [ 4.1313, 4.1313, 4.1313, 4.1313, 4.1313] +24-11-19 19:03:39 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:03:39 | D | sum error = [ 605.1788, 660.6429, 720.9089, 786.9107, 858.5811] +24-11-19 19:03:39 | D | best error = [ 4.1313, 4.1313, 4.1313, 4.1313, 4.1313] +24-11-19 19:03:39 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:03:39 | D | sum error = [ 936.9278, 1020.8378, 1110.7952, 1207.9970, 1311.0743] +24-11-19 19:03:39 | D | best error = [ 4.1313, 4.1313, 4.1313, 4.1313, 4.1313] +24-11-19 19:03:39 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:03:39 | D | sum error = [ 1420.4670, 1534.8437, 1654.3896, 1776.2351, 1901.0853] +24-11-19 19:03:39 | D | best error = [ 4.1313, 4.1313, 4.1313, 4.1313, 4.1313] +24-11-19 19:03:39 | D | + error = [4.1313] +24-11-19 19:03:39 | D | - Calibrating model.layers.23.self_attn.k_proj.weight +24-11-19 19:03:39 | D | + w: sint8 +24-11-19 19:03:39 | D | + x: None +24-11-19 19:03:39 | D | + y: None +24-11-19 19:03:39 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:03:39 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:03:39 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:03:39 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:03:40 | D | - range ratio = [ 1.0000] +24-11-19 19:03:40 | D | sum error = [ 4.5352] +24-11-19 19:03:40 | D | best error = [ 4.5352] +24-11-19 19:03:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:03:52 | D | sum error = [ 5.0897, 4.7168, 4.5454, 5.1897, 5.0143] +24-11-19 19:03:52 | D | best error = [ 4.5352, 4.5352, 4.5352, 4.5352, 4.5352] +24-11-19 19:03:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:03:52 | D | sum error = [ 4.9548, 5.5047, 5.8531, 5.0091, 5.4723] +24-11-19 19:03:52 | D | best error = [ 4.5352, 4.5352, 4.5352, 4.5352, 4.5352] +24-11-19 19:03:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:03:52 | D | sum error = [ 6.7766, 6.7892, 7.0201, 7.7224, 9.0940] +24-11-19 19:03:52 | D | best error = [ 4.5352, 4.5352, 4.5352, 4.5352, 4.5352] +24-11-19 19:03:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:03:52 | D | sum error = [ 10.3455, 12.4291, 11.3852, 14.0414, 16.1596] +24-11-19 19:03:52 | D | best error = [ 4.5352, 4.5352, 4.5352, 4.5352, 4.5352] +24-11-19 19:03:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:03:52 | D | sum error = [ 16.9330, 19.2524, 21.3737, 22.0837, 25.9383] +24-11-19 19:03:52 | D | best error = [ 4.5352, 4.5352, 4.5352, 4.5352, 4.5352] +24-11-19 19:03:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:03:52 | D | sum error = [ 28.4268, 31.1555, 35.0424, 37.8026, 41.5221] +24-11-19 19:03:52 | D | best error = [ 4.5352, 4.5352, 4.5352, 4.5352, 4.5352] +24-11-19 19:03:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:03:52 | D | sum error = [ 45.0568, 49.9397, 53.6274, 61.4471, 65.1936] +24-11-19 19:03:52 | D | best error = [ 4.5352, 4.5352, 4.5352, 4.5352, 4.5352] +24-11-19 19:03:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:03:52 | D | sum error = [ 70.3118, 76.2139, 82.6599, 88.5763, 98.2933] +24-11-19 19:03:52 | D | best error = [ 4.5352, 4.5352, 4.5352, 4.5352, 4.5352] +24-11-19 19:03:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:03:52 | D | sum error = [ 106.4367, 115.3997, 124.3276, 132.8099, 144.5255] +24-11-19 19:03:52 | D | best error = [ 4.5352, 4.5352, 4.5352, 4.5352, 4.5352] +24-11-19 19:03:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:03:52 | D | sum error = [ 156.4348, 171.6117, 185.2516, 199.0365, 213.1671] +24-11-19 19:03:52 | D | best error = [ 4.5352, 4.5352, 4.5352, 4.5352, 4.5352] +24-11-19 19:03:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:03:52 | D | sum error = [ 232.4518, 248.5204, 273.5343, 294.3914, 318.7149] +24-11-19 19:03:52 | D | best error = [ 4.5352, 4.5352, 4.5352, 4.5352, 4.5352] +24-11-19 19:03:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:03:52 | D | sum error = [ 345.7604, 373.8285, 405.2286, 443.8311, 482.5123] +24-11-19 19:03:52 | D | best error = [ 4.5352, 4.5352, 4.5352, 4.5352, 4.5352] +24-11-19 19:03:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:03:52 | D | sum error = [ 518.4774, 562.6526, 606.5857, 654.2285, 708.8016] +24-11-19 19:03:52 | D | best error = [ 4.5352, 4.5352, 4.5352, 4.5352, 4.5352] +24-11-19 19:03:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:03:52 | D | sum error = [ 778.8595, 835.2265, 900.4424, 970.2069, 1043.5164] +24-11-19 19:03:52 | D | best error = [ 4.5352, 4.5352, 4.5352, 4.5352, 4.5352] +24-11-19 19:03:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:03:52 | D | sum error = [ 1117.7936, 1220.8914, 1309.5677, 1400.2156, 1503.5003] +24-11-19 19:03:52 | D | best error = [ 4.5352, 4.5352, 4.5352, 4.5352, 4.5352] +24-11-19 19:03:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:03:52 | D | sum error = [ 1601.6495, 1712.3059, 1834.1585, 1943.5793, 2049.1817] +24-11-19 19:03:52 | D | best error = [ 4.5352, 4.5352, 4.5352, 4.5352, 4.5352] +24-11-19 19:03:52 | D | + error = [4.5352] +24-11-19 19:03:52 | D | - Calibrating model.layers.23.self_attn.v_proj.weight +24-11-19 19:03:52 | D | + w: sint8 +24-11-19 19:03:52 | D | + x: None +24-11-19 19:03:52 | D | + y: None +24-11-19 19:03:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:03:52 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:03:53 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:03:53 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:03:53 | D | - range ratio = [ 1.0000] +24-11-19 19:03:53 | D | sum error = [ 2.1443] +24-11-19 19:03:53 | D | best error = [ 2.1443] +24-11-19 19:03:53 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:03:53 | D | sum error = [ 2.1197, 2.1334, 2.1271, 2.1465, 2.1822] +24-11-19 19:03:53 | D | best error = [ 1.9681, 1.9058, 1.8724, 1.8507, 1.8413] +24-11-19 19:03:53 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:03:53 | D | sum error = [ 2.2511, 2.3278, 2.4096, 2.5153, 2.6424] +24-11-19 19:03:53 | D | best error = [ 1.8357, 1.8338, 1.8326, 1.8323, 1.8322] +24-11-19 19:03:53 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:03:53 | D | sum error = [ 2.7852, 2.9566, 3.1362, 3.3526, 3.5787] +24-11-19 19:03:53 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 19:03:53 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:03:53 | D | sum error = [ 3.8486, 4.1052, 4.4140, 4.7102, 5.0594] +24-11-19 19:03:53 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 19:03:53 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:03:53 | D | sum error = [ 5.4079, 5.8044, 6.2296, 6.6461, 7.1107] +24-11-19 19:03:53 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 19:03:53 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:03:53 | D | sum error = [ 7.6302, 8.1141, 8.6622, 9.2338, 9.8497] +24-11-19 19:03:53 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 19:03:53 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:03:53 | D | sum error = [ 10.5142, 11.1743, 11.9041, 12.6721, 13.4497] +24-11-19 19:03:53 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 19:03:53 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:03:53 | D | sum error = [ 14.2998, 15.1825, 16.1019, 17.0573, 18.0609] +24-11-19 19:03:53 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 19:03:53 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:03:53 | D | sum error = [ 19.1020, 20.2010, 21.3498, 22.5533, 23.7953] +24-11-19 19:03:53 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 19:03:53 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:03:53 | D | sum error = [ 25.1023, 26.4827, 27.9184, 29.4238, 30.9868] +24-11-19 19:03:53 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 19:03:53 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:03:53 | D | sum error = [ 32.6379, 34.3606, 36.1725, 38.0484, 39.9956] +24-11-19 19:03:53 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 19:03:53 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:03:53 | D | sum error = [ 42.0278, 44.1452, 46.3219, 48.6059, 50.9670] +24-11-19 19:03:53 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 19:03:53 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:03:53 | D | sum error = [ 53.4321, 55.9862, 58.6312, 61.3625, 64.1990] +24-11-19 19:03:53 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 19:03:53 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:03:53 | D | sum error = [ 67.1276, 70.1749, 73.3098, 76.5638, 79.9210] +24-11-19 19:03:53 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 19:03:53 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:03:53 | D | sum error = [ 83.3827, 86.9501, 90.6437, 94.4451, 98.3563] +24-11-19 19:03:53 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 19:03:53 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:03:53 | D | sum error = [ 102.3873, 106.5456, 110.8069, 115.1916, 119.6972] +24-11-19 19:03:53 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 19:03:53 | D | + error = [1.8322] +24-11-19 19:03:53 | D | - Calibrating model.layers.23.self_attn.o_proj.weight +24-11-19 19:03:53 | D | + w: sint8 +24-11-19 19:03:53 | D | + x: None +24-11-19 19:03:53 | D | + y: None +24-11-19 19:03:53 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:03:53 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:03:53 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:03:53 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:03:53 | D | - range ratio = [ 1.0000] +24-11-19 19:03:53 | D | sum error = [ 0.4629] +24-11-19 19:03:53 | D | best error = [ 0.4629] +24-11-19 19:03:54 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:03:54 | D | sum error = [ 0.4577, 0.4580, 0.4613, 0.4668, 0.4746] +24-11-19 19:03:54 | D | best error = [ 0.4294, 0.4151, 0.4066, 0.4015, 0.3979] +24-11-19 19:03:54 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:03:54 | D | sum error = [ 0.4869, 0.5047, 0.5244, 0.5487, 0.5774] +24-11-19 19:03:54 | D | best error = [ 0.3955, 0.3937, 0.3927, 0.3920, 0.3914] +24-11-19 19:03:54 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:03:54 | D | sum error = [ 0.6113, 0.6479, 0.6875, 0.7347, 0.7831] +24-11-19 19:03:54 | D | best error = [ 0.3910, 0.3907, 0.3905, 0.3904, 0.3903] +24-11-19 19:03:54 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:03:54 | D | sum error = [ 0.8400, 0.8959, 0.9602, 1.0297, 1.0999] +24-11-19 19:03:54 | D | best error = [ 0.3902, 0.3902, 0.3902, 0.3902, 0.3902] +24-11-19 19:03:54 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:03:54 | D | sum error = [ 1.1755, 1.2563, 1.3415, 1.4340, 1.5322] +24-11-19 19:03:54 | D | best error = [ 0.3902, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 19:03:54 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:03:54 | D | sum error = [ 1.6327, 1.7418, 1.8566, 1.9770, 2.1046] +24-11-19 19:03:54 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 19:03:54 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:03:54 | D | sum error = [ 2.2383, 2.3807, 2.5321, 2.6873, 2.8519] +24-11-19 19:03:54 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 19:03:54 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:03:54 | D | sum error = [ 3.0288, 3.2140, 3.4077, 3.6094, 3.8228] +24-11-19 19:03:54 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 19:03:54 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:03:54 | D | sum error = [ 4.0477, 4.2827, 4.5283, 4.7880, 5.0566] +24-11-19 19:03:54 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 19:03:54 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:03:54 | D | sum error = [ 5.3414, 5.6395, 5.9488, 6.2731, 6.6119] +24-11-19 19:03:54 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 19:03:54 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:03:54 | D | sum error = [ 6.9647, 7.3350, 7.7191, 8.1211, 8.5398] +24-11-19 19:03:54 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 19:03:54 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:03:54 | D | sum error = [ 8.9753, 9.4294, 9.9017, 10.3941, 10.9076] +24-11-19 19:03:54 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 19:03:54 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:03:54 | D | sum error = [ 11.4396, 11.9921, 12.5656, 13.1621, 13.7815] +24-11-19 19:03:54 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 19:03:54 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:03:54 | D | sum error = [ 14.4204, 15.0848, 15.7724, 16.4833, 17.2176] +24-11-19 19:03:54 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 19:03:54 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:03:54 | D | sum error = [ 17.9787, 18.7657, 19.5785, 20.4156, 21.2799] +24-11-19 19:03:54 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 19:03:54 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:03:54 | D | sum error = [ 22.1702, 23.0884, 24.0332, 25.0046, 26.0034] +24-11-19 19:03:54 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 19:03:54 | D | + error = [0.3901] +24-11-19 19:03:54 | D | - Calibrating model.layers.23.mlp.up_proj.weight +24-11-19 19:03:54 | D | + w: sint8 +24-11-19 19:03:54 | D | + x: None +24-11-19 19:03:54 | D | + y: None +24-11-19 19:03:54 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:03:54 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:03:54 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:03:54 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:03:54 | D | - range ratio = [ 1.0000] +24-11-19 19:03:54 | D | sum error = [ 7.5015] +24-11-19 19:03:54 | D | best error = [ 7.5015] +24-11-19 19:03:55 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:03:55 | D | sum error = [ 7.4407, 7.4283, 7.4715, 7.5481, 7.6788] +24-11-19 19:03:55 | D | best error = [ 6.8943, 6.6721, 6.5576, 6.4911, 6.4534] +24-11-19 19:03:55 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:03:55 | D | sum error = [ 7.8837, 8.1580, 8.4791, 8.8799, 9.3583] +24-11-19 19:03:55 | D | best error = [ 6.4358, 6.4263, 6.4235, 6.4224, 6.4222] +24-11-19 19:03:55 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:03:55 | D | sum error = [ 9.8993, 10.5035, 11.1561, 11.9539, 12.7493] +24-11-19 19:03:55 | D | best error = [ 6.4222, 6.4222, 6.4222, 6.4222, 6.4222] +24-11-19 19:03:55 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:03:55 | D | sum error = [ 13.6536, 14.6185, 15.6540, 16.7717, 17.9750] +24-11-19 19:03:55 | D | best error = [ 6.4222, 6.4222, 6.4222, 6.4222, 6.4222] +24-11-19 19:03:55 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:03:55 | D | sum error = [ 19.2510, 20.5927, 22.0537, 23.5714, 25.1771] +24-11-19 19:03:55 | D | best error = [ 6.4222, 6.4222, 6.4222, 6.4222, 6.4222] +24-11-19 19:03:55 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:03:55 | D | sum error = [ 26.9151, 28.7441, 30.6684, 32.7097, 34.8345] +24-11-19 19:03:55 | D | best error = [ 6.4222, 6.4222, 6.4222, 6.4222, 6.4222] +24-11-19 19:03:55 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:03:55 | D | sum error = [ 37.0912, 39.4732, 41.9691, 44.5968, 47.3694] +24-11-19 19:03:55 | D | best error = [ 6.4222, 6.4222, 6.4222, 6.4222, 6.4222] +24-11-19 19:03:55 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:03:55 | D | sum error = [ 50.2562, 53.3293, 56.5342, 59.8873, 63.4127] +24-11-19 19:03:55 | D | best error = [ 6.4222, 6.4222, 6.4222, 6.4222, 6.4222] +24-11-19 19:03:55 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:03:55 | D | sum error = [ 67.1012, 70.9647, 74.9986, 79.2419, 83.6617] +24-11-19 19:03:55 | D | best error = [ 6.4222, 6.4222, 6.4222, 6.4222, 6.4222] +24-11-19 19:03:55 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:03:55 | D | sum error = [ 88.2926, 93.1174, 98.1645, 103.4316, 108.9263] +24-11-19 19:03:55 | D | best error = [ 6.4222, 6.4222, 6.4222, 6.4222, 6.4222] +24-11-19 19:03:55 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:03:55 | D | sum error = [ 114.6347, 120.5865, 126.7969, 133.2440, 139.9298] +24-11-19 19:03:55 | D | best error = [ 6.4222, 6.4222, 6.4222, 6.4222, 6.4222] +24-11-19 19:03:55 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:03:55 | D | sum error = [ 146.9001, 154.1270, 161.6260, 169.3859, 177.4345] +24-11-19 19:03:55 | D | best error = [ 6.4222, 6.4222, 6.4222, 6.4222, 6.4222] +24-11-19 19:03:55 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:03:55 | D | sum error = [ 185.7688, 194.3968, 203.3229, 212.5526, 222.0991] +24-11-19 19:03:55 | D | best error = [ 6.4222, 6.4222, 6.4222, 6.4222, 6.4222] +24-11-19 19:03:55 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:03:55 | D | sum error = [ 231.9513, 242.1185, 252.6188, 263.4470, 274.5776] +24-11-19 19:03:55 | D | best error = [ 6.4222, 6.4222, 6.4222, 6.4222, 6.4222] +24-11-19 19:03:55 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:03:55 | D | sum error = [ 286.0760, 297.9294, 310.1330, 322.7075, 335.6395] +24-11-19 19:03:55 | D | best error = [ 6.4222, 6.4222, 6.4222, 6.4222, 6.4222] +24-11-19 19:03:55 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:03:55 | D | sum error = [ 348.9457, 362.6108, 376.6427, 391.0657, 405.8788] +24-11-19 19:03:55 | D | best error = [ 6.4222, 6.4222, 6.4222, 6.4222, 6.4222] +24-11-19 19:03:55 | D | + error = [6.4222] +24-11-19 19:03:55 | D | - Calibrating model.layers.23.mlp.gate_proj.weight +24-11-19 19:03:55 | D | + w: sint8 +24-11-19 19:03:55 | D | + x: None +24-11-19 19:03:55 | D | + y: None +24-11-19 19:03:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:03:55 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:03:56 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:03:56 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:03:56 | D | - range ratio = [ 1.0000] +24-11-19 19:03:56 | D | sum error = [ 10.1355] +24-11-19 19:03:56 | D | best error = [ 10.1355] +24-11-19 19:03:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:03:57 | D | sum error = [ 10.0173, 10.0141, 10.0575, 10.1761, 10.3483] +24-11-19 19:03:57 | D | best error = [ 9.3103, 9.0054, 8.8445, 8.7551, 8.7069] +24-11-19 19:03:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:03:57 | D | sum error = [ 10.6314, 10.9827, 11.4541, 11.9630, 12.6046] +24-11-19 19:03:57 | D | best error = [ 8.6802, 8.6686, 8.6650, 8.6633, 8.6629] +24-11-19 19:03:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:03:57 | D | sum error = [ 13.3528, 14.1758, 15.0623, 16.0630, 17.1722] +24-11-19 19:03:57 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 19:03:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:03:57 | D | sum error = [ 18.3971, 19.7123, 21.1373, 22.6841, 24.3217] +24-11-19 19:03:57 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 19:03:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:03:57 | D | sum error = [ 26.0657, 27.9452, 29.9499, 32.0419, 34.2663] +24-11-19 19:03:57 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 19:03:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:03:57 | D | sum error = [ 36.6504, 39.2011, 41.8650, 44.7288, 47.7661] +24-11-19 19:03:57 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 19:03:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:03:57 | D | sum error = [ 50.9076, 54.2655, 57.8243, 61.5875, 65.5566] +24-11-19 19:03:57 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 19:03:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:03:57 | D | sum error = [ 69.7885, 74.2016, 78.9046, 83.8733, 89.0860] +24-11-19 19:03:57 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 19:03:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:03:57 | D | sum error = [ 94.5962, 100.3854, 106.4970, 112.9248, 119.6945] +24-11-19 19:03:57 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 19:03:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:03:57 | D | sum error = [ 126.7843, 134.2732, 142.1795, 150.4363, 159.1372] +24-11-19 19:03:57 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 19:03:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:03:57 | D | sum error = [ 168.2719, 177.8334, 187.8830, 198.4251, 209.4888] +24-11-19 19:03:57 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 19:03:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:03:57 | D | sum error = [ 221.0662, 233.1956, 245.8780, 259.1214, 273.0159] +24-11-19 19:03:57 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 19:03:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:03:57 | D | sum error = [ 287.5237, 302.6525, 318.4508, 334.9165, 352.0636] +24-11-19 19:03:57 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 19:03:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:03:57 | D | sum error = [ 369.9208, 388.5563, 407.9253, 428.0804, 449.0227] +24-11-19 19:03:57 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 19:03:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:03:57 | D | sum error = [ 470.7537, 493.2945, 516.6150, 540.7580, 565.7345] +24-11-19 19:03:57 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 19:03:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:03:57 | D | sum error = [ 591.5412, 618.1577, 645.6307, 673.9538, 703.1029] +24-11-19 19:03:57 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 19:03:57 | D | + error = [8.6628] +24-11-19 19:03:57 | D | - Calibrating model.layers.23.mlp.down_proj.weight +24-11-19 19:03:57 | D | + w: sint8 +24-11-19 19:03:57 | D | + x: None +24-11-19 19:03:57 | D | + y: None +24-11-19 19:03:57 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:03:57 | D | + finished parsing calibration arguments, ram usage: 12.0 +24-11-19 19:03:57 | D | + finished reseting calibrator, ram usage: 11.9 +24-11-19 19:03:57 | D | + finished calculating the original outputs, ram usage: 11.8 +24-11-19 19:03:57 | D | - range ratio = [ 1.0000] +24-11-19 19:03:57 | D | sum error = [ 1.1715] +24-11-19 19:03:57 | D | best error = [ 1.1715] +24-11-19 19:03:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:03:59 | D | sum error = [ 1.1615, 1.1538, 1.1440, 1.1397, 1.1373] +24-11-19 19:03:59 | D | best error = [ 1.1222, 1.0980, 1.0805, 1.0673, 1.0574] +24-11-19 19:03:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:03:59 | D | sum error = [ 1.1378, 1.1438, 1.1523, 1.1649, 1.1837] +24-11-19 19:03:59 | D | best error = [ 1.0498, 1.0436, 1.0385, 1.0350, 1.0325] +24-11-19 19:03:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:03:59 | D | sum error = [ 1.2089, 1.2378, 1.2739, 1.3170, 1.3695] +24-11-19 19:03:59 | D | best error = [ 1.0305, 1.0289, 1.0277, 1.0271, 1.0266] +24-11-19 19:03:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:03:59 | D | sum error = [ 1.4301, 1.4957, 1.5711, 1.6587, 1.7560] +24-11-19 19:03:59 | D | best error = [ 1.0263, 1.0260, 1.0259, 1.0257, 1.0257] +24-11-19 19:03:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:03:59 | D | sum error = [ 1.8593, 1.9777, 2.1041, 2.2437, 2.3932] +24-11-19 19:03:59 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 19:03:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:03:59 | D | sum error = [ 2.5573, 2.7330, 2.9206, 3.1228, 3.3419] +24-11-19 19:03:59 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 19:03:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:03:59 | D | sum error = [ 3.5743, 3.8249, 4.0905, 4.3755, 4.6769] +24-11-19 19:03:59 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 19:03:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:03:59 | D | sum error = [ 4.9996, 5.3428, 5.7053, 6.0902, 6.4988] +24-11-19 19:03:59 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 19:03:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:03:59 | D | sum error = [ 6.9301, 7.3882, 7.8728, 8.3823, 8.9213] +24-11-19 19:03:59 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 19:03:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:03:59 | D | sum error = [ 9.4909, 10.0915, 10.7263, 11.3941, 12.0976] +24-11-19 19:03:59 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 19:03:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:03:59 | D | sum error = [ 12.8397, 13.6205, 14.4410, 15.3032, 16.2072] +24-11-19 19:03:59 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 19:03:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:03:59 | D | sum error = [ 17.1605, 18.1578, 19.2065, 20.3028, 21.4512] +24-11-19 19:03:59 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 19:03:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:03:59 | D | sum error = [ 22.6542, 23.9131, 25.2295, 26.6048, 28.0404] +24-11-19 19:03:59 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 19:03:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:03:59 | D | sum error = [ 29.5384, 31.1033, 32.7341, 34.4315, 36.1981] +24-11-19 19:03:59 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 19:03:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:03:59 | D | sum error = [ 38.0359, 39.9499, 41.9370, 44.0003, 46.1389] +24-11-19 19:03:59 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 19:03:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:03:59 | D | sum error = [ 48.3585, 50.6583, 53.0391, 55.5026, 58.0469] +24-11-19 19:03:59 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 19:03:59 | D | + error = [1.0257] +24-11-19 19:03:59 | D | - Quantizing model.layers.23.self_attn.q_proj.weight +24-11-19 19:04:00 | D | - Quantizing model.layers.23.self_attn.k_proj.weight +24-11-19 19:04:01 | D | - Quantizing model.layers.23.self_attn.v_proj.weight +24-11-19 19:04:02 | D | - Quantizing model.layers.23.self_attn.o_proj.weight +24-11-19 19:04:03 | D | - Quantizing model.layers.23.mlp.up_proj.weight +24-11-19 19:04:03 | D | - Quantizing model.layers.23.mlp.gate_proj.weight +24-11-19 19:04:04 | D | - Quantizing model.layers.23.mlp.down_proj.weight +24-11-19 19:04:15 | D | - Quantizing layer model.layers.24 +24-11-19 19:04:15 | D | - Calibrating model.layers.24.self_attn.q_proj.weight +24-11-19 19:04:15 | D | + w: sint8 +24-11-19 19:04:15 | D | + x: None +24-11-19 19:04:15 | D | + y: None +24-11-19 19:04:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:04:15 | D | + finished parsing calibration arguments, ram usage: 12.0 +24-11-19 19:04:15 | D | + finished reseting calibrator, ram usage: 12.0 +24-11-19 19:04:15 | D | + finished calculating the original outputs, ram usage: 12.0 +24-11-19 19:04:15 | D | - range ratio = [ 1.0000] +24-11-19 19:04:15 | D | sum error = [ 4.6562] +24-11-19 19:04:15 | D | best error = [ 4.6562] +24-11-19 19:04:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:04:29 | D | sum error = [ 4.6577, 4.7554, 4.7502, 4.7989, 4.9715] +24-11-19 19:04:29 | D | best error = [ 4.6562, 4.6562, 4.6562, 4.6562, 4.6562] +24-11-19 19:04:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:04:29 | D | sum error = [ 5.0521, 5.0643, 5.5726, 5.6647, 6.0442] +24-11-19 19:04:29 | D | best error = [ 4.6562, 4.6562, 4.6562, 4.6562, 4.6562] +24-11-19 19:04:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:04:29 | D | sum error = [ 6.3647, 6.8098, 7.4227, 7.9421, 8.5266] +24-11-19 19:04:29 | D | best error = [ 4.6562, 4.6562, 4.6562, 4.6562, 4.6562] +24-11-19 19:04:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:04:29 | D | sum error = [ 9.1855, 9.9876, 10.9053, 12.0979, 13.0545] +24-11-19 19:04:29 | D | best error = [ 4.6562, 4.6562, 4.6562, 4.6562, 4.6562] +24-11-19 19:04:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:04:29 | D | sum error = [ 14.0090, 15.5430, 16.7970, 18.1634, 19.6638] +24-11-19 19:04:29 | D | best error = [ 4.6562, 4.6562, 4.6562, 4.6562, 4.6562] +24-11-19 19:04:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:04:29 | D | sum error = [ 21.2311, 22.9998, 25.0360, 27.1505, 29.4890] +24-11-19 19:04:29 | D | best error = [ 4.6562, 4.6562, 4.6562, 4.6562, 4.6562] +24-11-19 19:04:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:04:29 | D | sum error = [ 31.8578, 34.7708, 37.3810, 40.5280, 43.9719] +24-11-19 19:04:29 | D | best error = [ 4.6562, 4.6562, 4.6562, 4.6562, 4.6562] +24-11-19 19:04:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:04:29 | D | sum error = [ 47.8552, 52.0088, 56.1666, 60.8571, 65.9223] +24-11-19 19:04:29 | D | best error = [ 4.6562, 4.6562, 4.6562, 4.6562, 4.6562] +24-11-19 19:04:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:04:29 | D | sum error = [ 70.9410, 76.9561, 83.3128, 89.6329, 97.1914] +24-11-19 19:04:29 | D | best error = [ 4.6562, 4.6562, 4.6562, 4.6562, 4.6562] +24-11-19 19:04:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:04:29 | D | sum error = [ 104.9667, 113.5695, 122.7236, 132.4011, 142.8517] +24-11-19 19:04:29 | D | best error = [ 4.6562, 4.6562, 4.6562, 4.6562, 4.6562] +24-11-19 19:04:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:04:29 | D | sum error = [ 154.5529, 166.7788, 180.0294, 194.2194, 209.6607] +24-11-19 19:04:29 | D | best error = [ 4.6562, 4.6562, 4.6562, 4.6562, 4.6562] +24-11-19 19:04:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:04:29 | D | sum error = [ 226.1840, 244.0598, 262.8314, 283.4679, 305.4489] +24-11-19 19:04:29 | D | best error = [ 4.6562, 4.6562, 4.6562, 4.6562, 4.6562] +24-11-19 19:04:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:04:29 | D | sum error = [ 329.4151, 355.0148, 382.5978, 412.5862, 444.8267] +24-11-19 19:04:29 | D | best error = [ 4.6562, 4.6562, 4.6562, 4.6562, 4.6562] +24-11-19 19:04:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:04:29 | D | sum error = [ 480.3898, 518.6626, 560.3618, 605.2246, 654.1137] +24-11-19 19:04:29 | D | best error = [ 4.6562, 4.6562, 4.6562, 4.6562, 4.6562] +24-11-19 19:04:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:04:29 | D | sum error = [ 707.0546, 764.1221, 826.0972, 892.4880, 963.3980] +24-11-19 19:04:29 | D | best error = [ 4.6562, 4.6562, 4.6562, 4.6562, 4.6562] +24-11-19 19:04:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:04:29 | D | sum error = [ 1038.5608, 1118.4232, 1200.7666, 1287.2022, 1375.3331] +24-11-19 19:04:29 | D | best error = [ 4.6562, 4.6562, 4.6562, 4.6562, 4.6562] +24-11-19 19:04:29 | D | + error = [4.6562] +24-11-19 19:04:30 | D | - Calibrating model.layers.24.self_attn.k_proj.weight +24-11-19 19:04:30 | D | + w: sint8 +24-11-19 19:04:30 | D | + x: None +24-11-19 19:04:30 | D | + y: None +24-11-19 19:04:30 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:04:30 | D | + finished parsing calibration arguments, ram usage: 11.9 +24-11-19 19:04:30 | D | + finished reseting calibrator, ram usage: 12.0 +24-11-19 19:04:30 | D | + finished calculating the original outputs, ram usage: 12.0 +24-11-19 19:04:30 | D | - range ratio = [ 1.0000] +24-11-19 19:04:30 | D | sum error = [ 4.3974] +24-11-19 19:04:30 | D | best error = [ 4.3974] +24-11-19 19:04:42 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:04:42 | D | sum error = [ 5.3100, 4.5512, 5.0710, 5.2623, 5.2560] +24-11-19 19:04:42 | D | best error = [ 4.3974, 4.3974, 4.3974, 4.3974, 4.3974] +24-11-19 19:04:42 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:04:42 | D | sum error = [ 4.9487, 4.9367, 6.2631, 5.4027, 6.0329] +24-11-19 19:04:42 | D | best error = [ 4.3974, 4.3974, 4.3974, 4.3974, 4.3974] +24-11-19 19:04:42 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:04:42 | D | sum error = [ 6.2589, 6.8989, 8.1136, 7.8072, 8.2606] +24-11-19 19:04:42 | D | best error = [ 4.3974, 4.3974, 4.3974, 4.3974, 4.3974] +24-11-19 19:04:42 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:04:42 | D | sum error = [ 9.5206, 10.1832, 10.9132, 12.2527, 13.1850] +24-11-19 19:04:42 | D | best error = [ 4.3974, 4.3974, 4.3974, 4.3974, 4.3974] +24-11-19 19:04:42 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:04:42 | D | sum error = [ 14.3002, 14.6180, 16.8342, 17.6914, 19.6920] +24-11-19 19:04:42 | D | best error = [ 4.3974, 4.3974, 4.3974, 4.3974, 4.3974] +24-11-19 19:04:42 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:04:42 | D | sum error = [ 21.8222, 22.4733, 24.1719, 26.5246, 27.8550] +24-11-19 19:04:42 | D | best error = [ 4.3974, 4.3974, 4.3974, 4.3974, 4.3974] +24-11-19 19:04:42 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:04:42 | D | sum error = [ 31.0094, 34.2092, 35.8646, 39.8357, 41.8061] +24-11-19 19:04:42 | D | best error = [ 4.3974, 4.3974, 4.3974, 4.3974, 4.3974] +24-11-19 19:04:42 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:04:42 | D | sum error = [ 45.9099, 50.3075, 53.4182, 58.6666, 63.7923] +24-11-19 19:04:42 | D | best error = [ 4.3974, 4.3974, 4.3974, 4.3974, 4.3974] +24-11-19 19:04:42 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:04:42 | D | sum error = [ 68.5194, 73.9827, 79.2739, 85.9408, 92.8540] +24-11-19 19:04:42 | D | best error = [ 4.3974, 4.3974, 4.3974, 4.3974, 4.3974] +24-11-19 19:04:42 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:04:42 | D | sum error = [ 99.5537, 109.0118, 117.2690, 126.2823, 136.4548] +24-11-19 19:04:42 | D | best error = [ 4.3974, 4.3974, 4.3974, 4.3974, 4.3974] +24-11-19 19:04:42 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:04:42 | D | sum error = [ 148.4494, 161.0287, 173.3109, 187.7840, 203.1349] +24-11-19 19:04:42 | D | best error = [ 4.3974, 4.3974, 4.3974, 4.3974, 4.3974] +24-11-19 19:04:42 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:04:42 | D | sum error = [ 221.1590, 240.2021, 257.2002, 276.3166, 302.0506] +24-11-19 19:04:42 | D | best error = [ 4.3974, 4.3974, 4.3974, 4.3974, 4.3974] +24-11-19 19:04:42 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:04:42 | D | sum error = [ 324.4557, 350.3387, 379.3512, 405.4179, 439.2967] +24-11-19 19:04:42 | D | best error = [ 4.3974, 4.3974, 4.3974, 4.3974, 4.3974] +24-11-19 19:04:42 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:04:42 | D | sum error = [ 474.5926, 506.8637, 551.9251, 596.6474, 644.1290] +24-11-19 19:04:42 | D | best error = [ 4.3974, 4.3974, 4.3974, 4.3974, 4.3974] +24-11-19 19:04:42 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:04:42 | D | sum error = [ 696.8600, 748.3901, 819.3023, 880.1041, 946.3620] +24-11-19 19:04:42 | D | best error = [ 4.3974, 4.3974, 4.3974, 4.3974, 4.3974] +24-11-19 19:04:42 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:04:42 | D | sum error = [ 1027.4543, 1104.6620, 1199.7997, 1279.3448, 1366.2348] +24-11-19 19:04:42 | D | best error = [ 4.3974, 4.3974, 4.3974, 4.3974, 4.3974] +24-11-19 19:04:42 | D | + error = [4.3974] +24-11-19 19:04:42 | D | - Calibrating model.layers.24.self_attn.v_proj.weight +24-11-19 19:04:42 | D | + w: sint8 +24-11-19 19:04:42 | D | + x: None +24-11-19 19:04:42 | D | + y: None +24-11-19 19:04:42 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:04:42 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:04:42 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:04:43 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:04:43 | D | - range ratio = [ 1.0000] +24-11-19 19:04:43 | D | sum error = [ 2.3518] +24-11-19 19:04:43 | D | best error = [ 2.3518] +24-11-19 19:04:43 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:04:43 | D | sum error = [ 2.3398, 2.3510, 2.3450, 2.3651, 2.4111] +24-11-19 19:04:43 | D | best error = [ 2.1712, 2.1007, 2.0578, 2.0335, 2.0223] +24-11-19 19:04:43 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:04:43 | D | sum error = [ 2.4926, 2.5687, 2.6653, 2.8064, 2.9361] +24-11-19 19:04:43 | D | best error = [ 2.0161, 2.0140, 2.0122, 2.0116, 2.0114] +24-11-19 19:04:43 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:04:43 | D | sum error = [ 3.1155, 3.2738, 3.4994, 3.7490, 4.0174] +24-11-19 19:04:43 | D | best error = [ 2.0113, 2.0113, 2.0113, 2.0113, 2.0113] +24-11-19 19:04:43 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:04:43 | D | sum error = [ 4.2976, 4.5899, 4.9207, 5.2706, 5.6321] +24-11-19 19:04:43 | D | best error = [ 2.0113, 2.0113, 2.0113, 2.0113, 2.0113] +24-11-19 19:04:43 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:04:43 | D | sum error = [ 6.0443, 6.4868, 6.9484, 7.4181, 7.9052] +24-11-19 19:04:43 | D | best error = [ 2.0113, 2.0113, 2.0113, 2.0113, 2.0113] +24-11-19 19:04:43 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:04:43 | D | sum error = [ 8.4803, 9.0297, 9.6240, 10.2526, 10.9317] +24-11-19 19:04:43 | D | best error = [ 2.0113, 2.0113, 2.0113, 2.0113, 2.0113] +24-11-19 19:04:43 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:04:43 | D | sum error = [ 11.6330, 12.3836, 13.1773, 13.9701, 14.8544] +24-11-19 19:04:43 | D | best error = [ 2.0113, 2.0113, 2.0113, 2.0113, 2.0113] +24-11-19 19:04:43 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:04:43 | D | sum error = [ 15.7772, 16.7569, 17.7745, 18.8360, 19.9418] +24-11-19 19:04:43 | D | best error = [ 2.0113, 2.0113, 2.0113, 2.0113, 2.0113] +24-11-19 19:04:43 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:04:43 | D | sum error = [ 21.1481, 22.3749, 23.6673, 25.0117, 26.4437] +24-11-19 19:04:43 | D | best error = [ 2.0113, 2.0113, 2.0113, 2.0113, 2.0113] +24-11-19 19:04:43 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:04:43 | D | sum error = [ 27.9287, 29.4567, 31.0981, 32.7713, 34.5662] +24-11-19 19:04:43 | D | best error = [ 2.0113, 2.0113, 2.0113, 2.0113, 2.0113] +24-11-19 19:04:43 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:04:43 | D | sum error = [ 36.3989, 38.3428, 40.3457, 42.4356, 44.6386] +24-11-19 19:04:43 | D | best error = [ 2.0113, 2.0113, 2.0113, 2.0113, 2.0113] +24-11-19 19:04:43 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:04:43 | D | sum error = [ 46.9095, 49.2839, 51.7297, 54.2869, 56.9539] +24-11-19 19:04:43 | D | best error = [ 2.0113, 2.0113, 2.0113, 2.0113, 2.0113] +24-11-19 19:04:43 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:04:43 | D | sum error = [ 59.7089, 62.5639, 65.5039, 68.5559, 71.7100] +24-11-19 19:04:43 | D | best error = [ 2.0113, 2.0113, 2.0113, 2.0113, 2.0113] +24-11-19 19:04:43 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:04:43 | D | sum error = [ 74.9624, 78.3230, 81.8181, 85.4221, 89.1571] +24-11-19 19:04:43 | D | best error = [ 2.0113, 2.0113, 2.0113, 2.0113, 2.0113] +24-11-19 19:04:43 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:04:43 | D | sum error = [ 92.9973, 96.9704, 101.0492, 105.2879, 109.6514] +24-11-19 19:04:43 | D | best error = [ 2.0113, 2.0113, 2.0113, 2.0113, 2.0113] +24-11-19 19:04:43 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:04:43 | D | sum error = [ 114.1207, 118.7217, 123.4542, 128.3100, 133.2940] +24-11-19 19:04:43 | D | best error = [ 2.0113, 2.0113, 2.0113, 2.0113, 2.0113] +24-11-19 19:04:43 | D | + error = [2.0113] +24-11-19 19:04:43 | D | - Calibrating model.layers.24.self_attn.o_proj.weight +24-11-19 19:04:43 | D | + w: sint8 +24-11-19 19:04:43 | D | + x: None +24-11-19 19:04:43 | D | + y: None +24-11-19 19:04:43 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:04:43 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:04:43 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:04:43 | D | + finished calculating the original outputs, ram usage: 12.2 +24-11-19 19:04:43 | D | - range ratio = [ 1.0000] +24-11-19 19:04:43 | D | sum error = [ 0.4864] +24-11-19 19:04:43 | D | best error = [ 0.4864] +24-11-19 19:04:43 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:04:43 | D | sum error = [ 0.4824, 0.4810, 0.4801, 0.4811, 0.4866] +24-11-19 19:04:43 | D | best error = [ 0.4500, 0.4343, 0.4240, 0.4172, 0.4122] +24-11-19 19:04:43 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:04:43 | D | sum error = [ 0.4927, 0.5041, 0.5174, 0.5329, 0.5512] +24-11-19 19:04:43 | D | best error = [ 0.4086, 0.4060, 0.4036, 0.4020, 0.4006] +24-11-19 19:04:43 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:04:43 | D | sum error = [ 0.5752, 0.6025, 0.6318, 0.6651, 0.7012] +24-11-19 19:04:43 | D | best error = [ 0.3996, 0.3989, 0.3983, 0.3979, 0.3974] +24-11-19 19:04:43 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:04:43 | D | sum error = [ 0.7433, 0.7889, 0.8377, 0.8904, 0.9503] +24-11-19 19:04:43 | D | best error = [ 0.3970, 0.3968, 0.3966, 0.3964, 0.3963] +24-11-19 19:04:43 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:04:43 | D | sum error = [ 1.0106, 1.0766, 1.1488, 1.2257, 1.3047] +24-11-19 19:04:43 | D | best error = [ 0.3962, 0.3961, 0.3961, 0.3960, 0.3960] +24-11-19 19:04:43 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:04:43 | D | sum error = [ 1.3919, 1.4825, 1.5783, 1.6802, 1.7882] +24-11-19 19:04:43 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 19:04:43 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:04:43 | D | sum error = [ 1.9021, 2.0208, 2.1480, 2.2821, 2.4235] +24-11-19 19:04:43 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 19:04:43 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:04:43 | D | sum error = [ 2.5700, 2.7263, 2.8901, 3.0602, 3.2403] +24-11-19 19:04:43 | D | best error = [ 0.3958, 0.3958, 0.3958, 0.3958, 0.3958] +24-11-19 19:04:43 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:04:43 | D | sum error = [ 3.4318, 3.6315, 3.8423, 4.0622, 4.2926] +24-11-19 19:04:43 | D | best error = [ 0.3958, 0.3958, 0.3958, 0.3958, 0.3958] +24-11-19 19:04:43 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:04:43 | D | sum error = [ 4.5352, 4.7906, 5.0568, 5.3354, 5.6272] +24-11-19 19:04:43 | D | best error = [ 0.3958, 0.3958, 0.3958, 0.3958, 0.3958] +24-11-19 19:04:43 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:04:43 | D | sum error = [ 5.9345, 6.2535, 6.5901, 6.9398, 7.3055] +24-11-19 19:04:43 | D | best error = [ 0.3958, 0.3958, 0.3958, 0.3958, 0.3958] +24-11-19 19:04:43 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:04:43 | D | sum error = [ 7.6864, 8.0855, 8.4991, 8.9308, 9.3813] +24-11-19 19:04:43 | D | best error = [ 0.3958, 0.3958, 0.3958, 0.3958, 0.3958] +24-11-19 19:04:43 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:04:43 | D | sum error = [ 9.8484, 10.3332, 10.8379, 11.3612, 11.9047] +24-11-19 19:04:43 | D | best error = [ 0.3958, 0.3958, 0.3958, 0.3958, 0.3958] +24-11-19 19:04:43 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:04:43 | D | sum error = [ 12.4675, 13.0514, 13.6547, 14.2826, 14.9305] +24-11-19 19:04:43 | D | best error = [ 0.3958, 0.3958, 0.3958, 0.3958, 0.3958] +24-11-19 19:04:43 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:04:43 | D | sum error = [ 15.6021, 16.2973, 17.0163, 17.7579, 18.5226] +24-11-19 19:04:43 | D | best error = [ 0.3958, 0.3958, 0.3958, 0.3958, 0.3958] +24-11-19 19:04:43 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:04:43 | D | sum error = [ 19.3113, 20.1233, 20.9596, 21.8216, 22.7095] +24-11-19 19:04:43 | D | best error = [ 0.3958, 0.3958, 0.3958, 0.3958, 0.3958] +24-11-19 19:04:43 | D | + error = [0.3958] +24-11-19 19:04:43 | D | - Calibrating model.layers.24.mlp.up_proj.weight +24-11-19 19:04:43 | D | + w: sint8 +24-11-19 19:04:43 | D | + x: None +24-11-19 19:04:43 | D | + y: None +24-11-19 19:04:43 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:04:43 | D | + finished parsing calibration arguments, ram usage: 11.9 +24-11-19 19:04:44 | D | + finished reseting calibrator, ram usage: 11.9 +24-11-19 19:04:44 | D | + finished calculating the original outputs, ram usage: 11.9 +24-11-19 19:04:44 | D | - range ratio = [ 1.0000] +24-11-19 19:04:44 | D | sum error = [ 7.7926] +24-11-19 19:04:44 | D | best error = [ 7.7926] +24-11-19 19:04:45 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:04:45 | D | sum error = [ 7.7183, 7.7217, 7.7354, 7.8169, 7.9710] +24-11-19 19:04:45 | D | best error = [ 7.1320, 6.8851, 6.7530, 6.6797, 6.6398] +24-11-19 19:04:45 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:04:45 | D | sum error = [ 8.1932, 8.4586, 8.7830, 9.1793, 9.6857] +24-11-19 19:04:45 | D | best error = [ 6.6212, 6.6122, 6.6094, 6.6082, 6.6078] +24-11-19 19:04:45 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:04:45 | D | sum error = [ 10.2418, 10.8941, 11.5780, 12.3574, 13.2075] +24-11-19 19:04:45 | D | best error = [ 6.6077, 6.6077, 6.6077, 6.6077, 6.6077] +24-11-19 19:04:45 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:04:45 | D | sum error = [ 14.1434, 15.1385, 16.2147, 17.3730, 18.6145] +24-11-19 19:04:45 | D | best error = [ 6.6077, 6.6077, 6.6077, 6.6077, 6.6077] +24-11-19 19:04:45 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:04:45 | D | sum error = [ 19.9420, 21.3732, 22.8631, 24.4509, 26.1557] +24-11-19 19:04:45 | D | best error = [ 6.6077, 6.6077, 6.6077, 6.6077, 6.6077] +24-11-19 19:04:45 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:04:45 | D | sum error = [ 27.9422, 29.8156, 31.8150, 33.9348, 36.1344] +24-11-19 19:04:45 | D | best error = [ 6.6077, 6.6077, 6.6077, 6.6077, 6.6077] +24-11-19 19:04:45 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:04:45 | D | sum error = [ 38.4650, 40.9320, 43.5316, 46.2553, 49.1193] +24-11-19 19:04:45 | D | best error = [ 6.6077, 6.6077, 6.6077, 6.6077, 6.6077] +24-11-19 19:04:45 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:04:45 | D | sum error = [ 52.1486, 55.3218, 58.6343, 62.1182, 65.7630] +24-11-19 19:04:45 | D | best error = [ 6.6077, 6.6077, 6.6077, 6.6077, 6.6077] +24-11-19 19:04:45 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:04:45 | D | sum error = [ 69.5991, 73.6108, 77.8027, 82.1969, 86.7616] +24-11-19 19:04:45 | D | best error = [ 6.6077, 6.6077, 6.6077, 6.6077, 6.6077] +24-11-19 19:04:45 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:04:45 | D | sum error = [ 91.5596, 96.5502, 101.7481, 107.2139, 112.8616] +24-11-19 19:04:45 | D | best error = [ 6.6077, 6.6077, 6.6077, 6.6077, 6.6077] +24-11-19 19:04:45 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:04:45 | D | sum error = [ 118.7586, 124.9062, 131.2904, 137.9397, 144.8280] +24-11-19 19:04:45 | D | best error = [ 6.6077, 6.6077, 6.6077, 6.6077, 6.6077] +24-11-19 19:04:45 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:04:45 | D | sum error = [ 151.9718, 159.3875, 167.0630, 175.0527, 183.2993] +24-11-19 19:04:45 | D | best error = [ 6.6077, 6.6077, 6.6077, 6.6077, 6.6077] +24-11-19 19:04:45 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:04:45 | D | sum error = [ 191.8599, 200.7081, 209.8574, 219.3170, 229.0905] +24-11-19 19:04:45 | D | best error = [ 6.6077, 6.6077, 6.6077, 6.6077, 6.6077] +24-11-19 19:04:45 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:04:45 | D | sum error = [ 239.1749, 249.5797, 260.3077, 271.3756, 282.7525] +24-11-19 19:04:45 | D | best error = [ 6.6077, 6.6077, 6.6077, 6.6077, 6.6077] +24-11-19 19:04:45 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:04:45 | D | sum error = [ 294.4829, 306.5473, 318.9549, 331.7333, 344.8509] +24-11-19 19:04:45 | D | best error = [ 6.6077, 6.6077, 6.6077, 6.6077, 6.6077] +24-11-19 19:04:45 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:04:45 | D | sum error = [ 358.3235, 372.1582, 386.3725, 400.9584, 415.9200] +24-11-19 19:04:45 | D | best error = [ 6.6077, 6.6077, 6.6077, 6.6077, 6.6077] +24-11-19 19:04:45 | D | + error = [6.6077] +24-11-19 19:04:45 | D | - Calibrating model.layers.24.mlp.gate_proj.weight +24-11-19 19:04:45 | D | + w: sint8 +24-11-19 19:04:45 | D | + x: None +24-11-19 19:04:45 | D | + y: None +24-11-19 19:04:45 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:04:45 | D | + finished parsing calibration arguments, ram usage: 12.0 +24-11-19 19:04:45 | D | + finished reseting calibrator, ram usage: 12.0 +24-11-19 19:04:45 | D | + finished calculating the original outputs, ram usage: 12.0 +24-11-19 19:04:45 | D | - range ratio = [ 1.0000] +24-11-19 19:04:45 | D | sum error = [ 10.4818] +24-11-19 19:04:45 | D | best error = [ 10.4818] +24-11-19 19:04:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:04:46 | D | sum error = [ 10.4447, 10.4173, 10.4425, 10.5731, 10.7610] +24-11-19 19:04:46 | D | best error = [ 9.6173, 9.2792, 9.1107, 9.0131, 8.9612] +24-11-19 19:04:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:04:46 | D | sum error = [ 11.0429, 11.3878, 11.8345, 12.3815, 13.0687] +24-11-19 19:04:46 | D | best error = [ 8.9351, 8.9239, 8.9191, 8.9174, 8.9167] +24-11-19 19:04:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:04:46 | D | sum error = [ 13.7903, 14.6514, 15.6248, 16.6616, 17.7918] +24-11-19 19:04:46 | D | best error = [ 8.9166, 8.9166, 8.9166, 8.9166, 8.9166] +24-11-19 19:04:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:04:46 | D | sum error = [ 19.0407, 20.3997, 21.8471, 23.4210, 25.1202] +24-11-19 19:04:46 | D | best error = [ 8.9166, 8.9166, 8.9166, 8.9166, 8.9166] +24-11-19 19:04:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:04:46 | D | sum error = [ 26.9183, 28.8386, 30.8767, 33.0538, 35.3838] +24-11-19 19:04:46 | D | best error = [ 8.9166, 8.9166, 8.9166, 8.9166, 8.9166] +24-11-19 19:04:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:04:46 | D | sum error = [ 37.8463, 40.4599, 43.2254, 46.1080, 49.2449] +24-11-19 19:04:46 | D | best error = [ 8.9166, 8.9166, 8.9166, 8.9166, 8.9166] +24-11-19 19:04:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:04:46 | D | sum error = [ 52.5012, 55.9408, 59.5835, 63.4596, 67.5581] +24-11-19 19:04:46 | D | best error = [ 8.9166, 8.9166, 8.9166, 8.9166, 8.9166] +24-11-19 19:04:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:04:46 | D | sum error = [ 71.8118, 76.3772, 81.1286, 86.1736, 91.4549] +24-11-19 19:04:46 | D | best error = [ 8.9166, 8.9166, 8.9166, 8.9166, 8.9166] +24-11-19 19:04:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:04:46 | D | sum error = [ 97.0594, 102.9189, 109.1307, 115.6446, 122.5296] +24-11-19 19:04:46 | D | best error = [ 8.9166, 8.9166, 8.9166, 8.9166, 8.9166] +24-11-19 19:04:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:04:46 | D | sum error = [ 129.7297, 137.2882, 145.2535, 153.6109, 162.3858] +24-11-19 19:04:46 | D | best error = [ 8.9166, 8.9166, 8.9166, 8.9166, 8.9166] +24-11-19 19:04:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:04:46 | D | sum error = [ 171.6073, 181.2619, 191.4024, 202.0027, 213.1426] +24-11-19 19:04:46 | D | best error = [ 8.9166, 8.9166, 8.9166, 8.9166, 8.9166] +24-11-19 19:04:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:04:46 | D | sum error = [ 224.8035, 236.9884, 249.7697, 263.1025, 277.0051] +24-11-19 19:04:46 | D | best error = [ 8.9166, 8.9166, 8.9166, 8.9166, 8.9166] +24-11-19 19:04:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:04:46 | D | sum error = [ 291.5519, 306.7060, 322.4721, 338.9186, 356.0551] +24-11-19 19:04:46 | D | best error = [ 8.9166, 8.9166, 8.9166, 8.9166, 8.9166] +24-11-19 19:04:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:04:46 | D | sum error = [ 373.8896, 392.4710, 411.7367, 431.7103, 452.4298] +24-11-19 19:04:46 | D | best error = [ 8.9166, 8.9166, 8.9166, 8.9166, 8.9166] +24-11-19 19:04:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:04:46 | D | sum error = [ 473.9166, 496.2150, 519.3141, 543.2231, 567.9860] +24-11-19 19:04:46 | D | best error = [ 8.9166, 8.9166, 8.9166, 8.9166, 8.9166] +24-11-19 19:04:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:04:46 | D | sum error = [ 593.5831, 619.9992, 647.2775, 675.3770, 704.3226] +24-11-19 19:04:46 | D | best error = [ 8.9166, 8.9166, 8.9166, 8.9166, 8.9166] +24-11-19 19:04:46 | D | + error = [8.9166] +24-11-19 19:04:46 | D | - Calibrating model.layers.24.mlp.down_proj.weight +24-11-19 19:04:46 | D | + w: sint8 +24-11-19 19:04:46 | D | + x: None +24-11-19 19:04:46 | D | + y: None +24-11-19 19:04:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:04:46 | D | + finished parsing calibration arguments, ram usage: 12.1 +24-11-19 19:04:46 | D | + finished reseting calibrator, ram usage: 12.1 +24-11-19 19:04:47 | D | + finished calculating the original outputs, ram usage: 12.1 +24-11-19 19:04:47 | D | - range ratio = [ 1.0000] +24-11-19 19:04:47 | D | sum error = [ 1.1968] +24-11-19 19:04:47 | D | best error = [ 1.1968] +24-11-19 19:04:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:04:48 | D | sum error = [ 1.1843, 1.1767, 1.1697, 1.1655, 1.1654] +24-11-19 19:04:48 | D | best error = [ 1.1430, 1.1164, 1.0988, 1.0857, 1.0754] +24-11-19 19:04:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:04:48 | D | sum error = [ 1.1723, 1.1772, 1.1877, 1.2063, 1.2310] +24-11-19 19:04:48 | D | best error = [ 1.0679, 1.0613, 1.0563, 1.0526, 1.0497] +24-11-19 19:04:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:04:48 | D | sum error = [ 1.2620, 1.2976, 1.3437, 1.3978, 1.4575] +24-11-19 19:04:48 | D | best error = [ 1.0474, 1.0460, 1.0451, 1.0443, 1.0438] +24-11-19 19:04:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:04:48 | D | sum error = [ 1.5283, 1.6068, 1.6934, 1.7954, 1.9035] +24-11-19 19:04:48 | D | best error = [ 1.0435, 1.0434, 1.0432, 1.0432, 1.0431] +24-11-19 19:04:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:04:48 | D | sum error = [ 2.0189, 2.1513, 2.2967, 2.4468, 2.6116] +24-11-19 19:04:48 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 19:04:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:04:48 | D | sum error = [ 2.7845, 2.9754, 3.1790, 3.3977, 3.6316] +24-11-19 19:04:48 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 19:04:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:04:48 | D | sum error = [ 3.8797, 4.1412, 4.4208, 4.7179, 5.0319] +24-11-19 19:04:48 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 19:04:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:04:48 | D | sum error = [ 5.3729, 5.7220, 6.1018, 6.4985, 6.9222] +24-11-19 19:04:48 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 19:04:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:04:48 | D | sum error = [ 7.3735, 7.8444, 8.3435, 8.8731, 9.4341] +24-11-19 19:04:48 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 19:04:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:04:48 | D | sum error = [ 10.0190, 10.6404, 11.2939, 11.9856, 12.7120] +24-11-19 19:04:48 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 19:04:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:04:48 | D | sum error = [ 13.4751, 14.2792, 15.1236, 16.0115, 16.9432] +24-11-19 19:04:48 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 19:04:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:04:48 | D | sum error = [ 17.9207, 18.9456, 20.0172, 21.1427, 22.3193] +24-11-19 19:04:48 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 19:04:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:04:48 | D | sum error = [ 23.5492, 24.8351, 26.1799, 27.5865, 29.0553] +24-11-19 19:04:48 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 19:04:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:04:48 | D | sum error = [ 30.5847, 32.1806, 33.8451, 35.5785, 37.3814] +24-11-19 19:04:48 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 19:04:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:04:48 | D | sum error = [ 39.2549, 41.2006, 43.2227, 45.3203, 47.4973] +24-11-19 19:04:48 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 19:04:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:04:48 | D | sum error = [ 49.7536, 52.0926, 54.5130, 57.0184, 59.6090] +24-11-19 19:04:48 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 19:04:48 | D | + error = [1.0431] +24-11-19 19:04:48 | D | - Quantizing model.layers.24.self_attn.q_proj.weight +24-11-19 19:04:49 | D | - Quantizing model.layers.24.self_attn.k_proj.weight +24-11-19 19:04:50 | D | - Quantizing model.layers.24.self_attn.v_proj.weight +24-11-19 19:04:51 | D | - Quantizing model.layers.24.self_attn.o_proj.weight +24-11-19 19:04:52 | D | - Quantizing model.layers.24.mlp.up_proj.weight +24-11-19 19:04:53 | D | - Quantizing model.layers.24.mlp.gate_proj.weight +24-11-19 19:04:54 | D | - Quantizing model.layers.24.mlp.down_proj.weight +24-11-19 19:05:05 | D | - Quantizing layer model.layers.25 +24-11-19 19:05:05 | D | - Calibrating model.layers.25.self_attn.q_proj.weight +24-11-19 19:05:05 | D | + w: sint8 +24-11-19 19:05:05 | D | + x: None +24-11-19 19:05:05 | D | + y: None +24-11-19 19:05:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:05:05 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:05:05 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:05:06 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:05:06 | D | - range ratio = [ 1.0000] +24-11-19 19:05:06 | D | sum error = [ 5.2701] +24-11-19 19:05:06 | D | best error = [ 5.2701] +24-11-19 19:05:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:05:18 | D | sum error = [ 5.5110, 5.4767, 5.4146, 5.5176, 5.8145] +24-11-19 19:05:18 | D | best error = [ 5.2701, 5.2701, 5.2701, 5.2701, 5.2701] +24-11-19 19:05:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:05:18 | D | sum error = [ 5.6015, 5.8005, 6.3239, 6.6500, 7.2311] +24-11-19 19:05:18 | D | best error = [ 5.2701, 5.2701, 5.2701, 5.2701, 5.2701] +24-11-19 19:05:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:05:18 | D | sum error = [ 7.8903, 8.4715, 9.2157, 10.0234, 10.6703] +24-11-19 19:05:18 | D | best error = [ 5.2701, 5.2701, 5.2701, 5.2701, 5.2701] +24-11-19 19:05:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:05:18 | D | sum error = [ 11.9850, 13.1731, 14.1703, 15.5132, 17.4324] +24-11-19 19:05:18 | D | best error = [ 5.2701, 5.2701, 5.2701, 5.2701, 5.2701] +24-11-19 19:05:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:05:18 | D | sum error = [ 19.0236, 20.2177, 22.0936, 23.8875, 25.2051] +24-11-19 19:05:18 | D | best error = [ 5.2701, 5.2701, 5.2701, 5.2701, 5.2701] +24-11-19 19:05:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:05:18 | D | sum error = [ 27.0828, 29.7772, 32.4946, 34.9494, 37.7513] +24-11-19 19:05:18 | D | best error = [ 5.2701, 5.2701, 5.2701, 5.2701, 5.2701] +24-11-19 19:05:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:05:18 | D | sum error = [ 40.7631, 44.3876, 47.6836, 52.0907, 56.3822] +24-11-19 19:05:18 | D | best error = [ 5.2701, 5.2701, 5.2701, 5.2701, 5.2701] +24-11-19 19:05:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:05:18 | D | sum error = [ 60.8674, 65.6734, 70.5399, 76.3957, 82.6871] +24-11-19 19:05:18 | D | best error = [ 5.2701, 5.2701, 5.2701, 5.2701, 5.2701] +24-11-19 19:05:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:05:18 | D | sum error = [ 89.2350, 96.0033, 103.1364, 111.3458, 119.7705] +24-11-19 19:05:18 | D | best error = [ 5.2701, 5.2701, 5.2701, 5.2701, 5.2701] +24-11-19 19:05:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:05:18 | D | sum error = [ 128.7197, 138.3279, 148.2517, 159.5659, 171.8853] +24-11-19 19:05:18 | D | best error = [ 5.2701, 5.2701, 5.2701, 5.2701, 5.2701] +24-11-19 19:05:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:05:18 | D | sum error = [ 184.3814, 196.9761, 211.1884, 226.9751, 243.1558] +24-11-19 19:05:18 | D | best error = [ 5.2701, 5.2701, 5.2701, 5.2701, 5.2701] +24-11-19 19:05:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:05:18 | D | sum error = [ 260.2251, 279.0274, 298.7941, 321.3055, 345.2567] +24-11-19 19:05:18 | D | best error = [ 5.2701, 5.2701, 5.2701, 5.2701, 5.2701] +24-11-19 19:05:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:05:18 | D | sum error = [ 370.8201, 398.6680, 428.7038, 460.5252, 495.0964] +24-11-19 19:05:18 | D | best error = [ 5.2701, 5.2701, 5.2701, 5.2701, 5.2701] +24-11-19 19:05:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:05:18 | D | sum error = [ 533.4533, 575.2654, 620.3211, 669.7873, 723.4511] +24-11-19 19:05:18 | D | best error = [ 5.2701, 5.2701, 5.2701, 5.2701, 5.2701] +24-11-19 19:05:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:05:18 | D | sum error = [ 781.5219, 844.9673, 913.2209, 985.9628, 1065.3228] +24-11-19 19:05:18 | D | best error = [ 5.2701, 5.2701, 5.2701, 5.2701, 5.2701] +24-11-19 19:05:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:05:18 | D | sum error = [ 1150.1990, 1241.9069, 1338.5162, 1439.7769, 1545.4926] +24-11-19 19:05:18 | D | best error = [ 5.2701, 5.2701, 5.2701, 5.2701, 5.2701] +24-11-19 19:05:18 | D | + error = [5.2701] +24-11-19 19:05:18 | D | - Calibrating model.layers.25.self_attn.k_proj.weight +24-11-19 19:05:18 | D | + w: sint8 +24-11-19 19:05:18 | D | + x: None +24-11-19 19:05:18 | D | + y: None +24-11-19 19:05:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:05:18 | D | + finished parsing calibration arguments, ram usage: 12.2 +24-11-19 19:05:18 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:05:19 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:05:19 | D | - range ratio = [ 1.0000] +24-11-19 19:05:19 | D | sum error = [ 6.6887] +24-11-19 19:05:19 | D | best error = [ 6.6887] +24-11-19 19:05:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:05:31 | D | sum error = [ 6.8163, 6.3375, 5.8625, 7.5800, 6.1880] +24-11-19 19:05:31 | D | best error = [ 6.6887, 6.3375, 5.8625, 5.8625, 5.8625] +24-11-19 19:05:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:05:31 | D | sum error = [ 7.1638, 6.2825, 7.0026, 7.2548, 8.5431] +24-11-19 19:05:31 | D | best error = [ 5.8625, 5.8625, 5.8625, 5.8625, 5.8625] +24-11-19 19:05:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:05:31 | D | sum error = [ 8.9755, 10.4230, 9.8744, 12.4351, 9.9962] +24-11-19 19:05:31 | D | best error = [ 5.8625, 5.8625, 5.8625, 5.8625, 5.8625] +24-11-19 19:05:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:05:31 | D | sum error = [ 13.1702, 10.9281, 13.8550, 13.7684, 15.9642] +24-11-19 19:05:31 | D | best error = [ 5.8625, 5.8625, 5.8625, 5.8625, 5.8625] +24-11-19 19:05:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:05:31 | D | sum error = [ 17.0612, 19.3003, 20.5168, 22.5308, 23.8629] +24-11-19 19:05:31 | D | best error = [ 5.8625, 5.8625, 5.8625, 5.8625, 5.8625] +24-11-19 19:05:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:05:31 | D | sum error = [ 25.9637, 27.8612, 29.7764, 33.2885, 35.6900] +24-11-19 19:05:31 | D | best error = [ 5.8625, 5.8625, 5.8625, 5.8625, 5.8625] +24-11-19 19:05:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:05:31 | D | sum error = [ 39.3053, 40.7311, 42.5632, 45.5860, 50.5427] +24-11-19 19:05:31 | D | best error = [ 5.8625, 5.8625, 5.8625, 5.8625, 5.8625] +24-11-19 19:05:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:05:31 | D | sum error = [ 53.3856, 56.9994, 59.7563, 64.3845, 70.3455] +24-11-19 19:05:31 | D | best error = [ 5.8625, 5.8625, 5.8625, 5.8625, 5.8625] +24-11-19 19:05:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:05:31 | D | sum error = [ 74.1416, 78.9380, 82.9605, 88.3690, 95.1030] +24-11-19 19:05:31 | D | best error = [ 5.8625, 5.8625, 5.8625, 5.8625, 5.8625] +24-11-19 19:05:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:05:31 | D | sum error = [ 101.1449, 105.9946, 113.0210, 120.5402, 129.0362] +24-11-19 19:05:31 | D | best error = [ 5.8625, 5.8625, 5.8625, 5.8625, 5.8625] +24-11-19 19:05:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:05:31 | D | sum error = [ 136.2766, 146.8080, 158.2456, 168.6277, 180.7779] +24-11-19 19:05:31 | D | best error = [ 5.8625, 5.8625, 5.8625, 5.8625, 5.8625] +24-11-19 19:05:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:05:31 | D | sum error = [ 195.6509, 211.1577, 226.7972, 244.8622, 262.7826] +24-11-19 19:05:31 | D | best error = [ 5.8625, 5.8625, 5.8625, 5.8625, 5.8625] +24-11-19 19:05:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:05:31 | D | sum error = [ 285.3591, 310.9706, 334.2684, 364.4049, 397.6109] +24-11-19 19:05:31 | D | best error = [ 5.8625, 5.8625, 5.8625, 5.8625, 5.8625] +24-11-19 19:05:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:05:31 | D | sum error = [ 429.9538, 464.6294, 507.5136, 552.3321, 599.2164] +24-11-19 19:05:31 | D | best error = [ 5.8625, 5.8625, 5.8625, 5.8625, 5.8625] +24-11-19 19:05:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:05:31 | D | sum error = [ 651.7464, 708.3867, 777.9968, 851.2465, 925.9062] +24-11-19 19:05:31 | D | best error = [ 5.8625, 5.8625, 5.8625, 5.8625, 5.8625] +24-11-19 19:05:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:05:31 | D | sum error = [ 1009.9865, 1101.8179, 1195.8205, 1302.3767, 1417.6563] +24-11-19 19:05:31 | D | best error = [ 5.8625, 5.8625, 5.8625, 5.8625, 5.8625] +24-11-19 19:05:31 | D | + error = [5.8625] +24-11-19 19:05:31 | D | - Calibrating model.layers.25.self_attn.v_proj.weight +24-11-19 19:05:31 | D | + w: sint8 +24-11-19 19:05:31 | D | + x: None +24-11-19 19:05:31 | D | + y: None +24-11-19 19:05:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:05:31 | D | + finished parsing calibration arguments, ram usage: 12.1 +24-11-19 19:05:31 | D | + finished reseting calibrator, ram usage: 12.1 +24-11-19 19:05:32 | D | + finished calculating the original outputs, ram usage: 12.1 +24-11-19 19:05:32 | D | - range ratio = [ 1.0000] +24-11-19 19:05:32 | D | sum error = [ 2.4341] +24-11-19 19:05:32 | D | best error = [ 2.4341] +24-11-19 19:05:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:05:32 | D | sum error = [ 2.4355, 2.4230, 2.4442, 2.4452, 2.4879] +24-11-19 19:05:32 | D | best error = [ 2.2240, 2.1409, 2.1030, 2.0832, 2.0702] +24-11-19 19:05:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:05:32 | D | sum error = [ 2.5593, 2.6551, 2.7346, 2.8482, 3.0240] +24-11-19 19:05:32 | D | best error = [ 2.0626, 2.0594, 2.0582, 2.0581, 2.0581] +24-11-19 19:05:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:05:32 | D | sum error = [ 3.2088, 3.4213, 3.6362, 3.8720, 4.1415] +24-11-19 19:05:32 | D | best error = [ 2.0581, 2.0581, 2.0581, 2.0581, 2.0581] +24-11-19 19:05:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:05:32 | D | sum error = [ 4.4387, 4.7773, 5.0741, 5.4517, 5.8664] +24-11-19 19:05:32 | D | best error = [ 2.0581, 2.0581, 2.0581, 2.0581, 2.0581] +24-11-19 19:05:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:05:32 | D | sum error = [ 6.2984, 6.7347, 7.1749, 7.6865, 8.1995] +24-11-19 19:05:32 | D | best error = [ 2.0581, 2.0581, 2.0581, 2.0581, 2.0581] +24-11-19 19:05:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:05:32 | D | sum error = [ 8.8026, 9.3851, 10.0038, 10.6626, 11.3671] +24-11-19 19:05:32 | D | best error = [ 2.0581, 2.0581, 2.0581, 2.0581, 2.0581] +24-11-19 19:05:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:05:32 | D | sum error = [ 12.0966, 12.8922, 13.6821, 14.5534, 15.4850] +24-11-19 19:05:32 | D | best error = [ 2.0581, 2.0581, 2.0581, 2.0581, 2.0581] +24-11-19 19:05:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:05:32 | D | sum error = [ 16.4481, 17.4578, 18.5353, 19.6379, 20.8233] +24-11-19 19:05:32 | D | best error = [ 2.0581, 2.0581, 2.0581, 2.0581, 2.0581] +24-11-19 19:05:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:05:32 | D | sum error = [ 22.0410, 23.3599, 24.7009, 26.1244, 27.6192] +24-11-19 19:05:32 | D | best error = [ 2.0581, 2.0581, 2.0581, 2.0581, 2.0581] +24-11-19 19:05:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:05:32 | D | sum error = [ 29.1940, 30.8287, 32.5319, 34.3020, 36.1733] +24-11-19 19:05:32 | D | best error = [ 2.0581, 2.0581, 2.0581, 2.0581, 2.0581] +24-11-19 19:05:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:05:32 | D | sum error = [ 38.1280, 40.1646, 42.2686, 44.4924, 46.7915] +24-11-19 19:05:32 | D | best error = [ 2.0581, 2.0581, 2.0581, 2.0581, 2.0581] +24-11-19 19:05:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:05:32 | D | sum error = [ 49.1987, 51.7242, 54.3242, 57.0410, 59.8794] +24-11-19 19:05:32 | D | best error = [ 2.0581, 2.0581, 2.0581, 2.0581, 2.0581] +24-11-19 19:05:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:05:32 | D | sum error = [ 62.8049, 65.8530, 69.0114, 72.2826, 75.6782] +24-11-19 19:05:32 | D | best error = [ 2.0581, 2.0581, 2.0581, 2.0581, 2.0581] +24-11-19 19:05:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:05:32 | D | sum error = [ 79.2047, 82.8245, 86.5778, 90.4754, 94.4993] +24-11-19 19:05:32 | D | best error = [ 2.0581, 2.0581, 2.0581, 2.0581, 2.0581] +24-11-19 19:05:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:05:32 | D | sum error = [ 98.6663, 102.9636, 107.3974, 111.9674, 116.6584] +24-11-19 19:05:32 | D | best error = [ 2.0581, 2.0581, 2.0581, 2.0581, 2.0581] +24-11-19 19:05:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:05:32 | D | sum error = [ 121.5005, 126.4888, 131.6162, 136.8745, 142.2845] +24-11-19 19:05:32 | D | best error = [ 2.0581, 2.0581, 2.0581, 2.0581, 2.0581] +24-11-19 19:05:32 | D | + error = [2.0581] +24-11-19 19:05:32 | D | - Calibrating model.layers.25.self_attn.o_proj.weight +24-11-19 19:05:32 | D | + w: sint8 +24-11-19 19:05:32 | D | + x: None +24-11-19 19:05:32 | D | + y: None +24-11-19 19:05:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:05:32 | D | + finished parsing calibration arguments, ram usage: 12.2 +24-11-19 19:05:32 | D | + finished reseting calibrator, ram usage: 12.2 +24-11-19 19:05:32 | D | + finished calculating the original outputs, ram usage: 12.2 +24-11-19 19:05:32 | D | - range ratio = [ 1.0000] +24-11-19 19:05:32 | D | sum error = [ 0.5030] +24-11-19 19:05:32 | D | best error = [ 0.5030] +24-11-19 19:05:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:05:32 | D | sum error = [ 0.4974, 0.4958, 0.4938, 0.4947, 0.4969] +24-11-19 19:05:32 | D | best error = [ 0.4707, 0.4562, 0.4470, 0.4407, 0.4361] +24-11-19 19:05:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:05:32 | D | sum error = [ 0.5017, 0.5098, 0.5214, 0.5343, 0.5523] +24-11-19 19:05:32 | D | best error = [ 0.4323, 0.4300, 0.4283, 0.4269, 0.4260] +24-11-19 19:05:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:05:32 | D | sum error = [ 0.5712, 0.5957, 0.6224, 0.6547, 0.6869] +24-11-19 19:05:32 | D | best error = [ 0.4255, 0.4250, 0.4246, 0.4243, 0.4240] +24-11-19 19:05:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:05:32 | D | sum error = [ 0.7272, 0.7704, 0.8175, 0.8695, 0.9241] +24-11-19 19:05:32 | D | best error = [ 0.4238, 0.4238, 0.4238, 0.4237, 0.4237] +24-11-19 19:05:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:05:32 | D | sum error = [ 0.9858, 1.0494, 1.1193, 1.1937, 1.2729] +24-11-19 19:05:32 | D | best error = [ 0.4237, 0.4236, 0.4236, 0.4236, 0.4236] +24-11-19 19:05:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:05:32 | D | sum error = [ 1.3588, 1.4488, 1.5441, 1.6459, 1.7543] +24-11-19 19:05:32 | D | best error = [ 0.4236, 0.4236, 0.4236, 0.4236, 0.4236] +24-11-19 19:05:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:05:32 | D | sum error = [ 1.8707, 1.9913, 2.1216, 2.2579, 2.4026] +24-11-19 19:05:32 | D | best error = [ 0.4236, 0.4236, 0.4236, 0.4236, 0.4236] +24-11-19 19:05:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:05:32 | D | sum error = [ 2.5548, 2.7181, 2.8889, 3.0692, 3.2592] +24-11-19 19:05:32 | D | best error = [ 0.4236, 0.4236, 0.4236, 0.4236, 0.4236] +24-11-19 19:05:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:05:32 | D | sum error = [ 3.4597, 3.6720, 3.8950, 4.1297, 4.3784] +24-11-19 19:05:32 | D | best error = [ 0.4236, 0.4236, 0.4236, 0.4236, 0.4236] +24-11-19 19:05:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:05:32 | D | sum error = [ 4.6379, 4.9123, 5.2002, 5.5032, 5.8202] +24-11-19 19:05:32 | D | best error = [ 0.4236, 0.4236, 0.4236, 0.4236, 0.4236] +24-11-19 19:05:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:05:32 | D | sum error = [ 6.1552, 6.5058, 6.8745, 7.2612, 7.6653] +24-11-19 19:05:32 | D | best error = [ 0.4236, 0.4236, 0.4236, 0.4236, 0.4236] +24-11-19 19:05:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:05:32 | D | sum error = [ 8.0897, 8.5361, 9.0034, 9.4926, 10.0039] +24-11-19 19:05:32 | D | best error = [ 0.4236, 0.4236, 0.4236, 0.4236, 0.4236] +24-11-19 19:05:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:05:32 | D | sum error = [ 10.5397, 11.1001, 11.6856, 12.2984, 12.9383] +24-11-19 19:05:32 | D | best error = [ 0.4236, 0.4236, 0.4236, 0.4236, 0.4236] +24-11-19 19:05:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:05:32 | D | sum error = [ 13.6062, 14.3023, 15.0299, 15.7878, 16.5751] +24-11-19 19:05:32 | D | best error = [ 0.4236, 0.4236, 0.4236, 0.4236, 0.4236] +24-11-19 19:05:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:05:32 | D | sum error = [ 17.3952, 18.2483, 19.1345, 20.0561, 21.0131] +24-11-19 19:05:32 | D | best error = [ 0.4236, 0.4236, 0.4236, 0.4236, 0.4236] +24-11-19 19:05:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:05:32 | D | sum error = [ 22.0068, 23.0353, 24.1009, 25.2030, 26.3439] +24-11-19 19:05:32 | D | best error = [ 0.4236, 0.4236, 0.4236, 0.4236, 0.4236] +24-11-19 19:05:32 | D | + error = [0.4236] +24-11-19 19:05:33 | D | - Calibrating model.layers.25.mlp.up_proj.weight +24-11-19 19:05:33 | D | + w: sint8 +24-11-19 19:05:33 | D | + x: None +24-11-19 19:05:33 | D | + y: None +24-11-19 19:05:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:05:33 | D | + finished parsing calibration arguments, ram usage: 12.2 +24-11-19 19:05:33 | D | + finished reseting calibrator, ram usage: 12.2 +24-11-19 19:05:33 | D | + finished calculating the original outputs, ram usage: 12.2 +24-11-19 19:05:33 | D | - range ratio = [ 1.0000] +24-11-19 19:05:33 | D | sum error = [ 8.1410] +24-11-19 19:05:33 | D | best error = [ 8.1410] +24-11-19 19:05:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:05:34 | D | sum error = [ 8.0786, 8.0705, 8.0805, 8.2032, 8.3502] +24-11-19 19:05:34 | D | best error = [ 7.3763, 7.1028, 6.9632, 6.8864, 6.8432] +24-11-19 19:05:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:05:34 | D | sum error = [ 8.5378, 8.8465, 9.1937, 9.6072, 10.1126] +24-11-19 19:05:34 | D | best error = [ 6.8228, 6.8132, 6.8090, 6.8077, 6.8074] +24-11-19 19:05:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:05:34 | D | sum error = [ 10.7032, 11.3542, 12.0955, 12.9234, 13.7670] +24-11-19 19:05:34 | D | best error = [ 6.8074, 6.8074, 6.8074, 6.8074, 6.8074] +24-11-19 19:05:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:05:34 | D | sum error = [ 14.7440, 15.7931, 16.9369, 18.1412, 19.4302] +24-11-19 19:05:34 | D | best error = [ 6.8074, 6.8074, 6.8074, 6.8074, 6.8074] +24-11-19 19:05:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:05:34 | D | sum error = [ 20.7821, 22.2752, 23.8440, 25.5007, 27.2941] +24-11-19 19:05:34 | D | best error = [ 6.8074, 6.8074, 6.8074, 6.8074, 6.8074] +24-11-19 19:05:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:05:34 | D | sum error = [ 29.1351, 31.1270, 33.2100, 35.4315, 37.7377] +24-11-19 19:05:34 | D | best error = [ 6.8074, 6.8074, 6.8074, 6.8074, 6.8074] +24-11-19 19:05:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:05:34 | D | sum error = [ 40.1721, 42.7552, 45.4597, 48.2878, 51.2855] +24-11-19 19:05:34 | D | best error = [ 6.8074, 6.8074, 6.8074, 6.8074, 6.8074] +24-11-19 19:05:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:05:34 | D | sum error = [ 54.4490, 57.7461, 61.2062, 64.8317, 68.6205] +24-11-19 19:05:34 | D | best error = [ 6.8074, 6.8074, 6.8074, 6.8074, 6.8074] +24-11-19 19:05:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:05:34 | D | sum error = [ 72.6071, 76.7497, 81.0887, 85.6698, 90.4168] +24-11-19 19:05:34 | D | best error = [ 6.8074, 6.8074, 6.8074, 6.8074, 6.8074] +24-11-19 19:05:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:05:34 | D | sum error = [ 95.3919, 100.5924, 106.0100, 111.6514, 117.5319] +24-11-19 19:05:34 | D | best error = [ 6.8074, 6.8074, 6.8074, 6.8074, 6.8074] +24-11-19 19:05:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:05:34 | D | sum error = [ 123.6422, 129.9809, 136.5716, 143.4084, 150.5025] +24-11-19 19:05:34 | D | best error = [ 6.8074, 6.8074, 6.8074, 6.8074, 6.8074] +24-11-19 19:05:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:05:34 | D | sum error = [ 157.8650, 165.5024, 173.4199, 181.6336, 190.1334] +24-11-19 19:05:34 | D | best error = [ 6.8074, 6.8074, 6.8074, 6.8074, 6.8074] +24-11-19 19:05:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:05:34 | D | sum error = [ 198.9433, 208.0420, 217.4504, 227.1609, 237.1918] +24-11-19 19:05:34 | D | best error = [ 6.8074, 6.8074, 6.8074, 6.8074, 6.8074] +24-11-19 19:05:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:05:34 | D | sum error = [ 247.5472, 258.2219, 269.2174, 280.5553, 292.2134] +24-11-19 19:05:34 | D | best error = [ 6.8074, 6.8074, 6.8074, 6.8074, 6.8074] +24-11-19 19:05:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:05:34 | D | sum error = [ 304.2020, 316.5376, 329.2208, 342.2596, 355.6462] +24-11-19 19:05:34 | D | best error = [ 6.8074, 6.8074, 6.8074, 6.8074, 6.8074] +24-11-19 19:05:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:05:34 | D | sum error = [ 369.4186, 383.5565, 398.0642, 412.9661, 428.2522] +24-11-19 19:05:34 | D | best error = [ 6.8074, 6.8074, 6.8074, 6.8074, 6.8074] +24-11-19 19:05:34 | D | + error = [6.8074] +24-11-19 19:05:34 | D | - Calibrating model.layers.25.mlp.gate_proj.weight +24-11-19 19:05:34 | D | + w: sint8 +24-11-19 19:05:34 | D | + x: None +24-11-19 19:05:34 | D | + y: None +24-11-19 19:05:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:05:34 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:05:34 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:05:34 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:05:34 | D | - range ratio = [ 1.0000] +24-11-19 19:05:34 | D | sum error = [ 10.9391] +24-11-19 19:05:34 | D | best error = [ 10.9391] +24-11-19 19:05:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:05:35 | D | sum error = [ 10.8715, 10.8532, 10.8992, 11.0190, 11.2061] +24-11-19 19:05:35 | D | best error = [ 9.9276, 9.5583, 9.3782, 9.2723, 9.2156] +24-11-19 19:05:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:05:35 | D | sum error = [ 11.5395, 11.8869, 12.4034, 13.0105, 13.6873] +24-11-19 19:05:35 | D | best error = [ 9.1859, 9.1714, 9.1665, 9.1645, 9.1641] +24-11-19 19:05:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:05:35 | D | sum error = [ 14.4635, 15.3671, 16.4001, 17.5093, 18.6909] +24-11-19 19:05:35 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 19:05:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:05:35 | D | sum error = [ 20.0394, 21.4643, 22.9807, 24.6722, 26.4526] +24-11-19 19:05:35 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 19:05:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:05:35 | D | sum error = [ 28.3204, 30.3768, 32.5283, 34.8516, 37.2383] +24-11-19 19:05:35 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 19:05:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:05:35 | D | sum error = [ 39.8814, 42.5737, 45.5212, 48.5662, 51.7860] +24-11-19 19:05:35 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 19:05:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:05:35 | D | sum error = [ 55.2406, 58.8787, 62.7752, 66.8267, 71.1313] +24-11-19 19:05:35 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 19:05:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:05:35 | D | sum error = [ 75.6156, 80.4511, 85.4831, 90.7507, 96.3126] +24-11-19 19:05:35 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 19:05:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:05:35 | D | sum error = [ 102.2011, 108.3889, 114.8495, 121.6863, 128.8300] +24-11-19 19:05:35 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 19:05:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:05:35 | D | sum error = [ 136.3783, 144.2855, 152.5706, 161.2801, 170.4641] +24-11-19 19:05:35 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 19:05:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:05:35 | D | sum error = [ 180.0030, 190.0445, 200.5666, 211.5504, 223.1052] +24-11-19 19:05:35 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 19:05:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:05:35 | D | sum error = [ 235.1191, 247.7707, 260.9392, 274.6984, 289.1026] +24-11-19 19:05:35 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 19:05:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:05:35 | D | sum error = [ 304.1673, 319.8624, 336.2257, 353.3089, 371.1043] +24-11-19 19:05:35 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 19:05:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:05:35 | D | sum error = [ 389.6246, 408.8402, 428.8756, 449.7021, 471.3079] +24-11-19 19:05:35 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 19:05:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:05:35 | D | sum error = [ 493.7484, 516.9825, 541.1014, 566.0058, 591.7450] +24-11-19 19:05:35 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 19:05:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:05:35 | D | sum error = [ 618.3474, 645.8176, 674.1442, 703.3239, 733.3685] +24-11-19 19:05:35 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 19:05:35 | D | + error = [9.1640] +24-11-19 19:05:36 | D | - Calibrating model.layers.25.mlp.down_proj.weight +24-11-19 19:05:36 | D | + w: sint8 +24-11-19 19:05:36 | D | + x: None +24-11-19 19:05:36 | D | + y: None +24-11-19 19:05:36 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:05:36 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:05:36 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:05:36 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:05:36 | D | - range ratio = [ 1.0000] +24-11-19 19:05:36 | D | sum error = [ 1.2566] +24-11-19 19:05:36 | D | best error = [ 1.2566] +24-11-19 19:05:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:05:37 | D | sum error = [ 1.2425, 1.2335, 1.2258, 1.2174, 1.2157] +24-11-19 19:05:37 | D | best error = [ 1.1996, 1.1737, 1.1562, 1.1431, 1.1320] +24-11-19 19:05:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:05:37 | D | sum error = [ 1.2156, 1.2193, 1.2244, 1.2385, 1.2572] +24-11-19 19:05:37 | D | best error = [ 1.1235, 1.1165, 1.1112, 1.1068, 1.1038] +24-11-19 19:05:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:05:37 | D | sum error = [ 1.2769, 1.3078, 1.3418, 1.3828, 1.4342] +24-11-19 19:05:37 | D | best error = [ 1.1017, 1.1003, 1.0993, 1.0984, 1.0977] +24-11-19 19:05:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:05:37 | D | sum error = [ 1.4955, 1.5604, 1.6349, 1.7236, 1.8224] +24-11-19 19:05:37 | D | best error = [ 1.0974, 1.0972, 1.0971, 1.0970, 1.0969] +24-11-19 19:05:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:05:37 | D | sum error = [ 1.9310, 2.0506, 2.1790, 2.3227, 2.4812] +24-11-19 19:05:37 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0969, 1.0969] +24-11-19 19:05:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:05:37 | D | sum error = [ 2.6467, 2.8320, 3.0309, 3.2445, 3.4717] +24-11-19 19:05:37 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0969, 1.0969] +24-11-19 19:05:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:05:37 | D | sum error = [ 3.7133, 3.9730, 4.2509, 4.5452, 4.8619] +24-11-19 19:05:37 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0969, 1.0969] +24-11-19 19:05:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:05:37 | D | sum error = [ 5.1957, 5.5513, 5.9295, 6.3299, 6.7549] +24-11-19 19:05:37 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0969, 1.0969] +24-11-19 19:05:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:05:37 | D | sum error = [ 7.2042, 7.6808, 8.1839, 8.7162, 9.2768] +24-11-19 19:05:37 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0969, 1.0969] +24-11-19 19:05:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:05:37 | D | sum error = [ 9.8736, 10.4988, 11.1604, 11.8558, 12.5892] +24-11-19 19:05:37 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0969, 1.0969] +24-11-19 19:05:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:05:37 | D | sum error = [ 13.3614, 14.1754, 15.0301, 15.9291, 16.8718] +24-11-19 19:05:37 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0969, 1.0969] +24-11-19 19:05:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:05:37 | D | sum error = [ 17.8620, 18.8978, 19.9858, 21.1243, 22.3172] +24-11-19 19:05:37 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0969, 1.0969] +24-11-19 19:05:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:05:37 | D | sum error = [ 23.5651, 24.8693, 26.2318, 27.6552, 29.1420] +24-11-19 19:05:37 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0969, 1.0969] +24-11-19 19:05:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:05:37 | D | sum error = [ 30.6915, 32.3051, 33.9859, 35.7375, 37.5580] +24-11-19 19:05:37 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0969, 1.0969] +24-11-19 19:05:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:05:37 | D | sum error = [ 39.4539, 41.4233, 43.4704, 45.5967, 47.8017] +24-11-19 19:05:37 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0969, 1.0969] +24-11-19 19:05:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:05:37 | D | sum error = [ 50.0886, 52.4594, 54.9123, 57.4508, 60.0757] +24-11-19 19:05:37 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0969, 1.0969] +24-11-19 19:05:37 | D | + error = [1.0969] +24-11-19 19:05:37 | D | - Quantizing model.layers.25.self_attn.q_proj.weight +24-11-19 19:05:38 | D | - Quantizing model.layers.25.self_attn.k_proj.weight +24-11-19 19:05:39 | D | - Quantizing model.layers.25.self_attn.v_proj.weight +24-11-19 19:05:40 | D | - Quantizing model.layers.25.self_attn.o_proj.weight +24-11-19 19:05:41 | D | - Quantizing model.layers.25.mlp.up_proj.weight +24-11-19 19:05:42 | D | - Quantizing model.layers.25.mlp.gate_proj.weight +24-11-19 19:05:43 | D | - Quantizing model.layers.25.mlp.down_proj.weight +24-11-19 19:05:52 | D | - Quantizing layer model.layers.26 +24-11-19 19:05:52 | D | - Calibrating model.layers.26.self_attn.q_proj.weight +24-11-19 19:05:52 | D | + w: sint8 +24-11-19 19:05:52 | D | + x: None +24-11-19 19:05:52 | D | + y: None +24-11-19 19:05:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:05:52 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:05:52 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:05:53 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:05:53 | D | - range ratio = [ 1.0000] +24-11-19 19:05:53 | D | sum error = [ 5.9581] +24-11-19 19:05:53 | D | best error = [ 5.9581] +24-11-19 19:06:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:06:05 | D | sum error = [ 6.1142, 5.8306, 6.0170, 6.1301, 6.1208] +24-11-19 19:06:05 | D | best error = [ 5.9581, 5.8306, 5.8306, 5.8306, 5.8306] +24-11-19 19:06:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:06:05 | D | sum error = [ 6.5392, 6.4858, 7.1927, 7.3887, 7.4526] +24-11-19 19:06:05 | D | best error = [ 5.8306, 5.8306, 5.8306, 5.8306, 5.8306] +24-11-19 19:06:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:06:05 | D | sum error = [ 8.2101, 8.9452, 9.2418, 9.8673, 10.7014] +24-11-19 19:06:05 | D | best error = [ 5.8306, 5.8306, 5.8306, 5.8306, 5.8306] +24-11-19 19:06:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:06:05 | D | sum error = [ 11.5039, 12.2785, 13.5687, 14.7678, 15.9472] +24-11-19 19:06:05 | D | best error = [ 5.8306, 5.8306, 5.8306, 5.8306, 5.8306] +24-11-19 19:06:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:06:05 | D | sum error = [ 17.3912, 18.9464, 20.3008, 22.0145, 23.9467] +24-11-19 19:06:05 | D | best error = [ 5.8306, 5.8306, 5.8306, 5.8306, 5.8306] +24-11-19 19:06:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:06:05 | D | sum error = [ 26.0227, 27.9946, 30.6525, 33.7547, 36.4875] +24-11-19 19:06:05 | D | best error = [ 5.8306, 5.8306, 5.8306, 5.8306, 5.8306] +24-11-19 19:06:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:06:05 | D | sum error = [ 39.7686, 42.8121, 47.3248, 51.0750, 55.4658] +24-11-19 19:06:05 | D | best error = [ 5.8306, 5.8306, 5.8306, 5.8306, 5.8306] +24-11-19 19:06:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:06:05 | D | sum error = [ 60.3345, 66.0830, 71.4853, 77.3820, 84.1911] +24-11-19 19:06:05 | D | best error = [ 5.8306, 5.8306, 5.8306, 5.8306, 5.8306] +24-11-19 19:06:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:06:05 | D | sum error = [ 90.7363, 98.8655, 107.3552, 116.3616, 125.7463] +24-11-19 19:06:05 | D | best error = [ 5.8306, 5.8306, 5.8306, 5.8306, 5.8306] +24-11-19 19:06:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:06:05 | D | sum error = [ 135.9502, 147.1320, 159.2561, 171.9985, 185.3930] +24-11-19 19:06:05 | D | best error = [ 5.8306, 5.8306, 5.8306, 5.8306, 5.8306] +24-11-19 19:06:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:06:05 | D | sum error = [ 199.6749, 215.2385, 230.9522, 248.8068, 267.0979] +24-11-19 19:06:05 | D | best error = [ 5.8306, 5.8306, 5.8306, 5.8306, 5.8306] +24-11-19 19:06:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:06:05 | D | sum error = [ 286.7482, 308.5427, 331.2587, 354.8207, 380.4910] +24-11-19 19:06:05 | D | best error = [ 5.8306, 5.8306, 5.8306, 5.8306, 5.8306] +24-11-19 19:06:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:06:05 | D | sum error = [ 408.1018, 437.7938, 468.1448, 501.0750, 536.5788] +24-11-19 19:06:05 | D | best error = [ 5.8306, 5.8306, 5.8306, 5.8306, 5.8306] +24-11-19 19:06:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:06:05 | D | sum error = [ 573.7357, 613.6159, 655.6364, 700.4496, 746.8833] +24-11-19 19:06:05 | D | best error = [ 5.8306, 5.8306, 5.8306, 5.8306, 5.8306] +24-11-19 19:06:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:06:05 | D | sum error = [ 796.5962, 849.2281, 903.7102, 961.2144, 1020.4810] +24-11-19 19:06:05 | D | best error = [ 5.8306, 5.8306, 5.8306, 5.8306, 5.8306] +24-11-19 19:06:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:06:05 | D | sum error = [ 1081.8978, 1144.8413, 1208.4741, 1272.8975, 1336.4230] +24-11-19 19:06:05 | D | best error = [ 5.8306, 5.8306, 5.8306, 5.8306, 5.8306] +24-11-19 19:06:05 | D | + error = [5.8306] +24-11-19 19:06:05 | D | - Calibrating model.layers.26.self_attn.k_proj.weight +24-11-19 19:06:05 | D | + w: sint8 +24-11-19 19:06:05 | D | + x: None +24-11-19 19:06:05 | D | + y: None +24-11-19 19:06:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:06:05 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:06:05 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:06:05 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:06:05 | D | - range ratio = [ 1.0000] +24-11-19 19:06:05 | D | sum error = [ 5.9518] +24-11-19 19:06:05 | D | best error = [ 5.9518] +24-11-19 19:06:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:06:17 | D | sum error = [ 5.8286, 6.9981, 6.5361, 6.7662, 5.8132] +24-11-19 19:06:17 | D | best error = [ 5.8286, 5.8286, 5.8286, 5.8286, 5.8132] +24-11-19 19:06:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:06:17 | D | sum error = [ 6.4320, 6.3697, 6.9276, 7.1981, 7.2925] +24-11-19 19:06:17 | D | best error = [ 5.8132, 5.8132, 5.8132, 5.8132, 5.8132] +24-11-19 19:06:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:06:17 | D | sum error = [ 8.3221, 9.6568, 11.2893, 10.0602, 10.4842] +24-11-19 19:06:17 | D | best error = [ 5.8132, 5.8132, 5.8132, 5.8132, 5.8132] +24-11-19 19:06:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:06:17 | D | sum error = [ 13.6009, 12.3155, 13.9100, 14.6109, 17.4225] +24-11-19 19:06:17 | D | best error = [ 5.8132, 5.8132, 5.8132, 5.8132, 5.8132] +24-11-19 19:06:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:06:17 | D | sum error = [ 17.6566, 18.6273, 19.8682, 21.4258, 23.3052] +24-11-19 19:06:17 | D | best error = [ 5.8132, 5.8132, 5.8132, 5.8132, 5.8132] +24-11-19 19:06:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:06:17 | D | sum error = [ 25.9756, 26.7419, 29.8970, 32.9105, 35.0677] +24-11-19 19:06:17 | D | best error = [ 5.8132, 5.8132, 5.8132, 5.8132, 5.8132] +24-11-19 19:06:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:06:17 | D | sum error = [ 37.8038, 40.7922, 44.4071, 46.9745, 50.7970] +24-11-19 19:06:17 | D | best error = [ 5.8132, 5.8132, 5.8132, 5.8132, 5.8132] +24-11-19 19:06:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:06:17 | D | sum error = [ 55.6616, 59.2938, 63.8828, 69.8431, 76.0197] +24-11-19 19:06:17 | D | best error = [ 5.8132, 5.8132, 5.8132, 5.8132, 5.8132] +24-11-19 19:06:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:06:17 | D | sum error = [ 81.0869, 85.8359, 95.7997, 102.1452, 111.3459] +24-11-19 19:06:17 | D | best error = [ 5.8132, 5.8132, 5.8132, 5.8132, 5.8132] +24-11-19 19:06:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:06:17 | D | sum error = [ 118.3767, 128.9895, 137.3353, 146.1921, 159.9609] +24-11-19 19:06:17 | D | best error = [ 5.8132, 5.8132, 5.8132, 5.8132, 5.8132] +24-11-19 19:06:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:06:17 | D | sum error = [ 171.2267, 182.6891, 197.5764, 214.5997, 231.0828] +24-11-19 19:06:17 | D | best error = [ 5.8132, 5.8132, 5.8132, 5.8132, 5.8132] +24-11-19 19:06:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:06:17 | D | sum error = [ 247.2159, 267.1435, 286.8063, 304.2143, 326.7198] +24-11-19 19:06:17 | D | best error = [ 5.8132, 5.8132, 5.8132, 5.8132, 5.8132] +24-11-19 19:06:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:06:17 | D | sum error = [ 350.5451, 378.6436, 402.5314, 431.7873, 464.4601] +24-11-19 19:06:17 | D | best error = [ 5.8132, 5.8132, 5.8132, 5.8132, 5.8132] +24-11-19 19:06:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:06:17 | D | sum error = [ 495.9054, 534.6976, 573.1571, 613.6914, 654.6191] +24-11-19 19:06:17 | D | best error = [ 5.8132, 5.8132, 5.8132, 5.8132, 5.8132] +24-11-19 19:06:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:06:17 | D | sum error = [ 699.8509, 747.4781, 806.2783, 855.6899, 919.6429] +24-11-19 19:06:17 | D | best error = [ 5.8132, 5.8132, 5.8132, 5.8132, 5.8132] +24-11-19 19:06:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:06:17 | D | sum error = [ 974.0158, 1036.8469, 1108.1992, 1175.6661, 1245.0786] +24-11-19 19:06:17 | D | best error = [ 5.8132, 5.8132, 5.8132, 5.8132, 5.8132] +24-11-19 19:06:17 | D | + error = [5.8132] +24-11-19 19:06:17 | D | - Calibrating model.layers.26.self_attn.v_proj.weight +24-11-19 19:06:17 | D | + w: sint8 +24-11-19 19:06:17 | D | + x: None +24-11-19 19:06:17 | D | + y: None +24-11-19 19:06:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:06:17 | D | + finished parsing calibration arguments, ram usage: 12.2 +24-11-19 19:06:18 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:06:18 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:06:18 | D | - range ratio = [ 1.0000] +24-11-19 19:06:18 | D | sum error = [ 2.4250] +24-11-19 19:06:18 | D | best error = [ 2.4250] +24-11-19 19:06:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:06:18 | D | sum error = [ 2.4024, 2.3860, 2.3803, 2.4439, 2.4704] +24-11-19 19:06:18 | D | best error = [ 2.1889, 2.1096, 2.0654, 2.0439, 2.0306] +24-11-19 19:06:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:06:18 | D | sum error = [ 2.5184, 2.6041, 2.7201, 2.8820, 3.0012] +24-11-19 19:06:18 | D | best error = [ 2.0218, 2.0193, 2.0178, 2.0170, 2.0170] +24-11-19 19:06:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:06:18 | D | sum error = [ 3.1473, 3.3890, 3.6177, 3.8171, 4.1184] +24-11-19 19:06:18 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 19:06:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:06:18 | D | sum error = [ 4.3623, 4.6830, 5.0142, 5.3881, 5.7596] +24-11-19 19:06:18 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 19:06:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:06:18 | D | sum error = [ 6.1458, 6.6017, 7.0412, 7.5297, 8.0440] +24-11-19 19:06:18 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 19:06:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:06:18 | D | sum error = [ 8.5914, 9.1704, 9.7760, 10.4122, 11.1028] +24-11-19 19:06:18 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 19:06:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:06:18 | D | sum error = [ 11.7860, 12.5277, 13.3887, 14.1812, 15.0888] +24-11-19 19:06:18 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 19:06:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:06:18 | D | sum error = [ 16.0149, 16.9864, 17.9853, 19.0754, 20.1663] +24-11-19 19:06:18 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 19:06:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:06:18 | D | sum error = [ 21.3655, 22.5483, 23.8774, 25.1963, 26.6120] +24-11-19 19:06:18 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 19:06:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:06:18 | D | sum error = [ 28.0867, 29.6175, 31.2253, 32.9025, 34.6401] +24-11-19 19:06:18 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 19:06:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:06:18 | D | sum error = [ 36.4521, 38.3266, 40.2836, 42.3021, 44.4401] +24-11-19 19:06:18 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 19:06:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:06:18 | D | sum error = [ 46.6344, 48.9186, 51.2748, 53.7252, 56.2676] +24-11-19 19:06:18 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 19:06:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:06:18 | D | sum error = [ 58.8855, 61.5867, 64.3786, 67.2619, 70.2334] +24-11-19 19:06:18 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 19:06:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:06:18 | D | sum error = [ 73.3058, 76.4558, 79.7193, 83.0883, 86.5356] +24-11-19 19:06:18 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 19:06:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:06:18 | D | sum error = [ 90.0954, 93.7647, 97.5340, 101.4217, 105.4143] +24-11-19 19:06:18 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 19:06:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:06:18 | D | sum error = [ 109.5296, 113.7377, 118.0578, 122.4699, 126.9948] +24-11-19 19:06:18 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 19:06:18 | D | + error = [2.0170] +24-11-19 19:06:18 | D | - Calibrating model.layers.26.self_attn.o_proj.weight +24-11-19 19:06:18 | D | + w: sint8 +24-11-19 19:06:18 | D | + x: None +24-11-19 19:06:18 | D | + y: None +24-11-19 19:06:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:06:18 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:06:18 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:06:18 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:06:18 | D | - range ratio = [ 1.0000] +24-11-19 19:06:18 | D | sum error = [ 0.5937] +24-11-19 19:06:18 | D | best error = [ 0.5937] +24-11-19 19:06:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:06:19 | D | sum error = [ 0.5904, 0.5886, 0.5891, 0.5922, 0.5979] +24-11-19 19:06:19 | D | best error = [ 0.5494, 0.5295, 0.5178, 0.5101, 0.5048] +24-11-19 19:06:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:06:19 | D | sum error = [ 0.6105, 0.6267, 0.6473, 0.6712, 0.7010] +24-11-19 19:06:19 | D | best error = [ 0.5013, 0.4988, 0.4971, 0.4959, 0.4951] +24-11-19 19:06:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:06:19 | D | sum error = [ 0.7331, 0.7705, 0.8132, 0.8621, 0.9171] +24-11-19 19:06:19 | D | best error = [ 0.4944, 0.4939, 0.4935, 0.4931, 0.4929] +24-11-19 19:06:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:06:19 | D | sum error = [ 0.9737, 1.0381, 1.1044, 1.1802, 1.2563] +24-11-19 19:06:19 | D | best error = [ 0.4927, 0.4927, 0.4926, 0.4926, 0.4925] +24-11-19 19:06:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:06:19 | D | sum error = [ 1.3408, 1.4306, 1.5290, 1.6321, 1.7405] +24-11-19 19:06:19 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 19:06:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:06:19 | D | sum error = [ 1.8540, 1.9762, 2.1063, 2.2426, 2.3891] +24-11-19 19:06:19 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 19:06:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:06:19 | D | sum error = [ 2.5408, 2.7006, 2.8687, 3.0501, 3.2380] +24-11-19 19:06:19 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 19:06:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:06:19 | D | sum error = [ 3.4347, 3.6432, 3.8634, 4.0936, 4.3401] +24-11-19 19:06:19 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 19:06:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:06:19 | D | sum error = [ 4.5971, 4.8666, 5.1487, 5.4442, 5.7567] +24-11-19 19:06:19 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 19:06:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:06:19 | D | sum error = [ 6.0812, 6.4249, 6.7817, 7.1577, 7.5484] +24-11-19 19:06:19 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 19:06:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:06:19 | D | sum error = [ 7.9607, 8.3908, 8.8406, 9.3082, 9.7984] +24-11-19 19:06:19 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 19:06:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:06:19 | D | sum error = [ 10.3113, 10.8493, 11.4089, 11.9932, 12.6043] +24-11-19 19:06:19 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 19:06:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:06:19 | D | sum error = [ 13.2415, 13.9028, 14.5925, 15.3141, 16.0634] +24-11-19 19:06:19 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 19:06:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:06:19 | D | sum error = [ 16.8423, 17.6528, 18.4939, 19.3692, 20.2781] +24-11-19 19:06:19 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 19:06:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:06:19 | D | sum error = [ 21.2210, 22.2008, 23.2157, 24.2682, 25.3556] +24-11-19 19:06:19 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 19:06:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:06:19 | D | sum error = [ 26.4803, 27.6449, 28.8480, 30.0913, 31.3743] +24-11-19 19:06:19 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 19:06:19 | D | + error = [0.4925] +24-11-19 19:06:19 | D | - Calibrating model.layers.26.mlp.up_proj.weight +24-11-19 19:06:19 | D | + w: sint8 +24-11-19 19:06:19 | D | + x: None +24-11-19 19:06:19 | D | + y: None +24-11-19 19:06:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:06:19 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:06:19 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:06:19 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:06:19 | D | - range ratio = [ 1.0000] +24-11-19 19:06:19 | D | sum error = [ 8.5112] +24-11-19 19:06:19 | D | best error = [ 8.5112] +24-11-19 19:06:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:06:20 | D | sum error = [ 8.4647, 8.4663, 8.4778, 8.5785, 8.7326] +24-11-19 19:06:20 | D | best error = [ 7.6647, 7.3566, 7.2007, 7.1142, 7.0649] +24-11-19 19:06:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:06:20 | D | sum error = [ 8.9636, 9.2936, 9.6227, 10.1189, 10.6313] +24-11-19 19:06:20 | D | best error = [ 7.0425, 7.0326, 7.0280, 7.0269, 7.0265] +24-11-19 19:06:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:06:20 | D | sum error = [ 11.2432, 11.9310, 12.7132, 13.5462, 14.4966] +24-11-19 19:06:20 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 19:06:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:06:20 | D | sum error = [ 15.4788, 16.6050, 17.7984, 19.1018, 20.4343] +24-11-19 19:06:20 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 19:06:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:06:20 | D | sum error = [ 21.9096, 23.4329, 25.0485, 26.8098, 28.6371] +24-11-19 19:06:20 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 19:06:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:06:20 | D | sum error = [ 30.5706, 32.6486, 34.8091, 37.0908, 39.5129] +24-11-19 19:06:20 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 19:06:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:06:20 | D | sum error = [ 42.0863, 44.7785, 47.6259, 50.6268, 53.7420] +24-11-19 19:06:20 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 19:06:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:06:20 | D | sum error = [ 57.0057, 60.4642, 64.0969, 67.8836, 71.8587] +24-11-19 19:06:20 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 19:06:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:06:20 | D | sum error = [ 76.0163, 80.3732, 84.9013, 89.6991, 94.6542] +24-11-19 19:06:20 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 19:06:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:06:20 | D | sum error = [ 99.8570, 105.2963, 110.9684, 116.8443, 122.9858] +24-11-19 19:06:20 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 19:06:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:06:20 | D | sum error = [ 129.3506, 136.0088, 142.9072, 150.0789, 157.5422] +24-11-19 19:06:20 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 19:06:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:06:20 | D | sum error = [ 165.2496, 173.2664, 181.5488, 190.1425, 199.0428] +24-11-19 19:06:20 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 19:06:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:06:20 | D | sum error = [ 208.2402, 217.7586, 227.6060, 237.7602, 248.2342] +24-11-19 19:06:20 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 19:06:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:06:20 | D | sum error = [ 259.0579, 270.2145, 281.7095, 293.5600, 305.7407] +24-11-19 19:06:20 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 19:06:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:06:20 | D | sum error = [ 318.2707, 331.2007, 344.4930, 358.1570, 372.2041] +24-11-19 19:06:20 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 19:06:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:06:20 | D | sum error = [ 386.6227, 401.4359, 416.6365, 432.2222, 448.2338] +24-11-19 19:06:20 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 19:06:20 | D | + error = [7.0264] +24-11-19 19:06:20 | D | - Calibrating model.layers.26.mlp.gate_proj.weight +24-11-19 19:06:20 | D | + w: sint8 +24-11-19 19:06:20 | D | + x: None +24-11-19 19:06:20 | D | + y: None +24-11-19 19:06:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:06:20 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:06:20 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:06:20 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:06:20 | D | - range ratio = [ 1.0000] +24-11-19 19:06:20 | D | sum error = [ 11.4903] +24-11-19 19:06:20 | D | best error = [ 11.4903] +24-11-19 19:06:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:06:22 | D | sum error = [ 11.3944, 11.3915, 11.4386, 11.5475, 11.7259] +24-11-19 19:06:22 | D | best error = [ 10.3062, 9.9043, 9.7029, 9.5837, 9.5160] +24-11-19 19:06:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:06:22 | D | sum error = [ 12.0933, 12.5050, 12.9552, 13.5918, 14.3243] +24-11-19 19:06:22 | D | best error = [ 9.4846, 9.4706, 9.4644, 9.4625, 9.4622] +24-11-19 19:06:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:06:22 | D | sum error = [ 15.1528, 16.0659, 17.0951, 18.2938, 19.5194] +24-11-19 19:06:22 | D | best error = [ 9.4619, 9.4619, 9.4619, 9.4619, 9.4619] +24-11-19 19:06:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:06:22 | D | sum error = [ 20.9232, 22.3674, 23.9586, 25.6656, 27.5287] +24-11-19 19:06:22 | D | best error = [ 9.4619, 9.4619, 9.4619, 9.4619, 9.4619] +24-11-19 19:06:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:06:22 | D | sum error = [ 29.4934, 31.5973, 33.8327, 36.1939, 38.7601] +24-11-19 19:06:22 | D | best error = [ 9.4619, 9.4619, 9.4619, 9.4619, 9.4619] +24-11-19 19:06:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:06:22 | D | sum error = [ 41.4288, 44.2756, 47.3073, 50.5189, 53.9301] +24-11-19 19:06:22 | D | best error = [ 9.4619, 9.4619, 9.4619, 9.4619, 9.4619] +24-11-19 19:06:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:06:22 | D | sum error = [ 57.4770, 61.2773, 65.3480, 69.5289, 74.0562] +24-11-19 19:06:22 | D | best error = [ 9.4619, 9.4619, 9.4619, 9.4619, 9.4619] +24-11-19 19:06:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:06:22 | D | sum error = [ 78.7959, 83.8376, 89.1147, 94.7148, 100.5971] +24-11-19 19:06:22 | D | best error = [ 9.4619, 9.4619, 9.4619, 9.4619, 9.4619] +24-11-19 19:06:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:06:22 | D | sum error = [ 106.7995, 113.3104, 120.2057, 127.4746, 135.0935] +24-11-19 19:06:22 | D | best error = [ 9.4619, 9.4619, 9.4619, 9.4619, 9.4619] +24-11-19 19:06:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:06:22 | D | sum error = [ 143.1077, 151.5226, 160.3807, 169.7006, 179.4744] +24-11-19 19:06:22 | D | best error = [ 9.4619, 9.4619, 9.4619, 9.4619, 9.4619] +24-11-19 19:06:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:06:22 | D | sum error = [ 189.7314, 200.5060, 211.8070, 223.6808, 236.0893] +24-11-19 19:06:22 | D | best error = [ 9.4619, 9.4619, 9.4619, 9.4619, 9.4619] +24-11-19 19:06:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:06:22 | D | sum error = [ 249.1418, 262.8260, 277.1263, 292.0474, 307.6338] +24-11-19 19:06:22 | D | best error = [ 9.4619, 9.4619, 9.4619, 9.4619, 9.4619] +24-11-19 19:06:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:06:22 | D | sum error = [ 323.9572, 340.9907, 358.6831, 377.2177, 396.4773] +24-11-19 19:06:22 | D | best error = [ 9.4619, 9.4619, 9.4619, 9.4619, 9.4619] +24-11-19 19:06:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:06:22 | D | sum error = [ 416.5609, 437.4944, 459.2304, 481.8324, 505.3285] +24-11-19 19:06:22 | D | best error = [ 9.4619, 9.4619, 9.4619, 9.4619, 9.4619] +24-11-19 19:06:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:06:22 | D | sum error = [ 529.7022, 554.9067, 581.0741, 608.1510, 636.2204] +24-11-19 19:06:22 | D | best error = [ 9.4619, 9.4619, 9.4619, 9.4619, 9.4619] +24-11-19 19:06:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:06:22 | D | sum error = [ 665.2050, 695.1499, 726.0895, 758.0482, 790.9150] +24-11-19 19:06:22 | D | best error = [ 9.4619, 9.4619, 9.4619, 9.4619, 9.4619] +24-11-19 19:06:22 | D | + error = [9.4619] +24-11-19 19:06:22 | D | - Calibrating model.layers.26.mlp.down_proj.weight +24-11-19 19:06:22 | D | + w: sint8 +24-11-19 19:06:22 | D | + x: None +24-11-19 19:06:22 | D | + y: None +24-11-19 19:06:22 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:06:22 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:06:22 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:06:22 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:06:22 | D | - range ratio = [ 1.0000] +24-11-19 19:06:22 | D | sum error = [ 1.3492] +24-11-19 19:06:22 | D | best error = [ 1.3492] +24-11-19 19:06:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:06:23 | D | sum error = [ 1.3381, 1.3239, 1.3171, 1.3115, 1.3057] +24-11-19 19:06:23 | D | best error = [ 1.2919, 1.2618, 1.2425, 1.2283, 1.2167] +24-11-19 19:06:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:06:23 | D | sum error = [ 1.3047, 1.3120, 1.3168, 1.3303, 1.3474] +24-11-19 19:06:23 | D | best error = [ 1.2072, 1.2004, 1.1949, 1.1909, 1.1880] +24-11-19 19:06:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:06:23 | D | sum error = [ 1.3742, 1.4017, 1.4397, 1.4830, 1.5367] +24-11-19 19:06:23 | D | best error = [ 1.1858, 1.1841, 1.1828, 1.1821, 1.1815] +24-11-19 19:06:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:06:23 | D | sum error = [ 1.5984, 1.6693, 1.7515, 1.8444, 1.9460] +24-11-19 19:06:23 | D | best error = [ 1.1811, 1.1809, 1.1807, 1.1807, 1.1806] +24-11-19 19:06:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:06:23 | D | sum error = [ 2.0596, 2.1840, 2.3227, 2.4739, 2.6371] +24-11-19 19:06:23 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 19:06:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:06:23 | D | sum error = [ 2.8147, 3.0062, 3.2100, 3.4354, 3.6739] +24-11-19 19:06:23 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 19:06:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:06:23 | D | sum error = [ 3.9281, 4.2025, 4.4962, 4.8063, 5.1397] +24-11-19 19:06:23 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 19:06:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:06:23 | D | sum error = [ 5.4947, 5.8730, 6.2715, 6.6942, 7.1464] +24-11-19 19:06:23 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 19:06:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:06:23 | D | sum error = [ 7.6253, 8.1319, 8.6690, 9.2372, 9.8360] +24-11-19 19:06:23 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 19:06:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:06:23 | D | sum error = [ 10.4695, 11.1393, 11.8457, 12.5900, 13.3728] +24-11-19 19:06:23 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 19:06:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:06:23 | D | sum error = [ 14.1979, 15.0671, 15.9827, 16.9435, 17.9530] +24-11-19 19:06:23 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 19:06:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:06:23 | D | sum error = [ 19.0130, 20.1247, 21.2925, 22.5154, 23.7975] +24-11-19 19:06:23 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 19:06:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:06:23 | D | sum error = [ 25.1360, 26.5376, 28.0003, 29.5308, 31.1299] +24-11-19 19:06:23 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 19:06:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:06:23 | D | sum error = [ 32.7946, 34.5319, 36.3420, 38.2275, 40.1894] +24-11-19 19:06:23 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 19:06:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:06:23 | D | sum error = [ 42.2294, 44.3511, 46.5525, 48.8379, 51.2091] +24-11-19 19:06:23 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 19:06:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:06:23 | D | sum error = [ 53.6671, 56.2151, 58.8517, 61.5796, 64.4011] +24-11-19 19:06:23 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 19:06:23 | D | + error = [1.1806] +24-11-19 19:06:23 | D | - Quantizing model.layers.26.self_attn.q_proj.weight +24-11-19 19:06:24 | D | - Quantizing model.layers.26.self_attn.k_proj.weight +24-11-19 19:06:25 | D | - Quantizing model.layers.26.self_attn.v_proj.weight +24-11-19 19:06:26 | D | - Quantizing model.layers.26.self_attn.o_proj.weight +24-11-19 19:06:27 | D | - Quantizing model.layers.26.mlp.up_proj.weight +24-11-19 19:06:28 | D | - Quantizing model.layers.26.mlp.gate_proj.weight +24-11-19 19:06:28 | D | - Quantizing model.layers.26.mlp.down_proj.weight +24-11-19 19:06:38 | D | - Quantizing layer model.layers.27 +24-11-19 19:06:38 | D | - Calibrating model.layers.27.self_attn.q_proj.weight +24-11-19 19:06:38 | D | + w: sint8 +24-11-19 19:06:38 | D | + x: None +24-11-19 19:06:38 | D | + y: None +24-11-19 19:06:38 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:06:38 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:06:38 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:06:39 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:06:39 | D | - range ratio = [ 1.0000] +24-11-19 19:06:39 | D | sum error = [ 7.2905] +24-11-19 19:06:39 | D | best error = [ 7.2905] +24-11-19 19:06:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:06:51 | D | sum error = [ 7.2998, 7.2170, 7.0535, 7.4973, 7.5581] +24-11-19 19:06:51 | D | best error = [ 7.2905, 7.2170, 7.0535, 7.0535, 7.0535] +24-11-19 19:06:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:06:51 | D | sum error = [ 7.8625, 7.7261, 8.3806, 8.6040, 9.1640] +24-11-19 19:06:51 | D | best error = [ 7.0535, 7.0535, 7.0535, 7.0535, 7.0535] +24-11-19 19:06:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:06:51 | D | sum error = [ 9.3896, 10.1915, 11.1074, 11.8085, 12.7288] +24-11-19 19:06:51 | D | best error = [ 7.0535, 7.0535, 7.0535, 7.0535, 7.0535] +24-11-19 19:06:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:06:51 | D | sum error = [ 13.7579, 15.2455, 16.0574, 17.0684, 19.4272] +24-11-19 19:06:51 | D | best error = [ 7.0535, 7.0535, 7.0535, 7.0535, 7.0535] +24-11-19 19:06:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:06:51 | D | sum error = [ 20.9470, 22.3405, 24.3364, 26.5016, 28.7561] +24-11-19 19:06:51 | D | best error = [ 7.0535, 7.0535, 7.0535, 7.0535, 7.0535] +24-11-19 19:06:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:06:51 | D | sum error = [ 30.7648, 33.5921, 36.6908, 39.4578, 42.4377] +24-11-19 19:06:51 | D | best error = [ 7.0535, 7.0535, 7.0535, 7.0535, 7.0535] +24-11-19 19:06:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:06:51 | D | sum error = [ 46.3090, 50.0529, 54.1755, 58.3548, 63.3750] +24-11-19 19:06:51 | D | best error = [ 7.0535, 7.0535, 7.0535, 7.0535, 7.0535] +24-11-19 19:06:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:06:51 | D | sum error = [ 68.6892, 74.3091, 80.4232, 86.7728, 94.0667] +24-11-19 19:06:51 | D | best error = [ 7.0535, 7.0535, 7.0535, 7.0535, 7.0535] +24-11-19 19:06:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:06:51 | D | sum error = [ 101.5855, 110.0611, 119.3813, 129.0943, 139.7559] +24-11-19 19:06:51 | D | best error = [ 7.0535, 7.0535, 7.0535, 7.0535, 7.0535] +24-11-19 19:06:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:06:51 | D | sum error = [ 151.1503, 163.4212, 176.9928, 190.6351, 206.1766] +24-11-19 19:06:51 | D | best error = [ 7.0535, 7.0535, 7.0535, 7.0535, 7.0535] +24-11-19 19:06:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:06:51 | D | sum error = [ 222.7040, 240.2121, 259.4067, 279.8340, 302.1297] +24-11-19 19:06:51 | D | best error = [ 7.0535, 7.0535, 7.0535, 7.0535, 7.0535] +24-11-19 19:06:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:06:51 | D | sum error = [ 326.5178, 352.6534, 381.4143, 412.0376, 445.8517] +24-11-19 19:06:51 | D | best error = [ 7.0535, 7.0535, 7.0535, 7.0535, 7.0535] +24-11-19 19:06:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:06:51 | D | sum error = [ 482.9575, 523.5330, 567.8078, 617.5176, 672.5325] +24-11-19 19:06:51 | D | best error = [ 7.0535, 7.0535, 7.0535, 7.0535, 7.0535] +24-11-19 19:06:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:06:51 | D | sum error = [ 732.6833, 799.8515, 873.8412, 955.3342, 1046.4411] +24-11-19 19:06:51 | D | best error = [ 7.0535, 7.0535, 7.0535, 7.0535, 7.0535] +24-11-19 19:06:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:06:51 | D | sum error = [ 1146.3905, 1258.7190, 1381.0040, 1515.1853, 1657.5800] +24-11-19 19:06:51 | D | best error = [ 7.0535, 7.0535, 7.0535, 7.0535, 7.0535] +24-11-19 19:06:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:06:51 | D | sum error = [ 1810.3062, 1973.0749, 2143.4710, 2316.3285, 2494.0581] +24-11-19 19:06:51 | D | best error = [ 7.0535, 7.0535, 7.0535, 7.0535, 7.0535] +24-11-19 19:06:51 | D | + error = [7.0535] +24-11-19 19:06:51 | D | - Calibrating model.layers.27.self_attn.k_proj.weight +24-11-19 19:06:51 | D | + w: sint8 +24-11-19 19:06:51 | D | + x: None +24-11-19 19:06:51 | D | + y: None +24-11-19 19:06:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:06:51 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:06:51 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:06:51 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:06:52 | D | - range ratio = [ 1.0000] +24-11-19 19:06:52 | D | sum error = [ 7.3379] +24-11-19 19:06:52 | D | best error = [ 7.3379] +24-11-19 19:07:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:07:03 | D | sum error = [ 6.6493, 6.6377, 7.2371, 7.2999, 7.7742] +24-11-19 19:07:03 | D | best error = [ 6.6493, 6.6377, 6.6377, 6.6377, 6.6377] +24-11-19 19:07:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:07:03 | D | sum error = [ 7.0705, 8.2111, 8.2229, 8.5325, 10.9501] +24-11-19 19:07:03 | D | best error = [ 6.6377, 6.6377, 6.6377, 6.6377, 6.6377] +24-11-19 19:07:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:07:03 | D | sum error = [ 9.9818, 9.9851, 11.6922, 10.8746, 14.2804] +24-11-19 19:07:03 | D | best error = [ 6.6377, 6.6377, 6.6377, 6.6377, 6.6377] +24-11-19 19:07:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:07:03 | D | sum error = [ 14.8988, 14.9437, 16.9058, 18.7117, 18.1782] +24-11-19 19:07:03 | D | best error = [ 6.6377, 6.6377, 6.6377, 6.6377, 6.6377] +24-11-19 19:07:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:07:03 | D | sum error = [ 19.6619, 21.2176, 23.7944, 24.6617, 25.5951] +24-11-19 19:07:03 | D | best error = [ 6.6377, 6.6377, 6.6377, 6.6377, 6.6377] +24-11-19 19:07:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:07:03 | D | sum error = [ 27.9357, 30.1256, 32.6344, 36.3293, 38.4604] +24-11-19 19:07:03 | D | best error = [ 6.6377, 6.6377, 6.6377, 6.6377, 6.6377] +24-11-19 19:07:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:07:03 | D | sum error = [ 41.4208, 45.5121, 47.7130, 52.6909, 56.8028] +24-11-19 19:07:03 | D | best error = [ 6.6377, 6.6377, 6.6377, 6.6377, 6.6377] +24-11-19 19:07:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:07:03 | D | sum error = [ 61.5517, 66.1107, 72.6039, 78.1724, 84.0507] +24-11-19 19:07:03 | D | best error = [ 6.6377, 6.6377, 6.6377, 6.6377, 6.6377] +24-11-19 19:07:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:07:03 | D | sum error = [ 91.3991, 99.5306, 107.2962, 115.2232, 125.1135] +24-11-19 19:07:03 | D | best error = [ 6.6377, 6.6377, 6.6377, 6.6377, 6.6377] +24-11-19 19:07:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:07:03 | D | sum error = [ 135.7932, 146.4059, 157.2733, 170.1603, 182.0939] +24-11-19 19:07:03 | D | best error = [ 6.6377, 6.6377, 6.6377, 6.6377, 6.6377] +24-11-19 19:07:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:07:03 | D | sum error = [ 198.0277, 212.1067, 229.1617, 249.7376, 270.4335] +24-11-19 19:07:03 | D | best error = [ 6.6377, 6.6377, 6.6377, 6.6377, 6.6377] +24-11-19 19:07:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:07:03 | D | sum error = [ 292.4064, 319.0527, 349.0593, 376.6005, 411.4345] +24-11-19 19:07:03 | D | best error = [ 6.6377, 6.6377, 6.6377, 6.6377, 6.6377] +24-11-19 19:07:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:07:03 | D | sum error = [ 449.2255, 486.1029, 535.6245, 580.1152, 639.6160] +24-11-19 19:07:03 | D | best error = [ 6.6377, 6.6377, 6.6377, 6.6377, 6.6377] +24-11-19 19:07:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:07:03 | D | sum error = [ 710.3983, 776.3768, 859.7773, 954.4076, 1030.8504] +24-11-19 19:07:03 | D | best error = [ 6.6377, 6.6377, 6.6377, 6.6377, 6.6377] +24-11-19 19:07:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:07:03 | D | sum error = [ 1145.9270, 1270.5062, 1380.1669, 1533.0993, 1701.7977] +24-11-19 19:07:03 | D | best error = [ 6.6377, 6.6377, 6.6377, 6.6377, 6.6377] +24-11-19 19:07:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:07:03 | D | sum error = [ 1844.3092, 2031.4871, 2227.5388, 2369.6979, 2566.3153] +24-11-19 19:07:03 | D | best error = [ 6.6377, 6.6377, 6.6377, 6.6377, 6.6377] +24-11-19 19:07:03 | D | + error = [6.6377] +24-11-19 19:07:04 | D | - Calibrating model.layers.27.self_attn.v_proj.weight +24-11-19 19:07:04 | D | + w: sint8 +24-11-19 19:07:04 | D | + x: None +24-11-19 19:07:04 | D | + y: None +24-11-19 19:07:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:07:04 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:07:04 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:07:04 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:07:04 | D | - range ratio = [ 1.0000] +24-11-19 19:07:04 | D | sum error = [ 2.8438] +24-11-19 19:07:04 | D | best error = [ 2.8438] +24-11-19 19:07:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:07:04 | D | sum error = [ 2.8474, 2.8218, 2.8616, 2.8918, 2.9296] +24-11-19 19:07:04 | D | best error = [ 2.5792, 2.4738, 2.4216, 2.3971, 2.3822] +24-11-19 19:07:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:07:04 | D | sum error = [ 3.0271, 3.1050, 3.2659, 3.4134, 3.5481] +24-11-19 19:07:04 | D | best error = [ 2.3732, 2.3691, 2.3678, 2.3676, 2.3674] +24-11-19 19:07:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:07:04 | D | sum error = [ 3.8004, 4.0425, 4.2360, 4.5293, 4.8174] +24-11-19 19:07:04 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 19:07:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:07:04 | D | sum error = [ 5.2143, 5.5329, 5.9922, 6.3637, 6.8296] +24-11-19 19:07:04 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 19:07:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:07:04 | D | sum error = [ 7.3036, 7.8225, 8.3133, 8.9209, 9.5157] +24-11-19 19:07:04 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 19:07:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:07:04 | D | sum error = [ 10.1718, 10.8625, 11.5934, 12.3100, 13.1390] +24-11-19 19:07:04 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 19:07:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:07:04 | D | sum error = [ 13.9500, 14.8481, 15.7992, 16.7771, 17.7981] +24-11-19 19:07:04 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 19:07:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:07:04 | D | sum error = [ 18.8992, 20.0691, 21.2855, 22.5942, 23.9045] +24-11-19 19:07:04 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 19:07:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:07:04 | D | sum error = [ 25.3144, 26.7916, 28.3035, 29.9328, 31.6333] +24-11-19 19:07:04 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 19:07:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:07:04 | D | sum error = [ 33.4242, 35.2609, 37.2281, 39.2160, 41.3601] +24-11-19 19:07:04 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 19:07:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:07:04 | D | sum error = [ 43.5389, 45.8571, 48.2642, 50.7608, 53.3674] +24-11-19 19:07:04 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 19:07:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:07:04 | D | sum error = [ 56.0704, 58.9033, 61.8109, 64.8759, 68.0412] +24-11-19 19:07:04 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 19:07:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:07:04 | D | sum error = [ 71.3440, 74.7331, 78.2832, 81.9156, 85.7114] +24-11-19 19:07:04 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 19:07:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:07:04 | D | sum error = [ 89.6389, 93.6645, 97.8461, 102.1623, 106.6407] +24-11-19 19:07:04 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 19:07:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:07:04 | D | sum error = [ 111.2458, 116.0275, 120.9540, 126.0167, 131.2298] +24-11-19 19:07:04 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 19:07:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:07:04 | D | sum error = [ 136.6076, 142.1433, 147.8444, 153.6981, 159.7154] +24-11-19 19:07:04 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 19:07:04 | D | + error = [2.3672] +24-11-19 19:07:04 | D | - Calibrating model.layers.27.self_attn.o_proj.weight +24-11-19 19:07:04 | D | + w: sint8 +24-11-19 19:07:04 | D | + x: None +24-11-19 19:07:04 | D | + y: None +24-11-19 19:07:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:07:04 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:07:04 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:07:04 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:07:04 | D | - range ratio = [ 1.0000] +24-11-19 19:07:04 | D | sum error = [ 0.6495] +24-11-19 19:07:04 | D | best error = [ 0.6495] +24-11-19 19:07:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:07:05 | D | sum error = [ 0.6454, 0.6425, 0.6443, 0.6531, 0.6581] +24-11-19 19:07:05 | D | best error = [ 0.5934, 0.5697, 0.5563, 0.5481, 0.5423] +24-11-19 19:07:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:07:05 | D | sum error = [ 0.6742, 0.6977, 0.7196, 0.7477, 0.7833] +24-11-19 19:07:05 | D | best error = [ 0.5385, 0.5363, 0.5347, 0.5337, 0.5331] +24-11-19 19:07:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:07:05 | D | sum error = [ 0.8238, 0.8685, 0.9200, 0.9763, 1.0381] +24-11-19 19:07:05 | D | best error = [ 0.5328, 0.5325, 0.5323, 0.5322, 0.5321] +24-11-19 19:07:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:07:05 | D | sum error = [ 1.1032, 1.1724, 1.2506, 1.3313, 1.4220] +24-11-19 19:07:05 | D | best error = [ 0.5321, 0.5321, 0.5320, 0.5320, 0.5320] +24-11-19 19:07:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:07:05 | D | sum error = [ 1.5126, 1.6132, 1.7204, 1.8339, 1.9559] +24-11-19 19:07:05 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5320] +24-11-19 19:07:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:07:05 | D | sum error = [ 2.0796, 2.2122, 2.3517, 2.5014, 2.6558] +24-11-19 19:07:05 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5320] +24-11-19 19:07:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:07:05 | D | sum error = [ 2.8175, 2.9913, 3.1736, 3.3657, 3.5668] +24-11-19 19:07:05 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5320] +24-11-19 19:07:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:07:05 | D | sum error = [ 3.7762, 3.9981, 4.2295, 4.4716, 4.7269] +24-11-19 19:07:05 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5320] +24-11-19 19:07:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:07:05 | D | sum error = [ 4.9942, 5.2766, 5.5668, 5.8749, 6.1976] +24-11-19 19:07:05 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5320] +24-11-19 19:07:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:07:05 | D | sum error = [ 6.5322, 6.8851, 7.2543, 7.6394, 8.0442] +24-11-19 19:07:05 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5320] +24-11-19 19:07:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:07:05 | D | sum error = [ 8.4675, 8.9080, 9.3674, 9.8480, 10.3487] +24-11-19 19:07:05 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5320] +24-11-19 19:07:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:07:05 | D | sum error = [ 10.8715, 11.4171, 11.9859, 12.5825, 13.2012] +24-11-19 19:07:05 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5320] +24-11-19 19:07:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:07:05 | D | sum error = [ 13.8511, 14.5263, 15.2265, 15.9549, 16.7148] +24-11-19 19:07:05 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5320] +24-11-19 19:07:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:07:05 | D | sum error = [ 17.5037, 18.3239, 19.1761, 20.0623, 20.9798] +24-11-19 19:07:05 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5320] +24-11-19 19:07:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:07:05 | D | sum error = [ 21.9352, 22.9242, 23.9508, 25.0176, 26.1198] +24-11-19 19:07:05 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5320] +24-11-19 19:07:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:07:05 | D | sum error = [ 27.2636, 28.4461, 29.6706, 30.9356, 32.2420] +24-11-19 19:07:05 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5320] +24-11-19 19:07:05 | D | + error = [0.5320] +24-11-19 19:07:05 | D | - Calibrating model.layers.27.mlp.up_proj.weight +24-11-19 19:07:05 | D | + w: sint8 +24-11-19 19:07:05 | D | + x: None +24-11-19 19:07:05 | D | + y: None +24-11-19 19:07:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:07:05 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:07:05 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:07:05 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:07:05 | D | - range ratio = [ 1.0000] +24-11-19 19:07:05 | D | sum error = [ 9.0153] +24-11-19 19:07:05 | D | best error = [ 9.0153] +24-11-19 19:07:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:07:06 | D | sum error = [ 8.9423, 8.9585, 8.9570, 9.0526, 9.2331] +24-11-19 19:07:06 | D | best error = [ 8.0264, 7.6847, 7.5094, 7.4144, 7.3622] +24-11-19 19:07:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:07:06 | D | sum error = [ 9.4771, 9.7982, 10.1742, 10.6344, 11.2298] +24-11-19 19:07:06 | D | best error = [ 7.3343, 7.3208, 7.3155, 7.3138, 7.3134] +24-11-19 19:07:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:07:06 | D | sum error = [ 11.8621, 12.6054, 13.4194, 14.2944, 15.2923] +24-11-19 19:07:06 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 19:07:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:07:06 | D | sum error = [ 16.3529, 17.5200, 18.7940, 20.1134, 21.5416] +24-11-19 19:07:06 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 19:07:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:07:06 | D | sum error = [ 23.0961, 24.7721, 26.4879, 28.3159, 30.2940] +24-11-19 19:07:06 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 19:07:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:07:06 | D | sum error = [ 32.3499, 34.5587, 36.8699, 39.3219, 41.9035] +24-11-19 19:07:06 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 19:07:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:07:06 | D | sum error = [ 44.6520, 47.4534, 50.5113, 53.6617, 57.0259] +24-11-19 19:07:06 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 19:07:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:07:06 | D | sum error = [ 60.5047, 64.1934, 68.0078, 72.0594, 76.2573] +24-11-19 19:07:06 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 19:07:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:07:06 | D | sum error = [ 80.6633, 85.3324, 90.1494, 95.2267, 100.5099] +24-11-19 19:07:06 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 19:07:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:07:06 | D | sum error = [ 106.0333, 111.7530, 117.7762, 124.0353, 130.5677] +24-11-19 19:07:06 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 19:07:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:07:06 | D | sum error = [ 137.3556, 144.4344, 151.7836, 159.4335, 167.3741] +24-11-19 19:07:06 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 19:07:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:07:06 | D | sum error = [ 175.6500, 184.1922, 193.0896, 202.3331, 211.8624] +24-11-19 19:07:06 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 19:07:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:07:06 | D | sum error = [ 221.7447, 231.9844, 242.5578, 253.4846, 264.8009] +24-11-19 19:07:06 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 19:07:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:07:06 | D | sum error = [ 276.5036, 288.5571, 301.0129, 313.8967, 327.1289] +24-11-19 19:07:06 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 19:07:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:07:06 | D | sum error = [ 340.7691, 354.8232, 369.2841, 384.1460, 399.4373] +24-11-19 19:07:06 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 19:07:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:07:06 | D | sum error = [ 415.1418, 431.2746, 447.8762, 464.9050, 482.3967] +24-11-19 19:07:06 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 19:07:06 | D | + error = [7.3133] +24-11-19 19:07:06 | D | - Calibrating model.layers.27.mlp.gate_proj.weight +24-11-19 19:07:06 | D | + w: sint8 +24-11-19 19:07:06 | D | + x: None +24-11-19 19:07:06 | D | + y: None +24-11-19 19:07:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:07:06 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:07:06 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:07:07 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:07:07 | D | - range ratio = [ 1.0000] +24-11-19 19:07:07 | D | sum error = [ 12.0516] +24-11-19 19:07:07 | D | best error = [ 12.0516] +24-11-19 19:07:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:07:08 | D | sum error = [ 11.9797, 12.0101, 11.9302, 12.1166, 12.3575] +24-11-19 19:07:08 | D | best error = [ 10.7410, 10.2841, 10.0484, 9.9218, 9.8509] +24-11-19 19:07:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:07:08 | D | sum error = [ 12.6953, 13.1128, 13.6408, 14.2715, 15.0514] +24-11-19 19:07:08 | D | best error = [ 9.8170, 9.8011, 9.7940, 9.7912, 9.7906] +24-11-19 19:07:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:07:08 | D | sum error = [ 15.8992, 16.9128, 18.0257, 19.2339, 20.6000] +24-11-19 19:07:08 | D | best error = [ 9.7905, 9.7905, 9.7905, 9.7905, 9.7905] +24-11-19 19:07:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:07:08 | D | sum error = [ 22.0493, 23.6119, 25.3702, 27.1575, 29.1515] +24-11-19 19:07:08 | D | best error = [ 9.7905, 9.7905, 9.7905, 9.7905, 9.7905] +24-11-19 19:07:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:07:08 | D | sum error = [ 31.2064, 33.5223, 35.8760, 38.4276, 41.2092] +24-11-19 19:07:08 | D | best error = [ 9.7905, 9.7905, 9.7905, 9.7905, 9.7905] +24-11-19 19:07:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:07:08 | D | sum error = [ 44.1089, 47.1371, 50.3583, 53.8308, 57.4963] +24-11-19 19:07:08 | D | best error = [ 9.7905, 9.7905, 9.7905, 9.7905, 9.7905] +24-11-19 19:07:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:07:08 | D | sum error = [ 61.3056, 65.3987, 69.7225, 74.2668, 79.1332] +24-11-19 19:07:08 | D | best error = [ 9.7905, 9.7905, 9.7905, 9.7905, 9.7905] +24-11-19 19:07:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:07:08 | D | sum error = [ 84.1903, 89.5535, 95.2787, 101.2682, 107.6293] +24-11-19 19:07:08 | D | best error = [ 9.7905, 9.7905, 9.7905, 9.7905, 9.7905] +24-11-19 19:07:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:07:08 | D | sum error = [ 114.2844, 121.3570, 128.7444, 136.6246, 144.8724] +24-11-19 19:07:08 | D | best error = [ 9.7905, 9.7905, 9.7905, 9.7905, 9.7905] +24-11-19 19:07:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:07:08 | D | sum error = [ 153.5883, 162.7511, 172.3899, 182.5428, 193.2320] +24-11-19 19:07:08 | D | best error = [ 9.7905, 9.7905, 9.7905, 9.7905, 9.7905] +24-11-19 19:07:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:07:08 | D | sum error = [ 204.4180, 216.1470, 228.4817, 241.4316, 254.9936] +24-11-19 19:07:08 | D | best error = [ 9.7905, 9.7905, 9.7905, 9.7905, 9.7905] +24-11-19 19:07:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:07:08 | D | sum error = [ 269.2173, 284.1776, 299.7164, 316.0653, 333.2209] +24-11-19 19:07:08 | D | best error = [ 9.7905, 9.7905, 9.7905, 9.7905, 9.7905] +24-11-19 19:07:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:07:08 | D | sum error = [ 351.1185, 369.8706, 389.4207, 409.9446, 431.3037] +24-11-19 19:07:08 | D | best error = [ 9.7905, 9.7905, 9.7905, 9.7905, 9.7905] +24-11-19 19:07:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:07:08 | D | sum error = [ 453.6232, 476.8070, 500.9012, 525.9647, 551.9873] +24-11-19 19:07:08 | D | best error = [ 9.7905, 9.7905, 9.7905, 9.7905, 9.7905] +24-11-19 19:07:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:07:08 | D | sum error = [ 579.0249, 607.0411, 636.1535, 666.2377, 697.3332] +24-11-19 19:07:08 | D | best error = [ 9.7905, 9.7905, 9.7905, 9.7905, 9.7905] +24-11-19 19:07:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:07:08 | D | sum error = [ 729.4846, 762.7037, 796.9472, 832.2606, 868.6140] +24-11-19 19:07:08 | D | best error = [ 9.7905, 9.7905, 9.7905, 9.7905, 9.7905] +24-11-19 19:07:08 | D | + error = [9.7905] +24-11-19 19:07:08 | D | - Calibrating model.layers.27.mlp.down_proj.weight +24-11-19 19:07:08 | D | + w: sint8 +24-11-19 19:07:08 | D | + x: None +24-11-19 19:07:08 | D | + y: None +24-11-19 19:07:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:07:08 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:07:08 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:07:08 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:07:08 | D | - range ratio = [ 1.0000] +24-11-19 19:07:08 | D | sum error = [ 1.6193] +24-11-19 19:07:08 | D | best error = [ 1.6193] +24-11-19 19:07:09 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:07:09 | D | sum error = [ 1.6074, 1.6013, 1.5859, 1.5800, 1.5645] +24-11-19 19:07:09 | D | best error = [ 1.5002, 1.4519, 1.4202, 1.3996, 1.3835] +24-11-19 19:07:09 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:07:09 | D | sum error = [ 1.5620, 1.5605, 1.5611, 1.5727, 1.5866] +24-11-19 19:07:09 | D | best error = [ 1.3703, 1.3599, 1.3519, 1.3456, 1.3408] +24-11-19 19:07:09 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:07:09 | D | sum error = [ 1.6024, 1.6352, 1.6653, 1.7091, 1.7572] +24-11-19 19:07:09 | D | best error = [ 1.3373, 1.3353, 1.3335, 1.3323, 1.3315] +24-11-19 19:07:09 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:07:09 | D | sum error = [ 1.8195, 1.8906, 1.9708, 2.0639, 2.1682] +24-11-19 19:07:09 | D | best error = [ 1.3310, 1.3305, 1.3303, 1.3302, 1.3301] +24-11-19 19:07:09 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:07:09 | D | sum error = [ 2.2859, 2.4211, 2.5651, 2.7235, 2.8929] +24-11-19 19:07:09 | D | best error = [ 1.3300, 1.3300, 1.3300, 1.3300, 1.3300] +24-11-19 19:07:09 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:07:09 | D | sum error = [ 3.0861, 3.2926, 3.5134, 3.7581, 4.0153] +24-11-19 19:07:09 | D | best error = [ 1.3299, 1.3299, 1.3299, 1.3299, 1.3299] +24-11-19 19:07:09 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:07:09 | D | sum error = [ 4.2886, 4.5849, 4.9030, 5.2391, 5.6043] +24-11-19 19:07:09 | D | best error = [ 1.3299, 1.3299, 1.3299, 1.3299, 1.3299] +24-11-19 19:07:09 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:07:09 | D | sum error = [ 5.9918, 6.4016, 6.8361, 7.2979, 7.7898] +24-11-19 19:07:09 | D | best error = [ 1.3299, 1.3299, 1.3299, 1.3299, 1.3299] +24-11-19 19:07:09 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:07:09 | D | sum error = [ 8.3101, 8.8627, 9.4473, 10.0697, 10.7239] +24-11-19 19:07:09 | D | best error = [ 1.3299, 1.3299, 1.3299, 1.3299, 1.3299] +24-11-19 19:07:09 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:07:09 | D | sum error = [ 11.4246, 12.1562, 12.9289, 13.7463, 14.6118] +24-11-19 19:07:09 | D | best error = [ 1.3299, 1.3299, 1.3299, 1.3299, 1.3299] +24-11-19 19:07:09 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:07:09 | D | sum error = [ 15.5238, 16.4818, 17.4910, 18.5501, 19.6648] +24-11-19 19:07:09 | D | best error = [ 1.3299, 1.3299, 1.3299, 1.3299, 1.3299] +24-11-19 19:07:09 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:07:09 | D | sum error = [ 20.8367, 22.0652, 23.3532, 24.7051, 26.1244] +24-11-19 19:07:09 | D | best error = [ 1.3299, 1.3299, 1.3299, 1.3299, 1.3299] +24-11-19 19:07:09 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:07:09 | D | sum error = [ 27.6092, 29.1682, 30.7964, 32.5026, 34.2850] +24-11-19 19:07:09 | D | best error = [ 1.3299, 1.3299, 1.3299, 1.3299, 1.3299] +24-11-19 19:07:09 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:07:09 | D | sum error = [ 36.1516, 38.1017, 40.1352, 42.2629, 44.4815] +24-11-19 19:07:09 | D | best error = [ 1.3299, 1.3299, 1.3299, 1.3299, 1.3299] +24-11-19 19:07:09 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:07:09 | D | sum error = [ 46.7950, 49.2114, 51.7329, 54.3561, 57.0881] +24-11-19 19:07:09 | D | best error = [ 1.3299, 1.3299, 1.3299, 1.3299, 1.3299] +24-11-19 19:07:09 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:07:09 | D | sum error = [ 59.9307, 62.8876, 65.9586, 69.1471, 72.4550] +24-11-19 19:07:09 | D | best error = [ 1.3299, 1.3299, 1.3299, 1.3299, 1.3299] +24-11-19 19:07:09 | D | + error = [1.3299] +24-11-19 19:07:09 | D | - Quantizing model.layers.27.self_attn.q_proj.weight +24-11-19 19:07:10 | D | - Quantizing model.layers.27.self_attn.k_proj.weight +24-11-19 19:07:11 | D | - Quantizing model.layers.27.self_attn.v_proj.weight +24-11-19 19:07:12 | D | - Quantizing model.layers.27.self_attn.o_proj.weight +24-11-19 19:07:13 | D | - Quantizing model.layers.27.mlp.up_proj.weight +24-11-19 19:07:14 | D | - Quantizing model.layers.27.mlp.gate_proj.weight +24-11-19 19:07:15 | D | - Quantizing model.layers.27.mlp.down_proj.weight +24-11-19 19:07:24 | D | - Quantizing layer model.layers.28 +24-11-19 19:07:24 | D | - Calibrating model.layers.28.self_attn.q_proj.weight +24-11-19 19:07:24 | D | + w: sint8 +24-11-19 19:07:24 | D | + x: None +24-11-19 19:07:24 | D | + y: None +24-11-19 19:07:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:07:24 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:07:24 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:07:25 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:07:25 | D | - range ratio = [ 1.0000] +24-11-19 19:07:25 | D | sum error = [ 7.4856] +24-11-19 19:07:25 | D | best error = [ 7.4856] +24-11-19 19:07:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:07:37 | D | sum error = [ 7.3115, 7.4027, 7.3370, 7.2925, 7.6971] +24-11-19 19:07:37 | D | best error = [ 7.3115, 7.3115, 7.3115, 7.2925, 7.2925] +24-11-19 19:07:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:07:37 | D | sum error = [ 7.8042, 7.9255, 8.2672, 8.6128, 8.8696] +24-11-19 19:07:37 | D | best error = [ 7.2925, 7.2925, 7.2925, 7.2925, 7.2925] +24-11-19 19:07:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:07:37 | D | sum error = [ 9.6912, 10.3365, 10.9210, 11.8602, 12.5639] +24-11-19 19:07:37 | D | best error = [ 7.2925, 7.2925, 7.2925, 7.2925, 7.2925] +24-11-19 19:07:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:07:37 | D | sum error = [ 13.9862, 14.6746, 15.5888, 17.5287, 18.8313] +24-11-19 19:07:37 | D | best error = [ 7.2925, 7.2925, 7.2925, 7.2925, 7.2925] +24-11-19 19:07:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:07:37 | D | sum error = [ 20.3148, 22.0154, 23.9055, 25.6287, 28.3563] +24-11-19 19:07:37 | D | best error = [ 7.2925, 7.2925, 7.2925, 7.2925, 7.2925] +24-11-19 19:07:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:07:37 | D | sum error = [ 30.5323, 33.9213, 36.2023, 38.9388, 42.5733] +24-11-19 19:07:37 | D | best error = [ 7.2925, 7.2925, 7.2925, 7.2925, 7.2925] +24-11-19 19:07:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:07:37 | D | sum error = [ 46.8443, 50.6597, 54.4876, 58.9310, 63.6437] +24-11-19 19:07:37 | D | best error = [ 7.2925, 7.2925, 7.2925, 7.2925, 7.2925] +24-11-19 19:07:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:07:37 | D | sum error = [ 68.7526, 75.0922, 80.9872, 86.8745, 94.0224] +24-11-19 19:07:37 | D | best error = [ 7.2925, 7.2925, 7.2925, 7.2925, 7.2925] +24-11-19 19:07:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:07:37 | D | sum error = [ 101.2528, 109.1355, 117.3963, 126.3281, 135.5974] +24-11-19 19:07:37 | D | best error = [ 7.2925, 7.2925, 7.2925, 7.2925, 7.2925] +24-11-19 19:07:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:07:37 | D | sum error = [ 145.6922, 155.9279, 167.7217, 180.0407, 193.2182] +24-11-19 19:07:37 | D | best error = [ 7.2925, 7.2925, 7.2925, 7.2925, 7.2925] +24-11-19 19:07:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:07:37 | D | sum error = [ 206.3914, 221.7425, 237.9021, 255.0081, 273.9483] +24-11-19 19:07:37 | D | best error = [ 7.2925, 7.2925, 7.2925, 7.2925, 7.2925] +24-11-19 19:07:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:07:37 | D | sum error = [ 293.4836, 314.8512, 337.3729, 362.3193, 387.9226] +24-11-19 19:07:37 | D | best error = [ 7.2925, 7.2925, 7.2925, 7.2925, 7.2925] +24-11-19 19:07:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:07:37 | D | sum error = [ 415.5807, 445.9329, 478.6181, 513.9962, 551.7774] +24-11-19 19:07:37 | D | best error = [ 7.2925, 7.2925, 7.2925, 7.2925, 7.2925] +24-11-19 19:07:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:07:37 | D | sum error = [ 593.2896, 637.6846, 686.3003, 738.5671, 793.9055] +24-11-19 19:07:37 | D | best error = [ 7.2925, 7.2925, 7.2925, 7.2925, 7.2925] +24-11-19 19:07:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:07:37 | D | sum error = [ 853.5907, 916.6746, 984.5421, 1056.7438, 1132.6465] +24-11-19 19:07:37 | D | best error = [ 7.2925, 7.2925, 7.2925, 7.2925, 7.2925] +24-11-19 19:07:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:07:37 | D | sum error = [ 1212.6309, 1296.8346, 1384.3033, 1474.4676, 1566.3710] +24-11-19 19:07:37 | D | best error = [ 7.2925, 7.2925, 7.2925, 7.2925, 7.2925] +24-11-19 19:07:37 | D | + error = [7.2925] +24-11-19 19:07:37 | D | - Calibrating model.layers.28.self_attn.k_proj.weight +24-11-19 19:07:37 | D | + w: sint8 +24-11-19 19:07:37 | D | + x: None +24-11-19 19:07:37 | D | + y: None +24-11-19 19:07:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:07:37 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:07:37 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:07:38 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:07:38 | D | - range ratio = [ 1.0000] +24-11-19 19:07:38 | D | sum error = [ 8.1714] +24-11-19 19:07:38 | D | best error = [ 8.1714] +24-11-19 19:07:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:07:50 | D | sum error = [ 7.3550, 7.8809, 7.6259, 7.8125, 8.0911] +24-11-19 19:07:50 | D | best error = [ 7.3550, 7.3550, 7.3550, 7.3550, 7.3550] +24-11-19 19:07:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:07:50 | D | sum error = [ 7.5799, 8.3003, 7.8612, 8.6490, 8.9483] +24-11-19 19:07:50 | D | best error = [ 7.3550, 7.3550, 7.3550, 7.3550, 7.3550] +24-11-19 19:07:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:07:50 | D | sum error = [ 9.3516, 10.1144, 10.8811, 11.3596, 12.6847] +24-11-19 19:07:50 | D | best error = [ 7.3550, 7.3550, 7.3550, 7.3550, 7.3550] +24-11-19 19:07:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:07:50 | D | sum error = [ 12.8488, 14.1079, 15.0202, 16.0075, 16.7658] +24-11-19 19:07:50 | D | best error = [ 7.3550, 7.3550, 7.3550, 7.3550, 7.3550] +24-11-19 19:07:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:07:50 | D | sum error = [ 17.7457, 20.4955, 22.3027, 22.7404, 25.2970] +24-11-19 19:07:50 | D | best error = [ 7.3550, 7.3550, 7.3550, 7.3550, 7.3550] +24-11-19 19:07:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:07:50 | D | sum error = [ 27.3041, 29.2189, 31.5856, 33.0715, 36.3899] +24-11-19 19:07:50 | D | best error = [ 7.3550, 7.3550, 7.3550, 7.3550, 7.3550] +24-11-19 19:07:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:07:50 | D | sum error = [ 38.5146, 41.7224, 44.8535, 48.5049, 52.4479] +24-11-19 19:07:50 | D | best error = [ 7.3550, 7.3550, 7.3550, 7.3550, 7.3550] +24-11-19 19:07:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:07:50 | D | sum error = [ 56.5522, 60.0698, 65.0388, 69.9577, 76.1903] +24-11-19 19:07:50 | D | best error = [ 7.3550, 7.3550, 7.3550, 7.3550, 7.3550] +24-11-19 19:07:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:07:50 | D | sum error = [ 81.5257, 87.3212, 93.8573, 99.9932, 108.3755] +24-11-19 19:07:50 | D | best error = [ 7.3550, 7.3550, 7.3550, 7.3550, 7.3550] +24-11-19 19:07:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:07:50 | D | sum error = [ 116.6520, 125.0037, 134.8063, 142.9751, 153.8333] +24-11-19 19:07:50 | D | best error = [ 7.3550, 7.3550, 7.3550, 7.3550, 7.3550] +24-11-19 19:07:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:07:50 | D | sum error = [ 166.6176, 179.2191, 193.0822, 207.2201, 223.1702] +24-11-19 19:07:50 | D | best error = [ 7.3550, 7.3550, 7.3550, 7.3550, 7.3550] +24-11-19 19:07:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:07:50 | D | sum error = [ 239.6263, 258.3249, 279.4257, 301.8414, 322.9023] +24-11-19 19:07:50 | D | best error = [ 7.3550, 7.3550, 7.3550, 7.3550, 7.3550] +24-11-19 19:07:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:07:50 | D | sum error = [ 347.9830, 376.0651, 406.5898, 440.7157, 478.5885] +24-11-19 19:07:50 | D | best error = [ 7.3550, 7.3550, 7.3550, 7.3550, 7.3550] +24-11-19 19:07:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:07:50 | D | sum error = [ 516.9837, 558.0171, 604.5847, 656.3757, 708.9797] +24-11-19 19:07:50 | D | best error = [ 7.3550, 7.3550, 7.3550, 7.3550, 7.3550] +24-11-19 19:07:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:07:50 | D | sum error = [ 771.6946, 831.6872, 901.7701, 973.7197, 1052.4494] +24-11-19 19:07:50 | D | best error = [ 7.3550, 7.3550, 7.3550, 7.3550, 7.3550] +24-11-19 19:07:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:07:50 | D | sum error = [ 1139.5664, 1228.5586, 1329.6123, 1419.8507, 1520.1916] +24-11-19 19:07:50 | D | best error = [ 7.3550, 7.3550, 7.3550, 7.3550, 7.3550] +24-11-19 19:07:50 | D | + error = [7.3550] +24-11-19 19:07:50 | D | - Calibrating model.layers.28.self_attn.v_proj.weight +24-11-19 19:07:50 | D | + w: sint8 +24-11-19 19:07:50 | D | + x: None +24-11-19 19:07:50 | D | + y: None +24-11-19 19:07:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:07:50 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:07:50 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:07:50 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:07:50 | D | - range ratio = [ 1.0000] +24-11-19 19:07:50 | D | sum error = [ 2.8252] +24-11-19 19:07:50 | D | best error = [ 2.8252] +24-11-19 19:07:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:07:50 | D | sum error = [ 2.8422, 2.8017, 2.8359, 2.8515, 2.9119] +24-11-19 19:07:50 | D | best error = [ 2.5299, 2.4135, 2.3663, 2.3405, 2.3252] +24-11-19 19:07:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:07:50 | D | sum error = [ 3.0069, 3.0513, 3.2090, 3.3516, 3.5651] +24-11-19 19:07:50 | D | best error = [ 2.3178, 2.3134, 2.3124, 2.3118, 2.3118] +24-11-19 19:07:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:07:50 | D | sum error = [ 3.7432, 3.9895, 4.2432, 4.5460, 4.8121] +24-11-19 19:07:50 | D | best error = [ 2.3118, 2.3118, 2.3118, 2.3118, 2.3118] +24-11-19 19:07:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:07:50 | D | sum error = [ 5.1428, 5.5564, 5.9171, 6.3232, 6.7957] +24-11-19 19:07:50 | D | best error = [ 2.3118, 2.3118, 2.3118, 2.3118, 2.3118] +24-11-19 19:07:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:07:50 | D | sum error = [ 7.2330, 7.7773, 8.2774, 8.8718, 9.4661] +24-11-19 19:07:50 | D | best error = [ 2.3118, 2.3118, 2.3118, 2.3118, 2.3118] +24-11-19 19:07:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:07:50 | D | sum error = [ 10.1428, 10.8065, 11.4883, 12.2827, 13.0563] +24-11-19 19:07:50 | D | best error = [ 2.3118, 2.3118, 2.3118, 2.3118, 2.3118] +24-11-19 19:07:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:07:50 | D | sum error = [ 13.8714, 14.7357, 15.6562, 16.6173, 17.6498] +24-11-19 19:07:50 | D | best error = [ 2.3118, 2.3118, 2.3118, 2.3118, 2.3118] +24-11-19 19:07:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:07:50 | D | sum error = [ 18.7078, 19.8500, 21.0345, 22.3095, 23.6324] +24-11-19 19:07:50 | D | best error = [ 2.3118, 2.3118, 2.3118, 2.3118, 2.3118] +24-11-19 19:07:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:07:50 | D | sum error = [ 25.0505, 26.4794, 27.9936, 29.5763, 31.2157] +24-11-19 19:07:50 | D | best error = [ 2.3118, 2.3118, 2.3118, 2.3118, 2.3118] +24-11-19 19:07:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:07:50 | D | sum error = [ 32.9285, 34.7220, 36.5608, 38.5011, 40.5076] +24-11-19 19:07:50 | D | best error = [ 2.3118, 2.3118, 2.3118, 2.3118, 2.3118] +24-11-19 19:07:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:07:50 | D | sum error = [ 42.6294, 44.8215, 47.0909, 49.4650, 51.8946] +24-11-19 19:07:50 | D | best error = [ 2.3118, 2.3118, 2.3118, 2.3118, 2.3118] +24-11-19 19:07:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:07:50 | D | sum error = [ 54.4455, 57.0748, 59.8265, 62.6306, 65.5648] +24-11-19 19:07:50 | D | best error = [ 2.3118, 2.3118, 2.3118, 2.3118, 2.3118] +24-11-19 19:07:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:07:50 | D | sum error = [ 68.6000, 71.7359, 74.9623, 78.3047, 81.7256] +24-11-19 19:07:50 | D | best error = [ 2.3118, 2.3118, 2.3118, 2.3118, 2.3118] +24-11-19 19:07:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:07:50 | D | sum error = [ 85.2907, 88.9698, 92.7687, 96.6828, 100.7124] +24-11-19 19:07:50 | D | best error = [ 2.3118, 2.3118, 2.3118, 2.3118, 2.3118] +24-11-19 19:07:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:07:50 | D | sum error = [ 104.8618, 109.1258, 113.5323, 118.0523, 122.6969] +24-11-19 19:07:50 | D | best error = [ 2.3118, 2.3118, 2.3118, 2.3118, 2.3118] +24-11-19 19:07:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:07:50 | D | sum error = [ 127.4744, 132.3645, 137.3742, 142.5502, 147.8547] +24-11-19 19:07:50 | D | best error = [ 2.3118, 2.3118, 2.3118, 2.3118, 2.3118] +24-11-19 19:07:50 | D | + error = [2.3118] +24-11-19 19:07:50 | D | - Calibrating model.layers.28.self_attn.o_proj.weight +24-11-19 19:07:50 | D | + w: sint8 +24-11-19 19:07:50 | D | + x: None +24-11-19 19:07:50 | D | + y: None +24-11-19 19:07:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:07:50 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:07:50 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:07:50 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:07:50 | D | - range ratio = [ 1.0000] +24-11-19 19:07:50 | D | sum error = [ 0.8159] +24-11-19 19:07:50 | D | best error = [ 0.8159] +24-11-19 19:07:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:07:51 | D | sum error = [ 0.8089, 0.8123, 0.8154, 0.8261, 0.8438] +24-11-19 19:07:51 | D | best error = [ 0.7612, 0.7390, 0.7259, 0.7175, 0.7124] +24-11-19 19:07:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:07:51 | D | sum error = [ 0.8654, 0.8961, 0.9335, 0.9789, 1.0323] +24-11-19 19:07:51 | D | best error = [ 0.7089, 0.7068, 0.7054, 0.7045, 0.7039] +24-11-19 19:07:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:07:51 | D | sum error = [ 1.0875, 1.1549, 1.2246, 1.3035, 1.3894] +24-11-19 19:07:51 | D | best error = [ 0.7035, 0.7032, 0.7031, 0.7030, 0.7029] +24-11-19 19:07:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:07:51 | D | sum error = [ 1.4768, 1.5746, 1.6797, 1.7894, 1.9075] +24-11-19 19:07:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 19:07:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:07:51 | D | sum error = [ 2.0334, 2.1665, 2.3052, 2.4475, 2.6028] +24-11-19 19:07:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 19:07:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:07:51 | D | sum error = [ 2.7653, 2.9340, 3.1140, 3.3019, 3.5012] +24-11-19 19:07:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 19:07:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:07:51 | D | sum error = [ 3.7095, 3.9271, 4.1550, 4.3955, 4.6455] +24-11-19 19:07:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 19:07:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:07:51 | D | sum error = [ 4.9064, 5.1825, 5.4729, 5.7736, 6.0867] +24-11-19 19:07:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 19:07:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:07:51 | D | sum error = [ 6.4186, 6.7621, 7.1269, 7.5013, 7.8987] +24-11-19 19:07:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 19:07:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:07:51 | D | sum error = [ 8.3132, 8.7456, 9.1954, 9.6648, 10.1514] +24-11-19 19:07:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 19:07:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:07:51 | D | sum error = [ 10.6639, 11.1953, 11.7510, 12.3302, 12.9350] +24-11-19 19:07:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 19:07:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:07:51 | D | sum error = [ 13.5617, 14.2203, 14.9024, 15.6152, 16.3569] +24-11-19 19:07:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 19:07:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:07:51 | D | sum error = [ 17.1280, 17.9313, 18.7664, 19.6322, 20.5357] +24-11-19 19:07:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 19:07:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:07:51 | D | sum error = [ 21.4728, 22.4459, 23.4559, 24.5049, 25.5921] +24-11-19 19:07:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 19:07:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:07:51 | D | sum error = [ 26.7203, 27.8916, 29.1028, 30.3586, 31.6600] +24-11-19 19:07:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 19:07:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:07:51 | D | sum error = [ 33.0049, 34.3965, 35.8341, 37.3195, 38.8569] +24-11-19 19:07:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 19:07:51 | D | + error = [0.7029] +24-11-19 19:07:51 | D | - Calibrating model.layers.28.mlp.up_proj.weight +24-11-19 19:07:51 | D | + w: sint8 +24-11-19 19:07:51 | D | + x: None +24-11-19 19:07:51 | D | + y: None +24-11-19 19:07:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:07:51 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:07:51 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:07:51 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:07:51 | D | - range ratio = [ 1.0000] +24-11-19 19:07:51 | D | sum error = [ 9.6317] +24-11-19 19:07:51 | D | best error = [ 9.6317] +24-11-19 19:07:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:07:52 | D | sum error = [ 9.5567, 9.5064, 9.5501, 9.6606, 9.8352] +24-11-19 19:07:52 | D | best error = [ 8.4920, 8.0930, 7.9058, 7.8068, 7.7496] +24-11-19 19:07:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:07:52 | D | sum error = [ 10.0987, 10.4526, 10.8703, 11.4010, 11.9495] +24-11-19 19:07:52 | D | best error = [ 7.7224, 7.7094, 7.7050, 7.7031, 7.7026] +24-11-19 19:07:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:07:52 | D | sum error = [ 12.6814, 13.4629, 14.2889, 15.2716, 16.3325] +24-11-19 19:07:52 | D | best error = [ 7.7024, 7.7023, 7.7023, 7.7023, 7.7023] +24-11-19 19:07:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:07:52 | D | sum error = [ 17.4766, 18.6777, 20.0325, 21.4526, 22.9759] +24-11-19 19:07:52 | D | best error = [ 7.7023, 7.7023, 7.7023, 7.7023, 7.7023] +24-11-19 19:07:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:07:52 | D | sum error = [ 24.6702, 26.3945, 28.2246, 30.1736, 32.3109] +24-11-19 19:07:52 | D | best error = [ 7.7023, 7.7023, 7.7023, 7.7023, 7.7023] +24-11-19 19:07:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:07:52 | D | sum error = [ 34.4965, 36.8268, 39.3245, 41.9146, 44.7002] +24-11-19 19:07:52 | D | best error = [ 7.7023, 7.7023, 7.7023, 7.7023, 7.7023] +24-11-19 19:07:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:07:52 | D | sum error = [ 47.5960, 50.6246, 53.8886, 57.2808, 60.8375] +24-11-19 19:07:52 | D | best error = [ 7.7023, 7.7023, 7.7023, 7.7023, 7.7023] +24-11-19 19:07:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:07:52 | D | sum error = [ 64.6304, 68.5891, 72.7398, 77.0991, 81.7491] +24-11-19 19:07:52 | D | best error = [ 7.7023, 7.7023, 7.7023, 7.7023, 7.7023] +24-11-19 19:07:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:07:52 | D | sum error = [ 86.5711, 91.6464, 96.9805, 102.4888, 108.2974] +24-11-19 19:07:52 | D | best error = [ 7.7023, 7.7023, 7.7023, 7.7023, 7.7023] +24-11-19 19:07:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:07:52 | D | sum error = [ 114.3943, 120.7455, 127.4131, 134.3389, 141.5860] +24-11-19 19:07:52 | D | best error = [ 7.7023, 7.7023, 7.7023, 7.7023, 7.7023] +24-11-19 19:07:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:07:52 | D | sum error = [ 149.1138, 157.0539, 165.2530, 173.8085, 182.7041] +24-11-19 19:07:52 | D | best error = [ 7.7023, 7.7023, 7.7023, 7.7023, 7.7023] +24-11-19 19:07:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:07:52 | D | sum error = [ 191.9496, 201.5833, 211.5585, 221.9365, 232.6728] +24-11-19 19:07:52 | D | best error = [ 7.7023, 7.7023, 7.7023, 7.7023, 7.7023] +24-11-19 19:07:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:07:52 | D | sum error = [ 243.8261, 255.3756, 267.3726, 279.8094, 292.6439] +24-11-19 19:07:52 | D | best error = [ 7.7023, 7.7023, 7.7023, 7.7023, 7.7023] +24-11-19 19:07:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:07:52 | D | sum error = [ 305.9455, 319.7011, 333.9246, 348.6482, 363.8402] +24-11-19 19:07:52 | D | best error = [ 7.7023, 7.7023, 7.7023, 7.7023, 7.7023] +24-11-19 19:07:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:07:52 | D | sum error = [ 379.5469, 395.7470, 412.4742, 429.7168, 447.4880] +24-11-19 19:07:52 | D | best error = [ 7.7023, 7.7023, 7.7023, 7.7023, 7.7023] +24-11-19 19:07:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:07:52 | D | sum error = [ 465.8031, 484.6620, 504.0386, 523.9811, 544.4600] +24-11-19 19:07:52 | D | best error = [ 7.7023, 7.7023, 7.7023, 7.7023, 7.7023] +24-11-19 19:07:52 | D | + error = [7.7023] +24-11-19 19:07:52 | D | - Calibrating model.layers.28.mlp.gate_proj.weight +24-11-19 19:07:52 | D | + w: sint8 +24-11-19 19:07:52 | D | + x: None +24-11-19 19:07:52 | D | + y: None +24-11-19 19:07:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:07:52 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:07:52 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:07:53 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:07:53 | D | - range ratio = [ 1.0000] +24-11-19 19:07:53 | D | sum error = [ 12.5619] +24-11-19 19:07:53 | D | best error = [ 12.5619] +24-11-19 19:07:54 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:07:54 | D | sum error = [ 12.4410, 12.4298, 12.4585, 12.6166, 12.8294] +24-11-19 19:07:54 | D | best error = [ 11.0526, 10.5567, 10.3079, 10.1801, 10.1059] +24-11-19 19:07:54 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:07:54 | D | sum error = [ 13.1823, 13.6848, 14.1400, 14.8331, 15.6473] +24-11-19 19:07:54 | D | best error = [ 10.0682, 10.0503, 10.0433, 10.0402, 10.0394] +24-11-19 19:07:54 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:07:54 | D | sum error = [ 16.5431, 17.5646, 18.7158, 19.9922, 21.4132] +24-11-19 19:07:54 | D | best error = [ 10.0392, 10.0392, 10.0391, 10.0391, 10.0391] +24-11-19 19:07:54 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:07:54 | D | sum error = [ 22.9229, 24.5770, 26.3455, 28.2876, 30.3198] +24-11-19 19:07:54 | D | best error = [ 10.0391, 10.0391, 10.0391, 10.0391, 10.0391] +24-11-19 19:07:54 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:07:54 | D | sum error = [ 32.5118, 34.9023, 37.3586, 40.0520, 42.8269] +24-11-19 19:07:54 | D | best error = [ 10.0391, 10.0391, 10.0391, 10.0391, 10.0391] +24-11-19 19:07:54 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:07:54 | D | sum error = [ 45.9025, 49.0830, 52.4687, 56.0810, 59.8536] +24-11-19 19:07:54 | D | best error = [ 10.0391, 10.0391, 10.0391, 10.0391, 10.0391] +24-11-19 19:07:54 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:07:54 | D | sum error = [ 63.8834, 68.1593, 72.7696, 77.5011, 82.6211] +24-11-19 19:07:54 | D | best error = [ 10.0391, 10.0391, 10.0391, 10.0391, 10.0391] +24-11-19 19:07:54 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:07:54 | D | sum error = [ 87.9486, 93.6743, 99.6664, 106.0387, 112.7134] +24-11-19 19:07:54 | D | best error = [ 10.0391, 10.0391, 10.0391, 10.0391, 10.0391] +24-11-19 19:07:54 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:07:54 | D | sum error = [ 119.8613, 127.3809, 135.2979, 143.7435, 152.5287] +24-11-19 19:07:54 | D | best error = [ 10.0391, 10.0391, 10.0391, 10.0391, 10.0391] +24-11-19 19:07:54 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:07:54 | D | sum error = [ 161.8733, 171.6993, 182.1403, 193.0957, 204.5343] +24-11-19 19:07:54 | D | best error = [ 10.0391, 10.0391, 10.0391, 10.0391, 10.0391] +24-11-19 19:07:54 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:07:54 | D | sum error = [ 216.6280, 229.3807, 242.7818, 256.8594, 271.6997] +24-11-19 19:07:54 | D | best error = [ 10.0391, 10.0391, 10.0391, 10.0391, 10.0391] +24-11-19 19:07:54 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:07:54 | D | sum error = [ 287.2091, 303.5138, 320.6047, 338.5502, 357.3297] +24-11-19 19:07:54 | D | best error = [ 10.0391, 10.0391, 10.0391, 10.0391, 10.0391] +24-11-19 19:07:54 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:07:54 | D | sum error = [ 376.9409, 397.5103, 419.0880, 441.5707, 465.0498] +24-11-19 19:07:54 | D | best error = [ 10.0391, 10.0391, 10.0391, 10.0391, 10.0391] +24-11-19 19:07:54 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:07:54 | D | sum error = [ 489.5323, 515.1192, 541.7402, 569.4136, 598.1579] +24-11-19 19:07:54 | D | best error = [ 10.0391, 10.0391, 10.0391, 10.0391, 10.0391] +24-11-19 19:07:54 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:07:54 | D | sum error = [ 627.9406, 658.8221, 690.8595, 724.0048, 758.3959] +24-11-19 19:07:54 | D | best error = [ 10.0391, 10.0391, 10.0391, 10.0391, 10.0391] +24-11-19 19:07:54 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:07:54 | D | sum error = [ 793.9469, 830.6738, 868.5952, 907.7667, 948.1970] +24-11-19 19:07:54 | D | best error = [ 10.0391, 10.0391, 10.0391, 10.0391, 10.0391] +24-11-19 19:07:54 | D | + error = [10.0391] +24-11-19 19:07:54 | D | - Calibrating model.layers.28.mlp.down_proj.weight +24-11-19 19:07:54 | D | + w: sint8 +24-11-19 19:07:54 | D | + x: None +24-11-19 19:07:54 | D | + y: None +24-11-19 19:07:54 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:07:54 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 19:07:54 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 19:07:54 | D | + finished calculating the original outputs, ram usage: 12.4 +24-11-19 19:07:54 | D | - range ratio = [ 1.0000] +24-11-19 19:07:54 | D | sum error = [ 1.8314] +24-11-19 19:07:54 | D | best error = [ 1.8314] +24-11-19 19:07:55 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:07:55 | D | sum error = [ 1.8175, 1.7947, 1.7822, 1.7743, 1.7616] +24-11-19 19:07:55 | D | best error = [ 1.7115, 1.6608, 1.6297, 1.6082, 1.5911] +24-11-19 19:07:55 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:07:55 | D | sum error = [ 1.7593, 1.7630, 1.7663, 1.7763, 1.7966] +24-11-19 19:07:55 | D | best error = [ 1.5776, 1.5674, 1.5587, 1.5519, 1.5472] +24-11-19 19:07:55 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:07:55 | D | sum error = [ 1.8225, 1.8547, 1.8861, 1.9365, 1.9927] +24-11-19 19:07:55 | D | best error = [ 1.5437, 1.5408, 1.5386, 1.5369, 1.5358] +24-11-19 19:07:55 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:07:55 | D | sum error = [ 2.0649, 2.1429, 2.2353, 2.3477, 2.4632] +24-11-19 19:07:55 | D | best error = [ 1.5351, 1.5344, 1.5342, 1.5339, 1.5338] +24-11-19 19:07:55 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:07:55 | D | sum error = [ 2.5966, 2.7474, 2.9091, 3.0907, 3.2832] +24-11-19 19:07:55 | D | best error = [ 1.5338, 1.5338, 1.5337, 1.5337, 1.5337] +24-11-19 19:07:55 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:07:55 | D | sum error = [ 3.4944, 3.7276, 3.9741, 4.2459, 4.5364] +24-11-19 19:07:55 | D | best error = [ 1.5337, 1.5337, 1.5337, 1.5337, 1.5337] +24-11-19 19:07:55 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:07:55 | D | sum error = [ 4.8390, 5.1778, 5.5252, 5.9117, 6.3130] +24-11-19 19:07:55 | D | best error = [ 1.5337, 1.5337, 1.5337, 1.5337, 1.5337] +24-11-19 19:07:55 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:07:55 | D | sum error = [ 6.7455, 7.2100, 7.6975, 8.2159, 8.7691] +24-11-19 19:07:55 | D | best error = [ 1.5337, 1.5337, 1.5337, 1.5337, 1.5337] +24-11-19 19:07:55 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:07:55 | D | sum error = [ 9.3517, 9.9745, 10.6351, 11.3302, 12.0737] +24-11-19 19:07:55 | D | best error = [ 1.5337, 1.5337, 1.5337, 1.5337, 1.5337] +24-11-19 19:07:55 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:07:55 | D | sum error = [ 12.8531, 13.6813, 14.5558, 15.4772, 16.4544] +24-11-19 19:07:55 | D | best error = [ 1.5337, 1.5337, 1.5337, 1.5337, 1.5337] +24-11-19 19:07:55 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:07:55 | D | sum error = [ 17.4815, 18.5710, 19.7172, 20.9268, 22.1985] +24-11-19 19:07:55 | D | best error = [ 1.5337, 1.5337, 1.5337, 1.5337, 1.5337] +24-11-19 19:07:55 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:07:55 | D | sum error = [ 23.5405, 24.9506, 26.4321, 27.9854, 29.6202] +24-11-19 19:07:55 | D | best error = [ 1.5337, 1.5337, 1.5337, 1.5337, 1.5337] +24-11-19 19:07:55 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:07:55 | D | sum error = [ 31.3355, 33.1320, 35.0176, 36.9945, 39.0645] +24-11-19 19:07:55 | D | best error = [ 1.5337, 1.5337, 1.5337, 1.5337, 1.5337] +24-11-19 19:07:55 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:07:55 | D | sum error = [ 41.2313, 43.4999, 45.8726, 48.3604, 50.9587] +24-11-19 19:07:55 | D | best error = [ 1.5337, 1.5337, 1.5337, 1.5337, 1.5337] +24-11-19 19:07:55 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:07:55 | D | sum error = [ 53.6722, 56.5073, 59.4655, 62.5469, 65.7589] +24-11-19 19:07:55 | D | best error = [ 1.5337, 1.5337, 1.5337, 1.5337, 1.5337] +24-11-19 19:07:55 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:07:55 | D | sum error = [ 69.1031, 72.5846, 76.2085, 79.9774, 83.8924] +24-11-19 19:07:55 | D | best error = [ 1.5337, 1.5337, 1.5337, 1.5337, 1.5337] +24-11-19 19:07:55 | D | + error = [1.5337] +24-11-19 19:07:55 | D | - Quantizing model.layers.28.self_attn.q_proj.weight +24-11-19 19:07:56 | D | - Quantizing model.layers.28.self_attn.k_proj.weight +24-11-19 19:07:57 | D | - Quantizing model.layers.28.self_attn.v_proj.weight +24-11-19 19:07:58 | D | - Quantizing model.layers.28.self_attn.o_proj.weight +24-11-19 19:07:59 | D | - Quantizing model.layers.28.mlp.up_proj.weight +24-11-19 19:08:00 | D | - Quantizing model.layers.28.mlp.gate_proj.weight +24-11-19 19:08:00 | D | - Quantizing model.layers.28.mlp.down_proj.weight +24-11-19 19:08:10 | D | - Quantizing layer model.layers.29 +24-11-19 19:08:10 | D | - Calibrating model.layers.29.self_attn.q_proj.weight +24-11-19 19:08:10 | D | + w: sint8 +24-11-19 19:08:10 | D | + x: None +24-11-19 19:08:10 | D | + y: None +24-11-19 19:08:10 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:08:10 | D | + finished parsing calibration arguments, ram usage: 11.9 +24-11-19 19:08:10 | D | + finished reseting calibrator, ram usage: 11.9 +24-11-19 19:08:10 | D | + finished calculating the original outputs, ram usage: 11.9 +24-11-19 19:08:10 | D | - range ratio = [ 1.0000] +24-11-19 19:08:10 | D | sum error = [ 9.4131] +24-11-19 19:08:10 | D | best error = [ 9.4131] +24-11-19 19:08:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:08:22 | D | sum error = [ 8.6612, 8.4947, 9.2881, 8.7742, 8.8820] +24-11-19 19:08:22 | D | best error = [ 8.6612, 8.4947, 8.4947, 8.4947, 8.4947] +24-11-19 19:08:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:08:22 | D | sum error = [ 9.0621, 9.7219, 10.1457, 10.0418, 12.1620] +24-11-19 19:08:22 | D | best error = [ 8.4947, 8.4947, 8.4947, 8.4947, 8.4947] +24-11-19 19:08:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:08:22 | D | sum error = [ 12.5262, 13.2117, 13.7651, 14.5613, 15.9932] +24-11-19 19:08:22 | D | best error = [ 8.4947, 8.4947, 8.4947, 8.4947, 8.4947] +24-11-19 19:08:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:08:22 | D | sum error = [ 18.1861, 19.3596, 19.9122, 23.0835, 24.7593] +24-11-19 19:08:22 | D | best error = [ 8.4947, 8.4947, 8.4947, 8.4947, 8.4947] +24-11-19 19:08:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:08:22 | D | sum error = [ 26.8859, 30.1881, 30.9646, 35.1759, 36.8395] +24-11-19 19:08:22 | D | best error = [ 8.4947, 8.4947, 8.4947, 8.4947, 8.4947] +24-11-19 19:08:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:08:22 | D | sum error = [ 39.5897, 42.5636, 45.9417, 49.0723, 53.3375] +24-11-19 19:08:22 | D | best error = [ 8.4947, 8.4947, 8.4947, 8.4947, 8.4947] +24-11-19 19:08:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:08:22 | D | sum error = [ 55.9569, 60.9584, 65.5590, 70.3109, 74.8707] +24-11-19 19:08:22 | D | best error = [ 8.4947, 8.4947, 8.4947, 8.4947, 8.4947] +24-11-19 19:08:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:08:22 | D | sum error = [ 81.2934, 86.5163, 92.6905, 99.9212, 106.6173] +24-11-19 19:08:22 | D | best error = [ 8.4947, 8.4947, 8.4947, 8.4947, 8.4947] +24-11-19 19:08:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:08:22 | D | sum error = [ 114.1623, 122.7964, 130.7256, 140.5047, 151.1184] +24-11-19 19:08:22 | D | best error = [ 8.4947, 8.4947, 8.4947, 8.4947, 8.4947] +24-11-19 19:08:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:08:22 | D | sum error = [ 161.7757, 173.4625, 186.7715, 201.2485, 216.3029] +24-11-19 19:08:22 | D | best error = [ 8.4947, 8.4947, 8.4947, 8.4947, 8.4947] +24-11-19 19:08:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:08:22 | D | sum error = [ 231.6200, 248.0135, 265.2424, 284.3561, 304.7462] +24-11-19 19:08:22 | D | best error = [ 8.4947, 8.4947, 8.4947, 8.4947, 8.4947] +24-11-19 19:08:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:08:22 | D | sum error = [ 326.1172, 349.6647, 374.8093, 402.2653, 432.6119] +24-11-19 19:08:22 | D | best error = [ 8.4947, 8.4947, 8.4947, 8.4947, 8.4947] +24-11-19 19:08:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:08:22 | D | sum error = [ 464.3204, 499.6175, 537.8942, 579.2429, 624.9598] +24-11-19 19:08:22 | D | best error = [ 8.4947, 8.4947, 8.4947, 8.4947, 8.4947] +24-11-19 19:08:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:08:22 | D | sum error = [ 675.1417, 729.2452, 788.9049, 853.9102, 926.0464] +24-11-19 19:08:22 | D | best error = [ 8.4947, 8.4947, 8.4947, 8.4947, 8.4947] +24-11-19 19:08:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:08:22 | D | sum error = [ 1002.7835, 1088.0124, 1180.8970, 1281.1555, 1390.1186] +24-11-19 19:08:22 | D | best error = [ 8.4947, 8.4947, 8.4947, 8.4947, 8.4947] +24-11-19 19:08:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:08:22 | D | sum error = [ 1508.0104, 1632.7693, 1767.0238, 1905.4675, 2051.1024] +24-11-19 19:08:22 | D | best error = [ 8.4947, 8.4947, 8.4947, 8.4947, 8.4947] +24-11-19 19:08:22 | D | + error = [8.4947] +24-11-19 19:08:22 | D | - Calibrating model.layers.29.self_attn.k_proj.weight +24-11-19 19:08:22 | D | + w: sint8 +24-11-19 19:08:22 | D | + x: None +24-11-19 19:08:22 | D | + y: None +24-11-19 19:08:22 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:08:22 | D | + finished parsing calibration arguments, ram usage: 11.9 +24-11-19 19:08:23 | D | + finished reseting calibrator, ram usage: 11.9 +24-11-19 19:08:23 | D | + finished calculating the original outputs, ram usage: 11.9 +24-11-19 19:08:23 | D | - range ratio = [ 1.0000] +24-11-19 19:08:23 | D | sum error = [ 8.8529] +24-11-19 19:08:23 | D | best error = [ 8.8529] +24-11-19 19:08:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:08:35 | D | sum error = [ 8.8187, 10.8413, 8.9488, 10.3471, 8.8247] +24-11-19 19:08:35 | D | best error = [ 8.8187, 8.8187, 8.8187, 8.8187, 8.8187] +24-11-19 19:08:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:08:35 | D | sum error = [ 9.4051, 10.6431, 10.1911, 11.2050, 11.3711] +24-11-19 19:08:35 | D | best error = [ 8.8187, 8.8187, 8.8187, 8.8187, 8.8187] +24-11-19 19:08:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:08:35 | D | sum error = [ 12.9705, 15.4164, 15.9144, 17.5859, 16.7951] +24-11-19 19:08:35 | D | best error = [ 8.8187, 8.8187, 8.8187, 8.8187, 8.8187] +24-11-19 19:08:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:08:35 | D | sum error = [ 15.7802, 17.6313, 22.0424, 24.4946, 22.8220] +24-11-19 19:08:35 | D | best error = [ 8.8187, 8.8187, 8.8187, 8.8187, 8.8187] +24-11-19 19:08:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:08:35 | D | sum error = [ 24.2328, 26.1108, 27.3872, 29.7469, 32.4524] +24-11-19 19:08:35 | D | best error = [ 8.8187, 8.8187, 8.8187, 8.8187, 8.8187] +24-11-19 19:08:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:08:35 | D | sum error = [ 33.6718, 37.1595, 38.2347, 42.0099, 45.4482] +24-11-19 19:08:35 | D | best error = [ 8.8187, 8.8187, 8.8187, 8.8187, 8.8187] +24-11-19 19:08:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:08:35 | D | sum error = [ 46.9040, 52.1127, 54.9035, 58.7115, 61.9777] +24-11-19 19:08:35 | D | best error = [ 8.8187, 8.8187, 8.8187, 8.8187, 8.8187] +24-11-19 19:08:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:08:35 | D | sum error = [ 65.6813, 71.2680, 74.4498, 81.7149, 88.3045] +24-11-19 19:08:35 | D | best error = [ 8.8187, 8.8187, 8.8187, 8.8187, 8.8187] +24-11-19 19:08:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:08:35 | D | sum error = [ 95.4517, 104.9500, 114.2273, 123.5590, 136.3117] +24-11-19 19:08:35 | D | best error = [ 8.8187, 8.8187, 8.8187, 8.8187, 8.8187] +24-11-19 19:08:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:08:35 | D | sum error = [ 150.5360, 162.6717, 179.1699, 198.0220, 214.1618] +24-11-19 19:08:35 | D | best error = [ 8.8187, 8.8187, 8.8187, 8.8187, 8.8187] +24-11-19 19:08:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:08:35 | D | sum error = [ 239.5585, 257.7292, 287.9611, 308.5363, 335.0173] +24-11-19 19:08:35 | D | best error = [ 8.8187, 8.8187, 8.8187, 8.8187, 8.8187] +24-11-19 19:08:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:08:35 | D | sum error = [ 362.9365, 393.4862, 424.6683, 456.6227, 489.4539] +24-11-19 19:08:35 | D | best error = [ 8.8187, 8.8187, 8.8187, 8.8187, 8.8187] +24-11-19 19:08:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:08:35 | D | sum error = [ 525.2996, 561.6603, 609.5335, 655.6447, 702.5998] +24-11-19 19:08:35 | D | best error = [ 8.8187, 8.8187, 8.8187, 8.8187, 8.8187] +24-11-19 19:08:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:08:35 | D | sum error = [ 754.6613, 804.0568, 874.1027, 922.5616, 1004.2547] +24-11-19 19:08:35 | D | best error = [ 8.8187, 8.8187, 8.8187, 8.8187, 8.8187] +24-11-19 19:08:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:08:35 | D | sum error = [ 1070.0423, 1160.2015, 1240.8854, 1346.9609, 1437.1827] +24-11-19 19:08:35 | D | best error = [ 8.8187, 8.8187, 8.8187, 8.8187, 8.8187] +24-11-19 19:08:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:08:35 | D | sum error = [ 1561.9639, 1671.0095, 1803.7318, 1933.0619, 2074.8925] +24-11-19 19:08:35 | D | best error = [ 8.8187, 8.8187, 8.8187, 8.8187, 8.8187] +24-11-19 19:08:35 | D | + error = [8.8187] +24-11-19 19:08:35 | D | - Calibrating model.layers.29.self_attn.v_proj.weight +24-11-19 19:08:35 | D | + w: sint8 +24-11-19 19:08:35 | D | + x: None +24-11-19 19:08:35 | D | + y: None +24-11-19 19:08:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:08:35 | D | + finished parsing calibration arguments, ram usage: 11.9 +24-11-19 19:08:35 | D | + finished reseting calibrator, ram usage: 11.9 +24-11-19 19:08:35 | D | + finished calculating the original outputs, ram usage: 11.9 +24-11-19 19:08:35 | D | - range ratio = [ 1.0000] +24-11-19 19:08:35 | D | sum error = [ 3.1148] +24-11-19 19:08:35 | D | best error = [ 3.1148] +24-11-19 19:08:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:08:35 | D | sum error = [ 3.0926, 3.1116, 3.1176, 3.1331, 3.2179] +24-11-19 19:08:35 | D | best error = [ 2.7893, 2.6825, 2.6252, 2.5870, 2.5712] +24-11-19 19:08:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:08:35 | D | sum error = [ 3.3547, 3.4158, 3.5195, 3.7244, 3.9557] +24-11-19 19:08:35 | D | best error = [ 2.5637, 2.5611, 2.5594, 2.5591, 2.5590] +24-11-19 19:08:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:08:35 | D | sum error = [ 4.1558, 4.3860, 4.6796, 5.0064, 5.3169] +24-11-19 19:08:35 | D | best error = [ 2.5589, 2.5589, 2.5589, 2.5589, 2.5589] +24-11-19 19:08:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:08:35 | D | sum error = [ 5.6997, 6.1311, 6.5308, 7.0238, 7.5364] +24-11-19 19:08:35 | D | best error = [ 2.5589, 2.5589, 2.5589, 2.5589, 2.5589] +24-11-19 19:08:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:08:35 | D | sum error = [ 8.0198, 8.6529, 9.2422, 9.9588, 10.5966] +24-11-19 19:08:35 | D | best error = [ 2.5589, 2.5589, 2.5589, 2.5589, 2.5589] +24-11-19 19:08:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:08:35 | D | sum error = [ 11.3258, 12.1103, 12.8957, 13.7195, 14.6770] +24-11-19 19:08:35 | D | best error = [ 2.5589, 2.5589, 2.5589, 2.5589, 2.5589] +24-11-19 19:08:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:08:35 | D | sum error = [ 15.6532, 16.6097, 17.7047, 18.7652, 19.9499] +24-11-19 19:08:35 | D | best error = [ 2.5589, 2.5589, 2.5589, 2.5589, 2.5589] +24-11-19 19:08:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:08:35 | D | sum error = [ 21.2001, 22.4887, 23.8513, 25.2751, 26.7295] +24-11-19 19:08:35 | D | best error = [ 2.5589, 2.5589, 2.5589, 2.5589, 2.5589] +24-11-19 19:08:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:08:35 | D | sum error = [ 28.2842, 29.9465, 31.6355, 33.4241, 35.3313] +24-11-19 19:08:35 | D | best error = [ 2.5589, 2.5589, 2.5589, 2.5589, 2.5589] +24-11-19 19:08:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:08:35 | D | sum error = [ 37.3280, 39.3790, 41.5178, 43.8073, 46.2377] +24-11-19 19:08:35 | D | best error = [ 2.5589, 2.5589, 2.5589, 2.5589, 2.5589] +24-11-19 19:08:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:08:35 | D | sum error = [ 48.6438, 51.2388, 53.9409, 56.7272, 59.6312] +24-11-19 19:08:35 | D | best error = [ 2.5589, 2.5589, 2.5589, 2.5589, 2.5589] +24-11-19 19:08:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:08:35 | D | sum error = [ 62.6968, 65.8294, 69.0928, 72.4990, 75.9877] +24-11-19 19:08:35 | D | best error = [ 2.5589, 2.5589, 2.5589, 2.5589, 2.5589] +24-11-19 19:08:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:08:35 | D | sum error = [ 79.6558, 83.4535, 87.3656, 91.4355, 95.6329] +24-11-19 19:08:35 | D | best error = [ 2.5589, 2.5589, 2.5589, 2.5589, 2.5589] +24-11-19 19:08:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:08:35 | D | sum error = [ 100.0007, 104.5089, 109.1728, 114.0240, 119.0019] +24-11-19 19:08:35 | D | best error = [ 2.5589, 2.5589, 2.5589, 2.5589, 2.5589] +24-11-19 19:08:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:08:35 | D | sum error = [ 124.1562, 129.4579, 134.9225, 140.5583, 146.3724] +24-11-19 19:08:35 | D | best error = [ 2.5589, 2.5589, 2.5589, 2.5589, 2.5589] +24-11-19 19:08:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:08:35 | D | sum error = [ 152.3368, 158.4866, 164.7962, 171.3020, 177.9760] +24-11-19 19:08:35 | D | best error = [ 2.5589, 2.5589, 2.5589, 2.5589, 2.5589] +24-11-19 19:08:35 | D | + error = [2.5589] +24-11-19 19:08:35 | D | - Calibrating model.layers.29.self_attn.o_proj.weight +24-11-19 19:08:35 | D | + w: sint8 +24-11-19 19:08:35 | D | + x: None +24-11-19 19:08:35 | D | + y: None +24-11-19 19:08:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:08:35 | D | + finished parsing calibration arguments, ram usage: 11.9 +24-11-19 19:08:35 | D | + finished reseting calibrator, ram usage: 11.9 +24-11-19 19:08:35 | D | + finished calculating the original outputs, ram usage: 11.9 +24-11-19 19:08:35 | D | - range ratio = [ 1.0000] +24-11-19 19:08:35 | D | sum error = [ 0.9301] +24-11-19 19:08:35 | D | best error = [ 0.9301] +24-11-19 19:08:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:08:36 | D | sum error = [ 0.9242, 0.9300, 0.9297, 0.9375, 0.9486] +24-11-19 19:08:36 | D | best error = [ 0.8409, 0.8043, 0.7831, 0.7689, 0.7602] +24-11-19 19:08:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:08:36 | D | sum error = [ 0.9734, 0.9996, 1.0290, 1.0752, 1.1220] +24-11-19 19:08:36 | D | best error = [ 0.7539, 0.7490, 0.7457, 0.7432, 0.7414] +24-11-19 19:08:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:08:36 | D | sum error = [ 1.1820, 1.2409, 1.3168, 1.3840, 1.4702] +24-11-19 19:08:36 | D | best error = [ 0.7401, 0.7392, 0.7385, 0.7381, 0.7378] +24-11-19 19:08:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:08:36 | D | sum error = [ 1.5602, 1.6652, 1.7759, 1.8849, 2.0047] +24-11-19 19:08:36 | D | best error = [ 0.7376, 0.7374, 0.7372, 0.7371, 0.7371] +24-11-19 19:08:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:08:36 | D | sum error = [ 2.1385, 2.2797, 2.4140, 2.5786, 2.7460] +24-11-19 19:08:36 | D | best error = [ 0.7370, 0.7370, 0.7370, 0.7370, 0.7369] +24-11-19 19:08:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:08:36 | D | sum error = [ 2.9151, 3.1004, 3.2929, 3.4999, 3.7110] +24-11-19 19:08:36 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 19:08:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:08:36 | D | sum error = [ 3.9390, 4.1778, 4.4293, 4.6918, 4.9679] +24-11-19 19:08:36 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 19:08:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:08:36 | D | sum error = [ 5.2608, 5.5714, 5.8903, 6.2376, 6.5899] +24-11-19 19:08:36 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 19:08:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:08:36 | D | sum error = [ 6.9727, 7.3722, 7.7878, 8.2381, 8.6995] +24-11-19 19:08:36 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 19:08:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:08:36 | D | sum error = [ 9.1900, 9.7060, 10.2479, 10.8195, 11.4184] +24-11-19 19:08:36 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 19:08:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:08:36 | D | sum error = [ 12.0553, 12.7334, 13.4442, 14.1937, 14.9888] +24-11-19 19:08:36 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 19:08:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:08:36 | D | sum error = [ 15.8184, 16.6983, 17.6189, 18.5900, 19.6074] +24-11-19 19:08:36 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 19:08:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:08:36 | D | sum error = [ 20.6815, 21.8080, 22.9944, 24.2405, 25.5460] +24-11-19 19:08:36 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 19:08:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:08:36 | D | sum error = [ 26.9187, 28.3562, 29.8675, 31.4495, 33.1053] +24-11-19 19:08:36 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 19:08:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:08:36 | D | sum error = [ 34.8335, 36.6416, 38.5269, 40.4915, 42.5406] +24-11-19 19:08:36 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 19:08:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:08:36 | D | sum error = [ 44.6777, 46.8980, 49.2122, 51.6109, 54.1070] +24-11-19 19:08:36 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 19:08:36 | D | + error = [0.7369] +24-11-19 19:08:36 | D | - Calibrating model.layers.29.mlp.up_proj.weight +24-11-19 19:08:36 | D | + w: sint8 +24-11-19 19:08:36 | D | + x: None +24-11-19 19:08:36 | D | + y: None +24-11-19 19:08:36 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:08:36 | D | + finished parsing calibration arguments, ram usage: 11.9 +24-11-19 19:08:36 | D | + finished reseting calibrator, ram usage: 11.9 +24-11-19 19:08:36 | D | + finished calculating the original outputs, ram usage: 11.9 +24-11-19 19:08:36 | D | - range ratio = [ 1.0000] +24-11-19 19:08:36 | D | sum error = [ 10.0567] +24-11-19 19:08:36 | D | best error = [ 10.0567] +24-11-19 19:08:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:08:37 | D | sum error = [ 9.9564, 9.9986, 9.9803, 10.0938, 10.2836] +24-11-19 19:08:37 | D | best error = [ 8.8172, 8.4240, 8.2227, 8.1148, 8.0550] +24-11-19 19:08:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:08:37 | D | sum error = [ 10.5883, 10.9224, 11.3832, 11.8716, 12.4705] +24-11-19 19:08:37 | D | best error = [ 8.0237, 8.0086, 8.0031, 8.0009, 8.0000] +24-11-19 19:08:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:08:37 | D | sum error = [ 13.2919, 14.0658, 14.9312, 15.9724, 17.1434] +24-11-19 19:08:37 | D | best error = [ 7.9999, 7.9999, 7.9999, 7.9999, 7.9999] +24-11-19 19:08:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:08:37 | D | sum error = [ 18.3090, 19.5580, 21.0146, 22.5715, 24.1440] +24-11-19 19:08:37 | D | best error = [ 7.9999, 7.9999, 7.9999, 7.9999, 7.9999] +24-11-19 19:08:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:08:37 | D | sum error = [ 25.8790, 27.7162, 29.6484, 31.8073, 33.9735] +24-11-19 19:08:37 | D | best error = [ 7.9999, 7.9999, 7.9999, 7.9999, 7.9999] +24-11-19 19:08:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:08:37 | D | sum error = [ 36.3128, 38.7938, 41.4475, 44.1963, 47.1646] +24-11-19 19:08:37 | D | best error = [ 7.9999, 7.9999, 7.9999, 7.9999, 7.9999] +24-11-19 19:08:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:08:37 | D | sum error = [ 50.2271, 53.5444, 56.9259, 60.5384, 64.3845] +24-11-19 19:08:37 | D | best error = [ 7.9999, 7.9999, 7.9999, 7.9999, 7.9999] +24-11-19 19:08:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:08:37 | D | sum error = [ 68.4024, 72.6571, 77.0938, 81.7902, 86.7174] +24-11-19 19:08:37 | D | best error = [ 7.9999, 7.9999, 7.9999, 7.9999, 7.9999] +24-11-19 19:08:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:08:37 | D | sum error = [ 91.9047, 97.3360, 102.9693, 108.9866, 115.1838] +24-11-19 19:08:37 | D | best error = [ 7.9999, 7.9999, 7.9999, 7.9999, 7.9999] +24-11-19 19:08:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:08:37 | D | sum error = [ 121.7344, 128.5923, 135.7542, 143.2413, 151.1004] +24-11-19 19:08:37 | D | best error = [ 7.9999, 7.9999, 7.9999, 7.9999, 7.9999] +24-11-19 19:08:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:08:37 | D | sum error = [ 159.3322, 167.9360, 176.9105, 186.3037, 196.1006] +24-11-19 19:08:37 | D | best error = [ 7.9999, 7.9999, 7.9999, 7.9999, 7.9999] +24-11-19 19:08:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:08:37 | D | sum error = [ 206.2841, 216.9661, 228.0817, 239.6940, 251.7442] +24-11-19 19:08:37 | D | best error = [ 7.9999, 7.9999, 7.9999, 7.9999, 7.9999] +24-11-19 19:08:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:08:37 | D | sum error = [ 264.2799, 277.3563, 290.9090, 304.9533, 319.5520] +24-11-19 19:08:37 | D | best error = [ 7.9999, 7.9999, 7.9999, 7.9999, 7.9999] +24-11-19 19:08:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:08:37 | D | sum error = [ 334.6933, 350.4369, 366.7298, 383.6376, 401.1299] +24-11-19 19:08:37 | D | best error = [ 7.9999, 7.9999, 7.9999, 7.9999, 7.9999] +24-11-19 19:08:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:08:37 | D | sum error = [ 419.2665, 437.9855, 457.3773, 477.3659, 497.9865] +24-11-19 19:08:37 | D | best error = [ 7.9999, 7.9999, 7.9999, 7.9999, 7.9999] +24-11-19 19:08:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:08:37 | D | sum error = [ 519.2483, 541.1403, 563.7281, 586.9712, 610.9051] +24-11-19 19:08:37 | D | best error = [ 7.9999, 7.9999, 7.9999, 7.9999, 7.9999] +24-11-19 19:08:37 | D | + error = [7.9999] +24-11-19 19:08:37 | D | - Calibrating model.layers.29.mlp.gate_proj.weight +24-11-19 19:08:37 | D | + w: sint8 +24-11-19 19:08:37 | D | + x: None +24-11-19 19:08:37 | D | + y: None +24-11-19 19:08:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:08:37 | D | + finished parsing calibration arguments, ram usage: 11.9 +24-11-19 19:08:37 | D | + finished reseting calibrator, ram usage: 11.9 +24-11-19 19:08:38 | D | + finished calculating the original outputs, ram usage: 11.9 +24-11-19 19:08:38 | D | - range ratio = [ 1.0000] +24-11-19 19:08:38 | D | sum error = [ 12.6724] +24-11-19 19:08:38 | D | best error = [ 12.6724] +24-11-19 19:08:39 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:08:39 | D | sum error = [ 12.6274, 12.6180, 12.6607, 12.7897, 13.0661] +24-11-19 19:08:39 | D | best error = [ 11.1780, 10.6702, 10.4197, 10.2811, 10.2116] +24-11-19 19:08:39 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:08:39 | D | sum error = [ 13.4138, 13.8508, 14.3321, 15.0832, 15.9331] +24-11-19 19:08:39 | D | best error = [ 10.1728, 10.1539, 10.1436, 10.1405, 10.1394] +24-11-19 19:08:39 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:08:39 | D | sum error = [ 16.8201, 17.8226, 19.0295, 20.3274, 21.7964] +24-11-19 19:08:39 | D | best error = [ 10.1392, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 19:08:39 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:08:39 | D | sum error = [ 23.2849, 24.9615, 26.7618, 28.7046, 30.8307] +24-11-19 19:08:39 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 19:08:39 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:08:39 | D | sum error = [ 33.0873, 35.4767, 37.9872, 40.6887, 43.6865] +24-11-19 19:08:39 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 19:08:39 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:08:39 | D | sum error = [ 46.6628, 49.9476, 53.3796, 57.0252, 60.9553] +24-11-19 19:08:39 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 19:08:39 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:08:39 | D | sum error = [ 65.0787, 69.4988, 74.1636, 79.0763, 84.3349] +24-11-19 19:08:39 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 19:08:39 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:08:39 | D | sum error = [ 89.8274, 95.7188, 101.9153, 108.4515, 115.3674] +24-11-19 19:08:39 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 19:08:39 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:08:39 | D | sum error = [ 122.7740, 130.5423, 138.7543, 147.4758, 156.7423] +24-11-19 19:08:39 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 19:08:39 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:08:39 | D | sum error = [ 166.4191, 176.7213, 187.5991, 199.0647, 211.1485] +24-11-19 19:08:39 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 19:08:39 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:08:39 | D | sum error = [ 223.9053, 237.2753, 251.3663, 266.2411, 281.8547] +24-11-19 19:08:39 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 19:08:39 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:08:39 | D | sum error = [ 298.3478, 315.5420, 333.7051, 352.8095, 372.7908] +24-11-19 19:08:39 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 19:08:39 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:08:39 | D | sum error = [ 393.7572, 415.7580, 438.8567, 462.9861, 488.2295] +24-11-19 19:08:39 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 19:08:39 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:08:39 | D | sum error = [ 514.5706, 542.0811, 570.7662, 600.6015, 631.5820] +24-11-19 19:08:39 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 19:08:39 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:08:39 | D | sum error = [ 663.8517, 697.3388, 732.0276, 767.9372, 805.0840] +24-11-19 19:08:39 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 19:08:39 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:08:39 | D | sum error = [ 843.5072, 883.1590, 924.1157, 966.3384, 1009.8002] +24-11-19 19:08:39 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 19:08:39 | D | + error = [10.1391] +24-11-19 19:08:39 | D | - Calibrating model.layers.29.mlp.down_proj.weight +24-11-19 19:08:39 | D | + w: sint8 +24-11-19 19:08:39 | D | + x: None +24-11-19 19:08:39 | D | + y: None +24-11-19 19:08:39 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:08:39 | D | + finished parsing calibration arguments, ram usage: 11.9 +24-11-19 19:08:39 | D | + finished reseting calibrator, ram usage: 11.9 +24-11-19 19:08:39 | D | + finished calculating the original outputs, ram usage: 11.9 +24-11-19 19:08:39 | D | - range ratio = [ 1.0000] +24-11-19 19:08:39 | D | sum error = [ 2.3909] +24-11-19 19:08:39 | D | best error = [ 2.3909] +24-11-19 19:08:40 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:08:40 | D | sum error = [ 2.3696, 2.3536, 2.3536, 2.3569, 2.3598] +24-11-19 19:08:40 | D | best error = [ 2.2139, 2.1402, 2.1008, 2.0719, 2.0489] +24-11-19 19:08:40 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:08:40 | D | sum error = [ 2.4009, 2.4189, 2.4710, 2.5233, 2.5745] +24-11-19 19:08:40 | D | best error = [ 2.0313, 2.0181, 2.0062, 1.9960, 1.9878] +24-11-19 19:08:40 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:08:40 | D | sum error = [ 2.6616, 2.7408, 2.8459, 2.9725, 3.0814] +24-11-19 19:08:40 | D | best error = [ 1.9821, 1.9772, 1.9732, 1.9708, 1.9689] +24-11-19 19:08:40 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:08:40 | D | sum error = [ 3.2220, 3.3783, 3.5419, 3.7241, 3.9085] +24-11-19 19:08:40 | D | best error = [ 1.9675, 1.9665, 1.9658, 1.9656, 1.9653] +24-11-19 19:08:40 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:08:40 | D | sum error = [ 4.1140, 4.3327, 4.5669, 4.8106, 5.0747] +24-11-19 19:08:40 | D | best error = [ 1.9652, 1.9652, 1.9651, 1.9651, 1.9650] +24-11-19 19:08:40 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:08:40 | D | sum error = [ 5.3654, 5.6559, 5.9774, 6.3255, 6.6833] +24-11-19 19:08:40 | D | best error = [ 1.9650, 1.9650, 1.9650, 1.9650, 1.9650] +24-11-19 19:08:40 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:08:40 | D | sum error = [ 7.0555, 7.4594, 7.8896, 8.3389, 8.8193] +24-11-19 19:08:40 | D | best error = [ 1.9650, 1.9650, 1.9650, 1.9650, 1.9650] +24-11-19 19:08:40 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:08:40 | D | sum error = [ 9.3308, 9.8766, 10.4460, 11.0540, 11.6961] +24-11-19 19:08:40 | D | best error = [ 1.9650, 1.9650, 1.9650, 1.9650, 1.9650] +24-11-19 19:08:40 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:08:40 | D | sum error = [ 12.3793, 13.1070, 13.8722, 14.6825, 15.5376] +24-11-19 19:08:40 | D | best error = [ 1.9650, 1.9650, 1.9650, 1.9650, 1.9650] +24-11-19 19:08:40 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:08:40 | D | sum error = [ 16.4411, 17.3986, 18.4056, 19.4785, 20.6055] +24-11-19 19:08:40 | D | best error = [ 1.9650, 1.9650, 1.9650, 1.9650, 1.9650] +24-11-19 19:08:40 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:08:40 | D | sum error = [ 21.7944, 23.0505, 24.3750, 25.7688, 27.2459] +24-11-19 19:08:40 | D | best error = [ 1.9650, 1.9650, 1.9650, 1.9650, 1.9650] +24-11-19 19:08:40 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:08:40 | D | sum error = [ 28.7948, 30.4342, 32.1532, 33.9643, 35.8763] +24-11-19 19:08:40 | D | best error = [ 1.9650, 1.9650, 1.9650, 1.9650, 1.9650] +24-11-19 19:08:40 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:08:40 | D | sum error = [ 37.8919, 40.0054, 42.2252, 44.5524, 46.9967] +24-11-19 19:08:40 | D | best error = [ 1.9650, 1.9650, 1.9650, 1.9650, 1.9650] +24-11-19 19:08:40 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:08:40 | D | sum error = [ 49.5560, 52.2387, 55.0604, 58.0039, 61.0933] +24-11-19 19:08:40 | D | best error = [ 1.9650, 1.9650, 1.9650, 1.9650, 1.9650] +24-11-19 19:08:40 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:08:40 | D | sum error = [ 64.3211, 67.7012, 71.2316, 74.9247, 78.7771] +24-11-19 19:08:40 | D | best error = [ 1.9650, 1.9650, 1.9650, 1.9650, 1.9650] +24-11-19 19:08:40 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:08:40 | D | sum error = [ 82.7946, 86.9829, 91.3512, 95.8864, 100.6168] +24-11-19 19:08:40 | D | best error = [ 1.9650, 1.9650, 1.9650, 1.9650, 1.9650] +24-11-19 19:08:40 | D | + error = [1.9650] +24-11-19 19:08:40 | D | - Quantizing model.layers.29.self_attn.q_proj.weight +24-11-19 19:08:42 | D | - Quantizing model.layers.29.self_attn.k_proj.weight +24-11-19 19:08:43 | D | - Quantizing model.layers.29.self_attn.v_proj.weight +24-11-19 19:08:44 | D | - Quantizing model.layers.29.self_attn.o_proj.weight +24-11-19 19:08:45 | D | - Quantizing model.layers.29.mlp.up_proj.weight +24-11-19 19:08:46 | D | - Quantizing model.layers.29.mlp.gate_proj.weight +24-11-19 19:08:47 | D | - Quantizing model.layers.29.mlp.down_proj.weight +24-11-19 19:08:57 | D | - Quantizing layer model.layers.30 +24-11-19 19:08:57 | D | - Calibrating model.layers.30.self_attn.q_proj.weight +24-11-19 19:08:57 | D | + w: sint8 +24-11-19 19:08:57 | D | + x: None +24-11-19 19:08:57 | D | + y: None +24-11-19 19:08:57 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:08:57 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:08:57 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:08:57 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:08:57 | D | - range ratio = [ 1.0000] +24-11-19 19:08:57 | D | sum error = [ 10.6022] +24-11-19 19:08:57 | D | best error = [ 10.6022] +24-11-19 19:09:09 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:09:09 | D | sum error = [ 10.8273, 10.6835, 10.7475, 11.0115, 11.6064] +24-11-19 19:09:09 | D | best error = [ 10.6022, 10.6022, 10.6022, 10.6022, 10.6022] +24-11-19 19:09:09 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:09:09 | D | sum error = [ 11.1390, 12.3490, 12.0915, 12.7439, 13.8652] +24-11-19 19:09:09 | D | best error = [ 10.6022, 10.6022, 10.6022, 10.6022, 10.6022] +24-11-19 19:09:09 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:09:09 | D | sum error = [ 14.2312, 14.9716, 15.8880, 17.0524, 18.3178] +24-11-19 19:09:09 | D | best error = [ 10.6022, 10.6022, 10.6022, 10.6022, 10.6022] +24-11-19 19:09:09 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:09:09 | D | sum error = [ 19.7344, 21.5673, 23.6710, 25.5678, 27.7058] +24-11-19 19:09:09 | D | best error = [ 10.6022, 10.6022, 10.6022, 10.6022, 10.6022] +24-11-19 19:09:09 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:09:09 | D | sum error = [ 30.0209, 32.5392, 35.0086, 38.4888, 41.6818] +24-11-19 19:09:09 | D | best error = [ 10.6022, 10.6022, 10.6022, 10.6022, 10.6022] +24-11-19 19:09:09 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:09:09 | D | sum error = [ 45.7576, 48.9788, 53.8097, 57.6933, 62.8959] +24-11-19 19:09:09 | D | best error = [ 10.6022, 10.6022, 10.6022, 10.6022, 10.6022] +24-11-19 19:09:09 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:09:09 | D | sum error = [ 67.6061, 73.9569, 78.9980, 85.6692, 92.1782] +24-11-19 19:09:09 | D | best error = [ 10.6022, 10.6022, 10.6022, 10.6022, 10.6022] +24-11-19 19:09:09 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:09:09 | D | sum error = [ 99.8293, 107.5136, 115.7014, 124.5353, 134.4599] +24-11-19 19:09:09 | D | best error = [ 10.6022, 10.6022, 10.6022, 10.6022, 10.6022] +24-11-19 19:09:09 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:09:09 | D | sum error = [ 143.9064, 154.7658, 166.2343, 179.3863, 192.8305] +24-11-19 19:09:09 | D | best error = [ 10.6022, 10.6022, 10.6022, 10.6022, 10.6022] +24-11-19 19:09:09 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:09:09 | D | sum error = [ 205.9788, 220.9120, 237.3300, 254.3961, 273.9074] +24-11-19 19:09:09 | D | best error = [ 10.6022, 10.6022, 10.6022, 10.6022, 10.6022] +24-11-19 19:09:09 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:09:09 | D | sum error = [ 293.0452, 314.7107, 337.9663, 363.3425, 390.8192] +24-11-19 19:09:09 | D | best error = [ 10.6022, 10.6022, 10.6022, 10.6022, 10.6022] +24-11-19 19:09:09 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:09:09 | D | sum error = [ 420.1996, 451.5616, 485.1501, 521.0993, 559.4711] +24-11-19 19:09:09 | D | best error = [ 10.6022, 10.6022, 10.6022, 10.6022, 10.6022] +24-11-19 19:09:09 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:09:09 | D | sum error = [ 601.4600, 646.2790, 693.7640, 744.4168, 798.3429] +24-11-19 19:09:09 | D | best error = [ 10.6022, 10.6022, 10.6022, 10.6022, 10.6022] +24-11-19 19:09:09 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:09:09 | D | sum error = [ 856.2103, 918.3362, 984.4465, 1054.8142, 1130.4722] +24-11-19 19:09:09 | D | best error = [ 10.6022, 10.6022, 10.6022, 10.6022, 10.6022] +24-11-19 19:09:09 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:09:09 | D | sum error = [ 1209.6482, 1294.7733, 1383.1511, 1476.7538, 1574.4089] +24-11-19 19:09:09 | D | best error = [ 10.6022, 10.6022, 10.6022, 10.6022, 10.6022] +24-11-19 19:09:09 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:09:09 | D | sum error = [ 1675.0451, 1778.4121, 1883.2273, 1988.2146, 2092.9306] +24-11-19 19:09:09 | D | best error = [ 10.6022, 10.6022, 10.6022, 10.6022, 10.6022] +24-11-19 19:09:09 | D | + error = [10.6022] +24-11-19 19:09:09 | D | - Calibrating model.layers.30.self_attn.k_proj.weight +24-11-19 19:09:09 | D | + w: sint8 +24-11-19 19:09:09 | D | + x: None +24-11-19 19:09:09 | D | + y: None +24-11-19 19:09:09 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:09:09 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:09:09 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:09:09 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:09:09 | D | - range ratio = [ 1.0000] +24-11-19 19:09:09 | D | sum error = [ 11.7122] +24-11-19 19:09:09 | D | best error = [ 11.7122] +24-11-19 19:09:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:09:21 | D | sum error = [ 9.8037, 10.7139, 10.7434, 11.4134, 11.1984] +24-11-19 19:09:21 | D | best error = [ 9.8037, 9.8037, 9.8037, 9.8037, 9.8037] +24-11-19 19:09:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:09:21 | D | sum error = [ 11.6391, 13.6742, 11.7036, 12.8785, 13.5286] +24-11-19 19:09:21 | D | best error = [ 9.8037, 9.8037, 9.8037, 9.8037, 9.8037] +24-11-19 19:09:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:09:21 | D | sum error = [ 14.3736, 15.5161, 16.4684, 17.2370, 18.0467] +24-11-19 19:09:21 | D | best error = [ 9.8037, 9.8037, 9.8037, 9.8037, 9.8037] +24-11-19 19:09:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:09:21 | D | sum error = [ 20.2773, 21.2444, 22.5461, 24.4102, 25.7661] +24-11-19 19:09:21 | D | best error = [ 9.8037, 9.8037, 9.8037, 9.8037, 9.8037] +24-11-19 19:09:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:09:21 | D | sum error = [ 28.2837, 29.9811, 31.2208, 33.9828, 36.4209] +24-11-19 19:09:21 | D | best error = [ 9.8037, 9.8037, 9.8037, 9.8037, 9.8037] +24-11-19 19:09:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:09:21 | D | sum error = [ 39.1971, 42.1686, 45.4350, 50.6436, 53.4132] +24-11-19 19:09:21 | D | best error = [ 9.8037, 9.8037, 9.8037, 9.8037, 9.8037] +24-11-19 19:09:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:09:21 | D | sum error = [ 58.5845, 62.5211, 68.7726, 72.9716, 78.3757] +24-11-19 19:09:21 | D | best error = [ 9.8037, 9.8037, 9.8037, 9.8037, 9.8037] +24-11-19 19:09:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:09:21 | D | sum error = [ 83.7439, 89.8431, 97.9484, 104.0319, 112.9146] +24-11-19 19:09:21 | D | best error = [ 9.8037, 9.8037, 9.8037, 9.8037, 9.8037] +24-11-19 19:09:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:09:21 | D | sum error = [ 121.1778, 132.0762, 142.4104, 152.5995, 164.5430] +24-11-19 19:09:21 | D | best error = [ 9.8037, 9.8037, 9.8037, 9.8037, 9.8037] +24-11-19 19:09:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:09:21 | D | sum error = [ 179.1977, 192.0047, 205.9664, 223.6388, 241.3198] +24-11-19 19:09:21 | D | best error = [ 9.8037, 9.8037, 9.8037, 9.8037, 9.8037] +24-11-19 19:09:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:09:21 | D | sum error = [ 259.9246, 279.6699, 301.2122, 322.2550, 347.8068] +24-11-19 19:09:21 | D | best error = [ 9.8037, 9.8037, 9.8037, 9.8037, 9.8037] +24-11-19 19:09:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:09:21 | D | sum error = [ 373.6739, 401.7516, 434.6997, 466.7046, 507.2264] +24-11-19 19:09:21 | D | best error = [ 9.8037, 9.8037, 9.8037, 9.8037, 9.8037] +24-11-19 19:09:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:09:21 | D | sum error = [ 544.4138, 585.1013, 626.1108, 672.3288, 720.1330] +24-11-19 19:09:21 | D | best error = [ 9.8037, 9.8037, 9.8037, 9.8037, 9.8037] +24-11-19 19:09:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:09:21 | D | sum error = [ 765.6350, 821.3583, 880.9493, 945.2215, 1008.8914] +24-11-19 19:09:21 | D | best error = [ 9.8037, 9.8037, 9.8037, 9.8037, 9.8037] +24-11-19 19:09:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:09:21 | D | sum error = [ 1079.2379, 1151.5076, 1232.0266, 1322.6687, 1402.6974] +24-11-19 19:09:21 | D | best error = [ 9.8037, 9.8037, 9.8037, 9.8037, 9.8037] +24-11-19 19:09:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:09:21 | D | sum error = [ 1520.7745, 1622.2549, 1728.8515, 1834.4079, 1944.5400] +24-11-19 19:09:21 | D | best error = [ 9.8037, 9.8037, 9.8037, 9.8037, 9.8037] +24-11-19 19:09:21 | D | + error = [9.8037] +24-11-19 19:09:21 | D | - Calibrating model.layers.30.self_attn.v_proj.weight +24-11-19 19:09:21 | D | + w: sint8 +24-11-19 19:09:21 | D | + x: None +24-11-19 19:09:21 | D | + y: None +24-11-19 19:09:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:09:21 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:09:21 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:09:21 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:09:21 | D | - range ratio = [ 1.0000] +24-11-19 19:09:21 | D | sum error = [ 3.5825] +24-11-19 19:09:21 | D | best error = [ 3.5825] +24-11-19 19:09:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:09:22 | D | sum error = [ 3.5417, 3.5697, 3.5479, 3.5821, 3.7178] +24-11-19 19:09:22 | D | best error = [ 3.1899, 3.0589, 2.9835, 2.9485, 2.9285] +24-11-19 19:09:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:09:22 | D | sum error = [ 3.8244, 3.9140, 4.0929, 4.2656, 4.4554] +24-11-19 19:09:22 | D | best error = [ 2.9182, 2.9134, 2.9115, 2.9110, 2.9105] +24-11-19 19:09:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:09:22 | D | sum error = [ 4.7647, 5.0932, 5.3034, 5.7910, 6.1626] +24-11-19 19:09:22 | D | best error = [ 2.9105, 2.9105, 2.9105, 2.9105, 2.9105] +24-11-19 19:09:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:09:22 | D | sum error = [ 6.5851, 7.0687, 7.6120, 8.1761, 8.7579] +24-11-19 19:09:22 | D | best error = [ 2.9105, 2.9105, 2.9105, 2.9105, 2.9105] +24-11-19 19:09:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:09:22 | D | sum error = [ 9.4519, 10.0880, 10.7927, 11.5210, 12.3037] +24-11-19 19:09:22 | D | best error = [ 2.9105, 2.9105, 2.9105, 2.9105, 2.9105] +24-11-19 19:09:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:09:22 | D | sum error = [ 13.1820, 14.0473, 15.0000, 15.9816, 17.0098] +24-11-19 19:09:22 | D | best error = [ 2.9105, 2.9105, 2.9105, 2.9105, 2.9105] +24-11-19 19:09:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:09:22 | D | sum error = [ 18.0626, 19.1980, 20.3933, 21.5916, 22.9232] +24-11-19 19:09:22 | D | best error = [ 2.9105, 2.9105, 2.9105, 2.9105, 2.9105] +24-11-19 19:09:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:09:22 | D | sum error = [ 24.2765, 25.6700, 27.1605, 28.6846, 30.3052] +24-11-19 19:09:22 | D | best error = [ 2.9105, 2.9105, 2.9105, 2.9105, 2.9105] +24-11-19 19:09:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:09:22 | D | sum error = [ 32.0437, 33.8563, 35.7538, 37.6783, 39.7535] +24-11-19 19:09:22 | D | best error = [ 2.9105, 2.9105, 2.9105, 2.9105, 2.9105] +24-11-19 19:09:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:09:22 | D | sum error = [ 41.9466, 44.1776, 46.5500, 48.9896, 51.5445] +24-11-19 19:09:22 | D | best error = [ 2.9105, 2.9105, 2.9105, 2.9105, 2.9105] +24-11-19 19:09:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:09:22 | D | sum error = [ 54.1459, 56.9147, 59.8203, 62.8050, 65.8836] +24-11-19 19:09:22 | D | best error = [ 2.9105, 2.9105, 2.9105, 2.9105, 2.9105] +24-11-19 19:09:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:09:22 | D | sum error = [ 69.0579, 72.3476, 75.7315, 79.2642, 82.8962] +24-11-19 19:09:22 | D | best error = [ 2.9105, 2.9105, 2.9105, 2.9105, 2.9105] +24-11-19 19:09:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:09:22 | D | sum error = [ 86.6655, 90.5497, 94.5308, 98.6539, 102.8899] +24-11-19 19:09:22 | D | best error = [ 2.9105, 2.9105, 2.9105, 2.9105, 2.9105] +24-11-19 19:09:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:09:22 | D | sum error = [ 107.2633, 111.7830, 116.4404, 121.2640, 126.2140] +24-11-19 19:09:22 | D | best error = [ 2.9105, 2.9105, 2.9105, 2.9105, 2.9105] +24-11-19 19:09:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:09:22 | D | sum error = [ 131.2797, 136.5047, 141.8938, 147.4374, 153.1161] +24-11-19 19:09:22 | D | best error = [ 2.9105, 2.9105, 2.9105, 2.9105, 2.9105] +24-11-19 19:09:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:09:22 | D | sum error = [ 158.9551, 164.9306, 171.0578, 177.3129, 183.7109] +24-11-19 19:09:22 | D | best error = [ 2.9105, 2.9105, 2.9105, 2.9105, 2.9105] +24-11-19 19:09:22 | D | + error = [2.9105] +24-11-19 19:09:22 | D | - Calibrating model.layers.30.self_attn.o_proj.weight +24-11-19 19:09:22 | D | + w: sint8 +24-11-19 19:09:22 | D | + x: None +24-11-19 19:09:22 | D | + y: None +24-11-19 19:09:22 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:09:22 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:09:22 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:09:22 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:09:22 | D | - range ratio = [ 1.0000] +24-11-19 19:09:22 | D | sum error = [ 1.0639] +24-11-19 19:09:22 | D | best error = [ 1.0639] +24-11-19 19:09:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:09:22 | D | sum error = [ 1.0498, 1.0494, 1.0489, 1.0600, 1.0738] +24-11-19 19:09:22 | D | best error = [ 0.9748, 0.9388, 0.9175, 0.9044, 0.8956] +24-11-19 19:09:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:09:22 | D | sum error = [ 1.0876, 1.1213, 1.1578, 1.2033, 1.2539] +24-11-19 19:09:22 | D | best error = [ 0.8893, 0.8851, 0.8825, 0.8811, 0.8798] +24-11-19 19:09:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:09:22 | D | sum error = [ 1.3113, 1.3808, 1.4521, 1.5393, 1.6380] +24-11-19 19:09:22 | D | best error = [ 0.8788, 0.8783, 0.8779, 0.8776, 0.8775] +24-11-19 19:09:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:09:22 | D | sum error = [ 1.7340, 1.8443, 1.9600, 2.0890, 2.2236] +24-11-19 19:09:22 | D | best error = [ 0.8774, 0.8773, 0.8773, 0.8773, 0.8772] +24-11-19 19:09:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:09:22 | D | sum error = [ 2.3708, 2.5219, 2.6838, 2.8595, 3.0455] +24-11-19 19:09:22 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 19:09:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:09:22 | D | sum error = [ 3.2312, 3.4363, 3.6551, 3.8869, 4.1239] +24-11-19 19:09:22 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 19:09:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:09:22 | D | sum error = [ 4.3711, 4.6421, 4.9193, 5.2172, 5.5368] +24-11-19 19:09:22 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 19:09:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:09:22 | D | sum error = [ 5.8668, 6.2105, 6.5718, 6.9598, 7.3614] +24-11-19 19:09:22 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 19:09:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:09:22 | D | sum error = [ 7.7914, 8.2382, 8.7065, 9.2036, 9.7244] +24-11-19 19:09:22 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 19:09:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:09:22 | D | sum error = [ 10.2755, 10.8491, 11.4563, 12.0911, 12.7597] +24-11-19 19:09:22 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 19:09:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:09:22 | D | sum error = [ 13.4650, 14.2035, 14.9709, 15.7840, 16.6314] +24-11-19 19:09:22 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 19:09:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:09:22 | D | sum error = [ 17.5194, 18.4506, 19.4280, 20.4525, 21.5258] +24-11-19 19:09:22 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 19:09:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:09:22 | D | sum error = [ 22.6436, 23.8169, 25.0422, 26.3206, 27.6618] +24-11-19 19:09:22 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 19:09:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:09:22 | D | sum error = [ 29.0646, 30.5335, 32.0665, 33.6680, 35.3369] +24-11-19 19:09:22 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 19:09:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:09:22 | D | sum error = [ 37.0770, 38.8900, 40.7808, 42.7460, 44.7880] +24-11-19 19:09:22 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 19:09:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:09:22 | D | sum error = [ 46.9081, 49.1098, 51.3963, 53.7645, 56.2213] +24-11-19 19:09:22 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 19:09:22 | D | + error = [0.8772] +24-11-19 19:09:22 | D | - Calibrating model.layers.30.mlp.up_proj.weight +24-11-19 19:09:22 | D | + w: sint8 +24-11-19 19:09:22 | D | + x: None +24-11-19 19:09:22 | D | + y: None +24-11-19 19:09:22 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:09:22 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:09:22 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:09:23 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:09:23 | D | - range ratio = [ 1.0000] +24-11-19 19:09:23 | D | sum error = [ 10.3655] +24-11-19 19:09:23 | D | best error = [ 10.3655] +24-11-19 19:09:24 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:09:24 | D | sum error = [ 10.3162, 10.2792, 10.3300, 10.4655, 10.6406] +24-11-19 19:09:24 | D | best error = [ 9.1123, 8.6780, 8.4643, 8.3496, 8.2898] +24-11-19 19:09:24 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:09:24 | D | sum error = [ 10.9358, 11.2734, 11.7294, 12.2770, 12.9659] +24-11-19 19:09:24 | D | best error = [ 8.2581, 8.2418, 8.2353, 8.2327, 8.2320] +24-11-19 19:09:24 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:09:24 | D | sum error = [ 13.7147, 14.5797, 15.5507, 16.5545, 17.7348] +24-11-19 19:09:24 | D | best error = [ 8.2318, 8.2317, 8.2317, 8.2317, 8.2317] +24-11-19 19:09:24 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:09:24 | D | sum error = [ 19.0013, 20.3820, 21.8205, 23.4444, 25.1543] +24-11-19 19:09:24 | D | best error = [ 8.2317, 8.2317, 8.2317, 8.2317, 8.2317] +24-11-19 19:09:24 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:09:24 | D | sum error = [ 26.9488, 28.8908, 30.9654, 33.1901, 35.5047] +24-11-19 19:09:24 | D | best error = [ 8.2317, 8.2317, 8.2317, 8.2317, 8.2317] +24-11-19 19:09:24 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:09:24 | D | sum error = [ 38.0191, 40.6584, 43.4851, 46.4262, 49.6119] +24-11-19 19:09:24 | D | best error = [ 8.2317, 8.2317, 8.2317, 8.2317, 8.2317] +24-11-19 19:09:24 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:09:24 | D | sum error = [ 52.9823, 56.5454, 60.2913, 64.2424, 68.4842] +24-11-19 19:09:24 | D | best error = [ 8.2317, 8.2317, 8.2317, 8.2317, 8.2317] +24-11-19 19:09:24 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:09:24 | D | sum error = [ 72.9060, 77.6140, 82.5705, 87.7569, 93.2643] +24-11-19 19:09:24 | D | best error = [ 8.2317, 8.2317, 8.2317, 8.2317, 8.2317] +24-11-19 19:09:24 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:09:24 | D | sum error = [ 99.0845, 105.2075, 111.6642, 118.5010, 125.6700] +24-11-19 19:09:24 | D | best error = [ 8.2317, 8.2317, 8.2317, 8.2317, 8.2317] +24-11-19 19:09:24 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:09:24 | D | sum error = [ 133.2531, 141.2984, 149.7410, 158.6689, 168.0438] +24-11-19 19:09:24 | D | best error = [ 8.2317, 8.2317, 8.2317, 8.2317, 8.2317] +24-11-19 19:09:24 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:09:24 | D | sum error = [ 177.8893, 188.2614, 199.1553, 210.5512, 222.5567] +24-11-19 19:09:24 | D | best error = [ 8.2317, 8.2317, 8.2317, 8.2317, 8.2317] +24-11-19 19:09:24 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:09:24 | D | sum error = [ 235.1491, 248.3527, 262.1722, 276.7057, 291.9785] +24-11-19 19:09:24 | D | best error = [ 8.2317, 8.2317, 8.2317, 8.2317, 8.2317] +24-11-19 19:09:24 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:09:24 | D | sum error = [ 307.9111, 324.5923, 341.9905, 360.2118, 379.1598] +24-11-19 19:09:24 | D | best error = [ 8.2317, 8.2317, 8.2317, 8.2317, 8.2317] +24-11-19 19:09:24 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:09:24 | D | sum error = [ 398.9841, 419.6592, 441.1907, 463.5997, 486.9053] +24-11-19 19:09:24 | D | best error = [ 8.2317, 8.2317, 8.2317, 8.2317, 8.2317] +24-11-19 19:09:24 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:09:24 | D | sum error = [ 511.0708, 536.1688, 562.1920, 589.1891, 617.0899] +24-11-19 19:09:24 | D | best error = [ 8.2317, 8.2317, 8.2317, 8.2317, 8.2317] +24-11-19 19:09:24 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:09:24 | D | sum error = [ 645.9234, 675.7436, 706.4973, 738.1995, 770.7982] +24-11-19 19:09:24 | D | best error = [ 8.2317, 8.2317, 8.2317, 8.2317, 8.2317] +24-11-19 19:09:24 | D | + error = [8.2317] +24-11-19 19:09:24 | D | - Calibrating model.layers.30.mlp.gate_proj.weight +24-11-19 19:09:24 | D | + w: sint8 +24-11-19 19:09:24 | D | + x: None +24-11-19 19:09:24 | D | + y: None +24-11-19 19:09:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:09:24 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:09:24 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:09:24 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:09:24 | D | - range ratio = [ 1.0000] +24-11-19 19:09:24 | D | sum error = [ 13.2767] +24-11-19 19:09:24 | D | best error = [ 13.2767] +24-11-19 19:09:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:09:25 | D | sum error = [ 13.2005, 13.1615, 13.2530, 13.3747, 13.5832] +24-11-19 19:09:25 | D | best error = [ 11.6504, 11.1163, 10.8487, 10.6983, 10.6183] +24-11-19 19:09:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:09:25 | D | sum error = [ 14.0231, 14.4815, 15.0496, 15.7266, 16.6068] +24-11-19 19:09:25 | D | best error = [ 10.5770, 10.5569, 10.5490, 10.5459, 10.5443] +24-11-19 19:09:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:09:25 | D | sum error = [ 17.5893, 18.6762, 19.9724, 21.3865, 22.7309] +24-11-19 19:09:25 | D | best error = [ 10.5442, 10.5441, 10.5440, 10.5440, 10.5440] +24-11-19 19:09:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:09:25 | D | sum error = [ 24.4163, 26.1992, 28.2111, 30.2669, 32.4597] +24-11-19 19:09:25 | D | best error = [ 10.5440, 10.5440, 10.5440, 10.5440, 10.5440] +24-11-19 19:09:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:09:25 | D | sum error = [ 34.9232, 37.5047, 40.1968, 43.1802, 46.2323] +24-11-19 19:09:25 | D | best error = [ 10.5440, 10.5440, 10.5440, 10.5440, 10.5440] +24-11-19 19:09:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:09:25 | D | sum error = [ 49.6221, 53.2019, 56.9149, 60.8902, 65.2028] +24-11-19 19:09:25 | D | best error = [ 10.5440, 10.5440, 10.5440, 10.5440, 10.5440] +24-11-19 19:09:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:09:25 | D | sum error = [ 69.7353, 74.4364, 79.6086, 84.9964, 90.7251] +24-11-19 19:09:25 | D | best error = [ 10.5440, 10.5440, 10.5440, 10.5440, 10.5440] +24-11-19 19:09:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:09:25 | D | sum error = [ 96.8712, 103.3776, 110.2338, 117.5403, 125.3656] +24-11-19 19:09:25 | D | best error = [ 10.5440, 10.5440, 10.5440, 10.5440, 10.5440] +24-11-19 19:09:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:09:25 | D | sum error = [ 133.5792, 142.3252, 151.5857, 161.4230, 171.8423] +24-11-19 19:09:25 | D | best error = [ 10.5440, 10.5440, 10.5440, 10.5440, 10.5440] +24-11-19 19:09:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:09:25 | D | sum error = [ 182.9198, 194.6332, 207.0423, 220.1492, 234.0209] +24-11-19 19:09:25 | D | best error = [ 10.5440, 10.5440, 10.5440, 10.5440, 10.5440] +24-11-19 19:09:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:09:25 | D | sum error = [ 248.7026, 264.1642, 280.5101, 297.7661, 315.9364] +24-11-19 19:09:25 | D | best error = [ 10.5440, 10.5440, 10.5440, 10.5440, 10.5440] +24-11-19 19:09:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:09:25 | D | sum error = [ 335.0877, 355.2670, 376.5482, 398.9215, 422.3825] +24-11-19 19:09:25 | D | best error = [ 10.5440, 10.5440, 10.5440, 10.5440, 10.5440] +24-11-19 19:09:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:09:25 | D | sum error = [ 447.0884, 473.0260, 500.2221, 528.7114, 558.4137] +24-11-19 19:09:25 | D | best error = [ 10.5440, 10.5440, 10.5440, 10.5440, 10.5440] +24-11-19 19:09:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:09:25 | D | sum error = [ 589.5638, 622.1045, 656.1028, 691.5853, 728.5268] +24-11-19 19:09:25 | D | best error = [ 10.5440, 10.5440, 10.5440, 10.5440, 10.5440] +24-11-19 19:09:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:09:25 | D | sum error = [ 766.9480, 806.8798, 848.4772, 891.5250, 936.1515] +24-11-19 19:09:25 | D | best error = [ 10.5440, 10.5440, 10.5440, 10.5440, 10.5440] +24-11-19 19:09:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:09:25 | D | sum error = [ 982.3259, 1030.0548, 1079.3474, 1130.0895, 1182.4395] +24-11-19 19:09:25 | D | best error = [ 10.5440, 10.5440, 10.5440, 10.5440, 10.5440] +24-11-19 19:09:25 | D | + error = [10.5440] +24-11-19 19:09:25 | D | - Calibrating model.layers.30.mlp.down_proj.weight +24-11-19 19:09:25 | D | + w: sint8 +24-11-19 19:09:25 | D | + x: None +24-11-19 19:09:25 | D | + y: None +24-11-19 19:09:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:09:25 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:09:25 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:09:25 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:09:26 | D | - range ratio = [ 1.0000] +24-11-19 19:09:26 | D | sum error = [ 3.9134] +24-11-19 19:09:26 | D | best error = [ 3.9134] +24-11-19 19:09:27 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:09:27 | D | sum error = [ 3.9153, 3.9556, 4.0141, 4.1526, 4.3184] +24-11-19 19:09:27 | D | best error = [ 3.5768, 3.4407, 3.3617, 3.3108, 3.2724] +24-11-19 19:09:27 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:09:27 | D | sum error = [ 4.5286, 4.7796, 5.0754, 5.3740, 5.7493] +24-11-19 19:09:27 | D | best error = [ 3.2404, 3.2121, 3.1886, 3.1690, 3.1514] +24-11-19 19:09:27 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:09:27 | D | sum error = [ 6.1247, 6.5423, 6.9782, 7.4276, 7.9268] +24-11-19 19:09:27 | D | best error = [ 3.1369, 3.1235, 3.1125, 3.1050, 3.0984] +24-11-19 19:09:27 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:09:27 | D | sum error = [ 8.4025, 8.9253, 9.4611, 10.0282, 10.6084] +24-11-19 19:09:27 | D | best error = [ 3.0929, 3.0874, 3.0841, 3.0813, 3.0790] +24-11-19 19:09:27 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:09:27 | D | sum error = [ 11.2060, 11.8250, 12.4663, 13.1163, 13.8031] +24-11-19 19:09:27 | D | best error = [ 3.0773, 3.0754, 3.0742, 3.0736, 3.0728] +24-11-19 19:09:27 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:09:27 | D | sum error = [ 14.4948, 15.2178, 15.9535, 16.7318, 17.5140] +24-11-19 19:09:27 | D | best error = [ 3.0726, 3.0725, 3.0723, 3.0722, 3.0722] +24-11-19 19:09:27 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:09:27 | D | sum error = [ 18.3442, 19.1846, 20.0554, 20.9593, 21.8938] +24-11-19 19:09:27 | D | best error = [ 3.0722, 3.0721, 3.0721, 3.0721, 3.0721] +24-11-19 19:09:27 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:09:27 | D | sum error = [ 22.8601, 23.8496, 24.8925, 25.9461, 27.0481] +24-11-19 19:09:27 | D | best error = [ 3.0720, 3.0720, 3.0720, 3.0720, 3.0720] +24-11-19 19:09:27 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:09:27 | D | sum error = [ 28.1881, 29.3775, 30.6133, 31.8918, 33.2316] +24-11-19 19:09:27 | D | best error = [ 3.0720, 3.0720, 3.0720, 3.0720, 3.0720] +24-11-19 19:09:27 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:09:27 | D | sum error = [ 34.6201, 36.0734, 37.5903, 39.1514, 40.7933] +24-11-19 19:09:27 | D | best error = [ 3.0720, 3.0720, 3.0720, 3.0720, 3.0720] +24-11-19 19:09:27 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:09:27 | D | sum error = [ 42.5229, 44.3251, 46.2123, 48.1991, 50.2725] +24-11-19 19:09:27 | D | best error = [ 3.0720, 3.0720, 3.0720, 3.0720, 3.0720] +24-11-19 19:09:27 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:09:27 | D | sum error = [ 52.4612, 54.7691, 57.2080, 59.7656, 62.4776] +24-11-19 19:09:27 | D | best error = [ 3.0720, 3.0720, 3.0720, 3.0720, 3.0720] +24-11-19 19:09:27 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:09:27 | D | sum error = [ 65.3322, 68.3389, 71.5073, 74.8673, 78.4063] +24-11-19 19:09:27 | D | best error = [ 3.0720, 3.0720, 3.0720, 3.0720, 3.0720] +24-11-19 19:09:27 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:09:27 | D | sum error = [ 82.1463, 86.0926, 90.2651, 94.6831, 99.3570] +24-11-19 19:09:27 | D | best error = [ 3.0720, 3.0720, 3.0720, 3.0720, 3.0720] +24-11-19 19:09:27 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:09:27 | D | sum error = [ 104.2895, 109.5086, 115.0308, 120.8776, 127.0717] +24-11-19 19:09:27 | D | best error = [ 3.0720, 3.0720, 3.0720, 3.0720, 3.0720] +24-11-19 19:09:27 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:09:27 | D | sum error = [ 133.6213, 140.5400, 147.8530, 155.5834, 163.7461] +24-11-19 19:09:27 | D | best error = [ 3.0720, 3.0720, 3.0720, 3.0720, 3.0720] +24-11-19 19:09:27 | D | + error = [3.0720] +24-11-19 19:09:27 | D | - Quantizing model.layers.30.self_attn.q_proj.weight +24-11-19 19:09:28 | D | - Quantizing model.layers.30.self_attn.k_proj.weight +24-11-19 19:09:28 | D | - Quantizing model.layers.30.self_attn.v_proj.weight +24-11-19 19:09:29 | D | - Quantizing model.layers.30.self_attn.o_proj.weight +24-11-19 19:09:30 | D | - Quantizing model.layers.30.mlp.up_proj.weight +24-11-19 19:09:31 | D | - Quantizing model.layers.30.mlp.gate_proj.weight +24-11-19 19:09:32 | D | - Quantizing model.layers.30.mlp.down_proj.weight +24-11-19 19:09:43 | D | - Quantizing layer model.layers.31 +24-11-19 19:09:43 | D | - Calibrating model.layers.31.self_attn.q_proj.weight +24-11-19 19:09:43 | D | + w: sint8 +24-11-19 19:09:43 | D | + x: None +24-11-19 19:09:43 | D | + y: None +24-11-19 19:09:43 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:09:43 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:09:43 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:09:43 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:09:43 | D | - range ratio = [ 1.0000] +24-11-19 19:09:43 | D | sum error = [ 8.8314] +24-11-19 19:09:43 | D | best error = [ 8.8314] +24-11-19 19:09:55 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:09:55 | D | sum error = [ 8.7699, 8.8430, 9.0934, 8.8364, 9.2608] +24-11-19 19:09:55 | D | best error = [ 8.7699, 8.7699, 8.7699, 8.7699, 8.7699] +24-11-19 19:09:55 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:09:55 | D | sum error = [ 9.4484, 9.7955, 10.1539, 10.5486, 11.7343] +24-11-19 19:09:55 | D | best error = [ 8.7699, 8.7699, 8.7699, 8.7699, 8.7699] +24-11-19 19:09:55 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:09:55 | D | sum error = [ 12.0824, 12.8048, 14.1212, 15.7775, 17.2639] +24-11-19 19:09:55 | D | best error = [ 8.7699, 8.7699, 8.7699, 8.7699, 8.7699] +24-11-19 19:09:55 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:09:55 | D | sum error = [ 17.4676, 19.0530, 20.5712, 22.6761, 24.0031] +24-11-19 19:09:55 | D | best error = [ 8.7699, 8.7699, 8.7699, 8.7699, 8.7699] +24-11-19 19:09:55 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:09:55 | D | sum error = [ 27.2168, 28.6698, 31.3077, 33.4831, 36.4049] +24-11-19 19:09:55 | D | best error = [ 8.7699, 8.7699, 8.7699, 8.7699, 8.7699] +24-11-19 19:09:55 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:09:55 | D | sum error = [ 39.2475, 42.4481, 45.9705, 49.7556, 53.0738] +24-11-19 19:09:55 | D | best error = [ 8.7699, 8.7699, 8.7699, 8.7699, 8.7699] +24-11-19 19:09:55 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:09:55 | D | sum error = [ 57.4674, 62.3952, 67.5511, 72.6061, 79.0494] +24-11-19 19:09:55 | D | best error = [ 8.7699, 8.7699, 8.7699, 8.7699, 8.7699] +24-11-19 19:09:55 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:09:55 | D | sum error = [ 85.5061, 92.4604, 99.2098, 107.1678, 115.5535] +24-11-19 19:09:55 | D | best error = [ 8.7699, 8.7699, 8.7699, 8.7699, 8.7699] +24-11-19 19:09:55 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:09:55 | D | sum error = [ 124.8772, 134.9853, 144.8954, 156.3523, 168.4174] +24-11-19 19:09:55 | D | best error = [ 8.7699, 8.7699, 8.7699, 8.7699, 8.7699] +24-11-19 19:09:55 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:09:55 | D | sum error = [ 181.1800, 195.1297, 210.1050, 226.3189, 244.1931] +24-11-19 19:09:55 | D | best error = [ 8.7699, 8.7699, 8.7699, 8.7699, 8.7699] +24-11-19 19:09:55 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:09:55 | D | sum error = [ 262.5695, 282.8912, 305.4093, 329.6389, 354.7517] +24-11-19 19:09:55 | D | best error = [ 8.7699, 8.7699, 8.7699, 8.7699, 8.7699] +24-11-19 19:09:55 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:09:55 | D | sum error = [ 382.8349, 412.8377, 444.9332, 480.6808, 518.3751] +24-11-19 19:09:55 | D | best error = [ 8.7699, 8.7699, 8.7699, 8.7699, 8.7699] +24-11-19 19:09:55 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:09:55 | D | sum error = [ 560.6180, 606.2276, 656.5339, 710.8461, 769.8616] +24-11-19 19:09:55 | D | best error = [ 8.7699, 8.7699, 8.7699, 8.7699, 8.7699] +24-11-19 19:09:55 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:09:55 | D | sum error = [ 833.9872, 903.9856, 981.0207, 1063.9918, 1154.8532] +24-11-19 19:09:55 | D | best error = [ 8.7699, 8.7699, 8.7699, 8.7699, 8.7699] +24-11-19 19:09:55 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:09:55 | D | sum error = [ 1253.7883, 1360.2833, 1476.6406, 1601.2074, 1735.2386] +24-11-19 19:09:55 | D | best error = [ 8.7699, 8.7699, 8.7699, 8.7699, 8.7699] +24-11-19 19:09:55 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:09:55 | D | sum error = [ 1878.4909, 2030.1969, 2188.8177, 2353.9561, 2524.1346] +24-11-19 19:09:55 | D | best error = [ 8.7699, 8.7699, 8.7699, 8.7699, 8.7699] +24-11-19 19:09:55 | D | + error = [8.7699] +24-11-19 19:09:55 | D | - Calibrating model.layers.31.self_attn.k_proj.weight +24-11-19 19:09:55 | D | + w: sint8 +24-11-19 19:09:55 | D | + x: None +24-11-19 19:09:55 | D | + y: None +24-11-19 19:09:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 19:09:55 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:09:55 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:09:55 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:09:55 | D | - range ratio = [ 1.0000] +24-11-19 19:09:55 | D | sum error = [ 9.8491] +24-11-19 19:09:55 | D | best error = [ 9.8491] +24-11-19 19:10:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:10:07 | D | sum error = [ 11.8001, 10.0953, 11.0830, 13.4700, 13.2318] +24-11-19 19:10:07 | D | best error = [ 9.8491, 9.8491, 9.8491, 9.8491, 9.8491] +24-11-19 19:10:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:10:07 | D | sum error = [ 11.8625, 10.8377, 11.3106, 12.2655, 12.7037] +24-11-19 19:10:07 | D | best error = [ 9.8491, 9.8491, 9.8491, 9.8491, 9.8491] +24-11-19 19:10:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:10:07 | D | sum error = [ 14.4710, 14.4051, 15.7906, 16.1109, 18.6970] +24-11-19 19:10:07 | D | best error = [ 9.8491, 9.8491, 9.8491, 9.8491, 9.8491] +24-11-19 19:10:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:10:07 | D | sum error = [ 19.6189, 21.6812, 23.6428, 23.3786, 25.4183] +24-11-19 19:10:07 | D | best error = [ 9.8491, 9.8491, 9.8491, 9.8491, 9.8491] +24-11-19 19:10:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:10:07 | D | sum error = [ 26.6220, 28.0517, 30.4672, 32.9542, 34.8987] +24-11-19 19:10:07 | D | best error = [ 9.8491, 9.8491, 9.8491, 9.8491, 9.8491] +24-11-19 19:10:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:10:07 | D | sum error = [ 37.9732, 39.9076, 43.1308, 46.2569, 50.7748] +24-11-19 19:10:07 | D | best error = [ 9.8491, 9.8491, 9.8491, 9.8491, 9.8491] +24-11-19 19:10:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:10:07 | D | sum error = [ 55.2007, 59.3304, 65.0175, 70.9173, 76.2727] +24-11-19 19:10:07 | D | best error = [ 9.8491, 9.8491, 9.8491, 9.8491, 9.8491] +24-11-19 19:10:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:10:07 | D | sum error = [ 82.4695, 91.2770, 98.7331, 108.2661, 118.8484] +24-11-19 19:10:07 | D | best error = [ 9.8491, 9.8491, 9.8491, 9.8491, 9.8491] +24-11-19 19:10:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:10:07 | D | sum error = [ 126.2168, 137.6872, 147.5332, 161.3072, 177.6123] +24-11-19 19:10:07 | D | best error = [ 9.8491, 9.8491, 9.8491, 9.8491, 9.8491] +24-11-19 19:10:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:10:07 | D | sum error = [ 193.0870, 206.7962, 224.3953, 242.9501, 264.0463] +24-11-19 19:10:07 | D | best error = [ 9.8491, 9.8491, 9.8491, 9.8491, 9.8491] +24-11-19 19:10:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:10:07 | D | sum error = [ 285.8099, 307.5516, 335.7821, 363.4315, 390.7343] +24-11-19 19:10:07 | D | best error = [ 9.8491, 9.8491, 9.8491, 9.8491, 9.8491] +24-11-19 19:10:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:10:07 | D | sum error = [ 422.6444, 461.7023, 495.8546, 532.5788, 572.4061] +24-11-19 19:10:07 | D | best error = [ 9.8491, 9.8491, 9.8491, 9.8491, 9.8491] +24-11-19 19:10:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:10:07 | D | sum error = [ 619.9053, 666.0255, 722.6596, 776.4119, 838.3588] +24-11-19 19:10:07 | D | best error = [ 9.8491, 9.8491, 9.8491, 9.8491, 9.8491] +24-11-19 19:10:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:10:07 | D | sum error = [ 907.3242, 979.6851, 1061.1517, 1158.5015, 1248.8620] +24-11-19 19:10:07 | D | best error = [ 9.8491, 9.8491, 9.8491, 9.8491, 9.8491] +24-11-19 19:10:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:10:07 | D | sum error = [ 1349.3814, 1454.6158, 1579.1192, 1711.7437, 1850.0066] +24-11-19 19:10:07 | D | best error = [ 9.8491, 9.8491, 9.8491, 9.8491, 9.8491] +24-11-19 19:10:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:10:07 | D | sum error = [ 1993.3826, 2138.2218, 2301.3497, 2458.9415, 2634.7603] +24-11-19 19:10:07 | D | best error = [ 9.8491, 9.8491, 9.8491, 9.8491, 9.8491] +24-11-19 19:10:07 | D | + error = [9.8491] +24-11-19 19:10:07 | D | - Calibrating model.layers.31.self_attn.v_proj.weight +24-11-19 19:10:07 | D | + w: sint8 +24-11-19 19:10:07 | D | + x: None +24-11-19 19:10:07 | D | + y: None +24-11-19 19:10:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:10:07 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:10:07 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:10:07 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:10:08 | D | - range ratio = [ 1.0000] +24-11-19 19:10:08 | D | sum error = [ 2.8085] +24-11-19 19:10:08 | D | best error = [ 2.8085] +24-11-19 19:10:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:10:08 | D | sum error = [ 2.7906, 2.8029, 2.8058, 2.8521, 2.8779] +24-11-19 19:10:08 | D | best error = [ 2.5454, 2.4521, 2.4063, 2.3815, 2.3665] +24-11-19 19:10:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:10:08 | D | sum error = [ 2.9983, 3.0659, 3.1913, 3.3455, 3.5051] +24-11-19 19:10:08 | D | best error = [ 2.3566, 2.3535, 2.3519, 2.3512, 2.3511] +24-11-19 19:10:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:10:08 | D | sum error = [ 3.6933, 3.9353, 4.1815, 4.4596, 4.7826] +24-11-19 19:10:08 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 19:10:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:10:08 | D | sum error = [ 5.0925, 5.4607, 5.8723, 6.2764, 6.7030] +24-11-19 19:10:08 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 19:10:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:10:08 | D | sum error = [ 7.1937, 7.7315, 8.2798, 8.8884, 9.5333] +24-11-19 19:10:08 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 19:10:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:10:08 | D | sum error = [ 10.1737, 10.9188, 11.6289, 12.4052, 13.2508] +24-11-19 19:10:08 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 19:10:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:10:08 | D | sum error = [ 14.1350, 15.1211, 16.0957, 17.1669, 18.2715] +24-11-19 19:10:08 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 19:10:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:10:08 | D | sum error = [ 19.5058, 20.7552, 22.0611, 23.4545, 24.8852] +24-11-19 19:10:08 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 19:10:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:10:08 | D | sum error = [ 26.4668, 28.0663, 29.7676, 31.5371, 33.4216] +24-11-19 19:10:08 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 19:10:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:10:08 | D | sum error = [ 35.3999, 37.4814, 39.6445, 41.9301, 44.3231] +24-11-19 19:10:08 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 19:10:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:10:08 | D | sum error = [ 46.8489, 49.5002, 52.2527, 55.1423, 58.1980] +24-11-19 19:10:08 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 19:10:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:10:08 | D | sum error = [ 61.3712, 64.7178, 68.2196, 71.8729, 75.7061] +24-11-19 19:10:08 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 19:10:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:10:08 | D | sum error = [ 79.6711, 83.8440, 88.1890, 92.7042, 97.4292] +24-11-19 19:10:08 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 19:10:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:10:08 | D | sum error = [ 102.3208, 107.4132, 112.7106, 118.2008, 123.9593] +24-11-19 19:10:08 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 19:10:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:10:08 | D | sum error = [ 129.9014, 136.1293, 142.5448, 149.1562, 156.0104] +24-11-19 19:10:08 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 19:10:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:10:08 | D | sum error = [ 163.0792, 170.3834, 177.8963, 185.6605, 193.6405] +24-11-19 19:10:08 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 19:10:08 | D | + error = [2.3511] +24-11-19 19:10:08 | D | - Calibrating model.layers.31.self_attn.o_proj.weight +24-11-19 19:10:08 | D | + w: sint8 +24-11-19 19:10:08 | D | + x: None +24-11-19 19:10:08 | D | + y: None +24-11-19 19:10:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:10:08 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:10:08 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:10:08 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:10:08 | D | - range ratio = [ 1.0000] +24-11-19 19:10:08 | D | sum error = [ 2.6015] +24-11-19 19:10:08 | D | best error = [ 2.6015] +24-11-19 19:10:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:10:08 | D | sum error = [ 2.5754, 2.5867, 2.5561, 2.5188, 2.5263] +24-11-19 19:10:08 | D | best error = [ 2.1181, 1.9664, 1.8784, 1.8242, 1.7876] +24-11-19 19:10:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:10:08 | D | sum error = [ 2.5289, 2.4783, 2.4945, 2.5074, 2.5374] +24-11-19 19:10:08 | D | best error = [ 1.7578, 1.7360, 1.7172, 1.7026, 1.6897] +24-11-19 19:10:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:10:08 | D | sum error = [ 2.5449, 2.5878, 2.6271, 2.6895, 2.7931] +24-11-19 19:10:08 | D | best error = [ 1.6812, 1.6725, 1.6634, 1.6586, 1.6532] +24-11-19 19:10:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:10:08 | D | sum error = [ 2.8535, 2.9251, 3.0685, 3.2171, 3.3344] +24-11-19 19:10:08 | D | best error = [ 1.6497, 1.6458, 1.6433, 1.6406, 1.6386] +24-11-19 19:10:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:10:08 | D | sum error = [ 3.5232, 3.7090, 3.9184, 4.1457, 4.4093] +24-11-19 19:10:08 | D | best error = [ 1.6371, 1.6357, 1.6342, 1.6335, 1.6328] +24-11-19 19:10:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:10:08 | D | sum error = [ 4.6464, 4.9635, 5.2858, 5.6253, 6.0084] +24-11-19 19:10:08 | D | best error = [ 1.6321, 1.6312, 1.6308, 1.6305, 1.6303] +24-11-19 19:10:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:10:08 | D | sum error = [ 6.3944, 6.8234, 7.2931, 7.7859, 8.2913] +24-11-19 19:10:08 | D | best error = [ 1.6301, 1.6300, 1.6300, 1.6299, 1.6299] +24-11-19 19:10:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:10:08 | D | sum error = [ 8.8826, 9.4942, 10.1226, 10.8567, 11.5835] +24-11-19 19:10:08 | D | best error = [ 1.6299, 1.6298, 1.6298, 1.6298, 1.6297] +24-11-19 19:10:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:10:08 | D | sum error = [ 12.3866, 13.2304, 14.1264, 15.0586, 16.0576] +24-11-19 19:10:08 | D | best error = [ 1.6297, 1.6296, 1.6296, 1.6296, 1.6296] +24-11-19 19:10:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:10:08 | D | sum error = [ 17.1420, 18.2810, 19.5016, 20.7781, 22.1364] +24-11-19 19:10:08 | D | best error = [ 1.6296, 1.6296, 1.6296, 1.6296, 1.6296] +24-11-19 19:10:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:10:08 | D | sum error = [ 23.5960, 25.1357, 26.7434, 28.4276, 30.2212] +24-11-19 19:10:08 | D | best error = [ 1.6296, 1.6296, 1.6296, 1.6296, 1.6296] +24-11-19 19:10:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:10:08 | D | sum error = [ 32.1155, 34.1183, 36.2316, 38.4776, 40.8358] +24-11-19 19:10:08 | D | best error = [ 1.6296, 1.6296, 1.6296, 1.6296, 1.6296] +24-11-19 19:10:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:10:08 | D | sum error = [ 43.3082, 45.8876, 48.6476, 51.5214, 54.5462] +24-11-19 19:10:08 | D | best error = [ 1.6296, 1.6296, 1.6296, 1.6296, 1.6296] +24-11-19 19:10:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:10:08 | D | sum error = [ 57.7060, 61.0178, 64.4872, 68.1402, 71.9545] +24-11-19 19:10:08 | D | best error = [ 1.6296, 1.6296, 1.6296, 1.6296, 1.6296] +24-11-19 19:10:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:10:08 | D | sum error = [ 75.9438, 80.1394, 84.4967, 89.0278, 93.7576] +24-11-19 19:10:08 | D | best error = [ 1.6296, 1.6296, 1.6296, 1.6296, 1.6296] +24-11-19 19:10:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:10:08 | D | sum error = [ 98.6816, 103.7994, 109.1175, 114.6273, 120.3704] +24-11-19 19:10:08 | D | best error = [ 1.6296, 1.6296, 1.6296, 1.6296, 1.6296] +24-11-19 19:10:08 | D | + error = [1.6296] +24-11-19 19:10:08 | D | - Calibrating model.layers.31.mlp.up_proj.weight +24-11-19 19:10:08 | D | + w: sint8 +24-11-19 19:10:08 | D | + x: None +24-11-19 19:10:08 | D | + y: None +24-11-19 19:10:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:10:08 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:10:08 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:10:09 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:10:09 | D | - range ratio = [ 1.0000] +24-11-19 19:10:09 | D | sum error = [ 9.9783] +24-11-19 19:10:09 | D | best error = [ 9.9783] +24-11-19 19:10:10 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:10:10 | D | sum error = [ 9.9424, 9.9147, 9.9320, 10.0528, 10.2351] +24-11-19 19:10:10 | D | best error = [ 8.8118, 8.3983, 8.2035, 8.0953, 8.0357] +24-11-19 19:10:10 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:10:10 | D | sum error = [ 10.4984, 10.8620, 11.3123, 11.8560, 12.5109] +24-11-19 19:10:10 | D | best error = [ 8.0030, 7.9871, 7.9811, 7.9791, 7.9783] +24-11-19 19:10:10 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:10:10 | D | sum error = [ 13.3098, 14.0729, 15.0804, 16.1354, 17.2848] +24-11-19 19:10:10 | D | best error = [ 7.9782, 7.9780, 7.9780, 7.9780, 7.9780] +24-11-19 19:10:10 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:10:10 | D | sum error = [ 18.6150, 19.9827, 21.4474, 23.0408, 24.7486] +24-11-19 19:10:10 | D | best error = [ 7.9780, 7.9780, 7.9780, 7.9780, 7.9780] +24-11-19 19:10:10 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:10:10 | D | sum error = [ 26.6398, 28.6494, 30.7326, 33.0280, 35.4949] +24-11-19 19:10:10 | D | best error = [ 7.9780, 7.9780, 7.9780, 7.9780, 7.9780] +24-11-19 19:10:10 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:10:10 | D | sum error = [ 38.1194, 40.9295, 43.8876, 47.1021, 50.5434] +24-11-19 19:10:10 | D | best error = [ 7.9780, 7.9780, 7.9780, 7.9780, 7.9780] +24-11-19 19:10:10 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:10:10 | D | sum error = [ 54.2126, 58.0408, 62.2240, 66.6763, 71.4143] +24-11-19 19:10:10 | D | best error = [ 7.9780, 7.9780, 7.9780, 7.9780, 7.9780] +24-11-19 19:10:10 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:10:10 | D | sum error = [ 76.4628, 81.8878, 87.6525, 93.8162, 100.3490] +24-11-19 19:10:10 | D | best error = [ 7.9780, 7.9780, 7.9780, 7.9780, 7.9780] +24-11-19 19:10:10 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:10:10 | D | sum error = [ 107.3218, 114.7822, 122.6969, 131.1413, 140.1114] +24-11-19 19:10:10 | D | best error = [ 7.9780, 7.9780, 7.9780, 7.9780, 7.9780] +24-11-19 19:10:10 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:10:10 | D | sum error = [ 149.7046, 159.9131, 170.8040, 182.3133, 194.5627] +24-11-19 19:10:10 | D | best error = [ 7.9780, 7.9780, 7.9780, 7.9780, 7.9780] +24-11-19 19:10:10 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:10:10 | D | sum error = [ 207.5544, 221.3191, 235.8506, 251.3458, 267.7362] +24-11-19 19:10:10 | D | best error = [ 7.9780, 7.9780, 7.9780, 7.9780, 7.9780] +24-11-19 19:10:10 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:10:10 | D | sum error = [ 285.0305, 303.2805, 322.5420, 342.8120, 364.1782] +24-11-19 19:10:10 | D | best error = [ 7.9780, 7.9780, 7.9780, 7.9780, 7.9780] +24-11-19 19:10:10 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:10:10 | D | sum error = [ 386.8140, 410.5498, 435.6189, 461.8549, 489.4759] +24-11-19 19:10:10 | D | best error = [ 7.9780, 7.9780, 7.9780, 7.9780, 7.9780] +24-11-19 19:10:10 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:10:10 | D | sum error = [ 518.3407, 548.5561, 580.0889, 613.0434, 647.4865] +24-11-19 19:10:10 | D | best error = [ 7.9780, 7.9780, 7.9780, 7.9780, 7.9780] +24-11-19 19:10:10 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:10:10 | D | sum error = [ 683.3234, 720.6703, 759.4627, 799.8410, 841.7168] +24-11-19 19:10:10 | D | best error = [ 7.9780, 7.9780, 7.9780, 7.9780, 7.9780] +24-11-19 19:10:10 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:10:10 | D | sum error = [ 885.0938, 929.9953, 976.4240, 1024.3623, 1073.7711] +24-11-19 19:10:10 | D | best error = [ 7.9780, 7.9780, 7.9780, 7.9780, 7.9780] +24-11-19 19:10:10 | D | + error = [7.9780] +24-11-19 19:10:10 | D | - Calibrating model.layers.31.mlp.gate_proj.weight +24-11-19 19:10:10 | D | + w: sint8 +24-11-19 19:10:10 | D | + x: None +24-11-19 19:10:10 | D | + y: None +24-11-19 19:10:10 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:10:10 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:10:10 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:10:10 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:10:10 | D | - range ratio = [ 1.0000] +24-11-19 19:10:10 | D | sum error = [ 12.5638] +24-11-19 19:10:10 | D | best error = [ 12.5638] +24-11-19 19:10:11 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:10:11 | D | sum error = [ 12.4318, 12.4505, 12.4922, 12.6182, 12.9064] +24-11-19 19:10:11 | D | best error = [ 11.0475, 10.5545, 10.3016, 10.1612, 10.0858] +24-11-19 19:10:11 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:10:11 | D | sum error = [ 13.2030, 13.5907, 14.2475, 15.0134, 15.7630] +24-11-19 19:10:11 | D | best error = [ 10.0471, 10.0264, 10.0189, 10.0157, 10.0143] +24-11-19 19:10:11 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:10:11 | D | sum error = [ 16.7036, 17.7760, 18.9998, 20.2861, 21.7089] +24-11-19 19:10:11 | D | best error = [ 10.0142, 10.0141, 10.0141, 10.0141, 10.0141] +24-11-19 19:10:11 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:10:11 | D | sum error = [ 23.3320, 25.0241, 26.7521, 28.8094, 30.9095] +24-11-19 19:10:11 | D | best error = [ 10.0141, 10.0141, 10.0141, 10.0141, 10.0141] +24-11-19 19:10:11 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:10:11 | D | sum error = [ 33.2214, 35.7615, 38.3682, 41.1761, 44.2519] +24-11-19 19:10:11 | D | best error = [ 10.0141, 10.0141, 10.0141, 10.0141, 10.0141] +24-11-19 19:10:11 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:10:11 | D | sum error = [ 47.4624, 50.9375, 54.6813, 58.6213, 62.8920] +24-11-19 19:10:11 | D | best error = [ 10.0141, 10.0141, 10.0141, 10.0141, 10.0141] +24-11-19 19:10:11 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:10:11 | D | sum error = [ 67.4828, 72.3928, 77.6052, 83.2018, 89.2029] +24-11-19 19:10:11 | D | best error = [ 10.0141, 10.0141, 10.0141, 10.0141, 10.0141] +24-11-19 19:10:11 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:10:11 | D | sum error = [ 95.6174, 102.4388, 109.7463, 117.5643, 125.9279] +24-11-19 19:10:11 | D | best error = [ 10.0141, 10.0141, 10.0141, 10.0141, 10.0141] +24-11-19 19:10:11 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:10:11 | D | sum error = [ 134.9334, 144.5651, 154.7651, 165.7986, 177.5448] +24-11-19 19:10:11 | D | best error = [ 10.0141, 10.0141, 10.0141, 10.0141, 10.0141] +24-11-19 19:10:11 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:10:11 | D | sum error = [ 190.0762, 203.4799, 217.7699, 233.0889, 249.4884] +24-11-19 19:10:11 | D | best error = [ 10.0141, 10.0141, 10.0141, 10.0141, 10.0141] +24-11-19 19:10:11 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:10:11 | D | sum error = [ 266.8724, 285.3947, 305.1885, 326.2155, 348.7294] +24-11-19 19:10:11 | D | best error = [ 10.0141, 10.0141, 10.0141, 10.0141, 10.0141] +24-11-19 19:10:11 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:10:11 | D | sum error = [ 372.4661, 397.7678, 424.6151, 453.1305, 483.3423] +24-11-19 19:10:11 | D | best error = [ 10.0141, 10.0141, 10.0141, 10.0141, 10.0141] +24-11-19 19:10:11 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:10:11 | D | sum error = [ 515.3654, 549.1500, 584.8031, 622.3630, 661.9483] +24-11-19 19:10:11 | D | best error = [ 10.0141, 10.0141, 10.0141, 10.0141, 10.0141] +24-11-19 19:10:11 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:10:11 | D | sum error = [ 703.5653, 747.2331, 793.0378, 841.0438, 891.1222] +24-11-19 19:10:11 | D | best error = [ 10.0141, 10.0141, 10.0141, 10.0141, 10.0141] +24-11-19 19:10:11 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:10:11 | D | sum error = [ 943.6325, 998.3685, 1055.4267, 1114.7847, 1176.6498] +24-11-19 19:10:11 | D | best error = [ 10.0141, 10.0141, 10.0141, 10.0141, 10.0141] +24-11-19 19:10:11 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:10:11 | D | sum error = [ 1240.8991, 1307.3818, 1376.4240, 1447.7860, 1521.5517] +24-11-19 19:10:11 | D | best error = [ 10.0141, 10.0141, 10.0141, 10.0141, 10.0141] +24-11-19 19:10:11 | D | + error = [10.0141] +24-11-19 19:10:11 | D | - Calibrating model.layers.31.mlp.down_proj.weight +24-11-19 19:10:11 | D | + w: sint8 +24-11-19 19:10:11 | D | + x: None +24-11-19 19:10:11 | D | + y: None +24-11-19 19:10:11 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 19:10:11 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 19:10:11 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 19:10:12 | D | + finished calculating the original outputs, ram usage: 12.3 +24-11-19 19:10:12 | D | - range ratio = [ 1.0000] +24-11-19 19:10:12 | D | sum error = [ 26.9078] +24-11-19 19:10:12 | D | best error = [ 26.9078] +24-11-19 19:10:13 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 19:10:13 | D | sum error = [ 26.5965, 26.5046, 25.8764, 26.1575, 25.6539] +24-11-19 19:10:13 | D | best error = [ 20.1250, 17.3405, 15.8857, 14.8830, 14.1901] +24-11-19 19:10:13 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 19:10:13 | D | sum error = [ 25.7848, 25.3535, 25.6093, 25.2613, 25.7577] +24-11-19 19:10:13 | D | best error = [ 13.6436, 13.1833, 12.7960, 12.4613, 12.1707] +24-11-19 19:10:13 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 19:10:13 | D | sum error = [ 26.1371, 26.4872, 27.3123, 28.0423, 28.8639] +24-11-19 19:10:13 | D | best error = [ 11.8980, 11.6842, 11.4551, 11.2479, 11.0611] +24-11-19 19:10:13 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 19:10:13 | D | sum error = [ 29.6404, 31.2483, 32.8311, 33.8544, 35.6501] +24-11-19 19:10:13 | D | best error = [ 10.9072, 10.7568, 10.6228, 10.5043, 10.3638] +24-11-19 19:10:13 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 19:10:13 | D | sum error = [ 37.7331, 39.3214, 41.7372, 44.7939, 47.1356] +24-11-19 19:10:13 | D | best error = [ 10.2318, 10.1244, 10.0102, 9.9060, 9.8041] +24-11-19 19:10:13 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 19:10:13 | D | sum error = [ 50.5735, 54.1990, 57.4562, 61.7173, 66.1717] +24-11-19 19:10:13 | D | best error = [ 9.7089, 9.6391, 9.5563, 9.4865, 9.4333] +24-11-19 19:10:13 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 19:10:13 | D | sum error = [ 70.8193, 75.8917, 81.1049, 87.2132, 93.7104] +24-11-19 19:10:13 | D | best error = [ 9.3755, 9.3366, 9.2989, 9.2673, 9.2251] +24-11-19 19:10:13 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 19:10:13 | D | sum error = [ 100.6549, 107.7815, 115.4381, 123.5708, 131.9708] +24-11-19 19:10:13 | D | best error = [ 9.1968, 9.1765, 9.1513, 9.1336, 9.1212] +24-11-19 19:10:13 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 19:10:13 | D | sum error = [ 141.2121, 150.8976, 161.0715, 171.8147, 183.2938] +24-11-19 19:10:13 | D | best error = [ 9.1078, 9.0994, 9.0937, 9.0863, 9.0746] +24-11-19 19:10:13 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 19:10:13 | D | sum error = [ 195.1580, 208.0146, 221.1707, 235.3207, 250.5710] +24-11-19 19:10:13 | D | best error = [ 9.0661, 9.0629, 9.0584, 9.0520, 9.0501] +24-11-19 19:10:13 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 19:10:13 | D | sum error = [ 266.5692, 283.6009, 302.1164, 321.4682, 342.1856] +24-11-19 19:10:13 | D | best error = [ 9.0472, 9.0437, 9.0425, 9.0410, 9.0371] +24-11-19 19:10:13 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 19:10:13 | D | sum error = [ 364.7345, 388.5908, 413.8399, 440.6608, 469.5161] +24-11-19 19:10:13 | D | best error = [ 9.0355, 9.0345, 9.0319, 9.0311, 9.0295] +24-11-19 19:10:13 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 19:10:13 | D | sum error = [ 499.9359, 532.0259, 565.8782, 601.7128, 639.7234] +24-11-19 19:10:13 | D | best error = [ 9.0283, 9.0282, 9.0282, 9.0282, 9.0282] +24-11-19 19:10:13 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 19:10:13 | D | sum error = [ 679.7435, 721.6736, 766.2445, 813.1200, 862.5583] +24-11-19 19:10:13 | D | best error = [ 9.0282, 9.0282, 9.0282, 9.0282, 9.0282] +24-11-19 19:10:13 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 19:10:13 | D | sum error = [ 914.4858, 969.3381, 1026.5717, 1086.4355, 1148.8717] +24-11-19 19:10:13 | D | best error = [ 9.0282, 9.0282, 9.0282, 9.0282, 9.0282] +24-11-19 19:10:13 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 19:10:13 | D | sum error = [ 1214.0555, 1281.9971, 1352.6952, 1426.1235, 1501.9487] +24-11-19 19:10:13 | D | best error = [ 9.0282, 9.0282, 9.0282, 9.0282, 9.0282] +24-11-19 19:10:13 | D | + error = [9.0282] +24-11-19 19:10:13 | D | - Quantizing model.layers.31.self_attn.q_proj.weight +24-11-19 19:10:14 | D | - Quantizing model.layers.31.self_attn.k_proj.weight +24-11-19 19:10:15 | D | - Quantizing model.layers.31.self_attn.v_proj.weight +24-11-19 19:10:16 | D | - Quantizing model.layers.31.self_attn.o_proj.weight +24-11-19 19:10:17 | D | - Quantizing model.layers.31.mlp.up_proj.weight +24-11-19 19:10:18 | D | - Quantizing model.layers.31.mlp.gate_proj.weight +24-11-19 19:10:19 | D | - Quantizing model.layers.31.mlp.down_proj.weight +24-11-19 19:10:23 | I | - Saving weight quantizer settings to runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt +24-11-19 19:10:23 | I | - Linking weight quantizer settings to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.183745.RUNNING/cache/wgts.pt +24-11-19 19:10:23 | I | * Quantizing activations +24-11-19 19:10:23 | I | - Generating activation quantizer settings +24-11-19 19:10:23 | D | Starting new HTTPS connection (7): huggingface.co:443 +24-11-19 19:10:29 | D | Starting new HTTPS connection (8): huggingface.co:443 +24-11-19 19:10:42 | D | Starting new HTTPS connection (3): s3.amazonaws.com:443 +24-11-19 19:10:54 | W | Repo card metadata block was not found. Setting CardData to empty. +24-11-19 19:10:54 | D | Starting new HTTPS connection (9): huggingface.co:443 +24-11-19 19:11:06 | W | Using the latest cached version of the dataset since mit-han-lab/pile-val-backup couldn't be found on the Hugging Face Hub +24-11-19 19:11:06 | W | Found the latest cached dataset configuration 'default' at /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4 (last modified on Tue Oct 8 18:58:39 2024). +24-11-19 19:11:06 | D | Attempting to acquire lock 23438703212688 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 19:11:06 | D | Lock 23438703212688 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 19:11:06 | D | open file: /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4/dataset_info.json +24-11-19 19:11:06 | D | Attempting to release lock 23438703212688 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 19:11:06 | D | Lock 23438703212688 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 19:11:19 | D | - Quantizing layer model.layers.0 +24-11-19 19:11:19 | D | - Calibrating model.layers.0.self_attn.v_proj.input +24-11-19 19:11:19 | D | - Calibrating model.layers.0.self_attn.k_rotary_emb.output +24-11-19 19:11:19 | D | + w: None +24-11-19 19:11:19 | D | + x: None +24-11-19 19:11:19 | D | + y: sint8 +24-11-19 19:11:19 | E | === Error === +24-11-19 19:11:19 | E | Traceback (most recent call last): +24-11-19 19:11:19 | E | File "/home/yujunlin/projects/deepcompressor/llm/deepcompressor/app/llm/ptq.py", line 384, in +24-11-19 19:11:19 | E | main(config, logging_level=tools.logging.DEBUG) +24-11-19 19:11:19 | E | File "/home/yujunlin/projects/deepcompressor/llm/deepcompressor/app/llm/ptq.py", line 352, in main +24-11-19 19:11:19 | E | model = ptq( +24-11-19 19:11:19 | E | ^^^^ +24-11-19 19:11:19 | E | File "/home/yujunlin/projects/deepcompressor/llm/deepcompressor/app/llm/ptq.py", line 290, in ptq +24-11-19 19:11:19 | E | quantizer_state_dict = quantize_llm_activations( +24-11-19 19:11:19 | E | ^^^^^^^^^^^^^^^^^^^^^^^^^ +24-11-19 19:11:19 | E | File "/home/yujunlin/miniconda3/envs/llm/lib/python3.12/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context +24-11-19 19:11:19 | E | return func(*args, **kwargs) +24-11-19 19:11:19 | E | ^^^^^^^^^^^^^^^^^^^^^ +24-11-19 19:11:19 | E | File "/home/yujunlin/projects/deepcompressor/llm/deepcompressor/app/llm/quant/activation.py", line 238, in quantize_llm_activations +24-11-19 19:11:19 | E | quantize_llm_layer_activations( +24-11-19 19:11:19 | E | File "/home/yujunlin/miniconda3/envs/llm/lib/python3.12/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context +24-11-19 19:11:19 | E | return func(*args, **kwargs) +24-11-19 19:11:19 | E | ^^^^^^^^^^^^^^^^^^^^^ +24-11-19 19:11:19 | E | File "/home/yujunlin/projects/deepcompressor/llm/deepcompressor/app/llm/quant/activation.py", line 153, in quantize_llm_layer_activations +24-11-19 19:11:19 | E | quantizer.calibrate_dynamic_range( +24-11-19 19:11:19 | E | File "/home/yujunlin/projects/deepcompressor/llm/deepcompressor/app/llm/quant/quantizer/quantizer.py", line 113, in calibrate_dynamic_range +24-11-19 19:11:19 | E | self.dynamic_range = calibrate_dynamic_range( +24-11-19 19:11:19 | E | ^^^^^^^^^^^^^^^^^^^^^^^^ +24-11-19 19:11:19 | E | File "/home/yujunlin/projects/deepcompressor/llm/deepcompressor/calib/range.py", line 395, in calibrate_dynamic_range +24-11-19 19:11:19 | E | ).calibrate( +24-11-19 19:11:19 | E | ^^^^^^^^^^ +24-11-19 19:11:19 | E | File "/home/yujunlin/projects/deepcompressor/llm/deepcompressor/calib/search.py", line 616, in calibrate +24-11-19 19:11:19 | E | ) = self._parse_args( +24-11-19 19:11:19 | E | ^^^^^^^^^^^^^^^^^ +24-11-19 19:11:19 | E | File "/home/yujunlin/projects/deepcompressor/llm/deepcompressor/calib/search.py", line 351, in _parse_args +24-11-19 19:11:19 | E | assert all( +24-11-19 19:11:19 | E | ^^^^ +24-11-19 19:11:19 | E | File "/home/yujunlin/projects/deepcompressor/llm/deepcompressor/calib/search.py", line 352, in +24-11-19 19:11:19 | E | p is w for (p, _), w in zip(orig_y_wgts, y_wgts, strict=True) +24-11-19 19:11:19 | E | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +24-11-19 19:11:19 | E | ValueError: zip() argument 2 is shorter than argument 1 +24-11-19 19:11:19 | E | diff --git a/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200545/run-241119.200545.log b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200545/run-241119.200545.log new file mode 100644 index 0000000000000000000000000000000000000000..a808ff21638c8182c0e283aa38b040c996928df1 --- /dev/null +++ b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200545/run-241119.200545.log @@ -0,0 +1,1323 @@ +24-11-19 20:05:45 | I | === Configurations === +24-11-19 20:05:45 | I | LlmPtqRunConfig( +24-11-19 20:05:45 | I | cache=LlmCacheConfig( +24-11-19 20:05:45 | I | root=runs/shang, +24-11-19 20:05:45 | I | dirpath=LlmQuantCacheConfig( +24-11-19 20:05:45 | I | rotation=runs/shang/llm/cache/quant/rotation/hadamard, +24-11-19 20:05:45 | I | reorder=, +24-11-19 20:05:45 | I | smooth=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2, +24-11-19 20:05:45 | I | wgts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[], +24-11-19 20:05:45 | I | acts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]), +24-11-19 20:05:45 | I | path=LlmQuantCacheConfig( +24-11-19 20:05:45 | I | rotation=runs/shang/llm/cache/quant/rotation/hadamard/llama-3-8b-instruct-gradient-1048k.pt, +24-11-19 20:05:45 | I | reorder=, +24-11-19 20:05:45 | I | smooth=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/llama-3-8b-instruct-gradient-1048k.pt, +24-11-19 20:05:45 | I | wgts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt, +24-11-19 20:05:45 | I | acts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt)), +24-11-19 20:05:45 | I | output=OutputConfig( +24-11-19 20:05:45 | I | root=runs/shang, +24-11-19 20:05:45 | I | dirname=skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0], +24-11-19 20:05:45 | I | job=run, +24-11-19 20:05:45 | I | dirpath=runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0], +24-11-19 20:05:45 | I | timestamp=241119.200545), +24-11-19 20:05:45 | I | model=LlmModelConfig( +24-11-19 20:05:45 | I | name=llama-3-8b-instruct-gradient-1048k, +24-11-19 20:05:45 | I | family=llama-3, +24-11-19 20:05:45 | I | path=/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k, +24-11-19 20:05:45 | I | root=, +24-11-19 20:05:45 | I | local_path=/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k, +24-11-19 20:05:45 | I | local_root=/home/yujunlin/models, +24-11-19 20:05:45 | I | size=8.0, +24-11-19 20:05:45 | I | variant=instruct-gradient-1048k, +24-11-19 20:05:45 | I | dtype=torch.float16, +24-11-19 20:05:45 | I | orig_dtype=torch.bfloat16), +24-11-19 20:05:45 | I | eval=LlmEvalConfig( +24-11-19 20:05:45 | I | num_gpus=1, +24-11-19 20:05:45 | I | batch_size=8, +24-11-19 20:05:45 | I | tasks=['wikitext'], +24-11-19 20:05:45 | I | max_seq_length=-4096, +24-11-19 20:05:45 | I | evaluators=['gptq']), +24-11-19 20:05:45 | I | quant=LlmQuantConfig( +24-11-19 20:05:45 | I | wgts=LlmWeightQuantizerConfig( +24-11-19 20:05:45 | I | dtype=sint8, +24-11-19 20:05:45 | I | zero_point=None, +24-11-19 20:05:45 | I | group_shapes=((1, -1, -1),), +24-11-19 20:05:45 | I | scale_dtypes=(torch.float16,), +24-11-19 20:05:45 | I | intermediate_dtypes=(), +24-11-19 20:05:45 | I | intermediate_levels=(), +24-11-19 20:05:45 | I | needs_dequant_saturation=False, +24-11-19 20:05:45 | I | skips=[], +24-11-19 20:05:45 | I | static=True, +24-11-19 20:05:45 | I | kernel_gptq=QuantGptqConfig( +24-11-19 20:05:45 | I | damp_percentage=0.01, +24-11-19 20:05:45 | I | block_size=128, +24-11-19 20:05:45 | I | num_inv_tries=250, +24-11-19 20:05:45 | I | hessian_block_size=512), +24-11-19 20:05:45 | I | calib_range=SkipBasedDynamicRangeCalibConfig( +24-11-19 20:05:45 | I | degree=2, +24-11-19 20:05:45 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 20:05:45 | I | strategy=SearchBasedCalibStrategy.GridSearch, +24-11-19 20:05:45 | I | granularity=SearchBasedCalibGranularity.Group, +24-11-19 20:05:45 | I | element_batch_size=64, +24-11-19 20:05:45 | I | sample_batch_size=-1, +24-11-19 20:05:45 | I | element_size=512, +24-11-19 20:05:45 | I | sample_size=-1, +24-11-19 20:05:45 | I | pre_reshape=True, +24-11-19 20:05:45 | I | outputs_device=cpu, +24-11-19 20:05:45 | I | ratio=1.0, +24-11-19 20:05:45 | I | max_shrink=0.2, +24-11-19 20:05:45 | I | max_expand=1.0, +24-11-19 20:05:45 | I | num_grids=80, +24-11-19 20:05:45 | I | allow_scale=False, +24-11-19 20:05:45 | I | skips=[])), +24-11-19 20:05:45 | I | ipts=LlmActivationQuantizerConfig( +24-11-19 20:05:45 | I | dtype=sint8, +24-11-19 20:05:45 | I | zero_point=None, +24-11-19 20:05:45 | I | group_shapes=((1, -1, -1),), +24-11-19 20:05:45 | I | scale_dtypes=(torch.float16,), +24-11-19 20:05:45 | I | intermediate_dtypes=(), +24-11-19 20:05:45 | I | intermediate_levels=(), +24-11-19 20:05:45 | I | needs_dequant_saturation=False, +24-11-19 20:05:45 | I | skips=[], +24-11-19 20:05:45 | I | static=False, +24-11-19 20:05:45 | I | kernel_gptq=None, +24-11-19 20:05:45 | I | calib_range=None), +24-11-19 20:05:45 | I | opts=LlmActivationQuantizerConfig( +24-11-19 20:05:45 | I | dtype=sint8, +24-11-19 20:05:45 | I | zero_point=None, +24-11-19 20:05:45 | I | group_shapes=((-1, -1, -1),), +24-11-19 20:05:45 | I | scale_dtypes=(torch.float16,), +24-11-19 20:05:45 | I | intermediate_dtypes=(), +24-11-19 20:05:45 | I | intermediate_levels=(), +24-11-19 20:05:45 | I | needs_dequant_saturation=False, +24-11-19 20:05:45 | I | skips=['attn_q'], +24-11-19 20:05:45 | I | static=True, +24-11-19 20:05:45 | I | kernel_gptq=None, +24-11-19 20:05:45 | I | calib_range=SkipBasedDynamicRangeCalibConfig( +24-11-19 20:05:45 | I | degree=2, +24-11-19 20:05:45 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 20:05:45 | I | strategy=SearchBasedCalibStrategy.Manual, +24-11-19 20:05:45 | I | granularity=SearchBasedCalibGranularity.Layer, +24-11-19 20:05:45 | I | element_batch_size=-1, +24-11-19 20:05:45 | I | sample_batch_size=-1, +24-11-19 20:05:45 | I | element_size=-1, +24-11-19 20:05:45 | I | sample_size=-1, +24-11-19 20:05:45 | I | pre_reshape=True, +24-11-19 20:05:45 | I | outputs_device=cpu, +24-11-19 20:05:45 | I | ratio=1.0, +24-11-19 20:05:45 | I | max_shrink=0.2, +24-11-19 20:05:45 | I | max_expand=1.0, +24-11-19 20:05:45 | I | num_grids=80, +24-11-19 20:05:45 | I | allow_scale=False, +24-11-19 20:05:45 | I | skips=[])), +24-11-19 20:05:45 | I | calib=LlmCalibDataLoaderConfig( +24-11-19 20:05:45 | I | data=pileval, +24-11-19 20:05:45 | I | num_samples=128, +24-11-19 20:05:45 | I | batch_size=1, +24-11-19 20:05:45 | I | path=mit-han-lab/pile-val-backup, +24-11-19 20:05:45 | I | seq_length=1024, +24-11-19 20:05:45 | I | min_seq_length=0, +24-11-19 20:05:45 | I | max_seq_length=0, +24-11-19 20:05:45 | I | local_path=), +24-11-19 20:05:45 | I | rotation=QuantRotationConfig( +24-11-19 20:05:45 | I | random=False, +24-11-19 20:05:45 | I | transforms=['out_proj']), +24-11-19 20:05:45 | I | reorder=None, +24-11-19 20:05:45 | I | smooth=SmoothTransfomerConfig( +24-11-19 20:05:45 | I | proj=None, +24-11-19 20:05:45 | I | attn=SmoothAttentionCalibConfig( +24-11-19 20:05:45 | I | degree=2, +24-11-19 20:05:45 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 20:05:45 | I | strategy=SearchBasedCalibStrategy.GridSearch, +24-11-19 20:05:45 | I | granularity=SearchBasedCalibGranularity.Layer, +24-11-19 20:05:45 | I | element_batch_size=-1, +24-11-19 20:05:45 | I | sample_batch_size=-1, +24-11-19 20:05:45 | I | element_size=-1, +24-11-19 20:05:45 | I | sample_size=-1, +24-11-19 20:05:45 | I | pre_reshape=True, +24-11-19 20:05:45 | I | outputs_device=cpu, +24-11-19 20:05:45 | I | allow_a_quant=True, +24-11-19 20:05:45 | I | allow_b_quant=True, +24-11-19 20:05:45 | I | spans=[(, )], +24-11-19 20:05:45 | I | a_spans=[], +24-11-19 20:05:45 | I | b_spans=[], +24-11-19 20:05:45 | I | alpha=0.5, +24-11-19 20:05:45 | I | beta=-2, +24-11-19 20:05:45 | I | num_grids=20, +24-11-19 20:05:45 | I | allow_low_rank=False)), +24-11-19 20:05:45 | I | develop_dtype=torch.float32), +24-11-19 20:05:45 | I | seed=12345, +24-11-19 20:05:45 | I | skip_eval=False, +24-11-19 20:05:45 | I | load_from=, +24-11-19 20:05:45 | I | save_model=true, +24-11-19 20:05:45 | I | copy_on_save=False) +24-11-19 20:05:45 | I | === Dumped Configurations === +24-11-19 20:05:45 | I | { 'cache': { 'path': { 'acts': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt', +24-11-19 20:05:45 | I | 'reorder': '', +24-11-19 20:05:45 | I | 'rotation': 'runs/shang/llm/cache/quant/rotation/hadamard/llama-3-8b-instruct-gradient-1048k.pt', +24-11-19 20:05:45 | I | 'smooth': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/llama-3-8b-instruct-gradient-1048k.pt', +24-11-19 20:05:45 | I | 'wgts': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt'}, +24-11-19 20:05:45 | I | 'root': 'runs/shang'}, +24-11-19 20:05:45 | I | 'copy_on_save': False, +24-11-19 20:05:45 | I | 'eval': {'batch_size': 8, 'evaluators': ['gptq'], 'max_seq_length': -4096, 'num_gpus': 1, 'tasks': ['wikitext']}, +24-11-19 20:05:45 | I | 'load_from': '', +24-11-19 20:05:45 | I | 'model': { 'dtype': 'torch.float16', +24-11-19 20:05:45 | I | 'family': 'llama-3', +24-11-19 20:05:45 | I | 'local_path': '/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k', +24-11-19 20:05:45 | I | 'local_root': '/home/yujunlin/models', +24-11-19 20:05:45 | I | 'name': 'llama-3-8b-instruct-gradient-1048k', +24-11-19 20:05:45 | I | 'path': '/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k', +24-11-19 20:05:45 | I | 'root': ''}, +24-11-19 20:05:45 | I | 'output': { 'dirname': 'skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]', +24-11-19 20:05:45 | I | 'job': 'run', +24-11-19 20:05:45 | I | 'root': 'runs/shang'}, +24-11-19 20:05:45 | I | 'quant': { 'calib': { 'data': 'pileval', +24-11-19 20:05:45 | I | 'local_path': '', +24-11-19 20:05:45 | I | 'max_seq_length': 0, +24-11-19 20:05:45 | I | 'min_seq_length': 0, +24-11-19 20:05:45 | I | 'num_samples': 128, +24-11-19 20:05:45 | I | 'path': 'mit-han-lab/pile-val-backup', +24-11-19 20:05:45 | I | 'seq_length': 1024}, +24-11-19 20:05:45 | I | 'develop_dtype': 'torch.float32', +24-11-19 20:05:45 | I | 'enable_reorder': False, +24-11-19 20:05:45 | I | 'enable_rotation': True, +24-11-19 20:05:45 | I | 'enable_smooth': True, +24-11-19 20:05:45 | I | 'ipts': { 'dtype': 'sint8', +24-11-19 20:05:45 | I | 'enable_calib_range': False, +24-11-19 20:05:45 | I | 'group_shapes': [[1, -1, -1]], +24-11-19 20:05:45 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 20:05:45 | I | 'skips': [], +24-11-19 20:05:45 | I | 'static': False, +24-11-19 20:05:45 | I | 'zero_point': None}, +24-11-19 20:05:45 | I | 'opts': { 'calib_range': { 'allow_scale': False, +24-11-19 20:05:45 | I | 'degree': 2, +24-11-19 20:05:45 | I | 'element_batch_size': -1, +24-11-19 20:05:45 | I | 'element_size': -1, +24-11-19 20:05:45 | I | 'granularity': 'Layer', +24-11-19 20:05:45 | I | 'max_expand': 1.0, +24-11-19 20:05:45 | I | 'max_shrink': 0.2, +24-11-19 20:05:45 | I | 'num_grids': 80, +24-11-19 20:05:45 | I | 'objective': 'OutputsError', +24-11-19 20:05:45 | I | 'outputs_device': 'cpu', +24-11-19 20:05:45 | I | 'pre_reshape': True, +24-11-19 20:05:45 | I | 'ratio': 1.0, +24-11-19 20:05:45 | I | 'sample_batch_size': -1, +24-11-19 20:05:45 | I | 'sample_size': -1, +24-11-19 20:05:45 | I | 'skips': [], +24-11-19 20:05:45 | I | 'strategy': 'Manual'}, +24-11-19 20:05:45 | I | 'dtype': 'sint8', +24-11-19 20:05:45 | I | 'enable_calib_range': True, +24-11-19 20:05:45 | I | 'group_shapes': [[-1, -1, -1]], +24-11-19 20:05:45 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 20:05:45 | I | 'skips': ['attn_q'], +24-11-19 20:05:45 | I | 'static': True, +24-11-19 20:05:45 | I | 'zero_point': None}, +24-11-19 20:05:45 | I | 'rotation': {'random': False, 'transforms': ['out_proj']}, +24-11-19 20:05:45 | I | 'smooth': { 'attn': { 'allow_a_quant': True, +24-11-19 20:05:45 | I | 'allow_b_quant': True, +24-11-19 20:05:45 | I | 'alpha': 0.5, +24-11-19 20:05:45 | I | 'beta': -2, +24-11-19 20:05:45 | I | 'degree': 2, +24-11-19 20:05:45 | I | 'num_grids': 20, +24-11-19 20:05:45 | I | 'outputs_device': 'cpu', +24-11-19 20:05:45 | I | 'sample_batch_size': -1, +24-11-19 20:05:45 | I | 'sample_size': -1, +24-11-19 20:05:45 | I | 'spans': [['AbsMax', 'AbsMax']], +24-11-19 20:05:45 | I | 'strategy': 'GridSearch'}, +24-11-19 20:05:45 | I | 'enable_attn': True, +24-11-19 20:05:45 | I | 'enable_proj': False}, +24-11-19 20:05:45 | I | 'wgts': { 'calib_range': { 'allow_scale': False, +24-11-19 20:05:45 | I | 'degree': 2, +24-11-19 20:05:45 | I | 'element_batch_size': 64, +24-11-19 20:05:45 | I | 'element_size': 512, +24-11-19 20:05:45 | I | 'granularity': 'Group', +24-11-19 20:05:45 | I | 'max_expand': 1.0, +24-11-19 20:05:45 | I | 'max_shrink': 0.2, +24-11-19 20:05:45 | I | 'num_grids': 80, +24-11-19 20:05:45 | I | 'objective': 'OutputsError', +24-11-19 20:05:45 | I | 'outputs_device': 'cpu', +24-11-19 20:05:45 | I | 'pre_reshape': True, +24-11-19 20:05:45 | I | 'ratio': 1.0, +24-11-19 20:05:45 | I | 'sample_batch_size': -1, +24-11-19 20:05:45 | I | 'sample_size': -1, +24-11-19 20:05:45 | I | 'skips': [], +24-11-19 20:05:45 | I | 'strategy': 'GridSearch'}, +24-11-19 20:05:45 | I | 'dtype': 'sint8', +24-11-19 20:05:45 | I | 'enable_calib_range': True, +24-11-19 20:05:45 | I | 'enable_kernel_gptq': True, +24-11-19 20:05:45 | I | 'group_shapes': [[1, -1, -1]], +24-11-19 20:05:45 | I | 'intermediate_dtypes': [], +24-11-19 20:05:45 | I | 'intermediate_levels': [], +24-11-19 20:05:45 | I | 'kernel_gptq': { 'block_size': 128, +24-11-19 20:05:45 | I | 'damp_percentage': 0.01, +24-11-19 20:05:45 | I | 'hessian_block_size': 512, +24-11-19 20:05:45 | I | 'num_inv_tries': 250}, +24-11-19 20:05:45 | I | 'needs_dequant_saturation': False, +24-11-19 20:05:45 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 20:05:45 | I | 'skips': [], +24-11-19 20:05:45 | I | 'zero_point': None}}, +24-11-19 20:05:45 | I | 'save_model': 'true', +24-11-19 20:05:45 | I | 'seed': 12345, +24-11-19 20:05:45 | I | 'skip_eval': False} +24-11-19 20:05:45 | I | === Output Directory === +24-11-19 20:05:45 | I | runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200545 +24-11-19 20:05:45 | I | === Start Evaluating === +24-11-19 20:05:45 | I | * Building model llama-3-8b-instruct-gradient-1048k from /home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k +24-11-19 20:05:46 | I | We will use 90% of the memory on device 0 for storing the model, and 10% for the buffer to avoid OOM. You can set `max_memory` in to a higher value to use more memory (at your own risk). +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.0.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.1.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.2.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.3.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.4.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.5.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.6.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.7.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.8.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.9.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.10.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.11.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.12.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.13.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.14.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.15.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.16.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.17.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.18.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.19.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.20.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.21.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.22.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.23.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.24.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.25.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.26.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.27.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.28.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.29.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.30.self_attn +24-11-19 20:05:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.31.self_attn +24-11-19 20:05:51 | I | * Rotating model +24-11-19 20:05:51 | I | - Loading rotation from runs/shang/llm/cache/quant/rotation/hadamard/llama-3-8b-instruct-gradient-1048k.pt +24-11-19 20:05:51 | D | - Transforming norm and linear in model.layers.0 +24-11-19 20:05:52 | D | - Transforming norm and linear in model.layers.1 +24-11-19 20:05:52 | D | - Transforming norm and linear in model.layers.2 +24-11-19 20:05:52 | D | - Transforming norm and linear in model.layers.3 +24-11-19 20:05:52 | D | - Transforming norm and linear in model.layers.4 +24-11-19 20:05:52 | D | - Transforming norm and linear in model.layers.5 +24-11-19 20:05:52 | D | - Transforming norm and linear in model.layers.6 +24-11-19 20:05:52 | D | - Transforming norm and linear in model.layers.7 +24-11-19 20:05:52 | D | - Transforming norm and linear in model.layers.8 +24-11-19 20:05:52 | D | - Transforming norm and linear in model.layers.9 +24-11-19 20:05:52 | D | - Transforming norm and linear in model.layers.10 +24-11-19 20:05:52 | D | - Transforming norm and linear in model.layers.11 +24-11-19 20:05:52 | D | - Transforming norm and linear in model.layers.12 +24-11-19 20:05:52 | D | - Transforming norm and linear in model.layers.13 +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.14 +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.15 +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.16 +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.17 +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.18 +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.19 +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.20 +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.21 +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.22 +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.23 +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.24 +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.25 +24-11-19 20:05:53 | D | - Transforming norm and linear in model.layers.26 +24-11-19 20:05:54 | D | - Transforming norm and linear in model.layers.27 +24-11-19 20:05:54 | D | - Transforming norm and linear in model.layers.28 +24-11-19 20:05:54 | D | - Transforming norm and linear in model.layers.29 +24-11-19 20:05:54 | D | - Transforming norm and linear in model.layers.30 +24-11-19 20:05:54 | D | - Transforming norm and linear in model.layers.31 +24-11-19 20:05:54 | D | - Transforming model.norm +24-11-19 20:05:54 | D | - Rotating model.embed_tokens +24-11-19 20:05:54 | D | - Rotating model.layers.0 +24-11-19 20:05:54 | D | - Rotating model.layers.0.self_attn.q_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.0.self_attn.k_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.0.self_attn.v_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.0.self_attn.o_proj (out) +24-11-19 20:05:54 | D | - Rotating model.layers.0.self_attn.v_proj (out) +24-11-19 20:05:54 | D | - Rotating model.layers.0.self_attn.o_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.0.mlp.up_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.0.mlp.gate_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.0.mlp.down_proj (out) +24-11-19 20:05:54 | D | - Rotating model.layers.1 +24-11-19 20:05:54 | D | - Rotating model.layers.1.self_attn.q_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.1.self_attn.k_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.1.self_attn.v_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.1.self_attn.o_proj (out) +24-11-19 20:05:54 | D | - Rotating model.layers.1.self_attn.v_proj (out) +24-11-19 20:05:54 | D | - Rotating model.layers.1.self_attn.o_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.1.mlp.up_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.1.mlp.gate_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.1.mlp.down_proj (out) +24-11-19 20:05:54 | D | - Rotating model.layers.2 +24-11-19 20:05:54 | D | - Rotating model.layers.2.self_attn.q_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.2.self_attn.k_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.2.self_attn.v_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.2.self_attn.o_proj (out) +24-11-19 20:05:54 | D | - Rotating model.layers.2.self_attn.v_proj (out) +24-11-19 20:05:54 | D | - Rotating model.layers.2.self_attn.o_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.2.mlp.up_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.2.mlp.gate_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.2.mlp.down_proj (out) +24-11-19 20:05:54 | D | - Rotating model.layers.3 +24-11-19 20:05:54 | D | - Rotating model.layers.3.self_attn.q_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.3.self_attn.k_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.3.self_attn.v_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.3.self_attn.o_proj (out) +24-11-19 20:05:54 | D | - Rotating model.layers.3.self_attn.v_proj (out) +24-11-19 20:05:54 | D | - Rotating model.layers.3.self_attn.o_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.3.mlp.up_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.3.mlp.gate_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.3.mlp.down_proj (out) +24-11-19 20:05:54 | D | - Rotating model.layers.4 +24-11-19 20:05:54 | D | - Rotating model.layers.4.self_attn.q_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.4.self_attn.k_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.4.self_attn.v_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.4.self_attn.o_proj (out) +24-11-19 20:05:54 | D | - Rotating model.layers.4.self_attn.v_proj (out) +24-11-19 20:05:54 | D | - Rotating model.layers.4.self_attn.o_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.4.mlp.up_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.4.mlp.gate_proj (in) +24-11-19 20:05:54 | D | - Rotating model.layers.4.mlp.down_proj (out) +24-11-19 20:05:54 | D | - Rotating model.layers.5 +24-11-19 20:05:54 | D | - Rotating model.layers.5.self_attn.q_proj (in) +24-11-19 20:05:54 | D | - 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Rotating model.layers.26 +24-11-19 20:05:56 | D | - Rotating model.layers.26.self_attn.q_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.26.self_attn.k_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.26.self_attn.v_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.26.self_attn.o_proj (out) +24-11-19 20:05:56 | D | - Rotating model.layers.26.self_attn.v_proj (out) +24-11-19 20:05:56 | D | - Rotating model.layers.26.self_attn.o_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.26.mlp.up_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.26.mlp.gate_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.26.mlp.down_proj (out) +24-11-19 20:05:56 | D | - Rotating model.layers.27 +24-11-19 20:05:56 | D | - Rotating model.layers.27.self_attn.q_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.27.self_attn.k_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.27.self_attn.v_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.27.self_attn.o_proj (out) +24-11-19 20:05:56 | D | - 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Rotating model.layers.29 +24-11-19 20:05:56 | D | - Rotating model.layers.29.self_attn.q_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.29.self_attn.k_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.29.self_attn.v_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.29.self_attn.o_proj (out) +24-11-19 20:05:56 | D | - Rotating model.layers.29.self_attn.v_proj (out) +24-11-19 20:05:56 | D | - Rotating model.layers.29.self_attn.o_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.29.mlp.up_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.29.mlp.gate_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.29.mlp.down_proj (out) +24-11-19 20:05:56 | D | - Rotating model.layers.30 +24-11-19 20:05:56 | D | - Rotating model.layers.30.self_attn.q_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.30.self_attn.k_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.30.self_attn.v_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.30.self_attn.o_proj (out) +24-11-19 20:05:56 | D | - Rotating model.layers.30.self_attn.v_proj (out) +24-11-19 20:05:56 | D | - Rotating model.layers.30.self_attn.o_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.30.mlp.up_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.30.mlp.gate_proj (in) +24-11-19 20:05:56 | D | - Rotating model.layers.30.mlp.down_proj (out) +24-11-19 20:05:57 | D | - Rotating model.layers.31 +24-11-19 20:05:57 | D | - Rotating model.layers.31.self_attn.q_proj (in) +24-11-19 20:05:57 | D | - Rotating model.layers.31.self_attn.k_proj (in) +24-11-19 20:05:57 | D | - Rotating model.layers.31.self_attn.v_proj (in) +24-11-19 20:05:57 | D | - Rotating model.layers.31.self_attn.o_proj (out) +24-11-19 20:05:57 | D | - Rotating model.layers.31.self_attn.v_proj (out) +24-11-19 20:05:57 | D | - Rotating model.layers.31.self_attn.o_proj (in) +24-11-19 20:05:57 | D | - Rotating model.layers.31.mlp.up_proj (in) +24-11-19 20:05:57 | D | - Rotating model.layers.31.mlp.gate_proj (in) +24-11-19 20:05:57 | D | - Rotating model.layers.31.mlp.down_proj (out) +24-11-19 20:05:57 | D | - Rotating lm_head (in) +24-11-19 20:05:57 | I | - Linking rotation to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200545.RUNNING/model/rotation.pt +24-11-19 20:05:57 | I | * Development dtype is torch.float32 +24-11-19 20:05:57 | I | * Smoothing model for quantization +24-11-19 20:05:57 | I | - Loading smooth scales from runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/llama-3-8b-instruct-gradient-1048k.pt +24-11-19 20:05:57 | D | - Smoothing model.layers.0 +24-11-19 20:05:57 | D | - model.layers.0.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.1 +24-11-19 20:05:57 | D | - model.layers.1.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.2 +24-11-19 20:05:57 | D | - model.layers.2.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.3 +24-11-19 20:05:57 | D | - model.layers.3.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.4 +24-11-19 20:05:57 | D | - model.layers.4.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.5 +24-11-19 20:05:57 | D | - model.layers.5.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.6 +24-11-19 20:05:57 | D | - model.layers.6.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.7 +24-11-19 20:05:57 | D | - model.layers.7.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.8 +24-11-19 20:05:57 | D | - model.layers.8.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.9 +24-11-19 20:05:57 | D | - model.layers.9.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.10 +24-11-19 20:05:57 | D | - model.layers.10.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.11 +24-11-19 20:05:57 | D | - model.layers.11.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.12 +24-11-19 20:05:57 | D | - model.layers.12.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.13 +24-11-19 20:05:57 | D | - model.layers.13.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.14 +24-11-19 20:05:57 | D | - model.layers.14.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.15 +24-11-19 20:05:57 | D | - model.layers.15.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.16 +24-11-19 20:05:57 | D | - model.layers.16.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.17 +24-11-19 20:05:57 | D | - model.layers.17.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.18 +24-11-19 20:05:57 | D | - model.layers.18.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.19 +24-11-19 20:05:57 | D | - model.layers.19.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.20 +24-11-19 20:05:57 | D | - model.layers.20.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.21 +24-11-19 20:05:57 | D | - model.layers.21.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.22 +24-11-19 20:05:57 | D | - model.layers.22.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.23 +24-11-19 20:05:57 | D | - model.layers.23.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.24 +24-11-19 20:05:57 | D | - model.layers.24.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.25 +24-11-19 20:05:57 | D | - model.layers.25.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.26 +24-11-19 20:05:57 | D | - model.layers.26.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.27 +24-11-19 20:05:57 | D | - model.layers.27.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.28 +24-11-19 20:05:57 | D | - model.layers.28.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.29 +24-11-19 20:05:57 | D | - model.layers.29.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.30 +24-11-19 20:05:57 | D | - model.layers.30.self_attn.attn_k +24-11-19 20:05:57 | D | - Smoothing model.layers.31 +24-11-19 20:05:57 | D | - model.layers.31.self_attn.attn_k +24-11-19 20:05:57 | I | - Linking smooth scales to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200545.RUNNING/model/smooth.pt +24-11-19 20:05:57 | I | * Quantizing weights +24-11-19 20:05:57 | I | - Loading weight quantizer settings from runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt +24-11-19 20:05:57 | D | Starting new HTTPS connection (1): huggingface.co:443 +24-11-19 20:06:07 | D | Starting new HTTPS connection (2): huggingface.co:443 +24-11-19 20:06:28 | D | Starting new HTTPS connection (1): s3.amazonaws.com:443 +24-11-19 20:06:49 | W | Repo card metadata block was not found. Setting CardData to empty. +24-11-19 20:06:49 | D | Starting new HTTPS connection (3): huggingface.co:443 +24-11-19 20:07:29 | W | Using the latest cached version of the dataset since mit-han-lab/pile-val-backup couldn't be found on the Hugging Face Hub +24-11-19 20:07:29 | W | Found the latest cached dataset configuration 'default' at /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4 (last modified on Tue Oct 8 18:58:39 2024). +24-11-19 20:07:29 | D | Attempting to acquire lock 23438945327040 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:07:29 | D | Lock 23438945327040 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:07:29 | D | open file: /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4/dataset_info.json +24-11-19 20:07:29 | D | Attempting to release lock 23438945327040 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:07:29 | D | Lock 23438945327040 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:07:49 | D | - Quantizing layer model.layers.0 +24-11-19 20:07:49 | D | - Quantizing model.layers.0.self_attn.q_proj.weight +24-11-19 20:07:50 | D | - Quantizing model.layers.0.self_attn.k_proj.weight +24-11-19 20:07:51 | D | - Quantizing model.layers.0.self_attn.v_proj.weight +24-11-19 20:07:52 | D | - Quantizing model.layers.0.self_attn.o_proj.weight +24-11-19 20:07:53 | D | - Quantizing model.layers.0.mlp.up_proj.weight +24-11-19 20:07:54 | D | - Quantizing model.layers.0.mlp.gate_proj.weight +24-11-19 20:07:55 | D | - Quantizing model.layers.0.mlp.down_proj.weight +24-11-19 20:08:05 | D | - Quantizing layer model.layers.1 +24-11-19 20:08:05 | D | - Quantizing model.layers.1.self_attn.q_proj.weight +24-11-19 20:08:06 | D | - Quantizing model.layers.1.self_attn.k_proj.weight +24-11-19 20:08:07 | D | - Quantizing model.layers.1.self_attn.v_proj.weight +24-11-19 20:08:07 | D | - Quantizing model.layers.1.self_attn.o_proj.weight +24-11-19 20:08:08 | D | - Quantizing model.layers.1.mlp.up_proj.weight +24-11-19 20:08:09 | D | - Quantizing model.layers.1.mlp.gate_proj.weight +24-11-19 20:08:10 | D | - Quantizing model.layers.1.mlp.down_proj.weight +24-11-19 20:08:21 | D | - Quantizing layer model.layers.2 +24-11-19 20:08:21 | D | - Quantizing model.layers.2.self_attn.q_proj.weight +24-11-19 20:08:22 | D | - Quantizing model.layers.2.self_attn.k_proj.weight +24-11-19 20:08:23 | D | - Quantizing model.layers.2.self_attn.v_proj.weight +24-11-19 20:08:24 | D | - Quantizing model.layers.2.self_attn.o_proj.weight +24-11-19 20:08:24 | D | - Quantizing model.layers.2.mlp.up_proj.weight +24-11-19 20:08:28 | D | - Quantizing model.layers.2.mlp.gate_proj.weight +24-11-19 20:08:30 | D | - Quantizing model.layers.2.mlp.down_proj.weight +24-11-19 20:08:40 | D | - Quantizing layer model.layers.3 +24-11-19 20:08:40 | D | - Quantizing model.layers.3.self_attn.q_proj.weight +24-11-19 20:08:43 | D | - Quantizing model.layers.3.self_attn.k_proj.weight +24-11-19 20:08:47 | D | - Quantizing model.layers.3.self_attn.v_proj.weight +24-11-19 20:08:50 | D | - Quantizing model.layers.3.self_attn.o_proj.weight +24-11-19 20:08:54 | D | - Quantizing model.layers.3.mlp.up_proj.weight +24-11-19 20:08:56 | D | - Quantizing model.layers.3.mlp.gate_proj.weight +24-11-19 20:08:57 | D | - Quantizing model.layers.3.mlp.down_proj.weight +24-11-19 20:09:07 | D | - Quantizing layer model.layers.4 +24-11-19 20:09:07 | D | - Quantizing model.layers.4.self_attn.q_proj.weight +24-11-19 20:09:10 | D | - Quantizing model.layers.4.self_attn.k_proj.weight +24-11-19 20:09:14 | D | - Quantizing model.layers.4.self_attn.v_proj.weight +24-11-19 20:09:14 | D | - Quantizing model.layers.4.self_attn.o_proj.weight +24-11-19 20:09:15 | D | - Quantizing model.layers.4.mlp.up_proj.weight +24-11-19 20:09:16 | D | - Quantizing model.layers.4.mlp.gate_proj.weight +24-11-19 20:09:17 | D | - Quantizing model.layers.4.mlp.down_proj.weight +24-11-19 20:09:27 | D | - Quantizing layer model.layers.5 +24-11-19 20:09:27 | D | - Quantizing model.layers.5.self_attn.q_proj.weight +24-11-19 20:09:28 | D | - Quantizing model.layers.5.self_attn.k_proj.weight +24-11-19 20:09:30 | D | - Quantizing model.layers.5.self_attn.v_proj.weight +24-11-19 20:09:33 | D | - Quantizing model.layers.5.self_attn.o_proj.weight +24-11-19 20:09:36 | D | - Quantizing model.layers.5.mlp.up_proj.weight +24-11-19 20:09:38 | D | - Quantizing model.layers.5.mlp.gate_proj.weight +24-11-19 20:09:39 | D | - Quantizing model.layers.5.mlp.down_proj.weight +24-11-19 20:09:50 | D | - Quantizing layer model.layers.6 +24-11-19 20:09:50 | D | - Quantizing model.layers.6.self_attn.q_proj.weight +24-11-19 20:09:52 | D | - Quantizing model.layers.6.self_attn.k_proj.weight +24-11-19 20:09:53 | D | - Quantizing model.layers.6.self_attn.v_proj.weight +24-11-19 20:09:56 | D | - Quantizing model.layers.6.self_attn.o_proj.weight +24-11-19 20:09:57 | D | - Quantizing model.layers.6.mlp.up_proj.weight +24-11-19 20:09:59 | D | - Quantizing model.layers.6.mlp.gate_proj.weight +24-11-19 20:10:00 | D | - Quantizing model.layers.6.mlp.down_proj.weight +24-11-19 20:10:11 | D | - Quantizing layer model.layers.7 +24-11-19 20:10:11 | D | - Quantizing model.layers.7.self_attn.q_proj.weight +24-11-19 20:10:12 | D | - Quantizing model.layers.7.self_attn.k_proj.weight +24-11-19 20:10:14 | D | - Quantizing model.layers.7.self_attn.v_proj.weight +24-11-19 20:10:15 | D | - Quantizing model.layers.7.self_attn.o_proj.weight +24-11-19 20:10:16 | D | - Quantizing model.layers.7.mlp.up_proj.weight +24-11-19 20:10:17 | D | - Quantizing model.layers.7.mlp.gate_proj.weight +24-11-19 20:10:18 | D | - Quantizing model.layers.7.mlp.down_proj.weight +24-11-19 20:10:28 | D | - Quantizing layer model.layers.8 +24-11-19 20:10:28 | D | - Quantizing model.layers.8.self_attn.q_proj.weight +24-11-19 20:10:29 | D | - Quantizing model.layers.8.self_attn.k_proj.weight +24-11-19 20:10:30 | D | - Quantizing model.layers.8.self_attn.v_proj.weight +24-11-19 20:10:31 | D | - Quantizing model.layers.8.self_attn.o_proj.weight +24-11-19 20:10:32 | D | - Quantizing model.layers.8.mlp.up_proj.weight +24-11-19 20:10:33 | D | - 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Quantizing model.layers.31.self_attn.o_proj.weight +24-11-19 20:17:25 | D | - Quantizing model.layers.31.mlp.up_proj.weight +24-11-19 20:17:26 | D | - Quantizing model.layers.31.mlp.gate_proj.weight +24-11-19 20:17:27 | D | - Quantizing model.layers.31.mlp.down_proj.weight +24-11-19 20:17:33 | I | - Linking weight quantizer settings to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200545.RUNNING/model/wgts.pt +24-11-19 20:17:33 | I | - Saving model checkpoint to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200545.RUNNING/model +24-11-19 20:17:59 | I | * Quantizing activations +24-11-19 20:17:59 | I | - Loading activation quantizer settings from runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.GridSearch.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.g20.bn2/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt +24-11-19 20:17:59 | D | - Quantizing layer model.layers.0 +24-11-19 20:17:59 | D | - Quantizing model.layers.0.self_attn.q_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.0.self_attn.k_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.0.self_attn.v_proj (inputs and outputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.0.self_attn.o_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.0.self_attn.k_rotary_emb (outputs) +24-11-19 20:17:59 | D | - 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Quantizing model.layers.24.mlp.gate_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.24.mlp.up_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.24.mlp.down_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing layer model.layers.25 +24-11-19 20:17:59 | D | - Quantizing model.layers.25.self_attn.q_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.25.self_attn.k_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.25.self_attn.v_proj (inputs and outputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.25.self_attn.o_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.25.self_attn.k_rotary_emb (outputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.25.mlp.gate_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.25.mlp.up_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.25.mlp.down_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing layer model.layers.26 +24-11-19 20:17:59 | D | - Quantizing model.layers.26.self_attn.q_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.26.self_attn.k_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.26.self_attn.v_proj (inputs and outputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.26.self_attn.o_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.26.self_attn.k_rotary_emb (outputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.26.mlp.gate_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.26.mlp.up_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.26.mlp.down_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing layer model.layers.27 +24-11-19 20:17:59 | D | - Quantizing model.layers.27.self_attn.q_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.27.self_attn.k_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.27.self_attn.v_proj (inputs and outputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.27.self_attn.o_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.27.self_attn.k_rotary_emb (outputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.27.mlp.gate_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.27.mlp.up_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.27.mlp.down_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing layer model.layers.28 +24-11-19 20:17:59 | D | - Quantizing model.layers.28.self_attn.q_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.28.self_attn.k_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.28.self_attn.v_proj (inputs and outputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.28.self_attn.o_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.28.self_attn.k_rotary_emb (outputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.28.mlp.gate_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.28.mlp.up_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.28.mlp.down_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing layer model.layers.29 +24-11-19 20:17:59 | D | - Quantizing model.layers.29.self_attn.q_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.29.self_attn.k_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.29.self_attn.v_proj (inputs and outputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.29.self_attn.o_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.29.self_attn.k_rotary_emb (outputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.29.mlp.gate_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.29.mlp.up_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.29.mlp.down_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing layer model.layers.30 +24-11-19 20:17:59 | D | - Quantizing model.layers.30.self_attn.q_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.30.self_attn.k_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.30.self_attn.v_proj (inputs and outputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.30.self_attn.o_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.30.self_attn.k_rotary_emb (outputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.30.mlp.gate_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.30.mlp.up_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.30.mlp.down_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing layer model.layers.31 +24-11-19 20:17:59 | D | - Quantizing model.layers.31.self_attn.q_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.31.self_attn.k_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.31.self_attn.v_proj (inputs and outputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.31.self_attn.o_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.31.self_attn.k_rotary_emb (outputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.31.mlp.gate_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.31.mlp.up_proj (inputs) +24-11-19 20:17:59 | D | - Quantizing model.layers.31.mlp.down_proj (inputs) +24-11-19 20:17:59 | I | - Linking activation quantizer settings to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200545.RUNNING/model/acts.pt +24-11-19 20:17:59 | I | * Evaluating model +24-11-19 20:17:59 | W | `pretrained` model kwarg is not of type `str`. Many other model arguments may be ignored. Please do not launch via accelerate or use `parallelize=True` if passing an existing model this way. +24-11-19 20:17:59 | I | Using model type 'default' +24-11-19 20:17:59 | W | Passed an already-initialized model through `pretrained`, assuming single-process call to evaluate() or custom distributed integration +24-11-19 20:17:59 | I | - Evaluator: gptq +24-11-19 20:17:59 | I | - Tasks: ['wikitext'] +24-11-19 20:17:59 | I | - Batch_size: 8 +24-11-19 20:17:59 | I | + Max_seq_length: 2048 +24-11-19 20:17:59 | D | Starting new HTTPS connection (4): huggingface.co:443 +24-11-19 20:18:05 | W | Using the latest cached version of the dataset since wikitext couldn't be found on the Hugging Face Hub +24-11-19 20:18:05 | W | Found the latest cached dataset configuration 'wikitext-2-raw-v1' at /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3 (last modified on Tue Oct 8 19:51:38 2024). +24-11-19 20:18:05 | D | Attempting to acquire lock 23438543032672 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:18:05 | D | Lock 23438543032672 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:18:05 | D | open file: /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3/dataset_info.json +24-11-19 20:18:05 | D | Attempting to release lock 23438543032672 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:18:05 | D | Lock 23438543032672 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:18:37 | I | - Results: +24-11-19 20:18:38 | I | | Task |Version| Metric |Value | |Stderr| +24-11-19 20:18:38 | I | |--------|------:|---------------|-----:|---|-----:| +24-11-19 20:18:38 | I | |wikitext| 1|word_perplexity|7.9897|± |7.9897| +24-11-19 20:18:38 | I | +24-11-19 20:18:38 | I | + Max_seq_length: 4096 +24-11-19 20:18:38 | D | Starting new HTTPS connection (5): huggingface.co:443 +24-11-19 20:18:44 | W | Using the latest cached version of the dataset since wikitext couldn't be found on the Hugging Face Hub +24-11-19 20:18:44 | W | Found the latest cached dataset configuration 'wikitext-2-raw-v1' at /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3 (last modified on Tue Oct 8 19:51:38 2024). +24-11-19 20:18:44 | D | Attempting to acquire lock 23438601893360 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:18:44 | D | Lock 23438601893360 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:18:44 | D | open file: /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3/dataset_info.json +24-11-19 20:18:44 | D | Attempting to release lock 23438601893360 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:18:44 | D | Lock 23438601893360 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:19:10 | I | - Results: +24-11-19 20:19:10 | I | | Task |Version| Metric |Value | |Stderr| +24-11-19 20:19:10 | I | |--------|------:|---------------|-----:|---|-----:| +24-11-19 20:19:10 | I | |wikitext| 1|word_perplexity|7.3967|± |7.3967| +24-11-19 20:19:10 | I | +24-11-19 20:19:10 | I | * Saving results to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.GridSearch.bn2.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200545 diff --git a/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200729/config-241119.200729.yaml b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200729/config-241119.200729.yaml new file mode 100644 index 0000000000000000000000000000000000000000..eb1e7697bf19809c12dcc333afe9b1e2765346c0 --- /dev/null +++ b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200729/config-241119.200729.yaml @@ -0,0 +1,146 @@ +cache: + root: runs/shang + path: + rotation: runs/shang/llm/cache/quant/rotation/hadamard/llama-3-8b-instruct-gradient-1048k.pt + reorder: '' + smooth: runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/llama-3-8b-instruct-gradient-1048k.pt + wgts: runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt + acts: runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt +output: + root: runs/shang + dirname: skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0] + job: run +model: + name: llama-3-8b-instruct-gradient-1048k + family: llama-3 + path: /home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k + root: '' + local_path: /home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k + local_root: /home/yujunlin/models + dtype: torch.float16 +eval: + num_gpus: 1 + batch_size: 8 + tasks: + - wikitext + max_seq_length: -4096 + evaluators: + - gptq +quant: + wgts: + dtype: sint8 + zero_point: null + group_shapes: + - - 1 + - -1 + - -1 + scale_dtypes: + - torch.float16 + intermediate_dtypes: [] + intermediate_levels: [] + needs_dequant_saturation: false + skips: [] + enable_kernel_gptq: true + kernel_gptq: + damp_percentage: 0.01 + block_size: 128 + num_inv_tries: 250 + hessian_block_size: 512 + enable_calib_range: true + calib_range: + degree: 2 + objective: OutputsError + strategy: GridSearch + granularity: Group + element_batch_size: 64 + sample_batch_size: -1 + element_size: 512 + sample_size: -1 + pre_reshape: true + outputs_device: cpu + ratio: 1.0 + max_shrink: 0.2 + max_expand: 1.0 + num_grids: 80 + allow_scale: false + skips: [] + ipts: + dtype: sint8 + zero_point: null + group_shapes: + - - 1 + - -1 + - -1 + scale_dtypes: + - torch.float16 + skips: [] + static: false + enable_calib_range: false + opts: + dtype: sint8 + zero_point: null + group_shapes: + - - -1 + - -1 + - -1 + scale_dtypes: + - torch.float16 + skips: + - attn_q + static: true + enable_calib_range: true + calib_range: + degree: 2 + objective: OutputsError + strategy: Manual + granularity: Layer + element_batch_size: -1 + sample_batch_size: -1 + element_size: -1 + sample_size: -1 + pre_reshape: true + outputs_device: cpu + ratio: 1.0 + max_shrink: 0.2 + max_expand: 1.0 + num_grids: 80 + allow_scale: false + skips: [] + calib: + data: pileval + num_samples: 128 + path: mit-han-lab/pile-val-backup + seq_length: 1024 + min_seq_length: 0 + max_seq_length: 0 + local_path: '' + enable_rotation: true + rotation: + random: false + transforms: + - out_proj + enable_reorder: false + enable_smooth: true + smooth: + enable_proj: false + enable_attn: true + attn: + degree: 2 + strategy: Manual + sample_batch_size: -1 + sample_size: -1 + outputs_device: cpu + allow_a_quant: true + allow_b_quant: true + spans: + - - AbsMax + - AbsMax + alpha: 0.5 + beta: 0 + num_grids: 20 + develop_dtype: torch.float32 +seed: 12345 +skip_eval: false +load_from: '' +save_model: 'true' +copy_on_save: false diff --git a/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200729/model/acts.pt b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200729/model/acts.pt new file mode 100644 index 0000000000000000000000000000000000000000..dbf436e0023eb84a21019d4c456d58db3af6ba10 --- /dev/null +++ b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200729/model/acts.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ac70125cfcf7096842127bff88c84a458b44f2fc66bf8fb1970940c922e9e805 +size 36034 diff --git 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@@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b399ac3cecb57039c93754780228596a35530dee066aee45312a98c3933a7f4b +size 5593150 diff --git a/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200729/results-241119.200729.json b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200729/results-241119.200729.json new file mode 100644 index 0000000000000000000000000000000000000000..a0916211550078fceb86346bb6a38b21a81d28b2 --- /dev/null +++ b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200729/results-241119.200729.json @@ -0,0 +1,32 @@ +{ + "gptq": { + "2048": { + "results": { + "wikitext": { + "word_perplexity": 7.989206018837591 + } + }, + "versions": { + "wikitext": 1 + }, + "config": { + "model": "llama-3-8b-instruct-gradient-1048k" + }, + "model": "llama-3-8b-instruct-gradient-1048k" + }, + "4096": { + "results": { + "wikitext": { + "word_perplexity": 7.399224506977849 + } + }, + "versions": { + "wikitext": 1 + }, + "config": { + "model": "llama-3-8b-instruct-gradient-1048k" + }, + "model": "llama-3-8b-instruct-gradient-1048k" + } + } +} \ No newline at end of file diff --git a/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200729/run-241119.200729.log b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200729/run-241119.200729.log new file mode 100644 index 0000000000000000000000000000000000000000..0a3a654890b7f4bf6e3b7434d6032f5bc7c6d6d9 --- /dev/null +++ b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200729/run-241119.200729.log @@ -0,0 +1,16166 @@ +24-11-19 20:07:29 | I | === Configurations === +24-11-19 20:07:29 | I | LlmPtqRunConfig( +24-11-19 20:07:29 | I | cache=LlmCacheConfig( +24-11-19 20:07:29 | I | root=runs/shang, +24-11-19 20:07:29 | I | dirpath=LlmQuantCacheConfig( +24-11-19 20:07:29 | I | rotation=runs/shang/llm/cache/quant/rotation/hadamard, +24-11-19 20:07:29 | I | reorder=, +24-11-19 20:07:29 | I | smooth=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0, +24-11-19 20:07:29 | I | wgts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[], +24-11-19 20:07:29 | I | acts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]), +24-11-19 20:07:29 | I | path=LlmQuantCacheConfig( +24-11-19 20:07:29 | I | rotation=runs/shang/llm/cache/quant/rotation/hadamard/llama-3-8b-instruct-gradient-1048k.pt, +24-11-19 20:07:29 | I | reorder=, +24-11-19 20:07:29 | I | smooth=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/llama-3-8b-instruct-gradient-1048k.pt, +24-11-19 20:07:29 | I | wgts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt, +24-11-19 20:07:29 | I | acts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt)), +24-11-19 20:07:29 | I | output=OutputConfig( +24-11-19 20:07:29 | I | root=runs/shang, +24-11-19 20:07:29 | I | dirname=skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0], +24-11-19 20:07:29 | I | job=run, +24-11-19 20:07:29 | I | dirpath=runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0], +24-11-19 20:07:29 | I | timestamp=241119.200729), +24-11-19 20:07:29 | I | model=LlmModelConfig( +24-11-19 20:07:29 | I | name=llama-3-8b-instruct-gradient-1048k, +24-11-19 20:07:29 | I | family=llama-3, +24-11-19 20:07:29 | I | path=/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k, +24-11-19 20:07:29 | I | root=, +24-11-19 20:07:29 | I | local_path=/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k, +24-11-19 20:07:29 | I | local_root=/home/yujunlin/models, +24-11-19 20:07:29 | I | size=8.0, +24-11-19 20:07:29 | I | variant=instruct-gradient-1048k, +24-11-19 20:07:29 | I | dtype=torch.float16, +24-11-19 20:07:29 | I | orig_dtype=torch.bfloat16), +24-11-19 20:07:29 | I | eval=LlmEvalConfig( +24-11-19 20:07:29 | I | num_gpus=1, +24-11-19 20:07:29 | I | batch_size=8, +24-11-19 20:07:29 | I | tasks=['wikitext'], +24-11-19 20:07:29 | I | max_seq_length=-4096, +24-11-19 20:07:29 | I | evaluators=['gptq']), +24-11-19 20:07:29 | I | quant=LlmQuantConfig( +24-11-19 20:07:29 | I | wgts=LlmWeightQuantizerConfig( +24-11-19 20:07:29 | I | dtype=sint8, +24-11-19 20:07:29 | I | zero_point=None, +24-11-19 20:07:29 | I | group_shapes=((1, -1, -1),), +24-11-19 20:07:29 | I | scale_dtypes=(torch.float16,), +24-11-19 20:07:29 | I | intermediate_dtypes=(), +24-11-19 20:07:29 | I | intermediate_levels=(), +24-11-19 20:07:29 | I | needs_dequant_saturation=False, +24-11-19 20:07:29 | I | skips=[], +24-11-19 20:07:29 | I | static=True, +24-11-19 20:07:29 | I | kernel_gptq=QuantGptqConfig( +24-11-19 20:07:29 | I | damp_percentage=0.01, +24-11-19 20:07:29 | I | block_size=128, +24-11-19 20:07:29 | I | num_inv_tries=250, +24-11-19 20:07:29 | I | hessian_block_size=512), +24-11-19 20:07:29 | I | calib_range=SkipBasedDynamicRangeCalibConfig( +24-11-19 20:07:29 | I | degree=2, +24-11-19 20:07:29 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 20:07:29 | I | strategy=SearchBasedCalibStrategy.GridSearch, +24-11-19 20:07:29 | I | granularity=SearchBasedCalibGranularity.Group, +24-11-19 20:07:29 | I | element_batch_size=64, +24-11-19 20:07:29 | I | sample_batch_size=-1, +24-11-19 20:07:29 | I | element_size=512, +24-11-19 20:07:29 | I | sample_size=-1, +24-11-19 20:07:29 | I | pre_reshape=True, +24-11-19 20:07:29 | I | outputs_device=cpu, +24-11-19 20:07:29 | I | ratio=1.0, +24-11-19 20:07:29 | I | max_shrink=0.2, +24-11-19 20:07:29 | I | max_expand=1.0, +24-11-19 20:07:29 | I | num_grids=80, +24-11-19 20:07:29 | I | allow_scale=False, +24-11-19 20:07:29 | I | skips=[])), +24-11-19 20:07:29 | I | ipts=LlmActivationQuantizerConfig( +24-11-19 20:07:29 | I | dtype=sint8, +24-11-19 20:07:29 | I | zero_point=None, +24-11-19 20:07:29 | I | group_shapes=((1, -1, -1),), +24-11-19 20:07:29 | I | scale_dtypes=(torch.float16,), +24-11-19 20:07:29 | I | intermediate_dtypes=(), +24-11-19 20:07:29 | I | intermediate_levels=(), +24-11-19 20:07:29 | I | needs_dequant_saturation=False, +24-11-19 20:07:29 | I | skips=[], +24-11-19 20:07:29 | I | static=False, +24-11-19 20:07:29 | I | kernel_gptq=None, +24-11-19 20:07:29 | I | calib_range=None), +24-11-19 20:07:29 | I | opts=LlmActivationQuantizerConfig( +24-11-19 20:07:29 | I | dtype=sint8, +24-11-19 20:07:29 | I | zero_point=None, +24-11-19 20:07:29 | I | group_shapes=((-1, -1, -1),), +24-11-19 20:07:29 | I | scale_dtypes=(torch.float16,), +24-11-19 20:07:29 | I | intermediate_dtypes=(), +24-11-19 20:07:29 | I | intermediate_levels=(), +24-11-19 20:07:29 | I | needs_dequant_saturation=False, +24-11-19 20:07:29 | I | skips=['attn_q'], +24-11-19 20:07:29 | I | static=True, +24-11-19 20:07:29 | I | kernel_gptq=None, +24-11-19 20:07:29 | I | calib_range=SkipBasedDynamicRangeCalibConfig( +24-11-19 20:07:29 | I | degree=2, +24-11-19 20:07:29 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 20:07:29 | I | strategy=SearchBasedCalibStrategy.Manual, +24-11-19 20:07:29 | I | granularity=SearchBasedCalibGranularity.Layer, +24-11-19 20:07:29 | I | element_batch_size=-1, +24-11-19 20:07:29 | I | sample_batch_size=-1, +24-11-19 20:07:29 | I | element_size=-1, +24-11-19 20:07:29 | I | sample_size=-1, +24-11-19 20:07:29 | I | pre_reshape=True, +24-11-19 20:07:29 | I | outputs_device=cpu, +24-11-19 20:07:29 | I | ratio=1.0, +24-11-19 20:07:29 | I | max_shrink=0.2, +24-11-19 20:07:29 | I | max_expand=1.0, +24-11-19 20:07:29 | I | num_grids=80, +24-11-19 20:07:29 | I | allow_scale=False, +24-11-19 20:07:29 | I | skips=[])), +24-11-19 20:07:29 | I | calib=LlmCalibDataLoaderConfig( +24-11-19 20:07:29 | I | data=pileval, +24-11-19 20:07:29 | I | num_samples=128, +24-11-19 20:07:29 | I | batch_size=1, +24-11-19 20:07:29 | I | path=mit-han-lab/pile-val-backup, +24-11-19 20:07:29 | I | seq_length=1024, +24-11-19 20:07:29 | I | min_seq_length=0, +24-11-19 20:07:29 | I | max_seq_length=0, +24-11-19 20:07:29 | I | local_path=), +24-11-19 20:07:29 | I | rotation=QuantRotationConfig( +24-11-19 20:07:29 | I | random=False, +24-11-19 20:07:29 | I | transforms=['out_proj']), +24-11-19 20:07:29 | I | reorder=None, +24-11-19 20:07:29 | I | smooth=SmoothTransfomerConfig( +24-11-19 20:07:29 | I | proj=None, +24-11-19 20:07:29 | I | attn=SmoothAttentionCalibConfig( +24-11-19 20:07:29 | I | degree=2, +24-11-19 20:07:29 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 20:07:29 | I | strategy=SearchBasedCalibStrategy.Manual, +24-11-19 20:07:29 | I | granularity=SearchBasedCalibGranularity.Layer, +24-11-19 20:07:29 | I | element_batch_size=-1, +24-11-19 20:07:29 | I | sample_batch_size=-1, +24-11-19 20:07:29 | I | element_size=-1, +24-11-19 20:07:29 | I | sample_size=-1, +24-11-19 20:07:29 | I | pre_reshape=True, +24-11-19 20:07:29 | I | outputs_device=cpu, +24-11-19 20:07:29 | I | allow_a_quant=True, +24-11-19 20:07:29 | I | allow_b_quant=True, +24-11-19 20:07:29 | I | spans=[(, )], +24-11-19 20:07:29 | I | a_spans=[], +24-11-19 20:07:29 | I | b_spans=[], +24-11-19 20:07:29 | I | alpha=0.5, +24-11-19 20:07:29 | I | beta=0, +24-11-19 20:07:29 | I | num_grids=20, +24-11-19 20:07:29 | I | allow_low_rank=False)), +24-11-19 20:07:29 | I | develop_dtype=torch.float32), +24-11-19 20:07:29 | I | seed=12345, +24-11-19 20:07:29 | I | skip_eval=False, +24-11-19 20:07:29 | I | load_from=, +24-11-19 20:07:29 | I | save_model=true, +24-11-19 20:07:29 | I | copy_on_save=False) +24-11-19 20:07:29 | I | === Dumped Configurations === +24-11-19 20:07:29 | I | { 'cache': { 'path': { 'acts': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt', +24-11-19 20:07:29 | I | 'reorder': '', +24-11-19 20:07:29 | I | 'rotation': 'runs/shang/llm/cache/quant/rotation/hadamard/llama-3-8b-instruct-gradient-1048k.pt', +24-11-19 20:07:29 | I | 'smooth': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/llama-3-8b-instruct-gradient-1048k.pt', +24-11-19 20:07:29 | I | 'wgts': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt'}, +24-11-19 20:07:29 | I | 'root': 'runs/shang'}, +24-11-19 20:07:29 | I | 'copy_on_save': False, +24-11-19 20:07:29 | I | 'eval': {'batch_size': 8, 'evaluators': ['gptq'], 'max_seq_length': -4096, 'num_gpus': 1, 'tasks': ['wikitext']}, +24-11-19 20:07:29 | I | 'load_from': '', +24-11-19 20:07:29 | I | 'model': { 'dtype': 'torch.float16', +24-11-19 20:07:29 | I | 'family': 'llama-3', +24-11-19 20:07:29 | I | 'local_path': '/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k', +24-11-19 20:07:29 | I | 'local_root': '/home/yujunlin/models', +24-11-19 20:07:29 | I | 'name': 'llama-3-8b-instruct-gradient-1048k', +24-11-19 20:07:29 | I | 'path': '/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k', +24-11-19 20:07:29 | I | 'root': ''}, +24-11-19 20:07:29 | I | 'output': { 'dirname': 'skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]', +24-11-19 20:07:29 | I | 'job': 'run', +24-11-19 20:07:29 | I | 'root': 'runs/shang'}, +24-11-19 20:07:29 | I | 'quant': { 'calib': { 'data': 'pileval', +24-11-19 20:07:29 | I | 'local_path': '', +24-11-19 20:07:29 | I | 'max_seq_length': 0, +24-11-19 20:07:29 | I | 'min_seq_length': 0, +24-11-19 20:07:29 | I | 'num_samples': 128, +24-11-19 20:07:29 | I | 'path': 'mit-han-lab/pile-val-backup', +24-11-19 20:07:29 | I | 'seq_length': 1024}, +24-11-19 20:07:29 | I | 'develop_dtype': 'torch.float32', +24-11-19 20:07:29 | I | 'enable_reorder': False, +24-11-19 20:07:29 | I | 'enable_rotation': True, +24-11-19 20:07:29 | I | 'enable_smooth': True, +24-11-19 20:07:29 | I | 'ipts': { 'dtype': 'sint8', +24-11-19 20:07:29 | I | 'enable_calib_range': False, +24-11-19 20:07:29 | I | 'group_shapes': [[1, -1, -1]], +24-11-19 20:07:29 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 20:07:29 | I | 'skips': [], +24-11-19 20:07:29 | I | 'static': False, +24-11-19 20:07:29 | I | 'zero_point': None}, +24-11-19 20:07:29 | I | 'opts': { 'calib_range': { 'allow_scale': False, +24-11-19 20:07:29 | I | 'degree': 2, +24-11-19 20:07:29 | I | 'element_batch_size': -1, +24-11-19 20:07:29 | I | 'element_size': -1, +24-11-19 20:07:29 | I | 'granularity': 'Layer', +24-11-19 20:07:29 | I | 'max_expand': 1.0, +24-11-19 20:07:29 | I | 'max_shrink': 0.2, +24-11-19 20:07:29 | I | 'num_grids': 80, +24-11-19 20:07:29 | I | 'objective': 'OutputsError', +24-11-19 20:07:29 | I | 'outputs_device': 'cpu', +24-11-19 20:07:29 | I | 'pre_reshape': True, +24-11-19 20:07:29 | I | 'ratio': 1.0, +24-11-19 20:07:29 | I | 'sample_batch_size': -1, +24-11-19 20:07:29 | I | 'sample_size': -1, +24-11-19 20:07:29 | I | 'skips': [], +24-11-19 20:07:29 | I | 'strategy': 'Manual'}, +24-11-19 20:07:29 | I | 'dtype': 'sint8', +24-11-19 20:07:29 | I | 'enable_calib_range': True, +24-11-19 20:07:29 | I | 'group_shapes': [[-1, -1, -1]], +24-11-19 20:07:29 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 20:07:29 | I | 'skips': ['attn_q'], +24-11-19 20:07:29 | I | 'static': True, +24-11-19 20:07:29 | I | 'zero_point': None}, +24-11-19 20:07:29 | I | 'rotation': {'random': False, 'transforms': ['out_proj']}, +24-11-19 20:07:29 | I | 'smooth': { 'attn': { 'allow_a_quant': True, +24-11-19 20:07:29 | I | 'allow_b_quant': True, +24-11-19 20:07:29 | I | 'alpha': 0.5, +24-11-19 20:07:29 | I | 'beta': 0, +24-11-19 20:07:29 | I | 'degree': 2, +24-11-19 20:07:29 | I | 'num_grids': 20, +24-11-19 20:07:29 | I | 'outputs_device': 'cpu', +24-11-19 20:07:29 | I | 'sample_batch_size': -1, +24-11-19 20:07:29 | I | 'sample_size': -1, +24-11-19 20:07:29 | I | 'spans': [['AbsMax', 'AbsMax']], +24-11-19 20:07:29 | I | 'strategy': 'Manual'}, +24-11-19 20:07:29 | I | 'enable_attn': True, +24-11-19 20:07:29 | I | 'enable_proj': False}, +24-11-19 20:07:29 | I | 'wgts': { 'calib_range': { 'allow_scale': False, +24-11-19 20:07:29 | I | 'degree': 2, +24-11-19 20:07:29 | I | 'element_batch_size': 64, +24-11-19 20:07:29 | I | 'element_size': 512, +24-11-19 20:07:29 | I | 'granularity': 'Group', +24-11-19 20:07:29 | I | 'max_expand': 1.0, +24-11-19 20:07:29 | I | 'max_shrink': 0.2, +24-11-19 20:07:29 | I | 'num_grids': 80, +24-11-19 20:07:29 | I | 'objective': 'OutputsError', +24-11-19 20:07:29 | I | 'outputs_device': 'cpu', +24-11-19 20:07:29 | I | 'pre_reshape': True, +24-11-19 20:07:29 | I | 'ratio': 1.0, +24-11-19 20:07:29 | I | 'sample_batch_size': -1, +24-11-19 20:07:29 | I | 'sample_size': -1, +24-11-19 20:07:29 | I | 'skips': [], +24-11-19 20:07:29 | I | 'strategy': 'GridSearch'}, +24-11-19 20:07:29 | I | 'dtype': 'sint8', +24-11-19 20:07:29 | I | 'enable_calib_range': True, +24-11-19 20:07:29 | I | 'enable_kernel_gptq': True, +24-11-19 20:07:29 | I | 'group_shapes': [[1, -1, -1]], +24-11-19 20:07:29 | I | 'intermediate_dtypes': [], +24-11-19 20:07:29 | I | 'intermediate_levels': [], +24-11-19 20:07:29 | I | 'kernel_gptq': { 'block_size': 128, +24-11-19 20:07:29 | I | 'damp_percentage': 0.01, +24-11-19 20:07:29 | I | 'hessian_block_size': 512, +24-11-19 20:07:29 | I | 'num_inv_tries': 250}, +24-11-19 20:07:29 | I | 'needs_dequant_saturation': False, +24-11-19 20:07:29 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 20:07:29 | I | 'skips': [], +24-11-19 20:07:29 | I | 'zero_point': None}}, +24-11-19 20:07:29 | I | 'save_model': 'true', +24-11-19 20:07:29 | I | 'seed': 12345, +24-11-19 20:07:29 | I | 'skip_eval': False} +24-11-19 20:07:29 | I | === Output Directory === +24-11-19 20:07:29 | I | runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200729 +24-11-19 20:07:29 | I | === Start Evaluating === +24-11-19 20:07:29 | I | * Building model llama-3-8b-instruct-gradient-1048k from /home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k +24-11-19 20:07:30 | I | We will use 90% of the memory on device 0 for storing the model, and 10% for the buffer to avoid OOM. You can set `max_memory` in to a higher value to use more memory (at your own risk). +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.0.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.1.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.2.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.3.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.4.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.5.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.6.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.7.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.8.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.9.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.10.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.11.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.12.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.13.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.14.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.15.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.16.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.17.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.18.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.19.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.20.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.21.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.22.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.23.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.24.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.25.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.26.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.27.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.28.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.29.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.30.self_attn +24-11-19 20:07:37 | I | - Patching LlamaSdpaAttention.forward in model.layers.31.self_attn +24-11-19 20:07:37 | I | * Rotating model +24-11-19 20:07:37 | I | - Loading rotation from runs/shang/llm/cache/quant/rotation/hadamard/llama-3-8b-instruct-gradient-1048k.pt +24-11-19 20:07:37 | D | - Transforming norm and linear in model.layers.0 +24-11-19 20:07:37 | D | - Transforming norm and linear in model.layers.1 +24-11-19 20:07:37 | D | - Transforming norm and linear in model.layers.2 +24-11-19 20:07:38 | D | - Transforming norm and linear in model.layers.3 +24-11-19 20:07:38 | D | - Transforming norm and linear in model.layers.4 +24-11-19 20:07:38 | D | - Transforming norm and linear in model.layers.5 +24-11-19 20:07:38 | D | - Transforming norm and linear in model.layers.6 +24-11-19 20:07:38 | D | - Transforming norm and linear in model.layers.7 +24-11-19 20:07:38 | D | - Transforming norm and linear in model.layers.8 +24-11-19 20:07:38 | D | - Transforming norm and linear in model.layers.9 +24-11-19 20:07:38 | D | - Transforming norm and linear in model.layers.10 +24-11-19 20:07:38 | D | - Transforming norm and linear in model.layers.11 +24-11-19 20:07:38 | D | - Transforming norm and linear in model.layers.12 +24-11-19 20:07:38 | D | - Transforming norm and linear in model.layers.13 +24-11-19 20:07:39 | D | - Transforming norm and linear in model.layers.14 +24-11-19 20:07:39 | D | - Transforming norm and linear in model.layers.15 +24-11-19 20:07:39 | D | - Transforming norm and linear in model.layers.16 +24-11-19 20:07:39 | D | - Transforming norm and linear in model.layers.17 +24-11-19 20:07:39 | D | - Transforming norm and linear in model.layers.18 +24-11-19 20:07:39 | D | - Transforming norm and linear in model.layers.19 +24-11-19 20:07:39 | D | - Transforming norm and linear in model.layers.20 +24-11-19 20:07:39 | D | - Transforming norm and linear in model.layers.21 +24-11-19 20:07:39 | D | - Transforming norm and linear in model.layers.22 +24-11-19 20:07:40 | D | - Transforming norm and linear in model.layers.23 +24-11-19 20:07:40 | D | - Transforming norm and linear in model.layers.24 +24-11-19 20:07:40 | D | - Transforming norm and linear in model.layers.25 +24-11-19 20:07:40 | D | - Transforming norm and linear in model.layers.26 +24-11-19 20:07:40 | D | - Transforming norm and linear in model.layers.27 +24-11-19 20:07:40 | D | - Transforming norm and linear in model.layers.28 +24-11-19 20:07:40 | D | - Transforming norm and linear in model.layers.29 +24-11-19 20:07:40 | D | - Transforming norm and linear in model.layers.30 +24-11-19 20:07:41 | D | - Transforming norm and linear in model.layers.31 +24-11-19 20:07:41 | D | - Transforming model.norm +24-11-19 20:07:41 | D | - Rotating model.embed_tokens +24-11-19 20:07:41 | D | - Rotating model.layers.0 +24-11-19 20:07:41 | D | - Rotating model.layers.0.self_attn.q_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.0.self_attn.k_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.0.self_attn.v_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.0.self_attn.o_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.0.self_attn.v_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.0.self_attn.o_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.0.mlp.up_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.0.mlp.gate_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.0.mlp.down_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.1 +24-11-19 20:07:41 | D | - Rotating model.layers.1.self_attn.q_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.1.self_attn.k_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.1.self_attn.v_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.1.self_attn.o_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.1.self_attn.v_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.1.self_attn.o_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.1.mlp.up_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.1.mlp.gate_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.1.mlp.down_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.2 +24-11-19 20:07:41 | D | - Rotating model.layers.2.self_attn.q_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.2.self_attn.k_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.2.self_attn.v_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.2.self_attn.o_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.2.self_attn.v_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.2.self_attn.o_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.2.mlp.up_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.2.mlp.gate_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.2.mlp.down_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.3 +24-11-19 20:07:41 | D | - Rotating model.layers.3.self_attn.q_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.3.self_attn.k_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.3.self_attn.v_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.3.self_attn.o_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.3.self_attn.v_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.3.self_attn.o_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.3.mlp.up_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.3.mlp.gate_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.3.mlp.down_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.4 +24-11-19 20:07:41 | D | - Rotating model.layers.4.self_attn.q_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.4.self_attn.k_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.4.self_attn.v_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.4.self_attn.o_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.4.self_attn.v_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.4.self_attn.o_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.4.mlp.up_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.4.mlp.gate_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.4.mlp.down_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.5 +24-11-19 20:07:41 | D | - Rotating model.layers.5.self_attn.q_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.5.self_attn.k_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.5.self_attn.v_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.5.self_attn.o_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.5.self_attn.v_proj (out) +24-11-19 20:07:41 | D | - Rotating model.layers.5.self_attn.o_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.5.mlp.up_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.5.mlp.gate_proj (in) +24-11-19 20:07:41 | D | - Rotating model.layers.5.mlp.down_proj (out) +24-11-19 20:07:42 | D | - Rotating model.layers.6 +24-11-19 20:07:42 | D | - Rotating model.layers.6.self_attn.q_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.6.self_attn.k_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.6.self_attn.v_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.6.self_attn.o_proj (out) +24-11-19 20:07:42 | D | - Rotating model.layers.6.self_attn.v_proj (out) +24-11-19 20:07:42 | D | - Rotating model.layers.6.self_attn.o_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.6.mlp.up_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.6.mlp.gate_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.6.mlp.down_proj (out) +24-11-19 20:07:42 | D | - Rotating model.layers.7 +24-11-19 20:07:42 | D | - Rotating model.layers.7.self_attn.q_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.7.self_attn.k_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.7.self_attn.v_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.7.self_attn.o_proj (out) +24-11-19 20:07:42 | D | - Rotating model.layers.7.self_attn.v_proj (out) +24-11-19 20:07:42 | D | - Rotating model.layers.7.self_attn.o_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.7.mlp.up_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.7.mlp.gate_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.7.mlp.down_proj (out) +24-11-19 20:07:42 | D | - Rotating model.layers.8 +24-11-19 20:07:42 | D | - Rotating model.layers.8.self_attn.q_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.8.self_attn.k_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.8.self_attn.v_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.8.self_attn.o_proj (out) +24-11-19 20:07:42 | D | - Rotating model.layers.8.self_attn.v_proj (out) +24-11-19 20:07:42 | D | - Rotating model.layers.8.self_attn.o_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.8.mlp.up_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.8.mlp.gate_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.8.mlp.down_proj (out) +24-11-19 20:07:42 | D | - Rotating model.layers.9 +24-11-19 20:07:42 | D | - Rotating model.layers.9.self_attn.q_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.9.self_attn.k_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.9.self_attn.v_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.9.self_attn.o_proj (out) +24-11-19 20:07:42 | D | - Rotating model.layers.9.self_attn.v_proj (out) +24-11-19 20:07:42 | D | - Rotating model.layers.9.self_attn.o_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.9.mlp.up_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.9.mlp.gate_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.9.mlp.down_proj (out) +24-11-19 20:07:42 | D | - Rotating model.layers.10 +24-11-19 20:07:42 | D | - Rotating model.layers.10.self_attn.q_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.10.self_attn.k_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.10.self_attn.v_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.10.self_attn.o_proj (out) +24-11-19 20:07:42 | D | - Rotating model.layers.10.self_attn.v_proj (out) +24-11-19 20:07:42 | D | - Rotating model.layers.10.self_attn.o_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.10.mlp.up_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.10.mlp.gate_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.10.mlp.down_proj (out) +24-11-19 20:07:42 | D | - Rotating model.layers.11 +24-11-19 20:07:42 | D | - Rotating model.layers.11.self_attn.q_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.11.self_attn.k_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.11.self_attn.v_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.11.self_attn.o_proj (out) +24-11-19 20:07:42 | D | - Rotating model.layers.11.self_attn.v_proj (out) +24-11-19 20:07:42 | D | - Rotating model.layers.11.self_attn.o_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.11.mlp.up_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.11.mlp.gate_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.11.mlp.down_proj (out) +24-11-19 20:07:42 | D | - Rotating model.layers.12 +24-11-19 20:07:42 | D | - Rotating model.layers.12.self_attn.q_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.12.self_attn.k_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.12.self_attn.v_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.12.self_attn.o_proj (out) +24-11-19 20:07:42 | D | - Rotating model.layers.12.self_attn.v_proj (out) +24-11-19 20:07:42 | D | - Rotating model.layers.12.self_attn.o_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.12.mlp.up_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.12.mlp.gate_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.12.mlp.down_proj (out) +24-11-19 20:07:42 | D | - Rotating model.layers.13 +24-11-19 20:07:42 | D | - Rotating model.layers.13.self_attn.q_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.13.self_attn.k_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.13.self_attn.v_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.13.self_attn.o_proj (out) +24-11-19 20:07:42 | D | - Rotating model.layers.13.self_attn.v_proj (out) +24-11-19 20:07:42 | D | - Rotating model.layers.13.self_attn.o_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.13.mlp.up_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.13.mlp.gate_proj (in) +24-11-19 20:07:42 | D | - Rotating model.layers.13.mlp.down_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.14 +24-11-19 20:07:43 | D | - Rotating model.layers.14.self_attn.q_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.14.self_attn.k_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.14.self_attn.v_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.14.self_attn.o_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.14.self_attn.v_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.14.self_attn.o_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.14.mlp.up_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.14.mlp.gate_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.14.mlp.down_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.15 +24-11-19 20:07:43 | D | - Rotating model.layers.15.self_attn.q_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.15.self_attn.k_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.15.self_attn.v_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.15.self_attn.o_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.15.self_attn.v_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.15.self_attn.o_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.15.mlp.up_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.15.mlp.gate_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.15.mlp.down_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.16 +24-11-19 20:07:43 | D | - Rotating model.layers.16.self_attn.q_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.16.self_attn.k_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.16.self_attn.v_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.16.self_attn.o_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.16.self_attn.v_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.16.self_attn.o_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.16.mlp.up_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.16.mlp.gate_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.16.mlp.down_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.17 +24-11-19 20:07:43 | D | - Rotating model.layers.17.self_attn.q_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.17.self_attn.k_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.17.self_attn.v_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.17.self_attn.o_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.17.self_attn.v_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.17.self_attn.o_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.17.mlp.up_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.17.mlp.gate_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.17.mlp.down_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.18 +24-11-19 20:07:43 | D | - Rotating model.layers.18.self_attn.q_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.18.self_attn.k_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.18.self_attn.v_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.18.self_attn.o_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.18.self_attn.v_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.18.self_attn.o_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.18.mlp.up_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.18.mlp.gate_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.18.mlp.down_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.19 +24-11-19 20:07:43 | D | - Rotating model.layers.19.self_attn.q_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.19.self_attn.k_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.19.self_attn.v_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.19.self_attn.o_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.19.self_attn.v_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.19.self_attn.o_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.19.mlp.up_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.19.mlp.gate_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.19.mlp.down_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.20 +24-11-19 20:07:43 | D | - Rotating model.layers.20.self_attn.q_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.20.self_attn.k_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.20.self_attn.v_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.20.self_attn.o_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.20.self_attn.v_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.20.self_attn.o_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.20.mlp.up_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.20.mlp.gate_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.20.mlp.down_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.21 +24-11-19 20:07:43 | D | - Rotating model.layers.21.self_attn.q_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.21.self_attn.k_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.21.self_attn.v_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.21.self_attn.o_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.21.self_attn.v_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.21.self_attn.o_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.21.mlp.up_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.21.mlp.gate_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.21.mlp.down_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.22 +24-11-19 20:07:43 | D | - Rotating model.layers.22.self_attn.q_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.22.self_attn.k_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.22.self_attn.v_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.22.self_attn.o_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.22.self_attn.v_proj (out) +24-11-19 20:07:43 | D | - Rotating model.layers.22.self_attn.o_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.22.mlp.up_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.22.mlp.gate_proj (in) +24-11-19 20:07:43 | D | - Rotating model.layers.22.mlp.down_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.23 +24-11-19 20:07:44 | D | - Rotating model.layers.23.self_attn.q_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.23.self_attn.k_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.23.self_attn.v_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.23.self_attn.o_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.23.self_attn.v_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.23.self_attn.o_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.23.mlp.up_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.23.mlp.gate_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.23.mlp.down_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.24 +24-11-19 20:07:44 | D | - Rotating model.layers.24.self_attn.q_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.24.self_attn.k_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.24.self_attn.v_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.24.self_attn.o_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.24.self_attn.v_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.24.self_attn.o_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.24.mlp.up_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.24.mlp.gate_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.24.mlp.down_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.25 +24-11-19 20:07:44 | D | - Rotating model.layers.25.self_attn.q_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.25.self_attn.k_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.25.self_attn.v_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.25.self_attn.o_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.25.self_attn.v_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.25.self_attn.o_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.25.mlp.up_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.25.mlp.gate_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.25.mlp.down_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.26 +24-11-19 20:07:44 | D | - Rotating model.layers.26.self_attn.q_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.26.self_attn.k_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.26.self_attn.v_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.26.self_attn.o_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.26.self_attn.v_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.26.self_attn.o_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.26.mlp.up_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.26.mlp.gate_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.26.mlp.down_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.27 +24-11-19 20:07:44 | D | - Rotating model.layers.27.self_attn.q_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.27.self_attn.k_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.27.self_attn.v_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.27.self_attn.o_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.27.self_attn.v_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.27.self_attn.o_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.27.mlp.up_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.27.mlp.gate_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.27.mlp.down_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.28 +24-11-19 20:07:44 | D | - Rotating model.layers.28.self_attn.q_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.28.self_attn.k_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.28.self_attn.v_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.28.self_attn.o_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.28.self_attn.v_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.28.self_attn.o_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.28.mlp.up_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.28.mlp.gate_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.28.mlp.down_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.29 +24-11-19 20:07:44 | D | - Rotating model.layers.29.self_attn.q_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.29.self_attn.k_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.29.self_attn.v_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.29.self_attn.o_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.29.self_attn.v_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.29.self_attn.o_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.29.mlp.up_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.29.mlp.gate_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.29.mlp.down_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.30 +24-11-19 20:07:44 | D | - Rotating model.layers.30.self_attn.q_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.30.self_attn.k_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.30.self_attn.v_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.30.self_attn.o_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.30.self_attn.v_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.30.self_attn.o_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.30.mlp.up_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.30.mlp.gate_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.30.mlp.down_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.31 +24-11-19 20:07:44 | D | - Rotating model.layers.31.self_attn.q_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.31.self_attn.k_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.31.self_attn.v_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.31.self_attn.o_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.31.self_attn.v_proj (out) +24-11-19 20:07:44 | D | - Rotating model.layers.31.self_attn.o_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.31.mlp.up_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.31.mlp.gate_proj (in) +24-11-19 20:07:44 | D | - Rotating model.layers.31.mlp.down_proj (out) +24-11-19 20:07:44 | D | - Rotating lm_head (in) +24-11-19 20:07:44 | I | - Linking rotation to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200729.RUNNING/model/rotation.pt +24-11-19 20:07:45 | I | * Development dtype is torch.float32 +24-11-19 20:07:45 | I | * Smoothing model for quantization +24-11-19 20:07:45 | I | - Generating smooth scales +24-11-19 20:07:45 | D | Starting new HTTPS connection (1): huggingface.co:443 +24-11-19 20:08:01 | D | Starting new HTTPS connection (2): huggingface.co:443 +24-11-19 20:08:21 | D | Starting new HTTPS connection (1): s3.amazonaws.com:443 +24-11-19 20:08:42 | W | Repo card metadata block was not found. Setting CardData to empty. +24-11-19 20:08:42 | D | Starting new HTTPS connection (3): huggingface.co:443 +24-11-19 20:09:22 | W | Using the latest cached version of the dataset since mit-han-lab/pile-val-backup couldn't be found on the Hugging Face Hub +24-11-19 20:09:22 | W | Found the latest cached dataset configuration 'default' at /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4 (last modified on Tue Oct 8 18:58:39 2024). +24-11-19 20:09:22 | D | Attempting to acquire lock 23438954777584 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:09:22 | D | Lock 23438954777584 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:09:22 | D | open file: /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4/dataset_info.json +24-11-19 20:09:22 | D | Attempting to release lock 23438954777584 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:09:22 | D | Lock 23438954777584 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:09:42 | D | - Smoothing model.layers.0 +24-11-19 20:09:42 | D | - model.layers.0.self_attn.attn_k +24-11-19 20:09:42 | D | + w: None +24-11-19 20:09:42 | D | + x: None +24-11-19 20:09:42 | D | + y: sint8 +24-11-19 20:09:42 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:09:42 | D | + finished parsing calibration arguments, ram usage: 13.0 +24-11-19 20:09:42 | D | + x - AbsMax +24-11-19 20:09:42 | D | + x = [min=1.3467, max=18.0000] +24-11-19 20:09:42 | D | + y - AbsMax +24-11-19 20:09:42 | D | + y = [min=1.5479, max=18.6094] +24-11-19 20:09:42 | D | + finished reseting calibrator, ram usage: 13.0 +24-11-19 20:09:43 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:09:43 | D | - alpha = [ 0.5000] +24-11-19 20:09:43 | D | - beta = [ 0.0000] +24-11-19 20:09:43 | D | - sum error = [ 2.7568] +24-11-19 20:09:43 | D | - best error = [ 2.7568] +24-11-19 20:09:43 | D | + error = 2.7568 +24-11-19 20:09:43 | D | + scale = [min=1.2441, max=4.3139] +24-11-19 20:09:51 | D | - Smoothing model.layers.1 +24-11-19 20:09:51 | D | - model.layers.1.self_attn.attn_k +24-11-19 20:09:51 | D | + w: None +24-11-19 20:09:51 | D | + x: None +24-11-19 20:09:51 | D | + y: sint8 +24-11-19 20:09:51 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:09:51 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:09:51 | D | + x - AbsMax +24-11-19 20:09:51 | D | + x = [min=2.2598, max=14.4688] +24-11-19 20:09:51 | D | + y - AbsMax +24-11-19 20:09:51 | D | + y = [min=2.4453, max=17.8125] +24-11-19 20:09:51 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:09:52 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:09:52 | D | - alpha = [ 0.5000] +24-11-19 20:09:52 | D | - beta = [ 0.0000] +24-11-19 20:09:52 | D | - sum error = [ 7.1286] +24-11-19 20:09:52 | D | - best error = [ 7.1286] +24-11-19 20:09:52 | D | + error = 7.1286 +24-11-19 20:09:52 | D | + scale = [min=1.5637, max=4.2205] +24-11-19 20:10:01 | D | - Smoothing model.layers.2 +24-11-19 20:10:01 | D | - model.layers.2.self_attn.attn_k +24-11-19 20:10:01 | D | + w: None +24-11-19 20:10:01 | D | + x: None +24-11-19 20:10:01 | D | + y: sint8 +24-11-19 20:10:01 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:10:01 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:10:01 | D | + x - AbsMax +24-11-19 20:10:01 | D | + x = [min=1.4365, max=15.0547] +24-11-19 20:10:01 | D | + y - AbsMax +24-11-19 20:10:01 | D | + y = [min=1.2695, max=21.7812] +24-11-19 20:10:01 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:10:02 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:10:02 | D | - alpha = [ 0.5000] +24-11-19 20:10:02 | D | - beta = [ 0.0000] +24-11-19 20:10:02 | D | - sum error = [ 7.3559] +24-11-19 20:10:02 | D | - best error = [ 7.3559] +24-11-19 20:10:02 | D | + error = 7.3559 +24-11-19 20:10:02 | D | + scale = [min=1.1267, max=4.6670] +24-11-19 20:10:10 | D | - Smoothing model.layers.3 +24-11-19 20:10:10 | D | - model.layers.3.self_attn.attn_k +24-11-19 20:10:10 | D | + w: None +24-11-19 20:10:10 | D | + x: None +24-11-19 20:10:10 | D | + y: sint8 +24-11-19 20:10:10 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:10:10 | D | + finished parsing calibration arguments, ram usage: 14.1 +24-11-19 20:10:10 | D | + x - AbsMax +24-11-19 20:10:10 | D | + x = [min=2.4746, max=15.6016] +24-11-19 20:10:10 | D | + y - AbsMax +24-11-19 20:10:10 | D | + y = [min=3.0293, max=23.3438] +24-11-19 20:10:10 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:10:11 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:10:11 | D | - alpha = [ 0.5000] +24-11-19 20:10:11 | D | - beta = [ 0.0000] +24-11-19 20:10:11 | D | - sum error = [ 11.2295] +24-11-19 20:10:11 | D | - best error = [ 11.2295] +24-11-19 20:10:11 | D | + error = 11.2295 +24-11-19 20:10:11 | D | + scale = [min=1.7405, max=4.8315] +24-11-19 20:10:19 | D | - Smoothing model.layers.4 +24-11-19 20:10:19 | D | - model.layers.4.self_attn.attn_k +24-11-19 20:10:19 | D | + w: None +24-11-19 20:10:19 | D | + x: None +24-11-19 20:10:19 | D | + y: sint8 +24-11-19 20:10:19 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:10:19 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:10:19 | D | + x - AbsMax +24-11-19 20:10:19 | D | + x = [min=2.1934, max=15.2812] +24-11-19 20:10:19 | D | + y - AbsMax +24-11-19 20:10:19 | D | + y = [min=3.4199, max=24.3125] +24-11-19 20:10:19 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:10:20 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:10:20 | D | - alpha = [ 0.5000] +24-11-19 20:10:20 | D | - beta = [ 0.0000] +24-11-19 20:10:20 | D | - sum error = [ 20.4703] +24-11-19 20:10:20 | D | - best error = [ 20.4703] +24-11-19 20:10:20 | D | + error = 20.4703 +24-11-19 20:10:20 | D | + scale = [min=1.8493, max=4.9308] +24-11-19 20:10:28 | D | - Smoothing model.layers.5 +24-11-19 20:10:28 | D | - model.layers.5.self_attn.attn_k +24-11-19 20:10:28 | D | + w: None +24-11-19 20:10:28 | D | + x: None +24-11-19 20:10:28 | D | + y: sint8 +24-11-19 20:10:28 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:10:28 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:10:28 | D | + x - AbsMax +24-11-19 20:10:28 | D | + x = [min=2.9180, max=18.8281] +24-11-19 20:10:28 | D | + y - AbsMax +24-11-19 20:10:28 | D | + y = [min=2.4434, max=27.2812] +24-11-19 20:10:28 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:10:29 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:10:29 | D | - alpha = [ 0.5000] +24-11-19 20:10:29 | D | - beta = [ 0.0000] +24-11-19 20:10:29 | D | - sum error = [ 19.7660] +24-11-19 20:10:29 | D | - best error = [ 19.7660] +24-11-19 20:10:29 | D | + error = 19.7660 +24-11-19 20:10:29 | D | + scale = [min=1.5631, max=5.2231] +24-11-19 20:10:37 | D | - Smoothing model.layers.6 +24-11-19 20:10:37 | D | - model.layers.6.self_attn.attn_k +24-11-19 20:10:37 | D | + w: None +24-11-19 20:10:37 | D | + x: None +24-11-19 20:10:37 | D | + y: sint8 +24-11-19 20:10:37 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:10:37 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:10:37 | D | + x - AbsMax +24-11-19 20:10:37 | D | + x = [min=2.4512, max=18.4844] +24-11-19 20:10:37 | D | + y - AbsMax +24-11-19 20:10:37 | D | + y = [min=3.5645, max=22.1094] +24-11-19 20:10:37 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:10:38 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:10:38 | D | - alpha = [ 0.5000] +24-11-19 20:10:38 | D | - beta = [ 0.0000] +24-11-19 20:10:38 | D | - sum error = [ 18.1268] +24-11-19 20:10:38 | D | - best error = [ 18.1268] +24-11-19 20:10:38 | D | + error = 18.1268 +24-11-19 20:10:38 | D | + scale = [min=1.8880, max=4.7021] +24-11-19 20:10:45 | D | - Smoothing model.layers.7 +24-11-19 20:10:45 | D | - model.layers.7.self_attn.attn_k +24-11-19 20:10:45 | D | + w: None +24-11-19 20:10:45 | D | + x: None +24-11-19 20:10:45 | D | + y: sint8 +24-11-19 20:10:45 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:10:45 | D | + finished parsing calibration arguments, ram usage: 14.1 +24-11-19 20:10:46 | D | + x - AbsMax +24-11-19 20:10:46 | D | + x = [min=2.7207, max=17.5469] +24-11-19 20:10:46 | D | + y - AbsMax +24-11-19 20:10:46 | D | + y = [min=3.4629, max=23.9844] +24-11-19 20:10:46 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:10:46 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:10:46 | D | - alpha = [ 0.5000] +24-11-19 20:10:46 | D | - beta = [ 0.0000] +24-11-19 20:10:46 | D | - sum error = [ 25.4320] +24-11-19 20:10:46 | D | - best error = [ 25.4320] +24-11-19 20:10:46 | D | + error = 25.4320 +24-11-19 20:10:46 | D | + scale = [min=1.8609, max=4.8974] +24-11-19 20:10:54 | D | - Smoothing model.layers.8 +24-11-19 20:10:54 | D | - model.layers.8.self_attn.attn_k +24-11-19 20:10:54 | D | + w: None +24-11-19 20:10:54 | D | + x: None +24-11-19 20:10:54 | D | + y: sint8 +24-11-19 20:10:54 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:10:54 | D | + finished parsing calibration arguments, ram usage: 14.7 +24-11-19 20:10:55 | D | + x - AbsMax +24-11-19 20:10:55 | D | + x = [min=2.5527, max=19.6406] +24-11-19 20:10:55 | D | + y - AbsMax +24-11-19 20:10:55 | D | + y = [min=2.7891, max=23.6719] +24-11-19 20:10:55 | D | + finished reseting calibrator, ram usage: 14.6 +24-11-19 20:10:55 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:10:55 | D | - alpha = [ 0.5000] +24-11-19 20:10:55 | D | - beta = [ 0.0000] +24-11-19 20:10:55 | D | - sum error = [ 21.6155] +24-11-19 20:10:55 | D | - best error = [ 21.6155] +24-11-19 20:10:55 | D | + error = 21.6155 +24-11-19 20:10:55 | D | + scale = [min=1.6700, max=4.8654] +24-11-19 20:11:03 | D | - Smoothing model.layers.9 +24-11-19 20:11:03 | D | - model.layers.9.self_attn.attn_k +24-11-19 20:11:03 | D | + w: None +24-11-19 20:11:03 | D | + x: None +24-11-19 20:11:03 | D | + y: sint8 +24-11-19 20:11:03 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:03 | D | + finished parsing calibration arguments, ram usage: 14.3 +24-11-19 20:11:03 | D | + x - AbsMax +24-11-19 20:11:03 | D | + x = [min=2.4062, max=15.3125] +24-11-19 20:11:03 | D | + y - AbsMax +24-11-19 20:11:03 | D | + y = [min=3.0723, max=25.1562] +24-11-19 20:11:03 | D | + finished reseting calibrator, ram usage: 14.3 +24-11-19 20:11:04 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:04 | D | - alpha = [ 0.5000] +24-11-19 20:11:04 | D | - beta = [ 0.0000] +24-11-19 20:11:04 | D | - sum error = [ 22.4573] +24-11-19 20:11:04 | D | - best error = [ 22.4573] +24-11-19 20:11:04 | D | + error = 22.4573 +24-11-19 20:11:04 | D | + scale = [min=1.7528, max=5.0156] +24-11-19 20:11:12 | D | - Smoothing model.layers.10 +24-11-19 20:11:12 | D | - model.layers.10.self_attn.attn_k +24-11-19 20:11:12 | D | + w: None +24-11-19 20:11:12 | D | + x: None +24-11-19 20:11:12 | D | + y: sint8 +24-11-19 20:11:12 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:12 | D | + finished parsing calibration arguments, ram usage: 14.3 +24-11-19 20:11:12 | D | + x - AbsMax +24-11-19 20:11:12 | D | + x = [min=2.7832, max=16.7969] +24-11-19 20:11:12 | D | + y - AbsMax +24-11-19 20:11:12 | D | + y = [min=3.5762, max=23.3750] +24-11-19 20:11:12 | D | + finished reseting calibrator, ram usage: 14.3 +24-11-19 20:11:12 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:12 | D | - alpha = [ 0.5000] +24-11-19 20:11:12 | D | - beta = [ 0.0000] +24-11-19 20:11:12 | D | - sum error = [ 19.7481] +24-11-19 20:11:12 | D | - best error = [ 19.7481] +24-11-19 20:11:12 | D | + error = 19.7481 +24-11-19 20:11:12 | D | + scale = [min=1.8911, max=4.8348] +24-11-19 20:11:20 | D | - Smoothing model.layers.11 +24-11-19 20:11:20 | D | - model.layers.11.self_attn.attn_k +24-11-19 20:11:20 | D | + w: None +24-11-19 20:11:20 | D | + x: None +24-11-19 20:11:20 | D | + y: sint8 +24-11-19 20:11:20 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:20 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:11:20 | D | + x - AbsMax +24-11-19 20:11:20 | D | + x = [min=2.3789, max=15.8125] +24-11-19 20:11:20 | D | + y - AbsMax +24-11-19 20:11:20 | D | + y = [min=3.2129, max=26.1406] +24-11-19 20:11:20 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:11:20 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:20 | D | - alpha = [ 0.5000] +24-11-19 20:11:20 | D | - beta = [ 0.0000] +24-11-19 20:11:20 | D | - sum error = [ 24.0137] +24-11-19 20:11:20 | D | - best error = [ 24.0137] +24-11-19 20:11:20 | D | + error = 24.0137 +24-11-19 20:11:20 | D | + scale = [min=1.7925, max=5.1128] +24-11-19 20:11:28 | D | - Smoothing model.layers.12 +24-11-19 20:11:28 | D | - model.layers.12.self_attn.attn_k +24-11-19 20:11:28 | D | + w: None +24-11-19 20:11:28 | D | + x: None +24-11-19 20:11:28 | D | + y: sint8 +24-11-19 20:11:28 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:28 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:11:28 | D | + x - AbsMax +24-11-19 20:11:28 | D | + x = [min=2.6582, max=21.0625] +24-11-19 20:11:28 | D | + y - AbsMax +24-11-19 20:11:28 | D | + y = [min=3.4844, max=25.3594] +24-11-19 20:11:28 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:11:29 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:29 | D | - alpha = [ 0.5000] +24-11-19 20:11:29 | D | - beta = [ 0.0000] +24-11-19 20:11:29 | D | - sum error = [ 32.7301] +24-11-19 20:11:29 | D | - best error = [ 32.7301] +24-11-19 20:11:29 | D | + error = 32.7301 +24-11-19 20:11:29 | D | + scale = [min=1.8666, max=5.0358] +24-11-19 20:11:37 | D | - Smoothing model.layers.13 +24-11-19 20:11:37 | D | - model.layers.13.self_attn.attn_k +24-11-19 20:11:37 | D | + w: None +24-11-19 20:11:37 | D | + x: None +24-11-19 20:11:37 | D | + y: sint8 +24-11-19 20:11:37 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:37 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:11:37 | D | + x - AbsMax +24-11-19 20:11:37 | D | + x = [min=2.3457, max=18.3906] +24-11-19 20:11:37 | D | + y - AbsMax +24-11-19 20:11:37 | D | + y = [min=2.7832, max=23.2812] +24-11-19 20:11:37 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:11:37 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:37 | D | - alpha = [ 0.5000] +24-11-19 20:11:37 | D | - beta = [ 0.0000] +24-11-19 20:11:37 | D | - sum error = [ 25.4453] +24-11-19 20:11:37 | D | - best error = [ 25.4453] +24-11-19 20:11:37 | D | + error = 25.4453 +24-11-19 20:11:37 | D | + scale = [min=1.6683, max=4.8251] +24-11-19 20:11:44 | D | - Smoothing model.layers.14 +24-11-19 20:11:44 | D | - model.layers.14.self_attn.attn_k +24-11-19 20:11:44 | D | + w: None +24-11-19 20:11:44 | D | + x: None +24-11-19 20:11:44 | D | + y: sint8 +24-11-19 20:11:44 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:44 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:11:44 | D | + x - AbsMax +24-11-19 20:11:44 | D | + x = [min=2.2734, max=16.0781] +24-11-19 20:11:44 | D | + y - AbsMax +24-11-19 20:11:44 | D | + y = [min=2.9512, max=25.4531] +24-11-19 20:11:44 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:11:45 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:45 | D | - alpha = [ 0.5000] +24-11-19 20:11:45 | D | - beta = [ 0.0000] +24-11-19 20:11:45 | D | - sum error = [ 30.6803] +24-11-19 20:11:45 | D | - best error = [ 30.6803] +24-11-19 20:11:45 | D | + error = 30.6803 +24-11-19 20:11:45 | D | + scale = [min=1.7179, max=5.0451] +24-11-19 20:11:52 | D | - Smoothing model.layers.15 +24-11-19 20:11:52 | D | - model.layers.15.self_attn.attn_k +24-11-19 20:11:52 | D | + w: None +24-11-19 20:11:52 | D | + x: None +24-11-19 20:11:52 | D | + y: sint8 +24-11-19 20:11:52 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:52 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:11:53 | D | + x - AbsMax +24-11-19 20:11:53 | D | + x = [min=2.6152, max=18.0625] +24-11-19 20:11:53 | D | + y - AbsMax +24-11-19 20:11:53 | D | + y = [min=3.1660, max=24.4531] +24-11-19 20:11:53 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:11:53 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:53 | D | - alpha = [ 0.5000] +24-11-19 20:11:53 | D | - beta = [ 0.0000] +24-11-19 20:11:53 | D | - sum error = [ 29.8959] +24-11-19 20:11:53 | D | - best error = [ 29.8959] +24-11-19 20:11:53 | D | + error = 29.8959 +24-11-19 20:11:53 | D | + scale = [min=1.7793, max=4.9450] +24-11-19 20:12:00 | D | - Smoothing model.layers.16 +24-11-19 20:12:00 | D | - model.layers.16.self_attn.attn_k +24-11-19 20:12:00 | D | + w: None +24-11-19 20:12:00 | D | + x: None +24-11-19 20:12:00 | D | + y: sint8 +24-11-19 20:12:00 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:00 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:12:00 | D | + x - AbsMax +24-11-19 20:12:00 | D | + x = [min=2.5508, max=19.0781] +24-11-19 20:12:00 | D | + y - AbsMax +24-11-19 20:12:00 | D | + y = [min=2.6094, max=25.7656] +24-11-19 20:12:00 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:12:01 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:01 | D | - alpha = [ 0.5000] +24-11-19 20:12:01 | D | - beta = [ 0.0000] +24-11-19 20:12:01 | D | - sum error = [ 34.2738] +24-11-19 20:12:01 | D | - best error = [ 34.2738] +24-11-19 20:12:01 | D | + error = 34.2738 +24-11-19 20:12:01 | D | + scale = [min=1.6154, max=5.0760] +24-11-19 20:12:08 | D | - Smoothing model.layers.17 +24-11-19 20:12:08 | D | - model.layers.17.self_attn.attn_k +24-11-19 20:12:08 | D | + w: None +24-11-19 20:12:08 | D | + x: None +24-11-19 20:12:08 | D | + y: sint8 +24-11-19 20:12:08 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:08 | D | + finished parsing calibration arguments, ram usage: 14.1 +24-11-19 20:12:08 | D | + x - AbsMax +24-11-19 20:12:08 | D | + x = [min=2.8594, max=18.2969] +24-11-19 20:12:08 | D | + y - AbsMax +24-11-19 20:12:08 | D | + y = [min=2.9941, max=23.2031] +24-11-19 20:12:08 | D | + finished reseting calibrator, ram usage: 14.2 +24-11-19 20:12:09 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:09 | D | - alpha = [ 0.5000] +24-11-19 20:12:09 | D | - beta = [ 0.0000] +24-11-19 20:12:09 | D | - sum error = [ 29.4680] +24-11-19 20:12:09 | D | - best error = [ 29.4680] +24-11-19 20:12:09 | D | + error = 29.4680 +24-11-19 20:12:09 | D | + scale = [min=1.7304, max=4.8170] +24-11-19 20:12:16 | D | - Smoothing model.layers.18 +24-11-19 20:12:16 | D | - model.layers.18.self_attn.attn_k +24-11-19 20:12:16 | D | + w: None +24-11-19 20:12:16 | D | + x: None +24-11-19 20:12:16 | D | + y: sint8 +24-11-19 20:12:16 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:16 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:12:16 | D | + x - AbsMax +24-11-19 20:12:16 | D | + x = [min=2.8047, max=17.0000] +24-11-19 20:12:16 | D | + y - AbsMax +24-11-19 20:12:16 | D | + y = [min=2.9727, max=22.5000] +24-11-19 20:12:16 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:12:17 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:17 | D | - alpha = [ 0.5000] +24-11-19 20:12:17 | D | - beta = [ 0.0000] +24-11-19 20:12:17 | D | - sum error = [ 23.9080] +24-11-19 20:12:17 | D | - best error = [ 23.9080] +24-11-19 20:12:17 | D | + error = 23.9080 +24-11-19 20:12:17 | D | + scale = [min=1.7241, max=4.7434] +24-11-19 20:12:24 | D | - Smoothing model.layers.19 +24-11-19 20:12:24 | D | - model.layers.19.self_attn.attn_k +24-11-19 20:12:24 | D | + w: None +24-11-19 20:12:24 | D | + x: None +24-11-19 20:12:24 | D | + y: sint8 +24-11-19 20:12:24 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:24 | D | + finished parsing calibration arguments, ram usage: 14.1 +24-11-19 20:12:24 | D | + x - AbsMax +24-11-19 20:12:24 | D | + x = [min=1.6318, max=18.2500] +24-11-19 20:12:24 | D | + y - AbsMax +24-11-19 20:12:24 | D | + y = [min=3.8086, max=22.5469] +24-11-19 20:12:24 | D | + finished reseting calibrator, ram usage: 14.2 +24-11-19 20:12:25 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:25 | D | - alpha = [ 0.5000] +24-11-19 20:12:25 | D | - beta = [ 0.0000] +24-11-19 20:12:25 | D | - sum error = [ 22.1298] +24-11-19 20:12:25 | D | - best error = [ 22.1298] +24-11-19 20:12:25 | D | + error = 22.1298 +24-11-19 20:12:25 | D | + scale = [min=1.9516, max=4.7484] +24-11-19 20:12:33 | D | - Smoothing model.layers.20 +24-11-19 20:12:33 | D | - model.layers.20.self_attn.attn_k +24-11-19 20:12:33 | D | + w: None +24-11-19 20:12:33 | D | + x: None +24-11-19 20:12:33 | D | + y: sint8 +24-11-19 20:12:33 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:33 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:12:33 | D | + x - AbsMax +24-11-19 20:12:33 | D | + x = [min=1.7852, max=18.7500] +24-11-19 20:12:33 | D | + y - AbsMax +24-11-19 20:12:33 | D | + y = [min=3.3359, max=21.0312] +24-11-19 20:12:33 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:12:33 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:33 | D | - alpha = [ 0.5000] +24-11-19 20:12:33 | D | - beta = [ 0.0000] +24-11-19 20:12:33 | D | - sum error = [ 20.8735] +24-11-19 20:12:33 | D | - best error = [ 20.8735] +24-11-19 20:12:33 | D | + error = 20.8735 +24-11-19 20:12:33 | D | + scale = [min=1.8265, max=4.5860] +24-11-19 20:12:39 | D | - Smoothing model.layers.21 +24-11-19 20:12:39 | D | - model.layers.21.self_attn.attn_k +24-11-19 20:12:39 | D | + w: None +24-11-19 20:12:39 | D | + x: None +24-11-19 20:12:39 | D | + y: sint8 +24-11-19 20:12:39 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:39 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:12:40 | D | + x - AbsMax +24-11-19 20:12:40 | D | + x = [min=2.5195, max=22.7344] +24-11-19 20:12:40 | D | + y - AbsMax +24-11-19 20:12:40 | D | + y = [min=3.4102, max=26.6094] +24-11-19 20:12:40 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:12:40 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:40 | D | - alpha = [ 0.5000] +24-11-19 20:12:40 | D | - beta = [ 0.0000] +24-11-19 20:12:40 | D | - sum error = [ 35.7271] +24-11-19 20:12:40 | D | - best error = [ 35.7271] +24-11-19 20:12:40 | D | + error = 35.7271 +24-11-19 20:12:40 | D | + scale = [min=1.8467, max=5.1584] +24-11-19 20:12:47 | D | - Smoothing model.layers.22 +24-11-19 20:12:47 | D | - model.layers.22.self_attn.attn_k +24-11-19 20:12:47 | D | + w: None +24-11-19 20:12:47 | D | + x: None +24-11-19 20:12:47 | D | + y: sint8 +24-11-19 20:12:47 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:47 | D | + finished parsing calibration arguments, ram usage: 14.1 +24-11-19 20:12:47 | D | + x - AbsMax +24-11-19 20:12:47 | D | + x = [min=2.2441, max=22.4375] +24-11-19 20:12:48 | D | + y - AbsMax +24-11-19 20:12:48 | D | + y = [min=3.7188, max=24.7969] +24-11-19 20:12:48 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:12:48 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:48 | D | - alpha = [ 0.5000] +24-11-19 20:12:48 | D | - beta = [ 0.0000] +24-11-19 20:12:48 | D | - sum error = [ 27.8256] +24-11-19 20:12:48 | D | - best error = [ 27.8256] +24-11-19 20:12:48 | D | + error = 27.8256 +24-11-19 20:12:48 | D | + scale = [min=1.9284, max=4.9796] +24-11-19 20:12:54 | D | - Smoothing model.layers.23 +24-11-19 20:12:54 | D | - model.layers.23.self_attn.attn_k +24-11-19 20:12:54 | D | + w: None +24-11-19 20:12:54 | D | + x: None +24-11-19 20:12:54 | D | + y: sint8 +24-11-19 20:12:54 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:54 | D | + finished parsing calibration arguments, ram usage: 14.2 +24-11-19 20:12:54 | D | + x - AbsMax +24-11-19 20:12:54 | D | + x = [min=2.4004, max=21.9688] +24-11-19 20:12:54 | D | + y - AbsMax +24-11-19 20:12:54 | D | + y = [min=3.2637, max=23.6719] +24-11-19 20:12:54 | D | + finished reseting calibrator, ram usage: 14.2 +24-11-19 20:12:55 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:55 | D | - alpha = [ 0.5000] +24-11-19 20:12:55 | D | - beta = [ 0.0000] +24-11-19 20:12:55 | D | - sum error = [ 29.4462] +24-11-19 20:12:55 | D | - best error = [ 29.4462] +24-11-19 20:12:55 | D | + error = 29.4462 +24-11-19 20:12:55 | D | + scale = [min=1.8066, max=4.8654] +24-11-19 20:13:01 | D | - Smoothing model.layers.24 +24-11-19 20:13:01 | D | - model.layers.24.self_attn.attn_k +24-11-19 20:13:01 | D | + w: None +24-11-19 20:13:01 | D | + x: None +24-11-19 20:13:01 | D | + y: sint8 +24-11-19 20:13:01 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:01 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:13:01 | D | + x - AbsMax +24-11-19 20:13:01 | D | + x = [min=2.2500, max=25.5156] +24-11-19 20:13:01 | D | + y - AbsMax +24-11-19 20:13:01 | D | + y = [min=3.3730, max=24.4688] +24-11-19 20:13:01 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:13:02 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:02 | D | - alpha = [ 0.5000] +24-11-19 20:13:02 | D | - beta = [ 0.0000] +24-11-19 20:13:02 | D | - sum error = [ 29.6528] +24-11-19 20:13:02 | D | - best error = [ 29.6528] +24-11-19 20:13:02 | D | + error = 29.6528 +24-11-19 20:13:02 | D | + scale = [min=1.8366, max=4.9466] +24-11-19 20:13:09 | D | - Smoothing model.layers.25 +24-11-19 20:13:09 | D | - model.layers.25.self_attn.attn_k +24-11-19 20:13:09 | D | + w: None +24-11-19 20:13:09 | D | + x: None +24-11-19 20:13:09 | D | + y: sint8 +24-11-19 20:13:09 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:09 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:13:09 | D | + x - AbsMax +24-11-19 20:13:09 | D | + x = [min=1.5195, max=26.2656] +24-11-19 20:13:09 | D | + y - AbsMax +24-11-19 20:13:09 | D | + y = [min=2.8398, max=25.7812] +24-11-19 20:13:09 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:13:10 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:10 | D | - alpha = [ 0.5000] +24-11-19 20:13:10 | D | - beta = [ 0.0000] +24-11-19 20:13:10 | D | - sum error = [ 43.2213] +24-11-19 20:13:10 | D | - best error = [ 43.2213] +24-11-19 20:13:10 | D | + error = 43.2213 +24-11-19 20:13:10 | D | + scale = [min=1.6852, max=5.0775] +24-11-19 20:13:16 | D | - Smoothing model.layers.26 +24-11-19 20:13:16 | D | - model.layers.26.self_attn.attn_k +24-11-19 20:13:16 | D | + w: None +24-11-19 20:13:16 | D | + x: None +24-11-19 20:13:16 | D | + y: sint8 +24-11-19 20:13:16 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:16 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:13:16 | D | + x - AbsMax +24-11-19 20:13:16 | D | + x = [min=1.6602, max=24.8750] +24-11-19 20:13:16 | D | + y - AbsMax +24-11-19 20:13:16 | D | + y = [min=2.8652, max=25.5156] +24-11-19 20:13:16 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:13:17 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:17 | D | - alpha = [ 0.5000] +24-11-19 20:13:17 | D | - beta = [ 0.0000] +24-11-19 20:13:17 | D | - sum error = [ 36.3745] +24-11-19 20:13:17 | D | - best error = [ 36.3745] +24-11-19 20:13:17 | D | + error = 36.3745 +24-11-19 20:13:17 | D | + scale = [min=1.6927, max=5.0513] +24-11-19 20:13:23 | D | - Smoothing model.layers.27 +24-11-19 20:13:23 | D | - model.layers.27.self_attn.attn_k +24-11-19 20:13:23 | D | + w: None +24-11-19 20:13:23 | D | + x: None +24-11-19 20:13:23 | D | + y: sint8 +24-11-19 20:13:23 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:23 | D | + finished parsing calibration arguments, ram usage: 14.1 +24-11-19 20:13:24 | D | + x - AbsMax +24-11-19 20:13:24 | D | + x = [min=2.0391, max=24.8750] +24-11-19 20:13:24 | D | + y - AbsMax +24-11-19 20:13:24 | D | + y = [min=2.9277, max=23.4844] +24-11-19 20:13:24 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:13:24 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:24 | D | - alpha = [ 0.5000] +24-11-19 20:13:24 | D | - beta = [ 0.0000] +24-11-19 20:13:24 | D | - sum error = [ 41.1900] +24-11-19 20:13:24 | D | - best error = [ 41.1900] +24-11-19 20:13:24 | D | + error = 41.1900 +24-11-19 20:13:24 | D | + scale = [min=1.7111, max=4.8461] +24-11-19 20:13:30 | D | - Smoothing model.layers.28 +24-11-19 20:13:30 | D | - model.layers.28.self_attn.attn_k +24-11-19 20:13:30 | D | + w: None +24-11-19 20:13:30 | D | + x: None +24-11-19 20:13:30 | D | + y: sint8 +24-11-19 20:13:30 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:30 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:13:30 | D | + x - AbsMax +24-11-19 20:13:30 | D | + x = [min=2.9023, max=21.4062] +24-11-19 20:13:30 | D | + y - AbsMax +24-11-19 20:13:30 | D | + y = [min=3.2109, max=25.6094] +24-11-19 20:13:30 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:13:30 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:30 | D | - alpha = [ 0.5000] +24-11-19 20:13:30 | D | - beta = [ 0.0000] +24-11-19 20:13:30 | D | - sum error = [ 52.4741] +24-11-19 20:13:30 | D | - best error = [ 52.4741] +24-11-19 20:13:30 | D | + error = 52.4741 +24-11-19 20:13:30 | D | + scale = [min=1.7919, max=5.0606] +24-11-19 20:13:38 | D | - Smoothing model.layers.29 +24-11-19 20:13:38 | D | - model.layers.29.self_attn.attn_k +24-11-19 20:13:38 | D | + w: None +24-11-19 20:13:38 | D | + x: None +24-11-19 20:13:38 | D | + y: sint8 +24-11-19 20:13:38 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:38 | D | + finished parsing calibration arguments, ram usage: 14.1 +24-11-19 20:13:38 | D | + x - AbsMax +24-11-19 20:13:38 | D | + x = [min=2.5352, max=18.3125] +24-11-19 20:13:38 | D | + y - AbsMax +24-11-19 20:13:38 | D | + y = [min=2.8203, max=41.7812] +24-11-19 20:13:38 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:13:39 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:39 | D | - alpha = [ 0.5000] +24-11-19 20:13:39 | D | - beta = [ 0.0000] +24-11-19 20:13:39 | D | - sum error = [ 72.9680] +24-11-19 20:13:39 | D | - best error = [ 72.9680] +24-11-19 20:13:39 | D | + error = 72.9680 +24-11-19 20:13:39 | D | + scale = [min=1.6794, max=6.4638] +24-11-19 20:13:45 | D | - Smoothing model.layers.30 +24-11-19 20:13:45 | D | - model.layers.30.self_attn.attn_k +24-11-19 20:13:45 | D | + w: None +24-11-19 20:13:45 | D | + x: None +24-11-19 20:13:45 | D | + y: sint8 +24-11-19 20:13:45 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:45 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:13:45 | D | + x - AbsMax +24-11-19 20:13:45 | D | + x = [min=2.7656, max=21.4531] +24-11-19 20:13:45 | D | + y - AbsMax +24-11-19 20:13:45 | D | + y = [min=2.6582, max=24.0781] +24-11-19 20:13:45 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:13:46 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:46 | D | - alpha = [ 0.5000] +24-11-19 20:13:46 | D | - beta = [ 0.0000] +24-11-19 20:13:46 | D | - sum error = [ 72.0842] +24-11-19 20:13:46 | D | - best error = [ 72.0842] +24-11-19 20:13:46 | D | + error = 72.0842 +24-11-19 20:13:46 | D | + scale = [min=1.6304, max=4.9069] +24-11-19 20:13:53 | D | - Smoothing model.layers.31 +24-11-19 20:13:53 | D | - model.layers.31.self_attn.attn_k +24-11-19 20:13:53 | D | + w: None +24-11-19 20:13:53 | D | + x: None +24-11-19 20:13:53 | D | + y: sint8 +24-11-19 20:13:53 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:53 | D | + finished parsing calibration arguments, ram usage: 14.1 +24-11-19 20:13:53 | D | + x - AbsMax +24-11-19 20:13:53 | D | + x = [min=2.5547, max=34.0000] +24-11-19 20:13:53 | D | + y - AbsMax +24-11-19 20:13:53 | D | + y = [min=3.4902, max=25.7031] +24-11-19 20:13:53 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:13:53 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:53 | D | - alpha = [ 0.5000] +24-11-19 20:13:53 | D | - beta = [ 0.0000] +24-11-19 20:13:53 | D | - sum error = [ 92.1100] +24-11-19 20:13:53 | D | - best error = [ 92.1100] +24-11-19 20:13:53 | D | + error = 92.1100 +24-11-19 20:13:53 | D | + scale = [min=1.8682, max=5.0698] +24-11-19 20:13:54 | I | - Saving smooth scales to runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/llama-3-8b-instruct-gradient-1048k.pt +24-11-19 20:13:54 | I | - Linking smooth scales to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200729.RUNNING/model/smooth.pt +24-11-19 20:13:54 | I | * Quantizing weights +24-11-19 20:13:54 | I | - Generating weight quantizer settings +24-11-19 20:13:54 | D | Starting new HTTPS connection (4): huggingface.co:443 +24-11-19 20:14:00 | D | Starting new HTTPS connection (5): huggingface.co:443 +24-11-19 20:14:13 | D | Starting new HTTPS connection (2): s3.amazonaws.com:443 +24-11-19 20:14:25 | W | Repo card metadata block was not found. Setting CardData to empty. +24-11-19 20:14:25 | D | Starting new HTTPS connection (6): huggingface.co:443 +24-11-19 20:14:37 | W | Using the latest cached version of the dataset since mit-han-lab/pile-val-backup couldn't be found on the Hugging Face Hub +24-11-19 20:14:37 | W | Found the latest cached dataset configuration 'default' at /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4 (last modified on Tue Oct 8 18:58:39 2024). +24-11-19 20:14:37 | D | Attempting to acquire lock 23438703677648 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:14:37 | D | Lock 23438703677648 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:14:37 | D | open file: /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4/dataset_info.json +24-11-19 20:14:37 | D | Attempting to release lock 23438703677648 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:14:37 | D | Lock 23438703677648 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:15:01 | D | - Quantizing layer model.layers.0 +24-11-19 20:15:01 | D | - Calibrating model.layers.0.self_attn.q_proj.weight +24-11-19 20:15:01 | D | + w: sint8 +24-11-19 20:15:01 | D | + x: None +24-11-19 20:15:01 | D | + y: None +24-11-19 20:15:01 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:15:01 | D | + finished parsing calibration arguments, ram usage: 13.0 +24-11-19 20:15:01 | D | + finished reseting calibrator, ram usage: 13.1 +24-11-19 20:15:02 | D | + finished calculating the original outputs, ram usage: 13.1 +24-11-19 20:15:02 | D | - range ratio = [ 1.0000] +24-11-19 20:15:02 | D | sum error = [ 0.1818] +24-11-19 20:15:02 | D | best error = [ 0.1818] +24-11-19 20:15:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:15:15 | D | sum error = [ 0.1862, 0.1834, 0.1933, 0.1903, 0.1964] +24-11-19 20:15:15 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:15:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:15:15 | D | sum error = [ 0.2075, 0.2202, 0.2260, 0.2481, 0.2600] +24-11-19 20:15:15 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:15:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:15:15 | D | sum error = [ 0.2845, 0.3135, 0.3310, 0.3717, 0.4073] +24-11-19 20:15:15 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:15:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:15:15 | D | sum error = [ 0.4469, 0.4925, 0.5352, 0.6000, 0.6564] +24-11-19 20:15:15 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:15:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:15:15 | D | sum error = [ 0.7285, 0.8037, 0.8810, 0.9639, 1.0532] +24-11-19 20:15:15 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:15:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:15:15 | D | sum error = [ 1.1548, 1.2637, 1.3807, 1.5182, 1.6574] +24-11-19 20:15:15 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:15:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:15:15 | D | sum error = [ 1.8244, 1.9919, 2.1868, 2.3910, 2.6134] +24-11-19 20:15:15 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:15:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:15:15 | D | sum error = [ 2.8529, 3.1085, 3.3841, 3.6950, 4.0164] +24-11-19 20:15:15 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:15:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:15:15 | D | sum error = [ 4.3799, 4.7601, 5.1673, 5.6166, 6.0977] +24-11-19 20:15:15 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:15:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:15:15 | D | sum error = [ 6.6171, 7.1735, 7.7714, 8.4094, 9.1165] +24-11-19 20:15:15 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:15:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:15:15 | D | sum error = [ 9.8615, 10.6515, 11.5167, 12.4299, 13.4183] +24-11-19 20:15:15 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:15:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:15:15 | D | sum error = [ 14.4722, 15.5939, 16.7929, 18.0823, 19.4521] +24-11-19 20:15:15 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:15:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:15:15 | D | sum error = [ 20.9099, 22.4552, 24.1043, 25.8565, 27.7222] +24-11-19 20:15:15 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:15:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:15:15 | D | sum error = [ 29.7028, 31.8024, 34.0330, 36.3976, 38.8938] +24-11-19 20:15:15 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:15:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:15:15 | D | sum error = [ 41.5371, 44.3233, 47.2564, 50.3541, 53.5983] +24-11-19 20:15:15 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:15:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:15:15 | D | sum error = [ 57.0034, 60.5521, 64.2432, 68.0593, 72.0273] +24-11-19 20:15:15 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:15:15 | D | + error = [0.1818] +24-11-19 20:15:15 | D | - Calibrating model.layers.0.self_attn.k_proj.weight +24-11-19 20:15:15 | D | + w: sint8 +24-11-19 20:15:15 | D | + x: None +24-11-19 20:15:15 | D | + y: None +24-11-19 20:15:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:15:15 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:15:15 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:15:16 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:15:16 | D | - range ratio = [ 1.0000] +24-11-19 20:15:16 | D | sum error = [ 0.2610] +24-11-19 20:15:16 | D | best error = [ 0.2610] +24-11-19 20:15:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:15:31 | D | sum error = [ 0.2527, 0.2527, 0.2593, 0.2672, 0.2687] +24-11-19 20:15:31 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:15:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:15:31 | D | sum error = [ 0.2629, 0.2841, 0.2897, 0.3170, 0.3270] +24-11-19 20:15:31 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:15:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:15:31 | D | sum error = [ 0.3463, 0.3707, 0.3977, 0.4353, 0.4669] +24-11-19 20:15:31 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:15:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:15:31 | D | sum error = [ 0.4979, 0.5421, 0.5783, 0.6215, 0.6825] +24-11-19 20:15:31 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:15:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:15:31 | D | sum error = [ 0.7390, 0.8081, 0.8727, 0.9415, 1.0085] +24-11-19 20:15:31 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:15:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:15:31 | D | sum error = [ 1.0981, 1.1878, 1.2934, 1.3954, 1.5227] +24-11-19 20:15:31 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:15:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:15:31 | D | sum error = [ 1.6478, 1.7870, 1.9563, 2.1100, 2.2874] +24-11-19 20:15:31 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:15:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:15:31 | D | sum error = [ 2.4847, 2.7054, 2.9378, 3.1862, 3.4787] +24-11-19 20:15:31 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:15:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:15:31 | D | sum error = [ 3.7706, 4.1027, 4.4550, 4.8394, 5.2635] +24-11-19 20:15:31 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:15:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:15:31 | D | sum error = [ 5.7166, 6.1996, 6.7284, 7.3047, 7.9279] +24-11-19 20:15:31 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:15:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:15:31 | D | sum error = [ 8.5921, 9.3047, 10.0871, 10.9268, 11.8338] +24-11-19 20:15:31 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:15:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:15:31 | D | sum error = [ 12.8018, 13.8315, 14.9640, 16.1545, 17.4531] +24-11-19 20:15:31 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:15:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:15:31 | D | sum error = [ 18.8485, 20.3267, 21.9163, 23.6371, 25.4693] +24-11-19 20:15:31 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:15:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:15:31 | D | sum error = [ 27.4219, 29.4933, 31.7215, 34.0708, 36.5831] +24-11-19 20:15:31 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:15:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:15:31 | D | sum error = [ 39.2514, 42.0872, 45.0593, 48.2143, 51.5417] +24-11-19 20:15:31 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:15:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:15:31 | D | sum error = [ 55.0357, 58.6948, 62.5208, 66.4986, 70.6701] +24-11-19 20:15:31 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:15:31 | D | + error = [0.2527] +24-11-19 20:15:31 | D | - Calibrating model.layers.0.self_attn.v_proj.weight +24-11-19 20:15:31 | D | + w: sint8 +24-11-19 20:15:31 | D | + x: None +24-11-19 20:15:31 | D | + y: None +24-11-19 20:15:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:15:31 | D | + finished parsing calibration arguments, ram usage: 13.0 +24-11-19 20:15:32 | D | + finished reseting calibrator, ram usage: 13.0 +24-11-19 20:15:32 | D | + finished calculating the original outputs, ram usage: 12.9 +24-11-19 20:15:32 | D | - range ratio = [ 1.0000] +24-11-19 20:15:32 | D | sum error = [ 0.2193] +24-11-19 20:15:32 | D | best error = [ 0.2193] +24-11-19 20:15:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:15:32 | D | sum error = [ 0.2178, 0.2165, 0.2172, 0.2209, 0.2241] +24-11-19 20:15:32 | D | best error = [ 0.2060, 0.2008, 0.1982, 0.1969, 0.1960] +24-11-19 20:15:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:15:32 | D | sum error = [ 0.2293, 0.2382, 0.2481, 0.2593, 0.2738] +24-11-19 20:15:32 | D | best error = [ 0.1956, 0.1954, 0.1954, 0.1953, 0.1953] +24-11-19 20:15:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:15:32 | D | sum error = [ 0.2899, 0.3096, 0.3280, 0.3501, 0.3750] +24-11-19 20:15:32 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:15:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:15:32 | D | sum error = [ 0.4020, 0.4313, 0.4606, 0.4962, 0.5293] +24-11-19 20:15:32 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:15:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:15:32 | D | sum error = [ 0.5675, 0.6087, 0.6506, 0.6965, 0.7455] +24-11-19 20:15:32 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:15:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:15:32 | D | sum error = [ 0.7961, 0.8488, 0.9054, 0.9655, 1.0301] +24-11-19 20:15:32 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:15:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:15:32 | D | sum error = [ 1.0968, 1.1670, 1.2410, 1.3205, 1.4035] +24-11-19 20:15:32 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:15:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:15:32 | D | sum error = [ 1.4913, 1.5827, 1.6815, 1.7853, 1.8956] +24-11-19 20:15:32 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:15:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:15:32 | D | sum error = [ 2.0087, 2.1281, 2.2525, 2.3848, 2.5248] +24-11-19 20:15:32 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:15:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:15:32 | D | sum error = [ 2.6681, 2.8214, 2.9810, 3.1454, 3.3203] +24-11-19 20:15:32 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:15:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:15:32 | D | sum error = [ 3.5019, 3.6937, 3.8935, 4.1018, 4.3188] +24-11-19 20:15:32 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:15:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:15:32 | D | sum error = [ 4.5428, 4.7796, 5.0255, 5.2814, 5.5463] +24-11-19 20:15:32 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:15:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:15:32 | D | sum error = [ 5.8234, 6.1121, 6.4115, 6.7200, 7.0420] +24-11-19 20:15:32 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:15:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:15:32 | D | sum error = [ 7.3753, 7.7223, 8.0823, 8.4551, 8.8431] +24-11-19 20:15:32 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:15:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:15:32 | D | sum error = [ 9.2382, 9.6566, 10.0822, 10.5254, 10.9777] +24-11-19 20:15:32 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:15:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:15:32 | D | sum error = [ 11.4473, 11.9355, 12.4371, 12.9462, 13.4751] +24-11-19 20:15:32 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:15:32 | D | + error = [0.1953] +24-11-19 20:15:32 | D | - Calibrating model.layers.0.self_attn.o_proj.weight +24-11-19 20:15:32 | D | + w: sint8 +24-11-19 20:15:32 | D | + x: None +24-11-19 20:15:32 | D | + y: None +24-11-19 20:15:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:15:32 | D | + finished parsing calibration arguments, ram usage: 12.6 +24-11-19 20:15:32 | D | + finished reseting calibrator, ram usage: 12.6 +24-11-19 20:15:33 | D | + finished calculating the original outputs, ram usage: 12.7 +24-11-19 20:15:33 | D | - range ratio = [ 1.0000] +24-11-19 20:15:33 | D | sum error = [ 0.1014] +24-11-19 20:15:33 | D | best error = [ 0.1014] +24-11-19 20:15:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:15:33 | D | sum error = [ 0.1011, 0.1008, 0.1004, 0.1013, 0.1026] +24-11-19 20:15:33 | D | best error = [ 0.0902, 0.0859, 0.0834, 0.0820, 0.0811] +24-11-19 20:15:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:15:33 | D | sum error = [ 0.1056, 0.1081, 0.1115, 0.1154, 0.1205] +24-11-19 20:15:33 | D | best error = [ 0.0806, 0.0803, 0.0801, 0.0799, 0.0798] +24-11-19 20:15:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:15:33 | D | sum error = [ 0.1252, 0.1319, 0.1386, 0.1464, 0.1553] +24-11-19 20:15:33 | D | best error = [ 0.0798, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:15:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:15:33 | D | sum error = [ 0.1643, 0.1749, 0.1848, 0.1957, 0.2081] +24-11-19 20:15:33 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:15:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:15:33 | D | sum error = [ 0.2214, 0.2347, 0.2486, 0.2639, 0.2793] +24-11-19 20:15:33 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:15:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:15:33 | D | sum error = [ 0.2963, 0.3145, 0.3331, 0.3528, 0.3731] +24-11-19 20:15:33 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:15:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:15:33 | D | sum error = [ 0.3947, 0.4176, 0.4414, 0.4663, 0.4933] +24-11-19 20:15:33 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:15:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:15:33 | D | sum error = [ 0.5207, 0.5495, 0.5802, 0.6122, 0.6453] +24-11-19 20:15:33 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:15:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:15:33 | D | sum error = [ 0.6803, 0.7163, 0.7551, 0.7950, 0.8371] +24-11-19 20:15:33 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:15:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:15:33 | D | sum error = [ 0.8808, 0.9269, 0.9751, 1.0255, 1.0783] +24-11-19 20:15:33 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:15:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:15:33 | D | sum error = [ 1.1342, 1.1924, 1.2527, 1.3168, 1.3838] +24-11-19 20:15:33 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:15:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:15:33 | D | sum error = [ 1.4544, 1.5281, 1.6059, 1.6874, 1.7732] +24-11-19 20:15:33 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:15:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:15:33 | D | sum error = [ 1.8639, 1.9588, 2.0590, 2.1650, 2.2763] +24-11-19 20:15:33 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:15:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:15:33 | D | sum error = [ 2.3937, 2.5177, 2.6487, 2.7875, 2.9339] +24-11-19 20:15:33 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:15:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:15:33 | D | sum error = [ 3.0887, 3.2524, 3.4251, 3.6073, 3.7999] +24-11-19 20:15:33 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:15:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:15:33 | D | sum error = [ 4.0032, 4.2180, 4.4442, 4.6817, 4.9316] +24-11-19 20:15:33 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:15:33 | D | + error = [0.0797] +24-11-19 20:15:33 | D | - Calibrating model.layers.0.mlp.up_proj.weight +24-11-19 20:15:33 | D | + w: sint8 +24-11-19 20:15:33 | D | + x: None +24-11-19 20:15:33 | D | + y: None +24-11-19 20:15:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:15:33 | D | + finished parsing calibration arguments, ram usage: 12.7 +24-11-19 20:15:33 | D | + finished reseting calibrator, ram usage: 12.7 +24-11-19 20:15:33 | D | + finished calculating the original outputs, ram usage: 12.7 +24-11-19 20:15:33 | D | - range ratio = [ 1.0000] +24-11-19 20:15:33 | D | sum error = [ 2.2606] +24-11-19 20:15:33 | D | best error = [ 2.2606] +24-11-19 20:15:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:15:35 | D | sum error = [ 2.2440, 2.2535, 2.2472, 2.2776, 2.3220] +24-11-19 20:15:35 | D | best error = [ 1.9587, 1.8600, 1.8120, 1.7873, 1.7745] +24-11-19 20:15:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:15:35 | D | sum error = [ 2.3844, 2.4639, 2.5580, 2.6769, 2.8204] +24-11-19 20:15:35 | D | best error = [ 1.7677, 1.7644, 1.7632, 1.7627, 1.7625] +24-11-19 20:15:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:15:35 | D | sum error = [ 2.9755, 3.1721, 3.3687, 3.5981, 3.8508] +24-11-19 20:15:35 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 20:15:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:15:35 | D | sum error = [ 4.1289, 4.4221, 4.7278, 5.0683, 5.4289] +24-11-19 20:15:35 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 20:15:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:15:35 | D | sum error = [ 5.8146, 6.2320, 6.6839, 7.1387, 7.6263] +24-11-19 20:15:35 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 20:15:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:15:35 | D | sum error = [ 8.1391, 8.6968, 9.2717, 9.8852, 10.5354] +24-11-19 20:15:35 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 20:15:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:15:35 | D | sum error = [ 11.2254, 11.9461, 12.7076, 13.5005, 14.3489] +24-11-19 20:15:35 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 20:15:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:15:35 | D | sum error = [ 15.2349, 16.1826, 17.1606, 18.1985, 19.2827] +24-11-19 20:15:35 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 20:15:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:15:35 | D | sum error = [ 20.4208, 21.6124, 22.8676, 24.1705, 25.5445] +24-11-19 20:15:35 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 20:15:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:15:35 | D | sum error = [ 26.9863, 28.4909, 30.0511, 31.6863, 33.3914] +24-11-19 20:15:35 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 20:15:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:15:35 | D | sum error = [ 35.1696, 37.0370, 38.9715, 40.9965, 43.1047] +24-11-19 20:15:35 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 20:15:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:15:35 | D | sum error = [ 45.2972, 47.5756, 49.9516, 52.4045, 54.9502] +24-11-19 20:15:35 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 20:15:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:15:35 | D | sum error = [ 57.5903, 60.3275, 63.1578, 66.0883, 69.1156] +24-11-19 20:15:35 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 20:15:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:15:35 | D | sum error = [ 72.2659, 75.5223, 78.8808, 82.3590, 85.9552] +24-11-19 20:15:35 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 20:15:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:15:35 | D | sum error = [ 89.6681, 93.5025, 97.4546, 101.5239, 105.7320] +24-11-19 20:15:35 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 20:15:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:15:35 | D | sum error = [ 110.0650, 114.5187, 119.0959, 123.8128, 128.6631] +24-11-19 20:15:35 | D | best error = [ 1.7625, 1.7625, 1.7625, 1.7625, 1.7625] +24-11-19 20:15:35 | D | + error = [1.7625] +24-11-19 20:15:35 | D | - Calibrating model.layers.0.mlp.gate_proj.weight +24-11-19 20:15:35 | D | + w: sint8 +24-11-19 20:15:35 | D | + x: None +24-11-19 20:15:35 | D | + y: None +24-11-19 20:15:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:15:35 | D | + finished parsing calibration arguments, ram usage: 12.8 +24-11-19 20:15:35 | D | + finished reseting calibrator, ram usage: 12.8 +24-11-19 20:15:35 | D | + finished calculating the original outputs, ram usage: 12.8 +24-11-19 20:15:35 | D | - range ratio = [ 1.0000] +24-11-19 20:15:35 | D | sum error = [ 2.4924] +24-11-19 20:15:35 | D | best error = [ 2.4924] +24-11-19 20:15:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:15:36 | D | sum error = [ 2.4686, 2.4669, 2.4705, 2.5084, 2.5608] +24-11-19 20:15:36 | D | best error = [ 2.1585, 2.0455, 1.9930, 1.9666, 1.9525] +24-11-19 20:15:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:15:36 | D | sum error = [ 2.6193, 2.7142, 2.8166, 2.9523, 3.1187] +24-11-19 20:15:36 | D | best error = [ 1.9451, 1.9417, 1.9406, 1.9400, 1.9399] +24-11-19 20:15:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:15:36 | D | sum error = [ 3.3007, 3.5003, 3.7488, 3.9832, 4.2777] +24-11-19 20:15:36 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:15:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:15:36 | D | sum error = [ 4.5814, 4.9088, 5.2640, 5.6560, 6.0629] +24-11-19 20:15:36 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:15:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:15:36 | D | sum error = [ 6.4869, 6.9653, 7.4492, 7.9751, 8.5344] +24-11-19 20:15:36 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:15:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:15:36 | D | sum error = [ 9.1347, 9.7686, 10.4226, 11.1435, 11.8855] +24-11-19 20:15:36 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:15:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:15:36 | D | sum error = [ 12.6732, 13.5071, 14.3957, 15.3216, 16.3075] +24-11-19 20:15:36 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:15:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:15:36 | D | sum error = [ 17.3394, 18.4393, 19.5982, 20.8128, 22.1063] +24-11-19 20:15:36 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:15:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:15:36 | D | sum error = [ 23.4631, 24.9015, 26.4145, 27.9974, 29.6842] +24-11-19 20:15:36 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:15:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:15:36 | D | sum error = [ 31.4595, 33.3231, 35.2821, 37.3383, 39.4905] +24-11-19 20:15:36 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:15:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:15:36 | D | sum error = [ 41.7524, 44.1281, 46.6129, 49.2286, 51.9738] +24-11-19 20:15:36 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:15:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:15:36 | D | sum error = [ 54.8395, 57.8361, 60.9742, 64.2671, 67.6999] +24-11-19 20:15:36 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:15:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:15:36 | D | sum error = [ 71.2954, 75.0445, 78.9600, 83.0353, 87.2868] +24-11-19 20:15:36 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:15:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:15:36 | D | sum error = [ 91.6987, 96.2940, 101.0753, 106.0368, 111.1842] +24-11-19 20:15:36 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:15:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:15:36 | D | sum error = [ 116.5355, 122.0654, 127.7924, 133.7300, 139.8649] +24-11-19 20:15:36 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:15:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:15:36 | D | sum error = [ 146.2091, 152.7502, 159.5064, 166.4504, 173.5986] +24-11-19 20:15:36 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:15:36 | D | + error = [1.9398] +24-11-19 20:15:37 | D | - Calibrating model.layers.0.mlp.down_proj.weight +24-11-19 20:15:37 | D | + w: sint8 +24-11-19 20:15:37 | D | + x: None +24-11-19 20:15:37 | D | + y: None +24-11-19 20:15:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:15:37 | D | + finished parsing calibration arguments, ram usage: 12.9 +24-11-19 20:15:37 | D | + finished reseting calibrator, ram usage: 13.0 +24-11-19 20:15:37 | D | + finished calculating the original outputs, ram usage: 13.0 +24-11-19 20:15:37 | D | - range ratio = [ 1.0000] +24-11-19 20:15:37 | D | sum error = [ 0.1641] +24-11-19 20:15:37 | D | best error = [ 0.1641] +24-11-19 20:15:38 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:15:38 | D | sum error = [ 0.1636, 0.1664, 0.1712, 0.1797, 0.1904] +24-11-19 20:15:38 | D | best error = [ 0.1496, 0.1434, 0.1397, 0.1370, 0.1349] +24-11-19 20:15:38 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:15:38 | D | sum error = [ 0.2039, 0.2198, 0.2368, 0.2571, 0.2792] +24-11-19 20:15:38 | D | best error = [ 0.1333, 0.1321, 0.1310, 0.1301, 0.1295] +24-11-19 20:15:38 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:15:38 | D | sum error = [ 0.3030, 0.3302, 0.3569, 0.3863, 0.4184] +24-11-19 20:15:38 | D | best error = [ 0.1289, 0.1285, 0.1281, 0.1278, 0.1277] +24-11-19 20:15:38 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:15:38 | D | sum error = [ 0.4518, 0.4874, 0.5259, 0.5652, 0.6072] +24-11-19 20:15:38 | D | best error = [ 0.1275, 0.1274, 0.1273, 0.1273, 0.1272] +24-11-19 20:15:38 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:15:38 | D | sum error = [ 0.6518, 0.6996, 0.7485, 0.8008, 0.8544] +24-11-19 20:15:38 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 20:15:38 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:15:38 | D | sum error = [ 0.9124, 0.9723, 1.0357, 1.1029, 1.1735] +24-11-19 20:15:38 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 20:15:38 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:15:38 | D | sum error = [ 1.2474, 1.3251, 1.4058, 1.4919, 1.5836] +24-11-19 20:15:38 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 20:15:38 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:15:38 | D | sum error = [ 1.6790, 1.7791, 1.8840, 1.9954, 2.1114] +24-11-19 20:15:38 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 20:15:38 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:15:38 | D | sum error = [ 2.2334, 2.3603, 2.4942, 2.6353, 2.7824] +24-11-19 20:15:38 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 20:15:38 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:15:38 | D | sum error = [ 2.9372, 3.0987, 3.2686, 3.4470, 3.6332] +24-11-19 20:15:38 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 20:15:38 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:15:38 | D | sum error = [ 3.8272, 4.0309, 4.2441, 4.4677, 4.7013] +24-11-19 20:15:38 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 20:15:38 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:15:38 | D | sum error = [ 4.9452, 5.1996, 5.4652, 5.7417, 6.0311] +24-11-19 20:15:38 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 20:15:38 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:15:38 | D | sum error = [ 6.3320, 6.6462, 6.9736, 7.3146, 7.6691] +24-11-19 20:15:38 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 20:15:38 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:15:38 | D | sum error = [ 8.0380, 8.4220, 8.8203, 9.2342, 9.6631] +24-11-19 20:15:38 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 20:15:38 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:15:38 | D | sum error = [ 10.1081, 10.5687, 11.0461, 11.5403, 12.0510] +24-11-19 20:15:38 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 20:15:38 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:15:38 | D | sum error = [ 12.5787, 13.1238, 13.6866, 14.2675, 14.8654] +24-11-19 20:15:38 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 20:15:38 | D | + error = [0.1272] +24-11-19 20:15:38 | D | - Quantizing model.layers.0.self_attn.q_proj.weight +24-11-19 20:15:41 | D | - Quantizing model.layers.0.self_attn.k_proj.weight +24-11-19 20:15:42 | D | - Quantizing model.layers.0.self_attn.v_proj.weight +24-11-19 20:15:43 | D | - Quantizing model.layers.0.self_attn.o_proj.weight +24-11-19 20:15:45 | D | - Quantizing model.layers.0.mlp.up_proj.weight +24-11-19 20:15:46 | D | - Quantizing model.layers.0.mlp.gate_proj.weight +24-11-19 20:15:47 | D | - Quantizing model.layers.0.mlp.down_proj.weight +24-11-19 20:15:59 | D | - Quantizing layer model.layers.1 +24-11-19 20:15:59 | D | - Calibrating model.layers.1.self_attn.q_proj.weight +24-11-19 20:15:59 | D | + w: sint8 +24-11-19 20:15:59 | D | + x: None +24-11-19 20:15:59 | D | + y: None +24-11-19 20:15:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:15:59 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:15:59 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:15:59 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:15:59 | D | - range ratio = [ 1.0000] +24-11-19 20:15:59 | D | sum error = [ 0.4305] +24-11-19 20:15:59 | D | best error = [ 0.4305] +24-11-19 20:16:13 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:16:13 | D | sum error = [ 0.4308, 0.4267, 0.4298, 0.4361, 0.4758] +24-11-19 20:16:13 | D | best error = [ 0.4305, 0.4267, 0.4267, 0.4267, 0.4267] +24-11-19 20:16:13 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:16:13 | D | sum error = [ 0.4746, 0.4785, 0.5152, 0.5498, 0.5929] +24-11-19 20:16:13 | D | best error = [ 0.4267, 0.4267, 0.4267, 0.4267, 0.4267] +24-11-19 20:16:13 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:16:13 | D | sum error = [ 0.6540, 0.7070, 0.7943, 0.8786, 1.0211] +24-11-19 20:16:13 | D | best error = [ 0.4267, 0.4267, 0.4267, 0.4267, 0.4267] +24-11-19 20:16:13 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:16:13 | D | sum error = [ 1.0990, 1.2233, 1.3652, 1.4755, 1.6635] +24-11-19 20:16:13 | D | best error = [ 0.4267, 0.4267, 0.4267, 0.4267, 0.4267] +24-11-19 20:16:13 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:16:13 | D | sum error = [ 1.9375, 2.1542, 2.3420, 2.6178, 2.9274] +24-11-19 20:16:13 | D | best error = [ 0.4267, 0.4267, 0.4267, 0.4267, 0.4267] +24-11-19 20:16:13 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:16:13 | D | sum error = [ 3.2407, 3.5787, 3.9416, 4.3537, 4.8290] +24-11-19 20:16:13 | D | best error = [ 0.4267, 0.4267, 0.4267, 0.4267, 0.4267] +24-11-19 20:16:13 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:16:13 | D | sum error = [ 5.2488, 5.7270, 6.2932, 6.8969, 7.4700] +24-11-19 20:16:13 | D | best error = [ 0.4267, 0.4267, 0.4267, 0.4267, 0.4267] +24-11-19 20:16:13 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:16:13 | D | sum error = [ 8.1107, 8.8107, 9.5404, 10.3350, 11.1639] +24-11-19 20:16:13 | D | best error = [ 0.4267, 0.4267, 0.4267, 0.4267, 0.4267] +24-11-19 20:16:13 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:16:13 | D | sum error = [ 12.0787, 13.0812, 14.1224, 15.2549, 16.4776] +24-11-19 20:16:13 | D | best error = [ 0.4267, 0.4267, 0.4267, 0.4267, 0.4267] +24-11-19 20:16:13 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:16:13 | D | sum error = [ 17.7355, 19.1657, 20.6521, 22.2740, 24.0864] +24-11-19 20:16:13 | D | best error = [ 0.4267, 0.4267, 0.4267, 0.4267, 0.4267] +24-11-19 20:16:13 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:16:13 | D | sum error = [ 25.9679, 28.0105, 30.1566, 32.4740, 34.9431] +24-11-19 20:16:13 | D | best error = [ 0.4267, 0.4267, 0.4267, 0.4267, 0.4267] +24-11-19 20:16:13 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:16:13 | D | sum error = [ 37.5710, 40.3548, 43.3579, 46.5111, 49.9069] +24-11-19 20:16:13 | D | best error = [ 0.4267, 0.4267, 0.4267, 0.4267, 0.4267] +24-11-19 20:16:13 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:16:13 | D | sum error = [ 53.4259, 57.2212, 61.3169, 65.6198, 70.2337] +24-11-19 20:16:13 | D | best error = [ 0.4267, 0.4267, 0.4267, 0.4267, 0.4267] +24-11-19 20:16:13 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:16:13 | D | sum error = [ 75.1433, 80.2931, 85.9241, 91.8233, 98.0761] +24-11-19 20:16:13 | D | best error = [ 0.4267, 0.4267, 0.4267, 0.4267, 0.4267] +24-11-19 20:16:13 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:16:13 | D | sum error = [ 104.7095, 111.8251, 119.2515, 127.1167, 135.3278] +24-11-19 20:16:13 | D | best error = [ 0.4267, 0.4267, 0.4267, 0.4267, 0.4267] +24-11-19 20:16:13 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:16:13 | D | sum error = [ 144.0006, 153.0604, 162.4623, 172.2378, 182.3780] +24-11-19 20:16:13 | D | best error = [ 0.4267, 0.4267, 0.4267, 0.4267, 0.4267] +24-11-19 20:16:13 | D | + error = [0.4267] +24-11-19 20:16:13 | D | - Calibrating model.layers.1.self_attn.k_proj.weight +24-11-19 20:16:13 | D | + w: sint8 +24-11-19 20:16:13 | D | + x: None +24-11-19 20:16:13 | D | + y: None +24-11-19 20:16:13 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:16:13 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:16:13 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:16:13 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:16:14 | D | - range ratio = [ 1.0000] +24-11-19 20:16:14 | D | sum error = [ 0.4861] +24-11-19 20:16:14 | D | best error = [ 0.4861] +24-11-19 20:16:27 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:16:27 | D | sum error = [ 0.5110, 0.5165, 0.5080, 0.5376, 0.5265] +24-11-19 20:16:27 | D | best error = [ 0.4861, 0.4861, 0.4861, 0.4861, 0.4861] +24-11-19 20:16:27 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:16:27 | D | sum error = [ 0.6111, 0.5553, 0.6484, 0.6222, 0.6905] +24-11-19 20:16:27 | D | best error = [ 0.4861, 0.4861, 0.4861, 0.4861, 0.4861] +24-11-19 20:16:27 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:16:27 | D | sum error = [ 0.7313, 0.7375, 0.8338, 0.8900, 0.9996] +24-11-19 20:16:27 | D | best error = [ 0.4861, 0.4861, 0.4861, 0.4861, 0.4861] +24-11-19 20:16:27 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:16:27 | D | sum error = [ 1.1137, 1.2352, 1.3565, 1.4838, 1.6478] +24-11-19 20:16:27 | D | best error = [ 0.4861, 0.4861, 0.4861, 0.4861, 0.4861] +24-11-19 20:16:27 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:16:27 | D | sum error = [ 1.9471, 2.0567, 2.3703, 2.5786, 2.8982] +24-11-19 20:16:27 | D | best error = [ 0.4861, 0.4861, 0.4861, 0.4861, 0.4861] +24-11-19 20:16:27 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:16:27 | D | sum error = [ 3.0601, 3.4451, 3.7929, 4.2877, 4.6171] +24-11-19 20:16:27 | D | best error = [ 0.4861, 0.4861, 0.4861, 0.4861, 0.4861] +24-11-19 20:16:27 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:16:27 | D | sum error = [ 5.2651, 5.6672, 6.3127, 7.0001, 7.5688] +24-11-19 20:16:27 | D | best error = [ 0.4861, 0.4861, 0.4861, 0.4861, 0.4861] +24-11-19 20:16:27 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:16:27 | D | sum error = [ 8.3794, 9.1034, 9.7984, 10.6327, 11.5358] +24-11-19 20:16:27 | D | best error = [ 0.4861, 0.4861, 0.4861, 0.4861, 0.4861] +24-11-19 20:16:27 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:16:27 | D | sum error = [ 12.3988, 13.4352, 14.4142, 15.4333, 16.6659] +24-11-19 20:16:27 | D | best error = [ 0.4861, 0.4861, 0.4861, 0.4861, 0.4861] +24-11-19 20:16:27 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:16:27 | D | sum error = [ 17.9146, 19.2795, 20.5874, 22.2790, 23.9092] +24-11-19 20:16:27 | D | best error = [ 0.4861, 0.4861, 0.4861, 0.4861, 0.4861] +24-11-19 20:16:27 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:16:27 | D | sum error = [ 25.7414, 27.5958, 29.7936, 31.9413, 34.2412] +24-11-19 20:16:27 | D | best error = [ 0.4861, 0.4861, 0.4861, 0.4861, 0.4861] +24-11-19 20:16:27 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:16:27 | D | sum error = [ 36.8737, 39.4560, 42.6218, 45.7204, 49.1426] +24-11-19 20:16:27 | D | best error = [ 0.4861, 0.4861, 0.4861, 0.4861, 0.4861] +24-11-19 20:16:27 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:16:27 | D | sum error = [ 53.0246, 56.9586, 61.0543, 65.4473, 69.9676] +24-11-19 20:16:27 | D | best error = [ 0.4861, 0.4861, 0.4861, 0.4861, 0.4861] +24-11-19 20:16:27 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:16:27 | D | sum error = [ 75.4358, 80.3800, 85.9378, 92.0913, 98.0116] +24-11-19 20:16:27 | D | best error = [ 0.4861, 0.4861, 0.4861, 0.4861, 0.4861] +24-11-19 20:16:27 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:16:27 | D | sum error = [ 105.0946, 111.7956, 119.1935, 126.9285, 135.1132] +24-11-19 20:16:27 | D | best error = [ 0.4861, 0.4861, 0.4861, 0.4861, 0.4861] +24-11-19 20:16:27 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:16:27 | D | sum error = [ 143.4234, 152.6937, 161.7168, 171.4614, 181.3751] +24-11-19 20:16:27 | D | best error = [ 0.4861, 0.4861, 0.4861, 0.4861, 0.4861] +24-11-19 20:16:27 | D | + error = [0.4861] +24-11-19 20:16:27 | D | - Calibrating model.layers.1.self_attn.v_proj.weight +24-11-19 20:16:27 | D | + w: sint8 +24-11-19 20:16:27 | D | + x: None +24-11-19 20:16:27 | D | + y: None +24-11-19 20:16:27 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:16:27 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:16:27 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:16:27 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:16:27 | D | - range ratio = [ 1.0000] +24-11-19 20:16:27 | D | sum error = [ 0.3294] +24-11-19 20:16:27 | D | best error = [ 0.3294] +24-11-19 20:16:28 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:16:28 | D | sum error = [ 0.3317, 0.3363, 0.3407, 0.3381, 0.3455] +24-11-19 20:16:28 | D | best error = [ 0.2894, 0.2763, 0.2705, 0.2663, 0.2638] +24-11-19 20:16:28 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:16:28 | D | sum error = [ 0.3513, 0.3679, 0.3774, 0.3980, 0.4161] +24-11-19 20:16:28 | D | best error = [ 0.2624, 0.2621, 0.2618, 0.2618, 0.2618] +24-11-19 20:16:28 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:16:28 | D | sum error = [ 0.4412, 0.4761, 0.5048, 0.5371, 0.5741] +24-11-19 20:16:28 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:16:28 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:16:28 | D | sum error = [ 0.6138, 0.6649, 0.7099, 0.7622, 0.8185] +24-11-19 20:16:28 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:16:28 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:16:28 | D | sum error = [ 0.8748, 0.9379, 1.0041, 1.0734, 1.1492] +24-11-19 20:16:28 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:16:28 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:16:28 | D | sum error = [ 1.2320, 1.3188, 1.4054, 1.5045, 1.6055] +24-11-19 20:16:28 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:16:28 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:16:28 | D | sum error = [ 1.7072, 1.8264, 1.9491, 2.0751, 2.2107] +24-11-19 20:16:28 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:16:28 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:16:28 | D | sum error = [ 2.3531, 2.5026, 2.6662, 2.8296, 3.0075] +24-11-19 20:16:28 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:16:28 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:16:28 | D | sum error = [ 3.1903, 3.3819, 3.5857, 3.8012, 4.0309] +24-11-19 20:16:28 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:16:28 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:16:28 | D | sum error = [ 4.2656, 4.5186, 4.7817, 5.0580, 5.3496] +24-11-19 20:16:28 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:16:28 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:16:28 | D | sum error = [ 5.6503, 5.9667, 6.2939, 6.6413, 7.0047] +24-11-19 20:16:28 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:16:28 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:16:28 | D | sum error = [ 7.3770, 7.7712, 8.1821, 8.6119, 9.0603] +24-11-19 20:16:28 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:16:28 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:16:28 | D | sum error = [ 9.5292, 10.0164, 10.5322, 11.0698, 11.6275] +24-11-19 20:16:28 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:16:28 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:16:28 | D | sum error = [ 12.2053, 12.8133, 13.4400, 14.0969, 14.7773] +24-11-19 20:16:28 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:16:28 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:16:28 | D | sum error = [ 15.4822, 16.2136, 16.9707, 17.7528, 18.5687] +24-11-19 20:16:28 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:16:28 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:16:28 | D | sum error = [ 19.4045, 20.2758, 21.1661, 22.0941, 23.0470] +24-11-19 20:16:28 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:16:28 | D | + error = [0.2618] +24-11-19 20:16:28 | D | - Calibrating model.layers.1.self_attn.o_proj.weight +24-11-19 20:16:28 | D | + w: sint8 +24-11-19 20:16:28 | D | + x: None +24-11-19 20:16:28 | D | + y: None +24-11-19 20:16:28 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:16:28 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:16:28 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:16:28 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:16:28 | D | - range ratio = [ 1.0000] +24-11-19 20:16:28 | D | sum error = [ 0.1715] +24-11-19 20:16:28 | D | best error = [ 0.1715] +24-11-19 20:16:28 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:16:28 | D | sum error = [ 0.1715, 0.1716, 0.1711, 0.1736, 0.1769] +24-11-19 20:16:28 | D | best error = [ 0.1452, 0.1357, 0.1308, 0.1277, 0.1256] +24-11-19 20:16:28 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:16:28 | D | sum error = [ 0.1835, 0.1906, 0.1981, 0.2086, 0.2177] +24-11-19 20:16:28 | D | best error = [ 0.1242, 0.1233, 0.1226, 0.1221, 0.1218] +24-11-19 20:16:28 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:16:28 | D | sum error = [ 0.2322, 0.2444, 0.2621, 0.2816, 0.2976] +24-11-19 20:16:28 | D | best error = [ 0.1216, 0.1214, 0.1212, 0.1212, 0.1211] +24-11-19 20:16:28 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:16:28 | D | sum error = [ 0.3189, 0.3423, 0.3661, 0.3919, 0.4202] +24-11-19 20:16:28 | D | best error = [ 0.1211, 0.1211, 0.1210, 0.1210, 0.1210] +24-11-19 20:16:28 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:16:28 | D | sum error = [ 0.4477, 0.4783, 0.5106, 0.5460, 0.5800] +24-11-19 20:16:28 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:16:28 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:16:28 | D | sum error = [ 0.6194, 0.6582, 0.6998, 0.7448, 0.7923] +24-11-19 20:16:28 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:16:28 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:16:28 | D | sum error = [ 0.8393, 0.8908, 0.9450, 1.0029, 1.0620] +24-11-19 20:16:28 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:16:28 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:16:28 | D | sum error = [ 1.1271, 1.1929, 1.2633, 1.3356, 1.4129] +24-11-19 20:16:28 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:16:28 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:16:28 | D | sum error = [ 1.4945, 1.5790, 1.6670, 1.7621, 1.8596] +24-11-19 20:16:28 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:16:28 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:16:28 | D | sum error = [ 1.9631, 2.0719, 2.1846, 2.3030, 2.4296] +24-11-19 20:16:28 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:16:28 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:16:28 | D | sum error = [ 2.5586, 2.6952, 2.8375, 2.9862, 3.1412] +24-11-19 20:16:28 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:16:28 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:16:28 | D | sum error = [ 3.3039, 3.4727, 3.6494, 3.8325, 4.0239] +24-11-19 20:16:28 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:16:28 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:16:28 | D | sum error = [ 4.2250, 4.4352, 4.6528, 4.8817, 5.1195] +24-11-19 20:16:28 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:16:28 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:16:28 | D | sum error = [ 5.3675, 5.6265, 5.8963, 6.1758, 6.4663] +24-11-19 20:16:28 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:16:28 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:16:28 | D | sum error = [ 6.7685, 7.0810, 7.4050, 7.7416, 8.0905] +24-11-19 20:16:28 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:16:28 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:16:28 | D | sum error = [ 8.4532, 8.8296, 9.2186, 9.6214, 10.0369] +24-11-19 20:16:28 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:16:28 | D | + error = [0.1210] +24-11-19 20:16:28 | D | - Calibrating model.layers.1.mlp.up_proj.weight +24-11-19 20:16:28 | D | + w: sint8 +24-11-19 20:16:28 | D | + x: None +24-11-19 20:16:28 | D | + y: None +24-11-19 20:16:28 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:16:28 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:16:29 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:16:29 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:16:29 | D | - range ratio = [ 1.0000] +24-11-19 20:16:29 | D | sum error = [ 2.8587] +24-11-19 20:16:29 | D | best error = [ 2.8587] +24-11-19 20:16:30 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:16:30 | D | sum error = [ 2.8479, 2.8403, 2.8455, 2.8715, 2.9348] +24-11-19 20:16:30 | D | best error = [ 2.5600, 2.4593, 2.4094, 2.3817, 2.3677] +24-11-19 20:16:30 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:16:30 | D | sum error = [ 3.0036, 3.1014, 3.2269, 3.3767, 3.5565] +24-11-19 20:16:30 | D | best error = [ 2.3598, 2.3563, 2.3549, 2.3545, 2.3543] +24-11-19 20:16:30 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:16:30 | D | sum error = [ 3.7699, 3.9968, 4.2593, 4.5402, 4.8494] +24-11-19 20:16:30 | D | best error = [ 2.3543, 2.3542, 2.3542, 2.3542, 2.3542] +24-11-19 20:16:30 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:16:30 | D | sum error = [ 5.1893, 5.5658, 5.9570, 6.3827, 6.8404] +24-11-19 20:16:30 | D | best error = [ 2.3542, 2.3542, 2.3542, 2.3542, 2.3542] +24-11-19 20:16:30 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:16:30 | D | sum error = [ 7.3236, 7.8433, 8.4096, 8.9831, 9.6152] +24-11-19 20:16:30 | D | best error = [ 2.3542, 2.3542, 2.3542, 2.3542, 2.3542] +24-11-19 20:16:30 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:16:30 | D | sum error = [ 10.2826, 10.9752, 11.7287, 12.5026, 13.3355] +24-11-19 20:16:30 | D | best error = [ 2.3542, 2.3542, 2.3542, 2.3542, 2.3542] +24-11-19 20:16:30 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:16:30 | D | sum error = [ 14.2070, 15.1247, 16.0843, 17.1081, 18.1666] +24-11-19 20:16:30 | D | best error = [ 2.3542, 2.3542, 2.3542, 2.3542, 2.3542] +24-11-19 20:16:30 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:16:30 | D | sum error = [ 19.3040, 20.4809, 21.7158, 23.0220, 24.3955] +24-11-19 20:16:30 | D | best error = [ 2.3542, 2.3542, 2.3542, 2.3542, 2.3542] +24-11-19 20:16:30 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:16:30 | D | sum error = [ 25.8039, 27.3004, 28.8619, 30.4906, 32.1963] +24-11-19 20:16:30 | D | best error = [ 2.3542, 2.3542, 2.3542, 2.3542, 2.3542] +24-11-19 20:16:30 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:16:30 | D | sum error = [ 33.9890, 35.8465, 37.7947, 39.8152, 41.9159] +24-11-19 20:16:30 | D | best error = [ 2.3542, 2.3542, 2.3542, 2.3542, 2.3542] +24-11-19 20:16:30 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:16:30 | D | sum error = [ 44.1046, 46.3848, 48.7587, 51.2121, 53.7632] +24-11-19 20:16:30 | D | best error = [ 2.3542, 2.3542, 2.3542, 2.3542, 2.3542] +24-11-19 20:16:30 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:16:30 | D | sum error = [ 56.4085, 59.1606, 62.0058, 64.9513, 68.0064] +24-11-19 20:16:30 | D | best error = [ 2.3542, 2.3542, 2.3542, 2.3542, 2.3542] +24-11-19 20:16:30 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:16:30 | D | sum error = [ 71.1719, 74.4241, 77.7939, 81.2802, 84.8696] +24-11-19 20:16:30 | D | best error = [ 2.3542, 2.3542, 2.3542, 2.3542, 2.3542] +24-11-19 20:16:30 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:16:30 | D | sum error = [ 88.5758, 92.4042, 96.3350, 100.3836, 104.5513] +24-11-19 20:16:30 | D | best error = [ 2.3542, 2.3542, 2.3542, 2.3542, 2.3542] +24-11-19 20:16:30 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:16:30 | D | sum error = [ 108.8215, 113.2295, 117.7614, 122.4100, 127.1860] +24-11-19 20:16:30 | D | best error = [ 2.3542, 2.3542, 2.3542, 2.3542, 2.3542] +24-11-19 20:16:30 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:16:30 | D | sum error = [ 132.1118, 137.1545, 142.3313, 147.6318, 153.0676] +24-11-19 20:16:30 | D | best error = [ 2.3542, 2.3542, 2.3542, 2.3542, 2.3542] +24-11-19 20:16:30 | D | + error = [2.3542] +24-11-19 20:16:30 | D | - Calibrating model.layers.1.mlp.gate_proj.weight +24-11-19 20:16:30 | D | + w: sint8 +24-11-19 20:16:30 | D | + x: None +24-11-19 20:16:30 | D | + y: None +24-11-19 20:16:30 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:16:30 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:16:30 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:16:30 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:16:30 | D | - range ratio = [ 1.0000] +24-11-19 20:16:30 | D | sum error = [ 3.1407] +24-11-19 20:16:30 | D | best error = [ 3.1407] +24-11-19 20:16:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:16:31 | D | sum error = [ 3.1194, 3.1114, 3.1216, 3.1555, 3.2209] +24-11-19 20:16:31 | D | best error = [ 2.8114, 2.7001, 2.6439, 2.6124, 2.5956] +24-11-19 20:16:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:16:31 | D | sum error = [ 3.2959, 3.4250, 3.5640, 3.7060, 3.9123] +24-11-19 20:16:31 | D | best error = [ 2.5874, 2.5835, 2.5818, 2.5813, 2.5812] +24-11-19 20:16:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:16:31 | D | sum error = [ 4.1402, 4.3993, 4.6880, 5.0056, 5.3382] +24-11-19 20:16:31 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:16:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:16:31 | D | sum error = [ 5.7275, 6.1404, 6.5765, 7.0423, 7.5546] +24-11-19 20:16:31 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:16:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:16:31 | D | sum error = [ 8.1076, 8.6790, 9.2921, 9.9557, 10.6584] +24-11-19 20:16:31 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:16:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:16:31 | D | sum error = [ 11.3908, 12.1813, 13.0139, 13.8810, 14.8352] +24-11-19 20:16:31 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:16:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:16:31 | D | sum error = [ 15.8139, 16.8597, 17.9432, 19.1228, 20.3504] +24-11-19 20:16:31 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:16:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:16:31 | D | sum error = [ 21.6440, 23.0064, 24.4395, 25.9435, 27.5298] +24-11-19 20:16:31 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:16:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:16:31 | D | sum error = [ 29.2008, 30.9584, 32.7998, 34.7388, 36.7929] +24-11-19 20:16:31 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:16:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:16:31 | D | sum error = [ 38.8934, 41.1369, 43.4850, 45.9341, 48.5120] +24-11-19 20:16:31 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:16:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:16:31 | D | sum error = [ 51.1918, 54.0087, 56.9479, 60.0067, 63.2202] +24-11-19 20:16:31 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:16:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:16:31 | D | sum error = [ 66.5710, 70.0570, 73.7007, 77.4991, 81.4448] +24-11-19 20:16:31 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:16:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:16:31 | D | sum error = [ 85.5672, 89.8659, 94.3502, 98.9872, 103.8050] +24-11-19 20:16:31 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:16:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:16:31 | D | sum error = [ 108.8136, 113.9961, 119.3809, 124.9679, 130.7178] +24-11-19 20:16:31 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:16:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:16:31 | D | sum error = [ 136.7094, 142.8825, 149.2667, 155.8643, 162.6940] +24-11-19 20:16:31 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:16:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:16:31 | D | sum error = [ 169.6982, 176.9104, 184.3600, 192.0217, 199.8969] +24-11-19 20:16:31 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:16:31 | D | + error = [2.5811] +24-11-19 20:16:32 | D | - Calibrating model.layers.1.mlp.down_proj.weight +24-11-19 20:16:32 | D | + w: sint8 +24-11-19 20:16:32 | D | + x: None +24-11-19 20:16:32 | D | + y: None +24-11-19 20:16:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:16:32 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:16:32 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:16:32 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:16:32 | D | - range ratio = [ 1.0000] +24-11-19 20:16:32 | D | sum error = [ 7.9590] +24-11-19 20:16:32 | D | best error = [ 7.9590] +24-11-19 20:16:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:16:33 | D | sum error = [ 7.9157, 7.8599, 7.6943, 7.6239, 7.6449] +24-11-19 20:16:33 | D | best error = [ 5.3060, 3.5582, 2.5455, 2.0892, 1.8232] +24-11-19 20:16:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:16:33 | D | sum error = [ 7.4926, 7.4258, 7.3341, 7.2714, 7.1535] +24-11-19 20:16:33 | D | best error = [ 1.6383, 1.4976, 1.3850, 1.2994, 1.2109] +24-11-19 20:16:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:16:33 | D | sum error = [ 7.1479, 7.0530, 6.9485, 6.9360, 6.8552] +24-11-19 20:16:33 | D | best error = [ 1.1279, 1.0695, 1.0200, 0.9717, 0.9319] +24-11-19 20:16:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:16:33 | D | sum error = [ 6.6392, 6.5878, 6.6797, 6.4963, 6.3144] +24-11-19 20:16:33 | D | best error = [ 0.9012, 0.8757, 0.8496, 0.8245, 0.8024] +24-11-19 20:16:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:16:33 | D | sum error = [ 6.3766, 6.2336, 6.1570, 6.0931, 6.0143] +24-11-19 20:16:33 | D | best error = [ 0.7824, 0.7624, 0.7423, 0.7271, 0.7084] +24-11-19 20:16:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:16:33 | D | sum error = [ 5.9206, 5.8804, 5.8284, 5.7613, 5.7061] +24-11-19 20:16:33 | D | best error = [ 0.6922, 0.6758, 0.6603, 0.6469, 0.6383] +24-11-19 20:16:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:16:33 | D | sum error = [ 5.8050, 6.0816, 6.5823, 7.5585, 9.0175] +24-11-19 20:16:33 | D | best error = [ 0.6261, 0.6182, 0.6088, 0.6042, 0.5984] +24-11-19 20:16:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:16:33 | D | sum error = [ 10.9589, 13.4599, 16.6622, 20.6219, 25.3742] +24-11-19 20:16:33 | D | best error = [ 0.5931, 0.5879, 0.5845, 0.5819, 0.5809] +24-11-19 20:16:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:16:33 | D | sum error = [ 30.9927, 37.6023, 45.2569, 53.9776, 63.7941] +24-11-19 20:16:33 | D | best error = [ 0.5778, 0.5774, 0.5771, 0.5763, 0.5760] +24-11-19 20:16:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:16:33 | D | sum error = [ 74.6270, 86.4612, 99.1825, 112.7859, 127.1700] +24-11-19 20:16:33 | D | best error = [ 0.5760, 0.5757, 0.5757, 0.5757, 0.5757] +24-11-19 20:16:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:16:33 | D | sum error = [ 142.2477, 157.9375, 174.1428, 190.7955, 207.8451] +24-11-19 20:16:33 | D | best error = [ 0.5756, 0.5755, 0.5755, 0.5754, 0.5754] +24-11-19 20:16:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:16:33 | D | sum error = [ 225.2527, 242.9581, 260.9093, 279.0828, 297.4516] +24-11-19 20:16:33 | D | best error = [ 0.5754, 0.5754, 0.5754, 0.5754, 0.5754] +24-11-19 20:16:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:16:33 | D | sum error = [ 315.9445, 334.5759, 353.3289, 372.1797, 391.1193] +24-11-19 20:16:33 | D | best error = [ 0.5754, 0.5754, 0.5754, 0.5754, 0.5754] +24-11-19 20:16:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:16:33 | D | sum error = [ 410.1271, 429.2160, 448.3446, 467.5505, 486.7679] +24-11-19 20:16:33 | D | best error = [ 0.5754, 0.5754, 0.5754, 0.5754, 0.5754] +24-11-19 20:16:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:16:33 | D | sum error = [ 506.0516, 525.3747, 544.7441, 564.1843, 583.7151] +24-11-19 20:16:33 | D | best error = [ 0.5754, 0.5754, 0.5754, 0.5754, 0.5754] +24-11-19 20:16:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:16:33 | D | sum error = [ 603.3709, 623.1899, 643.2468, 663.6149, 684.3711] +24-11-19 20:16:33 | D | best error = [ 0.5754, 0.5754, 0.5754, 0.5754, 0.5754] +24-11-19 20:16:33 | D | + error = [0.5754] +24-11-19 20:16:33 | D | - Quantizing model.layers.1.self_attn.q_proj.weight +24-11-19 20:16:37 | D | - Quantizing model.layers.1.self_attn.k_proj.weight +24-11-19 20:16:39 | D | - Quantizing model.layers.1.self_attn.v_proj.weight +24-11-19 20:16:41 | D | - Quantizing model.layers.1.self_attn.o_proj.weight +24-11-19 20:16:43 | D | - Quantizing model.layers.1.mlp.up_proj.weight +24-11-19 20:16:49 | D | - Quantizing model.layers.1.mlp.gate_proj.weight +24-11-19 20:16:53 | D | - Quantizing model.layers.1.mlp.down_proj.weight +24-11-19 20:17:03 | D | - Quantizing layer model.layers.2 +24-11-19 20:17:03 | D | - Calibrating model.layers.2.self_attn.q_proj.weight +24-11-19 20:17:03 | D | + w: sint8 +24-11-19 20:17:03 | D | + x: None +24-11-19 20:17:03 | D | + y: None +24-11-19 20:17:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:17:03 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:17:04 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:17:04 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:17:04 | D | - range ratio = [ 1.0000] +24-11-19 20:17:04 | D | sum error = [ 0.7824] +24-11-19 20:17:04 | D | best error = [ 0.7824] +24-11-19 20:17:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:18 | D | sum error = [ 0.7717, 0.7776, 0.7778, 0.7920, 0.8230] +24-11-19 20:17:18 | D | best error = [ 0.7717, 0.7717, 0.7717, 0.7717, 0.7717] +24-11-19 20:17:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:18 | D | sum error = [ 0.8498, 0.8764, 0.9263, 0.9897, 1.0666] +24-11-19 20:17:18 | D | best error = [ 0.7717, 0.7717, 0.7717, 0.7717, 0.7717] +24-11-19 20:17:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:18 | D | sum error = [ 1.1369, 1.2203, 1.3205, 1.4571, 1.5871] +24-11-19 20:17:18 | D | best error = [ 0.7717, 0.7717, 0.7717, 0.7717, 0.7717] +24-11-19 20:17:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:18 | D | sum error = [ 1.7287, 1.9167, 2.1031, 2.3105, 2.5183] +24-11-19 20:17:18 | D | best error = [ 0.7717, 0.7717, 0.7717, 0.7717, 0.7717] +24-11-19 20:17:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:18 | D | sum error = [ 2.7075, 3.0102, 3.2259, 3.6013, 3.9317] +24-11-19 20:17:18 | D | best error = [ 0.7717, 0.7717, 0.7717, 0.7717, 0.7717] +24-11-19 20:17:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:18 | D | sum error = [ 4.3808, 4.7073, 5.1657, 5.6255, 6.1483] +24-11-19 20:17:18 | D | best error = [ 0.7717, 0.7717, 0.7717, 0.7717, 0.7717] +24-11-19 20:17:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:18 | D | sum error = [ 6.7567, 7.3533, 8.0422, 8.7615, 9.6478] +24-11-19 20:17:18 | D | best error = [ 0.7717, 0.7717, 0.7717, 0.7717, 0.7717] +24-11-19 20:17:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:18 | D | sum error = [ 10.5272, 11.4962, 12.6163, 13.7537, 14.9855] +24-11-19 20:17:18 | D | best error = [ 0.7717, 0.7717, 0.7717, 0.7717, 0.7717] +24-11-19 20:17:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:18 | D | sum error = [ 16.4130, 17.9525, 19.5329, 21.3275, 23.2916] +24-11-19 20:17:18 | D | best error = [ 0.7717, 0.7717, 0.7717, 0.7717, 0.7717] +24-11-19 20:17:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:18 | D | sum error = [ 25.4125, 27.7098, 30.2512, 33.0663, 36.0663] +24-11-19 20:17:18 | D | best error = [ 0.7717, 0.7717, 0.7717, 0.7717, 0.7717] +24-11-19 20:17:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:18 | D | sum error = [ 39.2894, 42.8044, 46.6932, 50.9101, 55.4780] +24-11-19 20:17:18 | D | best error = [ 0.7717, 0.7717, 0.7717, 0.7717, 0.7717] +24-11-19 20:17:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:18 | D | sum error = [ 60.4387, 65.8559, 71.7223, 78.0824, 84.9648] +24-11-19 20:17:18 | D | best error = [ 0.7717, 0.7717, 0.7717, 0.7717, 0.7717] +24-11-19 20:17:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:18 | D | sum error = [ 92.3986, 100.5671, 109.2430, 118.7652, 128.9666] +24-11-19 20:17:18 | D | best error = [ 0.7717, 0.7717, 0.7717, 0.7717, 0.7717] +24-11-19 20:17:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:18 | D | sum error = [ 139.9663, 151.8639, 164.7166, 178.5391, 193.4172] +24-11-19 20:17:18 | D | best error = [ 0.7717, 0.7717, 0.7717, 0.7717, 0.7717] +24-11-19 20:17:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:18 | D | sum error = [ 209.3897, 226.5533, 245.0654, 264.8944, 286.4688] +24-11-19 20:17:18 | D | best error = [ 0.7717, 0.7717, 0.7717, 0.7717, 0.7717] +24-11-19 20:17:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:18 | D | sum error = [ 309.6568, 334.3990, 360.9555, 389.1157, 419.0835] +24-11-19 20:17:18 | D | best error = [ 0.7717, 0.7717, 0.7717, 0.7717, 0.7717] +24-11-19 20:17:18 | D | + error = [0.7717] +24-11-19 20:17:18 | D | - Calibrating model.layers.2.self_attn.k_proj.weight +24-11-19 20:17:18 | D | + w: sint8 +24-11-19 20:17:18 | D | + x: None +24-11-19 20:17:18 | D | + y: None +24-11-19 20:17:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:17:18 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:17:19 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:17:19 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:17:19 | D | - range ratio = [ 1.0000] +24-11-19 20:17:19 | D | sum error = [ 1.0477] +24-11-19 20:17:19 | D | best error = [ 1.0477] +24-11-19 20:17:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:34 | D | sum error = [ 0.9135, 0.9192, 0.8229, 0.8926, 1.1831] +24-11-19 20:17:34 | D | best error = [ 0.9135, 0.9135, 0.8229, 0.8229, 0.8229] +24-11-19 20:17:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:34 | D | sum error = [ 1.0690, 0.9818, 1.1710, 1.1685, 1.3064] +24-11-19 20:17:34 | D | best error = [ 0.8229, 0.8229, 0.8229, 0.8229, 0.8229] +24-11-19 20:17:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:34 | D | sum error = [ 1.2232, 1.3377, 1.5254, 1.7615, 1.7973] +24-11-19 20:17:34 | D | best error = [ 0.8229, 0.8229, 0.8229, 0.8229, 0.8229] +24-11-19 20:17:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:34 | D | sum error = [ 1.8345, 2.1245, 2.3404, 2.5198, 2.5880] +24-11-19 20:17:34 | D | best error = [ 0.8229, 0.8229, 0.8229, 0.8229, 0.8229] +24-11-19 20:17:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:34 | D | sum error = [ 2.8513, 3.0130, 3.2761, 3.4698, 3.9036] +24-11-19 20:17:34 | D | best error = [ 0.8229, 0.8229, 0.8229, 0.8229, 0.8229] +24-11-19 20:17:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:34 | D | sum error = [ 4.1860, 4.5587, 4.8785, 5.3143, 5.8218] +24-11-19 20:17:34 | D | best error = [ 0.8229, 0.8229, 0.8229, 0.8229, 0.8229] +24-11-19 20:17:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:34 | D | sum error = [ 6.4763, 6.9184, 7.6731, 8.3141, 9.0235] +24-11-19 20:17:34 | D | best error = [ 0.8229, 0.8229, 0.8229, 0.8229, 0.8229] +24-11-19 20:17:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:34 | D | sum error = [ 10.1661, 11.0404, 11.9217, 12.8724, 14.1416] +24-11-19 20:17:34 | D | best error = [ 0.8229, 0.8229, 0.8229, 0.8229, 0.8229] +24-11-19 20:17:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:34 | D | sum error = [ 15.4139, 16.9828, 18.4173, 20.2695, 22.1831] +24-11-19 20:17:34 | D | best error = [ 0.8229, 0.8229, 0.8229, 0.8229, 0.8229] +24-11-19 20:17:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:34 | D | sum error = [ 24.2997, 26.5786, 29.2642, 31.8685, 34.7039] +24-11-19 20:17:34 | D | best error = [ 0.8229, 0.8229, 0.8229, 0.8229, 0.8229] +24-11-19 20:17:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:34 | D | sum error = [ 38.0283, 41.5318, 45.3555, 49.6830, 53.6478] +24-11-19 20:17:34 | D | best error = [ 0.8229, 0.8229, 0.8229, 0.8229, 0.8229] +24-11-19 20:17:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:34 | D | sum error = [ 58.9135, 64.3543, 69.7608, 76.8081, 83.0045] +24-11-19 20:17:34 | D | best error = [ 0.8229, 0.8229, 0.8229, 0.8229, 0.8229] +24-11-19 20:17:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:34 | D | sum error = [ 90.7588, 98.6553, 106.8617, 116.3251, 126.3037] +24-11-19 20:17:34 | D | best error = [ 0.8229, 0.8229, 0.8229, 0.8229, 0.8229] +24-11-19 20:17:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:34 | D | sum error = [ 137.7845, 150.2847, 162.6462, 177.6494, 193.2102] +24-11-19 20:17:34 | D | best error = [ 0.8229, 0.8229, 0.8229, 0.8229, 0.8229] +24-11-19 20:17:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:34 | D | sum error = [ 209.3951, 228.1654, 246.8781, 267.7998, 290.9267] +24-11-19 20:17:34 | D | best error = [ 0.8229, 0.8229, 0.8229, 0.8229, 0.8229] +24-11-19 20:17:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:34 | D | sum error = [ 314.3081, 341.2496, 368.1140, 397.2358, 429.1697] +24-11-19 20:17:34 | D | best error = [ 0.8229, 0.8229, 0.8229, 0.8229, 0.8229] +24-11-19 20:17:34 | D | + error = [0.8229] +24-11-19 20:17:34 | D | - Calibrating model.layers.2.self_attn.v_proj.weight +24-11-19 20:17:34 | D | + w: sint8 +24-11-19 20:17:34 | D | + x: None +24-11-19 20:17:34 | D | + y: None +24-11-19 20:17:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:17:34 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:17:34 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:17:34 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:17:34 | D | - range ratio = [ 1.0000] +24-11-19 20:17:34 | D | sum error = [ 0.8205] +24-11-19 20:17:34 | D | best error = [ 0.8205] +24-11-19 20:17:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:35 | D | sum error = [ 0.8166, 0.8108, 0.8089, 0.8218, 0.8328] +24-11-19 20:17:35 | D | best error = [ 0.7552, 0.7304, 0.7184, 0.7126, 0.7094] +24-11-19 20:17:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:35 | D | sum error = [ 0.8651, 0.8976, 0.9324, 0.9729, 1.0205] +24-11-19 20:17:35 | D | best error = [ 0.7072, 0.7067, 0.7065, 0.7065, 0.7065] +24-11-19 20:17:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:35 | D | sum error = [ 1.0815, 1.1516, 1.2346, 1.3097, 1.4000] +24-11-19 20:17:35 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 20:17:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:35 | D | sum error = [ 1.5127, 1.6153, 1.7232, 1.8517, 1.9805] +24-11-19 20:17:35 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 20:17:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:35 | D | sum error = [ 2.1151, 2.2709, 2.4384, 2.6099, 2.7959] +24-11-19 20:17:35 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 20:17:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:35 | D | sum error = [ 2.9917, 3.2026, 3.4188, 3.6548, 3.8907] +24-11-19 20:17:35 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 20:17:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:35 | D | sum error = [ 4.1589, 4.4351, 4.7180, 5.0184, 5.3428] +24-11-19 20:17:35 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 20:17:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:35 | D | sum error = [ 5.6893, 6.0510, 6.4315, 6.8304, 7.2529] +24-11-19 20:17:35 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 20:17:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:35 | D | sum error = [ 7.6970, 8.1624, 8.6492, 9.1594, 9.6982] +24-11-19 20:17:35 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 20:17:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:35 | D | sum error = [ 10.2620, 10.8531, 11.4771, 12.1218, 12.7997] +24-11-19 20:17:35 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 20:17:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:35 | D | sum error = [ 13.5131, 14.2654, 15.0476, 15.8720, 16.7313] +24-11-19 20:17:35 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 20:17:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:35 | D | sum error = [ 17.6222, 18.5603, 19.5330, 20.5605, 21.6281] +24-11-19 20:17:35 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 20:17:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:35 | D | sum error = [ 22.7468, 23.9114, 25.1174, 26.3843, 27.6976] +24-11-19 20:17:35 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 20:17:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:35 | D | sum error = [ 29.0596, 30.4783, 31.9562, 33.4868, 35.0699] +24-11-19 20:17:35 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 20:17:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:35 | D | sum error = [ 36.7137, 38.4199, 40.1864, 42.0147, 43.9057] +24-11-19 20:17:35 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 20:17:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:35 | D | sum error = [ 45.8631, 47.8863, 49.9768, 52.1390, 54.3618] +24-11-19 20:17:35 | D | best error = [ 0.7065, 0.7065, 0.7065, 0.7065, 0.7065] +24-11-19 20:17:35 | D | + error = [0.7065] +24-11-19 20:17:35 | D | - Calibrating model.layers.2.self_attn.o_proj.weight +24-11-19 20:17:35 | D | + w: sint8 +24-11-19 20:17:35 | D | + x: None +24-11-19 20:17:35 | D | + y: None +24-11-19 20:17:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:17:35 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:17:35 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:17:35 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:17:35 | D | - range ratio = [ 1.0000] +24-11-19 20:17:35 | D | sum error = [ 0.1002] +24-11-19 20:17:35 | D | best error = [ 0.1002] +24-11-19 20:17:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:36 | D | sum error = [ 0.0992, 0.0992, 0.1000, 0.1004, 0.1026] +24-11-19 20:17:36 | D | best error = [ 0.0891, 0.0847, 0.0822, 0.0806, 0.0797] +24-11-19 20:17:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:36 | D | sum error = [ 0.1048, 0.1082, 0.1122, 0.1169, 0.1233] +24-11-19 20:17:36 | D | best error = [ 0.0790, 0.0786, 0.0783, 0.0781, 0.0781] +24-11-19 20:17:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:36 | D | sum error = [ 0.1288, 0.1373, 0.1451, 0.1545, 0.1648] +24-11-19 20:17:36 | D | best error = [ 0.0780, 0.0779, 0.0779, 0.0778, 0.0778] +24-11-19 20:17:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:36 | D | sum error = [ 0.1759, 0.1872, 0.1997, 0.2131, 0.2281] +24-11-19 20:17:36 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:17:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:36 | D | sum error = [ 0.2434, 0.2599, 0.2767, 0.2957, 0.3145] +24-11-19 20:17:36 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:17:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:36 | D | sum error = [ 0.3351, 0.3569, 0.3798, 0.4039, 0.4310] +24-11-19 20:17:36 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:17:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:36 | D | sum error = [ 0.4577, 0.4860, 0.5157, 0.5475, 0.5809] +24-11-19 20:17:36 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:17:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:36 | D | sum error = [ 0.6154, 0.6526, 0.6916, 0.7329, 0.7753] +24-11-19 20:17:36 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:17:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:36 | D | sum error = [ 0.8209, 0.8676, 0.9185, 0.9711, 1.0261] +24-11-19 20:17:36 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:17:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:36 | D | sum error = [ 1.0843, 1.1460, 1.2098, 1.2769, 1.3477] +24-11-19 20:17:36 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:17:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:36 | D | sum error = [ 1.4209, 1.4990, 1.5798, 1.6652, 1.7542] +24-11-19 20:17:36 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:17:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:36 | D | sum error = [ 1.8479, 1.9455, 2.0482, 2.1553, 2.2674] +24-11-19 20:17:36 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:17:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:36 | D | sum error = [ 2.3843, 2.5067, 2.6349, 2.7692, 2.9085] +24-11-19 20:17:36 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:17:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:36 | D | sum error = [ 3.0550, 3.2074, 3.3672, 3.5329, 3.7057] +24-11-19 20:17:36 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:17:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:36 | D | sum error = [ 3.8852, 4.0723, 4.2671, 4.4694, 4.6801] +24-11-19 20:17:36 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:17:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:36 | D | sum error = [ 4.8983, 5.1252, 5.3606, 5.6053, 5.8592] +24-11-19 20:17:36 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:17:36 | D | + error = [0.0778] +24-11-19 20:17:36 | D | - Calibrating model.layers.2.mlp.up_proj.weight +24-11-19 20:17:36 | D | + w: sint8 +24-11-19 20:17:36 | D | + x: None +24-11-19 20:17:36 | D | + y: None +24-11-19 20:17:36 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:17:36 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:17:36 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:17:36 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:17:36 | D | - range ratio = [ 1.0000] +24-11-19 20:17:36 | D | sum error = [ 3.5336] +24-11-19 20:17:36 | D | best error = [ 3.5336] +24-11-19 20:17:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:37 | D | sum error = [ 3.5089, 3.5031, 3.5199, 3.5563, 3.6226] +24-11-19 20:17:37 | D | best error = [ 3.2474, 3.1424, 3.0915, 3.0632, 3.0485] +24-11-19 20:17:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:37 | D | sum error = [ 3.7037, 3.8344, 3.9768, 4.1717, 4.3848] +24-11-19 20:17:37 | D | best error = [ 3.0411, 3.0383, 3.0373, 3.0370, 3.0369] +24-11-19 20:17:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:37 | D | sum error = [ 4.6433, 4.9324, 5.2460, 5.5986, 5.9849] +24-11-19 20:17:37 | D | best error = [ 3.0369, 3.0369, 3.0369, 3.0369, 3.0369] +24-11-19 20:17:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:37 | D | sum error = [ 6.4009, 6.8539, 7.3394, 7.8677, 8.4220] +24-11-19 20:17:37 | D | best error = [ 3.0369, 3.0369, 3.0369, 3.0369, 3.0369] +24-11-19 20:17:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:37 | D | sum error = [ 9.0258, 9.6695, 10.3381, 11.0431, 11.8103] +24-11-19 20:17:37 | D | best error = [ 3.0369, 3.0369, 3.0369, 3.0369, 3.0369] +24-11-19 20:17:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:37 | D | sum error = [ 12.6106, 13.4655, 14.3595, 15.3059, 16.2944] +24-11-19 20:17:37 | D | best error = [ 3.0369, 3.0369, 3.0369, 3.0369, 3.0369] +24-11-19 20:17:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:37 | D | sum error = [ 17.3486, 18.4573, 19.6121, 20.8390, 22.1253] +24-11-19 20:17:37 | D | best error = [ 3.0369, 3.0369, 3.0369, 3.0369, 3.0369] +24-11-19 20:17:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:37 | D | sum error = [ 23.4743, 24.8924, 26.3868, 27.9376, 29.5723] +24-11-19 20:17:37 | D | best error = [ 3.0369, 3.0369, 3.0369, 3.0369, 3.0369] +24-11-19 20:17:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:37 | D | sum error = [ 31.2824, 33.0532, 34.9262, 36.8739, 38.8969] +24-11-19 20:17:37 | D | best error = [ 3.0369, 3.0369, 3.0369, 3.0369, 3.0369] +24-11-19 20:17:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:37 | D | sum error = [ 41.0086, 43.2170, 45.5108, 47.8899, 50.3837] +24-11-19 20:17:37 | D | best error = [ 3.0369, 3.0369, 3.0369, 3.0369, 3.0369] +24-11-19 20:17:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:37 | D | sum error = [ 52.9508, 55.6318, 58.4029, 61.2821, 64.2638] +24-11-19 20:17:37 | D | best error = [ 3.0369, 3.0369, 3.0369, 3.0369, 3.0369] +24-11-19 20:17:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:37 | D | sum error = [ 67.3504, 70.5511, 73.8494, 77.2644, 80.7887] +24-11-19 20:17:37 | D | best error = [ 3.0369, 3.0369, 3.0369, 3.0369, 3.0369] +24-11-19 20:17:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:37 | D | sum error = [ 84.4280, 88.1789, 92.0527, 96.0417, 100.1533] +24-11-19 20:17:37 | D | best error = [ 3.0369, 3.0369, 3.0369, 3.0369, 3.0369] +24-11-19 20:17:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:37 | D | sum error = [ 104.3754, 108.7303, 113.1857, 117.7816, 122.4811] +24-11-19 20:17:37 | D | best error = [ 3.0369, 3.0369, 3.0369, 3.0369, 3.0369] +24-11-19 20:17:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:37 | D | sum error = [ 127.3142, 132.2701, 137.3480, 142.5572, 147.8887] +24-11-19 20:17:37 | D | best error = [ 3.0369, 3.0369, 3.0369, 3.0369, 3.0369] +24-11-19 20:17:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:37 | D | sum error = [ 153.3608, 158.9576, 164.7018, 170.5790, 176.6041] +24-11-19 20:17:37 | D | best error = [ 3.0369, 3.0369, 3.0369, 3.0369, 3.0369] +24-11-19 20:17:37 | D | + error = [3.0369] +24-11-19 20:17:38 | D | - Calibrating model.layers.2.mlp.gate_proj.weight +24-11-19 20:17:38 | D | + w: sint8 +24-11-19 20:17:38 | D | + x: None +24-11-19 20:17:38 | D | + y: None +24-11-19 20:17:38 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:17:38 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:17:38 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:17:38 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:17:38 | D | - range ratio = [ 1.0000] +24-11-19 20:17:38 | D | sum error = [ 3.9980] +24-11-19 20:17:38 | D | best error = [ 3.9980] +24-11-19 20:17:39 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:39 | D | sum error = [ 3.9787, 3.9603, 3.9845, 4.0197, 4.0982] +24-11-19 20:17:39 | D | best error = [ 3.6791, 3.5607, 3.5039, 3.4718, 3.4547] +24-11-19 20:17:39 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:39 | D | sum error = [ 4.2016, 4.3490, 4.5202, 4.7272, 4.9827] +24-11-19 20:17:39 | D | best error = [ 3.4468, 3.4437, 3.4427, 3.4424, 3.4423] +24-11-19 20:17:39 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:39 | D | sum error = [ 5.2611, 5.5996, 5.9433, 6.3509, 6.7836] +24-11-19 20:17:39 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:17:39 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:39 | D | sum error = [ 7.2726, 7.7934, 8.3510, 8.9396, 9.5742] +24-11-19 20:17:39 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:17:39 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:39 | D | sum error = [ 10.2558, 10.9923, 11.7529, 12.5644, 13.4403] +24-11-19 20:17:39 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:17:39 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:39 | D | sum error = [ 14.3534, 15.3235, 16.3636, 17.4522, 18.5963] +24-11-19 20:17:39 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:17:39 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:39 | D | sum error = [ 19.8088, 21.0841, 22.4183, 23.8391, 25.3311] +24-11-19 20:17:39 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:17:39 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:39 | D | sum error = [ 26.9097, 28.5592, 30.2878, 32.1125, 34.0179] +24-11-19 20:17:39 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:17:39 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:39 | D | sum error = [ 36.0200, 38.1139, 40.3159, 42.6220, 45.0295] +24-11-19 20:17:39 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:17:39 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:39 | D | sum error = [ 47.5569, 50.2099, 52.9697, 55.8778, 58.8923] +24-11-19 20:17:39 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:17:39 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:39 | D | sum error = [ 62.0536, 65.3527, 68.7919, 72.3748, 76.0956] +24-11-19 20:17:39 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:17:39 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:39 | D | sum error = [ 79.9834, 84.0265, 88.2232, 92.5851, 97.1232] +24-11-19 20:17:39 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:17:39 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:39 | D | sum error = [ 101.8328, 106.7280, 111.7996, 117.0729, 122.5209] +24-11-19 20:17:39 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:17:39 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:39 | D | sum error = [ 128.1654, 134.0273, 140.0560, 146.3138, 152.7700] +24-11-19 20:17:39 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:17:39 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:39 | D | sum error = [ 159.4406, 166.3253, 173.4329, 180.7569, 188.3040] +24-11-19 20:17:39 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:17:39 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:39 | D | sum error = [ 196.0708, 204.0783, 212.3105, 220.7756, 229.4785] +24-11-19 20:17:39 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:17:39 | D | + error = [3.4423] +24-11-19 20:17:40 | D | - Calibrating model.layers.2.mlp.down_proj.weight +24-11-19 20:17:40 | D | + w: sint8 +24-11-19 20:17:40 | D | + x: None +24-11-19 20:17:40 | D | + y: None +24-11-19 20:17:40 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:17:40 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:17:40 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:17:40 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:17:40 | D | - range ratio = [ 1.0000] +24-11-19 20:17:40 | D | sum error = [ 0.2097] +24-11-19 20:17:40 | D | best error = [ 0.2097] +24-11-19 20:17:41 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:41 | D | sum error = [ 0.2077, 0.2059, 0.2046, 0.2036, 0.2034] +24-11-19 20:17:41 | D | best error = [ 0.2027, 0.1991, 0.1964, 0.1945, 0.1930] +24-11-19 20:17:41 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:41 | D | sum error = [ 0.2029, 0.2035, 0.2046, 0.2068, 0.2094] +24-11-19 20:17:41 | D | best error = [ 0.1916, 0.1905, 0.1896, 0.1889, 0.1884] +24-11-19 20:17:41 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:41 | D | sum error = [ 0.2133, 0.2179, 0.2240, 0.2309, 0.2392] +24-11-19 20:17:41 | D | best error = [ 0.1880, 0.1878, 0.1876, 0.1874, 0.1873] +24-11-19 20:17:41 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:41 | D | sum error = [ 0.2496, 0.2608, 0.2740, 0.2886, 0.3048] +24-11-19 20:17:41 | D | best error = [ 0.1872, 0.1872, 0.1871, 0.1871, 0.1871] +24-11-19 20:17:41 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:41 | D | sum error = [ 0.3228, 0.3431, 0.3651, 0.3891, 0.4153] +24-11-19 20:17:41 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:17:41 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:41 | D | sum error = [ 0.4439, 0.4744, 0.5074, 0.5433, 0.5813] +24-11-19 20:17:41 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:17:41 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:41 | D | sum error = [ 0.6226, 0.6662, 0.7134, 0.7634, 0.8169] +24-11-19 20:17:41 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:17:41 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:41 | D | sum error = [ 0.8739, 0.9347, 0.9994, 1.0678, 1.1406] +24-11-19 20:17:41 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:17:41 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:41 | D | sum error = [ 1.2179, 1.2997, 1.3866, 1.4784, 1.5758] +24-11-19 20:17:41 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:17:41 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:41 | D | sum error = [ 1.6789, 1.7876, 1.9025, 2.0236, 2.1516] +24-11-19 20:17:41 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:17:41 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:41 | D | sum error = [ 2.2862, 2.4284, 2.5776, 2.7348, 2.9003] +24-11-19 20:17:41 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:17:41 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:41 | D | sum error = [ 3.0740, 3.2563, 3.4476, 3.6480, 3.8589] +24-11-19 20:17:41 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:17:41 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:41 | D | sum error = [ 4.0791, 4.3100, 4.5521, 4.8053, 5.0701] +24-11-19 20:17:41 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:17:41 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:41 | D | sum error = [ 5.3471, 5.6362, 5.9380, 6.2532, 6.5808] +24-11-19 20:17:41 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:17:41 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:41 | D | sum error = [ 6.9223, 7.2777, 7.6474, 8.0317, 8.4307] +24-11-19 20:17:41 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:17:41 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:41 | D | sum error = [ 8.8447, 9.2736, 9.7180, 10.1776, 10.6534] +24-11-19 20:17:41 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:17:41 | D | + error = [0.1871] +24-11-19 20:17:41 | D | - Quantizing model.layers.2.self_attn.q_proj.weight +24-11-19 20:17:42 | D | - Quantizing model.layers.2.self_attn.k_proj.weight +24-11-19 20:17:44 | D | - Quantizing model.layers.2.self_attn.v_proj.weight +24-11-19 20:17:45 | D | - Quantizing model.layers.2.self_attn.o_proj.weight +24-11-19 20:17:46 | D | - Quantizing model.layers.2.mlp.up_proj.weight +24-11-19 20:17:47 | D | - Quantizing model.layers.2.mlp.gate_proj.weight +24-11-19 20:17:48 | D | - Quantizing model.layers.2.mlp.down_proj.weight +24-11-19 20:17:59 | D | - Quantizing layer model.layers.3 +24-11-19 20:17:59 | D | - Calibrating model.layers.3.self_attn.q_proj.weight +24-11-19 20:17:59 | D | + w: sint8 +24-11-19 20:17:59 | D | + x: None +24-11-19 20:17:59 | D | + y: None +24-11-19 20:17:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:17:59 | D | + finished parsing calibration arguments, ram usage: 14.2 +24-11-19 20:17:59 | D | + finished reseting calibrator, ram usage: 14.2 +24-11-19 20:17:59 | D | + finished calculating the original outputs, ram usage: 14.2 +24-11-19 20:17:59 | D | - range ratio = [ 1.0000] +24-11-19 20:17:59 | D | sum error = [ 1.1055] +24-11-19 20:17:59 | D | best error = [ 1.1055] +24-11-19 20:18:11 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:11 | D | sum error = [ 1.1161, 1.0769, 1.0737, 1.1088, 1.1272] +24-11-19 20:18:11 | D | best error = [ 1.1055, 1.0769, 1.0737, 1.0737, 1.0737] +24-11-19 20:18:11 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:11 | D | sum error = [ 1.1446, 1.2365, 1.2804, 1.3654, 1.4650] +24-11-19 20:18:11 | D | best error = [ 1.0737, 1.0737, 1.0737, 1.0737, 1.0737] +24-11-19 20:18:11 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:11 | D | sum error = [ 1.6351, 1.7141, 1.9569, 2.1118, 2.3096] +24-11-19 20:18:11 | D | best error = [ 1.0737, 1.0737, 1.0737, 1.0737, 1.0737] +24-11-19 20:18:11 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:11 | D | sum error = [ 2.5287, 2.8027, 3.1217, 3.4914, 3.8075] +24-11-19 20:18:11 | D | best error = [ 1.0737, 1.0737, 1.0737, 1.0737, 1.0737] +24-11-19 20:18:11 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:11 | D | sum error = [ 4.2938, 4.6092, 5.1884, 5.7683, 6.4307] +24-11-19 20:18:11 | D | best error = [ 1.0737, 1.0737, 1.0737, 1.0737, 1.0737] +24-11-19 20:18:11 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:11 | D | sum error = [ 7.1315, 7.7777, 8.5674, 9.5438, 10.4645] +24-11-19 20:18:11 | D | best error = [ 1.0737, 1.0737, 1.0737, 1.0737, 1.0737] +24-11-19 20:18:11 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:11 | D | sum error = [ 11.5408, 12.6808, 13.9380, 15.4190, 16.8937] +24-11-19 20:18:11 | D | best error = [ 1.0737, 1.0737, 1.0737, 1.0737, 1.0737] +24-11-19 20:18:11 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:11 | D | sum error = [ 18.6423, 20.5979, 22.5233, 24.7737, 27.1876] +24-11-19 20:18:11 | D | best error = [ 1.0737, 1.0737, 1.0737, 1.0737, 1.0737] +24-11-19 20:18:11 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:11 | D | sum error = [ 29.9408, 32.8508, 35.9449, 39.4331, 43.0646] +24-11-19 20:18:11 | D | best error = [ 1.0737, 1.0737, 1.0737, 1.0737, 1.0737] +24-11-19 20:18:11 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:11 | D | sum error = [ 46.9748, 51.1630, 55.6770, 60.5973, 65.9134] +24-11-19 20:18:11 | D | best error = [ 1.0737, 1.0737, 1.0737, 1.0737, 1.0737] +24-11-19 20:18:11 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:11 | D | sum error = [ 71.5745, 77.6984, 84.2502, 91.1477, 98.4885] +24-11-19 20:18:11 | D | best error = [ 1.0737, 1.0737, 1.0737, 1.0737, 1.0737] +24-11-19 20:18:11 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:11 | D | sum error = [ 106.6980, 115.3626, 124.5842, 134.5268, 145.1295] +24-11-19 20:18:11 | D | best error = [ 1.0737, 1.0737, 1.0737, 1.0737, 1.0737] +24-11-19 20:18:11 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:11 | D | sum error = [ 156.4667, 168.5039, 181.3009, 194.9852, 209.5694] +24-11-19 20:18:11 | D | best error = [ 1.0737, 1.0737, 1.0737, 1.0737, 1.0737] +24-11-19 20:18:11 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:11 | D | sum error = [ 225.1143, 241.4413, 258.8614, 277.3791, 296.7756] +24-11-19 20:18:11 | D | best error = [ 1.0737, 1.0737, 1.0737, 1.0737, 1.0737] +24-11-19 20:18:11 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:11 | D | sum error = [ 317.4059, 338.9864, 361.5809, 384.9948, 409.3816] +24-11-19 20:18:11 | D | best error = [ 1.0737, 1.0737, 1.0737, 1.0737, 1.0737] +24-11-19 20:18:11 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:11 | D | sum error = [ 434.3189, 459.9702, 486.1409, 512.3972, 538.9556] +24-11-19 20:18:11 | D | best error = [ 1.0737, 1.0737, 1.0737, 1.0737, 1.0737] +24-11-19 20:18:11 | D | + error = [1.0737] +24-11-19 20:18:11 | D | - Calibrating model.layers.3.self_attn.k_proj.weight +24-11-19 20:18:11 | D | + w: sint8 +24-11-19 20:18:11 | D | + x: None +24-11-19 20:18:11 | D | + y: None +24-11-19 20:18:11 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:18:11 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:18:11 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:18:11 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:18:12 | D | - range ratio = [ 1.0000] +24-11-19 20:18:12 | D | sum error = [ 1.3398] +24-11-19 20:18:12 | D | best error = [ 1.3398] +24-11-19 20:18:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:25 | D | sum error = [ 1.2116, 1.1695, 1.3091, 1.2488, 1.2221] +24-11-19 20:18:25 | D | best error = [ 1.2116, 1.1695, 1.1695, 1.1695, 1.1695] +24-11-19 20:18:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:25 | D | sum error = [ 1.5822, 1.5165, 1.6732, 1.5543, 1.5805] +24-11-19 20:18:25 | D | best error = [ 1.1695, 1.1695, 1.1695, 1.1695, 1.1695] +24-11-19 20:18:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:25 | D | sum error = [ 1.7520, 2.2119, 2.1970, 2.5096, 2.6618] +24-11-19 20:18:25 | D | best error = [ 1.1695, 1.1695, 1.1695, 1.1695, 1.1695] +24-11-19 20:18:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:25 | D | sum error = [ 3.2793, 3.6771, 3.8477, 4.1126, 4.6209] +24-11-19 20:18:25 | D | best error = [ 1.1695, 1.1695, 1.1695, 1.1695, 1.1695] +24-11-19 20:18:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:25 | D | sum error = [ 4.9845, 5.7219, 6.1674, 6.8073, 7.3770] +24-11-19 20:18:25 | D | best error = [ 1.1695, 1.1695, 1.1695, 1.1695, 1.1695] +24-11-19 20:18:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:25 | D | sum error = [ 8.0779, 8.6250, 9.6037, 10.2752, 11.3650] +24-11-19 20:18:25 | D | best error = [ 1.1695, 1.1695, 1.1695, 1.1695, 1.1695] +24-11-19 20:18:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:25 | D | sum error = [ 12.6328, 13.7640, 14.9783, 16.5988, 18.0039] +24-11-19 20:18:25 | D | best error = [ 1.1695, 1.1695, 1.1695, 1.1695, 1.1695] +24-11-19 20:18:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:25 | D | sum error = [ 19.8300, 21.4329, 23.2058, 25.9113, 27.9470] +24-11-19 20:18:25 | D | best error = [ 1.1695, 1.1695, 1.1695, 1.1695, 1.1695] +24-11-19 20:18:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:25 | D | sum error = [ 30.7888, 33.4413, 36.3879, 39.7438, 43.7496] +24-11-19 20:18:25 | D | best error = [ 1.1695, 1.1695, 1.1695, 1.1695, 1.1695] +24-11-19 20:18:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:25 | D | sum error = [ 47.4593, 51.9902, 56.5599, 61.9235, 67.4168] +24-11-19 20:18:25 | D | best error = [ 1.1695, 1.1695, 1.1695, 1.1695, 1.1695] +24-11-19 20:18:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:25 | D | sum error = [ 73.8428, 80.9186, 87.6369, 95.4402, 104.5396] +24-11-19 20:18:25 | D | best error = [ 1.1695, 1.1695, 1.1695, 1.1695, 1.1695] +24-11-19 20:18:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:25 | D | sum error = [ 112.9983, 122.3572, 132.9854, 144.0848, 156.1166] +24-11-19 20:18:25 | D | best error = [ 1.1695, 1.1695, 1.1695, 1.1695, 1.1695] +24-11-19 20:18:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:25 | D | sum error = [ 168.5699, 182.0922, 196.7739, 211.1244, 227.8019] +24-11-19 20:18:25 | D | best error = [ 1.1695, 1.1695, 1.1695, 1.1695, 1.1695] +24-11-19 20:18:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:25 | D | sum error = [ 244.3134, 261.8899, 281.1860, 301.0200, 321.4950] +24-11-19 20:18:25 | D | best error = [ 1.1695, 1.1695, 1.1695, 1.1695, 1.1695] +24-11-19 20:18:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:25 | D | sum error = [ 344.5455, 367.0475, 391.0553, 416.3540, 441.6685] +24-11-19 20:18:25 | D | best error = [ 1.1695, 1.1695, 1.1695, 1.1695, 1.1695] +24-11-19 20:18:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:25 | D | sum error = [ 467.1036, 492.7950, 520.5034, 545.4494, 570.8862] +24-11-19 20:18:25 | D | best error = [ 1.1695, 1.1695, 1.1695, 1.1695, 1.1695] +24-11-19 20:18:25 | D | + error = [1.1695] +24-11-19 20:18:25 | D | - Calibrating model.layers.3.self_attn.v_proj.weight +24-11-19 20:18:25 | D | + w: sint8 +24-11-19 20:18:25 | D | + x: None +24-11-19 20:18:25 | D | + y: None +24-11-19 20:18:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:25 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:18:25 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:18:25 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:18:25 | D | - range ratio = [ 1.0000] +24-11-19 20:18:25 | D | sum error = [ 1.1202] +24-11-19 20:18:25 | D | best error = [ 1.1202] +24-11-19 20:18:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:25 | D | sum error = [ 1.1038, 1.1015, 1.1164, 1.1282, 1.1469] +24-11-19 20:18:25 | D | best error = [ 1.0294, 0.9987, 0.9838, 0.9763, 0.9716] +24-11-19 20:18:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:25 | D | sum error = [ 1.1881, 1.2076, 1.2721, 1.3148, 1.3862] +24-11-19 20:18:25 | D | best error = [ 0.9689, 0.9681, 0.9675, 0.9674, 0.9674] +24-11-19 20:18:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:25 | D | sum error = [ 1.4581, 1.5489, 1.6524, 1.7698, 1.8787] +24-11-19 20:18:25 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:18:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:25 | D | sum error = [ 2.0078, 2.1546, 2.2971, 2.4628, 2.6344] +24-11-19 20:18:25 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:18:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:25 | D | sum error = [ 2.8179, 3.0162, 3.2291, 3.4557, 3.6961] +24-11-19 20:18:25 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:18:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:25 | D | sum error = [ 3.9540, 4.2226, 4.5091, 4.8163, 5.1364] +24-11-19 20:18:25 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:18:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:25 | D | sum error = [ 5.4757, 5.8408, 6.2142, 6.6092, 7.0351] +24-11-19 20:18:25 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:18:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:25 | D | sum error = [ 7.4762, 7.9476, 8.4231, 8.9329, 9.4622] +24-11-19 20:18:25 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:18:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:25 | D | sum error = [ 10.0349, 10.6158, 11.2391, 11.8918, 12.5844] +24-11-19 20:18:25 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:18:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:25 | D | sum error = [ 13.3004, 14.0560, 14.8524, 15.6791, 16.5374] +24-11-19 20:18:25 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:18:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:25 | D | sum error = [ 17.4494, 18.3950, 19.3821, 20.4120, 21.4901] +24-11-19 20:18:25 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:18:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:25 | D | sum error = [ 22.6143, 23.7925, 25.0131, 26.2965, 27.6232] +24-11-19 20:18:25 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:18:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:25 | D | sum error = [ 29.0139, 30.4526, 31.9529, 33.5149, 35.1377] +24-11-19 20:18:25 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:18:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:25 | D | sum error = [ 36.8225, 38.5732, 40.3786, 42.2523, 44.1974] +24-11-19 20:18:25 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:18:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:25 | D | sum error = [ 46.2036, 48.2846, 50.4309, 52.6448, 54.9217] +24-11-19 20:18:25 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:18:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:25 | D | sum error = [ 57.2724, 59.6945, 62.1821, 64.7450, 67.3935] +24-11-19 20:18:25 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:18:25 | D | + error = [0.9674] +24-11-19 20:18:25 | D | - Calibrating model.layers.3.self_attn.o_proj.weight +24-11-19 20:18:25 | D | + w: sint8 +24-11-19 20:18:25 | D | + x: None +24-11-19 20:18:25 | D | + y: None +24-11-19 20:18:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:25 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:18:25 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:18:26 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:18:26 | D | - range ratio = [ 1.0000] +24-11-19 20:18:26 | D | sum error = [ 0.1798] +24-11-19 20:18:26 | D | best error = [ 0.1798] +24-11-19 20:18:26 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:26 | D | sum error = [ 0.1783, 0.1778, 0.1776, 0.1780, 0.1803] +24-11-19 20:18:26 | D | best error = [ 0.1672, 0.1616, 0.1581, 0.1557, 0.1542] +24-11-19 20:18:26 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:26 | D | sum error = [ 0.1819, 0.1860, 0.1905, 0.1969, 0.2034] +24-11-19 20:18:26 | D | best error = [ 0.1530, 0.1522, 0.1516, 0.1513, 0.1510] +24-11-19 20:18:26 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:26 | D | sum error = [ 0.2122, 0.2227, 0.2330, 0.2460, 0.2596] +24-11-19 20:18:26 | D | best error = [ 0.1509, 0.1508, 0.1507, 0.1506, 0.1505] +24-11-19 20:18:26 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:26 | D | sum error = [ 0.2748, 0.2923, 0.3100, 0.3300, 0.3510] +24-11-19 20:18:26 | D | best error = [ 0.1505, 0.1505, 0.1505, 0.1505, 0.1505] +24-11-19 20:18:26 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:26 | D | sum error = [ 0.3738, 0.3981, 0.4251, 0.4532, 0.4831] +24-11-19 20:18:26 | D | best error = [ 0.1505, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:18:26 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:26 | D | sum error = [ 0.5150, 0.5485, 0.5842, 0.6229, 0.6642] +24-11-19 20:18:26 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:18:26 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:26 | D | sum error = [ 0.7065, 0.7524, 0.8001, 0.8510, 0.9045] +24-11-19 20:18:26 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:18:26 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:26 | D | sum error = [ 0.9613, 1.0208, 1.0846, 1.1514, 1.2214] +24-11-19 20:18:26 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:18:26 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:26 | D | sum error = [ 1.2949, 1.3728, 1.4553, 1.5423, 1.6332] +24-11-19 20:18:26 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:18:26 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:26 | D | sum error = [ 1.7295, 1.8308, 1.9369, 2.0489, 2.1671] +24-11-19 20:18:26 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:18:26 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:26 | D | sum error = [ 2.2898, 2.4202, 2.5566, 2.6997, 2.8496] +24-11-19 20:18:26 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:18:26 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:26 | D | sum error = [ 3.0068, 3.1712, 3.3439, 3.5247, 3.7139] +24-11-19 20:18:26 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:18:26 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:26 | D | sum error = [ 3.9115, 4.1187, 4.3353, 4.5608, 4.7965] +24-11-19 20:18:26 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:18:26 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:26 | D | sum error = [ 5.0420, 5.2982, 5.5651, 5.8437, 6.1334] +24-11-19 20:18:26 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:18:26 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:26 | D | sum error = [ 6.4357, 6.7497, 7.0762, 7.4156, 7.7677] +24-11-19 20:18:26 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:18:26 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:26 | D | sum error = [ 8.1322, 8.5103, 8.9017, 9.3069, 9.7260] +24-11-19 20:18:26 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:18:26 | D | + error = [0.1504] +24-11-19 20:18:26 | D | - Calibrating model.layers.3.mlp.up_proj.weight +24-11-19 20:18:26 | D | + w: sint8 +24-11-19 20:18:26 | D | + x: None +24-11-19 20:18:26 | D | + y: None +24-11-19 20:18:26 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:26 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:18:26 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:18:26 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:18:26 | D | - range ratio = [ 1.0000] +24-11-19 20:18:26 | D | sum error = [ 3.8858] +24-11-19 20:18:26 | D | best error = [ 3.8858] +24-11-19 20:18:28 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:28 | D | sum error = [ 3.8495, 3.8298, 3.8438, 3.9054, 3.9737] +24-11-19 20:18:28 | D | best error = [ 3.5705, 3.4572, 3.4000, 3.3710, 3.3552] +24-11-19 20:18:28 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:28 | D | sum error = [ 4.0746, 4.2113, 4.3825, 4.5747, 4.8262] +24-11-19 20:18:28 | D | best error = [ 3.3480, 3.3448, 3.3439, 3.3436, 3.3435] +24-11-19 20:18:28 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:28 | D | sum error = [ 5.1139, 5.4051, 5.7598, 6.1635, 6.5766] +24-11-19 20:18:28 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 20:18:28 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:28 | D | sum error = [ 7.0281, 7.5319, 8.0673, 8.6491, 9.2538] +24-11-19 20:18:28 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 20:18:28 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:28 | D | sum error = [ 9.9231, 10.6267, 11.3770, 12.1681, 12.9935] +24-11-19 20:18:28 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 20:18:28 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:28 | D | sum error = [ 13.8947, 14.8313, 15.8232, 16.8647, 17.9754] +24-11-19 20:18:28 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 20:18:28 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:28 | D | sum error = [ 19.1255, 20.3585, 21.6464, 23.0087, 24.4219] +24-11-19 20:18:28 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 20:18:28 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:28 | D | sum error = [ 25.9166, 27.5021, 29.1570, 30.8857, 32.7117] +24-11-19 20:18:28 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 20:18:28 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:28 | D | sum error = [ 34.6083, 36.5923, 38.6801, 40.8624, 43.1335] +24-11-19 20:18:28 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 20:18:28 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:28 | D | sum error = [ 45.5005, 47.9878, 50.5666, 53.2684, 56.0743] +24-11-19 20:18:28 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 20:18:28 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:28 | D | sum error = [ 58.9893, 62.0306, 65.2002, 68.4724, 71.8889] +24-11-19 20:18:28 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 20:18:28 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:28 | D | sum error = [ 75.4248, 79.0978, 82.8955, 86.8376, 90.9211] +24-11-19 20:18:28 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 20:18:28 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:28 | D | sum error = [ 95.1526, 99.5300, 104.0584, 108.7451, 113.5770] +24-11-19 20:18:28 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 20:18:28 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:28 | D | sum error = [ 118.5642, 123.7167, 129.0106, 134.4874, 140.1172] +24-11-19 20:18:28 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 20:18:28 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:28 | D | sum error = [ 145.9276, 151.9052, 158.0568, 164.3821, 170.8889] +24-11-19 20:18:28 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 20:18:28 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:28 | D | sum error = [ 177.5804, 184.4588, 191.5196, 198.7798, 206.2363] +24-11-19 20:18:28 | D | best error = [ 3.3435, 3.3435, 3.3435, 3.3435, 3.3435] +24-11-19 20:18:28 | D | + error = [3.3435] +24-11-19 20:18:28 | D | - Calibrating model.layers.3.mlp.gate_proj.weight +24-11-19 20:18:28 | D | + w: sint8 +24-11-19 20:18:28 | D | + x: None +24-11-19 20:18:28 | D | + y: None +24-11-19 20:18:28 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:28 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:18:28 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:18:28 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:18:28 | D | - range ratio = [ 1.0000] +24-11-19 20:18:28 | D | sum error = [ 4.7580] +24-11-19 20:18:28 | D | best error = [ 4.7580] +24-11-19 20:18:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:29 | D | sum error = [ 4.7182, 4.7077, 4.7267, 4.7779, 4.8630] +24-11-19 20:18:29 | D | best error = [ 4.3768, 4.2405, 4.1707, 4.1337, 4.1127] +24-11-19 20:18:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:29 | D | sum error = [ 4.9953, 5.1655, 5.3741, 5.6176, 5.9281] +24-11-19 20:18:29 | D | best error = [ 4.1042, 4.1001, 4.0989, 4.0985, 4.0985] +24-11-19 20:18:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:29 | D | sum error = [ 6.2571, 6.6472, 7.0702, 7.5707, 8.0796] +24-11-19 20:18:29 | D | best error = [ 4.0985, 4.0985, 4.0985, 4.0985, 4.0985] +24-11-19 20:18:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:29 | D | sum error = [ 8.6595, 9.2766, 9.9357, 10.6677, 11.4207] +24-11-19 20:18:29 | D | best error = [ 4.0985, 4.0985, 4.0985, 4.0985, 4.0985] +24-11-19 20:18:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:29 | D | sum error = [ 12.2457, 13.1136, 14.0545, 15.0399, 16.0879] +24-11-19 20:18:29 | D | best error = [ 4.0985, 4.0985, 4.0985, 4.0985, 4.0985] +24-11-19 20:18:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:29 | D | sum error = [ 17.1969, 18.3752, 19.6289, 20.9564, 22.3439] +24-11-19 20:18:29 | D | best error = [ 4.0985, 4.0985, 4.0985, 4.0985, 4.0985] +24-11-19 20:18:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:29 | D | sum error = [ 23.8259, 25.3891, 27.0400, 28.7878, 30.6369] +24-11-19 20:18:29 | D | best error = [ 4.0985, 4.0985, 4.0985, 4.0985, 4.0985] +24-11-19 20:18:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:29 | D | sum error = [ 32.5807, 34.6026, 36.7704, 39.0535, 41.4396] +24-11-19 20:18:29 | D | best error = [ 4.0985, 4.0985, 4.0985, 4.0985, 4.0985] +24-11-19 20:18:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:29 | D | sum error = [ 43.9653, 46.6408, 49.4269, 52.3520, 55.4587] +24-11-19 20:18:29 | D | best error = [ 4.0985, 4.0985, 4.0985, 4.0985, 4.0985] +24-11-19 20:18:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:29 | D | sum error = [ 58.7164, 62.1325, 65.7023, 69.4850, 73.4441] +24-11-19 20:18:29 | D | best error = [ 4.0985, 4.0985, 4.0985, 4.0985, 4.0985] +24-11-19 20:18:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:29 | D | sum error = [ 77.5841, 81.9385, 86.5063, 91.2876, 96.2977] +24-11-19 20:18:29 | D | best error = [ 4.0985, 4.0985, 4.0985, 4.0985, 4.0985] +24-11-19 20:18:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:29 | D | sum error = [ 101.5214, 107.0065, 112.7241, 118.7088, 124.9519] +24-11-19 20:18:29 | D | best error = [ 4.0985, 4.0985, 4.0985, 4.0985, 4.0985] +24-11-19 20:18:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:29 | D | sum error = [ 131.4720, 138.2526, 145.3372, 152.7048, 160.3839] +24-11-19 20:18:29 | D | best error = [ 4.0985, 4.0985, 4.0985, 4.0985, 4.0985] +24-11-19 20:18:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:29 | D | sum error = [ 168.3540, 176.6415, 185.2601, 194.2061, 203.4959] +24-11-19 20:18:29 | D | best error = [ 4.0985, 4.0985, 4.0985, 4.0985, 4.0985] +24-11-19 20:18:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:29 | D | sum error = [ 213.1267, 223.1147, 233.4587, 244.1762, 255.2399] +24-11-19 20:18:29 | D | best error = [ 4.0985, 4.0985, 4.0985, 4.0985, 4.0985] +24-11-19 20:18:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:29 | D | sum error = [ 266.6803, 278.4838, 290.6468, 303.1751, 316.0770] +24-11-19 20:18:29 | D | best error = [ 4.0985, 4.0985, 4.0985, 4.0985, 4.0985] +24-11-19 20:18:29 | D | + error = [4.0985] +24-11-19 20:18:29 | D | - Calibrating model.layers.3.mlp.down_proj.weight +24-11-19 20:18:29 | D | + w: sint8 +24-11-19 20:18:29 | D | + x: None +24-11-19 20:18:29 | D | + y: None +24-11-19 20:18:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:29 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:18:29 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:18:30 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:18:30 | D | - range ratio = [ 1.0000] +24-11-19 20:18:30 | D | sum error = [ 0.2974] +24-11-19 20:18:30 | D | best error = [ 0.2974] +24-11-19 20:18:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:31 | D | sum error = [ 0.2938, 0.2916, 0.2897, 0.2884, 0.2877] +24-11-19 20:18:31 | D | best error = [ 0.2868, 0.2813, 0.2776, 0.2749, 0.2725] +24-11-19 20:18:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:31 | D | sum error = [ 0.2869, 0.2877, 0.2891, 0.2921, 0.2957] +24-11-19 20:18:31 | D | best error = [ 0.2705, 0.2689, 0.2676, 0.2667, 0.2660] +24-11-19 20:18:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:31 | D | sum error = [ 0.3008, 0.3074, 0.3158, 0.3259, 0.3375] +24-11-19 20:18:31 | D | best error = [ 0.2655, 0.2652, 0.2649, 0.2648, 0.2647] +24-11-19 20:18:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:31 | D | sum error = [ 0.3516, 0.3679, 0.3867, 0.4074, 0.4306] +24-11-19 20:18:31 | D | best error = [ 0.2646, 0.2646, 0.2645, 0.2645, 0.2645] +24-11-19 20:18:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:31 | D | sum error = [ 0.4566, 0.4854, 0.5165, 0.5507, 0.5888] +24-11-19 20:18:31 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 20:18:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:31 | D | sum error = [ 0.6297, 0.6735, 0.7208, 0.7714, 0.8260] +24-11-19 20:18:31 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 20:18:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:31 | D | sum error = [ 0.8843, 0.9475, 1.0139, 1.0858, 1.1614] +24-11-19 20:18:31 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 20:18:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:31 | D | sum error = [ 1.2423, 1.3282, 1.4192, 1.5160, 1.6184] +24-11-19 20:18:31 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 20:18:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:31 | D | sum error = [ 1.7274, 1.8430, 1.9650, 2.0948, 2.2321] +24-11-19 20:18:31 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 20:18:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:31 | D | sum error = [ 2.3768, 2.5298, 2.6909, 2.8611, 3.0404] +24-11-19 20:18:31 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 20:18:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:31 | D | sum error = [ 3.2293, 3.4286, 3.6385, 3.8595, 4.0909] +24-11-19 20:18:31 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 20:18:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:31 | D | sum error = [ 4.3350, 4.5906, 4.8594, 5.1416, 5.4365] +24-11-19 20:18:31 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 20:18:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:31 | D | sum error = [ 5.7458, 6.0698, 6.4087, 6.7633, 7.1341] +24-11-19 20:18:31 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 20:18:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:31 | D | sum error = [ 7.5210, 7.9259, 8.3473, 8.7876, 9.2450] +24-11-19 20:18:31 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 20:18:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:31 | D | sum error = [ 9.7218, 10.2176, 10.7336, 11.2697, 11.8265] +24-11-19 20:18:31 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 20:18:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:31 | D | sum error = [ 12.4038, 13.0026, 13.6227, 14.2642, 14.9285] +24-11-19 20:18:31 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 20:18:31 | D | + error = [0.2645] +24-11-19 20:18:31 | D | - Quantizing model.layers.3.self_attn.q_proj.weight +24-11-19 20:18:32 | D | - Quantizing model.layers.3.self_attn.k_proj.weight +24-11-19 20:18:33 | D | - Quantizing model.layers.3.self_attn.v_proj.weight +24-11-19 20:18:34 | D | - Quantizing model.layers.3.self_attn.o_proj.weight +24-11-19 20:18:35 | D | - Quantizing model.layers.3.mlp.up_proj.weight +24-11-19 20:18:36 | D | - Quantizing model.layers.3.mlp.gate_proj.weight +24-11-19 20:18:37 | D | - Quantizing model.layers.3.mlp.down_proj.weight +24-11-19 20:18:47 | D | - Quantizing layer model.layers.4 +24-11-19 20:18:47 | D | - Calibrating model.layers.4.self_attn.q_proj.weight +24-11-19 20:18:47 | D | + w: sint8 +24-11-19 20:18:47 | D | + x: None +24-11-19 20:18:47 | D | + y: None +24-11-19 20:18:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:18:47 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:18:47 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:18:48 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:18:48 | D | - range ratio = [ 1.0000] +24-11-19 20:18:48 | D | sum error = [ 1.4115] +24-11-19 20:18:48 | D | best error = [ 1.4115] +24-11-19 20:19:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:01 | D | sum error = [ 1.4183, 1.4444, 1.4245, 1.4537, 1.4807] +24-11-19 20:19:01 | D | best error = [ 1.4115, 1.4115, 1.4115, 1.4115, 1.4115] +24-11-19 20:19:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:01 | D | sum error = [ 1.5088, 1.6252, 1.7029, 1.7760, 1.8857] +24-11-19 20:19:01 | D | best error = [ 1.4115, 1.4115, 1.4115, 1.4115, 1.4115] +24-11-19 20:19:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:01 | D | sum error = [ 2.0057, 2.2284, 2.4215, 2.6001, 2.9333] +24-11-19 20:19:01 | D | best error = [ 1.4115, 1.4115, 1.4115, 1.4115, 1.4115] +24-11-19 20:19:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:01 | D | sum error = [ 3.2309, 3.4706, 3.9957, 4.3634, 4.8246] +24-11-19 20:19:01 | D | best error = [ 1.4115, 1.4115, 1.4115, 1.4115, 1.4115] +24-11-19 20:19:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:01 | D | sum error = [ 5.4083, 6.0382, 6.8659, 7.5908, 8.3739] +24-11-19 20:19:01 | D | best error = [ 1.4115, 1.4115, 1.4115, 1.4115, 1.4115] +24-11-19 20:19:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:01 | D | sum error = [ 9.2855, 10.5235, 11.7663, 13.1060, 14.6651] +24-11-19 20:19:01 | D | best error = [ 1.4115, 1.4115, 1.4115, 1.4115, 1.4115] +24-11-19 20:19:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:01 | D | sum error = [ 16.1897, 17.8968, 19.8853, 21.9835, 24.1570] +24-11-19 20:19:01 | D | best error = [ 1.4115, 1.4115, 1.4115, 1.4115, 1.4115] +24-11-19 20:19:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:01 | D | sum error = [ 26.5532, 29.2718, 31.9392, 34.8910, 38.0563] +24-11-19 20:19:01 | D | best error = [ 1.4115, 1.4115, 1.4115, 1.4115, 1.4115] +24-11-19 20:19:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:01 | D | sum error = [ 41.3383, 44.9690, 48.7556, 52.8655, 57.1856] +24-11-19 20:19:01 | D | best error = [ 1.4115, 1.4115, 1.4115, 1.4115, 1.4115] +24-11-19 20:19:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:01 | D | sum error = [ 62.2080, 67.3801, 72.8480, 78.7591, 85.0687] +24-11-19 20:19:01 | D | best error = [ 1.4115, 1.4115, 1.4115, 1.4115, 1.4115] +24-11-19 20:19:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:01 | D | sum error = [ 91.6043, 98.5409, 105.9323, 113.7096, 122.0435] +24-11-19 20:19:01 | D | best error = [ 1.4115, 1.4115, 1.4115, 1.4115, 1.4115] +24-11-19 20:19:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:01 | D | sum error = [ 131.0371, 140.4983, 150.3743, 161.0480, 172.2845] +24-11-19 20:19:01 | D | best error = [ 1.4115, 1.4115, 1.4115, 1.4115, 1.4115] +24-11-19 20:19:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:01 | D | sum error = [ 184.2995, 196.7462, 209.9629, 224.0541, 238.8386] +24-11-19 20:19:01 | D | best error = [ 1.4115, 1.4115, 1.4115, 1.4115, 1.4115] +24-11-19 20:19:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:01 | D | sum error = [ 254.1719, 270.4341, 287.1974, 304.6943, 322.9978] +24-11-19 20:19:01 | D | best error = [ 1.4115, 1.4115, 1.4115, 1.4115, 1.4115] +24-11-19 20:19:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:01 | D | sum error = [ 341.7130, 361.1643, 381.5009, 402.1102, 423.4249] +24-11-19 20:19:01 | D | best error = [ 1.4115, 1.4115, 1.4115, 1.4115, 1.4115] +24-11-19 20:19:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:01 | D | sum error = [ 445.3091, 467.5327, 490.4009, 513.3877, 536.6284] +24-11-19 20:19:01 | D | best error = [ 1.4115, 1.4115, 1.4115, 1.4115, 1.4115] +24-11-19 20:19:01 | D | + error = [1.4115] +24-11-19 20:19:02 | D | - Calibrating model.layers.4.self_attn.k_proj.weight +24-11-19 20:19:02 | D | + w: sint8 +24-11-19 20:19:02 | D | + x: None +24-11-19 20:19:02 | D | + y: None +24-11-19 20:19:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:19:02 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:19:02 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:19:02 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:19:02 | D | - range ratio = [ 1.0000] +24-11-19 20:19:02 | D | sum error = [ 1.5026] +24-11-19 20:19:02 | D | best error = [ 1.5026] +24-11-19 20:19:16 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:16 | D | sum error = [ 1.4729, 1.4938, 1.5934, 1.6018, 1.5114] +24-11-19 20:19:16 | D | best error = [ 1.4729, 1.4729, 1.4729, 1.4729, 1.4729] +24-11-19 20:19:16 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:16 | D | sum error = [ 1.6603, 1.7471, 1.7788, 1.7678, 2.0044] +24-11-19 20:19:16 | D | best error = [ 1.4729, 1.4729, 1.4729, 1.4729, 1.4729] +24-11-19 20:19:16 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:16 | D | sum error = [ 2.1640, 2.2014, 3.3528, 2.9603, 3.2171] +24-11-19 20:19:16 | D | best error = [ 1.4729, 1.4729, 1.4729, 1.4729, 1.4729] +24-11-19 20:19:16 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:16 | D | sum error = [ 3.7642, 3.9255, 4.3634, 5.1471, 5.6251] +24-11-19 20:19:16 | D | best error = [ 1.4729, 1.4729, 1.4729, 1.4729, 1.4729] +24-11-19 20:19:16 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:16 | D | sum error = [ 5.8832, 6.7194, 7.1636, 8.5495, 9.0812] +24-11-19 20:19:16 | D | best error = [ 1.4729, 1.4729, 1.4729, 1.4729, 1.4729] +24-11-19 20:19:16 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:16 | D | sum error = [ 9.9124, 10.3611, 11.7378, 13.0692, 14.2294] +24-11-19 20:19:16 | D | best error = [ 1.4729, 1.4729, 1.4729, 1.4729, 1.4729] +24-11-19 20:19:16 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:16 | D | sum error = [ 15.7388, 17.3497, 19.5204, 21.1943, 23.4257] +24-11-19 20:19:16 | D | best error = [ 1.4729, 1.4729, 1.4729, 1.4729, 1.4729] +24-11-19 20:19:16 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:16 | D | sum error = [ 25.5681, 27.7887, 30.1185, 33.0703, 35.8342] +24-11-19 20:19:16 | D | best error = [ 1.4729, 1.4729, 1.4729, 1.4729, 1.4729] +24-11-19 20:19:16 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:16 | D | sum error = [ 39.1956, 42.3861, 45.6605, 49.6206, 54.3031] +24-11-19 20:19:16 | D | best error = [ 1.4729, 1.4729, 1.4729, 1.4729, 1.4729] +24-11-19 20:19:16 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:16 | D | sum error = [ 58.6595, 63.1983, 67.9083, 74.0307, 80.0239] +24-11-19 20:19:16 | D | best error = [ 1.4729, 1.4729, 1.4729, 1.4729, 1.4729] +24-11-19 20:19:16 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:16 | D | sum error = [ 86.3293, 92.7203, 99.7766, 107.9328, 115.6030] +24-11-19 20:19:16 | D | best error = [ 1.4729, 1.4729, 1.4729, 1.4729, 1.4729] +24-11-19 20:19:16 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:16 | D | sum error = [ 124.5533, 133.9703, 143.1749, 155.2705, 166.6025] +24-11-19 20:19:16 | D | best error = [ 1.4729, 1.4729, 1.4729, 1.4729, 1.4729] +24-11-19 20:19:16 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:16 | D | sum error = [ 178.6829, 190.5009, 204.1515, 218.6915, 232.9251] +24-11-19 20:19:16 | D | best error = [ 1.4729, 1.4729, 1.4729, 1.4729, 1.4729] +24-11-19 20:19:16 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:16 | D | sum error = [ 248.4199, 264.3596, 281.2067, 300.0561, 318.1716] +24-11-19 20:19:16 | D | best error = [ 1.4729, 1.4729, 1.4729, 1.4729, 1.4729] +24-11-19 20:19:16 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:16 | D | sum error = [ 337.5354, 357.1782, 377.5983, 400.9048, 422.8490] +24-11-19 20:19:16 | D | best error = [ 1.4729, 1.4729, 1.4729, 1.4729, 1.4729] +24-11-19 20:19:16 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:16 | D | sum error = [ 444.9881, 468.5575, 492.4055, 517.5802, 540.8498] +24-11-19 20:19:16 | D | best error = [ 1.4729, 1.4729, 1.4729, 1.4729, 1.4729] +24-11-19 20:19:16 | D | + error = [1.4729] +24-11-19 20:19:16 | D | - Calibrating model.layers.4.self_attn.v_proj.weight +24-11-19 20:19:16 | D | + w: sint8 +24-11-19 20:19:16 | D | + x: None +24-11-19 20:19:16 | D | + y: None +24-11-19 20:19:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:16 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:19:16 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:19:17 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:19:17 | D | - range ratio = [ 1.0000] +24-11-19 20:19:17 | D | sum error = [ 1.0559] +24-11-19 20:19:17 | D | best error = [ 1.0559] +24-11-19 20:19:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:17 | D | sum error = [ 1.0358, 1.0336, 1.0432, 1.0469, 1.0660] +24-11-19 20:19:17 | D | best error = [ 0.9714, 0.9430, 0.9296, 0.9223, 0.9184] +24-11-19 20:19:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:17 | D | sum error = [ 1.0973, 1.1391, 1.1874, 1.2497, 1.3196] +24-11-19 20:19:17 | D | best error = [ 0.9167, 0.9160, 0.9157, 0.9157, 0.9157] +24-11-19 20:19:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:17 | D | sum error = [ 1.3910, 1.4980, 1.5854, 1.7003, 1.8230] +24-11-19 20:19:17 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:19:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:17 | D | sum error = [ 1.9659, 2.0959, 2.2570, 2.4121, 2.5986] +24-11-19 20:19:17 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:19:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:17 | D | sum error = [ 2.7800, 2.9869, 3.1974, 3.4214, 3.6610] +24-11-19 20:19:17 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:19:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:17 | D | sum error = [ 3.9064, 4.1849, 4.4681, 4.7679, 5.0881] +24-11-19 20:19:17 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:19:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:17 | D | sum error = [ 5.4305, 5.7682, 6.1446, 6.5422, 6.9583] +24-11-19 20:19:17 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:19:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:17 | D | sum error = [ 7.3822, 7.8468, 8.3165, 8.8234, 9.3477] +24-11-19 20:19:17 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:19:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:17 | D | sum error = [ 9.9035, 10.4907, 11.1056, 11.7555, 12.4313] +24-11-19 20:19:17 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:19:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:17 | D | sum error = [ 13.1423, 13.8891, 14.6719, 15.5029, 16.3635] +24-11-19 20:19:17 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:19:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:17 | D | sum error = [ 17.2649, 18.2128, 19.1940, 20.2226, 21.3003] +24-11-19 20:19:17 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:19:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:17 | D | sum error = [ 22.4253, 23.6092, 24.8411, 26.1333, 27.4703] +24-11-19 20:19:17 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:19:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:17 | D | sum error = [ 28.8628, 30.3236, 31.8370, 33.4093, 35.0451] +24-11-19 20:19:17 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:19:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:17 | D | sum error = [ 36.7506, 38.5107, 40.3456, 42.2487, 44.2114] +24-11-19 20:19:17 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:19:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:17 | D | sum error = [ 46.2457, 48.3503, 50.5300, 52.7812, 55.1036] +24-11-19 20:19:17 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:19:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:17 | D | sum error = [ 57.4954, 59.9633, 62.5067, 65.1163, 67.8065] +24-11-19 20:19:17 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:19:17 | D | + error = [0.9157] +24-11-19 20:19:17 | D | - Calibrating model.layers.4.self_attn.o_proj.weight +24-11-19 20:19:17 | D | + w: sint8 +24-11-19 20:19:17 | D | + x: None +24-11-19 20:19:17 | D | + y: None +24-11-19 20:19:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:17 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:19:17 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:19:17 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:19:17 | D | - range ratio = [ 1.0000] +24-11-19 20:19:17 | D | sum error = [ 0.2424] +24-11-19 20:19:17 | D | best error = [ 0.2424] +24-11-19 20:19:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:18 | D | sum error = [ 0.2397, 0.2394, 0.2387, 0.2408, 0.2439] +24-11-19 20:19:18 | D | best error = [ 0.2237, 0.2157, 0.2109, 0.2079, 0.2060] +24-11-19 20:19:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:18 | D | sum error = [ 0.2474, 0.2528, 0.2607, 0.2704, 0.2811] +24-11-19 20:19:18 | D | best error = [ 0.2045, 0.2035, 0.2029, 0.2025, 0.2022] +24-11-19 20:19:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:18 | D | sum error = [ 0.2929, 0.3088, 0.3251, 0.3436, 0.3637] +24-11-19 20:19:18 | D | best error = [ 0.2019, 0.2018, 0.2017, 0.2016, 0.2016] +24-11-19 20:19:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:18 | D | sum error = [ 0.3861, 0.4095, 0.4356, 0.4634, 0.4936] +24-11-19 20:19:18 | D | best error = [ 0.2016, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:19:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:18 | D | sum error = [ 0.5252, 0.5592, 0.5950, 0.6347, 0.6747] +24-11-19 20:19:18 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:19:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:18 | D | sum error = [ 0.7187, 0.7639, 0.8128, 0.8634, 0.9179] +24-11-19 20:19:18 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:19:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:18 | D | sum error = [ 0.9743, 1.0343, 1.0979, 1.1650, 1.2353] +24-11-19 20:19:18 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:19:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:18 | D | sum error = [ 1.3104, 1.3882, 1.4718, 1.5582, 1.6489] +24-11-19 20:19:18 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:19:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:18 | D | sum error = [ 1.7449, 1.8457, 1.9510, 2.0617, 2.1789] +24-11-19 20:19:18 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:19:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:18 | D | sum error = [ 2.3017, 2.4297, 2.5637, 2.7041, 2.8521] +24-11-19 20:19:18 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:19:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:18 | D | sum error = [ 3.0066, 3.1690, 3.3394, 3.5170, 3.7031] +24-11-19 20:19:18 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:19:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:18 | D | sum error = [ 3.8976, 4.0996, 4.3119, 4.5339, 4.7658] +24-11-19 20:19:18 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:19:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:18 | D | sum error = [ 5.0073, 5.2592, 5.5217, 5.7948, 6.0798] +24-11-19 20:19:18 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:19:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:18 | D | sum error = [ 6.3766, 6.6849, 7.0060, 7.3411, 7.6883] +24-11-19 20:19:18 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:19:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:18 | D | sum error = [ 8.0492, 8.4241, 8.8136, 9.2179, 9.6362] +24-11-19 20:19:18 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:19:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:18 | D | sum error = [ 10.0695, 10.5183, 10.9844, 11.4659, 11.9637] +24-11-19 20:19:18 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:19:18 | D | + error = [0.2015] +24-11-19 20:19:18 | D | - Calibrating model.layers.4.mlp.up_proj.weight +24-11-19 20:19:18 | D | + w: sint8 +24-11-19 20:19:18 | D | + x: None +24-11-19 20:19:18 | D | + y: None +24-11-19 20:19:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:18 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:19:18 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:19:18 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:19:18 | D | - range ratio = [ 1.0000] +24-11-19 20:19:18 | D | sum error = [ 4.1357] +24-11-19 20:19:18 | D | best error = [ 4.1357] +24-11-19 20:19:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:19 | D | sum error = [ 4.1021, 4.0974, 4.1086, 4.1658, 4.2359] +24-11-19 20:19:19 | D | best error = [ 3.8270, 3.7158, 3.6587, 3.6278, 3.6107] +24-11-19 20:19:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:19 | D | sum error = [ 4.3392, 4.4969, 4.6754, 4.9023, 5.1582] +24-11-19 20:19:19 | D | best error = [ 3.6026, 3.5994, 3.5982, 3.5979, 3.5979] +24-11-19 20:19:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:19 | D | sum error = [ 5.4483, 5.7921, 6.1835, 6.5923, 7.0500] +24-11-19 20:19:19 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:19:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:19 | D | sum error = [ 7.5438, 8.0815, 8.6602, 9.2840, 9.9547] +24-11-19 20:19:19 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:19:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:19 | D | sum error = [ 10.6534, 11.4023, 12.2030, 13.0592, 13.9612] +24-11-19 20:19:19 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:19:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:19 | D | sum error = [ 14.9064, 15.9095, 16.9849, 18.1105, 19.3026] +24-11-19 20:19:19 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:19:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:19 | D | sum error = [ 20.5504, 21.8652, 23.2475, 24.7100, 26.2477] +24-11-19 20:19:19 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:19:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:19 | D | sum error = [ 27.8628, 29.5585, 31.3395, 33.2042, 35.1704] +24-11-19 20:19:19 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:19:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:19 | D | sum error = [ 37.2259, 39.3770, 41.6459, 44.0022, 46.4750] +24-11-19 20:19:19 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:19:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:19 | D | sum error = [ 49.0545, 51.7584, 54.5821, 57.5212, 60.6016] +24-11-19 20:19:19 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:19:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:19 | D | sum error = [ 63.8102, 67.1503, 70.6425, 74.2487, 78.0203] +24-11-19 20:19:19 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:19:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:19 | D | sum error = [ 81.9274, 85.9963, 90.2176, 94.5902, 99.1324] +24-11-19 20:19:19 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:19:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:19 | D | sum error = [ 103.8336, 108.7011, 113.7399, 118.9547, 124.3431] +24-11-19 20:19:19 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:19:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:19 | D | sum error = [ 129.9156, 135.6814, 141.6158, 147.7634, 154.0973] +24-11-19 20:19:19 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:19:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:19 | D | sum error = [ 160.6363, 167.3648, 174.3038, 181.4467, 188.7956] +24-11-19 20:19:19 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:19:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:19 | D | sum error = [ 196.3650, 204.1527, 212.1553, 220.3828, 228.8302] +24-11-19 20:19:19 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:19:19 | D | + error = [3.5978] +24-11-19 20:19:19 | D | - Calibrating model.layers.4.mlp.gate_proj.weight +24-11-19 20:19:19 | D | + w: sint8 +24-11-19 20:19:19 | D | + x: None +24-11-19 20:19:19 | D | + y: None +24-11-19 20:19:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:20 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:19:20 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:19:20 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:19:20 | D | - range ratio = [ 1.0000] +24-11-19 20:19:20 | D | sum error = [ 5.4960] +24-11-19 20:19:20 | D | best error = [ 5.4960] +24-11-19 20:19:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:21 | D | sum error = [ 5.4535, 5.4445, 5.4727, 5.5372, 5.6339] +24-11-19 20:19:21 | D | best error = [ 5.0893, 4.9444, 4.8683, 4.8261, 4.8047] +24-11-19 20:19:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:21 | D | sum error = [ 5.7897, 5.9668, 6.2187, 6.5259, 6.8787] +24-11-19 20:19:21 | D | best error = [ 4.7952, 4.7910, 4.7899, 4.7895, 4.7894] +24-11-19 20:19:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:21 | D | sum error = [ 7.2652, 7.7116, 8.2114, 8.7682, 9.3671] +24-11-19 20:19:21 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:19:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:21 | D | sum error = [ 10.0431, 10.7755, 11.5433, 12.3934, 13.2801] +24-11-19 20:19:21 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:19:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:21 | D | sum error = [ 14.2493, 15.2755, 16.3797, 17.5405, 18.7777] +24-11-19 20:19:21 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:19:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:21 | D | sum error = [ 20.1102, 21.5072, 22.9976, 24.5691, 26.2361] +24-11-19 20:19:21 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:19:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:21 | D | sum error = [ 27.9979, 29.8765, 31.8543, 33.9416, 36.1605] +24-11-19 20:19:21 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:19:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:21 | D | sum error = [ 38.4971, 40.9794, 43.5951, 46.3712, 49.2883] +24-11-19 20:19:21 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:19:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:21 | D | sum error = [ 52.3766, 55.6444, 59.0768, 62.7126, 66.5532] +24-11-19 20:19:21 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:19:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:21 | D | sum error = [ 70.5940, 74.8492, 79.3288, 84.0478, 89.0120] +24-11-19 20:19:21 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:19:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:21 | D | sum error = [ 94.2469, 99.7545, 105.5372, 111.6289, 118.0181] +24-11-19 20:19:21 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:19:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:21 | D | sum error = [ 124.7384, 131.7816, 139.1682, 146.9168, 155.0214] +24-11-19 20:19:21 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:19:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:21 | D | sum error = [ 163.5174, 172.3996, 181.6818, 191.3780, 201.4911] +24-11-19 20:19:21 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:19:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:21 | D | sum error = [ 212.0399, 223.0294, 234.4890, 246.4256, 258.8226] +24-11-19 20:19:21 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:19:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:21 | D | sum error = [ 271.7169, 285.1238, 298.9961, 313.4072, 328.3234] +24-11-19 20:19:21 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:19:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:21 | D | sum error = [ 343.7500, 359.6715, 376.1127, 393.0745, 410.5550] +24-11-19 20:19:21 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:19:21 | D | + error = [4.7894] +24-11-19 20:19:21 | D | - Calibrating model.layers.4.mlp.down_proj.weight +24-11-19 20:19:21 | D | + w: sint8 +24-11-19 20:19:21 | D | + x: None +24-11-19 20:19:21 | D | + y: None +24-11-19 20:19:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:21 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:19:21 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:19:22 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:19:22 | D | - range ratio = [ 1.0000] +24-11-19 20:19:22 | D | sum error = [ 0.3828] +24-11-19 20:19:22 | D | best error = [ 0.3828] +24-11-19 20:19:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:23 | D | sum error = [ 0.3789, 0.3753, 0.3732, 0.3715, 0.3704] +24-11-19 20:19:23 | D | best error = [ 0.3693, 0.3621, 0.3570, 0.3534, 0.3505] +24-11-19 20:19:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:23 | D | sum error = [ 0.3710, 0.3719, 0.3745, 0.3787, 0.3835] +24-11-19 20:19:23 | D | best error = [ 0.3483, 0.3464, 0.3450, 0.3438, 0.3431] +24-11-19 20:19:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:23 | D | sum error = [ 0.3914, 0.4003, 0.4116, 0.4250, 0.4411] +24-11-19 20:19:23 | D | best error = [ 0.3425, 0.3421, 0.3419, 0.3416, 0.3415] +24-11-19 20:19:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:23 | D | sum error = [ 0.4600, 0.4816, 0.5051, 0.5331, 0.5625] +24-11-19 20:19:23 | D | best error = [ 0.3414, 0.3414, 0.3414, 0.3413, 0.3413] +24-11-19 20:19:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:23 | D | sum error = [ 0.5973, 0.6337, 0.6746, 0.7197, 0.7675] +24-11-19 20:19:23 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 20:19:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:23 | D | sum error = [ 0.8193, 0.8765, 0.9372, 1.0021, 1.0723] +24-11-19 20:19:23 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 20:19:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:23 | D | sum error = [ 1.1481, 1.2279, 1.3142, 1.4060, 1.5038] +24-11-19 20:19:23 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 20:19:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:23 | D | sum error = [ 1.6079, 1.7187, 1.8373, 1.9617, 2.0954] +24-11-19 20:19:23 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 20:19:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:23 | D | sum error = [ 2.2365, 2.3857, 2.5442, 2.7117, 2.8887] +24-11-19 20:19:23 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 20:19:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:23 | D | sum error = [ 3.0759, 3.2733, 3.4809, 3.7003, 3.9318] +24-11-19 20:19:23 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 20:19:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:23 | D | sum error = [ 4.1762, 4.4328, 4.7023, 4.9858, 5.2833] +24-11-19 20:19:23 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 20:19:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:23 | D | sum error = [ 5.5953, 5.9231, 6.2668, 6.6265, 7.0037] +24-11-19 20:19:23 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 20:19:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:23 | D | sum error = [ 7.3982, 7.8112, 8.2430, 8.6941, 9.1654] +24-11-19 20:19:23 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 20:19:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:23 | D | sum error = [ 9.6566, 10.1691, 10.7032, 11.2603, 11.8379] +24-11-19 20:19:23 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 20:19:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:23 | D | sum error = [ 12.4397, 13.0649, 13.7144, 14.3892, 15.0888] +24-11-19 20:19:23 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 20:19:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:23 | D | sum error = [ 15.8139, 16.5641, 17.3414, 18.1447, 18.9755] +24-11-19 20:19:23 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 20:19:23 | D | + error = [0.3413] +24-11-19 20:19:23 | D | - Quantizing model.layers.4.self_attn.q_proj.weight +24-11-19 20:19:24 | D | - Quantizing model.layers.4.self_attn.k_proj.weight +24-11-19 20:19:25 | D | - Quantizing model.layers.4.self_attn.v_proj.weight +24-11-19 20:19:26 | D | - Quantizing model.layers.4.self_attn.o_proj.weight +24-11-19 20:19:27 | D | - Quantizing model.layers.4.mlp.up_proj.weight +24-11-19 20:19:29 | D | - Quantizing model.layers.4.mlp.gate_proj.weight +24-11-19 20:19:30 | D | - Quantizing model.layers.4.mlp.down_proj.weight +24-11-19 20:19:40 | D | - Quantizing layer model.layers.5 +24-11-19 20:19:40 | D | - Calibrating model.layers.5.self_attn.q_proj.weight +24-11-19 20:19:40 | D | + w: sint8 +24-11-19 20:19:40 | D | + x: None +24-11-19 20:19:40 | D | + y: None +24-11-19 20:19:40 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:19:40 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:19:40 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:19:40 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:19:40 | D | - range ratio = [ 1.0000] +24-11-19 20:19:40 | D | sum error = [ 2.0468] +24-11-19 20:19:40 | D | best error = [ 2.0468] +24-11-19 20:19:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:52 | D | sum error = [ 2.1172, 2.0700, 2.0561, 2.0345, 2.0952] +24-11-19 20:19:52 | D | best error = [ 2.0468, 2.0468, 2.0468, 2.0345, 2.0345] +24-11-19 20:19:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:52 | D | sum error = [ 2.1232, 2.2289, 2.3385, 2.4674, 2.5063] +24-11-19 20:19:52 | D | best error = [ 2.0345, 2.0345, 2.0345, 2.0345, 2.0345] +24-11-19 20:19:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:52 | D | sum error = [ 2.7293, 2.9074, 3.0882, 3.4872, 3.6778] +24-11-19 20:19:52 | D | best error = [ 2.0345, 2.0345, 2.0345, 2.0345, 2.0345] +24-11-19 20:19:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:52 | D | sum error = [ 3.8684, 4.2163, 4.7095, 5.0314, 5.4593] +24-11-19 20:19:52 | D | best error = [ 2.0345, 2.0345, 2.0345, 2.0345, 2.0345] +24-11-19 20:19:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:52 | D | sum error = [ 5.9108, 6.3938, 7.0277, 7.5793, 8.1256] +24-11-19 20:19:52 | D | best error = [ 2.0345, 2.0345, 2.0345, 2.0345, 2.0345] +24-11-19 20:19:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:52 | D | sum error = [ 8.7992, 9.6818, 10.5855, 11.5590, 12.4472] +24-11-19 20:19:52 | D | best error = [ 2.0345, 2.0345, 2.0345, 2.0345, 2.0345] +24-11-19 20:19:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:52 | D | sum error = [ 13.5798, 14.6980, 16.1173, 17.5802, 19.1411] +24-11-19 20:19:52 | D | best error = [ 2.0345, 2.0345, 2.0345, 2.0345, 2.0345] +24-11-19 20:19:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:52 | D | sum error = [ 20.8468, 22.7052, 24.7736, 26.9268, 29.2969] +24-11-19 20:19:52 | D | best error = [ 2.0345, 2.0345, 2.0345, 2.0345, 2.0345] +24-11-19 20:19:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:52 | D | sum error = [ 31.8691, 34.7197, 37.5335, 40.7578, 44.0758] +24-11-19 20:19:52 | D | best error = [ 2.0345, 2.0345, 2.0345, 2.0345, 2.0345] +24-11-19 20:19:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:52 | D | sum error = [ 47.7690, 51.7482, 56.0035, 60.6078, 65.4801] +24-11-19 20:19:52 | D | best error = [ 2.0345, 2.0345, 2.0345, 2.0345, 2.0345] +24-11-19 20:19:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:52 | D | sum error = [ 70.8869, 76.4323, 82.4815, 88.8466, 95.6676] +24-11-19 20:19:52 | D | best error = [ 2.0345, 2.0345, 2.0345, 2.0345, 2.0345] +24-11-19 20:19:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:52 | D | sum error = [ 102.9269, 110.7618, 119.1992, 128.1365, 137.6907] +24-11-19 20:19:52 | D | best error = [ 2.0345, 2.0345, 2.0345, 2.0345, 2.0345] +24-11-19 20:19:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:52 | D | sum error = [ 147.9125, 158.8147, 170.2729, 182.4466, 195.2705] +24-11-19 20:19:52 | D | best error = [ 2.0345, 2.0345, 2.0345, 2.0345, 2.0345] +24-11-19 20:19:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:52 | D | sum error = [ 208.8609, 223.3736, 238.6085, 254.6972, 271.7324] +24-11-19 20:19:52 | D | best error = [ 2.0345, 2.0345, 2.0345, 2.0345, 2.0345] +24-11-19 20:19:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:52 | D | sum error = [ 289.4094, 308.0157, 327.3098, 347.4435, 368.1463] +24-11-19 20:19:52 | D | best error = [ 2.0345, 2.0345, 2.0345, 2.0345, 2.0345] +24-11-19 20:19:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:52 | D | sum error = [ 389.4551, 411.1694, 433.5061, 456.1630, 479.1222] +24-11-19 20:19:52 | D | best error = [ 2.0345, 2.0345, 2.0345, 2.0345, 2.0345] +24-11-19 20:19:52 | D | + error = [2.0345] +24-11-19 20:19:52 | D | - Calibrating model.layers.5.self_attn.k_proj.weight +24-11-19 20:19:52 | D | + w: sint8 +24-11-19 20:19:52 | D | + x: None +24-11-19 20:19:52 | D | + y: None +24-11-19 20:19:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:19:52 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:19:52 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:19:52 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:19:53 | D | - range ratio = [ 1.0000] +24-11-19 20:19:53 | D | sum error = [ 2.2218] +24-11-19 20:19:53 | D | best error = [ 2.2218] +24-11-19 20:20:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:04 | D | sum error = [ 2.0571, 2.1192, 2.1541, 2.2631, 2.1070] +24-11-19 20:20:04 | D | best error = [ 2.0571, 2.0571, 2.0571, 2.0571, 2.0571] +24-11-19 20:20:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:04 | D | sum error = [ 2.2257, 2.3524, 2.2878, 2.5588, 2.8291] +24-11-19 20:20:04 | D | best error = [ 2.0571, 2.0571, 2.0571, 2.0571, 2.0571] +24-11-19 20:20:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:04 | D | sum error = [ 3.0956, 3.3773, 4.1147, 4.2450, 4.6175] +24-11-19 20:20:04 | D | best error = [ 2.0571, 2.0571, 2.0571, 2.0571, 2.0571] +24-11-19 20:20:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:04 | D | sum error = [ 4.7363, 5.4489, 5.8972, 5.9426, 7.4477] +24-11-19 20:20:04 | D | best error = [ 2.0571, 2.0571, 2.0571, 2.0571, 2.0571] +24-11-19 20:20:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:04 | D | sum error = [ 7.3034, 8.2799, 9.4053, 10.1780, 10.5762] +24-11-19 20:20:04 | D | best error = [ 2.0571, 2.0571, 2.0571, 2.0571, 2.0571] +24-11-19 20:20:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:04 | D | sum error = [ 11.5035, 13.0318, 13.7071, 14.7895, 16.1743] +24-11-19 20:20:04 | D | best error = [ 2.0571, 2.0571, 2.0571, 2.0571, 2.0571] +24-11-19 20:20:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:04 | D | sum error = [ 17.4305, 18.7822, 20.7221, 22.2996, 24.5202] +24-11-19 20:20:04 | D | best error = [ 2.0571, 2.0571, 2.0571, 2.0571, 2.0571] +24-11-19 20:20:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:04 | D | sum error = [ 26.0825, 28.4418, 30.6498, 33.6439, 36.2857] +24-11-19 20:20:04 | D | best error = [ 2.0571, 2.0571, 2.0571, 2.0571, 2.0571] +24-11-19 20:20:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:04 | D | sum error = [ 38.9821, 42.2211, 44.8180, 48.6020, 52.4266] +24-11-19 20:20:04 | D | best error = [ 2.0571, 2.0571, 2.0571, 2.0571, 2.0571] +24-11-19 20:20:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:04 | D | sum error = [ 56.7208, 60.8225, 65.6537, 70.5250, 76.0053] +24-11-19 20:20:04 | D | best error = [ 2.0571, 2.0571, 2.0571, 2.0571, 2.0571] +24-11-19 20:20:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:04 | D | sum error = [ 81.6882, 88.4803, 95.1087, 102.4122, 110.1169] +24-11-19 20:20:04 | D | best error = [ 2.0571, 2.0571, 2.0571, 2.0571, 2.0571] +24-11-19 20:20:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:04 | D | sum error = [ 118.8695, 127.0920, 136.5170, 146.1122, 156.1948] +24-11-19 20:20:04 | D | best error = [ 2.0571, 2.0571, 2.0571, 2.0571, 2.0571] +24-11-19 20:20:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:04 | D | sum error = [ 167.6323, 179.2868, 191.3616, 204.2668, 218.2074] +24-11-19 20:20:04 | D | best error = [ 2.0571, 2.0571, 2.0571, 2.0571, 2.0571] +24-11-19 20:20:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:04 | D | sum error = [ 232.3085, 247.0306, 263.2766, 279.1778, 296.6146] +24-11-19 20:20:04 | D | best error = [ 2.0571, 2.0571, 2.0571, 2.0571, 2.0571] +24-11-19 20:20:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:04 | D | sum error = [ 315.4942, 333.3256, 353.7996, 373.9900, 394.5245] +24-11-19 20:20:04 | D | best error = [ 2.0571, 2.0571, 2.0571, 2.0571, 2.0571] +24-11-19 20:20:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:04 | D | sum error = [ 416.0638, 437.8687, 459.6345, 482.4955, 504.9518] +24-11-19 20:20:04 | D | best error = [ 2.0571, 2.0571, 2.0571, 2.0571, 2.0571] +24-11-19 20:20:04 | D | + error = [2.0571] +24-11-19 20:20:05 | D | - Calibrating model.layers.5.self_attn.v_proj.weight +24-11-19 20:20:05 | D | + w: sint8 +24-11-19 20:20:05 | D | + x: None +24-11-19 20:20:05 | D | + y: None +24-11-19 20:20:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:05 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:05 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:05 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:05 | D | - range ratio = [ 1.0000] +24-11-19 20:20:05 | D | sum error = [ 1.0032] +24-11-19 20:20:05 | D | best error = [ 1.0032] +24-11-19 20:20:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:05 | D | sum error = [ 1.0006, 0.9913, 1.0058, 1.0055, 1.0223] +24-11-19 20:20:05 | D | best error = [ 0.9389, 0.9116, 0.8993, 0.8916, 0.8878] +24-11-19 20:20:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:05 | D | sum error = [ 1.0522, 1.0929, 1.1407, 1.1925, 1.2558] +24-11-19 20:20:05 | D | best error = [ 0.8859, 0.8851, 0.8850, 0.8849, 0.8849] +24-11-19 20:20:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:05 | D | sum error = [ 1.3232, 1.4094, 1.4919, 1.5862, 1.7086] +24-11-19 20:20:05 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:20:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:05 | D | sum error = [ 1.8304, 1.9484, 2.0876, 2.2412, 2.4035] +24-11-19 20:20:05 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:20:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:05 | D | sum error = [ 2.5821, 2.7648, 2.9590, 3.1654, 3.3878] +24-11-19 20:20:05 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:20:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:05 | D | sum error = [ 3.6181, 3.8644, 4.1258, 4.4098, 4.6895] +24-11-19 20:20:05 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:20:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:05 | D | sum error = [ 5.0080, 5.3380, 5.6818, 6.0540, 6.4475] +24-11-19 20:20:05 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:20:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:05 | D | sum error = [ 6.8521, 7.2900, 7.7405, 8.2281, 8.7238] +24-11-19 20:20:05 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:20:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:05 | D | sum error = [ 9.2690, 9.8238, 10.4281, 11.0486, 11.7096] +24-11-19 20:20:05 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:20:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:05 | D | sum error = [ 12.4024, 13.1275, 13.8906, 14.6910, 15.5337] +24-11-19 20:20:05 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:20:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:05 | D | sum error = [ 16.4191, 17.3479, 18.3218, 19.3399, 20.4081] +24-11-19 20:20:05 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:20:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:05 | D | sum error = [ 21.5172, 22.6808, 23.8930, 25.1673, 26.4874] +24-11-19 20:20:05 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:20:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:05 | D | sum error = [ 27.8733, 29.3124, 30.8161, 32.3774, 34.0149] +24-11-19 20:20:05 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:20:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:05 | D | sum error = [ 35.7088, 37.4730, 39.3029, 41.2054, 43.1679] +24-11-19 20:20:05 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:20:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:05 | D | sum error = [ 45.2112, 47.3153, 49.5047, 51.7681, 54.1000] +24-11-19 20:20:05 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:20:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:05 | D | sum error = [ 56.5212, 59.0151, 61.5928, 64.2504, 66.9855] +24-11-19 20:20:05 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:20:05 | D | + error = [0.8849] +24-11-19 20:20:05 | D | - Calibrating model.layers.5.self_attn.o_proj.weight +24-11-19 20:20:05 | D | + w: sint8 +24-11-19 20:20:05 | D | + x: None +24-11-19 20:20:05 | D | + y: None +24-11-19 20:20:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:05 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:05 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:05 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:05 | D | - range ratio = [ 1.0000] +24-11-19 20:20:05 | D | sum error = [ 0.2897] +24-11-19 20:20:05 | D | best error = [ 0.2897] +24-11-19 20:20:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:06 | D | sum error = [ 0.2875, 0.2869, 0.2866, 0.2898, 0.2926] +24-11-19 20:20:06 | D | best error = [ 0.2659, 0.2556, 0.2494, 0.2453, 0.2425] +24-11-19 20:20:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:06 | D | sum error = [ 0.2993, 0.3056, 0.3169, 0.3281, 0.3434] +24-11-19 20:20:06 | D | best error = [ 0.2406, 0.2394, 0.2385, 0.2378, 0.2374] +24-11-19 20:20:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:06 | D | sum error = [ 0.3585, 0.3782, 0.3980, 0.4194, 0.4461] +24-11-19 20:20:06 | D | best error = [ 0.2371, 0.2370, 0.2368, 0.2367, 0.2366] +24-11-19 20:20:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:06 | D | sum error = [ 0.4731, 0.5006, 0.5320, 0.5664, 0.6014] +24-11-19 20:20:06 | D | best error = [ 0.2366, 0.2366, 0.2365, 0.2365, 0.2365] +24-11-19 20:20:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:06 | D | sum error = [ 0.6403, 0.6803, 0.7235, 0.7706, 0.8181] +24-11-19 20:20:06 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:20:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:06 | D | sum error = [ 0.8684, 0.9218, 0.9799, 1.0391, 1.1031] +24-11-19 20:20:06 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:20:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:06 | D | sum error = [ 1.1676, 1.2364, 1.3111, 1.3864, 1.4683] +24-11-19 20:20:06 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:20:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:06 | D | sum error = [ 1.5532, 1.6416, 1.7354, 1.8317, 1.9357] +24-11-19 20:20:06 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:20:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:06 | D | sum error = [ 2.0425, 2.1546, 2.2726, 2.3962, 2.5254] +24-11-19 20:20:06 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:20:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:06 | D | sum error = [ 2.6604, 2.8012, 2.9486, 3.1041, 3.2668] +24-11-19 20:20:06 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:20:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:06 | D | sum error = [ 3.4361, 3.6130, 3.7995, 3.9934, 4.1962] +24-11-19 20:20:06 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:20:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:06 | D | sum error = [ 4.4071, 4.6287, 4.8577, 5.0955, 5.3436] +24-11-19 20:20:06 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:20:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:06 | D | sum error = [ 5.6021, 5.8708, 6.1487, 6.4382, 6.7385] +24-11-19 20:20:06 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:20:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:06 | D | sum error = [ 7.0513, 7.3753, 7.7104, 8.0585, 8.4179] +24-11-19 20:20:06 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:20:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:06 | D | sum error = [ 8.7912, 9.1774, 9.5773, 9.9928, 10.4220] +24-11-19 20:20:06 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:20:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:06 | D | sum error = [ 10.8659, 11.3251, 11.7997, 12.2903, 12.7971] +24-11-19 20:20:06 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:20:06 | D | + error = [0.2365] +24-11-19 20:20:06 | D | - Calibrating model.layers.5.mlp.up_proj.weight +24-11-19 20:20:06 | D | + w: sint8 +24-11-19 20:20:06 | D | + x: None +24-11-19 20:20:06 | D | + y: None +24-11-19 20:20:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:06 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:06 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:06 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:06 | D | - range ratio = [ 1.0000] +24-11-19 20:20:06 | D | sum error = [ 4.4838] +24-11-19 20:20:06 | D | best error = [ 4.4838] +24-11-19 20:20:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:07 | D | sum error = [ 4.4294, 4.4433, 4.4538, 4.4916, 4.5817] +24-11-19 20:20:07 | D | best error = [ 4.1859, 4.0784, 4.0203, 3.9871, 3.9703] +24-11-19 20:20:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:07 | D | sum error = [ 4.6998, 4.8572, 5.0469, 5.2861, 5.5555] +24-11-19 20:20:07 | D | best error = [ 3.9623, 3.9588, 3.9578, 3.9575, 3.9574] +24-11-19 20:20:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:07 | D | sum error = [ 5.8673, 6.2451, 6.6416, 7.0829, 7.5657] +24-11-19 20:20:07 | D | best error = [ 3.9574, 3.9574, 3.9574, 3.9574, 3.9574] +24-11-19 20:20:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:07 | D | sum error = [ 8.1035, 8.6712, 9.2791, 9.9441, 10.6448] +24-11-19 20:20:07 | D | best error = [ 3.9574, 3.9574, 3.9574, 3.9574, 3.9574] +24-11-19 20:20:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:07 | D | sum error = [ 11.4113, 12.2051, 13.0635, 13.9665, 14.9323] +24-11-19 20:20:07 | D | best error = [ 3.9574, 3.9574, 3.9574, 3.9574, 3.9574] +24-11-19 20:20:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:07 | D | sum error = [ 15.9641, 17.0384, 18.1930, 19.4042, 20.6868] +24-11-19 20:20:07 | D | best error = [ 3.9574, 3.9574, 3.9574, 3.9574, 3.9574] +24-11-19 20:20:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:07 | D | sum error = [ 22.0294, 23.4578, 24.9633, 26.5502, 28.2241] +24-11-19 20:20:07 | D | best error = [ 3.9574, 3.9574, 3.9574, 3.9574, 3.9574] +24-11-19 20:20:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:07 | D | sum error = [ 29.9743, 31.8220, 33.7586, 35.8041, 37.9415] +24-11-19 20:20:07 | D | best error = [ 3.9574, 3.9574, 3.9574, 3.9574, 3.9574] +24-11-19 20:20:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:07 | D | sum error = [ 40.1804, 42.5377, 45.0026, 47.5839, 50.2882] +24-11-19 20:20:07 | D | best error = [ 3.9574, 3.9574, 3.9574, 3.9574, 3.9574] +24-11-19 20:20:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:07 | D | sum error = [ 53.1226, 56.0694, 59.1724, 62.4032, 65.7713] +24-11-19 20:20:07 | D | best error = [ 3.9574, 3.9574, 3.9574, 3.9574, 3.9574] +24-11-19 20:20:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:07 | D | sum error = [ 69.2911, 72.9592, 76.7913, 80.7708, 84.9215] +24-11-19 20:20:07 | D | best error = [ 3.9574, 3.9574, 3.9574, 3.9574, 3.9574] +24-11-19 20:20:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:07 | D | sum error = [ 89.2350, 93.7335, 98.4065, 103.2590, 108.3025] +24-11-19 20:20:07 | D | best error = [ 3.9574, 3.9574, 3.9574, 3.9574, 3.9574] +24-11-19 20:20:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:07 | D | sum error = [ 113.5282, 118.9534, 124.5635, 130.3857, 136.4149] +24-11-19 20:20:07 | D | best error = [ 3.9574, 3.9574, 3.9574, 3.9574, 3.9574] +24-11-19 20:20:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:07 | D | sum error = [ 142.6505, 149.0960, 155.7780, 162.6747, 169.7914] +24-11-19 20:20:07 | D | best error = [ 3.9574, 3.9574, 3.9574, 3.9574, 3.9574] +24-11-19 20:20:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:07 | D | sum error = [ 177.1423, 184.7284, 192.5317, 200.5875, 208.8747] +24-11-19 20:20:07 | D | best error = [ 3.9574, 3.9574, 3.9574, 3.9574, 3.9574] +24-11-19 20:20:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:07 | D | sum error = [ 217.4274, 226.2176, 235.2691, 244.5792, 254.1497] +24-11-19 20:20:07 | D | best error = [ 3.9574, 3.9574, 3.9574, 3.9574, 3.9574] +24-11-19 20:20:07 | D | + error = [3.9574] +24-11-19 20:20:07 | D | - Calibrating model.layers.5.mlp.gate_proj.weight +24-11-19 20:20:07 | D | + w: sint8 +24-11-19 20:20:07 | D | + x: None +24-11-19 20:20:07 | D | + y: None +24-11-19 20:20:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:07 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:07 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:08 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:08 | D | - range ratio = [ 1.0000] +24-11-19 20:20:08 | D | sum error = [ 5.8954] +24-11-19 20:20:08 | D | best error = [ 5.8954] +24-11-19 20:20:09 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:09 | D | sum error = [ 5.8588, 5.8434, 5.8620, 5.9250, 6.0496] +24-11-19 20:20:09 | D | best error = [ 5.5167, 5.3718, 5.2954, 5.2504, 5.2285] +24-11-19 20:20:09 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:09 | D | sum error = [ 6.2002, 6.4094, 6.6710, 6.9728, 7.3501] +24-11-19 20:20:09 | D | best error = [ 5.2189, 5.2144, 5.2134, 5.2132, 5.2131] +24-11-19 20:20:09 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:09 | D | sum error = [ 7.7801, 8.2688, 8.7929, 9.3941, 10.0414] +24-11-19 20:20:09 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 20:20:09 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:09 | D | sum error = [ 10.7525, 11.5324, 12.3634, 13.2522, 14.2207] +24-11-19 20:20:09 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 20:20:09 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:09 | D | sum error = [ 15.2585, 16.3515, 17.5425, 18.7956, 20.1323] +24-11-19 20:20:09 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 20:20:09 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:09 | D | sum error = [ 21.5499, 23.0594, 24.6703, 26.3768, 28.1796] +24-11-19 20:20:09 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 20:20:09 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:09 | D | sum error = [ 30.0819, 32.1205, 34.2575, 36.5258, 38.9360] +24-11-19 20:20:09 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 20:20:09 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:09 | D | sum error = [ 41.4823, 44.1633, 47.0024, 50.0170, 53.1956] +24-11-19 20:20:09 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 20:20:09 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:09 | D | sum error = [ 56.5629, 60.1220, 63.8763, 67.8486, 72.0174] +24-11-19 20:20:09 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 20:20:09 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:09 | D | sum error = [ 76.4416, 81.1113, 86.0156, 91.2042, 96.6460] +24-11-19 20:20:09 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 20:20:09 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:09 | D | sum error = [ 102.4079, 108.4406, 114.8113, 121.5285, 128.5542] +24-11-19 20:20:09 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 20:20:09 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:09 | D | sum error = [ 135.9612, 143.7150, 151.8733, 160.4020, 169.3451] +24-11-19 20:20:09 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 20:20:09 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:09 | D | sum error = [ 178.7249, 188.5379, 198.7995, 209.5447, 220.7663] +24-11-19 20:20:09 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 20:20:09 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:09 | D | sum error = [ 232.4657, 244.6648, 257.3858, 270.6638, 284.4648] +24-11-19 20:20:09 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 20:20:09 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:09 | D | sum error = [ 298.8116, 313.7133, 329.2023, 345.2373, 361.8452] +24-11-19 20:20:09 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 20:20:09 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:09 | D | sum error = [ 379.0463, 396.7995, 415.1379, 434.0567, 453.5689] +24-11-19 20:20:09 | D | best error = [ 5.2131, 5.2131, 5.2131, 5.2131, 5.2131] +24-11-19 20:20:09 | D | + error = [5.2131] +24-11-19 20:20:09 | D | - Calibrating model.layers.5.mlp.down_proj.weight +24-11-19 20:20:09 | D | + w: sint8 +24-11-19 20:20:09 | D | + x: None +24-11-19 20:20:09 | D | + y: None +24-11-19 20:20:09 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:09 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:09 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:09 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:09 | D | - range ratio = [ 1.0000] +24-11-19 20:20:09 | D | sum error = [ 0.4632] +24-11-19 20:20:09 | D | best error = [ 0.4632] +24-11-19 20:20:10 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:10 | D | sum error = [ 0.4583, 0.4555, 0.4528, 0.4524, 0.4522] +24-11-19 20:20:10 | D | best error = [ 0.4461, 0.4376, 0.4317, 0.4274, 0.4240] +24-11-19 20:20:10 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:10 | D | sum error = [ 0.4550, 0.4578, 0.4633, 0.4711, 0.4809] +24-11-19 20:20:10 | D | best error = [ 0.4215, 0.4196, 0.4180, 0.4168, 0.4161] +24-11-19 20:20:10 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:10 | D | sum error = [ 0.4947, 0.5096, 0.5273, 0.5487, 0.5717] +24-11-19 20:20:10 | D | best error = [ 0.4155, 0.4151, 0.4149, 0.4148, 0.4146] +24-11-19 20:20:10 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:10 | D | sum error = [ 0.6009, 0.6317, 0.6670, 0.7054, 0.7477] +24-11-19 20:20:10 | D | best error = [ 0.4146, 0.4145, 0.4145, 0.4145, 0.4145] +24-11-19 20:20:10 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:10 | D | sum error = [ 0.7937, 0.8448, 0.8999, 0.9614, 1.0254] +24-11-19 20:20:10 | D | best error = [ 0.4145, 0.4145, 0.4145, 0.4144, 0.4144] +24-11-19 20:20:10 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:10 | D | sum error = [ 1.0949, 1.1684, 1.2492, 1.3341, 1.4255] +24-11-19 20:20:10 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 20:20:10 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:10 | D | sum error = [ 1.5224, 1.6265, 1.7376, 1.8541, 1.9790] +24-11-19 20:20:10 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 20:20:10 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:10 | D | sum error = [ 2.1116, 2.2521, 2.4017, 2.5596, 2.7274] +24-11-19 20:20:10 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 20:20:10 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:10 | D | sum error = [ 2.9048, 3.0922, 3.2907, 3.5011, 3.7226] +24-11-19 20:20:10 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 20:20:10 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:10 | D | sum error = [ 3.9570, 4.2032, 4.4628, 4.7361, 5.0243] +24-11-19 20:20:10 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 20:20:10 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:10 | D | sum error = [ 5.3272, 5.6451, 5.9797, 6.3316, 6.7008] +24-11-19 20:20:10 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 20:20:10 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:10 | D | sum error = [ 7.0885, 7.4944, 7.9191, 8.3637, 8.8294] +24-11-19 20:20:10 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 20:20:10 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:10 | D | sum error = [ 9.3158, 9.8247, 10.3572, 10.9131, 11.4934] +24-11-19 20:20:10 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 20:20:10 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:10 | D | sum error = [ 12.0972, 12.7262, 13.3811, 14.0632, 14.7706] +24-11-19 20:20:10 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 20:20:10 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:10 | D | sum error = [ 15.5071, 16.2715, 17.0650, 17.8876, 18.7399] +24-11-19 20:20:10 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 20:20:10 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:10 | D | sum error = [ 19.6231, 20.5373, 21.4832, 22.4608, 23.4708] +24-11-19 20:20:10 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 20:20:10 | D | + error = [0.4144] +24-11-19 20:20:10 | D | - Quantizing model.layers.5.self_attn.q_proj.weight +24-11-19 20:20:12 | D | - Quantizing model.layers.5.self_attn.k_proj.weight +24-11-19 20:20:16 | D | - Quantizing model.layers.5.self_attn.v_proj.weight +24-11-19 20:20:17 | D | - Quantizing model.layers.5.self_attn.o_proj.weight +24-11-19 20:20:18 | D | - Quantizing model.layers.5.mlp.up_proj.weight +24-11-19 20:20:19 | D | - Quantizing model.layers.5.mlp.gate_proj.weight +24-11-19 20:20:20 | D | - Quantizing model.layers.5.mlp.down_proj.weight +24-11-19 20:20:31 | D | - Quantizing layer model.layers.6 +24-11-19 20:20:31 | D | - Calibrating model.layers.6.self_attn.q_proj.weight +24-11-19 20:20:31 | D | + w: sint8 +24-11-19 20:20:31 | D | + x: None +24-11-19 20:20:31 | D | + y: None +24-11-19 20:20:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:20:31 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:31 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:31 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:31 | D | - range ratio = [ 1.0000] +24-11-19 20:20:31 | D | sum error = [ 2.4121] +24-11-19 20:20:31 | D | best error = [ 2.4121] +24-11-19 20:20:43 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:43 | D | sum error = [ 2.3900, 2.4067, 2.4452, 2.3949, 2.5522] +24-11-19 20:20:43 | D | best error = [ 2.3900, 2.3900, 2.3900, 2.3900, 2.3900] +24-11-19 20:20:43 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:43 | D | sum error = [ 2.5460, 2.7371, 2.7960, 2.8688, 3.0171] +24-11-19 20:20:43 | D | best error = [ 2.3900, 2.3900, 2.3900, 2.3900, 2.3900] +24-11-19 20:20:43 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:43 | D | sum error = [ 3.2289, 3.5357, 3.7885, 4.1524, 4.4043] +24-11-19 20:20:43 | D | best error = [ 2.3900, 2.3900, 2.3900, 2.3900, 2.3900] +24-11-19 20:20:43 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:43 | D | sum error = [ 4.8571, 5.2076, 5.6865, 6.1439, 6.6837] +24-11-19 20:20:43 | D | best error = [ 2.3900, 2.3900, 2.3900, 2.3900, 2.3900] +24-11-19 20:20:43 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:43 | D | sum error = [ 7.3496, 7.9746, 8.7710, 9.5311, 10.3758] +24-11-19 20:20:43 | D | best error = [ 2.3900, 2.3900, 2.3900, 2.3900, 2.3900] +24-11-19 20:20:43 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:43 | D | sum error = [ 11.3012, 12.1729, 13.2961, 14.3671, 15.7384] +24-11-19 20:20:43 | D | best error = [ 2.3900, 2.3900, 2.3900, 2.3900, 2.3900] +24-11-19 20:20:43 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:43 | D | sum error = [ 16.9945, 18.4673, 19.9108, 21.5246, 23.2844] +24-11-19 20:20:43 | D | best error = [ 2.3900, 2.3900, 2.3900, 2.3900, 2.3900] +24-11-19 20:20:43 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:43 | D | sum error = [ 25.2307, 27.3260, 29.4470, 31.8290, 34.4596] +24-11-19 20:20:43 | D | best error = [ 2.3900, 2.3900, 2.3900, 2.3900, 2.3900] +24-11-19 20:20:43 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:43 | D | sum error = [ 37.0154, 40.0197, 43.0131, 46.1922, 49.7760] +24-11-19 20:20:43 | D | best error = [ 2.3900, 2.3900, 2.3900, 2.3900, 2.3900] +24-11-19 20:20:43 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:43 | D | sum error = [ 53.3785, 57.2432, 61.3204, 65.8382, 70.5764] +24-11-19 20:20:43 | D | best error = [ 2.3900, 2.3900, 2.3900, 2.3900, 2.3900] +24-11-19 20:20:43 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:43 | D | sum error = [ 75.4184, 80.6305, 86.2723, 92.1722, 98.6294] +24-11-19 20:20:43 | D | best error = [ 2.3900, 2.3900, 2.3900, 2.3900, 2.3900] +24-11-19 20:20:43 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:43 | D | sum error = [ 105.5066, 112.6684, 120.2911, 128.5209, 137.0017] +24-11-19 20:20:43 | D | best error = [ 2.3900, 2.3900, 2.3900, 2.3900, 2.3900] +24-11-19 20:20:43 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:43 | D | sum error = [ 146.2942, 156.1608, 166.5995, 177.6380, 189.4479] +24-11-19 20:20:43 | D | best error = [ 2.3900, 2.3900, 2.3900, 2.3900, 2.3900] +24-11-19 20:20:43 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:43 | D | sum error = [ 201.8311, 214.9511, 228.8035, 243.3641, 258.9791] +24-11-19 20:20:43 | D | best error = [ 2.3900, 2.3900, 2.3900, 2.3900, 2.3900] +24-11-19 20:20:43 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:43 | D | sum error = [ 275.3746, 292.6417, 310.7124, 329.5648, 349.2636] +24-11-19 20:20:43 | D | best error = [ 2.3900, 2.3900, 2.3900, 2.3900, 2.3900] +24-11-19 20:20:43 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:43 | D | sum error = [ 369.5787, 390.6769, 412.4157, 434.6272, 457.2531] +24-11-19 20:20:43 | D | best error = [ 2.3900, 2.3900, 2.3900, 2.3900, 2.3900] +24-11-19 20:20:43 | D | + error = [2.3900] +24-11-19 20:20:43 | D | - Calibrating model.layers.6.self_attn.k_proj.weight +24-11-19 20:20:43 | D | + w: sint8 +24-11-19 20:20:43 | D | + x: None +24-11-19 20:20:43 | D | + y: None +24-11-19 20:20:43 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:20:43 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:43 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:43 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:43 | D | - range ratio = [ 1.0000] +24-11-19 20:20:43 | D | sum error = [ 2.2605] +24-11-19 20:20:43 | D | best error = [ 2.2605] +24-11-19 20:20:55 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:55 | D | sum error = [ 2.3872, 2.3715, 2.2974, 2.7267, 2.7188] +24-11-19 20:20:55 | D | best error = [ 2.2605, 2.2605, 2.2605, 2.2605, 2.2605] +24-11-19 20:20:55 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:55 | D | sum error = [ 2.3413, 3.1914, 2.8077, 2.8485, 3.0652] +24-11-19 20:20:55 | D | best error = [ 2.2605, 2.2605, 2.2605, 2.2605, 2.2605] +24-11-19 20:20:55 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:55 | D | sum error = [ 3.5995, 3.7673, 3.9279, 4.0448, 4.9600] +24-11-19 20:20:55 | D | best error = [ 2.2605, 2.2605, 2.2605, 2.2605, 2.2605] +24-11-19 20:20:55 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:55 | D | sum error = [ 5.0215, 5.0152, 5.6286, 6.1061, 6.3026] +24-11-19 20:20:55 | D | best error = [ 2.2605, 2.2605, 2.2605, 2.2605, 2.2605] +24-11-19 20:20:55 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:55 | D | sum error = [ 6.4354, 7.6998, 8.0451, 8.3403, 9.6357] +24-11-19 20:20:55 | D | best error = [ 2.2605, 2.2605, 2.2605, 2.2605, 2.2605] +24-11-19 20:20:55 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:55 | D | sum error = [ 10.4898, 10.7493, 11.7422, 12.7794, 13.6543] +24-11-19 20:20:55 | D | best error = [ 2.2605, 2.2605, 2.2605, 2.2605, 2.2605] +24-11-19 20:20:55 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:55 | D | sum error = [ 15.0070, 16.2485, 17.4462, 18.8192, 20.5765] +24-11-19 20:20:55 | D | best error = [ 2.2605, 2.2605, 2.2605, 2.2605, 2.2605] +24-11-19 20:20:55 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:55 | D | sum error = [ 22.4037, 24.3429, 26.1638, 28.2211, 30.4959] +24-11-19 20:20:55 | D | best error = [ 2.2605, 2.2605, 2.2605, 2.2605, 2.2605] +24-11-19 20:20:55 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:55 | D | sum error = [ 32.8314, 35.7358, 38.3109, 41.3766, 44.5451] +24-11-19 20:20:55 | D | best error = [ 2.2605, 2.2605, 2.2605, 2.2605, 2.2605] +24-11-19 20:20:55 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:55 | D | sum error = [ 48.1472, 52.3389, 55.8548, 60.2152, 64.6512] +24-11-19 20:20:55 | D | best error = [ 2.2605, 2.2605, 2.2605, 2.2605, 2.2605] +24-11-19 20:20:55 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:55 | D | sum error = [ 69.5009, 74.4956, 80.2606, 86.0130, 92.3652] +24-11-19 20:20:55 | D | best error = [ 2.2605, 2.2605, 2.2605, 2.2605, 2.2605] +24-11-19 20:20:55 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:55 | D | sum error = [ 98.8938, 106.1277, 113.8037, 121.7399, 130.0761] +24-11-19 20:20:55 | D | best error = [ 2.2605, 2.2605, 2.2605, 2.2605, 2.2605] +24-11-19 20:20:55 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:55 | D | sum error = [ 139.5763, 149.2180, 159.5320, 171.1740, 182.8055] +24-11-19 20:20:55 | D | best error = [ 2.2605, 2.2605, 2.2605, 2.2605, 2.2605] +24-11-19 20:20:55 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:55 | D | sum error = [ 195.5519, 209.0733, 223.5989, 238.3382, 255.0588] +24-11-19 20:20:55 | D | best error = [ 2.2605, 2.2605, 2.2605, 2.2605, 2.2605] +24-11-19 20:20:55 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:55 | D | sum error = [ 271.9470, 290.3993, 309.3665, 328.4900, 348.7097] +24-11-19 20:20:55 | D | best error = [ 2.2605, 2.2605, 2.2605, 2.2605, 2.2605] +24-11-19 20:20:55 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:55 | D | sum error = [ 370.1035, 391.7050, 414.0028, 436.4669, 459.9811] +24-11-19 20:20:55 | D | best error = [ 2.2605, 2.2605, 2.2605, 2.2605, 2.2605] +24-11-19 20:20:55 | D | + error = [2.2605] +24-11-19 20:20:55 | D | - Calibrating model.layers.6.self_attn.v_proj.weight +24-11-19 20:20:55 | D | + w: sint8 +24-11-19 20:20:55 | D | + x: None +24-11-19 20:20:55 | D | + y: None +24-11-19 20:20:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:55 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:56 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:56 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:56 | D | - range ratio = [ 1.0000] +24-11-19 20:20:56 | D | sum error = [ 1.1027] +24-11-19 20:20:56 | D | best error = [ 1.1027] +24-11-19 20:20:56 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:56 | D | sum error = [ 1.0957, 1.0912, 1.1007, 1.1122, 1.1424] +24-11-19 20:20:56 | D | best error = [ 1.0284, 0.9990, 0.9846, 0.9774, 0.9746] +24-11-19 20:20:56 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:56 | D | sum error = [ 1.1567, 1.1924, 1.2336, 1.2966, 1.3712] +24-11-19 20:20:56 | D | best error = [ 0.9727, 0.9722, 0.9717, 0.9716, 0.9716] +24-11-19 20:20:56 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:56 | D | sum error = [ 1.4548, 1.5435, 1.6493, 1.7466, 1.8752] +24-11-19 20:20:56 | D | best error = [ 0.9716, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:20:56 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:56 | D | sum error = [ 2.0071, 2.1596, 2.3007, 2.4727, 2.6496] +24-11-19 20:20:56 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:20:56 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:56 | D | sum error = [ 2.8291, 3.0312, 3.2430, 3.4692, 3.7042] +24-11-19 20:20:56 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:20:56 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:56 | D | sum error = [ 3.9609, 4.2309, 4.5137, 4.8199, 5.1322] +24-11-19 20:20:56 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:20:56 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:56 | D | sum error = [ 5.4729, 5.8235, 6.2010, 6.6021, 7.0158] +24-11-19 20:20:56 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:20:56 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:56 | D | sum error = [ 7.4625, 7.9123, 8.4071, 8.9200, 9.4698] +24-11-19 20:20:56 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:20:56 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:56 | D | sum error = [ 10.0319, 10.6439, 11.2716, 11.9377, 12.6384] +24-11-19 20:20:56 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:20:56 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:56 | D | sum error = [ 13.3784, 14.1471, 14.9641, 15.8141, 16.7034] +24-11-19 20:20:56 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:20:56 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:56 | D | sum error = [ 17.6404, 18.6223, 19.6394, 20.7172, 21.8291] +24-11-19 20:20:56 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:20:56 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:56 | D | sum error = [ 23.0082, 24.2280, 25.5063, 26.8481, 28.2398] +24-11-19 20:20:56 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:20:56 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:56 | D | sum error = [ 29.6964, 31.2190, 32.7921, 34.4423, 36.1520] +24-11-19 20:20:56 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:20:56 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:56 | D | sum error = [ 37.9293, 39.7691, 41.6832, 43.6622, 45.7143] +24-11-19 20:20:56 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:20:56 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:56 | D | sum error = [ 47.8499, 50.0513, 52.3321, 54.6945, 57.1375] +24-11-19 20:20:56 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:20:56 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:56 | D | sum error = [ 59.6512, 62.2522, 64.9284, 67.6873, 70.5324] +24-11-19 20:20:56 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:20:56 | D | + error = [0.9715] +24-11-19 20:20:56 | D | - Calibrating model.layers.6.self_attn.o_proj.weight +24-11-19 20:20:56 | D | + w: sint8 +24-11-19 20:20:56 | D | + x: None +24-11-19 20:20:56 | D | + y: None +24-11-19 20:20:56 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:56 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:56 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:56 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:56 | D | - range ratio = [ 1.0000] +24-11-19 20:20:56 | D | sum error = [ 0.3658] +24-11-19 20:20:56 | D | best error = [ 0.3658] +24-11-19 20:20:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:57 | D | sum error = [ 0.3632, 0.3645, 0.3643, 0.3695, 0.3754] +24-11-19 20:20:57 | D | best error = [ 0.3373, 0.3257, 0.3186, 0.3143, 0.3114] +24-11-19 20:20:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:57 | D | sum error = [ 0.3849, 0.3965, 0.4123, 0.4311, 0.4512] +24-11-19 20:20:57 | D | best error = [ 0.3100, 0.3089, 0.3082, 0.3077, 0.3074] +24-11-19 20:20:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:57 | D | sum error = [ 0.4777, 0.5028, 0.5315, 0.5619, 0.6005] +24-11-19 20:20:57 | D | best error = [ 0.3071, 0.3068, 0.3067, 0.3066, 0.3065] +24-11-19 20:20:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:57 | D | sum error = [ 0.6389, 0.6787, 0.7215, 0.7688, 0.8186] +24-11-19 20:20:57 | D | best error = [ 0.3065, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:20:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:57 | D | sum error = [ 0.8700, 0.9266, 0.9854, 1.0467, 1.1119] +24-11-19 20:20:57 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:20:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:57 | D | sum error = [ 1.1817, 1.2512, 1.3274, 1.4067, 1.4906] +24-11-19 20:20:57 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:20:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:57 | D | sum error = [ 1.5770, 1.6686, 1.7646, 1.8652, 1.9707] +24-11-19 20:20:57 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:20:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:57 | D | sum error = [ 2.0797, 2.1950, 2.3163, 2.4404, 2.5729] +24-11-19 20:20:57 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:20:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:57 | D | sum error = [ 2.7099, 2.8548, 3.0064, 3.1647, 3.3297] +24-11-19 20:20:57 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:20:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:57 | D | sum error = [ 3.5038, 3.6846, 3.8737, 4.0721, 4.2777] +24-11-19 20:20:57 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:20:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:57 | D | sum error = [ 4.4932, 4.7173, 4.9503, 5.1924, 5.4453] +24-11-19 20:20:57 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:20:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:57 | D | sum error = [ 5.7074, 5.9806, 6.2659, 6.5612, 6.8695] +24-11-19 20:20:57 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:20:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:57 | D | sum error = [ 7.1904, 7.5228, 7.8678, 8.2259, 8.5967] +24-11-19 20:20:57 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:20:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:57 | D | sum error = [ 8.9824, 9.3806, 9.7944, 10.2231, 10.6647] +24-11-19 20:20:57 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:20:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:57 | D | sum error = [ 11.1238, 11.5974, 12.0869, 12.5934, 13.1172] +24-11-19 20:20:57 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:20:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:57 | D | sum error = [ 13.6587, 14.2181, 14.7961, 15.3933, 16.0099] +24-11-19 20:20:57 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:20:57 | D | + error = [0.3064] +24-11-19 20:20:57 | D | - Calibrating model.layers.6.mlp.up_proj.weight +24-11-19 20:20:57 | D | + w: sint8 +24-11-19 20:20:57 | D | + x: None +24-11-19 20:20:57 | D | + y: None +24-11-19 20:20:57 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:57 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:57 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:57 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:57 | D | - range ratio = [ 1.0000] +24-11-19 20:20:57 | D | sum error = [ 4.6048] +24-11-19 20:20:57 | D | best error = [ 4.6048] +24-11-19 20:20:58 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:58 | D | sum error = [ 4.5752, 4.5582, 4.5796, 4.6402, 4.7251] +24-11-19 20:20:58 | D | best error = [ 4.3024, 4.1885, 4.1248, 4.0899, 4.0726] +24-11-19 20:20:58 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:58 | D | sum error = [ 4.8312, 4.9963, 5.2097, 5.4387, 5.7220] +24-11-19 20:20:58 | D | best error = [ 4.0635, 4.0603, 4.0592, 4.0588, 4.0587] +24-11-19 20:20:58 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:58 | D | sum error = [ 6.0577, 6.4311, 6.8528, 7.3132, 7.8158] +24-11-19 20:20:58 | D | best error = [ 4.0587, 4.0587, 4.0587, 4.0587, 4.0587] +24-11-19 20:20:58 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:58 | D | sum error = [ 8.3580, 8.9582, 9.5978, 10.2743, 11.0164] +24-11-19 20:20:58 | D | best error = [ 4.0587, 4.0587, 4.0587, 4.0587, 4.0587] +24-11-19 20:20:58 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:58 | D | sum error = [ 11.7991, 12.6287, 13.5296, 14.4737, 15.4768] +24-11-19 20:20:58 | D | best error = [ 4.0587, 4.0587, 4.0587, 4.0587, 4.0587] +24-11-19 20:20:58 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:58 | D | sum error = [ 16.5435, 17.6614, 18.8577, 20.1140, 21.4431] +24-11-19 20:20:58 | D | best error = [ 4.0587, 4.0587, 4.0587, 4.0587, 4.0587] +24-11-19 20:20:58 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:58 | D | sum error = [ 22.8482, 24.3299, 25.9013, 27.5467, 29.2705] +24-11-19 20:20:58 | D | best error = [ 4.0587, 4.0587, 4.0587, 4.0587, 4.0587] +24-11-19 20:20:58 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:58 | D | sum error = [ 31.1015, 33.0176, 35.0288, 37.1577, 39.3901] +24-11-19 20:20:58 | D | best error = [ 4.0587, 4.0587, 4.0587, 4.0587, 4.0587] +24-11-19 20:20:58 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:58 | D | sum error = [ 41.7211, 44.1766, 46.7497, 49.4543, 52.2791] +24-11-19 20:20:58 | D | best error = [ 4.0587, 4.0587, 4.0587, 4.0587, 4.0587] +24-11-19 20:20:58 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:58 | D | sum error = [ 55.2352, 58.3296, 61.5644, 64.9536, 68.5031] +24-11-19 20:20:58 | D | best error = [ 4.0587, 4.0587, 4.0587, 4.0587, 4.0587] +24-11-19 20:20:58 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:58 | D | sum error = [ 72.1966, 76.0592, 80.0945, 84.3045, 88.6974] +24-11-19 20:20:58 | D | best error = [ 4.0587, 4.0587, 4.0587, 4.0587, 4.0587] +24-11-19 20:20:58 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:58 | D | sum error = [ 93.2650, 98.0224, 102.9740, 108.1382, 113.4873] +24-11-19 20:20:58 | D | best error = [ 4.0587, 4.0587, 4.0587, 4.0587, 4.0587] +24-11-19 20:20:58 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:58 | D | sum error = [ 119.0551, 124.8397, 130.8428, 137.0711, 143.5291] +24-11-19 20:20:58 | D | best error = [ 4.0587, 4.0587, 4.0587, 4.0587, 4.0587] +24-11-19 20:20:58 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:58 | D | sum error = [ 150.2347, 157.1657, 164.3638, 171.8046, 179.5001] +24-11-19 20:20:58 | D | best error = [ 4.0587, 4.0587, 4.0587, 4.0587, 4.0587] +24-11-19 20:20:58 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:58 | D | sum error = [ 187.4452, 195.6494, 204.1091, 212.8560, 221.8644] +24-11-19 20:20:58 | D | best error = [ 4.0587, 4.0587, 4.0587, 4.0587, 4.0587] +24-11-19 20:20:58 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:58 | D | sum error = [ 231.1578, 240.7258, 250.5829, 260.7126, 271.1356] +24-11-19 20:20:58 | D | best error = [ 4.0587, 4.0587, 4.0587, 4.0587, 4.0587] +24-11-19 20:20:58 | D | + error = [4.0587] +24-11-19 20:20:58 | D | - Calibrating model.layers.6.mlp.gate_proj.weight +24-11-19 20:20:58 | D | + w: sint8 +24-11-19 20:20:58 | D | + x: None +24-11-19 20:20:58 | D | + y: None +24-11-19 20:20:58 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:58 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:58 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:58 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:58 | D | - range ratio = [ 1.0000] +24-11-19 20:20:58 | D | sum error = [ 6.1107] +24-11-19 20:20:58 | D | best error = [ 6.1107] +24-11-19 20:21:00 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:00 | D | sum error = [ 6.0622, 6.0485, 6.0675, 6.1396, 6.2555] +24-11-19 20:21:00 | D | best error = [ 5.7028, 5.5487, 5.4697, 5.4239, 5.4017] +24-11-19 20:21:00 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:00 | D | sum error = [ 6.4336, 6.6375, 6.9192, 7.2442, 7.6370] +24-11-19 20:21:00 | D | best error = [ 5.3906, 5.3862, 5.3850, 5.3845, 5.3844] +24-11-19 20:21:00 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:00 | D | sum error = [ 8.0795, 8.5821, 9.1399, 9.7948, 10.4627] +24-11-19 20:21:00 | D | best error = [ 5.3844, 5.3844, 5.3844, 5.3844, 5.3844] +24-11-19 20:21:00 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:00 | D | sum error = [ 11.2294, 12.0334, 12.9126, 13.8539, 14.8837] +24-11-19 20:21:00 | D | best error = [ 5.3844, 5.3844, 5.3844, 5.3844, 5.3844] +24-11-19 20:21:00 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:00 | D | sum error = [ 15.9819, 17.1475, 18.3853, 19.7276, 21.1388] +24-11-19 20:21:00 | D | best error = [ 5.3844, 5.3844, 5.3844, 5.3844, 5.3844] +24-11-19 20:21:00 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:00 | D | sum error = [ 22.6416, 24.2582, 25.9562, 27.7584, 29.6803] +24-11-19 20:21:00 | D | best error = [ 5.3844, 5.3844, 5.3844, 5.3844, 5.3844] +24-11-19 20:21:00 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:00 | D | sum error = [ 31.7297, 33.9137, 36.1996, 38.6391, 41.2394] +24-11-19 20:21:00 | D | best error = [ 5.3844, 5.3844, 5.3844, 5.3844, 5.3844] +24-11-19 20:21:00 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:00 | D | sum error = [ 43.9906, 46.8855, 49.9798, 53.2414, 56.7036] +24-11-19 20:21:00 | D | best error = [ 5.3844, 5.3844, 5.3844, 5.3844, 5.3844] +24-11-19 20:21:00 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:00 | D | sum error = [ 60.3787, 64.2669, 68.3718, 72.7407, 77.3378] +24-11-19 20:21:00 | D | best error = [ 5.3844, 5.3844, 5.3844, 5.3844, 5.3844] +24-11-19 20:21:00 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:00 | D | sum error = [ 82.2117, 87.3837, 92.8349, 98.6009, 104.6908] +24-11-19 20:21:00 | D | best error = [ 5.3844, 5.3844, 5.3844, 5.3844, 5.3844] +24-11-19 20:21:00 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:00 | D | sum error = [ 111.1097, 117.8958, 125.0400, 132.5832, 140.5108] +24-11-19 20:21:00 | D | best error = [ 5.3844, 5.3844, 5.3844, 5.3844, 5.3844] +24-11-19 20:21:00 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:00 | D | sum error = [ 148.8520, 157.6351, 166.8916, 176.5994, 186.7975] +24-11-19 20:21:00 | D | best error = [ 5.3844, 5.3844, 5.3844, 5.3844, 5.3844] +24-11-19 20:21:00 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:00 | D | sum error = [ 197.5017, 208.7116, 220.4544, 232.7489, 245.6133] +24-11-19 20:21:00 | D | best error = [ 5.3844, 5.3844, 5.3844, 5.3844, 5.3844] +24-11-19 20:21:00 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:00 | D | sum error = [ 259.0452, 273.0754, 287.7167, 302.9758, 318.8766] +24-11-19 20:21:00 | D | best error = [ 5.3844, 5.3844, 5.3844, 5.3844, 5.3844] +24-11-19 20:21:00 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:00 | D | sum error = [ 335.4193, 352.6046, 370.4559, 388.9689, 408.1383] +24-11-19 20:21:00 | D | best error = [ 5.3844, 5.3844, 5.3844, 5.3844, 5.3844] +24-11-19 20:21:00 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:00 | D | sum error = [ 428.0101, 448.5664, 469.8091, 491.7264, 514.3242] +24-11-19 20:21:00 | D | best error = [ 5.3844, 5.3844, 5.3844, 5.3844, 5.3844] +24-11-19 20:21:00 | D | + error = [5.3844] +24-11-19 20:21:00 | D | - Calibrating model.layers.6.mlp.down_proj.weight +24-11-19 20:21:00 | D | + w: sint8 +24-11-19 20:21:00 | D | + x: None +24-11-19 20:21:00 | D | + y: None +24-11-19 20:21:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:00 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:00 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:00 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:00 | D | - range ratio = [ 1.0000] +24-11-19 20:21:00 | D | sum error = [ 0.5203] +24-11-19 20:21:00 | D | best error = [ 0.5203] +24-11-19 20:21:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:01 | D | sum error = [ 0.5157, 0.5109, 0.5083, 0.5064, 0.5061] +24-11-19 20:21:01 | D | best error = [ 0.5010, 0.4908, 0.4841, 0.4789, 0.4752] +24-11-19 20:21:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:01 | D | sum error = [ 0.5072, 0.5091, 0.5141, 0.5194, 0.5295] +24-11-19 20:21:01 | D | best error = [ 0.4724, 0.4700, 0.4683, 0.4672, 0.4663] +24-11-19 20:21:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:01 | D | sum error = [ 0.5416, 0.5557, 0.5747, 0.5952, 0.6194] +24-11-19 20:21:01 | D | best error = [ 0.4657, 0.4653, 0.4650, 0.4648, 0.4646] +24-11-19 20:21:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:01 | D | sum error = [ 0.6469, 0.6784, 0.7147, 0.7549, 0.7996] +24-11-19 20:21:01 | D | best error = [ 0.4645, 0.4645, 0.4645, 0.4645, 0.4644] +24-11-19 20:21:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:01 | D | sum error = [ 0.8483, 0.9029, 0.9611, 1.0242, 1.0938] +24-11-19 20:21:01 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 20:21:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:01 | D | sum error = [ 1.1684, 1.2488, 1.3351, 1.4276, 1.5264] +24-11-19 20:21:01 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 20:21:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:01 | D | sum error = [ 1.6316, 1.7449, 1.8667, 1.9947, 2.1322] +24-11-19 20:21:01 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 20:21:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:01 | D | sum error = [ 2.2766, 2.4320, 2.5962, 2.7693, 2.9538] +24-11-19 20:21:01 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 20:21:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:01 | D | sum error = [ 3.1490, 3.3558, 3.5752, 3.8063, 4.0506] +24-11-19 20:21:01 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 20:21:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:01 | D | sum error = [ 4.3089, 4.5810, 4.8683, 5.1705, 5.4897] +24-11-19 20:21:01 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 20:21:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:01 | D | sum error = [ 5.8259, 6.1782, 6.5497, 6.9398, 7.3492] +24-11-19 20:21:01 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 20:21:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:01 | D | sum error = [ 7.7794, 8.2313, 8.7040, 9.1987, 9.7165] +24-11-19 20:21:01 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 20:21:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:01 | D | sum error = [ 10.2585, 10.8252, 11.4174, 12.0358, 12.6805] +24-11-19 20:21:01 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 20:21:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:01 | D | sum error = [ 13.3534, 14.0541, 14.7839, 15.5438, 16.3325] +24-11-19 20:21:01 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 20:21:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:01 | D | sum error = [ 17.1533, 18.0050, 18.8894, 19.8068, 20.7577] +24-11-19 20:21:01 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 20:21:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:01 | D | sum error = [ 21.7426, 22.7625, 23.8181, 24.9100, 26.0377] +24-11-19 20:21:01 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 20:21:01 | D | + error = [0.4644] +24-11-19 20:21:01 | D | - Quantizing model.layers.6.self_attn.q_proj.weight +24-11-19 20:21:03 | D | - Quantizing model.layers.6.self_attn.k_proj.weight +24-11-19 20:21:08 | D | - Quantizing model.layers.6.self_attn.v_proj.weight +24-11-19 20:21:10 | D | - Quantizing model.layers.6.self_attn.o_proj.weight +24-11-19 20:21:11 | D | - Quantizing model.layers.6.mlp.up_proj.weight +24-11-19 20:21:12 | D | - Quantizing model.layers.6.mlp.gate_proj.weight +24-11-19 20:21:13 | D | - Quantizing model.layers.6.mlp.down_proj.weight +24-11-19 20:21:23 | D | - Quantizing layer model.layers.7 +24-11-19 20:21:23 | D | - Calibrating model.layers.7.self_attn.q_proj.weight +24-11-19 20:21:23 | D | + w: sint8 +24-11-19 20:21:23 | D | + x: None +24-11-19 20:21:23 | D | + y: None +24-11-19 20:21:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:21:23 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:23 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:24 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:24 | D | - range ratio = [ 1.0000] +24-11-19 20:21:24 | D | sum error = [ 2.9789] +24-11-19 20:21:24 | D | best error = [ 2.9789] +24-11-19 20:21:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:35 | D | sum error = [ 3.0443, 3.0330, 3.0040, 3.0426, 3.1252] +24-11-19 20:21:35 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:21:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:35 | D | sum error = [ 3.2023, 3.3448, 3.4555, 3.7735, 4.0069] +24-11-19 20:21:35 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:21:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:35 | D | sum error = [ 4.1046, 4.3399, 4.6806, 5.1174, 5.5711] +24-11-19 20:21:35 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:21:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:35 | D | sum error = [ 5.9237, 6.4324, 6.9684, 7.7086, 8.5113] +24-11-19 20:21:35 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:21:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:35 | D | sum error = [ 9.2906, 10.3196, 11.4538, 12.6351, 13.5293] +24-11-19 20:21:35 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:21:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:35 | D | sum error = [ 15.2086, 16.4631, 18.0239, 19.9953, 21.6852] +24-11-19 20:21:35 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:21:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:35 | D | sum error = [ 23.7743, 25.9138, 28.4876, 31.0213, 33.7566] +24-11-19 20:21:35 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:21:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:35 | D | sum error = [ 37.0125, 40.1612, 43.6668, 47.2602, 51.1331] +24-11-19 20:21:35 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:21:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:35 | D | sum error = [ 55.3984, 59.7389, 64.3750, 69.3468, 74.7749] +24-11-19 20:21:35 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:21:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:35 | D | sum error = [ 80.4054, 86.1289, 92.2853, 98.7920, 105.6667] +24-11-19 20:21:35 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:21:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:35 | D | sum error = [ 112.8652, 120.7391, 128.7209, 136.9886, 146.0022] +24-11-19 20:21:35 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:21:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:35 | D | sum error = [ 155.5516, 165.3769, 175.7751, 186.5114, 197.8125] +24-11-19 20:21:35 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:21:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:35 | D | sum error = [ 209.6564, 222.0312, 234.7954, 247.8484, 261.7160] +24-11-19 20:21:35 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:21:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:35 | D | sum error = [ 275.9596, 290.4257, 305.3216, 320.8835, 336.5719] +24-11-19 20:21:35 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:21:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:35 | D | sum error = [ 352.8655, 369.6992, 386.9244, 404.7384, 422.7993] +24-11-19 20:21:35 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:21:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:35 | D | sum error = [ 441.4000, 460.2994, 479.7075, 499.3996, 519.5023] +24-11-19 20:21:35 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:21:35 | D | + error = [2.9789] +24-11-19 20:21:35 | D | - Calibrating model.layers.7.self_attn.k_proj.weight +24-11-19 20:21:35 | D | + w: sint8 +24-11-19 20:21:35 | D | + x: None +24-11-19 20:21:35 | D | + y: None +24-11-19 20:21:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:21:35 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:35 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:36 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:36 | D | - range ratio = [ 1.0000] +24-11-19 20:21:36 | D | sum error = [ 3.1071] +24-11-19 20:21:36 | D | best error = [ 3.1071] +24-11-19 20:21:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:48 | D | sum error = [ 3.1245, 3.1378, 3.0674, 2.7602, 3.3573] +24-11-19 20:21:48 | D | best error = [ 3.1071, 3.1071, 3.0674, 2.7602, 2.7602] +24-11-19 20:21:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:48 | D | sum error = [ 2.9951, 3.0190, 3.4219, 3.6327, 3.6640] +24-11-19 20:21:48 | D | best error = [ 2.7602, 2.7602, 2.7602, 2.7602, 2.7602] +24-11-19 20:21:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:48 | D | sum error = [ 3.6493, 3.9515, 4.6863, 4.9299, 5.4348] +24-11-19 20:21:48 | D | best error = [ 2.7602, 2.7602, 2.7602, 2.7602, 2.7602] +24-11-19 20:21:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:48 | D | sum error = [ 5.7241, 5.9286, 6.3795, 7.2293, 7.8145] +24-11-19 20:21:48 | D | best error = [ 2.7602, 2.7602, 2.7602, 2.7602, 2.7602] +24-11-19 20:21:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:48 | D | sum error = [ 8.7558, 9.3326, 10.0648, 10.6626, 11.7853] +24-11-19 20:21:48 | D | best error = [ 2.7602, 2.7602, 2.7602, 2.7602, 2.7602] +24-11-19 20:21:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:48 | D | sum error = [ 12.6020, 13.9273, 14.4396, 16.4505, 17.2415] +24-11-19 20:21:48 | D | best error = [ 2.7602, 2.7602, 2.7602, 2.7602, 2.7602] +24-11-19 20:21:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:48 | D | sum error = [ 18.8011, 20.1435, 22.6101, 23.7426, 26.1996] +24-11-19 20:21:48 | D | best error = [ 2.7602, 2.7602, 2.7602, 2.7602, 2.7602] +24-11-19 20:21:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:48 | D | sum error = [ 29.2517, 31.8680, 34.5889, 38.0192, 41.2425] +24-11-19 20:21:48 | D | best error = [ 2.7602, 2.7602, 2.7602, 2.7602, 2.7602] +24-11-19 20:21:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:48 | D | sum error = [ 45.2991, 49.1431, 53.4199, 57.5069, 61.7136] +24-11-19 20:21:48 | D | best error = [ 2.7602, 2.7602, 2.7602, 2.7602, 2.7602] +24-11-19 20:21:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:48 | D | sum error = [ 67.4818, 72.5951, 78.5147, 84.6305, 91.1143] +24-11-19 20:21:48 | D | best error = [ 2.7602, 2.7602, 2.7602, 2.7602, 2.7602] +24-11-19 20:21:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:48 | D | sum error = [ 97.9405, 105.1780, 112.3975, 120.2225, 129.6356] +24-11-19 20:21:48 | D | best error = [ 2.7602, 2.7602, 2.7602, 2.7602, 2.7602] +24-11-19 20:21:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:48 | D | sum error = [ 138.3009, 147.6260, 156.1895, 166.5254, 176.7743] +24-11-19 20:21:48 | D | best error = [ 2.7602, 2.7602, 2.7602, 2.7602, 2.7602] +24-11-19 20:21:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:48 | D | sum error = [ 187.9512, 198.6435, 211.1321, 223.0972, 234.7753] +24-11-19 20:21:48 | D | best error = [ 2.7602, 2.7602, 2.7602, 2.7602, 2.7602] +24-11-19 20:21:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:48 | D | sum error = [ 249.5824, 264.2808, 279.4007, 295.1304, 312.3989] +24-11-19 20:21:48 | D | best error = [ 2.7602, 2.7602, 2.7602, 2.7602, 2.7602] +24-11-19 20:21:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:48 | D | sum error = [ 329.0065, 347.3609, 366.6840, 386.2819, 405.7505] +24-11-19 20:21:48 | D | best error = [ 2.7602, 2.7602, 2.7602, 2.7602, 2.7602] +24-11-19 20:21:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:48 | D | sum error = [ 426.5000, 447.3660, 468.4410, 489.9762, 511.7319] +24-11-19 20:21:48 | D | best error = [ 2.7602, 2.7602, 2.7602, 2.7602, 2.7602] +24-11-19 20:21:48 | D | + error = [2.7602] +24-11-19 20:21:48 | D | - Calibrating model.layers.7.self_attn.v_proj.weight +24-11-19 20:21:48 | D | + w: sint8 +24-11-19 20:21:48 | D | + x: None +24-11-19 20:21:48 | D | + y: None +24-11-19 20:21:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:48 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:48 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:48 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:48 | D | - range ratio = [ 1.0000] +24-11-19 20:21:48 | D | sum error = [ 1.1249] +24-11-19 20:21:48 | D | best error = [ 1.1249] +24-11-19 20:21:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:48 | D | sum error = [ 1.1199, 1.1085, 1.1299, 1.1321, 1.1591] +24-11-19 20:21:48 | D | best error = [ 1.0515, 1.0210, 1.0086, 1.0001, 0.9957] +24-11-19 20:21:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:48 | D | sum error = [ 1.1907, 1.2355, 1.2745, 1.3361, 1.4066] +24-11-19 20:21:48 | D | best error = [ 0.9935, 0.9925, 0.9922, 0.9921, 0.9921] +24-11-19 20:21:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:48 | D | sum error = [ 1.4878, 1.5789, 1.6868, 1.8055, 1.9353] +24-11-19 20:21:48 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:21:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:48 | D | sum error = [ 2.0685, 2.2238, 2.3759, 2.5632, 2.7579] +24-11-19 20:21:48 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:21:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:48 | D | sum error = [ 2.9356, 3.1512, 3.3771, 3.6219, 3.8686] +24-11-19 20:21:48 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:21:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:48 | D | sum error = [ 4.1491, 4.4317, 4.7418, 5.0630, 5.3926] +24-11-19 20:21:48 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:21:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:48 | D | sum error = [ 5.7566, 6.1291, 6.5343, 6.9568, 7.4034] +24-11-19 20:21:48 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:21:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:48 | D | sum error = [ 7.8810, 8.3781, 8.8991, 9.4552, 10.0462] +24-11-19 20:21:48 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:21:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:48 | D | sum error = [ 10.6642, 11.3071, 11.9922, 12.7133, 13.4618] +24-11-19 20:21:48 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:21:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:48 | D | sum error = [ 14.2609, 15.0906, 15.9592, 16.8739, 17.8271] +24-11-19 20:21:48 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:21:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:48 | D | sum error = [ 18.8384, 19.8928, 21.0052, 22.1702, 23.3842] +24-11-19 20:21:48 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:21:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:48 | D | sum error = [ 24.6594, 25.9890, 27.3875, 28.8502, 30.3807] +24-11-19 20:21:48 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:21:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:48 | D | sum error = [ 31.9761, 33.6430, 35.3721, 37.1793, 39.0546] +24-11-19 20:21:48 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:21:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:48 | D | sum error = [ 40.9993, 43.0162, 45.1189, 47.3033, 49.5732] +24-11-19 20:21:48 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:21:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:48 | D | sum error = [ 51.9218, 54.3647, 56.8911, 59.5154, 62.2241] +24-11-19 20:21:48 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:21:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:48 | D | sum error = [ 65.0229, 67.9188, 70.9071, 73.9882, 77.1598] +24-11-19 20:21:48 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:21:48 | D | + error = [0.9921] +24-11-19 20:21:48 | D | - Calibrating model.layers.7.self_attn.o_proj.weight +24-11-19 20:21:48 | D | + w: sint8 +24-11-19 20:21:48 | D | + x: None +24-11-19 20:21:48 | D | + y: None +24-11-19 20:21:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:48 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:48 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:48 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:48 | D | - range ratio = [ 1.0000] +24-11-19 20:21:48 | D | sum error = [ 0.4496] +24-11-19 20:21:48 | D | best error = [ 0.4496] +24-11-19 20:21:49 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:49 | D | sum error = [ 0.4475, 0.4437, 0.4447, 0.4467, 0.4540] +24-11-19 20:21:49 | D | best error = [ 0.4121, 0.3951, 0.3850, 0.3786, 0.3743] +24-11-19 20:21:49 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:49 | D | sum error = [ 0.4631, 0.4731, 0.4871, 0.5047, 0.5263] +24-11-19 20:21:49 | D | best error = [ 0.3719, 0.3702, 0.3692, 0.3684, 0.3680] +24-11-19 20:21:49 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:49 | D | sum error = [ 0.5504, 0.5750, 0.6075, 0.6398, 0.6770] +24-11-19 20:21:49 | D | best error = [ 0.3677, 0.3675, 0.3675, 0.3674, 0.3674] +24-11-19 20:21:49 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:49 | D | sum error = [ 0.7183, 0.7624, 0.8106, 0.8605, 0.9133] +24-11-19 20:21:49 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:21:49 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:49 | D | sum error = [ 0.9709, 1.0342, 1.0967, 1.1679, 1.2399] +24-11-19 20:21:49 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:21:49 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:49 | D | sum error = [ 1.3157, 1.3972, 1.4839, 1.5729, 1.6664] +24-11-19 20:21:49 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:21:49 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:49 | D | sum error = [ 1.7681, 1.8730, 1.9829, 2.1017, 2.2250] +24-11-19 20:21:49 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:21:49 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:49 | D | sum error = [ 2.3553, 2.4906, 2.6325, 2.7810, 2.9377] +24-11-19 20:21:49 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:21:49 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:49 | D | sum error = [ 3.1024, 3.2735, 3.4526, 3.6411, 3.8386] +24-11-19 20:21:49 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:21:49 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:49 | D | sum error = [ 4.0455, 4.2624, 4.4850, 4.7202, 4.9682] +24-11-19 20:21:49 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:21:49 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:49 | D | sum error = [ 5.2259, 5.4941, 5.7740, 6.0664, 6.3705] +24-11-19 20:21:49 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:21:49 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:49 | D | sum error = [ 6.6888, 7.0197, 7.3628, 7.7217, 8.0942] +24-11-19 20:21:49 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:21:49 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:49 | D | sum error = [ 8.4822, 8.8859, 9.3067, 9.7437, 10.1956] +24-11-19 20:21:49 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:21:49 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:49 | D | sum error = [ 10.6669, 11.1531, 11.6600, 12.1861, 12.7275] +24-11-19 20:21:49 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:21:49 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:49 | D | sum error = [ 13.2909, 13.8739, 14.4779, 15.1043, 15.7534] +24-11-19 20:21:49 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:21:49 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:49 | D | sum error = [ 16.4251, 17.1173, 17.8338, 18.5736, 19.3380] +24-11-19 20:21:49 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:21:49 | D | + error = [0.3674] +24-11-19 20:21:49 | D | - Calibrating model.layers.7.mlp.up_proj.weight +24-11-19 20:21:49 | D | + w: sint8 +24-11-19 20:21:49 | D | + x: None +24-11-19 20:21:49 | D | + y: None +24-11-19 20:21:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:49 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:49 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:49 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:49 | D | - range ratio = [ 1.0000] +24-11-19 20:21:49 | D | sum error = [ 4.6659] +24-11-19 20:21:49 | D | best error = [ 4.6659] +24-11-19 20:21:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:50 | D | sum error = [ 4.6410, 4.6288, 4.6488, 4.7027, 4.7907] +24-11-19 20:21:50 | D | best error = [ 4.3839, 4.2701, 4.2085, 4.1743, 4.1572] +24-11-19 20:21:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:50 | D | sum error = [ 4.9144, 5.0767, 5.2803, 5.5319, 5.8069] +24-11-19 20:21:50 | D | best error = [ 4.1483, 4.1449, 4.1437, 4.1434, 4.1433] +24-11-19 20:21:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:50 | D | sum error = [ 6.1500, 6.5394, 6.9589, 7.4258, 7.9270] +24-11-19 20:21:50 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 20:21:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:50 | D | sum error = [ 8.4883, 9.0836, 9.7309, 10.4403, 11.1904] +24-11-19 20:21:50 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 20:21:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:50 | D | sum error = [ 11.9937, 12.8414, 13.7437, 14.7060, 15.7192] +24-11-19 20:21:50 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 20:21:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:50 | D | sum error = [ 16.8098, 17.9550, 19.1694, 20.4579, 21.8142] +24-11-19 20:21:50 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 20:21:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:50 | D | sum error = [ 23.2598, 24.7711, 26.3566, 28.0514, 29.8227] +24-11-19 20:21:50 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 20:21:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:50 | D | sum error = [ 31.6939, 33.6672, 35.7286, 37.8948, 40.1758] +24-11-19 20:21:50 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 20:21:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:50 | D | sum error = [ 42.5690, 45.0947, 47.7306, 50.5202, 53.4217] +24-11-19 20:21:50 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 20:21:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:50 | D | sum error = [ 56.4785, 59.6828, 63.0382, 66.5535, 70.2262] +24-11-19 20:21:50 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 20:21:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:50 | D | sum error = [ 74.0740, 78.0890, 82.3027, 86.6834, 91.2684] +24-11-19 20:21:50 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 20:21:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:50 | D | sum error = [ 96.0454, 101.0303, 106.2235, 111.6367, 117.2756] +24-11-19 20:21:50 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 20:21:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:50 | D | sum error = [ 123.1395, 129.2437, 135.5739, 142.1655, 148.9995] +24-11-19 20:21:50 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 20:21:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:50 | D | sum error = [ 156.0914, 163.4441, 171.0838, 178.9948, 187.1834] +24-11-19 20:21:50 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 20:21:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:50 | D | sum error = [ 195.6613, 204.4334, 213.4935, 222.8614, 232.5271] +24-11-19 20:21:50 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 20:21:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:50 | D | sum error = [ 242.4949, 252.7701, 263.3604, 274.2510, 285.4616] +24-11-19 20:21:50 | D | best error = [ 4.1433, 4.1433, 4.1433, 4.1433, 4.1433] +24-11-19 20:21:50 | D | + error = [4.1433] +24-11-19 20:21:50 | D | - Calibrating model.layers.7.mlp.gate_proj.weight +24-11-19 20:21:50 | D | + w: sint8 +24-11-19 20:21:50 | D | + x: None +24-11-19 20:21:50 | D | + y: None +24-11-19 20:21:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:50 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:51 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:51 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:51 | D | - range ratio = [ 1.0000] +24-11-19 20:21:51 | D | sum error = [ 6.0136] +24-11-19 20:21:51 | D | best error = [ 6.0136] +24-11-19 20:21:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:52 | D | sum error = [ 5.9724, 5.9573, 5.9818, 6.0588, 6.1475] +24-11-19 20:21:52 | D | best error = [ 5.6383, 5.4908, 5.4114, 5.3687, 5.3457] +24-11-19 20:21:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:52 | D | sum error = [ 6.3128, 6.5432, 6.7937, 7.1166, 7.4979] +24-11-19 20:21:52 | D | best error = [ 5.3351, 5.3305, 5.3296, 5.3292, 5.3292] +24-11-19 20:21:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:52 | D | sum error = [ 7.9409, 8.4336, 8.9927, 9.6055, 10.2926] +24-11-19 20:21:52 | D | best error = [ 5.3292, 5.3292, 5.3292, 5.3292, 5.3292] +24-11-19 20:21:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:52 | D | sum error = [ 11.0289, 11.8167, 12.6932, 13.6236, 14.6304] +24-11-19 20:21:52 | D | best error = [ 5.3292, 5.3292, 5.3292, 5.3292, 5.3292] +24-11-19 20:21:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:52 | D | sum error = [ 15.6926, 16.8489, 18.0866, 19.3968, 20.7885] +24-11-19 20:21:52 | D | best error = [ 5.3292, 5.3292, 5.3292, 5.3292, 5.3292] +24-11-19 20:21:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:52 | D | sum error = [ 22.2776, 23.8776, 25.5589, 27.3552, 29.2766] +24-11-19 20:21:52 | D | best error = [ 5.3292, 5.3292, 5.3292, 5.3292, 5.3292] +24-11-19 20:21:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:52 | D | sum error = [ 31.3048, 33.4660, 35.7557, 38.1830, 40.7696] +24-11-19 20:21:52 | D | best error = [ 5.3292, 5.3292, 5.3292, 5.3292, 5.3292] +24-11-19 20:21:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:52 | D | sum error = [ 43.5168, 46.4230, 49.4958, 52.7677, 56.2440] +24-11-19 20:21:52 | D | best error = [ 5.3292, 5.3292, 5.3292, 5.3292, 5.3292] +24-11-19 20:21:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:52 | D | sum error = [ 59.9279, 63.8436, 67.9821, 72.3721, 77.0276] +24-11-19 20:21:52 | D | best error = [ 5.3292, 5.3292, 5.3292, 5.3292, 5.3292] +24-11-19 20:21:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:52 | D | sum error = [ 81.9558, 87.1755, 92.6887, 98.5317, 104.7040] +24-11-19 20:21:52 | D | best error = [ 5.3292, 5.3292, 5.3292, 5.3292, 5.3292] +24-11-19 20:21:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:52 | D | sum error = [ 111.2090, 118.1077, 125.3723, 133.0618, 141.1513] +24-11-19 20:21:52 | D | best error = [ 5.3292, 5.3292, 5.3292, 5.3292, 5.3292] +24-11-19 20:21:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:52 | D | sum error = [ 149.6877, 158.6746, 168.1161, 178.0521, 188.5101] +24-11-19 20:21:52 | D | best error = [ 5.3292, 5.3292, 5.3292, 5.3292, 5.3292] +24-11-19 20:21:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:52 | D | sum error = [ 199.4868, 211.0143, 223.1017, 235.7624, 249.0317] +24-11-19 20:21:52 | D | best error = [ 5.3292, 5.3292, 5.3292, 5.3292, 5.3292] +24-11-19 20:21:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:52 | D | sum error = [ 262.8919, 277.3934, 292.5289, 308.3282, 324.7794] +24-11-19 20:21:52 | D | best error = [ 5.3292, 5.3292, 5.3292, 5.3292, 5.3292] +24-11-19 20:21:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:52 | D | sum error = [ 341.8931, 359.7192, 378.2432, 397.4528, 417.3614] +24-11-19 20:21:52 | D | best error = [ 5.3292, 5.3292, 5.3292, 5.3292, 5.3292] +24-11-19 20:21:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:52 | D | sum error = [ 438.0172, 459.3691, 481.4712, 504.2571, 527.7367] +24-11-19 20:21:52 | D | best error = [ 5.3292, 5.3292, 5.3292, 5.3292, 5.3292] +24-11-19 20:21:52 | D | + error = [5.3292] +24-11-19 20:21:52 | D | - Calibrating model.layers.7.mlp.down_proj.weight +24-11-19 20:21:52 | D | + w: sint8 +24-11-19 20:21:52 | D | + x: None +24-11-19 20:21:52 | D | + y: None +24-11-19 20:21:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:52 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:52 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:52 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:52 | D | - range ratio = [ 1.0000] +24-11-19 20:21:52 | D | sum error = [ 0.5477] +24-11-19 20:21:52 | D | best error = [ 0.5477] +24-11-19 20:21:53 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:53 | D | sum error = [ 0.5422, 0.5389, 0.5358, 0.5343, 0.5340] +24-11-19 20:21:53 | D | best error = [ 0.5264, 0.5161, 0.5092, 0.5042, 0.5002] +24-11-19 20:21:53 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:53 | D | sum error = [ 0.5346, 0.5376, 0.5441, 0.5521, 0.5620] +24-11-19 20:21:53 | D | best error = [ 0.4972, 0.4948, 0.4932, 0.4921, 0.4912] +24-11-19 20:21:53 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:53 | D | sum error = [ 0.5759, 0.5915, 0.6106, 0.6344, 0.6613] +24-11-19 20:21:53 | D | best error = [ 0.4906, 0.4903, 0.4900, 0.4898, 0.4896] +24-11-19 20:21:53 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:53 | D | sum error = [ 0.6919, 0.7247, 0.7637, 0.8063, 0.8534] +24-11-19 20:21:53 | D | best error = [ 0.4895, 0.4895, 0.4895, 0.4894, 0.4894] +24-11-19 20:21:53 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:53 | D | sum error = [ 0.9053, 0.9627, 1.0258, 1.0910, 1.1641] +24-11-19 20:21:53 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 20:21:53 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:53 | D | sum error = [ 1.2417, 1.3266, 1.4166, 1.5130, 1.6179] +24-11-19 20:21:53 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 20:21:53 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:53 | D | sum error = [ 1.7285, 1.8457, 1.9722, 2.1071, 2.2488] +24-11-19 20:21:53 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 20:21:53 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:53 | D | sum error = [ 2.4005, 2.5624, 2.7322, 2.9129, 3.1034] +24-11-19 20:21:53 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 20:21:53 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:53 | D | sum error = [ 3.3058, 3.5205, 3.7456, 3.9850, 4.2381] +24-11-19 20:21:53 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 20:21:53 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:53 | D | sum error = [ 4.5051, 4.7864, 5.0837, 5.3966, 5.7258] +24-11-19 20:21:53 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 20:21:53 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:53 | D | sum error = [ 6.0721, 6.4367, 6.8197, 7.2218, 7.6440] +24-11-19 20:21:53 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 20:21:53 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:53 | D | sum error = [ 8.0864, 8.5511, 9.0366, 9.5449, 10.0762] +24-11-19 20:21:53 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 20:21:53 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:53 | D | sum error = [ 10.6319, 11.2134, 11.8195, 12.4531, 13.1137] +24-11-19 20:21:53 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 20:21:53 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:53 | D | sum error = [ 13.8024, 14.5203, 15.2671, 16.0445, 16.8511] +24-11-19 20:21:53 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 20:21:53 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:53 | D | sum error = [ 17.6901, 18.5607, 19.4645, 20.4022, 21.3733] +24-11-19 20:21:53 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 20:21:53 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:53 | D | sum error = [ 22.3795, 23.4207, 24.4966, 25.6099, 26.7585] +24-11-19 20:21:53 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 20:21:53 | D | + error = [0.4894] +24-11-19 20:21:54 | D | - Quantizing model.layers.7.self_attn.q_proj.weight +24-11-19 20:21:55 | D | - Quantizing model.layers.7.self_attn.k_proj.weight +24-11-19 20:21:56 | D | - Quantizing model.layers.7.self_attn.v_proj.weight +24-11-19 20:22:00 | D | - Quantizing model.layers.7.self_attn.o_proj.weight +24-11-19 20:22:02 | D | - Quantizing model.layers.7.mlp.up_proj.weight +24-11-19 20:22:06 | D | - Quantizing model.layers.7.mlp.gate_proj.weight +24-11-19 20:22:09 | D | - Quantizing model.layers.7.mlp.down_proj.weight +24-11-19 20:22:20 | D | - Quantizing layer model.layers.8 +24-11-19 20:22:20 | D | - Calibrating model.layers.8.self_attn.q_proj.weight +24-11-19 20:22:20 | D | + w: sint8 +24-11-19 20:22:20 | D | + x: None +24-11-19 20:22:20 | D | + y: None +24-11-19 20:22:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:22:20 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:22:20 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:22:20 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:22:20 | D | - range ratio = [ 1.0000] +24-11-19 20:22:20 | D | sum error = [ 3.4668] +24-11-19 20:22:20 | D | best error = [ 3.4668] +24-11-19 20:22:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:32 | D | sum error = [ 3.5190, 3.5161, 3.6723, 3.4568, 3.5320] +24-11-19 20:22:32 | D | best error = [ 3.4668, 3.4668, 3.4668, 3.4568, 3.4568] +24-11-19 20:22:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:32 | D | sum error = [ 3.6146, 3.7441, 4.0386, 4.2372, 4.3657] +24-11-19 20:22:32 | D | best error = [ 3.4568, 3.4568, 3.4568, 3.4568, 3.4568] +24-11-19 20:22:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:32 | D | sum error = [ 4.7633, 4.9029, 5.3729, 5.6691, 5.9696] +24-11-19 20:22:32 | D | best error = [ 3.4568, 3.4568, 3.4568, 3.4568, 3.4568] +24-11-19 20:22:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:32 | D | sum error = [ 6.4568, 6.9382, 7.6533, 8.1886, 8.7446] +24-11-19 20:22:32 | D | best error = [ 3.4568, 3.4568, 3.4568, 3.4568, 3.4568] +24-11-19 20:22:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:32 | D | sum error = [ 9.3645, 10.2539, 11.0009, 11.9218, 12.8658] +24-11-19 20:22:32 | D | best error = [ 3.4568, 3.4568, 3.4568, 3.4568, 3.4568] +24-11-19 20:22:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:32 | D | sum error = [ 13.8851, 14.9261, 16.1926, 17.5735, 19.0333] +24-11-19 20:22:32 | D | best error = [ 3.4568, 3.4568, 3.4568, 3.4568, 3.4568] +24-11-19 20:22:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:32 | D | sum error = [ 20.4226, 22.1959, 24.0917, 26.0136, 28.3465] +24-11-19 20:22:32 | D | best error = [ 3.4568, 3.4568, 3.4568, 3.4568, 3.4568] +24-11-19 20:22:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:32 | D | sum error = [ 30.6025, 33.0702, 35.7510, 38.6110, 41.6499] +24-11-19 20:22:32 | D | best error = [ 3.4568, 3.4568, 3.4568, 3.4568, 3.4568] +24-11-19 20:22:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:32 | D | sum error = [ 44.8295, 48.2900, 51.9085, 55.9288, 60.0986] +24-11-19 20:22:32 | D | best error = [ 3.4568, 3.4568, 3.4568, 3.4568, 3.4568] +24-11-19 20:22:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:32 | D | sum error = [ 64.6233, 69.3745, 74.3304, 79.6592, 85.0417] +24-11-19 20:22:32 | D | best error = [ 3.4568, 3.4568, 3.4568, 3.4568, 3.4568] +24-11-19 20:22:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:32 | D | sum error = [ 91.1011, 97.3435, 103.9554, 110.9745, 118.5053] +24-11-19 20:22:32 | D | best error = [ 3.4568, 3.4568, 3.4568, 3.4568, 3.4568] +24-11-19 20:22:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:32 | D | sum error = [ 126.4924, 134.8664, 143.5980, 152.9409, 162.7366] +24-11-19 20:22:32 | D | best error = [ 3.4568, 3.4568, 3.4568, 3.4568, 3.4568] +24-11-19 20:22:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:32 | D | sum error = [ 173.2540, 184.2164, 195.6189, 207.8585, 220.5207] +24-11-19 20:22:32 | D | best error = [ 3.4568, 3.4568, 3.4568, 3.4568, 3.4568] +24-11-19 20:22:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:32 | D | sum error = [ 233.7500, 247.6656, 262.0555, 276.9495, 292.4499] +24-11-19 20:22:32 | D | best error = [ 3.4568, 3.4568, 3.4568, 3.4568, 3.4568] +24-11-19 20:22:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:32 | D | sum error = [ 308.4118, 324.9224, 341.9392, 359.2812, 377.1348] +24-11-19 20:22:32 | D | best error = [ 3.4568, 3.4568, 3.4568, 3.4568, 3.4568] +24-11-19 20:22:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:32 | D | sum error = [ 395.3098, 413.7964, 432.5201, 451.2421, 470.1927] +24-11-19 20:22:32 | D | best error = [ 3.4568, 3.4568, 3.4568, 3.4568, 3.4568] +24-11-19 20:22:32 | D | + error = [3.4568] +24-11-19 20:22:32 | D | - Calibrating model.layers.8.self_attn.k_proj.weight +24-11-19 20:22:32 | D | + w: sint8 +24-11-19 20:22:32 | D | + x: None +24-11-19 20:22:32 | D | + y: None +24-11-19 20:22:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:22:32 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:32 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:32 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:32 | D | - range ratio = [ 1.0000] +24-11-19 20:22:32 | D | sum error = [ 2.8443] +24-11-19 20:22:32 | D | best error = [ 2.8443] +24-11-19 20:22:44 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:44 | D | sum error = [ 3.4004, 2.9865, 2.8194, 2.9561, 2.9802] +24-11-19 20:22:44 | D | best error = [ 2.8443, 2.8443, 2.8194, 2.8194, 2.8194] +24-11-19 20:22:44 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:44 | D | sum error = [ 3.2512, 3.4517, 3.2091, 3.5424, 3.5138] +24-11-19 20:22:44 | D | best error = [ 2.8194, 2.8194, 2.8194, 2.8194, 2.8194] +24-11-19 20:22:44 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:44 | D | sum error = [ 4.0484, 4.2564, 4.5476, 4.9165, 5.3993] +24-11-19 20:22:44 | D | best error = [ 2.8194, 2.8194, 2.8194, 2.8194, 2.8194] +24-11-19 20:22:44 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:44 | D | sum error = [ 5.6724, 6.1186, 6.2570, 6.9401, 7.5891] +24-11-19 20:22:44 | D | best error = [ 2.8194, 2.8194, 2.8194, 2.8194, 2.8194] +24-11-19 20:22:44 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:44 | D | sum error = [ 8.0807, 8.7464, 9.9777, 10.5519, 11.2014] +24-11-19 20:22:44 | D | best error = [ 2.8194, 2.8194, 2.8194, 2.8194, 2.8194] +24-11-19 20:22:44 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:44 | D | sum error = [ 11.9153, 12.8495, 13.8755, 15.4142, 16.2163] +24-11-19 20:22:44 | D | best error = [ 2.8194, 2.8194, 2.8194, 2.8194, 2.8194] +24-11-19 20:22:44 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:44 | D | sum error = [ 17.6498, 19.0762, 20.3386, 22.4256, 24.2674] +24-11-19 20:22:44 | D | best error = [ 2.8194, 2.8194, 2.8194, 2.8194, 2.8194] +24-11-19 20:22:44 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:44 | D | sum error = [ 26.3373, 28.6561, 30.7806, 33.5069, 36.3855] +24-11-19 20:22:44 | D | best error = [ 2.8194, 2.8194, 2.8194, 2.8194, 2.8194] +24-11-19 20:22:44 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:44 | D | sum error = [ 39.3542, 42.5247, 46.7045, 50.0388, 54.4495] +24-11-19 20:22:44 | D | best error = [ 2.8194, 2.8194, 2.8194, 2.8194, 2.8194] +24-11-19 20:22:44 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:44 | D | sum error = [ 58.6233, 63.8246, 69.1531, 74.3533, 80.1460] +24-11-19 20:22:44 | D | best error = [ 2.8194, 2.8194, 2.8194, 2.8194, 2.8194] +24-11-19 20:22:44 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:44 | D | sum error = [ 86.4930, 93.4216, 100.3069, 107.2214, 115.0908] +24-11-19 20:22:44 | D | best error = [ 2.8194, 2.8194, 2.8194, 2.8194, 2.8194] +24-11-19 20:22:44 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:44 | D | sum error = [ 123.1347, 132.0005, 141.0324, 150.6601, 160.4375] +24-11-19 20:22:44 | D | best error = [ 2.8194, 2.8194, 2.8194, 2.8194, 2.8194] +24-11-19 20:22:44 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:44 | D | sum error = [ 171.4957, 182.3926, 194.4506, 206.6120, 219.2603] +24-11-19 20:22:44 | D | best error = [ 2.8194, 2.8194, 2.8194, 2.8194, 2.8194] +24-11-19 20:22:44 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:44 | D | sum error = [ 232.7842, 246.7434, 261.4492, 276.6575, 292.1413] +24-11-19 20:22:44 | D | best error = [ 2.8194, 2.8194, 2.8194, 2.8194, 2.8194] +24-11-19 20:22:44 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:44 | D | sum error = [ 307.9835, 324.4532, 341.2712, 358.2922, 376.3058] +24-11-19 20:22:44 | D | best error = [ 2.8194, 2.8194, 2.8194, 2.8194, 2.8194] +24-11-19 20:22:44 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:44 | D | sum error = [ 393.9229, 412.3498, 430.5565, 449.1817, 468.3430] +24-11-19 20:22:44 | D | best error = [ 2.8194, 2.8194, 2.8194, 2.8194, 2.8194] +24-11-19 20:22:44 | D | + error = [2.8194] +24-11-19 20:22:44 | D | - Calibrating model.layers.8.self_attn.v_proj.weight +24-11-19 20:22:44 | D | + w: sint8 +24-11-19 20:22:44 | D | + x: None +24-11-19 20:22:44 | D | + y: None +24-11-19 20:22:44 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:44 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:44 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:44 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:44 | D | - range ratio = [ 1.0000] +24-11-19 20:22:44 | D | sum error = [ 1.2606] +24-11-19 20:22:44 | D | best error = [ 1.2606] +24-11-19 20:22:44 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:44 | D | sum error = [ 1.2597, 1.2430, 1.2569, 1.2738, 1.2949] +24-11-19 20:22:44 | D | best error = [ 1.1819, 1.1480, 1.1323, 1.1226, 1.1172] +24-11-19 20:22:44 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:44 | D | sum error = [ 1.3299, 1.3730, 1.4205, 1.4853, 1.5744] +24-11-19 20:22:44 | D | best error = [ 1.1153, 1.1139, 1.1135, 1.1135, 1.1135] +24-11-19 20:22:44 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:44 | D | sum error = [ 1.6739, 1.7801, 1.8901, 2.0186, 2.1591] +24-11-19 20:22:44 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:22:44 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:44 | D | sum error = [ 2.3206, 2.4873, 2.6691, 2.8543, 3.0664] +24-11-19 20:22:44 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:22:44 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:44 | D | sum error = [ 3.2912, 3.5229, 3.7753, 4.0315, 4.3188] +24-11-19 20:22:44 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:22:44 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:44 | D | sum error = [ 4.6192, 4.9186, 5.2777, 5.6324, 6.0148] +24-11-19 20:22:44 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:22:44 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:44 | D | sum error = [ 6.4041, 6.8144, 7.2586, 7.7248, 8.2197] +24-11-19 20:22:44 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:22:44 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:44 | D | sum error = [ 8.7294, 9.2844, 9.8476, 10.4481, 11.1002] +24-11-19 20:22:44 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:22:44 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:44 | D | sum error = [ 11.7585, 12.4682, 13.1999, 13.9765, 14.7857] +24-11-19 20:22:44 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:22:44 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:44 | D | sum error = [ 15.6336, 16.5240, 17.4429, 18.4145, 19.4270] +24-11-19 20:22:44 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:22:44 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:44 | D | sum error = [ 20.4903, 21.5898, 22.7625, 23.9678, 25.2324] +24-11-19 20:22:44 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:22:44 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:44 | D | sum error = [ 26.5501, 27.9250, 29.3591, 30.8572, 32.4198] +24-11-19 20:22:44 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:22:44 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:44 | D | sum error = [ 34.0433, 35.7379, 37.4992, 39.3452, 41.2519] +24-11-19 20:22:44 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:22:44 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:44 | D | sum error = [ 43.2340, 45.3028, 47.4334, 49.6528, 51.9439] +24-11-19 20:22:44 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:22:44 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:44 | D | sum error = [ 54.3176, 56.7631, 59.2940, 61.9130, 64.6106] +24-11-19 20:22:44 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:22:44 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:44 | D | sum error = [ 67.4026, 70.2790, 73.2412, 76.2904, 79.4230] +24-11-19 20:22:44 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:22:44 | D | + error = [1.1135] +24-11-19 20:22:44 | D | - Calibrating model.layers.8.self_attn.o_proj.weight +24-11-19 20:22:44 | D | + w: sint8 +24-11-19 20:22:44 | D | + x: None +24-11-19 20:22:44 | D | + y: None +24-11-19 20:22:44 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:44 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:44 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:45 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:45 | D | - range ratio = [ 1.0000] +24-11-19 20:22:45 | D | sum error = [ 0.5011] +24-11-19 20:22:45 | D | best error = [ 0.5011] +24-11-19 20:22:45 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:45 | D | sum error = [ 0.4978, 0.4973, 0.4995, 0.5023, 0.5113] +24-11-19 20:22:45 | D | best error = [ 0.4565, 0.4378, 0.4270, 0.4201, 0.4152] +24-11-19 20:22:45 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:45 | D | sum error = [ 0.5200, 0.5387, 0.5551, 0.5763, 0.6056] +24-11-19 20:22:45 | D | best error = [ 0.4121, 0.4102, 0.4091, 0.4084, 0.4080] +24-11-19 20:22:45 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:45 | D | sum error = [ 0.6366, 0.6693, 0.7043, 0.7466, 0.7908] +24-11-19 20:22:45 | D | best error = [ 0.4078, 0.4076, 0.4075, 0.4074, 0.4074] +24-11-19 20:22:45 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:45 | D | sum error = [ 0.8441, 0.8940, 0.9510, 1.0105, 1.0713] +24-11-19 20:22:45 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:22:45 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:45 | D | sum error = [ 1.1388, 1.2092, 1.2863, 1.3630, 1.4493] +24-11-19 20:22:45 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:22:45 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:45 | D | sum error = [ 1.5360, 1.6306, 1.7280, 1.8293, 1.9358] +24-11-19 20:22:45 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:22:45 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:45 | D | sum error = [ 2.0505, 2.1688, 2.2937, 2.4235, 2.5600] +24-11-19 20:22:45 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:22:45 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:45 | D | sum error = [ 2.7057, 2.8532, 3.0123, 3.1733, 3.3435] +24-11-19 20:22:45 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:22:45 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:45 | D | sum error = [ 3.5232, 3.7091, 3.9018, 4.1037, 4.3114] +24-11-19 20:22:45 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:22:45 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:45 | D | sum error = [ 4.5287, 4.7527, 4.9864, 5.2310, 5.4853] +24-11-19 20:22:45 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:22:45 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:45 | D | sum error = [ 5.7467, 6.0193, 6.3024, 6.5974, 6.8994] +24-11-19 20:22:45 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:22:45 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:45 | D | sum error = [ 7.2121, 7.5402, 7.8774, 8.2246, 8.5845] +24-11-19 20:22:45 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:22:45 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:45 | D | sum error = [ 8.9552, 9.3377, 9.7328, 10.1424, 10.5616] +24-11-19 20:22:45 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:22:45 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:45 | D | sum error = [ 10.9934, 11.4377, 11.8939, 12.3653, 12.8466] +24-11-19 20:22:45 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:22:45 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:45 | D | sum error = [ 13.3423, 13.8505, 14.3743, 14.9126, 15.4686] +24-11-19 20:22:45 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:22:45 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:45 | D | sum error = [ 16.0417, 16.6311, 17.2381, 17.8624, 18.5058] +24-11-19 20:22:45 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:22:45 | D | + error = [0.4073] +24-11-19 20:22:45 | D | - Calibrating model.layers.8.mlp.up_proj.weight +24-11-19 20:22:45 | D | + w: sint8 +24-11-19 20:22:45 | D | + x: None +24-11-19 20:22:45 | D | + y: None +24-11-19 20:22:45 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:45 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:45 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:45 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:45 | D | - range ratio = [ 1.0000] +24-11-19 20:22:45 | D | sum error = [ 4.7245] +24-11-19 20:22:45 | D | best error = [ 4.7245] +24-11-19 20:22:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:46 | D | sum error = [ 4.6828, 4.6833, 4.6899, 4.7489, 4.8349] +24-11-19 20:22:46 | D | best error = [ 4.4205, 4.3041, 4.2400, 4.2054, 4.1862] +24-11-19 20:22:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:46 | D | sum error = [ 4.9590, 5.1386, 5.3331, 5.5918, 5.8828] +24-11-19 20:22:46 | D | best error = [ 4.1772, 4.1735, 4.1722, 4.1718, 4.1718] +24-11-19 20:22:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:46 | D | sum error = [ 6.2150, 6.6078, 7.0392, 7.5052, 8.0219] +24-11-19 20:22:46 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:22:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:46 | D | sum error = [ 8.5911, 9.2104, 9.8582, 10.5696, 11.3240] +24-11-19 20:22:46 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:22:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:46 | D | sum error = [ 12.1384, 12.9842, 13.9020, 14.8783, 15.9155] +24-11-19 20:22:46 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:22:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:46 | D | sum error = [ 17.0043, 18.1635, 19.3982, 20.6972, 22.0697] +24-11-19 20:22:46 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:22:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:46 | D | sum error = [ 23.5188, 25.0558, 26.6595, 28.3695, 30.1571] +24-11-19 20:22:46 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:22:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:46 | D | sum error = [ 32.0381, 34.0270, 36.1228, 38.3207, 40.6333] +24-11-19 20:22:46 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:22:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:46 | D | sum error = [ 43.0630, 45.6116, 48.2903, 51.0959, 54.0434] +24-11-19 20:22:46 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:22:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:46 | D | sum error = [ 57.1205, 60.3409, 63.7244, 67.2592, 70.9500] +24-11-19 20:22:46 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:22:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:46 | D | sum error = [ 74.8223, 78.8667, 83.0939, 87.5124, 92.1228] +24-11-19 20:22:46 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:22:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:46 | D | sum error = [ 96.9360, 101.9607, 107.1877, 112.6407, 118.3255] +24-11-19 20:22:46 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:22:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:46 | D | sum error = [ 124.2262, 130.3574, 136.7408, 143.3710, 150.2449] +24-11-19 20:22:46 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:22:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:46 | D | sum error = [ 157.3723, 164.7550, 172.4199, 180.3583, 188.5599] +24-11-19 20:22:46 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:22:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:46 | D | sum error = [ 197.0484, 205.8211, 214.8863, 224.2442, 233.8989] +24-11-19 20:22:46 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:22:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:46 | D | sum error = [ 243.8652, 254.1392, 264.7269, 275.6279, 286.8468] +24-11-19 20:22:46 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:22:46 | D | + error = [4.1717] +24-11-19 20:22:47 | D | - Calibrating model.layers.8.mlp.gate_proj.weight +24-11-19 20:22:47 | D | + w: sint8 +24-11-19 20:22:47 | D | + x: None +24-11-19 20:22:47 | D | + y: None +24-11-19 20:22:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:47 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:47 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:47 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:47 | D | - range ratio = [ 1.0000] +24-11-19 20:22:47 | D | sum error = [ 6.1287] +24-11-19 20:22:47 | D | best error = [ 6.1287] +24-11-19 20:22:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:48 | D | sum error = [ 6.0861, 6.0777, 6.1024, 6.1625, 6.2796] +24-11-19 20:22:48 | D | best error = [ 5.7423, 5.5911, 5.5096, 5.4645, 5.4404] +24-11-19 20:22:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:48 | D | sum error = [ 6.4482, 6.6751, 6.9503, 7.2787, 7.6642] +24-11-19 20:22:48 | D | best error = [ 5.4297, 5.4250, 5.4235, 5.4231, 5.4230] +24-11-19 20:22:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:48 | D | sum error = [ 8.1255, 8.6346, 9.2139, 9.8370, 10.5507] +24-11-19 20:22:48 | D | best error = [ 5.4230, 5.4230, 5.4230, 5.4230, 5.4230] +24-11-19 20:22:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:48 | D | sum error = [ 11.3021, 12.1307, 13.0149, 13.9836, 15.0097] +24-11-19 20:22:48 | D | best error = [ 5.4230, 5.4230, 5.4230, 5.4230, 5.4230] +24-11-19 20:22:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:48 | D | sum error = [ 16.1111, 17.2967, 18.5565, 19.8997, 21.3592] +24-11-19 20:22:48 | D | best error = [ 5.4230, 5.4230, 5.4230, 5.4230, 5.4230] +24-11-19 20:22:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:48 | D | sum error = [ 22.8983, 24.5246, 26.2568, 28.1087, 30.0795] +24-11-19 20:22:48 | D | best error = [ 5.4230, 5.4230, 5.4230, 5.4230, 5.4230] +24-11-19 20:22:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:48 | D | sum error = [ 32.1602, 34.3814, 36.7392, 39.2419, 41.8944] +24-11-19 20:22:48 | D | best error = [ 5.4230, 5.4230, 5.4230, 5.4230, 5.4230] +24-11-19 20:22:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:48 | D | sum error = [ 44.7356, 47.7094, 50.9052, 54.2682, 57.8390] +24-11-19 20:22:48 | D | best error = [ 5.4230, 5.4230, 5.4230, 5.4230, 5.4230] +24-11-19 20:22:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:48 | D | sum error = [ 61.6327, 65.6644, 69.9371, 74.4653, 79.2612] +24-11-19 20:22:48 | D | best error = [ 5.4230, 5.4230, 5.4230, 5.4230, 5.4230] +24-11-19 20:22:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:48 | D | sum error = [ 84.3347, 89.7307, 95.4252, 101.4556, 107.8263] +24-11-19 20:22:48 | D | best error = [ 5.4230, 5.4230, 5.4230, 5.4230, 5.4230] +24-11-19 20:22:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:48 | D | sum error = [ 114.5839, 121.6890, 129.2186, 137.1749, 145.5408] +24-11-19 20:22:48 | D | best error = [ 5.4230, 5.4230, 5.4230, 5.4230, 5.4230] +24-11-19 20:22:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:48 | D | sum error = [ 154.3877, 163.6879, 173.4841, 183.7935, 194.6371] +24-11-19 20:22:48 | D | best error = [ 5.4230, 5.4230, 5.4230, 5.4230, 5.4230] +24-11-19 20:22:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:48 | D | sum error = [ 206.0222, 217.9765, 230.5193, 243.6502, 257.3968] +24-11-19 20:22:48 | D | best error = [ 5.4230, 5.4230, 5.4230, 5.4230, 5.4230] +24-11-19 20:22:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:48 | D | sum error = [ 271.7751, 286.8030, 302.4844, 318.8420, 335.9032] +24-11-19 20:22:48 | D | best error = [ 5.4230, 5.4230, 5.4230, 5.4230, 5.4230] +24-11-19 20:22:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:48 | D | sum error = [ 353.6801, 372.1531, 391.3352, 411.2548, 431.8599] +24-11-19 20:22:48 | D | best error = [ 5.4230, 5.4230, 5.4230, 5.4230, 5.4230] +24-11-19 20:22:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:48 | D | sum error = [ 453.2187, 475.2936, 498.1214, 521.6615, 545.9342] +24-11-19 20:22:48 | D | best error = [ 5.4230, 5.4230, 5.4230, 5.4230, 5.4230] +24-11-19 20:22:48 | D | + error = [5.4230] +24-11-19 20:22:48 | D | - Calibrating model.layers.8.mlp.down_proj.weight +24-11-19 20:22:48 | D | + w: sint8 +24-11-19 20:22:48 | D | + x: None +24-11-19 20:22:48 | D | + y: None +24-11-19 20:22:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:48 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:48 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:48 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:48 | D | - range ratio = [ 1.0000] +24-11-19 20:22:48 | D | sum error = [ 0.5646] +24-11-19 20:22:48 | D | best error = [ 0.5646] +24-11-19 20:22:49 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:49 | D | sum error = [ 0.5582, 0.5557, 0.5521, 0.5520, 0.5525] +24-11-19 20:22:49 | D | best error = [ 0.5424, 0.5320, 0.5248, 0.5195, 0.5155] +24-11-19 20:22:49 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:49 | D | sum error = [ 0.5541, 0.5591, 0.5674, 0.5761, 0.5904] +24-11-19 20:22:49 | D | best error = [ 0.5127, 0.5103, 0.5087, 0.5074, 0.5066] +24-11-19 20:22:49 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:49 | D | sum error = [ 0.6063, 0.6261, 0.6494, 0.6757, 0.7063] +24-11-19 20:22:49 | D | best error = [ 0.5061, 0.5057, 0.5054, 0.5052, 0.5051] +24-11-19 20:22:49 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:49 | D | sum error = [ 0.7415, 0.7806, 0.8257, 0.8750, 0.9275] +24-11-19 20:22:49 | D | best error = [ 0.5050, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 20:22:49 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:49 | D | sum error = [ 0.9858, 1.0478, 1.1167, 1.1918, 1.2708] +24-11-19 20:22:49 | D | best error = [ 0.5049, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 20:22:49 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:49 | D | sum error = [ 1.3547, 1.4467, 1.5440, 1.6491, 1.7597] +24-11-19 20:22:49 | D | best error = [ 0.5049, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 20:22:49 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:49 | D | sum error = [ 1.8791, 2.0057, 2.1388, 2.2819, 2.4335] +24-11-19 20:22:49 | D | best error = [ 0.5049, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 20:22:49 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:49 | D | sum error = [ 2.5940, 2.7652, 2.9457, 3.1364, 3.3386] +24-11-19 20:22:49 | D | best error = [ 0.5049, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 20:22:49 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:49 | D | sum error = [ 3.5519, 3.7772, 4.0159, 4.2669, 4.5324] +24-11-19 20:22:49 | D | best error = [ 0.5049, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 20:22:49 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:49 | D | sum error = [ 4.8131, 5.1071, 5.4167, 5.7440, 6.0876] +24-11-19 20:22:49 | D | best error = [ 0.5049, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 20:22:49 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:49 | D | sum error = [ 6.4500, 6.8291, 7.2276, 7.6475, 8.0868] +24-11-19 20:22:49 | D | best error = [ 0.5049, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 20:22:49 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:49 | D | sum error = [ 8.5468, 9.0303, 9.5353, 10.0634, 10.6158] +24-11-19 20:22:49 | D | best error = [ 0.5049, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 20:22:49 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:49 | D | sum error = [ 11.1940, 11.7983, 12.4287, 13.0860, 13.7714] +24-11-19 20:22:49 | D | best error = [ 0.5049, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 20:22:49 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:49 | D | sum error = [ 14.4856, 15.2294, 16.0034, 16.8081, 17.6441] +24-11-19 20:22:49 | D | best error = [ 0.5049, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 20:22:49 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:49 | D | sum error = [ 18.5142, 19.4170, 20.3545, 21.3269, 22.3348] +24-11-19 20:22:49 | D | best error = [ 0.5049, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 20:22:49 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:49 | D | sum error = [ 23.3787, 24.4584, 25.5758, 26.7293, 27.9203] +24-11-19 20:22:49 | D | best error = [ 0.5049, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 20:22:49 | D | + error = [0.5049] +24-11-19 20:22:49 | D | - Quantizing model.layers.8.self_attn.q_proj.weight +24-11-19 20:22:51 | D | - Quantizing model.layers.8.self_attn.k_proj.weight +24-11-19 20:22:52 | D | - Quantizing model.layers.8.self_attn.v_proj.weight +24-11-19 20:22:54 | D | - Quantizing model.layers.8.self_attn.o_proj.weight +24-11-19 20:22:56 | D | - Quantizing model.layers.8.mlp.up_proj.weight +24-11-19 20:22:58 | D | - Quantizing model.layers.8.mlp.gate_proj.weight +24-11-19 20:23:02 | D | - Quantizing model.layers.8.mlp.down_proj.weight +24-11-19 20:23:12 | D | - Quantizing layer model.layers.9 +24-11-19 20:23:12 | D | - Calibrating model.layers.9.self_attn.q_proj.weight +24-11-19 20:23:12 | D | + w: sint8 +24-11-19 20:23:12 | D | + x: None +24-11-19 20:23:12 | D | + y: None +24-11-19 20:23:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:23:12 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:23:12 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:23:13 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:23:13 | D | - range ratio = [ 1.0000] +24-11-19 20:23:13 | D | sum error = [ 3.9497] +24-11-19 20:23:13 | D | best error = [ 3.9497] +24-11-19 20:23:24 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:24 | D | sum error = [ 3.8355, 3.8674, 3.8350, 3.8625, 3.9307] +24-11-19 20:23:24 | D | best error = [ 3.8355, 3.8355, 3.8350, 3.8350, 3.8350] +24-11-19 20:23:24 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:24 | D | sum error = [ 4.0561, 4.3060, 4.4104, 4.6557, 4.9950] +24-11-19 20:23:24 | D | best error = [ 3.8350, 3.8350, 3.8350, 3.8350, 3.8350] +24-11-19 20:23:24 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:24 | D | sum error = [ 5.3018, 5.5171, 6.0457, 6.5601, 7.0485] +24-11-19 20:23:24 | D | best error = [ 3.8350, 3.8350, 3.8350, 3.8350, 3.8350] +24-11-19 20:23:24 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:24 | D | sum error = [ 7.6331, 8.1455, 8.7746, 9.4957, 10.1735] +24-11-19 20:23:24 | D | best error = [ 3.8350, 3.8350, 3.8350, 3.8350, 3.8350] +24-11-19 20:23:24 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:24 | D | sum error = [ 11.2778, 11.9275, 13.1373, 14.1466, 15.9315] +24-11-19 20:23:24 | D | best error = [ 3.8350, 3.8350, 3.8350, 3.8350, 3.8350] +24-11-19 20:23:24 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:24 | D | sum error = [ 16.8739, 18.2738, 19.8895, 21.4840, 23.2448] +24-11-19 20:23:24 | D | best error = [ 3.8350, 3.8350, 3.8350, 3.8350, 3.8350] +24-11-19 20:23:24 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:24 | D | sum error = [ 25.1583, 27.1849, 29.3088, 31.5671, 34.1788] +24-11-19 20:23:24 | D | best error = [ 3.8350, 3.8350, 3.8350, 3.8350, 3.8350] +24-11-19 20:23:24 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:24 | D | sum error = [ 36.9894, 40.0946, 43.3276, 46.5497, 50.4775] +24-11-19 20:23:24 | D | best error = [ 3.8350, 3.8350, 3.8350, 3.8350, 3.8350] +24-11-19 20:23:24 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:24 | D | sum error = [ 54.2520, 58.4603, 62.8936, 67.6503, 72.8643] +24-11-19 20:23:24 | D | best error = [ 3.8350, 3.8350, 3.8350, 3.8350, 3.8350] +24-11-19 20:23:24 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:24 | D | sum error = [ 78.4387, 84.4936, 90.6216, 97.4929, 104.6439] +24-11-19 20:23:24 | D | best error = [ 3.8350, 3.8350, 3.8350, 3.8350, 3.8350] +24-11-19 20:23:24 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:24 | D | sum error = [ 112.4871, 120.4380, 129.0945, 138.3466, 148.3035] +24-11-19 20:23:24 | D | best error = [ 3.8350, 3.8350, 3.8350, 3.8350, 3.8350] +24-11-19 20:23:24 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:24 | D | sum error = [ 158.5462, 169.4255, 180.8695, 192.7879, 205.2963] +24-11-19 20:23:24 | D | best error = [ 3.8350, 3.8350, 3.8350, 3.8350, 3.8350] +24-11-19 20:23:24 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:24 | D | sum error = [ 218.5395, 232.2023, 246.5550, 261.5223, 277.0254] +24-11-19 20:23:24 | D | best error = [ 3.8350, 3.8350, 3.8350, 3.8350, 3.8350] +24-11-19 20:23:24 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:24 | D | sum error = [ 293.2533, 310.1574, 327.6398, 345.9279, 364.6141] +24-11-19 20:23:24 | D | best error = [ 3.8350, 3.8350, 3.8350, 3.8350, 3.8350] +24-11-19 20:23:24 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:24 | D | sum error = [ 383.7446, 403.5651, 423.9433, 444.3285, 465.0772] +24-11-19 20:23:24 | D | best error = [ 3.8350, 3.8350, 3.8350, 3.8350, 3.8350] +24-11-19 20:23:24 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:24 | D | sum error = [ 485.8805, 506.8937, 527.8014, 548.8362, 569.8746] +24-11-19 20:23:24 | D | best error = [ 3.8350, 3.8350, 3.8350, 3.8350, 3.8350] +24-11-19 20:23:24 | D | + error = [3.8350] +24-11-19 20:23:25 | D | - Calibrating model.layers.9.self_attn.k_proj.weight +24-11-19 20:23:25 | D | + w: sint8 +24-11-19 20:23:25 | D | + x: None +24-11-19 20:23:25 | D | + y: None +24-11-19 20:23:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:23:25 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:25 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:25 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:25 | D | - range ratio = [ 1.0000] +24-11-19 20:23:25 | D | sum error = [ 3.1367] +24-11-19 20:23:25 | D | best error = [ 3.1367] +24-11-19 20:23:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:37 | D | sum error = [ 3.2868, 3.1340, 3.3668, 3.2931, 3.7421] +24-11-19 20:23:37 | D | best error = [ 3.1367, 3.1340, 3.1340, 3.1340, 3.1340] +24-11-19 20:23:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:37 | D | sum error = [ 3.2494, 3.6377, 3.7811, 3.8226, 4.4260] +24-11-19 20:23:37 | D | best error = [ 3.1340, 3.1340, 3.1340, 3.1340, 3.1340] +24-11-19 20:23:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:37 | D | sum error = [ 4.1318, 5.0578, 5.5094, 5.8502, 6.4963] +24-11-19 20:23:37 | D | best error = [ 3.1340, 3.1340, 3.1340, 3.1340, 3.1340] +24-11-19 20:23:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:37 | D | sum error = [ 6.7357, 7.4987, 7.5608, 9.1035, 9.0123] +24-11-19 20:23:37 | D | best error = [ 3.1340, 3.1340, 3.1340, 3.1340, 3.1340] +24-11-19 20:23:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:37 | D | sum error = [ 10.0369, 10.7241, 12.1032, 13.0505, 14.1279] +24-11-19 20:23:37 | D | best error = [ 3.1340, 3.1340, 3.1340, 3.1340, 3.1340] +24-11-19 20:23:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:37 | D | sum error = [ 15.2298, 17.0005, 17.9090, 19.7134, 20.9147] +24-11-19 20:23:37 | D | best error = [ 3.1340, 3.1340, 3.1340, 3.1340, 3.1340] +24-11-19 20:23:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:37 | D | sum error = [ 22.5075, 24.9218, 26.7580, 28.5963, 30.8273] +24-11-19 20:23:37 | D | best error = [ 3.1340, 3.1340, 3.1340, 3.1340, 3.1340] +24-11-19 20:23:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:37 | D | sum error = [ 33.4078, 36.3991, 39.6221, 42.9360, 46.0376] +24-11-19 20:23:37 | D | best error = [ 3.1340, 3.1340, 3.1340, 3.1340, 3.1340] +24-11-19 20:23:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:37 | D | sum error = [ 49.0538, 53.0869, 57.9270, 62.4262, 66.7704] +24-11-19 20:23:37 | D | best error = [ 3.1340, 3.1340, 3.1340, 3.1340, 3.1340] +24-11-19 20:23:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:37 | D | sum error = [ 71.5809, 77.4889, 82.6906, 88.8575, 95.6193] +24-11-19 20:23:37 | D | best error = [ 3.1340, 3.1340, 3.1340, 3.1340, 3.1340] +24-11-19 20:23:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:37 | D | sum error = [ 103.3108, 110.5110, 118.5000, 127.1393, 136.2967] +24-11-19 20:23:37 | D | best error = [ 3.1340, 3.1340, 3.1340, 3.1340, 3.1340] +24-11-19 20:23:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:37 | D | sum error = [ 146.2913, 156.3266, 166.7874, 179.7716, 191.6582] +24-11-19 20:23:37 | D | best error = [ 3.1340, 3.1340, 3.1340, 3.1340, 3.1340] +24-11-19 20:23:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:37 | D | sum error = [ 204.1558, 217.7277, 231.6684, 246.4165, 262.2196] +24-11-19 20:23:37 | D | best error = [ 3.1340, 3.1340, 3.1340, 3.1340, 3.1340] +24-11-19 20:23:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:37 | D | sum error = [ 277.5911, 294.9303, 311.9343, 330.7108, 348.8304] +24-11-19 20:23:37 | D | best error = [ 3.1340, 3.1340, 3.1340, 3.1340, 3.1340] +24-11-19 20:23:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:37 | D | sum error = [ 368.4065, 388.3653, 408.6860, 429.6544, 451.7306] +24-11-19 20:23:37 | D | best error = [ 3.1340, 3.1340, 3.1340, 3.1340, 3.1340] +24-11-19 20:23:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:37 | D | sum error = [ 473.2172, 495.0659, 517.7436, 539.5366, 561.4281] +24-11-19 20:23:37 | D | best error = [ 3.1340, 3.1340, 3.1340, 3.1340, 3.1340] +24-11-19 20:23:37 | D | + error = [3.1340] +24-11-19 20:23:37 | D | - Calibrating model.layers.9.self_attn.v_proj.weight +24-11-19 20:23:37 | D | + w: sint8 +24-11-19 20:23:37 | D | + x: None +24-11-19 20:23:37 | D | + y: None +24-11-19 20:23:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:37 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:37 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:37 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:37 | D | - range ratio = [ 1.0000] +24-11-19 20:23:37 | D | sum error = [ 1.5154] +24-11-19 20:23:37 | D | best error = [ 1.5154] +24-11-19 20:23:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:37 | D | sum error = [ 1.4846, 1.4870, 1.4861, 1.5137, 1.5481] +24-11-19 20:23:37 | D | best error = [ 1.3918, 1.3498, 1.3304, 1.3182, 1.3129] +24-11-19 20:23:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:37 | D | sum error = [ 1.5736, 1.6194, 1.6910, 1.7684, 1.8772] +24-11-19 20:23:37 | D | best error = [ 1.3102, 1.3090, 1.3083, 1.3080, 1.3079] +24-11-19 20:23:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:37 | D | sum error = [ 1.9685, 2.0881, 2.2212, 2.3690, 2.5327] +24-11-19 20:23:37 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 20:23:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:37 | D | sum error = [ 2.7144, 2.9169, 3.1262, 3.3473, 3.5932] +24-11-19 20:23:37 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 20:23:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:37 | D | sum error = [ 3.8467, 4.1142, 4.4017, 4.7176, 5.0320] +24-11-19 20:23:37 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 20:23:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:37 | D | sum error = [ 5.3655, 5.7427, 6.1359, 6.5291, 6.9685] +24-11-19 20:23:37 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 20:23:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:37 | D | sum error = [ 7.4181, 7.9068, 8.4137, 8.9445, 9.5171] +24-11-19 20:23:37 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 20:23:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:37 | D | sum error = [ 10.1042, 10.7327, 11.3958, 12.0976, 12.8040] +24-11-19 20:23:37 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 20:23:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:37 | D | sum error = [ 13.5730, 14.3843, 15.2318, 16.1326, 17.0590] +24-11-19 20:23:37 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 20:23:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:37 | D | sum error = [ 18.0457, 19.0807, 20.1648, 21.3049, 22.4921] +24-11-19 20:23:37 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 20:23:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:37 | D | sum error = [ 23.7519, 25.0506, 26.4223, 27.8446, 29.3259] +24-11-19 20:23:37 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 20:23:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:37 | D | sum error = [ 30.8812, 32.4901, 34.1792, 35.9361, 37.7566] +24-11-19 20:23:37 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 20:23:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:37 | D | sum error = [ 39.6575, 41.6315, 43.6693, 45.7924, 48.0013] +24-11-19 20:23:37 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 20:23:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:37 | D | sum error = [ 50.2936, 52.6619, 55.1279, 57.6747, 60.3189] +24-11-19 20:23:37 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 20:23:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:37 | D | sum error = [ 63.0729, 65.9147, 68.8619, 71.9143, 75.0676] +24-11-19 20:23:37 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 20:23:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:37 | D | sum error = [ 78.3039, 81.6621, 85.1177, 88.6777, 92.3427] +24-11-19 20:23:37 | D | best error = [ 1.3079, 1.3079, 1.3079, 1.3079, 1.3079] +24-11-19 20:23:37 | D | + error = [1.3079] +24-11-19 20:23:37 | D | - Calibrating model.layers.9.self_attn.o_proj.weight +24-11-19 20:23:37 | D | + w: sint8 +24-11-19 20:23:37 | D | + x: None +24-11-19 20:23:37 | D | + y: None +24-11-19 20:23:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:37 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:37 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:38 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:38 | D | - range ratio = [ 1.0000] +24-11-19 20:23:38 | D | sum error = [ 0.5988] +24-11-19 20:23:38 | D | best error = [ 0.5988] +24-11-19 20:23:38 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:38 | D | sum error = [ 0.5930, 0.5906, 0.5868, 0.5880, 0.5964] +24-11-19 20:23:38 | D | best error = [ 0.5446, 0.5202, 0.5060, 0.4951, 0.4882] +24-11-19 20:23:38 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:38 | D | sum error = [ 0.5957, 0.6081, 0.6182, 0.6324, 0.6502] +24-11-19 20:23:38 | D | best error = [ 0.4828, 0.4790, 0.4763, 0.4744, 0.4728] +24-11-19 20:23:38 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:38 | D | sum error = [ 0.6711, 0.6960, 0.7226, 0.7538, 0.7841] +24-11-19 20:23:38 | D | best error = [ 0.4718, 0.4711, 0.4706, 0.4703, 0.4700] +24-11-19 20:23:38 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:38 | D | sum error = [ 0.8265, 0.8686, 0.9099, 0.9582, 1.0102] +24-11-19 20:23:38 | D | best error = [ 0.4698, 0.4696, 0.4695, 0.4693, 0.4692] +24-11-19 20:23:38 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:38 | D | sum error = [ 1.0622, 1.1208, 1.1835, 1.2483, 1.3158] +24-11-19 20:23:38 | D | best error = [ 0.4691, 0.4691, 0.4690, 0.4690, 0.4689] +24-11-19 20:23:38 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:38 | D | sum error = [ 1.3890, 1.4621, 1.5436, 1.6302, 1.7199] +24-11-19 20:23:38 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 20:23:38 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:38 | D | sum error = [ 1.8138, 1.9098, 2.0154, 2.1217, 2.2345] +24-11-19 20:23:38 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 20:23:38 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:38 | D | sum error = [ 2.3530, 2.4802, 2.6102, 2.7485, 2.8942] +24-11-19 20:23:38 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 20:23:38 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:38 | D | sum error = [ 3.0425, 3.2010, 3.3631, 3.5379, 3.7172] +24-11-19 20:23:38 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 20:23:38 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:38 | D | sum error = [ 3.9093, 4.1079, 4.3168, 4.5313, 4.7593] +24-11-19 20:23:38 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 20:23:38 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:38 | D | sum error = [ 4.9992, 5.2464, 5.5025, 5.7740, 6.0577] +24-11-19 20:23:38 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 20:23:38 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:38 | D | sum error = [ 6.3518, 6.6595, 6.9776, 7.3092, 7.6533] +24-11-19 20:23:38 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 20:23:38 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:38 | D | sum error = [ 8.0123, 8.3840, 8.7703, 9.1733, 9.5954] +24-11-19 20:23:38 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 20:23:38 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:38 | D | sum error = [ 10.0306, 10.4825, 10.9524, 11.4374, 11.9388] +24-11-19 20:23:38 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 20:23:38 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:38 | D | sum error = [ 12.4578, 12.9968, 13.5531, 14.1285, 14.7244] +24-11-19 20:23:38 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 20:23:38 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:38 | D | sum error = [ 15.3433, 15.9824, 16.6457, 17.3309, 18.0442] +24-11-19 20:23:38 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 20:23:38 | D | + error = [0.4689] +24-11-19 20:23:38 | D | - Calibrating model.layers.9.mlp.up_proj.weight +24-11-19 20:23:38 | D | + w: sint8 +24-11-19 20:23:38 | D | + x: None +24-11-19 20:23:38 | D | + y: None +24-11-19 20:23:38 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:38 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:38 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:38 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:38 | D | - range ratio = [ 1.0000] +24-11-19 20:23:38 | D | sum error = [ 4.7746] +24-11-19 20:23:38 | D | best error = [ 4.7746] +24-11-19 20:23:39 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:39 | D | sum error = [ 4.7424, 4.7342, 4.7440, 4.8013, 4.8912] +24-11-19 20:23:39 | D | best error = [ 4.4662, 4.3421, 4.2771, 4.2399, 4.2209] +24-11-19 20:23:39 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:39 | D | sum error = [ 5.0195, 5.1865, 5.3996, 5.6577, 5.9477] +24-11-19 20:23:39 | D | best error = [ 4.2112, 4.2073, 4.2059, 4.2055, 4.2055] +24-11-19 20:23:39 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:39 | D | sum error = [ 6.2993, 6.6833, 7.1240, 7.6000, 8.1243] +24-11-19 20:23:39 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:23:39 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:39 | D | sum error = [ 8.7105, 9.3195, 9.9950, 10.7216, 11.4885] +24-11-19 20:23:39 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:23:39 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:39 | D | sum error = [ 12.3060, 13.1880, 14.1295, 15.1214, 16.1702] +24-11-19 20:23:39 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:23:39 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:39 | D | sum error = [ 17.2905, 18.4728, 19.7167, 21.0497, 22.4501] +24-11-19 20:23:39 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:23:39 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:39 | D | sum error = [ 23.9184, 25.4793, 27.1247, 28.8543, 30.6935] +24-11-19 20:23:39 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:23:39 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:39 | D | sum error = [ 32.6197, 34.6456, 36.7790, 39.0265, 41.3948] +24-11-19 20:23:39 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:23:39 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:39 | D | sum error = [ 43.8677, 46.4694, 49.2042, 52.0637, 55.0688] +24-11-19 20:23:39 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:23:39 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:39 | D | sum error = [ 58.2141, 61.5232, 64.9816, 68.6117, 72.3986] +24-11-19 20:23:39 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:23:39 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:39 | D | sum error = [ 76.3670, 80.5079, 84.8475, 89.3708, 94.0965] +24-11-19 20:23:39 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:23:39 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:39 | D | sum error = [ 99.0337, 104.1808, 109.5501, 115.1401, 120.9547] +24-11-19 20:23:39 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:23:39 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:39 | D | sum error = [ 127.0119, 133.3021, 139.8466, 146.6480, 153.7150] +24-11-19 20:23:39 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:23:39 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:39 | D | sum error = [ 161.0390, 168.6394, 176.5266, 184.6949, 193.1485] +24-11-19 20:23:39 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:23:39 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:39 | D | sum error = [ 201.8985, 210.9455, 220.2871, 229.9440, 239.9132] +24-11-19 20:23:39 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:23:39 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:39 | D | sum error = [ 250.1820, 260.7695, 271.6724, 282.9082, 294.4790] +24-11-19 20:23:39 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:23:39 | D | + error = [4.2054] +24-11-19 20:23:40 | D | - Calibrating model.layers.9.mlp.gate_proj.weight +24-11-19 20:23:40 | D | + w: sint8 +24-11-19 20:23:40 | D | + x: None +24-11-19 20:23:40 | D | + y: None +24-11-19 20:23:40 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:40 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:40 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:40 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:40 | D | - range ratio = [ 1.0000] +24-11-19 20:23:40 | D | sum error = [ 6.2400] +24-11-19 20:23:40 | D | best error = [ 6.2400] +24-11-19 20:23:41 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:41 | D | sum error = [ 6.1803, 6.1856, 6.1931, 6.2773, 6.3894] +24-11-19 20:23:41 | D | best error = [ 5.8297, 5.6701, 5.5852, 5.5365, 5.5106] +24-11-19 20:23:41 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:41 | D | sum error = [ 6.5548, 6.7607, 7.0566, 7.3733, 7.7653] +24-11-19 20:23:41 | D | best error = [ 5.4996, 5.4945, 5.4926, 5.4920, 5.4918] +24-11-19 20:23:41 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:41 | D | sum error = [ 8.2382, 8.7374, 9.3242, 9.9539, 10.6556] +24-11-19 20:23:41 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:23:41 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:41 | D | sum error = [ 11.4143, 12.2599, 13.1531, 14.1184, 15.1730] +24-11-19 20:23:41 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:23:41 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:41 | D | sum error = [ 16.2881, 17.4942, 18.7594, 20.1426, 21.6199] +24-11-19 20:23:41 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:23:41 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:41 | D | sum error = [ 23.1741, 24.8245, 26.5893, 28.4721, 30.4695] +24-11-19 20:23:41 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:23:41 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:41 | D | sum error = [ 32.5957, 34.8544, 37.2697, 39.8207, 42.5356] +24-11-19 20:23:41 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:23:41 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:41 | D | sum error = [ 45.4097, 48.4707, 51.7209, 55.1503, 58.8203] +24-11-19 20:23:41 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:23:41 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:41 | D | sum error = [ 62.6900, 66.8312, 71.1785, 75.8125, 80.7255] +24-11-19 20:23:41 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:23:41 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:41 | D | sum error = [ 85.9335, 91.4584, 97.3024, 103.4913, 110.0283] +24-11-19 20:23:41 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:23:41 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:41 | D | sum error = [ 116.9520, 124.2709, 132.0098, 140.1786, 148.7821] +24-11-19 20:23:41 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:23:41 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:41 | D | sum error = [ 157.8664, 167.4497, 177.5340, 188.1399, 199.2911] +24-11-19 20:23:41 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:23:41 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:41 | D | sum error = [ 211.0260, 223.3326, 236.2482, 249.7988, 264.0005] +24-11-19 20:23:41 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:23:41 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:41 | D | sum error = [ 278.8312, 294.3447, 310.5683, 327.4723, 345.1090] +24-11-19 20:23:41 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:23:41 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:41 | D | sum error = [ 363.4554, 382.5719, 402.4225, 423.0514, 444.4352] +24-11-19 20:23:41 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:23:41 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:41 | D | sum error = [ 466.5763, 489.4912, 513.1624, 537.5984, 562.7879] +24-11-19 20:23:41 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:23:41 | D | + error = [5.4918] +24-11-19 20:23:41 | D | - Calibrating model.layers.9.mlp.down_proj.weight +24-11-19 20:23:41 | D | + w: sint8 +24-11-19 20:23:41 | D | + x: None +24-11-19 20:23:41 | D | + y: None +24-11-19 20:23:41 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:41 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:41 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:41 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:41 | D | - range ratio = [ 1.0000] +24-11-19 20:23:41 | D | sum error = [ 0.5906] +24-11-19 20:23:41 | D | best error = [ 0.5906] +24-11-19 20:23:42 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:42 | D | sum error = [ 0.5843, 0.5794, 0.5773, 0.5768, 0.5766] +24-11-19 20:23:42 | D | best error = [ 0.5655, 0.5529, 0.5446, 0.5387, 0.5345] +24-11-19 20:23:42 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:42 | D | sum error = [ 0.5785, 0.5848, 0.5915, 0.6024, 0.6150] +24-11-19 20:23:42 | D | best error = [ 0.5313, 0.5287, 0.5270, 0.5258, 0.5249] +24-11-19 20:23:42 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:42 | D | sum error = [ 0.6326, 0.6527, 0.6753, 0.7030, 0.7342] +24-11-19 20:23:42 | D | best error = [ 0.5243, 0.5240, 0.5237, 0.5235, 0.5234] +24-11-19 20:23:42 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:42 | D | sum error = [ 0.7701, 0.8111, 0.8554, 0.9045, 0.9571] +24-11-19 20:23:42 | D | best error = [ 0.5233, 0.5233, 0.5233, 0.5233, 0.5233] +24-11-19 20:23:42 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:42 | D | sum error = [ 1.0170, 1.0821, 1.1512, 1.2273, 1.3080] +24-11-19 20:23:42 | D | best error = [ 0.5233, 0.5233, 0.5233, 0.5233, 0.5233] +24-11-19 20:23:42 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:42 | D | sum error = [ 1.3950, 1.4878, 1.5882, 1.6949, 1.8084] +24-11-19 20:23:42 | D | best error = [ 0.5233, 0.5233, 0.5233, 0.5233, 0.5233] +24-11-19 20:23:42 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:42 | D | sum error = [ 1.9320, 2.0598, 2.1987, 2.3447, 2.5002] +24-11-19 20:23:42 | D | best error = [ 0.5233, 0.5233, 0.5233, 0.5233, 0.5233] +24-11-19 20:23:42 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:42 | D | sum error = [ 2.6672, 2.8422, 3.0300, 3.2270, 3.4356] +24-11-19 20:23:42 | D | best error = [ 0.5233, 0.5233, 0.5233, 0.5233, 0.5233] +24-11-19 20:23:42 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:42 | D | sum error = [ 3.6575, 3.8907, 4.1383, 4.3993, 4.6732] +24-11-19 20:23:42 | D | best error = [ 0.5233, 0.5233, 0.5233, 0.5233, 0.5233] +24-11-19 20:23:42 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:42 | D | sum error = [ 4.9639, 5.2676, 5.5896, 5.9274, 6.2843] +24-11-19 20:23:42 | D | best error = [ 0.5233, 0.5233, 0.5233, 0.5233, 0.5233] +24-11-19 20:23:42 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:42 | D | sum error = [ 6.6587, 7.0522, 7.4643, 7.8971, 8.3498] +24-11-19 20:23:42 | D | best error = [ 0.5233, 0.5233, 0.5233, 0.5233, 0.5233] +24-11-19 20:23:42 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:42 | D | sum error = [ 8.8255, 9.3238, 9.8450, 10.3903, 10.9603] +24-11-19 20:23:42 | D | best error = [ 0.5233, 0.5233, 0.5233, 0.5233, 0.5233] +24-11-19 20:23:42 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:42 | D | sum error = [ 11.5570, 12.1802, 12.8316, 13.5102, 14.2187] +24-11-19 20:23:42 | D | best error = [ 0.5233, 0.5233, 0.5233, 0.5233, 0.5233] +24-11-19 20:23:42 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:42 | D | sum error = [ 14.9569, 15.7249, 16.5236, 17.3546, 18.2174] +24-11-19 20:23:42 | D | best error = [ 0.5233, 0.5233, 0.5233, 0.5233, 0.5233] +24-11-19 20:23:42 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:42 | D | sum error = [ 19.1143, 20.0449, 21.0109, 22.0112, 23.0493] +24-11-19 20:23:42 | D | best error = [ 0.5233, 0.5233, 0.5233, 0.5233, 0.5233] +24-11-19 20:23:42 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:42 | D | sum error = [ 24.1234, 25.2358, 26.3867, 27.5766, 28.8054] +24-11-19 20:23:42 | D | best error = [ 0.5233, 0.5233, 0.5233, 0.5233, 0.5233] +24-11-19 20:23:42 | D | + error = [0.5233] +24-11-19 20:23:43 | D | - Quantizing model.layers.9.self_attn.q_proj.weight +24-11-19 20:23:45 | D | - Quantizing model.layers.9.self_attn.k_proj.weight +24-11-19 20:23:47 | D | - Quantizing model.layers.9.self_attn.v_proj.weight +24-11-19 20:23:48 | D | - Quantizing model.layers.9.self_attn.o_proj.weight +24-11-19 20:23:50 | D | - Quantizing model.layers.9.mlp.up_proj.weight +24-11-19 20:23:55 | D | - Quantizing model.layers.9.mlp.gate_proj.weight +24-11-19 20:23:56 | D | - Quantizing model.layers.9.mlp.down_proj.weight +24-11-19 20:24:06 | D | - Quantizing layer model.layers.10 +24-11-19 20:24:06 | D | - Calibrating model.layers.10.self_attn.q_proj.weight +24-11-19 20:24:06 | D | + w: sint8 +24-11-19 20:24:06 | D | + x: None +24-11-19 20:24:06 | D | + y: None +24-11-19 20:24:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:24:06 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:06 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:07 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:07 | D | - range ratio = [ 1.0000] +24-11-19 20:24:07 | D | sum error = [ 4.0757] +24-11-19 20:24:07 | D | best error = [ 4.0757] +24-11-19 20:24:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:18 | D | sum error = [ 3.9989, 4.0930, 4.1257, 4.1743, 4.2067] +24-11-19 20:24:18 | D | best error = [ 3.9989, 3.9989, 3.9989, 3.9989, 3.9989] +24-11-19 20:24:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:18 | D | sum error = [ 4.3508, 4.4565, 4.5128, 5.0106, 5.1009] +24-11-19 20:24:18 | D | best error = [ 3.9989, 3.9989, 3.9989, 3.9989, 3.9989] +24-11-19 20:24:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:18 | D | sum error = [ 5.4978, 5.8760, 6.3317, 6.9135, 7.5886] +24-11-19 20:24:18 | D | best error = [ 3.9989, 3.9989, 3.9989, 3.9989, 3.9989] +24-11-19 20:24:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:18 | D | sum error = [ 8.0876, 8.6768, 9.6846, 10.3787, 11.1878] +24-11-19 20:24:18 | D | best error = [ 3.9989, 3.9989, 3.9989, 3.9989, 3.9989] +24-11-19 20:24:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:18 | D | sum error = [ 12.0859, 13.2910, 14.3348, 15.5170, 17.0065] +24-11-19 20:24:18 | D | best error = [ 3.9989, 3.9989, 3.9989, 3.9989, 3.9989] +24-11-19 20:24:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:18 | D | sum error = [ 17.8888, 19.5678, 20.6820, 22.4526, 24.0704] +24-11-19 20:24:18 | D | best error = [ 3.9989, 3.9989, 3.9989, 3.9989, 3.9989] +24-11-19 20:24:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:18 | D | sum error = [ 26.0588, 28.0435, 29.7889, 32.0045, 34.3606] +24-11-19 20:24:18 | D | best error = [ 3.9989, 3.9989, 3.9989, 3.9989, 3.9989] +24-11-19 20:24:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:18 | D | sum error = [ 36.9504, 40.0758, 42.9462, 46.3180, 49.6416] +24-11-19 20:24:18 | D | best error = [ 3.9989, 3.9989, 3.9989, 3.9989, 3.9989] +24-11-19 20:24:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:18 | D | sum error = [ 53.0952, 57.2757, 60.9089, 65.1368, 69.6323] +24-11-19 20:24:18 | D | best error = [ 3.9989, 3.9989, 3.9989, 3.9989, 3.9989] +24-11-19 20:24:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:18 | D | sum error = [ 74.2082, 79.1301, 84.4645, 90.3642, 96.3700] +24-11-19 20:24:18 | D | best error = [ 3.9989, 3.9989, 3.9989, 3.9989, 3.9989] +24-11-19 20:24:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:18 | D | sum error = [ 102.9737, 109.7562, 117.1608, 124.8612, 133.0465] +24-11-19 20:24:18 | D | best error = [ 3.9989, 3.9989, 3.9989, 3.9989, 3.9989] +24-11-19 20:24:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:18 | D | sum error = [ 141.5547, 150.8893, 160.4802, 170.7350, 181.4402] +24-11-19 20:24:18 | D | best error = [ 3.9989, 3.9989, 3.9989, 3.9989, 3.9989] +24-11-19 20:24:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:18 | D | sum error = [ 192.7496, 204.7794, 217.4348, 230.7159, 244.6777] +24-11-19 20:24:18 | D | best error = [ 3.9989, 3.9989, 3.9989, 3.9989, 3.9989] +24-11-19 20:24:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:18 | D | sum error = [ 259.2515, 274.8187, 291.0561, 308.0848, 325.9220] +24-11-19 20:24:18 | D | best error = [ 3.9989, 3.9989, 3.9989, 3.9989, 3.9989] +24-11-19 20:24:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:18 | D | sum error = [ 344.5533, 363.8735, 383.7553, 404.5038, 425.6324] +24-11-19 20:24:18 | D | best error = [ 3.9989, 3.9989, 3.9989, 3.9989, 3.9989] +24-11-19 20:24:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:18 | D | sum error = [ 447.3688, 469.6715, 492.1740, 515.0138, 537.9675] +24-11-19 20:24:18 | D | best error = [ 3.9989, 3.9989, 3.9989, 3.9989, 3.9989] +24-11-19 20:24:18 | D | + error = [3.9989] +24-11-19 20:24:19 | D | - Calibrating model.layers.10.self_attn.k_proj.weight +24-11-19 20:24:19 | D | + w: sint8 +24-11-19 20:24:19 | D | + x: None +24-11-19 20:24:19 | D | + y: None +24-11-19 20:24:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:24:19 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:19 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:19 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:19 | D | - range ratio = [ 1.0000] +24-11-19 20:24:19 | D | sum error = [ 3.5615] +24-11-19 20:24:19 | D | best error = [ 3.5615] +24-11-19 20:24:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:31 | D | sum error = [ 3.3730, 3.6201, 3.5159, 3.5745, 3.5101] +24-11-19 20:24:31 | D | best error = [ 3.3730, 3.3730, 3.3730, 3.3730, 3.3730] +24-11-19 20:24:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:31 | D | sum error = [ 4.2095, 3.9669, 3.9603, 4.4943, 5.0663] +24-11-19 20:24:31 | D | best error = [ 3.3730, 3.3730, 3.3730, 3.3730, 3.3730] +24-11-19 20:24:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:31 | D | sum error = [ 4.9663, 6.0665, 5.8828, 6.7320, 7.1482] +24-11-19 20:24:31 | D | best error = [ 3.3730, 3.3730, 3.3730, 3.3730, 3.3730] +24-11-19 20:24:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:31 | D | sum error = [ 7.4849, 9.2695, 9.8534, 10.3261, 11.9707] +24-11-19 20:24:31 | D | best error = [ 3.3730, 3.3730, 3.3730, 3.3730, 3.3730] +24-11-19 20:24:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:31 | D | sum error = [ 12.9245, 13.9469, 14.6343, 16.0922, 18.0551] +24-11-19 20:24:31 | D | best error = [ 3.3730, 3.3730, 3.3730, 3.3730, 3.3730] +24-11-19 20:24:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:31 | D | sum error = [ 18.5600, 21.2781, 22.0343, 22.9294, 24.1144] +24-11-19 20:24:31 | D | best error = [ 3.3730, 3.3730, 3.3730, 3.3730, 3.3730] +24-11-19 20:24:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:31 | D | sum error = [ 26.1687, 27.7724, 30.3045, 32.7894, 34.9489] +24-11-19 20:24:31 | D | best error = [ 3.3730, 3.3730, 3.3730, 3.3730, 3.3730] +24-11-19 20:24:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:31 | D | sum error = [ 37.4621, 40.9554, 43.4545, 47.8018, 49.9876] +24-11-19 20:24:31 | D | best error = [ 3.3730, 3.3730, 3.3730, 3.3730, 3.3730] +24-11-19 20:24:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:31 | D | sum error = [ 53.9105, 57.5321, 61.7340, 65.6505, 70.5478] +24-11-19 20:24:31 | D | best error = [ 3.3730, 3.3730, 3.3730, 3.3730, 3.3730] +24-11-19 20:24:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:31 | D | sum error = [ 74.7640, 79.6527, 84.7739, 90.6393, 96.7544] +24-11-19 20:24:31 | D | best error = [ 3.3730, 3.3730, 3.3730, 3.3730, 3.3730] +24-11-19 20:24:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:31 | D | sum error = [ 102.9333, 109.0982, 117.1457, 124.7313, 132.5354] +24-11-19 20:24:31 | D | best error = [ 3.3730, 3.3730, 3.3730, 3.3730, 3.3730] +24-11-19 20:24:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:31 | D | sum error = [ 140.8738, 149.6291, 159.1996, 169.3989, 180.0887] +24-11-19 20:24:31 | D | best error = [ 3.3730, 3.3730, 3.3730, 3.3730, 3.3730] +24-11-19 20:24:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:31 | D | sum error = [ 191.4317, 203.0227, 215.3033, 227.7431, 240.4221] +24-11-19 20:24:31 | D | best error = [ 3.3730, 3.3730, 3.3730, 3.3730, 3.3730] +24-11-19 20:24:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:31 | D | sum error = [ 254.1394, 268.6350, 283.9142, 300.3627, 317.5175] +24-11-19 20:24:31 | D | best error = [ 3.3730, 3.3730, 3.3730, 3.3730, 3.3730] +24-11-19 20:24:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:31 | D | sum error = [ 336.2964, 355.8796, 375.8569, 397.2607, 418.4240] +24-11-19 20:24:31 | D | best error = [ 3.3730, 3.3730, 3.3730, 3.3730, 3.3730] +24-11-19 20:24:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:31 | D | sum error = [ 440.9888, 462.7988, 485.6969, 509.0507, 533.0327] +24-11-19 20:24:31 | D | best error = [ 3.3730, 3.3730, 3.3730, 3.3730, 3.3730] +24-11-19 20:24:31 | D | + error = [3.3730] +24-11-19 20:24:31 | D | - Calibrating model.layers.10.self_attn.v_proj.weight +24-11-19 20:24:31 | D | + w: sint8 +24-11-19 20:24:31 | D | + x: None +24-11-19 20:24:31 | D | + y: None +24-11-19 20:24:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:31 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:31 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:31 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:31 | D | - range ratio = [ 1.0000] +24-11-19 20:24:31 | D | sum error = [ 1.2930] +24-11-19 20:24:31 | D | best error = [ 1.2930] +24-11-19 20:24:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:31 | D | sum error = [ 1.3016, 1.2853, 1.2941, 1.3082, 1.3242] +24-11-19 20:24:31 | D | best error = [ 1.2037, 1.1668, 1.1481, 1.1377, 1.1307] +24-11-19 20:24:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:31 | D | sum error = [ 1.3687, 1.4234, 1.4744, 1.5509, 1.6302] +24-11-19 20:24:31 | D | best error = [ 1.1289, 1.1277, 1.1274, 1.1272, 1.1272] +24-11-19 20:24:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:31 | D | sum error = [ 1.7168, 1.8473, 1.9672, 2.1094, 2.2627] +24-11-19 20:24:31 | D | best error = [ 1.1272, 1.1272, 1.1272, 1.1272, 1.1272] +24-11-19 20:24:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:31 | D | sum error = [ 2.4045, 2.5821, 2.7855, 2.9854, 3.2141] +24-11-19 20:24:31 | D | best error = [ 1.1272, 1.1272, 1.1272, 1.1272, 1.1272] +24-11-19 20:24:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:31 | D | sum error = [ 3.4368, 3.6796, 3.9366, 4.2032, 4.4994] +24-11-19 20:24:31 | D | best error = [ 1.1272, 1.1272, 1.1272, 1.1272, 1.1272] +24-11-19 20:24:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:31 | D | sum error = [ 4.8142, 5.1414, 5.4715, 5.8593, 6.2333] +24-11-19 20:24:31 | D | best error = [ 1.1272, 1.1272, 1.1272, 1.1272, 1.1272] +24-11-19 20:24:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:31 | D | sum error = [ 6.6529, 7.0764, 7.5334, 8.0243, 8.5344] +24-11-19 20:24:31 | D | best error = [ 1.1272, 1.1272, 1.1272, 1.1272, 1.1272] +24-11-19 20:24:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:31 | D | sum error = [ 9.0834, 9.6663, 10.2538, 10.8893, 11.5512] +24-11-19 20:24:31 | D | best error = [ 1.1272, 1.1272, 1.1272, 1.1272, 1.1272] +24-11-19 20:24:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:31 | D | sum error = [ 12.2463, 12.9690, 13.7459, 14.5357, 15.3966] +24-11-19 20:24:31 | D | best error = [ 1.1272, 1.1272, 1.1272, 1.1272, 1.1272] +24-11-19 20:24:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:31 | D | sum error = [ 16.2800, 17.2093, 18.1888, 19.2065, 20.2795] +24-11-19 20:24:31 | D | best error = [ 1.1272, 1.1272, 1.1272, 1.1272, 1.1272] +24-11-19 20:24:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:31 | D | sum error = [ 21.4050, 22.5716, 23.8084, 25.0864, 26.4302] +24-11-19 20:24:31 | D | best error = [ 1.1272, 1.1272, 1.1272, 1.1272, 1.1272] +24-11-19 20:24:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:31 | D | sum error = [ 27.8279, 29.2910, 30.8204, 32.4153, 34.0768] +24-11-19 20:24:31 | D | best error = [ 1.1272, 1.1272, 1.1272, 1.1272, 1.1272] +24-11-19 20:24:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:31 | D | sum error = [ 35.8109, 37.6034, 39.4814, 41.4300, 43.4511] +24-11-19 20:24:31 | D | best error = [ 1.1272, 1.1272, 1.1272, 1.1272, 1.1272] +24-11-19 20:24:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:31 | D | sum error = [ 45.5513, 47.7222, 49.9759, 52.3184, 54.7269] +24-11-19 20:24:31 | D | best error = [ 1.1272, 1.1272, 1.1272, 1.1272, 1.1272] +24-11-19 20:24:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:31 | D | sum error = [ 57.2291, 59.8201, 62.4904, 65.2598, 68.1089] +24-11-19 20:24:31 | D | best error = [ 1.1272, 1.1272, 1.1272, 1.1272, 1.1272] +24-11-19 20:24:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:31 | D | sum error = [ 71.0436, 74.0730, 77.1900, 80.4103, 83.7222] +24-11-19 20:24:31 | D | best error = [ 1.1272, 1.1272, 1.1272, 1.1272, 1.1272] +24-11-19 20:24:31 | D | + error = [1.1272] +24-11-19 20:24:31 | D | - Calibrating model.layers.10.self_attn.o_proj.weight +24-11-19 20:24:31 | D | + w: sint8 +24-11-19 20:24:31 | D | + x: None +24-11-19 20:24:31 | D | + y: None +24-11-19 20:24:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:31 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:31 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:32 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:32 | D | - range ratio = [ 1.0000] +24-11-19 20:24:32 | D | sum error = [ 0.5436] +24-11-19 20:24:32 | D | best error = [ 0.5436] +24-11-19 20:24:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:32 | D | sum error = [ 0.5385, 0.5361, 0.5382, 0.5383, 0.5443] +24-11-19 20:24:32 | D | best error = [ 0.4867, 0.4644, 0.4507, 0.4419, 0.4359] +24-11-19 20:24:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:32 | D | sum error = [ 0.5546, 0.5647, 0.5830, 0.6030, 0.6261] +24-11-19 20:24:32 | D | best error = [ 0.4318, 0.4284, 0.4264, 0.4250, 0.4240] +24-11-19 20:24:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:32 | D | sum error = [ 0.6536, 0.6809, 0.7134, 0.7493, 0.7945] +24-11-19 20:24:32 | D | best error = [ 0.4232, 0.4226, 0.4222, 0.4218, 0.4216] +24-11-19 20:24:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:32 | D | sum error = [ 0.8386, 0.8857, 0.9349, 0.9938, 1.0504] +24-11-19 20:24:32 | D | best error = [ 0.4215, 0.4213, 0.4212, 0.4211, 0.4210] +24-11-19 20:24:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:32 | D | sum error = [ 1.1144, 1.1828, 1.2536, 1.3300, 1.4098] +24-11-19 20:24:32 | D | best error = [ 0.4209, 0.4209, 0.4208, 0.4208, 0.4208] +24-11-19 20:24:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:32 | D | sum error = [ 1.4935, 1.5854, 1.6739, 1.7753, 1.8759] +24-11-19 20:24:32 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:24:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:32 | D | sum error = [ 1.9882, 2.0995, 2.2159, 2.3414, 2.4732] +24-11-19 20:24:32 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:24:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:32 | D | sum error = [ 2.6109, 2.7540, 2.9057, 3.0639, 3.2276] +24-11-19 20:24:32 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:24:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:32 | D | sum error = [ 3.4021, 3.5792, 3.7715, 3.9680, 4.1739] +24-11-19 20:24:32 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:24:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:32 | D | sum error = [ 4.3874, 4.6125, 4.8455, 5.0892, 5.3398] +24-11-19 20:24:32 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:24:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:32 | D | sum error = [ 5.6039, 5.8787, 6.1635, 6.4559, 6.7658] +24-11-19 20:24:32 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:24:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:32 | D | sum error = [ 7.0846, 7.4164, 7.7592, 8.1182, 8.4865] +24-11-19 20:24:32 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:24:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:32 | D | sum error = [ 8.8701, 9.2651, 9.6761, 10.1027, 10.5403] +24-11-19 20:24:32 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:24:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:32 | D | sum error = [ 10.9965, 11.4650, 11.9483, 12.4487, 12.9629] +24-11-19 20:24:32 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:24:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:32 | D | sum error = [ 13.4947, 14.0401, 14.6029, 15.1836, 15.7808] +24-11-19 20:24:32 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:24:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:32 | D | sum error = [ 16.3945, 17.0261, 17.6757, 18.3416, 19.0261] +24-11-19 20:24:32 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:24:32 | D | + error = [0.4208] +24-11-19 20:24:32 | D | - Calibrating model.layers.10.mlp.up_proj.weight +24-11-19 20:24:32 | D | + w: sint8 +24-11-19 20:24:32 | D | + x: None +24-11-19 20:24:32 | D | + y: None +24-11-19 20:24:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:32 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:32 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:32 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:32 | D | - range ratio = [ 1.0000] +24-11-19 20:24:32 | D | sum error = [ 4.9256] +24-11-19 20:24:32 | D | best error = [ 4.9256] +24-11-19 20:24:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:34 | D | sum error = [ 4.8767, 4.8760, 4.8902, 4.9433, 5.0448] +24-11-19 20:24:34 | D | best error = [ 4.5814, 4.4533, 4.3840, 4.3445, 4.3234] +24-11-19 20:24:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:34 | D | sum error = [ 5.1679, 5.3503, 5.5597, 5.8194, 6.1360] +24-11-19 20:24:34 | D | best error = [ 4.3138, 4.3091, 4.3078, 4.3073, 4.3072] +24-11-19 20:24:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:34 | D | sum error = [ 6.4729, 6.8698, 7.3241, 7.8104, 8.3543] +24-11-19 20:24:34 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:24:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:34 | D | sum error = [ 8.9462, 9.5741, 10.2649, 11.0110, 11.7875] +24-11-19 20:24:34 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:24:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:34 | D | sum error = [ 12.6272, 13.5349, 14.4926, 15.4917, 16.5715] +24-11-19 20:24:34 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:24:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:34 | D | sum error = [ 17.7114, 18.9209, 20.2034, 21.5575, 22.9869] +24-11-19 20:24:34 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:24:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:34 | D | sum error = [ 24.5018, 26.0886, 27.7730, 29.5384, 31.4141] +24-11-19 20:24:34 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:24:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:34 | D | sum error = [ 33.3779, 35.4477, 37.6240, 39.9137, 42.3249] +24-11-19 20:24:34 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:24:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:34 | D | sum error = [ 44.8556, 47.5182, 50.3072, 53.2325, 56.3009] +24-11-19 20:24:34 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:24:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:34 | D | sum error = [ 59.5174, 62.8778, 66.4106, 70.1052, 73.9589] +24-11-19 20:24:34 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:24:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:34 | D | sum error = [ 78.0032, 82.2116, 86.6239, 91.2110, 96.0236] +24-11-19 20:24:34 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:24:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:34 | D | sum error = [ 101.0313, 106.2512, 111.6929, 117.3443, 123.2296] +24-11-19 20:24:34 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:24:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:34 | D | sum error = [ 129.3550, 135.7184, 142.3155, 149.1909, 156.3223] +24-11-19 20:24:34 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:24:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:34 | D | sum error = [ 163.7152, 171.3854, 179.3330, 187.5797, 196.1061] +24-11-19 20:24:34 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:24:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:34 | D | sum error = [ 204.9242, 214.0354, 223.4636, 233.1960, 243.2489] +24-11-19 20:24:34 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:24:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:34 | D | sum error = [ 253.6031, 264.2853, 275.2823, 286.6052, 298.2628] +24-11-19 20:24:34 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:24:34 | D | + error = [4.3072] +24-11-19 20:24:34 | D | - Calibrating model.layers.10.mlp.gate_proj.weight +24-11-19 20:24:34 | D | + w: sint8 +24-11-19 20:24:34 | D | + x: None +24-11-19 20:24:34 | D | + y: None +24-11-19 20:24:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:34 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:34 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:34 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:34 | D | - range ratio = [ 1.0000] +24-11-19 20:24:34 | D | sum error = [ 6.1663] +24-11-19 20:24:34 | D | best error = [ 6.1663] +24-11-19 20:24:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:35 | D | sum error = [ 6.1187, 6.1047, 6.1389, 6.2018, 6.3049] +24-11-19 20:24:35 | D | best error = [ 5.7391, 5.5779, 5.4916, 5.4428, 5.4164] +24-11-19 20:24:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:35 | D | sum error = [ 6.4838, 6.7023, 6.9800, 7.3145, 7.7033] +24-11-19 20:24:35 | D | best error = [ 5.4036, 5.3984, 5.3963, 5.3958, 5.3957] +24-11-19 20:24:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:35 | D | sum error = [ 8.1569, 8.6706, 9.2525, 9.8714, 10.5724] +24-11-19 20:24:35 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:24:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:35 | D | sum error = [ 11.3335, 12.1451, 13.0660, 14.0112, 15.0403] +24-11-19 20:24:35 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:24:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:35 | D | sum error = [ 16.1732, 17.3328, 18.6218, 19.9746, 21.4165] +24-11-19 20:24:35 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:24:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:35 | D | sum error = [ 22.9595, 24.5747, 26.3320, 28.1762, 30.1369] +24-11-19 20:24:35 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:24:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:35 | D | sum error = [ 32.2085, 34.4486, 36.8158, 39.3136, 41.9888] +24-11-19 20:24:35 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:24:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:35 | D | sum error = [ 44.7983, 47.7950, 50.9899, 54.3597, 57.9665] +24-11-19 20:24:35 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:24:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:35 | D | sum error = [ 61.7553, 65.7834, 70.0648, 74.6027, 79.3902] +24-11-19 20:24:35 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:24:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:35 | D | sum error = [ 84.4633, 89.8591, 95.5741, 101.5873, 107.9739] +24-11-19 20:24:35 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:24:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:35 | D | sum error = [ 114.7144, 121.8334, 129.3429, 137.3148, 145.6752] +24-11-19 20:24:35 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:24:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:35 | D | sum error = [ 154.5139, 163.8234, 173.6207, 183.9280, 194.7671] +24-11-19 20:24:35 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:24:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:35 | D | sum error = [ 206.1157, 218.0466, 230.5664, 243.6613, 257.3763] +24-11-19 20:24:35 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:24:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:35 | D | sum error = [ 271.7433, 286.7187, 302.3926, 318.7516, 335.7852] +24-11-19 20:24:35 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:24:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:35 | D | sum error = [ 353.5459, 372.0098, 391.1886, 411.1085, 431.7607] +24-11-19 20:24:35 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:24:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:35 | D | sum error = [ 453.1838, 475.3182, 498.1956, 521.7860, 546.1134] +24-11-19 20:24:35 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:24:35 | D | + error = [5.3957] +24-11-19 20:24:35 | D | - Calibrating model.layers.10.mlp.down_proj.weight +24-11-19 20:24:35 | D | + w: sint8 +24-11-19 20:24:35 | D | + x: None +24-11-19 20:24:35 | D | + y: None +24-11-19 20:24:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:35 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:35 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:35 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:35 | D | - range ratio = [ 1.0000] +24-11-19 20:24:35 | D | sum error = [ 0.6022] +24-11-19 20:24:35 | D | best error = [ 0.6022] +24-11-19 20:24:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:36 | D | sum error = [ 0.5983, 0.5935, 0.5900, 0.5876, 0.5882] +24-11-19 20:24:36 | D | best error = [ 0.5786, 0.5662, 0.5583, 0.5522, 0.5474] +24-11-19 20:24:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:36 | D | sum error = [ 0.5914, 0.5947, 0.6016, 0.6101, 0.6227] +24-11-19 20:24:36 | D | best error = [ 0.5441, 0.5415, 0.5396, 0.5385, 0.5376] +24-11-19 20:24:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:36 | D | sum error = [ 0.6379, 0.6553, 0.6760, 0.7041, 0.7337] +24-11-19 20:24:36 | D | best error = [ 0.5372, 0.5368, 0.5366, 0.5363, 0.5362] +24-11-19 20:24:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:36 | D | sum error = [ 0.7679, 0.8068, 0.8510, 0.8989, 0.9513] +24-11-19 20:24:36 | D | best error = [ 0.5361, 0.5361, 0.5361, 0.5361, 0.5360] +24-11-19 20:24:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:36 | D | sum error = [ 1.0104, 1.0755, 1.1448, 1.2214, 1.3018] +24-11-19 20:24:36 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 20:24:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:36 | D | sum error = [ 1.3894, 1.4834, 1.5836, 1.6911, 1.8071] +24-11-19 20:24:36 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 20:24:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:36 | D | sum error = [ 1.9296, 2.0618, 2.2013, 2.3503, 2.5064] +24-11-19 20:24:36 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 20:24:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:36 | D | sum error = [ 2.6741, 2.8526, 3.0418, 3.2392, 3.4492] +24-11-19 20:24:36 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 20:24:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:36 | D | sum error = [ 3.6727, 3.9069, 4.1549, 4.4172, 4.6936] +24-11-19 20:24:36 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 20:24:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:36 | D | sum error = [ 4.9852, 5.2918, 5.6157, 5.9561, 6.3145] +24-11-19 20:24:36 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 20:24:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:36 | D | sum error = [ 6.6906, 7.0874, 7.5026, 7.9391, 8.3964] +24-11-19 20:24:36 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 20:24:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:36 | D | sum error = [ 8.8747, 9.3762, 9.9006, 10.4494, 11.0220] +24-11-19 20:24:36 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 20:24:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:36 | D | sum error = [ 11.6207, 12.2446, 12.8976, 13.5775, 14.2862] +24-11-19 20:24:36 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 20:24:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:36 | D | sum error = [ 15.0245, 15.7934, 16.5935, 17.4263, 18.2907] +24-11-19 20:24:36 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 20:24:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:36 | D | sum error = [ 19.1887, 20.1207, 21.0874, 22.0899, 23.1291] +24-11-19 20:24:36 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 20:24:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:36 | D | sum error = [ 24.2047, 25.3183, 26.4704, 27.6608, 28.8915] +24-11-19 20:24:36 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 20:24:36 | D | + error = [0.5360] +24-11-19 20:24:37 | D | - Quantizing model.layers.10.self_attn.q_proj.weight +24-11-19 20:24:38 | D | - Quantizing model.layers.10.self_attn.k_proj.weight +24-11-19 20:24:39 | D | - Quantizing model.layers.10.self_attn.v_proj.weight +24-11-19 20:24:40 | D | - Quantizing model.layers.10.self_attn.o_proj.weight +24-11-19 20:24:41 | D | - Quantizing model.layers.10.mlp.up_proj.weight +24-11-19 20:24:45 | D | - Quantizing model.layers.10.mlp.gate_proj.weight +24-11-19 20:24:47 | D | - Quantizing model.layers.10.mlp.down_proj.weight +24-11-19 20:24:58 | D | - Quantizing layer model.layers.11 +24-11-19 20:24:58 | D | - Calibrating model.layers.11.self_attn.q_proj.weight +24-11-19 20:24:58 | D | + w: sint8 +24-11-19 20:24:58 | D | + x: None +24-11-19 20:24:58 | D | + y: None +24-11-19 20:24:58 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:24:58 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:24:58 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:24:59 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:24:59 | D | - range ratio = [ 1.0000] +24-11-19 20:24:59 | D | sum error = [ 4.4979] +24-11-19 20:24:59 | D | best error = [ 4.4979] +24-11-19 20:25:11 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:11 | D | sum error = [ 4.3721, 4.4148, 4.4380, 4.4156, 4.5642] +24-11-19 20:25:11 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 20:25:11 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:11 | D | sum error = [ 4.6259, 4.9750, 5.0068, 5.3357, 5.5484] +24-11-19 20:25:11 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 20:25:11 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:11 | D | sum error = [ 6.0419, 6.3763, 6.8873, 7.1490, 7.6716] +24-11-19 20:25:11 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 20:25:11 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:11 | D | sum error = [ 8.5521, 8.9245, 9.6067, 10.3982, 11.3407] +24-11-19 20:25:11 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 20:25:11 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:11 | D | sum error = [ 12.3207, 13.2214, 14.6281, 16.0143, 17.6168] +24-11-19 20:25:11 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 20:25:11 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:11 | D | sum error = [ 19.0770, 20.5509, 22.3670, 24.2283, 26.5855] +24-11-19 20:25:11 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 20:25:11 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:11 | D | sum error = [ 28.7918, 31.3781, 33.3870, 36.2180, 38.7576] +24-11-19 20:25:11 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 20:25:11 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:11 | D | sum error = [ 41.6845, 44.4325, 47.8419, 51.2936, 54.9866] +24-11-19 20:25:11 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 20:25:11 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:11 | D | sum error = [ 58.6118, 62.6334, 66.7317, 71.0663, 75.8226] +24-11-19 20:25:11 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 20:25:11 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:11 | D | sum error = [ 80.7371, 85.9357, 91.3915, 97.2737, 103.1698] +24-11-19 20:25:11 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 20:25:11 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:11 | D | sum error = [ 109.5080, 116.0310, 122.9870, 130.4916, 138.3147] +24-11-19 20:25:11 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 20:25:11 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:11 | D | sum error = [ 146.1676, 154.9447, 163.7094, 173.1212, 182.6968] +24-11-19 20:25:11 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 20:25:11 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:11 | D | sum error = [ 192.8168, 203.5713, 214.5901, 226.1917, 238.1606] +24-11-19 20:25:11 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 20:25:11 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:11 | D | sum error = [ 250.6459, 263.6957, 277.2370, 291.2464, 305.9988] +24-11-19 20:25:11 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 20:25:11 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:11 | D | sum error = [ 321.1886, 337.1069, 353.5267, 370.5407, 388.0650] +24-11-19 20:25:11 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 20:25:11 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:11 | D | sum error = [ 406.1756, 424.8549, 443.8447, 463.4727, 483.3884] +24-11-19 20:25:11 | D | best error = [ 4.3721, 4.3721, 4.3721, 4.3721, 4.3721] +24-11-19 20:25:11 | D | + error = [4.3721] +24-11-19 20:25:11 | D | - Calibrating model.layers.11.self_attn.k_proj.weight +24-11-19 20:25:11 | D | + w: sint8 +24-11-19 20:25:11 | D | + x: None +24-11-19 20:25:11 | D | + y: None +24-11-19 20:25:11 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:25:11 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:11 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:11 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:11 | D | - range ratio = [ 1.0000] +24-11-19 20:25:11 | D | sum error = [ 3.9506] +24-11-19 20:25:11 | D | best error = [ 3.9506] +24-11-19 20:25:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:23 | D | sum error = [ 3.5568, 3.9704, 3.7614, 3.7873, 4.0482] +24-11-19 20:25:23 | D | best error = [ 3.5568, 3.5568, 3.5568, 3.5568, 3.5568] +24-11-19 20:25:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:23 | D | sum error = [ 3.9487, 3.9511, 4.7482, 4.6706, 4.7524] +24-11-19 20:25:23 | D | best error = [ 3.5568, 3.5568, 3.5568, 3.5568, 3.5568] +24-11-19 20:25:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:23 | D | sum error = [ 4.6702, 4.6857, 5.5968, 6.0473, 6.5862] +24-11-19 20:25:23 | D | best error = [ 3.5568, 3.5568, 3.5568, 3.5568, 3.5568] +24-11-19 20:25:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:23 | D | sum error = [ 6.4137, 7.3072, 7.3641, 8.3503, 8.6071] +24-11-19 20:25:23 | D | best error = [ 3.5568, 3.5568, 3.5568, 3.5568, 3.5568] +24-11-19 20:25:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:23 | D | sum error = [ 9.4011, 10.7947, 11.5223, 12.0085, 13.8912] +24-11-19 20:25:23 | D | best error = [ 3.5568, 3.5568, 3.5568, 3.5568, 3.5568] +24-11-19 20:25:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:23 | D | sum error = [ 14.8154, 15.3004, 16.7396, 17.6729, 18.7798] +24-11-19 20:25:23 | D | best error = [ 3.5568, 3.5568, 3.5568, 3.5568, 3.5568] +24-11-19 20:25:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:23 | D | sum error = [ 19.9201, 21.4951, 22.8311, 23.7535, 26.0103] +24-11-19 20:25:23 | D | best error = [ 3.5568, 3.5568, 3.5568, 3.5568, 3.5568] +24-11-19 20:25:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:23 | D | sum error = [ 27.9002, 30.2095, 32.6144, 35.0800, 38.1259] +24-11-19 20:25:23 | D | best error = [ 3.5568, 3.5568, 3.5568, 3.5568, 3.5568] +24-11-19 20:25:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:23 | D | sum error = [ 40.7787, 43.8307, 47.4060, 51.3500, 54.9848] +24-11-19 20:25:23 | D | best error = [ 3.5568, 3.5568, 3.5568, 3.5568, 3.5568] +24-11-19 20:25:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:23 | D | sum error = [ 59.2949, 63.2292, 67.9060, 73.2231, 78.1398] +24-11-19 20:25:23 | D | best error = [ 3.5568, 3.5568, 3.5568, 3.5568, 3.5568] +24-11-19 20:25:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:23 | D | sum error = [ 83.0258, 89.0987, 95.0870, 101.8584, 108.7720] +24-11-19 20:25:23 | D | best error = [ 3.5568, 3.5568, 3.5568, 3.5568, 3.5568] +24-11-19 20:25:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:23 | D | sum error = [ 116.9255, 125.2536, 133.9017, 143.3457, 153.3869] +24-11-19 20:25:23 | D | best error = [ 3.5568, 3.5568, 3.5568, 3.5568, 3.5568] +24-11-19 20:25:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:23 | D | sum error = [ 163.5092, 174.3253, 186.0759, 197.9923, 211.3691] +24-11-19 20:25:23 | D | best error = [ 3.5568, 3.5568, 3.5568, 3.5568, 3.5568] +24-11-19 20:25:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:23 | D | sum error = [ 224.5695, 238.5450, 253.1724, 267.4720, 283.2500] +24-11-19 20:25:23 | D | best error = [ 3.5568, 3.5568, 3.5568, 3.5568, 3.5568] +24-11-19 20:25:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:23 | D | sum error = [ 299.6615, 316.3230, 333.9629, 352.3220, 371.6266] +24-11-19 20:25:23 | D | best error = [ 3.5568, 3.5568, 3.5568, 3.5568, 3.5568] +24-11-19 20:25:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:23 | D | sum error = [ 391.5474, 411.7038, 432.5316, 453.5935, 474.6563] +24-11-19 20:25:23 | D | best error = [ 3.5568, 3.5568, 3.5568, 3.5568, 3.5568] +24-11-19 20:25:23 | D | + error = [3.5568] +24-11-19 20:25:23 | D | - Calibrating model.layers.11.self_attn.v_proj.weight +24-11-19 20:25:23 | D | + w: sint8 +24-11-19 20:25:23 | D | + x: None +24-11-19 20:25:23 | D | + y: None +24-11-19 20:25:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:23 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:23 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:23 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:23 | D | - range ratio = [ 1.0000] +24-11-19 20:25:23 | D | sum error = [ 1.3218] +24-11-19 20:25:23 | D | best error = [ 1.3218] +24-11-19 20:25:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:23 | D | sum error = [ 1.3346, 1.3229, 1.3282, 1.3424, 1.3747] +24-11-19 20:25:23 | D | best error = [ 1.2336, 1.1988, 1.1795, 1.1686, 1.1630] +24-11-19 20:25:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:23 | D | sum error = [ 1.4015, 1.4426, 1.5050, 1.5764, 1.6626] +24-11-19 20:25:23 | D | best error = [ 1.1605, 1.1597, 1.1594, 1.1593, 1.1593] +24-11-19 20:25:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:23 | D | sum error = [ 1.7673, 1.8567, 1.9720, 2.1075, 2.2687] +24-11-19 20:25:23 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:25:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:23 | D | sum error = [ 2.4105, 2.5891, 2.7742, 2.9766, 3.1838] +24-11-19 20:25:23 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:25:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:23 | D | sum error = [ 3.4142, 3.6699, 3.9295, 4.2133, 4.5067] +24-11-19 20:25:23 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:25:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:23 | D | sum error = [ 4.8198, 5.1588, 5.5152, 5.8746, 6.2908] +24-11-19 20:25:23 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:25:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:23 | D | sum error = [ 6.7135, 7.1528, 7.6380, 8.1288, 8.6426] +24-11-19 20:25:23 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:25:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:23 | D | sum error = [ 9.1915, 9.7821, 10.3851, 11.0337, 11.7098] +24-11-19 20:25:23 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:25:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:23 | D | sum error = [ 12.4336, 13.1913, 13.9876, 14.8252, 15.7179] +24-11-19 20:25:23 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:25:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:23 | D | sum error = [ 16.6359, 17.6124, 18.6211, 19.6839, 20.8004] +24-11-19 20:25:23 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:25:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:23 | D | sum error = [ 21.9703, 23.1891, 24.4650, 25.8167, 27.2143] +24-11-19 20:25:23 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:25:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:23 | D | sum error = [ 28.6792, 30.2062, 31.8126, 33.4812, 35.2097] +24-11-19 20:25:23 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:25:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:23 | D | sum error = [ 37.0239, 38.9125, 40.8811, 42.9275, 45.0578] +24-11-19 20:25:23 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:25:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:23 | D | sum error = [ 47.2748, 49.5773, 51.9749, 54.4574, 57.0344] +24-11-19 20:25:23 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:25:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:23 | D | sum error = [ 59.7054, 62.4856, 65.3571, 68.3335, 71.4034] +24-11-19 20:25:23 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:25:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:23 | D | sum error = [ 74.5717, 77.8480, 81.2233, 84.7112, 88.2921] +24-11-19 20:25:23 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:25:23 | D | + error = [1.1593] +24-11-19 20:25:23 | D | - Calibrating model.layers.11.self_attn.o_proj.weight +24-11-19 20:25:23 | D | + w: sint8 +24-11-19 20:25:23 | D | + x: None +24-11-19 20:25:23 | D | + y: None +24-11-19 20:25:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:23 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:23 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:24 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:24 | D | - range ratio = [ 1.0000] +24-11-19 20:25:24 | D | sum error = [ 0.5878] +24-11-19 20:25:24 | D | best error = [ 0.5878] +24-11-19 20:25:24 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:24 | D | sum error = [ 0.5827, 0.5814, 0.5757, 0.5830, 0.5843] +24-11-19 20:25:24 | D | best error = [ 0.5158, 0.4886, 0.4726, 0.4630, 0.4557] +24-11-19 20:25:24 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:24 | D | sum error = [ 0.5924, 0.6012, 0.6144, 0.6290, 0.6508] +24-11-19 20:25:24 | D | best error = [ 0.4504, 0.4463, 0.4428, 0.4403, 0.4385] +24-11-19 20:25:24 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:24 | D | sum error = [ 0.6713, 0.7039, 0.7310, 0.7717, 0.8036] +24-11-19 20:25:24 | D | best error = [ 0.4372, 0.4360, 0.4351, 0.4344, 0.4340] +24-11-19 20:25:24 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:24 | D | sum error = [ 0.8513, 0.8954, 0.9500, 1.0031, 1.0673] +24-11-19 20:25:24 | D | best error = [ 0.4336, 0.4333, 0.4329, 0.4326, 0.4324] +24-11-19 20:25:24 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:24 | D | sum error = [ 1.1290, 1.1941, 1.2661, 1.3500, 1.4292] +24-11-19 20:25:24 | D | best error = [ 0.4323, 0.4321, 0.4320, 0.4319, 0.4319] +24-11-19 20:25:24 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:24 | D | sum error = [ 1.5190, 1.6134, 1.7064, 1.8167, 1.9240] +24-11-19 20:25:24 | D | best error = [ 0.4318, 0.4318, 0.4317, 0.4317, 0.4317] +24-11-19 20:25:24 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:24 | D | sum error = [ 2.0390, 2.1607, 2.2902, 2.4260, 2.5694] +24-11-19 20:25:24 | D | best error = [ 0.4317, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:25:24 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:24 | D | sum error = [ 2.7165, 2.8716, 3.0333, 3.2051, 3.3805] +24-11-19 20:25:24 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:25:24 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:24 | D | sum error = [ 3.5674, 3.7593, 3.9608, 4.1712, 4.3928] +24-11-19 20:25:24 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:25:24 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:24 | D | sum error = [ 4.6183, 4.8550, 5.1029, 5.3602, 5.6299] +24-11-19 20:25:24 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:25:24 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:24 | D | sum error = [ 5.9100, 6.2020, 6.5040, 6.8137, 7.1409] +24-11-19 20:25:24 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:25:24 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:24 | D | sum error = [ 7.4726, 7.8196, 8.1781, 8.5488, 8.9277] +24-11-19 20:25:24 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:25:24 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:24 | D | sum error = [ 9.3240, 9.7289, 10.1461, 10.5736, 11.0149] +24-11-19 20:25:24 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:25:24 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:24 | D | sum error = [ 11.4714, 11.9357, 12.4137, 12.9032, 13.4039] +24-11-19 20:25:24 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:25:24 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:24 | D | sum error = [ 13.9175, 14.4441, 14.9840, 15.5361, 16.1025] +24-11-19 20:25:24 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:25:24 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:24 | D | sum error = [ 16.6821, 17.2712, 17.8726, 18.4904, 19.1221] +24-11-19 20:25:24 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:25:24 | D | + error = [0.4316] +24-11-19 20:25:24 | D | - Calibrating model.layers.11.mlp.up_proj.weight +24-11-19 20:25:24 | D | + w: sint8 +24-11-19 20:25:24 | D | + x: None +24-11-19 20:25:24 | D | + y: None +24-11-19 20:25:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:24 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:24 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:24 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:24 | D | - range ratio = [ 1.0000] +24-11-19 20:25:24 | D | sum error = [ 5.0178] +24-11-19 20:25:24 | D | best error = [ 5.0178] +24-11-19 20:25:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:25 | D | sum error = [ 4.9834, 4.9683, 4.9860, 5.0473, 5.1333] +24-11-19 20:25:25 | D | best error = [ 4.6584, 4.5242, 4.4524, 4.4121, 4.3904] +24-11-19 20:25:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:25 | D | sum error = [ 5.2572, 5.4364, 5.6594, 5.9256, 6.2305] +24-11-19 20:25:25 | D | best error = [ 4.3801, 4.3754, 4.3741, 4.3736, 4.3735] +24-11-19 20:25:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:25 | D | sum error = [ 6.5901, 7.0044, 7.4497, 7.9338, 8.4847] +24-11-19 20:25:25 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 20:25:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:25 | D | sum error = [ 9.0887, 9.7390, 10.4356, 11.1646, 11.9760] +24-11-19 20:25:25 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 20:25:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:25 | D | sum error = [ 12.8368, 13.7470, 14.7184, 15.7465, 16.8468] +24-11-19 20:25:25 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 20:25:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:25 | D | sum error = [ 18.0051, 19.2371, 20.5260, 21.9089, 23.3587] +24-11-19 20:25:25 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 20:25:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:25 | D | sum error = [ 24.8953, 26.5062, 28.2088, 30.0089, 31.8981] +24-11-19 20:25:25 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 20:25:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:25 | D | sum error = [ 33.8799, 35.9791, 38.1847, 40.5028, 42.9372] +24-11-19 20:25:25 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 20:25:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:25 | D | sum error = [ 45.4986, 48.1838, 51.0101, 53.9741, 57.0842] +24-11-19 20:25:25 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 20:25:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:25 | D | sum error = [ 60.3491, 63.7613, 67.3446, 71.0806, 74.9929] +24-11-19 20:25:25 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 20:25:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:25 | D | sum error = [ 79.0938, 83.3857, 87.8560, 92.5313, 97.4125] +24-11-19 20:25:25 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 20:25:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:25 | D | sum error = [ 102.4934, 107.7964, 113.3142, 119.0641, 125.0502] +24-11-19 20:25:25 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 20:25:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:25 | D | sum error = [ 131.2734, 137.7478, 144.4710, 151.4664, 158.7288] +24-11-19 20:25:25 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 20:25:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:25 | D | sum error = [ 166.2487, 174.0589, 182.1663, 190.5735, 199.2767] +24-11-19 20:25:25 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 20:25:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:25 | D | sum error = [ 208.2935, 217.5970, 227.2255, 237.1687, 247.4226] +24-11-19 20:25:25 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 20:25:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:25 | D | sum error = [ 258.0113, 268.9309, 280.1775, 291.7525, 303.6721] +24-11-19 20:25:25 | D | best error = [ 4.3735, 4.3735, 4.3735, 4.3735, 4.3735] +24-11-19 20:25:25 | D | + error = [4.3735] +24-11-19 20:25:26 | D | - Calibrating model.layers.11.mlp.gate_proj.weight +24-11-19 20:25:26 | D | + w: sint8 +24-11-19 20:25:26 | D | + x: None +24-11-19 20:25:26 | D | + y: None +24-11-19 20:25:26 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:26 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:26 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:26 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:26 | D | - range ratio = [ 1.0000] +24-11-19 20:25:26 | D | sum error = [ 6.1484] +24-11-19 20:25:26 | D | best error = [ 6.1484] +24-11-19 20:25:27 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:27 | D | sum error = [ 6.1071, 6.0891, 6.1144, 6.1729, 6.3092] +24-11-19 20:25:27 | D | best error = [ 5.7140, 5.5460, 5.4574, 5.4067, 5.3802] +24-11-19 20:25:27 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:27 | D | sum error = [ 6.4718, 6.6792, 6.9558, 7.2925, 7.6669] +24-11-19 20:25:27 | D | best error = [ 5.3678, 5.3623, 5.3607, 5.3602, 5.3601] +24-11-19 20:25:27 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:27 | D | sum error = [ 8.1321, 8.6422, 9.2205, 9.8339, 10.5395] +24-11-19 20:25:27 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:25:27 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:27 | D | sum error = [ 11.3227, 12.1327, 13.0341, 14.0025, 15.0359] +24-11-19 20:25:27 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:25:27 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:27 | D | sum error = [ 16.1512, 17.3468, 18.6197, 19.9621, 21.4343] +24-11-19 20:25:27 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:25:27 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:27 | D | sum error = [ 22.9688, 24.6137, 26.3813, 28.2282, 30.2034] +24-11-19 20:25:27 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:25:27 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:27 | D | sum error = [ 32.3122, 34.5553, 36.9235, 39.4511, 42.1412] +24-11-19 20:25:27 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:25:27 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:27 | D | sum error = [ 44.9864, 48.0101, 51.2224, 54.6452, 58.2439] +24-11-19 20:25:27 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:25:27 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:27 | D | sum error = [ 62.0633, 66.1355, 70.4293, 75.0011, 79.8360] +24-11-19 20:25:27 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:25:27 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:27 | D | sum error = [ 84.9547, 90.3965, 96.1310, 102.2118, 108.6535] +24-11-19 20:25:27 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:25:27 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:27 | D | sum error = [ 115.4952, 122.6842, 130.3043, 138.3655, 146.8423] +24-11-19 20:25:27 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:25:27 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:27 | D | sum error = [ 155.7895, 165.2405, 175.1986, 185.6491, 196.6596] +24-11-19 20:25:27 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:25:27 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:27 | D | sum error = [ 208.2394, 220.3803, 233.1349, 246.4872, 260.4758] +24-11-19 20:25:27 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:25:27 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:27 | D | sum error = [ 275.1101, 290.4096, 306.3798, 323.0686, 340.4757] +24-11-19 20:25:27 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:25:27 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:27 | D | sum error = [ 358.5696, 377.4143, 396.9943, 417.3194, 438.3875] +24-11-19 20:25:27 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:25:27 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:27 | D | sum error = [ 460.2233, 482.8103, 506.1780, 530.2587, 555.1143] +24-11-19 20:25:27 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:25:27 | D | + error = [5.3600] +24-11-19 20:25:27 | D | - Calibrating model.layers.11.mlp.down_proj.weight +24-11-19 20:25:27 | D | + w: sint8 +24-11-19 20:25:27 | D | + x: None +24-11-19 20:25:27 | D | + y: None +24-11-19 20:25:27 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:27 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:27 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:27 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:27 | D | - range ratio = [ 1.0000] +24-11-19 20:25:27 | D | sum error = [ 0.6149] +24-11-19 20:25:27 | D | best error = [ 0.6149] +24-11-19 20:25:28 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:28 | D | sum error = [ 0.6082, 0.6049, 0.6005, 0.5996, 0.5998] +24-11-19 20:25:28 | D | best error = [ 0.5874, 0.5755, 0.5670, 0.5611, 0.5565] +24-11-19 20:25:28 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:28 | D | sum error = [ 0.6030, 0.6091, 0.6170, 0.6286, 0.6416] +24-11-19 20:25:28 | D | best error = [ 0.5535, 0.5514, 0.5496, 0.5486, 0.5479] +24-11-19 20:25:28 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:28 | D | sum error = [ 0.6594, 0.6810, 0.7078, 0.7371, 0.7700] +24-11-19 20:25:28 | D | best error = [ 0.5473, 0.5470, 0.5467, 0.5465, 0.5465] +24-11-19 20:25:28 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:28 | D | sum error = [ 0.8069, 0.8506, 0.8969, 0.9485, 1.0060] +24-11-19 20:25:28 | D | best error = [ 0.5464, 0.5464, 0.5464, 0.5463, 0.5463] +24-11-19 20:25:28 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:28 | D | sum error = [ 1.0689, 1.1349, 1.2098, 1.2879, 1.3720] +24-11-19 20:25:28 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 20:25:28 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:28 | D | sum error = [ 1.4635, 1.5609, 1.6646, 1.7755, 1.8951] +24-11-19 20:25:28 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 20:25:28 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:28 | D | sum error = [ 2.0213, 2.1564, 2.3001, 2.4528, 2.6154] +24-11-19 20:25:28 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 20:25:28 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:28 | D | sum error = [ 2.7870, 2.9690, 3.1608, 3.3639, 3.5800] +24-11-19 20:25:28 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 20:25:28 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:28 | D | sum error = [ 3.8077, 4.0474, 4.3023, 4.5701, 4.8527] +24-11-19 20:25:28 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 20:25:28 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:28 | D | sum error = [ 5.1499, 5.4633, 5.7928, 6.1401, 6.5050] +24-11-19 20:25:28 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 20:25:28 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:28 | D | sum error = [ 6.8895, 7.2933, 7.7163, 8.1621, 8.6282] +24-11-19 20:25:28 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 20:25:28 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:28 | D | sum error = [ 9.1166, 9.6285, 10.1645, 10.7235, 11.3090] +24-11-19 20:25:28 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 20:25:28 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:28 | D | sum error = [ 11.9201, 12.5586, 13.2246, 13.9198, 14.6459] +24-11-19 20:25:28 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 20:25:28 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:28 | D | sum error = [ 15.4031, 16.1920, 17.0118, 17.8668, 18.7540] +24-11-19 20:25:28 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 20:25:28 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:28 | D | sum error = [ 19.6773, 20.6345, 21.6294, 22.6616, 23.7315] +24-11-19 20:25:28 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 20:25:28 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:28 | D | sum error = [ 24.8398, 25.9876, 27.1744, 28.4019, 29.6693] +24-11-19 20:25:28 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 20:25:28 | D | + error = [0.5463] +24-11-19 20:25:28 | D | - Quantizing model.layers.11.self_attn.q_proj.weight +24-11-19 20:25:29 | D | - Quantizing model.layers.11.self_attn.k_proj.weight +24-11-19 20:25:30 | D | - Quantizing model.layers.11.self_attn.v_proj.weight +24-11-19 20:25:31 | D | - Quantizing model.layers.11.self_attn.o_proj.weight +24-11-19 20:25:32 | D | - Quantizing model.layers.11.mlp.up_proj.weight +24-11-19 20:25:33 | D | - Quantizing model.layers.11.mlp.gate_proj.weight +24-11-19 20:25:34 | D | - Quantizing model.layers.11.mlp.down_proj.weight +24-11-19 20:25:47 | D | - Quantizing layer model.layers.12 +24-11-19 20:25:47 | D | - Calibrating model.layers.12.self_attn.q_proj.weight +24-11-19 20:25:47 | D | + w: sint8 +24-11-19 20:25:47 | D | + x: None +24-11-19 20:25:47 | D | + y: None +24-11-19 20:25:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:25:47 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:25:47 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:25:47 | D | + finished calculating the original outputs, ram usage: 13.3 +24-11-19 20:25:47 | D | - range ratio = [ 1.0000] +24-11-19 20:25:47 | D | sum error = [ 3.9265] +24-11-19 20:25:47 | D | best error = [ 3.9265] +24-11-19 20:25:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:59 | D | sum error = [ 3.8392, 3.9270, 3.8071, 3.9549, 4.1037] +24-11-19 20:25:59 | D | best error = [ 3.8392, 3.8392, 3.8071, 3.8071, 3.8071] +24-11-19 20:25:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:59 | D | sum error = [ 4.2005, 4.3698, 4.5978, 4.6249, 5.1402] +24-11-19 20:25:59 | D | best error = [ 3.8071, 3.8071, 3.8071, 3.8071, 3.8071] +24-11-19 20:25:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:59 | D | sum error = [ 5.2261, 5.6114, 5.9920, 6.5189, 6.9516] +24-11-19 20:25:59 | D | best error = [ 3.8071, 3.8071, 3.8071, 3.8071, 3.8071] +24-11-19 20:25:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:59 | D | sum error = [ 7.5446, 8.2079, 8.7829, 9.5531, 10.2997] +24-11-19 20:25:59 | D | best error = [ 3.8071, 3.8071, 3.8071, 3.8071, 3.8071] +24-11-19 20:25:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:59 | D | sum error = [ 11.2694, 12.3323, 13.5085, 14.8764, 16.2443] +24-11-19 20:25:59 | D | best error = [ 3.8071, 3.8071, 3.8071, 3.8071, 3.8071] +24-11-19 20:25:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:59 | D | sum error = [ 17.5503, 19.1539, 20.7981, 22.7758, 24.3639] +24-11-19 20:25:59 | D | best error = [ 3.8071, 3.8071, 3.8071, 3.8071, 3.8071] +24-11-19 20:25:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:59 | D | sum error = [ 26.6799, 28.6767, 30.8780, 33.2889, 35.8927] +24-11-19 20:25:59 | D | best error = [ 3.8071, 3.8071, 3.8071, 3.8071, 3.8071] +24-11-19 20:25:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:59 | D | sum error = [ 38.9408, 41.7762, 44.9015, 48.1980, 51.8362] +24-11-19 20:25:59 | D | best error = [ 3.8071, 3.8071, 3.8071, 3.8071, 3.8071] +24-11-19 20:25:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:59 | D | sum error = [ 55.5955, 59.5312, 63.8050, 68.3884, 72.9540] +24-11-19 20:25:59 | D | best error = [ 3.8071, 3.8071, 3.8071, 3.8071, 3.8071] +24-11-19 20:25:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:59 | D | sum error = [ 77.9239, 83.4649, 89.0688, 94.9961, 101.2492] +24-11-19 20:25:59 | D | best error = [ 3.8071, 3.8071, 3.8071, 3.8071, 3.8071] +24-11-19 20:25:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:59 | D | sum error = [ 107.7947, 114.6445, 121.9472, 129.3251, 137.4035] +24-11-19 20:25:59 | D | best error = [ 3.8071, 3.8071, 3.8071, 3.8071, 3.8071] +24-11-19 20:25:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:59 | D | sum error = [ 145.6282, 154.4435, 163.3398, 172.7734, 182.8057] +24-11-19 20:25:59 | D | best error = [ 3.8071, 3.8071, 3.8071, 3.8071, 3.8071] +24-11-19 20:25:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:59 | D | sum error = [ 193.0190, 203.9752, 215.4083, 227.0949, 239.7386] +24-11-19 20:25:59 | D | best error = [ 3.8071, 3.8071, 3.8071, 3.8071, 3.8071] +24-11-19 20:25:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:59 | D | sum error = [ 253.0967, 267.0042, 281.7740, 297.3182, 313.7029] +24-11-19 20:25:59 | D | best error = [ 3.8071, 3.8071, 3.8071, 3.8071, 3.8071] +24-11-19 20:25:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:59 | D | sum error = [ 331.0308, 349.1469, 368.1066, 387.9859, 408.6227] +24-11-19 20:25:59 | D | best error = [ 3.8071, 3.8071, 3.8071, 3.8071, 3.8071] +24-11-19 20:25:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:59 | D | sum error = [ 430.1422, 452.3383, 475.4091, 499.0596, 523.2358] +24-11-19 20:25:59 | D | best error = [ 3.8071, 3.8071, 3.8071, 3.8071, 3.8071] +24-11-19 20:25:59 | D | + error = [3.8071] +24-11-19 20:25:59 | D | - Calibrating model.layers.12.self_attn.k_proj.weight +24-11-19 20:25:59 | D | + w: sint8 +24-11-19 20:25:59 | D | + x: None +24-11-19 20:25:59 | D | + y: None +24-11-19 20:25:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:25:59 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:59 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:59 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:00 | D | - range ratio = [ 1.0000] +24-11-19 20:26:00 | D | sum error = [ 3.8877] +24-11-19 20:26:00 | D | best error = [ 3.8877] +24-11-19 20:26:11 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:11 | D | sum error = [ 3.5450, 3.6860, 4.0035, 4.0730, 3.7346] +24-11-19 20:26:11 | D | best error = [ 3.5450, 3.5450, 3.5450, 3.5450, 3.5450] +24-11-19 20:26:11 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:11 | D | sum error = [ 3.9543, 3.8303, 3.8440, 4.3742, 4.9371] +24-11-19 20:26:11 | D | best error = [ 3.5450, 3.5450, 3.5450, 3.5450, 3.5450] +24-11-19 20:26:11 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:11 | D | sum error = [ 5.1364, 5.5005, 5.9083, 5.5268, 6.4376] +24-11-19 20:26:11 | D | best error = [ 3.5450, 3.5450, 3.5450, 3.5450, 3.5450] +24-11-19 20:26:11 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:11 | D | sum error = [ 7.0018, 7.1663, 8.2748, 8.4647, 9.0509] +24-11-19 20:26:11 | D | best error = [ 3.5450, 3.5450, 3.5450, 3.5450, 3.5450] +24-11-19 20:26:11 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:11 | D | sum error = [ 9.5997, 11.3104, 12.3899, 12.4282, 13.7183] +24-11-19 20:26:11 | D | best error = [ 3.5450, 3.5450, 3.5450, 3.5450, 3.5450] +24-11-19 20:26:11 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:11 | D | sum error = [ 14.5279, 16.3019, 17.3984, 18.9612, 20.7093] +24-11-19 20:26:11 | D | best error = [ 3.5450, 3.5450, 3.5450, 3.5450, 3.5450] +24-11-19 20:26:11 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:11 | D | sum error = [ 22.0040, 23.7118, 25.9859, 27.8149, 30.3475] +24-11-19 20:26:11 | D | best error = [ 3.5450, 3.5450, 3.5450, 3.5450, 3.5450] +24-11-19 20:26:11 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:11 | D | sum error = [ 32.9760, 35.5748, 38.4056, 41.2230, 44.0194] +24-11-19 20:26:11 | D | best error = [ 3.5450, 3.5450, 3.5450, 3.5450, 3.5450] +24-11-19 20:26:11 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:11 | D | sum error = [ 47.5771, 51.0455, 54.2278, 58.3127, 62.4982] +24-11-19 20:26:11 | D | best error = [ 3.5450, 3.5450, 3.5450, 3.5450, 3.5450] +24-11-19 20:26:11 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:11 | D | sum error = [ 66.8923, 72.1744, 77.0655, 81.8676, 87.1833] +24-11-19 20:26:11 | D | best error = [ 3.5450, 3.5450, 3.5450, 3.5450, 3.5450] +24-11-19 20:26:11 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:11 | D | sum error = [ 92.7836, 99.4133, 106.2042, 113.3489, 120.9173] +24-11-19 20:26:11 | D | best error = [ 3.5450, 3.5450, 3.5450, 3.5450, 3.5450] +24-11-19 20:26:11 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:11 | D | sum error = [ 128.6062, 137.4996, 147.0152, 156.8451, 166.4739] +24-11-19 20:26:11 | D | best error = [ 3.5450, 3.5450, 3.5450, 3.5450, 3.5450] +24-11-19 20:26:11 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:11 | D | sum error = [ 177.1306, 188.8242, 200.6128, 213.0203, 226.6332] +24-11-19 20:26:11 | D | best error = [ 3.5450, 3.5450, 3.5450, 3.5450, 3.5450] +24-11-19 20:26:11 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:11 | D | sum error = [ 241.9368, 257.3110, 273.3944, 290.6236, 308.4424] +24-11-19 20:26:11 | D | best error = [ 3.5450, 3.5450, 3.5450, 3.5450, 3.5450] +24-11-19 20:26:11 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:11 | D | sum error = [ 326.1264, 345.1471, 364.8194, 386.1923, 406.8950] +24-11-19 20:26:11 | D | best error = [ 3.5450, 3.5450, 3.5450, 3.5450, 3.5450] +24-11-19 20:26:11 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:11 | D | sum error = [ 428.6218, 451.8193, 474.9028, 498.8532, 523.6834] +24-11-19 20:26:11 | D | best error = [ 3.5450, 3.5450, 3.5450, 3.5450, 3.5450] +24-11-19 20:26:11 | D | + error = [3.5450] +24-11-19 20:26:12 | D | - Calibrating model.layers.12.self_attn.v_proj.weight +24-11-19 20:26:12 | D | + w: sint8 +24-11-19 20:26:12 | D | + x: None +24-11-19 20:26:12 | D | + y: None +24-11-19 20:26:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:12 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:12 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:12 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:12 | D | - range ratio = [ 1.0000] +24-11-19 20:26:12 | D | sum error = [ 1.4830] +24-11-19 20:26:12 | D | best error = [ 1.4830] +24-11-19 20:26:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:12 | D | sum error = [ 1.4765, 1.4614, 1.4630, 1.4768, 1.5103] +24-11-19 20:26:12 | D | best error = [ 1.3705, 1.3279, 1.3040, 1.2913, 1.2850] +24-11-19 20:26:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:12 | D | sum error = [ 1.5584, 1.6064, 1.6758, 1.7461, 1.8507] +24-11-19 20:26:12 | D | best error = [ 1.2827, 1.2816, 1.2812, 1.2812, 1.2812] +24-11-19 20:26:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:12 | D | sum error = [ 1.9547, 2.0594, 2.2076, 2.3608, 2.5323] +24-11-19 20:26:12 | D | best error = [ 1.2812, 1.2812, 1.2812, 1.2812, 1.2812] +24-11-19 20:26:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:12 | D | sum error = [ 2.6900, 2.8793, 3.0993, 3.3177, 3.5565] +24-11-19 20:26:12 | D | best error = [ 1.2812, 1.2812, 1.2812, 1.2812, 1.2812] +24-11-19 20:26:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:12 | D | sum error = [ 3.8151, 4.1024, 4.3671, 4.6764, 4.9912] +24-11-19 20:26:12 | D | best error = [ 1.2812, 1.2812, 1.2812, 1.2812, 1.2812] +24-11-19 20:26:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:12 | D | sum error = [ 5.3541, 5.6956, 6.0710, 6.4643, 6.8867] +24-11-19 20:26:12 | D | best error = [ 1.2812, 1.2812, 1.2812, 1.2812, 1.2812] +24-11-19 20:26:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:12 | D | sum error = [ 7.3192, 7.7914, 8.2880, 8.8144, 9.3730] +24-11-19 20:26:12 | D | best error = [ 1.2812, 1.2812, 1.2812, 1.2812, 1.2812] +24-11-19 20:26:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:12 | D | sum error = [ 9.9518, 10.5887, 11.2227, 11.9154, 12.6187] +24-11-19 20:26:12 | D | best error = [ 1.2812, 1.2812, 1.2812, 1.2812, 1.2812] +24-11-19 20:26:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:12 | D | sum error = [ 13.3742, 14.1612, 14.9865, 15.8652, 16.7672] +24-11-19 20:26:12 | D | best error = [ 1.2812, 1.2812, 1.2812, 1.2812, 1.2812] +24-11-19 20:26:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:12 | D | sum error = [ 17.7348, 18.7319, 19.7907, 20.9008, 22.0486] +24-11-19 20:26:12 | D | best error = [ 1.2812, 1.2812, 1.2812, 1.2812, 1.2812] +24-11-19 20:26:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:12 | D | sum error = [ 23.2562, 24.5111, 25.8254, 27.2025, 28.6389] +24-11-19 20:26:12 | D | best error = [ 1.2812, 1.2812, 1.2812, 1.2812, 1.2812] +24-11-19 20:26:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:12 | D | sum error = [ 30.1280, 31.6760, 33.2886, 34.9687, 36.7128] +24-11-19 20:26:12 | D | best error = [ 1.2812, 1.2812, 1.2812, 1.2812, 1.2812] +24-11-19 20:26:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:12 | D | sum error = [ 38.5217, 40.3988, 42.3433, 44.3634, 46.4458] +24-11-19 20:26:12 | D | best error = [ 1.2812, 1.2812, 1.2812, 1.2812, 1.2812] +24-11-19 20:26:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:12 | D | sum error = [ 48.6074, 50.8597, 53.1745, 55.5874, 58.0888] +24-11-19 20:26:12 | D | best error = [ 1.2812, 1.2812, 1.2812, 1.2812, 1.2812] +24-11-19 20:26:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:12 | D | sum error = [ 60.6729, 63.3412, 66.1045, 68.9449, 71.8762] +24-11-19 20:26:12 | D | best error = [ 1.2812, 1.2812, 1.2812, 1.2812, 1.2812] +24-11-19 20:26:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:12 | D | sum error = [ 74.9023, 78.0122, 81.2210, 84.5212, 87.9257] +24-11-19 20:26:12 | D | best error = [ 1.2812, 1.2812, 1.2812, 1.2812, 1.2812] +24-11-19 20:26:12 | D | + error = [1.2812] +24-11-19 20:26:12 | D | - Calibrating model.layers.12.self_attn.o_proj.weight +24-11-19 20:26:12 | D | + w: sint8 +24-11-19 20:26:12 | D | + x: None +24-11-19 20:26:12 | D | + y: None +24-11-19 20:26:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:12 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:12 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:12 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:12 | D | - range ratio = [ 1.0000] +24-11-19 20:26:12 | D | sum error = [ 0.6289] +24-11-19 20:26:12 | D | best error = [ 0.6289] +24-11-19 20:26:13 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:13 | D | sum error = [ 0.6250, 0.6200, 0.6215, 0.6243, 0.6330] +24-11-19 20:26:13 | D | best error = [ 0.5732, 0.5483, 0.5347, 0.5259, 0.5200] +24-11-19 20:26:13 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:13 | D | sum error = [ 0.6442, 0.6590, 0.6755, 0.6963, 0.7223] +24-11-19 20:26:13 | D | best error = [ 0.5163, 0.5137, 0.5122, 0.5111, 0.5104] +24-11-19 20:26:13 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:13 | D | sum error = [ 0.7579, 0.7926, 0.8321, 0.8776, 0.9335] +24-11-19 20:26:13 | D | best error = [ 0.5100, 0.5098, 0.5096, 0.5096, 0.5095] +24-11-19 20:26:13 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:13 | D | sum error = [ 0.9844, 1.0463, 1.1124, 1.1852, 1.2639] +24-11-19 20:26:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:13 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:13 | D | sum error = [ 1.3422, 1.4332, 1.5255, 1.6273, 1.7308] +24-11-19 20:26:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:13 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:13 | D | sum error = [ 1.8446, 1.9602, 2.0878, 2.2212, 2.3595] +24-11-19 20:26:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:13 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:13 | D | sum error = [ 2.5071, 2.6610, 2.8226, 2.9966, 3.1769] +24-11-19 20:26:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:13 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:13 | D | sum error = [ 3.3624, 3.5629, 3.7722, 3.9892, 4.2193] +24-11-19 20:26:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:13 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:13 | D | sum error = [ 4.4532, 4.7079, 4.9695, 5.2449, 5.5311] +24-11-19 20:26:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:13 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:13 | D | sum error = [ 5.8292, 6.1454, 6.4711, 6.8132, 7.1664] +24-11-19 20:26:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:13 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:13 | D | sum error = [ 7.5351, 7.9199, 8.3152, 8.7278, 9.1561] +24-11-19 20:26:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:13 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:13 | D | sum error = [ 9.5972, 10.0581, 10.5330, 11.0279, 11.5381] +24-11-19 20:26:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:13 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:13 | D | sum error = [ 12.0650, 12.6098, 13.1714, 13.7515, 14.3501] +24-11-19 20:26:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:13 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:13 | D | sum error = [ 14.9624, 15.5946, 16.2466, 16.9153, 17.6012] +24-11-19 20:26:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:13 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:13 | D | sum error = [ 18.3061, 19.0288, 19.7712, 20.5323, 21.3134] +24-11-19 20:26:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:13 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:13 | D | sum error = [ 22.1184, 22.9427, 23.7845, 24.6459, 25.5300] +24-11-19 20:26:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:13 | D | + error = [0.5095] +24-11-19 20:26:13 | D | - Calibrating model.layers.12.mlp.up_proj.weight +24-11-19 20:26:13 | D | + w: sint8 +24-11-19 20:26:13 | D | + x: None +24-11-19 20:26:13 | D | + y: None +24-11-19 20:26:13 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:13 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:13 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:13 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:13 | D | - range ratio = [ 1.0000] +24-11-19 20:26:13 | D | sum error = [ 5.0365] +24-11-19 20:26:13 | D | best error = [ 5.0365] +24-11-19 20:26:14 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:14 | D | sum error = [ 4.9992, 4.9831, 5.0031, 5.0550, 5.1622] +24-11-19 20:26:14 | D | best error = [ 4.6634, 4.5225, 4.4472, 4.4068, 4.3856] +24-11-19 20:26:14 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:14 | D | sum error = [ 5.2902, 5.4588, 5.6779, 5.9660, 6.2834] +24-11-19 20:26:14 | D | best error = [ 4.3743, 4.3697, 4.3676, 4.3671, 4.3669] +24-11-19 20:26:14 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:14 | D | sum error = [ 6.6253, 7.0490, 7.5112, 8.0191, 8.5750] +24-11-19 20:26:14 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 20:26:14 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:14 | D | sum error = [ 9.1854, 9.8435, 10.5495, 11.3059, 12.1207] +24-11-19 20:26:14 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 20:26:14 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:14 | D | sum error = [ 12.9943, 13.9326, 14.9021, 15.9495, 17.0560] +24-11-19 20:26:14 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 20:26:14 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:14 | D | sum error = [ 18.2419, 19.4998, 20.8228, 22.2130, 23.7031] +24-11-19 20:26:14 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 20:26:14 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:14 | D | sum error = [ 25.2612, 26.9170, 28.6588, 30.4929, 32.4460] +24-11-19 20:26:14 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 20:26:14 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:14 | D | sum error = [ 34.4735, 36.6296, 38.9025, 41.2866, 43.7984] +24-11-19 20:26:14 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 20:26:14 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:14 | D | sum error = [ 46.4298, 49.2230, 52.1409, 55.2075, 58.4338] +24-11-19 20:26:14 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 20:26:14 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:14 | D | sum error = [ 61.8132, 65.3608, 69.0857, 72.9907, 77.0850] +24-11-19 20:26:14 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 20:26:14 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:14 | D | sum error = [ 81.3673, 85.8482, 90.5390, 95.4257, 100.5474] +24-11-19 20:26:14 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 20:26:14 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:14 | D | sum error = [ 105.8819, 111.4640, 117.2829, 123.3516, 129.6898] +24-11-19 20:26:14 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 20:26:14 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:14 | D | sum error = [ 136.2836, 143.1558, 150.3000, 157.7282, 165.4541] +24-11-19 20:26:14 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 20:26:14 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:14 | D | sum error = [ 173.4753, 181.8206, 190.4648, 199.4480, 208.7625] +24-11-19 20:26:14 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 20:26:14 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:14 | D | sum error = [ 218.3994, 228.3971, 238.7241, 249.4067, 260.4221] +24-11-19 20:26:14 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 20:26:14 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:14 | D | sum error = [ 271.7965, 283.5389, 295.6541, 308.1387, 320.9904] +24-11-19 20:26:14 | D | best error = [ 4.3669, 4.3669, 4.3669, 4.3669, 4.3669] +24-11-19 20:26:14 | D | + error = [4.3669] +24-11-19 20:26:14 | D | - Calibrating model.layers.12.mlp.gate_proj.weight +24-11-19 20:26:14 | D | + w: sint8 +24-11-19 20:26:14 | D | + x: None +24-11-19 20:26:14 | D | + y: None +24-11-19 20:26:14 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:14 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:14 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:15 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:15 | D | - range ratio = [ 1.0000] +24-11-19 20:26:15 | D | sum error = [ 5.9751] +24-11-19 20:26:15 | D | best error = [ 5.9751] +24-11-19 20:26:16 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:16 | D | sum error = [ 5.9570, 5.9283, 5.9470, 6.0203, 6.1548] +24-11-19 20:26:16 | D | best error = [ 5.5443, 5.3804, 5.2909, 5.2420, 5.2173] +24-11-19 20:26:16 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:16 | D | sum error = [ 6.3066, 6.5198, 6.7917, 7.1286, 7.4830] +24-11-19 20:26:16 | D | best error = [ 5.2051, 5.1999, 5.1980, 5.1975, 5.1973] +24-11-19 20:26:16 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:16 | D | sum error = [ 7.9521, 8.4357, 9.0027, 9.6159, 10.3269] +24-11-19 20:26:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:26:16 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:16 | D | sum error = [ 11.0722, 11.8820, 12.7620, 13.7099, 14.7452] +24-11-19 20:26:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:26:16 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:16 | D | sum error = [ 15.8366, 17.0186, 18.2575, 19.6104, 21.0406] +24-11-19 20:26:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:26:16 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:16 | D | sum error = [ 22.5982, 24.2121, 25.9551, 27.8393, 29.8088] +24-11-19 20:26:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:26:16 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:16 | D | sum error = [ 31.9263, 34.1830, 36.5888, 39.1222, 41.8438] +24-11-19 20:26:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:26:16 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:16 | D | sum error = [ 44.7143, 47.7781, 51.0599, 54.5147, 58.2046] +24-11-19 20:26:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:26:16 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:16 | D | sum error = [ 62.1233, 66.2846, 70.6880, 75.4191, 80.3983] +24-11-19 20:26:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:26:16 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:16 | D | sum error = [ 85.6788, 91.3065, 97.2582, 103.5574, 110.2586] +24-11-19 20:26:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:26:16 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:16 | D | sum error = [ 117.3563, 124.8376, 132.7871, 141.1947, 150.0761] +24-11-19 20:26:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:26:16 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:16 | D | sum error = [ 159.4484, 169.3101, 179.6966, 190.6571, 202.1757] +24-11-19 20:26:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:26:16 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:16 | D | sum error = [ 214.2930, 227.0676, 240.4547, 254.5145, 269.2129] +24-11-19 20:26:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:26:16 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:16 | D | sum error = [ 284.5919, 300.7039, 317.5226, 335.0870, 353.3939] +24-11-19 20:26:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:26:16 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:16 | D | sum error = [ 372.4577, 392.2672, 412.8739, 434.2689, 456.4575] +24-11-19 20:26:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:26:16 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:16 | D | sum error = [ 479.4486, 503.2001, 527.7626, 553.0989, 579.2419] +24-11-19 20:26:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:26:16 | D | + error = [5.1973] +24-11-19 20:26:16 | D | - Calibrating model.layers.12.mlp.down_proj.weight +24-11-19 20:26:16 | D | + w: sint8 +24-11-19 20:26:16 | D | + x: None +24-11-19 20:26:16 | D | + y: None +24-11-19 20:26:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:16 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:16 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:16 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:16 | D | - range ratio = [ 1.0000] +24-11-19 20:26:16 | D | sum error = [ 0.6718] +24-11-19 20:26:16 | D | best error = [ 0.6718] +24-11-19 20:26:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:17 | D | sum error = [ 0.6655, 0.6621, 0.6577, 0.6568, 0.6570] +24-11-19 20:26:17 | D | best error = [ 0.6427, 0.6294, 0.6205, 0.6136, 0.6089] +24-11-19 20:26:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:17 | D | sum error = [ 0.6589, 0.6633, 0.6710, 0.6818, 0.6945] +24-11-19 20:26:17 | D | best error = [ 0.6053, 0.6023, 0.6004, 0.5991, 0.5980] +24-11-19 20:26:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:17 | D | sum error = [ 0.7111, 0.7315, 0.7555, 0.7835, 0.8156] +24-11-19 20:26:17 | D | best error = [ 0.5974, 0.5970, 0.5966, 0.5964, 0.5962] +24-11-19 20:26:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:17 | D | sum error = [ 0.8548, 0.8959, 0.9423, 0.9943, 1.0517] +24-11-19 20:26:17 | D | best error = [ 0.5961, 0.5961, 0.5960, 0.5960, 0.5960] +24-11-19 20:26:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:17 | D | sum error = [ 1.1159, 1.1819, 1.2567, 1.3387, 1.4232] +24-11-19 20:26:17 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 20:26:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:17 | D | sum error = [ 1.5141, 1.6153, 1.7216, 1.8351, 1.9585] +24-11-19 20:26:17 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 20:26:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:17 | D | sum error = [ 2.0885, 2.2276, 2.3749, 2.5319, 2.6980] +24-11-19 20:26:17 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 20:26:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:17 | D | sum error = [ 2.8758, 3.0634, 3.2631, 3.4736, 3.6964] +24-11-19 20:26:17 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 20:26:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:17 | D | sum error = [ 3.9332, 4.1819, 4.4467, 4.7255, 5.0211] +24-11-19 20:26:17 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 20:26:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:17 | D | sum error = [ 5.3304, 5.6588, 6.0037, 6.3687, 6.7518] +24-11-19 20:26:17 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 20:26:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:17 | D | sum error = [ 7.1550, 7.5798, 8.0252, 8.4943, 8.9852] +24-11-19 20:26:17 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 20:26:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:17 | D | sum error = [ 9.5012, 10.0422, 10.6072, 11.2004, 11.8205] +24-11-19 20:26:17 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 20:26:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:17 | D | sum error = [ 12.4705, 13.1505, 13.8622, 14.6032, 15.3779] +24-11-19 20:26:17 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 20:26:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:17 | D | sum error = [ 16.1862, 17.0293, 17.9080, 18.8243, 19.7752] +24-11-19 20:26:17 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 20:26:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:17 | D | sum error = [ 20.7672, 21.7986, 22.8695, 23.9826, 25.1383] +24-11-19 20:26:17 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 20:26:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:17 | D | sum error = [ 26.3361, 27.5772, 28.8617, 30.1929, 31.5685] +24-11-19 20:26:17 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 20:26:17 | D | + error = [0.5960] +24-11-19 20:26:17 | D | - Quantizing model.layers.12.self_attn.q_proj.weight +24-11-19 20:26:18 | D | - Quantizing model.layers.12.self_attn.k_proj.weight +24-11-19 20:26:19 | D | - Quantizing model.layers.12.self_attn.v_proj.weight +24-11-19 20:26:20 | D | - Quantizing model.layers.12.self_attn.o_proj.weight +24-11-19 20:26:21 | D | - Quantizing model.layers.12.mlp.up_proj.weight +24-11-19 20:26:21 | D | - Quantizing model.layers.12.mlp.gate_proj.weight +24-11-19 20:26:22 | D | - Quantizing model.layers.12.mlp.down_proj.weight +24-11-19 20:26:33 | D | - Quantizing layer model.layers.13 +24-11-19 20:26:33 | D | - Calibrating model.layers.13.self_attn.q_proj.weight +24-11-19 20:26:33 | D | + w: sint8 +24-11-19 20:26:33 | D | + x: None +24-11-19 20:26:33 | D | + y: None +24-11-19 20:26:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:26:33 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:33 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:33 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:34 | D | - range ratio = [ 1.0000] +24-11-19 20:26:34 | D | sum error = [ 5.3621] +24-11-19 20:26:34 | D | best error = [ 5.3621] +24-11-19 20:26:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:46 | D | sum error = [ 5.3659, 5.4230, 5.5914, 5.5535, 5.4705] +24-11-19 20:26:46 | D | best error = [ 5.3621, 5.3621, 5.3621, 5.3621, 5.3621] +24-11-19 20:26:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:46 | D | sum error = [ 5.7092, 6.0047, 5.9713, 6.3029, 6.8037] +24-11-19 20:26:46 | D | best error = [ 5.3621, 5.3621, 5.3621, 5.3621, 5.3621] +24-11-19 20:26:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:46 | D | sum error = [ 7.0777, 7.4783, 8.0696, 8.7927, 9.4362] +24-11-19 20:26:46 | D | best error = [ 5.3621, 5.3621, 5.3621, 5.3621, 5.3621] +24-11-19 20:26:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:46 | D | sum error = [ 9.9617, 10.6384, 11.5387, 12.4112, 13.2163] +24-11-19 20:26:46 | D | best error = [ 5.3621, 5.3621, 5.3621, 5.3621, 5.3621] +24-11-19 20:26:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:46 | D | sum error = [ 14.5838, 15.4080, 16.9960, 18.2154, 19.6564] +24-11-19 20:26:46 | D | best error = [ 5.3621, 5.3621, 5.3621, 5.3621, 5.3621] +24-11-19 20:26:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:46 | D | sum error = [ 21.2087, 22.7960, 24.7356, 26.5390, 28.5711] +24-11-19 20:26:46 | D | best error = [ 5.3621, 5.3621, 5.3621, 5.3621, 5.3621] +24-11-19 20:26:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:46 | D | sum error = [ 30.8071, 33.3167, 35.9143, 38.5756, 41.5057] +24-11-19 20:26:46 | D | best error = [ 5.3621, 5.3621, 5.3621, 5.3621, 5.3621] +24-11-19 20:26:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:46 | D | sum error = [ 44.4663, 47.6579, 51.2128, 54.6665, 58.7847] +24-11-19 20:26:46 | D | best error = [ 5.3621, 5.3621, 5.3621, 5.3621, 5.3621] +24-11-19 20:26:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:46 | D | sum error = [ 62.6275, 67.0564, 71.7270, 76.5305, 81.6883] +24-11-19 20:26:46 | D | best error = [ 5.3621, 5.3621, 5.3621, 5.3621, 5.3621] +24-11-19 20:26:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:46 | D | sum error = [ 87.1117, 92.7468, 98.8385, 104.9812, 111.6609] +24-11-19 20:26:46 | D | best error = [ 5.3621, 5.3621, 5.3621, 5.3621, 5.3621] +24-11-19 20:26:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:46 | D | sum error = [ 118.4883, 125.7981, 133.8567, 141.9402, 150.5643] +24-11-19 20:26:46 | D | best error = [ 5.3621, 5.3621, 5.3621, 5.3621, 5.3621] +24-11-19 20:26:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:46 | D | sum error = [ 159.4000, 169.1239, 179.0246, 189.4160, 200.5353] +24-11-19 20:26:46 | D | best error = [ 5.3621, 5.3621, 5.3621, 5.3621, 5.3621] +24-11-19 20:26:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:46 | D | sum error = [ 211.8847, 223.8639, 236.3661, 249.4012, 262.9357] +24-11-19 20:26:46 | D | best error = [ 5.3621, 5.3621, 5.3621, 5.3621, 5.3621] +24-11-19 20:26:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:46 | D | sum error = [ 277.1683, 291.8407, 307.2405, 323.1931, 339.6313] +24-11-19 20:26:46 | D | best error = [ 5.3621, 5.3621, 5.3621, 5.3621, 5.3621] +24-11-19 20:26:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:46 | D | sum error = [ 356.8230, 374.4769, 392.7107, 411.5002, 430.7761] +24-11-19 20:26:46 | D | best error = [ 5.3621, 5.3621, 5.3621, 5.3621, 5.3621] +24-11-19 20:26:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:46 | D | sum error = [ 450.5660, 470.9204, 491.5884, 512.5781, 533.9415] +24-11-19 20:26:46 | D | best error = [ 5.3621, 5.3621, 5.3621, 5.3621, 5.3621] +24-11-19 20:26:46 | D | + error = [5.3621] +24-11-19 20:26:46 | D | - Calibrating model.layers.13.self_attn.k_proj.weight +24-11-19 20:26:46 | D | + w: sint8 +24-11-19 20:26:46 | D | + x: None +24-11-19 20:26:46 | D | + y: None +24-11-19 20:26:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:26:46 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:46 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:47 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:47 | D | - range ratio = [ 1.0000] +24-11-19 20:26:47 | D | sum error = [ 4.1818] +24-11-19 20:26:47 | D | best error = [ 4.1818] +24-11-19 20:26:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:59 | D | sum error = [ 4.1204, 3.9515, 4.2675, 4.1271, 4.3418] +24-11-19 20:26:59 | D | best error = [ 4.1204, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:26:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:59 | D | sum error = [ 4.4489, 4.6692, 4.6450, 4.9967, 5.0086] +24-11-19 20:26:59 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:26:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:59 | D | sum error = [ 5.5939, 5.8433, 5.9725, 6.3900, 7.1389] +24-11-19 20:26:59 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:26:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:59 | D | sum error = [ 7.4994, 8.2561, 8.8966, 9.2972, 10.1513] +24-11-19 20:26:59 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:26:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:59 | D | sum error = [ 11.0609, 11.8743, 13.2267, 14.0749, 15.2024] +24-11-19 20:26:59 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:26:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:59 | D | sum error = [ 16.4320, 17.6661, 19.0647, 20.8875, 23.1473] +24-11-19 20:26:59 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:26:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:59 | D | sum error = [ 24.0002, 26.6369, 28.6093, 30.8677, 33.9206] +24-11-19 20:26:59 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:26:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:59 | D | sum error = [ 36.3308, 39.9175, 43.3128, 46.7302, 50.2836] +24-11-19 20:26:59 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:26:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:59 | D | sum error = [ 54.2968, 57.6950, 62.6373, 67.4423, 72.8688] +24-11-19 20:26:59 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:26:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:59 | D | sum error = [ 77.9508, 84.3207, 90.0463, 96.6408, 103.9439] +24-11-19 20:26:59 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:26:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:59 | D | sum error = [ 111.1491, 119.1494, 127.2214, 135.9887, 144.7951] +24-11-19 20:26:59 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:26:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:59 | D | sum error = [ 154.3923, 163.8160, 173.9885, 184.8579, 195.7206] +24-11-19 20:26:59 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:26:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:59 | D | sum error = [ 207.6380, 219.3578, 232.0532, 244.4275, 257.1112] +24-11-19 20:26:59 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:26:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:59 | D | sum error = [ 270.7606, 284.6419, 298.8448, 313.8114, 329.0659] +24-11-19 20:26:59 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:26:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:59 | D | sum error = [ 345.3808, 362.0053, 379.2553, 397.1921, 415.8377] +24-11-19 20:26:59 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:26:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:59 | D | sum error = [ 434.8427, 454.6100, 475.3796, 496.3762, 518.1031] +24-11-19 20:26:59 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:26:59 | D | + error = [3.9515] +24-11-19 20:26:59 | D | - Calibrating model.layers.13.self_attn.v_proj.weight +24-11-19 20:26:59 | D | + w: sint8 +24-11-19 20:26:59 | D | + x: None +24-11-19 20:26:59 | D | + y: None +24-11-19 20:26:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:59 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:59 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:59 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:59 | D | - range ratio = [ 1.0000] +24-11-19 20:26:59 | D | sum error = [ 1.5428] +24-11-19 20:26:59 | D | best error = [ 1.5428] +24-11-19 20:26:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:59 | D | sum error = [ 1.5348, 1.5291, 1.5368, 1.5638, 1.5953] +24-11-19 20:26:59 | D | best error = [ 1.4091, 1.3641, 1.3423, 1.3298, 1.3237] +24-11-19 20:26:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:59 | D | sum error = [ 1.6296, 1.6694, 1.7426, 1.8536, 1.9289] +24-11-19 20:26:59 | D | best error = [ 1.3197, 1.3180, 1.3177, 1.3176, 1.3176] +24-11-19 20:26:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:59 | D | sum error = [ 2.0451, 2.1628, 2.3128, 2.4614, 2.6433] +24-11-19 20:26:59 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:26:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:59 | D | sum error = [ 2.8115, 3.0145, 3.2200, 3.4621, 3.6949] +24-11-19 20:26:59 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:26:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:59 | D | sum error = [ 3.9479, 4.2212, 4.5172, 4.8290, 5.1522] +24-11-19 20:26:59 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:26:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:59 | D | sum error = [ 5.4972, 5.8584, 6.2740, 6.6816, 7.1183] +24-11-19 20:26:59 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:26:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:59 | D | sum error = [ 7.5799, 8.0737, 8.6016, 9.1444, 9.7151] +24-11-19 20:26:59 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:26:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:59 | D | sum error = [ 10.3166, 10.9586, 11.6357, 12.3359, 13.0786] +24-11-19 20:26:59 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:26:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:59 | D | sum error = [ 13.8629, 14.6680, 15.5411, 16.4330, 17.3832] +24-11-19 20:26:59 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:26:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:59 | D | sum error = [ 18.3756, 19.4149, 20.4995, 21.6437, 22.8291] +24-11-19 20:26:59 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:26:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:59 | D | sum error = [ 24.0746, 25.3791, 26.7425, 28.1611, 29.6330] +24-11-19 20:26:59 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:26:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:59 | D | sum error = [ 31.1733, 32.7543, 34.4260, 36.1650, 37.9659] +24-11-19 20:26:59 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:26:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:59 | D | sum error = [ 39.8515, 41.8059, 43.8316, 45.9401, 48.1339] +24-11-19 20:26:59 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:26:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:59 | D | sum error = [ 50.3989, 52.7430, 55.1722, 57.6815, 60.2810] +24-11-19 20:26:59 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:26:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:59 | D | sum error = [ 62.9656, 65.7384, 68.6042, 71.5639, 74.6214] +24-11-19 20:26:59 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:26:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:59 | D | sum error = [ 77.7620, 81.0097, 84.3465, 87.7823, 91.3218] +24-11-19 20:26:59 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:26:59 | D | + error = [1.3176] +24-11-19 20:26:59 | D | - Calibrating model.layers.13.self_attn.o_proj.weight +24-11-19 20:26:59 | D | + w: sint8 +24-11-19 20:26:59 | D | + x: None +24-11-19 20:26:59 | D | + y: None +24-11-19 20:26:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:59 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:59 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:59 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:59 | D | - range ratio = [ 1.0000] +24-11-19 20:26:59 | D | sum error = [ 0.6587] +24-11-19 20:26:59 | D | best error = [ 0.6587] +24-11-19 20:27:00 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:00 | D | sum error = [ 0.6568, 0.6513, 0.6565, 0.6617, 0.6733] +24-11-19 20:27:00 | D | best error = [ 0.5910, 0.5594, 0.5430, 0.5318, 0.5247] +24-11-19 20:27:00 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:00 | D | sum error = [ 0.6896, 0.7038, 0.7347, 0.7634, 0.7994] +24-11-19 20:27:00 | D | best error = [ 0.5197, 0.5165, 0.5143, 0.5128, 0.5119] +24-11-19 20:27:00 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:00 | D | sum error = [ 0.8402, 0.8836, 0.9337, 0.9909, 1.0524] +24-11-19 20:27:00 | D | best error = [ 0.5113, 0.5110, 0.5107, 0.5106, 0.5105] +24-11-19 20:27:00 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:00 | D | sum error = [ 1.1176, 1.1876, 1.2632, 1.3457, 1.4343] +24-11-19 20:27:00 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:27:00 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:00 | D | sum error = [ 1.5245, 1.6275, 1.7294, 1.8398, 1.9526] +24-11-19 20:27:00 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:27:00 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:00 | D | sum error = [ 2.0767, 2.2060, 2.3415, 2.4837, 2.6290] +24-11-19 20:27:00 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:27:00 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:00 | D | sum error = [ 2.7884, 2.9507, 3.1277, 3.3049, 3.4925] +24-11-19 20:27:00 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:27:00 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:00 | D | sum error = [ 3.6902, 3.8972, 4.1131, 4.3373, 4.5714] +24-11-19 20:27:00 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:27:00 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:00 | D | sum error = [ 4.8160, 5.0716, 5.3360, 5.6189, 5.9092] +24-11-19 20:27:00 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:27:00 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:00 | D | sum error = [ 6.2090, 6.5233, 6.8497, 7.1830, 7.5348] +24-11-19 20:27:00 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:27:00 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:00 | D | sum error = [ 7.8947, 8.2694, 8.6547, 9.0563, 9.4675] +24-11-19 20:27:00 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:27:00 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:00 | D | sum error = [ 9.8937, 10.3314, 10.7801, 11.2478, 11.7240] +24-11-19 20:27:00 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:27:00 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:00 | D | sum error = [ 12.2150, 12.7220, 13.2423, 13.7801, 14.3275] +24-11-19 20:27:00 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:27:00 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:00 | D | sum error = [ 14.8906, 15.4726, 16.0652, 16.6783, 17.3042] +24-11-19 20:27:00 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:27:00 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:00 | D | sum error = [ 17.9500, 18.6115, 19.2876, 19.9886, 20.7097] +24-11-19 20:27:00 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:27:00 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:00 | D | sum error = [ 21.4504, 22.2120, 22.9944, 23.8020, 24.6377] +24-11-19 20:27:00 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:27:00 | D | + error = [0.5104] +24-11-19 20:27:00 | D | - Calibrating model.layers.13.mlp.up_proj.weight +24-11-19 20:27:00 | D | + w: sint8 +24-11-19 20:27:00 | D | + x: None +24-11-19 20:27:00 | D | + y: None +24-11-19 20:27:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:00 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:27:00 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:27:00 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:27:00 | D | - range ratio = [ 1.0000] +24-11-19 20:27:00 | D | sum error = [ 5.2105] +24-11-19 20:27:00 | D | best error = [ 5.2105] +24-11-19 20:27:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:01 | D | sum error = [ 5.1757, 5.1702, 5.2003, 5.2598, 5.3391] +24-11-19 20:27:01 | D | best error = [ 4.8357, 4.6922, 4.6135, 4.5708, 4.5483] +24-11-19 20:27:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:01 | D | sum error = [ 5.4805, 5.6725, 5.9001, 6.1787, 6.5039] +24-11-19 20:27:01 | D | best error = [ 4.5360, 4.5308, 4.5291, 4.5284, 4.5282] +24-11-19 20:27:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:01 | D | sum error = [ 6.8674, 7.3068, 7.7920, 8.3067, 8.8931] +24-11-19 20:27:01 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:27:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:01 | D | sum error = [ 9.4959, 10.1876, 10.9178, 11.6992, 12.5266] +24-11-19 20:27:01 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:27:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:01 | D | sum error = [ 13.4339, 14.3895, 15.4122, 16.5008, 17.6427] +24-11-19 20:27:01 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:27:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:01 | D | sum error = [ 18.8567, 20.1544, 21.5269, 22.9634, 24.4982] +24-11-19 20:27:01 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:27:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:01 | D | sum error = [ 26.0932, 27.8181, 29.6190, 31.4964, 33.5095] +24-11-19 20:27:01 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:27:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:01 | D | sum error = [ 35.6123, 37.8440, 40.1723, 42.6393, 45.2258] +24-11-19 20:27:01 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:27:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:01 | D | sum error = [ 47.9568, 50.8043, 53.8130, 56.9849, 60.2816] +24-11-19 20:27:01 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:27:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:01 | D | sum error = [ 63.7638, 67.4114, 71.2422, 75.2470, 79.4450] +24-11-19 20:27:01 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:27:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:01 | D | sum error = [ 83.8210, 88.4230, 93.2232, 98.2387, 103.4802] +24-11-19 20:27:01 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:27:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:01 | D | sum error = [ 108.9469, 114.6507, 120.6148, 126.8275, 133.3036] +24-11-19 20:27:01 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:27:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:01 | D | sum error = [ 140.0330, 147.0583, 154.3513, 161.9406, 169.8338] +24-11-19 20:27:01 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:27:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:01 | D | sum error = [ 178.0243, 186.5379, 195.3652, 204.5088, 213.9909] +24-11-19 20:27:01 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:27:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:01 | D | sum error = [ 223.8052, 233.9655, 244.4666, 255.3170, 266.5182] +24-11-19 20:27:01 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:27:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:01 | D | sum error = [ 278.0783, 290.0037, 302.3070, 314.9924, 328.0320] +24-11-19 20:27:01 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:27:01 | D | + error = [4.5282] +24-11-19 20:27:02 | D | - Calibrating model.layers.13.mlp.gate_proj.weight +24-11-19 20:27:02 | D | + w: sint8 +24-11-19 20:27:02 | D | + x: None +24-11-19 20:27:02 | D | + y: None +24-11-19 20:27:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:02 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:27:02 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:27:02 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:27:02 | D | - range ratio = [ 1.0000] +24-11-19 20:27:02 | D | sum error = [ 6.2255] +24-11-19 20:27:02 | D | best error = [ 6.2255] +24-11-19 20:27:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:03 | D | sum error = [ 6.1719, 6.1685, 6.2012, 6.2660, 6.3767] +24-11-19 20:27:03 | D | best error = [ 5.7638, 5.5892, 5.4983, 5.4460, 5.4176] +24-11-19 20:27:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:03 | D | sum error = [ 6.5522, 6.7686, 7.0497, 7.3911, 7.7923] +24-11-19 20:27:03 | D | best error = [ 5.4037, 5.3979, 5.3954, 5.3949, 5.3947] +24-11-19 20:27:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:03 | D | sum error = [ 8.2573, 8.7633, 9.3524, 10.0052, 10.7002] +24-11-19 20:27:03 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:27:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:03 | D | sum error = [ 11.4826, 12.3218, 13.2170, 14.2103, 15.2746] +24-11-19 20:27:03 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:27:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:03 | D | sum error = [ 16.3999, 17.5902, 18.8912, 20.2936, 21.7733] +24-11-19 20:27:03 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:27:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:03 | D | sum error = [ 23.3561, 25.0215, 26.8342, 28.7316, 30.7816] +24-11-19 20:27:03 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:27:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:03 | D | sum error = [ 32.9636, 35.2703, 37.7541, 40.3759, 43.1592] +24-11-19 20:27:03 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:27:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:03 | D | sum error = [ 46.1525, 49.3268, 52.7176, 56.3079, 60.1297] +24-11-19 20:27:03 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:27:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:03 | D | sum error = [ 64.2196, 68.5708, 73.1545, 78.0798, 83.2821] +24-11-19 20:27:03 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:27:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:03 | D | sum error = [ 88.8150, 94.7357, 100.9635, 107.6052, 114.6459] +24-11-19 20:27:03 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:27:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:03 | D | sum error = [ 122.0923, 129.9973, 138.3401, 147.1862, 156.5566] +24-11-19 20:27:03 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:27:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:03 | D | sum error = [ 166.4352, 176.8694, 187.8699, 199.4851, 211.7035] +24-11-19 20:27:03 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:27:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:03 | D | sum error = [ 224.5573, 238.0966, 252.3130, 267.2362, 282.8811] +24-11-19 20:27:03 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:27:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:03 | D | sum error = [ 299.2767, 316.4102, 334.3207, 352.9903, 372.4684] +24-11-19 20:27:03 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:27:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:03 | D | sum error = [ 392.7601, 413.8553, 435.8206, 458.5857, 482.2091] +24-11-19 20:27:03 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:27:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:03 | D | sum error = [ 506.6625, 531.9833, 558.1099, 585.0546, 612.8537] +24-11-19 20:27:03 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:27:03 | D | + error = [5.3946] +24-11-19 20:27:03 | D | - Calibrating model.layers.13.mlp.down_proj.weight +24-11-19 20:27:03 | D | + w: sint8 +24-11-19 20:27:03 | D | + x: None +24-11-19 20:27:03 | D | + y: None +24-11-19 20:27:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:03 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:27:03 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:27:03 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:27:03 | D | - range ratio = [ 1.0000] +24-11-19 20:27:03 | D | sum error = [ 0.7254] +24-11-19 20:27:03 | D | best error = [ 0.7254] +24-11-19 20:27:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:05 | D | sum error = [ 0.7192, 0.7146, 0.7102, 0.7098, 0.7082] +24-11-19 20:27:05 | D | best error = [ 0.6908, 0.6752, 0.6646, 0.6576, 0.6520] +24-11-19 20:27:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:05 | D | sum error = [ 0.7093, 0.7155, 0.7196, 0.7296, 0.7448] +24-11-19 20:27:05 | D | best error = [ 0.6481, 0.6447, 0.6422, 0.6406, 0.6394] +24-11-19 20:27:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:05 | D | sum error = [ 0.7647, 0.7823, 0.8085, 0.8380, 0.8746] +24-11-19 20:27:05 | D | best error = [ 0.6386, 0.6381, 0.6378, 0.6374, 0.6372] +24-11-19 20:27:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:05 | D | sum error = [ 0.9123, 0.9562, 1.0070, 1.0630, 1.1251] +24-11-19 20:27:05 | D | best error = [ 0.6371, 0.6370, 0.6370, 0.6370, 0.6369] +24-11-19 20:27:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:05 | D | sum error = [ 1.1921, 1.2647, 1.3460, 1.4341, 1.5274] +24-11-19 20:27:05 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 20:27:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:05 | D | sum error = [ 1.6281, 1.7397, 1.8550, 1.9804, 2.1134] +24-11-19 20:27:05 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 20:27:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:05 | D | sum error = [ 2.2568, 2.4085, 2.5715, 2.7445, 2.9283] +24-11-19 20:27:05 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 20:27:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:05 | D | sum error = [ 3.1222, 3.3280, 3.5468, 3.7791, 4.0240] +24-11-19 20:27:05 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 20:27:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:05 | D | sum error = [ 4.2826, 4.5580, 4.8473, 5.1517, 5.4752] +24-11-19 20:27:05 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 20:27:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:05 | D | sum error = [ 5.8154, 6.1744, 6.5526, 6.9505, 7.3688] +24-11-19 20:27:05 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 20:27:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:05 | D | sum error = [ 7.8083, 8.2707, 8.7601, 9.2692, 9.8057] +24-11-19 20:27:05 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 20:27:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:05 | D | sum error = [ 10.3667, 10.9554, 11.5725, 12.2183, 12.8948] +24-11-19 20:27:05 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 20:27:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:05 | D | sum error = [ 13.6020, 14.3385, 15.1090, 15.9132, 16.7517] +24-11-19 20:27:05 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 20:27:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:05 | D | sum error = [ 17.6263, 18.5390, 19.4881, 20.4774, 21.5060] +24-11-19 20:27:05 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 20:27:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:05 | D | sum error = [ 22.5745, 23.6865, 24.8398, 26.0346, 27.2734] +24-11-19 20:27:05 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 20:27:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:05 | D | sum error = [ 28.5545, 29.8808, 31.2531, 32.6709, 34.1346] +24-11-19 20:27:05 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 20:27:05 | D | + error = [0.6369] +24-11-19 20:27:05 | D | - Quantizing model.layers.13.self_attn.q_proj.weight +24-11-19 20:27:05 | D | - Quantizing model.layers.13.self_attn.k_proj.weight +24-11-19 20:27:06 | D | - Quantizing model.layers.13.self_attn.v_proj.weight +24-11-19 20:27:07 | D | - Quantizing model.layers.13.self_attn.o_proj.weight +24-11-19 20:27:08 | D | - Quantizing model.layers.13.mlp.up_proj.weight +24-11-19 20:27:09 | D | - Quantizing model.layers.13.mlp.gate_proj.weight +24-11-19 20:27:10 | D | - Quantizing model.layers.13.mlp.down_proj.weight +24-11-19 20:27:19 | D | - Quantizing layer model.layers.14 +24-11-19 20:27:19 | D | - Calibrating model.layers.14.self_attn.q_proj.weight +24-11-19 20:27:19 | D | + w: sint8 +24-11-19 20:27:19 | D | + x: None +24-11-19 20:27:19 | D | + y: None +24-11-19 20:27:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:27:19 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:27:19 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:27:20 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:27:20 | D | - range ratio = [ 1.0000] +24-11-19 20:27:20 | D | sum error = [ 5.5664] +24-11-19 20:27:20 | D | best error = [ 5.5664] +24-11-19 20:27:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:33 | D | sum error = [ 5.3943, 5.3932, 5.5596, 5.5181, 5.6141] +24-11-19 20:27:33 | D | best error = [ 5.3943, 5.3932, 5.3932, 5.3932, 5.3932] +24-11-19 20:27:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:33 | D | sum error = [ 5.9147, 5.9821, 6.2158, 6.5814, 6.9710] +24-11-19 20:27:33 | D | best error = [ 5.3932, 5.3932, 5.3932, 5.3932, 5.3932] +24-11-19 20:27:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:33 | D | sum error = [ 7.3039, 7.6795, 8.3421, 9.0794, 9.8158] +24-11-19 20:27:33 | D | best error = [ 5.3932, 5.3932, 5.3932, 5.3932, 5.3932] +24-11-19 20:27:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:33 | D | sum error = [ 10.1555, 10.9580, 11.9787, 12.7548, 13.8673] +24-11-19 20:27:33 | D | best error = [ 5.3932, 5.3932, 5.3932, 5.3932, 5.3932] +24-11-19 20:27:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:33 | D | sum error = [ 15.0062, 16.4133, 17.7837, 19.1014, 20.5580] +24-11-19 20:27:33 | D | best error = [ 5.3932, 5.3932, 5.3932, 5.3932, 5.3932] +24-11-19 20:27:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:33 | D | sum error = [ 22.1798, 24.0030, 25.5628, 27.5657, 30.0198] +24-11-19 20:27:33 | D | best error = [ 5.3932, 5.3932, 5.3932, 5.3932, 5.3932] +24-11-19 20:27:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:33 | D | sum error = [ 32.3494, 34.7001, 37.1057, 39.9885, 42.6508] +24-11-19 20:27:33 | D | best error = [ 5.3932, 5.3932, 5.3932, 5.3932, 5.3932] +24-11-19 20:27:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:33 | D | sum error = [ 45.6195, 49.0312, 52.2471, 55.9951, 59.6410] +24-11-19 20:27:33 | D | best error = [ 5.3932, 5.3932, 5.3932, 5.3932, 5.3932] +24-11-19 20:27:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:33 | D | sum error = [ 63.6679, 68.1497, 72.4097, 77.1966, 82.0669] +24-11-19 20:27:33 | D | best error = [ 5.3932, 5.3932, 5.3932, 5.3932, 5.3932] +24-11-19 20:27:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:33 | D | sum error = [ 87.1842, 92.3905, 97.9868, 103.7210, 109.9031] +24-11-19 20:27:33 | D | best error = [ 5.3932, 5.3932, 5.3932, 5.3932, 5.3932] +24-11-19 20:27:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:33 | D | sum error = [ 116.0415, 122.8492, 129.6671, 136.9231, 144.4015] +24-11-19 20:27:33 | D | best error = [ 5.3932, 5.3932, 5.3932, 5.3932, 5.3932] +24-11-19 20:27:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:33 | D | sum error = [ 152.1920, 160.3270, 169.0115, 178.0920, 187.8591] +24-11-19 20:27:33 | D | best error = [ 5.3932, 5.3932, 5.3932, 5.3932, 5.3932] +24-11-19 20:27:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:33 | D | sum error = [ 198.1988, 208.9759, 220.5287, 232.5326, 245.3065] +24-11-19 20:27:33 | D | best error = [ 5.3932, 5.3932, 5.3932, 5.3932, 5.3932] +24-11-19 20:27:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:33 | D | sum error = [ 258.7609, 273.1622, 288.1917, 304.1663, 321.2917] +24-11-19 20:27:33 | D | best error = [ 5.3932, 5.3932, 5.3932, 5.3932, 5.3932] +24-11-19 20:27:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:33 | D | sum error = [ 338.9801, 358.0341, 377.9591, 399.0753, 421.2024] +24-11-19 20:27:33 | D | best error = [ 5.3932, 5.3932, 5.3932, 5.3932, 5.3932] +24-11-19 20:27:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:33 | D | sum error = [ 444.3794, 468.7012, 494.2834, 520.9950, 548.7534] +24-11-19 20:27:33 | D | best error = [ 5.3932, 5.3932, 5.3932, 5.3932, 5.3932] +24-11-19 20:27:33 | D | + error = [5.3932] +24-11-19 20:27:34 | D | - Calibrating model.layers.14.self_attn.k_proj.weight +24-11-19 20:27:34 | D | + w: sint8 +24-11-19 20:27:34 | D | + x: None +24-11-19 20:27:34 | D | + y: None +24-11-19 20:27:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:27:34 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:27:34 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:27:34 | D | + finished calculating the original outputs, ram usage: 13.3 +24-11-19 20:27:34 | D | - range ratio = [ 1.0000] +24-11-19 20:27:34 | D | sum error = [ 4.4193] +24-11-19 20:27:34 | D | best error = [ 4.4193] +24-11-19 20:27:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:46 | D | sum error = [ 4.3569, 4.3738, 4.7639, 4.4363, 5.1150] +24-11-19 20:27:46 | D | best error = [ 4.3569, 4.3569, 4.3569, 4.3569, 4.3569] +24-11-19 20:27:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:46 | D | sum error = [ 4.8831, 4.5684, 5.6180, 5.2602, 5.5970] +24-11-19 20:27:46 | D | best error = [ 4.3569, 4.3569, 4.3569, 4.3569, 4.3569] +24-11-19 20:27:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:46 | D | sum error = [ 6.1327, 6.4971, 6.9282, 8.7750, 8.3298] +24-11-19 20:27:46 | D | best error = [ 4.3569, 4.3569, 4.3569, 4.3569, 4.3569] +24-11-19 20:27:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:46 | D | sum error = [ 8.4264, 9.7472, 10.1513, 11.7598, 12.0064] +24-11-19 20:27:46 | D | best error = [ 4.3569, 4.3569, 4.3569, 4.3569, 4.3569] +24-11-19 20:27:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:46 | D | sum error = [ 13.8648, 14.4355, 15.9422, 17.0992, 18.3722] +24-11-19 20:27:46 | D | best error = [ 4.3569, 4.3569, 4.3569, 4.3569, 4.3569] +24-11-19 20:27:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:46 | D | sum error = [ 19.1217, 20.7688, 23.0781, 25.2097, 26.2995] +24-11-19 20:27:46 | D | best error = [ 4.3569, 4.3569, 4.3569, 4.3569, 4.3569] +24-11-19 20:27:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:46 | D | sum error = [ 28.9320, 31.4072, 33.6032, 36.3906, 39.3729] +24-11-19 20:27:46 | D | best error = [ 4.3569, 4.3569, 4.3569, 4.3569, 4.3569] +24-11-19 20:27:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:46 | D | sum error = [ 42.3816, 44.6823, 48.7146, 51.5843, 55.5852] +24-11-19 20:27:46 | D | best error = [ 4.3569, 4.3569, 4.3569, 4.3569, 4.3569] +24-11-19 20:27:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:46 | D | sum error = [ 59.4662, 64.1725, 68.8706, 73.4824, 79.3069] +24-11-19 20:27:46 | D | best error = [ 4.3569, 4.3569, 4.3569, 4.3569, 4.3569] +24-11-19 20:27:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:46 | D | sum error = [ 84.6238, 90.3949, 96.2502, 102.6598, 109.4148] +24-11-19 20:27:46 | D | best error = [ 4.3569, 4.3569, 4.3569, 4.3569, 4.3569] +24-11-19 20:27:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:46 | D | sum error = [ 116.5599, 124.0456, 132.0297, 139.9627, 148.7217] +24-11-19 20:27:46 | D | best error = [ 4.3569, 4.3569, 4.3569, 4.3569, 4.3569] +24-11-19 20:27:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:46 | D | sum error = [ 158.2912, 167.9482, 178.3284, 189.4070, 201.0198] +24-11-19 20:27:46 | D | best error = [ 4.3569, 4.3569, 4.3569, 4.3569, 4.3569] +24-11-19 20:27:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:46 | D | sum error = [ 212.6940, 224.7938, 237.1421, 250.4937, 263.5100] +24-11-19 20:27:46 | D | best error = [ 4.3569, 4.3569, 4.3569, 4.3569, 4.3569] +24-11-19 20:27:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:46 | D | sum error = [ 277.8739, 293.2771, 308.4141, 325.0069, 341.9988] +24-11-19 20:27:46 | D | best error = [ 4.3569, 4.3569, 4.3569, 4.3569, 4.3569] +24-11-19 20:27:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:46 | D | sum error = [ 358.7814, 377.5065, 396.5372, 416.7070, 438.0069] +24-11-19 20:27:46 | D | best error = [ 4.3569, 4.3569, 4.3569, 4.3569, 4.3569] +24-11-19 20:27:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:46 | D | sum error = [ 459.4006, 482.6479, 506.5668, 531.4396, 557.7500] +24-11-19 20:27:46 | D | best error = [ 4.3569, 4.3569, 4.3569, 4.3569, 4.3569] +24-11-19 20:27:46 | D | + error = [4.3569] +24-11-19 20:27:46 | D | - Calibrating model.layers.14.self_attn.v_proj.weight +24-11-19 20:27:46 | D | + w: sint8 +24-11-19 20:27:46 | D | + x: None +24-11-19 20:27:46 | D | + y: None +24-11-19 20:27:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:46 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:27:46 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:27:46 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:27:46 | D | - range ratio = [ 1.0000] +24-11-19 20:27:46 | D | sum error = [ 1.4942] +24-11-19 20:27:46 | D | best error = [ 1.4942] +24-11-19 20:27:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:47 | D | sum error = [ 1.4890, 1.4768, 1.4870, 1.5102, 1.5456] +24-11-19 20:27:47 | D | best error = [ 1.3701, 1.3223, 1.3004, 1.2852, 1.2788] +24-11-19 20:27:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:47 | D | sum error = [ 1.5667, 1.6263, 1.6986, 1.7783, 1.8658] +24-11-19 20:27:47 | D | best error = [ 1.2744, 1.2731, 1.2724, 1.2723, 1.2722] +24-11-19 20:27:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:47 | D | sum error = [ 1.9870, 2.1071, 2.2512, 2.3752, 2.5734] +24-11-19 20:27:47 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:27:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:47 | D | sum error = [ 2.7605, 2.9326, 3.1610, 3.4007, 3.6390] +24-11-19 20:27:47 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:27:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:47 | D | sum error = [ 3.9002, 4.1944, 4.4885, 4.8095, 5.1387] +24-11-19 20:27:47 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:27:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:47 | D | sum error = [ 5.4927, 5.8659, 6.2688, 6.6846, 7.1314] +24-11-19 20:27:47 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:27:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:47 | D | sum error = [ 7.6036, 8.0844, 8.6038, 9.1471, 9.7344] +24-11-19 20:27:47 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:27:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:47 | D | sum error = [ 10.3430, 10.9814, 11.6504, 12.3596, 13.1074] +24-11-19 20:27:47 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:27:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:47 | D | sum error = [ 13.8900, 14.7083, 15.5776, 16.4892, 17.4256] +24-11-19 20:27:47 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:27:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:47 | D | sum error = [ 18.4275, 19.4653, 20.5696, 21.7079, 22.9093] +24-11-19 20:27:47 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:27:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:47 | D | sum error = [ 24.1585, 25.4725, 26.8391, 28.2720, 29.7671] +24-11-19 20:27:47 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:27:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:47 | D | sum error = [ 31.3250, 32.9410, 34.6352, 36.3937, 38.2185] +24-11-19 20:27:47 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:27:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:47 | D | sum error = [ 40.1054, 42.0849, 44.1341, 46.2825, 48.5122] +24-11-19 20:27:47 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:27:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:47 | D | sum error = [ 50.8352, 53.2304, 55.7146, 58.2850, 60.9375] +24-11-19 20:27:47 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:27:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:47 | D | sum error = [ 63.6859, 66.5355, 69.4739, 72.5210, 75.6748] +24-11-19 20:27:47 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:27:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:47 | D | sum error = [ 78.9121, 82.2576, 85.6910, 89.2244, 92.8599] +24-11-19 20:27:47 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:27:47 | D | + error = [1.2722] +24-11-19 20:27:47 | D | - Calibrating model.layers.14.self_attn.o_proj.weight +24-11-19 20:27:47 | D | + w: sint8 +24-11-19 20:27:47 | D | + x: None +24-11-19 20:27:47 | D | + y: None +24-11-19 20:27:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:47 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:27:47 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:27:47 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:27:47 | D | - range ratio = [ 1.0000] +24-11-19 20:27:47 | D | sum error = [ 0.6814] +24-11-19 20:27:47 | D | best error = [ 0.6814] +24-11-19 20:27:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:47 | D | sum error = [ 0.6728, 0.6722, 0.6699, 0.6736, 0.6789] +24-11-19 20:27:47 | D | best error = [ 0.6234, 0.5987, 0.5839, 0.5745, 0.5674] +24-11-19 20:27:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:47 | D | sum error = [ 0.6881, 0.7001, 0.7138, 0.7333, 0.7589] +24-11-19 20:27:47 | D | best error = [ 0.5631, 0.5598, 0.5578, 0.5566, 0.5558] +24-11-19 20:27:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:47 | D | sum error = [ 0.7888, 0.8182, 0.8608, 0.9040, 0.9496] +24-11-19 20:27:47 | D | best error = [ 0.5554, 0.5550, 0.5548, 0.5547, 0.5547] +24-11-19 20:27:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:47 | D | sum error = [ 0.9995, 1.0547, 1.1155, 1.1833, 1.2500] +24-11-19 20:27:47 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:27:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:47 | D | sum error = [ 1.3238, 1.4026, 1.4869, 1.5778, 1.6706] +24-11-19 20:27:47 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:27:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:47 | D | sum error = [ 1.7684, 1.8765, 1.9895, 2.1053, 2.2273] +24-11-19 20:27:47 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:27:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:47 | D | sum error = [ 2.3597, 2.4979, 2.6417, 2.7924, 2.9504] +24-11-19 20:27:47 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:27:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:47 | D | sum error = [ 3.1171, 3.2939, 3.4802, 3.6715, 3.8763] +24-11-19 20:27:47 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:27:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:47 | D | sum error = [ 4.0928, 4.3130, 4.5476, 4.7929, 5.0461] +24-11-19 20:27:47 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:27:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:47 | D | sum error = [ 5.3169, 5.5950, 5.8886, 6.1930, 6.5097] +24-11-19 20:27:47 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:27:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:47 | D | sum error = [ 6.8452, 7.1878, 7.5482, 7.9235, 8.3164] +24-11-19 20:27:47 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:27:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:47 | D | sum error = [ 8.7219, 9.1493, 9.5913, 10.0525, 10.5311] +24-11-19 20:27:47 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:27:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:47 | D | sum error = [ 11.0301, 11.5511, 12.0891, 12.6494, 13.2301] +24-11-19 20:27:47 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:27:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:47 | D | sum error = [ 13.8367, 14.4634, 15.1169, 15.7923, 16.4940] +24-11-19 20:27:47 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:27:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:47 | D | sum error = [ 17.2226, 17.9781, 18.7622, 19.5723, 20.4102] +24-11-19 20:27:47 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:27:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:47 | D | sum error = [ 21.2800, 22.1789, 23.1100, 24.0739, 25.0720] +24-11-19 20:27:47 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:27:47 | D | + error = [0.5546] +24-11-19 20:27:47 | D | - Calibrating model.layers.14.mlp.up_proj.weight +24-11-19 20:27:47 | D | + w: sint8 +24-11-19 20:27:47 | D | + x: None +24-11-19 20:27:47 | D | + y: None +24-11-19 20:27:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:47 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:27:48 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:27:48 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:27:48 | D | - range ratio = [ 1.0000] +24-11-19 20:27:48 | D | sum error = [ 5.4712] +24-11-19 20:27:48 | D | best error = [ 5.4712] +24-11-19 20:27:49 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:49 | D | sum error = [ 5.4285, 5.4062, 5.4441, 5.5010, 5.6019] +24-11-19 20:27:49 | D | best error = [ 5.0523, 4.8932, 4.8127, 4.7669, 4.7418] +24-11-19 20:27:49 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:49 | D | sum error = [ 5.7423, 5.9334, 6.1671, 6.4545, 6.7961] +24-11-19 20:27:49 | D | best error = [ 4.7298, 4.7246, 4.7226, 4.7219, 4.7218] +24-11-19 20:27:49 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:49 | D | sum error = [ 7.2133, 7.6295, 8.1356, 8.6844, 9.2915] +24-11-19 20:27:49 | D | best error = [ 4.7217, 4.7217, 4.7217, 4.7217, 4.7217] +24-11-19 20:27:49 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:49 | D | sum error = [ 9.9633, 10.6479, 11.4123, 12.2493, 13.1185] +24-11-19 20:27:49 | D | best error = [ 4.7217, 4.7217, 4.7217, 4.7217, 4.7217] +24-11-19 20:27:49 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:49 | D | sum error = [ 14.0544, 15.0453, 16.1228, 17.2528, 18.4524] +24-11-19 20:27:49 | D | best error = [ 4.7217, 4.7217, 4.7217, 4.7217, 4.7217] +24-11-19 20:27:49 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:49 | D | sum error = [ 19.7206, 21.0743, 22.5069, 24.0192, 25.6118] +24-11-19 20:27:49 | D | best error = [ 4.7217, 4.7217, 4.7217, 4.7217, 4.7217] +24-11-19 20:27:49 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:49 | D | sum error = [ 27.3110, 29.0919, 30.9650, 32.9491, 35.0386] +24-11-19 20:27:49 | D | best error = [ 4.7217, 4.7217, 4.7217, 4.7217, 4.7217] +24-11-19 20:27:49 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:49 | D | sum error = [ 37.2334, 39.5532, 41.9859, 44.5404, 47.2274] +24-11-19 20:27:49 | D | best error = [ 4.7217, 4.7217, 4.7217, 4.7217, 4.7217] +24-11-19 20:27:49 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:49 | D | sum error = [ 50.0478, 53.0075, 56.1215, 59.3903, 62.8004] +24-11-19 20:27:49 | D | best error = [ 4.7217, 4.7217, 4.7217, 4.7217, 4.7217] +24-11-19 20:27:49 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:49 | D | sum error = [ 66.3884, 70.1551, 74.0949, 78.2201, 82.5284] +24-11-19 20:27:49 | D | best error = [ 4.7217, 4.7217, 4.7217, 4.7217, 4.7217] +24-11-19 20:27:49 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:49 | D | sum error = [ 87.0295, 91.7353, 96.6587, 101.8015, 107.1625] +24-11-19 20:27:49 | D | best error = [ 4.7217, 4.7217, 4.7217, 4.7217, 4.7217] +24-11-19 20:27:49 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:49 | D | sum error = [ 112.7465, 118.5826, 124.6635, 130.9898, 137.5855] +24-11-19 20:27:49 | D | best error = [ 4.7217, 4.7217, 4.7217, 4.7217, 4.7217] +24-11-19 20:27:49 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:49 | D | sum error = [ 144.4492, 151.5837, 158.9927, 166.6991, 174.6868] +24-11-19 20:27:49 | D | best error = [ 4.7217, 4.7217, 4.7217, 4.7217, 4.7217] +24-11-19 20:27:49 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:49 | D | sum error = [ 182.9810, 191.5792, 200.4690, 209.6824, 219.2105] +24-11-19 20:27:49 | D | best error = [ 4.7217, 4.7217, 4.7217, 4.7217, 4.7217] +24-11-19 20:27:49 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:49 | D | sum error = [ 229.0661, 239.2504, 249.7716, 260.6182, 271.8102] +24-11-19 20:27:49 | D | best error = [ 4.7217, 4.7217, 4.7217, 4.7217, 4.7217] +24-11-19 20:27:49 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:49 | D | sum error = [ 283.3727, 295.2722, 307.5457, 320.1688, 333.1580] +24-11-19 20:27:49 | D | best error = [ 4.7217, 4.7217, 4.7217, 4.7217, 4.7217] +24-11-19 20:27:49 | D | + error = [4.7217] +24-11-19 20:27:49 | D | - Calibrating model.layers.14.mlp.gate_proj.weight +24-11-19 20:27:49 | D | + w: sint8 +24-11-19 20:27:49 | D | + x: None +24-11-19 20:27:49 | D | + y: None +24-11-19 20:27:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:49 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:27:49 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:27:49 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:27:49 | D | - range ratio = [ 1.0000] +24-11-19 20:27:49 | D | sum error = [ 6.6988] +24-11-19 20:27:49 | D | best error = [ 6.6988] +24-11-19 20:27:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:50 | D | sum error = [ 6.6454, 6.6272, 6.6651, 6.7275, 6.8616] +24-11-19 20:27:50 | D | best error = [ 6.1868, 5.9965, 5.9020, 5.8451, 5.8148] +24-11-19 20:27:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:50 | D | sum error = [ 7.0478, 7.2758, 7.5616, 7.9342, 8.3584] +24-11-19 20:27:50 | D | best error = [ 5.8007, 5.7952, 5.7933, 5.7927, 5.7926] +24-11-19 20:27:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:50 | D | sum error = [ 8.8599, 9.4083, 10.0452, 10.7454, 11.4981] +24-11-19 20:27:50 | D | best error = [ 5.7926, 5.7926, 5.7926, 5.7926, 5.7926] +24-11-19 20:27:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:50 | D | sum error = [ 12.3330, 13.2522, 14.2237, 15.2827, 16.4136] +24-11-19 20:27:50 | D | best error = [ 5.7926, 5.7926, 5.7926, 5.7926, 5.7926] +24-11-19 20:27:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:50 | D | sum error = [ 17.6522, 18.9545, 20.3690, 21.8564, 23.4708] +24-11-19 20:27:50 | D | best error = [ 5.7926, 5.7926, 5.7926, 5.7926, 5.7926] +24-11-19 20:27:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:50 | D | sum error = [ 25.1934, 27.0393, 28.9804, 31.0709, 33.3148] +24-11-19 20:27:50 | D | best error = [ 5.7926, 5.7926, 5.7926, 5.7926, 5.7926] +24-11-19 20:27:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:50 | D | sum error = [ 35.6805, 38.1954, 40.8963, 43.7549, 46.8116] +24-11-19 20:27:50 | D | best error = [ 5.7926, 5.7926, 5.7926, 5.7926, 5.7926] +24-11-19 20:27:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:50 | D | sum error = [ 50.0829, 53.5212, 57.2136, 61.1110, 65.3058] +24-11-19 20:27:50 | D | best error = [ 5.7926, 5.7926, 5.7926, 5.7926, 5.7926] +24-11-19 20:27:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:50 | D | sum error = [ 69.7507, 74.4775, 79.4976, 84.8456, 90.5539] +24-11-19 20:27:50 | D | best error = [ 5.7926, 5.7926, 5.7926, 5.7926, 5.7926] +24-11-19 20:27:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:50 | D | sum error = [ 96.5870, 103.0204, 109.8248, 117.0306, 124.7109] +24-11-19 20:27:50 | D | best error = [ 5.7926, 5.7926, 5.7926, 5.7926, 5.7926] +24-11-19 20:27:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:50 | D | sum error = [ 132.8447, 141.4390, 150.5280, 160.1762, 170.3549] +24-11-19 20:27:50 | D | best error = [ 5.7926, 5.7926, 5.7926, 5.7926, 5.7926] +24-11-19 20:27:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:50 | D | sum error = [ 181.1387, 192.5240, 204.5397, 217.1900, 230.5201] +24-11-19 20:27:50 | D | best error = [ 5.7926, 5.7926, 5.7926, 5.7926, 5.7926] +24-11-19 20:27:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:50 | D | sum error = [ 244.5706, 259.3073, 274.7879, 291.0218, 308.0589] +24-11-19 20:27:50 | D | best error = [ 5.7926, 5.7926, 5.7926, 5.7926, 5.7926] +24-11-19 20:27:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:50 | D | sum error = [ 325.9117, 344.5775, 364.0912, 384.4883, 405.7477] +24-11-19 20:27:50 | D | best error = [ 5.7926, 5.7926, 5.7926, 5.7926, 5.7926] +24-11-19 20:27:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:50 | D | sum error = [ 427.9224, 451.0179, 475.0241, 499.9473, 525.8120] +24-11-19 20:27:50 | D | best error = [ 5.7926, 5.7926, 5.7926, 5.7926, 5.7926] +24-11-19 20:27:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:50 | D | sum error = [ 552.6239, 580.3718, 609.0578, 638.6870, 669.2345] +24-11-19 20:27:50 | D | best error = [ 5.7926, 5.7926, 5.7926, 5.7926, 5.7926] +24-11-19 20:27:50 | D | + error = [5.7926] +24-11-19 20:27:51 | D | - Calibrating model.layers.14.mlp.down_proj.weight +24-11-19 20:27:51 | D | + w: sint8 +24-11-19 20:27:51 | D | + x: None +24-11-19 20:27:51 | D | + y: None +24-11-19 20:27:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:51 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:27:51 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:27:51 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:27:51 | D | - range ratio = [ 1.0000] +24-11-19 20:27:51 | D | sum error = [ 0.7967] +24-11-19 20:27:51 | D | best error = [ 0.7967] +24-11-19 20:27:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:52 | D | sum error = [ 0.7888, 0.7836, 0.7790, 0.7753, 0.7746] +24-11-19 20:27:52 | D | best error = [ 0.7628, 0.7467, 0.7364, 0.7290, 0.7230] +24-11-19 20:27:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:52 | D | sum error = [ 0.7773, 0.7802, 0.7861, 0.7968, 0.8095] +24-11-19 20:27:52 | D | best error = [ 0.7185, 0.7150, 0.7123, 0.7103, 0.7089] +24-11-19 20:27:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:52 | D | sum error = [ 0.8278, 0.8489, 0.8761, 0.9062, 0.9401] +24-11-19 20:27:52 | D | best error = [ 0.7076, 0.7070, 0.7063, 0.7060, 0.7055] +24-11-19 20:27:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:52 | D | sum error = [ 0.9830, 1.0299, 1.0807, 1.1377, 1.2049] +24-11-19 20:27:52 | D | best error = [ 0.7053, 0.7052, 0.7051, 0.7050, 0.7049] +24-11-19 20:27:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:52 | D | sum error = [ 1.2746, 1.3528, 1.4374, 1.5265, 1.6272] +24-11-19 20:27:52 | D | best error = [ 0.7049, 0.7048, 0.7047, 0.7047, 0.7047] +24-11-19 20:27:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:52 | D | sum error = [ 1.7339, 1.8485, 1.9717, 2.1025, 2.2434] +24-11-19 20:27:52 | D | best error = [ 0.7047, 0.7047, 0.7046, 0.7046, 0.7046] +24-11-19 20:27:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:52 | D | sum error = [ 2.3947, 2.5550, 2.7243, 2.9065, 3.1011] +24-11-19 20:27:52 | D | best error = [ 0.7046, 0.7046, 0.7046, 0.7046, 0.7046] +24-11-19 20:27:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:52 | D | sum error = [ 3.3057, 3.5248, 3.7553, 3.9999, 4.2571] +24-11-19 20:27:52 | D | best error = [ 0.7046, 0.7046, 0.7046, 0.7046, 0.7046] +24-11-19 20:27:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:52 | D | sum error = [ 4.5313, 4.8198, 5.1267, 5.4497, 5.7913] +24-11-19 20:27:52 | D | best error = [ 0.7046, 0.7046, 0.7046, 0.7046, 0.7046] +24-11-19 20:27:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:52 | D | sum error = [ 6.1521, 6.5305, 6.9300, 7.3519, 7.7945] +24-11-19 20:27:52 | D | best error = [ 0.7046, 0.7046, 0.7046, 0.7046, 0.7046] +24-11-19 20:27:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:52 | D | sum error = [ 8.2609, 8.7514, 9.2667, 9.8069, 10.3746] +24-11-19 20:27:52 | D | best error = [ 0.7046, 0.7046, 0.7046, 0.7046, 0.7046] +24-11-19 20:27:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:52 | D | sum error = [ 10.9707, 11.5954, 12.2510, 12.9370, 13.6561] +24-11-19 20:27:52 | D | best error = [ 0.7046, 0.7046, 0.7046, 0.7046, 0.7046] +24-11-19 20:27:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:52 | D | sum error = [ 14.4073, 15.1935, 16.0142, 16.8728, 17.7690] +24-11-19 20:27:52 | D | best error = [ 0.7046, 0.7046, 0.7046, 0.7046, 0.7046] +24-11-19 20:27:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:52 | D | sum error = [ 18.7041, 19.6786, 20.6943, 21.7536, 22.8548] +24-11-19 20:27:52 | D | best error = [ 0.7046, 0.7046, 0.7046, 0.7046, 0.7046] +24-11-19 20:27:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:52 | D | sum error = [ 24.0015, 25.1910, 26.4264, 27.7098, 29.0408] +24-11-19 20:27:52 | D | best error = [ 0.7046, 0.7046, 0.7046, 0.7046, 0.7046] +24-11-19 20:27:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:52 | D | sum error = [ 30.4206, 31.8493, 33.3299, 34.8596, 36.4424] +24-11-19 20:27:52 | D | best error = [ 0.7046, 0.7046, 0.7046, 0.7046, 0.7046] +24-11-19 20:27:52 | D | + error = [0.7046] +24-11-19 20:27:52 | D | - Quantizing model.layers.14.self_attn.q_proj.weight +24-11-19 20:27:53 | D | - Quantizing model.layers.14.self_attn.k_proj.weight +24-11-19 20:27:54 | D | - Quantizing model.layers.14.self_attn.v_proj.weight +24-11-19 20:27:54 | D | - Quantizing model.layers.14.self_attn.o_proj.weight +24-11-19 20:27:55 | D | - Quantizing model.layers.14.mlp.up_proj.weight +24-11-19 20:27:56 | D | - Quantizing model.layers.14.mlp.gate_proj.weight +24-11-19 20:27:57 | D | - Quantizing model.layers.14.mlp.down_proj.weight +24-11-19 20:28:07 | D | - Quantizing layer model.layers.15 +24-11-19 20:28:07 | D | - Calibrating model.layers.15.self_attn.q_proj.weight +24-11-19 20:28:07 | D | + w: sint8 +24-11-19 20:28:07 | D | + x: None +24-11-19 20:28:07 | D | + y: None +24-11-19 20:28:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:28:07 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:07 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:07 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:07 | D | - range ratio = [ 1.0000] +24-11-19 20:28:07 | D | sum error = [ 4.4366] +24-11-19 20:28:07 | D | best error = [ 4.4366] +24-11-19 20:28:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:19 | D | sum error = [ 4.4311, 4.3382, 4.3830, 4.4464, 4.5147] +24-11-19 20:28:19 | D | best error = [ 4.4311, 4.3382, 4.3382, 4.3382, 4.3382] +24-11-19 20:28:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:19 | D | sum error = [ 4.7110, 4.7836, 4.8930, 5.2249, 5.4161] +24-11-19 20:28:19 | D | best error = [ 4.3382, 4.3382, 4.3382, 4.3382, 4.3382] +24-11-19 20:28:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:19 | D | sum error = [ 5.8480, 6.2252, 6.6449, 7.1228, 7.7562] +24-11-19 20:28:19 | D | best error = [ 4.3382, 4.3382, 4.3382, 4.3382, 4.3382] +24-11-19 20:28:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:19 | D | sum error = [ 8.3270, 9.0492, 9.6504, 10.4646, 11.3561] +24-11-19 20:28:19 | D | best error = [ 4.3382, 4.3382, 4.3382, 4.3382, 4.3382] +24-11-19 20:28:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:19 | D | sum error = [ 12.2985, 13.1746, 14.3441, 15.5793, 16.7309] +24-11-19 20:28:19 | D | best error = [ 4.3382, 4.3382, 4.3382, 4.3382, 4.3382] +24-11-19 20:28:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:19 | D | sum error = [ 18.2081, 19.5334, 21.1300, 22.6491, 24.3158] +24-11-19 20:28:19 | D | best error = [ 4.3382, 4.3382, 4.3382, 4.3382, 4.3382] +24-11-19 20:28:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:19 | D | sum error = [ 26.2225, 28.1081, 30.1649, 32.3817, 34.7470] +24-11-19 20:28:19 | D | best error = [ 4.3382, 4.3382, 4.3382, 4.3382, 4.3382] +24-11-19 20:28:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:19 | D | sum error = [ 37.3752, 40.1949, 42.9787, 46.1743, 49.6583] +24-11-19 20:28:19 | D | best error = [ 4.3382, 4.3382, 4.3382, 4.3382, 4.3382] +24-11-19 20:28:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:19 | D | sum error = [ 53.0985, 56.9681, 61.1298, 65.6359, 70.2635] +24-11-19 20:28:19 | D | best error = [ 4.3382, 4.3382, 4.3382, 4.3382, 4.3382] +24-11-19 20:28:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:19 | D | sum error = [ 75.3095, 80.7776, 86.7534, 92.8332, 99.6893] +24-11-19 20:28:19 | D | best error = [ 4.3382, 4.3382, 4.3382, 4.3382, 4.3382] +24-11-19 20:28:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:19 | D | sum error = [ 106.6829, 114.5297, 122.9735, 131.7895, 141.3143] +24-11-19 20:28:19 | D | best error = [ 4.3382, 4.3382, 4.3382, 4.3382, 4.3382] +24-11-19 20:28:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:19 | D | sum error = [ 151.2387, 161.9671, 173.2595, 185.6190, 198.6087] +24-11-19 20:28:19 | D | best error = [ 4.3382, 4.3382, 4.3382, 4.3382, 4.3382] +24-11-19 20:28:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:19 | D | sum error = [ 212.3836, 227.2180, 243.0513, 259.7739, 277.5988] +24-11-19 20:28:19 | D | best error = [ 4.3382, 4.3382, 4.3382, 4.3382, 4.3382] +24-11-19 20:28:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:19 | D | sum error = [ 296.0710, 315.9343, 336.9693, 358.7230, 382.1232] +24-11-19 20:28:19 | D | best error = [ 4.3382, 4.3382, 4.3382, 4.3382, 4.3382] +24-11-19 20:28:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:19 | D | sum error = [ 406.6609, 432.3903, 459.2336, 487.4117, 517.0241] +24-11-19 20:28:19 | D | best error = [ 4.3382, 4.3382, 4.3382, 4.3382, 4.3382] +24-11-19 20:28:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:19 | D | sum error = [ 547.6567, 579.3960, 612.1282, 645.7328, 680.1827] +24-11-19 20:28:19 | D | best error = [ 4.3382, 4.3382, 4.3382, 4.3382, 4.3382] +24-11-19 20:28:19 | D | + error = [4.3382] +24-11-19 20:28:19 | D | - Calibrating model.layers.15.self_attn.k_proj.weight +24-11-19 20:28:19 | D | + w: sint8 +24-11-19 20:28:19 | D | + x: None +24-11-19 20:28:19 | D | + y: None +24-11-19 20:28:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:28:19 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:19 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:20 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:20 | D | - range ratio = [ 1.0000] +24-11-19 20:28:20 | D | sum error = [ 4.0175] +24-11-19 20:28:20 | D | best error = [ 4.0175] +24-11-19 20:28:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:32 | D | sum error = [ 4.0447, 4.6102, 4.2230, 4.0777, 4.3200] +24-11-19 20:28:32 | D | best error = [ 4.0175, 4.0175, 4.0175, 4.0175, 4.0175] +24-11-19 20:28:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:32 | D | sum error = [ 4.5623, 4.4081, 4.6320, 5.4038, 5.2349] +24-11-19 20:28:32 | D | best error = [ 4.0175, 4.0175, 4.0175, 4.0175, 4.0175] +24-11-19 20:28:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:32 | D | sum error = [ 5.5860, 5.6232, 6.1719, 6.8942, 7.1273] +24-11-19 20:28:32 | D | best error = [ 4.0175, 4.0175, 4.0175, 4.0175, 4.0175] +24-11-19 20:28:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:32 | D | sum error = [ 8.1687, 8.3258, 9.2219, 10.1397, 10.2803] +24-11-19 20:28:32 | D | best error = [ 4.0175, 4.0175, 4.0175, 4.0175, 4.0175] +24-11-19 20:28:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:32 | D | sum error = [ 11.3072, 11.8179, 12.1853, 14.0963, 14.2239] +24-11-19 20:28:32 | D | best error = [ 4.0175, 4.0175, 4.0175, 4.0175, 4.0175] +24-11-19 20:28:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:32 | D | sum error = [ 15.6164, 16.6393, 17.2596, 18.4879, 19.8973] +24-11-19 20:28:32 | D | best error = [ 4.0175, 4.0175, 4.0175, 4.0175, 4.0175] +24-11-19 20:28:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:32 | D | sum error = [ 20.8629, 22.4581, 23.8845, 25.7600, 27.7244] +24-11-19 20:28:32 | D | best error = [ 4.0175, 4.0175, 4.0175, 4.0175, 4.0175] +24-11-19 20:28:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:32 | D | sum error = [ 29.4143, 31.9353, 34.2865, 36.9108, 39.6587] +24-11-19 20:28:32 | D | best error = [ 4.0175, 4.0175, 4.0175, 4.0175, 4.0175] +24-11-19 20:28:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:32 | D | sum error = [ 42.6851, 45.9758, 49.8919, 53.6608, 57.9901] +24-11-19 20:28:32 | D | best error = [ 4.0175, 4.0175, 4.0175, 4.0175, 4.0175] +24-11-19 20:28:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:32 | D | sum error = [ 62.5503, 67.4799, 72.8531, 78.6814, 85.1471] +24-11-19 20:28:32 | D | best error = [ 4.0175, 4.0175, 4.0175, 4.0175, 4.0175] +24-11-19 20:28:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:32 | D | sum error = [ 92.3042, 99.3213, 106.9470, 115.0999, 124.3874] +24-11-19 20:28:32 | D | best error = [ 4.0175, 4.0175, 4.0175, 4.0175, 4.0175] +24-11-19 20:28:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:32 | D | sum error = [ 133.1081, 142.6876, 153.7122, 164.3086, 176.5236] +24-11-19 20:28:32 | D | best error = [ 4.0175, 4.0175, 4.0175, 4.0175, 4.0175] +24-11-19 20:28:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:32 | D | sum error = [ 188.8716, 202.7135, 217.0802, 232.4336, 248.7731] +24-11-19 20:28:32 | D | best error = [ 4.0175, 4.0175, 4.0175, 4.0175, 4.0175] +24-11-19 20:28:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:32 | D | sum error = [ 265.9872, 284.9032, 304.7925, 326.0555, 349.2453] +24-11-19 20:28:32 | D | best error = [ 4.0175, 4.0175, 4.0175, 4.0175, 4.0175] +24-11-19 20:28:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:32 | D | sum error = [ 373.6108, 399.7620, 427.0606, 456.3891, 487.1885] +24-11-19 20:28:32 | D | best error = [ 4.0175, 4.0175, 4.0175, 4.0175, 4.0175] +24-11-19 20:28:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:32 | D | sum error = [ 520.0104, 553.5227, 588.9727, 626.1780, 663.4023] +24-11-19 20:28:32 | D | best error = [ 4.0175, 4.0175, 4.0175, 4.0175, 4.0175] +24-11-19 20:28:32 | D | + error = [4.0175] +24-11-19 20:28:32 | D | - Calibrating model.layers.15.self_attn.v_proj.weight +24-11-19 20:28:32 | D | + w: sint8 +24-11-19 20:28:32 | D | + x: None +24-11-19 20:28:32 | D | + y: None +24-11-19 20:28:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:32 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:28:32 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:28:33 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:28:33 | D | - range ratio = [ 1.0000] +24-11-19 20:28:33 | D | sum error = [ 1.6269] +24-11-19 20:28:33 | D | best error = [ 1.6269] +24-11-19 20:28:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:33 | D | sum error = [ 1.6116, 1.6155, 1.6029, 1.6549, 1.6608] +24-11-19 20:28:33 | D | best error = [ 1.4883, 1.4404, 1.4181, 1.4064, 1.3978] +24-11-19 20:28:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:33 | D | sum error = [ 1.7149, 1.7675, 1.8274, 1.9185, 2.0204] +24-11-19 20:28:33 | D | best error = [ 1.3946, 1.3925, 1.3924, 1.3921, 1.3921] +24-11-19 20:28:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:33 | D | sum error = [ 2.1383, 2.2736, 2.4185, 2.5748, 2.7641] +24-11-19 20:28:33 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:28:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:33 | D | sum error = [ 2.9465, 3.1333, 3.3820, 3.6240, 3.8717] +24-11-19 20:28:33 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:28:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:33 | D | sum error = [ 4.1293, 4.4245, 4.7318, 5.0639, 5.4100] +24-11-19 20:28:33 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:28:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:33 | D | sum error = [ 5.7768, 6.1667, 6.5721, 7.0212, 7.4690] +24-11-19 20:28:33 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:28:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:33 | D | sum error = [ 7.9481, 8.4472, 8.9870, 9.5615, 10.1468] +24-11-19 20:28:33 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:28:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:33 | D | sum error = [ 10.7618, 11.4239, 12.1078, 12.8197, 13.5862] +24-11-19 20:28:33 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:28:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:33 | D | sum error = [ 14.3775, 15.2068, 16.0879, 16.9972, 17.9613] +24-11-19 20:28:33 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:28:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:33 | D | sum error = [ 18.9556, 20.0104, 21.1110, 22.2542, 23.4670] +24-11-19 20:28:33 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:28:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:33 | D | sum error = [ 24.7299, 26.0379, 27.4135, 28.8246, 30.3047] +24-11-19 20:28:33 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:28:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:33 | D | sum error = [ 31.8427, 33.4491, 35.1215, 36.8540, 38.6466] +24-11-19 20:28:33 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:28:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:33 | D | sum error = [ 40.5174, 42.4494, 44.4643, 46.5272, 48.6579] +24-11-19 20:28:33 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:28:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:33 | D | sum error = [ 50.8763, 53.1598, 55.5152, 57.9440, 60.4439] +24-11-19 20:28:33 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:28:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:33 | D | sum error = [ 63.0297, 65.6867, 68.4219, 71.2325, 74.1332] +24-11-19 20:28:33 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:28:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:33 | D | sum error = [ 77.1202, 80.1998, 83.3737, 86.6251, 89.9700] +24-11-19 20:28:33 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:28:33 | D | + error = [1.3921] +24-11-19 20:28:33 | D | - Calibrating model.layers.15.self_attn.o_proj.weight +24-11-19 20:28:33 | D | + w: sint8 +24-11-19 20:28:33 | D | + x: None +24-11-19 20:28:33 | D | + y: None +24-11-19 20:28:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:33 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:28:33 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:28:33 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:28:33 | D | - range ratio = [ 1.0000] +24-11-19 20:28:33 | D | sum error = [ 0.6806] +24-11-19 20:28:33 | D | best error = [ 0.6806] +24-11-19 20:28:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:33 | D | sum error = [ 0.6758, 0.6693, 0.6703, 0.6745, 0.6771] +24-11-19 20:28:33 | D | best error = [ 0.6258, 0.6001, 0.5850, 0.5754, 0.5683] +24-11-19 20:28:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:33 | D | sum error = [ 0.6902, 0.6962, 0.7136, 0.7314, 0.7520] +24-11-19 20:28:33 | D | best error = [ 0.5632, 0.5589, 0.5557, 0.5532, 0.5516] +24-11-19 20:28:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:33 | D | sum error = [ 0.7802, 0.8061, 0.8439, 0.8830, 0.9298] +24-11-19 20:28:33 | D | best error = [ 0.5498, 0.5485, 0.5476, 0.5467, 0.5460] +24-11-19 20:28:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:33 | D | sum error = [ 0.9744, 1.0239, 1.0824, 1.1405, 1.2042] +24-11-19 20:28:33 | D | best error = [ 0.5453, 0.5449, 0.5446, 0.5443, 0.5441] +24-11-19 20:28:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:33 | D | sum error = [ 1.2729, 1.3533, 1.4273, 1.5110, 1.5987] +24-11-19 20:28:33 | D | best error = [ 0.5439, 0.5437, 0.5436, 0.5435, 0.5435] +24-11-19 20:28:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:33 | D | sum error = [ 1.6909, 1.7876, 1.8895, 1.9987, 2.1132] +24-11-19 20:28:33 | D | best error = [ 0.5434, 0.5433, 0.5433, 0.5433, 0.5432] +24-11-19 20:28:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:33 | D | sum error = [ 2.2340, 2.3584, 2.4899, 2.6303, 2.7734] +24-11-19 20:28:33 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:28:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:33 | D | sum error = [ 2.9257, 3.0846, 3.2515, 3.4292, 3.6125] +24-11-19 20:28:33 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:28:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:33 | D | sum error = [ 3.8036, 4.0034, 4.2157, 4.4355, 4.6667] +24-11-19 20:28:33 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:28:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:33 | D | sum error = [ 4.9063, 5.1537, 5.4141, 5.6854, 5.9667] +24-11-19 20:28:33 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:28:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:33 | D | sum error = [ 6.2588, 6.5655, 6.8825, 7.2131, 7.5560] +24-11-19 20:28:33 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:28:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:33 | D | sum error = [ 7.9123, 8.2844, 8.6686, 9.0671, 9.4824] +24-11-19 20:28:33 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:28:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:33 | D | sum error = [ 9.9118, 10.3586, 10.8229, 11.3053, 11.8046] +24-11-19 20:28:33 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:28:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:33 | D | sum error = [ 12.3232, 12.8636, 13.4248, 14.0059, 14.6091] +24-11-19 20:28:33 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:28:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:33 | D | sum error = [ 15.2354, 15.8846, 16.5571, 17.2542, 17.9781] +24-11-19 20:28:33 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:28:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:33 | D | sum error = [ 18.7278, 19.5075, 20.3205, 21.1665, 22.0474] +24-11-19 20:28:33 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:28:33 | D | + error = [0.5432] +24-11-19 20:28:33 | D | - Calibrating model.layers.15.mlp.up_proj.weight +24-11-19 20:28:33 | D | + w: sint8 +24-11-19 20:28:33 | D | + x: None +24-11-19 20:28:33 | D | + y: None +24-11-19 20:28:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:33 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:28:34 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:28:34 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:28:34 | D | - range ratio = [ 1.0000] +24-11-19 20:28:34 | D | sum error = [ 5.6796] +24-11-19 20:28:34 | D | best error = [ 5.6796] +24-11-19 20:28:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:35 | D | sum error = [ 5.6422, 5.6327, 5.6515, 5.7000, 5.8245] +24-11-19 20:28:35 | D | best error = [ 5.2616, 5.1045, 5.0216, 4.9750, 4.9508] +24-11-19 20:28:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:35 | D | sum error = [ 5.9814, 6.1772, 6.4277, 6.7260, 7.0821] +24-11-19 20:28:35 | D | best error = [ 4.9390, 4.9339, 4.9322, 4.9315, 4.9313] +24-11-19 20:28:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:35 | D | sum error = [ 7.4984, 7.9564, 8.4570, 9.0273, 9.6643] +24-11-19 20:28:35 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:28:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:35 | D | sum error = [ 10.3478, 11.0877, 11.8820, 12.7243, 13.6444] +24-11-19 20:28:35 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:28:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:35 | D | sum error = [ 14.6131, 15.6527, 16.7529, 17.9256, 19.1709] +24-11-19 20:28:35 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:28:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:35 | D | sum error = [ 20.4745, 21.8762, 23.3465, 24.9341, 26.5649] +24-11-19 20:28:35 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:28:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:35 | D | sum error = [ 28.3121, 30.1529, 32.0846, 34.1313, 36.2847] +24-11-19 20:28:35 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:28:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:35 | D | sum error = [ 38.5421, 40.9325, 43.4415, 46.0673, 48.8435] +24-11-19 20:28:35 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:28:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:35 | D | sum error = [ 51.7537, 54.8031, 58.0004, 61.3772, 64.8933] +24-11-19 20:28:35 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:28:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:35 | D | sum error = [ 68.5860, 72.4616, 76.5103, 80.7603, 85.2012] +24-11-19 20:28:35 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:28:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:35 | D | sum error = [ 89.8359, 94.6839, 99.7467, 105.0365, 110.5358] +24-11-19 20:28:35 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:28:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:35 | D | sum error = [ 116.2797, 122.2550, 128.4779, 134.9598, 141.6941] +24-11-19 20:28:35 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:28:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:35 | D | sum error = [ 148.7001, 155.9761, 163.5399, 171.3904, 179.5351] +24-11-19 20:28:35 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:28:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:35 | D | sum error = [ 187.9862, 196.7382, 205.8042, 215.1814, 224.8946] +24-11-19 20:28:35 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:28:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:35 | D | sum error = [ 234.9423, 245.3159, 256.0445, 267.1311, 278.5664] +24-11-19 20:28:35 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:28:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:35 | D | sum error = [ 290.3557, 302.5109, 315.0463, 327.9421, 341.2213] +24-11-19 20:28:35 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:28:35 | D | + error = [4.9312] +24-11-19 20:28:35 | D | - Calibrating model.layers.15.mlp.gate_proj.weight +24-11-19 20:28:35 | D | + w: sint8 +24-11-19 20:28:35 | D | + x: None +24-11-19 20:28:35 | D | + y: None +24-11-19 20:28:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:35 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:35 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:35 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:35 | D | - range ratio = [ 1.0000] +24-11-19 20:28:35 | D | sum error = [ 7.1842] +24-11-19 20:28:35 | D | best error = [ 7.1842] +24-11-19 20:28:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:36 | D | sum error = [ 7.1492, 7.1240, 7.1596, 7.2402, 7.3490] +24-11-19 20:28:36 | D | best error = [ 6.6700, 6.4708, 6.3634, 6.3015, 6.2712] +24-11-19 20:28:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:36 | D | sum error = [ 7.5751, 7.8291, 8.1447, 8.5282, 8.9877] +24-11-19 20:28:36 | D | best error = [ 6.2558, 6.2490, 6.2465, 6.2455, 6.2453] +24-11-19 20:28:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:36 | D | sum error = [ 9.5111, 10.1127, 10.7897, 11.5528, 12.3673] +24-11-19 20:28:36 | D | best error = [ 6.2453, 6.2453, 6.2453, 6.2453, 6.2453] +24-11-19 20:28:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:36 | D | sum error = [ 13.2784, 14.2453, 15.3030, 16.4566, 17.6661] +24-11-19 20:28:36 | D | best error = [ 6.2453, 6.2453, 6.2453, 6.2453, 6.2453] +24-11-19 20:28:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:36 | D | sum error = [ 19.0042, 20.4014, 21.9019, 23.5477, 25.2952] +24-11-19 20:28:36 | D | best error = [ 6.2453, 6.2453, 6.2453, 6.2453, 6.2453] +24-11-19 20:28:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:36 | D | sum error = [ 27.1372, 29.1168, 31.2303, 33.4962, 35.8762] +24-11-19 20:28:36 | D | best error = [ 6.2453, 6.2453, 6.2453, 6.2453, 6.2453] +24-11-19 20:28:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:36 | D | sum error = [ 38.4357, 41.1514, 44.0487, 47.1413, 50.4284] +24-11-19 20:28:36 | D | best error = [ 6.2453, 6.2453, 6.2453, 6.2453, 6.2453] +24-11-19 20:28:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:36 | D | sum error = [ 53.9729, 57.6983, 61.6764, 65.8971, 70.4028] +24-11-19 20:28:36 | D | best error = [ 6.2453, 6.2453, 6.2453, 6.2453, 6.2453] +24-11-19 20:28:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:36 | D | sum error = [ 75.1971, 80.2868, 85.7055, 91.4980, 97.6335] +24-11-19 20:28:36 | D | best error = [ 6.2453, 6.2453, 6.2453, 6.2453, 6.2453] +24-11-19 20:28:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:36 | D | sum error = [ 104.1995, 111.1451, 118.5275, 126.3843, 134.6788] +24-11-19 20:28:36 | D | best error = [ 6.2453, 6.2453, 6.2453, 6.2453, 6.2453] +24-11-19 20:28:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:36 | D | sum error = [ 143.4945, 152.8107, 162.6900, 173.1652, 184.2243] +24-11-19 20:28:36 | D | best error = [ 6.2453, 6.2453, 6.2453, 6.2453, 6.2453] +24-11-19 20:28:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:36 | D | sum error = [ 195.9154, 208.3218, 221.3950, 235.1829, 249.6886] +24-11-19 20:28:36 | D | best error = [ 6.2453, 6.2453, 6.2453, 6.2453, 6.2453] +24-11-19 20:28:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:36 | D | sum error = [ 265.0091, 281.0960, 298.0290, 315.7850, 334.4554] +24-11-19 20:28:36 | D | best error = [ 6.2453, 6.2453, 6.2453, 6.2453, 6.2453] +24-11-19 20:28:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:36 | D | sum error = [ 354.0150, 374.4778, 395.8766, 418.2474, 441.5521] +24-11-19 20:28:36 | D | best error = [ 6.2453, 6.2453, 6.2453, 6.2453, 6.2453] +24-11-19 20:28:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:36 | D | sum error = [ 465.8588, 491.1559, 517.4526, 544.7480, 573.0629] +24-11-19 20:28:36 | D | best error = [ 6.2453, 6.2453, 6.2453, 6.2453, 6.2453] +24-11-19 20:28:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:36 | D | sum error = [ 602.3970, 632.7532, 664.1480, 696.5360, 729.9232] +24-11-19 20:28:36 | D | best error = [ 6.2453, 6.2453, 6.2453, 6.2453, 6.2453] +24-11-19 20:28:36 | D | + error = [6.2453] +24-11-19 20:28:36 | D | - Calibrating model.layers.15.mlp.down_proj.weight +24-11-19 20:28:36 | D | + w: sint8 +24-11-19 20:28:36 | D | + x: None +24-11-19 20:28:36 | D | + y: None +24-11-19 20:28:36 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:36 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:37 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:37 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:37 | D | - range ratio = [ 1.0000] +24-11-19 20:28:37 | D | sum error = [ 0.8764] +24-11-19 20:28:37 | D | best error = [ 0.8764] +24-11-19 20:28:38 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:38 | D | sum error = [ 0.8670, 0.8618, 0.8584, 0.8541, 0.8515] +24-11-19 20:28:38 | D | best error = [ 0.8410, 0.8240, 0.8125, 0.8034, 0.7968] +24-11-19 20:28:38 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:38 | D | sum error = [ 0.8562, 0.8597, 0.8678, 0.8780, 0.8916] +24-11-19 20:28:38 | D | best error = [ 0.7917, 0.7879, 0.7853, 0.7835, 0.7818] +24-11-19 20:28:38 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:38 | D | sum error = [ 0.9122, 0.9357, 0.9651, 0.9992, 1.0382] +24-11-19 20:28:38 | D | best error = [ 0.7807, 0.7799, 0.7795, 0.7792, 0.7789] +24-11-19 20:28:38 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:38 | D | sum error = [ 1.0855, 1.1377, 1.1940, 1.2615, 1.3334] +24-11-19 20:28:38 | D | best error = [ 0.7788, 0.7787, 0.7786, 0.7785, 0.7785] +24-11-19 20:28:38 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:38 | D | sum error = [ 1.4112, 1.4983, 1.5953, 1.6979, 1.8089] +24-11-19 20:28:38 | D | best error = [ 0.7785, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 20:28:38 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:38 | D | sum error = [ 1.9289, 2.0588, 2.1980, 2.3471, 2.5060] +24-11-19 20:28:38 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 20:28:38 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:38 | D | sum error = [ 2.6767, 2.8584, 3.0519, 3.2576, 3.4738] +24-11-19 20:28:38 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 20:28:38 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:38 | D | sum error = [ 3.7082, 3.9552, 4.2176, 4.4950, 4.7877] +24-11-19 20:28:38 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 20:28:38 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:38 | D | sum error = [ 5.0993, 5.4286, 5.7777, 6.1456, 6.5351] +24-11-19 20:28:38 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 20:28:38 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:38 | D | sum error = [ 6.9448, 7.3762, 7.8331, 8.3138, 8.8180] +24-11-19 20:28:38 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 20:28:38 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:38 | D | sum error = [ 9.3495, 9.9091, 10.4961, 11.1142, 11.7623] +24-11-19 20:28:38 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 20:28:38 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:38 | D | sum error = [ 12.4423, 13.1557, 13.9033, 14.6871, 15.5071] +24-11-19 20:28:38 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 20:28:38 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:38 | D | sum error = [ 16.3646, 17.2609, 18.1968, 19.1743, 20.1938] +24-11-19 20:28:38 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 20:28:38 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:38 | D | sum error = [ 21.2582, 22.3676, 23.5234, 24.7262, 25.9754] +24-11-19 20:28:38 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 20:28:38 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:38 | D | sum error = [ 27.2751, 28.6268, 30.0286, 31.4829, 32.9920] +24-11-19 20:28:38 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 20:28:38 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:38 | D | sum error = [ 34.5562, 36.1769, 37.8524, 39.5853, 41.3766] +24-11-19 20:28:38 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 20:28:38 | D | + error = [0.7784] +24-11-19 20:28:38 | D | - Quantizing model.layers.15.self_attn.q_proj.weight +24-11-19 20:28:39 | D | - Quantizing model.layers.15.self_attn.k_proj.weight +24-11-19 20:28:40 | D | - Quantizing model.layers.15.self_attn.v_proj.weight +24-11-19 20:28:41 | D | - Quantizing model.layers.15.self_attn.o_proj.weight +24-11-19 20:28:41 | D | - Quantizing model.layers.15.mlp.up_proj.weight +24-11-19 20:28:42 | D | - Quantizing model.layers.15.mlp.gate_proj.weight +24-11-19 20:28:43 | D | - Quantizing model.layers.15.mlp.down_proj.weight +24-11-19 20:28:53 | D | - Quantizing layer model.layers.16 +24-11-19 20:28:53 | D | - Calibrating model.layers.16.self_attn.q_proj.weight +24-11-19 20:28:53 | D | + w: sint8 +24-11-19 20:28:53 | D | + x: None +24-11-19 20:28:53 | D | + y: None +24-11-19 20:28:53 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:28:53 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:53 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:53 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:53 | D | - range ratio = [ 1.0000] +24-11-19 20:28:53 | D | sum error = [ 4.4234] +24-11-19 20:28:53 | D | best error = [ 4.4234] +24-11-19 20:29:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:06 | D | sum error = [ 4.3615, 4.3577, 4.4877, 4.4679, 4.5473] +24-11-19 20:29:06 | D | best error = [ 4.3615, 4.3577, 4.3577, 4.3577, 4.3577] +24-11-19 20:29:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:06 | D | sum error = [ 4.7743, 4.9364, 5.0214, 5.3474, 5.6523] +24-11-19 20:29:06 | D | best error = [ 4.3577, 4.3577, 4.3577, 4.3577, 4.3577] +24-11-19 20:29:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:06 | D | sum error = [ 5.9903, 6.4366, 6.9819, 7.6103, 8.2384] +24-11-19 20:29:06 | D | best error = [ 4.3577, 4.3577, 4.3577, 4.3577, 4.3577] +24-11-19 20:29:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:06 | D | sum error = [ 9.1605, 9.7705, 10.6106, 11.6732, 12.5217] +24-11-19 20:29:06 | D | best error = [ 4.3577, 4.3577, 4.3577, 4.3577, 4.3577] +24-11-19 20:29:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:06 | D | sum error = [ 13.6215, 14.9997, 16.3840, 17.8401, 19.4598] +24-11-19 20:29:06 | D | best error = [ 4.3577, 4.3577, 4.3577, 4.3577, 4.3577] +24-11-19 20:29:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:06 | D | sum error = [ 21.1703, 23.1788, 25.0809, 27.5629, 30.0514] +24-11-19 20:29:06 | D | best error = [ 4.3577, 4.3577, 4.3577, 4.3577, 4.3577] +24-11-19 20:29:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:06 | D | sum error = [ 32.5221, 35.5055, 38.5902, 42.1724, 45.8339] +24-11-19 20:29:06 | D | best error = [ 4.3577, 4.3577, 4.3577, 4.3577, 4.3577] +24-11-19 20:29:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:06 | D | sum error = [ 49.5729, 53.6854, 57.9860, 62.6712, 67.6826] +24-11-19 20:29:06 | D | best error = [ 4.3577, 4.3577, 4.3577, 4.3577, 4.3577] +24-11-19 20:29:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:06 | D | sum error = [ 72.8904, 78.2667, 83.9975, 90.1860, 97.0834] +24-11-19 20:29:06 | D | best error = [ 4.3577, 4.3577, 4.3577, 4.3577, 4.3577] +24-11-19 20:29:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:06 | D | sum error = [ 104.2646, 111.6090, 119.3119, 127.9598, 137.2236] +24-11-19 20:29:06 | D | best error = [ 4.3577, 4.3577, 4.3577, 4.3577, 4.3577] +24-11-19 20:29:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:06 | D | sum error = [ 147.0848, 157.1110, 168.1349, 179.7769, 192.0218] +24-11-19 20:29:06 | D | best error = [ 4.3577, 4.3577, 4.3577, 4.3577, 4.3577] +24-11-19 20:29:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:06 | D | sum error = [ 205.3714, 219.2912, 233.7893, 249.2906, 265.5540] +24-11-19 20:29:06 | D | best error = [ 4.3577, 4.3577, 4.3577, 4.3577, 4.3577] +24-11-19 20:29:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:06 | D | sum error = [ 282.7789, 301.2772, 320.2694, 340.8283, 362.1042] +24-11-19 20:29:06 | D | best error = [ 4.3577, 4.3577, 4.3577, 4.3577, 4.3577] +24-11-19 20:29:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:06 | D | sum error = [ 384.7985, 408.3402, 433.1099, 459.3227, 486.7930] +24-11-19 20:29:06 | D | best error = [ 4.3577, 4.3577, 4.3577, 4.3577, 4.3577] +24-11-19 20:29:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:06 | D | sum error = [ 515.3431, 545.1445, 576.1487, 608.1873, 641.5362] +24-11-19 20:29:06 | D | best error = [ 4.3577, 4.3577, 4.3577, 4.3577, 4.3577] +24-11-19 20:29:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:06 | D | sum error = [ 675.5677, 710.5019, 746.5717, 783.0471, 820.2444] +24-11-19 20:29:06 | D | best error = [ 4.3577, 4.3577, 4.3577, 4.3577, 4.3577] +24-11-19 20:29:06 | D | + error = [4.3577] +24-11-19 20:29:06 | D | - Calibrating model.layers.16.self_attn.k_proj.weight +24-11-19 20:29:06 | D | + w: sint8 +24-11-19 20:29:06 | D | + x: None +24-11-19 20:29:06 | D | + y: None +24-11-19 20:29:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:29:06 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:29:06 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:29:07 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:07 | D | - range ratio = [ 1.0000] +24-11-19 20:29:07 | D | sum error = [ 4.0214] +24-11-19 20:29:07 | D | best error = [ 4.0214] +24-11-19 20:29:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:19 | D | sum error = [ 4.3328, 4.2877, 4.7040, 4.2593, 4.0483] +24-11-19 20:29:19 | D | best error = [ 4.0214, 4.0214, 4.0214, 4.0214, 4.0214] +24-11-19 20:29:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:19 | D | sum error = [ 4.8322, 4.6906, 4.3583, 4.5228, 5.7286] +24-11-19 20:29:19 | D | best error = [ 4.0214, 4.0214, 4.0214, 4.0214, 4.0214] +24-11-19 20:29:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:19 | D | sum error = [ 5.5482, 5.8312, 5.8492, 6.5155, 6.7314] +24-11-19 20:29:19 | D | best error = [ 4.0214, 4.0214, 4.0214, 4.0214, 4.0214] +24-11-19 20:29:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:19 | D | sum error = [ 7.1581, 7.9409, 7.9592, 8.5324, 9.4657] +24-11-19 20:29:19 | D | best error = [ 4.0214, 4.0214, 4.0214, 4.0214, 4.0214] +24-11-19 20:29:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:19 | D | sum error = [ 10.0160, 10.6195, 11.9372, 12.5449, 13.2898] +24-11-19 20:29:19 | D | best error = [ 4.0214, 4.0214, 4.0214, 4.0214, 4.0214] +24-11-19 20:29:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:19 | D | sum error = [ 14.6349, 15.5808, 17.3571, 18.7902, 20.1273] +24-11-19 20:29:19 | D | best error = [ 4.0214, 4.0214, 4.0214, 4.0214, 4.0214] +24-11-19 20:29:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:19 | D | sum error = [ 21.8262, 23.5779, 25.2468, 27.2855, 29.5864] +24-11-19 20:29:19 | D | best error = [ 4.0214, 4.0214, 4.0214, 4.0214, 4.0214] +24-11-19 20:29:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:19 | D | sum error = [ 31.6280, 34.6976, 36.5367, 39.9849, 42.5479] +24-11-19 20:29:19 | D | best error = [ 4.0214, 4.0214, 4.0214, 4.0214, 4.0214] +24-11-19 20:29:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:19 | D | sum error = [ 45.2167, 48.5466, 51.5594, 55.3567, 59.8745] +24-11-19 20:29:19 | D | best error = [ 4.0214, 4.0214, 4.0214, 4.0214, 4.0214] +24-11-19 20:29:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:19 | D | sum error = [ 64.0076, 69.1531, 74.5633, 81.2990, 87.8341] +24-11-19 20:29:19 | D | best error = [ 4.0214, 4.0214, 4.0214, 4.0214, 4.0214] +24-11-19 20:29:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:19 | D | sum error = [ 95.7101, 103.6987, 113.0742, 122.2507, 134.0480] +24-11-19 20:29:19 | D | best error = [ 4.0214, 4.0214, 4.0214, 4.0214, 4.0214] +24-11-19 20:29:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:19 | D | sum error = [ 146.3202, 159.7121, 173.6079, 187.3021, 203.3980] +24-11-19 20:29:19 | D | best error = [ 4.0214, 4.0214, 4.0214, 4.0214, 4.0214] +24-11-19 20:29:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:19 | D | sum error = [ 219.3872, 236.8088, 255.6794, 274.7906, 296.4715] +24-11-19 20:29:19 | D | best error = [ 4.0214, 4.0214, 4.0214, 4.0214, 4.0214] +24-11-19 20:29:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:19 | D | sum error = [ 319.1401, 343.6714, 368.9182, 395.7555, 424.4228] +24-11-19 20:29:19 | D | best error = [ 4.0214, 4.0214, 4.0214, 4.0214, 4.0214] +24-11-19 20:29:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:19 | D | sum error = [ 452.6426, 485.5438, 516.9589, 551.7693, 588.6836] +24-11-19 20:29:19 | D | best error = [ 4.0214, 4.0214, 4.0214, 4.0214, 4.0214] +24-11-19 20:29:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:19 | D | sum error = [ 624.6191, 664.1508, 702.7205, 744.5142, 785.0234] +24-11-19 20:29:19 | D | best error = [ 4.0214, 4.0214, 4.0214, 4.0214, 4.0214] +24-11-19 20:29:19 | D | + error = [4.0214] +24-11-19 20:29:19 | D | - Calibrating model.layers.16.self_attn.v_proj.weight +24-11-19 20:29:19 | D | + w: sint8 +24-11-19 20:29:19 | D | + x: None +24-11-19 20:29:19 | D | + y: None +24-11-19 20:29:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:19 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:29:19 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:29:20 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:20 | D | - range ratio = [ 1.0000] +24-11-19 20:29:20 | D | sum error = [ 1.4684] +24-11-19 20:29:20 | D | best error = [ 1.4684] +24-11-19 20:29:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:20 | D | sum error = [ 1.4495, 1.4511, 1.4634, 1.4705, 1.4987] +24-11-19 20:29:20 | D | best error = [ 1.3527, 1.3114, 1.2901, 1.2772, 1.2715] +24-11-19 20:29:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:20 | D | sum error = [ 1.5348, 1.5796, 1.6526, 1.7303, 1.8125] +24-11-19 20:29:20 | D | best error = [ 1.2679, 1.2666, 1.2662, 1.2661, 1.2661] +24-11-19 20:29:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:20 | D | sum error = [ 1.9114, 2.0451, 2.1738, 2.3228, 2.4733] +24-11-19 20:29:20 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:29:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:20 | D | sum error = [ 2.6629, 2.8524, 3.0449, 3.2737, 3.5265] +24-11-19 20:29:20 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:29:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:20 | D | sum error = [ 3.7742, 4.0547, 4.3473, 4.6355, 4.9618] +24-11-19 20:29:20 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:29:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:20 | D | sum error = [ 5.3262, 5.6923, 6.0863, 6.4865, 6.9205] +24-11-19 20:29:20 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:29:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:20 | D | sum error = [ 7.3765, 7.8677, 8.3755, 8.9044, 9.4811] +24-11-19 20:29:20 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:29:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:20 | D | sum error = [ 10.0833, 10.7146, 11.3799, 12.0823, 12.8090] +24-11-19 20:29:20 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:29:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:20 | D | sum error = [ 13.5890, 14.4035, 15.2503, 16.1477, 17.0878] +24-11-19 20:29:20 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:29:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:20 | D | sum error = [ 18.0693, 19.1068, 20.1735, 21.3055, 22.4922] +24-11-19 20:29:20 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:29:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:20 | D | sum error = [ 23.7137, 24.9925, 26.3373, 27.7393, 29.1915] +24-11-19 20:29:20 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:29:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:20 | D | sum error = [ 30.7107, 32.2970, 33.9409, 35.6503, 37.4318] +24-11-19 20:29:20 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:29:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:20 | D | sum error = [ 39.2886, 41.2219, 43.2288, 45.3218, 47.4853] +24-11-19 20:29:20 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:29:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:20 | D | sum error = [ 49.7334, 52.0643, 54.4689, 56.9744, 59.5755] +24-11-19 20:29:20 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:29:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:20 | D | sum error = [ 62.2579, 65.0308, 67.8959, 70.8487, 73.8983] +24-11-19 20:29:20 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:29:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:20 | D | sum error = [ 77.0455, 80.2909, 83.6497, 87.1062, 90.6616] +24-11-19 20:29:20 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:29:20 | D | + error = [1.2661] +24-11-19 20:29:20 | D | - Calibrating model.layers.16.self_attn.o_proj.weight +24-11-19 20:29:20 | D | + w: sint8 +24-11-19 20:29:20 | D | + x: None +24-11-19 20:29:20 | D | + y: None +24-11-19 20:29:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:20 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:29:20 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:29:20 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:20 | D | - range ratio = [ 1.0000] +24-11-19 20:29:20 | D | sum error = [ 0.6277] +24-11-19 20:29:20 | D | best error = [ 0.6277] +24-11-19 20:29:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:21 | D | sum error = [ 0.6227, 0.6200, 0.6189, 0.6152, 0.6179] +24-11-19 20:29:21 | D | best error = [ 0.5784, 0.5565, 0.5427, 0.5331, 0.5259] +24-11-19 20:29:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:21 | D | sum error = [ 0.6237, 0.6279, 0.6367, 0.6484, 0.6660] +24-11-19 20:29:21 | D | best error = [ 0.5207, 0.5156, 0.5123, 0.5093, 0.5072] +24-11-19 20:29:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:21 | D | sum error = [ 0.6839, 0.7058, 0.7315, 0.7626, 0.7973] +24-11-19 20:29:21 | D | best error = [ 0.5050, 0.5036, 0.5023, 0.5011, 0.5003] +24-11-19 20:29:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:21 | D | sum error = [ 0.8355, 0.8744, 0.9234, 0.9755, 1.0310] +24-11-19 20:29:21 | D | best error = [ 0.4996, 0.4989, 0.4984, 0.4980, 0.4977] +24-11-19 20:29:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:21 | D | sum error = [ 1.0907, 1.1555, 1.2243, 1.3005, 1.3817] +24-11-19 20:29:21 | D | best error = [ 0.4976, 0.4974, 0.4972, 0.4971, 0.4970] +24-11-19 20:29:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:21 | D | sum error = [ 1.4691, 1.5601, 1.6581, 1.7620, 1.8733] +24-11-19 20:29:21 | D | best error = [ 0.4970, 0.4970, 0.4969, 0.4969, 0.4969] +24-11-19 20:29:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:21 | D | sum error = [ 1.9895, 2.1162, 2.2465, 2.3873, 2.5321] +24-11-19 20:29:21 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:29:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:21 | D | sum error = [ 2.6886, 2.8546, 3.0269, 3.2091, 3.4016] +24-11-19 20:29:21 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:29:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:21 | D | sum error = [ 3.6054, 3.8184, 4.0475, 4.2828, 4.5336] +24-11-19 20:29:21 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:29:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:21 | D | sum error = [ 4.7990, 5.0758, 5.3651, 5.6739, 5.9945] +24-11-19 20:29:21 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:29:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:21 | D | sum error = [ 6.3288, 6.6787, 7.0475, 7.4311, 7.8325] +24-11-19 20:29:21 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:29:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:21 | D | sum error = [ 8.2518, 8.6895, 9.1474, 9.6254, 10.1230] +24-11-19 20:29:21 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:29:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:21 | D | sum error = [ 10.6432, 11.1859, 11.7526, 12.3427, 12.9580] +24-11-19 20:29:21 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:29:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:21 | D | sum error = [ 13.6002, 14.2687, 14.9626, 15.6869, 16.4351] +24-11-19 20:29:21 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:29:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:21 | D | sum error = [ 17.2129, 18.0224, 18.8638, 19.7366, 20.6424] +24-11-19 20:29:21 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:29:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:21 | D | sum error = [ 21.5787, 22.5522, 23.5585, 24.6012, 25.6824] +24-11-19 20:29:21 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:29:21 | D | + error = [0.4968] +24-11-19 20:29:21 | D | - Calibrating model.layers.16.mlp.up_proj.weight +24-11-19 20:29:21 | D | + w: sint8 +24-11-19 20:29:21 | D | + x: None +24-11-19 20:29:21 | D | + y: None +24-11-19 20:29:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:21 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:29:21 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:29:21 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:21 | D | - range ratio = [ 1.0000] +24-11-19 20:29:21 | D | sum error = [ 5.9252] +24-11-19 20:29:21 | D | best error = [ 5.9252] +24-11-19 20:29:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:22 | D | sum error = [ 5.8709, 5.8619, 5.8929, 5.9623, 6.0602] +24-11-19 20:29:22 | D | best error = [ 5.5095, 5.3476, 5.2629, 5.2147, 5.1900] +24-11-19 20:29:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:22 | D | sum error = [ 6.2224, 6.4193, 6.6830, 7.0000, 7.3702] +24-11-19 20:29:22 | D | best error = [ 5.1771, 5.1716, 5.1696, 5.1692, 5.1690] +24-11-19 20:29:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:22 | D | sum error = [ 7.7780, 8.2704, 8.7927, 9.3919, 10.0396] +24-11-19 20:29:22 | D | best error = [ 5.1690, 5.1690, 5.1690, 5.1690, 5.1690] +24-11-19 20:29:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:22 | D | sum error = [ 10.7521, 11.4993, 12.3188, 13.2022, 14.1520] +24-11-19 20:29:22 | D | best error = [ 5.1690, 5.1690, 5.1690, 5.1690, 5.1690] +24-11-19 20:29:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:22 | D | sum error = [ 15.1579, 16.2353, 17.3723, 18.6015, 19.8787] +24-11-19 20:29:22 | D | best error = [ 5.1690, 5.1690, 5.1690, 5.1690, 5.1690] +24-11-19 20:29:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:22 | D | sum error = [ 21.2458, 22.6768, 24.2182, 25.8339, 27.5516] +24-11-19 20:29:22 | D | best error = [ 5.1690, 5.1690, 5.1690, 5.1690, 5.1690] +24-11-19 20:29:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:22 | D | sum error = [ 29.3302, 31.2322, 33.2265, 35.3340, 37.5414] +24-11-19 20:29:22 | D | best error = [ 5.1690, 5.1690, 5.1690, 5.1690, 5.1690] +24-11-19 20:29:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:22 | D | sum error = [ 39.8759, 42.3322, 44.9103, 47.5983, 50.4525] +24-11-19 20:29:22 | D | best error = [ 5.1690, 5.1690, 5.1690, 5.1690, 5.1690] +24-11-19 20:29:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:22 | D | sum error = [ 53.4532, 56.5863, 59.8767, 63.3223, 66.9340] +24-11-19 20:29:22 | D | best error = [ 5.1690, 5.1690, 5.1690, 5.1690, 5.1690] +24-11-19 20:29:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:22 | D | sum error = [ 70.7164, 74.6736, 78.8163, 83.1519, 87.6800] +24-11-19 20:29:22 | D | best error = [ 5.1690, 5.1690, 5.1690, 5.1690, 5.1690] +24-11-19 20:29:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:22 | D | sum error = [ 92.4031, 97.3335, 102.4847, 107.8564, 113.4470] +24-11-19 20:29:22 | D | best error = [ 5.1690, 5.1690, 5.1690, 5.1690, 5.1690] +24-11-19 20:29:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:22 | D | sum error = [ 119.2696, 125.3229, 131.6338, 138.1896, 144.9934] +24-11-19 20:29:22 | D | best error = [ 5.1690, 5.1690, 5.1690, 5.1690, 5.1690] +24-11-19 20:29:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:22 | D | sum error = [ 152.0722, 159.4084, 167.0246, 174.9074, 183.0966] +24-11-19 20:29:22 | D | best error = [ 5.1690, 5.1690, 5.1690, 5.1690, 5.1690] +24-11-19 20:29:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:22 | D | sum error = [ 191.5729, 200.3584, 209.4587, 218.8574, 228.5890] +24-11-19 20:29:22 | D | best error = [ 5.1690, 5.1690, 5.1690, 5.1690, 5.1690] +24-11-19 20:29:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:22 | D | sum error = [ 238.6420, 249.0269, 259.7459, 270.8148, 282.2115] +24-11-19 20:29:22 | D | best error = [ 5.1690, 5.1690, 5.1690, 5.1690, 5.1690] +24-11-19 20:29:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:22 | D | sum error = [ 293.9715, 306.0825, 318.5279, 331.3504, 344.5286] +24-11-19 20:29:22 | D | best error = [ 5.1690, 5.1690, 5.1690, 5.1690, 5.1690] +24-11-19 20:29:22 | D | + error = [5.1690] +24-11-19 20:29:22 | D | - Calibrating model.layers.16.mlp.gate_proj.weight +24-11-19 20:29:22 | D | + w: sint8 +24-11-19 20:29:22 | D | + x: None +24-11-19 20:29:22 | D | + y: None +24-11-19 20:29:22 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:22 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:29:22 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:29:22 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:29:22 | D | - range ratio = [ 1.0000] +24-11-19 20:29:22 | D | sum error = [ 7.7747] +24-11-19 20:29:22 | D | best error = [ 7.7747] +24-11-19 20:29:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:23 | D | sum error = [ 7.6983, 7.6781, 7.7148, 7.8141, 7.9645] +24-11-19 20:29:23 | D | best error = [ 7.2204, 7.0131, 6.9007, 6.8400, 6.8061] +24-11-19 20:29:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:23 | D | sum error = [ 8.1477, 8.4545, 8.7967, 9.2110, 9.7069] +24-11-19 20:29:23 | D | best error = [ 6.7892, 6.7830, 6.7801, 6.7793, 6.7792] +24-11-19 20:29:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:23 | D | sum error = [ 10.2834, 10.9297, 11.6474, 12.4713, 13.3167] +24-11-19 20:29:23 | D | best error = [ 6.7790, 6.7790, 6.7790, 6.7790, 6.7790] +24-11-19 20:29:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:23 | D | sum error = [ 14.2946, 15.3544, 16.4904, 17.6990, 19.0170] +24-11-19 20:29:23 | D | best error = [ 6.7790, 6.7790, 6.7790, 6.7790, 6.7790] +24-11-19 20:29:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:23 | D | sum error = [ 20.4309, 21.9268, 23.5459, 25.2746, 27.0733] +24-11-19 20:29:23 | D | best error = [ 6.7790, 6.7790, 6.7790, 6.7790, 6.7790] +24-11-19 20:29:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:23 | D | sum error = [ 29.0323, 31.1106, 33.3446, 35.6833, 38.2193] +24-11-19 20:29:23 | D | best error = [ 6.7790, 6.7790, 6.7790, 6.7790, 6.7790] +24-11-19 20:29:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:23 | D | sum error = [ 40.8819, 43.7113, 46.7525, 49.9639, 53.4077] +24-11-19 20:29:23 | D | best error = [ 6.7790, 6.7790, 6.7790, 6.7790, 6.7790] +24-11-19 20:29:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:23 | D | sum error = [ 57.0391, 60.9150, 65.0293, 69.3950, 74.0134] +24-11-19 20:29:23 | D | best error = [ 6.7790, 6.7790, 6.7790, 6.7790, 6.7790] +24-11-19 20:29:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:23 | D | sum error = [ 78.9324, 84.1715, 89.7125, 95.5798, 101.8140] +24-11-19 20:29:23 | D | best error = [ 6.7790, 6.7790, 6.7790, 6.7790, 6.7790] +24-11-19 20:29:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:23 | D | sum error = [ 108.4323, 115.4391, 122.8707, 130.7495, 139.0921] +24-11-19 20:29:23 | D | best error = [ 6.7790, 6.7790, 6.7790, 6.7790, 6.7790] +24-11-19 20:29:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:23 | D | sum error = [ 147.9049, 157.2431, 167.1295, 177.5718, 188.5842] +24-11-19 20:29:23 | D | best error = [ 6.7790, 6.7790, 6.7790, 6.7790, 6.7790] +24-11-19 20:29:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:23 | D | sum error = [ 200.1952, 212.4628, 225.3880, 238.9809, 253.2937] +24-11-19 20:29:23 | D | best error = [ 6.7790, 6.7790, 6.7790, 6.7790, 6.7790] +24-11-19 20:29:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:23 | D | sum error = [ 268.3473, 284.1628, 300.7393, 318.1477, 336.3912] +24-11-19 20:29:23 | D | best error = [ 6.7790, 6.7790, 6.7790, 6.7790, 6.7790] +24-11-19 20:29:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:23 | D | sum error = [ 355.4789, 375.4430, 396.2960, 418.0895, 440.7518] +24-11-19 20:29:23 | D | best error = [ 6.7790, 6.7790, 6.7790, 6.7790, 6.7790] +24-11-19 20:29:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:23 | D | sum error = [ 464.3843, 488.9739, 514.5134, 541.0253, 568.5356] +24-11-19 20:29:23 | D | best error = [ 6.7790, 6.7790, 6.7790, 6.7790, 6.7790] +24-11-19 20:29:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:23 | D | sum error = [ 597.0345, 626.5328, 657.0010, 688.4612, 720.9258] +24-11-19 20:29:23 | D | best error = [ 6.7790, 6.7790, 6.7790, 6.7790, 6.7790] +24-11-19 20:29:23 | D | + error = [6.7790] +24-11-19 20:29:24 | D | - Calibrating model.layers.16.mlp.down_proj.weight +24-11-19 20:29:24 | D | + w: sint8 +24-11-19 20:29:24 | D | + x: None +24-11-19 20:29:24 | D | + y: None +24-11-19 20:29:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:24 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:29:24 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:29:24 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:29:24 | D | - range ratio = [ 1.0000] +24-11-19 20:29:24 | D | sum error = [ 0.8971] +24-11-19 20:29:24 | D | best error = [ 0.8971] +24-11-19 20:29:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:25 | D | sum error = [ 0.8891, 0.8831, 0.8789, 0.8766, 0.8738] +24-11-19 20:29:25 | D | best error = [ 0.8583, 0.8395, 0.8280, 0.8194, 0.8126] +24-11-19 20:29:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:25 | D | sum error = [ 0.8759, 0.8810, 0.8906, 0.9009, 0.9184] +24-11-19 20:29:25 | D | best error = [ 0.8074, 0.8033, 0.8002, 0.7978, 0.7959] +24-11-19 20:29:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:25 | D | sum error = [ 0.9361, 0.9633, 0.9942, 1.0290, 1.0697] +24-11-19 20:29:25 | D | best error = [ 0.7945, 0.7937, 0.7930, 0.7926, 0.7923] +24-11-19 20:29:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:25 | D | sum error = [ 1.1145, 1.1711, 1.2314, 1.2985, 1.3710] +24-11-19 20:29:25 | D | best error = [ 0.7922, 0.7921, 0.7920, 0.7919, 0.7919] +24-11-19 20:29:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:25 | D | sum error = [ 1.4532, 1.5433, 1.6404, 1.7470, 1.8600] +24-11-19 20:29:25 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 20:29:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:25 | D | sum error = [ 1.9867, 2.1193, 2.2619, 2.4164, 2.5809] +24-11-19 20:29:25 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 20:29:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:25 | D | sum error = [ 2.7562, 2.9439, 3.1432, 3.3572, 3.5834] +24-11-19 20:29:25 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 20:29:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:25 | D | sum error = [ 3.8251, 4.0816, 4.3527, 4.6397, 4.9454] +24-11-19 20:29:25 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 20:29:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:25 | D | sum error = [ 5.2686, 5.6108, 5.9708, 6.3514, 6.7546] +24-11-19 20:29:25 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 20:29:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:25 | D | sum error = [ 7.1800, 7.6278, 8.1001, 8.5964, 9.1213] +24-11-19 20:29:25 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 20:29:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:25 | D | sum error = [ 9.6717, 10.2510, 10.8602, 11.5010, 12.1738] +24-11-19 20:29:25 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 20:29:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:25 | D | sum error = [ 12.8821, 13.6241, 14.4027, 15.2177, 16.0716] +24-11-19 20:29:25 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 20:29:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:25 | D | sum error = [ 16.9659, 17.9006, 18.8791, 19.9013, 20.9691] +24-11-19 20:29:25 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 20:29:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:25 | D | sum error = [ 22.0827, 23.2441, 24.4541, 25.7148, 27.0245] +24-11-19 20:29:25 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 20:29:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:25 | D | sum error = [ 28.3886, 29.8080, 31.2846, 32.8172, 34.4087] +24-11-19 20:29:25 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 20:29:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:25 | D | sum error = [ 36.0591, 37.7668, 39.5346, 41.3632, 43.2516] +24-11-19 20:29:25 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 20:29:25 | D | + error = [0.7918] +24-11-19 20:29:25 | D | - Quantizing model.layers.16.self_attn.q_proj.weight +24-11-19 20:29:26 | D | - Quantizing model.layers.16.self_attn.k_proj.weight +24-11-19 20:29:27 | D | - Quantizing model.layers.16.self_attn.v_proj.weight +24-11-19 20:29:28 | D | - Quantizing model.layers.16.self_attn.o_proj.weight +24-11-19 20:29:28 | D | - Quantizing model.layers.16.mlp.up_proj.weight +24-11-19 20:29:29 | D | - Quantizing model.layers.16.mlp.gate_proj.weight +24-11-19 20:29:30 | D | - Quantizing model.layers.16.mlp.down_proj.weight +24-11-19 20:29:40 | D | - Quantizing layer model.layers.17 +24-11-19 20:29:40 | D | - Calibrating model.layers.17.self_attn.q_proj.weight +24-11-19 20:29:40 | D | + w: sint8 +24-11-19 20:29:40 | D | + x: None +24-11-19 20:29:40 | D | + y: None +24-11-19 20:29:40 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:29:40 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:29:40 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:29:40 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:40 | D | - range ratio = [ 1.0000] +24-11-19 20:29:40 | D | sum error = [ 4.1912] +24-11-19 20:29:40 | D | best error = [ 4.1912] +24-11-19 20:29:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:52 | D | sum error = [ 4.1657, 4.0980, 4.1650, 4.2704, 4.3905] +24-11-19 20:29:52 | D | best error = [ 4.1657, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:29:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:52 | D | sum error = [ 4.3729, 4.5455, 4.9290, 4.9933, 5.3771] +24-11-19 20:29:52 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:29:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:52 | D | sum error = [ 5.5719, 5.9197, 6.5259, 6.8833, 7.5524] +24-11-19 20:29:52 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:29:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:52 | D | sum error = [ 8.0910, 8.8570, 9.5547, 10.3539, 11.1045] +24-11-19 20:29:52 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:29:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:52 | D | sum error = [ 11.9331, 13.0222, 14.0267, 15.2829, 16.4715] +24-11-19 20:29:52 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:29:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:52 | D | sum error = [ 17.9007, 19.4031, 21.0382, 22.5891, 24.6326] +24-11-19 20:29:52 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:29:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:52 | D | sum error = [ 26.6692, 28.8607, 31.1758, 33.6663, 36.5447] +24-11-19 20:29:52 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:29:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:52 | D | sum error = [ 39.3149, 42.5667, 45.9115, 49.6798, 53.7786] +24-11-19 20:29:52 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:29:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:52 | D | sum error = [ 58.0199, 62.4883, 67.5091, 72.8190, 78.4530] +24-11-19 20:29:52 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:29:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:52 | D | sum error = [ 84.5756, 90.9120, 97.7171, 105.2680, 113.2955] +24-11-19 20:29:52 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:29:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:52 | D | sum error = [ 121.8786, 131.2775, 141.3910, 152.0320, 163.6536] +24-11-19 20:29:52 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:29:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:52 | D | sum error = [ 175.9351, 189.0061, 203.1432, 218.3152, 234.4861] +24-11-19 20:29:52 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:29:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:52 | D | sum error = [ 252.0285, 270.6637, 290.6012, 311.9284, 335.0970] +24-11-19 20:29:52 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:29:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:52 | D | sum error = [ 359.6799, 386.1999, 414.5992, 444.7932, 476.5519] +24-11-19 20:29:52 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:29:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:52 | D | sum error = [ 510.1374, 545.3187, 582.3446, 621.1387, 661.7564] +24-11-19 20:29:52 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:29:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:52 | D | sum error = [ 703.5519, 746.8550, 791.2600, 836.2363, 881.3481] +24-11-19 20:29:52 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:29:52 | D | + error = [4.0980] +24-11-19 20:29:52 | D | - Calibrating model.layers.17.self_attn.k_proj.weight +24-11-19 20:29:52 | D | + w: sint8 +24-11-19 20:29:52 | D | + x: None +24-11-19 20:29:52 | D | + y: None +24-11-19 20:29:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:29:52 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:29:52 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:29:53 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:53 | D | - range ratio = [ 1.0000] +24-11-19 20:29:53 | D | sum error = [ 3.7504] +24-11-19 20:29:53 | D | best error = [ 3.7504] +24-11-19 20:30:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:05 | D | sum error = [ 3.5801, 3.8482, 3.8110, 3.9371, 4.4926] +24-11-19 20:30:05 | D | best error = [ 3.5801, 3.5801, 3.5801, 3.5801, 3.5801] +24-11-19 20:30:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:05 | D | sum error = [ 4.1095, 4.3962, 5.0414, 4.3609, 4.6656] +24-11-19 20:30:05 | D | best error = [ 3.5801, 3.5801, 3.5801, 3.5801, 3.5801] +24-11-19 20:30:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:05 | D | sum error = [ 5.0086, 5.8199, 5.5691, 5.9104, 7.4879] +24-11-19 20:30:05 | D | best error = [ 3.5801, 3.5801, 3.5801, 3.5801, 3.5801] +24-11-19 20:30:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:05 | D | sum error = [ 7.3980, 8.0650, 8.4944, 9.0525, 9.5102] +24-11-19 20:30:05 | D | best error = [ 3.5801, 3.5801, 3.5801, 3.5801, 3.5801] +24-11-19 20:30:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:05 | D | sum error = [ 10.4413, 11.4221, 12.0212, 13.5046, 14.3876] +24-11-19 20:30:05 | D | best error = [ 3.5801, 3.5801, 3.5801, 3.5801, 3.5801] +24-11-19 20:30:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:05 | D | sum error = [ 15.6076, 17.0890, 18.0760, 19.8248, 21.4858] +24-11-19 20:30:05 | D | best error = [ 3.5801, 3.5801, 3.5801, 3.5801, 3.5801] +24-11-19 20:30:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:05 | D | sum error = [ 22.4778, 24.7488, 27.2008, 29.0543, 30.7939] +24-11-19 20:30:05 | D | best error = [ 3.5801, 3.5801, 3.5801, 3.5801, 3.5801] +24-11-19 20:30:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:05 | D | sum error = [ 33.3121, 36.2787, 38.2309, 41.0447, 45.1573] +24-11-19 20:30:05 | D | best error = [ 3.5801, 3.5801, 3.5801, 3.5801, 3.5801] +24-11-19 20:30:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:05 | D | sum error = [ 47.9687, 51.7084, 55.5518, 59.8743, 63.7832] +24-11-19 20:30:05 | D | best error = [ 3.5801, 3.5801, 3.5801, 3.5801, 3.5801] +24-11-19 20:30:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:05 | D | sum error = [ 68.4356, 73.5203, 79.0504, 84.0972, 89.8032] +24-11-19 20:30:05 | D | best error = [ 3.5801, 3.5801, 3.5801, 3.5801, 3.5801] +24-11-19 20:30:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:05 | D | sum error = [ 96.3228, 103.1375, 111.2050, 119.8217, 128.9805] +24-11-19 20:30:05 | D | best error = [ 3.5801, 3.5801, 3.5801, 3.5801, 3.5801] +24-11-19 20:30:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:05 | D | sum error = [ 138.9913, 149.7756, 161.7760, 174.8598, 188.7120] +24-11-19 20:30:05 | D | best error = [ 3.5801, 3.5801, 3.5801, 3.5801, 3.5801] +24-11-19 20:30:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:05 | D | sum error = [ 204.5971, 221.0141, 239.5512, 258.6899, 279.3150] +24-11-19 20:30:05 | D | best error = [ 3.5801, 3.5801, 3.5801, 3.5801, 3.5801] +24-11-19 20:30:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:05 | D | sum error = [ 302.3646, 326.8354, 352.3821, 380.8808, 411.2557] +24-11-19 20:30:05 | D | best error = [ 3.5801, 3.5801, 3.5801, 3.5801, 3.5801] +24-11-19 20:30:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:05 | D | sum error = [ 442.3521, 477.0676, 512.6710, 551.6877, 591.7324] +24-11-19 20:30:05 | D | best error = [ 3.5801, 3.5801, 3.5801, 3.5801, 3.5801] +24-11-19 20:30:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:05 | D | sum error = [ 634.1558, 677.8829, 723.3617, 770.1872, 818.5397] +24-11-19 20:30:05 | D | best error = [ 3.5801, 3.5801, 3.5801, 3.5801, 3.5801] +24-11-19 20:30:05 | D | + error = [3.5801] +24-11-19 20:30:05 | D | - Calibrating model.layers.17.self_attn.v_proj.weight +24-11-19 20:30:05 | D | + w: sint8 +24-11-19 20:30:05 | D | + x: None +24-11-19 20:30:05 | D | + y: None +24-11-19 20:30:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:05 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:05 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:30:05 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:30:05 | D | - range ratio = [ 1.0000] +24-11-19 20:30:05 | D | sum error = [ 1.6668] +24-11-19 20:30:05 | D | best error = [ 1.6668] +24-11-19 20:30:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:06 | D | sum error = [ 1.6654, 1.6562, 1.6655, 1.6857, 1.7150] +24-11-19 20:30:06 | D | best error = [ 1.5438, 1.4955, 1.4715, 1.4579, 1.4506] +24-11-19 20:30:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:06 | D | sum error = [ 1.7561, 1.8143, 1.8831, 1.9786, 2.0718] +24-11-19 20:30:06 | D | best error = [ 1.4458, 1.4436, 1.4433, 1.4432, 1.4431] +24-11-19 20:30:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:06 | D | sum error = [ 2.2084, 2.3452, 2.4995, 2.6596, 2.8357] +24-11-19 20:30:06 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 20:30:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:06 | D | sum error = [ 3.0479, 3.2494, 3.4911, 3.7507, 4.0037] +24-11-19 20:30:06 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 20:30:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:06 | D | sum error = [ 4.2903, 4.5823, 4.9049, 5.2597, 5.6157] +24-11-19 20:30:06 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 20:30:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:06 | D | sum error = [ 5.9928, 6.3969, 6.8402, 7.2726, 7.7408] +24-11-19 20:30:06 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 20:30:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:06 | D | sum error = [ 8.2470, 8.7805, 9.3368, 9.9352, 10.5504] +24-11-19 20:30:06 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 20:30:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:06 | D | sum error = [ 11.2153, 11.8871, 12.6127, 13.3551, 14.1364] +24-11-19 20:30:06 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 20:30:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:06 | D | sum error = [ 14.9726, 15.8465, 16.7661, 17.7242, 18.7272] +24-11-19 20:30:06 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 20:30:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:06 | D | sum error = [ 19.7846, 20.8915, 22.0463, 23.2527, 24.5139] +24-11-19 20:30:06 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 20:30:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:06 | D | sum error = [ 25.8141, 27.1847, 28.5965, 30.0768, 31.6220] +24-11-19 20:30:06 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 20:30:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:06 | D | sum error = [ 33.2170, 34.8803, 36.6094, 38.3844, 40.2369] +24-11-19 20:30:06 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 20:30:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:06 | D | sum error = [ 42.1581, 44.1559, 46.2217, 48.3620, 50.5677] +24-11-19 20:30:06 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 20:30:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:06 | D | sum error = [ 52.8628, 55.2303, 57.6865, 60.2425, 62.8707] +24-11-19 20:30:06 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 20:30:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:06 | D | sum error = [ 65.5973, 68.3816, 71.2626, 74.2332, 77.2800] +24-11-19 20:30:06 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 20:30:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:06 | D | sum error = [ 80.4271, 83.6595, 86.9896, 90.4009, 93.9033] +24-11-19 20:30:06 | D | best error = [ 1.4431, 1.4431, 1.4431, 1.4431, 1.4431] +24-11-19 20:30:06 | D | + error = [1.4431] +24-11-19 20:30:06 | D | - Calibrating model.layers.17.self_attn.o_proj.weight +24-11-19 20:30:06 | D | + w: sint8 +24-11-19 20:30:06 | D | + x: None +24-11-19 20:30:06 | D | + y: None +24-11-19 20:30:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:06 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:06 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:30:06 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:30:06 | D | - range ratio = [ 1.0000] +24-11-19 20:30:06 | D | sum error = [ 0.6015] +24-11-19 20:30:06 | D | best error = [ 0.6015] +24-11-19 20:30:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:06 | D | sum error = [ 0.5980, 0.5916, 0.5862, 0.5858, 0.5807] +24-11-19 20:30:06 | D | best error = [ 0.5533, 0.5312, 0.5166, 0.5056, 0.4978] +24-11-19 20:30:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:06 | D | sum error = [ 0.5811, 0.5844, 0.5822, 0.5896, 0.5960] +24-11-19 20:30:06 | D | best error = [ 0.4915, 0.4865, 0.4824, 0.4789, 0.4762] +24-11-19 20:30:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:06 | D | sum error = [ 0.6033, 0.6143, 0.6273, 0.6404, 0.6582] +24-11-19 20:30:06 | D | best error = [ 0.4740, 0.4723, 0.4710, 0.4698, 0.4688] +24-11-19 20:30:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:06 | D | sum error = [ 0.6765, 0.6999, 0.7224, 0.7509, 0.7822] +24-11-19 20:30:06 | D | best error = [ 0.4678, 0.4669, 0.4663, 0.4658, 0.4654] +24-11-19 20:30:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:06 | D | sum error = [ 0.8122, 0.8503, 0.8868, 0.9303, 0.9774] +24-11-19 20:30:06 | D | best error = [ 0.4651, 0.4648, 0.4645, 0.4643, 0.4641] +24-11-19 20:30:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:06 | D | sum error = [ 1.0246, 1.0742, 1.1327, 1.1914, 1.2509] +24-11-19 20:30:06 | D | best error = [ 0.4640, 0.4638, 0.4637, 0.4636, 0.4635] +24-11-19 20:30:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:06 | D | sum error = [ 1.3211, 1.3886, 1.4615, 1.5410, 1.6243] +24-11-19 20:30:06 | D | best error = [ 0.4635, 0.4635, 0.4634, 0.4634, 0.4634] +24-11-19 20:30:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:06 | D | sum error = [ 1.7121, 1.8069, 1.9071, 2.0101, 2.1211] +24-11-19 20:30:06 | D | best error = [ 0.4634, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:30:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:06 | D | sum error = [ 2.2379, 2.3621, 2.4936, 2.6330, 2.7805] +24-11-19 20:30:06 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:30:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:06 | D | sum error = [ 2.9380, 3.1036, 3.2776, 3.4624, 3.6597] +24-11-19 20:30:06 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:30:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:06 | D | sum error = [ 3.8684, 4.0877, 4.3216, 4.5685, 4.8312] +24-11-19 20:30:06 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:30:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:06 | D | sum error = [ 5.1073, 5.4031, 5.7119, 6.0387, 6.3839] +24-11-19 20:30:06 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:30:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:06 | D | sum error = [ 6.7482, 7.1344, 7.5413, 7.9701, 8.4227] +24-11-19 20:30:06 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:30:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:06 | D | sum error = [ 8.8974, 9.3977, 9.9229, 10.4795, 11.0620] +24-11-19 20:30:06 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:30:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:06 | D | sum error = [ 11.6758, 12.3184, 12.9951, 13.7045, 14.4473] +24-11-19 20:30:06 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:30:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:06 | D | sum error = [ 15.2263, 16.0402, 16.8894, 17.7778, 18.7065] +24-11-19 20:30:06 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:30:06 | D | + error = [0.4633] +24-11-19 20:30:07 | D | - Calibrating model.layers.17.mlp.up_proj.weight +24-11-19 20:30:07 | D | + w: sint8 +24-11-19 20:30:07 | D | + x: None +24-11-19 20:30:07 | D | + y: None +24-11-19 20:30:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:07 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:07 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:30:07 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:30:07 | D | - range ratio = [ 1.0000] +24-11-19 20:30:07 | D | sum error = [ 6.0977] +24-11-19 20:30:07 | D | best error = [ 6.0977] +24-11-19 20:30:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:08 | D | sum error = [ 6.0669, 6.0418, 6.0688, 6.1281, 6.2540] +24-11-19 20:30:08 | D | best error = [ 5.6622, 5.4883, 5.3962, 5.3445, 5.3193] +24-11-19 20:30:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:08 | D | sum error = [ 6.3970, 6.6280, 6.8992, 7.2203, 7.5989] +24-11-19 20:30:08 | D | best error = [ 5.3066, 5.3009, 5.2988, 5.2982, 5.2979] +24-11-19 20:30:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:08 | D | sum error = [ 8.0352, 8.5257, 9.0861, 9.7061, 10.3661] +24-11-19 20:30:08 | D | best error = [ 5.2979, 5.2979, 5.2979, 5.2979, 5.2979] +24-11-19 20:30:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:08 | D | sum error = [ 11.0905, 11.8834, 12.7065, 13.6188, 14.5913] +24-11-19 20:30:08 | D | best error = [ 5.2979, 5.2979, 5.2979, 5.2979, 5.2979] +24-11-19 20:30:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:08 | D | sum error = [ 15.6320, 16.7420, 17.9370, 19.1724, 20.5082] +24-11-19 20:30:08 | D | best error = [ 5.2979, 5.2979, 5.2979, 5.2979, 5.2979] +24-11-19 20:30:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:08 | D | sum error = [ 21.9067, 23.3930, 24.9701, 26.6360, 28.3782] +24-11-19 20:30:08 | D | best error = [ 5.2979, 5.2979, 5.2979, 5.2979, 5.2979] +24-11-19 20:30:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:08 | D | sum error = [ 30.2426, 32.2074, 34.2560, 36.4167, 38.7193] +24-11-19 20:30:08 | D | best error = [ 5.2979, 5.2979, 5.2979, 5.2979, 5.2979] +24-11-19 20:30:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:08 | D | sum error = [ 41.1257, 43.6417, 46.3231, 49.1311, 52.0686] +24-11-19 20:30:08 | D | best error = [ 5.2979, 5.2979, 5.2979, 5.2979, 5.2979] +24-11-19 20:30:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:08 | D | sum error = [ 55.1758, 58.4010, 61.8026, 65.3775, 69.1106] +24-11-19 20:30:08 | D | best error = [ 5.2979, 5.2979, 5.2979, 5.2979, 5.2979] +24-11-19 20:30:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:08 | D | sum error = [ 73.0131, 77.0928, 81.3643, 85.8295, 90.4990] +24-11-19 20:30:08 | D | best error = [ 5.2979, 5.2979, 5.2979, 5.2979, 5.2979] +24-11-19 20:30:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:08 | D | sum error = [ 95.3876, 100.4851, 105.8086, 111.3570, 117.1535] +24-11-19 20:30:08 | D | best error = [ 5.2979, 5.2979, 5.2979, 5.2979, 5.2979] +24-11-19 20:30:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:08 | D | sum error = [ 123.1838, 129.4660, 136.0121, 142.8232, 149.8905] +24-11-19 20:30:08 | D | best error = [ 5.2979, 5.2979, 5.2979, 5.2979, 5.2979] +24-11-19 20:30:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:08 | D | sum error = [ 157.2308, 164.8674, 172.7787, 180.9881, 189.5043] +24-11-19 20:30:08 | D | best error = [ 5.2979, 5.2979, 5.2979, 5.2979, 5.2979] +24-11-19 20:30:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:08 | D | sum error = [ 198.3243, 207.4474, 216.8899, 226.6497, 236.7528] +24-11-19 20:30:08 | D | best error = [ 5.2979, 5.2979, 5.2979, 5.2979, 5.2979] +24-11-19 20:30:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:08 | D | sum error = [ 247.1875, 257.9724, 269.0993, 280.5821, 292.4166] +24-11-19 20:30:08 | D | best error = [ 5.2979, 5.2979, 5.2979, 5.2979, 5.2979] +24-11-19 20:30:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:08 | D | sum error = [ 304.6262, 317.1997, 330.1550, 343.4748, 357.1647] +24-11-19 20:30:08 | D | best error = [ 5.2979, 5.2979, 5.2979, 5.2979, 5.2979] +24-11-19 20:30:08 | D | + error = [5.2979] +24-11-19 20:30:08 | D | - Calibrating model.layers.17.mlp.gate_proj.weight +24-11-19 20:30:08 | D | + w: sint8 +24-11-19 20:30:08 | D | + x: None +24-11-19 20:30:08 | D | + y: None +24-11-19 20:30:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:08 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:08 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:30:08 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:30:08 | D | - range ratio = [ 1.0000] +24-11-19 20:30:08 | D | sum error = [ 8.1035] +24-11-19 20:30:08 | D | best error = [ 8.1035] +24-11-19 20:30:10 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:10 | D | sum error = [ 8.0413, 8.0430, 8.0739, 8.1555, 8.3148] +24-11-19 20:30:10 | D | best error = [ 7.5239, 7.3039, 7.1851, 7.1159, 7.0809] +24-11-19 20:30:10 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:10 | D | sum error = [ 8.5185, 8.8329, 9.1862, 9.6501, 10.1427] +24-11-19 20:30:10 | D | best error = [ 7.0628, 7.0551, 7.0521, 7.0511, 7.0507] +24-11-19 20:30:10 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:10 | D | sum error = [ 10.7626, 11.4116, 12.1669, 13.0057, 13.9311] +24-11-19 20:30:10 | D | best error = [ 7.0507, 7.0507, 7.0507, 7.0507, 7.0507] +24-11-19 20:30:10 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:10 | D | sum error = [ 14.9105, 16.0049, 17.2012, 18.4812, 19.8112] +24-11-19 20:30:10 | D | best error = [ 7.0507, 7.0507, 7.0507, 7.0507, 7.0507] +24-11-19 20:30:10 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:10 | D | sum error = [ 21.2876, 22.8186, 24.4993, 26.2932, 28.1674] +24-11-19 20:30:10 | D | best error = [ 7.0507, 7.0507, 7.0507, 7.0507, 7.0507] +24-11-19 20:30:10 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:10 | D | sum error = [ 30.2011, 32.3551, 34.6345, 37.0816, 39.6793] +24-11-19 20:30:10 | D | best error = [ 7.0507, 7.0507, 7.0507, 7.0507, 7.0507] +24-11-19 20:30:10 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:10 | D | sum error = [ 42.4137, 45.3526, 48.4816, 51.7913, 55.2983] +24-11-19 20:30:10 | D | best error = [ 7.0507, 7.0507, 7.0507, 7.0507, 7.0507] +24-11-19 20:30:10 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:10 | D | sum error = [ 59.0568, 62.9989, 67.2527, 71.7089, 76.4472] +24-11-19 20:30:10 | D | best error = [ 7.0507, 7.0507, 7.0507, 7.0507, 7.0507] +24-11-19 20:30:10 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:10 | D | sum error = [ 81.4747, 86.8458, 92.5190, 98.5233, 104.8839] +24-11-19 20:30:10 | D | best error = [ 7.0507, 7.0507, 7.0507, 7.0507, 7.0507] +24-11-19 20:30:10 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:10 | D | sum error = [ 111.6587, 118.8270, 126.3910, 134.4073, 142.8918] +24-11-19 20:30:10 | D | best error = [ 7.0507, 7.0507, 7.0507, 7.0507, 7.0507] +24-11-19 20:30:10 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:10 | D | sum error = [ 151.8779, 161.3712, 171.4011, 181.9993, 193.1694] +24-11-19 20:30:10 | D | best error = [ 7.0507, 7.0507, 7.0507, 7.0507, 7.0507] +24-11-19 20:30:10 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:10 | D | sum error = [ 204.9828, 217.4566, 230.5724, 244.3796, 258.8812] +24-11-19 20:30:10 | D | best error = [ 7.0507, 7.0507, 7.0507, 7.0507, 7.0507] +24-11-19 20:30:10 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:10 | D | sum error = [ 274.1403, 290.1717, 306.9621, 324.5957, 343.0655] +24-11-19 20:30:10 | D | best error = [ 7.0507, 7.0507, 7.0507, 7.0507, 7.0507] +24-11-19 20:30:10 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:10 | D | sum error = [ 362.3406, 382.5195, 403.5909, 425.5699, 448.4693] +24-11-19 20:30:10 | D | best error = [ 7.0507, 7.0507, 7.0507, 7.0507, 7.0507] +24-11-19 20:30:10 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:10 | D | sum error = [ 472.3409, 497.1602, 522.9715, 549.7364, 577.4998] +24-11-19 20:30:10 | D | best error = [ 7.0507, 7.0507, 7.0507, 7.0507, 7.0507] +24-11-19 20:30:10 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:10 | D | sum error = [ 606.2733, 636.0409, 666.7954, 698.5403, 731.2672] +24-11-19 20:30:10 | D | best error = [ 7.0507, 7.0507, 7.0507, 7.0507, 7.0507] +24-11-19 20:30:10 | D | + error = [7.0507] +24-11-19 20:30:10 | D | - Calibrating model.layers.17.mlp.down_proj.weight +24-11-19 20:30:10 | D | + w: sint8 +24-11-19 20:30:10 | D | + x: None +24-11-19 20:30:10 | D | + y: None +24-11-19 20:30:10 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:10 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:10 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:30:10 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:30:10 | D | - range ratio = [ 1.0000] +24-11-19 20:30:10 | D | sum error = [ 0.9949] +24-11-19 20:30:10 | D | best error = [ 0.9949] +24-11-19 20:30:11 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:11 | D | sum error = [ 0.9833, 0.9783, 0.9725, 0.9662, 0.9666] +24-11-19 20:30:11 | D | best error = [ 0.9523, 0.9320, 0.9183, 0.9080, 0.9002] +24-11-19 20:30:11 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:11 | D | sum error = [ 0.9665, 0.9706, 0.9799, 0.9883, 1.0060] +24-11-19 20:30:11 | D | best error = [ 0.8938, 0.8891, 0.8852, 0.8820, 0.8800] +24-11-19 20:30:11 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:11 | D | sum error = [ 1.0267, 1.0534, 1.0836, 1.1230, 1.1696] +24-11-19 20:30:11 | D | best error = [ 0.8784, 0.8773, 0.8766, 0.8760, 0.8757] +24-11-19 20:30:11 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:11 | D | sum error = [ 1.2186, 1.2782, 1.3444, 1.4174, 1.4990] +24-11-19 20:30:11 | D | best error = [ 0.8754, 0.8753, 0.8752, 0.8751, 0.8750] +24-11-19 20:30:11 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:11 | D | sum error = [ 1.5920, 1.6893, 1.8003, 1.9181, 2.0456] +24-11-19 20:30:11 | D | best error = [ 0.8750, 0.8750, 0.8749, 0.8749, 0.8749] +24-11-19 20:30:11 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:11 | D | sum error = [ 2.1853, 2.3335, 2.4937, 2.6649, 2.8495] +24-11-19 20:30:11 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 20:30:11 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:11 | D | sum error = [ 3.0461, 3.2541, 3.4795, 3.7216, 3.9741] +24-11-19 20:30:11 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 20:30:11 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:11 | D | sum error = [ 4.2439, 4.5292, 4.8360, 5.1591, 5.5010] +24-11-19 20:30:11 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 20:30:11 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:11 | D | sum error = [ 5.8646, 6.2495, 6.6563, 7.0845, 7.5390] +24-11-19 20:30:11 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 20:30:11 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:11 | D | sum error = [ 8.0190, 8.5257, 9.0593, 9.6211, 10.2109] +24-11-19 20:30:11 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 20:30:11 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:11 | D | sum error = [ 10.8318, 11.4871, 12.1777, 12.8987, 13.6593] +24-11-19 20:30:11 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 20:30:11 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:11 | D | sum error = [ 14.4568, 15.2926, 16.1695, 17.0853, 18.0451] +24-11-19 20:30:11 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 20:30:11 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:11 | D | sum error = [ 19.0480, 20.0970, 21.1905, 22.3331, 23.5274] +24-11-19 20:30:11 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 20:30:11 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:11 | D | sum error = [ 24.7687, 26.0610, 27.4101, 28.8121, 30.2668] +24-11-19 20:30:11 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 20:30:11 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:11 | D | sum error = [ 31.7817, 33.3539, 34.9842, 36.6768, 38.4298] +24-11-19 20:30:11 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 20:30:11 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:11 | D | sum error = [ 40.2438, 42.1218, 44.0608, 46.0659, 48.1357] +24-11-19 20:30:11 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 20:30:11 | D | + error = [0.8749] +24-11-19 20:30:11 | D | - Quantizing model.layers.17.self_attn.q_proj.weight +24-11-19 20:30:16 | D | - Quantizing model.layers.17.self_attn.k_proj.weight +24-11-19 20:30:16 | D | - Quantizing model.layers.17.self_attn.v_proj.weight +24-11-19 20:30:17 | D | - Quantizing model.layers.17.self_attn.o_proj.weight +24-11-19 20:30:18 | D | - Quantizing model.layers.17.mlp.up_proj.weight +24-11-19 20:30:19 | D | - Quantizing model.layers.17.mlp.gate_proj.weight +24-11-19 20:30:20 | D | - Quantizing model.layers.17.mlp.down_proj.weight +24-11-19 20:30:29 | D | - Quantizing layer model.layers.18 +24-11-19 20:30:29 | D | - Calibrating model.layers.18.self_attn.q_proj.weight +24-11-19 20:30:29 | D | + w: sint8 +24-11-19 20:30:29 | D | + x: None +24-11-19 20:30:29 | D | + y: None +24-11-19 20:30:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:30:29 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:29 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:30:29 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:30:30 | D | - range ratio = [ 1.0000] +24-11-19 20:30:30 | D | sum error = [ 3.8985] +24-11-19 20:30:30 | D | best error = [ 3.8985] +24-11-19 20:30:41 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:41 | D | sum error = [ 3.9140, 3.8333, 3.8695, 4.1069, 4.0887] +24-11-19 20:30:41 | D | best error = [ 3.8985, 3.8333, 3.8333, 3.8333, 3.8333] +24-11-19 20:30:41 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:41 | D | sum error = [ 4.1760, 4.3273, 4.5898, 4.7987, 5.1126] +24-11-19 20:30:41 | D | best error = [ 3.8333, 3.8333, 3.8333, 3.8333, 3.8333] +24-11-19 20:30:41 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:41 | D | sum error = [ 5.3565, 5.7751, 6.1813, 6.6779, 7.2022] +24-11-19 20:30:41 | D | best error = [ 3.8333, 3.8333, 3.8333, 3.8333, 3.8333] +24-11-19 20:30:41 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:41 | D | sum error = [ 7.7881, 8.3594, 9.0741, 9.9097, 10.6970] +24-11-19 20:30:41 | D | best error = [ 3.8333, 3.8333, 3.8333, 3.8333, 3.8333] +24-11-19 20:30:41 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:41 | D | sum error = [ 11.6425, 12.5659, 13.7770, 14.8445, 16.0891] +24-11-19 20:30:41 | D | best error = [ 3.8333, 3.8333, 3.8333, 3.8333, 3.8333] +24-11-19 20:30:41 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:41 | D | sum error = [ 17.5886, 19.0285, 20.6928, 22.5371, 24.5408] +24-11-19 20:30:41 | D | best error = [ 3.8333, 3.8333, 3.8333, 3.8333, 3.8333] +24-11-19 20:30:41 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:41 | D | sum error = [ 26.5867, 28.7428, 31.3660, 34.0833, 37.2118] +24-11-19 20:30:41 | D | best error = [ 3.8333, 3.8333, 3.8333, 3.8333, 3.8333] +24-11-19 20:30:41 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:41 | D | sum error = [ 40.3234, 43.7631, 47.4558, 51.1620, 55.3847] +24-11-19 20:30:41 | D | best error = [ 3.8333, 3.8333, 3.8333, 3.8333, 3.8333] +24-11-19 20:30:41 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:41 | D | sum error = [ 59.9771, 64.7655, 70.2494, 75.7477, 82.2297] +24-11-19 20:30:41 | D | best error = [ 3.8333, 3.8333, 3.8333, 3.8333, 3.8333] +24-11-19 20:30:41 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:41 | D | sum error = [ 88.5491, 95.8022, 103.2727, 111.2689, 119.8977] +24-11-19 20:30:41 | D | best error = [ 3.8333, 3.8333, 3.8333, 3.8333, 3.8333] +24-11-19 20:30:41 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:41 | D | sum error = [ 129.3576, 139.3623, 150.0551, 161.9054, 174.3640] +24-11-19 20:30:41 | D | best error = [ 3.8333, 3.8333, 3.8333, 3.8333, 3.8333] +24-11-19 20:30:41 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:41 | D | sum error = [ 188.0578, 202.9186, 219.0724, 236.4214, 255.2800] +24-11-19 20:30:41 | D | best error = [ 3.8333, 3.8333, 3.8333, 3.8333, 3.8333] +24-11-19 20:30:41 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:41 | D | sum error = [ 276.1220, 298.5578, 322.8284, 349.7400, 379.4971] +24-11-19 20:30:41 | D | best error = [ 3.8333, 3.8333, 3.8333, 3.8333, 3.8333] +24-11-19 20:30:41 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:41 | D | sum error = [ 411.0757, 446.4480, 484.8341, 527.5389, 574.1187] +24-11-19 20:30:41 | D | best error = [ 3.8333, 3.8333, 3.8333, 3.8333, 3.8333] +24-11-19 20:30:41 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:41 | D | sum error = [ 625.2311, 680.7031, 740.9309, 806.4318, 877.2133] +24-11-19 20:30:41 | D | best error = [ 3.8333, 3.8333, 3.8333, 3.8333, 3.8333] +24-11-19 20:30:41 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:41 | D | sum error = [ 952.6371, 1032.6991, 1117.4232, 1205.3087, 1294.9094] +24-11-19 20:30:41 | D | best error = [ 3.8333, 3.8333, 3.8333, 3.8333, 3.8333] +24-11-19 20:30:41 | D | + error = [3.8333] +24-11-19 20:30:41 | D | - Calibrating model.layers.18.self_attn.k_proj.weight +24-11-19 20:30:41 | D | + w: sint8 +24-11-19 20:30:41 | D | + x: None +24-11-19 20:30:41 | D | + y: None +24-11-19 20:30:41 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:30:41 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:41 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:30:41 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:30:42 | D | - range ratio = [ 1.0000] +24-11-19 20:30:42 | D | sum error = [ 4.1849] +24-11-19 20:30:42 | D | best error = [ 4.1849] +24-11-19 20:30:53 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:53 | D | sum error = [ 3.6076, 3.8207, 3.4359, 3.5759, 3.6882] +24-11-19 20:30:53 | D | best error = [ 3.6076, 3.6076, 3.4359, 3.4359, 3.4359] +24-11-19 20:30:53 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:53 | D | sum error = [ 4.4356, 4.2943, 3.9826, 4.1671, 4.5161] +24-11-19 20:30:53 | D | best error = [ 3.4359, 3.4359, 3.4359, 3.4359, 3.4359] +24-11-19 20:30:53 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:53 | D | sum error = [ 5.0344, 5.0598, 5.1972, 5.8970, 5.7855] +24-11-19 20:30:53 | D | best error = [ 3.4359, 3.4359, 3.4359, 3.4359, 3.4359] +24-11-19 20:30:53 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:53 | D | sum error = [ 6.3693, 7.0674, 7.5606, 7.9223, 9.2475] +24-11-19 20:30:53 | D | best error = [ 3.4359, 3.4359, 3.4359, 3.4359, 3.4359] +24-11-19 20:30:53 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:53 | D | sum error = [ 9.8807, 10.3572, 11.3758, 11.7339, 12.9821] +24-11-19 20:30:53 | D | best error = [ 3.4359, 3.4359, 3.4359, 3.4359, 3.4359] +24-11-19 20:30:53 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:53 | D | sum error = [ 13.8977, 15.1066, 16.0651, 17.2263, 18.4188] +24-11-19 20:30:53 | D | best error = [ 3.4359, 3.4359, 3.4359, 3.4359, 3.4359] +24-11-19 20:30:53 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:53 | D | sum error = [ 19.9820, 21.1627, 22.9828, 25.5179, 27.5226] +24-11-19 20:30:53 | D | best error = [ 3.4359, 3.4359, 3.4359, 3.4359, 3.4359] +24-11-19 20:30:53 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:53 | D | sum error = [ 29.7272, 31.9382, 34.2496, 37.0861, 40.4807] +24-11-19 20:30:53 | D | best error = [ 3.4359, 3.4359, 3.4359, 3.4359, 3.4359] +24-11-19 20:30:53 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:53 | D | sum error = [ 43.5373, 46.7275, 50.2754, 53.9951, 58.1625] +24-11-19 20:30:53 | D | best error = [ 3.4359, 3.4359, 3.4359, 3.4359, 3.4359] +24-11-19 20:30:53 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:53 | D | sum error = [ 62.4887, 67.1989, 71.7187, 77.8324, 83.9817] +24-11-19 20:30:53 | D | best error = [ 3.4359, 3.4359, 3.4359, 3.4359, 3.4359] +24-11-19 20:30:53 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:53 | D | sum error = [ 89.9374, 97.2863, 104.4101, 113.4430, 122.0891] +24-11-19 20:30:53 | D | best error = [ 3.4359, 3.4359, 3.4359, 3.4359, 3.4359] +24-11-19 20:30:53 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:53 | D | sum error = [ 132.7224, 143.4369, 155.9557, 168.6187, 182.5356] +24-11-19 20:30:53 | D | best error = [ 3.4359, 3.4359, 3.4359, 3.4359, 3.4359] +24-11-19 20:30:53 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:53 | D | sum error = [ 198.3745, 216.4795, 235.2712, 256.1797, 280.0120] +24-11-19 20:30:53 | D | best error = [ 3.4359, 3.4359, 3.4359, 3.4359, 3.4359] +24-11-19 20:30:53 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:53 | D | sum error = [ 305.8978, 335.0072, 366.8124, 402.5488, 442.9484] +24-11-19 20:30:53 | D | best error = [ 3.4359, 3.4359, 3.4359, 3.4359, 3.4359] +24-11-19 20:30:53 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:53 | D | sum error = [ 488.0001, 536.2650, 589.9654, 649.3516, 715.0721] +24-11-19 20:30:53 | D | best error = [ 3.4359, 3.4359, 3.4359, 3.4359, 3.4359] +24-11-19 20:30:53 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:53 | D | sum error = [ 786.6838, 864.7952, 948.9176, 1038.7901, 1135.5239] +24-11-19 20:30:53 | D | best error = [ 3.4359, 3.4359, 3.4359, 3.4359, 3.4359] +24-11-19 20:30:53 | D | + error = [3.4359] +24-11-19 20:30:54 | D | - Calibrating model.layers.18.self_attn.v_proj.weight +24-11-19 20:30:54 | D | + w: sint8 +24-11-19 20:30:54 | D | + x: None +24-11-19 20:30:54 | D | + y: None +24-11-19 20:30:54 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:54 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:30:54 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:30:54 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:30:54 | D | - range ratio = [ 1.0000] +24-11-19 20:30:54 | D | sum error = [ 1.5763] +24-11-19 20:30:54 | D | best error = [ 1.5763] +24-11-19 20:30:54 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:54 | D | sum error = [ 1.5521, 1.5676, 1.5642, 1.5786, 1.6102] +24-11-19 20:30:54 | D | best error = [ 1.4570, 1.4122, 1.3885, 1.3755, 1.3671] +24-11-19 20:30:54 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:54 | D | sum error = [ 1.6402, 1.7142, 1.7713, 1.8551, 1.9489] +24-11-19 20:30:54 | D | best error = [ 1.3635, 1.3623, 1.3619, 1.3617, 1.3616] +24-11-19 20:30:54 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:54 | D | sum error = [ 2.0695, 2.1984, 2.3500, 2.5073, 2.6849] +24-11-19 20:30:54 | D | best error = [ 1.3616, 1.3616, 1.3616, 1.3616, 1.3616] +24-11-19 20:30:54 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:54 | D | sum error = [ 2.8743, 3.0855, 3.2999, 3.5296, 3.7866] +24-11-19 20:30:54 | D | best error = [ 1.3616, 1.3616, 1.3616, 1.3616, 1.3616] +24-11-19 20:30:54 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:54 | D | sum error = [ 4.0744, 4.3587, 4.6778, 4.9985, 5.3414] +24-11-19 20:30:54 | D | best error = [ 1.3616, 1.3616, 1.3616, 1.3616, 1.3616] +24-11-19 20:30:54 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:54 | D | sum error = [ 5.7191, 6.1081, 6.5259, 6.9654, 7.4334] +24-11-19 20:30:54 | D | best error = [ 1.3616, 1.3616, 1.3616, 1.3616, 1.3616] +24-11-19 20:30:54 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:54 | D | sum error = [ 7.9336, 8.4678, 8.9968, 9.5804, 10.1706] +24-11-19 20:30:54 | D | best error = [ 1.3616, 1.3616, 1.3616, 1.3616, 1.3616] +24-11-19 20:30:54 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:54 | D | sum error = [ 10.8141, 11.4667, 12.1676, 12.9108, 13.6724] +24-11-19 20:30:54 | D | best error = [ 1.3616, 1.3616, 1.3616, 1.3616, 1.3616] +24-11-19 20:30:54 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:54 | D | sum error = [ 14.4917, 15.3348, 16.2349, 17.1731, 18.1451] +24-11-19 20:30:54 | D | best error = [ 1.3616, 1.3616, 1.3616, 1.3616, 1.3616] +24-11-19 20:30:54 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:54 | D | sum error = [ 19.1744, 20.2641, 21.3818, 22.5694, 23.8084] +24-11-19 20:30:54 | D | best error = [ 1.3616, 1.3616, 1.3616, 1.3616, 1.3616] +24-11-19 20:30:54 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:54 | D | sum error = [ 25.0938, 26.4393, 27.8539, 29.3363, 30.8825] +24-11-19 20:30:54 | D | best error = [ 1.3616, 1.3616, 1.3616, 1.3616, 1.3616] +24-11-19 20:30:54 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:54 | D | sum error = [ 32.4829, 34.1577, 35.8990, 37.7084, 39.5934] +24-11-19 20:30:54 | D | best error = [ 1.3616, 1.3616, 1.3616, 1.3616, 1.3616] +24-11-19 20:30:54 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:54 | D | sum error = [ 41.5581, 43.5936, 45.7140, 47.9124, 50.1971] +24-11-19 20:30:54 | D | best error = [ 1.3616, 1.3616, 1.3616, 1.3616, 1.3616] +24-11-19 20:30:54 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:54 | D | sum error = [ 52.5764, 55.0439, 57.6055, 60.2511, 63.0132] +24-11-19 20:30:54 | D | best error = [ 1.3616, 1.3616, 1.3616, 1.3616, 1.3616] +24-11-19 20:30:54 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:54 | D | sum error = [ 65.8642, 68.8150, 71.8669, 75.0194, 78.2801] +24-11-19 20:30:54 | D | best error = [ 1.3616, 1.3616, 1.3616, 1.3616, 1.3616] +24-11-19 20:30:54 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:54 | D | sum error = [ 81.6539, 85.1191, 88.6892, 92.3600, 96.1329] +24-11-19 20:30:54 | D | best error = [ 1.3616, 1.3616, 1.3616, 1.3616, 1.3616] +24-11-19 20:30:54 | D | + error = [1.3616] +24-11-19 20:30:54 | D | - Calibrating model.layers.18.self_attn.o_proj.weight +24-11-19 20:30:54 | D | + w: sint8 +24-11-19 20:30:54 | D | + x: None +24-11-19 20:30:54 | D | + y: None +24-11-19 20:30:54 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:54 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:30:54 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:30:54 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:30:54 | D | - range ratio = [ 1.0000] +24-11-19 20:30:54 | D | sum error = [ 0.4924] +24-11-19 20:30:54 | D | best error = [ 0.4924] +24-11-19 20:30:55 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:55 | D | sum error = [ 0.4870, 0.4854, 0.4819, 0.4841, 0.4836] +24-11-19 20:30:55 | D | best error = [ 0.4556, 0.4386, 0.4283, 0.4213, 0.4159] +24-11-19 20:30:55 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:55 | D | sum error = [ 0.4870, 0.4951, 0.5034, 0.5113, 0.5268] +24-11-19 20:30:55 | D | best error = [ 0.4119, 0.4089, 0.4067, 0.4051, 0.4042] +24-11-19 20:30:55 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:55 | D | sum error = [ 0.5403, 0.5584, 0.5780, 0.5977, 0.6243] +24-11-19 20:30:55 | D | best error = [ 0.4034, 0.4029, 0.4025, 0.4023, 0.4022] +24-11-19 20:30:55 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:55 | D | sum error = [ 0.6484, 0.6799, 0.7123, 0.7448, 0.7832] +24-11-19 20:30:55 | D | best error = [ 0.4020, 0.4020, 0.4020, 0.4020, 0.4019] +24-11-19 20:30:55 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:55 | D | sum error = [ 0.8232, 0.8658, 0.9089, 0.9588, 1.0084] +24-11-19 20:30:55 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:30:55 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:55 | D | sum error = [ 1.0615, 1.1191, 1.1801, 1.2435, 1.3120] +24-11-19 20:30:55 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:30:55 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:55 | D | sum error = [ 1.3825, 1.4564, 1.5382, 1.6195, 1.7082] +24-11-19 20:30:55 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:30:55 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:55 | D | sum error = [ 1.7987, 1.8984, 2.0010, 2.1087, 2.2234] +24-11-19 20:30:55 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:30:55 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:55 | D | sum error = [ 2.3415, 2.4686, 2.6022, 2.7452, 2.8931] +24-11-19 20:30:55 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:30:55 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:55 | D | sum error = [ 3.0509, 3.2166, 3.3933, 3.5780, 3.7739] +24-11-19 20:30:55 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:30:55 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:55 | D | sum error = [ 3.9791, 4.1975, 4.4247, 4.6665, 4.9201] +24-11-19 20:30:55 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:30:55 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:55 | D | sum error = [ 5.1900, 5.4735, 5.7724, 6.0869, 6.4186] +24-11-19 20:30:55 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:30:55 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:55 | D | sum error = [ 6.7680, 7.1370, 7.5225, 7.9298, 8.3570] +24-11-19 20:30:55 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:30:55 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:55 | D | sum error = [ 8.8052, 9.2746, 9.7677, 10.2858, 10.8283] +24-11-19 20:30:55 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:30:55 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:55 | D | sum error = [ 11.3966, 11.9901, 12.6101, 13.2573, 13.9338] +24-11-19 20:30:55 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:30:55 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:55 | D | sum error = [ 14.6404, 15.3777, 16.1465, 16.9486, 17.7824] +24-11-19 20:30:55 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:30:55 | D | + error = [0.4019] +24-11-19 20:30:55 | D | - Calibrating model.layers.18.mlp.up_proj.weight +24-11-19 20:30:55 | D | + w: sint8 +24-11-19 20:30:55 | D | + x: None +24-11-19 20:30:55 | D | + y: None +24-11-19 20:30:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:55 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:30:55 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:30:55 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:30:55 | D | - range ratio = [ 1.0000] +24-11-19 20:30:55 | D | sum error = [ 6.3109] +24-11-19 20:30:55 | D | best error = [ 6.3109] +24-11-19 20:30:56 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:56 | D | sum error = [ 6.2589, 6.2429, 6.2805, 6.3587, 6.4696] +24-11-19 20:30:56 | D | best error = [ 5.8604, 5.6852, 5.5973, 5.5463, 5.5186] +24-11-19 20:30:56 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:56 | D | sum error = [ 6.6286, 6.8763, 7.1337, 7.4650, 7.8848] +24-11-19 20:30:56 | D | best error = [ 5.5040, 5.4983, 5.4960, 5.4953, 5.4952] +24-11-19 20:30:56 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:56 | D | sum error = [ 8.3327, 8.8271, 9.3983, 10.0473, 10.7478] +24-11-19 20:30:56 | D | best error = [ 5.4951, 5.4951, 5.4951, 5.4951, 5.4951] +24-11-19 20:30:56 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:56 | D | sum error = [ 11.4969, 12.3175, 13.1835, 14.1329, 15.1611] +24-11-19 20:30:56 | D | best error = [ 5.4951, 5.4951, 5.4951, 5.4951, 5.4951] +24-11-19 20:30:56 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:56 | D | sum error = [ 16.2365, 17.3901, 18.6230, 19.9075, 21.2779] +24-11-19 20:30:56 | D | best error = [ 5.4951, 5.4951, 5.4951, 5.4951, 5.4951] +24-11-19 20:30:56 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:56 | D | sum error = [ 22.7557, 24.2898, 25.9269, 27.6547, 29.4780] +24-11-19 20:30:56 | D | best error = [ 5.4951, 5.4951, 5.4951, 5.4951, 5.4951] +24-11-19 20:30:56 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:56 | D | sum error = [ 31.3952, 33.4326, 35.5667, 37.8133, 40.1956] +24-11-19 20:30:56 | D | best error = [ 5.4951, 5.4951, 5.4951, 5.4951, 5.4951] +24-11-19 20:30:56 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:56 | D | sum error = [ 42.6688, 45.2981, 48.0400, 50.9336, 53.9675] +24-11-19 20:30:56 | D | best error = [ 5.4951, 5.4951, 5.4951, 5.4951, 5.4951] +24-11-19 20:30:56 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:56 | D | sum error = [ 57.1428, 60.4677, 63.9749, 67.6200, 71.4621] +24-11-19 20:30:56 | D | best error = [ 5.4951, 5.4951, 5.4951, 5.4951, 5.4951] +24-11-19 20:30:56 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:56 | D | sum error = [ 75.4640, 79.6728, 84.0541, 88.6385, 93.4311] +24-11-19 20:30:56 | D | best error = [ 5.4951, 5.4951, 5.4951, 5.4951, 5.4951] +24-11-19 20:30:56 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:56 | D | sum error = [ 98.4250, 103.6251, 109.0513, 114.7152, 120.5896] +24-11-19 20:30:56 | D | best error = [ 5.4951, 5.4951, 5.4951, 5.4951, 5.4951] +24-11-19 20:30:56 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:56 | D | sum error = [ 126.7226, 133.0859, 139.7154, 146.6145, 153.7653] +24-11-19 20:30:56 | D | best error = [ 5.4951, 5.4951, 5.4951, 5.4951, 5.4951] +24-11-19 20:30:56 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:56 | D | sum error = [ 161.2029, 168.9029, 176.8871, 185.1666, 193.7468] +24-11-19 20:30:56 | D | best error = [ 5.4951, 5.4951, 5.4951, 5.4951, 5.4951] +24-11-19 20:30:56 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:56 | D | sum error = [ 202.6159, 211.8002, 221.3014, 231.1183, 241.2702] +24-11-19 20:30:56 | D | best error = [ 5.4951, 5.4951, 5.4951, 5.4951, 5.4951] +24-11-19 20:30:56 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:56 | D | sum error = [ 251.7301, 262.5329, 273.6715, 285.1503, 296.9632] +24-11-19 20:30:56 | D | best error = [ 5.4951, 5.4951, 5.4951, 5.4951, 5.4951] +24-11-19 20:30:56 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:56 | D | sum error = [ 309.1618, 321.6987, 334.6045, 347.8714, 361.5175] +24-11-19 20:30:56 | D | best error = [ 5.4951, 5.4951, 5.4951, 5.4951, 5.4951] +24-11-19 20:30:56 | D | + error = [5.4951] +24-11-19 20:30:56 | D | - Calibrating model.layers.18.mlp.gate_proj.weight +24-11-19 20:30:56 | D | + w: sint8 +24-11-19 20:30:56 | D | + x: None +24-11-19 20:30:56 | D | + y: None +24-11-19 20:30:56 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:56 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:30:56 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:30:56 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:30:57 | D | - range ratio = [ 1.0000] +24-11-19 20:30:57 | D | sum error = [ 8.4714] +24-11-19 20:30:57 | D | best error = [ 8.4714] +24-11-19 20:30:58 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:58 | D | sum error = [ 8.4294, 8.3628, 8.3983, 8.5095, 8.6756] +24-11-19 20:30:58 | D | best error = [ 7.8769, 7.6394, 7.5129, 7.4428, 7.4049] +24-11-19 20:30:58 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:58 | D | sum error = [ 8.8912, 9.2047, 9.5662, 10.0269, 10.5290] +24-11-19 20:30:58 | D | best error = [ 7.3859, 7.3780, 7.3748, 7.3740, 7.3738] +24-11-19 20:30:58 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:58 | D | sum error = [ 11.1569, 11.8446, 12.6261, 13.4751, 14.4323] +24-11-19 20:30:58 | D | best error = [ 7.3738, 7.3738, 7.3738, 7.3738, 7.3738] +24-11-19 20:30:58 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:58 | D | sum error = [ 15.4654, 16.5579, 17.7401, 19.0476, 20.4240] +24-11-19 20:30:58 | D | best error = [ 7.3738, 7.3738, 7.3738, 7.3738, 7.3738] +24-11-19 20:30:58 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:58 | D | sum error = [ 21.9179, 23.5210, 25.2374, 27.0553, 28.9860] +24-11-19 20:30:58 | D | best error = [ 7.3738, 7.3738, 7.3738, 7.3738, 7.3738] +24-11-19 20:30:58 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:58 | D | sum error = [ 31.0401, 33.2400, 35.5837, 38.0453, 40.6928] +24-11-19 20:30:58 | D | best error = [ 7.3738, 7.3738, 7.3738, 7.3738, 7.3738] +24-11-19 20:30:58 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:58 | D | sum error = [ 43.4832, 46.4617, 49.6085, 52.9476, 56.5110] +24-11-19 20:30:58 | D | best error = [ 7.3738, 7.3738, 7.3738, 7.3738, 7.3738] +24-11-19 20:30:58 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:58 | D | sum error = [ 60.2402, 64.2201, 68.4708, 72.9326, 77.7122] +24-11-19 20:30:58 | D | best error = [ 7.3738, 7.3738, 7.3738, 7.3738, 7.3738] +24-11-19 20:30:58 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:58 | D | sum error = [ 82.7278, 88.0462, 93.6822, 99.6527, 105.9338] +24-11-19 20:30:58 | D | best error = [ 7.3738, 7.3738, 7.3738, 7.3738, 7.3738] +24-11-19 20:30:58 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:58 | D | sum error = [ 112.5566, 119.5944, 127.0273, 134.8455, 143.1171] +24-11-19 20:30:58 | D | best error = [ 7.3738, 7.3738, 7.3738, 7.3738, 7.3738] +24-11-19 20:30:58 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:58 | D | sum error = [ 151.8431, 161.0644, 170.7589, 181.0182, 191.7699] +24-11-19 20:30:58 | D | best error = [ 7.3738, 7.3738, 7.3738, 7.3738, 7.3738] +24-11-19 20:30:58 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:58 | D | sum error = [ 203.1215, 215.0911, 227.6172, 240.8271, 254.6618] +24-11-19 20:30:58 | D | best error = [ 7.3738, 7.3738, 7.3738, 7.3738, 7.3738] +24-11-19 20:30:58 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:58 | D | sum error = [ 269.2390, 284.5197, 300.5108, 317.2517, 334.7686] +24-11-19 20:30:58 | D | best error = [ 7.3738, 7.3738, 7.3738, 7.3738, 7.3738] +24-11-19 20:30:58 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:58 | D | sum error = [ 353.0760, 372.1831, 392.1418, 412.9484, 434.5920] +24-11-19 20:30:58 | D | best error = [ 7.3738, 7.3738, 7.3738, 7.3738, 7.3738] +24-11-19 20:30:58 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:58 | D | sum error = [ 457.1260, 480.5545, 504.8593, 530.0646, 556.1875] +24-11-19 20:30:58 | D | best error = [ 7.3738, 7.3738, 7.3738, 7.3738, 7.3738] +24-11-19 20:30:58 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:58 | D | sum error = [ 583.2298, 611.2137, 640.0885, 669.8832, 700.6247] +24-11-19 20:30:58 | D | best error = [ 7.3738, 7.3738, 7.3738, 7.3738, 7.3738] +24-11-19 20:30:58 | D | + error = [7.3738] +24-11-19 20:30:58 | D | - Calibrating model.layers.18.mlp.down_proj.weight +24-11-19 20:30:58 | D | + w: sint8 +24-11-19 20:30:58 | D | + x: None +24-11-19 20:30:58 | D | + y: None +24-11-19 20:30:58 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:58 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:30:58 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:30:58 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:30:58 | D | - range ratio = [ 1.0000] +24-11-19 20:30:58 | D | sum error = [ 0.9852] +24-11-19 20:30:58 | D | best error = [ 0.9852] +24-11-19 20:30:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:59 | D | sum error = [ 0.9770, 0.9693, 0.9631, 0.9602, 0.9585] +24-11-19 20:30:59 | D | best error = [ 0.9446, 0.9247, 0.9109, 0.9009, 0.8926] +24-11-19 20:30:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:59 | D | sum error = [ 0.9584, 0.9624, 0.9671, 0.9800, 0.9953] +24-11-19 20:30:59 | D | best error = [ 0.8861, 0.8810, 0.8769, 0.8740, 0.8718] +24-11-19 20:30:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:59 | D | sum error = [ 1.0133, 1.0375, 1.0678, 1.1058, 1.1471] +24-11-19 20:30:59 | D | best error = [ 0.8703, 0.8689, 0.8680, 0.8675, 0.8670] +24-11-19 20:30:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:59 | D | sum error = [ 1.1962, 1.2553, 1.3167, 1.3887, 1.4723] +24-11-19 20:30:59 | D | best error = [ 0.8667, 0.8666, 0.8664, 0.8663, 0.8663] +24-11-19 20:30:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:59 | D | sum error = [ 1.5593, 1.6580, 1.7640, 1.8811, 2.0079] +24-11-19 20:30:59 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 20:30:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:59 | D | sum error = [ 2.1449, 2.2957, 2.4527, 2.6250, 2.8092] +24-11-19 20:30:59 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 20:30:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:59 | D | sum error = [ 3.0041, 3.2152, 3.4365, 3.6759, 3.9290] +24-11-19 20:30:59 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 20:30:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:59 | D | sum error = [ 4.2012, 4.4882, 4.7926, 5.1171, 5.4616] +24-11-19 20:30:59 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 20:30:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:59 | D | sum error = [ 5.8253, 6.2100, 6.6179, 7.0479, 7.5032] +24-11-19 20:30:59 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 20:30:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:59 | D | sum error = [ 7.9834, 8.4890, 9.0217, 9.5829, 10.1732] +24-11-19 20:30:59 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 20:30:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:59 | D | sum error = [ 10.7943, 11.4462, 12.1304, 12.8513, 13.6065] +24-11-19 20:30:59 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 20:30:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:59 | D | sum error = [ 14.3994, 15.2325, 16.1041, 17.0136, 17.9712] +24-11-19 20:30:59 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 20:30:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:59 | D | sum error = [ 18.9686, 20.0137, 21.1051, 22.2455, 23.4332] +24-11-19 20:30:59 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 20:30:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:59 | D | sum error = [ 24.6712, 25.9603, 27.3028, 28.7009, 30.1530] +24-11-19 20:30:59 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 20:30:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:59 | D | sum error = [ 31.6616, 33.2286, 34.8544, 36.5401, 38.2863] +24-11-19 20:30:59 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 20:30:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:59 | D | sum error = [ 40.0927, 41.9620, 43.8953, 45.8915, 47.9518] +24-11-19 20:30:59 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 20:30:59 | D | + error = [0.8662] +24-11-19 20:30:59 | D | - Quantizing model.layers.18.self_attn.q_proj.weight +24-11-19 20:31:00 | D | - Quantizing model.layers.18.self_attn.k_proj.weight +24-11-19 20:31:01 | D | - Quantizing model.layers.18.self_attn.v_proj.weight +24-11-19 20:31:02 | D | - Quantizing model.layers.18.self_attn.o_proj.weight +24-11-19 20:31:03 | D | - Quantizing model.layers.18.mlp.up_proj.weight +24-11-19 20:31:06 | D | - Quantizing model.layers.18.mlp.gate_proj.weight +24-11-19 20:31:08 | D | - Quantizing model.layers.18.mlp.down_proj.weight +24-11-19 20:31:20 | D | - Quantizing layer model.layers.19 +24-11-19 20:31:20 | D | - Calibrating model.layers.19.self_attn.q_proj.weight +24-11-19 20:31:20 | D | + w: sint8 +24-11-19 20:31:20 | D | + x: None +24-11-19 20:31:20 | D | + y: None +24-11-19 20:31:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:31:20 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:31:20 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:31:20 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:31:21 | D | - range ratio = [ 1.0000] +24-11-19 20:31:21 | D | sum error = [ 3.5055] +24-11-19 20:31:21 | D | best error = [ 3.5055] +24-11-19 20:31:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:33 | D | sum error = [ 3.4733, 3.4244, 3.5524, 3.5067, 3.5755] +24-11-19 20:31:33 | D | best error = [ 3.4733, 3.4244, 3.4244, 3.4244, 3.4244] +24-11-19 20:31:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:33 | D | sum error = [ 3.7652, 3.8998, 3.9879, 4.3088, 4.6213] +24-11-19 20:31:33 | D | best error = [ 3.4244, 3.4244, 3.4244, 3.4244, 3.4244] +24-11-19 20:31:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:33 | D | sum error = [ 4.9843, 5.3621, 5.8486, 6.2949, 6.8406] +24-11-19 20:31:33 | D | best error = [ 3.4244, 3.4244, 3.4244, 3.4244, 3.4244] +24-11-19 20:31:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:33 | D | sum error = [ 7.4753, 8.1134, 9.0037, 9.7486, 10.5893] +24-11-19 20:31:33 | D | best error = [ 3.4244, 3.4244, 3.4244, 3.4244, 3.4244] +24-11-19 20:31:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:33 | D | sum error = [ 11.8468, 12.8294, 14.0481, 15.4489, 16.8529] +24-11-19 20:31:33 | D | best error = [ 3.4244, 3.4244, 3.4244, 3.4244, 3.4244] +24-11-19 20:31:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:33 | D | sum error = [ 18.5777, 20.4958, 22.6380, 24.7579, 27.1433] +24-11-19 20:31:33 | D | best error = [ 3.4244, 3.4244, 3.4244, 3.4244, 3.4244] +24-11-19 20:31:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:33 | D | sum error = [ 29.8964, 32.6796, 35.8753, 38.9846, 42.8889] +24-11-19 20:31:33 | D | best error = [ 3.4244, 3.4244, 3.4244, 3.4244, 3.4244] +24-11-19 20:31:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:33 | D | sum error = [ 46.6042, 51.2336, 55.8630, 61.2842, 66.8170] +24-11-19 20:31:33 | D | best error = [ 3.4244, 3.4244, 3.4244, 3.4244, 3.4244] +24-11-19 20:31:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:33 | D | sum error = [ 73.0399, 79.9390, 86.8470, 94.6378, 102.9622] +24-11-19 20:31:33 | D | best error = [ 3.4244, 3.4244, 3.4244, 3.4244, 3.4244] +24-11-19 20:31:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:33 | D | sum error = [ 112.2729, 122.4054, 132.9090, 144.3586, 157.0600] +24-11-19 20:31:33 | D | best error = [ 3.4244, 3.4244, 3.4244, 3.4244, 3.4244] +24-11-19 20:31:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:33 | D | sum error = [ 170.8940, 185.4974, 201.9971, 219.0118, 238.0333] +24-11-19 20:31:33 | D | best error = [ 3.4244, 3.4244, 3.4244, 3.4244, 3.4244] +24-11-19 20:31:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:33 | D | sum error = [ 258.7929, 281.4424, 305.8211, 332.9306, 361.9808] +24-11-19 20:31:33 | D | best error = [ 3.4244, 3.4244, 3.4244, 3.4244, 3.4244] +24-11-19 20:31:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:33 | D | sum error = [ 394.3444, 429.3826, 468.0002, 509.8841, 556.2930] +24-11-19 20:31:33 | D | best error = [ 3.4244, 3.4244, 3.4244, 3.4244, 3.4244] +24-11-19 20:31:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:33 | D | sum error = [ 606.3332, 661.8267, 722.1995, 787.4977, 858.9156] +24-11-19 20:31:33 | D | best error = [ 3.4244, 3.4244, 3.4244, 3.4244, 3.4244] +24-11-19 20:31:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:33 | D | sum error = [ 935.9595, 1018.3797, 1107.2805, 1201.8496, 1300.2423] +24-11-19 20:31:33 | D | best error = [ 3.4244, 3.4244, 3.4244, 3.4244, 3.4244] +24-11-19 20:31:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:33 | D | sum error = [ 1404.1257, 1511.1479, 1620.8131, 1732.4027, 1843.5928] +24-11-19 20:31:33 | D | best error = [ 3.4244, 3.4244, 3.4244, 3.4244, 3.4244] +24-11-19 20:31:33 | D | + error = [3.4244] +24-11-19 20:31:33 | D | - Calibrating model.layers.19.self_attn.k_proj.weight +24-11-19 20:31:33 | D | + w: sint8 +24-11-19 20:31:33 | D | + x: None +24-11-19 20:31:33 | D | + y: None +24-11-19 20:31:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:31:33 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:31:33 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:31:33 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:31:33 | D | - range ratio = [ 1.0000] +24-11-19 20:31:33 | D | sum error = [ 3.3689] +24-11-19 20:31:33 | D | best error = [ 3.3689] +24-11-19 20:31:45 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:45 | D | sum error = [ 3.1914, 3.2953, 3.4099, 3.3712, 3.5272] +24-11-19 20:31:45 | D | best error = [ 3.1914, 3.1914, 3.1914, 3.1914, 3.1914] +24-11-19 20:31:45 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:45 | D | sum error = [ 3.7570, 3.9927, 4.2189, 4.4874, 4.0808] +24-11-19 20:31:45 | D | best error = [ 3.1914, 3.1914, 3.1914, 3.1914, 3.1914] +24-11-19 20:31:45 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:45 | D | sum error = [ 4.6669, 5.0571, 4.9143, 5.7207, 6.2453] +24-11-19 20:31:45 | D | best error = [ 3.1914, 3.1914, 3.1914, 3.1914, 3.1914] +24-11-19 20:31:45 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:45 | D | sum error = [ 6.2960, 7.3295, 7.9450, 8.4395, 8.9557] +24-11-19 20:31:45 | D | best error = [ 3.1914, 3.1914, 3.1914, 3.1914, 3.1914] +24-11-19 20:31:45 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:45 | D | sum error = [ 9.5777, 10.3575, 11.7178, 13.2970, 13.8277] +24-11-19 20:31:45 | D | best error = [ 3.1914, 3.1914, 3.1914, 3.1914, 3.1914] +24-11-19 20:31:45 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:45 | D | sum error = [ 15.3394, 16.5800, 17.8616, 19.4361, 21.8821] +24-11-19 20:31:45 | D | best error = [ 3.1914, 3.1914, 3.1914, 3.1914, 3.1914] +24-11-19 20:31:45 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:45 | D | sum error = [ 23.0984, 24.9316, 27.3918, 28.6455, 31.5525] +24-11-19 20:31:45 | D | best error = [ 3.1914, 3.1914, 3.1914, 3.1914, 3.1914] +24-11-19 20:31:45 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:45 | D | sum error = [ 34.0010, 37.0843, 40.2504, 43.5327, 47.1747] +24-11-19 20:31:45 | D | best error = [ 3.1914, 3.1914, 3.1914, 3.1914, 3.1914] +24-11-19 20:31:45 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:45 | D | sum error = [ 50.5787, 54.8947, 58.8913, 63.5503, 68.0185] +24-11-19 20:31:45 | D | best error = [ 3.1914, 3.1914, 3.1914, 3.1914, 3.1914] +24-11-19 20:31:45 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:45 | D | sum error = [ 72.7895, 78.9055, 85.0236, 92.0191, 98.6859] +24-11-19 20:31:45 | D | best error = [ 3.1914, 3.1914, 3.1914, 3.1914, 3.1914] +24-11-19 20:31:45 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:45 | D | sum error = [ 106.6408, 115.4273, 125.0758, 135.7900, 147.0859] +24-11-19 20:31:45 | D | best error = [ 3.1914, 3.1914, 3.1914, 3.1914, 3.1914] +24-11-19 20:31:45 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:45 | D | sum error = [ 160.4573, 173.8017, 189.7263, 207.9189, 226.1720] +24-11-19 20:31:45 | D | best error = [ 3.1914, 3.1914, 3.1914, 3.1914, 3.1914] +24-11-19 20:31:45 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:45 | D | sum error = [ 248.2387, 271.8320, 299.2374, 328.3662, 361.9979] +24-11-19 20:31:45 | D | best error = [ 3.1914, 3.1914, 3.1914, 3.1914, 3.1914] +24-11-19 20:31:45 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:45 | D | sum error = [ 396.4749, 436.9463, 480.9459, 529.0706, 580.1061] +24-11-19 20:31:45 | D | best error = [ 3.1914, 3.1914, 3.1914, 3.1914, 3.1914] +24-11-19 20:31:45 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:45 | D | sum error = [ 636.5559, 699.7704, 767.8565, 844.7831, 928.3464] +24-11-19 20:31:45 | D | best error = [ 3.1914, 3.1914, 3.1914, 3.1914, 3.1914] +24-11-19 20:31:45 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:45 | D | sum error = [ 1021.9085, 1126.6794, 1237.2517, 1356.2341, 1482.4094] +24-11-19 20:31:45 | D | best error = [ 3.1914, 3.1914, 3.1914, 3.1914, 3.1914] +24-11-19 20:31:45 | D | + error = [3.1914] +24-11-19 20:31:45 | D | - Calibrating model.layers.19.self_attn.v_proj.weight +24-11-19 20:31:45 | D | + w: sint8 +24-11-19 20:31:45 | D | + x: None +24-11-19 20:31:45 | D | + y: None +24-11-19 20:31:45 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:46 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:31:46 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:31:46 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:31:46 | D | - range ratio = [ 1.0000] +24-11-19 20:31:46 | D | sum error = [ 1.6693] +24-11-19 20:31:46 | D | best error = [ 1.6693] +24-11-19 20:31:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:46 | D | sum error = [ 1.6538, 1.6523, 1.6483, 1.6796, 1.7039] +24-11-19 20:31:46 | D | best error = [ 1.5517, 1.5044, 1.4783, 1.4637, 1.4569] +24-11-19 20:31:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:46 | D | sum error = [ 1.7584, 1.8325, 1.8979, 1.9814, 2.0891] +24-11-19 20:31:46 | D | best error = [ 1.4537, 1.4519, 1.4510, 1.4510, 1.4510] +24-11-19 20:31:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:46 | D | sum error = [ 2.2059, 2.3502, 2.5085, 2.6758, 2.8681] +24-11-19 20:31:46 | D | best error = [ 1.4510, 1.4510, 1.4510, 1.4510, 1.4510] +24-11-19 20:31:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:46 | D | sum error = [ 3.0665, 3.2977, 3.5262, 3.7766, 4.0504] +24-11-19 20:31:46 | D | best error = [ 1.4510, 1.4510, 1.4510, 1.4510, 1.4510] +24-11-19 20:31:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:46 | D | sum error = [ 4.3567, 4.6810, 5.0112, 5.3732, 5.7394] +24-11-19 20:31:46 | D | best error = [ 1.4510, 1.4510, 1.4510, 1.4510, 1.4510] +24-11-19 20:31:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:46 | D | sum error = [ 6.1461, 6.5611, 7.0234, 7.4914, 7.9801] +24-11-19 20:31:46 | D | best error = [ 1.4510, 1.4510, 1.4510, 1.4510, 1.4510] +24-11-19 20:31:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:46 | D | sum error = [ 8.5145, 9.1001, 9.6884, 10.2945, 10.9646] +24-11-19 20:31:46 | D | best error = [ 1.4510, 1.4510, 1.4510, 1.4510, 1.4510] +24-11-19 20:31:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:46 | D | sum error = [ 11.6563, 12.3896, 13.1798, 13.9665, 14.8151] +24-11-19 20:31:46 | D | best error = [ 1.4510, 1.4510, 1.4510, 1.4510, 1.4510] +24-11-19 20:31:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:46 | D | sum error = [ 15.7021, 16.6455, 17.6164, 18.6359, 19.7230] +24-11-19 20:31:46 | D | best error = [ 1.4510, 1.4510, 1.4510, 1.4510, 1.4510] +24-11-19 20:31:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:46 | D | sum error = [ 20.8677, 22.0524, 23.3050, 24.5918, 25.9614] +24-11-19 20:31:46 | D | best error = [ 1.4510, 1.4510, 1.4510, 1.4510, 1.4510] +24-11-19 20:31:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:46 | D | sum error = [ 27.3882, 28.8896, 30.4525, 32.0711, 33.7827] +24-11-19 20:31:46 | D | best error = [ 1.4510, 1.4510, 1.4510, 1.4510, 1.4510] +24-11-19 20:31:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:46 | D | sum error = [ 35.5499, 37.3870, 39.3071, 41.3036, 43.3820] +24-11-19 20:31:46 | D | best error = [ 1.4510, 1.4510, 1.4510, 1.4510, 1.4510] +24-11-19 20:31:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:46 | D | sum error = [ 45.5445, 47.7910, 50.1312, 52.5601, 55.0910] +24-11-19 20:31:46 | D | best error = [ 1.4510, 1.4510, 1.4510, 1.4510, 1.4510] +24-11-19 20:31:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:46 | D | sum error = [ 57.7118, 60.4458, 63.2681, 66.1916, 69.2185] +24-11-19 20:31:46 | D | best error = [ 1.4510, 1.4510, 1.4510, 1.4510, 1.4510] +24-11-19 20:31:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:46 | D | sum error = [ 72.3490, 75.5808, 78.9188, 82.3739, 85.9292] +24-11-19 20:31:46 | D | best error = [ 1.4510, 1.4510, 1.4510, 1.4510, 1.4510] +24-11-19 20:31:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:46 | D | sum error = [ 89.6068, 93.3906, 97.2977, 101.3106, 105.4423] +24-11-19 20:31:46 | D | best error = [ 1.4510, 1.4510, 1.4510, 1.4510, 1.4510] +24-11-19 20:31:46 | D | + error = [1.4510] +24-11-19 20:31:46 | D | - Calibrating model.layers.19.self_attn.o_proj.weight +24-11-19 20:31:46 | D | + w: sint8 +24-11-19 20:31:46 | D | + x: None +24-11-19 20:31:46 | D | + y: None +24-11-19 20:31:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:46 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:31:46 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:31:46 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:31:46 | D | - range ratio = [ 1.0000] +24-11-19 20:31:46 | D | sum error = [ 0.3769] +24-11-19 20:31:46 | D | best error = [ 0.3769] +24-11-19 20:31:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:47 | D | sum error = [ 0.3739, 0.3729, 0.3742, 0.3756, 0.3787] +24-11-19 20:31:47 | D | best error = [ 0.3528, 0.3421, 0.3355, 0.3311, 0.3277] +24-11-19 20:31:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:47 | D | sum error = [ 0.3876, 0.3978, 0.4103, 0.4240, 0.4424] +24-11-19 20:31:47 | D | best error = [ 0.3256, 0.3238, 0.3226, 0.3217, 0.3209] +24-11-19 20:31:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:47 | D | sum error = [ 0.4618, 0.4867, 0.5129, 0.5426, 0.5725] +24-11-19 20:31:47 | D | best error = [ 0.3203, 0.3199, 0.3196, 0.3192, 0.3191] +24-11-19 20:31:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:47 | D | sum error = [ 0.6093, 0.6461, 0.6862, 0.7302, 0.7759] +24-11-19 20:31:47 | D | best error = [ 0.3189, 0.3189, 0.3188, 0.3187, 0.3187] +24-11-19 20:31:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:47 | D | sum error = [ 0.8265, 0.8794, 0.9357, 0.9960, 1.0572] +24-11-19 20:31:47 | D | best error = [ 0.3187, 0.3187, 0.3186, 0.3186, 0.3186] +24-11-19 20:31:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:47 | D | sum error = [ 1.1250, 1.1944, 1.2702, 1.3491, 1.4310] +24-11-19 20:31:47 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:31:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:47 | D | sum error = [ 1.5199, 1.6123, 1.7079, 1.8097, 1.9179] +24-11-19 20:31:47 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:31:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:47 | D | sum error = [ 2.0295, 2.1472, 2.2700, 2.3991, 2.5338] +24-11-19 20:31:47 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:31:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:47 | D | sum error = [ 2.6769, 2.8267, 2.9832, 3.1480, 3.3201] +24-11-19 20:31:47 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:31:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:47 | D | sum error = [ 3.5015, 3.6918, 3.8898, 4.0977, 4.3149] +24-11-19 20:31:47 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:31:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:47 | D | sum error = [ 4.5425, 4.7806, 5.0283, 5.2879, 5.5585] +24-11-19 20:31:47 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:31:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:47 | D | sum error = [ 5.8409, 6.1359, 6.4443, 6.7644, 7.0996] +24-11-19 20:31:47 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:31:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:47 | D | sum error = [ 7.4471, 7.8101, 8.1860, 8.5767, 8.9823] +24-11-19 20:31:47 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:31:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:47 | D | sum error = [ 9.4037, 9.8408, 10.2944, 10.7661, 11.2536] +24-11-19 20:31:47 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:31:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:47 | D | sum error = [ 11.7594, 12.2834, 12.8261, 13.3879, 13.9688] +24-11-19 20:31:47 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:31:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:47 | D | sum error = [ 14.5686, 15.1889, 15.8283, 16.4896, 17.1715] +24-11-19 20:31:47 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:31:47 | D | + error = [0.3186] +24-11-19 20:31:47 | D | - Calibrating model.layers.19.mlp.up_proj.weight +24-11-19 20:31:47 | D | + w: sint8 +24-11-19 20:31:47 | D | + x: None +24-11-19 20:31:47 | D | + y: None +24-11-19 20:31:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:47 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:31:47 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:31:47 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:31:47 | D | - range ratio = [ 1.0000] +24-11-19 20:31:47 | D | sum error = [ 6.5166] +24-11-19 20:31:47 | D | best error = [ 6.5166] +24-11-19 20:31:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:48 | D | sum error = [ 6.4671, 6.4598, 6.4680, 6.5435, 6.6678] +24-11-19 20:31:48 | D | best error = [ 6.0328, 5.8510, 5.7550, 5.7001, 5.6706] +24-11-19 20:31:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:48 | D | sum error = [ 6.8282, 7.0455, 7.3503, 7.6850, 8.0798] +24-11-19 20:31:48 | D | best error = [ 5.6569, 5.6506, 5.6478, 5.6470, 5.6468] +24-11-19 20:31:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:48 | D | sum error = [ 8.5416, 9.0687, 9.6612, 10.3071, 11.0193] +24-11-19 20:31:48 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 20:31:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:48 | D | sum error = [ 11.7937, 12.6167, 13.5122, 14.4817, 15.5122] +24-11-19 20:31:48 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 20:31:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:48 | D | sum error = [ 16.5966, 17.7793, 19.0326, 20.3634, 21.7694] +24-11-19 20:31:48 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 20:31:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:48 | D | sum error = [ 23.2455, 24.8390, 26.4932, 28.2685, 30.1319] +24-11-19 20:31:48 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 20:31:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:48 | D | sum error = [ 32.0830, 34.1469, 36.3174, 38.6050, 41.0203] +24-11-19 20:31:48 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 20:31:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:48 | D | sum error = [ 43.5603, 46.2150, 49.0193, 51.9463, 55.0226] +24-11-19 20:31:48 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 20:31:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:48 | D | sum error = [ 58.2603, 61.6454, 65.1931, 68.8990, 72.7873] +24-11-19 20:31:48 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 20:31:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:48 | D | sum error = [ 76.8572, 81.1147, 85.5699, 90.2008, 95.0512] +24-11-19 20:31:48 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 20:31:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:48 | D | sum error = [ 100.0969, 105.3696, 110.8630, 116.5775, 122.5248] +24-11-19 20:31:48 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 20:31:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:48 | D | sum error = [ 128.7046, 135.1234, 141.8101, 148.7419, 155.9266] +24-11-19 20:31:48 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 20:31:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:48 | D | sum error = [ 163.3892, 171.1233, 179.1355, 187.4361, 196.0257] +24-11-19 20:31:48 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 20:31:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:48 | D | sum error = [ 204.9087, 214.0947, 223.5849, 233.4032, 243.5267] +24-11-19 20:31:48 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 20:31:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:48 | D | sum error = [ 253.9686, 264.7436, 275.8401, 287.2782, 299.0475] +24-11-19 20:31:48 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 20:31:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:48 | D | sum error = [ 311.1870, 323.6770, 336.5246, 349.7278, 363.2917] +24-11-19 20:31:48 | D | best error = [ 5.6467, 5.6467, 5.6467, 5.6467, 5.6467] +24-11-19 20:31:48 | D | + error = [5.6467] +24-11-19 20:31:48 | D | - Calibrating model.layers.19.mlp.gate_proj.weight +24-11-19 20:31:48 | D | + w: sint8 +24-11-19 20:31:48 | D | + x: None +24-11-19 20:31:48 | D | + y: None +24-11-19 20:31:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:48 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:31:48 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:31:48 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:31:48 | D | - range ratio = [ 1.0000] +24-11-19 20:31:48 | D | sum error = [ 8.7897] +24-11-19 20:31:48 | D | best error = [ 8.7897] +24-11-19 20:31:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:50 | D | sum error = [ 8.7252, 8.7154, 8.7478, 8.8186, 9.0158] +24-11-19 20:31:50 | D | best error = [ 8.1413, 7.9016, 7.7734, 7.7009, 7.6608] +24-11-19 20:31:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:50 | D | sum error = [ 9.2218, 9.5534, 9.9452, 10.4360, 10.9775] +24-11-19 20:31:50 | D | best error = [ 7.6407, 7.6327, 7.6295, 7.6289, 7.6288] +24-11-19 20:31:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:50 | D | sum error = [ 11.6517, 12.3518, 13.1938, 14.0683, 15.0732] +24-11-19 20:31:50 | D | best error = [ 7.6286, 7.6286, 7.6286, 7.6286, 7.6286] +24-11-19 20:31:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:50 | D | sum error = [ 16.1477, 17.3154, 18.5731, 19.9119, 21.3774] +24-11-19 20:31:50 | D | best error = [ 7.6286, 7.6286, 7.6286, 7.6286, 7.6286] +24-11-19 20:31:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:50 | D | sum error = [ 22.9249, 24.6106, 26.3692, 28.2316, 30.2430] +24-11-19 20:31:50 | D | best error = [ 7.6286, 7.6286, 7.6286, 7.6286, 7.6286] +24-11-19 20:31:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:50 | D | sum error = [ 32.3735, 34.6329, 37.0569, 39.5940, 42.3187] +24-11-19 20:31:50 | D | best error = [ 7.6286, 7.6286, 7.6286, 7.6286, 7.6286] +24-11-19 20:31:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:50 | D | sum error = [ 45.1769, 48.2114, 51.4341, 54.8724, 58.4745] +24-11-19 20:31:50 | D | best error = [ 7.6286, 7.6286, 7.6286, 7.6286, 7.6286] +24-11-19 20:31:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:50 | D | sum error = [ 62.3056, 66.3516, 70.6754, 75.2008, 80.0125] +24-11-19 20:31:50 | D | best error = [ 7.6286, 7.6286, 7.6286, 7.6286, 7.6286] +24-11-19 20:31:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:50 | D | sum error = [ 85.0877, 90.4900, 96.1742, 102.2033, 108.5783] +24-11-19 20:31:50 | D | best error = [ 7.6286, 7.6286, 7.6286, 7.6286, 7.6286] +24-11-19 20:31:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:50 | D | sum error = [ 115.2930, 122.4213, 129.8793, 137.7795, 146.1060] +24-11-19 20:31:50 | D | best error = [ 7.6286, 7.6286, 7.6286, 7.6286, 7.6286] +24-11-19 20:31:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:50 | D | sum error = [ 154.8562, 164.0649, 173.7671, 184.0225, 194.7765] +24-11-19 20:31:50 | D | best error = [ 7.6286, 7.6286, 7.6286, 7.6286, 7.6286] +24-11-19 20:31:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:50 | D | sum error = [ 206.0453, 217.9129, 230.3645, 243.4297, 257.1232] +24-11-19 20:31:50 | D | best error = [ 7.6286, 7.6286, 7.6286, 7.6286, 7.6286] +24-11-19 20:31:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:50 | D | sum error = [ 271.4798, 286.4907, 302.2092, 318.6300, 335.7899] +24-11-19 20:31:50 | D | best error = [ 7.6286, 7.6286, 7.6286, 7.6286, 7.6286] +24-11-19 20:31:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:50 | D | sum error = [ 353.7466, 372.4661, 391.9841, 412.3532, 433.5288] +24-11-19 20:31:50 | D | best error = [ 7.6286, 7.6286, 7.6286, 7.6286, 7.6286] +24-11-19 20:31:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:50 | D | sum error = [ 455.5866, 478.4887, 502.2529, 526.8824, 552.4228] +24-11-19 20:31:50 | D | best error = [ 7.6286, 7.6286, 7.6286, 7.6286, 7.6286] +24-11-19 20:31:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:50 | D | sum error = [ 578.7987, 606.0663, 634.2277, 663.2444, 693.1745] +24-11-19 20:31:50 | D | best error = [ 7.6286, 7.6286, 7.6286, 7.6286, 7.6286] +24-11-19 20:31:50 | D | + error = [7.6286] +24-11-19 20:31:50 | D | - Calibrating model.layers.19.mlp.down_proj.weight +24-11-19 20:31:50 | D | + w: sint8 +24-11-19 20:31:50 | D | + x: None +24-11-19 20:31:50 | D | + y: None +24-11-19 20:31:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:50 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:31:50 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:31:50 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:31:50 | D | - range ratio = [ 1.0000] +24-11-19 20:31:50 | D | sum error = [ 0.9893] +24-11-19 20:31:50 | D | best error = [ 0.9893] +24-11-19 20:31:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:51 | D | sum error = [ 0.9835, 0.9754, 0.9692, 0.9637, 0.9633] +24-11-19 20:31:51 | D | best error = [ 0.9520, 0.9325, 0.9196, 0.9091, 0.9010] +24-11-19 20:31:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:51 | D | sum error = [ 0.9638, 0.9674, 0.9748, 0.9846, 0.9998] +24-11-19 20:31:51 | D | best error = [ 0.8951, 0.8900, 0.8860, 0.8831, 0.8809] +24-11-19 20:31:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:51 | D | sum error = [ 1.0199, 1.0462, 1.0778, 1.1125, 1.1565] +24-11-19 20:31:51 | D | best error = [ 0.8792, 0.8781, 0.8775, 0.8769, 0.8766] +24-11-19 20:31:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:51 | D | sum error = [ 1.2058, 1.2615, 1.3248, 1.3957, 1.4771] +24-11-19 20:31:51 | D | best error = [ 0.8763, 0.8762, 0.8761, 0.8760, 0.8760] +24-11-19 20:31:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:51 | D | sum error = [ 1.5649, 1.6607, 1.7651, 1.8798, 2.0055] +24-11-19 20:31:51 | D | best error = [ 0.8760, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 20:31:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:51 | D | sum error = [ 2.1373, 2.2859, 2.4424, 2.6091, 2.7919] +24-11-19 20:31:51 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 20:31:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:51 | D | sum error = [ 2.9842, 3.1909, 3.4139, 3.6487, 3.9004] +24-11-19 20:31:51 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 20:31:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:51 | D | sum error = [ 4.1664, 4.4509, 4.7538, 5.0751, 5.4138] +24-11-19 20:31:51 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 20:31:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:51 | D | sum error = [ 5.7748, 6.1569, 6.5610, 6.9888, 7.4419] +24-11-19 20:31:51 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 20:31:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:51 | D | sum error = [ 7.9200, 8.4235, 8.9569, 9.5169, 10.1087] +24-11-19 20:31:51 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 20:31:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:51 | D | sum error = [ 10.7303, 11.3874, 12.0748, 12.7996, 13.5585] +24-11-19 20:31:51 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 20:31:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:51 | D | sum error = [ 14.3569, 15.1947, 16.0730, 16.9920, 17.9542] +24-11-19 20:31:51 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 20:31:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:51 | D | sum error = [ 18.9609, 20.0151, 21.1158, 22.2636, 23.4609] +24-11-19 20:31:51 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 20:31:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:51 | D | sum error = [ 24.7092, 26.0100, 27.3627, 28.7715, 30.2341] +24-11-19 20:31:51 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 20:31:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:51 | D | sum error = [ 31.7540, 33.3339, 34.9735, 36.6735, 38.4362] +24-11-19 20:31:51 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 20:31:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:51 | D | sum error = [ 40.2626, 42.1529, 44.1085, 46.1285, 48.2123] +24-11-19 20:31:51 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 20:31:51 | D | + error = [0.8759] +24-11-19 20:31:51 | D | - Quantizing model.layers.19.self_attn.q_proj.weight +24-11-19 20:31:52 | D | - Quantizing model.layers.19.self_attn.k_proj.weight +24-11-19 20:31:53 | D | - Quantizing model.layers.19.self_attn.v_proj.weight +24-11-19 20:31:54 | D | - Quantizing model.layers.19.self_attn.o_proj.weight +24-11-19 20:31:55 | D | - Quantizing model.layers.19.mlp.up_proj.weight +24-11-19 20:31:55 | D | - Quantizing model.layers.19.mlp.gate_proj.weight +24-11-19 20:31:56 | D | - Quantizing model.layers.19.mlp.down_proj.weight +24-11-19 20:32:06 | D | - Quantizing layer model.layers.20 +24-11-19 20:32:06 | D | - Calibrating model.layers.20.self_attn.q_proj.weight +24-11-19 20:32:06 | D | + w: sint8 +24-11-19 20:32:06 | D | + x: None +24-11-19 20:32:06 | D | + y: None +24-11-19 20:32:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:32:06 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:32:06 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:32:07 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:32:07 | D | - range ratio = [ 1.0000] +24-11-19 20:32:07 | D | sum error = [ 3.9133] +24-11-19 20:32:07 | D | best error = [ 3.9133] +24-11-19 20:32:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:19 | D | sum error = [ 3.8408, 3.8512, 3.8782, 3.9104, 4.0355] +24-11-19 20:32:19 | D | best error = [ 3.8408, 3.8408, 3.8408, 3.8408, 3.8408] +24-11-19 20:32:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:19 | D | sum error = [ 4.1056, 4.2966, 4.4659, 4.7130, 4.8725] +24-11-19 20:32:19 | D | best error = [ 3.8408, 3.8408, 3.8408, 3.8408, 3.8408] +24-11-19 20:32:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:19 | D | sum error = [ 5.1569, 5.5024, 5.9707, 6.5179, 6.9974] +24-11-19 20:32:19 | D | best error = [ 3.8408, 3.8408, 3.8408, 3.8408, 3.8408] +24-11-19 20:32:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:19 | D | sum error = [ 7.7322, 8.1344, 8.8141, 10.0951, 10.7650] +24-11-19 20:32:19 | D | best error = [ 3.8408, 3.8408, 3.8408, 3.8408, 3.8408] +24-11-19 20:32:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:19 | D | sum error = [ 11.8638, 13.2217, 14.5589, 16.0171, 17.4598] +24-11-19 20:32:19 | D | best error = [ 3.8408, 3.8408, 3.8408, 3.8408, 3.8408] +24-11-19 20:32:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:19 | D | sum error = [ 19.2985, 21.4529, 23.5522, 25.7587, 28.5313] +24-11-19 20:32:19 | D | best error = [ 3.8408, 3.8408, 3.8408, 3.8408, 3.8408] +24-11-19 20:32:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:19 | D | sum error = [ 31.1700, 34.3823, 37.8847, 41.6759, 45.7799] +24-11-19 20:32:19 | D | best error = [ 3.8408, 3.8408, 3.8408, 3.8408, 3.8408] +24-11-19 20:32:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:19 | D | sum error = [ 50.6349, 55.5974, 61.1592, 67.5443, 74.3565] +24-11-19 20:32:19 | D | best error = [ 3.8408, 3.8408, 3.8408, 3.8408, 3.8408] +24-11-19 20:32:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:19 | D | sum error = [ 81.5558, 89.4921, 98.2780, 107.1852, 117.6587] +24-11-19 20:32:19 | D | best error = [ 3.8408, 3.8408, 3.8408, 3.8408, 3.8408] +24-11-19 20:32:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:19 | D | sum error = [ 129.4584, 141.3558, 156.0875, 170.8175, 187.3555] +24-11-19 20:32:19 | D | best error = [ 3.8408, 3.8408, 3.8408, 3.8408, 3.8408] +24-11-19 20:32:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:19 | D | sum error = [ 205.8331, 226.1960, 247.9985, 272.1458, 299.0399] +24-11-19 20:32:19 | D | best error = [ 3.8408, 3.8408, 3.8408, 3.8408, 3.8408] +24-11-19 20:32:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:19 | D | sum error = [ 328.1470, 360.3313, 396.5690, 436.5459, 480.6794] +24-11-19 20:32:19 | D | best error = [ 3.8408, 3.8408, 3.8408, 3.8408, 3.8408] +24-11-19 20:32:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:19 | D | sum error = [ 528.4459, 582.8735, 641.8859, 708.3003, 781.5856] +24-11-19 20:32:19 | D | best error = [ 3.8408, 3.8408, 3.8408, 3.8408, 3.8408] +24-11-19 20:32:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:19 | D | sum error = [ 862.0121, 951.0240, 1048.7978, 1155.4218, 1271.2844] +24-11-19 20:32:19 | D | best error = [ 3.8408, 3.8408, 3.8408, 3.8408, 3.8408] +24-11-19 20:32:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:19 | D | sum error = [ 1397.8819, 1536.8486, 1684.4958, 1843.8974, 2011.5728] +24-11-19 20:32:19 | D | best error = [ 3.8408, 3.8408, 3.8408, 3.8408, 3.8408] +24-11-19 20:32:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:19 | D | sum error = [ 2186.1464, 2365.2897, 2546.7898, 2727.0724, 2906.3622] +24-11-19 20:32:19 | D | best error = [ 3.8408, 3.8408, 3.8408, 3.8408, 3.8408] +24-11-19 20:32:19 | D | + error = [3.8408] +24-11-19 20:32:19 | D | - Calibrating model.layers.20.self_attn.k_proj.weight +24-11-19 20:32:19 | D | + w: sint8 +24-11-19 20:32:19 | D | + x: None +24-11-19 20:32:19 | D | + y: None +24-11-19 20:32:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:32:19 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:32:19 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:32:19 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:32:20 | D | - range ratio = [ 1.0000] +24-11-19 20:32:20 | D | sum error = [ 3.9855] +24-11-19 20:32:20 | D | best error = [ 3.9855] +24-11-19 20:32:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:31 | D | sum error = [ 3.9501, 3.9207, 3.9392, 3.6963, 3.9948] +24-11-19 20:32:31 | D | best error = [ 3.9501, 3.9207, 3.9207, 3.6963, 3.6963] +24-11-19 20:32:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:31 | D | sum error = [ 4.0315, 4.3745, 4.4623, 5.0163, 6.1136] +24-11-19 20:32:31 | D | best error = [ 3.6963, 3.6963, 3.6963, 3.6963, 3.6963] +24-11-19 20:32:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:31 | D | sum error = [ 5.5107, 6.2889, 8.0756, 7.5051, 9.0085] +24-11-19 20:32:31 | D | best error = [ 3.6963, 3.6963, 3.6963, 3.6963, 3.6963] +24-11-19 20:32:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:31 | D | sum error = [ 9.0921, 9.9352, 11.2091, 12.9698, 11.8418] +24-11-19 20:32:31 | D | best error = [ 3.6963, 3.6963, 3.6963, 3.6963, 3.6963] +24-11-19 20:32:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:31 | D | sum error = [ 13.8021, 14.0310, 16.8067, 16.7960, 18.2206] +24-11-19 20:32:31 | D | best error = [ 3.6963, 3.6963, 3.6963, 3.6963, 3.6963] +24-11-19 20:32:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:31 | D | sum error = [ 19.3289, 20.6696, 21.9594, 24.3529, 26.5926] +24-11-19 20:32:31 | D | best error = [ 3.6963, 3.6963, 3.6963, 3.6963, 3.6963] +24-11-19 20:32:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:31 | D | sum error = [ 29.7281, 33.6334, 37.3809, 38.8516, 41.2692] +24-11-19 20:32:31 | D | best error = [ 3.6963, 3.6963, 3.6963, 3.6963, 3.6963] +24-11-19 20:32:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:31 | D | sum error = [ 47.4061, 51.3821, 55.2690, 60.4337, 66.0935] +24-11-19 20:32:31 | D | best error = [ 3.6963, 3.6963, 3.6963, 3.6963, 3.6963] +24-11-19 20:32:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:31 | D | sum error = [ 70.0590, 75.9622, 83.3853, 90.9353, 99.0012] +24-11-19 20:32:31 | D | best error = [ 3.6963, 3.6963, 3.6963, 3.6963, 3.6963] +24-11-19 20:32:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:31 | D | sum error = [ 107.9439, 117.4001, 129.3458, 140.9443, 153.6062] +24-11-19 20:32:31 | D | best error = [ 3.6963, 3.6963, 3.6963, 3.6963, 3.6963] +24-11-19 20:32:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:31 | D | sum error = [ 168.5978, 184.4479, 201.7659, 223.0381, 244.1155] +24-11-19 20:32:31 | D | best error = [ 3.6963, 3.6963, 3.6963, 3.6963, 3.6963] +24-11-19 20:32:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:31 | D | sum error = [ 269.0435, 295.4484, 324.4260, 359.0557, 395.9452] +24-11-19 20:32:31 | D | best error = [ 3.6963, 3.6963, 3.6963, 3.6963, 3.6963] +24-11-19 20:32:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:31 | D | sum error = [ 437.6212, 483.3682, 536.9300, 599.1771, 665.6715] +24-11-19 20:32:31 | D | best error = [ 3.6963, 3.6963, 3.6963, 3.6963, 3.6963] +24-11-19 20:32:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:31 | D | sum error = [ 741.6897, 824.9211, 915.2645, 1019.0321, 1131.1273] +24-11-19 20:32:31 | D | best error = [ 3.6963, 3.6963, 3.6963, 3.6963, 3.6963] +24-11-19 20:32:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:31 | D | sum error = [ 1253.2628, 1386.2145, 1525.4427, 1686.5356, 1853.5757] +24-11-19 20:32:31 | D | best error = [ 3.6963, 3.6963, 3.6963, 3.6963, 3.6963] +24-11-19 20:32:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:31 | D | sum error = [ 2034.4630, 2221.5818, 2401.2514, 2591.9215, 2777.1266] +24-11-19 20:32:31 | D | best error = [ 3.6963, 3.6963, 3.6963, 3.6963, 3.6963] +24-11-19 20:32:31 | D | + error = [3.6963] +24-11-19 20:32:31 | D | - Calibrating model.layers.20.self_attn.v_proj.weight +24-11-19 20:32:31 | D | + w: sint8 +24-11-19 20:32:31 | D | + x: None +24-11-19 20:32:31 | D | + y: None +24-11-19 20:32:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:31 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:32:32 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:32:32 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:32:32 | D | - range ratio = [ 1.0000] +24-11-19 20:32:32 | D | sum error = [ 1.7736] +24-11-19 20:32:32 | D | best error = [ 1.7736] +24-11-19 20:32:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:32 | D | sum error = [ 1.7582, 1.7438, 1.7643, 1.7672, 1.8085] +24-11-19 20:32:32 | D | best error = [ 1.6387, 1.5847, 1.5594, 1.5454, 1.5366] +24-11-19 20:32:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:32 | D | sum error = [ 1.8776, 1.9164, 2.0074, 2.0977, 2.2089] +24-11-19 20:32:32 | D | best error = [ 1.5336, 1.5325, 1.5316, 1.5312, 1.5312] +24-11-19 20:32:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:32 | D | sum error = [ 2.3412, 2.5020, 2.6579, 2.8426, 3.0290] +24-11-19 20:32:32 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:32:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:32 | D | sum error = [ 3.2550, 3.4786, 3.7390, 4.0022, 4.3065] +24-11-19 20:32:32 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:32:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:32 | D | sum error = [ 4.5963, 4.9113, 5.2878, 5.6582, 6.0506] +24-11-19 20:32:32 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:32:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:32 | D | sum error = [ 6.4594, 6.9312, 7.3972, 7.8912, 8.4277] +24-11-19 20:32:32 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:32:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:32 | D | sum error = [ 8.9735, 9.5765, 10.1877, 10.8319, 11.5143] +24-11-19 20:32:32 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:32:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:32 | D | sum error = [ 12.2360, 13.0083, 13.7885, 14.6184, 15.4932] +24-11-19 20:32:32 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:32:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:32 | D | sum error = [ 16.4089, 17.3815, 18.3989, 19.4507, 20.5690] +24-11-19 20:32:32 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:32:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:32 | D | sum error = [ 21.7319, 22.9576, 24.2359, 25.5715, 26.9723] +24-11-19 20:32:32 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:32:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:32 | D | sum error = [ 28.4514, 29.9863, 31.5791, 33.2400, 34.9747] +24-11-19 20:32:32 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:32:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:32 | D | sum error = [ 36.7754, 38.6537, 40.6084, 42.6395, 44.7586] +24-11-19 20:32:32 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:32:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:32 | D | sum error = [ 46.9631, 49.2417, 51.6177, 54.0614, 56.6113] +24-11-19 20:32:32 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:32:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:32 | D | sum error = [ 59.2581, 61.9887, 64.8259, 67.7659, 70.8088] +24-11-19 20:32:32 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:32:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:32 | D | sum error = [ 73.9647, 77.2172, 80.5848, 84.0490, 87.6265] +24-11-19 20:32:32 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:32:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:32 | D | sum error = [ 91.3162, 95.0975, 98.9974, 102.9923, 107.1094] +24-11-19 20:32:32 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:32:32 | D | + error = [1.5312] +24-11-19 20:32:32 | D | - Calibrating model.layers.20.self_attn.o_proj.weight +24-11-19 20:32:32 | D | + w: sint8 +24-11-19 20:32:32 | D | + x: None +24-11-19 20:32:32 | D | + y: None +24-11-19 20:32:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:32 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:32:32 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:32:32 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:32:32 | D | - range ratio = [ 1.0000] +24-11-19 20:32:32 | D | sum error = [ 0.3942] +24-11-19 20:32:32 | D | best error = [ 0.3942] +24-11-19 20:32:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:33 | D | sum error = [ 0.3910, 0.3898, 0.3907, 0.3927, 0.3999] +24-11-19 20:32:33 | D | best error = [ 0.3712, 0.3608, 0.3546, 0.3503, 0.3478] +24-11-19 20:32:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:33 | D | sum error = [ 0.4069, 0.4173, 0.4312, 0.4466, 0.4671] +24-11-19 20:32:33 | D | best error = [ 0.3459, 0.3447, 0.3439, 0.3432, 0.3428] +24-11-19 20:32:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:33 | D | sum error = [ 0.4899, 0.5138, 0.5443, 0.5763, 0.6106] +24-11-19 20:32:33 | D | best error = [ 0.3426, 0.3424, 0.3423, 0.3422, 0.3422] +24-11-19 20:32:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:33 | D | sum error = [ 0.6510, 0.6931, 0.7384, 0.7868, 0.8398] +24-11-19 20:32:33 | D | best error = [ 0.3421, 0.3421, 0.3421, 0.3421, 0.3420] +24-11-19 20:32:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:33 | D | sum error = [ 0.8961, 0.9556, 1.0189, 1.0869, 1.1585] +24-11-19 20:32:33 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:32:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:33 | D | sum error = [ 1.2344, 1.3140, 1.3992, 1.4895, 1.5835] +24-11-19 20:32:33 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:32:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:33 | D | sum error = [ 1.6841, 1.7884, 1.9003, 2.0169, 2.1411] +24-11-19 20:32:33 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:32:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:33 | D | sum error = [ 2.2701, 2.4064, 2.5504, 2.7023, 2.8603] +24-11-19 20:32:33 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:32:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:33 | D | sum error = [ 3.0276, 3.2009, 3.3839, 3.5761, 3.7784] +24-11-19 20:32:33 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:32:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:33 | D | sum error = [ 3.9886, 4.2090, 4.4408, 4.6820, 4.9354] +24-11-19 20:32:33 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:32:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:33 | D | sum error = [ 5.1999, 5.4767, 5.7645, 6.0661, 6.3810] +24-11-19 20:32:33 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:32:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:33 | D | sum error = [ 6.7104, 7.0531, 7.4102, 7.7829, 8.1708] +24-11-19 20:32:33 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:32:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:33 | D | sum error = [ 8.5759, 8.9966, 9.4343, 9.8906, 10.3640] +24-11-19 20:32:33 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:32:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:33 | D | sum error = [ 10.8556, 11.3658, 11.8951, 12.4448, 13.0128] +24-11-19 20:32:33 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:32:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:33 | D | sum error = [ 13.6008, 14.2096, 14.8393, 15.4911, 16.1648] +24-11-19 20:32:33 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:32:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:33 | D | sum error = [ 16.8614, 17.5814, 18.3238, 19.0898, 19.8792] +24-11-19 20:32:33 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:32:33 | D | + error = [0.3420] +24-11-19 20:32:33 | D | - Calibrating model.layers.20.mlp.up_proj.weight +24-11-19 20:32:33 | D | + w: sint8 +24-11-19 20:32:33 | D | + x: None +24-11-19 20:32:33 | D | + y: None +24-11-19 20:32:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:33 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:32:33 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:32:33 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:32:33 | D | - range ratio = [ 1.0000] +24-11-19 20:32:33 | D | sum error = [ 6.7132] +24-11-19 20:32:33 | D | best error = [ 6.7132] +24-11-19 20:32:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:34 | D | sum error = [ 6.6595, 6.6497, 6.6919, 6.7611, 6.8796] +24-11-19 20:32:34 | D | best error = [ 6.2417, 6.0590, 5.9612, 5.9073, 5.8779] +24-11-19 20:32:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:34 | D | sum error = [ 7.0659, 7.3003, 7.6010, 7.9470, 8.3617] +24-11-19 20:32:34 | D | best error = [ 5.8638, 5.8578, 5.8560, 5.8555, 5.8554] +24-11-19 20:32:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:34 | D | sum error = [ 8.8512, 9.3928, 9.9933, 10.6768, 11.4226] +24-11-19 20:32:34 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:32:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:34 | D | sum error = [ 12.2094, 13.0857, 14.0368, 15.0242, 16.1102] +24-11-19 20:32:34 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:32:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:34 | D | sum error = [ 17.2629, 18.4871, 19.7821, 21.1576, 22.6246] +24-11-19 20:32:34 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:32:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:34 | D | sum error = [ 24.1821, 25.8155, 27.5715, 29.3924, 31.3218] +24-11-19 20:32:34 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:32:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:34 | D | sum error = [ 33.3659, 35.5100, 37.7793, 40.1737, 42.6910] +24-11-19 20:32:34 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:32:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:34 | D | sum error = [ 45.3059, 48.0827, 50.9990, 54.0418, 57.2412] +24-11-19 20:32:34 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:32:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:34 | D | sum error = [ 60.5992, 64.1207, 67.7985, 71.6575, 75.7006] +24-11-19 20:32:34 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:32:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:34 | D | sum error = [ 79.9195, 84.3376, 88.9364, 93.7350, 98.7492] +24-11-19 20:32:34 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:32:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:34 | D | sum error = [ 103.9695, 109.4229, 115.0952, 121.0245, 127.1725] +24-11-19 20:32:34 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:32:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:34 | D | sum error = [ 133.5761, 140.2183, 147.1311, 154.2767, 161.7127] +24-11-19 20:32:34 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:32:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:34 | D | sum error = [ 169.4183, 177.4112, 185.6899, 194.2595, 203.1362] +24-11-19 20:32:34 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:32:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:34 | D | sum error = [ 212.2999, 221.7842, 231.5760, 241.6961, 252.1278] +24-11-19 20:32:34 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:32:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:34 | D | sum error = [ 262.9039, 274.0084, 285.4544, 297.2435, 309.3847] +24-11-19 20:32:34 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:32:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:34 | D | sum error = [ 321.8880, 334.7514, 347.9788, 361.5719, 375.5384] +24-11-19 20:32:34 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:32:34 | D | + error = [5.8554] +24-11-19 20:32:34 | D | - Calibrating model.layers.20.mlp.gate_proj.weight +24-11-19 20:32:34 | D | + w: sint8 +24-11-19 20:32:34 | D | + x: None +24-11-19 20:32:34 | D | + y: None +24-11-19 20:32:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:34 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:32:34 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:32:34 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:32:34 | D | - range ratio = [ 1.0000] +24-11-19 20:32:34 | D | sum error = [ 9.0694] +24-11-19 20:32:34 | D | best error = [ 9.0694] +24-11-19 20:32:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:36 | D | sum error = [ 8.9874, 8.9778, 9.0108, 9.1162, 9.2854] +24-11-19 20:32:36 | D | best error = [ 8.4127, 8.1687, 8.0395, 7.9664, 7.9270] +24-11-19 20:32:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:36 | D | sum error = [ 9.5321, 9.8504, 10.2551, 10.7274, 11.3055] +24-11-19 20:32:36 | D | best error = [ 7.9086, 7.9009, 7.8978, 7.8968, 7.8965] +24-11-19 20:32:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:36 | D | sum error = [ 11.9364, 12.6698, 13.5204, 14.4277, 15.4422] +24-11-19 20:32:36 | D | best error = [ 7.8964, 7.8964, 7.8964, 7.8964, 7.8964] +24-11-19 20:32:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:36 | D | sum error = [ 16.5347, 17.7009, 19.0065, 20.3584, 21.8501] +24-11-19 20:32:36 | D | best error = [ 7.8964, 7.8964, 7.8964, 7.8964, 7.8964] +24-11-19 20:32:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:36 | D | sum error = [ 23.4200, 25.0950, 26.9034, 28.8102, 30.8711] +24-11-19 20:32:36 | D | best error = [ 7.8964, 7.8964, 7.8964, 7.8964, 7.8964] +24-11-19 20:32:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:36 | D | sum error = [ 33.0291, 35.3435, 37.7802, 40.3976, 43.1417] +24-11-19 20:32:36 | D | best error = [ 7.8964, 7.8964, 7.8964, 7.8964, 7.8964] +24-11-19 20:32:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:36 | D | sum error = [ 46.0812, 49.2017, 52.4725, 55.9555, 59.6395] +24-11-19 20:32:36 | D | best error = [ 7.8964, 7.8964, 7.8964, 7.8964, 7.8964] +24-11-19 20:32:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:36 | D | sum error = [ 63.5451, 67.6757, 72.0343, 76.6627, 81.5513] +24-11-19 20:32:36 | D | best error = [ 7.8964, 7.8964, 7.8964, 7.8964, 7.8964] +24-11-19 20:32:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:36 | D | sum error = [ 86.7036, 92.1719, 97.9538, 104.0568, 110.4901] +24-11-19 20:32:36 | D | best error = [ 7.8964, 7.8964, 7.8964, 7.8964, 7.8964] +24-11-19 20:32:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:36 | D | sum error = [ 117.2961, 124.4799, 132.0232, 139.9732, 148.3740] +24-11-19 20:32:36 | D | best error = [ 7.8964, 7.8964, 7.8964, 7.8964, 7.8964] +24-11-19 20:32:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:36 | D | sum error = [ 157.2043, 166.4985, 176.2504, 186.5441, 197.3483] +24-11-19 20:32:36 | D | best error = [ 7.8964, 7.8964, 7.8964, 7.8964, 7.8964] +24-11-19 20:32:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:36 | D | sum error = [ 208.6621, 220.5630, 233.0907, 246.1942, 259.9413] +24-11-19 20:32:36 | D | best error = [ 7.8964, 7.8964, 7.8964, 7.8964, 7.8964] +24-11-19 20:32:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:36 | D | sum error = [ 274.3449, 289.3741, 305.1344, 321.5913, 338.7911] +24-11-19 20:32:36 | D | best error = [ 7.8964, 7.8964, 7.8964, 7.8964, 7.8964] +24-11-19 20:32:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:36 | D | sum error = [ 356.7584, 375.4913, 395.0083, 415.3168, 436.4294] +24-11-19 20:32:36 | D | best error = [ 7.8964, 7.8964, 7.8964, 7.8964, 7.8964] +24-11-19 20:32:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:36 | D | sum error = [ 458.3730, 481.1768, 504.8509, 529.3841, 554.8009] +24-11-19 20:32:36 | D | best error = [ 7.8964, 7.8964, 7.8964, 7.8964, 7.8964] +24-11-19 20:32:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:36 | D | sum error = [ 581.0647, 608.2260, 636.2738, 665.2367, 695.0849] +24-11-19 20:32:36 | D | best error = [ 7.8964, 7.8964, 7.8964, 7.8964, 7.8964] +24-11-19 20:32:36 | D | + error = [7.8964] +24-11-19 20:32:36 | D | - Calibrating model.layers.20.mlp.down_proj.weight +24-11-19 20:32:36 | D | + w: sint8 +24-11-19 20:32:36 | D | + x: None +24-11-19 20:32:36 | D | + y: None +24-11-19 20:32:36 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:36 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:32:36 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:32:36 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:32:36 | D | - range ratio = [ 1.0000] +24-11-19 20:32:36 | D | sum error = [ 1.0446] +24-11-19 20:32:36 | D | best error = [ 1.0446] +24-11-19 20:32:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:37 | D | sum error = [ 1.0354, 1.0262, 1.0177, 1.0130, 1.0125] +24-11-19 20:32:37 | D | best error = [ 1.0020, 0.9806, 0.9655, 0.9548, 0.9462] +24-11-19 20:32:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:37 | D | sum error = [ 1.0128, 1.0173, 1.0232, 1.0326, 1.0463] +24-11-19 20:32:37 | D | best error = [ 0.9391, 0.9335, 0.9292, 0.9257, 0.9229] +24-11-19 20:32:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:37 | D | sum error = [ 1.0693, 1.0918, 1.1249, 1.1632, 1.2052] +24-11-19 20:32:37 | D | best error = [ 0.9213, 0.9201, 0.9193, 0.9188, 0.9184] +24-11-19 20:32:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:37 | D | sum error = [ 1.2558, 1.3140, 1.3809, 1.4551, 1.5368] +24-11-19 20:32:37 | D | best error = [ 0.9180, 0.9179, 0.9179, 0.9178, 0.9178] +24-11-19 20:32:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:37 | D | sum error = [ 1.6304, 1.7329, 1.8441, 1.9643, 2.0997] +24-11-19 20:32:37 | D | best error = [ 0.9178, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 20:32:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:37 | D | sum error = [ 2.2419, 2.3992, 2.5662, 2.7461, 2.9386] +24-11-19 20:32:37 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 20:32:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:37 | D | sum error = [ 3.1433, 3.3639, 3.6003, 3.8500, 4.1185] +24-11-19 20:32:37 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 20:32:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:37 | D | sum error = [ 4.4010, 4.7033, 5.0231, 5.3622, 5.7214] +24-11-19 20:32:37 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 20:32:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:37 | D | sum error = [ 6.1034, 6.5044, 6.9305, 7.3820, 7.8595] +24-11-19 20:32:37 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 20:32:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:37 | D | sum error = [ 8.3597, 8.8883, 9.4477, 10.0364, 10.6568] +24-11-19 20:32:37 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 20:32:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:37 | D | sum error = [ 11.3096, 11.9972, 12.7193, 13.4774, 14.2736] +24-11-19 20:32:37 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 20:32:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:37 | D | sum error = [ 15.1093, 15.9861, 16.9034, 17.8631, 18.8684] +24-11-19 20:32:37 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 20:32:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:37 | D | sum error = [ 19.9182, 21.0174, 22.1653, 23.3627, 24.6129] +24-11-19 20:32:37 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 20:32:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:37 | D | sum error = [ 25.9165, 27.2723, 28.6875, 30.1591, 31.6878] +24-11-19 20:32:37 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 20:32:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:37 | D | sum error = [ 33.2777, 34.9303, 36.6464, 38.4276, 40.2728] +24-11-19 20:32:37 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 20:32:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:37 | D | sum error = [ 42.1875, 44.1691, 46.2192, 48.3404, 50.5324] +24-11-19 20:32:37 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 20:32:37 | D | + error = [0.9177] +24-11-19 20:32:37 | D | - Quantizing model.layers.20.self_attn.q_proj.weight +24-11-19 20:32:38 | D | - Quantizing model.layers.20.self_attn.k_proj.weight +24-11-19 20:32:39 | D | - Quantizing model.layers.20.self_attn.v_proj.weight +24-11-19 20:32:40 | D | - Quantizing model.layers.20.self_attn.o_proj.weight +24-11-19 20:32:40 | D | - Quantizing model.layers.20.mlp.up_proj.weight +24-11-19 20:32:41 | D | - Quantizing model.layers.20.mlp.gate_proj.weight +24-11-19 20:32:42 | D | - Quantizing model.layers.20.mlp.down_proj.weight +24-11-19 20:32:51 | D | - Quantizing layer model.layers.21 +24-11-19 20:32:51 | D | - Calibrating model.layers.21.self_attn.q_proj.weight +24-11-19 20:32:51 | D | + w: sint8 +24-11-19 20:32:51 | D | + x: None +24-11-19 20:32:51 | D | + y: None +24-11-19 20:32:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:32:51 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:32:52 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:32:52 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:32:52 | D | - range ratio = [ 1.0000] +24-11-19 20:32:52 | D | sum error = [ 4.4958] +24-11-19 20:32:52 | D | best error = [ 4.4958] +24-11-19 20:33:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:04 | D | sum error = [ 4.4708, 4.3709, 4.4698, 4.4838, 4.6414] +24-11-19 20:33:04 | D | best error = [ 4.4708, 4.3709, 4.3709, 4.3709, 4.3709] +24-11-19 20:33:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:04 | D | sum error = [ 4.6544, 4.7697, 5.1954, 5.3140, 5.5799] +24-11-19 20:33:04 | D | best error = [ 4.3709, 4.3709, 4.3709, 4.3709, 4.3709] +24-11-19 20:33:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:04 | D | sum error = [ 5.9090, 6.2656, 6.7200, 7.1814, 7.7543] +24-11-19 20:33:04 | D | best error = [ 4.3709, 4.3709, 4.3709, 4.3709, 4.3709] +24-11-19 20:33:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:04 | D | sum error = [ 8.3799, 9.1786, 9.9406, 10.5495, 11.6750] +24-11-19 20:33:04 | D | best error = [ 4.3709, 4.3709, 4.3709, 4.3709, 4.3709] +24-11-19 20:33:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:04 | D | sum error = [ 12.7174, 13.8965, 15.0483, 16.3941, 17.9031] +24-11-19 20:33:04 | D | best error = [ 4.3709, 4.3709, 4.3709, 4.3709, 4.3709] +24-11-19 20:33:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:04 | D | sum error = [ 19.4042, 20.9844, 22.5707, 24.4023, 26.4855] +24-11-19 20:33:04 | D | best error = [ 4.3709, 4.3709, 4.3709, 4.3709, 4.3709] +24-11-19 20:33:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:04 | D | sum error = [ 28.4855, 30.9114, 33.1868, 36.0112, 38.8754] +24-11-19 20:33:04 | D | best error = [ 4.3709, 4.3709, 4.3709, 4.3709, 4.3709] +24-11-19 20:33:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:04 | D | sum error = [ 42.0191, 45.4535, 49.1028, 53.2837, 57.2959] +24-11-19 20:33:04 | D | best error = [ 4.3709, 4.3709, 4.3709, 4.3709, 4.3709] +24-11-19 20:33:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:04 | D | sum error = [ 61.8508, 67.1250, 72.5763, 78.5053, 84.9743] +24-11-19 20:33:04 | D | best error = [ 4.3709, 4.3709, 4.3709, 4.3709, 4.3709] +24-11-19 20:33:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:04 | D | sum error = [ 91.9500, 99.6084, 107.9333, 116.9584, 126.7154] +24-11-19 20:33:04 | D | best error = [ 4.3709, 4.3709, 4.3709, 4.3709, 4.3709] +24-11-19 20:33:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:04 | D | sum error = [ 137.2657, 148.6258, 161.1130, 174.4357, 188.6027] +24-11-19 20:33:04 | D | best error = [ 4.3709, 4.3709, 4.3709, 4.3709, 4.3709] +24-11-19 20:33:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:04 | D | sum error = [ 204.4974, 221.4285, 239.6986, 259.9464, 281.6074] +24-11-19 20:33:04 | D | best error = [ 4.3709, 4.3709, 4.3709, 4.3709, 4.3709] +24-11-19 20:33:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:04 | D | sum error = [ 305.3253, 330.9443, 358.5476, 388.5058, 421.4263] +24-11-19 20:33:04 | D | best error = [ 4.3709, 4.3709, 4.3709, 4.3709, 4.3709] +24-11-19 20:33:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:04 | D | sum error = [ 456.5016, 494.9248, 536.5311, 581.6586, 630.2858] +24-11-19 20:33:04 | D | best error = [ 4.3709, 4.3709, 4.3709, 4.3709, 4.3709] +24-11-19 20:33:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:04 | D | sum error = [ 683.4613, 740.5730, 801.4332, 866.9916, 936.7125] +24-11-19 20:33:04 | D | best error = [ 4.3709, 4.3709, 4.3709, 4.3709, 4.3709] +24-11-19 20:33:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:04 | D | sum error = [ 1010.6223, 1088.6525, 1169.8591, 1253.1859, 1338.1896] +24-11-19 20:33:04 | D | best error = [ 4.3709, 4.3709, 4.3709, 4.3709, 4.3709] +24-11-19 20:33:04 | D | + error = [4.3709] +24-11-19 20:33:04 | D | - Calibrating model.layers.21.self_attn.k_proj.weight +24-11-19 20:33:04 | D | + w: sint8 +24-11-19 20:33:04 | D | + x: None +24-11-19 20:33:04 | D | + y: None +24-11-19 20:33:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:33:04 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:33:04 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:33:05 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:33:05 | D | - range ratio = [ 1.0000] +24-11-19 20:33:05 | D | sum error = [ 4.6854] +24-11-19 20:33:05 | D | best error = [ 4.6854] +24-11-19 20:33:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:17 | D | sum error = [ 4.2752, 4.4963, 4.2887, 4.5438, 4.7517] +24-11-19 20:33:17 | D | best error = [ 4.2752, 4.2752, 4.2752, 4.2752, 4.2752] +24-11-19 20:33:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:17 | D | sum error = [ 4.5584, 4.7917, 4.7132, 5.3059, 5.7423] +24-11-19 20:33:17 | D | best error = [ 4.2752, 4.2752, 4.2752, 4.2752, 4.2752] +24-11-19 20:33:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:17 | D | sum error = [ 7.3422, 6.3706, 6.5150, 6.7261, 7.2007] +24-11-19 20:33:17 | D | best error = [ 4.2752, 4.2752, 4.2752, 4.2752, 4.2752] +24-11-19 20:33:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:17 | D | sum error = [ 8.1118, 9.2744, 9.7492, 10.9348, 11.6005] +24-11-19 20:33:17 | D | best error = [ 4.2752, 4.2752, 4.2752, 4.2752, 4.2752] +24-11-19 20:33:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:17 | D | sum error = [ 12.9011, 13.8203, 15.6974, 16.6079, 17.8651] +24-11-19 20:33:17 | D | best error = [ 4.2752, 4.2752, 4.2752, 4.2752, 4.2752] +24-11-19 20:33:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:17 | D | sum error = [ 19.5295, 22.0889, 24.3799, 26.6332, 29.1195] +24-11-19 20:33:17 | D | best error = [ 4.2752, 4.2752, 4.2752, 4.2752, 4.2752] +24-11-19 20:33:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:17 | D | sum error = [ 32.7660, 35.2931, 37.4191, 40.9449, 44.4288] +24-11-19 20:33:17 | D | best error = [ 4.2752, 4.2752, 4.2752, 4.2752, 4.2752] +24-11-19 20:33:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:17 | D | sum error = [ 47.4736, 52.6558, 57.2200, 62.7845, 68.2063] +24-11-19 20:33:17 | D | best error = [ 4.2752, 4.2752, 4.2752, 4.2752, 4.2752] +24-11-19 20:33:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:17 | D | sum error = [ 73.3716, 80.2028, 86.3505, 93.5502, 100.2671] +24-11-19 20:33:17 | D | best error = [ 4.2752, 4.2752, 4.2752, 4.2752, 4.2752] +24-11-19 20:33:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:17 | D | sum error = [ 108.7399, 117.4814, 125.2103, 134.9704, 143.9891] +24-11-19 20:33:17 | D | best error = [ 4.2752, 4.2752, 4.2752, 4.2752, 4.2752] +24-11-19 20:33:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:17 | D | sum error = [ 153.7453, 164.9408, 177.3034, 190.2002, 205.2526] +24-11-19 20:33:17 | D | best error = [ 4.2752, 4.2752, 4.2752, 4.2752, 4.2752] +24-11-19 20:33:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:17 | D | sum error = [ 220.2093, 237.7944, 256.8719, 276.8160, 299.3157] +24-11-19 20:33:17 | D | best error = [ 4.2752, 4.2752, 4.2752, 4.2752, 4.2752] +24-11-19 20:33:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:17 | D | sum error = [ 324.3818, 350.6419, 378.2299, 407.4555, 441.1521] +24-11-19 20:33:17 | D | best error = [ 4.2752, 4.2752, 4.2752, 4.2752, 4.2752] +24-11-19 20:33:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:17 | D | sum error = [ 476.5532, 516.0008, 557.1162, 601.7566, 651.1450] +24-11-19 20:33:17 | D | best error = [ 4.2752, 4.2752, 4.2752, 4.2752, 4.2752] +24-11-19 20:33:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:17 | D | sum error = [ 703.4032, 759.9706, 823.1405, 889.5704, 958.2417] +24-11-19 20:33:17 | D | best error = [ 4.2752, 4.2752, 4.2752, 4.2752, 4.2752] +24-11-19 20:33:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:17 | D | sum error = [ 1032.6218, 1108.5887, 1187.9164, 1271.7763, 1353.1050] +24-11-19 20:33:17 | D | best error = [ 4.2752, 4.2752, 4.2752, 4.2752, 4.2752] +24-11-19 20:33:17 | D | + error = [4.2752] +24-11-19 20:33:17 | D | - Calibrating model.layers.21.self_attn.v_proj.weight +24-11-19 20:33:17 | D | + w: sint8 +24-11-19 20:33:17 | D | + x: None +24-11-19 20:33:17 | D | + y: None +24-11-19 20:33:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:17 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:33:17 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:33:17 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:33:17 | D | - range ratio = [ 1.0000] +24-11-19 20:33:17 | D | sum error = [ 1.7953] +24-11-19 20:33:17 | D | best error = [ 1.7953] +24-11-19 20:33:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:17 | D | sum error = [ 1.7843, 1.7698, 1.7837, 1.8132, 1.8350] +24-11-19 20:33:17 | D | best error = [ 1.6671, 1.6125, 1.5854, 1.5721, 1.5641] +24-11-19 20:33:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:17 | D | sum error = [ 1.8772, 1.9551, 2.0486, 2.1259, 2.2459] +24-11-19 20:33:17 | D | best error = [ 1.5594, 1.5576, 1.5571, 1.5570, 1.5570] +24-11-19 20:33:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:17 | D | sum error = [ 2.3631, 2.5211, 2.7043, 2.8831, 3.0897] +24-11-19 20:33:17 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:33:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:17 | D | sum error = [ 3.3170, 3.5497, 3.7949, 4.0694, 4.3749] +24-11-19 20:33:17 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:33:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:17 | D | sum error = [ 4.6694, 4.9905, 5.3453, 5.7351, 6.1223] +24-11-19 20:33:17 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:33:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:17 | D | sum error = [ 6.5548, 6.9931, 7.4679, 7.9594, 8.4736] +24-11-19 20:33:17 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:33:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:17 | D | sum error = [ 9.0379, 9.6166, 10.2155, 10.8762, 11.5569] +24-11-19 20:33:17 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:33:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:17 | D | sum error = [ 12.2715, 13.0221, 13.8282, 14.6551, 15.5374] +24-11-19 20:33:17 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:33:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:17 | D | sum error = [ 16.4431, 17.4094, 18.4021, 19.4822, 20.5835] +24-11-19 20:33:17 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:33:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:17 | D | sum error = [ 21.7567, 22.9694, 24.2455, 25.5766, 26.9630] +24-11-19 20:33:17 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:33:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:17 | D | sum error = [ 28.4140, 29.9333, 31.5158, 33.1609, 34.8903] +24-11-19 20:33:17 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:33:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:17 | D | sum error = [ 36.6781, 38.5564, 40.5078, 42.5254, 44.6413] +24-11-19 20:33:17 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:33:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:17 | D | sum error = [ 46.8311, 49.1079, 51.4666, 53.9307, 56.4730] +24-11-19 20:33:17 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:33:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:17 | D | sum error = [ 59.1211, 61.8583, 64.6891, 67.6319, 70.6686] +24-11-19 20:33:17 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:33:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:17 | D | sum error = [ 73.8125, 77.0549, 80.4003, 83.8613, 87.4365] +24-11-19 20:33:17 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:33:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:17 | D | sum error = [ 91.1149, 94.9228, 98.8394, 102.8743, 107.0252] +24-11-19 20:33:17 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:33:17 | D | + error = [1.5570] +24-11-19 20:33:17 | D | - Calibrating model.layers.21.self_attn.o_proj.weight +24-11-19 20:33:17 | D | + w: sint8 +24-11-19 20:33:17 | D | + x: None +24-11-19 20:33:17 | D | + y: None +24-11-19 20:33:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:17 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:33:17 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:33:17 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:33:17 | D | - range ratio = [ 1.0000] +24-11-19 20:33:17 | D | sum error = [ 0.5899] +24-11-19 20:33:17 | D | best error = [ 0.5899] +24-11-19 20:33:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:18 | D | sum error = [ 0.5811, 0.5813, 0.5785, 0.5788, 0.5814] +24-11-19 20:33:18 | D | best error = [ 0.5376, 0.5165, 0.5026, 0.4939, 0.4874] +24-11-19 20:33:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:18 | D | sum error = [ 0.5868, 0.5924, 0.6037, 0.6165, 0.6325] +24-11-19 20:33:18 | D | best error = [ 0.4827, 0.4788, 0.4761, 0.4739, 0.4724] +24-11-19 20:33:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:18 | D | sum error = [ 0.6551, 0.6749, 0.7016, 0.7345, 0.7693] +24-11-19 20:33:18 | D | best error = [ 0.4711, 0.4703, 0.4695, 0.4690, 0.4686] +24-11-19 20:33:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:18 | D | sum error = [ 0.8086, 0.8538, 0.9033, 0.9548, 1.0130] +24-11-19 20:33:18 | D | best error = [ 0.4681, 0.4679, 0.4678, 0.4677, 0.4675] +24-11-19 20:33:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:18 | D | sum error = [ 1.0760, 1.1465, 1.2195, 1.2982, 1.3857] +24-11-19 20:33:18 | D | best error = [ 0.4675, 0.4674, 0.4673, 0.4672, 0.4672] +24-11-19 20:33:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:18 | D | sum error = [ 1.4736, 1.5694, 1.6722, 1.7826, 1.8994] +24-11-19 20:33:18 | D | best error = [ 0.4672, 0.4672, 0.4672, 0.4671, 0.4671] +24-11-19 20:33:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:18 | D | sum error = [ 2.0222, 2.1523, 2.2929, 2.4414, 2.5938] +24-11-19 20:33:18 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:33:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:18 | D | sum error = [ 2.7567, 2.9292, 3.1144, 3.3082, 3.5103] +24-11-19 20:33:18 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:33:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:18 | D | sum error = [ 3.7281, 3.9547, 4.1939, 4.4456, 4.7110] +24-11-19 20:33:18 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:33:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:18 | D | sum error = [ 4.9919, 5.2883, 5.5983, 5.9248, 6.2657] +24-11-19 20:33:18 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:33:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:18 | D | sum error = [ 6.6266, 7.0021, 7.3999, 7.8162, 8.2522] +24-11-19 20:33:18 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:33:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:18 | D | sum error = [ 8.7100, 9.1877, 9.6894, 10.2136, 10.7635] +24-11-19 20:33:18 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:33:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:18 | D | sum error = [ 11.3350, 11.9313, 12.5537, 13.2013, 13.8764] +24-11-19 20:33:18 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:33:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:18 | D | sum error = [ 14.5808, 15.3124, 16.0735, 16.8653, 17.6847] +24-11-19 20:33:18 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:33:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:18 | D | sum error = [ 18.5363, 19.4204, 20.3350, 21.2833, 22.2654] +24-11-19 20:33:18 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:33:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:18 | D | sum error = [ 23.2819, 24.3345, 25.4234, 26.5475, 27.7117] +24-11-19 20:33:18 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:33:18 | D | + error = [0.4671] +24-11-19 20:33:18 | D | - Calibrating model.layers.21.mlp.up_proj.weight +24-11-19 20:33:18 | D | + w: sint8 +24-11-19 20:33:18 | D | + x: None +24-11-19 20:33:18 | D | + y: None +24-11-19 20:33:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:18 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:33:18 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:33:18 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:33:18 | D | - range ratio = [ 1.0000] +24-11-19 20:33:18 | D | sum error = [ 7.0071] +24-11-19 20:33:18 | D | best error = [ 7.0071] +24-11-19 20:33:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:19 | D | sum error = [ 6.9548, 6.9440, 6.9954, 7.0738, 7.1956] +24-11-19 20:33:19 | D | best error = [ 6.4871, 6.2845, 6.1809, 6.1226, 6.0910] +24-11-19 20:33:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:19 | D | sum error = [ 7.3757, 7.6330, 7.9267, 8.3273, 8.7638] +24-11-19 20:33:19 | D | best error = [ 6.0742, 6.0675, 6.0648, 6.0641, 6.0639] +24-11-19 20:33:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:19 | D | sum error = [ 9.2648, 9.8230, 10.4797, 11.1770, 11.9633] +24-11-19 20:33:19 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:33:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:19 | D | sum error = [ 12.7783, 13.6959, 14.6622, 15.7111, 16.8586] +24-11-19 20:33:19 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:33:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:19 | D | sum error = [ 18.0488, 19.3102, 20.6827, 22.1231, 23.6501] +24-11-19 20:33:19 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:33:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:19 | D | sum error = [ 25.2579, 26.9903, 28.7859, 30.7264, 32.7192] +24-11-19 20:33:19 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:33:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:19 | D | sum error = [ 34.8504, 37.1045, 39.4740, 41.9731, 44.5936] +24-11-19 20:33:19 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:33:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:19 | D | sum error = [ 47.3344, 50.2477, 53.2816, 56.4822, 59.8300] +24-11-19 20:33:19 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:33:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:19 | D | sum error = [ 63.3377, 67.0038, 70.8604, 74.8811, 79.1135] +24-11-19 20:33:19 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:33:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:19 | D | sum error = [ 83.5330, 88.1415, 92.9644, 97.9968, 103.2614] +24-11-19 20:33:19 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:33:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:19 | D | sum error = [ 108.7430, 114.4466, 120.3998, 126.5978, 133.0643] +24-11-19 20:33:19 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:33:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:19 | D | sum error = [ 139.7754, 146.7381, 153.9862, 161.5005, 169.3071] +24-11-19 20:33:19 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:33:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:19 | D | sum error = [ 177.3784, 185.7589, 194.4458, 203.4420, 212.7459] +24-11-19 20:33:19 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:33:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:19 | D | sum error = [ 222.3839, 232.3290, 242.5887, 253.2082, 264.1294] +24-11-19 20:33:19 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:33:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:19 | D | sum error = [ 275.4155, 287.0472, 299.0478, 311.4138, 324.1344] +24-11-19 20:33:19 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:33:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:19 | D | sum error = [ 337.2206, 350.6961, 364.5666, 378.8222, 393.4885] +24-11-19 20:33:19 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:33:19 | D | + error = [6.0638] +24-11-19 20:33:20 | D | - Calibrating model.layers.21.mlp.gate_proj.weight +24-11-19 20:33:20 | D | + w: sint8 +24-11-19 20:33:20 | D | + x: None +24-11-19 20:33:20 | D | + y: None +24-11-19 20:33:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:20 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:33:20 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:33:20 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:33:20 | D | - range ratio = [ 1.0000] +24-11-19 20:33:20 | D | sum error = [ 9.5252] +24-11-19 20:33:20 | D | best error = [ 9.5252] +24-11-19 20:33:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:21 | D | sum error = [ 9.4760, 9.4153, 9.4600, 9.5681, 9.7499] +24-11-19 20:33:21 | D | best error = [ 8.8079, 8.5322, 8.3858, 8.3076, 8.2613] +24-11-19 20:33:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:21 | D | sum error = [ 10.0178, 10.3433, 10.7745, 11.2846, 11.8735] +24-11-19 20:33:21 | D | best error = [ 8.2399, 8.2297, 8.2261, 8.2250, 8.2247] +24-11-19 20:33:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:21 | D | sum error = [ 12.5656, 13.3101, 14.1923, 15.1488, 16.2133] +24-11-19 20:33:21 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 20:33:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:21 | D | sum error = [ 17.3582, 18.6176, 19.9741, 21.4337, 22.9989] +24-11-19 20:33:21 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 20:33:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:21 | D | sum error = [ 24.6502, 26.4254, 28.3501, 30.3495, 32.5219] +24-11-19 20:33:21 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 20:33:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:21 | D | sum error = [ 34.8217, 37.2311, 39.8486, 42.5568, 45.4574] +24-11-19 20:33:21 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 20:33:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:21 | D | sum error = [ 48.5477, 51.7944, 55.2519, 58.9104, 62.7662] +24-11-19 20:33:21 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 20:33:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:21 | D | sum error = [ 66.8654, 71.1809, 75.7480, 80.5593, 85.6904] +24-11-19 20:33:21 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 20:33:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:21 | D | sum error = [ 91.0892, 96.7912, 102.8375, 109.1877, 115.9334] +24-11-19 20:33:21 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 20:33:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:21 | D | sum error = [ 123.0387, 130.5102, 138.4365, 146.7591, 155.5346] +24-11-19 20:33:21 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 20:33:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:21 | D | sum error = [ 164.7502, 174.4881, 184.7436, 195.5134, 206.8531] +24-11-19 20:33:21 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 20:33:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:21 | D | sum error = [ 218.7801, 231.2763, 244.3851, 258.0949, 272.5168] +24-11-19 20:33:21 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 20:33:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:21 | D | sum error = [ 287.6093, 303.3972, 319.9147, 337.2268, 355.2691] +24-11-19 20:33:21 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 20:33:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:21 | D | sum error = [ 374.1293, 393.7756, 414.2347, 435.5375, 457.7095] +24-11-19 20:33:21 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 20:33:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:21 | D | sum error = [ 480.7521, 504.6562, 529.4916, 555.1829, 581.7815] +24-11-19 20:33:21 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 20:33:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:21 | D | sum error = [ 609.3176, 637.7344, 667.0742, 697.3704, 728.5685] +24-11-19 20:33:21 | D | best error = [ 8.2247, 8.2247, 8.2247, 8.2247, 8.2247] +24-11-19 20:33:21 | D | + error = [8.2247] +24-11-19 20:33:21 | D | - Calibrating model.layers.21.mlp.down_proj.weight +24-11-19 20:33:21 | D | + w: sint8 +24-11-19 20:33:21 | D | + x: None +24-11-19 20:33:21 | D | + y: None +24-11-19 20:33:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:21 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:33:21 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:33:21 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:33:21 | D | - range ratio = [ 1.0000] +24-11-19 20:33:21 | D | sum error = [ 1.1580] +24-11-19 20:33:21 | D | best error = [ 1.1580] +24-11-19 20:33:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:22 | D | sum error = [ 1.1479, 1.1366, 1.1267, 1.1219, 1.1181] +24-11-19 20:33:22 | D | best error = [ 1.1097, 1.0841, 1.0671, 1.0546, 1.0443] +24-11-19 20:33:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:22 | D | sum error = [ 1.1174, 1.1200, 1.1256, 1.1351, 1.1494] +24-11-19 20:33:22 | D | best error = [ 1.0363, 1.0299, 1.0245, 1.0207, 1.0177] +24-11-19 20:33:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:22 | D | sum error = [ 1.1705, 1.1955, 1.2250, 1.2643, 1.3086] +24-11-19 20:33:22 | D | best error = [ 1.0155, 1.0138, 1.0128, 1.0120, 1.0114] +24-11-19 20:33:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:22 | D | sum error = [ 1.3597, 1.4241, 1.4942, 1.5699, 1.6588] +24-11-19 20:33:22 | D | best error = [ 1.0110, 1.0108, 1.0106, 1.0104, 1.0103] +24-11-19 20:33:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:22 | D | sum error = [ 1.7568, 1.8645, 1.9855, 2.1140, 2.2553] +24-11-19 20:33:22 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 20:33:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:22 | D | sum error = [ 2.4068, 2.5747, 2.7529, 2.9444, 3.1522] +24-11-19 20:33:22 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 20:33:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:22 | D | sum error = [ 3.3721, 3.6114, 3.8626, 4.1341, 4.4211] +24-11-19 20:33:22 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 20:33:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:22 | D | sum error = [ 4.7283, 5.0536, 5.4004, 5.7673, 6.1561] +24-11-19 20:33:22 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 20:33:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:22 | D | sum error = [ 6.5660, 7.0033, 7.4658, 7.9554, 8.4709] +24-11-19 20:33:22 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 20:33:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:22 | D | sum error = [ 9.0159, 9.5953, 10.2044, 10.8467, 11.5223] +24-11-19 20:33:22 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 20:33:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:22 | D | sum error = [ 12.2362, 12.9862, 13.7752, 14.6053, 15.4713] +24-11-19 20:33:22 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 20:33:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:22 | D | sum error = [ 16.3868, 17.3466, 18.3499, 19.4049, 20.5058] +24-11-19 20:33:22 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 20:33:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:22 | D | sum error = [ 21.6608, 22.8685, 24.1319, 25.4538, 26.8331] +24-11-19 20:33:22 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 20:33:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:22 | D | sum error = [ 28.2726, 29.7764, 31.3427, 32.9783, 34.6778] +24-11-19 20:33:22 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 20:33:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:22 | D | sum error = [ 36.4506, 38.2936, 40.2106, 42.1988, 44.2618] +24-11-19 20:33:22 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 20:33:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:22 | D | sum error = [ 46.4021, 48.6210, 50.9217, 53.3033, 55.7682] +24-11-19 20:33:22 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 20:33:22 | D | + error = [1.0102] +24-11-19 20:33:23 | D | - Quantizing model.layers.21.self_attn.q_proj.weight +24-11-19 20:33:23 | D | - Quantizing model.layers.21.self_attn.k_proj.weight +24-11-19 20:33:24 | D | - Quantizing model.layers.21.self_attn.v_proj.weight +24-11-19 20:33:25 | D | - Quantizing model.layers.21.self_attn.o_proj.weight +24-11-19 20:33:26 | D | - Quantizing model.layers.21.mlp.up_proj.weight +24-11-19 20:33:27 | D | - Quantizing model.layers.21.mlp.gate_proj.weight +24-11-19 20:33:27 | D | - Quantizing model.layers.21.mlp.down_proj.weight +24-11-19 20:33:37 | D | - Quantizing layer model.layers.22 +24-11-19 20:33:37 | D | - Calibrating model.layers.22.self_attn.q_proj.weight +24-11-19 20:33:37 | D | + w: sint8 +24-11-19 20:33:37 | D | + x: None +24-11-19 20:33:37 | D | + y: None +24-11-19 20:33:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:33:37 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:33:37 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:33:37 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:33:38 | D | - range ratio = [ 1.0000] +24-11-19 20:33:38 | D | sum error = [ 4.6008] +24-11-19 20:33:38 | D | best error = [ 4.6008] +24-11-19 20:33:49 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:49 | D | sum error = [ 4.5870, 4.5364, 4.6362, 4.6300, 4.6585] +24-11-19 20:33:49 | D | best error = [ 4.5870, 4.5364, 4.5364, 4.5364, 4.5364] +24-11-19 20:33:49 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:49 | D | sum error = [ 4.8089, 5.0110, 5.2383, 5.5703, 5.8309] +24-11-19 20:33:49 | D | best error = [ 4.5364, 4.5364, 4.5364, 4.5364, 4.5364] +24-11-19 20:33:49 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:49 | D | sum error = [ 6.3333, 6.6720, 7.5161, 7.7813, 8.3160] +24-11-19 20:33:49 | D | best error = [ 4.5364, 4.5364, 4.5364, 4.5364, 4.5364] +24-11-19 20:33:49 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:49 | D | sum error = [ 9.0287, 9.7415, 10.6344, 11.5646, 12.4943] +24-11-19 20:33:49 | D | best error = [ 4.5364, 4.5364, 4.5364, 4.5364, 4.5364] +24-11-19 20:33:49 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:49 | D | sum error = [ 13.5419, 14.9867, 16.2065, 17.4388, 18.8827] +24-11-19 20:33:49 | D | best error = [ 4.5364, 4.5364, 4.5364, 4.5364, 4.5364] +24-11-19 20:33:49 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:49 | D | sum error = [ 20.4708, 22.3241, 24.3306, 26.2052, 28.4459] +24-11-19 20:33:49 | D | best error = [ 4.5364, 4.5364, 4.5364, 4.5364, 4.5364] +24-11-19 20:33:49 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:49 | D | sum error = [ 30.9749, 33.5931, 36.6310, 39.4337, 43.0076] +24-11-19 20:33:49 | D | best error = [ 4.5364, 4.5364, 4.5364, 4.5364, 4.5364] +24-11-19 20:33:49 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:49 | D | sum error = [ 46.2400, 50.3844, 54.4722, 59.2862, 64.2500] +24-11-19 20:33:49 | D | best error = [ 4.5364, 4.5364, 4.5364, 4.5364, 4.5364] +24-11-19 20:33:49 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:49 | D | sum error = [ 69.6170, 75.3394, 81.5752, 88.4549, 96.0565] +24-11-19 20:33:49 | D | best error = [ 4.5364, 4.5364, 4.5364, 4.5364, 4.5364] +24-11-19 20:33:49 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:49 | D | sum error = [ 104.1940, 113.1600, 122.9396, 133.6670, 145.1590] +24-11-19 20:33:49 | D | best error = [ 4.5364, 4.5364, 4.5364, 4.5364, 4.5364] +24-11-19 20:33:49 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:49 | D | sum error = [ 157.4526, 171.1853, 185.8927, 201.6467, 219.1595] +24-11-19 20:33:49 | D | best error = [ 4.5364, 4.5364, 4.5364, 4.5364, 4.5364] +24-11-19 20:33:49 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:49 | D | sum error = [ 238.7681, 259.8532, 282.6407, 307.7238, 335.6235] +24-11-19 20:33:49 | D | best error = [ 4.5364, 4.5364, 4.5364, 4.5364, 4.5364] +24-11-19 20:33:49 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:49 | D | sum error = [ 366.1966, 400.4226, 437.0589, 479.1488, 524.9067] +24-11-19 20:33:49 | D | best error = [ 4.5364, 4.5364, 4.5364, 4.5364, 4.5364] +24-11-19 20:33:49 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:49 | D | sum error = [ 576.2424, 634.4410, 697.9072, 767.2236, 844.3163] +24-11-19 20:33:49 | D | best error = [ 4.5364, 4.5364, 4.5364, 4.5364, 4.5364] +24-11-19 20:33:49 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:49 | D | sum error = [ 929.0762, 1021.8620, 1123.1769, 1231.2703, 1347.9565] +24-11-19 20:33:49 | D | best error = [ 4.5364, 4.5364, 4.5364, 4.5364, 4.5364] +24-11-19 20:33:49 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:49 | D | sum error = [ 1471.0196, 1600.1452, 1735.5921, 1871.7340, 2010.1948] +24-11-19 20:33:49 | D | best error = [ 4.5364, 4.5364, 4.5364, 4.5364, 4.5364] +24-11-19 20:33:49 | D | + error = [4.5364] +24-11-19 20:33:50 | D | - Calibrating model.layers.22.self_attn.k_proj.weight +24-11-19 20:33:50 | D | + w: sint8 +24-11-19 20:33:50 | D | + x: None +24-11-19 20:33:50 | D | + y: None +24-11-19 20:33:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:33:50 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:33:50 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:33:50 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:33:50 | D | - range ratio = [ 1.0000] +24-11-19 20:33:50 | D | sum error = [ 4.6041] +24-11-19 20:33:50 | D | best error = [ 4.6041] +24-11-19 20:34:02 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:02 | D | sum error = [ 4.0744, 3.9336, 4.1653, 4.7570, 5.1095] +24-11-19 20:34:02 | D | best error = [ 4.0744, 3.9336, 3.9336, 3.9336, 3.9336] +24-11-19 20:34:02 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:02 | D | sum error = [ 4.9040, 4.6251, 6.1620, 5.7456, 6.6188] +24-11-19 20:34:02 | D | best error = [ 3.9336, 3.9336, 3.9336, 3.9336, 3.9336] +24-11-19 20:34:02 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:02 | D | sum error = [ 6.9911, 8.1091, 8.1856, 9.5835, 9.5779] +24-11-19 20:34:02 | D | best error = [ 3.9336, 3.9336, 3.9336, 3.9336, 3.9336] +24-11-19 20:34:02 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:02 | D | sum error = [ 11.1041, 11.9284, 12.8967, 16.5657, 16.5641] +24-11-19 20:34:02 | D | best error = [ 3.9336, 3.9336, 3.9336, 3.9336, 3.9336] +24-11-19 20:34:02 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:02 | D | sum error = [ 19.6815, 20.2505, 21.6365, 24.3678, 25.9286] +24-11-19 20:34:02 | D | best error = [ 3.9336, 3.9336, 3.9336, 3.9336, 3.9336] +24-11-19 20:34:02 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:02 | D | sum error = [ 27.9156, 29.5361, 31.9431, 34.9508, 36.5276] +24-11-19 20:34:02 | D | best error = [ 3.9336, 3.9336, 3.9336, 3.9336, 3.9336] +24-11-19 20:34:02 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:02 | D | sum error = [ 40.5912, 43.9383, 46.8901, 50.1180, 54.4192] +24-11-19 20:34:02 | D | best error = [ 3.9336, 3.9336, 3.9336, 3.9336, 3.9336] +24-11-19 20:34:02 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:02 | D | sum error = [ 58.8775, 64.0026, 69.2513, 75.0793, 80.8420] +24-11-19 20:34:02 | D | best error = [ 3.9336, 3.9336, 3.9336, 3.9336, 3.9336] +24-11-19 20:34:02 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:02 | D | sum error = [ 86.9785, 93.9362, 101.2647, 109.2877, 117.1718] +24-11-19 20:34:02 | D | best error = [ 3.9336, 3.9336, 3.9336, 3.9336, 3.9336] +24-11-19 20:34:02 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:02 | D | sum error = [ 126.5646, 136.9997, 146.9724, 158.4489, 171.7867] +24-11-19 20:34:02 | D | best error = [ 3.9336, 3.9336, 3.9336, 3.9336, 3.9336] +24-11-19 20:34:02 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:02 | D | sum error = [ 184.4915, 200.4582, 216.4859, 232.5124, 253.5760] +24-11-19 20:34:02 | D | best error = [ 3.9336, 3.9336, 3.9336, 3.9336, 3.9336] +24-11-19 20:34:02 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:02 | D | sum error = [ 273.8589, 295.8204, 323.5392, 352.1778, 384.2276] +24-11-19 20:34:02 | D | best error = [ 3.9336, 3.9336, 3.9336, 3.9336, 3.9336] +24-11-19 20:34:02 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:02 | D | sum error = [ 422.9032, 462.3688, 505.4256, 552.8482, 605.0337] +24-11-19 20:34:02 | D | best error = [ 3.9336, 3.9336, 3.9336, 3.9336, 3.9336] +24-11-19 20:34:02 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:02 | D | sum error = [ 665.0387, 728.4602, 794.7975, 878.9830, 960.4094] +24-11-19 20:34:02 | D | best error = [ 3.9336, 3.9336, 3.9336, 3.9336, 3.9336] +24-11-19 20:34:02 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:02 | D | sum error = [ 1051.7992, 1160.5408, 1268.6857, 1396.0471, 1514.8052] +24-11-19 20:34:02 | D | best error = [ 3.9336, 3.9336, 3.9336, 3.9336, 3.9336] +24-11-19 20:34:02 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:02 | D | sum error = [ 1644.3281, 1785.1095, 1922.5367, 2055.9802, 2192.1204] +24-11-19 20:34:02 | D | best error = [ 3.9336, 3.9336, 3.9336, 3.9336, 3.9336] +24-11-19 20:34:02 | D | + error = [3.9336] +24-11-19 20:34:02 | D | - Calibrating model.layers.22.self_attn.v_proj.weight +24-11-19 20:34:02 | D | + w: sint8 +24-11-19 20:34:02 | D | + x: None +24-11-19 20:34:02 | D | + y: None +24-11-19 20:34:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:02 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:34:02 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:34:02 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:34:02 | D | - range ratio = [ 1.0000] +24-11-19 20:34:02 | D | sum error = [ 1.9819] +24-11-19 20:34:02 | D | best error = [ 1.9819] +24-11-19 20:34:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:03 | D | sum error = [ 1.9625, 1.9532, 1.9639, 2.0062, 2.0228] +24-11-19 20:34:03 | D | best error = [ 1.8301, 1.7730, 1.7419, 1.7254, 1.7147] +24-11-19 20:34:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:03 | D | sum error = [ 2.0774, 2.1477, 2.2107, 2.3219, 2.4458] +24-11-19 20:34:03 | D | best error = [ 1.7116, 1.7098, 1.7092, 1.7091, 1.7090] +24-11-19 20:34:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:03 | D | sum error = [ 2.5803, 2.7699, 2.9189, 3.1389, 3.3629] +24-11-19 20:34:03 | D | best error = [ 1.7090, 1.7090, 1.7090, 1.7090, 1.7090] +24-11-19 20:34:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:03 | D | sum error = [ 3.6046, 3.8515, 4.1134, 4.4079, 4.7146] +24-11-19 20:34:03 | D | best error = [ 1.7090, 1.7090, 1.7090, 1.7090, 1.7090] +24-11-19 20:34:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:03 | D | sum error = [ 5.0482, 5.4195, 5.8134, 6.1997, 6.6478] +24-11-19 20:34:03 | D | best error = [ 1.7090, 1.7090, 1.7090, 1.7090, 1.7090] +24-11-19 20:34:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:03 | D | sum error = [ 7.0997, 7.5797, 8.1034, 8.6461, 9.2121] +24-11-19 20:34:03 | D | best error = [ 1.7090, 1.7090, 1.7090, 1.7090, 1.7090] +24-11-19 20:34:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:03 | D | sum error = [ 9.8083, 10.4523, 11.1149, 11.8061, 12.5572] +24-11-19 20:34:03 | D | best error = [ 1.7090, 1.7090, 1.7090, 1.7090, 1.7090] +24-11-19 20:34:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:03 | D | sum error = [ 13.3256, 14.1326, 14.9952, 15.8894, 16.8350] +24-11-19 20:34:03 | D | best error = [ 1.7090, 1.7090, 1.7090, 1.7090, 1.7090] +24-11-19 20:34:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:03 | D | sum error = [ 17.8261, 18.8585, 19.9602, 21.1010, 22.3024] +24-11-19 20:34:03 | D | best error = [ 1.7090, 1.7090, 1.7090, 1.7090, 1.7090] +24-11-19 20:34:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:03 | D | sum error = [ 23.5547, 24.8743, 26.2563, 27.6744, 29.1489] +24-11-19 20:34:03 | D | best error = [ 1.7090, 1.7090, 1.7090, 1.7090, 1.7090] +24-11-19 20:34:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:03 | D | sum error = [ 30.7128, 32.3295, 33.9991, 35.7499, 37.5698] +24-11-19 20:34:03 | D | best error = [ 1.7090, 1.7090, 1.7090, 1.7090, 1.7090] +24-11-19 20:34:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:03 | D | sum error = [ 39.4627, 41.4354, 43.4860, 45.6301, 47.8655] +24-11-19 20:34:03 | D | best error = [ 1.7090, 1.7090, 1.7090, 1.7090, 1.7090] +24-11-19 20:34:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:03 | D | sum error = [ 50.1929, 52.6115, 55.1127, 57.7101, 60.4093] +24-11-19 20:34:03 | D | best error = [ 1.7090, 1.7090, 1.7090, 1.7090, 1.7090] +24-11-19 20:34:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:03 | D | sum error = [ 63.2115, 66.1025, 69.1026, 72.2080, 75.4136] +24-11-19 20:34:03 | D | best error = [ 1.7090, 1.7090, 1.7090, 1.7090, 1.7090] +24-11-19 20:34:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:03 | D | sum error = [ 78.7068, 82.1045, 85.6123, 89.2241, 92.9537] +24-11-19 20:34:03 | D | best error = [ 1.7090, 1.7090, 1.7090, 1.7090, 1.7090] +24-11-19 20:34:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:03 | D | sum error = [ 96.7848, 100.7267, 104.7819, 108.9552, 113.2405] +24-11-19 20:34:03 | D | best error = [ 1.7090, 1.7090, 1.7090, 1.7090, 1.7090] +24-11-19 20:34:03 | D | + error = [1.7090] +24-11-19 20:34:03 | D | - Calibrating model.layers.22.self_attn.o_proj.weight +24-11-19 20:34:03 | D | + w: sint8 +24-11-19 20:34:03 | D | + x: None +24-11-19 20:34:03 | D | + y: None +24-11-19 20:34:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:03 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:34:03 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:34:03 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:34:03 | D | - range ratio = [ 1.0000] +24-11-19 20:34:03 | D | sum error = [ 0.4521] +24-11-19 20:34:03 | D | best error = [ 0.4521] +24-11-19 20:34:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:03 | D | sum error = [ 0.4463, 0.4463, 0.4498, 0.4541, 0.4648] +24-11-19 20:34:03 | D | best error = [ 0.4190, 0.4053, 0.3975, 0.3927, 0.3900] +24-11-19 20:34:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:03 | D | sum error = [ 0.4753, 0.4901, 0.5115, 0.5335, 0.5614] +24-11-19 20:34:03 | D | best error = [ 0.3881, 0.3868, 0.3860, 0.3855, 0.3851] +24-11-19 20:34:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:03 | D | sum error = [ 0.5918, 0.6273, 0.6661, 0.7091, 0.7570] +24-11-19 20:34:03 | D | best error = [ 0.3849, 0.3847, 0.3846, 0.3845, 0.3845] +24-11-19 20:34:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:03 | D | sum error = [ 0.8045, 0.8604, 0.9179, 0.9810, 1.0458] +24-11-19 20:34:03 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:34:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:03 | D | sum error = [ 1.1162, 1.1911, 1.2712, 1.3522, 1.4395] +24-11-19 20:34:03 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:34:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:03 | D | sum error = [ 1.5323, 1.6322, 1.7358, 1.8422, 1.9597] +24-11-19 20:34:03 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:34:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:03 | D | sum error = [ 2.0797, 2.2068, 2.3396, 2.4787, 2.6271] +24-11-19 20:34:03 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:34:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:03 | D | sum error = [ 2.7820, 2.9427, 3.1131, 3.2902, 3.4761] +24-11-19 20:34:03 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:34:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:03 | D | sum error = [ 3.6724, 3.8757, 4.0892, 4.3114, 4.5451] +24-11-19 20:34:03 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:34:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:03 | D | sum error = [ 4.7889, 5.0448, 5.3101, 5.5881, 5.8795] +24-11-19 20:34:03 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:34:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:03 | D | sum error = [ 6.1821, 6.4970, 6.8244, 7.1662, 7.5220] +24-11-19 20:34:03 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:34:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:03 | D | sum error = [ 7.8929, 8.2769, 8.6774, 9.0924, 9.5240] +24-11-19 20:34:03 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:34:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:03 | D | sum error = [ 9.9719, 10.4356, 10.9169, 11.4144, 11.9308] +24-11-19 20:34:03 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:34:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:03 | D | sum error = [ 12.4651, 13.0176, 13.5889, 14.1805, 14.7907] +24-11-19 20:34:03 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:34:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:03 | D | sum error = [ 15.4209, 16.0719, 16.7426, 17.4352, 18.1492] +24-11-19 20:34:03 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:34:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:03 | D | sum error = [ 18.8845, 19.6428, 20.4218, 21.2230, 22.0477] +24-11-19 20:34:03 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:34:03 | D | + error = [0.3844] +24-11-19 20:34:04 | D | - Calibrating model.layers.22.mlp.up_proj.weight +24-11-19 20:34:04 | D | + w: sint8 +24-11-19 20:34:04 | D | + x: None +24-11-19 20:34:04 | D | + y: None +24-11-19 20:34:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:04 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:34:04 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:34:04 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:34:04 | D | - range ratio = [ 1.0000] +24-11-19 20:34:04 | D | sum error = [ 7.2488] +24-11-19 20:34:04 | D | best error = [ 7.2488] +24-11-19 20:34:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:05 | D | sum error = [ 7.2060, 7.1656, 7.2085, 7.2907, 7.4429] +24-11-19 20:34:05 | D | best error = [ 6.6944, 6.4776, 6.3679, 6.3077, 6.2738] +24-11-19 20:34:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:05 | D | sum error = [ 7.6010, 7.8750, 8.1861, 8.5719, 9.0196] +24-11-19 20:34:05 | D | best error = [ 6.2561, 6.2488, 6.2459, 6.2451, 6.2449] +24-11-19 20:34:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:05 | D | sum error = [ 9.5497, 10.1528, 10.8177, 11.5274, 12.3284] +24-11-19 20:34:05 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:34:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:05 | D | sum error = [ 13.2067, 14.1503, 15.1714, 16.2533, 17.4112] +24-11-19 20:34:05 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:34:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:05 | D | sum error = [ 18.6464, 19.9754, 21.3906, 22.8682, 24.4256] +24-11-19 20:34:05 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:34:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:05 | D | sum error = [ 26.1042, 27.8943, 29.7413, 31.7126, 33.7922] +24-11-19 20:34:05 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:34:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:05 | D | sum error = [ 35.9946, 38.2953, 40.7243, 43.2773, 45.9725] +24-11-19 20:34:05 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:34:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:05 | D | sum error = [ 48.7995, 51.7920, 54.9271, 58.1939, 61.6217] +24-11-19 20:34:05 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:34:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:05 | D | sum error = [ 65.2329, 69.0080, 72.9698, 77.1040, 81.4250] +24-11-19 20:34:05 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:34:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:05 | D | sum error = [ 85.9541, 90.6653, 95.5960, 100.7371, 106.1138] +24-11-19 20:34:05 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:34:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:05 | D | sum error = [ 111.6977, 117.5251, 123.5708, 129.8751, 136.4227] +24-11-19 20:34:05 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:34:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:05 | D | sum error = [ 143.2229, 150.3079, 157.6566, 165.2792, 173.1820] +24-11-19 20:34:05 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:34:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:05 | D | sum error = [ 181.3667, 189.8634, 198.6474, 207.7277, 217.1317] +24-11-19 20:34:05 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:34:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:05 | D | sum error = [ 226.8363, 236.8696, 247.2146, 257.9131, 268.9038] +24-11-19 20:34:05 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:34:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:05 | D | sum error = [ 280.2534, 291.9381, 303.9828, 316.3810, 329.1255] +24-11-19 20:34:05 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:34:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:05 | D | sum error = [ 342.2297, 355.7003, 369.5578, 383.7893, 398.4012] +24-11-19 20:34:05 | D | best error = [ 6.2449, 6.2449, 6.2449, 6.2449, 6.2449] +24-11-19 20:34:05 | D | + error = [6.2449] +24-11-19 20:34:05 | D | - Calibrating model.layers.22.mlp.gate_proj.weight +24-11-19 20:34:05 | D | + w: sint8 +24-11-19 20:34:05 | D | + x: None +24-11-19 20:34:05 | D | + y: None +24-11-19 20:34:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:05 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:34:05 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:34:05 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:34:05 | D | - range ratio = [ 1.0000] +24-11-19 20:34:05 | D | sum error = [ 9.7711] +24-11-19 20:34:05 | D | best error = [ 9.7711] +24-11-19 20:34:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:06 | D | sum error = [ 9.7379, 9.6911, 9.7718, 9.8510, 10.0476] +24-11-19 20:34:06 | D | best error = [ 9.0475, 8.7669, 8.6198, 8.5348, 8.4876] +24-11-19 20:34:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:06 | D | sum error = [ 10.2752, 10.6287, 11.0623, 11.6109, 12.2278] +24-11-19 20:34:06 | D | best error = [ 8.4647, 8.4548, 8.4510, 8.4499, 8.4498] +24-11-19 20:34:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:06 | D | sum error = [ 12.9505, 13.7052, 14.6157, 15.6297, 16.7243] +24-11-19 20:34:06 | D | best error = [ 8.4498, 8.4498, 8.4498, 8.4498, 8.4498] +24-11-19 20:34:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:06 | D | sum error = [ 17.9078, 19.1772, 20.5849, 22.0675, 23.6585] +24-11-19 20:34:07 | D | best error = [ 8.4498, 8.4498, 8.4498, 8.4498, 8.4498] +24-11-19 20:34:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:07 | D | sum error = [ 25.3927, 27.2238, 29.1697, 31.2626, 33.4642] +24-11-19 20:34:07 | D | best error = [ 8.4498, 8.4498, 8.4498, 8.4498, 8.4498] +24-11-19 20:34:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:07 | D | sum error = [ 35.7989, 38.2848, 40.9291, 43.7495, 46.7191] +24-11-19 20:34:07 | D | best error = [ 8.4498, 8.4498, 8.4498, 8.4498, 8.4498] +24-11-19 20:34:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:07 | D | sum error = [ 49.8714, 53.2277, 56.7208, 60.4680, 64.4043] +24-11-19 20:34:07 | D | best error = [ 8.4498, 8.4498, 8.4498, 8.4498, 8.4498] +24-11-19 20:34:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:07 | D | sum error = [ 68.5301, 72.9326, 77.5691, 82.4700, 87.6513] +24-11-19 20:34:07 | D | best error = [ 8.4498, 8.4498, 8.4498, 8.4498, 8.4498] +24-11-19 20:34:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:07 | D | sum error = [ 93.1061, 98.8711, 104.9350, 111.3344, 118.0841] +24-11-19 20:34:07 | D | best error = [ 8.4498, 8.4498, 8.4498, 8.4498, 8.4498] +24-11-19 20:34:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:07 | D | sum error = [ 125.2010, 132.6834, 140.5665, 148.8574, 157.5878] +24-11-19 20:34:07 | D | best error = [ 8.4498, 8.4498, 8.4498, 8.4498, 8.4498] +24-11-19 20:34:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:07 | D | sum error = [ 166.7895, 176.4125, 186.5611, 197.2012, 208.3712] +24-11-19 20:34:07 | D | best error = [ 8.4498, 8.4498, 8.4498, 8.4498, 8.4498] +24-11-19 20:34:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:07 | D | sum error = [ 220.0819, 232.3674, 245.2384, 258.7140, 272.8287] +24-11-19 20:34:07 | D | best error = [ 8.4498, 8.4498, 8.4498, 8.4498, 8.4498] +24-11-19 20:34:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:07 | D | sum error = [ 287.5690, 302.9958, 319.1416, 335.9671, 353.5434] +24-11-19 20:34:07 | D | best error = [ 8.4498, 8.4498, 8.4498, 8.4498, 8.4498] +24-11-19 20:34:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:07 | D | sum error = [ 371.8741, 390.9675, 410.8594, 431.5301, 453.0268] +24-11-19 20:34:07 | D | best error = [ 8.4498, 8.4498, 8.4498, 8.4498, 8.4498] +24-11-19 20:34:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:07 | D | sum error = [ 475.3386, 498.5085, 522.5326, 547.3655, 573.1122] +24-11-19 20:34:07 | D | best error = [ 8.4498, 8.4498, 8.4498, 8.4498, 8.4498] +24-11-19 20:34:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:07 | D | sum error = [ 599.7104, 627.1839, 655.5132, 684.7229, 714.8362] +24-11-19 20:34:07 | D | best error = [ 8.4498, 8.4498, 8.4498, 8.4498, 8.4498] +24-11-19 20:34:07 | D | + error = [8.4498] +24-11-19 20:34:07 | D | - Calibrating model.layers.22.mlp.down_proj.weight +24-11-19 20:34:07 | D | + w: sint8 +24-11-19 20:34:07 | D | + x: None +24-11-19 20:34:07 | D | + y: None +24-11-19 20:34:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:07 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:34:07 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:34:07 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:34:07 | D | - range ratio = [ 1.0000] +24-11-19 20:34:07 | D | sum error = [ 1.1781] +24-11-19 20:34:07 | D | best error = [ 1.1781] +24-11-19 20:34:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:08 | D | sum error = [ 1.1659, 1.1550, 1.1479, 1.1416, 1.1407] +24-11-19 20:34:08 | D | best error = [ 1.1238, 1.0967, 1.0792, 1.0661, 1.0556] +24-11-19 20:34:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:08 | D | sum error = [ 1.1382, 1.1428, 1.1506, 1.1579, 1.1756] +24-11-19 20:34:08 | D | best error = [ 1.0478, 1.0407, 1.0356, 1.0314, 1.0287] +24-11-19 20:34:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:08 | D | sum error = [ 1.1969, 1.2221, 1.2578, 1.2957, 1.3447] +24-11-19 20:34:08 | D | best error = [ 1.0264, 1.0245, 1.0234, 1.0225, 1.0218] +24-11-19 20:34:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:08 | D | sum error = [ 1.4011, 1.4649, 1.5419, 1.6232, 1.7123] +24-11-19 20:34:08 | D | best error = [ 1.0214, 1.0212, 1.0211, 1.0210, 1.0209] +24-11-19 20:34:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:08 | D | sum error = [ 1.8170, 1.9315, 2.0573, 2.1933, 2.3409] +24-11-19 20:34:08 | D | best error = [ 1.0209, 1.0209, 1.0209, 1.0209, 1.0209] +24-11-19 20:34:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:08 | D | sum error = [ 2.4998, 2.6761, 2.8611, 3.0610, 3.2786] +24-11-19 20:34:08 | D | best error = [ 1.0209, 1.0209, 1.0209, 1.0209, 1.0209] +24-11-19 20:34:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:08 | D | sum error = [ 3.5082, 3.7534, 4.0166, 4.2974, 4.5970] +24-11-19 20:34:08 | D | best error = [ 1.0209, 1.0209, 1.0209, 1.0209, 1.0209] +24-11-19 20:34:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:08 | D | sum error = [ 4.9142, 5.2533, 5.6146, 5.9942, 6.4009] +24-11-19 20:34:08 | D | best error = [ 1.0209, 1.0209, 1.0209, 1.0209, 1.0209] +24-11-19 20:34:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:08 | D | sum error = [ 6.8310, 7.2875, 7.7732, 8.2823, 8.8218] +24-11-19 20:34:08 | D | best error = [ 1.0209, 1.0209, 1.0209, 1.0209, 1.0209] +24-11-19 20:34:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:08 | D | sum error = [ 9.3914, 9.9938, 10.6282, 11.2972, 12.0004] +24-11-19 20:34:08 | D | best error = [ 1.0209, 1.0209, 1.0209, 1.0209, 1.0209] +24-11-19 20:34:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:08 | D | sum error = [ 12.7420, 13.5238, 14.3449, 15.2065, 16.1122] +24-11-19 20:34:08 | D | best error = [ 1.0209, 1.0209, 1.0209, 1.0209, 1.0209] +24-11-19 20:34:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:08 | D | sum error = [ 17.0625, 18.0600, 19.1062, 20.2021, 21.3513] +24-11-19 20:34:08 | D | best error = [ 1.0209, 1.0209, 1.0209, 1.0209, 1.0209] +24-11-19 20:34:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:08 | D | sum error = [ 22.5546, 23.8148, 25.1327, 26.5106, 27.9452] +24-11-19 20:34:08 | D | best error = [ 1.0209, 1.0209, 1.0209, 1.0209, 1.0209] +24-11-19 20:34:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:08 | D | sum error = [ 29.4443, 31.0062, 32.6344, 34.3326, 36.0958] +24-11-19 20:34:08 | D | best error = [ 1.0209, 1.0209, 1.0209, 1.0209, 1.0209] +24-11-19 20:34:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:08 | D | sum error = [ 37.9318, 39.8378, 41.8180, 43.8711, 46.0000] +24-11-19 20:34:08 | D | best error = [ 1.0209, 1.0209, 1.0209, 1.0209, 1.0209] +24-11-19 20:34:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:08 | D | sum error = [ 48.2072, 50.4927, 52.8595, 55.3074, 57.8364] +24-11-19 20:34:08 | D | best error = [ 1.0209, 1.0209, 1.0209, 1.0209, 1.0209] +24-11-19 20:34:08 | D | + error = [1.0209] +24-11-19 20:34:08 | D | - Quantizing model.layers.22.self_attn.q_proj.weight +24-11-19 20:34:09 | D | - Quantizing model.layers.22.self_attn.k_proj.weight +24-11-19 20:34:10 | D | - Quantizing model.layers.22.self_attn.v_proj.weight +24-11-19 20:34:11 | D | - Quantizing model.layers.22.self_attn.o_proj.weight +24-11-19 20:34:11 | D | - Quantizing model.layers.22.mlp.up_proj.weight +24-11-19 20:34:12 | D | - Quantizing model.layers.22.mlp.gate_proj.weight +24-11-19 20:34:13 | D | - Quantizing model.layers.22.mlp.down_proj.weight +24-11-19 20:34:23 | D | - Quantizing layer model.layers.23 +24-11-19 20:34:23 | D | - Calibrating model.layers.23.self_attn.q_proj.weight +24-11-19 20:34:23 | D | + w: sint8 +24-11-19 20:34:23 | D | + x: None +24-11-19 20:34:23 | D | + y: None +24-11-19 20:34:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:34:23 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:34:23 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:34:23 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:34:23 | D | - range ratio = [ 1.0000] +24-11-19 20:34:23 | D | sum error = [ 4.1562] +24-11-19 20:34:23 | D | best error = [ 4.1562] +24-11-19 20:34:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:35 | D | sum error = [ 4.1920, 4.1923, 4.1142, 4.2448, 4.3591] +24-11-19 20:34:35 | D | best error = [ 4.1562, 4.1562, 4.1142, 4.1142, 4.1142] +24-11-19 20:34:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:35 | D | sum error = [ 4.3725, 4.6473, 4.9069, 5.1022, 5.7760] +24-11-19 20:34:35 | D | best error = [ 4.1142, 4.1142, 4.1142, 4.1142, 4.1142] +24-11-19 20:34:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:35 | D | sum error = [ 5.8268, 6.4398, 6.7409, 7.2935, 8.1062] +24-11-19 20:34:35 | D | best error = [ 4.1142, 4.1142, 4.1142, 4.1142, 4.1142] +24-11-19 20:34:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:35 | D | sum error = [ 9.0391, 9.6926, 10.6454, 11.3835, 12.5556] +24-11-19 20:34:35 | D | best error = [ 4.1142, 4.1142, 4.1142, 4.1142, 4.1142] +24-11-19 20:34:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:35 | D | sum error = [ 13.7191, 15.0498, 16.3412, 18.0514, 19.7527] +24-11-19 20:34:35 | D | best error = [ 4.1142, 4.1142, 4.1142, 4.1142, 4.1142] +24-11-19 20:34:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:35 | D | sum error = [ 21.4826, 23.7132, 25.8155, 28.1432, 30.8255] +24-11-19 20:34:35 | D | best error = [ 4.1142, 4.1142, 4.1142, 4.1142, 4.1142] +24-11-19 20:34:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:35 | D | sum error = [ 33.6011, 36.6453, 39.8254, 43.0810, 46.9206] +24-11-19 20:34:35 | D | best error = [ 4.1142, 4.1142, 4.1142, 4.1142, 4.1142] +24-11-19 20:34:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:35 | D | sum error = [ 51.1900, 55.9034, 60.5924, 65.4524, 71.4760] +24-11-19 20:34:35 | D | best error = [ 4.1142, 4.1142, 4.1142, 4.1142, 4.1142] +24-11-19 20:34:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:35 | D | sum error = [ 77.6241, 84.2416, 91.2470, 99.1084, 107.2931] +24-11-19 20:34:35 | D | best error = [ 4.1142, 4.1142, 4.1142, 4.1142, 4.1142] +24-11-19 20:34:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:35 | D | sum error = [ 116.4565, 125.5513, 136.3125, 147.6028, 159.8610] +24-11-19 20:34:35 | D | best error = [ 4.1142, 4.1142, 4.1142, 4.1142, 4.1142] +24-11-19 20:34:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:35 | D | sum error = [ 173.0238, 187.3378, 203.1500, 220.4493, 238.8969] +24-11-19 20:34:35 | D | best error = [ 4.1142, 4.1142, 4.1142, 4.1142, 4.1142] +24-11-19 20:34:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:35 | D | sum error = [ 259.3672, 281.9537, 306.3724, 333.0411, 361.8606] +24-11-19 20:34:35 | D | best error = [ 4.1142, 4.1142, 4.1142, 4.1142, 4.1142] +24-11-19 20:34:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:35 | D | sum error = [ 393.9270, 428.8514, 466.8094, 508.3144, 554.3169] +24-11-19 20:34:35 | D | best error = [ 4.1142, 4.1142, 4.1142, 4.1142, 4.1142] +24-11-19 20:34:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:35 | D | sum error = [ 605.3450, 660.0350, 720.4914, 786.7991, 858.4150] +24-11-19 20:34:35 | D | best error = [ 4.1142, 4.1142, 4.1142, 4.1142, 4.1142] +24-11-19 20:34:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:35 | D | sum error = [ 936.2083, 1020.0619, 1110.6005, 1207.6020, 1310.5725] +24-11-19 20:34:35 | D | best error = [ 4.1142, 4.1142, 4.1142, 4.1142, 4.1142] +24-11-19 20:34:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:35 | D | sum error = [ 1419.8664, 1535.0156, 1653.5760, 1776.5640, 1900.1134] +24-11-19 20:34:35 | D | best error = [ 4.1142, 4.1142, 4.1142, 4.1142, 4.1142] +24-11-19 20:34:35 | D | + error = [4.1142] +24-11-19 20:34:35 | D | - Calibrating model.layers.23.self_attn.k_proj.weight +24-11-19 20:34:35 | D | + w: sint8 +24-11-19 20:34:35 | D | + x: None +24-11-19 20:34:35 | D | + y: None +24-11-19 20:34:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:34:35 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:34:35 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:34:35 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:34:35 | D | - range ratio = [ 1.0000] +24-11-19 20:34:35 | D | sum error = [ 5.0579] +24-11-19 20:34:35 | D | best error = [ 5.0579] +24-11-19 20:34:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:47 | D | sum error = [ 5.0410, 4.4162, 4.6949, 5.3078, 5.0134] +24-11-19 20:34:47 | D | best error = [ 5.0410, 4.4162, 4.4162, 4.4162, 4.4162] +24-11-19 20:34:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:47 | D | sum error = [ 4.9673, 5.1958, 5.6692, 5.2228, 5.5653] +24-11-19 20:34:47 | D | best error = [ 4.4162, 4.4162, 4.4162, 4.4162, 4.4162] +24-11-19 20:34:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:47 | D | sum error = [ 6.6571, 6.8654, 7.0327, 8.0223, 9.2323] +24-11-19 20:34:47 | D | best error = [ 4.4162, 4.4162, 4.4162, 4.4162, 4.4162] +24-11-19 20:34:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:47 | D | sum error = [ 9.8683, 12.1268, 11.7242, 14.2602, 15.5398] +24-11-19 20:34:47 | D | best error = [ 4.4162, 4.4162, 4.4162, 4.4162, 4.4162] +24-11-19 20:34:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:47 | D | sum error = [ 16.7100, 18.5109, 21.1940, 22.3343, 26.1221] +24-11-19 20:34:47 | D | best error = [ 4.4162, 4.4162, 4.4162, 4.4162, 4.4162] +24-11-19 20:34:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:47 | D | sum error = [ 28.4500, 31.2292, 34.6541, 37.5381, 41.0778] +24-11-19 20:34:47 | D | best error = [ 4.4162, 4.4162, 4.4162, 4.4162, 4.4162] +24-11-19 20:34:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:47 | D | sum error = [ 45.2630, 49.7627, 54.1265, 60.2764, 65.5134] +24-11-19 20:34:47 | D | best error = [ 4.4162, 4.4162, 4.4162, 4.4162, 4.4162] +24-11-19 20:34:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:47 | D | sum error = [ 69.4492, 76.3132, 83.2381, 89.2741, 97.4989] +24-11-19 20:34:47 | D | best error = [ 4.4162, 4.4162, 4.4162, 4.4162, 4.4162] +24-11-19 20:34:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:47 | D | sum error = [ 106.0325, 115.3694, 124.1067, 134.7342, 145.1650] +24-11-19 20:34:47 | D | best error = [ 4.4162, 4.4162, 4.4162, 4.4162, 4.4162] +24-11-19 20:34:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:47 | D | sum error = [ 157.5868, 170.9997, 184.8963, 199.3061, 215.3115] +24-11-19 20:34:47 | D | best error = [ 4.4162, 4.4162, 4.4162, 4.4162, 4.4162] +24-11-19 20:34:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:47 | D | sum error = [ 233.7864, 251.4117, 272.7470, 295.6642, 320.1038] +24-11-19 20:34:47 | D | best error = [ 4.4162, 4.4162, 4.4162, 4.4162, 4.4162] +24-11-19 20:34:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:47 | D | sum error = [ 343.8957, 372.8476, 405.2124, 440.4871, 478.0064] +24-11-19 20:34:47 | D | best error = [ 4.4162, 4.4162, 4.4162, 4.4162, 4.4162] +24-11-19 20:34:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:47 | D | sum error = [ 517.8599, 561.5439, 608.6236, 658.6290, 715.0555] +24-11-19 20:34:47 | D | best error = [ 4.4162, 4.4162, 4.4162, 4.4162, 4.4162] +24-11-19 20:34:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:47 | D | sum error = [ 769.1955, 832.4459, 900.3299, 971.8569, 1048.1609] +24-11-19 20:34:47 | D | best error = [ 4.4162, 4.4162, 4.4162, 4.4162, 4.4162] +24-11-19 20:34:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:47 | D | sum error = [ 1128.5441, 1213.9477, 1306.1212, 1403.2030, 1507.6165] +24-11-19 20:34:47 | D | best error = [ 4.4162, 4.4162, 4.4162, 4.4162, 4.4162] +24-11-19 20:34:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:47 | D | sum error = [ 1609.7108, 1716.5620, 1829.3168, 1938.9544, 2046.6143] +24-11-19 20:34:47 | D | best error = [ 4.4162, 4.4162, 4.4162, 4.4162, 4.4162] +24-11-19 20:34:47 | D | + error = [4.4162] +24-11-19 20:34:47 | D | - Calibrating model.layers.23.self_attn.v_proj.weight +24-11-19 20:34:47 | D | + w: sint8 +24-11-19 20:34:47 | D | + x: None +24-11-19 20:34:47 | D | + y: None +24-11-19 20:34:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:47 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:34:48 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:34:48 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:34:48 | D | - range ratio = [ 1.0000] +24-11-19 20:34:48 | D | sum error = [ 2.1441] +24-11-19 20:34:48 | D | best error = [ 2.1441] +24-11-19 20:34:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:48 | D | sum error = [ 2.1197, 2.1333, 2.1270, 2.1464, 2.1822] +24-11-19 20:34:48 | D | best error = [ 1.9681, 1.9058, 1.8722, 1.8505, 1.8411] +24-11-19 20:34:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:48 | D | sum error = [ 2.2511, 2.3280, 2.4097, 2.5153, 2.6427] +24-11-19 20:34:48 | D | best error = [ 1.8356, 1.8337, 1.8326, 1.8323, 1.8322] +24-11-19 20:34:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:48 | D | sum error = [ 2.7851, 2.9566, 3.1363, 3.3527, 3.5788] +24-11-19 20:34:48 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:34:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:48 | D | sum error = [ 3.8487, 4.1051, 4.4141, 4.7103, 5.0592] +24-11-19 20:34:48 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:34:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:48 | D | sum error = [ 5.4079, 5.8043, 6.2296, 6.6459, 7.1107] +24-11-19 20:34:48 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:34:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:48 | D | sum error = [ 7.6301, 8.1140, 8.6623, 9.2340, 9.8496] +24-11-19 20:34:48 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:34:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:48 | D | sum error = [ 10.5142, 11.1745, 11.9041, 12.6722, 13.4498] +24-11-19 20:34:48 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:34:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:48 | D | sum error = [ 14.2999, 15.1825, 16.1020, 17.0573, 18.0608] +24-11-19 20:34:48 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:34:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:48 | D | sum error = [ 19.1021, 20.2011, 21.3495, 22.5531, 23.7952] +24-11-19 20:34:48 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:34:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:48 | D | sum error = [ 25.1025, 26.4825, 27.9185, 29.4239, 30.9870] +24-11-19 20:34:48 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:34:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:48 | D | sum error = [ 32.6379, 34.3606, 36.1726, 38.0485, 39.9957] +24-11-19 20:34:48 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:34:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:48 | D | sum error = [ 42.0278, 44.1454, 46.3219, 48.6060, 50.9669] +24-11-19 20:34:48 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:34:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:48 | D | sum error = [ 53.4321, 55.9862, 58.6312, 61.3623, 64.1989] +24-11-19 20:34:48 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:34:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:48 | D | sum error = [ 67.1276, 70.1747, 73.3096, 76.5636, 79.9206] +24-11-19 20:34:48 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:34:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:48 | D | sum error = [ 83.3825, 86.9498, 90.6436, 94.4449, 98.3562] +24-11-19 20:34:48 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:34:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:48 | D | sum error = [ 102.3870, 106.5454, 110.8067, 115.1913, 119.6967] +24-11-19 20:34:48 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:34:48 | D | + error = [1.8322] +24-11-19 20:34:48 | D | - Calibrating model.layers.23.self_attn.o_proj.weight +24-11-19 20:34:48 | D | + w: sint8 +24-11-19 20:34:48 | D | + x: None +24-11-19 20:34:48 | D | + y: None +24-11-19 20:34:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:48 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:34:48 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:34:48 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:34:48 | D | - range ratio = [ 1.0000] +24-11-19 20:34:48 | D | sum error = [ 0.4629] +24-11-19 20:34:48 | D | best error = [ 0.4629] +24-11-19 20:34:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:48 | D | sum error = [ 0.4577, 0.4580, 0.4613, 0.4668, 0.4745] +24-11-19 20:34:48 | D | best error = [ 0.4294, 0.4151, 0.4065, 0.4015, 0.3978] +24-11-19 20:34:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:48 | D | sum error = [ 0.4869, 0.5047, 0.5244, 0.5487, 0.5774] +24-11-19 20:34:48 | D | best error = [ 0.3954, 0.3937, 0.3926, 0.3920, 0.3913] +24-11-19 20:34:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:48 | D | sum error = [ 0.6113, 0.6478, 0.6875, 0.7347, 0.7830] +24-11-19 20:34:48 | D | best error = [ 0.3909, 0.3907, 0.3905, 0.3904, 0.3903] +24-11-19 20:34:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:48 | D | sum error = [ 0.8399, 0.8959, 0.9601, 1.0296, 1.0999] +24-11-19 20:34:48 | D | best error = [ 0.3902, 0.3902, 0.3902, 0.3902, 0.3901] +24-11-19 20:34:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:48 | D | sum error = [ 1.1754, 1.2562, 1.3415, 1.4339, 1.5321] +24-11-19 20:34:48 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:34:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:48 | D | sum error = [ 1.6326, 1.7417, 1.8565, 1.9769, 2.1045] +24-11-19 20:34:48 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:34:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:48 | D | sum error = [ 2.2382, 2.3806, 2.5319, 2.6872, 2.8518] +24-11-19 20:34:48 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:34:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:48 | D | sum error = [ 3.0286, 3.2139, 3.4075, 3.6093, 3.8226] +24-11-19 20:34:48 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:34:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:48 | D | sum error = [ 4.0475, 4.2825, 4.5280, 4.7878, 5.0564] +24-11-19 20:34:48 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:34:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:48 | D | sum error = [ 5.3411, 5.6392, 5.9485, 6.2728, 6.6115] +24-11-19 20:34:48 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:34:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:48 | D | sum error = [ 6.9644, 7.3347, 7.7188, 8.1207, 8.5394] +24-11-19 20:34:48 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:34:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:48 | D | sum error = [ 8.9749, 9.4290, 9.9013, 10.3936, 10.9072] +24-11-19 20:34:48 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:34:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:48 | D | sum error = [ 11.4391, 11.9916, 12.5651, 13.1615, 13.7809] +24-11-19 20:34:48 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:34:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:48 | D | sum error = [ 14.4198, 15.0842, 15.7718, 16.4827, 17.2169] +24-11-19 20:34:48 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:34:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:48 | D | sum error = [ 17.9780, 18.7650, 19.5778, 20.4148, 21.2791] +24-11-19 20:34:48 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:34:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:48 | D | sum error = [ 22.1694, 23.0876, 24.0324, 25.0037, 26.0026] +24-11-19 20:34:48 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:34:48 | D | + error = [0.3901] +24-11-19 20:34:49 | D | - Calibrating model.layers.23.mlp.up_proj.weight +24-11-19 20:34:49 | D | + w: sint8 +24-11-19 20:34:49 | D | + x: None +24-11-19 20:34:49 | D | + y: None +24-11-19 20:34:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:49 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:34:49 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:34:49 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:34:49 | D | - range ratio = [ 1.0000] +24-11-19 20:34:49 | D | sum error = [ 7.5015] +24-11-19 20:34:49 | D | best error = [ 7.5015] +24-11-19 20:34:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:50 | D | sum error = [ 7.4406, 7.4284, 7.4714, 7.5484, 7.6788] +24-11-19 20:34:50 | D | best error = [ 6.8943, 6.6721, 6.5576, 6.4910, 6.4533] +24-11-19 20:34:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:50 | D | sum error = [ 7.8838, 8.1582, 8.4792, 8.8800, 9.3583] +24-11-19 20:34:50 | D | best error = [ 6.4357, 6.4262, 6.4234, 6.4223, 6.4221] +24-11-19 20:34:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:50 | D | sum error = [ 9.8993, 10.5036, 11.1561, 11.9540, 12.7494] +24-11-19 20:34:50 | D | best error = [ 6.4220, 6.4220, 6.4220, 6.4220, 6.4220] +24-11-19 20:34:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:50 | D | sum error = [ 13.6538, 14.6186, 15.6542, 16.7719, 17.9753] +24-11-19 20:34:50 | D | best error = [ 6.4220, 6.4220, 6.4220, 6.4220, 6.4220] +24-11-19 20:34:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:50 | D | sum error = [ 19.2512, 20.5929, 22.0538, 23.5714, 25.1772] +24-11-19 20:34:50 | D | best error = [ 6.4220, 6.4220, 6.4220, 6.4220, 6.4220] +24-11-19 20:34:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:50 | D | sum error = [ 26.9151, 28.7444, 30.6687, 32.7099, 34.8347] +24-11-19 20:34:50 | D | best error = [ 6.4220, 6.4220, 6.4220, 6.4220, 6.4220] +24-11-19 20:34:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:50 | D | sum error = [ 37.0915, 39.4732, 41.9690, 44.5970, 47.3696] +24-11-19 20:34:50 | D | best error = [ 6.4220, 6.4220, 6.4220, 6.4220, 6.4220] +24-11-19 20:34:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:50 | D | sum error = [ 50.2562, 53.3293, 56.5341, 59.8874, 63.4127] +24-11-19 20:34:50 | D | best error = [ 6.4220, 6.4220, 6.4220, 6.4220, 6.4220] +24-11-19 20:34:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:50 | D | sum error = [ 67.1012, 70.9649, 74.9988, 79.2421, 83.6619] +24-11-19 20:34:50 | D | best error = [ 6.4220, 6.4220, 6.4220, 6.4220, 6.4220] +24-11-19 20:34:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:50 | D | sum error = [ 88.2929, 93.1176, 98.1647, 103.4320, 108.9267] +24-11-19 20:34:50 | D | best error = [ 6.4220, 6.4220, 6.4220, 6.4220, 6.4220] +24-11-19 20:34:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:50 | D | sum error = [ 114.6351, 120.5869, 126.7973, 133.2444, 139.9302] +24-11-19 20:34:50 | D | best error = [ 6.4220, 6.4220, 6.4220, 6.4220, 6.4220] +24-11-19 20:34:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:50 | D | sum error = [ 146.9007, 154.1276, 161.6262, 169.3862, 177.4350] +24-11-19 20:34:50 | D | best error = [ 6.4220, 6.4220, 6.4220, 6.4220, 6.4220] +24-11-19 20:34:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:50 | D | sum error = [ 185.7693, 194.3976, 203.3234, 212.5533, 222.0997] +24-11-19 20:34:50 | D | best error = [ 6.4220, 6.4220, 6.4220, 6.4220, 6.4220] +24-11-19 20:34:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:50 | D | sum error = [ 231.9521, 242.1191, 252.6195, 263.4480, 274.5782] +24-11-19 20:34:50 | D | best error = [ 6.4220, 6.4220, 6.4220, 6.4220, 6.4220] +24-11-19 20:34:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:50 | D | sum error = [ 286.0770, 297.9302, 310.1340, 322.7088, 335.6404] +24-11-19 20:34:50 | D | best error = [ 6.4220, 6.4220, 6.4220, 6.4220, 6.4220] +24-11-19 20:34:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:50 | D | sum error = [ 348.9469, 362.6120, 376.6440, 391.0670, 405.8804] +24-11-19 20:34:50 | D | best error = [ 6.4220, 6.4220, 6.4220, 6.4220, 6.4220] +24-11-19 20:34:50 | D | + error = [6.4220] +24-11-19 20:34:50 | D | - Calibrating model.layers.23.mlp.gate_proj.weight +24-11-19 20:34:50 | D | + w: sint8 +24-11-19 20:34:50 | D | + x: None +24-11-19 20:34:50 | D | + y: None +24-11-19 20:34:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:50 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:34:50 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:34:50 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:34:50 | D | - range ratio = [ 1.0000] +24-11-19 20:34:50 | D | sum error = [ 10.1357] +24-11-19 20:34:50 | D | best error = [ 10.1357] +24-11-19 20:34:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:52 | D | sum error = [ 10.0170, 10.0139, 10.0576, 10.1764, 10.3485] +24-11-19 20:34:52 | D | best error = [ 9.3100, 9.0050, 8.8443, 8.7549, 8.7066] +24-11-19 20:34:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:52 | D | sum error = [ 10.6313, 10.9830, 11.4541, 11.9628, 12.6044] +24-11-19 20:34:52 | D | best error = [ 8.6799, 8.6682, 8.6647, 8.6630, 8.6626] +24-11-19 20:34:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:52 | D | sum error = [ 13.3529, 14.1757, 15.0623, 16.0631, 17.1722] +24-11-19 20:34:52 | D | best error = [ 8.6625, 8.6625, 8.6625, 8.6625, 8.6625] +24-11-19 20:34:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:52 | D | sum error = [ 18.3973, 19.7125, 21.1371, 22.6841, 24.3216] +24-11-19 20:34:52 | D | best error = [ 8.6625, 8.6625, 8.6625, 8.6625, 8.6625] +24-11-19 20:34:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:52 | D | sum error = [ 26.0661, 27.9454, 29.9499, 32.0419, 34.2660] +24-11-19 20:34:52 | D | best error = [ 8.6625, 8.6625, 8.6625, 8.6625, 8.6625] +24-11-19 20:34:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:52 | D | sum error = [ 36.6504, 39.2006, 41.8653, 44.7287, 47.7659] +24-11-19 20:34:52 | D | best error = [ 8.6625, 8.6625, 8.6625, 8.6625, 8.6625] +24-11-19 20:34:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:52 | D | sum error = [ 50.9079, 54.2652, 57.8238, 61.5876, 65.5565] +24-11-19 20:34:52 | D | best error = [ 8.6625, 8.6625, 8.6625, 8.6625, 8.6625] +24-11-19 20:34:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:52 | D | sum error = [ 69.7885, 74.2014, 78.9043, 83.8733, 89.0857] +24-11-19 20:34:52 | D | best error = [ 8.6625, 8.6625, 8.6625, 8.6625, 8.6625] +24-11-19 20:34:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:52 | D | sum error = [ 94.5962, 100.3852, 106.4969, 112.9249, 119.6947] +24-11-19 20:34:52 | D | best error = [ 8.6625, 8.6625, 8.6625, 8.6625, 8.6625] +24-11-19 20:34:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:52 | D | sum error = [ 126.7845, 134.2737, 142.1796, 150.4366, 159.1375] +24-11-19 20:34:52 | D | best error = [ 8.6625, 8.6625, 8.6625, 8.6625, 8.6625] +24-11-19 20:34:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:52 | D | sum error = [ 168.2720, 177.8337, 187.8831, 198.4258, 209.4893] +24-11-19 20:34:52 | D | best error = [ 8.6625, 8.6625, 8.6625, 8.6625, 8.6625] +24-11-19 20:34:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:52 | D | sum error = [ 221.0669, 233.1959, 245.8784, 259.1218, 273.0161] +24-11-19 20:34:52 | D | best error = [ 8.6625, 8.6625, 8.6625, 8.6625, 8.6625] +24-11-19 20:34:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:52 | D | sum error = [ 287.5247, 302.6532, 318.4516, 334.9176, 352.0644] +24-11-19 20:34:52 | D | best error = [ 8.6625, 8.6625, 8.6625, 8.6625, 8.6625] +24-11-19 20:34:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:52 | D | sum error = [ 369.9218, 388.5577, 407.9266, 428.0817, 449.0243] +24-11-19 20:34:52 | D | best error = [ 8.6625, 8.6625, 8.6625, 8.6625, 8.6625] +24-11-19 20:34:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:52 | D | sum error = [ 470.7560, 493.2964, 516.6170, 540.7602, 565.7370] +24-11-19 20:34:52 | D | best error = [ 8.6625, 8.6625, 8.6625, 8.6625, 8.6625] +24-11-19 20:34:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:52 | D | sum error = [ 591.5440, 618.1601, 645.6338, 673.9567, 703.1062] +24-11-19 20:34:52 | D | best error = [ 8.6625, 8.6625, 8.6625, 8.6625, 8.6625] +24-11-19 20:34:52 | D | + error = [8.6625] +24-11-19 20:34:52 | D | - Calibrating model.layers.23.mlp.down_proj.weight +24-11-19 20:34:52 | D | + w: sint8 +24-11-19 20:34:52 | D | + x: None +24-11-19 20:34:52 | D | + y: None +24-11-19 20:34:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:52 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:34:52 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:34:52 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:34:52 | D | - range ratio = [ 1.0000] +24-11-19 20:34:52 | D | sum error = [ 1.1715] +24-11-19 20:34:52 | D | best error = [ 1.1715] +24-11-19 20:34:53 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:53 | D | sum error = [ 1.1616, 1.1538, 1.1440, 1.1397, 1.1372] +24-11-19 20:34:53 | D | best error = [ 1.1222, 1.0980, 1.0805, 1.0673, 1.0574] +24-11-19 20:34:53 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:53 | D | sum error = [ 1.1379, 1.1438, 1.1522, 1.1650, 1.1837] +24-11-19 20:34:53 | D | best error = [ 1.0498, 1.0436, 1.0386, 1.0350, 1.0325] +24-11-19 20:34:53 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:53 | D | sum error = [ 1.2089, 1.2378, 1.2739, 1.3171, 1.3695] +24-11-19 20:34:53 | D | best error = [ 1.0305, 1.0289, 1.0277, 1.0271, 1.0266] +24-11-19 20:34:53 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:53 | D | sum error = [ 1.4300, 1.4957, 1.5711, 1.6587, 1.7560] +24-11-19 20:34:53 | D | best error = [ 1.0263, 1.0260, 1.0259, 1.0258, 1.0257] +24-11-19 20:34:53 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:53 | D | sum error = [ 1.8594, 1.9777, 2.1042, 2.2438, 2.3932] +24-11-19 20:34:53 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 20:34:53 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:53 | D | sum error = [ 2.5574, 2.7329, 2.9207, 3.1228, 3.3419] +24-11-19 20:34:53 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 20:34:53 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:53 | D | sum error = [ 3.5743, 3.8249, 4.0905, 4.3755, 4.6769] +24-11-19 20:34:53 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 20:34:53 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:53 | D | sum error = [ 4.9996, 5.3428, 5.7054, 6.0902, 6.4988] +24-11-19 20:34:53 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 20:34:53 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:53 | D | sum error = [ 6.9302, 7.3883, 7.8729, 8.3823, 8.9213] +24-11-19 20:34:53 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 20:34:53 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:53 | D | sum error = [ 9.4909, 10.0914, 10.7264, 11.3941, 12.0977] +24-11-19 20:34:53 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 20:34:53 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:53 | D | sum error = [ 12.8397, 13.6206, 14.4411, 15.3033, 16.2073] +24-11-19 20:34:53 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 20:34:53 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:53 | D | sum error = [ 17.1606, 18.1579, 19.2066, 20.3028, 21.4513] +24-11-19 20:34:53 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 20:34:53 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:53 | D | sum error = [ 22.6543, 23.9131, 25.2296, 26.6049, 28.0405] +24-11-19 20:34:53 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 20:34:53 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:53 | D | sum error = [ 29.5385, 31.1035, 32.7341, 34.4316, 36.1982] +24-11-19 20:34:53 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 20:34:53 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:53 | D | sum error = [ 38.0361, 39.9500, 41.9371, 44.0005, 46.1391] +24-11-19 20:34:53 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 20:34:53 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:53 | D | sum error = [ 48.3587, 50.6585, 53.0393, 55.5029, 58.0473] +24-11-19 20:34:53 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 20:34:53 | D | + error = [1.0257] +24-11-19 20:34:53 | D | - Quantizing model.layers.23.self_attn.q_proj.weight +24-11-19 20:34:54 | D | - Quantizing model.layers.23.self_attn.k_proj.weight +24-11-19 20:34:55 | D | - Quantizing model.layers.23.self_attn.v_proj.weight +24-11-19 20:34:56 | D | - Quantizing model.layers.23.self_attn.o_proj.weight +24-11-19 20:34:56 | D | - Quantizing model.layers.23.mlp.up_proj.weight +24-11-19 20:34:57 | D | - Quantizing model.layers.23.mlp.gate_proj.weight +24-11-19 20:34:58 | D | - Quantizing model.layers.23.mlp.down_proj.weight +24-11-19 20:35:08 | D | - Quantizing layer model.layers.24 +24-11-19 20:35:08 | D | - Calibrating model.layers.24.self_attn.q_proj.weight +24-11-19 20:35:08 | D | + w: sint8 +24-11-19 20:35:08 | D | + x: None +24-11-19 20:35:08 | D | + y: None +24-11-19 20:35:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:35:08 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:08 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:08 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:08 | D | - range ratio = [ 1.0000] +24-11-19 20:35:08 | D | sum error = [ 4.6773] +24-11-19 20:35:08 | D | best error = [ 4.6773] +24-11-19 20:35:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:20 | D | sum error = [ 4.7046, 4.7984, 4.7793, 4.7897, 4.9644] +24-11-19 20:35:20 | D | best error = [ 4.6773, 4.6773, 4.6773, 4.6773, 4.6773] +24-11-19 20:35:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:20 | D | sum error = [ 5.0389, 5.0717, 5.5804, 5.6436, 6.0939] +24-11-19 20:35:20 | D | best error = [ 4.6773, 4.6773, 4.6773, 4.6773, 4.6773] +24-11-19 20:35:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:20 | D | sum error = [ 6.4072, 6.9244, 7.3878, 7.9699, 8.5184] +24-11-19 20:35:20 | D | best error = [ 4.6773, 4.6773, 4.6773, 4.6773, 4.6773] +24-11-19 20:35:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:20 | D | sum error = [ 9.2537, 10.0420, 10.9091, 12.1199, 12.9743] +24-11-19 20:35:20 | D | best error = [ 4.6773, 4.6773, 4.6773, 4.6773, 4.6773] +24-11-19 20:35:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:20 | D | sum error = [ 14.0679, 15.5164, 16.8661, 18.0757, 19.6510] +24-11-19 20:35:20 | D | best error = [ 4.6773, 4.6773, 4.6773, 4.6773, 4.6773] +24-11-19 20:35:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:20 | D | sum error = [ 21.2887, 23.0515, 24.9663, 27.1553, 29.4921] +24-11-19 20:35:20 | D | best error = [ 4.6773, 4.6773, 4.6773, 4.6773, 4.6773] +24-11-19 20:35:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:20 | D | sum error = [ 31.7838, 34.7826, 37.3377, 40.5758, 44.0340] +24-11-19 20:35:20 | D | best error = [ 4.6773, 4.6773, 4.6773, 4.6773, 4.6773] +24-11-19 20:35:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:20 | D | sum error = [ 47.8533, 52.1003, 56.2167, 60.8540, 65.9223] +24-11-19 20:35:20 | D | best error = [ 4.6773, 4.6773, 4.6773, 4.6773, 4.6773] +24-11-19 20:35:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:20 | D | sum error = [ 70.8757, 76.8849, 83.2984, 89.7577, 97.1509] +24-11-19 20:35:20 | D | best error = [ 4.6773, 4.6773, 4.6773, 4.6773, 4.6773] +24-11-19 20:35:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:20 | D | sum error = [ 105.0243, 113.6647, 122.7488, 132.4510, 142.9820] +24-11-19 20:35:20 | D | best error = [ 4.6773, 4.6773, 4.6773, 4.6773, 4.6773] +24-11-19 20:35:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:20 | D | sum error = [ 154.4884, 166.7650, 180.0529, 194.2471, 209.7128] +24-11-19 20:35:20 | D | best error = [ 4.6773, 4.6773, 4.6773, 4.6773, 4.6773] +24-11-19 20:35:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:20 | D | sum error = [ 226.2655, 244.0942, 262.7642, 283.5329, 305.3532] +24-11-19 20:35:20 | D | best error = [ 4.6773, 4.6773, 4.6773, 4.6773, 4.6773] +24-11-19 20:35:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:20 | D | sum error = [ 329.1110, 354.9825, 382.6416, 412.5023, 444.9231] +24-11-19 20:35:20 | D | best error = [ 4.6773, 4.6773, 4.6773, 4.6773, 4.6773] +24-11-19 20:35:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:20 | D | sum error = [ 480.1844, 518.6432, 560.2248, 605.2830, 653.8954] +24-11-19 20:35:20 | D | best error = [ 4.6773, 4.6773, 4.6773, 4.6773, 4.6773] +24-11-19 20:35:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:20 | D | sum error = [ 706.8657, 764.2814, 826.1680, 892.5757, 963.3662] +24-11-19 20:35:20 | D | best error = [ 4.6773, 4.6773, 4.6773, 4.6773, 4.6773] +24-11-19 20:35:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:20 | D | sum error = [ 1038.7075, 1118.1562, 1200.7701, 1287.1550, 1375.1068] +24-11-19 20:35:20 | D | best error = [ 4.6773, 4.6773, 4.6773, 4.6773, 4.6773] +24-11-19 20:35:20 | D | + error = [4.6773] +24-11-19 20:35:20 | D | - Calibrating model.layers.24.self_attn.k_proj.weight +24-11-19 20:35:20 | D | + w: sint8 +24-11-19 20:35:20 | D | + x: None +24-11-19 20:35:20 | D | + y: None +24-11-19 20:35:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:35:20 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:20 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:20 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:20 | D | - range ratio = [ 1.0000] +24-11-19 20:35:20 | D | sum error = [ 4.5095] +24-11-19 20:35:20 | D | best error = [ 4.5095] +24-11-19 20:35:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:32 | D | sum error = [ 5.4636, 4.5038, 4.7747, 5.3317, 5.2156] +24-11-19 20:35:32 | D | best error = [ 4.5095, 4.5038, 4.5038, 4.5038, 4.5038] +24-11-19 20:35:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:32 | D | sum error = [ 5.0204, 5.0137, 5.9344, 5.2917, 6.0708] +24-11-19 20:35:32 | D | best error = [ 4.5038, 4.5038, 4.5038, 4.5038, 4.5038] +24-11-19 20:35:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:32 | D | sum error = [ 6.0816, 7.0078, 8.1374, 7.8807, 8.7301] +24-11-19 20:35:32 | D | best error = [ 4.5038, 4.5038, 4.5038, 4.5038, 4.5038] +24-11-19 20:35:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:32 | D | sum error = [ 9.5671, 10.4959, 10.5522, 12.3637, 12.8747] +24-11-19 20:35:32 | D | best error = [ 4.5038, 4.5038, 4.5038, 4.5038, 4.5038] +24-11-19 20:35:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:32 | D | sum error = [ 13.9605, 14.8246, 16.6459, 18.1302, 19.8852] +24-11-19 20:35:32 | D | best error = [ 4.5038, 4.5038, 4.5038, 4.5038, 4.5038] +24-11-19 20:35:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:32 | D | sum error = [ 21.4322, 22.3826, 24.1357, 26.8461, 28.1983] +24-11-19 20:35:32 | D | best error = [ 4.5038, 4.5038, 4.5038, 4.5038, 4.5038] +24-11-19 20:35:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:32 | D | sum error = [ 30.8654, 33.8116, 35.8930, 39.9728, 42.5013] +24-11-19 20:35:32 | D | best error = [ 4.5038, 4.5038, 4.5038, 4.5038, 4.5038] +24-11-19 20:35:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:32 | D | sum error = [ 45.7473, 50.0739, 53.4746, 58.6016, 63.7412] +24-11-19 20:35:32 | D | best error = [ 4.5038, 4.5038, 4.5038, 4.5038, 4.5038] +24-11-19 20:35:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:32 | D | sum error = [ 68.5969, 73.7684, 79.5555, 85.7870, 92.9327] +24-11-19 20:35:32 | D | best error = [ 4.5038, 4.5038, 4.5038, 4.5038, 4.5038] +24-11-19 20:35:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:32 | D | sum error = [ 100.2515, 109.2477, 117.9660, 126.3473, 136.4979] +24-11-19 20:35:32 | D | best error = [ 4.5038, 4.5038, 4.5038, 4.5038, 4.5038] +24-11-19 20:35:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:32 | D | sum error = [ 148.1486, 160.5207, 173.5189, 188.2495, 203.0961] +24-11-19 20:35:32 | D | best error = [ 4.5038, 4.5038, 4.5038, 4.5038, 4.5038] +24-11-19 20:35:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:32 | D | sum error = [ 221.3804, 238.7654, 257.8666, 278.3854, 300.6788] +24-11-19 20:35:32 | D | best error = [ 4.5038, 4.5038, 4.5038, 4.5038, 4.5038] +24-11-19 20:35:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:32 | D | sum error = [ 324.4872, 349.4509, 377.3343, 407.6781, 438.8442] +24-11-19 20:35:32 | D | best error = [ 4.5038, 4.5038, 4.5038, 4.5038, 4.5038] +24-11-19 20:35:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:32 | D | sum error = [ 473.4940, 510.0716, 551.5074, 594.9198, 643.1826] +24-11-19 20:35:32 | D | best error = [ 4.5038, 4.5038, 4.5038, 4.5038, 4.5038] +24-11-19 20:35:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:32 | D | sum error = [ 696.2807, 751.8965, 813.5955, 879.2221, 950.0846] +24-11-19 20:35:32 | D | best error = [ 4.5038, 4.5038, 4.5038, 4.5038, 4.5038] +24-11-19 20:35:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:32 | D | sum error = [ 1025.1189, 1106.9391, 1192.7939, 1281.6909, 1374.0362] +24-11-19 20:35:32 | D | best error = [ 4.5038, 4.5038, 4.5038, 4.5038, 4.5038] +24-11-19 20:35:32 | D | + error = [4.5038] +24-11-19 20:35:33 | D | - Calibrating model.layers.24.self_attn.v_proj.weight +24-11-19 20:35:33 | D | + w: sint8 +24-11-19 20:35:33 | D | + x: None +24-11-19 20:35:33 | D | + y: None +24-11-19 20:35:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:33 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:33 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:33 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:33 | D | - range ratio = [ 1.0000] +24-11-19 20:35:33 | D | sum error = [ 2.3517] +24-11-19 20:35:33 | D | best error = [ 2.3517] +24-11-19 20:35:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:33 | D | sum error = [ 2.3398, 2.3509, 2.3448, 2.3651, 2.4108] +24-11-19 20:35:33 | D | best error = [ 2.1712, 2.1005, 2.0575, 2.0332, 2.0219] +24-11-19 20:35:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:33 | D | sum error = [ 2.4925, 2.5686, 2.6655, 2.8063, 2.9362] +24-11-19 20:35:33 | D | best error = [ 2.0158, 2.0136, 2.0118, 2.0112, 2.0110] +24-11-19 20:35:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:33 | D | sum error = [ 3.1154, 3.2738, 3.4994, 3.7487, 4.0174] +24-11-19 20:35:33 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:35:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:33 | D | sum error = [ 4.2975, 4.5898, 4.9204, 5.2707, 5.6321] +24-11-19 20:35:33 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:35:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:33 | D | sum error = [ 6.0443, 6.4868, 6.9483, 7.4182, 7.9050] +24-11-19 20:35:33 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:35:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:33 | D | sum error = [ 8.4802, 9.0294, 9.6239, 10.2526, 10.9317] +24-11-19 20:35:33 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:35:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:33 | D | sum error = [ 11.6326, 12.3835, 13.1774, 13.9702, 14.8541] +24-11-19 20:35:33 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:35:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:33 | D | sum error = [ 15.7770, 16.7568, 17.7746, 18.8359, 19.9419] +24-11-19 20:35:33 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:35:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:33 | D | sum error = [ 21.1481, 22.3750, 23.6673, 25.0119, 26.4436] +24-11-19 20:35:33 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:35:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:33 | D | sum error = [ 27.9288, 29.4568, 31.0980, 32.7712, 34.5662] +24-11-19 20:35:33 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:35:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:33 | D | sum error = [ 36.3988, 38.3429, 40.3457, 42.4358, 44.6386] +24-11-19 20:35:33 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:35:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:33 | D | sum error = [ 46.9095, 49.2840, 51.7299, 54.2867, 56.9539] +24-11-19 20:35:33 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:35:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:33 | D | sum error = [ 59.7088, 62.5641, 65.5040, 68.5557, 71.7099] +24-11-19 20:35:33 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:35:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:33 | D | sum error = [ 74.9622, 78.3230, 81.8181, 85.4224, 89.1572] +24-11-19 20:35:33 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:35:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:33 | D | sum error = [ 92.9977, 96.9705, 101.0493, 105.2881, 109.6514] +24-11-19 20:35:33 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:35:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:33 | D | sum error = [ 114.1210, 118.7217, 123.4541, 128.3102, 133.2939] +24-11-19 20:35:33 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:35:33 | D | + error = [2.0108] +24-11-19 20:35:33 | D | - Calibrating model.layers.24.self_attn.o_proj.weight +24-11-19 20:35:33 | D | + w: sint8 +24-11-19 20:35:33 | D | + x: None +24-11-19 20:35:33 | D | + y: None +24-11-19 20:35:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:33 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:33 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:33 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:33 | D | - range ratio = [ 1.0000] +24-11-19 20:35:33 | D | sum error = [ 0.4864] +24-11-19 20:35:33 | D | best error = [ 0.4864] +24-11-19 20:35:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:34 | D | sum error = [ 0.4824, 0.4811, 0.4802, 0.4812, 0.4866] +24-11-19 20:35:34 | D | best error = [ 0.4501, 0.4344, 0.4240, 0.4173, 0.4123] +24-11-19 20:35:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:34 | D | sum error = [ 0.4927, 0.5041, 0.5175, 0.5329, 0.5512] +24-11-19 20:35:34 | D | best error = [ 0.4087, 0.4061, 0.4037, 0.4020, 0.4007] +24-11-19 20:35:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:34 | D | sum error = [ 0.5753, 0.6026, 0.6318, 0.6652, 0.7013] +24-11-19 20:35:34 | D | best error = [ 0.3997, 0.3990, 0.3984, 0.3980, 0.3975] +24-11-19 20:35:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:34 | D | sum error = [ 0.7434, 0.7890, 0.8378, 0.8905, 0.9505] +24-11-19 20:35:34 | D | best error = [ 0.3971, 0.3968, 0.3966, 0.3965, 0.3964] +24-11-19 20:35:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:34 | D | sum error = [ 1.0107, 1.0767, 1.1490, 1.2259, 1.3049] +24-11-19 20:35:34 | D | best error = [ 0.3963, 0.3962, 0.3961, 0.3961, 0.3961] +24-11-19 20:35:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:34 | D | sum error = [ 1.3922, 1.4828, 1.5786, 1.6805, 1.7885] +24-11-19 20:35:34 | D | best error = [ 0.3960, 0.3960, 0.3960, 0.3960, 0.3960] +24-11-19 20:35:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:34 | D | sum error = [ 1.9024, 2.0211, 2.1484, 2.2825, 2.4239] +24-11-19 20:35:34 | D | best error = [ 0.3960, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:35:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:34 | D | sum error = [ 2.5704, 2.7267, 2.8905, 3.0607, 3.2408] +24-11-19 20:35:34 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:35:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:34 | D | sum error = [ 3.4323, 3.6321, 3.8429, 4.0627, 4.2932] +24-11-19 20:35:34 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:35:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:34 | D | sum error = [ 4.5358, 4.7913, 5.0575, 5.3362, 5.6280] +24-11-19 20:35:34 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:35:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:34 | D | sum error = [ 5.9353, 6.2544, 6.5910, 6.9408, 7.3065] +24-11-19 20:35:34 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:35:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:34 | D | sum error = [ 7.6874, 8.0865, 8.5002, 8.9319, 9.3825] +24-11-19 20:35:34 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:35:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:34 | D | sum error = [ 9.8497, 10.3345, 10.8393, 11.3627, 11.9061] +24-11-19 20:35:34 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:35:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:34 | D | sum error = [ 12.4690, 13.0530, 13.6564, 14.2843, 14.9323] +24-11-19 20:35:34 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:35:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:34 | D | sum error = [ 15.6040, 16.2992, 17.0184, 17.7600, 18.5248] +24-11-19 20:35:34 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:35:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:34 | D | sum error = [ 19.3136, 20.1256, 20.9620, 21.8241, 22.7121] +24-11-19 20:35:34 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:35:34 | D | + error = [0.3959] +24-11-19 20:35:34 | D | - Calibrating model.layers.24.mlp.up_proj.weight +24-11-19 20:35:34 | D | + w: sint8 +24-11-19 20:35:34 | D | + x: None +24-11-19 20:35:34 | D | + y: None +24-11-19 20:35:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:34 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:34 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:34 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:34 | D | - range ratio = [ 1.0000] +24-11-19 20:35:34 | D | sum error = [ 7.7925] +24-11-19 20:35:34 | D | best error = [ 7.7925] +24-11-19 20:35:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:35 | D | sum error = [ 7.7182, 7.7217, 7.7354, 7.8167, 7.9711] +24-11-19 20:35:35 | D | best error = [ 7.1320, 6.8850, 6.7529, 6.6794, 6.6397] +24-11-19 20:35:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:35 | D | sum error = [ 8.1932, 8.4586, 8.7830, 9.1794, 9.6858] +24-11-19 20:35:35 | D | best error = [ 6.6210, 6.6120, 6.6092, 6.6080, 6.6075] +24-11-19 20:35:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:35 | D | sum error = [ 10.2419, 10.8942, 11.5781, 12.3572, 13.2075] +24-11-19 20:35:35 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:35:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:35 | D | sum error = [ 14.1434, 15.1384, 16.2145, 17.3729, 18.6145] +24-11-19 20:35:35 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:35:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:35 | D | sum error = [ 19.9418, 21.3732, 22.8630, 24.4508, 26.1557] +24-11-19 20:35:35 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:35:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:35 | D | sum error = [ 27.9420, 29.8156, 31.8148, 33.9349, 36.1343] +24-11-19 20:35:35 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:35:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:35 | D | sum error = [ 38.4649, 40.9319, 43.5314, 46.2550, 49.1192] +24-11-19 20:35:35 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:35:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:35 | D | sum error = [ 52.1487, 55.3217, 58.6341, 62.1180, 65.7629] +24-11-19 20:35:35 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:35:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:35 | D | sum error = [ 69.5989, 73.6106, 77.8027, 82.1969, 86.7614] +24-11-19 20:35:35 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:35:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:35 | D | sum error = [ 91.5594, 96.5501, 101.7480, 107.2137, 112.8617] +24-11-19 20:35:35 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:35:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:35 | D | sum error = [ 118.7586, 124.9062, 131.2903, 137.9395, 144.8279] +24-11-19 20:35:35 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:35:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:35 | D | sum error = [ 151.9718, 159.3874, 167.0625, 175.0529, 183.2993] +24-11-19 20:35:35 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:35:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:35 | D | sum error = [ 191.8600, 200.7079, 209.8574, 219.3172, 229.0905] +24-11-19 20:35:35 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:35:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:35 | D | sum error = [ 239.1748, 249.5797, 260.3075, 271.3757, 282.7526] +24-11-19 20:35:35 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:35:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:35 | D | sum error = [ 294.4832, 306.5473, 318.9552, 331.7335, 344.8514] +24-11-19 20:35:35 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:35:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:35 | D | sum error = [ 358.3238, 372.1585, 386.3728, 400.9587, 415.9204] +24-11-19 20:35:35 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:35:35 | D | + error = [6.6075] +24-11-19 20:35:35 | D | - Calibrating model.layers.24.mlp.gate_proj.weight +24-11-19 20:35:35 | D | + w: sint8 +24-11-19 20:35:35 | D | + x: None +24-11-19 20:35:35 | D | + y: None +24-11-19 20:35:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:35 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:35:35 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:35:35 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:35:35 | D | - range ratio = [ 1.0000] +24-11-19 20:35:35 | D | sum error = [ 10.4820] +24-11-19 20:35:35 | D | best error = [ 10.4820] +24-11-19 20:35:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:37 | D | sum error = [ 10.4450, 10.4171, 10.4423, 10.5726, 10.7611] +24-11-19 20:35:37 | D | best error = [ 9.6175, 9.2789, 9.1103, 9.0125, 8.9607] +24-11-19 20:35:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:37 | D | sum error = [ 11.0427, 11.3878, 11.8344, 12.3819, 13.0689] +24-11-19 20:35:37 | D | best error = [ 8.9346, 8.9235, 8.9187, 8.9169, 8.9162] +24-11-19 20:35:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:37 | D | sum error = [ 13.7903, 14.6514, 15.6246, 16.6613, 17.7917] +24-11-19 20:35:37 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:35:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:37 | D | sum error = [ 19.0405, 20.3996, 21.8468, 23.4208, 25.1201] +24-11-19 20:35:37 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:35:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:37 | D | sum error = [ 26.9178, 28.8383, 30.8766, 33.0536, 35.3834] +24-11-19 20:35:37 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:35:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:37 | D | sum error = [ 37.8459, 40.4597, 43.2253, 46.1078, 49.2449] +24-11-19 20:35:37 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:35:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:37 | D | sum error = [ 52.5010, 55.9404, 59.5832, 63.4590, 67.5576] +24-11-19 20:35:37 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:35:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:37 | D | sum error = [ 71.8115, 76.3769, 81.1279, 86.1733, 91.4546] +24-11-19 20:35:37 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:35:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:37 | D | sum error = [ 97.0592, 102.9184, 109.1303, 115.6443, 122.5291] +24-11-19 20:35:37 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:35:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:37 | D | sum error = [ 129.7296, 137.2880, 145.2531, 153.6107, 162.3857] +24-11-19 20:35:37 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:35:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:37 | D | sum error = [ 171.6074, 181.2616, 191.4027, 202.0026, 213.1428] +24-11-19 20:35:37 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:35:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:37 | D | sum error = [ 224.8038, 236.9883, 249.7701, 263.1030, 277.0046] +24-11-19 20:35:37 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:35:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:37 | D | sum error = [ 291.5521, 306.7064, 322.4727, 338.9192, 356.0559] +24-11-19 20:35:37 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:35:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:37 | D | sum error = [ 373.8904, 392.4718, 411.7378, 431.7112, 452.4312] +24-11-19 20:35:37 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:35:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:37 | D | sum error = [ 473.9178, 496.2166, 519.3158, 543.2248, 567.9879] +24-11-19 20:35:37 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:35:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:37 | D | sum error = [ 593.5856, 620.0019, 647.2799, 675.3803, 704.3256] +24-11-19 20:35:37 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:35:37 | D | + error = [8.9161] +24-11-19 20:35:37 | D | - Calibrating model.layers.24.mlp.down_proj.weight +24-11-19 20:35:37 | D | + w: sint8 +24-11-19 20:35:37 | D | + x: None +24-11-19 20:35:37 | D | + y: None +24-11-19 20:35:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:37 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:35:37 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:35:37 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:35:37 | D | - range ratio = [ 1.0000] +24-11-19 20:35:37 | D | sum error = [ 1.1968] +24-11-19 20:35:37 | D | best error = [ 1.1968] +24-11-19 20:35:38 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:38 | D | sum error = [ 1.1843, 1.1767, 1.1697, 1.1656, 1.1654] +24-11-19 20:35:38 | D | best error = [ 1.1429, 1.1164, 1.0987, 1.0857, 1.0754] +24-11-19 20:35:38 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:38 | D | sum error = [ 1.1724, 1.1771, 1.1877, 1.2062, 1.2311] +24-11-19 20:35:38 | D | best error = [ 1.0680, 1.0614, 1.0563, 1.0526, 1.0496] +24-11-19 20:35:38 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:38 | D | sum error = [ 1.2621, 1.2976, 1.3436, 1.3978, 1.4575] +24-11-19 20:35:38 | D | best error = [ 1.0474, 1.0460, 1.0451, 1.0443, 1.0438] +24-11-19 20:35:38 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:38 | D | sum error = [ 1.5283, 1.6069, 1.6934, 1.7954, 1.9036] +24-11-19 20:35:38 | D | best error = [ 1.0435, 1.0434, 1.0432, 1.0432, 1.0432] +24-11-19 20:35:38 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:38 | D | sum error = [ 2.0189, 2.1512, 2.2967, 2.4468, 2.6116] +24-11-19 20:35:38 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 20:35:38 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:38 | D | sum error = [ 2.7846, 2.9754, 3.1790, 3.3976, 3.6317] +24-11-19 20:35:38 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 20:35:38 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:38 | D | sum error = [ 3.8797, 4.1412, 4.4208, 4.7179, 5.0320] +24-11-19 20:35:38 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 20:35:38 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:38 | D | sum error = [ 5.3730, 5.7220, 6.1019, 6.4985, 6.9223] +24-11-19 20:35:38 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 20:35:38 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:38 | D | sum error = [ 7.3736, 7.8445, 8.3436, 8.8732, 9.4342] +24-11-19 20:35:38 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 20:35:38 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:38 | D | sum error = [ 10.0191, 10.6405, 11.2940, 11.9857, 12.7121] +24-11-19 20:35:38 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 20:35:38 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:38 | D | sum error = [ 13.4752, 14.2793, 15.1237, 16.0116, 16.9432] +24-11-19 20:35:38 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 20:35:38 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:38 | D | sum error = [ 17.9208, 18.9457, 20.0174, 21.1428, 22.3194] +24-11-19 20:35:38 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 20:35:38 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:38 | D | sum error = [ 23.5493, 24.8353, 26.1801, 27.5867, 29.0554] +24-11-19 20:35:38 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 20:35:38 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:38 | D | sum error = [ 30.5848, 32.1808, 33.8453, 35.5787, 37.3816] +24-11-19 20:35:38 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 20:35:38 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:38 | D | sum error = [ 39.2551, 41.2009, 43.2230, 45.3205, 47.4976] +24-11-19 20:35:38 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 20:35:38 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:38 | D | sum error = [ 49.7539, 52.0928, 54.5133, 57.0188, 59.6093] +24-11-19 20:35:38 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 20:35:38 | D | + error = [1.0431] +24-11-19 20:35:38 | D | - Quantizing model.layers.24.self_attn.q_proj.weight +24-11-19 20:35:39 | D | - Quantizing model.layers.24.self_attn.k_proj.weight +24-11-19 20:35:40 | D | - Quantizing model.layers.24.self_attn.v_proj.weight +24-11-19 20:35:41 | D | - Quantizing model.layers.24.self_attn.o_proj.weight +24-11-19 20:35:42 | D | - Quantizing model.layers.24.mlp.up_proj.weight +24-11-19 20:35:42 | D | - Quantizing model.layers.24.mlp.gate_proj.weight +24-11-19 20:35:43 | D | - Quantizing model.layers.24.mlp.down_proj.weight +24-11-19 20:35:53 | D | - Quantizing layer model.layers.25 +24-11-19 20:35:53 | D | - Calibrating model.layers.25.self_attn.q_proj.weight +24-11-19 20:35:53 | D | + w: sint8 +24-11-19 20:35:53 | D | + x: None +24-11-19 20:35:53 | D | + y: None +24-11-19 20:35:53 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:35:53 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:53 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:53 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:53 | D | - range ratio = [ 1.0000] +24-11-19 20:35:53 | D | sum error = [ 5.2793] +24-11-19 20:35:53 | D | best error = [ 5.2793] +24-11-19 20:36:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:05 | D | sum error = [ 5.4052, 5.4530, 5.5010, 5.5556, 5.8852] +24-11-19 20:36:05 | D | best error = [ 5.2793, 5.2793, 5.2793, 5.2793, 5.2793] +24-11-19 20:36:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:05 | D | sum error = [ 5.6707, 5.7953, 6.2794, 6.6994, 7.2264] +24-11-19 20:36:05 | D | best error = [ 5.2793, 5.2793, 5.2793, 5.2793, 5.2793] +24-11-19 20:36:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:05 | D | sum error = [ 7.9449, 8.4919, 9.2888, 9.9470, 10.6512] +24-11-19 20:36:05 | D | best error = [ 5.2793, 5.2793, 5.2793, 5.2793, 5.2793] +24-11-19 20:36:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:05 | D | sum error = [ 12.0372, 12.9655, 14.2642, 15.4322, 17.3180] +24-11-19 20:36:05 | D | best error = [ 5.2793, 5.2793, 5.2793, 5.2793, 5.2793] +24-11-19 20:36:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:05 | D | sum error = [ 19.1835, 20.1772, 22.0464, 23.8961, 24.9870] +24-11-19 20:36:05 | D | best error = [ 5.2793, 5.2793, 5.2793, 5.2793, 5.2793] +24-11-19 20:36:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:05 | D | sum error = [ 26.9434, 29.9115, 32.4241, 34.9794, 37.7414] +24-11-19 20:36:05 | D | best error = [ 5.2793, 5.2793, 5.2793, 5.2793, 5.2793] +24-11-19 20:36:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:05 | D | sum error = [ 40.7668, 44.1892, 47.5912, 52.0545, 56.2014] +24-11-19 20:36:05 | D | best error = [ 5.2793, 5.2793, 5.2793, 5.2793, 5.2793] +24-11-19 20:36:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:05 | D | sum error = [ 60.8466, 65.6327, 70.6781, 76.1807, 82.4010] +24-11-19 20:36:05 | D | best error = [ 5.2793, 5.2793, 5.2793, 5.2793, 5.2793] +24-11-19 20:36:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:05 | D | sum error = [ 89.2022, 96.2069, 103.2674, 111.1934, 119.5281] +24-11-19 20:36:05 | D | best error = [ 5.2793, 5.2793, 5.2793, 5.2793, 5.2793] +24-11-19 20:36:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:05 | D | sum error = [ 128.7625, 138.3743, 148.6361, 159.6875, 171.8828] +24-11-19 20:36:05 | D | best error = [ 5.2793, 5.2793, 5.2793, 5.2793, 5.2793] +24-11-19 20:36:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:05 | D | sum error = [ 184.1835, 197.1765, 211.5458, 227.0367, 243.1344] +24-11-19 20:36:05 | D | best error = [ 5.2793, 5.2793, 5.2793, 5.2793, 5.2793] +24-11-19 20:36:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:05 | D | sum error = [ 260.0735, 279.0599, 298.7621, 321.5251, 345.0803] +24-11-19 20:36:05 | D | best error = [ 5.2793, 5.2793, 5.2793, 5.2793, 5.2793] +24-11-19 20:36:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:05 | D | sum error = [ 370.7360, 398.7577, 428.3111, 460.3243, 495.4743] +24-11-19 20:36:05 | D | best error = [ 5.2793, 5.2793, 5.2793, 5.2793, 5.2793] +24-11-19 20:36:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:05 | D | sum error = [ 533.2490, 575.5307, 620.4447, 669.8929, 723.3178] +24-11-19 20:36:05 | D | best error = [ 5.2793, 5.2793, 5.2793, 5.2793, 5.2793] +24-11-19 20:36:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:05 | D | sum error = [ 781.8100, 844.7304, 912.8730, 986.3465, 1065.3599] +24-11-19 20:36:05 | D | best error = [ 5.2793, 5.2793, 5.2793, 5.2793, 5.2793] +24-11-19 20:36:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:05 | D | sum error = [ 1150.5494, 1241.9153, 1338.5109, 1439.8213, 1545.5583] +24-11-19 20:36:05 | D | best error = [ 5.2793, 5.2793, 5.2793, 5.2793, 5.2793] +24-11-19 20:36:05 | D | + error = [5.2793] +24-11-19 20:36:05 | D | - Calibrating model.layers.25.self_attn.k_proj.weight +24-11-19 20:36:05 | D | + w: sint8 +24-11-19 20:36:05 | D | + x: None +24-11-19 20:36:05 | D | + y: None +24-11-19 20:36:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:36:05 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:36:05 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:36:05 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:36:05 | D | - range ratio = [ 1.0000] +24-11-19 20:36:05 | D | sum error = [ 6.6442] +24-11-19 20:36:05 | D | best error = [ 6.6442] +24-11-19 20:36:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:17 | D | sum error = [ 6.2673, 5.8868, 5.7432, 7.6735, 6.1284] +24-11-19 20:36:17 | D | best error = [ 6.2673, 5.8868, 5.7432, 5.7432, 5.7432] +24-11-19 20:36:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:17 | D | sum error = [ 6.8569, 6.6084, 7.1543, 7.1136, 8.7407] +24-11-19 20:36:17 | D | best error = [ 5.7432, 5.7432, 5.7432, 5.7432, 5.7432] +24-11-19 20:36:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:17 | D | sum error = [ 9.1052, 10.1856, 9.5464, 12.1353, 10.1460] +24-11-19 20:36:17 | D | best error = [ 5.7432, 5.7432, 5.7432, 5.7432, 5.7432] +24-11-19 20:36:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:17 | D | sum error = [ 13.5302, 11.7071, 14.1461, 14.3108, 16.3332] +24-11-19 20:36:17 | D | best error = [ 5.7432, 5.7432, 5.7432, 5.7432, 5.7432] +24-11-19 20:36:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:17 | D | sum error = [ 16.9427, 19.2983, 20.4343, 22.7227, 23.8204] +24-11-19 20:36:17 | D | best error = [ 5.7432, 5.7432, 5.7432, 5.7432, 5.7432] +24-11-19 20:36:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:17 | D | sum error = [ 26.3708, 27.0732, 30.2705, 32.2617, 35.3477] +24-11-19 20:36:17 | D | best error = [ 5.7432, 5.7432, 5.7432, 5.7432, 5.7432] +24-11-19 20:36:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:17 | D | sum error = [ 38.9894, 41.3831, 42.3090, 45.7597, 50.5663] +24-11-19 20:36:17 | D | best error = [ 5.7432, 5.7432, 5.7432, 5.7432, 5.7432] +24-11-19 20:36:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:17 | D | sum error = [ 54.7001, 57.3326, 60.3722, 64.6543, 70.9790] +24-11-19 20:36:17 | D | best error = [ 5.7432, 5.7432, 5.7432, 5.7432, 5.7432] +24-11-19 20:36:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:17 | D | sum error = [ 73.8640, 79.0314, 83.7022, 88.9777, 95.0605] +24-11-19 20:36:17 | D | best error = [ 5.7432, 5.7432, 5.7432, 5.7432, 5.7432] +24-11-19 20:36:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:17 | D | sum error = [ 100.5330, 106.6576, 113.2362, 120.8783, 128.6082] +24-11-19 20:36:17 | D | best error = [ 5.7432, 5.7432, 5.7432, 5.7432, 5.7432] +24-11-19 20:36:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:17 | D | sum error = [ 137.5118, 147.7150, 158.0598, 169.2047, 181.3241] +24-11-19 20:36:17 | D | best error = [ 5.7432, 5.7432, 5.7432, 5.7432, 5.7432] +24-11-19 20:36:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:17 | D | sum error = [ 194.7607, 210.2296, 225.6952, 244.4818, 263.6794] +24-11-19 20:36:17 | D | best error = [ 5.7432, 5.7432, 5.7432, 5.7432, 5.7432] +24-11-19 20:36:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:17 | D | sum error = [ 285.3429, 309.8531, 335.9484, 365.5333, 394.7217] +24-11-19 20:36:17 | D | best error = [ 5.7432, 5.7432, 5.7432, 5.7432, 5.7432] +24-11-19 20:36:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:17 | D | sum error = [ 428.8909, 466.3079, 507.1481, 552.1072, 599.8385] +24-11-19 20:36:17 | D | best error = [ 5.7432, 5.7432, 5.7432, 5.7432, 5.7432] +24-11-19 20:36:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:17 | D | sum error = [ 653.4158, 713.1997, 777.8506, 847.9435, 926.9061] +24-11-19 20:36:17 | D | best error = [ 5.7432, 5.7432, 5.7432, 5.7432, 5.7432] +24-11-19 20:36:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:17 | D | sum error = [ 1008.5564, 1100.8086, 1198.7273, 1302.4205, 1412.3127] +24-11-19 20:36:17 | D | best error = [ 5.7432, 5.7432, 5.7432, 5.7432, 5.7432] +24-11-19 20:36:17 | D | + error = [5.7432] +24-11-19 20:36:17 | D | - Calibrating model.layers.25.self_attn.v_proj.weight +24-11-19 20:36:17 | D | + w: sint8 +24-11-19 20:36:17 | D | + x: None +24-11-19 20:36:17 | D | + y: None +24-11-19 20:36:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:17 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:36:17 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:36:17 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:36:17 | D | - range ratio = [ 1.0000] +24-11-19 20:36:17 | D | sum error = [ 2.4342] +24-11-19 20:36:17 | D | best error = [ 2.4342] +24-11-19 20:36:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:17 | D | sum error = [ 2.4354, 2.4230, 2.4442, 2.4452, 2.4877] +24-11-19 20:36:17 | D | best error = [ 2.2238, 2.1407, 2.1031, 2.0834, 2.0705] +24-11-19 20:36:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:17 | D | sum error = [ 2.5592, 2.6553, 2.7348, 2.8483, 3.0242] +24-11-19 20:36:17 | D | best error = [ 2.0628, 2.0597, 2.0585, 2.0583, 2.0583] +24-11-19 20:36:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:17 | D | sum error = [ 3.2089, 3.4212, 3.6363, 3.8721, 4.1415] +24-11-19 20:36:17 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:36:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:17 | D | sum error = [ 4.4388, 4.7773, 5.0742, 5.4516, 5.8664] +24-11-19 20:36:17 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:36:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:17 | D | sum error = [ 6.2986, 6.7347, 7.1747, 7.6866, 8.1994] +24-11-19 20:36:17 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:36:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:17 | D | sum error = [ 8.8025, 9.3849, 10.0040, 10.6627, 11.3672] +24-11-19 20:36:17 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:36:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:17 | D | sum error = [ 12.0968, 12.8923, 13.6822, 14.5535, 15.4850] +24-11-19 20:36:17 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:36:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:17 | D | sum error = [ 16.4480, 17.4576, 18.5354, 19.6379, 20.8234] +24-11-19 20:36:17 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:36:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:17 | D | sum error = [ 22.0409, 23.3600, 24.7010, 26.1245, 27.6190] +24-11-19 20:36:17 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:36:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:17 | D | sum error = [ 29.1940, 30.8288, 32.5319, 34.3024, 36.1733] +24-11-19 20:36:17 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:36:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:17 | D | sum error = [ 38.1282, 40.1644, 42.2688, 44.4926, 46.7914] +24-11-19 20:36:17 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:36:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:17 | D | sum error = [ 49.1989, 51.7245, 54.3243, 57.0414, 59.8794] +24-11-19 20:36:17 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:36:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:17 | D | sum error = [ 62.8051, 65.8535, 69.0113, 72.2829, 75.6784] +24-11-19 20:36:17 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:36:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:17 | D | sum error = [ 79.2047, 82.8245, 86.5779, 90.4755, 94.4993] +24-11-19 20:36:17 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:36:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:17 | D | sum error = [ 98.6663, 102.9635, 107.3974, 111.9674, 116.6582] +24-11-19 20:36:17 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:36:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:17 | D | sum error = [ 121.5003, 126.4887, 131.6159, 136.8743, 142.2841] +24-11-19 20:36:17 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:36:17 | D | + error = [2.0583] +24-11-19 20:36:17 | D | - Calibrating model.layers.25.self_attn.o_proj.weight +24-11-19 20:36:17 | D | + w: sint8 +24-11-19 20:36:17 | D | + x: None +24-11-19 20:36:17 | D | + y: None +24-11-19 20:36:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:17 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:36:17 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:36:18 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:36:18 | D | - range ratio = [ 1.0000] +24-11-19 20:36:18 | D | sum error = [ 0.5030] +24-11-19 20:36:18 | D | best error = [ 0.5030] +24-11-19 20:36:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:18 | D | sum error = [ 0.4973, 0.4957, 0.4937, 0.4947, 0.4968] +24-11-19 20:36:18 | D | best error = [ 0.4707, 0.4561, 0.4469, 0.4406, 0.4360] +24-11-19 20:36:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:18 | D | sum error = [ 0.5016, 0.5098, 0.5213, 0.5342, 0.5522] +24-11-19 20:36:18 | D | best error = [ 0.4322, 0.4299, 0.4282, 0.4268, 0.4259] +24-11-19 20:36:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:18 | D | sum error = [ 0.5712, 0.5956, 0.6223, 0.6546, 0.6869] +24-11-19 20:36:18 | D | best error = [ 0.4254, 0.4249, 0.4245, 0.4242, 0.4239] +24-11-19 20:36:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:18 | D | sum error = [ 0.7272, 0.7704, 0.8175, 0.8695, 0.9242] +24-11-19 20:36:18 | D | best error = [ 0.4238, 0.4237, 0.4237, 0.4236, 0.4236] +24-11-19 20:36:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:18 | D | sum error = [ 0.9858, 1.0494, 1.1193, 1.1937, 1.2730] +24-11-19 20:36:18 | D | best error = [ 0.4236, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:36:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:18 | D | sum error = [ 1.3589, 1.4489, 1.5441, 1.6460, 1.7544] +24-11-19 20:36:18 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:36:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:18 | D | sum error = [ 1.8707, 1.9914, 2.1217, 2.2579, 2.4027] +24-11-19 20:36:18 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:36:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:18 | D | sum error = [ 2.5549, 2.7181, 2.8889, 3.0693, 3.2592] +24-11-19 20:36:18 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:36:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:18 | D | sum error = [ 3.4598, 3.6721, 3.8950, 4.1297, 4.3784] +24-11-19 20:36:18 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:36:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:18 | D | sum error = [ 4.6379, 4.9122, 5.2002, 5.5032, 5.8201] +24-11-19 20:36:18 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:36:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:18 | D | sum error = [ 6.1551, 6.5057, 6.8744, 7.2611, 7.6652] +24-11-19 20:36:18 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:36:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:18 | D | sum error = [ 8.0896, 8.5359, 9.0032, 9.4925, 10.0036] +24-11-19 20:36:18 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:36:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:18 | D | sum error = [ 10.5395, 11.0998, 11.6853, 12.2980, 12.9379] +24-11-19 20:36:18 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:36:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:18 | D | sum error = [ 13.6057, 14.3019, 15.0294, 15.7873, 16.5745] +24-11-19 20:36:18 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:36:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:18 | D | sum error = [ 17.3946, 18.2476, 19.1337, 20.0552, 21.0121] +24-11-19 20:36:18 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:36:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:18 | D | sum error = [ 22.0058, 23.0342, 24.0997, 25.2017, 26.3426] +24-11-19 20:36:18 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:36:18 | D | + error = [0.4235] +24-11-19 20:36:18 | D | - Calibrating model.layers.25.mlp.up_proj.weight +24-11-19 20:36:18 | D | + w: sint8 +24-11-19 20:36:18 | D | + x: None +24-11-19 20:36:18 | D | + y: None +24-11-19 20:36:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:18 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:36:18 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:36:18 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:36:18 | D | - range ratio = [ 1.0000] +24-11-19 20:36:18 | D | sum error = [ 8.1411] +24-11-19 20:36:18 | D | best error = [ 8.1411] +24-11-19 20:36:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:20 | D | sum error = [ 8.0783, 8.0703, 8.0803, 8.2029, 8.3501] +24-11-19 20:36:20 | D | best error = [ 7.3762, 7.1028, 6.9632, 6.8861, 6.8430] +24-11-19 20:36:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:20 | D | sum error = [ 8.5379, 8.8465, 9.1937, 9.6072, 10.1128] +24-11-19 20:36:20 | D | best error = [ 6.8227, 6.8130, 6.8089, 6.8075, 6.8073] +24-11-19 20:36:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:20 | D | sum error = [ 10.7031, 11.3543, 12.0955, 12.9233, 13.7671] +24-11-19 20:36:20 | D | best error = [ 6.8072, 6.8072, 6.8072, 6.8072, 6.8072] +24-11-19 20:36:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:20 | D | sum error = [ 14.7440, 15.7932, 16.9369, 18.1413, 19.4303] +24-11-19 20:36:20 | D | best error = [ 6.8072, 6.8072, 6.8072, 6.8072, 6.8072] +24-11-19 20:36:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:20 | D | sum error = [ 20.7821, 22.2752, 23.8442, 25.5008, 27.2942] +24-11-19 20:36:20 | D | best error = [ 6.8072, 6.8072, 6.8072, 6.8072, 6.8072] +24-11-19 20:36:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:20 | D | sum error = [ 29.1353, 31.1271, 33.2101, 35.4317, 37.7379] +24-11-19 20:36:20 | D | best error = [ 6.8072, 6.8072, 6.8072, 6.8072, 6.8072] +24-11-19 20:36:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:20 | D | sum error = [ 40.1722, 42.7553, 45.4598, 48.2880, 51.2858] +24-11-19 20:36:20 | D | best error = [ 6.8072, 6.8072, 6.8072, 6.8072, 6.8072] +24-11-19 20:36:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:20 | D | sum error = [ 54.4491, 57.7462, 61.2063, 64.8318, 68.6207] +24-11-19 20:36:20 | D | best error = [ 6.8072, 6.8072, 6.8072, 6.8072, 6.8072] +24-11-19 20:36:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:20 | D | sum error = [ 72.6072, 76.7497, 81.0889, 85.6698, 90.4169] +24-11-19 20:36:20 | D | best error = [ 6.8072, 6.8072, 6.8072, 6.8072, 6.8072] +24-11-19 20:36:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:20 | D | sum error = [ 95.3920, 100.5926, 106.0103, 111.6516, 117.5321] +24-11-19 20:36:20 | D | best error = [ 6.8072, 6.8072, 6.8072, 6.8072, 6.8072] +24-11-19 20:36:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:20 | D | sum error = [ 123.6423, 129.9810, 136.5718, 143.4085, 150.5027] +24-11-19 20:36:20 | D | best error = [ 6.8072, 6.8072, 6.8072, 6.8072, 6.8072] +24-11-19 20:36:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:20 | D | sum error = [ 157.8653, 165.5026, 173.4202, 181.6336, 190.1338] +24-11-19 20:36:20 | D | best error = [ 6.8072, 6.8072, 6.8072, 6.8072, 6.8072] +24-11-19 20:36:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:20 | D | sum error = [ 198.9436, 208.0424, 217.4509, 227.1615, 237.1924] +24-11-19 20:36:20 | D | best error = [ 6.8072, 6.8072, 6.8072, 6.8072, 6.8072] +24-11-19 20:36:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:20 | D | sum error = [ 247.5478, 258.2224, 269.2180, 280.5562, 292.2142] +24-11-19 20:36:20 | D | best error = [ 6.8072, 6.8072, 6.8072, 6.8072, 6.8072] +24-11-19 20:36:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:20 | D | sum error = [ 304.2028, 316.5388, 329.2217, 342.2608, 355.6476] +24-11-19 20:36:20 | D | best error = [ 6.8072, 6.8072, 6.8072, 6.8072, 6.8072] +24-11-19 20:36:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:20 | D | sum error = [ 369.4200, 383.5583, 398.0658, 412.9678, 428.2541] +24-11-19 20:36:20 | D | best error = [ 6.8072, 6.8072, 6.8072, 6.8072, 6.8072] +24-11-19 20:36:20 | D | + error = [6.8072] +24-11-19 20:36:20 | D | - Calibrating model.layers.25.mlp.gate_proj.weight +24-11-19 20:36:20 | D | + w: sint8 +24-11-19 20:36:20 | D | + x: None +24-11-19 20:36:20 | D | + y: None +24-11-19 20:36:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:20 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:36:20 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:36:20 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:36:20 | D | - range ratio = [ 1.0000] +24-11-19 20:36:20 | D | sum error = [ 10.9390] +24-11-19 20:36:20 | D | best error = [ 10.9390] +24-11-19 20:36:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:21 | D | sum error = [ 10.8712, 10.8533, 10.8997, 11.0190, 11.2059] +24-11-19 20:36:21 | D | best error = [ 9.9272, 9.5581, 9.3783, 9.2728, 9.2161] +24-11-19 20:36:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:21 | D | sum error = [ 11.5399, 11.8872, 12.4038, 13.0102, 13.6877] +24-11-19 20:36:21 | D | best error = [ 9.1864, 9.1719, 9.1669, 9.1649, 9.1645] +24-11-19 20:36:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:21 | D | sum error = [ 14.4634, 15.3675, 16.4001, 17.5093, 18.6912] +24-11-19 20:36:21 | D | best error = [ 9.1644, 9.1643, 9.1643, 9.1643, 9.1643] +24-11-19 20:36:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:21 | D | sum error = [ 20.0396, 21.4645, 22.9807, 24.6723, 26.4523] +24-11-19 20:36:21 | D | best error = [ 9.1643, 9.1643, 9.1643, 9.1643, 9.1643] +24-11-19 20:36:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:21 | D | sum error = [ 28.3203, 30.3772, 32.5283, 34.8517, 37.2385] +24-11-19 20:36:21 | D | best error = [ 9.1643, 9.1643, 9.1643, 9.1643, 9.1643] +24-11-19 20:36:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:21 | D | sum error = [ 39.8812, 42.5737, 45.5213, 48.5665, 51.7863] +24-11-19 20:36:21 | D | best error = [ 9.1643, 9.1643, 9.1643, 9.1643, 9.1643] +24-11-19 20:36:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:21 | D | sum error = [ 55.2409, 58.8787, 62.7753, 66.8268, 71.1313] +24-11-19 20:36:21 | D | best error = [ 9.1643, 9.1643, 9.1643, 9.1643, 9.1643] +24-11-19 20:36:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:21 | D | sum error = [ 75.6155, 80.4513, 85.4834, 90.7508, 96.3126] +24-11-19 20:36:21 | D | best error = [ 9.1643, 9.1643, 9.1643, 9.1643, 9.1643] +24-11-19 20:36:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:21 | D | sum error = [ 102.2015, 108.3896, 114.8494, 121.6867, 128.8303] +24-11-19 20:36:21 | D | best error = [ 9.1643, 9.1643, 9.1643, 9.1643, 9.1643] +24-11-19 20:36:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:21 | D | sum error = [ 136.3788, 144.2860, 152.5712, 161.2804, 170.4649] +24-11-19 20:36:21 | D | best error = [ 9.1643, 9.1643, 9.1643, 9.1643, 9.1643] +24-11-19 20:36:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:21 | D | sum error = [ 180.0038, 190.0449, 200.5672, 211.5513, 223.1061] +24-11-19 20:36:21 | D | best error = [ 9.1643, 9.1643, 9.1643, 9.1643, 9.1643] +24-11-19 20:36:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:21 | D | sum error = [ 235.1202, 247.7721, 260.9406, 274.6997, 289.1043] +24-11-19 20:36:21 | D | best error = [ 9.1643, 9.1643, 9.1643, 9.1643, 9.1643] +24-11-19 20:36:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:21 | D | sum error = [ 304.1686, 319.8643, 336.2271, 353.3111, 371.1064] +24-11-19 20:36:21 | D | best error = [ 9.1643, 9.1643, 9.1643, 9.1643, 9.1643] +24-11-19 20:36:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:21 | D | sum error = [ 389.6268, 408.8424, 428.8781, 449.7053, 471.3109] +24-11-19 20:36:21 | D | best error = [ 9.1643, 9.1643, 9.1643, 9.1643, 9.1643] +24-11-19 20:36:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:21 | D | sum error = [ 493.7512, 516.9855, 541.1051, 566.0095, 591.7496] +24-11-19 20:36:21 | D | best error = [ 9.1643, 9.1643, 9.1643, 9.1643, 9.1643] +24-11-19 20:36:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:21 | D | sum error = [ 618.3520, 645.8222, 674.1493, 703.3288, 733.3739] +24-11-19 20:36:21 | D | best error = [ 9.1643, 9.1643, 9.1643, 9.1643, 9.1643] +24-11-19 20:36:21 | D | + error = [9.1643] +24-11-19 20:36:21 | D | - Calibrating model.layers.25.mlp.down_proj.weight +24-11-19 20:36:21 | D | + w: sint8 +24-11-19 20:36:21 | D | + x: None +24-11-19 20:36:21 | D | + y: None +24-11-19 20:36:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:21 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:36:21 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:36:21 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:36:21 | D | - range ratio = [ 1.0000] +24-11-19 20:36:21 | D | sum error = [ 1.2567] +24-11-19 20:36:21 | D | best error = [ 1.2567] +24-11-19 20:36:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:23 | D | sum error = [ 1.2425, 1.2335, 1.2258, 1.2174, 1.2157] +24-11-19 20:36:23 | D | best error = [ 1.1996, 1.1737, 1.1562, 1.1430, 1.1319] +24-11-19 20:36:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:23 | D | sum error = [ 1.2156, 1.2193, 1.2244, 1.2385, 1.2572] +24-11-19 20:36:23 | D | best error = [ 1.1234, 1.1165, 1.1111, 1.1067, 1.1037] +24-11-19 20:36:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:23 | D | sum error = [ 1.2769, 1.3077, 1.3418, 1.3828, 1.4341] +24-11-19 20:36:23 | D | best error = [ 1.1016, 1.1001, 1.0992, 1.0984, 1.0976] +24-11-19 20:36:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:23 | D | sum error = [ 1.4955, 1.5604, 1.6349, 1.7236, 1.8224] +24-11-19 20:36:23 | D | best error = [ 1.0973, 1.0971, 1.0970, 1.0969, 1.0969] +24-11-19 20:36:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:23 | D | sum error = [ 1.9310, 2.0506, 2.1790, 2.3227, 2.4813] +24-11-19 20:36:23 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0968, 1.0968] +24-11-19 20:36:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:23 | D | sum error = [ 2.6467, 2.8320, 3.0310, 3.2444, 3.4717] +24-11-19 20:36:23 | D | best error = [ 1.0968, 1.0968, 1.0968, 1.0968, 1.0968] +24-11-19 20:36:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:23 | D | sum error = [ 3.7134, 3.9730, 4.2509, 4.5453, 4.8620] +24-11-19 20:36:23 | D | best error = [ 1.0968, 1.0968, 1.0968, 1.0968, 1.0968] +24-11-19 20:36:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:23 | D | sum error = [ 5.1958, 5.5514, 5.9295, 6.3300, 6.7550] +24-11-19 20:36:23 | D | best error = [ 1.0968, 1.0968, 1.0968, 1.0968, 1.0968] +24-11-19 20:36:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:23 | D | sum error = [ 7.2042, 7.6809, 8.1840, 8.7163, 9.2769] +24-11-19 20:36:23 | D | best error = [ 1.0968, 1.0968, 1.0968, 1.0968, 1.0968] +24-11-19 20:36:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:23 | D | sum error = [ 9.8737, 10.4989, 11.1606, 11.8560, 12.5894] +24-11-19 20:36:23 | D | best error = [ 1.0968, 1.0968, 1.0968, 1.0968, 1.0968] +24-11-19 20:36:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:23 | D | sum error = [ 13.3616, 14.1756, 15.0303, 15.9294, 16.8720] +24-11-19 20:36:23 | D | best error = [ 1.0968, 1.0968, 1.0968, 1.0968, 1.0968] +24-11-19 20:36:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:23 | D | sum error = [ 17.8622, 18.8981, 19.9861, 21.1246, 22.3175] +24-11-19 20:36:23 | D | best error = [ 1.0968, 1.0968, 1.0968, 1.0968, 1.0968] +24-11-19 20:36:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:23 | D | sum error = [ 23.5654, 24.8696, 26.2322, 27.6555, 29.1423] +24-11-19 20:36:23 | D | best error = [ 1.0968, 1.0968, 1.0968, 1.0968, 1.0968] +24-11-19 20:36:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:23 | D | sum error = [ 30.6919, 32.3055, 33.9863, 35.7380, 37.5584] +24-11-19 20:36:23 | D | best error = [ 1.0968, 1.0968, 1.0968, 1.0968, 1.0968] +24-11-19 20:36:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:23 | D | sum error = [ 39.4543, 41.4238, 43.4709, 45.5972, 47.8023] +24-11-19 20:36:23 | D | best error = [ 1.0968, 1.0968, 1.0968, 1.0968, 1.0968] +24-11-19 20:36:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:23 | D | sum error = [ 50.0892, 52.4600, 54.9130, 57.4514, 60.0763] +24-11-19 20:36:23 | D | best error = [ 1.0968, 1.0968, 1.0968, 1.0968, 1.0968] +24-11-19 20:36:23 | D | + error = [1.0968] +24-11-19 20:36:23 | D | - Quantizing model.layers.25.self_attn.q_proj.weight +24-11-19 20:36:28 | D | - Quantizing model.layers.25.self_attn.k_proj.weight +24-11-19 20:36:30 | D | - Quantizing model.layers.25.self_attn.v_proj.weight +24-11-19 20:36:31 | D | - Quantizing model.layers.25.self_attn.o_proj.weight +24-11-19 20:36:31 | D | - Quantizing model.layers.25.mlp.up_proj.weight +24-11-19 20:36:32 | D | - Quantizing model.layers.25.mlp.gate_proj.weight +24-11-19 20:36:33 | D | - Quantizing model.layers.25.mlp.down_proj.weight +24-11-19 20:36:43 | D | - Quantizing layer model.layers.26 +24-11-19 20:36:43 | D | - Calibrating model.layers.26.self_attn.q_proj.weight +24-11-19 20:36:43 | D | + w: sint8 +24-11-19 20:36:43 | D | + x: None +24-11-19 20:36:43 | D | + y: None +24-11-19 20:36:43 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:36:43 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:36:43 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:36:43 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:36:43 | D | - range ratio = [ 1.0000] +24-11-19 20:36:43 | D | sum error = [ 6.0636] +24-11-19 20:36:43 | D | best error = [ 6.0636] +24-11-19 20:36:55 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:55 | D | sum error = [ 6.1672, 5.7334, 5.9701, 6.1390, 6.0602] +24-11-19 20:36:55 | D | best error = [ 6.0636, 5.7334, 5.7334, 5.7334, 5.7334] +24-11-19 20:36:55 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:55 | D | sum error = [ 6.4926, 6.4961, 7.0657, 7.3591, 7.5284] +24-11-19 20:36:55 | D | best error = [ 5.7334, 5.7334, 5.7334, 5.7334, 5.7334] +24-11-19 20:36:55 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:55 | D | sum error = [ 8.1510, 8.9754, 9.2148, 9.9340, 10.6208] +24-11-19 20:36:55 | D | best error = [ 5.7334, 5.7334, 5.7334, 5.7334, 5.7334] +24-11-19 20:36:55 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:55 | D | sum error = [ 11.5674, 12.2556, 13.5920, 14.7521, 15.9400] +24-11-19 20:36:55 | D | best error = [ 5.7334, 5.7334, 5.7334, 5.7334, 5.7334] +24-11-19 20:36:55 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:55 | D | sum error = [ 17.3821, 18.8898, 20.3193, 21.9288, 23.8393] +24-11-19 20:36:55 | D | best error = [ 5.7334, 5.7334, 5.7334, 5.7334, 5.7334] +24-11-19 20:36:55 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:55 | D | sum error = [ 26.1751, 27.9567, 30.5789, 33.8425, 36.4869] +24-11-19 20:36:55 | D | best error = [ 5.7334, 5.7334, 5.7334, 5.7334, 5.7334] +24-11-19 20:36:55 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:55 | D | sum error = [ 39.6697, 42.7946, 47.2540, 51.1885, 55.4956] +24-11-19 20:36:55 | D | best error = [ 5.7334, 5.7334, 5.7334, 5.7334, 5.7334] +24-11-19 20:36:55 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:55 | D | sum error = [ 60.2219, 66.0741, 71.3166, 77.4139, 84.0810] +24-11-19 20:36:55 | D | best error = [ 5.7334, 5.7334, 5.7334, 5.7334, 5.7334] +24-11-19 20:36:55 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:55 | D | sum error = [ 90.7988, 98.8095, 107.3326, 116.1764, 125.5803] +24-11-19 20:36:55 | D | best error = [ 5.7334, 5.7334, 5.7334, 5.7334, 5.7334] +24-11-19 20:36:55 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:55 | D | sum error = [ 136.1782, 147.0499, 159.3425, 171.9777, 185.2919] +24-11-19 20:36:55 | D | best error = [ 5.7334, 5.7334, 5.7334, 5.7334, 5.7334] +24-11-19 20:36:55 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:55 | D | sum error = [ 199.6555, 215.2522, 231.0409, 248.6316, 267.1601] +24-11-19 20:36:55 | D | best error = [ 5.7334, 5.7334, 5.7334, 5.7334, 5.7334] +24-11-19 20:36:55 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:55 | D | sum error = [ 286.6109, 308.5110, 331.0881, 354.7902, 380.6224] +24-11-19 20:36:55 | D | best error = [ 5.7334, 5.7334, 5.7334, 5.7334, 5.7334] +24-11-19 20:36:55 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:55 | D | sum error = [ 408.0181, 437.5608, 468.0713, 501.1884, 536.1955] +24-11-19 20:36:55 | D | best error = [ 5.7334, 5.7334, 5.7334, 5.7334, 5.7334] +24-11-19 20:36:55 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:55 | D | sum error = [ 573.8196, 613.9185, 655.8800, 700.0666, 746.5133] +24-11-19 20:36:55 | D | best error = [ 5.7334, 5.7334, 5.7334, 5.7334, 5.7334] +24-11-19 20:36:55 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:55 | D | sum error = [ 796.5897, 848.9454, 903.9404, 961.2360, 1020.5653] +24-11-19 20:36:55 | D | best error = [ 5.7334, 5.7334, 5.7334, 5.7334, 5.7334] +24-11-19 20:36:55 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:55 | D | sum error = [ 1081.9797, 1144.7158, 1208.4810, 1272.6605, 1336.7329] +24-11-19 20:36:55 | D | best error = [ 5.7334, 5.7334, 5.7334, 5.7334, 5.7334] +24-11-19 20:36:55 | D | + error = [5.7334] +24-11-19 20:36:55 | D | - Calibrating model.layers.26.self_attn.k_proj.weight +24-11-19 20:36:55 | D | + w: sint8 +24-11-19 20:36:55 | D | + x: None +24-11-19 20:36:55 | D | + y: None +24-11-19 20:36:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:36:55 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:36:55 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:36:55 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:36:56 | D | - range ratio = [ 1.0000] +24-11-19 20:36:56 | D | sum error = [ 6.0944] +24-11-19 20:36:56 | D | best error = [ 6.0944] +24-11-19 20:37:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:07 | D | sum error = [ 5.8751, 6.6532, 6.7353, 6.7816, 5.5923] +24-11-19 20:37:07 | D | best error = [ 5.8751, 5.8751, 5.8751, 5.8751, 5.5923] +24-11-19 20:37:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:07 | D | sum error = [ 6.5041, 6.4767, 7.0936, 7.1702, 7.1104] +24-11-19 20:37:07 | D | best error = [ 5.5923, 5.5923, 5.5923, 5.5923, 5.5923] +24-11-19 20:37:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:07 | D | sum error = [ 7.8940, 9.4306, 11.3928, 9.8008, 10.7365] +24-11-19 20:37:07 | D | best error = [ 5.5923, 5.5923, 5.5923, 5.5923, 5.5923] +24-11-19 20:37:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:07 | D | sum error = [ 13.5134, 12.1967, 14.4119, 14.6298, 17.9734] +24-11-19 20:37:07 | D | best error = [ 5.5923, 5.5923, 5.5923, 5.5923, 5.5923] +24-11-19 20:37:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:07 | D | sum error = [ 18.1167, 18.7632, 19.2872, 21.3360, 23.2648] +24-11-19 20:37:07 | D | best error = [ 5.5923, 5.5923, 5.5923, 5.5923, 5.5923] +24-11-19 20:37:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:07 | D | sum error = [ 25.9394, 26.7463, 29.8144, 32.3387, 34.5091] +24-11-19 20:37:07 | D | best error = [ 5.5923, 5.5923, 5.5923, 5.5923, 5.5923] +24-11-19 20:37:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:07 | D | sum error = [ 37.8384, 40.8629, 44.3443, 46.4069, 50.9713] +24-11-19 20:37:07 | D | best error = [ 5.5923, 5.5923, 5.5923, 5.5923, 5.5923] +24-11-19 20:37:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:07 | D | sum error = [ 55.1321, 60.0046, 63.9785, 70.0077, 75.6225] +24-11-19 20:37:07 | D | best error = [ 5.5923, 5.5923, 5.5923, 5.5923, 5.5923] +24-11-19 20:37:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:07 | D | sum error = [ 81.5161, 86.6554, 95.7132, 101.1793, 111.3641] +24-11-19 20:37:07 | D | best error = [ 5.5923, 5.5923, 5.5923, 5.5923, 5.5923] +24-11-19 20:37:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:07 | D | sum error = [ 118.4374, 128.2726, 136.2122, 147.6746, 159.3164] +24-11-19 20:37:07 | D | best error = [ 5.5923, 5.5923, 5.5923, 5.5923, 5.5923] +24-11-19 20:37:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:07 | D | sum error = [ 170.6887, 183.7268, 197.6636, 213.2197, 229.5485] +24-11-19 20:37:07 | D | best error = [ 5.5923, 5.5923, 5.5923, 5.5923, 5.5923] +24-11-19 20:37:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:07 | D | sum error = [ 247.8767, 265.8228, 286.6352, 305.3243, 327.2324] +24-11-19 20:37:07 | D | best error = [ 5.5923, 5.5923, 5.5923, 5.5923, 5.5923] +24-11-19 20:37:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:07 | D | sum error = [ 351.9192, 376.3201, 402.8716, 433.1052, 463.8924] +24-11-19 20:37:07 | D | best error = [ 5.5923, 5.5923, 5.5923, 5.5923, 5.5923] +24-11-19 20:37:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:07 | D | sum error = [ 499.1391, 533.8193, 571.8994, 613.0752, 655.6431] +24-11-19 20:37:07 | D | best error = [ 5.5923, 5.5923, 5.5923, 5.5923, 5.5923] +24-11-19 20:37:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:07 | D | sum error = [ 701.1012, 749.7263, 802.9874, 856.3703, 914.7334] +24-11-19 20:37:07 | D | best error = [ 5.5923, 5.5923, 5.5923, 5.5923, 5.5923] +24-11-19 20:37:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:07 | D | sum error = [ 975.7769, 1040.0740, 1105.8758, 1176.1223, 1244.4840] +24-11-19 20:37:07 | D | best error = [ 5.5923, 5.5923, 5.5923, 5.5923, 5.5923] +24-11-19 20:37:07 | D | + error = [5.5923] +24-11-19 20:37:07 | D | - Calibrating model.layers.26.self_attn.v_proj.weight +24-11-19 20:37:07 | D | + w: sint8 +24-11-19 20:37:07 | D | + x: None +24-11-19 20:37:07 | D | + y: None +24-11-19 20:37:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:07 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:08 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:08 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:08 | D | - range ratio = [ 1.0000] +24-11-19 20:37:08 | D | sum error = [ 2.4248] +24-11-19 20:37:08 | D | best error = [ 2.4248] +24-11-19 20:37:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:08 | D | sum error = [ 2.4027, 2.3860, 2.3805, 2.4439, 2.4702] +24-11-19 20:37:08 | D | best error = [ 2.1890, 2.1096, 2.0655, 2.0439, 2.0305] +24-11-19 20:37:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:08 | D | sum error = [ 2.5183, 2.6041, 2.7201, 2.8823, 3.0012] +24-11-19 20:37:08 | D | best error = [ 2.0217, 2.0192, 2.0177, 2.0170, 2.0169] +24-11-19 20:37:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:08 | D | sum error = [ 3.1473, 3.3889, 3.6178, 3.8172, 4.1185] +24-11-19 20:37:08 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:37:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:08 | D | sum error = [ 4.3624, 4.6830, 5.0142, 5.3881, 5.7596] +24-11-19 20:37:08 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:37:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:08 | D | sum error = [ 6.1458, 6.6017, 7.0412, 7.5298, 8.0439] +24-11-19 20:37:08 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:37:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:08 | D | sum error = [ 8.5916, 9.1705, 9.7760, 10.4123, 11.1028] +24-11-19 20:37:08 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:37:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:08 | D | sum error = [ 11.7860, 12.5277, 13.3886, 14.1812, 15.0888] +24-11-19 20:37:08 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:37:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:08 | D | sum error = [ 16.0147, 16.9862, 17.9852, 19.0754, 20.1664] +24-11-19 20:37:08 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:37:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:08 | D | sum error = [ 21.3656, 22.5483, 23.8772, 25.1962, 26.6120] +24-11-19 20:37:08 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:37:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:08 | D | sum error = [ 28.0866, 29.6175, 31.2250, 32.9023, 34.6398] +24-11-19 20:37:08 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:37:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:08 | D | sum error = [ 36.4516, 38.3265, 40.2833, 42.3019, 44.4397] +24-11-19 20:37:08 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:37:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:08 | D | sum error = [ 46.6341, 48.9183, 51.2745, 53.7248, 56.2670] +24-11-19 20:37:08 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:37:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:08 | D | sum error = [ 58.8851, 61.5864, 64.3782, 67.2615, 70.2331] +24-11-19 20:37:08 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:37:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:08 | D | sum error = [ 73.3054, 76.4554, 79.7188, 83.0880, 86.5351] +24-11-19 20:37:08 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:37:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:08 | D | sum error = [ 90.0948, 93.7639, 97.5337, 101.4211, 105.4135] +24-11-19 20:37:08 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:37:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:08 | D | sum error = [ 109.5293, 113.7371, 118.0573, 122.4693, 126.9941] +24-11-19 20:37:08 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:37:08 | D | + error = [2.0169] +24-11-19 20:37:08 | D | - Calibrating model.layers.26.self_attn.o_proj.weight +24-11-19 20:37:08 | D | + w: sint8 +24-11-19 20:37:08 | D | + x: None +24-11-19 20:37:08 | D | + y: None +24-11-19 20:37:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:08 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:08 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:08 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:08 | D | - range ratio = [ 1.0000] +24-11-19 20:37:08 | D | sum error = [ 0.5937] +24-11-19 20:37:08 | D | best error = [ 0.5937] +24-11-19 20:37:09 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:09 | D | sum error = [ 0.5904, 0.5886, 0.5892, 0.5923, 0.5979] +24-11-19 20:37:09 | D | best error = [ 0.5494, 0.5296, 0.5178, 0.5102, 0.5048] +24-11-19 20:37:09 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:09 | D | sum error = [ 0.6105, 0.6266, 0.6473, 0.6713, 0.7010] +24-11-19 20:37:09 | D | best error = [ 0.5013, 0.4988, 0.4971, 0.4959, 0.4951] +24-11-19 20:37:09 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:09 | D | sum error = [ 0.7332, 0.7704, 0.8133, 0.8621, 0.9171] +24-11-19 20:37:09 | D | best error = [ 0.4944, 0.4939, 0.4935, 0.4931, 0.4929] +24-11-19 20:37:09 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:09 | D | sum error = [ 0.9737, 1.0381, 1.1044, 1.1802, 1.2563] +24-11-19 20:37:09 | D | best error = [ 0.4927, 0.4927, 0.4926, 0.4925, 0.4925] +24-11-19 20:37:09 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:09 | D | sum error = [ 1.3408, 1.4306, 1.5291, 1.6321, 1.7405] +24-11-19 20:37:09 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 20:37:09 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:09 | D | sum error = [ 1.8540, 1.9762, 2.1063, 2.2427, 2.3891] +24-11-19 20:37:09 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 20:37:09 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:09 | D | sum error = [ 2.5408, 2.7007, 2.8687, 3.0501, 3.2381] +24-11-19 20:37:09 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 20:37:09 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:09 | D | sum error = [ 3.4348, 3.6433, 3.8634, 4.0936, 4.3402] +24-11-19 20:37:09 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 20:37:09 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:09 | D | sum error = [ 4.5972, 4.8666, 5.1487, 5.4443, 5.7568] +24-11-19 20:37:09 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 20:37:09 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:09 | D | sum error = [ 6.0812, 6.4250, 6.7818, 7.1578, 7.5485] +24-11-19 20:37:09 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 20:37:09 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:09 | D | sum error = [ 7.9608, 8.3909, 8.8407, 9.3083, 9.7985] +24-11-19 20:37:09 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 20:37:09 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:09 | D | sum error = [ 10.3115, 10.8495, 11.4090, 11.9934, 12.6044] +24-11-19 20:37:09 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 20:37:09 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:09 | D | sum error = [ 13.2416, 13.9029, 14.5926, 15.3143, 16.0635] +24-11-19 20:37:09 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 20:37:09 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:09 | D | sum error = [ 16.8424, 17.6530, 18.4941, 19.3694, 20.2783] +24-11-19 20:37:09 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 20:37:09 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:09 | D | sum error = [ 21.2212, 22.2010, 23.2159, 24.2685, 25.3558] +24-11-19 20:37:09 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 20:37:09 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:09 | D | sum error = [ 26.4805, 27.6452, 28.8482, 30.0916, 31.3745] +24-11-19 20:37:09 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 20:37:09 | D | + error = [0.4925] +24-11-19 20:37:09 | D | - Calibrating model.layers.26.mlp.up_proj.weight +24-11-19 20:37:09 | D | + w: sint8 +24-11-19 20:37:09 | D | + x: None +24-11-19 20:37:09 | D | + y: None +24-11-19 20:37:09 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:09 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:09 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:09 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:09 | D | - range ratio = [ 1.0000] +24-11-19 20:37:09 | D | sum error = [ 8.5111] +24-11-19 20:37:09 | D | best error = [ 8.5111] +24-11-19 20:37:10 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:10 | D | sum error = [ 8.4646, 8.4663, 8.4777, 8.5786, 8.7327] +24-11-19 20:37:10 | D | best error = [ 7.6646, 7.3562, 7.2006, 7.1141, 7.0648] +24-11-19 20:37:10 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:10 | D | sum error = [ 8.9637, 9.2936, 9.6227, 10.1189, 10.6314] +24-11-19 20:37:10 | D | best error = [ 7.0425, 7.0326, 7.0281, 7.0269, 7.0266] +24-11-19 20:37:10 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:10 | D | sum error = [ 11.2432, 11.9312, 12.7133, 13.5464, 14.4968] +24-11-19 20:37:10 | D | best error = [ 7.0265, 7.0265, 7.0265, 7.0265, 7.0265] +24-11-19 20:37:10 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:10 | D | sum error = [ 15.4790, 16.6051, 17.7986, 19.1017, 20.4345] +24-11-19 20:37:10 | D | best error = [ 7.0265, 7.0265, 7.0265, 7.0265, 7.0265] +24-11-19 20:37:10 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:10 | D | sum error = [ 21.9096, 23.4330, 25.0486, 26.8097, 28.6373] +24-11-19 20:37:10 | D | best error = [ 7.0265, 7.0265, 7.0265, 7.0265, 7.0265] +24-11-19 20:37:10 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:10 | D | sum error = [ 30.5706, 32.6485, 34.8091, 37.0909, 39.5129] +24-11-19 20:37:10 | D | best error = [ 7.0265, 7.0265, 7.0265, 7.0265, 7.0265] +24-11-19 20:37:10 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:10 | D | sum error = [ 42.0861, 44.7785, 47.6260, 50.6268, 53.7420] +24-11-19 20:37:10 | D | best error = [ 7.0265, 7.0265, 7.0265, 7.0265, 7.0265] +24-11-19 20:37:10 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:10 | D | sum error = [ 57.0056, 60.4643, 64.0969, 67.8836, 71.8587] +24-11-19 20:37:10 | D | best error = [ 7.0265, 7.0265, 7.0265, 7.0265, 7.0265] +24-11-19 20:37:10 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:10 | D | sum error = [ 76.0164, 80.3732, 84.9013, 89.6990, 94.6542] +24-11-19 20:37:10 | D | best error = [ 7.0265, 7.0265, 7.0265, 7.0265, 7.0265] +24-11-19 20:37:10 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:10 | D | sum error = [ 99.8570, 105.2964, 110.9683, 116.8442, 122.9857] +24-11-19 20:37:10 | D | best error = [ 7.0265, 7.0265, 7.0265, 7.0265, 7.0265] +24-11-19 20:37:10 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:10 | D | sum error = [ 129.3504, 136.0088, 142.9069, 150.0789, 157.5419] +24-11-19 20:37:10 | D | best error = [ 7.0265, 7.0265, 7.0265, 7.0265, 7.0265] +24-11-19 20:37:10 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:10 | D | sum error = [ 165.2497, 173.2663, 181.5486, 190.1423, 199.0428] +24-11-19 20:37:10 | D | best error = [ 7.0265, 7.0265, 7.0265, 7.0265, 7.0265] +24-11-19 20:37:10 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:10 | D | sum error = [ 208.2401, 217.7585, 227.6060, 237.7601, 248.2341] +24-11-19 20:37:10 | D | best error = [ 7.0265, 7.0265, 7.0265, 7.0265, 7.0265] +24-11-19 20:37:10 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:10 | D | sum error = [ 259.0577, 270.2144, 281.7094, 293.5600, 305.7406] +24-11-19 20:37:10 | D | best error = [ 7.0265, 7.0265, 7.0265, 7.0265, 7.0265] +24-11-19 20:37:10 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:10 | D | sum error = [ 318.2706, 331.2005, 344.4928, 358.1569, 372.2040] +24-11-19 20:37:10 | D | best error = [ 7.0265, 7.0265, 7.0265, 7.0265, 7.0265] +24-11-19 20:37:10 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:10 | D | sum error = [ 386.6226, 401.4358, 416.6362, 432.2223, 448.2336] +24-11-19 20:37:10 | D | best error = [ 7.0265, 7.0265, 7.0265, 7.0265, 7.0265] +24-11-19 20:37:10 | D | + error = [7.0265] +24-11-19 20:37:10 | D | - Calibrating model.layers.26.mlp.gate_proj.weight +24-11-19 20:37:10 | D | + w: sint8 +24-11-19 20:37:10 | D | + x: None +24-11-19 20:37:10 | D | + y: None +24-11-19 20:37:10 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:10 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:10 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:10 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:10 | D | - range ratio = [ 1.0000] +24-11-19 20:37:10 | D | sum error = [ 11.4901] +24-11-19 20:37:10 | D | best error = [ 11.4901] +24-11-19 20:37:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:12 | D | sum error = [ 11.3943, 11.3914, 11.4389, 11.5472, 11.7257] +24-11-19 20:37:12 | D | best error = [ 10.3060, 9.9039, 9.7024, 9.5831, 9.5155] +24-11-19 20:37:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:12 | D | sum error = [ 12.0932, 12.5050, 12.9553, 13.5919, 14.3241] +24-11-19 20:37:12 | D | best error = [ 9.4842, 9.4703, 9.4640, 9.4621, 9.4617] +24-11-19 20:37:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:12 | D | sum error = [ 15.1528, 16.0658, 17.0950, 18.2938, 19.5197] +24-11-19 20:37:12 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:37:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:12 | D | sum error = [ 20.9230, 22.3676, 23.9590, 25.6656, 27.5285] +24-11-19 20:37:12 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:37:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:12 | D | sum error = [ 29.4930, 31.5972, 33.8326, 36.1941, 38.7600] +24-11-19 20:37:12 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:37:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:12 | D | sum error = [ 41.4292, 44.2761, 47.3070, 50.5189, 53.9300] +24-11-19 20:37:12 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:37:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:12 | D | sum error = [ 57.4770, 61.2778, 65.3475, 69.5290, 74.0566] +24-11-19 20:37:12 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:37:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:12 | D | sum error = [ 78.7958, 83.8376, 89.1147, 94.7148, 100.5972] +24-11-19 20:37:12 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:37:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:12 | D | sum error = [ 106.8000, 113.3106, 120.2056, 127.4742, 135.0939] +24-11-19 20:37:12 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:37:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:12 | D | sum error = [ 143.1075, 151.5226, 160.3808, 169.7008, 179.4745] +24-11-19 20:37:12 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:37:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:12 | D | sum error = [ 189.7316, 200.5061, 211.8069, 223.6809, 236.0894] +24-11-19 20:37:12 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:37:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:12 | D | sum error = [ 249.1414, 262.8259, 277.1260, 292.0470, 307.6336] +24-11-19 20:37:12 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:37:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:12 | D | sum error = [ 323.9574, 340.9910, 358.6836, 377.2173, 396.4778] +24-11-19 20:37:12 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:37:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:12 | D | sum error = [ 416.5613, 437.4943, 459.2305, 481.8325, 505.3283] +24-11-19 20:37:12 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:37:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:12 | D | sum error = [ 529.7025, 554.9072, 581.0742, 608.1509, 636.2202] +24-11-19 20:37:12 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:37:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:12 | D | sum error = [ 665.2053, 695.1502, 726.0897, 758.0482, 790.9153] +24-11-19 20:37:12 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:37:12 | D | + error = [9.4615] +24-11-19 20:37:12 | D | - Calibrating model.layers.26.mlp.down_proj.weight +24-11-19 20:37:12 | D | + w: sint8 +24-11-19 20:37:12 | D | + x: None +24-11-19 20:37:12 | D | + y: None +24-11-19 20:37:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:12 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:12 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:12 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:12 | D | - range ratio = [ 1.0000] +24-11-19 20:37:12 | D | sum error = [ 1.3492] +24-11-19 20:37:12 | D | best error = [ 1.3492] +24-11-19 20:37:13 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:13 | D | sum error = [ 1.3382, 1.3239, 1.3171, 1.3114, 1.3057] +24-11-19 20:37:13 | D | best error = [ 1.2919, 1.2619, 1.2426, 1.2283, 1.2166] +24-11-19 20:37:13 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:13 | D | sum error = [ 1.3047, 1.3119, 1.3168, 1.3303, 1.3474] +24-11-19 20:37:13 | D | best error = [ 1.2072, 1.2004, 1.1949, 1.1909, 1.1880] +24-11-19 20:37:13 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:13 | D | sum error = [ 1.3742, 1.4017, 1.4397, 1.4830, 1.5367] +24-11-19 20:37:13 | D | best error = [ 1.1858, 1.1841, 1.1828, 1.1820, 1.1815] +24-11-19 20:37:13 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:13 | D | sum error = [ 1.5985, 1.6693, 1.7515, 1.8444, 1.9460] +24-11-19 20:37:13 | D | best error = [ 1.1811, 1.1808, 1.1807, 1.1807, 1.1806] +24-11-19 20:37:13 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:13 | D | sum error = [ 2.0596, 2.1841, 2.3228, 2.4739, 2.6371] +24-11-19 20:37:13 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 20:37:13 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:13 | D | sum error = [ 2.8148, 3.0064, 3.2101, 3.4354, 3.6740] +24-11-19 20:37:13 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 20:37:13 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:13 | D | sum error = [ 3.9281, 4.2026, 4.4962, 4.8065, 5.1398] +24-11-19 20:37:13 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 20:37:13 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:13 | D | sum error = [ 5.4948, 5.8731, 6.2716, 6.6944, 7.1465] +24-11-19 20:37:13 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 20:37:13 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:13 | D | sum error = [ 7.6254, 8.1320, 8.6691, 9.2374, 9.8361] +24-11-19 20:37:13 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 20:37:13 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:13 | D | sum error = [ 10.4696, 11.1395, 11.8459, 12.5903, 13.3731] +24-11-19 20:37:13 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 20:37:13 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:13 | D | sum error = [ 14.1981, 15.0672, 15.9829, 16.9437, 17.9533] +24-11-19 20:37:13 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 20:37:13 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:13 | D | sum error = [ 19.0132, 20.1249, 21.2928, 22.5157, 23.7978] +24-11-19 20:37:13 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 20:37:13 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:13 | D | sum error = [ 25.1363, 26.5379, 28.0006, 29.5311, 31.1303] +24-11-19 20:37:13 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 20:37:13 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:13 | D | sum error = [ 32.7950, 34.5324, 36.3424, 38.2280, 40.1899] +24-11-19 20:37:13 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 20:37:13 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:13 | D | sum error = [ 42.2299, 44.3516, 46.5530, 48.8384, 51.2096] +24-11-19 20:37:13 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 20:37:13 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:13 | D | sum error = [ 53.6676, 56.2156, 58.8522, 61.5801, 64.4016] +24-11-19 20:37:13 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 20:37:13 | D | + error = [1.1806] +24-11-19 20:37:13 | D | - Quantizing model.layers.26.self_attn.q_proj.weight +24-11-19 20:37:16 | D | - Quantizing model.layers.26.self_attn.k_proj.weight +24-11-19 20:37:19 | D | - Quantizing model.layers.26.self_attn.v_proj.weight +24-11-19 20:37:22 | D | - Quantizing model.layers.26.self_attn.o_proj.weight +24-11-19 20:37:25 | D | - Quantizing model.layers.26.mlp.up_proj.weight +24-11-19 20:37:26 | D | - Quantizing model.layers.26.mlp.gate_proj.weight +24-11-19 20:37:27 | D | - Quantizing model.layers.26.mlp.down_proj.weight +24-11-19 20:37:37 | D | - Quantizing layer model.layers.27 +24-11-19 20:37:37 | D | - Calibrating model.layers.27.self_attn.q_proj.weight +24-11-19 20:37:37 | D | + w: sint8 +24-11-19 20:37:37 | D | + x: None +24-11-19 20:37:37 | D | + y: None +24-11-19 20:37:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:37:37 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:37 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:37 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:37 | D | - range ratio = [ 1.0000] +24-11-19 20:37:37 | D | sum error = [ 7.3092] +24-11-19 20:37:37 | D | best error = [ 7.3092] +24-11-19 20:37:49 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:49 | D | sum error = [ 7.2774, 7.1991, 7.1305, 7.4447, 7.6212] +24-11-19 20:37:49 | D | best error = [ 7.2774, 7.1991, 7.1305, 7.1305, 7.1305] +24-11-19 20:37:49 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:49 | D | sum error = [ 7.8697, 7.6808, 8.3584, 8.6222, 9.2735] +24-11-19 20:37:49 | D | best error = [ 7.1305, 7.1305, 7.1305, 7.1305, 7.1305] +24-11-19 20:37:49 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:49 | D | sum error = [ 9.3522, 10.1753, 11.0867, 11.8660, 12.7266] +24-11-19 20:37:49 | D | best error = [ 7.1305, 7.1305, 7.1305, 7.1305, 7.1305] +24-11-19 20:37:49 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:49 | D | sum error = [ 13.7446, 15.2316, 16.0953, 16.9336, 19.4259] +24-11-19 20:37:49 | D | best error = [ 7.1305, 7.1305, 7.1305, 7.1305, 7.1305] +24-11-19 20:37:49 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:49 | D | sum error = [ 20.9117, 22.3811, 24.3606, 26.3981, 28.7857] +24-11-19 20:37:49 | D | best error = [ 7.1305, 7.1305, 7.1305, 7.1305, 7.1305] +24-11-19 20:37:49 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:49 | D | sum error = [ 30.7597, 33.5191, 36.6975, 39.5174, 42.4548] +24-11-19 20:37:49 | D | best error = [ 7.1305, 7.1305, 7.1305, 7.1305, 7.1305] +24-11-19 20:37:49 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:49 | D | sum error = [ 46.3292, 49.9857, 54.1269, 58.5287, 63.4124] +24-11-19 20:37:49 | D | best error = [ 7.1305, 7.1305, 7.1305, 7.1305, 7.1305] +24-11-19 20:37:49 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:49 | D | sum error = [ 68.6688, 74.2919, 80.4183, 86.6914, 94.0324] +24-11-19 20:37:49 | D | best error = [ 7.1305, 7.1305, 7.1305, 7.1305, 7.1305] +24-11-19 20:37:49 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:49 | D | sum error = [ 101.4636, 110.2247, 119.2550, 129.0253, 139.6815] +24-11-19 20:37:49 | D | best error = [ 7.1305, 7.1305, 7.1305, 7.1305, 7.1305] +24-11-19 20:37:49 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:49 | D | sum error = [ 151.0509, 163.3365, 176.7214, 190.3082, 206.1425] +24-11-19 20:37:49 | D | best error = [ 7.1305, 7.1305, 7.1305, 7.1305, 7.1305] +24-11-19 20:37:49 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:49 | D | sum error = [ 222.7517, 240.1245, 259.0778, 279.7284, 302.1260] +24-11-19 20:37:49 | D | best error = [ 7.1305, 7.1305, 7.1305, 7.1305, 7.1305] +24-11-19 20:37:49 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:49 | D | sum error = [ 326.4269, 352.6327, 381.0855, 411.8047, 445.6415] +24-11-19 20:37:49 | D | best error = [ 7.1305, 7.1305, 7.1305, 7.1305, 7.1305] +24-11-19 20:37:49 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:49 | D | sum error = [ 482.7719, 523.2796, 567.5516, 617.4720, 672.2354] +24-11-19 20:37:49 | D | best error = [ 7.1305, 7.1305, 7.1305, 7.1305, 7.1305] +24-11-19 20:37:49 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:49 | D | sum error = [ 732.8210, 799.6832, 873.5157, 955.4719, 1046.0067] +24-11-19 20:37:49 | D | best error = [ 7.1305, 7.1305, 7.1305, 7.1305, 7.1305] +24-11-19 20:37:49 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:49 | D | sum error = [ 1146.8690, 1258.4983, 1381.7397, 1515.4183, 1657.1175] +24-11-19 20:37:49 | D | best error = [ 7.1305, 7.1305, 7.1305, 7.1305, 7.1305] +24-11-19 20:37:49 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:49 | D | sum error = [ 1809.6197, 1972.9894, 2143.4634, 2316.1009, 2493.0223] +24-11-19 20:37:49 | D | best error = [ 7.1305, 7.1305, 7.1305, 7.1305, 7.1305] +24-11-19 20:37:49 | D | + error = [7.1305] +24-11-19 20:37:49 | D | - Calibrating model.layers.27.self_attn.k_proj.weight +24-11-19 20:37:49 | D | + w: sint8 +24-11-19 20:37:49 | D | + x: None +24-11-19 20:37:49 | D | + y: None +24-11-19 20:37:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:37:49 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:49 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:50 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:50 | D | - range ratio = [ 1.0000] +24-11-19 20:37:50 | D | sum error = [ 7.2322] +24-11-19 20:37:50 | D | best error = [ 7.2322] +24-11-19 20:38:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:01 | D | sum error = [ 6.9101, 7.0798, 7.1872, 7.6461, 8.1084] +24-11-19 20:38:01 | D | best error = [ 6.9101, 6.9101, 6.9101, 6.9101, 6.9101] +24-11-19 20:38:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:01 | D | sum error = [ 7.2869, 8.1940, 8.2533, 8.5861, 10.9539] +24-11-19 20:38:01 | D | best error = [ 6.9101, 6.9101, 6.9101, 6.9101, 6.9101] +24-11-19 20:38:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:01 | D | sum error = [ 9.8993, 10.1723, 11.1231, 11.1037, 13.8834] +24-11-19 20:38:01 | D | best error = [ 6.9101, 6.9101, 6.9101, 6.9101, 6.9101] +24-11-19 20:38:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:01 | D | sum error = [ 14.5593, 14.9151, 16.7654, 18.4166, 18.3533] +24-11-19 20:38:01 | D | best error = [ 6.9101, 6.9101, 6.9101, 6.9101, 6.9101] +24-11-19 20:38:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:01 | D | sum error = [ 20.4760, 21.0282, 23.6418, 24.6084, 25.8289] +24-11-19 20:38:01 | D | best error = [ 6.9101, 6.9101, 6.9101, 6.9101, 6.9101] +24-11-19 20:38:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:01 | D | sum error = [ 28.2087, 30.0856, 32.9075, 36.0193, 38.5763] +24-11-19 20:38:01 | D | best error = [ 6.9101, 6.9101, 6.9101, 6.9101, 6.9101] +24-11-19 20:38:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:01 | D | sum error = [ 41.1227, 45.3048, 47.9073, 52.6982, 56.4605] +24-11-19 20:38:01 | D | best error = [ 6.9101, 6.9101, 6.9101, 6.9101, 6.9101] +24-11-19 20:38:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:01 | D | sum error = [ 62.0622, 66.0183, 72.1738, 78.1685, 84.1722] +24-11-19 20:38:01 | D | best error = [ 6.9101, 6.9101, 6.9101, 6.9101, 6.9101] +24-11-19 20:38:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:01 | D | sum error = [ 91.8252, 98.8133, 107.4704, 116.0170, 125.0448] +24-11-19 20:38:01 | D | best error = [ 6.9101, 6.9101, 6.9101, 6.9101, 6.9101] +24-11-19 20:38:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:01 | D | sum error = [ 135.3747, 147.0743, 157.3629, 169.2349, 182.5556] +24-11-19 20:38:01 | D | best error = [ 6.9101, 6.9101, 6.9101, 6.9101, 6.9101] +24-11-19 20:38:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:01 | D | sum error = [ 197.9284, 212.1874, 230.3205, 249.1576, 269.1806] +24-11-19 20:38:01 | D | best error = [ 6.9101, 6.9101, 6.9101, 6.9101, 6.9101] +24-11-19 20:38:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:01 | D | sum error = [ 293.9503, 319.4442, 345.3170, 376.9326, 410.4866] +24-11-19 20:38:01 | D | best error = [ 6.9101, 6.9101, 6.9101, 6.9101, 6.9101] +24-11-19 20:38:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:01 | D | sum error = [ 447.2892, 489.3936, 534.7469, 586.3680, 640.2103] +24-11-19 20:38:01 | D | best error = [ 6.9101, 6.9101, 6.9101, 6.9101, 6.9101] +24-11-19 20:38:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:01 | D | sum error = [ 706.2900, 780.0278, 857.9257, 946.2803, 1045.3467] +24-11-19 20:38:01 | D | best error = [ 6.9101, 6.9101, 6.9101, 6.9101, 6.9101] +24-11-19 20:38:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:01 | D | sum error = [ 1145.0103, 1261.8154, 1390.2519, 1532.8854, 1688.5939] +24-11-19 20:38:01 | D | best error = [ 6.9101, 6.9101, 6.9101, 6.9101, 6.9101] +24-11-19 20:38:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:01 | D | sum error = [ 1856.5908, 2031.7099, 2199.4339, 2381.4659, 2567.5545] +24-11-19 20:38:01 | D | best error = [ 6.9101, 6.9101, 6.9101, 6.9101, 6.9101] +24-11-19 20:38:01 | D | + error = [6.9101] +24-11-19 20:38:01 | D | - Calibrating model.layers.27.self_attn.v_proj.weight +24-11-19 20:38:01 | D | + w: sint8 +24-11-19 20:38:01 | D | + x: None +24-11-19 20:38:01 | D | + y: None +24-11-19 20:38:01 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:01 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:01 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:02 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:02 | D | - range ratio = [ 1.0000] +24-11-19 20:38:02 | D | sum error = [ 2.8437] +24-11-19 20:38:02 | D | best error = [ 2.8437] +24-11-19 20:38:02 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:02 | D | sum error = [ 2.8472, 2.8219, 2.8615, 2.8917, 2.9293] +24-11-19 20:38:02 | D | best error = [ 2.5793, 2.4739, 2.4217, 2.3971, 2.3822] +24-11-19 20:38:02 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:02 | D | sum error = [ 3.0270, 3.1053, 3.2657, 3.4131, 3.5479] +24-11-19 20:38:02 | D | best error = [ 2.3732, 2.3692, 2.3679, 2.3677, 2.3675] +24-11-19 20:38:02 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:02 | D | sum error = [ 3.8003, 4.0426, 4.2360, 4.5295, 4.8173] +24-11-19 20:38:02 | D | best error = [ 2.3674, 2.3674, 2.3674, 2.3674, 2.3674] +24-11-19 20:38:02 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:02 | D | sum error = [ 5.2144, 5.5332, 5.9921, 6.3638, 6.8297] +24-11-19 20:38:02 | D | best error = [ 2.3674, 2.3674, 2.3674, 2.3674, 2.3674] +24-11-19 20:38:02 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:02 | D | sum error = [ 7.3036, 7.8225, 8.3132, 8.9209, 9.5157] +24-11-19 20:38:02 | D | best error = [ 2.3674, 2.3674, 2.3674, 2.3674, 2.3674] +24-11-19 20:38:02 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:02 | D | sum error = [ 10.1720, 10.8627, 11.5935, 12.3100, 13.1393] +24-11-19 20:38:02 | D | best error = [ 2.3674, 2.3674, 2.3674, 2.3674, 2.3674] +24-11-19 20:38:02 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:02 | D | sum error = [ 13.9500, 14.8479, 15.7992, 16.7771, 17.7978] +24-11-19 20:38:02 | D | best error = [ 2.3674, 2.3674, 2.3674, 2.3674, 2.3674] +24-11-19 20:38:02 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:02 | D | sum error = [ 18.8990, 20.0686, 21.2853, 22.5940, 23.9044] +24-11-19 20:38:02 | D | best error = [ 2.3674, 2.3674, 2.3674, 2.3674, 2.3674] +24-11-19 20:38:02 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:02 | D | sum error = [ 25.3142, 26.7915, 28.3031, 29.9326, 31.6333] +24-11-19 20:38:02 | D | best error = [ 2.3674, 2.3674, 2.3674, 2.3674, 2.3674] +24-11-19 20:38:02 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:02 | D | sum error = [ 33.4239, 35.2607, 37.2277, 39.2156, 41.3595] +24-11-19 20:38:02 | D | best error = [ 2.3674, 2.3674, 2.3674, 2.3674, 2.3674] +24-11-19 20:38:02 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:02 | D | sum error = [ 43.5382, 45.8568, 48.2637, 50.7602, 53.3670] +24-11-19 20:38:02 | D | best error = [ 2.3674, 2.3674, 2.3674, 2.3674, 2.3674] +24-11-19 20:38:02 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:02 | D | sum error = [ 56.0702, 58.9028, 61.8104, 64.8754, 68.0405] +24-11-19 20:38:02 | D | best error = [ 2.3674, 2.3674, 2.3674, 2.3674, 2.3674] +24-11-19 20:38:02 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:02 | D | sum error = [ 71.3434, 74.7326, 78.2822, 81.9149, 85.7108] +24-11-19 20:38:02 | D | best error = [ 2.3674, 2.3674, 2.3674, 2.3674, 2.3674] +24-11-19 20:38:02 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:02 | D | sum error = [ 89.6382, 93.6638, 97.8450, 102.1612, 106.6397] +24-11-19 20:38:02 | D | best error = [ 2.3674, 2.3674, 2.3674, 2.3674, 2.3674] +24-11-19 20:38:02 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:02 | D | sum error = [ 111.2447, 116.0263, 120.9529, 126.0154, 131.2287] +24-11-19 20:38:02 | D | best error = [ 2.3674, 2.3674, 2.3674, 2.3674, 2.3674] +24-11-19 20:38:02 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:02 | D | sum error = [ 136.6064, 142.1423, 147.8434, 153.6969, 159.7141] +24-11-19 20:38:02 | D | best error = [ 2.3674, 2.3674, 2.3674, 2.3674, 2.3674] +24-11-19 20:38:02 | D | + error = [2.3674] +24-11-19 20:38:02 | D | - Calibrating model.layers.27.self_attn.o_proj.weight +24-11-19 20:38:02 | D | + w: sint8 +24-11-19 20:38:02 | D | + x: None +24-11-19 20:38:02 | D | + y: None +24-11-19 20:38:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:02 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:02 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:02 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:02 | D | - range ratio = [ 1.0000] +24-11-19 20:38:02 | D | sum error = [ 0.6494] +24-11-19 20:38:02 | D | best error = [ 0.6494] +24-11-19 20:38:02 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:02 | D | sum error = [ 0.6454, 0.6425, 0.6442, 0.6530, 0.6581] +24-11-19 20:38:02 | D | best error = [ 0.5934, 0.5697, 0.5563, 0.5481, 0.5422] +24-11-19 20:38:02 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:02 | D | sum error = [ 0.6742, 0.6977, 0.7195, 0.7477, 0.7832] +24-11-19 20:38:02 | D | best error = [ 0.5384, 0.5363, 0.5347, 0.5337, 0.5331] +24-11-19 20:38:02 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:02 | D | sum error = [ 0.8237, 0.8684, 0.9200, 0.9762, 1.0380] +24-11-19 20:38:02 | D | best error = [ 0.5328, 0.5324, 0.5323, 0.5322, 0.5321] +24-11-19 20:38:02 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:02 | D | sum error = [ 1.1031, 1.1723, 1.2505, 1.3312, 1.4219] +24-11-19 20:38:02 | D | best error = [ 0.5321, 0.5321, 0.5320, 0.5320, 0.5320] +24-11-19 20:38:02 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:02 | D | sum error = [ 1.5125, 1.6131, 1.7203, 1.8337, 1.9558] +24-11-19 20:38:02 | D | best error = [ 0.5320, 0.5320, 0.5319, 0.5319, 0.5319] +24-11-19 20:38:02 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:02 | D | sum error = [ 2.0795, 2.2121, 2.3516, 2.5013, 2.6556] +24-11-19 20:38:02 | D | best error = [ 0.5319, 0.5319, 0.5319, 0.5319, 0.5319] +24-11-19 20:38:02 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:02 | D | sum error = [ 2.8173, 2.9911, 3.1734, 3.3655, 3.5665] +24-11-19 20:38:02 | D | best error = [ 0.5319, 0.5319, 0.5319, 0.5319, 0.5319] +24-11-19 20:38:02 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:02 | D | sum error = [ 3.7760, 3.9979, 4.2293, 4.4714, 4.7266] +24-11-19 20:38:02 | D | best error = [ 0.5319, 0.5319, 0.5319, 0.5319, 0.5319] +24-11-19 20:38:02 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:02 | D | sum error = [ 4.9939, 5.2764, 5.5666, 5.8746, 6.1973] +24-11-19 20:38:02 | D | best error = [ 0.5319, 0.5319, 0.5319, 0.5319, 0.5319] +24-11-19 20:38:02 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:02 | D | sum error = [ 6.5319, 6.8847, 7.2539, 7.6390, 8.0438] +24-11-19 20:38:02 | D | best error = [ 0.5319, 0.5319, 0.5319, 0.5319, 0.5319] +24-11-19 20:38:02 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:02 | D | sum error = [ 8.4671, 8.9076, 9.3669, 9.8475, 10.3482] +24-11-19 20:38:02 | D | best error = [ 0.5319, 0.5319, 0.5319, 0.5319, 0.5319] +24-11-19 20:38:02 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:02 | D | sum error = [ 10.8710, 11.4165, 11.9853, 12.5819, 13.2005] +24-11-19 20:38:02 | D | best error = [ 0.5319, 0.5319, 0.5319, 0.5319, 0.5319] +24-11-19 20:38:02 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:02 | D | sum error = [ 13.8505, 14.5256, 15.2257, 15.9542, 16.7140] +24-11-19 20:38:02 | D | best error = [ 0.5319, 0.5319, 0.5319, 0.5319, 0.5319] +24-11-19 20:38:02 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:02 | D | sum error = [ 17.5029, 18.3231, 19.1752, 20.0614, 20.9789] +24-11-19 20:38:02 | D | best error = [ 0.5319, 0.5319, 0.5319, 0.5319, 0.5319] +24-11-19 20:38:02 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:02 | D | sum error = [ 21.9342, 22.9232, 23.9497, 25.0166, 26.1186] +24-11-19 20:38:02 | D | best error = [ 0.5319, 0.5319, 0.5319, 0.5319, 0.5319] +24-11-19 20:38:02 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:02 | D | sum error = [ 27.2625, 28.4450, 29.6694, 30.9344, 32.2407] +24-11-19 20:38:02 | D | best error = [ 0.5319, 0.5319, 0.5319, 0.5319, 0.5319] +24-11-19 20:38:02 | D | + error = [0.5319] +24-11-19 20:38:03 | D | - Calibrating model.layers.27.mlp.up_proj.weight +24-11-19 20:38:03 | D | + w: sint8 +24-11-19 20:38:03 | D | + x: None +24-11-19 20:38:03 | D | + y: None +24-11-19 20:38:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:03 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:03 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:03 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:03 | D | - range ratio = [ 1.0000] +24-11-19 20:38:03 | D | sum error = [ 9.0154] +24-11-19 20:38:03 | D | best error = [ 9.0154] +24-11-19 20:38:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:04 | D | sum error = [ 8.9423, 8.9587, 8.9571, 9.0526, 9.2333] +24-11-19 20:38:04 | D | best error = [ 8.0264, 7.6850, 7.5096, 7.4145, 7.3624] +24-11-19 20:38:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:04 | D | sum error = [ 9.4773, 9.7982, 10.1742, 10.6346, 11.2298] +24-11-19 20:38:04 | D | best error = [ 7.3344, 7.3209, 7.3155, 7.3139, 7.3135] +24-11-19 20:38:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:04 | D | sum error = [ 11.8624, 12.6055, 13.4195, 14.2947, 15.2924] +24-11-19 20:38:04 | D | best error = [ 7.3134, 7.3134, 7.3134, 7.3134, 7.3134] +24-11-19 20:38:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:04 | D | sum error = [ 16.3531, 17.5200, 18.7942, 20.1137, 21.5417] +24-11-19 20:38:04 | D | best error = [ 7.3134, 7.3134, 7.3134, 7.3134, 7.3134] +24-11-19 20:38:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:04 | D | sum error = [ 23.0961, 24.7723, 26.4879, 28.3161, 30.2942] +24-11-19 20:38:04 | D | best error = [ 7.3134, 7.3134, 7.3134, 7.3134, 7.3134] +24-11-19 20:38:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:04 | D | sum error = [ 32.3500, 34.5590, 36.8701, 39.3221, 41.9037] +24-11-19 20:38:04 | D | best error = [ 7.3134, 7.3134, 7.3134, 7.3134, 7.3134] +24-11-19 20:38:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:04 | D | sum error = [ 44.6521, 47.4536, 50.5117, 53.6620, 57.0263] +24-11-19 20:38:04 | D | best error = [ 7.3134, 7.3134, 7.3134, 7.3134, 7.3134] +24-11-19 20:38:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:04 | D | sum error = [ 60.5050, 64.1936, 68.0082, 72.0597, 76.2577] +24-11-19 20:38:04 | D | best error = [ 7.3134, 7.3134, 7.3134, 7.3134, 7.3134] +24-11-19 20:38:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:04 | D | sum error = [ 80.6637, 85.3329, 90.1500, 95.2269, 100.5101] +24-11-19 20:38:04 | D | best error = [ 7.3134, 7.3134, 7.3134, 7.3134, 7.3134] +24-11-19 20:38:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:04 | D | sum error = [ 106.0338, 111.7534, 117.7768, 124.0357, 130.5682] +24-11-19 20:38:04 | D | best error = [ 7.3134, 7.3134, 7.3134, 7.3134, 7.3134] +24-11-19 20:38:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:04 | D | sum error = [ 137.3561, 144.4351, 151.7842, 159.4342, 167.3750] +24-11-19 20:38:04 | D | best error = [ 7.3134, 7.3134, 7.3134, 7.3134, 7.3134] +24-11-19 20:38:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:04 | D | sum error = [ 175.6509, 184.1930, 193.0905, 202.3339, 211.8635] +24-11-19 20:38:04 | D | best error = [ 7.3134, 7.3134, 7.3134, 7.3134, 7.3134] +24-11-19 20:38:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:04 | D | sum error = [ 221.7458, 231.9855, 242.5591, 253.4857, 264.8022] +24-11-19 20:38:04 | D | best error = [ 7.3134, 7.3134, 7.3134, 7.3134, 7.3134] +24-11-19 20:38:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:04 | D | sum error = [ 276.5048, 288.5586, 301.0144, 313.8981, 327.1306] +24-11-19 20:38:04 | D | best error = [ 7.3134, 7.3134, 7.3134, 7.3134, 7.3134] +24-11-19 20:38:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:04 | D | sum error = [ 340.7710, 354.8248, 369.2861, 384.1478, 399.4391] +24-11-19 20:38:04 | D | best error = [ 7.3134, 7.3134, 7.3134, 7.3134, 7.3134] +24-11-19 20:38:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:04 | D | sum error = [ 415.1438, 431.2767, 447.8781, 464.9075, 482.3992] +24-11-19 20:38:04 | D | best error = [ 7.3134, 7.3134, 7.3134, 7.3134, 7.3134] +24-11-19 20:38:04 | D | + error = [7.3134] +24-11-19 20:38:04 | D | - Calibrating model.layers.27.mlp.gate_proj.weight +24-11-19 20:38:04 | D | + w: sint8 +24-11-19 20:38:04 | D | + x: None +24-11-19 20:38:04 | D | + y: None +24-11-19 20:38:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:04 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:04 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:04 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:04 | D | - range ratio = [ 1.0000] +24-11-19 20:38:04 | D | sum error = [ 12.0512] +24-11-19 20:38:04 | D | best error = [ 12.0512] +24-11-19 20:38:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:06 | D | sum error = [ 11.9795, 12.0101, 11.9302, 12.1163, 12.3577] +24-11-19 20:38:06 | D | best error = [ 10.7406, 10.2837, 10.0479, 9.9211, 9.8502] +24-11-19 20:38:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:06 | D | sum error = [ 12.6953, 13.1129, 13.6410, 14.2719, 15.0512] +24-11-19 20:38:06 | D | best error = [ 9.8164, 9.8005, 9.7934, 9.7907, 9.7901] +24-11-19 20:38:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:06 | D | sum error = [ 15.8993, 16.9133, 18.0259, 19.2345, 20.6002] +24-11-19 20:38:06 | D | best error = [ 9.7900, 9.7900, 9.7900, 9.7900, 9.7900] +24-11-19 20:38:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:06 | D | sum error = [ 22.0495, 23.6121, 25.3709, 27.1578, 29.1521] +24-11-19 20:38:06 | D | best error = [ 9.7900, 9.7900, 9.7900, 9.7900, 9.7900] +24-11-19 20:38:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:06 | D | sum error = [ 31.2072, 33.5224, 35.8765, 38.4278, 41.2101] +24-11-19 20:38:06 | D | best error = [ 9.7900, 9.7900, 9.7900, 9.7900, 9.7900] +24-11-19 20:38:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:06 | D | sum error = [ 44.1097, 47.1372, 50.3595, 53.8311, 57.4964] +24-11-19 20:38:06 | D | best error = [ 9.7900, 9.7900, 9.7900, 9.7900, 9.7900] +24-11-19 20:38:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:06 | D | sum error = [ 61.3059, 65.3994, 69.7224, 74.2673, 79.1336] +24-11-19 20:38:06 | D | best error = [ 9.7900, 9.7900, 9.7900, 9.7900, 9.7900] +24-11-19 20:38:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:06 | D | sum error = [ 84.1900, 89.5535, 95.2794, 101.2686, 107.6297] +24-11-19 20:38:06 | D | best error = [ 9.7900, 9.7900, 9.7900, 9.7900, 9.7900] +24-11-19 20:38:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:06 | D | sum error = [ 114.2848, 121.3574, 128.7442, 136.6244, 144.8730] +24-11-19 20:38:06 | D | best error = [ 9.7900, 9.7900, 9.7900, 9.7900, 9.7900] +24-11-19 20:38:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:06 | D | sum error = [ 153.5889, 162.7514, 172.3907, 182.5435, 193.2328] +24-11-19 20:38:06 | D | best error = [ 9.7900, 9.7900, 9.7900, 9.7900, 9.7900] +24-11-19 20:38:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:06 | D | sum error = [ 204.4191, 216.1482, 228.4824, 241.4327, 254.9946] +24-11-19 20:38:06 | D | best error = [ 9.7900, 9.7900, 9.7900, 9.7900, 9.7900] +24-11-19 20:38:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:06 | D | sum error = [ 269.2188, 284.1785, 299.7178, 316.0667, 333.2220] +24-11-19 20:38:06 | D | best error = [ 9.7900, 9.7900, 9.7900, 9.7900, 9.7900] +24-11-19 20:38:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:06 | D | sum error = [ 351.1201, 369.8722, 389.4226, 409.9463, 431.3059] +24-11-19 20:38:06 | D | best error = [ 9.7900, 9.7900, 9.7900, 9.7900, 9.7900] +24-11-19 20:38:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:06 | D | sum error = [ 453.6252, 476.8093, 500.9036, 525.9674, 551.9901] +24-11-19 20:38:06 | D | best error = [ 9.7900, 9.7900, 9.7900, 9.7900, 9.7900] +24-11-19 20:38:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:06 | D | sum error = [ 579.0275, 607.0441, 636.1565, 666.2407, 697.3362] +24-11-19 20:38:06 | D | best error = [ 9.7900, 9.7900, 9.7900, 9.7900, 9.7900] +24-11-19 20:38:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:06 | D | sum error = [ 729.4877, 762.7072, 796.9508, 832.2643, 868.6179] +24-11-19 20:38:06 | D | best error = [ 9.7900, 9.7900, 9.7900, 9.7900, 9.7900] +24-11-19 20:38:06 | D | + error = [9.7900] +24-11-19 20:38:06 | D | - Calibrating model.layers.27.mlp.down_proj.weight +24-11-19 20:38:06 | D | + w: sint8 +24-11-19 20:38:06 | D | + x: None +24-11-19 20:38:06 | D | + y: None +24-11-19 20:38:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:06 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:06 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:06 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:06 | D | - range ratio = [ 1.0000] +24-11-19 20:38:06 | D | sum error = [ 1.6193] +24-11-19 20:38:06 | D | best error = [ 1.6193] +24-11-19 20:38:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:07 | D | sum error = [ 1.6075, 1.6014, 1.5860, 1.5800, 1.5645] +24-11-19 20:38:07 | D | best error = [ 1.5002, 1.4519, 1.4202, 1.3997, 1.3835] +24-11-19 20:38:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:07 | D | sum error = [ 1.5621, 1.5606, 1.5610, 1.5728, 1.5866] +24-11-19 20:38:07 | D | best error = [ 1.3704, 1.3599, 1.3519, 1.3456, 1.3409] +24-11-19 20:38:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:07 | D | sum error = [ 1.6025, 1.6352, 1.6653, 1.7091, 1.7572] +24-11-19 20:38:07 | D | best error = [ 1.3374, 1.3353, 1.3336, 1.3324, 1.3316] +24-11-19 20:38:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:07 | D | sum error = [ 1.8196, 1.8907, 1.9708, 2.0639, 2.1683] +24-11-19 20:38:07 | D | best error = [ 1.3311, 1.3305, 1.3303, 1.3302, 1.3302] +24-11-19 20:38:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:07 | D | sum error = [ 2.2859, 2.4212, 2.5652, 2.7236, 2.8929] +24-11-19 20:38:07 | D | best error = [ 1.3301, 1.3301, 1.3301, 1.3301, 1.3300] +24-11-19 20:38:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:07 | D | sum error = [ 3.0861, 3.2926, 3.5134, 3.7582, 4.0153] +24-11-19 20:38:07 | D | best error = [ 1.3300, 1.3300, 1.3300, 1.3300, 1.3300] +24-11-19 20:38:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:07 | D | sum error = [ 4.2887, 4.5849, 4.9031, 5.2391, 5.6042] +24-11-19 20:38:07 | D | best error = [ 1.3300, 1.3300, 1.3300, 1.3300, 1.3300] +24-11-19 20:38:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:07 | D | sum error = [ 5.9918, 6.4016, 6.8362, 7.2979, 7.7899] +24-11-19 20:38:07 | D | best error = [ 1.3300, 1.3300, 1.3300, 1.3300, 1.3300] +24-11-19 20:38:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:07 | D | sum error = [ 8.3102, 8.8628, 9.4473, 10.0698, 10.7239] +24-11-19 20:38:07 | D | best error = [ 1.3300, 1.3300, 1.3300, 1.3300, 1.3300] +24-11-19 20:38:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:07 | D | sum error = [ 11.4246, 12.1563, 12.9290, 13.7464, 14.6118] +24-11-19 20:38:07 | D | best error = [ 1.3300, 1.3300, 1.3300, 1.3300, 1.3300] +24-11-19 20:38:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:07 | D | sum error = [ 15.5238, 16.4819, 17.4910, 18.5501, 19.6649] +24-11-19 20:38:07 | D | best error = [ 1.3300, 1.3300, 1.3300, 1.3300, 1.3300] +24-11-19 20:38:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:07 | D | sum error = [ 20.8367, 22.0652, 23.3532, 24.7052, 26.1244] +24-11-19 20:38:07 | D | best error = [ 1.3300, 1.3300, 1.3300, 1.3300, 1.3300] +24-11-19 20:38:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:07 | D | sum error = [ 27.6093, 29.1683, 30.7965, 32.5026, 34.2851] +24-11-19 20:38:07 | D | best error = [ 1.3300, 1.3300, 1.3300, 1.3300, 1.3300] +24-11-19 20:38:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:07 | D | sum error = [ 36.1517, 38.1017, 40.1354, 42.2630, 44.4817] +24-11-19 20:38:07 | D | best error = [ 1.3300, 1.3300, 1.3300, 1.3300, 1.3300] +24-11-19 20:38:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:07 | D | sum error = [ 46.7952, 49.2117, 51.7332, 54.3564, 57.0884] +24-11-19 20:38:07 | D | best error = [ 1.3300, 1.3300, 1.3300, 1.3300, 1.3300] +24-11-19 20:38:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:07 | D | sum error = [ 59.9310, 62.8879, 65.9589, 69.1475, 72.4554] +24-11-19 20:38:07 | D | best error = [ 1.3300, 1.3300, 1.3300, 1.3300, 1.3300] +24-11-19 20:38:07 | D | + error = [1.3300] +24-11-19 20:38:07 | D | - Quantizing model.layers.27.self_attn.q_proj.weight +24-11-19 20:38:08 | D | - Quantizing model.layers.27.self_attn.k_proj.weight +24-11-19 20:38:09 | D | - Quantizing model.layers.27.self_attn.v_proj.weight +24-11-19 20:38:12 | D | - Quantizing model.layers.27.self_attn.o_proj.weight +24-11-19 20:38:13 | D | - Quantizing model.layers.27.mlp.up_proj.weight +24-11-19 20:38:14 | D | - Quantizing model.layers.27.mlp.gate_proj.weight +24-11-19 20:38:14 | D | - Quantizing model.layers.27.mlp.down_proj.weight +24-11-19 20:38:25 | D | - Quantizing layer model.layers.28 +24-11-19 20:38:25 | D | - Calibrating model.layers.28.self_attn.q_proj.weight +24-11-19 20:38:25 | D | + w: sint8 +24-11-19 20:38:25 | D | + x: None +24-11-19 20:38:25 | D | + y: None +24-11-19 20:38:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:38:25 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:38:25 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:38:25 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:38:26 | D | - range ratio = [ 1.0000] +24-11-19 20:38:26 | D | sum error = [ 7.4172] +24-11-19 20:38:26 | D | best error = [ 7.4172] +24-11-19 20:38:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:37 | D | sum error = [ 7.2840, 7.3586, 7.3586, 7.1868, 7.7970] +24-11-19 20:38:37 | D | best error = [ 7.2840, 7.2840, 7.2840, 7.1868, 7.1868] +24-11-19 20:38:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:37 | D | sum error = [ 7.8405, 7.9468, 8.4075, 8.5561, 8.8261] +24-11-19 20:38:37 | D | best error = [ 7.1868, 7.1868, 7.1868, 7.1868, 7.1868] +24-11-19 20:38:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:37 | D | sum error = [ 9.7720, 10.3129, 10.9047, 11.8544, 12.5666] +24-11-19 20:38:37 | D | best error = [ 7.1868, 7.1868, 7.1868, 7.1868, 7.1868] +24-11-19 20:38:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:37 | D | sum error = [ 13.9115, 14.6162, 15.5217, 17.5666, 18.8168] +24-11-19 20:38:37 | D | best error = [ 7.1868, 7.1868, 7.1868, 7.1868, 7.1868] +24-11-19 20:38:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:37 | D | sum error = [ 20.2729, 21.9846, 23.8520, 25.7913, 28.2398] +24-11-19 20:38:37 | D | best error = [ 7.1868, 7.1868, 7.1868, 7.1868, 7.1868] +24-11-19 20:38:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:37 | D | sum error = [ 30.5575, 33.9614, 36.3751, 38.9730, 42.7859] +24-11-19 20:38:37 | D | best error = [ 7.1868, 7.1868, 7.1868, 7.1868, 7.1868] +24-11-19 20:38:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:37 | D | sum error = [ 46.8608, 50.6138, 54.2927, 58.8785, 63.6034] +24-11-19 20:38:37 | D | best error = [ 7.1868, 7.1868, 7.1868, 7.1868, 7.1868] +24-11-19 20:38:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:37 | D | sum error = [ 68.8876, 75.0569, 80.8382, 86.9822, 93.9703] +24-11-19 20:38:37 | D | best error = [ 7.1868, 7.1868, 7.1868, 7.1868, 7.1868] +24-11-19 20:38:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:37 | D | sum error = [ 101.4745, 109.1137, 117.2410, 126.4255, 135.4499] +24-11-19 20:38:37 | D | best error = [ 7.1868, 7.1868, 7.1868, 7.1868, 7.1868] +24-11-19 20:38:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:37 | D | sum error = [ 145.4458, 156.0171, 167.4596, 179.9015, 193.1819] +24-11-19 20:38:37 | D | best error = [ 7.1868, 7.1868, 7.1868, 7.1868, 7.1868] +24-11-19 20:38:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:37 | D | sum error = [ 206.4901, 221.7890, 237.8270, 255.0699, 273.9189] +24-11-19 20:38:37 | D | best error = [ 7.1868, 7.1868, 7.1868, 7.1868, 7.1868] +24-11-19 20:38:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:37 | D | sum error = [ 293.6108, 314.9081, 337.4216, 362.3599, 387.7747] +24-11-19 20:38:37 | D | best error = [ 7.1868, 7.1868, 7.1868, 7.1868, 7.1868] +24-11-19 20:38:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:37 | D | sum error = [ 415.8018, 446.0458, 478.3988, 513.9057, 551.9894] +24-11-19 20:38:37 | D | best error = [ 7.1868, 7.1868, 7.1868, 7.1868, 7.1868] +24-11-19 20:38:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:37 | D | sum error = [ 593.0912, 637.6837, 686.2501, 738.5167, 794.0523] +24-11-19 20:38:37 | D | best error = [ 7.1868, 7.1868, 7.1868, 7.1868, 7.1868] +24-11-19 20:38:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:37 | D | sum error = [ 853.5434, 916.8507, 984.3952, 1056.5925, 1132.6779] +24-11-19 20:38:37 | D | best error = [ 7.1868, 7.1868, 7.1868, 7.1868, 7.1868] +24-11-19 20:38:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:37 | D | sum error = [ 1212.5526, 1296.7553, 1384.4591, 1474.6496, 1566.2589] +24-11-19 20:38:37 | D | best error = [ 7.1868, 7.1868, 7.1868, 7.1868, 7.1868] +24-11-19 20:38:37 | D | + error = [7.1868] +24-11-19 20:38:38 | D | - Calibrating model.layers.28.self_attn.k_proj.weight +24-11-19 20:38:38 | D | + w: sint8 +24-11-19 20:38:38 | D | + x: None +24-11-19 20:38:38 | D | + y: None +24-11-19 20:38:38 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:38:38 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:38 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:38 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:38 | D | - range ratio = [ 1.0000] +24-11-19 20:38:38 | D | sum error = [ 8.1762] +24-11-19 20:38:38 | D | best error = [ 8.1762] +24-11-19 20:38:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:50 | D | sum error = [ 7.3697, 7.7800, 7.4544, 7.6775, 7.5747] +24-11-19 20:38:50 | D | best error = [ 7.3697, 7.3697, 7.3697, 7.3697, 7.3697] +24-11-19 20:38:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:50 | D | sum error = [ 7.4817, 8.7499, 7.7638, 8.8433, 8.8322] +24-11-19 20:38:50 | D | best error = [ 7.3697, 7.3697, 7.3697, 7.3697, 7.3697] +24-11-19 20:38:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:50 | D | sum error = [ 9.2493, 10.3080, 10.9343, 11.2569, 12.6111] +24-11-19 20:38:50 | D | best error = [ 7.3697, 7.3697, 7.3697, 7.3697, 7.3697] +24-11-19 20:38:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:50 | D | sum error = [ 13.0361, 14.2519, 15.2691, 15.8271, 17.2371] +24-11-19 20:38:50 | D | best error = [ 7.3697, 7.3697, 7.3697, 7.3697, 7.3697] +24-11-19 20:38:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:50 | D | sum error = [ 17.7876, 20.3860, 21.7825, 23.3438, 25.3246] +24-11-19 20:38:50 | D | best error = [ 7.3697, 7.3697, 7.3697, 7.3697, 7.3697] +24-11-19 20:38:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:50 | D | sum error = [ 27.0649, 28.9774, 31.6190, 33.3700, 36.1952] +24-11-19 20:38:50 | D | best error = [ 7.3697, 7.3697, 7.3697, 7.3697, 7.3697] +24-11-19 20:38:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:50 | D | sum error = [ 38.9417, 41.7483, 44.5577, 48.6750, 52.4920] +24-11-19 20:38:50 | D | best error = [ 7.3697, 7.3697, 7.3697, 7.3697, 7.3697] +24-11-19 20:38:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:50 | D | sum error = [ 56.4396, 60.5117, 65.2430, 70.0757, 76.2895] +24-11-19 20:38:50 | D | best error = [ 7.3697, 7.3697, 7.3697, 7.3697, 7.3697] +24-11-19 20:38:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:50 | D | sum error = [ 81.1283, 87.5868, 93.9993, 100.0277, 107.9136] +24-11-19 20:38:50 | D | best error = [ 7.3697, 7.3697, 7.3697, 7.3697, 7.3697] +24-11-19 20:38:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:50 | D | sum error = [ 116.2047, 124.7302, 134.1265, 143.6484, 154.6479] +24-11-19 20:38:50 | D | best error = [ 7.3697, 7.3697, 7.3697, 7.3697, 7.3697] +24-11-19 20:38:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:50 | D | sum error = [ 166.3662, 178.6116, 193.2454, 206.9697, 223.0199] +24-11-19 20:38:50 | D | best error = [ 7.3697, 7.3697, 7.3697, 7.3697, 7.3697] +24-11-19 20:38:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:50 | D | sum error = [ 239.6816, 258.2332, 278.6431, 300.6314, 323.2112] +24-11-19 20:38:50 | D | best error = [ 7.3697, 7.3697, 7.3697, 7.3697, 7.3697] +24-11-19 20:38:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:50 | D | sum error = [ 348.9975, 376.4230, 407.1977, 440.1669, 476.2019] +24-11-19 20:38:50 | D | best error = [ 7.3697, 7.3697, 7.3697, 7.3697, 7.3697] +24-11-19 20:38:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:50 | D | sum error = [ 516.2116, 558.0483, 604.4288, 654.7264, 708.5755] +24-11-19 20:38:50 | D | best error = [ 7.3697, 7.3697, 7.3697, 7.3697, 7.3697] +24-11-19 20:38:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:50 | D | sum error = [ 767.8874, 830.8948, 899.9955, 974.6508, 1055.1419] +24-11-19 20:38:50 | D | best error = [ 7.3697, 7.3697, 7.3697, 7.3697, 7.3697] +24-11-19 20:38:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:50 | D | sum error = [ 1141.9305, 1230.1078, 1323.7266, 1418.2363, 1518.5525] +24-11-19 20:38:50 | D | best error = [ 7.3697, 7.3697, 7.3697, 7.3697, 7.3697] +24-11-19 20:38:50 | D | + error = [7.3697] +24-11-19 20:38:50 | D | - Calibrating model.layers.28.self_attn.v_proj.weight +24-11-19 20:38:50 | D | + w: sint8 +24-11-19 20:38:50 | D | + x: None +24-11-19 20:38:50 | D | + y: None +24-11-19 20:38:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:50 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:50 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:50 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:50 | D | - range ratio = [ 1.0000] +24-11-19 20:38:50 | D | sum error = [ 2.8252] +24-11-19 20:38:50 | D | best error = [ 2.8252] +24-11-19 20:38:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:50 | D | sum error = [ 2.8423, 2.8016, 2.8360, 2.8517, 2.9120] +24-11-19 20:38:50 | D | best error = [ 2.5300, 2.4138, 2.3664, 2.3407, 2.3254] +24-11-19 20:38:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:50 | D | sum error = [ 3.0067, 3.0510, 3.2089, 3.3514, 3.5649] +24-11-19 20:38:50 | D | best error = [ 2.3181, 2.3136, 2.3125, 2.3119, 2.3119] +24-11-19 20:38:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:50 | D | sum error = [ 3.7432, 3.9896, 4.2431, 4.5462, 4.8123] +24-11-19 20:38:50 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:38:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:50 | D | sum error = [ 5.1429, 5.5565, 5.9172, 6.3233, 6.7959] +24-11-19 20:38:50 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:38:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:50 | D | sum error = [ 7.2330, 7.7775, 8.2774, 8.8719, 9.4662] +24-11-19 20:38:50 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:38:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:50 | D | sum error = [ 10.1430, 10.8066, 11.4884, 12.2828, 13.0562] +24-11-19 20:38:50 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:38:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:50 | D | sum error = [ 13.8714, 14.7360, 15.6563, 16.6173, 17.6499] +24-11-19 20:38:50 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:38:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:50 | D | sum error = [ 18.7077, 19.8501, 21.0345, 22.3096, 23.6326] +24-11-19 20:38:50 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:38:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:50 | D | sum error = [ 25.0507, 26.4794, 27.9939, 29.5764, 31.2156] +24-11-19 20:38:50 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:38:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:50 | D | sum error = [ 32.9286, 34.7220, 36.5609, 38.5011, 40.5077] +24-11-19 20:38:50 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:38:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:50 | D | sum error = [ 42.6294, 44.8213, 47.0908, 49.4650, 51.8943] +24-11-19 20:38:50 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:38:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:50 | D | sum error = [ 54.4454, 57.0748, 59.8263, 62.6305, 65.5645] +24-11-19 20:38:50 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:38:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:50 | D | sum error = [ 68.5998, 71.7356, 74.9619, 78.3043, 81.7256] +24-11-19 20:38:50 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:38:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:50 | D | sum error = [ 85.2904, 88.9693, 92.7682, 96.6826, 100.7121] +24-11-19 20:38:50 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:38:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:50 | D | sum error = [ 104.8615, 109.1253, 113.5317, 118.0516, 122.6962] +24-11-19 20:38:50 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:38:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:50 | D | sum error = [ 127.4738, 132.3637, 137.3732, 142.5494, 147.8538] +24-11-19 20:38:50 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:38:50 | D | + error = [2.3119] +24-11-19 20:38:50 | D | - Calibrating model.layers.28.self_attn.o_proj.weight +24-11-19 20:38:50 | D | + w: sint8 +24-11-19 20:38:50 | D | + x: None +24-11-19 20:38:50 | D | + y: None +24-11-19 20:38:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:50 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:50 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:51 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:51 | D | - range ratio = [ 1.0000] +24-11-19 20:38:51 | D | sum error = [ 0.8159] +24-11-19 20:38:51 | D | best error = [ 0.8159] +24-11-19 20:38:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:51 | D | sum error = [ 0.8089, 0.8123, 0.8154, 0.8261, 0.8438] +24-11-19 20:38:51 | D | best error = [ 0.7612, 0.7390, 0.7259, 0.7175, 0.7124] +24-11-19 20:38:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:51 | D | sum error = [ 0.8654, 0.8961, 0.9336, 0.9789, 1.0323] +24-11-19 20:38:51 | D | best error = [ 0.7089, 0.7068, 0.7054, 0.7045, 0.7039] +24-11-19 20:38:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:51 | D | sum error = [ 1.0875, 1.1549, 1.2246, 1.3034, 1.3894] +24-11-19 20:38:51 | D | best error = [ 0.7035, 0.7032, 0.7031, 0.7031, 0.7030] +24-11-19 20:38:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:51 | D | sum error = [ 1.4768, 1.5746, 1.6798, 1.7894, 1.9075] +24-11-19 20:38:51 | D | best error = [ 0.7030, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 20:38:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:51 | D | sum error = [ 2.0334, 2.1666, 2.3053, 2.4475, 2.6029] +24-11-19 20:38:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 20:38:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:51 | D | sum error = [ 2.7654, 2.9341, 3.1141, 3.3019, 3.5013] +24-11-19 20:38:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 20:38:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:51 | D | sum error = [ 3.7096, 3.9272, 4.1550, 4.3956, 4.6455] +24-11-19 20:38:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 20:38:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:51 | D | sum error = [ 4.9065, 5.1826, 5.4730, 5.7737, 6.0868] +24-11-19 20:38:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 20:38:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:51 | D | sum error = [ 6.4187, 6.7623, 7.1270, 7.5014, 7.8988] +24-11-19 20:38:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 20:38:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:51 | D | sum error = [ 8.3133, 8.7458, 9.1955, 9.6649, 10.1514] +24-11-19 20:38:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 20:38:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:51 | D | sum error = [ 10.6641, 11.1954, 11.7511, 12.3302, 12.9351] +24-11-19 20:38:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 20:38:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:51 | D | sum error = [ 13.5618, 14.2203, 14.9024, 15.6152, 16.3570] +24-11-19 20:38:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 20:38:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:51 | D | sum error = [ 17.1281, 17.9314, 18.7665, 19.6322, 20.5358] +24-11-19 20:38:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 20:38:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:51 | D | sum error = [ 21.4729, 22.4460, 23.4560, 24.5050, 25.5922] +24-11-19 20:38:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 20:38:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:51 | D | sum error = [ 26.7204, 27.8917, 29.1029, 30.3588, 31.6602] +24-11-19 20:38:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 20:38:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:51 | D | sum error = [ 33.0051, 34.3967, 35.8342, 37.3198, 38.8572] +24-11-19 20:38:51 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 20:38:51 | D | + error = [0.7029] +24-11-19 20:38:51 | D | - Calibrating model.layers.28.mlp.up_proj.weight +24-11-19 20:38:51 | D | + w: sint8 +24-11-19 20:38:51 | D | + x: None +24-11-19 20:38:51 | D | + y: None +24-11-19 20:38:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:51 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:51 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:51 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:51 | D | - range ratio = [ 1.0000] +24-11-19 20:38:51 | D | sum error = [ 9.6318] +24-11-19 20:38:51 | D | best error = [ 9.6318] +24-11-19 20:38:53 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:53 | D | sum error = [ 9.5566, 9.5065, 9.5499, 9.6609, 9.8352] +24-11-19 20:38:53 | D | best error = [ 8.4917, 8.0926, 7.9057, 7.8068, 7.7494] +24-11-19 20:38:53 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:53 | D | sum error = [ 10.0986, 10.4525, 10.8705, 11.4009, 11.9495] +24-11-19 20:38:53 | D | best error = [ 7.7222, 7.7093, 7.7049, 7.7030, 7.7025] +24-11-19 20:38:53 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:53 | D | sum error = [ 12.6815, 13.4627, 14.2889, 15.2719, 16.3326] +24-11-19 20:38:53 | D | best error = [ 7.7023, 7.7023, 7.7022, 7.7022, 7.7022] +24-11-19 20:38:53 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:53 | D | sum error = [ 17.4766, 18.6777, 20.0324, 21.4527, 22.9762] +24-11-19 20:38:53 | D | best error = [ 7.7022, 7.7022, 7.7022, 7.7022, 7.7022] +24-11-19 20:38:53 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:53 | D | sum error = [ 24.6703, 26.3947, 28.2247, 30.1737, 32.3108] +24-11-19 20:38:53 | D | best error = [ 7.7022, 7.7022, 7.7022, 7.7022, 7.7022] +24-11-19 20:38:53 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:53 | D | sum error = [ 34.4969, 36.8270, 39.3246, 41.9150, 44.7005] +24-11-19 20:38:53 | D | best error = [ 7.7022, 7.7022, 7.7022, 7.7022, 7.7022] +24-11-19 20:38:53 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:53 | D | sum error = [ 47.5960, 50.6249, 53.8891, 57.2813, 60.8380] +24-11-19 20:38:53 | D | best error = [ 7.7022, 7.7022, 7.7022, 7.7022, 7.7022] +24-11-19 20:38:53 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:53 | D | sum error = [ 64.6308, 68.5895, 72.7399, 77.0994, 81.7495] +24-11-19 20:38:53 | D | best error = [ 7.7022, 7.7022, 7.7022, 7.7022, 7.7022] +24-11-19 20:38:53 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:53 | D | sum error = [ 86.5716, 91.6471, 96.9810, 102.4892, 108.2978] +24-11-19 20:38:53 | D | best error = [ 7.7022, 7.7022, 7.7022, 7.7022, 7.7022] +24-11-19 20:38:53 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:53 | D | sum error = [ 114.3946, 120.7460, 127.4133, 134.3389, 141.5865] +24-11-19 20:38:53 | D | best error = [ 7.7022, 7.7022, 7.7022, 7.7022, 7.7022] +24-11-19 20:38:53 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:53 | D | sum error = [ 149.1142, 157.0543, 165.2531, 173.8087, 182.7048] +24-11-19 20:38:53 | D | best error = [ 7.7022, 7.7022, 7.7022, 7.7022, 7.7022] +24-11-19 20:38:53 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:53 | D | sum error = [ 191.9500, 201.5838, 211.5591, 221.9368, 232.6732] +24-11-19 20:38:53 | D | best error = [ 7.7022, 7.7022, 7.7022, 7.7022, 7.7022] +24-11-19 20:38:53 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:53 | D | sum error = [ 243.8267, 255.3760, 267.3731, 279.8100, 292.6442] +24-11-19 20:38:53 | D | best error = [ 7.7022, 7.7022, 7.7022, 7.7022, 7.7022] +24-11-19 20:38:53 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:53 | D | sum error = [ 305.9461, 319.7013, 333.9254, 348.6486, 363.8411] +24-11-19 20:38:53 | D | best error = [ 7.7022, 7.7022, 7.7022, 7.7022, 7.7022] +24-11-19 20:38:53 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:53 | D | sum error = [ 379.5473, 395.7478, 412.4754, 429.7179, 447.4892] +24-11-19 20:38:53 | D | best error = [ 7.7022, 7.7022, 7.7022, 7.7022, 7.7022] +24-11-19 20:38:53 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:53 | D | sum error = [ 465.8042, 484.6632, 504.0401, 523.9828, 544.4615] +24-11-19 20:38:53 | D | best error = [ 7.7022, 7.7022, 7.7022, 7.7022, 7.7022] +24-11-19 20:38:53 | D | + error = [7.7022] +24-11-19 20:38:53 | D | - Calibrating model.layers.28.mlp.gate_proj.weight +24-11-19 20:38:53 | D | + w: sint8 +24-11-19 20:38:53 | D | + x: None +24-11-19 20:38:53 | D | + y: None +24-11-19 20:38:53 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:53 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:53 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:53 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:53 | D | - range ratio = [ 1.0000] +24-11-19 20:38:53 | D | sum error = [ 12.5618] +24-11-19 20:38:53 | D | best error = [ 12.5618] +24-11-19 20:38:54 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:54 | D | sum error = [ 12.4410, 12.4301, 12.4582, 12.6164, 12.8289] +24-11-19 20:38:54 | D | best error = [ 11.0524, 10.5567, 10.3079, 10.1796, 10.1051] +24-11-19 20:38:54 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:54 | D | sum error = [ 13.1827, 13.6857, 14.1401, 14.8339, 15.6476] +24-11-19 20:38:54 | D | best error = [ 10.0672, 10.0495, 10.0426, 10.0396, 10.0388] +24-11-19 20:38:54 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:54 | D | sum error = [ 16.5436, 17.5646, 18.7163, 19.9930, 21.4137] +24-11-19 20:38:54 | D | best error = [ 10.0386, 10.0386, 10.0384, 10.0384, 10.0384] +24-11-19 20:38:54 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:54 | D | sum error = [ 22.9227, 24.5772, 26.3463, 28.2877, 30.3203] +24-11-19 20:38:54 | D | best error = [ 10.0384, 10.0384, 10.0384, 10.0384, 10.0384] +24-11-19 20:38:54 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:54 | D | sum error = [ 32.5127, 34.9030, 37.3588, 40.0525, 42.8270] +24-11-19 20:38:54 | D | best error = [ 10.0384, 10.0384, 10.0384, 10.0384, 10.0384] +24-11-19 20:38:54 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:54 | D | sum error = [ 45.9031, 49.0830, 52.4698, 56.0817, 59.8543] +24-11-19 20:38:54 | D | best error = [ 10.0384, 10.0384, 10.0384, 10.0384, 10.0384] +24-11-19 20:38:54 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:54 | D | sum error = [ 63.8835, 68.1601, 72.7706, 77.5017, 82.6214] +24-11-19 20:38:54 | D | best error = [ 10.0384, 10.0384, 10.0384, 10.0384, 10.0384] +24-11-19 20:38:54 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:54 | D | sum error = [ 87.9488, 93.6752, 99.6663, 106.0394, 112.7136] +24-11-19 20:38:54 | D | best error = [ 10.0384, 10.0384, 10.0384, 10.0384, 10.0384] +24-11-19 20:38:54 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:54 | D | sum error = [ 119.8618, 127.3818, 135.2985, 143.7437, 152.5293] +24-11-19 20:38:54 | D | best error = [ 10.0384, 10.0384, 10.0384, 10.0384, 10.0384] +24-11-19 20:38:54 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:54 | D | sum error = [ 161.8735, 171.6996, 182.1408, 193.0960, 204.5342] +24-11-19 20:38:54 | D | best error = [ 10.0384, 10.0384, 10.0384, 10.0384, 10.0384] +24-11-19 20:38:54 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:54 | D | sum error = [ 216.6283, 229.3815, 242.7829, 256.8596, 271.6999] +24-11-19 20:38:54 | D | best error = [ 10.0384, 10.0384, 10.0384, 10.0384, 10.0384] +24-11-19 20:38:54 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:54 | D | sum error = [ 287.2098, 303.5143, 320.6051, 338.5512, 357.3303] +24-11-19 20:38:54 | D | best error = [ 10.0384, 10.0384, 10.0384, 10.0384, 10.0384] +24-11-19 20:38:54 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:54 | D | sum error = [ 376.9414, 397.5112, 419.0883, 441.5718, 465.0506] +24-11-19 20:38:54 | D | best error = [ 10.0384, 10.0384, 10.0384, 10.0384, 10.0384] +24-11-19 20:38:54 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:54 | D | sum error = [ 489.5325, 515.1196, 541.7409, 569.4148, 598.1579] +24-11-19 20:38:54 | D | best error = [ 10.0384, 10.0384, 10.0384, 10.0384, 10.0384] +24-11-19 20:38:54 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:54 | D | sum error = [ 627.9415, 658.8230, 690.8601, 724.0057, 758.3965] +24-11-19 20:38:54 | D | best error = [ 10.0384, 10.0384, 10.0384, 10.0384, 10.0384] +24-11-19 20:38:54 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:54 | D | sum error = [ 793.9475, 830.6744, 868.5961, 907.7679, 948.1983] +24-11-19 20:38:54 | D | best error = [ 10.0384, 10.0384, 10.0384, 10.0384, 10.0384] +24-11-19 20:38:54 | D | + error = [10.0384] +24-11-19 20:38:54 | D | - Calibrating model.layers.28.mlp.down_proj.weight +24-11-19 20:38:54 | D | + w: sint8 +24-11-19 20:38:54 | D | + x: None +24-11-19 20:38:54 | D | + y: None +24-11-19 20:38:54 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:54 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:38:54 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:38:54 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:38:54 | D | - range ratio = [ 1.0000] +24-11-19 20:38:54 | D | sum error = [ 1.8314] +24-11-19 20:38:54 | D | best error = [ 1.8314] +24-11-19 20:38:56 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:56 | D | sum error = [ 1.8174, 1.7947, 1.7822, 1.7744, 1.7616] +24-11-19 20:38:56 | D | best error = [ 1.7115, 1.6609, 1.6298, 1.6082, 1.5911] +24-11-19 20:38:56 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:56 | D | sum error = [ 1.7593, 1.7630, 1.7662, 1.7763, 1.7965] +24-11-19 20:38:56 | D | best error = [ 1.5777, 1.5675, 1.5587, 1.5519, 1.5472] +24-11-19 20:38:56 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:56 | D | sum error = [ 1.8225, 1.8547, 1.8861, 1.9365, 1.9928] +24-11-19 20:38:56 | D | best error = [ 1.5437, 1.5408, 1.5386, 1.5369, 1.5358] +24-11-19 20:38:56 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:56 | D | sum error = [ 2.0648, 2.1429, 2.2353, 2.3479, 2.4633] +24-11-19 20:38:56 | D | best error = [ 1.5351, 1.5344, 1.5342, 1.5339, 1.5338] +24-11-19 20:38:56 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:56 | D | sum error = [ 2.5968, 2.7474, 2.9092, 3.0909, 3.2832] +24-11-19 20:38:56 | D | best error = [ 1.5338, 1.5337, 1.5337, 1.5337, 1.5336] +24-11-19 20:38:56 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:56 | D | sum error = [ 3.4945, 3.7277, 3.9743, 4.2460, 4.5365] +24-11-19 20:38:56 | D | best error = [ 1.5336, 1.5336, 1.5336, 1.5336, 1.5336] +24-11-19 20:38:56 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:56 | D | sum error = [ 4.8392, 5.1780, 5.5254, 5.9120, 6.3132] +24-11-19 20:38:56 | D | best error = [ 1.5336, 1.5336, 1.5336, 1.5336, 1.5336] +24-11-19 20:38:56 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:56 | D | sum error = [ 6.7457, 7.2102, 7.6977, 8.2161, 8.7694] +24-11-19 20:38:56 | D | best error = [ 1.5336, 1.5336, 1.5336, 1.5336, 1.5336] +24-11-19 20:38:56 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:56 | D | sum error = [ 9.3519, 9.9748, 10.6355, 11.3306, 12.0741] +24-11-19 20:38:56 | D | best error = [ 1.5336, 1.5336, 1.5336, 1.5336, 1.5336] +24-11-19 20:38:56 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:56 | D | sum error = [ 12.8535, 13.6817, 14.5562, 15.4777, 16.4549] +24-11-19 20:38:56 | D | best error = [ 1.5336, 1.5336, 1.5336, 1.5336, 1.5336] +24-11-19 20:38:56 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:56 | D | sum error = [ 17.4819, 18.5714, 19.7177, 20.9273, 22.1990] +24-11-19 20:38:56 | D | best error = [ 1.5336, 1.5336, 1.5336, 1.5336, 1.5336] +24-11-19 20:38:56 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:56 | D | sum error = [ 23.5410, 24.9512, 26.4327, 27.9860, 29.6209] +24-11-19 20:38:56 | D | best error = [ 1.5336, 1.5336, 1.5336, 1.5336, 1.5336] +24-11-19 20:38:56 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:56 | D | sum error = [ 31.3362, 33.1326, 35.0184, 36.9952, 39.0652] +24-11-19 20:38:56 | D | best error = [ 1.5336, 1.5336, 1.5336, 1.5336, 1.5336] +24-11-19 20:38:56 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:56 | D | sum error = [ 41.2321, 43.5007, 45.8734, 48.3613, 50.9597] +24-11-19 20:38:56 | D | best error = [ 1.5336, 1.5336, 1.5336, 1.5336, 1.5336] +24-11-19 20:38:56 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:56 | D | sum error = [ 53.6731, 56.5083, 59.4665, 62.5479, 65.7600] +24-11-19 20:38:56 | D | best error = [ 1.5336, 1.5336, 1.5336, 1.5336, 1.5336] +24-11-19 20:38:56 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:56 | D | sum error = [ 69.1042, 72.5858, 76.2097, 79.9787, 83.8936] +24-11-19 20:38:56 | D | best error = [ 1.5336, 1.5336, 1.5336, 1.5336, 1.5336] +24-11-19 20:38:56 | D | + error = [1.5336] +24-11-19 20:38:56 | D | - Quantizing model.layers.28.self_attn.q_proj.weight +24-11-19 20:38:56 | D | - Quantizing model.layers.28.self_attn.k_proj.weight +24-11-19 20:38:57 | D | - Quantizing model.layers.28.self_attn.v_proj.weight +24-11-19 20:38:58 | D | - Quantizing model.layers.28.self_attn.o_proj.weight +24-11-19 20:38:59 | D | - Quantizing model.layers.28.mlp.up_proj.weight +24-11-19 20:39:00 | D | - Quantizing model.layers.28.mlp.gate_proj.weight +24-11-19 20:39:01 | D | - Quantizing model.layers.28.mlp.down_proj.weight +24-11-19 20:39:11 | D | - Quantizing layer model.layers.29 +24-11-19 20:39:11 | D | - Calibrating model.layers.29.self_attn.q_proj.weight +24-11-19 20:39:11 | D | + w: sint8 +24-11-19 20:39:11 | D | + x: None +24-11-19 20:39:11 | D | + y: None +24-11-19 20:39:11 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:39:11 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:39:11 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:39:12 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:39:12 | D | - range ratio = [ 1.0000] +24-11-19 20:39:12 | D | sum error = [ 9.8007] +24-11-19 20:39:12 | D | best error = [ 9.8007] +24-11-19 20:39:24 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:24 | D | sum error = [ 8.6413, 8.5372, 9.2312, 8.7982, 8.8597] +24-11-19 20:39:24 | D | best error = [ 8.6413, 8.5372, 8.5372, 8.5372, 8.5372] +24-11-19 20:39:24 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:24 | D | sum error = [ 9.1201, 9.4876, 10.0636, 10.1000, 12.2656] +24-11-19 20:39:24 | D | best error = [ 8.5372, 8.5372, 8.5372, 8.5372, 8.5372] +24-11-19 20:39:24 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:24 | D | sum error = [ 12.2574, 13.0756, 14.1846, 14.7603, 15.9317] +24-11-19 20:39:24 | D | best error = [ 8.5372, 8.5372, 8.5372, 8.5372, 8.5372] +24-11-19 20:39:24 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:24 | D | sum error = [ 17.8440, 19.3765, 19.7160, 23.0082, 24.8505] +24-11-19 20:39:24 | D | best error = [ 8.5372, 8.5372, 8.5372, 8.5372, 8.5372] +24-11-19 20:39:24 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:24 | D | sum error = [ 26.8216, 29.9867, 31.2522, 34.6330, 36.7432] +24-11-19 20:39:24 | D | best error = [ 8.5372, 8.5372, 8.5372, 8.5372, 8.5372] +24-11-19 20:39:24 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:24 | D | sum error = [ 39.7299, 42.2360, 46.0631, 49.2441, 53.2900] +24-11-19 20:39:24 | D | best error = [ 8.5372, 8.5372, 8.5372, 8.5372, 8.5372] +24-11-19 20:39:24 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:24 | D | sum error = [ 56.3988, 60.9355, 65.2455, 70.2935, 75.0354] +24-11-19 20:39:24 | D | best error = [ 8.5372, 8.5372, 8.5372, 8.5372, 8.5372] +24-11-19 20:39:24 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:24 | D | sum error = [ 80.8250, 86.3027, 92.9200, 99.8302, 106.5794] +24-11-19 20:39:24 | D | best error = [ 8.5372, 8.5372, 8.5372, 8.5372, 8.5372] +24-11-19 20:39:24 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:24 | D | sum error = [ 114.0269, 122.7645, 130.8407, 140.5974, 151.0806] +24-11-19 20:39:24 | D | best error = [ 8.5372, 8.5372, 8.5372, 8.5372, 8.5372] +24-11-19 20:39:24 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:24 | D | sum error = [ 161.4366, 173.6137, 186.9956, 201.2555, 215.9920] +24-11-19 20:39:24 | D | best error = [ 8.5372, 8.5372, 8.5372, 8.5372, 8.5372] +24-11-19 20:39:24 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:24 | D | sum error = [ 231.7140, 248.0460, 265.2202, 284.6879, 304.4190] +24-11-19 20:39:24 | D | best error = [ 8.5372, 8.5372, 8.5372, 8.5372, 8.5372] +24-11-19 20:39:24 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:24 | D | sum error = [ 325.8733, 349.7533, 374.7136, 402.2793, 432.6188] +24-11-19 20:39:24 | D | best error = [ 8.5372, 8.5372, 8.5372, 8.5372, 8.5372] +24-11-19 20:39:24 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:24 | D | sum error = [ 464.3630, 499.5440, 537.4014, 579.4733, 625.0604] +24-11-19 20:39:24 | D | best error = [ 8.5372, 8.5372, 8.5372, 8.5372, 8.5372] +24-11-19 20:39:24 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:24 | D | sum error = [ 675.2144, 728.8832, 788.8018, 854.2512, 925.9829] +24-11-19 20:39:24 | D | best error = [ 8.5372, 8.5372, 8.5372, 8.5372, 8.5372] +24-11-19 20:39:24 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:24 | D | sum error = [ 1003.1270, 1088.3188, 1180.9426, 1280.9718, 1389.8377] +24-11-19 20:39:24 | D | best error = [ 8.5372, 8.5372, 8.5372, 8.5372, 8.5372] +24-11-19 20:39:24 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:24 | D | sum error = [ 1507.9471, 1633.1477, 1767.2055, 1905.3205, 2051.5804] +24-11-19 20:39:24 | D | best error = [ 8.5372, 8.5372, 8.5372, 8.5372, 8.5372] +24-11-19 20:39:24 | D | + error = [8.5372] +24-11-19 20:39:24 | D | - Calibrating model.layers.29.self_attn.k_proj.weight +24-11-19 20:39:24 | D | + w: sint8 +24-11-19 20:39:24 | D | + x: None +24-11-19 20:39:24 | D | + y: None +24-11-19 20:39:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:39:24 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:39:24 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:39:24 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:39:24 | D | - range ratio = [ 1.0000] +24-11-19 20:39:24 | D | sum error = [ 8.6574] +24-11-19 20:39:24 | D | best error = [ 8.6574] +24-11-19 20:39:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:36 | D | sum error = [ 9.1479, 9.4793, 9.0136, 10.5626, 8.9972] +24-11-19 20:39:36 | D | best error = [ 8.6574, 8.6574, 8.6574, 8.6574, 8.6574] +24-11-19 20:39:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:36 | D | sum error = [ 9.1763, 11.4686, 10.1045, 10.8798, 11.1049] +24-11-19 20:39:36 | D | best error = [ 8.6574, 8.6574, 8.6574, 8.6574, 8.6574] +24-11-19 20:39:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:36 | D | sum error = [ 12.4531, 15.5599, 14.9588, 17.9919, 17.4151] +24-11-19 20:39:36 | D | best error = [ 8.6574, 8.6574, 8.6574, 8.6574, 8.6574] +24-11-19 20:39:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:36 | D | sum error = [ 15.7725, 17.4403, 21.2968, 25.1853, 23.1375] +24-11-19 20:39:36 | D | best error = [ 8.6574, 8.6574, 8.6574, 8.6574, 8.6574] +24-11-19 20:39:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:36 | D | sum error = [ 25.1588, 26.4831, 27.3866, 29.3573, 32.1256] +24-11-19 20:39:36 | D | best error = [ 8.6574, 8.6574, 8.6574, 8.6574, 8.6574] +24-11-19 20:39:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:36 | D | sum error = [ 33.4983, 37.1416, 38.8258, 42.0440, 45.1797] +24-11-19 20:39:36 | D | best error = [ 8.6574, 8.6574, 8.6574, 8.6574, 8.6574] +24-11-19 20:39:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:36 | D | sum error = [ 47.3098, 52.0494, 55.2273, 58.7484, 62.4132] +24-11-19 20:39:36 | D | best error = [ 8.6574, 8.6574, 8.6574, 8.6574, 8.6574] +24-11-19 20:39:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:36 | D | sum error = [ 66.1153, 71.1742, 75.6504, 82.1042, 88.6436] +24-11-19 20:39:36 | D | best error = [ 8.6574, 8.6574, 8.6574, 8.6574, 8.6574] +24-11-19 20:39:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:36 | D | sum error = [ 95.5680, 105.1530, 114.3001, 122.6169, 135.6393] +24-11-19 20:39:36 | D | best error = [ 8.6574, 8.6574, 8.6574, 8.6574, 8.6574] +24-11-19 20:39:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:36 | D | sum error = [ 149.2730, 161.1956, 177.6301, 196.3413, 217.7614] +24-11-19 20:39:36 | D | best error = [ 8.6574, 8.6574, 8.6574, 8.6574, 8.6574] +24-11-19 20:39:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:36 | D | sum error = [ 235.7483, 261.2837, 284.7118, 310.3125, 336.5484] +24-11-19 20:39:36 | D | best error = [ 8.6574, 8.6574, 8.6574, 8.6574, 8.6574] +24-11-19 20:39:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:36 | D | sum error = [ 365.9509, 395.7162, 423.4380, 458.8096, 490.1299] +24-11-19 20:39:36 | D | best error = [ 8.6574, 8.6574, 8.6574, 8.6574, 8.6574] +24-11-19 20:39:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:36 | D | sum error = [ 525.8638, 563.0879, 604.9643, 653.1447, 698.0218] +24-11-19 20:39:36 | D | best error = [ 8.6574, 8.6574, 8.6574, 8.6574, 8.6574] +24-11-19 20:39:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:36 | D | sum error = [ 750.0184, 807.6994, 865.8737, 929.9700, 1001.9002] +24-11-19 20:39:36 | D | best error = [ 8.6574, 8.6574, 8.6574, 8.6574, 8.6574] +24-11-19 20:39:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:36 | D | sum error = [ 1075.4187, 1155.2369, 1246.9624, 1338.4311, 1443.6289] +24-11-19 20:39:36 | D | best error = [ 8.6574, 8.6574, 8.6574, 8.6574, 8.6574] +24-11-19 20:39:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:36 | D | sum error = [ 1554.4373, 1673.2873, 1796.9015, 1930.3644, 2066.4680] +24-11-19 20:39:36 | D | best error = [ 8.6574, 8.6574, 8.6574, 8.6574, 8.6574] +24-11-19 20:39:36 | D | + error = [8.6574] +24-11-19 20:39:36 | D | - Calibrating model.layers.29.self_attn.v_proj.weight +24-11-19 20:39:36 | D | + w: sint8 +24-11-19 20:39:36 | D | + x: None +24-11-19 20:39:36 | D | + y: None +24-11-19 20:39:36 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:36 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:39:36 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:39:36 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:39:36 | D | - range ratio = [ 1.0000] +24-11-19 20:39:36 | D | sum error = [ 3.1149] +24-11-19 20:39:36 | D | best error = [ 3.1149] +24-11-19 20:39:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:36 | D | sum error = [ 3.0927, 3.1116, 3.1180, 3.1330, 3.2178] +24-11-19 20:39:36 | D | best error = [ 2.7895, 2.6829, 2.6256, 2.5873, 2.5716] +24-11-19 20:39:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:36 | D | sum error = [ 3.3542, 3.4156, 3.5193, 3.7241, 3.9557] +24-11-19 20:39:36 | D | best error = [ 2.5640, 2.5612, 2.5596, 2.5593, 2.5591] +24-11-19 20:39:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:36 | D | sum error = [ 4.1555, 4.3858, 4.6795, 5.0064, 5.3168] +24-11-19 20:39:36 | D | best error = [ 2.5591, 2.5591, 2.5591, 2.5591, 2.5591] +24-11-19 20:39:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:36 | D | sum error = [ 5.6993, 6.1314, 6.5306, 7.0237, 7.5362] +24-11-19 20:39:36 | D | best error = [ 2.5591, 2.5591, 2.5591, 2.5591, 2.5591] +24-11-19 20:39:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:36 | D | sum error = [ 8.0198, 8.6529, 9.2421, 9.9587, 10.5965] +24-11-19 20:39:36 | D | best error = [ 2.5591, 2.5591, 2.5591, 2.5591, 2.5591] +24-11-19 20:39:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:36 | D | sum error = [ 11.3258, 12.1102, 12.8957, 13.7193, 14.6770] +24-11-19 20:39:36 | D | best error = [ 2.5591, 2.5591, 2.5591, 2.5591, 2.5591] +24-11-19 20:39:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:36 | D | sum error = [ 15.6528, 16.6096, 17.7047, 18.7653, 19.9497] +24-11-19 20:39:36 | D | best error = [ 2.5591, 2.5591, 2.5591, 2.5591, 2.5591] +24-11-19 20:39:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:36 | D | sum error = [ 21.1998, 22.4885, 23.8512, 25.2751, 26.7294] +24-11-19 20:39:36 | D | best error = [ 2.5591, 2.5591, 2.5591, 2.5591, 2.5591] +24-11-19 20:39:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:36 | D | sum error = [ 28.2841, 29.9464, 31.6356, 33.4241, 35.3310] +24-11-19 20:39:36 | D | best error = [ 2.5591, 2.5591, 2.5591, 2.5591, 2.5591] +24-11-19 20:39:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:36 | D | sum error = [ 37.3278, 39.3789, 41.5179, 43.8074, 46.2379] +24-11-19 20:39:36 | D | best error = [ 2.5591, 2.5591, 2.5591, 2.5591, 2.5591] +24-11-19 20:39:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:36 | D | sum error = [ 48.6435, 51.2387, 53.9410, 56.7271, 59.6315] +24-11-19 20:39:36 | D | best error = [ 2.5591, 2.5591, 2.5591, 2.5591, 2.5591] +24-11-19 20:39:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:36 | D | sum error = [ 62.6971, 65.8295, 69.0931, 72.4990, 75.9880] +24-11-19 20:39:36 | D | best error = [ 2.5591, 2.5591, 2.5591, 2.5591, 2.5591] +24-11-19 20:39:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:36 | D | sum error = [ 79.6560, 83.4536, 87.3658, 91.4357, 95.6330] +24-11-19 20:39:36 | D | best error = [ 2.5591, 2.5591, 2.5591, 2.5591, 2.5591] +24-11-19 20:39:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:36 | D | sum error = [ 100.0009, 104.5090, 109.1727, 114.0242, 119.0021] +24-11-19 20:39:36 | D | best error = [ 2.5591, 2.5591, 2.5591, 2.5591, 2.5591] +24-11-19 20:39:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:36 | D | sum error = [ 124.1563, 129.4579, 134.9228, 140.5584, 146.3725] +24-11-19 20:39:36 | D | best error = [ 2.5591, 2.5591, 2.5591, 2.5591, 2.5591] +24-11-19 20:39:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:36 | D | sum error = [ 152.3370, 158.4865, 164.7962, 171.3020, 177.9759] +24-11-19 20:39:36 | D | best error = [ 2.5591, 2.5591, 2.5591, 2.5591, 2.5591] +24-11-19 20:39:36 | D | + error = [2.5591] +24-11-19 20:39:37 | D | - Calibrating model.layers.29.self_attn.o_proj.weight +24-11-19 20:39:37 | D | + w: sint8 +24-11-19 20:39:37 | D | + x: None +24-11-19 20:39:37 | D | + y: None +24-11-19 20:39:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:37 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:39:37 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:39:37 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:39:37 | D | - range ratio = [ 1.0000] +24-11-19 20:39:37 | D | sum error = [ 0.9301] +24-11-19 20:39:37 | D | best error = [ 0.9301] +24-11-19 20:39:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:37 | D | sum error = [ 0.9242, 0.9300, 0.9297, 0.9375, 0.9486] +24-11-19 20:39:37 | D | best error = [ 0.8409, 0.8043, 0.7831, 0.7689, 0.7602] +24-11-19 20:39:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:37 | D | sum error = [ 0.9733, 0.9996, 1.0290, 1.0752, 1.1220] +24-11-19 20:39:37 | D | best error = [ 0.7539, 0.7490, 0.7457, 0.7433, 0.7414] +24-11-19 20:39:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:37 | D | sum error = [ 1.1820, 1.2408, 1.3168, 1.3840, 1.4702] +24-11-19 20:39:37 | D | best error = [ 0.7402, 0.7392, 0.7385, 0.7381, 0.7377] +24-11-19 20:39:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:37 | D | sum error = [ 1.5602, 1.6652, 1.7759, 1.8849, 2.0047] +24-11-19 20:39:37 | D | best error = [ 0.7376, 0.7374, 0.7372, 0.7371, 0.7371] +24-11-19 20:39:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:37 | D | sum error = [ 2.1384, 2.2796, 2.4139, 2.5785, 2.7459] +24-11-19 20:39:37 | D | best error = [ 0.7370, 0.7370, 0.7370, 0.7370, 0.7369] +24-11-19 20:39:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:37 | D | sum error = [ 2.9150, 3.1003, 3.2928, 3.4998, 3.7108] +24-11-19 20:39:37 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:39:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:37 | D | sum error = [ 3.9388, 4.1777, 4.4292, 4.6916, 4.9676] +24-11-19 20:39:37 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:39:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:37 | D | sum error = [ 5.2606, 5.5712, 5.8900, 6.2373, 6.5895] +24-11-19 20:39:37 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:39:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:37 | D | sum error = [ 6.9723, 7.3718, 7.7874, 8.2377, 8.6990] +24-11-19 20:39:37 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:39:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:37 | D | sum error = [ 9.1896, 9.7055, 10.2473, 10.8189, 11.4178] +24-11-19 20:39:37 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:39:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:37 | D | sum error = [ 12.0547, 12.7327, 13.4436, 14.1930, 14.9881] +24-11-19 20:39:37 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:39:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:37 | D | sum error = [ 15.8177, 16.6976, 17.6181, 18.5892, 19.6066] +24-11-19 20:39:37 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:39:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:37 | D | sum error = [ 20.6808, 21.8071, 22.9935, 24.2396, 25.5451] +24-11-19 20:39:37 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:39:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:37 | D | sum error = [ 26.9179, 28.3553, 29.8666, 31.4486, 33.1043] +24-11-19 20:39:37 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:39:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:37 | D | sum error = [ 34.8326, 36.6407, 38.5260, 40.4906, 42.5396] +24-11-19 20:39:37 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:39:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:37 | D | sum error = [ 44.6768, 46.8970, 49.2113, 51.6101, 54.1061] +24-11-19 20:39:37 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:39:37 | D | + error = [0.7369] +24-11-19 20:39:37 | D | - Calibrating model.layers.29.mlp.up_proj.weight +24-11-19 20:39:37 | D | + w: sint8 +24-11-19 20:39:37 | D | + x: None +24-11-19 20:39:37 | D | + y: None +24-11-19 20:39:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:37 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:39:37 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:39:37 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:39:38 | D | - range ratio = [ 1.0000] +24-11-19 20:39:38 | D | sum error = [ 10.0569] +24-11-19 20:39:38 | D | best error = [ 10.0569] +24-11-19 20:39:39 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:39 | D | sum error = [ 9.9565, 9.9983, 9.9805, 10.0937, 10.2838] +24-11-19 20:39:39 | D | best error = [ 8.8173, 8.4239, 8.2225, 8.1148, 8.0550] +24-11-19 20:39:39 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:39 | D | sum error = [ 10.5881, 10.9228, 11.3831, 11.8718, 12.4702] +24-11-19 20:39:39 | D | best error = [ 8.0236, 8.0085, 8.0030, 8.0008, 7.9998] +24-11-19 20:39:39 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:39 | D | sum error = [ 13.2921, 14.0659, 14.9314, 15.9726, 17.1434] +24-11-19 20:39:39 | D | best error = [ 7.9997, 7.9997, 7.9997, 7.9997, 7.9997] +24-11-19 20:39:39 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:39 | D | sum error = [ 18.3091, 19.5582, 21.0149, 22.5720, 24.1442] +24-11-19 20:39:39 | D | best error = [ 7.9997, 7.9997, 7.9997, 7.9997, 7.9997] +24-11-19 20:39:39 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:39 | D | sum error = [ 25.8793, 27.7163, 29.6486, 31.8075, 33.9738] +24-11-19 20:39:39 | D | best error = [ 7.9997, 7.9997, 7.9997, 7.9997, 7.9997] +24-11-19 20:39:39 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:39 | D | sum error = [ 36.3131, 38.7939, 41.4478, 44.1961, 47.1648] +24-11-19 20:39:39 | D | best error = [ 7.9997, 7.9997, 7.9997, 7.9997, 7.9997] +24-11-19 20:39:39 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:39 | D | sum error = [ 50.2273, 53.5448, 56.9259, 60.5385, 64.3845] +24-11-19 20:39:39 | D | best error = [ 7.9997, 7.9997, 7.9997, 7.9997, 7.9997] +24-11-19 20:39:39 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:39 | D | sum error = [ 68.4031, 72.6574, 77.0940, 81.7902, 86.7178] +24-11-19 20:39:39 | D | best error = [ 7.9997, 7.9997, 7.9997, 7.9997, 7.9997] +24-11-19 20:39:39 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:39 | D | sum error = [ 91.9053, 97.3362, 102.9693, 108.9873, 115.1842] +24-11-19 20:39:39 | D | best error = [ 7.9997, 7.9997, 7.9997, 7.9997, 7.9997] +24-11-19 20:39:39 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:39 | D | sum error = [ 121.7346, 128.5925, 135.7547, 143.2418, 151.1014] +24-11-19 20:39:39 | D | best error = [ 7.9997, 7.9997, 7.9997, 7.9997, 7.9997] +24-11-19 20:39:39 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:39 | D | sum error = [ 159.3329, 167.9365, 176.9115, 186.3041, 196.1016] +24-11-19 20:39:39 | D | best error = [ 7.9997, 7.9997, 7.9997, 7.9997, 7.9997] +24-11-19 20:39:39 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:39 | D | sum error = [ 206.2847, 216.9665, 228.0825, 239.6946, 251.7451] +24-11-19 20:39:39 | D | best error = [ 7.9997, 7.9997, 7.9997, 7.9997, 7.9997] +24-11-19 20:39:39 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:39 | D | sum error = [ 264.2807, 277.3572, 290.9102, 304.9546, 319.5532] +24-11-19 20:39:39 | D | best error = [ 7.9997, 7.9997, 7.9997, 7.9997, 7.9997] +24-11-19 20:39:39 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:39 | D | sum error = [ 334.6943, 350.4384, 366.7315, 383.6389, 401.1320] +24-11-19 20:39:39 | D | best error = [ 7.9997, 7.9997, 7.9997, 7.9997, 7.9997] +24-11-19 20:39:39 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:39 | D | sum error = [ 419.2687, 437.9880, 457.3796, 477.3680, 497.9896] +24-11-19 20:39:39 | D | best error = [ 7.9997, 7.9997, 7.9997, 7.9997, 7.9997] +24-11-19 20:39:39 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:39 | D | sum error = [ 519.2509, 541.1430, 563.7309, 586.9751, 610.9084] +24-11-19 20:39:39 | D | best error = [ 7.9997, 7.9997, 7.9997, 7.9997, 7.9997] +24-11-19 20:39:39 | D | + error = [7.9997] +24-11-19 20:39:39 | D | - Calibrating model.layers.29.mlp.gate_proj.weight +24-11-19 20:39:39 | D | + w: sint8 +24-11-19 20:39:39 | D | + x: None +24-11-19 20:39:39 | D | + y: None +24-11-19 20:39:39 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:39 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:39:39 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:39:39 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:39:39 | D | - range ratio = [ 1.0000] +24-11-19 20:39:39 | D | sum error = [ 12.6718] +24-11-19 20:39:39 | D | best error = [ 12.6718] +24-11-19 20:39:40 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:40 | D | sum error = [ 12.6274, 12.6184, 12.6613, 12.7894, 13.0657] +24-11-19 20:39:40 | D | best error = [ 11.1778, 10.6699, 10.4196, 10.2807, 10.2113] +24-11-19 20:39:40 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:40 | D | sum error = [ 13.4135, 13.8503, 14.3324, 15.0840, 15.9334] +24-11-19 20:39:40 | D | best error = [ 10.1727, 10.1539, 10.1436, 10.1405, 10.1394] +24-11-19 20:39:40 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:40 | D | sum error = [ 16.8199, 17.8234, 19.0298, 20.3271, 21.7966] +24-11-19 20:39:40 | D | best error = [ 10.1392, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:39:40 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:40 | D | sum error = [ 23.2844, 24.9623, 26.7624, 28.7050, 30.8306] +24-11-19 20:39:40 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:39:40 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:40 | D | sum error = [ 33.0874, 35.4768, 37.9878, 40.6891, 43.6869] +24-11-19 20:39:40 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:39:40 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:40 | D | sum error = [ 46.6627, 49.9487, 53.3804, 57.0254, 60.9557] +24-11-19 20:39:40 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:39:40 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:40 | D | sum error = [ 65.0787, 69.4991, 74.1641, 79.0766, 84.3353] +24-11-19 20:39:40 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:39:40 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:40 | D | sum error = [ 89.8276, 95.7191, 101.9166, 108.4521, 115.3683] +24-11-19 20:39:40 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:39:40 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:40 | D | sum error = [ 122.7739, 130.5422, 138.7547, 147.4749, 156.7429] +24-11-19 20:39:40 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:39:40 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:40 | D | sum error = [ 166.4190, 176.7219, 187.5992, 199.0649, 211.1486] +24-11-19 20:39:40 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:39:40 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:40 | D | sum error = [ 223.9058, 237.2767, 251.3675, 266.2417, 281.8558] +24-11-19 20:39:40 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:39:40 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:40 | D | sum error = [ 298.3487, 315.5434, 333.7060, 352.8110, 372.7923] +24-11-19 20:39:40 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:39:40 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:40 | D | sum error = [ 393.7592, 415.7597, 438.8584, 462.9880, 488.2317] +24-11-19 20:39:40 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:39:40 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:40 | D | sum error = [ 514.5727, 542.0843, 570.7697, 600.6041, 631.5851] +24-11-19 20:39:40 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:39:40 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:40 | D | sum error = [ 663.8551, 697.3429, 732.0318, 767.9415, 805.0884] +24-11-19 20:39:40 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:39:40 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:40 | D | sum error = [ 843.5115, 883.1641, 924.1212, 966.3441, 1009.8062] +24-11-19 20:39:40 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:39:40 | D | + error = [10.1391] +24-11-19 20:39:40 | D | - Calibrating model.layers.29.mlp.down_proj.weight +24-11-19 20:39:40 | D | + w: sint8 +24-11-19 20:39:40 | D | + x: None +24-11-19 20:39:40 | D | + y: None +24-11-19 20:39:40 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:40 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:39:40 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:39:40 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:39:41 | D | - range ratio = [ 1.0000] +24-11-19 20:39:41 | D | sum error = [ 2.3909] +24-11-19 20:39:41 | D | best error = [ 2.3909] +24-11-19 20:39:42 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:42 | D | sum error = [ 2.3696, 2.3537, 2.3537, 2.3569, 2.3599] +24-11-19 20:39:42 | D | best error = [ 2.2139, 2.1402, 2.1009, 2.0718, 2.0489] +24-11-19 20:39:42 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:42 | D | sum error = [ 2.4010, 2.4190, 2.4712, 2.5235, 2.5747] +24-11-19 20:39:42 | D | best error = [ 2.0313, 2.0181, 2.0062, 1.9960, 1.9879] +24-11-19 20:39:42 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:42 | D | sum error = [ 2.6619, 2.7412, 2.8463, 2.9729, 3.0819] +24-11-19 20:39:42 | D | best error = [ 1.9822, 1.9772, 1.9732, 1.9708, 1.9689] +24-11-19 20:39:42 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:42 | D | sum error = [ 3.2225, 3.3789, 3.5426, 3.7249, 3.9093] +24-11-19 20:39:42 | D | best error = [ 1.9675, 1.9665, 1.9658, 1.9656, 1.9653] +24-11-19 20:39:42 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:42 | D | sum error = [ 4.1149, 4.3337, 4.5678, 4.8117, 5.0759] +24-11-19 20:39:42 | D | best error = [ 1.9652, 1.9651, 1.9651, 1.9651, 1.9649] +24-11-19 20:39:42 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:42 | D | sum error = [ 5.3667, 5.6572, 5.9787, 6.3269, 6.6847] +24-11-19 20:39:42 | D | best error = [ 1.9649, 1.9649, 1.9649, 1.9649, 1.9649] +24-11-19 20:39:42 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:42 | D | sum error = [ 7.0569, 7.4607, 7.8910, 8.3404, 8.8207] +24-11-19 20:39:42 | D | best error = [ 1.9649, 1.9649, 1.9649, 1.9649, 1.9649] +24-11-19 20:39:42 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:42 | D | sum error = [ 9.3324, 9.8780, 10.4475, 11.0556, 11.6976] +24-11-19 20:39:42 | D | best error = [ 1.9649, 1.9649, 1.9649, 1.9649, 1.9649] +24-11-19 20:39:42 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:42 | D | sum error = [ 12.3810, 13.1086, 13.8738, 14.6842, 15.5392] +24-11-19 20:39:42 | D | best error = [ 1.9649, 1.9649, 1.9649, 1.9649, 1.9649] +24-11-19 20:39:42 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:42 | D | sum error = [ 16.4428, 17.4002, 18.4072, 19.4801, 20.6072] +24-11-19 20:39:42 | D | best error = [ 1.9649, 1.9649, 1.9649, 1.9649, 1.9649] +24-11-19 20:39:42 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:42 | D | sum error = [ 21.7960, 23.0520, 24.3765, 25.7704, 27.2474] +24-11-19 20:39:42 | D | best error = [ 1.9649, 1.9649, 1.9649, 1.9649, 1.9649] +24-11-19 20:39:42 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:42 | D | sum error = [ 28.7963, 30.4357, 32.1547, 33.9658, 35.8779] +24-11-19 20:39:42 | D | best error = [ 1.9649, 1.9649, 1.9649, 1.9649, 1.9649] +24-11-19 20:39:42 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:42 | D | sum error = [ 37.8935, 40.0069, 42.2266, 44.5538, 46.9980] +24-11-19 20:39:42 | D | best error = [ 1.9649, 1.9649, 1.9649, 1.9649, 1.9649] +24-11-19 20:39:42 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:42 | D | sum error = [ 49.5574, 52.2400, 55.0617, 58.0052, 61.0944] +24-11-19 20:39:42 | D | best error = [ 1.9649, 1.9649, 1.9649, 1.9649, 1.9649] +24-11-19 20:39:42 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:42 | D | sum error = [ 64.3224, 67.7024, 71.2328, 74.9259, 78.7782] +24-11-19 20:39:42 | D | best error = [ 1.9649, 1.9649, 1.9649, 1.9649, 1.9649] +24-11-19 20:39:42 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:42 | D | sum error = [ 82.7957, 86.9839, 91.3521, 95.8874, 100.6177] +24-11-19 20:39:42 | D | best error = [ 1.9649, 1.9649, 1.9649, 1.9649, 1.9649] +24-11-19 20:39:42 | D | + error = [1.9649] +24-11-19 20:39:42 | D | - Quantizing model.layers.29.self_attn.q_proj.weight +24-11-19 20:39:43 | D | - Quantizing model.layers.29.self_attn.k_proj.weight +24-11-19 20:39:43 | D | - Quantizing model.layers.29.self_attn.v_proj.weight +24-11-19 20:39:44 | D | - Quantizing model.layers.29.self_attn.o_proj.weight +24-11-19 20:39:45 | D | - Quantizing model.layers.29.mlp.up_proj.weight +24-11-19 20:39:46 | D | - Quantizing model.layers.29.mlp.gate_proj.weight +24-11-19 20:39:47 | D | - Quantizing model.layers.29.mlp.down_proj.weight +24-11-19 20:39:57 | D | - Quantizing layer model.layers.30 +24-11-19 20:39:57 | D | - Calibrating model.layers.30.self_attn.q_proj.weight +24-11-19 20:39:57 | D | + w: sint8 +24-11-19 20:39:57 | D | + x: None +24-11-19 20:39:57 | D | + y: None +24-11-19 20:39:57 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:39:57 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:39:57 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:39:57 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:39:57 | D | - range ratio = [ 1.0000] +24-11-19 20:39:57 | D | sum error = [ 10.6490] +24-11-19 20:39:57 | D | best error = [ 10.6490] +24-11-19 20:40:10 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:10 | D | sum error = [ 10.8660, 10.9687, 10.7774, 10.9566, 11.7696] +24-11-19 20:40:10 | D | best error = [ 10.6490, 10.6490, 10.6490, 10.6490, 10.6490] +24-11-19 20:40:10 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:10 | D | sum error = [ 10.9963, 12.2304, 12.0805, 12.7654, 14.0568] +24-11-19 20:40:10 | D | best error = [ 10.6490, 10.6490, 10.6490, 10.6490, 10.6490] +24-11-19 20:40:10 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:10 | D | sum error = [ 14.1874, 15.0674, 15.8615, 17.0766, 18.4051] +24-11-19 20:40:10 | D | best error = [ 10.6490, 10.6490, 10.6490, 10.6490, 10.6490] +24-11-19 20:40:10 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:10 | D | sum error = [ 19.5510, 21.5559, 23.7147, 25.5232, 27.6429] +24-11-19 20:40:10 | D | best error = [ 10.6490, 10.6490, 10.6490, 10.6490, 10.6490] +24-11-19 20:40:10 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:10 | D | sum error = [ 29.9007, 32.5964, 34.8266, 38.2357, 41.7059] +24-11-19 20:40:10 | D | best error = [ 10.6490, 10.6490, 10.6490, 10.6490, 10.6490] +24-11-19 20:40:10 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:10 | D | sum error = [ 45.5961, 49.0155, 53.6258, 57.9158, 62.7850] +24-11-19 20:40:10 | D | best error = [ 10.6490, 10.6490, 10.6490, 10.6490, 10.6490] +24-11-19 20:40:10 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:10 | D | sum error = [ 67.6272, 73.7906, 78.9393, 85.6183, 92.2118] +24-11-19 20:40:10 | D | best error = [ 10.6490, 10.6490, 10.6490, 10.6490, 10.6490] +24-11-19 20:40:10 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:10 | D | sum error = [ 99.5707, 107.2495, 115.3895, 124.5541, 134.0861] +24-11-19 20:40:10 | D | best error = [ 10.6490, 10.6490, 10.6490, 10.6490, 10.6490] +24-11-19 20:40:10 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:10 | D | sum error = [ 143.9319, 154.8437, 166.1281, 179.4038, 192.9308] +24-11-19 20:40:10 | D | best error = [ 10.6490, 10.6490, 10.6490, 10.6490, 10.6490] +24-11-19 20:40:10 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:10 | D | sum error = [ 206.0731, 220.9988, 237.3545, 254.2834, 273.7479] +24-11-19 20:40:10 | D | best error = [ 10.6490, 10.6490, 10.6490, 10.6490, 10.6490] +24-11-19 20:40:10 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:10 | D | sum error = [ 293.0941, 314.8797, 338.2498, 363.0349, 390.6287] +24-11-19 20:40:10 | D | best error = [ 10.6490, 10.6490, 10.6490, 10.6490, 10.6490] +24-11-19 20:40:10 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:10 | D | sum error = [ 420.0878, 451.8220, 484.8532, 520.8460, 559.5095] +24-11-19 20:40:10 | D | best error = [ 10.6490, 10.6490, 10.6490, 10.6490, 10.6490] +24-11-19 20:40:10 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:10 | D | sum error = [ 601.5061, 645.5733, 693.3628, 744.4686, 798.5877] +24-11-19 20:40:10 | D | best error = [ 10.6490, 10.6490, 10.6490, 10.6490, 10.6490] +24-11-19 20:40:10 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:10 | D | sum error = [ 856.2657, 918.9836, 984.7486, 1054.3144, 1130.0948] +24-11-19 20:40:10 | D | best error = [ 10.6490, 10.6490, 10.6490, 10.6490, 10.6490] +24-11-19 20:40:10 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:10 | D | sum error = [ 1210.0018, 1294.5826, 1383.3664, 1476.8676, 1574.4173] +24-11-19 20:40:10 | D | best error = [ 10.6490, 10.6490, 10.6490, 10.6490, 10.6490] +24-11-19 20:40:10 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:10 | D | sum error = [ 1674.9122, 1778.5785, 1882.9600, 1988.1127, 2093.0899] +24-11-19 20:40:10 | D | best error = [ 10.6490, 10.6490, 10.6490, 10.6490, 10.6490] +24-11-19 20:40:10 | D | + error = [10.6490] +24-11-19 20:40:10 | D | - Calibrating model.layers.30.self_attn.k_proj.weight +24-11-19 20:40:10 | D | + w: sint8 +24-11-19 20:40:10 | D | + x: None +24-11-19 20:40:10 | D | + y: None +24-11-19 20:40:10 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:40:10 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:40:10 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:40:10 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:40:10 | D | - range ratio = [ 1.0000] +24-11-19 20:40:10 | D | sum error = [ 11.9151] +24-11-19 20:40:10 | D | best error = [ 11.9151] +24-11-19 20:40:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:22 | D | sum error = [ 9.9890, 10.8150, 10.1245, 11.3712, 11.0589] +24-11-19 20:40:22 | D | best error = [ 9.9890, 9.9890, 9.9890, 9.9890, 9.9890] +24-11-19 20:40:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:22 | D | sum error = [ 11.2645, 13.5411, 12.0084, 12.2418, 13.7621] +24-11-19 20:40:22 | D | best error = [ 9.9890, 9.9890, 9.9890, 9.9890, 9.9890] +24-11-19 20:40:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:22 | D | sum error = [ 14.3362, 15.1715, 16.5015, 17.2170, 18.3921] +24-11-19 20:40:22 | D | best error = [ 9.9890, 9.9890, 9.9890, 9.9890, 9.9890] +24-11-19 20:40:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:22 | D | sum error = [ 20.9788, 21.0744, 22.9462, 23.8161, 25.8395] +24-11-19 20:40:22 | D | best error = [ 9.9890, 9.9890, 9.9890, 9.9890, 9.9890] +24-11-19 20:40:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:22 | D | sum error = [ 28.4292, 30.5364, 31.4577, 34.3134, 36.9604] +24-11-19 20:40:22 | D | best error = [ 9.9890, 9.9890, 9.9890, 9.9890, 9.9890] +24-11-19 20:40:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:22 | D | sum error = [ 39.2314, 42.0111, 45.3133, 50.9911, 53.5053] +24-11-19 20:40:22 | D | best error = [ 9.9890, 9.9890, 9.9890, 9.9890, 9.9890] +24-11-19 20:40:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:22 | D | sum error = [ 58.6045, 62.4130, 68.3953, 72.7361, 78.1068] +24-11-19 20:40:22 | D | best error = [ 9.9890, 9.9890, 9.9890, 9.9890, 9.9890] +24-11-19 20:40:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:22 | D | sum error = [ 83.9795, 89.0422, 97.4910, 104.7483, 112.7819] +24-11-19 20:40:22 | D | best error = [ 9.9890, 9.9890, 9.9890, 9.9890, 9.9890] +24-11-19 20:40:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:22 | D | sum error = [ 121.4211, 132.6223, 140.9923, 153.0347, 163.9068] +24-11-19 20:40:22 | D | best error = [ 9.9890, 9.9890, 9.9890, 9.9890, 9.9890] +24-11-19 20:40:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:22 | D | sum error = [ 179.2562, 192.2938, 206.5993, 223.1120, 241.1493] +24-11-19 20:40:22 | D | best error = [ 9.9890, 9.9890, 9.9890, 9.9890, 9.9890] +24-11-19 20:40:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:22 | D | sum error = [ 259.2563, 279.6224, 301.4433, 322.6058, 347.9066] +24-11-19 20:40:22 | D | best error = [ 9.9890, 9.9890, 9.9890, 9.9890, 9.9890] +24-11-19 20:40:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:22 | D | sum error = [ 375.3820, 404.6288, 435.8471, 469.4100, 505.5794] +24-11-19 20:40:22 | D | best error = [ 9.9890, 9.9890, 9.9890, 9.9890, 9.9890] +24-11-19 20:40:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:22 | D | sum error = [ 544.1284, 583.5835, 626.7285, 670.3157, 717.6899] +24-11-19 20:40:22 | D | best error = [ 9.9890, 9.9890, 9.9890, 9.9890, 9.9890] +24-11-19 20:40:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:22 | D | sum error = [ 768.5632, 822.1977, 880.2745, 943.7353, 1009.6318] +24-11-19 20:40:22 | D | best error = [ 9.9890, 9.9890, 9.9890, 9.9890, 9.9890] +24-11-19 20:40:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:22 | D | sum error = [ 1080.9890, 1153.9061, 1237.3234, 1325.2565, 1415.9208] +24-11-19 20:40:22 | D | best error = [ 9.9890, 9.9890, 9.9890, 9.9890, 9.9890] +24-11-19 20:40:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:22 | D | sum error = [ 1510.5047, 1615.0411, 1718.7737, 1830.2873, 1940.2050] +24-11-19 20:40:22 | D | best error = [ 9.9890, 9.9890, 9.9890, 9.9890, 9.9890] +24-11-19 20:40:22 | D | + error = [9.9890] +24-11-19 20:40:22 | D | - Calibrating model.layers.30.self_attn.v_proj.weight +24-11-19 20:40:22 | D | + w: sint8 +24-11-19 20:40:22 | D | + x: None +24-11-19 20:40:22 | D | + y: None +24-11-19 20:40:22 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:22 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:40:22 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:40:22 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:22 | D | - range ratio = [ 1.0000] +24-11-19 20:40:22 | D | sum error = [ 3.5822] +24-11-19 20:40:22 | D | best error = [ 3.5822] +24-11-19 20:40:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:23 | D | sum error = [ 3.5418, 3.5695, 3.5480, 3.5820, 3.7175] +24-11-19 20:40:23 | D | best error = [ 3.1899, 3.0592, 2.9837, 2.9485, 2.9287] +24-11-19 20:40:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:23 | D | sum error = [ 3.8241, 3.9135, 4.0931, 4.2655, 4.4558] +24-11-19 20:40:23 | D | best error = [ 2.9185, 2.9136, 2.9116, 2.9111, 2.9107] +24-11-19 20:40:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:23 | D | sum error = [ 4.7648, 5.0934, 5.3035, 5.7910, 6.1629] +24-11-19 20:40:23 | D | best error = [ 2.9107, 2.9107, 2.9107, 2.9107, 2.9107] +24-11-19 20:40:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:23 | D | sum error = [ 6.5848, 7.0688, 7.6117, 8.1759, 8.7577] +24-11-19 20:40:23 | D | best error = [ 2.9107, 2.9107, 2.9107, 2.9107, 2.9107] +24-11-19 20:40:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:23 | D | sum error = [ 9.4520, 10.0880, 10.7926, 11.5205, 12.3036] +24-11-19 20:40:23 | D | best error = [ 2.9107, 2.9107, 2.9107, 2.9107, 2.9107] +24-11-19 20:40:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:23 | D | sum error = [ 13.1817, 14.0470, 14.9998, 15.9812, 17.0098] +24-11-19 20:40:23 | D | best error = [ 2.9107, 2.9107, 2.9107, 2.9107, 2.9107] +24-11-19 20:40:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:23 | D | sum error = [ 18.0625, 19.1979, 20.3930, 21.5913, 22.9230] +24-11-19 20:40:23 | D | best error = [ 2.9107, 2.9107, 2.9107, 2.9107, 2.9107] +24-11-19 20:40:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:23 | D | sum error = [ 24.2763, 25.6696, 27.1606, 28.6842, 30.3046] +24-11-19 20:40:23 | D | best error = [ 2.9107, 2.9107, 2.9107, 2.9107, 2.9107] +24-11-19 20:40:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:23 | D | sum error = [ 32.0433, 33.8560, 35.7538, 37.6782, 39.7531] +24-11-19 20:40:23 | D | best error = [ 2.9107, 2.9107, 2.9107, 2.9107, 2.9107] +24-11-19 20:40:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:23 | D | sum error = [ 41.9464, 44.1774, 46.5496, 48.9894, 51.5440] +24-11-19 20:40:23 | D | best error = [ 2.9107, 2.9107, 2.9107, 2.9107, 2.9107] +24-11-19 20:40:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:23 | D | sum error = [ 54.1455, 56.9146, 59.8199, 62.8047, 65.8831] +24-11-19 20:40:23 | D | best error = [ 2.9107, 2.9107, 2.9107, 2.9107, 2.9107] +24-11-19 20:40:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:23 | D | sum error = [ 69.0575, 72.3469, 75.7311, 79.2635, 82.8955] +24-11-19 20:40:23 | D | best error = [ 2.9107, 2.9107, 2.9107, 2.9107, 2.9107] +24-11-19 20:40:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:23 | D | sum error = [ 86.6647, 90.5487, 94.5299, 98.6530, 102.8893] +24-11-19 20:40:23 | D | best error = [ 2.9107, 2.9107, 2.9107, 2.9107, 2.9107] +24-11-19 20:40:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:23 | D | sum error = [ 107.2624, 111.7821, 116.4396, 121.2632, 126.2130] +24-11-19 20:40:23 | D | best error = [ 2.9107, 2.9107, 2.9107, 2.9107, 2.9107] +24-11-19 20:40:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:23 | D | sum error = [ 131.2787, 136.5036, 141.8926, 147.4364, 153.1148] +24-11-19 20:40:23 | D | best error = [ 2.9107, 2.9107, 2.9107, 2.9107, 2.9107] +24-11-19 20:40:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:23 | D | sum error = [ 158.9535, 164.9293, 171.0564, 177.3113, 183.7093] +24-11-19 20:40:23 | D | best error = [ 2.9107, 2.9107, 2.9107, 2.9107, 2.9107] +24-11-19 20:40:23 | D | + error = [2.9107] +24-11-19 20:40:23 | D | - Calibrating model.layers.30.self_attn.o_proj.weight +24-11-19 20:40:23 | D | + w: sint8 +24-11-19 20:40:23 | D | + x: None +24-11-19 20:40:23 | D | + y: None +24-11-19 20:40:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:23 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:40:23 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:40:23 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:23 | D | - range ratio = [ 1.0000] +24-11-19 20:40:23 | D | sum error = [ 1.0640] +24-11-19 20:40:23 | D | best error = [ 1.0640] +24-11-19 20:40:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:23 | D | sum error = [ 1.0499, 1.0495, 1.0489, 1.0600, 1.0738] +24-11-19 20:40:23 | D | best error = [ 0.9750, 0.9390, 0.9177, 0.9046, 0.8958] +24-11-19 20:40:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:23 | D | sum error = [ 1.0876, 1.1214, 1.1579, 1.2033, 1.2539] +24-11-19 20:40:23 | D | best error = [ 0.8894, 0.8852, 0.8827, 0.8812, 0.8799] +24-11-19 20:40:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:23 | D | sum error = [ 1.3114, 1.3809, 1.4521, 1.5394, 1.6381] +24-11-19 20:40:23 | D | best error = [ 0.8789, 0.8784, 0.8780, 0.8777, 0.8776] +24-11-19 20:40:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:23 | D | sum error = [ 1.7341, 1.8444, 1.9600, 2.0891, 2.2237] +24-11-19 20:40:23 | D | best error = [ 0.8775, 0.8774, 0.8774, 0.8774, 0.8773] +24-11-19 20:40:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:23 | D | sum error = [ 2.3710, 2.5220, 2.6840, 2.8596, 3.0456] +24-11-19 20:40:23 | D | best error = [ 0.8773, 0.8773, 0.8773, 0.8773, 0.8773] +24-11-19 20:40:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:23 | D | sum error = [ 3.2313, 3.4365, 3.6553, 3.8870, 4.1241] +24-11-19 20:40:23 | D | best error = [ 0.8773, 0.8773, 0.8773, 0.8773, 0.8773] +24-11-19 20:40:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:23 | D | sum error = [ 4.3713, 4.6423, 4.9195, 5.2174, 5.5371] +24-11-19 20:40:23 | D | best error = [ 0.8773, 0.8773, 0.8773, 0.8773, 0.8773] +24-11-19 20:40:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:23 | D | sum error = [ 5.8671, 6.2108, 6.5721, 6.9601, 7.3617] +24-11-19 20:40:23 | D | best error = [ 0.8773, 0.8773, 0.8773, 0.8773, 0.8773] +24-11-19 20:40:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:23 | D | sum error = [ 7.7918, 8.2386, 8.7070, 9.2040, 9.7249] +24-11-19 20:40:23 | D | best error = [ 0.8773, 0.8773, 0.8773, 0.8773, 0.8773] +24-11-19 20:40:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:23 | D | sum error = [ 10.2760, 10.8496, 11.4569, 12.0917, 12.7603] +24-11-19 20:40:23 | D | best error = [ 0.8773, 0.8773, 0.8773, 0.8773, 0.8773] +24-11-19 20:40:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:23 | D | sum error = [ 13.4656, 14.2041, 14.9716, 15.7846, 16.6322] +24-11-19 20:40:23 | D | best error = [ 0.8773, 0.8773, 0.8773, 0.8773, 0.8773] +24-11-19 20:40:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:23 | D | sum error = [ 17.5201, 18.4514, 19.4288, 20.4533, 21.5267] +24-11-19 20:40:23 | D | best error = [ 0.8773, 0.8773, 0.8773, 0.8773, 0.8773] +24-11-19 20:40:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:23 | D | sum error = [ 22.6446, 23.8179, 25.0432, 26.3216, 27.6628] +24-11-19 20:40:23 | D | best error = [ 0.8773, 0.8773, 0.8773, 0.8773, 0.8773] +24-11-19 20:40:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:23 | D | sum error = [ 29.0656, 30.5346, 32.0676, 33.6691, 35.3380] +24-11-19 20:40:23 | D | best error = [ 0.8773, 0.8773, 0.8773, 0.8773, 0.8773] +24-11-19 20:40:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:23 | D | sum error = [ 37.0781, 38.8910, 40.7818, 42.7471, 44.7890] +24-11-19 20:40:23 | D | best error = [ 0.8773, 0.8773, 0.8773, 0.8773, 0.8773] +24-11-19 20:40:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:23 | D | sum error = [ 46.9091, 49.1108, 51.3974, 53.7655, 56.2223] +24-11-19 20:40:23 | D | best error = [ 0.8773, 0.8773, 0.8773, 0.8773, 0.8773] +24-11-19 20:40:23 | D | + error = [0.8773] +24-11-19 20:40:23 | D | - Calibrating model.layers.30.mlp.up_proj.weight +24-11-19 20:40:23 | D | + w: sint8 +24-11-19 20:40:23 | D | + x: None +24-11-19 20:40:23 | D | + y: None +24-11-19 20:40:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:23 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:40:23 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:40:24 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:24 | D | - range ratio = [ 1.0000] +24-11-19 20:40:24 | D | sum error = [ 10.3654] +24-11-19 20:40:24 | D | best error = [ 10.3654] +24-11-19 20:40:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:25 | D | sum error = [ 10.3162, 10.2791, 10.3296, 10.4653, 10.6408] +24-11-19 20:40:25 | D | best error = [ 9.1121, 8.6775, 8.4640, 8.3491, 8.2893] +24-11-19 20:40:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:25 | D | sum error = [ 10.9359, 11.2730, 11.7296, 12.2767, 12.9659] +24-11-19 20:40:25 | D | best error = [ 8.2576, 8.2414, 8.2349, 8.2324, 8.2317] +24-11-19 20:40:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:25 | D | sum error = [ 13.7146, 14.5799, 15.5510, 16.5550, 17.7349] +24-11-19 20:40:25 | D | best error = [ 8.2315, 8.2314, 8.2314, 8.2314, 8.2314] +24-11-19 20:40:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:25 | D | sum error = [ 19.0012, 20.3822, 21.8206, 23.4450, 25.1543] +24-11-19 20:40:25 | D | best error = [ 8.2314, 8.2314, 8.2314, 8.2314, 8.2314] +24-11-19 20:40:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:25 | D | sum error = [ 26.9486, 28.8908, 30.9654, 33.1901, 35.5048] +24-11-19 20:40:25 | D | best error = [ 8.2314, 8.2314, 8.2314, 8.2314, 8.2314] +24-11-19 20:40:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:25 | D | sum error = [ 38.0194, 40.6583, 43.4847, 46.4264, 49.6120] +24-11-19 20:40:25 | D | best error = [ 8.2314, 8.2314, 8.2314, 8.2314, 8.2314] +24-11-19 20:40:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:25 | D | sum error = [ 52.9824, 56.5453, 60.2915, 64.2430, 68.4840] +24-11-19 20:40:25 | D | best error = [ 8.2314, 8.2314, 8.2314, 8.2314, 8.2314] +24-11-19 20:40:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:25 | D | sum error = [ 72.9064, 77.6135, 82.5705, 87.7575, 93.2647] +24-11-19 20:40:25 | D | best error = [ 8.2314, 8.2314, 8.2314, 8.2314, 8.2314] +24-11-19 20:40:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:25 | D | sum error = [ 99.0844, 105.2078, 111.6653, 118.5010, 125.6707] +24-11-19 20:40:25 | D | best error = [ 8.2314, 8.2314, 8.2314, 8.2314, 8.2314] +24-11-19 20:40:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:25 | D | sum error = [ 133.2532, 141.2984, 149.7414, 158.6697, 168.0449] +24-11-19 20:40:25 | D | best error = [ 8.2314, 8.2314, 8.2314, 8.2314, 8.2314] +24-11-19 20:40:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:25 | D | sum error = [ 177.8907, 188.2625, 199.1573, 210.5525, 222.5586] +24-11-19 20:40:25 | D | best error = [ 8.2314, 8.2314, 8.2314, 8.2314, 8.2314] +24-11-19 20:40:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:25 | D | sum error = [ 235.1515, 248.3555, 262.1758, 276.7082, 291.9824] +24-11-19 20:40:25 | D | best error = [ 8.2314, 8.2314, 8.2314, 8.2314, 8.2314] +24-11-19 20:40:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:25 | D | sum error = [ 307.9149, 324.5963, 341.9945, 360.2162, 379.1658] +24-11-19 20:40:25 | D | best error = [ 8.2314, 8.2314, 8.2314, 8.2314, 8.2314] +24-11-19 20:40:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:25 | D | sum error = [ 398.9905, 419.6656, 441.1970, 463.6070, 486.9132] +24-11-19 20:40:25 | D | best error = [ 8.2314, 8.2314, 8.2314, 8.2314, 8.2314] +24-11-19 20:40:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:25 | D | sum error = [ 511.0790, 536.1785, 562.2013, 589.2001, 617.1013] +24-11-19 20:40:25 | D | best error = [ 8.2314, 8.2314, 8.2314, 8.2314, 8.2314] +24-11-19 20:40:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:25 | D | sum error = [ 645.9352, 675.7560, 706.5107, 738.2137, 770.8133] +24-11-19 20:40:25 | D | best error = [ 8.2314, 8.2314, 8.2314, 8.2314, 8.2314] +24-11-19 20:40:25 | D | + error = [8.2314] +24-11-19 20:40:25 | D | - Calibrating model.layers.30.mlp.gate_proj.weight +24-11-19 20:40:25 | D | + w: sint8 +24-11-19 20:40:25 | D | + x: None +24-11-19 20:40:25 | D | + y: None +24-11-19 20:40:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:25 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:40:25 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:40:25 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:25 | D | - range ratio = [ 1.0000] +24-11-19 20:40:25 | D | sum error = [ 13.2772] +24-11-19 20:40:25 | D | best error = [ 13.2772] +24-11-19 20:40:26 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:26 | D | sum error = [ 13.2001, 13.1616, 13.2531, 13.3744, 13.5828] +24-11-19 20:40:26 | D | best error = [ 11.6508, 11.1166, 10.8488, 10.6983, 10.6181] +24-11-19 20:40:26 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:26 | D | sum error = [ 14.0229, 14.4818, 15.0496, 15.7270, 16.6068] +24-11-19 20:40:26 | D | best error = [ 10.5770, 10.5570, 10.5491, 10.5461, 10.5445] +24-11-19 20:40:26 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:26 | D | sum error = [ 17.5900, 18.6764, 19.9717, 21.3858, 22.7314] +24-11-19 20:40:26 | D | best error = [ 10.5443, 10.5443, 10.5442, 10.5442, 10.5442] +24-11-19 20:40:26 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:26 | D | sum error = [ 24.4162, 26.1985, 28.2116, 30.2679, 32.4599] +24-11-19 20:40:26 | D | best error = [ 10.5442, 10.5442, 10.5442, 10.5442, 10.5442] +24-11-19 20:40:26 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:26 | D | sum error = [ 34.9231, 37.5048, 40.1967, 43.1812, 46.2320] +24-11-19 20:40:26 | D | best error = [ 10.5442, 10.5442, 10.5442, 10.5442, 10.5442] +24-11-19 20:40:26 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:26 | D | sum error = [ 49.6223, 53.2024, 56.9156, 60.8905, 65.2031] +24-11-19 20:40:26 | D | best error = [ 10.5442, 10.5442, 10.5442, 10.5442, 10.5442] +24-11-19 20:40:26 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:26 | D | sum error = [ 69.7350, 74.4368, 79.6089, 84.9971, 90.7256] +24-11-19 20:40:26 | D | best error = [ 10.5442, 10.5442, 10.5442, 10.5442, 10.5442] +24-11-19 20:40:26 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:26 | D | sum error = [ 96.8715, 103.3785, 110.2342, 117.5405, 125.3664] +24-11-19 20:40:26 | D | best error = [ 10.5442, 10.5442, 10.5442, 10.5442, 10.5442] +24-11-19 20:40:26 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:26 | D | sum error = [ 133.5805, 142.3261, 151.5876, 161.4241, 171.8440] +24-11-19 20:40:26 | D | best error = [ 10.5442, 10.5442, 10.5442, 10.5442, 10.5442] +24-11-19 20:40:26 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:26 | D | sum error = [ 182.9216, 194.6352, 207.0443, 220.1515, 234.0230] +24-11-19 20:40:26 | D | best error = [ 10.5442, 10.5442, 10.5442, 10.5442, 10.5442] +24-11-19 20:40:26 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:26 | D | sum error = [ 248.7054, 264.1681, 280.5145, 297.7700, 315.9402] +24-11-19 20:40:26 | D | best error = [ 10.5442, 10.5442, 10.5442, 10.5442, 10.5442] +24-11-19 20:40:26 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:26 | D | sum error = [ 335.0924, 355.2723, 376.5530, 398.9278, 422.3898] +24-11-19 20:40:26 | D | best error = [ 10.5442, 10.5442, 10.5442, 10.5442, 10.5442] +24-11-19 20:40:26 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:26 | D | sum error = [ 447.0953, 473.0337, 500.2304, 528.7203, 558.4233] +24-11-19 20:40:26 | D | best error = [ 10.5442, 10.5442, 10.5442, 10.5442, 10.5442] +24-11-19 20:40:26 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:26 | D | sum error = [ 589.5745, 622.1153, 656.1148, 691.5977, 728.5394] +24-11-19 20:40:26 | D | best error = [ 10.5442, 10.5442, 10.5442, 10.5442, 10.5442] +24-11-19 20:40:26 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:26 | D | sum error = [ 766.9615, 806.8941, 848.4935, 891.5420, 936.1703] +24-11-19 20:40:26 | D | best error = [ 10.5442, 10.5442, 10.5442, 10.5442, 10.5442] +24-11-19 20:40:26 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:26 | D | sum error = [ 982.3449, 1030.0751, 1079.3683, 1130.1118, 1182.4636] +24-11-19 20:40:26 | D | best error = [ 10.5442, 10.5442, 10.5442, 10.5442, 10.5442] +24-11-19 20:40:26 | D | + error = [10.5442] +24-11-19 20:40:26 | D | - Calibrating model.layers.30.mlp.down_proj.weight +24-11-19 20:40:26 | D | + w: sint8 +24-11-19 20:40:26 | D | + x: None +24-11-19 20:40:26 | D | + y: None +24-11-19 20:40:26 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:26 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:40:27 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:40:27 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:27 | D | - range ratio = [ 1.0000] +24-11-19 20:40:27 | D | sum error = [ 3.9136] +24-11-19 20:40:27 | D | best error = [ 3.9136] +24-11-19 20:40:28 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:28 | D | sum error = [ 3.9156, 3.9557, 4.0146, 4.1531, 4.3192] +24-11-19 20:40:28 | D | best error = [ 3.5768, 3.4407, 3.3618, 3.3108, 3.2725] +24-11-19 20:40:28 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:28 | D | sum error = [ 4.5296, 4.7817, 5.0771, 5.3762, 5.7511] +24-11-19 20:40:28 | D | best error = [ 3.2405, 3.2121, 3.1886, 3.1690, 3.1515] +24-11-19 20:40:28 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:28 | D | sum error = [ 6.1274, 6.5448, 6.9801, 7.4305, 7.9304] +24-11-19 20:40:28 | D | best error = [ 3.1370, 3.1236, 3.1125, 3.1050, 3.0984] +24-11-19 20:40:28 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:28 | D | sum error = [ 8.4068, 8.9295, 9.4666, 10.0338, 10.6138] +24-11-19 20:40:28 | D | best error = [ 3.0929, 3.0875, 3.0842, 3.0813, 3.0791] +24-11-19 20:40:28 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:28 | D | sum error = [ 11.2118, 11.8307, 12.4730, 13.1232, 13.8114] +24-11-19 20:40:28 | D | best error = [ 3.0773, 3.0755, 3.0742, 3.0735, 3.0728] +24-11-19 20:40:28 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:28 | D | sum error = [ 14.5032, 15.2257, 15.9625, 16.7410, 17.5233] +24-11-19 20:40:28 | D | best error = [ 3.0726, 3.0724, 3.0722, 3.0722, 3.0722] +24-11-19 20:40:28 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:28 | D | sum error = [ 18.3540, 19.1949, 20.0661, 20.9705, 21.9050] +24-11-19 20:40:28 | D | best error = [ 3.0721, 3.0721, 3.0721, 3.0720, 3.0720] +24-11-19 20:40:28 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:28 | D | sum error = [ 22.8718, 23.8621, 24.9052, 25.9595, 27.0621] +24-11-19 20:40:28 | D | best error = [ 3.0720, 3.0720, 3.0720, 3.0720, 3.0720] +24-11-19 20:40:28 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:28 | D | sum error = [ 28.2018, 29.3918, 30.6282, 31.9068, 33.2470] +24-11-19 20:40:28 | D | best error = [ 3.0720, 3.0720, 3.0720, 3.0720, 3.0720] +24-11-19 20:40:28 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:28 | D | sum error = [ 34.6364, 36.0899, 37.6075, 39.1686, 40.8114] +24-11-19 20:40:28 | D | best error = [ 3.0720, 3.0720, 3.0720, 3.0720, 3.0720] +24-11-19 20:40:28 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:28 | D | sum error = [ 42.5412, 44.3437, 46.2318, 48.2184, 50.2918] +24-11-19 20:40:28 | D | best error = [ 3.0720, 3.0720, 3.0720, 3.0720, 3.0720] +24-11-19 20:40:28 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:28 | D | sum error = [ 52.4812, 54.7895, 57.2285, 59.7864, 62.4990] +24-11-19 20:40:28 | D | best error = [ 3.0720, 3.0720, 3.0720, 3.0720, 3.0720] +24-11-19 20:40:28 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:28 | D | sum error = [ 65.3538, 68.3607, 71.5294, 74.8895, 78.4289] +24-11-19 20:40:28 | D | best error = [ 3.0720, 3.0720, 3.0720, 3.0720, 3.0720] +24-11-19 20:40:28 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:28 | D | sum error = [ 82.1693, 86.1161, 90.2883, 94.7070, 99.3808] +24-11-19 20:40:28 | D | best error = [ 3.0720, 3.0720, 3.0720, 3.0720, 3.0720] +24-11-19 20:40:28 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:28 | D | sum error = [ 104.3137, 109.5328, 115.0549, 120.9024, 127.0963] +24-11-19 20:40:28 | D | best error = [ 3.0720, 3.0720, 3.0720, 3.0720, 3.0720] +24-11-19 20:40:28 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:28 | D | sum error = [ 133.6465, 140.5653, 147.8781, 155.6088, 163.7713] +24-11-19 20:40:28 | D | best error = [ 3.0720, 3.0720, 3.0720, 3.0720, 3.0720] +24-11-19 20:40:28 | D | + error = [3.0720] +24-11-19 20:40:28 | D | - Quantizing model.layers.30.self_attn.q_proj.weight +24-11-19 20:40:29 | D | - Quantizing model.layers.30.self_attn.k_proj.weight +24-11-19 20:40:30 | D | - Quantizing model.layers.30.self_attn.v_proj.weight +24-11-19 20:40:30 | D | - Quantizing model.layers.30.self_attn.o_proj.weight +24-11-19 20:40:31 | D | - Quantizing model.layers.30.mlp.up_proj.weight +24-11-19 20:40:32 | D | - Quantizing model.layers.30.mlp.gate_proj.weight +24-11-19 20:40:33 | D | - Quantizing model.layers.30.mlp.down_proj.weight +24-11-19 20:40:42 | D | - Quantizing layer model.layers.31 +24-11-19 20:40:42 | D | - Calibrating model.layers.31.self_attn.q_proj.weight +24-11-19 20:40:42 | D | + w: sint8 +24-11-19 20:40:42 | D | + x: None +24-11-19 20:40:42 | D | + y: None +24-11-19 20:40:42 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:40:42 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:40:42 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:40:43 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:43 | D | - range ratio = [ 1.0000] +24-11-19 20:40:43 | D | sum error = [ 8.8571] +24-11-19 20:40:43 | D | best error = [ 8.8571] +24-11-19 20:40:55 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:55 | D | sum error = [ 8.7276, 8.8295, 9.1316, 8.9102, 9.1873] +24-11-19 20:40:55 | D | best error = [ 8.7276, 8.7276, 8.7276, 8.7276, 8.7276] +24-11-19 20:40:55 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:55 | D | sum error = [ 9.5288, 9.8412, 10.1918, 10.5547, 11.6371] +24-11-19 20:40:55 | D | best error = [ 8.7276, 8.7276, 8.7276, 8.7276, 8.7276] +24-11-19 20:40:55 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:55 | D | sum error = [ 12.0429, 12.7222, 14.2973, 15.7461, 17.3692] +24-11-19 20:40:55 | D | best error = [ 8.7276, 8.7276, 8.7276, 8.7276, 8.7276] +24-11-19 20:40:55 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:55 | D | sum error = [ 17.6281, 18.7537, 20.5757, 22.5201, 24.2046] +24-11-19 20:40:55 | D | best error = [ 8.7276, 8.7276, 8.7276, 8.7276, 8.7276] +24-11-19 20:40:55 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:55 | D | sum error = [ 27.1332, 28.7073, 31.5956, 33.3276, 36.5258] +24-11-19 20:40:55 | D | best error = [ 8.7276, 8.7276, 8.7276, 8.7276, 8.7276] +24-11-19 20:40:55 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:55 | D | sum error = [ 39.3880, 42.3191, 45.8431, 50.0897, 53.2529] +24-11-19 20:40:55 | D | best error = [ 8.7276, 8.7276, 8.7276, 8.7276, 8.7276] +24-11-19 20:40:55 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:55 | D | sum error = [ 57.4080, 62.5534, 67.5568, 72.5977, 79.1988] +24-11-19 20:40:55 | D | best error = [ 8.7276, 8.7276, 8.7276, 8.7276, 8.7276] +24-11-19 20:40:55 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:55 | D | sum error = [ 85.4616, 92.3420, 99.2115, 107.3215, 115.6496] +24-11-19 20:40:55 | D | best error = [ 8.7276, 8.7276, 8.7276, 8.7276, 8.7276] +24-11-19 20:40:55 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:55 | D | sum error = [ 125.1138, 135.1317, 145.1457, 156.4494, 168.4765] +24-11-19 20:40:55 | D | best error = [ 8.7276, 8.7276, 8.7276, 8.7276, 8.7276] +24-11-19 20:40:55 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:55 | D | sum error = [ 181.2618, 194.9636, 210.0819, 226.3327, 244.0643] +24-11-19 20:40:55 | D | best error = [ 8.7276, 8.7276, 8.7276, 8.7276, 8.7276] +24-11-19 20:40:55 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:55 | D | sum error = [ 262.6805, 282.6606, 305.6541, 329.4240, 354.8169] +24-11-19 20:40:55 | D | best error = [ 8.7276, 8.7276, 8.7276, 8.7276, 8.7276] +24-11-19 20:40:55 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:55 | D | sum error = [ 382.8426, 412.8294, 444.9849, 480.5906, 518.4653] +24-11-19 20:40:55 | D | best error = [ 8.7276, 8.7276, 8.7276, 8.7276, 8.7276] +24-11-19 20:40:55 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:55 | D | sum error = [ 560.4926, 606.2923, 656.3964, 710.9672, 769.6336] +24-11-19 20:40:55 | D | best error = [ 8.7276, 8.7276, 8.7276, 8.7276, 8.7276] +24-11-19 20:40:55 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:55 | D | sum error = [ 834.2819, 904.3218, 980.3023, 1064.0417, 1154.3159] +24-11-19 20:40:55 | D | best error = [ 8.7276, 8.7276, 8.7276, 8.7276, 8.7276] +24-11-19 20:40:55 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:55 | D | sum error = [ 1253.6569, 1360.5019, 1476.5193, 1600.9717, 1735.0105] +24-11-19 20:40:55 | D | best error = [ 8.7276, 8.7276, 8.7276, 8.7276, 8.7276] +24-11-19 20:40:55 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:55 | D | sum error = [ 1878.1204, 2029.4175, 2188.5121, 2353.6053, 2524.1196] +24-11-19 20:40:55 | D | best error = [ 8.7276, 8.7276, 8.7276, 8.7276, 8.7276] +24-11-19 20:40:55 | D | + error = [8.7276] +24-11-19 20:40:55 | D | - Calibrating model.layers.31.self_attn.k_proj.weight +24-11-19 20:40:55 | D | + w: sint8 +24-11-19 20:40:55 | D | + x: None +24-11-19 20:40:55 | D | + y: None +24-11-19 20:40:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:40:55 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:40:55 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:40:55 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:56 | D | - range ratio = [ 1.0000] +24-11-19 20:40:56 | D | sum error = [ 9.6027] +24-11-19 20:40:56 | D | best error = [ 9.6027] +24-11-19 20:41:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:08 | D | sum error = [ 12.6685, 9.7846, 11.5340, 13.9960, 12.5127] +24-11-19 20:41:08 | D | best error = [ 9.6027, 9.6027, 9.6027, 9.6027, 9.6027] +24-11-19 20:41:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:08 | D | sum error = [ 11.8444, 10.5011, 11.3510, 12.5527, 12.5617] +24-11-19 20:41:08 | D | best error = [ 9.6027, 9.6027, 9.6027, 9.6027, 9.6027] +24-11-19 20:41:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:08 | D | sum error = [ 14.5428, 14.9383, 16.8178, 16.6011, 19.1587] +24-11-19 20:41:08 | D | best error = [ 9.6027, 9.6027, 9.6027, 9.6027, 9.6027] +24-11-19 20:41:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:08 | D | sum error = [ 19.6574, 20.6523, 23.7864, 23.6375, 25.5082] +24-11-19 20:41:08 | D | best error = [ 9.6027, 9.6027, 9.6027, 9.6027, 9.6027] +24-11-19 20:41:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:08 | D | sum error = [ 27.0115, 28.6278, 30.8623, 32.9753, 35.0502] +24-11-19 20:41:08 | D | best error = [ 9.6027, 9.6027, 9.6027, 9.6027, 9.6027] +24-11-19 20:41:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:08 | D | sum error = [ 38.2673, 40.1257, 43.3113, 46.7777, 50.7788] +24-11-19 20:41:08 | D | best error = [ 9.6027, 9.6027, 9.6027, 9.6027, 9.6027] +24-11-19 20:41:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:08 | D | sum error = [ 55.2144, 58.8198, 64.5683, 70.9214, 76.0213] +24-11-19 20:41:08 | D | best error = [ 9.6027, 9.6027, 9.6027, 9.6027, 9.6027] +24-11-19 20:41:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:08 | D | sum error = [ 82.5543, 90.5502, 98.6807, 107.8917, 118.1575] +24-11-19 20:41:08 | D | best error = [ 9.6027, 9.6027, 9.6027, 9.6027, 9.6027] +24-11-19 20:41:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:08 | D | sum error = [ 125.7095, 138.3896, 147.7451, 162.2798, 175.6075] +24-11-19 20:41:08 | D | best error = [ 9.6027, 9.6027, 9.6027, 9.6027, 9.6027] +24-11-19 20:41:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:08 | D | sum error = [ 190.9863, 207.0993, 224.5875, 242.4922, 263.5923] +24-11-19 20:41:08 | D | best error = [ 9.6027, 9.6027, 9.6027, 9.6027, 9.6027] +24-11-19 20:41:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:08 | D | sum error = [ 284.8742, 309.3351, 335.7312, 362.0108, 391.2833] +24-11-19 20:41:08 | D | best error = [ 9.6027, 9.6027, 9.6027, 9.6027, 9.6027] +24-11-19 20:41:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:08 | D | sum error = [ 424.8132, 458.9882, 494.3411, 533.0519, 575.3529] +24-11-19 20:41:08 | D | best error = [ 9.6027, 9.6027, 9.6027, 9.6027, 9.6027] +24-11-19 20:41:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:08 | D | sum error = [ 618.4308, 667.5690, 719.9390, 776.7162, 838.1255] +24-11-19 20:41:08 | D | best error = [ 9.6027, 9.6027, 9.6027, 9.6027, 9.6027] +24-11-19 20:41:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:08 | D | sum error = [ 906.1205, 980.9774, 1061.3409, 1150.7257, 1246.3365] +24-11-19 20:41:08 | D | best error = [ 9.6027, 9.6027, 9.6027, 9.6027, 9.6027] +24-11-19 20:41:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:08 | D | sum error = [ 1351.6850, 1462.1453, 1578.2307, 1707.3457, 1847.6064] +24-11-19 20:41:08 | D | best error = [ 9.6027, 9.6027, 9.6027, 9.6027, 9.6027] +24-11-19 20:41:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:08 | D | sum error = [ 1991.4923, 2141.9741, 2299.7118, 2461.4583, 2625.2265] +24-11-19 20:41:08 | D | best error = [ 9.6027, 9.6027, 9.6027, 9.6027, 9.6027] +24-11-19 20:41:08 | D | + error = [9.6027] +24-11-19 20:41:08 | D | - Calibrating model.layers.31.self_attn.v_proj.weight +24-11-19 20:41:08 | D | + w: sint8 +24-11-19 20:41:08 | D | + x: None +24-11-19 20:41:08 | D | + y: None +24-11-19 20:41:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:08 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:41:08 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:41:08 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:41:08 | D | - range ratio = [ 1.0000] +24-11-19 20:41:08 | D | sum error = [ 2.8082] +24-11-19 20:41:08 | D | best error = [ 2.8082] +24-11-19 20:41:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:08 | D | sum error = [ 2.7907, 2.8031, 2.8060, 2.8528, 2.8783] +24-11-19 20:41:08 | D | best error = [ 2.5451, 2.4516, 2.4059, 2.3813, 2.3663] +24-11-19 20:41:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:08 | D | sum error = [ 2.9984, 3.0659, 3.1913, 3.3452, 3.5050] +24-11-19 20:41:08 | D | best error = [ 2.3565, 2.3533, 2.3518, 2.3510, 2.3509] +24-11-19 20:41:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:08 | D | sum error = [ 3.6931, 3.9352, 4.1817, 4.4596, 4.7825] +24-11-19 20:41:08 | D | best error = [ 2.3509, 2.3509, 2.3509, 2.3509, 2.3509] +24-11-19 20:41:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:08 | D | sum error = [ 5.0928, 5.4607, 5.8726, 6.2765, 6.7032] +24-11-19 20:41:08 | D | best error = [ 2.3509, 2.3509, 2.3509, 2.3509, 2.3509] +24-11-19 20:41:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:08 | D | sum error = [ 7.1938, 7.7316, 8.2800, 8.8887, 9.5334] +24-11-19 20:41:08 | D | best error = [ 2.3509, 2.3509, 2.3509, 2.3509, 2.3509] +24-11-19 20:41:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:08 | D | sum error = [ 10.1736, 10.9190, 11.6294, 12.4056, 13.2509] +24-11-19 20:41:08 | D | best error = [ 2.3509, 2.3509, 2.3509, 2.3509, 2.3509] +24-11-19 20:41:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:08 | D | sum error = [ 14.1352, 15.1214, 16.0960, 17.1672, 18.2717] +24-11-19 20:41:08 | D | best error = [ 2.3509, 2.3509, 2.3509, 2.3509, 2.3509] +24-11-19 20:41:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:08 | D | sum error = [ 19.5062, 20.7551, 22.0611, 23.4550, 24.8850] +24-11-19 20:41:08 | D | best error = [ 2.3509, 2.3509, 2.3509, 2.3509, 2.3509] +24-11-19 20:41:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:08 | D | sum error = [ 26.4668, 28.0668, 29.7677, 31.5380, 33.4219] +24-11-19 20:41:08 | D | best error = [ 2.3509, 2.3509, 2.3509, 2.3509, 2.3509] +24-11-19 20:41:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:08 | D | sum error = [ 35.4001, 37.4817, 39.6445, 41.9307, 44.3239] +24-11-19 20:41:08 | D | best error = [ 2.3509, 2.3509, 2.3509, 2.3509, 2.3509] +24-11-19 20:41:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:08 | D | sum error = [ 46.8490, 49.5010, 52.2529, 55.1429, 58.1980] +24-11-19 20:41:08 | D | best error = [ 2.3509, 2.3509, 2.3509, 2.3509, 2.3509] +24-11-19 20:41:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:08 | D | sum error = [ 61.3716, 64.7184, 68.2197, 71.8731, 75.7062] +24-11-19 20:41:08 | D | best error = [ 2.3509, 2.3509, 2.3509, 2.3509, 2.3509] +24-11-19 20:41:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:08 | D | sum error = [ 79.6714, 83.8441, 88.1895, 92.7043, 97.4291] +24-11-19 20:41:08 | D | best error = [ 2.3509, 2.3509, 2.3509, 2.3509, 2.3509] +24-11-19 20:41:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:08 | D | sum error = [ 102.3208, 107.4136, 112.7113, 118.2006, 123.9590] +24-11-19 20:41:08 | D | best error = [ 2.3509, 2.3509, 2.3509, 2.3509, 2.3509] +24-11-19 20:41:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:08 | D | sum error = [ 129.9019, 136.1299, 142.5447, 149.1565, 156.0106] +24-11-19 20:41:08 | D | best error = [ 2.3509, 2.3509, 2.3509, 2.3509, 2.3509] +24-11-19 20:41:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:08 | D | sum error = [ 163.0793, 170.3837, 177.8967, 185.6606, 193.6407] +24-11-19 20:41:08 | D | best error = [ 2.3509, 2.3509, 2.3509, 2.3509, 2.3509] +24-11-19 20:41:08 | D | + error = [2.3509] +24-11-19 20:41:08 | D | - Calibrating model.layers.31.self_attn.o_proj.weight +24-11-19 20:41:08 | D | + w: sint8 +24-11-19 20:41:08 | D | + x: None +24-11-19 20:41:08 | D | + y: None +24-11-19 20:41:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:08 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:41:08 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:41:09 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:41:09 | D | - range ratio = [ 1.0000] +24-11-19 20:41:09 | D | sum error = [ 2.6016] +24-11-19 20:41:09 | D | best error = [ 2.6016] +24-11-19 20:41:09 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:09 | D | sum error = [ 2.5754, 2.5867, 2.5560, 2.5186, 2.5264] +24-11-19 20:41:09 | D | best error = [ 2.1182, 1.9665, 1.8783, 1.8241, 1.7875] +24-11-19 20:41:09 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:09 | D | sum error = [ 2.5288, 2.4782, 2.4945, 2.5073, 2.5373] +24-11-19 20:41:09 | D | best error = [ 1.7577, 1.7358, 1.7171, 1.7024, 1.6896] +24-11-19 20:41:09 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:09 | D | sum error = [ 2.5448, 2.5876, 2.6271, 2.6894, 2.7931] +24-11-19 20:41:09 | D | best error = [ 1.6810, 1.6723, 1.6634, 1.6585, 1.6531] +24-11-19 20:41:09 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:09 | D | sum error = [ 2.8533, 2.9250, 3.0683, 3.2171, 3.3342] +24-11-19 20:41:09 | D | best error = [ 1.6495, 1.6457, 1.6432, 1.6405, 1.6384] +24-11-19 20:41:09 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:09 | D | sum error = [ 3.5230, 3.7088, 3.9181, 4.1455, 4.4090] +24-11-19 20:41:09 | D | best error = [ 1.6370, 1.6356, 1.6341, 1.6334, 1.6327] +24-11-19 20:41:09 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:09 | D | sum error = [ 4.6461, 4.9632, 5.2854, 5.6250, 6.0082] +24-11-19 20:41:09 | D | best error = [ 1.6319, 1.6311, 1.6307, 1.6304, 1.6302] +24-11-19 20:41:09 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:09 | D | sum error = [ 6.3941, 6.8231, 7.2927, 7.7855, 8.2909] +24-11-19 20:41:09 | D | best error = [ 1.6300, 1.6299, 1.6298, 1.6298, 1.6298] +24-11-19 20:41:09 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:09 | D | sum error = [ 8.8822, 9.4938, 10.1222, 10.8562, 11.5832] +24-11-19 20:41:09 | D | best error = [ 1.6298, 1.6297, 1.6297, 1.6297, 1.6296] +24-11-19 20:41:09 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:09 | D | sum error = [ 12.3862, 13.2299, 14.1260, 15.0582, 16.0571] +24-11-19 20:41:09 | D | best error = [ 1.6296, 1.6295, 1.6295, 1.6295, 1.6295] +24-11-19 20:41:09 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:09 | D | sum error = [ 17.1416, 18.2806, 19.5011, 20.7777, 22.1359] +24-11-19 20:41:09 | D | best error = [ 1.6295, 1.6295, 1.6295, 1.6295, 1.6295] +24-11-19 20:41:09 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:09 | D | sum error = [ 23.5956, 25.1352, 26.7430, 28.4272, 30.2207] +24-11-19 20:41:09 | D | best error = [ 1.6295, 1.6295, 1.6295, 1.6295, 1.6295] +24-11-19 20:41:09 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:09 | D | sum error = [ 32.1150, 34.1178, 36.2312, 38.4771, 40.8353] +24-11-19 20:41:09 | D | best error = [ 1.6295, 1.6295, 1.6295, 1.6295, 1.6295] +24-11-19 20:41:09 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:09 | D | sum error = [ 43.3077, 45.8871, 48.6471, 51.5209, 54.5457] +24-11-19 20:41:09 | D | best error = [ 1.6295, 1.6295, 1.6295, 1.6295, 1.6295] +24-11-19 20:41:09 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:09 | D | sum error = [ 57.7056, 61.0175, 64.4869, 68.1400, 71.9543] +24-11-19 20:41:09 | D | best error = [ 1.6295, 1.6295, 1.6295, 1.6295, 1.6295] +24-11-19 20:41:09 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:09 | D | sum error = [ 75.9436, 80.1392, 84.4966, 89.0276, 93.7575] +24-11-19 20:41:09 | D | best error = [ 1.6295, 1.6295, 1.6295, 1.6295, 1.6295] +24-11-19 20:41:09 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:09 | D | sum error = [ 98.6816, 103.7993, 109.1175, 114.6273, 120.3704] +24-11-19 20:41:09 | D | best error = [ 1.6295, 1.6295, 1.6295, 1.6295, 1.6295] +24-11-19 20:41:09 | D | + error = [1.6295] +24-11-19 20:41:09 | D | - Calibrating model.layers.31.mlp.up_proj.weight +24-11-19 20:41:09 | D | + w: sint8 +24-11-19 20:41:09 | D | + x: None +24-11-19 20:41:09 | D | + y: None +24-11-19 20:41:09 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:09 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:41:09 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:41:09 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:41:09 | D | - range ratio = [ 1.0000] +24-11-19 20:41:09 | D | sum error = [ 9.9787] +24-11-19 20:41:09 | D | best error = [ 9.9787] +24-11-19 20:41:10 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:10 | D | sum error = [ 9.9420, 9.9150, 9.9317, 10.0523, 10.2344] +24-11-19 20:41:10 | D | best error = [ 8.8118, 8.3984, 8.2033, 8.0948, 8.0350] +24-11-19 20:41:10 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:10 | D | sum error = [ 10.4987, 10.8623, 11.3127, 11.8555, 12.5115] +24-11-19 20:41:10 | D | best error = [ 8.0025, 7.9867, 7.9806, 7.9786, 7.9778] +24-11-19 20:41:10 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:10 | D | sum error = [ 13.3092, 14.0735, 15.0808, 16.1352, 17.2854] +24-11-19 20:41:10 | D | best error = [ 7.9777, 7.9775, 7.9775, 7.9775, 7.9775] +24-11-19 20:41:10 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:10 | D | sum error = [ 18.6151, 19.9832, 21.4482, 23.0427, 24.7491] +24-11-19 20:41:10 | D | best error = [ 7.9775, 7.9775, 7.9775, 7.9775, 7.9775] +24-11-19 20:41:10 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:10 | D | sum error = [ 26.6412, 28.6495, 30.7336, 33.0286, 35.4961] +24-11-19 20:41:10 | D | best error = [ 7.9775, 7.9775, 7.9775, 7.9775, 7.9775] +24-11-19 20:41:10 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:10 | D | sum error = [ 38.1201, 40.9303, 43.8884, 47.1017, 50.5450] +24-11-19 20:41:10 | D | best error = [ 7.9775, 7.9775, 7.9775, 7.9775, 7.9775] +24-11-19 20:41:10 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:10 | D | sum error = [ 54.2130, 58.0417, 62.2241, 66.6763, 71.4154] +24-11-19 20:41:10 | D | best error = [ 7.9775, 7.9775, 7.9775, 7.9775, 7.9775] +24-11-19 20:41:10 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:10 | D | sum error = [ 76.4658, 81.8882, 87.6530, 93.8187, 100.3497] +24-11-19 20:41:10 | D | best error = [ 7.9775, 7.9775, 7.9775, 7.9775, 7.9775] +24-11-19 20:41:10 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:10 | D | sum error = [ 107.3227, 114.7829, 122.6995, 131.1433, 140.1134] +24-11-19 20:41:10 | D | best error = [ 7.9775, 7.9775, 7.9775, 7.9775, 7.9775] +24-11-19 20:41:10 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:10 | D | sum error = [ 149.7069, 159.9156, 170.8057, 182.3167, 194.5657] +24-11-19 20:41:10 | D | best error = [ 7.9775, 7.9775, 7.9775, 7.9775, 7.9775] +24-11-19 20:41:10 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:10 | D | sum error = [ 207.5573, 221.3210, 235.8548, 251.3468, 267.7388] +24-11-19 20:41:10 | D | best error = [ 7.9775, 7.9775, 7.9775, 7.9775, 7.9775] +24-11-19 20:41:10 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:10 | D | sum error = [ 285.0341, 303.2841, 322.5469, 342.8173, 364.1843] +24-11-19 20:41:10 | D | best error = [ 7.9775, 7.9775, 7.9775, 7.9775, 7.9775] +24-11-19 20:41:10 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:10 | D | sum error = [ 386.8188, 410.5523, 435.6238, 461.8611, 489.4826] +24-11-19 20:41:10 | D | best error = [ 7.9775, 7.9775, 7.9775, 7.9775, 7.9775] +24-11-19 20:41:10 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:10 | D | sum error = [ 518.3460, 548.5631, 580.0958, 613.0517, 647.4951] +24-11-19 20:41:10 | D | best error = [ 7.9775, 7.9775, 7.9775, 7.9775, 7.9775] +24-11-19 20:41:10 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:10 | D | sum error = [ 683.3307, 720.6779, 759.4724, 799.8513, 841.7262] +24-11-19 20:41:10 | D | best error = [ 7.9775, 7.9775, 7.9775, 7.9775, 7.9775] +24-11-19 20:41:10 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:10 | D | sum error = [ 885.1054, 930.0064, 976.4358, 1024.3756, 1073.7846] +24-11-19 20:41:10 | D | best error = [ 7.9775, 7.9775, 7.9775, 7.9775, 7.9775] +24-11-19 20:41:10 | D | + error = [7.9775] +24-11-19 20:41:11 | D | - Calibrating model.layers.31.mlp.gate_proj.weight +24-11-19 20:41:11 | D | + w: sint8 +24-11-19 20:41:11 | D | + x: None +24-11-19 20:41:11 | D | + y: None +24-11-19 20:41:11 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:11 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:41:11 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:41:11 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:41:11 | D | - range ratio = [ 1.0000] +24-11-19 20:41:11 | D | sum error = [ 12.5623] +24-11-19 20:41:11 | D | best error = [ 12.5623] +24-11-19 20:41:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:12 | D | sum error = [ 12.4310, 12.4519, 12.4930, 12.6193, 12.9073] +24-11-19 20:41:12 | D | best error = [ 11.0479, 10.5551, 10.3026, 10.1628, 10.0875] +24-11-19 20:41:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:12 | D | sum error = [ 13.2038, 13.5915, 14.2474, 15.0128, 15.7633] +24-11-19 20:41:12 | D | best error = [ 10.0485, 10.0278, 10.0203, 10.0171, 10.0158] +24-11-19 20:41:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:12 | D | sum error = [ 16.7054, 17.7768, 19.0011, 20.2880, 21.7104] +24-11-19 20:41:12 | D | best error = [ 10.0157, 10.0156, 10.0156, 10.0156, 10.0156] +24-11-19 20:41:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:12 | D | sum error = [ 23.3331, 25.0243, 26.7528, 28.8097, 30.9102] +24-11-19 20:41:12 | D | best error = [ 10.0156, 10.0156, 10.0156, 10.0156, 10.0156] +24-11-19 20:41:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:12 | D | sum error = [ 33.2227, 35.7619, 38.3694, 41.1774, 44.2527] +24-11-19 20:41:12 | D | best error = [ 10.0156, 10.0156, 10.0156, 10.0156, 10.0156] +24-11-19 20:41:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:12 | D | sum error = [ 47.4622, 50.9383, 54.6813, 58.6219, 62.8925] +24-11-19 20:41:12 | D | best error = [ 10.0156, 10.0156, 10.0156, 10.0156, 10.0156] +24-11-19 20:41:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:12 | D | sum error = [ 67.4847, 72.3931, 77.6065, 83.2035, 89.2037] +24-11-19 20:41:12 | D | best error = [ 10.0156, 10.0156, 10.0156, 10.0156, 10.0156] +24-11-19 20:41:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:12 | D | sum error = [ 95.6185, 102.4400, 109.7476, 117.5662, 125.9289] +24-11-19 20:41:12 | D | best error = [ 10.0156, 10.0156, 10.0156, 10.0156, 10.0156] +24-11-19 20:41:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:12 | D | sum error = [ 134.9338, 144.5692, 154.7682, 165.8005, 177.5459] +24-11-19 20:41:12 | D | best error = [ 10.0156, 10.0156, 10.0156, 10.0156, 10.0156] +24-11-19 20:41:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:12 | D | sum error = [ 190.0776, 203.4818, 217.7729, 233.0936, 249.4877] +24-11-19 20:41:12 | D | best error = [ 10.0156, 10.0156, 10.0156, 10.0156, 10.0156] +24-11-19 20:41:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:12 | D | sum error = [ 266.8763, 285.3996, 305.1929, 326.2179, 348.7359] +24-11-19 20:41:12 | D | best error = [ 10.0156, 10.0156, 10.0156, 10.0156, 10.0156] +24-11-19 20:41:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:12 | D | sum error = [ 372.4717, 397.7746, 424.6220, 453.1385, 483.3507] +24-11-19 20:41:12 | D | best error = [ 10.0156, 10.0156, 10.0156, 10.0156, 10.0156] +24-11-19 20:41:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:12 | D | sum error = [ 515.3722, 549.1591, 584.8121, 622.3757, 661.9594] +24-11-19 20:41:12 | D | best error = [ 10.0156, 10.0156, 10.0156, 10.0156, 10.0156] +24-11-19 20:41:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:12 | D | sum error = [ 703.5746, 747.2451, 793.0503, 841.0569, 891.1361] +24-11-19 20:41:12 | D | best error = [ 10.0156, 10.0156, 10.0156, 10.0156, 10.0156] +24-11-19 20:41:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:12 | D | sum error = [ 943.6484, 998.3851, 1055.4435, 1114.8028, 1176.6666] +24-11-19 20:41:12 | D | best error = [ 10.0156, 10.0156, 10.0156, 10.0156, 10.0156] +24-11-19 20:41:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:12 | D | sum error = [ 1240.9171, 1307.4000, 1376.4423, 1447.8083, 1521.5747] +24-11-19 20:41:12 | D | best error = [ 10.0156, 10.0156, 10.0156, 10.0156, 10.0156] +24-11-19 20:41:12 | D | + error = [10.0156] +24-11-19 20:41:12 | D | - Calibrating model.layers.31.mlp.down_proj.weight +24-11-19 20:41:12 | D | + w: sint8 +24-11-19 20:41:12 | D | + x: None +24-11-19 20:41:12 | D | + y: None +24-11-19 20:41:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:12 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:41:12 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:41:12 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:41:12 | D | - range ratio = [ 1.0000] +24-11-19 20:41:12 | D | sum error = [ 26.9511] +24-11-19 20:41:12 | D | best error = [ 26.9511] +24-11-19 20:41:14 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:14 | D | sum error = [ 26.6313, 26.5683, 25.8809, 26.1828, 25.6999] +24-11-19 20:41:14 | D | best error = [ 20.1548, 17.3628, 15.8888, 14.8817, 14.1780] +24-11-19 20:41:14 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:14 | D | sum error = [ 25.8037, 25.4046, 25.6142, 25.3169, 25.7622] +24-11-19 20:41:14 | D | best error = [ 13.6361, 13.1677, 12.7852, 12.4618, 12.1750] +24-11-19 20:41:14 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:14 | D | sum error = [ 26.1688, 26.5374, 27.3718, 28.0720, 28.9148] +24-11-19 20:41:14 | D | best error = [ 11.8991, 11.6856, 11.4621, 11.2559, 11.0750] +24-11-19 20:41:14 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:14 | D | sum error = [ 29.7096, 31.2874, 32.8914, 33.9038, 35.7181] +24-11-19 20:41:14 | D | best error = [ 10.9180, 10.7694, 10.6312, 10.5087, 10.3753] +24-11-19 20:41:14 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:14 | D | sum error = [ 37.8434, 39.4112, 41.8241, 44.9184, 47.2491] +24-11-19 20:41:14 | D | best error = [ 10.2444, 10.1409, 10.0229, 9.9194, 9.8177] +24-11-19 20:41:14 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:14 | D | sum error = [ 50.6808, 54.3437, 57.5972, 61.8888, 66.3610] +24-11-19 20:41:14 | D | best error = [ 9.7226, 9.6489, 9.5643, 9.4944, 9.4441] +24-11-19 20:41:14 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:14 | D | sum error = [ 70.9792, 76.0823, 81.3221, 87.4344, 93.9697] +24-11-19 20:41:14 | D | best error = [ 9.3864, 9.3506, 9.3125, 9.2800, 9.2369] +24-11-19 20:41:14 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:14 | D | sum error = [ 100.8892, 108.0561, 115.7081, 123.8380, 132.2954] +24-11-19 20:41:14 | D | best error = [ 9.2078, 9.1868, 9.1602, 9.1410, 9.1279] +24-11-19 20:41:14 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:14 | D | sum error = [ 141.5682, 151.2777, 161.4286, 172.2204, 183.6817] +24-11-19 20:41:14 | D | best error = [ 9.1158, 9.1074, 9.1020, 9.0951, 9.0826] +24-11-19 20:41:14 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:14 | D | sum error = [ 195.5884, 208.4978, 221.6431, 235.8284, 251.1012] +24-11-19 20:41:14 | D | best error = [ 9.0752, 9.0711, 9.0665, 9.0601, 9.0584] +24-11-19 20:41:14 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:14 | D | sum error = [ 267.1360, 284.2337, 302.7229, 322.1419, 342.9125] +24-11-19 20:41:14 | D | best error = [ 9.0548, 9.0516, 9.0507, 9.0494, 9.0461] +24-11-19 20:41:14 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:14 | D | sum error = [ 365.4456, 389.3685, 414.6521, 441.4679, 470.4257] +24-11-19 20:41:14 | D | best error = [ 9.0446, 9.0437, 9.0399, 9.0393, 9.0374] +24-11-19 20:41:14 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:14 | D | sum error = [ 500.8307, 532.9822, 566.8518, 602.7450, 640.8046] +24-11-19 20:41:14 | D | best error = [ 9.0362, 9.0362, 9.0362, 9.0362, 9.0362] +24-11-19 20:41:14 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:14 | D | sum error = [ 680.8467, 722.8387, 767.4300, 814.3354, 863.8006] +24-11-19 20:41:14 | D | best error = [ 9.0362, 9.0362, 9.0362, 9.0362, 9.0362] +24-11-19 20:41:14 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:14 | D | sum error = [ 915.7926, 970.6916, 1027.9566, 1087.8727, 1150.3547] +24-11-19 20:41:14 | D | best error = [ 9.0362, 9.0362, 9.0362, 9.0362, 9.0362] +24-11-19 20:41:14 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:14 | D | sum error = [ 1215.5872, 1283.5811, 1354.3329, 1427.8093, 1503.6932] +24-11-19 20:41:14 | D | best error = [ 9.0362, 9.0362, 9.0362, 9.0362, 9.0362] +24-11-19 20:41:14 | D | + error = [9.0362] +24-11-19 20:41:14 | D | - Quantizing model.layers.31.self_attn.q_proj.weight +24-11-19 20:41:15 | D | - Quantizing model.layers.31.self_attn.k_proj.weight +24-11-19 20:41:15 | D | - Quantizing model.layers.31.self_attn.v_proj.weight +24-11-19 20:41:16 | D | - Quantizing model.layers.31.self_attn.o_proj.weight +24-11-19 20:41:17 | D | - Quantizing model.layers.31.mlp.up_proj.weight +24-11-19 20:41:18 | D | - Quantizing model.layers.31.mlp.gate_proj.weight +24-11-19 20:41:19 | D | - Quantizing model.layers.31.mlp.down_proj.weight +24-11-19 20:41:23 | I | - Saving weight quantizer settings to runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt +24-11-19 20:41:23 | I | - Linking weight quantizer settings to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200729.RUNNING/model/wgts.pt +24-11-19 20:41:23 | I | - Saving model checkpoint to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200729.RUNNING/model +24-11-19 20:41:38 | I | * Quantizing activations +24-11-19 20:41:38 | I | - Generating activation quantizer settings +24-11-19 20:41:38 | D | Starting new HTTPS connection (7): huggingface.co:443 +24-11-19 20:41:44 | D | Starting new HTTPS connection (8): huggingface.co:443 +24-11-19 20:41:56 | D | Starting new HTTPS connection (3): s3.amazonaws.com:443 +24-11-19 20:42:08 | W | Repo card metadata block was not found. Setting CardData to empty. +24-11-19 20:42:08 | D | Starting new HTTPS connection (9): huggingface.co:443 +24-11-19 20:42:21 | W | Using the latest cached version of the dataset since mit-han-lab/pile-val-backup couldn't be found on the Hugging Face Hub +24-11-19 20:42:21 | W | Found the latest cached dataset configuration 'default' at /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4 (last modified on Tue Oct 8 18:58:39 2024). +24-11-19 20:42:21 | D | Attempting to acquire lock 23438703478256 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:42:21 | D | Lock 23438703478256 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:42:21 | D | open file: /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4/dataset_info.json +24-11-19 20:42:21 | D | Attempting to release lock 23438703478256 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:42:21 | D | Lock 23438703478256 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:42:36 | D | - Quantizing layer model.layers.0 +24-11-19 20:42:36 | D | - Calibrating model.layers.0.self_attn.v_proj.input +24-11-19 20:42:36 | D | - Calibrating model.layers.0.self_attn.k_rotary_emb.output +24-11-19 20:42:36 | D | + w: None +24-11-19 20:42:36 | D | + x: None +24-11-19 20:42:36 | D | + y: sint8 +24-11-19 20:42:36 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:42:36 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:42:36 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:42:36 | D | - range ratio = [ 1.0000] +24-11-19 20:42:36 | D | sum error = [ 2.8424] +24-11-19 20:42:36 | D | best error = [ 2.8424] +24-11-19 20:42:36 | D | + error = [2.8424] +24-11-19 20:42:37 | D | - Calibrating model.layers.0.self_attn.v_proj.output +24-11-19 20:42:37 | D | + w: None +24-11-19 20:42:37 | D | + x: None +24-11-19 20:42:37 | D | + y: sint8 +24-11-19 20:42:37 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:42:37 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:42:37 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:42:37 | D | - range ratio = [ 1.0000] +24-11-19 20:42:37 | D | sum error = [ 2.7431] +24-11-19 20:42:37 | D | best error = [ 2.7431] +24-11-19 20:42:37 | D | + error = [2.7431] +24-11-19 20:42:37 | D | - Calibrating model.layers.0.self_attn.o_proj.input +24-11-19 20:42:38 | D | - Calibrating model.layers.0.mlp.up_proj.input +24-11-19 20:42:38 | D | - Calibrating model.layers.0.mlp.down_proj.input +24-11-19 20:42:38 | D | - Quantizing model.layers.0.self_attn.q_proj (inputs) +24-11-19 20:42:38 | D | - Quantizing model.layers.0.self_attn.k_proj (inputs) +24-11-19 20:42:38 | D | - Quantizing model.layers.0.self_attn.v_proj (inputs and outputs) +24-11-19 20:42:38 | D | - Quantizing model.layers.0.self_attn.o_proj (inputs) +24-11-19 20:42:38 | D | - Quantizing model.layers.0.self_attn.k_rotary_emb (outputs) +24-11-19 20:42:38 | D | - Quantizing model.layers.0.mlp.gate_proj (inputs) +24-11-19 20:42:38 | D | - Quantizing model.layers.0.mlp.up_proj (inputs) +24-11-19 20:42:38 | D | - Quantizing model.layers.0.mlp.down_proj (inputs) +24-11-19 20:42:45 | D | - Quantizing layer model.layers.1 +24-11-19 20:42:45 | D | - Calibrating model.layers.1.self_attn.v_proj.input +24-11-19 20:42:45 | D | - Calibrating model.layers.1.self_attn.k_rotary_emb.output +24-11-19 20:42:45 | D | + w: None +24-11-19 20:42:45 | D | + x: None +24-11-19 20:42:45 | D | + y: sint8 +24-11-19 20:42:45 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:42:45 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:42:46 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:42:46 | D | - range ratio = [ 1.0000] +24-11-19 20:42:46 | D | sum error = [ 7.2982] +24-11-19 20:42:46 | D | best error = [ 7.2982] +24-11-19 20:42:46 | D | + error = [7.2982] +24-11-19 20:42:46 | D | - Calibrating model.layers.1.self_attn.v_proj.output +24-11-19 20:42:46 | D | + w: None +24-11-19 20:42:46 | D | + x: None +24-11-19 20:42:46 | D | + y: sint8 +24-11-19 20:42:46 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:42:46 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:42:46 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:42:47 | D | - range ratio = [ 1.0000] +24-11-19 20:42:47 | D | sum error = [ 14.4545] +24-11-19 20:42:47 | D | best error = [ 14.4545] +24-11-19 20:42:47 | D | + error = [14.4545] +24-11-19 20:42:47 | D | - Calibrating model.layers.1.self_attn.o_proj.input +24-11-19 20:42:47 | D | - Calibrating model.layers.1.mlp.up_proj.input +24-11-19 20:42:47 | D | - Calibrating model.layers.1.mlp.down_proj.input +24-11-19 20:42:47 | D | - Quantizing model.layers.1.self_attn.q_proj (inputs) +24-11-19 20:42:47 | D | - Quantizing model.layers.1.self_attn.k_proj (inputs) +24-11-19 20:42:47 | D | - Quantizing model.layers.1.self_attn.v_proj (inputs and outputs) +24-11-19 20:42:47 | D | - Quantizing model.layers.1.self_attn.o_proj (inputs) +24-11-19 20:42:47 | D | - Quantizing model.layers.1.self_attn.k_rotary_emb (outputs) +24-11-19 20:42:47 | D | - Quantizing model.layers.1.mlp.gate_proj (inputs) +24-11-19 20:42:47 | D | - Quantizing model.layers.1.mlp.up_proj (inputs) +24-11-19 20:42:47 | D | - Quantizing model.layers.1.mlp.down_proj (inputs) +24-11-19 20:42:54 | D | - Quantizing layer model.layers.2 +24-11-19 20:42:54 | D | - Calibrating model.layers.2.self_attn.v_proj.input +24-11-19 20:42:54 | D | - Calibrating model.layers.2.self_attn.k_rotary_emb.output +24-11-19 20:42:54 | D | + w: None +24-11-19 20:42:54 | D | + x: None +24-11-19 20:42:54 | D | + y: sint8 +24-11-19 20:42:54 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:42:54 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:42:54 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:42:55 | D | - range ratio = [ 1.0000] +24-11-19 20:42:55 | D | sum error = [ 8.0055] +24-11-19 20:42:55 | D | best error = [ 8.0055] +24-11-19 20:42:55 | D | + error = [8.0055] +24-11-19 20:42:55 | D | - Calibrating model.layers.2.self_attn.v_proj.output +24-11-19 20:42:55 | D | + w: None +24-11-19 20:42:55 | D | + x: None +24-11-19 20:42:55 | D | + y: sint8 +24-11-19 20:42:55 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:42:55 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:42:55 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:42:55 | D | - range ratio = [ 1.0000] +24-11-19 20:42:55 | D | sum error = [ 24.1621] +24-11-19 20:42:55 | D | best error = [ 24.1621] +24-11-19 20:42:55 | D | + error = [24.1621] +24-11-19 20:42:55 | D | - Calibrating model.layers.2.self_attn.o_proj.input +24-11-19 20:42:55 | D | - Calibrating model.layers.2.mlp.up_proj.input +24-11-19 20:42:56 | D | - Calibrating model.layers.2.mlp.down_proj.input +24-11-19 20:42:56 | D | - Quantizing model.layers.2.self_attn.q_proj (inputs) +24-11-19 20:42:56 | D | - Quantizing model.layers.2.self_attn.k_proj (inputs) +24-11-19 20:42:56 | D | - Quantizing model.layers.2.self_attn.v_proj (inputs and outputs) +24-11-19 20:42:56 | D | - Quantizing model.layers.2.self_attn.o_proj (inputs) +24-11-19 20:42:56 | D | - Quantizing model.layers.2.self_attn.k_rotary_emb (outputs) +24-11-19 20:42:56 | D | - Quantizing model.layers.2.mlp.gate_proj (inputs) +24-11-19 20:42:56 | D | - Quantizing model.layers.2.mlp.up_proj (inputs) +24-11-19 20:42:56 | D | - Quantizing model.layers.2.mlp.down_proj (inputs) +24-11-19 20:43:02 | D | - Quantizing layer model.layers.3 +24-11-19 20:43:02 | D | - Calibrating model.layers.3.self_attn.v_proj.input +24-11-19 20:43:02 | D | - Calibrating model.layers.3.self_attn.k_rotary_emb.output +24-11-19 20:43:02 | D | + w: None +24-11-19 20:43:02 | D | + x: None +24-11-19 20:43:02 | D | + y: sint8 +24-11-19 20:43:02 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:02 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:43:02 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:43:03 | D | - range ratio = [ 1.0000] +24-11-19 20:43:03 | D | sum error = [ 12.0008] +24-11-19 20:43:03 | D | best error = [ 12.0008] +24-11-19 20:43:03 | D | + error = [12.0008] +24-11-19 20:43:03 | D | - Calibrating model.layers.3.self_attn.v_proj.output +24-11-19 20:43:03 | D | + w: None +24-11-19 20:43:03 | D | + x: None +24-11-19 20:43:03 | D | + y: sint8 +24-11-19 20:43:03 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:03 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:43:03 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:43:04 | D | - range ratio = [ 1.0000] +24-11-19 20:43:04 | D | sum error = [ 57.6548] +24-11-19 20:43:04 | D | best error = [ 57.6548] +24-11-19 20:43:04 | D | + error = [57.6548] +24-11-19 20:43:04 | D | - Calibrating model.layers.3.self_attn.o_proj.input +24-11-19 20:43:04 | D | - Calibrating model.layers.3.mlp.up_proj.input +24-11-19 20:43:04 | D | - Calibrating model.layers.3.mlp.down_proj.input +24-11-19 20:43:04 | D | - Quantizing model.layers.3.self_attn.q_proj (inputs) +24-11-19 20:43:04 | D | - Quantizing model.layers.3.self_attn.k_proj (inputs) +24-11-19 20:43:04 | D | - Quantizing model.layers.3.self_attn.v_proj (inputs and outputs) +24-11-19 20:43:04 | D | - Quantizing model.layers.3.self_attn.o_proj (inputs) +24-11-19 20:43:04 | D | - Quantizing model.layers.3.self_attn.k_rotary_emb (outputs) +24-11-19 20:43:04 | D | - Quantizing model.layers.3.mlp.gate_proj (inputs) +24-11-19 20:43:04 | D | - Quantizing model.layers.3.mlp.up_proj (inputs) +24-11-19 20:43:04 | D | - Quantizing model.layers.3.mlp.down_proj (inputs) +24-11-19 20:43:10 | D | - Quantizing layer model.layers.4 +24-11-19 20:43:10 | D | - Calibrating model.layers.4.self_attn.v_proj.input +24-11-19 20:43:10 | D | - Calibrating model.layers.4.self_attn.k_rotary_emb.output +24-11-19 20:43:10 | D | + w: None +24-11-19 20:43:10 | D | + x: None +24-11-19 20:43:10 | D | + y: sint8 +24-11-19 20:43:10 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:10 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:43:10 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:43:11 | D | - range ratio = [ 1.0000] +24-11-19 20:43:11 | D | sum error = [ 21.1072] +24-11-19 20:43:11 | D | best error = [ 21.1072] +24-11-19 20:43:11 | D | + error = [21.1072] +24-11-19 20:43:11 | D | - Calibrating model.layers.4.self_attn.v_proj.output +24-11-19 20:43:11 | D | + w: None +24-11-19 20:43:11 | D | + x: None +24-11-19 20:43:11 | D | + y: sint8 +24-11-19 20:43:11 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:11 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:43:11 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:43:12 | D | - range ratio = [ 1.0000] +24-11-19 20:43:12 | D | sum error = [ 38.9878] +24-11-19 20:43:12 | D | best error = [ 38.9878] +24-11-19 20:43:12 | D | + error = [38.9878] +24-11-19 20:43:12 | D | - Calibrating model.layers.4.self_attn.o_proj.input +24-11-19 20:43:12 | D | - Calibrating model.layers.4.mlp.up_proj.input +24-11-19 20:43:12 | D | - Calibrating model.layers.4.mlp.down_proj.input +24-11-19 20:43:12 | D | - Quantizing model.layers.4.self_attn.q_proj (inputs) +24-11-19 20:43:12 | D | - Quantizing model.layers.4.self_attn.k_proj (inputs) +24-11-19 20:43:12 | D | - Quantizing model.layers.4.self_attn.v_proj (inputs and outputs) +24-11-19 20:43:12 | D | - Quantizing model.layers.4.self_attn.o_proj (inputs) +24-11-19 20:43:12 | D | - Quantizing model.layers.4.self_attn.k_rotary_emb (outputs) +24-11-19 20:43:12 | D | - Quantizing model.layers.4.mlp.gate_proj (inputs) +24-11-19 20:43:12 | D | - Quantizing model.layers.4.mlp.up_proj (inputs) +24-11-19 20:43:12 | D | - Quantizing model.layers.4.mlp.down_proj (inputs) +24-11-19 20:43:18 | D | - Quantizing layer model.layers.5 +24-11-19 20:43:18 | D | - Calibrating model.layers.5.self_attn.v_proj.input +24-11-19 20:43:18 | D | - Calibrating model.layers.5.self_attn.k_rotary_emb.output +24-11-19 20:43:18 | D | + w: None +24-11-19 20:43:18 | D | + x: None +24-11-19 20:43:18 | D | + y: sint8 +24-11-19 20:43:18 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:18 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:43:18 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:43:19 | D | - range ratio = [ 1.0000] +24-11-19 20:43:19 | D | sum error = [ 20.3689] +24-11-19 20:43:19 | D | best error = [ 20.3689] +24-11-19 20:43:19 | D | + error = [20.3689] +24-11-19 20:43:19 | D | - Calibrating model.layers.5.self_attn.v_proj.output +24-11-19 20:43:19 | D | + w: None +24-11-19 20:43:19 | D | + x: None +24-11-19 20:43:19 | D | + y: sint8 +24-11-19 20:43:19 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:19 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:43:19 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:43:20 | D | - range ratio = [ 1.0000] +24-11-19 20:43:20 | D | sum error = [ 30.7471] +24-11-19 20:43:20 | D | best error = [ 30.7471] +24-11-19 20:43:20 | D | + error = [30.7471] +24-11-19 20:43:20 | D | - Calibrating model.layers.5.self_attn.o_proj.input +24-11-19 20:43:20 | D | - Calibrating model.layers.5.mlp.up_proj.input +24-11-19 20:43:20 | D | - Calibrating model.layers.5.mlp.down_proj.input +24-11-19 20:43:20 | D | - Quantizing model.layers.5.self_attn.q_proj (inputs) +24-11-19 20:43:20 | D | - Quantizing model.layers.5.self_attn.k_proj (inputs) +24-11-19 20:43:20 | D | - Quantizing model.layers.5.self_attn.v_proj (inputs and outputs) +24-11-19 20:43:20 | D | - Quantizing model.layers.5.self_attn.o_proj (inputs) +24-11-19 20:43:20 | D | - Quantizing model.layers.5.self_attn.k_rotary_emb (outputs) +24-11-19 20:43:20 | D | - Quantizing model.layers.5.mlp.gate_proj (inputs) +24-11-19 20:43:20 | D | - Quantizing model.layers.5.mlp.up_proj (inputs) +24-11-19 20:43:20 | D | - Quantizing model.layers.5.mlp.down_proj (inputs) +24-11-19 20:43:27 | D | - Quantizing layer model.layers.6 +24-11-19 20:43:27 | D | - Calibrating model.layers.6.self_attn.v_proj.input +24-11-19 20:43:27 | D | - Calibrating model.layers.6.self_attn.k_rotary_emb.output +24-11-19 20:43:27 | D | + w: None +24-11-19 20:43:27 | D | + x: None +24-11-19 20:43:27 | D | + y: sint8 +24-11-19 20:43:27 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:27 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:43:27 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:43:27 | D | - range ratio = [ 1.0000] +24-11-19 20:43:27 | D | sum error = [ 18.8118] +24-11-19 20:43:27 | D | best error = [ 18.8118] +24-11-19 20:43:27 | D | + error = [18.8118] +24-11-19 20:43:27 | D | - Calibrating model.layers.6.self_attn.v_proj.output +24-11-19 20:43:27 | D | + w: None +24-11-19 20:43:27 | D | + x: None +24-11-19 20:43:27 | D | + y: sint8 +24-11-19 20:43:27 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:27 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:43:28 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:43:28 | D | - range ratio = [ 1.0000] +24-11-19 20:43:28 | D | sum error = [ 24.6352] +24-11-19 20:43:28 | D | best error = [ 24.6352] +24-11-19 20:43:28 | D | + error = [24.6352] +24-11-19 20:43:28 | D | - Calibrating model.layers.6.self_attn.o_proj.input +24-11-19 20:43:28 | D | - Calibrating model.layers.6.mlp.up_proj.input +24-11-19 20:43:29 | D | - Calibrating model.layers.6.mlp.down_proj.input +24-11-19 20:43:29 | D | - Quantizing model.layers.6.self_attn.q_proj (inputs) +24-11-19 20:43:29 | D | - Quantizing model.layers.6.self_attn.k_proj (inputs) +24-11-19 20:43:29 | D | - Quantizing model.layers.6.self_attn.v_proj (inputs and outputs) +24-11-19 20:43:29 | D | - Quantizing model.layers.6.self_attn.o_proj (inputs) +24-11-19 20:43:29 | D | - Quantizing model.layers.6.self_attn.k_rotary_emb (outputs) +24-11-19 20:43:29 | D | - Quantizing model.layers.6.mlp.gate_proj (inputs) +24-11-19 20:43:29 | D | - Quantizing model.layers.6.mlp.up_proj (inputs) +24-11-19 20:43:29 | D | - Quantizing model.layers.6.mlp.down_proj (inputs) +24-11-19 20:43:35 | D | - Quantizing layer model.layers.7 +24-11-19 20:43:35 | D | - Calibrating model.layers.7.self_attn.v_proj.input +24-11-19 20:43:36 | D | - Calibrating model.layers.7.self_attn.k_rotary_emb.output +24-11-19 20:43:36 | D | + w: None +24-11-19 20:43:36 | D | + x: None +24-11-19 20:43:36 | D | + y: sint8 +24-11-19 20:43:36 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:36 | D | + finished parsing calibration arguments, ram usage: 13.1 +24-11-19 20:43:36 | D | + finished reseting calibrator, ram usage: 13.1 +24-11-19 20:43:36 | D | - range ratio = [ 1.0000] +24-11-19 20:43:36 | D | sum error = [ 25.8581] +24-11-19 20:43:36 | D | best error = [ 25.8581] +24-11-19 20:43:36 | D | + error = [25.8581] +24-11-19 20:43:36 | D | - Calibrating model.layers.7.self_attn.v_proj.output +24-11-19 20:43:36 | D | + w: None +24-11-19 20:43:36 | D | + x: None +24-11-19 20:43:36 | D | + y: sint8 +24-11-19 20:43:36 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:36 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:43:37 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:43:37 | D | - range ratio = [ 1.0000] +24-11-19 20:43:37 | D | sum error = [ 23.6176] +24-11-19 20:43:37 | D | best error = [ 23.6176] +24-11-19 20:43:37 | D | + error = [23.6176] +24-11-19 20:43:37 | D | - Calibrating model.layers.7.self_attn.o_proj.input +24-11-19 20:43:37 | D | - Calibrating model.layers.7.mlp.up_proj.input +24-11-19 20:43:37 | D | - Calibrating model.layers.7.mlp.down_proj.input +24-11-19 20:43:37 | D | - Quantizing model.layers.7.self_attn.q_proj (inputs) +24-11-19 20:43:37 | D | - Quantizing model.layers.7.self_attn.k_proj (inputs) +24-11-19 20:43:37 | D | - Quantizing model.layers.7.self_attn.v_proj (inputs and outputs) +24-11-19 20:43:37 | D | - Quantizing model.layers.7.self_attn.o_proj (inputs) +24-11-19 20:43:37 | D | - Quantizing model.layers.7.self_attn.k_rotary_emb (outputs) +24-11-19 20:43:37 | D | - Quantizing model.layers.7.mlp.gate_proj (inputs) +24-11-19 20:43:37 | D | - Quantizing model.layers.7.mlp.up_proj (inputs) +24-11-19 20:43:37 | D | - Quantizing model.layers.7.mlp.down_proj (inputs) +24-11-19 20:43:44 | D | - Quantizing layer model.layers.8 +24-11-19 20:43:44 | D | - Calibrating model.layers.8.self_attn.v_proj.input +24-11-19 20:43:44 | D | - Calibrating model.layers.8.self_attn.k_rotary_emb.output +24-11-19 20:43:44 | D | + w: None +24-11-19 20:43:44 | D | + x: None +24-11-19 20:43:44 | D | + y: sint8 +24-11-19 20:43:44 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:44 | D | + finished parsing calibration arguments, ram usage: 14.1 +24-11-19 20:43:44 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:43:44 | D | - range ratio = [ 1.0000] +24-11-19 20:43:44 | D | sum error = [ 22.3405] +24-11-19 20:43:44 | D | best error = [ 22.3405] +24-11-19 20:43:44 | D | + error = [22.3405] +24-11-19 20:43:45 | D | - Calibrating model.layers.8.self_attn.v_proj.output +24-11-19 20:43:45 | D | + w: None +24-11-19 20:43:45 | D | + x: None +24-11-19 20:43:45 | D | + y: sint8 +24-11-19 20:43:45 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:45 | D | + finished parsing calibration arguments, ram usage: 14.1 +24-11-19 20:43:45 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:43:45 | D | - range ratio = [ 1.0000] +24-11-19 20:43:45 | D | sum error = [ 22.3038] +24-11-19 20:43:45 | D | best error = [ 22.3038] +24-11-19 20:43:45 | D | + error = [22.3038] +24-11-19 20:43:45 | D | - Calibrating model.layers.8.self_attn.o_proj.input +24-11-19 20:43:45 | D | - Calibrating model.layers.8.mlp.up_proj.input +24-11-19 20:43:45 | D | - Calibrating model.layers.8.mlp.down_proj.input +24-11-19 20:43:46 | D | - Quantizing model.layers.8.self_attn.q_proj (inputs) +24-11-19 20:43:46 | D | - Quantizing model.layers.8.self_attn.k_proj (inputs) +24-11-19 20:43:46 | D | - Quantizing model.layers.8.self_attn.v_proj (inputs and outputs) +24-11-19 20:43:46 | D | - Quantizing model.layers.8.self_attn.o_proj (inputs) +24-11-19 20:43:46 | D | - Quantizing model.layers.8.self_attn.k_rotary_emb (outputs) +24-11-19 20:43:46 | D | - Quantizing model.layers.8.mlp.gate_proj (inputs) +24-11-19 20:43:46 | D | - Quantizing model.layers.8.mlp.up_proj (inputs) +24-11-19 20:43:46 | D | - Quantizing model.layers.8.mlp.down_proj (inputs) +24-11-19 20:43:52 | D | - Quantizing layer model.layers.9 +24-11-19 20:43:52 | D | - Calibrating model.layers.9.self_attn.v_proj.input +24-11-19 20:43:52 | D | - Calibrating model.layers.9.self_attn.k_rotary_emb.output +24-11-19 20:43:52 | D | + w: None +24-11-19 20:43:52 | D | + x: None +24-11-19 20:43:52 | D | + y: sint8 +24-11-19 20:43:52 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:52 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:43:52 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:43:53 | D | - range ratio = [ 1.0000] +24-11-19 20:43:53 | D | sum error = [ 23.7120] +24-11-19 20:43:53 | D | best error = [ 23.7120] +24-11-19 20:43:53 | D | + error = [23.7120] +24-11-19 20:43:53 | D | - Calibrating model.layers.9.self_attn.v_proj.output +24-11-19 20:43:53 | D | + w: None +24-11-19 20:43:53 | D | + x: None +24-11-19 20:43:53 | D | + y: sint8 +24-11-19 20:43:53 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:53 | D | + finished parsing calibration arguments, ram usage: 14.1 +24-11-19 20:43:53 | D | + finished reseting calibrator, ram usage: 14.3 +24-11-19 20:43:54 | D | - range ratio = [ 1.0000] +24-11-19 20:43:54 | D | sum error = [ 59.9128] +24-11-19 20:43:54 | D | best error = [ 59.9128] +24-11-19 20:43:54 | D | + error = [59.9128] +24-11-19 20:43:54 | D | - Calibrating model.layers.9.self_attn.o_proj.input +24-11-19 20:43:54 | D | - Calibrating model.layers.9.mlp.up_proj.input +24-11-19 20:43:54 | D | - Calibrating model.layers.9.mlp.down_proj.input +24-11-19 20:43:54 | D | - Quantizing model.layers.9.self_attn.q_proj (inputs) +24-11-19 20:43:54 | D | - Quantizing model.layers.9.self_attn.k_proj (inputs) +24-11-19 20:43:54 | D | - Quantizing model.layers.9.self_attn.v_proj (inputs and outputs) +24-11-19 20:43:54 | D | - Quantizing model.layers.9.self_attn.o_proj (inputs) +24-11-19 20:43:54 | D | - Quantizing model.layers.9.self_attn.k_rotary_emb (outputs) +24-11-19 20:43:54 | D | - Quantizing model.layers.9.mlp.gate_proj (inputs) +24-11-19 20:43:54 | D | - Quantizing model.layers.9.mlp.up_proj (inputs) +24-11-19 20:43:54 | D | - Quantizing model.layers.9.mlp.down_proj (inputs) +24-11-19 20:44:00 | D | - Quantizing layer model.layers.10 +24-11-19 20:44:00 | D | - Calibrating model.layers.10.self_attn.v_proj.input +24-11-19 20:44:00 | D | - Calibrating model.layers.10.self_attn.k_rotary_emb.output +24-11-19 20:44:00 | D | + w: None +24-11-19 20:44:00 | D | + x: None +24-11-19 20:44:00 | D | + y: sint8 +24-11-19 20:44:00 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:00 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:44:00 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:44:01 | D | - range ratio = [ 1.0000] +24-11-19 20:44:01 | D | sum error = [ 21.4013] +24-11-19 20:44:01 | D | best error = [ 21.4013] +24-11-19 20:44:01 | D | + error = [21.4013] +24-11-19 20:44:01 | D | - Calibrating model.layers.10.self_attn.v_proj.output +24-11-19 20:44:01 | D | + w: None +24-11-19 20:44:01 | D | + x: None +24-11-19 20:44:01 | D | + y: sint8 +24-11-19 20:44:01 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:01 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:44:01 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:44:02 | D | - range ratio = [ 1.0000] +24-11-19 20:44:02 | D | sum error = [ 34.8545] +24-11-19 20:44:02 | D | best error = [ 34.8545] +24-11-19 20:44:02 | D | + error = [34.8545] +24-11-19 20:44:02 | D | - Calibrating model.layers.10.self_attn.o_proj.input +24-11-19 20:44:02 | D | - Calibrating model.layers.10.mlp.up_proj.input +24-11-19 20:44:02 | D | - Calibrating model.layers.10.mlp.down_proj.input +24-11-19 20:44:02 | D | - Quantizing model.layers.10.self_attn.q_proj (inputs) +24-11-19 20:44:02 | D | - Quantizing model.layers.10.self_attn.k_proj (inputs) +24-11-19 20:44:02 | D | - Quantizing model.layers.10.self_attn.v_proj (inputs and outputs) +24-11-19 20:44:02 | D | - Quantizing model.layers.10.self_attn.o_proj (inputs) +24-11-19 20:44:02 | D | - Quantizing model.layers.10.self_attn.k_rotary_emb (outputs) +24-11-19 20:44:02 | D | - Quantizing model.layers.10.mlp.gate_proj (inputs) +24-11-19 20:44:02 | D | - Quantizing model.layers.10.mlp.up_proj (inputs) +24-11-19 20:44:02 | D | - Quantizing model.layers.10.mlp.down_proj (inputs) +24-11-19 20:44:09 | D | - Quantizing layer model.layers.11 +24-11-19 20:44:09 | D | - Calibrating model.layers.11.self_attn.v_proj.input +24-11-19 20:44:09 | D | - Calibrating model.layers.11.self_attn.k_rotary_emb.output +24-11-19 20:44:09 | D | + w: None +24-11-19 20:44:09 | D | + x: None +24-11-19 20:44:09 | D | + y: sint8 +24-11-19 20:44:09 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:09 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:44:09 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:44:09 | D | - range ratio = [ 1.0000] +24-11-19 20:44:09 | D | sum error = [ 25.4689] +24-11-19 20:44:09 | D | best error = [ 25.4689] +24-11-19 20:44:09 | D | + error = [25.4689] +24-11-19 20:44:09 | D | - Calibrating model.layers.11.self_attn.v_proj.output +24-11-19 20:44:09 | D | + w: None +24-11-19 20:44:09 | D | + x: None +24-11-19 20:44:09 | D | + y: sint8 +24-11-19 20:44:09 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:09 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:44:10 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:44:10 | D | - range ratio = [ 1.0000] +24-11-19 20:44:10 | D | sum error = [ 27.3372] +24-11-19 20:44:10 | D | best error = [ 27.3372] +24-11-19 20:44:10 | D | + error = [27.3372] +24-11-19 20:44:10 | D | - Calibrating model.layers.11.self_attn.o_proj.input +24-11-19 20:44:10 | D | - Calibrating model.layers.11.mlp.up_proj.input +24-11-19 20:44:10 | D | - Calibrating model.layers.11.mlp.down_proj.input +24-11-19 20:44:10 | D | - Quantizing model.layers.11.self_attn.q_proj (inputs) +24-11-19 20:44:10 | D | - Quantizing model.layers.11.self_attn.k_proj (inputs) +24-11-19 20:44:10 | D | - Quantizing model.layers.11.self_attn.v_proj (inputs and outputs) +24-11-19 20:44:10 | D | - Quantizing model.layers.11.self_attn.o_proj (inputs) +24-11-19 20:44:10 | D | - Quantizing model.layers.11.self_attn.k_rotary_emb (outputs) +24-11-19 20:44:10 | D | - Quantizing model.layers.11.mlp.gate_proj (inputs) +24-11-19 20:44:10 | D | - Quantizing model.layers.11.mlp.up_proj (inputs) +24-11-19 20:44:10 | D | - Quantizing model.layers.11.mlp.down_proj (inputs) +24-11-19 20:44:17 | D | - Quantizing layer model.layers.12 +24-11-19 20:44:17 | D | - Calibrating model.layers.12.self_attn.v_proj.input +24-11-19 20:44:17 | D | - Calibrating model.layers.12.self_attn.k_rotary_emb.output +24-11-19 20:44:17 | D | + w: None +24-11-19 20:44:17 | D | + x: None +24-11-19 20:44:17 | D | + y: sint8 +24-11-19 20:44:17 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:17 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:44:17 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:44:18 | D | - range ratio = [ 1.0000] +24-11-19 20:44:18 | D | sum error = [ 33.4518] +24-11-19 20:44:18 | D | best error = [ 33.4518] +24-11-19 20:44:18 | D | + error = [33.4518] +24-11-19 20:44:18 | D | - Calibrating model.layers.12.self_attn.v_proj.output +24-11-19 20:44:18 | D | + w: None +24-11-19 20:44:18 | D | + x: None +24-11-19 20:44:18 | D | + y: sint8 +24-11-19 20:44:18 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:18 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:44:18 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:44:19 | D | - range ratio = [ 1.0000] +24-11-19 20:44:19 | D | sum error = [ 22.6205] +24-11-19 20:44:19 | D | best error = [ 22.6205] +24-11-19 20:44:19 | D | + error = [22.6205] +24-11-19 20:44:19 | D | - Calibrating model.layers.12.self_attn.o_proj.input +24-11-19 20:44:19 | D | - Calibrating model.layers.12.mlp.up_proj.input +24-11-19 20:44:19 | D | - Calibrating model.layers.12.mlp.down_proj.input +24-11-19 20:44:19 | D | - Quantizing model.layers.12.self_attn.q_proj (inputs) +24-11-19 20:44:19 | D | - Quantizing model.layers.12.self_attn.k_proj (inputs) +24-11-19 20:44:19 | D | - Quantizing model.layers.12.self_attn.v_proj (inputs and outputs) +24-11-19 20:44:19 | D | - Quantizing model.layers.12.self_attn.o_proj (inputs) +24-11-19 20:44:19 | D | - Quantizing model.layers.12.self_attn.k_rotary_emb (outputs) +24-11-19 20:44:19 | D | - Quantizing model.layers.12.mlp.gate_proj (inputs) +24-11-19 20:44:19 | D | - Quantizing model.layers.12.mlp.up_proj (inputs) +24-11-19 20:44:19 | D | - Quantizing model.layers.12.mlp.down_proj (inputs) +24-11-19 20:44:27 | D | - Quantizing layer model.layers.13 +24-11-19 20:44:27 | D | - Calibrating model.layers.13.self_attn.v_proj.input +24-11-19 20:44:27 | D | - Calibrating model.layers.13.self_attn.k_rotary_emb.output +24-11-19 20:44:27 | D | + w: None +24-11-19 20:44:27 | D | + x: None +24-11-19 20:44:27 | D | + y: sint8 +24-11-19 20:44:27 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:27 | D | + finished parsing calibration arguments, ram usage: 12.9 +24-11-19 20:44:27 | D | + finished reseting calibrator, ram usage: 12.9 +24-11-19 20:44:28 | D | - range ratio = [ 1.0000] +24-11-19 20:44:28 | D | sum error = [ 27.0379] +24-11-19 20:44:28 | D | best error = [ 27.0379] +24-11-19 20:44:28 | D | + error = [27.0379] +24-11-19 20:44:28 | D | - Calibrating model.layers.13.self_attn.v_proj.output +24-11-19 20:44:28 | D | + w: None +24-11-19 20:44:28 | D | + x: None +24-11-19 20:44:28 | D | + y: sint8 +24-11-19 20:44:28 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:28 | D | + finished parsing calibration arguments, ram usage: 13.1 +24-11-19 20:44:28 | D | + finished reseting calibrator, ram usage: 13.1 +24-11-19 20:44:28 | D | - range ratio = [ 1.0000] +24-11-19 20:44:28 | D | sum error = [ 26.5161] +24-11-19 20:44:28 | D | best error = [ 26.5161] +24-11-19 20:44:28 | D | + error = [26.5161] +24-11-19 20:44:28 | D | - Calibrating model.layers.13.self_attn.o_proj.input +24-11-19 20:44:28 | D | - Calibrating model.layers.13.mlp.up_proj.input +24-11-19 20:44:29 | D | - Calibrating model.layers.13.mlp.down_proj.input +24-11-19 20:44:29 | D | - Quantizing model.layers.13.self_attn.q_proj (inputs) +24-11-19 20:44:29 | D | - Quantizing model.layers.13.self_attn.k_proj (inputs) +24-11-19 20:44:29 | D | - Quantizing model.layers.13.self_attn.v_proj (inputs and outputs) +24-11-19 20:44:29 | D | - Quantizing model.layers.13.self_attn.o_proj (inputs) +24-11-19 20:44:29 | D | - Quantizing model.layers.13.self_attn.k_rotary_emb (outputs) +24-11-19 20:44:29 | D | - Quantizing model.layers.13.mlp.gate_proj (inputs) +24-11-19 20:44:29 | D | - Quantizing model.layers.13.mlp.up_proj (inputs) +24-11-19 20:44:29 | D | - Quantizing model.layers.13.mlp.down_proj (inputs) +24-11-19 20:44:36 | D | - Quantizing layer model.layers.14 +24-11-19 20:44:36 | D | - Calibrating model.layers.14.self_attn.v_proj.input +24-11-19 20:44:36 | D | - Calibrating model.layers.14.self_attn.k_rotary_emb.output +24-11-19 20:44:36 | D | + w: None +24-11-19 20:44:36 | D | + x: None +24-11-19 20:44:36 | D | + y: sint8 +24-11-19 20:44:36 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:36 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:44:36 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:44:37 | D | - range ratio = [ 1.0000] +24-11-19 20:44:37 | D | sum error = [ 31.7882] +24-11-19 20:44:37 | D | best error = [ 31.7882] +24-11-19 20:44:37 | D | + error = [31.7882] +24-11-19 20:44:37 | D | - Calibrating model.layers.14.self_attn.v_proj.output +24-11-19 20:44:37 | D | + w: None +24-11-19 20:44:37 | D | + x: None +24-11-19 20:44:37 | D | + y: sint8 +24-11-19 20:44:37 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:37 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:44:37 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:44:38 | D | - range ratio = [ 1.0000] +24-11-19 20:44:38 | D | sum error = [ 24.9399] +24-11-19 20:44:38 | D | best error = [ 24.9399] +24-11-19 20:44:38 | D | + error = [24.9399] +24-11-19 20:44:38 | D | - Calibrating model.layers.14.self_attn.o_proj.input +24-11-19 20:44:38 | D | - Calibrating model.layers.14.mlp.up_proj.input +24-11-19 20:44:38 | D | - Calibrating model.layers.14.mlp.down_proj.input +24-11-19 20:44:38 | D | - Quantizing model.layers.14.self_attn.q_proj (inputs) +24-11-19 20:44:38 | D | - Quantizing model.layers.14.self_attn.k_proj (inputs) +24-11-19 20:44:38 | D | - Quantizing model.layers.14.self_attn.v_proj (inputs and outputs) +24-11-19 20:44:38 | D | - Quantizing model.layers.14.self_attn.o_proj (inputs) +24-11-19 20:44:38 | D | - Quantizing model.layers.14.self_attn.k_rotary_emb (outputs) +24-11-19 20:44:38 | D | - Quantizing model.layers.14.mlp.gate_proj (inputs) +24-11-19 20:44:38 | D | - Quantizing model.layers.14.mlp.up_proj (inputs) +24-11-19 20:44:38 | D | - Quantizing model.layers.14.mlp.down_proj (inputs) +24-11-19 20:44:46 | D | - Quantizing layer model.layers.15 +24-11-19 20:44:46 | D | - Calibrating model.layers.15.self_attn.v_proj.input +24-11-19 20:44:46 | D | - Calibrating model.layers.15.self_attn.k_rotary_emb.output +24-11-19 20:44:46 | D | + w: None +24-11-19 20:44:46 | D | + x: None +24-11-19 20:44:46 | D | + y: sint8 +24-11-19 20:44:46 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:46 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:44:46 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:44:46 | D | - range ratio = [ 1.0000] +24-11-19 20:44:46 | D | sum error = [ 31.4752] +24-11-19 20:44:46 | D | best error = [ 31.4752] +24-11-19 20:44:46 | D | + error = [31.4752] +24-11-19 20:44:46 | D | - Calibrating model.layers.15.self_attn.v_proj.output +24-11-19 20:44:46 | D | + w: None +24-11-19 20:44:46 | D | + x: None +24-11-19 20:44:46 | D | + y: sint8 +24-11-19 20:44:46 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:46 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:44:47 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:44:47 | D | - range ratio = [ 1.0000] +24-11-19 20:44:47 | D | sum error = [ 46.2397] +24-11-19 20:44:47 | D | best error = [ 46.2397] +24-11-19 20:44:47 | D | + error = [46.2397] +24-11-19 20:44:47 | D | - Calibrating model.layers.15.self_attn.o_proj.input +24-11-19 20:44:47 | D | - Calibrating model.layers.15.mlp.up_proj.input +24-11-19 20:44:47 | D | - Calibrating model.layers.15.mlp.down_proj.input +24-11-19 20:44:47 | D | - Quantizing model.layers.15.self_attn.q_proj (inputs) +24-11-19 20:44:47 | D | - Quantizing model.layers.15.self_attn.k_proj (inputs) +24-11-19 20:44:47 | D | - Quantizing model.layers.15.self_attn.v_proj (inputs and outputs) +24-11-19 20:44:47 | D | - Quantizing model.layers.15.self_attn.o_proj (inputs) +24-11-19 20:44:47 | D | - Quantizing model.layers.15.self_attn.k_rotary_emb (outputs) +24-11-19 20:44:47 | D | - Quantizing model.layers.15.mlp.gate_proj (inputs) +24-11-19 20:44:47 | D | - Quantizing model.layers.15.mlp.up_proj (inputs) +24-11-19 20:44:47 | D | - Quantizing model.layers.15.mlp.down_proj (inputs) +24-11-19 20:44:54 | D | - Quantizing layer model.layers.16 +24-11-19 20:44:54 | D | - Calibrating model.layers.16.self_attn.v_proj.input +24-11-19 20:44:54 | D | - Calibrating model.layers.16.self_attn.k_rotary_emb.output +24-11-19 20:44:54 | D | + w: None +24-11-19 20:44:54 | D | + x: None +24-11-19 20:44:54 | D | + y: sint8 +24-11-19 20:44:54 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:54 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:44:55 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:44:55 | D | - range ratio = [ 1.0000] +24-11-19 20:44:55 | D | sum error = [ 35.6233] +24-11-19 20:44:55 | D | best error = [ 35.6233] +24-11-19 20:44:55 | D | + error = [35.6233] +24-11-19 20:44:55 | D | - Calibrating model.layers.16.self_attn.v_proj.output +24-11-19 20:44:55 | D | + w: None +24-11-19 20:44:55 | D | + x: None +24-11-19 20:44:55 | D | + y: sint8 +24-11-19 20:44:55 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:55 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:44:55 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:44:56 | D | - range ratio = [ 1.0000] +24-11-19 20:44:56 | D | sum error = [ 37.9692] +24-11-19 20:44:56 | D | best error = [ 37.9692] +24-11-19 20:44:56 | D | + error = [37.9692] +24-11-19 20:44:56 | D | - Calibrating model.layers.16.self_attn.o_proj.input +24-11-19 20:44:56 | D | - Calibrating model.layers.16.mlp.up_proj.input +24-11-19 20:44:56 | D | - Calibrating model.layers.16.mlp.down_proj.input +24-11-19 20:44:56 | D | - Quantizing model.layers.16.self_attn.q_proj (inputs) +24-11-19 20:44:56 | D | - Quantizing model.layers.16.self_attn.k_proj (inputs) +24-11-19 20:44:56 | D | - Quantizing model.layers.16.self_attn.v_proj (inputs and outputs) +24-11-19 20:44:56 | D | - Quantizing model.layers.16.self_attn.o_proj (inputs) +24-11-19 20:44:56 | D | - Quantizing model.layers.16.self_attn.k_rotary_emb (outputs) +24-11-19 20:44:56 | D | - Quantizing model.layers.16.mlp.gate_proj (inputs) +24-11-19 20:44:56 | D | - Quantizing model.layers.16.mlp.up_proj (inputs) +24-11-19 20:44:56 | D | - Quantizing model.layers.16.mlp.down_proj (inputs) +24-11-19 20:45:03 | D | - Quantizing layer model.layers.17 +24-11-19 20:45:03 | D | - Calibrating model.layers.17.self_attn.v_proj.input +24-11-19 20:45:03 | D | - Calibrating model.layers.17.self_attn.k_rotary_emb.output +24-11-19 20:45:03 | D | + w: None +24-11-19 20:45:03 | D | + x: None +24-11-19 20:45:03 | D | + y: sint8 +24-11-19 20:45:03 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:03 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:45:03 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:45:04 | D | - range ratio = [ 1.0000] +24-11-19 20:45:04 | D | sum error = [ 30.9909] +24-11-19 20:45:04 | D | best error = [ 30.9909] +24-11-19 20:45:04 | D | + error = [30.9909] +24-11-19 20:45:04 | D | - Calibrating model.layers.17.self_attn.v_proj.output +24-11-19 20:45:04 | D | + w: None +24-11-19 20:45:04 | D | + x: None +24-11-19 20:45:04 | D | + y: sint8 +24-11-19 20:45:04 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:04 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:45:04 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:45:05 | D | - range ratio = [ 1.0000] +24-11-19 20:45:05 | D | sum error = [ 57.4258] +24-11-19 20:45:05 | D | best error = [ 57.4258] +24-11-19 20:45:05 | D | + error = [57.4258] +24-11-19 20:45:05 | D | - Calibrating model.layers.17.self_attn.o_proj.input +24-11-19 20:45:05 | D | - Calibrating model.layers.17.mlp.up_proj.input +24-11-19 20:45:05 | D | - Calibrating model.layers.17.mlp.down_proj.input +24-11-19 20:45:05 | D | - Quantizing model.layers.17.self_attn.q_proj (inputs) +24-11-19 20:45:05 | D | - Quantizing model.layers.17.self_attn.k_proj (inputs) +24-11-19 20:45:05 | D | - Quantizing model.layers.17.self_attn.v_proj (inputs and outputs) +24-11-19 20:45:05 | D | - Quantizing model.layers.17.self_attn.o_proj (inputs) +24-11-19 20:45:05 | D | - Quantizing model.layers.17.self_attn.k_rotary_emb (outputs) +24-11-19 20:45:05 | D | - Quantizing model.layers.17.mlp.gate_proj (inputs) +24-11-19 20:45:05 | D | - Quantizing model.layers.17.mlp.up_proj (inputs) +24-11-19 20:45:05 | D | - Quantizing model.layers.17.mlp.down_proj (inputs) +24-11-19 20:45:12 | D | - Quantizing layer model.layers.18 +24-11-19 20:45:12 | D | - Calibrating model.layers.18.self_attn.v_proj.input +24-11-19 20:45:12 | D | - Calibrating model.layers.18.self_attn.k_rotary_emb.output +24-11-19 20:45:12 | D | + w: None +24-11-19 20:45:12 | D | + x: None +24-11-19 20:45:12 | D | + y: sint8 +24-11-19 20:45:12 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:12 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:45:12 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:45:13 | D | - range ratio = [ 1.0000] +24-11-19 20:45:13 | D | sum error = [ 25.3720] +24-11-19 20:45:13 | D | best error = [ 25.3720] +24-11-19 20:45:13 | D | + error = [25.3720] +24-11-19 20:45:13 | D | - Calibrating model.layers.18.self_attn.v_proj.output +24-11-19 20:45:13 | D | + w: None +24-11-19 20:45:13 | D | + x: None +24-11-19 20:45:13 | D | + y: sint8 +24-11-19 20:45:13 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:13 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:45:13 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:45:14 | D | - range ratio = [ 1.0000] +24-11-19 20:45:14 | D | sum error = [ 66.0689] +24-11-19 20:45:14 | D | best error = [ 66.0689] +24-11-19 20:45:14 | D | + error = [66.0689] +24-11-19 20:45:14 | D | - Calibrating model.layers.18.self_attn.o_proj.input +24-11-19 20:45:14 | D | - Calibrating model.layers.18.mlp.up_proj.input +24-11-19 20:45:14 | D | - Calibrating model.layers.18.mlp.down_proj.input +24-11-19 20:45:14 | D | - Quantizing model.layers.18.self_attn.q_proj (inputs) +24-11-19 20:45:14 | D | - Quantizing model.layers.18.self_attn.k_proj (inputs) +24-11-19 20:45:14 | D | - Quantizing model.layers.18.self_attn.v_proj (inputs and outputs) +24-11-19 20:45:14 | D | - Quantizing model.layers.18.self_attn.o_proj (inputs) +24-11-19 20:45:14 | D | - Quantizing model.layers.18.self_attn.k_rotary_emb (outputs) +24-11-19 20:45:14 | D | - Quantizing model.layers.18.mlp.gate_proj (inputs) +24-11-19 20:45:14 | D | - Quantizing model.layers.18.mlp.up_proj (inputs) +24-11-19 20:45:14 | D | - Quantizing model.layers.18.mlp.down_proj (inputs) +24-11-19 20:45:21 | D | - Quantizing layer model.layers.19 +24-11-19 20:45:21 | D | - Calibrating model.layers.19.self_attn.v_proj.input +24-11-19 20:45:21 | D | - Calibrating model.layers.19.self_attn.k_rotary_emb.output +24-11-19 20:45:21 | D | + w: None +24-11-19 20:45:21 | D | + x: None +24-11-19 20:45:21 | D | + y: sint8 +24-11-19 20:45:21 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:21 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:45:21 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:45:21 | D | - range ratio = [ 1.0000] +24-11-19 20:45:21 | D | sum error = [ 24.2636] +24-11-19 20:45:21 | D | best error = [ 24.2636] +24-11-19 20:45:21 | D | + error = [24.2636] +24-11-19 20:45:22 | D | - Calibrating model.layers.19.self_attn.v_proj.output +24-11-19 20:45:22 | D | + w: None +24-11-19 20:45:22 | D | + x: None +24-11-19 20:45:22 | D | + y: sint8 +24-11-19 20:45:22 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:22 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:45:22 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:45:22 | D | - range ratio = [ 1.0000] +24-11-19 20:45:22 | D | sum error = [ 62.9339] +24-11-19 20:45:22 | D | best error = [ 62.9339] +24-11-19 20:45:22 | D | + error = [62.9339] +24-11-19 20:45:22 | D | - Calibrating model.layers.19.self_attn.o_proj.input +24-11-19 20:45:22 | D | - Calibrating model.layers.19.mlp.up_proj.input +24-11-19 20:45:23 | D | - Calibrating model.layers.19.mlp.down_proj.input +24-11-19 20:45:23 | D | - Quantizing model.layers.19.self_attn.q_proj (inputs) +24-11-19 20:45:23 | D | - Quantizing model.layers.19.self_attn.k_proj (inputs) +24-11-19 20:45:23 | D | - Quantizing model.layers.19.self_attn.v_proj (inputs and outputs) +24-11-19 20:45:23 | D | - Quantizing model.layers.19.self_attn.o_proj (inputs) +24-11-19 20:45:23 | D | - Quantizing model.layers.19.self_attn.k_rotary_emb (outputs) +24-11-19 20:45:23 | D | - Quantizing model.layers.19.mlp.gate_proj (inputs) +24-11-19 20:45:23 | D | - Quantizing model.layers.19.mlp.up_proj (inputs) +24-11-19 20:45:23 | D | - Quantizing model.layers.19.mlp.down_proj (inputs) +24-11-19 20:45:29 | D | - Quantizing layer model.layers.20 +24-11-19 20:45:29 | D | - Calibrating model.layers.20.self_attn.v_proj.input +24-11-19 20:45:30 | D | - Calibrating model.layers.20.self_attn.k_rotary_emb.output +24-11-19 20:45:30 | D | + w: None +24-11-19 20:45:30 | D | + x: None +24-11-19 20:45:30 | D | + y: sint8 +24-11-19 20:45:30 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:30 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:45:30 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:45:30 | D | - range ratio = [ 1.0000] +24-11-19 20:45:30 | D | sum error = [ 24.2666] +24-11-19 20:45:30 | D | best error = [ 24.2666] +24-11-19 20:45:30 | D | + error = [24.2666] +24-11-19 20:45:30 | D | - Calibrating model.layers.20.self_attn.v_proj.output +24-11-19 20:45:30 | D | + w: None +24-11-19 20:45:30 | D | + x: None +24-11-19 20:45:30 | D | + y: sint8 +24-11-19 20:45:30 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:30 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:45:31 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:45:31 | D | - range ratio = [ 1.0000] +24-11-19 20:45:31 | D | sum error = [ 61.1436] +24-11-19 20:45:31 | D | best error = [ 61.1436] +24-11-19 20:45:31 | D | + error = [61.1436] +24-11-19 20:45:31 | D | - Calibrating model.layers.20.self_attn.o_proj.input +24-11-19 20:45:31 | D | - Calibrating model.layers.20.mlp.up_proj.input +24-11-19 20:45:31 | D | - Calibrating model.layers.20.mlp.down_proj.input +24-11-19 20:45:31 | D | - Quantizing model.layers.20.self_attn.q_proj (inputs) +24-11-19 20:45:31 | D | - Quantizing model.layers.20.self_attn.k_proj (inputs) +24-11-19 20:45:31 | D | - Quantizing model.layers.20.self_attn.v_proj (inputs and outputs) +24-11-19 20:45:31 | D | - Quantizing model.layers.20.self_attn.o_proj (inputs) +24-11-19 20:45:31 | D | - Quantizing model.layers.20.self_attn.k_rotary_emb (outputs) +24-11-19 20:45:31 | D | - Quantizing model.layers.20.mlp.gate_proj (inputs) +24-11-19 20:45:31 | D | - Quantizing model.layers.20.mlp.up_proj (inputs) +24-11-19 20:45:31 | D | - Quantizing model.layers.20.mlp.down_proj (inputs) +24-11-19 20:45:38 | D | - Quantizing layer model.layers.21 +24-11-19 20:45:38 | D | - Calibrating model.layers.21.self_attn.v_proj.input +24-11-19 20:45:38 | D | - Calibrating model.layers.21.self_attn.k_rotary_emb.output +24-11-19 20:45:38 | D | + w: None +24-11-19 20:45:38 | D | + x: None +24-11-19 20:45:38 | D | + y: sint8 +24-11-19 20:45:38 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:38 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:45:39 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:45:39 | D | - range ratio = [ 1.0000] +24-11-19 20:45:39 | D | sum error = [ 36.9288] +24-11-19 20:45:39 | D | best error = [ 36.9288] +24-11-19 20:45:39 | D | + error = [36.9288] +24-11-19 20:45:39 | D | - Calibrating model.layers.21.self_attn.v_proj.output +24-11-19 20:45:39 | D | + w: None +24-11-19 20:45:39 | D | + x: None +24-11-19 20:45:39 | D | + y: sint8 +24-11-19 20:45:39 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:39 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:45:39 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:45:40 | D | - range ratio = [ 1.0000] +24-11-19 20:45:40 | D | sum error = [ 66.4639] +24-11-19 20:45:40 | D | best error = [ 66.4639] +24-11-19 20:45:40 | D | + error = [66.4639] +24-11-19 20:45:40 | D | - Calibrating model.layers.21.self_attn.o_proj.input +24-11-19 20:45:40 | D | - Calibrating model.layers.21.mlp.up_proj.input +24-11-19 20:45:40 | D | - Calibrating model.layers.21.mlp.down_proj.input +24-11-19 20:45:40 | D | - Quantizing model.layers.21.self_attn.q_proj (inputs) +24-11-19 20:45:40 | D | - Quantizing model.layers.21.self_attn.k_proj (inputs) +24-11-19 20:45:40 | D | - Quantizing model.layers.21.self_attn.v_proj (inputs and outputs) +24-11-19 20:45:40 | D | - Quantizing model.layers.21.self_attn.o_proj (inputs) +24-11-19 20:45:40 | D | - Quantizing model.layers.21.self_attn.k_rotary_emb (outputs) +24-11-19 20:45:40 | D | - Quantizing model.layers.21.mlp.gate_proj (inputs) +24-11-19 20:45:40 | D | - Quantizing model.layers.21.mlp.up_proj (inputs) +24-11-19 20:45:40 | D | - Quantizing model.layers.21.mlp.down_proj (inputs) +24-11-19 20:45:47 | D | - Quantizing layer model.layers.22 +24-11-19 20:45:47 | D | - Calibrating model.layers.22.self_attn.v_proj.input +24-11-19 20:45:47 | D | - Calibrating model.layers.22.self_attn.k_rotary_emb.output +24-11-19 20:45:47 | D | + w: None +24-11-19 20:45:47 | D | + x: None +24-11-19 20:45:47 | D | + y: sint8 +24-11-19 20:45:47 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:47 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:45:47 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:45:48 | D | - range ratio = [ 1.0000] +24-11-19 20:45:48 | D | sum error = [ 30.3904] +24-11-19 20:45:48 | D | best error = [ 30.3904] +24-11-19 20:45:48 | D | + error = [30.3904] +24-11-19 20:45:48 | D | - Calibrating model.layers.22.self_attn.v_proj.output +24-11-19 20:45:48 | D | + w: None +24-11-19 20:45:48 | D | + x: None +24-11-19 20:45:48 | D | + y: sint8 +24-11-19 20:45:48 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:48 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:45:48 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:45:49 | D | - range ratio = [ 1.0000] +24-11-19 20:45:49 | D | sum error = [ 72.5404] +24-11-19 20:45:49 | D | best error = [ 72.5404] +24-11-19 20:45:49 | D | + error = [72.5404] +24-11-19 20:45:49 | D | - Calibrating model.layers.22.self_attn.o_proj.input +24-11-19 20:45:49 | D | - Calibrating model.layers.22.mlp.up_proj.input +24-11-19 20:45:49 | D | - Calibrating model.layers.22.mlp.down_proj.input +24-11-19 20:45:49 | D | - Quantizing model.layers.22.self_attn.q_proj (inputs) +24-11-19 20:45:49 | D | - Quantizing model.layers.22.self_attn.k_proj (inputs) +24-11-19 20:45:49 | D | - Quantizing model.layers.22.self_attn.v_proj (inputs and outputs) +24-11-19 20:45:49 | D | - Quantizing model.layers.22.self_attn.o_proj (inputs) +24-11-19 20:45:49 | D | - Quantizing model.layers.22.self_attn.k_rotary_emb (outputs) +24-11-19 20:45:49 | D | - Quantizing model.layers.22.mlp.gate_proj (inputs) +24-11-19 20:45:49 | D | - Quantizing model.layers.22.mlp.up_proj (inputs) +24-11-19 20:45:49 | D | - Quantizing model.layers.22.mlp.down_proj (inputs) +24-11-19 20:45:56 | D | - Quantizing layer model.layers.23 +24-11-19 20:45:56 | D | - Calibrating model.layers.23.self_attn.v_proj.input +24-11-19 20:45:56 | D | - Calibrating model.layers.23.self_attn.k_rotary_emb.output +24-11-19 20:45:56 | D | + w: None +24-11-19 20:45:56 | D | + x: None +24-11-19 20:45:56 | D | + y: sint8 +24-11-19 20:45:56 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:56 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:45:56 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:45:57 | D | - range ratio = [ 1.0000] +24-11-19 20:45:57 | D | sum error = [ 31.5279] +24-11-19 20:45:57 | D | best error = [ 31.5279] +24-11-19 20:45:57 | D | + error = [31.5279] +24-11-19 20:45:57 | D | - Calibrating model.layers.23.self_attn.v_proj.output +24-11-19 20:45:57 | D | + w: None +24-11-19 20:45:57 | D | + x: None +24-11-19 20:45:57 | D | + y: sint8 +24-11-19 20:45:57 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:57 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:45:57 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:45:57 | D | - range ratio = [ 1.0000] +24-11-19 20:45:57 | D | sum error = [ 75.8991] +24-11-19 20:45:57 | D | best error = [ 75.8991] +24-11-19 20:45:57 | D | + error = [75.8991] +24-11-19 20:45:57 | D | - Calibrating model.layers.23.self_attn.o_proj.input +24-11-19 20:45:57 | D | - Calibrating model.layers.23.mlp.up_proj.input +24-11-19 20:45:57 | D | - Calibrating model.layers.23.mlp.down_proj.input +24-11-19 20:45:58 | D | - Quantizing model.layers.23.self_attn.q_proj (inputs) +24-11-19 20:45:58 | D | - Quantizing model.layers.23.self_attn.k_proj (inputs) +24-11-19 20:45:58 | D | - Quantizing model.layers.23.self_attn.v_proj (inputs and outputs) +24-11-19 20:45:58 | D | - Quantizing model.layers.23.self_attn.o_proj (inputs) +24-11-19 20:45:58 | D | - Quantizing model.layers.23.self_attn.k_rotary_emb (outputs) +24-11-19 20:45:58 | D | - Quantizing model.layers.23.mlp.gate_proj (inputs) +24-11-19 20:45:58 | D | - Quantizing model.layers.23.mlp.up_proj (inputs) +24-11-19 20:45:58 | D | - Quantizing model.layers.23.mlp.down_proj (inputs) +24-11-19 20:46:04 | D | - Quantizing layer model.layers.24 +24-11-19 20:46:04 | D | - Calibrating model.layers.24.self_attn.v_proj.input +24-11-19 20:46:04 | D | - Calibrating model.layers.24.self_attn.k_rotary_emb.output +24-11-19 20:46:04 | D | + w: None +24-11-19 20:46:04 | D | + x: None +24-11-19 20:46:04 | D | + y: sint8 +24-11-19 20:46:04 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:04 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:46:04 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:46:05 | D | - range ratio = [ 1.0000] +24-11-19 20:46:05 | D | sum error = [ 33.1648] +24-11-19 20:46:05 | D | best error = [ 33.1648] +24-11-19 20:46:05 | D | + error = [33.1648] +24-11-19 20:46:05 | D | - Calibrating model.layers.24.self_attn.v_proj.output +24-11-19 20:46:05 | D | + w: None +24-11-19 20:46:05 | D | + x: None +24-11-19 20:46:05 | D | + y: sint8 +24-11-19 20:46:05 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:05 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:46:05 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:46:06 | D | - range ratio = [ 1.0000] +24-11-19 20:46:06 | D | sum error = [ 86.3566] +24-11-19 20:46:06 | D | best error = [ 86.3566] +24-11-19 20:46:06 | D | + error = [86.3566] +24-11-19 20:46:06 | D | - Calibrating model.layers.24.self_attn.o_proj.input +24-11-19 20:46:06 | D | - Calibrating model.layers.24.mlp.up_proj.input +24-11-19 20:46:06 | D | - Calibrating model.layers.24.mlp.down_proj.input +24-11-19 20:46:06 | D | - Quantizing model.layers.24.self_attn.q_proj (inputs) +24-11-19 20:46:06 | D | - Quantizing model.layers.24.self_attn.k_proj (inputs) +24-11-19 20:46:06 | D | - Quantizing model.layers.24.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:06 | D | - Quantizing model.layers.24.self_attn.o_proj (inputs) +24-11-19 20:46:06 | D | - Quantizing model.layers.24.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:06 | D | - Quantizing model.layers.24.mlp.gate_proj (inputs) +24-11-19 20:46:06 | D | - Quantizing model.layers.24.mlp.up_proj (inputs) +24-11-19 20:46:06 | D | - Quantizing model.layers.24.mlp.down_proj (inputs) +24-11-19 20:46:12 | D | - Quantizing layer model.layers.25 +24-11-19 20:46:12 | D | - Calibrating model.layers.25.self_attn.v_proj.input +24-11-19 20:46:13 | D | - Calibrating model.layers.25.self_attn.k_rotary_emb.output +24-11-19 20:46:13 | D | + w: None +24-11-19 20:46:13 | D | + x: None +24-11-19 20:46:13 | D | + y: sint8 +24-11-19 20:46:13 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:13 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:46:13 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:46:13 | D | - range ratio = [ 1.0000] +24-11-19 20:46:13 | D | sum error = [ 46.1502] +24-11-19 20:46:13 | D | best error = [ 46.1502] +24-11-19 20:46:13 | D | + error = [46.1502] +24-11-19 20:46:13 | D | - Calibrating model.layers.25.self_attn.v_proj.output +24-11-19 20:46:13 | D | + w: None +24-11-19 20:46:13 | D | + x: None +24-11-19 20:46:13 | D | + y: sint8 +24-11-19 20:46:13 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:13 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:46:13 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:46:14 | D | - range ratio = [ 1.0000] +24-11-19 20:46:14 | D | sum error = [ 104.0143] +24-11-19 20:46:14 | D | best error = [ 104.0143] +24-11-19 20:46:14 | D | + error = [104.0143] +24-11-19 20:46:14 | D | - Calibrating model.layers.25.self_attn.o_proj.input +24-11-19 20:46:14 | D | - Calibrating model.layers.25.mlp.up_proj.input +24-11-19 20:46:14 | D | - Calibrating model.layers.25.mlp.down_proj.input +24-11-19 20:46:14 | D | - Quantizing model.layers.25.self_attn.q_proj (inputs) +24-11-19 20:46:14 | D | - Quantizing model.layers.25.self_attn.k_proj (inputs) +24-11-19 20:46:14 | D | - Quantizing model.layers.25.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:14 | D | - Quantizing model.layers.25.self_attn.o_proj (inputs) +24-11-19 20:46:14 | D | - Quantizing model.layers.25.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:14 | D | - Quantizing model.layers.25.mlp.gate_proj (inputs) +24-11-19 20:46:14 | D | - Quantizing model.layers.25.mlp.up_proj (inputs) +24-11-19 20:46:14 | D | - Quantizing model.layers.25.mlp.down_proj (inputs) +24-11-19 20:46:21 | D | - Quantizing layer model.layers.26 +24-11-19 20:46:21 | D | - Calibrating model.layers.26.self_attn.v_proj.input +24-11-19 20:46:21 | D | - Calibrating model.layers.26.self_attn.k_rotary_emb.output +24-11-19 20:46:21 | D | + w: None +24-11-19 20:46:21 | D | + x: None +24-11-19 20:46:21 | D | + y: sint8 +24-11-19 20:46:21 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:21 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:46:21 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:46:21 | D | - range ratio = [ 1.0000] +24-11-19 20:46:21 | D | sum error = [ 39.2391] +24-11-19 20:46:21 | D | best error = [ 39.2391] +24-11-19 20:46:21 | D | + error = [39.2391] +24-11-19 20:46:22 | D | - Calibrating model.layers.26.self_attn.v_proj.output +24-11-19 20:46:22 | D | + w: None +24-11-19 20:46:22 | D | + x: None +24-11-19 20:46:22 | D | + y: sint8 +24-11-19 20:46:22 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:22 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:46:22 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:46:22 | D | - range ratio = [ 1.0000] +24-11-19 20:46:22 | D | sum error = [ 88.9979] +24-11-19 20:46:22 | D | best error = [ 88.9979] +24-11-19 20:46:22 | D | + error = [88.9979] +24-11-19 20:46:22 | D | - Calibrating model.layers.26.self_attn.o_proj.input +24-11-19 20:46:22 | D | - Calibrating model.layers.26.mlp.up_proj.input +24-11-19 20:46:22 | D | - Calibrating model.layers.26.mlp.down_proj.input +24-11-19 20:46:22 | D | - Quantizing model.layers.26.self_attn.q_proj (inputs) +24-11-19 20:46:22 | D | - Quantizing model.layers.26.self_attn.k_proj (inputs) +24-11-19 20:46:22 | D | - Quantizing model.layers.26.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:22 | D | - Quantizing model.layers.26.self_attn.o_proj (inputs) +24-11-19 20:46:22 | D | - Quantizing model.layers.26.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:22 | D | - Quantizing model.layers.26.mlp.gate_proj (inputs) +24-11-19 20:46:22 | D | - Quantizing model.layers.26.mlp.up_proj (inputs) +24-11-19 20:46:22 | D | - Quantizing model.layers.26.mlp.down_proj (inputs) +24-11-19 20:46:29 | D | - Quantizing layer model.layers.27 +24-11-19 20:46:29 | D | - Calibrating model.layers.27.self_attn.v_proj.input +24-11-19 20:46:29 | D | - Calibrating model.layers.27.self_attn.k_rotary_emb.output +24-11-19 20:46:29 | D | + w: None +24-11-19 20:46:29 | D | + x: None +24-11-19 20:46:29 | D | + y: sint8 +24-11-19 20:46:29 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:29 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:46:30 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:46:30 | D | - range ratio = [ 1.0000] +24-11-19 20:46:30 | D | sum error = [ 44.9467] +24-11-19 20:46:30 | D | best error = [ 44.9467] +24-11-19 20:46:30 | D | + error = [44.9467] +24-11-19 20:46:30 | D | - Calibrating model.layers.27.self_attn.v_proj.output +24-11-19 20:46:30 | D | + w: None +24-11-19 20:46:30 | D | + x: None +24-11-19 20:46:30 | D | + y: sint8 +24-11-19 20:46:30 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:30 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:46:30 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:46:31 | D | - range ratio = [ 1.0000] +24-11-19 20:46:31 | D | sum error = [ 114.9813] +24-11-19 20:46:31 | D | best error = [ 114.9813] +24-11-19 20:46:31 | D | + error = [114.9813] +24-11-19 20:46:31 | D | - Calibrating model.layers.27.self_attn.o_proj.input +24-11-19 20:46:31 | D | - Calibrating model.layers.27.mlp.up_proj.input +24-11-19 20:46:31 | D | - Calibrating model.layers.27.mlp.down_proj.input +24-11-19 20:46:31 | D | - Quantizing model.layers.27.self_attn.q_proj (inputs) +24-11-19 20:46:31 | D | - Quantizing model.layers.27.self_attn.k_proj (inputs) +24-11-19 20:46:31 | D | - Quantizing model.layers.27.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:31 | D | - Quantizing model.layers.27.self_attn.o_proj (inputs) +24-11-19 20:46:31 | D | - Quantizing model.layers.27.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:31 | D | - Quantizing model.layers.27.mlp.gate_proj (inputs) +24-11-19 20:46:31 | D | - Quantizing model.layers.27.mlp.up_proj (inputs) +24-11-19 20:46:31 | D | - Quantizing model.layers.27.mlp.down_proj (inputs) +24-11-19 20:46:38 | D | - Quantizing layer model.layers.28 +24-11-19 20:46:38 | D | - Calibrating model.layers.28.self_attn.v_proj.input +24-11-19 20:46:38 | D | - Calibrating model.layers.28.self_attn.k_rotary_emb.output +24-11-19 20:46:38 | D | + w: None +24-11-19 20:46:38 | D | + x: None +24-11-19 20:46:38 | D | + y: sint8 +24-11-19 20:46:38 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:38 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:46:38 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:46:38 | D | - range ratio = [ 1.0000] +24-11-19 20:46:38 | D | sum error = [ 55.7607] +24-11-19 20:46:38 | D | best error = [ 55.7607] +24-11-19 20:46:38 | D | + error = [55.7607] +24-11-19 20:46:38 | D | - Calibrating model.layers.28.self_attn.v_proj.output +24-11-19 20:46:38 | D | + w: None +24-11-19 20:46:38 | D | + x: None +24-11-19 20:46:38 | D | + y: sint8 +24-11-19 20:46:38 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:38 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:46:39 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:46:39 | D | - range ratio = [ 1.0000] +24-11-19 20:46:39 | D | sum error = [ 121.6871] +24-11-19 20:46:39 | D | best error = [ 121.6871] +24-11-19 20:46:39 | D | + error = [121.6871] +24-11-19 20:46:39 | D | - Calibrating model.layers.28.self_attn.o_proj.input +24-11-19 20:46:39 | D | - Calibrating model.layers.28.mlp.up_proj.input +24-11-19 20:46:39 | D | - Calibrating model.layers.28.mlp.down_proj.input +24-11-19 20:46:39 | D | - Quantizing model.layers.28.self_attn.q_proj (inputs) +24-11-19 20:46:39 | D | - Quantizing model.layers.28.self_attn.k_proj (inputs) +24-11-19 20:46:39 | D | - Quantizing model.layers.28.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:39 | D | - Quantizing model.layers.28.self_attn.o_proj (inputs) +24-11-19 20:46:39 | D | - Quantizing model.layers.28.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:39 | D | - Quantizing model.layers.28.mlp.gate_proj (inputs) +24-11-19 20:46:39 | D | - Quantizing model.layers.28.mlp.up_proj (inputs) +24-11-19 20:46:39 | D | - Quantizing model.layers.28.mlp.down_proj (inputs) +24-11-19 20:46:46 | D | - Quantizing layer model.layers.29 +24-11-19 20:46:46 | D | - Calibrating model.layers.29.self_attn.v_proj.input +24-11-19 20:46:47 | D | - Calibrating model.layers.29.self_attn.k_rotary_emb.output +24-11-19 20:46:47 | D | + w: None +24-11-19 20:46:47 | D | + x: None +24-11-19 20:46:47 | D | + y: sint8 +24-11-19 20:46:47 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:47 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:46:47 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:46:47 | D | - range ratio = [ 1.0000] +24-11-19 20:46:47 | D | sum error = [ 77.0110] +24-11-19 20:46:47 | D | best error = [ 77.0110] +24-11-19 20:46:47 | D | + error = [77.0110] +24-11-19 20:46:47 | D | - Calibrating model.layers.29.self_attn.v_proj.output +24-11-19 20:46:47 | D | + w: None +24-11-19 20:46:47 | D | + x: None +24-11-19 20:46:47 | D | + y: sint8 +24-11-19 20:46:47 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:47 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:46:48 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:46:48 | D | - range ratio = [ 1.0000] +24-11-19 20:46:48 | D | sum error = [ 149.2457] +24-11-19 20:46:48 | D | best error = [ 149.2457] +24-11-19 20:46:48 | D | + error = [149.2457] +24-11-19 20:46:48 | D | - Calibrating model.layers.29.self_attn.o_proj.input +24-11-19 20:46:48 | D | - Calibrating model.layers.29.mlp.up_proj.input +24-11-19 20:46:48 | D | - Calibrating model.layers.29.mlp.down_proj.input +24-11-19 20:46:48 | D | - Quantizing model.layers.29.self_attn.q_proj (inputs) +24-11-19 20:46:48 | D | - Quantizing model.layers.29.self_attn.k_proj (inputs) +24-11-19 20:46:48 | D | - Quantizing model.layers.29.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:48 | D | - Quantizing model.layers.29.self_attn.o_proj (inputs) +24-11-19 20:46:48 | D | - Quantizing model.layers.29.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:48 | D | - Quantizing model.layers.29.mlp.gate_proj (inputs) +24-11-19 20:46:48 | D | - Quantizing model.layers.29.mlp.up_proj (inputs) +24-11-19 20:46:48 | D | - Quantizing model.layers.29.mlp.down_proj (inputs) +24-11-19 20:46:55 | D | - Quantizing layer model.layers.30 +24-11-19 20:46:55 | D | - Calibrating model.layers.30.self_attn.v_proj.input +24-11-19 20:46:55 | D | - Calibrating model.layers.30.self_attn.k_rotary_emb.output +24-11-19 20:46:55 | D | + w: None +24-11-19 20:46:55 | D | + x: None +24-11-19 20:46:55 | D | + y: sint8 +24-11-19 20:46:55 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:55 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:46:55 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:46:56 | D | - range ratio = [ 1.0000] +24-11-19 20:46:56 | D | sum error = [ 76.2819] +24-11-19 20:46:56 | D | best error = [ 76.2819] +24-11-19 20:46:56 | D | + error = [76.2819] +24-11-19 20:46:56 | D | - Calibrating model.layers.30.self_attn.v_proj.output +24-11-19 20:46:56 | D | + w: None +24-11-19 20:46:56 | D | + x: None +24-11-19 20:46:56 | D | + y: sint8 +24-11-19 20:46:56 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:56 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:46:56 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:46:57 | D | - range ratio = [ 1.0000] +24-11-19 20:46:57 | D | sum error = [ 181.8451] +24-11-19 20:46:57 | D | best error = [ 181.8451] +24-11-19 20:46:57 | D | + error = [181.8451] +24-11-19 20:46:57 | D | - Calibrating model.layers.30.self_attn.o_proj.input +24-11-19 20:46:57 | D | - Calibrating model.layers.30.mlp.up_proj.input +24-11-19 20:46:57 | D | - Calibrating model.layers.30.mlp.down_proj.input +24-11-19 20:46:57 | D | - Quantizing model.layers.30.self_attn.q_proj (inputs) +24-11-19 20:46:57 | D | - Quantizing model.layers.30.self_attn.k_proj (inputs) +24-11-19 20:46:57 | D | - Quantizing model.layers.30.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:57 | D | - Quantizing model.layers.30.self_attn.o_proj (inputs) +24-11-19 20:46:57 | D | - Quantizing model.layers.30.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:57 | D | - Quantizing model.layers.30.mlp.gate_proj (inputs) +24-11-19 20:46:57 | D | - Quantizing model.layers.30.mlp.up_proj (inputs) +24-11-19 20:46:57 | D | - Quantizing model.layers.30.mlp.down_proj (inputs) +24-11-19 20:47:03 | D | - Quantizing layer model.layers.31 +24-11-19 20:47:03 | D | - Calibrating model.layers.31.self_attn.v_proj.input +24-11-19 20:47:04 | D | - Calibrating model.layers.31.self_attn.k_rotary_emb.output +24-11-19 20:47:04 | D | + w: None +24-11-19 20:47:04 | D | + x: None +24-11-19 20:47:04 | D | + y: sint8 +24-11-19 20:47:04 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:04 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:47:04 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:47:04 | D | - range ratio = [ 1.0000] +24-11-19 20:47:04 | D | sum error = [ 95.7450] +24-11-19 20:47:04 | D | best error = [ 95.7450] +24-11-19 20:47:04 | D | + error = [95.7450] +24-11-19 20:47:04 | D | - Calibrating model.layers.31.self_attn.v_proj.output +24-11-19 20:47:04 | D | + w: None +24-11-19 20:47:04 | D | + x: None +24-11-19 20:47:04 | D | + y: sint8 +24-11-19 20:47:04 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:04 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:47:04 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:47:05 | D | - range ratio = [ 1.0000] +24-11-19 20:47:05 | D | sum error = [ 147.7647] +24-11-19 20:47:05 | D | best error = [ 147.7647] +24-11-19 20:47:05 | D | + error = [147.7647] +24-11-19 20:47:05 | D | - Calibrating model.layers.31.self_attn.o_proj.input +24-11-19 20:47:05 | D | - Calibrating model.layers.31.mlp.up_proj.input +24-11-19 20:47:05 | D | - Calibrating model.layers.31.mlp.down_proj.input +24-11-19 20:47:05 | D | - Quantizing model.layers.31.self_attn.q_proj (inputs) +24-11-19 20:47:05 | D | - Quantizing model.layers.31.self_attn.k_proj (inputs) +24-11-19 20:47:05 | D | - Quantizing model.layers.31.self_attn.v_proj (inputs and outputs) +24-11-19 20:47:05 | D | - Quantizing model.layers.31.self_attn.o_proj (inputs) +24-11-19 20:47:05 | D | - Quantizing model.layers.31.self_attn.k_rotary_emb (outputs) +24-11-19 20:47:05 | D | - Quantizing model.layers.31.mlp.gate_proj (inputs) +24-11-19 20:47:05 | D | - Quantizing model.layers.31.mlp.up_proj (inputs) +24-11-19 20:47:05 | D | - Quantizing model.layers.31.mlp.down_proj (inputs) +24-11-19 20:47:06 | I | - Saving activation quantizer settings to runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.attn.[a.AbsMax.b.AbsMax]/smooth.attn.a0p5.b0/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt +24-11-19 20:47:06 | I | - Linking activation quantizer settings to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200729.RUNNING/model/acts.pt +24-11-19 20:47:06 | I | * Evaluating model +24-11-19 20:47:06 | W | `pretrained` model kwarg is not of type `str`. Many other model arguments may be ignored. Please do not launch via accelerate or use `parallelize=True` if passing an existing model this way. +24-11-19 20:47:06 | I | Using model type 'default' +24-11-19 20:47:06 | W | Passed an already-initialized model through `pretrained`, assuming single-process call to evaluate() or custom distributed integration +24-11-19 20:47:06 | I | - Evaluator: gptq +24-11-19 20:47:06 | I | - Tasks: ['wikitext'] +24-11-19 20:47:06 | I | - Batch_size: 8 +24-11-19 20:47:06 | I | + Max_seq_length: 2048 +24-11-19 20:47:06 | D | Starting new HTTPS connection (10): huggingface.co:443 +24-11-19 20:47:12 | W | Using the latest cached version of the dataset since wikitext couldn't be found on the Hugging Face Hub +24-11-19 20:47:12 | W | Found the latest cached dataset configuration 'wikitext-2-raw-v1' at /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3 (last modified on Tue Oct 8 19:51:38 2024). +24-11-19 20:47:12 | D | Attempting to acquire lock 23438275619120 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:47:12 | D | Lock 23438275619120 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:47:12 | D | open file: /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3/dataset_info.json +24-11-19 20:47:12 | D | Attempting to release lock 23438275619120 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:47:12 | D | Lock 23438275619120 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:47:44 | I | - Results: +24-11-19 20:47:44 | I | | Task |Version| Metric |Value | |Stderr| +24-11-19 20:47:44 | I | |--------|------:|---------------|-----:|---|-----:| +24-11-19 20:47:44 | I | |wikitext| 1|word_perplexity|7.9892|± |7.9892| +24-11-19 20:47:44 | I | +24-11-19 20:47:44 | I | + Max_seq_length: 4096 +24-11-19 20:47:44 | D | Starting new HTTPS connection (11): huggingface.co:443 +24-11-19 20:47:50 | W | Using the latest cached version of the dataset since wikitext couldn't be found on the Hugging Face Hub +24-11-19 20:47:50 | W | Found the latest cached dataset configuration 'wikitext-2-raw-v1' at /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3 (last modified on Tue Oct 8 19:51:38 2024). +24-11-19 20:47:50 | D | Attempting to acquire lock 23438409953264 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:47:50 | D | Lock 23438409953264 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:47:50 | D | open file: /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3/dataset_info.json +24-11-19 20:47:50 | D | Attempting to release lock 23438409953264 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:47:50 | D | Lock 23438409953264 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:48:18 | I | - Results: +24-11-19 20:48:18 | I | | Task |Version| Metric |Value | |Stderr| +24-11-19 20:48:18 | I | |--------|------:|---------------|-----:|---|-----:| +24-11-19 20:48:18 | I | |wikitext| 1|word_perplexity|7.3992|± |7.3992| +24-11-19 20:48:18 | I | +24-11-19 20:48:18 | I | * Saving results to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200729 diff --git a/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.proj.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.proj.a0p1.b0p9.[AbsMax].[fc2].attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200844/config-241119.200844.yaml b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.proj.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.proj.a0p1.b0p9.[AbsMax].[fc2].attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200844/config-241119.200844.yaml new file mode 100644 index 0000000000000000000000000000000000000000..cd330041b60d148f81bf597d9ace32ca568cd0ed --- /dev/null +++ b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.proj.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.proj.a0p1.b0p9.[AbsMax].[fc2].attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200844/config-241119.200844.yaml @@ -0,0 +1,170 @@ +cache: + root: runs/shang + path: + rotation: runs/shang/llm/cache/quant/rotation/hadamard/llama-3-8b-instruct-gradient-1048k.pt + reorder: '' + smooth: runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.proj.OutputsError.Manual.Layer.d2.en1.sn1-attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.proj.[a.AbsMax.b.AbsMax]-attn.[a.AbsMax.b.AbsMax]/smooth.proj.a0p1.b0p9-attn.a0p5.b0/smooth.proj.skip.[out_proj+qkv_proj+up_proj]/llama-3-8b-instruct-gradient-1048k.pt + wgts: runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.proj.OutputsError.Manual.Layer.d2.en1.sn1-attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.proj.[a.AbsMax.b.AbsMax]-attn.[a.AbsMax.b.AbsMax]/smooth.proj.a0p1.b0p9-attn.a0p5.b0/smooth.proj.skip.[out_proj+qkv_proj+up_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt + acts: 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/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k + local_root: /home/yujunlin/models + dtype: torch.float16 +eval: + num_gpus: 1 + batch_size: 8 + tasks: + - wikitext + max_seq_length: -4096 + evaluators: + - gptq +quant: + wgts: + dtype: sint8 + zero_point: null + group_shapes: + - - 1 + - -1 + - -1 + scale_dtypes: + - torch.float16 + intermediate_dtypes: [] + intermediate_levels: [] + needs_dequant_saturation: false + skips: [] + enable_kernel_gptq: true + kernel_gptq: + damp_percentage: 0.01 + block_size: 128 + num_inv_tries: 250 + hessian_block_size: 512 + enable_calib_range: true + calib_range: + degree: 2 + objective: OutputsError + strategy: GridSearch + granularity: Group + element_batch_size: 64 + sample_batch_size: -1 + element_size: 512 + sample_size: -1 + pre_reshape: true + outputs_device: cpu + ratio: 1.0 + max_shrink: 0.2 + max_expand: 1.0 + num_grids: 80 + allow_scale: false + skips: [] + ipts: + dtype: sint8 + zero_point: null + group_shapes: + - - 1 + - -1 + - -1 + scale_dtypes: + - torch.float16 + skips: [] + static: false + enable_calib_range: false + opts: + dtype: sint8 + zero_point: null + group_shapes: + - - -1 + - -1 + - -1 + scale_dtypes: + - torch.float16 + skips: + - attn_q + static: true + enable_calib_range: true + calib_range: + degree: 2 + objective: OutputsError + strategy: Manual + granularity: Layer + element_batch_size: -1 + sample_batch_size: -1 + element_size: -1 + sample_size: -1 + pre_reshape: true + outputs_device: cpu + ratio: 1.0 + max_shrink: 0.2 + max_expand: 1.0 + num_grids: 80 + allow_scale: false + skips: [] + calib: + data: pileval + num_samples: 128 + path: mit-han-lab/pile-val-backup + seq_length: 1024 + min_seq_length: 0 + max_seq_length: 0 + local_path: '' + enable_rotation: true + rotation: + random: false + transforms: + - out_proj + enable_reorder: false + enable_smooth: true + smooth: + enable_proj: true + proj: + degree: 2 + objective: OutputsError + strategy: Manual + granularity: Layer + element_batch_size: -1 + sample_batch_size: -1 + element_size: -1 + sample_size: -1 + pre_reshape: true + outputs_device: cpu + allow_a_quant: true + allow_b_quant: true + spans: + - - AbsMax + - AbsMax + alpha: 0.1 + beta: 0.9 + num_grids: 20 + allow_low_rank: false + skips: + - out_proj + - qkv_proj + - up_proj + enable_attn: true + attn: + degree: 2 + strategy: Manual + sample_batch_size: -1 + sample_size: -1 + outputs_device: cpu + allow_a_quant: true + allow_b_quant: true + spans: + - - AbsMax + - AbsMax + alpha: 0.5 + beta: 0 + num_grids: 20 + develop_dtype: torch.float32 +seed: 12345 +skip_eval: false +load_from: '' +save_model: 'true' +copy_on_save: false diff --git 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a/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.proj.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.proj.a0p1.b0p9.[AbsMax].[fc2].attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200844/run-241119.200844.log b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.proj.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.proj.a0p1.b0p9.[AbsMax].[fc2].attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200844/run-241119.200844.log new file mode 100644 index 0000000000000000000000000000000000000000..050f0b57aad567f93d564fd35fa2fd69231adfe4 --- /dev/null +++ b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.proj.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.proj.a0p1.b0p9.[AbsMax].[fc2].attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200844/run-241119.200844.log @@ -0,0 +1,16812 @@ +24-11-19 20:08:44 | I | === Configurations === +24-11-19 20:08:44 | I | LlmPtqRunConfig( +24-11-19 20:08:44 | I | cache=LlmCacheConfig( +24-11-19 20:08:44 | I | root=runs/shang, +24-11-19 20:08:44 | I | dirpath=LlmQuantCacheConfig( +24-11-19 20:08:44 | I | rotation=runs/shang/llm/cache/quant/rotation/hadamard, +24-11-19 20:08:44 | I | reorder=, +24-11-19 20:08:44 | I | smooth=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.proj.OutputsError.Manual.Layer.d2.en1.sn1-attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.proj.[a.AbsMax.b.AbsMax]-attn.[a.AbsMax.b.AbsMax]/smooth.proj.a0p1.b0p9-attn.a0p5.b0/smooth.proj.skip.[out_proj+qkv_proj+up_proj], +24-11-19 20:08:44 | I | wgts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.proj.OutputsError.Manual.Layer.d2.en1.sn1-attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.proj.[a.AbsMax.b.AbsMax]-attn.[a.AbsMax.b.AbsMax]/smooth.proj.a0p1.b0p9-attn.a0p5.b0/smooth.proj.skip.[out_proj+qkv_proj+up_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[], +24-11-19 20:08:44 | I | acts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.proj.OutputsError.Manual.Layer.d2.en1.sn1-attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.proj.[a.AbsMax.b.AbsMax]-attn.[a.AbsMax.b.AbsMax]/smooth.proj.a0p1.b0p9-attn.a0p5.b0/smooth.proj.skip.[out_proj+qkv_proj+up_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]), +24-11-19 20:08:44 | I | path=LlmQuantCacheConfig( +24-11-19 20:08:44 | I | rotation=runs/shang/llm/cache/quant/rotation/hadamard/llama-3-8b-instruct-gradient-1048k.pt, +24-11-19 20:08:44 | I | reorder=, +24-11-19 20:08:44 | I | smooth=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.proj.OutputsError.Manual.Layer.d2.en1.sn1-attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.proj.[a.AbsMax.b.AbsMax]-attn.[a.AbsMax.b.AbsMax]/smooth.proj.a0p1.b0p9-attn.a0p5.b0/smooth.proj.skip.[out_proj+qkv_proj+up_proj]/llama-3-8b-instruct-gradient-1048k.pt, +24-11-19 20:08:44 | I | wgts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.proj.OutputsError.Manual.Layer.d2.en1.sn1-attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.proj.[a.AbsMax.b.AbsMax]-attn.[a.AbsMax.b.AbsMax]/smooth.proj.a0p1.b0p9-attn.a0p5.b0/smooth.proj.skip.[out_proj+qkv_proj+up_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt, +24-11-19 20:08:44 | I | acts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.proj.OutputsError.Manual.Layer.d2.en1.sn1-attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.proj.[a.AbsMax.b.AbsMax]-attn.[a.AbsMax.b.AbsMax]/smooth.proj.a0p1.b0p9-attn.a0p5.b0/smooth.proj.skip.[out_proj+qkv_proj+up_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt)), +24-11-19 20:08:44 | I | output=OutputConfig( +24-11-19 20:08:44 | I | root=runs/shang, +24-11-19 20:08:44 | I | dirname=skip.y.[q]-gptq-rot.[+out]-smth.proj.a0p1.b0p9.[AbsMax].[fc2].attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0], +24-11-19 20:08:44 | I | job=run, +24-11-19 20:08:44 | I | dirpath=runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.proj.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.proj.a0p1.b0p9.[AbsMax].[fc2].attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0], +24-11-19 20:08:44 | I | timestamp=241119.200844), +24-11-19 20:08:44 | I | model=LlmModelConfig( +24-11-19 20:08:44 | I | name=llama-3-8b-instruct-gradient-1048k, +24-11-19 20:08:44 | I | family=llama-3, +24-11-19 20:08:44 | I | path=/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k, +24-11-19 20:08:44 | I | root=, +24-11-19 20:08:44 | I | local_path=/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k, +24-11-19 20:08:44 | I | local_root=/home/yujunlin/models, +24-11-19 20:08:44 | I | size=8.0, +24-11-19 20:08:44 | I | variant=instruct-gradient-1048k, +24-11-19 20:08:44 | I | dtype=torch.float16, +24-11-19 20:08:44 | I | orig_dtype=torch.bfloat16), +24-11-19 20:08:44 | I | eval=LlmEvalConfig( +24-11-19 20:08:44 | I | num_gpus=1, +24-11-19 20:08:44 | I | batch_size=8, +24-11-19 20:08:44 | I | tasks=['wikitext'], +24-11-19 20:08:44 | I | max_seq_length=-4096, +24-11-19 20:08:44 | I | evaluators=['gptq']), +24-11-19 20:08:44 | I | quant=LlmQuantConfig( +24-11-19 20:08:44 | I | wgts=LlmWeightQuantizerConfig( +24-11-19 20:08:44 | I | dtype=sint8, +24-11-19 20:08:44 | I | zero_point=None, +24-11-19 20:08:44 | I | group_shapes=((1, -1, -1),), +24-11-19 20:08:44 | I | scale_dtypes=(torch.float16,), +24-11-19 20:08:44 | I | intermediate_dtypes=(), +24-11-19 20:08:44 | I | intermediate_levels=(), +24-11-19 20:08:44 | I | needs_dequant_saturation=False, +24-11-19 20:08:44 | I | skips=[], +24-11-19 20:08:44 | I | static=True, +24-11-19 20:08:44 | I | kernel_gptq=QuantGptqConfig( +24-11-19 20:08:44 | I | damp_percentage=0.01, +24-11-19 20:08:44 | I | block_size=128, +24-11-19 20:08:44 | I | num_inv_tries=250, +24-11-19 20:08:44 | I | hessian_block_size=512), +24-11-19 20:08:44 | I | calib_range=SkipBasedDynamicRangeCalibConfig( +24-11-19 20:08:44 | I | degree=2, +24-11-19 20:08:44 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 20:08:44 | I | strategy=SearchBasedCalibStrategy.GridSearch, +24-11-19 20:08:44 | I | granularity=SearchBasedCalibGranularity.Group, +24-11-19 20:08:44 | I | element_batch_size=64, +24-11-19 20:08:44 | I | sample_batch_size=-1, +24-11-19 20:08:44 | I | element_size=512, +24-11-19 20:08:44 | I | sample_size=-1, +24-11-19 20:08:44 | I | pre_reshape=True, +24-11-19 20:08:44 | I | outputs_device=cpu, +24-11-19 20:08:44 | I | ratio=1.0, +24-11-19 20:08:44 | I | max_shrink=0.2, +24-11-19 20:08:44 | I | max_expand=1.0, +24-11-19 20:08:44 | I | num_grids=80, +24-11-19 20:08:44 | I | allow_scale=False, +24-11-19 20:08:44 | I | skips=[])), +24-11-19 20:08:44 | I | ipts=LlmActivationQuantizerConfig( +24-11-19 20:08:44 | I | dtype=sint8, +24-11-19 20:08:44 | I | zero_point=None, +24-11-19 20:08:44 | I | group_shapes=((1, -1, -1),), +24-11-19 20:08:44 | I | scale_dtypes=(torch.float16,), +24-11-19 20:08:44 | I | intermediate_dtypes=(), +24-11-19 20:08:44 | I | intermediate_levels=(), +24-11-19 20:08:44 | I | needs_dequant_saturation=False, +24-11-19 20:08:44 | I | skips=[], +24-11-19 20:08:44 | I | static=False, +24-11-19 20:08:44 | I | kernel_gptq=None, +24-11-19 20:08:44 | I | calib_range=None), +24-11-19 20:08:44 | I | opts=LlmActivationQuantizerConfig( +24-11-19 20:08:44 | I | dtype=sint8, +24-11-19 20:08:44 | I | zero_point=None, +24-11-19 20:08:44 | I | group_shapes=((-1, -1, -1),), +24-11-19 20:08:44 | I | scale_dtypes=(torch.float16,), +24-11-19 20:08:44 | I | intermediate_dtypes=(), +24-11-19 20:08:44 | I | intermediate_levels=(), +24-11-19 20:08:44 | I | needs_dequant_saturation=False, +24-11-19 20:08:44 | I | skips=['attn_q'], +24-11-19 20:08:44 | I | static=True, +24-11-19 20:08:44 | I | kernel_gptq=None, +24-11-19 20:08:44 | I | calib_range=SkipBasedDynamicRangeCalibConfig( +24-11-19 20:08:44 | I | degree=2, +24-11-19 20:08:44 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 20:08:44 | I | strategy=SearchBasedCalibStrategy.Manual, +24-11-19 20:08:44 | I | granularity=SearchBasedCalibGranularity.Layer, +24-11-19 20:08:44 | I | element_batch_size=-1, +24-11-19 20:08:44 | I | sample_batch_size=-1, +24-11-19 20:08:44 | I | element_size=-1, +24-11-19 20:08:44 | I | sample_size=-1, +24-11-19 20:08:44 | I | pre_reshape=True, +24-11-19 20:08:44 | I | outputs_device=cpu, +24-11-19 20:08:44 | I | ratio=1.0, +24-11-19 20:08:44 | I | max_shrink=0.2, +24-11-19 20:08:44 | I | max_expand=1.0, +24-11-19 20:08:44 | I | num_grids=80, +24-11-19 20:08:44 | I | allow_scale=False, +24-11-19 20:08:44 | I | skips=[])), +24-11-19 20:08:44 | I | calib=LlmCalibDataLoaderConfig( +24-11-19 20:08:44 | I | data=pileval, +24-11-19 20:08:44 | I | num_samples=128, +24-11-19 20:08:44 | I | batch_size=1, +24-11-19 20:08:44 | I | path=mit-han-lab/pile-val-backup, +24-11-19 20:08:44 | I | seq_length=1024, +24-11-19 20:08:44 | I | min_seq_length=0, +24-11-19 20:08:44 | I | max_seq_length=0, +24-11-19 20:08:44 | I | local_path=), +24-11-19 20:08:44 | I | rotation=QuantRotationConfig( +24-11-19 20:08:44 | I | random=False, +24-11-19 20:08:44 | I | transforms=['out_proj']), +24-11-19 20:08:44 | I | reorder=None, +24-11-19 20:08:44 | I | smooth=SmoothTransfomerConfig( +24-11-19 20:08:44 | I | proj=SkipBasedSmoothCalibConfig( +24-11-19 20:08:44 | I | degree=2, +24-11-19 20:08:44 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 20:08:44 | I | strategy=SearchBasedCalibStrategy.Manual, +24-11-19 20:08:44 | I | granularity=SearchBasedCalibGranularity.Layer, +24-11-19 20:08:44 | I | element_batch_size=-1, +24-11-19 20:08:44 | I | sample_batch_size=-1, +24-11-19 20:08:44 | I | element_size=-1, +24-11-19 20:08:44 | I | sample_size=-1, +24-11-19 20:08:44 | I | pre_reshape=True, +24-11-19 20:08:44 | I | outputs_device=cpu, +24-11-19 20:08:44 | I | allow_a_quant=True, +24-11-19 20:08:44 | I | allow_b_quant=True, +24-11-19 20:08:44 | I | spans=[(, )], +24-11-19 20:08:44 | I | a_spans=[], +24-11-19 20:08:44 | I | b_spans=[], +24-11-19 20:08:44 | I | alpha=0.1, +24-11-19 20:08:44 | I | beta=0.9, +24-11-19 20:08:44 | I | num_grids=20, +24-11-19 20:08:44 | I | allow_low_rank=False, +24-11-19 20:08:44 | I | skips=['out_proj', 'qkv_proj', 'up_proj']), +24-11-19 20:08:44 | I | attn=SmoothAttentionCalibConfig( +24-11-19 20:08:44 | I | degree=2, +24-11-19 20:08:44 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 20:08:44 | I | strategy=SearchBasedCalibStrategy.Manual, +24-11-19 20:08:44 | I | granularity=SearchBasedCalibGranularity.Layer, +24-11-19 20:08:44 | I | element_batch_size=-1, +24-11-19 20:08:44 | I | sample_batch_size=-1, +24-11-19 20:08:44 | I | element_size=-1, +24-11-19 20:08:44 | I | sample_size=-1, +24-11-19 20:08:44 | I | pre_reshape=True, +24-11-19 20:08:44 | I | outputs_device=cpu, +24-11-19 20:08:44 | I | allow_a_quant=True, +24-11-19 20:08:44 | I | allow_b_quant=True, +24-11-19 20:08:44 | I | spans=[(, )], +24-11-19 20:08:44 | I | a_spans=[], +24-11-19 20:08:44 | I | b_spans=[], +24-11-19 20:08:44 | I | alpha=0.5, +24-11-19 20:08:44 | I | beta=0, +24-11-19 20:08:44 | I | num_grids=20, +24-11-19 20:08:44 | I | allow_low_rank=False)), +24-11-19 20:08:44 | I | develop_dtype=torch.float32), +24-11-19 20:08:44 | I | seed=12345, +24-11-19 20:08:44 | I | skip_eval=False, +24-11-19 20:08:44 | I | load_from=, +24-11-19 20:08:44 | I | save_model=true, +24-11-19 20:08:44 | I | copy_on_save=False) +24-11-19 20:08:44 | I | === Dumped Configurations === +24-11-19 20:08:44 | I | { 'cache': { 'path': { 'acts': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.proj.OutputsError.Manual.Layer.d2.en1.sn1-attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.proj.[a.AbsMax.b.AbsMax]-attn.[a.AbsMax.b.AbsMax]/smooth.proj.a0p1.b0p9-attn.a0p5.b0/smooth.proj.skip.[out_proj+qkv_proj+up_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt', +24-11-19 20:08:44 | I | 'reorder': '', +24-11-19 20:08:44 | I | 'rotation': 'runs/shang/llm/cache/quant/rotation/hadamard/llama-3-8b-instruct-gradient-1048k.pt', +24-11-19 20:08:44 | I | 'smooth': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.proj.OutputsError.Manual.Layer.d2.en1.sn1-attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.proj.[a.AbsMax.b.AbsMax]-attn.[a.AbsMax.b.AbsMax]/smooth.proj.a0p1.b0p9-attn.a0p5.b0/smooth.proj.skip.[out_proj+qkv_proj+up_proj]/llama-3-8b-instruct-gradient-1048k.pt', +24-11-19 20:08:44 | I | 'wgts': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.proj.OutputsError.Manual.Layer.d2.en1.sn1-attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.proj.[a.AbsMax.b.AbsMax]-attn.[a.AbsMax.b.AbsMax]/smooth.proj.a0p1.b0p9-attn.a0p5.b0/smooth.proj.skip.[out_proj+qkv_proj+up_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt'}, +24-11-19 20:08:44 | I | 'root': 'runs/shang'}, +24-11-19 20:08:44 | I | 'copy_on_save': False, +24-11-19 20:08:44 | I | 'eval': {'batch_size': 8, 'evaluators': ['gptq'], 'max_seq_length': -4096, 'num_gpus': 1, 'tasks': ['wikitext']}, +24-11-19 20:08:44 | I | 'load_from': '', +24-11-19 20:08:44 | I | 'model': { 'dtype': 'torch.float16', +24-11-19 20:08:44 | I | 'family': 'llama-3', +24-11-19 20:08:44 | I | 'local_path': '/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k', +24-11-19 20:08:44 | I | 'local_root': '/home/yujunlin/models', +24-11-19 20:08:44 | I | 'name': 'llama-3-8b-instruct-gradient-1048k', +24-11-19 20:08:44 | I | 'path': '/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k', +24-11-19 20:08:44 | I | 'root': ''}, +24-11-19 20:08:44 | I | 'output': { 'dirname': 'skip.y.[q]-gptq-rot.[+out]-smth.proj.a0p1.b0p9.[AbsMax].[fc2].attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]', +24-11-19 20:08:44 | I | 'job': 'run', +24-11-19 20:08:44 | I | 'root': 'runs/shang'}, +24-11-19 20:08:44 | I | 'quant': { 'calib': { 'data': 'pileval', +24-11-19 20:08:44 | I | 'local_path': '', +24-11-19 20:08:44 | I | 'max_seq_length': 0, +24-11-19 20:08:44 | I | 'min_seq_length': 0, +24-11-19 20:08:44 | I | 'num_samples': 128, +24-11-19 20:08:44 | I | 'path': 'mit-han-lab/pile-val-backup', +24-11-19 20:08:44 | I | 'seq_length': 1024}, +24-11-19 20:08:44 | I | 'develop_dtype': 'torch.float32', +24-11-19 20:08:44 | I | 'enable_reorder': False, +24-11-19 20:08:44 | I | 'enable_rotation': True, +24-11-19 20:08:44 | I | 'enable_smooth': True, +24-11-19 20:08:44 | I | 'ipts': { 'dtype': 'sint8', +24-11-19 20:08:44 | I | 'enable_calib_range': False, +24-11-19 20:08:44 | I | 'group_shapes': [[1, -1, -1]], +24-11-19 20:08:44 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 20:08:44 | I | 'skips': [], +24-11-19 20:08:44 | I | 'static': False, +24-11-19 20:08:44 | I | 'zero_point': None}, +24-11-19 20:08:44 | I | 'opts': { 'calib_range': { 'allow_scale': False, +24-11-19 20:08:44 | I | 'degree': 2, +24-11-19 20:08:44 | I | 'element_batch_size': -1, +24-11-19 20:08:44 | I | 'element_size': -1, +24-11-19 20:08:44 | I | 'granularity': 'Layer', +24-11-19 20:08:44 | I | 'max_expand': 1.0, +24-11-19 20:08:44 | I | 'max_shrink': 0.2, +24-11-19 20:08:44 | I | 'num_grids': 80, +24-11-19 20:08:44 | I | 'objective': 'OutputsError', +24-11-19 20:08:44 | I | 'outputs_device': 'cpu', +24-11-19 20:08:44 | I | 'pre_reshape': True, +24-11-19 20:08:44 | I | 'ratio': 1.0, +24-11-19 20:08:44 | I | 'sample_batch_size': -1, +24-11-19 20:08:44 | I | 'sample_size': -1, +24-11-19 20:08:44 | I | 'skips': [], +24-11-19 20:08:44 | I | 'strategy': 'Manual'}, +24-11-19 20:08:44 | I | 'dtype': 'sint8', +24-11-19 20:08:44 | I | 'enable_calib_range': True, +24-11-19 20:08:44 | I | 'group_shapes': [[-1, -1, -1]], +24-11-19 20:08:44 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 20:08:44 | I | 'skips': ['attn_q'], +24-11-19 20:08:44 | I | 'static': True, +24-11-19 20:08:44 | I | 'zero_point': None}, +24-11-19 20:08:44 | I | 'rotation': {'random': False, 'transforms': ['out_proj']}, +24-11-19 20:08:44 | I | 'smooth': { 'attn': { 'allow_a_quant': True, +24-11-19 20:08:44 | I | 'allow_b_quant': True, +24-11-19 20:08:44 | I | 'alpha': 0.5, +24-11-19 20:08:44 | I | 'beta': 0, +24-11-19 20:08:44 | I | 'degree': 2, +24-11-19 20:08:44 | I | 'num_grids': 20, +24-11-19 20:08:44 | I | 'outputs_device': 'cpu', +24-11-19 20:08:44 | I | 'sample_batch_size': -1, +24-11-19 20:08:44 | I | 'sample_size': -1, +24-11-19 20:08:44 | I | 'spans': [['AbsMax', 'AbsMax']], +24-11-19 20:08:44 | I | 'strategy': 'Manual'}, +24-11-19 20:08:44 | I | 'enable_attn': True, +24-11-19 20:08:44 | I | 'enable_proj': True, +24-11-19 20:08:44 | I | 'proj': { 'allow_a_quant': True, +24-11-19 20:08:44 | I | 'allow_b_quant': True, +24-11-19 20:08:44 | I | 'allow_low_rank': False, +24-11-19 20:08:44 | I | 'alpha': 0.1, +24-11-19 20:08:44 | I | 'beta': 0.9, +24-11-19 20:08:44 | I | 'degree': 2, +24-11-19 20:08:44 | I | 'element_batch_size': -1, +24-11-19 20:08:44 | I | 'element_size': -1, +24-11-19 20:08:44 | I | 'granularity': 'Layer', +24-11-19 20:08:44 | I | 'num_grids': 20, +24-11-19 20:08:44 | I | 'objective': 'OutputsError', +24-11-19 20:08:44 | I | 'outputs_device': 'cpu', +24-11-19 20:08:44 | I | 'pre_reshape': True, +24-11-19 20:08:44 | I | 'sample_batch_size': -1, +24-11-19 20:08:44 | I | 'sample_size': -1, +24-11-19 20:08:44 | I | 'skips': ['out_proj', 'qkv_proj', 'up_proj'], +24-11-19 20:08:44 | I | 'spans': [['AbsMax', 'AbsMax']], +24-11-19 20:08:44 | I | 'strategy': 'Manual'}}, +24-11-19 20:08:44 | I | 'wgts': { 'calib_range': { 'allow_scale': False, +24-11-19 20:08:44 | I | 'degree': 2, +24-11-19 20:08:44 | I | 'element_batch_size': 64, +24-11-19 20:08:44 | I | 'element_size': 512, +24-11-19 20:08:44 | I | 'granularity': 'Group', +24-11-19 20:08:44 | I | 'max_expand': 1.0, +24-11-19 20:08:44 | I | 'max_shrink': 0.2, +24-11-19 20:08:44 | I | 'num_grids': 80, +24-11-19 20:08:44 | I | 'objective': 'OutputsError', +24-11-19 20:08:44 | I | 'outputs_device': 'cpu', +24-11-19 20:08:44 | I | 'pre_reshape': True, +24-11-19 20:08:44 | I | 'ratio': 1.0, +24-11-19 20:08:44 | I | 'sample_batch_size': -1, +24-11-19 20:08:44 | I | 'sample_size': -1, +24-11-19 20:08:44 | I | 'skips': [], +24-11-19 20:08:44 | I | 'strategy': 'GridSearch'}, +24-11-19 20:08:44 | I | 'dtype': 'sint8', +24-11-19 20:08:44 | I | 'enable_calib_range': True, +24-11-19 20:08:44 | I | 'enable_kernel_gptq': True, +24-11-19 20:08:44 | I | 'group_shapes': [[1, -1, -1]], +24-11-19 20:08:44 | I | 'intermediate_dtypes': [], +24-11-19 20:08:44 | I | 'intermediate_levels': [], +24-11-19 20:08:44 | I | 'kernel_gptq': { 'block_size': 128, +24-11-19 20:08:44 | I | 'damp_percentage': 0.01, +24-11-19 20:08:44 | I | 'hessian_block_size': 512, +24-11-19 20:08:44 | I | 'num_inv_tries': 250}, +24-11-19 20:08:44 | I | 'needs_dequant_saturation': False, +24-11-19 20:08:44 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 20:08:44 | I | 'skips': [], +24-11-19 20:08:44 | I | 'zero_point': None}}, +24-11-19 20:08:44 | I | 'save_model': 'true', +24-11-19 20:08:44 | I | 'seed': 12345, +24-11-19 20:08:44 | I | 'skip_eval': False} +24-11-19 20:08:44 | I | === Output Directory === +24-11-19 20:08:44 | I | runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.proj.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.proj.a0p1.b0p9.[AbsMax].[fc2].attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200844 +24-11-19 20:08:44 | I | === Start Evaluating === +24-11-19 20:08:44 | I | * Building model llama-3-8b-instruct-gradient-1048k from /home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k +24-11-19 20:08:44 | I | We will use 90% of the memory on device 0 for storing the model, and 10% for the buffer to avoid OOM. You can set `max_memory` in to a higher value to use more memory (at your own risk). +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.0.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.1.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.2.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.3.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.4.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.5.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.6.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.7.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.8.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.9.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.10.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.11.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.12.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.13.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.14.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.15.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.16.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.17.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.18.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.19.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.20.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.21.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.22.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.23.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.24.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.25.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.26.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.27.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.28.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.29.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.30.self_attn +24-11-19 20:08:51 | I | - Patching LlamaSdpaAttention.forward in model.layers.31.self_attn +24-11-19 20:08:51 | I | * Rotating model +24-11-19 20:08:51 | I | - Loading rotation from runs/shang/llm/cache/quant/rotation/hadamard/llama-3-8b-instruct-gradient-1048k.pt +24-11-19 20:08:51 | D | - Transforming norm and linear in model.layers.0 +24-11-19 20:08:52 | D | - Transforming norm and linear in model.layers.1 +24-11-19 20:08:52 | D | - Transforming norm and linear in model.layers.2 +24-11-19 20:08:52 | D | - Transforming norm and linear in model.layers.3 +24-11-19 20:08:52 | D | - Transforming norm and linear in model.layers.4 +24-11-19 20:08:52 | D | - Transforming norm and linear in model.layers.5 +24-11-19 20:08:52 | D | - Transforming norm and linear in model.layers.6 +24-11-19 20:08:52 | D | - Transforming norm and linear in model.layers.7 +24-11-19 20:08:52 | D | - Transforming norm and linear in model.layers.8 +24-11-19 20:08:52 | D | - Transforming norm and linear in model.layers.9 +24-11-19 20:08:52 | D | - Transforming norm and linear in model.layers.10 +24-11-19 20:08:52 | D | - Transforming norm and linear in model.layers.11 +24-11-19 20:08:53 | D | - Transforming norm and linear in model.layers.12 +24-11-19 20:08:53 | D | - Transforming norm and linear in model.layers.13 +24-11-19 20:08:53 | D | - Transforming norm and linear in model.layers.14 +24-11-19 20:08:53 | D | - Transforming norm and linear in model.layers.15 +24-11-19 20:08:53 | D | - Transforming norm and linear in model.layers.16 +24-11-19 20:08:53 | D | - Transforming norm and linear in model.layers.17 +24-11-19 20:08:53 | D | - Transforming norm and linear in model.layers.18 +24-11-19 20:08:53 | D | - Transforming norm and linear in model.layers.19 +24-11-19 20:08:53 | D | - Transforming norm and linear in model.layers.20 +24-11-19 20:08:54 | D | - Transforming norm and linear in model.layers.21 +24-11-19 20:08:54 | D | - Transforming norm and linear in model.layers.22 +24-11-19 20:08:54 | D | - Transforming norm and linear in model.layers.23 +24-11-19 20:08:54 | D | - Transforming norm and linear in model.layers.24 +24-11-19 20:08:54 | D | - Transforming norm and linear in model.layers.25 +24-11-19 20:08:54 | D | - Transforming norm and linear in model.layers.26 +24-11-19 20:08:54 | D | - Transforming norm and linear in model.layers.27 +24-11-19 20:08:54 | D | - Transforming norm and linear in model.layers.28 +24-11-19 20:08:54 | D | - Transforming norm and linear in model.layers.29 +24-11-19 20:08:55 | D | - Transforming norm and linear in model.layers.30 +24-11-19 20:08:55 | D | - Transforming norm and linear in model.layers.31 +24-11-19 20:08:55 | D | - Transforming model.norm +24-11-19 20:08:55 | D | - Rotating model.embed_tokens +24-11-19 20:08:55 | D | - Rotating model.layers.0 +24-11-19 20:08:55 | D | - Rotating model.layers.0.self_attn.q_proj (in) +24-11-19 20:08:55 | D | - Rotating model.layers.0.self_attn.k_proj (in) +24-11-19 20:08:55 | D | - Rotating model.layers.0.self_attn.v_proj (in) +24-11-19 20:08:55 | D | - Rotating model.layers.0.self_attn.o_proj (out) +24-11-19 20:08:55 | D | - Rotating model.layers.0.self_attn.v_proj (out) +24-11-19 20:08:55 | D | - Rotating model.layers.0.self_attn.o_proj (in) +24-11-19 20:08:55 | D | - Rotating model.layers.0.mlp.up_proj (in) +24-11-19 20:08:55 | D | - Rotating model.layers.0.mlp.gate_proj (in) +24-11-19 20:08:55 | D | - Rotating model.layers.0.mlp.down_proj (out) +24-11-19 20:08:55 | D | - Rotating model.layers.1 +24-11-19 20:08:55 | D | - Rotating model.layers.1.self_attn.q_proj (in) +24-11-19 20:08:55 | D | - Rotating model.layers.1.self_attn.k_proj (in) +24-11-19 20:08:55 | D | - Rotating model.layers.1.self_attn.v_proj (in) +24-11-19 20:08:55 | D | - Rotating model.layers.1.self_attn.o_proj (out) +24-11-19 20:08:55 | D | - Rotating model.layers.1.self_attn.v_proj (out) +24-11-19 20:08:55 | D | - Rotating model.layers.1.self_attn.o_proj (in) +24-11-19 20:08:55 | D | - Rotating model.layers.1.mlp.up_proj (in) +24-11-19 20:08:55 | D | - Rotating model.layers.1.mlp.gate_proj (in) +24-11-19 20:08:55 | D | - Rotating model.layers.1.mlp.down_proj (out) +24-11-19 20:08:55 | D | - Rotating model.layers.2 +24-11-19 20:08:55 | D | - Rotating model.layers.2.self_attn.q_proj (in) +24-11-19 20:08:55 | D | - Rotating model.layers.2.self_attn.k_proj (in) +24-11-19 20:08:55 | D | - Rotating model.layers.2.self_attn.v_proj (in) +24-11-19 20:08:55 | D | - Rotating model.layers.2.self_attn.o_proj (out) +24-11-19 20:08:55 | D | - Rotating model.layers.2.self_attn.v_proj (out) +24-11-19 20:08:55 | D | - Rotating model.layers.2.self_attn.o_proj (in) +24-11-19 20:08:55 | D | - Rotating model.layers.2.mlp.up_proj (in) +24-11-19 20:08:55 | D | - Rotating model.layers.2.mlp.gate_proj (in) +24-11-19 20:08:55 | D | - Rotating model.layers.2.mlp.down_proj (out) +24-11-19 20:08:55 | D | - Rotating model.layers.3 +24-11-19 20:08:55 | D | - Rotating model.layers.3.self_attn.q_proj (in) +24-11-19 20:08:55 | D | - Rotating model.layers.3.self_attn.k_proj (in) +24-11-19 20:08:55 | D | - Rotating model.layers.3.self_attn.v_proj (in) +24-11-19 20:08:55 | D | - Rotating model.layers.3.self_attn.o_proj (out) +24-11-19 20:08:55 | D | - Rotating model.layers.3.self_attn.v_proj (out) +24-11-19 20:08:55 | D | - Rotating model.layers.3.self_attn.o_proj (in) +24-11-19 20:08:55 | D | - 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Rotating model.layers.24.self_attn.v_proj (out) +24-11-19 20:08:57 | D | - Rotating model.layers.24.self_attn.o_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.24.mlp.up_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.24.mlp.gate_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.24.mlp.down_proj (out) +24-11-19 20:08:57 | D | - Rotating model.layers.25 +24-11-19 20:08:57 | D | - Rotating model.layers.25.self_attn.q_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.25.self_attn.k_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.25.self_attn.v_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.25.self_attn.o_proj (out) +24-11-19 20:08:57 | D | - Rotating model.layers.25.self_attn.v_proj (out) +24-11-19 20:08:57 | D | - Rotating model.layers.25.self_attn.o_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.25.mlp.up_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.25.mlp.gate_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.25.mlp.down_proj (out) +24-11-19 20:08:57 | D | - Rotating model.layers.26 +24-11-19 20:08:57 | D | - Rotating model.layers.26.self_attn.q_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.26.self_attn.k_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.26.self_attn.v_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.26.self_attn.o_proj (out) +24-11-19 20:08:57 | D | - Rotating model.layers.26.self_attn.v_proj (out) +24-11-19 20:08:57 | D | - Rotating model.layers.26.self_attn.o_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.26.mlp.up_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.26.mlp.gate_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.26.mlp.down_proj (out) +24-11-19 20:08:57 | D | - Rotating model.layers.27 +24-11-19 20:08:57 | D | - Rotating model.layers.27.self_attn.q_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.27.self_attn.k_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.27.self_attn.v_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.27.self_attn.o_proj (out) +24-11-19 20:08:57 | D | - Rotating model.layers.27.self_attn.v_proj (out) +24-11-19 20:08:57 | D | - Rotating model.layers.27.self_attn.o_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.27.mlp.up_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.27.mlp.gate_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.27.mlp.down_proj (out) +24-11-19 20:08:57 | D | - Rotating model.layers.28 +24-11-19 20:08:57 | D | - Rotating model.layers.28.self_attn.q_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.28.self_attn.k_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.28.self_attn.v_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.28.self_attn.o_proj (out) +24-11-19 20:08:57 | D | - Rotating model.layers.28.self_attn.v_proj (out) +24-11-19 20:08:57 | D | - Rotating model.layers.28.self_attn.o_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.28.mlp.up_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.28.mlp.gate_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.28.mlp.down_proj (out) +24-11-19 20:08:57 | D | - Rotating model.layers.29 +24-11-19 20:08:57 | D | - Rotating model.layers.29.self_attn.q_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.29.self_attn.k_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.29.self_attn.v_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.29.self_attn.o_proj (out) +24-11-19 20:08:57 | D | - Rotating model.layers.29.self_attn.v_proj (out) +24-11-19 20:08:57 | D | - Rotating model.layers.29.self_attn.o_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.29.mlp.up_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.29.mlp.gate_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.29.mlp.down_proj (out) +24-11-19 20:08:57 | D | - Rotating model.layers.30 +24-11-19 20:08:57 | D | - Rotating model.layers.30.self_attn.q_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.30.self_attn.k_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.30.self_attn.v_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.30.self_attn.o_proj (out) +24-11-19 20:08:57 | D | - Rotating model.layers.30.self_attn.v_proj (out) +24-11-19 20:08:57 | D | - Rotating model.layers.30.self_attn.o_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.30.mlp.up_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.30.mlp.gate_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.30.mlp.down_proj (out) +24-11-19 20:08:57 | D | - Rotating model.layers.31 +24-11-19 20:08:57 | D | - Rotating model.layers.31.self_attn.q_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.31.self_attn.k_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.31.self_attn.v_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.31.self_attn.o_proj (out) +24-11-19 20:08:57 | D | - Rotating model.layers.31.self_attn.v_proj (out) +24-11-19 20:08:57 | D | - Rotating model.layers.31.self_attn.o_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.31.mlp.up_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.31.mlp.gate_proj (in) +24-11-19 20:08:57 | D | - Rotating model.layers.31.mlp.down_proj (out) +24-11-19 20:08:57 | D | - Rotating lm_head (in) +24-11-19 20:08:58 | I | - Linking rotation to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.proj.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.proj.a0p1.b0p9.[AbsMax].[fc2].attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200844.RUNNING/model/rotation.pt +24-11-19 20:08:58 | I | * Development dtype is torch.float32 +24-11-19 20:08:58 | I | * Smoothing model for quantization +24-11-19 20:08:58 | I | - Generating smooth scales +24-11-19 20:08:58 | D | Starting new HTTPS connection (1): huggingface.co:443 +24-11-19 20:09:11 | D | Starting new HTTPS connection (2): huggingface.co:443 +24-11-19 20:09:27 | D | Starting new HTTPS connection (1): s3.amazonaws.com:443 +24-11-19 20:09:39 | W | Repo card metadata block was not found. Setting CardData to empty. +24-11-19 20:09:39 | D | Starting new HTTPS connection (3): huggingface.co:443 +24-11-19 20:09:51 | W | Using the latest cached version of the dataset since mit-han-lab/pile-val-backup couldn't be found on the Hugging Face Hub +24-11-19 20:09:51 | W | Found the latest cached dataset configuration 'default' at /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4 (last modified on Tue Oct 8 18:58:39 2024). +24-11-19 20:09:51 | D | Attempting to acquire lock 23438954661744 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:09:51 | D | Lock 23438954661744 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:09:51 | D | open file: /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4/dataset_info.json +24-11-19 20:09:51 | D | Attempting to release lock 23438954661744 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:09:51 | D | Lock 23438954661744 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:10:11 | D | - Smoothing model.layers.0 +24-11-19 20:10:11 | D | - model.layers.0.self_attn.attn_k +24-11-19 20:10:11 | D | + w: None +24-11-19 20:10:11 | D | + x: None +24-11-19 20:10:11 | D | + y: sint8 +24-11-19 20:10:11 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:10:11 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:10:11 | D | + x - AbsMax +24-11-19 20:10:11 | D | + x = [min=1.3467, max=18.0000] +24-11-19 20:10:11 | D | + y - AbsMax +24-11-19 20:10:11 | D | + y = [min=1.5479, max=18.6094] +24-11-19 20:10:11 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:10:12 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:10:12 | D | - alpha = [ 0.5000] +24-11-19 20:10:12 | D | - beta = [ 0.0000] +24-11-19 20:10:12 | D | - sum error = [ 2.7568] +24-11-19 20:10:12 | D | - best error = [ 2.7568] +24-11-19 20:10:12 | D | + error = 2.7568 +24-11-19 20:10:12 | D | + scale = [min=1.2441, max=4.3139] +24-11-19 20:10:12 | D | - model.layers.0.mlp.down_proj +24-11-19 20:10:12 | D | + w: sint8 +24-11-19 20:10:12 | D | + x: sint8 +24-11-19 20:10:12 | D | + y: None +24-11-19 20:10:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:10:12 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:10:13 | D | + x - AbsMax +24-11-19 20:10:13 | D | + x = [min=0.0380, max=6.9219] +24-11-19 20:10:13 | D | + w - AbsMax +24-11-19 20:10:13 | D | + w = [min=0.0275, max=0.0597] +24-11-19 20:10:13 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:10:14 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:10:14 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:10:14 | D | - alpha = [ 0.1000] +24-11-19 20:10:14 | D | - beta = [ 0.9000] +24-11-19 20:10:14 | D | - sum error = [ 24.8007] +24-11-19 20:10:14 | D | - best error = [ 24.8007] +24-11-19 20:10:14 | D | + error = 24.8007 +24-11-19 20:10:14 | D | + scale = [min=9.7755, max=23.6862] +24-11-19 20:10:22 | D | - Smoothing model.layers.1 +24-11-19 20:10:22 | D | - model.layers.1.self_attn.attn_k +24-11-19 20:10:22 | D | + w: None +24-11-19 20:10:22 | D | + x: None +24-11-19 20:10:22 | D | + y: sint8 +24-11-19 20:10:22 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:10:22 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:10:22 | D | + x - AbsMax +24-11-19 20:10:22 | D | + x = [min=2.2598, max=14.4688] +24-11-19 20:10:22 | D | + y - AbsMax +24-11-19 20:10:22 | D | + y = [min=2.4453, max=17.8125] +24-11-19 20:10:22 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:10:23 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:10:23 | D | - alpha = [ 0.5000] +24-11-19 20:10:23 | D | - beta = [ 0.0000] +24-11-19 20:10:23 | D | - sum error = [ 7.1286] +24-11-19 20:10:23 | D | - best error = [ 7.1286] +24-11-19 20:10:23 | D | + error = 7.1286 +24-11-19 20:10:23 | D | + scale = [min=1.5637, max=4.2205] +24-11-19 20:10:23 | D | - model.layers.1.mlp.down_proj +24-11-19 20:10:23 | D | + w: sint8 +24-11-19 20:10:23 | D | + x: sint8 +24-11-19 20:10:23 | D | + y: None +24-11-19 20:10:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:10:23 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:10:24 | D | + x - AbsMax +24-11-19 20:10:24 | D | + x = [min=0.0475, max=504.0000] +24-11-19 20:10:24 | D | + w - AbsMax +24-11-19 20:10:24 | D | + w = [min=0.0237, max=0.0700] +24-11-19 20:10:24 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:10:25 | D | + finished calculating the original outputs, ram usage: 13.4 +24-11-19 20:10:25 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:10:25 | D | - alpha = [ 0.1000] +24-11-19 20:10:25 | D | - beta = [ 0.9000] +24-11-19 20:10:25 | D | - sum error = [ 27.1505] +24-11-19 20:10:25 | D | - best error = [ 27.1505] +24-11-19 20:10:25 | D | + error = 27.1505 +24-11-19 20:10:25 | D | + scale = [min=10.1736, max=46.5831] +24-11-19 20:10:34 | D | - Smoothing model.layers.2 +24-11-19 20:10:34 | D | - model.layers.2.self_attn.attn_k +24-11-19 20:10:34 | D | + w: None +24-11-19 20:10:34 | D | + x: None +24-11-19 20:10:34 | D | + y: sint8 +24-11-19 20:10:34 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:10:34 | D | + finished parsing calibration arguments, ram usage: 14.2 +24-11-19 20:10:34 | D | + x - AbsMax +24-11-19 20:10:34 | D | + x = [min=1.4365, max=15.0547] +24-11-19 20:10:34 | D | + y - AbsMax +24-11-19 20:10:34 | D | + y = [min=1.2695, max=21.7812] +24-11-19 20:10:34 | D | + finished reseting calibrator, ram usage: 14.2 +24-11-19 20:10:34 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:10:34 | D | - alpha = [ 0.5000] +24-11-19 20:10:34 | D | - beta = [ 0.0000] +24-11-19 20:10:34 | D | - sum error = [ 7.3559] +24-11-19 20:10:34 | D | - best error = [ 7.3559] +24-11-19 20:10:34 | D | + error = 7.3559 +24-11-19 20:10:34 | D | + scale = [min=1.1267, max=4.6670] +24-11-19 20:10:35 | D | - model.layers.2.mlp.down_proj +24-11-19 20:10:35 | D | + w: sint8 +24-11-19 20:10:35 | D | + x: sint8 +24-11-19 20:10:35 | D | + y: None +24-11-19 20:10:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:10:35 | D | + finished parsing calibration arguments, ram usage: 14.3 +24-11-19 20:10:35 | D | + x - AbsMax +24-11-19 20:10:35 | D | + x = [min=0.0767, max=2.7754] +24-11-19 20:10:35 | D | + w - AbsMax +24-11-19 20:10:35 | D | + w = [min=0.0235, max=0.0581] +24-11-19 20:10:35 | D | + finished reseting calibrator, ram usage: 14.3 +24-11-19 20:10:36 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:10:36 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:10:36 | D | - alpha = [ 0.1000] +24-11-19 20:10:36 | D | - beta = [ 0.9000] +24-11-19 20:10:36 | D | - sum error = [ 32.3272] +24-11-19 20:10:36 | D | - best error = [ 32.3272] +24-11-19 20:10:36 | D | + error = 32.3272 +24-11-19 20:10:36 | D | + scale = [min=10.4215, max=25.9809] +24-11-19 20:10:44 | D | - Smoothing model.layers.3 +24-11-19 20:10:44 | D | - model.layers.3.self_attn.attn_k +24-11-19 20:10:44 | D | + w: None +24-11-19 20:10:44 | D | + x: None +24-11-19 20:10:44 | D | + y: sint8 +24-11-19 20:10:44 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:10:44 | D | + finished parsing calibration arguments, ram usage: 14.3 +24-11-19 20:10:44 | D | + x - AbsMax +24-11-19 20:10:44 | D | + x = [min=2.4746, max=15.6016] +24-11-19 20:10:44 | D | + y - AbsMax +24-11-19 20:10:44 | D | + y = [min=3.0293, max=23.3438] +24-11-19 20:10:44 | D | + finished reseting calibrator, ram usage: 14.4 +24-11-19 20:10:44 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:10:44 | D | - alpha = [ 0.5000] +24-11-19 20:10:44 | D | - beta = [ 0.0000] +24-11-19 20:10:44 | D | - sum error = [ 11.2295] +24-11-19 20:10:44 | D | - best error = [ 11.2295] +24-11-19 20:10:44 | D | + error = 11.2295 +24-11-19 20:10:44 | D | + scale = [min=1.7405, max=4.8315] +24-11-19 20:10:45 | D | - model.layers.3.mlp.down_proj +24-11-19 20:10:45 | D | + w: sint8 +24-11-19 20:10:45 | D | + x: sint8 +24-11-19 20:10:45 | D | + y: None +24-11-19 20:10:45 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:10:45 | D | + finished parsing calibration arguments, ram usage: 14.1 +24-11-19 20:10:45 | D | + x - AbsMax +24-11-19 20:10:45 | D | + x = [min=0.1042, max=2.8574] +24-11-19 20:10:45 | D | + w - AbsMax +24-11-19 20:10:45 | D | + w = [min=0.0229, max=0.0603] +24-11-19 20:10:45 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:10:46 | D | + finished calculating the original outputs, ram usage: 14.1 +24-11-19 20:10:46 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:10:46 | D | - alpha = [ 0.1000] +24-11-19 20:10:46 | D | - beta = [ 0.9000] +24-11-19 20:10:46 | D | - sum error = [ 31.8928] +24-11-19 20:10:46 | D | - best error = [ 31.8928] +24-11-19 20:10:46 | D | + error = 31.8928 +24-11-19 20:10:46 | D | + scale = [min=10.6599, max=31.3602] +24-11-19 20:10:53 | D | - Smoothing model.layers.4 +24-11-19 20:10:53 | D | - model.layers.4.self_attn.attn_k +24-11-19 20:10:53 | D | + w: None +24-11-19 20:10:53 | D | + x: None +24-11-19 20:10:53 | D | + y: sint8 +24-11-19 20:10:53 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:10:53 | D | + finished parsing calibration arguments, ram usage: 14.4 +24-11-19 20:10:53 | D | + x - AbsMax +24-11-19 20:10:53 | D | + x = [min=2.1934, max=15.2812] +24-11-19 20:10:53 | D | + y - AbsMax +24-11-19 20:10:53 | D | + y = [min=3.4199, max=24.3125] +24-11-19 20:10:53 | D | + finished reseting calibrator, ram usage: 14.4 +24-11-19 20:10:54 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:10:54 | D | - alpha = [ 0.5000] +24-11-19 20:10:54 | D | - beta = [ 0.0000] +24-11-19 20:10:54 | D | - sum error = [ 20.4703] +24-11-19 20:10:54 | D | - best error = [ 20.4703] +24-11-19 20:10:54 | D | + error = 20.4703 +24-11-19 20:10:54 | D | + scale = [min=1.8493, max=4.9308] +24-11-19 20:10:54 | D | - model.layers.4.mlp.down_proj +24-11-19 20:10:54 | D | + w: sint8 +24-11-19 20:10:54 | D | + x: sint8 +24-11-19 20:10:54 | D | + y: None +24-11-19 20:10:54 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:10:54 | D | + finished parsing calibration arguments, ram usage: 14.5 +24-11-19 20:10:55 | D | + x - AbsMax +24-11-19 20:10:55 | D | + x = [min=0.0875, max=4.7188] +24-11-19 20:10:55 | D | + w - AbsMax +24-11-19 20:10:55 | D | + w = [min=0.0214, max=0.0586] +24-11-19 20:10:55 | D | + finished reseting calibrator, ram usage: 14.5 +24-11-19 20:10:55 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:10:56 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:10:56 | D | - alpha = [ 0.1000] +24-11-19 20:10:56 | D | - beta = [ 0.9000] +24-11-19 20:10:56 | D | - sum error = [ 42.9206] +24-11-19 20:10:56 | D | - best error = [ 42.9206] +24-11-19 20:10:56 | D | + error = 42.9206 +24-11-19 20:10:56 | D | + scale = [min=10.7825, max=31.1358] +24-11-19 20:11:03 | D | - Smoothing model.layers.5 +24-11-19 20:11:03 | D | - model.layers.5.self_attn.attn_k +24-11-19 20:11:03 | D | + w: None +24-11-19 20:11:03 | D | + x: None +24-11-19 20:11:03 | D | + y: sint8 +24-11-19 20:11:03 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:03 | D | + finished parsing calibration arguments, ram usage: 14.3 +24-11-19 20:11:03 | D | + x - AbsMax +24-11-19 20:11:03 | D | + x = [min=2.9180, max=18.8281] +24-11-19 20:11:03 | D | + y - AbsMax +24-11-19 20:11:03 | D | + y = [min=2.4434, max=27.2812] +24-11-19 20:11:03 | D | + finished reseting calibrator, ram usage: 14.3 +24-11-19 20:11:04 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:04 | D | - alpha = [ 0.5000] +24-11-19 20:11:04 | D | - beta = [ 0.0000] +24-11-19 20:11:04 | D | - sum error = [ 19.7660] +24-11-19 20:11:04 | D | - best error = [ 19.7660] +24-11-19 20:11:04 | D | + error = 19.7660 +24-11-19 20:11:04 | D | + scale = [min=1.5631, max=5.2231] +24-11-19 20:11:04 | D | - model.layers.5.mlp.down_proj +24-11-19 20:11:04 | D | + w: sint8 +24-11-19 20:11:04 | D | + x: sint8 +24-11-19 20:11:04 | D | + y: None +24-11-19 20:11:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:04 | D | + finished parsing calibration arguments, ram usage: 14.4 +24-11-19 20:11:04 | D | + x - AbsMax +24-11-19 20:11:04 | D | + x = [min=0.1255, max=4.9297] +24-11-19 20:11:04 | D | + w - AbsMax +24-11-19 20:11:04 | D | + w = [min=0.0194, max=0.0735] +24-11-19 20:11:04 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:11:05 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:11:05 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:05 | D | - alpha = [ 0.1000] +24-11-19 20:11:05 | D | - beta = [ 0.9000] +24-11-19 20:11:05 | D | - sum error = [ 51.8428] +24-11-19 20:11:05 | D | - best error = [ 51.8428] +24-11-19 20:11:05 | D | + error = 51.8428 +24-11-19 20:11:05 | D | + scale = [min=9.9258, max=35.8484] +24-11-19 20:11:13 | D | - Smoothing model.layers.6 +24-11-19 20:11:13 | D | - model.layers.6.self_attn.attn_k +24-11-19 20:11:13 | D | + w: None +24-11-19 20:11:13 | D | + x: None +24-11-19 20:11:13 | D | + y: sint8 +24-11-19 20:11:13 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:13 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:11:13 | D | + x - AbsMax +24-11-19 20:11:13 | D | + x = [min=2.4512, max=18.4844] +24-11-19 20:11:13 | D | + y - AbsMax +24-11-19 20:11:13 | D | + y = [min=3.5645, max=22.1094] +24-11-19 20:11:13 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:11:14 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:14 | D | - alpha = [ 0.5000] +24-11-19 20:11:14 | D | - beta = [ 0.0000] +24-11-19 20:11:14 | D | - sum error = [ 18.1268] +24-11-19 20:11:14 | D | - best error = [ 18.1268] +24-11-19 20:11:14 | D | + error = 18.1268 +24-11-19 20:11:14 | D | + scale = [min=1.8880, max=4.7021] +24-11-19 20:11:14 | D | - model.layers.6.mlp.down_proj +24-11-19 20:11:14 | D | + w: sint8 +24-11-19 20:11:14 | D | + x: sint8 +24-11-19 20:11:14 | D | + y: None +24-11-19 20:11:14 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:14 | D | + finished parsing calibration arguments, ram usage: 14.1 +24-11-19 20:11:14 | D | + x - AbsMax +24-11-19 20:11:14 | D | + x = [min=0.1246, max=5.4297] +24-11-19 20:11:14 | D | + w - AbsMax +24-11-19 20:11:14 | D | + w = [min=0.0197, max=0.0604] +24-11-19 20:11:14 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:11:15 | D | + finished calculating the original outputs, ram usage: 13.1 +24-11-19 20:11:16 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:16 | D | - alpha = [ 0.1000] +24-11-19 20:11:16 | D | - beta = [ 0.9000] +24-11-19 20:11:16 | D | - sum error = [ 52.5239] +24-11-19 20:11:16 | D | - best error = [ 52.5239] +24-11-19 20:11:16 | D | + error = 52.5239 +24-11-19 20:11:16 | D | + scale = [min=11.2315, max=35.4599] +24-11-19 20:11:22 | D | - Smoothing model.layers.7 +24-11-19 20:11:22 | D | - model.layers.7.self_attn.attn_k +24-11-19 20:11:22 | D | + w: None +24-11-19 20:11:22 | D | + x: None +24-11-19 20:11:22 | D | + y: sint8 +24-11-19 20:11:22 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:22 | D | + finished parsing calibration arguments, ram usage: 14.1 +24-11-19 20:11:22 | D | + x - AbsMax +24-11-19 20:11:22 | D | + x = [min=2.7207, max=17.5469] +24-11-19 20:11:22 | D | + y - AbsMax +24-11-19 20:11:22 | D | + y = [min=3.4629, max=23.9844] +24-11-19 20:11:22 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:11:23 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:23 | D | - alpha = [ 0.5000] +24-11-19 20:11:23 | D | - beta = [ 0.0000] +24-11-19 20:11:23 | D | - sum error = [ 25.4320] +24-11-19 20:11:23 | D | - best error = [ 25.4320] +24-11-19 20:11:23 | D | + error = 25.4320 +24-11-19 20:11:23 | D | + scale = [min=1.8609, max=4.8974] +24-11-19 20:11:23 | D | - model.layers.7.mlp.down_proj +24-11-19 20:11:23 | D | + w: sint8 +24-11-19 20:11:23 | D | + x: sint8 +24-11-19 20:11:23 | D | + y: None +24-11-19 20:11:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:23 | D | + finished parsing calibration arguments, ram usage: 14.2 +24-11-19 20:11:23 | D | + x - AbsMax +24-11-19 20:11:23 | D | + x = [min=0.1279, max=5.0156] +24-11-19 20:11:23 | D | + w - AbsMax +24-11-19 20:11:23 | D | + w = [min=0.0238, max=0.0638] +24-11-19 20:11:23 | D | + finished reseting calibrator, ram usage: 14.2 +24-11-19 20:11:24 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:11:25 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:25 | D | - alpha = [ 0.1000] +24-11-19 20:11:25 | D | - beta = [ 0.9000] +24-11-19 20:11:25 | D | - sum error = [ 46.5051] +24-11-19 20:11:25 | D | - best error = [ 46.5051] +24-11-19 20:11:25 | D | + error = 46.5051 +24-11-19 20:11:25 | D | + scale = [min=10.8163, max=30.3377] +24-11-19 20:11:32 | D | - Smoothing model.layers.8 +24-11-19 20:11:32 | D | - model.layers.8.self_attn.attn_k +24-11-19 20:11:32 | D | + w: None +24-11-19 20:11:32 | D | + x: None +24-11-19 20:11:32 | D | + y: sint8 +24-11-19 20:11:32 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:32 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:11:32 | D | + x - AbsMax +24-11-19 20:11:32 | D | + x = [min=2.5527, max=19.6406] +24-11-19 20:11:32 | D | + y - AbsMax +24-11-19 20:11:32 | D | + y = [min=2.7891, max=23.6719] +24-11-19 20:11:32 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:11:32 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:32 | D | - alpha = [ 0.5000] +24-11-19 20:11:32 | D | - beta = [ 0.0000] +24-11-19 20:11:32 | D | - sum error = [ 21.6155] +24-11-19 20:11:32 | D | - best error = [ 21.6155] +24-11-19 20:11:32 | D | + error = 21.6155 +24-11-19 20:11:32 | D | + scale = [min=1.6700, max=4.8654] +24-11-19 20:11:33 | D | - model.layers.8.mlp.down_proj +24-11-19 20:11:33 | D | + w: sint8 +24-11-19 20:11:33 | D | + x: sint8 +24-11-19 20:11:33 | D | + y: None +24-11-19 20:11:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:33 | D | + finished parsing calibration arguments, ram usage: 14.1 +24-11-19 20:11:33 | D | + x - AbsMax +24-11-19 20:11:33 | D | + x = [min=0.1555, max=4.7812] +24-11-19 20:11:33 | D | + w - AbsMax +24-11-19 20:11:33 | D | + w = [min=0.0228, max=0.0617] +24-11-19 20:11:33 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:11:34 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:11:34 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:34 | D | - alpha = [ 0.1000] +24-11-19 20:11:34 | D | - beta = [ 0.9000] +24-11-19 20:11:34 | D | - sum error = [ 46.0913] +24-11-19 20:11:34 | D | - best error = [ 46.0913] +24-11-19 20:11:34 | D | + error = 46.0913 +24-11-19 20:11:34 | D | + scale = [min=11.1112, max=29.1957] +24-11-19 20:11:42 | D | - Smoothing model.layers.9 +24-11-19 20:11:42 | D | - model.layers.9.self_attn.attn_k +24-11-19 20:11:42 | D | + w: None +24-11-19 20:11:42 | D | + x: None +24-11-19 20:11:42 | D | + y: sint8 +24-11-19 20:11:42 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:42 | D | + finished parsing calibration arguments, ram usage: 14.2 +24-11-19 20:11:42 | D | + x - AbsMax +24-11-19 20:11:42 | D | + x = [min=2.4062, max=15.3125] +24-11-19 20:11:42 | D | + y - AbsMax +24-11-19 20:11:42 | D | + y = [min=3.0723, max=25.1562] +24-11-19 20:11:42 | D | + finished reseting calibrator, ram usage: 14.2 +24-11-19 20:11:42 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:42 | D | - alpha = [ 0.5000] +24-11-19 20:11:42 | D | - beta = [ 0.0000] +24-11-19 20:11:42 | D | - sum error = [ 22.4573] +24-11-19 20:11:42 | D | - best error = [ 22.4573] +24-11-19 20:11:42 | D | + error = 22.4573 +24-11-19 20:11:42 | D | + scale = [min=1.7528, max=5.0156] +24-11-19 20:11:42 | D | - model.layers.9.mlp.down_proj +24-11-19 20:11:42 | D | + w: sint8 +24-11-19 20:11:42 | D | + x: sint8 +24-11-19 20:11:42 | D | + y: None +24-11-19 20:11:42 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:42 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:11:43 | D | + x - AbsMax +24-11-19 20:11:43 | D | + x = [min=0.1764, max=7.0156] +24-11-19 20:11:43 | D | + w - AbsMax +24-11-19 20:11:43 | D | + w = [min=0.0215, max=0.0620] +24-11-19 20:11:43 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:11:43 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:11:44 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:44 | D | - alpha = [ 0.1000] +24-11-19 20:11:44 | D | - beta = [ 0.9000] +24-11-19 20:11:44 | D | - sum error = [ 52.0402] +24-11-19 20:11:44 | D | - best error = [ 52.0402] +24-11-19 20:11:44 | D | + error = 52.0402 +24-11-19 20:11:44 | D | + scale = [min=11.7412, max=33.5508] +24-11-19 20:11:51 | D | - Smoothing model.layers.10 +24-11-19 20:11:51 | D | - model.layers.10.self_attn.attn_k +24-11-19 20:11:51 | D | + w: None +24-11-19 20:11:51 | D | + x: None +24-11-19 20:11:51 | D | + y: sint8 +24-11-19 20:11:51 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:51 | D | + finished parsing calibration arguments, ram usage: 14.4 +24-11-19 20:11:51 | D | + x - AbsMax +24-11-19 20:11:51 | D | + x = [min=2.7832, max=16.7969] +24-11-19 20:11:51 | D | + y - AbsMax +24-11-19 20:11:51 | D | + y = [min=3.5762, max=23.3750] +24-11-19 20:11:51 | D | + finished reseting calibrator, ram usage: 14.4 +24-11-19 20:11:52 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:52 | D | - alpha = [ 0.5000] +24-11-19 20:11:52 | D | - beta = [ 0.0000] +24-11-19 20:11:52 | D | - sum error = [ 19.7481] +24-11-19 20:11:52 | D | - best error = [ 19.7481] +24-11-19 20:11:52 | D | + error = 19.7481 +24-11-19 20:11:52 | D | + scale = [min=1.8911, max=4.8348] +24-11-19 20:11:52 | D | - model.layers.10.mlp.down_proj +24-11-19 20:11:52 | D | + w: sint8 +24-11-19 20:11:52 | D | + x: sint8 +24-11-19 20:11:52 | D | + y: None +24-11-19 20:11:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:11:52 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:11:52 | D | + x - AbsMax +24-11-19 20:11:52 | D | + x = [min=0.2068, max=6.2539] +24-11-19 20:11:52 | D | + w - AbsMax +24-11-19 20:11:52 | D | + w = [min=0.0226, max=0.0599] +24-11-19 20:11:52 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:11:54 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:11:54 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:11:54 | D | - alpha = [ 0.1000] +24-11-19 20:11:54 | D | - beta = [ 0.9000] +24-11-19 20:11:54 | D | - sum error = [ 50.6967] +24-11-19 20:11:54 | D | - best error = [ 50.6967] +24-11-19 20:11:54 | D | + error = 50.6967 +24-11-19 20:11:54 | D | + scale = [min=11.4211, max=29.9922] +24-11-19 20:12:02 | D | - Smoothing model.layers.11 +24-11-19 20:12:02 | D | - model.layers.11.self_attn.attn_k +24-11-19 20:12:02 | D | + w: None +24-11-19 20:12:02 | D | + x: None +24-11-19 20:12:02 | D | + y: sint8 +24-11-19 20:12:02 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:02 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:12:02 | D | + x - AbsMax +24-11-19 20:12:02 | D | + x = [min=2.3789, max=15.8125] +24-11-19 20:12:02 | D | + y - AbsMax +24-11-19 20:12:02 | D | + y = [min=3.2129, max=26.1406] +24-11-19 20:12:02 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:12:03 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:03 | D | - alpha = [ 0.5000] +24-11-19 20:12:03 | D | - beta = [ 0.0000] +24-11-19 20:12:03 | D | - sum error = [ 24.0137] +24-11-19 20:12:03 | D | - best error = [ 24.0137] +24-11-19 20:12:03 | D | + error = 24.0137 +24-11-19 20:12:03 | D | + scale = [min=1.7925, max=5.1128] +24-11-19 20:12:03 | D | - model.layers.11.mlp.down_proj +24-11-19 20:12:03 | D | + w: sint8 +24-11-19 20:12:03 | D | + x: sint8 +24-11-19 20:12:03 | D | + y: None +24-11-19 20:12:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:03 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:12:03 | D | + x - AbsMax +24-11-19 20:12:03 | D | + x = [min=0.1968, max=5.8047] +24-11-19 20:12:03 | D | + w - AbsMax +24-11-19 20:12:03 | D | + w = [min=0.0204, max=0.0685] +24-11-19 20:12:03 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:12:04 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:12:04 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:04 | D | - alpha = [ 0.1000] +24-11-19 20:12:04 | D | - beta = [ 0.9000] +24-11-19 20:12:04 | D | - sum error = [ 51.3733] +24-11-19 20:12:04 | D | - best error = [ 51.3733] +24-11-19 20:12:04 | D | + error = 51.3733 +24-11-19 20:12:04 | D | + scale = [min=10.2005, max=35.7681] +24-11-19 20:12:12 | D | - Smoothing model.layers.12 +24-11-19 20:12:12 | D | - model.layers.12.self_attn.attn_k +24-11-19 20:12:12 | D | + w: None +24-11-19 20:12:12 | D | + x: None +24-11-19 20:12:12 | D | + y: sint8 +24-11-19 20:12:12 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:12 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:12:12 | D | + x - AbsMax +24-11-19 20:12:12 | D | + x = [min=2.6582, max=21.0625] +24-11-19 20:12:13 | D | + y - AbsMax +24-11-19 20:12:13 | D | + y = [min=3.4844, max=25.3594] +24-11-19 20:12:13 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:12:13 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:13 | D | - alpha = [ 0.5000] +24-11-19 20:12:13 | D | - beta = [ 0.0000] +24-11-19 20:12:13 | D | - sum error = [ 32.7301] +24-11-19 20:12:13 | D | - best error = [ 32.7301] +24-11-19 20:12:13 | D | + error = 32.7301 +24-11-19 20:12:13 | D | + scale = [min=1.8666, max=5.0358] +24-11-19 20:12:13 | D | - model.layers.12.mlp.down_proj +24-11-19 20:12:13 | D | + w: sint8 +24-11-19 20:12:13 | D | + x: sint8 +24-11-19 20:12:13 | D | + y: None +24-11-19 20:12:13 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:13 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:12:14 | D | + x - AbsMax +24-11-19 20:12:14 | D | + x = [min=0.1401, max=6.1250] +24-11-19 20:12:14 | D | + w - AbsMax +24-11-19 20:12:14 | D | + w = [min=0.0216, max=0.0722] +24-11-19 20:12:14 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:12:14 | D | + finished calculating the original outputs, ram usage: 13.3 +24-11-19 20:12:15 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:15 | D | - alpha = [ 0.1000] +24-11-19 20:12:15 | D | - beta = [ 0.9000] +24-11-19 20:12:15 | D | - sum error = [ 51.0661] +24-11-19 20:12:15 | D | - best error = [ 51.0661] +24-11-19 20:12:15 | D | + error = 51.0661 +24-11-19 20:12:15 | D | + scale = [min=9.8787, max=33.2987] +24-11-19 20:12:22 | D | - Smoothing model.layers.13 +24-11-19 20:12:22 | D | - model.layers.13.self_attn.attn_k +24-11-19 20:12:22 | D | + w: None +24-11-19 20:12:22 | D | + x: None +24-11-19 20:12:22 | D | + y: sint8 +24-11-19 20:12:22 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:22 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:12:22 | D | + x - AbsMax +24-11-19 20:12:22 | D | + x = [min=2.3457, max=18.3906] +24-11-19 20:12:22 | D | + y - AbsMax +24-11-19 20:12:22 | D | + y = [min=2.7832, max=23.2812] +24-11-19 20:12:22 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:12:23 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:23 | D | - alpha = [ 0.5000] +24-11-19 20:12:23 | D | - beta = [ 0.0000] +24-11-19 20:12:23 | D | - sum error = [ 25.4453] +24-11-19 20:12:23 | D | - best error = [ 25.4453] +24-11-19 20:12:23 | D | + error = 25.4453 +24-11-19 20:12:23 | D | + scale = [min=1.6683, max=4.8251] +24-11-19 20:12:23 | D | - model.layers.13.mlp.down_proj +24-11-19 20:12:23 | D | + w: sint8 +24-11-19 20:12:23 | D | + x: sint8 +24-11-19 20:12:23 | D | + y: None +24-11-19 20:12:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:23 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:12:24 | D | + x - AbsMax +24-11-19 20:12:24 | D | + x = [min=0.1967, max=6.7773] +24-11-19 20:12:24 | D | + w - AbsMax +24-11-19 20:12:24 | D | + w = [min=0.0212, max=0.0683] +24-11-19 20:12:24 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:12:24 | D | + finished calculating the original outputs, ram usage: 14.2 +24-11-19 20:12:25 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:25 | D | - alpha = [ 0.1000] +24-11-19 20:12:25 | D | - beta = [ 0.9000] +24-11-19 20:12:25 | D | - sum error = [ 62.9507] +24-11-19 20:12:25 | D | - best error = [ 62.9507] +24-11-19 20:12:25 | D | + error = 62.9507 +24-11-19 20:12:25 | D | + scale = [min=10.6207, max=34.0587] +24-11-19 20:12:33 | D | - Smoothing model.layers.14 +24-11-19 20:12:33 | D | - model.layers.14.self_attn.attn_k +24-11-19 20:12:33 | D | + w: None +24-11-19 20:12:33 | D | + x: None +24-11-19 20:12:33 | D | + y: sint8 +24-11-19 20:12:33 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:33 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:12:33 | D | + x - AbsMax +24-11-19 20:12:33 | D | + x = [min=2.2734, max=16.0781] +24-11-19 20:12:33 | D | + y - AbsMax +24-11-19 20:12:33 | D | + y = [min=2.9512, max=25.4531] +24-11-19 20:12:33 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:12:33 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:33 | D | - alpha = [ 0.5000] +24-11-19 20:12:33 | D | - beta = [ 0.0000] +24-11-19 20:12:33 | D | - sum error = [ 30.6803] +24-11-19 20:12:33 | D | - best error = [ 30.6803] +24-11-19 20:12:33 | D | + error = 30.6803 +24-11-19 20:12:33 | D | + scale = [min=1.7179, max=5.0451] +24-11-19 20:12:33 | D | - model.layers.14.mlp.down_proj +24-11-19 20:12:33 | D | + w: sint8 +24-11-19 20:12:33 | D | + x: sint8 +24-11-19 20:12:33 | D | + y: None +24-11-19 20:12:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:33 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:12:34 | D | + x - AbsMax +24-11-19 20:12:34 | D | + x = [min=0.1733, max=6.9570] +24-11-19 20:12:34 | D | + w - AbsMax +24-11-19 20:12:34 | D | + w = [min=0.0197, max=0.0730] +24-11-19 20:12:34 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:12:35 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:12:35 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:35 | D | - alpha = [ 0.1000] +24-11-19 20:12:35 | D | - beta = [ 0.9000] +24-11-19 20:12:35 | D | - sum error = [ 78.2689] +24-11-19 20:12:35 | D | - best error = [ 78.2689] +24-11-19 20:12:35 | D | + error = 78.2689 +24-11-19 20:12:35 | D | + scale = [min=9.4818, max=37.6123] +24-11-19 20:12:43 | D | - Smoothing model.layers.15 +24-11-19 20:12:43 | D | - model.layers.15.self_attn.attn_k +24-11-19 20:12:43 | D | + w: None +24-11-19 20:12:43 | D | + x: None +24-11-19 20:12:43 | D | + y: sint8 +24-11-19 20:12:43 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:43 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:12:43 | D | + x - AbsMax +24-11-19 20:12:43 | D | + x = [min=2.6152, max=18.0625] +24-11-19 20:12:43 | D | + y - AbsMax +24-11-19 20:12:43 | D | + y = [min=3.1660, max=24.4531] +24-11-19 20:12:43 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:12:43 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:43 | D | - alpha = [ 0.5000] +24-11-19 20:12:43 | D | - beta = [ 0.0000] +24-11-19 20:12:43 | D | - sum error = [ 29.8959] +24-11-19 20:12:43 | D | - best error = [ 29.8959] +24-11-19 20:12:43 | D | + error = 29.8959 +24-11-19 20:12:43 | D | + scale = [min=1.7793, max=4.9450] +24-11-19 20:12:44 | D | - model.layers.15.mlp.down_proj +24-11-19 20:12:44 | D | + w: sint8 +24-11-19 20:12:44 | D | + x: sint8 +24-11-19 20:12:44 | D | + y: None +24-11-19 20:12:44 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:44 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:12:44 | D | + x - AbsMax +24-11-19 20:12:44 | D | + x = [min=0.2151, max=9.5312] +24-11-19 20:12:44 | D | + w - AbsMax +24-11-19 20:12:44 | D | + w = [min=0.0214, max=0.0631] +24-11-19 20:12:44 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:12:45 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:12:45 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:45 | D | - alpha = [ 0.1000] +24-11-19 20:12:45 | D | - beta = [ 0.9000] +24-11-19 20:12:45 | D | - sum error = [ 97.0449] +24-11-19 20:12:45 | D | - best error = [ 97.0449] +24-11-19 20:12:45 | D | + error = 97.0449 +24-11-19 20:12:45 | D | + scale = [min=10.8533, max=36.1533] +24-11-19 20:12:53 | D | - Smoothing model.layers.16 +24-11-19 20:12:53 | D | - model.layers.16.self_attn.attn_k +24-11-19 20:12:53 | D | + w: None +24-11-19 20:12:53 | D | + x: None +24-11-19 20:12:53 | D | + y: sint8 +24-11-19 20:12:53 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:53 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:12:53 | D | + x - AbsMax +24-11-19 20:12:53 | D | + x = [min=2.5508, max=19.0781] +24-11-19 20:12:53 | D | + y - AbsMax +24-11-19 20:12:53 | D | + y = [min=2.6094, max=25.7656] +24-11-19 20:12:53 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:12:53 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:53 | D | - alpha = [ 0.5000] +24-11-19 20:12:53 | D | - beta = [ 0.0000] +24-11-19 20:12:53 | D | - sum error = [ 34.2738] +24-11-19 20:12:53 | D | - best error = [ 34.2738] +24-11-19 20:12:53 | D | + error = 34.2738 +24-11-19 20:12:53 | D | + scale = [min=1.6154, max=5.0760] +24-11-19 20:12:53 | D | - model.layers.16.mlp.down_proj +24-11-19 20:12:53 | D | + w: sint8 +24-11-19 20:12:53 | D | + x: sint8 +24-11-19 20:12:53 | D | + y: None +24-11-19 20:12:53 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:12:53 | D | + finished parsing calibration arguments, ram usage: 14.1 +24-11-19 20:12:54 | D | + x - AbsMax +24-11-19 20:12:54 | D | + x = [min=0.1919, max=11.1406] +24-11-19 20:12:54 | D | + w - AbsMax +24-11-19 20:12:54 | D | + w = [min=0.0200, max=0.0633] +24-11-19 20:12:54 | D | + finished reseting calibrator, ram usage: 14.2 +24-11-19 20:12:54 | D | + finished calculating the original outputs, ram usage: 14.3 +24-11-19 20:12:55 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:12:55 | D | - alpha = [ 0.1000] +24-11-19 20:12:55 | D | - beta = [ 0.9000] +24-11-19 20:12:55 | D | - sum error = [ 109.9668] +24-11-19 20:12:55 | D | - best error = [ 109.9668] +24-11-19 20:12:55 | D | + error = 109.9668 +24-11-19 20:12:55 | D | + scale = [min=11.8753, max=37.6204] +24-11-19 20:13:02 | D | - Smoothing model.layers.17 +24-11-19 20:13:02 | D | - model.layers.17.self_attn.attn_k +24-11-19 20:13:02 | D | + w: None +24-11-19 20:13:02 | D | + x: None +24-11-19 20:13:02 | D | + y: sint8 +24-11-19 20:13:02 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:02 | D | + finished parsing calibration arguments, ram usage: 14.2 +24-11-19 20:13:02 | D | + x - AbsMax +24-11-19 20:13:02 | D | + x = [min=2.8594, max=18.2969] +24-11-19 20:13:02 | D | + y - AbsMax +24-11-19 20:13:02 | D | + y = [min=2.9941, max=23.2031] +24-11-19 20:13:02 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:13:03 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:03 | D | - alpha = [ 0.5000] +24-11-19 20:13:03 | D | - beta = [ 0.0000] +24-11-19 20:13:03 | D | - sum error = [ 29.4680] +24-11-19 20:13:03 | D | - best error = [ 29.4680] +24-11-19 20:13:03 | D | + error = 29.4680 +24-11-19 20:13:03 | D | + scale = [min=1.7304, max=4.8170] +24-11-19 20:13:03 | D | - model.layers.17.mlp.down_proj +24-11-19 20:13:03 | D | + w: sint8 +24-11-19 20:13:03 | D | + x: sint8 +24-11-19 20:13:03 | D | + y: None +24-11-19 20:13:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:03 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:13:04 | D | + x - AbsMax +24-11-19 20:13:04 | D | + x = [min=0.3064, max=13.2812] +24-11-19 20:13:04 | D | + w - AbsMax +24-11-19 20:13:04 | D | + w = [min=0.0195, max=0.0630] +24-11-19 20:13:04 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:13:04 | D | + finished calculating the original outputs, ram usage: 14.1 +24-11-19 20:13:05 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:05 | D | - alpha = [ 0.1000] +24-11-19 20:13:05 | D | - beta = [ 0.9000] +24-11-19 20:13:05 | D | - sum error = [ 123.4335] +24-11-19 20:13:05 | D | - best error = [ 123.4335] +24-11-19 20:13:05 | D | + error = 123.4335 +24-11-19 20:13:05 | D | + scale = [min=11.4174, max=37.7031] +24-11-19 20:13:12 | D | - Smoothing model.layers.18 +24-11-19 20:13:12 | D | - model.layers.18.self_attn.attn_k +24-11-19 20:13:12 | D | + w: None +24-11-19 20:13:12 | D | + x: None +24-11-19 20:13:12 | D | + y: sint8 +24-11-19 20:13:12 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:12 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:13:12 | D | + x - AbsMax +24-11-19 20:13:12 | D | + x = [min=2.8047, max=17.0000] +24-11-19 20:13:12 | D | + y - AbsMax +24-11-19 20:13:12 | D | + y = [min=2.9727, max=22.5000] +24-11-19 20:13:12 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:13:13 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:13 | D | - alpha = [ 0.5000] +24-11-19 20:13:13 | D | - beta = [ 0.0000] +24-11-19 20:13:13 | D | - sum error = [ 23.9080] +24-11-19 20:13:13 | D | - best error = [ 23.9080] +24-11-19 20:13:13 | D | + error = 23.9080 +24-11-19 20:13:13 | D | + scale = [min=1.7241, max=4.7434] +24-11-19 20:13:13 | D | - model.layers.18.mlp.down_proj +24-11-19 20:13:13 | D | + w: sint8 +24-11-19 20:13:13 | D | + x: sint8 +24-11-19 20:13:13 | D | + y: None +24-11-19 20:13:13 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:13 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:13:13 | D | + x - AbsMax +24-11-19 20:13:13 | D | + x = [min=0.3228, max=13.8516] +24-11-19 20:13:13 | D | + w - AbsMax +24-11-19 20:13:13 | D | + w = [min=0.0196, max=0.0601] +24-11-19 20:13:13 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:13:14 | D | + finished calculating the original outputs, ram usage: 14.1 +24-11-19 20:13:14 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:14 | D | - alpha = [ 0.1000] +24-11-19 20:13:14 | D | - beta = [ 0.9000] +24-11-19 20:13:14 | D | - sum error = [ 122.6133] +24-11-19 20:13:14 | D | - best error = [ 122.6133] +24-11-19 20:13:14 | D | + error = 122.6133 +24-11-19 20:13:14 | D | + scale = [min=12.2049, max=38.2180] +24-11-19 20:13:22 | D | - Smoothing model.layers.19 +24-11-19 20:13:22 | D | - model.layers.19.self_attn.attn_k +24-11-19 20:13:22 | D | + w: None +24-11-19 20:13:22 | D | + x: None +24-11-19 20:13:22 | D | + y: sint8 +24-11-19 20:13:22 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:22 | D | + finished parsing calibration arguments, ram usage: 14.3 +24-11-19 20:13:22 | D | + x - AbsMax +24-11-19 20:13:22 | D | + x = [min=1.6318, max=18.2500] +24-11-19 20:13:22 | D | + y - AbsMax +24-11-19 20:13:22 | D | + y = [min=3.8086, max=22.5469] +24-11-19 20:13:22 | D | + finished reseting calibrator, ram usage: 14.3 +24-11-19 20:13:22 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:22 | D | - alpha = [ 0.5000] +24-11-19 20:13:22 | D | - beta = [ 0.0000] +24-11-19 20:13:22 | D | - sum error = [ 22.1298] +24-11-19 20:13:22 | D | - best error = [ 22.1298] +24-11-19 20:13:22 | D | + error = 22.1298 +24-11-19 20:13:22 | D | + scale = [min=1.9516, max=4.7484] +24-11-19 20:13:23 | D | - model.layers.19.mlp.down_proj +24-11-19 20:13:23 | D | + w: sint8 +24-11-19 20:13:23 | D | + x: sint8 +24-11-19 20:13:23 | D | + y: None +24-11-19 20:13:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:23 | D | + finished parsing calibration arguments, ram usage: 14.4 +24-11-19 20:13:23 | D | + x - AbsMax +24-11-19 20:13:23 | D | + x = [min=0.4241, max=15.0078] +24-11-19 20:13:23 | D | + w - AbsMax +24-11-19 20:13:23 | D | + w = [min=0.0193, max=0.0605] +24-11-19 20:13:23 | D | + finished reseting calibrator, ram usage: 14.2 +24-11-19 20:13:24 | D | + finished calculating the original outputs, ram usage: 14.1 +24-11-19 20:13:25 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:25 | D | - alpha = [ 0.1000] +24-11-19 20:13:25 | D | - beta = [ 0.9000] +24-11-19 20:13:25 | D | - sum error = [ 125.7033] +24-11-19 20:13:25 | D | - best error = [ 125.7033] +24-11-19 20:13:25 | D | + error = 125.7033 +24-11-19 20:13:25 | D | + scale = [min=12.1484, max=38.0697] +24-11-19 20:13:31 | D | - Smoothing model.layers.20 +24-11-19 20:13:31 | D | - model.layers.20.self_attn.attn_k +24-11-19 20:13:31 | D | + w: None +24-11-19 20:13:31 | D | + x: None +24-11-19 20:13:31 | D | + y: sint8 +24-11-19 20:13:31 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:31 | D | + finished parsing calibration arguments, ram usage: 14.1 +24-11-19 20:13:31 | D | + x - AbsMax +24-11-19 20:13:31 | D | + x = [min=1.7852, max=18.7500] +24-11-19 20:13:31 | D | + y - AbsMax +24-11-19 20:13:31 | D | + y = [min=3.3359, max=21.0312] +24-11-19 20:13:31 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:13:32 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:32 | D | - alpha = [ 0.5000] +24-11-19 20:13:32 | D | - beta = [ 0.0000] +24-11-19 20:13:32 | D | - sum error = [ 20.8735] +24-11-19 20:13:32 | D | - best error = [ 20.8735] +24-11-19 20:13:32 | D | + error = 20.8735 +24-11-19 20:13:32 | D | + scale = [min=1.8265, max=4.5860] +24-11-19 20:13:33 | D | - model.layers.20.mlp.down_proj +24-11-19 20:13:33 | D | + w: sint8 +24-11-19 20:13:33 | D | + x: sint8 +24-11-19 20:13:33 | D | + y: None +24-11-19 20:13:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:33 | D | + finished parsing calibration arguments, ram usage: 14.2 +24-11-19 20:13:33 | D | + x - AbsMax +24-11-19 20:13:33 | D | + x = [min=0.4150, max=21.4688] +24-11-19 20:13:33 | D | + w - AbsMax +24-11-19 20:13:33 | D | + w = [min=0.0233, max=0.0603] +24-11-19 20:13:33 | D | + finished reseting calibrator, ram usage: 14.2 +24-11-19 20:13:34 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:13:34 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:34 | D | - alpha = [ 0.1000] +24-11-19 20:13:34 | D | - beta = [ 0.9000] +24-11-19 20:13:34 | D | - sum error = [ 127.5757] +24-11-19 20:13:34 | D | - best error = [ 127.5757] +24-11-19 20:13:34 | D | + error = 127.5757 +24-11-19 20:13:34 | D | + scale = [min=13.0305, max=34.3638] +24-11-19 20:13:41 | D | - Smoothing model.layers.21 +24-11-19 20:13:41 | D | - model.layers.21.self_attn.attn_k +24-11-19 20:13:41 | D | + w: None +24-11-19 20:13:41 | D | + x: None +24-11-19 20:13:41 | D | + y: sint8 +24-11-19 20:13:41 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:41 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:13:41 | D | + x - AbsMax +24-11-19 20:13:41 | D | + x = [min=2.5195, max=22.7344] +24-11-19 20:13:41 | D | + y - AbsMax +24-11-19 20:13:41 | D | + y = [min=3.4102, max=26.6094] +24-11-19 20:13:41 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:13:42 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:42 | D | - alpha = [ 0.5000] +24-11-19 20:13:42 | D | - beta = [ 0.0000] +24-11-19 20:13:42 | D | - sum error = [ 35.7271] +24-11-19 20:13:42 | D | - best error = [ 35.7271] +24-11-19 20:13:42 | D | + error = 35.7271 +24-11-19 20:13:42 | D | + scale = [min=1.8467, max=5.1584] +24-11-19 20:13:42 | D | - model.layers.21.mlp.down_proj +24-11-19 20:13:42 | D | + w: sint8 +24-11-19 20:13:42 | D | + x: sint8 +24-11-19 20:13:42 | D | + y: None +24-11-19 20:13:42 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:42 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:13:42 | D | + x - AbsMax +24-11-19 20:13:42 | D | + x = [min=0.3052, max=15.5156] +24-11-19 20:13:42 | D | + w - AbsMax +24-11-19 20:13:42 | D | + w = [min=0.0195, max=0.0627] +24-11-19 20:13:42 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:13:43 | D | + finished calculating the original outputs, ram usage: 13.2 +24-11-19 20:13:44 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:44 | D | - alpha = [ 0.1000] +24-11-19 20:13:44 | D | - beta = [ 0.9000] +24-11-19 20:13:44 | D | - sum error = [ 137.4341] +24-11-19 20:13:44 | D | - best error = [ 137.4341] +24-11-19 20:13:44 | D | + error = 137.4341 +24-11-19 20:13:44 | D | + scale = [min=12.9835, max=39.5089] +24-11-19 20:13:51 | D | - Smoothing model.layers.22 +24-11-19 20:13:51 | D | - model.layers.22.self_attn.attn_k +24-11-19 20:13:51 | D | + w: None +24-11-19 20:13:51 | D | + x: None +24-11-19 20:13:51 | D | + y: sint8 +24-11-19 20:13:51 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:51 | D | + finished parsing calibration arguments, ram usage: 14.4 +24-11-19 20:13:51 | D | + x - AbsMax +24-11-19 20:13:51 | D | + x = [min=2.2441, max=22.4375] +24-11-19 20:13:51 | D | + y - AbsMax +24-11-19 20:13:51 | D | + y = [min=3.7188, max=24.7969] +24-11-19 20:13:51 | D | + finished reseting calibrator, ram usage: 14.3 +24-11-19 20:13:52 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:52 | D | - alpha = [ 0.5000] +24-11-19 20:13:52 | D | - beta = [ 0.0000] +24-11-19 20:13:52 | D | - sum error = [ 27.8256] +24-11-19 20:13:52 | D | - best error = [ 27.8256] +24-11-19 20:13:52 | D | + error = 27.8256 +24-11-19 20:13:52 | D | + scale = [min=1.9284, max=4.9796] +24-11-19 20:13:52 | D | - model.layers.22.mlp.down_proj +24-11-19 20:13:52 | D | + w: sint8 +24-11-19 20:13:52 | D | + x: sint8 +24-11-19 20:13:52 | D | + y: None +24-11-19 20:13:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:13:52 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:13:52 | D | + x - AbsMax +24-11-19 20:13:52 | D | + x = [min=0.5112, max=22.6406] +24-11-19 20:13:52 | D | + w - AbsMax +24-11-19 20:13:52 | D | + w = [min=0.0236, max=0.0622] +24-11-19 20:13:52 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:13:53 | D | + finished calculating the original outputs, ram usage: 14.1 +24-11-19 20:13:54 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:13:54 | D | - alpha = [ 0.1000] +24-11-19 20:13:54 | D | - beta = [ 0.9000] +24-11-19 20:13:54 | D | - sum error = [ 141.5589] +24-11-19 20:13:54 | D | - best error = [ 141.5589] +24-11-19 20:13:54 | D | + error = 141.5589 +24-11-19 20:13:54 | D | + scale = [min=12.3456, max=33.2850] +24-11-19 20:14:00 | D | - Smoothing model.layers.23 +24-11-19 20:14:00 | D | - model.layers.23.self_attn.attn_k +24-11-19 20:14:00 | D | + w: None +24-11-19 20:14:00 | D | + x: None +24-11-19 20:14:00 | D | + y: sint8 +24-11-19 20:14:00 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:14:00 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:14:00 | D | + x - AbsMax +24-11-19 20:14:00 | D | + x = [min=2.4004, max=21.9688] +24-11-19 20:14:01 | D | + y - AbsMax +24-11-19 20:14:01 | D | + y = [min=3.2637, max=23.6719] +24-11-19 20:14:01 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:14:01 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:14:01 | D | - alpha = [ 0.5000] +24-11-19 20:14:01 | D | - beta = [ 0.0000] +24-11-19 20:14:01 | D | - sum error = [ 29.4462] +24-11-19 20:14:01 | D | - best error = [ 29.4462] +24-11-19 20:14:01 | D | + error = 29.4462 +24-11-19 20:14:01 | D | + scale = [min=1.8066, max=4.8654] +24-11-19 20:14:01 | D | - model.layers.23.mlp.down_proj +24-11-19 20:14:01 | D | + w: sint8 +24-11-19 20:14:01 | D | + x: sint8 +24-11-19 20:14:01 | D | + y: None +24-11-19 20:14:01 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:14:01 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:14:02 | D | + x - AbsMax +24-11-19 20:14:02 | D | + x = [min=0.5376, max=26.7031] +24-11-19 20:14:02 | D | + w - AbsMax +24-11-19 20:14:02 | D | + w = [min=0.0246, max=0.0598] +24-11-19 20:14:02 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:14:02 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:14:03 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:14:03 | D | - alpha = [ 0.1000] +24-11-19 20:14:03 | D | - beta = [ 0.9000] +24-11-19 20:14:03 | D | - sum error = [ 146.4231] +24-11-19 20:14:03 | D | - best error = [ 146.4231] +24-11-19 20:14:03 | D | + error = 146.4231 +24-11-19 20:14:03 | D | + scale = [min=12.8932, max=35.8750] +24-11-19 20:14:10 | D | - Smoothing model.layers.24 +24-11-19 20:14:10 | D | - model.layers.24.self_attn.attn_k +24-11-19 20:14:10 | D | + w: None +24-11-19 20:14:10 | D | + x: None +24-11-19 20:14:10 | D | + y: sint8 +24-11-19 20:14:10 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:14:10 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:14:10 | D | + x - AbsMax +24-11-19 20:14:10 | D | + x = [min=2.2500, max=25.5156] +24-11-19 20:14:10 | D | + y - AbsMax +24-11-19 20:14:10 | D | + y = [min=3.3730, max=24.4688] +24-11-19 20:14:10 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:14:11 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:14:11 | D | - alpha = [ 0.5000] +24-11-19 20:14:11 | D | - beta = [ 0.0000] +24-11-19 20:14:11 | D | - sum error = [ 29.6528] +24-11-19 20:14:11 | D | - best error = [ 29.6528] +24-11-19 20:14:11 | D | + error = 29.6528 +24-11-19 20:14:11 | D | + scale = [min=1.8366, max=4.9466] +24-11-19 20:14:11 | D | - model.layers.24.mlp.down_proj +24-11-19 20:14:11 | D | + w: sint8 +24-11-19 20:14:11 | D | + x: sint8 +24-11-19 20:14:11 | D | + y: None +24-11-19 20:14:11 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:14:11 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:14:11 | D | + x - AbsMax +24-11-19 20:14:11 | D | + x = [min=0.5640, max=26.1406] +24-11-19 20:14:11 | D | + w - AbsMax +24-11-19 20:14:11 | D | + w = [min=0.0213, max=0.0608] +24-11-19 20:14:11 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:14:12 | D | + finished calculating the original outputs, ram usage: 13.4 +24-11-19 20:14:12 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:14:12 | D | - alpha = [ 0.1000] +24-11-19 20:14:12 | D | - beta = [ 0.9000] +24-11-19 20:14:12 | D | - sum error = [ 147.9969] +24-11-19 20:14:12 | D | - best error = [ 147.9969] +24-11-19 20:14:12 | D | + error = 147.9969 +24-11-19 20:14:12 | D | + scale = [min=12.8916, max=38.6400] +24-11-19 20:14:19 | D | - Smoothing model.layers.25 +24-11-19 20:14:19 | D | - model.layers.25.self_attn.attn_k +24-11-19 20:14:19 | D | + w: None +24-11-19 20:14:19 | D | + x: None +24-11-19 20:14:19 | D | + y: sint8 +24-11-19 20:14:19 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:14:19 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:14:19 | D | + x - AbsMax +24-11-19 20:14:19 | D | + x = [min=1.5195, max=26.2656] +24-11-19 20:14:19 | D | + y - AbsMax +24-11-19 20:14:19 | D | + y = [min=2.8398, max=25.7812] +24-11-19 20:14:19 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:14:20 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:14:20 | D | - alpha = [ 0.5000] +24-11-19 20:14:20 | D | - beta = [ 0.0000] +24-11-19 20:14:20 | D | - sum error = [ 43.2213] +24-11-19 20:14:20 | D | - best error = [ 43.2213] +24-11-19 20:14:20 | D | + error = 43.2213 +24-11-19 20:14:20 | D | + scale = [min=1.6852, max=5.0775] +24-11-19 20:14:20 | D | - model.layers.25.mlp.down_proj +24-11-19 20:14:20 | D | + w: sint8 +24-11-19 20:14:20 | D | + x: sint8 +24-11-19 20:14:20 | D | + y: None +24-11-19 20:14:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:14:20 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:14:21 | D | + x - AbsMax +24-11-19 20:14:21 | D | + x = [min=0.6274, max=28.4531] +24-11-19 20:14:21 | D | + w - AbsMax +24-11-19 20:14:21 | D | + w = [min=0.0220, max=0.0608] +24-11-19 20:14:21 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:14:21 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:14:22 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:14:22 | D | - alpha = [ 0.1000] +24-11-19 20:14:22 | D | - beta = [ 0.9000] +24-11-19 20:14:22 | D | - sum error = [ 153.9525] +24-11-19 20:14:22 | D | - best error = [ 153.9525] +24-11-19 20:14:22 | D | + error = 153.9525 +24-11-19 20:14:22 | D | + scale = [min=12.8830, max=36.9735] +24-11-19 20:14:29 | D | - Smoothing model.layers.26 +24-11-19 20:14:29 | D | - model.layers.26.self_attn.attn_k +24-11-19 20:14:29 | D | + w: None +24-11-19 20:14:29 | D | + x: None +24-11-19 20:14:29 | D | + y: sint8 +24-11-19 20:14:29 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:14:29 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:14:29 | D | + x - AbsMax +24-11-19 20:14:29 | D | + x = [min=1.6602, max=24.8750] +24-11-19 20:14:29 | D | + y - AbsMax +24-11-19 20:14:29 | D | + y = [min=2.8652, max=25.5156] +24-11-19 20:14:29 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:14:30 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:14:30 | D | - alpha = [ 0.5000] +24-11-19 20:14:30 | D | - beta = [ 0.0000] +24-11-19 20:14:30 | D | - sum error = [ 36.3745] +24-11-19 20:14:30 | D | - best error = [ 36.3745] +24-11-19 20:14:30 | D | + error = 36.3745 +24-11-19 20:14:30 | D | + scale = [min=1.6927, max=5.0513] +24-11-19 20:14:30 | D | - model.layers.26.mlp.down_proj +24-11-19 20:14:30 | D | + w: sint8 +24-11-19 20:14:30 | D | + x: sint8 +24-11-19 20:14:30 | D | + y: None +24-11-19 20:14:30 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:14:30 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:14:30 | D | + x - AbsMax +24-11-19 20:14:30 | D | + x = [min=0.4875, max=25.5625] +24-11-19 20:14:30 | D | + w - AbsMax +24-11-19 20:14:30 | D | + w = [min=0.0241, max=0.0614] +24-11-19 20:14:30 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:14:31 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:14:31 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:14:31 | D | - alpha = [ 0.1000] +24-11-19 20:14:31 | D | - beta = [ 0.9000] +24-11-19 20:14:31 | D | - sum error = [ 170.4323] +24-11-19 20:14:31 | D | - best error = [ 170.4323] +24-11-19 20:14:31 | D | + error = 170.4323 +24-11-19 20:14:31 | D | + scale = [min=12.2873, max=33.8018] +24-11-19 20:14:39 | D | - Smoothing model.layers.27 +24-11-19 20:14:39 | D | - model.layers.27.self_attn.attn_k +24-11-19 20:14:39 | D | + w: None +24-11-19 20:14:39 | D | + x: None +24-11-19 20:14:39 | D | + y: sint8 +24-11-19 20:14:39 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:14:39 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:14:39 | D | + x - AbsMax +24-11-19 20:14:39 | D | + x = [min=2.0391, max=24.8750] +24-11-19 20:14:39 | D | + y - AbsMax +24-11-19 20:14:39 | D | + y = [min=2.9277, max=23.4844] +24-11-19 20:14:39 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:14:39 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:14:39 | D | - alpha = [ 0.5000] +24-11-19 20:14:39 | D | - beta = [ 0.0000] +24-11-19 20:14:39 | D | - sum error = [ 41.1900] +24-11-19 20:14:39 | D | - best error = [ 41.1900] +24-11-19 20:14:39 | D | + error = 41.1900 +24-11-19 20:14:39 | D | + scale = [min=1.7111, max=4.8461] +24-11-19 20:14:39 | D | - model.layers.27.mlp.down_proj +24-11-19 20:14:39 | D | + w: sint8 +24-11-19 20:14:39 | D | + x: sint8 +24-11-19 20:14:39 | D | + y: None +24-11-19 20:14:39 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:14:39 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:14:40 | D | + x - AbsMax +24-11-19 20:14:40 | D | + x = [min=0.5415, max=35.8125] +24-11-19 20:14:40 | D | + w - AbsMax +24-11-19 20:14:40 | D | + w = [min=0.0231, max=0.0642] +24-11-19 20:14:40 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:14:40 | D | + finished calculating the original outputs, ram usage: 13.4 +24-11-19 20:14:41 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:14:41 | D | - alpha = [ 0.1000] +24-11-19 20:14:41 | D | - beta = [ 0.9000] +24-11-19 20:14:41 | D | - sum error = [ 212.9667] +24-11-19 20:14:41 | D | - best error = [ 212.9667] +24-11-19 20:14:41 | D | + error = 212.9667 +24-11-19 20:14:41 | D | + scale = [min=12.3469, max=37.1673] +24-11-19 20:14:48 | D | - Smoothing model.layers.28 +24-11-19 20:14:48 | D | - model.layers.28.self_attn.attn_k +24-11-19 20:14:48 | D | + w: None +24-11-19 20:14:48 | D | + x: None +24-11-19 20:14:48 | D | + y: sint8 +24-11-19 20:14:48 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:14:48 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:14:48 | D | + x - AbsMax +24-11-19 20:14:48 | D | + x = [min=2.9023, max=21.4062] +24-11-19 20:14:48 | D | + y - AbsMax +24-11-19 20:14:48 | D | + y = [min=3.2109, max=25.6094] +24-11-19 20:14:48 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:14:49 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:14:49 | D | - alpha = [ 0.5000] +24-11-19 20:14:49 | D | - beta = [ 0.0000] +24-11-19 20:14:49 | D | - sum error = [ 52.4741] +24-11-19 20:14:49 | D | - best error = [ 52.4741] +24-11-19 20:14:49 | D | + error = 52.4741 +24-11-19 20:14:49 | D | + scale = [min=1.7919, max=5.0606] +24-11-19 20:14:49 | D | - model.layers.28.mlp.down_proj +24-11-19 20:14:49 | D | + w: sint8 +24-11-19 20:14:49 | D | + x: sint8 +24-11-19 20:14:49 | D | + y: None +24-11-19 20:14:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:14:49 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:14:50 | D | + x - AbsMax +24-11-19 20:14:50 | D | + x = [min=0.7109, max=24.2500] +24-11-19 20:14:50 | D | + w - AbsMax +24-11-19 20:14:50 | D | + w = [min=0.0157, max=0.0743] +24-11-19 20:14:50 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:14:50 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:14:51 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:14:51 | D | - alpha = [ 0.1000] +24-11-19 20:14:51 | D | - beta = [ 0.9000] +24-11-19 20:14:51 | D | - sum error = [ 213.8311] +24-11-19 20:14:51 | D | - best error = [ 213.8311] +24-11-19 20:14:51 | D | + error = 213.8311 +24-11-19 20:14:51 | D | + scale = [min=11.6829, max=51.0850] +24-11-19 20:14:58 | D | - Smoothing model.layers.29 +24-11-19 20:14:58 | D | - model.layers.29.self_attn.attn_k +24-11-19 20:14:58 | D | + w: None +24-11-19 20:14:58 | D | + x: None +24-11-19 20:14:58 | D | + y: sint8 +24-11-19 20:14:58 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:14:58 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:14:58 | D | + x - AbsMax +24-11-19 20:14:58 | D | + x = [min=2.5352, max=18.3125] +24-11-19 20:14:58 | D | + y - AbsMax +24-11-19 20:14:58 | D | + y = [min=2.8203, max=41.7812] +24-11-19 20:14:58 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:14:59 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:14:59 | D | - alpha = [ 0.5000] +24-11-19 20:14:59 | D | - beta = [ 0.0000] +24-11-19 20:14:59 | D | - sum error = [ 72.9680] +24-11-19 20:14:59 | D | - best error = [ 72.9680] +24-11-19 20:14:59 | D | + error = 72.9680 +24-11-19 20:14:59 | D | + scale = [min=1.6794, max=6.4638] +24-11-19 20:14:59 | D | - model.layers.29.mlp.down_proj +24-11-19 20:14:59 | D | + w: sint8 +24-11-19 20:14:59 | D | + x: sint8 +24-11-19 20:14:59 | D | + y: None +24-11-19 20:14:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:14:59 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:14:59 | D | + x - AbsMax +24-11-19 20:14:59 | D | + x = [min=0.7856, max=37.7188] +24-11-19 20:14:59 | D | + w - AbsMax +24-11-19 20:14:59 | D | + w = [min=0.0205, max=0.1085] +24-11-19 20:14:59 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:15:00 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:15:00 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:15:00 | D | - alpha = [ 0.1000] +24-11-19 20:15:00 | D | - beta = [ 0.9000] +24-11-19 20:15:00 | D | - sum error = [ 252.0521] +24-11-19 20:15:00 | D | - best error = [ 252.0521] +24-11-19 20:15:00 | D | + error = 252.0521 +24-11-19 20:15:00 | D | + scale = [min=9.6607, max=44.3968] +24-11-19 20:15:07 | D | - Smoothing model.layers.30 +24-11-19 20:15:07 | D | - model.layers.30.self_attn.attn_k +24-11-19 20:15:07 | D | + w: None +24-11-19 20:15:07 | D | + x: None +24-11-19 20:15:07 | D | + y: sint8 +24-11-19 20:15:07 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:15:07 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:15:07 | D | + x - AbsMax +24-11-19 20:15:07 | D | + x = [min=2.7656, max=21.4531] +24-11-19 20:15:07 | D | + y - AbsMax +24-11-19 20:15:07 | D | + y = [min=2.6582, max=24.0781] +24-11-19 20:15:07 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:15:08 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:15:08 | D | - alpha = [ 0.5000] +24-11-19 20:15:08 | D | - beta = [ 0.0000] +24-11-19 20:15:08 | D | - sum error = [ 72.0842] +24-11-19 20:15:08 | D | - best error = [ 72.0842] +24-11-19 20:15:08 | D | + error = 72.0842 +24-11-19 20:15:08 | D | + scale = [min=1.6304, max=4.9069] +24-11-19 20:15:08 | D | - model.layers.30.mlp.down_proj +24-11-19 20:15:08 | D | + w: sint8 +24-11-19 20:15:08 | D | + x: sint8 +24-11-19 20:15:08 | D | + y: None +24-11-19 20:15:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:15:08 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:15:08 | D | + x - AbsMax +24-11-19 20:15:08 | D | + x = [min=0.9536, max=101.6875] +24-11-19 20:15:08 | D | + w - AbsMax +24-11-19 20:15:08 | D | + w = [min=0.0176, max=0.1025] +24-11-19 20:15:08 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:15:09 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:15:09 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:15:09 | D | - alpha = [ 0.1000] +24-11-19 20:15:09 | D | - beta = [ 0.9000] +24-11-19 20:15:09 | D | - sum error = [ 346.6661] +24-11-19 20:15:09 | D | - best error = [ 346.6661] +24-11-19 20:15:09 | D | + error = 346.6661 +24-11-19 20:15:09 | D | + scale = [min=10.1812, max=51.4830] +24-11-19 20:15:16 | D | - Smoothing model.layers.31 +24-11-19 20:15:16 | D | - model.layers.31.self_attn.attn_k +24-11-19 20:15:16 | D | + w: None +24-11-19 20:15:16 | D | + x: None +24-11-19 20:15:16 | D | + y: sint8 +24-11-19 20:15:16 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:15:16 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:15:17 | D | + x - AbsMax +24-11-19 20:15:17 | D | + x = [min=2.5547, max=34.0000] +24-11-19 20:15:17 | D | + y - AbsMax +24-11-19 20:15:17 | D | + y = [min=3.4902, max=25.7031] +24-11-19 20:15:17 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:15:17 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:15:17 | D | - alpha = [ 0.5000] +24-11-19 20:15:17 | D | - beta = [ 0.0000] +24-11-19 20:15:17 | D | - sum error = [ 92.1100] +24-11-19 20:15:17 | D | - best error = [ 92.1100] +24-11-19 20:15:17 | D | + error = 92.1100 +24-11-19 20:15:17 | D | + scale = [min=1.8682, max=5.0698] +24-11-19 20:15:17 | D | - model.layers.31.mlp.down_proj +24-11-19 20:15:17 | D | + w: sint8 +24-11-19 20:15:17 | D | + x: sint8 +24-11-19 20:15:17 | D | + y: None +24-11-19 20:15:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:15:17 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:15:18 | D | + x - AbsMax +24-11-19 20:15:18 | D | + x = [min=0.5498, max=2364.0000] +24-11-19 20:15:18 | D | + w - AbsMax +24-11-19 20:15:18 | D | + w = [min=0.0141, max=0.1208] +24-11-19 20:15:18 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:15:18 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:15:19 | D | - x / w range = AbsMax / AbsMax +24-11-19 20:15:19 | D | - alpha = [ 0.1000] +24-11-19 20:15:19 | D | - beta = [ 0.9000] +24-11-19 20:15:19 | D | - sum error = [ 649.7231] +24-11-19 20:15:19 | D | - best error = [ 649.7231] +24-11-19 20:15:19 | D | + error = 649.7231 +24-11-19 20:15:19 | D | + scale = [min=6.9020, max=69.1396] +24-11-19 20:15:20 | I | - Saving smooth scales to runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/smooth/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.proj.OutputsError.Manual.Layer.d2.en1.sn1-attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.proj.[a.AbsMax.b.AbsMax]-attn.[a.AbsMax.b.AbsMax]/smooth.proj.a0p1.b0p9-attn.a0p5.b0/smooth.proj.skip.[out_proj+qkv_proj+up_proj]/llama-3-8b-instruct-gradient-1048k.pt +24-11-19 20:15:20 | I | - Linking smooth scales to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.proj.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.proj.a0p1.b0p9.[AbsMax].[fc2].attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200844.RUNNING/model/smooth.pt +24-11-19 20:15:20 | I | * Quantizing weights +24-11-19 20:15:20 | I | - Generating weight quantizer settings +24-11-19 20:15:20 | D | Starting new HTTPS connection (4): huggingface.co:443 +24-11-19 20:15:36 | D | Starting new HTTPS connection (5): huggingface.co:443 +24-11-19 20:15:52 | D | Starting new HTTPS connection (2): s3.amazonaws.com:443 +24-11-19 20:16:13 | W | Repo card metadata block was not found. Setting CardData to empty. +24-11-19 20:16:13 | D | Starting new HTTPS connection (6): huggingface.co:443 +24-11-19 20:16:31 | W | Using the latest cached version of the dataset since mit-han-lab/pile-val-backup couldn't be found on the Hugging Face Hub +24-11-19 20:16:31 | W | Found the latest cached dataset configuration 'default' at /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4 (last modified on Tue Oct 8 18:58:39 2024). +24-11-19 20:16:31 | D | Attempting to acquire lock 23438703524416 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:16:31 | D | Lock 23438703524416 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:16:31 | D | open file: /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4/dataset_info.json +24-11-19 20:16:31 | D | Attempting to release lock 23438703524416 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:16:31 | D | Lock 23438703524416 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:16:56 | D | - Quantizing layer model.layers.0 +24-11-19 20:16:56 | D | - Calibrating model.layers.0.self_attn.q_proj.weight +24-11-19 20:16:56 | D | + w: sint8 +24-11-19 20:16:56 | D | + x: None +24-11-19 20:16:56 | D | + y: None +24-11-19 20:16:56 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:16:56 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:16:56 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:16:56 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:16:56 | D | - range ratio = [ 1.0000] +24-11-19 20:16:56 | D | sum error = [ 0.1818] +24-11-19 20:16:56 | D | best error = [ 0.1818] +24-11-19 20:17:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:08 | D | sum error = [ 0.1862, 0.1834, 0.1933, 0.1903, 0.1964] +24-11-19 20:17:08 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:17:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:08 | D | sum error = [ 0.2075, 0.2202, 0.2260, 0.2481, 0.2600] +24-11-19 20:17:08 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:17:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:08 | D | sum error = [ 0.2845, 0.3135, 0.3310, 0.3717, 0.4073] +24-11-19 20:17:08 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:17:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:08 | D | sum error = [ 0.4469, 0.4925, 0.5352, 0.6000, 0.6564] +24-11-19 20:17:08 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:17:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:08 | D | sum error = [ 0.7285, 0.8037, 0.8810, 0.9639, 1.0532] +24-11-19 20:17:08 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:17:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:08 | D | sum error = [ 1.1548, 1.2637, 1.3807, 1.5182, 1.6574] +24-11-19 20:17:08 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:17:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:08 | D | sum error = [ 1.8244, 1.9919, 2.1868, 2.3910, 2.6134] +24-11-19 20:17:08 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:17:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:08 | D | sum error = [ 2.8529, 3.1085, 3.3841, 3.6950, 4.0164] +24-11-19 20:17:08 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:17:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:08 | D | sum error = [ 4.3799, 4.7601, 5.1673, 5.6166, 6.0977] +24-11-19 20:17:08 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:17:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:08 | D | sum error = [ 6.6171, 7.1735, 7.7714, 8.4094, 9.1165] +24-11-19 20:17:08 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:17:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:08 | D | sum error = [ 9.8615, 10.6515, 11.5167, 12.4299, 13.4183] +24-11-19 20:17:08 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:17:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:08 | D | sum error = [ 14.4722, 15.5939, 16.7929, 18.0823, 19.4521] +24-11-19 20:17:08 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:17:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:08 | D | sum error = [ 20.9099, 22.4552, 24.1043, 25.8565, 27.7222] +24-11-19 20:17:08 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:17:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:08 | D | sum error = [ 29.7028, 31.8024, 34.0330, 36.3976, 38.8938] +24-11-19 20:17:08 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:17:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:08 | D | sum error = [ 41.5371, 44.3233, 47.2564, 50.3541, 53.5983] +24-11-19 20:17:08 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:17:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:08 | D | sum error = [ 57.0034, 60.5521, 64.2432, 68.0593, 72.0273] +24-11-19 20:17:08 | D | best error = [ 0.1818, 0.1818, 0.1818, 0.1818, 0.1818] +24-11-19 20:17:08 | D | + error = [0.1818] +24-11-19 20:17:08 | D | - Calibrating model.layers.0.self_attn.k_proj.weight +24-11-19 20:17:08 | D | + w: sint8 +24-11-19 20:17:08 | D | + x: None +24-11-19 20:17:08 | D | + y: None +24-11-19 20:17:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:17:08 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:17:08 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:17:09 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:17:09 | D | - range ratio = [ 1.0000] +24-11-19 20:17:09 | D | sum error = [ 0.2610] +24-11-19 20:17:09 | D | best error = [ 0.2610] +24-11-19 20:17:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:20 | D | sum error = [ 0.2527, 0.2527, 0.2593, 0.2672, 0.2687] +24-11-19 20:17:20 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:17:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:20 | D | sum error = [ 0.2629, 0.2841, 0.2897, 0.3170, 0.3270] +24-11-19 20:17:20 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:17:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:20 | D | sum error = [ 0.3463, 0.3707, 0.3977, 0.4353, 0.4669] +24-11-19 20:17:20 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:17:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:20 | D | sum error = [ 0.4979, 0.5421, 0.5783, 0.6215, 0.6825] +24-11-19 20:17:20 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:17:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:20 | D | sum error = [ 0.7390, 0.8081, 0.8727, 0.9415, 1.0085] +24-11-19 20:17:20 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:17:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:20 | D | sum error = [ 1.0981, 1.1878, 1.2934, 1.3954, 1.5227] +24-11-19 20:17:20 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:17:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:20 | D | sum error = [ 1.6478, 1.7870, 1.9563, 2.1100, 2.2874] +24-11-19 20:17:20 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:17:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:20 | D | sum error = [ 2.4847, 2.7054, 2.9378, 3.1862, 3.4787] +24-11-19 20:17:20 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:17:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:20 | D | sum error = [ 3.7706, 4.1027, 4.4550, 4.8394, 5.2635] +24-11-19 20:17:20 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:17:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:20 | D | sum error = [ 5.7166, 6.1996, 6.7284, 7.3047, 7.9279] +24-11-19 20:17:20 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:17:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:20 | D | sum error = [ 8.5921, 9.3047, 10.0871, 10.9268, 11.8338] +24-11-19 20:17:20 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:17:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:20 | D | sum error = [ 12.8018, 13.8315, 14.9640, 16.1545, 17.4531] +24-11-19 20:17:20 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:17:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:20 | D | sum error = [ 18.8485, 20.3267, 21.9163, 23.6371, 25.4693] +24-11-19 20:17:20 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:17:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:20 | D | sum error = [ 27.4219, 29.4933, 31.7215, 34.0708, 36.5831] +24-11-19 20:17:20 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:17:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:20 | D | sum error = [ 39.2514, 42.0872, 45.0593, 48.2143, 51.5417] +24-11-19 20:17:20 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:17:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:20 | D | sum error = [ 55.0357, 58.6948, 62.5208, 66.4986, 70.6701] +24-11-19 20:17:20 | D | best error = [ 0.2527, 0.2527, 0.2527, 0.2527, 0.2527] +24-11-19 20:17:20 | D | + error = [0.2527] +24-11-19 20:17:21 | D | - Calibrating model.layers.0.self_attn.v_proj.weight +24-11-19 20:17:21 | D | + w: sint8 +24-11-19 20:17:21 | D | + x: None +24-11-19 20:17:21 | D | + y: None +24-11-19 20:17:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:17:21 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:17:21 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:17:21 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:17:21 | D | - range ratio = [ 1.0000] +24-11-19 20:17:21 | D | sum error = [ 0.2193] +24-11-19 20:17:21 | D | best error = [ 0.2193] +24-11-19 20:17:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:21 | D | sum error = [ 0.2178, 0.2165, 0.2172, 0.2209, 0.2241] +24-11-19 20:17:21 | D | best error = [ 0.2060, 0.2008, 0.1982, 0.1969, 0.1960] +24-11-19 20:17:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:21 | D | sum error = [ 0.2293, 0.2382, 0.2481, 0.2593, 0.2738] +24-11-19 20:17:21 | D | best error = [ 0.1956, 0.1954, 0.1954, 0.1953, 0.1953] +24-11-19 20:17:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:21 | D | sum error = [ 0.2899, 0.3096, 0.3280, 0.3501, 0.3750] +24-11-19 20:17:21 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:17:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:21 | D | sum error = [ 0.4020, 0.4313, 0.4606, 0.4962, 0.5293] +24-11-19 20:17:21 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:17:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:21 | D | sum error = [ 0.5675, 0.6087, 0.6506, 0.6965, 0.7455] +24-11-19 20:17:21 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:17:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:21 | D | sum error = [ 0.7961, 0.8488, 0.9054, 0.9655, 1.0301] +24-11-19 20:17:21 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:17:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:21 | D | sum error = [ 1.0968, 1.1670, 1.2410, 1.3205, 1.4035] +24-11-19 20:17:21 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:17:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:21 | D | sum error = [ 1.4913, 1.5827, 1.6815, 1.7853, 1.8956] +24-11-19 20:17:21 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:17:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:21 | D | sum error = [ 2.0087, 2.1281, 2.2525, 2.3848, 2.5248] +24-11-19 20:17:21 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:17:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:21 | D | sum error = [ 2.6681, 2.8214, 2.9810, 3.1454, 3.3203] +24-11-19 20:17:21 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:17:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:21 | D | sum error = [ 3.5019, 3.6937, 3.8935, 4.1018, 4.3188] +24-11-19 20:17:21 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:17:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:21 | D | sum error = [ 4.5428, 4.7796, 5.0255, 5.2814, 5.5463] +24-11-19 20:17:21 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:17:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:21 | D | sum error = [ 5.8234, 6.1121, 6.4115, 6.7200, 7.0420] +24-11-19 20:17:21 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:17:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:21 | D | sum error = [ 7.3753, 7.7223, 8.0823, 8.4551, 8.8431] +24-11-19 20:17:21 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:17:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:21 | D | sum error = [ 9.2382, 9.6566, 10.0822, 10.5254, 10.9777] +24-11-19 20:17:21 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:17:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:21 | D | sum error = [ 11.4473, 11.9355, 12.4371, 12.9462, 13.4751] +24-11-19 20:17:21 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:17:21 | D | + error = [0.1953] +24-11-19 20:17:21 | D | - Calibrating model.layers.0.self_attn.o_proj.weight +24-11-19 20:17:21 | D | + w: sint8 +24-11-19 20:17:21 | D | + x: None +24-11-19 20:17:21 | D | + y: None +24-11-19 20:17:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:17:21 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:17:21 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:17:21 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:17:21 | D | - range ratio = [ 1.0000] +24-11-19 20:17:21 | D | sum error = [ 0.1014] +24-11-19 20:17:21 | D | best error = [ 0.1014] +24-11-19 20:17:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:22 | D | sum error = [ 0.1011, 0.1008, 0.1004, 0.1013, 0.1026] +24-11-19 20:17:22 | D | best error = [ 0.0902, 0.0859, 0.0834, 0.0820, 0.0811] +24-11-19 20:17:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:22 | D | sum error = [ 0.1056, 0.1081, 0.1115, 0.1154, 0.1205] +24-11-19 20:17:22 | D | best error = [ 0.0806, 0.0803, 0.0801, 0.0799, 0.0798] +24-11-19 20:17:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:22 | D | sum error = [ 0.1252, 0.1319, 0.1386, 0.1464, 0.1553] +24-11-19 20:17:22 | D | best error = [ 0.0798, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:17:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:22 | D | sum error = [ 0.1643, 0.1749, 0.1848, 0.1957, 0.2081] +24-11-19 20:17:22 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:17:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:22 | D | sum error = [ 0.2214, 0.2347, 0.2486, 0.2639, 0.2793] +24-11-19 20:17:22 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:17:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:22 | D | sum error = [ 0.2963, 0.3145, 0.3331, 0.3528, 0.3731] +24-11-19 20:17:22 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:17:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:22 | D | sum error = [ 0.3947, 0.4176, 0.4414, 0.4663, 0.4933] +24-11-19 20:17:22 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:17:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:22 | D | sum error = [ 0.5207, 0.5495, 0.5802, 0.6122, 0.6453] +24-11-19 20:17:22 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:17:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:22 | D | sum error = [ 0.6803, 0.7163, 0.7551, 0.7950, 0.8371] +24-11-19 20:17:22 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:17:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:22 | D | sum error = [ 0.8808, 0.9269, 0.9751, 1.0255, 1.0783] +24-11-19 20:17:22 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:17:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:22 | D | sum error = [ 1.1342, 1.1924, 1.2527, 1.3168, 1.3838] +24-11-19 20:17:22 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:17:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:22 | D | sum error = [ 1.4544, 1.5281, 1.6059, 1.6874, 1.7732] +24-11-19 20:17:22 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:17:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:22 | D | sum error = [ 1.8639, 1.9588, 2.0590, 2.1650, 2.2763] +24-11-19 20:17:22 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:17:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:22 | D | sum error = [ 2.3937, 2.5177, 2.6487, 2.7875, 2.9339] +24-11-19 20:17:22 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:17:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:22 | D | sum error = [ 3.0887, 3.2524, 3.4251, 3.6073, 3.7999] +24-11-19 20:17:22 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:17:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:22 | D | sum error = [ 4.0032, 4.2180, 4.4442, 4.6817, 4.9316] +24-11-19 20:17:22 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:17:22 | D | + error = [0.0797] +24-11-19 20:17:22 | D | - Calibrating model.layers.0.mlp.up_proj.weight +24-11-19 20:17:22 | D | + w: sint8 +24-11-19 20:17:22 | D | + x: None +24-11-19 20:17:22 | D | + y: None +24-11-19 20:17:22 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:17:22 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:17:22 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:17:22 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:17:22 | D | - range ratio = [ 1.0000] +24-11-19 20:17:22 | D | sum error = [ 0.1419] +24-11-19 20:17:22 | D | best error = [ 0.1419] +24-11-19 20:17:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:23 | D | sum error = [ 0.1409, 0.1409, 0.1412, 0.1432, 0.1459] +24-11-19 20:17:23 | D | best error = [ 0.1320, 0.1235, 0.1197, 0.1174, 0.1161] +24-11-19 20:17:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:23 | D | sum error = [ 0.1497, 0.1546, 0.1607, 0.1676, 0.1772] +24-11-19 20:17:23 | D | best error = [ 0.1155, 0.1152, 0.1150, 0.1149, 0.1149] +24-11-19 20:17:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:23 | D | sum error = [ 0.1880, 0.1997, 0.2124, 0.2256, 0.2416] +24-11-19 20:17:23 | D | best error = [ 0.1149, 0.1149, 0.1149, 0.1149, 0.1149] +24-11-19 20:17:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:23 | D | sum error = [ 0.2590, 0.2769, 0.2972, 0.3188, 0.3414] +24-11-19 20:17:23 | D | best error = [ 0.1149, 0.1149, 0.1149, 0.1149, 0.1149] +24-11-19 20:17:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:23 | D | sum error = [ 0.3653, 0.3914, 0.4195, 0.4489, 0.4792] +24-11-19 20:17:23 | D | best error = [ 0.1149, 0.1149, 0.1149, 0.1149, 0.1149] +24-11-19 20:17:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:23 | D | sum error = [ 0.5116, 0.5462, 0.5827, 0.6211, 0.6619] +24-11-19 20:17:23 | D | best error = [ 0.1149, 0.1149, 0.1149, 0.1149, 0.1149] +24-11-19 20:17:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:23 | D | sum error = [ 0.7050, 0.7503, 0.7982, 0.8477, 0.9015] +24-11-19 20:17:23 | D | best error = [ 0.1149, 0.1149, 0.1149, 0.1149, 0.1149] +24-11-19 20:17:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:23 | D | sum error = [ 0.9575, 1.0163, 1.0784, 1.1422, 1.2111] +24-11-19 20:17:23 | D | best error = [ 0.1149, 0.1149, 0.1149, 0.1149, 0.1149] +24-11-19 20:17:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:23 | D | sum error = [ 1.2820, 1.3574, 1.4362, 1.5181, 1.6042] +24-11-19 20:17:23 | D | best error = [ 0.1149, 0.1149, 0.1149, 0.1149, 0.1149] +24-11-19 20:17:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:23 | D | sum error = [ 1.6951, 1.7883, 1.8884, 1.9889, 2.0985] +24-11-19 20:17:23 | D | best error = [ 0.1149, 0.1149, 0.1149, 0.1149, 0.1149] +24-11-19 20:17:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:23 | D | sum error = [ 2.2093, 2.3283, 2.4472, 2.5752, 2.7074] +24-11-19 20:17:23 | D | best error = [ 0.1149, 0.1149, 0.1149, 0.1149, 0.1149] +24-11-19 20:17:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:23 | D | sum error = [ 2.8472, 2.9896, 3.1389, 3.2935, 3.4533] +24-11-19 20:17:23 | D | best error = [ 0.1149, 0.1149, 0.1149, 0.1149, 0.1149] +24-11-19 20:17:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:23 | D | sum error = [ 3.6216, 3.7928, 3.9725, 4.1547, 4.3485] +24-11-19 20:17:23 | D | best error = [ 0.1149, 0.1149, 0.1149, 0.1149, 0.1149] +24-11-19 20:17:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:23 | D | sum error = [ 4.5460, 4.7537, 4.9626, 5.1827, 5.4095] +24-11-19 20:17:23 | D | best error = [ 0.1149, 0.1149, 0.1149, 0.1149, 0.1149] +24-11-19 20:17:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:23 | D | sum error = [ 5.6452, 5.8868, 6.1349, 6.3946, 6.6590] +24-11-19 20:17:23 | D | best error = [ 0.1149, 0.1149, 0.1149, 0.1149, 0.1149] +24-11-19 20:17:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:23 | D | sum error = [ 6.9308, 7.2137, 7.5015, 7.8039, 8.1093] +24-11-19 20:17:23 | D | best error = [ 0.1149, 0.1149, 0.1149, 0.1149, 0.1149] +24-11-19 20:17:23 | D | + error = [0.1149] +24-11-19 20:17:23 | D | - Calibrating model.layers.0.mlp.gate_proj.weight +24-11-19 20:17:23 | D | + w: sint8 +24-11-19 20:17:23 | D | + x: None +24-11-19 20:17:23 | D | + y: None +24-11-19 20:17:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:17:23 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:17:24 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:17:24 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:17:24 | D | - range ratio = [ 1.0000] +24-11-19 20:17:24 | D | sum error = [ 2.4924] +24-11-19 20:17:24 | D | best error = [ 2.4924] +24-11-19 20:17:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:25 | D | sum error = [ 2.4686, 2.4669, 2.4705, 2.5084, 2.5608] +24-11-19 20:17:25 | D | best error = [ 2.1585, 2.0455, 1.9930, 1.9666, 1.9525] +24-11-19 20:17:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:25 | D | sum error = [ 2.6193, 2.7142, 2.8166, 2.9523, 3.1187] +24-11-19 20:17:25 | D | best error = [ 1.9451, 1.9417, 1.9406, 1.9400, 1.9399] +24-11-19 20:17:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:25 | D | sum error = [ 3.3007, 3.5003, 3.7488, 3.9832, 4.2777] +24-11-19 20:17:25 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:17:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:25 | D | sum error = [ 4.5814, 4.9088, 5.2640, 5.6560, 6.0629] +24-11-19 20:17:25 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:17:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:25 | D | sum error = [ 6.4869, 6.9653, 7.4492, 7.9751, 8.5344] +24-11-19 20:17:25 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:17:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:25 | D | sum error = [ 9.1347, 9.7686, 10.4226, 11.1435, 11.8855] +24-11-19 20:17:25 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:17:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:25 | D | sum error = [ 12.6732, 13.5071, 14.3957, 15.3216, 16.3075] +24-11-19 20:17:25 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:17:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:25 | D | sum error = [ 17.3394, 18.4393, 19.5982, 20.8128, 22.1063] +24-11-19 20:17:25 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:17:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:25 | D | sum error = [ 23.4631, 24.9015, 26.4145, 27.9974, 29.6842] +24-11-19 20:17:25 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:17:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:25 | D | sum error = [ 31.4595, 33.3231, 35.2821, 37.3383, 39.4905] +24-11-19 20:17:25 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:17:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:25 | D | sum error = [ 41.7524, 44.1281, 46.6129, 49.2286, 51.9738] +24-11-19 20:17:25 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:17:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:25 | D | sum error = [ 54.8395, 57.8361, 60.9742, 64.2671, 67.6999] +24-11-19 20:17:25 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:17:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:25 | D | sum error = [ 71.2954, 75.0445, 78.9600, 83.0353, 87.2868] +24-11-19 20:17:25 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:17:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:25 | D | sum error = [ 91.6987, 96.2940, 101.0753, 106.0368, 111.1842] +24-11-19 20:17:25 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:17:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:25 | D | sum error = [ 116.5355, 122.0654, 127.7924, 133.7300, 139.8649] +24-11-19 20:17:25 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:17:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:25 | D | sum error = [ 146.2091, 152.7502, 159.5064, 166.4504, 173.5986] +24-11-19 20:17:25 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:17:25 | D | + error = [1.9398] +24-11-19 20:17:25 | D | - Calibrating model.layers.0.mlp.down_proj.weight +24-11-19 20:17:25 | D | + w: sint8 +24-11-19 20:17:25 | D | + x: None +24-11-19 20:17:25 | D | + y: None +24-11-19 20:17:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:17:25 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:17:25 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:17:25 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:17:25 | D | - range ratio = [ 1.0000] +24-11-19 20:17:25 | D | sum error = [ 0.1589] +24-11-19 20:17:25 | D | best error = [ 0.1589] +24-11-19 20:17:27 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:27 | D | sum error = [ 0.1584, 0.1618, 0.1692, 0.1795, 0.1921] +24-11-19 20:17:27 | D | best error = [ 0.1453, 0.1395, 0.1358, 0.1334, 0.1316] +24-11-19 20:17:27 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:27 | D | sum error = [ 0.2100, 0.2292, 0.2527, 0.2782, 0.3043] +24-11-19 20:17:27 | D | best error = [ 0.1301, 0.1288, 0.1277, 0.1269, 0.1263] +24-11-19 20:17:27 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:27 | D | sum error = [ 0.3341, 0.3669, 0.3993, 0.4354, 0.4728] +24-11-19 20:17:27 | D | best error = [ 0.1257, 0.1254, 0.1251, 0.1249, 0.1248] +24-11-19 20:17:27 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:27 | D | sum error = [ 0.5119, 0.5535, 0.5981, 0.6443, 0.6928] +24-11-19 20:17:27 | D | best error = [ 0.1248, 0.1247, 0.1247, 0.1247, 0.1247] +24-11-19 20:17:27 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:27 | D | sum error = [ 0.7455, 0.7975, 0.8549, 0.9136, 0.9763] +24-11-19 20:17:27 | D | best error = [ 0.1247, 0.1247, 0.1247, 0.1247, 0.1247] +24-11-19 20:17:27 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:27 | D | sum error = [ 1.0399, 1.1084, 1.1793, 1.2543, 1.3323] +24-11-19 20:17:27 | D | best error = [ 0.1247, 0.1247, 0.1247, 0.1247, 0.1247] +24-11-19 20:17:27 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:27 | D | sum error = [ 1.4139, 1.5007, 1.5899, 1.6844, 1.7840] +24-11-19 20:17:27 | D | best error = [ 0.1247, 0.1247, 0.1247, 0.1247, 0.1247] +24-11-19 20:17:27 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:27 | D | sum error = [ 1.8870, 1.9955, 2.1087, 2.2279, 2.3518] +24-11-19 20:17:27 | D | best error = [ 0.1247, 0.1247, 0.1247, 0.1247, 0.1247] +24-11-19 20:17:27 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:27 | D | sum error = [ 2.4821, 2.6184, 2.7606, 2.9100, 3.0657] +24-11-19 20:17:27 | D | best error = [ 0.1247, 0.1247, 0.1247, 0.1247, 0.1247] +24-11-19 20:17:27 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:27 | D | sum error = [ 3.2282, 3.3978, 3.5750, 3.7595, 3.9516] +24-11-19 20:17:27 | D | best error = [ 0.1247, 0.1247, 0.1247, 0.1247, 0.1247] +24-11-19 20:17:27 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:27 | D | sum error = [ 4.1519, 4.3621, 4.5821, 4.8101, 5.0478] +24-11-19 20:17:27 | D | best error = [ 0.1247, 0.1247, 0.1247, 0.1247, 0.1247] +24-11-19 20:17:27 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:27 | D | sum error = [ 5.2965, 5.5564, 5.8242, 6.1033, 6.3949] +24-11-19 20:17:27 | D | best error = [ 0.1247, 0.1247, 0.1247, 0.1247, 0.1247] +24-11-19 20:17:27 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:27 | D | sum error = [ 6.6990, 7.0155, 7.3430, 7.6851, 8.0415] +24-11-19 20:17:27 | D | best error = [ 0.1247, 0.1247, 0.1247, 0.1247, 0.1247] +24-11-19 20:17:27 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:27 | D | sum error = [ 8.4111, 8.7948, 9.1923, 9.6044, 10.0321] +24-11-19 20:17:27 | D | best error = [ 0.1247, 0.1247, 0.1247, 0.1247, 0.1247] +24-11-19 20:17:27 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:27 | D | sum error = [ 10.4739, 10.9328, 11.4061, 11.8965, 12.4023] +24-11-19 20:17:27 | D | best error = [ 0.1247, 0.1247, 0.1247, 0.1247, 0.1247] +24-11-19 20:17:27 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:27 | D | sum error = [ 12.9254, 13.4648, 14.0211, 14.5953, 15.1845] +24-11-19 20:17:27 | D | best error = [ 0.1247, 0.1247, 0.1247, 0.1247, 0.1247] +24-11-19 20:17:27 | D | + error = [0.1247] +24-11-19 20:17:27 | D | - Quantizing model.layers.0.self_attn.q_proj.weight +24-11-19 20:17:28 | D | - Quantizing model.layers.0.self_attn.k_proj.weight +24-11-19 20:17:30 | D | - Quantizing model.layers.0.self_attn.v_proj.weight +24-11-19 20:17:31 | D | - Quantizing model.layers.0.self_attn.o_proj.weight +24-11-19 20:17:32 | D | - Quantizing model.layers.0.mlp.up_proj.weight +24-11-19 20:17:34 | D | - Quantizing model.layers.0.mlp.gate_proj.weight +24-11-19 20:17:35 | D | - Quantizing model.layers.0.mlp.down_proj.weight +24-11-19 20:17:47 | D | - Quantizing layer model.layers.1 +24-11-19 20:17:47 | D | - Calibrating model.layers.1.self_attn.q_proj.weight +24-11-19 20:17:47 | D | + w: sint8 +24-11-19 20:17:47 | D | + x: None +24-11-19 20:17:47 | D | + y: None +24-11-19 20:17:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:17:47 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:17:47 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:17:48 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:17:48 | D | - range ratio = [ 1.0000] +24-11-19 20:17:48 | D | sum error = [ 0.4306] +24-11-19 20:17:48 | D | best error = [ 0.4306] +24-11-19 20:18:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:01 | D | sum error = [ 0.4310, 0.4269, 0.4298, 0.4359, 0.4758] +24-11-19 20:18:01 | D | best error = [ 0.4306, 0.4269, 0.4269, 0.4269, 0.4269] +24-11-19 20:18:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:01 | D | sum error = [ 0.4748, 0.4785, 0.5152, 0.5501, 0.5929] +24-11-19 20:18:01 | D | best error = [ 0.4269, 0.4269, 0.4269, 0.4269, 0.4269] +24-11-19 20:18:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:01 | D | sum error = [ 0.6538, 0.7070, 0.7944, 0.8785, 1.0211] +24-11-19 20:18:01 | D | best error = [ 0.4269, 0.4269, 0.4269, 0.4269, 0.4269] +24-11-19 20:18:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:01 | D | sum error = [ 1.0992, 1.2233, 1.3654, 1.4756, 1.6637] +24-11-19 20:18:01 | D | best error = [ 0.4269, 0.4269, 0.4269, 0.4269, 0.4269] +24-11-19 20:18:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:01 | D | sum error = [ 1.9376, 2.1540, 2.3422, 2.6181, 2.9277] +24-11-19 20:18:01 | D | best error = [ 0.4269, 0.4269, 0.4269, 0.4269, 0.4269] +24-11-19 20:18:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:01 | D | sum error = [ 3.2407, 3.5787, 3.9417, 4.3537, 4.8291] +24-11-19 20:18:01 | D | best error = [ 0.4269, 0.4269, 0.4269, 0.4269, 0.4269] +24-11-19 20:18:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:01 | D | sum error = [ 5.2491, 5.7270, 6.2931, 6.8971, 7.4702] +24-11-19 20:18:01 | D | best error = [ 0.4269, 0.4269, 0.4269, 0.4269, 0.4269] +24-11-19 20:18:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:01 | D | sum error = [ 8.1106, 8.8109, 9.5405, 10.3349, 11.1642] +24-11-19 20:18:01 | D | best error = [ 0.4269, 0.4269, 0.4269, 0.4269, 0.4269] +24-11-19 20:18:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:01 | D | sum error = [ 12.0788, 13.0813, 14.1225, 15.2549, 16.4778] +24-11-19 20:18:01 | D | best error = [ 0.4269, 0.4269, 0.4269, 0.4269, 0.4269] +24-11-19 20:18:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:01 | D | sum error = [ 17.7355, 19.1655, 20.6517, 22.2741, 24.0863] +24-11-19 20:18:01 | D | best error = [ 0.4269, 0.4269, 0.4269, 0.4269, 0.4269] +24-11-19 20:18:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:01 | D | sum error = [ 25.9679, 28.0105, 30.1566, 32.4738, 34.9433] +24-11-19 20:18:01 | D | best error = [ 0.4269, 0.4269, 0.4269, 0.4269, 0.4269] +24-11-19 20:18:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:01 | D | sum error = [ 37.5710, 40.3547, 43.3579, 46.5107, 49.9067] +24-11-19 20:18:01 | D | best error = [ 0.4269, 0.4269, 0.4269, 0.4269, 0.4269] +24-11-19 20:18:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:01 | D | sum error = [ 53.4256, 57.2208, 61.3166, 65.6195, 70.2333] +24-11-19 20:18:01 | D | best error = [ 0.4269, 0.4269, 0.4269, 0.4269, 0.4269] +24-11-19 20:18:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:01 | D | sum error = [ 75.1429, 80.2924, 85.9233, 91.8227, 98.0756] +24-11-19 20:18:01 | D | best error = [ 0.4269, 0.4269, 0.4269, 0.4269, 0.4269] +24-11-19 20:18:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:01 | D | sum error = [ 104.7087, 111.8243, 119.2507, 127.1159, 135.3270] +24-11-19 20:18:01 | D | best error = [ 0.4269, 0.4269, 0.4269, 0.4269, 0.4269] +24-11-19 20:18:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:01 | D | sum error = [ 143.9997, 153.0594, 162.4614, 172.2369, 182.3772] +24-11-19 20:18:01 | D | best error = [ 0.4269, 0.4269, 0.4269, 0.4269, 0.4269] +24-11-19 20:18:01 | D | + error = [0.4269] +24-11-19 20:18:01 | D | - Calibrating model.layers.1.self_attn.k_proj.weight +24-11-19 20:18:01 | D | + w: sint8 +24-11-19 20:18:01 | D | + x: None +24-11-19 20:18:01 | D | + y: None +24-11-19 20:18:01 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:18:01 | D | + finished parsing calibration arguments, ram usage: 14.2 +24-11-19 20:18:01 | D | + finished reseting calibrator, ram usage: 14.2 +24-11-19 20:18:01 | D | + finished calculating the original outputs, ram usage: 14.2 +24-11-19 20:18:02 | D | - range ratio = [ 1.0000] +24-11-19 20:18:02 | D | sum error = [ 0.4864] +24-11-19 20:18:02 | D | best error = [ 0.4864] +24-11-19 20:18:14 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:14 | D | sum error = [ 0.5113, 0.5164, 0.5082, 0.5372, 0.5263] +24-11-19 20:18:14 | D | best error = [ 0.4864, 0.4864, 0.4864, 0.4864, 0.4864] +24-11-19 20:18:14 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:14 | D | sum error = [ 0.6116, 0.5552, 0.6481, 0.6223, 0.6901] +24-11-19 20:18:14 | D | best error = [ 0.4864, 0.4864, 0.4864, 0.4864, 0.4864] +24-11-19 20:18:14 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:14 | D | sum error = [ 0.7310, 0.7375, 0.8338, 0.8896, 0.9990] +24-11-19 20:18:14 | D | best error = [ 0.4864, 0.4864, 0.4864, 0.4864, 0.4864] +24-11-19 20:18:14 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:14 | D | sum error = [ 1.1138, 1.2349, 1.3563, 1.4839, 1.6478] +24-11-19 20:18:14 | D | best error = [ 0.4864, 0.4864, 0.4864, 0.4864, 0.4864] +24-11-19 20:18:14 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:14 | D | sum error = [ 1.9470, 2.0568, 2.3705, 2.5783, 2.8982] +24-11-19 20:18:14 | D | best error = [ 0.4864, 0.4864, 0.4864, 0.4864, 0.4864] +24-11-19 20:18:14 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:14 | D | sum error = [ 3.0600, 3.4454, 3.7931, 4.2878, 4.6169] +24-11-19 20:18:14 | D | best error = [ 0.4864, 0.4864, 0.4864, 0.4864, 0.4864] +24-11-19 20:18:14 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:14 | D | sum error = [ 5.2650, 5.6671, 6.3128, 7.0005, 7.5690] +24-11-19 20:18:14 | D | best error = [ 0.4864, 0.4864, 0.4864, 0.4864, 0.4864] +24-11-19 20:18:14 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:14 | D | sum error = [ 8.3793, 9.1033, 9.7984, 10.6327, 11.5357] +24-11-19 20:18:14 | D | best error = [ 0.4864, 0.4864, 0.4864, 0.4864, 0.4864] +24-11-19 20:18:14 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:14 | D | sum error = [ 12.3986, 13.4353, 14.4142, 15.4340, 16.6657] +24-11-19 20:18:14 | D | best error = [ 0.4864, 0.4864, 0.4864, 0.4864, 0.4864] +24-11-19 20:18:14 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:14 | D | sum error = [ 17.9146, 19.2797, 20.5877, 22.2791, 23.9095] +24-11-19 20:18:14 | D | best error = [ 0.4864, 0.4864, 0.4864, 0.4864, 0.4864] +24-11-19 20:18:14 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:14 | D | sum error = [ 25.7413, 27.5958, 29.7935, 31.9412, 34.2411] +24-11-19 20:18:14 | D | best error = [ 0.4864, 0.4864, 0.4864, 0.4864, 0.4864] +24-11-19 20:18:14 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:14 | D | sum error = [ 36.8739, 39.4562, 42.6214, 45.7202, 49.1423] +24-11-19 20:18:14 | D | best error = [ 0.4864, 0.4864, 0.4864, 0.4864, 0.4864] +24-11-19 20:18:14 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:14 | D | sum error = [ 53.0243, 56.9584, 61.0543, 65.4470, 69.9673] +24-11-19 20:18:14 | D | best error = [ 0.4864, 0.4864, 0.4864, 0.4864, 0.4864] +24-11-19 20:18:14 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:14 | D | sum error = [ 75.4357, 80.3797, 85.9375, 92.0908, 98.0111] +24-11-19 20:18:14 | D | best error = [ 0.4864, 0.4864, 0.4864, 0.4864, 0.4864] +24-11-19 20:18:14 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:14 | D | sum error = [ 105.0940, 111.7949, 119.1928, 126.9276, 135.1125] +24-11-19 20:18:14 | D | best error = [ 0.4864, 0.4864, 0.4864, 0.4864, 0.4864] +24-11-19 20:18:14 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:14 | D | sum error = [ 143.4226, 152.6930, 161.7160, 171.4605, 181.3741] +24-11-19 20:18:14 | D | best error = [ 0.4864, 0.4864, 0.4864, 0.4864, 0.4864] +24-11-19 20:18:14 | D | + error = [0.4864] +24-11-19 20:18:14 | D | - Calibrating model.layers.1.self_attn.v_proj.weight +24-11-19 20:18:14 | D | + w: sint8 +24-11-19 20:18:14 | D | + x: None +24-11-19 20:18:14 | D | + y: None +24-11-19 20:18:14 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:14 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:18:14 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:18:14 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:18:14 | D | - range ratio = [ 1.0000] +24-11-19 20:18:14 | D | sum error = [ 0.3294] +24-11-19 20:18:14 | D | best error = [ 0.3294] +24-11-19 20:18:14 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:14 | D | sum error = [ 0.3317, 0.3363, 0.3408, 0.3380, 0.3455] +24-11-19 20:18:14 | D | best error = [ 0.2894, 0.2763, 0.2705, 0.2663, 0.2637] +24-11-19 20:18:14 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:14 | D | sum error = [ 0.3513, 0.3679, 0.3774, 0.3979, 0.4161] +24-11-19 20:18:14 | D | best error = [ 0.2624, 0.2621, 0.2618, 0.2618, 0.2618] +24-11-19 20:18:14 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:14 | D | sum error = [ 0.4412, 0.4760, 0.5047, 0.5370, 0.5741] +24-11-19 20:18:14 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:18:14 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:14 | D | sum error = [ 0.6138, 0.6648, 0.7098, 0.7621, 0.8185] +24-11-19 20:18:14 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:18:14 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:14 | D | sum error = [ 0.8748, 0.9379, 1.0041, 1.0734, 1.1491] +24-11-19 20:18:14 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:18:14 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:14 | D | sum error = [ 1.2320, 1.3188, 1.4054, 1.5045, 1.6054] +24-11-19 20:18:14 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:18:14 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:14 | D | sum error = [ 1.7071, 1.8264, 1.9491, 2.0750, 2.2106] +24-11-19 20:18:14 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:18:14 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:14 | D | sum error = [ 2.3531, 2.5025, 2.6662, 2.8296, 3.0075] +24-11-19 20:18:14 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:18:14 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:14 | D | sum error = [ 3.1903, 3.3819, 3.5857, 3.8012, 4.0309] +24-11-19 20:18:14 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:18:14 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:14 | D | sum error = [ 4.2656, 4.5186, 4.7817, 5.0580, 5.3497] +24-11-19 20:18:14 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:18:14 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:14 | D | sum error = [ 5.6503, 5.9667, 6.2939, 6.6414, 7.0047] +24-11-19 20:18:14 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:18:14 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:14 | D | sum error = [ 7.3769, 7.7712, 8.1821, 8.6119, 9.0603] +24-11-19 20:18:14 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:18:14 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:14 | D | sum error = [ 9.5292, 10.0164, 10.5323, 11.0698, 11.6275] +24-11-19 20:18:14 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:18:14 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:14 | D | sum error = [ 12.2053, 12.8133, 13.4400, 14.0969, 14.7772] +24-11-19 20:18:14 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:18:14 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:14 | D | sum error = [ 15.4822, 16.2135, 16.9707, 17.7527, 18.5687] +24-11-19 20:18:14 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:18:14 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:14 | D | sum error = [ 19.4045, 20.2758, 21.1661, 22.0941, 23.0470] +24-11-19 20:18:14 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:18:14 | D | + error = [0.2618] +24-11-19 20:18:15 | D | - Calibrating model.layers.1.self_attn.o_proj.weight +24-11-19 20:18:15 | D | + w: sint8 +24-11-19 20:18:15 | D | + x: None +24-11-19 20:18:15 | D | + y: None +24-11-19 20:18:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:15 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:18:15 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:18:15 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:18:15 | D | - range ratio = [ 1.0000] +24-11-19 20:18:15 | D | sum error = [ 0.1715] +24-11-19 20:18:15 | D | best error = [ 0.1715] +24-11-19 20:18:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:15 | D | sum error = [ 0.1714, 0.1716, 0.1711, 0.1736, 0.1769] +24-11-19 20:18:15 | D | best error = [ 0.1452, 0.1357, 0.1308, 0.1276, 0.1256] +24-11-19 20:18:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:15 | D | sum error = [ 0.1835, 0.1906, 0.1982, 0.2086, 0.2177] +24-11-19 20:18:15 | D | best error = [ 0.1242, 0.1233, 0.1226, 0.1221, 0.1218] +24-11-19 20:18:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:15 | D | sum error = [ 0.2322, 0.2444, 0.2620, 0.2815, 0.2975] +24-11-19 20:18:15 | D | best error = [ 0.1216, 0.1214, 0.1213, 0.1212, 0.1211] +24-11-19 20:18:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:15 | D | sum error = [ 0.3189, 0.3423, 0.3661, 0.3919, 0.4202] +24-11-19 20:18:15 | D | best error = [ 0.1211, 0.1211, 0.1210, 0.1210, 0.1210] +24-11-19 20:18:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:15 | D | sum error = [ 0.4477, 0.4783, 0.5106, 0.5460, 0.5800] +24-11-19 20:18:15 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:18:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:15 | D | sum error = [ 0.6194, 0.6582, 0.6998, 0.7448, 0.7923] +24-11-19 20:18:15 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:18:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:15 | D | sum error = [ 0.8393, 0.8908, 0.9450, 1.0029, 1.0620] +24-11-19 20:18:15 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:18:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:15 | D | sum error = [ 1.1271, 1.1929, 1.2632, 1.3356, 1.4128] +24-11-19 20:18:15 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:18:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:15 | D | sum error = [ 1.4945, 1.5790, 1.6669, 1.7621, 1.8596] +24-11-19 20:18:15 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:18:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:15 | D | sum error = [ 1.9631, 2.0719, 2.1846, 2.3029, 2.4296] +24-11-19 20:18:15 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:18:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:15 | D | sum error = [ 2.5586, 2.6952, 2.8375, 2.9862, 3.1412] +24-11-19 20:18:15 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:18:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:15 | D | sum error = [ 3.3039, 3.4727, 3.6494, 3.8325, 4.0239] +24-11-19 20:18:15 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:18:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:15 | D | sum error = [ 4.2250, 4.4352, 4.6528, 4.8817, 5.1195] +24-11-19 20:18:15 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:18:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:15 | D | sum error = [ 5.3675, 5.6265, 5.8962, 6.1758, 6.4663] +24-11-19 20:18:15 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:18:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:15 | D | sum error = [ 6.7684, 7.0809, 7.4049, 7.7415, 8.0905] +24-11-19 20:18:15 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:18:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:15 | D | sum error = [ 8.4531, 8.8295, 9.2185, 9.6213, 10.0368] +24-11-19 20:18:15 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:18:15 | D | + error = [0.1210] +24-11-19 20:18:15 | D | - Calibrating model.layers.1.mlp.up_proj.weight +24-11-19 20:18:15 | D | + w: sint8 +24-11-19 20:18:15 | D | + x: None +24-11-19 20:18:15 | D | + y: None +24-11-19 20:18:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:15 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:18:15 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:18:16 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:18:16 | D | - range ratio = [ 1.0000] +24-11-19 20:18:16 | D | sum error = [ 0.1848] +24-11-19 20:18:16 | D | best error = [ 0.1848] +24-11-19 20:18:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:17 | D | sum error = [ 0.1837, 0.1834, 0.1843, 0.1862, 0.1903] +24-11-19 20:18:17 | D | best error = [ 0.1721, 0.1634, 0.1597, 0.1575, 0.1564] +24-11-19 20:18:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:17 | D | sum error = [ 0.1949, 0.2013, 0.2097, 0.2190, 0.2303] +24-11-19 20:18:17 | D | best error = [ 0.1558, 0.1555, 0.1554, 0.1553, 0.1553] +24-11-19 20:18:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:17 | D | sum error = [ 0.2440, 0.2595, 0.2757, 0.2942, 0.3136] +24-11-19 20:18:17 | D | best error = [ 0.1553, 0.1553, 0.1553, 0.1553, 0.1553] +24-11-19 20:18:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:17 | D | sum error = [ 0.3358, 0.3602, 0.3856, 0.4126, 0.4431] +24-11-19 20:18:17 | D | best error = [ 0.1553, 0.1553, 0.1553, 0.1553, 0.1553] +24-11-19 20:18:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:17 | D | sum error = [ 0.4740, 0.5069, 0.5430, 0.5806, 0.6205] +24-11-19 20:18:17 | D | best error = [ 0.1553, 0.1553, 0.1553, 0.1553, 0.1553] +24-11-19 20:18:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:17 | D | sum error = [ 0.6634, 0.7073, 0.7565, 0.8059, 0.8598] +24-11-19 20:18:17 | D | best error = [ 0.1553, 0.1553, 0.1553, 0.1553, 0.1553] +24-11-19 20:18:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:17 | D | sum error = [ 0.9140, 0.9727, 1.0355, 1.0998, 1.1678] +24-11-19 20:18:17 | D | best error = [ 0.1553, 0.1553, 0.1553, 0.1553, 0.1553] +24-11-19 20:18:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:17 | D | sum error = [ 1.2406, 1.3151, 1.3934, 1.4761, 1.5634] +24-11-19 20:18:17 | D | best error = [ 0.1553, 0.1553, 0.1553, 0.1553, 0.1553] +24-11-19 20:18:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:17 | D | sum error = [ 1.6536, 1.7475, 1.8464, 1.9493, 2.0579] +24-11-19 20:18:17 | D | best error = [ 0.1553, 0.1553, 0.1553, 0.1553, 0.1553] +24-11-19 20:18:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:17 | D | sum error = [ 2.1694, 2.2868, 2.4082, 2.5348, 2.6671] +24-11-19 20:18:17 | D | best error = [ 0.1553, 0.1553, 0.1553, 0.1553, 0.1553] +24-11-19 20:18:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:17 | D | sum error = [ 2.8034, 2.9471, 3.0946, 3.2469, 3.4080] +24-11-19 20:18:17 | D | best error = [ 0.1553, 0.1553, 0.1553, 0.1553, 0.1553] +24-11-19 20:18:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:17 | D | sum error = [ 3.5707, 3.7412, 3.9207, 4.1027, 4.2905] +24-11-19 20:18:17 | D | best error = [ 0.1553, 0.1553, 0.1553, 0.1553, 0.1553] +24-11-19 20:18:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:17 | D | sum error = [ 4.4836, 4.6891, 4.8956, 5.1083, 5.3301] +24-11-19 20:18:17 | D | best error = [ 0.1553, 0.1553, 0.1553, 0.1553, 0.1553] +24-11-19 20:18:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:17 | D | sum error = [ 5.5597, 5.7898, 6.0334, 6.2800, 6.5381] +24-11-19 20:18:17 | D | best error = [ 0.1553, 0.1553, 0.1553, 0.1553, 0.1553] +24-11-19 20:18:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:17 | D | sum error = [ 6.7917, 7.0633, 7.3392, 7.6162, 7.9096] +24-11-19 20:18:17 | D | best error = [ 0.1553, 0.1553, 0.1553, 0.1553, 0.1553] +24-11-19 20:18:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:17 | D | sum error = [ 8.2119, 8.5186, 8.8248, 9.1492, 9.4761] +24-11-19 20:18:17 | D | best error = [ 0.1553, 0.1553, 0.1553, 0.1553, 0.1553] +24-11-19 20:18:17 | D | + error = [0.1553] +24-11-19 20:18:17 | D | - Calibrating model.layers.1.mlp.gate_proj.weight +24-11-19 20:18:17 | D | + w: sint8 +24-11-19 20:18:17 | D | + x: None +24-11-19 20:18:17 | D | + y: None +24-11-19 20:18:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:17 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:18:17 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:18:17 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:18:17 | D | - range ratio = [ 1.0000] +24-11-19 20:18:17 | D | sum error = [ 3.1410] +24-11-19 20:18:17 | D | best error = [ 3.1410] +24-11-19 20:18:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:18 | D | sum error = [ 3.1194, 3.1115, 3.1217, 3.1554, 3.2209] +24-11-19 20:18:18 | D | best error = [ 2.8114, 2.7002, 2.6440, 2.6124, 2.5956] +24-11-19 20:18:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:18 | D | sum error = [ 3.2958, 3.4251, 3.5640, 3.7061, 3.9122] +24-11-19 20:18:18 | D | best error = [ 2.5874, 2.5835, 2.5818, 2.5813, 2.5812] +24-11-19 20:18:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:18 | D | sum error = [ 4.1402, 4.3995, 4.6882, 5.0058, 5.3384] +24-11-19 20:18:18 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:18:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:18 | D | sum error = [ 5.7277, 6.1407, 6.5767, 7.0425, 7.5548] +24-11-19 20:18:18 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:18:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:18 | D | sum error = [ 8.1077, 8.6793, 9.2922, 9.9559, 10.6588] +24-11-19 20:18:18 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:18:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:18 | D | sum error = [ 11.3908, 12.1815, 13.0142, 13.8809, 14.8355] +24-11-19 20:18:18 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:18:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:18 | D | sum error = [ 15.8146, 16.8600, 17.9438, 19.1235, 20.3511] +24-11-19 20:18:18 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:18:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:18 | D | sum error = [ 21.6448, 23.0070, 24.4407, 25.9441, 27.5314] +24-11-19 20:18:18 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:18:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:18 | D | sum error = [ 29.2021, 30.9590, 32.8005, 34.7392, 36.7936] +24-11-19 20:18:18 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:18:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:18 | D | sum error = [ 38.8943, 41.1377, 43.4864, 45.9350, 48.5138] +24-11-19 20:18:18 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:18:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:18 | D | sum error = [ 51.1935, 54.0094, 56.9495, 60.0074, 63.2220] +24-11-19 20:18:18 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:18:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:18 | D | sum error = [ 66.5725, 70.0584, 73.7017, 77.5004, 81.4463] +24-11-19 20:18:18 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:18:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:18 | D | sum error = [ 85.5685, 89.8673, 94.3515, 98.9882, 103.8063] +24-11-19 20:18:18 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:18:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:18 | D | sum error = [ 108.8154, 113.9980, 119.3828, 124.9694, 130.7190] +24-11-19 20:18:18 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:18:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:18 | D | sum error = [ 136.7114, 142.8840, 149.2688, 155.8667, 162.6957] +24-11-19 20:18:18 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:18:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:18 | D | sum error = [ 169.7005, 176.9131, 184.3620, 192.0236, 199.8993] +24-11-19 20:18:18 | D | best error = [ 2.5811, 2.5811, 2.5811, 2.5811, 2.5811] +24-11-19 20:18:18 | D | + error = [2.5811] +24-11-19 20:18:19 | D | - Calibrating model.layers.1.mlp.down_proj.weight +24-11-19 20:18:19 | D | + w: sint8 +24-11-19 20:18:19 | D | + x: None +24-11-19 20:18:19 | D | + y: None +24-11-19 20:18:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:19 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:18:19 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:18:19 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:18:19 | D | - range ratio = [ 1.0000] +24-11-19 20:18:19 | D | sum error = [ 2.3615] +24-11-19 20:18:19 | D | best error = [ 2.3615] +24-11-19 20:18:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:20 | D | sum error = [ 9.7874, 19.0664, 28.5025, 37.9607, 47.4181] +24-11-19 20:18:20 | D | best error = [ 1.5989, 1.2669, 1.0926, 0.9785, 0.9080] +24-11-19 20:18:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:20 | D | sum error = [ 56.8730, 66.3953, 75.8471, 85.3382, 94.8061] +24-11-19 20:18:20 | D | best error = [ 0.8442, 0.8041, 0.7632, 0.7278, 0.6968] +24-11-19 20:18:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:20 | D | sum error = [ 104.3126, 113.8287, 123.3277, 132.8938, 142.5472] +24-11-19 20:18:20 | D | best error = [ 0.6718, 0.6511, 0.6308, 0.6142, 0.6069] +24-11-19 20:18:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:20 | D | sum error = [ 152.3017, 162.1712, 172.1880, 182.3605, 192.7169] +24-11-19 20:18:20 | D | best error = [ 0.5994, 0.5940, 0.5899, 0.5864, 0.5826] +24-11-19 20:18:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:20 | D | sum error = [ 203.2087, 213.8368, 224.5940, 235.4447, 246.3766] +24-11-19 20:18:20 | D | best error = [ 0.5801, 0.5779, 0.5762, 0.5744, 0.5733] +24-11-19 20:18:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:20 | D | sum error = [ 257.3664, 268.4247, 279.5060, 290.6123, 301.7507] +24-11-19 20:18:20 | D | best error = [ 0.5726, 0.5720, 0.5713, 0.5710, 0.5707] +24-11-19 20:18:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:20 | D | sum error = [ 312.9100, 324.0703, 335.3055, 346.5619, 357.8520] +24-11-19 20:18:20 | D | best error = [ 0.5706, 0.5703, 0.5703, 0.5703, 0.5702] +24-11-19 20:18:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:20 | D | sum error = [ 369.1672, 380.5342, 392.0080, 403.4421, 414.9752] +24-11-19 20:18:20 | D | best error = [ 0.5702, 0.5702, 0.5702, 0.5702, 0.5702] +24-11-19 20:18:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:20 | D | sum error = [ 426.5629, 438.2085, 449.9409, 461.7405, 473.5968] +24-11-19 20:18:20 | D | best error = [ 0.5702, 0.5702, 0.5702, 0.5702, 0.5702] +24-11-19 20:18:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:20 | D | sum error = [ 485.5575, 497.5747, 509.6921, 521.8989, 534.1846] +24-11-19 20:18:20 | D | best error = [ 0.5702, 0.5702, 0.5702, 0.5702, 0.5702] +24-11-19 20:18:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:20 | D | sum error = [ 546.5573, 559.0372, 571.5893, 584.2587, 597.0174] +24-11-19 20:18:20 | D | best error = [ 0.5702, 0.5702, 0.5702, 0.5702, 0.5702] +24-11-19 20:18:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:20 | D | sum error = [ 609.8810, 622.8115, 635.8655, 649.0100, 662.2467] +24-11-19 20:18:20 | D | best error = [ 0.5702, 0.5702, 0.5702, 0.5702, 0.5702] +24-11-19 20:18:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:20 | D | sum error = [ 675.5795, 689.0062, 702.5105, 716.1284, 729.8303] +24-11-19 20:18:20 | D | best error = [ 0.5702, 0.5702, 0.5702, 0.5702, 0.5702] +24-11-19 20:18:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:20 | D | sum error = [ 743.5929, 757.4679, 771.4057, 785.4511, 799.5290] +24-11-19 20:18:20 | D | best error = [ 0.5702, 0.5702, 0.5702, 0.5702, 0.5702] +24-11-19 20:18:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:20 | D | sum error = [ 813.6889, 827.9324, 842.2475, 856.6175, 871.0522] +24-11-19 20:18:20 | D | best error = [ 0.5702, 0.5702, 0.5702, 0.5702, 0.5702] +24-11-19 20:18:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:20 | D | sum error = [ 885.5472, 900.1025, 914.7189, 929.3733, 944.0906] +24-11-19 20:18:20 | D | best error = [ 0.5702, 0.5702, 0.5702, 0.5702, 0.5702] +24-11-19 20:18:20 | D | + error = [0.5702] +24-11-19 20:18:20 | D | - Quantizing model.layers.1.self_attn.q_proj.weight +24-11-19 20:18:21 | D | - Quantizing model.layers.1.self_attn.k_proj.weight +24-11-19 20:18:22 | D | - Quantizing model.layers.1.self_attn.v_proj.weight +24-11-19 20:18:23 | D | - Quantizing model.layers.1.self_attn.o_proj.weight +24-11-19 20:18:25 | D | - Quantizing model.layers.1.mlp.up_proj.weight +24-11-19 20:18:26 | D | - Quantizing model.layers.1.mlp.gate_proj.weight +24-11-19 20:18:28 | D | - Quantizing model.layers.1.mlp.down_proj.weight +24-11-19 20:18:40 | D | - Quantizing layer model.layers.2 +24-11-19 20:18:40 | D | - Calibrating model.layers.2.self_attn.q_proj.weight +24-11-19 20:18:40 | D | + w: sint8 +24-11-19 20:18:40 | D | + x: None +24-11-19 20:18:40 | D | + y: None +24-11-19 20:18:40 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:18:40 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:18:40 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:18:40 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:18:40 | D | - range ratio = [ 1.0000] +24-11-19 20:18:40 | D | sum error = [ 0.7826] +24-11-19 20:18:40 | D | best error = [ 0.7826] +24-11-19 20:18:53 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:53 | D | sum error = [ 0.7725, 0.7762, 0.7780, 0.7921, 0.8231] +24-11-19 20:18:53 | D | best error = [ 0.7725, 0.7725, 0.7725, 0.7725, 0.7725] +24-11-19 20:18:53 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:53 | D | sum error = [ 0.8502, 0.8763, 0.9260, 0.9901, 1.0662] +24-11-19 20:18:53 | D | best error = [ 0.7725, 0.7725, 0.7725, 0.7725, 0.7725] +24-11-19 20:18:53 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:53 | D | sum error = [ 1.1371, 1.2203, 1.3207, 1.4569, 1.5866] +24-11-19 20:18:53 | D | best error = [ 0.7725, 0.7725, 0.7725, 0.7725, 0.7725] +24-11-19 20:18:53 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:53 | D | sum error = [ 1.7284, 1.9166, 2.1036, 2.3104, 2.5181] +24-11-19 20:18:53 | D | best error = [ 0.7725, 0.7725, 0.7725, 0.7725, 0.7725] +24-11-19 20:18:53 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:53 | D | sum error = [ 2.7073, 3.0104, 3.2260, 3.6011, 3.9314] +24-11-19 20:18:53 | D | best error = [ 0.7725, 0.7725, 0.7725, 0.7725, 0.7725] +24-11-19 20:18:53 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:53 | D | sum error = [ 4.3809, 4.7071, 5.1658, 5.6256, 6.1482] +24-11-19 20:18:53 | D | best error = [ 0.7725, 0.7725, 0.7725, 0.7725, 0.7725] +24-11-19 20:18:53 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:53 | D | sum error = [ 6.7564, 7.3533, 8.0417, 8.7608, 9.6475] +24-11-19 20:18:53 | D | best error = [ 0.7725, 0.7725, 0.7725, 0.7725, 0.7725] +24-11-19 20:18:53 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:53 | D | sum error = [ 10.5268, 11.4960, 12.6160, 13.7533, 14.9852] +24-11-19 20:18:53 | D | best error = [ 0.7725, 0.7725, 0.7725, 0.7725, 0.7725] +24-11-19 20:18:53 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:53 | D | sum error = [ 16.4128, 17.9529, 19.5330, 21.3276, 23.2914] +24-11-19 20:18:53 | D | best error = [ 0.7725, 0.7725, 0.7725, 0.7725, 0.7725] +24-11-19 20:18:53 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:53 | D | sum error = [ 25.4125, 27.7098, 30.2508, 33.0665, 36.0665] +24-11-19 20:18:53 | D | best error = [ 0.7725, 0.7725, 0.7725, 0.7725, 0.7725] +24-11-19 20:18:53 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:53 | D | sum error = [ 39.2893, 42.8046, 46.6935, 50.9103, 55.4785] +24-11-19 20:18:53 | D | best error = [ 0.7725, 0.7725, 0.7725, 0.7725, 0.7725] +24-11-19 20:18:53 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:53 | D | sum error = [ 60.4388, 65.8561, 71.7229, 78.0827, 84.9653] +24-11-19 20:18:53 | D | best error = [ 0.7725, 0.7725, 0.7725, 0.7725, 0.7725] +24-11-19 20:18:53 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:53 | D | sum error = [ 92.3990, 100.5678, 109.2440, 118.7661, 128.9675] +24-11-19 20:18:53 | D | best error = [ 0.7725, 0.7725, 0.7725, 0.7725, 0.7725] +24-11-19 20:18:53 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:53 | D | sum error = [ 139.9676, 151.8655, 164.7178, 178.5404, 193.4188] +24-11-19 20:18:53 | D | best error = [ 0.7725, 0.7725, 0.7725, 0.7725, 0.7725] +24-11-19 20:18:53 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:53 | D | sum error = [ 209.3912, 226.5549, 245.0668, 264.8956, 286.4700] +24-11-19 20:18:53 | D | best error = [ 0.7725, 0.7725, 0.7725, 0.7725, 0.7725] +24-11-19 20:18:53 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:53 | D | sum error = [ 309.6576, 334.3993, 360.9554, 389.1148, 419.0819] +24-11-19 20:18:53 | D | best error = [ 0.7725, 0.7725, 0.7725, 0.7725, 0.7725] +24-11-19 20:18:53 | D | + error = [0.7725] +24-11-19 20:18:53 | D | - Calibrating model.layers.2.self_attn.k_proj.weight +24-11-19 20:18:53 | D | + w: sint8 +24-11-19 20:18:53 | D | + x: None +24-11-19 20:18:53 | D | + y: None +24-11-19 20:18:53 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:18:53 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:18:53 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:18:53 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:18:54 | D | - range ratio = [ 1.0000] +24-11-19 20:18:54 | D | sum error = [ 1.0480] +24-11-19 20:18:54 | D | best error = [ 1.0480] +24-11-19 20:19:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:06 | D | sum error = [ 0.9134, 0.9191, 0.8234, 0.8918, 1.1826] +24-11-19 20:19:06 | D | best error = [ 0.9134, 0.9134, 0.8234, 0.8234, 0.8234] +24-11-19 20:19:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:06 | D | sum error = [ 1.0694, 0.9820, 1.1710, 1.1677, 1.3065] +24-11-19 20:19:06 | D | best error = [ 0.8234, 0.8234, 0.8234, 0.8234, 0.8234] +24-11-19 20:19:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:06 | D | sum error = [ 1.2231, 1.3385, 1.5258, 1.7621, 1.7976] +24-11-19 20:19:06 | D | best error = [ 0.8234, 0.8234, 0.8234, 0.8234, 0.8234] +24-11-19 20:19:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:06 | D | sum error = [ 1.8348, 2.1244, 2.3410, 2.5198, 2.5883] +24-11-19 20:19:06 | D | best error = [ 0.8234, 0.8234, 0.8234, 0.8234, 0.8234] +24-11-19 20:19:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:06 | D | sum error = [ 2.8515, 3.0125, 3.2767, 3.4708, 3.9049] +24-11-19 20:19:06 | D | best error = [ 0.8234, 0.8234, 0.8234, 0.8234, 0.8234] +24-11-19 20:19:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:06 | D | sum error = [ 4.1862, 4.5585, 4.8782, 5.3145, 5.8219] +24-11-19 20:19:06 | D | best error = [ 0.8234, 0.8234, 0.8234, 0.8234, 0.8234] +24-11-19 20:19:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:06 | D | sum error = [ 6.4769, 6.9190, 7.6740, 8.3141, 9.0239] +24-11-19 20:19:06 | D | best error = [ 0.8234, 0.8234, 0.8234, 0.8234, 0.8234] +24-11-19 20:19:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:06 | D | sum error = [ 10.1660, 11.0389, 11.9221, 12.8732, 14.1427] +24-11-19 20:19:06 | D | best error = [ 0.8234, 0.8234, 0.8234, 0.8234, 0.8234] +24-11-19 20:19:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:06 | D | sum error = [ 15.4146, 16.9845, 18.4178, 20.2690, 22.1828] +24-11-19 20:19:06 | D | best error = [ 0.8234, 0.8234, 0.8234, 0.8234, 0.8234] +24-11-19 20:19:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:06 | D | sum error = [ 24.2991, 26.5784, 29.2656, 31.8696, 34.7026] +24-11-19 20:19:06 | D | best error = [ 0.8234, 0.8234, 0.8234, 0.8234, 0.8234] +24-11-19 20:19:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:06 | D | sum error = [ 38.0279, 41.5323, 45.3539, 49.6815, 53.6484] +24-11-19 20:19:06 | D | best error = [ 0.8234, 0.8234, 0.8234, 0.8234, 0.8234] +24-11-19 20:19:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:06 | D | sum error = [ 58.9141, 64.3541, 69.7607, 76.8077, 83.0044] +24-11-19 20:19:06 | D | best error = [ 0.8234, 0.8234, 0.8234, 0.8234, 0.8234] +24-11-19 20:19:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:06 | D | sum error = [ 90.7578, 98.6551, 106.8624, 116.3239, 126.3040] +24-11-19 20:19:06 | D | best error = [ 0.8234, 0.8234, 0.8234, 0.8234, 0.8234] +24-11-19 20:19:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:06 | D | sum error = [ 137.7847, 150.2844, 162.6446, 177.6498, 193.2108] +24-11-19 20:19:06 | D | best error = [ 0.8234, 0.8234, 0.8234, 0.8234, 0.8234] +24-11-19 20:19:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:06 | D | sum error = [ 209.3941, 228.1647, 246.8776, 267.7996, 290.9276] +24-11-19 20:19:06 | D | best error = [ 0.8234, 0.8234, 0.8234, 0.8234, 0.8234] +24-11-19 20:19:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:06 | D | sum error = [ 314.3079, 341.2479, 368.1111, 397.2341, 429.1671] +24-11-19 20:19:06 | D | best error = [ 0.8234, 0.8234, 0.8234, 0.8234, 0.8234] +24-11-19 20:19:06 | D | + error = [0.8234] +24-11-19 20:19:06 | D | - Calibrating model.layers.2.self_attn.v_proj.weight +24-11-19 20:19:06 | D | + w: sint8 +24-11-19 20:19:06 | D | + x: None +24-11-19 20:19:06 | D | + y: None +24-11-19 20:19:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:06 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:19:06 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:19:06 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:19:06 | D | - range ratio = [ 1.0000] +24-11-19 20:19:06 | D | sum error = [ 0.8203] +24-11-19 20:19:06 | D | best error = [ 0.8203] +24-11-19 20:19:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:06 | D | sum error = [ 0.8166, 0.8108, 0.8090, 0.8220, 0.8328] +24-11-19 20:19:06 | D | best error = [ 0.7553, 0.7305, 0.7184, 0.7127, 0.7095] +24-11-19 20:19:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:06 | D | sum error = [ 0.8653, 0.8976, 0.9325, 0.9729, 1.0206] +24-11-19 20:19:06 | D | best error = [ 0.7073, 0.7068, 0.7067, 0.7066, 0.7066] +24-11-19 20:19:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:06 | D | sum error = [ 1.0815, 1.1517, 1.2347, 1.3098, 1.4000] +24-11-19 20:19:06 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:06 | D | sum error = [ 1.5128, 1.6155, 1.7233, 1.8518, 1.9805] +24-11-19 20:19:06 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:06 | D | sum error = [ 2.1150, 2.2710, 2.4384, 2.6100, 2.7959] +24-11-19 20:19:06 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:06 | D | sum error = [ 2.9917, 3.2027, 3.4188, 3.6550, 3.8908] +24-11-19 20:19:06 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:06 | D | sum error = [ 4.1589, 4.4352, 4.7180, 5.0184, 5.3428] +24-11-19 20:19:06 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:06 | D | sum error = [ 5.6892, 6.0510, 6.4314, 6.8304, 7.2528] +24-11-19 20:19:06 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:06 | D | sum error = [ 7.6970, 8.1624, 8.6492, 9.1594, 9.6983] +24-11-19 20:19:06 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:06 | D | sum error = [ 10.2620, 10.8530, 11.4770, 12.1217, 12.7998] +24-11-19 20:19:06 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:06 | D | sum error = [ 13.5131, 14.2654, 15.0477, 15.8721, 16.7312] +24-11-19 20:19:06 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:06 | D | sum error = [ 17.6222, 18.5603, 19.5332, 20.5604, 21.6281] +24-11-19 20:19:06 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:06 | D | sum error = [ 22.7468, 23.9115, 25.1174, 26.3844, 27.6976] +24-11-19 20:19:06 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:06 | D | sum error = [ 29.0596, 30.4783, 31.9562, 33.4869, 35.0699] +24-11-19 20:19:06 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:06 | D | sum error = [ 36.7137, 38.4199, 40.1865, 42.0148, 43.9057] +24-11-19 20:19:06 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:06 | D | sum error = [ 45.8631, 47.8863, 49.9768, 52.1390, 54.3619] +24-11-19 20:19:06 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:06 | D | + error = [0.7066] +24-11-19 20:19:06 | D | - Calibrating model.layers.2.self_attn.o_proj.weight +24-11-19 20:19:06 | D | + w: sint8 +24-11-19 20:19:06 | D | + x: None +24-11-19 20:19:06 | D | + y: None +24-11-19 20:19:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:06 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:19:06 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:19:07 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:19:07 | D | - range ratio = [ 1.0000] +24-11-19 20:19:07 | D | sum error = [ 0.1002] +24-11-19 20:19:07 | D | best error = [ 0.1002] +24-11-19 20:19:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:07 | D | sum error = [ 0.0992, 0.0992, 0.1000, 0.1004, 0.1026] +24-11-19 20:19:07 | D | best error = [ 0.0891, 0.0847, 0.0821, 0.0806, 0.0797] +24-11-19 20:19:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:07 | D | sum error = [ 0.1048, 0.1082, 0.1122, 0.1169, 0.1233] +24-11-19 20:19:07 | D | best error = [ 0.0790, 0.0786, 0.0783, 0.0781, 0.0780] +24-11-19 20:19:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:07 | D | sum error = [ 0.1288, 0.1373, 0.1451, 0.1545, 0.1649] +24-11-19 20:19:07 | D | best error = [ 0.0780, 0.0779, 0.0779, 0.0778, 0.0778] +24-11-19 20:19:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:07 | D | sum error = [ 0.1759, 0.1872, 0.1997, 0.2131, 0.2281] +24-11-19 20:19:07 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:19:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:07 | D | sum error = [ 0.2434, 0.2599, 0.2767, 0.2957, 0.3145] +24-11-19 20:19:07 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:19:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:07 | D | sum error = [ 0.3351, 0.3569, 0.3798, 0.4039, 0.4310] +24-11-19 20:19:07 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:19:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:07 | D | sum error = [ 0.4577, 0.4860, 0.5156, 0.5475, 0.5809] +24-11-19 20:19:07 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:19:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:07 | D | sum error = [ 0.6154, 0.6526, 0.6915, 0.7329, 0.7753] +24-11-19 20:19:07 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:19:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:07 | D | sum error = [ 0.8209, 0.8675, 0.9184, 0.9711, 1.0260] +24-11-19 20:19:07 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:19:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:07 | D | sum error = [ 1.0843, 1.1460, 1.2098, 1.2769, 1.3476] +24-11-19 20:19:07 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:19:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:07 | D | sum error = [ 1.4209, 1.4989, 1.5797, 1.6651, 1.7541] +24-11-19 20:19:07 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:19:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:07 | D | sum error = [ 1.8478, 1.9454, 2.0481, 2.1552, 2.2673] +24-11-19 20:19:07 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:19:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:07 | D | sum error = [ 2.3841, 2.5066, 2.6348, 2.7690, 2.9084] +24-11-19 20:19:07 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:19:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:07 | D | sum error = [ 3.0548, 3.2072, 3.3670, 3.5326, 3.7055] +24-11-19 20:19:07 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:19:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:07 | D | sum error = [ 3.8849, 4.0719, 4.2667, 4.4690, 4.6797] +24-11-19 20:19:07 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:19:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:07 | D | sum error = [ 4.8980, 5.1248, 5.3602, 5.6049, 5.8587] +24-11-19 20:19:07 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:19:07 | D | + error = [0.0778] +24-11-19 20:19:07 | D | - Calibrating model.layers.2.mlp.up_proj.weight +24-11-19 20:19:07 | D | + w: sint8 +24-11-19 20:19:07 | D | + x: None +24-11-19 20:19:07 | D | + y: None +24-11-19 20:19:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:07 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:19:07 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:19:07 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:19:07 | D | - range ratio = [ 1.0000] +24-11-19 20:19:07 | D | sum error = [ 0.2172] +24-11-19 20:19:07 | D | best error = [ 0.2172] +24-11-19 20:19:09 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:09 | D | sum error = [ 0.2162, 0.2157, 0.2164, 0.2187, 0.2229] +24-11-19 20:19:09 | D | best error = [ 0.2035, 0.1961, 0.1926, 0.1907, 0.1897] +24-11-19 20:19:09 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:09 | D | sum error = [ 0.2282, 0.2362, 0.2454, 0.2568, 0.2699] +24-11-19 20:19:09 | D | best error = [ 0.1892, 0.1890, 0.1889, 0.1889, 0.1889] +24-11-19 20:19:09 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:09 | D | sum error = [ 0.2855, 0.3041, 0.3229, 0.3447, 0.3687] +24-11-19 20:19:09 | D | best error = [ 0.1889, 0.1889, 0.1889, 0.1889, 0.1889] +24-11-19 20:19:09 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:09 | D | sum error = [ 0.3939, 0.4214, 0.4513, 0.4841, 0.5193] +24-11-19 20:19:09 | D | best error = [ 0.1889, 0.1889, 0.1889, 0.1889, 0.1889] +24-11-19 20:19:09 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:09 | D | sum error = [ 0.5557, 0.5947, 0.6361, 0.6801, 0.7268] +24-11-19 20:19:09 | D | best error = [ 0.1889, 0.1889, 0.1889, 0.1889, 0.1889] +24-11-19 20:19:09 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:09 | D | sum error = [ 0.7762, 0.8281, 0.8837, 0.9419, 1.0034] +24-11-19 20:19:09 | D | best error = [ 0.1889, 0.1889, 0.1889, 0.1889, 0.1889] +24-11-19 20:19:09 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:09 | D | sum error = [ 1.0668, 1.1361, 1.2077, 1.2822, 1.3617] +24-11-19 20:19:09 | D | best error = [ 0.1889, 0.1889, 0.1889, 0.1889, 0.1889] +24-11-19 20:19:09 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:09 | D | sum error = [ 1.4449, 1.5328, 1.6231, 1.7196, 1.8199] +24-11-19 20:19:09 | D | best error = [ 0.1889, 0.1889, 0.1889, 0.1889, 0.1889] +24-11-19 20:19:09 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:09 | D | sum error = [ 1.9245, 2.0334, 2.1484, 2.2681, 2.3924] +24-11-19 20:19:09 | D | best error = [ 0.1889, 0.1889, 0.1889, 0.1889, 0.1889] +24-11-19 20:19:09 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:09 | D | sum error = [ 2.5230, 2.6578, 2.7980, 2.9461, 3.0967] +24-11-19 20:19:09 | D | best error = [ 0.1889, 0.1889, 0.1889, 0.1889, 0.1889] +24-11-19 20:19:09 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:09 | D | sum error = [ 3.2555, 3.4209, 3.5889, 3.7694, 3.9484] +24-11-19 20:19:09 | D | best error = [ 0.1889, 0.1889, 0.1889, 0.1889, 0.1889] +24-11-19 20:19:09 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:09 | D | sum error = [ 4.1378, 4.3351, 4.5362, 4.7471, 4.9596] +24-11-19 20:19:09 | D | best error = [ 0.1889, 0.1889, 0.1889, 0.1889, 0.1889] +24-11-19 20:19:09 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:09 | D | sum error = [ 5.1849, 5.4160, 5.6496, 5.8953, 6.1450] +24-11-19 20:19:09 | D | best error = [ 0.1889, 0.1889, 0.1889, 0.1889, 0.1889] +24-11-19 20:19:09 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:09 | D | sum error = [ 6.4057, 6.6710, 6.9413, 7.2243, 7.5114] +24-11-19 20:19:09 | D | best error = [ 0.1889, 0.1889, 0.1889, 0.1889, 0.1889] +24-11-19 20:19:09 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:09 | D | sum error = [ 7.8046, 8.1078, 8.4176, 8.7366, 9.0586] +24-11-19 20:19:09 | D | best error = [ 0.1889, 0.1889, 0.1889, 0.1889, 0.1889] +24-11-19 20:19:09 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:09 | D | sum error = [ 9.3951, 9.7312, 10.0850, 10.4494, 10.8096] +24-11-19 20:19:09 | D | best error = [ 0.1889, 0.1889, 0.1889, 0.1889, 0.1889] +24-11-19 20:19:09 | D | + error = [0.1889] +24-11-19 20:19:09 | D | - Calibrating model.layers.2.mlp.gate_proj.weight +24-11-19 20:19:09 | D | + w: sint8 +24-11-19 20:19:09 | D | + x: None +24-11-19 20:19:09 | D | + y: None +24-11-19 20:19:09 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:09 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:19:09 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:19:09 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:19:09 | D | - range ratio = [ 1.0000] +24-11-19 20:19:09 | D | sum error = [ 3.9980] +24-11-19 20:19:09 | D | best error = [ 3.9980] +24-11-19 20:19:10 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:10 | D | sum error = [ 3.9787, 3.9603, 3.9844, 4.0198, 4.0983] +24-11-19 20:19:10 | D | best error = [ 3.6792, 3.5607, 3.5039, 3.4719, 3.4547] +24-11-19 20:19:10 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:10 | D | sum error = [ 4.2016, 4.3490, 4.5203, 4.7272, 4.9828] +24-11-19 20:19:10 | D | best error = [ 3.4469, 3.4437, 3.4427, 3.4424, 3.4424] +24-11-19 20:19:10 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:10 | D | sum error = [ 5.2611, 5.5996, 5.9433, 6.3510, 6.7837] +24-11-19 20:19:10 | D | best error = [ 3.4424, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:19:10 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:10 | D | sum error = [ 7.2726, 7.7935, 8.3511, 8.9397, 9.5743] +24-11-19 20:19:10 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:19:10 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:10 | D | sum error = [ 10.2558, 10.9925, 11.7530, 12.5646, 13.4403] +24-11-19 20:19:10 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:19:10 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:10 | D | sum error = [ 14.3534, 15.3236, 16.3637, 17.4523, 18.5964] +24-11-19 20:19:10 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:19:10 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:10 | D | sum error = [ 19.8090, 21.0842, 22.4185, 23.8393, 25.3314] +24-11-19 20:19:10 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:19:10 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:10 | D | sum error = [ 26.9098, 28.5594, 30.2880, 32.1128, 34.0182] +24-11-19 20:19:10 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:19:10 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:10 | D | sum error = [ 36.0202, 38.1140, 40.3162, 42.6223, 45.0299] +24-11-19 20:19:10 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:19:10 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:10 | D | sum error = [ 47.5572, 50.2104, 52.9702, 55.8783, 58.8931] +24-11-19 20:19:10 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:19:10 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:10 | D | sum error = [ 62.0542, 65.3535, 68.7929, 72.3759, 76.0969] +24-11-19 20:19:10 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:19:10 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:10 | D | sum error = [ 79.9847, 84.0279, 88.2250, 92.5872, 97.1252] +24-11-19 20:19:10 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:19:10 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:10 | D | sum error = [ 101.8349, 106.7303, 111.8022, 117.0760, 122.5243] +24-11-19 20:19:10 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:19:10 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:10 | D | sum error = [ 128.1689, 134.0313, 140.0604, 146.3186, 152.7752] +24-11-19 20:19:10 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:19:10 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:10 | D | sum error = [ 159.4462, 166.3312, 173.4393, 180.7639, 188.3113] +24-11-19 20:19:10 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:19:10 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:10 | D | sum error = [ 196.0788, 204.0869, 212.3197, 220.7854, 229.4890] +24-11-19 20:19:10 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:19:10 | D | + error = [3.4423] +24-11-19 20:19:10 | D | - Calibrating model.layers.2.mlp.down_proj.weight +24-11-19 20:19:10 | D | + w: sint8 +24-11-19 20:19:10 | D | + x: None +24-11-19 20:19:10 | D | + y: None +24-11-19 20:19:10 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:10 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:19:10 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:19:11 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:19:11 | D | - range ratio = [ 1.0000] +24-11-19 20:19:11 | D | sum error = [ 0.2038] +24-11-19 20:19:11 | D | best error = [ 0.2038] +24-11-19 20:19:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:12 | D | sum error = [ 0.2016, 0.2005, 0.1993, 0.1987, 0.1989] +24-11-19 20:19:12 | D | best error = [ 0.1971, 0.1936, 0.1911, 0.1893, 0.1878] +24-11-19 20:19:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:12 | D | sum error = [ 0.1998, 0.2017, 0.2041, 0.2081, 0.2135] +24-11-19 20:19:12 | D | best error = [ 0.1865, 0.1856, 0.1848, 0.1843, 0.1839] +24-11-19 20:19:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:12 | D | sum error = [ 0.2197, 0.2286, 0.2376, 0.2494, 0.2627] +24-11-19 20:19:12 | D | best error = [ 0.1837, 0.1836, 0.1834, 0.1834, 0.1834] +24-11-19 20:19:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:12 | D | sum error = [ 0.2775, 0.2946, 0.3129, 0.3337, 0.3564] +24-11-19 20:19:12 | D | best error = [ 0.1834, 0.1834, 0.1834, 0.1834, 0.1834] +24-11-19 20:19:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:12 | D | sum error = [ 0.3810, 0.4075, 0.4364, 0.4673, 0.5008] +24-11-19 20:19:12 | D | best error = [ 0.1834, 0.1834, 0.1834, 0.1834, 0.1834] +24-11-19 20:19:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:12 | D | sum error = [ 0.5359, 0.5737, 0.6138, 0.6569, 0.7024] +24-11-19 20:19:12 | D | best error = [ 0.1834, 0.1834, 0.1834, 0.1834, 0.1834] +24-11-19 20:19:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:12 | D | sum error = [ 0.7508, 0.8025, 0.8569, 0.9149, 0.9760] +24-11-19 20:19:12 | D | best error = [ 0.1834, 0.1834, 0.1834, 0.1834, 0.1834] +24-11-19 20:19:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:12 | D | sum error = [ 1.0410, 1.1094, 1.1818, 1.2581, 1.3391] +24-11-19 20:19:12 | D | best error = [ 0.1834, 0.1834, 0.1834, 0.1834, 0.1834] +24-11-19 20:19:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:12 | D | sum error = [ 1.4241, 1.5141, 1.6087, 1.7086, 1.8137] +24-11-19 20:19:12 | D | best error = [ 0.1834, 0.1834, 0.1834, 0.1834, 0.1834] +24-11-19 20:19:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:12 | D | sum error = [ 1.9247, 2.0411, 2.1637, 2.2925, 2.4279] +24-11-19 20:19:12 | D | best error = [ 0.1834, 0.1834, 0.1834, 0.1834, 0.1834] +24-11-19 20:19:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:12 | D | sum error = [ 2.5698, 2.7187, 2.8752, 3.0396, 3.2117] +24-11-19 20:19:12 | D | best error = [ 0.1834, 0.1834, 0.1834, 0.1834, 0.1834] +24-11-19 20:19:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:12 | D | sum error = [ 3.3918, 3.5806, 3.7786, 3.9858, 4.2022] +24-11-19 20:19:12 | D | best error = [ 0.1834, 0.1834, 0.1834, 0.1834, 0.1834] +24-11-19 20:19:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:12 | D | sum error = [ 4.4283, 4.6653, 4.9129, 5.1704, 5.4388] +24-11-19 20:19:12 | D | best error = [ 0.1834, 0.1834, 0.1834, 0.1834, 0.1834] +24-11-19 20:19:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:12 | D | sum error = [ 5.7195, 6.0123, 6.3167, 6.6338, 6.9634] +24-11-19 20:19:12 | D | best error = [ 0.1834, 0.1834, 0.1834, 0.1834, 0.1834] +24-11-19 20:19:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:12 | D | sum error = [ 7.3064, 7.6625, 8.0323, 8.4153, 8.8125] +24-11-19 20:19:12 | D | best error = [ 0.1834, 0.1834, 0.1834, 0.1834, 0.1834] +24-11-19 20:19:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:12 | D | sum error = [ 9.2237, 9.6493, 10.0894, 10.5441, 11.0134] +24-11-19 20:19:12 | D | best error = [ 0.1834, 0.1834, 0.1834, 0.1834, 0.1834] +24-11-19 20:19:12 | D | + error = [0.1834] +24-11-19 20:19:12 | D | - Quantizing model.layers.2.self_attn.q_proj.weight +24-11-19 20:19:13 | D | - Quantizing model.layers.2.self_attn.k_proj.weight +24-11-19 20:19:14 | D | - Quantizing model.layers.2.self_attn.v_proj.weight +24-11-19 20:19:15 | D | - Quantizing model.layers.2.self_attn.o_proj.weight +24-11-19 20:19:16 | D | - Quantizing model.layers.2.mlp.up_proj.weight +24-11-19 20:19:17 | D | - Quantizing model.layers.2.mlp.gate_proj.weight +24-11-19 20:19:20 | D | - Quantizing model.layers.2.mlp.down_proj.weight +24-11-19 20:19:32 | D | - Quantizing layer model.layers.3 +24-11-19 20:19:32 | D | - Calibrating model.layers.3.self_attn.q_proj.weight +24-11-19 20:19:32 | D | + w: sint8 +24-11-19 20:19:32 | D | + x: None +24-11-19 20:19:32 | D | + y: None +24-11-19 20:19:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:19:32 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:19:32 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:19:32 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:19:33 | D | - range ratio = [ 1.0000] +24-11-19 20:19:33 | D | sum error = [ 1.1055] +24-11-19 20:19:33 | D | best error = [ 1.1055] +24-11-19 20:19:45 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:45 | D | sum error = [ 1.1156, 1.0772, 1.0741, 1.1090, 1.1268] +24-11-19 20:19:45 | D | best error = [ 1.1055, 1.0772, 1.0741, 1.0741, 1.0741] +24-11-19 20:19:45 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:45 | D | sum error = [ 1.1442, 1.2365, 1.2808, 1.3658, 1.4654] +24-11-19 20:19:45 | D | best error = [ 1.0741, 1.0741, 1.0741, 1.0741, 1.0741] +24-11-19 20:19:45 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:45 | D | sum error = [ 1.6353, 1.7151, 1.9571, 2.1122, 2.3104] +24-11-19 20:19:45 | D | best error = [ 1.0741, 1.0741, 1.0741, 1.0741, 1.0741] +24-11-19 20:19:45 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:45 | D | sum error = [ 2.5293, 2.8034, 3.1227, 3.4915, 3.8073] +24-11-19 20:19:45 | D | best error = [ 1.0741, 1.0741, 1.0741, 1.0741, 1.0741] +24-11-19 20:19:45 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:45 | D | sum error = [ 4.2943, 4.6106, 5.1893, 5.7691, 6.4314] +24-11-19 20:19:45 | D | best error = [ 1.0741, 1.0741, 1.0741, 1.0741, 1.0741] +24-11-19 20:19:45 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:45 | D | sum error = [ 7.1324, 7.7783, 8.5686, 9.5444, 10.4652] +24-11-19 20:19:45 | D | best error = [ 1.0741, 1.0741, 1.0741, 1.0741, 1.0741] +24-11-19 20:19:45 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:45 | D | sum error = [ 11.5416, 12.6819, 13.9390, 15.4202, 16.8944] +24-11-19 20:19:45 | D | best error = [ 1.0741, 1.0741, 1.0741, 1.0741, 1.0741] +24-11-19 20:19:45 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:45 | D | sum error = [ 18.6441, 20.5994, 22.5251, 24.7753, 27.1898] +24-11-19 20:19:45 | D | best error = [ 1.0741, 1.0741, 1.0741, 1.0741, 1.0741] +24-11-19 20:19:45 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:45 | D | sum error = [ 29.9430, 32.8527, 35.9474, 39.4365, 43.0673] +24-11-19 20:19:45 | D | best error = [ 1.0741, 1.0741, 1.0741, 1.0741, 1.0741] +24-11-19 20:19:45 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:45 | D | sum error = [ 46.9778, 51.1661, 55.6808, 60.6011, 65.9176] +24-11-19 20:19:45 | D | best error = [ 1.0741, 1.0741, 1.0741, 1.0741, 1.0741] +24-11-19 20:19:45 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:45 | D | sum error = [ 71.5784, 77.7031, 84.2551, 91.1533, 98.4940] +24-11-19 20:19:45 | D | best error = [ 1.0741, 1.0741, 1.0741, 1.0741, 1.0741] +24-11-19 20:19:45 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:45 | D | sum error = [ 106.7037, 115.3690, 124.5905, 134.5340, 145.1366] +24-11-19 20:19:45 | D | best error = [ 1.0741, 1.0741, 1.0741, 1.0741, 1.0741] +24-11-19 20:19:45 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:45 | D | sum error = [ 156.4736, 168.5120, 181.3090, 194.9927, 209.5774] +24-11-19 20:19:45 | D | best error = [ 1.0741, 1.0741, 1.0741, 1.0741, 1.0741] +24-11-19 20:19:45 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:45 | D | sum error = [ 225.1221, 241.4499, 258.8696, 277.3873, 296.7834] +24-11-19 20:19:45 | D | best error = [ 1.0741, 1.0741, 1.0741, 1.0741, 1.0741] +24-11-19 20:19:45 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:45 | D | sum error = [ 317.4137, 338.9944, 361.5882, 385.0018, 409.3877] +24-11-19 20:19:45 | D | best error = [ 1.0741, 1.0741, 1.0741, 1.0741, 1.0741] +24-11-19 20:19:45 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:45 | D | sum error = [ 434.3245, 459.9752, 486.1449, 512.3996, 538.9567] +24-11-19 20:19:45 | D | best error = [ 1.0741, 1.0741, 1.0741, 1.0741, 1.0741] +24-11-19 20:19:45 | D | + error = [1.0741] +24-11-19 20:19:45 | D | - Calibrating model.layers.3.self_attn.k_proj.weight +24-11-19 20:19:45 | D | + w: sint8 +24-11-19 20:19:45 | D | + x: None +24-11-19 20:19:45 | D | + y: None +24-11-19 20:19:45 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:19:45 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:19:45 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:19:46 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:19:46 | D | - range ratio = [ 1.0000] +24-11-19 20:19:46 | D | sum error = [ 1.3411] +24-11-19 20:19:46 | D | best error = [ 1.3411] +24-11-19 20:19:58 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:58 | D | sum error = [ 1.2114, 1.1686, 1.3102, 1.2476, 1.2224] +24-11-19 20:19:58 | D | best error = [ 1.2114, 1.1686, 1.1686, 1.1686, 1.1686] +24-11-19 20:19:58 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:58 | D | sum error = [ 1.5801, 1.5165, 1.6760, 1.5546, 1.5816] +24-11-19 20:19:58 | D | best error = [ 1.1686, 1.1686, 1.1686, 1.1686, 1.1686] +24-11-19 20:19:58 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:58 | D | sum error = [ 1.7499, 2.2148, 2.1976, 2.5111, 2.6618] +24-11-19 20:19:58 | D | best error = [ 1.1686, 1.1686, 1.1686, 1.1686, 1.1686] +24-11-19 20:19:58 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:58 | D | sum error = [ 3.2816, 3.6783, 3.8460, 4.1151, 4.6214] +24-11-19 20:19:58 | D | best error = [ 1.1686, 1.1686, 1.1686, 1.1686, 1.1686] +24-11-19 20:19:58 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:58 | D | sum error = [ 4.9856, 5.7198, 6.1661, 6.8071, 7.3779] +24-11-19 20:19:58 | D | best error = [ 1.1686, 1.1686, 1.1686, 1.1686, 1.1686] +24-11-19 20:19:58 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:58 | D | sum error = [ 8.0790, 8.6269, 9.6058, 10.2730, 11.3696] +24-11-19 20:19:58 | D | best error = [ 1.1686, 1.1686, 1.1686, 1.1686, 1.1686] +24-11-19 20:19:58 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:58 | D | sum error = [ 12.6308, 13.7685, 14.9801, 16.6022, 18.0019] +24-11-19 20:19:58 | D | best error = [ 1.1686, 1.1686, 1.1686, 1.1686, 1.1686] +24-11-19 20:19:58 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:58 | D | sum error = [ 19.8324, 21.4353, 23.2059, 25.9134, 27.9476] +24-11-19 20:19:58 | D | best error = [ 1.1686, 1.1686, 1.1686, 1.1686, 1.1686] +24-11-19 20:19:58 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:58 | D | sum error = [ 30.7925, 33.4451, 36.3890, 39.7461, 43.7532] +24-11-19 20:19:58 | D | best error = [ 1.1686, 1.1686, 1.1686, 1.1686, 1.1686] +24-11-19 20:19:58 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:58 | D | sum error = [ 47.4625, 51.9920, 56.5609, 61.9249, 67.4201] +24-11-19 20:19:58 | D | best error = [ 1.1686, 1.1686, 1.1686, 1.1686, 1.1686] +24-11-19 20:19:58 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:58 | D | sum error = [ 73.8435, 80.9193, 87.6393, 95.4428, 104.5417] +24-11-19 20:19:58 | D | best error = [ 1.1686, 1.1686, 1.1686, 1.1686, 1.1686] +24-11-19 20:19:58 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:58 | D | sum error = [ 112.9993, 122.3618, 132.9889, 144.0894, 156.1201] +24-11-19 20:19:58 | D | best error = [ 1.1686, 1.1686, 1.1686, 1.1686, 1.1686] +24-11-19 20:19:58 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:58 | D | sum error = [ 168.5712, 182.0933, 196.7744, 211.1234, 227.8025] +24-11-19 20:19:58 | D | best error = [ 1.1686, 1.1686, 1.1686, 1.1686, 1.1686] +24-11-19 20:19:58 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:58 | D | sum error = [ 244.3147, 261.8899, 281.1877, 301.0215, 321.4927] +24-11-19 20:19:58 | D | best error = [ 1.1686, 1.1686, 1.1686, 1.1686, 1.1686] +24-11-19 20:19:58 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:58 | D | sum error = [ 344.5449, 367.0466, 391.0514, 416.3515, 441.6656] +24-11-19 20:19:58 | D | best error = [ 1.1686, 1.1686, 1.1686, 1.1686, 1.1686] +24-11-19 20:19:58 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:58 | D | sum error = [ 467.0992, 492.7882, 520.4985, 545.4416, 570.8772] +24-11-19 20:19:58 | D | best error = [ 1.1686, 1.1686, 1.1686, 1.1686, 1.1686] +24-11-19 20:19:58 | D | + error = [1.1686] +24-11-19 20:19:58 | D | - Calibrating model.layers.3.self_attn.v_proj.weight +24-11-19 20:19:58 | D | + w: sint8 +24-11-19 20:19:58 | D | + x: None +24-11-19 20:19:58 | D | + y: None +24-11-19 20:19:58 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:58 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:19:58 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:19:58 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:19:58 | D | - range ratio = [ 1.0000] +24-11-19 20:19:58 | D | sum error = [ 1.1203] +24-11-19 20:19:58 | D | best error = [ 1.1203] +24-11-19 20:19:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:59 | D | sum error = [ 1.1037, 1.1016, 1.1164, 1.1282, 1.1468] +24-11-19 20:19:59 | D | best error = [ 1.0294, 0.9987, 0.9838, 0.9763, 0.9715] +24-11-19 20:19:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:59 | D | sum error = [ 1.1882, 1.2076, 1.2720, 1.3148, 1.3862] +24-11-19 20:19:59 | D | best error = [ 0.9689, 0.9682, 0.9676, 0.9675, 0.9675] +24-11-19 20:19:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:59 | D | sum error = [ 1.4580, 1.5488, 1.6524, 1.7698, 1.8788] +24-11-19 20:19:59 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 20:19:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:59 | D | sum error = [ 2.0078, 2.1547, 2.2972, 2.4628, 2.6344] +24-11-19 20:19:59 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 20:19:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:59 | D | sum error = [ 2.8178, 3.0162, 3.2292, 3.4558, 3.6962] +24-11-19 20:19:59 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 20:19:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:59 | D | sum error = [ 3.9541, 4.2227, 4.5093, 4.8165, 5.1365] +24-11-19 20:19:59 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 20:19:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:59 | D | sum error = [ 5.4758, 5.8410, 6.2143, 6.6094, 7.0352] +24-11-19 20:19:59 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 20:19:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:59 | D | sum error = [ 7.4763, 7.9475, 8.4232, 8.9330, 9.4622] +24-11-19 20:19:59 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 20:19:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:59 | D | sum error = [ 10.0351, 10.6158, 11.2389, 11.8917, 12.5844] +24-11-19 20:19:59 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 20:19:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:59 | D | sum error = [ 13.3003, 14.0558, 14.8524, 15.6790, 16.5371] +24-11-19 20:19:59 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 20:19:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:59 | D | sum error = [ 17.4492, 18.3948, 19.3818, 20.4117, 21.4898] +24-11-19 20:19:59 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 20:19:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:59 | D | sum error = [ 22.6142, 23.7922, 25.0128, 26.2962, 27.6228] +24-11-19 20:19:59 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 20:19:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:59 | D | sum error = [ 29.0135, 30.4521, 31.9524, 33.5144, 35.1372] +24-11-19 20:19:59 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 20:19:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:59 | D | sum error = [ 36.8221, 38.5728, 40.3781, 42.2519, 44.1970] +24-11-19 20:19:59 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 20:19:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:59 | D | sum error = [ 46.2032, 48.2843, 50.4306, 52.6444, 54.9214] +24-11-19 20:19:59 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 20:19:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:59 | D | sum error = [ 57.2722, 59.6944, 62.1819, 64.7449, 67.3933] +24-11-19 20:19:59 | D | best error = [ 0.9675, 0.9675, 0.9675, 0.9675, 0.9675] +24-11-19 20:19:59 | D | + error = [0.9675] +24-11-19 20:19:59 | D | - Calibrating model.layers.3.self_attn.o_proj.weight +24-11-19 20:19:59 | D | + w: sint8 +24-11-19 20:19:59 | D | + x: None +24-11-19 20:19:59 | D | + y: None +24-11-19 20:19:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:59 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:19:59 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:19:59 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:19:59 | D | - range ratio = [ 1.0000] +24-11-19 20:19:59 | D | sum error = [ 0.1798] +24-11-19 20:19:59 | D | best error = [ 0.1798] +24-11-19 20:19:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:59 | D | sum error = [ 0.1783, 0.1778, 0.1776, 0.1780, 0.1803] +24-11-19 20:19:59 | D | best error = [ 0.1672, 0.1616, 0.1581, 0.1557, 0.1541] +24-11-19 20:19:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:59 | D | sum error = [ 0.1819, 0.1861, 0.1906, 0.1969, 0.2034] +24-11-19 20:19:59 | D | best error = [ 0.1530, 0.1522, 0.1516, 0.1513, 0.1511] +24-11-19 20:19:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:59 | D | sum error = [ 0.2122, 0.2227, 0.2331, 0.2460, 0.2596] +24-11-19 20:19:59 | D | best error = [ 0.1509, 0.1508, 0.1507, 0.1506, 0.1505] +24-11-19 20:19:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:59 | D | sum error = [ 0.2748, 0.2923, 0.3100, 0.3300, 0.3510] +24-11-19 20:19:59 | D | best error = [ 0.1505, 0.1505, 0.1505, 0.1505, 0.1505] +24-11-19 20:19:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:59 | D | sum error = [ 0.3739, 0.3982, 0.4251, 0.4532, 0.4831] +24-11-19 20:19:59 | D | best error = [ 0.1505, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:19:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:59 | D | sum error = [ 0.5150, 0.5485, 0.5843, 0.6229, 0.6643] +24-11-19 20:19:59 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:19:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:59 | D | sum error = [ 0.7066, 0.7525, 0.8002, 0.8511, 0.9046] +24-11-19 20:19:59 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:19:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:59 | D | sum error = [ 0.9613, 1.0209, 1.0847, 1.1515, 1.2215] +24-11-19 20:19:59 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:19:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:59 | D | sum error = [ 1.2950, 1.3729, 1.4554, 1.5424, 1.6334] +24-11-19 20:19:59 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:19:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:59 | D | sum error = [ 1.7296, 1.8310, 1.9371, 2.0490, 2.1673] +24-11-19 20:19:59 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:19:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:59 | D | sum error = [ 2.2900, 2.4204, 2.5567, 2.6999, 2.8498] +24-11-19 20:19:59 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:19:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:59 | D | sum error = [ 3.0071, 3.1714, 3.3442, 3.5249, 3.7142] +24-11-19 20:19:59 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:19:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:59 | D | sum error = [ 3.9118, 4.1190, 4.3356, 4.5611, 4.7968] +24-11-19 20:19:59 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:19:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:59 | D | sum error = [ 5.0423, 5.2985, 5.5654, 5.8441, 6.1338] +24-11-19 20:19:59 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:19:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:59 | D | sum error = [ 6.4362, 6.7501, 7.0767, 7.4161, 7.7682] +24-11-19 20:19:59 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:19:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:59 | D | sum error = [ 8.1327, 8.5108, 8.9023, 9.3075, 9.7266] +24-11-19 20:19:59 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:19:59 | D | + error = [0.1504] +24-11-19 20:19:59 | D | - Calibrating model.layers.3.mlp.up_proj.weight +24-11-19 20:19:59 | D | + w: sint8 +24-11-19 20:19:59 | D | + x: None +24-11-19 20:19:59 | D | + y: None +24-11-19 20:19:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:59 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:19:59 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:00 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:00 | D | - range ratio = [ 1.0000] +24-11-19 20:20:00 | D | sum error = [ 0.2313] +24-11-19 20:20:00 | D | best error = [ 0.2313] +24-11-19 20:20:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:01 | D | sum error = [ 0.2293, 0.2287, 0.2289, 0.2321, 0.2363] +24-11-19 20:20:01 | D | best error = [ 0.2163, 0.2085, 0.2049, 0.2029, 0.2018] +24-11-19 20:20:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:01 | D | sum error = [ 0.2429, 0.2516, 0.2612, 0.2730, 0.2878] +24-11-19 20:20:01 | D | best error = [ 0.2013, 0.2011, 0.2011, 0.2010, 0.2010] +24-11-19 20:20:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:01 | D | sum error = [ 0.3050, 0.3225, 0.3432, 0.3672, 0.3917] +24-11-19 20:20:01 | D | best error = [ 0.2010, 0.2010, 0.2010, 0.2010, 0.2010] +24-11-19 20:20:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:01 | D | sum error = [ 0.4192, 0.4489, 0.4809, 0.5157, 0.5518] +24-11-19 20:20:01 | D | best error = [ 0.2010, 0.2010, 0.2010, 0.2010, 0.2010] +24-11-19 20:20:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:01 | D | sum error = [ 0.5910, 0.6333, 0.6782, 0.7247, 0.7744] +24-11-19 20:20:01 | D | best error = [ 0.2010, 0.2010, 0.2010, 0.2010, 0.2010] +24-11-19 20:20:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:01 | D | sum error = [ 0.8278, 0.8833, 0.9427, 1.0041, 1.0706] +24-11-19 20:20:01 | D | best error = [ 0.2010, 0.2010, 0.2010, 0.2010, 0.2010] +24-11-19 20:20:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:01 | D | sum error = [ 1.1377, 1.2119, 1.2889, 1.3688, 1.4546] +24-11-19 20:20:01 | D | best error = [ 0.2010, 0.2010, 0.2010, 0.2010, 0.2010] +24-11-19 20:20:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:01 | D | sum error = [ 1.5431, 1.6365, 1.7356, 1.8397, 1.9472] +24-11-19 20:20:01 | D | best error = [ 0.2010, 0.2010, 0.2010, 0.2010, 0.2010] +24-11-19 20:20:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:01 | D | sum error = [ 2.0588, 2.1779, 2.3024, 2.4314, 2.5662] +24-11-19 20:20:01 | D | best error = [ 0.2010, 0.2010, 0.2010, 0.2010, 0.2010] +24-11-19 20:20:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:01 | D | sum error = [ 2.7085, 2.8546, 3.0073, 3.1688, 3.3362] +24-11-19 20:20:01 | D | best error = [ 0.2010, 0.2010, 0.2010, 0.2010, 0.2010] +24-11-19 20:20:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:01 | D | sum error = [ 3.5071, 3.6885, 3.8757, 4.0736, 4.2730] +24-11-19 20:20:01 | D | best error = [ 0.2010, 0.2010, 0.2010, 0.2010, 0.2010] +24-11-19 20:20:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:01 | D | sum error = [ 4.4829, 4.7013, 4.9269, 5.1589, 5.4012] +24-11-19 20:20:01 | D | best error = [ 0.2010, 0.2010, 0.2010, 0.2010, 0.2010] +24-11-19 20:20:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:01 | D | sum error = [ 5.6536, 5.9127, 6.1773, 6.4547, 6.7416] +24-11-19 20:20:01 | D | best error = [ 0.2010, 0.2010, 0.2010, 0.2010, 0.2010] +24-11-19 20:20:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:01 | D | sum error = [ 7.0373, 7.3393, 7.6542, 7.9757, 8.3082] +24-11-19 20:20:01 | D | best error = [ 0.2010, 0.2010, 0.2010, 0.2010, 0.2010] +24-11-19 20:20:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:01 | D | sum error = [ 8.6519, 9.0035, 9.3654, 9.7378, 10.1257] +24-11-19 20:20:01 | D | best error = [ 0.2010, 0.2010, 0.2010, 0.2010, 0.2010] +24-11-19 20:20:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:01 | D | sum error = [ 10.5168, 10.9178, 11.3391, 11.7687, 12.2056] +24-11-19 20:20:01 | D | best error = [ 0.2010, 0.2010, 0.2010, 0.2010, 0.2010] +24-11-19 20:20:01 | D | + error = [0.2010] +24-11-19 20:20:01 | D | - Calibrating model.layers.3.mlp.gate_proj.weight +24-11-19 20:20:01 | D | + w: sint8 +24-11-19 20:20:01 | D | + x: None +24-11-19 20:20:01 | D | + y: None +24-11-19 20:20:01 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:01 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:01 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:01 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:01 | D | - range ratio = [ 1.0000] +24-11-19 20:20:01 | D | sum error = [ 4.7581] +24-11-19 20:20:01 | D | best error = [ 4.7581] +24-11-19 20:20:02 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:02 | D | sum error = [ 4.7182, 4.7078, 4.7268, 4.7779, 4.8630] +24-11-19 20:20:02 | D | best error = [ 4.3769, 4.2407, 4.1709, 4.1338, 4.1129] +24-11-19 20:20:02 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:02 | D | sum error = [ 4.9952, 5.1655, 5.3742, 5.6178, 5.9281] +24-11-19 20:20:02 | D | best error = [ 4.1044, 4.1003, 4.0990, 4.0987, 4.0986] +24-11-19 20:20:02 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:02 | D | sum error = [ 6.2572, 6.6471, 7.0700, 7.5706, 8.0796] +24-11-19 20:20:02 | D | best error = [ 4.0986, 4.0986, 4.0986, 4.0986, 4.0986] +24-11-19 20:20:02 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:02 | D | sum error = [ 8.6596, 9.2767, 9.9357, 10.6675, 11.4207] +24-11-19 20:20:02 | D | best error = [ 4.0986, 4.0986, 4.0986, 4.0986, 4.0986] +24-11-19 20:20:02 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:02 | D | sum error = [ 12.2457, 13.1134, 14.0545, 15.0399, 16.0880] +24-11-19 20:20:02 | D | best error = [ 4.0986, 4.0986, 4.0986, 4.0986, 4.0986] +24-11-19 20:20:02 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:02 | D | sum error = [ 17.1968, 18.3753, 19.6288, 20.9564, 22.3440] +24-11-19 20:20:02 | D | best error = [ 4.0986, 4.0986, 4.0986, 4.0986, 4.0986] +24-11-19 20:20:02 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:02 | D | sum error = [ 23.8259, 25.3891, 27.0401, 28.7878, 30.6369] +24-11-19 20:20:02 | D | best error = [ 4.0986, 4.0986, 4.0986, 4.0986, 4.0986] +24-11-19 20:20:02 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:02 | D | sum error = [ 32.5807, 34.6029, 36.7707, 39.0538, 41.4398] +24-11-19 20:20:02 | D | best error = [ 4.0986, 4.0986, 4.0986, 4.0986, 4.0986] +24-11-19 20:20:02 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:02 | D | sum error = [ 43.9659, 46.6411, 49.4273, 52.3524, 55.4594] +24-11-19 20:20:02 | D | best error = [ 4.0986, 4.0986, 4.0986, 4.0986, 4.0986] +24-11-19 20:20:02 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:02 | D | sum error = [ 58.7172, 62.1333, 65.7031, 69.4860, 73.4453] +24-11-19 20:20:02 | D | best error = [ 4.0986, 4.0986, 4.0986, 4.0986, 4.0986] +24-11-19 20:20:02 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:02 | D | sum error = [ 77.5855, 81.9400, 86.5079, 91.2894, 96.2997] +24-11-19 20:20:02 | D | best error = [ 4.0986, 4.0986, 4.0986, 4.0986, 4.0986] +24-11-19 20:20:02 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:02 | D | sum error = [ 101.5235, 107.0091, 112.7269, 118.7115, 124.9550] +24-11-19 20:20:02 | D | best error = [ 4.0986, 4.0986, 4.0986, 4.0986, 4.0986] +24-11-19 20:20:02 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:02 | D | sum error = [ 131.4754, 138.2566, 145.3415, 152.7096, 160.3889] +24-11-19 20:20:02 | D | best error = [ 4.0986, 4.0986, 4.0986, 4.0986, 4.0986] +24-11-19 20:20:02 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:02 | D | sum error = [ 168.3595, 176.6476, 185.2668, 194.2131, 203.5036] +24-11-19 20:20:02 | D | best error = [ 4.0986, 4.0986, 4.0986, 4.0986, 4.0986] +24-11-19 20:20:02 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:02 | D | sum error = [ 213.1349, 223.1237, 233.4683, 244.1866, 255.2510] +24-11-19 20:20:02 | D | best error = [ 4.0986, 4.0986, 4.0986, 4.0986, 4.0986] +24-11-19 20:20:02 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:02 | D | sum error = [ 266.6924, 278.4964, 290.6603, 303.1896, 316.0923] +24-11-19 20:20:02 | D | best error = [ 4.0986, 4.0986, 4.0986, 4.0986, 4.0986] +24-11-19 20:20:02 | D | + error = [4.0986] +24-11-19 20:20:02 | D | - Calibrating model.layers.3.mlp.down_proj.weight +24-11-19 20:20:02 | D | + w: sint8 +24-11-19 20:20:02 | D | + x: None +24-11-19 20:20:02 | D | + y: None +24-11-19 20:20:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:02 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:03 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:03 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:03 | D | - range ratio = [ 1.0000] +24-11-19 20:20:03 | D | sum error = [ 0.2832] +24-11-19 20:20:03 | D | best error = [ 0.2832] +24-11-19 20:20:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:04 | D | sum error = [ 0.2810, 0.2784, 0.2773, 0.2765, 0.2772] +24-11-19 20:20:04 | D | best error = [ 0.2736, 0.2684, 0.2650, 0.2627, 0.2608] +24-11-19 20:20:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:04 | D | sum error = [ 0.2789, 0.2824, 0.2876, 0.2941, 0.3025] +24-11-19 20:20:04 | D | best error = [ 0.2593, 0.2583, 0.2576, 0.2571, 0.2568] +24-11-19 20:20:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:04 | D | sum error = [ 0.3138, 0.3268, 0.3422, 0.3610, 0.3820] +24-11-19 20:20:04 | D | best error = [ 0.2566, 0.2565, 0.2564, 0.2564, 0.2564] +24-11-19 20:20:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:04 | D | sum error = [ 0.4051, 0.4312, 0.4602, 0.4917, 0.5262] +24-11-19 20:20:04 | D | best error = [ 0.2564, 0.2564, 0.2564, 0.2564, 0.2564] +24-11-19 20:20:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:04 | D | sum error = [ 0.5638, 0.6046, 0.6479, 0.6941, 0.7439] +24-11-19 20:20:04 | D | best error = [ 0.2564, 0.2564, 0.2564, 0.2564, 0.2564] +24-11-19 20:20:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:04 | D | sum error = [ 0.7967, 0.8529, 0.9127, 0.9761, 1.0436] +24-11-19 20:20:04 | D | best error = [ 0.2564, 0.2564, 0.2564, 0.2564, 0.2564] +24-11-19 20:20:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:04 | D | sum error = [ 1.1153, 1.1912, 1.2709, 1.3562, 1.4452] +24-11-19 20:20:04 | D | best error = [ 0.2564, 0.2564, 0.2564, 0.2564, 0.2564] +24-11-19 20:20:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:04 | D | sum error = [ 1.5398, 1.6396, 1.7447, 1.8562, 1.9736] +24-11-19 20:20:04 | D | best error = [ 0.2564, 0.2564, 0.2564, 0.2564, 0.2564] +24-11-19 20:20:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:04 | D | sum error = [ 2.0975, 2.2278, 2.3655, 2.5097, 2.6623] +24-11-19 20:20:04 | D | best error = [ 0.2564, 0.2564, 0.2564, 0.2564, 0.2564] +24-11-19 20:20:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:04 | D | sum error = [ 2.8225, 2.9907, 3.1675, 3.3535, 3.5488] +24-11-19 20:20:04 | D | best error = [ 0.2564, 0.2564, 0.2564, 0.2564, 0.2564] +24-11-19 20:20:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:04 | D | sum error = [ 3.7533, 3.9678, 4.1927, 4.4281, 4.6750] +24-11-19 20:20:04 | D | best error = [ 0.2564, 0.2564, 0.2564, 0.2564, 0.2564] +24-11-19 20:20:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:04 | D | sum error = [ 4.9333, 5.2040, 5.4861, 5.7813, 6.0898] +24-11-19 20:20:04 | D | best error = [ 0.2564, 0.2564, 0.2564, 0.2564, 0.2564] +24-11-19 20:20:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:04 | D | sum error = [ 6.4121, 6.7487, 7.0987, 7.4629, 7.8430] +24-11-19 20:20:04 | D | best error = [ 0.2564, 0.2564, 0.2564, 0.2564, 0.2564] +24-11-19 20:20:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:04 | D | sum error = [ 8.2394, 8.6520, 9.0810, 9.5273, 9.9905] +24-11-19 20:20:04 | D | best error = [ 0.2564, 0.2564, 0.2564, 0.2564, 0.2564] +24-11-19 20:20:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:04 | D | sum error = [ 10.4716, 10.9708, 11.4878, 12.0239, 12.5782] +24-11-19 20:20:04 | D | best error = [ 0.2564, 0.2564, 0.2564, 0.2564, 0.2564] +24-11-19 20:20:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:04 | D | sum error = [ 13.1515, 13.7443, 14.3562, 14.9883, 15.6396] +24-11-19 20:20:04 | D | best error = [ 0.2564, 0.2564, 0.2564, 0.2564, 0.2564] +24-11-19 20:20:04 | D | + error = [0.2564] +24-11-19 20:20:04 | D | - Quantizing model.layers.3.self_attn.q_proj.weight +24-11-19 20:20:05 | D | - Quantizing model.layers.3.self_attn.k_proj.weight +24-11-19 20:20:06 | D | - Quantizing model.layers.3.self_attn.v_proj.weight +24-11-19 20:20:07 | D | - Quantizing model.layers.3.self_attn.o_proj.weight +24-11-19 20:20:08 | D | - Quantizing model.layers.3.mlp.up_proj.weight +24-11-19 20:20:09 | D | - Quantizing model.layers.3.mlp.gate_proj.weight +24-11-19 20:20:11 | D | - Quantizing model.layers.3.mlp.down_proj.weight +24-11-19 20:20:24 | D | - Quantizing layer model.layers.4 +24-11-19 20:20:24 | D | - Calibrating model.layers.4.self_attn.q_proj.weight +24-11-19 20:20:24 | D | + w: sint8 +24-11-19 20:20:24 | D | + x: None +24-11-19 20:20:24 | D | + y: None +24-11-19 20:20:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:20:24 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:20:24 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:20:25 | D | + finished calculating the original outputs, ram usage: 13.2 +24-11-19 20:20:25 | D | - range ratio = [ 1.0000] +24-11-19 20:20:25 | D | sum error = [ 1.4114] +24-11-19 20:20:25 | D | best error = [ 1.4114] +24-11-19 20:20:38 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:38 | D | sum error = [ 1.4183, 1.4442, 1.4254, 1.4537, 1.4810] +24-11-19 20:20:38 | D | best error = [ 1.4114, 1.4114, 1.4114, 1.4114, 1.4114] +24-11-19 20:20:38 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:38 | D | sum error = [ 1.5089, 1.6255, 1.7040, 1.7767, 1.8870] +24-11-19 20:20:38 | D | best error = [ 1.4114, 1.4114, 1.4114, 1.4114, 1.4114] +24-11-19 20:20:38 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:38 | D | sum error = [ 2.0058, 2.2288, 2.4216, 2.6005, 2.9344] +24-11-19 20:20:38 | D | best error = [ 1.4114, 1.4114, 1.4114, 1.4114, 1.4114] +24-11-19 20:20:38 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:38 | D | sum error = [ 3.2322, 3.4718, 3.9965, 4.3638, 4.8252] +24-11-19 20:20:38 | D | best error = [ 1.4114, 1.4114, 1.4114, 1.4114, 1.4114] +24-11-19 20:20:38 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:38 | D | sum error = [ 5.4093, 6.0385, 6.8668, 7.5909, 8.3746] +24-11-19 20:20:38 | D | best error = [ 1.4114, 1.4114, 1.4114, 1.4114, 1.4114] +24-11-19 20:20:38 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:38 | D | sum error = [ 9.2858, 10.5247, 11.7671, 13.1077, 14.6650] +24-11-19 20:20:38 | D | best error = [ 1.4114, 1.4114, 1.4114, 1.4114, 1.4114] +24-11-19 20:20:38 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:38 | D | sum error = [ 16.1906, 17.8985, 19.8873, 21.9841, 24.1580] +24-11-19 20:20:38 | D | best error = [ 1.4114, 1.4114, 1.4114, 1.4114, 1.4114] +24-11-19 20:20:38 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:38 | D | sum error = [ 26.5539, 29.2738, 31.9406, 34.8931, 38.0586] +24-11-19 20:20:38 | D | best error = [ 1.4114, 1.4114, 1.4114, 1.4114, 1.4114] +24-11-19 20:20:38 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:38 | D | sum error = [ 41.3402, 44.9709, 48.7581, 52.8667, 57.1879] +24-11-19 20:20:38 | D | best error = [ 1.4114, 1.4114, 1.4114, 1.4114, 1.4114] +24-11-19 20:20:38 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:38 | D | sum error = [ 62.2102, 67.3816, 72.8497, 78.7616, 85.0703] +24-11-19 20:20:38 | D | best error = [ 1.4114, 1.4114, 1.4114, 1.4114, 1.4114] +24-11-19 20:20:38 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:38 | D | sum error = [ 91.6064, 98.5436, 105.9344, 113.7122, 122.0458] +24-11-19 20:20:38 | D | best error = [ 1.4114, 1.4114, 1.4114, 1.4114, 1.4114] +24-11-19 20:20:38 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:38 | D | sum error = [ 131.0396, 140.5003, 150.3769, 161.0506, 172.2873] +24-11-19 20:20:38 | D | best error = [ 1.4114, 1.4114, 1.4114, 1.4114, 1.4114] +24-11-19 20:20:38 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:38 | D | sum error = [ 184.3015, 196.7477, 209.9656, 224.0562, 238.8404] +24-11-19 20:20:38 | D | best error = [ 1.4114, 1.4114, 1.4114, 1.4114, 1.4114] +24-11-19 20:20:38 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:38 | D | sum error = [ 254.1738, 270.4356, 287.1986, 304.6951, 322.9989] +24-11-19 20:20:38 | D | best error = [ 1.4114, 1.4114, 1.4114, 1.4114, 1.4114] +24-11-19 20:20:38 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:38 | D | sum error = [ 341.7131, 361.1648, 381.5011, 402.1102, 423.4248] +24-11-19 20:20:38 | D | best error = [ 1.4114, 1.4114, 1.4114, 1.4114, 1.4114] +24-11-19 20:20:38 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:38 | D | sum error = [ 445.3089, 467.5326, 490.4008, 513.3875, 536.6278] +24-11-19 20:20:38 | D | best error = [ 1.4114, 1.4114, 1.4114, 1.4114, 1.4114] +24-11-19 20:20:38 | D | + error = [1.4114] +24-11-19 20:20:38 | D | - Calibrating model.layers.4.self_attn.k_proj.weight +24-11-19 20:20:38 | D | + w: sint8 +24-11-19 20:20:38 | D | + x: None +24-11-19 20:20:38 | D | + y: None +24-11-19 20:20:38 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:20:38 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:38 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:38 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:39 | D | - range ratio = [ 1.0000] +24-11-19 20:20:39 | D | sum error = [ 1.5034] +24-11-19 20:20:39 | D | best error = [ 1.5034] +24-11-19 20:20:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:51 | D | sum error = [ 1.4734, 1.4924, 1.5917, 1.6019, 1.5116] +24-11-19 20:20:51 | D | best error = [ 1.4734, 1.4734, 1.4734, 1.4734, 1.4734] +24-11-19 20:20:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:51 | D | sum error = [ 1.6617, 1.7449, 1.7771, 1.7686, 2.0054] +24-11-19 20:20:51 | D | best error = [ 1.4734, 1.4734, 1.4734, 1.4734, 1.4734] +24-11-19 20:20:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:51 | D | sum error = [ 2.1621, 2.1998, 3.3514, 2.9621, 3.2168] +24-11-19 20:20:51 | D | best error = [ 1.4734, 1.4734, 1.4734, 1.4734, 1.4734] +24-11-19 20:20:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:51 | D | sum error = [ 3.7641, 3.9227, 4.3634, 5.1429, 5.6205] +24-11-19 20:20:51 | D | best error = [ 1.4734, 1.4734, 1.4734, 1.4734, 1.4734] +24-11-19 20:20:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:51 | D | sum error = [ 5.8837, 6.7187, 7.1629, 8.5484, 9.0757] +24-11-19 20:20:51 | D | best error = [ 1.4734, 1.4734, 1.4734, 1.4734, 1.4734] +24-11-19 20:20:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:51 | D | sum error = [ 9.9128, 10.3615, 11.7380, 13.0737, 14.2328] +24-11-19 20:20:51 | D | best error = [ 1.4734, 1.4734, 1.4734, 1.4734, 1.4734] +24-11-19 20:20:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:51 | D | sum error = [ 15.7398, 17.3509, 19.5294, 21.1914, 23.4298] +24-11-19 20:20:51 | D | best error = [ 1.4734, 1.4734, 1.4734, 1.4734, 1.4734] +24-11-19 20:20:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:51 | D | sum error = [ 25.5700, 27.7923, 30.1204, 33.0693, 35.8367] +24-11-19 20:20:51 | D | best error = [ 1.4734, 1.4734, 1.4734, 1.4734, 1.4734] +24-11-19 20:20:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:51 | D | sum error = [ 39.1957, 42.3863, 45.6611, 49.6185, 54.3053] +24-11-19 20:20:51 | D | best error = [ 1.4734, 1.4734, 1.4734, 1.4734, 1.4734] +24-11-19 20:20:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:51 | D | sum error = [ 58.6673, 63.1994, 67.9115, 74.0316, 80.0237] +24-11-19 20:20:51 | D | best error = [ 1.4734, 1.4734, 1.4734, 1.4734, 1.4734] +24-11-19 20:20:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:51 | D | sum error = [ 86.3336, 92.7257, 99.7778, 107.9378, 115.6059] +24-11-19 20:20:51 | D | best error = [ 1.4734, 1.4734, 1.4734, 1.4734, 1.4734] +24-11-19 20:20:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:51 | D | sum error = [ 124.5532, 133.9730, 143.1749, 155.2766, 166.6096] +24-11-19 20:20:51 | D | best error = [ 1.4734, 1.4734, 1.4734, 1.4734, 1.4734] +24-11-19 20:20:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:51 | D | sum error = [ 178.6848, 190.5042, 204.1494, 218.6903, 232.9213] +24-11-19 20:20:51 | D | best error = [ 1.4734, 1.4734, 1.4734, 1.4734, 1.4734] +24-11-19 20:20:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:51 | D | sum error = [ 248.4167, 264.3573, 281.2063, 300.0521, 318.1705] +24-11-19 20:20:51 | D | best error = [ 1.4734, 1.4734, 1.4734, 1.4734, 1.4734] +24-11-19 20:20:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:51 | D | sum error = [ 337.5338, 357.1777, 377.5993, 400.9041, 422.8444] +24-11-19 20:20:51 | D | best error = [ 1.4734, 1.4734, 1.4734, 1.4734, 1.4734] +24-11-19 20:20:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:51 | D | sum error = [ 444.9834, 468.5529, 492.4008, 517.5762, 540.8455] +24-11-19 20:20:51 | D | best error = [ 1.4734, 1.4734, 1.4734, 1.4734, 1.4734] +24-11-19 20:20:51 | D | + error = [1.4734] +24-11-19 20:20:51 | D | - Calibrating model.layers.4.self_attn.v_proj.weight +24-11-19 20:20:51 | D | + w: sint8 +24-11-19 20:20:51 | D | + x: None +24-11-19 20:20:51 | D | + y: None +24-11-19 20:20:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:51 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:51 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:51 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:51 | D | - range ratio = [ 1.0000] +24-11-19 20:20:51 | D | sum error = [ 1.0559] +24-11-19 20:20:51 | D | best error = [ 1.0559] +24-11-19 20:20:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:52 | D | sum error = [ 1.0357, 1.0335, 1.0431, 1.0469, 1.0658] +24-11-19 20:20:52 | D | best error = [ 0.9714, 0.9430, 0.9296, 0.9223, 0.9184] +24-11-19 20:20:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:52 | D | sum error = [ 1.0973, 1.1391, 1.1874, 1.2498, 1.3196] +24-11-19 20:20:52 | D | best error = [ 0.9167, 0.9160, 0.9157, 0.9157, 0.9157] +24-11-19 20:20:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:52 | D | sum error = [ 1.3911, 1.4980, 1.5854, 1.7004, 1.8231] +24-11-19 20:20:52 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:20:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:52 | D | sum error = [ 1.9658, 2.0960, 2.2572, 2.4121, 2.5987] +24-11-19 20:20:52 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:20:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:52 | D | sum error = [ 2.7800, 2.9869, 3.1974, 3.4214, 3.6612] +24-11-19 20:20:52 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:20:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:52 | D | sum error = [ 3.9064, 4.1849, 4.4682, 4.7680, 5.0882] +24-11-19 20:20:52 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:20:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:52 | D | sum error = [ 5.4306, 5.7683, 6.1446, 6.5423, 6.9585] +24-11-19 20:20:52 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:20:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:52 | D | sum error = [ 7.3823, 7.8469, 8.3167, 8.8235, 9.3479] +24-11-19 20:20:52 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:20:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:52 | D | sum error = [ 9.9036, 10.4908, 11.1057, 11.7557, 12.4314] +24-11-19 20:20:52 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:20:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:52 | D | sum error = [ 13.1425, 13.8893, 14.6721, 15.5031, 16.3637] +24-11-19 20:20:52 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:20:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:52 | D | sum error = [ 17.2651, 18.2130, 19.1941, 20.2229, 21.3006] +24-11-19 20:20:52 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:20:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:52 | D | sum error = [ 22.4257, 23.6095, 24.8415, 26.1335, 27.4705] +24-11-19 20:20:52 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:20:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:52 | D | sum error = [ 28.8632, 30.3240, 31.8374, 33.4097, 35.0457] +24-11-19 20:20:52 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:20:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:52 | D | sum error = [ 36.7511, 38.5113, 40.3462, 42.2494, 44.2121] +24-11-19 20:20:52 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:20:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:52 | D | sum error = [ 46.2465, 48.3511, 50.5310, 52.7821, 55.1046] +24-11-19 20:20:52 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:20:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:52 | D | sum error = [ 57.4964, 59.9645, 62.5078, 65.1175, 67.8078] +24-11-19 20:20:52 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:20:52 | D | + error = [0.9157] +24-11-19 20:20:52 | D | - Calibrating model.layers.4.self_attn.o_proj.weight +24-11-19 20:20:52 | D | + w: sint8 +24-11-19 20:20:52 | D | + x: None +24-11-19 20:20:52 | D | + y: None +24-11-19 20:20:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:52 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:52 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:52 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:52 | D | - range ratio = [ 1.0000] +24-11-19 20:20:52 | D | sum error = [ 0.2424] +24-11-19 20:20:52 | D | best error = [ 0.2424] +24-11-19 20:20:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:52 | D | sum error = [ 0.2397, 0.2394, 0.2387, 0.2408, 0.2439] +24-11-19 20:20:52 | D | best error = [ 0.2238, 0.2157, 0.2109, 0.2080, 0.2060] +24-11-19 20:20:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:52 | D | sum error = [ 0.2474, 0.2528, 0.2608, 0.2704, 0.2812] +24-11-19 20:20:52 | D | best error = [ 0.2045, 0.2036, 0.2029, 0.2025, 0.2022] +24-11-19 20:20:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:52 | D | sum error = [ 0.2929, 0.3088, 0.3251, 0.3436, 0.3638] +24-11-19 20:20:52 | D | best error = [ 0.2020, 0.2018, 0.2017, 0.2017, 0.2016] +24-11-19 20:20:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:52 | D | sum error = [ 0.3862, 0.4096, 0.4356, 0.4635, 0.4936] +24-11-19 20:20:52 | D | best error = [ 0.2016, 0.2016, 0.2015, 0.2015, 0.2015] +24-11-19 20:20:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:52 | D | sum error = [ 0.5252, 0.5593, 0.5951, 0.6347, 0.6748] +24-11-19 20:20:52 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:20:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:52 | D | sum error = [ 0.7187, 0.7640, 0.8129, 0.8635, 0.9179] +24-11-19 20:20:52 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:20:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:52 | D | sum error = [ 0.9745, 1.0344, 1.0980, 1.1651, 1.2354] +24-11-19 20:20:52 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:20:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:52 | D | sum error = [ 1.3106, 1.3883, 1.4719, 1.5584, 1.6491] +24-11-19 20:20:52 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:20:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:52 | D | sum error = [ 1.7451, 1.8459, 1.9512, 2.0620, 2.1792] +24-11-19 20:20:52 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:20:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:52 | D | sum error = [ 2.3019, 2.4300, 2.5640, 2.7044, 2.8525] +24-11-19 20:20:52 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:20:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:52 | D | sum error = [ 3.0070, 3.1694, 3.3398, 3.5174, 3.7036] +24-11-19 20:20:52 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:20:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:52 | D | sum error = [ 3.8981, 4.1001, 4.3123, 4.5345, 4.7664] +24-11-19 20:20:52 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:20:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:52 | D | sum error = [ 5.0079, 5.2598, 5.5223, 5.7955, 6.0805] +24-11-19 20:20:52 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:20:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:52 | D | sum error = [ 6.3773, 6.6856, 7.0067, 7.3419, 7.6891] +24-11-19 20:20:52 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:20:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:52 | D | sum error = [ 8.0501, 8.4249, 8.8145, 9.2188, 9.6371] +24-11-19 20:20:52 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:20:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:52 | D | sum error = [ 10.0705, 10.5193, 10.9854, 11.4669, 11.9648] +24-11-19 20:20:52 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:20:52 | D | + error = [0.2015] +24-11-19 20:20:52 | D | - Calibrating model.layers.4.mlp.up_proj.weight +24-11-19 20:20:52 | D | + w: sint8 +24-11-19 20:20:52 | D | + x: None +24-11-19 20:20:52 | D | + y: None +24-11-19 20:20:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:52 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:53 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:53 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:53 | D | - range ratio = [ 1.0000] +24-11-19 20:20:53 | D | sum error = [ 0.2324] +24-11-19 20:20:53 | D | best error = [ 0.2324] +24-11-19 20:20:54 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:54 | D | sum error = [ 0.2306, 0.2303, 0.2308, 0.2339, 0.2382] +24-11-19 20:20:54 | D | best error = [ 0.2185, 0.2113, 0.2077, 0.2058, 0.2048] +24-11-19 20:20:54 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:54 | D | sum error = [ 0.2439, 0.2524, 0.2626, 0.2756, 0.2902] +24-11-19 20:20:54 | D | best error = [ 0.2043, 0.2041, 0.2040, 0.2040, 0.2040] +24-11-19 20:20:54 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:54 | D | sum error = [ 0.3065, 0.3258, 0.3474, 0.3707, 0.3962] +24-11-19 20:20:54 | D | best error = [ 0.2040, 0.2040, 0.2040, 0.2040, 0.2040] +24-11-19 20:20:54 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:54 | D | sum error = [ 0.4242, 0.4551, 0.4871, 0.5223, 0.5602] +24-11-19 20:20:54 | D | best error = [ 0.2040, 0.2040, 0.2040, 0.2040, 0.2040] +24-11-19 20:20:54 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:54 | D | sum error = [ 0.5994, 0.6413, 0.6871, 0.7347, 0.7839] +24-11-19 20:20:54 | D | best error = [ 0.2040, 0.2040, 0.2040, 0.2040, 0.2040] +24-11-19 20:20:54 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:54 | D | sum error = [ 0.8381, 0.8943, 0.9543, 1.0181, 1.0849] +24-11-19 20:20:54 | D | best error = [ 0.2040, 0.2040, 0.2040, 0.2040, 0.2040] +24-11-19 20:20:54 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:54 | D | sum error = [ 1.1537, 1.2293, 1.3076, 1.3887, 1.4757] +24-11-19 20:20:54 | D | best error = [ 0.2040, 0.2040, 0.2040, 0.2040, 0.2040] +24-11-19 20:20:54 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:54 | D | sum error = [ 1.5661, 1.6614, 1.7609, 1.8669, 1.9766] +24-11-19 20:20:54 | D | best error = [ 0.2040, 0.2040, 0.2040, 0.2040, 0.2040] +24-11-19 20:20:54 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:54 | D | sum error = [ 2.0915, 2.2139, 2.3403, 2.4714, 2.6105] +24-11-19 20:20:54 | D | best error = [ 0.2040, 0.2040, 0.2040, 0.2040, 0.2040] +24-11-19 20:20:54 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:54 | D | sum error = [ 2.7568, 2.9075, 3.0658, 3.2311, 3.4032] +24-11-19 20:20:54 | D | best error = [ 0.2040, 0.2040, 0.2040, 0.2040, 0.2040] +24-11-19 20:20:54 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:54 | D | sum error = [ 3.5829, 3.7724, 3.9664, 4.1716, 4.3801] +24-11-19 20:20:54 | D | best error = [ 0.2040, 0.2040, 0.2040, 0.2040, 0.2040] +24-11-19 20:20:54 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:54 | D | sum error = [ 4.6001, 4.8277, 5.0652, 5.3127, 5.5658] +24-11-19 20:20:54 | D | best error = [ 0.2040, 0.2040, 0.2040, 0.2040, 0.2040] +24-11-19 20:20:54 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:54 | D | sum error = [ 5.8289, 6.1014, 6.3828, 6.6785, 6.9814] +24-11-19 20:20:54 | D | best error = [ 0.2040, 0.2040, 0.2040, 0.2040, 0.2040] +24-11-19 20:20:54 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:54 | D | sum error = [ 7.2907, 7.6151, 7.9472, 8.2941, 8.6466] +24-11-19 20:20:54 | D | best error = [ 0.2040, 0.2040, 0.2040, 0.2040, 0.2040] +24-11-19 20:20:54 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:54 | D | sum error = [ 9.0128, 9.3901, 9.7840, 10.1791, 10.5951] +24-11-19 20:20:54 | D | best error = [ 0.2040, 0.2040, 0.2040, 0.2040, 0.2040] +24-11-19 20:20:54 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:54 | D | sum error = [ 11.0162, 11.4514, 11.9016, 12.3642, 12.8379] +24-11-19 20:20:54 | D | best error = [ 0.2040, 0.2040, 0.2040, 0.2040, 0.2040] +24-11-19 20:20:54 | D | + error = [0.2040] +24-11-19 20:20:54 | D | - Calibrating model.layers.4.mlp.gate_proj.weight +24-11-19 20:20:54 | D | + w: sint8 +24-11-19 20:20:54 | D | + x: None +24-11-19 20:20:54 | D | + y: None +24-11-19 20:20:54 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:54 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:54 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:54 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:54 | D | - range ratio = [ 1.0000] +24-11-19 20:20:54 | D | sum error = [ 5.4959] +24-11-19 20:20:54 | D | best error = [ 5.4959] +24-11-19 20:20:55 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:55 | D | sum error = [ 5.4532, 5.4446, 5.4728, 5.5371, 5.6339] +24-11-19 20:20:55 | D | best error = [ 5.0892, 4.9443, 4.8683, 4.8261, 4.8047] +24-11-19 20:20:55 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:55 | D | sum error = [ 5.7897, 5.9666, 6.2184, 6.5259, 6.8785] +24-11-19 20:20:55 | D | best error = [ 4.7952, 4.7910, 4.7899, 4.7895, 4.7895] +24-11-19 20:20:55 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:55 | D | sum error = [ 7.2653, 7.7113, 8.2113, 8.7681, 9.3669] +24-11-19 20:20:55 | D | best error = [ 4.7895, 4.7895, 4.7895, 4.7895, 4.7895] +24-11-19 20:20:55 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:55 | D | sum error = [ 10.0429, 10.7753, 11.5431, 12.3932, 13.2799] +24-11-19 20:20:55 | D | best error = [ 4.7895, 4.7895, 4.7895, 4.7895, 4.7895] +24-11-19 20:20:55 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:55 | D | sum error = [ 14.2492, 15.2755, 16.3795, 17.5404, 18.7776] +24-11-19 20:20:55 | D | best error = [ 4.7895, 4.7895, 4.7895, 4.7895, 4.7895] +24-11-19 20:20:55 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:55 | D | sum error = [ 20.1101, 21.5070, 22.9977, 24.5692, 26.2362] +24-11-19 20:20:55 | D | best error = [ 4.7895, 4.7895, 4.7895, 4.7895, 4.7895] +24-11-19 20:20:55 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:55 | D | sum error = [ 27.9979, 29.8765, 31.8544, 33.9419, 36.1606] +24-11-19 20:20:55 | D | best error = [ 4.7895, 4.7895, 4.7895, 4.7895, 4.7895] +24-11-19 20:20:55 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:55 | D | sum error = [ 38.4974, 40.9800, 43.5956, 46.3717, 49.2891] +24-11-19 20:20:55 | D | best error = [ 4.7895, 4.7895, 4.7895, 4.7895, 4.7895] +24-11-19 20:20:55 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:55 | D | sum error = [ 52.3773, 55.6452, 59.0779, 62.7140, 66.5548] +24-11-19 20:20:55 | D | best error = [ 4.7895, 4.7895, 4.7895, 4.7895, 4.7895] +24-11-19 20:20:55 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:55 | D | sum error = [ 70.5959, 74.8511, 79.3310, 84.0502, 89.0147] +24-11-19 20:20:55 | D | best error = [ 4.7895, 4.7895, 4.7895, 4.7895, 4.7895] +24-11-19 20:20:55 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:55 | D | sum error = [ 94.2501, 99.7583, 105.5416, 111.6333, 118.0231] +24-11-19 20:20:55 | D | best error = [ 4.7895, 4.7895, 4.7895, 4.7895, 4.7895] +24-11-19 20:20:55 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:55 | D | sum error = [ 124.7438, 131.7877, 139.1750, 146.9240, 155.0295] +24-11-19 20:20:55 | D | best error = [ 4.7895, 4.7895, 4.7895, 4.7895, 4.7895] +24-11-19 20:20:55 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:55 | D | sum error = [ 163.5261, 172.4092, 181.6922, 191.3892, 201.5035] +24-11-19 20:20:55 | D | best error = [ 4.7895, 4.7895, 4.7895, 4.7895, 4.7895] +24-11-19 20:20:55 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:55 | D | sum error = [ 212.0531, 223.0437, 234.5044, 246.4420, 258.8403] +24-11-19 20:20:55 | D | best error = [ 4.7895, 4.7895, 4.7895, 4.7895, 4.7895] +24-11-19 20:20:55 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:55 | D | sum error = [ 271.7360, 285.1444, 299.0181, 313.4308, 328.3485] +24-11-19 20:20:55 | D | best error = [ 4.7895, 4.7895, 4.7895, 4.7895, 4.7895] +24-11-19 20:20:55 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:55 | D | sum error = [ 343.7767, 359.6998, 376.1427, 393.1063, 410.5890] +24-11-19 20:20:55 | D | best error = [ 4.7895, 4.7895, 4.7895, 4.7895, 4.7895] +24-11-19 20:20:55 | D | + error = [4.7895] +24-11-19 20:20:56 | D | - Calibrating model.layers.4.mlp.down_proj.weight +24-11-19 20:20:56 | D | + w: sint8 +24-11-19 20:20:56 | D | + x: None +24-11-19 20:20:56 | D | + y: None +24-11-19 20:20:56 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:56 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:56 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:56 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:56 | D | - range ratio = [ 1.0000] +24-11-19 20:20:56 | D | sum error = [ 0.3675] +24-11-19 20:20:56 | D | best error = [ 0.3675] +24-11-19 20:20:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:57 | D | sum error = [ 0.3638, 0.3613, 0.3595, 0.3586, 0.3597] +24-11-19 20:20:57 | D | best error = [ 0.3543, 0.3479, 0.3434, 0.3400, 0.3376] +24-11-19 20:20:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:57 | D | sum error = [ 0.3622, 0.3669, 0.3726, 0.3817, 0.3926] +24-11-19 20:20:57 | D | best error = [ 0.3359, 0.3346, 0.3335, 0.3329, 0.3324] +24-11-19 20:20:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:57 | D | sum error = [ 0.4073, 0.4240, 0.4444, 0.4676, 0.4949] +24-11-19 20:20:57 | D | best error = [ 0.3322, 0.3321, 0.3320, 0.3320, 0.3319] +24-11-19 20:20:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:57 | D | sum error = [ 0.5245, 0.5576, 0.5944, 0.6354, 0.6792] +24-11-19 20:20:57 | D | best error = [ 0.3319, 0.3319, 0.3319, 0.3319, 0.3319] +24-11-19 20:20:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:57 | D | sum error = [ 0.7272, 0.7783, 0.8340, 0.8930, 0.9572] +24-11-19 20:20:57 | D | best error = [ 0.3319, 0.3319, 0.3319, 0.3319, 0.3319] +24-11-19 20:20:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:57 | D | sum error = [ 1.0241, 1.0964, 1.1719, 1.2541, 1.3400] +24-11-19 20:20:57 | D | best error = [ 0.3319, 0.3319, 0.3319, 0.3319, 0.3319] +24-11-19 20:20:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:57 | D | sum error = [ 1.4319, 1.5282, 1.6313, 1.7405, 1.8552] +24-11-19 20:20:57 | D | best error = [ 0.3319, 0.3319, 0.3319, 0.3319, 0.3319] +24-11-19 20:20:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:57 | D | sum error = [ 1.9763, 2.1047, 2.2401, 2.3833, 2.5333] +24-11-19 20:20:57 | D | best error = [ 0.3319, 0.3319, 0.3319, 0.3319, 0.3319] +24-11-19 20:20:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:57 | D | sum error = [ 2.6922, 2.8586, 3.0352, 3.2198, 3.4150] +24-11-19 20:20:57 | D | best error = [ 0.3319, 0.3319, 0.3319, 0.3319, 0.3319] +24-11-19 20:20:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:57 | D | sum error = [ 3.6195, 3.8340, 4.0601, 4.2972, 4.5459] +24-11-19 20:20:57 | D | best error = [ 0.3319, 0.3319, 0.3319, 0.3319, 0.3319] +24-11-19 20:20:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:57 | D | sum error = [ 4.8064, 5.0801, 5.3662, 5.6661, 5.9797] +24-11-19 20:20:57 | D | best error = [ 0.3319, 0.3319, 0.3319, 0.3319, 0.3319] +24-11-19 20:20:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:57 | D | sum error = [ 6.3082, 6.6510, 7.0097, 7.3832, 7.7734] +24-11-19 20:20:57 | D | best error = [ 0.3319, 0.3319, 0.3319, 0.3319, 0.3319] +24-11-19 20:20:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:57 | D | sum error = [ 8.1805, 8.6053, 9.0480, 9.5084, 9.9874] +24-11-19 20:20:57 | D | best error = [ 0.3319, 0.3319, 0.3319, 0.3319, 0.3319] +24-11-19 20:20:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:57 | D | sum error = [ 10.4861, 11.0057, 11.5460, 12.1064, 12.6881] +24-11-19 20:20:57 | D | best error = [ 0.3319, 0.3319, 0.3319, 0.3319, 0.3319] +24-11-19 20:20:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:57 | D | sum error = [ 13.2915, 13.9170, 14.5649, 15.2356, 15.9296] +24-11-19 20:20:57 | D | best error = [ 0.3319, 0.3319, 0.3319, 0.3319, 0.3319] +24-11-19 20:20:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:57 | D | sum error = [ 16.6473, 17.3898, 18.1567, 18.9486, 19.7648] +24-11-19 20:20:57 | D | best error = [ 0.3319, 0.3319, 0.3319, 0.3319, 0.3319] +24-11-19 20:20:57 | D | + error = [0.3319] +24-11-19 20:20:57 | D | - Quantizing model.layers.4.self_attn.q_proj.weight +24-11-19 20:20:58 | D | - Quantizing model.layers.4.self_attn.k_proj.weight +24-11-19 20:20:59 | D | - Quantizing model.layers.4.self_attn.v_proj.weight +24-11-19 20:21:00 | D | - Quantizing model.layers.4.self_attn.o_proj.weight +24-11-19 20:21:01 | D | - Quantizing model.layers.4.mlp.up_proj.weight +24-11-19 20:21:03 | D | - Quantizing model.layers.4.mlp.gate_proj.weight +24-11-19 20:21:05 | D | - Quantizing model.layers.4.mlp.down_proj.weight +24-11-19 20:21:18 | D | - Quantizing layer model.layers.5 +24-11-19 20:21:18 | D | - Calibrating model.layers.5.self_attn.q_proj.weight +24-11-19 20:21:18 | D | + w: sint8 +24-11-19 20:21:18 | D | + x: None +24-11-19 20:21:18 | D | + y: None +24-11-19 20:21:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:21:18 | D | + finished parsing calibration arguments, ram usage: 13.1 +24-11-19 20:21:18 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:21:18 | D | + finished calculating the original outputs, ram usage: 13.2 +24-11-19 20:21:18 | D | - range ratio = [ 1.0000] +24-11-19 20:21:18 | D | sum error = [ 2.0475] +24-11-19 20:21:18 | D | best error = [ 2.0475] +24-11-19 20:21:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:31 | D | sum error = [ 2.1165, 2.0693, 2.0549, 2.0332, 2.0946] +24-11-19 20:21:31 | D | best error = [ 2.0475, 2.0475, 2.0475, 2.0332, 2.0332] +24-11-19 20:21:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:31 | D | sum error = [ 2.1222, 2.2282, 2.3391, 2.4668, 2.5057] +24-11-19 20:21:31 | D | best error = [ 2.0332, 2.0332, 2.0332, 2.0332, 2.0332] +24-11-19 20:21:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:31 | D | sum error = [ 2.7285, 2.9073, 3.0881, 3.4870, 3.6774] +24-11-19 20:21:31 | D | best error = [ 2.0332, 2.0332, 2.0332, 2.0332, 2.0332] +24-11-19 20:21:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:31 | D | sum error = [ 3.8683, 4.2157, 4.7094, 5.0308, 5.4591] +24-11-19 20:21:31 | D | best error = [ 2.0332, 2.0332, 2.0332, 2.0332, 2.0332] +24-11-19 20:21:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:31 | D | sum error = [ 5.9108, 6.3932, 7.0272, 7.5791, 8.1254] +24-11-19 20:21:31 | D | best error = [ 2.0332, 2.0332, 2.0332, 2.0332, 2.0332] +24-11-19 20:21:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:31 | D | sum error = [ 8.7989, 9.6811, 10.5853, 11.5589, 12.4471] +24-11-19 20:21:31 | D | best error = [ 2.0332, 2.0332, 2.0332, 2.0332, 2.0332] +24-11-19 20:21:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:31 | D | sum error = [ 13.5801, 14.6982, 16.1174, 17.5805, 19.1412] +24-11-19 20:21:31 | D | best error = [ 2.0332, 2.0332, 2.0332, 2.0332, 2.0332] +24-11-19 20:21:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:31 | D | sum error = [ 20.8466, 22.7050, 24.7735, 26.9264, 29.2975] +24-11-19 20:21:31 | D | best error = [ 2.0332, 2.0332, 2.0332, 2.0332, 2.0332] +24-11-19 20:21:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:31 | D | sum error = [ 31.8685, 34.7194, 37.5335, 40.7584, 44.0762] +24-11-19 20:21:31 | D | best error = [ 2.0332, 2.0332, 2.0332, 2.0332, 2.0332] +24-11-19 20:21:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:31 | D | sum error = [ 47.7691, 51.7487, 56.0040, 60.6084, 65.4805] +24-11-19 20:21:31 | D | best error = [ 2.0332, 2.0332, 2.0332, 2.0332, 2.0332] +24-11-19 20:21:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:31 | D | sum error = [ 70.8873, 76.4330, 82.4822, 88.8476, 95.6685] +24-11-19 20:21:31 | D | best error = [ 2.0332, 2.0332, 2.0332, 2.0332, 2.0332] +24-11-19 20:21:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:31 | D | sum error = [ 102.9282, 110.7627, 119.2002, 128.1375, 137.6917] +24-11-19 20:21:31 | D | best error = [ 2.0332, 2.0332, 2.0332, 2.0332, 2.0332] +24-11-19 20:21:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:31 | D | sum error = [ 147.9139, 158.8155, 170.2742, 182.4475, 195.2717] +24-11-19 20:21:31 | D | best error = [ 2.0332, 2.0332, 2.0332, 2.0332, 2.0332] +24-11-19 20:21:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:31 | D | sum error = [ 208.8624, 223.3755, 238.6105, 254.6995, 271.7349] +24-11-19 20:21:31 | D | best error = [ 2.0332, 2.0332, 2.0332, 2.0332, 2.0332] +24-11-19 20:21:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:31 | D | sum error = [ 289.4120, 308.0187, 327.3133, 347.4475, 368.1503] +24-11-19 20:21:31 | D | best error = [ 2.0332, 2.0332, 2.0332, 2.0332, 2.0332] +24-11-19 20:21:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:31 | D | sum error = [ 389.4598, 411.1747, 433.5118, 456.1691, 479.1287] +24-11-19 20:21:31 | D | best error = [ 2.0332, 2.0332, 2.0332, 2.0332, 2.0332] +24-11-19 20:21:31 | D | + error = [2.0332] +24-11-19 20:21:31 | D | - Calibrating model.layers.5.self_attn.k_proj.weight +24-11-19 20:21:31 | D | + w: sint8 +24-11-19 20:21:31 | D | + x: None +24-11-19 20:21:31 | D | + y: None +24-11-19 20:21:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:21:31 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:31 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:32 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:32 | D | - range ratio = [ 1.0000] +24-11-19 20:21:32 | D | sum error = [ 2.2222] +24-11-19 20:21:32 | D | best error = [ 2.2222] +24-11-19 20:21:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:46 | D | sum error = [ 2.0576, 2.1150, 2.1559, 2.2646, 2.1059] +24-11-19 20:21:46 | D | best error = [ 2.0576, 2.0576, 2.0576, 2.0576, 2.0576] +24-11-19 20:21:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:46 | D | sum error = [ 2.2252, 2.3518, 2.2883, 2.5583, 2.8292] +24-11-19 20:21:46 | D | best error = [ 2.0576, 2.0576, 2.0576, 2.0576, 2.0576] +24-11-19 20:21:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:46 | D | sum error = [ 3.0976, 3.3778, 4.1140, 4.2457, 4.6170] +24-11-19 20:21:46 | D | best error = [ 2.0576, 2.0576, 2.0576, 2.0576, 2.0576] +24-11-19 20:21:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:46 | D | sum error = [ 4.7374, 5.4477, 5.8958, 5.9414, 7.4453] +24-11-19 20:21:46 | D | best error = [ 2.0576, 2.0576, 2.0576, 2.0576, 2.0576] +24-11-19 20:21:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:46 | D | sum error = [ 7.3010, 8.2781, 9.4010, 10.1742, 10.5765] +24-11-19 20:21:46 | D | best error = [ 2.0576, 2.0576, 2.0576, 2.0576, 2.0576] +24-11-19 20:21:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:46 | D | sum error = [ 11.4974, 13.0280, 13.7042, 14.7840, 16.1718] +24-11-19 20:21:46 | D | best error = [ 2.0576, 2.0576, 2.0576, 2.0576, 2.0576] +24-11-19 20:21:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:46 | D | sum error = [ 17.4307, 18.7807, 20.7195, 22.2964, 24.5159] +24-11-19 20:21:46 | D | best error = [ 2.0576, 2.0576, 2.0576, 2.0576, 2.0576] +24-11-19 20:21:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:46 | D | sum error = [ 26.0810, 28.4395, 30.6463, 33.6423, 36.2819] +24-11-19 20:21:46 | D | best error = [ 2.0576, 2.0576, 2.0576, 2.0576, 2.0576] +24-11-19 20:21:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:46 | D | sum error = [ 38.9769, 42.2196, 44.8174, 48.6012, 52.4227] +24-11-19 20:21:46 | D | best error = [ 2.0576, 2.0576, 2.0576, 2.0576, 2.0576] +24-11-19 20:21:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:46 | D | sum error = [ 56.7189, 60.8207, 65.6506, 70.5245, 76.0024] +24-11-19 20:21:46 | D | best error = [ 2.0576, 2.0576, 2.0576, 2.0576, 2.0576] +24-11-19 20:21:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:46 | D | sum error = [ 81.6871, 88.4795, 95.1061, 102.4086, 110.1180] +24-11-19 20:21:46 | D | best error = [ 2.0576, 2.0576, 2.0576, 2.0576, 2.0576] +24-11-19 20:21:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:46 | D | sum error = [ 118.8686, 127.0912, 136.5196, 146.1146, 156.1955] +24-11-19 20:21:46 | D | best error = [ 2.0576, 2.0576, 2.0576, 2.0576, 2.0576] +24-11-19 20:21:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:46 | D | sum error = [ 167.6320, 179.2835, 191.3623, 204.2660, 218.2074] +24-11-19 20:21:46 | D | best error = [ 2.0576, 2.0576, 2.0576, 2.0576, 2.0576] +24-11-19 20:21:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:46 | D | sum error = [ 232.3117, 247.0310, 263.2776, 279.1788, 296.6160] +24-11-19 20:21:46 | D | best error = [ 2.0576, 2.0576, 2.0576, 2.0576, 2.0576] +24-11-19 20:21:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:46 | D | sum error = [ 315.4970, 333.3297, 353.8030, 373.9968, 394.5301] +24-11-19 20:21:46 | D | best error = [ 2.0576, 2.0576, 2.0576, 2.0576, 2.0576] +24-11-19 20:21:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:46 | D | sum error = [ 416.0696, 437.8749, 459.6424, 482.5026, 504.9607] +24-11-19 20:21:46 | D | best error = [ 2.0576, 2.0576, 2.0576, 2.0576, 2.0576] +24-11-19 20:21:46 | D | + error = [2.0576] +24-11-19 20:21:46 | D | - Calibrating model.layers.5.self_attn.v_proj.weight +24-11-19 20:21:46 | D | + w: sint8 +24-11-19 20:21:46 | D | + x: None +24-11-19 20:21:46 | D | + y: None +24-11-19 20:21:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:46 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:46 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:46 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:46 | D | - range ratio = [ 1.0000] +24-11-19 20:21:46 | D | sum error = [ 1.0032] +24-11-19 20:21:46 | D | best error = [ 1.0032] +24-11-19 20:21:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:46 | D | sum error = [ 1.0006, 0.9913, 1.0059, 1.0055, 1.0221] +24-11-19 20:21:46 | D | best error = [ 0.9390, 0.9116, 0.8993, 0.8917, 0.8879] +24-11-19 20:21:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:46 | D | sum error = [ 1.0523, 1.0928, 1.1407, 1.1925, 1.2558] +24-11-19 20:21:46 | D | best error = [ 0.8859, 0.8852, 0.8850, 0.8850, 0.8849] +24-11-19 20:21:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:46 | D | sum error = [ 1.3232, 1.4095, 1.4920, 1.5863, 1.7087] +24-11-19 20:21:46 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:21:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:46 | D | sum error = [ 1.8305, 1.9485, 2.0877, 2.2413, 2.4037] +24-11-19 20:21:46 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:21:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:46 | D | sum error = [ 2.5822, 2.7649, 2.9590, 3.1654, 3.3878] +24-11-19 20:21:46 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:21:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:46 | D | sum error = [ 3.6183, 3.8645, 4.1260, 4.4100, 4.6896] +24-11-19 20:21:46 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:21:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:46 | D | sum error = [ 5.0082, 5.3381, 5.6818, 6.0540, 6.4475] +24-11-19 20:21:46 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:21:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:46 | D | sum error = [ 6.8521, 7.2900, 7.7406, 8.2281, 8.7239] +24-11-19 20:21:46 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:21:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:46 | D | sum error = [ 9.2690, 9.8239, 10.4281, 11.0487, 11.7096] +24-11-19 20:21:46 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:21:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:46 | D | sum error = [ 12.4023, 13.1274, 13.8906, 14.6910, 15.5338] +24-11-19 20:21:46 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:21:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:46 | D | sum error = [ 16.4190, 17.3478, 18.3217, 19.3399, 20.4081] +24-11-19 20:21:46 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:21:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:46 | D | sum error = [ 21.5172, 22.6808, 23.8929, 25.1673, 26.4874] +24-11-19 20:21:46 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:21:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:46 | D | sum error = [ 27.8732, 29.3124, 30.8161, 32.3774, 34.0150] +24-11-19 20:21:46 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:21:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:46 | D | sum error = [ 35.7087, 37.4730, 39.3028, 41.2053, 43.1680] +24-11-19 20:21:46 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:21:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:46 | D | sum error = [ 45.2113, 47.3153, 49.5047, 51.7682, 54.1000] +24-11-19 20:21:46 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:21:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:46 | D | sum error = [ 56.5214, 59.0154, 61.5930, 64.2505, 66.9857] +24-11-19 20:21:46 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:21:46 | D | + error = [0.8849] +24-11-19 20:21:46 | D | - Calibrating model.layers.5.self_attn.o_proj.weight +24-11-19 20:21:46 | D | + w: sint8 +24-11-19 20:21:46 | D | + x: None +24-11-19 20:21:46 | D | + y: None +24-11-19 20:21:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:46 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:46 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:46 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:46 | D | - range ratio = [ 1.0000] +24-11-19 20:21:46 | D | sum error = [ 0.2897] +24-11-19 20:21:46 | D | best error = [ 0.2897] +24-11-19 20:21:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:47 | D | sum error = [ 0.2875, 0.2869, 0.2866, 0.2898, 0.2926] +24-11-19 20:21:47 | D | best error = [ 0.2659, 0.2556, 0.2493, 0.2453, 0.2425] +24-11-19 20:21:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:47 | D | sum error = [ 0.2993, 0.3056, 0.3169, 0.3281, 0.3434] +24-11-19 20:21:47 | D | best error = [ 0.2406, 0.2393, 0.2385, 0.2378, 0.2374] +24-11-19 20:21:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:47 | D | sum error = [ 0.3584, 0.3781, 0.3979, 0.4194, 0.4461] +24-11-19 20:21:47 | D | best error = [ 0.2371, 0.2369, 0.2368, 0.2367, 0.2366] +24-11-19 20:21:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:47 | D | sum error = [ 0.4731, 0.5006, 0.5319, 0.5664, 0.6014] +24-11-19 20:21:47 | D | best error = [ 0.2366, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:21:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:47 | D | sum error = [ 0.6403, 0.6803, 0.7234, 0.7705, 0.8181] +24-11-19 20:21:47 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:21:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:47 | D | sum error = [ 0.8684, 0.9218, 0.9799, 1.0391, 1.1031] +24-11-19 20:21:47 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:21:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:47 | D | sum error = [ 1.1676, 1.2364, 1.3110, 1.3864, 1.4683] +24-11-19 20:21:47 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:21:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:47 | D | sum error = [ 1.5531, 1.6416, 1.7354, 1.8317, 1.9357] +24-11-19 20:21:47 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:21:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:47 | D | sum error = [ 2.0425, 2.1546, 2.2726, 2.3962, 2.5254] +24-11-19 20:21:47 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:21:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:47 | D | sum error = [ 2.6604, 2.8012, 2.9486, 3.1041, 3.2668] +24-11-19 20:21:47 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:21:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:47 | D | sum error = [ 3.4361, 3.6130, 3.7995, 3.9934, 4.1962] +24-11-19 20:21:47 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:21:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:47 | D | sum error = [ 4.4071, 4.6287, 4.8577, 5.0955, 5.3437] +24-11-19 20:21:47 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:21:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:47 | D | sum error = [ 5.6021, 5.8708, 6.1488, 6.4382, 6.7386] +24-11-19 20:21:47 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:21:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:47 | D | sum error = [ 7.0514, 7.3754, 7.7105, 8.0586, 8.4180] +24-11-19 20:21:47 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:21:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:47 | D | sum error = [ 8.7913, 9.1775, 9.5774, 9.9929, 10.4222] +24-11-19 20:21:47 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:21:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:47 | D | sum error = [ 10.8661, 11.3252, 11.7999, 12.2905, 12.7972] +24-11-19 20:21:47 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:21:47 | D | + error = [0.2365] +24-11-19 20:21:47 | D | - Calibrating model.layers.5.mlp.up_proj.weight +24-11-19 20:21:47 | D | + w: sint8 +24-11-19 20:21:47 | D | + x: None +24-11-19 20:21:47 | D | + y: None +24-11-19 20:21:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:47 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:47 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:47 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:47 | D | - range ratio = [ 1.0000] +24-11-19 20:21:47 | D | sum error = [ 0.2470] +24-11-19 20:21:47 | D | best error = [ 0.2470] +24-11-19 20:21:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:48 | D | sum error = [ 0.2445, 0.2443, 0.2452, 0.2478, 0.2523] +24-11-19 20:21:48 | D | best error = [ 0.2331, 0.2265, 0.2229, 0.2211, 0.2201] +24-11-19 20:21:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:48 | D | sum error = [ 0.2596, 0.2677, 0.2784, 0.2916, 0.3066] +24-11-19 20:21:48 | D | best error = [ 0.2197, 0.2195, 0.2194, 0.2194, 0.2194] +24-11-19 20:21:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:48 | D | sum error = [ 0.3235, 0.3435, 0.3658, 0.3903, 0.4172] +24-11-19 20:21:48 | D | best error = [ 0.2194, 0.2194, 0.2194, 0.2194, 0.2194] +24-11-19 20:21:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:48 | D | sum error = [ 0.4462, 0.4778, 0.5113, 0.5484, 0.5868] +24-11-19 20:21:48 | D | best error = [ 0.2194, 0.2194, 0.2194, 0.2194, 0.2194] +24-11-19 20:21:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:48 | D | sum error = [ 0.6296, 0.6731, 0.7199, 0.7700, 0.8235] +24-11-19 20:21:48 | D | best error = [ 0.2194, 0.2194, 0.2194, 0.2194, 0.2194] +24-11-19 20:21:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:48 | D | sum error = [ 0.8797, 0.9395, 1.0027, 1.0691, 1.1399] +24-11-19 20:21:48 | D | best error = [ 0.2194, 0.2194, 0.2194, 0.2194, 0.2194] +24-11-19 20:21:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:48 | D | sum error = [ 1.2125, 1.2934, 1.3765, 1.4646, 1.5558] +24-11-19 20:21:48 | D | best error = [ 0.2194, 0.2194, 0.2194, 0.2194, 0.2194] +24-11-19 20:21:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:48 | D | sum error = [ 1.6520, 1.7536, 1.8616, 1.9756, 2.0915] +24-11-19 20:21:48 | D | best error = [ 0.2194, 0.2194, 0.2194, 0.2194, 0.2194] +24-11-19 20:21:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:48 | D | sum error = [ 2.2151, 2.3456, 2.4816, 2.6241, 2.7726] +24-11-19 20:21:48 | D | best error = [ 0.2194, 0.2194, 0.2194, 0.2194, 0.2194] +24-11-19 20:21:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:48 | D | sum error = [ 2.9303, 3.0937, 3.2633, 3.4417, 3.6271] +24-11-19 20:21:48 | D | best error = [ 0.2194, 0.2194, 0.2194, 0.2194, 0.2194] +24-11-19 20:21:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:48 | D | sum error = [ 3.8233, 4.0249, 4.2363, 4.4569, 4.6831] +24-11-19 20:21:48 | D | best error = [ 0.2194, 0.2194, 0.2194, 0.2194, 0.2194] +24-11-19 20:21:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:48 | D | sum error = [ 4.9245, 5.1728, 5.4317, 5.6986, 5.9772] +24-11-19 20:21:48 | D | best error = [ 0.2194, 0.2194, 0.2194, 0.2194, 0.2194] +24-11-19 20:21:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:48 | D | sum error = [ 6.2681, 6.5683, 6.8794, 7.1979, 7.5334] +24-11-19 20:21:48 | D | best error = [ 0.2194, 0.2194, 0.2194, 0.2194, 0.2194] +24-11-19 20:21:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:48 | D | sum error = [ 7.8784, 8.2344, 8.6024, 8.9859, 9.3837] +24-11-19 20:21:48 | D | best error = [ 0.2194, 0.2194, 0.2194, 0.2194, 0.2194] +24-11-19 20:21:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:48 | D | sum error = [ 9.7873, 10.2086, 10.6391, 11.0836, 11.5458] +24-11-19 20:21:48 | D | best error = [ 0.2194, 0.2194, 0.2194, 0.2194, 0.2194] +24-11-19 20:21:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:48 | D | sum error = [ 12.0182, 12.5016, 13.0071, 13.5257, 14.0542] +24-11-19 20:21:48 | D | best error = [ 0.2194, 0.2194, 0.2194, 0.2194, 0.2194] +24-11-19 20:21:48 | D | + error = [0.2194] +24-11-19 20:21:49 | D | - Calibrating model.layers.5.mlp.gate_proj.weight +24-11-19 20:21:49 | D | + w: sint8 +24-11-19 20:21:49 | D | + x: None +24-11-19 20:21:49 | D | + y: None +24-11-19 20:21:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:49 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:49 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:49 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:49 | D | - range ratio = [ 1.0000] +24-11-19 20:21:49 | D | sum error = [ 5.8952] +24-11-19 20:21:49 | D | best error = [ 5.8952] +24-11-19 20:21:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:50 | D | sum error = [ 5.8586, 5.8433, 5.8619, 5.9248, 6.0497] +24-11-19 20:21:50 | D | best error = [ 5.5165, 5.3719, 5.2953, 5.2502, 5.2284] +24-11-19 20:21:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:50 | D | sum error = [ 6.2001, 6.4094, 6.6709, 6.9728, 7.3503] +24-11-19 20:21:50 | D | best error = [ 5.2188, 5.2143, 5.2133, 5.2131, 5.2130] +24-11-19 20:21:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:50 | D | sum error = [ 7.7802, 8.2689, 8.7930, 9.3940, 10.0415] +24-11-19 20:21:50 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:21:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:50 | D | sum error = [ 10.7526, 11.5326, 12.3634, 13.2524, 14.2208] +24-11-19 20:21:50 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:21:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:50 | D | sum error = [ 15.2587, 16.3515, 17.5426, 18.7956, 20.1325] +24-11-19 20:21:50 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:21:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:50 | D | sum error = [ 21.5500, 23.0596, 24.6704, 26.3766, 28.1797] +24-11-19 20:21:50 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:21:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:50 | D | sum error = [ 30.0819, 32.1206, 34.2575, 36.5259, 38.9360] +24-11-19 20:21:50 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:21:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:50 | D | sum error = [ 41.4826, 44.1635, 47.0026, 50.0172, 53.1957] +24-11-19 20:21:50 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:21:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:50 | D | sum error = [ 56.5628, 60.1219, 63.8764, 67.8488, 72.0176] +24-11-19 20:21:50 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:21:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:50 | D | sum error = [ 76.4417, 81.1117, 86.0159, 91.2046, 96.6465] +24-11-19 20:21:50 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:21:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:50 | D | sum error = [ 102.4085, 108.4413, 114.8118, 121.5290, 128.5549] +24-11-19 20:21:50 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:21:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:50 | D | sum error = [ 135.9621, 143.7160, 151.8746, 160.4035, 169.3464] +24-11-19 20:21:50 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:21:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:50 | D | sum error = [ 178.7264, 188.5396, 198.8013, 209.5466, 220.7686] +24-11-19 20:21:50 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:21:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:50 | D | sum error = [ 232.4682, 244.6675, 257.3889, 270.6666, 284.4681] +24-11-19 20:21:50 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:21:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:50 | D | sum error = [ 298.8150, 313.7171, 329.2060, 345.2414, 361.8494] +24-11-19 20:21:50 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:21:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:50 | D | sum error = [ 379.0510, 396.8044, 415.1431, 434.0624, 453.5746] +24-11-19 20:21:50 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:21:50 | D | + error = [5.2130] +24-11-19 20:21:50 | D | - Calibrating model.layers.5.mlp.down_proj.weight +24-11-19 20:21:50 | D | + w: sint8 +24-11-19 20:21:50 | D | + x: None +24-11-19 20:21:50 | D | + y: None +24-11-19 20:21:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:50 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:50 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:51 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:51 | D | - range ratio = [ 1.0000] +24-11-19 20:21:51 | D | sum error = [ 0.4484] +24-11-19 20:21:51 | D | best error = [ 0.4484] +24-11-19 20:21:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:52 | D | sum error = [ 0.4440, 0.4413, 0.4384, 0.4383, 0.4394] +24-11-19 20:21:52 | D | best error = [ 0.4319, 0.4234, 0.4177, 0.4138, 0.4108] +24-11-19 20:21:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:52 | D | sum error = [ 0.4419, 0.4470, 0.4546, 0.4656, 0.4802] +24-11-19 20:21:52 | D | best error = [ 0.4085, 0.4069, 0.4057, 0.4050, 0.4044] +24-11-19 20:21:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:52 | D | sum error = [ 0.4972, 0.5190, 0.5439, 0.5731, 0.6066] +24-11-19 20:21:52 | D | best error = [ 0.4042, 0.4040, 0.4040, 0.4039, 0.4039] +24-11-19 20:21:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:52 | D | sum error = [ 0.6439, 0.6858, 0.7312, 0.7819, 0.8362] +24-11-19 20:21:52 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 20:21:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:52 | D | sum error = [ 0.8943, 0.9576, 1.0260, 1.0986, 1.1756] +24-11-19 20:21:52 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 20:21:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:52 | D | sum error = [ 1.2599, 1.3478, 1.4415, 1.5410, 1.6461] +24-11-19 20:21:52 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 20:21:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:52 | D | sum error = [ 1.7589, 1.8770, 2.0019, 2.1352, 2.2754] +24-11-19 20:21:52 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 20:21:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:52 | D | sum error = [ 2.4244, 2.5809, 2.7461, 2.9208, 3.1050] +24-11-19 20:21:52 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 20:21:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:52 | D | sum error = [ 3.2988, 3.5032, 3.7188, 3.9446, 4.1824] +24-11-19 20:21:52 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 20:21:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:52 | D | sum error = [ 4.4328, 4.6952, 4.9707, 5.2595, 5.5639] +24-11-19 20:21:52 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 20:21:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:52 | D | sum error = [ 5.8827, 6.2165, 6.5656, 6.9324, 7.3170] +24-11-19 20:21:52 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 20:21:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:52 | D | sum error = [ 7.7184, 8.1382, 8.5767, 9.0355, 9.5141] +24-11-19 20:21:52 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 20:21:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:52 | D | sum error = [ 10.0129, 10.5339, 11.0781, 11.6443, 12.2310] +24-11-19 20:21:52 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 20:21:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:52 | D | sum error = [ 12.8427, 13.4792, 14.1412, 14.8280, 15.5405] +24-11-19 20:21:52 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 20:21:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:52 | D | sum error = [ 16.2794, 17.0451, 17.8386, 18.6594, 19.5084] +24-11-19 20:21:52 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 20:21:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:52 | D | sum error = [ 20.3858, 21.2922, 22.2282, 23.1935, 24.1898] +24-11-19 20:21:52 | D | best error = [ 0.4039, 0.4039, 0.4039, 0.4039, 0.4039] +24-11-19 20:21:52 | D | + error = [0.4039] +24-11-19 20:21:52 | D | - Quantizing model.layers.5.self_attn.q_proj.weight +24-11-19 20:21:53 | D | - Quantizing model.layers.5.self_attn.k_proj.weight +24-11-19 20:21:54 | D | - Quantizing model.layers.5.self_attn.v_proj.weight +24-11-19 20:21:57 | D | - Quantizing model.layers.5.self_attn.o_proj.weight +24-11-19 20:22:02 | D | - Quantizing model.layers.5.mlp.up_proj.weight +24-11-19 20:22:03 | D | - Quantizing model.layers.5.mlp.gate_proj.weight +24-11-19 20:22:06 | D | - Quantizing model.layers.5.mlp.down_proj.weight +24-11-19 20:22:18 | D | - Quantizing layer model.layers.6 +24-11-19 20:22:18 | D | - Calibrating model.layers.6.self_attn.q_proj.weight +24-11-19 20:22:18 | D | + w: sint8 +24-11-19 20:22:18 | D | + x: None +24-11-19 20:22:18 | D | + y: None +24-11-19 20:22:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:22:18 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:22:18 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:22:18 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:22:19 | D | - range ratio = [ 1.0000] +24-11-19 20:22:19 | D | sum error = [ 2.4105] +24-11-19 20:22:19 | D | best error = [ 2.4105] +24-11-19 20:22:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:31 | D | sum error = [ 2.3898, 2.4054, 2.4449, 2.3946, 2.5525] +24-11-19 20:22:31 | D | best error = [ 2.3898, 2.3898, 2.3898, 2.3898, 2.3898] +24-11-19 20:22:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:31 | D | sum error = [ 2.5468, 2.7369, 2.7945, 2.8693, 3.0159] +24-11-19 20:22:31 | D | best error = [ 2.3898, 2.3898, 2.3898, 2.3898, 2.3898] +24-11-19 20:22:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:31 | D | sum error = [ 3.2283, 3.5357, 3.7877, 4.1522, 4.4045] +24-11-19 20:22:31 | D | best error = [ 2.3898, 2.3898, 2.3898, 2.3898, 2.3898] +24-11-19 20:22:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:31 | D | sum error = [ 4.8571, 5.2073, 5.6866, 6.1447, 6.6837] +24-11-19 20:22:31 | D | best error = [ 2.3898, 2.3898, 2.3898, 2.3898, 2.3898] +24-11-19 20:22:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:31 | D | sum error = [ 7.3496, 7.9749, 8.7712, 9.5313, 10.3768] +24-11-19 20:22:31 | D | best error = [ 2.3898, 2.3898, 2.3898, 2.3898, 2.3898] +24-11-19 20:22:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:31 | D | sum error = [ 11.3019, 12.1745, 13.2965, 14.3682, 15.7384] +24-11-19 20:22:31 | D | best error = [ 2.3898, 2.3898, 2.3898, 2.3898, 2.3898] +24-11-19 20:22:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:31 | D | sum error = [ 16.9945, 18.4676, 19.9115, 21.5239, 23.2836] +24-11-19 20:22:31 | D | best error = [ 2.3898, 2.3898, 2.3898, 2.3898, 2.3898] +24-11-19 20:22:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:31 | D | sum error = [ 25.2306, 27.3259, 29.4467, 31.8285, 34.4591] +24-11-19 20:22:31 | D | best error = [ 2.3898, 2.3898, 2.3898, 2.3898, 2.3898] +24-11-19 20:22:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:31 | D | sum error = [ 37.0148, 40.0191, 43.0129, 46.1914, 49.7752] +24-11-19 20:22:31 | D | best error = [ 2.3898, 2.3898, 2.3898, 2.3898, 2.3898] +24-11-19 20:22:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:31 | D | sum error = [ 53.3771, 57.2420, 61.3182, 65.8378, 70.5749] +24-11-19 20:22:31 | D | best error = [ 2.3898, 2.3898, 2.3898, 2.3898, 2.3898] +24-11-19 20:22:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:31 | D | sum error = [ 75.4166, 80.6287, 86.2705, 92.1702, 98.6271] +24-11-19 20:22:31 | D | best error = [ 2.3898, 2.3898, 2.3898, 2.3898, 2.3898] +24-11-19 20:22:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:31 | D | sum error = [ 105.5041, 112.6658, 120.2889, 128.5178, 136.9987] +24-11-19 20:22:31 | D | best error = [ 2.3898, 2.3898, 2.3898, 2.3898, 2.3898] +24-11-19 20:22:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:31 | D | sum error = [ 146.2910, 156.1578, 166.5967, 177.6349, 189.4444] +24-11-19 20:22:31 | D | best error = [ 2.3898, 2.3898, 2.3898, 2.3898, 2.3898] +24-11-19 20:22:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:31 | D | sum error = [ 201.8279, 214.9480, 228.7997, 243.3606, 258.9761] +24-11-19 20:22:31 | D | best error = [ 2.3898, 2.3898, 2.3898, 2.3898, 2.3898] +24-11-19 20:22:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:31 | D | sum error = [ 275.3713, 292.6389, 310.7094, 329.5619, 349.2611] +24-11-19 20:22:31 | D | best error = [ 2.3898, 2.3898, 2.3898, 2.3898, 2.3898] +24-11-19 20:22:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:31 | D | sum error = [ 369.5762, 390.6747, 412.4137, 434.6252, 457.2510] +24-11-19 20:22:31 | D | best error = [ 2.3898, 2.3898, 2.3898, 2.3898, 2.3898] +24-11-19 20:22:31 | D | + error = [2.3898] +24-11-19 20:22:31 | D | - Calibrating model.layers.6.self_attn.k_proj.weight +24-11-19 20:22:31 | D | + w: sint8 +24-11-19 20:22:31 | D | + x: None +24-11-19 20:22:31 | D | + y: None +24-11-19 20:22:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:22:31 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:31 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:32 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:32 | D | - range ratio = [ 1.0000] +24-11-19 20:22:32 | D | sum error = [ 2.2621] +24-11-19 20:22:32 | D | best error = [ 2.2621] +24-11-19 20:22:44 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:44 | D | sum error = [ 2.3890, 2.3691, 2.2949, 2.7282, 2.7148] +24-11-19 20:22:44 | D | best error = [ 2.2621, 2.2621, 2.2621, 2.2621, 2.2621] +24-11-19 20:22:44 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:44 | D | sum error = [ 2.3412, 3.1927, 2.8087, 2.8459, 3.0675] +24-11-19 20:22:44 | D | best error = [ 2.2621, 2.2621, 2.2621, 2.2621, 2.2621] +24-11-19 20:22:44 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:44 | D | sum error = [ 3.5997, 3.7671, 3.9299, 4.0445, 4.9615] +24-11-19 20:22:44 | D | best error = [ 2.2621, 2.2621, 2.2621, 2.2621, 2.2621] +24-11-19 20:22:44 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:44 | D | sum error = [ 5.0265, 5.0146, 5.6308, 6.1093, 6.3011] +24-11-19 20:22:44 | D | best error = [ 2.2621, 2.2621, 2.2621, 2.2621, 2.2621] +24-11-19 20:22:44 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:44 | D | sum error = [ 6.4384, 7.6960, 8.0480, 8.3407, 9.6407] +24-11-19 20:22:44 | D | best error = [ 2.2621, 2.2621, 2.2621, 2.2621, 2.2621] +24-11-19 20:22:44 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:44 | D | sum error = [ 10.4920, 10.7531, 11.7485, 12.7795, 13.6584] +24-11-19 20:22:44 | D | best error = [ 2.2621, 2.2621, 2.2621, 2.2621, 2.2621] +24-11-19 20:22:44 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:44 | D | sum error = [ 15.0072, 16.2503, 17.4498, 18.8223, 20.5800] +24-11-19 20:22:44 | D | best error = [ 2.2621, 2.2621, 2.2621, 2.2621, 2.2621] +24-11-19 20:22:44 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:44 | D | sum error = [ 22.4091, 24.3481, 26.1658, 28.2270, 30.4989] +24-11-19 20:22:44 | D | best error = [ 2.2621, 2.2621, 2.2621, 2.2621, 2.2621] +24-11-19 20:22:44 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:44 | D | sum error = [ 32.8338, 35.7426, 38.3142, 41.3808, 44.5489] +24-11-19 20:22:44 | D | best error = [ 2.2621, 2.2621, 2.2621, 2.2621, 2.2621] +24-11-19 20:22:44 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:44 | D | sum error = [ 48.1493, 52.3429, 55.8561, 60.2182, 64.6581] +24-11-19 20:22:44 | D | best error = [ 2.2621, 2.2621, 2.2621, 2.2621, 2.2621] +24-11-19 20:22:44 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:44 | D | sum error = [ 69.5016, 74.4963, 80.2623, 86.0200, 92.3657] +24-11-19 20:22:44 | D | best error = [ 2.2621, 2.2621, 2.2621, 2.2621, 2.2621] +24-11-19 20:22:44 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:44 | D | sum error = [ 98.8999, 106.1334, 113.8083, 121.7420, 130.0802] +24-11-19 20:22:44 | D | best error = [ 2.2621, 2.2621, 2.2621, 2.2621, 2.2621] +24-11-19 20:22:44 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:44 | D | sum error = [ 139.5787, 149.2223, 159.5369, 171.1779, 182.8103] +24-11-19 20:22:44 | D | best error = [ 2.2621, 2.2621, 2.2621, 2.2621, 2.2621] +24-11-19 20:22:44 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:44 | D | sum error = [ 195.5563, 209.0763, 223.6053, 238.3450, 255.0628] +24-11-19 20:22:44 | D | best error = [ 2.2621, 2.2621, 2.2621, 2.2621, 2.2621] +24-11-19 20:22:44 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:44 | D | sum error = [ 271.9509, 290.4030, 309.3709, 328.4945, 348.7135] +24-11-19 20:22:44 | D | best error = [ 2.2621, 2.2621, 2.2621, 2.2621, 2.2621] +24-11-19 20:22:44 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:44 | D | sum error = [ 370.1075, 391.7068, 414.0052, 436.4683, 459.9818] +24-11-19 20:22:44 | D | best error = [ 2.2621, 2.2621, 2.2621, 2.2621, 2.2621] +24-11-19 20:22:44 | D | + error = [2.2621] +24-11-19 20:22:44 | D | - Calibrating model.layers.6.self_attn.v_proj.weight +24-11-19 20:22:44 | D | + w: sint8 +24-11-19 20:22:44 | D | + x: None +24-11-19 20:22:44 | D | + y: None +24-11-19 20:22:44 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:44 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:44 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:44 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:44 | D | - range ratio = [ 1.0000] +24-11-19 20:22:44 | D | sum error = [ 1.1028] +24-11-19 20:22:44 | D | best error = [ 1.1028] +24-11-19 20:22:44 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:44 | D | sum error = [ 1.0957, 1.0913, 1.1007, 1.1123, 1.1424] +24-11-19 20:22:44 | D | best error = [ 1.0284, 0.9991, 0.9847, 0.9776, 0.9746] +24-11-19 20:22:44 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:44 | D | sum error = [ 1.1566, 1.1924, 1.2336, 1.2967, 1.3711] +24-11-19 20:22:44 | D | best error = [ 0.9728, 0.9723, 0.9718, 0.9717, 0.9716] +24-11-19 20:22:44 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:44 | D | sum error = [ 1.4548, 1.5435, 1.6494, 1.7467, 1.8753] +24-11-19 20:22:44 | D | best error = [ 0.9716, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:22:44 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:44 | D | sum error = [ 2.0072, 2.1597, 2.3008, 2.4727, 2.6497] +24-11-19 20:22:44 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:22:44 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:44 | D | sum error = [ 2.8291, 3.0313, 3.2430, 3.4693, 3.7042] +24-11-19 20:22:44 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:22:44 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:44 | D | sum error = [ 3.9609, 4.2310, 4.5137, 4.8200, 5.1322] +24-11-19 20:22:44 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:22:44 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:44 | D | sum error = [ 5.4729, 5.8235, 6.2011, 6.6021, 7.0158] +24-11-19 20:22:44 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:22:44 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:44 | D | sum error = [ 7.4625, 7.9124, 8.4073, 8.9201, 9.4699] +24-11-19 20:22:44 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:22:44 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:44 | D | sum error = [ 10.0319, 10.6439, 11.2716, 11.9378, 12.6385] +24-11-19 20:22:44 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:22:44 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:44 | D | sum error = [ 13.3784, 14.1472, 14.9642, 15.8143, 16.7035] +24-11-19 20:22:44 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:22:44 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:44 | D | sum error = [ 17.6406, 18.6225, 19.6395, 20.7173, 21.8293] +24-11-19 20:22:44 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:22:44 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:44 | D | sum error = [ 23.0083, 24.2282, 25.5066, 26.8483, 28.2400] +24-11-19 20:22:44 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:22:44 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:44 | D | sum error = [ 29.6966, 31.2193, 32.7923, 34.4425, 36.1522] +24-11-19 20:22:44 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:22:44 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:44 | D | sum error = [ 37.9293, 39.7695, 41.6834, 43.6624, 45.7147] +24-11-19 20:22:44 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:22:44 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:44 | D | sum error = [ 47.8502, 50.0515, 52.3323, 54.6947, 57.1377] +24-11-19 20:22:44 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:22:44 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:44 | D | sum error = [ 59.6515, 62.2524, 64.9287, 67.6875, 70.5328] +24-11-19 20:22:44 | D | best error = [ 0.9715, 0.9715, 0.9715, 0.9715, 0.9715] +24-11-19 20:22:44 | D | + error = [0.9715] +24-11-19 20:22:44 | D | - Calibrating model.layers.6.self_attn.o_proj.weight +24-11-19 20:22:44 | D | + w: sint8 +24-11-19 20:22:44 | D | + x: None +24-11-19 20:22:44 | D | + y: None +24-11-19 20:22:44 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:44 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:44 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:45 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:45 | D | - range ratio = [ 1.0000] +24-11-19 20:22:45 | D | sum error = [ 0.3658] +24-11-19 20:22:45 | D | best error = [ 0.3658] +24-11-19 20:22:45 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:45 | D | sum error = [ 0.3632, 0.3645, 0.3643, 0.3695, 0.3754] +24-11-19 20:22:45 | D | best error = [ 0.3374, 0.3257, 0.3187, 0.3143, 0.3114] +24-11-19 20:22:45 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:45 | D | sum error = [ 0.3849, 0.3965, 0.4123, 0.4311, 0.4513] +24-11-19 20:22:45 | D | best error = [ 0.3100, 0.3089, 0.3082, 0.3077, 0.3074] +24-11-19 20:22:45 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:45 | D | sum error = [ 0.4777, 0.5029, 0.5315, 0.5619, 0.6005] +24-11-19 20:22:45 | D | best error = [ 0.3071, 0.3068, 0.3067, 0.3066, 0.3065] +24-11-19 20:22:45 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:45 | D | sum error = [ 0.6390, 0.6788, 0.7216, 0.7689, 0.8187] +24-11-19 20:22:45 | D | best error = [ 0.3065, 0.3065, 0.3064, 0.3064, 0.3064] +24-11-19 20:22:45 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:45 | D | sum error = [ 0.8701, 0.9267, 0.9855, 1.0468, 1.1120] +24-11-19 20:22:45 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:22:45 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:45 | D | sum error = [ 1.1818, 1.2513, 1.3276, 1.4069, 1.4908] +24-11-19 20:22:45 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:22:45 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:45 | D | sum error = [ 1.5771, 1.6687, 1.7648, 1.8654, 1.9709] +24-11-19 20:22:45 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:22:45 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:45 | D | sum error = [ 2.0799, 2.1952, 2.3165, 2.4406, 2.5731] +24-11-19 20:22:45 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:22:45 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:45 | D | sum error = [ 2.7101, 2.8551, 3.0066, 3.1649, 3.3300] +24-11-19 20:22:45 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:22:45 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:45 | D | sum error = [ 3.5041, 3.6849, 3.8740, 4.0724, 4.2780] +24-11-19 20:22:45 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:22:45 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:45 | D | sum error = [ 4.4935, 4.7176, 4.9506, 5.1927, 5.4457] +24-11-19 20:22:45 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:22:45 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:45 | D | sum error = [ 5.7077, 5.9809, 6.2662, 6.5616, 6.8698] +24-11-19 20:22:45 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:22:45 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:45 | D | sum error = [ 7.1907, 7.5231, 7.8681, 8.2262, 8.5971] +24-11-19 20:22:45 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:22:45 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:45 | D | sum error = [ 8.9827, 9.3809, 9.7947, 10.2234, 10.6650] +24-11-19 20:22:45 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:22:45 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:45 | D | sum error = [ 11.1241, 11.5977, 12.0872, 12.5937, 13.1175] +24-11-19 20:22:45 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:22:45 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:45 | D | sum error = [ 13.6590, 14.2184, 14.7964, 15.3936, 16.0103] +24-11-19 20:22:45 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:22:45 | D | + error = [0.3064] +24-11-19 20:22:45 | D | - Calibrating model.layers.6.mlp.up_proj.weight +24-11-19 20:22:45 | D | + w: sint8 +24-11-19 20:22:45 | D | + x: None +24-11-19 20:22:45 | D | + y: None +24-11-19 20:22:45 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:45 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:45 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:45 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:45 | D | - range ratio = [ 1.0000] +24-11-19 20:22:45 | D | sum error = [ 0.2532] +24-11-19 20:22:45 | D | best error = [ 0.2532] +24-11-19 20:22:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:47 | D | sum error = [ 0.2515, 0.2509, 0.2522, 0.2547, 0.2600] +24-11-19 20:22:47 | D | best error = [ 0.2389, 0.2318, 0.2283, 0.2263, 0.2253] +24-11-19 20:22:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:47 | D | sum error = [ 0.2660, 0.2750, 0.2862, 0.2997, 0.3151] +24-11-19 20:22:47 | D | best error = [ 0.2248, 0.2246, 0.2245, 0.2245, 0.2245] +24-11-19 20:22:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:47 | D | sum error = [ 0.3332, 0.3538, 0.3769, 0.4022, 0.4294] +24-11-19 20:22:47 | D | best error = [ 0.2245, 0.2245, 0.2245, 0.2245, 0.2245] +24-11-19 20:22:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:47 | D | sum error = [ 0.4596, 0.4924, 0.5278, 0.5653, 0.6055] +24-11-19 20:22:47 | D | best error = [ 0.2245, 0.2245, 0.2245, 0.2245, 0.2245] +24-11-19 20:22:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:47 | D | sum error = [ 0.6492, 0.6955, 0.7443, 0.7962, 0.8510] +24-11-19 20:22:47 | D | best error = [ 0.2245, 0.2245, 0.2245, 0.2245, 0.2245] +24-11-19 20:22:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:47 | D | sum error = [ 0.9091, 0.9712, 1.0368, 1.1057, 1.1790] +24-11-19 20:22:47 | D | best error = [ 0.2245, 0.2245, 0.2245, 0.2245, 0.2245] +24-11-19 20:22:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:47 | D | sum error = [ 1.2553, 1.3379, 1.4239, 1.5145, 1.6097] +24-11-19 20:22:47 | D | best error = [ 0.2245, 0.2245, 0.2245, 0.2245, 0.2245] +24-11-19 20:22:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:47 | D | sum error = [ 1.7105, 1.8155, 1.9267, 2.0445, 2.1653] +24-11-19 20:22:47 | D | best error = [ 0.2245, 0.2245, 0.2245, 0.2245, 0.2245] +24-11-19 20:22:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:47 | D | sum error = [ 2.2932, 2.4290, 2.5694, 2.7180, 2.8752] +24-11-19 20:22:47 | D | best error = [ 0.2245, 0.2245, 0.2245, 0.2245, 0.2245] +24-11-19 20:22:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:47 | D | sum error = [ 3.0381, 3.2081, 3.3852, 3.5712, 3.7683] +24-11-19 20:22:47 | D | best error = [ 0.2245, 0.2245, 0.2245, 0.2245, 0.2245] +24-11-19 20:22:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:47 | D | sum error = [ 3.9716, 4.1834, 4.4051, 4.6382, 4.8793] +24-11-19 20:22:47 | D | best error = [ 0.2245, 0.2245, 0.2245, 0.2245, 0.2245] +24-11-19 20:22:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:47 | D | sum error = [ 5.1280, 5.3905, 5.6637, 5.9487, 6.2459] +24-11-19 20:22:47 | D | best error = [ 0.2245, 0.2245, 0.2245, 0.2245, 0.2245] +24-11-19 20:22:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:47 | D | sum error = [ 6.5507, 6.8698, 7.1955, 7.5439, 7.9003] +24-11-19 20:22:47 | D | best error = [ 0.2245, 0.2245, 0.2245, 0.2245, 0.2245] +24-11-19 20:22:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:47 | D | sum error = [ 8.2687, 8.6517, 9.0461, 9.4585, 9.8829] +24-11-19 20:22:47 | D | best error = [ 0.2245, 0.2245, 0.2245, 0.2245, 0.2245] +24-11-19 20:22:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:47 | D | sum error = [ 10.3174, 10.7682, 11.2336, 11.7246, 12.2197] +24-11-19 20:22:47 | D | best error = [ 0.2245, 0.2245, 0.2245, 0.2245, 0.2245] +24-11-19 20:22:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:47 | D | sum error = [ 12.7260, 13.2510, 13.7933, 14.3647, 14.9338] +24-11-19 20:22:47 | D | best error = [ 0.2245, 0.2245, 0.2245, 0.2245, 0.2245] +24-11-19 20:22:47 | D | + error = [0.2245] +24-11-19 20:22:47 | D | - Calibrating model.layers.6.mlp.gate_proj.weight +24-11-19 20:22:47 | D | + w: sint8 +24-11-19 20:22:47 | D | + x: None +24-11-19 20:22:47 | D | + y: None +24-11-19 20:22:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:47 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:47 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:47 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:47 | D | - range ratio = [ 1.0000] +24-11-19 20:22:47 | D | sum error = [ 6.1108] +24-11-19 20:22:47 | D | best error = [ 6.1108] +24-11-19 20:22:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:48 | D | sum error = [ 6.0620, 6.0487, 6.0675, 6.1396, 6.2554] +24-11-19 20:22:48 | D | best error = [ 5.7028, 5.5490, 5.4699, 5.4240, 5.4018] +24-11-19 20:22:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:48 | D | sum error = [ 6.4333, 6.6373, 6.9195, 7.2442, 7.6370] +24-11-19 20:22:48 | D | best error = [ 5.3908, 5.3864, 5.3852, 5.3847, 5.3846] +24-11-19 20:22:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:48 | D | sum error = [ 8.0795, 8.5822, 9.1399, 9.7947, 10.4628] +24-11-19 20:22:48 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 20:22:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:48 | D | sum error = [ 11.2295, 12.0334, 12.9129, 13.8544, 14.8838] +24-11-19 20:22:48 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 20:22:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:48 | D | sum error = [ 15.9821, 17.1478, 18.3856, 19.7279, 21.1394] +24-11-19 20:22:48 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 20:22:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:48 | D | sum error = [ 22.6418, 24.2583, 25.9565, 27.7585, 29.6807] +24-11-19 20:22:48 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 20:22:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:48 | D | sum error = [ 31.7300, 33.9141, 36.1998, 38.6395, 41.2399] +24-11-19 20:22:48 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 20:22:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:48 | D | sum error = [ 43.9911, 46.8861, 49.9801, 53.2418, 56.7042] +24-11-19 20:22:48 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 20:22:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:48 | D | sum error = [ 60.3797, 64.2676, 68.3726, 72.7416, 77.3389] +24-11-19 20:22:48 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 20:22:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:48 | D | sum error = [ 82.2128, 87.3850, 92.8364, 98.6027, 104.6927] +24-11-19 20:22:48 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 20:22:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:48 | D | sum error = [ 111.1118, 117.8977, 125.0425, 132.5859, 140.5138] +24-11-19 20:22:48 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 20:22:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:48 | D | sum error = [ 148.8550, 157.6383, 166.8955, 176.6036, 186.8021] +24-11-19 20:22:48 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 20:22:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:48 | D | sum error = [ 197.5065, 208.7173, 220.4600, 232.7549, 245.6196] +24-11-19 20:22:48 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 20:22:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:48 | D | sum error = [ 259.0524, 273.0832, 287.7250, 302.9847, 318.8861] +24-11-19 20:22:48 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 20:22:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:48 | D | sum error = [ 335.4296, 352.6154, 370.4670, 388.9812, 408.1515] +24-11-19 20:22:48 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 20:22:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:48 | D | sum error = [ 428.0239, 448.5811, 469.8246, 491.7428, 514.3417] +24-11-19 20:22:48 | D | best error = [ 5.3846, 5.3846, 5.3846, 5.3846, 5.3846] +24-11-19 20:22:48 | D | + error = [5.3846] +24-11-19 20:22:48 | D | - Calibrating model.layers.6.mlp.down_proj.weight +24-11-19 20:22:48 | D | + w: sint8 +24-11-19 20:22:48 | D | + x: None +24-11-19 20:22:48 | D | + y: None +24-11-19 20:22:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:48 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:48 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:48 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:48 | D | - range ratio = [ 1.0000] +24-11-19 20:22:48 | D | sum error = [ 0.4981] +24-11-19 20:22:48 | D | best error = [ 0.4981] +24-11-19 20:22:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:50 | D | sum error = [ 0.4938, 0.4908, 0.4877, 0.4867, 0.4878] +24-11-19 20:22:50 | D | best error = [ 0.4791, 0.4700, 0.4638, 0.4591, 0.4554] +24-11-19 20:22:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:50 | D | sum error = [ 0.4907, 0.4966, 0.5049, 0.5166, 0.5324] +24-11-19 20:22:50 | D | best error = [ 0.4529, 0.4511, 0.4498, 0.4492, 0.4487] +24-11-19 20:22:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:50 | D | sum error = [ 0.5529, 0.5752, 0.6042, 0.6367, 0.6738] +24-11-19 20:22:50 | D | best error = [ 0.4485, 0.4484, 0.4483, 0.4483, 0.4483] +24-11-19 20:22:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:50 | D | sum error = [ 0.7150, 0.7622, 0.8136, 0.8694, 0.9313] +24-11-19 20:22:50 | D | best error = [ 0.4483, 0.4483, 0.4483, 0.4483, 0.4483] +24-11-19 20:22:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:50 | D | sum error = [ 0.9968, 1.0669, 1.1432, 1.2255, 1.3118] +24-11-19 20:22:50 | D | best error = [ 0.4483, 0.4483, 0.4483, 0.4483, 0.4483] +24-11-19 20:22:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:50 | D | sum error = [ 1.4055, 1.5039, 1.6084, 1.7205, 1.8390] +24-11-19 20:22:50 | D | best error = [ 0.4483, 0.4483, 0.4483, 0.4483, 0.4483] +24-11-19 20:22:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:50 | D | sum error = [ 1.9642, 2.0979, 2.2380, 2.3886, 2.5460] +24-11-19 20:22:50 | D | best error = [ 0.4483, 0.4483, 0.4483, 0.4483, 0.4483] +24-11-19 20:22:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:50 | D | sum error = [ 2.7124, 2.8884, 3.0748, 3.2700, 3.4765] +24-11-19 20:22:50 | D | best error = [ 0.4483, 0.4483, 0.4483, 0.4483, 0.4483] +24-11-19 20:22:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:50 | D | sum error = [ 3.6929, 3.9229, 4.1644, 4.4177, 4.6854] +24-11-19 20:22:50 | D | best error = [ 0.4483, 0.4483, 0.4483, 0.4483, 0.4483] +24-11-19 20:22:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:50 | D | sum error = [ 4.9661, 5.2622, 5.5726, 5.8979, 6.2398] +24-11-19 20:22:50 | D | best error = [ 0.4483, 0.4483, 0.4483, 0.4483, 0.4483] +24-11-19 20:22:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:50 | D | sum error = [ 6.5985, 6.9736, 7.3671, 7.7795, 8.2110] +24-11-19 20:22:50 | D | best error = [ 0.4483, 0.4483, 0.4483, 0.4483, 0.4483] +24-11-19 20:22:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:50 | D | sum error = [ 8.6616, 9.1331, 9.6245, 10.1403, 10.6773] +24-11-19 20:22:50 | D | best error = [ 0.4483, 0.4483, 0.4483, 0.4483, 0.4483] +24-11-19 20:22:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:50 | D | sum error = [ 11.2366, 11.8204, 12.4286, 13.0618, 13.7185] +24-11-19 20:22:50 | D | best error = [ 0.4483, 0.4483, 0.4483, 0.4483, 0.4483] +24-11-19 20:22:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:50 | D | sum error = [ 14.4024, 15.1162, 15.8558, 16.6232, 17.4180] +24-11-19 20:22:50 | D | best error = [ 0.4483, 0.4483, 0.4483, 0.4483, 0.4483] +24-11-19 20:22:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:50 | D | sum error = [ 18.2424, 19.0965, 19.9807, 20.8950, 21.8410] +24-11-19 20:22:50 | D | best error = [ 0.4483, 0.4483, 0.4483, 0.4483, 0.4483] +24-11-19 20:22:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:50 | D | sum error = [ 22.8189, 23.8295, 24.8734, 25.9507, 27.0629] +24-11-19 20:22:50 | D | best error = [ 0.4483, 0.4483, 0.4483, 0.4483, 0.4483] +24-11-19 20:22:50 | D | + error = [0.4483] +24-11-19 20:22:50 | D | - Quantizing model.layers.6.self_attn.q_proj.weight +24-11-19 20:22:51 | D | - Quantizing model.layers.6.self_attn.k_proj.weight +24-11-19 20:22:52 | D | - Quantizing model.layers.6.self_attn.v_proj.weight +24-11-19 20:22:53 | D | - Quantizing model.layers.6.self_attn.o_proj.weight +24-11-19 20:22:54 | D | - Quantizing model.layers.6.mlp.up_proj.weight +24-11-19 20:22:55 | D | - Quantizing model.layers.6.mlp.gate_proj.weight +24-11-19 20:22:57 | D | - Quantizing model.layers.6.mlp.down_proj.weight +24-11-19 20:23:09 | D | - Quantizing layer model.layers.7 +24-11-19 20:23:09 | D | - Calibrating model.layers.7.self_attn.q_proj.weight +24-11-19 20:23:09 | D | + w: sint8 +24-11-19 20:23:09 | D | + x: None +24-11-19 20:23:09 | D | + y: None +24-11-19 20:23:09 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:23:09 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:23:09 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:23:10 | D | + finished calculating the original outputs, ram usage: 13.4 +24-11-19 20:23:10 | D | - range ratio = [ 1.0000] +24-11-19 20:23:10 | D | sum error = [ 2.9789] +24-11-19 20:23:10 | D | best error = [ 2.9789] +24-11-19 20:23:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:22 | D | sum error = [ 3.0438, 3.0332, 3.0042, 3.0428, 3.1257] +24-11-19 20:23:22 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:23:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:22 | D | sum error = [ 3.2027, 3.3464, 3.4568, 3.7740, 4.0078] +24-11-19 20:23:22 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:23:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:22 | D | sum error = [ 4.1059, 4.3398, 4.6807, 5.1180, 5.5717] +24-11-19 20:23:22 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:23:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:22 | D | sum error = [ 5.9237, 6.4323, 6.9679, 7.7086, 8.5105] +24-11-19 20:23:22 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:23:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:22 | D | sum error = [ 9.2898, 10.3180, 11.4530, 12.6347, 13.5274] +24-11-19 20:23:22 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:23:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:22 | D | sum error = [ 15.2069, 16.4612, 18.0219, 19.9933, 21.6827] +24-11-19 20:23:22 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:23:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:22 | D | sum error = [ 23.7717, 25.9119, 28.4843, 31.0191, 33.7540] +24-11-19 20:23:22 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:23:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:22 | D | sum error = [ 37.0103, 40.1571, 43.6639, 47.2553, 51.1287] +24-11-19 20:23:22 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:23:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:22 | D | sum error = [ 55.3926, 59.7348, 64.3702, 69.3413, 74.7683] +24-11-19 20:23:22 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:23:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:22 | D | sum error = [ 80.3994, 86.1226, 92.2788, 98.7846, 105.6597] +24-11-19 20:23:22 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:23:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:22 | D | sum error = [ 112.8567, 120.7322, 128.7120, 136.9808, 145.9935] +24-11-19 20:23:22 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:23:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:22 | D | sum error = [ 155.5434, 165.3685, 175.7660, 186.5025, 197.8044] +24-11-19 20:23:22 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:23:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:22 | D | sum error = [ 209.6475, 222.0220, 234.7873, 247.8403, 261.7076] +24-11-19 20:23:22 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:23:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:22 | D | sum error = [ 275.9513, 290.4177, 305.3137, 320.8755, 336.5639] +24-11-19 20:23:22 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:23:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:22 | D | sum error = [ 352.8585, 369.6915, 386.9170, 404.7313, 422.7922] +24-11-19 20:23:22 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:23:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:22 | D | sum error = [ 441.3936, 460.2935, 479.7017, 499.3940, 519.4972] +24-11-19 20:23:22 | D | best error = [ 2.9789, 2.9789, 2.9789, 2.9789, 2.9789] +24-11-19 20:23:22 | D | + error = [2.9789] +24-11-19 20:23:22 | D | - Calibrating model.layers.7.self_attn.k_proj.weight +24-11-19 20:23:22 | D | + w: sint8 +24-11-19 20:23:22 | D | + x: None +24-11-19 20:23:22 | D | + y: None +24-11-19 20:23:22 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:23:22 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:22 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:22 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:23 | D | - range ratio = [ 1.0000] +24-11-19 20:23:23 | D | sum error = [ 3.1047] +24-11-19 20:23:23 | D | best error = [ 3.1047] +24-11-19 20:23:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:35 | D | sum error = [ 3.1263, 3.1433, 3.0636, 2.7595, 3.3568] +24-11-19 20:23:35 | D | best error = [ 3.1047, 3.1047, 3.0636, 2.7595, 2.7595] +24-11-19 20:23:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:35 | D | sum error = [ 2.9976, 3.0180, 3.4232, 3.6307, 3.6649] +24-11-19 20:23:35 | D | best error = [ 2.7595, 2.7595, 2.7595, 2.7595, 2.7595] +24-11-19 20:23:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:35 | D | sum error = [ 3.6474, 3.9529, 4.6851, 4.9272, 5.4338] +24-11-19 20:23:35 | D | best error = [ 2.7595, 2.7595, 2.7595, 2.7595, 2.7595] +24-11-19 20:23:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:35 | D | sum error = [ 5.7192, 5.9350, 6.3743, 7.2311, 7.8114] +24-11-19 20:23:35 | D | best error = [ 2.7595, 2.7595, 2.7595, 2.7595, 2.7595] +24-11-19 20:23:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:35 | D | sum error = [ 8.7561, 9.3325, 10.0605, 10.6623, 11.7783] +24-11-19 20:23:35 | D | best error = [ 2.7595, 2.7595, 2.7595, 2.7595, 2.7595] +24-11-19 20:23:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:35 | D | sum error = [ 12.6018, 13.9259, 14.4374, 16.4527, 17.2377] +24-11-19 20:23:35 | D | best error = [ 2.7595, 2.7595, 2.7595, 2.7595, 2.7595] +24-11-19 20:23:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:35 | D | sum error = [ 18.8033, 20.1407, 22.6046, 23.7382, 26.1900] +24-11-19 20:23:35 | D | best error = [ 2.7595, 2.7595, 2.7595, 2.7595, 2.7595] +24-11-19 20:23:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:35 | D | sum error = [ 29.2485, 31.8656, 34.5802, 38.0134, 41.2374] +24-11-19 20:23:35 | D | best error = [ 2.7595, 2.7595, 2.7595, 2.7595, 2.7595] +24-11-19 20:23:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:35 | D | sum error = [ 45.2965, 49.1386, 53.4232, 57.5070, 61.7135] +24-11-19 20:23:35 | D | best error = [ 2.7595, 2.7595, 2.7595, 2.7595, 2.7595] +24-11-19 20:23:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:35 | D | sum error = [ 67.4729, 72.5921, 78.5113, 84.6264, 91.1086] +24-11-19 20:23:35 | D | best error = [ 2.7595, 2.7595, 2.7595, 2.7595, 2.7595] +24-11-19 20:23:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:35 | D | sum error = [ 97.9368, 105.1733, 112.3932, 120.2209, 129.6358] +24-11-19 20:23:35 | D | best error = [ 2.7595, 2.7595, 2.7595, 2.7595, 2.7595] +24-11-19 20:23:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:35 | D | sum error = [ 138.2988, 147.6228, 156.1818, 166.5209, 176.7681] +24-11-19 20:23:35 | D | best error = [ 2.7595, 2.7595, 2.7595, 2.7595, 2.7595] +24-11-19 20:23:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:35 | D | sum error = [ 187.9454, 198.6444, 211.1260, 223.0939, 234.7702] +24-11-19 20:23:35 | D | best error = [ 2.7595, 2.7595, 2.7595, 2.7595, 2.7595] +24-11-19 20:23:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:35 | D | sum error = [ 249.5763, 264.2748, 279.3972, 295.1247, 312.3923] +24-11-19 20:23:35 | D | best error = [ 2.7595, 2.7595, 2.7595, 2.7595, 2.7595] +24-11-19 20:23:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:35 | D | sum error = [ 329.0007, 347.3556, 366.6800, 386.2777, 405.7470] +24-11-19 20:23:35 | D | best error = [ 2.7595, 2.7595, 2.7595, 2.7595, 2.7595] +24-11-19 20:23:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:35 | D | sum error = [ 426.4977, 447.3628, 468.4370, 489.9724, 511.7299] +24-11-19 20:23:35 | D | best error = [ 2.7595, 2.7595, 2.7595, 2.7595, 2.7595] +24-11-19 20:23:35 | D | + error = [2.7595] +24-11-19 20:23:35 | D | - Calibrating model.layers.7.self_attn.v_proj.weight +24-11-19 20:23:35 | D | + w: sint8 +24-11-19 20:23:35 | D | + x: None +24-11-19 20:23:35 | D | + y: None +24-11-19 20:23:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:35 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:35 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:35 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:35 | D | - range ratio = [ 1.0000] +24-11-19 20:23:35 | D | sum error = [ 1.1249] +24-11-19 20:23:35 | D | best error = [ 1.1249] +24-11-19 20:23:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:35 | D | sum error = [ 1.1200, 1.1085, 1.1300, 1.1321, 1.1591] +24-11-19 20:23:35 | D | best error = [ 1.0514, 1.0209, 1.0085, 1.0001, 0.9957] +24-11-19 20:23:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:35 | D | sum error = [ 1.1907, 1.2354, 1.2746, 1.3360, 1.4063] +24-11-19 20:23:35 | D | best error = [ 0.9935, 0.9924, 0.9922, 0.9920, 0.9920] +24-11-19 20:23:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:35 | D | sum error = [ 1.4877, 1.5789, 1.6867, 1.8055, 1.9353] +24-11-19 20:23:35 | D | best error = [ 0.9920, 0.9920, 0.9920, 0.9920, 0.9920] +24-11-19 20:23:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:35 | D | sum error = [ 2.0684, 2.2238, 2.3759, 2.5632, 2.7578] +24-11-19 20:23:35 | D | best error = [ 0.9920, 0.9920, 0.9920, 0.9920, 0.9920] +24-11-19 20:23:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:35 | D | sum error = [ 2.9355, 3.1511, 3.3770, 3.6219, 3.8686] +24-11-19 20:23:35 | D | best error = [ 0.9920, 0.9920, 0.9920, 0.9920, 0.9920] +24-11-19 20:23:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:35 | D | sum error = [ 4.1491, 4.4317, 4.7419, 5.0630, 5.3925] +24-11-19 20:23:35 | D | best error = [ 0.9920, 0.9920, 0.9920, 0.9920, 0.9920] +24-11-19 20:23:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:35 | D | sum error = [ 5.7567, 6.1290, 6.5344, 6.9568, 7.4033] +24-11-19 20:23:35 | D | best error = [ 0.9920, 0.9920, 0.9920, 0.9920, 0.9920] +24-11-19 20:23:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:35 | D | sum error = [ 7.8808, 8.3780, 8.8991, 9.4552, 10.0461] +24-11-19 20:23:35 | D | best error = [ 0.9920, 0.9920, 0.9920, 0.9920, 0.9920] +24-11-19 20:23:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:35 | D | sum error = [ 10.6641, 11.3070, 11.9922, 12.7132, 13.4617] +24-11-19 20:23:35 | D | best error = [ 0.9920, 0.9920, 0.9920, 0.9920, 0.9920] +24-11-19 20:23:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:35 | D | sum error = [ 14.2609, 15.0903, 15.9591, 16.8737, 17.8269] +24-11-19 20:23:35 | D | best error = [ 0.9920, 0.9920, 0.9920, 0.9920, 0.9920] +24-11-19 20:23:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:35 | D | sum error = [ 18.8383, 19.8927, 21.0050, 22.1700, 23.3841] +24-11-19 20:23:35 | D | best error = [ 0.9920, 0.9920, 0.9920, 0.9920, 0.9920] +24-11-19 20:23:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:35 | D | sum error = [ 24.6590, 25.9887, 27.3872, 28.8499, 30.3804] +24-11-19 20:23:35 | D | best error = [ 0.9920, 0.9920, 0.9920, 0.9920, 0.9920] +24-11-19 20:23:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:35 | D | sum error = [ 31.9758, 33.6427, 35.3716, 37.1791, 39.0540] +24-11-19 20:23:35 | D | best error = [ 0.9920, 0.9920, 0.9920, 0.9920, 0.9920] +24-11-19 20:23:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:35 | D | sum error = [ 40.9989, 43.0158, 45.1185, 47.3028, 49.5726] +24-11-19 20:23:35 | D | best error = [ 0.9920, 0.9920, 0.9920, 0.9920, 0.9920] +24-11-19 20:23:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:35 | D | sum error = [ 51.9212, 54.3643, 56.8907, 59.5149, 62.2235] +24-11-19 20:23:35 | D | best error = [ 0.9920, 0.9920, 0.9920, 0.9920, 0.9920] +24-11-19 20:23:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:35 | D | sum error = [ 65.0222, 67.9182, 70.9064, 73.9874, 77.1591] +24-11-19 20:23:35 | D | best error = [ 0.9920, 0.9920, 0.9920, 0.9920, 0.9920] +24-11-19 20:23:35 | D | + error = [0.9920] +24-11-19 20:23:35 | D | - Calibrating model.layers.7.self_attn.o_proj.weight +24-11-19 20:23:35 | D | + w: sint8 +24-11-19 20:23:35 | D | + x: None +24-11-19 20:23:35 | D | + y: None +24-11-19 20:23:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:35 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:35 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:36 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:36 | D | - range ratio = [ 1.0000] +24-11-19 20:23:36 | D | sum error = [ 0.4496] +24-11-19 20:23:36 | D | best error = [ 0.4496] +24-11-19 20:23:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:36 | D | sum error = [ 0.4475, 0.4438, 0.4447, 0.4467, 0.4540] +24-11-19 20:23:36 | D | best error = [ 0.4121, 0.3951, 0.3850, 0.3786, 0.3743] +24-11-19 20:23:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:36 | D | sum error = [ 0.4631, 0.4731, 0.4871, 0.5047, 0.5263] +24-11-19 20:23:36 | D | best error = [ 0.3719, 0.3702, 0.3692, 0.3684, 0.3680] +24-11-19 20:23:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:36 | D | sum error = [ 0.5504, 0.5751, 0.6075, 0.6399, 0.6770] +24-11-19 20:23:36 | D | best error = [ 0.3677, 0.3675, 0.3675, 0.3674, 0.3674] +24-11-19 20:23:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:36 | D | sum error = [ 0.7183, 0.7624, 0.8106, 0.8605, 0.9133] +24-11-19 20:23:36 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:23:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:36 | D | sum error = [ 0.9709, 1.0342, 1.0967, 1.1679, 1.2399] +24-11-19 20:23:36 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:23:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:36 | D | sum error = [ 1.3157, 1.3972, 1.4839, 1.5729, 1.6664] +24-11-19 20:23:36 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:23:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:36 | D | sum error = [ 1.7682, 1.8730, 1.9829, 2.1017, 2.2251] +24-11-19 20:23:36 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:23:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:36 | D | sum error = [ 2.3554, 2.4906, 2.6325, 2.7811, 2.9377] +24-11-19 20:23:36 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:23:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:36 | D | sum error = [ 3.1024, 3.2736, 3.4526, 3.6411, 3.8386] +24-11-19 20:23:36 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:23:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:36 | D | sum error = [ 4.0455, 4.2624, 4.4851, 4.7202, 4.9682] +24-11-19 20:23:36 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:23:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:36 | D | sum error = [ 5.2259, 5.4941, 5.7740, 6.0665, 6.3706] +24-11-19 20:23:36 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:23:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:36 | D | sum error = [ 6.6889, 7.0198, 7.3629, 7.7218, 8.0944] +24-11-19 20:23:36 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:23:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:36 | D | sum error = [ 8.4824, 8.8861, 9.3069, 9.7438, 10.1958] +24-11-19 20:23:36 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:23:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:36 | D | sum error = [ 10.6671, 11.1533, 11.6602, 12.1863, 12.7278] +24-11-19 20:23:36 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:23:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:36 | D | sum error = [ 13.2912, 13.8741, 14.4781, 15.1046, 15.7537] +24-11-19 20:23:36 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:23:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:36 | D | sum error = [ 16.4254, 17.1177, 17.8341, 18.5740, 19.3384] +24-11-19 20:23:36 | D | best error = [ 0.3674, 0.3674, 0.3674, 0.3674, 0.3674] +24-11-19 20:23:36 | D | + error = [0.3674] +24-11-19 20:23:36 | D | - Calibrating model.layers.7.mlp.up_proj.weight +24-11-19 20:23:36 | D | + w: sint8 +24-11-19 20:23:36 | D | + x: None +24-11-19 20:23:36 | D | + y: None +24-11-19 20:23:36 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:36 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:36 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:36 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:36 | D | - range ratio = [ 1.0000] +24-11-19 20:23:36 | D | sum error = [ 0.2625] +24-11-19 20:23:36 | D | best error = [ 0.2625] +24-11-19 20:23:38 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:38 | D | sum error = [ 0.2611, 0.2605, 0.2615, 0.2645, 0.2694] +24-11-19 20:23:38 | D | best error = [ 0.2480, 0.2415, 0.2379, 0.2359, 0.2349] +24-11-19 20:23:38 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:38 | D | sum error = [ 0.2762, 0.2857, 0.2969, 0.3110, 0.3269] +24-11-19 20:23:38 | D | best error = [ 0.2344, 0.2342, 0.2341, 0.2341, 0.2341] +24-11-19 20:23:38 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:38 | D | sum error = [ 0.3465, 0.3682, 0.3917, 0.4178, 0.4463] +24-11-19 20:23:38 | D | best error = [ 0.2341, 0.2341, 0.2341, 0.2341, 0.2341] +24-11-19 20:23:38 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:38 | D | sum error = [ 0.4776, 0.5113, 0.5471, 0.5871, 0.6291] +24-11-19 20:23:38 | D | best error = [ 0.2341, 0.2341, 0.2341, 0.2341, 0.2341] +24-11-19 20:23:38 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:38 | D | sum error = [ 0.6745, 0.7219, 0.7723, 0.8271, 0.8845] +24-11-19 20:23:38 | D | best error = [ 0.2341, 0.2341, 0.2341, 0.2341, 0.2341] +24-11-19 20:23:38 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:38 | D | sum error = [ 0.9450, 1.0095, 1.0779, 1.1503, 1.2267] +24-11-19 20:23:38 | D | best error = [ 0.2341, 0.2341, 0.2341, 0.2341, 0.2341] +24-11-19 20:23:38 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:38 | D | sum error = [ 1.3058, 1.3927, 1.4828, 1.5770, 1.6771] +24-11-19 20:23:38 | D | best error = [ 0.2341, 0.2341, 0.2341, 0.2341, 0.2341] +24-11-19 20:23:38 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:38 | D | sum error = [ 1.7817, 1.8925, 2.0089, 2.1317, 2.2588] +24-11-19 20:23:38 | D | best error = [ 0.2341, 0.2341, 0.2341, 0.2341, 0.2341] +24-11-19 20:23:38 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:38 | D | sum error = [ 2.3932, 2.5357, 2.6849, 2.8410, 3.0049] +24-11-19 20:23:38 | D | best error = [ 0.2341, 0.2341, 0.2341, 0.2341, 0.2341] +24-11-19 20:23:38 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:38 | D | sum error = [ 3.1772, 3.3571, 3.5452, 3.7426, 3.9509] +24-11-19 20:23:38 | D | best error = [ 0.2341, 0.2341, 0.2341, 0.2341, 0.2341] +24-11-19 20:23:38 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:38 | D | sum error = [ 4.1655, 4.3917, 4.6291, 4.8780, 5.1345] +24-11-19 20:23:38 | D | best error = [ 0.2341, 0.2341, 0.2341, 0.2341, 0.2341] +24-11-19 20:23:38 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:38 | D | sum error = [ 5.4041, 5.6841, 5.9760, 6.2796, 6.5986] +24-11-19 20:23:38 | D | best error = [ 0.2341, 0.2341, 0.2341, 0.2341, 0.2341] +24-11-19 20:23:38 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:38 | D | sum error = [ 6.9299, 7.2728, 7.6271, 7.9997, 8.3878] +24-11-19 20:23:38 | D | best error = [ 0.2341, 0.2341, 0.2341, 0.2341, 0.2341] +24-11-19 20:23:38 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:38 | D | sum error = [ 8.7881, 9.2005, 9.6302, 10.0774, 10.5406] +24-11-19 20:23:38 | D | best error = [ 0.2341, 0.2341, 0.2341, 0.2341, 0.2341] +24-11-19 20:23:38 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:38 | D | sum error = [ 11.0132, 11.5080, 12.0236, 12.5505, 13.0934] +24-11-19 20:23:38 | D | best error = [ 0.2341, 0.2341, 0.2341, 0.2341, 0.2341] +24-11-19 20:23:38 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:38 | D | sum error = [ 13.6614, 14.2402, 14.8382, 15.4509, 16.0863] +24-11-19 20:23:38 | D | best error = [ 0.2341, 0.2341, 0.2341, 0.2341, 0.2341] +24-11-19 20:23:38 | D | + error = [0.2341] +24-11-19 20:23:38 | D | - Calibrating model.layers.7.mlp.gate_proj.weight +24-11-19 20:23:38 | D | + w: sint8 +24-11-19 20:23:38 | D | + x: None +24-11-19 20:23:38 | D | + y: None +24-11-19 20:23:38 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:38 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:38 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:38 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:38 | D | - range ratio = [ 1.0000] +24-11-19 20:23:38 | D | sum error = [ 6.0135] +24-11-19 20:23:38 | D | best error = [ 6.0135] +24-11-19 20:23:39 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:39 | D | sum error = [ 5.9721, 5.9571, 5.9817, 6.0586, 6.1472] +24-11-19 20:23:39 | D | best error = [ 5.6382, 5.4907, 5.4113, 5.3686, 5.3456] +24-11-19 20:23:39 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:39 | D | sum error = [ 6.3129, 6.5435, 6.7938, 7.1166, 7.4979] +24-11-19 20:23:39 | D | best error = [ 5.3350, 5.3304, 5.3294, 5.3290, 5.3290] +24-11-19 20:23:39 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:39 | D | sum error = [ 7.9407, 8.4336, 8.9925, 9.6054, 10.2926] +24-11-19 20:23:39 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 20:23:39 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:39 | D | sum error = [ 11.0288, 11.8169, 12.6930, 13.6235, 14.6305] +24-11-19 20:23:39 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 20:23:39 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:39 | D | sum error = [ 15.6923, 16.8489, 18.0866, 19.3969, 20.7884] +24-11-19 20:23:39 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 20:23:39 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:39 | D | sum error = [ 22.2776, 23.8776, 25.5589, 27.3551, 29.2766] +24-11-19 20:23:39 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 20:23:39 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:39 | D | sum error = [ 31.3049, 33.4663, 35.7558, 38.1832, 40.7699] +24-11-19 20:23:39 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 20:23:39 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:39 | D | sum error = [ 43.5172, 46.4236, 49.4965, 52.7684, 56.2444] +24-11-19 20:23:39 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 20:23:39 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:39 | D | sum error = [ 59.9286, 63.8444, 67.9832, 72.3732, 77.0285] +24-11-19 20:23:39 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 20:23:39 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:39 | D | sum error = [ 81.9570, 87.1768, 92.6905, 98.5333, 104.7058] +24-11-19 20:23:39 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 20:23:39 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:39 | D | sum error = [ 111.2111, 118.1098, 125.3747, 133.0644, 141.1543] +24-11-19 20:23:39 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 20:23:39 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:39 | D | sum error = [ 149.6908, 158.6783, 168.1197, 178.0561, 188.5143] +24-11-19 20:23:39 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 20:23:39 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:39 | D | sum error = [ 199.4915, 211.0191, 223.1073, 235.7683, 249.0382] +24-11-19 20:23:39 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 20:23:39 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:39 | D | sum error = [ 262.8987, 277.4005, 292.5366, 308.3365, 324.7883] +24-11-19 20:23:39 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 20:23:39 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:39 | D | sum error = [ 341.9023, 359.7296, 378.2538, 397.4642, 417.3736] +24-11-19 20:23:39 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 20:23:39 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:39 | D | sum error = [ 438.0299, 459.3824, 481.4854, 504.2721, 527.7525] +24-11-19 20:23:39 | D | best error = [ 5.3290, 5.3290, 5.3290, 5.3290, 5.3290] +24-11-19 20:23:39 | D | + error = [5.3290] +24-11-19 20:23:39 | D | - Calibrating model.layers.7.mlp.down_proj.weight +24-11-19 20:23:39 | D | + w: sint8 +24-11-19 20:23:39 | D | + x: None +24-11-19 20:23:39 | D | + y: None +24-11-19 20:23:39 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:39 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:39 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:40 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:40 | D | - range ratio = [ 1.0000] +24-11-19 20:23:40 | D | sum error = [ 0.5208] +24-11-19 20:23:40 | D | best error = [ 0.5208] +24-11-19 20:23:41 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:41 | D | sum error = [ 0.5165, 0.5130, 0.5101, 0.5100, 0.5116] +24-11-19 20:23:41 | D | best error = [ 0.5012, 0.4914, 0.4850, 0.4799, 0.4764] +24-11-19 20:23:41 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:41 | D | sum error = [ 0.5134, 0.5198, 0.5289, 0.5419, 0.5580] +24-11-19 20:23:41 | D | best error = [ 0.4739, 0.4720, 0.4709, 0.4702, 0.4699] +24-11-19 20:23:41 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:41 | D | sum error = [ 0.5788, 0.6040, 0.6335, 0.6681, 0.7079] +24-11-19 20:23:41 | D | best error = [ 0.4696, 0.4695, 0.4694, 0.4694, 0.4694] +24-11-19 20:23:41 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:41 | D | sum error = [ 0.7531, 0.8021, 0.8559, 0.9147, 0.9790] +24-11-19 20:23:41 | D | best error = [ 0.4694, 0.4694, 0.4694, 0.4694, 0.4694] +24-11-19 20:23:41 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:41 | D | sum error = [ 1.0478, 1.1232, 1.2046, 1.2900, 1.3826] +24-11-19 20:23:41 | D | best error = [ 0.4694, 0.4694, 0.4694, 0.4694, 0.4694] +24-11-19 20:23:41 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:41 | D | sum error = [ 1.4802, 1.5859, 1.6961, 1.8141, 1.9391] +24-11-19 20:23:41 | D | best error = [ 0.4694, 0.4694, 0.4694, 0.4694, 0.4694] +24-11-19 20:23:41 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:41 | D | sum error = [ 2.0717, 2.2119, 2.3594, 2.5168, 2.6837] +24-11-19 20:23:41 | D | best error = [ 0.4694, 0.4694, 0.4694, 0.4694, 0.4694] +24-11-19 20:23:41 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:41 | D | sum error = [ 2.8583, 3.0432, 3.2380, 3.4432, 3.6599] +24-11-19 20:23:41 | D | best error = [ 0.4694, 0.4694, 0.4694, 0.4694, 0.4694] +24-11-19 20:23:41 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:41 | D | sum error = [ 3.8866, 4.1276, 4.3804, 4.6469, 4.9257] +24-11-19 20:23:41 | D | best error = [ 0.4694, 0.4694, 0.4694, 0.4694, 0.4694] +24-11-19 20:23:41 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:41 | D | sum error = [ 5.2189, 5.5270, 5.8499, 6.1884, 6.5450] +24-11-19 20:23:41 | D | best error = [ 0.4694, 0.4694, 0.4694, 0.4694, 0.4694] +24-11-19 20:23:41 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:41 | D | sum error = [ 6.9175, 7.3086, 7.7174, 8.1460, 8.5940] +24-11-19 20:23:41 | D | best error = [ 0.4694, 0.4694, 0.4694, 0.4694, 0.4694] +24-11-19 20:23:41 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:41 | D | sum error = [ 9.0620, 9.5510, 10.0618, 10.5935, 11.1481] +24-11-19 20:23:41 | D | best error = [ 0.4694, 0.4694, 0.4694, 0.4694, 0.4694] +24-11-19 20:23:41 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:41 | D | sum error = [ 11.7241, 12.3271, 12.9539, 13.6046, 14.2795] +24-11-19 20:23:41 | D | best error = [ 0.4694, 0.4694, 0.4694, 0.4694, 0.4694] +24-11-19 20:23:41 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:41 | D | sum error = [ 14.9826, 15.7139, 16.4725, 17.2583, 18.0723] +24-11-19 20:23:41 | D | best error = [ 0.4694, 0.4694, 0.4694, 0.4694, 0.4694] +24-11-19 20:23:41 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:41 | D | sum error = [ 18.9165, 19.7905, 20.6956, 21.6315, 22.5992] +24-11-19 20:23:41 | D | best error = [ 0.4694, 0.4694, 0.4694, 0.4694, 0.4694] +24-11-19 20:23:41 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:41 | D | sum error = [ 23.5978, 24.6292, 25.6925, 26.7900, 27.9206] +24-11-19 20:23:41 | D | best error = [ 0.4694, 0.4694, 0.4694, 0.4694, 0.4694] +24-11-19 20:23:41 | D | + error = [0.4694] +24-11-19 20:23:41 | D | - Quantizing model.layers.7.self_attn.q_proj.weight +24-11-19 20:23:42 | D | - Quantizing model.layers.7.self_attn.k_proj.weight +24-11-19 20:23:43 | D | - Quantizing model.layers.7.self_attn.v_proj.weight +24-11-19 20:23:45 | D | - Quantizing model.layers.7.self_attn.o_proj.weight +24-11-19 20:23:47 | D | - Quantizing model.layers.7.mlp.up_proj.weight +24-11-19 20:23:48 | D | - Quantizing model.layers.7.mlp.gate_proj.weight +24-11-19 20:23:49 | D | - Quantizing model.layers.7.mlp.down_proj.weight +24-11-19 20:24:02 | D | - Quantizing layer model.layers.8 +24-11-19 20:24:02 | D | - Calibrating model.layers.8.self_attn.q_proj.weight +24-11-19 20:24:02 | D | + w: sint8 +24-11-19 20:24:02 | D | + x: None +24-11-19 20:24:02 | D | + y: None +24-11-19 20:24:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:24:02 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:24:02 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:24:03 | D | + finished calculating the original outputs, ram usage: 13.3 +24-11-19 20:24:03 | D | - range ratio = [ 1.0000] +24-11-19 20:24:03 | D | sum error = [ 3.4661] +24-11-19 20:24:03 | D | best error = [ 3.4661] +24-11-19 20:24:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:15 | D | sum error = [ 3.5190, 3.5160, 3.6719, 3.4575, 3.5315] +24-11-19 20:24:15 | D | best error = [ 3.4661, 3.4661, 3.4661, 3.4575, 3.4575] +24-11-19 20:24:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:15 | D | sum error = [ 3.6151, 3.7445, 4.0380, 4.2383, 4.3657] +24-11-19 20:24:15 | D | best error = [ 3.4575, 3.4575, 3.4575, 3.4575, 3.4575] +24-11-19 20:24:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:15 | D | sum error = [ 4.7640, 4.9038, 5.3723, 5.6693, 5.9691] +24-11-19 20:24:15 | D | best error = [ 3.4575, 3.4575, 3.4575, 3.4575, 3.4575] +24-11-19 20:24:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:15 | D | sum error = [ 6.4562, 6.9382, 7.6538, 8.1894, 8.7452] +24-11-19 20:24:15 | D | best error = [ 3.4575, 3.4575, 3.4575, 3.4575, 3.4575] +24-11-19 20:24:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:15 | D | sum error = [ 9.3643, 10.2534, 11.0012, 11.9216, 12.8657] +24-11-19 20:24:15 | D | best error = [ 3.4575, 3.4575, 3.4575, 3.4575, 3.4575] +24-11-19 20:24:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:15 | D | sum error = [ 13.8851, 14.9256, 16.1926, 17.5728, 19.0329] +24-11-19 20:24:15 | D | best error = [ 3.4575, 3.4575, 3.4575, 3.4575, 3.4575] +24-11-19 20:24:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:15 | D | sum error = [ 20.4228, 22.1951, 24.0915, 26.0132, 28.3466] +24-11-19 20:24:15 | D | best error = [ 3.4575, 3.4575, 3.4575, 3.4575, 3.4575] +24-11-19 20:24:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:15 | D | sum error = [ 30.6012, 33.0692, 35.7504, 38.6100, 41.6492] +24-11-19 20:24:15 | D | best error = [ 3.4575, 3.4575, 3.4575, 3.4575, 3.4575] +24-11-19 20:24:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:15 | D | sum error = [ 44.8283, 48.2893, 51.9067, 55.9281, 60.0973] +24-11-19 20:24:15 | D | best error = [ 3.4575, 3.4575, 3.4575, 3.4575, 3.4575] +24-11-19 20:24:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:15 | D | sum error = [ 64.6230, 69.3738, 74.3293, 79.6579, 85.0417] +24-11-19 20:24:15 | D | best error = [ 3.4575, 3.4575, 3.4575, 3.4575, 3.4575] +24-11-19 20:24:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:15 | D | sum error = [ 91.1012, 97.3432, 103.9550, 110.9733, 118.5048] +24-11-19 20:24:15 | D | best error = [ 3.4575, 3.4575, 3.4575, 3.4575, 3.4575] +24-11-19 20:24:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:15 | D | sum error = [ 126.4919, 134.8658, 143.5978, 152.9405, 162.7366] +24-11-19 20:24:15 | D | best error = [ 3.4575, 3.4575, 3.4575, 3.4575, 3.4575] +24-11-19 20:24:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:15 | D | sum error = [ 173.2539, 184.2159, 195.6186, 207.8587, 220.5206] +24-11-19 20:24:15 | D | best error = [ 3.4575, 3.4575, 3.4575, 3.4575, 3.4575] +24-11-19 20:24:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:15 | D | sum error = [ 233.7501, 247.6660, 262.0560, 276.9493, 292.4499] +24-11-19 20:24:15 | D | best error = [ 3.4575, 3.4575, 3.4575, 3.4575, 3.4575] +24-11-19 20:24:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:15 | D | sum error = [ 308.4116, 324.9226, 341.9390, 359.2809, 377.1343] +24-11-19 20:24:15 | D | best error = [ 3.4575, 3.4575, 3.4575, 3.4575, 3.4575] +24-11-19 20:24:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:15 | D | sum error = [ 395.3090, 413.7953, 432.5185, 451.2405, 470.1908] +24-11-19 20:24:15 | D | best error = [ 3.4575, 3.4575, 3.4575, 3.4575, 3.4575] +24-11-19 20:24:15 | D | + error = [3.4575] +24-11-19 20:24:15 | D | - Calibrating model.layers.8.self_attn.k_proj.weight +24-11-19 20:24:15 | D | + w: sint8 +24-11-19 20:24:15 | D | + x: None +24-11-19 20:24:15 | D | + y: None +24-11-19 20:24:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:24:15 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:15 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:16 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:16 | D | - range ratio = [ 1.0000] +24-11-19 20:24:16 | D | sum error = [ 2.8423] +24-11-19 20:24:16 | D | best error = [ 2.8423] +24-11-19 20:24:28 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:28 | D | sum error = [ 3.3984, 2.9835, 2.8214, 2.9553, 2.9799] +24-11-19 20:24:28 | D | best error = [ 2.8423, 2.8423, 2.8214, 2.8214, 2.8214] +24-11-19 20:24:28 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:28 | D | sum error = [ 3.2522, 3.4515, 3.2093, 3.5412, 3.5143] +24-11-19 20:24:28 | D | best error = [ 2.8214, 2.8214, 2.8214, 2.8214, 2.8214] +24-11-19 20:24:28 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:28 | D | sum error = [ 4.0517, 4.2532, 4.5503, 4.9189, 5.4015] +24-11-19 20:24:28 | D | best error = [ 2.8214, 2.8214, 2.8214, 2.8214, 2.8214] +24-11-19 20:24:28 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:28 | D | sum error = [ 5.6770, 6.1200, 6.2598, 6.9423, 7.5871] +24-11-19 20:24:28 | D | best error = [ 2.8214, 2.8214, 2.8214, 2.8214, 2.8214] +24-11-19 20:24:28 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:28 | D | sum error = [ 8.0793, 8.7473, 9.9799, 10.5542, 11.2035] +24-11-19 20:24:28 | D | best error = [ 2.8214, 2.8214, 2.8214, 2.8214, 2.8214] +24-11-19 20:24:28 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:28 | D | sum error = [ 11.9187, 12.8517, 13.8758, 15.4131, 16.2169] +24-11-19 20:24:28 | D | best error = [ 2.8214, 2.8214, 2.8214, 2.8214, 2.8214] +24-11-19 20:24:28 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:28 | D | sum error = [ 17.6516, 19.0772, 20.3387, 22.4235, 24.2682] +24-11-19 20:24:28 | D | best error = [ 2.8214, 2.8214, 2.8214, 2.8214, 2.8214] +24-11-19 20:24:28 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:28 | D | sum error = [ 26.3397, 28.6581, 30.7832, 33.5074, 36.3863] +24-11-19 20:24:28 | D | best error = [ 2.8214, 2.8214, 2.8214, 2.8214, 2.8214] +24-11-19 20:24:28 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:28 | D | sum error = [ 39.3557, 42.5245, 46.7036, 50.0363, 54.4543] +24-11-19 20:24:28 | D | best error = [ 2.8214, 2.8214, 2.8214, 2.8214, 2.8214] +24-11-19 20:24:28 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:28 | D | sum error = [ 58.6237, 63.8244, 69.1545, 74.3550, 80.1502] +24-11-19 20:24:28 | D | best error = [ 2.8214, 2.8214, 2.8214, 2.8214, 2.8214] +24-11-19 20:24:28 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:28 | D | sum error = [ 86.4887, 93.4242, 100.3044, 107.2203, 115.0936] +24-11-19 20:24:28 | D | best error = [ 2.8214, 2.8214, 2.8214, 2.8214, 2.8214] +24-11-19 20:24:28 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:28 | D | sum error = [ 123.1344, 131.9997, 141.0278, 150.6606, 160.4364] +24-11-19 20:24:28 | D | best error = [ 2.8214, 2.8214, 2.8214, 2.8214, 2.8214] +24-11-19 20:24:28 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:28 | D | sum error = [ 171.4951, 182.3884, 194.4510, 206.6106, 219.2574] +24-11-19 20:24:28 | D | best error = [ 2.8214, 2.8214, 2.8214, 2.8214, 2.8214] +24-11-19 20:24:28 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:28 | D | sum error = [ 232.7831, 246.7390, 261.4456, 276.6552, 292.1374] +24-11-19 20:24:28 | D | best error = [ 2.8214, 2.8214, 2.8214, 2.8214, 2.8214] +24-11-19 20:24:28 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:28 | D | sum error = [ 307.9809, 324.4488, 341.2668, 358.2876, 376.3016] +24-11-19 20:24:28 | D | best error = [ 2.8214, 2.8214, 2.8214, 2.8214, 2.8214] +24-11-19 20:24:28 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:28 | D | sum error = [ 393.9190, 412.3458, 430.5525, 449.1777, 468.3372] +24-11-19 20:24:28 | D | best error = [ 2.8214, 2.8214, 2.8214, 2.8214, 2.8214] +24-11-19 20:24:28 | D | + error = [2.8214] +24-11-19 20:24:28 | D | - Calibrating model.layers.8.self_attn.v_proj.weight +24-11-19 20:24:28 | D | + w: sint8 +24-11-19 20:24:28 | D | + x: None +24-11-19 20:24:28 | D | + y: None +24-11-19 20:24:28 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:28 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:28 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:28 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:28 | D | - range ratio = [ 1.0000] +24-11-19 20:24:28 | D | sum error = [ 1.2605] +24-11-19 20:24:28 | D | best error = [ 1.2605] +24-11-19 20:24:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:29 | D | sum error = [ 1.2596, 1.2429, 1.2569, 1.2737, 1.2946] +24-11-19 20:24:29 | D | best error = [ 1.1818, 1.1479, 1.1322, 1.1226, 1.1172] +24-11-19 20:24:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:29 | D | sum error = [ 1.3298, 1.3730, 1.4204, 1.4853, 1.5743] +24-11-19 20:24:29 | D | best error = [ 1.1153, 1.1139, 1.1135, 1.1135, 1.1135] +24-11-19 20:24:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:29 | D | sum error = [ 1.6740, 1.7800, 1.8900, 2.0185, 2.1591] +24-11-19 20:24:29 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:24:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:29 | D | sum error = [ 2.3206, 2.4872, 2.6690, 2.8543, 3.0664] +24-11-19 20:24:29 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:24:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:29 | D | sum error = [ 3.2911, 3.5228, 3.7752, 4.0314, 4.3186] +24-11-19 20:24:29 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:24:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:29 | D | sum error = [ 4.6191, 4.9184, 5.2776, 5.6322, 6.0146] +24-11-19 20:24:29 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:24:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:29 | D | sum error = [ 6.4039, 6.8142, 7.2584, 7.7245, 8.2196] +24-11-19 20:24:29 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:24:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:29 | D | sum error = [ 8.7293, 9.2843, 9.8474, 10.4480, 11.1000] +24-11-19 20:24:29 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:24:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:29 | D | sum error = [ 11.7584, 12.4682, 13.1998, 13.9762, 14.7856] +24-11-19 20:24:29 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:24:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:29 | D | sum error = [ 15.6335, 16.5239, 17.4429, 18.4143, 19.4270] +24-11-19 20:24:29 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:24:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:29 | D | sum error = [ 20.4902, 21.5896, 22.7624, 23.9676, 25.2321] +24-11-19 20:24:29 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:24:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:29 | D | sum error = [ 26.5499, 27.9248, 29.3588, 30.8570, 32.4194] +24-11-19 20:24:29 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:24:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:29 | D | sum error = [ 34.0430, 35.7377, 37.4989, 39.3448, 41.2515] +24-11-19 20:24:29 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:24:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:29 | D | sum error = [ 43.2337, 45.3025, 47.4331, 49.6524, 51.9436] +24-11-19 20:24:29 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:24:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:29 | D | sum error = [ 54.3171, 56.7626, 59.2936, 61.9126, 64.6099] +24-11-19 20:24:29 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:24:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:29 | D | sum error = [ 67.4020, 70.2784, 73.2406, 76.2897, 79.4222] +24-11-19 20:24:29 | D | best error = [ 1.1135, 1.1135, 1.1135, 1.1135, 1.1135] +24-11-19 20:24:29 | D | + error = [1.1135] +24-11-19 20:24:29 | D | - Calibrating model.layers.8.self_attn.o_proj.weight +24-11-19 20:24:29 | D | + w: sint8 +24-11-19 20:24:29 | D | + x: None +24-11-19 20:24:29 | D | + y: None +24-11-19 20:24:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:29 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:29 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:29 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:29 | D | - range ratio = [ 1.0000] +24-11-19 20:24:29 | D | sum error = [ 0.5011] +24-11-19 20:24:29 | D | best error = [ 0.5011] +24-11-19 20:24:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:29 | D | sum error = [ 0.4978, 0.4973, 0.4996, 0.5023, 0.5113] +24-11-19 20:24:29 | D | best error = [ 0.4565, 0.4378, 0.4270, 0.4201, 0.4153] +24-11-19 20:24:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:29 | D | sum error = [ 0.5200, 0.5387, 0.5551, 0.5763, 0.6056] +24-11-19 20:24:29 | D | best error = [ 0.4121, 0.4102, 0.4091, 0.4084, 0.4080] +24-11-19 20:24:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:29 | D | sum error = [ 0.6366, 0.6694, 0.7043, 0.7466, 0.7908] +24-11-19 20:24:29 | D | best error = [ 0.4078, 0.4076, 0.4075, 0.4074, 0.4074] +24-11-19 20:24:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:29 | D | sum error = [ 0.8441, 0.8941, 0.9510, 1.0105, 1.0713] +24-11-19 20:24:29 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:24:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:29 | D | sum error = [ 1.1388, 1.2093, 1.2863, 1.3631, 1.4494] +24-11-19 20:24:29 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:24:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:29 | D | sum error = [ 1.5361, 1.6307, 1.7281, 1.8294, 1.9360] +24-11-19 20:24:29 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:24:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:29 | D | sum error = [ 2.0506, 2.1689, 2.2938, 2.4236, 2.5601] +24-11-19 20:24:29 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:24:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:29 | D | sum error = [ 2.7059, 2.8533, 3.0125, 3.1735, 3.3437] +24-11-19 20:24:29 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:24:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:29 | D | sum error = [ 3.5234, 3.7092, 3.9019, 4.1039, 4.3116] +24-11-19 20:24:29 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:24:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:29 | D | sum error = [ 4.5289, 4.7529, 4.9866, 5.2312, 5.4855] +24-11-19 20:24:29 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:24:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:29 | D | sum error = [ 5.7469, 6.0195, 6.3026, 6.5977, 6.8997] +24-11-19 20:24:29 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:24:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:29 | D | sum error = [ 7.2123, 7.5405, 7.8777, 8.2249, 8.5848] +24-11-19 20:24:29 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:24:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:29 | D | sum error = [ 8.9555, 9.3380, 9.7330, 10.1427, 10.5619] +24-11-19 20:24:29 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:24:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:29 | D | sum error = [ 10.9937, 11.4379, 11.8942, 12.3655, 12.8468] +24-11-19 20:24:29 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:24:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:29 | D | sum error = [ 13.3425, 13.8507, 14.3744, 14.9128, 15.4687] +24-11-19 20:24:29 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:24:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:29 | D | sum error = [ 16.0417, 16.6311, 17.2381, 17.8623, 18.5057] +24-11-19 20:24:29 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:24:29 | D | + error = [0.4073] +24-11-19 20:24:29 | D | - Calibrating model.layers.8.mlp.up_proj.weight +24-11-19 20:24:29 | D | + w: sint8 +24-11-19 20:24:29 | D | + x: None +24-11-19 20:24:29 | D | + y: None +24-11-19 20:24:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:29 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:29 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:30 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:30 | D | - range ratio = [ 1.0000] +24-11-19 20:24:30 | D | sum error = [ 0.2641] +24-11-19 20:24:30 | D | best error = [ 0.2641] +24-11-19 20:24:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:31 | D | sum error = [ 0.2627, 0.2621, 0.2631, 0.2661, 0.2709] +24-11-19 20:24:31 | D | best error = [ 0.2495, 0.2425, 0.2388, 0.2369, 0.2358] +24-11-19 20:24:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:31 | D | sum error = [ 0.2780, 0.2877, 0.2992, 0.3135, 0.3300] +24-11-19 20:24:31 | D | best error = [ 0.2353, 0.2351, 0.2350, 0.2350, 0.2350] +24-11-19 20:24:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:31 | D | sum error = [ 0.3490, 0.3706, 0.3942, 0.4214, 0.4502] +24-11-19 20:24:31 | D | best error = [ 0.2350, 0.2350, 0.2350, 0.2350, 0.2350] +24-11-19 20:24:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:31 | D | sum error = [ 0.4818, 0.5166, 0.5526, 0.5927, 0.6354] +24-11-19 20:24:31 | D | best error = [ 0.2350, 0.2350, 0.2350, 0.2350, 0.2350] +24-11-19 20:24:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:31 | D | sum error = [ 0.6801, 0.7287, 0.7800, 0.8343, 0.8922] +24-11-19 20:24:31 | D | best error = [ 0.2350, 0.2350, 0.2350, 0.2350, 0.2350] +24-11-19 20:24:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:31 | D | sum error = [ 0.9535, 1.0187, 1.0880, 1.1613, 1.2378] +24-11-19 20:24:31 | D | best error = [ 0.2350, 0.2350, 0.2350, 0.2350, 0.2350] +24-11-19 20:24:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:31 | D | sum error = [ 1.3180, 1.4053, 1.4959, 1.5912, 1.6926] +24-11-19 20:24:31 | D | best error = [ 0.2350, 0.2350, 0.2350, 0.2350, 0.2350] +24-11-19 20:24:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:31 | D | sum error = [ 1.7976, 1.9099, 2.0273, 2.1532, 2.2814] +24-11-19 20:24:31 | D | best error = [ 0.2350, 0.2350, 0.2350, 0.2350, 0.2350] +24-11-19 20:24:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:31 | D | sum error = [ 2.4175, 2.5617, 2.7126, 2.8687, 3.0337] +24-11-19 20:24:31 | D | best error = [ 0.2350, 0.2350, 0.2350, 0.2350, 0.2350] +24-11-19 20:24:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:31 | D | sum error = [ 3.2088, 3.3878, 3.5788, 3.7787, 3.9860] +24-11-19 20:24:31 | D | best error = [ 0.2350, 0.2350, 0.2350, 0.2350, 0.2350] +24-11-19 20:24:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:31 | D | sum error = [ 4.2031, 4.4322, 4.6710, 4.9208, 5.1785] +24-11-19 20:24:31 | D | best error = [ 0.2350, 0.2350, 0.2350, 0.2350, 0.2350] +24-11-19 20:24:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:31 | D | sum error = [ 5.4517, 5.7333, 6.0282, 6.3349, 6.6549] +24-11-19 20:24:31 | D | best error = [ 0.2350, 0.2350, 0.2350, 0.2350, 0.2350] +24-11-19 20:24:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:31 | D | sum error = [ 6.9903, 7.3365, 7.6965, 8.0708, 8.4597] +24-11-19 20:24:31 | D | best error = [ 0.2350, 0.2350, 0.2350, 0.2350, 0.2350] +24-11-19 20:24:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:31 | D | sum error = [ 8.8621, 9.2788, 9.7122, 10.1603, 10.6246] +24-11-19 20:24:31 | D | best error = [ 0.2350, 0.2350, 0.2350, 0.2350, 0.2350] +24-11-19 20:24:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:31 | D | sum error = [ 11.1058, 11.6006, 12.1124, 12.6425, 13.1865] +24-11-19 20:24:31 | D | best error = [ 0.2350, 0.2350, 0.2350, 0.2350, 0.2350] +24-11-19 20:24:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:31 | D | sum error = [ 13.7537, 14.3273, 14.9315, 15.5453, 16.1811] +24-11-19 20:24:31 | D | best error = [ 0.2350, 0.2350, 0.2350, 0.2350, 0.2350] +24-11-19 20:24:31 | D | + error = [0.2350] +24-11-19 20:24:31 | D | - Calibrating model.layers.8.mlp.gate_proj.weight +24-11-19 20:24:31 | D | + w: sint8 +24-11-19 20:24:31 | D | + x: None +24-11-19 20:24:31 | D | + y: None +24-11-19 20:24:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:31 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:31 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:31 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:31 | D | - range ratio = [ 1.0000] +24-11-19 20:24:31 | D | sum error = [ 6.1287] +24-11-19 20:24:31 | D | best error = [ 6.1287] +24-11-19 20:24:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:32 | D | sum error = [ 6.0860, 6.0778, 6.1027, 6.1629, 6.2803] +24-11-19 20:24:32 | D | best error = [ 5.7421, 5.5911, 5.5097, 5.4645, 5.4406] +24-11-19 20:24:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:32 | D | sum error = [ 6.4480, 6.6752, 6.9506, 7.2789, 7.6642] +24-11-19 20:24:32 | D | best error = [ 5.4298, 5.4251, 5.4236, 5.4232, 5.4231] +24-11-19 20:24:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:32 | D | sum error = [ 8.1259, 8.6348, 9.2143, 9.8370, 10.5512] +24-11-19 20:24:32 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:24:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:32 | D | sum error = [ 11.3023, 12.1308, 13.0153, 13.9838, 15.0100] +24-11-19 20:24:32 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:24:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:32 | D | sum error = [ 16.1112, 17.2971, 18.5568, 19.8995, 21.3594] +24-11-19 20:24:32 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:24:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:32 | D | sum error = [ 22.8984, 24.5246, 26.2572, 28.1090, 30.0801] +24-11-19 20:24:32 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:24:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:32 | D | sum error = [ 32.1603, 34.3814, 36.7395, 39.2423, 41.8950] +24-11-19 20:24:32 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:24:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:32 | D | sum error = [ 44.7360, 47.7097, 50.9055, 54.2690, 57.8395] +24-11-19 20:24:32 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:24:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:32 | D | sum error = [ 61.6331, 65.6646, 69.9374, 74.4655, 79.2613] +24-11-19 20:24:32 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:24:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:32 | D | sum error = [ 84.3348, 89.7305, 95.4254, 101.4554, 107.8260] +24-11-19 20:24:32 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:24:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:32 | D | sum error = [ 114.5835, 121.6886, 129.2180, 137.1743, 145.5403] +24-11-19 20:24:32 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:24:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:32 | D | sum error = [ 154.3872, 163.6870, 173.4834, 183.7925, 194.6356] +24-11-19 20:24:32 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:24:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:32 | D | sum error = [ 206.0207, 217.9750, 230.5177, 243.6485, 257.3950] +24-11-19 20:24:32 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:24:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:32 | D | sum error = [ 271.7731, 286.8002, 302.4817, 318.8390, 335.9003] +24-11-19 20:24:32 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:24:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:32 | D | sum error = [ 353.6767, 372.1495, 391.3315, 411.2507, 431.8556] +24-11-19 20:24:32 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:24:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:32 | D | sum error = [ 453.2141, 475.2887, 498.1164, 521.6559, 545.9283] +24-11-19 20:24:32 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:24:32 | D | + error = [5.4231] +24-11-19 20:24:32 | D | - Calibrating model.layers.8.mlp.down_proj.weight +24-11-19 20:24:32 | D | + w: sint8 +24-11-19 20:24:32 | D | + x: None +24-11-19 20:24:32 | D | + y: None +24-11-19 20:24:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:32 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:33 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:33 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:33 | D | - range ratio = [ 1.0000] +24-11-19 20:24:33 | D | sum error = [ 0.5373] +24-11-19 20:24:33 | D | best error = [ 0.5373] +24-11-19 20:24:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:34 | D | sum error = [ 0.5320, 0.5274, 0.5247, 0.5244, 0.5247] +24-11-19 20:24:34 | D | best error = [ 0.5164, 0.5054, 0.4984, 0.4936, 0.4899] +24-11-19 20:24:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:34 | D | sum error = [ 0.5286, 0.5342, 0.5428, 0.5554, 0.5735] +24-11-19 20:24:34 | D | best error = [ 0.4872, 0.4854, 0.4843, 0.4837, 0.4832] +24-11-19 20:24:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:34 | D | sum error = [ 0.5936, 0.6187, 0.6485, 0.6849, 0.7240] +24-11-19 20:24:34 | D | best error = [ 0.4829, 0.4828, 0.4828, 0.4827, 0.4827] +24-11-19 20:24:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:34 | D | sum error = [ 0.7698, 0.8198, 0.8740, 0.9357, 1.0004] +24-11-19 20:24:34 | D | best error = [ 0.4827, 0.4827, 0.4827, 0.4827, 0.4827] +24-11-19 20:24:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:34 | D | sum error = [ 1.0731, 1.1506, 1.2336, 1.3220, 1.4176] +24-11-19 20:24:34 | D | best error = [ 0.4827, 0.4827, 0.4827, 0.4827, 0.4827] +24-11-19 20:24:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:34 | D | sum error = [ 1.5189, 1.6275, 1.7424, 1.8645, 1.9938] +24-11-19 20:24:34 | D | best error = [ 0.4827, 0.4827, 0.4827, 0.4827, 0.4827] +24-11-19 20:24:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:34 | D | sum error = [ 2.1309, 2.2772, 2.4315, 2.5940, 2.7664] +24-11-19 20:24:34 | D | best error = [ 0.4827, 0.4827, 0.4827, 0.4827, 0.4827] +24-11-19 20:24:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:34 | D | sum error = [ 2.9486, 3.1394, 3.3411, 3.5534, 3.7775] +24-11-19 20:24:34 | D | best error = [ 0.4827, 0.4827, 0.4827, 0.4827, 0.4827] +24-11-19 20:24:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:34 | D | sum error = [ 4.0136, 4.2630, 4.5230, 4.7967, 5.0857] +24-11-19 20:24:34 | D | best error = [ 0.4827, 0.4827, 0.4827, 0.4827, 0.4827] +24-11-19 20:24:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:34 | D | sum error = [ 5.3892, 5.7074, 6.0415, 6.3920, 6.7596] +24-11-19 20:24:34 | D | best error = [ 0.4827, 0.4827, 0.4827, 0.4827, 0.4827] +24-11-19 20:24:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:34 | D | sum error = [ 7.1446, 7.5473, 7.9698, 8.4128, 8.8747] +24-11-19 20:24:34 | D | best error = [ 0.4827, 0.4827, 0.4827, 0.4827, 0.4827] +24-11-19 20:24:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:34 | D | sum error = [ 9.3576, 9.8607, 10.3875, 10.9369, 11.5076] +24-11-19 20:24:34 | D | best error = [ 0.4827, 0.4827, 0.4827, 0.4827, 0.4827] +24-11-19 20:24:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:34 | D | sum error = [ 12.1033, 12.7250, 13.3727, 14.0452, 14.7441] +24-11-19 20:24:34 | D | best error = [ 0.4827, 0.4827, 0.4827, 0.4827, 0.4827] +24-11-19 20:24:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:34 | D | sum error = [ 15.4724, 16.2301, 17.0150, 17.8310, 18.6753] +24-11-19 20:24:34 | D | best error = [ 0.4827, 0.4827, 0.4827, 0.4827, 0.4827] +24-11-19 20:24:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:34 | D | sum error = [ 19.5528, 20.4610, 21.4017, 22.3734, 23.3775] +24-11-19 20:24:34 | D | best error = [ 0.4827, 0.4827, 0.4827, 0.4827, 0.4827] +24-11-19 20:24:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:34 | D | sum error = [ 24.4149, 25.4861, 26.5917, 27.7331, 28.9086] +24-11-19 20:24:34 | D | best error = [ 0.4827, 0.4827, 0.4827, 0.4827, 0.4827] +24-11-19 20:24:34 | D | + error = [0.4827] +24-11-19 20:24:34 | D | - Quantizing model.layers.8.self_attn.q_proj.weight +24-11-19 20:24:35 | D | - Quantizing model.layers.8.self_attn.k_proj.weight +24-11-19 20:24:36 | D | - Quantizing model.layers.8.self_attn.v_proj.weight +24-11-19 20:24:37 | D | - Quantizing model.layers.8.self_attn.o_proj.weight +24-11-19 20:24:38 | D | - Quantizing model.layers.8.mlp.up_proj.weight +24-11-19 20:24:39 | D | - Quantizing model.layers.8.mlp.gate_proj.weight +24-11-19 20:24:41 | D | - Quantizing model.layers.8.mlp.down_proj.weight +24-11-19 20:24:55 | D | - Quantizing layer model.layers.9 +24-11-19 20:24:55 | D | - Calibrating model.layers.9.self_attn.q_proj.weight +24-11-19 20:24:55 | D | + w: sint8 +24-11-19 20:24:55 | D | + x: None +24-11-19 20:24:55 | D | + y: None +24-11-19 20:24:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:24:55 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:24:55 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:24:56 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:24:56 | D | - range ratio = [ 1.0000] +24-11-19 20:24:56 | D | sum error = [ 3.9479] +24-11-19 20:24:56 | D | best error = [ 3.9479] +24-11-19 20:25:09 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:09 | D | sum error = [ 3.8356, 3.8682, 3.8354, 3.8610, 3.9304] +24-11-19 20:25:09 | D | best error = [ 3.8356, 3.8356, 3.8354, 3.8354, 3.8354] +24-11-19 20:25:09 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:09 | D | sum error = [ 4.0567, 4.3054, 4.4103, 4.6555, 4.9950] +24-11-19 20:25:09 | D | best error = [ 3.8354, 3.8354, 3.8354, 3.8354, 3.8354] +24-11-19 20:25:09 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:09 | D | sum error = [ 5.3021, 5.5168, 6.0450, 6.5601, 7.0475] +24-11-19 20:25:09 | D | best error = [ 3.8354, 3.8354, 3.8354, 3.8354, 3.8354] +24-11-19 20:25:09 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:09 | D | sum error = [ 7.6327, 8.1458, 8.7743, 9.4948, 10.1727] +24-11-19 20:25:09 | D | best error = [ 3.8354, 3.8354, 3.8354, 3.8354, 3.8354] +24-11-19 20:25:09 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:09 | D | sum error = [ 11.2774, 11.9260, 13.1366, 14.1456, 15.9305] +24-11-19 20:25:09 | D | best error = [ 3.8354, 3.8354, 3.8354, 3.8354, 3.8354] +24-11-19 20:25:09 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:09 | D | sum error = [ 16.8724, 18.2728, 19.8883, 21.4833, 23.2433] +24-11-19 20:25:09 | D | best error = [ 3.8354, 3.8354, 3.8354, 3.8354, 3.8354] +24-11-19 20:25:09 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:09 | D | sum error = [ 25.1571, 27.1835, 29.3076, 31.5665, 34.1768] +24-11-19 20:25:09 | D | best error = [ 3.8354, 3.8354, 3.8354, 3.8354, 3.8354] +24-11-19 20:25:09 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:09 | D | sum error = [ 36.9887, 40.0930, 43.3271, 46.5483, 50.4761] +24-11-19 20:25:09 | D | best error = [ 3.8354, 3.8354, 3.8354, 3.8354, 3.8354] +24-11-19 20:25:09 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:09 | D | sum error = [ 54.2509, 58.4582, 62.8918, 67.6484, 72.8615] +24-11-19 20:25:09 | D | best error = [ 3.8354, 3.8354, 3.8354, 3.8354, 3.8354] +24-11-19 20:25:09 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:09 | D | sum error = [ 78.4363, 84.4917, 90.6204, 97.4915, 104.6422] +24-11-19 20:25:09 | D | best error = [ 3.8354, 3.8354, 3.8354, 3.8354, 3.8354] +24-11-19 20:25:09 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:09 | D | sum error = [ 112.4851, 120.4360, 129.0920, 138.3437, 148.3007] +24-11-19 20:25:09 | D | best error = [ 3.8354, 3.8354, 3.8354, 3.8354, 3.8354] +24-11-19 20:25:09 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:09 | D | sum error = [ 158.5434, 169.4222, 180.8662, 192.7848, 205.2918] +24-11-19 20:25:09 | D | best error = [ 3.8354, 3.8354, 3.8354, 3.8354, 3.8354] +24-11-19 20:25:09 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:09 | D | sum error = [ 218.5349, 232.1967, 246.5494, 261.5170, 277.0200] +24-11-19 20:25:09 | D | best error = [ 3.8354, 3.8354, 3.8354, 3.8354, 3.8354] +24-11-19 20:25:09 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:09 | D | sum error = [ 293.2474, 310.1512, 327.6333, 345.9215, 364.6068] +24-11-19 20:25:09 | D | best error = [ 3.8354, 3.8354, 3.8354, 3.8354, 3.8354] +24-11-19 20:25:09 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:09 | D | sum error = [ 383.7372, 403.5579, 423.9360, 444.3203, 465.0691] +24-11-19 20:25:09 | D | best error = [ 3.8354, 3.8354, 3.8354, 3.8354, 3.8354] +24-11-19 20:25:09 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:09 | D | sum error = [ 485.8725, 506.8852, 527.7929, 548.8275, 569.8655] +24-11-19 20:25:09 | D | best error = [ 3.8354, 3.8354, 3.8354, 3.8354, 3.8354] +24-11-19 20:25:09 | D | + error = [3.8354] +24-11-19 20:25:10 | D | - Calibrating model.layers.9.self_attn.k_proj.weight +24-11-19 20:25:10 | D | + w: sint8 +24-11-19 20:25:10 | D | + x: None +24-11-19 20:25:10 | D | + y: None +24-11-19 20:25:10 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:25:10 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:10 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:10 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:10 | D | - range ratio = [ 1.0000] +24-11-19 20:25:10 | D | sum error = [ 3.1349] +24-11-19 20:25:10 | D | best error = [ 3.1349] +24-11-19 20:25:24 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:24 | D | sum error = [ 3.2871, 3.1323, 3.3696, 3.2957, 3.7409] +24-11-19 20:25:24 | D | best error = [ 3.1349, 3.1323, 3.1323, 3.1323, 3.1323] +24-11-19 20:25:24 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:24 | D | sum error = [ 3.2452, 3.6402, 3.7805, 3.8227, 4.4241] +24-11-19 20:25:24 | D | best error = [ 3.1323, 3.1323, 3.1323, 3.1323, 3.1323] +24-11-19 20:25:24 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:24 | D | sum error = [ 4.1346, 5.0603, 5.5117, 5.8538, 6.4954] +24-11-19 20:25:24 | D | best error = [ 3.1323, 3.1323, 3.1323, 3.1323, 3.1323] +24-11-19 20:25:24 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:24 | D | sum error = [ 6.7388, 7.4997, 7.5629, 9.1079, 9.0120] +24-11-19 20:25:24 | D | best error = [ 3.1323, 3.1323, 3.1323, 3.1323, 3.1323] +24-11-19 20:25:24 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:24 | D | sum error = [ 10.0377, 10.7274, 12.0999, 13.0537, 14.1348] +24-11-19 20:25:24 | D | best error = [ 3.1323, 3.1323, 3.1323, 3.1323, 3.1323] +24-11-19 20:25:24 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:24 | D | sum error = [ 15.2363, 17.0042, 17.9123, 19.7207, 20.9152] +24-11-19 20:25:24 | D | best error = [ 3.1323, 3.1323, 3.1323, 3.1323, 3.1323] +24-11-19 20:25:24 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:24 | D | sum error = [ 22.5090, 24.9215, 26.7647, 28.5956, 30.8292] +24-11-19 20:25:24 | D | best error = [ 3.1323, 3.1323, 3.1323, 3.1323, 3.1323] +24-11-19 20:25:24 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:24 | D | sum error = [ 33.4113, 36.4006, 39.6276, 42.9408, 46.0407] +24-11-19 20:25:24 | D | best error = [ 3.1323, 3.1323, 3.1323, 3.1323, 3.1323] +24-11-19 20:25:24 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:24 | D | sum error = [ 49.0577, 53.0832, 57.9339, 62.4299, 66.7715] +24-11-19 20:25:24 | D | best error = [ 3.1323, 3.1323, 3.1323, 3.1323, 3.1323] +24-11-19 20:25:24 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:24 | D | sum error = [ 71.5852, 77.4876, 82.6936, 88.8588, 95.6135] +24-11-19 20:25:24 | D | best error = [ 3.1323, 3.1323, 3.1323, 3.1323, 3.1323] +24-11-19 20:25:24 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:24 | D | sum error = [ 103.3101, 110.5065, 118.4986, 127.1394, 136.2955] +24-11-19 20:25:24 | D | best error = [ 3.1323, 3.1323, 3.1323, 3.1323, 3.1323] +24-11-19 20:25:24 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:24 | D | sum error = [ 146.2923, 156.3260, 166.7823, 179.7720, 191.6645] +24-11-19 20:25:24 | D | best error = [ 3.1323, 3.1323, 3.1323, 3.1323, 3.1323] +24-11-19 20:25:24 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:24 | D | sum error = [ 204.1536, 217.7217, 231.6700, 246.4202, 262.2190] +24-11-19 20:25:24 | D | best error = [ 3.1323, 3.1323, 3.1323, 3.1323, 3.1323] +24-11-19 20:25:24 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:24 | D | sum error = [ 277.5873, 294.9295, 311.9312, 330.7058, 348.8256] +24-11-19 20:25:24 | D | best error = [ 3.1323, 3.1323, 3.1323, 3.1323, 3.1323] +24-11-19 20:25:24 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:24 | D | sum error = [ 368.4042, 388.3615, 408.6825, 429.6502, 451.7230] +24-11-19 20:25:24 | D | best error = [ 3.1323, 3.1323, 3.1323, 3.1323, 3.1323] +24-11-19 20:25:24 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:24 | D | sum error = [ 473.2138, 495.0608, 517.7383, 539.5269, 561.4201] +24-11-19 20:25:24 | D | best error = [ 3.1323, 3.1323, 3.1323, 3.1323, 3.1323] +24-11-19 20:25:24 | D | + error = [3.1323] +24-11-19 20:25:24 | D | - Calibrating model.layers.9.self_attn.v_proj.weight +24-11-19 20:25:24 | D | + w: sint8 +24-11-19 20:25:24 | D | + x: None +24-11-19 20:25:24 | D | + y: None +24-11-19 20:25:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:24 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:24 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:25 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:25 | D | - range ratio = [ 1.0000] +24-11-19 20:25:25 | D | sum error = [ 1.5156] +24-11-19 20:25:25 | D | best error = [ 1.5156] +24-11-19 20:25:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:25 | D | sum error = [ 1.4845, 1.4869, 1.4861, 1.5137, 1.5481] +24-11-19 20:25:25 | D | best error = [ 1.3919, 1.3500, 1.3307, 1.3184, 1.3130] +24-11-19 20:25:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:25 | D | sum error = [ 1.5736, 1.6195, 1.6910, 1.7684, 1.8773] +24-11-19 20:25:25 | D | best error = [ 1.3103, 1.3092, 1.3085, 1.3081, 1.3081] +24-11-19 20:25:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:25 | D | sum error = [ 1.9686, 2.0882, 2.2213, 2.3690, 2.5329] +24-11-19 20:25:25 | D | best error = [ 1.3081, 1.3081, 1.3081, 1.3081, 1.3081] +24-11-19 20:25:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:25 | D | sum error = [ 2.7144, 2.9170, 3.1263, 3.3474, 3.5932] +24-11-19 20:25:25 | D | best error = [ 1.3081, 1.3081, 1.3081, 1.3081, 1.3081] +24-11-19 20:25:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:25 | D | sum error = [ 3.8468, 4.1142, 4.4017, 4.7178, 5.0318] +24-11-19 20:25:25 | D | best error = [ 1.3081, 1.3081, 1.3081, 1.3081, 1.3081] +24-11-19 20:25:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:25 | D | sum error = [ 5.3654, 5.7428, 6.1357, 6.5291, 6.9685] +24-11-19 20:25:25 | D | best error = [ 1.3081, 1.3081, 1.3081, 1.3081, 1.3081] +24-11-19 20:25:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:25 | D | sum error = [ 7.4179, 7.9068, 8.4135, 8.9444, 9.5170] +24-11-19 20:25:25 | D | best error = [ 1.3081, 1.3081, 1.3081, 1.3081, 1.3081] +24-11-19 20:25:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:25 | D | sum error = [ 10.1042, 10.7327, 11.3957, 12.0976, 12.8040] +24-11-19 20:25:25 | D | best error = [ 1.3081, 1.3081, 1.3081, 1.3081, 1.3081] +24-11-19 20:25:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:25 | D | sum error = [ 13.5729, 14.3842, 15.2313, 16.1326, 17.0588] +24-11-19 20:25:25 | D | best error = [ 1.3081, 1.3081, 1.3081, 1.3081, 1.3081] +24-11-19 20:25:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:25 | D | sum error = [ 18.0454, 19.0804, 20.1645, 21.3044, 22.4918] +24-11-19 20:25:25 | D | best error = [ 1.3081, 1.3081, 1.3081, 1.3081, 1.3081] +24-11-19 20:25:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:25 | D | sum error = [ 23.7517, 25.0504, 26.4222, 27.8443, 29.3256] +24-11-19 20:25:25 | D | best error = [ 1.3081, 1.3081, 1.3081, 1.3081, 1.3081] +24-11-19 20:25:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:25 | D | sum error = [ 30.8808, 32.4898, 34.1791, 35.9357, 37.7564] +24-11-19 20:25:25 | D | best error = [ 1.3081, 1.3081, 1.3081, 1.3081, 1.3081] +24-11-19 20:25:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:25 | D | sum error = [ 39.6573, 41.6314, 43.6691, 45.7924, 48.0012] +24-11-19 20:25:25 | D | best error = [ 1.3081, 1.3081, 1.3081, 1.3081, 1.3081] +24-11-19 20:25:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:25 | D | sum error = [ 50.2934, 52.6616, 55.1276, 57.6744, 60.3188] +24-11-19 20:25:25 | D | best error = [ 1.3081, 1.3081, 1.3081, 1.3081, 1.3081] +24-11-19 20:25:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:25 | D | sum error = [ 63.0725, 65.9142, 68.8613, 71.9137, 75.0671] +24-11-19 20:25:25 | D | best error = [ 1.3081, 1.3081, 1.3081, 1.3081, 1.3081] +24-11-19 20:25:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:25 | D | sum error = [ 78.3034, 81.6614, 85.1170, 88.6768, 92.3419] +24-11-19 20:25:25 | D | best error = [ 1.3081, 1.3081, 1.3081, 1.3081, 1.3081] +24-11-19 20:25:25 | D | + error = [1.3081] +24-11-19 20:25:25 | D | - Calibrating model.layers.9.self_attn.o_proj.weight +24-11-19 20:25:25 | D | + w: sint8 +24-11-19 20:25:25 | D | + x: None +24-11-19 20:25:25 | D | + y: None +24-11-19 20:25:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:25 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:25 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:25 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:25 | D | - range ratio = [ 1.0000] +24-11-19 20:25:25 | D | sum error = [ 0.5988] +24-11-19 20:25:25 | D | best error = [ 0.5988] +24-11-19 20:25:26 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:26 | D | sum error = [ 0.5930, 0.5906, 0.5868, 0.5880, 0.5964] +24-11-19 20:25:26 | D | best error = [ 0.5446, 0.5202, 0.5059, 0.4950, 0.4882] +24-11-19 20:25:26 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:26 | D | sum error = [ 0.5957, 0.6081, 0.6182, 0.6324, 0.6502] +24-11-19 20:25:26 | D | best error = [ 0.4828, 0.4790, 0.4763, 0.4744, 0.4728] +24-11-19 20:25:26 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:26 | D | sum error = [ 0.6711, 0.6959, 0.7226, 0.7537, 0.7841] +24-11-19 20:25:26 | D | best error = [ 0.4717, 0.4711, 0.4706, 0.4703, 0.4700] +24-11-19 20:25:26 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:26 | D | sum error = [ 0.8264, 0.8686, 0.9098, 0.9581, 1.0101] +24-11-19 20:25:26 | D | best error = [ 0.4697, 0.4696, 0.4695, 0.4693, 0.4692] +24-11-19 20:25:26 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:26 | D | sum error = [ 1.0621, 1.1207, 1.1834, 1.2482, 1.3157] +24-11-19 20:25:26 | D | best error = [ 0.4691, 0.4690, 0.4690, 0.4690, 0.4689] +24-11-19 20:25:26 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:26 | D | sum error = [ 1.3890, 1.4620, 1.5435, 1.6301, 1.7198] +24-11-19 20:25:26 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 20:25:26 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:26 | D | sum error = [ 1.8136, 1.9097, 2.0153, 2.1215, 2.2344] +24-11-19 20:25:26 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 20:25:26 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:26 | D | sum error = [ 2.3529, 2.4800, 2.6100, 2.7484, 2.8941] +24-11-19 20:25:26 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 20:25:26 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:26 | D | sum error = [ 3.0423, 3.2009, 3.3630, 3.5377, 3.7171] +24-11-19 20:25:26 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 20:25:26 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:26 | D | sum error = [ 3.9092, 4.1077, 4.3167, 4.5312, 4.7592] +24-11-19 20:25:26 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 20:25:26 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:26 | D | sum error = [ 4.9990, 5.2462, 5.5024, 5.7738, 6.0575] +24-11-19 20:25:26 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 20:25:26 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:26 | D | sum error = [ 6.3517, 6.6594, 6.9775, 7.3091, 7.6532] +24-11-19 20:25:26 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 20:25:26 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:26 | D | sum error = [ 8.0122, 8.3840, 8.7702, 9.1733, 9.5953] +24-11-19 20:25:26 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 20:25:26 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:26 | D | sum error = [ 10.0305, 10.4824, 10.9523, 11.4373, 11.9387] +24-11-19 20:25:26 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 20:25:26 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:26 | D | sum error = [ 12.4577, 12.9967, 13.5530, 14.1284, 14.7243] +24-11-19 20:25:26 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 20:25:26 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:26 | D | sum error = [ 15.3431, 15.9823, 16.6455, 17.3307, 18.0441] +24-11-19 20:25:26 | D | best error = [ 0.4689, 0.4689, 0.4689, 0.4689, 0.4689] +24-11-19 20:25:26 | D | + error = [0.4689] +24-11-19 20:25:26 | D | - Calibrating model.layers.9.mlp.up_proj.weight +24-11-19 20:25:26 | D | + w: sint8 +24-11-19 20:25:26 | D | + x: None +24-11-19 20:25:26 | D | + y: None +24-11-19 20:25:26 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:26 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:26 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:26 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:26 | D | - range ratio = [ 1.0000] +24-11-19 20:25:26 | D | sum error = [ 0.2686] +24-11-19 20:25:26 | D | best error = [ 0.2686] +24-11-19 20:25:27 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:27 | D | sum error = [ 0.2665, 0.2657, 0.2668, 0.2700, 0.2749] +24-11-19 20:25:27 | D | best error = [ 0.2528, 0.2454, 0.2415, 0.2393, 0.2383] +24-11-19 20:25:27 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:27 | D | sum error = [ 0.2824, 0.2917, 0.3036, 0.3178, 0.3346] +24-11-19 20:25:27 | D | best error = [ 0.2377, 0.2375, 0.2374, 0.2373, 0.2373] +24-11-19 20:25:27 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:27 | D | sum error = [ 0.3542, 0.3753, 0.4003, 0.4278, 0.4564] +24-11-19 20:25:27 | D | best error = [ 0.2373, 0.2373, 0.2373, 0.2373, 0.2373] +24-11-19 20:25:27 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:27 | D | sum error = [ 0.4891, 0.5240, 0.5617, 0.6016, 0.6456] +24-11-19 20:25:27 | D | best error = [ 0.2373, 0.2373, 0.2373, 0.2373, 0.2373] +24-11-19 20:25:27 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:27 | D | sum error = [ 0.6915, 0.7413, 0.7942, 0.8498, 0.9091] +24-11-19 20:25:27 | D | best error = [ 0.2373, 0.2373, 0.2373, 0.2373, 0.2373] +24-11-19 20:25:27 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:27 | D | sum error = [ 0.9713, 1.0382, 1.1081, 1.1827, 1.2620] +24-11-19 20:25:27 | D | best error = [ 0.2373, 0.2373, 0.2373, 0.2373, 0.2373] +24-11-19 20:25:27 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:27 | D | sum error = [ 1.3441, 1.4321, 1.5249, 1.6225, 1.7253] +24-11-19 20:25:27 | D | best error = [ 0.2373, 0.2373, 0.2373, 0.2373, 0.2373] +24-11-19 20:25:27 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:27 | D | sum error = [ 1.8340, 1.9475, 2.0682, 2.1953, 2.3269] +24-11-19 20:25:27 | D | best error = [ 0.2373, 0.2373, 0.2373, 0.2373, 0.2373] +24-11-19 20:25:27 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:27 | D | sum error = [ 2.4660, 2.6125, 2.7665, 2.9272, 3.0966] +24-11-19 20:25:27 | D | best error = [ 0.2373, 0.2373, 0.2373, 0.2373, 0.2373] +24-11-19 20:25:27 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:27 | D | sum error = [ 3.2747, 3.4601, 3.6553, 3.8586, 4.0725] +24-11-19 20:25:27 | D | best error = [ 0.2373, 0.2373, 0.2373, 0.2373, 0.2373] +24-11-19 20:25:27 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:27 | D | sum error = [ 4.2979, 4.5309, 4.7737, 5.0282, 5.2956] +24-11-19 20:25:27 | D | best error = [ 0.2373, 0.2373, 0.2373, 0.2373, 0.2373] +24-11-19 20:25:27 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:27 | D | sum error = [ 5.5731, 5.8630, 6.1649, 6.4817, 6.8095] +24-11-19 20:25:27 | D | best error = [ 0.2373, 0.2373, 0.2373, 0.2373, 0.2373] +24-11-19 20:25:27 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:27 | D | sum error = [ 7.1513, 7.5084, 7.8746, 8.2618, 8.6576] +24-11-19 20:25:27 | D | best error = [ 0.2373, 0.2373, 0.2373, 0.2373, 0.2373] +24-11-19 20:25:27 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:27 | D | sum error = [ 9.0731, 9.4990, 9.9473, 10.4081, 10.8870] +24-11-19 20:25:27 | D | best error = [ 0.2373, 0.2373, 0.2373, 0.2373, 0.2373] +24-11-19 20:25:27 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:27 | D | sum error = [ 11.3780, 11.8883, 12.4130, 12.9627, 13.5305] +24-11-19 20:25:27 | D | best error = [ 0.2373, 0.2373, 0.2373, 0.2373, 0.2373] +24-11-19 20:25:27 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:27 | D | sum error = [ 14.1071, 14.7089, 15.3127, 15.9530, 16.6034] +24-11-19 20:25:27 | D | best error = [ 0.2373, 0.2373, 0.2373, 0.2373, 0.2373] +24-11-19 20:25:27 | D | + error = [0.2373] +24-11-19 20:25:27 | D | - Calibrating model.layers.9.mlp.gate_proj.weight +24-11-19 20:25:27 | D | + w: sint8 +24-11-19 20:25:27 | D | + x: None +24-11-19 20:25:27 | D | + y: None +24-11-19 20:25:27 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:27 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:27 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:27 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:27 | D | - range ratio = [ 1.0000] +24-11-19 20:25:27 | D | sum error = [ 6.2402] +24-11-19 20:25:27 | D | best error = [ 6.2402] +24-11-19 20:25:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:29 | D | sum error = [ 6.1803, 6.1856, 6.1930, 6.2769, 6.3896] +24-11-19 20:25:29 | D | best error = [ 5.8300, 5.6701, 5.5852, 5.5366, 5.5106] +24-11-19 20:25:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:29 | D | sum error = [ 6.5549, 6.7608, 7.0568, 7.3733, 7.7654] +24-11-19 20:25:29 | D | best error = [ 5.4997, 5.4947, 5.4927, 5.4921, 5.4920] +24-11-19 20:25:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:29 | D | sum error = [ 8.2381, 8.7376, 9.3241, 9.9540, 10.6554] +24-11-19 20:25:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 20:25:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:29 | D | sum error = [ 11.4143, 12.2600, 13.1533, 14.1183, 15.1730] +24-11-19 20:25:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 20:25:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:29 | D | sum error = [ 16.2883, 17.4942, 18.7592, 20.1430, 21.6196] +24-11-19 20:25:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 20:25:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:29 | D | sum error = [ 23.1745, 24.8245, 26.5893, 28.4721, 30.4693] +24-11-19 20:25:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 20:25:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:29 | D | sum error = [ 32.5958, 34.8545, 37.2696, 39.8206, 42.5355] +24-11-19 20:25:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 20:25:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:29 | D | sum error = [ 45.4098, 48.4704, 51.7207, 55.1503, 58.8199] +24-11-19 20:25:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 20:25:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:29 | D | sum error = [ 62.6900, 66.8309, 71.1781, 75.8122, 80.7250] +24-11-19 20:25:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 20:25:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:29 | D | sum error = [ 85.9325, 91.4576, 97.3016, 103.4905, 110.0273] +24-11-19 20:25:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 20:25:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:29 | D | sum error = [ 116.9512, 124.2699, 132.0088, 140.1773, 148.7806] +24-11-19 20:25:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 20:25:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:29 | D | sum error = [ 157.8651, 167.4479, 177.5322, 188.1377, 199.2886] +24-11-19 20:25:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 20:25:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:29 | D | sum error = [ 211.0233, 223.3298, 236.2451, 249.7953, 263.9966] +24-11-19 20:25:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 20:25:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:29 | D | sum error = [ 278.8272, 294.3407, 310.5632, 327.4671, 345.1030] +24-11-19 20:25:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 20:25:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:29 | D | sum error = [ 363.4488, 382.5650, 402.4151, 423.0434, 444.4268] +24-11-19 20:25:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 20:25:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:29 | D | sum error = [ 466.5673, 489.4820, 513.1523, 537.5875, 562.7764] +24-11-19 20:25:29 | D | best error = [ 5.4920, 5.4920, 5.4920, 5.4920, 5.4920] +24-11-19 20:25:29 | D | + error = [5.4920] +24-11-19 20:25:29 | D | - Calibrating model.layers.9.mlp.down_proj.weight +24-11-19 20:25:29 | D | + w: sint8 +24-11-19 20:25:29 | D | + x: None +24-11-19 20:25:29 | D | + y: None +24-11-19 20:25:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:29 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:29 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:29 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:29 | D | - range ratio = [ 1.0000] +24-11-19 20:25:29 | D | sum error = [ 0.5615] +24-11-19 20:25:29 | D | best error = [ 0.5615] +24-11-19 20:25:30 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:30 | D | sum error = [ 0.5581, 0.5527, 0.5490, 0.5484, 0.5501] +24-11-19 20:25:30 | D | best error = [ 0.5384, 0.5263, 0.5186, 0.5128, 0.5086] +24-11-19 20:25:30 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:30 | D | sum error = [ 0.5531, 0.5592, 0.5696, 0.5834, 0.6030] +24-11-19 20:25:30 | D | best error = [ 0.5058, 0.5038, 0.5024, 0.5017, 0.5014] +24-11-19 20:25:30 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:30 | D | sum error = [ 0.6239, 0.6517, 0.6830, 0.7217, 0.7637] +24-11-19 20:25:30 | D | best error = [ 0.5011, 0.5010, 0.5010, 0.5010, 0.5009] +24-11-19 20:25:30 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:30 | D | sum error = [ 0.8113, 0.8635, 0.9212, 0.9858, 1.0561] +24-11-19 20:25:30 | D | best error = [ 0.5009, 0.5009, 0.5009, 0.5009, 0.5009] +24-11-19 20:25:30 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:30 | D | sum error = [ 1.1293, 1.2078, 1.2966, 1.3887, 1.4880] +24-11-19 20:25:30 | D | best error = [ 0.5009, 0.5009, 0.5009, 0.5009, 0.5009] +24-11-19 20:25:30 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:30 | D | sum error = [ 1.5930, 1.7057, 1.8249, 1.9515, 2.0857] +24-11-19 20:25:30 | D | best error = [ 0.5009, 0.5009, 0.5009, 0.5009, 0.5009] +24-11-19 20:25:30 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:30 | D | sum error = [ 2.2281, 2.3785, 2.5397, 2.7095, 2.8875] +24-11-19 20:25:30 | D | best error = [ 0.5009, 0.5009, 0.5009, 0.5009, 0.5009] +24-11-19 20:25:30 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:30 | D | sum error = [ 3.0763, 3.2753, 3.4864, 3.7084, 3.9406] +24-11-19 20:25:30 | D | best error = [ 0.5009, 0.5009, 0.5009, 0.5009, 0.5009] +24-11-19 20:25:30 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:30 | D | sum error = [ 4.1879, 4.4471, 4.7193, 5.0062, 5.3073] +24-11-19 20:25:30 | D | best error = [ 0.5009, 0.5009, 0.5009, 0.5009, 0.5009] +24-11-19 20:25:30 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:30 | D | sum error = [ 5.6244, 5.9572, 6.3056, 6.6729, 7.0567] +24-11-19 20:25:30 | D | best error = [ 0.5009, 0.5009, 0.5009, 0.5009, 0.5009] +24-11-19 20:25:30 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:30 | D | sum error = [ 7.4595, 7.8803, 8.3197, 8.7798, 9.2599] +24-11-19 20:25:30 | D | best error = [ 0.5009, 0.5009, 0.5009, 0.5009, 0.5009] +24-11-19 20:25:30 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:30 | D | sum error = [ 9.7627, 10.2868, 10.8352, 11.4064, 12.0009] +24-11-19 20:25:30 | D | best error = [ 0.5009, 0.5009, 0.5009, 0.5009, 0.5009] +24-11-19 20:25:30 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:30 | D | sum error = [ 12.6200, 13.2668, 13.9404, 14.6392, 15.3639] +24-11-19 20:25:30 | D | best error = [ 0.5009, 0.5009, 0.5009, 0.5009, 0.5009] +24-11-19 20:25:30 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:30 | D | sum error = [ 16.1188, 16.9035, 17.7160, 18.5591, 19.4320] +24-11-19 20:25:30 | D | best error = [ 0.5009, 0.5009, 0.5009, 0.5009, 0.5009] +24-11-19 20:25:30 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:30 | D | sum error = [ 20.3360, 21.2725, 22.2426, 23.2454, 24.2828] +24-11-19 20:25:30 | D | best error = [ 0.5009, 0.5009, 0.5009, 0.5009, 0.5009] +24-11-19 20:25:30 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:30 | D | sum error = [ 25.3540, 26.4603, 27.5997, 28.7755, 29.9862] +24-11-19 20:25:30 | D | best error = [ 0.5009, 0.5009, 0.5009, 0.5009, 0.5009] +24-11-19 20:25:30 | D | + error = [0.5009] +24-11-19 20:25:30 | D | - Quantizing model.layers.9.self_attn.q_proj.weight +24-11-19 20:25:31 | D | - Quantizing model.layers.9.self_attn.k_proj.weight +24-11-19 20:25:32 | D | - Quantizing model.layers.9.self_attn.v_proj.weight +24-11-19 20:25:33 | D | - Quantizing model.layers.9.self_attn.o_proj.weight +24-11-19 20:25:35 | D | - Quantizing model.layers.9.mlp.up_proj.weight +24-11-19 20:25:36 | D | - Quantizing model.layers.9.mlp.gate_proj.weight +24-11-19 20:25:39 | D | - Quantizing model.layers.9.mlp.down_proj.weight +24-11-19 20:25:52 | D | - Quantizing layer model.layers.10 +24-11-19 20:25:52 | D | - Calibrating model.layers.10.self_attn.q_proj.weight +24-11-19 20:25:52 | D | + w: sint8 +24-11-19 20:25:52 | D | + x: None +24-11-19 20:25:52 | D | + y: None +24-11-19 20:25:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:25:52 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:25:52 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:25:53 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:25:53 | D | - range ratio = [ 1.0000] +24-11-19 20:25:53 | D | sum error = [ 4.0744] +24-11-19 20:25:53 | D | best error = [ 4.0744] +24-11-19 20:26:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:07 | D | sum error = [ 3.9990, 4.0939, 4.1248, 4.1749, 4.2051] +24-11-19 20:26:07 | D | best error = [ 3.9990, 3.9990, 3.9990, 3.9990, 3.9990] +24-11-19 20:26:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:07 | D | sum error = [ 4.3530, 4.4558, 4.5108, 5.0099, 5.1017] +24-11-19 20:26:07 | D | best error = [ 3.9990, 3.9990, 3.9990, 3.9990, 3.9990] +24-11-19 20:26:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:07 | D | sum error = [ 5.4973, 5.8754, 6.3300, 6.9126, 7.5881] +24-11-19 20:26:07 | D | best error = [ 3.9990, 3.9990, 3.9990, 3.9990, 3.9990] +24-11-19 20:26:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:07 | D | sum error = [ 8.0877, 8.6773, 9.6858, 10.3778, 11.1878] +24-11-19 20:26:07 | D | best error = [ 3.9990, 3.9990, 3.9990, 3.9990, 3.9990] +24-11-19 20:26:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:07 | D | sum error = [ 12.0853, 13.2905, 14.3344, 15.5185, 17.0069] +24-11-19 20:26:07 | D | best error = [ 3.9990, 3.9990, 3.9990, 3.9990, 3.9990] +24-11-19 20:26:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:07 | D | sum error = [ 17.8900, 19.5677, 20.6829, 22.4541, 24.0692] +24-11-19 20:26:07 | D | best error = [ 3.9990, 3.9990, 3.9990, 3.9990, 3.9990] +24-11-19 20:26:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:07 | D | sum error = [ 26.0578, 28.0437, 29.7895, 32.0035, 34.3606] +24-11-19 20:26:07 | D | best error = [ 3.9990, 3.9990, 3.9990, 3.9990, 3.9990] +24-11-19 20:26:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:07 | D | sum error = [ 36.9499, 40.0758, 42.9451, 46.3177, 49.6406] +24-11-19 20:26:07 | D | best error = [ 3.9990, 3.9990, 3.9990, 3.9990, 3.9990] +24-11-19 20:26:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:07 | D | sum error = [ 53.0939, 57.2757, 60.9080, 65.1361, 69.6326] +24-11-19 20:26:07 | D | best error = [ 3.9990, 3.9990, 3.9990, 3.9990, 3.9990] +24-11-19 20:26:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:07 | D | sum error = [ 74.2065, 79.1289, 84.4617, 90.3630, 96.3691] +24-11-19 20:26:07 | D | best error = [ 3.9990, 3.9990, 3.9990, 3.9990, 3.9990] +24-11-19 20:26:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:07 | D | sum error = [ 102.9723, 109.7551, 117.1584, 124.8586, 133.0450] +24-11-19 20:26:07 | D | best error = [ 3.9990, 3.9990, 3.9990, 3.9990, 3.9990] +24-11-19 20:26:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:07 | D | sum error = [ 141.5533, 150.8878, 160.4778, 170.7330, 181.4384] +24-11-19 20:26:07 | D | best error = [ 3.9990, 3.9990, 3.9990, 3.9990, 3.9990] +24-11-19 20:26:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:07 | D | sum error = [ 192.7478, 204.7772, 217.4328, 230.7131, 244.6748] +24-11-19 20:26:07 | D | best error = [ 3.9990, 3.9990, 3.9990, 3.9990, 3.9990] +24-11-19 20:26:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:07 | D | sum error = [ 259.2490, 274.8158, 291.0541, 308.0828, 325.9192] +24-11-19 20:26:07 | D | best error = [ 3.9990, 3.9990, 3.9990, 3.9990, 3.9990] +24-11-19 20:26:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:07 | D | sum error = [ 344.5512, 363.8713, 383.7535, 404.5020, 425.6313] +24-11-19 20:26:07 | D | best error = [ 3.9990, 3.9990, 3.9990, 3.9990, 3.9990] +24-11-19 20:26:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:07 | D | sum error = [ 447.3677, 469.6705, 492.1731, 515.0129, 537.9665] +24-11-19 20:26:07 | D | best error = [ 3.9990, 3.9990, 3.9990, 3.9990, 3.9990] +24-11-19 20:26:07 | D | + error = [3.9990] +24-11-19 20:26:07 | D | - Calibrating model.layers.10.self_attn.k_proj.weight +24-11-19 20:26:07 | D | + w: sint8 +24-11-19 20:26:07 | D | + x: None +24-11-19 20:26:07 | D | + y: None +24-11-19 20:26:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:26:07 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:07 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:07 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:07 | D | - range ratio = [ 1.0000] +24-11-19 20:26:07 | D | sum error = [ 3.5632] +24-11-19 20:26:07 | D | best error = [ 3.5632] +24-11-19 20:26:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:20 | D | sum error = [ 3.3686, 3.6174, 3.5198, 3.5783, 3.5089] +24-11-19 20:26:20 | D | best error = [ 3.3686, 3.3686, 3.3686, 3.3686, 3.3686] +24-11-19 20:26:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:20 | D | sum error = [ 4.2147, 3.9705, 3.9660, 4.4995, 5.0704] +24-11-19 20:26:20 | D | best error = [ 3.3686, 3.3686, 3.3686, 3.3686, 3.3686] +24-11-19 20:26:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:20 | D | sum error = [ 4.9674, 6.0738, 5.8913, 6.7250, 7.1537] +24-11-19 20:26:20 | D | best error = [ 3.3686, 3.3686, 3.3686, 3.3686, 3.3686] +24-11-19 20:26:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:20 | D | sum error = [ 7.4831, 9.2685, 9.8616, 10.3229, 11.9702] +24-11-19 20:26:20 | D | best error = [ 3.3686, 3.3686, 3.3686, 3.3686, 3.3686] +24-11-19 20:26:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:20 | D | sum error = [ 12.9350, 13.9550, 14.6263, 16.0908, 18.0552] +24-11-19 20:26:20 | D | best error = [ 3.3686, 3.3686, 3.3686, 3.3686, 3.3686] +24-11-19 20:26:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:20 | D | sum error = [ 18.5659, 21.2878, 22.0383, 22.9320, 24.1115] +24-11-19 20:26:20 | D | best error = [ 3.3686, 3.3686, 3.3686, 3.3686, 3.3686] +24-11-19 20:26:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:20 | D | sum error = [ 26.1687, 27.7690, 30.3064, 32.7913, 34.9534] +24-11-19 20:26:20 | D | best error = [ 3.3686, 3.3686, 3.3686, 3.3686, 3.3686] +24-11-19 20:26:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:20 | D | sum error = [ 37.4578, 40.9557, 43.4528, 47.8020, 49.9907] +24-11-19 20:26:20 | D | best error = [ 3.3686, 3.3686, 3.3686, 3.3686, 3.3686] +24-11-19 20:26:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:20 | D | sum error = [ 53.9077, 57.5347, 61.7364, 65.6575, 70.5509] +24-11-19 20:26:20 | D | best error = [ 3.3686, 3.3686, 3.3686, 3.3686, 3.3686] +24-11-19 20:26:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:20 | D | sum error = [ 74.7645, 79.6545, 84.7719, 90.6339, 96.7535] +24-11-19 20:26:20 | D | best error = [ 3.3686, 3.3686, 3.3686, 3.3686, 3.3686] +24-11-19 20:26:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:20 | D | sum error = [ 102.9314, 109.0955, 117.1452, 124.7259, 132.5336] +24-11-19 20:26:20 | D | best error = [ 3.3686, 3.3686, 3.3686, 3.3686, 3.3686] +24-11-19 20:26:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:20 | D | sum error = [ 140.8717, 149.6178, 159.1969, 169.4002, 180.0876] +24-11-19 20:26:20 | D | best error = [ 3.3686, 3.3686, 3.3686, 3.3686, 3.3686] +24-11-19 20:26:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:20 | D | sum error = [ 191.4267, 203.0155, 215.2980, 227.7346, 240.4168] +24-11-19 20:26:20 | D | best error = [ 3.3686, 3.3686, 3.3686, 3.3686, 3.3686] +24-11-19 20:26:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:20 | D | sum error = [ 254.1343, 268.6282, 283.9061, 300.3595, 317.5095] +24-11-19 20:26:20 | D | best error = [ 3.3686, 3.3686, 3.3686, 3.3686, 3.3686] +24-11-19 20:26:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:20 | D | sum error = [ 336.2905, 355.8751, 375.8542, 397.2540, 418.4187] +24-11-19 20:26:20 | D | best error = [ 3.3686, 3.3686, 3.3686, 3.3686, 3.3686] +24-11-19 20:26:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:20 | D | sum error = [ 440.9849, 462.7956, 485.6911, 509.0475, 533.0272] +24-11-19 20:26:20 | D | best error = [ 3.3686, 3.3686, 3.3686, 3.3686, 3.3686] +24-11-19 20:26:20 | D | + error = [3.3686] +24-11-19 20:26:20 | D | - Calibrating model.layers.10.self_attn.v_proj.weight +24-11-19 20:26:20 | D | + w: sint8 +24-11-19 20:26:20 | D | + x: None +24-11-19 20:26:20 | D | + y: None +24-11-19 20:26:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:20 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:20 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:20 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:20 | D | - range ratio = [ 1.0000] +24-11-19 20:26:20 | D | sum error = [ 1.2932] +24-11-19 20:26:20 | D | best error = [ 1.2932] +24-11-19 20:26:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:20 | D | sum error = [ 1.3014, 1.2853, 1.2941, 1.3081, 1.3241] +24-11-19 20:26:20 | D | best error = [ 1.2036, 1.1667, 1.1481, 1.1376, 1.1307] +24-11-19 20:26:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:20 | D | sum error = [ 1.3685, 1.4234, 1.4742, 1.5508, 1.6301] +24-11-19 20:26:20 | D | best error = [ 1.1289, 1.1277, 1.1274, 1.1273, 1.1273] +24-11-19 20:26:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:20 | D | sum error = [ 1.7165, 1.8472, 1.9670, 2.1093, 2.2625] +24-11-19 20:26:20 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:26:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:20 | D | sum error = [ 2.4047, 2.5820, 2.7854, 2.9852, 3.2138] +24-11-19 20:26:20 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:26:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:20 | D | sum error = [ 3.4368, 3.6794, 3.9366, 4.2032, 4.4994] +24-11-19 20:26:20 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:26:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:20 | D | sum error = [ 4.8142, 5.1414, 5.4714, 5.8593, 6.2332] +24-11-19 20:26:20 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:26:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:20 | D | sum error = [ 6.6527, 7.0762, 7.5335, 8.0240, 8.5342] +24-11-19 20:26:20 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:26:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:20 | D | sum error = [ 9.0834, 9.6662, 10.2538, 10.8892, 11.5511] +24-11-19 20:26:20 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:26:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:20 | D | sum error = [ 12.2460, 12.9688, 13.7455, 14.5354, 15.3964] +24-11-19 20:26:20 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:26:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:20 | D | sum error = [ 16.2797, 17.2092, 18.1886, 19.2062, 20.2793] +24-11-19 20:26:20 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:26:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:20 | D | sum error = [ 21.4047, 22.5716, 23.8080, 25.0862, 26.4299] +24-11-19 20:26:20 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:26:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:20 | D | sum error = [ 27.8277, 29.2907, 30.8200, 32.4151, 34.0764] +24-11-19 20:26:20 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:26:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:20 | D | sum error = [ 35.8106, 37.6030, 39.4812, 41.4297, 43.4508] +24-11-19 20:26:20 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:26:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:20 | D | sum error = [ 45.5511, 47.7219, 49.9756, 52.3182, 54.7267] +24-11-19 20:26:20 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:26:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:20 | D | sum error = [ 57.2288, 59.8199, 62.4903, 65.2596, 68.1089] +24-11-19 20:26:20 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:26:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:20 | D | sum error = [ 71.0436, 74.0729, 77.1901, 80.4105, 83.7224] +24-11-19 20:26:20 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:26:20 | D | + error = [1.1273] +24-11-19 20:26:20 | D | - Calibrating model.layers.10.self_attn.o_proj.weight +24-11-19 20:26:20 | D | + w: sint8 +24-11-19 20:26:20 | D | + x: None +24-11-19 20:26:20 | D | + y: None +24-11-19 20:26:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:20 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:21 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:21 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:21 | D | - range ratio = [ 1.0000] +24-11-19 20:26:21 | D | sum error = [ 0.5436] +24-11-19 20:26:21 | D | best error = [ 0.5436] +24-11-19 20:26:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:21 | D | sum error = [ 0.5385, 0.5361, 0.5382, 0.5384, 0.5443] +24-11-19 20:26:21 | D | best error = [ 0.4867, 0.4644, 0.4507, 0.4419, 0.4359] +24-11-19 20:26:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:21 | D | sum error = [ 0.5546, 0.5648, 0.5830, 0.6030, 0.6261] +24-11-19 20:26:21 | D | best error = [ 0.4318, 0.4284, 0.4264, 0.4250, 0.4240] +24-11-19 20:26:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:21 | D | sum error = [ 0.6536, 0.6809, 0.7134, 0.7493, 0.7945] +24-11-19 20:26:21 | D | best error = [ 0.4233, 0.4227, 0.4223, 0.4219, 0.4216] +24-11-19 20:26:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:21 | D | sum error = [ 0.8386, 0.8857, 0.9349, 0.9938, 1.0504] +24-11-19 20:26:21 | D | best error = [ 0.4215, 0.4213, 0.4212, 0.4211, 0.4210] +24-11-19 20:26:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:21 | D | sum error = [ 1.1144, 1.1828, 1.2536, 1.3300, 1.4098] +24-11-19 20:26:21 | D | best error = [ 0.4210, 0.4209, 0.4209, 0.4209, 0.4208] +24-11-19 20:26:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:21 | D | sum error = [ 1.4935, 1.5854, 1.6739, 1.7753, 1.8759] +24-11-19 20:26:21 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:26:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:21 | D | sum error = [ 1.9882, 2.0995, 2.2159, 2.3414, 2.4732] +24-11-19 20:26:21 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:26:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:21 | D | sum error = [ 2.6109, 2.7540, 2.9058, 3.0639, 3.2277] +24-11-19 20:26:21 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:26:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:21 | D | sum error = [ 3.4022, 3.5793, 3.7716, 3.9681, 4.1740] +24-11-19 20:26:21 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:26:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:21 | D | sum error = [ 4.3875, 4.6126, 4.8456, 5.0894, 5.3399] +24-11-19 20:26:21 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:26:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:21 | D | sum error = [ 5.6041, 5.8788, 6.1637, 6.4561, 6.7660] +24-11-19 20:26:21 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:26:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:21 | D | sum error = [ 7.0848, 7.4166, 7.7594, 8.1184, 8.4867] +24-11-19 20:26:21 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:26:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:21 | D | sum error = [ 8.8704, 9.2653, 9.6764, 10.1030, 10.5406] +24-11-19 20:26:21 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:26:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:21 | D | sum error = [ 10.9968, 11.4654, 11.9486, 12.4490, 12.9632] +24-11-19 20:26:21 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:26:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:21 | D | sum error = [ 13.4951, 14.0404, 14.6033, 15.1840, 15.7812] +24-11-19 20:26:21 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:26:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:21 | D | sum error = [ 16.3949, 17.0266, 17.6762, 18.3421, 19.0266] +24-11-19 20:26:21 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:26:21 | D | + error = [0.4208] +24-11-19 20:26:21 | D | - Calibrating model.layers.10.mlp.up_proj.weight +24-11-19 20:26:21 | D | + w: sint8 +24-11-19 20:26:21 | D | + x: None +24-11-19 20:26:21 | D | + y: None +24-11-19 20:26:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:21 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:21 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:21 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:22 | D | - range ratio = [ 1.0000] +24-11-19 20:26:22 | D | sum error = [ 0.2801] +24-11-19 20:26:22 | D | best error = [ 0.2801] +24-11-19 20:26:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:23 | D | sum error = [ 0.2771, 0.2763, 0.2777, 0.2809, 0.2866] +24-11-19 20:26:23 | D | best error = [ 0.2619, 0.2540, 0.2499, 0.2477, 0.2465] +24-11-19 20:26:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:23 | D | sum error = [ 0.2939, 0.3039, 0.3155, 0.3307, 0.3481] +24-11-19 20:26:23 | D | best error = [ 0.2458, 0.2456, 0.2455, 0.2454, 0.2454] +24-11-19 20:26:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:23 | D | sum error = [ 0.3675, 0.3903, 0.4154, 0.4432, 0.4746] +24-11-19 20:26:23 | D | best error = [ 0.2454, 0.2454, 0.2454, 0.2454, 0.2454] +24-11-19 20:26:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:23 | D | sum error = [ 0.5082, 0.5434, 0.5827, 0.6246, 0.6691] +24-11-19 20:26:23 | D | best error = [ 0.2454, 0.2454, 0.2454, 0.2454, 0.2454] +24-11-19 20:26:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:23 | D | sum error = [ 0.7169, 0.7681, 0.8217, 0.8791, 0.9397] +24-11-19 20:26:23 | D | best error = [ 0.2454, 0.2454, 0.2454, 0.2454, 0.2454] +24-11-19 20:26:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:23 | D | sum error = [ 1.0049, 1.0743, 1.1463, 1.2227, 1.3036] +24-11-19 20:26:23 | D | best error = [ 0.2454, 0.2454, 0.2454, 0.2454, 0.2454] +24-11-19 20:26:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:23 | D | sum error = [ 1.3889, 1.4800, 1.5763, 1.6755, 1.7816] +24-11-19 20:26:23 | D | best error = [ 0.2454, 0.2454, 0.2454, 0.2454, 0.2454] +24-11-19 20:26:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:23 | D | sum error = [ 1.8930, 2.0116, 2.1338, 2.2650, 2.3999] +24-11-19 20:26:23 | D | best error = [ 0.2454, 0.2454, 0.2454, 0.2454, 0.2454] +24-11-19 20:26:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:23 | D | sum error = [ 2.5442, 2.6949, 2.8525, 3.0186, 3.1938] +24-11-19 20:26:23 | D | best error = [ 0.2454, 0.2454, 0.2454, 0.2454, 0.2454] +24-11-19 20:26:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:23 | D | sum error = [ 3.3764, 3.5677, 3.7669, 3.9769, 4.1961] +24-11-19 20:26:23 | D | best error = [ 0.2454, 0.2454, 0.2454, 0.2454, 0.2454] +24-11-19 20:26:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:23 | D | sum error = [ 4.4239, 4.6622, 4.9142, 5.1736, 5.4458] +24-11-19 20:26:23 | D | best error = [ 0.2454, 0.2454, 0.2454, 0.2454, 0.2454] +24-11-19 20:26:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:23 | D | sum error = [ 5.7320, 6.0273, 6.3338, 6.6550, 6.9904] +24-11-19 20:26:23 | D | best error = [ 0.2454, 0.2454, 0.2454, 0.2454, 0.2454] +24-11-19 20:26:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:23 | D | sum error = [ 7.3365, 7.6978, 8.0695, 8.4602, 8.8650] +24-11-19 20:26:23 | D | best error = [ 0.2454, 0.2454, 0.2454, 0.2454, 0.2454] +24-11-19 20:26:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:23 | D | sum error = [ 9.2855, 9.7170, 10.1725, 10.6383, 11.1202] +24-11-19 20:26:23 | D | best error = [ 0.2454, 0.2454, 0.2454, 0.2454, 0.2454] +24-11-19 20:26:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:23 | D | sum error = [ 11.6187, 12.1412, 12.6773, 13.2265, 13.7930] +24-11-19 20:26:23 | D | best error = [ 0.2454, 0.2454, 0.2454, 0.2454, 0.2454] +24-11-19 20:26:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:23 | D | sum error = [ 14.3865, 14.9910, 15.6083, 16.2621, 16.9207] +24-11-19 20:26:23 | D | best error = [ 0.2454, 0.2454, 0.2454, 0.2454, 0.2454] +24-11-19 20:26:23 | D | + error = [0.2454] +24-11-19 20:26:23 | D | - Calibrating model.layers.10.mlp.gate_proj.weight +24-11-19 20:26:23 | D | + w: sint8 +24-11-19 20:26:23 | D | + x: None +24-11-19 20:26:23 | D | + y: None +24-11-19 20:26:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:23 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:23 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:23 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:23 | D | - range ratio = [ 1.0000] +24-11-19 20:26:23 | D | sum error = [ 6.1665] +24-11-19 20:26:23 | D | best error = [ 6.1665] +24-11-19 20:26:24 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:24 | D | sum error = [ 6.1189, 6.1050, 6.1386, 6.2019, 6.3047] +24-11-19 20:26:24 | D | best error = [ 5.7391, 5.5778, 5.4917, 5.4429, 5.4163] +24-11-19 20:26:24 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:24 | D | sum error = [ 6.4835, 6.7024, 6.9801, 7.3143, 7.7031] +24-11-19 20:26:24 | D | best error = [ 5.4033, 5.3982, 5.3961, 5.3957, 5.3956] +24-11-19 20:26:24 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:24 | D | sum error = [ 8.1570, 8.6704, 9.2526, 9.8715, 10.5723] +24-11-19 20:26:24 | D | best error = [ 5.3956, 5.3956, 5.3956, 5.3956, 5.3956] +24-11-19 20:26:24 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:24 | D | sum error = [ 11.3336, 12.1451, 13.0659, 14.0113, 15.0402] +24-11-19 20:26:24 | D | best error = [ 5.3956, 5.3956, 5.3956, 5.3956, 5.3956] +24-11-19 20:26:24 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:24 | D | sum error = [ 16.1732, 17.3328, 18.6219, 19.9743, 21.4163] +24-11-19 20:26:24 | D | best error = [ 5.3956, 5.3956, 5.3956, 5.3956, 5.3956] +24-11-19 20:26:24 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:24 | D | sum error = [ 22.9595, 24.5748, 26.3318, 28.1763, 30.1366] +24-11-19 20:26:24 | D | best error = [ 5.3956, 5.3956, 5.3956, 5.3956, 5.3956] +24-11-19 20:26:24 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:24 | D | sum error = [ 32.2084, 34.4484, 36.8158, 39.3133, 41.9885] +24-11-19 20:26:24 | D | best error = [ 5.3956, 5.3956, 5.3956, 5.3956, 5.3956] +24-11-19 20:26:24 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:24 | D | sum error = [ 44.7980, 47.7951, 50.9899, 54.3593, 57.9661] +24-11-19 20:26:24 | D | best error = [ 5.3956, 5.3956, 5.3956, 5.3956, 5.3956] +24-11-19 20:26:24 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:24 | D | sum error = [ 61.7552, 65.7830, 70.0647, 74.6024, 79.3895] +24-11-19 20:26:24 | D | best error = [ 5.3956, 5.3956, 5.3956, 5.3956, 5.3956] +24-11-19 20:26:24 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:24 | D | sum error = [ 84.4627, 89.8586, 95.5734, 101.5861, 107.9730] +24-11-19 20:26:24 | D | best error = [ 5.3956, 5.3956, 5.3956, 5.3956, 5.3956] +24-11-19 20:26:24 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:24 | D | sum error = [ 114.7133, 121.8323, 129.3411, 137.3134, 145.6737] +24-11-19 20:26:24 | D | best error = [ 5.3956, 5.3956, 5.3956, 5.3956, 5.3956] +24-11-19 20:26:24 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:24 | D | sum error = [ 154.5121, 163.8217, 173.6184, 183.9257, 194.7647] +24-11-19 20:26:24 | D | best error = [ 5.3956, 5.3956, 5.3956, 5.3956, 5.3956] +24-11-19 20:26:24 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:24 | D | sum error = [ 206.1130, 218.0434, 230.5631, 243.6577, 257.3726] +24-11-19 20:26:24 | D | best error = [ 5.3956, 5.3956, 5.3956, 5.3956, 5.3956] +24-11-19 20:26:24 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:24 | D | sum error = [ 271.7391, 286.7143, 302.3875, 318.7463, 335.7792] +24-11-19 20:26:24 | D | best error = [ 5.3956, 5.3956, 5.3956, 5.3956, 5.3956] +24-11-19 20:26:24 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:24 | D | sum error = [ 353.5400, 372.0032, 391.1815, 411.1010, 431.7526] +24-11-19 20:26:24 | D | best error = [ 5.3956, 5.3956, 5.3956, 5.3956, 5.3956] +24-11-19 20:26:24 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:24 | D | sum error = [ 453.1752, 475.3091, 498.1859, 521.7757, 546.1027] +24-11-19 20:26:24 | D | best error = [ 5.3956, 5.3956, 5.3956, 5.3956, 5.3956] +24-11-19 20:26:24 | D | + error = [5.3956] +24-11-19 20:26:24 | D | - Calibrating model.layers.10.mlp.down_proj.weight +24-11-19 20:26:24 | D | + w: sint8 +24-11-19 20:26:24 | D | + x: None +24-11-19 20:26:24 | D | + y: None +24-11-19 20:26:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:24 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:24 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:25 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:25 | D | - range ratio = [ 1.0000] +24-11-19 20:26:25 | D | sum error = [ 0.5681] +24-11-19 20:26:25 | D | best error = [ 0.5681] +24-11-19 20:26:26 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:26 | D | sum error = [ 0.5628, 0.5589, 0.5559, 0.5565, 0.5581] +24-11-19 20:26:26 | D | best error = [ 0.5447, 0.5329, 0.5253, 0.5202, 0.5166] +24-11-19 20:26:26 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:26 | D | sum error = [ 0.5640, 0.5727, 0.5838, 0.6007, 0.6217] +24-11-19 20:26:26 | D | best error = [ 0.5139, 0.5122, 0.5110, 0.5103, 0.5099] +24-11-19 20:26:26 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:26 | D | sum error = [ 0.6466, 0.6782, 0.7138, 0.7552, 0.8013] +24-11-19 20:26:26 | D | best error = [ 0.5097, 0.5096, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:26 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:26 | D | sum error = [ 0.8537, 0.9104, 0.9741, 1.0411, 1.1162] +24-11-19 20:26:26 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:26 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:26 | D | sum error = [ 1.1952, 1.2828, 1.3749, 1.4732, 1.5799] +24-11-19 20:26:26 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:26 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:26 | D | sum error = [ 1.6915, 1.8101, 1.9372, 2.0696, 2.2098] +24-11-19 20:26:26 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:26 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:26 | D | sum error = [ 2.3607, 2.5184, 2.6860, 2.8628, 3.0488] +24-11-19 20:26:26 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:26 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:26 | D | sum error = [ 3.2445, 3.4525, 3.6687, 3.8968, 4.1382] +24-11-19 20:26:26 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:26 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:26 | D | sum error = [ 4.3917, 4.6594, 4.9390, 5.2333, 5.5429] +24-11-19 20:26:26 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:26 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:26 | D | sum error = [ 5.8679, 6.2073, 6.5646, 6.9374, 7.3288] +24-11-19 20:26:26 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:26 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:26 | D | sum error = [ 7.7377, 8.1647, 8.6110, 9.0773, 9.5646] +24-11-19 20:26:26 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:26 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:26 | D | sum error = [ 10.0718, 10.6027, 11.1563, 11.7338, 12.3314] +24-11-19 20:26:26 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:26 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:26 | D | sum error = [ 12.9549, 13.6043, 14.2813, 14.9817, 15.7090] +24-11-19 20:26:26 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:26 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:26 | D | sum error = [ 16.4650, 17.2510, 18.0656, 18.9094, 19.7836] +24-11-19 20:26:26 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:26 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:26 | D | sum error = [ 20.6886, 21.6243, 22.5930, 23.5935, 24.6265] +24-11-19 20:26:26 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:26 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:26 | D | sum error = [ 25.6934, 26.7936, 27.9288, 29.0997, 30.3059] +24-11-19 20:26:26 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:26:26 | D | + error = [0.5095] +24-11-19 20:26:26 | D | - Quantizing model.layers.10.self_attn.q_proj.weight +24-11-19 20:26:27 | D | - Quantizing model.layers.10.self_attn.k_proj.weight +24-11-19 20:26:28 | D | - Quantizing model.layers.10.self_attn.v_proj.weight +24-11-19 20:26:29 | D | - Quantizing model.layers.10.self_attn.o_proj.weight +24-11-19 20:26:30 | D | - Quantizing model.layers.10.mlp.up_proj.weight +24-11-19 20:26:32 | D | - Quantizing model.layers.10.mlp.gate_proj.weight +24-11-19 20:26:33 | D | - Quantizing model.layers.10.mlp.down_proj.weight +24-11-19 20:26:45 | D | - Quantizing layer model.layers.11 +24-11-19 20:26:45 | D | - Calibrating model.layers.11.self_attn.q_proj.weight +24-11-19 20:26:45 | D | + w: sint8 +24-11-19 20:26:45 | D | + x: None +24-11-19 20:26:45 | D | + y: None +24-11-19 20:26:45 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:26:45 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:26:45 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:26:46 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:26:46 | D | - range ratio = [ 1.0000] +24-11-19 20:26:46 | D | sum error = [ 4.4978] +24-11-19 20:26:46 | D | best error = [ 4.4978] +24-11-19 20:26:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:59 | D | sum error = [ 4.3736, 4.4148, 4.4373, 4.4152, 4.5635] +24-11-19 20:26:59 | D | best error = [ 4.3736, 4.3736, 4.3736, 4.3736, 4.3736] +24-11-19 20:26:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:59 | D | sum error = [ 4.6237, 4.9748, 5.0067, 5.3358, 5.5478] +24-11-19 20:26:59 | D | best error = [ 4.3736, 4.3736, 4.3736, 4.3736, 4.3736] +24-11-19 20:26:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:59 | D | sum error = [ 6.0404, 6.3755, 6.8873, 7.1472, 7.6703] +24-11-19 20:26:59 | D | best error = [ 4.3736, 4.3736, 4.3736, 4.3736, 4.3736] +24-11-19 20:26:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:59 | D | sum error = [ 8.5509, 8.9240, 9.6047, 10.3980, 11.3396] +24-11-19 20:26:59 | D | best error = [ 4.3736, 4.3736, 4.3736, 4.3736, 4.3736] +24-11-19 20:26:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:59 | D | sum error = [ 12.3190, 13.2194, 14.6268, 16.0113, 17.6145] +24-11-19 20:26:59 | D | best error = [ 4.3736, 4.3736, 4.3736, 4.3736, 4.3736] +24-11-19 20:26:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:59 | D | sum error = [ 19.0752, 20.5492, 22.3658, 24.2248, 26.5819] +24-11-19 20:26:59 | D | best error = [ 4.3736, 4.3736, 4.3736, 4.3736, 4.3736] +24-11-19 20:26:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:59 | D | sum error = [ 28.7900, 31.3752, 33.3839, 36.2151, 38.7523] +24-11-19 20:26:59 | D | best error = [ 4.3736, 4.3736, 4.3736, 4.3736, 4.3736] +24-11-19 20:26:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:59 | D | sum error = [ 41.6818, 44.4294, 47.8386, 51.2900, 54.9830] +24-11-19 20:26:59 | D | best error = [ 4.3736, 4.3736, 4.3736, 4.3736, 4.3736] +24-11-19 20:26:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:59 | D | sum error = [ 58.6089, 62.6307, 66.7282, 71.0622, 75.8187] +24-11-19 20:26:59 | D | best error = [ 4.3736, 4.3736, 4.3736, 4.3736, 4.3736] +24-11-19 20:26:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:59 | D | sum error = [ 80.7331, 85.9307, 91.3864, 97.2693, 103.1641] +24-11-19 20:26:59 | D | best error = [ 4.3736, 4.3736, 4.3736, 4.3736, 4.3736] +24-11-19 20:26:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:59 | D | sum error = [ 109.5030, 116.0253, 122.9817, 130.4853, 138.3080] +24-11-19 20:26:59 | D | best error = [ 4.3736, 4.3736, 4.3736, 4.3736, 4.3736] +24-11-19 20:26:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:59 | D | sum error = [ 146.1626, 154.9389, 163.7034, 173.1149, 182.6909] +24-11-19 20:26:59 | D | best error = [ 4.3736, 4.3736, 4.3736, 4.3736, 4.3736] +24-11-19 20:26:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:59 | D | sum error = [ 192.8106, 203.5654, 214.5840, 226.1856, 238.1551] +24-11-19 20:26:59 | D | best error = [ 4.3736, 4.3736, 4.3736, 4.3736, 4.3736] +24-11-19 20:26:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:59 | D | sum error = [ 250.6406, 263.6910, 277.2325, 291.2422, 305.9951] +24-11-19 20:26:59 | D | best error = [ 4.3736, 4.3736, 4.3736, 4.3736, 4.3736] +24-11-19 20:26:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:59 | D | sum error = [ 321.1854, 337.1040, 353.5249, 370.5391, 388.0644] +24-11-19 20:26:59 | D | best error = [ 4.3736, 4.3736, 4.3736, 4.3736, 4.3736] +24-11-19 20:26:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:59 | D | sum error = [ 406.1758, 424.8557, 443.8464, 463.4754, 483.3919] +24-11-19 20:26:59 | D | best error = [ 4.3736, 4.3736, 4.3736, 4.3736, 4.3736] +24-11-19 20:26:59 | D | + error = [4.3736] +24-11-19 20:27:00 | D | - Calibrating model.layers.11.self_attn.k_proj.weight +24-11-19 20:27:00 | D | + w: sint8 +24-11-19 20:27:00 | D | + x: None +24-11-19 20:27:00 | D | + y: None +24-11-19 20:27:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:27:00 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:27:00 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:27:00 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:27:00 | D | - range ratio = [ 1.0000] +24-11-19 20:27:00 | D | sum error = [ 3.9498] +24-11-19 20:27:00 | D | best error = [ 3.9498] +24-11-19 20:27:14 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:14 | D | sum error = [ 3.5557, 3.9728, 3.7644, 3.7860, 4.0472] +24-11-19 20:27:14 | D | best error = [ 3.5557, 3.5557, 3.5557, 3.5557, 3.5557] +24-11-19 20:27:14 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:14 | D | sum error = [ 3.9480, 3.9465, 4.7454, 4.6656, 4.7482] +24-11-19 20:27:14 | D | best error = [ 3.5557, 3.5557, 3.5557, 3.5557, 3.5557] +24-11-19 20:27:14 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:14 | D | sum error = [ 4.6695, 4.6850, 5.5959, 6.0428, 6.5874] +24-11-19 20:27:14 | D | best error = [ 3.5557, 3.5557, 3.5557, 3.5557, 3.5557] +24-11-19 20:27:14 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:14 | D | sum error = [ 6.4126, 7.3049, 7.3621, 8.3470, 8.6069] +24-11-19 20:27:14 | D | best error = [ 3.5557, 3.5557, 3.5557, 3.5557, 3.5557] +24-11-19 20:27:14 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:14 | D | sum error = [ 9.4019, 10.7878, 11.5244, 12.0062, 13.8908] +24-11-19 20:27:14 | D | best error = [ 3.5557, 3.5557, 3.5557, 3.5557, 3.5557] +24-11-19 20:27:14 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:14 | D | sum error = [ 14.8130, 15.2995, 16.7427, 17.6682, 18.7775] +24-11-19 20:27:14 | D | best error = [ 3.5557, 3.5557, 3.5557, 3.5557, 3.5557] +24-11-19 20:27:14 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:14 | D | sum error = [ 19.9203, 21.4973, 22.8332, 23.7578, 26.0066] +24-11-19 20:27:14 | D | best error = [ 3.5557, 3.5557, 3.5557, 3.5557, 3.5557] +24-11-19 20:27:14 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:14 | D | sum error = [ 27.9045, 30.2109, 32.6184, 35.0786, 38.1273] +24-11-19 20:27:14 | D | best error = [ 3.5557, 3.5557, 3.5557, 3.5557, 3.5557] +24-11-19 20:27:14 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:14 | D | sum error = [ 40.7789, 43.8325, 47.4075, 51.3526, 54.9864] +24-11-19 20:27:14 | D | best error = [ 3.5557, 3.5557, 3.5557, 3.5557, 3.5557] +24-11-19 20:27:14 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:14 | D | sum error = [ 59.2928, 63.2285, 67.9090, 73.2208, 78.1465] +24-11-19 20:27:14 | D | best error = [ 3.5557, 3.5557, 3.5557, 3.5557, 3.5557] +24-11-19 20:27:14 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:14 | D | sum error = [ 83.0334, 89.1009, 95.0905, 101.8592, 108.7788] +24-11-19 20:27:14 | D | best error = [ 3.5557, 3.5557, 3.5557, 3.5557, 3.5557] +24-11-19 20:27:14 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:14 | D | sum error = [ 116.9279, 125.2551, 133.9046, 143.3479, 153.3885] +24-11-19 20:27:14 | D | best error = [ 3.5557, 3.5557, 3.5557, 3.5557, 3.5557] +24-11-19 20:27:14 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:14 | D | sum error = [ 163.5150, 174.3344, 186.0808, 197.9957, 211.3725] +24-11-19 20:27:14 | D | best error = [ 3.5557, 3.5557, 3.5557, 3.5557, 3.5557] +24-11-19 20:27:14 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:14 | D | sum error = [ 224.5767, 238.5495, 253.1793, 267.4773, 283.2556] +24-11-19 20:27:14 | D | best error = [ 3.5557, 3.5557, 3.5557, 3.5557, 3.5557] +24-11-19 20:27:14 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:14 | D | sum error = [ 299.6683, 316.3299, 333.9671, 352.3272, 371.6322] +24-11-19 20:27:14 | D | best error = [ 3.5557, 3.5557, 3.5557, 3.5557, 3.5557] +24-11-19 20:27:14 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:14 | D | sum error = [ 391.5544, 411.7106, 432.5379, 453.5995, 474.6623] +24-11-19 20:27:14 | D | best error = [ 3.5557, 3.5557, 3.5557, 3.5557, 3.5557] +24-11-19 20:27:14 | D | + error = [3.5557] +24-11-19 20:27:14 | D | - Calibrating model.layers.11.self_attn.v_proj.weight +24-11-19 20:27:14 | D | + w: sint8 +24-11-19 20:27:14 | D | + x: None +24-11-19 20:27:14 | D | + y: None +24-11-19 20:27:14 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:14 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:27:14 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:27:15 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:27:15 | D | - range ratio = [ 1.0000] +24-11-19 20:27:15 | D | sum error = [ 1.3217] +24-11-19 20:27:15 | D | best error = [ 1.3217] +24-11-19 20:27:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:15 | D | sum error = [ 1.3346, 1.3230, 1.3282, 1.3426, 1.3749] +24-11-19 20:27:15 | D | best error = [ 1.2337, 1.1990, 1.1795, 1.1686, 1.1630] +24-11-19 20:27:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:15 | D | sum error = [ 1.4017, 1.4425, 1.5051, 1.5767, 1.6626] +24-11-19 20:27:15 | D | best error = [ 1.1605, 1.1596, 1.1594, 1.1593, 1.1593] +24-11-19 20:27:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:15 | D | sum error = [ 1.7675, 1.8567, 1.9720, 2.1075, 2.2687] +24-11-19 20:27:15 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:27:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:15 | D | sum error = [ 2.4105, 2.5892, 2.7743, 2.9767, 3.1839] +24-11-19 20:27:15 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:27:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:15 | D | sum error = [ 3.4141, 3.6700, 3.9295, 4.2133, 4.5068] +24-11-19 20:27:15 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:27:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:15 | D | sum error = [ 4.8200, 5.1588, 5.5152, 5.8746, 6.2908] +24-11-19 20:27:15 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:27:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:15 | D | sum error = [ 6.7136, 7.1528, 7.6381, 8.1287, 8.6426] +24-11-19 20:27:15 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:27:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:15 | D | sum error = [ 9.1916, 9.7821, 10.3851, 11.0338, 11.7097] +24-11-19 20:27:15 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:27:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:15 | D | sum error = [ 12.4335, 13.1913, 13.9876, 14.8251, 15.7178] +24-11-19 20:27:15 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:27:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:15 | D | sum error = [ 16.6360, 17.6123, 18.6210, 19.6838, 20.8004] +24-11-19 20:27:15 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:27:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:15 | D | sum error = [ 21.9702, 23.1892, 24.4649, 25.8167, 27.2142] +24-11-19 20:27:15 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:27:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:15 | D | sum error = [ 28.6794, 30.2065, 31.8126, 33.4813, 35.2097] +24-11-19 20:27:15 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:27:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:15 | D | sum error = [ 37.0242, 38.9126, 40.8815, 42.9278, 45.0581] +24-11-19 20:27:15 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:27:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:15 | D | sum error = [ 47.2751, 49.5775, 51.9750, 54.4578, 57.0348] +24-11-19 20:27:15 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:27:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:15 | D | sum error = [ 59.7056, 62.4859, 65.3576, 68.3337, 71.4037] +24-11-19 20:27:15 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:27:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:15 | D | sum error = [ 74.5722, 77.8484, 81.2239, 84.7116, 88.2925] +24-11-19 20:27:15 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:27:15 | D | + error = [1.1593] +24-11-19 20:27:15 | D | - Calibrating model.layers.11.self_attn.o_proj.weight +24-11-19 20:27:15 | D | + w: sint8 +24-11-19 20:27:15 | D | + x: None +24-11-19 20:27:15 | D | + y: None +24-11-19 20:27:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:15 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:27:15 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:27:15 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:27:15 | D | - range ratio = [ 1.0000] +24-11-19 20:27:15 | D | sum error = [ 0.5878] +24-11-19 20:27:15 | D | best error = [ 0.5878] +24-11-19 20:27:16 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:16 | D | sum error = [ 0.5827, 0.5814, 0.5757, 0.5830, 0.5843] +24-11-19 20:27:16 | D | best error = [ 0.5158, 0.4885, 0.4726, 0.4630, 0.4556] +24-11-19 20:27:16 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:16 | D | sum error = [ 0.5924, 0.6012, 0.6144, 0.6290, 0.6508] +24-11-19 20:27:16 | D | best error = [ 0.4504, 0.4463, 0.4428, 0.4403, 0.4385] +24-11-19 20:27:16 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:16 | D | sum error = [ 0.6713, 0.7039, 0.7310, 0.7717, 0.8036] +24-11-19 20:27:16 | D | best error = [ 0.4372, 0.4359, 0.4351, 0.4344, 0.4340] +24-11-19 20:27:16 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:16 | D | sum error = [ 0.8513, 0.8954, 0.9500, 1.0031, 1.0673] +24-11-19 20:27:16 | D | best error = [ 0.4336, 0.4333, 0.4329, 0.4326, 0.4324] +24-11-19 20:27:16 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:16 | D | sum error = [ 1.1290, 1.1941, 1.2661, 1.3499, 1.4292] +24-11-19 20:27:16 | D | best error = [ 0.4322, 0.4321, 0.4319, 0.4319, 0.4319] +24-11-19 20:27:16 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:16 | D | sum error = [ 1.5190, 1.6133, 1.7064, 1.8167, 1.9240] +24-11-19 20:27:16 | D | best error = [ 0.4318, 0.4318, 0.4317, 0.4317, 0.4317] +24-11-19 20:27:16 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:16 | D | sum error = [ 2.0390, 2.1607, 2.2902, 2.4260, 2.5694] +24-11-19 20:27:16 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:27:16 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:16 | D | sum error = [ 2.7165, 2.8715, 3.0333, 3.2051, 3.3804] +24-11-19 20:27:16 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:27:16 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:16 | D | sum error = [ 3.5674, 3.7593, 3.9608, 4.1712, 4.3928] +24-11-19 20:27:16 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:27:16 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:16 | D | sum error = [ 4.6182, 4.8549, 5.1028, 5.3601, 5.6298] +24-11-19 20:27:16 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:27:16 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:16 | D | sum error = [ 5.9099, 6.2019, 6.5038, 6.8136, 7.1408] +24-11-19 20:27:16 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:27:16 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:16 | D | sum error = [ 7.4725, 7.8194, 8.1779, 8.5486, 8.9275] +24-11-19 20:27:16 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:27:16 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:16 | D | sum error = [ 9.3238, 9.7287, 10.1459, 10.5734, 11.0147] +24-11-19 20:27:16 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:27:16 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:16 | D | sum error = [ 11.4712, 11.9354, 12.4134, 12.9028, 13.4036] +24-11-19 20:27:16 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:27:16 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:16 | D | sum error = [ 13.9172, 14.4437, 14.9836, 15.5357, 16.1021] +24-11-19 20:27:16 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:27:16 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:16 | D | sum error = [ 16.6817, 17.2708, 17.8722, 18.4899, 19.1217] +24-11-19 20:27:16 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:27:16 | D | + error = [0.4316] +24-11-19 20:27:16 | D | - Calibrating model.layers.11.mlp.up_proj.weight +24-11-19 20:27:16 | D | + w: sint8 +24-11-19 20:27:16 | D | + x: None +24-11-19 20:27:16 | D | + y: None +24-11-19 20:27:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:16 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:27:16 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:27:16 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:27:16 | D | - range ratio = [ 1.0000] +24-11-19 20:27:16 | D | sum error = [ 0.2889] +24-11-19 20:27:16 | D | best error = [ 0.2889] +24-11-19 20:27:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:17 | D | sum error = [ 0.2863, 0.2851, 0.2866, 0.2899, 0.2950] +24-11-19 20:27:17 | D | best error = [ 0.2693, 0.2609, 0.2566, 0.2542, 0.2529] +24-11-19 20:27:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:17 | D | sum error = [ 0.3024, 0.3126, 0.3251, 0.3402, 0.3580] +24-11-19 20:27:17 | D | best error = [ 0.2523, 0.2520, 0.2519, 0.2519, 0.2519] +24-11-19 20:27:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:17 | D | sum error = [ 0.3792, 0.4015, 0.4275, 0.4565, 0.4872] +24-11-19 20:27:17 | D | best error = [ 0.2519, 0.2519, 0.2519, 0.2519, 0.2519] +24-11-19 20:27:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:17 | D | sum error = [ 0.5229, 0.5595, 0.5989, 0.6421, 0.6882] +24-11-19 20:27:17 | D | best error = [ 0.2519, 0.2519, 0.2519, 0.2519, 0.2519] +24-11-19 20:27:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:17 | D | sum error = [ 0.7376, 0.7893, 0.8453, 0.9044, 0.9670] +24-11-19 20:27:17 | D | best error = [ 0.2519, 0.2519, 0.2519, 0.2519, 0.2519] +24-11-19 20:27:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:17 | D | sum error = [ 1.0338, 1.1048, 1.1777, 1.2579, 1.3409] +24-11-19 20:27:17 | D | best error = [ 0.2519, 0.2519, 0.2519, 0.2519, 0.2519] +24-11-19 20:27:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:17 | D | sum error = [ 1.4280, 1.5219, 1.6200, 1.7234, 1.8313] +24-11-19 20:27:17 | D | best error = [ 0.2519, 0.2519, 0.2519, 0.2519, 0.2519] +24-11-19 20:27:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:17 | D | sum error = [ 1.9457, 2.0662, 2.1933, 2.3264, 2.4651] +24-11-19 20:27:17 | D | best error = [ 0.2519, 0.2519, 0.2519, 0.2519, 0.2519] +24-11-19 20:27:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:17 | D | sum error = [ 2.6126, 2.7662, 2.9283, 3.0977, 3.2758] +24-11-19 20:27:17 | D | best error = [ 0.2519, 0.2519, 0.2519, 0.2519, 0.2519] +24-11-19 20:27:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:17 | D | sum error = [ 3.4639, 3.6592, 3.8660, 4.0796, 4.3050] +24-11-19 20:27:17 | D | best error = [ 0.2519, 0.2519, 0.2519, 0.2519, 0.2519] +24-11-19 20:27:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:17 | D | sum error = [ 4.5383, 4.7836, 5.0405, 5.3094, 5.5866] +24-11-19 20:27:17 | D | best error = [ 0.2519, 0.2519, 0.2519, 0.2519, 0.2519] +24-11-19 20:27:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:17 | D | sum error = [ 5.8785, 6.1816, 6.4981, 6.8271, 7.1687] +24-11-19 20:27:17 | D | best error = [ 0.2519, 0.2519, 0.2519, 0.2519, 0.2519] +24-11-19 20:27:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:17 | D | sum error = [ 7.5240, 7.8971, 8.2798, 8.6810, 9.0932] +24-11-19 20:27:17 | D | best error = [ 0.2519, 0.2519, 0.2519, 0.2519, 0.2519] +24-11-19 20:27:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:17 | D | sum error = [ 9.5250, 9.9729, 10.4330, 10.9137, 11.4111] +24-11-19 20:27:17 | D | best error = [ 0.2519, 0.2519, 0.2519, 0.2519, 0.2519] +24-11-19 20:27:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:17 | D | sum error = [ 11.9227, 12.4560, 13.0033, 13.5693, 14.1594] +24-11-19 20:27:17 | D | best error = [ 0.2519, 0.2519, 0.2519, 0.2519, 0.2519] +24-11-19 20:27:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:17 | D | sum error = [ 14.7615, 15.3845, 16.0227, 16.6811, 17.3649] +24-11-19 20:27:17 | D | best error = [ 0.2519, 0.2519, 0.2519, 0.2519, 0.2519] +24-11-19 20:27:17 | D | + error = [0.2519] +24-11-19 20:27:18 | D | - Calibrating model.layers.11.mlp.gate_proj.weight +24-11-19 20:27:18 | D | + w: sint8 +24-11-19 20:27:18 | D | + x: None +24-11-19 20:27:18 | D | + y: None +24-11-19 20:27:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:18 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:27:18 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:27:18 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:27:18 | D | - range ratio = [ 1.0000] +24-11-19 20:27:18 | D | sum error = [ 6.1485] +24-11-19 20:27:18 | D | best error = [ 6.1485] +24-11-19 20:27:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:19 | D | sum error = [ 6.1071, 6.0890, 6.1144, 6.1729, 6.3091] +24-11-19 20:27:19 | D | best error = [ 5.7140, 5.5463, 5.4576, 5.4069, 5.3803] +24-11-19 20:27:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:19 | D | sum error = [ 6.4718, 6.6798, 6.9561, 7.2925, 7.6670] +24-11-19 20:27:19 | D | best error = [ 5.3678, 5.3624, 5.3607, 5.3602, 5.3601] +24-11-19 20:27:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:19 | D | sum error = [ 8.1324, 8.6423, 9.2208, 9.8340, 10.5397] +24-11-19 20:27:19 | D | best error = [ 5.3601, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:27:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:19 | D | sum error = [ 11.3229, 12.1331, 13.0344, 14.0028, 15.0363] +24-11-19 20:27:19 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:27:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:19 | D | sum error = [ 16.1514, 17.3471, 18.6202, 19.9622, 21.4344] +24-11-19 20:27:19 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:27:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:19 | D | sum error = [ 22.9689, 24.6136, 26.3812, 28.2282, 30.2035] +24-11-19 20:27:19 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:27:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:19 | D | sum error = [ 32.3122, 34.5553, 36.9235, 39.4513, 42.1410] +24-11-19 20:27:19 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:27:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:19 | D | sum error = [ 44.9862, 48.0099, 51.2216, 54.6449, 58.2437] +24-11-19 20:27:19 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:27:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:19 | D | sum error = [ 62.0630, 66.1354, 70.4291, 75.0006, 79.8356] +24-11-19 20:27:19 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:27:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:19 | D | sum error = [ 84.9539, 90.3954, 96.1301, 102.2111, 108.6526] +24-11-19 20:27:19 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:27:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:19 | D | sum error = [ 115.4939, 122.6827, 130.3028, 138.3636, 146.8405] +24-11-19 20:27:19 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:27:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:19 | D | sum error = [ 155.7872, 165.2378, 175.1958, 185.6459, 196.6564] +24-11-19 20:27:19 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:27:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:19 | D | sum error = [ 208.2357, 220.3763, 233.1303, 246.4824, 260.4708] +24-11-19 20:27:19 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:27:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:19 | D | sum error = [ 275.1044, 290.4032, 306.3733, 323.0613, 340.4675] +24-11-19 20:27:19 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:27:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:19 | D | sum error = [ 358.5610, 377.4052, 396.9845, 417.3088, 438.3763] +24-11-19 20:27:19 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:27:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:19 | D | sum error = [ 460.2111, 482.7975, 506.1643, 530.2445, 555.0992] +24-11-19 20:27:19 | D | best error = [ 5.3600, 5.3600, 5.3600, 5.3600, 5.3600] +24-11-19 20:27:19 | D | + error = [5.3600] +24-11-19 20:27:19 | D | - Calibrating model.layers.11.mlp.down_proj.weight +24-11-19 20:27:19 | D | + w: sint8 +24-11-19 20:27:19 | D | + x: None +24-11-19 20:27:19 | D | + y: None +24-11-19 20:27:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:19 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:27:19 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:27:19 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:27:19 | D | - range ratio = [ 1.0000] +24-11-19 20:27:19 | D | sum error = [ 0.5767] +24-11-19 20:27:19 | D | best error = [ 0.5767] +24-11-19 20:27:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:21 | D | sum error = [ 0.5717, 0.5674, 0.5647, 0.5639, 0.5667] +24-11-19 20:27:21 | D | best error = [ 0.5527, 0.5413, 0.5336, 0.5282, 0.5243] +24-11-19 20:27:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:21 | D | sum error = [ 0.5715, 0.5791, 0.5902, 0.6073, 0.6279] +24-11-19 20:27:21 | D | best error = [ 0.5216, 0.5199, 0.5188, 0.5181, 0.5177] +24-11-19 20:27:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:21 | D | sum error = [ 0.6544, 0.6840, 0.7190, 0.7621, 0.8083] +24-11-19 20:27:21 | D | best error = [ 0.5175, 0.5173, 0.5173, 0.5173, 0.5173] +24-11-19 20:27:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:21 | D | sum error = [ 0.8622, 0.9204, 0.9860, 1.0560, 1.1302] +24-11-19 20:27:21 | D | best error = [ 0.5173, 0.5173, 0.5173, 0.5173, 0.5173] +24-11-19 20:27:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:21 | D | sum error = [ 1.2142, 1.3010, 1.3960, 1.4972, 1.6044] +24-11-19 20:27:21 | D | best error = [ 0.5173, 0.5173, 0.5173, 0.5173, 0.5173] +24-11-19 20:27:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:21 | D | sum error = [ 1.7190, 1.8401, 1.9680, 2.1033, 2.2471] +24-11-19 20:27:21 | D | best error = [ 0.5173, 0.5173, 0.5173, 0.5173, 0.5173] +24-11-19 20:27:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:21 | D | sum error = [ 2.4000, 2.5590, 2.7306, 2.9101, 3.0996] +24-11-19 20:27:21 | D | best error = [ 0.5173, 0.5173, 0.5173, 0.5173, 0.5173] +24-11-19 20:27:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:21 | D | sum error = [ 3.2986, 3.5102, 3.7323, 3.9643, 4.2105] +24-11-19 20:27:21 | D | best error = [ 0.5173, 0.5173, 0.5173, 0.5173, 0.5173] +24-11-19 20:27:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:21 | D | sum error = [ 4.4692, 4.7413, 5.0260, 5.3263, 5.6409] +24-11-19 20:27:21 | D | best error = [ 0.5173, 0.5173, 0.5173, 0.5173, 0.5173] +24-11-19 20:27:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:21 | D | sum error = [ 5.9709, 6.3189, 6.6833, 7.0663, 7.4668] +24-11-19 20:27:21 | D | best error = [ 0.5173, 0.5173, 0.5173, 0.5173, 0.5173] +24-11-19 20:27:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:21 | D | sum error = [ 7.8869, 8.3247, 8.7847, 9.2641, 9.7664] +24-11-19 20:27:21 | D | best error = [ 0.5173, 0.5173, 0.5173, 0.5173, 0.5173] +24-11-19 20:27:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:21 | D | sum error = [ 10.2894, 10.8356, 11.4062, 11.9996, 12.6158] +24-11-19 20:27:21 | D | best error = [ 0.5173, 0.5173, 0.5173, 0.5173, 0.5173] +24-11-19 20:27:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:21 | D | sum error = [ 13.2591, 13.9302, 14.6284, 15.3513, 16.1017] +24-11-19 20:27:21 | D | best error = [ 0.5173, 0.5173, 0.5173, 0.5173, 0.5173] +24-11-19 20:27:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:21 | D | sum error = [ 16.8832, 17.6947, 18.5351, 19.4077, 20.3103] +24-11-19 20:27:21 | D | best error = [ 0.5173, 0.5173, 0.5173, 0.5173, 0.5173] +24-11-19 20:27:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:21 | D | sum error = [ 21.2454, 22.2117, 23.2115, 24.2444, 25.3128] +24-11-19 20:27:21 | D | best error = [ 0.5173, 0.5173, 0.5173, 0.5173, 0.5173] +24-11-19 20:27:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:21 | D | sum error = [ 26.4151, 27.5547, 28.7277, 29.9393, 31.1858] +24-11-19 20:27:21 | D | best error = [ 0.5173, 0.5173, 0.5173, 0.5173, 0.5173] +24-11-19 20:27:21 | D | + error = [0.5173] +24-11-19 20:27:21 | D | - Quantizing model.layers.11.self_attn.q_proj.weight +24-11-19 20:27:24 | D | - Quantizing model.layers.11.self_attn.k_proj.weight +24-11-19 20:27:26 | D | - Quantizing model.layers.11.self_attn.v_proj.weight +24-11-19 20:27:29 | D | - Quantizing model.layers.11.self_attn.o_proj.weight +24-11-19 20:27:30 | D | - Quantizing model.layers.11.mlp.up_proj.weight +24-11-19 20:27:31 | D | - Quantizing model.layers.11.mlp.gate_proj.weight +24-11-19 20:27:32 | D | - Quantizing model.layers.11.mlp.down_proj.weight +24-11-19 20:27:42 | D | - Quantizing layer model.layers.12 +24-11-19 20:27:42 | D | - Calibrating model.layers.12.self_attn.q_proj.weight +24-11-19 20:27:42 | D | + w: sint8 +24-11-19 20:27:42 | D | + x: None +24-11-19 20:27:42 | D | + y: None +24-11-19 20:27:42 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:27:42 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:27:43 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:27:43 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:27:43 | D | - range ratio = [ 1.0000] +24-11-19 20:27:43 | D | sum error = [ 3.9262] +24-11-19 20:27:43 | D | best error = [ 3.9262] +24-11-19 20:27:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:57 | D | sum error = [ 3.8389, 3.9261, 3.8073, 3.9538, 4.1040] +24-11-19 20:27:57 | D | best error = [ 3.8389, 3.8389, 3.8073, 3.8073, 3.8073] +24-11-19 20:27:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:57 | D | sum error = [ 4.2024, 4.3696, 4.5975, 4.6256, 5.1401] +24-11-19 20:27:57 | D | best error = [ 3.8073, 3.8073, 3.8073, 3.8073, 3.8073] +24-11-19 20:27:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:57 | D | sum error = [ 5.2262, 5.6116, 5.9927, 6.5187, 6.9516] +24-11-19 20:27:57 | D | best error = [ 3.8073, 3.8073, 3.8073, 3.8073, 3.8073] +24-11-19 20:27:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:57 | D | sum error = [ 7.5437, 8.2075, 8.7830, 9.5525, 10.2993] +24-11-19 20:27:57 | D | best error = [ 3.8073, 3.8073, 3.8073, 3.8073, 3.8073] +24-11-19 20:27:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:57 | D | sum error = [ 11.2690, 12.3314, 13.5084, 14.8766, 16.2433] +24-11-19 20:27:57 | D | best error = [ 3.8073, 3.8073, 3.8073, 3.8073, 3.8073] +24-11-19 20:27:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:57 | D | sum error = [ 17.5501, 19.1539, 20.7980, 22.7762, 24.3637] +24-11-19 20:27:57 | D | best error = [ 3.8073, 3.8073, 3.8073, 3.8073, 3.8073] +24-11-19 20:27:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:57 | D | sum error = [ 26.6796, 28.6764, 30.8771, 33.2885, 35.8917] +24-11-19 20:27:57 | D | best error = [ 3.8073, 3.8073, 3.8073, 3.8073, 3.8073] +24-11-19 20:27:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:57 | D | sum error = [ 38.9405, 41.7755, 44.9007, 48.1977, 51.8352] +24-11-19 20:27:57 | D | best error = [ 3.8073, 3.8073, 3.8073, 3.8073, 3.8073] +24-11-19 20:27:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:57 | D | sum error = [ 55.5945, 59.5311, 63.8050, 68.3889, 72.9538] +24-11-19 20:27:57 | D | best error = [ 3.8073, 3.8073, 3.8073, 3.8073, 3.8073] +24-11-19 20:27:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:57 | D | sum error = [ 77.9238, 83.4659, 89.0691, 94.9977, 101.2503] +24-11-19 20:27:57 | D | best error = [ 3.8073, 3.8073, 3.8073, 3.8073, 3.8073] +24-11-19 20:27:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:57 | D | sum error = [ 107.7964, 114.6454, 121.9481, 129.3264, 137.4057] +24-11-19 20:27:57 | D | best error = [ 3.8073, 3.8073, 3.8073, 3.8073, 3.8073] +24-11-19 20:27:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:57 | D | sum error = [ 145.6295, 154.4458, 163.3425, 172.7760, 182.8074] +24-11-19 20:27:57 | D | best error = [ 3.8073, 3.8073, 3.8073, 3.8073, 3.8073] +24-11-19 20:27:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:57 | D | sum error = [ 193.0217, 203.9774, 215.4108, 227.0976, 239.7405] +24-11-19 20:27:57 | D | best error = [ 3.8073, 3.8073, 3.8073, 3.8073, 3.8073] +24-11-19 20:27:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:57 | D | sum error = [ 253.0983, 267.0057, 281.7753, 297.3192, 313.7036] +24-11-19 20:27:57 | D | best error = [ 3.8073, 3.8073, 3.8073, 3.8073, 3.8073] +24-11-19 20:27:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:57 | D | sum error = [ 331.0306, 349.1461, 368.1058, 387.9847, 408.6202] +24-11-19 20:27:57 | D | best error = [ 3.8073, 3.8073, 3.8073, 3.8073, 3.8073] +24-11-19 20:27:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:57 | D | sum error = [ 430.1402, 452.3357, 475.4058, 499.0560, 523.2320] +24-11-19 20:27:57 | D | best error = [ 3.8073, 3.8073, 3.8073, 3.8073, 3.8073] +24-11-19 20:27:57 | D | + error = [3.8073] +24-11-19 20:27:58 | D | - Calibrating model.layers.12.self_attn.k_proj.weight +24-11-19 20:27:58 | D | + w: sint8 +24-11-19 20:27:58 | D | + x: None +24-11-19 20:27:58 | D | + y: None +24-11-19 20:27:58 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:27:58 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:27:58 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:27:58 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:27:58 | D | - range ratio = [ 1.0000] +24-11-19 20:27:58 | D | sum error = [ 3.8910] +24-11-19 20:27:58 | D | best error = [ 3.8910] +24-11-19 20:28:11 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:11 | D | sum error = [ 3.5472, 3.6887, 3.9986, 4.0754, 3.7385] +24-11-19 20:28:11 | D | best error = [ 3.5472, 3.5472, 3.5472, 3.5472, 3.5472] +24-11-19 20:28:11 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:11 | D | sum error = [ 3.9587, 3.8329, 3.8451, 4.3786, 4.9365] +24-11-19 20:28:11 | D | best error = [ 3.5472, 3.5472, 3.5472, 3.5472, 3.5472] +24-11-19 20:28:11 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:11 | D | sum error = [ 5.1404, 5.5043, 5.9099, 5.5243, 6.4359] +24-11-19 20:28:11 | D | best error = [ 3.5472, 3.5472, 3.5472, 3.5472, 3.5472] +24-11-19 20:28:11 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:11 | D | sum error = [ 7.0077, 7.1663, 8.2774, 8.4671, 9.0566] +24-11-19 20:28:11 | D | best error = [ 3.5472, 3.5472, 3.5472, 3.5472, 3.5472] +24-11-19 20:28:11 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:11 | D | sum error = [ 9.6028, 11.3103, 12.3939, 12.4293, 13.7071] +24-11-19 20:28:11 | D | best error = [ 3.5472, 3.5472, 3.5472, 3.5472, 3.5472] +24-11-19 20:28:11 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:11 | D | sum error = [ 14.5267, 16.2956, 17.4005, 18.9560, 20.7095] +24-11-19 20:28:11 | D | best error = [ 3.5472, 3.5472, 3.5472, 3.5472, 3.5472] +24-11-19 20:28:11 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:11 | D | sum error = [ 22.0047, 23.7069, 25.9891, 27.8154, 30.3482] +24-11-19 20:28:11 | D | best error = [ 3.5472, 3.5472, 3.5472, 3.5472, 3.5472] +24-11-19 20:28:11 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:11 | D | sum error = [ 32.9752, 35.5699, 38.4040, 41.2220, 44.0164] +24-11-19 20:28:11 | D | best error = [ 3.5472, 3.5472, 3.5472, 3.5472, 3.5472] +24-11-19 20:28:11 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:11 | D | sum error = [ 47.5788, 51.0475, 54.2263, 58.3172, 62.4957] +24-11-19 20:28:11 | D | best error = [ 3.5472, 3.5472, 3.5472, 3.5472, 3.5472] +24-11-19 20:28:11 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:11 | D | sum error = [ 66.8913, 72.1692, 77.0623, 81.8657, 87.1808] +24-11-19 20:28:11 | D | best error = [ 3.5472, 3.5472, 3.5472, 3.5472, 3.5472] +24-11-19 20:28:11 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:11 | D | sum error = [ 92.7855, 99.4101, 106.2047, 113.3481, 120.9183] +24-11-19 20:28:11 | D | best error = [ 3.5472, 3.5472, 3.5472, 3.5472, 3.5472] +24-11-19 20:28:11 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:11 | D | sum error = [ 128.6049, 137.4957, 147.0115, 156.8440, 166.4716] +24-11-19 20:28:11 | D | best error = [ 3.5472, 3.5472, 3.5472, 3.5472, 3.5472] +24-11-19 20:28:11 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:11 | D | sum error = [ 177.1286, 188.8216, 200.6091, 213.0171, 226.6285] +24-11-19 20:28:11 | D | best error = [ 3.5472, 3.5472, 3.5472, 3.5472, 3.5472] +24-11-19 20:28:11 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:11 | D | sum error = [ 241.9337, 257.3112, 273.3900, 290.6192, 308.4392] +24-11-19 20:28:11 | D | best error = [ 3.5472, 3.5472, 3.5472, 3.5472, 3.5472] +24-11-19 20:28:11 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:11 | D | sum error = [ 326.1235, 345.1431, 364.8170, 386.1868, 406.8911] +24-11-19 20:28:11 | D | best error = [ 3.5472, 3.5472, 3.5472, 3.5472, 3.5472] +24-11-19 20:28:11 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:11 | D | sum error = [ 428.6171, 451.8134, 474.8980, 498.8498, 523.6796] +24-11-19 20:28:11 | D | best error = [ 3.5472, 3.5472, 3.5472, 3.5472, 3.5472] +24-11-19 20:28:11 | D | + error = [3.5472] +24-11-19 20:28:11 | D | - Calibrating model.layers.12.self_attn.v_proj.weight +24-11-19 20:28:11 | D | + w: sint8 +24-11-19 20:28:11 | D | + x: None +24-11-19 20:28:11 | D | + y: None +24-11-19 20:28:11 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:11 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:12 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:12 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:12 | D | - range ratio = [ 1.0000] +24-11-19 20:28:12 | D | sum error = [ 1.4829] +24-11-19 20:28:12 | D | best error = [ 1.4829] +24-11-19 20:28:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:12 | D | sum error = [ 1.4765, 1.4614, 1.4631, 1.4769, 1.5101] +24-11-19 20:28:12 | D | best error = [ 1.3706, 1.3279, 1.3039, 1.2912, 1.2849] +24-11-19 20:28:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:12 | D | sum error = [ 1.5585, 1.6065, 1.6759, 1.7461, 1.8507] +24-11-19 20:28:12 | D | best error = [ 1.2825, 1.2815, 1.2811, 1.2811, 1.2811] +24-11-19 20:28:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:12 | D | sum error = [ 1.9547, 2.0594, 2.2076, 2.3607, 2.5322] +24-11-19 20:28:12 | D | best error = [ 1.2811, 1.2811, 1.2811, 1.2811, 1.2811] +24-11-19 20:28:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:12 | D | sum error = [ 2.6900, 2.8792, 3.0993, 3.3177, 3.5564] +24-11-19 20:28:12 | D | best error = [ 1.2811, 1.2811, 1.2811, 1.2811, 1.2811] +24-11-19 20:28:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:12 | D | sum error = [ 3.8151, 4.1023, 4.3671, 4.6765, 4.9911] +24-11-19 20:28:12 | D | best error = [ 1.2811, 1.2811, 1.2811, 1.2811, 1.2811] +24-11-19 20:28:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:12 | D | sum error = [ 5.3541, 5.6955, 6.0711, 6.4642, 6.8865] +24-11-19 20:28:12 | D | best error = [ 1.2811, 1.2811, 1.2811, 1.2811, 1.2811] +24-11-19 20:28:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:12 | D | sum error = [ 7.3192, 7.7913, 8.2880, 8.8146, 9.3729] +24-11-19 20:28:12 | D | best error = [ 1.2811, 1.2811, 1.2811, 1.2811, 1.2811] +24-11-19 20:28:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:12 | D | sum error = [ 9.9517, 10.5889, 11.2228, 11.9155, 12.6189] +24-11-19 20:28:12 | D | best error = [ 1.2811, 1.2811, 1.2811, 1.2811, 1.2811] +24-11-19 20:28:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:12 | D | sum error = [ 13.3743, 14.1612, 14.9865, 15.8654, 16.7671] +24-11-19 20:28:12 | D | best error = [ 1.2811, 1.2811, 1.2811, 1.2811, 1.2811] +24-11-19 20:28:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:12 | D | sum error = [ 17.7346, 18.7319, 19.7908, 20.9008, 22.0487] +24-11-19 20:28:12 | D | best error = [ 1.2811, 1.2811, 1.2811, 1.2811, 1.2811] +24-11-19 20:28:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:12 | D | sum error = [ 23.2562, 24.5111, 25.8254, 27.2024, 28.6387] +24-11-19 20:28:12 | D | best error = [ 1.2811, 1.2811, 1.2811, 1.2811, 1.2811] +24-11-19 20:28:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:12 | D | sum error = [ 30.1278, 31.6757, 33.2885, 34.9686, 36.7127] +24-11-19 20:28:12 | D | best error = [ 1.2811, 1.2811, 1.2811, 1.2811, 1.2811] +24-11-19 20:28:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:12 | D | sum error = [ 38.5215, 40.3986, 42.3432, 44.3633, 46.4457] +24-11-19 20:28:12 | D | best error = [ 1.2811, 1.2811, 1.2811, 1.2811, 1.2811] +24-11-19 20:28:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:12 | D | sum error = [ 48.6075, 50.8596, 53.1744, 55.5874, 58.0887] +24-11-19 20:28:12 | D | best error = [ 1.2811, 1.2811, 1.2811, 1.2811, 1.2811] +24-11-19 20:28:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:12 | D | sum error = [ 60.6728, 63.3412, 66.1045, 68.9448, 71.8761] +24-11-19 20:28:12 | D | best error = [ 1.2811, 1.2811, 1.2811, 1.2811, 1.2811] +24-11-19 20:28:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:12 | D | sum error = [ 74.9024, 78.0122, 81.2211, 84.5212, 87.9258] +24-11-19 20:28:12 | D | best error = [ 1.2811, 1.2811, 1.2811, 1.2811, 1.2811] +24-11-19 20:28:12 | D | + error = [1.2811] +24-11-19 20:28:12 | D | - Calibrating model.layers.12.self_attn.o_proj.weight +24-11-19 20:28:12 | D | + w: sint8 +24-11-19 20:28:12 | D | + x: None +24-11-19 20:28:12 | D | + y: None +24-11-19 20:28:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:12 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:12 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:12 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:12 | D | - range ratio = [ 1.0000] +24-11-19 20:28:12 | D | sum error = [ 0.6289] +24-11-19 20:28:12 | D | best error = [ 0.6289] +24-11-19 20:28:13 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:13 | D | sum error = [ 0.6250, 0.6200, 0.6215, 0.6243, 0.6330] +24-11-19 20:28:13 | D | best error = [ 0.5732, 0.5483, 0.5347, 0.5259, 0.5200] +24-11-19 20:28:13 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:13 | D | sum error = [ 0.6442, 0.6590, 0.6755, 0.6963, 0.7223] +24-11-19 20:28:13 | D | best error = [ 0.5163, 0.5137, 0.5122, 0.5111, 0.5104] +24-11-19 20:28:13 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:13 | D | sum error = [ 0.7579, 0.7926, 0.8321, 0.8776, 0.9335] +24-11-19 20:28:13 | D | best error = [ 0.5100, 0.5098, 0.5096, 0.5096, 0.5095] +24-11-19 20:28:13 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:13 | D | sum error = [ 0.9844, 1.0463, 1.1124, 1.1852, 1.2638] +24-11-19 20:28:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:13 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:13 | D | sum error = [ 1.3421, 1.4331, 1.5255, 1.6273, 1.7308] +24-11-19 20:28:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:13 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:13 | D | sum error = [ 1.8446, 1.9602, 2.0878, 2.2211, 2.3595] +24-11-19 20:28:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:13 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:13 | D | sum error = [ 2.5071, 2.6610, 2.8226, 2.9966, 3.1768] +24-11-19 20:28:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:13 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:13 | D | sum error = [ 3.3623, 3.5629, 3.7721, 3.9891, 4.2193] +24-11-19 20:28:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:13 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:13 | D | sum error = [ 4.4532, 4.7078, 4.9694, 5.2448, 5.5310] +24-11-19 20:28:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:13 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:13 | D | sum error = [ 5.8291, 6.1453, 6.4711, 6.8131, 7.1663] +24-11-19 20:28:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:13 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:13 | D | sum error = [ 7.5350, 7.9198, 8.3150, 8.7276, 9.1560] +24-11-19 20:28:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:13 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:13 | D | sum error = [ 9.5970, 10.0580, 10.5328, 11.0277, 11.5380] +24-11-19 20:28:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:13 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:13 | D | sum error = [ 12.0649, 12.6096, 13.1713, 13.7514, 14.3500] +24-11-19 20:28:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:13 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:13 | D | sum error = [ 14.9623, 15.5945, 16.2465, 16.9153, 17.6012] +24-11-19 20:28:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:13 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:13 | D | sum error = [ 18.3060, 19.0288, 19.7712, 20.5323, 21.3134] +24-11-19 20:28:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:13 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:13 | D | sum error = [ 22.1184, 22.9428, 23.7846, 24.6461, 25.5301] +24-11-19 20:28:13 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:13 | D | + error = [0.5095] +24-11-19 20:28:13 | D | - Calibrating model.layers.12.mlp.up_proj.weight +24-11-19 20:28:13 | D | + w: sint8 +24-11-19 20:28:13 | D | + x: None +24-11-19 20:28:13 | D | + y: None +24-11-19 20:28:13 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:13 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:13 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:13 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:13 | D | - range ratio = [ 1.0000] +24-11-19 20:28:13 | D | sum error = [ 0.2929] +24-11-19 20:28:13 | D | best error = [ 0.2929] +24-11-19 20:28:14 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:14 | D | sum error = [ 0.2907, 0.2901, 0.2908, 0.2944, 0.3000] +24-11-19 20:28:14 | D | best error = [ 0.2725, 0.2638, 0.2594, 0.2570, 0.2557] +24-11-19 20:28:14 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:14 | D | sum error = [ 0.3076, 0.3180, 0.3302, 0.3469, 0.3654] +24-11-19 20:28:14 | D | best error = [ 0.2550, 0.2547, 0.2546, 0.2546, 0.2546] +24-11-19 20:28:14 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:14 | D | sum error = [ 0.3860, 0.4105, 0.4360, 0.4665, 0.4985] +24-11-19 20:28:14 | D | best error = [ 0.2546, 0.2546, 0.2546, 0.2546, 0.2546] +24-11-19 20:28:14 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:14 | D | sum error = [ 0.5337, 0.5725, 0.6129, 0.6575, 0.7042] +24-11-19 20:28:14 | D | best error = [ 0.2546, 0.2546, 0.2546, 0.2546, 0.2546] +24-11-19 20:28:14 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:14 | D | sum error = [ 0.7554, 0.8089, 0.8666, 0.9264, 0.9919] +24-11-19 20:28:14 | D | best error = [ 0.2546, 0.2546, 0.2546, 0.2546, 0.2546] +24-11-19 20:28:14 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:14 | D | sum error = [ 1.0602, 1.1328, 1.2090, 1.2898, 1.3763] +24-11-19 20:28:14 | D | best error = [ 0.2546, 0.2546, 0.2546, 0.2546, 0.2546] +24-11-19 20:28:14 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:14 | D | sum error = [ 1.4659, 1.5623, 1.6639, 1.7698, 1.8835] +24-11-19 20:28:14 | D | best error = [ 0.2546, 0.2546, 0.2546, 0.2546, 0.2546] +24-11-19 20:28:14 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:14 | D | sum error = [ 2.0013, 2.1254, 2.2567, 2.3952, 2.5399] +24-11-19 20:28:14 | D | best error = [ 0.2546, 0.2546, 0.2546, 0.2546, 0.2546] +24-11-19 20:28:14 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:14 | D | sum error = [ 2.6920, 2.8538, 3.0224, 3.1984, 3.3860] +24-11-19 20:28:14 | D | best error = [ 0.2546, 0.2546, 0.2546, 0.2546, 0.2546] +24-11-19 20:28:14 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:14 | D | sum error = [ 3.5804, 3.7859, 4.0000, 4.2259, 4.4622] +24-11-19 20:28:14 | D | best error = [ 0.2546, 0.2546, 0.2546, 0.2546, 0.2546] +24-11-19 20:28:14 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:14 | D | sum error = [ 4.7062, 4.9654, 5.2346, 5.5180, 5.8132] +24-11-19 20:28:14 | D | best error = [ 0.2546, 0.2546, 0.2546, 0.2546, 0.2546] +24-11-19 20:28:14 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:14 | D | sum error = [ 6.1197, 6.4381, 6.7706, 7.1241, 7.4874] +24-11-19 20:28:14 | D | best error = [ 0.2546, 0.2546, 0.2546, 0.2546, 0.2546] +24-11-19 20:28:14 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:14 | D | sum error = [ 7.8680, 8.2595, 8.6693, 9.1035, 9.5436] +24-11-19 20:28:14 | D | best error = [ 0.2546, 0.2546, 0.2546, 0.2546, 0.2546] +24-11-19 20:28:14 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:14 | D | sum error = [ 10.0015, 10.4807, 10.9747, 11.4961, 12.0280] +24-11-19 20:28:14 | D | best error = [ 0.2546, 0.2546, 0.2546, 0.2546, 0.2546] +24-11-19 20:28:14 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:14 | D | sum error = [ 12.5812, 13.1501, 13.7467, 14.3621, 14.9906] +24-11-19 20:28:14 | D | best error = [ 0.2546, 0.2546, 0.2546, 0.2546, 0.2546] +24-11-19 20:28:14 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:14 | D | sum error = [ 15.6426, 16.3176, 17.0113, 17.7293, 18.4606] +24-11-19 20:28:14 | D | best error = [ 0.2546, 0.2546, 0.2546, 0.2546, 0.2546] +24-11-19 20:28:14 | D | + error = [0.2546] +24-11-19 20:28:14 | D | - Calibrating model.layers.12.mlp.gate_proj.weight +24-11-19 20:28:14 | D | + w: sint8 +24-11-19 20:28:14 | D | + x: None +24-11-19 20:28:14 | D | + y: None +24-11-19 20:28:14 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:14 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:15 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:15 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:15 | D | - range ratio = [ 1.0000] +24-11-19 20:28:15 | D | sum error = [ 5.9748] +24-11-19 20:28:15 | D | best error = [ 5.9748] +24-11-19 20:28:16 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:16 | D | sum error = [ 5.9571, 5.9285, 5.9472, 6.0205, 6.1545] +24-11-19 20:28:16 | D | best error = [ 5.5443, 5.3803, 5.2911, 5.2422, 5.2174] +24-11-19 20:28:16 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:16 | D | sum error = [ 6.3066, 6.5201, 6.7918, 7.1286, 7.4832] +24-11-19 20:28:16 | D | best error = [ 5.2051, 5.2000, 5.1980, 5.1975, 5.1973] +24-11-19 20:28:16 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:16 | D | sum error = [ 7.9518, 8.4358, 9.0025, 9.6158, 10.3267] +24-11-19 20:28:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:28:16 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:16 | D | sum error = [ 11.0721, 11.8822, 12.7622, 13.7102, 14.7454] +24-11-19 20:28:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:28:16 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:16 | D | sum error = [ 15.8366, 17.0189, 18.2575, 19.6106, 21.0405] +24-11-19 20:28:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:28:16 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:16 | D | sum error = [ 22.5981, 24.2123, 25.9549, 27.8392, 29.8087] +24-11-19 20:28:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:28:16 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:16 | D | sum error = [ 31.9258, 34.1828, 36.5884, 39.1221, 41.8433] +24-11-19 20:28:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:28:16 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:16 | D | sum error = [ 44.7140, 47.7781, 51.0596, 54.5142, 58.2038] +24-11-19 20:28:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:28:16 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:16 | D | sum error = [ 62.1226, 66.2840, 70.6875, 75.4186, 80.3978] +24-11-19 20:28:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:28:16 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:16 | D | sum error = [ 85.6780, 91.3055, 97.2570, 103.5564, 110.2577] +24-11-19 20:28:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:28:16 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:16 | D | sum error = [ 117.3551, 124.8364, 132.7855, 141.1932, 150.0744] +24-11-19 20:28:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:28:16 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:16 | D | sum error = [ 159.4470, 169.3085, 179.6946, 190.6552, 202.1740] +24-11-19 20:28:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:28:16 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:16 | D | sum error = [ 214.2906, 227.0653, 240.4522, 254.5118, 269.2103] +24-11-19 20:28:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:28:16 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:16 | D | sum error = [ 284.5891, 300.7008, 317.5197, 335.0835, 353.3900] +24-11-19 20:28:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:28:16 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:16 | D | sum error = [ 372.4536, 392.2629, 412.8693, 434.2641, 456.4525] +24-11-19 20:28:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:28:16 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:16 | D | sum error = [ 479.4434, 503.1947, 527.7568, 553.0924, 579.2353] +24-11-19 20:28:16 | D | best error = [ 5.1973, 5.1973, 5.1973, 5.1973, 5.1973] +24-11-19 20:28:16 | D | + error = [5.1973] +24-11-19 20:28:16 | D | - Calibrating model.layers.12.mlp.down_proj.weight +24-11-19 20:28:16 | D | + w: sint8 +24-11-19 20:28:16 | D | + x: None +24-11-19 20:28:16 | D | + y: None +24-11-19 20:28:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:16 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:17 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:17 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:17 | D | - range ratio = [ 1.0000] +24-11-19 20:28:17 | D | sum error = [ 0.6235] +24-11-19 20:28:17 | D | best error = [ 0.6235] +24-11-19 20:28:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:18 | D | sum error = [ 0.6165, 0.6125, 0.6107, 0.6093, 0.6100] +24-11-19 20:28:18 | D | best error = [ 0.5960, 0.5835, 0.5756, 0.5702, 0.5659] +24-11-19 20:28:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:18 | D | sum error = [ 0.6143, 0.6222, 0.6327, 0.6493, 0.6707] +24-11-19 20:28:18 | D | best error = [ 0.5628, 0.5609, 0.5597, 0.5590, 0.5586] +24-11-19 20:28:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:18 | D | sum error = [ 0.6938, 0.7236, 0.7608, 0.8026, 0.8516] +24-11-19 20:28:18 | D | best error = [ 0.5583, 0.5582, 0.5582, 0.5581, 0.5581] +24-11-19 20:28:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:18 | D | sum error = [ 0.9055, 0.9666, 1.0308, 1.1048, 1.1848] +24-11-19 20:28:18 | D | best error = [ 0.5581, 0.5581, 0.5581, 0.5581, 0.5581] +24-11-19 20:28:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:18 | D | sum error = [ 1.2673, 1.3592, 1.4566, 1.5627, 1.6748] +24-11-19 20:28:18 | D | best error = [ 0.5581, 0.5581, 0.5581, 0.5581, 0.5581] +24-11-19 20:28:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:18 | D | sum error = [ 1.7943, 1.9208, 2.0548, 2.1972, 2.3487] +24-11-19 20:28:18 | D | best error = [ 0.5581, 0.5581, 0.5581, 0.5581, 0.5581] +24-11-19 20:28:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:18 | D | sum error = [ 2.5087, 2.6796, 2.8591, 3.0491, 3.2487] +24-11-19 20:28:18 | D | best error = [ 0.5581, 0.5581, 0.5581, 0.5581, 0.5581] +24-11-19 20:28:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:18 | D | sum error = [ 3.4607, 3.6861, 3.9215, 4.1703, 4.4322] +24-11-19 20:28:18 | D | best error = [ 0.5581, 0.5581, 0.5581, 0.5581, 0.5581] +24-11-19 20:28:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:18 | D | sum error = [ 4.7073, 4.9971, 5.3027, 5.6228, 5.9604] +24-11-19 20:28:18 | D | best error = [ 0.5581, 0.5581, 0.5581, 0.5581, 0.5581] +24-11-19 20:28:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:18 | D | sum error = [ 6.3140, 6.6845, 7.0748, 7.4814, 7.9106] +24-11-19 20:28:18 | D | best error = [ 0.5581, 0.5581, 0.5581, 0.5581, 0.5581] +24-11-19 20:28:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:18 | D | sum error = [ 8.3599, 8.8302, 9.3209, 9.8352, 10.3735] +24-11-19 20:28:18 | D | best error = [ 0.5581, 0.5581, 0.5581, 0.5581, 0.5581] +24-11-19 20:28:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:18 | D | sum error = [ 10.9345, 11.5199, 12.1312, 12.7694, 13.4338] +24-11-19 20:28:18 | D | best error = [ 0.5581, 0.5581, 0.5581, 0.5581, 0.5581] +24-11-19 20:28:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:18 | D | sum error = [ 14.1245, 14.8454, 15.5955, 16.3731, 17.1799] +24-11-19 20:28:18 | D | best error = [ 0.5581, 0.5581, 0.5581, 0.5581, 0.5581] +24-11-19 20:28:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:18 | D | sum error = [ 18.0196, 18.8940, 19.8004, 20.7422, 21.7160] +24-11-19 20:28:18 | D | best error = [ 0.5581, 0.5581, 0.5581, 0.5581, 0.5581] +24-11-19 20:28:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:18 | D | sum error = [ 22.7265, 23.7735, 24.8570, 25.9764, 27.1357] +24-11-19 20:28:18 | D | best error = [ 0.5581, 0.5581, 0.5581, 0.5581, 0.5581] +24-11-19 20:28:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:18 | D | sum error = [ 28.3325, 29.5676, 30.8424, 32.1555, 33.5089] +24-11-19 20:28:18 | D | best error = [ 0.5581, 0.5581, 0.5581, 0.5581, 0.5581] +24-11-19 20:28:18 | D | + error = [0.5581] +24-11-19 20:28:18 | D | - Quantizing model.layers.12.self_attn.q_proj.weight +24-11-19 20:28:19 | D | - Quantizing model.layers.12.self_attn.k_proj.weight +24-11-19 20:28:22 | D | - Quantizing model.layers.12.self_attn.v_proj.weight +24-11-19 20:28:23 | D | - Quantizing model.layers.12.self_attn.o_proj.weight +24-11-19 20:28:23 | D | - Quantizing model.layers.12.mlp.up_proj.weight +24-11-19 20:28:24 | D | - Quantizing model.layers.12.mlp.gate_proj.weight +24-11-19 20:28:25 | D | - Quantizing model.layers.12.mlp.down_proj.weight +24-11-19 20:28:35 | D | - Quantizing layer model.layers.13 +24-11-19 20:28:35 | D | - Calibrating model.layers.13.self_attn.q_proj.weight +24-11-19 20:28:35 | D | + w: sint8 +24-11-19 20:28:35 | D | + x: None +24-11-19 20:28:35 | D | + y: None +24-11-19 20:28:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:28:35 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:35 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:36 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:36 | D | - range ratio = [ 1.0000] +24-11-19 20:28:36 | D | sum error = [ 5.3627] +24-11-19 20:28:36 | D | best error = [ 5.3627] +24-11-19 20:28:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:51 | D | sum error = [ 5.3655, 5.4240, 5.5931, 5.5544, 5.4719] +24-11-19 20:28:51 | D | best error = [ 5.3627, 5.3627, 5.3627, 5.3627, 5.3627] +24-11-19 20:28:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:51 | D | sum error = [ 5.7091, 6.0044, 5.9707, 6.3041, 6.8037] +24-11-19 20:28:51 | D | best error = [ 5.3627, 5.3627, 5.3627, 5.3627, 5.3627] +24-11-19 20:28:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:51 | D | sum error = [ 7.0767, 7.4780, 8.0688, 8.7925, 9.4339] +24-11-19 20:28:51 | D | best error = [ 5.3627, 5.3627, 5.3627, 5.3627, 5.3627] +24-11-19 20:28:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:51 | D | sum error = [ 9.9617, 10.6395, 11.5372, 12.4111, 13.2158] +24-11-19 20:28:51 | D | best error = [ 5.3627, 5.3627, 5.3627, 5.3627, 5.3627] +24-11-19 20:28:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:51 | D | sum error = [ 14.5843, 15.4055, 16.9955, 18.2138, 19.6545] +24-11-19 20:28:51 | D | best error = [ 5.3627, 5.3627, 5.3627, 5.3627, 5.3627] +24-11-19 20:28:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:51 | D | sum error = [ 21.2076, 22.7946, 24.7347, 26.5361, 28.5689] +24-11-19 20:28:51 | D | best error = [ 5.3627, 5.3627, 5.3627, 5.3627, 5.3627] +24-11-19 20:28:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:51 | D | sum error = [ 30.8053, 33.3156, 35.9141, 38.5751, 41.5040] +24-11-19 20:28:51 | D | best error = [ 5.3627, 5.3627, 5.3627, 5.3627, 5.3627] +24-11-19 20:28:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:51 | D | sum error = [ 44.4632, 47.6560, 51.2108, 54.6642, 58.7836] +24-11-19 20:28:51 | D | best error = [ 5.3627, 5.3627, 5.3627, 5.3627, 5.3627] +24-11-19 20:28:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:51 | D | sum error = [ 62.6261, 67.0545, 71.7257, 76.5270, 81.6861] +24-11-19 20:28:51 | D | best error = [ 5.3627, 5.3627, 5.3627, 5.3627, 5.3627] +24-11-19 20:28:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:51 | D | sum error = [ 87.1099, 92.7456, 98.8360, 104.9789, 111.6585] +24-11-19 20:28:51 | D | best error = [ 5.3627, 5.3627, 5.3627, 5.3627, 5.3627] +24-11-19 20:28:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:51 | D | sum error = [ 118.4866, 125.7959, 133.8543, 141.9370, 150.5617] +24-11-19 20:28:51 | D | best error = [ 5.3627, 5.3627, 5.3627, 5.3627, 5.3627] +24-11-19 20:28:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:51 | D | sum error = [ 159.3967, 169.1213, 179.0222, 189.4126, 200.5317] +24-11-19 20:28:51 | D | best error = [ 5.3627, 5.3627, 5.3627, 5.3627, 5.3627] +24-11-19 20:28:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:51 | D | sum error = [ 211.8813, 223.8608, 236.3629, 249.3982, 262.9321] +24-11-19 20:28:51 | D | best error = [ 5.3627, 5.3627, 5.3627, 5.3627, 5.3627] +24-11-19 20:28:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:51 | D | sum error = [ 277.1650, 291.8370, 307.2367, 323.1902, 339.6280] +24-11-19 20:28:51 | D | best error = [ 5.3627, 5.3627, 5.3627, 5.3627, 5.3627] +24-11-19 20:28:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:51 | D | sum error = [ 356.8194, 374.4731, 392.7072, 411.4963, 430.7721] +24-11-19 20:28:51 | D | best error = [ 5.3627, 5.3627, 5.3627, 5.3627, 5.3627] +24-11-19 20:28:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:51 | D | sum error = [ 450.5625, 470.9172, 491.5850, 512.5750, 533.9386] +24-11-19 20:28:51 | D | best error = [ 5.3627, 5.3627, 5.3627, 5.3627, 5.3627] +24-11-19 20:28:51 | D | + error = [5.3627] +24-11-19 20:28:51 | D | - Calibrating model.layers.13.self_attn.k_proj.weight +24-11-19 20:28:51 | D | + w: sint8 +24-11-19 20:28:51 | D | + x: None +24-11-19 20:28:51 | D | + y: None +24-11-19 20:28:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:28:51 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:28:51 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:28:51 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:28:51 | D | - range ratio = [ 1.0000] +24-11-19 20:28:51 | D | sum error = [ 4.1786] +24-11-19 20:28:51 | D | best error = [ 4.1786] +24-11-19 20:29:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:05 | D | sum error = [ 4.1255, 3.9560, 4.2677, 4.1280, 4.3368] +24-11-19 20:29:05 | D | best error = [ 4.1255, 3.9560, 3.9560, 3.9560, 3.9560] +24-11-19 20:29:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:05 | D | sum error = [ 4.4522, 4.6689, 4.6399, 4.9933, 5.0085] +24-11-19 20:29:05 | D | best error = [ 3.9560, 3.9560, 3.9560, 3.9560, 3.9560] +24-11-19 20:29:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:05 | D | sum error = [ 5.5936, 5.8462, 5.9739, 6.3900, 7.1373] +24-11-19 20:29:05 | D | best error = [ 3.9560, 3.9560, 3.9560, 3.9560, 3.9560] +24-11-19 20:29:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:05 | D | sum error = [ 7.5000, 8.2541, 8.8954, 9.2988, 10.1515] +24-11-19 20:29:05 | D | best error = [ 3.9560, 3.9560, 3.9560, 3.9560, 3.9560] +24-11-19 20:29:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:05 | D | sum error = [ 11.0580, 11.8720, 13.2229, 14.0769, 15.2011] +24-11-19 20:29:05 | D | best error = [ 3.9560, 3.9560, 3.9560, 3.9560, 3.9560] +24-11-19 20:29:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:05 | D | sum error = [ 16.4320, 17.6631, 19.0631, 20.8857, 23.1428] +24-11-19 20:29:05 | D | best error = [ 3.9560, 3.9560, 3.9560, 3.9560, 3.9560] +24-11-19 20:29:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:05 | D | sum error = [ 24.0012, 26.6328, 28.6147, 30.8630, 33.9210] +24-11-19 20:29:05 | D | best error = [ 3.9560, 3.9560, 3.9560, 3.9560, 3.9560] +24-11-19 20:29:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:05 | D | sum error = [ 36.3253, 39.9141, 43.3085, 46.7316, 50.2852] +24-11-19 20:29:05 | D | best error = [ 3.9560, 3.9560, 3.9560, 3.9560, 3.9560] +24-11-19 20:29:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:05 | D | sum error = [ 54.2977, 57.6922, 62.6346, 67.4409, 72.8680] +24-11-19 20:29:05 | D | best error = [ 3.9560, 3.9560, 3.9560, 3.9560, 3.9560] +24-11-19 20:29:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:05 | D | sum error = [ 77.9502, 84.3160, 90.0441, 96.6378, 103.9509] +24-11-19 20:29:05 | D | best error = [ 3.9560, 3.9560, 3.9560, 3.9560, 3.9560] +24-11-19 20:29:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:05 | D | sum error = [ 111.1488, 119.1517, 127.2258, 135.9862, 144.7956] +24-11-19 20:29:05 | D | best error = [ 3.9560, 3.9560, 3.9560, 3.9560, 3.9560] +24-11-19 20:29:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:05 | D | sum error = [ 154.3903, 163.8199, 173.9886, 184.8633, 195.7186] +24-11-19 20:29:05 | D | best error = [ 3.9560, 3.9560, 3.9560, 3.9560, 3.9560] +24-11-19 20:29:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:05 | D | sum error = [ 207.6330, 219.3582, 232.0520, 244.4244, 257.1092] +24-11-19 20:29:05 | D | best error = [ 3.9560, 3.9560, 3.9560, 3.9560, 3.9560] +24-11-19 20:29:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:05 | D | sum error = [ 270.7605, 284.6397, 298.8481, 313.8136, 329.0651] +24-11-19 20:29:05 | D | best error = [ 3.9560, 3.9560, 3.9560, 3.9560, 3.9560] +24-11-19 20:29:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:05 | D | sum error = [ 345.3837, 362.0066, 379.2566, 397.1929, 415.8415] +24-11-19 20:29:05 | D | best error = [ 3.9560, 3.9560, 3.9560, 3.9560, 3.9560] +24-11-19 20:29:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:05 | D | sum error = [ 434.8441, 454.6113, 475.3816, 496.3784, 518.1053] +24-11-19 20:29:05 | D | best error = [ 3.9560, 3.9560, 3.9560, 3.9560, 3.9560] +24-11-19 20:29:05 | D | + error = [3.9560] +24-11-19 20:29:05 | D | - Calibrating model.layers.13.self_attn.v_proj.weight +24-11-19 20:29:05 | D | + w: sint8 +24-11-19 20:29:05 | D | + x: None +24-11-19 20:29:05 | D | + y: None +24-11-19 20:29:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:05 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:29:05 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:29:06 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:06 | D | - range ratio = [ 1.0000] +24-11-19 20:29:06 | D | sum error = [ 1.5429] +24-11-19 20:29:06 | D | best error = [ 1.5429] +24-11-19 20:29:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:06 | D | sum error = [ 1.5349, 1.5291, 1.5369, 1.5637, 1.5954] +24-11-19 20:29:06 | D | best error = [ 1.4094, 1.3643, 1.3425, 1.3299, 1.3238] +24-11-19 20:29:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:06 | D | sum error = [ 1.6296, 1.6695, 1.7425, 1.8536, 1.9290] +24-11-19 20:29:06 | D | best error = [ 1.3197, 1.3181, 1.3177, 1.3177, 1.3177] +24-11-19 20:29:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:06 | D | sum error = [ 2.0450, 2.1626, 2.3127, 2.4614, 2.6433] +24-11-19 20:29:06 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 20:29:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:06 | D | sum error = [ 2.8113, 3.0143, 3.2199, 3.4621, 3.6949] +24-11-19 20:29:06 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 20:29:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:06 | D | sum error = [ 3.9477, 4.2212, 4.5171, 4.8289, 5.1521] +24-11-19 20:29:06 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 20:29:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:06 | D | sum error = [ 5.4971, 5.8583, 6.2739, 6.6814, 7.1181] +24-11-19 20:29:06 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 20:29:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:06 | D | sum error = [ 7.5799, 8.0736, 8.6014, 9.1443, 9.7149] +24-11-19 20:29:06 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 20:29:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:06 | D | sum error = [ 10.3165, 10.9584, 11.6357, 12.3358, 13.0785] +24-11-19 20:29:06 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 20:29:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:06 | D | sum error = [ 13.8629, 14.6678, 15.5409, 16.4328, 17.3831] +24-11-19 20:29:06 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 20:29:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:06 | D | sum error = [ 18.3756, 19.4147, 20.4995, 21.6437, 22.8290] +24-11-19 20:29:06 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 20:29:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:06 | D | sum error = [ 24.0746, 25.3792, 26.7423, 28.1611, 29.6332] +24-11-19 20:29:06 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 20:29:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:06 | D | sum error = [ 31.1734, 32.7542, 34.4260, 36.1648, 37.9660] +24-11-19 20:29:06 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 20:29:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:06 | D | sum error = [ 39.8517, 41.8062, 43.8319, 45.9402, 48.1342] +24-11-19 20:29:06 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 20:29:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:06 | D | sum error = [ 50.3993, 52.7435, 55.1726, 57.6820, 60.2814] +24-11-19 20:29:06 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 20:29:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:06 | D | sum error = [ 62.9661, 65.7390, 68.6049, 71.5647, 74.6224] +24-11-19 20:29:06 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 20:29:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:06 | D | sum error = [ 77.7629, 81.0108, 84.3474, 87.7836, 91.3231] +24-11-19 20:29:06 | D | best error = [ 1.3177, 1.3177, 1.3177, 1.3177, 1.3177] +24-11-19 20:29:06 | D | + error = [1.3177] +24-11-19 20:29:06 | D | - Calibrating model.layers.13.self_attn.o_proj.weight +24-11-19 20:29:06 | D | + w: sint8 +24-11-19 20:29:06 | D | + x: None +24-11-19 20:29:06 | D | + y: None +24-11-19 20:29:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:06 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:29:06 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:29:06 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:06 | D | - range ratio = [ 1.0000] +24-11-19 20:29:06 | D | sum error = [ 0.6587] +24-11-19 20:29:06 | D | best error = [ 0.6587] +24-11-19 20:29:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:07 | D | sum error = [ 0.6568, 0.6513, 0.6565, 0.6617, 0.6734] +24-11-19 20:29:07 | D | best error = [ 0.5910, 0.5594, 0.5430, 0.5318, 0.5248] +24-11-19 20:29:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:07 | D | sum error = [ 0.6896, 0.7038, 0.7348, 0.7634, 0.7994] +24-11-19 20:29:07 | D | best error = [ 0.5198, 0.5166, 0.5144, 0.5129, 0.5119] +24-11-19 20:29:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:07 | D | sum error = [ 0.8402, 0.8837, 0.9337, 0.9909, 1.0525] +24-11-19 20:29:07 | D | best error = [ 0.5114, 0.5110, 0.5107, 0.5106, 0.5105] +24-11-19 20:29:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:07 | D | sum error = [ 1.1176, 1.1876, 1.2632, 1.3458, 1.4343] +24-11-19 20:29:07 | D | best error = [ 0.5105, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:07 | D | sum error = [ 1.5245, 1.6275, 1.7294, 1.8398, 1.9527] +24-11-19 20:29:07 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:07 | D | sum error = [ 2.0767, 2.2060, 2.3415, 2.4838, 2.6290] +24-11-19 20:29:07 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:07 | D | sum error = [ 2.7885, 2.9507, 3.1278, 3.3050, 3.4926] +24-11-19 20:29:07 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:07 | D | sum error = [ 3.6902, 3.8973, 4.1131, 4.3373, 4.5714] +24-11-19 20:29:07 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:07 | D | sum error = [ 4.8161, 5.0717, 5.3361, 5.6190, 5.9093] +24-11-19 20:29:07 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:07 | D | sum error = [ 6.2090, 6.5234, 6.8498, 7.1831, 7.5349] +24-11-19 20:29:07 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:07 | D | sum error = [ 7.8948, 8.2694, 8.6549, 9.0564, 9.4677] +24-11-19 20:29:07 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:07 | D | sum error = [ 9.8939, 10.3316, 10.7803, 11.2480, 11.7242] +24-11-19 20:29:07 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:07 | D | sum error = [ 12.2152, 12.7222, 13.2426, 13.7804, 14.3278] +24-11-19 20:29:07 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:07 | D | sum error = [ 14.8910, 15.4730, 16.0656, 16.6787, 17.3046] +24-11-19 20:29:07 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:07 | D | sum error = [ 17.9505, 18.6120, 19.2881, 19.9892, 20.7103] +24-11-19 20:29:07 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:07 | D | sum error = [ 21.4511, 22.2127, 22.9951, 23.8027, 24.6386] +24-11-19 20:29:07 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:07 | D | + error = [0.5104] +24-11-19 20:29:07 | D | - Calibrating model.layers.13.mlp.up_proj.weight +24-11-19 20:29:07 | D | + w: sint8 +24-11-19 20:29:07 | D | + x: None +24-11-19 20:29:07 | D | + y: None +24-11-19 20:29:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:07 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:29:07 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:29:07 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:07 | D | - range ratio = [ 1.0000] +24-11-19 20:29:07 | D | sum error = [ 0.2993] +24-11-19 20:29:07 | D | best error = [ 0.2993] +24-11-19 20:29:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:08 | D | sum error = [ 0.2977, 0.2965, 0.2987, 0.3017, 0.3064] +24-11-19 20:29:08 | D | best error = [ 0.2785, 0.2699, 0.2655, 0.2630, 0.2616] +24-11-19 20:29:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:08 | D | sum error = [ 0.3145, 0.3255, 0.3383, 0.3547, 0.3733] +24-11-19 20:29:08 | D | best error = [ 0.2609, 0.2606, 0.2605, 0.2604, 0.2604] +24-11-19 20:29:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:08 | D | sum error = [ 0.3940, 0.4187, 0.4472, 0.4769, 0.5098] +24-11-19 20:29:08 | D | best error = [ 0.2604, 0.2604, 0.2604, 0.2604, 0.2604] +24-11-19 20:29:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:08 | D | sum error = [ 0.5451, 0.5843, 0.6260, 0.6709, 0.7188] +24-11-19 20:29:08 | D | best error = [ 0.2604, 0.2604, 0.2604, 0.2604, 0.2604] +24-11-19 20:29:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:08 | D | sum error = [ 0.7701, 0.8255, 0.8842, 0.9457, 1.0115] +24-11-19 20:29:08 | D | best error = [ 0.2604, 0.2604, 0.2604, 0.2604, 0.2604] +24-11-19 20:29:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:08 | D | sum error = [ 1.0804, 1.1556, 1.2341, 1.3162, 1.4048] +24-11-19 20:29:08 | D | best error = [ 0.2604, 0.2604, 0.2604, 0.2604, 0.2604] +24-11-19 20:29:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:08 | D | sum error = [ 1.4955, 1.5935, 1.6973, 1.8054, 1.9196] +24-11-19 20:29:08 | D | best error = [ 0.2604, 0.2604, 0.2604, 0.2604, 0.2604] +24-11-19 20:29:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:08 | D | sum error = [ 2.0402, 2.1676, 2.3004, 2.4413, 2.5889] +24-11-19 20:29:08 | D | best error = [ 0.2604, 0.2604, 0.2604, 0.2604, 0.2604] +24-11-19 20:29:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:08 | D | sum error = [ 2.7456, 2.9083, 3.0807, 3.2598, 3.4506] +24-11-19 20:29:08 | D | best error = [ 0.2604, 0.2604, 0.2604, 0.2604, 0.2604] +24-11-19 20:29:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:08 | D | sum error = [ 3.6476, 3.8576, 4.0740, 4.3035, 4.5413] +24-11-19 20:29:08 | D | best error = [ 0.2604, 0.2604, 0.2604, 0.2604, 0.2604] +24-11-19 20:29:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:08 | D | sum error = [ 4.7893, 5.0522, 5.3256, 5.6106, 5.9081] +24-11-19 20:29:08 | D | best error = [ 0.2604, 0.2604, 0.2604, 0.2604, 0.2604] +24-11-19 20:29:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:08 | D | sum error = [ 6.2207, 6.5426, 6.8845, 7.2338, 7.6039] +24-11-19 20:29:08 | D | best error = [ 0.2604, 0.2604, 0.2604, 0.2604, 0.2604] +24-11-19 20:29:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:08 | D | sum error = [ 7.9860, 8.3850, 8.7968, 9.2222, 9.6729] +24-11-19 20:29:08 | D | best error = [ 0.2604, 0.2604, 0.2604, 0.2604, 0.2604] +24-11-19 20:29:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:08 | D | sum error = [ 10.1354, 10.6188, 11.1169, 11.6374, 12.1680] +24-11-19 20:29:08 | D | best error = [ 0.2604, 0.2604, 0.2604, 0.2604, 0.2604] +24-11-19 20:29:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:08 | D | sum error = [ 12.7250, 13.2932, 13.8927, 14.5005, 15.1241] +24-11-19 20:29:08 | D | best error = [ 0.2604, 0.2604, 0.2604, 0.2604, 0.2604] +24-11-19 20:29:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:08 | D | sum error = [ 15.7860, 16.4573, 17.1496, 17.8593, 18.6056] +24-11-19 20:29:08 | D | best error = [ 0.2604, 0.2604, 0.2604, 0.2604, 0.2604] +24-11-19 20:29:08 | D | + error = [0.2604] +24-11-19 20:29:08 | D | - Calibrating model.layers.13.mlp.gate_proj.weight +24-11-19 20:29:08 | D | + w: sint8 +24-11-19 20:29:08 | D | + x: None +24-11-19 20:29:08 | D | + y: None +24-11-19 20:29:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:08 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:29:09 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:29:09 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:29:09 | D | - range ratio = [ 1.0000] +24-11-19 20:29:09 | D | sum error = [ 6.2253] +24-11-19 20:29:09 | D | best error = [ 6.2253] +24-11-19 20:29:10 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:10 | D | sum error = [ 6.1721, 6.1681, 6.2013, 6.2660, 6.3768] +24-11-19 20:29:10 | D | best error = [ 5.7639, 5.5890, 5.4981, 5.4459, 5.4176] +24-11-19 20:29:10 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:10 | D | sum error = [ 6.5523, 6.7688, 7.0501, 7.3915, 7.7923] +24-11-19 20:29:10 | D | best error = [ 5.4037, 5.3978, 5.3954, 5.3949, 5.3947] +24-11-19 20:29:10 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:10 | D | sum error = [ 8.2575, 8.7634, 9.3524, 10.0057, 10.7002] +24-11-19 20:29:10 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:10 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:10 | D | sum error = [ 11.4828, 12.3222, 13.2170, 14.2106, 15.2749] +24-11-19 20:29:10 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:10 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:10 | D | sum error = [ 16.4007, 17.5905, 18.8916, 20.2939, 21.7735] +24-11-19 20:29:10 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:10 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:10 | D | sum error = [ 23.3563, 25.0218, 26.8343, 28.7314, 30.7816] +24-11-19 20:29:10 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:10 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:10 | D | sum error = [ 32.9636, 35.2701, 37.7539, 40.3759, 43.1596] +24-11-19 20:29:10 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:10 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:10 | D | sum error = [ 46.1525, 49.3271, 52.7176, 56.3080, 60.1292] +24-11-19 20:29:10 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:10 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:10 | D | sum error = [ 64.2196, 68.5704, 73.1546, 78.0797, 83.2818] +24-11-19 20:29:10 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:10 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:10 | D | sum error = [ 88.8146, 94.7357, 100.9633, 107.6044, 114.6454] +24-11-19 20:29:10 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:10 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:10 | D | sum error = [ 122.0916, 129.9967, 138.3394, 147.1850, 156.5555] +24-11-19 20:29:10 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:10 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:10 | D | sum error = [ 166.4340, 176.8680, 187.8683, 199.4835, 211.7017] +24-11-19 20:29:10 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:10 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:10 | D | sum error = [ 224.5552, 238.0947, 252.3107, 267.2339, 282.8783] +24-11-19 20:29:10 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:10 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:10 | D | sum error = [ 299.2736, 316.4071, 334.3174, 352.9868, 372.4646] +24-11-19 20:29:10 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:10 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:10 | D | sum error = [ 392.7558, 413.8512, 435.8156, 458.5807, 482.2040] +24-11-19 20:29:10 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:10 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:10 | D | sum error = [ 506.6569, 531.9775, 558.1035, 585.0479, 612.8466] +24-11-19 20:29:10 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:10 | D | + error = [5.3946] +24-11-19 20:29:10 | D | - Calibrating model.layers.13.mlp.down_proj.weight +24-11-19 20:29:10 | D | + w: sint8 +24-11-19 20:29:10 | D | + x: None +24-11-19 20:29:10 | D | + y: None +24-11-19 20:29:10 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:10 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:29:10 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:29:10 | D | + finished calculating the original outputs, ram usage: 13.4 +24-11-19 20:29:10 | D | - range ratio = [ 1.0000] +24-11-19 20:29:10 | D | sum error = [ 0.6740] +24-11-19 20:29:10 | D | best error = [ 0.6740] +24-11-19 20:29:11 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:11 | D | sum error = [ 0.6691, 0.6629, 0.6608, 0.6602, 0.6633] +24-11-19 20:29:11 | D | best error = [ 0.6438, 0.6287, 0.6195, 0.6135, 0.6088] +24-11-19 20:29:11 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:11 | D | sum error = [ 0.6687, 0.6793, 0.6909, 0.7106, 0.7331] +24-11-19 20:29:11 | D | best error = [ 0.6061, 0.6038, 0.6023, 0.6015, 0.6010] +24-11-19 20:29:11 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:11 | D | sum error = [ 0.7616, 0.7960, 0.8363, 0.8851, 0.9387] +24-11-19 20:29:11 | D | best error = [ 0.6008, 0.6007, 0.6006, 0.6005, 0.6005] +24-11-19 20:29:11 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:11 | D | sum error = [ 0.9958, 1.0653, 1.1366, 1.2166, 1.3022] +24-11-19 20:29:11 | D | best error = [ 0.6005, 0.6005, 0.6005, 0.6005, 0.6005] +24-11-19 20:29:11 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:11 | D | sum error = [ 1.3973, 1.4980, 1.6096, 1.7231, 1.8464] +24-11-19 20:29:11 | D | best error = [ 0.6005, 0.6005, 0.6005, 0.6005, 0.6005] +24-11-19 20:29:11 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:11 | D | sum error = [ 1.9781, 2.1174, 2.2657, 2.4215, 2.5860] +24-11-19 20:29:11 | D | best error = [ 0.6005, 0.6005, 0.6005, 0.6005, 0.6005] +24-11-19 20:29:11 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:11 | D | sum error = [ 2.7613, 2.9480, 3.1438, 3.3523, 3.5716] +24-11-19 20:29:11 | D | best error = [ 0.6005, 0.6005, 0.6005, 0.6005, 0.6005] +24-11-19 20:29:11 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:11 | D | sum error = [ 3.8032, 4.0480, 4.3053, 4.5764, 4.8624] +24-11-19 20:29:11 | D | best error = [ 0.6005, 0.6005, 0.6005, 0.6005, 0.6005] +24-11-19 20:29:11 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:11 | D | sum error = [ 5.1634, 5.4811, 5.8138, 6.1636, 6.5335] +24-11-19 20:29:11 | D | best error = [ 0.6005, 0.6005, 0.6005, 0.6005, 0.6005] +24-11-19 20:29:11 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:11 | D | sum error = [ 6.9182, 7.3234, 7.7482, 8.1924, 8.6586] +24-11-19 20:29:11 | D | best error = [ 0.6005, 0.6005, 0.6005, 0.6005, 0.6005] +24-11-19 20:29:11 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:11 | D | sum error = [ 9.1462, 9.6556, 10.1867, 10.7442, 11.3256] +24-11-19 20:29:11 | D | best error = [ 0.6005, 0.6005, 0.6005, 0.6005, 0.6005] +24-11-19 20:29:11 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:11 | D | sum error = [ 11.9319, 12.5659, 13.2261, 13.9162, 14.6335] +24-11-19 20:29:11 | D | best error = [ 0.6005, 0.6005, 0.6005, 0.6005, 0.6005] +24-11-19 20:29:11 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:11 | D | sum error = [ 15.3788, 16.1552, 16.9639, 17.8036, 18.6711] +24-11-19 20:29:11 | D | best error = [ 0.6005, 0.6005, 0.6005, 0.6005, 0.6005] +24-11-19 20:29:11 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:11 | D | sum error = [ 19.5735, 20.5134, 21.4880, 22.4973, 23.5405] +24-11-19 20:29:11 | D | best error = [ 0.6005, 0.6005, 0.6005, 0.6005, 0.6005] +24-11-19 20:29:11 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:11 | D | sum error = [ 24.6215, 25.7399, 26.8969, 28.0910, 29.3246] +24-11-19 20:29:11 | D | best error = [ 0.6005, 0.6005, 0.6005, 0.6005, 0.6005] +24-11-19 20:29:11 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:11 | D | sum error = [ 30.5963, 31.9069, 33.2575, 34.6487, 36.0824] +24-11-19 20:29:11 | D | best error = [ 0.6005, 0.6005, 0.6005, 0.6005, 0.6005] +24-11-19 20:29:11 | D | + error = [0.6005] +24-11-19 20:29:12 | D | - Quantizing model.layers.13.self_attn.q_proj.weight +24-11-19 20:29:13 | D | - Quantizing model.layers.13.self_attn.k_proj.weight +24-11-19 20:29:13 | D | - Quantizing model.layers.13.self_attn.v_proj.weight +24-11-19 20:29:14 | D | - Quantizing model.layers.13.self_attn.o_proj.weight +24-11-19 20:29:16 | D | - Quantizing model.layers.13.mlp.up_proj.weight +24-11-19 20:29:17 | D | - Quantizing model.layers.13.mlp.gate_proj.weight +24-11-19 20:29:18 | D | - Quantizing model.layers.13.mlp.down_proj.weight +24-11-19 20:29:29 | D | - Quantizing layer model.layers.14 +24-11-19 20:29:29 | D | - Calibrating model.layers.14.self_attn.q_proj.weight +24-11-19 20:29:29 | D | + w: sint8 +24-11-19 20:29:29 | D | + x: None +24-11-19 20:29:29 | D | + y: None +24-11-19 20:29:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:29:29 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:29:29 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:29:30 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:30 | D | - range ratio = [ 1.0000] +24-11-19 20:29:30 | D | sum error = [ 5.5671] +24-11-19 20:29:30 | D | best error = [ 5.5671] +24-11-19 20:29:43 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:43 | D | sum error = [ 5.3951, 5.3947, 5.5603, 5.5190, 5.6117] +24-11-19 20:29:43 | D | best error = [ 5.3951, 5.3947, 5.3947, 5.3947, 5.3947] +24-11-19 20:29:43 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:43 | D | sum error = [ 5.9153, 5.9822, 6.2173, 6.5811, 6.9722] +24-11-19 20:29:43 | D | best error = [ 5.3947, 5.3947, 5.3947, 5.3947, 5.3947] +24-11-19 20:29:43 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:43 | D | sum error = [ 7.3051, 7.6799, 8.3429, 9.0788, 9.8169] +24-11-19 20:29:43 | D | best error = [ 5.3947, 5.3947, 5.3947, 5.3947, 5.3947] +24-11-19 20:29:43 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:43 | D | sum error = [ 10.1557, 10.9593, 11.9777, 12.7545, 13.8670] +24-11-19 20:29:43 | D | best error = [ 5.3947, 5.3947, 5.3947, 5.3947, 5.3947] +24-11-19 20:29:43 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:43 | D | sum error = [ 15.0053, 16.4137, 17.7825, 19.1009, 20.5568] +24-11-19 20:29:43 | D | best error = [ 5.3947, 5.3947, 5.3947, 5.3947, 5.3947] +24-11-19 20:29:43 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:43 | D | sum error = [ 22.1774, 24.0017, 25.5610, 27.5662, 30.0181] +24-11-19 20:29:43 | D | best error = [ 5.3947, 5.3947, 5.3947, 5.3947, 5.3947] +24-11-19 20:29:43 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:43 | D | sum error = [ 32.3489, 34.6991, 37.1032, 39.9869, 42.6490] +24-11-19 20:29:43 | D | best error = [ 5.3947, 5.3947, 5.3947, 5.3947, 5.3947] +24-11-19 20:29:43 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:43 | D | sum error = [ 45.6179, 49.0289, 52.2442, 55.9914, 59.6373] +24-11-19 20:29:43 | D | best error = [ 5.3947, 5.3947, 5.3947, 5.3947, 5.3947] +24-11-19 20:29:43 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:43 | D | sum error = [ 63.6658, 68.1467, 72.4086, 77.1926, 82.0632] +24-11-19 20:29:43 | D | best error = [ 5.3947, 5.3947, 5.3947, 5.3947, 5.3947] +24-11-19 20:29:43 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:43 | D | sum error = [ 87.1807, 92.3873, 97.9833, 103.7169, 109.8998] +24-11-19 20:29:43 | D | best error = [ 5.3947, 5.3947, 5.3947, 5.3947, 5.3947] +24-11-19 20:29:43 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:43 | D | sum error = [ 116.0366, 122.8450, 129.6623, 136.9186, 144.3969] +24-11-19 20:29:43 | D | best error = [ 5.3947, 5.3947, 5.3947, 5.3947, 5.3947] +24-11-19 20:29:43 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:43 | D | sum error = [ 152.1867, 160.3233, 169.0077, 178.0864, 187.8544] +24-11-19 20:29:43 | D | best error = [ 5.3947, 5.3947, 5.3947, 5.3947, 5.3947] +24-11-19 20:29:43 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:43 | D | sum error = [ 198.1939, 208.9718, 220.5251, 232.5287, 245.3028] +24-11-19 20:29:43 | D | best error = [ 5.3947, 5.3947, 5.3947, 5.3947, 5.3947] +24-11-19 20:29:43 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:43 | D | sum error = [ 258.7580, 273.1598, 288.1899, 304.1647, 321.2902] +24-11-19 20:29:43 | D | best error = [ 5.3947, 5.3947, 5.3947, 5.3947, 5.3947] +24-11-19 20:29:43 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:43 | D | sum error = [ 338.9791, 358.0341, 377.9598, 399.0758, 421.2044] +24-11-19 20:29:43 | D | best error = [ 5.3947, 5.3947, 5.3947, 5.3947, 5.3947] +24-11-19 20:29:43 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:43 | D | sum error = [ 444.3818, 468.7043, 494.2873, 521.0000, 548.7591] +24-11-19 20:29:43 | D | best error = [ 5.3947, 5.3947, 5.3947, 5.3947, 5.3947] +24-11-19 20:29:43 | D | + error = [5.3947] +24-11-19 20:29:44 | D | - Calibrating model.layers.14.self_attn.k_proj.weight +24-11-19 20:29:44 | D | + w: sint8 +24-11-19 20:29:44 | D | + x: None +24-11-19 20:29:44 | D | + y: None +24-11-19 20:29:44 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:29:44 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:29:44 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:29:44 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:44 | D | - range ratio = [ 1.0000] +24-11-19 20:29:44 | D | sum error = [ 4.4161] +24-11-19 20:29:44 | D | best error = [ 4.4161] +24-11-19 20:29:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:59 | D | sum error = [ 4.3556, 4.3787, 4.7589, 4.4366, 5.1184] +24-11-19 20:29:59 | D | best error = [ 4.3556, 4.3556, 4.3556, 4.3556, 4.3556] +24-11-19 20:29:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:59 | D | sum error = [ 4.8836, 4.5704, 5.6149, 5.2659, 5.5914] +24-11-19 20:29:59 | D | best error = [ 4.3556, 4.3556, 4.3556, 4.3556, 4.3556] +24-11-19 20:29:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:59 | D | sum error = [ 6.1290, 6.5032, 6.9280, 8.7753, 8.3329] +24-11-19 20:29:59 | D | best error = [ 4.3556, 4.3556, 4.3556, 4.3556, 4.3556] +24-11-19 20:29:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:59 | D | sum error = [ 8.4291, 9.7477, 10.1560, 11.7612, 12.0074] +24-11-19 20:29:59 | D | best error = [ 4.3556, 4.3556, 4.3556, 4.3556, 4.3556] +24-11-19 20:29:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:59 | D | sum error = [ 13.8692, 14.4413, 15.9417, 17.0913, 18.3798] +24-11-19 20:29:59 | D | best error = [ 4.3556, 4.3556, 4.3556, 4.3556, 4.3556] +24-11-19 20:29:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:59 | D | sum error = [ 19.1213, 20.7727, 23.0779, 25.2052, 26.3008] +24-11-19 20:29:59 | D | best error = [ 4.3556, 4.3556, 4.3556, 4.3556, 4.3556] +24-11-19 20:29:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:59 | D | sum error = [ 28.9315, 31.4113, 33.6052, 36.3912, 39.3783] +24-11-19 20:29:59 | D | best error = [ 4.3556, 4.3556, 4.3556, 4.3556, 4.3556] +24-11-19 20:29:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:59 | D | sum error = [ 42.3799, 44.6866, 48.7160, 51.5880, 55.5900] +24-11-19 20:29:59 | D | best error = [ 4.3556, 4.3556, 4.3556, 4.3556, 4.3556] +24-11-19 20:29:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:59 | D | sum error = [ 59.4659, 64.1781, 68.8774, 73.4902, 79.3125] +24-11-19 20:29:59 | D | best error = [ 4.3556, 4.3556, 4.3556, 4.3556, 4.3556] +24-11-19 20:29:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:59 | D | sum error = [ 84.6233, 90.3955, 96.2559, 102.6637, 109.4240] +24-11-19 20:29:59 | D | best error = [ 4.3556, 4.3556, 4.3556, 4.3556, 4.3556] +24-11-19 20:29:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:59 | D | sum error = [ 116.5625, 124.0487, 132.0330, 139.9713, 148.7226] +24-11-19 20:29:59 | D | best error = [ 4.3556, 4.3556, 4.3556, 4.3556, 4.3556] +24-11-19 20:29:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:59 | D | sum error = [ 158.2937, 167.9515, 178.3314, 189.4050, 201.0238] +24-11-19 20:29:59 | D | best error = [ 4.3556, 4.3556, 4.3556, 4.3556, 4.3556] +24-11-19 20:29:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:59 | D | sum error = [ 212.6944, 224.8003, 237.1472, 250.4953, 263.5127] +24-11-19 20:29:59 | D | best error = [ 4.3556, 4.3556, 4.3556, 4.3556, 4.3556] +24-11-19 20:29:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:59 | D | sum error = [ 277.8753, 293.2819, 308.4165, 325.0122, 342.0005] +24-11-19 20:29:59 | D | best error = [ 4.3556, 4.3556, 4.3556, 4.3556, 4.3556] +24-11-19 20:29:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:59 | D | sum error = [ 358.7856, 377.5072, 396.5424, 416.7089, 438.0102] +24-11-19 20:29:59 | D | best error = [ 4.3556, 4.3556, 4.3556, 4.3556, 4.3556] +24-11-19 20:29:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:59 | D | sum error = [ 459.4037, 482.6549, 506.5716, 531.4438, 557.7593] +24-11-19 20:29:59 | D | best error = [ 4.3556, 4.3556, 4.3556, 4.3556, 4.3556] +24-11-19 20:29:59 | D | + error = [4.3556] +24-11-19 20:30:00 | D | - Calibrating model.layers.14.self_attn.v_proj.weight +24-11-19 20:30:00 | D | + w: sint8 +24-11-19 20:30:00 | D | + x: None +24-11-19 20:30:00 | D | + y: None +24-11-19 20:30:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:00 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:30:00 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:30:00 | D | + finished calculating the original outputs, ram usage: 13.3 +24-11-19 20:30:00 | D | - range ratio = [ 1.0000] +24-11-19 20:30:00 | D | sum error = [ 1.4941] +24-11-19 20:30:00 | D | best error = [ 1.4941] +24-11-19 20:30:00 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:00 | D | sum error = [ 1.4891, 1.4769, 1.4868, 1.5101, 1.5456] +24-11-19 20:30:00 | D | best error = [ 1.3700, 1.3221, 1.3003, 1.2851, 1.2788] +24-11-19 20:30:00 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:00 | D | sum error = [ 1.5668, 1.6263, 1.6987, 1.7781, 1.8660] +24-11-19 20:30:00 | D | best error = [ 1.2744, 1.2731, 1.2724, 1.2723, 1.2722] +24-11-19 20:30:00 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:00 | D | sum error = [ 1.9870, 2.1071, 2.2513, 2.3752, 2.5734] +24-11-19 20:30:00 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:30:00 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:00 | D | sum error = [ 2.7604, 2.9327, 3.1610, 3.4006, 3.6389] +24-11-19 20:30:00 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:30:00 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:00 | D | sum error = [ 3.9003, 4.1942, 4.4885, 4.8094, 5.1388] +24-11-19 20:30:00 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:30:00 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:00 | D | sum error = [ 5.4926, 5.8659, 6.2688, 6.6846, 7.1313] +24-11-19 20:30:00 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:30:00 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:00 | D | sum error = [ 7.6036, 8.0843, 8.6038, 9.1467, 9.7345] +24-11-19 20:30:00 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:30:00 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:00 | D | sum error = [ 10.3430, 10.9813, 11.6502, 12.3595, 13.1073] +24-11-19 20:30:00 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:30:00 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:00 | D | sum error = [ 13.8899, 14.7083, 15.5774, 16.4892, 17.4255] +24-11-19 20:30:00 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:30:00 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:00 | D | sum error = [ 18.4274, 19.4652, 20.5694, 21.7077, 22.9092] +24-11-19 20:30:00 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:30:00 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:00 | D | sum error = [ 24.1582, 25.4723, 26.8392, 28.2720, 29.7671] +24-11-19 20:30:00 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:30:00 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:00 | D | sum error = [ 31.3248, 32.9409, 34.6352, 36.3935, 38.2185] +24-11-19 20:30:00 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:30:00 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:00 | D | sum error = [ 40.1054, 42.0850, 44.1342, 46.2825, 48.5121] +24-11-19 20:30:00 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:30:00 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:00 | D | sum error = [ 50.8351, 53.2304, 55.7146, 58.2850, 60.9376] +24-11-19 20:30:00 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:30:00 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:00 | D | sum error = [ 63.6859, 66.5356, 69.4740, 72.5212, 75.6751] +24-11-19 20:30:00 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:30:00 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:00 | D | sum error = [ 78.9123, 82.2578, 85.6911, 89.2245, 92.8602] +24-11-19 20:30:00 | D | best error = [ 1.2722, 1.2722, 1.2722, 1.2722, 1.2722] +24-11-19 20:30:00 | D | + error = [1.2722] +24-11-19 20:30:00 | D | - Calibrating model.layers.14.self_attn.o_proj.weight +24-11-19 20:30:00 | D | + w: sint8 +24-11-19 20:30:00 | D | + x: None +24-11-19 20:30:00 | D | + y: None +24-11-19 20:30:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:00 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:30:00 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:30:00 | D | + finished calculating the original outputs, ram usage: 13.3 +24-11-19 20:30:00 | D | - range ratio = [ 1.0000] +24-11-19 20:30:00 | D | sum error = [ 0.6814] +24-11-19 20:30:00 | D | best error = [ 0.6814] +24-11-19 20:30:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:01 | D | sum error = [ 0.6728, 0.6722, 0.6699, 0.6736, 0.6789] +24-11-19 20:30:01 | D | best error = [ 0.6233, 0.5987, 0.5839, 0.5744, 0.5674] +24-11-19 20:30:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:01 | D | sum error = [ 0.6881, 0.7001, 0.7138, 0.7333, 0.7589] +24-11-19 20:30:01 | D | best error = [ 0.5631, 0.5598, 0.5578, 0.5565, 0.5558] +24-11-19 20:30:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:01 | D | sum error = [ 0.7888, 0.8182, 0.8608, 0.9040, 0.9496] +24-11-19 20:30:01 | D | best error = [ 0.5554, 0.5550, 0.5548, 0.5547, 0.5547] +24-11-19 20:30:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:01 | D | sum error = [ 0.9995, 1.0547, 1.1155, 1.1834, 1.2500] +24-11-19 20:30:01 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:01 | D | sum error = [ 1.3238, 1.4026, 1.4869, 1.5779, 1.6707] +24-11-19 20:30:01 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:01 | D | sum error = [ 1.7684, 1.8766, 1.9895, 2.1054, 2.2274] +24-11-19 20:30:01 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:01 | D | sum error = [ 2.3598, 2.4980, 2.6418, 2.7925, 2.9504] +24-11-19 20:30:01 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:01 | D | sum error = [ 3.1172, 3.2940, 3.4803, 3.6715, 3.8763] +24-11-19 20:30:01 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:01 | D | sum error = [ 4.0929, 4.3130, 4.5477, 4.7930, 5.0462] +24-11-19 20:30:01 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:01 | D | sum error = [ 5.3170, 5.5951, 5.8887, 6.1931, 6.5098] +24-11-19 20:30:01 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:01 | D | sum error = [ 6.8453, 7.1880, 7.5484, 7.9237, 8.3166] +24-11-19 20:30:01 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:01 | D | sum error = [ 8.7220, 9.1495, 9.5915, 10.0527, 10.5313] +24-11-19 20:30:01 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:01 | D | sum error = [ 11.0302, 11.5512, 12.0893, 12.6496, 13.2303] +24-11-19 20:30:01 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:01 | D | sum error = [ 13.8369, 14.4635, 15.1170, 15.7925, 16.4942] +24-11-19 20:30:01 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:01 | D | sum error = [ 17.2228, 17.9782, 18.7624, 19.5725, 20.4104] +24-11-19 20:30:01 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:01 | D | sum error = [ 21.2801, 22.1790, 23.1101, 24.0740, 25.0720] +24-11-19 20:30:01 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:01 | D | + error = [0.5546] +24-11-19 20:30:01 | D | - Calibrating model.layers.14.mlp.up_proj.weight +24-11-19 20:30:01 | D | + w: sint8 +24-11-19 20:30:01 | D | + x: None +24-11-19 20:30:01 | D | + y: None +24-11-19 20:30:01 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:01 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:30:01 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:30:01 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:30:01 | D | - range ratio = [ 1.0000] +24-11-19 20:30:01 | D | sum error = [ 0.3079] +24-11-19 20:30:01 | D | best error = [ 0.3079] +24-11-19 20:30:02 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:02 | D | sum error = [ 0.3056, 0.3053, 0.3069, 0.3101, 0.3160] +24-11-19 20:30:02 | D | best error = [ 0.2853, 0.2765, 0.2718, 0.2692, 0.2678] +24-11-19 20:30:02 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:02 | D | sum error = [ 0.3234, 0.3342, 0.3478, 0.3639, 0.3843] +24-11-19 20:30:02 | D | best error = [ 0.2671, 0.2668, 0.2667, 0.2667, 0.2667] +24-11-19 20:30:02 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:02 | D | sum error = [ 0.4064, 0.4303, 0.4593, 0.4901, 0.5234] +24-11-19 20:30:02 | D | best error = [ 0.2667, 0.2667, 0.2667, 0.2667, 0.2667] +24-11-19 20:30:02 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:02 | D | sum error = [ 0.5613, 0.6000, 0.6443, 0.6902, 0.7393] +24-11-19 20:30:02 | D | best error = [ 0.2667, 0.2667, 0.2667, 0.2667, 0.2667] +24-11-19 20:30:02 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:02 | D | sum error = [ 0.7923, 0.8482, 0.9079, 0.9720, 1.0401] +24-11-19 20:30:02 | D | best error = [ 0.2667, 0.2667, 0.2667, 0.2667, 0.2667] +24-11-19 20:30:02 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:02 | D | sum error = [ 1.1107, 1.1871, 1.2659, 1.3521, 1.4420] +24-11-19 20:30:02 | D | best error = [ 0.2667, 0.2667, 0.2667, 0.2667, 0.2667] +24-11-19 20:30:02 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:02 | D | sum error = [ 1.5363, 1.6366, 1.7419, 1.8526, 1.9699] +24-11-19 20:30:02 | D | best error = [ 0.2667, 0.2667, 0.2667, 0.2667, 0.2667] +24-11-19 20:30:02 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:02 | D | sum error = [ 2.0931, 2.2228, 2.3588, 2.5022, 2.6526] +24-11-19 20:30:02 | D | best error = [ 0.2667, 0.2667, 0.2667, 0.2667, 0.2667] +24-11-19 20:30:02 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:02 | D | sum error = [ 2.8107, 2.9746, 3.1492, 3.3325, 3.5231] +24-11-19 20:30:02 | D | best error = [ 0.2667, 0.2667, 0.2667, 0.2667, 0.2667] +24-11-19 20:30:02 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:02 | D | sum error = [ 3.7235, 3.9324, 4.1522, 4.3815, 4.6222] +24-11-19 20:30:02 | D | best error = [ 0.2667, 0.2667, 0.2667, 0.2667, 0.2667] +24-11-19 20:30:02 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:02 | D | sum error = [ 4.8724, 5.1355, 5.4076, 5.6941, 5.9925] +24-11-19 20:30:02 | D | best error = [ 0.2667, 0.2667, 0.2667, 0.2667, 0.2667] +24-11-19 20:30:02 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:02 | D | sum error = [ 6.3016, 6.6235, 6.9620, 7.3132, 7.6769] +24-11-19 20:30:02 | D | best error = [ 0.2667, 0.2667, 0.2667, 0.2667, 0.2667] +24-11-19 20:30:02 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:02 | D | sum error = [ 8.0561, 8.4501, 8.8610, 9.2844, 9.7243] +24-11-19 20:30:02 | D | best error = [ 0.2667, 0.2667, 0.2667, 0.2667, 0.2667] +24-11-19 20:30:02 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:02 | D | sum error = [ 10.1822, 10.6588, 11.1482, 11.6546, 12.1768] +24-11-19 20:30:02 | D | best error = [ 0.2667, 0.2667, 0.2667, 0.2667, 0.2667] +24-11-19 20:30:02 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:02 | D | sum error = [ 12.7191, 13.2796, 13.8569, 14.4525, 15.0675] +24-11-19 20:30:02 | D | best error = [ 0.2667, 0.2667, 0.2667, 0.2667, 0.2667] +24-11-19 20:30:02 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:02 | D | sum error = [ 15.6960, 16.3475, 17.0217, 17.7141, 18.4247] +24-11-19 20:30:02 | D | best error = [ 0.2667, 0.2667, 0.2667, 0.2667, 0.2667] +24-11-19 20:30:02 | D | + error = [0.2667] +24-11-19 20:30:02 | D | - Calibrating model.layers.14.mlp.gate_proj.weight +24-11-19 20:30:02 | D | + w: sint8 +24-11-19 20:30:02 | D | + x: None +24-11-19 20:30:02 | D | + y: None +24-11-19 20:30:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:02 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:30:03 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:30:03 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:30:03 | D | - range ratio = [ 1.0000] +24-11-19 20:30:03 | D | sum error = [ 6.6990] +24-11-19 20:30:03 | D | best error = [ 6.6990] +24-11-19 20:30:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:04 | D | sum error = [ 6.6456, 6.6273, 6.6649, 6.7277, 6.8619] +24-11-19 20:30:04 | D | best error = [ 6.1869, 5.9965, 5.9021, 5.8453, 5.8150] +24-11-19 20:30:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:04 | D | sum error = [ 7.0478, 7.2757, 7.5615, 7.9341, 8.3586] +24-11-19 20:30:04 | D | best error = [ 5.8010, 5.7954, 5.7934, 5.7929, 5.7927] +24-11-19 20:30:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:04 | D | sum error = [ 8.8601, 9.4082, 10.0450, 10.7455, 11.4980] +24-11-19 20:30:04 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 20:30:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:04 | D | sum error = [ 12.3331, 13.2528, 14.2244, 15.2834, 16.4137] +24-11-19 20:30:04 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 20:30:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:04 | D | sum error = [ 17.6528, 18.9550, 20.3694, 21.8571, 23.4712] +24-11-19 20:30:04 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 20:30:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:04 | D | sum error = [ 25.1937, 27.0398, 28.9808, 31.0712, 33.3151] +24-11-19 20:30:04 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 20:30:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:04 | D | sum error = [ 35.6810, 38.1959, 40.8973, 43.7556, 46.8122] +24-11-19 20:30:04 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 20:30:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:04 | D | sum error = [ 50.0838, 53.5224, 57.2146, 61.1119, 65.3068] +24-11-19 20:30:04 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 20:30:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:04 | D | sum error = [ 69.7523, 74.4784, 79.4985, 84.8470, 90.5553] +24-11-19 20:30:04 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 20:30:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:04 | D | sum error = [ 96.5880, 103.0219, 109.8263, 117.0315, 124.7123] +24-11-19 20:30:04 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 20:30:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:04 | D | sum error = [ 132.8461, 141.4399, 150.5290, 160.1774, 170.3568] +24-11-19 20:30:04 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 20:30:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:04 | D | sum error = [ 181.1405, 192.5250, 204.5411, 217.1916, 230.5221] +24-11-19 20:30:04 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 20:30:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:04 | D | sum error = [ 244.5726, 259.3092, 274.7898, 291.0241, 308.0611] +24-11-19 20:30:04 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 20:30:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:04 | D | sum error = [ 325.9140, 344.5794, 364.0934, 384.4908, 405.7502] +24-11-19 20:30:04 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 20:30:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:04 | D | sum error = [ 427.9254, 451.0210, 475.0271, 499.9506, 525.8153] +24-11-19 20:30:04 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 20:30:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:04 | D | sum error = [ 552.6273, 580.3753, 609.0615, 638.6912, 669.2386] +24-11-19 20:30:04 | D | best error = [ 5.7927, 5.7927, 5.7927, 5.7927, 5.7927] +24-11-19 20:30:04 | D | + error = [5.7927] +24-11-19 20:30:04 | D | - Calibrating model.layers.14.mlp.down_proj.weight +24-11-19 20:30:04 | D | + w: sint8 +24-11-19 20:30:04 | D | + x: None +24-11-19 20:30:04 | D | + y: None +24-11-19 20:30:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:04 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:04 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:30:04 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:30:04 | D | - range ratio = [ 1.0000] +24-11-19 20:30:04 | D | sum error = [ 0.7285] +24-11-19 20:30:04 | D | best error = [ 0.7285] +24-11-19 20:30:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:06 | D | sum error = [ 0.7218, 0.7166, 0.7152, 0.7131, 0.7158] +24-11-19 20:30:06 | D | best error = [ 0.7005, 0.6867, 0.6781, 0.6715, 0.6665] +24-11-19 20:30:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:06 | D | sum error = [ 0.7237, 0.7339, 0.7488, 0.7699, 0.7964] +24-11-19 20:30:06 | D | best error = [ 0.6634, 0.6611, 0.6594, 0.6585, 0.6581] +24-11-19 20:30:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:06 | D | sum error = [ 0.8267, 0.8651, 0.9111, 0.9622, 1.0211] +24-11-19 20:30:06 | D | best error = [ 0.6578, 0.6577, 0.6576, 0.6575, 0.6575] +24-11-19 20:30:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:06 | D | sum error = [ 1.0856, 1.1580, 1.2371, 1.3244, 1.4195] +24-11-19 20:30:06 | D | best error = [ 0.6575, 0.6575, 0.6575, 0.6575, 0.6575] +24-11-19 20:30:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:06 | D | sum error = [ 1.5212, 1.6315, 1.7487, 1.8732, 2.0074] +24-11-19 20:30:06 | D | best error = [ 0.6575, 0.6575, 0.6575, 0.6575, 0.6575] +24-11-19 20:30:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:06 | D | sum error = [ 2.1505, 2.3023, 2.4639, 2.6345, 2.8138] +24-11-19 20:30:06 | D | best error = [ 0.6575, 0.6575, 0.6575, 0.6575, 0.6575] +24-11-19 20:30:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:06 | D | sum error = [ 3.0053, 3.2067, 3.4206, 3.6472, 3.8861] +24-11-19 20:30:06 | D | best error = [ 0.6575, 0.6575, 0.6575, 0.6575, 0.6575] +24-11-19 20:30:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:06 | D | sum error = [ 4.1371, 4.4036, 4.6859, 4.9811, 5.2933] +24-11-19 20:30:06 | D | best error = [ 0.6575, 0.6575, 0.6575, 0.6575, 0.6575] +24-11-19 20:30:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:06 | D | sum error = [ 5.6192, 5.9648, 6.3269, 6.7084, 7.1076] +24-11-19 20:30:06 | D | best error = [ 0.6575, 0.6575, 0.6575, 0.6575, 0.6575] +24-11-19 20:30:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:06 | D | sum error = [ 7.5277, 7.9677, 8.4280, 8.9122, 9.4164] +24-11-19 20:30:06 | D | best error = [ 0.6575, 0.6575, 0.6575, 0.6575, 0.6575] +24-11-19 20:30:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:06 | D | sum error = [ 9.9466, 10.4997, 11.0773, 11.6820, 12.3117] +24-11-19 20:30:06 | D | best error = [ 0.6575, 0.6575, 0.6575, 0.6575, 0.6575] +24-11-19 20:30:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:06 | D | sum error = [ 12.9702, 13.6542, 14.3677, 15.1103, 15.8836] +24-11-19 20:30:06 | D | best error = [ 0.6575, 0.6575, 0.6575, 0.6575, 0.6575] +24-11-19 20:30:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:06 | D | sum error = [ 16.6882, 17.5239, 18.3937, 19.2968, 20.2340] +24-11-19 20:30:06 | D | best error = [ 0.6575, 0.6575, 0.6575, 0.6575, 0.6575] +24-11-19 20:30:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:06 | D | sum error = [ 21.2034, 22.2108, 23.2559, 24.3395, 25.4622] +24-11-19 20:30:06 | D | best error = [ 0.6575, 0.6575, 0.6575, 0.6575, 0.6575] +24-11-19 20:30:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:06 | D | sum error = [ 26.6235, 27.8226, 29.0629, 30.3453, 31.6694] +24-11-19 20:30:06 | D | best error = [ 0.6575, 0.6575, 0.6575, 0.6575, 0.6575] +24-11-19 20:30:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:06 | D | sum error = [ 33.0371, 34.4475, 35.9008, 37.3969, 38.9392] +24-11-19 20:30:06 | D | best error = [ 0.6575, 0.6575, 0.6575, 0.6575, 0.6575] +24-11-19 20:30:06 | D | + error = [0.6575] +24-11-19 20:30:06 | D | - Quantizing model.layers.14.self_attn.q_proj.weight +24-11-19 20:30:07 | D | - Quantizing model.layers.14.self_attn.k_proj.weight +24-11-19 20:30:07 | D | - Quantizing model.layers.14.self_attn.v_proj.weight +24-11-19 20:30:08 | D | - Quantizing model.layers.14.self_attn.o_proj.weight +24-11-19 20:30:09 | D | - Quantizing model.layers.14.mlp.up_proj.weight +24-11-19 20:30:10 | D | - Quantizing model.layers.14.mlp.gate_proj.weight +24-11-19 20:30:11 | D | - Quantizing model.layers.14.mlp.down_proj.weight +24-11-19 20:30:23 | D | - Quantizing layer model.layers.15 +24-11-19 20:30:23 | D | - Calibrating model.layers.15.self_attn.q_proj.weight +24-11-19 20:30:23 | D | + w: sint8 +24-11-19 20:30:23 | D | + x: None +24-11-19 20:30:23 | D | + y: None +24-11-19 20:30:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:30:23 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:23 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:30:24 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:30:24 | D | - range ratio = [ 1.0000] +24-11-19 20:30:24 | D | sum error = [ 4.4359] +24-11-19 20:30:24 | D | best error = [ 4.4359] +24-11-19 20:30:38 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:38 | D | sum error = [ 4.4305, 4.3390, 4.3832, 4.4464, 4.5151] +24-11-19 20:30:38 | D | best error = [ 4.4305, 4.3390, 4.3390, 4.3390, 4.3390] +24-11-19 20:30:38 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:38 | D | sum error = [ 4.7116, 4.7835, 4.8932, 5.2248, 5.4172] +24-11-19 20:30:38 | D | best error = [ 4.3390, 4.3390, 4.3390, 4.3390, 4.3390] +24-11-19 20:30:38 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:38 | D | sum error = [ 5.8496, 6.2260, 6.6458, 7.1227, 7.7567] +24-11-19 20:30:38 | D | best error = [ 4.3390, 4.3390, 4.3390, 4.3390, 4.3390] +24-11-19 20:30:38 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:38 | D | sum error = [ 8.3279, 9.0503, 9.6514, 10.4642, 11.3565] +24-11-19 20:30:38 | D | best error = [ 4.3390, 4.3390, 4.3390, 4.3390, 4.3390] +24-11-19 20:30:38 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:38 | D | sum error = [ 12.2990, 13.1743, 14.3440, 15.5794, 16.7305] +24-11-19 20:30:38 | D | best error = [ 4.3390, 4.3390, 4.3390, 4.3390, 4.3390] +24-11-19 20:30:38 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:38 | D | sum error = [ 18.2091, 19.5339, 21.1312, 22.6495, 24.3160] +24-11-19 20:30:38 | D | best error = [ 4.3390, 4.3390, 4.3390, 4.3390, 4.3390] +24-11-19 20:30:38 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:38 | D | sum error = [ 26.2221, 28.1088, 30.1658, 32.3820, 34.7464] +24-11-19 20:30:38 | D | best error = [ 4.3390, 4.3390, 4.3390, 4.3390, 4.3390] +24-11-19 20:30:38 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:38 | D | sum error = [ 37.3751, 40.1960, 42.9784, 46.1754, 49.6578] +24-11-19 20:30:38 | D | best error = [ 4.3390, 4.3390, 4.3390, 4.3390, 4.3390] +24-11-19 20:30:38 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:38 | D | sum error = [ 53.1000, 56.9683, 61.1306, 65.6356, 70.2629] +24-11-19 20:30:38 | D | best error = [ 4.3390, 4.3390, 4.3390, 4.3390, 4.3390] +24-11-19 20:30:38 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:38 | D | sum error = [ 75.3097, 80.7775, 86.7530, 92.8339, 99.6895] +24-11-19 20:30:38 | D | best error = [ 4.3390, 4.3390, 4.3390, 4.3390, 4.3390] +24-11-19 20:30:38 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:38 | D | sum error = [ 106.6832, 114.5298, 122.9744, 131.7894, 141.3145] +24-11-19 20:30:38 | D | best error = [ 4.3390, 4.3390, 4.3390, 4.3390, 4.3390] +24-11-19 20:30:38 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:38 | D | sum error = [ 151.2387, 161.9664, 173.2590, 185.6183, 198.6079] +24-11-19 20:30:38 | D | best error = [ 4.3390, 4.3390, 4.3390, 4.3390, 4.3390] +24-11-19 20:30:38 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:38 | D | sum error = [ 212.3823, 227.2161, 243.0493, 259.7714, 277.5955] +24-11-19 20:30:38 | D | best error = [ 4.3390, 4.3390, 4.3390, 4.3390, 4.3390] +24-11-19 20:30:38 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:38 | D | sum error = [ 296.0669, 315.9298, 336.9634, 358.7161, 382.1150] +24-11-19 20:30:38 | D | best error = [ 4.3390, 4.3390, 4.3390, 4.3390, 4.3390] +24-11-19 20:30:38 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:38 | D | sum error = [ 406.6519, 432.3800, 459.2216, 487.3986, 517.0092] +24-11-19 20:30:38 | D | best error = [ 4.3390, 4.3390, 4.3390, 4.3390, 4.3390] +24-11-19 20:30:38 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:38 | D | sum error = [ 547.6404, 579.3774, 612.1077, 645.7108, 680.1586] +24-11-19 20:30:38 | D | best error = [ 4.3390, 4.3390, 4.3390, 4.3390, 4.3390] +24-11-19 20:30:38 | D | + error = [4.3390] +24-11-19 20:30:38 | D | - Calibrating model.layers.15.self_attn.k_proj.weight +24-11-19 20:30:38 | D | + w: sint8 +24-11-19 20:30:38 | D | + x: None +24-11-19 20:30:38 | D | + y: None +24-11-19 20:30:38 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:30:38 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:38 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:30:38 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:30:39 | D | - range ratio = [ 1.0000] +24-11-19 20:30:39 | D | sum error = [ 4.0176] +24-11-19 20:30:39 | D | best error = [ 4.0176] +24-11-19 20:30:54 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:54 | D | sum error = [ 4.0400, 4.6034, 4.2285, 4.0841, 4.3221] +24-11-19 20:30:54 | D | best error = [ 4.0176, 4.0176, 4.0176, 4.0176, 4.0176] +24-11-19 20:30:54 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:54 | D | sum error = [ 4.5613, 4.4100, 4.6255, 5.4054, 5.2350] +24-11-19 20:30:54 | D | best error = [ 4.0176, 4.0176, 4.0176, 4.0176, 4.0176] +24-11-19 20:30:54 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:54 | D | sum error = [ 5.5914, 5.6290, 6.1728, 6.9035, 7.1280] +24-11-19 20:30:54 | D | best error = [ 4.0176, 4.0176, 4.0176, 4.0176, 4.0176] +24-11-19 20:30:54 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:54 | D | sum error = [ 8.1708, 8.3267, 9.2310, 10.1439, 10.2844] +24-11-19 20:30:54 | D | best error = [ 4.0176, 4.0176, 4.0176, 4.0176, 4.0176] +24-11-19 20:30:54 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:54 | D | sum error = [ 11.3155, 11.8202, 12.1922, 14.1041, 14.2309] +24-11-19 20:30:54 | D | best error = [ 4.0176, 4.0176, 4.0176, 4.0176, 4.0176] +24-11-19 20:30:54 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:54 | D | sum error = [ 15.6185, 16.6406, 17.2682, 18.4962, 19.9019] +24-11-19 20:30:54 | D | best error = [ 4.0176, 4.0176, 4.0176, 4.0176, 4.0176] +24-11-19 20:30:54 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:54 | D | sum error = [ 20.8705, 22.4614, 23.8907, 25.7672, 27.7307] +24-11-19 20:30:54 | D | best error = [ 4.0176, 4.0176, 4.0176, 4.0176, 4.0176] +24-11-19 20:30:54 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:54 | D | sum error = [ 29.4183, 31.9418, 34.2943, 36.9139, 39.6592] +24-11-19 20:30:54 | D | best error = [ 4.0176, 4.0176, 4.0176, 4.0176, 4.0176] +24-11-19 20:30:54 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:54 | D | sum error = [ 42.6884, 45.9784, 49.8905, 53.6623, 57.9954] +24-11-19 20:30:54 | D | best error = [ 4.0176, 4.0176, 4.0176, 4.0176, 4.0176] +24-11-19 20:30:54 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:54 | D | sum error = [ 62.5495, 67.4808, 72.8542, 78.6794, 85.1501] +24-11-19 20:30:54 | D | best error = [ 4.0176, 4.0176, 4.0176, 4.0176, 4.0176] +24-11-19 20:30:54 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:54 | D | sum error = [ 92.3057, 99.3176, 106.9464, 115.0979, 124.3855] +24-11-19 20:30:54 | D | best error = [ 4.0176, 4.0176, 4.0176, 4.0176, 4.0176] +24-11-19 20:30:54 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:54 | D | sum error = [ 133.1076, 142.6835, 153.7047, 164.3054, 176.5181] +24-11-19 20:30:54 | D | best error = [ 4.0176, 4.0176, 4.0176, 4.0176, 4.0176] +24-11-19 20:30:54 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:54 | D | sum error = [ 188.8623, 202.7073, 217.0788, 232.4269, 248.7705] +24-11-19 20:30:54 | D | best error = [ 4.0176, 4.0176, 4.0176, 4.0176, 4.0176] +24-11-19 20:30:54 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:54 | D | sum error = [ 265.9846, 284.8989, 304.7871, 326.0489, 349.2340] +24-11-19 20:30:54 | D | best error = [ 4.0176, 4.0176, 4.0176, 4.0176, 4.0176] +24-11-19 20:30:54 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:54 | D | sum error = [ 373.6050, 399.7543, 427.0539, 456.3805, 487.1723] +24-11-19 20:30:54 | D | best error = [ 4.0176, 4.0176, 4.0176, 4.0176, 4.0176] +24-11-19 20:30:54 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:54 | D | sum error = [ 519.9904, 553.5051, 588.9547, 626.1530, 663.3752] +24-11-19 20:30:54 | D | best error = [ 4.0176, 4.0176, 4.0176, 4.0176, 4.0176] +24-11-19 20:30:54 | D | + error = [4.0176] +24-11-19 20:30:54 | D | - Calibrating model.layers.15.self_attn.v_proj.weight +24-11-19 20:30:54 | D | + w: sint8 +24-11-19 20:30:54 | D | + x: None +24-11-19 20:30:54 | D | + y: None +24-11-19 20:30:54 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:54 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:30:54 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:30:55 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:30:55 | D | - range ratio = [ 1.0000] +24-11-19 20:30:55 | D | sum error = [ 1.6270] +24-11-19 20:30:55 | D | best error = [ 1.6270] +24-11-19 20:30:55 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:55 | D | sum error = [ 1.6116, 1.6156, 1.6029, 1.6550, 1.6608] +24-11-19 20:30:55 | D | best error = [ 1.4883, 1.4403, 1.4182, 1.4064, 1.3978] +24-11-19 20:30:55 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:55 | D | sum error = [ 1.7147, 1.7674, 1.8274, 1.9184, 2.0202] +24-11-19 20:30:55 | D | best error = [ 1.3946, 1.3926, 1.3924, 1.3921, 1.3921] +24-11-19 20:30:55 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:55 | D | sum error = [ 2.1382, 2.2736, 2.4186, 2.5748, 2.7641] +24-11-19 20:30:55 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:30:55 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:55 | D | sum error = [ 2.9466, 3.1333, 3.3821, 3.6242, 3.8716] +24-11-19 20:30:55 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:30:55 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:55 | D | sum error = [ 4.1293, 4.4244, 4.7318, 5.0640, 5.4102] +24-11-19 20:30:55 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:30:55 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:55 | D | sum error = [ 5.7768, 6.1667, 6.5723, 7.0212, 7.4690] +24-11-19 20:30:55 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:30:55 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:55 | D | sum error = [ 7.9482, 8.4473, 8.9871, 9.5615, 10.1468] +24-11-19 20:30:55 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:30:55 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:55 | D | sum error = [ 10.7619, 11.4240, 12.1079, 12.8196, 13.5862] +24-11-19 20:30:55 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:30:55 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:55 | D | sum error = [ 14.3775, 15.2068, 16.0879, 16.9972, 17.9612] +24-11-19 20:30:55 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:30:55 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:55 | D | sum error = [ 18.9555, 20.0105, 21.1110, 22.2542, 23.4670] +24-11-19 20:30:55 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:30:55 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:55 | D | sum error = [ 24.7297, 26.0379, 27.4134, 28.8245, 30.3046] +24-11-19 20:30:55 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:30:55 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:55 | D | sum error = [ 31.8425, 33.4489, 35.1212, 36.8538, 38.6463] +24-11-19 20:30:55 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:30:55 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:55 | D | sum error = [ 40.5170, 42.4492, 44.4640, 46.5268, 48.6575] +24-11-19 20:30:55 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:30:55 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:55 | D | sum error = [ 50.8758, 53.1595, 55.5147, 57.9435, 60.4433] +24-11-19 20:30:55 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:30:55 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:55 | D | sum error = [ 63.0292, 65.6859, 68.4212, 71.2319, 74.1322] +24-11-19 20:30:55 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:30:55 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:55 | D | sum error = [ 77.1194, 80.1991, 83.3726, 86.6240, 89.9690] +24-11-19 20:30:55 | D | best error = [ 1.3921, 1.3921, 1.3921, 1.3921, 1.3921] +24-11-19 20:30:55 | D | + error = [1.3921] +24-11-19 20:30:55 | D | - Calibrating model.layers.15.self_attn.o_proj.weight +24-11-19 20:30:55 | D | + w: sint8 +24-11-19 20:30:55 | D | + x: None +24-11-19 20:30:55 | D | + y: None +24-11-19 20:30:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:55 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:30:55 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:30:55 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:30:55 | D | - range ratio = [ 1.0000] +24-11-19 20:30:55 | D | sum error = [ 0.6806] +24-11-19 20:30:55 | D | best error = [ 0.6806] +24-11-19 20:30:56 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:56 | D | sum error = [ 0.6758, 0.6693, 0.6703, 0.6746, 0.6771] +24-11-19 20:30:56 | D | best error = [ 0.6258, 0.6001, 0.5850, 0.5755, 0.5683] +24-11-19 20:30:56 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:56 | D | sum error = [ 0.6902, 0.6962, 0.7136, 0.7314, 0.7520] +24-11-19 20:30:56 | D | best error = [ 0.5632, 0.5589, 0.5557, 0.5533, 0.5516] +24-11-19 20:30:56 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:56 | D | sum error = [ 0.7802, 0.8061, 0.8439, 0.8830, 0.9298] +24-11-19 20:30:56 | D | best error = [ 0.5498, 0.5486, 0.5476, 0.5467, 0.5460] +24-11-19 20:30:56 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:56 | D | sum error = [ 0.9744, 1.0239, 1.0824, 1.1405, 1.2042] +24-11-19 20:30:56 | D | best error = [ 0.5453, 0.5449, 0.5446, 0.5443, 0.5441] +24-11-19 20:30:56 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:56 | D | sum error = [ 1.2729, 1.3533, 1.4273, 1.5110, 1.5987] +24-11-19 20:30:56 | D | best error = [ 0.5439, 0.5437, 0.5436, 0.5436, 0.5435] +24-11-19 20:30:56 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:56 | D | sum error = [ 1.6909, 1.7875, 1.8895, 1.9987, 2.1131] +24-11-19 20:30:56 | D | best error = [ 0.5434, 0.5434, 0.5433, 0.5433, 0.5432] +24-11-19 20:30:56 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:56 | D | sum error = [ 2.2339, 2.3583, 2.4899, 2.6302, 2.7733] +24-11-19 20:30:56 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:30:56 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:56 | D | sum error = [ 2.9256, 3.0846, 3.2514, 3.4292, 3.6125] +24-11-19 20:30:56 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:30:56 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:56 | D | sum error = [ 3.8035, 4.0034, 4.2157, 4.4355, 4.6666] +24-11-19 20:30:56 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:30:56 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:56 | D | sum error = [ 4.9062, 5.1536, 5.4140, 5.6853, 5.9666] +24-11-19 20:30:56 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:30:56 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:56 | D | sum error = [ 6.2587, 6.5654, 6.8824, 7.2130, 7.5559] +24-11-19 20:30:56 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:30:56 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:56 | D | sum error = [ 7.9122, 8.2843, 8.6685, 9.0670, 9.4823] +24-11-19 20:30:56 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:30:56 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:56 | D | sum error = [ 9.9117, 10.3585, 10.8228, 11.3052, 11.8046] +24-11-19 20:30:56 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:30:56 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:56 | D | sum error = [ 12.3232, 12.8636, 13.4248, 14.0060, 14.6092] +24-11-19 20:30:56 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:30:56 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:56 | D | sum error = [ 15.2355, 15.8848, 16.5574, 17.2545, 17.9784] +24-11-19 20:30:56 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:30:56 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:56 | D | sum error = [ 18.7282, 19.5079, 20.3209, 21.1669, 22.0479] +24-11-19 20:30:56 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:30:56 | D | + error = [0.5432] +24-11-19 20:30:56 | D | - Calibrating model.layers.15.mlp.up_proj.weight +24-11-19 20:30:56 | D | + w: sint8 +24-11-19 20:30:56 | D | + x: None +24-11-19 20:30:56 | D | + y: None +24-11-19 20:30:56 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:56 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:30:56 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:30:56 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:30:56 | D | - range ratio = [ 1.0000] +24-11-19 20:30:56 | D | sum error = [ 0.3102] +24-11-19 20:30:56 | D | best error = [ 0.3102] +24-11-19 20:30:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:57 | D | sum error = [ 0.3085, 0.3074, 0.3094, 0.3128, 0.3182] +24-11-19 20:30:57 | D | best error = [ 0.2885, 0.2796, 0.2752, 0.2726, 0.2713] +24-11-19 20:30:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:57 | D | sum error = [ 0.3270, 0.3374, 0.3514, 0.3685, 0.3881] +24-11-19 20:30:57 | D | best error = [ 0.2706, 0.2703, 0.2702, 0.2701, 0.2701] +24-11-19 20:30:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:57 | D | sum error = [ 0.4100, 0.4348, 0.4632, 0.4935, 0.5276] +24-11-19 20:30:57 | D | best error = [ 0.2701, 0.2701, 0.2701, 0.2701, 0.2701] +24-11-19 20:30:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:57 | D | sum error = [ 0.5665, 0.6065, 0.6500, 0.6953, 0.7456] +24-11-19 20:30:57 | D | best error = [ 0.2701, 0.2701, 0.2701, 0.2701, 0.2701] +24-11-19 20:30:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:57 | D | sum error = [ 0.7989, 0.8558, 0.9161, 0.9801, 1.0480] +24-11-19 20:30:57 | D | best error = [ 0.2701, 0.2701, 0.2701, 0.2701, 0.2701] +24-11-19 20:30:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:57 | D | sum error = [ 1.1191, 1.1959, 1.2768, 1.3622, 1.4511] +24-11-19 20:30:57 | D | best error = [ 0.2701, 0.2701, 0.2701, 0.2701, 0.2701] +24-11-19 20:30:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:57 | D | sum error = [ 1.5471, 1.6470, 1.7519, 1.8638, 1.9806] +24-11-19 20:30:57 | D | best error = [ 0.2701, 0.2701, 0.2701, 0.2701, 0.2701] +24-11-19 20:30:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:57 | D | sum error = [ 2.1039, 2.2339, 2.3707, 2.5138, 2.6649] +24-11-19 20:30:57 | D | best error = [ 0.2701, 0.2701, 0.2701, 0.2701, 0.2701] +24-11-19 20:30:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:57 | D | sum error = [ 2.8222, 2.9887, 3.1622, 3.3457, 3.5357] +24-11-19 20:30:57 | D | best error = [ 0.2701, 0.2701, 0.2701, 0.2701, 0.2701] +24-11-19 20:30:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:57 | D | sum error = [ 3.7354, 3.9441, 4.1651, 4.3938, 4.6339] +24-11-19 20:30:57 | D | best error = [ 0.2701, 0.2701, 0.2701, 0.2701, 0.2701] +24-11-19 20:30:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:57 | D | sum error = [ 4.8859, 5.1482, 5.4214, 5.7062, 6.0020] +24-11-19 20:30:57 | D | best error = [ 0.2701, 0.2701, 0.2701, 0.2701, 0.2701] +24-11-19 20:30:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:57 | D | sum error = [ 6.3142, 6.6351, 6.9698, 7.3204, 7.6810] +24-11-19 20:30:57 | D | best error = [ 0.2701, 0.2701, 0.2701, 0.2701, 0.2701] +24-11-19 20:30:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:57 | D | sum error = [ 8.0576, 8.4478, 8.8551, 9.2765, 9.7106] +24-11-19 20:30:57 | D | best error = [ 0.2701, 0.2701, 0.2701, 0.2701, 0.2701] +24-11-19 20:30:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:57 | D | sum error = [ 10.1649, 10.6343, 11.1183, 11.6192, 12.1430] +24-11-19 20:30:57 | D | best error = [ 0.2701, 0.2701, 0.2701, 0.2701, 0.2701] +24-11-19 20:30:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:57 | D | sum error = [ 12.6765, 13.2282, 13.7996, 14.3966, 15.0094] +24-11-19 20:30:57 | D | best error = [ 0.2701, 0.2701, 0.2701, 0.2701, 0.2701] +24-11-19 20:30:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:57 | D | sum error = [ 15.6351, 16.2796, 16.9490, 17.6354, 18.3495] +24-11-19 20:30:57 | D | best error = [ 0.2701, 0.2701, 0.2701, 0.2701, 0.2701] +24-11-19 20:30:57 | D | + error = [0.2701] +24-11-19 20:30:57 | D | - Calibrating model.layers.15.mlp.gate_proj.weight +24-11-19 20:30:57 | D | + w: sint8 +24-11-19 20:30:57 | D | + x: None +24-11-19 20:30:57 | D | + y: None +24-11-19 20:30:57 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:57 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:30:57 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:30:58 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:30:58 | D | - range ratio = [ 1.0000] +24-11-19 20:30:58 | D | sum error = [ 7.1843] +24-11-19 20:30:58 | D | best error = [ 7.1843] +24-11-19 20:30:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:59 | D | sum error = [ 7.1496, 7.1244, 7.1600, 7.2399, 7.3489] +24-11-19 20:30:59 | D | best error = [ 6.6706, 6.4709, 6.3635, 6.3019, 6.2716] +24-11-19 20:30:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:59 | D | sum error = [ 7.5750, 7.8294, 8.1448, 8.5286, 8.9878] +24-11-19 20:30:59 | D | best error = [ 6.2561, 6.2493, 6.2468, 6.2458, 6.2456] +24-11-19 20:30:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:59 | D | sum error = [ 9.5115, 10.1128, 10.7900, 11.5532, 12.3677] +24-11-19 20:30:59 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:30:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:59 | D | sum error = [ 13.2786, 14.2452, 15.3033, 16.4568, 17.6659] +24-11-19 20:30:59 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:30:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:59 | D | sum error = [ 19.0042, 20.4014, 21.9023, 23.5479, 25.2954] +24-11-19 20:30:59 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:30:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:59 | D | sum error = [ 27.1372, 29.1170, 31.2304, 33.4963, 35.8760] +24-11-19 20:30:59 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:30:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:59 | D | sum error = [ 38.4356, 41.1517, 44.0487, 47.1414, 50.4282] +24-11-19 20:30:59 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:30:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:59 | D | sum error = [ 53.9728, 57.6981, 61.6760, 65.8971, 70.4030] +24-11-19 20:30:59 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:30:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:59 | D | sum error = [ 75.1971, 80.2867, 85.7060, 91.4979, 97.6336] +24-11-19 20:30:59 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:30:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:59 | D | sum error = [ 104.1992, 111.1454, 118.5277, 126.3841, 134.6787] +24-11-19 20:30:59 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:30:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:59 | D | sum error = [ 143.4940, 152.8103, 162.6897, 173.1649, 184.2240] +24-11-19 20:30:59 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:30:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:59 | D | sum error = [ 195.9154, 208.3217, 221.3944, 235.1823, 249.6878] +24-11-19 20:30:59 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:30:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:59 | D | sum error = [ 265.0079, 281.0948, 298.0283, 315.7840, 334.4547] +24-11-19 20:30:59 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:30:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:59 | D | sum error = [ 354.0139, 374.4769, 395.8753, 418.2462, 441.5506] +24-11-19 20:30:59 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:30:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:59 | D | sum error = [ 465.8576, 491.1543, 517.4504, 544.7461, 573.0609] +24-11-19 20:30:59 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:30:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:59 | D | sum error = [ 602.3949, 632.7510, 664.1459, 696.5337, 729.9205] +24-11-19 20:30:59 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:30:59 | D | + error = [6.2456] +24-11-19 20:30:59 | D | - Calibrating model.layers.15.mlp.down_proj.weight +24-11-19 20:30:59 | D | + w: sint8 +24-11-19 20:30:59 | D | + x: None +24-11-19 20:30:59 | D | + y: None +24-11-19 20:30:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:59 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:59 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:30:59 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:30:59 | D | - range ratio = [ 1.0000] +24-11-19 20:30:59 | D | sum error = [ 0.8134] +24-11-19 20:30:59 | D | best error = [ 0.8134] +24-11-19 20:31:00 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:00 | D | sum error = [ 0.8061, 0.8004, 0.7966, 0.7998, 0.8003] +24-11-19 20:31:00 | D | best error = [ 0.7828, 0.7671, 0.7566, 0.7493, 0.7441] +24-11-19 20:31:00 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:00 | D | sum error = [ 0.8086, 0.8215, 0.8403, 0.8626, 0.8911] +24-11-19 20:31:00 | D | best error = [ 0.7404, 0.7377, 0.7361, 0.7350, 0.7343] +24-11-19 20:31:00 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:00 | D | sum error = [ 0.9298, 0.9715, 1.0216, 1.0801, 1.1449] +24-11-19 20:31:00 | D | best error = [ 0.7339, 0.7337, 0.7337, 0.7337, 0.7336] +24-11-19 20:31:00 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:00 | D | sum error = [ 1.2176, 1.2986, 1.3854, 1.4828, 1.5877] +24-11-19 20:31:00 | D | best error = [ 0.7336, 0.7336, 0.7336, 0.7336, 0.7336] +24-11-19 20:31:00 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:00 | D | sum error = [ 1.7004, 1.8217, 1.9516, 2.0897, 2.2350] +24-11-19 20:31:00 | D | best error = [ 0.7336, 0.7336, 0.7336, 0.7336, 0.7336] +24-11-19 20:31:00 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:00 | D | sum error = [ 2.3918, 2.5570, 2.7363, 2.9241, 3.1227] +24-11-19 20:31:00 | D | best error = [ 0.7336, 0.7336, 0.7336, 0.7336, 0.7336] +24-11-19 20:31:00 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:00 | D | sum error = [ 3.3329, 3.5565, 3.7893, 4.0394, 4.3011] +24-11-19 20:31:00 | D | best error = [ 0.7336, 0.7336, 0.7336, 0.7336, 0.7336] +24-11-19 20:31:00 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:00 | D | sum error = [ 4.5781, 4.8714, 5.1797, 5.5056, 5.8494] +24-11-19 20:31:00 | D | best error = [ 0.7336, 0.7336, 0.7336, 0.7336, 0.7336] +24-11-19 20:31:00 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:00 | D | sum error = [ 6.2069, 6.5858, 6.9834, 7.4017, 7.8404] +24-11-19 20:31:00 | D | best error = [ 0.7336, 0.7336, 0.7336, 0.7336, 0.7336] +24-11-19 20:31:00 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:00 | D | sum error = [ 8.3012, 8.7849, 9.2915, 9.8239, 10.3810] +24-11-19 20:31:00 | D | best error = [ 0.7336, 0.7336, 0.7336, 0.7336, 0.7336] +24-11-19 20:31:00 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:00 | D | sum error = [ 10.9629, 11.5729, 12.2127, 12.8798, 13.5773] +24-11-19 20:31:00 | D | best error = [ 0.7336, 0.7336, 0.7336, 0.7336, 0.7336] +24-11-19 20:31:00 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:00 | D | sum error = [ 14.3062, 15.0673, 15.8589, 16.6866, 17.5491] +24-11-19 20:31:00 | D | best error = [ 0.7336, 0.7336, 0.7336, 0.7336, 0.7336] +24-11-19 20:31:00 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:00 | D | sum error = [ 18.4485, 19.3837, 20.3553, 21.3679, 22.4217] +24-11-19 20:31:00 | D | best error = [ 0.7336, 0.7336, 0.7336, 0.7336, 0.7336] +24-11-19 20:31:00 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:00 | D | sum error = [ 23.5163, 24.6476, 25.8254, 27.0471, 28.3157] +24-11-19 20:31:00 | D | best error = [ 0.7336, 0.7336, 0.7336, 0.7336, 0.7336] +24-11-19 20:31:00 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:00 | D | sum error = [ 29.6281, 30.9867, 32.3942, 33.8496, 35.3538] +24-11-19 20:31:00 | D | best error = [ 0.7336, 0.7336, 0.7336, 0.7336, 0.7336] +24-11-19 20:31:00 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:00 | D | sum error = [ 36.9082, 38.5124, 40.1676, 41.8753, 43.6364] +24-11-19 20:31:00 | D | best error = [ 0.7336, 0.7336, 0.7336, 0.7336, 0.7336] +24-11-19 20:31:00 | D | + error = [0.7336] +24-11-19 20:31:01 | D | - Quantizing model.layers.15.self_attn.q_proj.weight +24-11-19 20:31:02 | D | - Quantizing model.layers.15.self_attn.k_proj.weight +24-11-19 20:31:03 | D | - Quantizing model.layers.15.self_attn.v_proj.weight +24-11-19 20:31:06 | D | - Quantizing model.layers.15.self_attn.o_proj.weight +24-11-19 20:31:08 | D | - Quantizing model.layers.15.mlp.up_proj.weight +24-11-19 20:31:12 | D | - Quantizing model.layers.15.mlp.gate_proj.weight +24-11-19 20:31:13 | D | - Quantizing model.layers.15.mlp.down_proj.weight +24-11-19 20:31:23 | D | - Quantizing layer model.layers.16 +24-11-19 20:31:23 | D | - Calibrating model.layers.16.self_attn.q_proj.weight +24-11-19 20:31:23 | D | + w: sint8 +24-11-19 20:31:23 | D | + x: None +24-11-19 20:31:23 | D | + y: None +24-11-19 20:31:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:31:23 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:31:23 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:31:23 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:31:24 | D | - range ratio = [ 1.0000] +24-11-19 20:31:24 | D | sum error = [ 4.4229] +24-11-19 20:31:24 | D | best error = [ 4.4229] +24-11-19 20:31:38 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:38 | D | sum error = [ 4.3610, 4.3588, 4.4871, 4.4685, 4.5468] +24-11-19 20:31:38 | D | best error = [ 4.3610, 4.3588, 4.3588, 4.3588, 4.3588] +24-11-19 20:31:38 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:38 | D | sum error = [ 4.7763, 4.9369, 5.0216, 5.3469, 5.6531] +24-11-19 20:31:38 | D | best error = [ 4.3588, 4.3588, 4.3588, 4.3588, 4.3588] +24-11-19 20:31:38 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:38 | D | sum error = [ 5.9908, 6.4369, 6.9839, 7.6117, 8.2388] +24-11-19 20:31:38 | D | best error = [ 4.3588, 4.3588, 4.3588, 4.3588, 4.3588] +24-11-19 20:31:38 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:38 | D | sum error = [ 9.1608, 9.7707, 10.6119, 11.6741, 12.5240] +24-11-19 20:31:38 | D | best error = [ 4.3588, 4.3588, 4.3588, 4.3588, 4.3588] +24-11-19 20:31:38 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:38 | D | sum error = [ 13.6228, 15.0008, 16.3842, 17.8402, 19.4609] +24-11-19 20:31:38 | D | best error = [ 4.3588, 4.3588, 4.3588, 4.3588, 4.3588] +24-11-19 20:31:38 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:38 | D | sum error = [ 21.1715, 23.1804, 25.0839, 27.5654, 30.0544] +24-11-19 20:31:38 | D | best error = [ 4.3588, 4.3588, 4.3588, 4.3588, 4.3588] +24-11-19 20:31:38 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:38 | D | sum error = [ 32.5236, 35.5077, 38.5923, 42.1750, 45.8365] +24-11-19 20:31:38 | D | best error = [ 4.3588, 4.3588, 4.3588, 4.3588, 4.3588] +24-11-19 20:31:38 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:38 | D | sum error = [ 49.5751, 53.6879, 57.9887, 62.6745, 67.6855] +24-11-19 20:31:38 | D | best error = [ 4.3588, 4.3588, 4.3588, 4.3588, 4.3588] +24-11-19 20:31:38 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:38 | D | sum error = [ 72.8934, 78.2706, 84.0005, 90.1899, 97.0862] +24-11-19 20:31:38 | D | best error = [ 4.3588, 4.3588, 4.3588, 4.3588, 4.3588] +24-11-19 20:31:38 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:38 | D | sum error = [ 104.2681, 111.6126, 119.3145, 127.9634, 137.2267] +24-11-19 20:31:38 | D | best error = [ 4.3588, 4.3588, 4.3588, 4.3588, 4.3588] +24-11-19 20:31:38 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:38 | D | sum error = [ 147.0870, 157.1146, 168.1393, 179.7811, 192.0262] +24-11-19 20:31:38 | D | best error = [ 4.3588, 4.3588, 4.3588, 4.3588, 4.3588] +24-11-19 20:31:38 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:38 | D | sum error = [ 205.3755, 219.2953, 233.7929, 249.2948, 265.5583] +24-11-19 20:31:38 | D | best error = [ 4.3588, 4.3588, 4.3588, 4.3588, 4.3588] +24-11-19 20:31:38 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:38 | D | sum error = [ 282.7834, 301.2817, 320.2740, 340.8330, 362.1086] +24-11-19 20:31:38 | D | best error = [ 4.3588, 4.3588, 4.3588, 4.3588, 4.3588] +24-11-19 20:31:38 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:38 | D | sum error = [ 384.8029, 408.3445, 433.1147, 459.3278, 486.7983] +24-11-19 20:31:38 | D | best error = [ 4.3588, 4.3588, 4.3588, 4.3588, 4.3588] +24-11-19 20:31:38 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:38 | D | sum error = [ 515.3485, 545.1499, 576.1553, 608.1935, 641.5432] +24-11-19 20:31:38 | D | best error = [ 4.3588, 4.3588, 4.3588, 4.3588, 4.3588] +24-11-19 20:31:38 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:38 | D | sum error = [ 675.5748, 710.5097, 746.5799, 783.0560, 820.2540] +24-11-19 20:31:38 | D | best error = [ 4.3588, 4.3588, 4.3588, 4.3588, 4.3588] +24-11-19 20:31:38 | D | + error = [4.3588] +24-11-19 20:31:39 | D | - Calibrating model.layers.16.self_attn.k_proj.weight +24-11-19 20:31:39 | D | + w: sint8 +24-11-19 20:31:39 | D | + x: None +24-11-19 20:31:39 | D | + y: None +24-11-19 20:31:39 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:31:39 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:31:39 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:31:39 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:31:40 | D | - range ratio = [ 1.0000] +24-11-19 20:31:40 | D | sum error = [ 4.0230] +24-11-19 20:31:40 | D | best error = [ 4.0230] +24-11-19 20:31:54 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:54 | D | sum error = [ 4.3298, 4.2837, 4.7043, 4.2627, 4.0424] +24-11-19 20:31:54 | D | best error = [ 4.0230, 4.0230, 4.0230, 4.0230, 4.0230] +24-11-19 20:31:54 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:54 | D | sum error = [ 4.8342, 4.6944, 4.3552, 4.5240, 5.7326] +24-11-19 20:31:54 | D | best error = [ 4.0230, 4.0230, 4.0230, 4.0230, 4.0230] +24-11-19 20:31:54 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:54 | D | sum error = [ 5.5479, 5.8308, 5.8495, 6.5169, 6.7298] +24-11-19 20:31:54 | D | best error = [ 4.0230, 4.0230, 4.0230, 4.0230, 4.0230] +24-11-19 20:31:54 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:54 | D | sum error = [ 7.1604, 7.9454, 7.9614, 8.5339, 9.4671] +24-11-19 20:31:54 | D | best error = [ 4.0230, 4.0230, 4.0230, 4.0230, 4.0230] +24-11-19 20:31:54 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:54 | D | sum error = [ 10.0170, 10.6186, 11.9396, 12.5482, 13.2895] +24-11-19 20:31:54 | D | best error = [ 4.0230, 4.0230, 4.0230, 4.0230, 4.0230] +24-11-19 20:31:54 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:54 | D | sum error = [ 14.6410, 15.5842, 17.3601, 18.7877, 20.1315] +24-11-19 20:31:54 | D | best error = [ 4.0230, 4.0230, 4.0230, 4.0230, 4.0230] +24-11-19 20:31:54 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:54 | D | sum error = [ 21.8291, 23.5800, 25.2502, 27.2893, 29.5877] +24-11-19 20:31:54 | D | best error = [ 4.0230, 4.0230, 4.0230, 4.0230, 4.0230] +24-11-19 20:31:54 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:54 | D | sum error = [ 31.6291, 34.7051, 36.5396, 39.9901, 42.5541] +24-11-19 20:31:54 | D | best error = [ 4.0230, 4.0230, 4.0230, 4.0230, 4.0230] +24-11-19 20:31:54 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:54 | D | sum error = [ 45.2160, 48.5467, 51.5645, 55.3611, 59.8771] +24-11-19 20:31:54 | D | best error = [ 4.0230, 4.0230, 4.0230, 4.0230, 4.0230] +24-11-19 20:31:54 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:54 | D | sum error = [ 64.0121, 69.1577, 74.5665, 81.3089, 87.8379] +24-11-19 20:31:54 | D | best error = [ 4.0230, 4.0230, 4.0230, 4.0230, 4.0230] +24-11-19 20:31:54 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:54 | D | sum error = [ 95.7232, 103.7043, 113.0827, 122.2619, 134.0577] +24-11-19 20:31:54 | D | best error = [ 4.0230, 4.0230, 4.0230, 4.0230, 4.0230] +24-11-19 20:31:54 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:54 | D | sum error = [ 146.3287, 159.7241, 173.6123, 187.3122, 203.4101] +24-11-19 20:31:54 | D | best error = [ 4.0230, 4.0230, 4.0230, 4.0230, 4.0230] +24-11-19 20:31:54 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:54 | D | sum error = [ 219.3955, 236.8188, 255.6920, 274.7986, 296.4828] +24-11-19 20:31:54 | D | best error = [ 4.0230, 4.0230, 4.0230, 4.0230, 4.0230] +24-11-19 20:31:54 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:54 | D | sum error = [ 319.1556, 343.6795, 368.9265, 395.7678, 424.4296] +24-11-19 20:31:54 | D | best error = [ 4.0230, 4.0230, 4.0230, 4.0230, 4.0230] +24-11-19 20:31:54 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:54 | D | sum error = [ 452.6506, 485.5516, 516.9665, 551.7762, 588.6916] +24-11-19 20:31:54 | D | best error = [ 4.0230, 4.0230, 4.0230, 4.0230, 4.0230] +24-11-19 20:31:54 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:54 | D | sum error = [ 624.6313, 664.1631, 702.7261, 744.5229, 785.0327] +24-11-19 20:31:54 | D | best error = [ 4.0230, 4.0230, 4.0230, 4.0230, 4.0230] +24-11-19 20:31:54 | D | + error = [4.0230] +24-11-19 20:31:54 | D | - Calibrating model.layers.16.self_attn.v_proj.weight +24-11-19 20:31:54 | D | + w: sint8 +24-11-19 20:31:54 | D | + x: None +24-11-19 20:31:54 | D | + y: None +24-11-19 20:31:54 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:54 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:31:54 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:31:54 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:31:54 | D | - range ratio = [ 1.0000] +24-11-19 20:31:54 | D | sum error = [ 1.4683] +24-11-19 20:31:54 | D | best error = [ 1.4683] +24-11-19 20:31:55 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:55 | D | sum error = [ 1.4495, 1.4512, 1.4632, 1.4704, 1.4986] +24-11-19 20:31:55 | D | best error = [ 1.3527, 1.3115, 1.2900, 1.2770, 1.2714] +24-11-19 20:31:55 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:55 | D | sum error = [ 1.5349, 1.5794, 1.6526, 1.7301, 1.8125] +24-11-19 20:31:55 | D | best error = [ 1.2677, 1.2664, 1.2660, 1.2659, 1.2659] +24-11-19 20:31:55 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:55 | D | sum error = [ 1.9113, 2.0451, 2.1740, 2.3227, 2.4734] +24-11-19 20:31:55 | D | best error = [ 1.2659, 1.2659, 1.2659, 1.2659, 1.2659] +24-11-19 20:31:55 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:55 | D | sum error = [ 2.6628, 2.8524, 3.0448, 3.2737, 3.5263] +24-11-19 20:31:55 | D | best error = [ 1.2659, 1.2659, 1.2659, 1.2659, 1.2659] +24-11-19 20:31:55 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:55 | D | sum error = [ 3.7740, 4.0546, 4.3472, 4.6353, 4.9617] +24-11-19 20:31:55 | D | best error = [ 1.2659, 1.2659, 1.2659, 1.2659, 1.2659] +24-11-19 20:31:55 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:55 | D | sum error = [ 5.3261, 5.6924, 6.0862, 6.4865, 6.9206] +24-11-19 20:31:55 | D | best error = [ 1.2659, 1.2659, 1.2659, 1.2659, 1.2659] +24-11-19 20:31:55 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:55 | D | sum error = [ 7.3765, 7.8677, 8.3754, 8.9043, 9.4811] +24-11-19 20:31:55 | D | best error = [ 1.2659, 1.2659, 1.2659, 1.2659, 1.2659] +24-11-19 20:31:55 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:55 | D | sum error = [ 10.0832, 10.7145, 11.3799, 12.0822, 12.8089] +24-11-19 20:31:55 | D | best error = [ 1.2659, 1.2659, 1.2659, 1.2659, 1.2659] +24-11-19 20:31:55 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:55 | D | sum error = [ 13.5891, 14.4034, 15.2502, 16.1477, 17.0878] +24-11-19 20:31:55 | D | best error = [ 1.2659, 1.2659, 1.2659, 1.2659, 1.2659] +24-11-19 20:31:55 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:55 | D | sum error = [ 18.0694, 19.1067, 20.1733, 21.3054, 22.4923] +24-11-19 20:31:55 | D | best error = [ 1.2659, 1.2659, 1.2659, 1.2659, 1.2659] +24-11-19 20:31:55 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:55 | D | sum error = [ 23.7137, 24.9922, 26.3372, 27.7392, 29.1915] +24-11-19 20:31:55 | D | best error = [ 1.2659, 1.2659, 1.2659, 1.2659, 1.2659] +24-11-19 20:31:55 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:55 | D | sum error = [ 30.7105, 32.2969, 33.9408, 35.6502, 37.4316] +24-11-19 20:31:55 | D | best error = [ 1.2659, 1.2659, 1.2659, 1.2659, 1.2659] +24-11-19 20:31:55 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:55 | D | sum error = [ 39.2884, 41.2215, 43.2287, 45.3215, 47.4851] +24-11-19 20:31:55 | D | best error = [ 1.2659, 1.2659, 1.2659, 1.2659, 1.2659] +24-11-19 20:31:55 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:55 | D | sum error = [ 49.7329, 52.0639, 54.4687, 56.9740, 59.5754] +24-11-19 20:31:55 | D | best error = [ 1.2659, 1.2659, 1.2659, 1.2659, 1.2659] +24-11-19 20:31:55 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:55 | D | sum error = [ 62.2574, 65.0304, 67.8955, 70.8482, 73.8979] +24-11-19 20:31:55 | D | best error = [ 1.2659, 1.2659, 1.2659, 1.2659, 1.2659] +24-11-19 20:31:55 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:55 | D | sum error = [ 77.0449, 80.2904, 83.6491, 87.1057, 90.6611] +24-11-19 20:31:55 | D | best error = [ 1.2659, 1.2659, 1.2659, 1.2659, 1.2659] +24-11-19 20:31:55 | D | + error = [1.2659] +24-11-19 20:31:55 | D | - Calibrating model.layers.16.self_attn.o_proj.weight +24-11-19 20:31:55 | D | + w: sint8 +24-11-19 20:31:55 | D | + x: None +24-11-19 20:31:55 | D | + y: None +24-11-19 20:31:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:55 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:31:55 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:31:55 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:31:55 | D | - range ratio = [ 1.0000] +24-11-19 20:31:55 | D | sum error = [ 0.6277] +24-11-19 20:31:55 | D | best error = [ 0.6277] +24-11-19 20:31:55 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:55 | D | sum error = [ 0.6227, 0.6200, 0.6189, 0.6152, 0.6179] +24-11-19 20:31:55 | D | best error = [ 0.5784, 0.5565, 0.5427, 0.5331, 0.5259] +24-11-19 20:31:55 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:55 | D | sum error = [ 0.6237, 0.6279, 0.6367, 0.6484, 0.6660] +24-11-19 20:31:55 | D | best error = [ 0.5207, 0.5156, 0.5123, 0.5093, 0.5072] +24-11-19 20:31:55 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:55 | D | sum error = [ 0.6839, 0.7058, 0.7315, 0.7626, 0.7972] +24-11-19 20:31:55 | D | best error = [ 0.5050, 0.5036, 0.5023, 0.5011, 0.5003] +24-11-19 20:31:55 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:55 | D | sum error = [ 0.8354, 0.8744, 0.9234, 0.9755, 1.0310] +24-11-19 20:31:55 | D | best error = [ 0.4996, 0.4989, 0.4983, 0.4980, 0.4976] +24-11-19 20:31:55 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:55 | D | sum error = [ 1.0907, 1.1554, 1.2243, 1.3004, 1.3817] +24-11-19 20:31:55 | D | best error = [ 0.4975, 0.4973, 0.4971, 0.4971, 0.4970] +24-11-19 20:31:55 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:55 | D | sum error = [ 1.4691, 1.5601, 1.6581, 1.7620, 1.8733] +24-11-19 20:31:55 | D | best error = [ 0.4970, 0.4969, 0.4969, 0.4968, 0.4968] +24-11-19 20:31:55 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:55 | D | sum error = [ 1.9895, 2.1162, 2.2465, 2.3873, 2.5321] +24-11-19 20:31:55 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:31:55 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:55 | D | sum error = [ 2.6885, 2.8545, 3.0268, 3.2090, 3.4016] +24-11-19 20:31:55 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:31:55 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:55 | D | sum error = [ 3.6054, 3.8184, 4.0475, 4.2828, 4.5335] +24-11-19 20:31:55 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:31:55 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:55 | D | sum error = [ 4.7989, 5.0757, 5.3651, 5.6739, 5.9944] +24-11-19 20:31:55 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:31:55 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:55 | D | sum error = [ 6.3287, 6.6786, 7.0474, 7.4310, 7.8324] +24-11-19 20:31:55 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:31:55 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:55 | D | sum error = [ 8.2517, 8.6894, 9.1472, 9.6252, 10.1228] +24-11-19 20:31:55 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:31:55 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:55 | D | sum error = [ 10.6430, 11.1857, 11.7524, 12.3425, 12.9577] +24-11-19 20:31:55 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:31:55 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:55 | D | sum error = [ 13.5999, 14.2684, 14.9623, 15.6865, 16.4347] +24-11-19 20:31:55 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:31:55 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:55 | D | sum error = [ 17.2125, 18.0220, 18.8633, 19.7362, 20.6420] +24-11-19 20:31:55 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:31:55 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:55 | D | sum error = [ 21.5782, 22.5517, 23.5579, 24.6006, 25.6818] +24-11-19 20:31:55 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:31:55 | D | + error = [0.4968] +24-11-19 20:31:55 | D | - Calibrating model.layers.16.mlp.up_proj.weight +24-11-19 20:31:55 | D | + w: sint8 +24-11-19 20:31:55 | D | + x: None +24-11-19 20:31:55 | D | + y: None +24-11-19 20:31:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:55 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:31:56 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:31:56 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:31:56 | D | - range ratio = [ 1.0000] +24-11-19 20:31:56 | D | sum error = [ 0.3156] +24-11-19 20:31:56 | D | best error = [ 0.3156] +24-11-19 20:31:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:57 | D | sum error = [ 0.3130, 0.3127, 0.3149, 0.3184, 0.3239] +24-11-19 20:31:57 | D | best error = [ 0.2945, 0.2861, 0.2816, 0.2790, 0.2776] +24-11-19 20:31:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:57 | D | sum error = [ 0.3327, 0.3426, 0.3575, 0.3743, 0.3932] +24-11-19 20:31:57 | D | best error = [ 0.2770, 0.2767, 0.2765, 0.2765, 0.2765] +24-11-19 20:31:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:57 | D | sum error = [ 0.4152, 0.4411, 0.4704, 0.5016, 0.5364] +24-11-19 20:31:57 | D | best error = [ 0.2765, 0.2765, 0.2765, 0.2765, 0.2765] +24-11-19 20:31:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:57 | D | sum error = [ 0.5734, 0.6139, 0.6575, 0.7043, 0.7551] +24-11-19 20:31:57 | D | best error = [ 0.2765, 0.2765, 0.2765, 0.2765, 0.2765] +24-11-19 20:31:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:57 | D | sum error = [ 0.8092, 0.8661, 0.9271, 0.9920, 1.0602] +24-11-19 20:31:57 | D | best error = [ 0.2765, 0.2765, 0.2765, 0.2765, 0.2765] +24-11-19 20:31:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:57 | D | sum error = [ 1.1334, 1.2100, 1.2922, 1.3784, 1.4695] +24-11-19 20:31:57 | D | best error = [ 0.2765, 0.2765, 0.2765, 0.2765, 0.2765] +24-11-19 20:31:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:57 | D | sum error = [ 1.5653, 1.6657, 1.7712, 1.8829, 2.0021] +24-11-19 20:31:57 | D | best error = [ 0.2765, 0.2765, 0.2765, 0.2765, 0.2765] +24-11-19 20:31:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:57 | D | sum error = [ 2.1265, 2.2567, 2.3932, 2.5366, 2.6885] +24-11-19 20:31:57 | D | best error = [ 0.2765, 0.2765, 0.2765, 0.2765, 0.2765] +24-11-19 20:31:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:57 | D | sum error = [ 2.8474, 3.0136, 3.1885, 3.3720, 3.5634] +24-11-19 20:31:57 | D | best error = [ 0.2765, 0.2765, 0.2765, 0.2765, 0.2765] +24-11-19 20:31:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:57 | D | sum error = [ 3.7637, 3.9740, 4.1950, 4.4236, 4.6635] +24-11-19 20:31:57 | D | best error = [ 0.2765, 0.2765, 0.2765, 0.2765, 0.2765] +24-11-19 20:31:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:57 | D | sum error = [ 4.9127, 5.1732, 5.4456, 5.7303, 6.0271] +24-11-19 20:31:57 | D | best error = [ 0.2765, 0.2765, 0.2765, 0.2765, 0.2765] +24-11-19 20:31:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:57 | D | sum error = [ 6.3330, 6.6535, 6.9869, 7.3345, 7.6921] +24-11-19 20:31:57 | D | best error = [ 0.2765, 0.2765, 0.2765, 0.2765, 0.2765] +24-11-19 20:31:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:57 | D | sum error = [ 8.0671, 8.4571, 8.8575, 9.2725, 9.7019] +24-11-19 20:31:57 | D | best error = [ 0.2765, 0.2765, 0.2765, 0.2765, 0.2765] +24-11-19 20:31:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:57 | D | sum error = [ 10.1487, 10.6114, 11.0913, 11.5855, 12.0962] +24-11-19 20:31:57 | D | best error = [ 0.2765, 0.2765, 0.2765, 0.2765, 0.2765] +24-11-19 20:31:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:57 | D | sum error = [ 12.6269, 13.1719, 13.7354, 14.3144, 14.9138] +24-11-19 20:31:57 | D | best error = [ 0.2765, 0.2765, 0.2765, 0.2765, 0.2765] +24-11-19 20:31:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:57 | D | sum error = [ 15.5375, 16.1673, 16.8200, 17.4984, 18.1924] +24-11-19 20:31:57 | D | best error = [ 0.2765, 0.2765, 0.2765, 0.2765, 0.2765] +24-11-19 20:31:57 | D | + error = [0.2765] +24-11-19 20:31:57 | D | - Calibrating model.layers.16.mlp.gate_proj.weight +24-11-19 20:31:57 | D | + w: sint8 +24-11-19 20:31:57 | D | + x: None +24-11-19 20:31:57 | D | + y: None +24-11-19 20:31:57 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:57 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:31:57 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:31:57 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:31:57 | D | - range ratio = [ 1.0000] +24-11-19 20:31:57 | D | sum error = [ 7.7745] +24-11-19 20:31:57 | D | best error = [ 7.7745] +24-11-19 20:31:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:59 | D | sum error = [ 7.6983, 7.6780, 7.7147, 7.8140, 7.9644] +24-11-19 20:31:59 | D | best error = [ 7.2201, 7.0129, 6.9001, 6.8396, 6.8057] +24-11-19 20:31:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:59 | D | sum error = [ 8.1479, 8.4546, 8.7964, 9.2110, 9.7068] +24-11-19 20:31:59 | D | best error = [ 6.7887, 6.7826, 6.7797, 6.7788, 6.7787] +24-11-19 20:31:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:59 | D | sum error = [ 10.2835, 10.9298, 11.6473, 12.4713, 13.3163] +24-11-19 20:31:59 | D | best error = [ 6.7786, 6.7786, 6.7786, 6.7786, 6.7786] +24-11-19 20:31:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:59 | D | sum error = [ 14.2945, 15.3545, 16.4903, 17.6989, 19.0174] +24-11-19 20:31:59 | D | best error = [ 6.7786, 6.7786, 6.7786, 6.7786, 6.7786] +24-11-19 20:31:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:59 | D | sum error = [ 20.4310, 21.9271, 23.5461, 25.2744, 27.0734] +24-11-19 20:31:59 | D | best error = [ 6.7786, 6.7786, 6.7786, 6.7786, 6.7786] +24-11-19 20:31:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:59 | D | sum error = [ 29.0324, 31.1105, 33.3447, 35.6836, 38.2195] +24-11-19 20:31:59 | D | best error = [ 6.7786, 6.7786, 6.7786, 6.7786, 6.7786] +24-11-19 20:31:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:59 | D | sum error = [ 40.8822, 43.7112, 46.7525, 49.9641, 53.4076] +24-11-19 20:31:59 | D | best error = [ 6.7786, 6.7786, 6.7786, 6.7786, 6.7786] +24-11-19 20:31:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:59 | D | sum error = [ 57.0391, 60.9150, 65.0295, 69.3948, 74.0132] +24-11-19 20:31:59 | D | best error = [ 6.7786, 6.7786, 6.7786, 6.7786, 6.7786] +24-11-19 20:31:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:59 | D | sum error = [ 78.9331, 84.1717, 89.7129, 95.5802, 101.8138] +24-11-19 20:31:59 | D | best error = [ 6.7786, 6.7786, 6.7786, 6.7786, 6.7786] +24-11-19 20:31:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:59 | D | sum error = [ 108.4328, 115.4395, 122.8709, 130.7499, 139.0927] +24-11-19 20:31:59 | D | best error = [ 6.7786, 6.7786, 6.7786, 6.7786, 6.7786] +24-11-19 20:31:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:59 | D | sum error = [ 147.9050, 157.2436, 167.1299, 177.5719, 188.5841] +24-11-19 20:31:59 | D | best error = [ 6.7786, 6.7786, 6.7786, 6.7786, 6.7786] +24-11-19 20:31:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:59 | D | sum error = [ 200.1961, 212.4633, 225.3888, 238.9821, 253.2945] +24-11-19 20:31:59 | D | best error = [ 6.7786, 6.7786, 6.7786, 6.7786, 6.7786] +24-11-19 20:31:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:59 | D | sum error = [ 268.3478, 284.1640, 300.7407, 318.1490, 336.3923] +24-11-19 20:31:59 | D | best error = [ 6.7786, 6.7786, 6.7786, 6.7786, 6.7786] +24-11-19 20:31:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:59 | D | sum error = [ 355.4802, 375.4444, 396.2977, 418.0913, 440.7531] +24-11-19 20:31:59 | D | best error = [ 6.7786, 6.7786, 6.7786, 6.7786, 6.7786] +24-11-19 20:31:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:59 | D | sum error = [ 464.3861, 488.9757, 514.5153, 541.0275, 568.5379] +24-11-19 20:31:59 | D | best error = [ 6.7786, 6.7786, 6.7786, 6.7786, 6.7786] +24-11-19 20:31:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:59 | D | sum error = [ 597.0372, 626.5355, 657.0036, 688.4642, 720.9288] +24-11-19 20:31:59 | D | best error = [ 6.7786, 6.7786, 6.7786, 6.7786, 6.7786] +24-11-19 20:31:59 | D | + error = [6.7786] +24-11-19 20:31:59 | D | - Calibrating model.layers.16.mlp.down_proj.weight +24-11-19 20:31:59 | D | + w: sint8 +24-11-19 20:31:59 | D | + x: None +24-11-19 20:31:59 | D | + y: None +24-11-19 20:31:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:59 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:31:59 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:31:59 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:31:59 | D | - range ratio = [ 1.0000] +24-11-19 20:31:59 | D | sum error = [ 0.8450] +24-11-19 20:31:59 | D | best error = [ 0.8450] +24-11-19 20:32:00 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:00 | D | sum error = [ 0.8365, 0.8306, 0.8280, 0.8269, 0.8292] +24-11-19 20:32:00 | D | best error = [ 0.8098, 0.7925, 0.7818, 0.7735, 0.7681] +24-11-19 20:32:00 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:00 | D | sum error = [ 0.8352, 0.8470, 0.8621, 0.8825, 0.9120] +24-11-19 20:32:00 | D | best error = [ 0.7638, 0.7610, 0.7589, 0.7577, 0.7569] +24-11-19 20:32:00 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:00 | D | sum error = [ 0.9448, 0.9859, 1.0331, 1.0905, 1.1526] +24-11-19 20:32:00 | D | best error = [ 0.7565, 0.7562, 0.7561, 0.7561, 0.7560] +24-11-19 20:32:00 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:00 | D | sum error = [ 1.2243, 1.3033, 1.3893, 1.4846, 1.5862] +24-11-19 20:32:00 | D | best error = [ 0.7560, 0.7560, 0.7560, 0.7560, 0.7560] +24-11-19 20:32:00 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:00 | D | sum error = [ 1.6989, 1.8209, 1.9484, 2.0890, 2.2355] +24-11-19 20:32:00 | D | best error = [ 0.7560, 0.7560, 0.7560, 0.7560, 0.7560] +24-11-19 20:32:00 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:00 | D | sum error = [ 2.3932, 2.5632, 2.7420, 2.9315, 3.1341] +24-11-19 20:32:00 | D | best error = [ 0.7560, 0.7560, 0.7560, 0.7560, 0.7560] +24-11-19 20:32:00 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:00 | D | sum error = [ 3.3518, 3.5779, 3.8189, 4.0735, 4.3419] +24-11-19 20:32:00 | D | best error = [ 0.7560, 0.7560, 0.7560, 0.7560, 0.7560] +24-11-19 20:32:00 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:00 | D | sum error = [ 4.6280, 4.9305, 5.2510, 5.5861, 5.9430] +24-11-19 20:32:00 | D | best error = [ 0.7560, 0.7560, 0.7560, 0.7560, 0.7560] +24-11-19 20:32:00 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:00 | D | sum error = [ 6.3173, 6.7123, 7.1271, 7.5627, 8.0240] +24-11-19 20:32:00 | D | best error = [ 0.7560, 0.7560, 0.7560, 0.7560, 0.7560] +24-11-19 20:32:00 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:00 | D | sum error = [ 8.5041, 9.0108, 9.5437, 10.1002, 10.6853] +24-11-19 20:32:00 | D | best error = [ 0.7560, 0.7560, 0.7560, 0.7560, 0.7560] +24-11-19 20:32:00 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:00 | D | sum error = [ 11.2978, 11.9396, 12.6110, 13.3120, 14.0465] +24-11-19 20:32:00 | D | best error = [ 0.7560, 0.7560, 0.7560, 0.7560, 0.7560] +24-11-19 20:32:00 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:00 | D | sum error = [ 14.8123, 15.6126, 16.4476, 17.3182, 18.2259] +24-11-19 20:32:00 | D | best error = [ 0.7560, 0.7560, 0.7560, 0.7560, 0.7560] +24-11-19 20:32:00 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:00 | D | sum error = [ 19.1732, 20.1595, 21.1852, 22.2509, 23.3623] +24-11-19 20:32:00 | D | best error = [ 0.7560, 0.7560, 0.7560, 0.7560, 0.7560] +24-11-19 20:32:00 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:00 | D | sum error = [ 24.5156, 25.7104, 26.9502, 28.2364, 29.5727] +24-11-19 20:32:00 | D | best error = [ 0.7560, 0.7560, 0.7560, 0.7560, 0.7560] +24-11-19 20:32:00 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:00 | D | sum error = [ 30.9563, 32.3879, 33.8683, 35.3995, 36.9830] +24-11-19 20:32:00 | D | best error = [ 0.7560, 0.7560, 0.7560, 0.7560, 0.7560] +24-11-19 20:32:00 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:00 | D | sum error = [ 38.6194, 40.3097, 42.0501, 43.8423, 45.6876] +24-11-19 20:32:00 | D | best error = [ 0.7560, 0.7560, 0.7560, 0.7560, 0.7560] +24-11-19 20:32:00 | D | + error = [0.7560] +24-11-19 20:32:00 | D | - Quantizing model.layers.16.self_attn.q_proj.weight +24-11-19 20:32:01 | D | - Quantizing model.layers.16.self_attn.k_proj.weight +24-11-19 20:32:02 | D | - Quantizing model.layers.16.self_attn.v_proj.weight +24-11-19 20:32:03 | D | - Quantizing model.layers.16.self_attn.o_proj.weight +24-11-19 20:32:04 | D | - Quantizing model.layers.16.mlp.up_proj.weight +24-11-19 20:32:05 | D | - Quantizing model.layers.16.mlp.gate_proj.weight +24-11-19 20:32:06 | D | - Quantizing model.layers.16.mlp.down_proj.weight +24-11-19 20:32:17 | D | - Quantizing layer model.layers.17 +24-11-19 20:32:17 | D | - Calibrating model.layers.17.self_attn.q_proj.weight +24-11-19 20:32:17 | D | + w: sint8 +24-11-19 20:32:17 | D | + x: None +24-11-19 20:32:17 | D | + y: None +24-11-19 20:32:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:32:17 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:32:17 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:32:17 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:32:17 | D | - range ratio = [ 1.0000] +24-11-19 20:32:17 | D | sum error = [ 4.1901] +24-11-19 20:32:17 | D | best error = [ 4.1901] +24-11-19 20:32:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:33 | D | sum error = [ 4.1657, 4.0980, 4.1642, 4.2712, 4.3881] +24-11-19 20:32:33 | D | best error = [ 4.1657, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:32:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:33 | D | sum error = [ 4.3717, 4.5436, 4.9277, 4.9935, 5.3752] +24-11-19 20:32:33 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:32:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:33 | D | sum error = [ 5.5704, 5.9190, 6.5256, 6.8834, 7.5518] +24-11-19 20:32:33 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:32:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:33 | D | sum error = [ 8.0905, 8.8550, 9.5549, 10.3515, 11.1039] +24-11-19 20:32:33 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:32:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:33 | D | sum error = [ 11.9308, 13.0203, 14.0243, 15.2803, 16.4688] +24-11-19 20:32:33 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:32:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:33 | D | sum error = [ 17.8982, 19.4027, 21.0365, 22.5864, 24.6312] +24-11-19 20:32:33 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:32:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:33 | D | sum error = [ 26.6676, 28.8585, 31.1725, 33.6643, 36.5419] +24-11-19 20:32:33 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:32:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:33 | D | sum error = [ 39.3138, 42.5654, 45.9092, 49.6779, 53.7772] +24-11-19 20:32:33 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:32:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:33 | D | sum error = [ 58.0179, 62.4869, 67.5072, 72.8163, 78.4500] +24-11-19 20:32:33 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:32:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:33 | D | sum error = [ 84.5728, 90.9100, 97.7139, 105.2647, 113.2925] +24-11-19 20:32:33 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:32:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:33 | D | sum error = [ 121.8765, 131.2760, 141.3882, 152.0298, 163.6511] +24-11-19 20:32:33 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:32:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:33 | D | sum error = [ 175.9320, 189.0032, 203.1411, 218.3123, 234.4844] +24-11-19 20:32:33 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:32:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:33 | D | sum error = [ 252.0276, 270.6611, 290.5994, 311.9265, 335.0945] +24-11-19 20:32:33 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:32:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:33 | D | sum error = [ 359.6782, 386.1978, 414.5975, 444.7910, 476.5506] +24-11-19 20:32:33 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:32:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:33 | D | sum error = [ 510.1363, 545.3183, 582.3443, 621.1390, 661.7575] +24-11-19 20:32:33 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:32:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:33 | D | sum error = [ 703.5538, 746.8582, 791.2645, 836.2424, 881.3555] +24-11-19 20:32:33 | D | best error = [ 4.0980, 4.0980, 4.0980, 4.0980, 4.0980] +24-11-19 20:32:33 | D | + error = [4.0980] +24-11-19 20:32:33 | D | - Calibrating model.layers.17.self_attn.k_proj.weight +24-11-19 20:32:33 | D | + w: sint8 +24-11-19 20:32:33 | D | + x: None +24-11-19 20:32:33 | D | + y: None +24-11-19 20:32:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:32:33 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:32:33 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:32:33 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:32:34 | D | - range ratio = [ 1.0000] +24-11-19 20:32:34 | D | sum error = [ 3.7516] +24-11-19 20:32:34 | D | best error = [ 3.7516] +24-11-19 20:32:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:48 | D | sum error = [ 3.5847, 3.8476, 3.8092, 3.9429, 4.4920] +24-11-19 20:32:48 | D | best error = [ 3.5847, 3.5847, 3.5847, 3.5847, 3.5847] +24-11-19 20:32:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:48 | D | sum error = [ 4.1082, 4.3963, 5.0445, 4.3610, 4.6600] +24-11-19 20:32:48 | D | best error = [ 3.5847, 3.5847, 3.5847, 3.5847, 3.5847] +24-11-19 20:32:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:48 | D | sum error = [ 5.0115, 5.8245, 5.5719, 5.9140, 7.4905] +24-11-19 20:32:48 | D | best error = [ 3.5847, 3.5847, 3.5847, 3.5847, 3.5847] +24-11-19 20:32:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:48 | D | sum error = [ 7.4005, 8.0670, 8.4954, 9.0581, 9.5107] +24-11-19 20:32:48 | D | best error = [ 3.5847, 3.5847, 3.5847, 3.5847, 3.5847] +24-11-19 20:32:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:48 | D | sum error = [ 10.4418, 11.4259, 12.0267, 13.5111, 14.3951] +24-11-19 20:32:48 | D | best error = [ 3.5847, 3.5847, 3.5847, 3.5847, 3.5847] +24-11-19 20:32:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:48 | D | sum error = [ 15.6131, 17.0913, 18.0776, 19.8288, 21.4900] +24-11-19 20:32:48 | D | best error = [ 3.5847, 3.5847, 3.5847, 3.5847, 3.5847] +24-11-19 20:32:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:48 | D | sum error = [ 22.4801, 24.7480, 27.2051, 29.0503, 30.7983] +24-11-19 20:32:48 | D | best error = [ 3.5847, 3.5847, 3.5847, 3.5847, 3.5847] +24-11-19 20:32:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:48 | D | sum error = [ 33.3139, 36.2777, 38.2342, 41.0525, 45.1596] +24-11-19 20:32:48 | D | best error = [ 3.5847, 3.5847, 3.5847, 3.5847, 3.5847] +24-11-19 20:32:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:48 | D | sum error = [ 47.9690, 51.7127, 55.5542, 59.8732, 63.7843] +24-11-19 20:32:48 | D | best error = [ 3.5847, 3.5847, 3.5847, 3.5847, 3.5847] +24-11-19 20:32:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:48 | D | sum error = [ 68.4393, 73.5240, 79.0500, 84.0978, 89.7962] +24-11-19 20:32:48 | D | best error = [ 3.5847, 3.5847, 3.5847, 3.5847, 3.5847] +24-11-19 20:32:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:48 | D | sum error = [ 96.3255, 103.1312, 111.2024, 119.8212, 128.9767] +24-11-19 20:32:48 | D | best error = [ 3.5847, 3.5847, 3.5847, 3.5847, 3.5847] +24-11-19 20:32:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:48 | D | sum error = [ 138.9893, 149.7697, 161.7778, 174.8570, 188.7055] +24-11-19 20:32:48 | D | best error = [ 3.5847, 3.5847, 3.5847, 3.5847, 3.5847] +24-11-19 20:32:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:48 | D | sum error = [ 204.5926, 221.0091, 239.5453, 258.6857, 279.3088] +24-11-19 20:32:48 | D | best error = [ 3.5847, 3.5847, 3.5847, 3.5847, 3.5847] +24-11-19 20:32:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:48 | D | sum error = [ 302.3607, 326.8296, 352.3707, 380.8764, 411.2519] +24-11-19 20:32:48 | D | best error = [ 3.5847, 3.5847, 3.5847, 3.5847, 3.5847] +24-11-19 20:32:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:48 | D | sum error = [ 442.3492, 477.0608, 512.6692, 551.6818, 591.7285] +24-11-19 20:32:48 | D | best error = [ 3.5847, 3.5847, 3.5847, 3.5847, 3.5847] +24-11-19 20:32:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:48 | D | sum error = [ 634.1532, 677.8848, 723.3661, 770.1878, 818.5426] +24-11-19 20:32:48 | D | best error = [ 3.5847, 3.5847, 3.5847, 3.5847, 3.5847] +24-11-19 20:32:48 | D | + error = [3.5847] +24-11-19 20:32:48 | D | - Calibrating model.layers.17.self_attn.v_proj.weight +24-11-19 20:32:48 | D | + w: sint8 +24-11-19 20:32:48 | D | + x: None +24-11-19 20:32:48 | D | + y: None +24-11-19 20:32:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:48 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:32:48 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:32:48 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:32:48 | D | - range ratio = [ 1.0000] +24-11-19 20:32:48 | D | sum error = [ 1.6666] +24-11-19 20:32:48 | D | best error = [ 1.6666] +24-11-19 20:32:49 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:49 | D | sum error = [ 1.6655, 1.6562, 1.6657, 1.6857, 1.7151] +24-11-19 20:32:49 | D | best error = [ 1.5437, 1.4953, 1.4715, 1.4578, 1.4505] +24-11-19 20:32:49 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:49 | D | sum error = [ 1.7561, 1.8143, 1.8830, 1.9787, 2.0719] +24-11-19 20:32:49 | D | best error = [ 1.4458, 1.4436, 1.4432, 1.4431, 1.4430] +24-11-19 20:32:49 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:49 | D | sum error = [ 2.2084, 2.3453, 2.4997, 2.6597, 2.8357] +24-11-19 20:32:49 | D | best error = [ 1.4430, 1.4430, 1.4430, 1.4430, 1.4430] +24-11-19 20:32:49 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:49 | D | sum error = [ 3.0480, 3.2494, 3.4911, 3.7507, 4.0036] +24-11-19 20:32:49 | D | best error = [ 1.4430, 1.4430, 1.4430, 1.4430, 1.4430] +24-11-19 20:32:49 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:49 | D | sum error = [ 4.2904, 4.5823, 4.9049, 5.2598, 5.6157] +24-11-19 20:32:49 | D | best error = [ 1.4430, 1.4430, 1.4430, 1.4430, 1.4430] +24-11-19 20:32:49 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:49 | D | sum error = [ 5.9929, 6.3972, 6.8404, 7.2727, 7.7410] +24-11-19 20:32:49 | D | best error = [ 1.4430, 1.4430, 1.4430, 1.4430, 1.4430] +24-11-19 20:32:49 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:49 | D | sum error = [ 8.2470, 8.7805, 9.3371, 9.9354, 10.5506] +24-11-19 20:32:49 | D | best error = [ 1.4430, 1.4430, 1.4430, 1.4430, 1.4430] +24-11-19 20:32:49 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:49 | D | sum error = [ 11.2154, 11.8872, 12.6129, 13.3552, 14.1363] +24-11-19 20:32:49 | D | best error = [ 1.4430, 1.4430, 1.4430, 1.4430, 1.4430] +24-11-19 20:32:49 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:49 | D | sum error = [ 14.9728, 15.8468, 16.7663, 17.7242, 18.7275] +24-11-19 20:32:49 | D | best error = [ 1.4430, 1.4430, 1.4430, 1.4430, 1.4430] +24-11-19 20:32:49 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:49 | D | sum error = [ 19.7848, 20.8917, 22.0463, 23.2528, 24.5139] +24-11-19 20:32:49 | D | best error = [ 1.4430, 1.4430, 1.4430, 1.4430, 1.4430] +24-11-19 20:32:49 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:49 | D | sum error = [ 25.8142, 27.1850, 28.5965, 30.0768, 31.6222] +24-11-19 20:32:49 | D | best error = [ 1.4430, 1.4430, 1.4430, 1.4430, 1.4430] +24-11-19 20:32:49 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:49 | D | sum error = [ 33.2171, 34.8804, 36.6094, 38.3844, 40.2370] +24-11-19 20:32:49 | D | best error = [ 1.4430, 1.4430, 1.4430, 1.4430, 1.4430] +24-11-19 20:32:49 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:49 | D | sum error = [ 42.1580, 44.1559, 46.2216, 48.3620, 50.5676] +24-11-19 20:32:49 | D | best error = [ 1.4430, 1.4430, 1.4430, 1.4430, 1.4430] +24-11-19 20:32:49 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:49 | D | sum error = [ 52.8626, 55.2300, 57.6865, 60.2423, 62.8705] +24-11-19 20:32:49 | D | best error = [ 1.4430, 1.4430, 1.4430, 1.4430, 1.4430] +24-11-19 20:32:49 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:49 | D | sum error = [ 65.5970, 68.3815, 71.2624, 74.2331, 77.2796] +24-11-19 20:32:49 | D | best error = [ 1.4430, 1.4430, 1.4430, 1.4430, 1.4430] +24-11-19 20:32:49 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:49 | D | sum error = [ 80.4267, 83.6593, 86.9893, 90.4006, 93.9027] +24-11-19 20:32:49 | D | best error = [ 1.4430, 1.4430, 1.4430, 1.4430, 1.4430] +24-11-19 20:32:49 | D | + error = [1.4430] +24-11-19 20:32:49 | D | - Calibrating model.layers.17.self_attn.o_proj.weight +24-11-19 20:32:49 | D | + w: sint8 +24-11-19 20:32:49 | D | + x: None +24-11-19 20:32:49 | D | + y: None +24-11-19 20:32:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:49 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:32:49 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:32:49 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:32:49 | D | - range ratio = [ 1.0000] +24-11-19 20:32:49 | D | sum error = [ 0.6014] +24-11-19 20:32:49 | D | best error = [ 0.6014] +24-11-19 20:32:49 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:49 | D | sum error = [ 0.5980, 0.5916, 0.5862, 0.5857, 0.5806] +24-11-19 20:32:49 | D | best error = [ 0.5533, 0.5311, 0.5165, 0.5056, 0.4978] +24-11-19 20:32:49 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:49 | D | sum error = [ 0.5811, 0.5843, 0.5822, 0.5896, 0.5959] +24-11-19 20:32:49 | D | best error = [ 0.4915, 0.4865, 0.4824, 0.4789, 0.4762] +24-11-19 20:32:49 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:49 | D | sum error = [ 0.6033, 0.6143, 0.6273, 0.6404, 0.6582] +24-11-19 20:32:49 | D | best error = [ 0.4740, 0.4723, 0.4710, 0.4698, 0.4688] +24-11-19 20:32:49 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:49 | D | sum error = [ 0.6765, 0.6999, 0.7225, 0.7510, 0.7822] +24-11-19 20:32:49 | D | best error = [ 0.4678, 0.4670, 0.4663, 0.4658, 0.4654] +24-11-19 20:32:49 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:49 | D | sum error = [ 0.8123, 0.8503, 0.8869, 0.9303, 0.9775] +24-11-19 20:32:49 | D | best error = [ 0.4651, 0.4648, 0.4645, 0.4643, 0.4641] +24-11-19 20:32:49 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:49 | D | sum error = [ 1.0247, 1.0743, 1.1328, 1.1915, 1.2510] +24-11-19 20:32:49 | D | best error = [ 0.4640, 0.4638, 0.4637, 0.4636, 0.4635] +24-11-19 20:32:49 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:49 | D | sum error = [ 1.3212, 1.3887, 1.4616, 1.5411, 1.6244] +24-11-19 20:32:49 | D | best error = [ 0.4635, 0.4635, 0.4634, 0.4634, 0.4634] +24-11-19 20:32:49 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:49 | D | sum error = [ 1.7122, 1.8071, 1.9072, 2.0103, 2.1213] +24-11-19 20:32:49 | D | best error = [ 0.4634, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:32:49 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:49 | D | sum error = [ 2.2380, 2.3622, 2.4938, 2.6331, 2.7806] +24-11-19 20:32:49 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:32:49 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:49 | D | sum error = [ 2.9381, 3.1037, 3.2778, 3.4625, 3.6598] +24-11-19 20:32:49 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:32:49 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:49 | D | sum error = [ 3.8686, 4.0879, 4.3218, 4.5687, 4.8314] +24-11-19 20:32:49 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:32:49 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:49 | D | sum error = [ 5.1075, 5.4032, 5.7120, 6.0388, 6.3840] +24-11-19 20:32:49 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:32:49 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:49 | D | sum error = [ 6.7482, 7.1344, 7.5413, 7.9701, 8.4227] +24-11-19 20:32:49 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:32:49 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:49 | D | sum error = [ 8.8973, 9.3976, 9.9228, 10.4793, 11.0618] +24-11-19 20:32:49 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:32:49 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:49 | D | sum error = [ 11.6756, 12.3181, 12.9948, 13.7043, 14.4471] +24-11-19 20:32:49 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:32:49 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:49 | D | sum error = [ 15.2260, 16.0398, 16.8890, 17.7774, 18.7060] +24-11-19 20:32:49 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:32:49 | D | + error = [0.4633] +24-11-19 20:32:50 | D | - Calibrating model.layers.17.mlp.up_proj.weight +24-11-19 20:32:50 | D | + w: sint8 +24-11-19 20:32:50 | D | + x: None +24-11-19 20:32:50 | D | + y: None +24-11-19 20:32:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:50 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:32:50 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:32:50 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:32:50 | D | - range ratio = [ 1.0000] +24-11-19 20:32:50 | D | sum error = [ 0.3201] +24-11-19 20:32:50 | D | best error = [ 0.3201] +24-11-19 20:32:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:51 | D | sum error = [ 0.3178, 0.3169, 0.3178, 0.3212, 0.3274] +24-11-19 20:32:51 | D | best error = [ 0.2972, 0.2882, 0.2834, 0.2806, 0.2792] +24-11-19 20:32:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:51 | D | sum error = [ 0.3349, 0.3479, 0.3616, 0.3780, 0.3981] +24-11-19 20:32:51 | D | best error = [ 0.2785, 0.2781, 0.2780, 0.2779, 0.2779] +24-11-19 20:32:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:51 | D | sum error = [ 0.4207, 0.4469, 0.4758, 0.5085, 0.5426] +24-11-19 20:32:51 | D | best error = [ 0.2779, 0.2779, 0.2779, 0.2779, 0.2779] +24-11-19 20:32:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:51 | D | sum error = [ 0.5812, 0.6219, 0.6659, 0.7134, 0.7641] +24-11-19 20:32:51 | D | best error = [ 0.2779, 0.2779, 0.2779, 0.2779, 0.2779] +24-11-19 20:32:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:51 | D | sum error = [ 0.8185, 0.8756, 0.9380, 1.0034, 1.0731] +24-11-19 20:32:51 | D | best error = [ 0.2779, 0.2779, 0.2779, 0.2779, 0.2779] +24-11-19 20:32:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:51 | D | sum error = [ 1.1465, 1.2244, 1.3063, 1.3938, 1.4852] +24-11-19 20:32:51 | D | best error = [ 0.2779, 0.2779, 0.2779, 0.2779, 0.2779] +24-11-19 20:32:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:51 | D | sum error = [ 1.5817, 1.6851, 1.7921, 1.9052, 2.0250] +24-11-19 20:32:51 | D | best error = [ 0.2779, 0.2779, 0.2779, 0.2779, 0.2779] +24-11-19 20:32:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:51 | D | sum error = [ 2.1505, 2.2832, 2.4220, 2.5687, 2.7231] +24-11-19 20:32:51 | D | best error = [ 0.2779, 0.2779, 0.2779, 0.2779, 0.2779] +24-11-19 20:32:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:51 | D | sum error = [ 2.8836, 3.0513, 3.2290, 3.4148, 3.6107] +24-11-19 20:32:51 | D | best error = [ 0.2779, 0.2779, 0.2779, 0.2779, 0.2779] +24-11-19 20:32:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:51 | D | sum error = [ 3.8122, 4.0256, 4.2474, 4.4788, 4.7227] +24-11-19 20:32:51 | D | best error = [ 0.2779, 0.2779, 0.2779, 0.2779, 0.2779] +24-11-19 20:32:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:51 | D | sum error = [ 4.9770, 5.2429, 5.5186, 5.8055, 6.1061] +24-11-19 20:32:51 | D | best error = [ 0.2779, 0.2779, 0.2779, 0.2779, 0.2779] +24-11-19 20:32:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:51 | D | sum error = [ 6.4195, 6.7454, 7.0849, 7.4374, 7.8040] +24-11-19 20:32:51 | D | best error = [ 0.2779, 0.2779, 0.2779, 0.2779, 0.2779] +24-11-19 20:32:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:51 | D | sum error = [ 8.1839, 8.5775, 8.9840, 9.4088, 9.8515] +24-11-19 20:32:51 | D | best error = [ 0.2779, 0.2779, 0.2779, 0.2779, 0.2779] +24-11-19 20:32:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:51 | D | sum error = [ 10.3048, 10.7788, 11.2619, 11.7645, 12.2845] +24-11-19 20:32:51 | D | best error = [ 0.2779, 0.2779, 0.2779, 0.2779, 0.2779] +24-11-19 20:32:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:51 | D | sum error = [ 12.8227, 13.3780, 13.9509, 14.5373, 15.1459] +24-11-19 20:32:51 | D | best error = [ 0.2779, 0.2779, 0.2779, 0.2779, 0.2779] +24-11-19 20:32:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:51 | D | sum error = [ 15.7728, 16.4215, 17.0833, 17.7672, 18.4700] +24-11-19 20:32:51 | D | best error = [ 0.2779, 0.2779, 0.2779, 0.2779, 0.2779] +24-11-19 20:32:51 | D | + error = [0.2779] +24-11-19 20:32:51 | D | - Calibrating model.layers.17.mlp.gate_proj.weight +24-11-19 20:32:51 | D | + w: sint8 +24-11-19 20:32:51 | D | + x: None +24-11-19 20:32:51 | D | + y: None +24-11-19 20:32:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:51 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:32:51 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:32:51 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:32:51 | D | - range ratio = [ 1.0000] +24-11-19 20:32:51 | D | sum error = [ 8.1033] +24-11-19 20:32:51 | D | best error = [ 8.1033] +24-11-19 20:32:53 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:53 | D | sum error = [ 8.0412, 8.0431, 8.0745, 8.1551, 8.3145] +24-11-19 20:32:53 | D | best error = [ 7.5235, 7.3032, 7.1846, 7.1154, 7.0805] +24-11-19 20:32:53 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:53 | D | sum error = [ 8.5187, 8.8327, 9.1854, 9.6503, 10.1428] +24-11-19 20:32:53 | D | best error = [ 7.0625, 7.0547, 7.0517, 7.0507, 7.0503] +24-11-19 20:32:53 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:53 | D | sum error = [ 10.7626, 11.4113, 12.1670, 13.0057, 13.9308] +24-11-19 20:32:53 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 20:32:53 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:53 | D | sum error = [ 14.9108, 16.0049, 17.2013, 18.4813, 19.8111] +24-11-19 20:32:53 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 20:32:53 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:53 | D | sum error = [ 21.2876, 22.8188, 24.4993, 26.2933, 28.1669] +24-11-19 20:32:53 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 20:32:53 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:53 | D | sum error = [ 30.2005, 32.3548, 34.6342, 37.0814, 39.6794] +24-11-19 20:32:53 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 20:32:53 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:53 | D | sum error = [ 42.4135, 45.3523, 48.4809, 51.7908, 55.2978] +24-11-19 20:32:53 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 20:32:53 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:53 | D | sum error = [ 59.0563, 62.9979, 67.2518, 71.7080, 76.4460] +24-11-19 20:32:53 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 20:32:53 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:53 | D | sum error = [ 81.4733, 86.8444, 92.5176, 98.5217, 104.8823] +24-11-19 20:32:53 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 20:32:53 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:53 | D | sum error = [ 111.6572, 118.8254, 126.3890, 134.4050, 142.8886] +24-11-19 20:32:53 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 20:32:53 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:53 | D | sum error = [ 151.8750, 161.3684, 171.3973, 181.9954, 193.1650] +24-11-19 20:32:53 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 20:32:53 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:53 | D | sum error = [ 204.9779, 217.4511, 230.5668, 244.3738, 258.8748] +24-11-19 20:32:53 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 20:32:53 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:53 | D | sum error = [ 274.1331, 290.1638, 306.9543, 324.5868, 343.0565] +24-11-19 20:32:53 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 20:32:53 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:53 | D | sum error = [ 362.3304, 382.5088, 403.5792, 425.5579, 448.4554] +24-11-19 20:32:53 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 20:32:53 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:53 | D | sum error = [ 472.3264, 497.1452, 522.9559, 549.7188, 577.4813] +24-11-19 20:32:53 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 20:32:53 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:53 | D | sum error = [ 606.2543, 636.0213, 666.7740, 698.5181, 731.2437] +24-11-19 20:32:53 | D | best error = [ 7.0503, 7.0503, 7.0503, 7.0503, 7.0503] +24-11-19 20:32:53 | D | + error = [7.0503] +24-11-19 20:32:53 | D | - Calibrating model.layers.17.mlp.down_proj.weight +24-11-19 20:32:53 | D | + w: sint8 +24-11-19 20:32:53 | D | + x: None +24-11-19 20:32:53 | D | + y: None +24-11-19 20:32:53 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:53 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:32:53 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:32:53 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:32:53 | D | - range ratio = [ 1.0000] +24-11-19 20:32:53 | D | sum error = [ 0.9371] +24-11-19 20:32:53 | D | best error = [ 0.9371] +24-11-19 20:32:54 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:54 | D | sum error = [ 0.9282, 0.9213, 0.9189, 0.9183, 0.9224] +24-11-19 20:32:54 | D | best error = [ 0.9000, 0.8807, 0.8685, 0.8598, 0.8529] +24-11-19 20:32:54 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:54 | D | sum error = [ 0.9284, 0.9435, 0.9616, 0.9862, 1.0179] +24-11-19 20:32:54 | D | best error = [ 0.8477, 0.8444, 0.8420, 0.8404, 0.8393] +24-11-19 20:32:54 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:54 | D | sum error = [ 1.0570, 1.1047, 1.1589, 1.2230, 1.2979] +24-11-19 20:32:54 | D | best error = [ 0.8385, 0.8381, 0.8379, 0.8378, 0.8378] +24-11-19 20:32:54 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:54 | D | sum error = [ 1.3785, 1.4693, 1.5683, 1.6783, 1.7951] +24-11-19 20:32:54 | D | best error = [ 0.8377, 0.8377, 0.8377, 0.8377, 0.8377] +24-11-19 20:32:54 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:54 | D | sum error = [ 1.9215, 2.0589, 2.2059, 2.3647, 2.5329] +24-11-19 20:32:54 | D | best error = [ 0.8377, 0.8377, 0.8377, 0.8377, 0.8377] +24-11-19 20:32:54 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:54 | D | sum error = [ 2.7159, 2.9047, 3.1061, 3.3265, 3.5541] +24-11-19 20:32:54 | D | best error = [ 0.8377, 0.8377, 0.8377, 0.8377, 0.8377] +24-11-19 20:32:54 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:54 | D | sum error = [ 3.7959, 4.0528, 4.3236, 4.6096, 4.9122] +24-11-19 20:32:54 | D | best error = [ 0.8377, 0.8377, 0.8377, 0.8377, 0.8377] +24-11-19 20:32:54 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:54 | D | sum error = [ 5.2302, 5.5682, 5.9239, 6.2984, 6.6925] +24-11-19 20:32:54 | D | best error = [ 0.8377, 0.8377, 0.8377, 0.8377, 0.8377] +24-11-19 20:32:54 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:54 | D | sum error = [ 7.1085, 7.5465, 8.0056, 8.4893, 8.9971] +24-11-19 20:32:54 | D | best error = [ 0.8377, 0.8377, 0.8377, 0.8377, 0.8377] +24-11-19 20:32:54 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:54 | D | sum error = [ 9.5285, 10.0894, 10.6768, 11.2923, 11.9368] +24-11-19 20:32:54 | D | best error = [ 0.8377, 0.8377, 0.8377, 0.8377, 0.8377] +24-11-19 20:32:54 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:54 | D | sum error = [ 12.6139, 13.3199, 14.0610, 14.8353, 15.6425] +24-11-19 20:32:54 | D | best error = [ 0.8377, 0.8377, 0.8377, 0.8377, 0.8377] +24-11-19 20:32:54 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:54 | D | sum error = [ 16.4857, 17.3690, 18.2902, 19.2507, 20.2529] +24-11-19 20:32:54 | D | best error = [ 0.8377, 0.8377, 0.8377, 0.8377, 0.8377] +24-11-19 20:32:54 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:54 | D | sum error = [ 21.2947, 22.3810, 23.5091, 24.6833, 25.9043] +24-11-19 20:32:54 | D | best error = [ 0.8377, 0.8377, 0.8377, 0.8377, 0.8377] +24-11-19 20:32:54 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:54 | D | sum error = [ 27.1719, 28.4869, 29.8496, 31.2636, 32.7311] +24-11-19 20:32:54 | D | best error = [ 0.8377, 0.8377, 0.8377, 0.8377, 0.8377] +24-11-19 20:32:54 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:54 | D | sum error = [ 34.2510, 35.8209, 37.4456, 39.1250, 40.8611] +24-11-19 20:32:54 | D | best error = [ 0.8377, 0.8377, 0.8377, 0.8377, 0.8377] +24-11-19 20:32:54 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:54 | D | sum error = [ 42.6528, 44.5032, 46.4090, 48.3758, 50.4021] +24-11-19 20:32:54 | D | best error = [ 0.8377, 0.8377, 0.8377, 0.8377, 0.8377] +24-11-19 20:32:54 | D | + error = [0.8377] +24-11-19 20:32:54 | D | - Quantizing model.layers.17.self_attn.q_proj.weight +24-11-19 20:32:55 | D | - Quantizing model.layers.17.self_attn.k_proj.weight +24-11-19 20:32:57 | D | - Quantizing model.layers.17.self_attn.v_proj.weight +24-11-19 20:32:58 | D | - Quantizing model.layers.17.self_attn.o_proj.weight +24-11-19 20:32:59 | D | - Quantizing model.layers.17.mlp.up_proj.weight +24-11-19 20:33:00 | D | - Quantizing model.layers.17.mlp.gate_proj.weight +24-11-19 20:33:01 | D | - Quantizing model.layers.17.mlp.down_proj.weight +24-11-19 20:33:12 | D | - Quantizing layer model.layers.18 +24-11-19 20:33:12 | D | - Calibrating model.layers.18.self_attn.q_proj.weight +24-11-19 20:33:12 | D | + w: sint8 +24-11-19 20:33:12 | D | + x: None +24-11-19 20:33:12 | D | + y: None +24-11-19 20:33:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:33:12 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:33:12 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:33:12 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:33:13 | D | - range ratio = [ 1.0000] +24-11-19 20:33:13 | D | sum error = [ 3.8989] +24-11-19 20:33:13 | D | best error = [ 3.8989] +24-11-19 20:33:27 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:27 | D | sum error = [ 3.9134, 3.8327, 3.8696, 4.1064, 4.0895] +24-11-19 20:33:27 | D | best error = [ 3.8989, 3.8327, 3.8327, 3.8327, 3.8327] +24-11-19 20:33:27 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:27 | D | sum error = [ 4.1754, 4.3264, 4.5898, 4.8002, 5.1109] +24-11-19 20:33:27 | D | best error = [ 3.8327, 3.8327, 3.8327, 3.8327, 3.8327] +24-11-19 20:33:27 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:27 | D | sum error = [ 5.3573, 5.7767, 6.1810, 6.6782, 7.2023] +24-11-19 20:33:27 | D | best error = [ 3.8327, 3.8327, 3.8327, 3.8327, 3.8327] +24-11-19 20:33:27 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:27 | D | sum error = [ 7.7881, 8.3593, 9.0740, 9.9099, 10.6968] +24-11-19 20:33:27 | D | best error = [ 3.8327, 3.8327, 3.8327, 3.8327, 3.8327] +24-11-19 20:33:27 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:27 | D | sum error = [ 11.6442, 12.5667, 13.7780, 14.8449, 16.0896] +24-11-19 20:33:27 | D | best error = [ 3.8327, 3.8327, 3.8327, 3.8327, 3.8327] +24-11-19 20:33:27 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:27 | D | sum error = [ 17.5888, 19.0297, 20.6942, 22.5381, 24.5412] +24-11-19 20:33:27 | D | best error = [ 3.8327, 3.8327, 3.8327, 3.8327, 3.8327] +24-11-19 20:33:27 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:27 | D | sum error = [ 26.5870, 28.7432, 31.3672, 34.0851, 37.2134] +24-11-19 20:33:27 | D | best error = [ 3.8327, 3.8327, 3.8327, 3.8327, 3.8327] +24-11-19 20:33:27 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:27 | D | sum error = [ 40.3257, 43.7644, 47.4582, 51.1638, 55.3868] +24-11-19 20:33:27 | D | best error = [ 3.8327, 3.8327, 3.8327, 3.8327, 3.8327] +24-11-19 20:33:27 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:27 | D | sum error = [ 59.9797, 64.7679, 70.2531, 75.7507, 82.2333] +24-11-19 20:33:27 | D | best error = [ 3.8327, 3.8327, 3.8327, 3.8327, 3.8327] +24-11-19 20:33:27 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:27 | D | sum error = [ 88.5531, 95.8059, 103.2780, 111.2742, 119.9034] +24-11-19 20:33:27 | D | best error = [ 3.8327, 3.8327, 3.8327, 3.8327, 3.8327] +24-11-19 20:33:27 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:27 | D | sum error = [ 129.3645, 139.3685, 150.0633, 161.9138, 174.3729] +24-11-19 20:33:27 | D | best error = [ 3.8327, 3.8327, 3.8327, 3.8327, 3.8327] +24-11-19 20:33:27 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:27 | D | sum error = [ 188.0672, 202.9291, 219.0829, 236.4329, 255.2941] +24-11-19 20:33:27 | D | best error = [ 3.8327, 3.8327, 3.8327, 3.8327, 3.8327] +24-11-19 20:33:27 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:27 | D | sum error = [ 276.1359, 298.5731, 322.8457, 349.7589, 379.5175] +24-11-19 20:33:27 | D | best error = [ 3.8327, 3.8327, 3.8327, 3.8327, 3.8327] +24-11-19 20:33:27 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:27 | D | sum error = [ 411.0979, 446.4721, 484.8588, 527.5636, 574.1472] +24-11-19 20:33:27 | D | best error = [ 3.8327, 3.8327, 3.8327, 3.8327, 3.8327] +24-11-19 20:33:27 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:27 | D | sum error = [ 625.2611, 680.7341, 740.9634, 806.4654, 877.2458] +24-11-19 20:33:27 | D | best error = [ 3.8327, 3.8327, 3.8327, 3.8327, 3.8327] +24-11-19 20:33:27 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:27 | D | sum error = [ 952.6663, 1032.7277, 1117.4498, 1205.3312, 1294.9266] +24-11-19 20:33:27 | D | best error = [ 3.8327, 3.8327, 3.8327, 3.8327, 3.8327] +24-11-19 20:33:27 | D | + error = [3.8327] +24-11-19 20:33:27 | D | - Calibrating model.layers.18.self_attn.k_proj.weight +24-11-19 20:33:27 | D | + w: sint8 +24-11-19 20:33:27 | D | + x: None +24-11-19 20:33:27 | D | + y: None +24-11-19 20:33:27 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:33:27 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:33:27 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:33:27 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:33:28 | D | - range ratio = [ 1.0000] +24-11-19 20:33:28 | D | sum error = [ 4.1840] +24-11-19 20:33:28 | D | best error = [ 4.1840] +24-11-19 20:33:39 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:39 | D | sum error = [ 3.6097, 3.8202, 3.4396, 3.5717, 3.6923] +24-11-19 20:33:39 | D | best error = [ 3.6097, 3.6097, 3.4396, 3.4396, 3.4396] +24-11-19 20:33:39 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:39 | D | sum error = [ 4.4356, 4.2957, 3.9779, 4.1730, 4.5107] +24-11-19 20:33:39 | D | best error = [ 3.4396, 3.4396, 3.4396, 3.4396, 3.4396] +24-11-19 20:33:39 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:39 | D | sum error = [ 5.0290, 5.0570, 5.1900, 5.8950, 5.7826] +24-11-19 20:33:39 | D | best error = [ 3.4396, 3.4396, 3.4396, 3.4396, 3.4396] +24-11-19 20:33:39 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:39 | D | sum error = [ 6.3718, 7.0739, 7.5532, 7.9199, 9.2472] +24-11-19 20:33:39 | D | best error = [ 3.4396, 3.4396, 3.4396, 3.4396, 3.4396] +24-11-19 20:33:39 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:39 | D | sum error = [ 9.8836, 10.3594, 11.3814, 11.7323, 12.9861] +24-11-19 20:33:39 | D | best error = [ 3.4396, 3.4396, 3.4396, 3.4396, 3.4396] +24-11-19 20:33:39 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:39 | D | sum error = [ 13.8975, 15.1094, 16.0712, 17.2327, 18.4189] +24-11-19 20:33:39 | D | best error = [ 3.4396, 3.4396, 3.4396, 3.4396, 3.4396] +24-11-19 20:33:39 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:39 | D | sum error = [ 19.9834, 21.1671, 22.9942, 25.5240, 27.5278] +24-11-19 20:33:39 | D | best error = [ 3.4396, 3.4396, 3.4396, 3.4396, 3.4396] +24-11-19 20:33:39 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:39 | D | sum error = [ 29.7303, 31.9464, 34.2549, 37.0900, 40.4870] +24-11-19 20:33:39 | D | best error = [ 3.4396, 3.4396, 3.4396, 3.4396, 3.4396] +24-11-19 20:33:39 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:39 | D | sum error = [ 43.5441, 46.7358, 50.2826, 54.0005, 58.1702] +24-11-19 20:33:39 | D | best error = [ 3.4396, 3.4396, 3.4396, 3.4396, 3.4396] +24-11-19 20:33:39 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:39 | D | sum error = [ 62.4946, 67.2074, 71.7259, 77.8414, 83.9900] +24-11-19 20:33:39 | D | best error = [ 3.4396, 3.4396, 3.4396, 3.4396, 3.4396] +24-11-19 20:33:39 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:39 | D | sum error = [ 89.9459, 97.2913, 104.4173, 113.4527, 122.0917] +24-11-19 20:33:39 | D | best error = [ 3.4396, 3.4396, 3.4396, 3.4396, 3.4396] +24-11-19 20:33:39 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:39 | D | sum error = [ 132.7228, 143.4436, 155.9655, 168.6353, 182.5516] +24-11-19 20:33:39 | D | best error = [ 3.4396, 3.4396, 3.4396, 3.4396, 3.4396] +24-11-19 20:33:39 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:39 | D | sum error = [ 198.3849, 216.4977, 235.2865, 256.1963, 280.0303] +24-11-19 20:33:39 | D | best error = [ 3.4396, 3.4396, 3.4396, 3.4396, 3.4396] +24-11-19 20:33:39 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:39 | D | sum error = [ 305.9124, 335.0277, 366.8290, 402.5731, 442.9720] +24-11-19 20:33:39 | D | best error = [ 3.4396, 3.4396, 3.4396, 3.4396, 3.4396] +24-11-19 20:33:39 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:39 | D | sum error = [ 488.0283, 536.2873, 590.0023, 649.3988, 715.0943] +24-11-19 20:33:39 | D | best error = [ 3.4396, 3.4396, 3.4396, 3.4396, 3.4396] +24-11-19 20:33:39 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:39 | D | sum error = [ 786.7186, 864.8253, 948.9502, 1038.8174, 1135.5498] +24-11-19 20:33:39 | D | best error = [ 3.4396, 3.4396, 3.4396, 3.4396, 3.4396] +24-11-19 20:33:39 | D | + error = [3.4396] +24-11-19 20:33:40 | D | - Calibrating model.layers.18.self_attn.v_proj.weight +24-11-19 20:33:40 | D | + w: sint8 +24-11-19 20:33:40 | D | + x: None +24-11-19 20:33:40 | D | + y: None +24-11-19 20:33:40 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:40 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:33:40 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:33:40 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:33:40 | D | - range ratio = [ 1.0000] +24-11-19 20:33:40 | D | sum error = [ 1.5763] +24-11-19 20:33:40 | D | best error = [ 1.5763] +24-11-19 20:33:40 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:40 | D | sum error = [ 1.5521, 1.5676, 1.5644, 1.5785, 1.6103] +24-11-19 20:33:40 | D | best error = [ 1.4571, 1.4122, 1.3883, 1.3754, 1.3671] +24-11-19 20:33:40 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:40 | D | sum error = [ 1.6402, 1.7142, 1.7711, 1.8552, 1.9490] +24-11-19 20:33:40 | D | best error = [ 1.3634, 1.3622, 1.3618, 1.3616, 1.3615] +24-11-19 20:33:40 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:40 | D | sum error = [ 2.0697, 2.1986, 2.3500, 2.5075, 2.6849] +24-11-19 20:33:40 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:40 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:40 | D | sum error = [ 2.8744, 3.0856, 3.3000, 3.5296, 3.7866] +24-11-19 20:33:40 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:40 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:40 | D | sum error = [ 4.0744, 4.3588, 4.6779, 4.9985, 5.3415] +24-11-19 20:33:40 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:40 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:40 | D | sum error = [ 5.7191, 6.1082, 6.5259, 6.9654, 7.4333] +24-11-19 20:33:40 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:40 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:40 | D | sum error = [ 7.9338, 8.4679, 8.9969, 9.5805, 10.1707] +24-11-19 20:33:40 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:40 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:40 | D | sum error = [ 10.8143, 11.4665, 12.1676, 12.9110, 13.6725] +24-11-19 20:33:40 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:40 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:40 | D | sum error = [ 14.4917, 15.3349, 16.2349, 17.1733, 18.1453] +24-11-19 20:33:40 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:40 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:40 | D | sum error = [ 19.1744, 20.2641, 21.3818, 22.5695, 23.8087] +24-11-19 20:33:40 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:40 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:40 | D | sum error = [ 25.0938, 26.4395, 27.8540, 29.3364, 30.8827] +24-11-19 20:33:40 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:40 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:40 | D | sum error = [ 32.4828, 34.1578, 35.8991, 37.7085, 39.5935] +24-11-19 20:33:40 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:40 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:40 | D | sum error = [ 41.5581, 43.5938, 45.7139, 47.9125, 50.1971] +24-11-19 20:33:40 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:40 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:40 | D | sum error = [ 52.5766, 55.0438, 57.6055, 60.2512, 63.0132] +24-11-19 20:33:40 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:40 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:40 | D | sum error = [ 65.8645, 68.8151, 71.8672, 75.0196, 78.2802] +24-11-19 20:33:40 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:40 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:40 | D | sum error = [ 81.6542, 85.1194, 88.6896, 92.3605, 96.1334] +24-11-19 20:33:40 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:40 | D | + error = [1.3615] +24-11-19 20:33:40 | D | - Calibrating model.layers.18.self_attn.o_proj.weight +24-11-19 20:33:40 | D | + w: sint8 +24-11-19 20:33:40 | D | + x: None +24-11-19 20:33:40 | D | + y: None +24-11-19 20:33:40 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:40 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:33:40 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:33:40 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:33:40 | D | - range ratio = [ 1.0000] +24-11-19 20:33:40 | D | sum error = [ 0.4923] +24-11-19 20:33:40 | D | best error = [ 0.4923] +24-11-19 20:33:41 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:41 | D | sum error = [ 0.4870, 0.4853, 0.4819, 0.4840, 0.4836] +24-11-19 20:33:41 | D | best error = [ 0.4556, 0.4386, 0.4283, 0.4213, 0.4159] +24-11-19 20:33:41 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:41 | D | sum error = [ 0.4869, 0.4951, 0.5034, 0.5113, 0.5267] +24-11-19 20:33:41 | D | best error = [ 0.4119, 0.4089, 0.4067, 0.4051, 0.4042] +24-11-19 20:33:41 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:41 | D | sum error = [ 0.5403, 0.5584, 0.5780, 0.5977, 0.6243] +24-11-19 20:33:41 | D | best error = [ 0.4034, 0.4029, 0.4025, 0.4023, 0.4021] +24-11-19 20:33:41 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:41 | D | sum error = [ 0.6484, 0.6799, 0.7123, 0.7448, 0.7831] +24-11-19 20:33:41 | D | best error = [ 0.4020, 0.4020, 0.4020, 0.4019, 0.4019] +24-11-19 20:33:41 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:41 | D | sum error = [ 0.8231, 0.8657, 0.9089, 0.9587, 1.0083] +24-11-19 20:33:41 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:33:41 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:41 | D | sum error = [ 1.0613, 1.1190, 1.1800, 1.2434, 1.3119] +24-11-19 20:33:41 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:33:41 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:41 | D | sum error = [ 1.3824, 1.4563, 1.5380, 1.6193, 1.7080] +24-11-19 20:33:41 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:33:41 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:41 | D | sum error = [ 1.7985, 1.8982, 2.0008, 2.1086, 2.2232] +24-11-19 20:33:41 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:33:41 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:41 | D | sum error = [ 2.3412, 2.4684, 2.6020, 2.7450, 2.8929] +24-11-19 20:33:41 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:33:41 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:41 | D | sum error = [ 3.0506, 3.2163, 3.3930, 3.5777, 3.7736] +24-11-19 20:33:41 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:33:41 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:41 | D | sum error = [ 3.9788, 4.1971, 4.4244, 4.6661, 4.9197] +24-11-19 20:33:41 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:33:41 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:41 | D | sum error = [ 5.1896, 5.4731, 5.7719, 6.0865, 6.4181] +24-11-19 20:33:41 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:33:41 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:41 | D | sum error = [ 6.7675, 7.1365, 7.5219, 7.9292, 8.3564] +24-11-19 20:33:41 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:33:41 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:41 | D | sum error = [ 8.8047, 9.2740, 9.7671, 10.2852, 10.8277] +24-11-19 20:33:41 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:33:41 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:41 | D | sum error = [ 11.3959, 11.9895, 12.6094, 13.2566, 13.9331] +24-11-19 20:33:41 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:33:41 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:41 | D | sum error = [ 14.6396, 15.3770, 16.1457, 16.9478, 17.7816] +24-11-19 20:33:41 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:33:41 | D | + error = [0.4019] +24-11-19 20:33:41 | D | - Calibrating model.layers.18.mlp.up_proj.weight +24-11-19 20:33:41 | D | + w: sint8 +24-11-19 20:33:41 | D | + x: None +24-11-19 20:33:41 | D | + y: None +24-11-19 20:33:41 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:41 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:33:41 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:33:41 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:33:41 | D | - range ratio = [ 1.0000] +24-11-19 20:33:41 | D | sum error = [ 0.3286] +24-11-19 20:33:41 | D | best error = [ 0.3286] +24-11-19 20:33:42 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:42 | D | sum error = [ 0.3266, 0.3257, 0.3274, 0.3305, 0.3368] +24-11-19 20:33:42 | D | best error = [ 0.3058, 0.2968, 0.2919, 0.2892, 0.2876] +24-11-19 20:33:42 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:42 | D | sum error = [ 0.3445, 0.3569, 0.3711, 0.3890, 0.4096] +24-11-19 20:33:42 | D | best error = [ 0.2869, 0.2866, 0.2865, 0.2865, 0.2864] +24-11-19 20:33:42 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:42 | D | sum error = [ 0.4329, 0.4599, 0.4889, 0.5230, 0.5596] +24-11-19 20:33:42 | D | best error = [ 0.2864, 0.2864, 0.2864, 0.2864, 0.2864] +24-11-19 20:33:42 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:42 | D | sum error = [ 0.5982, 0.6400, 0.6867, 0.7357, 0.7885] +24-11-19 20:33:42 | D | best error = [ 0.2864, 0.2864, 0.2864, 0.2864, 0.2864] +24-11-19 20:33:42 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:42 | D | sum error = [ 0.8455, 0.9050, 0.9684, 1.0358, 1.1077] +24-11-19 20:33:42 | D | best error = [ 0.2864, 0.2864, 0.2864, 0.2864, 0.2864] +24-11-19 20:33:42 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:42 | D | sum error = [ 1.1839, 1.2645, 1.3486, 1.4388, 1.5335] +24-11-19 20:33:42 | D | best error = [ 0.2864, 0.2864, 0.2864, 0.2864, 0.2864] +24-11-19 20:33:42 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:42 | D | sum error = [ 1.6330, 1.7393, 1.8495, 1.9675, 2.0904] +24-11-19 20:33:42 | D | best error = [ 0.2864, 0.2864, 0.2864, 0.2864, 0.2864] +24-11-19 20:33:42 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:42 | D | sum error = [ 2.2199, 2.3554, 2.4984, 2.6485, 2.8051] +24-11-19 20:33:42 | D | best error = [ 0.2864, 0.2864, 0.2864, 0.2864, 0.2864] +24-11-19 20:33:42 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:42 | D | sum error = [ 2.9704, 3.1429, 3.3240, 3.5149, 3.7133] +24-11-19 20:33:42 | D | best error = [ 0.2864, 0.2864, 0.2864, 0.2864, 0.2864] +24-11-19 20:33:42 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:42 | D | sum error = [ 3.9207, 4.1375, 4.3656, 4.6028, 4.8507] +24-11-19 20:33:42 | D | best error = [ 0.2864, 0.2864, 0.2864, 0.2864, 0.2864] +24-11-19 20:33:42 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:42 | D | sum error = [ 5.1096, 5.3795, 5.6588, 5.9519, 6.2553] +24-11-19 20:33:42 | D | best error = [ 0.2864, 0.2864, 0.2864, 0.2864, 0.2864] +24-11-19 20:33:42 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:42 | D | sum error = [ 6.5724, 6.9025, 7.2422, 7.5983, 7.9684] +24-11-19 20:33:42 | D | best error = [ 0.2864, 0.2864, 0.2864, 0.2864, 0.2864] +24-11-19 20:33:42 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:42 | D | sum error = [ 8.3502, 8.7471, 9.1567, 9.5855, 10.0279] +24-11-19 20:33:42 | D | best error = [ 0.2864, 0.2864, 0.2864, 0.2864, 0.2864] +24-11-19 20:33:42 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:42 | D | sum error = [ 10.4815, 10.9539, 11.4401, 11.9447, 12.4691] +24-11-19 20:33:42 | D | best error = [ 0.2864, 0.2864, 0.2864, 0.2864, 0.2864] +24-11-19 20:33:42 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:42 | D | sum error = [ 13.0080, 13.5596, 14.1301, 14.7196, 15.3328] +24-11-19 20:33:42 | D | best error = [ 0.2864, 0.2864, 0.2864, 0.2864, 0.2864] +24-11-19 20:33:42 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:42 | D | sum error = [ 15.9503, 16.5965, 17.2598, 17.9336, 18.6345] +24-11-19 20:33:42 | D | best error = [ 0.2864, 0.2864, 0.2864, 0.2864, 0.2864] +24-11-19 20:33:42 | D | + error = [0.2864] +24-11-19 20:33:42 | D | - Calibrating model.layers.18.mlp.gate_proj.weight +24-11-19 20:33:42 | D | + w: sint8 +24-11-19 20:33:42 | D | + x: None +24-11-19 20:33:42 | D | + y: None +24-11-19 20:33:42 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:42 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:33:43 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:33:43 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:33:43 | D | - range ratio = [ 1.0000] +24-11-19 20:33:43 | D | sum error = [ 8.4717] +24-11-19 20:33:43 | D | best error = [ 8.4717] +24-11-19 20:33:44 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:44 | D | sum error = [ 8.4295, 8.3632, 8.3983, 8.5100, 8.6758] +24-11-19 20:33:44 | D | best error = [ 7.8766, 7.6394, 7.5129, 7.4430, 7.4052] +24-11-19 20:33:44 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:44 | D | sum error = [ 8.8915, 9.2044, 9.5660, 10.0268, 10.5292] +24-11-19 20:33:44 | D | best error = [ 7.3861, 7.3780, 7.3749, 7.3741, 7.3739] +24-11-19 20:33:44 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:44 | D | sum error = [ 11.1575, 11.8447, 12.6265, 13.4754, 14.4327] +24-11-19 20:33:44 | D | best error = [ 7.3739, 7.3739, 7.3739, 7.3739, 7.3739] +24-11-19 20:33:44 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:44 | D | sum error = [ 15.4653, 16.5582, 17.7398, 19.0474, 20.4238] +24-11-19 20:33:44 | D | best error = [ 7.3739, 7.3739, 7.3739, 7.3739, 7.3739] +24-11-19 20:33:44 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:44 | D | sum error = [ 21.9184, 23.5214, 25.2374, 27.0554, 28.9862] +24-11-19 20:33:44 | D | best error = [ 7.3739, 7.3739, 7.3739, 7.3739, 7.3739] +24-11-19 20:33:44 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:44 | D | sum error = [ 31.0400, 33.2399, 35.5837, 38.0454, 40.6930] +24-11-19 20:33:44 | D | best error = [ 7.3739, 7.3739, 7.3739, 7.3739, 7.3739] +24-11-19 20:33:44 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:44 | D | sum error = [ 43.4830, 46.4613, 49.6086, 52.9476, 56.5112] +24-11-19 20:33:44 | D | best error = [ 7.3739, 7.3739, 7.3739, 7.3739, 7.3739] +24-11-19 20:33:44 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:44 | D | sum error = [ 60.2405, 64.2199, 68.4705, 72.9323, 77.7124] +24-11-19 20:33:44 | D | best error = [ 7.3739, 7.3739, 7.3739, 7.3739, 7.3739] +24-11-19 20:33:44 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:44 | D | sum error = [ 82.7279, 88.0463, 93.6824, 99.6526, 105.9338] +24-11-19 20:33:44 | D | best error = [ 7.3739, 7.3739, 7.3739, 7.3739, 7.3739] +24-11-19 20:33:44 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:44 | D | sum error = [ 112.5564, 119.5945, 127.0276, 134.8454, 143.1172] +24-11-19 20:33:44 | D | best error = [ 7.3739, 7.3739, 7.3739, 7.3739, 7.3739] +24-11-19 20:33:44 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:44 | D | sum error = [ 151.8433, 161.0648, 170.7594, 181.0184, 191.7708] +24-11-19 20:33:44 | D | best error = [ 7.3739, 7.3739, 7.3739, 7.3739, 7.3739] +24-11-19 20:33:44 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:44 | D | sum error = [ 203.1220, 215.0914, 227.6171, 240.8270, 254.6624] +24-11-19 20:33:44 | D | best error = [ 7.3739, 7.3739, 7.3739, 7.3739, 7.3739] +24-11-19 20:33:44 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:44 | D | sum error = [ 269.2392, 284.5200, 300.5111, 317.2526, 334.7693] +24-11-19 20:33:44 | D | best error = [ 7.3739, 7.3739, 7.3739, 7.3739, 7.3739] +24-11-19 20:33:44 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:44 | D | sum error = [ 353.0768, 372.1839, 392.1421, 412.9496, 434.5932] +24-11-19 20:33:44 | D | best error = [ 7.3739, 7.3739, 7.3739, 7.3739, 7.3739] +24-11-19 20:33:44 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:44 | D | sum error = [ 457.1273, 480.5555, 504.8599, 530.0657, 556.1887] +24-11-19 20:33:44 | D | best error = [ 7.3739, 7.3739, 7.3739, 7.3739, 7.3739] +24-11-19 20:33:44 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:44 | D | sum error = [ 583.2314, 611.2155, 640.0905, 669.8846, 700.6264] +24-11-19 20:33:44 | D | best error = [ 7.3739, 7.3739, 7.3739, 7.3739, 7.3739] +24-11-19 20:33:44 | D | + error = [7.3739] +24-11-19 20:33:44 | D | - Calibrating model.layers.18.mlp.down_proj.weight +24-11-19 20:33:44 | D | + w: sint8 +24-11-19 20:33:44 | D | + x: None +24-11-19 20:33:44 | D | + y: None +24-11-19 20:33:44 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:44 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:33:44 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:33:44 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:33:44 | D | - range ratio = [ 1.0000] +24-11-19 20:33:44 | D | sum error = [ 0.9310] +24-11-19 20:33:44 | D | best error = [ 0.9310] +24-11-19 20:33:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:46 | D | sum error = [ 0.9223, 0.9162, 0.9131, 0.9115, 0.9161] +24-11-19 20:33:46 | D | best error = [ 0.8926, 0.8745, 0.8626, 0.8536, 0.8471] +24-11-19 20:33:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:46 | D | sum error = [ 0.9236, 0.9396, 0.9591, 0.9857, 1.0170] +24-11-19 20:33:46 | D | best error = [ 0.8426, 0.8390, 0.8366, 0.8350, 0.8339] +24-11-19 20:33:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:46 | D | sum error = [ 1.0579, 1.1082, 1.1653, 1.2301, 1.3055] +24-11-19 20:33:46 | D | best error = [ 0.8333, 0.8330, 0.8327, 0.8327, 0.8326] +24-11-19 20:33:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:46 | D | sum error = [ 1.3894, 1.4816, 1.5819, 1.6926, 1.8145] +24-11-19 20:33:46 | D | best error = [ 0.8326, 0.8326, 0.8326, 0.8326, 0.8326] +24-11-19 20:33:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:46 | D | sum error = [ 1.9410, 2.0793, 2.2289, 2.3881, 2.5582] +24-11-19 20:33:46 | D | best error = [ 0.8326, 0.8326, 0.8326, 0.8326, 0.8326] +24-11-19 20:33:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:46 | D | sum error = [ 2.7375, 2.9304, 3.1337, 3.3481, 3.5782] +24-11-19 20:33:46 | D | best error = [ 0.8326, 0.8326, 0.8326, 0.8326, 0.8326] +24-11-19 20:33:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:46 | D | sum error = [ 3.8201, 4.0752, 4.3472, 4.6338, 4.9351] +24-11-19 20:33:46 | D | best error = [ 0.8326, 0.8326, 0.8326, 0.8326, 0.8326] +24-11-19 20:33:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:46 | D | sum error = [ 5.2540, 5.5878, 5.9446, 6.3181, 6.7110] +24-11-19 20:33:46 | D | best error = [ 0.8326, 0.8326, 0.8326, 0.8326, 0.8326] +24-11-19 20:33:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:46 | D | sum error = [ 7.1262, 7.5621, 8.0199, 8.5017, 9.0076] +24-11-19 20:33:46 | D | best error = [ 0.8326, 0.8326, 0.8326, 0.8326, 0.8326] +24-11-19 20:33:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:46 | D | sum error = [ 9.5376, 10.0935, 10.6792, 11.2909, 11.9330] +24-11-19 20:33:46 | D | best error = [ 0.8326, 0.8326, 0.8326, 0.8326, 0.8326] +24-11-19 20:33:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:46 | D | sum error = [ 12.6053, 13.3090, 14.0450, 14.8148, 15.6204] +24-11-19 20:33:46 | D | best error = [ 0.8326, 0.8326, 0.8326, 0.8326, 0.8326] +24-11-19 20:33:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:46 | D | sum error = [ 16.4611, 17.3403, 18.2557, 19.2108, 20.2065] +24-11-19 20:33:46 | D | best error = [ 0.8326, 0.8326, 0.8326, 0.8326, 0.8326] +24-11-19 20:33:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:46 | D | sum error = [ 21.2445, 22.3251, 23.4497, 24.6186, 25.8338] +24-11-19 20:33:46 | D | best error = [ 0.8326, 0.8326, 0.8326, 0.8326, 0.8326] +24-11-19 20:33:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:46 | D | sum error = [ 27.0958, 28.4049, 29.7622, 31.1703, 32.6319] +24-11-19 20:33:46 | D | best error = [ 0.8326, 0.8326, 0.8326, 0.8326, 0.8326] +24-11-19 20:33:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:46 | D | sum error = [ 34.1445, 35.7092, 37.3264, 38.9998, 40.7266] +24-11-19 20:33:46 | D | best error = [ 0.8326, 0.8326, 0.8326, 0.8326, 0.8326] +24-11-19 20:33:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:46 | D | sum error = [ 42.5107, 44.3506, 46.2474, 48.2034, 50.2179] +24-11-19 20:33:46 | D | best error = [ 0.8326, 0.8326, 0.8326, 0.8326, 0.8326] +24-11-19 20:33:46 | D | + error = [0.8326] +24-11-19 20:33:46 | D | - Quantizing model.layers.18.self_attn.q_proj.weight +24-11-19 20:33:47 | D | - Quantizing model.layers.18.self_attn.k_proj.weight +24-11-19 20:33:48 | D | - Quantizing model.layers.18.self_attn.v_proj.weight +24-11-19 20:33:49 | D | - Quantizing model.layers.18.self_attn.o_proj.weight +24-11-19 20:33:50 | D | - Quantizing model.layers.18.mlp.up_proj.weight +24-11-19 20:33:51 | D | - Quantizing model.layers.18.mlp.gate_proj.weight +24-11-19 20:33:52 | D | - Quantizing model.layers.18.mlp.down_proj.weight +24-11-19 20:34:03 | D | - Quantizing layer model.layers.19 +24-11-19 20:34:03 | D | - Calibrating model.layers.19.self_attn.q_proj.weight +24-11-19 20:34:03 | D | + w: sint8 +24-11-19 20:34:03 | D | + x: None +24-11-19 20:34:03 | D | + y: None +24-11-19 20:34:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:34:03 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:34:03 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:34:03 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:34:03 | D | - range ratio = [ 1.0000] +24-11-19 20:34:03 | D | sum error = [ 3.5052] +24-11-19 20:34:03 | D | best error = [ 3.5052] +24-11-19 20:34:16 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:16 | D | sum error = [ 3.4731, 3.4253, 3.5529, 3.5059, 3.5722] +24-11-19 20:34:16 | D | best error = [ 3.4731, 3.4253, 3.4253, 3.4253, 3.4253] +24-11-19 20:34:16 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:16 | D | sum error = [ 3.7662, 3.8995, 3.9879, 4.3098, 4.6222] +24-11-19 20:34:16 | D | best error = [ 3.4253, 3.4253, 3.4253, 3.4253, 3.4253] +24-11-19 20:34:16 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:16 | D | sum error = [ 4.9844, 5.3622, 5.8500, 6.2959, 6.8406] +24-11-19 20:34:16 | D | best error = [ 3.4253, 3.4253, 3.4253, 3.4253, 3.4253] +24-11-19 20:34:16 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:16 | D | sum error = [ 7.4757, 8.1152, 9.0040, 9.7486, 10.5905] +24-11-19 20:34:16 | D | best error = [ 3.4253, 3.4253, 3.4253, 3.4253, 3.4253] +24-11-19 20:34:16 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:16 | D | sum error = [ 11.8483, 12.8307, 14.0485, 15.4506, 16.8538] +24-11-19 20:34:16 | D | best error = [ 3.4253, 3.4253, 3.4253, 3.4253, 3.4253] +24-11-19 20:34:16 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:16 | D | sum error = [ 18.5789, 20.4961, 22.6378, 24.7592, 27.1434] +24-11-19 20:34:16 | D | best error = [ 3.4253, 3.4253, 3.4253, 3.4253, 3.4253] +24-11-19 20:34:16 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:16 | D | sum error = [ 29.8958, 32.6798, 35.8751, 38.9844, 42.8897] +24-11-19 20:34:16 | D | best error = [ 3.4253, 3.4253, 3.4253, 3.4253, 3.4253] +24-11-19 20:34:16 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:16 | D | sum error = [ 46.6042, 51.2331, 55.8629, 61.2829, 66.8166] +24-11-19 20:34:16 | D | best error = [ 3.4253, 3.4253, 3.4253, 3.4253, 3.4253] +24-11-19 20:34:16 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:16 | D | sum error = [ 73.0387, 79.9374, 86.8462, 94.6364, 102.9596] +24-11-19 20:34:16 | D | best error = [ 3.4253, 3.4253, 3.4253, 3.4253, 3.4253] +24-11-19 20:34:16 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:16 | D | sum error = [ 112.2719, 122.4049, 132.9062, 144.3567, 157.0578] +24-11-19 20:34:16 | D | best error = [ 3.4253, 3.4253, 3.4253, 3.4253, 3.4253] +24-11-19 20:34:16 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:16 | D | sum error = [ 170.8912, 185.4945, 201.9934, 219.0071, 238.0269] +24-11-19 20:34:16 | D | best error = [ 3.4253, 3.4253, 3.4253, 3.4253, 3.4253] +24-11-19 20:34:16 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:16 | D | sum error = [ 258.7874, 281.4347, 305.8141, 332.9209, 361.9696] +24-11-19 20:34:16 | D | best error = [ 3.4253, 3.4253, 3.4253, 3.4253, 3.4253] +24-11-19 20:34:16 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:16 | D | sum error = [ 394.3332, 429.3699, 467.9854, 509.8677, 556.2740] +24-11-19 20:34:16 | D | best error = [ 3.4253, 3.4253, 3.4253, 3.4253, 3.4253] +24-11-19 20:34:16 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:16 | D | sum error = [ 606.3114, 661.8032, 722.1729, 787.4683, 858.8834] +24-11-19 20:34:16 | D | best error = [ 3.4253, 3.4253, 3.4253, 3.4253, 3.4253] +24-11-19 20:34:16 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:16 | D | sum error = [ 935.9231, 1018.3397, 1107.2370, 1201.8016, 1300.1886] +24-11-19 20:34:16 | D | best error = [ 3.4253, 3.4253, 3.4253, 3.4253, 3.4253] +24-11-19 20:34:16 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:16 | D | sum error = [ 1404.0652, 1511.0816, 1620.7401, 1732.3249, 1843.5099] +24-11-19 20:34:16 | D | best error = [ 3.4253, 3.4253, 3.4253, 3.4253, 3.4253] +24-11-19 20:34:16 | D | + error = [3.4253] +24-11-19 20:34:16 | D | - Calibrating model.layers.19.self_attn.k_proj.weight +24-11-19 20:34:16 | D | + w: sint8 +24-11-19 20:34:16 | D | + x: None +24-11-19 20:34:16 | D | + y: None +24-11-19 20:34:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:34:16 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:34:17 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:34:17 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:34:17 | D | - range ratio = [ 1.0000] +24-11-19 20:34:17 | D | sum error = [ 3.3766] +24-11-19 20:34:17 | D | best error = [ 3.3766] +24-11-19 20:34:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:29 | D | sum error = [ 3.1974, 3.2942, 3.4059, 3.3704, 3.5163] +24-11-19 20:34:29 | D | best error = [ 3.1974, 3.1974, 3.1974, 3.1974, 3.1974] +24-11-19 20:34:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:29 | D | sum error = [ 3.7549, 3.9897, 4.2180, 4.4808, 4.0753] +24-11-19 20:34:29 | D | best error = [ 3.1974, 3.1974, 3.1974, 3.1974, 3.1974] +24-11-19 20:34:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:29 | D | sum error = [ 4.6685, 5.0496, 4.9180, 5.7209, 6.2473] +24-11-19 20:34:29 | D | best error = [ 3.1974, 3.1974, 3.1974, 3.1974, 3.1974] +24-11-19 20:34:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:29 | D | sum error = [ 6.2928, 7.3289, 7.9465, 8.4397, 8.9559] +24-11-19 20:34:29 | D | best error = [ 3.1974, 3.1974, 3.1974, 3.1974, 3.1974] +24-11-19 20:34:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:29 | D | sum error = [ 9.5805, 10.3549, 11.7143, 13.2986, 13.8263] +24-11-19 20:34:29 | D | best error = [ 3.1974, 3.1974, 3.1974, 3.1974, 3.1974] +24-11-19 20:34:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:29 | D | sum error = [ 15.3421, 16.5821, 17.8616, 19.4335, 21.8852] +24-11-19 20:34:29 | D | best error = [ 3.1974, 3.1974, 3.1974, 3.1974, 3.1974] +24-11-19 20:34:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:29 | D | sum error = [ 23.1007, 24.9320, 27.3964, 28.6500, 31.5593] +24-11-19 20:34:29 | D | best error = [ 3.1974, 3.1974, 3.1974, 3.1974, 3.1974] +24-11-19 20:34:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:29 | D | sum error = [ 33.9995, 37.0958, 40.2515, 43.5301, 47.1798] +24-11-19 20:34:29 | D | best error = [ 3.1974, 3.1974, 3.1974, 3.1974, 3.1974] +24-11-19 20:34:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:29 | D | sum error = [ 50.5801, 54.8974, 58.8862, 63.5488, 68.0177] +24-11-19 20:34:29 | D | best error = [ 3.1974, 3.1974, 3.1974, 3.1974, 3.1974] +24-11-19 20:34:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:29 | D | sum error = [ 72.7835, 78.9108, 85.0206, 92.0115, 98.6801] +24-11-19 20:34:29 | D | best error = [ 3.1974, 3.1974, 3.1974, 3.1974, 3.1974] +24-11-19 20:34:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:29 | D | sum error = [ 106.6341, 115.4251, 125.0706, 135.7859, 147.0821] +24-11-19 20:34:29 | D | best error = [ 3.1974, 3.1974, 3.1974, 3.1974, 3.1974] +24-11-19 20:34:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:29 | D | sum error = [ 160.4506, 173.7946, 189.7232, 207.9091, 226.1574] +24-11-19 20:34:29 | D | best error = [ 3.1974, 3.1974, 3.1974, 3.1974, 3.1974] +24-11-19 20:34:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:29 | D | sum error = [ 248.2247, 271.8190, 299.2236, 328.3553, 361.9824] +24-11-19 20:34:29 | D | best error = [ 3.1974, 3.1974, 3.1974, 3.1974, 3.1974] +24-11-19 20:34:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:29 | D | sum error = [ 396.4547, 436.9212, 480.9240, 529.0564, 580.0769] +24-11-19 20:34:29 | D | best error = [ 3.1974, 3.1974, 3.1974, 3.1974, 3.1974] +24-11-19 20:34:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:29 | D | sum error = [ 636.5243, 699.7320, 767.8333, 844.7372, 928.3039] +24-11-19 20:34:29 | D | best error = [ 3.1974, 3.1974, 3.1974, 3.1974, 3.1974] +24-11-19 20:34:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:29 | D | sum error = [ 1021.8556, 1126.6012, 1237.1721, 1356.1640, 1482.3374] +24-11-19 20:34:29 | D | best error = [ 3.1974, 3.1974, 3.1974, 3.1974, 3.1974] +24-11-19 20:34:29 | D | + error = [3.1974] +24-11-19 20:34:29 | D | - Calibrating model.layers.19.self_attn.v_proj.weight +24-11-19 20:34:29 | D | + w: sint8 +24-11-19 20:34:29 | D | + x: None +24-11-19 20:34:29 | D | + y: None +24-11-19 20:34:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:29 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:34:29 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:34:29 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:34:29 | D | - range ratio = [ 1.0000] +24-11-19 20:34:29 | D | sum error = [ 1.6693] +24-11-19 20:34:29 | D | best error = [ 1.6693] +24-11-19 20:34:30 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:30 | D | sum error = [ 1.6538, 1.6520, 1.6486, 1.6794, 1.7040] +24-11-19 20:34:30 | D | best error = [ 1.5517, 1.5042, 1.4782, 1.4636, 1.4568] +24-11-19 20:34:30 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:30 | D | sum error = [ 1.7584, 1.8324, 1.8979, 1.9813, 2.0892] +24-11-19 20:34:30 | D | best error = [ 1.4536, 1.4518, 1.4509, 1.4509, 1.4508] +24-11-19 20:34:30 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:30 | D | sum error = [ 2.2059, 2.3502, 2.5086, 2.6760, 2.8681] +24-11-19 20:34:30 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 20:34:30 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:30 | D | sum error = [ 3.0665, 3.2977, 3.5261, 3.7767, 4.0503] +24-11-19 20:34:30 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 20:34:30 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:30 | D | sum error = [ 4.3569, 4.6809, 5.0112, 5.3732, 5.7394] +24-11-19 20:34:30 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 20:34:30 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:30 | D | sum error = [ 6.1461, 6.5612, 7.0235, 7.4913, 7.9801] +24-11-19 20:34:30 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 20:34:30 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:30 | D | sum error = [ 8.5144, 9.1003, 9.6885, 10.2945, 10.9647] +24-11-19 20:34:30 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 20:34:30 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:30 | D | sum error = [ 11.6563, 12.3897, 13.1798, 13.9666, 14.8151] +24-11-19 20:34:30 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 20:34:30 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:30 | D | sum error = [ 15.7023, 16.6454, 17.6164, 18.6359, 19.7230] +24-11-19 20:34:30 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 20:34:30 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:30 | D | sum error = [ 20.8676, 22.0524, 23.3049, 24.5917, 25.9613] +24-11-19 20:34:30 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 20:34:30 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:30 | D | sum error = [ 27.3882, 28.8893, 30.4524, 32.0712, 33.7826] +24-11-19 20:34:30 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 20:34:30 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:30 | D | sum error = [ 35.5498, 37.3870, 39.3069, 41.3034, 43.3819] +24-11-19 20:34:30 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 20:34:30 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:30 | D | sum error = [ 45.5443, 47.7909, 50.1310, 52.5600, 55.0908] +24-11-19 20:34:30 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 20:34:30 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:30 | D | sum error = [ 57.7116, 60.4456, 63.2678, 66.1914, 69.2183] +24-11-19 20:34:30 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 20:34:30 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:30 | D | sum error = [ 72.3488, 75.5806, 78.9187, 82.3736, 85.9288] +24-11-19 20:34:30 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 20:34:30 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:30 | D | sum error = [ 89.6063, 93.3902, 97.2972, 101.3101, 105.4416] +24-11-19 20:34:30 | D | best error = [ 1.4508, 1.4508, 1.4508, 1.4508, 1.4508] +24-11-19 20:34:30 | D | + error = [1.4508] +24-11-19 20:34:30 | D | - Calibrating model.layers.19.self_attn.o_proj.weight +24-11-19 20:34:30 | D | + w: sint8 +24-11-19 20:34:30 | D | + x: None +24-11-19 20:34:30 | D | + y: None +24-11-19 20:34:30 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:30 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:34:30 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:34:30 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:34:30 | D | - range ratio = [ 1.0000] +24-11-19 20:34:30 | D | sum error = [ 0.3769] +24-11-19 20:34:30 | D | best error = [ 0.3769] +24-11-19 20:34:30 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:30 | D | sum error = [ 0.3739, 0.3729, 0.3743, 0.3756, 0.3787] +24-11-19 20:34:30 | D | best error = [ 0.3528, 0.3421, 0.3355, 0.3311, 0.3277] +24-11-19 20:34:30 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:30 | D | sum error = [ 0.3876, 0.3978, 0.4103, 0.4240, 0.4424] +24-11-19 20:34:30 | D | best error = [ 0.3256, 0.3238, 0.3226, 0.3216, 0.3209] +24-11-19 20:34:30 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:30 | D | sum error = [ 0.4618, 0.4867, 0.5129, 0.5426, 0.5725] +24-11-19 20:34:30 | D | best error = [ 0.3203, 0.3199, 0.3196, 0.3192, 0.3191] +24-11-19 20:34:30 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:30 | D | sum error = [ 0.6093, 0.6461, 0.6862, 0.7301, 0.7758] +24-11-19 20:34:30 | D | best error = [ 0.3189, 0.3189, 0.3188, 0.3187, 0.3187] +24-11-19 20:34:30 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:30 | D | sum error = [ 0.8265, 0.8794, 0.9357, 0.9959, 1.0572] +24-11-19 20:34:30 | D | best error = [ 0.3187, 0.3187, 0.3186, 0.3186, 0.3186] +24-11-19 20:34:30 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:30 | D | sum error = [ 1.1250, 1.1944, 1.2701, 1.3490, 1.4309] +24-11-19 20:34:30 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:34:30 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:30 | D | sum error = [ 1.5199, 1.6122, 1.7079, 1.8097, 1.9178] +24-11-19 20:34:30 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:34:30 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:30 | D | sum error = [ 2.0295, 2.1471, 2.2699, 2.3990, 2.5337] +24-11-19 20:34:30 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:34:30 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:30 | D | sum error = [ 2.6769, 2.8266, 2.9831, 3.1478, 3.3200] +24-11-19 20:34:30 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:34:30 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:30 | D | sum error = [ 3.5014, 3.6917, 3.8897, 4.0976, 4.3147] +24-11-19 20:34:30 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:34:30 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:30 | D | sum error = [ 4.5424, 4.7805, 5.0282, 5.2878, 5.5583] +24-11-19 20:34:30 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:34:30 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:30 | D | sum error = [ 5.8408, 6.1357, 6.4442, 6.7643, 7.0995] +24-11-19 20:34:30 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:34:30 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:30 | D | sum error = [ 7.4469, 7.8100, 8.1858, 8.5765, 8.9821] +24-11-19 20:34:30 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:34:30 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:30 | D | sum error = [ 9.4034, 9.8405, 10.2941, 10.7657, 11.2533] +24-11-19 20:34:30 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:34:30 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:30 | D | sum error = [ 11.7590, 12.2830, 12.8257, 13.3875, 13.9684] +24-11-19 20:34:30 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:34:30 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:30 | D | sum error = [ 14.5682, 15.1884, 15.8278, 16.4891, 17.1710] +24-11-19 20:34:30 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:34:30 | D | + error = [0.3186] +24-11-19 20:34:31 | D | - Calibrating model.layers.19.mlp.up_proj.weight +24-11-19 20:34:31 | D | + w: sint8 +24-11-19 20:34:31 | D | + x: None +24-11-19 20:34:31 | D | + y: None +24-11-19 20:34:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:31 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:34:31 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:34:31 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:34:31 | D | - range ratio = [ 1.0000] +24-11-19 20:34:31 | D | sum error = [ 0.3383] +24-11-19 20:34:31 | D | best error = [ 0.3383] +24-11-19 20:34:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:32 | D | sum error = [ 0.3349, 0.3348, 0.3350, 0.3397, 0.3459] +24-11-19 20:34:32 | D | best error = [ 0.3133, 0.3037, 0.2987, 0.2957, 0.2942] +24-11-19 20:34:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:32 | D | sum error = [ 0.3545, 0.3662, 0.3806, 0.3989, 0.4191] +24-11-19 20:34:32 | D | best error = [ 0.2934, 0.2930, 0.2929, 0.2929, 0.2929] +24-11-19 20:34:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:32 | D | sum error = [ 0.4435, 0.4702, 0.5015, 0.5349, 0.5716] +24-11-19 20:34:32 | D | best error = [ 0.2929, 0.2929, 0.2929, 0.2929, 0.2929] +24-11-19 20:34:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:32 | D | sum error = [ 0.6116, 0.6541, 0.7009, 0.7513, 0.8049] +24-11-19 20:34:32 | D | best error = [ 0.2929, 0.2929, 0.2929, 0.2929, 0.2929] +24-11-19 20:34:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:32 | D | sum error = [ 0.8609, 0.9225, 0.9866, 1.0563, 1.1286] +24-11-19 20:34:32 | D | best error = [ 0.2929, 0.2929, 0.2929, 0.2929, 0.2929] +24-11-19 20:34:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:32 | D | sum error = [ 1.2056, 1.2878, 1.3734, 1.4650, 1.5620] +24-11-19 20:34:32 | D | best error = [ 0.2929, 0.2929, 0.2929, 0.2929, 0.2929] +24-11-19 20:34:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:32 | D | sum error = [ 1.6634, 1.7702, 1.8827, 2.0003, 2.1251] +24-11-19 20:34:32 | D | best error = [ 0.2929, 0.2929, 0.2929, 0.2929, 0.2929] +24-11-19 20:34:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:32 | D | sum error = [ 2.2569, 2.3944, 2.5397, 2.6906, 2.8505] +24-11-19 20:34:32 | D | best error = [ 0.2929, 0.2929, 0.2929, 0.2929, 0.2929] +24-11-19 20:34:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:32 | D | sum error = [ 3.0178, 3.1924, 3.3756, 3.5660, 3.7678] +24-11-19 20:34:32 | D | best error = [ 0.2929, 0.2929, 0.2929, 0.2929, 0.2929] +24-11-19 20:34:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:32 | D | sum error = [ 3.9785, 4.1979, 4.4276, 4.6673, 4.9177] +24-11-19 20:34:32 | D | best error = [ 0.2929, 0.2929, 0.2929, 0.2929, 0.2929] +24-11-19 20:34:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:32 | D | sum error = [ 5.1781, 5.4501, 5.7342, 6.0274, 6.3338] +24-11-19 20:34:32 | D | best error = [ 0.2929, 0.2929, 0.2929, 0.2929, 0.2929] +24-11-19 20:34:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:32 | D | sum error = [ 6.6533, 6.9828, 7.3276, 7.6835, 8.0546] +24-11-19 20:34:32 | D | best error = [ 0.2929, 0.2929, 0.2929, 0.2929, 0.2929] +24-11-19 20:34:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:32 | D | sum error = [ 8.4368, 8.8321, 9.2466, 9.6721, 10.1124] +24-11-19 20:34:32 | D | best error = [ 0.2929, 0.2929, 0.2929, 0.2929, 0.2929] +24-11-19 20:34:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:32 | D | sum error = [ 10.5664, 11.0394, 11.5253, 12.0277, 12.5450] +24-11-19 20:34:32 | D | best error = [ 0.2929, 0.2929, 0.2929, 0.2929, 0.2929] +24-11-19 20:34:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:32 | D | sum error = [ 13.0832, 13.6350, 14.2000, 14.7848, 15.3837] +24-11-19 20:34:32 | D | best error = [ 0.2929, 0.2929, 0.2929, 0.2929, 0.2929] +24-11-19 20:34:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:32 | D | sum error = [ 16.0113, 16.6496, 17.3056, 17.9820, 18.6730] +24-11-19 20:34:32 | D | best error = [ 0.2929, 0.2929, 0.2929, 0.2929, 0.2929] +24-11-19 20:34:32 | D | + error = [0.2929] +24-11-19 20:34:32 | D | - Calibrating model.layers.19.mlp.gate_proj.weight +24-11-19 20:34:32 | D | + w: sint8 +24-11-19 20:34:32 | D | + x: None +24-11-19 20:34:32 | D | + y: None +24-11-19 20:34:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:32 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:34:32 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:34:33 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:34:33 | D | - range ratio = [ 1.0000] +24-11-19 20:34:33 | D | sum error = [ 8.7903] +24-11-19 20:34:33 | D | best error = [ 8.7903] +24-11-19 20:34:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:34 | D | sum error = [ 8.7251, 8.7153, 8.7479, 8.8186, 9.0158] +24-11-19 20:34:34 | D | best error = [ 8.1414, 7.9014, 7.7731, 7.7006, 7.6605] +24-11-19 20:34:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:34 | D | sum error = [ 9.2218, 9.5535, 9.9454, 10.4357, 10.9779] +24-11-19 20:34:34 | D | best error = [ 7.6404, 7.6325, 7.6293, 7.6286, 7.6285] +24-11-19 20:34:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:34 | D | sum error = [ 11.6510, 12.3517, 13.1932, 14.0686, 15.0735] +24-11-19 20:34:34 | D | best error = [ 7.6284, 7.6284, 7.6284, 7.6284, 7.6284] +24-11-19 20:34:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:34 | D | sum error = [ 16.1480, 17.3155, 18.5732, 19.9122, 21.3774] +24-11-19 20:34:34 | D | best error = [ 7.6284, 7.6284, 7.6284, 7.6284, 7.6284] +24-11-19 20:34:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:34 | D | sum error = [ 22.9256, 24.6111, 26.3698, 28.2315, 30.2432] +24-11-19 20:34:34 | D | best error = [ 7.6284, 7.6284, 7.6284, 7.6284, 7.6284] +24-11-19 20:34:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:34 | D | sum error = [ 32.3738, 34.6333, 37.0574, 39.5944, 42.3189] +24-11-19 20:34:34 | D | best error = [ 7.6284, 7.6284, 7.6284, 7.6284, 7.6284] +24-11-19 20:34:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:34 | D | sum error = [ 45.1770, 48.2122, 51.4344, 54.8726, 58.4751] +24-11-19 20:34:34 | D | best error = [ 7.6284, 7.6284, 7.6284, 7.6284, 7.6284] +24-11-19 20:34:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:34 | D | sum error = [ 62.3062, 66.3518, 70.6760, 75.2018, 80.0131] +24-11-19 20:34:34 | D | best error = [ 7.6284, 7.6284, 7.6284, 7.6284, 7.6284] +24-11-19 20:34:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:34 | D | sum error = [ 85.0885, 90.4910, 96.1752, 102.2043, 108.5798] +24-11-19 20:34:34 | D | best error = [ 7.6284, 7.6284, 7.6284, 7.6284, 7.6284] +24-11-19 20:34:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:34 | D | sum error = [ 115.2947, 122.4230, 129.8809, 137.7813, 146.1082] +24-11-19 20:34:34 | D | best error = [ 7.6284, 7.6284, 7.6284, 7.6284, 7.6284] +24-11-19 20:34:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:34 | D | sum error = [ 154.8587, 164.0675, 173.7703, 184.0262, 194.7805] +24-11-19 20:34:34 | D | best error = [ 7.6284, 7.6284, 7.6284, 7.6284, 7.6284] +24-11-19 20:34:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:34 | D | sum error = [ 206.0495, 217.9172, 230.3694, 243.4349, 257.1288] +24-11-19 20:34:34 | D | best error = [ 7.6284, 7.6284, 7.6284, 7.6284, 7.6284] +24-11-19 20:34:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:34 | D | sum error = [ 271.4857, 286.4976, 302.2169, 318.6382, 335.7989] +24-11-19 20:34:34 | D | best error = [ 7.6284, 7.6284, 7.6284, 7.6284, 7.6284] +24-11-19 20:34:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:34 | D | sum error = [ 353.7557, 372.4765, 391.9949, 412.3646, 433.5413] +24-11-19 20:34:34 | D | best error = [ 7.6284, 7.6284, 7.6284, 7.6284, 7.6284] +24-11-19 20:34:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:34 | D | sum error = [ 455.6001, 478.5030, 502.2686, 526.8989, 552.4403] +24-11-19 20:34:34 | D | best error = [ 7.6284, 7.6284, 7.6284, 7.6284, 7.6284] +24-11-19 20:34:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:34 | D | sum error = [ 578.8173, 606.0860, 634.2485, 663.2665, 693.1979] +24-11-19 20:34:34 | D | best error = [ 7.6284, 7.6284, 7.6284, 7.6284, 7.6284] +24-11-19 20:34:34 | D | + error = [7.6284] +24-11-19 20:34:34 | D | - Calibrating model.layers.19.mlp.down_proj.weight +24-11-19 20:34:34 | D | + w: sint8 +24-11-19 20:34:34 | D | + x: None +24-11-19 20:34:34 | D | + y: None +24-11-19 20:34:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:34 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:34:34 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:34:34 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:34:34 | D | - range ratio = [ 1.0000] +24-11-19 20:34:34 | D | sum error = [ 0.9360] +24-11-19 20:34:34 | D | best error = [ 0.9360] +24-11-19 20:34:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:36 | D | sum error = [ 0.9290, 0.9212, 0.9200, 0.9177, 0.9209] +24-11-19 20:34:36 | D | best error = [ 0.9024, 0.8842, 0.8727, 0.8640, 0.8578] +24-11-19 20:34:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:36 | D | sum error = [ 0.9297, 0.9425, 0.9609, 0.9859, 1.0186] +24-11-19 20:34:36 | D | best error = [ 0.8533, 0.8500, 0.8476, 0.8462, 0.8454] +24-11-19 20:34:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:36 | D | sum error = [ 1.0558, 1.1035, 1.1558, 1.2213, 1.2915] +24-11-19 20:34:36 | D | best error = [ 0.8447, 0.8445, 0.8443, 0.8443, 0.8442] +24-11-19 20:34:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:36 | D | sum error = [ 1.3720, 1.4608, 1.5585, 1.6657, 1.7821] +24-11-19 20:34:36 | D | best error = [ 0.8442, 0.8442, 0.8442, 0.8442, 0.8442] +24-11-19 20:34:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:36 | D | sum error = [ 1.9101, 2.0443, 2.1931, 2.3493, 2.5179] +24-11-19 20:34:36 | D | best error = [ 0.8442, 0.8442, 0.8442, 0.8442, 0.8442] +24-11-19 20:34:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:36 | D | sum error = [ 2.6978, 2.8878, 3.0911, 3.3074, 3.5332] +24-11-19 20:34:36 | D | best error = [ 0.8442, 0.8442, 0.8442, 0.8442, 0.8442] +24-11-19 20:34:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:36 | D | sum error = [ 3.7770, 4.0347, 4.3056, 4.5926, 4.8953] +24-11-19 20:34:36 | D | best error = [ 0.8442, 0.8442, 0.8442, 0.8442, 0.8442] +24-11-19 20:34:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:36 | D | sum error = [ 5.2153, 5.5520, 5.9075, 6.2844, 6.6817] +24-11-19 20:34:36 | D | best error = [ 0.8442, 0.8442, 0.8442, 0.8442, 0.8442] +24-11-19 20:34:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:36 | D | sum error = [ 7.1002, 7.5411, 8.0028, 8.4904, 9.0026] +24-11-19 20:34:36 | D | best error = [ 0.8442, 0.8442, 0.8442, 0.8442, 0.8442] +24-11-19 20:34:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:36 | D | sum error = [ 9.5395, 10.1033, 10.6939, 11.3132, 11.9597] +24-11-19 20:34:36 | D | best error = [ 0.8442, 0.8442, 0.8442, 0.8442, 0.8442] +24-11-19 20:34:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:36 | D | sum error = [ 12.6382, 13.3493, 14.0944, 14.8729, 15.6845] +24-11-19 20:34:36 | D | best error = [ 0.8442, 0.8442, 0.8442, 0.8442, 0.8442] +24-11-19 20:34:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:36 | D | sum error = [ 16.5342, 17.4216, 18.3482, 19.3134, 20.3174] +24-11-19 20:34:36 | D | best error = [ 0.8442, 0.8442, 0.8442, 0.8442, 0.8442] +24-11-19 20:34:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:36 | D | sum error = [ 21.3641, 22.4565, 23.5907, 24.7691, 25.9933] +24-11-19 20:34:36 | D | best error = [ 0.8442, 0.8442, 0.8442, 0.8442, 0.8442] +24-11-19 20:34:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:36 | D | sum error = [ 27.2677, 28.5870, 29.9547, 31.3737, 32.8471] +24-11-19 20:34:36 | D | best error = [ 0.8442, 0.8442, 0.8442, 0.8442, 0.8442] +24-11-19 20:34:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:36 | D | sum error = [ 34.3739, 35.9531, 37.5864, 39.2768, 41.0226] +24-11-19 20:34:36 | D | best error = [ 0.8442, 0.8442, 0.8442, 0.8442, 0.8442] +24-11-19 20:34:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:36 | D | sum error = [ 42.8248, 44.6858, 46.6029, 48.5810, 50.6180] +24-11-19 20:34:36 | D | best error = [ 0.8442, 0.8442, 0.8442, 0.8442, 0.8442] +24-11-19 20:34:36 | D | + error = [0.8442] +24-11-19 20:34:36 | D | - Quantizing model.layers.19.self_attn.q_proj.weight +24-11-19 20:34:37 | D | - Quantizing model.layers.19.self_attn.k_proj.weight +24-11-19 20:34:38 | D | - Quantizing model.layers.19.self_attn.v_proj.weight +24-11-19 20:34:39 | D | - Quantizing model.layers.19.self_attn.o_proj.weight +24-11-19 20:34:40 | D | - Quantizing model.layers.19.mlp.up_proj.weight +24-11-19 20:34:41 | D | - Quantizing model.layers.19.mlp.gate_proj.weight +24-11-19 20:34:42 | D | - Quantizing model.layers.19.mlp.down_proj.weight +24-11-19 20:34:53 | D | - Quantizing layer model.layers.20 +24-11-19 20:34:53 | D | - Calibrating model.layers.20.self_attn.q_proj.weight +24-11-19 20:34:53 | D | + w: sint8 +24-11-19 20:34:53 | D | + x: None +24-11-19 20:34:53 | D | + y: None +24-11-19 20:34:53 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:34:53 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:34:54 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:34:54 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:34:54 | D | - range ratio = [ 1.0000] +24-11-19 20:34:54 | D | sum error = [ 3.9137] +24-11-19 20:34:54 | D | best error = [ 3.9137] +24-11-19 20:35:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:06 | D | sum error = [ 3.8410, 3.8536, 3.8794, 3.9097, 4.0355] +24-11-19 20:35:06 | D | best error = [ 3.8410, 3.8410, 3.8410, 3.8410, 3.8410] +24-11-19 20:35:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:06 | D | sum error = [ 4.1059, 4.2979, 4.4671, 4.7138, 4.8743] +24-11-19 20:35:06 | D | best error = [ 3.8410, 3.8410, 3.8410, 3.8410, 3.8410] +24-11-19 20:35:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:06 | D | sum error = [ 5.1583, 5.5046, 5.9715, 6.5187, 6.9978] +24-11-19 20:35:06 | D | best error = [ 3.8410, 3.8410, 3.8410, 3.8410, 3.8410] +24-11-19 20:35:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:06 | D | sum error = [ 7.7334, 8.1353, 8.8152, 10.0961, 10.7664] +24-11-19 20:35:06 | D | best error = [ 3.8410, 3.8410, 3.8410, 3.8410, 3.8410] +24-11-19 20:35:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:06 | D | sum error = [ 11.8643, 13.2215, 14.5582, 16.0179, 17.4601] +24-11-19 20:35:06 | D | best error = [ 3.8410, 3.8410, 3.8410, 3.8410, 3.8410] +24-11-19 20:35:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:06 | D | sum error = [ 19.2969, 21.4521, 23.5501, 25.7573, 28.5277] +24-11-19 20:35:06 | D | best error = [ 3.8410, 3.8410, 3.8410, 3.8410, 3.8410] +24-11-19 20:35:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:06 | D | sum error = [ 31.1656, 34.3783, 37.8790, 41.6695, 45.7745] +24-11-19 20:35:06 | D | best error = [ 3.8410, 3.8410, 3.8410, 3.8410, 3.8410] +24-11-19 20:35:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:06 | D | sum error = [ 50.6263, 55.5882, 61.1481, 67.5317, 74.3430] +24-11-19 20:35:06 | D | best error = [ 3.8410, 3.8410, 3.8410, 3.8410, 3.8410] +24-11-19 20:35:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:06 | D | sum error = [ 81.5401, 89.4751, 98.2576, 107.1637, 117.6340] +24-11-19 20:35:06 | D | best error = [ 3.8410, 3.8410, 3.8410, 3.8410, 3.8410] +24-11-19 20:35:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:06 | D | sum error = [ 129.4316, 141.3253, 156.0524, 170.7811, 187.3138] +24-11-19 20:35:06 | D | best error = [ 3.8410, 3.8410, 3.8410, 3.8410, 3.8410] +24-11-19 20:35:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:06 | D | sum error = [ 205.7876, 226.1449, 247.9434, 272.0829, 298.9709] +24-11-19 20:35:06 | D | best error = [ 3.8410, 3.8410, 3.8410, 3.8410, 3.8410] +24-11-19 20:35:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:06 | D | sum error = [ 328.0713, 360.2474, 396.4767, 436.4425, 480.5654] +24-11-19 20:35:06 | D | best error = [ 3.8410, 3.8410, 3.8410, 3.8410, 3.8410] +24-11-19 20:35:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:06 | D | sum error = [ 528.3210, 582.7376, 641.7373, 708.1367, 781.4150] +24-11-19 20:35:06 | D | best error = [ 3.8410, 3.8410, 3.8410, 3.8410, 3.8410] +24-11-19 20:35:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:06 | D | sum error = [ 861.8238, 950.8219, 1048.5871, 1155.1934, 1271.0399] +24-11-19 20:35:06 | D | best error = [ 3.8410, 3.8410, 3.8410, 3.8410, 3.8410] +24-11-19 20:35:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:06 | D | sum error = [ 1397.6243, 1536.5731, 1684.2090, 1843.5966, 2011.2648] +24-11-19 20:35:06 | D | best error = [ 3.8410, 3.8410, 3.8410, 3.8410, 3.8410] +24-11-19 20:35:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:06 | D | sum error = [ 2185.8335, 2364.9719, 2546.4719, 2726.7550, 2906.0501] +24-11-19 20:35:06 | D | best error = [ 3.8410, 3.8410, 3.8410, 3.8410, 3.8410] +24-11-19 20:35:06 | D | + error = [3.8410] +24-11-19 20:35:06 | D | - Calibrating model.layers.20.self_attn.k_proj.weight +24-11-19 20:35:06 | D | + w: sint8 +24-11-19 20:35:06 | D | + x: None +24-11-19 20:35:06 | D | + y: None +24-11-19 20:35:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:35:06 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:35:06 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:07 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:07 | D | - range ratio = [ 1.0000] +24-11-19 20:35:07 | D | sum error = [ 3.9957] +24-11-19 20:35:07 | D | best error = [ 3.9957] +24-11-19 20:35:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:19 | D | sum error = [ 3.9480, 3.9188, 3.9412, 3.6884, 4.0011] +24-11-19 20:35:19 | D | best error = [ 3.9480, 3.9188, 3.9188, 3.6884, 3.6884] +24-11-19 20:35:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:19 | D | sum error = [ 4.0308, 4.3661, 4.4587, 5.0115, 6.0954] +24-11-19 20:35:19 | D | best error = [ 3.6884, 3.6884, 3.6884, 3.6884, 3.6884] +24-11-19 20:35:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:19 | D | sum error = [ 5.5064, 6.2811, 8.0634, 7.4986, 8.9982] +24-11-19 20:35:19 | D | best error = [ 3.6884, 3.6884, 3.6884, 3.6884, 3.6884] +24-11-19 20:35:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:19 | D | sum error = [ 9.0949, 9.9171, 11.1928, 12.9613, 11.8327] +24-11-19 20:35:19 | D | best error = [ 3.6884, 3.6884, 3.6884, 3.6884, 3.6884] +24-11-19 20:35:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:19 | D | sum error = [ 13.8071, 14.0281, 16.7935, 16.7839, 18.1990] +24-11-19 20:35:19 | D | best error = [ 3.6884, 3.6884, 3.6884, 3.6884, 3.6884] +24-11-19 20:35:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:19 | D | sum error = [ 19.3161, 20.6564, 21.9488, 24.3408, 26.5806] +24-11-19 20:35:19 | D | best error = [ 3.6884, 3.6884, 3.6884, 3.6884, 3.6884] +24-11-19 20:35:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:19 | D | sum error = [ 29.7252, 33.6194, 37.3492, 38.8341, 41.2490] +24-11-19 20:35:19 | D | best error = [ 3.6884, 3.6884, 3.6884, 3.6884, 3.6884] +24-11-19 20:35:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:19 | D | sum error = [ 47.3906, 51.3677, 55.2589, 60.4184, 66.0824] +24-11-19 20:35:19 | D | best error = [ 3.6884, 3.6884, 3.6884, 3.6884, 3.6884] +24-11-19 20:35:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:19 | D | sum error = [ 70.0378, 75.9345, 83.3642, 90.8969, 98.9743] +24-11-19 20:35:19 | D | best error = [ 3.6884, 3.6884, 3.6884, 3.6884, 3.6884] +24-11-19 20:35:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:19 | D | sum error = [ 107.9129, 117.3624, 129.3175, 140.9184, 153.5767] +24-11-19 20:35:19 | D | best error = [ 3.6884, 3.6884, 3.6884, 3.6884, 3.6884] +24-11-19 20:35:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:19 | D | sum error = [ 168.5406, 184.3905, 201.7230, 222.9812, 244.0451] +24-11-19 20:35:19 | D | best error = [ 3.6884, 3.6884, 3.6884, 3.6884, 3.6884] +24-11-19 20:35:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:19 | D | sum error = [ 268.9619, 295.3689, 324.3328, 358.9570, 395.8260] +24-11-19 20:35:19 | D | best error = [ 3.6884, 3.6884, 3.6884, 3.6884, 3.6884] +24-11-19 20:35:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:19 | D | sum error = [ 437.5111, 483.2239, 536.7801, 599.0361, 665.4655] +24-11-19 20:35:19 | D | best error = [ 3.6884, 3.6884, 3.6884, 3.6884, 3.6884] +24-11-19 20:35:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:19 | D | sum error = [ 741.4820, 824.6793, 915.0563, 1018.7897, 1130.8517] +24-11-19 20:35:19 | D | best error = [ 3.6884, 3.6884, 3.6884, 3.6884, 3.6884] +24-11-19 20:35:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:19 | D | sum error = [ 1252.9880, 1385.9116, 1525.1190, 1686.1997, 1853.2331] +24-11-19 20:35:19 | D | best error = [ 3.6884, 3.6884, 3.6884, 3.6884, 3.6884] +24-11-19 20:35:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:19 | D | sum error = [ 2034.1130, 2221.2510, 2400.8942, 2591.6005, 2776.7740] +24-11-19 20:35:19 | D | best error = [ 3.6884, 3.6884, 3.6884, 3.6884, 3.6884] +24-11-19 20:35:19 | D | + error = [3.6884] +24-11-19 20:35:19 | D | - Calibrating model.layers.20.self_attn.v_proj.weight +24-11-19 20:35:19 | D | + w: sint8 +24-11-19 20:35:19 | D | + x: None +24-11-19 20:35:19 | D | + y: None +24-11-19 20:35:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:19 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:19 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:19 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:19 | D | - range ratio = [ 1.0000] +24-11-19 20:35:19 | D | sum error = [ 1.7733] +24-11-19 20:35:19 | D | best error = [ 1.7733] +24-11-19 20:35:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:19 | D | sum error = [ 1.7581, 1.7437, 1.7644, 1.7671, 1.8086] +24-11-19 20:35:19 | D | best error = [ 1.6387, 1.5847, 1.5594, 1.5454, 1.5367] +24-11-19 20:35:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:19 | D | sum error = [ 1.8773, 1.9166, 2.0073, 2.0976, 2.2088] +24-11-19 20:35:19 | D | best error = [ 1.5336, 1.5326, 1.5317, 1.5313, 1.5312] +24-11-19 20:35:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:19 | D | sum error = [ 2.3411, 2.5020, 2.6575, 2.8426, 3.0289] +24-11-19 20:35:19 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:19 | D | sum error = [ 3.2548, 3.4785, 3.7389, 4.0022, 4.3062] +24-11-19 20:35:19 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:19 | D | sum error = [ 4.5963, 4.9113, 5.2877, 5.6583, 6.0504] +24-11-19 20:35:19 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:19 | D | sum error = [ 6.4593, 6.9310, 7.3971, 7.8911, 8.4277] +24-11-19 20:35:19 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:19 | D | sum error = [ 8.9734, 9.5765, 10.1876, 10.8317, 11.5141] +24-11-19 20:35:19 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:19 | D | sum error = [ 12.2358, 13.0083, 13.7884, 14.6182, 15.4930] +24-11-19 20:35:19 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:19 | D | sum error = [ 16.4088, 17.3813, 18.3989, 19.4506, 20.5689] +24-11-19 20:35:19 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:19 | D | sum error = [ 21.7317, 22.9575, 24.2357, 25.5712, 26.9721] +24-11-19 20:35:19 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:19 | D | sum error = [ 28.4512, 29.9860, 31.5788, 33.2397, 34.9744] +24-11-19 20:35:19 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:19 | D | sum error = [ 36.7751, 38.6533, 40.6081, 42.6395, 44.7585] +24-11-19 20:35:19 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:19 | D | sum error = [ 46.9630, 49.2416, 51.6175, 54.0614, 56.6112] +24-11-19 20:35:19 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:19 | D | sum error = [ 59.2582, 61.9889, 64.8261, 67.7661, 70.8091] +24-11-19 20:35:19 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:19 | D | sum error = [ 73.9650, 77.2175, 80.5851, 84.0494, 87.6268] +24-11-19 20:35:19 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:19 | D | sum error = [ 91.3167, 95.0980, 98.9980, 102.9930, 107.1103] +24-11-19 20:35:19 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:19 | D | + error = [1.5312] +24-11-19 20:35:19 | D | - Calibrating model.layers.20.self_attn.o_proj.weight +24-11-19 20:35:19 | D | + w: sint8 +24-11-19 20:35:19 | D | + x: None +24-11-19 20:35:19 | D | + y: None +24-11-19 20:35:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:19 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:20 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:20 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:20 | D | - range ratio = [ 1.0000] +24-11-19 20:35:20 | D | sum error = [ 0.3942] +24-11-19 20:35:20 | D | best error = [ 0.3942] +24-11-19 20:35:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:20 | D | sum error = [ 0.3909, 0.3897, 0.3906, 0.3927, 0.3999] +24-11-19 20:35:20 | D | best error = [ 0.3712, 0.3607, 0.3546, 0.3502, 0.3477] +24-11-19 20:35:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:20 | D | sum error = [ 0.4070, 0.4172, 0.4312, 0.4465, 0.4671] +24-11-19 20:35:20 | D | best error = [ 0.3459, 0.3447, 0.3439, 0.3432, 0.3428] +24-11-19 20:35:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:20 | D | sum error = [ 0.4898, 0.5137, 0.5443, 0.5763, 0.6105] +24-11-19 20:35:20 | D | best error = [ 0.3425, 0.3424, 0.3423, 0.3422, 0.3422] +24-11-19 20:35:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:20 | D | sum error = [ 0.6510, 0.6930, 0.7384, 0.7867, 0.8397] +24-11-19 20:35:20 | D | best error = [ 0.3421, 0.3421, 0.3420, 0.3420, 0.3420] +24-11-19 20:35:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:20 | D | sum error = [ 0.8960, 0.9556, 1.0188, 1.0868, 1.1584] +24-11-19 20:35:20 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:35:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:20 | D | sum error = [ 1.2343, 1.3139, 1.3991, 1.4893, 1.5833] +24-11-19 20:35:20 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:35:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:20 | D | sum error = [ 1.6839, 1.7882, 1.9001, 2.0167, 2.1409] +24-11-19 20:35:20 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:35:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:20 | D | sum error = [ 2.2699, 2.4061, 2.5502, 2.7020, 2.8600] +24-11-19 20:35:20 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:35:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:20 | D | sum error = [ 3.0273, 3.2006, 3.3836, 3.5757, 3.7780] +24-11-19 20:35:20 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:35:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:20 | D | sum error = [ 3.9882, 4.2086, 4.4403, 4.6815, 4.9349] +24-11-19 20:35:20 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:35:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:20 | D | sum error = [ 5.1994, 5.4761, 5.7639, 6.0655, 6.3803] +24-11-19 20:35:20 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:35:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:20 | D | sum error = [ 6.7097, 7.0524, 7.4095, 7.7821, 8.1700] +24-11-19 20:35:20 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:35:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:20 | D | sum error = [ 8.5750, 8.9957, 9.4333, 9.8896, 10.3630] +24-11-19 20:35:20 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:35:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:20 | D | sum error = [ 10.8545, 11.3647, 11.8940, 12.4436, 13.0115] +24-11-19 20:35:20 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:35:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:20 | D | sum error = [ 13.5995, 14.2082, 14.8379, 15.4896, 16.1632] +24-11-19 20:35:20 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:35:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:20 | D | sum error = [ 16.8598, 17.5796, 18.3221, 19.0880, 19.8773] +24-11-19 20:35:20 | D | best error = [ 0.3420, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:35:20 | D | + error = [0.3420] +24-11-19 20:35:20 | D | - Calibrating model.layers.20.mlp.up_proj.weight +24-11-19 20:35:20 | D | + w: sint8 +24-11-19 20:35:20 | D | + x: None +24-11-19 20:35:20 | D | + y: None +24-11-19 20:35:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:20 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:20 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:20 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:20 | D | - range ratio = [ 1.0000] +24-11-19 20:35:20 | D | sum error = [ 0.3499] +24-11-19 20:35:20 | D | best error = [ 0.3499] +24-11-19 20:35:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:22 | D | sum error = [ 0.3474, 0.3466, 0.3484, 0.3519, 0.3590] +24-11-19 20:35:22 | D | best error = [ 0.3257, 0.3160, 0.3109, 0.3081, 0.3065] +24-11-19 20:35:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:22 | D | sum error = [ 0.3676, 0.3806, 0.3960, 0.4143, 0.4362] +24-11-19 20:35:22 | D | best error = [ 0.3057, 0.3054, 0.3053, 0.3053, 0.3053] +24-11-19 20:35:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:22 | D | sum error = [ 0.4612, 0.4891, 0.5214, 0.5562, 0.5944] +24-11-19 20:35:22 | D | best error = [ 0.3053, 0.3053, 0.3053, 0.3053, 0.3053] +24-11-19 20:35:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:22 | D | sum error = [ 0.6371, 0.6826, 0.7320, 0.7837, 0.8390] +24-11-19 20:35:22 | D | best error = [ 0.3053, 0.3053, 0.3053, 0.3053, 0.3053] +24-11-19 20:35:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:22 | D | sum error = [ 0.8991, 0.9635, 1.0300, 1.1022, 1.1781] +24-11-19 20:35:22 | D | best error = [ 0.3053, 0.3053, 0.3053, 0.3053, 0.3053] +24-11-19 20:35:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:22 | D | sum error = [ 1.2597, 1.3450, 1.4353, 1.5307, 1.6313] +24-11-19 20:35:22 | D | best error = [ 0.3053, 0.3053, 0.3053, 0.3053, 0.3053] +24-11-19 20:35:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:22 | D | sum error = [ 1.7383, 1.8487, 1.9660, 2.0911, 2.2213] +24-11-19 20:35:22 | D | best error = [ 0.3053, 0.3053, 0.3053, 0.3053, 0.3053] +24-11-19 20:35:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:22 | D | sum error = [ 2.3567, 2.5020, 2.6533, 2.8108, 2.9775] +24-11-19 20:35:22 | D | best error = [ 0.3053, 0.3053, 0.3053, 0.3053, 0.3053] +24-11-19 20:35:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:22 | D | sum error = [ 3.1513, 3.3345, 3.5251, 3.7251, 3.9356] +24-11-19 20:35:22 | D | best error = [ 0.3053, 0.3053, 0.3053, 0.3053, 0.3053] +24-11-19 20:35:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:22 | D | sum error = [ 4.1544, 4.3823, 4.6212, 4.8696, 5.1307] +24-11-19 20:35:22 | D | best error = [ 0.3053, 0.3053, 0.3053, 0.3053, 0.3053] +24-11-19 20:35:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:22 | D | sum error = [ 5.3997, 5.6827, 5.9772, 6.2818, 6.6029] +24-11-19 20:35:22 | D | best error = [ 0.3053, 0.3053, 0.3053, 0.3053, 0.3053] +24-11-19 20:35:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:22 | D | sum error = [ 6.9351, 7.2798, 7.6355, 8.0065, 8.3908] +24-11-19 20:35:22 | D | best error = [ 0.3053, 0.3053, 0.3053, 0.3053, 0.3053] +24-11-19 20:35:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:22 | D | sum error = [ 8.7892, 9.2012, 9.6319, 10.0725, 10.5285] +24-11-19 20:35:22 | D | best error = [ 0.3053, 0.3053, 0.3053, 0.3053, 0.3053] +24-11-19 20:35:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:22 | D | sum error = [ 11.0024, 11.4923, 11.9984, 12.5167, 13.0573] +24-11-19 20:35:22 | D | best error = [ 0.3053, 0.3053, 0.3053, 0.3053, 0.3053] +24-11-19 20:35:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:22 | D | sum error = [ 13.6152, 14.1902, 14.7789, 15.3855, 16.0087] +24-11-19 20:35:22 | D | best error = [ 0.3053, 0.3053, 0.3053, 0.3053, 0.3053] +24-11-19 20:35:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:22 | D | sum error = [ 16.6579, 17.3217, 18.0007, 18.6986, 19.4143] +24-11-19 20:35:22 | D | best error = [ 0.3053, 0.3053, 0.3053, 0.3053, 0.3053] +24-11-19 20:35:22 | D | + error = [0.3053] +24-11-19 20:35:22 | D | - Calibrating model.layers.20.mlp.gate_proj.weight +24-11-19 20:35:22 | D | + w: sint8 +24-11-19 20:35:22 | D | + x: None +24-11-19 20:35:22 | D | + y: None +24-11-19 20:35:22 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:22 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:22 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:22 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:22 | D | - range ratio = [ 1.0000] +24-11-19 20:35:22 | D | sum error = [ 9.0694] +24-11-19 20:35:22 | D | best error = [ 9.0694] +24-11-19 20:35:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:23 | D | sum error = [ 8.9869, 8.9783, 9.0105, 9.1163, 9.2851] +24-11-19 20:35:23 | D | best error = [ 8.4123, 8.1683, 8.0391, 7.9659, 7.9266] +24-11-19 20:35:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:23 | D | sum error = [ 9.5321, 9.8504, 10.2552, 10.7273, 11.3057] +24-11-19 20:35:23 | D | best error = [ 7.9082, 7.9006, 7.8975, 7.8964, 7.8961] +24-11-19 20:35:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:23 | D | sum error = [ 11.9361, 12.6699, 13.5206, 14.4278, 15.4423] +24-11-19 20:35:23 | D | best error = [ 7.8960, 7.8960, 7.8960, 7.8960, 7.8960] +24-11-19 20:35:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:23 | D | sum error = [ 16.5347, 17.7013, 19.0068, 20.3585, 21.8505] +24-11-19 20:35:23 | D | best error = [ 7.8960, 7.8960, 7.8960, 7.8960, 7.8960] +24-11-19 20:35:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:23 | D | sum error = [ 23.4206, 25.0951, 26.9036, 28.8102, 30.8712] +24-11-19 20:35:23 | D | best error = [ 7.8960, 7.8960, 7.8960, 7.8960, 7.8960] +24-11-19 20:35:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:23 | D | sum error = [ 33.0291, 35.3436, 37.7805, 40.3977, 43.1420] +24-11-19 20:35:23 | D | best error = [ 7.8960, 7.8960, 7.8960, 7.8960, 7.8960] +24-11-19 20:35:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:23 | D | sum error = [ 46.0813, 49.2019, 52.4727, 55.9560, 59.6398] +24-11-19 20:35:23 | D | best error = [ 7.8960, 7.8960, 7.8960, 7.8960, 7.8960] +24-11-19 20:35:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:23 | D | sum error = [ 63.5453, 67.6760, 72.0348, 76.6635, 81.5520] +24-11-19 20:35:23 | D | best error = [ 7.8960, 7.8960, 7.8960, 7.8960, 7.8960] +24-11-19 20:35:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:23 | D | sum error = [ 86.7044, 92.1729, 97.9547, 104.0580, 110.4914] +24-11-19 20:35:23 | D | best error = [ 7.8960, 7.8960, 7.8960, 7.8960, 7.8960] +24-11-19 20:35:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:23 | D | sum error = [ 117.2978, 124.4816, 132.0252, 139.9754, 148.3764] +24-11-19 20:35:23 | D | best error = [ 7.8960, 7.8960, 7.8960, 7.8960, 7.8960] +24-11-19 20:35:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:23 | D | sum error = [ 157.2070, 166.5014, 176.2535, 186.5473, 197.3520] +24-11-19 20:35:23 | D | best error = [ 7.8960, 7.8960, 7.8960, 7.8960, 7.8960] +24-11-19 20:35:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:23 | D | sum error = [ 208.6661, 220.5671, 233.0959, 246.1996, 259.9474] +24-11-19 20:35:23 | D | best error = [ 7.8960, 7.8960, 7.8960, 7.8960, 7.8960] +24-11-19 20:35:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:23 | D | sum error = [ 274.3514, 289.3818, 305.1416, 321.6001, 338.8001] +24-11-19 20:35:23 | D | best error = [ 7.8960, 7.8960, 7.8960, 7.8960, 7.8960] +24-11-19 20:35:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:23 | D | sum error = [ 356.7684, 375.5021, 395.0197, 415.3292, 436.4429] +24-11-19 20:35:23 | D | best error = [ 7.8960, 7.8960, 7.8960, 7.8960, 7.8960] +24-11-19 20:35:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:23 | D | sum error = [ 458.3873, 481.1928, 504.8673, 529.4019, 554.8199] +24-11-19 20:35:23 | D | best error = [ 7.8960, 7.8960, 7.8960, 7.8960, 7.8960] +24-11-19 20:35:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:23 | D | sum error = [ 581.0852, 608.2473, 636.2970, 665.2609, 695.1105] +24-11-19 20:35:23 | D | best error = [ 7.8960, 7.8960, 7.8960, 7.8960, 7.8960] +24-11-19 20:35:23 | D | + error = [7.8960] +24-11-19 20:35:23 | D | - Calibrating model.layers.20.mlp.down_proj.weight +24-11-19 20:35:23 | D | + w: sint8 +24-11-19 20:35:23 | D | + x: None +24-11-19 20:35:23 | D | + y: None +24-11-19 20:35:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:23 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:23 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:24 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:24 | D | - range ratio = [ 1.0000] +24-11-19 20:35:24 | D | sum error = [ 0.9903] +24-11-19 20:35:24 | D | best error = [ 0.9903] +24-11-19 20:35:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:25 | D | sum error = [ 0.9806, 0.9747, 0.9712, 0.9716, 0.9735] +24-11-19 20:35:25 | D | best error = [ 0.9506, 0.9307, 0.9181, 0.9091, 0.9021] +24-11-19 20:35:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:25 | D | sum error = [ 0.9817, 0.9969, 1.0155, 1.0437, 1.0765] +24-11-19 20:35:25 | D | best error = [ 0.8971, 0.8933, 0.8910, 0.8896, 0.8887] +24-11-19 20:35:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:25 | D | sum error = [ 1.1176, 1.1663, 1.2248, 1.2946, 1.3705] +24-11-19 20:35:25 | D | best error = [ 0.8880, 0.8877, 0.8875, 0.8874, 0.8874] +24-11-19 20:35:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:25 | D | sum error = [ 1.4541, 1.5505, 1.6561, 1.7717, 1.8960] +24-11-19 20:35:25 | D | best error = [ 0.8873, 0.8873, 0.8873, 0.8873, 0.8873] +24-11-19 20:35:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:25 | D | sum error = [ 2.0303, 2.1741, 2.3287, 2.4971, 2.6749] +24-11-19 20:35:25 | D | best error = [ 0.8873, 0.8873, 0.8873, 0.8873, 0.8873] +24-11-19 20:35:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:25 | D | sum error = [ 2.8628, 3.0616, 3.2741, 3.5012, 3.7402] +24-11-19 20:35:25 | D | best error = [ 0.8873, 0.8873, 0.8873, 0.8873, 0.8873] +24-11-19 20:35:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:25 | D | sum error = [ 3.9924, 4.2612, 4.5433, 4.8404, 5.1558] +24-11-19 20:35:25 | D | best error = [ 0.8873, 0.8873, 0.8873, 0.8873, 0.8873] +24-11-19 20:35:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:25 | D | sum error = [ 5.4882, 5.8373, 6.2065, 6.5972, 7.0037] +24-11-19 20:35:25 | D | best error = [ 0.8873, 0.8873, 0.8873, 0.8873, 0.8873] +24-11-19 20:35:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:25 | D | sum error = [ 7.4359, 7.8905, 8.3675, 8.8683, 9.3957] +24-11-19 20:35:25 | D | best error = [ 0.8873, 0.8873, 0.8873, 0.8873, 0.8873] +24-11-19 20:35:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:25 | D | sum error = [ 9.9475, 10.5261, 11.1347, 11.7709, 12.4400] +24-11-19 20:35:25 | D | best error = [ 0.8873, 0.8873, 0.8873, 0.8873, 0.8873] +24-11-19 20:35:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:25 | D | sum error = [ 13.1375, 13.8697, 14.6375, 15.4411, 16.2799] +24-11-19 20:35:25 | D | best error = [ 0.8873, 0.8873, 0.8873, 0.8873, 0.8873] +24-11-19 20:35:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:25 | D | sum error = [ 17.1580, 18.0744, 19.0325, 20.0329, 21.0742] +24-11-19 20:35:25 | D | best error = [ 0.8873, 0.8873, 0.8873, 0.8873, 0.8873] +24-11-19 20:35:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:25 | D | sum error = [ 22.1599, 23.2933, 24.4744, 25.7015, 26.9770] +24-11-19 20:35:25 | D | best error = [ 0.8873, 0.8873, 0.8873, 0.8873, 0.8873] +24-11-19 20:35:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:25 | D | sum error = [ 28.3063, 29.6852, 31.1173, 32.6021, 34.1447] +24-11-19 20:35:25 | D | best error = [ 0.8873, 0.8873, 0.8873, 0.8873, 0.8873] +24-11-19 20:35:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:25 | D | sum error = [ 35.7458, 37.4021, 39.1166, 40.8931, 42.7295] +24-11-19 20:35:25 | D | best error = [ 0.8873, 0.8873, 0.8873, 0.8873, 0.8873] +24-11-19 20:35:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:25 | D | sum error = [ 44.6273, 46.5876, 48.6103, 50.6967, 52.8500] +24-11-19 20:35:25 | D | best error = [ 0.8873, 0.8873, 0.8873, 0.8873, 0.8873] +24-11-19 20:35:25 | D | + error = [0.8873] +24-11-19 20:35:25 | D | - Quantizing model.layers.20.self_attn.q_proj.weight +24-11-19 20:35:26 | D | - Quantizing model.layers.20.self_attn.k_proj.weight +24-11-19 20:35:27 | D | - Quantizing model.layers.20.self_attn.v_proj.weight +24-11-19 20:35:28 | D | - Quantizing model.layers.20.self_attn.o_proj.weight +24-11-19 20:35:29 | D | - Quantizing model.layers.20.mlp.up_proj.weight +24-11-19 20:35:30 | D | - Quantizing model.layers.20.mlp.gate_proj.weight +24-11-19 20:35:30 | D | - Quantizing model.layers.20.mlp.down_proj.weight +24-11-19 20:35:41 | D | - Quantizing layer model.layers.21 +24-11-19 20:35:41 | D | - Calibrating model.layers.21.self_attn.q_proj.weight +24-11-19 20:35:41 | D | + w: sint8 +24-11-19 20:35:41 | D | + x: None +24-11-19 20:35:41 | D | + y: None +24-11-19 20:35:41 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:35:41 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:35:41 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:35:41 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:35:42 | D | - range ratio = [ 1.0000] +24-11-19 20:35:42 | D | sum error = [ 4.4958] +24-11-19 20:35:42 | D | best error = [ 4.4958] +24-11-19 20:35:56 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:56 | D | sum error = [ 4.4704, 4.3697, 4.4700, 4.4859, 4.6402] +24-11-19 20:35:56 | D | best error = [ 4.4704, 4.3697, 4.3697, 4.3697, 4.3697] +24-11-19 20:35:56 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:56 | D | sum error = [ 4.6566, 4.7701, 5.1943, 5.3149, 5.5797] +24-11-19 20:35:56 | D | best error = [ 4.3697, 4.3697, 4.3697, 4.3697, 4.3697] +24-11-19 20:35:56 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:56 | D | sum error = [ 5.9108, 6.2656, 6.7206, 7.1812, 7.7542] +24-11-19 20:35:56 | D | best error = [ 4.3697, 4.3697, 4.3697, 4.3697, 4.3697] +24-11-19 20:35:56 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:56 | D | sum error = [ 8.3808, 9.1789, 9.9425, 10.5520, 11.6755] +24-11-19 20:35:56 | D | best error = [ 4.3697, 4.3697, 4.3697, 4.3697, 4.3697] +24-11-19 20:35:56 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:56 | D | sum error = [ 12.7196, 13.8984, 15.0515, 16.3959, 17.9051] +24-11-19 20:35:56 | D | best error = [ 4.3697, 4.3697, 4.3697, 4.3697, 4.3697] +24-11-19 20:35:56 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:56 | D | sum error = [ 19.4078, 20.9870, 22.5732, 24.4045, 26.4881] +24-11-19 20:35:56 | D | best error = [ 4.3697, 4.3697, 4.3697, 4.3697, 4.3697] +24-11-19 20:35:56 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:56 | D | sum error = [ 28.4879, 30.9144, 33.1906, 36.0132, 38.8786] +24-11-19 20:35:56 | D | best error = [ 4.3697, 4.3697, 4.3697, 4.3697, 4.3697] +24-11-19 20:35:56 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:56 | D | sum error = [ 42.0212, 45.4562, 49.1047, 53.2855, 57.2971] +24-11-19 20:35:56 | D | best error = [ 4.3697, 4.3697, 4.3697, 4.3697, 4.3697] +24-11-19 20:35:56 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:56 | D | sum error = [ 61.8521, 67.1245, 72.5771, 78.5045, 84.9740] +24-11-19 20:35:56 | D | best error = [ 4.3697, 4.3697, 4.3697, 4.3697, 4.3697] +24-11-19 20:35:56 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:56 | D | sum error = [ 91.9488, 99.6069, 107.9301, 116.9538, 126.7103] +24-11-19 20:35:56 | D | best error = [ 4.3697, 4.3697, 4.3697, 4.3697, 4.3697] +24-11-19 20:35:56 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:56 | D | sum error = [ 137.2593, 148.6181, 161.1039, 174.4260, 188.5907] +24-11-19 20:35:56 | D | best error = [ 4.3697, 4.3697, 4.3697, 4.3697, 4.3697] +24-11-19 20:35:56 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:56 | D | sum error = [ 204.4837, 221.4130, 239.6805, 259.9264, 281.5840] +24-11-19 20:35:56 | D | best error = [ 4.3697, 4.3697, 4.3697, 4.3697, 4.3697] +24-11-19 20:35:56 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:56 | D | sum error = [ 305.3007, 330.9169, 358.5177, 388.4724, 421.3902] +24-11-19 20:35:56 | D | best error = [ 4.3697, 4.3697, 4.3697, 4.3697, 4.3697] +24-11-19 20:35:56 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:56 | D | sum error = [ 456.4619, 494.8824, 536.4865, 581.6122, 630.2372] +24-11-19 20:35:56 | D | best error = [ 4.3697, 4.3697, 4.3697, 4.3697, 4.3697] +24-11-19 20:35:56 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:56 | D | sum error = [ 683.4118, 740.5227, 801.3828, 866.9423, 936.6662] +24-11-19 20:35:56 | D | best error = [ 4.3697, 4.3697, 4.3697, 4.3697, 4.3697] +24-11-19 20:35:56 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:56 | D | sum error = [ 1010.5794, 1088.6153, 1169.8299, 1253.1668, 1338.1822] +24-11-19 20:35:56 | D | best error = [ 4.3697, 4.3697, 4.3697, 4.3697, 4.3697] +24-11-19 20:35:56 | D | + error = [4.3697] +24-11-19 20:35:56 | D | - Calibrating model.layers.21.self_attn.k_proj.weight +24-11-19 20:35:56 | D | + w: sint8 +24-11-19 20:35:56 | D | + x: None +24-11-19 20:35:56 | D | + y: None +24-11-19 20:35:56 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:35:56 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:56 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:57 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:57 | D | - range ratio = [ 1.0000] +24-11-19 20:35:57 | D | sum error = [ 4.6933] +24-11-19 20:35:57 | D | best error = [ 4.6933] +24-11-19 20:36:11 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:11 | D | sum error = [ 4.2762, 4.4943, 4.2906, 4.5502, 4.7469] +24-11-19 20:36:11 | D | best error = [ 4.2762, 4.2762, 4.2762, 4.2762, 4.2762] +24-11-19 20:36:11 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:11 | D | sum error = [ 4.5603, 4.7954, 4.7152, 5.3073, 5.7426] +24-11-19 20:36:11 | D | best error = [ 4.2762, 4.2762, 4.2762, 4.2762, 4.2762] +24-11-19 20:36:11 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:11 | D | sum error = [ 7.3446, 6.3742, 6.5142, 6.7277, 7.2034] +24-11-19 20:36:11 | D | best error = [ 4.2762, 4.2762, 4.2762, 4.2762, 4.2762] +24-11-19 20:36:11 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:11 | D | sum error = [ 8.1091, 9.2742, 9.7458, 10.9402, 11.6099] +24-11-19 20:36:11 | D | best error = [ 4.2762, 4.2762, 4.2762, 4.2762, 4.2762] +24-11-19 20:36:11 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:11 | D | sum error = [ 12.9024, 13.8188, 15.7031, 16.6180, 17.8697] +24-11-19 20:36:11 | D | best error = [ 4.2762, 4.2762, 4.2762, 4.2762, 4.2762] +24-11-19 20:36:11 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:11 | D | sum error = [ 19.5357, 22.0941, 24.3891, 26.6354, 29.1309] +24-11-19 20:36:11 | D | best error = [ 4.2762, 4.2762, 4.2762, 4.2762, 4.2762] +24-11-19 20:36:11 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:11 | D | sum error = [ 32.7689, 35.2918, 37.4325, 40.9475, 44.4393] +24-11-19 20:36:11 | D | best error = [ 4.2762, 4.2762, 4.2762, 4.2762, 4.2762] +24-11-19 20:36:11 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:11 | D | sum error = [ 47.4809, 52.6541, 57.2261, 62.7861, 68.2141] +24-11-19 20:36:11 | D | best error = [ 4.2762, 4.2762, 4.2762, 4.2762, 4.2762] +24-11-19 20:36:11 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:11 | D | sum error = [ 73.3717, 80.2113, 86.3561, 93.5481, 100.2639] +24-11-19 20:36:11 | D | best error = [ 4.2762, 4.2762, 4.2762, 4.2762, 4.2762] +24-11-19 20:36:11 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:11 | D | sum error = [ 108.7402, 117.4803, 125.2175, 134.9827, 143.9867] +24-11-19 20:36:11 | D | best error = [ 4.2762, 4.2762, 4.2762, 4.2762, 4.2762] +24-11-19 20:36:11 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:11 | D | sum error = [ 153.7406, 164.9447, 177.3050, 190.1928, 205.2536] +24-11-19 20:36:11 | D | best error = [ 4.2762, 4.2762, 4.2762, 4.2762, 4.2762] +24-11-19 20:36:11 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:11 | D | sum error = [ 220.2114, 237.7934, 256.8650, 276.8176, 299.3094] +24-11-19 20:36:11 | D | best error = [ 4.2762, 4.2762, 4.2762, 4.2762, 4.2762] +24-11-19 20:36:11 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:11 | D | sum error = [ 324.3655, 350.6289, 378.2233, 407.4426, 441.1377] +24-11-19 20:36:11 | D | best error = [ 4.2762, 4.2762, 4.2762, 4.2762, 4.2762] +24-11-19 20:36:11 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:11 | D | sum error = [ 476.5255, 515.9921, 557.0971, 601.7322, 651.1209] +24-11-19 20:36:11 | D | best error = [ 4.2762, 4.2762, 4.2762, 4.2762, 4.2762] +24-11-19 20:36:11 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:11 | D | sum error = [ 703.3737, 759.9390, 823.1153, 889.5445, 958.2185] +24-11-19 20:36:11 | D | best error = [ 4.2762, 4.2762, 4.2762, 4.2762, 4.2762] +24-11-19 20:36:11 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:11 | D | sum error = [ 1032.5970, 1108.5706, 1187.9052, 1271.7715, 1353.1108] +24-11-19 20:36:11 | D | best error = [ 4.2762, 4.2762, 4.2762, 4.2762, 4.2762] +24-11-19 20:36:11 | D | + error = [4.2762] +24-11-19 20:36:12 | D | - Calibrating model.layers.21.self_attn.v_proj.weight +24-11-19 20:36:12 | D | + w: sint8 +24-11-19 20:36:12 | D | + x: None +24-11-19 20:36:12 | D | + y: None +24-11-19 20:36:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:12 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:36:12 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:36:12 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:36:12 | D | - range ratio = [ 1.0000] +24-11-19 20:36:12 | D | sum error = [ 1.7952] +24-11-19 20:36:12 | D | best error = [ 1.7952] +24-11-19 20:36:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:12 | D | sum error = [ 1.7840, 1.7698, 1.7839, 1.8131, 1.8351] +24-11-19 20:36:12 | D | best error = [ 1.6670, 1.6125, 1.5854, 1.5722, 1.5641] +24-11-19 20:36:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:12 | D | sum error = [ 1.8772, 1.9552, 2.0486, 2.1261, 2.2457] +24-11-19 20:36:12 | D | best error = [ 1.5593, 1.5576, 1.5571, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:12 | D | sum error = [ 2.3630, 2.5210, 2.7043, 2.8830, 3.0898] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:12 | D | sum error = [ 3.3169, 3.5497, 3.7950, 4.0695, 4.3750] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:12 | D | sum error = [ 4.6695, 4.9906, 5.3453, 5.7353, 6.1225] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:12 | D | sum error = [ 6.5550, 6.9932, 7.4679, 7.9596, 8.4738] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:12 | D | sum error = [ 9.0383, 9.6168, 10.2157, 10.8765, 11.5572] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:12 | D | sum error = [ 12.2718, 13.0223, 13.8284, 14.6554, 15.5376] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:12 | D | sum error = [ 16.4432, 17.4096, 18.4023, 19.4825, 20.5836] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:12 | D | sum error = [ 21.7571, 22.9695, 24.2458, 25.5770, 26.9631] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:12 | D | sum error = [ 28.4143, 29.9336, 31.5163, 33.1610, 34.8905] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:12 | D | sum error = [ 36.6782, 38.5569, 40.5080, 42.5257, 44.6416] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:12 | D | sum error = [ 46.8314, 49.1081, 51.4668, 53.9307, 56.4732] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:12 | D | sum error = [ 59.1214, 61.8586, 64.6892, 67.6321, 70.6689] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:12 | D | sum error = [ 73.8126, 77.0549, 80.4004, 83.8615, 87.4368] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:12 | D | sum error = [ 91.1150, 94.9232, 98.8398, 102.8747, 107.0257] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | + error = [1.5570] +24-11-19 20:36:12 | D | - Calibrating model.layers.21.self_attn.o_proj.weight +24-11-19 20:36:12 | D | + w: sint8 +24-11-19 20:36:12 | D | + x: None +24-11-19 20:36:12 | D | + y: None +24-11-19 20:36:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:12 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:36:12 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:36:12 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:36:12 | D | - range ratio = [ 1.0000] +24-11-19 20:36:12 | D | sum error = [ 0.5899] +24-11-19 20:36:12 | D | best error = [ 0.5899] +24-11-19 20:36:13 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:13 | D | sum error = [ 0.5811, 0.5813, 0.5784, 0.5789, 0.5814] +24-11-19 20:36:13 | D | best error = [ 0.5375, 0.5164, 0.5026, 0.4939, 0.4873] +24-11-19 20:36:13 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:13 | D | sum error = [ 0.5868, 0.5924, 0.6037, 0.6165, 0.6325] +24-11-19 20:36:13 | D | best error = [ 0.4827, 0.4788, 0.4761, 0.4739, 0.4723] +24-11-19 20:36:13 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:13 | D | sum error = [ 0.6550, 0.6749, 0.7016, 0.7346, 0.7693] +24-11-19 20:36:13 | D | best error = [ 0.4711, 0.4702, 0.4695, 0.4690, 0.4685] +24-11-19 20:36:13 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:13 | D | sum error = [ 0.8085, 0.8538, 0.9033, 0.9548, 1.0130] +24-11-19 20:36:13 | D | best error = [ 0.4681, 0.4679, 0.4678, 0.4676, 0.4675] +24-11-19 20:36:13 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:13 | D | sum error = [ 1.0760, 1.1464, 1.2195, 1.2982, 1.3856] +24-11-19 20:36:13 | D | best error = [ 0.4675, 0.4674, 0.4673, 0.4672, 0.4672] +24-11-19 20:36:13 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:13 | D | sum error = [ 1.4736, 1.5694, 1.6721, 1.7826, 1.8993] +24-11-19 20:36:13 | D | best error = [ 0.4672, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:36:13 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:13 | D | sum error = [ 2.0222, 2.1523, 2.2929, 2.4414, 2.5938] +24-11-19 20:36:13 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:36:13 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:13 | D | sum error = [ 2.7567, 2.9292, 3.1144, 3.3082, 3.5103] +24-11-19 20:36:13 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:36:13 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:13 | D | sum error = [ 3.7281, 3.9547, 4.1939, 4.4457, 4.7110] +24-11-19 20:36:13 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:36:13 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:13 | D | sum error = [ 4.9919, 5.2883, 5.5983, 5.9249, 6.2657] +24-11-19 20:36:13 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:36:13 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:13 | D | sum error = [ 6.6267, 7.0021, 7.3999, 7.8163, 8.2523] +24-11-19 20:36:13 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:36:13 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:13 | D | sum error = [ 8.7100, 9.1877, 9.6894, 10.2136, 10.7635] +24-11-19 20:36:13 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:36:13 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:13 | D | sum error = [ 11.3350, 11.9313, 12.5537, 13.2012, 13.8764] +24-11-19 20:36:13 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:36:13 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:13 | D | sum error = [ 14.5807, 15.3123, 16.0734, 16.8652, 17.6847] +24-11-19 20:36:13 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:36:13 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:13 | D | sum error = [ 18.5362, 19.4203, 20.3349, 21.2833, 22.2654] +24-11-19 20:36:13 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:36:13 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:13 | D | sum error = [ 23.2819, 24.3345, 25.4234, 26.5474, 27.7117] +24-11-19 20:36:13 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:36:13 | D | + error = [0.4671] +24-11-19 20:36:13 | D | - Calibrating model.layers.21.mlp.up_proj.weight +24-11-19 20:36:13 | D | + w: sint8 +24-11-19 20:36:13 | D | + x: None +24-11-19 20:36:13 | D | + y: None +24-11-19 20:36:13 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:13 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:36:13 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:36:13 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:36:13 | D | - range ratio = [ 1.0000] +24-11-19 20:36:13 | D | sum error = [ 0.3655] +24-11-19 20:36:13 | D | best error = [ 0.3655] +24-11-19 20:36:14 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:14 | D | sum error = [ 0.3627, 0.3623, 0.3644, 0.3688, 0.3757] +24-11-19 20:36:14 | D | best error = [ 0.3385, 0.3280, 0.3227, 0.3195, 0.3178] +24-11-19 20:36:14 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:14 | D | sum error = [ 0.3841, 0.3976, 0.4137, 0.4342, 0.4573] +24-11-19 20:36:14 | D | best error = [ 0.3170, 0.3167, 0.3165, 0.3165, 0.3164] +24-11-19 20:36:14 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:14 | D | sum error = [ 0.4828, 0.5126, 0.5456, 0.5824, 0.6238] +24-11-19 20:36:14 | D | best error = [ 0.3164, 0.3164, 0.3164, 0.3164, 0.3164] +24-11-19 20:36:14 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:14 | D | sum error = [ 0.6672, 0.7138, 0.7648, 0.8192, 0.8783] +24-11-19 20:36:14 | D | best error = [ 0.3164, 0.3164, 0.3164, 0.3164, 0.3164] +24-11-19 20:36:14 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:14 | D | sum error = [ 0.9399, 1.0054, 1.0772, 1.1521, 1.2308] +24-11-19 20:36:14 | D | best error = [ 0.3164, 0.3164, 0.3164, 0.3164, 0.3164] +24-11-19 20:36:14 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:14 | D | sum error = [ 1.3149, 1.4051, 1.4992, 1.5995, 1.7039] +24-11-19 20:36:14 | D | best error = [ 0.3164, 0.3164, 0.3164, 0.3164, 0.3164] +24-11-19 20:36:14 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:14 | D | sum error = [ 1.8159, 1.9321, 2.0547, 2.1852, 2.3215] +24-11-19 20:36:14 | D | best error = [ 0.3164, 0.3164, 0.3164, 0.3164, 0.3164] +24-11-19 20:36:14 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:14 | D | sum error = [ 2.4643, 2.6154, 2.7726, 2.9374, 3.1126] +24-11-19 20:36:14 | D | best error = [ 0.3164, 0.3164, 0.3164, 0.3164, 0.3164] +24-11-19 20:36:14 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:14 | D | sum error = [ 3.2945, 3.4852, 3.6853, 3.8922, 4.1120] +24-11-19 20:36:14 | D | best error = [ 0.3164, 0.3164, 0.3164, 0.3164, 0.3164] +24-11-19 20:36:14 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:14 | D | sum error = [ 4.3416, 4.5786, 4.8285, 5.0886, 5.3615] +24-11-19 20:36:14 | D | best error = [ 0.3164, 0.3164, 0.3164, 0.3164, 0.3164] +24-11-19 20:36:14 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:14 | D | sum error = [ 5.6467, 5.9395, 6.2483, 6.5683, 6.9015] +24-11-19 20:36:14 | D | best error = [ 0.3164, 0.3164, 0.3164, 0.3164, 0.3164] +24-11-19 20:36:14 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:14 | D | sum error = [ 7.2471, 7.6083, 7.9793, 8.3647, 8.7676] +24-11-19 20:36:14 | D | best error = [ 0.3164, 0.3164, 0.3164, 0.3164, 0.3164] +24-11-19 20:36:14 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:14 | D | sum error = [ 9.1840, 9.6118, 10.0577, 10.5207, 10.9967] +24-11-19 20:36:14 | D | best error = [ 0.3164, 0.3164, 0.3164, 0.3164, 0.3164] +24-11-19 20:36:14 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:14 | D | sum error = [ 11.4922, 12.0002, 12.5253, 13.0659, 13.6264] +24-11-19 20:36:14 | D | best error = [ 0.3164, 0.3164, 0.3164, 0.3164, 0.3164] +24-11-19 20:36:14 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:14 | D | sum error = [ 14.2052, 14.7992, 15.4126, 16.0441, 16.6879] +24-11-19 20:36:14 | D | best error = [ 0.3164, 0.3164, 0.3164, 0.3164, 0.3164] +24-11-19 20:36:14 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:14 | D | sum error = [ 17.3580, 18.0441, 18.7515, 19.4781, 20.2232] +24-11-19 20:36:14 | D | best error = [ 0.3164, 0.3164, 0.3164, 0.3164, 0.3164] +24-11-19 20:36:14 | D | + error = [0.3164] +24-11-19 20:36:15 | D | - Calibrating model.layers.21.mlp.gate_proj.weight +24-11-19 20:36:15 | D | + w: sint8 +24-11-19 20:36:15 | D | + x: None +24-11-19 20:36:15 | D | + y: None +24-11-19 20:36:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:15 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:36:15 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:36:15 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:36:15 | D | - range ratio = [ 1.0000] +24-11-19 20:36:15 | D | sum error = [ 9.5249] +24-11-19 20:36:15 | D | best error = [ 9.5249] +24-11-19 20:36:16 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:16 | D | sum error = [ 9.4767, 9.4156, 9.4596, 9.5680, 9.7495] +24-11-19 20:36:16 | D | best error = [ 8.8085, 8.5325, 8.3858, 8.3079, 8.2616] +24-11-19 20:36:16 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:16 | D | sum error = [ 10.0182, 10.3434, 10.7751, 11.2848, 11.8735] +24-11-19 20:36:16 | D | best error = [ 8.2403, 8.2303, 8.2266, 8.2255, 8.2252] +24-11-19 20:36:16 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:16 | D | sum error = [ 12.5656, 13.3105, 14.1926, 15.1486, 16.2132] +24-11-19 20:36:16 | D | best error = [ 8.2252, 8.2252, 8.2252, 8.2252, 8.2252] +24-11-19 20:36:16 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:16 | D | sum error = [ 17.3586, 18.6171, 19.9743, 21.4338, 22.9993] +24-11-19 20:36:16 | D | best error = [ 8.2252, 8.2252, 8.2252, 8.2252, 8.2252] +24-11-19 20:36:16 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:16 | D | sum error = [ 24.6507, 26.4258, 28.3499, 30.3495, 32.5225] +24-11-19 20:36:16 | D | best error = [ 8.2252, 8.2252, 8.2252, 8.2252, 8.2252] +24-11-19 20:36:16 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:16 | D | sum error = [ 34.8220, 37.2315, 39.8490, 42.5568, 45.4575] +24-11-19 20:36:16 | D | best error = [ 8.2252, 8.2252, 8.2252, 8.2252, 8.2252] +24-11-19 20:36:16 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:16 | D | sum error = [ 48.5479, 51.7949, 55.2517, 58.9104, 62.7668] +24-11-19 20:36:16 | D | best error = [ 8.2252, 8.2252, 8.2252, 8.2252, 8.2252] +24-11-19 20:36:16 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:16 | D | sum error = [ 66.8655, 71.1816, 75.7476, 80.5595, 85.6907] +24-11-19 20:36:16 | D | best error = [ 8.2252, 8.2252, 8.2252, 8.2252, 8.2252] +24-11-19 20:36:16 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:16 | D | sum error = [ 91.0896, 96.7913, 102.8376, 109.1880, 115.9334] +24-11-19 20:36:16 | D | best error = [ 8.2252, 8.2252, 8.2252, 8.2252, 8.2252] +24-11-19 20:36:16 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:16 | D | sum error = [ 123.0388, 130.5105, 138.4366, 146.7591, 155.5347] +24-11-19 20:36:16 | D | best error = [ 8.2252, 8.2252, 8.2252, 8.2252, 8.2252] +24-11-19 20:36:16 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:16 | D | sum error = [ 164.7503, 174.4885, 184.7436, 195.5139, 206.8535] +24-11-19 20:36:16 | D | best error = [ 8.2252, 8.2252, 8.2252, 8.2252, 8.2252] +24-11-19 20:36:16 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:16 | D | sum error = [ 218.7807, 231.2769, 244.3856, 258.0954, 272.5176] +24-11-19 20:36:16 | D | best error = [ 8.2252, 8.2252, 8.2252, 8.2252, 8.2252] +24-11-19 20:36:16 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:16 | D | sum error = [ 287.6100, 303.3976, 319.9156, 337.2279, 355.2702] +24-11-19 20:36:16 | D | best error = [ 8.2252, 8.2252, 8.2252, 8.2252, 8.2252] +24-11-19 20:36:16 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:16 | D | sum error = [ 374.1304, 393.7765, 414.2360, 435.5388, 457.7109] +24-11-19 20:36:16 | D | best error = [ 8.2252, 8.2252, 8.2252, 8.2252, 8.2252] +24-11-19 20:36:16 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:16 | D | sum error = [ 480.7535, 504.6576, 529.4932, 555.1848, 581.7834] +24-11-19 20:36:16 | D | best error = [ 8.2252, 8.2252, 8.2252, 8.2252, 8.2252] +24-11-19 20:36:16 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:16 | D | sum error = [ 609.3195, 637.7365, 667.0763, 697.3734, 728.5716] +24-11-19 20:36:16 | D | best error = [ 8.2252, 8.2252, 8.2252, 8.2252, 8.2252] +24-11-19 20:36:16 | D | + error = [8.2252] +24-11-19 20:36:16 | D | - Calibrating model.layers.21.mlp.down_proj.weight +24-11-19 20:36:16 | D | + w: sint8 +24-11-19 20:36:16 | D | + x: None +24-11-19 20:36:16 | D | + y: None +24-11-19 20:36:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:16 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:36:17 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:36:17 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:36:17 | D | - range ratio = [ 1.0000] +24-11-19 20:36:17 | D | sum error = [ 1.0801] +24-11-19 20:36:17 | D | best error = [ 1.0801] +24-11-19 20:36:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:18 | D | sum error = [ 1.0729, 1.0648, 1.0612, 1.0621, 1.0680] +24-11-19 20:36:18 | D | best error = [ 1.0384, 1.0165, 1.0024, 0.9920, 0.9840] +24-11-19 20:36:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:18 | D | sum error = [ 1.0810, 1.0990, 1.1232, 1.1596, 1.1998] +24-11-19 20:36:18 | D | best error = [ 0.9788, 0.9750, 0.9721, 0.9702, 0.9690] +24-11-19 20:36:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:18 | D | sum error = [ 1.2549, 1.3126, 1.3846, 1.4640, 1.5576] +24-11-19 20:36:18 | D | best error = [ 0.9685, 0.9680, 0.9677, 0.9675, 0.9674] +24-11-19 20:36:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:18 | D | sum error = [ 1.6565, 1.7681, 1.8914, 2.0244, 2.1670] +24-11-19 20:36:18 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:36:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:18 | D | sum error = [ 2.3236, 2.4859, 2.6651, 2.8506, 3.0535] +24-11-19 20:36:18 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:36:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:18 | D | sum error = [ 3.2650, 3.4913, 3.7315, 3.9844, 4.2532] +24-11-19 20:36:18 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:36:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:18 | D | sum error = [ 4.5358, 4.8393, 5.1563, 5.4905, 5.8434] +24-11-19 20:36:18 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:36:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:18 | D | sum error = [ 6.2154, 6.6074, 7.0195, 7.4586, 7.9206] +24-11-19 20:36:18 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:36:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:18 | D | sum error = [ 8.4036, 8.9171, 9.4526, 10.0181, 10.6109] +24-11-19 20:36:18 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:36:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:18 | D | sum error = [ 11.2363, 11.8910, 12.5775, 13.2974, 14.0528] +24-11-19 20:36:18 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:36:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:18 | D | sum error = [ 14.8430, 15.6684, 16.5339, 17.4377, 18.3833] +24-11-19 20:36:18 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:36:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:18 | D | sum error = [ 19.3724, 20.4024, 21.4796, 22.6050, 23.7770] +24-11-19 20:36:18 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:36:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:18 | D | sum error = [ 24.9979, 26.2727, 27.6000, 28.9783, 30.4130] +24-11-19 20:36:18 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:36:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:18 | D | sum error = [ 31.9030, 33.4518, 35.0574, 36.7207, 38.4500] +24-11-19 20:36:18 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:36:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:18 | D | sum error = [ 40.2433, 42.1000, 44.0200, 46.0069, 48.0609] +24-11-19 20:36:18 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:36:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:18 | D | sum error = [ 50.1856, 52.3810, 54.6488, 56.9857, 59.3940] +24-11-19 20:36:18 | D | best error = [ 0.9674, 0.9674, 0.9674, 0.9674, 0.9674] +24-11-19 20:36:18 | D | + error = [0.9674] +24-11-19 20:36:18 | D | - Quantizing model.layers.21.self_attn.q_proj.weight +24-11-19 20:36:19 | D | - Quantizing model.layers.21.self_attn.k_proj.weight +24-11-19 20:36:21 | D | - Quantizing model.layers.21.self_attn.v_proj.weight +24-11-19 20:36:22 | D | - Quantizing model.layers.21.self_attn.o_proj.weight +24-11-19 20:36:23 | D | - Quantizing model.layers.21.mlp.up_proj.weight +24-11-19 20:36:27 | D | - Quantizing model.layers.21.mlp.gate_proj.weight +24-11-19 20:36:29 | D | - Quantizing model.layers.21.mlp.down_proj.weight +24-11-19 20:36:38 | D | - Quantizing layer model.layers.22 +24-11-19 20:36:38 | D | - Calibrating model.layers.22.self_attn.q_proj.weight +24-11-19 20:36:38 | D | + w: sint8 +24-11-19 20:36:38 | D | + x: None +24-11-19 20:36:38 | D | + y: None +24-11-19 20:36:38 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:36:38 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:36:39 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:36:39 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:36:39 | D | - range ratio = [ 1.0000] +24-11-19 20:36:39 | D | sum error = [ 4.5998] +24-11-19 20:36:39 | D | best error = [ 4.5998] +24-11-19 20:36:53 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:53 | D | sum error = [ 4.5853, 4.5368, 4.6364, 4.6307, 4.6598] +24-11-19 20:36:53 | D | best error = [ 4.5853, 4.5368, 4.5368, 4.5368, 4.5368] +24-11-19 20:36:53 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:53 | D | sum error = [ 4.8093, 5.0113, 5.2385, 5.5715, 5.8309] +24-11-19 20:36:53 | D | best error = [ 4.5368, 4.5368, 4.5368, 4.5368, 4.5368] +24-11-19 20:36:53 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:53 | D | sum error = [ 6.3334, 6.6737, 7.5176, 7.7829, 8.3173] +24-11-19 20:36:53 | D | best error = [ 4.5368, 4.5368, 4.5368, 4.5368, 4.5368] +24-11-19 20:36:53 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:53 | D | sum error = [ 9.0286, 9.7427, 10.6372, 11.5673, 12.4952] +24-11-19 20:36:53 | D | best error = [ 4.5368, 4.5368, 4.5368, 4.5368, 4.5368] +24-11-19 20:36:53 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:53 | D | sum error = [ 13.5429, 14.9906, 16.2091, 17.4419, 18.8845] +24-11-19 20:36:53 | D | best error = [ 4.5368, 4.5368, 4.5368, 4.5368, 4.5368] +24-11-19 20:36:53 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:53 | D | sum error = [ 20.4730, 22.3270, 24.3331, 26.2068, 28.4482] +24-11-19 20:36:53 | D | best error = [ 4.5368, 4.5368, 4.5368, 4.5368, 4.5368] +24-11-19 20:36:53 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:53 | D | sum error = [ 30.9765, 33.5939, 36.6325, 39.4350, 43.0095] +24-11-19 20:36:53 | D | best error = [ 4.5368, 4.5368, 4.5368, 4.5368, 4.5368] +24-11-19 20:36:53 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:53 | D | sum error = [ 46.2407, 50.3858, 54.4722, 59.2871, 64.2498] +24-11-19 20:36:53 | D | best error = [ 4.5368, 4.5368, 4.5368, 4.5368, 4.5368] +24-11-19 20:36:53 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:53 | D | sum error = [ 69.6156, 75.3386, 81.5735, 88.4513, 96.0543] +24-11-19 20:36:53 | D | best error = [ 4.5368, 4.5368, 4.5368, 4.5368, 4.5368] +24-11-19 20:36:53 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:53 | D | sum error = [ 104.1911, 113.1555, 122.9341, 133.6608, 145.1519] +24-11-19 20:36:53 | D | best error = [ 4.5368, 4.5368, 4.5368, 4.5368, 4.5368] +24-11-19 20:36:53 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:53 | D | sum error = [ 157.4438, 171.1762, 185.8826, 201.6346, 219.1447] +24-11-19 20:36:53 | D | best error = [ 4.5368, 4.5368, 4.5368, 4.5368, 4.5368] +24-11-19 20:36:53 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:53 | D | sum error = [ 238.7532, 259.8345, 282.6219, 307.7021, 335.5977] +24-11-19 20:36:53 | D | best error = [ 4.5368, 4.5368, 4.5368, 4.5368, 4.5368] +24-11-19 20:36:53 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:53 | D | sum error = [ 366.1687, 400.3915, 437.0264, 479.1134, 524.8673] +24-11-19 20:36:53 | D | best error = [ 4.5368, 4.5368, 4.5368, 4.5368, 4.5368] +24-11-19 20:36:53 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:53 | D | sum error = [ 576.2004, 634.3979, 697.8583, 767.1756, 844.2682] +24-11-19 20:36:53 | D | best error = [ 4.5368, 4.5368, 4.5368, 4.5368, 4.5368] +24-11-19 20:36:53 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:53 | D | sum error = [ 929.0260, 1021.8149, 1123.1347, 1231.2320, 1347.9291] +24-11-19 20:36:53 | D | best error = [ 4.5368, 4.5368, 4.5368, 4.5368, 4.5368] +24-11-19 20:36:53 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:53 | D | sum error = [ 1471.0020, 1600.1431, 1735.6065, 1871.7683, 2010.2533] +24-11-19 20:36:53 | D | best error = [ 4.5368, 4.5368, 4.5368, 4.5368, 4.5368] +24-11-19 20:36:53 | D | + error = [4.5368] +24-11-19 20:36:53 | D | - Calibrating model.layers.22.self_attn.k_proj.weight +24-11-19 20:36:53 | D | + w: sint8 +24-11-19 20:36:53 | D | + x: None +24-11-19 20:36:53 | D | + y: None +24-11-19 20:36:53 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:36:53 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:36:53 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:36:54 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:36:54 | D | - range ratio = [ 1.0000] +24-11-19 20:36:54 | D | sum error = [ 4.6028] +24-11-19 20:36:54 | D | best error = [ 4.6028] +24-11-19 20:37:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:06 | D | sum error = [ 4.0704, 3.9263, 4.1687, 4.7538, 5.1020] +24-11-19 20:37:06 | D | best error = [ 4.0704, 3.9263, 3.9263, 3.9263, 3.9263] +24-11-19 20:37:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:06 | D | sum error = [ 4.9049, 4.6235, 6.1586, 5.7452, 6.6225] +24-11-19 20:37:06 | D | best error = [ 3.9263, 3.9263, 3.9263, 3.9263, 3.9263] +24-11-19 20:37:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:06 | D | sum error = [ 6.9930, 8.1066, 8.1731, 9.5806, 9.5821] +24-11-19 20:37:06 | D | best error = [ 3.9263, 3.9263, 3.9263, 3.9263, 3.9263] +24-11-19 20:37:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:06 | D | sum error = [ 11.1110, 11.9128, 12.9001, 16.5811, 16.5590] +24-11-19 20:37:06 | D | best error = [ 3.9263, 3.9263, 3.9263, 3.9263, 3.9263] +24-11-19 20:37:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:06 | D | sum error = [ 19.6743, 20.2539, 21.6244, 24.3576, 25.9364] +24-11-19 20:37:06 | D | best error = [ 3.9263, 3.9263, 3.9263, 3.9263, 3.9263] +24-11-19 20:37:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:06 | D | sum error = [ 27.9168, 29.5247, 31.9399, 34.9361, 36.5191] +24-11-19 20:37:06 | D | best error = [ 3.9263, 3.9263, 3.9263, 3.9263, 3.9263] +24-11-19 20:37:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:06 | D | sum error = [ 40.5869, 43.9285, 46.8799, 50.1157, 54.4133] +24-11-19 20:37:06 | D | best error = [ 3.9263, 3.9263, 3.9263, 3.9263, 3.9263] +24-11-19 20:37:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:06 | D | sum error = [ 58.8786, 63.9990, 69.2296, 75.0791, 80.8424] +24-11-19 20:37:06 | D | best error = [ 3.9263, 3.9263, 3.9263, 3.9263, 3.9263] +24-11-19 20:37:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:06 | D | sum error = [ 86.9699, 93.9322, 101.2541, 109.2871, 117.1654] +24-11-19 20:37:06 | D | best error = [ 3.9263, 3.9263, 3.9263, 3.9263, 3.9263] +24-11-19 20:37:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:06 | D | sum error = [ 126.5592, 136.9925, 146.9639, 158.4476, 171.7775] +24-11-19 20:37:06 | D | best error = [ 3.9263, 3.9263, 3.9263, 3.9263, 3.9263] +24-11-19 20:37:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:06 | D | sum error = [ 184.4854, 200.4453, 216.4627, 232.4976, 253.5602] +24-11-19 20:37:06 | D | best error = [ 3.9263, 3.9263, 3.9263, 3.9263, 3.9263] +24-11-19 20:37:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:06 | D | sum error = [ 273.8367, 295.8030, 323.5140, 352.1817, 384.1828] +24-11-19 20:37:06 | D | best error = [ 3.9263, 3.9263, 3.9263, 3.9263, 3.9263] +24-11-19 20:37:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:06 | D | sum error = [ 422.8914, 462.3631, 505.3840, 552.8250, 605.0015] +24-11-19 20:37:06 | D | best error = [ 3.9263, 3.9263, 3.9263, 3.9263, 3.9263] +24-11-19 20:37:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:06 | D | sum error = [ 664.9998, 728.4280, 794.7684, 878.9448, 960.3644] +24-11-19 20:37:06 | D | best error = [ 3.9263, 3.9263, 3.9263, 3.9263, 3.9263] +24-11-19 20:37:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:06 | D | sum error = [ 1051.7742, 1160.5183, 1268.6646, 1396.0270, 1514.8211] +24-11-19 20:37:06 | D | best error = [ 3.9263, 3.9263, 3.9263, 3.9263, 3.9263] +24-11-19 20:37:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:06 | D | sum error = [ 1644.3045, 1785.1436, 1922.5728, 2056.0455, 2192.2087] +24-11-19 20:37:06 | D | best error = [ 3.9263, 3.9263, 3.9263, 3.9263, 3.9263] +24-11-19 20:37:06 | D | + error = [3.9263] +24-11-19 20:37:06 | D | - Calibrating model.layers.22.self_attn.v_proj.weight +24-11-19 20:37:06 | D | + w: sint8 +24-11-19 20:37:06 | D | + x: None +24-11-19 20:37:06 | D | + y: None +24-11-19 20:37:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:06 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:06 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:06 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:06 | D | - range ratio = [ 1.0000] +24-11-19 20:37:06 | D | sum error = [ 1.9819] +24-11-19 20:37:06 | D | best error = [ 1.9819] +24-11-19 20:37:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:06 | D | sum error = [ 1.9627, 1.9531, 1.9640, 2.0061, 2.0230] +24-11-19 20:37:06 | D | best error = [ 1.8302, 1.7730, 1.7420, 1.7255, 1.7148] +24-11-19 20:37:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:06 | D | sum error = [ 2.0774, 2.1477, 2.2105, 2.3220, 2.4457] +24-11-19 20:37:06 | D | best error = [ 1.7117, 1.7098, 1.7093, 1.7091, 1.7091] +24-11-19 20:37:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:06 | D | sum error = [ 2.5803, 2.7699, 2.9191, 3.1389, 3.3628] +24-11-19 20:37:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:06 | D | sum error = [ 3.6046, 3.8514, 4.1133, 4.4080, 4.7144] +24-11-19 20:37:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:06 | D | sum error = [ 5.0481, 5.4193, 5.8135, 6.1997, 6.6478] +24-11-19 20:37:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:06 | D | sum error = [ 7.0996, 7.5797, 8.1034, 8.6460, 9.2119] +24-11-19 20:37:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:06 | D | sum error = [ 9.8084, 10.4521, 11.1150, 11.8063, 12.5571] +24-11-19 20:37:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:06 | D | sum error = [ 13.3254, 14.1323, 14.9952, 15.8896, 16.8349] +24-11-19 20:37:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:06 | D | sum error = [ 17.8258, 18.8586, 19.9603, 21.1006, 22.3023] +24-11-19 20:37:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:06 | D | sum error = [ 23.5547, 24.8742, 26.2560, 27.6743, 29.1487] +24-11-19 20:37:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:06 | D | sum error = [ 30.7127, 32.3295, 33.9992, 35.7501, 37.5702] +24-11-19 20:37:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:06 | D | sum error = [ 39.4627, 41.4358, 43.4861, 45.6303, 47.8657] +24-11-19 20:37:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:06 | D | sum error = [ 50.1932, 52.6118, 55.1130, 57.7106, 60.4095] +24-11-19 20:37:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:06 | D | sum error = [ 63.2118, 66.1030, 69.1032, 72.2085, 75.4141] +24-11-19 20:37:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:06 | D | sum error = [ 78.7074, 82.1051, 85.6130, 89.2247, 92.9545] +24-11-19 20:37:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:06 | D | sum error = [ 96.7858, 100.7278, 104.7830, 108.9563, 113.2420] +24-11-19 20:37:06 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:06 | D | + error = [1.7091] +24-11-19 20:37:06 | D | - Calibrating model.layers.22.self_attn.o_proj.weight +24-11-19 20:37:06 | D | + w: sint8 +24-11-19 20:37:06 | D | + x: None +24-11-19 20:37:06 | D | + y: None +24-11-19 20:37:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:06 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:06 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:07 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:07 | D | - range ratio = [ 1.0000] +24-11-19 20:37:07 | D | sum error = [ 0.4522] +24-11-19 20:37:07 | D | best error = [ 0.4522] +24-11-19 20:37:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:07 | D | sum error = [ 0.4464, 0.4464, 0.4499, 0.4541, 0.4649] +24-11-19 20:37:07 | D | best error = [ 0.4191, 0.4054, 0.3976, 0.3928, 0.3900] +24-11-19 20:37:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:07 | D | sum error = [ 0.4754, 0.4901, 0.5116, 0.5336, 0.5614] +24-11-19 20:37:07 | D | best error = [ 0.3881, 0.3868, 0.3860, 0.3855, 0.3851] +24-11-19 20:37:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:07 | D | sum error = [ 0.5919, 0.6273, 0.6662, 0.7092, 0.7571] +24-11-19 20:37:07 | D | best error = [ 0.3849, 0.3847, 0.3846, 0.3845, 0.3845] +24-11-19 20:37:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:07 | D | sum error = [ 0.8047, 0.8605, 0.9181, 0.9811, 1.0459] +24-11-19 20:37:07 | D | best error = [ 0.3845, 0.3845, 0.3844, 0.3844, 0.3844] +24-11-19 20:37:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:07 | D | sum error = [ 1.1164, 1.1913, 1.2714, 1.3524, 1.4398] +24-11-19 20:37:07 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:37:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:07 | D | sum error = [ 1.5325, 1.6324, 1.7360, 1.8424, 1.9599] +24-11-19 20:37:07 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:37:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:07 | D | sum error = [ 2.0800, 2.2071, 2.3399, 2.4791, 2.6275] +24-11-19 20:37:07 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:37:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:07 | D | sum error = [ 2.7823, 2.9431, 3.1135, 3.2905, 3.4766] +24-11-19 20:37:07 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:37:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:07 | D | sum error = [ 3.6728, 3.8762, 4.0896, 4.3119, 4.5456] +24-11-19 20:37:07 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:37:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:07 | D | sum error = [ 4.7894, 5.0454, 5.3107, 5.5887, 5.8801] +24-11-19 20:37:07 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:37:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:07 | D | sum error = [ 6.1828, 6.4978, 6.8252, 7.1670, 7.5229] +24-11-19 20:37:07 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:37:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:07 | D | sum error = [ 7.8938, 8.2778, 8.6784, 9.0935, 9.5250] +24-11-19 20:37:07 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:37:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:07 | D | sum error = [ 9.9730, 10.4368, 10.9181, 11.4157, 11.9321] +24-11-19 20:37:07 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:37:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:07 | D | sum error = [ 12.4665, 13.0191, 13.5904, 14.1820, 14.7924] +24-11-19 20:37:07 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:37:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:07 | D | sum error = [ 15.4226, 16.0736, 16.7444, 17.4371, 18.1512] +24-11-19 20:37:07 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:37:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:07 | D | sum error = [ 18.8866, 19.6450, 20.4240, 21.2254, 22.0501] +24-11-19 20:37:07 | D | best error = [ 0.3844, 0.3844, 0.3844, 0.3844, 0.3844] +24-11-19 20:37:07 | D | + error = [0.3844] +24-11-19 20:37:07 | D | - Calibrating model.layers.22.mlp.up_proj.weight +24-11-19 20:37:07 | D | + w: sint8 +24-11-19 20:37:07 | D | + x: None +24-11-19 20:37:07 | D | + y: None +24-11-19 20:37:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:07 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:07 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:07 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:07 | D | - range ratio = [ 1.0000] +24-11-19 20:37:07 | D | sum error = [ 0.3780] +24-11-19 20:37:07 | D | best error = [ 0.3780] +24-11-19 20:37:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:08 | D | sum error = [ 0.3753, 0.3735, 0.3757, 0.3802, 0.3875] +24-11-19 20:37:08 | D | best error = [ 0.3494, 0.3379, 0.3321, 0.3289, 0.3271] +24-11-19 20:37:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:08 | D | sum error = [ 0.3968, 0.4108, 0.4268, 0.4461, 0.4699] +24-11-19 20:37:08 | D | best error = [ 0.3262, 0.3258, 0.3257, 0.3257, 0.3256] +24-11-19 20:37:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:08 | D | sum error = [ 0.4976, 0.5284, 0.5633, 0.6022, 0.6424] +24-11-19 20:37:08 | D | best error = [ 0.3256, 0.3256, 0.3256, 0.3256, 0.3256] +24-11-19 20:37:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:08 | D | sum error = [ 0.6880, 0.7382, 0.7898, 0.8466, 0.9071] +24-11-19 20:37:08 | D | best error = [ 0.3256, 0.3256, 0.3256, 0.3256, 0.3256] +24-11-19 20:37:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:08 | D | sum error = [ 0.9715, 1.0403, 1.1130, 1.1907, 1.2725] +24-11-19 20:37:08 | D | best error = [ 0.3256, 0.3256, 0.3256, 0.3256, 0.3256] +24-11-19 20:37:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:08 | D | sum error = [ 1.3590, 1.4530, 1.5484, 1.6508, 1.7591] +24-11-19 20:37:08 | D | best error = [ 0.3256, 0.3256, 0.3256, 0.3256, 0.3256] +24-11-19 20:37:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:08 | D | sum error = [ 1.8749, 1.9933, 2.1199, 2.2520, 2.3921] +24-11-19 20:37:08 | D | best error = [ 0.3256, 0.3256, 0.3256, 0.3256, 0.3256] +24-11-19 20:37:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:08 | D | sum error = [ 2.5383, 2.6951, 2.8567, 3.0251, 3.2042] +24-11-19 20:37:08 | D | best error = [ 0.3256, 0.3256, 0.3256, 0.3256, 0.3256] +24-11-19 20:37:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:08 | D | sum error = [ 3.3923, 3.5883, 3.7929, 4.0075, 4.2320] +24-11-19 20:37:08 | D | best error = [ 0.3256, 0.3256, 0.3256, 0.3256, 0.3256] +24-11-19 20:37:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:08 | D | sum error = [ 4.4664, 4.7098, 4.9661, 5.2316, 5.5106] +24-11-19 20:37:08 | D | best error = [ 0.3256, 0.3256, 0.3256, 0.3256, 0.3256] +24-11-19 20:37:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:08 | D | sum error = [ 5.8011, 6.1013, 6.4140, 6.7395, 7.0787] +24-11-19 20:37:08 | D | best error = [ 0.3256, 0.3256, 0.3256, 0.3256, 0.3256] +24-11-19 20:37:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:08 | D | sum error = [ 7.4307, 7.7949, 8.1710, 8.5681, 8.9719] +24-11-19 20:37:08 | D | best error = [ 0.3256, 0.3256, 0.3256, 0.3256, 0.3256] +24-11-19 20:37:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:08 | D | sum error = [ 9.3949, 9.8334, 10.2845, 10.7522, 11.2329] +24-11-19 20:37:08 | D | best error = [ 0.3256, 0.3256, 0.3256, 0.3256, 0.3256] +24-11-19 20:37:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:08 | D | sum error = [ 11.7326, 12.2483, 12.7773, 13.3231, 13.8884] +24-11-19 20:37:08 | D | best error = [ 0.3256, 0.3256, 0.3256, 0.3256, 0.3256] +24-11-19 20:37:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:08 | D | sum error = [ 14.4703, 15.0694, 15.6845, 16.3184, 16.9653] +24-11-19 20:37:08 | D | best error = [ 0.3256, 0.3256, 0.3256, 0.3256, 0.3256] +24-11-19 20:37:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:08 | D | sum error = [ 17.6371, 18.3295, 19.0320, 19.7659, 20.5079] +24-11-19 20:37:08 | D | best error = [ 0.3256, 0.3256, 0.3256, 0.3256, 0.3256] +24-11-19 20:37:08 | D | + error = [0.3256] +24-11-19 20:37:09 | D | - Calibrating model.layers.22.mlp.gate_proj.weight +24-11-19 20:37:09 | D | + w: sint8 +24-11-19 20:37:09 | D | + x: None +24-11-19 20:37:09 | D | + y: None +24-11-19 20:37:09 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:09 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:09 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:09 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:09 | D | - range ratio = [ 1.0000] +24-11-19 20:37:09 | D | sum error = [ 9.7712] +24-11-19 20:37:09 | D | best error = [ 9.7712] +24-11-19 20:37:10 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:10 | D | sum error = [ 9.7384, 9.6916, 9.7717, 9.8512, 10.0476] +24-11-19 20:37:10 | D | best error = [ 9.0478, 8.7673, 8.6198, 8.5347, 8.4876] +24-11-19 20:37:10 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:10 | D | sum error = [ 10.2753, 10.6291, 11.0621, 11.6112, 12.2279] +24-11-19 20:37:10 | D | best error = [ 8.4646, 8.4548, 8.4509, 8.4498, 8.4497] +24-11-19 20:37:10 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:10 | D | sum error = [ 12.9503, 13.7049, 14.6157, 15.6298, 16.7240] +24-11-19 20:37:10 | D | best error = [ 8.4497, 8.4497, 8.4497, 8.4497, 8.4497] +24-11-19 20:37:10 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:10 | D | sum error = [ 17.9074, 19.1767, 20.5849, 22.0673, 23.6584] +24-11-19 20:37:10 | D | best error = [ 8.4497, 8.4497, 8.4497, 8.4497, 8.4497] +24-11-19 20:37:10 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:10 | D | sum error = [ 25.3930, 27.2236, 29.1695, 31.2623, 33.4641] +24-11-19 20:37:10 | D | best error = [ 8.4497, 8.4497, 8.4497, 8.4497, 8.4497] +24-11-19 20:37:10 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:10 | D | sum error = [ 35.7988, 38.2846, 40.9289, 43.7493, 46.7189] +24-11-19 20:37:10 | D | best error = [ 8.4497, 8.4497, 8.4497, 8.4497, 8.4497] +24-11-19 20:37:10 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:10 | D | sum error = [ 49.8711, 53.2275, 56.7204, 60.4682, 64.4039] +24-11-19 20:37:10 | D | best error = [ 8.4497, 8.4497, 8.4497, 8.4497, 8.4497] +24-11-19 20:37:10 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:10 | D | sum error = [ 68.5294, 72.9318, 77.5689, 82.4700, 87.6507] +24-11-19 20:37:10 | D | best error = [ 8.4497, 8.4497, 8.4497, 8.4497, 8.4497] +24-11-19 20:37:10 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:10 | D | sum error = [ 93.1059, 98.8705, 104.9345, 111.3334, 118.0836] +24-11-19 20:37:10 | D | best error = [ 8.4497, 8.4497, 8.4497, 8.4497, 8.4497] +24-11-19 20:37:10 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:10 | D | sum error = [ 125.2002, 132.6822, 140.5656, 148.8565, 157.5866] +24-11-19 20:37:10 | D | best error = [ 8.4497, 8.4497, 8.4497, 8.4497, 8.4497] +24-11-19 20:37:10 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:10 | D | sum error = [ 166.7885, 176.4113, 186.5598, 197.1996, 208.3691] +24-11-19 20:37:10 | D | best error = [ 8.4497, 8.4497, 8.4497, 8.4497, 8.4497] +24-11-19 20:37:10 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:10 | D | sum error = [ 220.0804, 232.3654, 245.2362, 258.7114, 272.8260] +24-11-19 20:37:10 | D | best error = [ 8.4497, 8.4497, 8.4497, 8.4497, 8.4497] +24-11-19 20:37:10 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:10 | D | sum error = [ 287.5659, 302.9924, 319.1381, 335.9635, 353.5393] +24-11-19 20:37:10 | D | best error = [ 8.4497, 8.4497, 8.4497, 8.4497, 8.4497] +24-11-19 20:37:10 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:10 | D | sum error = [ 371.8697, 390.9629, 410.8536, 431.5246, 453.0211] +24-11-19 20:37:10 | D | best error = [ 8.4497, 8.4497, 8.4497, 8.4497, 8.4497] +24-11-19 20:37:10 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:10 | D | sum error = [ 475.3321, 498.5016, 522.5253, 547.3580, 573.1042] +24-11-19 20:37:10 | D | best error = [ 8.4497, 8.4497, 8.4497, 8.4497, 8.4497] +24-11-19 20:37:10 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:10 | D | sum error = [ 599.7020, 627.1748, 655.5037, 684.7125, 714.8259] +24-11-19 20:37:10 | D | best error = [ 8.4497, 8.4497, 8.4497, 8.4497, 8.4497] +24-11-19 20:37:10 | D | + error = [8.4497] +24-11-19 20:37:10 | D | - Calibrating model.layers.22.mlp.down_proj.weight +24-11-19 20:37:10 | D | + w: sint8 +24-11-19 20:37:10 | D | + x: None +24-11-19 20:37:10 | D | + y: None +24-11-19 20:37:10 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:10 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:10 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:11 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:11 | D | - range ratio = [ 1.0000] +24-11-19 20:37:11 | D | sum error = [ 1.1098] +24-11-19 20:37:11 | D | best error = [ 1.1098] +24-11-19 20:37:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:12 | D | sum error = [ 1.0996, 1.0930, 1.0911, 1.0929, 1.0965] +24-11-19 20:37:12 | D | best error = [ 1.0625, 1.0389, 1.0240, 1.0129, 1.0046] +24-11-19 20:37:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:12 | D | sum error = [ 1.1084, 1.1276, 1.1500, 1.1879, 1.2294] +24-11-19 20:37:12 | D | best error = [ 0.9982, 0.9938, 0.9907, 0.9882, 0.9867] +24-11-19 20:37:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:12 | D | sum error = [ 1.2805, 1.3394, 1.4092, 1.4946, 1.5848] +24-11-19 20:37:12 | D | best error = [ 0.9859, 0.9854, 0.9851, 0.9849, 0.9847] +24-11-19 20:37:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:12 | D | sum error = [ 1.6854, 1.8002, 1.9226, 2.0587, 2.2072] +24-11-19 20:37:12 | D | best error = [ 0.9847, 0.9847, 0.9847, 0.9846, 0.9846] +24-11-19 20:37:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:12 | D | sum error = [ 2.3620, 2.5311, 2.7111, 2.9051, 3.1118] +24-11-19 20:37:12 | D | best error = [ 0.9846, 0.9846, 0.9846, 0.9846, 0.9846] +24-11-19 20:37:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:12 | D | sum error = [ 3.3326, 3.5641, 3.8132, 4.0746, 4.3517] +24-11-19 20:37:12 | D | best error = [ 0.9846, 0.9846, 0.9846, 0.9846, 0.9846] +24-11-19 20:37:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:12 | D | sum error = [ 4.6458, 4.9570, 5.2833, 5.6293, 5.9921] +24-11-19 20:37:12 | D | best error = [ 0.9846, 0.9846, 0.9846, 0.9846, 0.9846] +24-11-19 20:37:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:12 | D | sum error = [ 6.3770, 6.7815, 7.2086, 7.6581, 8.1284] +24-11-19 20:37:12 | D | best error = [ 0.9846, 0.9846, 0.9846, 0.9846, 0.9846] +24-11-19 20:37:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:12 | D | sum error = [ 8.6270, 9.1490, 9.6994, 10.2760, 10.8835] +24-11-19 20:37:12 | D | best error = [ 0.9846, 0.9846, 0.9846, 0.9846, 0.9846] +24-11-19 20:37:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:12 | D | sum error = [ 11.5184, 12.1847, 12.8859, 13.6170, 14.3849] +24-11-19 20:37:12 | D | best error = [ 0.9846, 0.9846, 0.9846, 0.9846, 0.9846] +24-11-19 20:37:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:12 | D | sum error = [ 15.1899, 16.0311, 16.9149, 17.8377, 18.8014] +24-11-19 20:37:12 | D | best error = [ 0.9846, 0.9846, 0.9846, 0.9846, 0.9846] +24-11-19 20:37:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:12 | D | sum error = [ 19.8097, 20.8647, 21.9653, 23.1153, 24.3142] +24-11-19 20:37:12 | D | best error = [ 0.9846, 0.9846, 0.9846, 0.9846, 0.9846] +24-11-19 20:37:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:12 | D | sum error = [ 25.5622, 26.8637, 28.2222, 29.6339, 31.1018] +24-11-19 20:37:12 | D | best error = [ 0.9846, 0.9846, 0.9846, 0.9846, 0.9846] +24-11-19 20:37:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:12 | D | sum error = [ 32.6318, 34.2202, 35.8696, 37.5794, 39.3578] +24-11-19 20:37:12 | D | best error = [ 0.9846, 0.9846, 0.9846, 0.9846, 0.9846] +24-11-19 20:37:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:12 | D | sum error = [ 41.2007, 43.1093, 45.0822, 47.1267, 49.2401] +24-11-19 20:37:12 | D | best error = [ 0.9846, 0.9846, 0.9846, 0.9846, 0.9846] +24-11-19 20:37:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:12 | D | sum error = [ 51.4248, 53.6826, 56.0141, 58.4209, 60.9024] +24-11-19 20:37:12 | D | best error = [ 0.9846, 0.9846, 0.9846, 0.9846, 0.9846] +24-11-19 20:37:12 | D | + error = [0.9846] +24-11-19 20:37:12 | D | - Quantizing model.layers.22.self_attn.q_proj.weight +24-11-19 20:37:13 | D | - Quantizing model.layers.22.self_attn.k_proj.weight +24-11-19 20:37:16 | D | - Quantizing model.layers.22.self_attn.v_proj.weight +24-11-19 20:37:19 | D | - Quantizing model.layers.22.self_attn.o_proj.weight +24-11-19 20:37:22 | D | - Quantizing model.layers.22.mlp.up_proj.weight +24-11-19 20:37:25 | D | - Quantizing model.layers.22.mlp.gate_proj.weight +24-11-19 20:37:26 | D | - Quantizing model.layers.22.mlp.down_proj.weight +24-11-19 20:37:37 | D | - Quantizing layer model.layers.23 +24-11-19 20:37:37 | D | - Calibrating model.layers.23.self_attn.q_proj.weight +24-11-19 20:37:37 | D | + w: sint8 +24-11-19 20:37:37 | D | + x: None +24-11-19 20:37:37 | D | + y: None +24-11-19 20:37:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:37:37 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:37 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:37 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:38 | D | - range ratio = [ 1.0000] +24-11-19 20:37:38 | D | sum error = [ 4.1575] +24-11-19 20:37:38 | D | best error = [ 4.1575] +24-11-19 20:37:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:50 | D | sum error = [ 4.1903, 4.1938, 4.1147, 4.2448, 4.3593] +24-11-19 20:37:50 | D | best error = [ 4.1575, 4.1575, 4.1147, 4.1147, 4.1147] +24-11-19 20:37:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:50 | D | sum error = [ 4.3738, 4.6492, 4.9074, 5.1051, 5.7774] +24-11-19 20:37:50 | D | best error = [ 4.1147, 4.1147, 4.1147, 4.1147, 4.1147] +24-11-19 20:37:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:50 | D | sum error = [ 5.8275, 6.4413, 6.7431, 7.2945, 8.1082] +24-11-19 20:37:50 | D | best error = [ 4.1147, 4.1147, 4.1147, 4.1147, 4.1147] +24-11-19 20:37:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:50 | D | sum error = [ 9.0386, 9.6924, 10.6467, 11.3850, 12.5571] +24-11-19 20:37:50 | D | best error = [ 4.1147, 4.1147, 4.1147, 4.1147, 4.1147] +24-11-19 20:37:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:50 | D | sum error = [ 13.7199, 15.0510, 16.3411, 18.0524, 19.7544] +24-11-19 20:37:50 | D | best error = [ 4.1147, 4.1147, 4.1147, 4.1147, 4.1147] +24-11-19 20:37:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:50 | D | sum error = [ 21.4823, 23.7147, 25.8165, 28.1432, 30.8279] +24-11-19 20:37:50 | D | best error = [ 4.1147, 4.1147, 4.1147, 4.1147, 4.1147] +24-11-19 20:37:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:50 | D | sum error = [ 33.6022, 36.6443, 39.8249, 43.0813, 46.9200] +24-11-19 20:37:50 | D | best error = [ 4.1147, 4.1147, 4.1147, 4.1147, 4.1147] +24-11-19 20:37:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:50 | D | sum error = [ 51.1911, 55.9019, 60.5930, 65.4526, 71.4758] +24-11-19 20:37:50 | D | best error = [ 4.1147, 4.1147, 4.1147, 4.1147, 4.1147] +24-11-19 20:37:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:50 | D | sum error = [ 77.6243, 84.2412, 91.2472, 99.1066, 107.2947] +24-11-19 20:37:50 | D | best error = [ 4.1147, 4.1147, 4.1147, 4.1147, 4.1147] +24-11-19 20:37:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:50 | D | sum error = [ 116.4568, 125.5514, 136.3116, 147.6035, 159.8630] +24-11-19 20:37:50 | D | best error = [ 4.1147, 4.1147, 4.1147, 4.1147, 4.1147] +24-11-19 20:37:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:50 | D | sum error = [ 173.0242, 187.3391, 203.1510, 220.4488, 238.8967] +24-11-19 20:37:50 | D | best error = [ 4.1147, 4.1147, 4.1147, 4.1147, 4.1147] +24-11-19 20:37:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:50 | D | sum error = [ 259.3667, 281.9529, 306.3719, 333.0413, 361.8611] +24-11-19 20:37:50 | D | best error = [ 4.1147, 4.1147, 4.1147, 4.1147, 4.1147] +24-11-19 20:37:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:50 | D | sum error = [ 393.9279, 428.8525, 466.8102, 508.3152, 554.3193] +24-11-19 20:37:50 | D | best error = [ 4.1147, 4.1147, 4.1147, 4.1147, 4.1147] +24-11-19 20:37:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:50 | D | sum error = [ 605.3461, 660.0365, 720.4916, 786.8008, 858.4193] +24-11-19 20:37:50 | D | best error = [ 4.1147, 4.1147, 4.1147, 4.1147, 4.1147] +24-11-19 20:37:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:50 | D | sum error = [ 936.2123, 1020.0680, 1110.6063, 1207.6108, 1310.5842] +24-11-19 20:37:50 | D | best error = [ 4.1147, 4.1147, 4.1147, 4.1147, 4.1147] +24-11-19 20:37:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:50 | D | sum error = [ 1419.8815, 1535.0334, 1653.5991, 1776.5929, 1900.1460] +24-11-19 20:37:50 | D | best error = [ 4.1147, 4.1147, 4.1147, 4.1147, 4.1147] +24-11-19 20:37:50 | D | + error = [4.1147] +24-11-19 20:37:50 | D | - Calibrating model.layers.23.self_attn.k_proj.weight +24-11-19 20:37:50 | D | + w: sint8 +24-11-19 20:37:50 | D | + x: None +24-11-19 20:37:50 | D | + y: None +24-11-19 20:37:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:37:50 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:50 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:50 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:50 | D | - range ratio = [ 1.0000] +24-11-19 20:37:50 | D | sum error = [ 5.0593] +24-11-19 20:37:50 | D | best error = [ 5.0593] +24-11-19 20:38:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:03 | D | sum error = [ 5.0488, 4.4080, 4.6889, 5.3175, 5.0122] +24-11-19 20:38:03 | D | best error = [ 5.0488, 4.4080, 4.4080, 4.4080, 4.4080] +24-11-19 20:38:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:03 | D | sum error = [ 4.9607, 5.1975, 5.6748, 5.2196, 5.5600] +24-11-19 20:38:03 | D | best error = [ 4.4080, 4.4080, 4.4080, 4.4080, 4.4080] +24-11-19 20:38:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:03 | D | sum error = [ 6.6555, 6.8609, 7.0239, 8.0235, 9.2315] +24-11-19 20:38:03 | D | best error = [ 4.4080, 4.4080, 4.4080, 4.4080, 4.4080] +24-11-19 20:38:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:03 | D | sum error = [ 9.8705, 12.1214, 11.7110, 14.2563, 15.5353] +24-11-19 20:38:03 | D | best error = [ 4.4080, 4.4080, 4.4080, 4.4080, 4.4080] +24-11-19 20:38:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:03 | D | sum error = [ 16.7092, 18.5205, 21.1880, 22.3290, 26.1291] +24-11-19 20:38:03 | D | best error = [ 4.4080, 4.4080, 4.4080, 4.4080, 4.4080] +24-11-19 20:38:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:03 | D | sum error = [ 28.4595, 31.2245, 34.6707, 37.5367, 41.0676] +24-11-19 20:38:03 | D | best error = [ 4.4080, 4.4080, 4.4080, 4.4080, 4.4080] +24-11-19 20:38:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:03 | D | sum error = [ 45.2565, 49.7532, 54.1303, 60.2782, 65.5127] +24-11-19 20:38:03 | D | best error = [ 4.4080, 4.4080, 4.4080, 4.4080, 4.4080] +24-11-19 20:38:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:03 | D | sum error = [ 69.4446, 76.2995, 83.2348, 89.2818, 97.4997] +24-11-19 20:38:03 | D | best error = [ 4.4080, 4.4080, 4.4080, 4.4080, 4.4080] +24-11-19 20:38:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:03 | D | sum error = [ 106.0227, 115.3882, 124.1131, 134.7392, 145.1680] +24-11-19 20:38:03 | D | best error = [ 4.4080, 4.4080, 4.4080, 4.4080, 4.4080] +24-11-19 20:38:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:03 | D | sum error = [ 157.5947, 171.0065, 184.9005, 199.3148, 215.3141] +24-11-19 20:38:03 | D | best error = [ 4.4080, 4.4080, 4.4080, 4.4080, 4.4080] +24-11-19 20:38:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:03 | D | sum error = [ 233.7873, 251.4218, 272.7677, 295.6737, 320.1087] +24-11-19 20:38:03 | D | best error = [ 4.4080, 4.4080, 4.4080, 4.4080, 4.4080] +24-11-19 20:38:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:03 | D | sum error = [ 343.8985, 372.8767, 405.2367, 440.5088, 478.0289] +24-11-19 20:38:03 | D | best error = [ 4.4080, 4.4080, 4.4080, 4.4080, 4.4080] +24-11-19 20:38:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:03 | D | sum error = [ 517.8670, 561.5535, 608.6408, 658.6438, 715.0863] +24-11-19 20:38:03 | D | best error = [ 4.4080, 4.4080, 4.4080, 4.4080, 4.4080] +24-11-19 20:38:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:03 | D | sum error = [ 769.2166, 832.4637, 900.3618, 971.9051, 1048.1869] +24-11-19 20:38:03 | D | best error = [ 4.4080, 4.4080, 4.4080, 4.4080, 4.4080] +24-11-19 20:38:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:03 | D | sum error = [ 1128.5730, 1213.9967, 1306.1694, 1403.2351, 1507.6388] +24-11-19 20:38:03 | D | best error = [ 4.4080, 4.4080, 4.4080, 4.4080, 4.4080] +24-11-19 20:38:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:03 | D | sum error = [ 1609.7536, 1716.6133, 1829.3782, 1939.0098, 2046.6765] +24-11-19 20:38:03 | D | best error = [ 4.4080, 4.4080, 4.4080, 4.4080, 4.4080] +24-11-19 20:38:03 | D | + error = [4.4080] +24-11-19 20:38:03 | D | - Calibrating model.layers.23.self_attn.v_proj.weight +24-11-19 20:38:03 | D | + w: sint8 +24-11-19 20:38:03 | D | + x: None +24-11-19 20:38:03 | D | + y: None +24-11-19 20:38:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:03 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:03 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:03 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:03 | D | - range ratio = [ 1.0000] +24-11-19 20:38:03 | D | sum error = [ 2.1443] +24-11-19 20:38:03 | D | best error = [ 2.1443] +24-11-19 20:38:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:03 | D | sum error = [ 2.1199, 2.1334, 2.1272, 2.1463, 2.1822] +24-11-19 20:38:03 | D | best error = [ 1.9683, 1.9060, 1.8722, 1.8505, 1.8411] +24-11-19 20:38:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:03 | D | sum error = [ 2.2513, 2.3279, 2.4097, 2.5156, 2.6426] +24-11-19 20:38:03 | D | best error = [ 1.8356, 1.8337, 1.8326, 1.8322, 1.8322] +24-11-19 20:38:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:03 | D | sum error = [ 2.7853, 2.9566, 3.1364, 3.3528, 3.5790] +24-11-19 20:38:03 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:38:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:03 | D | sum error = [ 3.8487, 4.1053, 4.4142, 4.7104, 5.0595] +24-11-19 20:38:03 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:38:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:03 | D | sum error = [ 5.4082, 5.8045, 6.2298, 6.6462, 7.1108] +24-11-19 20:38:03 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:38:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:03 | D | sum error = [ 7.6303, 8.1141, 8.6623, 9.2339, 9.8496] +24-11-19 20:38:03 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:38:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:03 | D | sum error = [ 10.5143, 11.1744, 11.9043, 12.6722, 13.4499] +24-11-19 20:38:03 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:38:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:03 | D | sum error = [ 14.2998, 15.1824, 16.1020, 17.0573, 18.0608] +24-11-19 20:38:03 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:38:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:03 | D | sum error = [ 19.1021, 20.2011, 21.3497, 22.5531, 23.7952] +24-11-19 20:38:03 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:38:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:03 | D | sum error = [ 25.1023, 26.4824, 27.9186, 29.4238, 30.9868] +24-11-19 20:38:03 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:38:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:03 | D | sum error = [ 32.6378, 34.3607, 36.1724, 38.0486, 39.9954] +24-11-19 20:38:03 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:38:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:03 | D | sum error = [ 42.0277, 44.1451, 46.3217, 48.6057, 50.9669] +24-11-19 20:38:03 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:38:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:03 | D | sum error = [ 53.4319, 55.9860, 58.6310, 61.3622, 64.1988] +24-11-19 20:38:03 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:38:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:03 | D | sum error = [ 67.1274, 70.1744, 73.3094, 76.5635, 79.9205] +24-11-19 20:38:03 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:38:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:03 | D | sum error = [ 83.3823, 86.9496, 90.6433, 94.4444, 98.3557] +24-11-19 20:38:03 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:38:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:03 | D | sum error = [ 102.3866, 106.5448, 110.8062, 115.1907, 119.6963] +24-11-19 20:38:03 | D | best error = [ 1.8322, 1.8322, 1.8322, 1.8322, 1.8322] +24-11-19 20:38:03 | D | + error = [1.8322] +24-11-19 20:38:03 | D | - Calibrating model.layers.23.self_attn.o_proj.weight +24-11-19 20:38:03 | D | + w: sint8 +24-11-19 20:38:03 | D | + x: None +24-11-19 20:38:03 | D | + y: None +24-11-19 20:38:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:03 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:03 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:04 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:04 | D | - range ratio = [ 1.0000] +24-11-19 20:38:04 | D | sum error = [ 0.4629] +24-11-19 20:38:04 | D | best error = [ 0.4629] +24-11-19 20:38:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:04 | D | sum error = [ 0.4577, 0.4580, 0.4613, 0.4668, 0.4745] +24-11-19 20:38:04 | D | best error = [ 0.4294, 0.4151, 0.4065, 0.4015, 0.3978] +24-11-19 20:38:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:04 | D | sum error = [ 0.4869, 0.5047, 0.5244, 0.5487, 0.5774] +24-11-19 20:38:04 | D | best error = [ 0.3955, 0.3937, 0.3926, 0.3920, 0.3913] +24-11-19 20:38:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:04 | D | sum error = [ 0.6113, 0.6478, 0.6875, 0.7347, 0.7830] +24-11-19 20:38:04 | D | best error = [ 0.3909, 0.3907, 0.3905, 0.3904, 0.3903] +24-11-19 20:38:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:04 | D | sum error = [ 0.8399, 0.8959, 0.9601, 1.0297, 1.0999] +24-11-19 20:38:04 | D | best error = [ 0.3902, 0.3902, 0.3902, 0.3902, 0.3901] +24-11-19 20:38:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:04 | D | sum error = [ 1.1755, 1.2563, 1.3415, 1.4340, 1.5322] +24-11-19 20:38:04 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:38:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:04 | D | sum error = [ 1.6326, 1.7418, 1.8566, 1.9770, 2.1045] +24-11-19 20:38:04 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:38:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:04 | D | sum error = [ 2.2382, 2.3807, 2.5320, 2.6873, 2.8519] +24-11-19 20:38:04 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:38:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:04 | D | sum error = [ 3.0287, 3.2139, 3.4076, 3.6093, 3.8227] +24-11-19 20:38:04 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:38:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:04 | D | sum error = [ 4.0476, 4.2826, 4.5281, 4.7879, 5.0565] +24-11-19 20:38:04 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:38:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:04 | D | sum error = [ 5.3412, 5.6393, 5.9486, 6.2729, 6.6116] +24-11-19 20:38:04 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:38:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:04 | D | sum error = [ 6.9645, 7.3348, 7.7189, 8.1208, 8.5395] +24-11-19 20:38:04 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:38:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:04 | D | sum error = [ 8.9750, 9.4290, 9.9013, 10.3937, 10.9072] +24-11-19 20:38:04 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:38:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:04 | D | sum error = [ 11.4392, 11.9917, 12.5651, 13.1616, 13.7809] +24-11-19 20:38:04 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:38:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:04 | D | sum error = [ 14.4198, 15.0842, 15.7718, 16.4827, 17.2169] +24-11-19 20:38:04 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:38:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:04 | D | sum error = [ 17.9780, 18.7650, 19.5778, 20.4148, 21.2791] +24-11-19 20:38:04 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:38:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:04 | D | sum error = [ 22.1694, 23.0876, 24.0324, 25.0037, 26.0026] +24-11-19 20:38:04 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:38:04 | D | + error = [0.3901] +24-11-19 20:38:04 | D | - Calibrating model.layers.23.mlp.up_proj.weight +24-11-19 20:38:04 | D | + w: sint8 +24-11-19 20:38:04 | D | + x: None +24-11-19 20:38:04 | D | + y: None +24-11-19 20:38:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:04 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:04 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:04 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:04 | D | - range ratio = [ 1.0000] +24-11-19 20:38:04 | D | sum error = [ 0.3935] +24-11-19 20:38:04 | D | best error = [ 0.3935] +24-11-19 20:38:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:06 | D | sum error = [ 0.3912, 0.3894, 0.3920, 0.3967, 0.4031] +24-11-19 20:38:06 | D | best error = [ 0.3625, 0.3506, 0.3442, 0.3408, 0.3388] +24-11-19 20:38:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:06 | D | sum error = [ 0.4138, 0.4279, 0.4454, 0.4662, 0.4902] +24-11-19 20:38:06 | D | best error = [ 0.3378, 0.3373, 0.3372, 0.3371, 0.3371] +24-11-19 20:38:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:06 | D | sum error = [ 0.5190, 0.5515, 0.5857, 0.6275, 0.6692] +24-11-19 20:38:06 | D | best error = [ 0.3371, 0.3371, 0.3371, 0.3371, 0.3371] +24-11-19 20:38:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:06 | D | sum error = [ 0.7161, 0.7659, 0.8207, 0.8804, 0.9429] +24-11-19 20:38:06 | D | best error = [ 0.3371, 0.3371, 0.3371, 0.3371, 0.3371] +24-11-19 20:38:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:06 | D | sum error = [ 1.0090, 1.0798, 1.1557, 1.2351, 1.3195] +24-11-19 20:38:06 | D | best error = [ 0.3371, 0.3371, 0.3371, 0.3371, 0.3371] +24-11-19 20:38:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:06 | D | sum error = [ 1.4105, 1.5066, 1.6079, 1.7152, 1.8258] +24-11-19 20:38:06 | D | best error = [ 0.3371, 0.3371, 0.3371, 0.3371, 0.3371] +24-11-19 20:38:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:06 | D | sum error = [ 1.9448, 2.0684, 2.1992, 2.3376, 2.4812] +24-11-19 20:38:06 | D | best error = [ 0.3371, 0.3371, 0.3371, 0.3371, 0.3371] +24-11-19 20:38:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:06 | D | sum error = [ 2.6339, 2.7943, 2.9605, 3.1356, 3.3205] +24-11-19 20:38:06 | D | best error = [ 0.3371, 0.3371, 0.3371, 0.3371, 0.3371] +24-11-19 20:38:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:06 | D | sum error = [ 3.5147, 3.7159, 3.9283, 4.1484, 4.3794] +24-11-19 20:38:06 | D | best error = [ 0.3371, 0.3371, 0.3371, 0.3371, 0.3371] +24-11-19 20:38:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:06 | D | sum error = [ 4.6214, 4.8727, 5.1367, 5.4121, 5.6985] +24-11-19 20:38:06 | D | best error = [ 0.3371, 0.3371, 0.3371, 0.3371, 0.3371] +24-11-19 20:38:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:06 | D | sum error = [ 5.9969, 6.3071, 6.6303, 6.9653, 7.3153] +24-11-19 20:38:06 | D | best error = [ 0.3371, 0.3371, 0.3371, 0.3371, 0.3371] +24-11-19 20:38:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:06 | D | sum error = [ 7.6801, 8.0574, 8.4444, 8.8515, 9.2703] +24-11-19 20:38:06 | D | best error = [ 0.3371, 0.3371, 0.3371, 0.3371, 0.3371] +24-11-19 20:38:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:06 | D | sum error = [ 9.7041, 10.1519, 10.6168, 11.0965, 11.5910] +24-11-19 20:38:06 | D | best error = [ 0.3371, 0.3371, 0.3371, 0.3371, 0.3371] +24-11-19 20:38:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:06 | D | sum error = [ 12.1040, 12.6314, 13.1761, 13.7386, 14.3172] +24-11-19 20:38:06 | D | best error = [ 0.3371, 0.3371, 0.3371, 0.3371, 0.3371] +24-11-19 20:38:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:06 | D | sum error = [ 14.9125, 15.5270, 16.1600, 16.8107, 17.4784] +24-11-19 20:38:06 | D | best error = [ 0.3371, 0.3371, 0.3371, 0.3371, 0.3371] +24-11-19 20:38:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:06 | D | sum error = [ 18.1692, 18.8773, 19.6020, 20.3467, 21.1136] +24-11-19 20:38:06 | D | best error = [ 0.3371, 0.3371, 0.3371, 0.3371, 0.3371] +24-11-19 20:38:06 | D | + error = [0.3371] +24-11-19 20:38:06 | D | - Calibrating model.layers.23.mlp.gate_proj.weight +24-11-19 20:38:06 | D | + w: sint8 +24-11-19 20:38:06 | D | + x: None +24-11-19 20:38:06 | D | + y: None +24-11-19 20:38:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:06 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:06 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:06 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:06 | D | - range ratio = [ 1.0000] +24-11-19 20:38:06 | D | sum error = [ 10.1359] +24-11-19 20:38:06 | D | best error = [ 10.1359] +24-11-19 20:38:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:07 | D | sum error = [ 10.0173, 10.0142, 10.0578, 10.1764, 10.3487] +24-11-19 20:38:07 | D | best error = [ 9.3102, 9.0053, 8.8445, 8.7552, 8.7071] +24-11-19 20:38:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:07 | D | sum error = [ 10.6310, 10.9826, 11.4539, 11.9627, 12.6045] +24-11-19 20:38:07 | D | best error = [ 8.6802, 8.6687, 8.6650, 8.6634, 8.6630] +24-11-19 20:38:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:07 | D | sum error = [ 13.3530, 14.1759, 15.0623, 16.0631, 17.1723] +24-11-19 20:38:07 | D | best error = [ 8.6629, 8.6629, 8.6629, 8.6629, 8.6629] +24-11-19 20:38:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:07 | D | sum error = [ 18.3972, 19.7121, 21.1374, 22.6840, 24.3216] +24-11-19 20:38:07 | D | best error = [ 8.6629, 8.6629, 8.6629, 8.6629, 8.6629] +24-11-19 20:38:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:07 | D | sum error = [ 26.0660, 27.9452, 29.9499, 32.0416, 34.2661] +24-11-19 20:38:07 | D | best error = [ 8.6629, 8.6629, 8.6629, 8.6629, 8.6629] +24-11-19 20:38:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:07 | D | sum error = [ 36.6503, 39.2007, 41.8649, 44.7284, 47.7657] +24-11-19 20:38:07 | D | best error = [ 8.6629, 8.6629, 8.6629, 8.6629, 8.6629] +24-11-19 20:38:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:07 | D | sum error = [ 50.9077, 54.2653, 57.8237, 61.5874, 65.5564] +24-11-19 20:38:07 | D | best error = [ 8.6629, 8.6629, 8.6629, 8.6629, 8.6629] +24-11-19 20:38:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:07 | D | sum error = [ 69.7882, 74.2008, 78.9042, 83.8728, 89.0853] +24-11-19 20:38:07 | D | best error = [ 8.6629, 8.6629, 8.6629, 8.6629, 8.6629] +24-11-19 20:38:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:07 | D | sum error = [ 94.5956, 100.3847, 106.4958, 112.9236, 119.6937] +24-11-19 20:38:07 | D | best error = [ 8.6629, 8.6629, 8.6629, 8.6629, 8.6629] +24-11-19 20:38:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:07 | D | sum error = [ 126.7834, 134.2724, 142.1784, 150.4349, 159.1359] +24-11-19 20:38:07 | D | best error = [ 8.6629, 8.6629, 8.6629, 8.6629, 8.6629] +24-11-19 20:38:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:07 | D | sum error = [ 168.2704, 177.8322, 187.8814, 198.4233, 209.4871] +24-11-19 20:38:07 | D | best error = [ 8.6629, 8.6629, 8.6629, 8.6629, 8.6629] +24-11-19 20:38:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:07 | D | sum error = [ 221.0643, 233.1929, 245.8753, 259.1183, 273.0122] +24-11-19 20:38:07 | D | best error = [ 8.6629, 8.6629, 8.6629, 8.6629, 8.6629] +24-11-19 20:38:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:07 | D | sum error = [ 287.5203, 302.6485, 318.4463, 334.9120, 352.0585] +24-11-19 20:38:07 | D | best error = [ 8.6629, 8.6629, 8.6629, 8.6629, 8.6629] +24-11-19 20:38:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:07 | D | sum error = [ 369.9150, 388.5509, 407.9187, 428.0734, 449.0152] +24-11-19 20:38:07 | D | best error = [ 8.6629, 8.6629, 8.6629, 8.6629, 8.6629] +24-11-19 20:38:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:07 | D | sum error = [ 470.7458, 493.2859, 516.6055, 540.7478, 565.7235] +24-11-19 20:38:07 | D | best error = [ 8.6629, 8.6629, 8.6629, 8.6629, 8.6629] +24-11-19 20:38:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:07 | D | sum error = [ 591.5296, 618.1449, 645.6174, 673.9397, 703.0878] +24-11-19 20:38:07 | D | best error = [ 8.6629, 8.6629, 8.6629, 8.6629, 8.6629] +24-11-19 20:38:07 | D | + error = [8.6629] +24-11-19 20:38:07 | D | - Calibrating model.layers.23.mlp.down_proj.weight +24-11-19 20:38:07 | D | + w: sint8 +24-11-19 20:38:07 | D | + x: None +24-11-19 20:38:07 | D | + y: None +24-11-19 20:38:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:07 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:38:07 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:38:08 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:38:08 | D | - range ratio = [ 1.0000] +24-11-19 20:38:08 | D | sum error = [ 1.1252] +24-11-19 20:38:08 | D | best error = [ 1.1252] +24-11-19 20:38:09 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:09 | D | sum error = [ 1.1136, 1.1079, 1.1044, 1.1051, 1.1108] +24-11-19 20:38:09 | D | best error = [ 1.0768, 1.0544, 1.0402, 1.0292, 1.0214] +24-11-19 20:38:09 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:09 | D | sum error = [ 1.1222, 1.1393, 1.1606, 1.1948, 1.2330] +24-11-19 20:38:09 | D | best error = [ 1.0155, 1.0112, 1.0083, 1.0062, 1.0051] +24-11-19 20:38:09 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:09 | D | sum error = [ 1.2829, 1.3382, 1.4057, 1.4860, 1.5666] +24-11-19 20:38:09 | D | best error = [ 1.0042, 1.0036, 1.0033, 1.0032, 1.0032] +24-11-19 20:38:09 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:09 | D | sum error = [ 1.6660, 1.7749, 1.8933, 2.0257, 2.1657] +24-11-19 20:38:09 | D | best error = [ 1.0032, 1.0032, 1.0031, 1.0031, 1.0031] +24-11-19 20:38:09 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:09 | D | sum error = [ 2.3151, 2.4814, 2.6562, 2.8432, 3.0417] +24-11-19 20:38:09 | D | best error = [ 1.0031, 1.0031, 1.0031, 1.0031, 1.0031] +24-11-19 20:38:09 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:09 | D | sum error = [ 3.2522, 3.4804, 3.7197, 3.9725, 4.2395] +24-11-19 20:38:09 | D | best error = [ 1.0031, 1.0031, 1.0031, 1.0031, 1.0031] +24-11-19 20:38:09 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:09 | D | sum error = [ 4.5235, 4.8234, 5.1405, 5.4764, 5.8304] +24-11-19 20:38:09 | D | best error = [ 1.0031, 1.0031, 1.0031, 1.0031, 1.0031] +24-11-19 20:38:09 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:09 | D | sum error = [ 6.2029, 6.5972, 7.0104, 7.4499, 7.9093] +24-11-19 20:38:09 | D | best error = [ 1.0031, 1.0031, 1.0031, 1.0031, 1.0031] +24-11-19 20:38:09 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:09 | D | sum error = [ 8.3959, 8.9111, 9.4500, 10.0158, 10.6105] +24-11-19 20:38:09 | D | best error = [ 1.0031, 1.0031, 1.0031, 1.0031, 1.0031] +24-11-19 20:38:09 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:09 | D | sum error = [ 11.2353, 11.8943, 12.5843, 13.3076, 14.0668] +24-11-19 20:38:09 | D | best error = [ 1.0031, 1.0031, 1.0031, 1.0031, 1.0031] +24-11-19 20:38:09 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:09 | D | sum error = [ 14.8669, 15.6993, 16.5746, 17.4885, 18.4452] +24-11-19 20:38:09 | D | best error = [ 1.0031, 1.0031, 1.0031, 1.0031, 1.0031] +24-11-19 20:38:09 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:09 | D | sum error = [ 19.4478, 20.4938, 21.5882, 22.7319, 23.9242] +24-11-19 20:38:09 | D | best error = [ 1.0031, 1.0031, 1.0031, 1.0031, 1.0031] +24-11-19 20:38:09 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:09 | D | sum error = [ 25.1699, 26.4692, 27.8260, 29.2350, 30.7066] +24-11-19 20:38:09 | D | best error = [ 1.0031, 1.0031, 1.0031, 1.0031, 1.0031] +24-11-19 20:38:09 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:09 | D | sum error = [ 32.2377, 33.8283, 35.4822, 37.1993, 38.9826] +24-11-19 20:38:09 | D | best error = [ 1.0031, 1.0031, 1.0031, 1.0031, 1.0031] +24-11-19 20:38:09 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:09 | D | sum error = [ 40.8353, 42.7551, 44.7445, 46.8052, 48.9356] +24-11-19 20:38:09 | D | best error = [ 1.0031, 1.0031, 1.0031, 1.0031, 1.0031] +24-11-19 20:38:09 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:09 | D | sum error = [ 51.1385, 53.4134, 55.7639, 58.1896, 60.6912] +24-11-19 20:38:09 | D | best error = [ 1.0031, 1.0031, 1.0031, 1.0031, 1.0031] +24-11-19 20:38:09 | D | + error = [1.0031] +24-11-19 20:38:09 | D | - Quantizing model.layers.23.self_attn.q_proj.weight +24-11-19 20:38:12 | D | - Quantizing model.layers.23.self_attn.k_proj.weight +24-11-19 20:38:13 | D | - Quantizing model.layers.23.self_attn.v_proj.weight +24-11-19 20:38:14 | D | - Quantizing model.layers.23.self_attn.o_proj.weight +24-11-19 20:38:15 | D | - Quantizing model.layers.23.mlp.up_proj.weight +24-11-19 20:38:16 | D | - Quantizing model.layers.23.mlp.gate_proj.weight +24-11-19 20:38:17 | D | - Quantizing model.layers.23.mlp.down_proj.weight +24-11-19 20:38:27 | D | - Quantizing layer model.layers.24 +24-11-19 20:38:27 | D | - Calibrating model.layers.24.self_attn.q_proj.weight +24-11-19 20:38:27 | D | + w: sint8 +24-11-19 20:38:27 | D | + x: None +24-11-19 20:38:27 | D | + y: None +24-11-19 20:38:27 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:38:27 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:27 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:28 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:28 | D | - range ratio = [ 1.0000] +24-11-19 20:38:28 | D | sum error = [ 4.6793] +24-11-19 20:38:28 | D | best error = [ 4.6793] +24-11-19 20:38:42 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:42 | D | sum error = [ 4.7035, 4.7991, 4.7821, 4.7886, 4.9648] +24-11-19 20:38:42 | D | best error = [ 4.6793, 4.6793, 4.6793, 4.6793, 4.6793] +24-11-19 20:38:42 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:42 | D | sum error = [ 5.0390, 5.0740, 5.5811, 5.6460, 6.0958] +24-11-19 20:38:42 | D | best error = [ 4.6793, 4.6793, 4.6793, 4.6793, 4.6793] +24-11-19 20:38:42 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:42 | D | sum error = [ 6.4084, 6.9266, 7.3900, 7.9717, 8.5219] +24-11-19 20:38:42 | D | best error = [ 4.6793, 4.6793, 4.6793, 4.6793, 4.6793] +24-11-19 20:38:42 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:42 | D | sum error = [ 9.2552, 10.0470, 10.9124, 12.1237, 12.9783] +24-11-19 20:38:42 | D | best error = [ 4.6793, 4.6793, 4.6793, 4.6793, 4.6793] +24-11-19 20:38:42 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:42 | D | sum error = [ 14.0715, 15.5184, 16.8675, 18.0764, 19.6532] +24-11-19 20:38:42 | D | best error = [ 4.6793, 4.6793, 4.6793, 4.6793, 4.6793] +24-11-19 20:38:42 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:42 | D | sum error = [ 21.2914, 23.0539, 24.9685, 27.1584, 29.4932] +24-11-19 20:38:42 | D | best error = [ 4.6793, 4.6793, 4.6793, 4.6793, 4.6793] +24-11-19 20:38:42 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:42 | D | sum error = [ 31.7853, 34.7861, 37.3412, 40.5791, 44.0372] +24-11-19 20:38:42 | D | best error = [ 4.6793, 4.6793, 4.6793, 4.6793, 4.6793] +24-11-19 20:38:42 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:42 | D | sum error = [ 47.8542, 52.1022, 56.2193, 60.8550, 65.9257] +24-11-19 20:38:42 | D | best error = [ 4.6793, 4.6793, 4.6793, 4.6793, 4.6793] +24-11-19 20:38:42 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:42 | D | sum error = [ 70.8779, 76.8862, 83.3024, 89.7586, 97.1528] +24-11-19 20:38:42 | D | best error = [ 4.6793, 4.6793, 4.6793, 4.6793, 4.6793] +24-11-19 20:38:42 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:42 | D | sum error = [ 105.0266, 113.6678, 122.7502, 132.4541, 142.9849] +24-11-19 20:38:42 | D | best error = [ 4.6793, 4.6793, 4.6793, 4.6793, 4.6793] +24-11-19 20:38:42 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:42 | D | sum error = [ 154.4925, 166.7678, 180.0557, 194.2508, 209.7163] +24-11-19 20:38:42 | D | best error = [ 4.6793, 4.6793, 4.6793, 4.6793, 4.6793] +24-11-19 20:38:42 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:42 | D | sum error = [ 226.2698, 244.1003, 262.7702, 283.5400, 305.3610] +24-11-19 20:38:42 | D | best error = [ 4.6793, 4.6793, 4.6793, 4.6793, 4.6793] +24-11-19 20:38:42 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:42 | D | sum error = [ 329.1195, 354.9923, 382.6511, 412.5144, 444.9362] +24-11-19 20:38:42 | D | best error = [ 4.6793, 4.6793, 4.6793, 4.6793, 4.6793] +24-11-19 20:38:42 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:42 | D | sum error = [ 480.1990, 518.6598, 560.2438, 605.3039, 653.9186] +24-11-19 20:38:42 | D | best error = [ 4.6793, 4.6793, 4.6793, 4.6793, 4.6793] +24-11-19 20:38:42 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:42 | D | sum error = [ 706.8906, 764.3096, 826.1982, 892.6089, 963.4026] +24-11-19 20:38:42 | D | best error = [ 4.6793, 4.6793, 4.6793, 4.6793, 4.6793] +24-11-19 20:38:42 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:42 | D | sum error = [ 1038.7478, 1118.1995, 1200.8167, 1287.2064, 1375.1614] +24-11-19 20:38:42 | D | best error = [ 4.6793, 4.6793, 4.6793, 4.6793, 4.6793] +24-11-19 20:38:42 | D | + error = [4.6793] +24-11-19 20:38:42 | D | - Calibrating model.layers.24.self_attn.k_proj.weight +24-11-19 20:38:42 | D | + w: sint8 +24-11-19 20:38:42 | D | + x: None +24-11-19 20:38:42 | D | + y: None +24-11-19 20:38:42 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:38:42 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:42 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:43 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:43 | D | - range ratio = [ 1.0000] +24-11-19 20:38:43 | D | sum error = [ 4.5102] +24-11-19 20:38:43 | D | best error = [ 4.5102] +24-11-19 20:38:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:57 | D | sum error = [ 5.4636, 4.5036, 4.7664, 5.3366, 5.2143] +24-11-19 20:38:57 | D | best error = [ 4.5102, 4.5036, 4.5036, 4.5036, 4.5036] +24-11-19 20:38:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:57 | D | sum error = [ 5.0176, 5.0134, 5.9279, 5.2832, 6.0690] +24-11-19 20:38:57 | D | best error = [ 4.5036, 4.5036, 4.5036, 4.5036, 4.5036] +24-11-19 20:38:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:57 | D | sum error = [ 6.0815, 7.0000, 8.1279, 7.8767, 8.7334] +24-11-19 20:38:57 | D | best error = [ 4.5036, 4.5036, 4.5036, 4.5036, 4.5036] +24-11-19 20:38:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:57 | D | sum error = [ 9.5555, 10.4931, 10.5427, 12.3585, 12.8750] +24-11-19 20:38:57 | D | best error = [ 4.5036, 4.5036, 4.5036, 4.5036, 4.5036] +24-11-19 20:38:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:57 | D | sum error = [ 13.9595, 14.8194, 16.6422, 18.1204, 19.8846] +24-11-19 20:38:57 | D | best error = [ 4.5036, 4.5036, 4.5036, 4.5036, 4.5036] +24-11-19 20:38:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:57 | D | sum error = [ 21.4264, 22.3858, 24.1298, 26.8402, 28.1925] +24-11-19 20:38:57 | D | best error = [ 4.5036, 4.5036, 4.5036, 4.5036, 4.5036] +24-11-19 20:38:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:57 | D | sum error = [ 30.8656, 33.8069, 35.8861, 39.9684, 42.4933] +24-11-19 20:38:57 | D | best error = [ 4.5036, 4.5036, 4.5036, 4.5036, 4.5036] +24-11-19 20:38:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:57 | D | sum error = [ 45.7336, 50.0601, 53.4640, 58.5954, 63.7394] +24-11-19 20:38:57 | D | best error = [ 4.5036, 4.5036, 4.5036, 4.5036, 4.5036] +24-11-19 20:38:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:57 | D | sum error = [ 68.5936, 73.7738, 79.5513, 85.7894, 92.9212] +24-11-19 20:38:57 | D | best error = [ 4.5036, 4.5036, 4.5036, 4.5036, 4.5036] +24-11-19 20:38:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:57 | D | sum error = [ 100.2447, 109.2440, 117.9588, 126.3435, 136.4957] +24-11-19 20:38:57 | D | best error = [ 4.5036, 4.5036, 4.5036, 4.5036, 4.5036] +24-11-19 20:38:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:57 | D | sum error = [ 148.1498, 160.5200, 173.5202, 188.2387, 203.0965] +24-11-19 20:38:57 | D | best error = [ 4.5036, 4.5036, 4.5036, 4.5036, 4.5036] +24-11-19 20:38:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:57 | D | sum error = [ 221.3829, 238.7691, 257.8731, 278.3958, 300.6859] +24-11-19 20:38:57 | D | best error = [ 4.5036, 4.5036, 4.5036, 4.5036, 4.5036] +24-11-19 20:38:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:57 | D | sum error = [ 324.4850, 349.4629, 377.3412, 407.6749, 438.8578] +24-11-19 20:38:57 | D | best error = [ 4.5036, 4.5036, 4.5036, 4.5036, 4.5036] +24-11-19 20:38:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:57 | D | sum error = [ 473.5020, 510.0856, 551.5197, 594.9274, 643.2011] +24-11-19 20:38:57 | D | best error = [ 4.5036, 4.5036, 4.5036, 4.5036, 4.5036] +24-11-19 20:38:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:57 | D | sum error = [ 696.3038, 751.9226, 813.6221, 879.2436, 950.1182] +24-11-19 20:38:57 | D | best error = [ 4.5036, 4.5036, 4.5036, 4.5036, 4.5036] +24-11-19 20:38:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:57 | D | sum error = [ 1025.1603, 1106.9853, 1192.8242, 1281.7542, 1374.0905] +24-11-19 20:38:57 | D | best error = [ 4.5036, 4.5036, 4.5036, 4.5036, 4.5036] +24-11-19 20:38:57 | D | + error = [4.5036] +24-11-19 20:38:57 | D | - Calibrating model.layers.24.self_attn.v_proj.weight +24-11-19 20:38:57 | D | + w: sint8 +24-11-19 20:38:57 | D | + x: None +24-11-19 20:38:57 | D | + y: None +24-11-19 20:38:57 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:57 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:38:57 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:38:58 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:38:58 | D | - range ratio = [ 1.0000] +24-11-19 20:38:58 | D | sum error = [ 2.3518] +24-11-19 20:38:58 | D | best error = [ 2.3518] +24-11-19 20:38:58 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:58 | D | sum error = [ 2.3400, 2.3507, 2.3445, 2.3651, 2.4109] +24-11-19 20:38:58 | D | best error = [ 2.1713, 2.1007, 2.0574, 2.0331, 2.0218] +24-11-19 20:38:58 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:58 | D | sum error = [ 2.4923, 2.5686, 2.6655, 2.8064, 2.9360] +24-11-19 20:38:58 | D | best error = [ 2.0157, 2.0135, 2.0117, 2.0111, 2.0109] +24-11-19 20:38:58 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:58 | D | sum error = [ 3.1152, 3.2738, 3.4992, 3.7487, 4.0173] +24-11-19 20:38:58 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:38:58 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:58 | D | sum error = [ 4.2973, 4.5896, 4.9203, 5.2703, 5.6319] +24-11-19 20:38:58 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:38:58 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:58 | D | sum error = [ 6.0440, 6.4868, 6.9483, 7.4178, 7.9048] +24-11-19 20:38:58 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:38:58 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:58 | D | sum error = [ 8.4802, 9.0293, 9.6237, 10.2523, 10.9315] +24-11-19 20:38:58 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:38:58 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:58 | D | sum error = [ 11.6326, 12.3835, 13.1771, 13.9697, 14.8538] +24-11-19 20:38:58 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:38:58 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:58 | D | sum error = [ 15.7768, 16.7564, 17.7744, 18.8355, 19.9416] +24-11-19 20:38:58 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:38:58 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:58 | D | sum error = [ 21.1477, 22.3746, 23.6671, 25.0114, 26.4432] +24-11-19 20:38:58 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:38:58 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:58 | D | sum error = [ 27.9283, 29.4565, 31.0979, 32.7711, 34.5660] +24-11-19 20:38:58 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:38:58 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:58 | D | sum error = [ 36.3988, 38.3425, 40.3457, 42.4355, 44.6385] +24-11-19 20:38:58 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:38:58 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:58 | D | sum error = [ 46.9094, 49.2838, 51.7297, 54.2864, 56.9538] +24-11-19 20:38:58 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:38:58 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:58 | D | sum error = [ 59.7088, 62.5638, 65.5038, 68.5557, 71.7100] +24-11-19 20:38:58 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:38:58 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:58 | D | sum error = [ 74.9622, 78.3230, 81.8179, 85.4223, 89.1569] +24-11-19 20:38:58 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:38:58 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:58 | D | sum error = [ 92.9974, 96.9702, 101.0492, 105.2880, 109.6514] +24-11-19 20:38:58 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:38:58 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:58 | D | sum error = [ 114.1209, 118.7217, 123.4540, 128.3101, 133.2938] +24-11-19 20:38:58 | D | best error = [ 2.0108, 2.0108, 2.0108, 2.0108, 2.0108] +24-11-19 20:38:58 | D | + error = [2.0108] +24-11-19 20:38:58 | D | - Calibrating model.layers.24.self_attn.o_proj.weight +24-11-19 20:38:58 | D | + w: sint8 +24-11-19 20:38:58 | D | + x: None +24-11-19 20:38:58 | D | + y: None +24-11-19 20:38:58 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:58 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:38:58 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:38:58 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:38:58 | D | - range ratio = [ 1.0000] +24-11-19 20:38:58 | D | sum error = [ 0.4864] +24-11-19 20:38:58 | D | best error = [ 0.4864] +24-11-19 20:38:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:59 | D | sum error = [ 0.4824, 0.4811, 0.4802, 0.4812, 0.4867] +24-11-19 20:38:59 | D | best error = [ 0.4501, 0.4344, 0.4241, 0.4173, 0.4123] +24-11-19 20:38:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:59 | D | sum error = [ 0.4927, 0.5042, 0.5175, 0.5330, 0.5513] +24-11-19 20:38:59 | D | best error = [ 0.4087, 0.4060, 0.4037, 0.4021, 0.4007] +24-11-19 20:38:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:59 | D | sum error = [ 0.5753, 0.6026, 0.6319, 0.6652, 0.7013] +24-11-19 20:38:59 | D | best error = [ 0.3997, 0.3990, 0.3984, 0.3980, 0.3975] +24-11-19 20:38:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:59 | D | sum error = [ 0.7434, 0.7890, 0.8378, 0.8905, 0.9505] +24-11-19 20:38:59 | D | best error = [ 0.3971, 0.3968, 0.3966, 0.3965, 0.3964] +24-11-19 20:38:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:59 | D | sum error = [ 1.0107, 1.0768, 1.1490, 1.2259, 1.3049] +24-11-19 20:38:59 | D | best error = [ 0.3963, 0.3962, 0.3961, 0.3961, 0.3961] +24-11-19 20:38:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:59 | D | sum error = [ 1.3922, 1.4828, 1.5786, 1.6806, 1.7886] +24-11-19 20:38:59 | D | best error = [ 0.3960, 0.3960, 0.3960, 0.3960, 0.3960] +24-11-19 20:38:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:59 | D | sum error = [ 1.9024, 2.0212, 2.1484, 2.2826, 2.4239] +24-11-19 20:38:59 | D | best error = [ 0.3960, 0.3960, 0.3960, 0.3960, 0.3960] +24-11-19 20:38:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:59 | D | sum error = [ 2.5704, 2.7267, 2.8906, 3.0607, 3.2408] +24-11-19 20:38:59 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:38:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:59 | D | sum error = [ 3.4324, 3.6321, 3.8430, 4.0628, 4.2933] +24-11-19 20:38:59 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:38:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:59 | D | sum error = [ 4.5359, 4.7914, 5.0576, 5.3363, 5.6281] +24-11-19 20:38:59 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:38:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:59 | D | sum error = [ 5.9355, 6.2546, 6.5912, 6.9410, 7.3067] +24-11-19 20:38:59 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:38:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:59 | D | sum error = [ 7.6876, 8.0868, 8.5005, 8.9322, 9.3828] +24-11-19 20:38:59 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:38:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:59 | D | sum error = [ 9.8500, 10.3349, 10.8397, 11.3630, 11.9066] +24-11-19 20:38:59 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:38:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:59 | D | sum error = [ 12.4695, 13.0535, 13.6569, 14.2849, 14.9329] +24-11-19 20:38:59 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:38:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:59 | D | sum error = [ 15.6046, 16.2999, 17.0190, 17.7607, 18.5256] +24-11-19 20:38:59 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:38:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:59 | D | sum error = [ 19.3144, 20.1264, 20.9629, 21.8250, 22.7131] +24-11-19 20:38:59 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:38:59 | D | + error = [0.3959] +24-11-19 20:38:59 | D | - Calibrating model.layers.24.mlp.up_proj.weight +24-11-19 20:38:59 | D | + w: sint8 +24-11-19 20:38:59 | D | + x: None +24-11-19 20:38:59 | D | + y: None +24-11-19 20:38:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:59 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:59 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:59 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:59 | D | - range ratio = [ 1.0000] +24-11-19 20:38:59 | D | sum error = [ 0.4104] +24-11-19 20:38:59 | D | best error = [ 0.4104] +24-11-19 20:39:00 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:00 | D | sum error = [ 0.4078, 0.4067, 0.4073, 0.4119, 0.4210] +24-11-19 20:39:00 | D | best error = [ 0.3761, 0.3629, 0.3559, 0.3519, 0.3499] +24-11-19 20:39:00 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:00 | D | sum error = [ 0.4315, 0.4449, 0.4628, 0.4846, 0.5106] +24-11-19 20:39:00 | D | best error = [ 0.3489, 0.3483, 0.3482, 0.3481, 0.3481] +24-11-19 20:39:00 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:00 | D | sum error = [ 0.5402, 0.5740, 0.6108, 0.6517, 0.6958] +24-11-19 20:39:00 | D | best error = [ 0.3481, 0.3481, 0.3481, 0.3481, 0.3481] +24-11-19 20:39:00 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:00 | D | sum error = [ 0.7455, 0.7985, 0.8552, 0.9159, 0.9813] +24-11-19 20:39:00 | D | best error = [ 0.3481, 0.3481, 0.3481, 0.3481, 0.3481] +24-11-19 20:39:00 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:00 | D | sum error = [ 1.0525, 1.1264, 1.2050, 1.2903, 1.3788] +24-11-19 20:39:00 | D | best error = [ 0.3481, 0.3481, 0.3481, 0.3481, 0.3481] +24-11-19 20:39:00 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:00 | D | sum error = [ 1.4725, 1.5719, 1.6762, 1.7880, 1.9039] +24-11-19 20:39:00 | D | best error = [ 0.3481, 0.3481, 0.3481, 0.3481, 0.3481] +24-11-19 20:39:00 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:00 | D | sum error = [ 2.0272, 2.1581, 2.2931, 2.4373, 2.5884] +24-11-19 20:39:00 | D | best error = [ 0.3481, 0.3481, 0.3481, 0.3481, 0.3481] +24-11-19 20:39:00 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:00 | D | sum error = [ 2.7471, 2.9141, 3.0882, 3.2700, 3.4639] +24-11-19 20:39:00 | D | best error = [ 0.3481, 0.3481, 0.3481, 0.3481, 0.3481] +24-11-19 20:39:00 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:00 | D | sum error = [ 3.6644, 3.8753, 4.0971, 4.3272, 4.5674] +24-11-19 20:39:00 | D | best error = [ 0.3481, 0.3481, 0.3481, 0.3481, 0.3481] +24-11-19 20:39:00 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:00 | D | sum error = [ 4.8174, 5.0809, 5.3542, 5.6409, 5.9366] +24-11-19 20:39:00 | D | best error = [ 0.3481, 0.3481, 0.3481, 0.3481, 0.3481] +24-11-19 20:39:00 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:00 | D | sum error = [ 6.2494, 6.5695, 6.9022, 7.2535, 7.6127] +24-11-19 20:39:00 | D | best error = [ 0.3481, 0.3481, 0.3481, 0.3481, 0.3481] +24-11-19 20:39:00 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:00 | D | sum error = [ 7.9869, 8.3752, 8.7776, 9.1951, 9.6270] +24-11-19 20:39:00 | D | best error = [ 0.3481, 0.3481, 0.3481, 0.3481, 0.3481] +24-11-19 20:39:00 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:00 | D | sum error = [ 10.0747, 10.5337, 11.0128, 11.5043, 12.0157] +24-11-19 20:39:00 | D | best error = [ 0.3481, 0.3481, 0.3481, 0.3481, 0.3481] +24-11-19 20:39:00 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:00 | D | sum error = [ 12.5396, 13.0815, 13.6391, 14.2178, 14.8077] +24-11-19 20:39:00 | D | best error = [ 0.3481, 0.3481, 0.3481, 0.3481, 0.3481] +24-11-19 20:39:00 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:00 | D | sum error = [ 15.4166, 16.0425, 16.6922, 17.3493, 18.0324] +24-11-19 20:39:00 | D | best error = [ 0.3481, 0.3481, 0.3481, 0.3481, 0.3481] +24-11-19 20:39:00 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:00 | D | sum error = [ 18.7357, 19.4536, 20.1823, 20.9403, 21.7216] +24-11-19 20:39:00 | D | best error = [ 0.3481, 0.3481, 0.3481, 0.3481, 0.3481] +24-11-19 20:39:00 | D | + error = [0.3481] +24-11-19 20:39:00 | D | - Calibrating model.layers.24.mlp.gate_proj.weight +24-11-19 20:39:00 | D | + w: sint8 +24-11-19 20:39:00 | D | + x: None +24-11-19 20:39:00 | D | + y: None +24-11-19 20:39:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:00 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:39:01 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:39:01 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:39:01 | D | - range ratio = [ 1.0000] +24-11-19 20:39:01 | D | sum error = [ 10.4819] +24-11-19 20:39:01 | D | best error = [ 10.4819] +24-11-19 20:39:02 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:02 | D | sum error = [ 10.4450, 10.4172, 10.4423, 10.5727, 10.7609] +24-11-19 20:39:02 | D | best error = [ 9.6175, 9.2792, 9.1106, 9.0126, 8.9608] +24-11-19 20:39:02 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:02 | D | sum error = [ 11.0425, 11.3881, 11.8349, 12.3816, 13.0691] +24-11-19 20:39:02 | D | best error = [ 8.9346, 8.9234, 8.9186, 8.9168, 8.9162] +24-11-19 20:39:02 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:02 | D | sum error = [ 13.7905, 14.6513, 15.6247, 16.6615, 17.7917] +24-11-19 20:39:02 | D | best error = [ 8.9160, 8.9160, 8.9160, 8.9160, 8.9160] +24-11-19 20:39:02 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:02 | D | sum error = [ 19.0411, 20.3998, 21.8471, 23.4211, 25.1202] +24-11-19 20:39:02 | D | best error = [ 8.9160, 8.9160, 8.9160, 8.9160, 8.9160] +24-11-19 20:39:02 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:02 | D | sum error = [ 26.9184, 28.8389, 30.8770, 33.0536, 35.3837] +24-11-19 20:39:02 | D | best error = [ 8.9160, 8.9160, 8.9160, 8.9160, 8.9160] +24-11-19 20:39:02 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:02 | D | sum error = [ 37.8461, 40.4599, 43.2255, 46.1083, 49.2451] +24-11-19 20:39:02 | D | best error = [ 8.9160, 8.9160, 8.9160, 8.9160, 8.9160] +24-11-19 20:39:02 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:02 | D | sum error = [ 52.5012, 55.9406, 59.5839, 63.4595, 67.5578] +24-11-19 20:39:02 | D | best error = [ 8.9160, 8.9160, 8.9160, 8.9160, 8.9160] +24-11-19 20:39:02 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:02 | D | sum error = [ 71.8119, 76.3770, 81.1280, 86.1733, 91.4544] +24-11-19 20:39:02 | D | best error = [ 8.9160, 8.9160, 8.9160, 8.9160, 8.9160] +24-11-19 20:39:02 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:02 | D | sum error = [ 97.0588, 102.9183, 109.1300, 115.6441, 122.5291] +24-11-19 20:39:02 | D | best error = [ 8.9160, 8.9160, 8.9160, 8.9160, 8.9160] +24-11-19 20:39:02 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:02 | D | sum error = [ 129.7290, 137.2875, 145.2524, 153.6095, 162.3846] +24-11-19 20:39:02 | D | best error = [ 8.9160, 8.9160, 8.9160, 8.9160, 8.9160] +24-11-19 20:39:02 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:02 | D | sum error = [ 171.6061, 181.2604, 191.4011, 202.0015, 213.1411] +24-11-19 20:39:02 | D | best error = [ 8.9160, 8.9160, 8.9160, 8.9160, 8.9160] +24-11-19 20:39:02 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:02 | D | sum error = [ 224.8017, 236.9865, 249.7676, 263.1004, 277.0022] +24-11-19 20:39:02 | D | best error = [ 8.9160, 8.9160, 8.9160, 8.9160, 8.9160] +24-11-19 20:39:02 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:02 | D | sum error = [ 291.5495, 306.7037, 322.4693, 338.9158, 356.0524] +24-11-19 20:39:02 | D | best error = [ 8.9160, 8.9160, 8.9160, 8.9160, 8.9160] +24-11-19 20:39:02 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:02 | D | sum error = [ 373.8864, 392.4678, 411.7334, 431.7067, 452.4260] +24-11-19 20:39:02 | D | best error = [ 8.9160, 8.9160, 8.9160, 8.9160, 8.9160] +24-11-19 20:39:02 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:02 | D | sum error = [ 473.9125, 496.2110, 519.3102, 543.2185, 567.9814] +24-11-19 20:39:02 | D | best error = [ 8.9160, 8.9160, 8.9160, 8.9160, 8.9160] +24-11-19 20:39:02 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:02 | D | sum error = [ 593.5783, 619.9941, 647.2721, 675.3717, 704.3170] +24-11-19 20:39:02 | D | best error = [ 8.9160, 8.9160, 8.9160, 8.9160, 8.9160] +24-11-19 20:39:02 | D | + error = [8.9160] +24-11-19 20:39:02 | D | - Calibrating model.layers.24.mlp.down_proj.weight +24-11-19 20:39:02 | D | + w: sint8 +24-11-19 20:39:02 | D | + x: None +24-11-19 20:39:02 | D | + y: None +24-11-19 20:39:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:02 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:39:02 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:39:03 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:39:03 | D | - range ratio = [ 1.0000] +24-11-19 20:39:03 | D | sum error = [ 1.1536] +24-11-19 20:39:03 | D | best error = [ 1.1536] +24-11-19 20:39:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:04 | D | sum error = [ 1.1428, 1.1327, 1.1291, 1.1323, 1.1379] +24-11-19 20:39:04 | D | best error = [ 1.1031, 1.0779, 1.0614, 1.0501, 1.0417] +24-11-19 20:39:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:04 | D | sum error = [ 1.1501, 1.1637, 1.1883, 1.2197, 1.2623] +24-11-19 20:39:04 | D | best error = [ 1.0359, 1.0317, 1.0287, 1.0268, 1.0255] +24-11-19 20:39:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:04 | D | sum error = [ 1.3092, 1.3674, 1.4343, 1.5089, 1.6017] +24-11-19 20:39:04 | D | best error = [ 1.0248, 1.0243, 1.0239, 1.0238, 1.0238] +24-11-19 20:39:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:04 | D | sum error = [ 1.6979, 1.8087, 1.9298, 2.0582, 2.1993] +24-11-19 20:39:04 | D | best error = [ 1.0237, 1.0237, 1.0237, 1.0237, 1.0237] +24-11-19 20:39:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:04 | D | sum error = [ 2.3522, 2.5180, 2.6973, 2.8844, 3.0880] +24-11-19 20:39:04 | D | best error = [ 1.0237, 1.0237, 1.0237, 1.0237, 1.0237] +24-11-19 20:39:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:04 | D | sum error = [ 3.3010, 3.5316, 3.7738, 4.0316, 4.3060] +24-11-19 20:39:04 | D | best error = [ 1.0237, 1.0237, 1.0237, 1.0237, 1.0237] +24-11-19 20:39:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:04 | D | sum error = [ 4.5979, 4.9049, 5.2285, 5.5724, 5.9313] +24-11-19 20:39:04 | D | best error = [ 1.0237, 1.0237, 1.0237, 1.0237, 1.0237] +24-11-19 20:39:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:04 | D | sum error = [ 6.3130, 6.7154, 7.1447, 7.5874, 8.0607] +24-11-19 20:39:04 | D | best error = [ 1.0237, 1.0237, 1.0237, 1.0237, 1.0237] +24-11-19 20:39:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:04 | D | sum error = [ 8.5564, 9.0793, 9.6308, 10.2097, 10.8176] +24-11-19 20:39:04 | D | best error = [ 1.0237, 1.0237, 1.0237, 1.0237, 1.0237] +24-11-19 20:39:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:04 | D | sum error = [ 11.4571, 12.1311, 12.8350, 13.5748, 14.3506] +24-11-19 20:39:04 | D | best error = [ 1.0237, 1.0237, 1.0237, 1.0237, 1.0237] +24-11-19 20:39:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:04 | D | sum error = [ 15.1661, 16.0228, 16.9171, 17.8539, 18.8337] +24-11-19 20:39:04 | D | best error = [ 1.0237, 1.0237, 1.0237, 1.0237, 1.0237] +24-11-19 20:39:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:04 | D | sum error = [ 19.8559, 20.9266, 22.0430, 23.2119, 24.4321] +24-11-19 20:39:04 | D | best error = [ 1.0237, 1.0237, 1.0237, 1.0237, 1.0237] +24-11-19 20:39:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:04 | D | sum error = [ 25.7033, 27.0313, 28.4156, 29.8573, 31.3593] +24-11-19 20:39:04 | D | best error = [ 1.0237, 1.0237, 1.0237, 1.0237, 1.0237] +24-11-19 20:39:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:04 | D | sum error = [ 32.9230, 34.5495, 36.2377, 37.9900, 39.8112] +24-11-19 20:39:04 | D | best error = [ 1.0237, 1.0237, 1.0237, 1.0237, 1.0237] +24-11-19 20:39:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:04 | D | sum error = [ 41.7000, 43.6581, 45.6851, 47.7851, 49.9547] +24-11-19 20:39:04 | D | best error = [ 1.0237, 1.0237, 1.0237, 1.0237, 1.0237] +24-11-19 20:39:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:04 | D | sum error = [ 52.1991, 54.5204, 56.9166, 59.3889, 61.9402] +24-11-19 20:39:04 | D | best error = [ 1.0237, 1.0237, 1.0237, 1.0237, 1.0237] +24-11-19 20:39:04 | D | + error = [1.0237] +24-11-19 20:39:04 | D | - Quantizing model.layers.24.self_attn.q_proj.weight +24-11-19 20:39:05 | D | - Quantizing model.layers.24.self_attn.k_proj.weight +24-11-19 20:39:06 | D | - Quantizing model.layers.24.self_attn.v_proj.weight +24-11-19 20:39:07 | D | - Quantizing model.layers.24.self_attn.o_proj.weight +24-11-19 20:39:08 | D | - Quantizing model.layers.24.mlp.up_proj.weight +24-11-19 20:39:09 | D | - Quantizing model.layers.24.mlp.gate_proj.weight +24-11-19 20:39:10 | D | - Quantizing model.layers.24.mlp.down_proj.weight +24-11-19 20:39:21 | D | - Quantizing layer model.layers.25 +24-11-19 20:39:21 | D | - Calibrating model.layers.25.self_attn.q_proj.weight +24-11-19 20:39:21 | D | + w: sint8 +24-11-19 20:39:21 | D | + x: None +24-11-19 20:39:21 | D | + y: None +24-11-19 20:39:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:39:21 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:39:21 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:39:22 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:39:22 | D | - range ratio = [ 1.0000] +24-11-19 20:39:22 | D | sum error = [ 5.2802] +24-11-19 20:39:22 | D | best error = [ 5.2802] +24-11-19 20:39:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:37 | D | sum error = [ 5.4056, 5.4521, 5.5028, 5.5560, 5.8899] +24-11-19 20:39:37 | D | best error = [ 5.2802, 5.2802, 5.2802, 5.2802, 5.2802] +24-11-19 20:39:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:37 | D | sum error = [ 5.6678, 5.8000, 6.2784, 6.6974, 7.2289] +24-11-19 20:39:37 | D | best error = [ 5.2802, 5.2802, 5.2802, 5.2802, 5.2802] +24-11-19 20:39:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:37 | D | sum error = [ 7.9478, 8.4931, 9.2914, 9.9487, 10.6508] +24-11-19 20:39:37 | D | best error = [ 5.2802, 5.2802, 5.2802, 5.2802, 5.2802] +24-11-19 20:39:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:37 | D | sum error = [ 12.0385, 12.9663, 14.2657, 15.4296, 17.3164] +24-11-19 20:39:37 | D | best error = [ 5.2802, 5.2802, 5.2802, 5.2802, 5.2802] +24-11-19 20:39:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:37 | D | sum error = [ 19.1842, 20.1752, 22.0451, 23.8970, 24.9870] +24-11-19 20:39:37 | D | best error = [ 5.2802, 5.2802, 5.2802, 5.2802, 5.2802] +24-11-19 20:39:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:37 | D | sum error = [ 26.9392, 29.9120, 32.4217, 34.9801, 37.7388] +24-11-19 20:39:37 | D | best error = [ 5.2802, 5.2802, 5.2802, 5.2802, 5.2802] +24-11-19 20:39:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:37 | D | sum error = [ 40.7632, 44.1876, 47.5876, 52.0514, 56.1972] +24-11-19 20:39:37 | D | best error = [ 5.2802, 5.2802, 5.2802, 5.2802, 5.2802] +24-11-19 20:39:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:37 | D | sum error = [ 60.8464, 65.6266, 70.6765, 76.1765, 82.3972] +24-11-19 20:39:37 | D | best error = [ 5.2802, 5.2802, 5.2802, 5.2802, 5.2802] +24-11-19 20:39:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:37 | D | sum error = [ 89.1983, 96.2012, 103.2619, 111.1912, 119.5219] +24-11-19 20:39:37 | D | best error = [ 5.2802, 5.2802, 5.2802, 5.2802, 5.2802] +24-11-19 20:39:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:37 | D | sum error = [ 128.7575, 138.3678, 148.6289, 159.6813, 171.8763] +24-11-19 20:39:37 | D | best error = [ 5.2802, 5.2802, 5.2802, 5.2802, 5.2802] +24-11-19 20:39:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:37 | D | sum error = [ 184.1769, 197.1713, 211.5409, 227.0326, 243.1306] +24-11-19 20:39:37 | D | best error = [ 5.2802, 5.2802, 5.2802, 5.2802, 5.2802] +24-11-19 20:39:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:37 | D | sum error = [ 260.0701, 279.0573, 298.7595, 321.5253, 345.0804] +24-11-19 20:39:37 | D | best error = [ 5.2802, 5.2802, 5.2802, 5.2802, 5.2802] +24-11-19 20:39:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:37 | D | sum error = [ 370.7381, 398.7626, 428.3171, 460.3332, 495.4849] +24-11-19 20:39:37 | D | best error = [ 5.2802, 5.2802, 5.2802, 5.2802, 5.2802] +24-11-19 20:39:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:37 | D | sum error = [ 533.2644, 575.5492, 620.4681, 669.9187, 723.3499] +24-11-19 20:39:37 | D | best error = [ 5.2802, 5.2802, 5.2802, 5.2802, 5.2802] +24-11-19 20:39:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:37 | D | sum error = [ 781.8459, 844.7723, 912.9209, 986.3996, 1065.4182] +24-11-19 20:39:37 | D | best error = [ 5.2802, 5.2802, 5.2802, 5.2802, 5.2802] +24-11-19 20:39:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:37 | D | sum error = [ 1150.6145, 1241.9864, 1338.5872, 1439.9033, 1545.6462] +24-11-19 20:39:37 | D | best error = [ 5.2802, 5.2802, 5.2802, 5.2802, 5.2802] +24-11-19 20:39:37 | D | + error = [5.2802] +24-11-19 20:39:37 | D | - Calibrating model.layers.25.self_attn.k_proj.weight +24-11-19 20:39:37 | D | + w: sint8 +24-11-19 20:39:37 | D | + x: None +24-11-19 20:39:37 | D | + y: None +24-11-19 20:39:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:39:37 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:39:37 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:39:37 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:39:38 | D | - range ratio = [ 1.0000] +24-11-19 20:39:38 | D | sum error = [ 6.6351] +24-11-19 20:39:38 | D | best error = [ 6.6351] +24-11-19 20:39:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:51 | D | sum error = [ 6.2628, 5.8761, 5.7492, 7.6683, 6.1380] +24-11-19 20:39:51 | D | best error = [ 6.2628, 5.8761, 5.7492, 5.7492, 5.7492] +24-11-19 20:39:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:51 | D | sum error = [ 6.8635, 6.6034, 7.1559, 7.1211, 8.7534] +24-11-19 20:39:51 | D | best error = [ 5.7492, 5.7492, 5.7492, 5.7492, 5.7492] +24-11-19 20:39:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:51 | D | sum error = [ 9.1174, 10.1910, 9.5546, 12.1511, 10.1592] +24-11-19 20:39:51 | D | best error = [ 5.7492, 5.7492, 5.7492, 5.7492, 5.7492] +24-11-19 20:39:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:51 | D | sum error = [ 13.5324, 11.7020, 14.1429, 14.3130, 16.3438] +24-11-19 20:39:51 | D | best error = [ 5.7492, 5.7492, 5.7492, 5.7492, 5.7492] +24-11-19 20:39:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:51 | D | sum error = [ 16.9541, 19.3079, 20.4246, 22.7260, 23.8284] +24-11-19 20:39:51 | D | best error = [ 5.7492, 5.7492, 5.7492, 5.7492, 5.7492] +24-11-19 20:39:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:51 | D | sum error = [ 26.3812, 27.0845, 30.2841, 32.2662, 35.3494] +24-11-19 20:39:51 | D | best error = [ 5.7492, 5.7492, 5.7492, 5.7492, 5.7492] +24-11-19 20:39:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:51 | D | sum error = [ 38.9965, 41.3836, 42.3180, 45.7571, 50.5815] +24-11-19 20:39:51 | D | best error = [ 5.7492, 5.7492, 5.7492, 5.7492, 5.7492] +24-11-19 20:39:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:51 | D | sum error = [ 54.6992, 57.3380, 60.3769, 64.6433, 70.9819] +24-11-19 20:39:51 | D | best error = [ 5.7492, 5.7492, 5.7492, 5.7492, 5.7492] +24-11-19 20:39:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:51 | D | sum error = [ 73.8674, 79.0387, 83.7115, 88.9750, 95.0735] +24-11-19 20:39:51 | D | best error = [ 5.7492, 5.7492, 5.7492, 5.7492, 5.7492] +24-11-19 20:39:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:51 | D | sum error = [ 100.5315, 106.6677, 113.2383, 120.8785, 128.6089] +24-11-19 20:39:51 | D | best error = [ 5.7492, 5.7492, 5.7492, 5.7492, 5.7492] +24-11-19 20:39:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:51 | D | sum error = [ 137.5124, 147.7162, 158.0635, 169.2067, 181.3237] +24-11-19 20:39:51 | D | best error = [ 5.7492, 5.7492, 5.7492, 5.7492, 5.7492] +24-11-19 20:39:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:51 | D | sum error = [ 194.7595, 210.2304, 225.6993, 244.4785, 263.6791] +24-11-19 20:39:51 | D | best error = [ 5.7492, 5.7492, 5.7492, 5.7492, 5.7492] +24-11-19 20:39:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:51 | D | sum error = [ 285.3429, 309.8488, 335.9474, 365.5415, 394.7234] +24-11-19 20:39:51 | D | best error = [ 5.7492, 5.7492, 5.7492, 5.7492, 5.7492] +24-11-19 20:39:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:51 | D | sum error = [ 428.8979, 466.3193, 507.1596, 552.1193, 599.8479] +24-11-19 20:39:51 | D | best error = [ 5.7492, 5.7492, 5.7492, 5.7492, 5.7492] +24-11-19 20:39:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:51 | D | sum error = [ 653.4313, 713.2298, 777.8803, 847.9715, 926.9315] +24-11-19 20:39:51 | D | best error = [ 5.7492, 5.7492, 5.7492, 5.7492, 5.7492] +24-11-19 20:39:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:51 | D | sum error = [ 1008.6029, 1100.8568, 1198.7724, 1302.4779, 1412.3778] +24-11-19 20:39:51 | D | best error = [ 5.7492, 5.7492, 5.7492, 5.7492, 5.7492] +24-11-19 20:39:51 | D | + error = [5.7492] +24-11-19 20:39:51 | D | - Calibrating model.layers.25.self_attn.v_proj.weight +24-11-19 20:39:51 | D | + w: sint8 +24-11-19 20:39:51 | D | + x: None +24-11-19 20:39:51 | D | + y: None +24-11-19 20:39:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:51 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:39:51 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:39:51 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:39:51 | D | - range ratio = [ 1.0000] +24-11-19 20:39:51 | D | sum error = [ 2.4341] +24-11-19 20:39:51 | D | best error = [ 2.4341] +24-11-19 20:39:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:52 | D | sum error = [ 2.4355, 2.4232, 2.4445, 2.4453, 2.4879] +24-11-19 20:39:52 | D | best error = [ 2.2238, 2.1408, 2.1032, 2.0835, 2.0705] +24-11-19 20:39:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:52 | D | sum error = [ 2.5593, 2.6552, 2.7347, 2.8482, 3.0241] +24-11-19 20:39:52 | D | best error = [ 2.0628, 2.0597, 2.0585, 2.0584, 2.0584] +24-11-19 20:39:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:52 | D | sum error = [ 3.2090, 3.4213, 3.6362, 3.8723, 4.1415] +24-11-19 20:39:52 | D | best error = [ 2.0584, 2.0584, 2.0584, 2.0584, 2.0584] +24-11-19 20:39:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:52 | D | sum error = [ 4.4387, 4.7775, 5.0743, 5.4518, 5.8665] +24-11-19 20:39:52 | D | best error = [ 2.0584, 2.0584, 2.0584, 2.0584, 2.0584] +24-11-19 20:39:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:52 | D | sum error = [ 6.2986, 6.7346, 7.1753, 7.6866, 8.1995] +24-11-19 20:39:52 | D | best error = [ 2.0584, 2.0584, 2.0584, 2.0584, 2.0584] +24-11-19 20:39:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:52 | D | sum error = [ 8.8029, 9.3851, 10.0040, 10.6626, 11.3671] +24-11-19 20:39:52 | D | best error = [ 2.0584, 2.0584, 2.0584, 2.0584, 2.0584] +24-11-19 20:39:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:52 | D | sum error = [ 12.0966, 12.8922, 13.6821, 14.5535, 15.4851] +24-11-19 20:39:52 | D | best error = [ 2.0584, 2.0584, 2.0584, 2.0584, 2.0584] +24-11-19 20:39:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:52 | D | sum error = [ 16.4480, 17.4577, 18.5355, 19.6377, 20.8234] +24-11-19 20:39:52 | D | best error = [ 2.0584, 2.0584, 2.0584, 2.0584, 2.0584] +24-11-19 20:39:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:52 | D | sum error = [ 22.0410, 23.3600, 24.7011, 26.1244, 27.6192] +24-11-19 20:39:52 | D | best error = [ 2.0584, 2.0584, 2.0584, 2.0584, 2.0584] +24-11-19 20:39:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:52 | D | sum error = [ 29.1940, 30.8289, 32.5318, 34.3022, 36.1734] +24-11-19 20:39:52 | D | best error = [ 2.0584, 2.0584, 2.0584, 2.0584, 2.0584] +24-11-19 20:39:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:52 | D | sum error = [ 38.1281, 40.1646, 42.2688, 44.4926, 46.7915] +24-11-19 20:39:52 | D | best error = [ 2.0584, 2.0584, 2.0584, 2.0584, 2.0584] +24-11-19 20:39:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:52 | D | sum error = [ 49.1989, 51.7248, 54.3244, 57.0410, 59.8794] +24-11-19 20:39:52 | D | best error = [ 2.0584, 2.0584, 2.0584, 2.0584, 2.0584] +24-11-19 20:39:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:52 | D | sum error = [ 62.8049, 65.8534, 69.0111, 72.2828, 75.6784] +24-11-19 20:39:52 | D | best error = [ 2.0584, 2.0584, 2.0584, 2.0584, 2.0584] +24-11-19 20:39:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:52 | D | sum error = [ 79.2045, 82.8243, 86.5778, 90.4752, 94.4990] +24-11-19 20:39:52 | D | best error = [ 2.0584, 2.0584, 2.0584, 2.0584, 2.0584] +24-11-19 20:39:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:52 | D | sum error = [ 98.6662, 102.9633, 107.3972, 111.9672, 116.6580] +24-11-19 20:39:52 | D | best error = [ 2.0584, 2.0584, 2.0584, 2.0584, 2.0584] +24-11-19 20:39:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:52 | D | sum error = [ 121.5000, 126.4880, 131.6155, 136.8737, 142.2838] +24-11-19 20:39:52 | D | best error = [ 2.0584, 2.0584, 2.0584, 2.0584, 2.0584] +24-11-19 20:39:52 | D | + error = [2.0584] +24-11-19 20:39:52 | D | - Calibrating model.layers.25.self_attn.o_proj.weight +24-11-19 20:39:52 | D | + w: sint8 +24-11-19 20:39:52 | D | + x: None +24-11-19 20:39:52 | D | + y: None +24-11-19 20:39:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:52 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:39:52 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:39:52 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:39:52 | D | - range ratio = [ 1.0000] +24-11-19 20:39:52 | D | sum error = [ 0.5030] +24-11-19 20:39:52 | D | best error = [ 0.5030] +24-11-19 20:39:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:52 | D | sum error = [ 0.4973, 0.4957, 0.4937, 0.4946, 0.4968] +24-11-19 20:39:52 | D | best error = [ 0.4706, 0.4561, 0.4469, 0.4406, 0.4360] +24-11-19 20:39:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:52 | D | sum error = [ 0.5016, 0.5098, 0.5213, 0.5342, 0.5523] +24-11-19 20:39:52 | D | best error = [ 0.4322, 0.4299, 0.4282, 0.4268, 0.4259] +24-11-19 20:39:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:52 | D | sum error = [ 0.5712, 0.5957, 0.6224, 0.6547, 0.6870] +24-11-19 20:39:52 | D | best error = [ 0.4254, 0.4249, 0.4245, 0.4242, 0.4239] +24-11-19 20:39:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:52 | D | sum error = [ 0.7273, 0.7705, 0.8175, 0.8695, 0.9243] +24-11-19 20:39:52 | D | best error = [ 0.4238, 0.4237, 0.4237, 0.4236, 0.4236] +24-11-19 20:39:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:52 | D | sum error = [ 0.9858, 1.0494, 1.1193, 1.1938, 1.2731] +24-11-19 20:39:52 | D | best error = [ 0.4236, 0.4236, 0.4235, 0.4235, 0.4235] +24-11-19 20:39:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:52 | D | sum error = [ 1.3589, 1.4489, 1.5442, 1.6461, 1.7545] +24-11-19 20:39:52 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:39:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:52 | D | sum error = [ 1.8708, 1.9915, 2.1218, 2.2581, 2.4028] +24-11-19 20:39:52 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:39:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:52 | D | sum error = [ 2.5551, 2.7183, 2.8891, 3.0695, 3.2594] +24-11-19 20:39:52 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:39:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:52 | D | sum error = [ 3.4600, 3.6723, 3.8952, 4.1300, 4.3786] +24-11-19 20:39:52 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:39:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:52 | D | sum error = [ 4.6381, 4.9126, 5.2005, 5.5035, 5.8205] +24-11-19 20:39:52 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:39:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:52 | D | sum error = [ 6.1555, 6.5061, 6.8748, 7.2615, 7.6657] +24-11-19 20:39:52 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:39:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:52 | D | sum error = [ 8.0901, 8.5364, 9.0038, 9.4930, 10.0043] +24-11-19 20:39:52 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:39:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:52 | D | sum error = [ 10.5401, 11.1005, 11.6861, 12.2988, 12.9387] +24-11-19 20:39:52 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:39:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:52 | D | sum error = [ 13.6066, 14.3028, 15.0303, 15.7883, 16.5756] +24-11-19 20:39:52 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:39:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:52 | D | sum error = [ 17.3957, 18.2488, 19.1348, 20.0564, 21.0134] +24-11-19 20:39:52 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:39:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:52 | D | sum error = [ 22.0071, 23.0355, 24.1011, 25.2031, 26.3440] +24-11-19 20:39:52 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:39:52 | D | + error = [0.4235] +24-11-19 20:39:53 | D | - Calibrating model.layers.25.mlp.up_proj.weight +24-11-19 20:39:53 | D | + w: sint8 +24-11-19 20:39:53 | D | + x: None +24-11-19 20:39:53 | D | + y: None +24-11-19 20:39:53 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:53 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:39:53 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:39:53 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:39:53 | D | - range ratio = [ 1.0000] +24-11-19 20:39:53 | D | sum error = [ 0.4339] +24-11-19 20:39:53 | D | best error = [ 0.4339] +24-11-19 20:39:54 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:54 | D | sum error = [ 0.4311, 0.4296, 0.4301, 0.4362, 0.4441] +24-11-19 20:39:54 | D | best error = [ 0.3937, 0.3788, 0.3711, 0.3669, 0.3645] +24-11-19 20:39:54 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:54 | D | sum error = [ 0.4543, 0.4713, 0.4878, 0.5115, 0.5375] +24-11-19 20:39:54 | D | best error = [ 0.3632, 0.3627, 0.3625, 0.3624, 0.3624] +24-11-19 20:39:54 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:54 | D | sum error = [ 0.5696, 0.6048, 0.6432, 0.6879, 0.7330] +24-11-19 20:39:54 | D | best error = [ 0.3624, 0.3624, 0.3624, 0.3624, 0.3624] +24-11-19 20:39:54 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:54 | D | sum error = [ 0.7849, 0.8401, 0.9011, 0.9658, 1.0331] +24-11-19 20:39:54 | D | best error = [ 0.3624, 0.3624, 0.3624, 0.3624, 0.3624] +24-11-19 20:39:54 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:54 | D | sum error = [ 1.1060, 1.1854, 1.2681, 1.3563, 1.4517] +24-11-19 20:39:54 | D | best error = [ 0.3624, 0.3624, 0.3624, 0.3624, 0.3624] +24-11-19 20:39:54 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:54 | D | sum error = [ 1.5503, 1.6553, 1.7670, 1.8840, 2.0064] +24-11-19 20:39:54 | D | best error = [ 0.3624, 0.3624, 0.3624, 0.3624, 0.3624] +24-11-19 20:39:54 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:54 | D | sum error = [ 2.1377, 2.2739, 2.4175, 2.5669, 2.7259] +24-11-19 20:39:54 | D | best error = [ 0.3624, 0.3624, 0.3624, 0.3624, 0.3624] +24-11-19 20:39:54 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:54 | D | sum error = [ 2.8933, 3.0688, 3.2534, 3.4432, 3.6438] +24-11-19 20:39:54 | D | best error = [ 0.3624, 0.3624, 0.3624, 0.3624, 0.3624] +24-11-19 20:39:54 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:54 | D | sum error = [ 3.8539, 4.0751, 4.3047, 4.5458, 4.7970] +24-11-19 20:39:54 | D | best error = [ 0.3624, 0.3624, 0.3624, 0.3624, 0.3624] +24-11-19 20:39:54 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:54 | D | sum error = [ 5.0590, 5.3340, 5.6186, 5.9193, 6.2267] +24-11-19 20:39:54 | D | best error = [ 0.3624, 0.3624, 0.3624, 0.3624, 0.3624] +24-11-19 20:39:54 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:54 | D | sum error = [ 6.5488, 6.8809, 7.2285, 7.5874, 7.9593] +24-11-19 20:39:54 | D | best error = [ 0.3624, 0.3624, 0.3624, 0.3624, 0.3624] +24-11-19 20:39:54 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:54 | D | sum error = [ 8.3466, 8.7471, 9.1635, 9.5934, 10.0383] +24-11-19 20:39:54 | D | best error = [ 0.3624, 0.3624, 0.3624, 0.3624, 0.3624] +24-11-19 20:39:54 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:54 | D | sum error = [ 10.4992, 10.9736, 11.4647, 11.9724, 12.4943] +24-11-19 20:39:54 | D | best error = [ 0.3624, 0.3624, 0.3624, 0.3624, 0.3624] +24-11-19 20:39:54 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:54 | D | sum error = [ 13.0334, 13.5895, 14.1641, 14.7505, 15.3594] +24-11-19 20:39:54 | D | best error = [ 0.3624, 0.3624, 0.3624, 0.3624, 0.3624] +24-11-19 20:39:54 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:54 | D | sum error = [ 15.9799, 16.6186, 17.2784, 17.9568, 18.6503] +24-11-19 20:39:54 | D | best error = [ 0.3624, 0.3624, 0.3624, 0.3624, 0.3624] +24-11-19 20:39:54 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:54 | D | sum error = [ 19.3590, 20.0948, 20.8414, 21.6117, 22.4010] +24-11-19 20:39:54 | D | best error = [ 0.3624, 0.3624, 0.3624, 0.3624, 0.3624] +24-11-19 20:39:54 | D | + error = [0.3624] +24-11-19 20:39:54 | D | - Calibrating model.layers.25.mlp.gate_proj.weight +24-11-19 20:39:54 | D | + w: sint8 +24-11-19 20:39:54 | D | + x: None +24-11-19 20:39:54 | D | + y: None +24-11-19 20:39:54 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:54 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:39:54 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:39:55 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:39:55 | D | - range ratio = [ 1.0000] +24-11-19 20:39:55 | D | sum error = [ 10.9392] +24-11-19 20:39:55 | D | best error = [ 10.9392] +24-11-19 20:39:56 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:56 | D | sum error = [ 10.8715, 10.8531, 10.8998, 11.0190, 11.2059] +24-11-19 20:39:56 | D | best error = [ 9.9274, 9.5581, 9.3780, 9.2724, 9.2155] +24-11-19 20:39:56 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:56 | D | sum error = [ 11.5394, 11.8869, 12.4038, 13.0103, 13.6876] +24-11-19 20:39:56 | D | best error = [ 9.1857, 9.1712, 9.1664, 9.1644, 9.1640] +24-11-19 20:39:56 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:56 | D | sum error = [ 14.4633, 15.3672, 16.4001, 17.5092, 18.6912] +24-11-19 20:39:56 | D | best error = [ 9.1639, 9.1638, 9.1638, 9.1638, 9.1638] +24-11-19 20:39:56 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:56 | D | sum error = [ 20.0395, 21.4641, 22.9806, 24.6725, 26.4526] +24-11-19 20:39:56 | D | best error = [ 9.1638, 9.1638, 9.1638, 9.1638, 9.1638] +24-11-19 20:39:56 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:56 | D | sum error = [ 28.3201, 30.3771, 32.5283, 34.8515, 37.2384] +24-11-19 20:39:56 | D | best error = [ 9.1638, 9.1638, 9.1638, 9.1638, 9.1638] +24-11-19 20:39:56 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:56 | D | sum error = [ 39.8811, 42.5737, 45.5212, 48.5663, 51.7860] +24-11-19 20:39:56 | D | best error = [ 9.1638, 9.1638, 9.1638, 9.1638, 9.1638] +24-11-19 20:39:56 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:56 | D | sum error = [ 55.2408, 58.8788, 62.7749, 66.8264, 71.1312] +24-11-19 20:39:56 | D | best error = [ 9.1638, 9.1638, 9.1638, 9.1638, 9.1638] +24-11-19 20:39:56 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:56 | D | sum error = [ 75.6155, 80.4510, 85.4828, 90.7505, 96.3130] +24-11-19 20:39:56 | D | best error = [ 9.1638, 9.1638, 9.1638, 9.1638, 9.1638] +24-11-19 20:39:56 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:56 | D | sum error = [ 102.2010, 108.3891, 114.8492, 121.6864, 128.8300] +24-11-19 20:39:56 | D | best error = [ 9.1638, 9.1638, 9.1638, 9.1638, 9.1638] +24-11-19 20:39:56 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:56 | D | sum error = [ 136.3782, 144.2857, 152.5709, 161.2804, 170.4640] +24-11-19 20:39:56 | D | best error = [ 9.1638, 9.1638, 9.1638, 9.1638, 9.1638] +24-11-19 20:39:56 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:56 | D | sum error = [ 180.0026, 190.0447, 200.5661, 211.5502, 223.1051] +24-11-19 20:39:56 | D | best error = [ 9.1638, 9.1638, 9.1638, 9.1638, 9.1638] +24-11-19 20:39:56 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:56 | D | sum error = [ 235.1187, 247.7701, 260.9385, 274.6974, 289.1019] +24-11-19 20:39:56 | D | best error = [ 9.1638, 9.1638, 9.1638, 9.1638, 9.1638] +24-11-19 20:39:56 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:56 | D | sum error = [ 304.1659, 319.8612, 336.2237, 353.3073, 371.1021] +24-11-19 20:39:56 | D | best error = [ 9.1638, 9.1638, 9.1638, 9.1638, 9.1638] +24-11-19 20:39:56 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:56 | D | sum error = [ 389.6223, 408.8374, 428.8725, 449.6989, 471.3043] +24-11-19 20:39:56 | D | best error = [ 9.1638, 9.1638, 9.1638, 9.1638, 9.1638] +24-11-19 20:39:56 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:56 | D | sum error = [ 493.7443, 516.9779, 541.0965, 566.0002, 591.7398] +24-11-19 20:39:56 | D | best error = [ 9.1638, 9.1638, 9.1638, 9.1638, 9.1638] +24-11-19 20:39:56 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:56 | D | sum error = [ 618.3417, 645.8108, 674.1372, 703.3157, 733.3602] +24-11-19 20:39:56 | D | best error = [ 9.1638, 9.1638, 9.1638, 9.1638, 9.1638] +24-11-19 20:39:56 | D | + error = [9.1638] +24-11-19 20:39:56 | D | - Calibrating model.layers.25.mlp.down_proj.weight +24-11-19 20:39:56 | D | + w: sint8 +24-11-19 20:39:56 | D | + x: None +24-11-19 20:39:56 | D | + y: None +24-11-19 20:39:56 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:56 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:39:56 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:39:56 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:39:56 | D | - range ratio = [ 1.0000] +24-11-19 20:39:56 | D | sum error = [ 1.1901] +24-11-19 20:39:56 | D | best error = [ 1.1901] +24-11-19 20:39:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:57 | D | sum error = [ 1.1816, 1.1752, 1.1733, 1.1717, 1.1787] +24-11-19 20:39:57 | D | best error = [ 1.1442, 1.1208, 1.1057, 1.0952, 1.0871] +24-11-19 20:39:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:57 | D | sum error = [ 1.1900, 1.2084, 1.2359, 1.2684, 1.3130] +24-11-19 20:39:57 | D | best error = [ 1.0814, 1.0764, 1.0733, 1.0713, 1.0699] +24-11-19 20:39:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:57 | D | sum error = [ 1.3652, 1.4237, 1.4991, 1.5770, 1.6717] +24-11-19 20:39:57 | D | best error = [ 1.0691, 1.0684, 1.0681, 1.0679, 1.0678] +24-11-19 20:39:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:57 | D | sum error = [ 1.7740, 1.8871, 2.0144, 2.1510, 2.2992] +24-11-19 20:39:57 | D | best error = [ 1.0677, 1.0677, 1.0677, 1.0677, 1.0677] +24-11-19 20:39:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:57 | D | sum error = [ 2.4609, 2.6321, 2.8173, 3.0161, 3.2280] +24-11-19 20:39:57 | D | best error = [ 1.0677, 1.0677, 1.0677, 1.0677, 1.0677] +24-11-19 20:39:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:57 | D | sum error = [ 3.4558, 3.6963, 3.9554, 4.2219, 4.5129] +24-11-19 20:39:57 | D | best error = [ 1.0677, 1.0677, 1.0677, 1.0677, 1.0677] +24-11-19 20:39:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:57 | D | sum error = [ 4.8177, 5.1400, 5.4798, 5.8390, 6.2168] +24-11-19 20:39:57 | D | best error = [ 1.0677, 1.0677, 1.0677, 1.0677, 1.0677] +24-11-19 20:39:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:57 | D | sum error = [ 6.6168, 7.0387, 7.4862, 7.9519, 8.4471] +24-11-19 20:39:57 | D | best error = [ 1.0677, 1.0677, 1.0677, 1.0677, 1.0677] +24-11-19 20:39:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:57 | D | sum error = [ 8.9683, 9.5128, 10.0857, 10.6915, 11.3238] +24-11-19 20:39:57 | D | best error = [ 1.0677, 1.0677, 1.0677, 1.0677, 1.0677] +24-11-19 20:39:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:57 | D | sum error = [ 11.9892, 12.6870, 13.4187, 14.1867, 14.9910] +24-11-19 20:39:57 | D | best error = [ 1.0677, 1.0677, 1.0677, 1.0677, 1.0677] +24-11-19 20:39:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:57 | D | sum error = [ 15.8339, 16.7164, 17.6427, 18.6086, 19.6188] +24-11-19 20:39:57 | D | best error = [ 1.0677, 1.0677, 1.0677, 1.0677, 1.0677] +24-11-19 20:39:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:57 | D | sum error = [ 20.6745, 21.7782, 22.9274, 24.1283, 25.3761] +24-11-19 20:39:57 | D | best error = [ 1.0677, 1.0677, 1.0677, 1.0677, 1.0677] +24-11-19 20:39:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:57 | D | sum error = [ 26.6781, 28.0344, 29.4458, 30.9137, 32.4381] +24-11-19 20:39:57 | D | best error = [ 1.0677, 1.0677, 1.0677, 1.0677, 1.0677] +24-11-19 20:39:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:57 | D | sum error = [ 34.0217, 35.6696, 37.3779, 39.1499, 40.9892] +24-11-19 20:39:57 | D | best error = [ 1.0677, 1.0677, 1.0677, 1.0677, 1.0677] +24-11-19 20:39:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:57 | D | sum error = [ 42.8963, 44.8721, 46.9198, 49.0347, 51.2244] +24-11-19 20:39:57 | D | best error = [ 1.0677, 1.0677, 1.0677, 1.0677, 1.0677] +24-11-19 20:39:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:57 | D | sum error = [ 53.4868, 55.8243, 58.2356, 60.7273, 63.2965] +24-11-19 20:39:57 | D | best error = [ 1.0677, 1.0677, 1.0677, 1.0677, 1.0677] +24-11-19 20:39:57 | D | + error = [1.0677] +24-11-19 20:39:58 | D | - Quantizing model.layers.25.self_attn.q_proj.weight +24-11-19 20:39:59 | D | - Quantizing model.layers.25.self_attn.k_proj.weight +24-11-19 20:40:00 | D | - Quantizing model.layers.25.self_attn.v_proj.weight +24-11-19 20:40:01 | D | - Quantizing model.layers.25.self_attn.o_proj.weight +24-11-19 20:40:02 | D | - Quantizing model.layers.25.mlp.up_proj.weight +24-11-19 20:40:03 | D | - Quantizing model.layers.25.mlp.gate_proj.weight +24-11-19 20:40:04 | D | - Quantizing model.layers.25.mlp.down_proj.weight +24-11-19 20:40:15 | D | - Quantizing layer model.layers.26 +24-11-19 20:40:15 | D | - Calibrating model.layers.26.self_attn.q_proj.weight +24-11-19 20:40:15 | D | + w: sint8 +24-11-19 20:40:15 | D | + x: None +24-11-19 20:40:15 | D | + y: None +24-11-19 20:40:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:40:15 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:40:15 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:40:15 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:15 | D | - range ratio = [ 1.0000] +24-11-19 20:40:15 | D | sum error = [ 6.0599] +24-11-19 20:40:15 | D | best error = [ 6.0599] +24-11-19 20:40:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:29 | D | sum error = [ 6.1647, 5.7329, 5.9699, 6.1397, 6.0607] +24-11-19 20:40:29 | D | best error = [ 6.0599, 5.7329, 5.7329, 5.7329, 5.7329] +24-11-19 20:40:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:29 | D | sum error = [ 6.4952, 6.4950, 7.0647, 7.3584, 7.5296] +24-11-19 20:40:29 | D | best error = [ 5.7329, 5.7329, 5.7329, 5.7329, 5.7329] +24-11-19 20:40:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:29 | D | sum error = [ 8.1523, 8.9730, 9.2147, 9.9322, 10.6238] +24-11-19 20:40:29 | D | best error = [ 5.7329, 5.7329, 5.7329, 5.7329, 5.7329] +24-11-19 20:40:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:29 | D | sum error = [ 11.5669, 12.2576, 13.5912, 14.7519, 15.9435] +24-11-19 20:40:29 | D | best error = [ 5.7329, 5.7329, 5.7329, 5.7329, 5.7329] +24-11-19 20:40:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:29 | D | sum error = [ 17.3830, 18.8889, 20.3191, 21.9301, 23.8390] +24-11-19 20:40:29 | D | best error = [ 5.7329, 5.7329, 5.7329, 5.7329, 5.7329] +24-11-19 20:40:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:29 | D | sum error = [ 26.1783, 27.9601, 30.5808, 33.8433, 36.4874] +24-11-19 20:40:29 | D | best error = [ 5.7329, 5.7329, 5.7329, 5.7329, 5.7329] +24-11-19 20:40:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:29 | D | sum error = [ 39.6715, 42.7938, 47.2551, 51.1878, 55.4954] +24-11-19 20:40:29 | D | best error = [ 5.7329, 5.7329, 5.7329, 5.7329, 5.7329] +24-11-19 20:40:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:29 | D | sum error = [ 60.2242, 66.0759, 71.3181, 77.4162, 84.0813] +24-11-19 20:40:29 | D | best error = [ 5.7329, 5.7329, 5.7329, 5.7329, 5.7329] +24-11-19 20:40:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:29 | D | sum error = [ 90.7993, 98.8111, 107.3343, 116.1759, 125.5807] +24-11-19 20:40:29 | D | best error = [ 5.7329, 5.7329, 5.7329, 5.7329, 5.7329] +24-11-19 20:40:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:29 | D | sum error = [ 136.1790, 147.0493, 159.3424, 171.9799, 185.2938] +24-11-19 20:40:29 | D | best error = [ 5.7329, 5.7329, 5.7329, 5.7329, 5.7329] +24-11-19 20:40:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:29 | D | sum error = [ 199.6579, 215.2561, 231.0435, 248.6347, 267.1624] +24-11-19 20:40:29 | D | best error = [ 5.7329, 5.7329, 5.7329, 5.7329, 5.7329] +24-11-19 20:40:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:29 | D | sum error = [ 286.6162, 308.5135, 331.0929, 354.7963, 380.6284] +24-11-19 20:40:29 | D | best error = [ 5.7329, 5.7329, 5.7329, 5.7329, 5.7329] +24-11-19 20:40:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:29 | D | sum error = [ 408.0265, 437.5686, 468.0808, 501.1973, 536.2056] +24-11-19 20:40:29 | D | best error = [ 5.7329, 5.7329, 5.7329, 5.7329, 5.7329] +24-11-19 20:40:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:29 | D | sum error = [ 573.8299, 613.9294, 655.8919, 700.0787, 746.5262] +24-11-19 20:40:29 | D | best error = [ 5.7329, 5.7329, 5.7329, 5.7329, 5.7329] +24-11-19 20:40:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:29 | D | sum error = [ 796.6022, 848.9584, 903.9539, 961.2490, 1020.5781] +24-11-19 20:40:29 | D | best error = [ 5.7329, 5.7329, 5.7329, 5.7329, 5.7329] +24-11-19 20:40:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:29 | D | sum error = [ 1081.9909, 1144.7268, 1208.4908, 1272.6690, 1336.7388] +24-11-19 20:40:29 | D | best error = [ 5.7329, 5.7329, 5.7329, 5.7329, 5.7329] +24-11-19 20:40:29 | D | + error = [5.7329] +24-11-19 20:40:29 | D | - Calibrating model.layers.26.self_attn.k_proj.weight +24-11-19 20:40:29 | D | + w: sint8 +24-11-19 20:40:29 | D | + x: None +24-11-19 20:40:29 | D | + y: None +24-11-19 20:40:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:40:29 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:40:29 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:40:29 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:40:30 | D | - range ratio = [ 1.0000] +24-11-19 20:40:30 | D | sum error = [ 6.0926] +24-11-19 20:40:30 | D | best error = [ 6.0926] +24-11-19 20:40:42 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:42 | D | sum error = [ 5.8672, 6.6562, 6.7479, 6.7805, 5.6005] +24-11-19 20:40:42 | D | best error = [ 5.8672, 5.8672, 5.8672, 5.8672, 5.6005] +24-11-19 20:40:42 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:42 | D | sum error = [ 6.5094, 6.4776, 7.0948, 7.1771, 7.1169] +24-11-19 20:40:42 | D | best error = [ 5.6005, 5.6005, 5.6005, 5.6005, 5.6005] +24-11-19 20:40:42 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:42 | D | sum error = [ 7.8910, 9.4339, 11.3930, 9.7986, 10.7334] +24-11-19 20:40:42 | D | best error = [ 5.6005, 5.6005, 5.6005, 5.6005, 5.6005] +24-11-19 20:40:42 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:42 | D | sum error = [ 13.5176, 12.2047, 14.4135, 14.6299, 17.9746] +24-11-19 20:40:42 | D | best error = [ 5.6005, 5.6005, 5.6005, 5.6005, 5.6005] +24-11-19 20:40:42 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:42 | D | sum error = [ 18.1188, 18.7682, 19.2829, 21.3414, 23.2627] +24-11-19 20:40:42 | D | best error = [ 5.6005, 5.6005, 5.6005, 5.6005, 5.6005] +24-11-19 20:40:42 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:42 | D | sum error = [ 25.9335, 26.7432, 29.8110, 32.3515, 34.5112] +24-11-19 20:40:42 | D | best error = [ 5.6005, 5.6005, 5.6005, 5.6005, 5.6005] +24-11-19 20:40:42 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:42 | D | sum error = [ 37.8402, 40.8559, 44.3520, 46.4108, 50.9674] +24-11-19 20:40:42 | D | best error = [ 5.6005, 5.6005, 5.6005, 5.6005, 5.6005] +24-11-19 20:40:42 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:42 | D | sum error = [ 55.1286, 60.0121, 63.9827, 70.0122, 75.6311] +24-11-19 20:40:42 | D | best error = [ 5.6005, 5.6005, 5.6005, 5.6005, 5.6005] +24-11-19 20:40:42 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:42 | D | sum error = [ 81.5188, 86.6595, 95.7305, 101.1743, 111.3674] +24-11-19 20:40:42 | D | best error = [ 5.6005, 5.6005, 5.6005, 5.6005, 5.6005] +24-11-19 20:40:42 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:42 | D | sum error = [ 118.4474, 128.2910, 136.2217, 147.6830, 159.3254] +24-11-19 20:40:42 | D | best error = [ 5.6005, 5.6005, 5.6005, 5.6005, 5.6005] +24-11-19 20:40:42 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:42 | D | sum error = [ 170.6992, 183.7440, 197.6675, 213.2254, 229.5582] +24-11-19 20:40:42 | D | best error = [ 5.6005, 5.6005, 5.6005, 5.6005, 5.6005] +24-11-19 20:40:42 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:42 | D | sum error = [ 247.8878, 265.8429, 286.6578, 305.3443, 327.2473] +24-11-19 20:40:42 | D | best error = [ 5.6005, 5.6005, 5.6005, 5.6005, 5.6005] +24-11-19 20:40:42 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:42 | D | sum error = [ 351.9569, 376.3469, 402.8931, 433.1390, 463.9365] +24-11-19 20:40:42 | D | best error = [ 5.6005, 5.6005, 5.6005, 5.6005, 5.6005] +24-11-19 20:40:42 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:42 | D | sum error = [ 499.1762, 533.8688, 571.9380, 613.1053, 655.6856] +24-11-19 20:40:42 | D | best error = [ 5.6005, 5.6005, 5.6005, 5.6005, 5.6005] +24-11-19 20:40:42 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:42 | D | sum error = [ 701.1540, 749.7778, 803.0404, 856.4256, 914.7857] +24-11-19 20:40:42 | D | best error = [ 5.6005, 5.6005, 5.6005, 5.6005, 5.6005] +24-11-19 20:40:42 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:42 | D | sum error = [ 975.8376, 1040.1278, 1105.9268, 1176.1661, 1244.5231] +24-11-19 20:40:42 | D | best error = [ 5.6005, 5.6005, 5.6005, 5.6005, 5.6005] +24-11-19 20:40:42 | D | + error = [5.6005] +24-11-19 20:40:42 | D | - Calibrating model.layers.26.self_attn.v_proj.weight +24-11-19 20:40:42 | D | + w: sint8 +24-11-19 20:40:42 | D | + x: None +24-11-19 20:40:42 | D | + y: None +24-11-19 20:40:42 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:42 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:40:42 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:40:42 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:42 | D | - range ratio = [ 1.0000] +24-11-19 20:40:42 | D | sum error = [ 2.4248] +24-11-19 20:40:42 | D | best error = [ 2.4248] +24-11-19 20:40:42 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:42 | D | sum error = [ 2.4024, 2.3859, 2.3805, 2.4439, 2.4704] +24-11-19 20:40:42 | D | best error = [ 2.1887, 2.1093, 2.0654, 2.0439, 2.0305] +24-11-19 20:40:42 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:42 | D | sum error = [ 2.5183, 2.6040, 2.7198, 2.8819, 3.0012] +24-11-19 20:40:42 | D | best error = [ 2.0218, 2.0192, 2.0178, 2.0170, 2.0170] +24-11-19 20:40:42 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:42 | D | sum error = [ 3.1474, 3.3887, 3.6177, 3.8172, 4.1185] +24-11-19 20:40:42 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 20:40:42 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:42 | D | sum error = [ 4.3623, 4.6830, 5.0141, 5.3884, 5.7596] +24-11-19 20:40:42 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 20:40:42 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:42 | D | sum error = [ 6.1457, 6.6018, 7.0412, 7.5300, 8.0441] +24-11-19 20:40:42 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 20:40:42 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:42 | D | sum error = [ 8.5915, 9.1705, 9.7760, 10.4123, 11.1029] +24-11-19 20:40:42 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 20:40:42 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:42 | D | sum error = [ 11.7859, 12.5277, 13.3887, 14.1812, 15.0887] +24-11-19 20:40:42 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 20:40:42 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:42 | D | sum error = [ 16.0147, 16.9862, 17.9851, 19.0754, 20.1663] +24-11-19 20:40:42 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 20:40:42 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:42 | D | sum error = [ 21.3655, 22.5483, 23.8772, 25.1961, 26.6118] +24-11-19 20:40:42 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 20:40:42 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:42 | D | sum error = [ 28.0866, 29.6174, 31.2250, 32.9021, 34.6398] +24-11-19 20:40:42 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 20:40:42 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:42 | D | sum error = [ 36.4518, 38.3266, 40.2833, 42.3020, 44.4398] +24-11-19 20:40:42 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 20:40:42 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:42 | D | sum error = [ 46.6340, 48.9183, 51.2743, 53.7250, 56.2670] +24-11-19 20:40:42 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 20:40:42 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:42 | D | sum error = [ 58.8851, 61.5865, 64.3782, 67.2615, 70.2331] +24-11-19 20:40:42 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 20:40:42 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:42 | D | sum error = [ 73.3053, 76.4552, 79.7188, 83.0877, 86.5351] +24-11-19 20:40:42 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 20:40:42 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:42 | D | sum error = [ 90.0949, 93.7640, 97.5335, 101.4211, 105.4139] +24-11-19 20:40:42 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 20:40:42 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:42 | D | sum error = [ 109.5293, 113.7373, 118.0573, 122.4693, 126.9942] +24-11-19 20:40:42 | D | best error = [ 2.0170, 2.0170, 2.0170, 2.0170, 2.0170] +24-11-19 20:40:42 | D | + error = [2.0170] +24-11-19 20:40:43 | D | - Calibrating model.layers.26.self_attn.o_proj.weight +24-11-19 20:40:43 | D | + w: sint8 +24-11-19 20:40:43 | D | + x: None +24-11-19 20:40:43 | D | + y: None +24-11-19 20:40:43 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:43 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:40:43 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:40:43 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:43 | D | - range ratio = [ 1.0000] +24-11-19 20:40:43 | D | sum error = [ 0.5938] +24-11-19 20:40:43 | D | best error = [ 0.5938] +24-11-19 20:40:43 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:43 | D | sum error = [ 0.5904, 0.5887, 0.5892, 0.5923, 0.5980] +24-11-19 20:40:43 | D | best error = [ 0.5494, 0.5296, 0.5179, 0.5102, 0.5048] +24-11-19 20:40:43 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:43 | D | sum error = [ 0.6106, 0.6267, 0.6473, 0.6713, 0.7010] +24-11-19 20:40:43 | D | best error = [ 0.5013, 0.4988, 0.4971, 0.4959, 0.4951] +24-11-19 20:40:43 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:43 | D | sum error = [ 0.7332, 0.7705, 0.8133, 0.8622, 0.9172] +24-11-19 20:40:43 | D | best error = [ 0.4945, 0.4939, 0.4935, 0.4932, 0.4929] +24-11-19 20:40:43 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:43 | D | sum error = [ 0.9737, 1.0382, 1.1045, 1.1803, 1.2564] +24-11-19 20:40:43 | D | best error = [ 0.4928, 0.4927, 0.4926, 0.4926, 0.4925] +24-11-19 20:40:43 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:43 | D | sum error = [ 1.3408, 1.4308, 1.5291, 1.6322, 1.7406] +24-11-19 20:40:43 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 20:40:43 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:43 | D | sum error = [ 1.8541, 1.9763, 2.1065, 2.2428, 2.3893] +24-11-19 20:40:43 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 20:40:43 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:43 | D | sum error = [ 2.5410, 2.7008, 2.8689, 3.0503, 3.2382] +24-11-19 20:40:43 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 20:40:43 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:43 | D | sum error = [ 3.4350, 3.6435, 3.8637, 4.0939, 4.3404] +24-11-19 20:40:43 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 20:40:43 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:43 | D | sum error = [ 4.5975, 4.8669, 5.1491, 5.4447, 5.7572] +24-11-19 20:40:43 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 20:40:43 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:43 | D | sum error = [ 6.0817, 6.4255, 6.7823, 7.1583, 7.5491] +24-11-19 20:40:43 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 20:40:43 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:43 | D | sum error = [ 7.9614, 8.3915, 8.8414, 9.3090, 9.7993] +24-11-19 20:40:43 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 20:40:43 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:43 | D | sum error = [ 10.3123, 10.8503, 11.4099, 11.9943, 12.6054] +24-11-19 20:40:43 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 20:40:43 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:43 | D | sum error = [ 13.2426, 13.9040, 14.5937, 15.3154, 16.0647] +24-11-19 20:40:43 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 20:40:43 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:43 | D | sum error = [ 16.8437, 17.6542, 18.4954, 19.3708, 20.2797] +24-11-19 20:40:43 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 20:40:43 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:43 | D | sum error = [ 21.2227, 22.2026, 23.2176, 24.2702, 25.3575] +24-11-19 20:40:43 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 20:40:43 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:43 | D | sum error = [ 26.4823, 27.6470, 28.8502, 30.0936, 31.3766] +24-11-19 20:40:43 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4925, 0.4925] +24-11-19 20:40:43 | D | + error = [0.4925] +24-11-19 20:40:43 | D | - Calibrating model.layers.26.mlp.up_proj.weight +24-11-19 20:40:43 | D | + w: sint8 +24-11-19 20:40:43 | D | + x: None +24-11-19 20:40:43 | D | + y: None +24-11-19 20:40:43 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:43 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:40:44 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:40:44 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:44 | D | - range ratio = [ 1.0000] +24-11-19 20:40:44 | D | sum error = [ 0.4543] +24-11-19 20:40:44 | D | best error = [ 0.4543] +24-11-19 20:40:45 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:45 | D | sum error = [ 0.4518, 0.4521, 0.4522, 0.4591, 0.4660] +24-11-19 20:40:45 | D | best error = [ 0.4097, 0.3935, 0.3852, 0.3807, 0.3782] +24-11-19 20:40:45 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:45 | D | sum error = [ 0.4784, 0.4958, 0.5146, 0.5404, 0.5672] +24-11-19 20:40:45 | D | best error = [ 0.3768, 0.3762, 0.3760, 0.3759, 0.3759] +24-11-19 20:40:45 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:45 | D | sum error = [ 0.6008, 0.6376, 0.6806, 0.7245, 0.7757] +24-11-19 20:40:45 | D | best error = [ 0.3759, 0.3759, 0.3759, 0.3759, 0.3759] +24-11-19 20:40:45 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:45 | D | sum error = [ 0.8271, 0.8875, 0.9504, 1.0209, 1.0913] +24-11-19 20:40:45 | D | best error = [ 0.3759, 0.3759, 0.3759, 0.3759, 0.3759] +24-11-19 20:40:45 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:45 | D | sum error = [ 1.1704, 1.2509, 1.3383, 1.4301, 1.5286] +24-11-19 20:40:45 | D | best error = [ 0.3759, 0.3759, 0.3759, 0.3759, 0.3759] +24-11-19 20:40:45 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:45 | D | sum error = [ 1.6320, 1.7441, 1.8592, 1.9810, 2.1094] +24-11-19 20:40:45 | D | best error = [ 0.3759, 0.3759, 0.3759, 0.3759, 0.3759] +24-11-19 20:40:45 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:45 | D | sum error = [ 2.2474, 2.3887, 2.5401, 2.7000, 2.8660] +24-11-19 20:40:45 | D | best error = [ 0.3759, 0.3759, 0.3759, 0.3759, 0.3759] +24-11-19 20:40:45 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:45 | D | sum error = [ 3.0416, 3.2255, 3.4178, 3.6176, 3.8289] +24-11-19 20:40:45 | D | best error = [ 0.3759, 0.3759, 0.3759, 0.3759, 0.3759] +24-11-19 20:40:45 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:45 | D | sum error = [ 4.0497, 4.2821, 4.5232, 4.7757, 5.0384] +24-11-19 20:40:45 | D | best error = [ 0.3759, 0.3759, 0.3759, 0.3759, 0.3759] +24-11-19 20:40:45 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:45 | D | sum error = [ 5.3159, 5.6011, 5.9028, 6.2138, 6.5390] +24-11-19 20:40:45 | D | best error = [ 0.3759, 0.3759, 0.3759, 0.3759, 0.3759] +24-11-19 20:40:45 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:45 | D | sum error = [ 6.8750, 7.2260, 7.5904, 7.9685, 8.3603] +24-11-19 20:40:45 | D | best error = [ 0.3759, 0.3759, 0.3759, 0.3759, 0.3759] +24-11-19 20:40:45 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:45 | D | sum error = [ 8.7677, 9.1884, 9.6249, 10.0769, 10.5460] +24-11-19 20:40:45 | D | best error = [ 0.3759, 0.3759, 0.3759, 0.3759, 0.3759] +24-11-19 20:40:45 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:45 | D | sum error = [ 11.0265, 11.5264, 12.0433, 12.5713, 13.1191] +24-11-19 20:40:45 | D | best error = [ 0.3759, 0.3759, 0.3759, 0.3759, 0.3759] +24-11-19 20:40:45 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:45 | D | sum error = [ 13.6841, 14.2642, 14.8650, 15.4817, 16.1163] +24-11-19 20:40:45 | D | best error = [ 0.3759, 0.3759, 0.3759, 0.3759, 0.3759] +24-11-19 20:40:45 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:45 | D | sum error = [ 16.7654, 17.4356, 18.1276, 18.8327, 19.5609] +24-11-19 20:40:45 | D | best error = [ 0.3759, 0.3759, 0.3759, 0.3759, 0.3759] +24-11-19 20:40:45 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:45 | D | sum error = [ 20.3082, 21.0729, 21.8558, 22.6598, 23.4842] +24-11-19 20:40:45 | D | best error = [ 0.3759, 0.3759, 0.3759, 0.3759, 0.3759] +24-11-19 20:40:45 | D | + error = [0.3759] +24-11-19 20:40:45 | D | - Calibrating model.layers.26.mlp.gate_proj.weight +24-11-19 20:40:45 | D | + w: sint8 +24-11-19 20:40:45 | D | + x: None +24-11-19 20:40:45 | D | + y: None +24-11-19 20:40:45 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:45 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:40:45 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:40:45 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:45 | D | - range ratio = [ 1.0000] +24-11-19 20:40:45 | D | sum error = [ 11.4900] +24-11-19 20:40:45 | D | best error = [ 11.4900] +24-11-19 20:40:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:47 | D | sum error = [ 11.3942, 11.3913, 11.4394, 11.5475, 11.7260] +24-11-19 20:40:47 | D | best error = [ 10.3062, 9.9039, 9.7026, 9.5833, 9.5154] +24-11-19 20:40:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:47 | D | sum error = [ 12.0930, 12.5045, 12.9554, 13.5918, 14.3242] +24-11-19 20:40:47 | D | best error = [ 9.4839, 9.4700, 9.4638, 9.4619, 9.4615] +24-11-19 20:40:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:47 | D | sum error = [ 15.1527, 16.0658, 17.0957, 18.2945, 19.5194] +24-11-19 20:40:47 | D | best error = [ 9.4613, 9.4613, 9.4613, 9.4613, 9.4613] +24-11-19 20:40:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:47 | D | sum error = [ 20.9232, 22.3675, 23.9583, 25.6657, 27.5290] +24-11-19 20:40:47 | D | best error = [ 9.4613, 9.4613, 9.4613, 9.4613, 9.4613] +24-11-19 20:40:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:47 | D | sum error = [ 29.4934, 31.5973, 33.8328, 36.1941, 38.7603] +24-11-19 20:40:47 | D | best error = [ 9.4613, 9.4613, 9.4613, 9.4613, 9.4613] +24-11-19 20:40:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:47 | D | sum error = [ 41.4290, 44.2760, 47.3069, 50.5189, 53.9303] +24-11-19 20:40:47 | D | best error = [ 9.4613, 9.4613, 9.4613, 9.4613, 9.4613] +24-11-19 20:40:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:47 | D | sum error = [ 57.4773, 61.2778, 65.3476, 69.5287, 74.0568] +24-11-19 20:40:47 | D | best error = [ 9.4613, 9.4613, 9.4613, 9.4613, 9.4613] +24-11-19 20:40:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:47 | D | sum error = [ 78.7961, 83.8376, 89.1149, 94.7144, 100.5970] +24-11-19 20:40:47 | D | best error = [ 9.4613, 9.4613, 9.4613, 9.4613, 9.4613] +24-11-19 20:40:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:47 | D | sum error = [ 106.7995, 113.3104, 120.2053, 127.4743, 135.0936] +24-11-19 20:40:47 | D | best error = [ 9.4613, 9.4613, 9.4613, 9.4613, 9.4613] +24-11-19 20:40:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:47 | D | sum error = [ 143.1079, 151.5223, 160.3807, 169.7006, 179.4744] +24-11-19 20:40:47 | D | best error = [ 9.4613, 9.4613, 9.4613, 9.4613, 9.4613] +24-11-19 20:40:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:47 | D | sum error = [ 189.7315, 200.5056, 211.8068, 223.6805, 236.0892] +24-11-19 20:40:47 | D | best error = [ 9.4613, 9.4613, 9.4613, 9.4613, 9.4613] +24-11-19 20:40:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:47 | D | sum error = [ 249.1414, 262.8264, 277.1261, 292.0473, 307.6338] +24-11-19 20:40:47 | D | best error = [ 9.4613, 9.4613, 9.4613, 9.4613, 9.4613] +24-11-19 20:40:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:47 | D | sum error = [ 323.9574, 340.9906, 358.6834, 377.2175, 396.4772] +24-11-19 20:40:47 | D | best error = [ 9.4613, 9.4613, 9.4613, 9.4613, 9.4613] +24-11-19 20:40:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:47 | D | sum error = [ 416.5611, 437.4936, 459.2297, 481.8319, 505.3276] +24-11-19 20:40:47 | D | best error = [ 9.4613, 9.4613, 9.4613, 9.4613, 9.4613] +24-11-19 20:40:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:47 | D | sum error = [ 529.7016, 554.9066, 581.0731, 608.1503, 636.2191] +24-11-19 20:40:47 | D | best error = [ 9.4613, 9.4613, 9.4613, 9.4613, 9.4613] +24-11-19 20:40:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:47 | D | sum error = [ 665.2039, 695.1490, 726.0882, 758.0469, 790.9136] +24-11-19 20:40:47 | D | best error = [ 9.4613, 9.4613, 9.4613, 9.4613, 9.4613] +24-11-19 20:40:47 | D | + error = [9.4613] +24-11-19 20:40:47 | D | - Calibrating model.layers.26.mlp.down_proj.weight +24-11-19 20:40:47 | D | + w: sint8 +24-11-19 20:40:47 | D | + x: None +24-11-19 20:40:47 | D | + y: None +24-11-19 20:40:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:47 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:40:47 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:40:47 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:47 | D | - range ratio = [ 1.0000] +24-11-19 20:40:47 | D | sum error = [ 1.2786] +24-11-19 20:40:47 | D | best error = [ 1.2786] +24-11-19 20:40:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:48 | D | sum error = [ 1.2683, 1.2623, 1.2581, 1.2591, 1.2665] +24-11-19 20:40:48 | D | best error = [ 1.2271, 1.2027, 1.1863, 1.1752, 1.1668] +24-11-19 20:40:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:48 | D | sum error = [ 1.2823, 1.3023, 1.3298, 1.3669, 1.4122] +24-11-19 20:40:48 | D | best error = [ 1.1602, 1.1559, 1.1527, 1.1504, 1.1490] +24-11-19 20:40:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:48 | D | sum error = [ 1.4731, 1.5392, 1.6198, 1.7086, 1.8101] +24-11-19 20:40:48 | D | best error = [ 1.1480, 1.1475, 1.1472, 1.1470, 1.1469] +24-11-19 20:40:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:48 | D | sum error = [ 1.9168, 2.0422, 2.1764, 2.3254, 2.4828] +24-11-19 20:40:48 | D | best error = [ 1.1468, 1.1468, 1.1468, 1.1468, 1.1468] +24-11-19 20:40:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:48 | D | sum error = [ 2.6595, 2.8398, 3.0407, 3.2495, 3.4789] +24-11-19 20:40:48 | D | best error = [ 1.1468, 1.1468, 1.1468, 1.1468, 1.1468] +24-11-19 20:40:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:48 | D | sum error = [ 3.7185, 3.9767, 4.2460, 4.5389, 4.8419] +24-11-19 20:40:48 | D | best error = [ 1.1468, 1.1468, 1.1468, 1.1468, 1.1468] +24-11-19 20:40:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:48 | D | sum error = [ 5.1670, 5.5074, 5.8679, 6.2515, 6.6515] +24-11-19 20:40:48 | D | best error = [ 1.1468, 1.1468, 1.1468, 1.1468, 1.1468] +24-11-19 20:40:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:48 | D | sum error = [ 7.0792, 7.5241, 7.9955, 8.4934, 9.0181] +24-11-19 20:40:48 | D | best error = [ 1.1468, 1.1468, 1.1468, 1.1468, 1.1468] +24-11-19 20:40:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:48 | D | sum error = [ 9.5687, 10.1484, 10.7594, 11.4013, 12.0764] +24-11-19 20:40:48 | D | best error = [ 1.1468, 1.1468, 1.1468, 1.1468, 1.1468] +24-11-19 20:40:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:48 | D | sum error = [ 12.7821, 13.5260, 14.3063, 15.1220, 15.9803] +24-11-19 20:40:48 | D | best error = [ 1.1468, 1.1468, 1.1468, 1.1468, 1.1468] +24-11-19 20:40:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:48 | D | sum error = [ 16.8763, 17.8153, 18.7991, 19.8286, 20.9041] +24-11-19 20:40:48 | D | best error = [ 1.1468, 1.1468, 1.1468, 1.1468, 1.1468] +24-11-19 20:40:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:48 | D | sum error = [ 22.0268, 23.1994, 24.4241, 25.7000, 27.0318] +24-11-19 20:40:48 | D | best error = [ 1.1468, 1.1468, 1.1468, 1.1468, 1.1468] +24-11-19 20:40:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:48 | D | sum error = [ 28.4218, 29.8671, 31.3747, 32.9436, 34.5773] +24-11-19 20:40:48 | D | best error = [ 1.1468, 1.1468, 1.1468, 1.1468, 1.1468] +24-11-19 20:40:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:48 | D | sum error = [ 36.2729, 38.0390, 39.8691, 41.7693, 43.7442] +24-11-19 20:40:48 | D | best error = [ 1.1468, 1.1468, 1.1468, 1.1468, 1.1468] +24-11-19 20:40:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:48 | D | sum error = [ 45.7896, 47.9113, 50.1105, 52.3836, 54.7371] +24-11-19 20:40:48 | D | best error = [ 1.1468, 1.1468, 1.1468, 1.1468, 1.1468] +24-11-19 20:40:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:48 | D | sum error = [ 57.1695, 59.6841, 62.2775, 64.9556, 67.7183] +24-11-19 20:40:48 | D | best error = [ 1.1468, 1.1468, 1.1468, 1.1468, 1.1468] +24-11-19 20:40:48 | D | + error = [1.1468] +24-11-19 20:40:49 | D | - Quantizing model.layers.26.self_attn.q_proj.weight +24-11-19 20:40:50 | D | - Quantizing model.layers.26.self_attn.k_proj.weight +24-11-19 20:40:51 | D | - Quantizing model.layers.26.self_attn.v_proj.weight +24-11-19 20:40:52 | D | - Quantizing model.layers.26.self_attn.o_proj.weight +24-11-19 20:40:53 | D | - Quantizing model.layers.26.mlp.up_proj.weight +24-11-19 20:40:54 | D | - Quantizing model.layers.26.mlp.gate_proj.weight +24-11-19 20:40:55 | D | - Quantizing model.layers.26.mlp.down_proj.weight +24-11-19 20:41:05 | D | - Quantizing layer model.layers.27 +24-11-19 20:41:05 | D | - Calibrating model.layers.27.self_attn.q_proj.weight +24-11-19 20:41:05 | D | + w: sint8 +24-11-19 20:41:05 | D | + x: None +24-11-19 20:41:05 | D | + y: None +24-11-19 20:41:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:41:05 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:41:05 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:41:06 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:41:06 | D | - range ratio = [ 1.0000] +24-11-19 20:41:06 | D | sum error = [ 7.3035] +24-11-19 20:41:06 | D | best error = [ 7.3035] +24-11-19 20:41:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:20 | D | sum error = [ 7.2764, 7.1982, 7.1313, 7.4479, 7.6171] +24-11-19 20:41:20 | D | best error = [ 7.2764, 7.1982, 7.1313, 7.1313, 7.1313] +24-11-19 20:41:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:20 | D | sum error = [ 7.8688, 7.6809, 8.3579, 8.6187, 9.2746] +24-11-19 20:41:20 | D | best error = [ 7.1313, 7.1313, 7.1313, 7.1313, 7.1313] +24-11-19 20:41:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:20 | D | sum error = [ 9.3505, 10.1749, 11.0851, 11.8654, 12.7269] +24-11-19 20:41:20 | D | best error = [ 7.1313, 7.1313, 7.1313, 7.1313, 7.1313] +24-11-19 20:41:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:20 | D | sum error = [ 13.7429, 15.2301, 16.0916, 16.9315, 19.4263] +24-11-19 20:41:20 | D | best error = [ 7.1313, 7.1313, 7.1313, 7.1313, 7.1313] +24-11-19 20:41:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:20 | D | sum error = [ 20.9119, 22.3811, 24.3586, 26.3987, 28.7875] +24-11-19 20:41:20 | D | best error = [ 7.1313, 7.1313, 7.1313, 7.1313, 7.1313] +24-11-19 20:41:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:20 | D | sum error = [ 30.7627, 33.5189, 36.7004, 39.5218, 42.4578] +24-11-19 20:41:20 | D | best error = [ 7.1313, 7.1313, 7.1313, 7.1313, 7.1313] +24-11-19 20:41:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:20 | D | sum error = [ 46.3325, 49.9867, 54.1294, 58.5342, 63.4191] +24-11-19 20:41:20 | D | best error = [ 7.1313, 7.1313, 7.1313, 7.1313, 7.1313] +24-11-19 20:41:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:20 | D | sum error = [ 68.6762, 74.2967, 80.4245, 86.6990, 94.0436] +24-11-19 20:41:20 | D | best error = [ 7.1313, 7.1313, 7.1313, 7.1313, 7.1313] +24-11-19 20:41:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:20 | D | sum error = [ 101.4744, 110.2344, 119.2677, 129.0371, 139.6959] +24-11-19 20:41:20 | D | best error = [ 7.1313, 7.1313, 7.1313, 7.1313, 7.1313] +24-11-19 20:41:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:20 | D | sum error = [ 151.0653, 163.3544, 176.7397, 190.3297, 206.1653] +24-11-19 20:41:20 | D | best error = [ 7.1313, 7.1313, 7.1313, 7.1313, 7.1313] +24-11-19 20:41:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:20 | D | sum error = [ 222.7763, 240.1559, 259.1101, 279.7638, 302.1672] +24-11-19 20:41:20 | D | best error = [ 7.1313, 7.1313, 7.1313, 7.1313, 7.1313] +24-11-19 20:41:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:20 | D | sum error = [ 326.4685, 352.6798, 381.1380, 411.8613, 445.7045] +24-11-19 20:41:20 | D | best error = [ 7.1313, 7.1313, 7.1313, 7.1313, 7.1313] +24-11-19 20:41:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:20 | D | sum error = [ 482.8397, 523.3541, 567.6345, 617.5614, 672.3333] +24-11-19 20:41:20 | D | best error = [ 7.1313, 7.1313, 7.1313, 7.1313, 7.1313] +24-11-19 20:41:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:20 | D | sum error = [ 732.9318, 799.8069, 873.6481, 955.6140, 1046.1651] +24-11-19 20:41:20 | D | best error = [ 7.1313, 7.1313, 7.1313, 7.1313, 7.1313] +24-11-19 20:41:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:20 | D | sum error = [ 1147.0406, 1258.6848, 1381.9380, 1515.6305, 1657.3348] +24-11-19 20:41:20 | D | best error = [ 7.1313, 7.1313, 7.1313, 7.1313, 7.1313] +24-11-19 20:41:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:20 | D | sum error = [ 1809.8463, 1973.2215, 2143.6991, 2316.3370, 2493.2499] +24-11-19 20:41:20 | D | best error = [ 7.1313, 7.1313, 7.1313, 7.1313, 7.1313] +24-11-19 20:41:20 | D | + error = [7.1313] +24-11-19 20:41:20 | D | - Calibrating model.layers.27.self_attn.k_proj.weight +24-11-19 20:41:20 | D | + w: sint8 +24-11-19 20:41:20 | D | + x: None +24-11-19 20:41:20 | D | + y: None +24-11-19 20:41:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:41:20 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:41:20 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:41:20 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:41:20 | D | - range ratio = [ 1.0000] +24-11-19 20:41:20 | D | sum error = [ 7.2260] +24-11-19 20:41:20 | D | best error = [ 7.2260] +24-11-19 20:41:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:32 | D | sum error = [ 6.9096, 7.0775, 7.1938, 7.6423, 8.1158] +24-11-19 20:41:32 | D | best error = [ 6.9096, 6.9096, 6.9096, 6.9096, 6.9096] +24-11-19 20:41:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:32 | D | sum error = [ 7.2953, 8.1779, 8.2521, 8.5817, 10.9489] +24-11-19 20:41:32 | D | best error = [ 6.9096, 6.9096, 6.9096, 6.9096, 6.9096] +24-11-19 20:41:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:32 | D | sum error = [ 9.8959, 10.1586, 11.1167, 11.0932, 13.8781] +24-11-19 20:41:32 | D | best error = [ 6.9096, 6.9096, 6.9096, 6.9096, 6.9096] +24-11-19 20:41:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:32 | D | sum error = [ 14.5508, 14.9111, 16.7579, 18.4070, 18.3554] +24-11-19 20:41:32 | D | best error = [ 6.9096, 6.9096, 6.9096, 6.9096, 6.9096] +24-11-19 20:41:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:32 | D | sum error = [ 20.4605, 21.0270, 23.6334, 24.5928, 25.8221] +24-11-19 20:41:32 | D | best error = [ 6.9096, 6.9096, 6.9096, 6.9096, 6.9096] +24-11-19 20:41:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:32 | D | sum error = [ 28.2068, 30.0815, 32.9029, 36.0148, 38.5692] +24-11-19 20:41:32 | D | best error = [ 6.9096, 6.9096, 6.9096, 6.9096, 6.9096] +24-11-19 20:41:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:32 | D | sum error = [ 41.1092, 45.3046, 47.9122, 52.6945, 56.4665] +24-11-19 20:41:32 | D | best error = [ 6.9096, 6.9096, 6.9096, 6.9096, 6.9096] +24-11-19 20:41:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:32 | D | sum error = [ 62.0692, 66.0197, 72.1789, 78.1674, 84.1794] +24-11-19 20:41:32 | D | best error = [ 6.9096, 6.9096, 6.9096, 6.9096, 6.9096] +24-11-19 20:41:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:32 | D | sum error = [ 91.8420, 98.8207, 107.4809, 116.0350, 125.0607] +24-11-19 20:41:32 | D | best error = [ 6.9096, 6.9096, 6.9096, 6.9096, 6.9096] +24-11-19 20:41:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:32 | D | sum error = [ 135.3962, 147.1019, 157.3757, 169.2579, 182.5829] +24-11-19 20:41:32 | D | best error = [ 6.9096, 6.9096, 6.9096, 6.9096, 6.9096] +24-11-19 20:41:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:32 | D | sum error = [ 197.9503, 212.2211, 230.3548, 249.1961, 269.2296] +24-11-19 20:41:32 | D | best error = [ 6.9096, 6.9096, 6.9096, 6.9096, 6.9096] +24-11-19 20:41:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:32 | D | sum error = [ 293.9955, 319.5016, 345.3668, 377.0073, 410.5690] +24-11-19 20:41:32 | D | best error = [ 6.9096, 6.9096, 6.9096, 6.9096, 6.9096] +24-11-19 20:41:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:32 | D | sum error = [ 447.3717, 489.4854, 534.8503, 586.4625, 640.3213] +24-11-19 20:41:32 | D | best error = [ 6.9096, 6.9096, 6.9096, 6.9096, 6.9096] +24-11-19 20:41:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:32 | D | sum error = [ 706.4079, 780.1692, 858.0727, 946.4316, 1045.5145] +24-11-19 20:41:32 | D | best error = [ 6.9096, 6.9096, 6.9096, 6.9096, 6.9096] +24-11-19 20:41:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:32 | D | sum error = [ 1145.1832, 1262.0279, 1390.4540, 1533.0956, 1688.7962] +24-11-19 20:41:32 | D | best error = [ 6.9096, 6.9096, 6.9096, 6.9096, 6.9096] +24-11-19 20:41:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:32 | D | sum error = [ 1856.7868, 2031.9369, 2199.6828, 2381.6860, 2567.7780] +24-11-19 20:41:32 | D | best error = [ 6.9096, 6.9096, 6.9096, 6.9096, 6.9096] +24-11-19 20:41:32 | D | + error = [6.9096] +24-11-19 20:41:32 | D | - Calibrating model.layers.27.self_attn.v_proj.weight +24-11-19 20:41:32 | D | + w: sint8 +24-11-19 20:41:32 | D | + x: None +24-11-19 20:41:32 | D | + y: None +24-11-19 20:41:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:32 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:41:32 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:41:33 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:41:33 | D | - range ratio = [ 1.0000] +24-11-19 20:41:33 | D | sum error = [ 2.8438] +24-11-19 20:41:33 | D | best error = [ 2.8438] +24-11-19 20:41:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:33 | D | sum error = [ 2.8470, 2.8218, 2.8615, 2.8916, 2.9297] +24-11-19 20:41:33 | D | best error = [ 2.5791, 2.4736, 2.4214, 2.3967, 2.3819] +24-11-19 20:41:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:33 | D | sum error = [ 3.0267, 3.1052, 3.2660, 3.4134, 3.5483] +24-11-19 20:41:33 | D | best error = [ 2.3729, 2.3689, 2.3676, 2.3674, 2.3672] +24-11-19 20:41:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:33 | D | sum error = [ 3.8009, 4.0427, 4.2363, 4.5297, 4.8177] +24-11-19 20:41:33 | D | best error = [ 2.3671, 2.3671, 2.3671, 2.3671, 2.3671] +24-11-19 20:41:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:33 | D | sum error = [ 5.2144, 5.5332, 5.9924, 6.3641, 6.8300] +24-11-19 20:41:33 | D | best error = [ 2.3671, 2.3671, 2.3671, 2.3671, 2.3671] +24-11-19 20:41:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:33 | D | sum error = [ 7.3038, 7.8227, 8.3138, 8.9211, 9.5160] +24-11-19 20:41:33 | D | best error = [ 2.3671, 2.3671, 2.3671, 2.3671, 2.3671] +24-11-19 20:41:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:33 | D | sum error = [ 10.1723, 10.8626, 11.5938, 12.3105, 13.1394] +24-11-19 20:41:33 | D | best error = [ 2.3671, 2.3671, 2.3671, 2.3671, 2.3671] +24-11-19 20:41:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:33 | D | sum error = [ 13.9503, 14.8484, 15.7996, 16.7775, 17.7982] +24-11-19 20:41:33 | D | best error = [ 2.3671, 2.3671, 2.3671, 2.3671, 2.3671] +24-11-19 20:41:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:33 | D | sum error = [ 18.8995, 20.0691, 21.2856, 22.5944, 23.9049] +24-11-19 20:41:33 | D | best error = [ 2.3671, 2.3671, 2.3671, 2.3671, 2.3671] +24-11-19 20:41:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:33 | D | sum error = [ 25.3144, 26.7916, 28.3030, 29.9330, 31.6334] +24-11-19 20:41:33 | D | best error = [ 2.3671, 2.3671, 2.3671, 2.3671, 2.3671] +24-11-19 20:41:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:33 | D | sum error = [ 33.4242, 35.2610, 37.2278, 39.2158, 41.3603] +24-11-19 20:41:33 | D | best error = [ 2.3671, 2.3671, 2.3671, 2.3671, 2.3671] +24-11-19 20:41:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:33 | D | sum error = [ 43.5386, 45.8572, 48.2643, 50.7605, 53.3674] +24-11-19 20:41:33 | D | best error = [ 2.3671, 2.3671, 2.3671, 2.3671, 2.3671] +24-11-19 20:41:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:33 | D | sum error = [ 56.0703, 58.9030, 61.8104, 64.8753, 68.0408] +24-11-19 20:41:33 | D | best error = [ 2.3671, 2.3671, 2.3671, 2.3671, 2.3671] +24-11-19 20:41:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:33 | D | sum error = [ 71.3436, 74.7325, 78.2823, 81.9148, 85.7106] +24-11-19 20:41:33 | D | best error = [ 2.3671, 2.3671, 2.3671, 2.3671, 2.3671] +24-11-19 20:41:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:33 | D | sum error = [ 89.6382, 93.6638, 97.8451, 102.1612, 106.6395] +24-11-19 20:41:33 | D | best error = [ 2.3671, 2.3671, 2.3671, 2.3671, 2.3671] +24-11-19 20:41:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:33 | D | sum error = [ 111.2450, 116.0265, 120.9531, 126.0157, 131.2289] +24-11-19 20:41:33 | D | best error = [ 2.3671, 2.3671, 2.3671, 2.3671, 2.3671] +24-11-19 20:41:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:33 | D | sum error = [ 136.6064, 142.1425, 147.8434, 153.6970, 159.7145] +24-11-19 20:41:33 | D | best error = [ 2.3671, 2.3671, 2.3671, 2.3671, 2.3671] +24-11-19 20:41:33 | D | + error = [2.3671] +24-11-19 20:41:33 | D | - Calibrating model.layers.27.self_attn.o_proj.weight +24-11-19 20:41:33 | D | + w: sint8 +24-11-19 20:41:33 | D | + x: None +24-11-19 20:41:33 | D | + y: None +24-11-19 20:41:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:33 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:41:33 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:41:33 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:41:33 | D | - range ratio = [ 1.0000] +24-11-19 20:41:33 | D | sum error = [ 0.6495] +24-11-19 20:41:33 | D | best error = [ 0.6495] +24-11-19 20:41:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:34 | D | sum error = [ 0.6454, 0.6425, 0.6443, 0.6531, 0.6582] +24-11-19 20:41:34 | D | best error = [ 0.5935, 0.5697, 0.5563, 0.5481, 0.5423] +24-11-19 20:41:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:34 | D | sum error = [ 0.6742, 0.6977, 0.7196, 0.7477, 0.7833] +24-11-19 20:41:34 | D | best error = [ 0.5385, 0.5363, 0.5348, 0.5337, 0.5332] +24-11-19 20:41:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:34 | D | sum error = [ 0.8238, 0.8685, 0.9200, 0.9763, 1.0381] +24-11-19 20:41:34 | D | best error = [ 0.5328, 0.5325, 0.5323, 0.5322, 0.5322] +24-11-19 20:41:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:34 | D | sum error = [ 1.1032, 1.1723, 1.2505, 1.3313, 1.4220] +24-11-19 20:41:34 | D | best error = [ 0.5321, 0.5321, 0.5321, 0.5320, 0.5320] +24-11-19 20:41:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:34 | D | sum error = [ 1.5125, 1.6131, 1.7204, 1.8339, 1.9559] +24-11-19 20:41:34 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5320] +24-11-19 20:41:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:34 | D | sum error = [ 2.0796, 2.2122, 2.3517, 2.5014, 2.6557] +24-11-19 20:41:34 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5320] +24-11-19 20:41:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:34 | D | sum error = [ 2.8174, 2.9913, 3.1735, 3.3656, 3.5667] +24-11-19 20:41:34 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5320] +24-11-19 20:41:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:34 | D | sum error = [ 3.7761, 3.9980, 4.2294, 4.4714, 4.7267] +24-11-19 20:41:34 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5320] +24-11-19 20:41:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:34 | D | sum error = [ 4.9940, 5.2764, 5.5666, 5.8747, 6.1974] +24-11-19 20:41:34 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5320] +24-11-19 20:41:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:34 | D | sum error = [ 6.5319, 6.8848, 7.2540, 7.6390, 8.0438] +24-11-19 20:41:34 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5320] +24-11-19 20:41:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:34 | D | sum error = [ 8.4671, 8.9076, 9.3670, 9.8475, 10.3482] +24-11-19 20:41:34 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5320] +24-11-19 20:41:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:34 | D | sum error = [ 10.8710, 11.4165, 11.9853, 12.5819, 13.2005] +24-11-19 20:41:34 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5320] +24-11-19 20:41:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:34 | D | sum error = [ 13.8505, 14.5256, 15.2257, 15.9542, 16.7141] +24-11-19 20:41:34 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5320] +24-11-19 20:41:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:34 | D | sum error = [ 17.5030, 18.3232, 19.1754, 20.0616, 20.9791] +24-11-19 20:41:34 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5320] +24-11-19 20:41:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:34 | D | sum error = [ 21.9344, 22.9235, 23.9500, 25.0169, 26.1190] +24-11-19 20:41:34 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5320] +24-11-19 20:41:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:34 | D | sum error = [ 27.2629, 28.4454, 29.6698, 30.9349, 32.2413] +24-11-19 20:41:34 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5320] +24-11-19 20:41:34 | D | + error = [0.5320] +24-11-19 20:41:34 | D | - Calibrating model.layers.27.mlp.up_proj.weight +24-11-19 20:41:34 | D | + w: sint8 +24-11-19 20:41:34 | D | + x: None +24-11-19 20:41:34 | D | + y: None +24-11-19 20:41:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:34 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:41:34 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:41:34 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:41:34 | D | - range ratio = [ 1.0000] +24-11-19 20:41:34 | D | sum error = [ 0.4840] +24-11-19 20:41:34 | D | best error = [ 0.4840] +24-11-19 20:41:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:35 | D | sum error = [ 0.4808, 0.4816, 0.4821, 0.4858, 0.4958] +24-11-19 20:41:35 | D | best error = [ 0.4316, 0.4136, 0.4041, 0.3989, 0.3961] +24-11-19 20:41:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:35 | D | sum error = [ 0.5078, 0.5264, 0.5458, 0.5712, 0.6027] +24-11-19 20:41:35 | D | best error = [ 0.3946, 0.3939, 0.3936, 0.3935, 0.3935] +24-11-19 20:41:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:35 | D | sum error = [ 0.6378, 0.6764, 0.7206, 0.7671, 0.8227] +24-11-19 20:41:35 | D | best error = [ 0.3935, 0.3935, 0.3935, 0.3935, 0.3935] +24-11-19 20:41:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:35 | D | sum error = [ 0.8788, 0.9410, 1.0094, 1.0809, 1.1561] +24-11-19 20:41:35 | D | best error = [ 0.3935, 0.3935, 0.3935, 0.3935, 0.3935] +24-11-19 20:41:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:35 | D | sum error = [ 1.2414, 1.3288, 1.4222, 1.5202, 1.6264] +24-11-19 20:41:35 | D | best error = [ 0.3935, 0.3935, 0.3935, 0.3935, 0.3935] +24-11-19 20:41:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:35 | D | sum error = [ 1.7367, 1.8555, 1.9787, 2.1118, 2.2482] +24-11-19 20:41:35 | D | best error = [ 0.3935, 0.3935, 0.3935, 0.3935, 0.3935] +24-11-19 20:41:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:35 | D | sum error = [ 2.3957, 2.5453, 2.7082, 2.8772, 3.0565] +24-11-19 20:41:35 | D | best error = [ 0.3935, 0.3935, 0.3935, 0.3935, 0.3935] +24-11-19 20:41:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:35 | D | sum error = [ 3.2428, 3.4395, 3.6432, 3.8571, 4.0816] +24-11-19 20:41:35 | D | best error = [ 0.3935, 0.3935, 0.3935, 0.3935, 0.3935] +24-11-19 20:41:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:35 | D | sum error = [ 4.3165, 4.5638, 4.8189, 5.0900, 5.3706] +24-11-19 20:41:35 | D | best error = [ 0.3935, 0.3935, 0.3935, 0.3935, 0.3935] +24-11-19 20:41:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:35 | D | sum error = [ 5.6628, 5.9656, 6.2844, 6.6140, 6.9589] +24-11-19 20:41:35 | D | best error = [ 0.3935, 0.3935, 0.3935, 0.3935, 0.3935] +24-11-19 20:41:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:35 | D | sum error = [ 7.3193, 7.6912, 8.0804, 8.4809, 8.8971] +24-11-19 20:41:35 | D | best error = [ 0.3935, 0.3935, 0.3935, 0.3935, 0.3935] +24-11-19 20:41:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:35 | D | sum error = [ 9.3310, 9.7805, 10.2442, 10.7274, 11.2251] +24-11-19 20:41:35 | D | best error = [ 0.3935, 0.3935, 0.3935, 0.3935, 0.3935] +24-11-19 20:41:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:35 | D | sum error = [ 11.7406, 12.2724, 12.8249, 13.3899, 13.9733] +24-11-19 20:41:35 | D | best error = [ 0.3935, 0.3935, 0.3935, 0.3935, 0.3935] +24-11-19 20:41:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:35 | D | sum error = [ 14.5796, 15.2034, 15.8455, 16.5081, 17.1905] +24-11-19 20:41:35 | D | best error = [ 0.3935, 0.3935, 0.3935, 0.3935, 0.3935] +24-11-19 20:41:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:35 | D | sum error = [ 17.8879, 18.6092, 19.3498, 20.1106, 20.8932] +24-11-19 20:41:35 | D | best error = [ 0.3935, 0.3935, 0.3935, 0.3935, 0.3935] +24-11-19 20:41:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:35 | D | sum error = [ 21.6927, 22.5182, 23.3558, 24.2275, 25.1160] +24-11-19 20:41:35 | D | best error = [ 0.3935, 0.3935, 0.3935, 0.3935, 0.3935] +24-11-19 20:41:35 | D | + error = [0.3935] +24-11-19 20:41:35 | D | - Calibrating model.layers.27.mlp.gate_proj.weight +24-11-19 20:41:35 | D | + w: sint8 +24-11-19 20:41:35 | D | + x: None +24-11-19 20:41:35 | D | + y: None +24-11-19 20:41:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:35 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:41:35 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:41:36 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:41:36 | D | - range ratio = [ 1.0000] +24-11-19 20:41:36 | D | sum error = [ 12.0512] +24-11-19 20:41:36 | D | best error = [ 12.0512] +24-11-19 20:41:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:37 | D | sum error = [ 11.9798, 12.0098, 11.9300, 12.1168, 12.3571] +24-11-19 20:41:37 | D | best error = [ 10.7409, 10.2835, 10.0481, 9.9213, 9.8505] +24-11-19 20:41:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:37 | D | sum error = [ 12.6947, 13.1128, 13.6409, 14.2716, 15.0511] +24-11-19 20:41:37 | D | best error = [ 9.8167, 9.8008, 9.7937, 9.7910, 9.7904] +24-11-19 20:41:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:37 | D | sum error = [ 15.8988, 16.9125, 18.0255, 19.2337, 20.5998] +24-11-19 20:41:37 | D | best error = [ 9.7903, 9.7903, 9.7903, 9.7903, 9.7903] +24-11-19 20:41:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:37 | D | sum error = [ 22.0497, 23.6119, 25.3702, 27.1574, 29.1514] +24-11-19 20:41:37 | D | best error = [ 9.7903, 9.7903, 9.7903, 9.7903, 9.7903] +24-11-19 20:41:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:37 | D | sum error = [ 31.2066, 33.5224, 35.8763, 38.4274, 41.2093] +24-11-19 20:41:37 | D | best error = [ 9.7903, 9.7903, 9.7903, 9.7903, 9.7903] +24-11-19 20:41:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:37 | D | sum error = [ 44.1088, 47.1369, 50.3589, 53.8309, 57.4962] +24-11-19 20:41:37 | D | best error = [ 9.7903, 9.7903, 9.7903, 9.7903, 9.7903] +24-11-19 20:41:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:37 | D | sum error = [ 61.3055, 65.3989, 69.7222, 74.2668, 79.1332] +24-11-19 20:41:37 | D | best error = [ 9.7903, 9.7903, 9.7903, 9.7903, 9.7903] +24-11-19 20:41:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:37 | D | sum error = [ 84.1900, 89.5530, 95.2788, 101.2679, 107.6290] +24-11-19 20:41:37 | D | best error = [ 9.7903, 9.7903, 9.7903, 9.7903, 9.7903] +24-11-19 20:41:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:37 | D | sum error = [ 114.2840, 121.3566, 128.7437, 136.6242, 144.8730] +24-11-19 20:41:37 | D | best error = [ 9.7903, 9.7903, 9.7903, 9.7903, 9.7903] +24-11-19 20:41:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:37 | D | sum error = [ 153.5881, 162.7501, 172.3897, 182.5427, 193.2319] +24-11-19 20:41:37 | D | best error = [ 9.7903, 9.7903, 9.7903, 9.7903, 9.7903] +24-11-19 20:41:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:37 | D | sum error = [ 204.4178, 216.1464, 228.4819, 241.4312, 254.9935] +24-11-19 20:41:37 | D | best error = [ 9.7903, 9.7903, 9.7903, 9.7903, 9.7903] +24-11-19 20:41:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:37 | D | sum error = [ 269.2171, 284.1769, 299.7156, 316.0646, 333.2195] +24-11-19 20:41:37 | D | best error = [ 9.7903, 9.7903, 9.7903, 9.7903, 9.7903] +24-11-19 20:41:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:37 | D | sum error = [ 351.1180, 369.8693, 389.4191, 409.9431, 431.3025] +24-11-19 20:41:37 | D | best error = [ 9.7903, 9.7903, 9.7903, 9.7903, 9.7903] +24-11-19 20:41:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:37 | D | sum error = [ 453.6220, 476.8056, 500.8993, 525.9629, 551.9849] +24-11-19 20:41:37 | D | best error = [ 9.7903, 9.7903, 9.7903, 9.7903, 9.7903] +24-11-19 20:41:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:37 | D | sum error = [ 579.0229, 607.0388, 636.1507, 666.2352, 697.3300] +24-11-19 20:41:37 | D | best error = [ 9.7903, 9.7903, 9.7903, 9.7903, 9.7903] +24-11-19 20:41:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:37 | D | sum error = [ 729.4807, 762.7002, 796.9437, 832.2564, 868.6096] +24-11-19 20:41:37 | D | best error = [ 9.7903, 9.7903, 9.7903, 9.7903, 9.7903] +24-11-19 20:41:37 | D | + error = [9.7903] +24-11-19 20:41:37 | D | - Calibrating model.layers.27.mlp.down_proj.weight +24-11-19 20:41:37 | D | + w: sint8 +24-11-19 20:41:37 | D | + x: None +24-11-19 20:41:37 | D | + y: None +24-11-19 20:41:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:37 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:41:37 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:41:37 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:41:37 | D | - range ratio = [ 1.0000] +24-11-19 20:41:37 | D | sum error = [ 1.4496] +24-11-19 20:41:37 | D | best error = [ 1.4496] +24-11-19 20:41:38 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:38 | D | sum error = [ 1.4367, 1.4327, 1.4284, 1.4336, 1.4556] +24-11-19 20:41:38 | D | best error = [ 1.3703, 1.3375, 1.3162, 1.3014, 1.2915] +24-11-19 20:41:38 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:38 | D | sum error = [ 1.4714, 1.5107, 1.5574, 1.6125, 1.6773] +24-11-19 20:41:38 | D | best error = [ 1.2841, 1.2789, 1.2754, 1.2735, 1.2720] +24-11-19 20:41:38 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:38 | D | sum error = [ 1.7567, 1.8479, 1.9537, 2.0759, 2.2029] +24-11-19 20:41:38 | D | best error = [ 1.2711, 1.2704, 1.2700, 1.2697, 1.2696] +24-11-19 20:41:38 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:38 | D | sum error = [ 2.3511, 2.5069, 2.6812, 2.8632, 3.0683] +24-11-19 20:41:38 | D | best error = [ 1.2695, 1.2695, 1.2695, 1.2695, 1.2695] +24-11-19 20:41:38 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:38 | D | sum error = [ 3.2872, 3.5149, 3.7625, 4.0259, 4.3055] +24-11-19 20:41:38 | D | best error = [ 1.2695, 1.2695, 1.2695, 1.2695, 1.2695] +24-11-19 20:41:38 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:38 | D | sum error = [ 4.5978, 4.9137, 5.2537, 5.6007, 5.9710] +24-11-19 20:41:38 | D | best error = [ 1.2695, 1.2695, 1.2695, 1.2695, 1.2695] +24-11-19 20:41:38 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:38 | D | sum error = [ 6.3674, 6.7820, 7.2222, 7.6859, 8.1757] +24-11-19 20:41:38 | D | best error = [ 1.2695, 1.2695, 1.2695, 1.2695, 1.2695] +24-11-19 20:41:38 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:38 | D | sum error = [ 8.6863, 9.2204, 9.7884, 10.3895, 11.0181] +24-11-19 20:41:38 | D | best error = [ 1.2695, 1.2695, 1.2695, 1.2695, 1.2695] +24-11-19 20:41:38 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:38 | D | sum error = [ 11.6832, 12.3847, 13.1195, 13.8946, 14.6969] +24-11-19 20:41:38 | D | best error = [ 1.2695, 1.2695, 1.2695, 1.2695, 1.2695] +24-11-19 20:41:38 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:38 | D | sum error = [ 15.5434, 16.4336, 17.3624, 18.3354, 19.3611] +24-11-19 20:41:38 | D | best error = [ 1.2695, 1.2695, 1.2695, 1.2695, 1.2695] +24-11-19 20:41:38 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:38 | D | sum error = [ 20.4298, 21.5484, 22.7203, 23.9436, 25.2218] +24-11-19 20:41:38 | D | best error = [ 1.2695, 1.2695, 1.2695, 1.2695, 1.2695] +24-11-19 20:41:38 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:38 | D | sum error = [ 26.5565, 27.9531, 29.4090, 30.9314, 32.5161] +24-11-19 20:41:38 | D | best error = [ 1.2695, 1.2695, 1.2695, 1.2695, 1.2695] +24-11-19 20:41:38 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:38 | D | sum error = [ 34.1610, 35.8717, 37.6536, 39.5024, 41.4339] +24-11-19 20:41:38 | D | best error = [ 1.2695, 1.2695, 1.2695, 1.2695, 1.2695] +24-11-19 20:41:38 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:38 | D | sum error = [ 43.4389, 45.5244, 47.6846, 49.9188, 52.2371] +24-11-19 20:41:38 | D | best error = [ 1.2695, 1.2695, 1.2695, 1.2695, 1.2695] +24-11-19 20:41:38 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:38 | D | sum error = [ 54.6441, 57.1338, 59.7094, 62.3747, 65.1229] +24-11-19 20:41:38 | D | best error = [ 1.2695, 1.2695, 1.2695, 1.2695, 1.2695] +24-11-19 20:41:38 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:38 | D | sum error = [ 67.9647, 70.9020, 73.9314, 77.0537, 80.2716] +24-11-19 20:41:38 | D | best error = [ 1.2695, 1.2695, 1.2695, 1.2695, 1.2695] +24-11-19 20:41:38 | D | + error = [1.2695] +24-11-19 20:41:38 | D | - Quantizing model.layers.27.self_attn.q_proj.weight +24-11-19 20:41:40 | D | - Quantizing model.layers.27.self_attn.k_proj.weight +24-11-19 20:41:41 | D | - Quantizing model.layers.27.self_attn.v_proj.weight +24-11-19 20:41:42 | D | - Quantizing model.layers.27.self_attn.o_proj.weight +24-11-19 20:41:44 | D | - Quantizing model.layers.27.mlp.up_proj.weight +24-11-19 20:41:45 | D | - Quantizing model.layers.27.mlp.gate_proj.weight +24-11-19 20:41:46 | D | - Quantizing model.layers.27.mlp.down_proj.weight +24-11-19 20:41:55 | D | - Quantizing layer model.layers.28 +24-11-19 20:41:55 | D | - Calibrating model.layers.28.self_attn.q_proj.weight +24-11-19 20:41:55 | D | + w: sint8 +24-11-19 20:41:55 | D | + x: None +24-11-19 20:41:55 | D | + y: None +24-11-19 20:41:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:41:55 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:41:56 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:41:56 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:41:56 | D | - range ratio = [ 1.0000] +24-11-19 20:41:56 | D | sum error = [ 7.4172] +24-11-19 20:41:56 | D | best error = [ 7.4172] +24-11-19 20:42:11 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:42:11 | D | sum error = [ 7.2836, 7.3593, 7.3581, 7.1876, 7.7983] +24-11-19 20:42:11 | D | best error = [ 7.2836, 7.2836, 7.2836, 7.1876, 7.1876] +24-11-19 20:42:11 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:42:11 | D | sum error = [ 7.8426, 7.9464, 8.4098, 8.5575, 8.8257] +24-11-19 20:42:11 | D | best error = [ 7.1876, 7.1876, 7.1876, 7.1876, 7.1876] +24-11-19 20:42:11 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:42:11 | D | sum error = [ 9.7759, 10.3135, 10.9060, 11.8571, 12.5673] +24-11-19 20:42:11 | D | best error = [ 7.1876, 7.1876, 7.1876, 7.1876, 7.1876] +24-11-19 20:42:11 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:42:11 | D | sum error = [ 13.9143, 14.6189, 15.5235, 17.5671, 18.8176] +24-11-19 20:42:11 | D | best error = [ 7.1876, 7.1876, 7.1876, 7.1876, 7.1876] +24-11-19 20:42:11 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:42:11 | D | sum error = [ 20.2732, 21.9863, 23.8513, 25.7926, 28.2403] +24-11-19 20:42:11 | D | best error = [ 7.1876, 7.1876, 7.1876, 7.1876, 7.1876] +24-11-19 20:42:11 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:42:11 | D | sum error = [ 30.5574, 33.9605, 36.3752, 38.9730, 42.7863] +24-11-19 20:42:11 | D | best error = [ 7.1876, 7.1876, 7.1876, 7.1876, 7.1876] +24-11-19 20:42:11 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:42:11 | D | sum error = [ 46.8615, 50.6149, 54.2932, 58.8799, 63.6023] +24-11-19 20:42:11 | D | best error = [ 7.1876, 7.1876, 7.1876, 7.1876, 7.1876] +24-11-19 20:42:11 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:42:11 | D | sum error = [ 68.8882, 75.0605, 80.8413, 86.9822, 93.9730] +24-11-19 20:42:11 | D | best error = [ 7.1876, 7.1876, 7.1876, 7.1876, 7.1876] +24-11-19 20:42:11 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:42:11 | D | sum error = [ 101.4779, 109.1174, 117.2452, 126.4280, 135.4523] +24-11-19 20:42:11 | D | best error = [ 7.1876, 7.1876, 7.1876, 7.1876, 7.1876] +24-11-19 20:42:11 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:42:11 | D | sum error = [ 145.4479, 156.0214, 167.4649, 179.9071, 193.1890] +24-11-19 20:42:11 | D | best error = [ 7.1876, 7.1876, 7.1876, 7.1876, 7.1876] +24-11-19 20:42:11 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:42:11 | D | sum error = [ 206.4996, 221.7992, 237.8372, 255.0820, 273.9319] +24-11-19 20:42:11 | D | best error = [ 7.1876, 7.1876, 7.1876, 7.1876, 7.1876] +24-11-19 20:42:11 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:42:11 | D | sum error = [ 293.6237, 314.9226, 337.4359, 362.3765, 387.7932] +24-11-19 20:42:11 | D | best error = [ 7.1876, 7.1876, 7.1876, 7.1876, 7.1876] +24-11-19 20:42:11 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:42:11 | D | sum error = [ 415.8218, 446.0676, 478.4212, 513.9309, 552.0157] +24-11-19 20:42:11 | D | best error = [ 7.1876, 7.1876, 7.1876, 7.1876, 7.1876] +24-11-19 20:42:11 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:42:11 | D | sum error = [ 593.1198, 637.7131, 686.2819, 738.5482, 794.0857] +24-11-19 20:42:11 | D | best error = [ 7.1876, 7.1876, 7.1876, 7.1876, 7.1876] +24-11-19 20:42:11 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:42:11 | D | sum error = [ 853.5789, 916.8881, 984.4323, 1056.6320, 1132.7176] +24-11-19 20:42:11 | D | best error = [ 7.1876, 7.1876, 7.1876, 7.1876, 7.1876] +24-11-19 20:42:11 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:42:11 | D | sum error = [ 1212.5920, 1296.7942, 1384.4960, 1474.6837, 1566.2899] +24-11-19 20:42:11 | D | best error = [ 7.1876, 7.1876, 7.1876, 7.1876, 7.1876] +24-11-19 20:42:11 | D | + error = [7.1876] +24-11-19 20:42:11 | D | - Calibrating model.layers.28.self_attn.k_proj.weight +24-11-19 20:42:11 | D | + w: sint8 +24-11-19 20:42:11 | D | + x: None +24-11-19 20:42:11 | D | + y: None +24-11-19 20:42:11 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:42:11 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:42:11 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:42:11 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:42:11 | D | - range ratio = [ 1.0000] +24-11-19 20:42:11 | D | sum error = [ 8.1622] +24-11-19 20:42:11 | D | best error = [ 8.1622] +24-11-19 20:42:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:42:25 | D | sum error = [ 7.3707, 7.7899, 7.4569, 7.6654, 7.5752] +24-11-19 20:42:25 | D | best error = [ 7.3707, 7.3707, 7.3707, 7.3707, 7.3707] +24-11-19 20:42:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:42:25 | D | sum error = [ 7.4781, 8.7372, 7.7616, 8.8444, 8.8327] +24-11-19 20:42:25 | D | best error = [ 7.3707, 7.3707, 7.3707, 7.3707, 7.3707] +24-11-19 20:42:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:42:25 | D | sum error = [ 9.2531, 10.3026, 10.9449, 11.2561, 12.6089] +24-11-19 20:42:25 | D | best error = [ 7.3707, 7.3707, 7.3707, 7.3707, 7.3707] +24-11-19 20:42:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:42:25 | D | sum error = [ 13.0382, 14.2558, 15.2736, 15.8284, 17.2424] +24-11-19 20:42:25 | D | best error = [ 7.3707, 7.3707, 7.3707, 7.3707, 7.3707] +24-11-19 20:42:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:42:25 | D | sum error = [ 17.7893, 20.3848, 21.7905, 23.3401, 25.3257] +24-11-19 20:42:25 | D | best error = [ 7.3707, 7.3707, 7.3707, 7.3707, 7.3707] +24-11-19 20:42:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:42:25 | D | sum error = [ 27.0704, 28.9840, 31.6172, 33.3695, 36.1973] +24-11-19 20:42:25 | D | best error = [ 7.3707, 7.3707, 7.3707, 7.3707, 7.3707] +24-11-19 20:42:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:42:25 | D | sum error = [ 38.9394, 41.7501, 44.5621, 48.6839, 52.4900] +24-11-19 20:42:25 | D | best error = [ 7.3707, 7.3707, 7.3707, 7.3707, 7.3707] +24-11-19 20:42:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:42:25 | D | sum error = [ 56.4417, 60.5121, 65.2456, 70.0785, 76.2946] +24-11-19 20:42:25 | D | best error = [ 7.3707, 7.3707, 7.3707, 7.3707, 7.3707] +24-11-19 20:42:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:42:25 | D | sum error = [ 81.1262, 87.5920, 94.0047, 100.0332, 107.9252] +24-11-19 20:42:25 | D | best error = [ 7.3707, 7.3707, 7.3707, 7.3707, 7.3707] +24-11-19 20:42:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:42:25 | D | sum error = [ 116.2068, 124.7337, 134.1306, 143.6617, 154.6578] +24-11-19 20:42:25 | D | best error = [ 7.3707, 7.3707, 7.3707, 7.3707, 7.3707] +24-11-19 20:42:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:42:25 | D | sum error = [ 166.3849, 178.6285, 193.2579, 206.9842, 223.0326] +24-11-19 20:42:25 | D | best error = [ 7.3707, 7.3707, 7.3707, 7.3707, 7.3707] +24-11-19 20:42:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:42:25 | D | sum error = [ 239.6944, 258.2565, 278.6619, 300.6582, 323.2351] +24-11-19 20:42:25 | D | best error = [ 7.3707, 7.3707, 7.3707, 7.3707, 7.3707] +24-11-19 20:42:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:42:25 | D | sum error = [ 349.0180, 376.4480, 407.2248, 440.1973, 476.2310] +24-11-19 20:42:25 | D | best error = [ 7.3707, 7.3707, 7.3707, 7.3707, 7.3707] +24-11-19 20:42:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:42:25 | D | sum error = [ 516.2393, 558.0852, 604.4659, 654.7688, 708.6194] +24-11-19 20:42:25 | D | best error = [ 7.3707, 7.3707, 7.3707, 7.3707, 7.3707] +24-11-19 20:42:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:42:25 | D | sum error = [ 767.9416, 830.9426, 900.0475, 974.6990, 1055.1992] +24-11-19 20:42:25 | D | best error = [ 7.3707, 7.3707, 7.3707, 7.3707, 7.3707] +24-11-19 20:42:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:42:25 | D | sum error = [ 1141.9816, 1230.1680, 1323.7691, 1418.2872, 1518.5933] +24-11-19 20:42:25 | D | best error = [ 7.3707, 7.3707, 7.3707, 7.3707, 7.3707] +24-11-19 20:42:25 | D | + error = [7.3707] +24-11-19 20:42:25 | D | - Calibrating model.layers.28.self_attn.v_proj.weight +24-11-19 20:42:25 | D | + w: sint8 +24-11-19 20:42:25 | D | + x: None +24-11-19 20:42:25 | D | + y: None +24-11-19 20:42:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:42:25 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:42:25 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:42:26 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:42:26 | D | - range ratio = [ 1.0000] +24-11-19 20:42:26 | D | sum error = [ 2.8251] +24-11-19 20:42:26 | D | best error = [ 2.8251] +24-11-19 20:42:26 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:42:26 | D | sum error = [ 2.8422, 2.8019, 2.8361, 2.8516, 2.9121] +24-11-19 20:42:26 | D | best error = [ 2.5296, 2.4137, 2.3662, 2.3406, 2.3253] +24-11-19 20:42:26 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:42:26 | D | sum error = [ 3.0069, 3.0513, 3.2092, 3.3516, 3.5651] +24-11-19 20:42:26 | D | best error = [ 2.3180, 2.3136, 2.3125, 2.3119, 2.3119] +24-11-19 20:42:26 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:42:26 | D | sum error = [ 3.7432, 3.9899, 4.2434, 4.5464, 4.8125] +24-11-19 20:42:26 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:42:26 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:42:26 | D | sum error = [ 5.1427, 5.5566, 5.9173, 6.3237, 6.7958] +24-11-19 20:42:26 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:42:26 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:42:26 | D | sum error = [ 7.2333, 7.7776, 8.2776, 8.8720, 9.4667] +24-11-19 20:42:26 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:42:26 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:42:26 | D | sum error = [ 10.1432, 10.8067, 11.4885, 12.2829, 13.0566] +24-11-19 20:42:26 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:42:26 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:42:26 | D | sum error = [ 13.8715, 14.7360, 15.6565, 16.6176, 17.6501] +24-11-19 20:42:26 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:42:26 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:42:26 | D | sum error = [ 18.7082, 19.8505, 21.0346, 22.3097, 23.6328] +24-11-19 20:42:26 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:42:26 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:42:26 | D | sum error = [ 25.0508, 26.4795, 27.9940, 29.5767, 31.2160] +24-11-19 20:42:26 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:42:26 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:42:26 | D | sum error = [ 32.9288, 34.7223, 36.5611, 38.5013, 40.5078] +24-11-19 20:42:26 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:42:26 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:42:26 | D | sum error = [ 42.6294, 44.8214, 47.0909, 49.4652, 51.8944] +24-11-19 20:42:26 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:42:26 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:42:26 | D | sum error = [ 54.4455, 57.0746, 59.8264, 62.6304, 65.5644] +24-11-19 20:42:26 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:42:26 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:42:26 | D | sum error = [ 68.5997, 71.7355, 74.9618, 78.3039, 81.7253] +24-11-19 20:42:26 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:42:26 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:42:26 | D | sum error = [ 85.2902, 88.9690, 92.7677, 96.6820, 100.7115] +24-11-19 20:42:26 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:42:26 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:42:26 | D | sum error = [ 104.8606, 109.1244, 113.5309, 118.0509, 122.6953] +24-11-19 20:42:26 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:42:26 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:42:26 | D | sum error = [ 127.4731, 132.3629, 137.3724, 142.5484, 147.8530] +24-11-19 20:42:26 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:42:26 | D | + error = [2.3119] +24-11-19 20:42:26 | D | - Calibrating model.layers.28.self_attn.o_proj.weight +24-11-19 20:42:26 | D | + w: sint8 +24-11-19 20:42:26 | D | + x: None +24-11-19 20:42:26 | D | + y: None +24-11-19 20:42:26 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:42:26 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:42:26 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:42:26 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:42:26 | D | - range ratio = [ 1.0000] +24-11-19 20:42:26 | D | sum error = [ 0.8158] +24-11-19 20:42:26 | D | best error = [ 0.8158] +24-11-19 20:42:27 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:42:27 | D | sum error = [ 0.8088, 0.8123, 0.8154, 0.8261, 0.8438] +24-11-19 20:42:27 | D | best error = [ 0.7611, 0.7389, 0.7259, 0.7175, 0.7123] +24-11-19 20:42:27 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:42:27 | D | sum error = [ 0.8654, 0.8961, 0.9335, 0.9789, 1.0323] +24-11-19 20:42:27 | D | best error = [ 0.7089, 0.7067, 0.7054, 0.7045, 0.7039] +24-11-19 20:42:27 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:42:27 | D | sum error = [ 1.0875, 1.1548, 1.2245, 1.3034, 1.3893] +24-11-19 20:42:27 | D | best error = [ 0.7034, 0.7032, 0.7031, 0.7030, 0.7029] +24-11-19 20:42:27 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:42:27 | D | sum error = [ 1.4767, 1.5745, 1.6796, 1.7892, 1.9073] +24-11-19 20:42:27 | D | best error = [ 0.7029, 0.7029, 0.7029, 0.7029, 0.7029] +24-11-19 20:42:27 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:42:27 | D | sum error = [ 2.0332, 2.1663, 2.3051, 2.4473, 2.6026] +24-11-19 20:42:27 | D | best error = [ 0.7028, 0.7028, 0.7028, 0.7028, 0.7028] +24-11-19 20:42:27 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:42:27 | D | sum error = [ 2.7650, 2.9338, 3.1137, 3.3015, 3.5009] +24-11-19 20:42:27 | D | best error = [ 0.7028, 0.7028, 0.7028, 0.7028, 0.7028] +24-11-19 20:42:27 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:42:27 | D | sum error = [ 3.7091, 3.9267, 4.1545, 4.3950, 4.6450] +24-11-19 20:42:27 | D | best error = [ 0.7028, 0.7028, 0.7028, 0.7028, 0.7028] +24-11-19 20:42:27 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:42:27 | D | sum error = [ 4.9059, 5.1819, 5.4724, 5.7730, 6.0860] +24-11-19 20:42:27 | D | best error = [ 0.7028, 0.7028, 0.7028, 0.7028, 0.7028] +24-11-19 20:42:27 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:42:27 | D | sum error = [ 6.4179, 6.7615, 7.1261, 7.5005, 7.8979] +24-11-19 20:42:27 | D | best error = [ 0.7028, 0.7028, 0.7028, 0.7028, 0.7028] +24-11-19 20:42:27 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:42:27 | D | sum error = [ 8.3123, 8.7447, 9.1945, 9.6638, 10.1503] +24-11-19 20:42:27 | D | best error = [ 0.7028, 0.7028, 0.7028, 0.7028, 0.7028] +24-11-19 20:42:27 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:42:27 | D | sum error = [ 10.6629, 11.1941, 11.7498, 12.3289, 12.9337] +24-11-19 20:42:27 | D | best error = [ 0.7028, 0.7028, 0.7028, 0.7028, 0.7028] +24-11-19 20:42:27 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:42:27 | D | sum error = [ 13.5603, 14.2188, 14.9008, 15.6135, 16.3552] +24-11-19 20:42:27 | D | best error = [ 0.7028, 0.7028, 0.7028, 0.7028, 0.7028] +24-11-19 20:42:27 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:42:27 | D | sum error = [ 17.1262, 17.9294, 18.7644, 19.6301, 20.5335] +24-11-19 20:42:27 | D | best error = [ 0.7028, 0.7028, 0.7028, 0.7028, 0.7028] +24-11-19 20:42:27 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:42:27 | D | sum error = [ 21.4706, 22.4436, 23.4535, 24.5023, 25.5894] +24-11-19 20:42:27 | D | best error = [ 0.7028, 0.7028, 0.7028, 0.7028, 0.7028] +24-11-19 20:42:27 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:42:27 | D | sum error = [ 26.7175, 27.8886, 29.0998, 30.3555, 31.6567] +24-11-19 20:42:27 | D | best error = [ 0.7028, 0.7028, 0.7028, 0.7028, 0.7028] +24-11-19 20:42:27 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:42:27 | D | sum error = [ 33.0015, 34.3929, 35.8304, 37.3158, 38.8531] +24-11-19 20:42:27 | D | best error = [ 0.7028, 0.7028, 0.7028, 0.7028, 0.7028] +24-11-19 20:42:27 | D | + error = [0.7028] +24-11-19 20:42:27 | D | - Calibrating model.layers.28.mlp.up_proj.weight +24-11-19 20:42:27 | D | + w: sint8 +24-11-19 20:42:27 | D | + x: None +24-11-19 20:42:27 | D | + y: None +24-11-19 20:42:27 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:42:27 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:42:27 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:42:27 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:42:27 | D | - range ratio = [ 1.0000] +24-11-19 20:42:27 | D | sum error = [ 0.5199] +24-11-19 20:42:27 | D | best error = [ 0.5199] +24-11-19 20:42:28 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:42:28 | D | sum error = [ 0.5156, 0.5127, 0.5174, 0.5215, 0.5310] +24-11-19 20:42:28 | D | best error = [ 0.4590, 0.4376, 0.4276, 0.4221, 0.4192] +24-11-19 20:42:28 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:42:28 | D | sum error = [ 0.5457, 0.5648, 0.5875, 0.6151, 0.6459] +24-11-19 20:42:28 | D | best error = [ 0.4177, 0.4169, 0.4166, 0.4165, 0.4164] +24-11-19 20:42:28 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:42:28 | D | sum error = [ 0.6831, 0.7276, 0.7722, 0.8242, 0.8828] +24-11-19 20:42:28 | D | best error = [ 0.4164, 0.4164, 0.4164, 0.4164, 0.4164] +24-11-19 20:42:28 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:42:28 | D | sum error = [ 0.9453, 1.0086, 1.0807, 1.1590, 1.2413] +24-11-19 20:42:28 | D | best error = [ 0.4164, 0.4164, 0.4164, 0.4164, 0.4164] +24-11-19 20:42:28 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:42:28 | D | sum error = [ 1.3307, 1.4236, 1.5234, 1.6288, 1.7419] +24-11-19 20:42:28 | D | best error = [ 0.4164, 0.4164, 0.4164, 0.4164, 0.4164] +24-11-19 20:42:28 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:42:28 | D | sum error = [ 1.8604, 1.9858, 2.1193, 2.2592, 2.4086] +24-11-19 20:42:28 | D | best error = [ 0.4164, 0.4164, 0.4164, 0.4164, 0.4164] +24-11-19 20:42:28 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:42:28 | D | sum error = [ 2.5629, 2.7261, 2.8992, 3.0816, 3.2720] +24-11-19 20:42:28 | D | best error = [ 0.4164, 0.4164, 0.4164, 0.4164, 0.4164] +24-11-19 20:42:28 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:42:28 | D | sum error = [ 3.4738, 3.6859, 3.9048, 4.1364, 4.3816] +24-11-19 20:42:28 | D | best error = [ 0.4164, 0.4164, 0.4164, 0.4164, 0.4164] +24-11-19 20:42:28 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:42:28 | D | sum error = [ 4.6387, 4.9080, 5.1887, 5.4797, 5.7873] +24-11-19 20:42:28 | D | best error = [ 0.4164, 0.4164, 0.4164, 0.4164, 0.4164] +24-11-19 20:42:28 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:42:28 | D | sum error = [ 6.1077, 6.4404, 6.7886, 7.1529, 7.5313] +24-11-19 20:42:28 | D | best error = [ 0.4164, 0.4164, 0.4164, 0.4164, 0.4164] +24-11-19 20:42:28 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:42:28 | D | sum error = [ 7.9260, 8.3355, 8.7627, 9.2045, 9.6667] +24-11-19 20:42:28 | D | best error = [ 0.4164, 0.4164, 0.4164, 0.4164, 0.4164] +24-11-19 20:42:28 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:42:28 | D | sum error = [ 10.1438, 10.6403, 11.1523, 11.6824, 12.2315] +24-11-19 20:42:28 | D | best error = [ 0.4164, 0.4164, 0.4164, 0.4164, 0.4164] +24-11-19 20:42:28 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:42:28 | D | sum error = [ 12.8010, 13.3896, 13.9980, 14.6299, 15.2800] +24-11-19 20:42:28 | D | best error = [ 0.4164, 0.4164, 0.4164, 0.4164, 0.4164] +24-11-19 20:42:28 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:42:28 | D | sum error = [ 15.9470, 16.6366, 17.3512, 18.0864, 18.8434] +24-11-19 20:42:28 | D | best error = [ 0.4164, 0.4164, 0.4164, 0.4164, 0.4164] +24-11-19 20:42:28 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:42:28 | D | sum error = [ 19.6234, 20.4314, 21.2612, 22.1147, 22.9893] +24-11-19 20:42:28 | D | best error = [ 0.4164, 0.4164, 0.4164, 0.4164, 0.4164] +24-11-19 20:42:28 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:42:28 | D | sum error = [ 23.8952, 24.8273, 25.7784, 26.7513, 27.7489] +24-11-19 20:42:28 | D | best error = [ 0.4164, 0.4164, 0.4164, 0.4164, 0.4164] +24-11-19 20:42:28 | D | + error = [0.4164] +24-11-19 20:42:28 | D | - Calibrating model.layers.28.mlp.gate_proj.weight +24-11-19 20:42:28 | D | + w: sint8 +24-11-19 20:42:28 | D | + x: None +24-11-19 20:42:28 | D | + y: None +24-11-19 20:42:28 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:42:28 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:42:28 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:42:29 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:42:29 | D | - range ratio = [ 1.0000] +24-11-19 20:42:29 | D | sum error = [ 12.5620] +24-11-19 20:42:29 | D | best error = [ 12.5620] +24-11-19 20:42:30 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:42:30 | D | sum error = [ 12.4409, 12.4304, 12.4579, 12.6164, 12.8288] +24-11-19 20:42:30 | D | best error = [ 11.0524, 10.5564, 10.3077, 10.1795, 10.1051] +24-11-19 20:42:30 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:42:30 | D | sum error = [ 13.1825, 13.6849, 14.1400, 14.8340, 15.6469] +24-11-19 20:42:30 | D | best error = [ 10.0672, 10.0495, 10.0425, 10.0394, 10.0386] +24-11-19 20:42:30 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:42:30 | D | sum error = [ 16.5433, 17.5649, 18.7160, 19.9926, 21.4132] +24-11-19 20:42:30 | D | best error = [ 10.0385, 10.0384, 10.0383, 10.0383, 10.0383] +24-11-19 20:42:30 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:42:30 | D | sum error = [ 22.9232, 24.5769, 26.3455, 28.2880, 30.3195] +24-11-19 20:42:30 | D | best error = [ 10.0383, 10.0383, 10.0383, 10.0383, 10.0383] +24-11-19 20:42:30 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:42:30 | D | sum error = [ 32.5122, 34.9027, 37.3582, 40.0527, 42.8263] +24-11-19 20:42:30 | D | best error = [ 10.0383, 10.0383, 10.0383, 10.0383, 10.0383] +24-11-19 20:42:30 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:42:30 | D | sum error = [ 45.9026, 49.0826, 52.4690, 56.0810, 59.8534] +24-11-19 20:42:30 | D | best error = [ 10.0383, 10.0383, 10.0383, 10.0383, 10.0383] +24-11-19 20:42:30 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:42:30 | D | sum error = [ 63.8829, 68.1597, 72.7695, 77.5007, 82.6207] +24-11-19 20:42:30 | D | best error = [ 10.0383, 10.0383, 10.0383, 10.0383, 10.0383] +24-11-19 20:42:30 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:42:30 | D | sum error = [ 87.9482, 93.6740, 99.6654, 106.0379, 112.7124] +24-11-19 20:42:30 | D | best error = [ 10.0383, 10.0383, 10.0383, 10.0383, 10.0383] +24-11-19 20:42:30 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:42:30 | D | sum error = [ 119.8602, 127.3799, 135.2971, 143.7415, 152.5269] +24-11-19 20:42:30 | D | best error = [ 10.0383, 10.0383, 10.0383, 10.0383, 10.0383] +24-11-19 20:42:30 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:42:30 | D | sum error = [ 161.8712, 171.6972, 182.1383, 193.0930, 204.5322] +24-11-19 20:42:30 | D | best error = [ 10.0383, 10.0383, 10.0383, 10.0383, 10.0383] +24-11-19 20:42:30 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:42:30 | D | sum error = [ 216.6249, 229.3770, 242.7790, 256.8554, 271.6951] +24-11-19 20:42:30 | D | best error = [ 10.0383, 10.0383, 10.0383, 10.0383, 10.0383] +24-11-19 20:42:30 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:42:30 | D | sum error = [ 287.2048, 303.5089, 320.5995, 338.5454, 357.3244] +24-11-19 20:42:30 | D | best error = [ 10.0383, 10.0383, 10.0383, 10.0383, 10.0383] +24-11-19 20:42:30 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:42:30 | D | sum error = [ 376.9350, 397.5041, 419.0809, 441.5637, 465.0418] +24-11-19 20:42:30 | D | best error = [ 10.0383, 10.0383, 10.0383, 10.0383, 10.0383] +24-11-19 20:42:30 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:42:30 | D | sum error = [ 489.5238, 515.1096, 541.7301, 569.4037, 598.1465] +24-11-19 20:42:30 | D | best error = [ 10.0383, 10.0383, 10.0383, 10.0383, 10.0383] +24-11-19 20:42:30 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:42:30 | D | sum error = [ 627.9289, 658.8100, 690.8459, 723.9906, 758.3806] +24-11-19 20:42:30 | D | best error = [ 10.0383, 10.0383, 10.0383, 10.0383, 10.0383] +24-11-19 20:42:30 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:42:30 | D | sum error = [ 793.9311, 830.6569, 868.5771, 907.7477, 948.1772] +24-11-19 20:42:30 | D | best error = [ 10.0383, 10.0383, 10.0383, 10.0383, 10.0383] +24-11-19 20:42:30 | D | + error = [10.0383] +24-11-19 20:42:30 | D | - Calibrating model.layers.28.mlp.down_proj.weight +24-11-19 20:42:30 | D | + w: sint8 +24-11-19 20:42:30 | D | + x: None +24-11-19 20:42:30 | D | + y: None +24-11-19 20:42:30 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:42:30 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:42:30 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:42:30 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:42:30 | D | - range ratio = [ 1.0000] +24-11-19 20:42:30 | D | sum error = [ 1.6458] +24-11-19 20:42:30 | D | best error = [ 1.6458] +24-11-19 20:42:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:42:31 | D | sum error = [ 1.6299, 1.6282, 1.6203, 1.6243, 1.6390] +24-11-19 20:42:31 | D | best error = [ 1.5568, 1.5225, 1.4998, 1.4844, 1.4726] +24-11-19 20:42:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:42:31 | D | sum error = [ 1.6562, 1.6912, 1.7354, 1.7911, 1.8617] +24-11-19 20:42:31 | D | best error = [ 1.4645, 1.4589, 1.4551, 1.4527, 1.4508] +24-11-19 20:42:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:42:31 | D | sum error = [ 1.9456, 2.0389, 2.1504, 2.2726, 2.4148] +24-11-19 20:42:31 | D | best error = [ 1.4497, 1.4487, 1.4483, 1.4481, 1.4479] +24-11-19 20:42:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:42:31 | D | sum error = [ 2.5679, 2.7404, 2.9262, 3.1315, 3.3515] +24-11-19 20:42:31 | D | best error = [ 1.4477, 1.4477, 1.4477, 1.4477, 1.4477] +24-11-19 20:42:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:42:31 | D | sum error = [ 3.5833, 3.8356, 4.1121, 4.3969, 4.7074] +24-11-19 20:42:31 | D | best error = [ 1.4477, 1.4477, 1.4477, 1.4477, 1.4477] +24-11-19 20:42:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:42:31 | D | sum error = [ 5.0299, 5.3774, 5.7427, 6.1383, 6.5486] +24-11-19 20:42:31 | D | best error = [ 1.4477, 1.4477, 1.4477, 1.4477, 1.4477] +24-11-19 20:42:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:42:31 | D | sum error = [ 6.9799, 7.4365, 7.9250, 8.4438, 8.9809] +24-11-19 20:42:31 | D | best error = [ 1.4477, 1.4477, 1.4477, 1.4477, 1.4477] +24-11-19 20:42:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:42:31 | D | sum error = [ 9.5537, 10.1584, 10.7918, 11.4669, 12.1712] +24-11-19 20:42:31 | D | best error = [ 1.4477, 1.4477, 1.4477, 1.4477, 1.4477] +24-11-19 20:42:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:42:31 | D | sum error = [ 12.9144, 13.6975, 14.5269, 15.4008, 16.3136] +24-11-19 20:42:31 | D | best error = [ 1.4477, 1.4477, 1.4477, 1.4477, 1.4477] +24-11-19 20:42:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:42:31 | D | sum error = [ 17.2757, 18.2812, 19.3403, 20.4479, 21.6073] +24-11-19 20:42:31 | D | best error = [ 1.4477, 1.4477, 1.4477, 1.4477, 1.4477] +24-11-19 20:42:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:42:31 | D | sum error = [ 22.8258, 24.1024, 25.4373, 26.8409, 28.3104] +24-11-19 20:42:31 | D | best error = [ 1.4477, 1.4477, 1.4477, 1.4477, 1.4477] +24-11-19 20:42:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:42:31 | D | sum error = [ 29.8533, 31.4596, 33.1440, 34.9035, 36.7382] +24-11-19 20:42:31 | D | best error = [ 1.4477, 1.4477, 1.4477, 1.4477, 1.4477] +24-11-19 20:42:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:42:31 | D | sum error = [ 38.6515, 40.6499, 42.7282, 44.8954, 47.1511] +24-11-19 20:42:31 | D | best error = [ 1.4477, 1.4477, 1.4477, 1.4477, 1.4477] +24-11-19 20:42:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:42:31 | D | sum error = [ 49.4977, 51.9411, 54.4783, 57.1133, 59.8560] +24-11-19 20:42:31 | D | best error = [ 1.4477, 1.4477, 1.4477, 1.4477, 1.4477] +24-11-19 20:42:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:42:31 | D | sum error = [ 62.6960, 65.6451, 68.6984, 71.8634, 75.1375] +24-11-19 20:42:31 | D | best error = [ 1.4477, 1.4477, 1.4477, 1.4477, 1.4477] +24-11-19 20:42:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:42:31 | D | sum error = [ 78.5176, 82.0120, 85.6196, 89.3484, 93.1889] +24-11-19 20:42:31 | D | best error = [ 1.4477, 1.4477, 1.4477, 1.4477, 1.4477] +24-11-19 20:42:31 | D | + error = [1.4477] +24-11-19 20:42:32 | D | - Quantizing model.layers.28.self_attn.q_proj.weight +24-11-19 20:42:32 | D | - Quantizing model.layers.28.self_attn.k_proj.weight +24-11-19 20:42:33 | D | - Quantizing model.layers.28.self_attn.v_proj.weight +24-11-19 20:42:34 | D | - Quantizing model.layers.28.self_attn.o_proj.weight +24-11-19 20:42:35 | D | - Quantizing model.layers.28.mlp.up_proj.weight +24-11-19 20:42:36 | D | - Quantizing model.layers.28.mlp.gate_proj.weight +24-11-19 20:42:37 | D | - Quantizing model.layers.28.mlp.down_proj.weight +24-11-19 20:42:48 | D | - Quantizing layer model.layers.29 +24-11-19 20:42:48 | D | - Calibrating model.layers.29.self_attn.q_proj.weight +24-11-19 20:42:48 | D | + w: sint8 +24-11-19 20:42:48 | D | + x: None +24-11-19 20:42:48 | D | + y: None +24-11-19 20:42:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:42:48 | D | + finished parsing calibration arguments, ram usage: 12.8 +24-11-19 20:42:48 | D | + finished reseting calibrator, ram usage: 12.8 +24-11-19 20:42:49 | D | + finished calculating the original outputs, ram usage: 12.8 +24-11-19 20:42:49 | D | - range ratio = [ 1.0000] +24-11-19 20:42:49 | D | sum error = [ 9.7939] +24-11-19 20:42:49 | D | best error = [ 9.7939] +24-11-19 20:43:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:43:03 | D | sum error = [ 8.6501, 8.5427, 9.2308, 8.7931, 8.8597] +24-11-19 20:43:03 | D | best error = [ 8.6501, 8.5427, 8.5427, 8.5427, 8.5427] +24-11-19 20:43:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:43:03 | D | sum error = [ 9.1262, 9.4929, 10.0634, 10.0989, 12.2678] +24-11-19 20:43:03 | D | best error = [ 8.5427, 8.5427, 8.5427, 8.5427, 8.5427] +24-11-19 20:43:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:43:03 | D | sum error = [ 12.2620, 13.0810, 14.1887, 14.7632, 15.9372] +24-11-19 20:43:03 | D | best error = [ 8.5427, 8.5427, 8.5427, 8.5427, 8.5427] +24-11-19 20:43:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:43:03 | D | sum error = [ 17.8499, 19.3770, 19.7127, 23.0048, 24.8537] +24-11-19 20:43:03 | D | best error = [ 8.5427, 8.5427, 8.5427, 8.5427, 8.5427] +24-11-19 20:43:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:43:03 | D | sum error = [ 26.8192, 29.9891, 31.2523, 34.6382, 36.7458] +24-11-19 20:43:03 | D | best error = [ 8.5427, 8.5427, 8.5427, 8.5427, 8.5427] +24-11-19 20:43:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:43:03 | D | sum error = [ 39.7366, 42.2460, 46.0661, 49.2506, 53.2969] +24-11-19 20:43:03 | D | best error = [ 8.5427, 8.5427, 8.5427, 8.5427, 8.5427] +24-11-19 20:43:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:43:03 | D | sum error = [ 56.4014, 60.9381, 65.2524, 70.2948, 75.0372] +24-11-19 20:43:03 | D | best error = [ 8.5427, 8.5427, 8.5427, 8.5427, 8.5427] +24-11-19 20:43:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:43:03 | D | sum error = [ 80.8298, 86.3089, 92.9216, 99.8344, 106.5776] +24-11-19 20:43:03 | D | best error = [ 8.5427, 8.5427, 8.5427, 8.5427, 8.5427] +24-11-19 20:43:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:43:03 | D | sum error = [ 114.0314, 122.7650, 130.8482, 140.6030, 151.0875] +24-11-19 20:43:03 | D | best error = [ 8.5427, 8.5427, 8.5427, 8.5427, 8.5427] +24-11-19 20:43:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:43:03 | D | sum error = [ 161.4435, 173.6196, 187.0015, 201.2664, 216.0039] +24-11-19 20:43:03 | D | best error = [ 8.5427, 8.5427, 8.5427, 8.5427, 8.5427] +24-11-19 20:43:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:43:03 | D | sum error = [ 231.7217, 248.0511, 265.2332, 284.7012, 304.4324] +24-11-19 20:43:03 | D | best error = [ 8.5427, 8.5427, 8.5427, 8.5427, 8.5427] +24-11-19 20:43:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:43:03 | D | sum error = [ 325.8890, 349.7698, 374.7354, 402.3033, 432.6442] +24-11-19 20:43:03 | D | best error = [ 8.5427, 8.5427, 8.5427, 8.5427, 8.5427] +24-11-19 20:43:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:43:03 | D | sum error = [ 464.3894, 499.5787, 537.4354, 579.5138, 625.1038] +24-11-19 20:43:03 | D | best error = [ 8.5427, 8.5427, 8.5427, 8.5427, 8.5427] +24-11-19 20:43:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:43:03 | D | sum error = [ 675.2653, 728.9357, 788.8620, 854.3180, 926.0545] +24-11-19 20:43:03 | D | best error = [ 8.5427, 8.5427, 8.5427, 8.5427, 8.5427] +24-11-19 20:43:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:43:03 | D | sum error = [ 1003.2037, 1088.4020, 1181.0338, 1281.0665, 1389.9366] +24-11-19 20:43:03 | D | best error = [ 8.5427, 8.5427, 8.5427, 8.5427, 8.5427] +24-11-19 20:43:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:43:03 | D | sum error = [ 1508.0499, 1633.2553, 1767.3172, 1905.4305, 2051.6905] +24-11-19 20:43:03 | D | best error = [ 8.5427, 8.5427, 8.5427, 8.5427, 8.5427] +24-11-19 20:43:03 | D | + error = [8.5427] +24-11-19 20:43:03 | D | - Calibrating model.layers.29.self_attn.k_proj.weight +24-11-19 20:43:03 | D | + w: sint8 +24-11-19 20:43:03 | D | + x: None +24-11-19 20:43:03 | D | + y: None +24-11-19 20:43:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:03 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:43:03 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:43:04 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:43:04 | D | - range ratio = [ 1.0000] +24-11-19 20:43:04 | D | sum error = [ 8.6612] +24-11-19 20:43:04 | D | best error = [ 8.6612] +24-11-19 20:43:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:43:17 | D | sum error = [ 9.1538, 9.4795, 9.0033, 10.5610, 8.9971] +24-11-19 20:43:17 | D | best error = [ 8.6612, 8.6612, 8.6612, 8.6612, 8.6612] +24-11-19 20:43:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:43:17 | D | sum error = [ 9.1825, 11.4481, 10.1042, 10.8807, 11.1058] +24-11-19 20:43:17 | D | best error = [ 8.6612, 8.6612, 8.6612, 8.6612, 8.6612] +24-11-19 20:43:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:43:17 | D | sum error = [ 12.4379, 15.5520, 14.9485, 18.0048, 17.4225] +24-11-19 20:43:17 | D | best error = [ 8.6612, 8.6612, 8.6612, 8.6612, 8.6612] +24-11-19 20:43:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:43:17 | D | sum error = [ 15.7561, 17.4394, 21.3013, 25.1892, 23.1298] +24-11-19 20:43:17 | D | best error = [ 8.6612, 8.6612, 8.6612, 8.6612, 8.6612] +24-11-19 20:43:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:43:17 | D | sum error = [ 25.1638, 26.4950, 27.3945, 29.3695, 32.1318] +24-11-19 20:43:17 | D | best error = [ 8.6612, 8.6612, 8.6612, 8.6612, 8.6612] +24-11-19 20:43:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:43:17 | D | sum error = [ 33.5083, 37.1375, 38.8372, 42.0509, 45.1856] +24-11-19 20:43:17 | D | best error = [ 8.6612, 8.6612, 8.6612, 8.6612, 8.6612] +24-11-19 20:43:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:43:17 | D | sum error = [ 47.3146, 52.0619, 55.2275, 58.7666, 62.4288] +24-11-19 20:43:17 | D | best error = [ 8.6612, 8.6612, 8.6612, 8.6612, 8.6612] +24-11-19 20:43:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:43:17 | D | sum error = [ 66.1193, 71.1896, 75.6615, 82.1028, 88.6574] +24-11-19 20:43:17 | D | best error = [ 8.6612, 8.6612, 8.6612, 8.6612, 8.6612] +24-11-19 20:43:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:43:17 | D | sum error = [ 95.5965, 105.1686, 114.3150, 122.6238, 135.6442] +24-11-19 20:43:17 | D | best error = [ 8.6612, 8.6612, 8.6612, 8.6612, 8.6612] +24-11-19 20:43:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:43:17 | D | sum error = [ 149.2944, 161.2233, 177.6570, 196.3592, 217.7920] +24-11-19 20:43:17 | D | best error = [ 8.6612, 8.6612, 8.6612, 8.6612, 8.6612] +24-11-19 20:43:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:43:17 | D | sum error = [ 235.7669, 261.3173, 284.7416, 310.3426, 336.5852] +24-11-19 20:43:17 | D | best error = [ 8.6612, 8.6612, 8.6612, 8.6612, 8.6612] +24-11-19 20:43:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:43:17 | D | sum error = [ 365.9833, 395.7471, 423.4720, 458.8485, 490.1792] +24-11-19 20:43:17 | D | best error = [ 8.6612, 8.6612, 8.6612, 8.6612, 8.6612] +24-11-19 20:43:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:43:17 | D | sum error = [ 525.9312, 563.1329, 605.0210, 653.2228, 698.0840] +24-11-19 20:43:17 | D | best error = [ 8.6612, 8.6612, 8.6612, 8.6612, 8.6612] +24-11-19 20:43:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:43:17 | D | sum error = [ 750.0805, 807.7844, 865.9450, 930.0521, 1001.9961] +24-11-19 20:43:17 | D | best error = [ 8.6612, 8.6612, 8.6612, 8.6612, 8.6612] +24-11-19 20:43:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:43:17 | D | sum error = [ 1075.5023, 1155.3134, 1247.0485, 1338.5275, 1443.7119] +24-11-19 20:43:17 | D | best error = [ 8.6612, 8.6612, 8.6612, 8.6612, 8.6612] +24-11-19 20:43:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:43:17 | D | sum error = [ 1554.5330, 1673.3827, 1796.9974, 1930.4752, 2066.5708] +24-11-19 20:43:17 | D | best error = [ 8.6612, 8.6612, 8.6612, 8.6612, 8.6612] +24-11-19 20:43:17 | D | + error = [8.6612] +24-11-19 20:43:18 | D | - Calibrating model.layers.29.self_attn.v_proj.weight +24-11-19 20:43:18 | D | + w: sint8 +24-11-19 20:43:18 | D | + x: None +24-11-19 20:43:18 | D | + y: None +24-11-19 20:43:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:43:18 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:43:18 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:43:18 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:43:18 | D | - range ratio = [ 1.0000] +24-11-19 20:43:18 | D | sum error = [ 3.1148] +24-11-19 20:43:18 | D | best error = [ 3.1148] +24-11-19 20:43:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:43:18 | D | sum error = [ 3.0928, 3.1116, 3.1179, 3.1334, 3.2179] +24-11-19 20:43:18 | D | best error = [ 2.7894, 2.6828, 2.6259, 2.5875, 2.5719] +24-11-19 20:43:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:43:18 | D | sum error = [ 3.3544, 3.4160, 3.5193, 3.7246, 3.9557] +24-11-19 20:43:18 | D | best error = [ 2.5641, 2.5614, 2.5597, 2.5594, 2.5593] +24-11-19 20:43:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:43:18 | D | sum error = [ 4.1557, 4.3859, 4.6796, 5.0063, 5.3169] +24-11-19 20:43:18 | D | best error = [ 2.5592, 2.5592, 2.5592, 2.5592, 2.5592] +24-11-19 20:43:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:43:18 | D | sum error = [ 5.6994, 6.1313, 6.5307, 7.0238, 7.5363] +24-11-19 20:43:18 | D | best error = [ 2.5592, 2.5592, 2.5592, 2.5592, 2.5592] +24-11-19 20:43:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:43:18 | D | sum error = [ 8.0198, 8.6527, 9.2420, 9.9588, 10.5964] +24-11-19 20:43:18 | D | best error = [ 2.5592, 2.5592, 2.5592, 2.5592, 2.5592] +24-11-19 20:43:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:43:18 | D | sum error = [ 11.3254, 12.1103, 12.8957, 13.7194, 14.6767] +24-11-19 20:43:18 | D | best error = [ 2.5592, 2.5592, 2.5592, 2.5592, 2.5592] +24-11-19 20:43:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:43:18 | D | sum error = [ 15.6529, 16.6094, 17.7044, 18.7651, 19.9497] +24-11-19 20:43:18 | D | best error = [ 2.5592, 2.5592, 2.5592, 2.5592, 2.5592] +24-11-19 20:43:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:43:18 | D | sum error = [ 21.1996, 22.4880, 23.8509, 25.2748, 26.7291] +24-11-19 20:43:18 | D | best error = [ 2.5592, 2.5592, 2.5592, 2.5592, 2.5592] +24-11-19 20:43:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:43:18 | D | sum error = [ 28.2837, 29.9462, 31.6351, 33.4234, 35.3310] +24-11-19 20:43:18 | D | best error = [ 2.5592, 2.5592, 2.5592, 2.5592, 2.5592] +24-11-19 20:43:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:43:18 | D | sum error = [ 37.3275, 39.3786, 41.5175, 43.8067, 46.2371] +24-11-19 20:43:18 | D | best error = [ 2.5592, 2.5592, 2.5592, 2.5592, 2.5592] +24-11-19 20:43:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:43:18 | D | sum error = [ 48.6431, 51.2383, 53.9402, 56.7262, 59.6308] +24-11-19 20:43:18 | D | best error = [ 2.5592, 2.5592, 2.5592, 2.5592, 2.5592] +24-11-19 20:43:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:43:18 | D | sum error = [ 62.6961, 65.8288, 69.0921, 72.4981, 75.9869] +24-11-19 20:43:18 | D | best error = [ 2.5592, 2.5592, 2.5592, 2.5592, 2.5592] +24-11-19 20:43:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:43:18 | D | sum error = [ 79.6547, 83.4524, 87.3647, 91.4345, 95.6317] +24-11-19 20:43:18 | D | best error = [ 2.5592, 2.5592, 2.5592, 2.5592, 2.5592] +24-11-19 20:43:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:43:18 | D | sum error = [ 99.9999, 104.5079, 109.1715, 114.0228, 119.0006] +24-11-19 20:43:18 | D | best error = [ 2.5592, 2.5592, 2.5592, 2.5592, 2.5592] +24-11-19 20:43:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:43:18 | D | sum error = [ 124.1548, 129.4563, 134.9210, 140.5569, 146.3709] +24-11-19 20:43:18 | D | best error = [ 2.5592, 2.5592, 2.5592, 2.5592, 2.5592] +24-11-19 20:43:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:43:18 | D | sum error = [ 152.3356, 158.4851, 164.7949, 171.3004, 177.9744] +24-11-19 20:43:18 | D | best error = [ 2.5592, 2.5592, 2.5592, 2.5592, 2.5592] +24-11-19 20:43:18 | D | + error = [2.5592] +24-11-19 20:43:18 | D | - Calibrating model.layers.29.self_attn.o_proj.weight +24-11-19 20:43:18 | D | + w: sint8 +24-11-19 20:43:18 | D | + x: None +24-11-19 20:43:18 | D | + y: None +24-11-19 20:43:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:43:18 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:43:18 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:43:18 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:43:18 | D | - range ratio = [ 1.0000] +24-11-19 20:43:18 | D | sum error = [ 0.9301] +24-11-19 20:43:18 | D | best error = [ 0.9301] +24-11-19 20:43:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:43:19 | D | sum error = [ 0.9242, 0.9300, 0.9297, 0.9375, 0.9487] +24-11-19 20:43:19 | D | best error = [ 0.8409, 0.8043, 0.7831, 0.7690, 0.7602] +24-11-19 20:43:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:43:19 | D | sum error = [ 0.9733, 0.9996, 1.0290, 1.0752, 1.1220] +24-11-19 20:43:19 | D | best error = [ 0.7539, 0.7490, 0.7457, 0.7433, 0.7414] +24-11-19 20:43:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:43:19 | D | sum error = [ 1.1820, 1.2409, 1.3168, 1.3840, 1.4703] +24-11-19 20:43:19 | D | best error = [ 0.7402, 0.7392, 0.7385, 0.7381, 0.7378] +24-11-19 20:43:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:43:19 | D | sum error = [ 1.5603, 1.6653, 1.7760, 1.8850, 2.0048] +24-11-19 20:43:19 | D | best error = [ 0.7376, 0.7374, 0.7372, 0.7371, 0.7371] +24-11-19 20:43:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:43:19 | D | sum error = [ 2.1385, 2.2797, 2.4140, 2.5786, 2.7460] +24-11-19 20:43:19 | D | best error = [ 0.7371, 0.7370, 0.7370, 0.7370, 0.7370] +24-11-19 20:43:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:43:19 | D | sum error = [ 2.9151, 3.1004, 3.2929, 3.4999, 3.7110] +24-11-19 20:43:19 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:43:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:43:19 | D | sum error = [ 3.9390, 4.1779, 4.4294, 4.6918, 4.9680] +24-11-19 20:43:19 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:43:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:43:19 | D | sum error = [ 5.2609, 5.5715, 5.8904, 6.2377, 6.5900] +24-11-19 20:43:19 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:43:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:43:19 | D | sum error = [ 6.9728, 7.3723, 7.7879, 8.2382, 8.6996] +24-11-19 20:43:19 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:43:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:43:19 | D | sum error = [ 9.1902, 9.7061, 10.2480, 10.8196, 11.4186] +24-11-19 20:43:19 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:43:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:43:19 | D | sum error = [ 12.0557, 12.7337, 13.4447, 14.1941, 14.9893] +24-11-19 20:43:19 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:43:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:43:19 | D | sum error = [ 15.8190, 16.6989, 17.6195, 18.5908, 19.6083] +24-11-19 20:43:19 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:43:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:43:19 | D | sum error = [ 20.6825, 21.8090, 22.9955, 24.2418, 25.5474] +24-11-19 20:43:19 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:43:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:43:19 | D | sum error = [ 26.9202, 28.3578, 29.8692, 31.4514, 33.1072] +24-11-19 20:43:19 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:43:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:43:19 | D | sum error = [ 34.8357, 36.6439, 38.5294, 40.4942, 42.5434] +24-11-19 20:43:19 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:43:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:43:19 | D | sum error = [ 44.6808, 46.9011, 49.2156, 51.6145, 54.1107] +24-11-19 20:43:19 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:43:19 | D | + error = [0.7369] +24-11-19 20:43:19 | D | - Calibrating model.layers.29.mlp.up_proj.weight +24-11-19 20:43:19 | D | + w: sint8 +24-11-19 20:43:19 | D | + x: None +24-11-19 20:43:19 | D | + y: None +24-11-19 20:43:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:43:19 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:43:19 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:43:19 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:43:19 | D | - range ratio = [ 1.0000] +24-11-19 20:43:19 | D | sum error = [ 0.5501] +24-11-19 20:43:19 | D | best error = [ 0.5501] +24-11-19 20:43:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:43:21 | D | sum error = [ 0.5443, 0.5452, 0.5453, 0.5494, 0.5588] +24-11-19 20:43:21 | D | best error = [ 0.4817, 0.4593, 0.4485, 0.4425, 0.4392] +24-11-19 20:43:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:43:21 | D | sum error = [ 0.5756, 0.5943, 0.6199, 0.6482, 0.6799] +24-11-19 20:43:21 | D | best error = [ 0.4373, 0.4365, 0.4362, 0.4360, 0.4360] +24-11-19 20:43:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:43:21 | D | sum error = [ 0.7250, 0.7664, 0.8139, 0.8693, 0.9344] +24-11-19 20:43:21 | D | best error = [ 0.4360, 0.4360, 0.4360, 0.4360, 0.4360] +24-11-19 20:43:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:43:21 | D | sum error = [ 0.9944, 1.0654, 1.1419, 1.2272, 1.3122] +24-11-19 20:43:21 | D | best error = [ 0.4360, 0.4360, 0.4360, 0.4360, 0.4360] +24-11-19 20:43:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:43:21 | D | sum error = [ 1.4060, 1.5047, 1.6098, 1.7255, 1.8440] +24-11-19 20:43:21 | D | best error = [ 0.4360, 0.4360, 0.4360, 0.4360, 0.4360] +24-11-19 20:43:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:43:21 | D | sum error = [ 1.9701, 2.1029, 2.2474, 2.3960, 2.5552] +24-11-19 20:43:21 | D | best error = [ 0.4360, 0.4360, 0.4360, 0.4360, 0.4360] +24-11-19 20:43:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:43:21 | D | sum error = [ 2.7209, 2.8978, 3.0833, 3.2760, 3.4802] +24-11-19 20:43:21 | D | best error = [ 0.4360, 0.4360, 0.4360, 0.4360, 0.4360] +24-11-19 20:43:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:43:21 | D | sum error = [ 3.6977, 3.9242, 4.1608, 4.4087, 4.6710] +24-11-19 20:43:21 | D | best error = [ 0.4360, 0.4360, 0.4360, 0.4360, 0.4360] +24-11-19 20:43:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:43:21 | D | sum error = [ 4.9496, 5.2358, 5.5354, 5.8510, 6.1795] +24-11-19 20:43:21 | D | best error = [ 0.4360, 0.4360, 0.4360, 0.4360, 0.4360] +24-11-19 20:43:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:43:21 | D | sum error = [ 6.5204, 6.8820, 7.2535, 7.6443, 8.0525] +24-11-19 20:43:21 | D | best error = [ 0.4360, 0.4360, 0.4360, 0.4360, 0.4360] +24-11-19 20:43:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:43:21 | D | sum error = [ 8.4792, 8.9235, 9.3859, 9.8707, 10.3722] +24-11-19 20:43:21 | D | best error = [ 0.4360, 0.4360, 0.4360, 0.4360, 0.4360] +24-11-19 20:43:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:43:21 | D | sum error = [ 10.8961, 11.4380, 12.0025, 12.5887, 13.1939] +24-11-19 20:43:21 | D | best error = [ 0.4360, 0.4360, 0.4360, 0.4360, 0.4360] +24-11-19 20:43:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:43:21 | D | sum error = [ 13.8323, 14.4844, 15.1626, 15.8665, 16.5864] +24-11-19 20:43:21 | D | best error = [ 0.4360, 0.4360, 0.4360, 0.4360, 0.4360] +24-11-19 20:43:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:43:21 | D | sum error = [ 17.3400, 18.1193, 18.9219, 19.7549, 20.6101] +24-11-19 20:43:21 | D | best error = [ 0.4360, 0.4360, 0.4360, 0.4360, 0.4360] +24-11-19 20:43:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:43:21 | D | sum error = [ 21.4960, 22.4174, 23.3560, 24.3323, 25.3313] +24-11-19 20:43:21 | D | best error = [ 0.4360, 0.4360, 0.4360, 0.4360, 0.4360] +24-11-19 20:43:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:43:21 | D | sum error = [ 26.3598, 27.4219, 28.5088, 29.6340, 30.7881] +24-11-19 20:43:21 | D | best error = [ 0.4360, 0.4360, 0.4360, 0.4360, 0.4360] +24-11-19 20:43:21 | D | + error = [0.4360] +24-11-19 20:43:21 | D | - Calibrating model.layers.29.mlp.gate_proj.weight +24-11-19 20:43:21 | D | + w: sint8 +24-11-19 20:43:21 | D | + x: None +24-11-19 20:43:21 | D | + y: None +24-11-19 20:43:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:43:21 | D | + finished parsing calibration arguments, ram usage: 13.1 +24-11-19 20:43:21 | D | + finished reseting calibrator, ram usage: 13.1 +24-11-19 20:43:21 | D | + finished calculating the original outputs, ram usage: 13.1 +24-11-19 20:43:21 | D | - range ratio = [ 1.0000] +24-11-19 20:43:21 | D | sum error = [ 12.6728] +24-11-19 20:43:21 | D | best error = [ 12.6728] +24-11-19 20:43:22 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:43:22 | D | sum error = [ 12.6270, 12.6185, 12.6617, 12.7899, 13.0662] +24-11-19 20:43:22 | D | best error = [ 11.1781, 10.6698, 10.4195, 10.2807, 10.2112] +24-11-19 20:43:22 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:43:22 | D | sum error = [ 13.4136, 13.8508, 14.3321, 15.0833, 15.9330] +24-11-19 20:43:22 | D | best error = [ 10.1725, 10.1537, 10.1434, 10.1402, 10.1392] +24-11-19 20:43:22 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:43:22 | D | sum error = [ 16.8198, 17.8233, 19.0301, 20.3275, 21.7960] +24-11-19 20:43:22 | D | best error = [ 10.1389, 10.1389, 10.1389, 10.1389, 10.1389] +24-11-19 20:43:22 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:43:22 | D | sum error = [ 23.2846, 24.9616, 26.7623, 28.7049, 30.8306] +24-11-19 20:43:22 | D | best error = [ 10.1389, 10.1389, 10.1389, 10.1389, 10.1389] +24-11-19 20:43:22 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:43:22 | D | sum error = [ 33.0873, 35.4766, 37.9868, 40.6885, 43.6864] +24-11-19 20:43:22 | D | best error = [ 10.1389, 10.1389, 10.1389, 10.1389, 10.1389] +24-11-19 20:43:22 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:43:22 | D | sum error = [ 46.6623, 49.9479, 53.3797, 57.0247, 60.9550] +24-11-19 20:43:22 | D | best error = [ 10.1389, 10.1389, 10.1389, 10.1389, 10.1389] +24-11-19 20:43:22 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:43:22 | D | sum error = [ 65.0783, 69.4987, 74.1633, 79.0756, 84.3346] +24-11-19 20:43:22 | D | best error = [ 10.1389, 10.1389, 10.1389, 10.1389, 10.1389] +24-11-19 20:43:22 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:43:22 | D | sum error = [ 89.8267, 95.7185, 101.9149, 108.4507, 115.3671] +24-11-19 20:43:22 | D | best error = [ 10.1389, 10.1389, 10.1389, 10.1389, 10.1389] +24-11-19 20:43:22 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:43:22 | D | sum error = [ 122.7733, 130.5411, 138.7529, 147.4739, 156.7406] +24-11-19 20:43:22 | D | best error = [ 10.1389, 10.1389, 10.1389, 10.1389, 10.1389] +24-11-19 20:43:22 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:43:22 | D | sum error = [ 166.4172, 176.7194, 187.5972, 199.0627, 211.1466] +24-11-19 20:43:22 | D | best error = [ 10.1389, 10.1389, 10.1389, 10.1389, 10.1389] +24-11-19 20:43:22 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:43:22 | D | sum error = [ 223.9030, 237.2736, 251.3648, 266.2387, 281.8520] +24-11-19 20:43:22 | D | best error = [ 10.1389, 10.1389, 10.1389, 10.1389, 10.1389] +24-11-19 20:43:22 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:43:22 | D | sum error = [ 298.3448, 315.5387, 333.7006, 352.8060, 372.7866] +24-11-19 20:43:22 | D | best error = [ 10.1389, 10.1389, 10.1389, 10.1389, 10.1389] +24-11-19 20:43:22 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:43:22 | D | sum error = [ 393.7525, 415.7535, 438.8517, 462.9812, 488.2237] +24-11-19 20:43:22 | D | best error = [ 10.1389, 10.1389, 10.1389, 10.1389, 10.1389] +24-11-19 20:43:22 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:43:22 | D | sum error = [ 514.5640, 542.0751, 570.7592, 600.5933, 631.5733] +24-11-19 20:43:22 | D | best error = [ 10.1389, 10.1389, 10.1389, 10.1389, 10.1389] +24-11-19 20:43:22 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:43:22 | D | sum error = [ 663.8430, 697.3303, 732.0177, 767.9268, 805.0734] +24-11-19 20:43:22 | D | best error = [ 10.1389, 10.1389, 10.1389, 10.1389, 10.1389] +24-11-19 20:43:22 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:43:22 | D | sum error = [ 843.4958, 883.1474, 924.1033, 966.3251, 1009.7862] +24-11-19 20:43:22 | D | best error = [ 10.1389, 10.1389, 10.1389, 10.1389, 10.1389] +24-11-19 20:43:22 | D | + error = [10.1389] +24-11-19 20:43:22 | D | - Calibrating model.layers.29.mlp.down_proj.weight +24-11-19 20:43:22 | D | + w: sint8 +24-11-19 20:43:22 | D | + x: None +24-11-19 20:43:22 | D | + y: None +24-11-19 20:43:22 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:43:22 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:43:22 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:43:23 | D | + finished calculating the original outputs, ram usage: 13.3 +24-11-19 20:43:23 | D | - range ratio = [ 1.0000] +24-11-19 20:43:23 | D | sum error = [ 2.0388] +24-11-19 20:43:23 | D | best error = [ 2.0388] +24-11-19 20:43:24 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:43:24 | D | sum error = [ 2.0124, 2.0082, 1.9996, 2.0095, 2.0233] +24-11-19 20:43:24 | D | best error = [ 1.9083, 1.8574, 1.8254, 1.8058, 1.7895] +24-11-19 20:43:24 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:43:24 | D | sum error = [ 2.0591, 2.0998, 2.1534, 2.2333, 2.3213] +24-11-19 20:43:24 | D | best error = [ 1.7783, 1.7701, 1.7643, 1.7604, 1.7577] +24-11-19 20:43:24 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:43:24 | D | sum error = [ 2.4277, 2.5525, 2.6946, 2.8654, 3.0440] +24-11-19 20:43:24 | D | best error = [ 1.7560, 1.7544, 1.7538, 1.7534, 1.7531] +24-11-19 20:43:24 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:43:24 | D | sum error = [ 3.2517, 3.4823, 3.7081, 3.9736, 4.2605] +24-11-19 20:43:24 | D | best error = [ 1.7529, 1.7528, 1.7527, 1.7527, 1.7527] +24-11-19 20:43:24 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:43:24 | D | sum error = [ 4.5617, 4.8815, 5.2256, 5.5963, 5.9921] +24-11-19 20:43:24 | D | best error = [ 1.7527, 1.7527, 1.7527, 1.7527, 1.7527] +24-11-19 20:43:24 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:43:24 | D | sum error = [ 6.4040, 6.8518, 7.3122, 7.8072, 8.3270] +24-11-19 20:43:24 | D | best error = [ 1.7527, 1.7527, 1.7527, 1.7527, 1.7527] +24-11-19 20:43:24 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:43:24 | D | sum error = [ 8.8837, 9.4572, 10.0675, 10.7225, 11.3926] +24-11-19 20:43:24 | D | best error = [ 1.7527, 1.7527, 1.7527, 1.7527, 1.7527] +24-11-19 20:43:24 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:43:24 | D | sum error = [ 12.1229, 12.8846, 13.6726, 14.5141, 15.4012] +24-11-19 20:43:24 | D | best error = [ 1.7527, 1.7527, 1.7527, 1.7527, 1.7527] +24-11-19 20:43:24 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:43:24 | D | sum error = [ 16.3401, 17.3195, 18.3433, 19.4341, 20.5688] +24-11-19 20:43:24 | D | best error = [ 1.7527, 1.7527, 1.7527, 1.7527, 1.7527] +24-11-19 20:43:24 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:43:24 | D | sum error = [ 21.7647, 23.0165, 24.3378, 25.7129, 27.1551] +24-11-19 20:43:24 | D | best error = [ 1.7527, 1.7527, 1.7527, 1.7527, 1.7527] +24-11-19 20:43:24 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:43:24 | D | sum error = [ 28.6789, 30.2747, 31.9423, 33.6874, 35.5040] +24-11-19 20:43:24 | D | best error = [ 1.7527, 1.7527, 1.7527, 1.7527, 1.7527] +24-11-19 20:43:24 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:43:24 | D | sum error = [ 37.4157, 39.3968, 41.4715, 43.6416, 45.9102] +24-11-19 20:43:24 | D | best error = [ 1.7527, 1.7527, 1.7527, 1.7527, 1.7527] +24-11-19 20:43:24 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:43:24 | D | sum error = [ 48.2726, 50.7283, 53.2912, 55.9565, 58.7289] +24-11-19 20:43:24 | D | best error = [ 1.7527, 1.7527, 1.7527, 1.7527, 1.7527] +24-11-19 20:43:24 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:43:24 | D | sum error = [ 61.6050, 64.6038, 67.7143, 70.9407, 74.2809] +24-11-19 20:43:24 | D | best error = [ 1.7527, 1.7527, 1.7527, 1.7527, 1.7527] +24-11-19 20:43:24 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:43:24 | D | sum error = [ 77.7573, 81.3535, 85.0769, 88.9237, 92.8986] +24-11-19 20:43:24 | D | best error = [ 1.7527, 1.7527, 1.7527, 1.7527, 1.7527] +24-11-19 20:43:24 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:43:24 | D | sum error = [ 97.0019, 101.2392, 105.6072, 110.1080, 114.7449] +24-11-19 20:43:24 | D | best error = [ 1.7527, 1.7527, 1.7527, 1.7527, 1.7527] +24-11-19 20:43:24 | D | + error = [1.7527] +24-11-19 20:43:24 | D | - Quantizing model.layers.29.self_attn.q_proj.weight +24-11-19 20:43:25 | D | - Quantizing model.layers.29.self_attn.k_proj.weight +24-11-19 20:43:26 | D | - Quantizing model.layers.29.self_attn.v_proj.weight +24-11-19 20:43:27 | D | - Quantizing model.layers.29.self_attn.o_proj.weight +24-11-19 20:43:28 | D | - Quantizing model.layers.29.mlp.up_proj.weight +24-11-19 20:43:29 | D | - Quantizing model.layers.29.mlp.gate_proj.weight +24-11-19 20:43:31 | D | - Quantizing model.layers.29.mlp.down_proj.weight +24-11-19 20:43:41 | D | - Quantizing layer model.layers.30 +24-11-19 20:43:41 | D | - Calibrating model.layers.30.self_attn.q_proj.weight +24-11-19 20:43:41 | D | + w: sint8 +24-11-19 20:43:41 | D | + x: None +24-11-19 20:43:41 | D | + y: None +24-11-19 20:43:41 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:41 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:43:41 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:43:41 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:43:41 | D | - range ratio = [ 1.0000] +24-11-19 20:43:41 | D | sum error = [ 10.6479] +24-11-19 20:43:41 | D | best error = [ 10.6479] +24-11-19 20:43:53 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:43:53 | D | sum error = [ 10.8656, 10.9704, 10.7769, 10.9550, 11.7689] +24-11-19 20:43:53 | D | best error = [ 10.6479, 10.6479, 10.6479, 10.6479, 10.6479] +24-11-19 20:43:53 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:43:53 | D | sum error = [ 10.9974, 12.2270, 12.0757, 12.7635, 14.0541] +24-11-19 20:43:53 | D | best error = [ 10.6479, 10.6479, 10.6479, 10.6479, 10.6479] +24-11-19 20:43:53 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:43:53 | D | sum error = [ 14.1854, 15.0654, 15.8608, 17.0723, 18.4037] +24-11-19 20:43:53 | D | best error = [ 10.6479, 10.6479, 10.6479, 10.6479, 10.6479] +24-11-19 20:43:53 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:43:53 | D | sum error = [ 19.5493, 21.5527, 23.7100, 25.5201, 27.6385] +24-11-19 20:43:53 | D | best error = [ 10.6479, 10.6479, 10.6479, 10.6479, 10.6479] +24-11-19 20:43:53 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:43:53 | D | sum error = [ 29.8998, 32.5933, 34.8264, 38.2301, 41.7038] +24-11-19 20:43:53 | D | best error = [ 10.6479, 10.6479, 10.6479, 10.6479, 10.6479] +24-11-19 20:43:53 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:43:53 | D | sum error = [ 45.5957, 49.0125, 53.6230, 57.9122, 62.7817] +24-11-19 20:43:53 | D | best error = [ 10.6479, 10.6479, 10.6479, 10.6479, 10.6479] +24-11-19 20:43:53 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:43:53 | D | sum error = [ 67.6251, 73.7868, 78.9372, 85.6176, 92.2074] +24-11-19 20:43:53 | D | best error = [ 10.6479, 10.6479, 10.6479, 10.6479, 10.6479] +24-11-19 20:43:53 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:43:53 | D | sum error = [ 99.5695, 107.2479, 115.3888, 124.5536, 134.0864] +24-11-19 20:43:53 | D | best error = [ 10.6479, 10.6479, 10.6479, 10.6479, 10.6479] +24-11-19 20:43:53 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:43:53 | D | sum error = [ 143.9305, 154.8423, 166.1258, 179.4061, 192.9321] +24-11-19 20:43:53 | D | best error = [ 10.6479, 10.6479, 10.6479, 10.6479, 10.6479] +24-11-19 20:43:53 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:43:53 | D | sum error = [ 206.0714, 221.0014, 237.3552, 254.2862, 273.7509] +24-11-19 20:43:53 | D | best error = [ 10.6479, 10.6479, 10.6479, 10.6479, 10.6479] +24-11-19 20:43:53 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:43:53 | D | sum error = [ 293.0990, 314.8815, 338.2524, 363.0370, 390.6341] +24-11-19 20:43:53 | D | best error = [ 10.6479, 10.6479, 10.6479, 10.6479, 10.6479] +24-11-19 20:43:53 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:43:53 | D | sum error = [ 420.0945, 451.8289, 484.8616, 520.8546, 559.5202] +24-11-19 20:43:53 | D | best error = [ 10.6479, 10.6479, 10.6479, 10.6479, 10.6479] +24-11-19 20:43:53 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:43:53 | D | sum error = [ 601.5156, 645.5839, 693.3754, 744.4838, 798.6020] +24-11-19 20:43:53 | D | best error = [ 10.6479, 10.6479, 10.6479, 10.6479, 10.6479] +24-11-19 20:43:53 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:43:53 | D | sum error = [ 856.2831, 918.9998, 984.7673, 1054.3333, 1130.1137] +24-11-19 20:43:53 | D | best error = [ 10.6479, 10.6479, 10.6479, 10.6479, 10.6479] +24-11-19 20:43:53 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:43:53 | D | sum error = [ 1210.0208, 1294.6029, 1383.3860, 1476.8864, 1574.4340] +24-11-19 20:43:53 | D | best error = [ 10.6479, 10.6479, 10.6479, 10.6479, 10.6479] +24-11-19 20:43:53 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:43:53 | D | sum error = [ 1674.9279, 1778.5917, 1882.9685, 1988.1182, 2093.0896] +24-11-19 20:43:53 | D | best error = [ 10.6479, 10.6479, 10.6479, 10.6479, 10.6479] +24-11-19 20:43:53 | D | + error = [10.6479] +24-11-19 20:43:54 | D | - Calibrating model.layers.30.self_attn.k_proj.weight +24-11-19 20:43:54 | D | + w: sint8 +24-11-19 20:43:54 | D | + x: None +24-11-19 20:43:54 | D | + y: None +24-11-19 20:43:54 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:54 | D | + finished parsing calibration arguments, ram usage: 14.1 +24-11-19 20:43:54 | D | + finished reseting calibrator, ram usage: 14.1 +24-11-19 20:43:54 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:43:54 | D | - range ratio = [ 1.0000] +24-11-19 20:43:54 | D | sum error = [ 11.9190] +24-11-19 20:43:54 | D | best error = [ 11.9190] +24-11-19 20:44:10 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:44:10 | D | sum error = [ 9.9972, 10.8027, 10.1234, 11.3561, 11.0477] +24-11-19 20:44:10 | D | best error = [ 9.9972, 9.9972, 9.9972, 9.9972, 9.9972] +24-11-19 20:44:10 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:44:10 | D | sum error = [ 11.2456, 13.5339, 12.0139, 12.2427, 13.7828] +24-11-19 20:44:10 | D | best error = [ 9.9972, 9.9972, 9.9972, 9.9972, 9.9972] +24-11-19 20:44:10 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:44:10 | D | sum error = [ 14.3378, 15.1655, 16.5213, 17.2177, 18.4071] +24-11-19 20:44:10 | D | best error = [ 9.9972, 9.9972, 9.9972, 9.9972, 9.9972] +24-11-19 20:44:10 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:44:10 | D | sum error = [ 20.9874, 21.0718, 22.9491, 23.8129, 25.8440] +24-11-19 20:44:10 | D | best error = [ 9.9972, 9.9972, 9.9972, 9.9972, 9.9972] +24-11-19 20:44:10 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:44:10 | D | sum error = [ 28.4278, 30.5325, 31.4599, 34.3254, 36.9436] +24-11-19 20:44:10 | D | best error = [ 9.9972, 9.9972, 9.9972, 9.9972, 9.9972] +24-11-19 20:44:10 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:44:10 | D | sum error = [ 39.2208, 42.0159, 45.3166, 50.9898, 53.4910] +24-11-19 20:44:10 | D | best error = [ 9.9972, 9.9972, 9.9972, 9.9972, 9.9972] +24-11-19 20:44:10 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:44:10 | D | sum error = [ 58.6057, 62.4081, 68.3974, 72.7274, 78.1030] +24-11-19 20:44:10 | D | best error = [ 9.9972, 9.9972, 9.9972, 9.9972, 9.9972] +24-11-19 20:44:10 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:44:10 | D | sum error = [ 83.9790, 89.0374, 97.4908, 104.7547, 112.7624] +24-11-19 20:44:10 | D | best error = [ 9.9972, 9.9972, 9.9972, 9.9972, 9.9972] +24-11-19 20:44:10 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:44:10 | D | sum error = [ 121.4082, 132.6206, 140.9942, 153.0305, 163.8920] +24-11-19 20:44:10 | D | best error = [ 9.9972, 9.9972, 9.9972, 9.9972, 9.9972] +24-11-19 20:44:10 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:44:10 | D | sum error = [ 179.2373, 192.2965, 206.5805, 223.0971, 241.1302] +24-11-19 20:44:10 | D | best error = [ 9.9972, 9.9972, 9.9972, 9.9972, 9.9972] +24-11-19 20:44:10 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:44:10 | D | sum error = [ 259.2286, 279.6343, 301.4267, 322.5983, 347.8951] +24-11-19 20:44:10 | D | best error = [ 9.9972, 9.9972, 9.9972, 9.9972, 9.9972] +24-11-19 20:44:10 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:44:10 | D | sum error = [ 375.3677, 404.6190, 435.8548, 469.3832, 505.5778] +24-11-19 20:44:10 | D | best error = [ 9.9972, 9.9972, 9.9972, 9.9972, 9.9972] +24-11-19 20:44:10 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:44:10 | D | sum error = [ 544.1276, 583.5837, 626.7264, 670.2959, 717.6614] +24-11-19 20:44:10 | D | best error = [ 9.9972, 9.9972, 9.9972, 9.9972, 9.9972] +24-11-19 20:44:10 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:44:10 | D | sum error = [ 768.5551, 822.2017, 880.2709, 943.7384, 1009.6450] +24-11-19 20:44:10 | D | best error = [ 9.9972, 9.9972, 9.9972, 9.9972, 9.9972] +24-11-19 20:44:10 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:44:10 | D | sum error = [ 1081.0059, 1153.9415, 1237.3360, 1325.2748, 1415.9616] +24-11-19 20:44:10 | D | best error = [ 9.9972, 9.9972, 9.9972, 9.9972, 9.9972] +24-11-19 20:44:10 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:44:10 | D | sum error = [ 1510.5237, 1615.1052, 1718.8064, 1830.3159, 1940.2287] +24-11-19 20:44:10 | D | best error = [ 9.9972, 9.9972, 9.9972, 9.9972, 9.9972] +24-11-19 20:44:10 | D | + error = [9.9972] +24-11-19 20:44:10 | D | - Calibrating model.layers.30.self_attn.v_proj.weight +24-11-19 20:44:10 | D | + w: sint8 +24-11-19 20:44:10 | D | + x: None +24-11-19 20:44:10 | D | + y: None +24-11-19 20:44:10 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:44:10 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:44:10 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:44:11 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:44:11 | D | - range ratio = [ 1.0000] +24-11-19 20:44:11 | D | sum error = [ 3.5822] +24-11-19 20:44:11 | D | best error = [ 3.5822] +24-11-19 20:44:11 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:44:11 | D | sum error = [ 3.5419, 3.5692, 3.5482, 3.5819, 3.7177] +24-11-19 20:44:11 | D | best error = [ 3.1900, 3.0590, 2.9837, 2.9485, 2.9287] +24-11-19 20:44:11 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:44:11 | D | sum error = [ 3.8240, 3.9137, 4.0930, 4.2653, 4.4554] +24-11-19 20:44:11 | D | best error = [ 2.9186, 2.9137, 2.9117, 2.9112, 2.9108] +24-11-19 20:44:11 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:44:11 | D | sum error = [ 4.7646, 5.0932, 5.3034, 5.7911, 6.1626] +24-11-19 20:44:11 | D | best error = [ 2.9108, 2.9108, 2.9108, 2.9108, 2.9108] +24-11-19 20:44:11 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:44:11 | D | sum error = [ 6.5851, 7.0687, 7.6120, 8.1763, 8.7577] +24-11-19 20:44:11 | D | best error = [ 2.9108, 2.9108, 2.9108, 2.9108, 2.9108] +24-11-19 20:44:11 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:44:11 | D | sum error = [ 9.4520, 10.0879, 10.7926, 11.5206, 12.3034] +24-11-19 20:44:11 | D | best error = [ 2.9108, 2.9108, 2.9108, 2.9108, 2.9108] +24-11-19 20:44:11 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:44:11 | D | sum error = [ 13.1815, 14.0473, 14.9999, 15.9813, 17.0096] +24-11-19 20:44:11 | D | best error = [ 2.9108, 2.9108, 2.9108, 2.9108, 2.9108] +24-11-19 20:44:11 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:44:11 | D | sum error = [ 18.0623, 19.1979, 20.3929, 21.5913, 22.9230] +24-11-19 20:44:11 | D | best error = [ 2.9108, 2.9108, 2.9108, 2.9108, 2.9108] +24-11-19 20:44:11 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:44:11 | D | sum error = [ 24.2762, 25.6696, 27.1604, 28.6839, 30.3046] +24-11-19 20:44:11 | D | best error = [ 2.9108, 2.9108, 2.9108, 2.9108, 2.9108] +24-11-19 20:44:11 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:44:11 | D | sum error = [ 32.0431, 33.8557, 35.7535, 37.6777, 39.7530] +24-11-19 20:44:11 | D | best error = [ 2.9108, 2.9108, 2.9108, 2.9108, 2.9108] +24-11-19 20:44:11 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:44:11 | D | sum error = [ 41.9461, 44.1772, 46.5497, 48.9892, 51.5437] +24-11-19 20:44:11 | D | best error = [ 2.9108, 2.9108, 2.9108, 2.9108, 2.9108] +24-11-19 20:44:11 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:44:11 | D | sum error = [ 54.1453, 56.9145, 59.8198, 62.8045, 65.8830] +24-11-19 20:44:11 | D | best error = [ 2.9108, 2.9108, 2.9108, 2.9108, 2.9108] +24-11-19 20:44:11 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:44:11 | D | sum error = [ 69.0575, 72.3470, 75.7308, 79.2634, 82.8953] +24-11-19 20:44:11 | D | best error = [ 2.9108, 2.9108, 2.9108, 2.9108, 2.9108] +24-11-19 20:44:11 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:44:11 | D | sum error = [ 86.6648, 90.5489, 94.5300, 98.6532, 102.8893] +24-11-19 20:44:11 | D | best error = [ 2.9108, 2.9108, 2.9108, 2.9108, 2.9108] +24-11-19 20:44:11 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:44:11 | D | sum error = [ 107.2624, 111.7822, 116.4398, 121.2630, 126.2130] +24-11-19 20:44:11 | D | best error = [ 2.9108, 2.9108, 2.9108, 2.9108, 2.9108] +24-11-19 20:44:11 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:44:11 | D | sum error = [ 131.2789, 136.5040, 141.8929, 147.4365, 153.1154] +24-11-19 20:44:11 | D | best error = [ 2.9108, 2.9108, 2.9108, 2.9108, 2.9108] +24-11-19 20:44:11 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:44:11 | D | sum error = [ 158.9540, 164.9297, 171.0567, 177.3120, 183.7097] +24-11-19 20:44:11 | D | best error = [ 2.9108, 2.9108, 2.9108, 2.9108, 2.9108] +24-11-19 20:44:11 | D | + error = [2.9108] +24-11-19 20:44:11 | D | - Calibrating model.layers.30.self_attn.o_proj.weight +24-11-19 20:44:11 | D | + w: sint8 +24-11-19 20:44:11 | D | + x: None +24-11-19 20:44:11 | D | + y: None +24-11-19 20:44:11 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:44:11 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:44:11 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:44:11 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:44:11 | D | - range ratio = [ 1.0000] +24-11-19 20:44:11 | D | sum error = [ 1.0639] +24-11-19 20:44:11 | D | best error = [ 1.0639] +24-11-19 20:44:11 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:44:11 | D | sum error = [ 1.0498, 1.0495, 1.0488, 1.0599, 1.0737] +24-11-19 20:44:11 | D | best error = [ 0.9748, 0.9388, 0.9175, 0.9044, 0.8956] +24-11-19 20:44:11 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:44:11 | D | sum error = [ 1.0876, 1.1213, 1.1578, 1.2032, 1.2538] +24-11-19 20:44:11 | D | best error = [ 0.8893, 0.8850, 0.8825, 0.8810, 0.8798] +24-11-19 20:44:11 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:44:11 | D | sum error = [ 1.3113, 1.3808, 1.4521, 1.5392, 1.6379] +24-11-19 20:44:11 | D | best error = [ 0.8788, 0.8783, 0.8779, 0.8776, 0.8774] +24-11-19 20:44:11 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:44:11 | D | sum error = [ 1.7340, 1.8442, 1.9599, 2.0889, 2.2234] +24-11-19 20:44:11 | D | best error = [ 0.8773, 0.8773, 0.8773, 0.8772, 0.8772] +24-11-19 20:44:11 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:44:11 | D | sum error = [ 2.3707, 2.5217, 2.6836, 2.8593, 3.0453] +24-11-19 20:44:11 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 20:44:11 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:44:11 | D | sum error = [ 3.2310, 3.4361, 3.6549, 3.8866, 4.1236] +24-11-19 20:44:11 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 20:44:11 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:44:11 | D | sum error = [ 4.3709, 4.6418, 4.9190, 5.2169, 5.5366] +24-11-19 20:44:11 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 20:44:11 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:44:11 | D | sum error = [ 5.8665, 6.2102, 6.5714, 6.9595, 7.3610] +24-11-19 20:44:11 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 20:44:11 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:44:11 | D | sum error = [ 7.7911, 8.2380, 8.7063, 9.2033, 9.7241] +24-11-19 20:44:11 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 20:44:11 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:44:11 | D | sum error = [ 10.2752, 10.8489, 11.4561, 12.0909, 12.7595] +24-11-19 20:44:11 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 20:44:11 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:44:11 | D | sum error = [ 13.4648, 14.2033, 14.9707, 15.7838, 16.6312] +24-11-19 20:44:11 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 20:44:11 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:44:11 | D | sum error = [ 17.5192, 18.4504, 19.4279, 20.4523, 21.5258] +24-11-19 20:44:11 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 20:44:11 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:44:11 | D | sum error = [ 22.6436, 23.8170, 25.0424, 26.3208, 27.6621] +24-11-19 20:44:11 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 20:44:11 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:44:11 | D | sum error = [ 29.0649, 30.5341, 32.0671, 33.6687, 35.3377] +24-11-19 20:44:11 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 20:44:11 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:44:11 | D | sum error = [ 37.0779, 38.8909, 40.7819, 42.7472, 44.7894] +24-11-19 20:44:11 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 20:44:11 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:44:11 | D | sum error = [ 46.9097, 49.1116, 51.3983, 53.7667, 56.2239] +24-11-19 20:44:11 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 20:44:11 | D | + error = [0.8772] +24-11-19 20:44:12 | D | - Calibrating model.layers.30.mlp.up_proj.weight +24-11-19 20:44:12 | D | + w: sint8 +24-11-19 20:44:12 | D | + x: None +24-11-19 20:44:12 | D | + y: None +24-11-19 20:44:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:44:12 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:44:12 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:44:12 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:44:12 | D | - range ratio = [ 1.0000] +24-11-19 20:44:12 | D | sum error = [ 0.5652] +24-11-19 20:44:12 | D | best error = [ 0.5652] +24-11-19 20:44:13 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:44:13 | D | sum error = [ 0.5605, 0.5590, 0.5621, 0.5680, 0.5792] +24-11-19 20:44:13 | D | best error = [ 0.4964, 0.4726, 0.4613, 0.4551, 0.4516] +24-11-19 20:44:13 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:44:13 | D | sum error = [ 0.5957, 0.6140, 0.6391, 0.6685, 0.7060] +24-11-19 20:44:13 | D | best error = [ 0.4499, 0.4489, 0.4486, 0.4485, 0.4484] +24-11-19 20:44:13 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:44:13 | D | sum error = [ 0.7481, 0.7932, 0.8443, 0.9007, 0.9635] +24-11-19 20:44:13 | D | best error = [ 0.4484, 0.4484, 0.4484, 0.4484, 0.4484] +24-11-19 20:44:13 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:44:13 | D | sum error = [ 1.0340, 1.1043, 1.1863, 1.2713, 1.3648] +24-11-19 20:44:13 | D | best error = [ 0.4484, 0.4484, 0.4484, 0.4484, 0.4484] +24-11-19 20:44:13 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:44:13 | D | sum error = [ 1.4594, 1.5628, 1.6752, 1.7937, 1.9183] +24-11-19 20:44:13 | D | best error = [ 0.4484, 0.4484, 0.4484, 0.4484, 0.4484] +24-11-19 20:44:13 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:44:13 | D | sum error = [ 2.0521, 2.1917, 2.3405, 2.4951, 2.6661] +24-11-19 20:44:13 | D | best error = [ 0.4484, 0.4484, 0.4484, 0.4484, 0.4484] +24-11-19 20:44:13 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:44:13 | D | sum error = [ 2.8405, 3.0295, 3.2251, 3.4337, 3.6512] +24-11-19 20:44:13 | D | best error = [ 0.4484, 0.4484, 0.4484, 0.4484, 0.4484] +24-11-19 20:44:13 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:44:13 | D | sum error = [ 3.8817, 4.1256, 4.3797, 4.6456, 4.9265] +24-11-19 20:44:13 | D | best error = [ 0.4484, 0.4484, 0.4484, 0.4484, 0.4484] +24-11-19 20:44:13 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:44:13 | D | sum error = [ 5.2222, 5.5301, 5.8575, 6.2008, 6.5606] +24-11-19 20:44:13 | D | best error = [ 0.4484, 0.4484, 0.4484, 0.4484, 0.4484] +24-11-19 20:44:13 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:44:13 | D | sum error = [ 6.9398, 7.3359, 7.7541, 8.1914, 8.6518] +24-11-19 20:44:13 | D | best error = [ 0.4484, 0.4484, 0.4484, 0.4484, 0.4484] +24-11-19 20:44:13 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:44:13 | D | sum error = [ 9.1312, 9.6314, 10.1579, 10.7049, 11.2773] +24-11-19 20:44:13 | D | best error = [ 0.4484, 0.4484, 0.4484, 0.4484, 0.4484] +24-11-19 20:44:13 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:44:13 | D | sum error = [ 11.8764, 12.4960, 13.1460, 13.8297, 14.5345] +24-11-19 20:44:13 | D | best error = [ 0.4484, 0.4484, 0.4484, 0.4484, 0.4484] +24-11-19 20:44:13 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:44:13 | D | sum error = [ 15.2772, 16.0488, 16.8550, 17.6881, 18.5505] +24-11-19 20:44:13 | D | best error = [ 0.4484, 0.4484, 0.4484, 0.4484, 0.4484] +24-11-19 20:44:13 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:44:13 | D | sum error = [ 19.4509, 20.3910, 21.3703, 22.3736, 23.4180] +24-11-19 20:44:13 | D | best error = [ 0.4484, 0.4484, 0.4484, 0.4484, 0.4484] +24-11-19 20:44:13 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:44:13 | D | sum error = [ 24.5015, 25.6217, 26.7790, 27.9795, 29.2211] +24-11-19 20:44:13 | D | best error = [ 0.4484, 0.4484, 0.4484, 0.4484, 0.4484] +24-11-19 20:44:13 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:44:13 | D | sum error = [ 30.4852, 31.8190, 33.1710, 34.5666, 36.0199] +24-11-19 20:44:13 | D | best error = [ 0.4484, 0.4484, 0.4484, 0.4484, 0.4484] +24-11-19 20:44:13 | D | + error = [0.4484] +24-11-19 20:44:13 | D | - Calibrating model.layers.30.mlp.gate_proj.weight +24-11-19 20:44:13 | D | + w: sint8 +24-11-19 20:44:13 | D | + x: None +24-11-19 20:44:13 | D | + y: None +24-11-19 20:44:13 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:44:13 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:44:13 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:44:13 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:44:13 | D | - range ratio = [ 1.0000] +24-11-19 20:44:13 | D | sum error = [ 13.2771] +24-11-19 20:44:13 | D | best error = [ 13.2771] +24-11-19 20:44:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:44:15 | D | sum error = [ 13.2002, 13.1613, 13.2532, 13.3749, 13.5833] +24-11-19 20:44:15 | D | best error = [ 11.6504, 11.1155, 10.8477, 10.6975, 10.6175] +24-11-19 20:44:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:44:15 | D | sum error = [ 14.0231, 14.4812, 15.0505, 15.7271, 16.6078] +24-11-19 20:44:15 | D | best error = [ 10.5763, 10.5561, 10.5482, 10.5451, 10.5435] +24-11-19 20:44:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:44:15 | D | sum error = [ 17.5899, 18.6769, 19.9724, 21.3861, 22.7318] +24-11-19 20:44:15 | D | best error = [ 10.5434, 10.5433, 10.5432, 10.5432, 10.5432] +24-11-19 20:44:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:44:15 | D | sum error = [ 24.4171, 26.1993, 28.2120, 30.2679, 32.4594] +24-11-19 20:44:15 | D | best error = [ 10.5432, 10.5432, 10.5432, 10.5432, 10.5432] +24-11-19 20:44:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:44:15 | D | sum error = [ 34.9233, 37.5047, 40.1972, 43.1810, 46.2329] +24-11-19 20:44:15 | D | best error = [ 10.5432, 10.5432, 10.5432, 10.5432, 10.5432] +24-11-19 20:44:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:44:15 | D | sum error = [ 49.6225, 53.2027, 56.9151, 60.8906, 65.2036] +24-11-19 20:44:15 | D | best error = [ 10.5432, 10.5432, 10.5432, 10.5432, 10.5432] +24-11-19 20:44:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:44:15 | D | sum error = [ 69.7361, 74.4378, 79.6090, 84.9970, 90.7264] +24-11-19 20:44:15 | D | best error = [ 10.5432, 10.5432, 10.5432, 10.5432, 10.5432] +24-11-19 20:44:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:44:15 | D | sum error = [ 96.8716, 103.3788, 110.2340, 117.5400, 125.3658] +24-11-19 20:44:15 | D | best error = [ 10.5432, 10.5432, 10.5432, 10.5432, 10.5432] +24-11-19 20:44:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:44:15 | D | sum error = [ 133.5793, 142.3254, 151.5875, 161.4238, 171.8434] +24-11-19 20:44:15 | D | best error = [ 10.5432, 10.5432, 10.5432, 10.5432, 10.5432] +24-11-19 20:44:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:44:15 | D | sum error = [ 182.9217, 194.6339, 207.0429, 220.1499, 234.0221] +24-11-19 20:44:15 | D | best error = [ 10.5432, 10.5432, 10.5432, 10.5432, 10.5432] +24-11-19 20:44:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:44:15 | D | sum error = [ 248.7039, 264.1659, 280.5121, 297.7675, 315.9384] +24-11-19 20:44:15 | D | best error = [ 10.5432, 10.5432, 10.5432, 10.5432, 10.5432] +24-11-19 20:44:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:44:15 | D | sum error = [ 335.0899, 355.2694, 376.5504, 398.9240, 422.3862] +24-11-19 20:44:15 | D | best error = [ 10.5432, 10.5432, 10.5432, 10.5432, 10.5432] +24-11-19 20:44:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:44:15 | D | sum error = [ 447.0914, 473.0292, 500.2265, 528.7148, 558.4178] +24-11-19 20:44:15 | D | best error = [ 10.5432, 10.5432, 10.5432, 10.5432, 10.5432] +24-11-19 20:44:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:44:15 | D | sum error = [ 589.5680, 622.1098, 656.1087, 691.5922, 728.5327] +24-11-19 20:44:15 | D | best error = [ 10.5432, 10.5432, 10.5432, 10.5432, 10.5432] +24-11-19 20:44:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:44:15 | D | sum error = [ 766.9540, 806.8868, 848.4861, 891.5336, 936.1612] +24-11-19 20:44:15 | D | best error = [ 10.5432, 10.5432, 10.5432, 10.5432, 10.5432] +24-11-19 20:44:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:44:15 | D | sum error = [ 982.3358, 1030.0652, 1079.3587, 1130.1009, 1182.4520] +24-11-19 20:44:15 | D | best error = [ 10.5432, 10.5432, 10.5432, 10.5432, 10.5432] +24-11-19 20:44:15 | D | + error = [10.5432] +24-11-19 20:44:15 | D | - Calibrating model.layers.30.mlp.down_proj.weight +24-11-19 20:44:15 | D | + w: sint8 +24-11-19 20:44:15 | D | + x: None +24-11-19 20:44:15 | D | + y: None +24-11-19 20:44:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:44:15 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:44:15 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:44:15 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:44:15 | D | - range ratio = [ 1.0000] +24-11-19 20:44:15 | D | sum error = [ 2.9925] +24-11-19 20:44:15 | D | best error = [ 2.9925] +24-11-19 20:44:16 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:44:16 | D | sum error = [ 2.9879, 2.9860, 3.0303, 3.0843, 3.1911] +24-11-19 20:44:16 | D | best error = [ 2.7830, 2.6933, 2.6399, 2.6011, 2.5741] +24-11-19 20:44:16 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:44:16 | D | sum error = [ 3.3280, 3.5020, 3.7090, 3.9246, 4.2133] +24-11-19 20:44:16 | D | best error = [ 2.5530, 2.5380, 2.5273, 2.5199, 2.5139] +24-11-19 20:44:16 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:44:16 | D | sum error = [ 4.5203, 4.8418, 5.2005, 5.5936, 6.0108] +24-11-19 20:44:16 | D | best error = [ 2.5100, 2.5077, 2.5057, 2.5039, 2.5033] +24-11-19 20:44:16 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:44:16 | D | sum error = [ 6.4802, 6.9480, 7.4503, 7.9886, 8.5447] +24-11-19 20:44:16 | D | best error = [ 2.5029, 2.5024, 2.5022, 2.5019, 2.5018] +24-11-19 20:44:16 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:44:16 | D | sum error = [ 9.1308, 9.7682, 10.4316, 11.1339, 11.8658] +24-11-19 20:44:16 | D | best error = [ 2.5018, 2.5018, 2.5017, 2.5017, 2.5017] +24-11-19 20:44:16 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:44:16 | D | sum error = [ 12.6372, 13.4612, 14.3089, 15.2050, 16.1440] +24-11-19 20:44:16 | D | best error = [ 2.5017, 2.5017, 2.5017, 2.5017, 2.5017] +24-11-19 20:44:16 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:44:16 | D | sum error = [ 17.1279, 18.1736, 19.2673, 20.4218, 21.6253] +24-11-19 20:44:16 | D | best error = [ 2.5017, 2.5017, 2.5017, 2.5017, 2.5017] +24-11-19 20:44:16 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:44:16 | D | sum error = [ 22.8920, 24.2276, 25.6187, 27.0752, 28.6089] +24-11-19 20:44:16 | D | best error = [ 2.5017, 2.5017, 2.5017, 2.5017, 2.5017] +24-11-19 20:44:16 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:44:16 | D | sum error = [ 30.2307, 31.9229, 33.7037, 35.5604, 37.5117] +24-11-19 20:44:16 | D | best error = [ 2.5017, 2.5017, 2.5017, 2.5017, 2.5017] +24-11-19 20:44:16 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:44:16 | D | sum error = [ 39.5594, 41.7121, 43.9730, 46.3426, 48.8235] +24-11-19 20:44:16 | D | best error = [ 2.5017, 2.5017, 2.5017, 2.5017, 2.5017] +24-11-19 20:44:16 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:44:16 | D | sum error = [ 51.4417, 54.1841, 57.0631, 60.0757, 63.2372] +24-11-19 20:44:16 | D | best error = [ 2.5017, 2.5017, 2.5017, 2.5017, 2.5017] +24-11-19 20:44:16 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:44:16 | D | sum error = [ 66.5556, 70.0248, 73.6713, 77.4705, 81.4589] +24-11-19 20:44:16 | D | best error = [ 2.5017, 2.5017, 2.5017, 2.5017, 2.5017] +24-11-19 20:44:16 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:44:16 | D | sum error = [ 85.6255, 89.9722, 94.5183, 99.2752, 104.2270] +24-11-19 20:44:16 | D | best error = [ 2.5017, 2.5017, 2.5017, 2.5017, 2.5017] +24-11-19 20:44:16 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:44:16 | D | sum error = [ 109.3978, 114.7905, 120.4054, 126.2529, 132.3542] +24-11-19 20:44:16 | D | best error = [ 2.5017, 2.5017, 2.5017, 2.5017, 2.5017] +24-11-19 20:44:16 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:44:16 | D | sum error = [ 138.6905, 145.2752, 152.1219, 159.2234, 166.5953] +24-11-19 20:44:16 | D | best error = [ 2.5017, 2.5017, 2.5017, 2.5017, 2.5017] +24-11-19 20:44:16 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:44:16 | D | sum error = [ 174.2257, 182.1172, 190.2755, 198.7056, 207.4098] +24-11-19 20:44:16 | D | best error = [ 2.5017, 2.5017, 2.5017, 2.5017, 2.5017] +24-11-19 20:44:16 | D | + error = [2.5017] +24-11-19 20:44:16 | D | - Quantizing model.layers.30.self_attn.q_proj.weight +24-11-19 20:44:17 | D | - Quantizing model.layers.30.self_attn.k_proj.weight +24-11-19 20:44:18 | D | - Quantizing model.layers.30.self_attn.v_proj.weight +24-11-19 20:44:19 | D | - Quantizing model.layers.30.self_attn.o_proj.weight +24-11-19 20:44:20 | D | - Quantizing model.layers.30.mlp.up_proj.weight +24-11-19 20:44:21 | D | - Quantizing model.layers.30.mlp.gate_proj.weight +24-11-19 20:44:22 | D | - Quantizing model.layers.30.mlp.down_proj.weight +24-11-19 20:44:32 | D | - Quantizing layer model.layers.31 +24-11-19 20:44:32 | D | - Calibrating model.layers.31.self_attn.q_proj.weight +24-11-19 20:44:32 | D | + w: sint8 +24-11-19 20:44:32 | D | + x: None +24-11-19 20:44:32 | D | + y: None +24-11-19 20:44:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:32 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:44:32 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:44:32 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:44:33 | D | - range ratio = [ 1.0000] +24-11-19 20:44:33 | D | sum error = [ 8.8568] +24-11-19 20:44:33 | D | best error = [ 8.8568] +24-11-19 20:44:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:44:47 | D | sum error = [ 8.7270, 8.8324, 9.1349, 8.9112, 9.1874] +24-11-19 20:44:47 | D | best error = [ 8.7270, 8.7270, 8.7270, 8.7270, 8.7270] +24-11-19 20:44:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:44:47 | D | sum error = [ 9.5289, 9.8405, 10.1875, 10.5506, 11.6334] +24-11-19 20:44:47 | D | best error = [ 8.7270, 8.7270, 8.7270, 8.7270, 8.7270] +24-11-19 20:44:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:44:47 | D | sum error = [ 12.0431, 12.7207, 14.2956, 15.7481, 17.3678] +24-11-19 20:44:47 | D | best error = [ 8.7270, 8.7270, 8.7270, 8.7270, 8.7270] +24-11-19 20:44:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:44:47 | D | sum error = [ 17.6276, 18.7539, 20.5750, 22.5205, 24.2042] +24-11-19 20:44:47 | D | best error = [ 8.7270, 8.7270, 8.7270, 8.7270, 8.7270] +24-11-19 20:44:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:44:47 | D | sum error = [ 27.1300, 28.7036, 31.5943, 33.3268, 36.5213] +24-11-19 20:44:47 | D | best error = [ 8.7270, 8.7270, 8.7270, 8.7270, 8.7270] +24-11-19 20:44:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:44:47 | D | sum error = [ 39.3866, 42.3199, 45.8429, 50.0887, 53.2525] +24-11-19 20:44:47 | D | best error = [ 8.7270, 8.7270, 8.7270, 8.7270, 8.7270] +24-11-19 20:44:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:44:47 | D | sum error = [ 57.4073, 62.5536, 67.5565, 72.5964, 79.2005] +24-11-19 20:44:47 | D | best error = [ 8.7270, 8.7270, 8.7270, 8.7270, 8.7270] +24-11-19 20:44:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:44:47 | D | sum error = [ 85.4574, 92.3437, 99.2121, 107.3199, 115.6505] +24-11-19 20:44:47 | D | best error = [ 8.7270, 8.7270, 8.7270, 8.7270, 8.7270] +24-11-19 20:44:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:44:47 | D | sum error = [ 125.1123, 135.1302, 145.1459, 156.4490, 168.4775] +24-11-19 20:44:47 | D | best error = [ 8.7270, 8.7270, 8.7270, 8.7270, 8.7270] +24-11-19 20:44:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:44:47 | D | sum error = [ 181.2611, 194.9627, 210.0835, 226.3322, 244.0647] +24-11-19 20:44:47 | D | best error = [ 8.7270, 8.7270, 8.7270, 8.7270, 8.7270] +24-11-19 20:44:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:44:47 | D | sum error = [ 262.6797, 282.6627, 305.6553, 329.4250, 354.8171] +24-11-19 20:44:47 | D | best error = [ 8.7270, 8.7270, 8.7270, 8.7270, 8.7270] +24-11-19 20:44:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:44:47 | D | sum error = [ 382.8455, 412.8293, 444.9869, 480.5911, 518.4669] +24-11-19 20:44:47 | D | best error = [ 8.7270, 8.7270, 8.7270, 8.7270, 8.7270] +24-11-19 20:44:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:44:47 | D | sum error = [ 560.4917, 606.2941, 656.3986, 710.9684, 769.6353] +24-11-19 20:44:47 | D | best error = [ 8.7270, 8.7270, 8.7270, 8.7270, 8.7270] +24-11-19 20:44:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:44:47 | D | sum error = [ 834.2800, 904.3209, 980.3000, 1064.0399, 1154.3124] +24-11-19 20:44:47 | D | best error = [ 8.7270, 8.7270, 8.7270, 8.7270, 8.7270] +24-11-19 20:44:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:44:47 | D | sum error = [ 1253.6517, 1360.4951, 1476.5129, 1600.9635, 1735.0006] +24-11-19 20:44:47 | D | best error = [ 8.7270, 8.7270, 8.7270, 8.7270, 8.7270] +24-11-19 20:44:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:44:47 | D | sum error = [ 1878.1050, 2029.3981, 2188.4894, 2353.5764, 2524.0854] +24-11-19 20:44:47 | D | best error = [ 8.7270, 8.7270, 8.7270, 8.7270, 8.7270] +24-11-19 20:44:47 | D | + error = [8.7270] +24-11-19 20:44:47 | D | - Calibrating model.layers.31.self_attn.k_proj.weight +24-11-19 20:44:47 | D | + w: sint8 +24-11-19 20:44:47 | D | + x: None +24-11-19 20:44:47 | D | + y: None +24-11-19 20:44:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:44:47 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:44:47 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:44:47 | D | + finished calculating the original outputs, ram usage: 13.4 +24-11-19 20:44:47 | D | - range ratio = [ 1.0000] +24-11-19 20:44:47 | D | sum error = [ 9.5956] +24-11-19 20:44:47 | D | best error = [ 9.5956] +24-11-19 20:44:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:44:59 | D | sum error = [ 12.6613, 9.7945, 11.5547, 13.9776, 12.5174] +24-11-19 20:44:59 | D | best error = [ 9.5956, 9.5956, 9.5956, 9.5956, 9.5956] +24-11-19 20:44:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:44:59 | D | sum error = [ 11.8329, 10.5035, 11.3439, 12.5457, 12.5564] +24-11-19 20:44:59 | D | best error = [ 9.5956, 9.5956, 9.5956, 9.5956, 9.5956] +24-11-19 20:44:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:44:59 | D | sum error = [ 14.5278, 14.9245, 16.8251, 16.5958, 19.1541] +24-11-19 20:44:59 | D | best error = [ 9.5956, 9.5956, 9.5956, 9.5956, 9.5956] +24-11-19 20:44:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:44:59 | D | sum error = [ 19.6638, 20.6541, 23.7845, 23.6378, 25.5088] +24-11-19 20:44:59 | D | best error = [ 9.5956, 9.5956, 9.5956, 9.5956, 9.5956] +24-11-19 20:44:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:44:59 | D | sum error = [ 27.0041, 28.6251, 30.8567, 32.9740, 35.0547] +24-11-19 20:44:59 | D | best error = [ 9.5956, 9.5956, 9.5956, 9.5956, 9.5956] +24-11-19 20:44:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:44:59 | D | sum error = [ 38.2606, 40.1250, 43.3165, 46.7870, 50.7801] +24-11-19 20:44:59 | D | best error = [ 9.5956, 9.5956, 9.5956, 9.5956, 9.5956] +24-11-19 20:44:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:44:59 | D | sum error = [ 55.2167, 58.8171, 64.5615, 70.9133, 76.0191] +24-11-19 20:44:59 | D | best error = [ 9.5956, 9.5956, 9.5956, 9.5956, 9.5956] +24-11-19 20:44:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:44:59 | D | sum error = [ 82.5556, 90.5485, 98.6818, 107.8913, 118.1566] +24-11-19 20:44:59 | D | best error = [ 9.5956, 9.5956, 9.5956, 9.5956, 9.5956] +24-11-19 20:44:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:44:59 | D | sum error = [ 125.7089, 138.3800, 147.7487, 162.2810, 175.6032] +24-11-19 20:44:59 | D | best error = [ 9.5956, 9.5956, 9.5956, 9.5956, 9.5956] +24-11-19 20:44:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:44:59 | D | sum error = [ 190.9745, 207.1061, 224.5840, 242.4898, 263.5906] +24-11-19 20:44:59 | D | best error = [ 9.5956, 9.5956, 9.5956, 9.5956, 9.5956] +24-11-19 20:44:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:44:59 | D | sum error = [ 284.8739, 309.3394, 335.7376, 362.0084, 391.2877] +24-11-19 20:44:59 | D | best error = [ 9.5956, 9.5956, 9.5956, 9.5956, 9.5956] +24-11-19 20:44:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:44:59 | D | sum error = [ 424.8096, 458.9820, 494.3376, 533.0446, 575.3544] +24-11-19 20:44:59 | D | best error = [ 9.5956, 9.5956, 9.5956, 9.5956, 9.5956] +24-11-19 20:44:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:44:59 | D | sum error = [ 618.4353, 667.5687, 719.9340, 776.7199, 838.1285] +24-11-19 20:44:59 | D | best error = [ 9.5956, 9.5956, 9.5956, 9.5956, 9.5956] +24-11-19 20:44:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:44:59 | D | sum error = [ 906.1286, 980.9826, 1061.3501, 1150.7444, 1246.3393] +24-11-19 20:44:59 | D | best error = [ 9.5956, 9.5956, 9.5956, 9.5956, 9.5956] +24-11-19 20:44:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:44:59 | D | sum error = [ 1351.7000, 1462.1634, 1578.2457, 1707.3627, 1847.6195] +24-11-19 20:44:59 | D | best error = [ 9.5956, 9.5956, 9.5956, 9.5956, 9.5956] +24-11-19 20:44:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:44:59 | D | sum error = [ 1991.4994, 2141.9767, 2299.7143, 2461.4532, 2625.2128] +24-11-19 20:44:59 | D | best error = [ 9.5956, 9.5956, 9.5956, 9.5956, 9.5956] +24-11-19 20:44:59 | D | + error = [9.5956] +24-11-19 20:44:59 | D | - Calibrating model.layers.31.self_attn.v_proj.weight +24-11-19 20:44:59 | D | + w: sint8 +24-11-19 20:44:59 | D | + x: None +24-11-19 20:44:59 | D | + y: None +24-11-19 20:44:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:44:59 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:44:59 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:45:00 | D | + finished calculating the original outputs, ram usage: 13.4 +24-11-19 20:45:00 | D | - range ratio = [ 1.0000] +24-11-19 20:45:00 | D | sum error = [ 2.8085] +24-11-19 20:45:00 | D | best error = [ 2.8085] +24-11-19 20:45:00 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:45:00 | D | sum error = [ 2.7907, 2.8031, 2.8063, 2.8527, 2.8783] +24-11-19 20:45:00 | D | best error = [ 2.5452, 2.4516, 2.4060, 2.3814, 2.3666] +24-11-19 20:45:00 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:45:00 | D | sum error = [ 2.9986, 3.0659, 3.1913, 3.3455, 3.5055] +24-11-19 20:45:00 | D | best error = [ 2.3567, 2.3536, 2.3520, 2.3512, 2.3511] +24-11-19 20:45:00 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:45:00 | D | sum error = [ 3.6934, 3.9354, 4.1819, 4.4598, 4.7827] +24-11-19 20:45:00 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 20:45:00 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:45:00 | D | sum error = [ 5.0930, 5.4610, 5.8724, 6.2768, 6.7033] +24-11-19 20:45:00 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 20:45:00 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:45:00 | D | sum error = [ 7.1942, 7.7319, 8.2802, 8.8892, 9.5336] +24-11-19 20:45:00 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 20:45:00 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:45:00 | D | sum error = [ 10.1741, 10.9193, 11.6294, 12.4059, 13.2511] +24-11-19 20:45:00 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 20:45:00 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:45:00 | D | sum error = [ 14.1354, 15.1215, 16.0964, 17.1676, 18.2720] +24-11-19 20:45:00 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 20:45:00 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:45:00 | D | sum error = [ 19.5063, 20.7550, 22.0611, 23.4553, 24.8853] +24-11-19 20:45:00 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 20:45:00 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:45:00 | D | sum error = [ 26.4671, 28.0669, 29.7679, 31.5378, 33.4218] +24-11-19 20:45:00 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 20:45:00 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:45:00 | D | sum error = [ 35.4007, 37.4819, 39.6449, 41.9311, 44.3243] +24-11-19 20:45:00 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 20:45:00 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:45:00 | D | sum error = [ 46.8495, 49.5010, 52.2533, 55.1432, 58.1982] +24-11-19 20:45:00 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 20:45:00 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:45:00 | D | sum error = [ 61.3716, 64.7183, 68.2198, 71.8731, 75.7062] +24-11-19 20:45:00 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 20:45:00 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:45:00 | D | sum error = [ 79.6715, 83.8441, 88.1890, 92.7044, 97.4292] +24-11-19 20:45:00 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 20:45:00 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:45:00 | D | sum error = [ 102.3209, 107.4136, 112.7113, 118.2007, 123.9592] +24-11-19 20:45:00 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 20:45:00 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:45:00 | D | sum error = [ 129.9018, 136.1296, 142.5446, 149.1563, 156.0104] +24-11-19 20:45:00 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 20:45:00 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:45:00 | D | sum error = [ 163.0788, 170.3835, 177.8962, 185.6607, 193.6401] +24-11-19 20:45:00 | D | best error = [ 2.3511, 2.3511, 2.3511, 2.3511, 2.3511] +24-11-19 20:45:00 | D | + error = [2.3511] +24-11-19 20:45:00 | D | - Calibrating model.layers.31.self_attn.o_proj.weight +24-11-19 20:45:00 | D | + w: sint8 +24-11-19 20:45:00 | D | + x: None +24-11-19 20:45:00 | D | + y: None +24-11-19 20:45:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:45:00 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:45:00 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:45:00 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:45:00 | D | - range ratio = [ 1.0000] +24-11-19 20:45:00 | D | sum error = [ 2.6017] +24-11-19 20:45:00 | D | best error = [ 2.6017] +24-11-19 20:45:00 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:45:00 | D | sum error = [ 2.5754, 2.5867, 2.5560, 2.5188, 2.5264] +24-11-19 20:45:00 | D | best error = [ 2.1183, 1.9665, 1.8784, 1.8242, 1.7876] +24-11-19 20:45:00 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:45:00 | D | sum error = [ 2.5288, 2.4783, 2.4944, 2.5073, 2.5374] +24-11-19 20:45:00 | D | best error = [ 1.7578, 1.7360, 1.7172, 1.7025, 1.6897] +24-11-19 20:45:00 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:45:00 | D | sum error = [ 2.5449, 2.5877, 2.6272, 2.6895, 2.7932] +24-11-19 20:45:00 | D | best error = [ 1.6811, 1.6724, 1.6634, 1.6585, 1.6531] +24-11-19 20:45:00 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:45:00 | D | sum error = [ 2.8534, 2.9250, 3.0684, 3.2171, 3.3344] +24-11-19 20:45:00 | D | best error = [ 1.6495, 1.6457, 1.6432, 1.6405, 1.6385] +24-11-19 20:45:00 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:45:00 | D | sum error = [ 3.5231, 3.7089, 3.9182, 4.1457, 4.4091] +24-11-19 20:45:00 | D | best error = [ 1.6370, 1.6356, 1.6341, 1.6334, 1.6327] +24-11-19 20:45:00 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:45:00 | D | sum error = [ 4.6463, 4.9634, 5.2857, 5.6252, 6.0084] +24-11-19 20:45:00 | D | best error = [ 1.6319, 1.6311, 1.6307, 1.6304, 1.6302] +24-11-19 20:45:00 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:45:00 | D | sum error = [ 6.3944, 6.8233, 7.2930, 7.7857, 8.2912] +24-11-19 20:45:00 | D | best error = [ 1.6300, 1.6299, 1.6298, 1.6298, 1.6298] +24-11-19 20:45:00 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:45:00 | D | sum error = [ 8.8825, 9.4940, 10.1224, 10.8564, 11.5833] +24-11-19 20:45:00 | D | best error = [ 1.6298, 1.6297, 1.6297, 1.6297, 1.6296] +24-11-19 20:45:00 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:45:00 | D | sum error = [ 12.3864, 13.2302, 14.1262, 15.0585, 16.0574] +24-11-19 20:45:00 | D | best error = [ 1.6296, 1.6295, 1.6295, 1.6295, 1.6295] +24-11-19 20:45:00 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:45:00 | D | sum error = [ 17.1419, 18.2809, 19.5016, 20.7781, 22.1364] +24-11-19 20:45:00 | D | best error = [ 1.6295, 1.6295, 1.6295, 1.6295, 1.6295] +24-11-19 20:45:00 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:45:00 | D | sum error = [ 23.5962, 25.1358, 26.7436, 28.4278, 30.2214] +24-11-19 20:45:00 | D | best error = [ 1.6295, 1.6295, 1.6295, 1.6295, 1.6295] +24-11-19 20:45:00 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:45:00 | D | sum error = [ 32.1159, 34.1187, 36.2319, 38.4777, 40.8361] +24-11-19 20:45:00 | D | best error = [ 1.6295, 1.6295, 1.6295, 1.6295, 1.6295] +24-11-19 20:45:00 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:45:00 | D | sum error = [ 43.3085, 45.8878, 48.6479, 51.5217, 54.5466] +24-11-19 20:45:00 | D | best error = [ 1.6295, 1.6295, 1.6295, 1.6295, 1.6295] +24-11-19 20:45:00 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:45:00 | D | sum error = [ 57.7064, 61.0182, 64.4876, 68.1406, 71.9549] +24-11-19 20:45:00 | D | best error = [ 1.6295, 1.6295, 1.6295, 1.6295, 1.6295] +24-11-19 20:45:00 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:45:00 | D | sum error = [ 75.9442, 80.1398, 84.4972, 89.0282, 93.7580] +24-11-19 20:45:00 | D | best error = [ 1.6295, 1.6295, 1.6295, 1.6295, 1.6295] +24-11-19 20:45:00 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:45:00 | D | sum error = [ 98.6822, 103.7999, 109.1181, 114.6277, 120.3707] +24-11-19 20:45:00 | D | best error = [ 1.6295, 1.6295, 1.6295, 1.6295, 1.6295] +24-11-19 20:45:00 | D | + error = [1.6295] +24-11-19 20:45:01 | D | - Calibrating model.layers.31.mlp.up_proj.weight +24-11-19 20:45:01 | D | + w: sint8 +24-11-19 20:45:01 | D | + x: None +24-11-19 20:45:01 | D | + y: None +24-11-19 20:45:01 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:45:01 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:45:01 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:45:01 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:45:01 | D | - range ratio = [ 1.0000] +24-11-19 20:45:01 | D | sum error = [ 0.5410] +24-11-19 20:45:01 | D | best error = [ 0.5410] +24-11-19 20:45:02 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:45:02 | D | sum error = [ 0.5379, 0.5363, 0.5371, 0.5430, 0.5542] +24-11-19 20:45:02 | D | best error = [ 0.4784, 0.4557, 0.4444, 0.4382, 0.4349] +24-11-19 20:45:02 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:45:02 | D | sum error = [ 0.5696, 0.5877, 0.6123, 0.6390, 0.6774] +24-11-19 20:45:02 | D | best error = [ 0.4332, 0.4323, 0.4320, 0.4318, 0.4318] +24-11-19 20:45:02 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:45:02 | D | sum error = [ 0.7156, 0.7575, 0.8103, 0.8669, 0.9271] +24-11-19 20:45:02 | D | best error = [ 0.4318, 0.4318, 0.4318, 0.4318, 0.4318] +24-11-19 20:45:02 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:45:02 | D | sum error = [ 0.9966, 1.0678, 1.1420, 1.2249, 1.3141] +24-11-19 20:45:02 | D | best error = [ 0.4318, 0.4318, 0.4318, 0.4318, 0.4318] +24-11-19 20:45:02 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:45:02 | D | sum error = [ 1.4116, 1.5160, 1.6219, 1.7385, 1.8630] +24-11-19 20:45:02 | D | best error = [ 0.4318, 0.4318, 0.4318, 0.4318, 0.4318] +24-11-19 20:45:02 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:45:02 | D | sum error = [ 1.9949, 2.1356, 2.2844, 2.4431, 2.6137] +24-11-19 20:45:02 | D | best error = [ 0.4318, 0.4318, 0.4318, 0.4318, 0.4318] +24-11-19 20:45:02 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:45:02 | D | sum error = [ 2.7936, 2.9825, 3.1823, 3.3979, 3.6263] +24-11-19 20:45:02 | D | best error = [ 0.4318, 0.4318, 0.4318, 0.4318, 0.4318] +24-11-19 20:45:02 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:45:02 | D | sum error = [ 3.8645, 4.1196, 4.3931, 4.6790, 4.9826] +24-11-19 20:45:02 | D | best error = [ 0.4318, 0.4318, 0.4318, 0.4318, 0.4318] +24-11-19 20:45:02 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:45:02 | D | sum error = [ 5.3016, 5.6451, 6.0089, 6.3868, 6.7925] +24-11-19 20:45:02 | D | best error = [ 0.4318, 0.4318, 0.4318, 0.4318, 0.4318] +24-11-19 20:45:02 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:45:02 | D | sum error = [ 7.2185, 7.6697, 8.1465, 8.6496, 9.1823] +24-11-19 20:45:02 | D | best error = [ 0.4318, 0.4318, 0.4318, 0.4318, 0.4318] +24-11-19 20:45:02 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:45:02 | D | sum error = [ 9.7458, 10.3333, 10.9607, 11.6141, 12.3056] +24-11-19 20:45:02 | D | best error = [ 0.4318, 0.4318, 0.4318, 0.4318, 0.4318] +24-11-19 20:45:02 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:45:02 | D | sum error = [ 13.0349, 13.8015, 14.6078, 15.4463, 16.3375] +24-11-19 20:45:02 | D | best error = [ 0.4318, 0.4318, 0.4318, 0.4318, 0.4318] +24-11-19 20:45:02 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:45:02 | D | sum error = [ 17.2677, 18.2498, 19.2738, 20.3535, 21.4709] +24-11-19 20:45:02 | D | best error = [ 0.4318, 0.4318, 0.4318, 0.4318, 0.4318] +24-11-19 20:45:02 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:45:02 | D | sum error = [ 22.6451, 23.8673, 25.1420, 26.4722, 27.8482] +24-11-19 20:45:02 | D | best error = [ 0.4318, 0.4318, 0.4318, 0.4318, 0.4318] +24-11-19 20:45:02 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:45:02 | D | sum error = [ 29.2873, 30.7776, 32.3310, 33.9488, 35.6100] +24-11-19 20:45:02 | D | best error = [ 0.4318, 0.4318, 0.4318, 0.4318, 0.4318] +24-11-19 20:45:02 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:45:02 | D | sum error = [ 37.3441, 39.1359, 40.9723, 42.8755, 44.8470] +24-11-19 20:45:02 | D | best error = [ 0.4318, 0.4318, 0.4318, 0.4318, 0.4318] +24-11-19 20:45:02 | D | + error = [0.4318] +24-11-19 20:45:02 | D | - Calibrating model.layers.31.mlp.gate_proj.weight +24-11-19 20:45:02 | D | + w: sint8 +24-11-19 20:45:02 | D | + x: None +24-11-19 20:45:02 | D | + y: None +24-11-19 20:45:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:45:02 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:45:02 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:45:02 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:45:02 | D | - range ratio = [ 1.0000] +24-11-19 20:45:02 | D | sum error = [ 12.5636] +24-11-19 20:45:02 | D | best error = [ 12.5636] +24-11-19 20:45:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:45:03 | D | sum error = [ 12.4301, 12.4518, 12.4922, 12.6191, 12.9085] +24-11-19 20:45:03 | D | best error = [ 11.0469, 10.5549, 10.3021, 10.1624, 10.0872] +24-11-19 20:45:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:45:03 | D | sum error = [ 13.2040, 13.5912, 14.2480, 15.0137, 15.7627] +24-11-19 20:45:03 | D | best error = [ 10.0481, 10.0274, 10.0197, 10.0166, 10.0153] +24-11-19 20:45:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:45:03 | D | sum error = [ 16.7051, 17.7769, 19.0008, 20.2873, 21.7100] +24-11-19 20:45:03 | D | best error = [ 10.0152, 10.0151, 10.0151, 10.0151, 10.0151] +24-11-19 20:45:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:45:03 | D | sum error = [ 23.3337, 25.0251, 26.7531, 28.8100, 30.9113] +24-11-19 20:45:03 | D | best error = [ 10.0151, 10.0151, 10.0151, 10.0151, 10.0151] +24-11-19 20:45:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:45:03 | D | sum error = [ 33.2226, 35.7629, 38.3705, 41.1778, 44.2534] +24-11-19 20:45:03 | D | best error = [ 10.0151, 10.0151, 10.0151, 10.0151, 10.0151] +24-11-19 20:45:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:45:03 | D | sum error = [ 47.4640, 50.9391, 54.6820, 58.6236, 62.8932] +24-11-19 20:45:03 | D | best error = [ 10.0151, 10.0151, 10.0151, 10.0151, 10.0151] +24-11-19 20:45:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:45:03 | D | sum error = [ 67.4859, 72.3948, 77.6080, 83.2059, 89.2055] +24-11-19 20:45:03 | D | best error = [ 10.0151, 10.0151, 10.0151, 10.0151, 10.0151] +24-11-19 20:45:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:45:03 | D | sum error = [ 95.6230, 102.4424, 109.7494, 117.5690, 125.9321] +24-11-19 20:45:03 | D | best error = [ 10.0151, 10.0151, 10.0151, 10.0151, 10.0151] +24-11-19 20:45:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:45:03 | D | sum error = [ 134.9390, 144.5722, 154.7720, 165.8064, 177.5518] +24-11-19 20:45:03 | D | best error = [ 10.0151, 10.0151, 10.0151, 10.0151, 10.0151] +24-11-19 20:45:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:45:03 | D | sum error = [ 190.0838, 203.4895, 217.7799, 233.1001, 249.4967] +24-11-19 20:45:03 | D | best error = [ 10.0151, 10.0151, 10.0151, 10.0151, 10.0151] +24-11-19 20:45:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:45:03 | D | sum error = [ 266.8847, 285.4061, 305.1999, 326.2300, 348.7445] +24-11-19 20:45:03 | D | best error = [ 10.0151, 10.0151, 10.0151, 10.0151, 10.0151] +24-11-19 20:45:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:45:03 | D | sum error = [ 372.4820, 397.7849, 424.6342, 453.1514, 483.3617] +24-11-19 20:45:03 | D | best error = [ 10.0151, 10.0151, 10.0151, 10.0151, 10.0151] +24-11-19 20:45:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:45:03 | D | sum error = [ 515.3860, 549.1713, 584.8263, 622.3893, 661.9720] +24-11-19 20:45:03 | D | best error = [ 10.0151, 10.0151, 10.0151, 10.0151, 10.0151] +24-11-19 20:45:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:45:03 | D | sum error = [ 703.5931, 747.2610, 793.0672, 841.0751, 891.1548] +24-11-19 20:45:03 | D | best error = [ 10.0151, 10.0151, 10.0151, 10.0151, 10.0151] +24-11-19 20:45:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:45:03 | D | sum error = [ 943.6657, 998.4041, 1055.4633, 1114.8227, 1176.6907] +24-11-19 20:45:03 | D | best error = [ 10.0151, 10.0151, 10.0151, 10.0151, 10.0151] +24-11-19 20:45:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:45:03 | D | sum error = [ 1240.9382, 1307.4212, 1376.4640, 1447.8283, 1521.5973] +24-11-19 20:45:03 | D | best error = [ 10.0151, 10.0151, 10.0151, 10.0151, 10.0151] +24-11-19 20:45:03 | D | + error = [10.0151] +24-11-19 20:45:04 | D | - Calibrating model.layers.31.mlp.down_proj.weight +24-11-19 20:45:04 | D | + w: sint8 +24-11-19 20:45:04 | D | + x: None +24-11-19 20:45:04 | D | + y: None +24-11-19 20:45:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:45:04 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:45:04 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:45:04 | D | + finished calculating the original outputs, ram usage: 13.2 +24-11-19 20:45:04 | D | - range ratio = [ 1.0000] +24-11-19 20:45:04 | D | sum error = [ 13.4982] +24-11-19 20:45:04 | D | best error = [ 13.4982] +24-11-19 20:45:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:45:05 | D | sum error = [ 18.1582, 28.2392, 39.9062, 51.9174, 64.4759] +24-11-19 20:45:05 | D | best error = [ 10.6041, 9.5378, 8.9366, 8.6237, 8.4204] +24-11-19 20:45:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:45:05 | D | sum error = [ 77.3606, 90.8970, 104.3148, 118.4523, 132.4045] +24-11-19 20:45:05 | D | best error = [ 8.2615, 8.1563, 8.0673, 7.9938, 7.9449] +24-11-19 20:45:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:45:05 | D | sum error = [ 146.7530, 161.3884, 176.2075, 190.9706, 206.4237] +24-11-19 20:45:05 | D | best error = [ 7.9019, 7.8702, 7.8445, 7.8274, 7.8128] +24-11-19 20:45:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:45:05 | D | sum error = [ 221.9128, 238.0089, 253.9444, 270.3113, 287.0735] +24-11-19 20:45:05 | D | best error = [ 7.8036, 7.7946, 7.7894, 7.7846, 7.7819] +24-11-19 20:45:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:45:05 | D | sum error = [ 304.2173, 321.6039, 339.3091, 357.5690, 375.9015] +24-11-19 20:45:05 | D | best error = [ 7.7800, 7.7786, 7.7764, 7.7756, 7.7756] +24-11-19 20:45:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:45:05 | D | sum error = [ 394.9360, 414.3999, 434.2037, 454.5371, 475.3604] +24-11-19 20:45:05 | D | best error = [ 7.7750, 7.7747, 7.7746, 7.7743, 7.7743] +24-11-19 20:45:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:45:05 | D | sum error = [ 496.5035, 518.2042, 540.4443, 562.9999, 586.4237] +24-11-19 20:45:05 | D | best error = [ 7.7743, 7.7743, 7.7743, 7.7743, 7.7743] +24-11-19 20:45:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:45:05 | D | sum error = [ 610.0868, 634.6175, 659.4365, 684.9159, 710.6944] +24-11-19 20:45:05 | D | best error = [ 7.7743, 7.7743, 7.7743, 7.7743, 7.7743] +24-11-19 20:45:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:45:05 | D | sum error = [ 737.2788, 764.6176, 792.3631, 820.7717, 849.6788] +24-11-19 20:45:05 | D | best error = [ 7.7743, 7.7743, 7.7743, 7.7743, 7.7743] +24-11-19 20:45:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:45:05 | D | sum error = [ 879.5673, 909.8373, 940.9695, 972.6391, 1004.9434] +24-11-19 20:45:05 | D | best error = [ 7.7743, 7.7743, 7.7743, 7.7743, 7.7743] +24-11-19 20:45:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:45:05 | D | sum error = [ 1037.9198, 1071.6985, 1106.1283, 1141.2888, 1177.1557] +24-11-19 20:45:05 | D | best error = [ 7.7743, 7.7743, 7.7743, 7.7743, 7.7743] +24-11-19 20:45:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:45:05 | D | sum error = [ 1213.6457, 1250.9509, 1289.1611, 1328.0947, 1367.8032] +24-11-19 20:45:05 | D | best error = [ 7.7743, 7.7743, 7.7743, 7.7743, 7.7743] +24-11-19 20:45:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:45:05 | D | sum error = [ 1408.2406, 1449.3729, 1491.5552, 1534.4315, 1578.1509] +24-11-19 20:45:05 | D | best error = [ 7.7743, 7.7743, 7.7743, 7.7743, 7.7743] +24-11-19 20:45:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:45:05 | D | sum error = [ 1622.5487, 1667.7553, 1713.7928, 1760.6080, 1808.2388] +24-11-19 20:45:05 | D | best error = [ 7.7743, 7.7743, 7.7743, 7.7743, 7.7743] +24-11-19 20:45:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:45:05 | D | sum error = [ 1856.7865, 1906.1017, 1956.2313, 2007.1168, 2058.8089] +24-11-19 20:45:05 | D | best error = [ 7.7743, 7.7743, 7.7743, 7.7743, 7.7743] +24-11-19 20:45:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:45:05 | D | sum error = [ 2111.3393, 2164.6977, 2218.8760, 2273.8962, 2329.8382] +24-11-19 20:45:05 | D | best error = [ 7.7743, 7.7743, 7.7743, 7.7743, 7.7743] +24-11-19 20:45:05 | D | + error = [7.7743] +24-11-19 20:45:05 | D | - Quantizing model.layers.31.self_attn.q_proj.weight +24-11-19 20:45:06 | D | - Quantizing model.layers.31.self_attn.k_proj.weight +24-11-19 20:45:07 | D | - Quantizing model.layers.31.self_attn.v_proj.weight +24-11-19 20:45:08 | D | - Quantizing model.layers.31.self_attn.o_proj.weight +24-11-19 20:45:09 | D | - Quantizing model.layers.31.mlp.up_proj.weight +24-11-19 20:45:10 | D | - Quantizing model.layers.31.mlp.gate_proj.weight +24-11-19 20:45:11 | D | - Quantizing model.layers.31.mlp.down_proj.weight +24-11-19 20:45:15 | I | - Saving weight quantizer settings to runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.proj.OutputsError.Manual.Layer.d2.en1.sn1-attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.proj.[a.AbsMax.b.AbsMax]-attn.[a.AbsMax.b.AbsMax]/smooth.proj.a0p1.b0p9-attn.a0p5.b0/smooth.proj.skip.[out_proj+qkv_proj+up_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt +24-11-19 20:45:15 | I | - Linking weight quantizer settings to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.proj.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.proj.a0p1.b0p9.[AbsMax].[fc2].attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200844.RUNNING/model/wgts.pt +24-11-19 20:45:15 | I | - Saving model checkpoint to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.proj.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.proj.a0p1.b0p9.[AbsMax].[fc2].attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200844.RUNNING/model +24-11-19 20:45:37 | I | * Quantizing activations +24-11-19 20:45:37 | I | - Generating activation quantizer settings +24-11-19 20:45:37 | D | Starting new HTTPS connection (7): huggingface.co:443 +24-11-19 20:45:43 | D | Starting new HTTPS connection (8): huggingface.co:443 +24-11-19 20:45:55 | D | Starting new HTTPS connection (3): s3.amazonaws.com:443 +24-11-19 20:46:07 | W | Repo card metadata block was not found. Setting CardData to empty. +24-11-19 20:46:07 | D | Starting new HTTPS connection (9): huggingface.co:443 +24-11-19 20:46:19 | W | Using the latest cached version of the dataset since mit-han-lab/pile-val-backup couldn't be found on the Hugging Face Hub +24-11-19 20:46:19 | W | Found the latest cached dataset configuration 'default' at /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4 (last modified on Tue Oct 8 18:58:39 2024). +24-11-19 20:46:19 | D | Attempting to acquire lock 23438275854064 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:46:19 | D | Lock 23438275854064 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:46:19 | D | open file: /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4/dataset_info.json +24-11-19 20:46:19 | D | Attempting to release lock 23438275854064 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:46:19 | D | Lock 23438275854064 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:46:33 | D | - Quantizing layer model.layers.0 +24-11-19 20:46:33 | D | - Calibrating model.layers.0.self_attn.v_proj.input +24-11-19 20:46:33 | D | - Calibrating model.layers.0.self_attn.k_rotary_emb.output +24-11-19 20:46:33 | D | + w: None +24-11-19 20:46:33 | D | + x: None +24-11-19 20:46:33 | D | + y: sint8 +24-11-19 20:46:33 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:33 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:46:33 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:46:34 | D | - range ratio = [ 1.0000] +24-11-19 20:46:34 | D | sum error = [ 2.8424] +24-11-19 20:46:34 | D | best error = [ 2.8424] +24-11-19 20:46:34 | D | + error = [2.8424] +24-11-19 20:46:34 | D | - Calibrating model.layers.0.self_attn.v_proj.output +24-11-19 20:46:34 | D | + w: None +24-11-19 20:46:34 | D | + x: None +24-11-19 20:46:34 | D | + y: sint8 +24-11-19 20:46:34 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:34 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:46:34 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:46:35 | D | - range ratio = [ 1.0000] +24-11-19 20:46:35 | D | sum error = [ 2.7431] +24-11-19 20:46:35 | D | best error = [ 2.7431] +24-11-19 20:46:35 | D | + error = [2.7431] +24-11-19 20:46:35 | D | - Calibrating model.layers.0.self_attn.o_proj.input +24-11-19 20:46:35 | D | - Calibrating model.layers.0.mlp.up_proj.input +24-11-19 20:46:35 | D | - Calibrating model.layers.0.mlp.down_proj.input +24-11-19 20:46:36 | D | - Quantizing model.layers.0.self_attn.q_proj (inputs) +24-11-19 20:46:36 | D | - Quantizing model.layers.0.self_attn.k_proj (inputs) +24-11-19 20:46:36 | D | - Quantizing model.layers.0.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:36 | D | - Quantizing model.layers.0.self_attn.o_proj (inputs) +24-11-19 20:46:36 | D | - Quantizing model.layers.0.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:36 | D | - Quantizing model.layers.0.mlp.gate_proj (inputs) +24-11-19 20:46:36 | D | - Quantizing model.layers.0.mlp.up_proj (inputs) +24-11-19 20:46:36 | D | - Quantizing model.layers.0.mlp.down_proj (inputs) +24-11-19 20:46:42 | D | - Quantizing layer model.layers.1 +24-11-19 20:46:42 | D | - Calibrating model.layers.1.self_attn.v_proj.input +24-11-19 20:46:42 | D | - Calibrating model.layers.1.self_attn.k_rotary_emb.output +24-11-19 20:46:42 | D | + w: None +24-11-19 20:46:42 | D | + x: None +24-11-19 20:46:42 | D | + y: sint8 +24-11-19 20:46:42 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:42 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:46:42 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:46:43 | D | - range ratio = [ 1.0000] +24-11-19 20:46:43 | D | sum error = [ 7.2634] +24-11-19 20:46:43 | D | best error = [ 7.2634] +24-11-19 20:46:43 | D | + error = [7.2634] +24-11-19 20:46:43 | D | - Calibrating model.layers.1.self_attn.v_proj.output +24-11-19 20:46:43 | D | + w: None +24-11-19 20:46:43 | D | + x: None +24-11-19 20:46:43 | D | + y: sint8 +24-11-19 20:46:43 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:43 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:46:43 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:46:43 | D | - range ratio = [ 1.0000] +24-11-19 20:46:43 | D | sum error = [ 14.4172] +24-11-19 20:46:43 | D | best error = [ 14.4172] +24-11-19 20:46:43 | D | + error = [14.4172] +24-11-19 20:46:44 | D | - Calibrating model.layers.1.self_attn.o_proj.input +24-11-19 20:46:44 | D | - Calibrating model.layers.1.mlp.up_proj.input +24-11-19 20:46:44 | D | - Calibrating model.layers.1.mlp.down_proj.input +24-11-19 20:46:44 | D | - Quantizing model.layers.1.self_attn.q_proj (inputs) +24-11-19 20:46:44 | D | - Quantizing model.layers.1.self_attn.k_proj (inputs) +24-11-19 20:46:44 | D | - Quantizing model.layers.1.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:44 | D | - Quantizing model.layers.1.self_attn.o_proj (inputs) +24-11-19 20:46:44 | D | - Quantizing model.layers.1.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:44 | D | - Quantizing model.layers.1.mlp.gate_proj (inputs) +24-11-19 20:46:44 | D | - Quantizing model.layers.1.mlp.up_proj (inputs) +24-11-19 20:46:44 | D | - Quantizing model.layers.1.mlp.down_proj (inputs) +24-11-19 20:46:51 | D | - Quantizing layer model.layers.2 +24-11-19 20:46:51 | D | - Calibrating model.layers.2.self_attn.v_proj.input +24-11-19 20:46:51 | D | - Calibrating model.layers.2.self_attn.k_rotary_emb.output +24-11-19 20:46:51 | D | + w: None +24-11-19 20:46:51 | D | + x: None +24-11-19 20:46:51 | D | + y: sint8 +24-11-19 20:46:51 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:51 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:46:51 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:46:52 | D | - range ratio = [ 1.0000] +24-11-19 20:46:52 | D | sum error = [ 7.8009] +24-11-19 20:46:52 | D | best error = [ 7.8009] +24-11-19 20:46:52 | D | + error = [7.8009] +24-11-19 20:46:52 | D | - Calibrating model.layers.2.self_attn.v_proj.output +24-11-19 20:46:52 | D | + w: None +24-11-19 20:46:52 | D | + x: None +24-11-19 20:46:52 | D | + y: sint8 +24-11-19 20:46:52 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:52 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:46:52 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:46:53 | D | - range ratio = [ 1.0000] +24-11-19 20:46:53 | D | sum error = [ 23.5831] +24-11-19 20:46:53 | D | best error = [ 23.5831] +24-11-19 20:46:53 | D | + error = [23.5831] +24-11-19 20:46:53 | D | - Calibrating model.layers.2.self_attn.o_proj.input +24-11-19 20:46:53 | D | - Calibrating model.layers.2.mlp.up_proj.input +24-11-19 20:46:53 | D | - Calibrating model.layers.2.mlp.down_proj.input +24-11-19 20:46:53 | D | - Quantizing model.layers.2.self_attn.q_proj (inputs) +24-11-19 20:46:53 | D | - Quantizing model.layers.2.self_attn.k_proj (inputs) +24-11-19 20:46:53 | D | - Quantizing model.layers.2.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:53 | D | - Quantizing model.layers.2.self_attn.o_proj (inputs) +24-11-19 20:46:53 | D | - Quantizing model.layers.2.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:53 | D | - Quantizing model.layers.2.mlp.gate_proj (inputs) +24-11-19 20:46:53 | D | - Quantizing model.layers.2.mlp.up_proj (inputs) +24-11-19 20:46:53 | D | - Quantizing model.layers.2.mlp.down_proj (inputs) +24-11-19 20:46:59 | D | - Quantizing layer model.layers.3 +24-11-19 20:46:59 | D | - Calibrating model.layers.3.self_attn.v_proj.input +24-11-19 20:46:59 | D | - Calibrating model.layers.3.self_attn.k_rotary_emb.output +24-11-19 20:46:59 | D | + w: None +24-11-19 20:46:59 | D | + x: None +24-11-19 20:46:59 | D | + y: sint8 +24-11-19 20:46:59 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:59 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:47:00 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:47:00 | D | - range ratio = [ 1.0000] +24-11-19 20:47:00 | D | sum error = [ 12.0750] +24-11-19 20:47:00 | D | best error = [ 12.0750] +24-11-19 20:47:00 | D | + error = [12.0750] +24-11-19 20:47:01 | D | - Calibrating model.layers.3.self_attn.v_proj.output +24-11-19 20:47:01 | D | + w: None +24-11-19 20:47:01 | D | + x: None +24-11-19 20:47:01 | D | + y: sint8 +24-11-19 20:47:01 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:01 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:47:01 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:47:01 | D | - range ratio = [ 1.0000] +24-11-19 20:47:01 | D | sum error = [ 58.7599] +24-11-19 20:47:01 | D | best error = [ 58.7599] +24-11-19 20:47:01 | D | + error = [58.7599] +24-11-19 20:47:01 | D | - Calibrating model.layers.3.self_attn.o_proj.input +24-11-19 20:47:01 | D | - Calibrating model.layers.3.mlp.up_proj.input +24-11-19 20:47:02 | D | - Calibrating model.layers.3.mlp.down_proj.input +24-11-19 20:47:02 | D | - Quantizing model.layers.3.self_attn.q_proj (inputs) +24-11-19 20:47:02 | D | - Quantizing model.layers.3.self_attn.k_proj (inputs) +24-11-19 20:47:02 | D | - Quantizing model.layers.3.self_attn.v_proj (inputs and outputs) +24-11-19 20:47:02 | D | - Quantizing model.layers.3.self_attn.o_proj (inputs) +24-11-19 20:47:02 | D | - Quantizing model.layers.3.self_attn.k_rotary_emb (outputs) +24-11-19 20:47:02 | D | - Quantizing model.layers.3.mlp.gate_proj (inputs) +24-11-19 20:47:02 | D | - Quantizing model.layers.3.mlp.up_proj (inputs) +24-11-19 20:47:02 | D | - Quantizing model.layers.3.mlp.down_proj (inputs) +24-11-19 20:47:08 | D | - Quantizing layer model.layers.4 +24-11-19 20:47:08 | D | - Calibrating model.layers.4.self_attn.v_proj.input +24-11-19 20:47:08 | D | - Calibrating model.layers.4.self_attn.k_rotary_emb.output +24-11-19 20:47:08 | D | + w: None +24-11-19 20:47:08 | D | + x: None +24-11-19 20:47:08 | D | + y: sint8 +24-11-19 20:47:08 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:08 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:47:08 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:47:09 | D | - range ratio = [ 1.0000] +24-11-19 20:47:09 | D | sum error = [ 20.7458] +24-11-19 20:47:09 | D | best error = [ 20.7458] +24-11-19 20:47:09 | D | + error = [20.7458] +24-11-19 20:47:09 | D | - Calibrating model.layers.4.self_attn.v_proj.output +24-11-19 20:47:09 | D | + w: None +24-11-19 20:47:09 | D | + x: None +24-11-19 20:47:09 | D | + y: sint8 +24-11-19 20:47:09 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:09 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:47:09 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:47:10 | D | - range ratio = [ 1.0000] +24-11-19 20:47:10 | D | sum error = [ 38.9847] +24-11-19 20:47:10 | D | best error = [ 38.9847] +24-11-19 20:47:10 | D | + error = [38.9847] +24-11-19 20:47:10 | D | - Calibrating model.layers.4.self_attn.o_proj.input +24-11-19 20:47:10 | D | - Calibrating model.layers.4.mlp.up_proj.input +24-11-19 20:47:10 | D | - Calibrating model.layers.4.mlp.down_proj.input +24-11-19 20:47:10 | D | - Quantizing model.layers.4.self_attn.q_proj (inputs) +24-11-19 20:47:10 | D | - Quantizing model.layers.4.self_attn.k_proj (inputs) +24-11-19 20:47:10 | D | - Quantizing model.layers.4.self_attn.v_proj (inputs and outputs) +24-11-19 20:47:10 | D | - Quantizing model.layers.4.self_attn.o_proj (inputs) +24-11-19 20:47:10 | D | - Quantizing model.layers.4.self_attn.k_rotary_emb (outputs) +24-11-19 20:47:10 | D | - Quantizing model.layers.4.mlp.gate_proj (inputs) +24-11-19 20:47:10 | D | - Quantizing model.layers.4.mlp.up_proj (inputs) +24-11-19 20:47:10 | D | - Quantizing model.layers.4.mlp.down_proj (inputs) +24-11-19 20:47:16 | D | - Quantizing layer model.layers.5 +24-11-19 20:47:16 | D | - Calibrating model.layers.5.self_attn.v_proj.input +24-11-19 20:47:16 | D | - Calibrating model.layers.5.self_attn.k_rotary_emb.output +24-11-19 20:47:16 | D | + w: None +24-11-19 20:47:16 | D | + x: None +24-11-19 20:47:16 | D | + y: sint8 +24-11-19 20:47:16 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:16 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:47:16 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:47:17 | D | - range ratio = [ 1.0000] +24-11-19 20:47:17 | D | sum error = [ 20.3592] +24-11-19 20:47:17 | D | best error = [ 20.3592] +24-11-19 20:47:17 | D | + error = [20.3592] +24-11-19 20:47:17 | D | - Calibrating model.layers.5.self_attn.v_proj.output +24-11-19 20:47:17 | D | + w: None +24-11-19 20:47:17 | D | + x: None +24-11-19 20:47:17 | D | + y: sint8 +24-11-19 20:47:17 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:17 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:47:17 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:47:18 | D | - range ratio = [ 1.0000] +24-11-19 20:47:18 | D | sum error = [ 30.9404] +24-11-19 20:47:18 | D | best error = [ 30.9404] +24-11-19 20:47:18 | D | + error = [30.9404] +24-11-19 20:47:18 | D | - Calibrating model.layers.5.self_attn.o_proj.input +24-11-19 20:47:18 | D | - Calibrating model.layers.5.mlp.up_proj.input +24-11-19 20:47:19 | D | - Calibrating model.layers.5.mlp.down_proj.input +24-11-19 20:47:19 | D | - Quantizing model.layers.5.self_attn.q_proj (inputs) +24-11-19 20:47:19 | D | - Quantizing model.layers.5.self_attn.k_proj (inputs) +24-11-19 20:47:19 | D | - Quantizing model.layers.5.self_attn.v_proj (inputs and outputs) +24-11-19 20:47:19 | D | - Quantizing model.layers.5.self_attn.o_proj (inputs) +24-11-19 20:47:19 | D | - Quantizing model.layers.5.self_attn.k_rotary_emb (outputs) +24-11-19 20:47:19 | D | - Quantizing model.layers.5.mlp.gate_proj (inputs) +24-11-19 20:47:19 | D | - Quantizing model.layers.5.mlp.up_proj (inputs) +24-11-19 20:47:19 | D | - Quantizing model.layers.5.mlp.down_proj (inputs) +24-11-19 20:47:25 | D | - Quantizing layer model.layers.6 +24-11-19 20:47:25 | D | - Calibrating model.layers.6.self_attn.v_proj.input +24-11-19 20:47:25 | D | - Calibrating model.layers.6.self_attn.k_rotary_emb.output +24-11-19 20:47:25 | D | + w: None +24-11-19 20:47:25 | D | + x: None +24-11-19 20:47:25 | D | + y: sint8 +24-11-19 20:47:25 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:25 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:47:25 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:47:26 | D | - range ratio = [ 1.0000] +24-11-19 20:47:26 | D | sum error = [ 18.9730] +24-11-19 20:47:26 | D | best error = [ 18.9730] +24-11-19 20:47:26 | D | + error = [18.9730] +24-11-19 20:47:26 | D | - Calibrating model.layers.6.self_attn.v_proj.output +24-11-19 20:47:26 | D | + w: None +24-11-19 20:47:26 | D | + x: None +24-11-19 20:47:26 | D | + y: sint8 +24-11-19 20:47:26 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:26 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:47:26 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:47:27 | D | - range ratio = [ 1.0000] +24-11-19 20:47:27 | D | sum error = [ 24.5174] +24-11-19 20:47:27 | D | best error = [ 24.5174] +24-11-19 20:47:27 | D | + error = [24.5174] +24-11-19 20:47:27 | D | - Calibrating model.layers.6.self_attn.o_proj.input +24-11-19 20:47:27 | D | - Calibrating model.layers.6.mlp.up_proj.input +24-11-19 20:47:27 | D | - Calibrating model.layers.6.mlp.down_proj.input +24-11-19 20:47:28 | D | - Quantizing model.layers.6.self_attn.q_proj (inputs) +24-11-19 20:47:28 | D | - Quantizing model.layers.6.self_attn.k_proj (inputs) +24-11-19 20:47:28 | D | - Quantizing model.layers.6.self_attn.v_proj (inputs and outputs) +24-11-19 20:47:28 | D | - Quantizing model.layers.6.self_attn.o_proj (inputs) +24-11-19 20:47:28 | D | - Quantizing model.layers.6.self_attn.k_rotary_emb (outputs) +24-11-19 20:47:28 | D | - Quantizing model.layers.6.mlp.gate_proj (inputs) +24-11-19 20:47:28 | D | - Quantizing model.layers.6.mlp.up_proj (inputs) +24-11-19 20:47:28 | D | - Quantizing model.layers.6.mlp.down_proj (inputs) +24-11-19 20:47:33 | D | - Quantizing layer model.layers.7 +24-11-19 20:47:33 | D | - Calibrating model.layers.7.self_attn.v_proj.input +24-11-19 20:47:33 | D | - Calibrating model.layers.7.self_attn.k_rotary_emb.output +24-11-19 20:47:33 | D | + w: None +24-11-19 20:47:33 | D | + x: None +24-11-19 20:47:33 | D | + y: sint8 +24-11-19 20:47:33 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:33 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:47:33 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:47:34 | D | - range ratio = [ 1.0000] +24-11-19 20:47:34 | D | sum error = [ 25.7963] +24-11-19 20:47:34 | D | best error = [ 25.7963] +24-11-19 20:47:34 | D | + error = [25.7963] +24-11-19 20:47:34 | D | - Calibrating model.layers.7.self_attn.v_proj.output +24-11-19 20:47:34 | D | + w: None +24-11-19 20:47:34 | D | + x: None +24-11-19 20:47:34 | D | + y: sint8 +24-11-19 20:47:34 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:34 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:47:35 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:47:35 | D | - range ratio = [ 1.0000] +24-11-19 20:47:35 | D | sum error = [ 23.7130] +24-11-19 20:47:35 | D | best error = [ 23.7130] +24-11-19 20:47:35 | D | + error = [23.7130] +24-11-19 20:47:36 | D | - Calibrating model.layers.7.self_attn.o_proj.input +24-11-19 20:47:36 | D | - Calibrating model.layers.7.mlp.up_proj.input +24-11-19 20:47:36 | D | - Calibrating model.layers.7.mlp.down_proj.input +24-11-19 20:47:36 | D | - Quantizing model.layers.7.self_attn.q_proj (inputs) +24-11-19 20:47:36 | D | - Quantizing model.layers.7.self_attn.k_proj (inputs) +24-11-19 20:47:36 | D | - Quantizing model.layers.7.self_attn.v_proj (inputs and outputs) +24-11-19 20:47:36 | D | - Quantizing model.layers.7.self_attn.o_proj (inputs) +24-11-19 20:47:36 | D | - Quantizing model.layers.7.self_attn.k_rotary_emb (outputs) +24-11-19 20:47:36 | D | - Quantizing model.layers.7.mlp.gate_proj (inputs) +24-11-19 20:47:36 | D | - Quantizing model.layers.7.mlp.up_proj (inputs) +24-11-19 20:47:36 | D | - Quantizing model.layers.7.mlp.down_proj (inputs) +24-11-19 20:47:42 | D | - Quantizing layer model.layers.8 +24-11-19 20:47:42 | D | - Calibrating model.layers.8.self_attn.v_proj.input +24-11-19 20:47:42 | D | - Calibrating model.layers.8.self_attn.k_rotary_emb.output +24-11-19 20:47:42 | D | + w: None +24-11-19 20:47:42 | D | + x: None +24-11-19 20:47:42 | D | + y: sint8 +24-11-19 20:47:42 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:42 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:47:42 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:47:43 | D | - range ratio = [ 1.0000] +24-11-19 20:47:43 | D | sum error = [ 22.4836] +24-11-19 20:47:43 | D | best error = [ 22.4836] +24-11-19 20:47:43 | D | + error = [22.4836] +24-11-19 20:47:43 | D | - Calibrating model.layers.8.self_attn.v_proj.output +24-11-19 20:47:43 | D | + w: None +24-11-19 20:47:43 | D | + x: None +24-11-19 20:47:43 | D | + y: sint8 +24-11-19 20:47:43 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:43 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:47:43 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:47:44 | D | - range ratio = [ 1.0000] +24-11-19 20:47:44 | D | sum error = [ 22.2032] +24-11-19 20:47:44 | D | best error = [ 22.2032] +24-11-19 20:47:44 | D | + error = [22.2032] +24-11-19 20:47:44 | D | - Calibrating model.layers.8.self_attn.o_proj.input +24-11-19 20:47:44 | D | - Calibrating model.layers.8.mlp.up_proj.input +24-11-19 20:47:44 | D | - Calibrating model.layers.8.mlp.down_proj.input +24-11-19 20:47:44 | D | - Quantizing model.layers.8.self_attn.q_proj (inputs) +24-11-19 20:47:44 | D | - Quantizing model.layers.8.self_attn.k_proj (inputs) +24-11-19 20:47:44 | D | - Quantizing model.layers.8.self_attn.v_proj (inputs and outputs) +24-11-19 20:47:44 | D | - Quantizing model.layers.8.self_attn.o_proj (inputs) +24-11-19 20:47:44 | D | - Quantizing model.layers.8.self_attn.k_rotary_emb (outputs) +24-11-19 20:47:44 | D | - Quantizing model.layers.8.mlp.gate_proj (inputs) +24-11-19 20:47:44 | D | - Quantizing model.layers.8.mlp.up_proj (inputs) +24-11-19 20:47:44 | D | - Quantizing model.layers.8.mlp.down_proj (inputs) +24-11-19 20:47:51 | D | - Quantizing layer model.layers.9 +24-11-19 20:47:51 | D | - Calibrating model.layers.9.self_attn.v_proj.input +24-11-19 20:47:51 | D | - Calibrating model.layers.9.self_attn.k_rotary_emb.output +24-11-19 20:47:51 | D | + w: None +24-11-19 20:47:51 | D | + x: None +24-11-19 20:47:51 | D | + y: sint8 +24-11-19 20:47:51 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:51 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:47:51 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:47:51 | D | - range ratio = [ 1.0000] +24-11-19 20:47:51 | D | sum error = [ 23.4914] +24-11-19 20:47:51 | D | best error = [ 23.4914] +24-11-19 20:47:51 | D | + error = [23.4914] +24-11-19 20:47:51 | D | - Calibrating model.layers.9.self_attn.v_proj.output +24-11-19 20:47:51 | D | + w: None +24-11-19 20:47:51 | D | + x: None +24-11-19 20:47:51 | D | + y: sint8 +24-11-19 20:47:51 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:51 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:47:52 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:47:52 | D | - range ratio = [ 1.0000] +24-11-19 20:47:52 | D | sum error = [ 59.9370] +24-11-19 20:47:52 | D | best error = [ 59.9370] +24-11-19 20:47:52 | D | + error = [59.9370] +24-11-19 20:47:52 | D | - Calibrating model.layers.9.self_attn.o_proj.input +24-11-19 20:47:52 | D | - Calibrating model.layers.9.mlp.up_proj.input +24-11-19 20:47:52 | D | - Calibrating model.layers.9.mlp.down_proj.input +24-11-19 20:47:52 | D | - Quantizing model.layers.9.self_attn.q_proj (inputs) +24-11-19 20:47:52 | D | - Quantizing model.layers.9.self_attn.k_proj (inputs) +24-11-19 20:47:52 | D | - Quantizing model.layers.9.self_attn.v_proj (inputs and outputs) +24-11-19 20:47:52 | D | - Quantizing model.layers.9.self_attn.o_proj (inputs) +24-11-19 20:47:52 | D | - Quantizing model.layers.9.self_attn.k_rotary_emb (outputs) +24-11-19 20:47:52 | D | - Quantizing model.layers.9.mlp.gate_proj (inputs) +24-11-19 20:47:52 | D | - Quantizing model.layers.9.mlp.up_proj (inputs) +24-11-19 20:47:52 | D | - Quantizing model.layers.9.mlp.down_proj (inputs) +24-11-19 20:47:58 | D | - Quantizing layer model.layers.10 +24-11-19 20:47:58 | D | - Calibrating model.layers.10.self_attn.v_proj.input +24-11-19 20:47:58 | D | - Calibrating model.layers.10.self_attn.k_rotary_emb.output +24-11-19 20:47:58 | D | + w: None +24-11-19 20:47:58 | D | + x: None +24-11-19 20:47:58 | D | + y: sint8 +24-11-19 20:47:58 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:58 | D | + finished parsing calibration arguments, ram usage: 13.1 +24-11-19 20:47:59 | D | + finished reseting calibrator, ram usage: 13.1 +24-11-19 20:47:59 | D | - range ratio = [ 1.0000] +24-11-19 20:47:59 | D | sum error = [ 21.5836] +24-11-19 20:47:59 | D | best error = [ 21.5836] +24-11-19 20:47:59 | D | + error = [21.5836] +24-11-19 20:47:59 | D | - Calibrating model.layers.10.self_attn.v_proj.output +24-11-19 20:47:59 | D | + w: None +24-11-19 20:47:59 | D | + x: None +24-11-19 20:47:59 | D | + y: sint8 +24-11-19 20:47:59 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:59 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:47:59 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:48:00 | D | - range ratio = [ 1.0000] +24-11-19 20:48:00 | D | sum error = [ 35.0400] +24-11-19 20:48:00 | D | best error = [ 35.0400] +24-11-19 20:48:00 | D | + error = [35.0400] +24-11-19 20:48:00 | D | - Calibrating model.layers.10.self_attn.o_proj.input +24-11-19 20:48:00 | D | - Calibrating model.layers.10.mlp.up_proj.input +24-11-19 20:48:00 | D | - Calibrating model.layers.10.mlp.down_proj.input +24-11-19 20:48:00 | D | - Quantizing model.layers.10.self_attn.q_proj (inputs) +24-11-19 20:48:00 | D | - Quantizing model.layers.10.self_attn.k_proj (inputs) +24-11-19 20:48:00 | D | - Quantizing model.layers.10.self_attn.v_proj (inputs and outputs) +24-11-19 20:48:00 | D | - Quantizing model.layers.10.self_attn.o_proj (inputs) +24-11-19 20:48:00 | D | - Quantizing model.layers.10.self_attn.k_rotary_emb (outputs) +24-11-19 20:48:00 | D | - Quantizing model.layers.10.mlp.gate_proj (inputs) +24-11-19 20:48:00 | D | - Quantizing model.layers.10.mlp.up_proj (inputs) +24-11-19 20:48:00 | D | - Quantizing model.layers.10.mlp.down_proj (inputs) +24-11-19 20:48:06 | D | - Quantizing layer model.layers.11 +24-11-19 20:48:06 | D | - Calibrating model.layers.11.self_attn.v_proj.input +24-11-19 20:48:06 | D | - Calibrating model.layers.11.self_attn.k_rotary_emb.output +24-11-19 20:48:06 | D | + w: None +24-11-19 20:48:06 | D | + x: None +24-11-19 20:48:06 | D | + y: sint8 +24-11-19 20:48:06 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:06 | D | + finished parsing calibration arguments, ram usage: 13.0 +24-11-19 20:48:07 | D | + finished reseting calibrator, ram usage: 13.0 +24-11-19 20:48:07 | D | - range ratio = [ 1.0000] +24-11-19 20:48:07 | D | sum error = [ 25.2779] +24-11-19 20:48:07 | D | best error = [ 25.2779] +24-11-19 20:48:07 | D | + error = [25.2779] +24-11-19 20:48:07 | D | - Calibrating model.layers.11.self_attn.v_proj.output +24-11-19 20:48:07 | D | + w: None +24-11-19 20:48:07 | D | + x: None +24-11-19 20:48:07 | D | + y: sint8 +24-11-19 20:48:07 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:07 | D | + finished parsing calibration arguments, ram usage: 13.1 +24-11-19 20:48:07 | D | + finished reseting calibrator, ram usage: 13.1 +24-11-19 20:48:08 | D | - range ratio = [ 1.0000] +24-11-19 20:48:08 | D | sum error = [ 27.0682] +24-11-19 20:48:08 | D | best error = [ 27.0682] +24-11-19 20:48:08 | D | + error = [27.0682] +24-11-19 20:48:08 | D | - Calibrating model.layers.11.self_attn.o_proj.input +24-11-19 20:48:08 | D | - Calibrating model.layers.11.mlp.up_proj.input +24-11-19 20:48:08 | D | - Calibrating model.layers.11.mlp.down_proj.input +24-11-19 20:48:08 | D | - Quantizing model.layers.11.self_attn.q_proj (inputs) +24-11-19 20:48:08 | D | - Quantizing model.layers.11.self_attn.k_proj (inputs) +24-11-19 20:48:08 | D | - Quantizing model.layers.11.self_attn.v_proj (inputs and outputs) +24-11-19 20:48:08 | D | - Quantizing model.layers.11.self_attn.o_proj (inputs) +24-11-19 20:48:08 | D | - Quantizing model.layers.11.self_attn.k_rotary_emb (outputs) +24-11-19 20:48:08 | D | - Quantizing model.layers.11.mlp.gate_proj (inputs) +24-11-19 20:48:08 | D | - Quantizing model.layers.11.mlp.up_proj (inputs) +24-11-19 20:48:08 | D | - Quantizing model.layers.11.mlp.down_proj (inputs) +24-11-19 20:48:14 | D | - Quantizing layer model.layers.12 +24-11-19 20:48:14 | D | - Calibrating model.layers.12.self_attn.v_proj.input +24-11-19 20:48:14 | D | - Calibrating model.layers.12.self_attn.k_rotary_emb.output +24-11-19 20:48:14 | D | + w: None +24-11-19 20:48:14 | D | + x: None +24-11-19 20:48:14 | D | + y: sint8 +24-11-19 20:48:14 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:14 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:48:14 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:48:15 | D | - range ratio = [ 1.0000] +24-11-19 20:48:15 | D | sum error = [ 33.3716] +24-11-19 20:48:15 | D | best error = [ 33.3716] +24-11-19 20:48:15 | D | + error = [33.3716] +24-11-19 20:48:15 | D | - Calibrating model.layers.12.self_attn.v_proj.output +24-11-19 20:48:15 | D | + w: None +24-11-19 20:48:15 | D | + x: None +24-11-19 20:48:15 | D | + y: sint8 +24-11-19 20:48:15 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:15 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:48:15 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:48:16 | D | - range ratio = [ 1.0000] +24-11-19 20:48:16 | D | sum error = [ 22.4449] +24-11-19 20:48:16 | D | best error = [ 22.4449] +24-11-19 20:48:16 | D | + error = [22.4449] +24-11-19 20:48:16 | D | - Calibrating model.layers.12.self_attn.o_proj.input +24-11-19 20:48:16 | D | - Calibrating model.layers.12.mlp.up_proj.input +24-11-19 20:48:16 | D | - Calibrating model.layers.12.mlp.down_proj.input +24-11-19 20:48:16 | D | - Quantizing model.layers.12.self_attn.q_proj (inputs) +24-11-19 20:48:16 | D | - Quantizing model.layers.12.self_attn.k_proj (inputs) +24-11-19 20:48:16 | D | - Quantizing model.layers.12.self_attn.v_proj (inputs and outputs) +24-11-19 20:48:16 | D | - Quantizing model.layers.12.self_attn.o_proj (inputs) +24-11-19 20:48:16 | D | - Quantizing model.layers.12.self_attn.k_rotary_emb (outputs) +24-11-19 20:48:16 | D | - Quantizing model.layers.12.mlp.gate_proj (inputs) +24-11-19 20:48:16 | D | - Quantizing model.layers.12.mlp.up_proj (inputs) +24-11-19 20:48:16 | D | - Quantizing model.layers.12.mlp.down_proj (inputs) +24-11-19 20:48:22 | D | - Quantizing layer model.layers.13 +24-11-19 20:48:22 | D | - Calibrating model.layers.13.self_attn.v_proj.input +24-11-19 20:48:22 | D | - Calibrating model.layers.13.self_attn.k_rotary_emb.output +24-11-19 20:48:22 | D | + w: None +24-11-19 20:48:22 | D | + x: None +24-11-19 20:48:22 | D | + y: sint8 +24-11-19 20:48:22 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:22 | D | + finished parsing calibration arguments, ram usage: 12.9 +24-11-19 20:48:22 | D | + finished reseting calibrator, ram usage: 13.0 +24-11-19 20:48:23 | D | - range ratio = [ 1.0000] +24-11-19 20:48:23 | D | sum error = [ 26.9409] +24-11-19 20:48:23 | D | best error = [ 26.9409] +24-11-19 20:48:23 | D | + error = [26.9409] +24-11-19 20:48:23 | D | - Calibrating model.layers.13.self_attn.v_proj.output +24-11-19 20:48:23 | D | + w: None +24-11-19 20:48:23 | D | + x: None +24-11-19 20:48:23 | D | + y: sint8 +24-11-19 20:48:23 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:23 | D | + finished parsing calibration arguments, ram usage: 13.1 +24-11-19 20:48:23 | D | + finished reseting calibrator, ram usage: 13.1 +24-11-19 20:48:24 | D | - range ratio = [ 1.0000] +24-11-19 20:48:24 | D | sum error = [ 26.5200] +24-11-19 20:48:24 | D | best error = [ 26.5200] +24-11-19 20:48:24 | D | + error = [26.5200] +24-11-19 20:48:24 | D | - Calibrating model.layers.13.self_attn.o_proj.input +24-11-19 20:48:24 | D | - Calibrating model.layers.13.mlp.up_proj.input +24-11-19 20:48:24 | D | - Calibrating model.layers.13.mlp.down_proj.input +24-11-19 20:48:24 | D | - Quantizing model.layers.13.self_attn.q_proj (inputs) +24-11-19 20:48:24 | D | - Quantizing model.layers.13.self_attn.k_proj (inputs) +24-11-19 20:48:24 | D | - Quantizing model.layers.13.self_attn.v_proj (inputs and outputs) +24-11-19 20:48:24 | D | - Quantizing model.layers.13.self_attn.o_proj (inputs) +24-11-19 20:48:24 | D | - Quantizing model.layers.13.self_attn.k_rotary_emb (outputs) +24-11-19 20:48:24 | D | - Quantizing model.layers.13.mlp.gate_proj (inputs) +24-11-19 20:48:24 | D | - Quantizing model.layers.13.mlp.up_proj (inputs) +24-11-19 20:48:24 | D | - Quantizing model.layers.13.mlp.down_proj (inputs) +24-11-19 20:48:30 | D | - Quantizing layer model.layers.14 +24-11-19 20:48:30 | D | - Calibrating model.layers.14.self_attn.v_proj.input +24-11-19 20:48:31 | D | - Calibrating model.layers.14.self_attn.k_rotary_emb.output +24-11-19 20:48:31 | D | + w: None +24-11-19 20:48:31 | D | + x: None +24-11-19 20:48:31 | D | + y: sint8 +24-11-19 20:48:31 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:31 | D | + finished parsing calibration arguments, ram usage: 12.9 +24-11-19 20:48:31 | D | + finished reseting calibrator, ram usage: 12.9 +24-11-19 20:48:31 | D | - range ratio = [ 1.0000] +24-11-19 20:48:31 | D | sum error = [ 32.1233] +24-11-19 20:48:31 | D | best error = [ 32.1233] +24-11-19 20:48:31 | D | + error = [32.1233] +24-11-19 20:48:31 | D | - Calibrating model.layers.14.self_attn.v_proj.output +24-11-19 20:48:31 | D | + w: None +24-11-19 20:48:31 | D | + x: None +24-11-19 20:48:31 | D | + y: sint8 +24-11-19 20:48:31 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:31 | D | + finished parsing calibration arguments, ram usage: 13.0 +24-11-19 20:48:31 | D | + finished reseting calibrator, ram usage: 13.0 +24-11-19 20:48:32 | D | - range ratio = [ 1.0000] +24-11-19 20:48:32 | D | sum error = [ 25.0331] +24-11-19 20:48:32 | D | best error = [ 25.0331] +24-11-19 20:48:32 | D | + error = [25.0331] +24-11-19 20:48:32 | D | - Calibrating model.layers.14.self_attn.o_proj.input +24-11-19 20:48:32 | D | - Calibrating model.layers.14.mlp.up_proj.input +24-11-19 20:48:32 | D | - Calibrating model.layers.14.mlp.down_proj.input +24-11-19 20:48:32 | D | - Quantizing model.layers.14.self_attn.q_proj (inputs) +24-11-19 20:48:32 | D | - Quantizing model.layers.14.self_attn.k_proj (inputs) +24-11-19 20:48:32 | D | - Quantizing model.layers.14.self_attn.v_proj (inputs and outputs) +24-11-19 20:48:32 | D | - Quantizing model.layers.14.self_attn.o_proj (inputs) +24-11-19 20:48:32 | D | - Quantizing model.layers.14.self_attn.k_rotary_emb (outputs) +24-11-19 20:48:32 | D | - Quantizing model.layers.14.mlp.gate_proj (inputs) +24-11-19 20:48:32 | D | - Quantizing model.layers.14.mlp.up_proj (inputs) +24-11-19 20:48:32 | D | - Quantizing model.layers.14.mlp.down_proj (inputs) +24-11-19 20:48:38 | D | - Quantizing layer model.layers.15 +24-11-19 20:48:38 | D | - Calibrating model.layers.15.self_attn.v_proj.input +24-11-19 20:48:38 | D | - Calibrating model.layers.15.self_attn.k_rotary_emb.output +24-11-19 20:48:38 | D | + w: None +24-11-19 20:48:38 | D | + x: None +24-11-19 20:48:38 | D | + y: sint8 +24-11-19 20:48:38 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:38 | D | + finished parsing calibration arguments, ram usage: 12.6 +24-11-19 20:48:38 | D | + finished reseting calibrator, ram usage: 12.6 +24-11-19 20:48:39 | D | - range ratio = [ 1.0000] +24-11-19 20:48:39 | D | sum error = [ 31.5877] +24-11-19 20:48:39 | D | best error = [ 31.5877] +24-11-19 20:48:39 | D | + error = [31.5877] +24-11-19 20:48:39 | D | - Calibrating model.layers.15.self_attn.v_proj.output +24-11-19 20:48:39 | D | + w: None +24-11-19 20:48:39 | D | + x: None +24-11-19 20:48:39 | D | + y: sint8 +24-11-19 20:48:39 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:39 | D | + finished parsing calibration arguments, ram usage: 12.7 +24-11-19 20:48:39 | D | + finished reseting calibrator, ram usage: 12.7 +24-11-19 20:48:39 | D | - range ratio = [ 1.0000] +24-11-19 20:48:39 | D | sum error = [ 45.9508] +24-11-19 20:48:39 | D | best error = [ 45.9508] +24-11-19 20:48:39 | D | + error = [45.9508] +24-11-19 20:48:40 | D | - Calibrating model.layers.15.self_attn.o_proj.input +24-11-19 20:48:40 | D | - Calibrating model.layers.15.mlp.up_proj.input +24-11-19 20:48:40 | D | - Calibrating model.layers.15.mlp.down_proj.input +24-11-19 20:48:40 | D | - Quantizing model.layers.15.self_attn.q_proj (inputs) +24-11-19 20:48:40 | D | - Quantizing model.layers.15.self_attn.k_proj (inputs) +24-11-19 20:48:40 | D | - Quantizing model.layers.15.self_attn.v_proj (inputs and outputs) +24-11-19 20:48:40 | D | - Quantizing model.layers.15.self_attn.o_proj (inputs) +24-11-19 20:48:40 | D | - Quantizing model.layers.15.self_attn.k_rotary_emb (outputs) +24-11-19 20:48:40 | D | - Quantizing model.layers.15.mlp.gate_proj (inputs) +24-11-19 20:48:40 | D | - Quantizing model.layers.15.mlp.up_proj (inputs) +24-11-19 20:48:40 | D | - Quantizing model.layers.15.mlp.down_proj (inputs) +24-11-19 20:48:45 | D | - Quantizing layer model.layers.16 +24-11-19 20:48:45 | D | - Calibrating model.layers.16.self_attn.v_proj.input +24-11-19 20:48:45 | D | - Calibrating model.layers.16.self_attn.k_rotary_emb.output +24-11-19 20:48:45 | D | + w: None +24-11-19 20:48:45 | D | + x: None +24-11-19 20:48:45 | D | + y: sint8 +24-11-19 20:48:45 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:45 | D | + finished parsing calibration arguments, ram usage: 12.8 +24-11-19 20:48:46 | D | + finished reseting calibrator, ram usage: 12.8 +24-11-19 20:48:46 | D | - range ratio = [ 1.0000] +24-11-19 20:48:46 | D | sum error = [ 35.8231] +24-11-19 20:48:46 | D | best error = [ 35.8231] +24-11-19 20:48:46 | D | + error = [35.8231] +24-11-19 20:48:46 | D | - Calibrating model.layers.16.self_attn.v_proj.output +24-11-19 20:48:46 | D | + w: None +24-11-19 20:48:46 | D | + x: None +24-11-19 20:48:46 | D | + y: sint8 +24-11-19 20:48:46 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:46 | D | + finished parsing calibration arguments, ram usage: 12.6 +24-11-19 20:48:46 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 20:48:47 | D | - range ratio = [ 1.0000] +24-11-19 20:48:47 | D | sum error = [ 37.9238] +24-11-19 20:48:47 | D | best error = [ 37.9238] +24-11-19 20:48:47 | D | + error = [37.9238] +24-11-19 20:48:47 | D | - Calibrating model.layers.16.self_attn.o_proj.input +24-11-19 20:48:47 | D | - Calibrating model.layers.16.mlp.up_proj.input +24-11-19 20:48:47 | D | - Calibrating model.layers.16.mlp.down_proj.input +24-11-19 20:48:47 | D | - Quantizing model.layers.16.self_attn.q_proj (inputs) +24-11-19 20:48:47 | D | - Quantizing model.layers.16.self_attn.k_proj (inputs) +24-11-19 20:48:47 | D | - Quantizing model.layers.16.self_attn.v_proj (inputs and outputs) +24-11-19 20:48:47 | D | - Quantizing model.layers.16.self_attn.o_proj (inputs) +24-11-19 20:48:47 | D | - Quantizing model.layers.16.self_attn.k_rotary_emb (outputs) +24-11-19 20:48:47 | D | - Quantizing model.layers.16.mlp.gate_proj (inputs) +24-11-19 20:48:47 | D | - Quantizing model.layers.16.mlp.up_proj (inputs) +24-11-19 20:48:47 | D | - Quantizing model.layers.16.mlp.down_proj (inputs) +24-11-19 20:48:53 | D | - Quantizing layer model.layers.17 +24-11-19 20:48:53 | D | - Calibrating model.layers.17.self_attn.v_proj.input +24-11-19 20:48:53 | D | - Calibrating model.layers.17.self_attn.k_rotary_emb.output +24-11-19 20:48:53 | D | + w: None +24-11-19 20:48:53 | D | + x: None +24-11-19 20:48:53 | D | + y: sint8 +24-11-19 20:48:53 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:53 | D | + finished parsing calibration arguments, ram usage: 12.8 +24-11-19 20:48:53 | D | + finished reseting calibrator, ram usage: 12.8 +24-11-19 20:48:54 | D | - range ratio = [ 1.0000] +24-11-19 20:48:54 | D | sum error = [ 30.6936] +24-11-19 20:48:54 | D | best error = [ 30.6936] +24-11-19 20:48:54 | D | + error = [30.6936] +24-11-19 20:48:54 | D | - Calibrating model.layers.17.self_attn.v_proj.output +24-11-19 20:48:54 | D | + w: None +24-11-19 20:48:54 | D | + x: None +24-11-19 20:48:54 | D | + y: sint8 +24-11-19 20:48:54 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:54 | D | + finished parsing calibration arguments, ram usage: 12.8 +24-11-19 20:48:54 | D | + finished reseting calibrator, ram usage: 12.8 +24-11-19 20:48:54 | D | - range ratio = [ 1.0000] +24-11-19 20:48:54 | D | sum error = [ 57.3002] +24-11-19 20:48:54 | D | best error = [ 57.3002] +24-11-19 20:48:54 | D | + error = [57.3002] +24-11-19 20:48:54 | D | - Calibrating model.layers.17.self_attn.o_proj.input +24-11-19 20:48:54 | D | - Calibrating model.layers.17.mlp.up_proj.input +24-11-19 20:48:55 | D | - Calibrating model.layers.17.mlp.down_proj.input +24-11-19 20:48:55 | D | - Quantizing model.layers.17.self_attn.q_proj (inputs) +24-11-19 20:48:55 | D | - Quantizing model.layers.17.self_attn.k_proj (inputs) +24-11-19 20:48:55 | D | - Quantizing model.layers.17.self_attn.v_proj (inputs and outputs) +24-11-19 20:48:55 | D | - Quantizing model.layers.17.self_attn.o_proj (inputs) +24-11-19 20:48:55 | D | - Quantizing model.layers.17.self_attn.k_rotary_emb (outputs) +24-11-19 20:48:55 | D | - Quantizing model.layers.17.mlp.gate_proj (inputs) +24-11-19 20:48:55 | D | - Quantizing model.layers.17.mlp.up_proj (inputs) +24-11-19 20:48:55 | D | - Quantizing model.layers.17.mlp.down_proj (inputs) +24-11-19 20:49:00 | D | - Quantizing layer model.layers.18 +24-11-19 20:49:00 | D | - Calibrating model.layers.18.self_attn.v_proj.input +24-11-19 20:49:00 | D | - Calibrating model.layers.18.self_attn.k_rotary_emb.output +24-11-19 20:49:00 | D | + w: None +24-11-19 20:49:00 | D | + x: None +24-11-19 20:49:00 | D | + y: sint8 +24-11-19 20:49:00 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:00 | D | + finished parsing calibration arguments, ram usage: 12.7 +24-11-19 20:49:00 | D | + finished reseting calibrator, ram usage: 12.7 +24-11-19 20:49:00 | D | - range ratio = [ 1.0000] +24-11-19 20:49:00 | D | sum error = [ 25.2760] +24-11-19 20:49:00 | D | best error = [ 25.2760] +24-11-19 20:49:00 | D | + error = [25.2760] +24-11-19 20:49:00 | D | - Calibrating model.layers.18.self_attn.v_proj.output +24-11-19 20:49:00 | D | + w: None +24-11-19 20:49:00 | D | + x: None +24-11-19 20:49:00 | D | + y: sint8 +24-11-19 20:49:00 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:00 | D | + finished parsing calibration arguments, ram usage: 12.8 +24-11-19 20:49:01 | D | + finished reseting calibrator, ram usage: 12.8 +24-11-19 20:49:01 | D | - range ratio = [ 1.0000] +24-11-19 20:49:01 | D | sum error = [ 66.6233] +24-11-19 20:49:01 | D | best error = [ 66.6233] +24-11-19 20:49:01 | D | + error = [66.6233] +24-11-19 20:49:01 | D | - Calibrating model.layers.18.self_attn.o_proj.input +24-11-19 20:49:01 | D | - Calibrating model.layers.18.mlp.up_proj.input +24-11-19 20:49:01 | D | - Calibrating model.layers.18.mlp.down_proj.input +24-11-19 20:49:02 | D | - Quantizing model.layers.18.self_attn.q_proj (inputs) +24-11-19 20:49:02 | D | - Quantizing model.layers.18.self_attn.k_proj (inputs) +24-11-19 20:49:02 | D | - Quantizing model.layers.18.self_attn.v_proj (inputs and outputs) +24-11-19 20:49:02 | D | - Quantizing model.layers.18.self_attn.o_proj (inputs) +24-11-19 20:49:02 | D | - Quantizing model.layers.18.self_attn.k_rotary_emb (outputs) +24-11-19 20:49:02 | D | - Quantizing model.layers.18.mlp.gate_proj (inputs) +24-11-19 20:49:02 | D | - Quantizing model.layers.18.mlp.up_proj (inputs) +24-11-19 20:49:02 | D | - Quantizing model.layers.18.mlp.down_proj (inputs) +24-11-19 20:49:07 | D | - Quantizing layer model.layers.19 +24-11-19 20:49:07 | D | - Calibrating model.layers.19.self_attn.v_proj.input +24-11-19 20:49:07 | D | - Calibrating model.layers.19.self_attn.k_rotary_emb.output +24-11-19 20:49:07 | D | + w: None +24-11-19 20:49:07 | D | + x: None +24-11-19 20:49:07 | D | + y: sint8 +24-11-19 20:49:07 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:07 | D | + finished parsing calibration arguments, ram usage: 12.7 +24-11-19 20:49:07 | D | + finished reseting calibrator, ram usage: 12.7 +24-11-19 20:49:08 | D | - range ratio = [ 1.0000] +24-11-19 20:49:08 | D | sum error = [ 24.1634] +24-11-19 20:49:08 | D | best error = [ 24.1634] +24-11-19 20:49:08 | D | + error = [24.1634] +24-11-19 20:49:08 | D | - Calibrating model.layers.19.self_attn.v_proj.output +24-11-19 20:49:08 | D | + w: None +24-11-19 20:49:08 | D | + x: None +24-11-19 20:49:08 | D | + y: sint8 +24-11-19 20:49:08 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:08 | D | + finished parsing calibration arguments, ram usage: 12.8 +24-11-19 20:49:08 | D | + finished reseting calibrator, ram usage: 12.8 +24-11-19 20:49:09 | D | - range ratio = [ 1.0000] +24-11-19 20:49:09 | D | sum error = [ 62.8229] +24-11-19 20:49:09 | D | best error = [ 62.8229] +24-11-19 20:49:09 | D | + error = [62.8229] +24-11-19 20:49:09 | D | - Calibrating model.layers.19.self_attn.o_proj.input +24-11-19 20:49:09 | D | - Calibrating model.layers.19.mlp.up_proj.input +24-11-19 20:49:09 | D | - Calibrating model.layers.19.mlp.down_proj.input +24-11-19 20:49:09 | D | - Quantizing model.layers.19.self_attn.q_proj (inputs) +24-11-19 20:49:09 | D | - Quantizing model.layers.19.self_attn.k_proj (inputs) +24-11-19 20:49:09 | D | - Quantizing model.layers.19.self_attn.v_proj (inputs and outputs) +24-11-19 20:49:09 | D | - Quantizing model.layers.19.self_attn.o_proj (inputs) +24-11-19 20:49:09 | D | - Quantizing model.layers.19.self_attn.k_rotary_emb (outputs) +24-11-19 20:49:09 | D | - Quantizing model.layers.19.mlp.gate_proj (inputs) +24-11-19 20:49:09 | D | - Quantizing model.layers.19.mlp.up_proj (inputs) +24-11-19 20:49:09 | D | - Quantizing model.layers.19.mlp.down_proj (inputs) +24-11-19 20:49:15 | D | - Quantizing layer model.layers.20 +24-11-19 20:49:15 | D | - Calibrating model.layers.20.self_attn.v_proj.input +24-11-19 20:49:15 | D | - Calibrating model.layers.20.self_attn.k_rotary_emb.output +24-11-19 20:49:15 | D | + w: None +24-11-19 20:49:15 | D | + x: None +24-11-19 20:49:15 | D | + y: sint8 +24-11-19 20:49:15 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:15 | D | + finished parsing calibration arguments, ram usage: 12.7 +24-11-19 20:49:15 | D | + finished reseting calibrator, ram usage: 12.7 +24-11-19 20:49:15 | D | - range ratio = [ 1.0000] +24-11-19 20:49:15 | D | sum error = [ 23.3351] +24-11-19 20:49:15 | D | best error = [ 23.3351] +24-11-19 20:49:15 | D | + error = [23.3351] +24-11-19 20:49:16 | D | - Calibrating model.layers.20.self_attn.v_proj.output +24-11-19 20:49:16 | D | + w: None +24-11-19 20:49:16 | D | + x: None +24-11-19 20:49:16 | D | + y: sint8 +24-11-19 20:49:16 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:16 | D | + finished parsing calibration arguments, ram usage: 12.8 +24-11-19 20:49:16 | D | + finished reseting calibrator, ram usage: 12.8 +24-11-19 20:49:16 | D | - range ratio = [ 1.0000] +24-11-19 20:49:16 | D | sum error = [ 63.3045] +24-11-19 20:49:16 | D | best error = [ 63.3045] +24-11-19 20:49:16 | D | + error = [63.3045] +24-11-19 20:49:16 | D | - Calibrating model.layers.20.self_attn.o_proj.input +24-11-19 20:49:16 | D | - Calibrating model.layers.20.mlp.up_proj.input +24-11-19 20:49:16 | D | - Calibrating model.layers.20.mlp.down_proj.input +24-11-19 20:49:16 | D | - Quantizing model.layers.20.self_attn.q_proj (inputs) +24-11-19 20:49:16 | D | - Quantizing model.layers.20.self_attn.k_proj (inputs) +24-11-19 20:49:16 | D | - Quantizing model.layers.20.self_attn.v_proj (inputs and outputs) +24-11-19 20:49:16 | D | - Quantizing model.layers.20.self_attn.o_proj (inputs) +24-11-19 20:49:16 | D | - Quantizing model.layers.20.self_attn.k_rotary_emb (outputs) +24-11-19 20:49:16 | D | - Quantizing model.layers.20.mlp.gate_proj (inputs) +24-11-19 20:49:16 | D | - Quantizing model.layers.20.mlp.up_proj (inputs) +24-11-19 20:49:16 | D | - Quantizing model.layers.20.mlp.down_proj (inputs) +24-11-19 20:49:22 | D | - Quantizing layer model.layers.21 +24-11-19 20:49:22 | D | - Calibrating model.layers.21.self_attn.v_proj.input +24-11-19 20:49:22 | D | - Calibrating model.layers.21.self_attn.k_rotary_emb.output +24-11-19 20:49:22 | D | + w: None +24-11-19 20:49:22 | D | + x: None +24-11-19 20:49:22 | D | + y: sint8 +24-11-19 20:49:22 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:22 | D | + finished parsing calibration arguments, ram usage: 12.6 +24-11-19 20:49:22 | D | + finished reseting calibrator, ram usage: 12.6 +24-11-19 20:49:23 | D | - range ratio = [ 1.0000] +24-11-19 20:49:23 | D | sum error = [ 37.2038] +24-11-19 20:49:23 | D | best error = [ 37.2038] +24-11-19 20:49:23 | D | + error = [37.2038] +24-11-19 20:49:23 | D | - Calibrating model.layers.21.self_attn.v_proj.output +24-11-19 20:49:23 | D | + w: None +24-11-19 20:49:23 | D | + x: None +24-11-19 20:49:23 | D | + y: sint8 +24-11-19 20:49:23 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:23 | D | + finished parsing calibration arguments, ram usage: 12.6 +24-11-19 20:49:23 | D | + finished reseting calibrator, ram usage: 12.6 +24-11-19 20:49:23 | D | - range ratio = [ 1.0000] +24-11-19 20:49:23 | D | sum error = [ 67.9431] +24-11-19 20:49:23 | D | best error = [ 67.9431] +24-11-19 20:49:23 | D | + error = [67.9431] +24-11-19 20:49:23 | D | - Calibrating model.layers.21.self_attn.o_proj.input +24-11-19 20:49:24 | D | - Calibrating model.layers.21.mlp.up_proj.input +24-11-19 20:49:24 | D | - Calibrating model.layers.21.mlp.down_proj.input +24-11-19 20:49:24 | D | - Quantizing model.layers.21.self_attn.q_proj (inputs) +24-11-19 20:49:24 | D | - Quantizing model.layers.21.self_attn.k_proj (inputs) +24-11-19 20:49:24 | D | - Quantizing model.layers.21.self_attn.v_proj (inputs and outputs) +24-11-19 20:49:24 | D | - Quantizing model.layers.21.self_attn.o_proj (inputs) +24-11-19 20:49:24 | D | - Quantizing model.layers.21.self_attn.k_rotary_emb (outputs) +24-11-19 20:49:24 | D | - Quantizing model.layers.21.mlp.gate_proj (inputs) +24-11-19 20:49:24 | D | - Quantizing model.layers.21.mlp.up_proj (inputs) +24-11-19 20:49:24 | D | - Quantizing model.layers.21.mlp.down_proj (inputs) +24-11-19 20:49:29 | D | - Quantizing layer model.layers.22 +24-11-19 20:49:29 | D | - Calibrating model.layers.22.self_attn.v_proj.input +24-11-19 20:49:29 | D | - Calibrating model.layers.22.self_attn.k_rotary_emb.output +24-11-19 20:49:29 | D | + w: None +24-11-19 20:49:29 | D | + x: None +24-11-19 20:49:29 | D | + y: sint8 +24-11-19 20:49:29 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:29 | D | + finished parsing calibration arguments, ram usage: 12.5 +24-11-19 20:49:29 | D | + finished reseting calibrator, ram usage: 12.5 +24-11-19 20:49:30 | D | - range ratio = [ 1.0000] +24-11-19 20:49:30 | D | sum error = [ 30.8216] +24-11-19 20:49:30 | D | best error = [ 30.8216] +24-11-19 20:49:30 | D | + error = [30.8216] +24-11-19 20:49:30 | D | - Calibrating model.layers.22.self_attn.v_proj.output +24-11-19 20:49:30 | D | + w: None +24-11-19 20:49:30 | D | + x: None +24-11-19 20:49:30 | D | + y: sint8 +24-11-19 20:49:30 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:30 | D | + finished parsing calibration arguments, ram usage: 12.5 +24-11-19 20:49:30 | D | + finished reseting calibrator, ram usage: 12.6 +24-11-19 20:49:30 | D | - range ratio = [ 1.0000] +24-11-19 20:49:30 | D | sum error = [ 70.2739] +24-11-19 20:49:30 | D | best error = [ 70.2739] +24-11-19 20:49:30 | D | + error = [70.2739] +24-11-19 20:49:30 | D | - Calibrating model.layers.22.self_attn.o_proj.input +24-11-19 20:49:31 | D | - Calibrating model.layers.22.mlp.up_proj.input +24-11-19 20:49:31 | D | - Calibrating model.layers.22.mlp.down_proj.input +24-11-19 20:49:31 | D | - Quantizing model.layers.22.self_attn.q_proj (inputs) +24-11-19 20:49:31 | D | - Quantizing model.layers.22.self_attn.k_proj (inputs) +24-11-19 20:49:31 | D | - Quantizing model.layers.22.self_attn.v_proj (inputs and outputs) +24-11-19 20:49:31 | D | - Quantizing model.layers.22.self_attn.o_proj (inputs) +24-11-19 20:49:31 | D | - Quantizing model.layers.22.self_attn.k_rotary_emb (outputs) +24-11-19 20:49:31 | D | - Quantizing model.layers.22.mlp.gate_proj (inputs) +24-11-19 20:49:31 | D | - Quantizing model.layers.22.mlp.up_proj (inputs) +24-11-19 20:49:31 | D | - Quantizing model.layers.22.mlp.down_proj (inputs) +24-11-19 20:49:36 | D | - Quantizing layer model.layers.23 +24-11-19 20:49:36 | D | - Calibrating model.layers.23.self_attn.v_proj.input +24-11-19 20:49:36 | D | - Calibrating model.layers.23.self_attn.k_rotary_emb.output +24-11-19 20:49:36 | D | + w: None +24-11-19 20:49:36 | D | + x: None +24-11-19 20:49:36 | D | + y: sint8 +24-11-19 20:49:36 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:36 | D | + finished parsing calibration arguments, ram usage: 12.5 +24-11-19 20:49:37 | D | + finished reseting calibrator, ram usage: 12.5 +24-11-19 20:49:37 | D | - range ratio = [ 1.0000] +24-11-19 20:49:37 | D | sum error = [ 31.5411] +24-11-19 20:49:37 | D | best error = [ 31.5411] +24-11-19 20:49:37 | D | + error = [31.5411] +24-11-19 20:49:37 | D | - Calibrating model.layers.23.self_attn.v_proj.output +24-11-19 20:49:37 | D | + w: None +24-11-19 20:49:37 | D | + x: None +24-11-19 20:49:37 | D | + y: sint8 +24-11-19 20:49:37 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:37 | D | + finished parsing calibration arguments, ram usage: 12.5 +24-11-19 20:49:37 | D | + finished reseting calibrator, ram usage: 12.6 +24-11-19 20:49:38 | D | - range ratio = [ 1.0000] +24-11-19 20:49:38 | D | sum error = [ 76.3069] +24-11-19 20:49:38 | D | best error = [ 76.3069] +24-11-19 20:49:38 | D | + error = [76.3069] +24-11-19 20:49:38 | D | - Calibrating model.layers.23.self_attn.o_proj.input +24-11-19 20:49:38 | D | - Calibrating model.layers.23.mlp.up_proj.input +24-11-19 20:49:38 | D | - Calibrating model.layers.23.mlp.down_proj.input +24-11-19 20:49:38 | D | - Quantizing model.layers.23.self_attn.q_proj (inputs) +24-11-19 20:49:38 | D | - Quantizing model.layers.23.self_attn.k_proj (inputs) +24-11-19 20:49:38 | D | - Quantizing model.layers.23.self_attn.v_proj (inputs and outputs) +24-11-19 20:49:38 | D | - Quantizing model.layers.23.self_attn.o_proj (inputs) +24-11-19 20:49:38 | D | - Quantizing model.layers.23.self_attn.k_rotary_emb (outputs) +24-11-19 20:49:38 | D | - Quantizing model.layers.23.mlp.gate_proj (inputs) +24-11-19 20:49:38 | D | - Quantizing model.layers.23.mlp.up_proj (inputs) +24-11-19 20:49:38 | D | - Quantizing model.layers.23.mlp.down_proj (inputs) +24-11-19 20:49:43 | D | - Quantizing layer model.layers.24 +24-11-19 20:49:43 | D | - Calibrating model.layers.24.self_attn.v_proj.input +24-11-19 20:49:43 | D | - Calibrating model.layers.24.self_attn.k_rotary_emb.output +24-11-19 20:49:43 | D | + w: None +24-11-19 20:49:43 | D | + x: None +24-11-19 20:49:43 | D | + y: sint8 +24-11-19 20:49:43 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:43 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 20:49:44 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 20:49:44 | D | - range ratio = [ 1.0000] +24-11-19 20:49:44 | D | sum error = [ 33.4371] +24-11-19 20:49:44 | D | best error = [ 33.4371] +24-11-19 20:49:44 | D | + error = [33.4371] +24-11-19 20:49:44 | D | - Calibrating model.layers.24.self_attn.v_proj.output +24-11-19 20:49:44 | D | + w: None +24-11-19 20:49:44 | D | + x: None +24-11-19 20:49:44 | D | + y: sint8 +24-11-19 20:49:44 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:44 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 20:49:44 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 20:49:45 | D | - range ratio = [ 1.0000] +24-11-19 20:49:45 | D | sum error = [ 87.4198] +24-11-19 20:49:45 | D | best error = [ 87.4198] +24-11-19 20:49:45 | D | + error = [87.4198] +24-11-19 20:49:45 | D | - Calibrating model.layers.24.self_attn.o_proj.input +24-11-19 20:49:45 | D | - Calibrating model.layers.24.mlp.up_proj.input +24-11-19 20:49:45 | D | - Calibrating model.layers.24.mlp.down_proj.input +24-11-19 20:49:45 | D | - Quantizing model.layers.24.self_attn.q_proj (inputs) +24-11-19 20:49:45 | D | - Quantizing model.layers.24.self_attn.k_proj (inputs) +24-11-19 20:49:45 | D | - Quantizing model.layers.24.self_attn.v_proj (inputs and outputs) +24-11-19 20:49:45 | D | - Quantizing model.layers.24.self_attn.o_proj (inputs) +24-11-19 20:49:45 | D | - Quantizing model.layers.24.self_attn.k_rotary_emb (outputs) +24-11-19 20:49:45 | D | - Quantizing model.layers.24.mlp.gate_proj (inputs) +24-11-19 20:49:45 | D | - Quantizing model.layers.24.mlp.up_proj (inputs) +24-11-19 20:49:45 | D | - Quantizing model.layers.24.mlp.down_proj (inputs) +24-11-19 20:49:51 | D | - Quantizing layer model.layers.25 +24-11-19 20:49:51 | D | - Calibrating model.layers.25.self_attn.v_proj.input +24-11-19 20:49:51 | D | - Calibrating model.layers.25.self_attn.k_rotary_emb.output +24-11-19 20:49:51 | D | + w: None +24-11-19 20:49:51 | D | + x: None +24-11-19 20:49:51 | D | + y: sint8 +24-11-19 20:49:51 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:51 | D | + finished parsing calibration arguments, ram usage: 12.8 +24-11-19 20:49:51 | D | + finished reseting calibrator, ram usage: 12.6 +24-11-19 20:49:51 | D | - range ratio = [ 1.0000] +24-11-19 20:49:51 | D | sum error = [ 46.6329] +24-11-19 20:49:51 | D | best error = [ 46.6329] +24-11-19 20:49:51 | D | + error = [46.6329] +24-11-19 20:49:51 | D | - Calibrating model.layers.25.self_attn.v_proj.output +24-11-19 20:49:51 | D | + w: None +24-11-19 20:49:51 | D | + x: None +24-11-19 20:49:51 | D | + y: sint8 +24-11-19 20:49:51 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:51 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 20:49:52 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 20:49:52 | D | - range ratio = [ 1.0000] +24-11-19 20:49:52 | D | sum error = [ 104.4932] +24-11-19 20:49:52 | D | best error = [ 104.4932] +24-11-19 20:49:52 | D | + error = [104.4932] +24-11-19 20:49:52 | D | - Calibrating model.layers.25.self_attn.o_proj.input +24-11-19 20:49:52 | D | - Calibrating model.layers.25.mlp.up_proj.input +24-11-19 20:49:52 | D | - Calibrating model.layers.25.mlp.down_proj.input +24-11-19 20:49:52 | D | - Quantizing model.layers.25.self_attn.q_proj (inputs) +24-11-19 20:49:52 | D | - Quantizing model.layers.25.self_attn.k_proj (inputs) +24-11-19 20:49:52 | D | - Quantizing model.layers.25.self_attn.v_proj (inputs and outputs) +24-11-19 20:49:52 | D | - Quantizing model.layers.25.self_attn.o_proj (inputs) +24-11-19 20:49:52 | D | - Quantizing model.layers.25.self_attn.k_rotary_emb (outputs) +24-11-19 20:49:52 | D | - Quantizing model.layers.25.mlp.gate_proj (inputs) +24-11-19 20:49:52 | D | - Quantizing model.layers.25.mlp.up_proj (inputs) +24-11-19 20:49:52 | D | - Quantizing model.layers.25.mlp.down_proj (inputs) +24-11-19 20:49:57 | D | - Quantizing layer model.layers.26 +24-11-19 20:49:57 | D | - Calibrating model.layers.26.self_attn.v_proj.input +24-11-19 20:49:57 | D | - Calibrating model.layers.26.self_attn.k_rotary_emb.output +24-11-19 20:49:57 | D | + w: None +24-11-19 20:49:57 | D | + x: None +24-11-19 20:49:57 | D | + y: sint8 +24-11-19 20:49:57 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:57 | D | + finished parsing calibration arguments, ram usage: 12.8 +24-11-19 20:49:58 | D | + finished reseting calibrator, ram usage: 12.8 +24-11-19 20:49:58 | D | - range ratio = [ 1.0000] +24-11-19 20:49:58 | D | sum error = [ 39.4237] +24-11-19 20:49:58 | D | best error = [ 39.4237] +24-11-19 20:49:58 | D | + error = [39.4237] +24-11-19 20:49:58 | D | - Calibrating model.layers.26.self_attn.v_proj.output +24-11-19 20:49:58 | D | + w: None +24-11-19 20:49:58 | D | + x: None +24-11-19 20:49:58 | D | + y: sint8 +24-11-19 20:49:58 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:58 | D | + finished parsing calibration arguments, ram usage: 12.8 +24-11-19 20:49:59 | D | + finished reseting calibrator, ram usage: 12.8 +24-11-19 20:49:59 | D | - range ratio = [ 1.0000] +24-11-19 20:49:59 | D | sum error = [ 88.7769] +24-11-19 20:49:59 | D | best error = [ 88.7769] +24-11-19 20:49:59 | D | + error = [88.7769] +24-11-19 20:49:59 | D | - Calibrating model.layers.26.self_attn.o_proj.input +24-11-19 20:49:59 | D | - Calibrating model.layers.26.mlp.up_proj.input +24-11-19 20:49:59 | D | - Calibrating model.layers.26.mlp.down_proj.input +24-11-19 20:49:59 | D | - Quantizing model.layers.26.self_attn.q_proj (inputs) +24-11-19 20:49:59 | D | - Quantizing model.layers.26.self_attn.k_proj (inputs) +24-11-19 20:49:59 | D | - Quantizing model.layers.26.self_attn.v_proj (inputs and outputs) +24-11-19 20:49:59 | D | - Quantizing model.layers.26.self_attn.o_proj (inputs) +24-11-19 20:49:59 | D | - Quantizing model.layers.26.self_attn.k_rotary_emb (outputs) +24-11-19 20:49:59 | D | - Quantizing model.layers.26.mlp.gate_proj (inputs) +24-11-19 20:49:59 | D | - Quantizing model.layers.26.mlp.up_proj (inputs) +24-11-19 20:49:59 | D | - Quantizing model.layers.26.mlp.down_proj (inputs) +24-11-19 20:50:05 | D | - Quantizing layer model.layers.27 +24-11-19 20:50:05 | D | - Calibrating model.layers.27.self_attn.v_proj.input +24-11-19 20:50:05 | D | - Calibrating model.layers.27.self_attn.k_rotary_emb.output +24-11-19 20:50:05 | D | + w: None +24-11-19 20:50:05 | D | + x: None +24-11-19 20:50:05 | D | + y: sint8 +24-11-19 20:50:05 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:50:05 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 20:50:05 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 20:50:05 | D | - range ratio = [ 1.0000] +24-11-19 20:50:05 | D | sum error = [ 45.0525] +24-11-19 20:50:05 | D | best error = [ 45.0525] +24-11-19 20:50:05 | D | + error = [45.0525] +24-11-19 20:50:06 | D | - Calibrating model.layers.27.self_attn.v_proj.output +24-11-19 20:50:06 | D | + w: None +24-11-19 20:50:06 | D | + x: None +24-11-19 20:50:06 | D | + y: sint8 +24-11-19 20:50:06 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:50:06 | D | + finished parsing calibration arguments, ram usage: 12.3 +24-11-19 20:50:06 | D | + finished reseting calibrator, ram usage: 12.3 +24-11-19 20:50:06 | D | - range ratio = [ 1.0000] +24-11-19 20:50:06 | D | sum error = [ 116.6503] +24-11-19 20:50:06 | D | best error = [ 116.6503] +24-11-19 20:50:06 | D | + error = [116.6503] +24-11-19 20:50:06 | D | - Calibrating model.layers.27.self_attn.o_proj.input +24-11-19 20:50:06 | D | - Calibrating model.layers.27.mlp.up_proj.input +24-11-19 20:50:06 | D | - Calibrating model.layers.27.mlp.down_proj.input +24-11-19 20:50:06 | D | - Quantizing model.layers.27.self_attn.q_proj (inputs) +24-11-19 20:50:06 | D | - Quantizing model.layers.27.self_attn.k_proj (inputs) +24-11-19 20:50:06 | D | - Quantizing model.layers.27.self_attn.v_proj (inputs and outputs) +24-11-19 20:50:06 | D | - Quantizing model.layers.27.self_attn.o_proj (inputs) +24-11-19 20:50:06 | D | - Quantizing model.layers.27.self_attn.k_rotary_emb (outputs) +24-11-19 20:50:06 | D | - Quantizing model.layers.27.mlp.gate_proj (inputs) +24-11-19 20:50:06 | D | - Quantizing model.layers.27.mlp.up_proj (inputs) +24-11-19 20:50:06 | D | - Quantizing model.layers.27.mlp.down_proj (inputs) +24-11-19 20:50:12 | D | - Quantizing layer model.layers.28 +24-11-19 20:50:12 | D | - Calibrating model.layers.28.self_attn.v_proj.input +24-11-19 20:50:12 | D | - Calibrating model.layers.28.self_attn.k_rotary_emb.output +24-11-19 20:50:12 | D | + w: None +24-11-19 20:50:12 | D | + x: None +24-11-19 20:50:12 | D | + y: sint8 +24-11-19 20:50:12 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:50:12 | D | + finished parsing calibration arguments, ram usage: 11.9 +24-11-19 20:50:12 | D | + finished reseting calibrator, ram usage: 11.9 +24-11-19 20:50:12 | D | - range ratio = [ 1.0000] +24-11-19 20:50:12 | D | sum error = [ 56.3077] +24-11-19 20:50:12 | D | best error = [ 56.3077] +24-11-19 20:50:12 | D | + error = [56.3077] +24-11-19 20:50:12 | D | - Calibrating model.layers.28.self_attn.v_proj.output +24-11-19 20:50:12 | D | + w: None +24-11-19 20:50:12 | D | + x: None +24-11-19 20:50:12 | D | + y: sint8 +24-11-19 20:50:12 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:50:12 | D | + finished parsing calibration arguments, ram usage: 11.9 +24-11-19 20:50:13 | D | + finished reseting calibrator, ram usage: 11.9 +24-11-19 20:50:13 | D | - range ratio = [ 1.0000] +24-11-19 20:50:13 | D | sum error = [ 121.8090] +24-11-19 20:50:13 | D | best error = [ 121.8090] +24-11-19 20:50:13 | D | + error = [121.8090] +24-11-19 20:50:13 | D | - Calibrating model.layers.28.self_attn.o_proj.input +24-11-19 20:50:13 | D | - Calibrating model.layers.28.mlp.up_proj.input +24-11-19 20:50:13 | D | - Calibrating model.layers.28.mlp.down_proj.input +24-11-19 20:50:13 | D | - Quantizing model.layers.28.self_attn.q_proj (inputs) +24-11-19 20:50:13 | D | - Quantizing model.layers.28.self_attn.k_proj (inputs) +24-11-19 20:50:13 | D | - Quantizing model.layers.28.self_attn.v_proj (inputs and outputs) +24-11-19 20:50:13 | D | - Quantizing model.layers.28.self_attn.o_proj (inputs) +24-11-19 20:50:13 | D | - Quantizing model.layers.28.self_attn.k_rotary_emb (outputs) +24-11-19 20:50:13 | D | - Quantizing model.layers.28.mlp.gate_proj (inputs) +24-11-19 20:50:13 | D | - Quantizing model.layers.28.mlp.up_proj (inputs) +24-11-19 20:50:13 | D | - Quantizing model.layers.28.mlp.down_proj (inputs) +24-11-19 20:50:19 | D | - Quantizing layer model.layers.29 +24-11-19 20:50:19 | D | - Calibrating model.layers.29.self_attn.v_proj.input +24-11-19 20:50:19 | D | - Calibrating model.layers.29.self_attn.k_rotary_emb.output +24-11-19 20:50:19 | D | + w: None +24-11-19 20:50:19 | D | + x: None +24-11-19 20:50:19 | D | + y: sint8 +24-11-19 20:50:19 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:50:19 | D | + finished parsing calibration arguments, ram usage: 12.0 +24-11-19 20:50:19 | D | + finished reseting calibrator, ram usage: 12.0 +24-11-19 20:50:20 | D | - range ratio = [ 1.0000] +24-11-19 20:50:20 | D | sum error = [ 76.2966] +24-11-19 20:50:20 | D | best error = [ 76.2966] +24-11-19 20:50:20 | D | + error = [76.2966] +24-11-19 20:50:20 | D | - Calibrating model.layers.29.self_attn.v_proj.output +24-11-19 20:50:20 | D | + w: None +24-11-19 20:50:20 | D | + x: None +24-11-19 20:50:20 | D | + y: sint8 +24-11-19 20:50:20 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:50:20 | D | + finished parsing calibration arguments, ram usage: 12.0 +24-11-19 20:50:20 | D | + finished reseting calibrator, ram usage: 12.0 +24-11-19 20:50:20 | D | - range ratio = [ 1.0000] +24-11-19 20:50:20 | D | sum error = [ 147.9003] +24-11-19 20:50:20 | D | best error = [ 147.9003] +24-11-19 20:50:20 | D | + error = [147.9003] +24-11-19 20:50:21 | D | - Calibrating model.layers.29.self_attn.o_proj.input +24-11-19 20:50:21 | D | - Calibrating model.layers.29.mlp.up_proj.input +24-11-19 20:50:21 | D | - Calibrating model.layers.29.mlp.down_proj.input +24-11-19 20:50:21 | D | - Quantizing model.layers.29.self_attn.q_proj (inputs) +24-11-19 20:50:21 | D | - Quantizing model.layers.29.self_attn.k_proj (inputs) +24-11-19 20:50:21 | D | - Quantizing model.layers.29.self_attn.v_proj (inputs and outputs) +24-11-19 20:50:21 | D | - Quantizing model.layers.29.self_attn.o_proj (inputs) +24-11-19 20:50:21 | D | - Quantizing model.layers.29.self_attn.k_rotary_emb (outputs) +24-11-19 20:50:21 | D | - Quantizing model.layers.29.mlp.gate_proj (inputs) +24-11-19 20:50:21 | D | - Quantizing model.layers.29.mlp.up_proj (inputs) +24-11-19 20:50:21 | D | - Quantizing model.layers.29.mlp.down_proj (inputs) +24-11-19 20:50:26 | D | - Quantizing layer model.layers.30 +24-11-19 20:50:26 | D | - Calibrating model.layers.30.self_attn.v_proj.input +24-11-19 20:50:26 | D | - Calibrating model.layers.30.self_attn.k_rotary_emb.output +24-11-19 20:50:26 | D | + w: None +24-11-19 20:50:26 | D | + x: None +24-11-19 20:50:26 | D | + y: sint8 +24-11-19 20:50:26 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:50:26 | D | + finished parsing calibration arguments, ram usage: 11.9 +24-11-19 20:50:26 | D | + finished reseting calibrator, ram usage: 11.9 +24-11-19 20:50:27 | D | - range ratio = [ 1.0000] +24-11-19 20:50:27 | D | sum error = [ 76.0929] +24-11-19 20:50:27 | D | best error = [ 76.0929] +24-11-19 20:50:27 | D | + error = [76.0929] +24-11-19 20:50:27 | D | - Calibrating model.layers.30.self_attn.v_proj.output +24-11-19 20:50:27 | D | + w: None +24-11-19 20:50:27 | D | + x: None +24-11-19 20:50:27 | D | + y: sint8 +24-11-19 20:50:27 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:50:27 | D | + finished parsing calibration arguments, ram usage: 11.9 +24-11-19 20:50:27 | D | + finished reseting calibrator, ram usage: 11.9 +24-11-19 20:50:27 | D | - range ratio = [ 1.0000] +24-11-19 20:50:27 | D | sum error = [ 184.7832] +24-11-19 20:50:27 | D | best error = [ 184.7832] +24-11-19 20:50:27 | D | + error = [184.7832] +24-11-19 20:50:28 | D | - Calibrating model.layers.30.self_attn.o_proj.input +24-11-19 20:50:28 | D | - Calibrating model.layers.30.mlp.up_proj.input +24-11-19 20:50:28 | D | - Calibrating model.layers.30.mlp.down_proj.input +24-11-19 20:50:28 | D | - Quantizing model.layers.30.self_attn.q_proj (inputs) +24-11-19 20:50:28 | D | - Quantizing model.layers.30.self_attn.k_proj (inputs) +24-11-19 20:50:28 | D | - Quantizing model.layers.30.self_attn.v_proj (inputs and outputs) +24-11-19 20:50:28 | D | - Quantizing model.layers.30.self_attn.o_proj (inputs) +24-11-19 20:50:28 | D | - Quantizing model.layers.30.self_attn.k_rotary_emb (outputs) +24-11-19 20:50:28 | D | - Quantizing model.layers.30.mlp.gate_proj (inputs) +24-11-19 20:50:28 | D | - Quantizing model.layers.30.mlp.up_proj (inputs) +24-11-19 20:50:28 | D | - Quantizing model.layers.30.mlp.down_proj (inputs) +24-11-19 20:50:33 | D | - Quantizing layer model.layers.31 +24-11-19 20:50:33 | D | - Calibrating model.layers.31.self_attn.v_proj.input +24-11-19 20:50:33 | D | - Calibrating model.layers.31.self_attn.k_rotary_emb.output +24-11-19 20:50:33 | D | + w: None +24-11-19 20:50:33 | D | + x: None +24-11-19 20:50:33 | D | + y: sint8 +24-11-19 20:50:33 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:50:33 | D | + finished parsing calibration arguments, ram usage: 12.0 +24-11-19 20:50:33 | D | + finished reseting calibrator, ram usage: 12.0 +24-11-19 20:50:34 | D | - range ratio = [ 1.0000] +24-11-19 20:50:34 | D | sum error = [ 95.3470] +24-11-19 20:50:34 | D | best error = [ 95.3470] +24-11-19 20:50:34 | D | + error = [95.3470] +24-11-19 20:50:34 | D | - Calibrating model.layers.31.self_attn.v_proj.output +24-11-19 20:50:34 | D | + w: None +24-11-19 20:50:34 | D | + x: None +24-11-19 20:50:34 | D | + y: sint8 +24-11-19 20:50:34 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:50:34 | D | + finished parsing calibration arguments, ram usage: 12.0 +24-11-19 20:50:34 | D | + finished reseting calibrator, ram usage: 12.0 +24-11-19 20:50:34 | D | - range ratio = [ 1.0000] +24-11-19 20:50:34 | D | sum error = [ 148.1132] +24-11-19 20:50:34 | D | best error = [ 148.1132] +24-11-19 20:50:34 | D | + error = [148.1132] +24-11-19 20:50:34 | D | - Calibrating model.layers.31.self_attn.o_proj.input +24-11-19 20:50:34 | D | - Calibrating model.layers.31.mlp.up_proj.input +24-11-19 20:50:35 | D | - Calibrating model.layers.31.mlp.down_proj.input +24-11-19 20:50:35 | D | - Quantizing model.layers.31.self_attn.q_proj (inputs) +24-11-19 20:50:35 | D | - Quantizing model.layers.31.self_attn.k_proj (inputs) +24-11-19 20:50:35 | D | - Quantizing model.layers.31.self_attn.v_proj (inputs and outputs) +24-11-19 20:50:35 | D | - Quantizing model.layers.31.self_attn.o_proj (inputs) +24-11-19 20:50:35 | D | - Quantizing model.layers.31.self_attn.k_rotary_emb (outputs) +24-11-19 20:50:35 | D | - Quantizing model.layers.31.mlp.gate_proj (inputs) +24-11-19 20:50:35 | D | - Quantizing model.layers.31.mlp.up_proj (inputs) +24-11-19 20:50:35 | D | - Quantizing model.layers.31.mlp.down_proj (inputs) +24-11-19 20:50:35 | I | - Saving activation quantizer settings to runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/smooth.proj.OutputsError.Manual.Layer.d2.en1.sn1-attn.OutputsError.Manual.Layer.d2.en1.sn1/smooth.proj.[a.AbsMax.b.AbsMax]-attn.[a.AbsMax.b.AbsMax]/smooth.proj.a0p1.b0p9-attn.a0p5.b0/smooth.proj.skip.[out_proj+qkv_proj+up_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt +24-11-19 20:50:35 | I | - Linking activation quantizer settings to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.proj.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.proj.a0p1.b0p9.[AbsMax].[fc2].attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.200844.RUNNING/model/acts.pt +24-11-19 20:50:35 | I | * Evaluating model +24-11-19 20:50:35 | W | `pretrained` model kwarg is not of type `str`. Many other model arguments may be ignored. Please do not launch via accelerate or use `parallelize=True` if passing an existing model this way. +24-11-19 20:50:35 | I | Using model type 'default' +24-11-19 20:50:35 | W | Passed an already-initialized model through `pretrained`, assuming single-process call to evaluate() or custom distributed integration +24-11-19 20:50:35 | I | - Evaluator: gptq +24-11-19 20:50:35 | I | - Tasks: ['wikitext'] +24-11-19 20:50:35 | I | - Batch_size: 8 +24-11-19 20:50:35 | I | + Max_seq_length: 2048 +24-11-19 20:50:35 | D | Starting new HTTPS connection (10): huggingface.co:443 +24-11-19 20:50:45 | W | Using the latest cached version of the dataset since wikitext couldn't be found on the Hugging Face Hub +24-11-19 20:50:45 | W | Found the latest cached dataset configuration 'wikitext-2-raw-v1' at /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3 (last modified on Tue Oct 8 19:51:38 2024). +24-11-19 20:50:45 | D | Attempting to acquire lock 23438409872976 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:50:45 | D | Lock 23438409872976 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:50:45 | D | open file: /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3/dataset_info.json +24-11-19 20:50:45 | D | Attempting to release lock 23438409872976 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:50:45 | D | Lock 23438409872976 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:51:17 | I | - Results: +24-11-19 20:51:17 | I | | Task |Version| Metric |Value | |Stderr| +24-11-19 20:51:17 | I | |--------|------:|---------------|-----:|---|-----:| +24-11-19 20:51:17 | I | |wikitext| 1|word_perplexity|7.9634|± |7.9634| +24-11-19 20:51:17 | I | +24-11-19 20:51:17 | I | + Max_seq_length: 4096 +24-11-19 20:51:17 | D | Starting new HTTPS connection (11): huggingface.co:443 +24-11-19 20:51:23 | W | Using the latest cached version of the dataset since wikitext couldn't be found on the Hugging Face Hub +24-11-19 20:51:23 | W | Found the latest cached dataset configuration 'wikitext-2-raw-v1' at /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3 (last modified on Tue Oct 8 19:51:38 2024). +24-11-19 20:51:23 | D | Attempting to acquire lock 23438703785408 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:51:23 | D | Lock 23438703785408 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:51:23 | D | open file: /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3/dataset_info.json +24-11-19 20:51:23 | D | Attempting to release lock 23438703785408 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:51:23 | D | Lock 23438703785408 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:51:51 | I | - Results: +24-11-19 20:51:51 | I | | Task |Version| Metric |Value | |Stderr| +24-11-19 20:51:51 | I | |--------|------:|---------------|-----:|---|-----:| +24-11-19 20:51:51 | I | |wikitext| 1|word_perplexity|7.3677|± |7.3677| +24-11-19 20:51:51 | I | +24-11-19 20:51:51 | I | * Saving results to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-smooth.proj.attn-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-smth.proj.a0p1.b0p9.[AbsMax].[fc2].attn.a0p5.b0.[AbsMax]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.200844 diff --git a/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.201603/config-241119.201603.yaml b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.201603/config-241119.201603.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9219f6f4b979b106b1fdd9e56d64df7380d29618 --- /dev/null +++ b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.201603/config-241119.201603.yaml @@ -0,0 +1,129 @@ +cache: + root: runs/shang + path: + rotation: runs/shang/llm/cache/quant/rotation/hadamard/llama-3-8b-instruct-gradient-1048k.pt + reorder: '' + smooth: '' + wgts: runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt + acts: runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt +output: + root: runs/shang + dirname: skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0] + job: run +model: + name: llama-3-8b-instruct-gradient-1048k + family: llama-3 + path: /home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k + root: '' + local_path: /home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k + local_root: /home/yujunlin/models + dtype: torch.float16 +eval: + num_gpus: 1 + batch_size: 8 + tasks: + - wikitext + max_seq_length: -4096 + evaluators: + - gptq +quant: + wgts: + dtype: sint8 + zero_point: null + group_shapes: + - - 1 + - -1 + - -1 + scale_dtypes: + - torch.float16 + intermediate_dtypes: [] + intermediate_levels: [] + needs_dequant_saturation: false + skips: [] + enable_kernel_gptq: true + kernel_gptq: + damp_percentage: 0.01 + block_size: 128 + num_inv_tries: 250 + hessian_block_size: 512 + enable_calib_range: true + calib_range: + degree: 2 + objective: OutputsError + strategy: GridSearch + granularity: Group + element_batch_size: 64 + sample_batch_size: -1 + element_size: 512 + sample_size: -1 + pre_reshape: true + outputs_device: cpu + ratio: 1.0 + max_shrink: 0.2 + max_expand: 1.0 + num_grids: 80 + allow_scale: false + skips: [] + ipts: + dtype: sint8 + zero_point: null + group_shapes: + - - 1 + - -1 + - -1 + scale_dtypes: + - torch.float16 + skips: [] + static: false + enable_calib_range: false + opts: + dtype: sint8 + zero_point: null + group_shapes: + - - -1 + - -1 + - -1 + scale_dtypes: + - torch.float16 + skips: + - attn_q + static: true + enable_calib_range: true + calib_range: + degree: 2 + objective: OutputsError + strategy: Manual + granularity: Layer + element_batch_size: -1 + sample_batch_size: -1 + element_size: -1 + sample_size: -1 + pre_reshape: true + outputs_device: cpu + ratio: 1.0 + max_shrink: 0.2 + max_expand: 1.0 + num_grids: 80 + allow_scale: false + skips: [] + calib: + data: pileval + num_samples: 128 + path: mit-han-lab/pile-val-backup + seq_length: 1024 + min_seq_length: 0 + max_seq_length: 0 + local_path: '' + enable_rotation: true + rotation: + random: false + transforms: + - 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+version https://git-lfs.github.com/spec/v1 +oid sha256:09fce87b9c670a5de807dfb7255b6300c5e4e211f90613d2fca4c714a8160e18 +size 5593150 diff --git a/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.201603/results-241119.201603.json b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.201603/results-241119.201603.json new file mode 100644 index 0000000000000000000000000000000000000000..933dace429d1bdb232de6589d41668ebe9fc07d4 --- /dev/null +++ b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.201603/results-241119.201603.json @@ -0,0 +1,32 @@ +{ + "gptq": { + "2048": { + "results": { + "wikitext": { + "word_perplexity": 7.995572407861825 + } + }, + "versions": { + "wikitext": 1 + }, + "config": { + "model": "llama-3-8b-instruct-gradient-1048k" + }, + "model": "llama-3-8b-instruct-gradient-1048k" + }, + "4096": { + "results": { + "wikitext": { + "word_perplexity": 7.403749074472347 + } + }, + "versions": { + "wikitext": 1 + }, + "config": { + "model": "llama-3-8b-instruct-gradient-1048k" + }, + "model": "llama-3-8b-instruct-gradient-1048k" + } + } +} \ No newline at end of file diff --git a/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.201603/run-241119.201603.log b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.201603/run-241119.201603.log new file mode 100644 index 0000000000000000000000000000000000000000..b5f0aee14f0b05bd2d8639f142f4e3242d58571d --- /dev/null +++ b/runs/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.201603/run-241119.201603.log @@ -0,0 +1,15508 @@ +24-11-19 20:16:03 | I | === Configurations === +24-11-19 20:16:03 | I | LlmPtqRunConfig( +24-11-19 20:16:03 | I | cache=LlmCacheConfig( +24-11-19 20:16:03 | I | root=runs/shang, +24-11-19 20:16:03 | I | dirpath=LlmQuantCacheConfig( +24-11-19 20:16:03 | I | rotation=runs/shang/llm/cache/quant/rotation/hadamard, +24-11-19 20:16:03 | I | reorder=, +24-11-19 20:16:03 | I | smooth=, +24-11-19 20:16:03 | I | wgts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[], +24-11-19 20:16:03 | I | acts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]), +24-11-19 20:16:03 | I | path=LlmQuantCacheConfig( +24-11-19 20:16:03 | I | rotation=runs/shang/llm/cache/quant/rotation/hadamard/llama-3-8b-instruct-gradient-1048k.pt, +24-11-19 20:16:03 | I | reorder=, +24-11-19 20:16:03 | I | smooth=, +24-11-19 20:16:03 | I | wgts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt, +24-11-19 20:16:03 | I | acts=runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt)), +24-11-19 20:16:03 | I | output=OutputConfig( +24-11-19 20:16:03 | I | root=runs/shang, +24-11-19 20:16:03 | I | dirname=skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0], +24-11-19 20:16:03 | I | job=run, +24-11-19 20:16:03 | I | dirpath=runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0], +24-11-19 20:16:03 | I | timestamp=241119.201603), +24-11-19 20:16:03 | I | model=LlmModelConfig( +24-11-19 20:16:03 | I | name=llama-3-8b-instruct-gradient-1048k, +24-11-19 20:16:03 | I | family=llama-3, +24-11-19 20:16:03 | I | path=/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k, +24-11-19 20:16:03 | I | root=, +24-11-19 20:16:03 | I | local_path=/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k, +24-11-19 20:16:03 | I | local_root=/home/yujunlin/models, +24-11-19 20:16:03 | I | size=8.0, +24-11-19 20:16:03 | I | variant=instruct-gradient-1048k, +24-11-19 20:16:03 | I | dtype=torch.float16, +24-11-19 20:16:03 | I | orig_dtype=torch.bfloat16), +24-11-19 20:16:03 | I | eval=LlmEvalConfig( +24-11-19 20:16:03 | I | num_gpus=1, +24-11-19 20:16:03 | I | batch_size=8, +24-11-19 20:16:03 | I | tasks=['wikitext'], +24-11-19 20:16:03 | I | max_seq_length=-4096, +24-11-19 20:16:03 | I | evaluators=['gptq']), +24-11-19 20:16:03 | I | quant=LlmQuantConfig( +24-11-19 20:16:03 | I | wgts=LlmWeightQuantizerConfig( +24-11-19 20:16:03 | I | dtype=sint8, +24-11-19 20:16:03 | I | zero_point=None, +24-11-19 20:16:03 | I | group_shapes=((1, -1, -1),), +24-11-19 20:16:03 | I | scale_dtypes=(torch.float16,), +24-11-19 20:16:03 | I | intermediate_dtypes=(), +24-11-19 20:16:03 | I | intermediate_levels=(), +24-11-19 20:16:03 | I | needs_dequant_saturation=False, +24-11-19 20:16:03 | I | skips=[], +24-11-19 20:16:03 | I | static=True, +24-11-19 20:16:03 | I | kernel_gptq=QuantGptqConfig( +24-11-19 20:16:03 | I | damp_percentage=0.01, +24-11-19 20:16:03 | I | block_size=128, +24-11-19 20:16:03 | I | num_inv_tries=250, +24-11-19 20:16:03 | I | hessian_block_size=512), +24-11-19 20:16:03 | I | calib_range=SkipBasedDynamicRangeCalibConfig( +24-11-19 20:16:03 | I | degree=2, +24-11-19 20:16:03 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 20:16:03 | I | strategy=SearchBasedCalibStrategy.GridSearch, +24-11-19 20:16:03 | I | granularity=SearchBasedCalibGranularity.Group, +24-11-19 20:16:03 | I | element_batch_size=64, +24-11-19 20:16:03 | I | sample_batch_size=-1, +24-11-19 20:16:03 | I | element_size=512, +24-11-19 20:16:03 | I | sample_size=-1, +24-11-19 20:16:03 | I | pre_reshape=True, +24-11-19 20:16:03 | I | outputs_device=cpu, +24-11-19 20:16:03 | I | ratio=1.0, +24-11-19 20:16:03 | I | max_shrink=0.2, +24-11-19 20:16:03 | I | max_expand=1.0, +24-11-19 20:16:03 | I | num_grids=80, +24-11-19 20:16:03 | I | allow_scale=False, +24-11-19 20:16:03 | I | skips=[])), +24-11-19 20:16:03 | I | ipts=LlmActivationQuantizerConfig( +24-11-19 20:16:03 | I | dtype=sint8, +24-11-19 20:16:03 | I | zero_point=None, +24-11-19 20:16:03 | I | group_shapes=((1, -1, -1),), +24-11-19 20:16:03 | I | scale_dtypes=(torch.float16,), +24-11-19 20:16:03 | I | intermediate_dtypes=(), +24-11-19 20:16:03 | I | intermediate_levels=(), +24-11-19 20:16:03 | I | needs_dequant_saturation=False, +24-11-19 20:16:03 | I | skips=[], +24-11-19 20:16:03 | I | static=False, +24-11-19 20:16:03 | I | kernel_gptq=None, +24-11-19 20:16:03 | I | calib_range=None), +24-11-19 20:16:03 | I | opts=LlmActivationQuantizerConfig( +24-11-19 20:16:03 | I | dtype=sint8, +24-11-19 20:16:03 | I | zero_point=None, +24-11-19 20:16:03 | I | group_shapes=((-1, -1, -1),), +24-11-19 20:16:03 | I | scale_dtypes=(torch.float16,), +24-11-19 20:16:03 | I | intermediate_dtypes=(), +24-11-19 20:16:03 | I | intermediate_levels=(), +24-11-19 20:16:03 | I | needs_dequant_saturation=False, +24-11-19 20:16:03 | I | skips=['attn_q'], +24-11-19 20:16:03 | I | static=True, +24-11-19 20:16:03 | I | kernel_gptq=None, +24-11-19 20:16:03 | I | calib_range=SkipBasedDynamicRangeCalibConfig( +24-11-19 20:16:03 | I | degree=2, +24-11-19 20:16:03 | I | objective=SearchBasedCalibObjective.OutputsError, +24-11-19 20:16:03 | I | strategy=SearchBasedCalibStrategy.Manual, +24-11-19 20:16:03 | I | granularity=SearchBasedCalibGranularity.Layer, +24-11-19 20:16:03 | I | element_batch_size=-1, +24-11-19 20:16:03 | I | sample_batch_size=-1, +24-11-19 20:16:03 | I | element_size=-1, +24-11-19 20:16:03 | I | sample_size=-1, +24-11-19 20:16:03 | I | pre_reshape=True, +24-11-19 20:16:03 | I | outputs_device=cpu, +24-11-19 20:16:03 | I | ratio=1.0, +24-11-19 20:16:03 | I | max_shrink=0.2, +24-11-19 20:16:03 | I | max_expand=1.0, +24-11-19 20:16:03 | I | num_grids=80, +24-11-19 20:16:03 | I | allow_scale=False, +24-11-19 20:16:03 | I | skips=[])), +24-11-19 20:16:03 | I | calib=LlmCalibDataLoaderConfig( +24-11-19 20:16:03 | I | data=pileval, +24-11-19 20:16:03 | I | num_samples=128, +24-11-19 20:16:03 | I | batch_size=1, +24-11-19 20:16:03 | I | path=mit-han-lab/pile-val-backup, +24-11-19 20:16:03 | I | seq_length=1024, +24-11-19 20:16:03 | I | min_seq_length=0, +24-11-19 20:16:03 | I | max_seq_length=0, +24-11-19 20:16:03 | I | local_path=), +24-11-19 20:16:03 | I | rotation=QuantRotationConfig( +24-11-19 20:16:03 | I | random=False, +24-11-19 20:16:03 | I | transforms=['out_proj']), +24-11-19 20:16:03 | I | reorder=None, +24-11-19 20:16:03 | I | smooth=None, +24-11-19 20:16:03 | I | develop_dtype=torch.float32), +24-11-19 20:16:03 | I | seed=12345, +24-11-19 20:16:03 | I | skip_eval=False, +24-11-19 20:16:03 | I | load_from=, +24-11-19 20:16:03 | I | save_model=true, +24-11-19 20:16:03 | I | copy_on_save=False) +24-11-19 20:16:03 | I | === Dumped Configurations === +24-11-19 20:16:03 | I | { 'cache': { 'path': { 'acts': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt', +24-11-19 20:16:03 | I | 'reorder': '', +24-11-19 20:16:03 | I | 'rotation': 'runs/shang/llm/cache/quant/rotation/hadamard/llama-3-8b-instruct-gradient-1048k.pt', +24-11-19 20:16:03 | I | 'smooth': '', +24-11-19 20:16:03 | I | 'wgts': 'runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt'}, +24-11-19 20:16:03 | I | 'root': 'runs/shang'}, +24-11-19 20:16:03 | I | 'copy_on_save': False, +24-11-19 20:16:03 | I | 'eval': {'batch_size': 8, 'evaluators': ['gptq'], 'max_seq_length': -4096, 'num_gpus': 1, 'tasks': ['wikitext']}, +24-11-19 20:16:03 | I | 'load_from': '', +24-11-19 20:16:03 | I | 'model': { 'dtype': 'torch.float16', +24-11-19 20:16:03 | I | 'family': 'llama-3', +24-11-19 20:16:03 | I | 'local_path': '/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k', +24-11-19 20:16:03 | I | 'local_root': '/home/yujunlin/models', +24-11-19 20:16:03 | I | 'name': 'llama-3-8b-instruct-gradient-1048k', +24-11-19 20:16:03 | I | 'path': '/home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k', +24-11-19 20:16:03 | I | 'root': ''}, +24-11-19 20:16:03 | I | 'output': { 'dirname': 'skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]', +24-11-19 20:16:03 | I | 'job': 'run', +24-11-19 20:16:03 | I | 'root': 'runs/shang'}, +24-11-19 20:16:03 | I | 'quant': { 'calib': { 'data': 'pileval', +24-11-19 20:16:03 | I | 'local_path': '', +24-11-19 20:16:03 | I | 'max_seq_length': 0, +24-11-19 20:16:03 | I | 'min_seq_length': 0, +24-11-19 20:16:03 | I | 'num_samples': 128, +24-11-19 20:16:03 | I | 'path': 'mit-han-lab/pile-val-backup', +24-11-19 20:16:03 | I | 'seq_length': 1024}, +24-11-19 20:16:03 | I | 'develop_dtype': 'torch.float32', +24-11-19 20:16:03 | I | 'enable_reorder': False, +24-11-19 20:16:03 | I | 'enable_rotation': True, +24-11-19 20:16:03 | I | 'enable_smooth': False, +24-11-19 20:16:03 | I | 'ipts': { 'dtype': 'sint8', +24-11-19 20:16:03 | I | 'enable_calib_range': False, +24-11-19 20:16:03 | I | 'group_shapes': [[1, -1, -1]], +24-11-19 20:16:03 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 20:16:03 | I | 'skips': [], +24-11-19 20:16:03 | I | 'static': False, +24-11-19 20:16:03 | I | 'zero_point': None}, +24-11-19 20:16:03 | I | 'opts': { 'calib_range': { 'allow_scale': False, +24-11-19 20:16:03 | I | 'degree': 2, +24-11-19 20:16:03 | I | 'element_batch_size': -1, +24-11-19 20:16:03 | I | 'element_size': -1, +24-11-19 20:16:03 | I | 'granularity': 'Layer', +24-11-19 20:16:03 | I | 'max_expand': 1.0, +24-11-19 20:16:03 | I | 'max_shrink': 0.2, +24-11-19 20:16:03 | I | 'num_grids': 80, +24-11-19 20:16:03 | I | 'objective': 'OutputsError', +24-11-19 20:16:03 | I | 'outputs_device': 'cpu', +24-11-19 20:16:03 | I | 'pre_reshape': True, +24-11-19 20:16:03 | I | 'ratio': 1.0, +24-11-19 20:16:03 | I | 'sample_batch_size': -1, +24-11-19 20:16:03 | I | 'sample_size': -1, +24-11-19 20:16:03 | I | 'skips': [], +24-11-19 20:16:03 | I | 'strategy': 'Manual'}, +24-11-19 20:16:03 | I | 'dtype': 'sint8', +24-11-19 20:16:03 | I | 'enable_calib_range': True, +24-11-19 20:16:03 | I | 'group_shapes': [[-1, -1, -1]], +24-11-19 20:16:03 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 20:16:03 | I | 'skips': ['attn_q'], +24-11-19 20:16:03 | I | 'static': True, +24-11-19 20:16:03 | I | 'zero_point': None}, +24-11-19 20:16:03 | I | 'rotation': {'random': False, 'transforms': ['out_proj']}, +24-11-19 20:16:03 | I | 'wgts': { 'calib_range': { 'allow_scale': False, +24-11-19 20:16:03 | I | 'degree': 2, +24-11-19 20:16:03 | I | 'element_batch_size': 64, +24-11-19 20:16:03 | I | 'element_size': 512, +24-11-19 20:16:03 | I | 'granularity': 'Group', +24-11-19 20:16:03 | I | 'max_expand': 1.0, +24-11-19 20:16:03 | I | 'max_shrink': 0.2, +24-11-19 20:16:03 | I | 'num_grids': 80, +24-11-19 20:16:03 | I | 'objective': 'OutputsError', +24-11-19 20:16:03 | I | 'outputs_device': 'cpu', +24-11-19 20:16:03 | I | 'pre_reshape': True, +24-11-19 20:16:03 | I | 'ratio': 1.0, +24-11-19 20:16:03 | I | 'sample_batch_size': -1, +24-11-19 20:16:03 | I | 'sample_size': -1, +24-11-19 20:16:03 | I | 'skips': [], +24-11-19 20:16:03 | I | 'strategy': 'GridSearch'}, +24-11-19 20:16:03 | I | 'dtype': 'sint8', +24-11-19 20:16:03 | I | 'enable_calib_range': True, +24-11-19 20:16:03 | I | 'enable_kernel_gptq': True, +24-11-19 20:16:03 | I | 'group_shapes': [[1, -1, -1]], +24-11-19 20:16:03 | I | 'intermediate_dtypes': [], +24-11-19 20:16:03 | I | 'intermediate_levels': [], +24-11-19 20:16:03 | I | 'kernel_gptq': { 'block_size': 128, +24-11-19 20:16:03 | I | 'damp_percentage': 0.01, +24-11-19 20:16:03 | I | 'hessian_block_size': 512, +24-11-19 20:16:03 | I | 'num_inv_tries': 250}, +24-11-19 20:16:03 | I | 'needs_dequant_saturation': False, +24-11-19 20:16:03 | I | 'scale_dtypes': ['torch.float16'], +24-11-19 20:16:03 | I | 'skips': [], +24-11-19 20:16:03 | I | 'zero_point': None}}, +24-11-19 20:16:03 | I | 'save_model': 'true', +24-11-19 20:16:03 | I | 'seed': 12345, +24-11-19 20:16:03 | I | 'skip_eval': False} +24-11-19 20:16:03 | I | === Output Directory === +24-11-19 20:16:03 | I | runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.201603 +24-11-19 20:16:03 | I | === Start Evaluating === +24-11-19 20:16:03 | I | * Building model llama-3-8b-instruct-gradient-1048k from /home/yujunlin/models/llama-3/llama-3-8b-instruct-gradient-1048k +24-11-19 20:16:04 | I | We will use 90% of the memory on device 0 for storing the model, and 10% for the buffer to avoid OOM. You can set `max_memory` in to a higher value to use more memory (at your own risk). +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.0.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.1.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.2.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.3.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.4.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.5.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.6.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.7.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.8.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.9.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.10.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.11.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.12.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.13.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.14.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.15.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.16.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.17.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.18.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.19.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.20.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.21.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.22.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.23.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.24.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.25.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.26.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.27.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.28.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.29.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.30.self_attn +24-11-19 20:16:09 | I | - Patching LlamaSdpaAttention.forward in model.layers.31.self_attn +24-11-19 20:16:09 | I | * Rotating model +24-11-19 20:16:09 | I | - Loading rotation from runs/shang/llm/cache/quant/rotation/hadamard/llama-3-8b-instruct-gradient-1048k.pt +24-11-19 20:16:09 | D | - Transforming norm and linear in model.layers.0 +24-11-19 20:16:09 | D | - Transforming norm and linear in model.layers.1 +24-11-19 20:16:09 | D | - Transforming norm and linear in model.layers.2 +24-11-19 20:16:09 | D | - Transforming norm and linear in model.layers.3 +24-11-19 20:16:09 | D | - Transforming norm and linear in model.layers.4 +24-11-19 20:16:09 | D | - Transforming norm and linear in model.layers.5 +24-11-19 20:16:09 | D | - Transforming norm and linear in model.layers.6 +24-11-19 20:16:09 | D | - Transforming norm and linear in model.layers.7 +24-11-19 20:16:09 | D | - Transforming norm and linear in model.layers.8 +24-11-19 20:16:10 | D | - Transforming norm and linear in model.layers.9 +24-11-19 20:16:10 | D | - Transforming norm and linear in model.layers.10 +24-11-19 20:16:10 | D | - Transforming norm and linear in model.layers.11 +24-11-19 20:16:10 | D | - Transforming norm and linear in model.layers.12 +24-11-19 20:16:10 | D | - Transforming norm and linear in model.layers.13 +24-11-19 20:16:10 | D | - Transforming norm and linear in model.layers.14 +24-11-19 20:16:10 | D | - Transforming norm and linear in model.layers.15 +24-11-19 20:16:10 | D | - Transforming norm and linear in model.layers.16 +24-11-19 20:16:10 | D | - Transforming norm and linear in model.layers.17 +24-11-19 20:16:10 | D | - Transforming norm and linear in model.layers.18 +24-11-19 20:16:10 | D | - Transforming norm and linear in model.layers.19 +24-11-19 20:16:11 | D | - Transforming norm and linear in model.layers.20 +24-11-19 20:16:11 | D | - Transforming norm and linear in model.layers.21 +24-11-19 20:16:11 | D | - Transforming norm and linear in model.layers.22 +24-11-19 20:16:11 | D | - Transforming norm and linear in model.layers.23 +24-11-19 20:16:11 | D | - Transforming norm and linear in model.layers.24 +24-11-19 20:16:11 | D | - Transforming norm and linear in model.layers.25 +24-11-19 20:16:11 | D | - Transforming norm and linear in model.layers.26 +24-11-19 20:16:11 | D | - Transforming norm and linear in model.layers.27 +24-11-19 20:16:11 | D | - Transforming norm and linear in model.layers.28 +24-11-19 20:16:11 | D | - Transforming norm and linear in model.layers.29 +24-11-19 20:16:11 | D | - Transforming norm and linear in model.layers.30 +24-11-19 20:16:11 | D | - Transforming norm and linear in model.layers.31 +24-11-19 20:16:12 | D | - Transforming model.norm +24-11-19 20:16:12 | D | - Rotating model.embed_tokens +24-11-19 20:16:12 | D | - Rotating model.layers.0 +24-11-19 20:16:12 | D | - Rotating model.layers.0.self_attn.q_proj (in) +24-11-19 20:16:12 | D | - Rotating model.layers.0.self_attn.k_proj (in) +24-11-19 20:16:12 | D | - Rotating model.layers.0.self_attn.v_proj (in) +24-11-19 20:16:12 | D | - Rotating model.layers.0.self_attn.o_proj (out) +24-11-19 20:16:12 | D | - Rotating model.layers.0.self_attn.v_proj (out) +24-11-19 20:16:12 | D | - Rotating model.layers.0.self_attn.o_proj (in) +24-11-19 20:16:12 | D | - Rotating model.layers.0.mlp.up_proj (in) +24-11-19 20:16:12 | D | - Rotating model.layers.0.mlp.gate_proj (in) +24-11-19 20:16:12 | D | - Rotating model.layers.0.mlp.down_proj (out) +24-11-19 20:16:12 | D | - Rotating model.layers.1 +24-11-19 20:16:12 | D | - Rotating model.layers.1.self_attn.q_proj (in) +24-11-19 20:16:12 | D | - Rotating model.layers.1.self_attn.k_proj (in) +24-11-19 20:16:12 | D | - Rotating model.layers.1.self_attn.v_proj (in) +24-11-19 20:16:12 | D | - Rotating model.layers.1.self_attn.o_proj (out) +24-11-19 20:16:12 | D | - Rotating model.layers.1.self_attn.v_proj (out) +24-11-19 20:16:12 | D | - Rotating model.layers.1.self_attn.o_proj (in) +24-11-19 20:16:12 | D | - Rotating model.layers.1.mlp.up_proj (in) +24-11-19 20:16:12 | D | - Rotating model.layers.1.mlp.gate_proj (in) +24-11-19 20:16:12 | D | - Rotating model.layers.1.mlp.down_proj (out) +24-11-19 20:16:12 | D | - Rotating model.layers.2 +24-11-19 20:16:12 | D | - Rotating model.layers.2.self_attn.q_proj (in) +24-11-19 20:16:12 | D | - Rotating model.layers.2.self_attn.k_proj (in) +24-11-19 20:16:12 | D | - Rotating model.layers.2.self_attn.v_proj (in) +24-11-19 20:16:12 | D | - Rotating model.layers.2.self_attn.o_proj (out) +24-11-19 20:16:12 | D | - Rotating model.layers.2.self_attn.v_proj (out) +24-11-19 20:16:12 | D | - Rotating model.layers.2.self_attn.o_proj (in) +24-11-19 20:16:12 | D | - Rotating model.layers.2.mlp.up_proj (in) +24-11-19 20:16:12 | D | - Rotating model.layers.2.mlp.gate_proj (in) +24-11-19 20:16:12 | D | - Rotating model.layers.2.mlp.down_proj (out) +24-11-19 20:16:12 | D | - Rotating model.layers.3 +24-11-19 20:16:12 | D | - Rotating model.layers.3.self_attn.q_proj (in) +24-11-19 20:16:12 | D | - Rotating model.layers.3.self_attn.k_proj (in) +24-11-19 20:16:12 | D | - Rotating model.layers.3.self_attn.v_proj (in) +24-11-19 20:16:12 | D | - Rotating model.layers.3.self_attn.o_proj (out) +24-11-19 20:16:12 | D | - Rotating model.layers.3.self_attn.v_proj (out) +24-11-19 20:16:12 | D | - Rotating model.layers.3.self_attn.o_proj (in) +24-11-19 20:16:12 | D | - 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Rotating model.layers.20 +24-11-19 20:16:14 | D | - Rotating model.layers.20.self_attn.q_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.20.self_attn.k_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.20.self_attn.v_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.20.self_attn.o_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.20.self_attn.v_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.20.self_attn.o_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.20.mlp.up_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.20.mlp.gate_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.20.mlp.down_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.21 +24-11-19 20:16:14 | D | - Rotating model.layers.21.self_attn.q_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.21.self_attn.k_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.21.self_attn.v_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.21.self_attn.o_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.21.self_attn.v_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.21.self_attn.o_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.21.mlp.up_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.21.mlp.gate_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.21.mlp.down_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.22 +24-11-19 20:16:14 | D | - Rotating model.layers.22.self_attn.q_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.22.self_attn.k_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.22.self_attn.v_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.22.self_attn.o_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.22.self_attn.v_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.22.self_attn.o_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.22.mlp.up_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.22.mlp.gate_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.22.mlp.down_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.23 +24-11-19 20:16:14 | D | - Rotating model.layers.23.self_attn.q_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.23.self_attn.k_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.23.self_attn.v_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.23.self_attn.o_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.23.self_attn.v_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.23.self_attn.o_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.23.mlp.up_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.23.mlp.gate_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.23.mlp.down_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.24 +24-11-19 20:16:14 | D | - Rotating model.layers.24.self_attn.q_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.24.self_attn.k_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.24.self_attn.v_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.24.self_attn.o_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.24.self_attn.v_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.24.self_attn.o_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.24.mlp.up_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.24.mlp.gate_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.24.mlp.down_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.25 +24-11-19 20:16:14 | D | - Rotating model.layers.25.self_attn.q_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.25.self_attn.k_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.25.self_attn.v_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.25.self_attn.o_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.25.self_attn.v_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.25.self_attn.o_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.25.mlp.up_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.25.mlp.gate_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.25.mlp.down_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.26 +24-11-19 20:16:14 | D | - Rotating model.layers.26.self_attn.q_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.26.self_attn.k_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.26.self_attn.v_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.26.self_attn.o_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.26.self_attn.v_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.26.self_attn.o_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.26.mlp.up_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.26.mlp.gate_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.26.mlp.down_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.27 +24-11-19 20:16:14 | D | - Rotating model.layers.27.self_attn.q_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.27.self_attn.k_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.27.self_attn.v_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.27.self_attn.o_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.27.self_attn.v_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.27.self_attn.o_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.27.mlp.up_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.27.mlp.gate_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.27.mlp.down_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.28 +24-11-19 20:16:14 | D | - Rotating model.layers.28.self_attn.q_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.28.self_attn.k_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.28.self_attn.v_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.28.self_attn.o_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.28.self_attn.v_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.28.self_attn.o_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.28.mlp.up_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.28.mlp.gate_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.28.mlp.down_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.29 +24-11-19 20:16:14 | D | - Rotating model.layers.29.self_attn.q_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.29.self_attn.k_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.29.self_attn.v_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.29.self_attn.o_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.29.self_attn.v_proj (out) +24-11-19 20:16:14 | D | - Rotating model.layers.29.self_attn.o_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.29.mlp.up_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.29.mlp.gate_proj (in) +24-11-19 20:16:14 | D | - Rotating model.layers.29.mlp.down_proj (out) +24-11-19 20:16:15 | D | - Rotating model.layers.30 +24-11-19 20:16:15 | D | - Rotating model.layers.30.self_attn.q_proj (in) +24-11-19 20:16:15 | D | - Rotating model.layers.30.self_attn.k_proj (in) +24-11-19 20:16:15 | D | - Rotating model.layers.30.self_attn.v_proj (in) +24-11-19 20:16:15 | D | - Rotating model.layers.30.self_attn.o_proj (out) +24-11-19 20:16:15 | D | - Rotating model.layers.30.self_attn.v_proj (out) +24-11-19 20:16:15 | D | - Rotating model.layers.30.self_attn.o_proj (in) +24-11-19 20:16:15 | D | - Rotating model.layers.30.mlp.up_proj (in) +24-11-19 20:16:15 | D | - Rotating model.layers.30.mlp.gate_proj (in) +24-11-19 20:16:15 | D | - Rotating model.layers.30.mlp.down_proj (out) +24-11-19 20:16:15 | D | - Rotating model.layers.31 +24-11-19 20:16:15 | D | - Rotating model.layers.31.self_attn.q_proj (in) +24-11-19 20:16:15 | D | - Rotating model.layers.31.self_attn.k_proj (in) +24-11-19 20:16:15 | D | - Rotating model.layers.31.self_attn.v_proj (in) +24-11-19 20:16:15 | D | - Rotating model.layers.31.self_attn.o_proj (out) +24-11-19 20:16:15 | D | - Rotating model.layers.31.self_attn.v_proj (out) +24-11-19 20:16:15 | D | - Rotating model.layers.31.self_attn.o_proj (in) +24-11-19 20:16:15 | D | - Rotating model.layers.31.mlp.up_proj (in) +24-11-19 20:16:15 | D | - Rotating model.layers.31.mlp.gate_proj (in) +24-11-19 20:16:15 | D | - Rotating model.layers.31.mlp.down_proj (out) +24-11-19 20:16:15 | D | - Rotating lm_head (in) +24-11-19 20:16:15 | I | - Linking rotation to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.201603.RUNNING/model/rotation.pt +24-11-19 20:16:15 | I | * Development dtype is torch.float32 +24-11-19 20:16:15 | I | * Quantizing weights +24-11-19 20:16:15 | I | - Generating weight quantizer settings +24-11-19 20:16:15 | D | Starting new HTTPS connection (1): huggingface.co:443 +24-11-19 20:16:38 | D | Starting new HTTPS connection (2): huggingface.co:443 +24-11-19 20:16:54 | D | Starting new HTTPS connection (1): s3.amazonaws.com:443 +24-11-19 20:17:12 | W | Repo card metadata block was not found. Setting CardData to empty. +24-11-19 20:17:12 | D | Starting new HTTPS connection (3): huggingface.co:443 +24-11-19 20:17:25 | W | Using the latest cached version of the dataset since mit-han-lab/pile-val-backup couldn't be found on the Hugging Face Hub +24-11-19 20:17:25 | W | Found the latest cached dataset configuration 'default' at /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4 (last modified on Tue Oct 8 18:58:39 2024). +24-11-19 20:17:25 | D | Attempting to acquire lock 23438954660976 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:17:25 | D | Lock 23438954660976 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:17:25 | D | open file: /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4/dataset_info.json +24-11-19 20:17:25 | D | Attempting to release lock 23438954660976 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:17:25 | D | Lock 23438954660976 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:17:46 | D | - Quantizing layer model.layers.0 +24-11-19 20:17:46 | D | - Calibrating model.layers.0.self_attn.q_proj.weight +24-11-19 20:17:46 | D | + w: sint8 +24-11-19 20:17:46 | D | + x: None +24-11-19 20:17:46 | D | + y: None +24-11-19 20:17:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:17:46 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:17:46 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:17:46 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:17:46 | D | - range ratio = [ 1.0000] +24-11-19 20:17:46 | D | sum error = [ 0.1833] +24-11-19 20:17:46 | D | best error = [ 0.1833] +24-11-19 20:17:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:17:59 | D | sum error = [ 0.1883, 0.1847, 0.1907, 0.1910, 0.1938] +24-11-19 20:17:59 | D | best error = [ 0.1833, 0.1833, 0.1833, 0.1833, 0.1833] +24-11-19 20:17:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:17:59 | D | sum error = [ 0.2076, 0.2210, 0.2253, 0.2490, 0.2604] +24-11-19 20:17:59 | D | best error = [ 0.1833, 0.1833, 0.1833, 0.1833, 0.1833] +24-11-19 20:17:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:17:59 | D | sum error = [ 0.2845, 0.3097, 0.3318, 0.3718, 0.4041] +24-11-19 20:17:59 | D | best error = [ 0.1833, 0.1833, 0.1833, 0.1833, 0.1833] +24-11-19 20:17:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:17:59 | D | sum error = [ 0.4481, 0.4892, 0.5353, 0.6011, 0.6569] +24-11-19 20:17:59 | D | best error = [ 0.1833, 0.1833, 0.1833, 0.1833, 0.1833] +24-11-19 20:17:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:17:59 | D | sum error = [ 0.7304, 0.8075, 0.8816, 0.9667, 1.0548] +24-11-19 20:17:59 | D | best error = [ 0.1833, 0.1833, 0.1833, 0.1833, 0.1833] +24-11-19 20:17:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:17:59 | D | sum error = [ 1.1506, 1.2637, 1.3806, 1.5186, 1.6606] +24-11-19 20:17:59 | D | best error = [ 0.1833, 0.1833, 0.1833, 0.1833, 0.1833] +24-11-19 20:17:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:17:59 | D | sum error = [ 1.8239, 1.9922, 2.1854, 2.3927, 2.6116] +24-11-19 20:17:59 | D | best error = [ 0.1833, 0.1833, 0.1833, 0.1833, 0.1833] +24-11-19 20:17:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:17:59 | D | sum error = [ 2.8536, 3.1102, 3.3827, 3.6893, 4.0176] +24-11-19 20:17:59 | D | best error = [ 0.1833, 0.1833, 0.1833, 0.1833, 0.1833] +24-11-19 20:17:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:17:59 | D | sum error = [ 4.3806, 4.7584, 5.1700, 5.6191, 6.0972] +24-11-19 20:17:59 | D | best error = [ 0.1833, 0.1833, 0.1833, 0.1833, 0.1833] +24-11-19 20:17:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:17:59 | D | sum error = [ 6.6125, 7.1741, 7.7687, 8.4119, 9.1186] +24-11-19 20:17:59 | D | best error = [ 0.1833, 0.1833, 0.1833, 0.1833, 0.1833] +24-11-19 20:17:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:17:59 | D | sum error = [ 9.8586, 10.6535, 11.5118, 12.4307, 13.4194] +24-11-19 20:17:59 | D | best error = [ 0.1833, 0.1833, 0.1833, 0.1833, 0.1833] +24-11-19 20:17:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:17:59 | D | sum error = [ 14.4719, 15.5937, 16.7957, 18.0833, 19.4544] +24-11-19 20:17:59 | D | best error = [ 0.1833, 0.1833, 0.1833, 0.1833, 0.1833] +24-11-19 20:17:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:17:59 | D | sum error = [ 20.9047, 22.4530, 24.1071, 25.8520, 27.7246] +24-11-19 20:17:59 | D | best error = [ 0.1833, 0.1833, 0.1833, 0.1833, 0.1833] +24-11-19 20:17:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:17:59 | D | sum error = [ 29.6987, 31.8020, 34.0316, 36.3918, 38.8951] +24-11-19 20:17:59 | D | best error = [ 0.1833, 0.1833, 0.1833, 0.1833, 0.1833] +24-11-19 20:17:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:17:59 | D | sum error = [ 41.5357, 44.3146, 47.2575, 50.3481, 53.5938] +24-11-19 20:17:59 | D | best error = [ 0.1833, 0.1833, 0.1833, 0.1833, 0.1833] +24-11-19 20:17:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:17:59 | D | sum error = [ 57.0028, 60.5567, 64.2410, 68.0654, 72.0278] +24-11-19 20:17:59 | D | best error = [ 0.1833, 0.1833, 0.1833, 0.1833, 0.1833] +24-11-19 20:17:59 | D | + error = [0.1833] +24-11-19 20:17:59 | D | - Calibrating model.layers.0.self_attn.k_proj.weight +24-11-19 20:17:59 | D | + w: sint8 +24-11-19 20:17:59 | D | + x: None +24-11-19 20:17:59 | D | + y: None +24-11-19 20:17:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:17:59 | D | + finished parsing calibration arguments, ram usage: 14.2 +24-11-19 20:17:59 | D | + finished reseting calibrator, ram usage: 14.2 +24-11-19 20:18:00 | D | + finished calculating the original outputs, ram usage: 14.2 +24-11-19 20:18:00 | D | - range ratio = [ 1.0000] +24-11-19 20:18:00 | D | sum error = [ 0.2603] +24-11-19 20:18:00 | D | best error = [ 0.2603] +24-11-19 20:18:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:12 | D | sum error = [ 0.2525, 0.2540, 0.2589, 0.2709, 0.2652] +24-11-19 20:18:12 | D | best error = [ 0.2525, 0.2525, 0.2525, 0.2525, 0.2525] +24-11-19 20:18:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:12 | D | sum error = [ 0.2616, 0.2799, 0.2916, 0.3137, 0.3225] +24-11-19 20:18:12 | D | best error = [ 0.2525, 0.2525, 0.2525, 0.2525, 0.2525] +24-11-19 20:18:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:12 | D | sum error = [ 0.3480, 0.3667, 0.3941, 0.4340, 0.4699] +24-11-19 20:18:12 | D | best error = [ 0.2525, 0.2525, 0.2525, 0.2525, 0.2525] +24-11-19 20:18:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:12 | D | sum error = [ 0.4959, 0.5458, 0.5766, 0.6193, 0.6824] +24-11-19 20:18:12 | D | best error = [ 0.2525, 0.2525, 0.2525, 0.2525, 0.2525] +24-11-19 20:18:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:12 | D | sum error = [ 0.7393, 0.8057, 0.8707, 0.9375, 1.0065] +24-11-19 20:18:12 | D | best error = [ 0.2525, 0.2525, 0.2525, 0.2525, 0.2525] +24-11-19 20:18:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:12 | D | sum error = [ 1.0937, 1.1864, 1.2942, 1.3947, 1.5254] +24-11-19 20:18:12 | D | best error = [ 0.2525, 0.2525, 0.2525, 0.2525, 0.2525] +24-11-19 20:18:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:12 | D | sum error = [ 1.6447, 1.7947, 1.9508, 2.1118, 2.2894] +24-11-19 20:18:12 | D | best error = [ 0.2525, 0.2525, 0.2525, 0.2525, 0.2525] +24-11-19 20:18:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:12 | D | sum error = [ 2.4870, 2.7008, 2.9403, 3.1886, 3.4740] +24-11-19 20:18:12 | D | best error = [ 0.2525, 0.2525, 0.2525, 0.2525, 0.2525] +24-11-19 20:18:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:12 | D | sum error = [ 3.7727, 4.1009, 4.4526, 4.8416, 5.2606] +24-11-19 20:18:12 | D | best error = [ 0.2525, 0.2525, 0.2525, 0.2525, 0.2525] +24-11-19 20:18:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:12 | D | sum error = [ 5.7164, 6.2029, 6.7242, 7.3043, 7.9232] +24-11-19 20:18:12 | D | best error = [ 0.2525, 0.2525, 0.2525, 0.2525, 0.2525] +24-11-19 20:18:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:12 | D | sum error = [ 8.5872, 9.3079, 10.0854, 10.9301, 11.8217] +24-11-19 20:18:12 | D | best error = [ 0.2525, 0.2525, 0.2525, 0.2525, 0.2525] +24-11-19 20:18:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:12 | D | sum error = [ 12.8012, 13.8366, 14.9619, 16.1554, 17.4513] +24-11-19 20:18:12 | D | best error = [ 0.2525, 0.2525, 0.2525, 0.2525, 0.2525] +24-11-19 20:18:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:12 | D | sum error = [ 18.8445, 20.3223, 21.9233, 23.6343, 25.4697] +24-11-19 20:18:12 | D | best error = [ 0.2525, 0.2525, 0.2525, 0.2525, 0.2525] +24-11-19 20:18:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:12 | D | sum error = [ 27.4196, 29.4971, 31.7139, 34.0749, 36.5768] +24-11-19 20:18:12 | D | best error = [ 0.2525, 0.2525, 0.2525, 0.2525, 0.2525] +24-11-19 20:18:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:12 | D | sum error = [ 39.2473, 42.0771, 45.0624, 48.2125, 51.5388] +24-11-19 20:18:12 | D | best error = [ 0.2525, 0.2525, 0.2525, 0.2525, 0.2525] +24-11-19 20:18:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:12 | D | sum error = [ 55.0221, 58.6858, 62.5085, 66.4949, 70.6579] +24-11-19 20:18:12 | D | best error = [ 0.2525, 0.2525, 0.2525, 0.2525, 0.2525] +24-11-19 20:18:12 | D | + error = [0.2525] +24-11-19 20:18:13 | D | - Calibrating model.layers.0.self_attn.v_proj.weight +24-11-19 20:18:13 | D | + w: sint8 +24-11-19 20:18:13 | D | + x: None +24-11-19 20:18:13 | D | + y: None +24-11-19 20:18:13 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:13 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:18:13 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:18:13 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:18:13 | D | - range ratio = [ 1.0000] +24-11-19 20:18:13 | D | sum error = [ 0.2193] +24-11-19 20:18:13 | D | best error = [ 0.2193] +24-11-19 20:18:13 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:13 | D | sum error = [ 0.2178, 0.2165, 0.2172, 0.2209, 0.2241] +24-11-19 20:18:13 | D | best error = [ 0.2060, 0.2008, 0.1982, 0.1969, 0.1960] +24-11-19 20:18:13 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:13 | D | sum error = [ 0.2293, 0.2382, 0.2481, 0.2593, 0.2738] +24-11-19 20:18:13 | D | best error = [ 0.1956, 0.1954, 0.1954, 0.1953, 0.1953] +24-11-19 20:18:13 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:13 | D | sum error = [ 0.2899, 0.3096, 0.3280, 0.3501, 0.3750] +24-11-19 20:18:13 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:18:13 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:13 | D | sum error = [ 0.4020, 0.4313, 0.4606, 0.4962, 0.5293] +24-11-19 20:18:13 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:18:13 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:13 | D | sum error = [ 0.5675, 0.6087, 0.6506, 0.6965, 0.7455] +24-11-19 20:18:13 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:18:13 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:13 | D | sum error = [ 0.7961, 0.8488, 0.9054, 0.9655, 1.0301] +24-11-19 20:18:13 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:18:13 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:13 | D | sum error = [ 1.0968, 1.1670, 1.2410, 1.3205, 1.4035] +24-11-19 20:18:13 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:18:13 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:13 | D | sum error = [ 1.4913, 1.5827, 1.6815, 1.7853, 1.8956] +24-11-19 20:18:13 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:18:13 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:13 | D | sum error = [ 2.0087, 2.1281, 2.2525, 2.3848, 2.5248] +24-11-19 20:18:13 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:18:13 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:13 | D | sum error = [ 2.6681, 2.8214, 2.9810, 3.1454, 3.3203] +24-11-19 20:18:13 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:18:13 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:13 | D | sum error = [ 3.5019, 3.6937, 3.8935, 4.1018, 4.3188] +24-11-19 20:18:13 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:18:13 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:13 | D | sum error = [ 4.5428, 4.7796, 5.0255, 5.2814, 5.5463] +24-11-19 20:18:13 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:18:13 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:13 | D | sum error = [ 5.8234, 6.1121, 6.4115, 6.7200, 7.0420] +24-11-19 20:18:13 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:18:13 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:13 | D | sum error = [ 7.3753, 7.7223, 8.0823, 8.4551, 8.8431] +24-11-19 20:18:13 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:18:13 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:13 | D | sum error = [ 9.2382, 9.6566, 10.0822, 10.5254, 10.9777] +24-11-19 20:18:13 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:18:13 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:13 | D | sum error = [ 11.4473, 11.9355, 12.4371, 12.9462, 13.4751] +24-11-19 20:18:13 | D | best error = [ 0.1953, 0.1953, 0.1953, 0.1953, 0.1953] +24-11-19 20:18:13 | D | + error = [0.1953] +24-11-19 20:18:13 | D | - Calibrating model.layers.0.self_attn.o_proj.weight +24-11-19 20:18:13 | D | + w: sint8 +24-11-19 20:18:13 | D | + x: None +24-11-19 20:18:13 | D | + y: None +24-11-19 20:18:13 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:13 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:18:13 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:18:13 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:18:13 | D | - range ratio = [ 1.0000] +24-11-19 20:18:13 | D | sum error = [ 0.1014] +24-11-19 20:18:13 | D | best error = [ 0.1014] +24-11-19 20:18:14 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:14 | D | sum error = [ 0.1011, 0.1009, 0.1004, 0.1013, 0.1026] +24-11-19 20:18:14 | D | best error = [ 0.0902, 0.0859, 0.0834, 0.0820, 0.0811] +24-11-19 20:18:14 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:14 | D | sum error = [ 0.1056, 0.1081, 0.1115, 0.1154, 0.1205] +24-11-19 20:18:14 | D | best error = [ 0.0806, 0.0803, 0.0801, 0.0799, 0.0798] +24-11-19 20:18:14 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:14 | D | sum error = [ 0.1252, 0.1319, 0.1386, 0.1464, 0.1553] +24-11-19 20:18:14 | D | best error = [ 0.0798, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:18:14 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:14 | D | sum error = [ 0.1643, 0.1749, 0.1848, 0.1957, 0.2081] +24-11-19 20:18:14 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:18:14 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:14 | D | sum error = [ 0.2214, 0.2347, 0.2486, 0.2639, 0.2793] +24-11-19 20:18:14 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:18:14 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:14 | D | sum error = [ 0.2963, 0.3145, 0.3331, 0.3528, 0.3731] +24-11-19 20:18:14 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:18:14 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:14 | D | sum error = [ 0.3947, 0.4176, 0.4414, 0.4663, 0.4933] +24-11-19 20:18:14 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:18:14 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:14 | D | sum error = [ 0.5207, 0.5495, 0.5802, 0.6122, 0.6453] +24-11-19 20:18:14 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:18:14 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:14 | D | sum error = [ 0.6803, 0.7163, 0.7551, 0.7950, 0.8371] +24-11-19 20:18:14 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:18:14 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:14 | D | sum error = [ 0.8808, 0.9269, 0.9751, 1.0255, 1.0783] +24-11-19 20:18:14 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:18:14 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:14 | D | sum error = [ 1.1342, 1.1924, 1.2527, 1.3168, 1.3838] +24-11-19 20:18:14 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:18:14 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:14 | D | sum error = [ 1.4544, 1.5281, 1.6059, 1.6874, 1.7732] +24-11-19 20:18:14 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:18:14 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:14 | D | sum error = [ 1.8639, 1.9588, 2.0590, 2.1650, 2.2763] +24-11-19 20:18:14 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:18:14 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:14 | D | sum error = [ 2.3937, 2.5177, 2.6487, 2.7875, 2.9339] +24-11-19 20:18:14 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:18:14 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:14 | D | sum error = [ 3.0887, 3.2524, 3.4251, 3.6072, 3.7999] +24-11-19 20:18:14 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:18:14 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:14 | D | sum error = [ 4.0032, 4.2180, 4.4442, 4.6816, 4.9316] +24-11-19 20:18:14 | D | best error = [ 0.0797, 0.0797, 0.0797, 0.0797, 0.0797] +24-11-19 20:18:14 | D | + error = [0.0797] +24-11-19 20:18:14 | D | - Calibrating model.layers.0.mlp.up_proj.weight +24-11-19 20:18:14 | D | + w: sint8 +24-11-19 20:18:14 | D | + x: None +24-11-19 20:18:14 | D | + y: None +24-11-19 20:18:14 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:14 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:18:14 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:18:14 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:18:14 | D | - range ratio = [ 1.0000] +24-11-19 20:18:14 | D | sum error = [ 2.2606] +24-11-19 20:18:14 | D | best error = [ 2.2606] +24-11-19 20:18:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:15 | D | sum error = [ 2.2440, 2.2534, 2.2473, 2.2776, 2.3221] +24-11-19 20:18:15 | D | best error = [ 1.9587, 1.8600, 1.8120, 1.7874, 1.7745] +24-11-19 20:18:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:15 | D | sum error = [ 2.3844, 2.4639, 2.5580, 2.6769, 2.8204] +24-11-19 20:18:15 | D | best error = [ 1.7677, 1.7645, 1.7632, 1.7628, 1.7626] +24-11-19 20:18:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:15 | D | sum error = [ 2.9755, 3.1722, 3.3687, 3.5980, 3.8507] +24-11-19 20:18:15 | D | best error = [ 1.7626, 1.7626, 1.7626, 1.7626, 1.7626] +24-11-19 20:18:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:15 | D | sum error = [ 4.1289, 4.4220, 4.7278, 5.0683, 5.4289] +24-11-19 20:18:15 | D | best error = [ 1.7626, 1.7626, 1.7626, 1.7626, 1.7626] +24-11-19 20:18:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:15 | D | sum error = [ 5.8146, 6.2320, 6.6838, 7.1387, 7.6262] +24-11-19 20:18:15 | D | best error = [ 1.7626, 1.7626, 1.7626, 1.7626, 1.7626] +24-11-19 20:18:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:15 | D | sum error = [ 8.1390, 8.6967, 9.2717, 9.8851, 10.5354] +24-11-19 20:18:15 | D | best error = [ 1.7626, 1.7626, 1.7626, 1.7626, 1.7626] +24-11-19 20:18:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:15 | D | sum error = [ 11.2254, 11.9460, 12.7076, 13.5005, 14.3488] +24-11-19 20:18:15 | D | best error = [ 1.7626, 1.7626, 1.7626, 1.7626, 1.7626] +24-11-19 20:18:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:15 | D | sum error = [ 15.2349, 16.1826, 17.1605, 18.1984, 19.2827] +24-11-19 20:18:15 | D | best error = [ 1.7626, 1.7626, 1.7626, 1.7626, 1.7626] +24-11-19 20:18:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:15 | D | sum error = [ 20.4208, 21.6124, 22.8676, 24.1705, 25.5446] +24-11-19 20:18:15 | D | best error = [ 1.7626, 1.7626, 1.7626, 1.7626, 1.7626] +24-11-19 20:18:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:15 | D | sum error = [ 26.9864, 28.4909, 30.0511, 31.6863, 33.3915] +24-11-19 20:18:15 | D | best error = [ 1.7626, 1.7626, 1.7626, 1.7626, 1.7626] +24-11-19 20:18:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:15 | D | sum error = [ 35.1697, 37.0370, 38.9716, 40.9966, 43.1049] +24-11-19 20:18:15 | D | best error = [ 1.7626, 1.7626, 1.7626, 1.7626, 1.7626] +24-11-19 20:18:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:15 | D | sum error = [ 45.2972, 47.5757, 49.9517, 52.4047, 54.9504] +24-11-19 20:18:15 | D | best error = [ 1.7626, 1.7626, 1.7626, 1.7626, 1.7626] +24-11-19 20:18:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:15 | D | sum error = [ 57.5904, 60.3278, 63.1581, 66.0886, 69.1158] +24-11-19 20:18:15 | D | best error = [ 1.7626, 1.7626, 1.7626, 1.7626, 1.7626] +24-11-19 20:18:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:15 | D | sum error = [ 72.2662, 75.5226, 78.8812, 82.3593, 85.9556] +24-11-19 20:18:15 | D | best error = [ 1.7626, 1.7626, 1.7626, 1.7626, 1.7626] +24-11-19 20:18:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:15 | D | sum error = [ 89.6685, 93.5031, 97.4551, 101.5245, 105.7326] +24-11-19 20:18:15 | D | best error = [ 1.7626, 1.7626, 1.7626, 1.7626, 1.7626] +24-11-19 20:18:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:15 | D | sum error = [ 110.0656, 114.5193, 119.0967, 123.8137, 128.6639] +24-11-19 20:18:15 | D | best error = [ 1.7626, 1.7626, 1.7626, 1.7626, 1.7626] +24-11-19 20:18:15 | D | + error = [1.7626] +24-11-19 20:18:15 | D | - Calibrating model.layers.0.mlp.gate_proj.weight +24-11-19 20:18:15 | D | + w: sint8 +24-11-19 20:18:15 | D | + x: None +24-11-19 20:18:15 | D | + y: None +24-11-19 20:18:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:15 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:18:16 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:18:16 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:18:16 | D | - range ratio = [ 1.0000] +24-11-19 20:18:16 | D | sum error = [ 2.4924] +24-11-19 20:18:16 | D | best error = [ 2.4924] +24-11-19 20:18:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:17 | D | sum error = [ 2.4685, 2.4669, 2.4704, 2.5084, 2.5608] +24-11-19 20:18:17 | D | best error = [ 2.1585, 2.0455, 1.9930, 1.9666, 1.9526] +24-11-19 20:18:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:17 | D | sum error = [ 2.6193, 2.7141, 2.8165, 2.9523, 3.1187] +24-11-19 20:18:17 | D | best error = [ 1.9451, 1.9417, 1.9405, 1.9400, 1.9399] +24-11-19 20:18:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:17 | D | sum error = [ 3.3006, 3.5002, 3.7486, 3.9830, 4.2775] +24-11-19 20:18:17 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:18:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:17 | D | sum error = [ 4.5813, 4.9087, 5.2640, 5.6559, 6.0629] +24-11-19 20:18:17 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:18:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:17 | D | sum error = [ 6.4868, 6.9653, 7.4492, 7.9750, 8.5342] +24-11-19 20:18:17 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:18:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:17 | D | sum error = [ 9.1346, 9.7685, 10.4225, 11.1434, 11.8855] +24-11-19 20:18:17 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:18:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:17 | D | sum error = [ 12.6732, 13.5071, 14.3957, 15.3215, 16.3074] +24-11-19 20:18:17 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:18:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:17 | D | sum error = [ 17.3392, 18.4391, 19.5982, 20.8127, 22.1063] +24-11-19 20:18:17 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:18:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:17 | D | sum error = [ 23.4629, 24.9015, 26.4145, 27.9974, 29.6842] +24-11-19 20:18:17 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:18:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:17 | D | sum error = [ 31.4596, 33.3230, 35.2820, 37.3383, 39.4905] +24-11-19 20:18:17 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:18:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:17 | D | sum error = [ 41.7524, 44.1282, 46.6128, 49.2287, 51.9740] +24-11-19 20:18:17 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:18:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:17 | D | sum error = [ 54.8396, 57.8362, 60.9742, 64.2674, 67.7001] +24-11-19 20:18:17 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:18:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:17 | D | sum error = [ 71.2957, 75.0447, 78.9602, 83.0357, 87.2870] +24-11-19 20:18:17 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:18:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:17 | D | sum error = [ 91.6990, 96.2943, 101.0755, 106.0370, 111.1848] +24-11-19 20:18:17 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:18:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:17 | D | sum error = [ 116.5361, 122.0659, 127.7930, 133.7307, 139.8657] +24-11-19 20:18:17 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:18:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:17 | D | sum error = [ 146.2098, 152.7511, 159.5073, 166.4515, 173.5995] +24-11-19 20:18:17 | D | best error = [ 1.9398, 1.9398, 1.9398, 1.9398, 1.9398] +24-11-19 20:18:17 | D | + error = [1.9398] +24-11-19 20:18:17 | D | - Calibrating model.layers.0.mlp.down_proj.weight +24-11-19 20:18:17 | D | + w: sint8 +24-11-19 20:18:17 | D | + x: None +24-11-19 20:18:17 | D | + y: None +24-11-19 20:18:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:18:17 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:18:17 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:18:17 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:18:17 | D | - range ratio = [ 1.0000] +24-11-19 20:18:17 | D | sum error = [ 0.1641] +24-11-19 20:18:17 | D | best error = [ 0.1641] +24-11-19 20:18:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:19 | D | sum error = [ 0.1636, 0.1663, 0.1712, 0.1797, 0.1903] +24-11-19 20:18:19 | D | best error = [ 0.1496, 0.1435, 0.1397, 0.1370, 0.1349] +24-11-19 20:18:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:19 | D | sum error = [ 0.2039, 0.2198, 0.2368, 0.2570, 0.2792] +24-11-19 20:18:19 | D | best error = [ 0.1333, 0.1321, 0.1310, 0.1301, 0.1295] +24-11-19 20:18:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:19 | D | sum error = [ 0.3030, 0.3302, 0.3569, 0.3863, 0.4184] +24-11-19 20:18:19 | D | best error = [ 0.1289, 0.1285, 0.1281, 0.1278, 0.1277] +24-11-19 20:18:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:19 | D | sum error = [ 0.4518, 0.4873, 0.5258, 0.5652, 0.6071] +24-11-19 20:18:19 | D | best error = [ 0.1275, 0.1274, 0.1273, 0.1273, 0.1272] +24-11-19 20:18:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:19 | D | sum error = [ 0.6517, 0.6995, 0.7484, 0.8007, 0.8543] +24-11-19 20:18:19 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 20:18:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:19 | D | sum error = [ 0.9123, 0.9722, 1.0357, 1.1027, 1.1735] +24-11-19 20:18:19 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 20:18:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:19 | D | sum error = [ 1.2473, 1.3251, 1.4057, 1.4918, 1.5835] +24-11-19 20:18:19 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 20:18:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:19 | D | sum error = [ 1.6788, 1.7790, 1.8839, 1.9952, 2.1113] +24-11-19 20:18:19 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 20:18:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:19 | D | sum error = [ 2.2332, 2.3601, 2.4940, 2.6351, 2.7822] +24-11-19 20:18:19 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 20:18:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:19 | D | sum error = [ 2.9370, 3.0984, 3.2684, 3.4468, 3.6330] +24-11-19 20:18:19 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 20:18:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:19 | D | sum error = [ 3.8270, 4.0307, 4.2438, 4.4675, 4.7010] +24-11-19 20:18:19 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 20:18:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:19 | D | sum error = [ 4.9449, 5.1993, 5.4649, 5.7414, 6.0308] +24-11-19 20:18:19 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 20:18:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:19 | D | sum error = [ 6.3317, 6.6458, 6.9733, 7.3142, 7.6687] +24-11-19 20:18:19 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 20:18:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:19 | D | sum error = [ 8.0376, 8.4216, 8.8199, 9.2337, 9.6627] +24-11-19 20:18:19 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 20:18:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:19 | D | sum error = [ 10.1077, 10.5682, 11.0456, 11.5397, 12.0505] +24-11-19 20:18:19 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 20:18:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:19 | D | sum error = [ 12.5782, 13.1233, 13.6861, 14.2670, 14.8648] +24-11-19 20:18:19 | D | best error = [ 0.1272, 0.1272, 0.1272, 0.1272, 0.1272] +24-11-19 20:18:19 | D | + error = [0.1272] +24-11-19 20:18:19 | D | - Quantizing model.layers.0.self_attn.q_proj.weight +24-11-19 20:18:20 | D | - Quantizing model.layers.0.self_attn.k_proj.weight +24-11-19 20:18:21 | D | - Quantizing model.layers.0.self_attn.v_proj.weight +24-11-19 20:18:22 | D | - Quantizing model.layers.0.self_attn.o_proj.weight +24-11-19 20:18:23 | D | - Quantizing model.layers.0.mlp.up_proj.weight +24-11-19 20:18:24 | D | - Quantizing model.layers.0.mlp.gate_proj.weight +24-11-19 20:18:25 | D | - Quantizing model.layers.0.mlp.down_proj.weight +24-11-19 20:18:38 | D | - Quantizing layer model.layers.1 +24-11-19 20:18:38 | D | - Calibrating model.layers.1.self_attn.q_proj.weight +24-11-19 20:18:38 | D | + w: sint8 +24-11-19 20:18:38 | D | + x: None +24-11-19 20:18:38 | D | + y: None +24-11-19 20:18:38 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:18:38 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:18:38 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:18:39 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:18:39 | D | - range ratio = [ 1.0000] +24-11-19 20:18:39 | D | sum error = [ 0.4282] +24-11-19 20:18:39 | D | best error = [ 0.4282] +24-11-19 20:18:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:18:52 | D | sum error = [ 0.4355, 0.4341, 0.4297, 0.4391, 0.4770] +24-11-19 20:18:52 | D | best error = [ 0.4282, 0.4282, 0.4282, 0.4282, 0.4282] +24-11-19 20:18:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:18:52 | D | sum error = [ 0.4723, 0.4835, 0.5161, 0.5398, 0.5851] +24-11-19 20:18:52 | D | best error = [ 0.4282, 0.4282, 0.4282, 0.4282, 0.4282] +24-11-19 20:18:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:18:52 | D | sum error = [ 0.6522, 0.7079, 0.7928, 0.8729, 1.0160] +24-11-19 20:18:52 | D | best error = [ 0.4282, 0.4282, 0.4282, 0.4282, 0.4282] +24-11-19 20:18:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:18:52 | D | sum error = [ 1.0940, 1.2184, 1.3702, 1.4881, 1.6503] +24-11-19 20:18:52 | D | best error = [ 0.4282, 0.4282, 0.4282, 0.4282, 0.4282] +24-11-19 20:18:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:18:52 | D | sum error = [ 1.9350, 2.1549, 2.3260, 2.6427, 2.8984] +24-11-19 20:18:52 | D | best error = [ 0.4282, 0.4282, 0.4282, 0.4282, 0.4282] +24-11-19 20:18:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:18:52 | D | sum error = [ 3.2490, 3.5527, 3.9597, 4.3410, 4.7984] +24-11-19 20:18:52 | D | best error = [ 0.4282, 0.4282, 0.4282, 0.4282, 0.4282] +24-11-19 20:18:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:18:52 | D | sum error = [ 5.2453, 5.7343, 6.2858, 6.8684, 7.4959] +24-11-19 20:18:52 | D | best error = [ 0.4282, 0.4282, 0.4282, 0.4282, 0.4282] +24-11-19 20:18:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:18:52 | D | sum error = [ 8.1252, 8.7992, 9.5139, 10.2925, 11.1630] +24-11-19 20:18:52 | D | best error = [ 0.4282, 0.4282, 0.4282, 0.4282, 0.4282] +24-11-19 20:18:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:18:52 | D | sum error = [ 12.0512, 13.0769, 14.1172, 15.2158, 16.4457] +24-11-19 20:18:52 | D | best error = [ 0.4282, 0.4282, 0.4282, 0.4282, 0.4282] +24-11-19 20:18:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:18:52 | D | sum error = [ 17.7263, 19.1745, 20.6979, 22.2537, 24.1049] +24-11-19 20:18:52 | D | best error = [ 0.4282, 0.4282, 0.4282, 0.4282, 0.4282] +24-11-19 20:18:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:18:52 | D | sum error = [ 25.9692, 28.0490, 30.1361, 32.4957, 34.9166] +24-11-19 20:18:52 | D | best error = [ 0.4282, 0.4282, 0.4282, 0.4282, 0.4282] +24-11-19 20:18:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:18:52 | D | sum error = [ 37.6197, 40.3470, 43.3305, 46.4812, 49.8734] +24-11-19 20:18:52 | D | best error = [ 0.4282, 0.4282, 0.4282, 0.4282, 0.4282] +24-11-19 20:18:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:18:52 | D | sum error = [ 53.4467, 57.2745, 61.2319, 65.5398, 70.2706] +24-11-19 20:18:52 | D | best error = [ 0.4282, 0.4282, 0.4282, 0.4282, 0.4282] +24-11-19 20:18:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:18:52 | D | sum error = [ 75.1153, 80.4039, 85.8966, 91.7230, 98.0800] +24-11-19 20:18:52 | D | best error = [ 0.4282, 0.4282, 0.4282, 0.4282, 0.4282] +24-11-19 20:18:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:18:52 | D | sum error = [ 104.7697, 111.7778, 119.1958, 127.1807, 135.3928] +24-11-19 20:18:52 | D | best error = [ 0.4282, 0.4282, 0.4282, 0.4282, 0.4282] +24-11-19 20:18:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:18:52 | D | sum error = [ 144.0351, 153.0610, 162.4554, 172.3121, 182.2680] +24-11-19 20:18:52 | D | best error = [ 0.4282, 0.4282, 0.4282, 0.4282, 0.4282] +24-11-19 20:18:52 | D | + error = [0.4282] +24-11-19 20:18:52 | D | - Calibrating model.layers.1.self_attn.k_proj.weight +24-11-19 20:18:52 | D | + w: sint8 +24-11-19 20:18:52 | D | + x: None +24-11-19 20:18:52 | D | + y: None +24-11-19 20:18:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:18:52 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:18:52 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:18:52 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:18:53 | D | - range ratio = [ 1.0000] +24-11-19 20:18:53 | D | sum error = [ 0.4843] +24-11-19 20:18:53 | D | best error = [ 0.4843] +24-11-19 20:19:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:05 | D | sum error = [ 0.5262, 0.5158, 0.5322, 0.5270, 0.5437] +24-11-19 20:19:05 | D | best error = [ 0.4843, 0.4843, 0.4843, 0.4843, 0.4843] +24-11-19 20:19:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:05 | D | sum error = [ 0.6025, 0.5543, 0.6208, 0.6240, 0.6896] +24-11-19 20:19:05 | D | best error = [ 0.4843, 0.4843, 0.4843, 0.4843, 0.4843] +24-11-19 20:19:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:05 | D | sum error = [ 0.7293, 0.7420, 0.8260, 0.8916, 0.9719] +24-11-19 20:19:05 | D | best error = [ 0.4843, 0.4843, 0.4843, 0.4843, 0.4843] +24-11-19 20:19:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:05 | D | sum error = [ 1.1270, 1.2238, 1.3432, 1.4962, 1.6821] +24-11-19 20:19:05 | D | best error = [ 0.4843, 0.4843, 0.4843, 0.4843, 0.4843] +24-11-19 20:19:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:05 | D | sum error = [ 1.9625, 2.1024, 2.3709, 2.6296, 2.8930] +24-11-19 20:19:05 | D | best error = [ 0.4843, 0.4843, 0.4843, 0.4843, 0.4843] +24-11-19 20:19:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:05 | D | sum error = [ 3.0914, 3.3897, 3.8448, 4.2434, 4.6340] +24-11-19 20:19:05 | D | best error = [ 0.4843, 0.4843, 0.4843, 0.4843, 0.4843] +24-11-19 20:19:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:05 | D | sum error = [ 5.2280, 5.6295, 6.3560, 6.9226, 7.6140] +24-11-19 20:19:05 | D | best error = [ 0.4843, 0.4843, 0.4843, 0.4843, 0.4843] +24-11-19 20:19:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:05 | D | sum error = [ 8.3403, 9.0679, 9.7474, 10.6874, 11.5093] +24-11-19 20:19:05 | D | best error = [ 0.4843, 0.4843, 0.4843, 0.4843, 0.4843] +24-11-19 20:19:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:05 | D | sum error = [ 12.4070, 13.4127, 14.4388, 15.5450, 16.6865] +24-11-19 20:19:05 | D | best error = [ 0.4843, 0.4843, 0.4843, 0.4843, 0.4843] +24-11-19 20:19:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:05 | D | sum error = [ 17.9267, 19.2211, 20.6912, 22.1763, 23.8521] +24-11-19 20:19:05 | D | best error = [ 0.4843, 0.4843, 0.4843, 0.4843, 0.4843] +24-11-19 20:19:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:05 | D | sum error = [ 25.6898, 27.5873, 29.7299, 31.9218, 34.2782] +24-11-19 20:19:05 | D | best error = [ 0.4843, 0.4843, 0.4843, 0.4843, 0.4843] +24-11-19 20:19:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:05 | D | sum error = [ 36.8380, 39.5999, 42.5720, 45.7738, 49.0905] +24-11-19 20:19:05 | D | best error = [ 0.4843, 0.4843, 0.4843, 0.4843, 0.4843] +24-11-19 20:19:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:05 | D | sum error = [ 52.8469, 56.7387, 60.9651, 65.4535, 70.2049] +24-11-19 20:19:05 | D | best error = [ 0.4843, 0.4843, 0.4843, 0.4843, 0.4843] +24-11-19 20:19:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:05 | D | sum error = [ 75.2813, 80.5155, 86.1315, 91.9569, 98.3261] +24-11-19 20:19:05 | D | best error = [ 0.4843, 0.4843, 0.4843, 0.4843, 0.4843] +24-11-19 20:19:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:05 | D | sum error = [ 104.8002, 111.7995, 119.2446, 127.0271, 135.0764] +24-11-19 20:19:05 | D | best error = [ 0.4843, 0.4843, 0.4843, 0.4843, 0.4843] +24-11-19 20:19:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:05 | D | sum error = [ 143.5263, 152.5715, 161.8446, 171.4737, 181.4421] +24-11-19 20:19:05 | D | best error = [ 0.4843, 0.4843, 0.4843, 0.4843, 0.4843] +24-11-19 20:19:05 | D | + error = [0.4843] +24-11-19 20:19:05 | D | - Calibrating model.layers.1.self_attn.v_proj.weight +24-11-19 20:19:05 | D | + w: sint8 +24-11-19 20:19:05 | D | + x: None +24-11-19 20:19:05 | D | + y: None +24-11-19 20:19:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:05 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:19:05 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:19:05 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:19:05 | D | - range ratio = [ 1.0000] +24-11-19 20:19:05 | D | sum error = [ 0.3294] +24-11-19 20:19:05 | D | best error = [ 0.3294] +24-11-19 20:19:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:06 | D | sum error = [ 0.3318, 0.3363, 0.3408, 0.3381, 0.3455] +24-11-19 20:19:06 | D | best error = [ 0.2894, 0.2763, 0.2705, 0.2663, 0.2638] +24-11-19 20:19:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:06 | D | sum error = [ 0.3512, 0.3679, 0.3774, 0.3980, 0.4161] +24-11-19 20:19:06 | D | best error = [ 0.2624, 0.2621, 0.2619, 0.2618, 0.2618] +24-11-19 20:19:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:06 | D | sum error = [ 0.4412, 0.4761, 0.5048, 0.5371, 0.5741] +24-11-19 20:19:06 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:19:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:06 | D | sum error = [ 0.6138, 0.6649, 0.7099, 0.7621, 0.8185] +24-11-19 20:19:06 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:19:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:06 | D | sum error = [ 0.8748, 0.9379, 1.0041, 1.0734, 1.1491] +24-11-19 20:19:06 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:19:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:06 | D | sum error = [ 1.2320, 1.3188, 1.4054, 1.5045, 1.6055] +24-11-19 20:19:06 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:19:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:06 | D | sum error = [ 1.7072, 1.8264, 1.9491, 2.0750, 2.2106] +24-11-19 20:19:06 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:19:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:06 | D | sum error = [ 2.3531, 2.5025, 2.6662, 2.8296, 3.0075] +24-11-19 20:19:06 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:19:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:06 | D | sum error = [ 3.1903, 3.3819, 3.5857, 3.8012, 4.0309] +24-11-19 20:19:06 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:19:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:06 | D | sum error = [ 4.2656, 4.5186, 4.7816, 5.0579, 5.3497] +24-11-19 20:19:06 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:19:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:06 | D | sum error = [ 5.6503, 5.9666, 6.2939, 6.6413, 7.0047] +24-11-19 20:19:06 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:19:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:06 | D | sum error = [ 7.3769, 7.7712, 8.1822, 8.6119, 9.0603] +24-11-19 20:19:06 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:19:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:06 | D | sum error = [ 9.5292, 10.0163, 10.5323, 11.0698, 11.6275] +24-11-19 20:19:06 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:19:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:06 | D | sum error = [ 12.2054, 12.8133, 13.4400, 14.0968, 14.7772] +24-11-19 20:19:06 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:19:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:06 | D | sum error = [ 15.4822, 16.2136, 16.9707, 17.7527, 18.5688] +24-11-19 20:19:06 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:19:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:06 | D | sum error = [ 19.4045, 20.2758, 21.1662, 22.0942, 23.0471] +24-11-19 20:19:06 | D | best error = [ 0.2618, 0.2618, 0.2618, 0.2618, 0.2618] +24-11-19 20:19:06 | D | + error = [0.2618] +24-11-19 20:19:06 | D | - Calibrating model.layers.1.self_attn.o_proj.weight +24-11-19 20:19:06 | D | + w: sint8 +24-11-19 20:19:06 | D | + x: None +24-11-19 20:19:06 | D | + y: None +24-11-19 20:19:06 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:06 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:19:06 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:19:06 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:19:06 | D | - range ratio = [ 1.0000] +24-11-19 20:19:06 | D | sum error = [ 0.1715] +24-11-19 20:19:06 | D | best error = [ 0.1715] +24-11-19 20:19:06 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:06 | D | sum error = [ 0.1715, 0.1715, 0.1711, 0.1736, 0.1769] +24-11-19 20:19:06 | D | best error = [ 0.1452, 0.1357, 0.1308, 0.1276, 0.1256] +24-11-19 20:19:06 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:06 | D | sum error = [ 0.1835, 0.1906, 0.1981, 0.2086, 0.2177] +24-11-19 20:19:06 | D | best error = [ 0.1242, 0.1233, 0.1226, 0.1221, 0.1218] +24-11-19 20:19:06 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:06 | D | sum error = [ 0.2322, 0.2444, 0.2621, 0.2816, 0.2976] +24-11-19 20:19:06 | D | best error = [ 0.1216, 0.1214, 0.1212, 0.1212, 0.1211] +24-11-19 20:19:06 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:06 | D | sum error = [ 0.3189, 0.3423, 0.3661, 0.3919, 0.4202] +24-11-19 20:19:06 | D | best error = [ 0.1211, 0.1211, 0.1210, 0.1210, 0.1210] +24-11-19 20:19:06 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:06 | D | sum error = [ 0.4477, 0.4783, 0.5106, 0.5460, 0.5800] +24-11-19 20:19:06 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:19:06 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:06 | D | sum error = [ 0.6194, 0.6582, 0.6998, 0.7448, 0.7923] +24-11-19 20:19:06 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:19:06 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:06 | D | sum error = [ 0.8393, 0.8908, 0.9449, 1.0029, 1.0620] +24-11-19 20:19:06 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:19:06 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:06 | D | sum error = [ 1.1271, 1.1929, 1.2632, 1.3356, 1.4128] +24-11-19 20:19:06 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:19:06 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:06 | D | sum error = [ 1.4945, 1.5789, 1.6669, 1.7620, 1.8595] +24-11-19 20:19:06 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:19:06 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:06 | D | sum error = [ 1.9630, 2.0718, 2.1845, 2.3029, 2.4296] +24-11-19 20:19:06 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:19:06 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:06 | D | sum error = [ 2.5586, 2.6952, 2.8374, 2.9861, 3.1412] +24-11-19 20:19:06 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:19:06 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:06 | D | sum error = [ 3.3038, 3.4726, 3.6493, 3.8324, 4.0238] +24-11-19 20:19:06 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:19:06 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:06 | D | sum error = [ 4.2248, 4.4351, 4.6526, 4.8816, 5.1193] +24-11-19 20:19:06 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:19:06 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:06 | D | sum error = [ 5.3673, 5.6263, 5.8961, 6.1755, 6.4661] +24-11-19 20:19:06 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:19:06 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:06 | D | sum error = [ 6.7682, 7.0807, 7.4047, 7.7412, 8.0902] +24-11-19 20:19:06 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:19:06 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:06 | D | sum error = [ 8.4528, 8.8292, 9.2182, 9.6210, 10.0364] +24-11-19 20:19:06 | D | best error = [ 0.1210, 0.1210, 0.1210, 0.1210, 0.1210] +24-11-19 20:19:06 | D | + error = [0.1210] +24-11-19 20:19:07 | D | - Calibrating model.layers.1.mlp.up_proj.weight +24-11-19 20:19:07 | D | + w: sint8 +24-11-19 20:19:07 | D | + x: None +24-11-19 20:19:07 | D | + y: None +24-11-19 20:19:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:07 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:19:07 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:19:07 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:19:07 | D | - range ratio = [ 1.0000] +24-11-19 20:19:07 | D | sum error = [ 2.8587] +24-11-19 20:19:07 | D | best error = [ 2.8587] +24-11-19 20:19:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:08 | D | sum error = [ 2.8478, 2.8403, 2.8455, 2.8715, 2.9349] +24-11-19 20:19:08 | D | best error = [ 2.5600, 2.4592, 2.4094, 2.3818, 2.3678] +24-11-19 20:19:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:08 | D | sum error = [ 3.0035, 3.1014, 3.2269, 3.3767, 3.5564] +24-11-19 20:19:08 | D | best error = [ 2.3599, 2.3563, 2.3549, 2.3545, 2.3543] +24-11-19 20:19:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:08 | D | sum error = [ 3.7698, 3.9968, 4.2593, 4.5402, 4.8493] +24-11-19 20:19:08 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 20:19:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:08 | D | sum error = [ 5.1894, 5.5659, 5.9570, 6.3827, 6.8404] +24-11-19 20:19:08 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 20:19:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:08 | D | sum error = [ 7.3236, 7.8433, 8.4096, 8.9832, 9.6153] +24-11-19 20:19:08 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 20:19:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:08 | D | sum error = [ 10.2823, 10.9749, 11.7285, 12.5025, 13.3356] +24-11-19 20:19:08 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 20:19:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:08 | D | sum error = [ 14.2071, 15.1244, 16.0845, 17.1082, 18.1666] +24-11-19 20:19:08 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 20:19:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:08 | D | sum error = [ 19.3034, 20.4810, 21.7155, 23.0215, 24.3956] +24-11-19 20:19:08 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 20:19:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:08 | D | sum error = [ 25.8040, 27.3004, 28.8620, 30.4908, 32.1956] +24-11-19 20:19:08 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 20:19:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:08 | D | sum error = [ 33.9886, 35.8464, 37.7941, 39.8153, 41.9160] +24-11-19 20:19:08 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 20:19:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:08 | D | sum error = [ 44.1045, 46.3846, 48.7581, 51.2121, 53.7626] +24-11-19 20:19:08 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 20:19:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:08 | D | sum error = [ 56.4088, 59.1607, 62.0060, 64.9515, 68.0061] +24-11-19 20:19:08 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 20:19:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:08 | D | sum error = [ 71.1717, 74.4238, 77.7940, 81.2801, 84.8698] +24-11-19 20:19:08 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 20:19:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:08 | D | sum error = [ 88.5757, 92.4044, 96.3352, 100.3835, 104.5512] +24-11-19 20:19:08 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 20:19:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:08 | D | sum error = [ 108.8210, 113.2295, 117.7611, 122.4102, 127.1857] +24-11-19 20:19:08 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 20:19:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:08 | D | sum error = [ 132.1114, 137.1546, 142.3313, 147.6320, 153.0673] +24-11-19 20:19:08 | D | best error = [ 2.3543, 2.3543, 2.3543, 2.3543, 2.3543] +24-11-19 20:19:08 | D | + error = [2.3543] +24-11-19 20:19:08 | D | - Calibrating model.layers.1.mlp.gate_proj.weight +24-11-19 20:19:08 | D | + w: sint8 +24-11-19 20:19:08 | D | + x: None +24-11-19 20:19:08 | D | + y: None +24-11-19 20:19:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:08 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:19:08 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:19:08 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:19:09 | D | - range ratio = [ 1.0000] +24-11-19 20:19:09 | D | sum error = [ 3.1408] +24-11-19 20:19:09 | D | best error = [ 3.1408] +24-11-19 20:19:10 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:10 | D | sum error = [ 3.1194, 3.1113, 3.1215, 3.1554, 3.2210] +24-11-19 20:19:10 | D | best error = [ 2.8114, 2.7002, 2.6440, 2.6125, 2.5957] +24-11-19 20:19:10 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:10 | D | sum error = [ 3.2958, 3.4251, 3.5639, 3.7059, 3.9123] +24-11-19 20:19:10 | D | best error = [ 2.5874, 2.5835, 2.5818, 2.5813, 2.5812] +24-11-19 20:19:10 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:10 | D | sum error = [ 4.1399, 4.3991, 4.6880, 5.0055, 5.3380] +24-11-19 20:19:10 | D | best error = [ 2.5812, 2.5812, 2.5812, 2.5812, 2.5812] +24-11-19 20:19:10 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:10 | D | sum error = [ 5.7274, 6.1404, 6.5764, 7.0419, 7.5543] +24-11-19 20:19:10 | D | best error = [ 2.5812, 2.5812, 2.5812, 2.5812, 2.5812] +24-11-19 20:19:10 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:10 | D | sum error = [ 8.1073, 8.6787, 9.2917, 9.9558, 10.6585] +24-11-19 20:19:10 | D | best error = [ 2.5812, 2.5812, 2.5812, 2.5812, 2.5812] +24-11-19 20:19:10 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:10 | D | sum error = [ 11.3903, 12.1811, 13.0135, 13.8805, 14.8346] +24-11-19 20:19:10 | D | best error = [ 2.5812, 2.5812, 2.5812, 2.5812, 2.5812] +24-11-19 20:19:10 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:10 | D | sum error = [ 15.8136, 16.8595, 17.9430, 19.1223, 20.3504] +24-11-19 20:19:10 | D | best error = [ 2.5812, 2.5812, 2.5812, 2.5812, 2.5812] +24-11-19 20:19:10 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:10 | D | sum error = [ 21.6440, 23.0054, 24.4396, 25.9431, 27.5296] +24-11-19 20:19:10 | D | best error = [ 2.5812, 2.5812, 2.5812, 2.5812, 2.5812] +24-11-19 20:19:10 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:10 | D | sum error = [ 29.2007, 30.9582, 32.7992, 34.7387, 36.7924] +24-11-19 20:19:10 | D | best error = [ 2.5812, 2.5812, 2.5812, 2.5812, 2.5812] +24-11-19 20:19:10 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:10 | D | sum error = [ 38.8925, 41.1367, 43.4851, 45.9334, 48.5122] +24-11-19 20:19:10 | D | best error = [ 2.5812, 2.5812, 2.5812, 2.5812, 2.5812] +24-11-19 20:19:10 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:10 | D | sum error = [ 51.1915, 54.0084, 56.9482, 60.0059, 63.2203] +24-11-19 20:19:10 | D | best error = [ 2.5812, 2.5812, 2.5812, 2.5812, 2.5812] +24-11-19 20:19:10 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:10 | D | sum error = [ 66.5709, 70.0569, 73.7013, 77.4990, 81.4452] +24-11-19 20:19:10 | D | best error = [ 2.5812, 2.5812, 2.5812, 2.5812, 2.5812] +24-11-19 20:19:10 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:10 | D | sum error = [ 85.5669, 89.8657, 94.3500, 98.9867, 103.8053] +24-11-19 20:19:10 | D | best error = [ 2.5812, 2.5812, 2.5812, 2.5812, 2.5812] +24-11-19 20:19:10 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:10 | D | sum error = [ 108.8140, 113.9961, 119.3811, 124.9673, 130.7175] +24-11-19 20:19:10 | D | best error = [ 2.5812, 2.5812, 2.5812, 2.5812, 2.5812] +24-11-19 20:19:10 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:10 | D | sum error = [ 136.7092, 142.8814, 149.2673, 155.8645, 162.6935] +24-11-19 20:19:10 | D | best error = [ 2.5812, 2.5812, 2.5812, 2.5812, 2.5812] +24-11-19 20:19:10 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:10 | D | sum error = [ 169.6983, 176.9107, 184.3597, 192.0216, 199.8966] +24-11-19 20:19:10 | D | best error = [ 2.5812, 2.5812, 2.5812, 2.5812, 2.5812] +24-11-19 20:19:10 | D | + error = [2.5812] +24-11-19 20:19:10 | D | - Calibrating model.layers.1.mlp.down_proj.weight +24-11-19 20:19:10 | D | + w: sint8 +24-11-19 20:19:10 | D | + x: None +24-11-19 20:19:10 | D | + y: None +24-11-19 20:19:10 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:10 | D | + finished parsing calibration arguments, ram usage: 14.0 +24-11-19 20:19:10 | D | + finished reseting calibrator, ram usage: 14.0 +24-11-19 20:19:10 | D | + finished calculating the original outputs, ram usage: 14.0 +24-11-19 20:19:10 | D | - range ratio = [ 1.0000] +24-11-19 20:19:10 | D | sum error = [ 7.9591] +24-11-19 20:19:10 | D | best error = [ 7.9591] +24-11-19 20:19:11 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:11 | D | sum error = [ 7.9157, 7.8600, 7.6944, 7.6239, 7.6451] +24-11-19 20:19:11 | D | best error = [ 5.3060, 3.5581, 2.5455, 2.0892, 1.8233] +24-11-19 20:19:11 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:11 | D | sum error = [ 7.4927, 7.4258, 7.3341, 7.2715, 7.1534] +24-11-19 20:19:11 | D | best error = [ 1.6384, 1.4976, 1.3851, 1.2995, 1.2109] +24-11-19 20:19:11 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:11 | D | sum error = [ 7.1480, 7.0531, 6.9486, 6.9361, 6.8553] +24-11-19 20:19:11 | D | best error = [ 1.1280, 1.0695, 1.0201, 0.9718, 0.9320] +24-11-19 20:19:11 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:11 | D | sum error = [ 6.6392, 6.5877, 6.6797, 6.4963, 6.3144] +24-11-19 20:19:11 | D | best error = [ 0.9013, 0.8758, 0.8497, 0.8245, 0.8024] +24-11-19 20:19:11 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:11 | D | sum error = [ 6.3767, 6.2337, 6.1571, 6.0932, 6.0145] +24-11-19 20:19:11 | D | best error = [ 0.7824, 0.7624, 0.7423, 0.7271, 0.7084] +24-11-19 20:19:11 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:11 | D | sum error = [ 5.9206, 5.8804, 5.8285, 5.7614, 5.7062] +24-11-19 20:19:11 | D | best error = [ 0.6922, 0.6758, 0.6603, 0.6469, 0.6383] +24-11-19 20:19:11 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:11 | D | sum error = [ 5.8050, 6.0816, 6.5824, 7.5586, 9.0175] +24-11-19 20:19:11 | D | best error = [ 0.6261, 0.6182, 0.6088, 0.6042, 0.5984] +24-11-19 20:19:11 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:11 | D | sum error = [ 10.9590, 13.4601, 16.6624, 20.6222, 25.3745] +24-11-19 20:19:11 | D | best error = [ 0.5932, 0.5879, 0.5846, 0.5820, 0.5810] +24-11-19 20:19:11 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:11 | D | sum error = [ 30.9931, 37.6028, 45.2574, 53.9782, 63.7948] +24-11-19 20:19:11 | D | best error = [ 0.5779, 0.5775, 0.5771, 0.5763, 0.5761] +24-11-19 20:19:11 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:11 | D | sum error = [ 74.6279, 86.4621, 99.1837, 112.7871, 127.1712] +24-11-19 20:19:11 | D | best error = [ 0.5761, 0.5757, 0.5757, 0.5757, 0.5757] +24-11-19 20:19:11 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:11 | D | sum error = [ 142.2491, 157.9393, 174.1446, 190.7975, 207.8472] +24-11-19 20:19:11 | D | best error = [ 0.5757, 0.5755, 0.5755, 0.5754, 0.5754] +24-11-19 20:19:11 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:11 | D | sum error = [ 225.2549, 242.9607, 260.9119, 279.0856, 297.4546] +24-11-19 20:19:11 | D | best error = [ 0.5754, 0.5754, 0.5754, 0.5754, 0.5754] +24-11-19 20:19:11 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:11 | D | sum error = [ 315.9477, 334.5793, 353.3325, 372.1835, 391.1234] +24-11-19 20:19:11 | D | best error = [ 0.5754, 0.5754, 0.5754, 0.5754, 0.5754] +24-11-19 20:19:11 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:11 | D | sum error = [ 410.1313, 429.2203, 448.3491, 467.5553, 486.7729] +24-11-19 20:19:11 | D | best error = [ 0.5754, 0.5754, 0.5754, 0.5754, 0.5754] +24-11-19 20:19:11 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:11 | D | sum error = [ 506.0568, 525.3801, 544.7497, 564.1901, 583.7211] +24-11-19 20:19:11 | D | best error = [ 0.5754, 0.5754, 0.5754, 0.5754, 0.5754] +24-11-19 20:19:11 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:11 | D | sum error = [ 603.3770, 623.1962, 643.2532, 663.6216, 684.3780] +24-11-19 20:19:11 | D | best error = [ 0.5754, 0.5754, 0.5754, 0.5754, 0.5754] +24-11-19 20:19:11 | D | + error = [0.5754] +24-11-19 20:19:11 | D | - Quantizing model.layers.1.self_attn.q_proj.weight +24-11-19 20:19:13 | D | - Quantizing model.layers.1.self_attn.k_proj.weight +24-11-19 20:19:14 | D | - Quantizing model.layers.1.self_attn.v_proj.weight +24-11-19 20:19:15 | D | - Quantizing model.layers.1.self_attn.o_proj.weight +24-11-19 20:19:16 | D | - Quantizing model.layers.1.mlp.up_proj.weight +24-11-19 20:19:17 | D | - Quantizing model.layers.1.mlp.gate_proj.weight +24-11-19 20:19:20 | D | - Quantizing model.layers.1.mlp.down_proj.weight +24-11-19 20:19:33 | D | - Quantizing layer model.layers.2 +24-11-19 20:19:33 | D | - Calibrating model.layers.2.self_attn.q_proj.weight +24-11-19 20:19:33 | D | + w: sint8 +24-11-19 20:19:33 | D | + x: None +24-11-19 20:19:33 | D | + y: None +24-11-19 20:19:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:19:33 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:19:33 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:19:33 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:19:33 | D | - range ratio = [ 1.0000] +24-11-19 20:19:33 | D | sum error = [ 0.7849] +24-11-19 20:19:33 | D | best error = [ 0.7849] +24-11-19 20:19:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:46 | D | sum error = [ 0.7704, 0.7787, 0.7752, 0.7866, 0.8223] +24-11-19 20:19:46 | D | best error = [ 0.7704, 0.7704, 0.7704, 0.7704, 0.7704] +24-11-19 20:19:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:46 | D | sum error = [ 0.8491, 0.8806, 0.9334, 0.9823, 1.0801] +24-11-19 20:19:46 | D | best error = [ 0.7704, 0.7704, 0.7704, 0.7704, 0.7704] +24-11-19 20:19:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:46 | D | sum error = [ 1.1292, 1.2142, 1.3291, 1.4649, 1.5858] +24-11-19 20:19:46 | D | best error = [ 0.7704, 0.7704, 0.7704, 0.7704, 0.7704] +24-11-19 20:19:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:46 | D | sum error = [ 1.7325, 1.9283, 2.1107, 2.3306, 2.5154] +24-11-19 20:19:46 | D | best error = [ 0.7704, 0.7704, 0.7704, 0.7704, 0.7704] +24-11-19 20:19:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:46 | D | sum error = [ 2.7097, 2.9775, 3.2410, 3.6037, 3.9491] +24-11-19 20:19:46 | D | best error = [ 0.7704, 0.7704, 0.7704, 0.7704, 0.7704] +24-11-19 20:19:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:46 | D | sum error = [ 4.3925, 4.7095, 5.1403, 5.6322, 6.1580] +24-11-19 20:19:46 | D | best error = [ 0.7704, 0.7704, 0.7704, 0.7704, 0.7704] +24-11-19 20:19:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:46 | D | sum error = [ 6.7602, 7.3717, 8.0381, 8.7830, 9.6792] +24-11-19 20:19:46 | D | best error = [ 0.7704, 0.7704, 0.7704, 0.7704, 0.7704] +24-11-19 20:19:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:46 | D | sum error = [ 10.5167, 11.4969, 12.6435, 13.7487, 14.9960] +24-11-19 20:19:46 | D | best error = [ 0.7704, 0.7704, 0.7704, 0.7704, 0.7704] +24-11-19 20:19:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:46 | D | sum error = [ 16.4446, 17.9088, 19.5440, 21.3495, 23.2721] +24-11-19 20:19:46 | D | best error = [ 0.7704, 0.7704, 0.7704, 0.7704, 0.7704] +24-11-19 20:19:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:46 | D | sum error = [ 25.3907, 27.7281, 30.2861, 33.0548, 36.1185] +24-11-19 20:19:46 | D | best error = [ 0.7704, 0.7704, 0.7704, 0.7704, 0.7704] +24-11-19 20:19:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:46 | D | sum error = [ 39.2755, 42.8546, 46.7381, 50.8663, 55.4790] +24-11-19 20:19:46 | D | best error = [ 0.7704, 0.7704, 0.7704, 0.7704, 0.7704] +24-11-19 20:19:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:46 | D | sum error = [ 60.3589, 65.8170, 71.7134, 78.0230, 85.0167] +24-11-19 20:19:46 | D | best error = [ 0.7704, 0.7704, 0.7704, 0.7704, 0.7704] +24-11-19 20:19:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:46 | D | sum error = [ 92.3515, 100.6281, 109.3030, 118.8021, 128.9238] +24-11-19 20:19:46 | D | best error = [ 0.7704, 0.7704, 0.7704, 0.7704, 0.7704] +24-11-19 20:19:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:46 | D | sum error = [ 139.9300, 151.9905, 164.7146, 178.4739, 193.4181] +24-11-19 20:19:46 | D | best error = [ 0.7704, 0.7704, 0.7704, 0.7704, 0.7704] +24-11-19 20:19:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:46 | D | sum error = [ 209.3401, 226.6599, 244.9549, 264.9396, 286.5046] +24-11-19 20:19:46 | D | best error = [ 0.7704, 0.7704, 0.7704, 0.7704, 0.7704] +24-11-19 20:19:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:46 | D | sum error = [ 309.5874, 334.2566, 360.8629, 389.1649, 418.9334] +24-11-19 20:19:46 | D | best error = [ 0.7704, 0.7704, 0.7704, 0.7704, 0.7704] +24-11-19 20:19:46 | D | + error = [0.7704] +24-11-19 20:19:46 | D | - Calibrating model.layers.2.self_attn.k_proj.weight +24-11-19 20:19:46 | D | + w: sint8 +24-11-19 20:19:46 | D | + x: None +24-11-19 20:19:46 | D | + y: None +24-11-19 20:19:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:19:46 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:19:46 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:19:46 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:19:46 | D | - range ratio = [ 1.0000] +24-11-19 20:19:46 | D | sum error = [ 1.0471] +24-11-19 20:19:46 | D | best error = [ 1.0471] +24-11-19 20:19:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:59 | D | sum error = [ 0.9317, 0.9074, 0.8292, 0.9575, 1.1383] +24-11-19 20:19:59 | D | best error = [ 0.9317, 0.9074, 0.8292, 0.8292, 0.8292] +24-11-19 20:19:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:59 | D | sum error = [ 1.1057, 1.0135, 1.1687, 1.1716, 1.2804] +24-11-19 20:19:59 | D | best error = [ 0.8292, 0.8292, 0.8292, 0.8292, 0.8292] +24-11-19 20:19:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:59 | D | sum error = [ 1.2056, 1.3547, 1.4846, 1.7430, 1.7868] +24-11-19 20:19:59 | D | best error = [ 0.8292, 0.8292, 0.8292, 0.8292, 0.8292] +24-11-19 20:19:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:59 | D | sum error = [ 1.8537, 2.1995, 2.3824, 2.4872, 2.5539] +24-11-19 20:19:59 | D | best error = [ 0.8292, 0.8292, 0.8292, 0.8292, 0.8292] +24-11-19 20:19:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:59 | D | sum error = [ 2.8171, 3.0273, 3.2563, 3.4494, 3.8974] +24-11-19 20:19:59 | D | best error = [ 0.8292, 0.8292, 0.8292, 0.8292, 0.8292] +24-11-19 20:19:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:59 | D | sum error = [ 4.1791, 4.4689, 4.8367, 5.3247, 5.8291] +24-11-19 20:19:59 | D | best error = [ 0.8292, 0.8292, 0.8292, 0.8292, 0.8292] +24-11-19 20:19:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:59 | D | sum error = [ 6.5179, 6.9626, 7.6542, 8.3334, 9.0400] +24-11-19 20:19:59 | D | best error = [ 0.8292, 0.8292, 0.8292, 0.8292, 0.8292] +24-11-19 20:19:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:59 | D | sum error = [ 10.0856, 11.0077, 11.8651, 12.8760, 14.1177] +24-11-19 20:19:59 | D | best error = [ 0.8292, 0.8292, 0.8292, 0.8292, 0.8292] +24-11-19 20:19:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:59 | D | sum error = [ 15.4786, 16.9470, 18.4812, 20.3649, 22.1117] +24-11-19 20:19:59 | D | best error = [ 0.8292, 0.8292, 0.8292, 0.8292, 0.8292] +24-11-19 20:19:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:59 | D | sum error = [ 24.1927, 26.7109, 29.2389, 31.9061, 34.7899] +24-11-19 20:19:59 | D | best error = [ 0.8292, 0.8292, 0.8292, 0.8292, 0.8292] +24-11-19 20:19:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:59 | D | sum error = [ 38.0717, 41.5116, 45.2895, 49.5512, 53.9019] +24-11-19 20:19:59 | D | best error = [ 0.8292, 0.8292, 0.8292, 0.8292, 0.8292] +24-11-19 20:19:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:59 | D | sum error = [ 58.8410, 64.1463, 69.7238, 76.4318, 83.1741] +24-11-19 20:19:59 | D | best error = [ 0.8292, 0.8292, 0.8292, 0.8292, 0.8292] +24-11-19 20:19:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:59 | D | sum error = [ 90.4036, 98.2138, 106.9035, 116.1820, 126.4904] +24-11-19 20:19:59 | D | best error = [ 0.8292, 0.8292, 0.8292, 0.8292, 0.8292] +24-11-19 20:19:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:59 | D | sum error = [ 137.8867, 150.1921, 163.2171, 177.4678, 193.1061] +24-11-19 20:19:59 | D | best error = [ 0.8292, 0.8292, 0.8292, 0.8292, 0.8292] +24-11-19 20:19:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:59 | D | sum error = [ 209.7158, 227.5809, 247.0388, 267.9573, 290.3299] +24-11-19 20:19:59 | D | best error = [ 0.8292, 0.8292, 0.8292, 0.8292, 0.8292] +24-11-19 20:19:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:59 | D | sum error = [ 314.3672, 340.1315, 368.2259, 397.7113, 428.6936] +24-11-19 20:19:59 | D | best error = [ 0.8292, 0.8292, 0.8292, 0.8292, 0.8292] +24-11-19 20:19:59 | D | + error = [0.8292] +24-11-19 20:19:59 | D | - Calibrating model.layers.2.self_attn.v_proj.weight +24-11-19 20:19:59 | D | + w: sint8 +24-11-19 20:19:59 | D | + x: None +24-11-19 20:19:59 | D | + y: None +24-11-19 20:19:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:59 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:19:59 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:19:59 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:19:59 | D | - range ratio = [ 1.0000] +24-11-19 20:19:59 | D | sum error = [ 0.8206] +24-11-19 20:19:59 | D | best error = [ 0.8206] +24-11-19 20:19:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:19:59 | D | sum error = [ 0.8166, 0.8108, 0.8090, 0.8218, 0.8327] +24-11-19 20:19:59 | D | best error = [ 0.7554, 0.7306, 0.7185, 0.7127, 0.7094] +24-11-19 20:19:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:19:59 | D | sum error = [ 0.8652, 0.8975, 0.9325, 0.9729, 1.0205] +24-11-19 20:19:59 | D | best error = [ 0.7073, 0.7068, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:19:59 | D | sum error = [ 1.0815, 1.1517, 1.2347, 1.3097, 1.4000] +24-11-19 20:19:59 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:19:59 | D | sum error = [ 1.5127, 1.6152, 1.7232, 1.8518, 1.9805] +24-11-19 20:19:59 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:19:59 | D | sum error = [ 2.1151, 2.2710, 2.4385, 2.6100, 2.7959] +24-11-19 20:19:59 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:19:59 | D | sum error = [ 2.9916, 3.2027, 3.4188, 3.6549, 3.8908] +24-11-19 20:19:59 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:19:59 | D | sum error = [ 4.1590, 4.4351, 4.7179, 5.0185, 5.3429] +24-11-19 20:19:59 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:19:59 | D | sum error = [ 5.6892, 6.0510, 6.4315, 6.8304, 7.2529] +24-11-19 20:19:59 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:19:59 | D | sum error = [ 7.6971, 8.1624, 8.6492, 9.1593, 9.6983] +24-11-19 20:19:59 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:19:59 | D | sum error = [ 10.2621, 10.8530, 11.4770, 12.1218, 12.7997] +24-11-19 20:19:59 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:19:59 | D | sum error = [ 13.5131, 14.2653, 15.0476, 15.8721, 16.7313] +24-11-19 20:19:59 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:19:59 | D | sum error = [ 17.6223, 18.5602, 19.5330, 20.5604, 21.6280] +24-11-19 20:19:59 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:19:59 | D | sum error = [ 22.7468, 23.9114, 25.1173, 26.3843, 27.6975] +24-11-19 20:19:59 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:19:59 | D | sum error = [ 29.0595, 30.4782, 31.9561, 33.4867, 35.0699] +24-11-19 20:19:59 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:19:59 | D | sum error = [ 36.7135, 38.4198, 40.1863, 42.0146, 43.9055] +24-11-19 20:19:59 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:19:59 | D | sum error = [ 45.8630, 47.8860, 49.9767, 52.1387, 54.3616] +24-11-19 20:19:59 | D | best error = [ 0.7066, 0.7066, 0.7066, 0.7066, 0.7066] +24-11-19 20:19:59 | D | + error = [0.7066] +24-11-19 20:19:59 | D | - Calibrating model.layers.2.self_attn.o_proj.weight +24-11-19 20:19:59 | D | + w: sint8 +24-11-19 20:19:59 | D | + x: None +24-11-19 20:19:59 | D | + y: None +24-11-19 20:19:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:19:59 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:00 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:00 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:00 | D | - range ratio = [ 1.0000] +24-11-19 20:20:00 | D | sum error = [ 0.1002] +24-11-19 20:20:00 | D | best error = [ 0.1002] +24-11-19 20:20:00 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:00 | D | sum error = [ 0.0992, 0.0992, 0.1000, 0.1004, 0.1026] +24-11-19 20:20:00 | D | best error = [ 0.0891, 0.0847, 0.0822, 0.0806, 0.0797] +24-11-19 20:20:00 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:00 | D | sum error = [ 0.1048, 0.1082, 0.1122, 0.1169, 0.1233] +24-11-19 20:20:00 | D | best error = [ 0.0790, 0.0786, 0.0783, 0.0781, 0.0780] +24-11-19 20:20:00 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:00 | D | sum error = [ 0.1288, 0.1373, 0.1451, 0.1546, 0.1649] +24-11-19 20:20:00 | D | best error = [ 0.0780, 0.0779, 0.0779, 0.0778, 0.0778] +24-11-19 20:20:00 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:00 | D | sum error = [ 0.1759, 0.1872, 0.1997, 0.2131, 0.2281] +24-11-19 20:20:00 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:20:00 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:00 | D | sum error = [ 0.2434, 0.2599, 0.2767, 0.2957, 0.3145] +24-11-19 20:20:00 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:20:00 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:00 | D | sum error = [ 0.3351, 0.3569, 0.3798, 0.4040, 0.4310] +24-11-19 20:20:00 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:20:00 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:00 | D | sum error = [ 0.4577, 0.4860, 0.5157, 0.5475, 0.5809] +24-11-19 20:20:00 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:20:00 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:00 | D | sum error = [ 0.6154, 0.6526, 0.6916, 0.7329, 0.7753] +24-11-19 20:20:00 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:20:00 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:00 | D | sum error = [ 0.8209, 0.8676, 0.9185, 0.9712, 1.0261] +24-11-19 20:20:00 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:20:00 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:00 | D | sum error = [ 1.0844, 1.1460, 1.2098, 1.2770, 1.3477] +24-11-19 20:20:00 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:20:00 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:00 | D | sum error = [ 1.4210, 1.4990, 1.5798, 1.6652, 1.7543] +24-11-19 20:20:00 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:20:00 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:00 | D | sum error = [ 1.8480, 1.9456, 2.0482, 2.1554, 2.2674] +24-11-19 20:20:00 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:20:00 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:00 | D | sum error = [ 2.3843, 2.5068, 2.6350, 2.7693, 2.9086] +24-11-19 20:20:00 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:20:00 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:00 | D | sum error = [ 3.0550, 3.2075, 3.3673, 3.5329, 3.7058] +24-11-19 20:20:00 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:20:00 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:00 | D | sum error = [ 3.8852, 4.0723, 4.2671, 4.4695, 4.6802] +24-11-19 20:20:00 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:20:00 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:00 | D | sum error = [ 4.8984, 5.1253, 5.3607, 5.6054, 5.8593] +24-11-19 20:20:00 | D | best error = [ 0.0778, 0.0778, 0.0778, 0.0778, 0.0778] +24-11-19 20:20:00 | D | + error = [0.0778] +24-11-19 20:20:00 | D | - Calibrating model.layers.2.mlp.up_proj.weight +24-11-19 20:20:00 | D | + w: sint8 +24-11-19 20:20:00 | D | + x: None +24-11-19 20:20:00 | D | + y: None +24-11-19 20:20:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:00 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:00 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:01 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:01 | D | - range ratio = [ 1.0000] +24-11-19 20:20:01 | D | sum error = [ 3.5336] +24-11-19 20:20:01 | D | best error = [ 3.5336] +24-11-19 20:20:02 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:02 | D | sum error = [ 3.5090, 3.5031, 3.5199, 3.5563, 3.6225] +24-11-19 20:20:02 | D | best error = [ 3.2475, 3.1424, 3.0915, 3.0633, 3.0485] +24-11-19 20:20:02 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:02 | D | sum error = [ 3.7037, 3.8344, 3.9768, 4.1717, 4.3847] +24-11-19 20:20:02 | D | best error = [ 3.0412, 3.0384, 3.0374, 3.0371, 3.0370] +24-11-19 20:20:02 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:02 | D | sum error = [ 4.6433, 4.9324, 5.2460, 5.5985, 5.9849] +24-11-19 20:20:02 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 20:20:02 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:02 | D | sum error = [ 6.4009, 6.8539, 7.3394, 7.8677, 8.4220] +24-11-19 20:20:02 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 20:20:02 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:02 | D | sum error = [ 9.0258, 9.6695, 10.3381, 11.0432, 11.8103] +24-11-19 20:20:02 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 20:20:02 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:02 | D | sum error = [ 12.6106, 13.4655, 14.3595, 15.3059, 16.2943] +24-11-19 20:20:02 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 20:20:02 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:02 | D | sum error = [ 17.3485, 18.4573, 19.6121, 20.8390, 22.1253] +24-11-19 20:20:02 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 20:20:02 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:02 | D | sum error = [ 23.4742, 24.8924, 26.3868, 27.9376, 29.5723] +24-11-19 20:20:02 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 20:20:02 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:02 | D | sum error = [ 31.2824, 33.0532, 34.9262, 36.8740, 38.8968] +24-11-19 20:20:02 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 20:20:02 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:02 | D | sum error = [ 41.0087, 43.2170, 45.5108, 47.8900, 50.3837] +24-11-19 20:20:02 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 20:20:02 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:02 | D | sum error = [ 52.9509, 55.6319, 58.4030, 61.2823, 64.2640] +24-11-19 20:20:02 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 20:20:02 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:02 | D | sum error = [ 67.3505, 70.5512, 73.8495, 77.2646, 80.7889] +24-11-19 20:20:02 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 20:20:02 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:02 | D | sum error = [ 84.4283, 88.1791, 92.0529, 96.0420, 100.1537] +24-11-19 20:20:02 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 20:20:02 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:02 | D | sum error = [ 104.3757, 108.7308, 113.1862, 117.7821, 122.4816] +24-11-19 20:20:02 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 20:20:02 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:02 | D | sum error = [ 127.3148, 132.2707, 137.3487, 142.5580, 147.8896] +24-11-19 20:20:02 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 20:20:02 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:02 | D | sum error = [ 153.3617, 158.9587, 164.7029, 170.5801, 176.6053] +24-11-19 20:20:02 | D | best error = [ 3.0370, 3.0370, 3.0370, 3.0370, 3.0370] +24-11-19 20:20:02 | D | + error = [3.0370] +24-11-19 20:20:02 | D | - Calibrating model.layers.2.mlp.gate_proj.weight +24-11-19 20:20:02 | D | + w: sint8 +24-11-19 20:20:02 | D | + x: None +24-11-19 20:20:02 | D | + y: None +24-11-19 20:20:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:02 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:02 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:02 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:02 | D | - range ratio = [ 1.0000] +24-11-19 20:20:02 | D | sum error = [ 3.9979] +24-11-19 20:20:02 | D | best error = [ 3.9979] +24-11-19 20:20:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:03 | D | sum error = [ 3.9786, 3.9602, 3.9845, 4.0197, 4.0982] +24-11-19 20:20:03 | D | best error = [ 3.6791, 3.5607, 3.5039, 3.4718, 3.4547] +24-11-19 20:20:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:03 | D | sum error = [ 4.2016, 4.3490, 4.5202, 4.7271, 4.9827] +24-11-19 20:20:03 | D | best error = [ 3.4468, 3.4436, 3.4427, 3.4423, 3.4423] +24-11-19 20:20:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:03 | D | sum error = [ 5.2610, 5.5997, 5.9431, 6.3508, 6.7836] +24-11-19 20:20:03 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:20:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:03 | D | sum error = [ 7.2726, 7.7933, 8.3510, 8.9396, 9.5742] +24-11-19 20:20:03 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:20:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:03 | D | sum error = [ 10.2557, 10.9923, 11.7529, 12.5644, 13.4402] +24-11-19 20:20:03 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:20:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:03 | D | sum error = [ 14.3533, 15.3234, 16.3636, 17.4521, 18.5963] +24-11-19 20:20:03 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:20:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:03 | D | sum error = [ 19.8087, 21.0840, 22.4182, 23.8391, 25.3311] +24-11-19 20:20:03 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:20:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:03 | D | sum error = [ 26.9096, 28.5592, 30.2878, 32.1126, 34.0178] +24-11-19 20:20:03 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:20:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:03 | D | sum error = [ 36.0199, 38.1137, 40.3158, 42.6220, 45.0296] +24-11-19 20:20:03 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:20:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:03 | D | sum error = [ 47.5568, 50.2098, 52.9698, 55.8779, 58.8924] +24-11-19 20:20:03 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:20:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:03 | D | sum error = [ 62.0537, 65.3526, 68.7920, 72.3749, 76.0956] +24-11-19 20:20:03 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:20:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:03 | D | sum error = [ 79.9834, 84.0268, 88.2236, 92.5855, 97.1235] +24-11-19 20:20:03 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:20:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:03 | D | sum error = [ 101.8331, 106.7281, 111.7999, 117.0733, 122.5213] +24-11-19 20:20:03 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:20:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:03 | D | sum error = [ 128.1659, 134.0279, 140.0567, 146.3147, 152.7707] +24-11-19 20:20:03 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:20:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:03 | D | sum error = [ 159.4414, 166.3261, 173.4338, 180.7577, 188.3048] +24-11-19 20:20:03 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:20:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:03 | D | sum error = [ 196.0720, 204.0795, 212.3117, 220.7768, 229.4797] +24-11-19 20:20:03 | D | best error = [ 3.4423, 3.4423, 3.4423, 3.4423, 3.4423] +24-11-19 20:20:03 | D | + error = [3.4423] +24-11-19 20:20:03 | D | - Calibrating model.layers.2.mlp.down_proj.weight +24-11-19 20:20:03 | D | + w: sint8 +24-11-19 20:20:03 | D | + x: None +24-11-19 20:20:03 | D | + y: None +24-11-19 20:20:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:03 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:03 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:04 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:04 | D | - range ratio = [ 1.0000] +24-11-19 20:20:04 | D | sum error = [ 0.2097] +24-11-19 20:20:04 | D | best error = [ 0.2097] +24-11-19 20:20:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:05 | D | sum error = [ 0.2077, 0.2059, 0.2046, 0.2036, 0.2034] +24-11-19 20:20:05 | D | best error = [ 0.2027, 0.1991, 0.1964, 0.1945, 0.1930] +24-11-19 20:20:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:05 | D | sum error = [ 0.2029, 0.2035, 0.2046, 0.2068, 0.2094] +24-11-19 20:20:05 | D | best error = [ 0.1916, 0.1905, 0.1896, 0.1889, 0.1884] +24-11-19 20:20:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:05 | D | sum error = [ 0.2133, 0.2179, 0.2240, 0.2308, 0.2392] +24-11-19 20:20:05 | D | best error = [ 0.1880, 0.1878, 0.1876, 0.1874, 0.1873] +24-11-19 20:20:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:05 | D | sum error = [ 0.2496, 0.2608, 0.2740, 0.2886, 0.3048] +24-11-19 20:20:05 | D | best error = [ 0.1872, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:20:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:05 | D | sum error = [ 0.3229, 0.3432, 0.3651, 0.3891, 0.4153] +24-11-19 20:20:05 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:20:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:05 | D | sum error = [ 0.4439, 0.4744, 0.5074, 0.5433, 0.5813] +24-11-19 20:20:05 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:20:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:05 | D | sum error = [ 0.6226, 0.6662, 0.7134, 0.7634, 0.8170] +24-11-19 20:20:05 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:20:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:05 | D | sum error = [ 0.8739, 0.9347, 0.9994, 1.0678, 1.1406] +24-11-19 20:20:05 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:20:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:05 | D | sum error = [ 1.2180, 1.2998, 1.3866, 1.4784, 1.5758] +24-11-19 20:20:05 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:20:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:05 | D | sum error = [ 1.6789, 1.7876, 1.9025, 2.0236, 2.1516] +24-11-19 20:20:05 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:20:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:05 | D | sum error = [ 2.2862, 2.4284, 2.5776, 2.7349, 2.9004] +24-11-19 20:20:05 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:20:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:05 | D | sum error = [ 3.0740, 3.2564, 3.4477, 3.6480, 3.8590] +24-11-19 20:20:05 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:20:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:05 | D | sum error = [ 4.0792, 4.3101, 4.5522, 4.8054, 5.0701] +24-11-19 20:20:05 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:20:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:05 | D | sum error = [ 5.3472, 5.6363, 5.9380, 6.2533, 6.5809] +24-11-19 20:20:05 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:20:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:05 | D | sum error = [ 6.9224, 7.2778, 7.6475, 8.0318, 8.4308] +24-11-19 20:20:05 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:20:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:05 | D | sum error = [ 8.8448, 9.2738, 9.7182, 10.1778, 10.6535] +24-11-19 20:20:05 | D | best error = [ 0.1871, 0.1871, 0.1871, 0.1871, 0.1871] +24-11-19 20:20:05 | D | + error = [0.1871] +24-11-19 20:20:05 | D | - Quantizing model.layers.2.self_attn.q_proj.weight +24-11-19 20:20:06 | D | - Quantizing model.layers.2.self_attn.k_proj.weight +24-11-19 20:20:07 | D | - Quantizing model.layers.2.self_attn.v_proj.weight +24-11-19 20:20:08 | D | - Quantizing model.layers.2.self_attn.o_proj.weight +24-11-19 20:20:09 | D | - Quantizing model.layers.2.mlp.up_proj.weight +24-11-19 20:20:11 | D | - Quantizing model.layers.2.mlp.gate_proj.weight +24-11-19 20:20:12 | D | - Quantizing model.layers.2.mlp.down_proj.weight +24-11-19 20:20:25 | D | - Quantizing layer model.layers.3 +24-11-19 20:20:25 | D | - Calibrating model.layers.3.self_attn.q_proj.weight +24-11-19 20:20:25 | D | + w: sint8 +24-11-19 20:20:25 | D | + x: None +24-11-19 20:20:25 | D | + y: None +24-11-19 20:20:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:20:25 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:20:25 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:20:25 | D | + finished calculating the original outputs, ram usage: 13.2 +24-11-19 20:20:25 | D | - range ratio = [ 1.0000] +24-11-19 20:20:25 | D | sum error = [ 1.1043] +24-11-19 20:20:25 | D | best error = [ 1.1043] +24-11-19 20:20:38 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:38 | D | sum error = [ 1.1012, 1.1062, 1.0834, 1.1246, 1.1392] +24-11-19 20:20:38 | D | best error = [ 1.1012, 1.1012, 1.0834, 1.0834, 1.0834] +24-11-19 20:20:38 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:38 | D | sum error = [ 1.1466, 1.2368, 1.2812, 1.3912, 1.4697] +24-11-19 20:20:38 | D | best error = [ 1.0834, 1.0834, 1.0834, 1.0834, 1.0834] +24-11-19 20:20:38 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:38 | D | sum error = [ 1.6375, 1.7140, 1.9410, 2.1257, 2.2858] +24-11-19 20:20:38 | D | best error = [ 1.0834, 1.0834, 1.0834, 1.0834, 1.0834] +24-11-19 20:20:38 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:38 | D | sum error = [ 2.5396, 2.8202, 3.1136, 3.4969, 3.8106] +24-11-19 20:20:38 | D | best error = [ 1.0834, 1.0834, 1.0834, 1.0834, 1.0834] +24-11-19 20:20:38 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:38 | D | sum error = [ 4.2868, 4.6375, 5.1740, 5.7273, 6.4082] +24-11-19 20:20:38 | D | best error = [ 1.0834, 1.0834, 1.0834, 1.0834, 1.0834] +24-11-19 20:20:38 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:38 | D | sum error = [ 7.1028, 7.8023, 8.5855, 9.5428, 10.4426] +24-11-19 20:20:38 | D | best error = [ 1.0834, 1.0834, 1.0834, 1.0834, 1.0834] +24-11-19 20:20:38 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:38 | D | sum error = [ 11.5220, 12.6264, 13.9552, 15.4387, 16.9413] +24-11-19 20:20:38 | D | best error = [ 1.0834, 1.0834, 1.0834, 1.0834, 1.0834] +24-11-19 20:20:38 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:38 | D | sum error = [ 18.6932, 20.6032, 22.5725, 24.7844, 27.1996] +24-11-19 20:20:38 | D | best error = [ 1.0834, 1.0834, 1.0834, 1.0834, 1.0834] +24-11-19 20:20:38 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:38 | D | sum error = [ 29.9556, 32.8717, 35.9668, 39.4186, 42.9919] +24-11-19 20:20:38 | D | best error = [ 1.0834, 1.0834, 1.0834, 1.0834, 1.0834] +24-11-19 20:20:38 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:38 | D | sum error = [ 46.9763, 51.3205, 55.8212, 60.5845, 65.8919] +24-11-19 20:20:38 | D | best error = [ 1.0834, 1.0834, 1.0834, 1.0834, 1.0834] +24-11-19 20:20:38 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:38 | D | sum error = [ 71.5512, 77.6740, 84.2954, 91.2005, 98.4902] +24-11-19 20:20:38 | D | best error = [ 1.0834, 1.0834, 1.0834, 1.0834, 1.0834] +24-11-19 20:20:38 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:38 | D | sum error = [ 106.6689, 115.2105, 124.5743, 134.5547, 145.2688] +24-11-19 20:20:38 | D | best error = [ 1.0834, 1.0834, 1.0834, 1.0834, 1.0834] +24-11-19 20:20:38 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:38 | D | sum error = [ 156.5754, 168.3684, 181.2854, 195.0487, 209.4949] +24-11-19 20:20:38 | D | best error = [ 1.0834, 1.0834, 1.0834, 1.0834, 1.0834] +24-11-19 20:20:38 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:38 | D | sum error = [ 224.9354, 241.5909, 258.8920, 277.1718, 296.6189] +24-11-19 20:20:38 | D | best error = [ 1.0834, 1.0834, 1.0834, 1.0834, 1.0834] +24-11-19 20:20:38 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:38 | D | sum error = [ 317.2524, 338.9487, 361.4204, 385.0182, 409.2765] +24-11-19 20:20:38 | D | best error = [ 1.0834, 1.0834, 1.0834, 1.0834, 1.0834] +24-11-19 20:20:38 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:38 | D | sum error = [ 434.4582, 459.7654, 486.2094, 512.4019, 538.8992] +24-11-19 20:20:38 | D | best error = [ 1.0834, 1.0834, 1.0834, 1.0834, 1.0834] +24-11-19 20:20:38 | D | + error = [1.0834] +24-11-19 20:20:38 | D | - Calibrating model.layers.3.self_attn.k_proj.weight +24-11-19 20:20:38 | D | + w: sint8 +24-11-19 20:20:38 | D | + x: None +24-11-19 20:20:38 | D | + y: None +24-11-19 20:20:38 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:20:38 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:38 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:38 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:38 | D | - range ratio = [ 1.0000] +24-11-19 20:20:38 | D | sum error = [ 1.2536] +24-11-19 20:20:38 | D | best error = [ 1.2536] +24-11-19 20:20:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:51 | D | sum error = [ 1.2223, 1.1755, 1.3606, 1.3067, 1.2065] +24-11-19 20:20:51 | D | best error = [ 1.2223, 1.1755, 1.1755, 1.1755, 1.1755] +24-11-19 20:20:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:51 | D | sum error = [ 1.5960, 1.5947, 1.6459, 1.5654, 1.6024] +24-11-19 20:20:51 | D | best error = [ 1.1755, 1.1755, 1.1755, 1.1755, 1.1755] +24-11-19 20:20:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:51 | D | sum error = [ 1.7671, 2.1555, 2.1663, 2.5345, 2.6862] +24-11-19 20:20:51 | D | best error = [ 1.1755, 1.1755, 1.1755, 1.1755, 1.1755] +24-11-19 20:20:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:51 | D | sum error = [ 3.2196, 3.6067, 3.7819, 4.1617, 4.5280] +24-11-19 20:20:51 | D | best error = [ 1.1755, 1.1755, 1.1755, 1.1755, 1.1755] +24-11-19 20:20:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:51 | D | sum error = [ 5.0374, 5.7101, 6.1235, 6.7523, 7.3442] +24-11-19 20:20:51 | D | best error = [ 1.1755, 1.1755, 1.1755, 1.1755, 1.1755] +24-11-19 20:20:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:51 | D | sum error = [ 7.9850, 8.6965, 9.6021, 10.2929, 11.5127] +24-11-19 20:20:51 | D | best error = [ 1.1755, 1.1755, 1.1755, 1.1755, 1.1755] +24-11-19 20:20:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:51 | D | sum error = [ 12.6596, 13.7540, 15.0139, 16.4077, 17.9014] +24-11-19 20:20:51 | D | best error = [ 1.1755, 1.1755, 1.1755, 1.1755, 1.1755] +24-11-19 20:20:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:51 | D | sum error = [ 19.8394, 21.4597, 23.2485, 25.8556, 28.0267] +24-11-19 20:20:51 | D | best error = [ 1.1755, 1.1755, 1.1755, 1.1755, 1.1755] +24-11-19 20:20:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:51 | D | sum error = [ 30.7642, 33.4921, 36.5152, 39.8823, 43.7007] +24-11-19 20:20:51 | D | best error = [ 1.1755, 1.1755, 1.1755, 1.1755, 1.1755] +24-11-19 20:20:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:51 | D | sum error = [ 47.6934, 51.9535, 56.6662, 61.8657, 67.5682] +24-11-19 20:20:51 | D | best error = [ 1.1755, 1.1755, 1.1755, 1.1755, 1.1755] +24-11-19 20:20:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:51 | D | sum error = [ 73.9427, 80.4778, 87.7310, 95.6817, 104.0848] +24-11-19 20:20:51 | D | best error = [ 1.1755, 1.1755, 1.1755, 1.1755, 1.1755] +24-11-19 20:20:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:51 | D | sum error = [ 113.1233, 122.8185, 133.1906, 144.3266, 156.3433] +24-11-19 20:20:51 | D | best error = [ 1.1755, 1.1755, 1.1755, 1.1755, 1.1755] +24-11-19 20:20:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:51 | D | sum error = [ 168.8556, 182.1604, 196.1916, 211.4089, 227.2788] +24-11-19 20:20:51 | D | best error = [ 1.1755, 1.1755, 1.1755, 1.1755, 1.1755] +24-11-19 20:20:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:51 | D | sum error = [ 244.0295, 261.7601, 280.9732, 301.2761, 321.8264] +24-11-19 20:20:51 | D | best error = [ 1.1755, 1.1755, 1.1755, 1.1755, 1.1755] +24-11-19 20:20:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:51 | D | sum error = [ 344.1851, 367.6157, 391.2812, 415.8285, 441.4167] +24-11-19 20:20:51 | D | best error = [ 1.1755, 1.1755, 1.1755, 1.1755, 1.1755] +24-11-19 20:20:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:51 | D | sum error = [ 467.2742, 493.1093, 519.2063, 545.6392, 571.7935] +24-11-19 20:20:51 | D | best error = [ 1.1755, 1.1755, 1.1755, 1.1755, 1.1755] +24-11-19 20:20:51 | D | + error = [1.1755] +24-11-19 20:20:51 | D | - Calibrating model.layers.3.self_attn.v_proj.weight +24-11-19 20:20:51 | D | + w: sint8 +24-11-19 20:20:51 | D | + x: None +24-11-19 20:20:51 | D | + y: None +24-11-19 20:20:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:51 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:51 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:51 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:51 | D | - range ratio = [ 1.0000] +24-11-19 20:20:51 | D | sum error = [ 1.1202] +24-11-19 20:20:51 | D | best error = [ 1.1202] +24-11-19 20:20:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:51 | D | sum error = [ 1.1038, 1.1016, 1.1164, 1.1283, 1.1469] +24-11-19 20:20:51 | D | best error = [ 1.0295, 0.9988, 0.9839, 0.9765, 0.9716] +24-11-19 20:20:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:51 | D | sum error = [ 1.1881, 1.2076, 1.2720, 1.3149, 1.3862] +24-11-19 20:20:51 | D | best error = [ 0.9690, 0.9683, 0.9677, 0.9676, 0.9676] +24-11-19 20:20:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:51 | D | sum error = [ 1.4581, 1.5489, 1.6523, 1.7699, 1.8787] +24-11-19 20:20:51 | D | best error = [ 0.9676, 0.9676, 0.9676, 0.9676, 0.9676] +24-11-19 20:20:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:51 | D | sum error = [ 2.0079, 2.1545, 2.2971, 2.4628, 2.6343] +24-11-19 20:20:51 | D | best error = [ 0.9676, 0.9676, 0.9676, 0.9676, 0.9676] +24-11-19 20:20:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:51 | D | sum error = [ 2.8179, 3.0161, 3.2291, 3.4557, 3.6961] +24-11-19 20:20:51 | D | best error = [ 0.9676, 0.9676, 0.9676, 0.9676, 0.9676] +24-11-19 20:20:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:51 | D | sum error = [ 3.9542, 4.2226, 4.5092, 4.8166, 5.1366] +24-11-19 20:20:51 | D | best error = [ 0.9676, 0.9676, 0.9676, 0.9676, 0.9676] +24-11-19 20:20:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:51 | D | sum error = [ 5.4757, 5.8410, 6.2142, 6.6093, 7.0351] +24-11-19 20:20:51 | D | best error = [ 0.9676, 0.9676, 0.9676, 0.9676, 0.9676] +24-11-19 20:20:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:51 | D | sum error = [ 7.4763, 7.9477, 8.4232, 8.9330, 9.4623] +24-11-19 20:20:51 | D | best error = [ 0.9676, 0.9676, 0.9676, 0.9676, 0.9676] +24-11-19 20:20:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:51 | D | sum error = [ 10.0352, 10.6160, 11.2391, 11.8919, 12.5845] +24-11-19 20:20:51 | D | best error = [ 0.9676, 0.9676, 0.9676, 0.9676, 0.9676] +24-11-19 20:20:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:51 | D | sum error = [ 13.3005, 14.0561, 14.8525, 15.6793, 16.5375] +24-11-19 20:20:51 | D | best error = [ 0.9676, 0.9676, 0.9676, 0.9676, 0.9676] +24-11-19 20:20:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:51 | D | sum error = [ 17.4495, 18.3951, 19.3821, 20.4121, 21.4901] +24-11-19 20:20:51 | D | best error = [ 0.9676, 0.9676, 0.9676, 0.9676, 0.9676] +24-11-19 20:20:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:51 | D | sum error = [ 22.6144, 23.7926, 25.0131, 26.2966, 27.6232] +24-11-19 20:20:51 | D | best error = [ 0.9676, 0.9676, 0.9676, 0.9676, 0.9676] +24-11-19 20:20:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:51 | D | sum error = [ 29.0139, 30.4526, 31.9529, 33.5148, 35.1377] +24-11-19 20:20:51 | D | best error = [ 0.9676, 0.9676, 0.9676, 0.9676, 0.9676] +24-11-19 20:20:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:51 | D | sum error = [ 36.8225, 38.5732, 40.3786, 42.2524, 44.1974] +24-11-19 20:20:51 | D | best error = [ 0.9676, 0.9676, 0.9676, 0.9676, 0.9676] +24-11-19 20:20:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:51 | D | sum error = [ 46.2037, 48.2846, 50.4309, 52.6448, 54.9218] +24-11-19 20:20:51 | D | best error = [ 0.9676, 0.9676, 0.9676, 0.9676, 0.9676] +24-11-19 20:20:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:51 | D | sum error = [ 57.2726, 59.6946, 62.1821, 64.7451, 67.3935] +24-11-19 20:20:51 | D | best error = [ 0.9676, 0.9676, 0.9676, 0.9676, 0.9676] +24-11-19 20:20:51 | D | + error = [0.9676] +24-11-19 20:20:51 | D | - Calibrating model.layers.3.self_attn.o_proj.weight +24-11-19 20:20:51 | D | + w: sint8 +24-11-19 20:20:51 | D | + x: None +24-11-19 20:20:51 | D | + y: None +24-11-19 20:20:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:51 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:51 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:52 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:52 | D | - range ratio = [ 1.0000] +24-11-19 20:20:52 | D | sum error = [ 0.1798] +24-11-19 20:20:52 | D | best error = [ 0.1798] +24-11-19 20:20:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:52 | D | sum error = [ 0.1783, 0.1778, 0.1776, 0.1780, 0.1803] +24-11-19 20:20:52 | D | best error = [ 0.1672, 0.1616, 0.1581, 0.1557, 0.1542] +24-11-19 20:20:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:52 | D | sum error = [ 0.1819, 0.1861, 0.1906, 0.1969, 0.2034] +24-11-19 20:20:52 | D | best error = [ 0.1530, 0.1522, 0.1516, 0.1513, 0.1511] +24-11-19 20:20:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:52 | D | sum error = [ 0.2122, 0.2227, 0.2331, 0.2460, 0.2596] +24-11-19 20:20:52 | D | best error = [ 0.1509, 0.1508, 0.1507, 0.1506, 0.1506] +24-11-19 20:20:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:52 | D | sum error = [ 0.2748, 0.2923, 0.3100, 0.3300, 0.3510] +24-11-19 20:20:52 | D | best error = [ 0.1505, 0.1505, 0.1505, 0.1505, 0.1505] +24-11-19 20:20:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:52 | D | sum error = [ 0.3739, 0.3981, 0.4251, 0.4532, 0.4831] +24-11-19 20:20:52 | D | best error = [ 0.1505, 0.1505, 0.1505, 0.1505, 0.1505] +24-11-19 20:20:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:52 | D | sum error = [ 0.5150, 0.5485, 0.5842, 0.6229, 0.6642] +24-11-19 20:20:52 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:20:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:52 | D | sum error = [ 0.7066, 0.7525, 0.8001, 0.8510, 0.9046] +24-11-19 20:20:52 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:20:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:52 | D | sum error = [ 0.9613, 1.0208, 1.0847, 1.1514, 1.2215] +24-11-19 20:20:52 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:20:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:52 | D | sum error = [ 1.2949, 1.3728, 1.4554, 1.5424, 1.6333] +24-11-19 20:20:52 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:20:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:52 | D | sum error = [ 1.7296, 1.8309, 1.9370, 2.0490, 2.1672] +24-11-19 20:20:52 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:20:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:52 | D | sum error = [ 2.2899, 2.4203, 2.5567, 2.6998, 2.8497] +24-11-19 20:20:52 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:20:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:52 | D | sum error = [ 3.0070, 3.1713, 3.3441, 3.5249, 3.7141] +24-11-19 20:20:52 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:20:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:52 | D | sum error = [ 3.9117, 4.1189, 4.3356, 4.5611, 4.7967] +24-11-19 20:20:52 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:20:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:52 | D | sum error = [ 5.0422, 5.2984, 5.5654, 5.8440, 6.1337] +24-11-19 20:20:52 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:20:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:52 | D | sum error = [ 6.4360, 6.7500, 7.0766, 7.4160, 7.7681] +24-11-19 20:20:52 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:20:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:52 | D | sum error = [ 8.1326, 8.5107, 8.9022, 9.3074, 9.7264] +24-11-19 20:20:52 | D | best error = [ 0.1504, 0.1504, 0.1504, 0.1504, 0.1504] +24-11-19 20:20:52 | D | + error = [0.1504] +24-11-19 20:20:52 | D | - Calibrating model.layers.3.mlp.up_proj.weight +24-11-19 20:20:52 | D | + w: sint8 +24-11-19 20:20:52 | D | + x: None +24-11-19 20:20:52 | D | + y: None +24-11-19 20:20:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:52 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:52 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:52 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:52 | D | - range ratio = [ 1.0000] +24-11-19 20:20:52 | D | sum error = [ 3.8858] +24-11-19 20:20:52 | D | best error = [ 3.8858] +24-11-19 20:20:53 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:53 | D | sum error = [ 3.8495, 3.8297, 3.8439, 3.9054, 3.9737] +24-11-19 20:20:53 | D | best error = [ 3.5704, 3.4572, 3.4001, 3.3711, 3.3552] +24-11-19 20:20:53 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:53 | D | sum error = [ 4.0747, 4.2112, 4.3825, 4.5749, 4.8263] +24-11-19 20:20:53 | D | best error = [ 3.3480, 3.3449, 3.3439, 3.3436, 3.3436] +24-11-19 20:20:53 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:53 | D | sum error = [ 5.1139, 5.4051, 5.7598, 6.1636, 6.5767] +24-11-19 20:20:53 | D | best error = [ 3.3436, 3.3436, 3.3436, 3.3436, 3.3436] +24-11-19 20:20:53 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:53 | D | sum error = [ 7.0282, 7.5319, 8.0674, 8.6492, 9.2538] +24-11-19 20:20:53 | D | best error = [ 3.3436, 3.3436, 3.3436, 3.3436, 3.3436] +24-11-19 20:20:53 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:53 | D | sum error = [ 9.9232, 10.6269, 11.3771, 12.1682, 12.9937] +24-11-19 20:20:53 | D | best error = [ 3.3436, 3.3436, 3.3436, 3.3436, 3.3436] +24-11-19 20:20:53 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:53 | D | sum error = [ 13.8948, 14.8315, 15.8233, 16.8648, 17.9755] +24-11-19 20:20:53 | D | best error = [ 3.3436, 3.3436, 3.3436, 3.3436, 3.3436] +24-11-19 20:20:53 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:53 | D | sum error = [ 19.1255, 20.3587, 21.6465, 23.0089, 24.4221] +24-11-19 20:20:53 | D | best error = [ 3.3436, 3.3436, 3.3436, 3.3436, 3.3436] +24-11-19 20:20:53 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:53 | D | sum error = [ 25.9168, 27.5024, 29.1571, 30.8859, 32.7119] +24-11-19 20:20:53 | D | best error = [ 3.3436, 3.3436, 3.3436, 3.3436, 3.3436] +24-11-19 20:20:53 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:53 | D | sum error = [ 34.6085, 36.5925, 38.6803, 40.8626, 43.1337] +24-11-19 20:20:53 | D | best error = [ 3.3436, 3.3436, 3.3436, 3.3436, 3.3436] +24-11-19 20:20:53 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:53 | D | sum error = [ 45.5008, 47.9881, 50.5669, 53.2686, 56.0745] +24-11-19 20:20:53 | D | best error = [ 3.3436, 3.3436, 3.3436, 3.3436, 3.3436] +24-11-19 20:20:53 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:53 | D | sum error = [ 58.9896, 62.0309, 65.2005, 68.4726, 71.8893] +24-11-19 20:20:53 | D | best error = [ 3.3436, 3.3436, 3.3436, 3.3436, 3.3436] +24-11-19 20:20:53 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:53 | D | sum error = [ 75.4251, 79.0982, 82.8958, 86.8380, 90.9216] +24-11-19 20:20:53 | D | best error = [ 3.3436, 3.3436, 3.3436, 3.3436, 3.3436] +24-11-19 20:20:53 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:53 | D | sum error = [ 95.1530, 99.5305, 104.0590, 108.7457, 113.5776] +24-11-19 20:20:53 | D | best error = [ 3.3436, 3.3436, 3.3436, 3.3436, 3.3436] +24-11-19 20:20:53 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:53 | D | sum error = [ 118.5648, 123.7175, 129.0113, 134.4882, 140.1180] +24-11-19 20:20:53 | D | best error = [ 3.3436, 3.3436, 3.3436, 3.3436, 3.3436] +24-11-19 20:20:53 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:53 | D | sum error = [ 145.9285, 151.9061, 158.0578, 164.3832, 170.8901] +24-11-19 20:20:53 | D | best error = [ 3.3436, 3.3436, 3.3436, 3.3436, 3.3436] +24-11-19 20:20:53 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:53 | D | sum error = [ 177.5816, 184.4600, 191.5209, 198.7813, 206.2378] +24-11-19 20:20:53 | D | best error = [ 3.3436, 3.3436, 3.3436, 3.3436, 3.3436] +24-11-19 20:20:53 | D | + error = [3.3436] +24-11-19 20:20:54 | D | - Calibrating model.layers.3.mlp.gate_proj.weight +24-11-19 20:20:54 | D | + w: sint8 +24-11-19 20:20:54 | D | + x: None +24-11-19 20:20:54 | D | + y: None +24-11-19 20:20:54 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:54 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:54 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:54 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:54 | D | - range ratio = [ 1.0000] +24-11-19 20:20:54 | D | sum error = [ 4.7581] +24-11-19 20:20:54 | D | best error = [ 4.7581] +24-11-19 20:20:55 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:55 | D | sum error = [ 4.7183, 4.7078, 4.7267, 4.7779, 4.8630] +24-11-19 20:20:55 | D | best error = [ 4.3770, 4.2407, 4.1709, 4.1339, 4.1130] +24-11-19 20:20:55 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:55 | D | sum error = [ 4.9953, 5.1656, 5.3743, 5.6179, 5.9282] +24-11-19 20:20:55 | D | best error = [ 4.1045, 4.1004, 4.0992, 4.0988, 4.0988] +24-11-19 20:20:55 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:55 | D | sum error = [ 6.2572, 6.6472, 7.0701, 7.5707, 8.0797] +24-11-19 20:20:55 | D | best error = [ 4.0988, 4.0988, 4.0988, 4.0988, 4.0988] +24-11-19 20:20:55 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:55 | D | sum error = [ 8.6596, 9.2766, 9.9357, 10.6678, 11.4207] +24-11-19 20:20:55 | D | best error = [ 4.0988, 4.0988, 4.0988, 4.0988, 4.0988] +24-11-19 20:20:55 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:55 | D | sum error = [ 12.2458, 13.1136, 14.0546, 15.0400, 16.0881] +24-11-19 20:20:55 | D | best error = [ 4.0988, 4.0988, 4.0988, 4.0988, 4.0988] +24-11-19 20:20:55 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:55 | D | sum error = [ 17.1968, 18.3752, 19.6288, 20.9566, 22.3441] +24-11-19 20:20:55 | D | best error = [ 4.0988, 4.0988, 4.0988, 4.0988, 4.0988] +24-11-19 20:20:55 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:55 | D | sum error = [ 23.8260, 25.3891, 27.0400, 28.7877, 30.6367] +24-11-19 20:20:55 | D | best error = [ 4.0988, 4.0988, 4.0988, 4.0988, 4.0988] +24-11-19 20:20:55 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:55 | D | sum error = [ 32.5806, 34.6026, 36.7705, 39.0537, 41.4397] +24-11-19 20:20:55 | D | best error = [ 4.0988, 4.0988, 4.0988, 4.0988, 4.0988] +24-11-19 20:20:55 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:55 | D | sum error = [ 43.9655, 46.6409, 49.4270, 52.3521, 55.4588] +24-11-19 20:20:55 | D | best error = [ 4.0988, 4.0988, 4.0988, 4.0988, 4.0988] +24-11-19 20:20:55 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:55 | D | sum error = [ 58.7166, 62.1327, 65.7024, 69.4852, 73.4447] +24-11-19 20:20:55 | D | best error = [ 4.0988, 4.0988, 4.0988, 4.0988, 4.0988] +24-11-19 20:20:55 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:55 | D | sum error = [ 77.5845, 81.9387, 86.5066, 91.2880, 96.2981] +24-11-19 20:20:55 | D | best error = [ 4.0988, 4.0988, 4.0988, 4.0988, 4.0988] +24-11-19 20:20:55 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:55 | D | sum error = [ 101.5217, 107.0070, 112.7247, 118.7094, 124.9526] +24-11-19 20:20:55 | D | best error = [ 4.0988, 4.0988, 4.0988, 4.0988, 4.0988] +24-11-19 20:20:55 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:55 | D | sum error = [ 131.4727, 138.2534, 145.3380, 152.7058, 160.3849] +24-11-19 20:20:55 | D | best error = [ 4.0988, 4.0988, 4.0988, 4.0988, 4.0988] +24-11-19 20:20:55 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:55 | D | sum error = [ 168.3548, 176.6426, 185.2612, 194.2071, 203.4971] +24-11-19 20:20:55 | D | best error = [ 4.0988, 4.0988, 4.0988, 4.0988, 4.0988] +24-11-19 20:20:55 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:55 | D | sum error = [ 213.1279, 223.1160, 233.4600, 244.1777, 255.2412] +24-11-19 20:20:55 | D | best error = [ 4.0988, 4.0988, 4.0988, 4.0988, 4.0988] +24-11-19 20:20:55 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:55 | D | sum error = [ 266.6820, 278.4855, 290.6487, 303.1770, 316.0792] +24-11-19 20:20:55 | D | best error = [ 4.0988, 4.0988, 4.0988, 4.0988, 4.0988] +24-11-19 20:20:55 | D | + error = [4.0988] +24-11-19 20:20:55 | D | - Calibrating model.layers.3.mlp.down_proj.weight +24-11-19 20:20:55 | D | + w: sint8 +24-11-19 20:20:55 | D | + x: None +24-11-19 20:20:55 | D | + y: None +24-11-19 20:20:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:20:55 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:20:55 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:20:55 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:20:55 | D | - range ratio = [ 1.0000] +24-11-19 20:20:55 | D | sum error = [ 0.2974] +24-11-19 20:20:55 | D | best error = [ 0.2974] +24-11-19 20:20:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:20:57 | D | sum error = [ 0.2938, 0.2916, 0.2897, 0.2884, 0.2877] +24-11-19 20:20:57 | D | best error = [ 0.2868, 0.2813, 0.2776, 0.2749, 0.2726] +24-11-19 20:20:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:20:57 | D | sum error = [ 0.2869, 0.2877, 0.2891, 0.2921, 0.2957] +24-11-19 20:20:57 | D | best error = [ 0.2705, 0.2689, 0.2676, 0.2667, 0.2660] +24-11-19 20:20:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:20:57 | D | sum error = [ 0.3008, 0.3074, 0.3158, 0.3259, 0.3375] +24-11-19 20:20:57 | D | best error = [ 0.2655, 0.2652, 0.2649, 0.2648, 0.2647] +24-11-19 20:20:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:20:57 | D | sum error = [ 0.3516, 0.3679, 0.3867, 0.4074, 0.4306] +24-11-19 20:20:57 | D | best error = [ 0.2646, 0.2646, 0.2645, 0.2645, 0.2645] +24-11-19 20:20:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:20:57 | D | sum error = [ 0.4566, 0.4854, 0.5165, 0.5507, 0.5888] +24-11-19 20:20:57 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 20:20:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:20:57 | D | sum error = [ 0.6297, 0.6735, 0.7208, 0.7714, 0.8260] +24-11-19 20:20:57 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 20:20:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:20:57 | D | sum error = [ 0.8843, 0.9475, 1.0139, 1.0858, 1.1614] +24-11-19 20:20:57 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 20:20:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:20:57 | D | sum error = [ 1.2423, 1.3283, 1.4192, 1.5161, 1.6185] +24-11-19 20:20:57 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 20:20:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:20:57 | D | sum error = [ 1.7274, 1.8430, 1.9650, 2.0948, 2.2321] +24-11-19 20:20:57 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 20:20:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:20:57 | D | sum error = [ 2.3768, 2.5298, 2.6910, 2.8612, 3.0405] +24-11-19 20:20:57 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 20:20:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:20:57 | D | sum error = [ 3.2293, 3.4286, 3.6385, 3.8596, 4.0910] +24-11-19 20:20:57 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 20:20:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:20:57 | D | sum error = [ 4.3351, 4.5907, 4.8594, 5.1416, 5.4365] +24-11-19 20:20:57 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 20:20:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:20:57 | D | sum error = [ 5.7458, 6.0699, 6.4088, 6.7633, 7.1341] +24-11-19 20:20:57 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 20:20:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:20:57 | D | sum error = [ 7.5211, 7.9259, 8.3473, 8.7877, 9.2451] +24-11-19 20:20:57 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 20:20:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:20:57 | D | sum error = [ 9.7218, 10.2177, 10.7336, 11.2697, 11.8265] +24-11-19 20:20:57 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 20:20:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:20:57 | D | sum error = [ 12.4039, 13.0026, 13.6227, 14.2643, 14.9285] +24-11-19 20:20:57 | D | best error = [ 0.2645, 0.2645, 0.2645, 0.2645, 0.2645] +24-11-19 20:20:57 | D | + error = [0.2645] +24-11-19 20:20:57 | D | - Quantizing model.layers.3.self_attn.q_proj.weight +24-11-19 20:20:58 | D | - Quantizing model.layers.3.self_attn.k_proj.weight +24-11-19 20:20:59 | D | - Quantizing model.layers.3.self_attn.v_proj.weight +24-11-19 20:21:00 | D | - Quantizing model.layers.3.self_attn.o_proj.weight +24-11-19 20:21:01 | D | - Quantizing model.layers.3.mlp.up_proj.weight +24-11-19 20:21:02 | D | - Quantizing model.layers.3.mlp.gate_proj.weight +24-11-19 20:21:04 | D | - Quantizing model.layers.3.mlp.down_proj.weight +24-11-19 20:21:17 | D | - Quantizing layer model.layers.4 +24-11-19 20:21:17 | D | - Calibrating model.layers.4.self_attn.q_proj.weight +24-11-19 20:21:17 | D | + w: sint8 +24-11-19 20:21:17 | D | + x: None +24-11-19 20:21:17 | D | + y: None +24-11-19 20:21:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:21:17 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:21:17 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:21:18 | D | + finished calculating the original outputs, ram usage: 13.2 +24-11-19 20:21:18 | D | - range ratio = [ 1.0000] +24-11-19 20:21:18 | D | sum error = [ 1.4107] +24-11-19 20:21:18 | D | best error = [ 1.4107] +24-11-19 20:21:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:31 | D | sum error = [ 1.4233, 1.4308, 1.4256, 1.4588, 1.4941] +24-11-19 20:21:31 | D | best error = [ 1.4107, 1.4107, 1.4107, 1.4107, 1.4107] +24-11-19 20:21:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:31 | D | sum error = [ 1.4984, 1.6047, 1.6998, 1.7732, 1.8907] +24-11-19 20:21:31 | D | best error = [ 1.4107, 1.4107, 1.4107, 1.4107, 1.4107] +24-11-19 20:21:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:31 | D | sum error = [ 1.9799, 2.2122, 2.3991, 2.6207, 2.9160] +24-11-19 20:21:31 | D | best error = [ 1.4107, 1.4107, 1.4107, 1.4107, 1.4107] +24-11-19 20:21:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:31 | D | sum error = [ 3.2369, 3.4542, 3.9834, 4.3571, 4.8529] +24-11-19 20:21:31 | D | best error = [ 1.4107, 1.4107, 1.4107, 1.4107, 1.4107] +24-11-19 20:21:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:31 | D | sum error = [ 5.4186, 6.0797, 6.9086, 7.5968, 8.3890] +24-11-19 20:21:31 | D | best error = [ 1.4107, 1.4107, 1.4107, 1.4107, 1.4107] +24-11-19 20:21:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:31 | D | sum error = [ 9.3295, 10.4763, 11.7665, 13.1504, 14.6239] +24-11-19 20:21:31 | D | best error = [ 1.4107, 1.4107, 1.4107, 1.4107, 1.4107] +24-11-19 20:21:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:31 | D | sum error = [ 16.2419, 17.8926, 19.8857, 22.0205, 24.1262] +24-11-19 20:21:31 | D | best error = [ 1.4107, 1.4107, 1.4107, 1.4107, 1.4107] +24-11-19 20:21:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:31 | D | sum error = [ 26.6033, 29.2574, 31.9112, 34.8680, 38.0477] +24-11-19 20:21:31 | D | best error = [ 1.4107, 1.4107, 1.4107, 1.4107, 1.4107] +24-11-19 20:21:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:31 | D | sum error = [ 41.2973, 44.9270, 48.6754, 52.9054, 57.1948] +24-11-19 20:21:31 | D | best error = [ 1.4107, 1.4107, 1.4107, 1.4107, 1.4107] +24-11-19 20:21:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:31 | D | sum error = [ 62.1242, 67.2936, 72.8275, 78.6077, 85.1247] +24-11-19 20:21:31 | D | best error = [ 1.4107, 1.4107, 1.4107, 1.4107, 1.4107] +24-11-19 20:21:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:31 | D | sum error = [ 91.5871, 98.5695, 105.9045, 113.8092, 121.9646] +24-11-19 20:21:31 | D | best error = [ 1.4107, 1.4107, 1.4107, 1.4107, 1.4107] +24-11-19 20:21:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:31 | D | sum error = [ 131.0244, 140.3103, 150.3979, 160.8660, 172.2739] +24-11-19 20:21:31 | D | best error = [ 1.4107, 1.4107, 1.4107, 1.4107, 1.4107] +24-11-19 20:21:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:31 | D | sum error = [ 184.1058, 196.7807, 209.9316, 223.9462, 238.9124] +24-11-19 20:21:31 | D | best error = [ 1.4107, 1.4107, 1.4107, 1.4107, 1.4107] +24-11-19 20:21:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:31 | D | sum error = [ 254.1828, 270.2418, 287.2658, 304.7084, 323.0091] +24-11-19 20:21:31 | D | best error = [ 1.4107, 1.4107, 1.4107, 1.4107, 1.4107] +24-11-19 20:21:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:31 | D | sum error = [ 341.6937, 361.3190, 381.4115, 401.9750, 423.3325] +24-11-19 20:21:31 | D | best error = [ 1.4107, 1.4107, 1.4107, 1.4107, 1.4107] +24-11-19 20:21:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:31 | D | sum error = [ 445.0810, 467.5434, 490.2628, 513.4414, 536.6551] +24-11-19 20:21:31 | D | best error = [ 1.4107, 1.4107, 1.4107, 1.4107, 1.4107] +24-11-19 20:21:31 | D | + error = [1.4107] +24-11-19 20:21:31 | D | - Calibrating model.layers.4.self_attn.k_proj.weight +24-11-19 20:21:31 | D | + w: sint8 +24-11-19 20:21:31 | D | + x: None +24-11-19 20:21:31 | D | + y: None +24-11-19 20:21:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:21:31 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:31 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:31 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:31 | D | - range ratio = [ 1.0000] +24-11-19 20:21:31 | D | sum error = [ 1.4874] +24-11-19 20:21:31 | D | best error = [ 1.4874] +24-11-19 20:21:44 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:44 | D | sum error = [ 1.5110, 1.5209, 1.6302, 1.4986, 1.4659] +24-11-19 20:21:44 | D | best error = [ 1.4874, 1.4874, 1.4874, 1.4874, 1.4659] +24-11-19 20:21:44 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:44 | D | sum error = [ 1.5511, 1.7715, 1.8428, 1.7223, 2.0384] +24-11-19 20:21:44 | D | best error = [ 1.4659, 1.4659, 1.4659, 1.4659, 1.4659] +24-11-19 20:21:44 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:44 | D | sum error = [ 2.1766, 2.1175, 3.1194, 2.7839, 3.1403] +24-11-19 20:21:44 | D | best error = [ 1.4659, 1.4659, 1.4659, 1.4659, 1.4659] +24-11-19 20:21:44 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:44 | D | sum error = [ 3.7863, 4.0348, 4.3836, 4.9139, 5.6440] +24-11-19 20:21:44 | D | best error = [ 1.4659, 1.4659, 1.4659, 1.4659, 1.4659] +24-11-19 20:21:44 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:44 | D | sum error = [ 5.9208, 6.8417, 7.5154, 8.5545, 8.9746] +24-11-19 20:21:44 | D | best error = [ 1.4659, 1.4659, 1.4659, 1.4659, 1.4659] +24-11-19 20:21:44 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:44 | D | sum error = [ 9.9543, 10.2645, 11.7888, 13.1555, 14.1623] +24-11-19 20:21:44 | D | best error = [ 1.4659, 1.4659, 1.4659, 1.4659, 1.4659] +24-11-19 20:21:44 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:44 | D | sum error = [ 15.9860, 17.3351, 19.6201, 21.6842, 23.5036] +24-11-19 20:21:44 | D | best error = [ 1.4659, 1.4659, 1.4659, 1.4659, 1.4659] +24-11-19 20:21:44 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:44 | D | sum error = [ 25.5206, 27.7963, 30.2951, 33.2575, 35.8290] +24-11-19 20:21:44 | D | best error = [ 1.4659, 1.4659, 1.4659, 1.4659, 1.4659] +24-11-19 20:21:44 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:44 | D | sum error = [ 39.4070, 42.4075, 45.8859, 49.7674, 54.1526] +24-11-19 20:21:44 | D | best error = [ 1.4659, 1.4659, 1.4659, 1.4659, 1.4659] +24-11-19 20:21:44 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:44 | D | sum error = [ 58.5839, 63.2410, 67.9935, 73.7561, 79.7111] +24-11-19 20:21:44 | D | best error = [ 1.4659, 1.4659, 1.4659, 1.4659, 1.4659] +24-11-19 20:21:44 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:44 | D | sum error = [ 86.2416, 92.8840, 99.9771, 107.3720, 115.2863] +24-11-19 20:21:44 | D | best error = [ 1.4659, 1.4659, 1.4659, 1.4659, 1.4659] +24-11-19 20:21:44 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:44 | D | sum error = [ 124.0894, 133.9263, 143.6124, 154.7197, 166.2351] +24-11-19 20:21:44 | D | best error = [ 1.4659, 1.4659, 1.4659, 1.4659, 1.4659] +24-11-19 20:21:44 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:44 | D | sum error = [ 178.6267, 190.9946, 204.1968, 218.2873, 232.9437] +24-11-19 20:21:44 | D | best error = [ 1.4659, 1.4659, 1.4659, 1.4659, 1.4659] +24-11-19 20:21:44 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:44 | D | sum error = [ 248.5340, 264.6879, 281.9860, 299.8560, 318.4516] +24-11-19 20:21:44 | D | best error = [ 1.4659, 1.4659, 1.4659, 1.4659, 1.4659] +24-11-19 20:21:44 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:44 | D | sum error = [ 337.4781, 357.5271, 378.2088, 399.8866, 422.4793] +24-11-19 20:21:44 | D | best error = [ 1.4659, 1.4659, 1.4659, 1.4659, 1.4659] +24-11-19 20:21:44 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:44 | D | sum error = [ 445.6069, 469.1242, 492.9320, 516.7447, 540.9289] +24-11-19 20:21:44 | D | best error = [ 1.4659, 1.4659, 1.4659, 1.4659, 1.4659] +24-11-19 20:21:44 | D | + error = [1.4659] +24-11-19 20:21:44 | D | - Calibrating model.layers.4.self_attn.v_proj.weight +24-11-19 20:21:44 | D | + w: sint8 +24-11-19 20:21:44 | D | + x: None +24-11-19 20:21:44 | D | + y: None +24-11-19 20:21:44 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:44 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:44 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:44 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:44 | D | - range ratio = [ 1.0000] +24-11-19 20:21:44 | D | sum error = [ 1.0558] +24-11-19 20:21:44 | D | best error = [ 1.0558] +24-11-19 20:21:44 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:44 | D | sum error = [ 1.0356, 1.0336, 1.0433, 1.0470, 1.0659] +24-11-19 20:21:44 | D | best error = [ 0.9714, 0.9430, 0.9295, 0.9223, 0.9183] +24-11-19 20:21:44 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:44 | D | sum error = [ 1.0973, 1.1392, 1.1874, 1.2497, 1.3197] +24-11-19 20:21:44 | D | best error = [ 0.9166, 0.9159, 0.9157, 0.9157, 0.9157] +24-11-19 20:21:44 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:44 | D | sum error = [ 1.3910, 1.4979, 1.5854, 1.7004, 1.8229] +24-11-19 20:21:44 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:21:44 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:44 | D | sum error = [ 1.9659, 2.0958, 2.2570, 2.4120, 2.5986] +24-11-19 20:21:44 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:21:44 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:44 | D | sum error = [ 2.7800, 2.9869, 3.1973, 3.4213, 3.6610] +24-11-19 20:21:44 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:21:44 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:44 | D | sum error = [ 3.9063, 4.1849, 4.4681, 4.7678, 5.0881] +24-11-19 20:21:44 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:21:44 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:44 | D | sum error = [ 5.4304, 5.7681, 6.1445, 6.5421, 6.9583] +24-11-19 20:21:44 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:21:44 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:44 | D | sum error = [ 7.3821, 7.8468, 8.3164, 8.8234, 9.3476] +24-11-19 20:21:44 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:21:44 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:44 | D | sum error = [ 9.9034, 10.4907, 11.1055, 11.7554, 12.4312] +24-11-19 20:21:44 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:21:44 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:44 | D | sum error = [ 13.1424, 13.8891, 14.6720, 15.5030, 16.3635] +24-11-19 20:21:44 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:21:44 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:44 | D | sum error = [ 17.2650, 18.2129, 19.1940, 20.2227, 21.3005] +24-11-19 20:21:44 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:21:44 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:44 | D | sum error = [ 22.4254, 23.6093, 24.8413, 26.1333, 27.4702] +24-11-19 20:21:44 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:21:44 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:44 | D | sum error = [ 28.8627, 30.3236, 31.8370, 33.4092, 35.0453] +24-11-19 20:21:44 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:21:44 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:44 | D | sum error = [ 36.7506, 38.5106, 40.3455, 42.2486, 44.2112] +24-11-19 20:21:44 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:21:44 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:44 | D | sum error = [ 46.2455, 48.3502, 50.5299, 52.7810, 55.1033] +24-11-19 20:21:44 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:21:44 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:44 | D | sum error = [ 57.4952, 59.9632, 62.5065, 65.1160, 67.8062] +24-11-19 20:21:44 | D | best error = [ 0.9157, 0.9157, 0.9157, 0.9157, 0.9157] +24-11-19 20:21:44 | D | + error = [0.9157] +24-11-19 20:21:44 | D | - Calibrating model.layers.4.self_attn.o_proj.weight +24-11-19 20:21:44 | D | + w: sint8 +24-11-19 20:21:44 | D | + x: None +24-11-19 20:21:44 | D | + y: None +24-11-19 20:21:44 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:44 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:44 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:45 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:45 | D | - range ratio = [ 1.0000] +24-11-19 20:21:45 | D | sum error = [ 0.2424] +24-11-19 20:21:45 | D | best error = [ 0.2424] +24-11-19 20:21:45 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:45 | D | sum error = [ 0.2397, 0.2394, 0.2387, 0.2408, 0.2439] +24-11-19 20:21:45 | D | best error = [ 0.2238, 0.2157, 0.2109, 0.2080, 0.2060] +24-11-19 20:21:45 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:45 | D | sum error = [ 0.2474, 0.2528, 0.2607, 0.2704, 0.2811] +24-11-19 20:21:45 | D | best error = [ 0.2045, 0.2035, 0.2029, 0.2025, 0.2022] +24-11-19 20:21:45 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:45 | D | sum error = [ 0.2929, 0.3088, 0.3251, 0.3436, 0.3637] +24-11-19 20:21:45 | D | best error = [ 0.2020, 0.2018, 0.2017, 0.2017, 0.2016] +24-11-19 20:21:45 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:45 | D | sum error = [ 0.3861, 0.4096, 0.4356, 0.4634, 0.4936] +24-11-19 20:21:45 | D | best error = [ 0.2016, 0.2016, 0.2015, 0.2015, 0.2015] +24-11-19 20:21:45 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:45 | D | sum error = [ 0.5252, 0.5592, 0.5951, 0.6347, 0.6747] +24-11-19 20:21:45 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:21:45 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:45 | D | sum error = [ 0.7187, 0.7639, 0.8129, 0.8634, 0.9179] +24-11-19 20:21:45 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:21:45 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:45 | D | sum error = [ 0.9744, 1.0344, 1.0979, 1.1650, 1.2353] +24-11-19 20:21:45 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:21:45 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:45 | D | sum error = [ 1.3105, 1.3882, 1.4718, 1.5583, 1.6490] +24-11-19 20:21:45 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:21:45 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:45 | D | sum error = [ 1.7450, 1.8458, 1.9511, 2.0618, 2.1790] +24-11-19 20:21:45 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:21:45 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:45 | D | sum error = [ 2.3018, 2.4298, 2.5638, 2.7042, 2.8523] +24-11-19 20:21:45 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:21:45 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:45 | D | sum error = [ 3.0068, 3.1691, 3.3395, 3.5172, 3.7033] +24-11-19 20:21:45 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:21:45 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:45 | D | sum error = [ 3.8978, 4.0998, 4.3120, 4.5341, 4.7660] +24-11-19 20:21:45 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:21:45 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:45 | D | sum error = [ 5.0075, 5.2594, 5.5219, 5.7951, 6.0801] +24-11-19 20:21:45 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:21:45 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:45 | D | sum error = [ 6.3768, 6.6851, 7.0062, 7.3414, 7.6885] +24-11-19 20:21:45 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:21:45 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:45 | D | sum error = [ 8.0495, 8.4243, 8.8139, 9.2182, 9.6365] +24-11-19 20:21:45 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:21:45 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:45 | D | sum error = [ 10.0698, 10.5186, 10.9847, 11.4662, 11.9640] +24-11-19 20:21:45 | D | best error = [ 0.2015, 0.2015, 0.2015, 0.2015, 0.2015] +24-11-19 20:21:45 | D | + error = [0.2015] +24-11-19 20:21:45 | D | - Calibrating model.layers.4.mlp.up_proj.weight +24-11-19 20:21:45 | D | + w: sint8 +24-11-19 20:21:45 | D | + x: None +24-11-19 20:21:45 | D | + y: None +24-11-19 20:21:45 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:45 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:45 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:45 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:46 | D | - range ratio = [ 1.0000] +24-11-19 20:21:46 | D | sum error = [ 4.1357] +24-11-19 20:21:46 | D | best error = [ 4.1357] +24-11-19 20:21:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:47 | D | sum error = [ 4.1021, 4.0975, 4.1084, 4.1657, 4.2358] +24-11-19 20:21:47 | D | best error = [ 3.8270, 3.7159, 3.6586, 3.6278, 3.6106] +24-11-19 20:21:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:47 | D | sum error = [ 4.3392, 4.4968, 4.6754, 4.9023, 5.1582] +24-11-19 20:21:47 | D | best error = [ 3.6025, 3.5994, 3.5982, 3.5979, 3.5979] +24-11-19 20:21:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:47 | D | sum error = [ 5.4483, 5.7921, 6.1834, 6.5923, 7.0501] +24-11-19 20:21:47 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:21:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:47 | D | sum error = [ 7.5437, 8.0813, 8.6601, 9.2839, 9.9546] +24-11-19 20:21:47 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:21:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:47 | D | sum error = [ 10.6534, 11.4022, 12.2030, 13.0591, 13.9611] +24-11-19 20:21:47 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:21:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:47 | D | sum error = [ 14.9062, 15.9094, 16.9848, 18.1103, 19.3025] +24-11-19 20:21:47 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:21:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:47 | D | sum error = [ 20.5503, 21.8651, 23.2473, 24.7098, 26.2476] +24-11-19 20:21:47 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:21:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:47 | D | sum error = [ 27.8628, 29.5584, 31.3393, 33.2040, 35.1703] +24-11-19 20:21:47 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:21:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:47 | D | sum error = [ 37.2257, 39.3768, 41.6457, 44.0021, 46.4749] +24-11-19 20:21:47 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:21:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:47 | D | sum error = [ 49.0542, 51.7583, 54.5819, 57.5210, 60.6015] +24-11-19 20:21:47 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:21:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:47 | D | sum error = [ 63.8101, 67.1502, 70.6424, 74.2485, 78.0202] +24-11-19 20:21:47 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:21:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:47 | D | sum error = [ 81.9273, 85.9961, 90.2174, 94.5900, 99.1323] +24-11-19 20:21:47 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:21:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:47 | D | sum error = [ 103.8335, 108.7008, 113.7397, 118.9545, 124.3430] +24-11-19 20:21:47 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:21:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:47 | D | sum error = [ 129.9153, 135.6813, 141.6156, 147.7633, 154.0971] +24-11-19 20:21:47 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:21:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:47 | D | sum error = [ 160.6362, 167.3646, 174.3035, 181.4467, 188.7954] +24-11-19 20:21:47 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:21:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:47 | D | sum error = [ 196.3649, 204.1524, 212.1550, 220.3826, 228.8300] +24-11-19 20:21:47 | D | best error = [ 3.5978, 3.5978, 3.5978, 3.5978, 3.5978] +24-11-19 20:21:47 | D | + error = [3.5978] +24-11-19 20:21:47 | D | - Calibrating model.layers.4.mlp.gate_proj.weight +24-11-19 20:21:47 | D | + w: sint8 +24-11-19 20:21:47 | D | + x: None +24-11-19 20:21:47 | D | + y: None +24-11-19 20:21:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:47 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:47 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:47 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:47 | D | - range ratio = [ 1.0000] +24-11-19 20:21:47 | D | sum error = [ 5.4959] +24-11-19 20:21:47 | D | best error = [ 5.4959] +24-11-19 20:21:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:48 | D | sum error = [ 5.4531, 5.4446, 5.4725, 5.5372, 5.6337] +24-11-19 20:21:48 | D | best error = [ 5.0892, 4.9443, 4.8681, 4.8260, 4.8046] +24-11-19 20:21:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:48 | D | sum error = [ 5.7896, 5.9668, 6.2185, 6.5256, 6.8788] +24-11-19 20:21:48 | D | best error = [ 4.7951, 4.7910, 4.7898, 4.7894, 4.7894] +24-11-19 20:21:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:48 | D | sum error = [ 7.2652, 7.7116, 8.2113, 8.7682, 9.3671] +24-11-19 20:21:48 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:21:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:48 | D | sum error = [ 10.0432, 10.7754, 11.5433, 12.3934, 13.2801] +24-11-19 20:21:48 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:21:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:48 | D | sum error = [ 14.2491, 15.2755, 16.3797, 17.5404, 18.7775] +24-11-19 20:21:48 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:21:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:48 | D | sum error = [ 20.1102, 21.5073, 22.9976, 24.5688, 26.2360] +24-11-19 20:21:48 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:21:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:48 | D | sum error = [ 27.9979, 29.8765, 31.8540, 33.9417, 36.1604] +24-11-19 20:21:48 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:21:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:48 | D | sum error = [ 38.4969, 40.9795, 43.5950, 46.3710, 49.2883] +24-11-19 20:21:48 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:21:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:48 | D | sum error = [ 52.3766, 55.6443, 59.0768, 62.7125, 66.5532] +24-11-19 20:21:48 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:21:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:48 | D | sum error = [ 70.5941, 74.8492, 79.3288, 84.0477, 89.0119] +24-11-19 20:21:48 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:21:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:48 | D | sum error = [ 94.2468, 99.7546, 105.5374, 111.6286, 118.0181] +24-11-19 20:21:48 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:21:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:48 | D | sum error = [ 124.7382, 131.7816, 139.1680, 146.9166, 155.0212] +24-11-19 20:21:48 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:21:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:48 | D | sum error = [ 163.5172, 172.3996, 181.6816, 191.3779, 201.4910] +24-11-19 20:21:48 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:21:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:48 | D | sum error = [ 212.0397, 223.0292, 234.4888, 246.4254, 258.8226] +24-11-19 20:21:48 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:21:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:48 | D | sum error = [ 271.7168, 285.1238, 298.9958, 313.4072, 328.3232] +24-11-19 20:21:48 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:21:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:48 | D | sum error = [ 343.7499, 359.6713, 376.1125, 393.0745, 410.5552] +24-11-19 20:21:48 | D | best error = [ 4.7894, 4.7894, 4.7894, 4.7894, 4.7894] +24-11-19 20:21:48 | D | + error = [4.7894] +24-11-19 20:21:48 | D | - Calibrating model.layers.4.mlp.down_proj.weight +24-11-19 20:21:48 | D | + w: sint8 +24-11-19 20:21:48 | D | + x: None +24-11-19 20:21:48 | D | + y: None +24-11-19 20:21:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:21:48 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:21:48 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:21:49 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:21:49 | D | - range ratio = [ 1.0000] +24-11-19 20:21:49 | D | sum error = [ 0.3828] +24-11-19 20:21:49 | D | best error = [ 0.3828] +24-11-19 20:21:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:21:50 | D | sum error = [ 0.3789, 0.3753, 0.3732, 0.3715, 0.3704] +24-11-19 20:21:50 | D | best error = [ 0.3693, 0.3621, 0.3570, 0.3534, 0.3505] +24-11-19 20:21:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:21:50 | D | sum error = [ 0.3710, 0.3719, 0.3745, 0.3787, 0.3835] +24-11-19 20:21:50 | D | best error = [ 0.3483, 0.3464, 0.3450, 0.3438, 0.3431] +24-11-19 20:21:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:21:50 | D | sum error = [ 0.3914, 0.4003, 0.4116, 0.4250, 0.4411] +24-11-19 20:21:50 | D | best error = [ 0.3425, 0.3421, 0.3419, 0.3417, 0.3416] +24-11-19 20:21:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:21:50 | D | sum error = [ 0.4599, 0.4816, 0.5050, 0.5331, 0.5625] +24-11-19 20:21:50 | D | best error = [ 0.3415, 0.3414, 0.3414, 0.3414, 0.3413] +24-11-19 20:21:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:21:50 | D | sum error = [ 0.5973, 0.6337, 0.6746, 0.7197, 0.7675] +24-11-19 20:21:50 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 20:21:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:21:50 | D | sum error = [ 0.8193, 0.8765, 0.9372, 1.0021, 1.0723] +24-11-19 20:21:50 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 20:21:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:21:50 | D | sum error = [ 1.1481, 1.2279, 1.3142, 1.4060, 1.5038] +24-11-19 20:21:50 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 20:21:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:21:50 | D | sum error = [ 1.6080, 1.7187, 1.8374, 1.9617, 2.0954] +24-11-19 20:21:50 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 20:21:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:21:50 | D | sum error = [ 2.2365, 2.3857, 2.5442, 2.7117, 2.8887] +24-11-19 20:21:50 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 20:21:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:21:50 | D | sum error = [ 3.0759, 3.2734, 3.4809, 3.7004, 3.9318] +24-11-19 20:21:50 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 20:21:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:21:50 | D | sum error = [ 4.1762, 4.4328, 4.7023, 4.9859, 5.2834] +24-11-19 20:21:50 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 20:21:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:21:50 | D | sum error = [ 5.5953, 5.9231, 6.2669, 6.6266, 7.0038] +24-11-19 20:21:50 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 20:21:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:21:50 | D | sum error = [ 7.3983, 7.8113, 8.2430, 8.6941, 9.1655] +24-11-19 20:21:50 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 20:21:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:21:50 | D | sum error = [ 9.6567, 10.1692, 10.7033, 11.2604, 11.8380] +24-11-19 20:21:50 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 20:21:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:21:50 | D | sum error = [ 12.4398, 13.0649, 13.7145, 14.3893, 15.0889] +24-11-19 20:21:50 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 20:21:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:21:50 | D | sum error = [ 15.8140, 16.5642, 17.3415, 18.1448, 18.9756] +24-11-19 20:21:50 | D | best error = [ 0.3413, 0.3413, 0.3413, 0.3413, 0.3413] +24-11-19 20:21:50 | D | + error = [0.3413] +24-11-19 20:21:50 | D | - Quantizing model.layers.4.self_attn.q_proj.weight +24-11-19 20:21:51 | D | - Quantizing model.layers.4.self_attn.k_proj.weight +24-11-19 20:21:52 | D | - Quantizing model.layers.4.self_attn.v_proj.weight +24-11-19 20:21:53 | D | - Quantizing model.layers.4.self_attn.o_proj.weight +24-11-19 20:21:54 | D | - Quantizing model.layers.4.mlp.up_proj.weight +24-11-19 20:21:56 | D | - Quantizing model.layers.4.mlp.gate_proj.weight +24-11-19 20:22:01 | D | - Quantizing model.layers.4.mlp.down_proj.weight +24-11-19 20:22:16 | D | - Quantizing layer model.layers.5 +24-11-19 20:22:16 | D | - Calibrating model.layers.5.self_attn.q_proj.weight +24-11-19 20:22:16 | D | + w: sint8 +24-11-19 20:22:16 | D | + x: None +24-11-19 20:22:16 | D | + y: None +24-11-19 20:22:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:22:16 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:22:16 | D | + finished reseting calibrator, ram usage: 13.1 +24-11-19 20:22:16 | D | + finished calculating the original outputs, ram usage: 13.1 +24-11-19 20:22:16 | D | - range ratio = [ 1.0000] +24-11-19 20:22:16 | D | sum error = [ 2.0732] +24-11-19 20:22:16 | D | best error = [ 2.0732] +24-11-19 20:22:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:29 | D | sum error = [ 2.1492, 2.0525, 2.0758, 2.0364, 2.1182] +24-11-19 20:22:29 | D | best error = [ 2.0732, 2.0525, 2.0525, 2.0364, 2.0364] +24-11-19 20:22:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:29 | D | sum error = [ 2.1210, 2.2241, 2.3254, 2.4855, 2.5048] +24-11-19 20:22:29 | D | best error = [ 2.0364, 2.0364, 2.0364, 2.0364, 2.0364] +24-11-19 20:22:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:29 | D | sum error = [ 2.7160, 2.8997, 3.1108, 3.4714, 3.6825] +24-11-19 20:22:29 | D | best error = [ 2.0364, 2.0364, 2.0364, 2.0364, 2.0364] +24-11-19 20:22:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:29 | D | sum error = [ 3.8809, 4.1840, 4.6916, 5.0291, 5.4870] +24-11-19 20:22:29 | D | best error = [ 2.0364, 2.0364, 2.0364, 2.0364, 2.0364] +24-11-19 20:22:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:29 | D | sum error = [ 5.9331, 6.4048, 7.0195, 7.5757, 8.1290] +24-11-19 20:22:29 | D | best error = [ 2.0364, 2.0364, 2.0364, 2.0364, 2.0364] +24-11-19 20:22:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:29 | D | sum error = [ 8.8133, 9.6911, 10.5594, 11.5483, 12.4590] +24-11-19 20:22:29 | D | best error = [ 2.0364, 2.0364, 2.0364, 2.0364, 2.0364] +24-11-19 20:22:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:29 | D | sum error = [ 13.5689, 14.7101, 16.1414, 17.5893, 19.1459] +24-11-19 20:22:29 | D | best error = [ 2.0364, 2.0364, 2.0364, 2.0364, 2.0364] +24-11-19 20:22:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:29 | D | sum error = [ 20.8776, 22.6905, 24.7943, 26.9422, 29.2973] +24-11-19 20:22:29 | D | best error = [ 2.0364, 2.0364, 2.0364, 2.0364, 2.0364] +24-11-19 20:22:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:29 | D | sum error = [ 31.9104, 34.7173, 37.4853, 40.7205, 44.0598] +24-11-19 20:22:29 | D | best error = [ 2.0364, 2.0364, 2.0364, 2.0364, 2.0364] +24-11-19 20:22:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:29 | D | sum error = [ 47.8364, 51.7211, 55.9821, 60.6061, 65.5390] +24-11-19 20:22:29 | D | best error = [ 2.0364, 2.0364, 2.0364, 2.0364, 2.0364] +24-11-19 20:22:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:29 | D | sum error = [ 70.8953, 76.4325, 82.4679, 88.8006, 95.6669] +24-11-19 20:22:29 | D | best error = [ 2.0364, 2.0364, 2.0364, 2.0364, 2.0364] +24-11-19 20:22:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:29 | D | sum error = [ 103.0099, 110.7963, 119.1662, 128.1922, 137.7832] +24-11-19 20:22:29 | D | best error = [ 2.0364, 2.0364, 2.0364, 2.0364, 2.0364] +24-11-19 20:22:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:29 | D | sum error = [ 147.8622, 158.8315, 170.2864, 182.4339, 195.4528] +24-11-19 20:22:29 | D | best error = [ 2.0364, 2.0364, 2.0364, 2.0364, 2.0364] +24-11-19 20:22:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:29 | D | sum error = [ 208.9046, 223.3441, 238.6253, 254.6740, 271.6749] +24-11-19 20:22:29 | D | best error = [ 2.0364, 2.0364, 2.0364, 2.0364, 2.0364] +24-11-19 20:22:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:29 | D | sum error = [ 289.5201, 307.9847, 327.3420, 347.4263, 368.0827] +24-11-19 20:22:29 | D | best error = [ 2.0364, 2.0364, 2.0364, 2.0364, 2.0364] +24-11-19 20:22:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:29 | D | sum error = [ 389.4338, 411.1846, 433.4803, 456.1030, 479.1664] +24-11-19 20:22:29 | D | best error = [ 2.0364, 2.0364, 2.0364, 2.0364, 2.0364] +24-11-19 20:22:29 | D | + error = [2.0364] +24-11-19 20:22:29 | D | - Calibrating model.layers.5.self_attn.k_proj.weight +24-11-19 20:22:29 | D | + w: sint8 +24-11-19 20:22:29 | D | + x: None +24-11-19 20:22:29 | D | + y: None +24-11-19 20:22:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:22:29 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:29 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:30 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:30 | D | - range ratio = [ 1.0000] +24-11-19 20:22:30 | D | sum error = [ 2.1862] +24-11-19 20:22:30 | D | best error = [ 2.1862] +24-11-19 20:22:42 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:42 | D | sum error = [ 2.1929, 2.1315, 2.0579, 2.2028, 2.2268] +24-11-19 20:22:42 | D | best error = [ 2.1862, 2.1315, 2.0579, 2.0579, 2.0579] +24-11-19 20:22:42 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:42 | D | sum error = [ 2.1231, 2.3076, 2.3035, 2.6097, 2.8436] +24-11-19 20:22:42 | D | best error = [ 2.0579, 2.0579, 2.0579, 2.0579, 2.0579] +24-11-19 20:22:42 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:42 | D | sum error = [ 3.0798, 3.5551, 4.0804, 4.2234, 4.5211] +24-11-19 20:22:42 | D | best error = [ 2.0579, 2.0579, 2.0579, 2.0579, 2.0579] +24-11-19 20:22:42 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:42 | D | sum error = [ 4.8597, 5.4145, 6.0454, 6.0329, 7.5221] +24-11-19 20:22:42 | D | best error = [ 2.0579, 2.0579, 2.0579, 2.0579, 2.0579] +24-11-19 20:22:42 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:42 | D | sum error = [ 7.3105, 8.2399, 9.4908, 10.2255, 10.5769] +24-11-19 20:22:42 | D | best error = [ 2.0579, 2.0579, 2.0579, 2.0579, 2.0579] +24-11-19 20:22:42 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:42 | D | sum error = [ 11.4897, 12.9139, 13.8707, 14.5911, 16.1791] +24-11-19 20:22:42 | D | best error = [ 2.0579, 2.0579, 2.0579, 2.0579, 2.0579] +24-11-19 20:22:42 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:42 | D | sum error = [ 17.3755, 18.7697, 20.6774, 22.2379, 24.6198] +24-11-19 20:22:42 | D | best error = [ 2.0579, 2.0579, 2.0579, 2.0579, 2.0579] +24-11-19 20:22:42 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:42 | D | sum error = [ 25.9780, 28.5136, 30.6606, 33.5958, 36.2184] +24-11-19 20:22:42 | D | best error = [ 2.0579, 2.0579, 2.0579, 2.0579, 2.0579] +24-11-19 20:22:42 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:42 | D | sum error = [ 38.8837, 42.3073, 45.0077, 48.6390, 52.4873] +24-11-19 20:22:42 | D | best error = [ 2.0579, 2.0579, 2.0579, 2.0579, 2.0579] +24-11-19 20:22:42 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:42 | D | sum error = [ 56.8798, 60.9991, 65.5469, 70.6561, 75.8561] +24-11-19 20:22:42 | D | best error = [ 2.0579, 2.0579, 2.0579, 2.0579, 2.0579] +24-11-19 20:22:42 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:42 | D | sum error = [ 82.0189, 88.4426, 95.2922, 102.4350, 110.1960] +24-11-19 20:22:42 | D | best error = [ 2.0579, 2.0579, 2.0579, 2.0579, 2.0579] +24-11-19 20:22:42 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:42 | D | sum error = [ 118.7387, 127.2010, 136.6767, 146.1700, 156.4298] +24-11-19 20:22:42 | D | best error = [ 2.0579, 2.0579, 2.0579, 2.0579, 2.0579] +24-11-19 20:22:42 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:42 | D | sum error = [ 167.6540, 179.0454, 191.3189, 204.0369, 217.7392] +24-11-19 20:22:42 | D | best error = [ 2.0579, 2.0579, 2.0579, 2.0579, 2.0579] +24-11-19 20:22:42 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:42 | D | sum error = [ 232.3590, 247.3796, 262.8923, 279.4438, 296.7984] +24-11-19 20:22:42 | D | best error = [ 2.0579, 2.0579, 2.0579, 2.0579, 2.0579] +24-11-19 20:22:42 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:42 | D | sum error = [ 315.0576, 333.9453, 353.7253, 373.8947, 394.6096] +24-11-19 20:22:42 | D | best error = [ 2.0579, 2.0579, 2.0579, 2.0579, 2.0579] +24-11-19 20:22:42 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:42 | D | sum error = [ 415.8235, 437.6603, 459.9032, 482.2780, 504.4248] +24-11-19 20:22:42 | D | best error = [ 2.0579, 2.0579, 2.0579, 2.0579, 2.0579] +24-11-19 20:22:42 | D | + error = [2.0579] +24-11-19 20:22:43 | D | - Calibrating model.layers.5.self_attn.v_proj.weight +24-11-19 20:22:43 | D | + w: sint8 +24-11-19 20:22:43 | D | + x: None +24-11-19 20:22:43 | D | + y: None +24-11-19 20:22:43 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:43 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:43 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:43 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:43 | D | - range ratio = [ 1.0000] +24-11-19 20:22:43 | D | sum error = [ 1.0031] +24-11-19 20:22:43 | D | best error = [ 1.0031] +24-11-19 20:22:43 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:43 | D | sum error = [ 1.0005, 0.9913, 1.0058, 1.0055, 1.0222] +24-11-19 20:22:43 | D | best error = [ 0.9389, 0.9115, 0.8993, 0.8917, 0.8878] +24-11-19 20:22:43 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:43 | D | sum error = [ 1.0523, 1.0928, 1.1407, 1.1926, 1.2559] +24-11-19 20:22:43 | D | best error = [ 0.8860, 0.8852, 0.8850, 0.8850, 0.8849] +24-11-19 20:22:43 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:43 | D | sum error = [ 1.3232, 1.4095, 1.4920, 1.5862, 1.7086] +24-11-19 20:22:43 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:22:43 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:43 | D | sum error = [ 1.8306, 1.9484, 2.0877, 2.2412, 2.4037] +24-11-19 20:22:43 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:22:43 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:43 | D | sum error = [ 2.5822, 2.7649, 2.9592, 3.1655, 3.3878] +24-11-19 20:22:43 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:22:43 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:43 | D | sum error = [ 3.6183, 3.8646, 4.1260, 4.4099, 4.6896] +24-11-19 20:22:43 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:22:43 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:43 | D | sum error = [ 5.0081, 5.3380, 5.6820, 6.0541, 6.4475] +24-11-19 20:22:43 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:22:43 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:43 | D | sum error = [ 6.8521, 7.2901, 7.7406, 8.2282, 8.7238] +24-11-19 20:22:43 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:22:43 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:43 | D | sum error = [ 9.2691, 9.8239, 10.4282, 11.0487, 11.7095] +24-11-19 20:22:43 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:22:43 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:43 | D | sum error = [ 12.4024, 13.1276, 13.8908, 14.6911, 15.5338] +24-11-19 20:22:43 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:22:43 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:43 | D | sum error = [ 16.4190, 17.3480, 18.3219, 19.3400, 20.4081] +24-11-19 20:22:43 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:22:43 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:43 | D | sum error = [ 21.5173, 22.6809, 23.8930, 25.1674, 26.4875] +24-11-19 20:22:43 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:22:43 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:43 | D | sum error = [ 27.8732, 29.3123, 30.8161, 32.3774, 34.0150] +24-11-19 20:22:43 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:22:43 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:43 | D | sum error = [ 35.7088, 37.4730, 39.3028, 41.2054, 43.1680] +24-11-19 20:22:43 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:22:43 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:43 | D | sum error = [ 45.2113, 47.3152, 49.5047, 51.7681, 54.1000] +24-11-19 20:22:43 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:22:43 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:43 | D | sum error = [ 56.5213, 59.0152, 61.5928, 64.2504, 66.9856] +24-11-19 20:22:43 | D | best error = [ 0.8849, 0.8849, 0.8849, 0.8849, 0.8849] +24-11-19 20:22:43 | D | + error = [0.8849] +24-11-19 20:22:43 | D | - Calibrating model.layers.5.self_attn.o_proj.weight +24-11-19 20:22:43 | D | + w: sint8 +24-11-19 20:22:43 | D | + x: None +24-11-19 20:22:43 | D | + y: None +24-11-19 20:22:43 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:43 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:43 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:43 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:43 | D | - range ratio = [ 1.0000] +24-11-19 20:22:43 | D | sum error = [ 0.2897] +24-11-19 20:22:43 | D | best error = [ 0.2897] +24-11-19 20:22:44 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:44 | D | sum error = [ 0.2875, 0.2869, 0.2866, 0.2898, 0.2926] +24-11-19 20:22:44 | D | best error = [ 0.2659, 0.2556, 0.2494, 0.2454, 0.2425] +24-11-19 20:22:44 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:44 | D | sum error = [ 0.2993, 0.3056, 0.3169, 0.3281, 0.3435] +24-11-19 20:22:44 | D | best error = [ 0.2406, 0.2394, 0.2385, 0.2378, 0.2375] +24-11-19 20:22:44 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:44 | D | sum error = [ 0.3585, 0.3782, 0.3980, 0.4194, 0.4462] +24-11-19 20:22:44 | D | best error = [ 0.2372, 0.2370, 0.2369, 0.2368, 0.2367] +24-11-19 20:22:44 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:44 | D | sum error = [ 0.4732, 0.5006, 0.5320, 0.5665, 0.6015] +24-11-19 20:22:44 | D | best error = [ 0.2366, 0.2366, 0.2366, 0.2365, 0.2365] +24-11-19 20:22:44 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:44 | D | sum error = [ 0.6404, 0.6804, 0.7235, 0.7706, 0.8182] +24-11-19 20:22:44 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:22:44 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:44 | D | sum error = [ 0.8685, 0.9219, 0.9800, 1.0392, 1.1032] +24-11-19 20:22:44 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:22:44 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:44 | D | sum error = [ 1.1677, 1.2365, 1.3112, 1.3865, 1.4685] +24-11-19 20:22:44 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:22:44 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:44 | D | sum error = [ 1.5533, 1.6417, 1.7355, 1.8319, 1.9358] +24-11-19 20:22:44 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:22:44 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:44 | D | sum error = [ 2.0426, 2.1547, 2.2727, 2.3964, 2.5256] +24-11-19 20:22:44 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:22:44 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:44 | D | sum error = [ 2.6606, 2.8015, 2.9488, 3.1043, 3.2670] +24-11-19 20:22:44 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:22:44 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:44 | D | sum error = [ 3.4364, 3.6133, 3.7998, 3.9937, 4.1965] +24-11-19 20:22:44 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:22:44 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:44 | D | sum error = [ 4.4074, 4.6290, 4.8581, 5.0959, 5.3440] +24-11-19 20:22:44 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:22:44 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:44 | D | sum error = [ 5.6025, 5.8712, 6.1492, 6.4386, 6.7390] +24-11-19 20:22:44 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:22:44 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:44 | D | sum error = [ 7.0518, 7.3759, 7.7110, 8.0591, 8.4185] +24-11-19 20:22:44 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:22:44 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:44 | D | sum error = [ 8.7918, 9.1780, 9.5780, 9.9935, 10.4228] +24-11-19 20:22:44 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:22:44 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:44 | D | sum error = [ 10.8667, 11.3259, 11.8006, 12.2912, 12.7980] +24-11-19 20:22:44 | D | best error = [ 0.2365, 0.2365, 0.2365, 0.2365, 0.2365] +24-11-19 20:22:44 | D | + error = [0.2365] +24-11-19 20:22:44 | D | - Calibrating model.layers.5.mlp.up_proj.weight +24-11-19 20:22:44 | D | + w: sint8 +24-11-19 20:22:44 | D | + x: None +24-11-19 20:22:44 | D | + y: None +24-11-19 20:22:44 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:44 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:44 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:44 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:44 | D | - range ratio = [ 1.0000] +24-11-19 20:22:44 | D | sum error = [ 4.4837] +24-11-19 20:22:44 | D | best error = [ 4.4837] +24-11-19 20:22:45 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:45 | D | sum error = [ 4.4296, 4.4434, 4.4538, 4.4915, 4.5817] +24-11-19 20:22:45 | D | best error = [ 4.1859, 4.0785, 4.0203, 3.9871, 3.9702] +24-11-19 20:22:45 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:45 | D | sum error = [ 4.6998, 4.8572, 5.0469, 5.2861, 5.5556] +24-11-19 20:22:45 | D | best error = [ 3.9622, 3.9587, 3.9577, 3.9574, 3.9573] +24-11-19 20:22:45 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:45 | D | sum error = [ 5.8673, 6.2452, 6.6417, 7.0830, 7.5656] +24-11-19 20:22:45 | D | best error = [ 3.9573, 3.9573, 3.9573, 3.9573, 3.9573] +24-11-19 20:22:45 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:45 | D | sum error = [ 8.1035, 8.6711, 9.2791, 9.9442, 10.6448] +24-11-19 20:22:45 | D | best error = [ 3.9573, 3.9573, 3.9573, 3.9573, 3.9573] +24-11-19 20:22:45 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:45 | D | sum error = [ 11.4113, 12.2050, 13.0635, 13.9665, 14.9323] +24-11-19 20:22:45 | D | best error = [ 3.9573, 3.9573, 3.9573, 3.9573, 3.9573] +24-11-19 20:22:45 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:45 | D | sum error = [ 15.9641, 17.0384, 18.1930, 19.4041, 20.6867] +24-11-19 20:22:45 | D | best error = [ 3.9573, 3.9573, 3.9573, 3.9573, 3.9573] +24-11-19 20:22:45 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:45 | D | sum error = [ 22.0293, 23.4578, 24.9633, 26.5502, 28.2242] +24-11-19 20:22:45 | D | best error = [ 3.9573, 3.9573, 3.9573, 3.9573, 3.9573] +24-11-19 20:22:45 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:45 | D | sum error = [ 29.9742, 31.8220, 33.7586, 35.8041, 37.9416] +24-11-19 20:22:45 | D | best error = [ 3.9573, 3.9573, 3.9573, 3.9573, 3.9573] +24-11-19 20:22:45 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:45 | D | sum error = [ 40.1805, 42.5378, 45.0026, 47.5839, 50.2883] +24-11-19 20:22:45 | D | best error = [ 3.9573, 3.9573, 3.9573, 3.9573, 3.9573] +24-11-19 20:22:45 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:45 | D | sum error = [ 53.1227, 56.0694, 59.1723, 62.4033, 65.7713] +24-11-19 20:22:45 | D | best error = [ 3.9573, 3.9573, 3.9573, 3.9573, 3.9573] +24-11-19 20:22:45 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:45 | D | sum error = [ 69.2910, 72.9592, 76.7915, 80.7706, 84.9214] +24-11-19 20:22:45 | D | best error = [ 3.9573, 3.9573, 3.9573, 3.9573, 3.9573] +24-11-19 20:22:45 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:45 | D | sum error = [ 89.2350, 93.7335, 98.4065, 103.2590, 108.3024] +24-11-19 20:22:45 | D | best error = [ 3.9573, 3.9573, 3.9573, 3.9573, 3.9573] +24-11-19 20:22:45 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:45 | D | sum error = [ 113.5282, 118.9534, 124.5637, 130.3858, 136.4150] +24-11-19 20:22:45 | D | best error = [ 3.9573, 3.9573, 3.9573, 3.9573, 3.9573] +24-11-19 20:22:45 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:45 | D | sum error = [ 142.6506, 149.0961, 155.7783, 162.6750, 169.7917] +24-11-19 20:22:45 | D | best error = [ 3.9573, 3.9573, 3.9573, 3.9573, 3.9573] +24-11-19 20:22:45 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:45 | D | sum error = [ 177.1427, 184.7288, 192.5323, 200.5878, 208.8750] +24-11-19 20:22:45 | D | best error = [ 3.9573, 3.9573, 3.9573, 3.9573, 3.9573] +24-11-19 20:22:45 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:45 | D | sum error = [ 217.4278, 226.2180, 235.2696, 244.5798, 254.1501] +24-11-19 20:22:45 | D | best error = [ 3.9573, 3.9573, 3.9573, 3.9573, 3.9573] +24-11-19 20:22:45 | D | + error = [3.9573] +24-11-19 20:22:45 | D | - Calibrating model.layers.5.mlp.gate_proj.weight +24-11-19 20:22:45 | D | + w: sint8 +24-11-19 20:22:45 | D | + x: None +24-11-19 20:22:45 | D | + y: None +24-11-19 20:22:45 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:45 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:46 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:46 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:46 | D | - range ratio = [ 1.0000] +24-11-19 20:22:46 | D | sum error = [ 5.8952] +24-11-19 20:22:46 | D | best error = [ 5.8952] +24-11-19 20:22:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:47 | D | sum error = [ 5.8587, 5.8434, 5.8619, 5.9249, 6.0496] +24-11-19 20:22:47 | D | best error = [ 5.5166, 5.3718, 5.2953, 5.2504, 5.2284] +24-11-19 20:22:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:47 | D | sum error = [ 6.2001, 6.4093, 6.6709, 6.9729, 7.3503] +24-11-19 20:22:47 | D | best error = [ 5.2188, 5.2143, 5.2133, 5.2131, 5.2130] +24-11-19 20:22:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:47 | D | sum error = [ 7.7802, 8.2690, 8.7927, 9.3940, 10.0414] +24-11-19 20:22:47 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:22:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:47 | D | sum error = [ 10.7525, 11.5323, 12.3633, 13.2524, 14.2209] +24-11-19 20:22:47 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:22:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:47 | D | sum error = [ 15.2584, 16.3516, 17.5422, 18.7956, 20.1324] +24-11-19 20:22:47 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:22:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:47 | D | sum error = [ 21.5498, 23.0593, 24.6701, 26.3764, 28.1794] +24-11-19 20:22:47 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:22:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:47 | D | sum error = [ 30.0818, 32.1206, 34.2574, 36.5255, 38.9356] +24-11-19 20:22:47 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:22:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:47 | D | sum error = [ 41.4824, 44.1631, 47.0023, 50.0170, 53.1955] +24-11-19 20:22:47 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:22:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:47 | D | sum error = [ 56.5628, 60.1215, 63.8761, 67.8483, 72.0171] +24-11-19 20:22:47 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:22:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:47 | D | sum error = [ 76.4412, 81.1109, 86.0155, 91.2038, 96.6457] +24-11-19 20:22:47 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:22:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:47 | D | sum error = [ 102.4078, 108.4401, 114.8110, 121.5281, 128.5539] +24-11-19 20:22:47 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:22:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:47 | D | sum error = [ 135.9605, 143.7145, 151.8726, 160.4014, 169.3445] +24-11-19 20:22:47 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:22:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:47 | D | sum error = [ 178.7243, 188.5373, 198.7988, 209.5438, 220.7655] +24-11-19 20:22:47 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:22:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:47 | D | sum error = [ 232.4650, 244.6639, 257.3850, 270.6628, 284.4641] +24-11-19 20:22:47 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:22:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:47 | D | sum error = [ 298.8109, 313.7124, 329.2011, 345.2362, 361.8439] +24-11-19 20:22:47 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:22:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:47 | D | sum error = [ 379.0452, 396.7982, 415.1366, 434.0554, 453.5674] +24-11-19 20:22:47 | D | best error = [ 5.2130, 5.2130, 5.2130, 5.2130, 5.2130] +24-11-19 20:22:47 | D | + error = [5.2130] +24-11-19 20:22:47 | D | - Calibrating model.layers.5.mlp.down_proj.weight +24-11-19 20:22:47 | D | + w: sint8 +24-11-19 20:22:47 | D | + x: None +24-11-19 20:22:47 | D | + y: None +24-11-19 20:22:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:22:47 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:22:47 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:22:47 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:22:47 | D | - range ratio = [ 1.0000] +24-11-19 20:22:47 | D | sum error = [ 0.4632] +24-11-19 20:22:47 | D | best error = [ 0.4632] +24-11-19 20:22:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:22:48 | D | sum error = [ 0.4583, 0.4555, 0.4528, 0.4524, 0.4521] +24-11-19 20:22:48 | D | best error = [ 0.4461, 0.4376, 0.4317, 0.4274, 0.4240] +24-11-19 20:22:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:22:48 | D | sum error = [ 0.4550, 0.4578, 0.4633, 0.4711, 0.4809] +24-11-19 20:22:48 | D | best error = [ 0.4215, 0.4196, 0.4179, 0.4168, 0.4161] +24-11-19 20:22:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:22:48 | D | sum error = [ 0.4947, 0.5096, 0.5273, 0.5487, 0.5717] +24-11-19 20:22:48 | D | best error = [ 0.4155, 0.4151, 0.4149, 0.4148, 0.4146] +24-11-19 20:22:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:22:48 | D | sum error = [ 0.6009, 0.6317, 0.6670, 0.7054, 0.7477] +24-11-19 20:22:48 | D | best error = [ 0.4146, 0.4145, 0.4145, 0.4145, 0.4145] +24-11-19 20:22:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:22:48 | D | sum error = [ 0.7936, 0.8447, 0.8999, 0.9614, 1.0254] +24-11-19 20:22:48 | D | best error = [ 0.4145, 0.4145, 0.4145, 0.4144, 0.4144] +24-11-19 20:22:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:22:48 | D | sum error = [ 1.0949, 1.1684, 1.2491, 1.3340, 1.4255] +24-11-19 20:22:48 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 20:22:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:22:48 | D | sum error = [ 1.5224, 1.6264, 1.7376, 1.8541, 1.9790] +24-11-19 20:22:48 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 20:22:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:22:48 | D | sum error = [ 2.1116, 2.2521, 2.4017, 2.5596, 2.7274] +24-11-19 20:22:48 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 20:22:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:22:48 | D | sum error = [ 2.9047, 3.0922, 3.2906, 3.5010, 3.7225] +24-11-19 20:22:48 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 20:22:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:22:48 | D | sum error = [ 3.9569, 4.2032, 4.4627, 4.7360, 5.0242] +24-11-19 20:22:48 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 20:22:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:22:48 | D | sum error = [ 5.3272, 5.6450, 5.9796, 6.3315, 6.7007] +24-11-19 20:22:48 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 20:22:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:22:48 | D | sum error = [ 7.0884, 7.4943, 7.9190, 8.3636, 8.8293] +24-11-19 20:22:48 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 20:22:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:22:48 | D | sum error = [ 9.3157, 9.8246, 10.3571, 10.9130, 11.4932] +24-11-19 20:22:48 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 20:22:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:22:48 | D | sum error = [ 12.0970, 12.7260, 13.3810, 14.0631, 14.7705] +24-11-19 20:22:48 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 20:22:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:22:48 | D | sum error = [ 15.5069, 16.2713, 17.0648, 17.8874, 18.7397] +24-11-19 20:22:48 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 20:22:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:22:48 | D | sum error = [ 19.6229, 20.5370, 21.4829, 22.4606, 23.4706] +24-11-19 20:22:48 | D | best error = [ 0.4144, 0.4144, 0.4144, 0.4144, 0.4144] +24-11-19 20:22:48 | D | + error = [0.4144] +24-11-19 20:22:49 | D | - Quantizing model.layers.5.self_attn.q_proj.weight +24-11-19 20:22:49 | D | - Quantizing model.layers.5.self_attn.k_proj.weight +24-11-19 20:22:51 | D | - Quantizing model.layers.5.self_attn.v_proj.weight +24-11-19 20:22:52 | D | - Quantizing model.layers.5.self_attn.o_proj.weight +24-11-19 20:22:54 | D | - Quantizing model.layers.5.mlp.up_proj.weight +24-11-19 20:22:55 | D | - Quantizing model.layers.5.mlp.gate_proj.weight +24-11-19 20:22:57 | D | - Quantizing model.layers.5.mlp.down_proj.weight +24-11-19 20:23:10 | D | - Quantizing layer model.layers.6 +24-11-19 20:23:10 | D | - Calibrating model.layers.6.self_attn.q_proj.weight +24-11-19 20:23:10 | D | + w: sint8 +24-11-19 20:23:10 | D | + x: None +24-11-19 20:23:10 | D | + y: None +24-11-19 20:23:10 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:23:10 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:23:10 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:23:10 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:23:11 | D | - range ratio = [ 1.0000] +24-11-19 20:23:11 | D | sum error = [ 2.4073] +24-11-19 20:23:11 | D | best error = [ 2.4073] +24-11-19 20:23:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:23 | D | sum error = [ 2.4008, 2.4260, 2.4836, 2.4021, 2.5166] +24-11-19 20:23:23 | D | best error = [ 2.4008, 2.4008, 2.4008, 2.4008, 2.4008] +24-11-19 20:23:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:23 | D | sum error = [ 2.5970, 2.7742, 2.7990, 2.8735, 3.0610] +24-11-19 20:23:23 | D | best error = [ 2.4008, 2.4008, 2.4008, 2.4008, 2.4008] +24-11-19 20:23:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:23 | D | sum error = [ 3.2375, 3.5626, 3.7853, 4.1577, 4.4028] +24-11-19 20:23:23 | D | best error = [ 2.4008, 2.4008, 2.4008, 2.4008, 2.4008] +24-11-19 20:23:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:23 | D | sum error = [ 4.8264, 5.1823, 5.7005, 6.1577, 6.6695] +24-11-19 20:23:23 | D | best error = [ 2.4008, 2.4008, 2.4008, 2.4008, 2.4008] +24-11-19 20:23:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:23 | D | sum error = [ 7.3472, 7.9566, 8.7550, 9.4792, 10.3656] +24-11-19 20:23:23 | D | best error = [ 2.4008, 2.4008, 2.4008, 2.4008, 2.4008] +24-11-19 20:23:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:23 | D | sum error = [ 11.3179, 12.1881, 13.2955, 14.3676, 15.7177] +24-11-19 20:23:23 | D | best error = [ 2.4008, 2.4008, 2.4008, 2.4008, 2.4008] +24-11-19 20:23:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:23 | D | sum error = [ 16.9609, 18.4562, 19.8767, 21.5057, 23.2952] +24-11-19 20:23:23 | D | best error = [ 2.4008, 2.4008, 2.4008, 2.4008, 2.4008] +24-11-19 20:23:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:23 | D | sum error = [ 25.2488, 27.2740, 29.4739, 31.8475, 34.4083] +24-11-19 20:23:23 | D | best error = [ 2.4008, 2.4008, 2.4008, 2.4008, 2.4008] +24-11-19 20:23:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:23 | D | sum error = [ 37.0824, 39.9841, 43.0561, 46.2409, 49.7786] +24-11-19 20:23:23 | D | best error = [ 2.4008, 2.4008, 2.4008, 2.4008, 2.4008] +24-11-19 20:23:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:23 | D | sum error = [ 53.3854, 57.2631, 61.3468, 65.8177, 70.5062] +24-11-19 20:23:23 | D | best error = [ 2.4008, 2.4008, 2.4008, 2.4008, 2.4008] +24-11-19 20:23:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:23 | D | sum error = [ 75.4854, 80.7341, 86.3371, 92.1864, 98.6200] +24-11-19 20:23:23 | D | best error = [ 2.4008, 2.4008, 2.4008, 2.4008, 2.4008] +24-11-19 20:23:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:23 | D | sum error = [ 105.4907, 112.5827, 120.4167, 128.4154, 137.0566] +24-11-19 20:23:23 | D | best error = [ 2.4008, 2.4008, 2.4008, 2.4008, 2.4008] +24-11-19 20:23:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:23 | D | sum error = [ 146.3695, 156.1575, 166.5676, 177.5421, 189.3027] +24-11-19 20:23:23 | D | best error = [ 2.4008, 2.4008, 2.4008, 2.4008, 2.4008] +24-11-19 20:23:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:23 | D | sum error = [ 201.8054, 214.9074, 228.8258, 243.3977, 259.0008] +24-11-19 20:23:23 | D | best error = [ 2.4008, 2.4008, 2.4008, 2.4008, 2.4008] +24-11-19 20:23:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:23 | D | sum error = [ 275.2472, 292.4970, 310.7419, 329.4979, 349.3695] +24-11-19 20:23:23 | D | best error = [ 2.4008, 2.4008, 2.4008, 2.4008, 2.4008] +24-11-19 20:23:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:23 | D | sum error = [ 369.6927, 390.6802, 412.4688, 434.5260, 457.3066] +24-11-19 20:23:23 | D | best error = [ 2.4008, 2.4008, 2.4008, 2.4008, 2.4008] +24-11-19 20:23:23 | D | + error = [2.4008] +24-11-19 20:23:23 | D | - Calibrating model.layers.6.self_attn.k_proj.weight +24-11-19 20:23:23 | D | + w: sint8 +24-11-19 20:23:23 | D | + x: None +24-11-19 20:23:23 | D | + y: None +24-11-19 20:23:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:23:23 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:23 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:24 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:24 | D | - range ratio = [ 1.0000] +24-11-19 20:23:24 | D | sum error = [ 2.2780] +24-11-19 20:23:24 | D | best error = [ 2.2780] +24-11-19 20:23:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:36 | D | sum error = [ 2.3422, 2.3107, 2.3612, 2.6582, 2.7523] +24-11-19 20:23:36 | D | best error = [ 2.2780, 2.2780, 2.2780, 2.2780, 2.2780] +24-11-19 20:23:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:36 | D | sum error = [ 2.4789, 3.1952, 2.7345, 2.7679, 3.1254] +24-11-19 20:23:36 | D | best error = [ 2.2780, 2.2780, 2.2780, 2.2780, 2.2780] +24-11-19 20:23:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:36 | D | sum error = [ 3.5560, 3.7505, 3.8613, 4.0561, 4.8421] +24-11-19 20:23:36 | D | best error = [ 2.2780, 2.2780, 2.2780, 2.2780, 2.2780] +24-11-19 20:23:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:36 | D | sum error = [ 4.9870, 5.0715, 5.7096, 6.1202, 6.3432] +24-11-19 20:23:36 | D | best error = [ 2.2780, 2.2780, 2.2780, 2.2780, 2.2780] +24-11-19 20:23:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:36 | D | sum error = [ 6.4498, 7.6895, 7.7955, 8.3366, 9.5797] +24-11-19 20:23:36 | D | best error = [ 2.2780, 2.2780, 2.2780, 2.2780, 2.2780] +24-11-19 20:23:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:36 | D | sum error = [ 10.4767, 10.7750, 11.7513, 12.6763, 13.6768] +24-11-19 20:23:36 | D | best error = [ 2.2780, 2.2780, 2.2780, 2.2780, 2.2780] +24-11-19 20:23:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:36 | D | sum error = [ 15.0227, 16.3606, 17.5782, 18.9596, 20.4943] +24-11-19 20:23:36 | D | best error = [ 2.2780, 2.2780, 2.2780, 2.2780, 2.2780] +24-11-19 20:23:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:36 | D | sum error = [ 22.3674, 24.2783, 26.0999, 28.1019, 30.7953] +24-11-19 20:23:36 | D | best error = [ 2.2780, 2.2780, 2.2780, 2.2780, 2.2780] +24-11-19 20:23:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:36 | D | sum error = [ 32.7203, 35.7341, 38.4429, 41.2350, 44.5830] +24-11-19 20:23:36 | D | best error = [ 2.2780, 2.2780, 2.2780, 2.2780, 2.2780] +24-11-19 20:23:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:36 | D | sum error = [ 48.0895, 52.2855, 55.8403, 60.3008, 64.6185] +24-11-19 20:23:36 | D | best error = [ 2.2780, 2.2780, 2.2780, 2.2780, 2.2780] +24-11-19 20:23:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:36 | D | sum error = [ 69.3134, 74.6386, 80.3260, 86.0477, 92.2432] +24-11-19 20:23:36 | D | best error = [ 2.2780, 2.2780, 2.2780, 2.2780, 2.2780] +24-11-19 20:23:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:36 | D | sum error = [ 98.8095, 106.1022, 113.7372, 121.6598, 130.2800] +24-11-19 20:23:36 | D | best error = [ 2.2780, 2.2780, 2.2780, 2.2780, 2.2780] +24-11-19 20:23:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:36 | D | sum error = [ 139.3543, 149.3068, 159.8472, 170.9659, 182.6146] +24-11-19 20:23:36 | D | best error = [ 2.2780, 2.2780, 2.2780, 2.2780, 2.2780] +24-11-19 20:23:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:36 | D | sum error = [ 195.4775, 208.8471, 223.3621, 238.7473, 255.0283] +24-11-19 20:23:36 | D | best error = [ 2.2780, 2.2780, 2.2780, 2.2780, 2.2780] +24-11-19 20:23:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:36 | D | sum error = [ 272.2159, 290.0759, 308.9941, 328.4416, 348.8676] +24-11-19 20:23:36 | D | best error = [ 2.2780, 2.2780, 2.2780, 2.2780, 2.2780] +24-11-19 20:23:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:36 | D | sum error = [ 369.9743, 391.6636, 413.9733, 436.7088, 459.4202] +24-11-19 20:23:36 | D | best error = [ 2.2780, 2.2780, 2.2780, 2.2780, 2.2780] +24-11-19 20:23:36 | D | + error = [2.2780] +24-11-19 20:23:36 | D | - Calibrating model.layers.6.self_attn.v_proj.weight +24-11-19 20:23:36 | D | + w: sint8 +24-11-19 20:23:36 | D | + x: None +24-11-19 20:23:36 | D | + y: None +24-11-19 20:23:36 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:36 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:36 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:36 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:36 | D | - range ratio = [ 1.0000] +24-11-19 20:23:36 | D | sum error = [ 1.1028] +24-11-19 20:23:36 | D | best error = [ 1.1028] +24-11-19 20:23:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:36 | D | sum error = [ 1.0958, 1.0913, 1.1007, 1.1122, 1.1424] +24-11-19 20:23:36 | D | best error = [ 1.0285, 0.9991, 0.9847, 0.9776, 0.9746] +24-11-19 20:23:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:36 | D | sum error = [ 1.1566, 1.1924, 1.2335, 1.2966, 1.3712] +24-11-19 20:23:36 | D | best error = [ 0.9728, 0.9723, 0.9718, 0.9717, 0.9716] +24-11-19 20:23:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:36 | D | sum error = [ 1.4549, 1.5435, 1.6493, 1.7468, 1.8753] +24-11-19 20:23:36 | D | best error = [ 0.9716, 0.9716, 0.9716, 0.9716, 0.9716] +24-11-19 20:23:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:36 | D | sum error = [ 2.0072, 2.1596, 2.3008, 2.4728, 2.6497] +24-11-19 20:23:36 | D | best error = [ 0.9716, 0.9716, 0.9716, 0.9716, 0.9716] +24-11-19 20:23:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:36 | D | sum error = [ 2.8291, 3.0313, 3.2430, 3.4692, 3.7042] +24-11-19 20:23:36 | D | best error = [ 0.9716, 0.9716, 0.9716, 0.9716, 0.9716] +24-11-19 20:23:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:36 | D | sum error = [ 3.9609, 4.2310, 4.5137, 4.8199, 5.1322] +24-11-19 20:23:36 | D | best error = [ 0.9716, 0.9716, 0.9716, 0.9716, 0.9716] +24-11-19 20:23:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:36 | D | sum error = [ 5.4729, 5.8235, 6.2010, 6.6020, 7.0157] +24-11-19 20:23:36 | D | best error = [ 0.9716, 0.9716, 0.9716, 0.9716, 0.9716] +24-11-19 20:23:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:36 | D | sum error = [ 7.4625, 7.9124, 8.4071, 8.9201, 9.4699] +24-11-19 20:23:36 | D | best error = [ 0.9716, 0.9716, 0.9716, 0.9716, 0.9716] +24-11-19 20:23:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:36 | D | sum error = [ 10.0319, 10.6439, 11.2716, 11.9378, 12.6385] +24-11-19 20:23:36 | D | best error = [ 0.9716, 0.9716, 0.9716, 0.9716, 0.9716] +24-11-19 20:23:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:36 | D | sum error = [ 13.3784, 14.1471, 14.9640, 15.8141, 16.7034] +24-11-19 20:23:36 | D | best error = [ 0.9716, 0.9716, 0.9716, 0.9716, 0.9716] +24-11-19 20:23:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:36 | D | sum error = [ 17.6404, 18.6222, 19.6393, 20.7171, 21.8289] +24-11-19 20:23:36 | D | best error = [ 0.9716, 0.9716, 0.9716, 0.9716, 0.9716] +24-11-19 20:23:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:36 | D | sum error = [ 23.0080, 24.2279, 25.5063, 26.8480, 28.2395] +24-11-19 20:23:36 | D | best error = [ 0.9716, 0.9716, 0.9716, 0.9716, 0.9716] +24-11-19 20:23:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:36 | D | sum error = [ 29.6963, 31.2189, 32.7920, 34.4421, 36.1518] +24-11-19 20:23:36 | D | best error = [ 0.9716, 0.9716, 0.9716, 0.9716, 0.9716] +24-11-19 20:23:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:36 | D | sum error = [ 37.9290, 39.7689, 41.6829, 43.6619, 45.7141] +24-11-19 20:23:36 | D | best error = [ 0.9716, 0.9716, 0.9716, 0.9716, 0.9716] +24-11-19 20:23:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:36 | D | sum error = [ 47.8496, 50.0509, 52.3318, 54.6941, 57.1372] +24-11-19 20:23:36 | D | best error = [ 0.9716, 0.9716, 0.9716, 0.9716, 0.9716] +24-11-19 20:23:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:36 | D | sum error = [ 59.6508, 62.2518, 64.9279, 67.6868, 70.5321] +24-11-19 20:23:36 | D | best error = [ 0.9716, 0.9716, 0.9716, 0.9716, 0.9716] +24-11-19 20:23:36 | D | + error = [0.9716] +24-11-19 20:23:37 | D | - Calibrating model.layers.6.self_attn.o_proj.weight +24-11-19 20:23:37 | D | + w: sint8 +24-11-19 20:23:37 | D | + x: None +24-11-19 20:23:37 | D | + y: None +24-11-19 20:23:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:37 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:37 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:37 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:37 | D | - range ratio = [ 1.0000] +24-11-19 20:23:37 | D | sum error = [ 0.3658] +24-11-19 20:23:37 | D | best error = [ 0.3658] +24-11-19 20:23:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:37 | D | sum error = [ 0.3632, 0.3645, 0.3643, 0.3695, 0.3754] +24-11-19 20:23:37 | D | best error = [ 0.3373, 0.3257, 0.3186, 0.3143, 0.3114] +24-11-19 20:23:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:37 | D | sum error = [ 0.3849, 0.3964, 0.4123, 0.4311, 0.4512] +24-11-19 20:23:37 | D | best error = [ 0.3100, 0.3089, 0.3082, 0.3077, 0.3074] +24-11-19 20:23:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:37 | D | sum error = [ 0.4776, 0.5028, 0.5314, 0.5618, 0.6004] +24-11-19 20:23:37 | D | best error = [ 0.3070, 0.3068, 0.3067, 0.3066, 0.3065] +24-11-19 20:23:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:37 | D | sum error = [ 0.6388, 0.6786, 0.7214, 0.7687, 0.8185] +24-11-19 20:23:37 | D | best error = [ 0.3065, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:23:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:37 | D | sum error = [ 0.8699, 0.9265, 0.9852, 1.0466, 1.1118] +24-11-19 20:23:37 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:23:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:37 | D | sum error = [ 1.1816, 1.2510, 1.3272, 1.4065, 1.4904] +24-11-19 20:23:37 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:23:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:37 | D | sum error = [ 1.5768, 1.6684, 1.7644, 1.8649, 1.9705] +24-11-19 20:23:37 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:23:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:37 | D | sum error = [ 2.0794, 2.1947, 2.3160, 2.4401, 2.5726] +24-11-19 20:23:37 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:23:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:37 | D | sum error = [ 2.7096, 2.8545, 3.0060, 3.1643, 3.3293] +24-11-19 20:23:37 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:23:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:37 | D | sum error = [ 3.5034, 3.6842, 3.8732, 4.0717, 4.2772] +24-11-19 20:23:37 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:23:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:37 | D | sum error = [ 4.4926, 4.7168, 4.9498, 5.1919, 5.4448] +24-11-19 20:23:37 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:23:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:37 | D | sum error = [ 5.7068, 5.9800, 6.2653, 6.5606, 6.8688] +24-11-19 20:23:37 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:23:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:37 | D | sum error = [ 7.1897, 7.5221, 7.8671, 8.2252, 8.5960] +24-11-19 20:23:37 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:23:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:37 | D | sum error = [ 8.9816, 9.3799, 9.7937, 10.2223, 10.6639] +24-11-19 20:23:37 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:23:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:37 | D | sum error = [ 11.1230, 11.5966, 12.0861, 12.5925, 13.1163] +24-11-19 20:23:37 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:23:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:37 | D | sum error = [ 13.6578, 14.2172, 14.7952, 15.3924, 16.0090] +24-11-19 20:23:37 | D | best error = [ 0.3064, 0.3064, 0.3064, 0.3064, 0.3064] +24-11-19 20:23:37 | D | + error = [0.3064] +24-11-19 20:23:37 | D | - Calibrating model.layers.6.mlp.up_proj.weight +24-11-19 20:23:37 | D | + w: sint8 +24-11-19 20:23:37 | D | + x: None +24-11-19 20:23:37 | D | + y: None +24-11-19 20:23:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:37 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:37 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:38 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:38 | D | - range ratio = [ 1.0000] +24-11-19 20:23:38 | D | sum error = [ 4.6048] +24-11-19 20:23:38 | D | best error = [ 4.6048] +24-11-19 20:23:39 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:39 | D | sum error = [ 4.5751, 4.5580, 4.5795, 4.6403, 4.7250] +24-11-19 20:23:39 | D | best error = [ 4.3023, 4.1883, 4.1246, 4.0898, 4.0724] +24-11-19 20:23:39 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:39 | D | sum error = [ 4.8312, 4.9964, 5.2097, 5.4387, 5.7219] +24-11-19 20:23:39 | D | best error = [ 4.0634, 4.0602, 4.0590, 4.0587, 4.0586] +24-11-19 20:23:39 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:39 | D | sum error = [ 6.0575, 6.4312, 6.8528, 7.3133, 7.8158] +24-11-19 20:23:39 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 20:23:39 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:39 | D | sum error = [ 8.3582, 8.9582, 9.5980, 10.2744, 11.0165] +24-11-19 20:23:39 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 20:23:39 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:39 | D | sum error = [ 11.7991, 12.6288, 13.5297, 14.4738, 15.4768] +24-11-19 20:23:39 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 20:23:39 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:39 | D | sum error = [ 16.5435, 17.6615, 18.8578, 20.1140, 21.4432] +24-11-19 20:23:39 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 20:23:39 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:39 | D | sum error = [ 22.8482, 24.3298, 25.9014, 27.5467, 29.2704] +24-11-19 20:23:39 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 20:23:39 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:39 | D | sum error = [ 31.1016, 33.0175, 35.0288, 37.1579, 39.3903] +24-11-19 20:23:39 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 20:23:39 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:39 | D | sum error = [ 41.7211, 44.1764, 46.7496, 49.4543, 52.2792] +24-11-19 20:23:39 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 20:23:39 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:39 | D | sum error = [ 55.2352, 58.3295, 61.5643, 64.9536, 68.5032] +24-11-19 20:23:39 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 20:23:39 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:39 | D | sum error = [ 72.1966, 76.0591, 80.0944, 84.3043, 88.6972] +24-11-19 20:23:39 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 20:23:39 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:39 | D | sum error = [ 93.2649, 98.0222, 102.9737, 108.1378, 113.4867] +24-11-19 20:23:39 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 20:23:39 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:39 | D | sum error = [ 119.0547, 124.8393, 130.8424, 137.0706, 143.5283] +24-11-19 20:23:39 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 20:23:39 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:39 | D | sum error = [ 150.2342, 157.1648, 164.3629, 171.8037, 179.4991] +24-11-19 20:23:39 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 20:23:39 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:39 | D | sum error = [ 187.4443, 195.6485, 204.1078, 212.8547, 221.8630] +24-11-19 20:23:39 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 20:23:39 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:39 | D | sum error = [ 231.1562, 240.7240, 250.5812, 260.7106, 271.1334] +24-11-19 20:23:39 | D | best error = [ 4.0586, 4.0586, 4.0586, 4.0586, 4.0586] +24-11-19 20:23:39 | D | + error = [4.0586] +24-11-19 20:23:39 | D | - Calibrating model.layers.6.mlp.gate_proj.weight +24-11-19 20:23:39 | D | + w: sint8 +24-11-19 20:23:39 | D | + x: None +24-11-19 20:23:39 | D | + y: None +24-11-19 20:23:39 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:39 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:39 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:39 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:39 | D | - range ratio = [ 1.0000] +24-11-19 20:23:39 | D | sum error = [ 6.1103] +24-11-19 20:23:39 | D | best error = [ 6.1103] +24-11-19 20:23:40 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:40 | D | sum error = [ 6.0622, 6.0487, 6.0676, 6.1397, 6.2557] +24-11-19 20:23:40 | D | best error = [ 5.7028, 5.5490, 5.4700, 5.4242, 5.4019] +24-11-19 20:23:40 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:40 | D | sum error = [ 6.4338, 6.6374, 6.9191, 7.2440, 7.6370] +24-11-19 20:23:40 | D | best error = [ 5.3910, 5.3865, 5.3853, 5.3848, 5.3847] +24-11-19 20:23:40 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:40 | D | sum error = [ 8.0797, 8.5823, 9.1400, 9.7951, 10.4627] +24-11-19 20:23:40 | D | best error = [ 5.3847, 5.3847, 5.3847, 5.3847, 5.3847] +24-11-19 20:23:40 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:40 | D | sum error = [ 11.2295, 12.0334, 12.9126, 13.8542, 14.8836] +24-11-19 20:23:40 | D | best error = [ 5.3847, 5.3847, 5.3847, 5.3847, 5.3847] +24-11-19 20:23:40 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:40 | D | sum error = [ 15.9818, 17.1475, 18.3853, 19.7277, 21.1390] +24-11-19 20:23:40 | D | best error = [ 5.3847, 5.3847, 5.3847, 5.3847, 5.3847] +24-11-19 20:23:40 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:40 | D | sum error = [ 22.6415, 24.2583, 25.9563, 27.7583, 29.6803] +24-11-19 20:23:40 | D | best error = [ 5.3847, 5.3847, 5.3847, 5.3847, 5.3847] +24-11-19 20:23:40 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:40 | D | sum error = [ 31.7296, 33.9135, 36.1995, 38.6389, 41.2396] +24-11-19 20:23:40 | D | best error = [ 5.3847, 5.3847, 5.3847, 5.3847, 5.3847] +24-11-19 20:23:40 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:40 | D | sum error = [ 43.9905, 46.8853, 49.9794, 53.2409, 56.7032] +24-11-19 20:23:40 | D | best error = [ 5.3847, 5.3847, 5.3847, 5.3847, 5.3847] +24-11-19 20:23:40 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:40 | D | sum error = [ 60.3782, 64.2660, 68.3712, 72.7398, 77.3369] +24-11-19 20:23:40 | D | best error = [ 5.3847, 5.3847, 5.3847, 5.3847, 5.3847] +24-11-19 20:23:40 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:40 | D | sum error = [ 82.2105, 87.3826, 92.8334, 98.5992, 104.6897] +24-11-19 20:23:40 | D | best error = [ 5.3847, 5.3847, 5.3847, 5.3847, 5.3847] +24-11-19 20:23:40 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:40 | D | sum error = [ 111.1083, 117.8939, 125.0383, 132.5809, 140.5085] +24-11-19 20:23:40 | D | best error = [ 5.3847, 5.3847, 5.3847, 5.3847, 5.3847] +24-11-19 20:23:40 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:40 | D | sum error = [ 148.8493, 157.6321, 166.8888, 176.5964, 186.7942] +24-11-19 20:23:40 | D | best error = [ 5.3847, 5.3847, 5.3847, 5.3847, 5.3847] +24-11-19 20:23:40 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:40 | D | sum error = [ 197.4981, 208.7079, 220.4500, 232.7443, 245.6082] +24-11-19 20:23:40 | D | best error = [ 5.3847, 5.3847, 5.3847, 5.3847, 5.3847] +24-11-19 20:23:40 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:40 | D | sum error = [ 259.0398, 273.0696, 287.7105, 302.9693, 318.8695] +24-11-19 20:23:40 | D | best error = [ 5.3847, 5.3847, 5.3847, 5.3847, 5.3847] +24-11-19 20:23:40 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:40 | D | sum error = [ 335.4118, 352.5964, 370.4469, 388.9597, 408.1286] +24-11-19 20:23:40 | D | best error = [ 5.3847, 5.3847, 5.3847, 5.3847, 5.3847] +24-11-19 20:23:40 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:40 | D | sum error = [ 427.9997, 448.5553, 469.7972, 491.7139, 514.3113] +24-11-19 20:23:40 | D | best error = [ 5.3847, 5.3847, 5.3847, 5.3847, 5.3847] +24-11-19 20:23:40 | D | + error = [5.3847] +24-11-19 20:23:40 | D | - Calibrating model.layers.6.mlp.down_proj.weight +24-11-19 20:23:40 | D | + w: sint8 +24-11-19 20:23:40 | D | + x: None +24-11-19 20:23:40 | D | + y: None +24-11-19 20:23:40 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:23:40 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:23:40 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:23:41 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:23:41 | D | - range ratio = [ 1.0000] +24-11-19 20:23:41 | D | sum error = [ 0.5203] +24-11-19 20:23:41 | D | best error = [ 0.5203] +24-11-19 20:23:42 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:23:42 | D | sum error = [ 0.5156, 0.5109, 0.5083, 0.5064, 0.5061] +24-11-19 20:23:42 | D | best error = [ 0.5010, 0.4908, 0.4841, 0.4789, 0.4752] +24-11-19 20:23:42 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:23:42 | D | sum error = [ 0.5071, 0.5091, 0.5140, 0.5193, 0.5295] +24-11-19 20:23:42 | D | best error = [ 0.4724, 0.4700, 0.4683, 0.4672, 0.4663] +24-11-19 20:23:42 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:23:42 | D | sum error = [ 0.5416, 0.5557, 0.5747, 0.5952, 0.6194] +24-11-19 20:23:42 | D | best error = [ 0.4657, 0.4653, 0.4649, 0.4647, 0.4646] +24-11-19 20:23:42 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:23:42 | D | sum error = [ 0.6469, 0.6784, 0.7146, 0.7549, 0.7996] +24-11-19 20:23:42 | D | best error = [ 0.4645, 0.4645, 0.4645, 0.4644, 0.4644] +24-11-19 20:23:42 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:23:42 | D | sum error = [ 0.8482, 0.9028, 0.9610, 1.0242, 1.0937] +24-11-19 20:23:42 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 20:23:42 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:23:42 | D | sum error = [ 1.1684, 1.2487, 1.3351, 1.4275, 1.5263] +24-11-19 20:23:42 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 20:23:42 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:23:42 | D | sum error = [ 1.6315, 1.7449, 1.8666, 1.9946, 2.1321] +24-11-19 20:23:42 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 20:23:42 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:23:42 | D | sum error = [ 2.2766, 2.4320, 2.5962, 2.7693, 2.9537] +24-11-19 20:23:42 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 20:23:42 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:23:42 | D | sum error = [ 3.1490, 3.3557, 3.5751, 3.8062, 4.0505] +24-11-19 20:23:42 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 20:23:42 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:23:42 | D | sum error = [ 4.3088, 4.5809, 4.8682, 5.1704, 5.4896] +24-11-19 20:23:42 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 20:23:42 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:23:42 | D | sum error = [ 5.8257, 6.1781, 6.5496, 6.9396, 7.3491] +24-11-19 20:23:42 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 20:23:42 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:23:42 | D | sum error = [ 7.7792, 8.2311, 8.7038, 9.1985, 9.7163] +24-11-19 20:23:42 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 20:23:42 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:23:42 | D | sum error = [ 10.2583, 10.8249, 11.4171, 12.0356, 12.6803] +24-11-19 20:23:42 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 20:23:42 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:23:42 | D | sum error = [ 13.3531, 14.0538, 14.7836, 15.5435, 16.3321] +24-11-19 20:23:42 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 20:23:42 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:23:42 | D | sum error = [ 17.1529, 18.0045, 18.8889, 19.8062, 20.7572] +24-11-19 20:23:42 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 20:23:42 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:23:42 | D | sum error = [ 21.7421, 22.7620, 23.8175, 24.9094, 26.0370] +24-11-19 20:23:42 | D | best error = [ 0.4644, 0.4644, 0.4644, 0.4644, 0.4644] +24-11-19 20:23:42 | D | + error = [0.4644] +24-11-19 20:23:42 | D | - Quantizing model.layers.6.self_attn.q_proj.weight +24-11-19 20:23:43 | D | - Quantizing model.layers.6.self_attn.k_proj.weight +24-11-19 20:23:45 | D | - Quantizing model.layers.6.self_attn.v_proj.weight +24-11-19 20:23:46 | D | - Quantizing model.layers.6.self_attn.o_proj.weight +24-11-19 20:23:48 | D | - Quantizing model.layers.6.mlp.up_proj.weight +24-11-19 20:23:49 | D | - Quantizing model.layers.6.mlp.gate_proj.weight +24-11-19 20:23:50 | D | - Quantizing model.layers.6.mlp.down_proj.weight +24-11-19 20:24:03 | D | - Quantizing layer model.layers.7 +24-11-19 20:24:03 | D | - Calibrating model.layers.7.self_attn.q_proj.weight +24-11-19 20:24:03 | D | + w: sint8 +24-11-19 20:24:03 | D | + x: None +24-11-19 20:24:03 | D | + y: None +24-11-19 20:24:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:24:03 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:24:04 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:24:04 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:24:04 | D | - range ratio = [ 1.0000] +24-11-19 20:24:04 | D | sum error = [ 2.9767] +24-11-19 20:24:04 | D | best error = [ 2.9767] +24-11-19 20:24:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:17 | D | sum error = [ 3.0171, 3.0151, 3.0277, 3.0585, 3.1088] +24-11-19 20:24:17 | D | best error = [ 2.9767, 2.9767, 2.9767, 2.9767, 2.9767] +24-11-19 20:24:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:17 | D | sum error = [ 3.1735, 3.3582, 3.4262, 3.7763, 4.0405] +24-11-19 20:24:17 | D | best error = [ 2.9767, 2.9767, 2.9767, 2.9767, 2.9767] +24-11-19 20:24:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:17 | D | sum error = [ 4.1054, 4.3466, 4.6770, 5.1639, 5.5433] +24-11-19 20:24:17 | D | best error = [ 2.9767, 2.9767, 2.9767, 2.9767, 2.9767] +24-11-19 20:24:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:17 | D | sum error = [ 5.9543, 6.5099, 6.9370, 7.6982, 8.5361] +24-11-19 20:24:17 | D | best error = [ 2.9767, 2.9767, 2.9767, 2.9767, 2.9767] +24-11-19 20:24:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:17 | D | sum error = [ 9.2553, 10.3064, 11.4682, 12.6646, 13.5239] +24-11-19 20:24:17 | D | best error = [ 2.9767, 2.9767, 2.9767, 2.9767, 2.9767] +24-11-19 20:24:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:17 | D | sum error = [ 15.2221, 16.4967, 18.0618, 19.9912, 21.6761] +24-11-19 20:24:17 | D | best error = [ 2.9767, 2.9767, 2.9767, 2.9767, 2.9767] +24-11-19 20:24:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:17 | D | sum error = [ 23.7325, 25.8979, 28.4294, 31.1437, 33.7144] +24-11-19 20:24:17 | D | best error = [ 2.9767, 2.9767, 2.9767, 2.9767, 2.9767] +24-11-19 20:24:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:17 | D | sum error = [ 37.0459, 40.1411, 43.6068, 47.2431, 51.0894] +24-11-19 20:24:17 | D | best error = [ 2.9767, 2.9767, 2.9767, 2.9767, 2.9767] +24-11-19 20:24:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:17 | D | sum error = [ 55.3860, 59.7018, 64.3134, 69.3846, 74.8153] +24-11-19 20:24:17 | D | best error = [ 2.9767, 2.9767, 2.9767, 2.9767, 2.9767] +24-11-19 20:24:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:17 | D | sum error = [ 80.3985, 86.1570, 92.2309, 98.8567, 105.6803] +24-11-19 20:24:17 | D | best error = [ 2.9767, 2.9767, 2.9767, 2.9767, 2.9767] +24-11-19 20:24:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:17 | D | sum error = [ 113.0983, 120.6991, 128.8468, 137.1316, 146.1940] +24-11-19 20:24:17 | D | best error = [ 2.9767, 2.9767, 2.9767, 2.9767, 2.9767] +24-11-19 20:24:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:17 | D | sum error = [ 155.5448, 165.2288, 175.7515, 186.6400, 197.7939] +24-11-19 20:24:17 | D | best error = [ 2.9767, 2.9767, 2.9767, 2.9767, 2.9767] +24-11-19 20:24:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:17 | D | sum error = [ 209.6565, 221.9133, 234.6272, 247.9224, 261.8067] +24-11-19 20:24:17 | D | best error = [ 2.9767, 2.9767, 2.9767, 2.9767, 2.9767] +24-11-19 20:24:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:17 | D | sum error = [ 276.0049, 290.7874, 305.3991, 321.0072, 336.4618] +24-11-19 20:24:17 | D | best error = [ 2.9767, 2.9767, 2.9767, 2.9767, 2.9767] +24-11-19 20:24:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:17 | D | sum error = [ 353.0748, 369.7076, 387.0373, 404.6781, 422.7463] +24-11-19 20:24:17 | D | best error = [ 2.9767, 2.9767, 2.9767, 2.9767, 2.9767] +24-11-19 20:24:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:17 | D | sum error = [ 441.4848, 460.2731, 479.6464, 499.3690, 519.7316] +24-11-19 20:24:17 | D | best error = [ 2.9767, 2.9767, 2.9767, 2.9767, 2.9767] +24-11-19 20:24:17 | D | + error = [2.9767] +24-11-19 20:24:17 | D | - Calibrating model.layers.7.self_attn.k_proj.weight +24-11-19 20:24:17 | D | + w: sint8 +24-11-19 20:24:17 | D | + x: None +24-11-19 20:24:17 | D | + y: None +24-11-19 20:24:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:24:17 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:17 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:17 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:18 | D | - range ratio = [ 1.0000] +24-11-19 20:24:18 | D | sum error = [ 3.1498] +24-11-19 20:24:18 | D | best error = [ 3.1498] +24-11-19 20:24:30 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:30 | D | sum error = [ 2.8709, 3.3215, 3.0537, 2.7179, 3.2492] +24-11-19 20:24:30 | D | best error = [ 2.8709, 2.8709, 2.8709, 2.7179, 2.7179] +24-11-19 20:24:30 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:30 | D | sum error = [ 3.0847, 2.8941, 3.4649, 3.8272, 3.5087] +24-11-19 20:24:30 | D | best error = [ 2.7179, 2.7179, 2.7179, 2.7179, 2.7179] +24-11-19 20:24:30 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:30 | D | sum error = [ 3.8040, 3.9446, 4.6265, 4.8181, 5.3574] +24-11-19 20:24:30 | D | best error = [ 2.7179, 2.7179, 2.7179, 2.7179, 2.7179] +24-11-19 20:24:30 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:30 | D | sum error = [ 5.5507, 6.0624, 6.1785, 7.1912, 7.7705] +24-11-19 20:24:30 | D | best error = [ 2.7179, 2.7179, 2.7179, 2.7179, 2.7179] +24-11-19 20:24:30 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:30 | D | sum error = [ 8.6689, 9.2458, 9.9512, 10.8408, 11.6543] +24-11-19 20:24:30 | D | best error = [ 2.7179, 2.7179, 2.7179, 2.7179, 2.7179] +24-11-19 20:24:30 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:30 | D | sum error = [ 12.6431, 13.7935, 14.3884, 16.2810, 17.2057] +24-11-19 20:24:30 | D | best error = [ 2.7179, 2.7179, 2.7179, 2.7179, 2.7179] +24-11-19 20:24:30 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:30 | D | sum error = [ 18.7486, 20.1313, 22.5105, 24.1511, 26.5715] +24-11-19 20:24:30 | D | best error = [ 2.7179, 2.7179, 2.7179, 2.7179, 2.7179] +24-11-19 20:24:30 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:30 | D | sum error = [ 29.1094, 31.7704, 34.5827, 38.4679, 41.4830] +24-11-19 20:24:30 | D | best error = [ 2.7179, 2.7179, 2.7179, 2.7179, 2.7179] +24-11-19 20:24:30 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:30 | D | sum error = [ 45.2735, 49.2238, 53.4675, 57.8005, 61.8031] +24-11-19 20:24:30 | D | best error = [ 2.7179, 2.7179, 2.7179, 2.7179, 2.7179] +24-11-19 20:24:30 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:30 | D | sum error = [ 67.2173, 72.6992, 78.3887, 84.8756, 90.9722] +24-11-19 20:24:30 | D | best error = [ 2.7179, 2.7179, 2.7179, 2.7179, 2.7179] +24-11-19 20:24:30 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:30 | D | sum error = [ 98.3424, 105.3880, 112.9188, 120.9011, 129.8093] +24-11-19 20:24:30 | D | best error = [ 2.7179, 2.7179, 2.7179, 2.7179, 2.7179] +24-11-19 20:24:30 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:30 | D | sum error = [ 137.9081, 147.0337, 156.2513, 166.3548, 176.4532] +24-11-19 20:24:30 | D | best error = [ 2.7179, 2.7179, 2.7179, 2.7179, 2.7179] +24-11-19 20:24:30 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:30 | D | sum error = [ 187.7651, 198.8838, 210.8422, 222.9656, 235.3294] +24-11-19 20:24:30 | D | best error = [ 2.7179, 2.7179, 2.7179, 2.7179, 2.7179] +24-11-19 20:24:30 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:30 | D | sum error = [ 249.1889, 264.5284, 279.4596, 295.5980, 312.1865] +24-11-19 20:24:30 | D | best error = [ 2.7179, 2.7179, 2.7179, 2.7179, 2.7179] +24-11-19 20:24:30 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:30 | D | sum error = [ 329.4414, 347.8884, 366.7638, 386.2745, 406.0730] +24-11-19 20:24:30 | D | best error = [ 2.7179, 2.7179, 2.7179, 2.7179, 2.7179] +24-11-19 20:24:30 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:30 | D | sum error = [ 426.3189, 447.0565, 468.1285, 489.7824, 511.8907] +24-11-19 20:24:30 | D | best error = [ 2.7179, 2.7179, 2.7179, 2.7179, 2.7179] +24-11-19 20:24:30 | D | + error = [2.7179] +24-11-19 20:24:30 | D | - Calibrating model.layers.7.self_attn.v_proj.weight +24-11-19 20:24:30 | D | + w: sint8 +24-11-19 20:24:30 | D | + x: None +24-11-19 20:24:30 | D | + y: None +24-11-19 20:24:30 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:30 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:30 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:30 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:30 | D | - range ratio = [ 1.0000] +24-11-19 20:24:30 | D | sum error = [ 1.1250] +24-11-19 20:24:30 | D | best error = [ 1.1250] +24-11-19 20:24:30 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:30 | D | sum error = [ 1.1200, 1.1084, 1.1300, 1.1321, 1.1591] +24-11-19 20:24:30 | D | best error = [ 1.0516, 1.0210, 1.0087, 1.0002, 0.9957] +24-11-19 20:24:30 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:30 | D | sum error = [ 1.1906, 1.2354, 1.2745, 1.3361, 1.4065] +24-11-19 20:24:30 | D | best error = [ 0.9935, 0.9924, 0.9922, 0.9921, 0.9921] +24-11-19 20:24:30 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:30 | D | sum error = [ 1.4879, 1.5791, 1.6869, 1.8055, 1.9354] +24-11-19 20:24:30 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:24:30 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:30 | D | sum error = [ 2.0686, 2.2238, 2.3760, 2.5633, 2.7579] +24-11-19 20:24:30 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:24:30 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:30 | D | sum error = [ 2.9356, 3.1513, 3.3771, 3.6220, 3.8686] +24-11-19 20:24:30 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:24:30 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:30 | D | sum error = [ 4.1492, 4.4319, 4.7419, 5.0631, 5.3927] +24-11-19 20:24:30 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:24:30 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:30 | D | sum error = [ 5.7567, 6.1290, 6.5344, 6.9568, 7.4034] +24-11-19 20:24:30 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:24:30 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:30 | D | sum error = [ 7.8809, 8.3782, 8.8992, 9.4552, 10.0461] +24-11-19 20:24:30 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:24:30 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:30 | D | sum error = [ 10.6640, 11.3072, 11.9923, 12.7132, 13.4617] +24-11-19 20:24:30 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:24:30 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:30 | D | sum error = [ 14.2609, 15.0904, 15.9592, 16.8738, 17.8270] +24-11-19 20:24:30 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:24:30 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:30 | D | sum error = [ 18.8383, 19.8926, 21.0050, 22.1700, 23.3840] +24-11-19 20:24:30 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:24:30 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:30 | D | sum error = [ 24.6591, 25.9887, 27.3872, 28.8498, 30.3803] +24-11-19 20:24:30 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:24:30 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:30 | D | sum error = [ 31.9758, 33.6425, 35.3716, 37.1790, 39.0540] +24-11-19 20:24:30 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:24:30 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:30 | D | sum error = [ 40.9988, 43.0157, 45.1184, 47.3027, 49.5725] +24-11-19 20:24:30 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:24:30 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:30 | D | sum error = [ 51.9212, 54.3640, 56.8904, 59.5147, 62.2232] +24-11-19 20:24:30 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:24:30 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:30 | D | sum error = [ 65.0220, 67.9180, 70.9062, 73.9873, 77.1589] +24-11-19 20:24:30 | D | best error = [ 0.9921, 0.9921, 0.9921, 0.9921, 0.9921] +24-11-19 20:24:30 | D | + error = [0.9921] +24-11-19 20:24:30 | D | - Calibrating model.layers.7.self_attn.o_proj.weight +24-11-19 20:24:30 | D | + w: sint8 +24-11-19 20:24:30 | D | + x: None +24-11-19 20:24:30 | D | + y: None +24-11-19 20:24:30 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:30 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:31 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:31 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:31 | D | - range ratio = [ 1.0000] +24-11-19 20:24:31 | D | sum error = [ 0.4495] +24-11-19 20:24:31 | D | best error = [ 0.4495] +24-11-19 20:24:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:31 | D | sum error = [ 0.4475, 0.4437, 0.4447, 0.4467, 0.4539] +24-11-19 20:24:31 | D | best error = [ 0.4121, 0.3951, 0.3850, 0.3786, 0.3743] +24-11-19 20:24:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:31 | D | sum error = [ 0.4631, 0.4731, 0.4871, 0.5047, 0.5262] +24-11-19 20:24:31 | D | best error = [ 0.3719, 0.3701, 0.3692, 0.3684, 0.3680] +24-11-19 20:24:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:31 | D | sum error = [ 0.5504, 0.5750, 0.6075, 0.6398, 0.6770] +24-11-19 20:24:31 | D | best error = [ 0.3677, 0.3675, 0.3674, 0.3674, 0.3674] +24-11-19 20:24:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:31 | D | sum error = [ 0.7182, 0.7623, 0.8106, 0.8605, 0.9132] +24-11-19 20:24:31 | D | best error = [ 0.3674, 0.3674, 0.3673, 0.3673, 0.3673] +24-11-19 20:24:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:31 | D | sum error = [ 0.9709, 1.0341, 1.0966, 1.1679, 1.2398] +24-11-19 20:24:31 | D | best error = [ 0.3673, 0.3673, 0.3673, 0.3673, 0.3673] +24-11-19 20:24:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:31 | D | sum error = [ 1.3156, 1.3971, 1.4838, 1.5728, 1.6663] +24-11-19 20:24:31 | D | best error = [ 0.3673, 0.3673, 0.3673, 0.3673, 0.3673] +24-11-19 20:24:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:31 | D | sum error = [ 1.7680, 1.8729, 1.9828, 2.1016, 2.2249] +24-11-19 20:24:31 | D | best error = [ 0.3673, 0.3673, 0.3673, 0.3673, 0.3673] +24-11-19 20:24:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:31 | D | sum error = [ 2.3552, 2.4905, 2.6323, 2.7809, 2.9375] +24-11-19 20:24:31 | D | best error = [ 0.3673, 0.3673, 0.3673, 0.3673, 0.3673] +24-11-19 20:24:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:31 | D | sum error = [ 3.1022, 3.2733, 3.4524, 3.6409, 3.8383] +24-11-19 20:24:31 | D | best error = [ 0.3673, 0.3673, 0.3673, 0.3673, 0.3673] +24-11-19 20:24:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:31 | D | sum error = [ 4.0452, 4.2621, 4.4847, 4.7199, 4.9679] +24-11-19 20:24:31 | D | best error = [ 0.3673, 0.3673, 0.3673, 0.3673, 0.3673] +24-11-19 20:24:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:31 | D | sum error = [ 5.2256, 5.4937, 5.7736, 6.0660, 6.3701] +24-11-19 20:24:31 | D | best error = [ 0.3673, 0.3673, 0.3673, 0.3673, 0.3673] +24-11-19 20:24:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:31 | D | sum error = [ 6.6884, 7.0193, 7.3623, 7.7213, 8.0938] +24-11-19 20:24:31 | D | best error = [ 0.3673, 0.3673, 0.3673, 0.3673, 0.3673] +24-11-19 20:24:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:31 | D | sum error = [ 8.4818, 8.8854, 9.3062, 9.7432, 10.1951] +24-11-19 20:24:31 | D | best error = [ 0.3673, 0.3673, 0.3673, 0.3673, 0.3673] +24-11-19 20:24:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:31 | D | sum error = [ 10.6664, 11.1525, 11.6594, 12.1855, 12.7269] +24-11-19 20:24:31 | D | best error = [ 0.3673, 0.3673, 0.3673, 0.3673, 0.3673] +24-11-19 20:24:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:31 | D | sum error = [ 13.2903, 13.8732, 14.4772, 15.1036, 15.7527] +24-11-19 20:24:31 | D | best error = [ 0.3673, 0.3673, 0.3673, 0.3673, 0.3673] +24-11-19 20:24:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:31 | D | sum error = [ 16.4243, 17.1166, 17.8330, 18.5728, 19.3372] +24-11-19 20:24:31 | D | best error = [ 0.3673, 0.3673, 0.3673, 0.3673, 0.3673] +24-11-19 20:24:31 | D | + error = [0.3673] +24-11-19 20:24:31 | D | - Calibrating model.layers.7.mlp.up_proj.weight +24-11-19 20:24:31 | D | + w: sint8 +24-11-19 20:24:31 | D | + x: None +24-11-19 20:24:31 | D | + y: None +24-11-19 20:24:31 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:31 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:31 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:31 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:31 | D | - range ratio = [ 1.0000] +24-11-19 20:24:31 | D | sum error = [ 4.6659] +24-11-19 20:24:31 | D | best error = [ 4.6659] +24-11-19 20:24:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:33 | D | sum error = [ 4.6409, 4.6287, 4.6488, 4.7027, 4.7907] +24-11-19 20:24:33 | D | best error = [ 4.3839, 4.2702, 4.2086, 4.1743, 4.1572] +24-11-19 20:24:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:33 | D | sum error = [ 4.9144, 5.0767, 5.2803, 5.5319, 5.8070] +24-11-19 20:24:33 | D | best error = [ 4.1484, 4.1450, 4.1438, 4.1435, 4.1434] +24-11-19 20:24:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:33 | D | sum error = [ 6.1501, 6.5394, 6.9590, 7.4257, 7.9270] +24-11-19 20:24:33 | D | best error = [ 4.1434, 4.1434, 4.1434, 4.1434, 4.1434] +24-11-19 20:24:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:33 | D | sum error = [ 8.4882, 9.0837, 9.7309, 10.4403, 11.1904] +24-11-19 20:24:33 | D | best error = [ 4.1434, 4.1434, 4.1434, 4.1434, 4.1434] +24-11-19 20:24:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:33 | D | sum error = [ 11.9936, 12.8413, 13.7437, 14.7060, 15.7193] +24-11-19 20:24:33 | D | best error = [ 4.1434, 4.1434, 4.1434, 4.1434, 4.1434] +24-11-19 20:24:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:33 | D | sum error = [ 16.8098, 17.9549, 19.1694, 20.4579, 21.8142] +24-11-19 20:24:33 | D | best error = [ 4.1434, 4.1434, 4.1434, 4.1434, 4.1434] +24-11-19 20:24:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:33 | D | sum error = [ 23.2598, 24.7710, 26.3566, 28.0513, 29.8227] +24-11-19 20:24:33 | D | best error = [ 4.1434, 4.1434, 4.1434, 4.1434, 4.1434] +24-11-19 20:24:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:33 | D | sum error = [ 31.6939, 33.6672, 35.7285, 37.8948, 40.1757] +24-11-19 20:24:33 | D | best error = [ 4.1434, 4.1434, 4.1434, 4.1434, 4.1434] +24-11-19 20:24:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:33 | D | sum error = [ 42.5690, 45.0945, 47.7306, 50.5201, 53.4214] +24-11-19 20:24:33 | D | best error = [ 4.1434, 4.1434, 4.1434, 4.1434, 4.1434] +24-11-19 20:24:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:33 | D | sum error = [ 56.4783, 59.6828, 63.0381, 66.5533, 70.2260] +24-11-19 20:24:33 | D | best error = [ 4.1434, 4.1434, 4.1434, 4.1434, 4.1434] +24-11-19 20:24:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:33 | D | sum error = [ 74.0737, 78.0889, 82.3025, 86.6830, 91.2682] +24-11-19 20:24:33 | D | best error = [ 4.1434, 4.1434, 4.1434, 4.1434, 4.1434] +24-11-19 20:24:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:33 | D | sum error = [ 96.0450, 101.0299, 106.2231, 111.6361, 117.2752] +24-11-19 20:24:33 | D | best error = [ 4.1434, 4.1434, 4.1434, 4.1434, 4.1434] +24-11-19 20:24:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:33 | D | sum error = [ 123.1391, 129.2431, 135.5734, 142.1647, 148.9988] +24-11-19 20:24:33 | D | best error = [ 4.1434, 4.1434, 4.1434, 4.1434, 4.1434] +24-11-19 20:24:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:33 | D | sum error = [ 156.0903, 163.4430, 171.0827, 178.9936, 187.1824] +24-11-19 20:24:33 | D | best error = [ 4.1434, 4.1434, 4.1434, 4.1434, 4.1434] +24-11-19 20:24:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:33 | D | sum error = [ 195.6601, 204.4319, 213.4920, 222.8597, 232.5254] +24-11-19 20:24:33 | D | best error = [ 4.1434, 4.1434, 4.1434, 4.1434, 4.1434] +24-11-19 20:24:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:33 | D | sum error = [ 242.4930, 252.7680, 263.3583, 274.2486, 285.4592] +24-11-19 20:24:33 | D | best error = [ 4.1434, 4.1434, 4.1434, 4.1434, 4.1434] +24-11-19 20:24:33 | D | + error = [4.1434] +24-11-19 20:24:33 | D | - Calibrating model.layers.7.mlp.gate_proj.weight +24-11-19 20:24:33 | D | + w: sint8 +24-11-19 20:24:33 | D | + x: None +24-11-19 20:24:33 | D | + y: None +24-11-19 20:24:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:33 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:33 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:33 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:33 | D | - range ratio = [ 1.0000] +24-11-19 20:24:33 | D | sum error = [ 6.0134] +24-11-19 20:24:33 | D | best error = [ 6.0134] +24-11-19 20:24:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:34 | D | sum error = [ 5.9721, 5.9572, 5.9815, 6.0587, 6.1474] +24-11-19 20:24:34 | D | best error = [ 5.6380, 5.4905, 5.4112, 5.3685, 5.3456] +24-11-19 20:24:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:34 | D | sum error = [ 6.3128, 6.5435, 6.7939, 7.1167, 7.4979] +24-11-19 20:24:34 | D | best error = [ 5.3351, 5.3305, 5.3295, 5.3291, 5.3291] +24-11-19 20:24:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:34 | D | sum error = [ 7.9409, 8.4336, 8.9926, 9.6053, 10.2924] +24-11-19 20:24:34 | D | best error = [ 5.3291, 5.3291, 5.3291, 5.3291, 5.3291] +24-11-19 20:24:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:34 | D | sum error = [ 11.0287, 11.8169, 12.6931, 13.6237, 14.6305] +24-11-19 20:24:34 | D | best error = [ 5.3291, 5.3291, 5.3291, 5.3291, 5.3291] +24-11-19 20:24:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:34 | D | sum error = [ 15.6925, 16.8489, 18.0866, 19.3968, 20.7884] +24-11-19 20:24:34 | D | best error = [ 5.3291, 5.3291, 5.3291, 5.3291, 5.3291] +24-11-19 20:24:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:34 | D | sum error = [ 22.2776, 23.8774, 25.5590, 27.3551, 29.2763] +24-11-19 20:24:34 | D | best error = [ 5.3291, 5.3291, 5.3291, 5.3291, 5.3291] +24-11-19 20:24:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:34 | D | sum error = [ 31.3047, 33.4660, 35.7557, 38.1829, 40.7695] +24-11-19 20:24:34 | D | best error = [ 5.3291, 5.3291, 5.3291, 5.3291, 5.3291] +24-11-19 20:24:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:34 | D | sum error = [ 43.5167, 46.4230, 49.4956, 52.7671, 56.2434] +24-11-19 20:24:34 | D | best error = [ 5.3291, 5.3291, 5.3291, 5.3291, 5.3291] +24-11-19 20:24:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:34 | D | sum error = [ 59.9273, 63.8430, 67.9818, 72.3714, 77.0266] +24-11-19 20:24:34 | D | best error = [ 5.3291, 5.3291, 5.3291, 5.3291, 5.3291] +24-11-19 20:24:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:34 | D | sum error = [ 81.9551, 87.1747, 92.6880, 98.5305, 104.7024] +24-11-19 20:24:34 | D | best error = [ 5.3291, 5.3291, 5.3291, 5.3291, 5.3291] +24-11-19 20:24:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:34 | D | sum error = [ 111.2074, 118.1060, 125.3705, 133.0598, 141.1491] +24-11-19 20:24:34 | D | best error = [ 5.3291, 5.3291, 5.3291, 5.3291, 5.3291] +24-11-19 20:24:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:34 | D | sum error = [ 149.6853, 158.6721, 168.1136, 178.0491, 188.5065] +24-11-19 20:24:34 | D | best error = [ 5.3291, 5.3291, 5.3291, 5.3291, 5.3291] +24-11-19 20:24:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:34 | D | sum error = [ 199.4833, 211.0104, 223.0976, 235.7580, 249.0269] +24-11-19 20:24:34 | D | best error = [ 5.3291, 5.3291, 5.3291, 5.3291, 5.3291] +24-11-19 20:24:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:34 | D | sum error = [ 262.8868, 277.3875, 292.5226, 308.3215, 324.7726] +24-11-19 20:24:34 | D | best error = [ 5.3291, 5.3291, 5.3291, 5.3291, 5.3291] +24-11-19 20:24:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:34 | D | sum error = [ 341.8853, 359.7113, 378.2345, 397.4434, 417.3517] +24-11-19 20:24:34 | D | best error = [ 5.3291, 5.3291, 5.3291, 5.3291, 5.3291] +24-11-19 20:24:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:34 | D | sum error = [ 438.0065, 459.3576, 481.4591, 504.2443, 527.7231] +24-11-19 20:24:34 | D | best error = [ 5.3291, 5.3291, 5.3291, 5.3291, 5.3291] +24-11-19 20:24:34 | D | + error = [5.3291] +24-11-19 20:24:34 | D | - Calibrating model.layers.7.mlp.down_proj.weight +24-11-19 20:24:34 | D | + w: sint8 +24-11-19 20:24:34 | D | + x: None +24-11-19 20:24:34 | D | + y: None +24-11-19 20:24:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:24:34 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:24:34 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:24:35 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:24:35 | D | - range ratio = [ 1.0000] +24-11-19 20:24:35 | D | sum error = [ 0.5477] +24-11-19 20:24:35 | D | best error = [ 0.5477] +24-11-19 20:24:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:24:36 | D | sum error = [ 0.5423, 0.5389, 0.5358, 0.5344, 0.5340] +24-11-19 20:24:36 | D | best error = [ 0.5264, 0.5161, 0.5092, 0.5042, 0.5002] +24-11-19 20:24:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:24:36 | D | sum error = [ 0.5346, 0.5375, 0.5441, 0.5521, 0.5620] +24-11-19 20:24:36 | D | best error = [ 0.4972, 0.4948, 0.4932, 0.4921, 0.4912] +24-11-19 20:24:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:24:36 | D | sum error = [ 0.5759, 0.5915, 0.6106, 0.6344, 0.6613] +24-11-19 20:24:36 | D | best error = [ 0.4907, 0.4903, 0.4900, 0.4898, 0.4897] +24-11-19 20:24:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:24:36 | D | sum error = [ 0.6919, 0.7247, 0.7637, 0.8063, 0.8534] +24-11-19 20:24:36 | D | best error = [ 0.4895, 0.4895, 0.4895, 0.4894, 0.4894] +24-11-19 20:24:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:24:36 | D | sum error = [ 0.9053, 0.9627, 1.0258, 1.0910, 1.1641] +24-11-19 20:24:36 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 20:24:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:24:36 | D | sum error = [ 1.2417, 1.3266, 1.4166, 1.5129, 1.6178] +24-11-19 20:24:36 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 20:24:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:24:36 | D | sum error = [ 1.7284, 1.8457, 1.9722, 2.1070, 2.2487] +24-11-19 20:24:36 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 20:24:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:24:36 | D | sum error = [ 2.4004, 2.5623, 2.7321, 2.9128, 3.1033] +24-11-19 20:24:36 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 20:24:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:24:36 | D | sum error = [ 3.3057, 3.5204, 3.7455, 3.9848, 4.2380] +24-11-19 20:24:36 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 20:24:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:24:36 | D | sum error = [ 4.5050, 4.7862, 5.0835, 5.3965, 5.7256] +24-11-19 20:24:36 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 20:24:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:24:36 | D | sum error = [ 6.0719, 6.4365, 6.8195, 7.2215, 7.6437] +24-11-19 20:24:36 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 20:24:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:24:36 | D | sum error = [ 8.0862, 8.5508, 9.0363, 9.5446, 10.0759] +24-11-19 20:24:36 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 20:24:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:24:36 | D | sum error = [ 10.6315, 11.2130, 11.8192, 12.4528, 13.1133] +24-11-19 20:24:36 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 20:24:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:24:36 | D | sum error = [ 13.8020, 14.5198, 15.2667, 16.0440, 16.8506] +24-11-19 20:24:36 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 20:24:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:24:36 | D | sum error = [ 17.6896, 18.5601, 19.4638, 20.4015, 21.3726] +24-11-19 20:24:36 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 20:24:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:24:36 | D | sum error = [ 22.3788, 23.4199, 24.4958, 25.6091, 26.7576] +24-11-19 20:24:36 | D | best error = [ 0.4894, 0.4894, 0.4894, 0.4894, 0.4894] +24-11-19 20:24:36 | D | + error = [0.4894] +24-11-19 20:24:36 | D | - Quantizing model.layers.7.self_attn.q_proj.weight +24-11-19 20:24:37 | D | - Quantizing model.layers.7.self_attn.k_proj.weight +24-11-19 20:24:38 | D | - Quantizing model.layers.7.self_attn.v_proj.weight +24-11-19 20:24:39 | D | - Quantizing model.layers.7.self_attn.o_proj.weight +24-11-19 20:24:41 | D | - Quantizing model.layers.7.mlp.up_proj.weight +24-11-19 20:24:45 | D | - Quantizing model.layers.7.mlp.gate_proj.weight +24-11-19 20:24:46 | D | - Quantizing model.layers.7.mlp.down_proj.weight +24-11-19 20:24:58 | D | - Quantizing layer model.layers.8 +24-11-19 20:24:58 | D | - Calibrating model.layers.8.self_attn.q_proj.weight +24-11-19 20:24:58 | D | + w: sint8 +24-11-19 20:24:58 | D | + x: None +24-11-19 20:24:58 | D | + y: None +24-11-19 20:24:58 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:24:58 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:24:58 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:24:59 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:24:59 | D | - range ratio = [ 1.0000] +24-11-19 20:24:59 | D | sum error = [ 3.4949] +24-11-19 20:24:59 | D | best error = [ 3.4949] +24-11-19 20:25:11 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:11 | D | sum error = [ 3.5648, 3.4498, 3.6794, 3.4386, 3.5676] +24-11-19 20:25:11 | D | best error = [ 3.4949, 3.4498, 3.4498, 3.4386, 3.4386] +24-11-19 20:25:11 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:11 | D | sum error = [ 3.5862, 3.7656, 4.0176, 4.2750, 4.4102] +24-11-19 20:25:11 | D | best error = [ 3.4386, 3.4386, 3.4386, 3.4386, 3.4386] +24-11-19 20:25:11 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:11 | D | sum error = [ 4.6872, 4.9264, 5.3431, 5.6612, 6.0051] +24-11-19 20:25:11 | D | best error = [ 3.4386, 3.4386, 3.4386, 3.4386, 3.4386] +24-11-19 20:25:11 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:11 | D | sum error = [ 6.4707, 6.9637, 7.6313, 8.1343, 8.7557] +24-11-19 20:25:11 | D | best error = [ 3.4386, 3.4386, 3.4386, 3.4386, 3.4386] +24-11-19 20:25:11 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:11 | D | sum error = [ 9.3574, 10.2539, 11.0172, 11.9205, 12.8341] +24-11-19 20:25:11 | D | best error = [ 3.4386, 3.4386, 3.4386, 3.4386, 3.4386] +24-11-19 20:25:11 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:11 | D | sum error = [ 13.9148, 14.9255, 16.1901, 17.6079, 19.0520] +24-11-19 20:25:11 | D | best error = [ 3.4386, 3.4386, 3.4386, 3.4386, 3.4386] +24-11-19 20:25:11 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:11 | D | sum error = [ 20.4617, 22.2015, 24.0837, 26.0501, 28.3671] +24-11-19 20:25:11 | D | best error = [ 3.4386, 3.4386, 3.4386, 3.4386, 3.4386] +24-11-19 20:25:11 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:11 | D | sum error = [ 30.5682, 33.0285, 35.7752, 38.6255, 41.6538] +24-11-19 20:25:11 | D | best error = [ 3.4386, 3.4386, 3.4386, 3.4386, 3.4386] +24-11-19 20:25:11 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:11 | D | sum error = [ 44.8748, 48.2770, 51.9522, 55.9124, 60.1235] +24-11-19 20:25:11 | D | best error = [ 3.4386, 3.4386, 3.4386, 3.4386, 3.4386] +24-11-19 20:25:11 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:11 | D | sum error = [ 64.6802, 69.3214, 74.3018, 79.6456, 85.0100] +24-11-19 20:25:11 | D | best error = [ 3.4386, 3.4386, 3.4386, 3.4386, 3.4386] +24-11-19 20:25:11 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:11 | D | sum error = [ 91.1940, 97.3321, 103.9117, 111.0471, 118.5536] +24-11-19 20:25:11 | D | best error = [ 3.4386, 3.4386, 3.4386, 3.4386, 3.4386] +24-11-19 20:25:11 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:11 | D | sum error = [ 126.4979, 134.8541, 143.7454, 153.0016, 162.7618] +24-11-19 20:25:11 | D | best error = [ 3.4386, 3.4386, 3.4386, 3.4386, 3.4386] +24-11-19 20:25:11 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:11 | D | sum error = [ 173.3109, 184.2503, 195.6561, 207.9269, 220.5621] +24-11-19 20:25:11 | D | best error = [ 3.4386, 3.4386, 3.4386, 3.4386, 3.4386] +24-11-19 20:25:11 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:11 | D | sum error = [ 233.7722, 247.7699, 262.0952, 276.9820, 292.5351] +24-11-19 20:25:11 | D | best error = [ 3.4386, 3.4386, 3.4386, 3.4386, 3.4386] +24-11-19 20:25:11 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:11 | D | sum error = [ 308.4797, 324.9828, 341.9626, 359.2699, 377.2179] +24-11-19 20:25:11 | D | best error = [ 3.4386, 3.4386, 3.4386, 3.4386, 3.4386] +24-11-19 20:25:11 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:11 | D | sum error = [ 395.3758, 413.9948, 432.5310, 451.2388, 470.2464] +24-11-19 20:25:11 | D | best error = [ 3.4386, 3.4386, 3.4386, 3.4386, 3.4386] +24-11-19 20:25:11 | D | + error = [3.4386] +24-11-19 20:25:11 | D | - Calibrating model.layers.8.self_attn.k_proj.weight +24-11-19 20:25:11 | D | + w: sint8 +24-11-19 20:25:11 | D | + x: None +24-11-19 20:25:11 | D | + y: None +24-11-19 20:25:11 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:25:11 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:11 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:12 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:12 | D | - range ratio = [ 1.0000] +24-11-19 20:25:12 | D | sum error = [ 2.8944] +24-11-19 20:25:12 | D | best error = [ 2.8944] +24-11-19 20:25:24 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:24 | D | sum error = [ 3.3795, 3.0248, 2.8039, 2.9498, 3.0857] +24-11-19 20:25:24 | D | best error = [ 2.8944, 2.8944, 2.8039, 2.8039, 2.8039] +24-11-19 20:25:24 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:24 | D | sum error = [ 3.2680, 3.4451, 3.1909, 3.5747, 3.5544] +24-11-19 20:25:24 | D | best error = [ 2.8039, 2.8039, 2.8039, 2.8039, 2.8039] +24-11-19 20:25:24 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:24 | D | sum error = [ 4.1047, 4.3479, 4.5460, 4.9063, 5.2863] +24-11-19 20:25:24 | D | best error = [ 2.8039, 2.8039, 2.8039, 2.8039, 2.8039] +24-11-19 20:25:24 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:24 | D | sum error = [ 5.6947, 6.1330, 6.2423, 6.9685, 7.5435] +24-11-19 20:25:24 | D | best error = [ 2.8039, 2.8039, 2.8039, 2.8039, 2.8039] +24-11-19 20:25:24 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:24 | D | sum error = [ 8.0766, 8.7102, 9.8000, 10.4731, 11.2888] +24-11-19 20:25:24 | D | best error = [ 2.8039, 2.8039, 2.8039, 2.8039, 2.8039] +24-11-19 20:25:24 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:24 | D | sum error = [ 11.9342, 12.8867, 13.9905, 15.3970, 16.2953] +24-11-19 20:25:24 | D | best error = [ 2.8039, 2.8039, 2.8039, 2.8039, 2.8039] +24-11-19 20:25:24 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:24 | D | sum error = [ 17.4773, 19.1364, 20.2314, 22.4302, 24.2946] +24-11-19 20:25:24 | D | best error = [ 2.8039, 2.8039, 2.8039, 2.8039, 2.8039] +24-11-19 20:25:24 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:24 | D | sum error = [ 26.3645, 28.6044, 30.8935, 33.3744, 36.3975] +24-11-19 20:25:24 | D | best error = [ 2.8039, 2.8039, 2.8039, 2.8039, 2.8039] +24-11-19 20:25:24 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:24 | D | sum error = [ 39.4439, 42.5733, 46.7422, 50.1820, 54.2366] +24-11-19 20:25:24 | D | best error = [ 2.8039, 2.8039, 2.8039, 2.8039, 2.8039] +24-11-19 20:25:24 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:24 | D | sum error = [ 58.7586, 63.7379, 68.9726, 74.3697, 80.0866] +24-11-19 20:25:24 | D | best error = [ 2.8039, 2.8039, 2.8039, 2.8039, 2.8039] +24-11-19 20:25:24 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:24 | D | sum error = [ 86.6983, 93.4975, 100.2335, 107.4020, 114.9584] +24-11-19 20:25:24 | D | best error = [ 2.8039, 2.8039, 2.8039, 2.8039, 2.8039] +24-11-19 20:25:24 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:24 | D | sum error = [ 123.0465, 132.0156, 141.0361, 150.5646, 160.6386] +24-11-19 20:25:24 | D | best error = [ 2.8039, 2.8039, 2.8039, 2.8039, 2.8039] +24-11-19 20:25:24 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:24 | D | sum error = [ 171.3913, 182.5349, 194.3939, 206.3358, 219.5159] +24-11-19 20:25:24 | D | best error = [ 2.8039, 2.8039, 2.8039, 2.8039, 2.8039] +24-11-19 20:25:24 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:24 | D | sum error = [ 232.8426, 246.6829, 261.3783, 276.3997, 292.1193] +24-11-19 20:25:24 | D | best error = [ 2.8039, 2.8039, 2.8039, 2.8039, 2.8039] +24-11-19 20:25:24 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:24 | D | sum error = [ 308.1392, 324.5487, 341.3593, 358.4958, 376.1365] +24-11-19 20:25:24 | D | best error = [ 2.8039, 2.8039, 2.8039, 2.8039, 2.8039] +24-11-19 20:25:24 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:24 | D | sum error = [ 393.8516, 412.2838, 430.7279, 449.3647, 468.2604] +24-11-19 20:25:24 | D | best error = [ 2.8039, 2.8039, 2.8039, 2.8039, 2.8039] +24-11-19 20:25:24 | D | + error = [2.8039] +24-11-19 20:25:24 | D | - Calibrating model.layers.8.self_attn.v_proj.weight +24-11-19 20:25:24 | D | + w: sint8 +24-11-19 20:25:24 | D | + x: None +24-11-19 20:25:24 | D | + y: None +24-11-19 20:25:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:24 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:24 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:24 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:24 | D | - range ratio = [ 1.0000] +24-11-19 20:25:24 | D | sum error = [ 1.2607] +24-11-19 20:25:24 | D | best error = [ 1.2607] +24-11-19 20:25:24 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:24 | D | sum error = [ 1.2595, 1.2429, 1.2569, 1.2738, 1.2947] +24-11-19 20:25:24 | D | best error = [ 1.1818, 1.1479, 1.1322, 1.1225, 1.1171] +24-11-19 20:25:24 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:24 | D | sum error = [ 1.3299, 1.3729, 1.4204, 1.4853, 1.5743] +24-11-19 20:25:24 | D | best error = [ 1.1152, 1.1138, 1.1134, 1.1134, 1.1134] +24-11-19 20:25:24 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:24 | D | sum error = [ 1.6739, 1.7801, 1.8900, 2.0186, 2.1589] +24-11-19 20:25:24 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 20:25:24 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:24 | D | sum error = [ 2.3205, 2.4873, 2.6690, 2.8542, 3.0665] +24-11-19 20:25:24 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 20:25:24 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:24 | D | sum error = [ 3.2911, 3.5228, 3.7752, 4.0314, 4.3186] +24-11-19 20:25:24 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 20:25:24 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:24 | D | sum error = [ 4.6192, 4.9185, 5.2776, 5.6323, 6.0147] +24-11-19 20:25:24 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 20:25:24 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:24 | D | sum error = [ 6.4038, 6.8142, 7.2585, 7.7246, 8.2197] +24-11-19 20:25:24 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 20:25:24 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:24 | D | sum error = [ 8.7292, 9.2843, 9.8474, 10.4481, 11.1000] +24-11-19 20:25:24 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 20:25:24 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:24 | D | sum error = [ 11.7585, 12.4682, 13.1997, 13.9764, 14.7856] +24-11-19 20:25:24 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 20:25:24 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:24 | D | sum error = [ 15.6336, 16.5240, 17.4428, 18.4144, 19.4271] +24-11-19 20:25:24 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 20:25:24 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:24 | D | sum error = [ 20.4903, 21.5897, 22.7625, 23.9678, 25.2323] +24-11-19 20:25:24 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 20:25:24 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:24 | D | sum error = [ 26.5500, 27.9250, 29.3590, 30.8572, 32.4195] +24-11-19 20:25:24 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 20:25:24 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:24 | D | sum error = [ 34.0432, 35.7378, 37.4992, 39.3451, 41.2519] +24-11-19 20:25:24 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 20:25:24 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:24 | D | sum error = [ 43.2339, 45.3027, 47.4333, 49.6525, 51.9437] +24-11-19 20:25:24 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 20:25:24 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:24 | D | sum error = [ 54.3174, 56.7628, 59.2938, 61.9127, 64.6102] +24-11-19 20:25:24 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 20:25:24 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:24 | D | sum error = [ 67.4022, 70.2786, 73.2408, 76.2899, 79.4223] +24-11-19 20:25:24 | D | best error = [ 1.1134, 1.1134, 1.1134, 1.1134, 1.1134] +24-11-19 20:25:24 | D | + error = [1.1134] +24-11-19 20:25:24 | D | - Calibrating model.layers.8.self_attn.o_proj.weight +24-11-19 20:25:24 | D | + w: sint8 +24-11-19 20:25:24 | D | + x: None +24-11-19 20:25:24 | D | + y: None +24-11-19 20:25:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:24 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:24 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:25 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:25 | D | - range ratio = [ 1.0000] +24-11-19 20:25:25 | D | sum error = [ 0.5011] +24-11-19 20:25:25 | D | best error = [ 0.5011] +24-11-19 20:25:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:25 | D | sum error = [ 0.4978, 0.4973, 0.4995, 0.5023, 0.5113] +24-11-19 20:25:25 | D | best error = [ 0.4565, 0.4378, 0.4271, 0.4201, 0.4153] +24-11-19 20:25:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:25 | D | sum error = [ 0.5200, 0.5386, 0.5551, 0.5763, 0.6056] +24-11-19 20:25:25 | D | best error = [ 0.4121, 0.4103, 0.4091, 0.4084, 0.4080] +24-11-19 20:25:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:25 | D | sum error = [ 0.6366, 0.6693, 0.7043, 0.7465, 0.7907] +24-11-19 20:25:25 | D | best error = [ 0.4078, 0.4076, 0.4075, 0.4074, 0.4074] +24-11-19 20:25:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:25 | D | sum error = [ 0.8441, 0.8940, 0.9509, 1.0105, 1.0713] +24-11-19 20:25:25 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:25:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:25 | D | sum error = [ 1.1387, 1.2091, 1.2862, 1.3629, 1.4493] +24-11-19 20:25:25 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:25:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:25 | D | sum error = [ 1.5360, 1.6305, 1.7280, 1.8292, 1.9358] +24-11-19 20:25:25 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:25:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:25 | D | sum error = [ 2.0505, 2.1688, 2.2936, 2.4234, 2.5599] +24-11-19 20:25:25 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:25:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:25 | D | sum error = [ 2.7056, 2.8531, 3.0122, 3.1732, 3.3434] +24-11-19 20:25:25 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:25:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:25 | D | sum error = [ 3.5231, 3.7089, 3.9016, 4.1035, 4.3112] +24-11-19 20:25:25 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:25:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:25 | D | sum error = [ 4.5285, 4.7525, 4.9862, 5.2308, 5.4851] +24-11-19 20:25:25 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:25:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:25 | D | sum error = [ 5.7465, 6.0191, 6.3022, 6.5972, 6.8991] +24-11-19 20:25:25 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:25:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:25 | D | sum error = [ 7.2118, 7.5399, 7.8771, 8.2243, 8.5842] +24-11-19 20:25:25 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:25:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:25 | D | sum error = [ 8.9548, 9.3374, 9.7324, 10.1420, 10.5612] +24-11-19 20:25:25 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:25:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:25 | D | sum error = [ 10.9930, 11.4373, 11.8935, 12.3648, 12.8462] +24-11-19 20:25:25 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:25:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:25 | D | sum error = [ 13.3418, 13.8500, 14.3738, 14.9121, 15.4681] +24-11-19 20:25:25 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:25:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:25 | D | sum error = [ 16.0411, 16.6306, 17.2376, 17.8618, 18.5052] +24-11-19 20:25:25 | D | best error = [ 0.4073, 0.4073, 0.4073, 0.4073, 0.4073] +24-11-19 20:25:25 | D | + error = [0.4073] +24-11-19 20:25:25 | D | - Calibrating model.layers.8.mlp.up_proj.weight +24-11-19 20:25:25 | D | + w: sint8 +24-11-19 20:25:25 | D | + x: None +24-11-19 20:25:25 | D | + y: None +24-11-19 20:25:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:25 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:25 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:25 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:25 | D | - range ratio = [ 1.0000] +24-11-19 20:25:25 | D | sum error = [ 4.7245] +24-11-19 20:25:25 | D | best error = [ 4.7245] +24-11-19 20:25:27 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:27 | D | sum error = [ 4.6829, 4.6834, 4.6900, 4.7488, 4.8350] +24-11-19 20:25:27 | D | best error = [ 4.4206, 4.3042, 4.2399, 4.2054, 4.1862] +24-11-19 20:25:27 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:27 | D | sum error = [ 4.9589, 5.1386, 5.3332, 5.5918, 5.8828] +24-11-19 20:25:27 | D | best error = [ 4.1772, 4.1735, 4.1722, 4.1718, 4.1718] +24-11-19 20:25:27 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:27 | D | sum error = [ 6.2150, 6.6079, 7.0392, 7.5052, 8.0221] +24-11-19 20:25:27 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:25:27 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:27 | D | sum error = [ 8.5912, 9.2105, 9.8582, 10.5697, 11.3240] +24-11-19 20:25:27 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:25:27 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:27 | D | sum error = [ 12.1384, 12.9842, 13.9022, 14.8785, 15.9156] +24-11-19 20:25:27 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:25:27 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:27 | D | sum error = [ 17.0044, 18.1636, 19.3983, 20.6972, 22.0697] +24-11-19 20:25:27 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:25:27 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:27 | D | sum error = [ 23.5188, 25.0558, 26.6594, 28.3695, 30.1572] +24-11-19 20:25:27 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:25:27 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:27 | D | sum error = [ 32.0381, 34.0269, 36.1227, 38.3207, 40.6332] +24-11-19 20:25:27 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:25:27 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:27 | D | sum error = [ 43.0629, 45.6114, 48.2901, 51.0959, 54.0434] +24-11-19 20:25:27 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:25:27 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:27 | D | sum error = [ 57.1202, 60.3407, 63.7241, 67.2589, 70.9496] +24-11-19 20:25:27 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:25:27 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:27 | D | sum error = [ 74.8220, 78.8663, 83.0934, 87.5118, 92.1221] +24-11-19 20:25:27 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:25:27 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:27 | D | sum error = [ 96.9353, 101.9601, 107.1869, 112.6398, 118.3246] +24-11-19 20:25:27 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:25:27 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:27 | D | sum error = [ 124.2251, 130.3563, 136.7398, 143.3698, 150.2435] +24-11-19 20:25:27 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:25:27 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:27 | D | sum error = [ 157.3709, 164.7533, 172.4182, 180.3563, 188.5578] +24-11-19 20:25:27 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:25:27 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:27 | D | sum error = [ 197.0462, 205.8186, 214.8837, 224.2412, 233.8956] +24-11-19 20:25:27 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:25:27 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:27 | D | sum error = [ 243.8618, 254.1356, 264.7231, 275.6240, 286.8425] +24-11-19 20:25:27 | D | best error = [ 4.1717, 4.1717, 4.1717, 4.1717, 4.1717] +24-11-19 20:25:27 | D | + error = [4.1717] +24-11-19 20:25:27 | D | - Calibrating model.layers.8.mlp.gate_proj.weight +24-11-19 20:25:27 | D | + w: sint8 +24-11-19 20:25:27 | D | + x: None +24-11-19 20:25:27 | D | + y: None +24-11-19 20:25:27 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:27 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:27 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:27 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:27 | D | - range ratio = [ 1.0000] +24-11-19 20:25:27 | D | sum error = [ 6.1287] +24-11-19 20:25:27 | D | best error = [ 6.1287] +24-11-19 20:25:28 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:28 | D | sum error = [ 6.0863, 6.0776, 6.1026, 6.1629, 6.2801] +24-11-19 20:25:28 | D | best error = [ 5.7423, 5.5912, 5.5096, 5.4646, 5.4407] +24-11-19 20:25:28 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:28 | D | sum error = [ 6.4480, 6.6752, 6.9502, 7.2787, 7.6642] +24-11-19 20:25:28 | D | best error = [ 5.4298, 5.4251, 5.4237, 5.4233, 5.4231] +24-11-19 20:25:28 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:28 | D | sum error = [ 8.1257, 8.6346, 9.2141, 9.8369, 10.5509] +24-11-19 20:25:28 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:25:28 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:28 | D | sum error = [ 11.3023, 12.1307, 13.0150, 13.9840, 15.0099] +24-11-19 20:25:28 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:25:28 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:28 | D | sum error = [ 16.1110, 17.2968, 18.5567, 19.8995, 21.3593] +24-11-19 20:25:28 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:25:28 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:28 | D | sum error = [ 22.8983, 24.5247, 26.2570, 28.1087, 30.0797] +24-11-19 20:25:28 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:25:28 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:28 | D | sum error = [ 32.1601, 34.3814, 36.7389, 39.2417, 41.8945] +24-11-19 20:25:28 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:25:28 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:28 | D | sum error = [ 44.7356, 47.7094, 50.9050, 54.2679, 57.8386] +24-11-19 20:25:28 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:25:28 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:28 | D | sum error = [ 61.6321, 65.6638, 69.9365, 74.4646, 79.2605] +24-11-19 20:25:28 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:25:28 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:28 | D | sum error = [ 84.3339, 89.7298, 95.4241, 101.4543, 107.8248] +24-11-19 20:25:28 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:25:28 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:28 | D | sum error = [ 114.5822, 121.6872, 129.2166, 137.1727, 145.5384] +24-11-19 20:25:28 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:25:28 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:28 | D | sum error = [ 154.3851, 163.6851, 173.4810, 183.7898, 194.6330] +24-11-19 20:25:28 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:25:28 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:28 | D | sum error = [ 206.0178, 217.9719, 230.5141, 243.6448, 257.3912] +24-11-19 20:25:28 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:25:28 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:28 | D | sum error = [ 271.7687, 286.7960, 302.4770, 318.8340, 335.8948] +24-11-19 20:25:28 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:25:28 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:28 | D | sum error = [ 353.6708, 372.1432, 391.3246, 411.2437, 431.8477] +24-11-19 20:25:28 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:25:28 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:28 | D | sum error = [ 453.2062, 475.2801, 498.1072, 521.6463, 545.9183] +24-11-19 20:25:28 | D | best error = [ 5.4231, 5.4231, 5.4231, 5.4231, 5.4231] +24-11-19 20:25:28 | D | + error = [5.4231] +24-11-19 20:25:28 | D | - Calibrating model.layers.8.mlp.down_proj.weight +24-11-19 20:25:28 | D | + w: sint8 +24-11-19 20:25:28 | D | + x: None +24-11-19 20:25:28 | D | + y: None +24-11-19 20:25:28 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:25:28 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:25:28 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:25:28 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:25:29 | D | - range ratio = [ 1.0000] +24-11-19 20:25:29 | D | sum error = [ 0.5645] +24-11-19 20:25:29 | D | best error = [ 0.5645] +24-11-19 20:25:30 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:25:30 | D | sum error = [ 0.5582, 0.5556, 0.5521, 0.5519, 0.5525] +24-11-19 20:25:30 | D | best error = [ 0.5423, 0.5320, 0.5247, 0.5195, 0.5154] +24-11-19 20:25:30 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:25:30 | D | sum error = [ 0.5541, 0.5590, 0.5673, 0.5761, 0.5903] +24-11-19 20:25:30 | D | best error = [ 0.5126, 0.5103, 0.5087, 0.5074, 0.5066] +24-11-19 20:25:30 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:25:30 | D | sum error = [ 0.6063, 0.6261, 0.6493, 0.6756, 0.7062] +24-11-19 20:25:30 | D | best error = [ 0.5061, 0.5056, 0.5054, 0.5052, 0.5050] +24-11-19 20:25:30 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:25:30 | D | sum error = [ 0.7415, 0.7806, 0.8257, 0.8750, 0.9274] +24-11-19 20:25:30 | D | best error = [ 0.5050, 0.5049, 0.5049, 0.5049, 0.5049] +24-11-19 20:25:30 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:25:30 | D | sum error = [ 0.9858, 1.0477, 1.1167, 1.1918, 1.2707] +24-11-19 20:25:30 | D | best error = [ 0.5049, 0.5049, 0.5048, 0.5048, 0.5048] +24-11-19 20:25:30 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:25:30 | D | sum error = [ 1.3547, 1.4466, 1.5439, 1.6491, 1.7596] +24-11-19 20:25:30 | D | best error = [ 0.5048, 0.5048, 0.5048, 0.5048, 0.5048] +24-11-19 20:25:30 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:25:30 | D | sum error = [ 1.8791, 2.0057, 2.1387, 2.2819, 2.4334] +24-11-19 20:25:30 | D | best error = [ 0.5048, 0.5048, 0.5048, 0.5048, 0.5048] +24-11-19 20:25:30 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:25:30 | D | sum error = [ 2.5939, 2.7652, 2.9457, 3.1363, 3.3385] +24-11-19 20:25:30 | D | best error = [ 0.5048, 0.5048, 0.5048, 0.5048, 0.5048] +24-11-19 20:25:30 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:25:30 | D | sum error = [ 3.5517, 3.7771, 4.0157, 4.2668, 4.5323] +24-11-19 20:25:30 | D | best error = [ 0.5048, 0.5048, 0.5048, 0.5048, 0.5048] +24-11-19 20:25:30 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:25:30 | D | sum error = [ 4.8129, 5.1069, 5.4166, 5.7437, 6.0873] +24-11-19 20:25:30 | D | best error = [ 0.5048, 0.5048, 0.5048, 0.5048, 0.5048] +24-11-19 20:25:30 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:25:30 | D | sum error = [ 6.4497, 6.8289, 7.2273, 7.6472, 8.0865] +24-11-19 20:25:30 | D | best error = [ 0.5048, 0.5048, 0.5048, 0.5048, 0.5048] +24-11-19 20:25:30 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:25:30 | D | sum error = [ 8.5465, 9.0300, 9.5349, 10.0630, 10.6154] +24-11-19 20:25:30 | D | best error = [ 0.5048, 0.5048, 0.5048, 0.5048, 0.5048] +24-11-19 20:25:30 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:25:30 | D | sum error = [ 11.1935, 11.7978, 12.4282, 13.0855, 13.7708] +24-11-19 20:25:30 | D | best error = [ 0.5048, 0.5048, 0.5048, 0.5048, 0.5048] +24-11-19 20:25:30 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:25:30 | D | sum error = [ 14.4851, 15.2288, 16.0028, 16.8074, 17.6434] +24-11-19 20:25:30 | D | best error = [ 0.5048, 0.5048, 0.5048, 0.5048, 0.5048] +24-11-19 20:25:30 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:25:30 | D | sum error = [ 18.5135, 19.4163, 20.3537, 21.3261, 22.3339] +24-11-19 20:25:30 | D | best error = [ 0.5048, 0.5048, 0.5048, 0.5048, 0.5048] +24-11-19 20:25:30 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:25:30 | D | sum error = [ 23.3778, 24.4575, 25.5748, 26.7282, 27.9192] +24-11-19 20:25:30 | D | best error = [ 0.5048, 0.5048, 0.5048, 0.5048, 0.5048] +24-11-19 20:25:30 | D | + error = [0.5048] +24-11-19 20:25:30 | D | - Quantizing model.layers.8.self_attn.q_proj.weight +24-11-19 20:25:31 | D | - Quantizing model.layers.8.self_attn.k_proj.weight +24-11-19 20:25:32 | D | - Quantizing model.layers.8.self_attn.v_proj.weight +24-11-19 20:25:33 | D | - Quantizing model.layers.8.self_attn.o_proj.weight +24-11-19 20:25:34 | D | - Quantizing model.layers.8.mlp.up_proj.weight +24-11-19 20:25:35 | D | - Quantizing model.layers.8.mlp.gate_proj.weight +24-11-19 20:25:38 | D | - Quantizing model.layers.8.mlp.down_proj.weight +24-11-19 20:25:52 | D | - Quantizing layer model.layers.9 +24-11-19 20:25:52 | D | - Calibrating model.layers.9.self_attn.q_proj.weight +24-11-19 20:25:52 | D | + w: sint8 +24-11-19 20:25:52 | D | + x: None +24-11-19 20:25:52 | D | + y: None +24-11-19 20:25:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:25:52 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:25:52 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:25:52 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:25:53 | D | - range ratio = [ 1.0000] +24-11-19 20:25:53 | D | sum error = [ 3.9111] +24-11-19 20:25:53 | D | best error = [ 3.9111] +24-11-19 20:26:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:07 | D | sum error = [ 3.8448, 3.9324, 3.8488, 3.8764, 3.9358] +24-11-19 20:26:07 | D | best error = [ 3.8448, 3.8448, 3.8448, 3.8448, 3.8448] +24-11-19 20:26:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:07 | D | sum error = [ 4.0572, 4.2354, 4.4191, 4.6673, 4.9802] +24-11-19 20:26:07 | D | best error = [ 3.8448, 3.8448, 3.8448, 3.8448, 3.8448] +24-11-19 20:26:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:07 | D | sum error = [ 5.2928, 5.4809, 6.0696, 6.5277, 7.0737] +24-11-19 20:26:07 | D | best error = [ 3.8448, 3.8448, 3.8448, 3.8448, 3.8448] +24-11-19 20:26:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:07 | D | sum error = [ 7.6860, 8.1288, 8.7794, 9.4971, 10.2342] +24-11-19 20:26:07 | D | best error = [ 3.8448, 3.8448, 3.8448, 3.8448, 3.8448] +24-11-19 20:26:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:07 | D | sum error = [ 11.3328, 11.9829, 13.0749, 14.0529, 15.9063] +24-11-19 20:26:07 | D | best error = [ 3.8448, 3.8448, 3.8448, 3.8448, 3.8448] +24-11-19 20:26:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:07 | D | sum error = [ 16.7910, 18.2148, 19.8748, 21.5093, 23.2456] +24-11-19 20:26:07 | D | best error = [ 3.8448, 3.8448, 3.8448, 3.8448, 3.8448] +24-11-19 20:26:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:07 | D | sum error = [ 25.2730, 27.1414, 29.3262, 31.5753, 34.1398] +24-11-19 20:26:07 | D | best error = [ 3.8448, 3.8448, 3.8448, 3.8448, 3.8448] +24-11-19 20:26:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:07 | D | sum error = [ 36.9463, 40.1076, 43.3158, 46.5682, 50.4439] +24-11-19 20:26:07 | D | best error = [ 3.8448, 3.8448, 3.8448, 3.8448, 3.8448] +24-11-19 20:26:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:07 | D | sum error = [ 54.2067, 58.5364, 62.9478, 67.6886, 72.7883] +24-11-19 20:26:07 | D | best error = [ 3.8448, 3.8448, 3.8448, 3.8448, 3.8448] +24-11-19 20:26:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:07 | D | sum error = [ 78.4294, 84.3636, 90.6834, 97.4879, 104.6102] +24-11-19 20:26:07 | D | best error = [ 3.8448, 3.8448, 3.8448, 3.8448, 3.8448] +24-11-19 20:26:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:07 | D | sum error = [ 112.3621, 120.4127, 129.0832, 138.3351, 148.1447] +24-11-19 20:26:07 | D | best error = [ 3.8448, 3.8448, 3.8448, 3.8448, 3.8448] +24-11-19 20:26:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:07 | D | sum error = [ 158.6363, 169.5025, 180.8572, 192.8263, 205.1350] +24-11-19 20:26:07 | D | best error = [ 3.8448, 3.8448, 3.8448, 3.8448, 3.8448] +24-11-19 20:26:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:07 | D | sum error = [ 218.6471, 232.1220, 246.4173, 261.4902, 276.8393] +24-11-19 20:26:07 | D | best error = [ 3.8448, 3.8448, 3.8448, 3.8448, 3.8448] +24-11-19 20:26:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:07 | D | sum error = [ 293.3177, 310.2542, 327.6864, 345.9418, 364.6576] +24-11-19 20:26:07 | D | best error = [ 3.8448, 3.8448, 3.8448, 3.8448, 3.8448] +24-11-19 20:26:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:07 | D | sum error = [ 383.8379, 403.7723, 424.0334, 444.4014, 465.0915] +24-11-19 20:26:07 | D | best error = [ 3.8448, 3.8448, 3.8448, 3.8448, 3.8448] +24-11-19 20:26:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:07 | D | sum error = [ 485.8459, 506.8443, 527.8835, 548.9152, 569.8069] +24-11-19 20:26:07 | D | best error = [ 3.8448, 3.8448, 3.8448, 3.8448, 3.8448] +24-11-19 20:26:07 | D | + error = [3.8448] +24-11-19 20:26:07 | D | - Calibrating model.layers.9.self_attn.k_proj.weight +24-11-19 20:26:07 | D | + w: sint8 +24-11-19 20:26:07 | D | + x: None +24-11-19 20:26:07 | D | + y: None +24-11-19 20:26:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:26:07 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:07 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:08 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:08 | D | - range ratio = [ 1.0000] +24-11-19 20:26:08 | D | sum error = [ 3.2315] +24-11-19 20:26:08 | D | best error = [ 3.2315] +24-11-19 20:26:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:20 | D | sum error = [ 3.3070, 3.1686, 3.4578, 3.2475, 3.4738] +24-11-19 20:26:20 | D | best error = [ 3.2315, 3.1686, 3.1686, 3.1686, 3.1686] +24-11-19 20:26:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:20 | D | sum error = [ 3.2402, 3.7948, 3.8624, 3.7807, 4.3761] +24-11-19 20:26:20 | D | best error = [ 3.1686, 3.1686, 3.1686, 3.1686, 3.1686] +24-11-19 20:26:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:20 | D | sum error = [ 4.1731, 4.9659, 5.5276, 5.7718, 6.5832] +24-11-19 20:26:20 | D | best error = [ 3.1686, 3.1686, 3.1686, 3.1686, 3.1686] +24-11-19 20:26:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:20 | D | sum error = [ 6.7844, 7.4358, 7.7440, 9.0034, 8.9001] +24-11-19 20:26:20 | D | best error = [ 3.1686, 3.1686, 3.1686, 3.1686, 3.1686] +24-11-19 20:26:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:20 | D | sum error = [ 10.1049, 10.9869, 12.0888, 13.1198, 14.2103] +24-11-19 20:26:20 | D | best error = [ 3.1686, 3.1686, 3.1686, 3.1686, 3.1686] +24-11-19 20:26:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:20 | D | sum error = [ 15.3197, 16.7991, 18.0088, 19.6842, 20.9579] +24-11-19 20:26:20 | D | best error = [ 3.1686, 3.1686, 3.1686, 3.1686, 3.1686] +24-11-19 20:26:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:20 | D | sum error = [ 22.3879, 24.7756, 26.8618, 28.3606, 30.5526] +24-11-19 20:26:20 | D | best error = [ 3.1686, 3.1686, 3.1686, 3.1686, 3.1686] +24-11-19 20:26:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:20 | D | sum error = [ 33.4333, 36.2702, 39.6238, 43.0679, 46.0107] +24-11-19 20:26:20 | D | best error = [ 3.1686, 3.1686, 3.1686, 3.1686, 3.1686] +24-11-19 20:26:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:20 | D | sum error = [ 49.0031, 52.8291, 58.2096, 62.3283, 66.9232] +24-11-19 20:26:20 | D | best error = [ 3.1686, 3.1686, 3.1686, 3.1686, 3.1686] +24-11-19 20:26:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:20 | D | sum error = [ 71.6233, 77.1634, 82.6336, 88.8629, 95.3888] +24-11-19 20:26:20 | D | best error = [ 3.1686, 3.1686, 3.1686, 3.1686, 3.1686] +24-11-19 20:26:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:20 | D | sum error = [ 103.0020, 110.3732, 118.2496, 127.0367, 136.2596] +24-11-19 20:26:20 | D | best error = [ 3.1686, 3.1686, 3.1686, 3.1686, 3.1686] +24-11-19 20:26:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:20 | D | sum error = [ 146.0755, 156.4385, 167.1211, 179.1660, 191.2398] +24-11-19 20:26:20 | D | best error = [ 3.1686, 3.1686, 3.1686, 3.1686, 3.1686] +24-11-19 20:26:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:20 | D | sum error = [ 203.9305, 217.3535, 231.7030, 246.6635, 262.0073] +24-11-19 20:26:20 | D | best error = [ 3.1686, 3.1686, 3.1686, 3.1686, 3.1686] +24-11-19 20:26:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:20 | D | sum error = [ 277.8182, 295.0012, 312.2097, 330.5358, 349.1844] +24-11-19 20:26:20 | D | best error = [ 3.1686, 3.1686, 3.1686, 3.1686, 3.1686] +24-11-19 20:26:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:20 | D | sum error = [ 368.7938, 388.3360, 408.6770, 429.7736, 451.1066] +24-11-19 20:26:20 | D | best error = [ 3.1686, 3.1686, 3.1686, 3.1686, 3.1686] +24-11-19 20:26:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:20 | D | sum error = [ 473.1863, 495.1837, 517.4678, 539.6440, 561.9996] +24-11-19 20:26:20 | D | best error = [ 3.1686, 3.1686, 3.1686, 3.1686, 3.1686] +24-11-19 20:26:20 | D | + error = [3.1686] +24-11-19 20:26:20 | D | - Calibrating model.layers.9.self_attn.v_proj.weight +24-11-19 20:26:20 | D | + w: sint8 +24-11-19 20:26:20 | D | + x: None +24-11-19 20:26:20 | D | + y: None +24-11-19 20:26:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:20 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:20 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:21 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:21 | D | - range ratio = [ 1.0000] +24-11-19 20:26:21 | D | sum error = [ 1.5156] +24-11-19 20:26:21 | D | best error = [ 1.5156] +24-11-19 20:26:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:21 | D | sum error = [ 1.4846, 1.4869, 1.4861, 1.5137, 1.5482] +24-11-19 20:26:21 | D | best error = [ 1.3919, 1.3497, 1.3305, 1.3182, 1.3129] +24-11-19 20:26:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:21 | D | sum error = [ 1.5736, 1.6195, 1.6910, 1.7682, 1.8772] +24-11-19 20:26:21 | D | best error = [ 1.3101, 1.3089, 1.3082, 1.3079, 1.3078] +24-11-19 20:26:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:21 | D | sum error = [ 1.9684, 2.0882, 2.2213, 2.3690, 2.5328] +24-11-19 20:26:21 | D | best error = [ 1.3078, 1.3078, 1.3078, 1.3078, 1.3078] +24-11-19 20:26:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:21 | D | sum error = [ 2.7145, 2.9170, 3.1263, 3.3474, 3.5933] +24-11-19 20:26:21 | D | best error = [ 1.3078, 1.3078, 1.3078, 1.3078, 1.3078] +24-11-19 20:26:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:21 | D | sum error = [ 3.8469, 4.1143, 4.4018, 4.7178, 5.0320] +24-11-19 20:26:21 | D | best error = [ 1.3078, 1.3078, 1.3078, 1.3078, 1.3078] +24-11-19 20:26:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:21 | D | sum error = [ 5.3656, 5.7428, 6.1360, 6.5292, 6.9686] +24-11-19 20:26:21 | D | best error = [ 1.3078, 1.3078, 1.3078, 1.3078, 1.3078] +24-11-19 20:26:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:21 | D | sum error = [ 7.4181, 7.9070, 8.4138, 8.9447, 9.5172] +24-11-19 20:26:21 | D | best error = [ 1.3078, 1.3078, 1.3078, 1.3078, 1.3078] +24-11-19 20:26:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:21 | D | sum error = [ 10.1044, 10.7328, 11.3958, 12.0978, 12.8042] +24-11-19 20:26:21 | D | best error = [ 1.3078, 1.3078, 1.3078, 1.3078, 1.3078] +24-11-19 20:26:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:21 | D | sum error = [ 13.5731, 14.3844, 15.2318, 16.1329, 17.0592] +24-11-19 20:26:21 | D | best error = [ 1.3078, 1.3078, 1.3078, 1.3078, 1.3078] +24-11-19 20:26:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:21 | D | sum error = [ 18.0459, 19.0809, 20.1650, 21.3051, 22.4924] +24-11-19 20:26:21 | D | best error = [ 1.3078, 1.3078, 1.3078, 1.3078, 1.3078] +24-11-19 20:26:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:21 | D | sum error = [ 23.7522, 25.0507, 26.4225, 27.8449, 29.3261] +24-11-19 20:26:21 | D | best error = [ 1.3078, 1.3078, 1.3078, 1.3078, 1.3078] +24-11-19 20:26:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:21 | D | sum error = [ 30.8813, 32.4904, 34.1798, 35.9365, 37.7571] +24-11-19 20:26:21 | D | best error = [ 1.3078, 1.3078, 1.3078, 1.3078, 1.3078] +24-11-19 20:26:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:21 | D | sum error = [ 39.6581, 41.6322, 43.6700, 45.7929, 48.0020] +24-11-19 20:26:21 | D | best error = [ 1.3078, 1.3078, 1.3078, 1.3078, 1.3078] +24-11-19 20:26:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:21 | D | sum error = [ 50.2943, 52.6626, 55.1288, 57.6757, 60.3201] +24-11-19 20:26:21 | D | best error = [ 1.3078, 1.3078, 1.3078, 1.3078, 1.3078] +24-11-19 20:26:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:21 | D | sum error = [ 63.0739, 65.9157, 68.8629, 71.9155, 75.0687] +24-11-19 20:26:21 | D | best error = [ 1.3078, 1.3078, 1.3078, 1.3078, 1.3078] +24-11-19 20:26:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:21 | D | sum error = [ 78.3051, 81.6634, 85.1191, 88.6791, 92.3442] +24-11-19 20:26:21 | D | best error = [ 1.3078, 1.3078, 1.3078, 1.3078, 1.3078] +24-11-19 20:26:21 | D | + error = [1.3078] +24-11-19 20:26:21 | D | - Calibrating model.layers.9.self_attn.o_proj.weight +24-11-19 20:26:21 | D | + w: sint8 +24-11-19 20:26:21 | D | + x: None +24-11-19 20:26:21 | D | + y: None +24-11-19 20:26:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:21 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:21 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:21 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:21 | D | - range ratio = [ 1.0000] +24-11-19 20:26:21 | D | sum error = [ 0.5988] +24-11-19 20:26:21 | D | best error = [ 0.5988] +24-11-19 20:26:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:21 | D | sum error = [ 0.5930, 0.5906, 0.5868, 0.5881, 0.5964] +24-11-19 20:26:21 | D | best error = [ 0.5446, 0.5202, 0.5060, 0.4951, 0.4882] +24-11-19 20:26:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:21 | D | sum error = [ 0.5958, 0.6081, 0.6182, 0.6324, 0.6503] +24-11-19 20:26:21 | D | best error = [ 0.4828, 0.4790, 0.4763, 0.4744, 0.4729] +24-11-19 20:26:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:21 | D | sum error = [ 0.6711, 0.6960, 0.7227, 0.7539, 0.7842] +24-11-19 20:26:21 | D | best error = [ 0.4718, 0.4712, 0.4707, 0.4704, 0.4700] +24-11-19 20:26:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:21 | D | sum error = [ 0.8265, 0.8687, 0.9099, 0.9582, 1.0102] +24-11-19 20:26:21 | D | best error = [ 0.4698, 0.4696, 0.4695, 0.4694, 0.4692] +24-11-19 20:26:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:21 | D | sum error = [ 1.0622, 1.1209, 1.1836, 1.2484, 1.3159] +24-11-19 20:26:21 | D | best error = [ 0.4692, 0.4691, 0.4690, 0.4690, 0.4690] +24-11-19 20:26:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:21 | D | sum error = [ 1.3891, 1.4622, 1.5437, 1.6304, 1.7200] +24-11-19 20:26:21 | D | best error = [ 0.4690, 0.4690, 0.4690, 0.4690, 0.4690] +24-11-19 20:26:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:21 | D | sum error = [ 1.8139, 1.9099, 2.0155, 2.1218, 2.2346] +24-11-19 20:26:21 | D | best error = [ 0.4690, 0.4690, 0.4690, 0.4690, 0.4690] +24-11-19 20:26:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:21 | D | sum error = [ 2.3532, 2.4804, 2.6103, 2.7487, 2.8944] +24-11-19 20:26:21 | D | best error = [ 0.4690, 0.4690, 0.4690, 0.4690, 0.4690] +24-11-19 20:26:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:21 | D | sum error = [ 3.0427, 3.2013, 3.3634, 3.5381, 3.7175] +24-11-19 20:26:21 | D | best error = [ 0.4690, 0.4690, 0.4690, 0.4690, 0.4690] +24-11-19 20:26:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:21 | D | sum error = [ 3.9096, 4.1082, 4.3171, 4.5317, 4.7597] +24-11-19 20:26:21 | D | best error = [ 0.4690, 0.4690, 0.4690, 0.4690, 0.4690] +24-11-19 20:26:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:21 | D | sum error = [ 4.9996, 5.2468, 5.5029, 5.7744, 6.0581] +24-11-19 20:26:21 | D | best error = [ 0.4690, 0.4690, 0.4690, 0.4690, 0.4690] +24-11-19 20:26:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:21 | D | sum error = [ 6.3522, 6.6600, 6.9782, 7.3098, 7.6539] +24-11-19 20:26:21 | D | best error = [ 0.4690, 0.4690, 0.4690, 0.4690, 0.4690] +24-11-19 20:26:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:21 | D | sum error = [ 8.0129, 8.3846, 8.7709, 9.1740, 9.5960] +24-11-19 20:26:21 | D | best error = [ 0.4690, 0.4690, 0.4690, 0.4690, 0.4690] +24-11-19 20:26:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:21 | D | sum error = [ 10.0312, 10.4832, 10.9531, 11.4381, 11.9395] +24-11-19 20:26:21 | D | best error = [ 0.4690, 0.4690, 0.4690, 0.4690, 0.4690] +24-11-19 20:26:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:21 | D | sum error = [ 12.4586, 12.9976, 13.5540, 14.1294, 14.7253] +24-11-19 20:26:21 | D | best error = [ 0.4690, 0.4690, 0.4690, 0.4690, 0.4690] +24-11-19 20:26:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:21 | D | sum error = [ 15.3442, 15.9834, 16.6467, 17.3319, 18.0453] +24-11-19 20:26:21 | D | best error = [ 0.4690, 0.4690, 0.4690, 0.4690, 0.4690] +24-11-19 20:26:21 | D | + error = [0.4690] +24-11-19 20:26:22 | D | - Calibrating model.layers.9.mlp.up_proj.weight +24-11-19 20:26:22 | D | + w: sint8 +24-11-19 20:26:22 | D | + x: None +24-11-19 20:26:22 | D | + y: None +24-11-19 20:26:22 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:22 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:22 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:22 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:22 | D | - range ratio = [ 1.0000] +24-11-19 20:26:22 | D | sum error = [ 4.7745] +24-11-19 20:26:22 | D | best error = [ 4.7745] +24-11-19 20:26:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:23 | D | sum error = [ 4.7424, 4.7342, 4.7438, 4.8014, 4.8914] +24-11-19 20:26:23 | D | best error = [ 4.4662, 4.3420, 4.2769, 4.2399, 4.2209] +24-11-19 20:26:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:23 | D | sum error = [ 5.0194, 5.1864, 5.3995, 5.6576, 5.9478] +24-11-19 20:26:23 | D | best error = [ 4.2113, 4.2073, 4.2059, 4.2056, 4.2055] +24-11-19 20:26:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:23 | D | sum error = [ 6.2995, 6.6833, 7.1240, 7.6001, 8.1242] +24-11-19 20:26:23 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:26:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:23 | D | sum error = [ 8.7107, 9.3195, 9.9951, 10.7216, 11.4885] +24-11-19 20:26:23 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:26:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:23 | D | sum error = [ 12.3060, 13.1879, 14.1295, 15.1214, 16.1702] +24-11-19 20:26:23 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:26:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:23 | D | sum error = [ 17.2905, 18.4728, 19.7167, 21.0497, 22.4500] +24-11-19 20:26:23 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:26:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:23 | D | sum error = [ 23.9183, 25.4793, 27.1247, 28.8544, 30.6933] +24-11-19 20:26:23 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:26:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:23 | D | sum error = [ 32.6197, 34.6457, 36.7789, 39.0264, 41.3948] +24-11-19 20:26:23 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:26:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:23 | D | sum error = [ 43.8677, 46.4695, 49.2042, 52.0635, 55.0686] +24-11-19 20:26:23 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:26:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:23 | D | sum error = [ 58.2142, 61.5232, 64.9817, 68.6119, 72.3986] +24-11-19 20:26:23 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:26:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:23 | D | sum error = [ 76.3668, 80.5078, 84.8474, 89.3705, 94.0964] +24-11-19 20:26:23 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:26:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:23 | D | sum error = [ 99.0336, 104.1807, 109.5499, 115.1400, 120.9544] +24-11-19 20:26:23 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:26:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:23 | D | sum error = [ 127.0116, 133.3018, 139.8461, 146.6476, 153.7144] +24-11-19 20:26:23 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:26:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:23 | D | sum error = [ 161.0382, 168.6388, 176.5258, 184.6943, 193.1477] +24-11-19 20:26:23 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:26:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:23 | D | sum error = [ 201.8976, 210.9443, 220.2861, 229.9428, 239.9119] +24-11-19 20:26:23 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:26:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:23 | D | sum error = [ 250.1808, 260.7682, 271.6709, 282.9066, 294.4773] +24-11-19 20:26:23 | D | best error = [ 4.2054, 4.2054, 4.2054, 4.2054, 4.2054] +24-11-19 20:26:23 | D | + error = [4.2054] +24-11-19 20:26:23 | D | - Calibrating model.layers.9.mlp.gate_proj.weight +24-11-19 20:26:23 | D | + w: sint8 +24-11-19 20:26:23 | D | + x: None +24-11-19 20:26:23 | D | + y: None +24-11-19 20:26:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:23 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:23 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:23 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:23 | D | - range ratio = [ 1.0000] +24-11-19 20:26:23 | D | sum error = [ 6.2403] +24-11-19 20:26:23 | D | best error = [ 6.2403] +24-11-19 20:26:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:25 | D | sum error = [ 6.1806, 6.1856, 6.1933, 6.2771, 6.3895] +24-11-19 20:26:25 | D | best error = [ 5.8300, 5.6702, 5.5852, 5.5366, 5.5106] +24-11-19 20:26:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:25 | D | sum error = [ 6.5550, 6.7608, 7.0566, 7.3730, 7.7653] +24-11-19 20:26:25 | D | best error = [ 5.4997, 5.4945, 5.4926, 5.4920, 5.4918] +24-11-19 20:26:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:25 | D | sum error = [ 8.2380, 8.7374, 9.3241, 9.9537, 10.6554] +24-11-19 20:26:25 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:26:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:25 | D | sum error = [ 11.4142, 12.2594, 13.1530, 14.1181, 15.1731] +24-11-19 20:26:25 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:26:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:25 | D | sum error = [ 16.2881, 17.4942, 18.7591, 20.1426, 21.6191] +24-11-19 20:26:25 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:26:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:25 | D | sum error = [ 23.1741, 24.8242, 26.5891, 28.4719, 30.4691] +24-11-19 20:26:25 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:26:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:25 | D | sum error = [ 32.5954, 34.8543, 37.2694, 39.8204, 42.5354] +24-11-19 20:26:25 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:26:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:25 | D | sum error = [ 45.4095, 48.4704, 51.7208, 55.1500, 58.8197] +24-11-19 20:26:25 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:26:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:25 | D | sum error = [ 62.6896, 66.8306, 71.1776, 75.8115, 80.7245] +24-11-19 20:26:25 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:26:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:25 | D | sum error = [ 85.9324, 91.4572, 97.3012, 103.4898, 110.0266] +24-11-19 20:26:25 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:26:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:25 | D | sum error = [ 116.9503, 124.2692, 132.0075, 140.1764, 148.7797] +24-11-19 20:26:25 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:26:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:25 | D | sum error = [ 157.8636, 167.4469, 177.5311, 188.1363, 199.2875] +24-11-19 20:26:25 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:26:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:25 | D | sum error = [ 211.0222, 223.3284, 236.2434, 249.7937, 263.9950] +24-11-19 20:26:25 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:26:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:25 | D | sum error = [ 278.8254, 294.3387, 310.5614, 327.4654, 345.1013] +24-11-19 20:26:25 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:26:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:25 | D | sum error = [ 363.4471, 382.5629, 402.4131, 423.0411, 444.4249] +24-11-19 20:26:25 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:26:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:25 | D | sum error = [ 466.5649, 489.4792, 513.1496, 537.5847, 562.7735] +24-11-19 20:26:25 | D | best error = [ 5.4918, 5.4918, 5.4918, 5.4918, 5.4918] +24-11-19 20:26:25 | D | + error = [5.4918] +24-11-19 20:26:25 | D | - Calibrating model.layers.9.mlp.down_proj.weight +24-11-19 20:26:25 | D | + w: sint8 +24-11-19 20:26:25 | D | + x: None +24-11-19 20:26:25 | D | + y: None +24-11-19 20:26:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:26:25 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:25 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:25 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:25 | D | - range ratio = [ 1.0000] +24-11-19 20:26:25 | D | sum error = [ 0.5906] +24-11-19 20:26:25 | D | best error = [ 0.5906] +24-11-19 20:26:26 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:26 | D | sum error = [ 0.5843, 0.5794, 0.5773, 0.5767, 0.5766] +24-11-19 20:26:26 | D | best error = [ 0.5655, 0.5529, 0.5446, 0.5387, 0.5345] +24-11-19 20:26:26 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:26 | D | sum error = [ 0.5784, 0.5848, 0.5915, 0.6024, 0.6150] +24-11-19 20:26:26 | D | best error = [ 0.5313, 0.5287, 0.5269, 0.5258, 0.5249] +24-11-19 20:26:26 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:26 | D | sum error = [ 0.6326, 0.6527, 0.6753, 0.7030, 0.7342] +24-11-19 20:26:26 | D | best error = [ 0.5243, 0.5240, 0.5237, 0.5235, 0.5234] +24-11-19 20:26:26 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:26 | D | sum error = [ 0.7701, 0.8111, 0.8553, 0.9045, 0.9570] +24-11-19 20:26:26 | D | best error = [ 0.5233, 0.5233, 0.5233, 0.5233, 0.5233] +24-11-19 20:26:26 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:26 | D | sum error = [ 1.0170, 1.0821, 1.1512, 1.2273, 1.3080] +24-11-19 20:26:26 | D | best error = [ 0.5232, 0.5232, 0.5232, 0.5232, 0.5232] +24-11-19 20:26:26 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:26 | D | sum error = [ 1.3949, 1.4878, 1.5881, 1.6948, 1.8084] +24-11-19 20:26:26 | D | best error = [ 0.5232, 0.5232, 0.5232, 0.5232, 0.5232] +24-11-19 20:26:26 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:26 | D | sum error = [ 1.9320, 2.0598, 2.1987, 2.3447, 2.5002] +24-11-19 20:26:26 | D | best error = [ 0.5232, 0.5232, 0.5232, 0.5232, 0.5232] +24-11-19 20:26:26 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:26 | D | sum error = [ 2.6672, 2.8422, 3.0300, 3.2269, 3.4356] +24-11-19 20:26:26 | D | best error = [ 0.5232, 0.5232, 0.5232, 0.5232, 0.5232] +24-11-19 20:26:26 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:26 | D | sum error = [ 3.6575, 3.8907, 4.1383, 4.3992, 4.6732] +24-11-19 20:26:26 | D | best error = [ 0.5232, 0.5232, 0.5232, 0.5232, 0.5232] +24-11-19 20:26:26 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:26 | D | sum error = [ 4.9638, 5.2675, 5.5895, 5.9273, 6.2842] +24-11-19 20:26:26 | D | best error = [ 0.5232, 0.5232, 0.5232, 0.5232, 0.5232] +24-11-19 20:26:26 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:26 | D | sum error = [ 6.6586, 7.0521, 7.4642, 7.8970, 8.3498] +24-11-19 20:26:26 | D | best error = [ 0.5232, 0.5232, 0.5232, 0.5232, 0.5232] +24-11-19 20:26:26 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:26 | D | sum error = [ 8.8254, 9.3237, 9.8449, 10.3902, 10.9602] +24-11-19 20:26:26 | D | best error = [ 0.5232, 0.5232, 0.5232, 0.5232, 0.5232] +24-11-19 20:26:26 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:26 | D | sum error = [ 11.5569, 12.1802, 12.8315, 13.5101, 14.2186] +24-11-19 20:26:26 | D | best error = [ 0.5232, 0.5232, 0.5232, 0.5232, 0.5232] +24-11-19 20:26:26 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:26 | D | sum error = [ 14.9568, 15.7248, 16.5235, 17.3545, 18.2173] +24-11-19 20:26:26 | D | best error = [ 0.5232, 0.5232, 0.5232, 0.5232, 0.5232] +24-11-19 20:26:26 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:26 | D | sum error = [ 19.1141, 20.0447, 21.0108, 22.0111, 23.0491] +24-11-19 20:26:26 | D | best error = [ 0.5232, 0.5232, 0.5232, 0.5232, 0.5232] +24-11-19 20:26:26 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:26 | D | sum error = [ 24.1233, 25.2356, 26.3866, 27.5765, 28.8053] +24-11-19 20:26:26 | D | best error = [ 0.5232, 0.5232, 0.5232, 0.5232, 0.5232] +24-11-19 20:26:26 | D | + error = [0.5232] +24-11-19 20:26:26 | D | - Quantizing model.layers.9.self_attn.q_proj.weight +24-11-19 20:26:27 | D | - Quantizing model.layers.9.self_attn.k_proj.weight +24-11-19 20:26:28 | D | - Quantizing model.layers.9.self_attn.v_proj.weight +24-11-19 20:26:30 | D | - Quantizing model.layers.9.self_attn.o_proj.weight +24-11-19 20:26:31 | D | - Quantizing model.layers.9.mlp.up_proj.weight +24-11-19 20:26:33 | D | - Quantizing model.layers.9.mlp.gate_proj.weight +24-11-19 20:26:34 | D | - Quantizing model.layers.9.mlp.down_proj.weight +24-11-19 20:26:46 | D | - Quantizing layer model.layers.10 +24-11-19 20:26:46 | D | - Calibrating model.layers.10.self_attn.q_proj.weight +24-11-19 20:26:46 | D | + w: sint8 +24-11-19 20:26:46 | D | + x: None +24-11-19 20:26:46 | D | + y: None +24-11-19 20:26:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:26:46 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:26:46 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:26:46 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:46 | D | - range ratio = [ 1.0000] +24-11-19 20:26:46 | D | sum error = [ 4.0533] +24-11-19 20:26:46 | D | best error = [ 4.0533] +24-11-19 20:26:58 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:26:58 | D | sum error = [ 4.0168, 4.0625, 4.0969, 4.1324, 4.2329] +24-11-19 20:26:58 | D | best error = [ 4.0168, 4.0168, 4.0168, 4.0168, 4.0168] +24-11-19 20:26:58 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:26:58 | D | sum error = [ 4.3910, 4.4522, 4.5577, 4.9968, 5.0516] +24-11-19 20:26:58 | D | best error = [ 4.0168, 4.0168, 4.0168, 4.0168, 4.0168] +24-11-19 20:26:58 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:26:58 | D | sum error = [ 5.5265, 5.8896, 6.3022, 6.9290, 7.5646] +24-11-19 20:26:58 | D | best error = [ 4.0168, 4.0168, 4.0168, 4.0168, 4.0168] +24-11-19 20:26:58 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:26:58 | D | sum error = [ 8.1206, 8.5751, 9.6002, 10.3153, 11.1814] +24-11-19 20:26:58 | D | best error = [ 4.0168, 4.0168, 4.0168, 4.0168, 4.0168] +24-11-19 20:26:58 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:26:58 | D | sum error = [ 12.1382, 13.3377, 14.4076, 15.4986, 16.9609] +24-11-19 20:26:58 | D | best error = [ 4.0168, 4.0168, 4.0168, 4.0168, 4.0168] +24-11-19 20:26:58 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:26:58 | D | sum error = [ 17.9191, 19.5681, 20.7389, 22.4445, 24.1092] +24-11-19 20:26:58 | D | best error = [ 4.0168, 4.0168, 4.0168, 4.0168, 4.0168] +24-11-19 20:26:58 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:26:58 | D | sum error = [ 26.0133, 28.0088, 29.7557, 32.0834, 34.3933] +24-11-19 20:26:58 | D | best error = [ 4.0168, 4.0168, 4.0168, 4.0168, 4.0168] +24-11-19 20:26:58 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:26:58 | D | sum error = [ 36.8544, 40.0147, 42.9756, 46.3181, 49.6494] +24-11-19 20:26:58 | D | best error = [ 4.0168, 4.0168, 4.0168, 4.0168, 4.0168] +24-11-19 20:26:58 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:26:58 | D | sum error = [ 52.9999, 57.2256, 60.7923, 65.2271, 69.5534] +24-11-19 20:26:58 | D | best error = [ 4.0168, 4.0168, 4.0168, 4.0168, 4.0168] +24-11-19 20:26:58 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:26:58 | D | sum error = [ 74.1184, 79.1421, 84.4950, 90.3328, 96.3289] +24-11-19 20:26:58 | D | best error = [ 4.0168, 4.0168, 4.0168, 4.0168, 4.0168] +24-11-19 20:26:58 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:26:58 | D | sum error = [ 103.0103, 109.7140, 117.1212, 124.9111, 133.0853] +24-11-19 20:26:58 | D | best error = [ 4.0168, 4.0168, 4.0168, 4.0168, 4.0168] +24-11-19 20:26:58 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:26:58 | D | sum error = [ 141.5310, 150.7598, 160.5512, 170.6045, 181.4122] +24-11-19 20:26:58 | D | best error = [ 4.0168, 4.0168, 4.0168, 4.0168, 4.0168] +24-11-19 20:26:58 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:26:58 | D | sum error = [ 192.6598, 204.6722, 217.4339, 230.7345, 244.6241] +24-11-19 20:26:58 | D | best error = [ 4.0168, 4.0168, 4.0168, 4.0168, 4.0168] +24-11-19 20:26:58 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:26:58 | D | sum error = [ 259.2376, 274.7204, 291.0335, 308.0472, 325.9810] +24-11-19 20:26:58 | D | best error = [ 4.0168, 4.0168, 4.0168, 4.0168, 4.0168] +24-11-19 20:26:58 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:26:58 | D | sum error = [ 344.3812, 363.7263, 383.8044, 404.4144, 425.4360] +24-11-19 20:26:58 | D | best error = [ 4.0168, 4.0168, 4.0168, 4.0168, 4.0168] +24-11-19 20:26:58 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:26:58 | D | sum error = [ 447.2520, 469.5900, 492.2283, 515.0420, 537.9185] +24-11-19 20:26:58 | D | best error = [ 4.0168, 4.0168, 4.0168, 4.0168, 4.0168] +24-11-19 20:26:58 | D | + error = [4.0168] +24-11-19 20:26:59 | D | - Calibrating model.layers.10.self_attn.k_proj.weight +24-11-19 20:26:59 | D | + w: sint8 +24-11-19 20:26:59 | D | + x: None +24-11-19 20:26:59 | D | + y: None +24-11-19 20:26:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:26:59 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:26:59 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:26:59 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:26:59 | D | - range ratio = [ 1.0000] +24-11-19 20:26:59 | D | sum error = [ 3.5501] +24-11-19 20:26:59 | D | best error = [ 3.5501] +24-11-19 20:27:11 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:11 | D | sum error = [ 3.4674, 3.6765, 3.4759, 3.4528, 3.6057] +24-11-19 20:27:11 | D | best error = [ 3.4674, 3.4674, 3.4674, 3.4528, 3.4528] +24-11-19 20:27:11 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:11 | D | sum error = [ 4.0672, 3.9638, 4.0129, 4.5454, 5.0904] +24-11-19 20:27:11 | D | best error = [ 3.4528, 3.4528, 3.4528, 3.4528, 3.4528] +24-11-19 20:27:11 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:11 | D | sum error = [ 5.2339, 6.0803, 6.0546, 6.9443, 7.1634] +24-11-19 20:27:11 | D | best error = [ 3.4528, 3.4528, 3.4528, 3.4528, 3.4528] +24-11-19 20:27:11 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:11 | D | sum error = [ 7.7009, 9.5388, 9.7744, 10.5510, 11.8400] +24-11-19 20:27:11 | D | best error = [ 3.4528, 3.4528, 3.4528, 3.4528, 3.4528] +24-11-19 20:27:11 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:11 | D | sum error = [ 12.7047, 13.6942, 14.4438, 16.2173, 17.9663] +24-11-19 20:27:11 | D | best error = [ 3.4528, 3.4528, 3.4528, 3.4528, 3.4528] +24-11-19 20:27:11 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:11 | D | sum error = [ 18.5594, 21.2256, 21.8095, 23.4302, 24.0368] +24-11-19 20:27:11 | D | best error = [ 3.4528, 3.4528, 3.4528, 3.4528, 3.4528] +24-11-19 20:27:11 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:11 | D | sum error = [ 26.1692, 27.7382, 29.9738, 32.6806, 34.8729] +24-11-19 20:27:11 | D | best error = [ 3.4528, 3.4528, 3.4528, 3.4528, 3.4528] +24-11-19 20:27:11 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:11 | D | sum error = [ 37.2985, 40.8315, 43.3710, 47.3289, 49.6711] +24-11-19 20:27:11 | D | best error = [ 3.4528, 3.4528, 3.4528, 3.4528, 3.4528] +24-11-19 20:27:11 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:11 | D | sum error = [ 53.4382, 57.5642, 61.6082, 65.5293, 70.3080] +24-11-19 20:27:11 | D | best error = [ 3.4528, 3.4528, 3.4528, 3.4528, 3.4528] +24-11-19 20:27:11 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:11 | D | sum error = [ 74.6608, 79.7567, 84.7623, 90.6387, 96.8736] +24-11-19 20:27:11 | D | best error = [ 3.4528, 3.4528, 3.4528, 3.4528, 3.4528] +24-11-19 20:27:11 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:11 | D | sum error = [ 102.8421, 109.1600, 116.9967, 124.5749, 132.4156] +24-11-19 20:27:11 | D | best error = [ 3.4528, 3.4528, 3.4528, 3.4528, 3.4528] +24-11-19 20:27:11 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:11 | D | sum error = [ 140.6294, 149.8921, 159.2357, 169.4166, 180.1030] +24-11-19 20:27:11 | D | best error = [ 3.4528, 3.4528, 3.4528, 3.4528, 3.4528] +24-11-19 20:27:11 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:11 | D | sum error = [ 191.5258, 203.1603, 214.7820, 227.2796, 240.2868] +24-11-19 20:27:11 | D | best error = [ 3.4528, 3.4528, 3.4528, 3.4528, 3.4528] +24-11-19 20:27:11 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:11 | D | sum error = [ 253.9418, 268.9216, 284.2222, 300.4592, 317.8022] +24-11-19 20:27:11 | D | best error = [ 3.4528, 3.4528, 3.4528, 3.4528, 3.4528] +24-11-19 20:27:11 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:11 | D | sum error = [ 336.4354, 355.9466, 375.8974, 396.9691, 418.5461] +24-11-19 20:27:11 | D | best error = [ 3.4528, 3.4528, 3.4528, 3.4528, 3.4528] +24-11-19 20:27:11 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:11 | D | sum error = [ 440.7984, 462.8955, 485.5347, 508.9225, 532.6954] +24-11-19 20:27:11 | D | best error = [ 3.4528, 3.4528, 3.4528, 3.4528, 3.4528] +24-11-19 20:27:11 | D | + error = [3.4528] +24-11-19 20:27:11 | D | - Calibrating model.layers.10.self_attn.v_proj.weight +24-11-19 20:27:11 | D | + w: sint8 +24-11-19 20:27:11 | D | + x: None +24-11-19 20:27:11 | D | + y: None +24-11-19 20:27:11 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:11 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:27:11 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:27:12 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:27:12 | D | - range ratio = [ 1.0000] +24-11-19 20:27:12 | D | sum error = [ 1.2931] +24-11-19 20:27:12 | D | best error = [ 1.2931] +24-11-19 20:27:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:12 | D | sum error = [ 1.3015, 1.2853, 1.2941, 1.3080, 1.3242] +24-11-19 20:27:12 | D | best error = [ 1.2036, 1.1667, 1.1481, 1.1376, 1.1307] +24-11-19 20:27:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:12 | D | sum error = [ 1.3685, 1.4234, 1.4744, 1.5509, 1.6300] +24-11-19 20:27:12 | D | best error = [ 1.1289, 1.1277, 1.1274, 1.1273, 1.1273] +24-11-19 20:27:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:12 | D | sum error = [ 1.7166, 1.8473, 1.9670, 2.1095, 2.2625] +24-11-19 20:27:12 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:27:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:12 | D | sum error = [ 2.4045, 2.5820, 2.7854, 2.9852, 3.2139] +24-11-19 20:27:12 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:27:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:12 | D | sum error = [ 3.4369, 3.6795, 3.9366, 4.2032, 4.4993] +24-11-19 20:27:12 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:27:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:12 | D | sum error = [ 4.8142, 5.1414, 5.4713, 5.8594, 6.2333] +24-11-19 20:27:12 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:27:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:12 | D | sum error = [ 6.6527, 7.0764, 7.5335, 8.0242, 8.5344] +24-11-19 20:27:12 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:27:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:12 | D | sum error = [ 9.0834, 9.6663, 10.2538, 10.8894, 11.5513] +24-11-19 20:27:12 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:27:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:12 | D | sum error = [ 12.2462, 12.9691, 13.7459, 14.5356, 15.3966] +24-11-19 20:27:12 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:27:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:12 | D | sum error = [ 16.2800, 17.2093, 18.1888, 19.2065, 20.2796] +24-11-19 20:27:12 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:27:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:12 | D | sum error = [ 21.4051, 22.5717, 23.8083, 25.0865, 26.4302] +24-11-19 20:27:12 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:27:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:12 | D | sum error = [ 27.8280, 29.2909, 30.8203, 32.4154, 34.0766] +24-11-19 20:27:12 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:27:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:12 | D | sum error = [ 35.8109, 37.6032, 39.4813, 41.4298, 43.4510] +24-11-19 20:27:12 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:27:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:12 | D | sum error = [ 45.5513, 47.7222, 49.9759, 52.3185, 54.7269] +24-11-19 20:27:12 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:27:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:12 | D | sum error = [ 57.2291, 59.8200, 62.4904, 65.2599, 68.1088] +24-11-19 20:27:12 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:27:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:12 | D | sum error = [ 71.0436, 74.0731, 77.1902, 80.4104, 83.7223] +24-11-19 20:27:12 | D | best error = [ 1.1273, 1.1273, 1.1273, 1.1273, 1.1273] +24-11-19 20:27:12 | D | + error = [1.1273] +24-11-19 20:27:12 | D | - Calibrating model.layers.10.self_attn.o_proj.weight +24-11-19 20:27:12 | D | + w: sint8 +24-11-19 20:27:12 | D | + x: None +24-11-19 20:27:12 | D | + y: None +24-11-19 20:27:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:12 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:27:12 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:27:12 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:27:12 | D | - range ratio = [ 1.0000] +24-11-19 20:27:12 | D | sum error = [ 0.5436] +24-11-19 20:27:12 | D | best error = [ 0.5436] +24-11-19 20:27:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:12 | D | sum error = [ 0.5385, 0.5361, 0.5382, 0.5384, 0.5443] +24-11-19 20:27:12 | D | best error = [ 0.4867, 0.4644, 0.4507, 0.4419, 0.4359] +24-11-19 20:27:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:12 | D | sum error = [ 0.5546, 0.5648, 0.5830, 0.6030, 0.6261] +24-11-19 20:27:12 | D | best error = [ 0.4318, 0.4284, 0.4264, 0.4250, 0.4240] +24-11-19 20:27:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:12 | D | sum error = [ 0.6536, 0.6809, 0.7134, 0.7493, 0.7945] +24-11-19 20:27:12 | D | best error = [ 0.4233, 0.4227, 0.4223, 0.4219, 0.4216] +24-11-19 20:27:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:12 | D | sum error = [ 0.8386, 0.8857, 0.9349, 0.9938, 1.0504] +24-11-19 20:27:12 | D | best error = [ 0.4215, 0.4213, 0.4212, 0.4211, 0.4210] +24-11-19 20:27:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:12 | D | sum error = [ 1.1144, 1.1828, 1.2536, 1.3300, 1.4098] +24-11-19 20:27:12 | D | best error = [ 0.4209, 0.4209, 0.4208, 0.4208, 0.4208] +24-11-19 20:27:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:12 | D | sum error = [ 1.4935, 1.5854, 1.6739, 1.7753, 1.8759] +24-11-19 20:27:12 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:27:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:12 | D | sum error = [ 1.9882, 2.0995, 2.2159, 2.3414, 2.4732] +24-11-19 20:27:12 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:27:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:12 | D | sum error = [ 2.6109, 2.7540, 2.9057, 3.0639, 3.2277] +24-11-19 20:27:12 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:27:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:12 | D | sum error = [ 3.4022, 3.5793, 3.7716, 3.9681, 4.1739] +24-11-19 20:27:12 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:27:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:12 | D | sum error = [ 4.3875, 4.6126, 4.8455, 5.0893, 5.3398] +24-11-19 20:27:12 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:27:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:12 | D | sum error = [ 5.6039, 5.8787, 6.1635, 6.4559, 6.7658] +24-11-19 20:27:12 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:27:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:12 | D | sum error = [ 7.0846, 7.4164, 7.7592, 8.1182, 8.4865] +24-11-19 20:27:12 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:27:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:12 | D | sum error = [ 8.8701, 9.2650, 9.6761, 10.1027, 10.5403] +24-11-19 20:27:12 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:27:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:12 | D | sum error = [ 10.9965, 11.4650, 11.9482, 12.4487, 12.9628] +24-11-19 20:27:12 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:27:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:12 | D | sum error = [ 13.4947, 14.0400, 14.6028, 15.1835, 15.7807] +24-11-19 20:27:12 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:27:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:12 | D | sum error = [ 16.3944, 17.0260, 17.6756, 18.3415, 19.0260] +24-11-19 20:27:12 | D | best error = [ 0.4208, 0.4208, 0.4208, 0.4208, 0.4208] +24-11-19 20:27:12 | D | + error = [0.4208] +24-11-19 20:27:12 | D | - Calibrating model.layers.10.mlp.up_proj.weight +24-11-19 20:27:12 | D | + w: sint8 +24-11-19 20:27:12 | D | + x: None +24-11-19 20:27:12 | D | + y: None +24-11-19 20:27:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:12 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:27:13 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:27:13 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:27:13 | D | - range ratio = [ 1.0000] +24-11-19 20:27:13 | D | sum error = [ 4.9257] +24-11-19 20:27:13 | D | best error = [ 4.9257] +24-11-19 20:27:14 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:14 | D | sum error = [ 4.8766, 4.8760, 4.8902, 4.9433, 5.0449] +24-11-19 20:27:14 | D | best error = [ 4.5814, 4.4534, 4.3840, 4.3444, 4.3234] +24-11-19 20:27:14 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:14 | D | sum error = [ 5.1680, 5.3505, 5.5599, 5.8195, 6.1359] +24-11-19 20:27:14 | D | best error = [ 4.3138, 4.3091, 4.3078, 4.3073, 4.3072] +24-11-19 20:27:14 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:14 | D | sum error = [ 6.4730, 6.8697, 7.3242, 7.8104, 8.3543] +24-11-19 20:27:14 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:27:14 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:14 | D | sum error = [ 8.9461, 9.5741, 10.2649, 11.0111, 11.7875] +24-11-19 20:27:14 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:27:14 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:14 | D | sum error = [ 12.6272, 13.5350, 14.4926, 15.4918, 16.5714] +24-11-19 20:27:14 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:27:14 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:14 | D | sum error = [ 17.7114, 18.9209, 20.2033, 21.5576, 22.9870] +24-11-19 20:27:14 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:27:14 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:14 | D | sum error = [ 24.5018, 26.0885, 27.7730, 29.5383, 31.4141] +24-11-19 20:27:14 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:27:14 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:14 | D | sum error = [ 33.3779, 35.4478, 37.6240, 39.9138, 42.3248] +24-11-19 20:27:14 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:27:14 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:14 | D | sum error = [ 44.8557, 47.5182, 50.3071, 53.2323, 56.3010] +24-11-19 20:27:14 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:27:14 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:14 | D | sum error = [ 59.5175, 62.8779, 66.4105, 70.1052, 73.9589] +24-11-19 20:27:14 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:27:14 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:14 | D | sum error = [ 78.0031, 82.2116, 86.6239, 91.2109, 96.0237] +24-11-19 20:27:14 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:27:14 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:14 | D | sum error = [ 101.0313, 106.2510, 111.6930, 117.3443, 123.2297] +24-11-19 20:27:14 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:27:14 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:14 | D | sum error = [ 129.3548, 135.7184, 142.3153, 149.1910, 156.3223] +24-11-19 20:27:14 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:27:14 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:14 | D | sum error = [ 163.7152, 171.3853, 179.3331, 187.5795, 196.1062] +24-11-19 20:27:14 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:27:14 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:14 | D | sum error = [ 204.9240, 214.0352, 223.4636, 233.1959, 243.2489] +24-11-19 20:27:14 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:27:14 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:14 | D | sum error = [ 253.6028, 264.2853, 275.2823, 286.6051, 298.2628] +24-11-19 20:27:14 | D | best error = [ 4.3072, 4.3072, 4.3072, 4.3072, 4.3072] +24-11-19 20:27:14 | D | + error = [4.3072] +24-11-19 20:27:14 | D | - Calibrating model.layers.10.mlp.gate_proj.weight +24-11-19 20:27:14 | D | + w: sint8 +24-11-19 20:27:14 | D | + x: None +24-11-19 20:27:14 | D | + y: None +24-11-19 20:27:14 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:14 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:27:14 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:27:14 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:27:14 | D | - range ratio = [ 1.0000] +24-11-19 20:27:14 | D | sum error = [ 6.1664] +24-11-19 20:27:14 | D | best error = [ 6.1664] +24-11-19 20:27:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:15 | D | sum error = [ 6.1187, 6.1048, 6.1388, 6.2020, 6.3050] +24-11-19 20:27:15 | D | best error = [ 5.7391, 5.5780, 5.4917, 5.4429, 5.4164] +24-11-19 20:27:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:15 | D | sum error = [ 6.4838, 6.7023, 6.9804, 7.3145, 7.7034] +24-11-19 20:27:15 | D | best error = [ 5.4035, 5.3984, 5.3963, 5.3959, 5.3958] +24-11-19 20:27:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:15 | D | sum error = [ 8.1570, 8.6704, 9.2524, 9.8711, 10.5724] +24-11-19 20:27:15 | D | best error = [ 5.3958, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:27:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:15 | D | sum error = [ 11.3334, 12.1451, 13.0659, 14.0112, 15.0401] +24-11-19 20:27:15 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:27:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:15 | D | sum error = [ 16.1732, 17.3326, 18.6217, 19.9743, 21.4163] +24-11-19 20:27:15 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:27:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:15 | D | sum error = [ 22.9593, 24.5746, 26.3319, 28.1760, 30.1369] +24-11-19 20:27:15 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:27:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:15 | D | sum error = [ 32.2087, 34.4484, 36.8156, 39.3131, 41.9883] +24-11-19 20:27:15 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:27:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:15 | D | sum error = [ 44.7979, 47.7949, 50.9895, 54.3590, 57.9660] +24-11-19 20:27:15 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:27:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:15 | D | sum error = [ 61.7549, 65.7828, 70.0643, 74.6021, 79.3894] +24-11-19 20:27:15 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:27:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:15 | D | sum error = [ 84.4627, 89.8583, 95.5733, 101.5860, 107.9728] +24-11-19 20:27:15 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:27:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:15 | D | sum error = [ 114.7133, 121.8317, 129.3408, 137.3133, 145.6735] +24-11-19 20:27:15 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:27:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:15 | D | sum error = [ 154.5121, 163.8216, 173.6185, 183.9255, 194.7644] +24-11-19 20:27:15 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:27:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:15 | D | sum error = [ 206.1126, 218.0432, 230.5627, 243.6576, 257.3725] +24-11-19 20:27:15 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:27:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:15 | D | sum error = [ 271.7393, 286.7141, 302.3876, 318.7464, 335.7794] +24-11-19 20:27:15 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:27:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:15 | D | sum error = [ 353.5401, 372.0034, 391.1816, 411.1013, 431.7530] +24-11-19 20:27:15 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:27:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:15 | D | sum error = [ 453.1755, 475.3095, 498.1865, 521.7763, 546.1035] +24-11-19 20:27:15 | D | best error = [ 5.3957, 5.3957, 5.3957, 5.3957, 5.3957] +24-11-19 20:27:15 | D | + error = [5.3957] +24-11-19 20:27:16 | D | - Calibrating model.layers.10.mlp.down_proj.weight +24-11-19 20:27:16 | D | + w: sint8 +24-11-19 20:27:16 | D | + x: None +24-11-19 20:27:16 | D | + y: None +24-11-19 20:27:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:27:16 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:27:16 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:27:16 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:27:16 | D | - range ratio = [ 1.0000] +24-11-19 20:27:16 | D | sum error = [ 0.6023] +24-11-19 20:27:16 | D | best error = [ 0.6023] +24-11-19 20:27:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:17 | D | sum error = [ 0.5983, 0.5935, 0.5899, 0.5876, 0.5882] +24-11-19 20:27:17 | D | best error = [ 0.5786, 0.5662, 0.5582, 0.5521, 0.5474] +24-11-19 20:27:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:17 | D | sum error = [ 0.5915, 0.5948, 0.6016, 0.6101, 0.6227] +24-11-19 20:27:17 | D | best error = [ 0.5441, 0.5415, 0.5396, 0.5385, 0.5377] +24-11-19 20:27:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:17 | D | sum error = [ 0.6379, 0.6553, 0.6760, 0.7040, 0.7337] +24-11-19 20:27:17 | D | best error = [ 0.5372, 0.5368, 0.5365, 0.5363, 0.5362] +24-11-19 20:27:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:17 | D | sum error = [ 0.7680, 0.8067, 0.8510, 0.8989, 0.9513] +24-11-19 20:27:17 | D | best error = [ 0.5361, 0.5361, 0.5361, 0.5361, 0.5360] +24-11-19 20:27:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:17 | D | sum error = [ 1.0104, 1.0755, 1.1448, 1.2214, 1.3018] +24-11-19 20:27:17 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 20:27:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:17 | D | sum error = [ 1.3894, 1.4834, 1.5836, 1.6911, 1.8071] +24-11-19 20:27:17 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 20:27:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:17 | D | sum error = [ 1.9296, 2.0618, 2.2013, 2.3503, 2.5064] +24-11-19 20:27:17 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 20:27:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:17 | D | sum error = [ 2.6741, 2.8526, 3.0418, 3.2392, 3.4492] +24-11-19 20:27:17 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 20:27:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:17 | D | sum error = [ 3.6727, 3.9070, 4.1549, 4.4172, 4.6936] +24-11-19 20:27:17 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 20:27:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:17 | D | sum error = [ 4.9852, 5.2918, 5.6157, 5.9561, 6.3145] +24-11-19 20:27:17 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 20:27:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:17 | D | sum error = [ 6.6906, 7.0875, 7.5026, 7.9391, 8.3964] +24-11-19 20:27:17 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 20:27:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:17 | D | sum error = [ 8.8747, 9.3763, 9.9006, 10.4494, 11.0220] +24-11-19 20:27:17 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 20:27:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:17 | D | sum error = [ 11.6207, 12.2446, 12.8976, 13.5776, 14.2862] +24-11-19 20:27:17 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 20:27:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:17 | D | sum error = [ 15.0246, 15.7934, 16.5936, 17.4263, 18.2908] +24-11-19 20:27:17 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 20:27:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:17 | D | sum error = [ 19.1887, 20.1207, 21.0874, 22.0900, 23.1292] +24-11-19 20:27:17 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 20:27:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:17 | D | sum error = [ 24.2049, 25.3184, 26.4706, 27.6609, 28.8917] +24-11-19 20:27:17 | D | best error = [ 0.5360, 0.5360, 0.5360, 0.5360, 0.5360] +24-11-19 20:27:17 | D | + error = [0.5360] +24-11-19 20:27:17 | D | - Quantizing model.layers.10.self_attn.q_proj.weight +24-11-19 20:27:18 | D | - Quantizing model.layers.10.self_attn.k_proj.weight +24-11-19 20:27:19 | D | - Quantizing model.layers.10.self_attn.v_proj.weight +24-11-19 20:27:20 | D | - Quantizing model.layers.10.self_attn.o_proj.weight +24-11-19 20:27:21 | D | - Quantizing model.layers.10.mlp.up_proj.weight +24-11-19 20:27:23 | D | - Quantizing model.layers.10.mlp.gate_proj.weight +24-11-19 20:27:26 | D | - Quantizing model.layers.10.mlp.down_proj.weight +24-11-19 20:27:38 | D | - Quantizing layer model.layers.11 +24-11-19 20:27:38 | D | - Calibrating model.layers.11.self_attn.q_proj.weight +24-11-19 20:27:38 | D | + w: sint8 +24-11-19 20:27:38 | D | + x: None +24-11-19 20:27:38 | D | + y: None +24-11-19 20:27:38 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:27:38 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:27:38 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:27:38 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:27:39 | D | - range ratio = [ 1.0000] +24-11-19 20:27:39 | D | sum error = [ 4.5055] +24-11-19 20:27:39 | D | best error = [ 4.5055] +24-11-19 20:27:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:27:51 | D | sum error = [ 4.3451, 4.3873, 4.4390, 4.4244, 4.5635] +24-11-19 20:27:51 | D | best error = [ 4.3451, 4.3451, 4.3451, 4.3451, 4.3451] +24-11-19 20:27:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:27:51 | D | sum error = [ 4.6386, 4.9620, 5.0378, 5.3446, 5.6075] +24-11-19 20:27:51 | D | best error = [ 4.3451, 4.3451, 4.3451, 4.3451, 4.3451] +24-11-19 20:27:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:27:51 | D | sum error = [ 6.0741, 6.3736, 6.8606, 7.2149, 7.6415] +24-11-19 20:27:51 | D | best error = [ 4.3451, 4.3451, 4.3451, 4.3451, 4.3451] +24-11-19 20:27:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:27:51 | D | sum error = [ 8.4944, 8.9668, 9.6102, 10.4288, 11.3562] +24-11-19 20:27:51 | D | best error = [ 4.3451, 4.3451, 4.3451, 4.3451, 4.3451] +24-11-19 20:27:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:27:51 | D | sum error = [ 12.3107, 13.2530, 14.5948, 15.9696, 17.5952] +24-11-19 20:27:51 | D | best error = [ 4.3451, 4.3451, 4.3451, 4.3451, 4.3451] +24-11-19 20:27:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:27:51 | D | sum error = [ 19.1540, 20.5317, 22.3775, 24.2060, 26.5278] +24-11-19 20:27:51 | D | best error = [ 4.3451, 4.3451, 4.3451, 4.3451, 4.3451] +24-11-19 20:27:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:27:51 | D | sum error = [ 28.6769, 31.3164, 33.4211, 36.1198, 38.7760] +24-11-19 20:27:51 | D | best error = [ 4.3451, 4.3451, 4.3451, 4.3451, 4.3451] +24-11-19 20:27:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:27:51 | D | sum error = [ 41.7306, 44.5115, 47.8439, 51.3222, 54.9441] +24-11-19 20:27:51 | D | best error = [ 4.3451, 4.3451, 4.3451, 4.3451, 4.3451] +24-11-19 20:27:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:27:51 | D | sum error = [ 58.6570, 62.6371, 66.8224, 71.0528, 75.8255] +24-11-19 20:27:51 | D | best error = [ 4.3451, 4.3451, 4.3451, 4.3451, 4.3451] +24-11-19 20:27:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:27:51 | D | sum error = [ 80.7632, 85.9871, 91.4257, 97.2168, 103.2272] +24-11-19 20:27:51 | D | best error = [ 4.3451, 4.3451, 4.3451, 4.3451, 4.3451] +24-11-19 20:27:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:27:51 | D | sum error = [ 109.4651, 116.0130, 123.0653, 130.5327, 138.3126] +24-11-19 20:27:51 | D | best error = [ 4.3451, 4.3451, 4.3451, 4.3451, 4.3451] +24-11-19 20:27:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:27:51 | D | sum error = [ 146.3476, 154.9633, 163.6559, 173.2866, 182.8612] +24-11-19 20:27:51 | D | best error = [ 4.3451, 4.3451, 4.3451, 4.3451, 4.3451] +24-11-19 20:27:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:27:51 | D | sum error = [ 192.8422, 203.6507, 214.7667, 226.3459, 238.3259] +24-11-19 20:27:51 | D | best error = [ 4.3451, 4.3451, 4.3451, 4.3451, 4.3451] +24-11-19 20:27:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:27:51 | D | sum error = [ 250.6133, 263.6887, 277.1665, 291.1714, 306.0113] +24-11-19 20:27:51 | D | best error = [ 4.3451, 4.3451, 4.3451, 4.3451, 4.3451] +24-11-19 20:27:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:27:51 | D | sum error = [ 321.2206, 337.1480, 353.6163, 370.5164, 388.0258] +24-11-19 20:27:51 | D | best error = [ 4.3451, 4.3451, 4.3451, 4.3451, 4.3451] +24-11-19 20:27:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:27:51 | D | sum error = [ 406.2360, 424.8321, 443.9018, 463.4729, 483.4245] +24-11-19 20:27:51 | D | best error = [ 4.3451, 4.3451, 4.3451, 4.3451, 4.3451] +24-11-19 20:27:51 | D | + error = [4.3451] +24-11-19 20:27:51 | D | - Calibrating model.layers.11.self_attn.k_proj.weight +24-11-19 20:27:51 | D | + w: sint8 +24-11-19 20:27:51 | D | + x: None +24-11-19 20:27:51 | D | + y: None +24-11-19 20:27:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:27:51 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:27:51 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:27:51 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:27:51 | D | - range ratio = [ 1.0000] +24-11-19 20:27:51 | D | sum error = [ 3.6860] +24-11-19 20:27:51 | D | best error = [ 3.6860] +24-11-19 20:28:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:04 | D | sum error = [ 3.7541, 3.7679, 3.6307, 3.7750, 3.9079] +24-11-19 20:28:04 | D | best error = [ 3.6860, 3.6860, 3.6307, 3.6307, 3.6307] +24-11-19 20:28:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:04 | D | sum error = [ 4.1590, 3.8234, 4.7908, 4.7998, 4.7369] +24-11-19 20:28:04 | D | best error = [ 3.6307, 3.6307, 3.6307, 3.6307, 3.6307] +24-11-19 20:28:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:04 | D | sum error = [ 4.6363, 4.7729, 5.6315, 6.0290, 6.6701] +24-11-19 20:28:04 | D | best error = [ 3.6307, 3.6307, 3.6307, 3.6307, 3.6307] +24-11-19 20:28:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:04 | D | sum error = [ 6.5550, 6.9421, 7.5332, 8.5418, 8.8684] +24-11-19 20:28:04 | D | best error = [ 3.6307, 3.6307, 3.6307, 3.6307, 3.6307] +24-11-19 20:28:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:04 | D | sum error = [ 9.4173, 10.5858, 11.5939, 12.2453, 13.9114] +24-11-19 20:28:04 | D | best error = [ 3.6307, 3.6307, 3.6307, 3.6307, 3.6307] +24-11-19 20:28:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:04 | D | sum error = [ 14.7685, 15.1772, 16.6194, 17.7037, 18.9145] +24-11-19 20:28:04 | D | best error = [ 3.6307, 3.6307, 3.6307, 3.6307, 3.6307] +24-11-19 20:28:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:04 | D | sum error = [ 19.8514, 21.5835, 22.7499, 23.8985, 26.0637] +24-11-19 20:28:04 | D | best error = [ 3.6307, 3.6307, 3.6307, 3.6307, 3.6307] +24-11-19 20:28:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:04 | D | sum error = [ 27.8031, 30.1773, 32.6278, 35.1158, 38.2814] +24-11-19 20:28:04 | D | best error = [ 3.6307, 3.6307, 3.6307, 3.6307, 3.6307] +24-11-19 20:28:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:04 | D | sum error = [ 40.6523, 43.9390, 47.2902, 51.2371, 54.9125] +24-11-19 20:28:04 | D | best error = [ 3.6307, 3.6307, 3.6307, 3.6307, 3.6307] +24-11-19 20:28:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:04 | D | sum error = [ 59.2583, 63.2191, 68.1444, 73.3419, 78.1466] +24-11-19 20:28:04 | D | best error = [ 3.6307, 3.6307, 3.6307, 3.6307, 3.6307] +24-11-19 20:28:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:04 | D | sum error = [ 82.9297, 89.1471, 95.0940, 101.8693, 108.9009] +24-11-19 20:28:04 | D | best error = [ 3.6307, 3.6307, 3.6307, 3.6307, 3.6307] +24-11-19 20:28:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:04 | D | sum error = [ 117.0008, 125.1482, 133.8490, 143.1265, 153.3954] +24-11-19 20:28:04 | D | best error = [ 3.6307, 3.6307, 3.6307, 3.6307, 3.6307] +24-11-19 20:28:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:04 | D | sum error = [ 163.3108, 174.3637, 185.9895, 198.1722, 211.1969] +24-11-19 20:28:04 | D | best error = [ 3.6307, 3.6307, 3.6307, 3.6307, 3.6307] +24-11-19 20:28:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:04 | D | sum error = [ 224.5560, 238.6962, 253.0588, 267.7281, 283.2374] +24-11-19 20:28:04 | D | best error = [ 3.6307, 3.6307, 3.6307, 3.6307, 3.6307] +24-11-19 20:28:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:04 | D | sum error = [ 299.4758, 316.2695, 333.9634, 352.4655, 371.6831] +24-11-19 20:28:04 | D | best error = [ 3.6307, 3.6307, 3.6307, 3.6307, 3.6307] +24-11-19 20:28:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:04 | D | sum error = [ 391.5509, 411.6678, 432.5212, 453.5481, 474.5474] +24-11-19 20:28:04 | D | best error = [ 3.6307, 3.6307, 3.6307, 3.6307, 3.6307] +24-11-19 20:28:04 | D | + error = [3.6307] +24-11-19 20:28:04 | D | - Calibrating model.layers.11.self_attn.v_proj.weight +24-11-19 20:28:04 | D | + w: sint8 +24-11-19 20:28:04 | D | + x: None +24-11-19 20:28:04 | D | + y: None +24-11-19 20:28:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:04 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:28:04 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:28:04 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:28:04 | D | - range ratio = [ 1.0000] +24-11-19 20:28:04 | D | sum error = [ 1.3219] +24-11-19 20:28:04 | D | best error = [ 1.3219] +24-11-19 20:28:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:04 | D | sum error = [ 1.3345, 1.3230, 1.3282, 1.3426, 1.3746] +24-11-19 20:28:04 | D | best error = [ 1.2336, 1.1989, 1.1795, 1.1686, 1.1630] +24-11-19 20:28:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:04 | D | sum error = [ 1.4016, 1.4425, 1.5051, 1.5766, 1.6628] +24-11-19 20:28:04 | D | best error = [ 1.1605, 1.1596, 1.1594, 1.1593, 1.1593] +24-11-19 20:28:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:04 | D | sum error = [ 1.7674, 1.8568, 1.9720, 2.1077, 2.2688] +24-11-19 20:28:04 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:28:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:04 | D | sum error = [ 2.4106, 2.5890, 2.7743, 2.9768, 3.1839] +24-11-19 20:28:04 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:28:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:04 | D | sum error = [ 3.4141, 3.6701, 3.9297, 4.2134, 4.5068] +24-11-19 20:28:04 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:28:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:04 | D | sum error = [ 4.8200, 5.1588, 5.5152, 5.8747, 6.2910] +24-11-19 20:28:04 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:28:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:04 | D | sum error = [ 6.7137, 7.1530, 7.6381, 8.1288, 8.6428] +24-11-19 20:28:04 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:28:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:04 | D | sum error = [ 9.1918, 9.7822, 10.3853, 11.0340, 11.7100] +24-11-19 20:28:04 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:28:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:04 | D | sum error = [ 12.4337, 13.1915, 13.9878, 14.8253, 15.7180] +24-11-19 20:28:04 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:28:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:04 | D | sum error = [ 16.6361, 17.6125, 18.6213, 19.6841, 20.8006] +24-11-19 20:28:04 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:28:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:04 | D | sum error = [ 21.9705, 23.1895, 24.4651, 25.8168, 27.2145] +24-11-19 20:28:04 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:28:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:04 | D | sum error = [ 28.6795, 30.2068, 31.8130, 33.4813, 35.2100] +24-11-19 20:28:04 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:28:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:04 | D | sum error = [ 37.0242, 38.9129, 40.8815, 42.9278, 45.0582] +24-11-19 20:28:04 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:28:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:04 | D | sum error = [ 47.2752, 49.5777, 51.9753, 54.4579, 57.0347] +24-11-19 20:28:04 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:28:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:04 | D | sum error = [ 59.7059, 62.4860, 65.3577, 68.3338, 71.4037] +24-11-19 20:28:04 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:28:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:04 | D | sum error = [ 74.5723, 77.8486, 81.2240, 84.7116, 88.2927] +24-11-19 20:28:04 | D | best error = [ 1.1593, 1.1593, 1.1593, 1.1593, 1.1593] +24-11-19 20:28:04 | D | + error = [1.1593] +24-11-19 20:28:04 | D | - Calibrating model.layers.11.self_attn.o_proj.weight +24-11-19 20:28:04 | D | + w: sint8 +24-11-19 20:28:04 | D | + x: None +24-11-19 20:28:04 | D | + y: None +24-11-19 20:28:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:04 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:28:04 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:28:05 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:28:05 | D | - range ratio = [ 1.0000] +24-11-19 20:28:05 | D | sum error = [ 0.5878] +24-11-19 20:28:05 | D | best error = [ 0.5878] +24-11-19 20:28:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:05 | D | sum error = [ 0.5827, 0.5813, 0.5757, 0.5829, 0.5843] +24-11-19 20:28:05 | D | best error = [ 0.5158, 0.4885, 0.4726, 0.4630, 0.4556] +24-11-19 20:28:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:05 | D | sum error = [ 0.5924, 0.6012, 0.6144, 0.6290, 0.6508] +24-11-19 20:28:05 | D | best error = [ 0.4504, 0.4463, 0.4428, 0.4402, 0.4385] +24-11-19 20:28:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:05 | D | sum error = [ 0.6713, 0.7039, 0.7309, 0.7717, 0.8035] +24-11-19 20:28:05 | D | best error = [ 0.4372, 0.4359, 0.4351, 0.4344, 0.4340] +24-11-19 20:28:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:05 | D | sum error = [ 0.8513, 0.8954, 0.9500, 1.0031, 1.0673] +24-11-19 20:28:05 | D | best error = [ 0.4336, 0.4333, 0.4329, 0.4326, 0.4324] +24-11-19 20:28:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:05 | D | sum error = [ 1.1290, 1.1940, 1.2661, 1.3499, 1.4292] +24-11-19 20:28:05 | D | best error = [ 0.4322, 0.4321, 0.4319, 0.4319, 0.4319] +24-11-19 20:28:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:05 | D | sum error = [ 1.5190, 1.6133, 1.7064, 1.8166, 1.9239] +24-11-19 20:28:05 | D | best error = [ 0.4318, 0.4317, 0.4317, 0.4316, 0.4316] +24-11-19 20:28:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:05 | D | sum error = [ 2.0389, 2.1606, 2.2901, 2.4259, 2.5693] +24-11-19 20:28:05 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:28:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:05 | D | sum error = [ 2.7164, 2.8714, 3.0332, 3.2050, 3.3803] +24-11-19 20:28:05 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:28:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:05 | D | sum error = [ 3.5672, 3.7591, 3.9606, 4.1710, 4.3926] +24-11-19 20:28:05 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:28:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:05 | D | sum error = [ 4.6180, 4.8547, 5.1026, 5.3599, 5.6296] +24-11-19 20:28:05 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:28:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:05 | D | sum error = [ 5.9096, 6.2017, 6.5036, 6.8133, 7.1405] +24-11-19 20:28:05 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:28:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:05 | D | sum error = [ 7.4722, 7.8191, 8.1776, 8.5482, 8.9272] +24-11-19 20:28:05 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:28:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:05 | D | sum error = [ 9.3234, 9.7283, 10.1455, 10.5730, 11.0142] +24-11-19 20:28:05 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:28:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:05 | D | sum error = [ 11.4707, 11.9349, 12.4130, 12.9023, 13.4031] +24-11-19 20:28:05 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:28:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:05 | D | sum error = [ 13.9166, 14.4432, 14.9830, 15.5351, 16.1014] +24-11-19 20:28:05 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:28:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:05 | D | sum error = [ 16.6811, 17.2701, 17.8715, 18.4892, 19.1209] +24-11-19 20:28:05 | D | best error = [ 0.4316, 0.4316, 0.4316, 0.4316, 0.4316] +24-11-19 20:28:05 | D | + error = [0.4316] +24-11-19 20:28:05 | D | - Calibrating model.layers.11.mlp.up_proj.weight +24-11-19 20:28:05 | D | + w: sint8 +24-11-19 20:28:05 | D | + x: None +24-11-19 20:28:05 | D | + y: None +24-11-19 20:28:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:05 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:28:05 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:28:05 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:28:05 | D | - range ratio = [ 1.0000] +24-11-19 20:28:05 | D | sum error = [ 5.0177] +24-11-19 20:28:05 | D | best error = [ 5.0177] +24-11-19 20:28:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:07 | D | sum error = [ 4.9834, 4.9685, 4.9860, 5.0473, 5.1333] +24-11-19 20:28:07 | D | best error = [ 4.6582, 4.5241, 4.4523, 4.4120, 4.3903] +24-11-19 20:28:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:07 | D | sum error = [ 5.2572, 5.4363, 5.6595, 5.9254, 6.2305] +24-11-19 20:28:07 | D | best error = [ 4.3799, 4.3753, 4.3739, 4.3734, 4.3734] +24-11-19 20:28:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:07 | D | sum error = [ 6.5900, 7.0043, 7.4496, 7.9338, 8.4847] +24-11-19 20:28:07 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:28:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:07 | D | sum error = [ 9.0886, 9.7389, 10.4356, 11.1645, 11.9760] +24-11-19 20:28:07 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:28:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:07 | D | sum error = [ 12.8367, 13.7470, 14.7184, 15.7466, 16.8466] +24-11-19 20:28:07 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:28:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:07 | D | sum error = [ 18.0051, 19.2370, 20.5260, 21.9090, 23.3588] +24-11-19 20:28:07 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:28:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:07 | D | sum error = [ 24.8953, 26.5059, 28.2087, 30.0088, 31.8980] +24-11-19 20:28:07 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:28:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:07 | D | sum error = [ 33.8796, 35.9790, 38.1846, 40.5027, 42.9371] +24-11-19 20:28:07 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:28:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:07 | D | sum error = [ 45.4986, 48.1837, 51.0099, 53.9740, 57.0840] +24-11-19 20:28:07 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:28:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:07 | D | sum error = [ 60.3490, 63.7612, 67.3443, 71.0804, 74.9927] +24-11-19 20:28:07 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:28:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:07 | D | sum error = [ 79.0936, 83.3854, 87.8557, 92.5310, 97.4121] +24-11-19 20:28:07 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:28:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:07 | D | sum error = [ 102.4929, 107.7960, 113.3137, 119.0636, 125.0496] +24-11-19 20:28:07 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:28:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:07 | D | sum error = [ 131.2729, 137.7473, 144.4706, 151.4661, 158.7281] +24-11-19 20:28:07 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:28:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:07 | D | sum error = [ 166.2480, 174.0583, 182.1655, 190.5726, 199.2758] +24-11-19 20:28:07 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:28:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:07 | D | sum error = [ 208.2926, 217.5960, 227.2244, 237.1676, 247.4213] +24-11-19 20:28:07 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:28:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:07 | D | sum error = [ 258.0101, 268.9294, 280.1759, 291.7511, 303.6706] +24-11-19 20:28:07 | D | best error = [ 4.3733, 4.3733, 4.3733, 4.3733, 4.3733] +24-11-19 20:28:07 | D | + error = [4.3733] +24-11-19 20:28:07 | D | - Calibrating model.layers.11.mlp.gate_proj.weight +24-11-19 20:28:07 | D | + w: sint8 +24-11-19 20:28:07 | D | + x: None +24-11-19 20:28:07 | D | + y: None +24-11-19 20:28:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:07 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:07 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:07 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:07 | D | - range ratio = [ 1.0000] +24-11-19 20:28:07 | D | sum error = [ 6.1487] +24-11-19 20:28:07 | D | best error = [ 6.1487] +24-11-19 20:28:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:08 | D | sum error = [ 6.1074, 6.0891, 6.1143, 6.1731, 6.3092] +24-11-19 20:28:08 | D | best error = [ 5.7142, 5.5466, 5.4579, 5.4070, 5.3804] +24-11-19 20:28:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:08 | D | sum error = [ 6.4718, 6.6796, 6.9560, 7.2924, 7.6671] +24-11-19 20:28:08 | D | best error = [ 5.3680, 5.3625, 5.3609, 5.3604, 5.3602] +24-11-19 20:28:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:08 | D | sum error = [ 8.1323, 8.6422, 9.2205, 9.8339, 10.5394] +24-11-19 20:28:08 | D | best error = [ 5.3602, 5.3602, 5.3602, 5.3602, 5.3602] +24-11-19 20:28:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:08 | D | sum error = [ 11.3230, 12.1331, 13.0343, 14.0030, 15.0361] +24-11-19 20:28:08 | D | best error = [ 5.3602, 5.3602, 5.3602, 5.3602, 5.3602] +24-11-19 20:28:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:08 | D | sum error = [ 16.1516, 17.3471, 18.6200, 19.9622, 21.4343] +24-11-19 20:28:08 | D | best error = [ 5.3602, 5.3602, 5.3602, 5.3602, 5.3602] +24-11-19 20:28:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:08 | D | sum error = [ 22.9687, 24.6135, 26.3813, 28.2285, 30.2032] +24-11-19 20:28:08 | D | best error = [ 5.3602, 5.3602, 5.3602, 5.3602, 5.3602] +24-11-19 20:28:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:08 | D | sum error = [ 32.3122, 34.5552, 36.9235, 39.4512, 42.1413] +24-11-19 20:28:08 | D | best error = [ 5.3602, 5.3602, 5.3602, 5.3602, 5.3602] +24-11-19 20:28:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:08 | D | sum error = [ 44.9863, 48.0099, 51.2223, 54.6450, 58.2435] +24-11-19 20:28:08 | D | best error = [ 5.3602, 5.3602, 5.3602, 5.3602, 5.3602] +24-11-19 20:28:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:08 | D | sum error = [ 62.0631, 66.1354, 70.4289, 75.0009, 79.8359] +24-11-19 20:28:08 | D | best error = [ 5.3602, 5.3602, 5.3602, 5.3602, 5.3602] +24-11-19 20:28:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:08 | D | sum error = [ 84.9542, 90.3958, 96.1304, 102.2113, 108.6530] +24-11-19 20:28:08 | D | best error = [ 5.3602, 5.3602, 5.3602, 5.3602, 5.3602] +24-11-19 20:28:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:08 | D | sum error = [ 115.4944, 122.6832, 130.3036, 138.3646, 146.8412] +24-11-19 20:28:08 | D | best error = [ 5.3602, 5.3602, 5.3602, 5.3602, 5.3602] +24-11-19 20:28:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:08 | D | sum error = [ 155.7883, 165.2390, 175.1971, 185.6472, 196.6576] +24-11-19 20:28:08 | D | best error = [ 5.3602, 5.3602, 5.3602, 5.3602, 5.3602] +24-11-19 20:28:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:08 | D | sum error = [ 208.2370, 220.3779, 233.1320, 246.4843, 260.4729] +24-11-19 20:28:08 | D | best error = [ 5.3602, 5.3602, 5.3602, 5.3602, 5.3602] +24-11-19 20:28:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:08 | D | sum error = [ 275.1066, 290.4054, 306.3758, 323.0641, 340.4705] +24-11-19 20:28:08 | D | best error = [ 5.3602, 5.3602, 5.3602, 5.3602, 5.3602] +24-11-19 20:28:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:08 | D | sum error = [ 358.5643, 377.4088, 396.9883, 417.3127, 438.3805] +24-11-19 20:28:08 | D | best error = [ 5.3602, 5.3602, 5.3602, 5.3602, 5.3602] +24-11-19 20:28:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:08 | D | sum error = [ 460.2157, 482.8022, 506.1693, 530.2495, 555.1045] +24-11-19 20:28:08 | D | best error = [ 5.3602, 5.3602, 5.3602, 5.3602, 5.3602] +24-11-19 20:28:08 | D | + error = [5.3602] +24-11-19 20:28:08 | D | - Calibrating model.layers.11.mlp.down_proj.weight +24-11-19 20:28:08 | D | + w: sint8 +24-11-19 20:28:08 | D | + x: None +24-11-19 20:28:08 | D | + y: None +24-11-19 20:28:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:08 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:08 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:09 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:09 | D | - range ratio = [ 1.0000] +24-11-19 20:28:09 | D | sum error = [ 0.6149] +24-11-19 20:28:09 | D | best error = [ 0.6149] +24-11-19 20:28:10 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:10 | D | sum error = [ 0.6082, 0.6049, 0.6005, 0.5996, 0.5998] +24-11-19 20:28:10 | D | best error = [ 0.5874, 0.5755, 0.5671, 0.5611, 0.5565] +24-11-19 20:28:10 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:10 | D | sum error = [ 0.6031, 0.6090, 0.6170, 0.6286, 0.6416] +24-11-19 20:28:10 | D | best error = [ 0.5535, 0.5514, 0.5496, 0.5486, 0.5478] +24-11-19 20:28:10 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:10 | D | sum error = [ 0.6594, 0.6810, 0.7079, 0.7371, 0.7700] +24-11-19 20:28:10 | D | best error = [ 0.5473, 0.5470, 0.5467, 0.5465, 0.5465] +24-11-19 20:28:10 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:10 | D | sum error = [ 0.8069, 0.8505, 0.8969, 0.9485, 1.0060] +24-11-19 20:28:10 | D | best error = [ 0.5464, 0.5464, 0.5463, 0.5463, 0.5463] +24-11-19 20:28:10 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:10 | D | sum error = [ 1.0688, 1.1349, 1.2098, 1.2879, 1.3720] +24-11-19 20:28:10 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 20:28:10 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:10 | D | sum error = [ 1.4635, 1.5609, 1.6646, 1.7755, 1.8951] +24-11-19 20:28:10 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 20:28:10 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:10 | D | sum error = [ 2.0213, 2.1564, 2.3001, 2.4528, 2.6154] +24-11-19 20:28:10 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 20:28:10 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:10 | D | sum error = [ 2.7869, 2.9690, 3.1608, 3.3639, 3.5799] +24-11-19 20:28:10 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 20:28:10 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:10 | D | sum error = [ 3.8076, 4.0473, 4.3023, 4.5700, 4.8527] +24-11-19 20:28:10 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 20:28:10 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:10 | D | sum error = [ 5.1499, 5.4633, 5.7928, 6.1401, 6.5050] +24-11-19 20:28:10 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 20:28:10 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:10 | D | sum error = [ 6.8894, 7.2932, 7.7163, 8.1621, 8.6281] +24-11-19 20:28:10 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 20:28:10 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:10 | D | sum error = [ 9.1166, 9.6284, 10.1645, 10.7234, 11.3089] +24-11-19 20:28:10 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 20:28:10 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:10 | D | sum error = [ 11.9200, 12.5585, 13.2245, 13.9197, 14.6458] +24-11-19 20:28:10 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 20:28:10 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:10 | D | sum error = [ 15.4030, 16.1920, 17.0117, 17.8666, 18.7539] +24-11-19 20:28:10 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 20:28:10 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:10 | D | sum error = [ 19.6771, 20.6344, 21.6293, 22.6615, 23.7314] +24-11-19 20:28:10 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 20:28:10 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:10 | D | sum error = [ 24.8396, 25.9874, 27.1742, 28.4017, 29.6691] +24-11-19 20:28:10 | D | best error = [ 0.5463, 0.5463, 0.5463, 0.5463, 0.5463] +24-11-19 20:28:10 | D | + error = [0.5463] +24-11-19 20:28:10 | D | - Quantizing model.layers.11.self_attn.q_proj.weight +24-11-19 20:28:11 | D | - Quantizing model.layers.11.self_attn.k_proj.weight +24-11-19 20:28:12 | D | - Quantizing model.layers.11.self_attn.v_proj.weight +24-11-19 20:28:13 | D | - Quantizing model.layers.11.self_attn.o_proj.weight +24-11-19 20:28:13 | D | - Quantizing model.layers.11.mlp.up_proj.weight +24-11-19 20:28:14 | D | - Quantizing model.layers.11.mlp.gate_proj.weight +24-11-19 20:28:15 | D | - Quantizing model.layers.11.mlp.down_proj.weight +24-11-19 20:28:26 | D | - Quantizing layer model.layers.12 +24-11-19 20:28:26 | D | - Calibrating model.layers.12.self_attn.q_proj.weight +24-11-19 20:28:26 | D | + w: sint8 +24-11-19 20:28:26 | D | + x: None +24-11-19 20:28:26 | D | + y: None +24-11-19 20:28:26 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:28:26 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:28:26 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:28:27 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:28:27 | D | - range ratio = [ 1.0000] +24-11-19 20:28:27 | D | sum error = [ 3.9112] +24-11-19 20:28:27 | D | best error = [ 3.9112] +24-11-19 20:28:39 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:39 | D | sum error = [ 3.8453, 3.8776, 3.8182, 3.9670, 4.0901] +24-11-19 20:28:39 | D | best error = [ 3.8453, 3.8453, 3.8182, 3.8182, 3.8182] +24-11-19 20:28:39 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:39 | D | sum error = [ 4.1767, 4.3333, 4.5494, 4.6154, 5.0761] +24-11-19 20:28:39 | D | best error = [ 3.8182, 3.8182, 3.8182, 3.8182, 3.8182] +24-11-19 20:28:39 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:39 | D | sum error = [ 5.2466, 5.6286, 6.0207, 6.5032, 6.9597] +24-11-19 20:28:39 | D | best error = [ 3.8182, 3.8182, 3.8182, 3.8182, 3.8182] +24-11-19 20:28:39 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:39 | D | sum error = [ 7.5300, 8.1805, 8.7577, 9.6446, 10.3282] +24-11-19 20:28:39 | D | best error = [ 3.8182, 3.8182, 3.8182, 3.8182, 3.8182] +24-11-19 20:28:39 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:39 | D | sum error = [ 11.2800, 12.3871, 13.5312, 14.8228, 16.2269] +24-11-19 20:28:39 | D | best error = [ 3.8182, 3.8182, 3.8182, 3.8182, 3.8182] +24-11-19 20:28:39 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:39 | D | sum error = [ 17.5638, 19.1742, 20.8164, 22.7998, 24.3880] +24-11-19 20:28:39 | D | best error = [ 3.8182, 3.8182, 3.8182, 3.8182, 3.8182] +24-11-19 20:28:39 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:39 | D | sum error = [ 26.6806, 28.5709, 30.8422, 33.3292, 35.8951] +24-11-19 20:28:39 | D | best error = [ 3.8182, 3.8182, 3.8182, 3.8182, 3.8182] +24-11-19 20:28:39 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:39 | D | sum error = [ 38.8970, 41.7605, 44.9078, 48.1998, 51.9050] +24-11-19 20:28:39 | D | best error = [ 3.8182, 3.8182, 3.8182, 3.8182, 3.8182] +24-11-19 20:28:39 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:39 | D | sum error = [ 55.6074, 59.6623, 63.7970, 68.4278, 72.9278] +24-11-19 20:28:39 | D | best error = [ 3.8182, 3.8182, 3.8182, 3.8182, 3.8182] +24-11-19 20:28:39 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:39 | D | sum error = [ 78.0147, 83.4931, 89.2197, 95.0037, 101.3633] +24-11-19 20:28:39 | D | best error = [ 3.8182, 3.8182, 3.8182, 3.8182, 3.8182] +24-11-19 20:28:39 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:39 | D | sum error = [ 107.7961, 114.6762, 121.9592, 129.4256, 137.3562] +24-11-19 20:28:39 | D | best error = [ 3.8182, 3.8182, 3.8182, 3.8182, 3.8182] +24-11-19 20:28:39 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:39 | D | sum error = [ 145.7635, 154.3906, 163.3946, 172.8448, 182.8551] +24-11-19 20:28:39 | D | best error = [ 3.8182, 3.8182, 3.8182, 3.8182, 3.8182] +24-11-19 20:28:39 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:39 | D | sum error = [ 193.0945, 203.9676, 215.3898, 227.2620, 239.7703] +24-11-19 20:28:39 | D | best error = [ 3.8182, 3.8182, 3.8182, 3.8182, 3.8182] +24-11-19 20:28:39 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:39 | D | sum error = [ 253.0361, 266.9807, 281.7898, 297.4109, 313.7502] +24-11-19 20:28:39 | D | best error = [ 3.8182, 3.8182, 3.8182, 3.8182, 3.8182] +24-11-19 20:28:39 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:39 | D | sum error = [ 331.0069, 349.3016, 368.2033, 387.9973, 408.7274] +24-11-19 20:28:39 | D | best error = [ 3.8182, 3.8182, 3.8182, 3.8182, 3.8182] +24-11-19 20:28:39 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:39 | D | sum error = [ 430.1405, 452.3806, 475.3862, 499.0955, 523.2480] +24-11-19 20:28:39 | D | best error = [ 3.8182, 3.8182, 3.8182, 3.8182, 3.8182] +24-11-19 20:28:39 | D | + error = [3.8182] +24-11-19 20:28:39 | D | - Calibrating model.layers.12.self_attn.k_proj.weight +24-11-19 20:28:39 | D | + w: sint8 +24-11-19 20:28:39 | D | + x: None +24-11-19 20:28:39 | D | + y: None +24-11-19 20:28:39 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:28:39 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:39 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:39 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:39 | D | - range ratio = [ 1.0000] +24-11-19 20:28:39 | D | sum error = [ 3.7411] +24-11-19 20:28:39 | D | best error = [ 3.7411] +24-11-19 20:28:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:51 | D | sum error = [ 3.6264, 3.5775, 4.0808, 3.9760, 4.0376] +24-11-19 20:28:51 | D | best error = [ 3.6264, 3.5775, 3.5775, 3.5775, 3.5775] +24-11-19 20:28:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:51 | D | sum error = [ 4.2120, 4.0321, 3.9404, 4.4403, 4.8509] +24-11-19 20:28:51 | D | best error = [ 3.5775, 3.5775, 3.5775, 3.5775, 3.5775] +24-11-19 20:28:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:51 | D | sum error = [ 5.0826, 5.4610, 5.9050, 5.5459, 6.3897] +24-11-19 20:28:51 | D | best error = [ 3.5775, 3.5775, 3.5775, 3.5775, 3.5775] +24-11-19 20:28:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:51 | D | sum error = [ 7.1067, 7.1747, 8.1500, 8.6585, 9.2040] +24-11-19 20:28:51 | D | best error = [ 3.5775, 3.5775, 3.5775, 3.5775, 3.5775] +24-11-19 20:28:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:51 | D | sum error = [ 9.6641, 11.2445, 12.5972, 12.5513, 13.6340] +24-11-19 20:28:51 | D | best error = [ 3.5775, 3.5775, 3.5775, 3.5775, 3.5775] +24-11-19 20:28:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:51 | D | sum error = [ 14.4780, 16.3237, 17.2977, 18.8192, 20.5369] +24-11-19 20:28:51 | D | best error = [ 3.5775, 3.5775, 3.5775, 3.5775, 3.5775] +24-11-19 20:28:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:51 | D | sum error = [ 22.1502, 23.4709, 26.0227, 28.0831, 30.3916] +24-11-19 20:28:51 | D | best error = [ 3.5775, 3.5775, 3.5775, 3.5775, 3.5775] +24-11-19 20:28:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:51 | D | sum error = [ 32.8068, 35.4630, 38.3581, 41.2321, 44.2702] +24-11-19 20:28:51 | D | best error = [ 3.5775, 3.5775, 3.5775, 3.5775, 3.5775] +24-11-19 20:28:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:51 | D | sum error = [ 47.4302, 50.9234, 53.9796, 58.4238, 62.3315] +24-11-19 20:28:51 | D | best error = [ 3.5775, 3.5775, 3.5775, 3.5775, 3.5775] +24-11-19 20:28:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:51 | D | sum error = [ 67.0102, 71.8414, 76.7739, 81.8275, 87.2247] +24-11-19 20:28:51 | D | best error = [ 3.5775, 3.5775, 3.5775, 3.5775, 3.5775] +24-11-19 20:28:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:51 | D | sum error = [ 92.9181, 99.1757, 106.2024, 113.3858, 120.8831] +24-11-19 20:28:51 | D | best error = [ 3.5775, 3.5775, 3.5775, 3.5775, 3.5775] +24-11-19 20:28:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:51 | D | sum error = [ 129.0344, 137.5848, 146.6952, 156.6748, 166.8325] +24-11-19 20:28:51 | D | best error = [ 3.5775, 3.5775, 3.5775, 3.5775, 3.5775] +24-11-19 20:28:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:51 | D | sum error = [ 177.2251, 188.7724, 200.3682, 212.9054, 226.8630] +24-11-19 20:28:51 | D | best error = [ 3.5775, 3.5775, 3.5775, 3.5775, 3.5775] +24-11-19 20:28:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:51 | D | sum error = [ 241.8612, 257.0972, 273.2780, 290.2642, 308.1298] +24-11-19 20:28:51 | D | best error = [ 3.5775, 3.5775, 3.5775, 3.5775, 3.5775] +24-11-19 20:28:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:51 | D | sum error = [ 326.1689, 345.3223, 365.2619, 385.6032, 406.7334] +24-11-19 20:28:51 | D | best error = [ 3.5775, 3.5775, 3.5775, 3.5775, 3.5775] +24-11-19 20:28:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:51 | D | sum error = [ 428.8381, 451.7011, 475.0663, 498.8413, 523.2054] +24-11-19 20:28:51 | D | best error = [ 3.5775, 3.5775, 3.5775, 3.5775, 3.5775] +24-11-19 20:28:51 | D | + error = [3.5775] +24-11-19 20:28:52 | D | - Calibrating model.layers.12.self_attn.v_proj.weight +24-11-19 20:28:52 | D | + w: sint8 +24-11-19 20:28:52 | D | + x: None +24-11-19 20:28:52 | D | + y: None +24-11-19 20:28:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:52 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:28:52 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:28:52 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:28:52 | D | - range ratio = [ 1.0000] +24-11-19 20:28:52 | D | sum error = [ 1.4830] +24-11-19 20:28:52 | D | best error = [ 1.4830] +24-11-19 20:28:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:52 | D | sum error = [ 1.4766, 1.4615, 1.4630, 1.4769, 1.5103] +24-11-19 20:28:52 | D | best error = [ 1.3706, 1.3280, 1.3040, 1.2913, 1.2851] +24-11-19 20:28:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:52 | D | sum error = [ 1.5585, 1.6066, 1.6758, 1.7462, 1.8505] +24-11-19 20:28:52 | D | best error = [ 1.2827, 1.2816, 1.2813, 1.2813, 1.2813] +24-11-19 20:28:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:52 | D | sum error = [ 1.9547, 2.0593, 2.2076, 2.3605, 2.5322] +24-11-19 20:28:52 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 20:28:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:52 | D | sum error = [ 2.6901, 2.8793, 3.0992, 3.3176, 3.5564] +24-11-19 20:28:52 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 20:28:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:52 | D | sum error = [ 3.8150, 4.1024, 4.3671, 4.6764, 4.9913] +24-11-19 20:28:52 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 20:28:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:52 | D | sum error = [ 5.3541, 5.6954, 6.0710, 6.4641, 6.8866] +24-11-19 20:28:52 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 20:28:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:52 | D | sum error = [ 7.3191, 7.7912, 8.2879, 8.8144, 9.3727] +24-11-19 20:28:52 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 20:28:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:52 | D | sum error = [ 9.9516, 10.5887, 11.2227, 11.9153, 12.6187] +24-11-19 20:28:52 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 20:28:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:52 | D | sum error = [ 13.3743, 14.1610, 14.9865, 15.8653, 16.7672] +24-11-19 20:28:52 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 20:28:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:52 | D | sum error = [ 17.7346, 18.7319, 19.7905, 20.9008, 22.0486] +24-11-19 20:28:52 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 20:28:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:52 | D | sum error = [ 23.2562, 24.5111, 25.8253, 27.2025, 28.6387] +24-11-19 20:28:52 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 20:28:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:52 | D | sum error = [ 30.1279, 31.6758, 33.2884, 34.9686, 36.7126] +24-11-19 20:28:52 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 20:28:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:52 | D | sum error = [ 38.5214, 40.3986, 42.3432, 44.3634, 46.4458] +24-11-19 20:28:52 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 20:28:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:52 | D | sum error = [ 48.6074, 50.8596, 53.1745, 55.5873, 58.0888] +24-11-19 20:28:52 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 20:28:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:52 | D | sum error = [ 60.6727, 63.3413, 66.1045, 68.9448, 71.8761] +24-11-19 20:28:52 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 20:28:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:52 | D | sum error = [ 74.9025, 78.0122, 81.2211, 84.5213, 87.9258] +24-11-19 20:28:52 | D | best error = [ 1.2813, 1.2813, 1.2813, 1.2813, 1.2813] +24-11-19 20:28:52 | D | + error = [1.2813] +24-11-19 20:28:52 | D | - Calibrating model.layers.12.self_attn.o_proj.weight +24-11-19 20:28:52 | D | + w: sint8 +24-11-19 20:28:52 | D | + x: None +24-11-19 20:28:52 | D | + y: None +24-11-19 20:28:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:52 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:28:52 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:52 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:52 | D | - range ratio = [ 1.0000] +24-11-19 20:28:52 | D | sum error = [ 0.6289] +24-11-19 20:28:52 | D | best error = [ 0.6289] +24-11-19 20:28:53 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:53 | D | sum error = [ 0.6250, 0.6200, 0.6215, 0.6243, 0.6330] +24-11-19 20:28:53 | D | best error = [ 0.5732, 0.5483, 0.5348, 0.5259, 0.5200] +24-11-19 20:28:53 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:53 | D | sum error = [ 0.6442, 0.6590, 0.6755, 0.6964, 0.7224] +24-11-19 20:28:53 | D | best error = [ 0.5164, 0.5137, 0.5122, 0.5112, 0.5104] +24-11-19 20:28:53 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:53 | D | sum error = [ 0.7579, 0.7926, 0.8321, 0.8777, 0.9335] +24-11-19 20:28:53 | D | best error = [ 0.5100, 0.5098, 0.5096, 0.5096, 0.5095] +24-11-19 20:28:53 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:53 | D | sum error = [ 0.9845, 1.0463, 1.1124, 1.1853, 1.2639] +24-11-19 20:28:53 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:53 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:53 | D | sum error = [ 1.3422, 1.4332, 1.5256, 1.6274, 1.7308] +24-11-19 20:28:53 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:53 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:53 | D | sum error = [ 1.8447, 1.9604, 2.0879, 2.2213, 2.3596] +24-11-19 20:28:53 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:53 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:53 | D | sum error = [ 2.5072, 2.6611, 2.8227, 2.9967, 3.1770] +24-11-19 20:28:53 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:53 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:53 | D | sum error = [ 3.3625, 3.5631, 3.7723, 3.9893, 4.2195] +24-11-19 20:28:53 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:53 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:53 | D | sum error = [ 4.4534, 4.7080, 4.9696, 5.2450, 5.5313] +24-11-19 20:28:53 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:53 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:53 | D | sum error = [ 5.8293, 6.1455, 6.4713, 6.8134, 7.1666] +24-11-19 20:28:53 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:53 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:53 | D | sum error = [ 7.5353, 7.9201, 8.3154, 8.7280, 9.1563] +24-11-19 20:28:53 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:53 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:53 | D | sum error = [ 9.5974, 10.0583, 10.5332, 11.0281, 11.5384] +24-11-19 20:28:53 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:53 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:53 | D | sum error = [ 12.0653, 12.6100, 13.1717, 13.7518, 14.3504] +24-11-19 20:28:53 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:53 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:53 | D | sum error = [ 14.9626, 15.5949, 16.2469, 16.9157, 17.6016] +24-11-19 20:28:53 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:53 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:53 | D | sum error = [ 18.3064, 19.0292, 19.7716, 20.5327, 21.3137] +24-11-19 20:28:53 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:53 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:53 | D | sum error = [ 22.1188, 22.9431, 23.7848, 24.6463, 25.5304] +24-11-19 20:28:53 | D | best error = [ 0.5095, 0.5095, 0.5095, 0.5095, 0.5095] +24-11-19 20:28:53 | D | + error = [0.5095] +24-11-19 20:28:53 | D | - Calibrating model.layers.12.mlp.up_proj.weight +24-11-19 20:28:53 | D | + w: sint8 +24-11-19 20:28:53 | D | + x: None +24-11-19 20:28:53 | D | + y: None +24-11-19 20:28:53 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:53 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:53 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:53 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:53 | D | - range ratio = [ 1.0000] +24-11-19 20:28:53 | D | sum error = [ 5.0366] +24-11-19 20:28:53 | D | best error = [ 5.0366] +24-11-19 20:28:54 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:54 | D | sum error = [ 4.9991, 4.9832, 5.0030, 5.0551, 5.1622] +24-11-19 20:28:54 | D | best error = [ 4.6633, 4.5224, 4.4471, 4.4068, 4.3857] +24-11-19 20:28:54 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:54 | D | sum error = [ 5.2900, 5.4587, 5.6777, 5.9659, 6.2835] +24-11-19 20:28:54 | D | best error = [ 4.3742, 4.3695, 4.3675, 4.3670, 4.3668] +24-11-19 20:28:54 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:54 | D | sum error = [ 6.6253, 7.0488, 7.5110, 8.0189, 8.5748] +24-11-19 20:28:54 | D | best error = [ 4.3668, 4.3668, 4.3668, 4.3668, 4.3668] +24-11-19 20:28:54 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:54 | D | sum error = [ 9.1852, 9.8435, 10.5493, 11.3059, 12.1205] +24-11-19 20:28:54 | D | best error = [ 4.3668, 4.3668, 4.3668, 4.3668, 4.3668] +24-11-19 20:28:54 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:54 | D | sum error = [ 12.9943, 13.9325, 14.9021, 15.9494, 17.0560] +24-11-19 20:28:54 | D | best error = [ 4.3668, 4.3668, 4.3668, 4.3668, 4.3668] +24-11-19 20:28:54 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:54 | D | sum error = [ 18.2420, 19.4998, 20.8226, 22.2130, 23.7029] +24-11-19 20:28:54 | D | best error = [ 4.3668, 4.3668, 4.3668, 4.3668, 4.3668] +24-11-19 20:28:54 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:54 | D | sum error = [ 25.2611, 26.9169, 28.6585, 30.4928, 32.4458] +24-11-19 20:28:54 | D | best error = [ 4.3668, 4.3668, 4.3668, 4.3668, 4.3668] +24-11-19 20:28:54 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:54 | D | sum error = [ 34.4734, 36.6294, 38.9024, 41.2865, 43.7985] +24-11-19 20:28:54 | D | best error = [ 4.3668, 4.3668, 4.3668, 4.3668, 4.3668] +24-11-19 20:28:54 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:54 | D | sum error = [ 46.4299, 49.2229, 52.1408, 55.2076, 58.4339] +24-11-19 20:28:54 | D | best error = [ 4.3668, 4.3668, 4.3668, 4.3668, 4.3668] +24-11-19 20:28:54 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:54 | D | sum error = [ 61.8131, 65.3609, 69.0857, 72.9909, 77.0853] +24-11-19 20:28:54 | D | best error = [ 4.3668, 4.3668, 4.3668, 4.3668, 4.3668] +24-11-19 20:28:54 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:54 | D | sum error = [ 81.3674, 85.8482, 90.5391, 95.4258, 100.5475] +24-11-19 20:28:54 | D | best error = [ 4.3668, 4.3668, 4.3668, 4.3668, 4.3668] +24-11-19 20:28:54 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:54 | D | sum error = [ 105.8821, 111.4640, 117.2831, 123.3518, 129.6900] +24-11-19 20:28:54 | D | best error = [ 4.3668, 4.3668, 4.3668, 4.3668, 4.3668] +24-11-19 20:28:54 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:54 | D | sum error = [ 136.2840, 143.1559, 150.3003, 157.7286, 165.4541] +24-11-19 20:28:54 | D | best error = [ 4.3668, 4.3668, 4.3668, 4.3668, 4.3668] +24-11-19 20:28:54 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:54 | D | sum error = [ 173.4756, 181.8208, 190.4652, 199.4482, 208.7629] +24-11-19 20:28:54 | D | best error = [ 4.3668, 4.3668, 4.3668, 4.3668, 4.3668] +24-11-19 20:28:54 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:54 | D | sum error = [ 218.3997, 228.3973, 238.7247, 249.4071, 260.4224] +24-11-19 20:28:54 | D | best error = [ 4.3668, 4.3668, 4.3668, 4.3668, 4.3668] +24-11-19 20:28:54 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:54 | D | sum error = [ 271.7969, 283.5395, 295.6547, 308.1392, 320.9910] +24-11-19 20:28:54 | D | best error = [ 4.3668, 4.3668, 4.3668, 4.3668, 4.3668] +24-11-19 20:28:54 | D | + error = [4.3668] +24-11-19 20:28:54 | D | - Calibrating model.layers.12.mlp.gate_proj.weight +24-11-19 20:28:54 | D | + w: sint8 +24-11-19 20:28:54 | D | + x: None +24-11-19 20:28:54 | D | + y: None +24-11-19 20:28:54 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:54 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:55 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:55 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:55 | D | - range ratio = [ 1.0000] +24-11-19 20:28:55 | D | sum error = [ 5.9745] +24-11-19 20:28:55 | D | best error = [ 5.9745] +24-11-19 20:28:56 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:56 | D | sum error = [ 5.9570, 5.9289, 5.9472, 6.0207, 6.1547] +24-11-19 20:28:56 | D | best error = [ 5.5441, 5.3802, 5.2908, 5.2420, 5.2173] +24-11-19 20:28:56 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:56 | D | sum error = [ 6.3066, 6.5199, 6.7917, 7.1287, 7.4831] +24-11-19 20:28:56 | D | best error = [ 5.2051, 5.1999, 5.1979, 5.1974, 5.1972] +24-11-19 20:28:56 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:56 | D | sum error = [ 7.9523, 8.4359, 9.0023, 9.6157, 10.3269] +24-11-19 20:28:56 | D | best error = [ 5.1972, 5.1972, 5.1972, 5.1972, 5.1972] +24-11-19 20:28:56 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:56 | D | sum error = [ 11.0721, 11.8820, 12.7621, 13.7102, 14.7453] +24-11-19 20:28:56 | D | best error = [ 5.1972, 5.1972, 5.1972, 5.1972, 5.1972] +24-11-19 20:28:56 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:56 | D | sum error = [ 15.8367, 17.0187, 18.2574, 19.6105, 21.0407] +24-11-19 20:28:56 | D | best error = [ 5.1972, 5.1972, 5.1972, 5.1972, 5.1972] +24-11-19 20:28:56 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:56 | D | sum error = [ 22.5982, 24.2124, 25.9554, 27.8393, 29.8089] +24-11-19 20:28:56 | D | best error = [ 5.1972, 5.1972, 5.1972, 5.1972, 5.1972] +24-11-19 20:28:56 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:56 | D | sum error = [ 31.9260, 34.1833, 36.5886, 39.1223, 41.8438] +24-11-19 20:28:56 | D | best error = [ 5.1972, 5.1972, 5.1972, 5.1972, 5.1972] +24-11-19 20:28:56 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:56 | D | sum error = [ 44.7144, 47.7782, 51.0602, 54.5150, 58.2049] +24-11-19 20:28:56 | D | best error = [ 5.1972, 5.1972, 5.1972, 5.1972, 5.1972] +24-11-19 20:28:56 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:56 | D | sum error = [ 62.1235, 66.2850, 70.6884, 75.4196, 80.3989] +24-11-19 20:28:56 | D | best error = [ 5.1972, 5.1972, 5.1972, 5.1972, 5.1972] +24-11-19 20:28:56 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:56 | D | sum error = [ 85.6794, 91.3070, 97.2588, 103.5586, 110.2598] +24-11-19 20:28:56 | D | best error = [ 5.1972, 5.1972, 5.1972, 5.1972, 5.1972] +24-11-19 20:28:56 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:56 | D | sum error = [ 117.3575, 124.8387, 132.7882, 141.1963, 150.0778] +24-11-19 20:28:56 | D | best error = [ 5.1972, 5.1972, 5.1972, 5.1972, 5.1972] +24-11-19 20:28:56 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:56 | D | sum error = [ 159.4500, 169.3121, 179.6986, 190.6591, 202.1785] +24-11-19 20:28:56 | D | best error = [ 5.1972, 5.1972, 5.1972, 5.1972, 5.1972] +24-11-19 20:28:56 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:56 | D | sum error = [ 214.2956, 227.0706, 240.4577, 254.5177, 269.2169] +24-11-19 20:28:56 | D | best error = [ 5.1972, 5.1972, 5.1972, 5.1972, 5.1972] +24-11-19 20:28:56 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:56 | D | sum error = [ 284.5961, 300.7079, 317.5276, 335.0923, 353.3989] +24-11-19 20:28:56 | D | best error = [ 5.1972, 5.1972, 5.1972, 5.1972, 5.1972] +24-11-19 20:28:56 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:56 | D | sum error = [ 372.4631, 392.2731, 412.8802, 434.2757, 456.4649] +24-11-19 20:28:56 | D | best error = [ 5.1972, 5.1972, 5.1972, 5.1972, 5.1972] +24-11-19 20:28:56 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:56 | D | sum error = [ 479.4566, 503.2084, 527.7715, 553.1081, 579.2521] +24-11-19 20:28:56 | D | best error = [ 5.1972, 5.1972, 5.1972, 5.1972, 5.1972] +24-11-19 20:28:56 | D | + error = [5.1972] +24-11-19 20:28:56 | D | - Calibrating model.layers.12.mlp.down_proj.weight +24-11-19 20:28:56 | D | + w: sint8 +24-11-19 20:28:56 | D | + x: None +24-11-19 20:28:56 | D | + y: None +24-11-19 20:28:56 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:28:56 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:28:56 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:28:56 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:28:56 | D | - range ratio = [ 1.0000] +24-11-19 20:28:56 | D | sum error = [ 0.6718] +24-11-19 20:28:56 | D | best error = [ 0.6718] +24-11-19 20:28:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:28:57 | D | sum error = [ 0.6655, 0.6622, 0.6577, 0.6568, 0.6570] +24-11-19 20:28:57 | D | best error = [ 0.6427, 0.6294, 0.6205, 0.6136, 0.6089] +24-11-19 20:28:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:28:57 | D | sum error = [ 0.6588, 0.6633, 0.6711, 0.6818, 0.6946] +24-11-19 20:28:57 | D | best error = [ 0.6053, 0.6024, 0.6004, 0.5992, 0.5980] +24-11-19 20:28:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:28:57 | D | sum error = [ 0.7111, 0.7315, 0.7555, 0.7835, 0.8156] +24-11-19 20:28:57 | D | best error = [ 0.5974, 0.5970, 0.5967, 0.5964, 0.5962] +24-11-19 20:28:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:28:57 | D | sum error = [ 0.8549, 0.8959, 0.9423, 0.9943, 1.0517] +24-11-19 20:28:57 | D | best error = [ 0.5961, 0.5961, 0.5961, 0.5960, 0.5960] +24-11-19 20:28:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:28:57 | D | sum error = [ 1.1160, 1.1819, 1.2567, 1.3388, 1.4232] +24-11-19 20:28:57 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 20:28:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:28:57 | D | sum error = [ 1.5142, 1.6153, 1.7216, 1.8352, 1.9585] +24-11-19 20:28:57 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 20:28:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:28:57 | D | sum error = [ 2.0885, 2.2277, 2.3749, 2.5319, 2.6981] +24-11-19 20:28:57 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 20:28:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:28:57 | D | sum error = [ 2.8758, 3.0634, 3.2631, 3.4736, 3.6964] +24-11-19 20:28:57 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 20:28:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:28:57 | D | sum error = [ 3.9332, 4.1819, 4.4467, 4.7255, 5.0212] +24-11-19 20:28:57 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 20:28:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:28:57 | D | sum error = [ 5.3305, 5.6588, 6.0038, 6.3687, 6.7519] +24-11-19 20:28:57 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 20:28:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:28:57 | D | sum error = [ 7.1550, 7.5799, 8.0253, 8.4943, 8.9852] +24-11-19 20:28:57 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 20:28:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:28:57 | D | sum error = [ 9.5012, 10.0423, 10.6073, 11.2004, 11.8206] +24-11-19 20:28:57 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 20:28:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:28:57 | D | sum error = [ 12.4706, 13.1506, 13.8623, 14.6033, 15.3780] +24-11-19 20:28:57 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 20:28:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:28:57 | D | sum error = [ 16.1863, 17.0294, 17.9081, 18.8245, 19.7754] +24-11-19 20:28:57 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 20:28:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:28:57 | D | sum error = [ 20.7673, 21.7988, 22.8697, 23.9828, 25.1385] +24-11-19 20:28:57 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 20:28:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:28:57 | D | sum error = [ 26.3363, 27.5774, 28.8619, 30.1931, 31.5687] +24-11-19 20:28:57 | D | best error = [ 0.5960, 0.5960, 0.5960, 0.5960, 0.5960] +24-11-19 20:28:57 | D | + error = [0.5960] +24-11-19 20:28:58 | D | - Quantizing model.layers.12.self_attn.q_proj.weight +24-11-19 20:28:58 | D | - Quantizing model.layers.12.self_attn.k_proj.weight +24-11-19 20:28:59 | D | - Quantizing model.layers.12.self_attn.v_proj.weight +24-11-19 20:29:00 | D | - Quantizing model.layers.12.self_attn.o_proj.weight +24-11-19 20:29:01 | D | - Quantizing model.layers.12.mlp.up_proj.weight +24-11-19 20:29:02 | D | - Quantizing model.layers.12.mlp.gate_proj.weight +24-11-19 20:29:04 | D | - Quantizing model.layers.12.mlp.down_proj.weight +24-11-19 20:29:15 | D | - Quantizing layer model.layers.13 +24-11-19 20:29:15 | D | - Calibrating model.layers.13.self_attn.q_proj.weight +24-11-19 20:29:15 | D | + w: sint8 +24-11-19 20:29:15 | D | + x: None +24-11-19 20:29:15 | D | + y: None +24-11-19 20:29:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:29:15 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:29:15 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:29:15 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:29:15 | D | - range ratio = [ 1.0000] +24-11-19 20:29:15 | D | sum error = [ 5.3675] +24-11-19 20:29:15 | D | best error = [ 5.3675] +24-11-19 20:29:28 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:28 | D | sum error = [ 5.4238, 5.4320, 5.5983, 5.6060, 5.4170] +24-11-19 20:29:28 | D | best error = [ 5.3675, 5.3675, 5.3675, 5.3675, 5.3675] +24-11-19 20:29:28 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:28 | D | sum error = [ 5.6324, 5.9634, 5.9258, 6.2992, 6.8072] +24-11-19 20:29:28 | D | best error = [ 5.3675, 5.3675, 5.3675, 5.3675, 5.3675] +24-11-19 20:29:28 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:28 | D | sum error = [ 7.1036, 7.4669, 8.1326, 8.7265, 9.4604] +24-11-19 20:29:28 | D | best error = [ 5.3675, 5.3675, 5.3675, 5.3675, 5.3675] +24-11-19 20:29:28 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:28 | D | sum error = [ 9.9534, 10.6502, 11.5594, 12.4221, 13.2478] +24-11-19 20:29:28 | D | best error = [ 5.3675, 5.3675, 5.3675, 5.3675, 5.3675] +24-11-19 20:29:28 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:28 | D | sum error = [ 14.5685, 15.4081, 16.9953, 18.2326, 19.6513] +24-11-19 20:29:28 | D | best error = [ 5.3675, 5.3675, 5.3675, 5.3675, 5.3675] +24-11-19 20:29:28 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:28 | D | sum error = [ 21.2712, 22.7309, 24.7023, 26.4518, 28.5244] +24-11-19 20:29:28 | D | best error = [ 5.3675, 5.3675, 5.3675, 5.3675, 5.3675] +24-11-19 20:29:28 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:28 | D | sum error = [ 30.8558, 33.3142, 35.9237, 38.5756, 41.4965] +24-11-19 20:29:28 | D | best error = [ 5.3675, 5.3675, 5.3675, 5.3675, 5.3675] +24-11-19 20:29:28 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:28 | D | sum error = [ 44.5069, 47.6727, 51.1222, 54.6737, 58.7785] +24-11-19 20:29:28 | D | best error = [ 5.3675, 5.3675, 5.3675, 5.3675, 5.3675] +24-11-19 20:29:28 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:28 | D | sum error = [ 62.6464, 67.0086, 71.7580, 76.5129, 81.6604] +24-11-19 20:29:28 | D | best error = [ 5.3675, 5.3675, 5.3675, 5.3675, 5.3675] +24-11-19 20:29:28 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:28 | D | sum error = [ 87.1299, 92.7017, 98.7554, 104.9133, 111.6415] +24-11-19 20:29:28 | D | best error = [ 5.3675, 5.3675, 5.3675, 5.3675, 5.3675] +24-11-19 20:29:28 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:28 | D | sum error = [ 118.4862, 125.8632, 133.7450, 141.9230, 150.5900] +24-11-19 20:29:28 | D | best error = [ 5.3675, 5.3675, 5.3675, 5.3675, 5.3675] +24-11-19 20:29:28 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:28 | D | sum error = [ 159.3729, 168.9863, 178.9757, 189.5308, 200.5371] +24-11-19 20:29:28 | D | best error = [ 5.3675, 5.3675, 5.3675, 5.3675, 5.3675] +24-11-19 20:29:28 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:28 | D | sum error = [ 211.9128, 223.8668, 236.3259, 249.3486, 262.9117] +24-11-19 20:29:28 | D | best error = [ 5.3675, 5.3675, 5.3675, 5.3675, 5.3675] +24-11-19 20:29:28 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:28 | D | sum error = [ 277.1346, 291.8395, 307.2502, 323.1192, 339.6568] +24-11-19 20:29:28 | D | best error = [ 5.3675, 5.3675, 5.3675, 5.3675, 5.3675] +24-11-19 20:29:28 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:28 | D | sum error = [ 356.8417, 374.4175, 392.7231, 411.4991, 430.7611] +24-11-19 20:29:28 | D | best error = [ 5.3675, 5.3675, 5.3675, 5.3675, 5.3675] +24-11-19 20:29:28 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:28 | D | sum error = [ 450.6118, 470.8902, 491.5841, 512.5551, 533.9538] +24-11-19 20:29:28 | D | best error = [ 5.3675, 5.3675, 5.3675, 5.3675, 5.3675] +24-11-19 20:29:28 | D | + error = [5.3675] +24-11-19 20:29:28 | D | - Calibrating model.layers.13.self_attn.k_proj.weight +24-11-19 20:29:28 | D | + w: sint8 +24-11-19 20:29:28 | D | + x: None +24-11-19 20:29:28 | D | + y: None +24-11-19 20:29:28 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:29:28 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:29:28 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:29:28 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:28 | D | - range ratio = [ 1.0000] +24-11-19 20:29:28 | D | sum error = [ 4.2823] +24-11-19 20:29:28 | D | best error = [ 4.2823] +24-11-19 20:29:41 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:41 | D | sum error = [ 4.0497, 3.9515, 4.2880, 4.2461, 4.3760] +24-11-19 20:29:41 | D | best error = [ 4.0497, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:29:41 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:41 | D | sum error = [ 4.3221, 4.8506, 4.7499, 4.9547, 4.9650] +24-11-19 20:29:41 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:29:41 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:41 | D | sum error = [ 5.4934, 5.7386, 6.0687, 6.3229, 7.1649] +24-11-19 20:29:41 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:29:41 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:41 | D | sum error = [ 7.5880, 8.2354, 8.8980, 9.2506, 10.0678] +24-11-19 20:29:41 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:29:41 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:41 | D | sum error = [ 11.1131, 11.9437, 13.0990, 14.1468, 15.2724] +24-11-19 20:29:41 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:29:41 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:41 | D | sum error = [ 16.3848, 17.6749, 19.1968, 21.0981, 23.3017] +24-11-19 20:29:41 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:29:41 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:41 | D | sum error = [ 23.9711, 26.6035, 28.5695, 31.1530, 34.0306] +24-11-19 20:29:41 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:29:41 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:41 | D | sum error = [ 36.4156, 40.0551, 43.3333, 46.5954, 50.3104] +24-11-19 20:29:41 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:29:41 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:41 | D | sum error = [ 54.0018, 57.8128, 62.6191, 67.7655, 72.8690] +24-11-19 20:29:41 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:29:41 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:41 | D | sum error = [ 77.8906, 84.3618, 89.9026, 96.5391, 103.8918] +24-11-19 20:29:41 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:29:41 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:41 | D | sum error = [ 111.0413, 119.0957, 127.3526, 135.9408, 144.7330] +24-11-19 20:29:41 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:29:41 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:41 | D | sum error = [ 154.3687, 163.6559, 173.9952, 184.9767, 195.7502] +24-11-19 20:29:41 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:29:41 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:41 | D | sum error = [ 207.4922, 219.3499, 231.8114, 244.2445, 257.2649] +24-11-19 20:29:41 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:29:41 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:41 | D | sum error = [ 270.5652, 284.6851, 298.8993, 313.6351, 328.9346] +24-11-19 20:29:41 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:29:41 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:41 | D | sum error = [ 345.2137, 361.7876, 378.9996, 397.1662, 415.8023] +24-11-19 20:29:41 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:29:41 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:41 | D | sum error = [ 434.9616, 454.7448, 475.3305, 496.4506, 518.0782] +24-11-19 20:29:41 | D | best error = [ 3.9515, 3.9515, 3.9515, 3.9515, 3.9515] +24-11-19 20:29:41 | D | + error = [3.9515] +24-11-19 20:29:41 | D | - Calibrating model.layers.13.self_attn.v_proj.weight +24-11-19 20:29:41 | D | + w: sint8 +24-11-19 20:29:41 | D | + x: None +24-11-19 20:29:41 | D | + y: None +24-11-19 20:29:41 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:41 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:29:41 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:29:41 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:41 | D | - range ratio = [ 1.0000] +24-11-19 20:29:41 | D | sum error = [ 1.5428] +24-11-19 20:29:41 | D | best error = [ 1.5428] +24-11-19 20:29:41 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:41 | D | sum error = [ 1.5350, 1.5291, 1.5368, 1.5638, 1.5954] +24-11-19 20:29:41 | D | best error = [ 1.4093, 1.3642, 1.3424, 1.3299, 1.3237] +24-11-19 20:29:41 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:41 | D | sum error = [ 1.6296, 1.6694, 1.7427, 1.8535, 1.9289] +24-11-19 20:29:41 | D | best error = [ 1.3197, 1.3180, 1.3177, 1.3176, 1.3176] +24-11-19 20:29:41 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:41 | D | sum error = [ 2.0450, 2.1626, 2.3127, 2.4614, 2.6433] +24-11-19 20:29:41 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:29:41 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:41 | D | sum error = [ 2.8114, 3.0145, 3.2199, 3.4621, 3.6949] +24-11-19 20:29:41 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:29:41 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:41 | D | sum error = [ 3.9478, 4.2212, 4.5171, 4.8289, 5.1522] +24-11-19 20:29:41 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:29:41 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:41 | D | sum error = [ 5.4972, 5.8584, 6.2740, 6.6815, 7.1182] +24-11-19 20:29:41 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:29:41 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:41 | D | sum error = [ 7.5800, 8.0736, 8.6015, 9.1444, 9.7152] +24-11-19 20:29:41 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:29:41 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:41 | D | sum error = [ 10.3166, 10.9585, 11.6357, 12.3358, 13.0785] +24-11-19 20:29:41 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:29:41 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:41 | D | sum error = [ 13.8629, 14.6679, 15.5410, 16.4330, 17.3833] +24-11-19 20:29:41 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:29:41 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:41 | D | sum error = [ 18.3758, 19.4148, 20.4997, 21.6437, 22.8291] +24-11-19 20:29:41 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:29:41 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:41 | D | sum error = [ 24.0747, 25.3793, 26.7425, 28.1613, 29.6332] +24-11-19 20:29:41 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:29:41 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:41 | D | sum error = [ 31.1735, 32.7545, 34.4262, 36.1651, 37.9661] +24-11-19 20:29:41 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:29:41 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:41 | D | sum error = [ 39.8518, 41.8063, 43.8320, 45.9404, 48.1343] +24-11-19 20:29:41 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:29:41 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:41 | D | sum error = [ 50.3993, 52.7434, 55.1726, 57.6821, 60.2814] +24-11-19 20:29:41 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:29:41 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:41 | D | sum error = [ 62.9660, 65.7389, 68.6048, 71.5647, 74.6222] +24-11-19 20:29:41 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:29:41 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:41 | D | sum error = [ 77.7627, 81.0105, 84.3472, 87.7832, 91.3226] +24-11-19 20:29:41 | D | best error = [ 1.3176, 1.3176, 1.3176, 1.3176, 1.3176] +24-11-19 20:29:41 | D | + error = [1.3176] +24-11-19 20:29:41 | D | - Calibrating model.layers.13.self_attn.o_proj.weight +24-11-19 20:29:41 | D | + w: sint8 +24-11-19 20:29:41 | D | + x: None +24-11-19 20:29:41 | D | + y: None +24-11-19 20:29:41 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:41 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:29:41 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:29:42 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:42 | D | - range ratio = [ 1.0000] +24-11-19 20:29:42 | D | sum error = [ 0.6588] +24-11-19 20:29:42 | D | best error = [ 0.6588] +24-11-19 20:29:42 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:42 | D | sum error = [ 0.6569, 0.6514, 0.6566, 0.6617, 0.6734] +24-11-19 20:29:42 | D | best error = [ 0.5910, 0.5595, 0.5430, 0.5318, 0.5248] +24-11-19 20:29:42 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:42 | D | sum error = [ 0.6896, 0.7039, 0.7348, 0.7634, 0.7994] +24-11-19 20:29:42 | D | best error = [ 0.5198, 0.5166, 0.5144, 0.5129, 0.5119] +24-11-19 20:29:42 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:42 | D | sum error = [ 0.8402, 0.8837, 0.9338, 0.9910, 1.0525] +24-11-19 20:29:42 | D | best error = [ 0.5114, 0.5110, 0.5108, 0.5106, 0.5105] +24-11-19 20:29:42 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:42 | D | sum error = [ 1.1177, 1.1877, 1.2632, 1.3458, 1.4344] +24-11-19 20:29:42 | D | best error = [ 0.5105, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:42 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:42 | D | sum error = [ 1.5245, 1.6276, 1.7295, 1.8399, 1.9527] +24-11-19 20:29:42 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:42 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:42 | D | sum error = [ 2.0768, 2.2061, 2.3416, 2.4839, 2.6291] +24-11-19 20:29:42 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:42 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:42 | D | sum error = [ 2.7886, 2.9508, 3.1279, 3.3051, 3.4927] +24-11-19 20:29:42 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:42 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:42 | D | sum error = [ 3.6904, 3.8974, 4.1133, 4.3375, 4.5716] +24-11-19 20:29:42 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:42 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:42 | D | sum error = [ 4.8163, 5.0719, 5.3363, 5.6192, 5.9095] +24-11-19 20:29:42 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:42 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:42 | D | sum error = [ 6.2093, 6.5237, 6.8501, 7.1835, 7.5352] +24-11-19 20:29:42 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:42 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:42 | D | sum error = [ 7.8951, 8.2699, 8.6553, 9.0569, 9.4681] +24-11-19 20:29:42 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:42 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:42 | D | sum error = [ 9.8943, 10.3320, 10.7808, 11.2485, 11.7247] +24-11-19 20:29:42 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:42 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:42 | D | sum error = [ 12.2158, 12.7228, 13.2431, 13.7810, 14.3284] +24-11-19 20:29:42 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:42 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:42 | D | sum error = [ 14.8916, 15.4736, 16.0662, 16.6793, 17.3053] +24-11-19 20:29:42 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:42 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:42 | D | sum error = [ 17.9512, 18.6127, 19.2888, 19.9899, 20.7110] +24-11-19 20:29:42 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:42 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:42 | D | sum error = [ 21.4518, 22.2134, 22.9959, 23.8035, 24.6393] +24-11-19 20:29:42 | D | best error = [ 0.5104, 0.5104, 0.5104, 0.5104, 0.5104] +24-11-19 20:29:42 | D | + error = [0.5104] +24-11-19 20:29:42 | D | - Calibrating model.layers.13.mlp.up_proj.weight +24-11-19 20:29:42 | D | + w: sint8 +24-11-19 20:29:42 | D | + x: None +24-11-19 20:29:42 | D | + y: None +24-11-19 20:29:42 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:42 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:29:42 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:29:42 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:42 | D | - range ratio = [ 1.0000] +24-11-19 20:29:42 | D | sum error = [ 5.2102] +24-11-19 20:29:42 | D | best error = [ 5.2102] +24-11-19 20:29:44 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:44 | D | sum error = [ 5.1757, 5.1701, 5.2002, 5.2597, 5.3389] +24-11-19 20:29:44 | D | best error = [ 4.8356, 4.6921, 4.6134, 4.5707, 4.5482] +24-11-19 20:29:44 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:44 | D | sum error = [ 5.4806, 5.6728, 5.9000, 6.1788, 6.5040] +24-11-19 20:29:44 | D | best error = [ 4.5359, 4.5308, 4.5290, 4.5284, 4.5282] +24-11-19 20:29:44 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:44 | D | sum error = [ 6.8675, 7.3068, 7.7922, 8.3069, 8.8933] +24-11-19 20:29:44 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:29:44 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:44 | D | sum error = [ 9.4960, 10.1877, 10.9180, 11.6994, 12.5264] +24-11-19 20:29:44 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:29:44 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:44 | D | sum error = [ 13.4340, 14.3896, 15.4123, 16.5009, 17.6428] +24-11-19 20:29:44 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:29:44 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:44 | D | sum error = [ 18.8569, 20.1545, 21.5269, 22.9633, 24.4982] +24-11-19 20:29:44 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:29:44 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:44 | D | sum error = [ 26.0932, 27.8184, 29.6190, 31.4964, 33.5093] +24-11-19 20:29:44 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:29:44 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:44 | D | sum error = [ 35.6125, 37.8440, 40.1721, 42.6393, 45.2260] +24-11-19 20:29:44 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:29:44 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:44 | D | sum error = [ 47.9568, 50.8044, 53.8130, 56.9847, 60.2815] +24-11-19 20:29:44 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:29:44 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:44 | D | sum error = [ 63.7636, 67.4111, 71.2420, 75.2470, 79.4448] +24-11-19 20:29:44 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:29:44 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:44 | D | sum error = [ 83.8205, 88.4226, 93.2231, 98.2383, 103.4799] +24-11-19 20:29:44 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:29:44 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:44 | D | sum error = [ 108.9464, 114.6504, 120.6141, 126.8272, 133.3032] +24-11-19 20:29:44 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:29:44 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:44 | D | sum error = [ 140.0323, 147.0580, 154.3509, 161.9400, 169.8333] +24-11-19 20:29:44 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:29:44 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:44 | D | sum error = [ 178.0238, 186.5372, 195.3646, 204.5083, 213.9906] +24-11-19 20:29:44 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:29:44 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:44 | D | sum error = [ 223.8048, 233.9650, 244.4663, 255.3165, 266.5179] +24-11-19 20:29:44 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:29:44 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:44 | D | sum error = [ 278.0779, 290.0030, 302.3068, 314.9921, 328.0312] +24-11-19 20:29:44 | D | best error = [ 4.5282, 4.5282, 4.5282, 4.5282, 4.5282] +24-11-19 20:29:44 | D | + error = [4.5282] +24-11-19 20:29:44 | D | - Calibrating model.layers.13.mlp.gate_proj.weight +24-11-19 20:29:44 | D | + w: sint8 +24-11-19 20:29:44 | D | + x: None +24-11-19 20:29:44 | D | + y: None +24-11-19 20:29:44 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:44 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:29:44 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:29:44 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:44 | D | - range ratio = [ 1.0000] +24-11-19 20:29:44 | D | sum error = [ 6.2253] +24-11-19 20:29:44 | D | best error = [ 6.2253] +24-11-19 20:29:45 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:45 | D | sum error = [ 6.1719, 6.1681, 6.2013, 6.2660, 6.3767] +24-11-19 20:29:45 | D | best error = [ 5.7637, 5.5891, 5.4982, 5.4457, 5.4175] +24-11-19 20:29:45 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:45 | D | sum error = [ 6.5522, 6.7686, 7.0495, 7.3910, 7.7922] +24-11-19 20:29:45 | D | best error = [ 5.4035, 5.3978, 5.3954, 5.3948, 5.3946] +24-11-19 20:29:45 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:45 | D | sum error = [ 8.2571, 8.7631, 9.3521, 10.0050, 10.7001] +24-11-19 20:29:45 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:45 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:45 | D | sum error = [ 11.4825, 12.3218, 13.2170, 14.2106, 15.2751] +24-11-19 20:29:45 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:45 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:45 | D | sum error = [ 16.4004, 17.5901, 18.8915, 20.2941, 21.7733] +24-11-19 20:29:45 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:45 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:45 | D | sum error = [ 23.3562, 25.0217, 26.8342, 28.7317, 30.7818] +24-11-19 20:29:45 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:45 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:45 | D | sum error = [ 32.9636, 35.2703, 37.7539, 40.3761, 43.1596] +24-11-19 20:29:45 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:45 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:45 | D | sum error = [ 46.1527, 49.3270, 52.7176, 56.3083, 60.1296] +24-11-19 20:29:45 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:45 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:45 | D | sum error = [ 64.2196, 68.5708, 73.1551, 78.0802, 83.2820] +24-11-19 20:29:45 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:45 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:45 | D | sum error = [ 88.8148, 94.7359, 100.9641, 107.6054, 114.6461] +24-11-19 20:29:45 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:45 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:45 | D | sum error = [ 122.0923, 129.9977, 138.3403, 147.1861, 156.5568] +24-11-19 20:29:45 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:45 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:45 | D | sum error = [ 166.4354, 176.8699, 187.8701, 199.4853, 211.7040] +24-11-19 20:29:45 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:45 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:45 | D | sum error = [ 224.5578, 238.0968, 252.3136, 267.2370, 282.8815] +24-11-19 20:29:45 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:45 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:45 | D | sum error = [ 299.2773, 316.4110, 334.3215, 352.9912, 372.4694] +24-11-19 20:29:45 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:45 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:45 | D | sum error = [ 392.7608, 413.8566, 435.8217, 458.5867, 482.2105] +24-11-19 20:29:45 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:45 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:45 | D | sum error = [ 506.6643, 531.9847, 558.1111, 585.0561, 612.8549] +24-11-19 20:29:45 | D | best error = [ 5.3946, 5.3946, 5.3946, 5.3946, 5.3946] +24-11-19 20:29:45 | D | + error = [5.3946] +24-11-19 20:29:45 | D | - Calibrating model.layers.13.mlp.down_proj.weight +24-11-19 20:29:45 | D | + w: sint8 +24-11-19 20:29:45 | D | + x: None +24-11-19 20:29:45 | D | + y: None +24-11-19 20:29:45 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:29:45 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:29:45 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:29:46 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:29:46 | D | - range ratio = [ 1.0000] +24-11-19 20:29:46 | D | sum error = [ 0.7254] +24-11-19 20:29:46 | D | best error = [ 0.7254] +24-11-19 20:29:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:29:47 | D | sum error = [ 0.7192, 0.7146, 0.7103, 0.7098, 0.7082] +24-11-19 20:29:47 | D | best error = [ 0.6907, 0.6752, 0.6646, 0.6576, 0.6520] +24-11-19 20:29:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:29:47 | D | sum error = [ 0.7093, 0.7155, 0.7196, 0.7297, 0.7448] +24-11-19 20:29:47 | D | best error = [ 0.6481, 0.6447, 0.6422, 0.6406, 0.6395] +24-11-19 20:29:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:29:47 | D | sum error = [ 0.7647, 0.7823, 0.8085, 0.8381, 0.8746] +24-11-19 20:29:47 | D | best error = [ 0.6387, 0.6381, 0.6378, 0.6374, 0.6373] +24-11-19 20:29:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:29:47 | D | sum error = [ 0.9123, 0.9563, 1.0070, 1.0631, 1.1251] +24-11-19 20:29:47 | D | best error = [ 0.6372, 0.6371, 0.6370, 0.6370, 0.6370] +24-11-19 20:29:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:29:47 | D | sum error = [ 1.1921, 1.2647, 1.3460, 1.4341, 1.5275] +24-11-19 20:29:47 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 20:29:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:29:47 | D | sum error = [ 1.6281, 1.7397, 1.8550, 1.9804, 2.1134] +24-11-19 20:29:47 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 20:29:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:29:47 | D | sum error = [ 2.2568, 2.4086, 2.5715, 2.7445, 2.9283] +24-11-19 20:29:47 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 20:29:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:29:47 | D | sum error = [ 3.1222, 3.3280, 3.5468, 3.7791, 4.0240] +24-11-19 20:29:47 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 20:29:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:29:47 | D | sum error = [ 4.2826, 4.5580, 4.8473, 5.1518, 5.4752] +24-11-19 20:29:47 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 20:29:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:29:47 | D | sum error = [ 5.8155, 6.1744, 6.5526, 6.9505, 7.3689] +24-11-19 20:29:47 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 20:29:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:29:47 | D | sum error = [ 7.8084, 8.2707, 8.7602, 9.2693, 9.8058] +24-11-19 20:29:47 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 20:29:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:29:47 | D | sum error = [ 10.3668, 10.9555, 11.5726, 12.2184, 12.8949] +24-11-19 20:29:47 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 20:29:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:29:47 | D | sum error = [ 13.6021, 14.3386, 15.1091, 15.9133, 16.7518] +24-11-19 20:29:47 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 20:29:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:29:47 | D | sum error = [ 17.6265, 18.5392, 19.4883, 20.4775, 21.5062] +24-11-19 20:29:47 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 20:29:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:29:47 | D | sum error = [ 22.5747, 23.6867, 24.8400, 26.0348, 27.2736] +24-11-19 20:29:47 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 20:29:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:29:47 | D | sum error = [ 28.5547, 29.8811, 31.2533, 32.6711, 34.1348] +24-11-19 20:29:47 | D | best error = [ 0.6369, 0.6369, 0.6369, 0.6369, 0.6369] +24-11-19 20:29:47 | D | + error = [0.6369] +24-11-19 20:29:47 | D | - Quantizing model.layers.13.self_attn.q_proj.weight +24-11-19 20:29:48 | D | - Quantizing model.layers.13.self_attn.k_proj.weight +24-11-19 20:29:49 | D | - Quantizing model.layers.13.self_attn.v_proj.weight +24-11-19 20:29:49 | D | - Quantizing model.layers.13.self_attn.o_proj.weight +24-11-19 20:29:50 | D | - Quantizing model.layers.13.mlp.up_proj.weight +24-11-19 20:29:51 | D | - Quantizing model.layers.13.mlp.gate_proj.weight +24-11-19 20:29:52 | D | - Quantizing model.layers.13.mlp.down_proj.weight +24-11-19 20:30:04 | D | - Quantizing layer model.layers.14 +24-11-19 20:30:04 | D | - Calibrating model.layers.14.self_attn.q_proj.weight +24-11-19 20:30:04 | D | + w: sint8 +24-11-19 20:30:04 | D | + x: None +24-11-19 20:30:04 | D | + y: None +24-11-19 20:30:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:30:04 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:04 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:30:05 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:30:05 | D | - range ratio = [ 1.0000] +24-11-19 20:30:05 | D | sum error = [ 5.6000] +24-11-19 20:30:05 | D | best error = [ 5.6000] +24-11-19 20:30:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:20 | D | sum error = [ 5.3647, 5.3899, 5.5604, 5.5944, 5.6106] +24-11-19 20:30:20 | D | best error = [ 5.3647, 5.3647, 5.3647, 5.3647, 5.3647] +24-11-19 20:30:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:20 | D | sum error = [ 5.8630, 6.0077, 6.2346, 6.5510, 6.9729] +24-11-19 20:30:20 | D | best error = [ 5.3647, 5.3647, 5.3647, 5.3647, 5.3647] +24-11-19 20:30:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:20 | D | sum error = [ 7.3419, 7.6109, 8.3943, 9.0700, 9.8520] +24-11-19 20:30:20 | D | best error = [ 5.3647, 5.3647, 5.3647, 5.3647, 5.3647] +24-11-19 20:30:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:20 | D | sum error = [ 10.0902, 10.9528, 12.0084, 12.7457, 13.9294] +24-11-19 20:30:20 | D | best error = [ 5.3647, 5.3647, 5.3647, 5.3647, 5.3647] +24-11-19 20:30:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:20 | D | sum error = [ 15.0024, 16.4169, 17.7098, 19.1404, 20.5418] +24-11-19 20:30:20 | D | best error = [ 5.3647, 5.3647, 5.3647, 5.3647, 5.3647] +24-11-19 20:30:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:20 | D | sum error = [ 22.2318, 24.0372, 25.6762, 27.5955, 30.0427] +24-11-19 20:30:20 | D | best error = [ 5.3647, 5.3647, 5.3647, 5.3647, 5.3647] +24-11-19 20:30:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:20 | D | sum error = [ 32.4613, 34.6419, 37.1017, 40.0632, 42.6100] +24-11-19 20:30:20 | D | best error = [ 5.3647, 5.3647, 5.3647, 5.3647, 5.3647] +24-11-19 20:30:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:20 | D | sum error = [ 45.6811, 49.0017, 52.4611, 56.0464, 59.5725] +24-11-19 20:30:20 | D | best error = [ 5.3647, 5.3647, 5.3647, 5.3647, 5.3647] +24-11-19 20:30:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:20 | D | sum error = [ 63.6230, 68.1537, 72.4790, 77.1979, 82.1083] +24-11-19 20:30:20 | D | best error = [ 5.3647, 5.3647, 5.3647, 5.3647, 5.3647] +24-11-19 20:30:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:20 | D | sum error = [ 87.2373, 92.4266, 97.8820, 103.7885, 109.8963] +24-11-19 20:30:20 | D | best error = [ 5.3647, 5.3647, 5.3647, 5.3647, 5.3647] +24-11-19 20:30:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:20 | D | sum error = [ 116.0365, 122.8601, 129.7147, 136.9768, 144.5312] +24-11-19 20:30:20 | D | best error = [ 5.3647, 5.3647, 5.3647, 5.3647, 5.3647] +24-11-19 20:30:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:20 | D | sum error = [ 152.2187, 160.3319, 168.9418, 178.2240, 187.8661] +24-11-19 20:30:20 | D | best error = [ 5.3647, 5.3647, 5.3647, 5.3647, 5.3647] +24-11-19 20:30:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:20 | D | sum error = [ 198.1606, 209.0398, 220.5067, 232.5891, 245.3409] +24-11-19 20:30:20 | D | best error = [ 5.3647, 5.3647, 5.3647, 5.3647, 5.3647] +24-11-19 20:30:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:20 | D | sum error = [ 258.7546, 273.0627, 288.2467, 304.2053, 321.2382] +24-11-19 20:30:20 | D | best error = [ 5.3647, 5.3647, 5.3647, 5.3647, 5.3647] +24-11-19 20:30:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:20 | D | sum error = [ 339.0815, 358.0237, 377.9519, 399.0742, 421.2632] +24-11-19 20:30:20 | D | best error = [ 5.3647, 5.3647, 5.3647, 5.3647, 5.3647] +24-11-19 20:30:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:20 | D | sum error = [ 444.3998, 468.7735, 494.2959, 521.0378, 548.8294] +24-11-19 20:30:20 | D | best error = [ 5.3647, 5.3647, 5.3647, 5.3647, 5.3647] +24-11-19 20:30:20 | D | + error = [5.3647] +24-11-19 20:30:20 | D | - Calibrating model.layers.14.self_attn.k_proj.weight +24-11-19 20:30:20 | D | + w: sint8 +24-11-19 20:30:20 | D | + x: None +24-11-19 20:30:20 | D | + y: None +24-11-19 20:30:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:30:20 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:30:20 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:30:21 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:30:21 | D | - range ratio = [ 1.0000] +24-11-19 20:30:21 | D | sum error = [ 4.4281] +24-11-19 20:30:21 | D | best error = [ 4.4281] +24-11-19 20:30:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:36 | D | sum error = [ 4.5349, 4.2550, 4.6465, 4.5613, 5.1504] +24-11-19 20:30:36 | D | best error = [ 4.4281, 4.2550, 4.2550, 4.2550, 4.2550] +24-11-19 20:30:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:36 | D | sum error = [ 4.7218, 4.5482, 5.6649, 5.1942, 5.6665] +24-11-19 20:30:36 | D | best error = [ 4.2550, 4.2550, 4.2550, 4.2550, 4.2550] +24-11-19 20:30:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:36 | D | sum error = [ 6.0520, 6.6852, 6.9171, 8.6080, 8.3177] +24-11-19 20:30:36 | D | best error = [ 4.2550, 4.2550, 4.2550, 4.2550, 4.2550] +24-11-19 20:30:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:36 | D | sum error = [ 8.5671, 9.7020, 10.2081, 11.8589, 11.8172] +24-11-19 20:30:36 | D | best error = [ 4.2550, 4.2550, 4.2550, 4.2550, 4.2550] +24-11-19 20:30:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:36 | D | sum error = [ 13.8512, 14.4422, 15.9096, 17.1770, 18.3933] +24-11-19 20:30:36 | D | best error = [ 4.2550, 4.2550, 4.2550, 4.2550, 4.2550] +24-11-19 20:30:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:36 | D | sum error = [ 19.2770, 21.1045, 22.9029, 25.1693, 26.6109] +24-11-19 20:30:36 | D | best error = [ 4.2550, 4.2550, 4.2550, 4.2550, 4.2550] +24-11-19 20:30:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:36 | D | sum error = [ 28.5181, 31.3835, 33.8359, 36.1726, 39.2612] +24-11-19 20:30:36 | D | best error = [ 4.2550, 4.2550, 4.2550, 4.2550, 4.2550] +24-11-19 20:30:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:36 | D | sum error = [ 42.3353, 44.6010, 48.5261, 51.4685, 55.4586] +24-11-19 20:30:36 | D | best error = [ 4.2550, 4.2550, 4.2550, 4.2550, 4.2550] +24-11-19 20:30:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:36 | D | sum error = [ 59.5020, 64.2089, 68.9777, 73.3325, 79.4673] +24-11-19 20:30:36 | D | best error = [ 4.2550, 4.2550, 4.2550, 4.2550, 4.2550] +24-11-19 20:30:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:36 | D | sum error = [ 84.6831, 90.4090, 96.1137, 102.5003, 109.3670] +24-11-19 20:30:36 | D | best error = [ 4.2550, 4.2550, 4.2550, 4.2550, 4.2550] +24-11-19 20:30:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:36 | D | sum error = [ 116.5523, 123.8692, 132.0756, 140.1995, 148.6415] +24-11-19 20:30:36 | D | best error = [ 4.2550, 4.2550, 4.2550, 4.2550, 4.2550] +24-11-19 20:30:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:36 | D | sum error = [ 157.9781, 167.8057, 178.4592, 189.4388, 200.9831] +24-11-19 20:30:36 | D | best error = [ 4.2550, 4.2550, 4.2550, 4.2550, 4.2550] +24-11-19 20:30:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:36 | D | sum error = [ 212.8702, 224.7391, 237.1373, 250.2088, 263.6692] +24-11-19 20:30:36 | D | best error = [ 4.2550, 4.2550, 4.2550, 4.2550, 4.2550] +24-11-19 20:30:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:36 | D | sum error = [ 277.8278, 293.3247, 308.4335, 324.6978, 341.7341] +24-11-19 20:30:36 | D | best error = [ 4.2550, 4.2550, 4.2550, 4.2550, 4.2550] +24-11-19 20:30:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:36 | D | sum error = [ 359.2405, 377.5024, 396.5322, 416.5683, 437.6187] +24-11-19 20:30:36 | D | best error = [ 4.2550, 4.2550, 4.2550, 4.2550, 4.2550] +24-11-19 20:30:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:36 | D | sum error = [ 459.6777, 482.5979, 506.6274, 531.5760, 557.5427] +24-11-19 20:30:36 | D | best error = [ 4.2550, 4.2550, 4.2550, 4.2550, 4.2550] +24-11-19 20:30:36 | D | + error = [4.2550] +24-11-19 20:30:37 | D | - Calibrating model.layers.14.self_attn.v_proj.weight +24-11-19 20:30:37 | D | + w: sint8 +24-11-19 20:30:37 | D | + x: None +24-11-19 20:30:37 | D | + y: None +24-11-19 20:30:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:37 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:37 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:30:37 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:30:37 | D | - range ratio = [ 1.0000] +24-11-19 20:30:37 | D | sum error = [ 1.4940] +24-11-19 20:30:37 | D | best error = [ 1.4940] +24-11-19 20:30:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:37 | D | sum error = [ 1.4890, 1.4767, 1.4869, 1.5100, 1.5455] +24-11-19 20:30:37 | D | best error = [ 1.3699, 1.3222, 1.3004, 1.2852, 1.2788] +24-11-19 20:30:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:37 | D | sum error = [ 1.5668, 1.6263, 1.6987, 1.7780, 1.8659] +24-11-19 20:30:37 | D | best error = [ 1.2745, 1.2732, 1.2725, 1.2724, 1.2723] +24-11-19 20:30:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:37 | D | sum error = [ 1.9869, 2.1071, 2.2512, 2.3753, 2.5735] +24-11-19 20:30:37 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 20:30:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:37 | D | sum error = [ 2.7604, 2.9326, 3.1610, 3.4005, 3.6390] +24-11-19 20:30:37 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 20:30:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:37 | D | sum error = [ 3.9002, 4.1943, 4.4887, 4.8094, 5.1388] +24-11-19 20:30:37 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 20:30:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:37 | D | sum error = [ 5.4927, 5.8661, 6.2687, 6.6845, 7.1313] +24-11-19 20:30:37 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 20:30:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:37 | D | sum error = [ 7.6038, 8.0843, 8.6038, 9.1469, 9.7344] +24-11-19 20:30:37 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 20:30:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:37 | D | sum error = [ 10.3429, 10.9813, 11.6503, 12.3596, 13.1072] +24-11-19 20:30:37 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 20:30:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:37 | D | sum error = [ 13.8899, 14.7083, 15.5774, 16.4892, 17.4256] +24-11-19 20:30:37 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 20:30:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:37 | D | sum error = [ 18.4275, 19.4651, 20.5695, 21.7078, 22.9092] +24-11-19 20:30:37 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 20:30:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:37 | D | sum error = [ 24.1582, 25.4724, 26.8390, 28.2718, 29.7667] +24-11-19 20:30:37 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 20:30:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:37 | D | sum error = [ 31.3247, 32.9408, 34.6348, 36.3933, 38.2182] +24-11-19 20:30:37 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 20:30:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:37 | D | sum error = [ 40.1051, 42.0846, 44.1339, 46.2822, 48.5119] +24-11-19 20:30:37 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 20:30:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:37 | D | sum error = [ 50.8348, 53.2301, 55.7143, 58.2846, 60.9373] +24-11-19 20:30:37 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 20:30:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:37 | D | sum error = [ 63.6854, 66.5353, 69.4736, 72.5208, 75.6746] +24-11-19 20:30:37 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 20:30:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:37 | D | sum error = [ 78.9117, 82.2573, 85.6907, 89.2240, 92.8597] +24-11-19 20:30:37 | D | best error = [ 1.2723, 1.2723, 1.2723, 1.2723, 1.2723] +24-11-19 20:30:37 | D | + error = [1.2723] +24-11-19 20:30:37 | D | - Calibrating model.layers.14.self_attn.o_proj.weight +24-11-19 20:30:37 | D | + w: sint8 +24-11-19 20:30:37 | D | + x: None +24-11-19 20:30:37 | D | + y: None +24-11-19 20:30:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:37 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:37 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:30:37 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:30:37 | D | - range ratio = [ 1.0000] +24-11-19 20:30:37 | D | sum error = [ 0.6814] +24-11-19 20:30:37 | D | best error = [ 0.6814] +24-11-19 20:30:38 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:38 | D | sum error = [ 0.6728, 0.6722, 0.6699, 0.6736, 0.6789] +24-11-19 20:30:38 | D | best error = [ 0.6233, 0.5987, 0.5839, 0.5745, 0.5674] +24-11-19 20:30:38 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:38 | D | sum error = [ 0.6880, 0.7000, 0.7138, 0.7333, 0.7589] +24-11-19 20:30:38 | D | best error = [ 0.5631, 0.5598, 0.5578, 0.5565, 0.5558] +24-11-19 20:30:38 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:38 | D | sum error = [ 0.7888, 0.8182, 0.8607, 0.9040, 0.9496] +24-11-19 20:30:38 | D | best error = [ 0.5553, 0.5550, 0.5548, 0.5547, 0.5547] +24-11-19 20:30:38 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:38 | D | sum error = [ 0.9995, 1.0547, 1.1155, 1.1833, 1.2499] +24-11-19 20:30:38 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:38 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:38 | D | sum error = [ 1.3238, 1.4026, 1.4868, 1.5778, 1.6706] +24-11-19 20:30:38 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:38 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:38 | D | sum error = [ 1.7684, 1.8765, 1.9895, 2.1053, 2.2274] +24-11-19 20:30:38 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:38 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:38 | D | sum error = [ 2.3597, 2.4979, 2.6417, 2.7924, 2.9504] +24-11-19 20:30:38 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:38 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:38 | D | sum error = [ 3.1171, 3.2939, 3.4802, 3.6714, 3.8762] +24-11-19 20:30:38 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:38 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:38 | D | sum error = [ 4.0928, 4.3129, 4.5476, 4.7929, 5.0461] +24-11-19 20:30:38 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:38 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:38 | D | sum error = [ 5.3169, 5.5949, 5.8886, 6.1930, 6.5096] +24-11-19 20:30:38 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:38 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:38 | D | sum error = [ 6.8451, 7.1878, 7.5482, 7.9235, 8.3164] +24-11-19 20:30:38 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:38 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:38 | D | sum error = [ 8.7218, 9.1492, 9.5912, 10.0525, 10.5310] +24-11-19 20:30:38 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:38 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:38 | D | sum error = [ 11.0300, 11.5510, 12.0891, 12.6494, 13.2300] +24-11-19 20:30:38 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:38 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:38 | D | sum error = [ 13.8366, 14.4633, 15.1168, 15.7923, 16.4939] +24-11-19 20:30:38 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:38 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:38 | D | sum error = [ 17.2225, 17.9780, 18.7622, 19.5723, 20.4102] +24-11-19 20:30:38 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:38 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:38 | D | sum error = [ 21.2799, 22.1788, 23.1099, 24.0739, 25.0719] +24-11-19 20:30:38 | D | best error = [ 0.5546, 0.5546, 0.5546, 0.5546, 0.5546] +24-11-19 20:30:38 | D | + error = [0.5546] +24-11-19 20:30:38 | D | - Calibrating model.layers.14.mlp.up_proj.weight +24-11-19 20:30:38 | D | + w: sint8 +24-11-19 20:30:38 | D | + x: None +24-11-19 20:30:38 | D | + y: None +24-11-19 20:30:38 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:38 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:38 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:30:38 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:30:38 | D | - range ratio = [ 1.0000] +24-11-19 20:30:38 | D | sum error = [ 5.4712] +24-11-19 20:30:38 | D | best error = [ 5.4712] +24-11-19 20:30:39 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:39 | D | sum error = [ 5.4285, 5.4063, 5.4441, 5.5012, 5.6020] +24-11-19 20:30:39 | D | best error = [ 5.0523, 4.8933, 4.8129, 4.7671, 4.7420] +24-11-19 20:30:39 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:39 | D | sum error = [ 5.7424, 5.9334, 6.1672, 6.4545, 6.7961] +24-11-19 20:30:39 | D | best error = [ 4.7301, 4.7248, 4.7228, 4.7222, 4.7220] +24-11-19 20:30:39 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:39 | D | sum error = [ 7.2132, 7.6294, 8.1356, 8.6843, 9.2916] +24-11-19 20:30:39 | D | best error = [ 4.7220, 4.7220, 4.7220, 4.7220, 4.7220] +24-11-19 20:30:39 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:39 | D | sum error = [ 9.9632, 10.6480, 11.4124, 12.2493, 13.1185] +24-11-19 20:30:39 | D | best error = [ 4.7220, 4.7220, 4.7220, 4.7220, 4.7220] +24-11-19 20:30:39 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:39 | D | sum error = [ 14.0544, 15.0453, 16.1228, 17.2528, 18.4524] +24-11-19 20:30:39 | D | best error = [ 4.7220, 4.7220, 4.7220, 4.7220, 4.7220] +24-11-19 20:30:39 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:39 | D | sum error = [ 19.7205, 21.0742, 22.5068, 24.0193, 25.6118] +24-11-19 20:30:39 | D | best error = [ 4.7220, 4.7220, 4.7220, 4.7220, 4.7220] +24-11-19 20:30:39 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:39 | D | sum error = [ 27.3111, 29.0917, 30.9650, 32.9490, 35.0386] +24-11-19 20:30:39 | D | best error = [ 4.7220, 4.7220, 4.7220, 4.7220, 4.7220] +24-11-19 20:30:39 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:39 | D | sum error = [ 37.2334, 39.5530, 41.9860, 44.5406, 47.2273] +24-11-19 20:30:39 | D | best error = [ 4.7220, 4.7220, 4.7220, 4.7220, 4.7220] +24-11-19 20:30:39 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:39 | D | sum error = [ 50.0477, 53.0075, 56.1214, 59.3902, 62.8002] +24-11-19 20:30:39 | D | best error = [ 4.7220, 4.7220, 4.7220, 4.7220, 4.7220] +24-11-19 20:30:39 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:39 | D | sum error = [ 66.3883, 70.1551, 74.0946, 78.2199, 82.5282] +24-11-19 20:30:39 | D | best error = [ 4.7220, 4.7220, 4.7220, 4.7220, 4.7220] +24-11-19 20:30:39 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:39 | D | sum error = [ 87.0293, 91.7352, 96.6586, 101.8014, 107.1622] +24-11-19 20:30:39 | D | best error = [ 4.7220, 4.7220, 4.7220, 4.7220, 4.7220] +24-11-19 20:30:39 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:39 | D | sum error = [ 112.7463, 118.5824, 124.6633, 130.9895, 137.5852] +24-11-19 20:30:39 | D | best error = [ 4.7220, 4.7220, 4.7220, 4.7220, 4.7220] +24-11-19 20:30:39 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:39 | D | sum error = [ 144.4488, 151.5834, 158.9921, 166.6986, 174.6864] +24-11-19 20:30:39 | D | best error = [ 4.7220, 4.7220, 4.7220, 4.7220, 4.7220] +24-11-19 20:30:39 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:39 | D | sum error = [ 182.9803, 191.5783, 200.4683, 209.6816, 219.2098] +24-11-19 20:30:39 | D | best error = [ 4.7220, 4.7220, 4.7220, 4.7220, 4.7220] +24-11-19 20:30:39 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:39 | D | sum error = [ 229.0655, 239.2496, 249.7707, 260.6172, 271.8092] +24-11-19 20:30:39 | D | best error = [ 4.7220, 4.7220, 4.7220, 4.7220, 4.7220] +24-11-19 20:30:39 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:39 | D | sum error = [ 283.3716, 295.2709, 307.5443, 320.1673, 333.1566] +24-11-19 20:30:39 | D | best error = [ 4.7220, 4.7220, 4.7220, 4.7220, 4.7220] +24-11-19 20:30:39 | D | + error = [4.7220] +24-11-19 20:30:40 | D | - Calibrating model.layers.14.mlp.gate_proj.weight +24-11-19 20:30:40 | D | + w: sint8 +24-11-19 20:30:40 | D | + x: None +24-11-19 20:30:40 | D | + y: None +24-11-19 20:30:40 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:40 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:40 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:30:40 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:30:40 | D | - range ratio = [ 1.0000] +24-11-19 20:30:40 | D | sum error = [ 6.6988] +24-11-19 20:30:40 | D | best error = [ 6.6988] +24-11-19 20:30:41 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:41 | D | sum error = [ 6.6454, 6.6272, 6.6654, 6.7274, 6.8619] +24-11-19 20:30:41 | D | best error = [ 6.1869, 5.9966, 5.9021, 5.8453, 5.8152] +24-11-19 20:30:41 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:41 | D | sum error = [ 7.0483, 7.2754, 7.5616, 7.9343, 8.3582] +24-11-19 20:30:41 | D | best error = [ 5.8012, 5.7956, 5.7936, 5.7931, 5.7930] +24-11-19 20:30:41 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:41 | D | sum error = [ 8.8596, 9.4085, 10.0452, 10.7454, 11.4982] +24-11-19 20:30:41 | D | best error = [ 5.7930, 5.7930, 5.7930, 5.7930, 5.7930] +24-11-19 20:30:41 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:41 | D | sum error = [ 12.3329, 13.2525, 14.2243, 15.2827, 16.4135] +24-11-19 20:30:41 | D | best error = [ 5.7930, 5.7930, 5.7930, 5.7930, 5.7930] +24-11-19 20:30:41 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:41 | D | sum error = [ 17.6524, 18.9550, 20.3690, 21.8569, 23.4716] +24-11-19 20:30:41 | D | best error = [ 5.7930, 5.7930, 5.7930, 5.7930, 5.7930] +24-11-19 20:30:41 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:41 | D | sum error = [ 25.1939, 27.0398, 28.9809, 31.0714, 33.3151] +24-11-19 20:30:41 | D | best error = [ 5.7930, 5.7930, 5.7930, 5.7930, 5.7930] +24-11-19 20:30:41 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:41 | D | sum error = [ 35.6811, 38.1962, 40.8970, 43.7557, 46.8121] +24-11-19 20:30:41 | D | best error = [ 5.7930, 5.7930, 5.7930, 5.7930, 5.7930] +24-11-19 20:30:41 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:41 | D | sum error = [ 50.0836, 53.5218, 57.2141, 61.1115, 65.3066] +24-11-19 20:30:41 | D | best error = [ 5.7930, 5.7930, 5.7930, 5.7930, 5.7930] +24-11-19 20:30:41 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:41 | D | sum error = [ 69.7515, 74.4780, 79.4980, 84.8465, 90.5544] +24-11-19 20:30:41 | D | best error = [ 5.7930, 5.7930, 5.7930, 5.7930, 5.7930] +24-11-19 20:30:41 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:41 | D | sum error = [ 96.5871, 103.0212, 109.8255, 117.0309, 124.7113] +24-11-19 20:30:41 | D | best error = [ 5.7930, 5.7930, 5.7930, 5.7930, 5.7930] +24-11-19 20:30:41 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:41 | D | sum error = [ 132.8448, 141.4394, 150.5281, 160.1760, 170.3553] +24-11-19 20:30:41 | D | best error = [ 5.7930, 5.7930, 5.7930, 5.7930, 5.7930] +24-11-19 20:30:41 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:41 | D | sum error = [ 181.1389, 192.5239, 204.5392, 217.1896, 230.5199] +24-11-19 20:30:41 | D | best error = [ 5.7930, 5.7930, 5.7930, 5.7930, 5.7930] +24-11-19 20:30:41 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:41 | D | sum error = [ 244.5703, 259.3072, 274.7873, 291.0210, 308.0581] +24-11-19 20:30:41 | D | best error = [ 5.7930, 5.7930, 5.7930, 5.7930, 5.7930] +24-11-19 20:30:41 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:41 | D | sum error = [ 325.9108, 344.5761, 364.0898, 384.4871, 405.7459] +24-11-19 20:30:41 | D | best error = [ 5.7930, 5.7930, 5.7930, 5.7930, 5.7930] +24-11-19 20:30:41 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:41 | D | sum error = [ 427.9211, 451.0162, 475.0220, 499.9449, 525.8100] +24-11-19 20:30:41 | D | best error = [ 5.7930, 5.7930, 5.7930, 5.7930, 5.7930] +24-11-19 20:30:41 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:41 | D | sum error = [ 552.6214, 580.3691, 609.0548, 638.6840, 669.2312] +24-11-19 20:30:41 | D | best error = [ 5.7930, 5.7930, 5.7930, 5.7930, 5.7930] +24-11-19 20:30:41 | D | + error = [5.7930] +24-11-19 20:30:41 | D | - Calibrating model.layers.14.mlp.down_proj.weight +24-11-19 20:30:41 | D | + w: sint8 +24-11-19 20:30:41 | D | + x: None +24-11-19 20:30:41 | D | + y: None +24-11-19 20:30:41 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:30:41 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:41 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:30:41 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:30:41 | D | - range ratio = [ 1.0000] +24-11-19 20:30:41 | D | sum error = [ 0.7967] +24-11-19 20:30:41 | D | best error = [ 0.7967] +24-11-19 20:30:43 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:30:43 | D | sum error = [ 0.7889, 0.7836, 0.7790, 0.7753, 0.7746] +24-11-19 20:30:43 | D | best error = [ 0.7628, 0.7467, 0.7364, 0.7289, 0.7230] +24-11-19 20:30:43 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:30:43 | D | sum error = [ 0.7773, 0.7803, 0.7861, 0.7968, 0.8095] +24-11-19 20:30:43 | D | best error = [ 0.7185, 0.7150, 0.7122, 0.7103, 0.7088] +24-11-19 20:30:43 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:30:43 | D | sum error = [ 0.8278, 0.8489, 0.8761, 0.9062, 0.9401] +24-11-19 20:30:43 | D | best error = [ 0.7076, 0.7069, 0.7063, 0.7059, 0.7055] +24-11-19 20:30:43 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:30:43 | D | sum error = [ 0.9830, 1.0299, 1.0806, 1.1377, 1.2048] +24-11-19 20:30:43 | D | best error = [ 0.7053, 0.7052, 0.7050, 0.7049, 0.7048] +24-11-19 20:30:43 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:30:43 | D | sum error = [ 1.2745, 1.3528, 1.4373, 1.5264, 1.6271] +24-11-19 20:30:43 | D | best error = [ 0.7048, 0.7047, 0.7047, 0.7046, 0.7046] +24-11-19 20:30:43 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:30:43 | D | sum error = [ 1.7339, 1.8484, 1.9717, 2.1025, 2.2434] +24-11-19 20:30:43 | D | best error = [ 0.7046, 0.7046, 0.7046, 0.7046, 0.7046] +24-11-19 20:30:43 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:30:43 | D | sum error = [ 2.3946, 2.5550, 2.7242, 2.9065, 3.1010] +24-11-19 20:30:43 | D | best error = [ 0.7046, 0.7046, 0.7045, 0.7045, 0.7045] +24-11-19 20:30:43 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:30:43 | D | sum error = [ 3.3056, 3.5247, 3.7552, 3.9998, 4.2570] +24-11-19 20:30:43 | D | best error = [ 0.7045, 0.7045, 0.7045, 0.7045, 0.7045] +24-11-19 20:30:43 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:30:43 | D | sum error = [ 4.5311, 4.8197, 5.1266, 5.4496, 5.7912] +24-11-19 20:30:43 | D | best error = [ 0.7045, 0.7045, 0.7045, 0.7045, 0.7045] +24-11-19 20:30:43 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:30:43 | D | sum error = [ 6.1520, 6.5304, 6.9298, 7.3518, 7.7944] +24-11-19 20:30:43 | D | best error = [ 0.7045, 0.7045, 0.7045, 0.7045, 0.7045] +24-11-19 20:30:43 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:30:43 | D | sum error = [ 8.2608, 8.7512, 9.2665, 9.8067, 10.3744] +24-11-19 20:30:43 | D | best error = [ 0.7045, 0.7045, 0.7045, 0.7045, 0.7045] +24-11-19 20:30:43 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:30:43 | D | sum error = [ 10.9705, 11.5951, 12.2508, 12.9367, 13.6558] +24-11-19 20:30:43 | D | best error = [ 0.7045, 0.7045, 0.7045, 0.7045, 0.7045] +24-11-19 20:30:43 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:30:43 | D | sum error = [ 14.4070, 15.1932, 16.0139, 16.8725, 17.7687] +24-11-19 20:30:43 | D | best error = [ 0.7045, 0.7045, 0.7045, 0.7045, 0.7045] +24-11-19 20:30:43 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:30:43 | D | sum error = [ 18.7037, 19.6783, 20.6939, 21.7533, 22.8544] +24-11-19 20:30:43 | D | best error = [ 0.7045, 0.7045, 0.7045, 0.7045, 0.7045] +24-11-19 20:30:43 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:30:43 | D | sum error = [ 24.0011, 25.1906, 26.4260, 27.7094, 29.0404] +24-11-19 20:30:43 | D | best error = [ 0.7045, 0.7045, 0.7045, 0.7045, 0.7045] +24-11-19 20:30:43 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:30:43 | D | sum error = [ 30.4202, 31.8488, 33.3294, 34.8591, 36.4419] +24-11-19 20:30:43 | D | best error = [ 0.7045, 0.7045, 0.7045, 0.7045, 0.7045] +24-11-19 20:30:43 | D | + error = [0.7045] +24-11-19 20:30:43 | D | - Quantizing model.layers.14.self_attn.q_proj.weight +24-11-19 20:30:44 | D | - Quantizing model.layers.14.self_attn.k_proj.weight +24-11-19 20:30:45 | D | - Quantizing model.layers.14.self_attn.v_proj.weight +24-11-19 20:30:46 | D | - Quantizing model.layers.14.self_attn.o_proj.weight +24-11-19 20:30:47 | D | - Quantizing model.layers.14.mlp.up_proj.weight +24-11-19 20:30:48 | D | - Quantizing model.layers.14.mlp.gate_proj.weight +24-11-19 20:30:49 | D | - Quantizing model.layers.14.mlp.down_proj.weight +24-11-19 20:30:59 | D | - Quantizing layer model.layers.15 +24-11-19 20:30:59 | D | - Calibrating model.layers.15.self_attn.q_proj.weight +24-11-19 20:30:59 | D | + w: sint8 +24-11-19 20:30:59 | D | + x: None +24-11-19 20:30:59 | D | + y: None +24-11-19 20:30:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:30:59 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:30:59 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:30:59 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:30:59 | D | - range ratio = [ 1.0000] +24-11-19 20:30:59 | D | sum error = [ 4.3911] +24-11-19 20:30:59 | D | best error = [ 4.3911] +24-11-19 20:31:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:12 | D | sum error = [ 4.4460, 4.3639, 4.3571, 4.4737, 4.5099] +24-11-19 20:31:12 | D | best error = [ 4.3911, 4.3639, 4.3571, 4.3571, 4.3571] +24-11-19 20:31:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:12 | D | sum error = [ 4.6949, 4.7699, 4.8818, 5.2102, 5.4337] +24-11-19 20:31:12 | D | best error = [ 4.3571, 4.3571, 4.3571, 4.3571, 4.3571] +24-11-19 20:31:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:12 | D | sum error = [ 5.8784, 6.2584, 6.6418, 7.1015, 7.7766] +24-11-19 20:31:12 | D | best error = [ 4.3571, 4.3571, 4.3571, 4.3571, 4.3571] +24-11-19 20:31:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:12 | D | sum error = [ 8.3713, 9.0660, 9.6145, 10.4725, 11.3444] +24-11-19 20:31:12 | D | best error = [ 4.3571, 4.3571, 4.3571, 4.3571, 4.3571] +24-11-19 20:31:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:12 | D | sum error = [ 12.3006, 13.2074, 14.3422, 15.5287, 16.7016] +24-11-19 20:31:12 | D | best error = [ 4.3571, 4.3571, 4.3571, 4.3571, 4.3571] +24-11-19 20:31:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:12 | D | sum error = [ 18.2125, 19.5475, 21.1292, 22.6225, 24.3411] +24-11-19 20:31:12 | D | best error = [ 4.3571, 4.3571, 4.3571, 4.3571, 4.3571] +24-11-19 20:31:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:12 | D | sum error = [ 26.3001, 28.0814, 30.0892, 32.3997, 34.7512] +24-11-19 20:31:12 | D | best error = [ 4.3571, 4.3571, 4.3571, 4.3571, 4.3571] +24-11-19 20:31:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:12 | D | sum error = [ 37.3848, 40.1539, 42.9297, 46.1342, 49.6288] +24-11-19 20:31:12 | D | best error = [ 4.3571, 4.3571, 4.3571, 4.3571, 4.3571] +24-11-19 20:31:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:12 | D | sum error = [ 53.1033, 56.9590, 61.1456, 65.5917, 70.2055] +24-11-19 20:31:12 | D | best error = [ 4.3571, 4.3571, 4.3571, 4.3571, 4.3571] +24-11-19 20:31:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:12 | D | sum error = [ 75.3099, 80.7985, 86.7257, 92.9049, 99.6820] +24-11-19 20:31:12 | D | best error = [ 4.3571, 4.3571, 4.3571, 4.3571, 4.3571] +24-11-19 20:31:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:12 | D | sum error = [ 106.6083, 114.5054, 122.9164, 131.8742, 141.2717] +24-11-19 20:31:12 | D | best error = [ 4.3571, 4.3571, 4.3571, 4.3571, 4.3571] +24-11-19 20:31:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:12 | D | sum error = [ 151.2043, 161.9067, 173.2979, 185.5782, 198.5545] +24-11-19 20:31:12 | D | best error = [ 4.3571, 4.3571, 4.3571, 4.3571, 4.3571] +24-11-19 20:31:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:12 | D | sum error = [ 212.4653, 227.1841, 242.9778, 259.6795, 277.5694] +24-11-19 20:31:12 | D | best error = [ 4.3571, 4.3571, 4.3571, 4.3571, 4.3571] +24-11-19 20:31:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:12 | D | sum error = [ 296.1017, 315.9836, 336.9017, 358.7666, 382.2616] +24-11-19 20:31:12 | D | best error = [ 4.3571, 4.3571, 4.3571, 4.3571, 4.3571] +24-11-19 20:31:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:12 | D | sum error = [ 406.6705, 432.3058, 459.1795, 487.4807, 517.0061] +24-11-19 20:31:12 | D | best error = [ 4.3571, 4.3571, 4.3571, 4.3571, 4.3571] +24-11-19 20:31:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:12 | D | sum error = [ 547.7126, 579.5103, 611.9937, 645.8262, 680.1681] +24-11-19 20:31:12 | D | best error = [ 4.3571, 4.3571, 4.3571, 4.3571, 4.3571] +24-11-19 20:31:12 | D | + error = [4.3571] +24-11-19 20:31:12 | D | - Calibrating model.layers.15.self_attn.k_proj.weight +24-11-19 20:31:12 | D | + w: sint8 +24-11-19 20:31:12 | D | + x: None +24-11-19 20:31:12 | D | + y: None +24-11-19 20:31:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:31:12 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:31:12 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:31:12 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:31:12 | D | - range ratio = [ 1.0000] +24-11-19 20:31:12 | D | sum error = [ 4.0106] +24-11-19 20:31:12 | D | best error = [ 4.0106] +24-11-19 20:31:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:25 | D | sum error = [ 4.1071, 4.5709, 4.1462, 4.1274, 4.3630] +24-11-19 20:31:25 | D | best error = [ 4.0106, 4.0106, 4.0106, 4.0106, 4.0106] +24-11-19 20:31:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:25 | D | sum error = [ 4.4333, 4.3659, 4.4982, 5.2251, 5.1180] +24-11-19 20:31:25 | D | best error = [ 4.0106, 4.0106, 4.0106, 4.0106, 4.0106] +24-11-19 20:31:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:25 | D | sum error = [ 5.6997, 5.7850, 6.3381, 6.6884, 7.3297] +24-11-19 20:31:25 | D | best error = [ 4.0106, 4.0106, 4.0106, 4.0106, 4.0106] +24-11-19 20:31:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:25 | D | sum error = [ 8.2318, 8.2346, 9.1407, 10.0360, 10.1285] +24-11-19 20:31:25 | D | best error = [ 4.0106, 4.0106, 4.0106, 4.0106, 4.0106] +24-11-19 20:31:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:25 | D | sum error = [ 11.2425, 11.7999, 12.3378, 14.1356, 14.2619] +24-11-19 20:31:25 | D | best error = [ 4.0106, 4.0106, 4.0106, 4.0106, 4.0106] +24-11-19 20:31:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:25 | D | sum error = [ 15.6630, 16.4822, 17.1910, 18.4147, 19.8793] +24-11-19 20:31:25 | D | best error = [ 4.0106, 4.0106, 4.0106, 4.0106, 4.0106] +24-11-19 20:31:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:25 | D | sum error = [ 20.8174, 22.4408, 23.8838, 25.8343, 27.6659] +24-11-19 20:31:25 | D | best error = [ 4.0106, 4.0106, 4.0106, 4.0106, 4.0106] +24-11-19 20:31:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:25 | D | sum error = [ 29.5038, 31.9302, 34.2670, 36.8706, 39.7308] +24-11-19 20:31:25 | D | best error = [ 4.0106, 4.0106, 4.0106, 4.0106, 4.0106] +24-11-19 20:31:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:25 | D | sum error = [ 42.6950, 46.0226, 49.8799, 53.7213, 57.9164] +24-11-19 20:31:25 | D | best error = [ 4.0106, 4.0106, 4.0106, 4.0106, 4.0106] +24-11-19 20:31:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:25 | D | sum error = [ 62.5940, 67.4252, 72.9255, 78.7264, 85.1890] +24-11-19 20:31:25 | D | best error = [ 4.0106, 4.0106, 4.0106, 4.0106, 4.0106] +24-11-19 20:31:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:25 | D | sum error = [ 92.1192, 99.5269, 107.0334, 115.1863, 124.3663] +24-11-19 20:31:25 | D | best error = [ 4.0106, 4.0106, 4.0106, 4.0106, 4.0106] +24-11-19 20:31:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:25 | D | sum error = [ 133.0501, 142.8488, 153.7412, 164.5384, 176.4199] +24-11-19 20:31:25 | D | best error = [ 4.0106, 4.0106, 4.0106, 4.0106, 4.0106] +24-11-19 20:31:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:25 | D | sum error = [ 188.9294, 202.5581, 217.1423, 232.3373, 248.8026] +24-11-19 20:31:25 | D | best error = [ 4.0106, 4.0106, 4.0106, 4.0106, 4.0106] +24-11-19 20:31:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:25 | D | sum error = [ 266.2173, 285.1067, 304.7602, 326.3201, 349.2459] +24-11-19 20:31:25 | D | best error = [ 4.0106, 4.0106, 4.0106, 4.0106, 4.0106] +24-11-19 20:31:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:25 | D | sum error = [ 373.6672, 399.5622, 426.9846, 456.4947, 486.8712] +24-11-19 20:31:25 | D | best error = [ 4.0106, 4.0106, 4.0106, 4.0106, 4.0106] +24-11-19 20:31:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:25 | D | sum error = [ 519.3648, 553.6660, 589.2488, 625.8652, 663.5188] +24-11-19 20:31:25 | D | best error = [ 4.0106, 4.0106, 4.0106, 4.0106, 4.0106] +24-11-19 20:31:25 | D | + error = [4.0106] +24-11-19 20:31:25 | D | - Calibrating model.layers.15.self_attn.v_proj.weight +24-11-19 20:31:25 | D | + w: sint8 +24-11-19 20:31:25 | D | + x: None +24-11-19 20:31:25 | D | + y: None +24-11-19 20:31:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:25 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:31:25 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:31:25 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:31:25 | D | - range ratio = [ 1.0000] +24-11-19 20:31:25 | D | sum error = [ 1.6270] +24-11-19 20:31:25 | D | best error = [ 1.6270] +24-11-19 20:31:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:25 | D | sum error = [ 1.6116, 1.6156, 1.6028, 1.6549, 1.6609] +24-11-19 20:31:25 | D | best error = [ 1.4884, 1.4404, 1.4181, 1.4064, 1.3979] +24-11-19 20:31:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:25 | D | sum error = [ 1.7147, 1.7675, 1.8274, 1.9185, 2.0201] +24-11-19 20:31:25 | D | best error = [ 1.3947, 1.3926, 1.3924, 1.3922, 1.3922] +24-11-19 20:31:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:25 | D | sum error = [ 2.1382, 2.2736, 2.4185, 2.5748, 2.7641] +24-11-19 20:31:25 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 20:31:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:25 | D | sum error = [ 2.9466, 3.1333, 3.3820, 3.6240, 3.8716] +24-11-19 20:31:25 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 20:31:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:25 | D | sum error = [ 4.1292, 4.4243, 4.7317, 5.0637, 5.4100] +24-11-19 20:31:25 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 20:31:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:25 | D | sum error = [ 5.7768, 6.1667, 6.5721, 7.0211, 7.4689] +24-11-19 20:31:25 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 20:31:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:25 | D | sum error = [ 7.9480, 8.4471, 8.9869, 9.5614, 10.1468] +24-11-19 20:31:25 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 20:31:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:25 | D | sum error = [ 10.7618, 11.4239, 12.1079, 12.8198, 13.5862] +24-11-19 20:31:25 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 20:31:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:25 | D | sum error = [ 14.3775, 15.2068, 16.0878, 16.9972, 17.9612] +24-11-19 20:31:25 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 20:31:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:25 | D | sum error = [ 18.9555, 20.0105, 21.1110, 22.2542, 23.4670] +24-11-19 20:31:25 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 20:31:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:25 | D | sum error = [ 24.7296, 26.0378, 27.4133, 28.8245, 30.3044] +24-11-19 20:31:25 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 20:31:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:25 | D | sum error = [ 31.8425, 33.4486, 35.1211, 36.8536, 38.6462] +24-11-19 20:31:25 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 20:31:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:25 | D | sum error = [ 40.5168, 42.4489, 44.4638, 46.5268, 48.6573] +24-11-19 20:31:25 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 20:31:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:25 | D | sum error = [ 50.8756, 53.1592, 55.5144, 57.9434, 60.4432] +24-11-19 20:31:25 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 20:31:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:25 | D | sum error = [ 63.0288, 65.6857, 68.4209, 71.2316, 74.1320] +24-11-19 20:31:25 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 20:31:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:25 | D | sum error = [ 77.1190, 80.1987, 83.3723, 86.6237, 89.9685] +24-11-19 20:31:25 | D | best error = [ 1.3922, 1.3922, 1.3922, 1.3922, 1.3922] +24-11-19 20:31:25 | D | + error = [1.3922] +24-11-19 20:31:25 | D | - Calibrating model.layers.15.self_attn.o_proj.weight +24-11-19 20:31:25 | D | + w: sint8 +24-11-19 20:31:25 | D | + x: None +24-11-19 20:31:25 | D | + y: None +24-11-19 20:31:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:25 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:31:25 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:31:26 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:31:26 | D | - range ratio = [ 1.0000] +24-11-19 20:31:26 | D | sum error = [ 0.6805] +24-11-19 20:31:26 | D | best error = [ 0.6805] +24-11-19 20:31:26 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:26 | D | sum error = [ 0.6758, 0.6693, 0.6703, 0.6746, 0.6771] +24-11-19 20:31:26 | D | best error = [ 0.6258, 0.6001, 0.5850, 0.5755, 0.5683] +24-11-19 20:31:26 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:26 | D | sum error = [ 0.6902, 0.6962, 0.7136, 0.7314, 0.7520] +24-11-19 20:31:26 | D | best error = [ 0.5632, 0.5589, 0.5557, 0.5533, 0.5516] +24-11-19 20:31:26 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:26 | D | sum error = [ 0.7802, 0.8061, 0.8438, 0.8830, 0.9297] +24-11-19 20:31:26 | D | best error = [ 0.5498, 0.5486, 0.5476, 0.5468, 0.5460] +24-11-19 20:31:26 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:26 | D | sum error = [ 0.9743, 1.0238, 1.0824, 1.1404, 1.2041] +24-11-19 20:31:26 | D | best error = [ 0.5453, 0.5449, 0.5446, 0.5443, 0.5441] +24-11-19 20:31:26 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:26 | D | sum error = [ 1.2728, 1.3532, 1.4273, 1.5110, 1.5986] +24-11-19 20:31:26 | D | best error = [ 0.5439, 0.5437, 0.5436, 0.5436, 0.5435] +24-11-19 20:31:26 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:26 | D | sum error = [ 1.6908, 1.7875, 1.8895, 1.9986, 2.1131] +24-11-19 20:31:26 | D | best error = [ 0.5434, 0.5434, 0.5433, 0.5433, 0.5432] +24-11-19 20:31:26 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:26 | D | sum error = [ 2.2339, 2.3583, 2.4898, 2.6302, 2.7733] +24-11-19 20:31:26 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:31:26 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:26 | D | sum error = [ 2.9256, 3.0845, 3.2514, 3.4291, 3.6125] +24-11-19 20:31:26 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:31:26 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:26 | D | sum error = [ 3.8035, 4.0034, 4.2156, 4.4354, 4.6666] +24-11-19 20:31:26 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:31:26 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:26 | D | sum error = [ 4.9062, 5.1536, 5.4140, 5.6852, 5.9666] +24-11-19 20:31:26 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:31:26 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:26 | D | sum error = [ 6.2587, 6.5654, 6.8824, 7.2130, 7.5558] +24-11-19 20:31:26 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:31:26 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:26 | D | sum error = [ 7.9122, 8.2843, 8.6685, 9.0670, 9.4823] +24-11-19 20:31:26 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:31:26 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:26 | D | sum error = [ 9.9117, 10.3584, 10.8227, 11.3052, 11.8045] +24-11-19 20:31:26 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:31:26 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:26 | D | sum error = [ 12.3232, 12.8635, 13.4247, 14.0059, 14.6091] +24-11-19 20:31:26 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:31:26 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:26 | D | sum error = [ 15.2354, 15.8847, 16.5572, 17.2543, 17.9783] +24-11-19 20:31:26 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:31:26 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:26 | D | sum error = [ 18.7280, 19.5077, 20.3207, 21.1667, 22.0477] +24-11-19 20:31:26 | D | best error = [ 0.5432, 0.5432, 0.5432, 0.5432, 0.5432] +24-11-19 20:31:26 | D | + error = [0.5432] +24-11-19 20:31:26 | D | - Calibrating model.layers.15.mlp.up_proj.weight +24-11-19 20:31:26 | D | + w: sint8 +24-11-19 20:31:26 | D | + x: None +24-11-19 20:31:26 | D | + y: None +24-11-19 20:31:26 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:26 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:31:26 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:31:26 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:31:26 | D | - range ratio = [ 1.0000] +24-11-19 20:31:26 | D | sum error = [ 5.6796] +24-11-19 20:31:26 | D | best error = [ 5.6796] +24-11-19 20:31:28 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:28 | D | sum error = [ 5.6421, 5.6327, 5.6514, 5.7000, 5.8245] +24-11-19 20:31:28 | D | best error = [ 5.2615, 5.1045, 5.0214, 4.9749, 4.9507] +24-11-19 20:31:28 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:28 | D | sum error = [ 5.9815, 6.1772, 6.4275, 6.7260, 7.0820] +24-11-19 20:31:28 | D | best error = [ 4.9390, 4.9338, 4.9322, 4.9314, 4.9312] +24-11-19 20:31:28 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:28 | D | sum error = [ 7.4986, 7.9564, 8.4571, 9.0273, 9.6644] +24-11-19 20:31:28 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:31:28 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:28 | D | sum error = [ 10.3479, 11.0877, 11.8821, 12.7242, 13.6446] +24-11-19 20:31:28 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:31:28 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:28 | D | sum error = [ 14.6132, 15.6528, 16.7530, 17.9256, 19.1709] +24-11-19 20:31:28 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:31:28 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:28 | D | sum error = [ 20.4745, 21.8763, 23.3467, 24.9341, 26.5648] +24-11-19 20:31:28 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:31:28 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:28 | D | sum error = [ 28.3120, 30.1529, 32.0845, 34.1314, 36.2846] +24-11-19 20:31:28 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:31:28 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:28 | D | sum error = [ 38.5422, 40.9324, 43.4415, 46.0673, 48.8435] +24-11-19 20:31:28 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:31:28 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:28 | D | sum error = [ 51.7538, 54.8031, 58.0003, 61.3770, 64.8932] +24-11-19 20:31:28 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:31:28 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:28 | D | sum error = [ 68.5861, 72.4615, 76.5101, 80.7601, 85.2011] +24-11-19 20:31:28 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:31:28 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:28 | D | sum error = [ 89.8357, 94.6838, 99.7465, 105.0362, 110.5357] +24-11-19 20:31:28 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:31:28 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:28 | D | sum error = [ 116.2795, 122.2549, 128.4778, 134.9597, 141.6940] +24-11-19 20:31:28 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:31:28 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:28 | D | sum error = [ 148.7000, 155.9760, 163.5396, 171.3902, 179.5350] +24-11-19 20:31:28 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:31:28 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:28 | D | sum error = [ 187.9859, 196.7383, 205.8039, 215.1810, 224.8943] +24-11-19 20:31:28 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:31:28 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:28 | D | sum error = [ 234.9420, 245.3156, 256.0440, 267.1305, 278.5659] +24-11-19 20:31:28 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:31:28 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:28 | D | sum error = [ 290.3552, 302.5104, 315.0459, 327.9417, 341.2206] +24-11-19 20:31:28 | D | best error = [ 4.9312, 4.9312, 4.9312, 4.9312, 4.9312] +24-11-19 20:31:28 | D | + error = [4.9312] +24-11-19 20:31:28 | D | - Calibrating model.layers.15.mlp.gate_proj.weight +24-11-19 20:31:28 | D | + w: sint8 +24-11-19 20:31:28 | D | + x: None +24-11-19 20:31:28 | D | + y: None +24-11-19 20:31:28 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:28 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:31:28 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:31:28 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:31:28 | D | - range ratio = [ 1.0000] +24-11-19 20:31:28 | D | sum error = [ 7.1842] +24-11-19 20:31:28 | D | best error = [ 7.1842] +24-11-19 20:31:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:29 | D | sum error = [ 7.1498, 7.1236, 7.1600, 7.2399, 7.3489] +24-11-19 20:31:29 | D | best error = [ 6.6704, 6.4709, 6.3635, 6.3019, 6.2714] +24-11-19 20:31:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:29 | D | sum error = [ 7.5751, 7.8294, 8.1447, 8.5282, 8.9876] +24-11-19 20:31:29 | D | best error = [ 6.2560, 6.2493, 6.2467, 6.2458, 6.2456] +24-11-19 20:31:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:29 | D | sum error = [ 9.5112, 10.1125, 10.7899, 11.5528, 12.3673] +24-11-19 20:31:29 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:31:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:29 | D | sum error = [ 13.2783, 14.2454, 15.3032, 16.4565, 17.6658] +24-11-19 20:31:29 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:31:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:29 | D | sum error = [ 19.0040, 20.4012, 21.9020, 23.5479, 25.2953] +24-11-19 20:31:29 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:31:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:29 | D | sum error = [ 27.1373, 29.1167, 31.2304, 33.4958, 35.8766] +24-11-19 20:31:29 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:31:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:29 | D | sum error = [ 38.4355, 41.1515, 44.0487, 47.1412, 50.4282] +24-11-19 20:31:29 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:31:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:29 | D | sum error = [ 53.9730, 57.6983, 61.6757, 65.8970, 70.4025] +24-11-19 20:31:29 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:31:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:29 | D | sum error = [ 75.1969, 80.2865, 85.7059, 91.4983, 97.6328] +24-11-19 20:31:29 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:31:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:29 | D | sum error = [ 104.1992, 111.1447, 118.5278, 126.3842, 134.6788] +24-11-19 20:31:29 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:31:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:29 | D | sum error = [ 143.4938, 152.8109, 162.6896, 173.1647, 184.2237] +24-11-19 20:31:29 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:31:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:29 | D | sum error = [ 195.9151, 208.3215, 221.3939, 235.1823, 249.6876] +24-11-19 20:31:29 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:31:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:29 | D | sum error = [ 265.0084, 281.0948, 298.0276, 315.7836, 334.4542] +24-11-19 20:31:29 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:31:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:29 | D | sum error = [ 354.0135, 374.4759, 395.8749, 418.2456, 441.5500] +24-11-19 20:31:29 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:31:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:29 | D | sum error = [ 465.8568, 491.1533, 517.4498, 544.7453, 573.0596] +24-11-19 20:31:29 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:31:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:29 | D | sum error = [ 602.3934, 632.7497, 664.1442, 696.5324, 729.9189] +24-11-19 20:31:29 | D | best error = [ 6.2456, 6.2456, 6.2456, 6.2456, 6.2456] +24-11-19 20:31:29 | D | + error = [6.2456] +24-11-19 20:31:29 | D | - Calibrating model.layers.15.mlp.down_proj.weight +24-11-19 20:31:29 | D | + w: sint8 +24-11-19 20:31:29 | D | + x: None +24-11-19 20:31:29 | D | + y: None +24-11-19 20:31:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:31:29 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:31:29 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:31:30 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:31:30 | D | - range ratio = [ 1.0000] +24-11-19 20:31:30 | D | sum error = [ 0.8763] +24-11-19 20:31:30 | D | best error = [ 0.8763] +24-11-19 20:31:31 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:31:31 | D | sum error = [ 0.8670, 0.8617, 0.8584, 0.8541, 0.8515] +24-11-19 20:31:31 | D | best error = [ 0.8409, 0.8240, 0.8125, 0.8035, 0.7968] +24-11-19 20:31:31 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:31:31 | D | sum error = [ 0.8561, 0.8597, 0.8677, 0.8780, 0.8916] +24-11-19 20:31:31 | D | best error = [ 0.7917, 0.7879, 0.7853, 0.7836, 0.7818] +24-11-19 20:31:31 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:31:31 | D | sum error = [ 0.9122, 0.9357, 0.9651, 0.9992, 1.0382] +24-11-19 20:31:31 | D | best error = [ 0.7807, 0.7799, 0.7795, 0.7791, 0.7789] +24-11-19 20:31:31 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:31:31 | D | sum error = [ 1.0854, 1.1376, 1.1940, 1.2615, 1.3334] +24-11-19 20:31:31 | D | best error = [ 0.7788, 0.7787, 0.7786, 0.7785, 0.7785] +24-11-19 20:31:31 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:31:31 | D | sum error = [ 1.4112, 1.4983, 1.5953, 1.6979, 1.8089] +24-11-19 20:31:31 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 20:31:31 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:31:31 | D | sum error = [ 1.9289, 2.0588, 2.1980, 2.3471, 2.5060] +24-11-19 20:31:31 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 20:31:31 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:31:31 | D | sum error = [ 2.6767, 2.8583, 3.0519, 3.2576, 3.4738] +24-11-19 20:31:31 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 20:31:31 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:31:31 | D | sum error = [ 3.7082, 3.9552, 4.2176, 4.4949, 4.7877] +24-11-19 20:31:31 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 20:31:31 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:31:31 | D | sum error = [ 5.0992, 5.4286, 5.7777, 6.1456, 6.5351] +24-11-19 20:31:31 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 20:31:31 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:31:31 | D | sum error = [ 6.9448, 7.3762, 7.8330, 8.3138, 8.8180] +24-11-19 20:31:31 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 20:31:31 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:31:31 | D | sum error = [ 9.3495, 9.9091, 10.4961, 11.1141, 11.7623] +24-11-19 20:31:31 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 20:31:31 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:31:31 | D | sum error = [ 12.4422, 13.1556, 13.9032, 14.6871, 15.5070] +24-11-19 20:31:31 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 20:31:31 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:31:31 | D | sum error = [ 16.3645, 17.2608, 18.1967, 19.1742, 20.1937] +24-11-19 20:31:31 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 20:31:31 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:31:31 | D | sum error = [ 21.2581, 22.3675, 23.5233, 24.7261, 25.9753] +24-11-19 20:31:31 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 20:31:31 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:31:31 | D | sum error = [ 27.2750, 28.6267, 30.0285, 31.4828, 32.9919] +24-11-19 20:31:31 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 20:31:31 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:31:31 | D | sum error = [ 34.5560, 36.1768, 37.8522, 39.5851, 41.3765] +24-11-19 20:31:31 | D | best error = [ 0.7784, 0.7784, 0.7784, 0.7784, 0.7784] +24-11-19 20:31:31 | D | + error = [0.7784] +24-11-19 20:31:31 | D | - Quantizing model.layers.15.self_attn.q_proj.weight +24-11-19 20:31:32 | D | - Quantizing model.layers.15.self_attn.k_proj.weight +24-11-19 20:31:33 | D | - Quantizing model.layers.15.self_attn.v_proj.weight +24-11-19 20:31:35 | D | - Quantizing model.layers.15.self_attn.o_proj.weight +24-11-19 20:31:36 | D | - Quantizing model.layers.15.mlp.up_proj.weight +24-11-19 20:31:37 | D | - Quantizing model.layers.15.mlp.gate_proj.weight +24-11-19 20:31:38 | D | - Quantizing model.layers.15.mlp.down_proj.weight +24-11-19 20:31:48 | D | - Quantizing layer model.layers.16 +24-11-19 20:31:48 | D | - Calibrating model.layers.16.self_attn.q_proj.weight +24-11-19 20:31:48 | D | + w: sint8 +24-11-19 20:31:48 | D | + x: None +24-11-19 20:31:48 | D | + y: None +24-11-19 20:31:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:31:48 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:31:48 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:31:49 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:31:49 | D | - range ratio = [ 1.0000] +24-11-19 20:31:49 | D | sum error = [ 4.4274] +24-11-19 20:31:49 | D | best error = [ 4.4274] +24-11-19 20:32:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:01 | D | sum error = [ 4.3395, 4.3652, 4.5212, 4.5314, 4.5321] +24-11-19 20:32:01 | D | best error = [ 4.3395, 4.3395, 4.3395, 4.3395, 4.3395] +24-11-19 20:32:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:01 | D | sum error = [ 4.7907, 4.9057, 5.0332, 5.3838, 5.7486] +24-11-19 20:32:01 | D | best error = [ 4.3395, 4.3395, 4.3395, 4.3395, 4.3395] +24-11-19 20:32:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:01 | D | sum error = [ 5.9476, 6.4789, 7.0289, 7.6079, 8.2632] +24-11-19 20:32:01 | D | best error = [ 4.3395, 4.3395, 4.3395, 4.3395, 4.3395] +24-11-19 20:32:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:01 | D | sum error = [ 9.1596, 9.7563, 10.6311, 11.7480, 12.5105] +24-11-19 20:32:01 | D | best error = [ 4.3395, 4.3395, 4.3395, 4.3395, 4.3395] +24-11-19 20:32:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:01 | D | sum error = [ 13.5672, 15.0457, 16.4766, 17.9303, 19.4333] +24-11-19 20:32:01 | D | best error = [ 4.3395, 4.3395, 4.3395, 4.3395, 4.3395] +24-11-19 20:32:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:01 | D | sum error = [ 21.1257, 23.1984, 24.9678, 27.4506, 30.0077] +24-11-19 20:32:01 | D | best error = [ 4.3395, 4.3395, 4.3395, 4.3395, 4.3395] +24-11-19 20:32:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:01 | D | sum error = [ 32.4945, 35.5990, 38.5434, 42.0344, 45.7687] +24-11-19 20:32:01 | D | best error = [ 4.3395, 4.3395, 4.3395, 4.3395, 4.3395] +24-11-19 20:32:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:01 | D | sum error = [ 49.6335, 53.7112, 58.0946, 62.7419, 67.6984] +24-11-19 20:32:01 | D | best error = [ 4.3395, 4.3395, 4.3395, 4.3395, 4.3395] +24-11-19 20:32:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:01 | D | sum error = [ 72.8080, 78.3356, 83.9308, 90.3141, 97.1357] +24-11-19 20:32:01 | D | best error = [ 4.3395, 4.3395, 4.3395, 4.3395, 4.3395] +24-11-19 20:32:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:01 | D | sum error = [ 104.2442, 111.6197, 119.4373, 127.9477, 137.2217] +24-11-19 20:32:01 | D | best error = [ 4.3395, 4.3395, 4.3395, 4.3395, 4.3395] +24-11-19 20:32:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:01 | D | sum error = [ 147.1477, 157.1706, 168.0767, 179.7819, 192.1723] +24-11-19 20:32:01 | D | best error = [ 4.3395, 4.3395, 4.3395, 4.3395, 4.3395] +24-11-19 20:32:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:01 | D | sum error = [ 205.4779, 219.1190, 233.8316, 249.3357, 265.4827] +24-11-19 20:32:01 | D | best error = [ 4.3395, 4.3395, 4.3395, 4.3395, 4.3395] +24-11-19 20:32:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:01 | D | sum error = [ 282.6814, 301.2422, 320.2435, 340.8055, 361.9886] +24-11-19 20:32:01 | D | best error = [ 4.3395, 4.3395, 4.3395, 4.3395, 4.3395] +24-11-19 20:32:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:01 | D | sum error = [ 384.6613, 408.2699, 432.7628, 459.2537, 486.7700] +24-11-19 20:32:01 | D | best error = [ 4.3395, 4.3395, 4.3395, 4.3395, 4.3395] +24-11-19 20:32:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:01 | D | sum error = [ 515.0900, 545.0435, 576.0104, 608.1585, 641.5324] +24-11-19 20:32:01 | D | best error = [ 4.3395, 4.3395, 4.3395, 4.3395, 4.3395] +24-11-19 20:32:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:01 | D | sum error = [ 675.6515, 710.5652, 746.4967, 783.1032, 820.1865] +24-11-19 20:32:01 | D | best error = [ 4.3395, 4.3395, 4.3395, 4.3395, 4.3395] +24-11-19 20:32:01 | D | + error = [4.3395] +24-11-19 20:32:02 | D | - Calibrating model.layers.16.self_attn.k_proj.weight +24-11-19 20:32:02 | D | + w: sint8 +24-11-19 20:32:02 | D | + x: None +24-11-19 20:32:02 | D | + y: None +24-11-19 20:32:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:32:02 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:32:02 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:32:02 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:32:02 | D | - range ratio = [ 1.0000] +24-11-19 20:32:02 | D | sum error = [ 4.2126] +24-11-19 20:32:02 | D | best error = [ 4.2126] +24-11-19 20:32:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:15 | D | sum error = [ 4.2160, 4.2100, 4.5515, 4.0941, 4.0417] +24-11-19 20:32:15 | D | best error = [ 4.2126, 4.2100, 4.2100, 4.0941, 4.0417] +24-11-19 20:32:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:15 | D | sum error = [ 4.9865, 4.8453, 4.3744, 4.5882, 5.6223] +24-11-19 20:32:15 | D | best error = [ 4.0417, 4.0417, 4.0417, 4.0417, 4.0417] +24-11-19 20:32:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:15 | D | sum error = [ 5.4687, 5.5417, 5.7713, 6.3582, 6.7278] +24-11-19 20:32:15 | D | best error = [ 4.0417, 4.0417, 4.0417, 4.0417, 4.0417] +24-11-19 20:32:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:15 | D | sum error = [ 7.3465, 7.8760, 8.0690, 8.5066, 9.5047] +24-11-19 20:32:15 | D | best error = [ 4.0417, 4.0417, 4.0417, 4.0417, 4.0417] +24-11-19 20:32:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:15 | D | sum error = [ 10.0019, 10.7205, 12.1240, 12.5781, 13.2582] +24-11-19 20:32:15 | D | best error = [ 4.0417, 4.0417, 4.0417, 4.0417, 4.0417] +24-11-19 20:32:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:15 | D | sum error = [ 14.7115, 15.5767, 17.3627, 18.8119, 20.0840] +24-11-19 20:32:15 | D | best error = [ 4.0417, 4.0417, 4.0417, 4.0417, 4.0417] +24-11-19 20:32:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:15 | D | sum error = [ 21.8558, 23.7421, 25.2993, 27.3198, 29.6431] +24-11-19 20:32:15 | D | best error = [ 4.0417, 4.0417, 4.0417, 4.0417, 4.0417] +24-11-19 20:32:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:15 | D | sum error = [ 31.6548, 34.5549, 36.5581, 39.8296, 42.6960] +24-11-19 20:32:15 | D | best error = [ 4.0417, 4.0417, 4.0417, 4.0417, 4.0417] +24-11-19 20:32:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:15 | D | sum error = [ 45.1839, 48.5488, 51.4572, 55.5170, 59.7130] +24-11-19 20:32:15 | D | best error = [ 4.0417, 4.0417, 4.0417, 4.0417, 4.0417] +24-11-19 20:32:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:15 | D | sum error = [ 64.0504, 69.1320, 74.7254, 81.2811, 87.8377] +24-11-19 20:32:15 | D | best error = [ 4.0417, 4.0417, 4.0417, 4.0417, 4.0417] +24-11-19 20:32:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:15 | D | sum error = [ 95.4529, 103.7122, 112.8971, 122.4707, 133.7898] +24-11-19 20:32:15 | D | best error = [ 4.0417, 4.0417, 4.0417, 4.0417, 4.0417] +24-11-19 20:32:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:15 | D | sum error = [ 146.4175, 159.6783, 173.0009, 187.5947, 203.0766] +24-11-19 20:32:15 | D | best error = [ 4.0417, 4.0417, 4.0417, 4.0417, 4.0417] +24-11-19 20:32:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:15 | D | sum error = [ 219.3045, 236.5318, 255.4949, 275.0250, 296.4888] +24-11-19 20:32:15 | D | best error = [ 4.0417, 4.0417, 4.0417, 4.0417, 4.0417] +24-11-19 20:32:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:15 | D | sum error = [ 319.1764, 343.6317, 369.5886, 395.9833, 423.8211] +24-11-19 20:32:15 | D | best error = [ 4.0417, 4.0417, 4.0417, 4.0417, 4.0417] +24-11-19 20:32:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:15 | D | sum error = [ 453.5243, 485.3850, 517.6773, 552.4231, 587.8309] +24-11-19 20:32:15 | D | best error = [ 4.0417, 4.0417, 4.0417, 4.0417, 4.0417] +24-11-19 20:32:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:15 | D | sum error = [ 624.7209, 663.4350, 703.6041, 744.4556, 786.2844] +24-11-19 20:32:15 | D | best error = [ 4.0417, 4.0417, 4.0417, 4.0417, 4.0417] +24-11-19 20:32:15 | D | + error = [4.0417] +24-11-19 20:32:15 | D | - Calibrating model.layers.16.self_attn.v_proj.weight +24-11-19 20:32:15 | D | + w: sint8 +24-11-19 20:32:15 | D | + x: None +24-11-19 20:32:15 | D | + y: None +24-11-19 20:32:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:15 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:32:15 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:32:16 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:32:16 | D | - range ratio = [ 1.0000] +24-11-19 20:32:16 | D | sum error = [ 1.4683] +24-11-19 20:32:16 | D | best error = [ 1.4683] +24-11-19 20:32:16 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:16 | D | sum error = [ 1.4495, 1.4512, 1.4634, 1.4703, 1.4987] +24-11-19 20:32:16 | D | best error = [ 1.3528, 1.3116, 1.2902, 1.2772, 1.2715] +24-11-19 20:32:16 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:16 | D | sum error = [ 1.5349, 1.5797, 1.6524, 1.7303, 1.8125] +24-11-19 20:32:16 | D | best error = [ 1.2679, 1.2667, 1.2662, 1.2661, 1.2661] +24-11-19 20:32:16 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:16 | D | sum error = [ 1.9113, 2.0451, 2.1737, 2.3226, 2.4734] +24-11-19 20:32:16 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:32:16 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:16 | D | sum error = [ 2.6628, 2.8524, 3.0448, 3.2736, 3.5264] +24-11-19 20:32:16 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:32:16 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:16 | D | sum error = [ 3.7739, 4.0546, 4.3470, 4.6351, 4.9615] +24-11-19 20:32:16 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:32:16 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:16 | D | sum error = [ 5.3259, 5.6923, 6.0860, 6.4863, 6.9203] +24-11-19 20:32:16 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:32:16 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:16 | D | sum error = [ 7.3761, 7.8675, 8.3753, 8.9042, 9.4809] +24-11-19 20:32:16 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:32:16 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:16 | D | sum error = [ 10.0830, 10.7143, 11.3797, 12.0820, 12.8087] +24-11-19 20:32:16 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:32:16 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:16 | D | sum error = [ 13.5888, 14.4031, 15.2501, 16.1473, 17.0875] +24-11-19 20:32:16 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:32:16 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:16 | D | sum error = [ 18.0690, 19.1064, 20.1731, 21.3051, 22.4918] +24-11-19 20:32:16 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:32:16 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:16 | D | sum error = [ 23.7134, 24.9919, 26.3369, 27.7388, 29.1910] +24-11-19 20:32:16 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:32:16 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:16 | D | sum error = [ 30.7102, 32.2966, 33.9402, 35.6497, 37.4311] +24-11-19 20:32:16 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:32:16 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:16 | D | sum error = [ 39.2878, 41.2211, 43.2281, 45.3211, 47.4846] +24-11-19 20:32:16 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:32:16 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:16 | D | sum error = [ 49.7325, 52.0635, 54.4681, 56.9734, 59.5746] +24-11-19 20:32:16 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:32:16 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:16 | D | sum error = [ 62.2568, 65.0297, 67.8947, 70.8476, 73.8971] +24-11-19 20:32:16 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:32:16 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:16 | D | sum error = [ 77.0441, 80.2897, 83.6484, 87.1050, 90.6602] +24-11-19 20:32:16 | D | best error = [ 1.2661, 1.2661, 1.2661, 1.2661, 1.2661] +24-11-19 20:32:16 | D | + error = [1.2661] +24-11-19 20:32:16 | D | - Calibrating model.layers.16.self_attn.o_proj.weight +24-11-19 20:32:16 | D | + w: sint8 +24-11-19 20:32:16 | D | + x: None +24-11-19 20:32:16 | D | + y: None +24-11-19 20:32:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:16 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:32:16 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:32:16 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:32:16 | D | - range ratio = [ 1.0000] +24-11-19 20:32:16 | D | sum error = [ 0.6277] +24-11-19 20:32:16 | D | best error = [ 0.6277] +24-11-19 20:32:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:17 | D | sum error = [ 0.6227, 0.6200, 0.6188, 0.6152, 0.6179] +24-11-19 20:32:17 | D | best error = [ 0.5784, 0.5565, 0.5427, 0.5331, 0.5259] +24-11-19 20:32:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:17 | D | sum error = [ 0.6236, 0.6279, 0.6367, 0.6484, 0.6660] +24-11-19 20:32:17 | D | best error = [ 0.5207, 0.5156, 0.5123, 0.5093, 0.5072] +24-11-19 20:32:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:17 | D | sum error = [ 0.6838, 0.7058, 0.7315, 0.7625, 0.7972] +24-11-19 20:32:17 | D | best error = [ 0.5050, 0.5036, 0.5023, 0.5011, 0.5003] +24-11-19 20:32:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:17 | D | sum error = [ 0.8354, 0.8744, 0.9234, 0.9754, 1.0309] +24-11-19 20:32:17 | D | best error = [ 0.4996, 0.4989, 0.4983, 0.4980, 0.4976] +24-11-19 20:32:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:17 | D | sum error = [ 1.0907, 1.1554, 1.2242, 1.3004, 1.3817] +24-11-19 20:32:17 | D | best error = [ 0.4975, 0.4974, 0.4972, 0.4971, 0.4970] +24-11-19 20:32:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:17 | D | sum error = [ 1.4690, 1.5601, 1.6581, 1.7620, 1.8733] +24-11-19 20:32:17 | D | best error = [ 0.4970, 0.4970, 0.4969, 0.4969, 0.4968] +24-11-19 20:32:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:17 | D | sum error = [ 1.9894, 2.1161, 2.2464, 2.3872, 2.5320] +24-11-19 20:32:17 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:32:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:17 | D | sum error = [ 2.6885, 2.8545, 3.0268, 3.2090, 3.4015] +24-11-19 20:32:17 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:32:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:17 | D | sum error = [ 3.6053, 3.8183, 4.0474, 4.2827, 4.5334] +24-11-19 20:32:17 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:32:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:17 | D | sum error = [ 4.7988, 5.0756, 5.3650, 5.6738, 5.9943] +24-11-19 20:32:17 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:32:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:17 | D | sum error = [ 6.3286, 6.6785, 7.0473, 7.4309, 7.8323] +24-11-19 20:32:17 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:32:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:17 | D | sum error = [ 8.2516, 8.6893, 9.1471, 9.6252, 10.1227] +24-11-19 20:32:17 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:32:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:17 | D | sum error = [ 10.6429, 11.1856, 11.7522, 12.3424, 12.9576] +24-11-19 20:32:17 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:32:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:17 | D | sum error = [ 13.5998, 14.2683, 14.9621, 15.6864, 16.4346] +24-11-19 20:32:17 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:32:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:17 | D | sum error = [ 17.2124, 18.0218, 18.8632, 19.7360, 20.6418] +24-11-19 20:32:17 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:32:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:17 | D | sum error = [ 21.5780, 22.5515, 23.5577, 24.6004, 25.6815] +24-11-19 20:32:17 | D | best error = [ 0.4968, 0.4968, 0.4968, 0.4968, 0.4968] +24-11-19 20:32:17 | D | + error = [0.4968] +24-11-19 20:32:17 | D | - Calibrating model.layers.16.mlp.up_proj.weight +24-11-19 20:32:17 | D | + w: sint8 +24-11-19 20:32:17 | D | + x: None +24-11-19 20:32:17 | D | + y: None +24-11-19 20:32:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:17 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:32:17 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:32:17 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:32:17 | D | - range ratio = [ 1.0000] +24-11-19 20:32:17 | D | sum error = [ 5.9253] +24-11-19 20:32:17 | D | best error = [ 5.9253] +24-11-19 20:32:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:18 | D | sum error = [ 5.8708, 5.8619, 5.8930, 5.9624, 6.0604] +24-11-19 20:32:18 | D | best error = [ 5.5094, 5.3475, 5.2629, 5.2147, 5.1900] +24-11-19 20:32:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:18 | D | sum error = [ 6.2225, 6.4194, 6.6830, 7.0001, 7.3703] +24-11-19 20:32:18 | D | best error = [ 5.1771, 5.1717, 5.1697, 5.1692, 5.1691] +24-11-19 20:32:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:18 | D | sum error = [ 7.7782, 8.2705, 8.7928, 9.3919, 10.0397] +24-11-19 20:32:18 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 20:32:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:18 | D | sum error = [ 10.7522, 11.4994, 12.3190, 13.2023, 14.1520] +24-11-19 20:32:18 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 20:32:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:18 | D | sum error = [ 15.1581, 16.2356, 17.3723, 18.6017, 19.8787] +24-11-19 20:32:18 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 20:32:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:18 | D | sum error = [ 21.2459, 22.6769, 24.2183, 25.8339, 27.5517] +24-11-19 20:32:18 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 20:32:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:18 | D | sum error = [ 29.3302, 31.2322, 33.2266, 35.3339, 37.5414] +24-11-19 20:32:18 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 20:32:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:18 | D | sum error = [ 39.8757, 42.3320, 44.9101, 47.5981, 50.4524] +24-11-19 20:32:18 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 20:32:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:18 | D | sum error = [ 53.4531, 56.5861, 59.8766, 63.3223, 66.9339] +24-11-19 20:32:18 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 20:32:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:18 | D | sum error = [ 70.7163, 74.6736, 78.8162, 83.1520, 87.6799] +24-11-19 20:32:18 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 20:32:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:18 | D | sum error = [ 92.4031, 97.3334, 102.4844, 107.8562, 113.4468] +24-11-19 20:32:18 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 20:32:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:18 | D | sum error = [ 119.2693, 125.3229, 131.6337, 138.1892, 144.9932] +24-11-19 20:32:18 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 20:32:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:18 | D | sum error = [ 152.0719, 159.4081, 167.0241, 174.9071, 183.0964] +24-11-19 20:32:18 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 20:32:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:18 | D | sum error = [ 191.5726, 200.3579, 209.4582, 218.8568, 228.5886] +24-11-19 20:32:18 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 20:32:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:18 | D | sum error = [ 238.6416, 249.0263, 259.7457, 270.8140, 282.2107] +24-11-19 20:32:18 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 20:32:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:18 | D | sum error = [ 293.9707, 306.0817, 318.5270, 331.3495, 344.5278] +24-11-19 20:32:18 | D | best error = [ 5.1691, 5.1691, 5.1691, 5.1691, 5.1691] +24-11-19 20:32:18 | D | + error = [5.1691] +24-11-19 20:32:18 | D | - Calibrating model.layers.16.mlp.gate_proj.weight +24-11-19 20:32:18 | D | + w: sint8 +24-11-19 20:32:18 | D | + x: None +24-11-19 20:32:18 | D | + y: None +24-11-19 20:32:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:18 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:32:18 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:32:19 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:32:19 | D | - range ratio = [ 1.0000] +24-11-19 20:32:19 | D | sum error = [ 7.7746] +24-11-19 20:32:19 | D | best error = [ 7.7746] +24-11-19 20:32:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:20 | D | sum error = [ 7.6989, 7.6778, 7.7144, 7.8136, 7.9645] +24-11-19 20:32:20 | D | best error = [ 7.2206, 7.0132, 6.9005, 6.8399, 6.8061] +24-11-19 20:32:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:20 | D | sum error = [ 8.1476, 8.4544, 8.7966, 9.2107, 9.7074] +24-11-19 20:32:20 | D | best error = [ 6.7890, 6.7828, 6.7799, 6.7790, 6.7789] +24-11-19 20:32:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:20 | D | sum error = [ 10.2840, 10.9301, 11.6476, 12.4713, 13.3166] +24-11-19 20:32:20 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 20:32:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:20 | D | sum error = [ 14.2946, 15.3549, 16.4904, 17.6994, 19.0173] +24-11-19 20:32:20 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 20:32:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:20 | D | sum error = [ 20.4309, 21.9273, 23.5462, 25.2748, 27.0737] +24-11-19 20:32:20 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 20:32:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:20 | D | sum error = [ 29.0327, 31.1109, 33.3452, 35.6838, 38.2198] +24-11-19 20:32:20 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 20:32:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:20 | D | sum error = [ 40.8824, 43.7117, 46.7531, 49.9643, 53.4079] +24-11-19 20:32:20 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 20:32:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:20 | D | sum error = [ 57.0391, 60.9151, 65.0292, 69.3950, 74.0136] +24-11-19 20:32:20 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 20:32:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:20 | D | sum error = [ 78.9325, 84.1718, 89.7126, 95.5800, 101.8137] +24-11-19 20:32:20 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 20:32:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:20 | D | sum error = [ 108.4326, 115.4389, 122.8708, 130.7493, 139.0918] +24-11-19 20:32:20 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 20:32:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:20 | D | sum error = [ 147.9046, 157.2425, 167.1288, 177.5710, 188.5834] +24-11-19 20:32:20 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 20:32:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:20 | D | sum error = [ 200.1944, 212.4616, 225.3874, 238.9805, 253.2924] +24-11-19 20:32:20 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 20:32:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:20 | D | sum error = [ 268.3456, 284.1613, 300.7382, 318.1460, 336.3895] +24-11-19 20:32:20 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 20:32:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:20 | D | sum error = [ 355.4767, 375.4411, 396.2939, 418.0868, 440.7487] +24-11-19 20:32:20 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 20:32:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:20 | D | sum error = [ 464.3813, 488.9708, 514.5099, 541.0218, 568.5314] +24-11-19 20:32:20 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 20:32:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:20 | D | sum error = [ 597.0305, 626.5283, 656.9963, 688.4566, 720.9204] +24-11-19 20:32:20 | D | best error = [ 6.7787, 6.7787, 6.7787, 6.7787, 6.7787] +24-11-19 20:32:20 | D | + error = [6.7787] +24-11-19 20:32:20 | D | - Calibrating model.layers.16.mlp.down_proj.weight +24-11-19 20:32:20 | D | + w: sint8 +24-11-19 20:32:20 | D | + x: None +24-11-19 20:32:20 | D | + y: None +24-11-19 20:32:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:32:20 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:32:20 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:32:20 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:32:20 | D | - range ratio = [ 1.0000] +24-11-19 20:32:20 | D | sum error = [ 0.8971] +24-11-19 20:32:20 | D | best error = [ 0.8971] +24-11-19 20:32:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:21 | D | sum error = [ 0.8891, 0.8830, 0.8788, 0.8766, 0.8738] +24-11-19 20:32:21 | D | best error = [ 0.8583, 0.8395, 0.8280, 0.8193, 0.8126] +24-11-19 20:32:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:21 | D | sum error = [ 0.8759, 0.8810, 0.8906, 0.9009, 0.9184] +24-11-19 20:32:21 | D | best error = [ 0.8074, 0.8033, 0.8001, 0.7977, 0.7959] +24-11-19 20:32:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:21 | D | sum error = [ 0.9360, 0.9633, 0.9942, 1.0290, 1.0697] +24-11-19 20:32:21 | D | best error = [ 0.7945, 0.7936, 0.7930, 0.7926, 0.7923] +24-11-19 20:32:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:21 | D | sum error = [ 1.1145, 1.1710, 1.2314, 1.2985, 1.3710] +24-11-19 20:32:21 | D | best error = [ 0.7922, 0.7920, 0.7919, 0.7919, 0.7918] +24-11-19 20:32:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:21 | D | sum error = [ 1.4532, 1.5433, 1.6405, 1.7470, 1.8601] +24-11-19 20:32:21 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 20:32:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:21 | D | sum error = [ 1.9867, 2.1194, 2.2619, 2.4165, 2.5809] +24-11-19 20:32:21 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 20:32:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:21 | D | sum error = [ 2.7562, 2.9440, 3.1432, 3.3573, 3.5835] +24-11-19 20:32:21 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 20:32:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:21 | D | sum error = [ 3.8251, 4.0816, 4.3527, 4.6397, 4.9454] +24-11-19 20:32:21 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 20:32:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:21 | D | sum error = [ 5.2686, 5.6108, 5.9708, 6.3514, 6.7546] +24-11-19 20:32:21 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 20:32:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:21 | D | sum error = [ 7.1801, 7.6278, 8.1002, 8.5964, 9.1213] +24-11-19 20:32:21 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 20:32:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:21 | D | sum error = [ 9.6717, 10.2510, 10.8603, 11.5011, 12.1738] +24-11-19 20:32:21 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 20:32:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:21 | D | sum error = [ 12.8822, 13.6242, 14.4028, 15.2177, 16.0717] +24-11-19 20:32:21 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 20:32:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:21 | D | sum error = [ 16.9659, 17.9007, 18.8791, 19.9013, 20.9692] +24-11-19 20:32:21 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 20:32:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:21 | D | sum error = [ 22.0827, 23.2441, 24.4542, 25.7149, 27.0246] +24-11-19 20:32:21 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 20:32:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:21 | D | sum error = [ 28.3887, 29.8081, 31.2846, 32.8173, 34.4087] +24-11-19 20:32:21 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 20:32:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:21 | D | sum error = [ 36.0592, 37.7668, 39.5347, 41.3633, 43.2517] +24-11-19 20:32:21 | D | best error = [ 0.7918, 0.7918, 0.7918, 0.7918, 0.7918] +24-11-19 20:32:21 | D | + error = [0.7918] +24-11-19 20:32:21 | D | - Quantizing model.layers.16.self_attn.q_proj.weight +24-11-19 20:32:22 | D | - Quantizing model.layers.16.self_attn.k_proj.weight +24-11-19 20:32:23 | D | - Quantizing model.layers.16.self_attn.v_proj.weight +24-11-19 20:32:24 | D | - Quantizing model.layers.16.self_attn.o_proj.weight +24-11-19 20:32:25 | D | - Quantizing model.layers.16.mlp.up_proj.weight +24-11-19 20:32:26 | D | - Quantizing model.layers.16.mlp.gate_proj.weight +24-11-19 20:32:27 | D | - Quantizing model.layers.16.mlp.down_proj.weight +24-11-19 20:32:37 | D | - Quantizing layer model.layers.17 +24-11-19 20:32:37 | D | - Calibrating model.layers.17.self_attn.q_proj.weight +24-11-19 20:32:37 | D | + w: sint8 +24-11-19 20:32:37 | D | + x: None +24-11-19 20:32:37 | D | + y: None +24-11-19 20:32:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:32:37 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:32:37 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:32:37 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:32:37 | D | - range ratio = [ 1.0000] +24-11-19 20:32:37 | D | sum error = [ 4.1651] +24-11-19 20:32:37 | D | best error = [ 4.1651] +24-11-19 20:32:49 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:32:49 | D | sum error = [ 4.1906, 4.1089, 4.1467, 4.2248, 4.3631] +24-11-19 20:32:49 | D | best error = [ 4.1651, 4.1089, 4.1089, 4.1089, 4.1089] +24-11-19 20:32:49 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:32:49 | D | sum error = [ 4.4244, 4.6251, 4.9215, 5.0498, 5.3692] +24-11-19 20:32:49 | D | best error = [ 4.1089, 4.1089, 4.1089, 4.1089, 4.1089] +24-11-19 20:32:49 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:32:49 | D | sum error = [ 5.5287, 5.9277, 6.5964, 6.8922, 7.4604] +24-11-19 20:32:49 | D | best error = [ 4.1089, 4.1089, 4.1089, 4.1089, 4.1089] +24-11-19 20:32:49 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:32:49 | D | sum error = [ 8.0863, 8.8430, 9.5306, 10.3447, 11.0769] +24-11-19 20:32:49 | D | best error = [ 4.1089, 4.1089, 4.1089, 4.1089, 4.1089] +24-11-19 20:32:49 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:32:49 | D | sum error = [ 11.9670, 13.0417, 14.0144, 15.2200, 16.5441] +24-11-19 20:32:49 | D | best error = [ 4.1089, 4.1089, 4.1089, 4.1089, 4.1089] +24-11-19 20:32:49 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:32:49 | D | sum error = [ 17.9260, 19.3685, 21.0999, 22.6407, 24.5993] +24-11-19 20:32:49 | D | best error = [ 4.1089, 4.1089, 4.1089, 4.1089, 4.1089] +24-11-19 20:32:49 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:32:49 | D | sum error = [ 26.6500, 28.8241, 31.1542, 33.6606, 36.5218] +24-11-19 20:32:49 | D | best error = [ 4.1089, 4.1089, 4.1089, 4.1089, 4.1089] +24-11-19 20:32:49 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:32:49 | D | sum error = [ 39.2384, 42.5853, 45.9515, 49.6540, 53.8033] +24-11-19 20:32:49 | D | best error = [ 4.1089, 4.1089, 4.1089, 4.1089, 4.1089] +24-11-19 20:32:49 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:32:49 | D | sum error = [ 58.0679, 62.4700, 67.5602, 72.8407, 78.5131] +24-11-19 20:32:49 | D | best error = [ 4.1089, 4.1089, 4.1089, 4.1089, 4.1089] +24-11-19 20:32:49 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:32:49 | D | sum error = [ 84.5341, 90.9774, 97.8235, 105.2600, 113.2594] +24-11-19 20:32:49 | D | best error = [ 4.1089, 4.1089, 4.1089, 4.1089, 4.1089] +24-11-19 20:32:49 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:32:49 | D | sum error = [ 121.8806, 131.3761, 141.4759, 151.9917, 163.6607] +24-11-19 20:32:49 | D | best error = [ 4.1089, 4.1089, 4.1089, 4.1089, 4.1089] +24-11-19 20:32:49 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:32:49 | D | sum error = [ 175.8785, 189.0585, 203.2393, 218.3981, 234.6459] +24-11-19 20:32:49 | D | best error = [ 4.1089, 4.1089, 4.1089, 4.1089, 4.1089] +24-11-19 20:32:49 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:32:49 | D | sum error = [ 251.9161, 270.6258, 290.6638, 312.0116, 334.9249] +24-11-19 20:32:49 | D | best error = [ 4.1089, 4.1089, 4.1089, 4.1089, 4.1089] +24-11-19 20:32:49 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:32:49 | D | sum error = [ 359.7833, 386.2427, 414.4487, 444.8505, 476.5530] +24-11-19 20:32:49 | D | best error = [ 4.1089, 4.1089, 4.1089, 4.1089, 4.1089] +24-11-19 20:32:49 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:32:49 | D | sum error = [ 509.9754, 545.3933, 582.3802, 621.1741, 661.7612] +24-11-19 20:32:49 | D | best error = [ 4.1089, 4.1089, 4.1089, 4.1089, 4.1089] +24-11-19 20:32:49 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:32:49 | D | sum error = [ 703.6411, 746.8386, 791.0668, 836.1195, 881.4029] +24-11-19 20:32:49 | D | best error = [ 4.1089, 4.1089, 4.1089, 4.1089, 4.1089] +24-11-19 20:32:49 | D | + error = [4.1089] +24-11-19 20:32:49 | D | - Calibrating model.layers.17.self_attn.k_proj.weight +24-11-19 20:32:49 | D | + w: sint8 +24-11-19 20:32:49 | D | + x: None +24-11-19 20:32:49 | D | + y: None +24-11-19 20:32:49 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:32:49 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:32:49 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:32:50 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:32:50 | D | - range ratio = [ 1.0000] +24-11-19 20:32:50 | D | sum error = [ 3.7610] +24-11-19 20:32:50 | D | best error = [ 3.7610] +24-11-19 20:33:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:03 | D | sum error = [ 3.5985, 3.7001, 3.8239, 4.1453, 4.3255] +24-11-19 20:33:03 | D | best error = [ 3.5985, 3.5985, 3.5985, 3.5985, 3.5985] +24-11-19 20:33:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:03 | D | sum error = [ 4.0863, 4.3254, 4.9095, 4.3557, 4.5182] +24-11-19 20:33:03 | D | best error = [ 3.5985, 3.5985, 3.5985, 3.5985, 3.5985] +24-11-19 20:33:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:03 | D | sum error = [ 5.1331, 5.9068, 5.7101, 5.9147, 7.5170] +24-11-19 20:33:03 | D | best error = [ 3.5985, 3.5985, 3.5985, 3.5985, 3.5985] +24-11-19 20:33:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:03 | D | sum error = [ 7.3152, 7.8537, 8.4570, 9.0934, 9.8718] +24-11-19 20:33:03 | D | best error = [ 3.5985, 3.5985, 3.5985, 3.5985, 3.5985] +24-11-19 20:33:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:03 | D | sum error = [ 10.3246, 11.4971, 12.1346, 13.6982, 14.3919] +24-11-19 20:33:03 | D | best error = [ 3.5985, 3.5985, 3.5985, 3.5985, 3.5985] +24-11-19 20:33:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:03 | D | sum error = [ 15.6987, 17.0138, 18.0741, 19.7698, 21.5092] +24-11-19 20:33:03 | D | best error = [ 3.5985, 3.5985, 3.5985, 3.5985, 3.5985] +24-11-19 20:33:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:03 | D | sum error = [ 22.5855, 24.9134, 27.2216, 29.0721, 31.0782] +24-11-19 20:33:03 | D | best error = [ 3.5985, 3.5985, 3.5985, 3.5985, 3.5985] +24-11-19 20:33:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:03 | D | sum error = [ 33.5234, 36.3641, 38.3701, 41.3093, 45.2626] +24-11-19 20:33:03 | D | best error = [ 3.5985, 3.5985, 3.5985, 3.5985, 3.5985] +24-11-19 20:33:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:03 | D | sum error = [ 48.1365, 51.6568, 55.8208, 59.8745, 63.6249] +24-11-19 20:33:03 | D | best error = [ 3.5985, 3.5985, 3.5985, 3.5985, 3.5985] +24-11-19 20:33:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:03 | D | sum error = [ 68.4696, 73.5334, 79.1776, 84.1922, 89.9758] +24-11-19 20:33:03 | D | best error = [ 3.5985, 3.5985, 3.5985, 3.5985, 3.5985] +24-11-19 20:33:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:03 | D | sum error = [ 96.1939, 103.2038, 111.1418, 120.0953, 128.8751] +24-11-19 20:33:03 | D | best error = [ 3.5985, 3.5985, 3.5985, 3.5985, 3.5985] +24-11-19 20:33:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:03 | D | sum error = [ 138.9857, 149.7414, 161.9769, 175.1667, 188.9128] +24-11-19 20:33:03 | D | best error = [ 3.5985, 3.5985, 3.5985, 3.5985, 3.5985] +24-11-19 20:33:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:03 | D | sum error = [ 204.5119, 221.5845, 239.2598, 258.2581, 279.1695] +24-11-19 20:33:03 | D | best error = [ 3.5985, 3.5985, 3.5985, 3.5985, 3.5985] +24-11-19 20:33:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:03 | D | sum error = [ 302.2368, 326.5860, 352.6729, 381.0293, 411.2926] +24-11-19 20:33:03 | D | best error = [ 3.5985, 3.5985, 3.5985, 3.5985, 3.5985] +24-11-19 20:33:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:03 | D | sum error = [ 442.7802, 477.1148, 513.0808, 551.2787, 592.0245] +24-11-19 20:33:03 | D | best error = [ 3.5985, 3.5985, 3.5985, 3.5985, 3.5985] +24-11-19 20:33:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:03 | D | sum error = [ 634.2150, 678.0890, 723.7315, 770.3866, 819.0697] +24-11-19 20:33:03 | D | best error = [ 3.5985, 3.5985, 3.5985, 3.5985, 3.5985] +24-11-19 20:33:03 | D | + error = [3.5985] +24-11-19 20:33:03 | D | - Calibrating model.layers.17.self_attn.v_proj.weight +24-11-19 20:33:03 | D | + w: sint8 +24-11-19 20:33:03 | D | + x: None +24-11-19 20:33:03 | D | + y: None +24-11-19 20:33:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:03 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:33:03 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:33:03 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:33:03 | D | - range ratio = [ 1.0000] +24-11-19 20:33:03 | D | sum error = [ 1.6668] +24-11-19 20:33:03 | D | best error = [ 1.6668] +24-11-19 20:33:03 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:03 | D | sum error = [ 1.6654, 1.6562, 1.6656, 1.6857, 1.7149] +24-11-19 20:33:03 | D | best error = [ 1.5439, 1.4955, 1.4716, 1.4581, 1.4506] +24-11-19 20:33:03 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:03 | D | sum error = [ 1.7562, 1.8144, 1.8831, 1.9787, 2.0719] +24-11-19 20:33:03 | D | best error = [ 1.4460, 1.4438, 1.4434, 1.4433, 1.4433] +24-11-19 20:33:03 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:03 | D | sum error = [ 2.2086, 2.3453, 2.4996, 2.6596, 2.8357] +24-11-19 20:33:03 | D | best error = [ 1.4433, 1.4432, 1.4432, 1.4432, 1.4432] +24-11-19 20:33:03 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:03 | D | sum error = [ 3.0480, 3.2495, 3.4911, 3.7507, 4.0038] +24-11-19 20:33:03 | D | best error = [ 1.4432, 1.4432, 1.4432, 1.4432, 1.4432] +24-11-19 20:33:03 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:03 | D | sum error = [ 4.2904, 4.5823, 4.9049, 5.2598, 5.6157] +24-11-19 20:33:03 | D | best error = [ 1.4432, 1.4432, 1.4432, 1.4432, 1.4432] +24-11-19 20:33:03 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:03 | D | sum error = [ 5.9929, 6.3970, 6.8403, 7.2728, 7.7410] +24-11-19 20:33:03 | D | best error = [ 1.4432, 1.4432, 1.4432, 1.4432, 1.4432] +24-11-19 20:33:03 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:03 | D | sum error = [ 8.2471, 8.7805, 9.3370, 9.9355, 10.5505] +24-11-19 20:33:03 | D | best error = [ 1.4432, 1.4432, 1.4432, 1.4432, 1.4432] +24-11-19 20:33:03 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:03 | D | sum error = [ 11.2154, 11.8872, 12.6127, 13.3552, 14.1363] +24-11-19 20:33:03 | D | best error = [ 1.4432, 1.4432, 1.4432, 1.4432, 1.4432] +24-11-19 20:33:03 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:03 | D | sum error = [ 14.9727, 15.8467, 16.7662, 17.7241, 18.7273] +24-11-19 20:33:03 | D | best error = [ 1.4432, 1.4432, 1.4432, 1.4432, 1.4432] +24-11-19 20:33:03 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:03 | D | sum error = [ 19.7847, 20.8915, 22.0462, 23.2528, 24.5139] +24-11-19 20:33:03 | D | best error = [ 1.4432, 1.4432, 1.4432, 1.4432, 1.4432] +24-11-19 20:33:03 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:03 | D | sum error = [ 25.8142, 27.1849, 28.5965, 30.0768, 31.6222] +24-11-19 20:33:03 | D | best error = [ 1.4432, 1.4432, 1.4432, 1.4432, 1.4432] +24-11-19 20:33:03 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:03 | D | sum error = [ 33.2171, 34.8805, 36.6095, 38.3844, 40.2371] +24-11-19 20:33:03 | D | best error = [ 1.4432, 1.4432, 1.4432, 1.4432, 1.4432] +24-11-19 20:33:03 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:03 | D | sum error = [ 42.1582, 44.1559, 46.2219, 48.3622, 50.5678] +24-11-19 20:33:03 | D | best error = [ 1.4432, 1.4432, 1.4432, 1.4432, 1.4432] +24-11-19 20:33:03 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:03 | D | sum error = [ 52.8628, 55.2303, 57.6866, 60.2426, 62.8708] +24-11-19 20:33:03 | D | best error = [ 1.4432, 1.4432, 1.4432, 1.4432, 1.4432] +24-11-19 20:33:03 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:03 | D | sum error = [ 65.5973, 68.3817, 71.2627, 74.2333, 77.2800] +24-11-19 20:33:03 | D | best error = [ 1.4432, 1.4432, 1.4432, 1.4432, 1.4432] +24-11-19 20:33:03 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:03 | D | sum error = [ 80.4272, 83.6597, 86.9899, 90.4011, 93.9033] +24-11-19 20:33:03 | D | best error = [ 1.4432, 1.4432, 1.4432, 1.4432, 1.4432] +24-11-19 20:33:03 | D | + error = [1.4432] +24-11-19 20:33:03 | D | - Calibrating model.layers.17.self_attn.o_proj.weight +24-11-19 20:33:03 | D | + w: sint8 +24-11-19 20:33:03 | D | + x: None +24-11-19 20:33:03 | D | + y: None +24-11-19 20:33:03 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:03 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:33:03 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:33:03 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:33:03 | D | - range ratio = [ 1.0000] +24-11-19 20:33:03 | D | sum error = [ 0.6015] +24-11-19 20:33:03 | D | best error = [ 0.6015] +24-11-19 20:33:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:04 | D | sum error = [ 0.5980, 0.5916, 0.5862, 0.5857, 0.5806] +24-11-19 20:33:04 | D | best error = [ 0.5533, 0.5312, 0.5165, 0.5056, 0.4978] +24-11-19 20:33:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:04 | D | sum error = [ 0.5811, 0.5844, 0.5822, 0.5896, 0.5960] +24-11-19 20:33:04 | D | best error = [ 0.4915, 0.4865, 0.4824, 0.4789, 0.4762] +24-11-19 20:33:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:04 | D | sum error = [ 0.6033, 0.6143, 0.6273, 0.6405, 0.6582] +24-11-19 20:33:04 | D | best error = [ 0.4740, 0.4723, 0.4710, 0.4698, 0.4687] +24-11-19 20:33:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:04 | D | sum error = [ 0.6765, 0.6999, 0.7225, 0.7510, 0.7822] +24-11-19 20:33:04 | D | best error = [ 0.4677, 0.4669, 0.4663, 0.4658, 0.4654] +24-11-19 20:33:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:04 | D | sum error = [ 0.8122, 0.8503, 0.8869, 0.9303, 0.9775] +24-11-19 20:33:04 | D | best error = [ 0.4651, 0.4648, 0.4645, 0.4643, 0.4641] +24-11-19 20:33:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:04 | D | sum error = [ 1.0247, 1.0743, 1.1328, 1.1914, 1.2510] +24-11-19 20:33:04 | D | best error = [ 0.4640, 0.4638, 0.4637, 0.4636, 0.4635] +24-11-19 20:33:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:04 | D | sum error = [ 1.3212, 1.3886, 1.4616, 1.5411, 1.6243] +24-11-19 20:33:04 | D | best error = [ 0.4635, 0.4635, 0.4634, 0.4634, 0.4634] +24-11-19 20:33:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:04 | D | sum error = [ 1.7122, 1.8070, 1.9072, 2.0102, 2.1212] +24-11-19 20:33:04 | D | best error = [ 0.4634, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:33:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:04 | D | sum error = [ 2.2380, 2.3621, 2.4937, 2.6331, 2.7805] +24-11-19 20:33:04 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:33:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:04 | D | sum error = [ 2.9380, 3.1036, 3.2777, 3.4624, 3.6597] +24-11-19 20:33:04 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:33:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:04 | D | sum error = [ 3.8684, 4.0877, 4.3216, 4.5685, 4.8313] +24-11-19 20:33:04 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:33:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:04 | D | sum error = [ 5.1073, 5.4031, 5.7119, 6.0386, 6.3839] +24-11-19 20:33:04 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:33:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:04 | D | sum error = [ 6.7481, 7.1343, 7.5412, 7.9700, 8.4225] +24-11-19 20:33:04 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:33:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:04 | D | sum error = [ 8.8972, 9.3976, 9.9227, 10.4793, 11.0618] +24-11-19 20:33:04 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:33:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:04 | D | sum error = [ 11.6756, 12.3181, 12.9948, 13.7042, 14.4470] +24-11-19 20:33:04 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:33:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:04 | D | sum error = [ 15.2260, 16.0398, 16.8890, 17.7774, 18.7060] +24-11-19 20:33:04 | D | best error = [ 0.4633, 0.4633, 0.4633, 0.4633, 0.4633] +24-11-19 20:33:04 | D | + error = [0.4633] +24-11-19 20:33:04 | D | - Calibrating model.layers.17.mlp.up_proj.weight +24-11-19 20:33:04 | D | + w: sint8 +24-11-19 20:33:04 | D | + x: None +24-11-19 20:33:04 | D | + y: None +24-11-19 20:33:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:04 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:33:04 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:33:04 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:33:04 | D | - range ratio = [ 1.0000] +24-11-19 20:33:04 | D | sum error = [ 6.0977] +24-11-19 20:33:04 | D | best error = [ 6.0977] +24-11-19 20:33:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:05 | D | sum error = [ 6.0667, 6.0417, 6.0689, 6.1282, 6.2541] +24-11-19 20:33:05 | D | best error = [ 5.6620, 5.4881, 5.3961, 5.3444, 5.3191] +24-11-19 20:33:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:05 | D | sum error = [ 6.3969, 6.6280, 6.8991, 7.2202, 7.5990] +24-11-19 20:33:05 | D | best error = [ 5.3064, 5.3007, 5.2986, 5.2980, 5.2977] +24-11-19 20:33:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:05 | D | sum error = [ 8.0352, 8.5258, 9.0863, 9.7059, 10.3661] +24-11-19 20:33:05 | D | best error = [ 5.2977, 5.2977, 5.2977, 5.2977, 5.2977] +24-11-19 20:33:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:05 | D | sum error = [ 11.0904, 11.8835, 12.7067, 13.6189, 14.5913] +24-11-19 20:33:05 | D | best error = [ 5.2977, 5.2977, 5.2977, 5.2977, 5.2977] +24-11-19 20:33:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:05 | D | sum error = [ 15.6320, 16.7419, 17.9372, 19.1723, 20.5082] +24-11-19 20:33:05 | D | best error = [ 5.2977, 5.2977, 5.2977, 5.2977, 5.2977] +24-11-19 20:33:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:05 | D | sum error = [ 21.9067, 23.3930, 24.9702, 26.6361, 28.3782] +24-11-19 20:33:05 | D | best error = [ 5.2977, 5.2977, 5.2977, 5.2977, 5.2977] +24-11-19 20:33:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:05 | D | sum error = [ 30.2428, 32.2075, 34.2561, 36.4167, 38.7193] +24-11-19 20:33:05 | D | best error = [ 5.2977, 5.2977, 5.2977, 5.2977, 5.2977] +24-11-19 20:33:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:05 | D | sum error = [ 41.1257, 43.6418, 46.3231, 49.1313, 52.0685] +24-11-19 20:33:05 | D | best error = [ 5.2977, 5.2977, 5.2977, 5.2977, 5.2977] +24-11-19 20:33:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:05 | D | sum error = [ 55.1759, 58.4010, 61.8026, 65.3776, 69.1106] +24-11-19 20:33:05 | D | best error = [ 5.2977, 5.2977, 5.2977, 5.2977, 5.2977] +24-11-19 20:33:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:05 | D | sum error = [ 73.0132, 77.0928, 81.3644, 85.8297, 90.4991] +24-11-19 20:33:05 | D | best error = [ 5.2977, 5.2977, 5.2977, 5.2977, 5.2977] +24-11-19 20:33:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:05 | D | sum error = [ 95.3876, 100.4850, 105.8085, 111.3572, 117.1536] +24-11-19 20:33:05 | D | best error = [ 5.2977, 5.2977, 5.2977, 5.2977, 5.2977] +24-11-19 20:33:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:05 | D | sum error = [ 123.1838, 129.4659, 136.0118, 142.8229, 149.8902] +24-11-19 20:33:05 | D | best error = [ 5.2977, 5.2977, 5.2977, 5.2977, 5.2977] +24-11-19 20:33:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:05 | D | sum error = [ 157.2307, 164.8670, 172.7783, 180.9878, 189.5037] +24-11-19 20:33:05 | D | best error = [ 5.2977, 5.2977, 5.2977, 5.2977, 5.2977] +24-11-19 20:33:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:05 | D | sum error = [ 198.3238, 207.4467, 216.8894, 226.6488, 236.7520] +24-11-19 20:33:05 | D | best error = [ 5.2977, 5.2977, 5.2977, 5.2977, 5.2977] +24-11-19 20:33:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:05 | D | sum error = [ 247.1865, 257.9713, 269.0982, 280.5811, 292.4153] +24-11-19 20:33:05 | D | best error = [ 5.2977, 5.2977, 5.2977, 5.2977, 5.2977] +24-11-19 20:33:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:05 | D | sum error = [ 304.6249, 317.1981, 330.1535, 343.4731, 357.1629] +24-11-19 20:33:05 | D | best error = [ 5.2977, 5.2977, 5.2977, 5.2977, 5.2977] +24-11-19 20:33:05 | D | + error = [5.2977] +24-11-19 20:33:05 | D | - Calibrating model.layers.17.mlp.gate_proj.weight +24-11-19 20:33:05 | D | + w: sint8 +24-11-19 20:33:05 | D | + x: None +24-11-19 20:33:05 | D | + y: None +24-11-19 20:33:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:05 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:33:05 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:33:06 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:33:06 | D | - range ratio = [ 1.0000] +24-11-19 20:33:06 | D | sum error = [ 8.1033] +24-11-19 20:33:06 | D | best error = [ 8.1033] +24-11-19 20:33:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:07 | D | sum error = [ 8.0414, 8.0431, 8.0742, 8.1554, 8.3145] +24-11-19 20:33:07 | D | best error = [ 7.5235, 7.3034, 7.1847, 7.1155, 7.0805] +24-11-19 20:33:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:07 | D | sum error = [ 8.5181, 8.8325, 9.1864, 9.6503, 10.1428] +24-11-19 20:33:07 | D | best error = [ 7.0624, 7.0546, 7.0515, 7.0506, 7.0502] +24-11-19 20:33:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:07 | D | sum error = [ 10.7633, 11.4115, 12.1670, 13.0055, 13.9314] +24-11-19 20:33:07 | D | best error = [ 7.0502, 7.0502, 7.0502, 7.0502, 7.0502] +24-11-19 20:33:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:07 | D | sum error = [ 14.9109, 16.0054, 17.2015, 18.4812, 19.8115] +24-11-19 20:33:07 | D | best error = [ 7.0502, 7.0502, 7.0502, 7.0502, 7.0502] +24-11-19 20:33:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:07 | D | sum error = [ 21.2880, 22.8193, 24.4994, 26.2937, 28.1679] +24-11-19 20:33:07 | D | best error = [ 7.0502, 7.0502, 7.0502, 7.0502, 7.0502] +24-11-19 20:33:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:07 | D | sum error = [ 30.2014, 32.3555, 34.6346, 37.0821, 39.6802] +24-11-19 20:33:07 | D | best error = [ 7.0502, 7.0502, 7.0502, 7.0502, 7.0502] +24-11-19 20:33:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:07 | D | sum error = [ 42.4144, 45.3533, 48.4816, 51.7915, 55.2984] +24-11-19 20:33:07 | D | best error = [ 7.0502, 7.0502, 7.0502, 7.0502, 7.0502] +24-11-19 20:33:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:07 | D | sum error = [ 59.0569, 62.9992, 67.2528, 71.7089, 76.4474] +24-11-19 20:33:07 | D | best error = [ 7.0502, 7.0502, 7.0502, 7.0502, 7.0502] +24-11-19 20:33:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:07 | D | sum error = [ 81.4751, 86.8457, 92.5186, 98.5235, 104.8836] +24-11-19 20:33:07 | D | best error = [ 7.0502, 7.0502, 7.0502, 7.0502, 7.0502] +24-11-19 20:33:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:07 | D | sum error = [ 111.6588, 118.8268, 126.3908, 134.4069, 142.8910] +24-11-19 20:33:07 | D | best error = [ 7.0502, 7.0502, 7.0502, 7.0502, 7.0502] +24-11-19 20:33:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:07 | D | sum error = [ 151.8775, 161.3708, 171.4005, 181.9981, 193.1685] +24-11-19 20:33:07 | D | best error = [ 7.0502, 7.0502, 7.0502, 7.0502, 7.0502] +24-11-19 20:33:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:07 | D | sum error = [ 204.9814, 217.4546, 230.5704, 244.3776, 258.8791] +24-11-19 20:33:07 | D | best error = [ 7.0502, 7.0502, 7.0502, 7.0502, 7.0502] +24-11-19 20:33:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:07 | D | sum error = [ 274.1377, 290.1688, 306.9594, 324.5927, 343.0616] +24-11-19 20:33:07 | D | best error = [ 7.0502, 7.0502, 7.0502, 7.0502, 7.0502] +24-11-19 20:33:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:07 | D | sum error = [ 362.3366, 382.5153, 403.5862, 425.5652, 448.4634] +24-11-19 20:33:07 | D | best error = [ 7.0502, 7.0502, 7.0502, 7.0502, 7.0502] +24-11-19 20:33:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:07 | D | sum error = [ 472.3350, 497.1543, 522.9655, 549.7290, 577.4921] +24-11-19 20:33:07 | D | best error = [ 7.0502, 7.0502, 7.0502, 7.0502, 7.0502] +24-11-19 20:33:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:07 | D | sum error = [ 606.2658, 636.0330, 666.7863, 698.5312, 731.2573] +24-11-19 20:33:07 | D | best error = [ 7.0502, 7.0502, 7.0502, 7.0502, 7.0502] +24-11-19 20:33:07 | D | + error = [7.0502] +24-11-19 20:33:07 | D | - Calibrating model.layers.17.mlp.down_proj.weight +24-11-19 20:33:07 | D | + w: sint8 +24-11-19 20:33:07 | D | + x: None +24-11-19 20:33:07 | D | + y: None +24-11-19 20:33:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:07 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:33:07 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:33:07 | D | + finished calculating the original outputs, ram usage: 13.4 +24-11-19 20:33:07 | D | - range ratio = [ 1.0000] +24-11-19 20:33:07 | D | sum error = [ 0.9949] +24-11-19 20:33:07 | D | best error = [ 0.9949] +24-11-19 20:33:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:08 | D | sum error = [ 0.9833, 0.9783, 0.9724, 0.9662, 0.9667] +24-11-19 20:33:08 | D | best error = [ 0.9523, 0.9319, 0.9183, 0.9080, 0.9002] +24-11-19 20:33:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:08 | D | sum error = [ 0.9665, 0.9706, 0.9799, 0.9883, 1.0060] +24-11-19 20:33:08 | D | best error = [ 0.8938, 0.8891, 0.8852, 0.8820, 0.8800] +24-11-19 20:33:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:08 | D | sum error = [ 1.0266, 1.0534, 1.0836, 1.1229, 1.1695] +24-11-19 20:33:08 | D | best error = [ 0.8784, 0.8773, 0.8766, 0.8760, 0.8756] +24-11-19 20:33:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:08 | D | sum error = [ 1.2186, 1.2781, 1.3444, 1.4174, 1.4990] +24-11-19 20:33:08 | D | best error = [ 0.8754, 0.8753, 0.8751, 0.8751, 0.8750] +24-11-19 20:33:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:08 | D | sum error = [ 1.5920, 1.6893, 1.8003, 1.9181, 2.0456] +24-11-19 20:33:08 | D | best error = [ 0.8750, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 20:33:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:08 | D | sum error = [ 2.1852, 2.3335, 2.4937, 2.6648, 2.8494] +24-11-19 20:33:08 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 20:33:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:08 | D | sum error = [ 3.0460, 3.2541, 3.4794, 3.7215, 3.9740] +24-11-19 20:33:08 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 20:33:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:08 | D | sum error = [ 4.2438, 4.5292, 4.8359, 5.1591, 5.5010] +24-11-19 20:33:08 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 20:33:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:08 | D | sum error = [ 5.8645, 6.2495, 6.6563, 7.0844, 7.5389] +24-11-19 20:33:08 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 20:33:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:08 | D | sum error = [ 8.0189, 8.5256, 9.0592, 9.6210, 10.2108] +24-11-19 20:33:08 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 20:33:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:08 | D | sum error = [ 10.8317, 11.4869, 12.1776, 12.8985, 13.6591] +24-11-19 20:33:08 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 20:33:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:08 | D | sum error = [ 14.4566, 15.2923, 16.1693, 17.0850, 18.0448] +24-11-19 20:33:08 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 20:33:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:08 | D | sum error = [ 19.0477, 20.0966, 21.1903, 22.3327, 23.5270] +24-11-19 20:33:08 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 20:33:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:08 | D | sum error = [ 24.7684, 26.0607, 27.4097, 28.8117, 30.2664] +24-11-19 20:33:08 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 20:33:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:08 | D | sum error = [ 31.7812, 33.3535, 34.9837, 36.6763, 38.4294] +24-11-19 20:33:08 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 20:33:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:08 | D | sum error = [ 40.2432, 42.1212, 44.0603, 46.0653, 48.1351] +24-11-19 20:33:08 | D | best error = [ 0.8749, 0.8749, 0.8749, 0.8749, 0.8749] +24-11-19 20:33:08 | D | + error = [0.8749] +24-11-19 20:33:08 | D | - Quantizing model.layers.17.self_attn.q_proj.weight +24-11-19 20:33:09 | D | - Quantizing model.layers.17.self_attn.k_proj.weight +24-11-19 20:33:10 | D | - Quantizing model.layers.17.self_attn.v_proj.weight +24-11-19 20:33:11 | D | - Quantizing model.layers.17.self_attn.o_proj.weight +24-11-19 20:33:12 | D | - Quantizing model.layers.17.mlp.up_proj.weight +24-11-19 20:33:13 | D | - Quantizing model.layers.17.mlp.gate_proj.weight +24-11-19 20:33:14 | D | - Quantizing model.layers.17.mlp.down_proj.weight +24-11-19 20:33:24 | D | - Quantizing layer model.layers.18 +24-11-19 20:33:24 | D | - Calibrating model.layers.18.self_attn.q_proj.weight +24-11-19 20:33:24 | D | + w: sint8 +24-11-19 20:33:24 | D | + x: None +24-11-19 20:33:24 | D | + y: None +24-11-19 20:33:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:33:24 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:33:24 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:33:24 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:33:24 | D | - range ratio = [ 1.0000] +24-11-19 20:33:24 | D | sum error = [ 3.8922] +24-11-19 20:33:24 | D | best error = [ 3.8922] +24-11-19 20:33:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:37 | D | sum error = [ 3.9381, 3.8646, 3.8690, 4.0927, 4.0528] +24-11-19 20:33:37 | D | best error = [ 3.8922, 3.8646, 3.8646, 3.8646, 3.8646] +24-11-19 20:33:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:37 | D | sum error = [ 4.1688, 4.3521, 4.6128, 4.8092, 5.0866] +24-11-19 20:33:37 | D | best error = [ 3.8646, 3.8646, 3.8646, 3.8646, 3.8646] +24-11-19 20:33:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:37 | D | sum error = [ 5.3654, 5.7699, 6.2226, 6.6683, 7.2225] +24-11-19 20:33:37 | D | best error = [ 3.8646, 3.8646, 3.8646, 3.8646, 3.8646] +24-11-19 20:33:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:37 | D | sum error = [ 7.7718, 8.3604, 9.1484, 9.9513, 10.7358] +24-11-19 20:33:37 | D | best error = [ 3.8646, 3.8646, 3.8646, 3.8646, 3.8646] +24-11-19 20:33:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:37 | D | sum error = [ 11.6586, 12.5295, 13.7803, 14.8615, 16.1218] +24-11-19 20:33:37 | D | best error = [ 3.8646, 3.8646, 3.8646, 3.8646, 3.8646] +24-11-19 20:33:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:37 | D | sum error = [ 17.6162, 19.0746, 20.7099, 22.5832, 24.5233] +24-11-19 20:33:37 | D | best error = [ 3.8646, 3.8646, 3.8646, 3.8646, 3.8646] +24-11-19 20:33:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:37 | D | sum error = [ 26.6364, 28.7987, 31.3693, 34.1058, 37.2691] +24-11-19 20:33:37 | D | best error = [ 3.8646, 3.8646, 3.8646, 3.8646, 3.8646] +24-11-19 20:33:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:37 | D | sum error = [ 40.3267, 43.8316, 47.3594, 51.1296, 55.4868] +24-11-19 20:33:37 | D | best error = [ 3.8646, 3.8646, 3.8646, 3.8646, 3.8646] +24-11-19 20:33:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:37 | D | sum error = [ 60.0494, 64.9029, 70.3522, 75.7829, 82.2778] +24-11-19 20:33:37 | D | best error = [ 3.8646, 3.8646, 3.8646, 3.8646, 3.8646] +24-11-19 20:33:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:37 | D | sum error = [ 88.6536, 95.7844, 103.2118, 111.3371, 119.9265] +24-11-19 20:33:37 | D | best error = [ 3.8646, 3.8646, 3.8646, 3.8646, 3.8646] +24-11-19 20:33:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:37 | D | sum error = [ 129.2478, 139.3149, 150.1836, 161.9868, 174.4756] +24-11-19 20:33:37 | D | best error = [ 3.8646, 3.8646, 3.8646, 3.8646, 3.8646] +24-11-19 20:33:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:37 | D | sum error = [ 187.9747, 202.8374, 219.0146, 236.3187, 255.2358] +24-11-19 20:33:37 | D | best error = [ 3.8646, 3.8646, 3.8646, 3.8646, 3.8646] +24-11-19 20:33:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:37 | D | sum error = [ 275.8780, 298.5257, 322.8924, 349.7411, 379.5441] +24-11-19 20:33:37 | D | best error = [ 3.8646, 3.8646, 3.8646, 3.8646, 3.8646] +24-11-19 20:33:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:37 | D | sum error = [ 411.1312, 446.5101, 485.2325, 527.5396, 574.1741] +24-11-19 20:33:37 | D | best error = [ 3.8646, 3.8646, 3.8646, 3.8646, 3.8646] +24-11-19 20:33:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:37 | D | sum error = [ 625.2736, 680.6426, 740.9842, 806.3411, 877.0952] +24-11-19 20:33:37 | D | best error = [ 3.8646, 3.8646, 3.8646, 3.8646, 3.8646] +24-11-19 20:33:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:37 | D | sum error = [ 952.6794, 1032.7037, 1117.4838, 1204.8990, 1294.6423] +24-11-19 20:33:37 | D | best error = [ 3.8646, 3.8646, 3.8646, 3.8646, 3.8646] +24-11-19 20:33:37 | D | + error = [3.8646] +24-11-19 20:33:37 | D | - Calibrating model.layers.18.self_attn.k_proj.weight +24-11-19 20:33:37 | D | + w: sint8 +24-11-19 20:33:37 | D | + x: None +24-11-19 20:33:37 | D | + y: None +24-11-19 20:33:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:33:37 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:33:37 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:33:37 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:33:37 | D | - range ratio = [ 1.0000] +24-11-19 20:33:37 | D | sum error = [ 4.0701] +24-11-19 20:33:37 | D | best error = [ 4.0701] +24-11-19 20:33:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:50 | D | sum error = [ 3.5935, 3.7961, 3.4841, 3.4829, 3.5167] +24-11-19 20:33:50 | D | best error = [ 3.5935, 3.5935, 3.4841, 3.4829, 3.4829] +24-11-19 20:33:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:50 | D | sum error = [ 4.4187, 4.1500, 3.8971, 4.1725, 4.4250] +24-11-19 20:33:50 | D | best error = [ 3.4829, 3.4829, 3.4829, 3.4829, 3.4829] +24-11-19 20:33:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:50 | D | sum error = [ 5.2103, 5.1550, 5.3334, 5.9621, 5.8043] +24-11-19 20:33:50 | D | best error = [ 3.4829, 3.4829, 3.4829, 3.4829, 3.4829] +24-11-19 20:33:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:50 | D | sum error = [ 6.3795, 7.1190, 7.6053, 8.0041, 9.3467] +24-11-19 20:33:50 | D | best error = [ 3.4829, 3.4829, 3.4829, 3.4829, 3.4829] +24-11-19 20:33:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:50 | D | sum error = [ 9.9030, 10.4670, 11.2432, 11.6829, 12.7008] +24-11-19 20:33:50 | D | best error = [ 3.4829, 3.4829, 3.4829, 3.4829, 3.4829] +24-11-19 20:33:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:50 | D | sum error = [ 13.8916, 14.9794, 15.9211, 17.1983, 18.3628] +24-11-19 20:33:50 | D | best error = [ 3.4829, 3.4829, 3.4829, 3.4829, 3.4829] +24-11-19 20:33:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:50 | D | sum error = [ 20.0233, 21.1812, 22.8872, 25.5884, 27.6467] +24-11-19 20:33:50 | D | best error = [ 3.4829, 3.4829, 3.4829, 3.4829, 3.4829] +24-11-19 20:33:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:50 | D | sum error = [ 29.5645, 31.8996, 34.3873, 37.1874, 40.6417] +24-11-19 20:33:50 | D | best error = [ 3.4829, 3.4829, 3.4829, 3.4829, 3.4829] +24-11-19 20:33:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:50 | D | sum error = [ 43.7167, 46.6073, 50.4784, 54.0320, 58.0597] +24-11-19 20:33:50 | D | best error = [ 3.4829, 3.4829, 3.4829, 3.4829, 3.4829] +24-11-19 20:33:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:50 | D | sum error = [ 62.4949, 67.2238, 71.5866, 77.7157, 83.9802] +24-11-19 20:33:50 | D | best error = [ 3.4829, 3.4829, 3.4829, 3.4829, 3.4829] +24-11-19 20:33:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:50 | D | sum error = [ 90.1716, 97.3891, 104.7038, 113.4140, 122.3696] +24-11-19 20:33:50 | D | best error = [ 3.4829, 3.4829, 3.4829, 3.4829, 3.4829] +24-11-19 20:33:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:50 | D | sum error = [ 132.7885, 143.0519, 155.9294, 168.7376, 182.7545] +24-11-19 20:33:50 | D | best error = [ 3.4829, 3.4829, 3.4829, 3.4829, 3.4829] +24-11-19 20:33:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:50 | D | sum error = [ 198.4276, 216.0725, 235.3305, 256.4433, 280.0215] +24-11-19 20:33:50 | D | best error = [ 3.4829, 3.4829, 3.4829, 3.4829, 3.4829] +24-11-19 20:33:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:50 | D | sum error = [ 305.4870, 334.2301, 367.1503, 402.9667, 442.9036] +24-11-19 20:33:50 | D | best error = [ 3.4829, 3.4829, 3.4829, 3.4829, 3.4829] +24-11-19 20:33:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:50 | D | sum error = [ 488.0672, 536.3136, 590.0637, 649.8424, 714.7773] +24-11-19 20:33:50 | D | best error = [ 3.4829, 3.4829, 3.4829, 3.4829, 3.4829] +24-11-19 20:33:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:50 | D | sum error = [ 787.5376, 864.0174, 948.8610, 1039.2044, 1136.0713] +24-11-19 20:33:50 | D | best error = [ 3.4829, 3.4829, 3.4829, 3.4829, 3.4829] +24-11-19 20:33:50 | D | + error = [3.4829] +24-11-19 20:33:50 | D | - Calibrating model.layers.18.self_attn.v_proj.weight +24-11-19 20:33:50 | D | + w: sint8 +24-11-19 20:33:50 | D | + x: None +24-11-19 20:33:50 | D | + y: None +24-11-19 20:33:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:50 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:33:51 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:33:51 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:33:51 | D | - range ratio = [ 1.0000] +24-11-19 20:33:51 | D | sum error = [ 1.5762] +24-11-19 20:33:51 | D | best error = [ 1.5762] +24-11-19 20:33:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:51 | D | sum error = [ 1.5522, 1.5675, 1.5643, 1.5786, 1.6104] +24-11-19 20:33:51 | D | best error = [ 1.4571, 1.4122, 1.3883, 1.3754, 1.3670] +24-11-19 20:33:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:51 | D | sum error = [ 1.6403, 1.7143, 1.7711, 1.8551, 1.9490] +24-11-19 20:33:51 | D | best error = [ 1.3634, 1.3621, 1.3618, 1.3615, 1.3615] +24-11-19 20:33:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:51 | D | sum error = [ 2.0695, 2.1986, 2.3498, 2.5075, 2.6848] +24-11-19 20:33:51 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:51 | D | sum error = [ 2.8742, 3.0855, 3.2999, 3.5296, 3.7866] +24-11-19 20:33:51 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:51 | D | sum error = [ 4.0744, 4.3587, 4.6778, 4.9983, 5.3414] +24-11-19 20:33:51 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:51 | D | sum error = [ 5.7190, 6.1081, 6.5257, 6.9652, 7.4332] +24-11-19 20:33:51 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:51 | D | sum error = [ 7.9336, 8.4678, 8.9967, 9.5803, 10.1705] +24-11-19 20:33:51 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:51 | D | sum error = [ 10.8141, 11.4666, 12.1675, 12.9107, 13.6724] +24-11-19 20:33:51 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:51 | D | sum error = [ 14.4917, 15.3347, 16.2347, 17.1733, 18.1451] +24-11-19 20:33:51 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:51 | D | sum error = [ 19.1744, 20.2641, 21.3818, 22.5694, 23.8087] +24-11-19 20:33:51 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:51 | D | sum error = [ 25.0939, 26.4394, 27.8540, 29.3363, 30.8827] +24-11-19 20:33:51 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:51 | D | sum error = [ 32.4828, 34.1577, 35.8990, 37.7084, 39.5935] +24-11-19 20:33:51 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:51 | D | sum error = [ 41.5583, 43.5937, 45.7140, 47.9125, 50.1973] +24-11-19 20:33:51 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:51 | D | sum error = [ 52.5765, 55.0440, 57.6057, 60.2512, 63.0132] +24-11-19 20:33:51 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:51 | D | sum error = [ 65.8646, 68.8150, 71.8671, 75.0196, 78.2802] +24-11-19 20:33:51 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:51 | D | sum error = [ 81.6542, 85.1194, 88.6896, 92.3602, 96.1332] +24-11-19 20:33:51 | D | best error = [ 1.3615, 1.3615, 1.3615, 1.3615, 1.3615] +24-11-19 20:33:51 | D | + error = [1.3615] +24-11-19 20:33:51 | D | - Calibrating model.layers.18.self_attn.o_proj.weight +24-11-19 20:33:51 | D | + w: sint8 +24-11-19 20:33:51 | D | + x: None +24-11-19 20:33:51 | D | + y: None +24-11-19 20:33:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:51 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:33:51 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:33:52 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:33:52 | D | - range ratio = [ 1.0000] +24-11-19 20:33:52 | D | sum error = [ 0.4923] +24-11-19 20:33:52 | D | best error = [ 0.4923] +24-11-19 20:33:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:52 | D | sum error = [ 0.4870, 0.4854, 0.4819, 0.4841, 0.4836] +24-11-19 20:33:52 | D | best error = [ 0.4556, 0.4386, 0.4283, 0.4213, 0.4159] +24-11-19 20:33:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:52 | D | sum error = [ 0.4870, 0.4951, 0.5034, 0.5113, 0.5268] +24-11-19 20:33:52 | D | best error = [ 0.4119, 0.4089, 0.4067, 0.4051, 0.4042] +24-11-19 20:33:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:52 | D | sum error = [ 0.5403, 0.5584, 0.5781, 0.5977, 0.6243] +24-11-19 20:33:52 | D | best error = [ 0.4034, 0.4029, 0.4025, 0.4023, 0.4021] +24-11-19 20:33:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:52 | D | sum error = [ 0.6485, 0.6800, 0.7124, 0.7449, 0.7832] +24-11-19 20:33:52 | D | best error = [ 0.4020, 0.4020, 0.4020, 0.4019, 0.4019] +24-11-19 20:33:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:52 | D | sum error = [ 0.8233, 0.8659, 0.9090, 0.9589, 1.0085] +24-11-19 20:33:52 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:33:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:52 | D | sum error = [ 1.0615, 1.1192, 1.1802, 1.2436, 1.3122] +24-11-19 20:33:52 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:33:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:52 | D | sum error = [ 1.3826, 1.4565, 1.5383, 1.6196, 1.7084] +24-11-19 20:33:52 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:33:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:52 | D | sum error = [ 1.7988, 1.8985, 2.0012, 2.1089, 2.2236] +24-11-19 20:33:52 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:33:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:52 | D | sum error = [ 2.3416, 2.4688, 2.6024, 2.7454, 2.8933] +24-11-19 20:33:52 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:33:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:52 | D | sum error = [ 3.0511, 3.2168, 3.3935, 3.5782, 3.7741] +24-11-19 20:33:52 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:33:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:52 | D | sum error = [ 3.9793, 4.1977, 4.4250, 4.6667, 4.9203] +24-11-19 20:33:52 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:33:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:52 | D | sum error = [ 5.1902, 5.4737, 5.7725, 6.0871, 6.4188] +24-11-19 20:33:52 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:33:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:52 | D | sum error = [ 6.7682, 7.1371, 7.5226, 7.9299, 8.3571] +24-11-19 20:33:52 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:33:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:52 | D | sum error = [ 8.8054, 9.2747, 9.7678, 10.2859, 10.8284] +24-11-19 20:33:52 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:33:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:52 | D | sum error = [ 11.3967, 11.9902, 12.6101, 13.2573, 13.9339] +24-11-19 20:33:52 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:33:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:52 | D | sum error = [ 14.6404, 15.3777, 16.1464, 16.9485, 17.7823] +24-11-19 20:33:52 | D | best error = [ 0.4019, 0.4019, 0.4019, 0.4019, 0.4019] +24-11-19 20:33:52 | D | + error = [0.4019] +24-11-19 20:33:52 | D | - Calibrating model.layers.18.mlp.up_proj.weight +24-11-19 20:33:52 | D | + w: sint8 +24-11-19 20:33:52 | D | + x: None +24-11-19 20:33:52 | D | + y: None +24-11-19 20:33:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:52 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:33:52 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:33:53 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:33:53 | D | - range ratio = [ 1.0000] +24-11-19 20:33:53 | D | sum error = [ 6.3109] +24-11-19 20:33:53 | D | best error = [ 6.3109] +24-11-19 20:33:54 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:54 | D | sum error = [ 6.2589, 6.2429, 6.2805, 6.3586, 6.4696] +24-11-19 20:33:54 | D | best error = [ 5.8604, 5.6850, 5.5972, 5.5462, 5.5186] +24-11-19 20:33:54 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:54 | D | sum error = [ 6.6287, 6.8763, 7.1339, 7.4650, 7.8847] +24-11-19 20:33:54 | D | best error = [ 5.5040, 5.4982, 5.4959, 5.4952, 5.4950] +24-11-19 20:33:54 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:54 | D | sum error = [ 8.3328, 8.8272, 9.3984, 10.0472, 10.7478] +24-11-19 20:33:54 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 20:33:54 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:54 | D | sum error = [ 11.4969, 12.3175, 13.1836, 14.1329, 15.1610] +24-11-19 20:33:54 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 20:33:54 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:54 | D | sum error = [ 16.2364, 17.3902, 18.6230, 19.9076, 21.2779] +24-11-19 20:33:54 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 20:33:54 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:54 | D | sum error = [ 22.7558, 24.2898, 25.9268, 27.6547, 29.4780] +24-11-19 20:33:54 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 20:33:54 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:54 | D | sum error = [ 31.3952, 33.4326, 35.5667, 37.8131, 40.1955] +24-11-19 20:33:54 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 20:33:54 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:54 | D | sum error = [ 42.6688, 45.2981, 48.0399, 50.9335, 53.9676] +24-11-19 20:33:54 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 20:33:54 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:54 | D | sum error = [ 57.1426, 60.4674, 63.9746, 67.6201, 71.4618] +24-11-19 20:33:54 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 20:33:54 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:54 | D | sum error = [ 75.4640, 79.6724, 84.0538, 88.6385, 93.4310] +24-11-19 20:33:54 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 20:33:54 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:54 | D | sum error = [ 98.4248, 103.6248, 109.0511, 114.7149, 120.5894] +24-11-19 20:33:54 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 20:33:54 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:54 | D | sum error = [ 126.7224, 133.0858, 139.7151, 146.6143, 153.7648] +24-11-19 20:33:54 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 20:33:54 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:54 | D | sum error = [ 161.2026, 168.9026, 176.8866, 185.1662, 193.7466] +24-11-19 20:33:54 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 20:33:54 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:54 | D | sum error = [ 202.6157, 211.7997, 221.3011, 231.1179, 241.2699] +24-11-19 20:33:54 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 20:33:54 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:54 | D | sum error = [ 251.7296, 262.5324, 273.6709, 285.1497, 296.9624] +24-11-19 20:33:54 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 20:33:54 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:54 | D | sum error = [ 309.1611, 321.6980, 334.6039, 347.8706, 361.5166] +24-11-19 20:33:54 | D | best error = [ 5.4950, 5.4950, 5.4950, 5.4950, 5.4950] +24-11-19 20:33:54 | D | + error = [5.4950] +24-11-19 20:33:54 | D | - Calibrating model.layers.18.mlp.gate_proj.weight +24-11-19 20:33:54 | D | + w: sint8 +24-11-19 20:33:54 | D | + x: None +24-11-19 20:33:54 | D | + y: None +24-11-19 20:33:54 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:54 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:33:54 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:33:54 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:33:54 | D | - range ratio = [ 1.0000] +24-11-19 20:33:54 | D | sum error = [ 8.4717] +24-11-19 20:33:54 | D | best error = [ 8.4717] +24-11-19 20:33:55 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:55 | D | sum error = [ 8.4293, 8.3631, 8.3986, 8.5095, 8.6753] +24-11-19 20:33:55 | D | best error = [ 7.8768, 7.6393, 7.5129, 7.4427, 7.4047] +24-11-19 20:33:55 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:55 | D | sum error = [ 8.8913, 9.2042, 9.5661, 10.0267, 10.5291] +24-11-19 20:33:55 | D | best error = [ 7.3858, 7.3777, 7.3746, 7.3738, 7.3736] +24-11-19 20:33:55 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:55 | D | sum error = [ 11.1571, 11.8451, 12.6261, 13.4751, 14.4328] +24-11-19 20:33:55 | D | best error = [ 7.3736, 7.3736, 7.3736, 7.3736, 7.3736] +24-11-19 20:33:55 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:55 | D | sum error = [ 15.4657, 16.5580, 17.7401, 19.0476, 20.4241] +24-11-19 20:33:55 | D | best error = [ 7.3736, 7.3736, 7.3736, 7.3736, 7.3736] +24-11-19 20:33:55 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:55 | D | sum error = [ 21.9183, 23.5213, 25.2376, 27.0553, 28.9862] +24-11-19 20:33:55 | D | best error = [ 7.3736, 7.3736, 7.3736, 7.3736, 7.3736] +24-11-19 20:33:55 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:55 | D | sum error = [ 31.0405, 33.2399, 35.5840, 38.0454, 40.6926] +24-11-19 20:33:55 | D | best error = [ 7.3736, 7.3736, 7.3736, 7.3736, 7.3736] +24-11-19 20:33:55 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:55 | D | sum error = [ 43.4833, 46.4616, 49.6088, 52.9474, 56.5112] +24-11-19 20:33:55 | D | best error = [ 7.3736, 7.3736, 7.3736, 7.3736, 7.3736] +24-11-19 20:33:55 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:55 | D | sum error = [ 60.2400, 64.2201, 68.4707, 72.9324, 77.7124] +24-11-19 20:33:55 | D | best error = [ 7.3736, 7.3736, 7.3736, 7.3736, 7.3736] +24-11-19 20:33:55 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:55 | D | sum error = [ 82.7279, 88.0463, 93.6820, 99.6529, 105.9338] +24-11-19 20:33:55 | D | best error = [ 7.3736, 7.3736, 7.3736, 7.3736, 7.3736] +24-11-19 20:33:55 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:55 | D | sum error = [ 112.5565, 119.5948, 127.0273, 134.8457, 143.1171] +24-11-19 20:33:55 | D | best error = [ 7.3736, 7.3736, 7.3736, 7.3736, 7.3736] +24-11-19 20:33:55 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:55 | D | sum error = [ 151.8434, 161.0644, 170.7592, 181.0181, 191.7704] +24-11-19 20:33:55 | D | best error = [ 7.3736, 7.3736, 7.3736, 7.3736, 7.3736] +24-11-19 20:33:55 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:55 | D | sum error = [ 203.1216, 215.0915, 227.6173, 240.8269, 254.6622] +24-11-19 20:33:55 | D | best error = [ 7.3736, 7.3736, 7.3736, 7.3736, 7.3736] +24-11-19 20:33:55 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:55 | D | sum error = [ 269.2389, 284.5195, 300.5109, 317.2520, 334.7688] +24-11-19 20:33:55 | D | best error = [ 7.3736, 7.3736, 7.3736, 7.3736, 7.3736] +24-11-19 20:33:55 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:55 | D | sum error = [ 353.0764, 372.1835, 392.1419, 412.9485, 434.5922] +24-11-19 20:33:55 | D | best error = [ 7.3736, 7.3736, 7.3736, 7.3736, 7.3736] +24-11-19 20:33:55 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:55 | D | sum error = [ 457.1265, 480.5547, 504.8591, 530.0648, 556.1877] +24-11-19 20:33:55 | D | best error = [ 7.3736, 7.3736, 7.3736, 7.3736, 7.3736] +24-11-19 20:33:55 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:55 | D | sum error = [ 583.2303, 611.2140, 640.0889, 669.8835, 700.6251] +24-11-19 20:33:55 | D | best error = [ 7.3736, 7.3736, 7.3736, 7.3736, 7.3736] +24-11-19 20:33:55 | D | + error = [7.3736] +24-11-19 20:33:55 | D | - Calibrating model.layers.18.mlp.down_proj.weight +24-11-19 20:33:55 | D | + w: sint8 +24-11-19 20:33:55 | D | + x: None +24-11-19 20:33:55 | D | + y: None +24-11-19 20:33:55 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:33:55 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:33:55 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:33:56 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:33:56 | D | - range ratio = [ 1.0000] +24-11-19 20:33:56 | D | sum error = [ 0.9852] +24-11-19 20:33:56 | D | best error = [ 0.9852] +24-11-19 20:33:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:33:57 | D | sum error = [ 0.9770, 0.9693, 0.9631, 0.9602, 0.9585] +24-11-19 20:33:57 | D | best error = [ 0.9447, 0.9247, 0.9108, 0.9008, 0.8926] +24-11-19 20:33:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:33:57 | D | sum error = [ 0.9584, 0.9624, 0.9671, 0.9801, 0.9953] +24-11-19 20:33:57 | D | best error = [ 0.8861, 0.8810, 0.8769, 0.8740, 0.8719] +24-11-19 20:33:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:33:57 | D | sum error = [ 1.0134, 1.0375, 1.0677, 1.1058, 1.1472] +24-11-19 20:33:57 | D | best error = [ 0.8703, 0.8689, 0.8680, 0.8675, 0.8670] +24-11-19 20:33:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:33:57 | D | sum error = [ 1.1962, 1.2554, 1.3167, 1.3887, 1.4723] +24-11-19 20:33:57 | D | best error = [ 0.8667, 0.8666, 0.8665, 0.8663, 0.8663] +24-11-19 20:33:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:33:57 | D | sum error = [ 1.5593, 1.6580, 1.7640, 1.8811, 2.0079] +24-11-19 20:33:57 | D | best error = [ 0.8663, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 20:33:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:33:57 | D | sum error = [ 2.1449, 2.2957, 2.4526, 2.6250, 2.8092] +24-11-19 20:33:57 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 20:33:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:33:57 | D | sum error = [ 3.0041, 3.2153, 3.4365, 3.6759, 3.9290] +24-11-19 20:33:57 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 20:33:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:33:57 | D | sum error = [ 4.2012, 4.4882, 4.7926, 5.1172, 5.4616] +24-11-19 20:33:57 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 20:33:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:33:57 | D | sum error = [ 5.8253, 6.2100, 6.6179, 7.0479, 7.5032] +24-11-19 20:33:57 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 20:33:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:33:57 | D | sum error = [ 7.9834, 8.4890, 9.0217, 9.5829, 10.1732] +24-11-19 20:33:57 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 20:33:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:33:57 | D | sum error = [ 10.7944, 11.4462, 12.1305, 12.8513, 13.6066] +24-11-19 20:33:57 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 20:33:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:33:57 | D | sum error = [ 14.3994, 15.2325, 16.1042, 17.0137, 17.9713] +24-11-19 20:33:57 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 20:33:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:33:57 | D | sum error = [ 18.9687, 20.0138, 21.1052, 22.2455, 23.4333] +24-11-19 20:33:57 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 20:33:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:33:57 | D | sum error = [ 24.6713, 25.9604, 27.3030, 28.7011, 30.1531] +24-11-19 20:33:57 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 20:33:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:33:57 | D | sum error = [ 31.6618, 33.2288, 34.8545, 36.5403, 38.2864] +24-11-19 20:33:57 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 20:33:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:33:57 | D | sum error = [ 40.0928, 41.9621, 43.8955, 45.8917, 47.9519] +24-11-19 20:33:57 | D | best error = [ 0.8662, 0.8662, 0.8662, 0.8662, 0.8662] +24-11-19 20:33:57 | D | + error = [0.8662] +24-11-19 20:33:57 | D | - Quantizing model.layers.18.self_attn.q_proj.weight +24-11-19 20:33:58 | D | - Quantizing model.layers.18.self_attn.k_proj.weight +24-11-19 20:33:59 | D | - Quantizing model.layers.18.self_attn.v_proj.weight +24-11-19 20:33:59 | D | - Quantizing model.layers.18.self_attn.o_proj.weight +24-11-19 20:34:00 | D | - Quantizing model.layers.18.mlp.up_proj.weight +24-11-19 20:34:01 | D | - Quantizing model.layers.18.mlp.gate_proj.weight +24-11-19 20:34:02 | D | - Quantizing model.layers.18.mlp.down_proj.weight +24-11-19 20:34:12 | D | - Quantizing layer model.layers.19 +24-11-19 20:34:12 | D | - Calibrating model.layers.19.self_attn.q_proj.weight +24-11-19 20:34:12 | D | + w: sint8 +24-11-19 20:34:12 | D | + x: None +24-11-19 20:34:12 | D | + y: None +24-11-19 20:34:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:34:12 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:34:12 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:34:12 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:34:12 | D | - range ratio = [ 1.0000] +24-11-19 20:34:12 | D | sum error = [ 3.5064] +24-11-19 20:34:12 | D | best error = [ 3.5064] +24-11-19 20:34:24 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:24 | D | sum error = [ 3.4698, 3.4395, 3.5295, 3.5421, 3.5984] +24-11-19 20:34:24 | D | best error = [ 3.4698, 3.4395, 3.4395, 3.4395, 3.4395] +24-11-19 20:34:24 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:24 | D | sum error = [ 3.7823, 3.9218, 4.0099, 4.3046, 4.6283] +24-11-19 20:34:24 | D | best error = [ 3.4395, 3.4395, 3.4395, 3.4395, 3.4395] +24-11-19 20:34:24 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:24 | D | sum error = [ 5.0182, 5.3450, 5.7958, 6.3381, 6.8297] +24-11-19 20:34:24 | D | best error = [ 3.4395, 3.4395, 3.4395, 3.4395, 3.4395] +24-11-19 20:34:24 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:24 | D | sum error = [ 7.4690, 8.1982, 8.9800, 9.7725, 10.6315] +24-11-19 20:34:24 | D | best error = [ 3.4395, 3.4395, 3.4395, 3.4395, 3.4395] +24-11-19 20:34:24 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:24 | D | sum error = [ 11.8489, 12.8568, 14.0541, 15.4831, 16.8873] +24-11-19 20:34:24 | D | best error = [ 3.4395, 3.4395, 3.4395, 3.4395, 3.4395] +24-11-19 20:34:24 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:24 | D | sum error = [ 18.5731, 20.5296, 22.6445, 24.8194, 27.1758] +24-11-19 20:34:24 | D | best error = [ 3.4395, 3.4395, 3.4395, 3.4395, 3.4395] +24-11-19 20:34:24 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:24 | D | sum error = [ 29.8425, 32.6224, 35.8364, 38.9895, 42.8786] +24-11-19 20:34:24 | D | best error = [ 3.4395, 3.4395, 3.4395, 3.4395, 3.4395] +24-11-19 20:34:24 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:24 | D | sum error = [ 46.6156, 51.2012, 55.9149, 61.1869, 66.8480] +24-11-19 20:34:24 | D | best error = [ 3.4395, 3.4395, 3.4395, 3.4395, 3.4395] +24-11-19 20:34:24 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:24 | D | sum error = [ 72.9722, 79.9556, 86.9110, 94.7010, 103.0242] +24-11-19 20:34:24 | D | best error = [ 3.4395, 3.4395, 3.4395, 3.4395, 3.4395] +24-11-19 20:34:24 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:24 | D | sum error = [ 112.2833, 122.1540, 132.9243, 144.4085, 157.0442] +24-11-19 20:34:24 | D | best error = [ 3.4395, 3.4395, 3.4395, 3.4395, 3.4395] +24-11-19 20:34:24 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:24 | D | sum error = [ 170.8310, 185.4917, 201.8154, 219.1322, 238.1834] +24-11-19 20:34:24 | D | best error = [ 3.4395, 3.4395, 3.4395, 3.4395, 3.4395] +24-11-19 20:34:24 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:24 | D | sum error = [ 258.6476, 281.3568, 305.8814, 332.8258, 362.1492] +24-11-19 20:34:24 | D | best error = [ 3.4395, 3.4395, 3.4395, 3.4395, 3.4395] +24-11-19 20:34:24 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:24 | D | sum error = [ 393.9968, 429.4451, 467.8829, 510.0966, 556.1673] +24-11-19 20:34:24 | D | best error = [ 3.4395, 3.4395, 3.4395, 3.4395, 3.4395] +24-11-19 20:34:24 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:24 | D | sum error = [ 606.5202, 661.6199, 722.1969, 787.5576, 858.5721] +24-11-19 20:34:24 | D | best error = [ 3.4395, 3.4395, 3.4395, 3.4395, 3.4395] +24-11-19 20:34:24 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:24 | D | sum error = [ 935.7951, 1018.6020, 1107.5408, 1201.6783, 1300.7113] +24-11-19 20:34:24 | D | best error = [ 3.4395, 3.4395, 3.4395, 3.4395, 3.4395] +24-11-19 20:34:24 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:24 | D | sum error = [ 1404.1387, 1511.2850, 1620.9206, 1732.0847, 1843.9753] +24-11-19 20:34:24 | D | best error = [ 3.4395, 3.4395, 3.4395, 3.4395, 3.4395] +24-11-19 20:34:24 | D | + error = [3.4395] +24-11-19 20:34:24 | D | - Calibrating model.layers.19.self_attn.k_proj.weight +24-11-19 20:34:24 | D | + w: sint8 +24-11-19 20:34:24 | D | + x: None +24-11-19 20:34:24 | D | + y: None +24-11-19 20:34:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:34:24 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:34:25 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:34:25 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:34:25 | D | - range ratio = [ 1.0000] +24-11-19 20:34:25 | D | sum error = [ 3.4173] +24-11-19 20:34:25 | D | best error = [ 3.4173] +24-11-19 20:34:38 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:38 | D | sum error = [ 3.1584, 3.5609, 3.3893, 3.3779, 3.3756] +24-11-19 20:34:38 | D | best error = [ 3.1584, 3.1584, 3.1584, 3.1584, 3.1584] +24-11-19 20:34:38 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:38 | D | sum error = [ 3.7418, 4.1385, 4.3011, 4.3653, 4.2253] +24-11-19 20:34:38 | D | best error = [ 3.1584, 3.1584, 3.1584, 3.1584, 3.1584] +24-11-19 20:34:38 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:38 | D | sum error = [ 4.6281, 5.2637, 5.1728, 5.7787, 6.2889] +24-11-19 20:34:38 | D | best error = [ 3.1584, 3.1584, 3.1584, 3.1584, 3.1584] +24-11-19 20:34:38 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:38 | D | sum error = [ 6.3819, 7.2427, 7.7983, 8.5006, 8.9696] +24-11-19 20:34:38 | D | best error = [ 3.1584, 3.1584, 3.1584, 3.1584, 3.1584] +24-11-19 20:34:38 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:38 | D | sum error = [ 9.6811, 10.4459, 11.7103, 13.3274, 13.8697] +24-11-19 20:34:38 | D | best error = [ 3.1584, 3.1584, 3.1584, 3.1584, 3.1584] +24-11-19 20:34:38 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:38 | D | sum error = [ 15.4361, 16.5927, 17.8132, 19.3891, 21.7874] +24-11-19 20:34:38 | D | best error = [ 3.1584, 3.1584, 3.1584, 3.1584, 3.1584] +24-11-19 20:34:38 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:38 | D | sum error = [ 22.8990, 24.7454, 27.3225, 28.6487, 31.5125] +24-11-19 20:34:38 | D | best error = [ 3.1584, 3.1584, 3.1584, 3.1584, 3.1584] +24-11-19 20:34:38 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:38 | D | sum error = [ 34.0362, 37.1667, 40.2918, 43.5556, 47.1955] +24-11-19 20:34:38 | D | best error = [ 3.1584, 3.1584, 3.1584, 3.1584, 3.1584] +24-11-19 20:34:38 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:38 | D | sum error = [ 50.6617, 54.9213, 58.7895, 63.3419, 67.8666] +24-11-19 20:34:38 | D | best error = [ 3.1584, 3.1584, 3.1584, 3.1584, 3.1584] +24-11-19 20:34:38 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:38 | D | sum error = [ 72.9649, 78.6757, 84.7906, 91.7767, 98.6221] +24-11-19 20:34:38 | D | best error = [ 3.1584, 3.1584, 3.1584, 3.1584, 3.1584] +24-11-19 20:34:38 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:38 | D | sum error = [ 106.8213, 115.0529, 125.1796, 135.6142, 147.0775] +24-11-19 20:34:38 | D | best error = [ 3.1584, 3.1584, 3.1584, 3.1584, 3.1584] +24-11-19 20:34:38 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:38 | D | sum error = [ 160.3929, 174.3526, 189.8612, 208.0367, 226.3125] +24-11-19 20:34:38 | D | best error = [ 3.1584, 3.1584, 3.1584, 3.1584, 3.1584] +24-11-19 20:34:38 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:38 | D | sum error = [ 248.1890, 272.3867, 299.1843, 328.1866, 361.5484] +24-11-19 20:34:38 | D | best error = [ 3.1584, 3.1584, 3.1584, 3.1584, 3.1584] +24-11-19 20:34:38 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:38 | D | sum error = [ 397.0181, 436.7317, 480.7288, 528.6204, 580.1001] +24-11-19 20:34:38 | D | best error = [ 3.1584, 3.1584, 3.1584, 3.1584, 3.1584] +24-11-19 20:34:38 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:38 | D | sum error = [ 636.8655, 699.8071, 769.0631, 845.8772, 929.4838] +24-11-19 20:34:38 | D | best error = [ 3.1584, 3.1584, 3.1584, 3.1584, 3.1584] +24-11-19 20:34:38 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:38 | D | sum error = [ 1022.9200, 1126.1399, 1236.9542, 1355.5839, 1481.0346] +24-11-19 20:34:38 | D | best error = [ 3.1584, 3.1584, 3.1584, 3.1584, 3.1584] +24-11-19 20:34:38 | D | + error = [3.1584] +24-11-19 20:34:38 | D | - Calibrating model.layers.19.self_attn.v_proj.weight +24-11-19 20:34:38 | D | + w: sint8 +24-11-19 20:34:38 | D | + x: None +24-11-19 20:34:38 | D | + y: None +24-11-19 20:34:38 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:38 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:34:38 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:34:38 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:34:38 | D | - range ratio = [ 1.0000] +24-11-19 20:34:38 | D | sum error = [ 1.6691] +24-11-19 20:34:38 | D | best error = [ 1.6691] +24-11-19 20:34:38 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:38 | D | sum error = [ 1.6539, 1.6521, 1.6484, 1.6795, 1.7041] +24-11-19 20:34:38 | D | best error = [ 1.5519, 1.5043, 1.4781, 1.4636, 1.4568] +24-11-19 20:34:38 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:38 | D | sum error = [ 1.7582, 1.8327, 1.8980, 1.9815, 2.0892] +24-11-19 20:34:38 | D | best error = [ 1.4536, 1.4518, 1.4509, 1.4509, 1.4509] +24-11-19 20:34:38 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:38 | D | sum error = [ 2.2061, 2.3503, 2.5087, 2.6760, 2.8682] +24-11-19 20:34:38 | D | best error = [ 1.4509, 1.4509, 1.4509, 1.4509, 1.4509] +24-11-19 20:34:38 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:38 | D | sum error = [ 3.0667, 3.2979, 3.5263, 3.7767, 4.0505] +24-11-19 20:34:38 | D | best error = [ 1.4509, 1.4509, 1.4509, 1.4509, 1.4509] +24-11-19 20:34:38 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:38 | D | sum error = [ 4.3569, 4.6812, 5.0114, 5.3733, 5.7395] +24-11-19 20:34:38 | D | best error = [ 1.4509, 1.4509, 1.4509, 1.4509, 1.4509] +24-11-19 20:34:38 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:38 | D | sum error = [ 6.1461, 6.5613, 7.0236, 7.4913, 7.9801] +24-11-19 20:34:38 | D | best error = [ 1.4509, 1.4509, 1.4509, 1.4509, 1.4509] +24-11-19 20:34:38 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:38 | D | sum error = [ 8.5144, 9.1002, 9.6883, 10.2943, 10.9646] +24-11-19 20:34:38 | D | best error = [ 1.4509, 1.4509, 1.4509, 1.4509, 1.4509] +24-11-19 20:34:38 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:38 | D | sum error = [ 11.6563, 12.3896, 13.1797, 13.9666, 14.8151] +24-11-19 20:34:38 | D | best error = [ 1.4509, 1.4509, 1.4509, 1.4509, 1.4509] +24-11-19 20:34:38 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:38 | D | sum error = [ 15.7023, 16.6456, 17.6164, 18.6359, 19.7231] +24-11-19 20:34:38 | D | best error = [ 1.4509, 1.4509, 1.4509, 1.4509, 1.4509] +24-11-19 20:34:38 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:38 | D | sum error = [ 20.8675, 22.0526, 23.3051, 24.5920, 25.9614] +24-11-19 20:34:38 | D | best error = [ 1.4509, 1.4509, 1.4509, 1.4509, 1.4509] +24-11-19 20:34:38 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:38 | D | sum error = [ 27.3885, 28.8895, 30.4526, 32.0714, 33.7829] +24-11-19 20:34:38 | D | best error = [ 1.4509, 1.4509, 1.4509, 1.4509, 1.4509] +24-11-19 20:34:38 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:38 | D | sum error = [ 35.5500, 37.3872, 39.3070, 41.3036, 43.3823] +24-11-19 20:34:38 | D | best error = [ 1.4509, 1.4509, 1.4509, 1.4509, 1.4509] +24-11-19 20:34:38 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:38 | D | sum error = [ 45.5447, 47.7913, 50.1315, 52.5604, 55.0915] +24-11-19 20:34:38 | D | best error = [ 1.4509, 1.4509, 1.4509, 1.4509, 1.4509] +24-11-19 20:34:38 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:38 | D | sum error = [ 57.7121, 60.4459, 63.2683, 66.1920, 69.2188] +24-11-19 20:34:38 | D | best error = [ 1.4509, 1.4509, 1.4509, 1.4509, 1.4509] +24-11-19 20:34:38 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:38 | D | sum error = [ 72.3495, 75.5812, 78.9192, 82.3743, 85.9296] +24-11-19 20:34:38 | D | best error = [ 1.4509, 1.4509, 1.4509, 1.4509, 1.4509] +24-11-19 20:34:38 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:38 | D | sum error = [ 89.6070, 93.3908, 97.2980, 101.3109, 105.4425] +24-11-19 20:34:38 | D | best error = [ 1.4509, 1.4509, 1.4509, 1.4509, 1.4509] +24-11-19 20:34:38 | D | + error = [1.4509] +24-11-19 20:34:38 | D | - Calibrating model.layers.19.self_attn.o_proj.weight +24-11-19 20:34:38 | D | + w: sint8 +24-11-19 20:34:38 | D | + x: None +24-11-19 20:34:38 | D | + y: None +24-11-19 20:34:38 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:38 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:34:38 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:34:38 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:34:38 | D | - range ratio = [ 1.0000] +24-11-19 20:34:38 | D | sum error = [ 0.3769] +24-11-19 20:34:38 | D | best error = [ 0.3769] +24-11-19 20:34:39 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:39 | D | sum error = [ 0.3739, 0.3729, 0.3743, 0.3756, 0.3787] +24-11-19 20:34:39 | D | best error = [ 0.3528, 0.3421, 0.3355, 0.3311, 0.3277] +24-11-19 20:34:39 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:39 | D | sum error = [ 0.3877, 0.3978, 0.4103, 0.4241, 0.4425] +24-11-19 20:34:39 | D | best error = [ 0.3256, 0.3238, 0.3226, 0.3217, 0.3209] +24-11-19 20:34:39 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:39 | D | sum error = [ 0.4618, 0.4867, 0.5129, 0.5426, 0.5725] +24-11-19 20:34:39 | D | best error = [ 0.3203, 0.3199, 0.3196, 0.3192, 0.3191] +24-11-19 20:34:39 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:39 | D | sum error = [ 0.6093, 0.6461, 0.6862, 0.7302, 0.7759] +24-11-19 20:34:39 | D | best error = [ 0.3189, 0.3189, 0.3188, 0.3187, 0.3187] +24-11-19 20:34:39 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:39 | D | sum error = [ 0.8265, 0.8794, 0.9357, 0.9960, 1.0572] +24-11-19 20:34:39 | D | best error = [ 0.3187, 0.3187, 0.3187, 0.3186, 0.3186] +24-11-19 20:34:39 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:39 | D | sum error = [ 1.1250, 1.1944, 1.2702, 1.3491, 1.4310] +24-11-19 20:34:39 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:34:39 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:39 | D | sum error = [ 1.5199, 1.6123, 1.7079, 1.8098, 1.9179] +24-11-19 20:34:39 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:34:39 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:39 | D | sum error = [ 2.0295, 2.1472, 2.2700, 2.3991, 2.5338] +24-11-19 20:34:39 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:34:39 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:39 | D | sum error = [ 2.6770, 2.8267, 2.9832, 3.1480, 3.3202] +24-11-19 20:34:39 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:34:39 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:39 | D | sum error = [ 3.5015, 3.6918, 3.8898, 4.0977, 4.3149] +24-11-19 20:34:39 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:34:39 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:39 | D | sum error = [ 4.5425, 4.7806, 5.0283, 5.2879, 5.5585] +24-11-19 20:34:39 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:34:39 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:39 | D | sum error = [ 5.8410, 6.1359, 6.4444, 6.7645, 7.0997] +24-11-19 20:34:39 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:34:39 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:39 | D | sum error = [ 7.4472, 7.8102, 8.1861, 8.5769, 8.9824] +24-11-19 20:34:39 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:34:39 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:39 | D | sum error = [ 9.4038, 9.8409, 10.2946, 10.7663, 11.2538] +24-11-19 20:34:39 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:34:39 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:39 | D | sum error = [ 11.7596, 12.2836, 12.8263, 13.3882, 13.9692] +24-11-19 20:34:39 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:34:39 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:39 | D | sum error = [ 14.5690, 15.1893, 15.8287, 16.4900, 17.1719] +24-11-19 20:34:39 | D | best error = [ 0.3186, 0.3186, 0.3186, 0.3186, 0.3186] +24-11-19 20:34:39 | D | + error = [0.3186] +24-11-19 20:34:39 | D | - Calibrating model.layers.19.mlp.up_proj.weight +24-11-19 20:34:39 | D | + w: sint8 +24-11-19 20:34:39 | D | + x: None +24-11-19 20:34:39 | D | + y: None +24-11-19 20:34:39 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:39 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:34:39 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:34:39 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:34:39 | D | - range ratio = [ 1.0000] +24-11-19 20:34:39 | D | sum error = [ 6.5167] +24-11-19 20:34:39 | D | best error = [ 6.5167] +24-11-19 20:34:40 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:40 | D | sum error = [ 6.4672, 6.4597, 6.4681, 6.5433, 6.6676] +24-11-19 20:34:40 | D | best error = [ 6.0329, 5.8510, 5.7552, 5.7001, 5.6706] +24-11-19 20:34:40 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:40 | D | sum error = [ 6.8280, 7.0453, 7.3503, 7.6849, 8.0797] +24-11-19 20:34:40 | D | best error = [ 5.6569, 5.6506, 5.6478, 5.6470, 5.6468] +24-11-19 20:34:40 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:40 | D | sum error = [ 8.5415, 9.0687, 9.6608, 10.3071, 11.0192] +24-11-19 20:34:40 | D | best error = [ 5.6468, 5.6468, 5.6468, 5.6468, 5.6468] +24-11-19 20:34:40 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:40 | D | sum error = [ 11.7937, 12.6166, 13.5123, 14.4818, 15.5121] +24-11-19 20:34:40 | D | best error = [ 5.6468, 5.6468, 5.6468, 5.6468, 5.6468] +24-11-19 20:34:40 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:40 | D | sum error = [ 16.5966, 17.7795, 19.0325, 20.3634, 21.7692] +24-11-19 20:34:40 | D | best error = [ 5.6468, 5.6468, 5.6468, 5.6468, 5.6468] +24-11-19 20:34:40 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:40 | D | sum error = [ 23.2454, 24.8391, 26.4932, 28.2685, 30.1318] +24-11-19 20:34:40 | D | best error = [ 5.6468, 5.6468, 5.6468, 5.6468, 5.6468] +24-11-19 20:34:40 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:40 | D | sum error = [ 32.0830, 34.1471, 36.3175, 38.6051, 41.0205] +24-11-19 20:34:40 | D | best error = [ 5.6468, 5.6468, 5.6468, 5.6468, 5.6468] +24-11-19 20:34:40 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:40 | D | sum error = [ 43.5602, 46.2150, 49.0195, 51.9463, 55.0225] +24-11-19 20:34:40 | D | best error = [ 5.6468, 5.6468, 5.6468, 5.6468, 5.6468] +24-11-19 20:34:40 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:40 | D | sum error = [ 58.2603, 61.6454, 65.1932, 68.8991, 72.7874] +24-11-19 20:34:40 | D | best error = [ 5.6468, 5.6468, 5.6468, 5.6468, 5.6468] +24-11-19 20:34:40 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:40 | D | sum error = [ 76.8573, 81.1150, 85.5700, 90.2011, 95.0513] +24-11-19 20:34:40 | D | best error = [ 5.6468, 5.6468, 5.6468, 5.6468, 5.6468] +24-11-19 20:34:40 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:40 | D | sum error = [ 100.0971, 105.3696, 110.8633, 116.5776, 122.5251] +24-11-19 20:34:40 | D | best error = [ 5.6468, 5.6468, 5.6468, 5.6468, 5.6468] +24-11-19 20:34:40 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:40 | D | sum error = [ 128.7047, 135.1235, 141.8105, 148.7421, 155.9270] +24-11-19 20:34:40 | D | best error = [ 5.6468, 5.6468, 5.6468, 5.6468, 5.6468] +24-11-19 20:34:40 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:40 | D | sum error = [ 163.3895, 171.1235, 179.1358, 187.4364, 196.0261] +24-11-19 20:34:40 | D | best error = [ 5.6468, 5.6468, 5.6468, 5.6468, 5.6468] +24-11-19 20:34:40 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:40 | D | sum error = [ 204.9089, 214.0950, 223.5852, 233.4035, 243.5269] +24-11-19 20:34:40 | D | best error = [ 5.6468, 5.6468, 5.6468, 5.6468, 5.6468] +24-11-19 20:34:40 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:40 | D | sum error = [ 253.9689, 264.7440, 275.8404, 287.2785, 299.0479] +24-11-19 20:34:40 | D | best error = [ 5.6468, 5.6468, 5.6468, 5.6468, 5.6468] +24-11-19 20:34:40 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:40 | D | sum error = [ 311.1874, 323.6774, 336.5253, 349.7284, 363.2920] +24-11-19 20:34:40 | D | best error = [ 5.6468, 5.6468, 5.6468, 5.6468, 5.6468] +24-11-19 20:34:40 | D | + error = [5.6468] +24-11-19 20:34:40 | D | - Calibrating model.layers.19.mlp.gate_proj.weight +24-11-19 20:34:40 | D | + w: sint8 +24-11-19 20:34:40 | D | + x: None +24-11-19 20:34:40 | D | + y: None +24-11-19 20:34:40 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:40 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:34:40 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:34:41 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:34:41 | D | - range ratio = [ 1.0000] +24-11-19 20:34:41 | D | sum error = [ 8.7901] +24-11-19 20:34:41 | D | best error = [ 8.7901] +24-11-19 20:34:42 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:42 | D | sum error = [ 8.7249, 8.7155, 8.7477, 8.8183, 9.0155] +24-11-19 20:34:42 | D | best error = [ 8.1413, 7.9015, 7.7731, 7.7004, 7.6604] +24-11-19 20:34:42 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:42 | D | sum error = [ 9.2217, 9.5531, 9.9452, 10.4355, 10.9773] +24-11-19 20:34:42 | D | best error = [ 7.6403, 7.6323, 7.6292, 7.6285, 7.6284] +24-11-19 20:34:42 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:42 | D | sum error = [ 11.6511, 12.3521, 13.1935, 14.0685, 15.0733] +24-11-19 20:34:42 | D | best error = [ 7.6283, 7.6283, 7.6283, 7.6283, 7.6283] +24-11-19 20:34:42 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:42 | D | sum error = [ 16.1476, 17.3152, 18.5728, 19.9121, 21.3773] +24-11-19 20:34:42 | D | best error = [ 7.6283, 7.6283, 7.6283, 7.6283, 7.6283] +24-11-19 20:34:42 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:42 | D | sum error = [ 22.9252, 24.6107, 26.3692, 28.2312, 30.2433] +24-11-19 20:34:42 | D | best error = [ 7.6283, 7.6283, 7.6283, 7.6283, 7.6283] +24-11-19 20:34:42 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:42 | D | sum error = [ 32.3736, 34.6330, 37.0573, 39.5943, 42.3185] +24-11-19 20:34:42 | D | best error = [ 7.6283, 7.6283, 7.6283, 7.6283, 7.6283] +24-11-19 20:34:42 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:42 | D | sum error = [ 45.1769, 48.2116, 51.4342, 54.8726, 58.4748] +24-11-19 20:34:42 | D | best error = [ 7.6283, 7.6283, 7.6283, 7.6283, 7.6283] +24-11-19 20:34:42 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:42 | D | sum error = [ 62.3060, 66.3514, 70.6753, 75.2012, 80.0125] +24-11-19 20:34:42 | D | best error = [ 7.6283, 7.6283, 7.6283, 7.6283, 7.6283] +24-11-19 20:34:42 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:42 | D | sum error = [ 85.0879, 90.4903, 96.1738, 102.2030, 108.5788] +24-11-19 20:34:42 | D | best error = [ 7.6283, 7.6283, 7.6283, 7.6283, 7.6283] +24-11-19 20:34:42 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:42 | D | sum error = [ 115.2930, 122.4217, 129.8791, 137.7794, 146.1059] +24-11-19 20:34:42 | D | best error = [ 7.6283, 7.6283, 7.6283, 7.6283, 7.6283] +24-11-19 20:34:42 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:42 | D | sum error = [ 154.8560, 164.0647, 173.7672, 184.0228, 194.7765] +24-11-19 20:34:42 | D | best error = [ 7.6283, 7.6283, 7.6283, 7.6283, 7.6283] +24-11-19 20:34:42 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:42 | D | sum error = [ 206.0455, 217.9125, 230.3642, 243.4294, 257.1230] +24-11-19 20:34:42 | D | best error = [ 7.6283, 7.6283, 7.6283, 7.6283, 7.6283] +24-11-19 20:34:42 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:42 | D | sum error = [ 271.4797, 286.4907, 302.2091, 318.6298, 335.7902] +24-11-19 20:34:42 | D | best error = [ 7.6283, 7.6283, 7.6283, 7.6283, 7.6283] +24-11-19 20:34:42 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:42 | D | sum error = [ 353.7460, 372.4660, 391.9842, 412.3530, 433.5286] +24-11-19 20:34:42 | D | best error = [ 7.6283, 7.6283, 7.6283, 7.6283, 7.6283] +24-11-19 20:34:42 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:42 | D | sum error = [ 455.5866, 478.4883, 502.2527, 526.8821, 552.4228] +24-11-19 20:34:42 | D | best error = [ 7.6283, 7.6283, 7.6283, 7.6283, 7.6283] +24-11-19 20:34:42 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:42 | D | sum error = [ 578.7985, 606.0662, 634.2271, 663.2442, 693.1744] +24-11-19 20:34:42 | D | best error = [ 7.6283, 7.6283, 7.6283, 7.6283, 7.6283] +24-11-19 20:34:42 | D | + error = [7.6283] +24-11-19 20:34:42 | D | - Calibrating model.layers.19.mlp.down_proj.weight +24-11-19 20:34:42 | D | + w: sint8 +24-11-19 20:34:42 | D | + x: None +24-11-19 20:34:42 | D | + y: None +24-11-19 20:34:42 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:34:42 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:34:42 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:34:42 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:34:42 | D | - range ratio = [ 1.0000] +24-11-19 20:34:42 | D | sum error = [ 0.9893] +24-11-19 20:34:42 | D | best error = [ 0.9893] +24-11-19 20:34:43 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:34:43 | D | sum error = [ 0.9835, 0.9754, 0.9692, 0.9637, 0.9633] +24-11-19 20:34:43 | D | best error = [ 0.9520, 0.9325, 0.9196, 0.9091, 0.9011] +24-11-19 20:34:43 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:34:43 | D | sum error = [ 0.9638, 0.9674, 0.9748, 0.9846, 0.9998] +24-11-19 20:34:43 | D | best error = [ 0.8951, 0.8901, 0.8860, 0.8832, 0.8809] +24-11-19 20:34:43 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:34:43 | D | sum error = [ 1.0199, 1.0462, 1.0778, 1.1125, 1.1565] +24-11-19 20:34:43 | D | best error = [ 0.8792, 0.8781, 0.8775, 0.8769, 0.8766] +24-11-19 20:34:43 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:34:43 | D | sum error = [ 1.2059, 1.2616, 1.3248, 1.3957, 1.4771] +24-11-19 20:34:43 | D | best error = [ 0.8764, 0.8762, 0.8761, 0.8760, 0.8760] +24-11-19 20:34:43 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:34:43 | D | sum error = [ 1.5650, 1.6607, 1.7651, 1.8798, 2.0054] +24-11-19 20:34:43 | D | best error = [ 0.8760, 0.8760, 0.8760, 0.8759, 0.8759] +24-11-19 20:34:43 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:34:43 | D | sum error = [ 2.1373, 2.2859, 2.4424, 2.6091, 2.7919] +24-11-19 20:34:43 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 20:34:43 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:34:43 | D | sum error = [ 2.9842, 3.1909, 3.4138, 3.6487, 3.9005] +24-11-19 20:34:43 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 20:34:43 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:34:43 | D | sum error = [ 4.1664, 4.4509, 4.7538, 5.0751, 5.4139] +24-11-19 20:34:43 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 20:34:43 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:34:43 | D | sum error = [ 5.7748, 6.1569, 6.5609, 6.9888, 7.4419] +24-11-19 20:34:43 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 20:34:43 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:34:43 | D | sum error = [ 7.9200, 8.4235, 8.9568, 9.5169, 10.1087] +24-11-19 20:34:43 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 20:34:43 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:34:43 | D | sum error = [ 10.7303, 11.3874, 12.0748, 12.7996, 13.5585] +24-11-19 20:34:43 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 20:34:43 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:34:43 | D | sum error = [ 14.3569, 15.1947, 16.0730, 16.9920, 17.9542] +24-11-19 20:34:43 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 20:34:43 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:34:43 | D | sum error = [ 18.9608, 20.0151, 21.1158, 22.2636, 23.4609] +24-11-19 20:34:43 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 20:34:43 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:34:43 | D | sum error = [ 24.7092, 26.0100, 27.3627, 28.7715, 30.2341] +24-11-19 20:34:43 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 20:34:43 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:34:43 | D | sum error = [ 31.7539, 33.3339, 34.9734, 36.6735, 38.4362] +24-11-19 20:34:43 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 20:34:43 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:34:43 | D | sum error = [ 40.2626, 42.1529, 44.1086, 46.1285, 48.2124] +24-11-19 20:34:43 | D | best error = [ 0.8759, 0.8759, 0.8759, 0.8759, 0.8759] +24-11-19 20:34:43 | D | + error = [0.8759] +24-11-19 20:34:43 | D | - Quantizing model.layers.19.self_attn.q_proj.weight +24-11-19 20:34:44 | D | - Quantizing model.layers.19.self_attn.k_proj.weight +24-11-19 20:34:45 | D | - Quantizing model.layers.19.self_attn.v_proj.weight +24-11-19 20:34:46 | D | - Quantizing model.layers.19.self_attn.o_proj.weight +24-11-19 20:34:47 | D | - Quantizing model.layers.19.mlp.up_proj.weight +24-11-19 20:34:48 | D | - Quantizing model.layers.19.mlp.gate_proj.weight +24-11-19 20:34:49 | D | - Quantizing model.layers.19.mlp.down_proj.weight +24-11-19 20:34:58 | D | - Quantizing layer model.layers.20 +24-11-19 20:34:58 | D | - Calibrating model.layers.20.self_attn.q_proj.weight +24-11-19 20:34:58 | D | + w: sint8 +24-11-19 20:34:58 | D | + x: None +24-11-19 20:34:58 | D | + y: None +24-11-19 20:34:58 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:34:58 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:34:59 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:34:59 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:34:59 | D | - range ratio = [ 1.0000] +24-11-19 20:34:59 | D | sum error = [ 3.9067] +24-11-19 20:34:59 | D | best error = [ 3.9067] +24-11-19 20:35:11 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:11 | D | sum error = [ 3.8111, 3.8466, 3.9026, 3.9285, 4.0468] +24-11-19 20:35:11 | D | best error = [ 3.8111, 3.8111, 3.8111, 3.8111, 3.8111] +24-11-19 20:35:11 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:11 | D | sum error = [ 4.0917, 4.3158, 4.5020, 4.6656, 4.8782] +24-11-19 20:35:11 | D | best error = [ 3.8111, 3.8111, 3.8111, 3.8111, 3.8111] +24-11-19 20:35:11 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:11 | D | sum error = [ 5.1483, 5.5022, 5.9923, 6.4605, 7.0377] +24-11-19 20:35:11 | D | best error = [ 3.8111, 3.8111, 3.8111, 3.8111, 3.8111] +24-11-19 20:35:11 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:11 | D | sum error = [ 7.7642, 8.1405, 8.8357, 10.1009, 10.8629] +24-11-19 20:35:11 | D | best error = [ 3.8111, 3.8111, 3.8111, 3.8111, 3.8111] +24-11-19 20:35:11 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:11 | D | sum error = [ 11.9038, 13.2085, 14.5550, 16.0502, 17.4814] +24-11-19 20:35:11 | D | best error = [ 3.8111, 3.8111, 3.8111, 3.8111, 3.8111] +24-11-19 20:35:11 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:11 | D | sum error = [ 19.2955, 21.4452, 23.5380, 25.6673, 28.5415] +24-11-19 20:35:11 | D | best error = [ 3.8111, 3.8111, 3.8111, 3.8111, 3.8111] +24-11-19 20:35:11 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:11 | D | sum error = [ 31.1987, 34.3622, 37.8432, 41.6260, 45.8196] +24-11-19 20:35:11 | D | best error = [ 3.8111, 3.8111, 3.8111, 3.8111, 3.8111] +24-11-19 20:35:11 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:11 | D | sum error = [ 50.6643, 55.4950, 61.2079, 67.5501, 74.2458] +24-11-19 20:35:11 | D | best error = [ 3.8111, 3.8111, 3.8111, 3.8111, 3.8111] +24-11-19 20:35:11 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:11 | D | sum error = [ 81.4504, 89.5362, 98.2543, 107.2373, 117.6138] +24-11-19 20:35:11 | D | best error = [ 3.8111, 3.8111, 3.8111, 3.8111, 3.8111] +24-11-19 20:35:11 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:11 | D | sum error = [ 129.4020, 141.6275, 156.0048, 170.7580, 187.4621] +24-11-19 20:35:11 | D | best error = [ 3.8111, 3.8111, 3.8111, 3.8111, 3.8111] +24-11-19 20:35:11 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:11 | D | sum error = [ 205.8668, 226.3366, 248.0665, 272.0072, 299.0718] +24-11-19 20:35:11 | D | best error = [ 3.8111, 3.8111, 3.8111, 3.8111, 3.8111] +24-11-19 20:35:11 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:11 | D | sum error = [ 327.9835, 360.5564, 396.7564, 436.6000, 480.7163] +24-11-19 20:35:11 | D | best error = [ 3.8111, 3.8111, 3.8111, 3.8111, 3.8111] +24-11-19 20:35:11 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:11 | D | sum error = [ 528.7664, 582.7596, 642.1736, 708.4776, 781.4089] +24-11-19 20:35:11 | D | best error = [ 3.8111, 3.8111, 3.8111, 3.8111, 3.8111] +24-11-19 20:35:11 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:11 | D | sum error = [ 862.7856, 950.4913, 1048.9666, 1154.4566, 1271.4977] +24-11-19 20:35:11 | D | best error = [ 3.8111, 3.8111, 3.8111, 3.8111, 3.8111] +24-11-19 20:35:11 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:11 | D | sum error = [ 1397.5573, 1536.2150, 1683.9133, 1845.6861, 2011.2701] +24-11-19 20:35:11 | D | best error = [ 3.8111, 3.8111, 3.8111, 3.8111, 3.8111] +24-11-19 20:35:11 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:11 | D | sum error = [ 2186.1150, 2364.4189, 2546.9617, 2726.1676, 2905.5612] +24-11-19 20:35:11 | D | best error = [ 3.8111, 3.8111, 3.8111, 3.8111, 3.8111] +24-11-19 20:35:11 | D | + error = [3.8111] +24-11-19 20:35:11 | D | - Calibrating model.layers.20.self_attn.k_proj.weight +24-11-19 20:35:11 | D | + w: sint8 +24-11-19 20:35:11 | D | + x: None +24-11-19 20:35:11 | D | + y: None +24-11-19 20:35:11 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:35:11 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:11 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:11 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:11 | D | - range ratio = [ 1.0000] +24-11-19 20:35:11 | D | sum error = [ 3.9056] +24-11-19 20:35:11 | D | best error = [ 3.9056] +24-11-19 20:35:24 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:24 | D | sum error = [ 4.1316, 3.8519, 3.8854, 3.6834, 3.9449] +24-11-19 20:35:24 | D | best error = [ 3.9056, 3.8519, 3.8519, 3.6834, 3.6834] +24-11-19 20:35:24 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:24 | D | sum error = [ 4.1202, 4.3523, 4.5625, 5.0140, 6.4568] +24-11-19 20:35:24 | D | best error = [ 3.6834, 3.6834, 3.6834, 3.6834, 3.6834] +24-11-19 20:35:24 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:24 | D | sum error = [ 5.6464, 6.2251, 7.7055, 7.3280, 9.4148] +24-11-19 20:35:24 | D | best error = [ 3.6834, 3.6834, 3.6834, 3.6834, 3.6834] +24-11-19 20:35:24 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:24 | D | sum error = [ 9.0057, 9.3562, 11.0974, 12.7819, 11.6087] +24-11-19 20:35:24 | D | best error = [ 3.6834, 3.6834, 3.6834, 3.6834, 3.6834] +24-11-19 20:35:24 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:24 | D | sum error = [ 14.1360, 14.7933, 16.2999, 17.0426, 17.8657] +24-11-19 20:35:24 | D | best error = [ 3.6834, 3.6834, 3.6834, 3.6834, 3.6834] +24-11-19 20:35:24 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:24 | D | sum error = [ 19.1963, 20.5840, 21.8540, 24.4399, 26.6714] +24-11-19 20:35:24 | D | best error = [ 3.6834, 3.6834, 3.6834, 3.6834, 3.6834] +24-11-19 20:35:24 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:24 | D | sum error = [ 29.5843, 33.2917, 37.6018, 38.8926, 41.4856] +24-11-19 20:35:24 | D | best error = [ 3.6834, 3.6834, 3.6834, 3.6834, 3.6834] +24-11-19 20:35:24 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:24 | D | sum error = [ 47.5070, 51.5487, 55.2636, 60.2090, 66.2666] +24-11-19 20:35:24 | D | best error = [ 3.6834, 3.6834, 3.6834, 3.6834, 3.6834] +24-11-19 20:35:24 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:24 | D | sum error = [ 70.1683, 75.6490, 83.5009, 91.1597, 99.5701] +24-11-19 20:35:24 | D | best error = [ 3.6834, 3.6834, 3.6834, 3.6834, 3.6834] +24-11-19 20:35:24 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:24 | D | sum error = [ 108.6566, 117.1914, 129.5562, 140.8953, 154.4614] +24-11-19 20:35:24 | D | best error = [ 3.6834, 3.6834, 3.6834, 3.6834, 3.6834] +24-11-19 20:35:24 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:24 | D | sum error = [ 168.6346, 185.0115, 202.4034, 223.3102, 244.2759] +24-11-19 20:35:24 | D | best error = [ 3.6834, 3.6834, 3.6834, 3.6834, 3.6834] +24-11-19 20:35:24 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:24 | D | sum error = [ 268.9145, 295.2450, 323.9846, 358.4428, 396.1219] +24-11-19 20:35:24 | D | best error = [ 3.6834, 3.6834, 3.6834, 3.6834, 3.6834] +24-11-19 20:35:24 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:24 | D | sum error = [ 436.8898, 483.7625, 536.9210, 599.7191, 667.4378] +24-11-19 20:35:24 | D | best error = [ 3.6834, 3.6834, 3.6834, 3.6834, 3.6834] +24-11-19 20:35:24 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:24 | D | sum error = [ 739.4405, 823.3686, 915.2992, 1017.4104, 1132.4674] +24-11-19 20:35:24 | D | best error = [ 3.6834, 3.6834, 3.6834, 3.6834, 3.6834] +24-11-19 20:35:24 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:24 | D | sum error = [ 1253.7093, 1385.9432, 1532.3440, 1689.4697, 1856.5661] +24-11-19 20:35:24 | D | best error = [ 3.6834, 3.6834, 3.6834, 3.6834, 3.6834] +24-11-19 20:35:24 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:24 | D | sum error = [ 2028.7155, 2215.8414, 2401.6246, 2589.1473, 2777.4793] +24-11-19 20:35:24 | D | best error = [ 3.6834, 3.6834, 3.6834, 3.6834, 3.6834] +24-11-19 20:35:24 | D | + error = [3.6834] +24-11-19 20:35:24 | D | - Calibrating model.layers.20.self_attn.v_proj.weight +24-11-19 20:35:24 | D | + w: sint8 +24-11-19 20:35:24 | D | + x: None +24-11-19 20:35:24 | D | + y: None +24-11-19 20:35:24 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:24 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:24 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:35:24 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:35:24 | D | - range ratio = [ 1.0000] +24-11-19 20:35:24 | D | sum error = [ 1.7734] +24-11-19 20:35:24 | D | best error = [ 1.7734] +24-11-19 20:35:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:25 | D | sum error = [ 1.7580, 1.7439, 1.7643, 1.7672, 1.8086] +24-11-19 20:35:25 | D | best error = [ 1.6385, 1.5847, 1.5594, 1.5454, 1.5366] +24-11-19 20:35:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:25 | D | sum error = [ 1.8776, 1.9165, 2.0074, 2.0977, 2.2090] +24-11-19 20:35:25 | D | best error = [ 1.5335, 1.5325, 1.5316, 1.5312, 1.5312] +24-11-19 20:35:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:25 | D | sum error = [ 2.3412, 2.5019, 2.6576, 2.8425, 3.0290] +24-11-19 20:35:25 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:25 | D | sum error = [ 3.2551, 3.4786, 3.7390, 4.0023, 4.3063] +24-11-19 20:35:25 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:25 | D | sum error = [ 4.5964, 4.9114, 5.2879, 5.6584, 6.0506] +24-11-19 20:35:25 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:25 | D | sum error = [ 6.4595, 6.9312, 7.3973, 7.8913, 8.4278] +24-11-19 20:35:25 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:25 | D | sum error = [ 8.9735, 9.5765, 10.1879, 10.8318, 11.5143] +24-11-19 20:35:25 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:25 | D | sum error = [ 12.2359, 13.0084, 13.7886, 14.6185, 15.4932] +24-11-19 20:35:25 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:25 | D | sum error = [ 16.4091, 17.3815, 18.3992, 19.4508, 20.5691] +24-11-19 20:35:25 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:25 | D | sum error = [ 21.7318, 22.9575, 24.2358, 25.5715, 26.9723] +24-11-19 20:35:25 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:25 | D | sum error = [ 28.4513, 29.9864, 31.5792, 33.2400, 34.9748] +24-11-19 20:35:25 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:25 | D | sum error = [ 36.7755, 38.6540, 40.6085, 42.6399, 44.7589] +24-11-19 20:35:25 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:25 | D | sum error = [ 46.9633, 49.2419, 51.6179, 54.0616, 56.6113] +24-11-19 20:35:25 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:25 | D | sum error = [ 59.2584, 61.9889, 64.8263, 67.7663, 70.8091] +24-11-19 20:35:25 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:25 | D | sum error = [ 73.9652, 77.2177, 80.5850, 84.0495, 87.6269] +24-11-19 20:35:25 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:25 | D | sum error = [ 91.3166, 95.0979, 98.9979, 102.9931, 107.1103] +24-11-19 20:35:25 | D | best error = [ 1.5312, 1.5312, 1.5312, 1.5312, 1.5312] +24-11-19 20:35:25 | D | + error = [1.5312] +24-11-19 20:35:25 | D | - Calibrating model.layers.20.self_attn.o_proj.weight +24-11-19 20:35:25 | D | + w: sint8 +24-11-19 20:35:25 | D | + x: None +24-11-19 20:35:25 | D | + y: None +24-11-19 20:35:25 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:25 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:35:25 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:35:25 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:35:25 | D | - range ratio = [ 1.0000] +24-11-19 20:35:25 | D | sum error = [ 0.3942] +24-11-19 20:35:25 | D | best error = [ 0.3942] +24-11-19 20:35:25 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:25 | D | sum error = [ 0.3909, 0.3897, 0.3906, 0.3927, 0.3999] +24-11-19 20:35:25 | D | best error = [ 0.3712, 0.3607, 0.3546, 0.3502, 0.3477] +24-11-19 20:35:25 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:25 | D | sum error = [ 0.4069, 0.4172, 0.4312, 0.4465, 0.4671] +24-11-19 20:35:25 | D | best error = [ 0.3458, 0.3446, 0.3438, 0.3431, 0.3427] +24-11-19 20:35:25 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:25 | D | sum error = [ 0.4898, 0.5137, 0.5443, 0.5763, 0.6105] +24-11-19 20:35:25 | D | best error = [ 0.3425, 0.3424, 0.3422, 0.3422, 0.3421] +24-11-19 20:35:25 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:25 | D | sum error = [ 0.6509, 0.6930, 0.7384, 0.7867, 0.8397] +24-11-19 20:35:25 | D | best error = [ 0.3421, 0.3420, 0.3420, 0.3420, 0.3420] +24-11-19 20:35:25 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:25 | D | sum error = [ 0.8960, 0.9556, 1.0188, 1.0868, 1.1584] +24-11-19 20:35:25 | D | best error = [ 0.3420, 0.3419, 0.3419, 0.3419, 0.3419] +24-11-19 20:35:25 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:25 | D | sum error = [ 1.2343, 1.3139, 1.3991, 1.4894, 1.5833] +24-11-19 20:35:25 | D | best error = [ 0.3419, 0.3419, 0.3419, 0.3419, 0.3419] +24-11-19 20:35:25 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:25 | D | sum error = [ 1.6839, 1.7882, 1.9001, 2.0167, 2.1409] +24-11-19 20:35:25 | D | best error = [ 0.3419, 0.3419, 0.3419, 0.3419, 0.3419] +24-11-19 20:35:25 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:25 | D | sum error = [ 2.2699, 2.4062, 2.5502, 2.7020, 2.8600] +24-11-19 20:35:25 | D | best error = [ 0.3419, 0.3419, 0.3419, 0.3419, 0.3419] +24-11-19 20:35:25 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:25 | D | sum error = [ 3.0273, 3.2006, 3.3836, 3.5758, 3.7780] +24-11-19 20:35:25 | D | best error = [ 0.3419, 0.3419, 0.3419, 0.3419, 0.3419] +24-11-19 20:35:25 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:25 | D | sum error = [ 3.9882, 4.2086, 4.4404, 4.6815, 4.9349] +24-11-19 20:35:25 | D | best error = [ 0.3419, 0.3419, 0.3419, 0.3419, 0.3419] +24-11-19 20:35:25 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:25 | D | sum error = [ 5.1994, 5.4761, 5.7639, 6.0655, 6.3803] +24-11-19 20:35:25 | D | best error = [ 0.3419, 0.3419, 0.3419, 0.3419, 0.3419] +24-11-19 20:35:25 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:25 | D | sum error = [ 6.7097, 7.0523, 7.4094, 7.7820, 8.1700] +24-11-19 20:35:25 | D | best error = [ 0.3419, 0.3419, 0.3419, 0.3419, 0.3419] +24-11-19 20:35:25 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:25 | D | sum error = [ 8.5749, 8.9956, 9.4332, 9.8895, 10.3629] +24-11-19 20:35:25 | D | best error = [ 0.3419, 0.3419, 0.3419, 0.3419, 0.3419] +24-11-19 20:35:25 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:25 | D | sum error = [ 10.8544, 11.3645, 11.8938, 12.4434, 13.0113] +24-11-19 20:35:25 | D | best error = [ 0.3419, 0.3419, 0.3419, 0.3419, 0.3419] +24-11-19 20:35:25 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:25 | D | sum error = [ 13.5992, 14.2079, 14.8376, 15.4893, 16.1629] +24-11-19 20:35:25 | D | best error = [ 0.3419, 0.3419, 0.3419, 0.3419, 0.3419] +24-11-19 20:35:25 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:25 | D | sum error = [ 16.8594, 17.5792, 18.3216, 19.0875, 19.8767] +24-11-19 20:35:25 | D | best error = [ 0.3419, 0.3419, 0.3419, 0.3419, 0.3419] +24-11-19 20:35:25 | D | + error = [0.3419] +24-11-19 20:35:26 | D | - Calibrating model.layers.20.mlp.up_proj.weight +24-11-19 20:35:26 | D | + w: sint8 +24-11-19 20:35:26 | D | + x: None +24-11-19 20:35:26 | D | + y: None +24-11-19 20:35:26 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:26 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:35:26 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:35:26 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:35:26 | D | - range ratio = [ 1.0000] +24-11-19 20:35:26 | D | sum error = [ 6.7131] +24-11-19 20:35:26 | D | best error = [ 6.7131] +24-11-19 20:35:27 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:27 | D | sum error = [ 6.6595, 6.6497, 6.6918, 6.7611, 6.8798] +24-11-19 20:35:27 | D | best error = [ 6.2415, 6.0589, 5.9610, 5.9072, 5.8778] +24-11-19 20:35:27 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:27 | D | sum error = [ 7.0658, 7.3002, 7.6011, 7.9474, 8.3617] +24-11-19 20:35:27 | D | best error = [ 5.8638, 5.8578, 5.8560, 5.8555, 5.8554] +24-11-19 20:35:27 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:27 | D | sum error = [ 8.8515, 9.3929, 9.9933, 10.6768, 11.4228] +24-11-19 20:35:27 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:35:27 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:27 | D | sum error = [ 12.2095, 13.0857, 14.0368, 15.0242, 16.1103] +24-11-19 20:35:27 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:35:27 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:27 | D | sum error = [ 17.2631, 18.4870, 19.7821, 21.1576, 22.6246] +24-11-19 20:35:27 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:35:27 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:27 | D | sum error = [ 24.1822, 25.8156, 27.5714, 29.3924, 31.3218] +24-11-19 20:35:27 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:35:27 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:27 | D | sum error = [ 33.3660, 35.5100, 37.7794, 40.1738, 42.6909] +24-11-19 20:35:27 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:35:27 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:27 | D | sum error = [ 45.3060, 48.0827, 50.9991, 54.0418, 57.2413] +24-11-19 20:35:27 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:35:27 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:27 | D | sum error = [ 60.5992, 64.1208, 67.7987, 71.6574, 75.7006] +24-11-19 20:35:27 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:35:27 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:27 | D | sum error = [ 79.9196, 84.3377, 88.9365, 93.7350, 98.7492] +24-11-19 20:35:27 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:35:27 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:27 | D | sum error = [ 103.9696, 109.4230, 115.0952, 121.0245, 127.1728] +24-11-19 20:35:27 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:35:27 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:27 | D | sum error = [ 133.5760, 140.2186, 147.1312, 154.2767, 161.7126] +24-11-19 20:35:27 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:35:27 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:27 | D | sum error = [ 169.4183, 177.4111, 185.6899, 194.2594, 203.1361] +24-11-19 20:35:27 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:35:27 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:27 | D | sum error = [ 212.2997, 221.7840, 231.5757, 241.6959, 252.1278] +24-11-19 20:35:27 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:35:27 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:27 | D | sum error = [ 262.9036, 274.0080, 285.4541, 297.2432, 309.3843] +24-11-19 20:35:27 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:35:27 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:27 | D | sum error = [ 321.8875, 334.7505, 347.9782, 361.5713, 375.5375] +24-11-19 20:35:27 | D | best error = [ 5.8554, 5.8554, 5.8554, 5.8554, 5.8554] +24-11-19 20:35:27 | D | + error = [5.8554] +24-11-19 20:35:27 | D | - Calibrating model.layers.20.mlp.gate_proj.weight +24-11-19 20:35:27 | D | + w: sint8 +24-11-19 20:35:27 | D | + x: None +24-11-19 20:35:27 | D | + y: None +24-11-19 20:35:27 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:27 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:35:27 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:35:27 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:35:27 | D | - range ratio = [ 1.0000] +24-11-19 20:35:27 | D | sum error = [ 9.0694] +24-11-19 20:35:27 | D | best error = [ 9.0694] +24-11-19 20:35:28 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:28 | D | sum error = [ 8.9872, 8.9783, 9.0108, 9.1158, 9.2856] +24-11-19 20:35:28 | D | best error = [ 8.4127, 8.1688, 8.0394, 7.9661, 7.9267] +24-11-19 20:35:28 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:28 | D | sum error = [ 9.5324, 9.8505, 10.2553, 10.7273, 11.3058] +24-11-19 20:35:28 | D | best error = [ 7.9083, 7.9006, 7.8975, 7.8964, 7.8961] +24-11-19 20:35:28 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:28 | D | sum error = [ 11.9361, 12.6699, 13.5208, 14.4278, 15.4424] +24-11-19 20:35:28 | D | best error = [ 7.8961, 7.8961, 7.8961, 7.8961, 7.8961] +24-11-19 20:35:28 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:28 | D | sum error = [ 16.5346, 17.7014, 19.0067, 20.3585, 21.8508] +24-11-19 20:35:28 | D | best error = [ 7.8961, 7.8961, 7.8961, 7.8961, 7.8961] +24-11-19 20:35:28 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:28 | D | sum error = [ 23.4203, 25.0949, 26.9035, 28.8103, 30.8712] +24-11-19 20:35:28 | D | best error = [ 7.8961, 7.8961, 7.8961, 7.8961, 7.8961] +24-11-19 20:35:28 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:28 | D | sum error = [ 33.0289, 35.3437, 37.7802, 40.3978, 43.1415] +24-11-19 20:35:28 | D | best error = [ 7.8961, 7.8961, 7.8961, 7.8961, 7.8961] +24-11-19 20:35:28 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:28 | D | sum error = [ 46.0813, 49.2015, 52.4724, 55.9555, 59.6395] +24-11-19 20:35:28 | D | best error = [ 7.8961, 7.8961, 7.8961, 7.8961, 7.8961] +24-11-19 20:35:28 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:28 | D | sum error = [ 63.5448, 67.6754, 72.0344, 76.6626, 81.5510] +24-11-19 20:35:28 | D | best error = [ 7.8961, 7.8961, 7.8961, 7.8961, 7.8961] +24-11-19 20:35:28 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:28 | D | sum error = [ 86.7034, 92.1716, 97.9534, 104.0567, 110.4900] +24-11-19 20:35:28 | D | best error = [ 7.8961, 7.8961, 7.8961, 7.8961, 7.8961] +24-11-19 20:35:28 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:28 | D | sum error = [ 117.2956, 124.4801, 132.0229, 139.9729, 148.3734] +24-11-19 20:35:28 | D | best error = [ 7.8961, 7.8961, 7.8961, 7.8961, 7.8961] +24-11-19 20:35:28 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:28 | D | sum error = [ 157.2036, 166.4978, 176.2496, 186.5429, 197.3474] +24-11-19 20:35:28 | D | best error = [ 7.8961, 7.8961, 7.8961, 7.8961, 7.8961] +24-11-19 20:35:28 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:28 | D | sum error = [ 208.6604, 220.5617, 233.0892, 246.1924, 259.9396] +24-11-19 20:35:28 | D | best error = [ 7.8961, 7.8961, 7.8961, 7.8961, 7.8961] +24-11-19 20:35:28 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:28 | D | sum error = [ 274.3428, 289.3719, 305.1321, 321.5885, 338.7880] +24-11-19 20:35:28 | D | best error = [ 7.8961, 7.8961, 7.8961, 7.8961, 7.8961] +24-11-19 20:35:28 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:28 | D | sum error = [ 356.7553, 375.4876, 395.0047, 415.3127, 436.4253] +24-11-19 20:35:28 | D | best error = [ 7.8961, 7.8961, 7.8961, 7.8961, 7.8961] +24-11-19 20:35:28 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:28 | D | sum error = [ 458.3686, 481.1718, 504.8453, 529.3789, 554.7946] +24-11-19 20:35:28 | D | best error = [ 7.8961, 7.8961, 7.8961, 7.8961, 7.8961] +24-11-19 20:35:28 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:28 | D | sum error = [ 581.0584, 608.2191, 636.2668, 665.2287, 695.0766] +24-11-19 20:35:28 | D | best error = [ 7.8961, 7.8961, 7.8961, 7.8961, 7.8961] +24-11-19 20:35:28 | D | + error = [7.8961] +24-11-19 20:35:29 | D | - Calibrating model.layers.20.mlp.down_proj.weight +24-11-19 20:35:29 | D | + w: sint8 +24-11-19 20:35:29 | D | + x: None +24-11-19 20:35:29 | D | + y: None +24-11-19 20:35:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:35:29 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:29 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:29 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:29 | D | - range ratio = [ 1.0000] +24-11-19 20:35:29 | D | sum error = [ 1.0445] +24-11-19 20:35:29 | D | best error = [ 1.0445] +24-11-19 20:35:30 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:30 | D | sum error = [ 1.0354, 1.0262, 1.0177, 1.0130, 1.0125] +24-11-19 20:35:30 | D | best error = [ 1.0019, 0.9806, 0.9655, 0.9548, 0.9461] +24-11-19 20:35:30 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:30 | D | sum error = [ 1.0128, 1.0173, 1.0231, 1.0325, 1.0463] +24-11-19 20:35:30 | D | best error = [ 0.9390, 0.9335, 0.9292, 0.9257, 0.9229] +24-11-19 20:35:30 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:30 | D | sum error = [ 1.0694, 1.0918, 1.1249, 1.1633, 1.2052] +24-11-19 20:35:30 | D | best error = [ 0.9213, 0.9201, 0.9193, 0.9188, 0.9184] +24-11-19 20:35:30 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:30 | D | sum error = [ 1.2558, 1.3140, 1.3810, 1.4551, 1.5369] +24-11-19 20:35:30 | D | best error = [ 0.9180, 0.9179, 0.9179, 0.9178, 0.9178] +24-11-19 20:35:30 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:30 | D | sum error = [ 1.6305, 1.7330, 1.8441, 1.9643, 2.0998] +24-11-19 20:35:30 | D | best error = [ 0.9178, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 20:35:30 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:30 | D | sum error = [ 2.2419, 2.3992, 2.5662, 2.7461, 2.9386] +24-11-19 20:35:30 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 20:35:30 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:30 | D | sum error = [ 3.1433, 3.3639, 3.6002, 3.8500, 4.1185] +24-11-19 20:35:30 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 20:35:30 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:30 | D | sum error = [ 4.4010, 4.7033, 5.0231, 5.3622, 5.7214] +24-11-19 20:35:30 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 20:35:30 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:30 | D | sum error = [ 6.1035, 6.5043, 6.9304, 7.3819, 7.8595] +24-11-19 20:35:30 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 20:35:30 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:30 | D | sum error = [ 8.3597, 8.8882, 9.4477, 10.0363, 10.6568] +24-11-19 20:35:30 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 20:35:30 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:30 | D | sum error = [ 11.3095, 11.9971, 12.7192, 13.4773, 14.2735] +24-11-19 20:35:30 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 20:35:30 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:30 | D | sum error = [ 15.1091, 15.9859, 16.9033, 17.8629, 18.8683] +24-11-19 20:35:30 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 20:35:30 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:30 | D | sum error = [ 19.9181, 21.0173, 22.1652, 23.3625, 24.6127] +24-11-19 20:35:30 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 20:35:30 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:30 | D | sum error = [ 25.9163, 27.2722, 28.6873, 30.1589, 31.6877] +24-11-19 20:35:30 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 20:35:30 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:30 | D | sum error = [ 33.2775, 34.9301, 36.6462, 38.4274, 40.2726] +24-11-19 20:35:30 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 20:35:30 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:30 | D | sum error = [ 42.1873, 44.1688, 46.2189, 48.3402, 50.5320] +24-11-19 20:35:30 | D | best error = [ 0.9177, 0.9177, 0.9177, 0.9177, 0.9177] +24-11-19 20:35:30 | D | + error = [0.9177] +24-11-19 20:35:30 | D | - Quantizing model.layers.20.self_attn.q_proj.weight +24-11-19 20:35:31 | D | - Quantizing model.layers.20.self_attn.k_proj.weight +24-11-19 20:35:32 | D | - Quantizing model.layers.20.self_attn.v_proj.weight +24-11-19 20:35:33 | D | - Quantizing model.layers.20.self_attn.o_proj.weight +24-11-19 20:35:34 | D | - Quantizing model.layers.20.mlp.up_proj.weight +24-11-19 20:35:35 | D | - Quantizing model.layers.20.mlp.gate_proj.weight +24-11-19 20:35:36 | D | - Quantizing model.layers.20.mlp.down_proj.weight +24-11-19 20:35:46 | D | - Quantizing layer model.layers.21 +24-11-19 20:35:46 | D | - Calibrating model.layers.21.self_attn.q_proj.weight +24-11-19 20:35:46 | D | + w: sint8 +24-11-19 20:35:46 | D | + x: None +24-11-19 20:35:46 | D | + y: None +24-11-19 20:35:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:35:46 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:46 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:46 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:46 | D | - range ratio = [ 1.0000] +24-11-19 20:35:46 | D | sum error = [ 4.4565] +24-11-19 20:35:46 | D | best error = [ 4.4565] +24-11-19 20:35:58 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:35:58 | D | sum error = [ 4.5007, 4.3662, 4.4520, 4.4962, 4.5829] +24-11-19 20:35:58 | D | best error = [ 4.4565, 4.3662, 4.3662, 4.3662, 4.3662] +24-11-19 20:35:58 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:35:58 | D | sum error = [ 4.6286, 4.7718, 5.1801, 5.2958, 5.5907] +24-11-19 20:35:58 | D | best error = [ 4.3662, 4.3662, 4.3662, 4.3662, 4.3662] +24-11-19 20:35:58 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:35:58 | D | sum error = [ 5.9361, 6.2324, 6.7243, 7.2207, 7.7926] +24-11-19 20:35:58 | D | best error = [ 4.3662, 4.3662, 4.3662, 4.3662, 4.3662] +24-11-19 20:35:58 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:35:58 | D | sum error = [ 8.3905, 9.1801, 9.8932, 10.5199, 11.7251] +24-11-19 20:35:58 | D | best error = [ 4.3662, 4.3662, 4.3662, 4.3662, 4.3662] +24-11-19 20:35:58 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:35:58 | D | sum error = [ 12.7328, 13.8944, 15.0709, 16.4218, 17.8169] +24-11-19 20:35:58 | D | best error = [ 4.3662, 4.3662, 4.3662, 4.3662, 4.3662] +24-11-19 20:35:58 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:35:58 | D | sum error = [ 19.3690, 21.0177, 22.6542, 24.3377, 26.3982] +24-11-19 20:35:58 | D | best error = [ 4.3662, 4.3662, 4.3662, 4.3662, 4.3662] +24-11-19 20:35:58 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:35:58 | D | sum error = [ 28.4621, 30.9864, 33.2013, 35.9260, 38.8464] +24-11-19 20:35:58 | D | best error = [ 4.3662, 4.3662, 4.3662, 4.3662, 4.3662] +24-11-19 20:35:58 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:35:58 | D | sum error = [ 41.9634, 45.4645, 49.0642, 53.2039, 57.4036] +24-11-19 20:35:58 | D | best error = [ 4.3662, 4.3662, 4.3662, 4.3662, 4.3662] +24-11-19 20:35:58 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:35:58 | D | sum error = [ 61.8583, 67.1709, 72.4618, 78.4422, 85.0046] +24-11-19 20:35:58 | D | best error = [ 4.3662, 4.3662, 4.3662, 4.3662, 4.3662] +24-11-19 20:35:58 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:35:58 | D | sum error = [ 91.9336, 99.6806, 107.8507, 116.9948, 126.7405] +24-11-19 20:35:58 | D | best error = [ 4.3662, 4.3662, 4.3662, 4.3662, 4.3662] +24-11-19 20:35:58 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:35:58 | D | sum error = [ 137.2412, 148.5879, 160.9745, 174.4356, 188.5058] +24-11-19 20:35:58 | D | best error = [ 4.3662, 4.3662, 4.3662, 4.3662, 4.3662] +24-11-19 20:35:58 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:35:58 | D | sum error = [ 204.4938, 221.5387, 239.7885, 259.8081, 281.4653] +24-11-19 20:35:58 | D | best error = [ 4.3662, 4.3662, 4.3662, 4.3662, 4.3662] +24-11-19 20:35:58 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:35:58 | D | sum error = [ 305.2089, 331.0927, 358.6858, 388.7565, 421.4229] +24-11-19 20:35:58 | D | best error = [ 4.3662, 4.3662, 4.3662, 4.3662, 4.3662] +24-11-19 20:35:58 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:35:58 | D | sum error = [ 456.6650, 494.9522, 536.5800, 581.8361, 630.5531] +24-11-19 20:35:58 | D | best error = [ 4.3662, 4.3662, 4.3662, 4.3662, 4.3662] +24-11-19 20:35:58 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:35:58 | D | sum error = [ 683.5744, 740.5116, 801.6833, 867.0067, 936.8188] +24-11-19 20:35:58 | D | best error = [ 4.3662, 4.3662, 4.3662, 4.3662, 4.3662] +24-11-19 20:35:58 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:35:58 | D | sum error = [ 1010.8708, 1088.7758, 1170.1875, 1253.2730, 1338.0731] +24-11-19 20:35:58 | D | best error = [ 4.3662, 4.3662, 4.3662, 4.3662, 4.3662] +24-11-19 20:35:58 | D | + error = [4.3662] +24-11-19 20:35:58 | D | - Calibrating model.layers.21.self_attn.k_proj.weight +24-11-19 20:35:58 | D | + w: sint8 +24-11-19 20:35:58 | D | + x: None +24-11-19 20:35:58 | D | + y: None +24-11-19 20:35:58 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:35:58 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:35:58 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:35:59 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:35:59 | D | - range ratio = [ 1.0000] +24-11-19 20:35:59 | D | sum error = [ 4.6074] +24-11-19 20:35:59 | D | best error = [ 4.6074] +24-11-19 20:36:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:12 | D | sum error = [ 4.4034, 4.2827, 4.3239, 4.5758, 4.7341] +24-11-19 20:36:12 | D | best error = [ 4.4034, 4.2827, 4.2827, 4.2827, 4.2827] +24-11-19 20:36:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:12 | D | sum error = [ 4.4346, 4.9269, 4.7536, 5.2223, 5.6571] +24-11-19 20:36:12 | D | best error = [ 4.2827, 4.2827, 4.2827, 4.2827, 4.2827] +24-11-19 20:36:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:12 | D | sum error = [ 7.1919, 6.2540, 6.4855, 6.7802, 7.1110] +24-11-19 20:36:12 | D | best error = [ 4.2827, 4.2827, 4.2827, 4.2827, 4.2827] +24-11-19 20:36:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:12 | D | sum error = [ 8.0199, 9.0703, 9.7801, 11.0878, 11.6967] +24-11-19 20:36:12 | D | best error = [ 4.2827, 4.2827, 4.2827, 4.2827, 4.2827] +24-11-19 20:36:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:12 | D | sum error = [ 12.9333, 13.8790, 15.3873, 16.4117, 17.4859] +24-11-19 20:36:12 | D | best error = [ 4.2827, 4.2827, 4.2827, 4.2827, 4.2827] +24-11-19 20:36:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:12 | D | sum error = [ 19.4282, 22.2895, 24.3536, 26.5873, 29.0835] +24-11-19 20:36:12 | D | best error = [ 4.2827, 4.2827, 4.2827, 4.2827, 4.2827] +24-11-19 20:36:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:12 | D | sum error = [ 32.5731, 35.4135, 37.4428, 41.1435, 44.4238] +24-11-19 20:36:12 | D | best error = [ 4.2827, 4.2827, 4.2827, 4.2827, 4.2827] +24-11-19 20:36:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:12 | D | sum error = [ 47.3968, 52.4234, 57.8074, 62.4127, 68.2827] +24-11-19 20:36:12 | D | best error = [ 4.2827, 4.2827, 4.2827, 4.2827, 4.2827] +24-11-19 20:36:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:12 | D | sum error = [ 73.8527, 80.1051, 86.6627, 93.4223, 100.8628] +24-11-19 20:36:12 | D | best error = [ 4.2827, 4.2827, 4.2827, 4.2827, 4.2827] +24-11-19 20:36:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:12 | D | sum error = [ 109.0456, 116.9270, 125.1558, 135.2801, 144.0165] +24-11-19 20:36:12 | D | best error = [ 4.2827, 4.2827, 4.2827, 4.2827, 4.2827] +24-11-19 20:36:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:12 | D | sum error = [ 153.6995, 165.1936, 177.6711, 190.3903, 205.0912] +24-11-19 20:36:12 | D | best error = [ 4.2827, 4.2827, 4.2827, 4.2827, 4.2827] +24-11-19 20:36:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:12 | D | sum error = [ 220.2512, 238.0133, 257.6424, 277.7660, 299.5010] +24-11-19 20:36:12 | D | best error = [ 4.2827, 4.2827, 4.2827, 4.2827, 4.2827] +24-11-19 20:36:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:12 | D | sum error = [ 324.3273, 350.1016, 377.9818, 408.4175, 441.4471] +24-11-19 20:36:12 | D | best error = [ 4.2827, 4.2827, 4.2827, 4.2827, 4.2827] +24-11-19 20:36:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:12 | D | sum error = [ 477.4555, 516.1853, 557.3692, 602.2236, 651.5578] +24-11-19 20:36:12 | D | best error = [ 4.2827, 4.2827, 4.2827, 4.2827, 4.2827] +24-11-19 20:36:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:12 | D | sum error = [ 703.6605, 761.0386, 822.4531, 889.1063, 958.6007] +24-11-19 20:36:12 | D | best error = [ 4.2827, 4.2827, 4.2827, 4.2827, 4.2827] +24-11-19 20:36:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:12 | D | sum error = [ 1031.6527, 1108.3789, 1188.6734, 1269.7487, 1352.8152] +24-11-19 20:36:12 | D | best error = [ 4.2827, 4.2827, 4.2827, 4.2827, 4.2827] +24-11-19 20:36:12 | D | + error = [4.2827] +24-11-19 20:36:12 | D | - Calibrating model.layers.21.self_attn.v_proj.weight +24-11-19 20:36:12 | D | + w: sint8 +24-11-19 20:36:12 | D | + x: None +24-11-19 20:36:12 | D | + y: None +24-11-19 20:36:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:12 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:36:12 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:36:12 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:36:12 | D | - range ratio = [ 1.0000] +24-11-19 20:36:12 | D | sum error = [ 1.7953] +24-11-19 20:36:12 | D | best error = [ 1.7953] +24-11-19 20:36:12 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:12 | D | sum error = [ 1.7842, 1.7698, 1.7838, 1.8133, 1.8350] +24-11-19 20:36:12 | D | best error = [ 1.6671, 1.6124, 1.5853, 1.5722, 1.5642] +24-11-19 20:36:12 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:12 | D | sum error = [ 1.8773, 1.9553, 2.0487, 2.1259, 2.2459] +24-11-19 20:36:12 | D | best error = [ 1.5594, 1.5576, 1.5571, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:12 | D | sum error = [ 2.3630, 2.5209, 2.7042, 2.8830, 3.0898] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:12 | D | sum error = [ 3.3171, 3.5498, 3.7950, 4.0694, 4.3749] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:12 | D | sum error = [ 4.6694, 4.9906, 5.3453, 5.7352, 6.1224] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:12 | D | sum error = [ 6.5548, 6.9930, 7.4678, 7.9594, 8.4736] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:12 | D | sum error = [ 9.0380, 9.6167, 10.2156, 10.8761, 11.5569] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:12 | D | sum error = [ 12.2717, 13.0219, 13.8282, 14.6551, 15.5375] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:12 | D | sum error = [ 16.4431, 17.4095, 18.4021, 19.4822, 20.5835] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:12 | D | sum error = [ 21.7567, 22.9693, 24.2455, 25.5767, 26.9629] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:12 | D | sum error = [ 28.4141, 29.9333, 31.5159, 33.1605, 34.8903] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:12 | D | sum error = [ 36.6780, 38.5565, 40.5078, 42.5254, 44.6412] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:12 | D | sum error = [ 46.8311, 49.1078, 51.4666, 53.9305, 56.4730] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:12 | D | sum error = [ 59.1210, 61.8583, 64.6889, 67.6319, 70.6686] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:12 | D | sum error = [ 73.8124, 77.0547, 80.4002, 83.8611, 87.4364] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:12 | D | sum error = [ 91.1147, 94.9228, 98.8395, 102.8744, 107.0253] +24-11-19 20:36:12 | D | best error = [ 1.5570, 1.5570, 1.5570, 1.5570, 1.5570] +24-11-19 20:36:12 | D | + error = [1.5570] +24-11-19 20:36:12 | D | - Calibrating model.layers.21.self_attn.o_proj.weight +24-11-19 20:36:12 | D | + w: sint8 +24-11-19 20:36:12 | D | + x: None +24-11-19 20:36:12 | D | + y: None +24-11-19 20:36:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:12 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:36:12 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:36:13 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:36:13 | D | - range ratio = [ 1.0000] +24-11-19 20:36:13 | D | sum error = [ 0.5899] +24-11-19 20:36:13 | D | best error = [ 0.5899] +24-11-19 20:36:13 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:13 | D | sum error = [ 0.5811, 0.5813, 0.5785, 0.5789, 0.5814] +24-11-19 20:36:13 | D | best error = [ 0.5376, 0.5165, 0.5026, 0.4939, 0.4874] +24-11-19 20:36:13 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:13 | D | sum error = [ 0.5868, 0.5925, 0.6038, 0.6165, 0.6325] +24-11-19 20:36:13 | D | best error = [ 0.4827, 0.4789, 0.4761, 0.4739, 0.4724] +24-11-19 20:36:13 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:13 | D | sum error = [ 0.6551, 0.6750, 0.7017, 0.7346, 0.7694] +24-11-19 20:36:13 | D | best error = [ 0.4712, 0.4703, 0.4696, 0.4690, 0.4686] +24-11-19 20:36:13 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:13 | D | sum error = [ 0.8086, 0.8539, 0.9034, 0.9549, 1.0131] +24-11-19 20:36:13 | D | best error = [ 0.4682, 0.4680, 0.4678, 0.4677, 0.4676] +24-11-19 20:36:13 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:13 | D | sum error = [ 1.0761, 1.1466, 1.2196, 1.2983, 1.3858] +24-11-19 20:36:13 | D | best error = [ 0.4675, 0.4674, 0.4673, 0.4672, 0.4672] +24-11-19 20:36:13 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:13 | D | sum error = [ 1.4737, 1.5695, 1.6723, 1.7827, 1.8995] +24-11-19 20:36:13 | D | best error = [ 0.4672, 0.4672, 0.4672, 0.4672, 0.4671] +24-11-19 20:36:13 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:13 | D | sum error = [ 2.0223, 2.1525, 2.2931, 2.4416, 2.5940] +24-11-19 20:36:13 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:36:13 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:13 | D | sum error = [ 2.7569, 2.9294, 3.1146, 3.3085, 3.5106] +24-11-19 20:36:13 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:36:13 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:13 | D | sum error = [ 3.7284, 3.9549, 4.1942, 4.4460, 4.7113] +24-11-19 20:36:13 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:36:13 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:13 | D | sum error = [ 4.9922, 5.2886, 5.5986, 5.9252, 6.2661] +24-11-19 20:36:13 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:36:13 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:13 | D | sum error = [ 6.6271, 7.0025, 7.4004, 7.8167, 8.2527] +24-11-19 20:36:13 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:36:13 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:13 | D | sum error = [ 8.7105, 9.1882, 9.6900, 10.2142, 10.7641] +24-11-19 20:36:13 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:36:13 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:13 | D | sum error = [ 11.3357, 11.9320, 12.5544, 13.2020, 13.8772] +24-11-19 20:36:13 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:36:13 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:13 | D | sum error = [ 14.5816, 15.3132, 16.0743, 16.8661, 17.6856] +24-11-19 20:36:13 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:36:13 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:13 | D | sum error = [ 18.5372, 19.4213, 20.3359, 21.2843, 22.2664] +24-11-19 20:36:13 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:36:13 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:13 | D | sum error = [ 23.2830, 24.3356, 25.4246, 26.5486, 27.7129] +24-11-19 20:36:13 | D | best error = [ 0.4671, 0.4671, 0.4671, 0.4671, 0.4671] +24-11-19 20:36:13 | D | + error = [0.4671] +24-11-19 20:36:13 | D | - Calibrating model.layers.21.mlp.up_proj.weight +24-11-19 20:36:13 | D | + w: sint8 +24-11-19 20:36:13 | D | + x: None +24-11-19 20:36:13 | D | + y: None +24-11-19 20:36:13 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:13 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:36:13 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:36:13 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:36:13 | D | - range ratio = [ 1.0000] +24-11-19 20:36:13 | D | sum error = [ 7.0070] +24-11-19 20:36:13 | D | best error = [ 7.0070] +24-11-19 20:36:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:15 | D | sum error = [ 6.9547, 6.9440, 6.9954, 7.0738, 7.1956] +24-11-19 20:36:15 | D | best error = [ 6.4868, 6.2843, 6.1807, 6.1225, 6.0910] +24-11-19 20:36:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:15 | D | sum error = [ 7.3758, 7.6330, 7.9267, 8.3273, 8.7638] +24-11-19 20:36:15 | D | best error = [ 6.0741, 6.0675, 6.0648, 6.0641, 6.0639] +24-11-19 20:36:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:15 | D | sum error = [ 9.2650, 9.8230, 10.4799, 11.1772, 11.9633] +24-11-19 20:36:15 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:36:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:15 | D | sum error = [ 12.7783, 13.6960, 14.6624, 15.7112, 16.8587] +24-11-19 20:36:15 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:36:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:15 | D | sum error = [ 18.0487, 19.3102, 20.6825, 22.1232, 23.6501] +24-11-19 20:36:15 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:36:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:15 | D | sum error = [ 25.2579, 26.9904, 28.7860, 30.7265, 32.7192] +24-11-19 20:36:15 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:36:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:15 | D | sum error = [ 34.8506, 37.1045, 39.4741, 41.9731, 44.5935] +24-11-19 20:36:15 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:36:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:15 | D | sum error = [ 47.3344, 50.2476, 53.2815, 56.4822, 59.8300] +24-11-19 20:36:15 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:36:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:15 | D | sum error = [ 63.3377, 67.0038, 70.8605, 74.8811, 79.1135] +24-11-19 20:36:15 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:36:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:15 | D | sum error = [ 83.5331, 88.1415, 92.9643, 97.9968, 103.2614] +24-11-19 20:36:15 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:36:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:15 | D | sum error = [ 108.7432, 114.4467, 120.3995, 126.5976, 133.0643] +24-11-19 20:36:15 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:36:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:15 | D | sum error = [ 139.7753, 146.7380, 153.9862, 161.5003, 169.3070] +24-11-19 20:36:15 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:36:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:15 | D | sum error = [ 177.3781, 185.7588, 194.4456, 203.4418, 212.7457] +24-11-19 20:36:15 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:36:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:15 | D | sum error = [ 222.3838, 232.3286, 242.5883, 253.2080, 264.1288] +24-11-19 20:36:15 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:36:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:15 | D | sum error = [ 275.4149, 287.0468, 299.0473, 311.4134, 324.1338] +24-11-19 20:36:15 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:36:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:15 | D | sum error = [ 337.2201, 350.6951, 364.5658, 378.8215, 393.4876] +24-11-19 20:36:15 | D | best error = [ 6.0638, 6.0638, 6.0638, 6.0638, 6.0638] +24-11-19 20:36:15 | D | + error = [6.0638] +24-11-19 20:36:15 | D | - Calibrating model.layers.21.mlp.gate_proj.weight +24-11-19 20:36:15 | D | + w: sint8 +24-11-19 20:36:15 | D | + x: None +24-11-19 20:36:15 | D | + y: None +24-11-19 20:36:15 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:15 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:36:15 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:36:15 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:36:15 | D | - range ratio = [ 1.0000] +24-11-19 20:36:15 | D | sum error = [ 9.5250] +24-11-19 20:36:15 | D | best error = [ 9.5250] +24-11-19 20:36:16 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:16 | D | sum error = [ 9.4766, 9.4156, 9.4597, 9.5680, 9.7496] +24-11-19 20:36:16 | D | best error = [ 8.8083, 8.5324, 8.3859, 8.3077, 8.2614] +24-11-19 20:36:16 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:16 | D | sum error = [ 10.0179, 10.3437, 10.7749, 11.2851, 11.8736] +24-11-19 20:36:16 | D | best error = [ 8.2402, 8.2300, 8.2264, 8.2253, 8.2250] +24-11-19 20:36:16 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:16 | D | sum error = [ 12.5654, 13.3103, 14.1925, 15.1482, 16.2136] +24-11-19 20:36:16 | D | best error = [ 8.2250, 8.2250, 8.2250, 8.2250, 8.2250] +24-11-19 20:36:16 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:16 | D | sum error = [ 17.3582, 18.6174, 19.9742, 21.4335, 22.9991] +24-11-19 20:36:16 | D | best error = [ 8.2250, 8.2250, 8.2250, 8.2250, 8.2250] +24-11-19 20:36:16 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:16 | D | sum error = [ 24.6501, 26.4254, 28.3498, 30.3495, 32.5220] +24-11-19 20:36:16 | D | best error = [ 8.2250, 8.2250, 8.2250, 8.2250, 8.2250] +24-11-19 20:36:16 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:16 | D | sum error = [ 34.8219, 37.2310, 39.8487, 42.5562, 45.4574] +24-11-19 20:36:16 | D | best error = [ 8.2250, 8.2250, 8.2250, 8.2250, 8.2250] +24-11-19 20:36:16 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:16 | D | sum error = [ 48.5476, 51.7946, 55.2518, 58.9102, 62.7665] +24-11-19 20:36:16 | D | best error = [ 8.2250, 8.2250, 8.2250, 8.2250, 8.2250] +24-11-19 20:36:16 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:16 | D | sum error = [ 66.8653, 71.1807, 75.7476, 80.5592, 85.6900] +24-11-19 20:36:16 | D | best error = [ 8.2250, 8.2250, 8.2250, 8.2250, 8.2250] +24-11-19 20:36:16 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:16 | D | sum error = [ 91.0889, 96.7910, 102.8375, 109.1874, 115.9331] +24-11-19 20:36:16 | D | best error = [ 8.2250, 8.2250, 8.2250, 8.2250, 8.2250] +24-11-19 20:36:16 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:16 | D | sum error = [ 123.0383, 130.5099, 138.4358, 146.7588, 155.5340] +24-11-19 20:36:16 | D | best error = [ 8.2250, 8.2250, 8.2250, 8.2250, 8.2250] +24-11-19 20:36:16 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:16 | D | sum error = [ 164.7495, 174.4878, 184.7424, 195.5126, 206.8522] +24-11-19 20:36:16 | D | best error = [ 8.2250, 8.2250, 8.2250, 8.2250, 8.2250] +24-11-19 20:36:16 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:16 | D | sum error = [ 218.7790, 231.2749, 244.3837, 258.0932, 272.5147] +24-11-19 20:36:16 | D | best error = [ 8.2250, 8.2250, 8.2250, 8.2250, 8.2250] +24-11-19 20:36:16 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:16 | D | sum error = [ 287.6072, 303.3948, 319.9120, 337.2243, 355.2660] +24-11-19 20:36:16 | D | best error = [ 8.2250, 8.2250, 8.2250, 8.2250, 8.2250] +24-11-19 20:36:16 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:16 | D | sum error = [ 374.1261, 393.7724, 414.2314, 435.5334, 457.7051] +24-11-19 20:36:16 | D | best error = [ 8.2250, 8.2250, 8.2250, 8.2250, 8.2250] +24-11-19 20:36:16 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:16 | D | sum error = [ 480.7470, 504.6508, 529.4860, 555.1771, 581.7748] +24-11-19 20:36:16 | D | best error = [ 8.2250, 8.2250, 8.2250, 8.2250, 8.2250] +24-11-19 20:36:16 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:16 | D | sum error = [ 609.3108, 637.7268, 667.0662, 697.3622, 728.5600] +24-11-19 20:36:16 | D | best error = [ 8.2250, 8.2250, 8.2250, 8.2250, 8.2250] +24-11-19 20:36:16 | D | + error = [8.2250] +24-11-19 20:36:16 | D | - Calibrating model.layers.21.mlp.down_proj.weight +24-11-19 20:36:16 | D | + w: sint8 +24-11-19 20:36:16 | D | + x: None +24-11-19 20:36:16 | D | + y: None +24-11-19 20:36:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:36:16 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:36:16 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:36:17 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:36:17 | D | - range ratio = [ 1.0000] +24-11-19 20:36:17 | D | sum error = [ 1.1580] +24-11-19 20:36:17 | D | best error = [ 1.1580] +24-11-19 20:36:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:18 | D | sum error = [ 1.1479, 1.1366, 1.1266, 1.1219, 1.1182] +24-11-19 20:36:18 | D | best error = [ 1.1096, 1.0841, 1.0671, 1.0546, 1.0443] +24-11-19 20:36:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:18 | D | sum error = [ 1.1174, 1.1200, 1.1255, 1.1351, 1.1493] +24-11-19 20:36:18 | D | best error = [ 1.0363, 1.0299, 1.0245, 1.0207, 1.0178] +24-11-19 20:36:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:18 | D | sum error = [ 1.1706, 1.1956, 1.2250, 1.2643, 1.3086] +24-11-19 20:36:18 | D | best error = [ 1.0155, 1.0139, 1.0129, 1.0120, 1.0115] +24-11-19 20:36:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:18 | D | sum error = [ 1.3597, 1.4241, 1.4942, 1.5699, 1.6587] +24-11-19 20:36:18 | D | best error = [ 1.0111, 1.0108, 1.0106, 1.0104, 1.0103] +24-11-19 20:36:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:18 | D | sum error = [ 1.7568, 1.8645, 1.9855, 2.1140, 2.2552] +24-11-19 20:36:18 | D | best error = [ 1.0103, 1.0103, 1.0103, 1.0103, 1.0102] +24-11-19 20:36:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:18 | D | sum error = [ 2.4067, 2.5747, 2.7529, 2.9443, 3.1520] +24-11-19 20:36:18 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 20:36:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:18 | D | sum error = [ 3.3720, 3.6112, 3.8626, 4.1340, 4.4209] +24-11-19 20:36:18 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 20:36:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:18 | D | sum error = [ 4.7282, 5.0534, 5.4002, 5.7671, 6.1559] +24-11-19 20:36:18 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 20:36:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:18 | D | sum error = [ 6.5658, 7.0031, 7.4656, 7.9552, 8.4707] +24-11-19 20:36:18 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 20:36:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:18 | D | sum error = [ 9.0156, 9.5951, 10.2042, 10.8465, 11.5220] +24-11-19 20:36:18 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 20:36:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:18 | D | sum error = [ 12.2360, 12.9859, 13.7749, 14.6050, 15.4709] +24-11-19 20:36:18 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 20:36:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:18 | D | sum error = [ 16.3865, 17.3463, 18.3495, 19.4046, 20.5055] +24-11-19 20:36:18 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 20:36:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:18 | D | sum error = [ 21.6604, 22.8681, 24.1315, 25.4534, 26.8326] +24-11-19 20:36:18 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 20:36:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:18 | D | sum error = [ 28.2722, 29.7759, 31.3423, 32.9778, 34.6773] +24-11-19 20:36:18 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 20:36:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:18 | D | sum error = [ 36.4501, 38.2931, 40.2101, 42.1983, 44.2611] +24-11-19 20:36:18 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 20:36:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:18 | D | sum error = [ 46.4015, 48.6204, 50.9209, 53.3025, 55.7675] +24-11-19 20:36:18 | D | best error = [ 1.0102, 1.0102, 1.0102, 1.0102, 1.0102] +24-11-19 20:36:18 | D | + error = [1.0102] +24-11-19 20:36:18 | D | - Quantizing model.layers.21.self_attn.q_proj.weight +24-11-19 20:36:19 | D | - Quantizing model.layers.21.self_attn.k_proj.weight +24-11-19 20:36:20 | D | - Quantizing model.layers.21.self_attn.v_proj.weight +24-11-19 20:36:20 | D | - Quantizing model.layers.21.self_attn.o_proj.weight +24-11-19 20:36:21 | D | - Quantizing model.layers.21.mlp.up_proj.weight +24-11-19 20:36:22 | D | - Quantizing model.layers.21.mlp.gate_proj.weight +24-11-19 20:36:23 | D | - Quantizing model.layers.21.mlp.down_proj.weight +24-11-19 20:36:34 | D | - Quantizing layer model.layers.22 +24-11-19 20:36:34 | D | - Calibrating model.layers.22.self_attn.q_proj.weight +24-11-19 20:36:34 | D | + w: sint8 +24-11-19 20:36:34 | D | + x: None +24-11-19 20:36:34 | D | + y: None +24-11-19 20:36:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:36:34 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:36:34 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:36:35 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:36:35 | D | - range ratio = [ 1.0000] +24-11-19 20:36:35 | D | sum error = [ 4.6023] +24-11-19 20:36:35 | D | best error = [ 4.6023] +24-11-19 20:36:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:36:47 | D | sum error = [ 4.5615, 4.5510, 4.5606, 4.6662, 4.6629] +24-11-19 20:36:47 | D | best error = [ 4.5615, 4.5510, 4.5510, 4.5510, 4.5510] +24-11-19 20:36:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:36:47 | D | sum error = [ 4.7998, 4.9818, 5.2382, 5.5539, 5.8720] +24-11-19 20:36:47 | D | best error = [ 4.5510, 4.5510, 4.5510, 4.5510, 4.5510] +24-11-19 20:36:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:36:47 | D | sum error = [ 6.3059, 6.6661, 7.4708, 7.7907, 8.3101] +24-11-19 20:36:47 | D | best error = [ 4.5510, 4.5510, 4.5510, 4.5510, 4.5510] +24-11-19 20:36:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:36:47 | D | sum error = [ 9.0250, 9.8159, 10.6242, 11.5542, 12.4202] +24-11-19 20:36:47 | D | best error = [ 4.5510, 4.5510, 4.5510, 4.5510, 4.5510] +24-11-19 20:36:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:36:47 | D | sum error = [ 13.5630, 14.9699, 16.1772, 17.5502, 18.7790] +24-11-19 20:36:47 | D | best error = [ 4.5510, 4.5510, 4.5510, 4.5510, 4.5510] +24-11-19 20:36:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:36:47 | D | sum error = [ 20.5330, 22.3408, 24.2953, 26.1654, 28.5204] +24-11-19 20:36:47 | D | best error = [ 4.5510, 4.5510, 4.5510, 4.5510, 4.5510] +24-11-19 20:36:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:36:47 | D | sum error = [ 30.9763, 33.5979, 36.5580, 39.4124, 43.0342] +24-11-19 20:36:47 | D | best error = [ 4.5510, 4.5510, 4.5510, 4.5510, 4.5510] +24-11-19 20:36:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:36:47 | D | sum error = [ 46.3088, 50.3809, 54.5635, 59.2342, 64.1913] +24-11-19 20:36:47 | D | best error = [ 4.5510, 4.5510, 4.5510, 4.5510, 4.5510] +24-11-19 20:36:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:36:47 | D | sum error = [ 69.6428, 75.3475, 81.5995, 88.5856, 96.0322] +24-11-19 20:36:47 | D | best error = [ 4.5510, 4.5510, 4.5510, 4.5510, 4.5510] +24-11-19 20:36:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:36:47 | D | sum error = [ 104.2682, 113.1255, 122.9861, 133.7965, 145.2012] +24-11-19 20:36:47 | D | best error = [ 4.5510, 4.5510, 4.5510, 4.5510, 4.5510] +24-11-19 20:36:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:36:47 | D | sum error = [ 157.3224, 171.1546, 185.7809, 201.9194, 219.2206] +24-11-19 20:36:47 | D | best error = [ 4.5510, 4.5510, 4.5510, 4.5510, 4.5510] +24-11-19 20:36:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:36:47 | D | sum error = [ 238.6451, 260.0222, 282.8848, 308.2827, 335.7564] +24-11-19 20:36:47 | D | best error = [ 4.5510, 4.5510, 4.5510, 4.5510, 4.5510] +24-11-19 20:36:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:36:47 | D | sum error = [ 366.4035, 400.2001, 437.5451, 479.1223, 525.4900] +24-11-19 20:36:47 | D | best error = [ 4.5510, 4.5510, 4.5510, 4.5510, 4.5510] +24-11-19 20:36:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:36:47 | D | sum error = [ 576.2736, 634.9186, 698.2188, 767.4163, 844.3600] +24-11-19 20:36:47 | D | best error = [ 4.5510, 4.5510, 4.5510, 4.5510, 4.5510] +24-11-19 20:36:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:36:47 | D | sum error = [ 929.2274, 1022.9180, 1123.9562, 1231.5340, 1348.2177] +24-11-19 20:36:47 | D | best error = [ 4.5510, 4.5510, 4.5510, 4.5510, 4.5510] +24-11-19 20:36:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:36:47 | D | sum error = [ 1469.9488, 1601.9240, 1735.0626, 1871.9550, 2011.3836] +24-11-19 20:36:47 | D | best error = [ 4.5510, 4.5510, 4.5510, 4.5510, 4.5510] +24-11-19 20:36:47 | D | + error = [4.5510] +24-11-19 20:36:47 | D | - Calibrating model.layers.22.self_attn.k_proj.weight +24-11-19 20:36:47 | D | + w: sint8 +24-11-19 20:36:47 | D | + x: None +24-11-19 20:36:47 | D | + y: None +24-11-19 20:36:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:36:47 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:36:47 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:36:47 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:36:47 | D | - range ratio = [ 1.0000] +24-11-19 20:36:47 | D | sum error = [ 4.3224] +24-11-19 20:36:47 | D | best error = [ 4.3224] +24-11-19 20:37:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:01 | D | sum error = [ 3.9870, 4.0201, 4.1657, 4.6697, 5.1546] +24-11-19 20:37:01 | D | best error = [ 3.9870, 3.9870, 3.9870, 3.9870, 3.9870] +24-11-19 20:37:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:01 | D | sum error = [ 4.6640, 4.6586, 5.9099, 5.6617, 6.4945] +24-11-19 20:37:01 | D | best error = [ 3.9870, 3.9870, 3.9870, 3.9870, 3.9870] +24-11-19 20:37:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:01 | D | sum error = [ 7.1772, 7.9921, 7.9281, 9.5669, 9.3205] +24-11-19 20:37:01 | D | best error = [ 3.9870, 3.9870, 3.9870, 3.9870, 3.9870] +24-11-19 20:37:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:01 | D | sum error = [ 11.0303, 12.2423, 12.9020, 16.6975, 16.7796] +24-11-19 20:37:01 | D | best error = [ 3.9870, 3.9870, 3.9870, 3.9870, 3.9870] +24-11-19 20:37:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:01 | D | sum error = [ 19.5280, 20.0967, 21.6195, 23.9715, 26.0600] +24-11-19 20:37:01 | D | best error = [ 3.9870, 3.9870, 3.9870, 3.9870, 3.9870] +24-11-19 20:37:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:01 | D | sum error = [ 27.7936, 29.6668, 32.0816, 34.6813, 36.7389] +24-11-19 20:37:01 | D | best error = [ 3.9870, 3.9870, 3.9870, 3.9870, 3.9870] +24-11-19 20:37:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:01 | D | sum error = [ 40.2930, 44.0781, 46.9214, 49.9636, 54.7369] +24-11-19 20:37:01 | D | best error = [ 3.9870, 3.9870, 3.9870, 3.9870, 3.9870] +24-11-19 20:37:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:01 | D | sum error = [ 59.6233, 64.0118, 69.2345, 75.0297, 80.6760] +24-11-19 20:37:01 | D | best error = [ 3.9870, 3.9870, 3.9870, 3.9870, 3.9870] +24-11-19 20:37:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:01 | D | sum error = [ 86.8342, 93.9110, 101.4412, 109.0699, 117.2115] +24-11-19 20:37:01 | D | best error = [ 3.9870, 3.9870, 3.9870, 3.9870, 3.9870] +24-11-19 20:37:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:01 | D | sum error = [ 126.6663, 136.9390, 147.1864, 158.6699, 171.5141] +24-11-19 20:37:01 | D | best error = [ 3.9870, 3.9870, 3.9870, 3.9870, 3.9870] +24-11-19 20:37:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:01 | D | sum error = [ 184.6417, 200.1020, 215.7055, 233.0062, 253.0654] +24-11-19 20:37:01 | D | best error = [ 3.9870, 3.9870, 3.9870, 3.9870, 3.9870] +24-11-19 20:37:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:01 | D | sum error = [ 273.2672, 295.9145, 323.2861, 351.7717, 384.9657] +24-11-19 20:37:01 | D | best error = [ 3.9870, 3.9870, 3.9870, 3.9870, 3.9870] +24-11-19 20:37:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:01 | D | sum error = [ 421.6677, 462.4745, 505.4191, 553.3260, 606.1500] +24-11-19 20:37:01 | D | best error = [ 3.9870, 3.9870, 3.9870, 3.9870, 3.9870] +24-11-19 20:37:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:01 | D | sum error = [ 664.3614, 726.5025, 796.2673, 876.2971, 959.0394] +24-11-19 20:37:01 | D | best error = [ 3.9870, 3.9870, 3.9870, 3.9870, 3.9870] +24-11-19 20:37:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:01 | D | sum error = [ 1053.5979, 1158.1827, 1268.1022, 1389.8891, 1515.0779] +24-11-19 20:37:01 | D | best error = [ 3.9870, 3.9870, 3.9870, 3.9870, 3.9870] +24-11-19 20:37:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:01 | D | sum error = [ 1645.9594, 1782.8427, 1920.0286, 2056.3087, 2188.9719] +24-11-19 20:37:01 | D | best error = [ 3.9870, 3.9870, 3.9870, 3.9870, 3.9870] +24-11-19 20:37:01 | D | + error = [3.9870] +24-11-19 20:37:01 | D | - Calibrating model.layers.22.self_attn.v_proj.weight +24-11-19 20:37:01 | D | + w: sint8 +24-11-19 20:37:01 | D | + x: None +24-11-19 20:37:01 | D | + y: None +24-11-19 20:37:01 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:01 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:37:01 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:37:01 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:37:01 | D | - range ratio = [ 1.0000] +24-11-19 20:37:01 | D | sum error = [ 1.9818] +24-11-19 20:37:01 | D | best error = [ 1.9818] +24-11-19 20:37:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:01 | D | sum error = [ 1.9626, 1.9531, 1.9640, 2.0063, 2.0230] +24-11-19 20:37:01 | D | best error = [ 1.8301, 1.7728, 1.7420, 1.7255, 1.7149] +24-11-19 20:37:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:01 | D | sum error = [ 2.0775, 2.1477, 2.2106, 2.3220, 2.4456] +24-11-19 20:37:01 | D | best error = [ 1.7118, 1.7099, 1.7094, 1.7092, 1.7092] +24-11-19 20:37:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:01 | D | sum error = [ 2.5804, 2.7699, 2.9191, 3.1389, 3.3629] +24-11-19 20:37:01 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:01 | D | sum error = [ 3.6045, 3.8514, 4.1132, 4.4080, 4.7145] +24-11-19 20:37:01 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:01 | D | sum error = [ 5.0482, 5.4194, 5.8134, 6.1997, 6.6478] +24-11-19 20:37:01 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:01 | D | sum error = [ 7.0997, 7.5797, 8.1034, 8.6460, 9.2121] +24-11-19 20:37:01 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:01 | D | sum error = [ 9.8084, 10.4523, 11.1151, 11.8063, 12.5571] +24-11-19 20:37:01 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:01 | D | sum error = [ 13.3256, 14.1325, 14.9953, 15.8896, 16.8351] +24-11-19 20:37:01 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:01 | D | sum error = [ 17.8261, 18.8586, 19.9603, 21.1009, 22.3025] +24-11-19 20:37:01 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:01 | D | sum error = [ 23.5549, 24.8745, 26.2564, 27.6745, 29.1490] +24-11-19 20:37:01 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:01 | D | sum error = [ 30.7128, 32.3297, 33.9995, 35.7502, 37.5704] +24-11-19 20:37:01 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:01 | D | sum error = [ 39.4629, 41.4359, 43.4864, 45.6307, 47.8660] +24-11-19 20:37:01 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:01 | D | sum error = [ 50.1935, 52.6120, 55.1131, 57.7107, 60.4098] +24-11-19 20:37:01 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:01 | D | sum error = [ 63.2122, 66.1031, 69.1033, 72.2087, 75.4143] +24-11-19 20:37:01 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:01 | D | sum error = [ 78.7077, 82.1052, 85.6131, 89.2248, 92.9546] +24-11-19 20:37:01 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:01 | D | sum error = [ 96.7856, 100.7278, 104.7830, 108.9560, 113.2418] +24-11-19 20:37:01 | D | best error = [ 1.7091, 1.7091, 1.7091, 1.7091, 1.7091] +24-11-19 20:37:01 | D | + error = [1.7091] +24-11-19 20:37:01 | D | - Calibrating model.layers.22.self_attn.o_proj.weight +24-11-19 20:37:01 | D | + w: sint8 +24-11-19 20:37:01 | D | + x: None +24-11-19 20:37:01 | D | + y: None +24-11-19 20:37:01 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:01 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:02 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:02 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:02 | D | - range ratio = [ 1.0000] +24-11-19 20:37:02 | D | sum error = [ 0.4521] +24-11-19 20:37:02 | D | best error = [ 0.4521] +24-11-19 20:37:02 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:02 | D | sum error = [ 0.4464, 0.4464, 0.4499, 0.4541, 0.4649] +24-11-19 20:37:02 | D | best error = [ 0.4190, 0.4053, 0.3976, 0.3928, 0.3900] +24-11-19 20:37:02 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:02 | D | sum error = [ 0.4754, 0.4901, 0.5116, 0.5336, 0.5614] +24-11-19 20:37:02 | D | best error = [ 0.3881, 0.3868, 0.3860, 0.3855, 0.3851] +24-11-19 20:37:02 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:02 | D | sum error = [ 0.5918, 0.6273, 0.6662, 0.7091, 0.7571] +24-11-19 20:37:02 | D | best error = [ 0.3849, 0.3848, 0.3847, 0.3846, 0.3845] +24-11-19 20:37:02 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:02 | D | sum error = [ 0.8046, 0.8604, 0.9180, 0.9811, 1.0458] +24-11-19 20:37:02 | D | best error = [ 0.3845, 0.3845, 0.3845, 0.3845, 0.3845] +24-11-19 20:37:02 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:02 | D | sum error = [ 1.1163, 1.1912, 1.2713, 1.3523, 1.4397] +24-11-19 20:37:02 | D | best error = [ 0.3845, 0.3845, 0.3845, 0.3845, 0.3845] +24-11-19 20:37:02 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:02 | D | sum error = [ 1.5324, 1.6323, 1.7360, 1.8423, 1.9598] +24-11-19 20:37:02 | D | best error = [ 0.3845, 0.3845, 0.3845, 0.3845, 0.3845] +24-11-19 20:37:02 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:02 | D | sum error = [ 2.0799, 2.2070, 2.3398, 2.4790, 2.6274] +24-11-19 20:37:02 | D | best error = [ 0.3845, 0.3845, 0.3845, 0.3845, 0.3845] +24-11-19 20:37:02 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:02 | D | sum error = [ 2.7822, 2.9430, 3.1133, 3.2904, 3.4764] +24-11-19 20:37:02 | D | best error = [ 0.3845, 0.3845, 0.3845, 0.3845, 0.3845] +24-11-19 20:37:02 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:02 | D | sum error = [ 3.6726, 3.8760, 4.0895, 4.3117, 4.5454] +24-11-19 20:37:02 | D | best error = [ 0.3845, 0.3845, 0.3845, 0.3845, 0.3845] +24-11-19 20:37:02 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:02 | D | sum error = [ 4.7893, 5.0452, 5.3105, 5.5886, 5.8799] +24-11-19 20:37:02 | D | best error = [ 0.3845, 0.3845, 0.3845, 0.3845, 0.3845] +24-11-19 20:37:02 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:02 | D | sum error = [ 6.1826, 6.4975, 6.8249, 7.1668, 7.5226] +24-11-19 20:37:02 | D | best error = [ 0.3845, 0.3845, 0.3845, 0.3845, 0.3845] +24-11-19 20:37:02 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:02 | D | sum error = [ 7.8936, 8.2775, 8.6780, 9.0931, 9.5247] +24-11-19 20:37:02 | D | best error = [ 0.3845, 0.3845, 0.3845, 0.3845, 0.3845] +24-11-19 20:37:02 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:02 | D | sum error = [ 9.9726, 10.4364, 10.9177, 11.4152, 11.9316] +24-11-19 20:37:02 | D | best error = [ 0.3845, 0.3845, 0.3845, 0.3845, 0.3845] +24-11-19 20:37:02 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:02 | D | sum error = [ 12.4660, 13.0186, 13.5899, 14.1815, 14.7918] +24-11-19 20:37:02 | D | best error = [ 0.3845, 0.3845, 0.3845, 0.3845, 0.3845] +24-11-19 20:37:02 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:02 | D | sum error = [ 15.4220, 16.0729, 16.7438, 17.4364, 18.1504] +24-11-19 20:37:02 | D | best error = [ 0.3845, 0.3845, 0.3845, 0.3845, 0.3845] +24-11-19 20:37:02 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:02 | D | sum error = [ 18.8858, 19.6442, 20.4232, 21.2244, 22.0492] +24-11-19 20:37:02 | D | best error = [ 0.3845, 0.3845, 0.3845, 0.3845, 0.3845] +24-11-19 20:37:02 | D | + error = [0.3845] +24-11-19 20:37:02 | D | - Calibrating model.layers.22.mlp.up_proj.weight +24-11-19 20:37:02 | D | + w: sint8 +24-11-19 20:37:02 | D | + x: None +24-11-19 20:37:02 | D | + y: None +24-11-19 20:37:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:02 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:02 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:02 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:02 | D | - range ratio = [ 1.0000] +24-11-19 20:37:02 | D | sum error = [ 7.2487] +24-11-19 20:37:02 | D | best error = [ 7.2487] +24-11-19 20:37:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:04 | D | sum error = [ 7.2060, 7.1657, 7.2085, 7.2906, 7.4430] +24-11-19 20:37:04 | D | best error = [ 6.6942, 6.4775, 6.3678, 6.3077, 6.2739] +24-11-19 20:37:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:04 | D | sum error = [ 7.6011, 7.8749, 8.1862, 8.5719, 9.0194] +24-11-19 20:37:04 | D | best error = [ 6.2561, 6.2488, 6.2459, 6.2451, 6.2448] +24-11-19 20:37:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:04 | D | sum error = [ 9.5496, 10.1527, 10.8179, 11.5274, 12.3284] +24-11-19 20:37:04 | D | best error = [ 6.2448, 6.2448, 6.2448, 6.2448, 6.2448] +24-11-19 20:37:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:04 | D | sum error = [ 13.2067, 14.1499, 15.1714, 16.2531, 17.4112] +24-11-19 20:37:04 | D | best error = [ 6.2448, 6.2448, 6.2448, 6.2448, 6.2448] +24-11-19 20:37:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:04 | D | sum error = [ 18.6463, 19.9752, 21.3904, 22.8679, 24.4253] +24-11-19 20:37:04 | D | best error = [ 6.2448, 6.2448, 6.2448, 6.2448, 6.2448] +24-11-19 20:37:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:04 | D | sum error = [ 26.1040, 27.8943, 29.7411, 31.7125, 33.7920] +24-11-19 20:37:04 | D | best error = [ 6.2448, 6.2448, 6.2448, 6.2448, 6.2448] +24-11-19 20:37:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:04 | D | sum error = [ 35.9944, 38.2950, 40.7242, 43.2771, 45.9723] +24-11-19 20:37:04 | D | best error = [ 6.2448, 6.2448, 6.2448, 6.2448, 6.2448] +24-11-19 20:37:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:04 | D | sum error = [ 48.7991, 51.7918, 54.9269, 58.1934, 61.6215] +24-11-19 20:37:04 | D | best error = [ 6.2448, 6.2448, 6.2448, 6.2448, 6.2448] +24-11-19 20:37:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:04 | D | sum error = [ 65.2326, 69.0077, 72.9696, 77.1037, 81.4246] +24-11-19 20:37:04 | D | best error = [ 6.2448, 6.2448, 6.2448, 6.2448, 6.2448] +24-11-19 20:37:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:04 | D | sum error = [ 85.9537, 90.6649, 95.5957, 100.7368, 106.1136] +24-11-19 20:37:04 | D | best error = [ 6.2448, 6.2448, 6.2448, 6.2448, 6.2448] +24-11-19 20:37:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:04 | D | sum error = [ 111.6977, 117.5247, 123.5704, 129.8747, 136.4225] +24-11-19 20:37:04 | D | best error = [ 6.2448, 6.2448, 6.2448, 6.2448, 6.2448] +24-11-19 20:37:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:04 | D | sum error = [ 143.2229, 150.3077, 157.6564, 165.2790, 173.1820] +24-11-19 20:37:04 | D | best error = [ 6.2448, 6.2448, 6.2448, 6.2448, 6.2448] +24-11-19 20:37:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:04 | D | sum error = [ 181.3665, 189.8633, 198.6472, 207.7276, 217.1314] +24-11-19 20:37:04 | D | best error = [ 6.2448, 6.2448, 6.2448, 6.2448, 6.2448] +24-11-19 20:37:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:04 | D | sum error = [ 226.8363, 236.8698, 247.2148, 257.9135, 268.9041] +24-11-19 20:37:04 | D | best error = [ 6.2448, 6.2448, 6.2448, 6.2448, 6.2448] +24-11-19 20:37:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:04 | D | sum error = [ 280.2537, 291.9383, 303.9832, 316.3816, 329.1258] +24-11-19 20:37:04 | D | best error = [ 6.2448, 6.2448, 6.2448, 6.2448, 6.2448] +24-11-19 20:37:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:04 | D | sum error = [ 342.2302, 355.7008, 369.5585, 383.7902, 398.4022] +24-11-19 20:37:04 | D | best error = [ 6.2448, 6.2448, 6.2448, 6.2448, 6.2448] +24-11-19 20:37:04 | D | + error = [6.2448] +24-11-19 20:37:04 | D | - Calibrating model.layers.22.mlp.gate_proj.weight +24-11-19 20:37:04 | D | + w: sint8 +24-11-19 20:37:04 | D | + x: None +24-11-19 20:37:04 | D | + y: None +24-11-19 20:37:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:04 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:04 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:04 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:04 | D | - range ratio = [ 1.0000] +24-11-19 20:37:04 | D | sum error = [ 9.7714] +24-11-19 20:37:04 | D | best error = [ 9.7714] +24-11-19 20:37:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:05 | D | sum error = [ 9.7383, 9.6908, 9.7718, 9.8513, 10.0470] +24-11-19 20:37:05 | D | best error = [ 9.0478, 8.7671, 8.6199, 8.5348, 8.4878] +24-11-19 20:37:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:05 | D | sum error = [ 10.2750, 10.6287, 11.0622, 11.6108, 12.2279] +24-11-19 20:37:05 | D | best error = [ 8.4645, 8.4547, 8.4509, 8.4498, 8.4496] +24-11-19 20:37:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:05 | D | sum error = [ 12.9503, 13.7049, 14.6157, 15.6298, 16.7240] +24-11-19 20:37:05 | D | best error = [ 8.4496, 8.4496, 8.4496, 8.4496, 8.4496] +24-11-19 20:37:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:05 | D | sum error = [ 17.9080, 19.1768, 20.5847, 22.0672, 23.6583] +24-11-19 20:37:05 | D | best error = [ 8.4496, 8.4496, 8.4496, 8.4496, 8.4496] +24-11-19 20:37:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:05 | D | sum error = [ 25.3928, 27.2237, 29.1697, 31.2627, 33.4642] +24-11-19 20:37:05 | D | best error = [ 8.4496, 8.4496, 8.4496, 8.4496, 8.4496] +24-11-19 20:37:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:05 | D | sum error = [ 35.7989, 38.2847, 40.9293, 43.7495, 46.7190] +24-11-19 20:37:05 | D | best error = [ 8.4496, 8.4496, 8.4496, 8.4496, 8.4496] +24-11-19 20:37:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:05 | D | sum error = [ 49.8712, 53.2277, 56.7204, 60.4684, 64.4040] +24-11-19 20:37:05 | D | best error = [ 8.4496, 8.4496, 8.4496, 8.4496, 8.4496] +24-11-19 20:37:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:05 | D | sum error = [ 68.5299, 72.9325, 77.5689, 82.4699, 87.6509] +24-11-19 20:37:05 | D | best error = [ 8.4496, 8.4496, 8.4496, 8.4496, 8.4496] +24-11-19 20:37:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:05 | D | sum error = [ 93.1063, 98.8712, 104.9350, 111.3340, 118.0842] +24-11-19 20:37:05 | D | best error = [ 8.4496, 8.4496, 8.4496, 8.4496, 8.4496] +24-11-19 20:37:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:05 | D | sum error = [ 125.2012, 132.6835, 140.5666, 148.8574, 157.5875] +24-11-19 20:37:05 | D | best error = [ 8.4496, 8.4496, 8.4496, 8.4496, 8.4496] +24-11-19 20:37:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:05 | D | sum error = [ 166.7893, 176.4122, 186.5612, 197.2012, 208.3709] +24-11-19 20:37:05 | D | best error = [ 8.4496, 8.4496, 8.4496, 8.4496, 8.4496] +24-11-19 20:37:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:05 | D | sum error = [ 220.0822, 232.3678, 245.2383, 258.7137, 272.8287] +24-11-19 20:37:05 | D | best error = [ 8.4496, 8.4496, 8.4496, 8.4496, 8.4496] +24-11-19 20:37:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:05 | D | sum error = [ 287.5685, 302.9954, 319.1413, 335.9671, 353.5430] +24-11-19 20:37:05 | D | best error = [ 8.4496, 8.4496, 8.4496, 8.4496, 8.4496] +24-11-19 20:37:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:05 | D | sum error = [ 371.8736, 390.9674, 410.8587, 431.5297, 453.0262] +24-11-19 20:37:05 | D | best error = [ 8.4496, 8.4496, 8.4496, 8.4496, 8.4496] +24-11-19 20:37:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:05 | D | sum error = [ 475.3381, 498.5080, 522.5323, 547.3649, 573.1117] +24-11-19 20:37:05 | D | best error = [ 8.4496, 8.4496, 8.4496, 8.4496, 8.4496] +24-11-19 20:37:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:05 | D | sum error = [ 599.7098, 627.1832, 655.5128, 684.7222, 714.8356] +24-11-19 20:37:05 | D | best error = [ 8.4496, 8.4496, 8.4496, 8.4496, 8.4496] +24-11-19 20:37:05 | D | + error = [8.4496] +24-11-19 20:37:05 | D | - Calibrating model.layers.22.mlp.down_proj.weight +24-11-19 20:37:05 | D | + w: sint8 +24-11-19 20:37:05 | D | + x: None +24-11-19 20:37:05 | D | + y: None +24-11-19 20:37:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:05 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:05 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:05 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:05 | D | - range ratio = [ 1.0000] +24-11-19 20:37:05 | D | sum error = [ 1.1781] +24-11-19 20:37:05 | D | best error = [ 1.1781] +24-11-19 20:37:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:07 | D | sum error = [ 1.1659, 1.1550, 1.1480, 1.1417, 1.1407] +24-11-19 20:37:07 | D | best error = [ 1.1238, 1.0967, 1.0792, 1.0661, 1.0556] +24-11-19 20:37:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:07 | D | sum error = [ 1.1382, 1.1428, 1.1506, 1.1579, 1.1757] +24-11-19 20:37:07 | D | best error = [ 1.0478, 1.0407, 1.0355, 1.0314, 1.0286] +24-11-19 20:37:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:07 | D | sum error = [ 1.1970, 1.2222, 1.2579, 1.2957, 1.3447] +24-11-19 20:37:07 | D | best error = [ 1.0264, 1.0245, 1.0234, 1.0225, 1.0218] +24-11-19 20:37:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:07 | D | sum error = [ 1.4012, 1.4650, 1.5420, 1.6232, 1.7123] +24-11-19 20:37:07 | D | best error = [ 1.0214, 1.0212, 1.0211, 1.0210, 1.0209] +24-11-19 20:37:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:07 | D | sum error = [ 1.8171, 1.9316, 2.0575, 2.1934, 2.3411] +24-11-19 20:37:07 | D | best error = [ 1.0209, 1.0208, 1.0208, 1.0208, 1.0208] +24-11-19 20:37:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:07 | D | sum error = [ 2.4999, 2.6762, 2.8612, 3.0611, 3.2786] +24-11-19 20:37:07 | D | best error = [ 1.0208, 1.0208, 1.0208, 1.0208, 1.0208] +24-11-19 20:37:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:07 | D | sum error = [ 3.5084, 3.7536, 4.0168, 4.2977, 4.5972] +24-11-19 20:37:07 | D | best error = [ 1.0208, 1.0208, 1.0208, 1.0208, 1.0208] +24-11-19 20:37:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:07 | D | sum error = [ 4.9144, 5.2536, 5.6149, 5.9945, 6.4011] +24-11-19 20:37:07 | D | best error = [ 1.0208, 1.0208, 1.0208, 1.0208, 1.0208] +24-11-19 20:37:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:07 | D | sum error = [ 6.8313, 7.2878, 7.7736, 8.2827, 8.8222] +24-11-19 20:37:07 | D | best error = [ 1.0208, 1.0208, 1.0208, 1.0208, 1.0208] +24-11-19 20:37:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:07 | D | sum error = [ 9.3918, 9.9942, 10.6286, 11.2976, 12.0008] +24-11-19 20:37:07 | D | best error = [ 1.0208, 1.0208, 1.0208, 1.0208, 1.0208] +24-11-19 20:37:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:07 | D | sum error = [ 12.7424, 13.5242, 14.3454, 15.2070, 16.1128] +24-11-19 20:37:07 | D | best error = [ 1.0208, 1.0208, 1.0208, 1.0208, 1.0208] +24-11-19 20:37:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:07 | D | sum error = [ 17.0631, 18.0606, 19.1069, 20.2028, 21.3520] +24-11-19 20:37:07 | D | best error = [ 1.0208, 1.0208, 1.0208, 1.0208, 1.0208] +24-11-19 20:37:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:07 | D | sum error = [ 22.5554, 23.8155, 25.1336, 26.5115, 27.9461] +24-11-19 20:37:07 | D | best error = [ 1.0208, 1.0208, 1.0208, 1.0208, 1.0208] +24-11-19 20:37:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:07 | D | sum error = [ 29.4453, 31.0072, 32.6354, 34.3337, 36.0969] +24-11-19 20:37:07 | D | best error = [ 1.0208, 1.0208, 1.0208, 1.0208, 1.0208] +24-11-19 20:37:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:07 | D | sum error = [ 37.9329, 39.8390, 41.8192, 43.8724, 46.0013] +24-11-19 20:37:07 | D | best error = [ 1.0208, 1.0208, 1.0208, 1.0208, 1.0208] +24-11-19 20:37:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:07 | D | sum error = [ 48.2086, 50.4941, 52.8610, 55.3090, 57.8380] +24-11-19 20:37:07 | D | best error = [ 1.0208, 1.0208, 1.0208, 1.0208, 1.0208] +24-11-19 20:37:07 | D | + error = [1.0208] +24-11-19 20:37:07 | D | - Quantizing model.layers.22.self_attn.q_proj.weight +24-11-19 20:37:08 | D | - Quantizing model.layers.22.self_attn.k_proj.weight +24-11-19 20:37:09 | D | - Quantizing model.layers.22.self_attn.v_proj.weight +24-11-19 20:37:09 | D | - Quantizing model.layers.22.self_attn.o_proj.weight +24-11-19 20:37:10 | D | - Quantizing model.layers.22.mlp.up_proj.weight +24-11-19 20:37:11 | D | - Quantizing model.layers.22.mlp.gate_proj.weight +24-11-19 20:37:12 | D | - Quantizing model.layers.22.mlp.down_proj.weight +24-11-19 20:37:23 | D | - Quantizing layer model.layers.23 +24-11-19 20:37:23 | D | - Calibrating model.layers.23.self_attn.q_proj.weight +24-11-19 20:37:23 | D | + w: sint8 +24-11-19 20:37:23 | D | + x: None +24-11-19 20:37:23 | D | + y: None +24-11-19 20:37:23 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:37:23 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:23 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:23 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:23 | D | - range ratio = [ 1.0000] +24-11-19 20:37:23 | D | sum error = [ 4.1854] +24-11-19 20:37:23 | D | best error = [ 4.1854] +24-11-19 20:37:36 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:36 | D | sum error = [ 4.1444, 4.1721, 4.1211, 4.2364, 4.3624] +24-11-19 20:37:36 | D | best error = [ 4.1444, 4.1444, 4.1211, 4.1211, 4.1211] +24-11-19 20:37:36 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:36 | D | sum error = [ 4.3413, 4.6546, 4.8960, 5.1236, 5.7724] +24-11-19 20:37:36 | D | best error = [ 4.1211, 4.1211, 4.1211, 4.1211, 4.1211] +24-11-19 20:37:36 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:36 | D | sum error = [ 5.7824, 6.3720, 6.7253, 7.3117, 8.1031] +24-11-19 20:37:36 | D | best error = [ 4.1211, 4.1211, 4.1211, 4.1211, 4.1211] +24-11-19 20:37:36 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:36 | D | sum error = [ 9.1263, 9.7189, 10.6016, 11.4321, 12.5734] +24-11-19 20:37:36 | D | best error = [ 4.1211, 4.1211, 4.1211, 4.1211, 4.1211] +24-11-19 20:37:36 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:36 | D | sum error = [ 13.6179, 15.0282, 16.3366, 18.0492, 19.7311] +24-11-19 20:37:36 | D | best error = [ 4.1211, 4.1211, 4.1211, 4.1211, 4.1211] +24-11-19 20:37:36 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:36 | D | sum error = [ 21.4780, 23.7826, 25.8592, 28.1564, 30.8454] +24-11-19 20:37:36 | D | best error = [ 4.1211, 4.1211, 4.1211, 4.1211, 4.1211] +24-11-19 20:37:36 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:36 | D | sum error = [ 33.6269, 36.5236, 39.7580, 43.1115, 46.9982] +24-11-19 20:37:36 | D | best error = [ 4.1211, 4.1211, 4.1211, 4.1211, 4.1211] +24-11-19 20:37:36 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:36 | D | sum error = [ 51.2358, 55.8739, 60.5985, 65.4765, 71.4392] +24-11-19 20:37:36 | D | best error = [ 4.1211, 4.1211, 4.1211, 4.1211, 4.1211] +24-11-19 20:37:36 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:36 | D | sum error = [ 77.6516, 84.2220, 91.2730, 99.1093, 107.3944] +24-11-19 20:37:36 | D | best error = [ 4.1211, 4.1211, 4.1211, 4.1211, 4.1211] +24-11-19 20:37:36 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:36 | D | sum error = [ 116.3529, 125.4753, 136.2411, 147.5351, 159.8366] +24-11-19 20:37:36 | D | best error = [ 4.1211, 4.1211, 4.1211, 4.1211, 4.1211] +24-11-19 20:37:36 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:36 | D | sum error = [ 172.9869, 187.2636, 203.1969, 220.3311, 238.8988] +24-11-19 20:37:36 | D | best error = [ 4.1211, 4.1211, 4.1211, 4.1211, 4.1211] +24-11-19 20:37:36 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:36 | D | sum error = [ 259.3431, 281.8083, 306.1547, 333.1613, 362.0191] +24-11-19 20:37:36 | D | best error = [ 4.1211, 4.1211, 4.1211, 4.1211, 4.1211] +24-11-19 20:37:36 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:36 | D | sum error = [ 393.8345, 428.6754, 466.7141, 508.2489, 554.7959] +24-11-19 20:37:36 | D | best error = [ 4.1211, 4.1211, 4.1211, 4.1211, 4.1211] +24-11-19 20:37:36 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:36 | D | sum error = [ 604.9765, 660.2367, 721.1184, 786.7855, 858.9002] +24-11-19 20:37:36 | D | best error = [ 4.1211, 4.1211, 4.1211, 4.1211, 4.1211] +24-11-19 20:37:36 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:36 | D | sum error = [ 936.0887, 1020.5092, 1110.5667, 1207.2428, 1311.1261] +24-11-19 20:37:36 | D | best error = [ 4.1211, 4.1211, 4.1211, 4.1211, 4.1211] +24-11-19 20:37:36 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:36 | D | sum error = [ 1419.4093, 1535.2853, 1654.1669, 1776.5952, 1900.7212] +24-11-19 20:37:36 | D | best error = [ 4.1211, 4.1211, 4.1211, 4.1211, 4.1211] +24-11-19 20:37:36 | D | + error = [4.1211] +24-11-19 20:37:37 | D | - Calibrating model.layers.23.self_attn.k_proj.weight +24-11-19 20:37:37 | D | + w: sint8 +24-11-19 20:37:37 | D | + x: None +24-11-19 20:37:37 | D | + y: None +24-11-19 20:37:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:37:37 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:37 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:37 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:37 | D | - range ratio = [ 1.0000] +24-11-19 20:37:37 | D | sum error = [ 5.1233] +24-11-19 20:37:37 | D | best error = [ 5.1233] +24-11-19 20:37:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:51 | D | sum error = [ 5.0622, 4.2642, 4.6392, 5.2517, 4.7272] +24-11-19 20:37:51 | D | best error = [ 5.0622, 4.2642, 4.2642, 4.2642, 4.2642] +24-11-19 20:37:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:51 | D | sum error = [ 5.1680, 5.2073, 5.5426, 5.2454, 5.5310] +24-11-19 20:37:51 | D | best error = [ 4.2642, 4.2642, 4.2642, 4.2642, 4.2642] +24-11-19 20:37:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:51 | D | sum error = [ 6.8368, 6.7280, 7.2083, 7.7135, 8.9704] +24-11-19 20:37:51 | D | best error = [ 4.2642, 4.2642, 4.2642, 4.2642, 4.2642] +24-11-19 20:37:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:51 | D | sum error = [ 9.8927, 12.1357, 11.8058, 14.3079, 15.5965] +24-11-19 20:37:51 | D | best error = [ 4.2642, 4.2642, 4.2642, 4.2642, 4.2642] +24-11-19 20:37:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:51 | D | sum error = [ 16.6019, 18.5502, 21.1727, 22.4005, 25.9860] +24-11-19 20:37:51 | D | best error = [ 4.2642, 4.2642, 4.2642, 4.2642, 4.2642] +24-11-19 20:37:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:51 | D | sum error = [ 28.9302, 30.8951, 34.2787, 37.4614, 40.8478] +24-11-19 20:37:51 | D | best error = [ 4.2642, 4.2642, 4.2642, 4.2642, 4.2642] +24-11-19 20:37:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:51 | D | sum error = [ 45.0502, 49.9466, 53.9957, 60.5116, 64.8442] +24-11-19 20:37:51 | D | best error = [ 4.2642, 4.2642, 4.2642, 4.2642, 4.2642] +24-11-19 20:37:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:51 | D | sum error = [ 69.7217, 76.3820, 83.0391, 88.9504, 97.4227] +24-11-19 20:37:51 | D | best error = [ 4.2642, 4.2642, 4.2642, 4.2642, 4.2642] +24-11-19 20:37:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:51 | D | sum error = [ 106.3111, 115.4317, 124.3658, 134.1380, 144.8237] +24-11-19 20:37:51 | D | best error = [ 4.2642, 4.2642, 4.2642, 4.2642, 4.2642] +24-11-19 20:37:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:51 | D | sum error = [ 157.2337, 171.2912, 184.6520, 198.8489, 215.0795] +24-11-19 20:37:51 | D | best error = [ 4.2642, 4.2642, 4.2642, 4.2642, 4.2642] +24-11-19 20:37:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:51 | D | sum error = [ 233.0022, 251.8841, 271.8209, 294.3111, 318.5723] +24-11-19 20:37:51 | D | best error = [ 4.2642, 4.2642, 4.2642, 4.2642, 4.2642] +24-11-19 20:37:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:51 | D | sum error = [ 344.1662, 373.3199, 405.3515, 440.7008, 478.0547] +24-11-19 20:37:51 | D | best error = [ 4.2642, 4.2642, 4.2642, 4.2642, 4.2642] +24-11-19 20:37:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:51 | D | sum error = [ 517.4641, 560.4768, 608.3263, 656.8908, 712.4176] +24-11-19 20:37:51 | D | best error = [ 4.2642, 4.2642, 4.2642, 4.2642, 4.2642] +24-11-19 20:37:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:51 | D | sum error = [ 771.2388, 832.2940, 900.5876, 971.8891, 1048.3787] +24-11-19 20:37:51 | D | best error = [ 4.2642, 4.2642, 4.2642, 4.2642, 4.2642] +24-11-19 20:37:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:51 | D | sum error = [ 1127.6584, 1212.4564, 1303.6247, 1400.9874, 1504.3040] +24-11-19 20:37:51 | D | best error = [ 4.2642, 4.2642, 4.2642, 4.2642, 4.2642] +24-11-19 20:37:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:51 | D | sum error = [ 1610.7748, 1719.3850, 1830.0242, 1938.5178, 2046.9892] +24-11-19 20:37:51 | D | best error = [ 4.2642, 4.2642, 4.2642, 4.2642, 4.2642] +24-11-19 20:37:51 | D | + error = [4.2642] +24-11-19 20:37:51 | D | - Calibrating model.layers.23.self_attn.v_proj.weight +24-11-19 20:37:51 | D | + w: sint8 +24-11-19 20:37:51 | D | + x: None +24-11-19 20:37:51 | D | + y: None +24-11-19 20:37:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:51 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:51 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:51 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:51 | D | - range ratio = [ 1.0000] +24-11-19 20:37:51 | D | sum error = [ 2.1442] +24-11-19 20:37:51 | D | best error = [ 2.1442] +24-11-19 20:37:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:52 | D | sum error = [ 2.1200, 2.1334, 2.1272, 2.1463, 2.1822] +24-11-19 20:37:52 | D | best error = [ 1.9683, 1.9061, 1.8724, 1.8507, 1.8413] +24-11-19 20:37:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:52 | D | sum error = [ 2.2512, 2.3281, 2.4096, 2.5155, 2.6427] +24-11-19 20:37:52 | D | best error = [ 1.8357, 1.8338, 1.8327, 1.8323, 1.8323] +24-11-19 20:37:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:52 | D | sum error = [ 2.7853, 2.9567, 3.1363, 3.3528, 3.5789] +24-11-19 20:37:52 | D | best error = [ 1.8323, 1.8323, 1.8323, 1.8323, 1.8323] +24-11-19 20:37:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:52 | D | sum error = [ 3.8489, 4.1053, 4.4143, 4.7105, 5.0595] +24-11-19 20:37:52 | D | best error = [ 1.8323, 1.8323, 1.8323, 1.8323, 1.8323] +24-11-19 20:37:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:52 | D | sum error = [ 5.4082, 5.8047, 6.2299, 6.6462, 7.1109] +24-11-19 20:37:52 | D | best error = [ 1.8323, 1.8323, 1.8323, 1.8323, 1.8323] +24-11-19 20:37:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:52 | D | sum error = [ 7.6304, 8.1142, 8.6625, 9.2342, 9.8499] +24-11-19 20:37:52 | D | best error = [ 1.8323, 1.8323, 1.8323, 1.8323, 1.8323] +24-11-19 20:37:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:52 | D | sum error = [ 10.5145, 11.1745, 11.9044, 12.6724, 13.4501] +24-11-19 20:37:52 | D | best error = [ 1.8323, 1.8323, 1.8323, 1.8323, 1.8323] +24-11-19 20:37:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:52 | D | sum error = [ 14.3001, 15.1826, 16.1022, 17.0575, 18.0610] +24-11-19 20:37:52 | D | best error = [ 1.8323, 1.8323, 1.8323, 1.8323, 1.8323] +24-11-19 20:37:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:52 | D | sum error = [ 19.1024, 20.2014, 21.3499, 22.5535, 23.7956] +24-11-19 20:37:52 | D | best error = [ 1.8323, 1.8323, 1.8323, 1.8323, 1.8323] +24-11-19 20:37:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:52 | D | sum error = [ 25.1025, 26.4829, 27.9188, 29.4242, 30.9872] +24-11-19 20:37:52 | D | best error = [ 1.8323, 1.8323, 1.8323, 1.8323, 1.8323] +24-11-19 20:37:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:52 | D | sum error = [ 32.6383, 34.3607, 36.1730, 38.0488, 39.9958] +24-11-19 20:37:52 | D | best error = [ 1.8323, 1.8323, 1.8323, 1.8323, 1.8323] +24-11-19 20:37:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:52 | D | sum error = [ 42.0280, 44.1456, 46.3223, 48.6065, 50.9673] +24-11-19 20:37:52 | D | best error = [ 1.8323, 1.8323, 1.8323, 1.8323, 1.8323] +24-11-19 20:37:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:52 | D | sum error = [ 53.4325, 55.9866, 58.6317, 61.3629, 64.1995] +24-11-19 20:37:52 | D | best error = [ 1.8323, 1.8323, 1.8323, 1.8323, 1.8323] +24-11-19 20:37:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:52 | D | sum error = [ 67.1280, 70.1752, 73.3103, 76.5645, 79.9216] +24-11-19 20:37:52 | D | best error = [ 1.8323, 1.8323, 1.8323, 1.8323, 1.8323] +24-11-19 20:37:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:52 | D | sum error = [ 83.3834, 86.9508, 90.6446, 94.4458, 98.3573] +24-11-19 20:37:52 | D | best error = [ 1.8323, 1.8323, 1.8323, 1.8323, 1.8323] +24-11-19 20:37:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:52 | D | sum error = [ 102.3882, 106.5464, 110.8078, 115.1925, 119.6980] +24-11-19 20:37:52 | D | best error = [ 1.8323, 1.8323, 1.8323, 1.8323, 1.8323] +24-11-19 20:37:52 | D | + error = [1.8323] +24-11-19 20:37:52 | D | - Calibrating model.layers.23.self_attn.o_proj.weight +24-11-19 20:37:52 | D | + w: sint8 +24-11-19 20:37:52 | D | + x: None +24-11-19 20:37:52 | D | + y: None +24-11-19 20:37:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:52 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:52 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:52 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:52 | D | - range ratio = [ 1.0000] +24-11-19 20:37:52 | D | sum error = [ 0.4630] +24-11-19 20:37:52 | D | best error = [ 0.4630] +24-11-19 20:37:52 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:52 | D | sum error = [ 0.4577, 0.4580, 0.4613, 0.4668, 0.4745] +24-11-19 20:37:52 | D | best error = [ 0.4294, 0.4151, 0.4065, 0.4015, 0.3979] +24-11-19 20:37:52 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:52 | D | sum error = [ 0.4869, 0.5047, 0.5244, 0.5487, 0.5775] +24-11-19 20:37:52 | D | best error = [ 0.3955, 0.3937, 0.3927, 0.3920, 0.3913] +24-11-19 20:37:52 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:52 | D | sum error = [ 0.6113, 0.6479, 0.6875, 0.7347, 0.7831] +24-11-19 20:37:52 | D | best error = [ 0.3910, 0.3907, 0.3905, 0.3904, 0.3903] +24-11-19 20:37:52 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:52 | D | sum error = [ 0.8400, 0.8960, 0.9602, 1.0297, 1.1000] +24-11-19 20:37:52 | D | best error = [ 0.3902, 0.3902, 0.3902, 0.3902, 0.3902] +24-11-19 20:37:52 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:52 | D | sum error = [ 1.1755, 1.2563, 1.3416, 1.4340, 1.5322] +24-11-19 20:37:52 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:37:52 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:52 | D | sum error = [ 1.6327, 1.7419, 1.8567, 1.9771, 2.1046] +24-11-19 20:37:52 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:37:52 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:52 | D | sum error = [ 2.2383, 2.3808, 2.5321, 2.6874, 2.8520] +24-11-19 20:37:52 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:37:52 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:52 | D | sum error = [ 3.0288, 3.2141, 3.4078, 3.6095, 3.8229] +24-11-19 20:37:52 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:37:52 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:52 | D | sum error = [ 4.0478, 4.2828, 4.5284, 4.7881, 5.0567] +24-11-19 20:37:52 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:37:52 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:52 | D | sum error = [ 5.3416, 5.6397, 5.9490, 6.2733, 6.6120] +24-11-19 20:37:52 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:37:52 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:52 | D | sum error = [ 6.9649, 7.3352, 7.7193, 8.1213, 8.5400] +24-11-19 20:37:52 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:37:52 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:52 | D | sum error = [ 8.9755, 9.4296, 9.9020, 10.3943, 10.9079] +24-11-19 20:37:52 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:37:52 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:52 | D | sum error = [ 11.4399, 11.9924, 12.5659, 13.1624, 13.7818] +24-11-19 20:37:52 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:37:52 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:52 | D | sum error = [ 14.4207, 15.0852, 15.7729, 16.4837, 17.2180] +24-11-19 20:37:52 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:37:52 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:52 | D | sum error = [ 17.9792, 18.7662, 19.5790, 20.4161, 21.2805] +24-11-19 20:37:52 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:37:52 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:52 | D | sum error = [ 22.1709, 23.0891, 24.0339, 25.0053, 26.0042] +24-11-19 20:37:52 | D | best error = [ 0.3901, 0.3901, 0.3901, 0.3901, 0.3901] +24-11-19 20:37:52 | D | + error = [0.3901] +24-11-19 20:37:52 | D | - Calibrating model.layers.23.mlp.up_proj.weight +24-11-19 20:37:52 | D | + w: sint8 +24-11-19 20:37:52 | D | + x: None +24-11-19 20:37:52 | D | + y: None +24-11-19 20:37:52 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:52 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:52 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:53 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:53 | D | - range ratio = [ 1.0000] +24-11-19 20:37:53 | D | sum error = [ 7.5016] +24-11-19 20:37:53 | D | best error = [ 7.5016] +24-11-19 20:37:54 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:54 | D | sum error = [ 7.4408, 7.4284, 7.4715, 7.5484, 7.6790] +24-11-19 20:37:54 | D | best error = [ 6.8944, 6.6721, 6.5576, 6.4911, 6.4534] +24-11-19 20:37:54 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:54 | D | sum error = [ 7.8839, 8.1581, 8.4791, 8.8799, 9.3585] +24-11-19 20:37:54 | D | best error = [ 6.4358, 6.4263, 6.4235, 6.4224, 6.4222] +24-11-19 20:37:54 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:54 | D | sum error = [ 9.8993, 10.5035, 11.1561, 11.9540, 12.7494] +24-11-19 20:37:54 | D | best error = [ 6.4221, 6.4221, 6.4221, 6.4221, 6.4221] +24-11-19 20:37:54 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:54 | D | sum error = [ 13.6537, 14.6187, 15.6541, 16.7718, 17.9752] +24-11-19 20:37:54 | D | best error = [ 6.4221, 6.4221, 6.4221, 6.4221, 6.4221] +24-11-19 20:37:54 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:54 | D | sum error = [ 19.2512, 20.5928, 22.0538, 23.5714, 25.1772] +24-11-19 20:37:54 | D | best error = [ 6.4221, 6.4221, 6.4221, 6.4221, 6.4221] +24-11-19 20:37:54 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:54 | D | sum error = [ 26.9151, 28.7444, 30.6687, 32.7099, 34.8347] +24-11-19 20:37:54 | D | best error = [ 6.4221, 6.4221, 6.4221, 6.4221, 6.4221] +24-11-19 20:37:54 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:54 | D | sum error = [ 37.0914, 39.4733, 41.9691, 44.5970, 47.3696] +24-11-19 20:37:54 | D | best error = [ 6.4221, 6.4221, 6.4221, 6.4221, 6.4221] +24-11-19 20:37:54 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:54 | D | sum error = [ 50.2563, 53.3295, 56.5344, 59.8875, 63.4129] +24-11-19 20:37:54 | D | best error = [ 6.4221, 6.4221, 6.4221, 6.4221, 6.4221] +24-11-19 20:37:54 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:54 | D | sum error = [ 67.1016, 70.9650, 74.9990, 79.2423, 83.6620] +24-11-19 20:37:54 | D | best error = [ 6.4221, 6.4221, 6.4221, 6.4221, 6.4221] +24-11-19 20:37:54 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:54 | D | sum error = [ 88.2929, 93.1178, 98.1648, 103.4321, 108.9269] +24-11-19 20:37:54 | D | best error = [ 6.4221, 6.4221, 6.4221, 6.4221, 6.4221] +24-11-19 20:37:54 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:54 | D | sum error = [ 114.6354, 120.5871, 126.7974, 133.2447, 139.9305] +24-11-19 20:37:54 | D | best error = [ 6.4221, 6.4221, 6.4221, 6.4221, 6.4221] +24-11-19 20:37:54 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:54 | D | sum error = [ 146.9010, 154.1277, 161.6267, 169.3866, 177.4352] +24-11-19 20:37:54 | D | best error = [ 6.4221, 6.4221, 6.4221, 6.4221, 6.4221] +24-11-19 20:37:54 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:54 | D | sum error = [ 185.7696, 194.3981, 203.3240, 212.5539, 222.1004] +24-11-19 20:37:54 | D | best error = [ 6.4221, 6.4221, 6.4221, 6.4221, 6.4221] +24-11-19 20:37:54 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:54 | D | sum error = [ 231.9527, 242.1200, 252.6204, 263.4487, 274.5793] +24-11-19 20:37:54 | D | best error = [ 6.4221, 6.4221, 6.4221, 6.4221, 6.4221] +24-11-19 20:37:54 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:54 | D | sum error = [ 286.0779, 297.9314, 310.1353, 322.7100, 335.6419] +24-11-19 20:37:54 | D | best error = [ 6.4221, 6.4221, 6.4221, 6.4221, 6.4221] +24-11-19 20:37:54 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:54 | D | sum error = [ 348.9484, 362.6137, 376.6457, 391.0689, 405.8821] +24-11-19 20:37:54 | D | best error = [ 6.4221, 6.4221, 6.4221, 6.4221, 6.4221] +24-11-19 20:37:54 | D | + error = [6.4221] +24-11-19 20:37:54 | D | - Calibrating model.layers.23.mlp.gate_proj.weight +24-11-19 20:37:54 | D | + w: sint8 +24-11-19 20:37:54 | D | + x: None +24-11-19 20:37:54 | D | + y: None +24-11-19 20:37:54 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:54 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:54 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:54 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:54 | D | - range ratio = [ 1.0000] +24-11-19 20:37:54 | D | sum error = [ 10.1359] +24-11-19 20:37:54 | D | best error = [ 10.1359] +24-11-19 20:37:55 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:55 | D | sum error = [ 10.0175, 10.0140, 10.0575, 10.1762, 10.3484] +24-11-19 20:37:55 | D | best error = [ 9.3105, 9.0054, 8.8444, 8.7550, 8.7068] +24-11-19 20:37:55 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:55 | D | sum error = [ 10.6312, 10.9826, 11.4539, 11.9629, 12.6045] +24-11-19 20:37:55 | D | best error = [ 8.6800, 8.6685, 8.6649, 8.6632, 8.6628] +24-11-19 20:37:55 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:55 | D | sum error = [ 13.3531, 14.1759, 15.0622, 16.0633, 17.1722] +24-11-19 20:37:55 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 20:37:55 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:55 | D | sum error = [ 18.3973, 19.7124, 21.1372, 22.6843, 24.3215] +24-11-19 20:37:55 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 20:37:55 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:55 | D | sum error = [ 26.0661, 27.9451, 29.9500, 32.0417, 34.2662] +24-11-19 20:37:55 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 20:37:55 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:55 | D | sum error = [ 36.6506, 39.2007, 41.8652, 44.7285, 47.7657] +24-11-19 20:37:55 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 20:37:55 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:55 | D | sum error = [ 50.9077, 54.2652, 57.8240, 61.5876, 65.5563] +24-11-19 20:37:55 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 20:37:55 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:55 | D | sum error = [ 69.7882, 74.2011, 78.9043, 83.8731, 89.0857] +24-11-19 20:37:55 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 20:37:55 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:55 | D | sum error = [ 94.5964, 100.3851, 106.4969, 112.9246, 119.6945] +24-11-19 20:37:55 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 20:37:55 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:55 | D | sum error = [ 126.7843, 134.2734, 142.1793, 150.4361, 159.1373] +24-11-19 20:37:55 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 20:37:55 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:55 | D | sum error = [ 168.2721, 177.8340, 187.8831, 198.4260, 209.4897] +24-11-19 20:37:55 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 20:37:55 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:55 | D | sum error = [ 221.0667, 233.1962, 245.8788, 259.1221, 273.0165] +24-11-19 20:37:55 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 20:37:55 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:55 | D | sum error = [ 287.5249, 302.6539, 318.4520, 334.9184, 352.0653] +24-11-19 20:37:55 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 20:37:55 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:55 | D | sum error = [ 369.9225, 388.5587, 407.9274, 428.0828, 449.0256] +24-11-19 20:37:55 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 20:37:55 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:55 | D | sum error = [ 470.7572, 493.2982, 516.6186, 540.7622, 565.7388] +24-11-19 20:37:55 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 20:37:55 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:55 | D | sum error = [ 591.5457, 618.1624, 645.6358, 673.9593, 703.1086] +24-11-19 20:37:55 | D | best error = [ 8.6628, 8.6628, 8.6628, 8.6628, 8.6628] +24-11-19 20:37:55 | D | + error = [8.6628] +24-11-19 20:37:56 | D | - Calibrating model.layers.23.mlp.down_proj.weight +24-11-19 20:37:56 | D | + w: sint8 +24-11-19 20:37:56 | D | + x: None +24-11-19 20:37:56 | D | + y: None +24-11-19 20:37:56 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:37:56 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:37:56 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:37:56 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:37:56 | D | - range ratio = [ 1.0000] +24-11-19 20:37:56 | D | sum error = [ 1.1715] +24-11-19 20:37:56 | D | best error = [ 1.1715] +24-11-19 20:37:57 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:37:57 | D | sum error = [ 1.1616, 1.1538, 1.1441, 1.1398, 1.1373] +24-11-19 20:37:57 | D | best error = [ 1.1222, 1.0981, 1.0805, 1.0673, 1.0575] +24-11-19 20:37:57 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:37:57 | D | sum error = [ 1.1379, 1.1438, 1.1523, 1.1650, 1.1837] +24-11-19 20:37:57 | D | best error = [ 1.0498, 1.0436, 1.0386, 1.0350, 1.0325] +24-11-19 20:37:57 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:37:57 | D | sum error = [ 1.2089, 1.2378, 1.2740, 1.3171, 1.3695] +24-11-19 20:37:57 | D | best error = [ 1.0305, 1.0289, 1.0277, 1.0272, 1.0266] +24-11-19 20:37:57 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:37:57 | D | sum error = [ 1.4301, 1.4957, 1.5711, 1.6587, 1.7560] +24-11-19 20:37:57 | D | best error = [ 1.0263, 1.0260, 1.0259, 1.0258, 1.0257] +24-11-19 20:37:57 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:37:57 | D | sum error = [ 1.8594, 1.9778, 2.1042, 2.2438, 2.3932] +24-11-19 20:37:57 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 20:37:57 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:37:57 | D | sum error = [ 2.5574, 2.7330, 2.9207, 3.1228, 3.3419] +24-11-19 20:37:57 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 20:37:57 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:37:57 | D | sum error = [ 3.5744, 3.8250, 4.0906, 4.3755, 4.6770] +24-11-19 20:37:57 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 20:37:57 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:37:57 | D | sum error = [ 4.9997, 5.3429, 5.7055, 6.0903, 6.4990] +24-11-19 20:37:57 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 20:37:57 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:37:57 | D | sum error = [ 6.9303, 7.3884, 7.8730, 8.3825, 8.9215] +24-11-19 20:37:57 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 20:37:57 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:37:57 | D | sum error = [ 9.4911, 10.0916, 10.7266, 11.3943, 12.0980] +24-11-19 20:37:57 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 20:37:57 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:37:57 | D | sum error = [ 12.8399, 13.6209, 14.4414, 15.3037, 16.2076] +24-11-19 20:37:57 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 20:37:57 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:37:57 | D | sum error = [ 17.1610, 18.1582, 19.2070, 20.3033, 21.4518] +24-11-19 20:37:57 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 20:37:57 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:37:57 | D | sum error = [ 22.6548, 23.9137, 25.2302, 26.6055, 28.0411] +24-11-19 20:37:57 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 20:37:57 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:37:57 | D | sum error = [ 29.5391, 31.1041, 32.7349, 34.4323, 36.1990] +24-11-19 20:37:57 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 20:37:57 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:37:57 | D | sum error = [ 38.0369, 39.9509, 41.9380, 44.0014, 46.1399] +24-11-19 20:37:57 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 20:37:57 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:37:57 | D | sum error = [ 48.3596, 50.6595, 53.0402, 55.5039, 58.0483] +24-11-19 20:37:57 | D | best error = [ 1.0257, 1.0257, 1.0257, 1.0257, 1.0257] +24-11-19 20:37:57 | D | + error = [1.0257] +24-11-19 20:37:57 | D | - Quantizing model.layers.23.self_attn.q_proj.weight +24-11-19 20:37:58 | D | - Quantizing model.layers.23.self_attn.k_proj.weight +24-11-19 20:37:59 | D | - Quantizing model.layers.23.self_attn.v_proj.weight +24-11-19 20:38:00 | D | - Quantizing model.layers.23.self_attn.o_proj.weight +24-11-19 20:38:01 | D | - Quantizing model.layers.23.mlp.up_proj.weight +24-11-19 20:38:01 | D | - Quantizing model.layers.23.mlp.gate_proj.weight +24-11-19 20:38:02 | D | - Quantizing model.layers.23.mlp.down_proj.weight +24-11-19 20:38:12 | D | - Quantizing layer model.layers.24 +24-11-19 20:38:12 | D | - Calibrating model.layers.24.self_attn.q_proj.weight +24-11-19 20:38:12 | D | + w: sint8 +24-11-19 20:38:12 | D | + x: None +24-11-19 20:38:12 | D | + y: None +24-11-19 20:38:12 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:38:12 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:12 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:13 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:13 | D | - range ratio = [ 1.0000] +24-11-19 20:38:13 | D | sum error = [ 4.7230] +24-11-19 20:38:13 | D | best error = [ 4.7230] +24-11-19 20:38:26 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:26 | D | sum error = [ 4.6661, 4.7665, 4.7427, 4.8066, 4.9027] +24-11-19 20:38:26 | D | best error = [ 4.6661, 4.6661, 4.6661, 4.6661, 4.6661] +24-11-19 20:38:26 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:26 | D | sum error = [ 5.0314, 5.1088, 5.5303, 5.6580, 6.0852] +24-11-19 20:38:26 | D | best error = [ 4.6661, 4.6661, 4.6661, 4.6661, 4.6661] +24-11-19 20:38:26 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:26 | D | sum error = [ 6.4171, 6.8424, 7.4024, 7.9346, 8.5359] +24-11-19 20:38:26 | D | best error = [ 4.6661, 4.6661, 4.6661, 4.6661, 4.6661] +24-11-19 20:38:26 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:26 | D | sum error = [ 9.2071, 10.0092, 10.9292, 12.0767, 13.0557] +24-11-19 20:38:26 | D | best error = [ 4.6661, 4.6661, 4.6661, 4.6661, 4.6661] +24-11-19 20:38:26 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:26 | D | sum error = [ 13.9929, 15.5836, 16.8276, 18.0670, 19.7291] +24-11-19 20:38:26 | D | best error = [ 4.6661, 4.6661, 4.6661, 4.6661, 4.6661] +24-11-19 20:38:26 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:26 | D | sum error = [ 21.2528, 23.0080, 24.9882, 27.0289, 29.4790] +24-11-19 20:38:26 | D | best error = [ 4.6661, 4.6661, 4.6661, 4.6661, 4.6661] +24-11-19 20:38:26 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:26 | D | sum error = [ 31.9046, 34.7582, 37.3587, 40.6488, 44.0787] +24-11-19 20:38:26 | D | best error = [ 4.6661, 4.6661, 4.6661, 4.6661, 4.6661] +24-11-19 20:38:26 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:26 | D | sum error = [ 47.8786, 51.9872, 56.2657, 60.7938, 65.8954] +24-11-19 20:38:26 | D | best error = [ 4.6661, 4.6661, 4.6661, 4.6661, 4.6661] +24-11-19 20:38:26 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:26 | D | sum error = [ 70.9535, 76.8948, 83.2669, 89.7328, 97.1294] +24-11-19 20:38:26 | D | best error = [ 4.6661, 4.6661, 4.6661, 4.6661, 4.6661] +24-11-19 20:38:26 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:26 | D | sum error = [ 104.9660, 113.5987, 122.7889, 132.3555, 142.9767] +24-11-19 20:38:26 | D | best error = [ 4.6661, 4.6661, 4.6661, 4.6661, 4.6661] +24-11-19 20:38:26 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:26 | D | sum error = [ 154.5615, 166.7409, 180.0321, 194.0975, 209.7129] +24-11-19 20:38:26 | D | best error = [ 4.6661, 4.6661, 4.6661, 4.6661, 4.6661] +24-11-19 20:38:26 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:26 | D | sum error = [ 226.2355, 244.0694, 262.8233, 283.5396, 305.5301] +24-11-19 20:38:26 | D | best error = [ 4.6661, 4.6661, 4.6661, 4.6661, 4.6661] +24-11-19 20:38:26 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:26 | D | sum error = [ 329.2742, 355.1409, 382.7896, 412.4844, 444.9207] +24-11-19 20:38:26 | D | best error = [ 4.6661, 4.6661, 4.6661, 4.6661, 4.6661] +24-11-19 20:38:26 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:26 | D | sum error = [ 480.1948, 518.5941, 560.1721, 605.3713, 654.1440] +24-11-19 20:38:26 | D | best error = [ 4.6661, 4.6661, 4.6661, 4.6661, 4.6661] +24-11-19 20:38:26 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:26 | D | sum error = [ 706.8615, 764.6174, 826.2400, 892.7441, 963.5077] +24-11-19 20:38:26 | D | best error = [ 4.6661, 4.6661, 4.6661, 4.6661, 4.6661] +24-11-19 20:38:26 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:26 | D | sum error = [ 1038.3016, 1117.9941, 1200.7756, 1287.0107, 1375.5641] +24-11-19 20:38:26 | D | best error = [ 4.6661, 4.6661, 4.6661, 4.6661, 4.6661] +24-11-19 20:38:26 | D | + error = [4.6661] +24-11-19 20:38:26 | D | - Calibrating model.layers.24.self_attn.k_proj.weight +24-11-19 20:38:26 | D | + w: sint8 +24-11-19 20:38:26 | D | + x: None +24-11-19 20:38:26 | D | + y: None +24-11-19 20:38:26 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:38:26 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:38:26 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:38:26 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:26 | D | - range ratio = [ 1.0000] +24-11-19 20:38:26 | D | sum error = [ 4.4979] +24-11-19 20:38:26 | D | best error = [ 4.4979] +24-11-19 20:38:39 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:39 | D | sum error = [ 5.3462, 4.3956, 4.4704, 5.2793, 5.2699] +24-11-19 20:38:39 | D | best error = [ 4.4979, 4.3956, 4.3956, 4.3956, 4.3956] +24-11-19 20:38:39 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:39 | D | sum error = [ 4.9995, 5.0118, 6.1556, 5.2320, 5.7676] +24-11-19 20:38:39 | D | best error = [ 4.3956, 4.3956, 4.3956, 4.3956, 4.3956] +24-11-19 20:38:39 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:39 | D | sum error = [ 6.2301, 7.0808, 7.9422, 7.7582, 8.5199] +24-11-19 20:38:39 | D | best error = [ 4.3956, 4.3956, 4.3956, 4.3956, 4.3956] +24-11-19 20:38:39 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:39 | D | sum error = [ 9.4797, 10.6063, 10.5258, 12.5938, 12.8733] +24-11-19 20:38:39 | D | best error = [ 4.3956, 4.3956, 4.3956, 4.3956, 4.3956] +24-11-19 20:38:39 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:39 | D | sum error = [ 14.0668, 14.8664, 16.9084, 18.1521, 19.9055] +24-11-19 20:38:39 | D | best error = [ 4.3956, 4.3956, 4.3956, 4.3956, 4.3956] +24-11-19 20:38:39 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:39 | D | sum error = [ 21.3702, 22.2653, 23.9552, 26.8234, 28.2946] +24-11-19 20:38:39 | D | best error = [ 4.3956, 4.3956, 4.3956, 4.3956, 4.3956] +24-11-19 20:38:39 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:39 | D | sum error = [ 30.6744, 33.8932, 35.7764, 39.9927, 42.1179] +24-11-19 20:38:39 | D | best error = [ 4.3956, 4.3956, 4.3956, 4.3956, 4.3956] +24-11-19 20:38:39 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:39 | D | sum error = [ 45.8448, 50.3134, 53.3982, 58.4761, 63.8053] +24-11-19 20:38:39 | D | best error = [ 4.3956, 4.3956, 4.3956, 4.3956, 4.3956] +24-11-19 20:38:39 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:39 | D | sum error = [ 68.5358, 73.7433, 79.6460, 85.8561, 92.5793] +24-11-19 20:38:39 | D | best error = [ 4.3956, 4.3956, 4.3956, 4.3956, 4.3956] +24-11-19 20:38:39 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:39 | D | sum error = [ 100.2963, 109.1299, 117.6909, 126.3218, 137.1056] +24-11-19 20:38:39 | D | best error = [ 4.3956, 4.3956, 4.3956, 4.3956, 4.3956] +24-11-19 20:38:39 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:39 | D | sum error = [ 148.1291, 160.5123, 173.3349, 188.1213, 203.0804] +24-11-19 20:38:39 | D | best error = [ 4.3956, 4.3956, 4.3956, 4.3956, 4.3956] +24-11-19 20:38:39 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:39 | D | sum error = [ 221.3689, 238.9967, 257.9466, 277.8608, 300.3447] +24-11-19 20:38:39 | D | best error = [ 4.3956, 4.3956, 4.3956, 4.3956, 4.3956] +24-11-19 20:38:39 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:39 | D | sum error = [ 324.4812, 349.6054, 378.4677, 408.0052, 438.3803] +24-11-19 20:38:39 | D | best error = [ 4.3956, 4.3956, 4.3956, 4.3956, 4.3956] +24-11-19 20:38:39 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:39 | D | sum error = [ 473.6783, 509.8383, 551.0209, 596.6321, 642.8791] +24-11-19 20:38:39 | D | best error = [ 4.3956, 4.3956, 4.3956, 4.3956, 4.3956] +24-11-19 20:38:39 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:39 | D | sum error = [ 695.8668, 752.0157, 813.3753, 879.5874, 950.8542] +24-11-19 20:38:39 | D | best error = [ 4.3956, 4.3956, 4.3956, 4.3956, 4.3956] +24-11-19 20:38:39 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:39 | D | sum error = [ 1026.6803, 1107.3562, 1193.0134, 1281.9622, 1371.9704] +24-11-19 20:38:39 | D | best error = [ 4.3956, 4.3956, 4.3956, 4.3956, 4.3956] +24-11-19 20:38:39 | D | + error = [4.3956] +24-11-19 20:38:39 | D | - Calibrating model.layers.24.self_attn.v_proj.weight +24-11-19 20:38:39 | D | + w: sint8 +24-11-19 20:38:39 | D | + x: None +24-11-19 20:38:39 | D | + y: None +24-11-19 20:38:39 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:39 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:39 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:39 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:39 | D | - range ratio = [ 1.0000] +24-11-19 20:38:39 | D | sum error = [ 2.3517] +24-11-19 20:38:39 | D | best error = [ 2.3517] +24-11-19 20:38:39 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:39 | D | sum error = [ 2.3399, 2.3510, 2.3446, 2.3653, 2.4108] +24-11-19 20:38:39 | D | best error = [ 2.1713, 2.1007, 2.0576, 2.0334, 2.0220] +24-11-19 20:38:39 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:39 | D | sum error = [ 2.4924, 2.5688, 2.6657, 2.8066, 2.9362] +24-11-19 20:38:39 | D | best error = [ 2.0159, 2.0137, 2.0118, 2.0113, 2.0111] +24-11-19 20:38:39 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:39 | D | sum error = [ 3.1155, 3.2741, 3.4993, 3.7489, 4.0175] +24-11-19 20:38:39 | D | best error = [ 2.0110, 2.0110, 2.0110, 2.0110, 2.0110] +24-11-19 20:38:39 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:39 | D | sum error = [ 4.2976, 4.5899, 4.9207, 5.2707, 5.6323] +24-11-19 20:38:39 | D | best error = [ 2.0110, 2.0110, 2.0110, 2.0110, 2.0110] +24-11-19 20:38:39 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:39 | D | sum error = [ 6.0445, 6.4870, 6.9485, 7.4183, 7.9052] +24-11-19 20:38:39 | D | best error = [ 2.0110, 2.0110, 2.0110, 2.0110, 2.0110] +24-11-19 20:38:39 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:39 | D | sum error = [ 8.4803, 9.0297, 9.6242, 10.2527, 10.9318] +24-11-19 20:38:39 | D | best error = [ 2.0110, 2.0110, 2.0110, 2.0110, 2.0110] +24-11-19 20:38:39 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:39 | D | sum error = [ 11.6331, 12.3838, 13.1775, 13.9703, 14.8542] +24-11-19 20:38:39 | D | best error = [ 2.0110, 2.0110, 2.0110, 2.0110, 2.0110] +24-11-19 20:38:39 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:39 | D | sum error = [ 15.7771, 16.7570, 17.7749, 18.8362, 19.9420] +24-11-19 20:38:39 | D | best error = [ 2.0110, 2.0110, 2.0110, 2.0110, 2.0110] +24-11-19 20:38:39 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:39 | D | sum error = [ 21.1481, 22.3751, 23.6674, 25.0121, 26.4438] +24-11-19 20:38:39 | D | best error = [ 2.0110, 2.0110, 2.0110, 2.0110, 2.0110] +24-11-19 20:38:39 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:39 | D | sum error = [ 27.9291, 29.4571, 31.0983, 32.7715, 34.5664] +24-11-19 20:38:39 | D | best error = [ 2.0110, 2.0110, 2.0110, 2.0110, 2.0110] +24-11-19 20:38:39 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:39 | D | sum error = [ 36.3991, 38.3430, 40.3459, 42.4360, 44.6389] +24-11-19 20:38:39 | D | best error = [ 2.0110, 2.0110, 2.0110, 2.0110, 2.0110] +24-11-19 20:38:39 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:39 | D | sum error = [ 46.9099, 49.2844, 51.7302, 54.2870, 56.9543] +24-11-19 20:38:39 | D | best error = [ 2.0110, 2.0110, 2.0110, 2.0110, 2.0110] +24-11-19 20:38:39 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:39 | D | sum error = [ 59.7091, 62.5643, 65.5041, 68.5561, 71.7103] +24-11-19 20:38:39 | D | best error = [ 2.0110, 2.0110, 2.0110, 2.0110, 2.0110] +24-11-19 20:38:39 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:39 | D | sum error = [ 74.9628, 78.3235, 81.8186, 85.4229, 89.1576] +24-11-19 20:38:39 | D | best error = [ 2.0110, 2.0110, 2.0110, 2.0110, 2.0110] +24-11-19 20:38:39 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:39 | D | sum error = [ 92.9980, 96.9711, 101.0499, 105.2888, 109.6521] +24-11-19 20:38:39 | D | best error = [ 2.0110, 2.0110, 2.0110, 2.0110, 2.0110] +24-11-19 20:38:39 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:39 | D | sum error = [ 114.1216, 118.7226, 123.4550, 128.3111, 133.2945] +24-11-19 20:38:39 | D | best error = [ 2.0110, 2.0110, 2.0110, 2.0110, 2.0110] +24-11-19 20:38:39 | D | + error = [2.0110] +24-11-19 20:38:39 | D | - Calibrating model.layers.24.self_attn.o_proj.weight +24-11-19 20:38:39 | D | + w: sint8 +24-11-19 20:38:39 | D | + x: None +24-11-19 20:38:39 | D | + y: None +24-11-19 20:38:39 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:39 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:40 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:40 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:40 | D | - range ratio = [ 1.0000] +24-11-19 20:38:40 | D | sum error = [ 0.4864] +24-11-19 20:38:40 | D | best error = [ 0.4864] +24-11-19 20:38:40 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:40 | D | sum error = [ 0.4824, 0.4810, 0.4801, 0.4811, 0.4866] +24-11-19 20:38:40 | D | best error = [ 0.4501, 0.4343, 0.4240, 0.4173, 0.4122] +24-11-19 20:38:40 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:40 | D | sum error = [ 0.4927, 0.5041, 0.5174, 0.5329, 0.5512] +24-11-19 20:38:40 | D | best error = [ 0.4087, 0.4060, 0.4036, 0.4020, 0.4006] +24-11-19 20:38:40 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:40 | D | sum error = [ 0.5752, 0.6025, 0.6318, 0.6651, 0.7013] +24-11-19 20:38:40 | D | best error = [ 0.3997, 0.3990, 0.3984, 0.3979, 0.3975] +24-11-19 20:38:40 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:40 | D | sum error = [ 0.7434, 0.7890, 0.8377, 0.8905, 0.9504] +24-11-19 20:38:40 | D | best error = [ 0.3971, 0.3968, 0.3966, 0.3965, 0.3963] +24-11-19 20:38:40 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:40 | D | sum error = [ 1.0107, 1.0767, 1.1489, 1.2258, 1.3048] +24-11-19 20:38:40 | D | best error = [ 0.3962, 0.3961, 0.3961, 0.3961, 0.3960] +24-11-19 20:38:40 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:40 | D | sum error = [ 1.3921, 1.4827, 1.5785, 1.6804, 1.7884] +24-11-19 20:38:40 | D | best error = [ 0.3960, 0.3960, 0.3959, 0.3959, 0.3959] +24-11-19 20:38:40 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:40 | D | sum error = [ 1.9023, 2.0209, 2.1482, 2.2824, 2.4237] +24-11-19 20:38:40 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:38:40 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:40 | D | sum error = [ 2.5702, 2.7265, 2.8904, 3.0605, 3.2405] +24-11-19 20:38:40 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:38:40 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:40 | D | sum error = [ 3.4321, 3.6318, 3.8426, 4.0625, 4.2929] +24-11-19 20:38:40 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:38:40 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:40 | D | sum error = [ 4.5355, 4.7910, 5.0571, 5.3358, 5.6277] +24-11-19 20:38:40 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:38:40 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:40 | D | sum error = [ 5.9350, 6.2540, 6.5906, 6.9403, 7.3060] +24-11-19 20:38:40 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:38:40 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:40 | D | sum error = [ 7.6869, 8.0860, 8.4997, 8.9314, 9.3819] +24-11-19 20:38:40 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:38:40 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:40 | D | sum error = [ 9.8491, 10.3339, 10.8386, 11.3620, 11.9055] +24-11-19 20:38:40 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:38:40 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:40 | D | sum error = [ 12.4683, 13.0522, 13.6556, 14.2835, 14.9314] +24-11-19 20:38:40 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:38:40 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:40 | D | sum error = [ 15.6031, 16.2983, 17.0174, 17.7590, 18.5238] +24-11-19 20:38:40 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:38:40 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:40 | D | sum error = [ 19.3125, 20.1244, 20.9608, 21.8228, 22.7108] +24-11-19 20:38:40 | D | best error = [ 0.3959, 0.3959, 0.3959, 0.3959, 0.3959] +24-11-19 20:38:40 | D | + error = [0.3959] +24-11-19 20:38:40 | D | - Calibrating model.layers.24.mlp.up_proj.weight +24-11-19 20:38:40 | D | + w: sint8 +24-11-19 20:38:40 | D | + x: None +24-11-19 20:38:40 | D | + y: None +24-11-19 20:38:40 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:40 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:40 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:40 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:40 | D | - range ratio = [ 1.0000] +24-11-19 20:38:40 | D | sum error = [ 7.7926] +24-11-19 20:38:40 | D | best error = [ 7.7926] +24-11-19 20:38:42 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:42 | D | sum error = [ 7.7182, 7.7217, 7.7355, 7.8169, 7.9711] +24-11-19 20:38:42 | D | best error = [ 7.1319, 6.8849, 6.7527, 6.6793, 6.6396] +24-11-19 20:38:42 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:42 | D | sum error = [ 8.1930, 8.4585, 8.7830, 9.1793, 9.6855] +24-11-19 20:38:42 | D | best error = [ 6.6211, 6.6121, 6.6092, 6.6081, 6.6076] +24-11-19 20:38:42 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:42 | D | sum error = [ 10.2418, 10.8943, 11.5781, 12.3573, 13.2076] +24-11-19 20:38:42 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:38:42 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:42 | D | sum error = [ 14.1435, 15.1384, 16.2146, 17.3732, 18.6144] +24-11-19 20:38:42 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:38:42 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:42 | D | sum error = [ 19.9421, 21.3732, 22.8631, 24.4508, 26.1557] +24-11-19 20:38:42 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:38:42 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:42 | D | sum error = [ 27.9422, 29.8157, 31.8150, 33.9348, 36.1343] +24-11-19 20:38:42 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:38:42 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:42 | D | sum error = [ 38.4649, 40.9322, 43.5319, 46.2553, 49.1196] +24-11-19 20:38:42 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:38:42 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:42 | D | sum error = [ 52.1487, 55.3219, 58.6343, 62.1182, 65.7633] +24-11-19 20:38:42 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:38:42 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:42 | D | sum error = [ 69.5991, 73.6108, 77.8030, 82.1970, 86.7619] +24-11-19 20:38:42 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:38:42 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:42 | D | sum error = [ 91.5596, 96.5505, 101.7484, 107.2140, 112.8621] +24-11-19 20:38:42 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:38:42 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:42 | D | sum error = [ 118.7588, 124.9066, 131.2907, 137.9401, 144.8283] +24-11-19 20:38:42 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:38:42 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:42 | D | sum error = [ 151.9723, 159.3882, 167.0633, 175.0536, 183.3002] +24-11-19 20:38:42 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:38:42 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:42 | D | sum error = [ 191.8608, 200.7090, 209.8583, 219.3180, 229.0917] +24-11-19 20:38:42 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:38:42 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:42 | D | sum error = [ 239.1758, 249.5811, 260.3089, 271.3771, 282.7542] +24-11-19 20:38:42 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:38:42 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:42 | D | sum error = [ 294.4849, 306.5492, 318.9573, 331.7355, 344.8533] +24-11-19 20:38:42 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:38:42 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:42 | D | sum error = [ 358.3263, 372.1608, 386.3755, 400.9616, 415.9234] +24-11-19 20:38:42 | D | best error = [ 6.6075, 6.6075, 6.6075, 6.6075, 6.6075] +24-11-19 20:38:42 | D | + error = [6.6075] +24-11-19 20:38:42 | D | - Calibrating model.layers.24.mlp.gate_proj.weight +24-11-19 20:38:42 | D | + w: sint8 +24-11-19 20:38:42 | D | + x: None +24-11-19 20:38:42 | D | + y: None +24-11-19 20:38:42 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:42 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:42 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:42 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:42 | D | - range ratio = [ 1.0000] +24-11-19 20:38:42 | D | sum error = [ 10.4817] +24-11-19 20:38:42 | D | best error = [ 10.4817] +24-11-19 20:38:43 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:43 | D | sum error = [ 10.4447, 10.4169, 10.4425, 10.5727, 10.7608] +24-11-19 20:38:43 | D | best error = [ 9.6172, 9.2790, 9.1106, 9.0125, 8.9607] +24-11-19 20:38:43 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:43 | D | sum error = [ 11.0423, 11.3877, 11.8345, 12.3813, 13.0689] +24-11-19 20:38:43 | D | best error = [ 8.9346, 8.9235, 8.9187, 8.9169, 8.9162] +24-11-19 20:38:43 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:43 | D | sum error = [ 13.7901, 14.6511, 15.6241, 16.6613, 17.7913] +24-11-19 20:38:43 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:38:43 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:43 | D | sum error = [ 19.0402, 20.3994, 21.8467, 23.4209, 25.1202] +24-11-19 20:38:43 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:38:43 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:43 | D | sum error = [ 26.9180, 28.8383, 30.8764, 33.0533, 35.3833] +24-11-19 20:38:43 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:38:43 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:43 | D | sum error = [ 37.8457, 40.4596, 43.2249, 46.1077, 49.2446] +24-11-19 20:38:43 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:38:43 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:43 | D | sum error = [ 52.5008, 55.9402, 59.5833, 63.4591, 67.5576] +24-11-19 20:38:43 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:38:43 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:43 | D | sum error = [ 71.8115, 76.3769, 81.1280, 86.1735, 91.4546] +24-11-19 20:38:43 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:38:43 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:43 | D | sum error = [ 97.0591, 102.9185, 109.1308, 115.6443, 122.5294] +24-11-19 20:38:43 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:38:43 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:43 | D | sum error = [ 129.7298, 137.2882, 145.2534, 153.6112, 162.3861] +24-11-19 20:38:43 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:38:43 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:43 | D | sum error = [ 171.6080, 181.2623, 191.4031, 202.0036, 213.1436] +24-11-19 20:38:43 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:38:43 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:43 | D | sum error = [ 224.8046, 236.9896, 249.7712, 263.1037, 277.0060] +24-11-19 20:38:43 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:38:43 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:43 | D | sum error = [ 291.5536, 306.7077, 322.4740, 338.9209, 356.0578] +24-11-19 20:38:43 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:38:43 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:43 | D | sum error = [ 373.8925, 392.4745, 411.7403, 431.7143, 452.4339] +24-11-19 20:38:43 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:38:43 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:43 | D | sum error = [ 473.9214, 496.2201, 519.3198, 543.2289, 567.9926] +24-11-19 20:38:43 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:38:43 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:43 | D | sum error = [ 593.5899, 620.0067, 647.2854, 675.3856, 704.3318] +24-11-19 20:38:43 | D | best error = [ 8.9161, 8.9161, 8.9161, 8.9161, 8.9161] +24-11-19 20:38:43 | D | + error = [8.9161] +24-11-19 20:38:43 | D | - Calibrating model.layers.24.mlp.down_proj.weight +24-11-19 20:38:43 | D | + w: sint8 +24-11-19 20:38:43 | D | + x: None +24-11-19 20:38:43 | D | + y: None +24-11-19 20:38:43 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:38:43 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:38:43 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:38:44 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:38:44 | D | - range ratio = [ 1.0000] +24-11-19 20:38:44 | D | sum error = [ 1.1968] +24-11-19 20:38:44 | D | best error = [ 1.1968] +24-11-19 20:38:45 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:38:45 | D | sum error = [ 1.1844, 1.1767, 1.1697, 1.1656, 1.1655] +24-11-19 20:38:45 | D | best error = [ 1.1430, 1.1164, 1.0988, 1.0857, 1.0754] +24-11-19 20:38:45 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:38:45 | D | sum error = [ 1.1724, 1.1772, 1.1877, 1.2063, 1.2311] +24-11-19 20:38:45 | D | best error = [ 1.0680, 1.0614, 1.0563, 1.0526, 1.0497] +24-11-19 20:38:45 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:38:45 | D | sum error = [ 1.2621, 1.2977, 1.3437, 1.3979, 1.4575] +24-11-19 20:38:45 | D | best error = [ 1.0474, 1.0460, 1.0451, 1.0444, 1.0438] +24-11-19 20:38:45 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:38:45 | D | sum error = [ 1.5284, 1.6070, 1.6935, 1.7955, 1.9037] +24-11-19 20:38:45 | D | best error = [ 1.0436, 1.0434, 1.0433, 1.0432, 1.0432] +24-11-19 20:38:45 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:38:45 | D | sum error = [ 2.0190, 2.1514, 2.2969, 2.4469, 2.6117] +24-11-19 20:38:45 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 20:38:45 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:38:45 | D | sum error = [ 2.7847, 2.9756, 3.1792, 3.3978, 3.6318] +24-11-19 20:38:45 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 20:38:45 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:38:45 | D | sum error = [ 3.8799, 4.1414, 4.4210, 4.7181, 5.0323] +24-11-19 20:38:45 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 20:38:45 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:38:45 | D | sum error = [ 5.3732, 5.7222, 6.1021, 6.4987, 6.9225] +24-11-19 20:38:45 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 20:38:45 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:38:45 | D | sum error = [ 7.3738, 7.8448, 8.3439, 8.8735, 9.4345] +24-11-19 20:38:45 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 20:38:45 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:38:45 | D | sum error = [ 10.0194, 10.6408, 11.2944, 11.9860, 12.7125] +24-11-19 20:38:45 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 20:38:45 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:38:45 | D | sum error = [ 13.4757, 14.2798, 15.1242, 16.0121, 16.9438] +24-11-19 20:38:45 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 20:38:45 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:38:45 | D | sum error = [ 17.9213, 18.9462, 20.0180, 21.1434, 22.3200] +24-11-19 20:38:45 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 20:38:45 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:38:45 | D | sum error = [ 23.5500, 24.8359, 26.1808, 27.5874, 29.0561] +24-11-19 20:38:45 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 20:38:45 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:38:45 | D | sum error = [ 30.5856, 32.1816, 33.8461, 35.5795, 37.3826] +24-11-19 20:38:45 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 20:38:45 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:38:45 | D | sum error = [ 39.2561, 41.2018, 43.2240, 45.3215, 47.4986] +24-11-19 20:38:45 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 20:38:45 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:38:45 | D | sum error = [ 49.7551, 52.0940, 54.5145, 57.0201, 59.6107] +24-11-19 20:38:45 | D | best error = [ 1.0431, 1.0431, 1.0431, 1.0431, 1.0431] +24-11-19 20:38:45 | D | + error = [1.0431] +24-11-19 20:38:45 | D | - Quantizing model.layers.24.self_attn.q_proj.weight +24-11-19 20:38:46 | D | - Quantizing model.layers.24.self_attn.k_proj.weight +24-11-19 20:38:46 | D | - Quantizing model.layers.24.self_attn.v_proj.weight +24-11-19 20:38:47 | D | - Quantizing model.layers.24.self_attn.o_proj.weight +24-11-19 20:38:48 | D | - Quantizing model.layers.24.mlp.up_proj.weight +24-11-19 20:38:49 | D | - Quantizing model.layers.24.mlp.gate_proj.weight +24-11-19 20:38:50 | D | - Quantizing model.layers.24.mlp.down_proj.weight +24-11-19 20:39:00 | D | - Quantizing layer model.layers.25 +24-11-19 20:39:00 | D | - Calibrating model.layers.25.self_attn.q_proj.weight +24-11-19 20:39:00 | D | + w: sint8 +24-11-19 20:39:00 | D | + x: None +24-11-19 20:39:00 | D | + y: None +24-11-19 20:39:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:39:00 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:39:00 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:39:00 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:39:00 | D | - range ratio = [ 1.0000] +24-11-19 20:39:00 | D | sum error = [ 5.3165] +24-11-19 20:39:00 | D | best error = [ 5.3165] +24-11-19 20:39:13 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:13 | D | sum error = [ 5.2912, 5.5582, 5.5707, 5.5927, 5.8812] +24-11-19 20:39:13 | D | best error = [ 5.2912, 5.2912, 5.2912, 5.2912, 5.2912] +24-11-19 20:39:13 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:13 | D | sum error = [ 5.6464, 5.8261, 6.3626, 6.6865, 7.2010] +24-11-19 20:39:13 | D | best error = [ 5.2912, 5.2912, 5.2912, 5.2912, 5.2912] +24-11-19 20:39:13 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:13 | D | sum error = [ 7.9958, 8.6845, 9.2771, 9.9871, 10.8034] +24-11-19 20:39:13 | D | best error = [ 5.2912, 5.2912, 5.2912, 5.2912, 5.2912] +24-11-19 20:39:13 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:13 | D | sum error = [ 11.9763, 13.0699, 14.0823, 15.3757, 17.3665] +24-11-19 20:39:13 | D | best error = [ 5.2912, 5.2912, 5.2912, 5.2912, 5.2912] +24-11-19 20:39:13 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:13 | D | sum error = [ 18.9263, 20.3313, 22.0465, 23.9055, 25.2686] +24-11-19 20:39:13 | D | best error = [ 5.2912, 5.2912, 5.2912, 5.2912, 5.2912] +24-11-19 20:39:13 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:13 | D | sum error = [ 27.0602, 29.8574, 32.2918, 34.9616, 37.5658] +24-11-19 20:39:13 | D | best error = [ 5.2912, 5.2912, 5.2912, 5.2912, 5.2912] +24-11-19 20:39:13 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:13 | D | sum error = [ 40.7540, 44.3748, 47.4495, 51.9810, 56.3009] +24-11-19 20:39:13 | D | best error = [ 5.2912, 5.2912, 5.2912, 5.2912, 5.2912] +24-11-19 20:39:13 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:13 | D | sum error = [ 60.7924, 65.4861, 70.3739, 76.1331, 82.3671] +24-11-19 20:39:13 | D | best error = [ 5.2912, 5.2912, 5.2912, 5.2912, 5.2912] +24-11-19 20:39:13 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:13 | D | sum error = [ 89.2117, 96.2608, 103.1130, 111.3356, 119.3844] +24-11-19 20:39:13 | D | best error = [ 5.2912, 5.2912, 5.2912, 5.2912, 5.2912] +24-11-19 20:39:13 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:13 | D | sum error = [ 128.8379, 138.5036, 148.6325, 159.3578, 171.7874] +24-11-19 20:39:13 | D | best error = [ 5.2912, 5.2912, 5.2912, 5.2912, 5.2912] +24-11-19 20:39:13 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:13 | D | sum error = [ 184.3381, 197.2672, 211.1577, 226.5681, 243.0434] +24-11-19 20:39:13 | D | best error = [ 5.2912, 5.2912, 5.2912, 5.2912, 5.2912] +24-11-19 20:39:13 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:13 | D | sum error = [ 260.1097, 278.8781, 298.6544, 321.4113, 344.9041] +24-11-19 20:39:13 | D | best error = [ 5.2912, 5.2912, 5.2912, 5.2912, 5.2912] +24-11-19 20:39:13 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:13 | D | sum error = [ 370.8846, 398.0431, 428.2227, 460.1377, 495.3304] +24-11-19 20:39:13 | D | best error = [ 5.2912, 5.2912, 5.2912, 5.2912, 5.2912] +24-11-19 20:39:13 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:13 | D | sum error = [ 533.6211, 575.6913, 620.1414, 670.2858, 723.3250] +24-11-19 20:39:13 | D | best error = [ 5.2912, 5.2912, 5.2912, 5.2912, 5.2912] +24-11-19 20:39:13 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:13 | D | sum error = [ 781.7944, 845.2923, 912.7740, 986.3819, 1064.8337] +24-11-19 20:39:13 | D | best error = [ 5.2912, 5.2912, 5.2912, 5.2912, 5.2912] +24-11-19 20:39:13 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:13 | D | sum error = [ 1150.7197, 1241.4734, 1338.3063, 1439.5806, 1545.7587] +24-11-19 20:39:13 | D | best error = [ 5.2912, 5.2912, 5.2912, 5.2912, 5.2912] +24-11-19 20:39:13 | D | + error = [5.2912] +24-11-19 20:39:13 | D | - Calibrating model.layers.25.self_attn.k_proj.weight +24-11-19 20:39:13 | D | + w: sint8 +24-11-19 20:39:13 | D | + x: None +24-11-19 20:39:13 | D | + y: None +24-11-19 20:39:13 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:39:13 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:39:13 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:39:13 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:39:14 | D | - range ratio = [ 1.0000] +24-11-19 20:39:14 | D | sum error = [ 6.8959] +24-11-19 20:39:14 | D | best error = [ 6.8959] +24-11-19 20:39:26 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:26 | D | sum error = [ 6.4046, 6.0025, 5.9255, 8.3960, 6.0669] +24-11-19 20:39:26 | D | best error = [ 6.4046, 6.0025, 5.9255, 5.9255, 5.9255] +24-11-19 20:39:26 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:26 | D | sum error = [ 6.9304, 6.5578, 7.1925, 7.1278, 8.6967] +24-11-19 20:39:26 | D | best error = [ 5.9255, 5.9255, 5.9255, 5.9255, 5.9255] +24-11-19 20:39:26 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:26 | D | sum error = [ 8.7593, 10.4856, 9.9958, 11.8775, 9.8844] +24-11-19 20:39:26 | D | best error = [ 5.9255, 5.9255, 5.9255, 5.9255, 5.9255] +24-11-19 20:39:26 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:26 | D | sum error = [ 13.4387, 11.6704, 13.4343, 13.8713, 16.2158] +24-11-19 20:39:26 | D | best error = [ 5.9255, 5.9255, 5.9255, 5.9255, 5.9255] +24-11-19 20:39:26 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:26 | D | sum error = [ 17.5359, 19.2345, 20.3376, 23.0075, 24.0121] +24-11-19 20:39:26 | D | best error = [ 5.9255, 5.9255, 5.9255, 5.9255, 5.9255] +24-11-19 20:39:26 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:26 | D | sum error = [ 25.3513, 27.3501, 30.3139, 32.9286, 35.0905] +24-11-19 20:39:26 | D | best error = [ 5.9255, 5.9255, 5.9255, 5.9255, 5.9255] +24-11-19 20:39:26 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:26 | D | sum error = [ 39.4774, 40.6474, 43.1445, 45.0623, 50.5447] +24-11-19 20:39:26 | D | best error = [ 5.9255, 5.9255, 5.9255, 5.9255, 5.9255] +24-11-19 20:39:26 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:26 | D | sum error = [ 53.8530, 57.2185, 60.1400, 64.6468, 70.8114] +24-11-19 20:39:26 | D | best error = [ 5.9255, 5.9255, 5.9255, 5.9255, 5.9255] +24-11-19 20:39:26 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:26 | D | sum error = [ 73.6955, 78.9883, 84.0606, 88.9079, 95.2104] +24-11-19 20:39:26 | D | best error = [ 5.9255, 5.9255, 5.9255, 5.9255, 5.9255] +24-11-19 20:39:26 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:26 | D | sum error = [ 100.4095, 106.2285, 113.4904, 120.4271, 128.9741] +24-11-19 20:39:26 | D | best error = [ 5.9255, 5.9255, 5.9255, 5.9255, 5.9255] +24-11-19 20:39:26 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:26 | D | sum error = [ 137.0317, 147.2678, 157.9695, 169.3557, 181.3632] +24-11-19 20:39:26 | D | best error = [ 5.9255, 5.9255, 5.9255, 5.9255, 5.9255] +24-11-19 20:39:26 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:26 | D | sum error = [ 194.5835, 210.8636, 226.0319, 244.1931, 263.8025] +24-11-19 20:39:26 | D | best error = [ 5.9255, 5.9255, 5.9255, 5.9255, 5.9255] +24-11-19 20:39:26 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:26 | D | sum error = [ 285.1944, 309.6407, 336.2734, 364.3834, 395.7196] +24-11-19 20:39:26 | D | best error = [ 5.9255, 5.9255, 5.9255, 5.9255, 5.9255] +24-11-19 20:39:26 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:26 | D | sum error = [ 429.1541, 466.2111, 507.0146, 551.9674, 599.6091] +24-11-19 20:39:26 | D | best error = [ 5.9255, 5.9255, 5.9255, 5.9255, 5.9255] +24-11-19 20:39:26 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:26 | D | sum error = [ 654.0162, 712.0991, 778.1012, 848.4962, 926.5592] +24-11-19 20:39:26 | D | best error = [ 5.9255, 5.9255, 5.9255, 5.9255, 5.9255] +24-11-19 20:39:26 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:26 | D | sum error = [ 1010.1969, 1099.6731, 1197.7081, 1302.5298, 1411.6011] +24-11-19 20:39:26 | D | best error = [ 5.9255, 5.9255, 5.9255, 5.9255, 5.9255] +24-11-19 20:39:26 | D | + error = [5.9255] +24-11-19 20:39:26 | D | - Calibrating model.layers.25.self_attn.v_proj.weight +24-11-19 20:39:26 | D | + w: sint8 +24-11-19 20:39:26 | D | + x: None +24-11-19 20:39:26 | D | + y: None +24-11-19 20:39:26 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:26 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:39:26 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:39:26 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:39:26 | D | - range ratio = [ 1.0000] +24-11-19 20:39:26 | D | sum error = [ 2.4342] +24-11-19 20:39:26 | D | best error = [ 2.4342] +24-11-19 20:39:26 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:26 | D | sum error = [ 2.4353, 2.4229, 2.4442, 2.4455, 2.4879] +24-11-19 20:39:26 | D | best error = [ 2.2240, 2.1411, 2.1033, 2.0837, 2.0706] +24-11-19 20:39:26 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:26 | D | sum error = [ 2.5592, 2.6553, 2.7347, 2.8482, 3.0240] +24-11-19 20:39:26 | D | best error = [ 2.0628, 2.0597, 2.0584, 2.0583, 2.0583] +24-11-19 20:39:26 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:26 | D | sum error = [ 3.2089, 3.4211, 3.6362, 3.8722, 4.1416] +24-11-19 20:39:26 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:39:26 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:26 | D | sum error = [ 4.4388, 4.7773, 5.0743, 5.4517, 5.8664] +24-11-19 20:39:26 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:39:26 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:26 | D | sum error = [ 6.2984, 6.7348, 7.1750, 7.6867, 8.1996] +24-11-19 20:39:26 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:39:26 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:26 | D | sum error = [ 8.8027, 9.3851, 10.0038, 10.6626, 11.3671] +24-11-19 20:39:26 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:39:26 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:26 | D | sum error = [ 12.0967, 12.8921, 13.6822, 14.5537, 15.4850] +24-11-19 20:39:26 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:39:26 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:26 | D | sum error = [ 16.4482, 17.4578, 18.5355, 19.6381, 20.8233] +24-11-19 20:39:26 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:39:26 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:26 | D | sum error = [ 22.0409, 23.3601, 24.7011, 26.1245, 27.6193] +24-11-19 20:39:26 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:39:26 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:26 | D | sum error = [ 29.1940, 30.8288, 32.5321, 34.3024, 36.1735] +24-11-19 20:39:26 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:39:26 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:26 | D | sum error = [ 38.1283, 40.1648, 42.2688, 44.4929, 46.7914] +24-11-19 20:39:26 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:39:26 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:26 | D | sum error = [ 49.1991, 51.7247, 54.3243, 57.0415, 59.8796] +24-11-19 20:39:26 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:39:26 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:26 | D | sum error = [ 62.8052, 65.8536, 69.0114, 72.2832, 75.6789] +24-11-19 20:39:26 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:39:26 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:26 | D | sum error = [ 79.2049, 82.8248, 86.5783, 90.4760, 94.4998] +24-11-19 20:39:26 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:39:26 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:26 | D | sum error = [ 98.6668, 102.9640, 107.3979, 111.9681, 116.6588] +24-11-19 20:39:26 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:39:26 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:26 | D | sum error = [ 121.5011, 126.4894, 131.6165, 136.8750, 142.2850] +24-11-19 20:39:26 | D | best error = [ 2.0583, 2.0583, 2.0583, 2.0583, 2.0583] +24-11-19 20:39:26 | D | + error = [2.0583] +24-11-19 20:39:26 | D | - Calibrating model.layers.25.self_attn.o_proj.weight +24-11-19 20:39:26 | D | + w: sint8 +24-11-19 20:39:26 | D | + x: None +24-11-19 20:39:26 | D | + y: None +24-11-19 20:39:26 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:26 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:39:27 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:39:27 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:39:27 | D | - range ratio = [ 1.0000] +24-11-19 20:39:27 | D | sum error = [ 0.5029] +24-11-19 20:39:27 | D | best error = [ 0.5029] +24-11-19 20:39:27 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:27 | D | sum error = [ 0.4973, 0.4957, 0.4937, 0.4946, 0.4968] +24-11-19 20:39:27 | D | best error = [ 0.4706, 0.4561, 0.4469, 0.4406, 0.4360] +24-11-19 20:39:27 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:27 | D | sum error = [ 0.5016, 0.5097, 0.5213, 0.5342, 0.5522] +24-11-19 20:39:27 | D | best error = [ 0.4322, 0.4299, 0.4282, 0.4268, 0.4259] +24-11-19 20:39:27 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:27 | D | sum error = [ 0.5711, 0.5955, 0.6222, 0.6545, 0.6868] +24-11-19 20:39:27 | D | best error = [ 0.4254, 0.4249, 0.4245, 0.4242, 0.4239] +24-11-19 20:39:27 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:27 | D | sum error = [ 0.7271, 0.7703, 0.8173, 0.8693, 0.9240] +24-11-19 20:39:27 | D | best error = [ 0.4238, 0.4237, 0.4237, 0.4236, 0.4236] +24-11-19 20:39:27 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:27 | D | sum error = [ 0.9856, 1.0492, 1.1191, 1.1935, 1.2727] +24-11-19 20:39:27 | D | best error = [ 0.4236, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:39:27 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:27 | D | sum error = [ 1.3586, 1.4486, 1.5438, 1.6457, 1.7541] +24-11-19 20:39:27 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:39:27 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:27 | D | sum error = [ 1.8704, 1.9910, 2.1214, 2.2576, 2.4023] +24-11-19 20:39:27 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:39:27 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:27 | D | sum error = [ 2.5545, 2.7177, 2.8885, 3.0688, 3.2587] +24-11-19 20:39:27 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:39:27 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:27 | D | sum error = [ 3.4592, 3.6715, 3.8944, 4.1291, 4.3777] +24-11-19 20:39:27 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:39:27 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:27 | D | sum error = [ 4.6372, 4.9115, 5.1994, 5.5024, 5.8193] +24-11-19 20:39:27 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:39:27 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:27 | D | sum error = [ 6.1543, 6.5048, 6.8735, 7.2601, 7.6642] +24-11-19 20:39:27 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:39:27 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:27 | D | sum error = [ 8.0885, 8.5348, 9.0020, 9.4912, 10.0024] +24-11-19 20:39:27 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:39:27 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:27 | D | sum error = [ 10.5382, 11.0985, 11.6839, 12.2965, 12.9363] +24-11-19 20:39:27 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:39:27 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:27 | D | sum error = [ 13.6041, 14.3002, 15.0276, 15.7854, 16.5726] +24-11-19 20:39:27 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:39:27 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:27 | D | sum error = [ 17.3926, 18.2455, 19.1315, 20.0529, 21.0098] +24-11-19 20:39:27 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:39:27 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:27 | D | sum error = [ 22.0033, 23.0316, 24.0970, 25.1989, 26.3397] +24-11-19 20:39:27 | D | best error = [ 0.4235, 0.4235, 0.4235, 0.4235, 0.4235] +24-11-19 20:39:27 | D | + error = [0.4235] +24-11-19 20:39:27 | D | - Calibrating model.layers.25.mlp.up_proj.weight +24-11-19 20:39:27 | D | + w: sint8 +24-11-19 20:39:27 | D | + x: None +24-11-19 20:39:27 | D | + y: None +24-11-19 20:39:27 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:27 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:39:27 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:39:27 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:39:28 | D | - range ratio = [ 1.0000] +24-11-19 20:39:28 | D | sum error = [ 8.1411] +24-11-19 20:39:28 | D | best error = [ 8.1411] +24-11-19 20:39:29 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:29 | D | sum error = [ 8.0784, 8.0704, 8.0805, 8.2032, 8.3501] +24-11-19 20:39:29 | D | best error = [ 7.3761, 7.1027, 6.9633, 6.8864, 6.8432] +24-11-19 20:39:29 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:29 | D | sum error = [ 8.5378, 8.8466, 9.1937, 9.6073, 10.1127] +24-11-19 20:39:29 | D | best error = [ 6.8229, 6.8133, 6.8091, 6.8078, 6.8075] +24-11-19 20:39:29 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:29 | D | sum error = [ 10.7032, 11.3541, 12.0954, 12.9232, 13.7668] +24-11-19 20:39:29 | D | best error = [ 6.8075, 6.8075, 6.8075, 6.8075, 6.8075] +24-11-19 20:39:29 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:29 | D | sum error = [ 14.7439, 15.7931, 16.9369, 18.1413, 19.4301] +24-11-19 20:39:29 | D | best error = [ 6.8075, 6.8075, 6.8075, 6.8075, 6.8075] +24-11-19 20:39:29 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:29 | D | sum error = [ 20.7819, 22.2750, 23.8440, 25.5006, 27.2939] +24-11-19 20:39:29 | D | best error = [ 6.8075, 6.8075, 6.8075, 6.8075, 6.8075] +24-11-19 20:39:29 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:29 | D | sum error = [ 29.1351, 31.1271, 33.2100, 35.4315, 37.7378] +24-11-19 20:39:29 | D | best error = [ 6.8075, 6.8075, 6.8075, 6.8075, 6.8075] +24-11-19 20:39:29 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:29 | D | sum error = [ 40.1721, 42.7552, 45.4597, 48.2879, 51.2856] +24-11-19 20:39:29 | D | best error = [ 6.8075, 6.8075, 6.8075, 6.8075, 6.8075] +24-11-19 20:39:29 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:29 | D | sum error = [ 54.4489, 57.7458, 61.2062, 64.8317, 68.6205] +24-11-19 20:39:29 | D | best error = [ 6.8075, 6.8075, 6.8075, 6.8075, 6.8075] +24-11-19 20:39:29 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:29 | D | sum error = [ 72.6072, 76.7496, 81.0888, 85.6698, 90.4169] +24-11-19 20:39:29 | D | best error = [ 6.8075, 6.8075, 6.8075, 6.8075, 6.8075] +24-11-19 20:39:29 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:29 | D | sum error = [ 95.3920, 100.5925, 106.0103, 111.6515, 117.5320] +24-11-19 20:39:29 | D | best error = [ 6.8075, 6.8075, 6.8075, 6.8075, 6.8075] +24-11-19 20:39:29 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:29 | D | sum error = [ 123.6425, 129.9813, 136.5720, 143.4086, 150.5029] +24-11-19 20:39:29 | D | best error = [ 6.8075, 6.8075, 6.8075, 6.8075, 6.8075] +24-11-19 20:39:29 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:29 | D | sum error = [ 157.8659, 165.5030, 173.4206, 181.6339, 190.1344] +24-11-19 20:39:29 | D | best error = [ 6.8075, 6.8075, 6.8075, 6.8075, 6.8075] +24-11-19 20:39:29 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:29 | D | sum error = [ 198.9439, 208.0430, 217.4515, 227.1622, 237.1933] +24-11-19 20:39:29 | D | best error = [ 6.8075, 6.8075, 6.8075, 6.8075, 6.8075] +24-11-19 20:39:29 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:29 | D | sum error = [ 247.5486, 258.2234, 269.2188, 280.5572, 292.2154] +24-11-19 20:39:29 | D | best error = [ 6.8075, 6.8075, 6.8075, 6.8075, 6.8075] +24-11-19 20:39:29 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:29 | D | sum error = [ 304.2040, 316.5400, 329.2231, 342.2622, 355.6491] +24-11-19 20:39:29 | D | best error = [ 6.8075, 6.8075, 6.8075, 6.8075, 6.8075] +24-11-19 20:39:29 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:29 | D | sum error = [ 369.4218, 383.5600, 398.0677, 412.9697, 428.2564] +24-11-19 20:39:29 | D | best error = [ 6.8075, 6.8075, 6.8075, 6.8075, 6.8075] +24-11-19 20:39:29 | D | + error = [6.8075] +24-11-19 20:39:29 | D | - Calibrating model.layers.25.mlp.gate_proj.weight +24-11-19 20:39:29 | D | + w: sint8 +24-11-19 20:39:29 | D | + x: None +24-11-19 20:39:29 | D | + y: None +24-11-19 20:39:29 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:29 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:39:29 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:39:29 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:39:29 | D | - range ratio = [ 1.0000] +24-11-19 20:39:29 | D | sum error = [ 10.9390] +24-11-19 20:39:29 | D | best error = [ 10.9390] +24-11-19 20:39:30 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:30 | D | sum error = [ 10.8715, 10.8526, 10.8993, 11.0193, 11.2059] +24-11-19 20:39:30 | D | best error = [ 9.9277, 9.5581, 9.3781, 9.2725, 9.2158] +24-11-19 20:39:30 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:30 | D | sum error = [ 11.5395, 11.8868, 12.4034, 13.0098, 13.6873] +24-11-19 20:39:30 | D | best error = [ 9.1861, 9.1715, 9.1666, 9.1646, 9.1642] +24-11-19 20:39:30 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:30 | D | sum error = [ 14.4630, 15.3669, 16.3996, 17.5089, 18.6909] +24-11-19 20:39:30 | D | best error = [ 9.1641, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 20:39:30 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:30 | D | sum error = [ 20.0389, 21.4637, 22.9803, 24.6723, 26.4526] +24-11-19 20:39:30 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 20:39:30 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:30 | D | sum error = [ 28.3200, 30.3770, 32.5286, 34.8515, 37.2384] +24-11-19 20:39:30 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 20:39:30 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:30 | D | sum error = [ 39.8813, 42.5735, 45.5213, 48.5663, 51.7864] +24-11-19 20:39:30 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 20:39:30 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:30 | D | sum error = [ 55.2410, 58.8786, 62.7755, 66.8266, 71.1317] +24-11-19 20:39:30 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 20:39:30 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:30 | D | sum error = [ 75.6158, 80.4514, 85.4833, 90.7505, 96.3132] +24-11-19 20:39:30 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 20:39:30 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:30 | D | sum error = [ 102.2013, 108.3894, 114.8497, 121.6868, 128.8306] +24-11-19 20:39:30 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 20:39:30 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:30 | D | sum error = [ 136.3785, 144.2864, 152.5715, 161.2808, 170.4654] +24-11-19 20:39:30 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 20:39:30 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:30 | D | sum error = [ 180.0041, 190.0455, 200.5675, 211.5518, 223.1070] +24-11-19 20:39:30 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 20:39:30 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:30 | D | sum error = [ 235.1214, 247.7728, 260.9412, 274.7010, 289.1059] +24-11-19 20:39:30 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 20:39:30 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:30 | D | sum error = [ 304.1697, 319.8658, 336.2290, 353.3127, 371.1085] +24-11-19 20:39:30 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 20:39:30 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:30 | D | sum error = [ 389.6287, 408.8445, 428.8801, 449.7075, 471.3138] +24-11-19 20:39:30 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 20:39:30 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:30 | D | sum error = [ 493.7545, 516.9891, 541.1087, 566.0134, 591.7535] +24-11-19 20:39:30 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 20:39:30 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:30 | D | sum error = [ 618.3567, 645.8269, 674.1543, 703.3343, 733.3798] +24-11-19 20:39:30 | D | best error = [ 9.1640, 9.1640, 9.1640, 9.1640, 9.1640] +24-11-19 20:39:30 | D | + error = [9.1640] +24-11-19 20:39:30 | D | - Calibrating model.layers.25.mlp.down_proj.weight +24-11-19 20:39:30 | D | + w: sint8 +24-11-19 20:39:30 | D | + x: None +24-11-19 20:39:30 | D | + y: None +24-11-19 20:39:30 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:39:30 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:39:30 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:39:31 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:39:31 | D | - range ratio = [ 1.0000] +24-11-19 20:39:31 | D | sum error = [ 1.2566] +24-11-19 20:39:31 | D | best error = [ 1.2566] +24-11-19 20:39:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:32 | D | sum error = [ 1.2426, 1.2335, 1.2258, 1.2174, 1.2157] +24-11-19 20:39:32 | D | best error = [ 1.1997, 1.1738, 1.1563, 1.1431, 1.1320] +24-11-19 20:39:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:32 | D | sum error = [ 1.2157, 1.2193, 1.2244, 1.2385, 1.2572] +24-11-19 20:39:32 | D | best error = [ 1.1234, 1.1165, 1.1111, 1.1068, 1.1038] +24-11-19 20:39:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:32 | D | sum error = [ 1.2769, 1.3078, 1.3418, 1.3828, 1.4341] +24-11-19 20:39:32 | D | best error = [ 1.1017, 1.1002, 1.0992, 1.0984, 1.0977] +24-11-19 20:39:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:32 | D | sum error = [ 1.4954, 1.5604, 1.6349, 1.7236, 1.8224] +24-11-19 20:39:32 | D | best error = [ 1.0974, 1.0971, 1.0970, 1.0969, 1.0969] +24-11-19 20:39:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:32 | D | sum error = [ 1.9309, 2.0506, 2.1790, 2.3227, 2.4813] +24-11-19 20:39:32 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0969, 1.0969] +24-11-19 20:39:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:32 | D | sum error = [ 2.6467, 2.8321, 3.0310, 3.2444, 3.4717] +24-11-19 20:39:32 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0969, 1.0969] +24-11-19 20:39:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:32 | D | sum error = [ 3.7133, 3.9730, 4.2509, 4.5452, 4.8619] +24-11-19 20:39:32 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0969, 1.0969] +24-11-19 20:39:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:32 | D | sum error = [ 5.1957, 5.5513, 5.9295, 6.3300, 6.7550] +24-11-19 20:39:32 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0969, 1.0969] +24-11-19 20:39:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:32 | D | sum error = [ 7.2043, 7.6809, 8.1839, 8.7163, 9.2769] +24-11-19 20:39:32 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0969, 1.0969] +24-11-19 20:39:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:32 | D | sum error = [ 9.8737, 10.4989, 11.1606, 11.8559, 12.5894] +24-11-19 20:39:32 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0969, 1.0969] +24-11-19 20:39:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:32 | D | sum error = [ 13.3616, 14.1755, 15.0303, 15.9293, 16.8721] +24-11-19 20:39:32 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0969, 1.0969] +24-11-19 20:39:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:32 | D | sum error = [ 17.8622, 18.8981, 19.9862, 21.1246, 22.3175] +24-11-19 20:39:32 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0969, 1.0969] +24-11-19 20:39:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:32 | D | sum error = [ 23.5654, 24.8697, 26.2322, 27.6555, 29.1424] +24-11-19 20:39:32 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0969, 1.0969] +24-11-19 20:39:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:32 | D | sum error = [ 30.6919, 32.3055, 33.9863, 35.7381, 37.5585] +24-11-19 20:39:32 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0969, 1.0969] +24-11-19 20:39:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:32 | D | sum error = [ 39.4544, 41.4239, 43.4710, 45.5973, 47.8023] +24-11-19 20:39:32 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0969, 1.0969] +24-11-19 20:39:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:32 | D | sum error = [ 50.0892, 52.4600, 54.9129, 57.4514, 60.0764] +24-11-19 20:39:32 | D | best error = [ 1.0969, 1.0969, 1.0969, 1.0969, 1.0969] +24-11-19 20:39:32 | D | + error = [1.0969] +24-11-19 20:39:32 | D | - Quantizing model.layers.25.self_attn.q_proj.weight +24-11-19 20:39:33 | D | - Quantizing model.layers.25.self_attn.k_proj.weight +24-11-19 20:39:34 | D | - Quantizing model.layers.25.self_attn.v_proj.weight +24-11-19 20:39:34 | D | - Quantizing model.layers.25.self_attn.o_proj.weight +24-11-19 20:39:35 | D | - Quantizing model.layers.25.mlp.up_proj.weight +24-11-19 20:39:36 | D | - Quantizing model.layers.25.mlp.gate_proj.weight +24-11-19 20:39:37 | D | - Quantizing model.layers.25.mlp.down_proj.weight +24-11-19 20:39:47 | D | - Quantizing layer model.layers.26 +24-11-19 20:39:47 | D | - Calibrating model.layers.26.self_attn.q_proj.weight +24-11-19 20:39:47 | D | + w: sint8 +24-11-19 20:39:47 | D | + x: None +24-11-19 20:39:47 | D | + y: None +24-11-19 20:39:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:39:47 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:39:47 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:39:47 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:39:47 | D | - range ratio = [ 1.0000] +24-11-19 20:39:47 | D | sum error = [ 6.0002] +24-11-19 20:39:47 | D | best error = [ 6.0002] +24-11-19 20:39:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:39:59 | D | sum error = [ 6.1010, 5.7463, 5.9933, 6.1441, 6.0922] +24-11-19 20:39:59 | D | best error = [ 6.0002, 5.7463, 5.7463, 5.7463, 5.7463] +24-11-19 20:39:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:39:59 | D | sum error = [ 6.4921, 6.4595, 7.1581, 7.3611, 7.5397] +24-11-19 20:39:59 | D | best error = [ 5.7463, 5.7463, 5.7463, 5.7463, 5.7463] +24-11-19 20:39:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:39:59 | D | sum error = [ 8.1710, 8.9881, 9.1682, 9.8721, 10.6248] +24-11-19 20:39:59 | D | best error = [ 5.7463, 5.7463, 5.7463, 5.7463, 5.7463] +24-11-19 20:39:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:39:59 | D | sum error = [ 11.5412, 12.2710, 13.6448, 14.7161, 15.8926] +24-11-19 20:39:59 | D | best error = [ 5.7463, 5.7463, 5.7463, 5.7463, 5.7463] +24-11-19 20:39:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:39:59 | D | sum error = [ 17.4619, 18.9535, 20.3072, 21.9899, 23.9439] +24-11-19 20:39:59 | D | best error = [ 5.7463, 5.7463, 5.7463, 5.7463, 5.7463] +24-11-19 20:39:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:39:59 | D | sum error = [ 26.1103, 27.9602, 30.5758, 33.8367, 36.4875] +24-11-19 20:39:59 | D | best error = [ 5.7463, 5.7463, 5.7463, 5.7463, 5.7463] +24-11-19 20:39:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:39:59 | D | sum error = [ 39.8071, 42.7687, 47.2351, 51.1911, 55.5648] +24-11-19 20:39:59 | D | best error = [ 5.7463, 5.7463, 5.7463, 5.7463, 5.7463] +24-11-19 20:39:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:39:59 | D | sum error = [ 60.3220, 66.0151, 71.3072, 77.3125, 84.0982] +24-11-19 20:39:59 | D | best error = [ 5.7463, 5.7463, 5.7463, 5.7463, 5.7463] +24-11-19 20:39:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:39:59 | D | sum error = [ 90.9034, 98.9000, 107.2022, 116.2565, 125.6991] +24-11-19 20:39:59 | D | best error = [ 5.7463, 5.7463, 5.7463, 5.7463, 5.7463] +24-11-19 20:39:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:39:59 | D | sum error = [ 136.0524, 146.9562, 159.2898, 171.9231, 185.3178] +24-11-19 20:39:59 | D | best error = [ 5.7463, 5.7463, 5.7463, 5.7463, 5.7463] +24-11-19 20:39:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:39:59 | D | sum error = [ 199.6891, 214.9793, 231.0074, 248.6069, 267.0505] +24-11-19 20:39:59 | D | best error = [ 5.7463, 5.7463, 5.7463, 5.7463, 5.7463] +24-11-19 20:39:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:39:59 | D | sum error = [ 286.6949, 308.4269, 330.7383, 354.8061, 380.7139] +24-11-19 20:39:59 | D | best error = [ 5.7463, 5.7463, 5.7463, 5.7463, 5.7463] +24-11-19 20:39:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:39:59 | D | sum error = [ 407.9416, 437.3278, 467.8471, 500.9632, 536.4247] +24-11-19 20:39:59 | D | best error = [ 5.7463, 5.7463, 5.7463, 5.7463, 5.7463] +24-11-19 20:39:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:39:59 | D | sum error = [ 573.4123, 613.7985, 656.0074, 699.8788, 746.6858] +24-11-19 20:39:59 | D | best error = [ 5.7463, 5.7463, 5.7463, 5.7463, 5.7463] +24-11-19 20:39:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:39:59 | D | sum error = [ 796.6561, 848.9828, 903.8433, 961.3325, 1020.4163] +24-11-19 20:39:59 | D | best error = [ 5.7463, 5.7463, 5.7463, 5.7463, 5.7463] +24-11-19 20:39:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:39:59 | D | sum error = [ 1082.0268, 1144.8126, 1208.4194, 1272.6513, 1336.6773] +24-11-19 20:39:59 | D | best error = [ 5.7463, 5.7463, 5.7463, 5.7463, 5.7463] +24-11-19 20:39:59 | D | + error = [5.7463] +24-11-19 20:39:59 | D | - Calibrating model.layers.26.self_attn.k_proj.weight +24-11-19 20:39:59 | D | + w: sint8 +24-11-19 20:39:59 | D | + x: None +24-11-19 20:39:59 | D | + y: None +24-11-19 20:39:59 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:39:59 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:39:59 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:40:00 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:00 | D | - range ratio = [ 1.0000] +24-11-19 20:40:00 | D | sum error = [ 6.2976] +24-11-19 20:40:00 | D | best error = [ 6.2976] +24-11-19 20:40:13 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:13 | D | sum error = [ 6.0356, 6.9464, 7.0150, 6.7283, 5.7022] +24-11-19 20:40:13 | D | best error = [ 6.0356, 6.0356, 6.0356, 6.0356, 5.7022] +24-11-19 20:40:13 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:13 | D | sum error = [ 6.5321, 6.4152, 6.8259, 7.2772, 7.2606] +24-11-19 20:40:13 | D | best error = [ 5.7022, 5.7022, 5.7022, 5.7022, 5.7022] +24-11-19 20:40:13 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:13 | D | sum error = [ 8.1437, 9.3841, 11.6228, 10.1708, 10.6069] +24-11-19 20:40:13 | D | best error = [ 5.7022, 5.7022, 5.7022, 5.7022, 5.7022] +24-11-19 20:40:13 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:13 | D | sum error = [ 13.7951, 12.1183, 14.4648, 14.7992, 17.8740] +24-11-19 20:40:13 | D | best error = [ 5.7022, 5.7022, 5.7022, 5.7022, 5.7022] +24-11-19 20:40:13 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:13 | D | sum error = [ 17.8120, 18.8870, 19.5558, 21.3515, 23.3024] +24-11-19 20:40:13 | D | best error = [ 5.7022, 5.7022, 5.7022, 5.7022, 5.7022] +24-11-19 20:40:13 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:13 | D | sum error = [ 26.0322, 26.6084, 29.7084, 32.4669, 34.7219] +24-11-19 20:40:13 | D | best error = [ 5.7022, 5.7022, 5.7022, 5.7022, 5.7022] +24-11-19 20:40:13 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:13 | D | sum error = [ 37.4536, 40.6336, 44.3900, 46.9491, 50.9490] +24-11-19 20:40:13 | D | best error = [ 5.7022, 5.7022, 5.7022, 5.7022, 5.7022] +24-11-19 20:40:13 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:13 | D | sum error = [ 55.7389, 60.3216, 64.2629, 70.0232, 75.8684] +24-11-19 20:40:13 | D | best error = [ 5.7022, 5.7022, 5.7022, 5.7022, 5.7022] +24-11-19 20:40:13 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:13 | D | sum error = [ 81.4909, 86.4874, 95.3641, 101.1995, 111.7281] +24-11-19 20:40:13 | D | best error = [ 5.7022, 5.7022, 5.7022, 5.7022, 5.7022] +24-11-19 20:40:13 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:13 | D | sum error = [ 118.3743, 128.6062, 135.9630, 147.7237, 158.8969] +24-11-19 20:40:13 | D | best error = [ 5.7022, 5.7022, 5.7022, 5.7022, 5.7022] +24-11-19 20:40:13 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:13 | D | sum error = [ 171.1042, 183.9673, 197.8550, 213.3188, 230.3147] +24-11-19 20:40:13 | D | best error = [ 5.7022, 5.7022, 5.7022, 5.7022, 5.7022] +24-11-19 20:40:13 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:13 | D | sum error = [ 247.6647, 265.9628, 286.5003, 306.0597, 327.0509] +24-11-19 20:40:13 | D | best error = [ 5.7022, 5.7022, 5.7022, 5.7022, 5.7022] +24-11-19 20:40:13 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:13 | D | sum error = [ 351.9519, 376.6993, 403.2001, 432.9095, 464.1616] +24-11-19 20:40:13 | D | best error = [ 5.7022, 5.7022, 5.7022, 5.7022, 5.7022] +24-11-19 20:40:13 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:13 | D | sum error = [ 499.4736, 535.5862, 572.6523, 613.3296, 655.7716] +24-11-19 20:40:13 | D | best error = [ 5.7022, 5.7022, 5.7022, 5.7022, 5.7022] +24-11-19 20:40:13 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:13 | D | sum error = [ 701.4789, 750.3827, 802.3699, 856.8515, 914.4910] +24-11-19 20:40:13 | D | best error = [ 5.7022, 5.7022, 5.7022, 5.7022, 5.7022] +24-11-19 20:40:13 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:13 | D | sum error = [ 974.9937, 1039.0892, 1106.4223, 1175.6959, 1245.3363] +24-11-19 20:40:13 | D | best error = [ 5.7022, 5.7022, 5.7022, 5.7022, 5.7022] +24-11-19 20:40:13 | D | + error = [5.7022] +24-11-19 20:40:13 | D | - Calibrating model.layers.26.self_attn.v_proj.weight +24-11-19 20:40:13 | D | + w: sint8 +24-11-19 20:40:13 | D | + x: None +24-11-19 20:40:13 | D | + y: None +24-11-19 20:40:13 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:13 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:40:13 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:40:13 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:40:13 | D | - range ratio = [ 1.0000] +24-11-19 20:40:13 | D | sum error = [ 2.4249] +24-11-19 20:40:13 | D | best error = [ 2.4249] +24-11-19 20:40:13 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:13 | D | sum error = [ 2.4027, 2.3859, 2.3804, 2.4440, 2.4703] +24-11-19 20:40:13 | D | best error = [ 2.1891, 2.1095, 2.0654, 2.0439, 2.0304] +24-11-19 20:40:13 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:13 | D | sum error = [ 2.5184, 2.6041, 2.7200, 2.8820, 3.0010] +24-11-19 20:40:13 | D | best error = [ 2.0217, 2.0191, 2.0177, 2.0170, 2.0169] +24-11-19 20:40:13 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:13 | D | sum error = [ 3.1474, 3.3889, 3.6177, 3.8173, 4.1185] +24-11-19 20:40:13 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:40:13 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:13 | D | sum error = [ 4.3624, 4.6831, 5.0141, 5.3883, 5.7598] +24-11-19 20:40:13 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:40:13 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:13 | D | sum error = [ 6.1458, 6.6018, 7.0413, 7.5300, 8.0441] +24-11-19 20:40:13 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:40:13 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:13 | D | sum error = [ 8.5915, 9.1705, 9.7763, 10.4125, 11.1030] +24-11-19 20:40:13 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:40:13 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:13 | D | sum error = [ 11.7862, 12.5278, 13.3888, 14.1815, 15.0889] +24-11-19 20:40:13 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:40:13 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:13 | D | sum error = [ 16.0151, 16.9864, 17.9854, 19.0755, 20.1666] +24-11-19 20:40:13 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:40:13 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:13 | D | sum error = [ 21.3657, 22.5486, 23.8775, 25.1964, 26.6120] +24-11-19 20:40:13 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:40:13 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:13 | D | sum error = [ 28.0868, 29.6176, 31.2252, 32.9023, 34.6400] +24-11-19 20:40:13 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:40:13 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:13 | D | sum error = [ 36.4523, 38.3269, 40.2835, 42.3022, 44.4401] +24-11-19 20:40:13 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:40:13 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:13 | D | sum error = [ 46.6344, 48.9188, 51.2749, 53.7254, 56.2677] +24-11-19 20:40:13 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:40:13 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:13 | D | sum error = [ 58.8857, 61.5871, 64.3788, 67.2621, 70.2338] +24-11-19 20:40:13 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:40:13 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:13 | D | sum error = [ 73.3062, 76.4562, 79.7197, 83.0887, 86.5360] +24-11-19 20:40:13 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:40:13 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:13 | D | sum error = [ 90.0957, 93.7652, 97.5347, 101.4225, 105.4152] +24-11-19 20:40:13 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:40:13 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:13 | D | sum error = [ 109.5307, 113.7386, 118.0588, 122.4709, 126.9957] +24-11-19 20:40:13 | D | best error = [ 2.0169, 2.0169, 2.0169, 2.0169, 2.0169] +24-11-19 20:40:13 | D | + error = [2.0169] +24-11-19 20:40:13 | D | - Calibrating model.layers.26.self_attn.o_proj.weight +24-11-19 20:40:13 | D | + w: sint8 +24-11-19 20:40:13 | D | + x: None +24-11-19 20:40:13 | D | + y: None +24-11-19 20:40:13 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:13 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:40:13 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:40:13 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:13 | D | - range ratio = [ 1.0000] +24-11-19 20:40:13 | D | sum error = [ 0.5937] +24-11-19 20:40:13 | D | best error = [ 0.5937] +24-11-19 20:40:14 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:14 | D | sum error = [ 0.5903, 0.5886, 0.5891, 0.5923, 0.5980] +24-11-19 20:40:14 | D | best error = [ 0.5494, 0.5295, 0.5178, 0.5101, 0.5048] +24-11-19 20:40:14 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:14 | D | sum error = [ 0.6105, 0.6266, 0.6472, 0.6712, 0.7010] +24-11-19 20:40:14 | D | best error = [ 0.5013, 0.4988, 0.4970, 0.4959, 0.4950] +24-11-19 20:40:14 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:14 | D | sum error = [ 0.7331, 0.7704, 0.8132, 0.8621, 0.9171] +24-11-19 20:40:14 | D | best error = [ 0.4944, 0.4938, 0.4934, 0.4931, 0.4929] +24-11-19 20:40:14 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:14 | D | sum error = [ 0.9737, 1.0381, 1.1044, 1.1802, 1.2563] +24-11-19 20:40:14 | D | best error = [ 0.4927, 0.4926, 0.4925, 0.4925, 0.4925] +24-11-19 20:40:14 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:14 | D | sum error = [ 1.3407, 1.4306, 1.5290, 1.6320, 1.7405] +24-11-19 20:40:14 | D | best error = [ 0.4925, 0.4925, 0.4925, 0.4924, 0.4924] +24-11-19 20:40:14 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:14 | D | sum error = [ 1.8540, 1.9761, 2.1063, 2.2426, 2.3891] +24-11-19 20:40:14 | D | best error = [ 0.4924, 0.4924, 0.4924, 0.4924, 0.4924] +24-11-19 20:40:14 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:14 | D | sum error = [ 2.5408, 2.7006, 2.8686, 3.0500, 3.2380] +24-11-19 20:40:14 | D | best error = [ 0.4924, 0.4924, 0.4924, 0.4924, 0.4924] +24-11-19 20:40:14 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:14 | D | sum error = [ 3.4346, 3.6432, 3.8633, 4.0935, 4.3400] +24-11-19 20:40:14 | D | best error = [ 0.4924, 0.4924, 0.4924, 0.4924, 0.4924] +24-11-19 20:40:14 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:14 | D | sum error = [ 4.5970, 4.8664, 5.1485, 5.4441, 5.7565] +24-11-19 20:40:14 | D | best error = [ 0.4924, 0.4924, 0.4924, 0.4924, 0.4924] +24-11-19 20:40:14 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:14 | D | sum error = [ 6.0810, 6.4247, 6.7816, 7.1575, 7.5482] +24-11-19 20:40:14 | D | best error = [ 0.4924, 0.4924, 0.4924, 0.4924, 0.4924] +24-11-19 20:40:14 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:14 | D | sum error = [ 7.9605, 8.3905, 8.8404, 9.3079, 9.7982] +24-11-19 20:40:14 | D | best error = [ 0.4924, 0.4924, 0.4924, 0.4924, 0.4924] +24-11-19 20:40:14 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:14 | D | sum error = [ 10.3110, 10.8491, 11.4086, 11.9929, 12.6039] +24-11-19 20:40:14 | D | best error = [ 0.4924, 0.4924, 0.4924, 0.4924, 0.4924] +24-11-19 20:40:14 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:14 | D | sum error = [ 13.2411, 13.9024, 14.5921, 15.3136, 16.0629] +24-11-19 20:40:14 | D | best error = [ 0.4924, 0.4924, 0.4924, 0.4924, 0.4924] +24-11-19 20:40:14 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:14 | D | sum error = [ 16.8418, 17.6523, 18.4933, 19.3686, 20.2775] +24-11-19 20:40:14 | D | best error = [ 0.4924, 0.4924, 0.4924, 0.4924, 0.4924] +24-11-19 20:40:14 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:14 | D | sum error = [ 21.2204, 22.2001, 23.2150, 24.2675, 25.3548] +24-11-19 20:40:14 | D | best error = [ 0.4924, 0.4924, 0.4924, 0.4924, 0.4924] +24-11-19 20:40:14 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:14 | D | sum error = [ 26.4795, 27.6441, 28.8471, 30.0904, 31.3733] +24-11-19 20:40:14 | D | best error = [ 0.4924, 0.4924, 0.4924, 0.4924, 0.4924] +24-11-19 20:40:14 | D | + error = [0.4924] +24-11-19 20:40:14 | D | - Calibrating model.layers.26.mlp.up_proj.weight +24-11-19 20:40:14 | D | + w: sint8 +24-11-19 20:40:14 | D | + x: None +24-11-19 20:40:14 | D | + y: None +24-11-19 20:40:14 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:14 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:40:14 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:40:14 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:14 | D | - range ratio = [ 1.0000] +24-11-19 20:40:14 | D | sum error = [ 8.5111] +24-11-19 20:40:14 | D | best error = [ 8.5111] +24-11-19 20:40:15 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:15 | D | sum error = [ 8.4647, 8.4662, 8.4778, 8.5785, 8.7326] +24-11-19 20:40:15 | D | best error = [ 7.6647, 7.3564, 7.2006, 7.1141, 7.0648] +24-11-19 20:40:15 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:15 | D | sum error = [ 8.9638, 9.2935, 9.6225, 10.1186, 10.6314] +24-11-19 20:40:15 | D | best error = [ 7.0424, 7.0326, 7.0280, 7.0268, 7.0265] +24-11-19 20:40:15 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:15 | D | sum error = [ 11.2432, 11.9310, 12.7132, 13.5464, 14.4966] +24-11-19 20:40:15 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 20:40:15 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:15 | D | sum error = [ 15.4788, 16.6050, 17.7984, 19.1016, 20.4341] +24-11-19 20:40:15 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 20:40:15 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:15 | D | sum error = [ 21.9096, 23.4328, 25.0484, 26.8097, 28.6372] +24-11-19 20:40:15 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 20:40:15 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:15 | D | sum error = [ 30.5706, 32.6484, 34.8090, 37.0907, 39.5128] +24-11-19 20:40:15 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 20:40:15 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:15 | D | sum error = [ 42.0862, 44.7785, 47.6259, 50.6266, 53.7419] +24-11-19 20:40:15 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 20:40:15 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:15 | D | sum error = [ 57.0055, 60.4641, 64.0967, 67.8837, 71.8587] +24-11-19 20:40:15 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 20:40:15 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:15 | D | sum error = [ 76.0163, 80.3731, 84.9013, 89.6991, 94.6542] +24-11-19 20:40:15 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 20:40:15 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:15 | D | sum error = [ 99.8571, 105.2965, 110.9682, 116.8444, 122.9859] +24-11-19 20:40:15 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 20:40:15 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:15 | D | sum error = [ 129.3507, 136.0090, 142.9073, 150.0793, 157.5424] +24-11-19 20:40:15 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 20:40:15 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:15 | D | sum error = [ 165.2499, 173.2667, 181.5491, 190.1427, 199.0432] +24-11-19 20:40:15 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 20:40:15 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:15 | D | sum error = [ 208.2406, 217.7591, 227.6066, 237.7610, 248.2352] +24-11-19 20:40:15 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 20:40:15 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:15 | D | sum error = [ 259.0587, 270.2155, 281.7107, 293.5614, 305.7420] +24-11-19 20:40:15 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 20:40:15 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:15 | D | sum error = [ 318.2720, 331.2023, 344.4946, 358.1586, 372.2061] +24-11-19 20:40:15 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 20:40:15 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:15 | D | sum error = [ 386.6248, 401.4381, 416.6388, 432.2247, 448.2364] +24-11-19 20:40:15 | D | best error = [ 7.0264, 7.0264, 7.0264, 7.0264, 7.0264] +24-11-19 20:40:15 | D | + error = [7.0264] +24-11-19 20:40:16 | D | - Calibrating model.layers.26.mlp.gate_proj.weight +24-11-19 20:40:16 | D | + w: sint8 +24-11-19 20:40:16 | D | + x: None +24-11-19 20:40:16 | D | + y: None +24-11-19 20:40:16 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:16 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:40:16 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:40:16 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:16 | D | - range ratio = [ 1.0000] +24-11-19 20:40:16 | D | sum error = [ 11.4900] +24-11-19 20:40:16 | D | best error = [ 11.4900] +24-11-19 20:40:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:17 | D | sum error = [ 11.3945, 11.3913, 11.4390, 11.5478, 11.7258] +24-11-19 20:40:17 | D | best error = [ 10.3060, 9.9040, 9.7028, 9.5835, 9.5156] +24-11-19 20:40:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:17 | D | sum error = [ 12.0931, 12.5046, 12.9554, 13.5917, 14.3245] +24-11-19 20:40:17 | D | best error = [ 9.4842, 9.4703, 9.4640, 9.4621, 9.4618] +24-11-19 20:40:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:17 | D | sum error = [ 15.1527, 16.0660, 17.0957, 18.2940, 19.5192] +24-11-19 20:40:17 | D | best error = [ 9.4616, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:40:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:17 | D | sum error = [ 20.9233, 22.3680, 23.9590, 25.6658, 27.5290] +24-11-19 20:40:17 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:40:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:17 | D | sum error = [ 29.4936, 31.5976, 33.8330, 36.1941, 38.7601] +24-11-19 20:40:17 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:40:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:17 | D | sum error = [ 41.4289, 44.2758, 47.3069, 50.5187, 53.9301] +24-11-19 20:40:17 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:40:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:17 | D | sum error = [ 57.4772, 61.2773, 65.3482, 69.5292, 74.0567] +24-11-19 20:40:17 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:40:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:17 | D | sum error = [ 78.7962, 83.8380, 89.1153, 94.7151, 100.5976] +24-11-19 20:40:17 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:40:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:17 | D | sum error = [ 106.8002, 113.3107, 120.2059, 127.4744, 135.0939] +24-11-19 20:40:17 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:40:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:17 | D | sum error = [ 143.1079, 151.5231, 160.3812, 169.7012, 179.4750] +24-11-19 20:40:17 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:40:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:17 | D | sum error = [ 189.7321, 200.5067, 211.8079, 223.6816, 236.0903] +24-11-19 20:40:17 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:40:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:17 | D | sum error = [ 249.1426, 262.8278, 277.1276, 292.0490, 307.6355] +24-11-19 20:40:17 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:40:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:17 | D | sum error = [ 323.9595, 340.9926, 358.6852, 377.2197, 396.4799] +24-11-19 20:40:17 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:40:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:17 | D | sum error = [ 416.5641, 437.4975, 459.2338, 481.8355, 505.3322] +24-11-19 20:40:17 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:40:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:17 | D | sum error = [ 529.7065, 554.9113, 581.0786, 608.1561, 636.2250] +24-11-19 20:40:17 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:40:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:17 | D | sum error = [ 665.2108, 695.1562, 726.0955, 758.0551, 790.9218] +24-11-19 20:40:17 | D | best error = [ 9.4615, 9.4615, 9.4615, 9.4615, 9.4615] +24-11-19 20:40:17 | D | + error = [9.4615] +24-11-19 20:40:17 | D | - Calibrating model.layers.26.mlp.down_proj.weight +24-11-19 20:40:17 | D | + w: sint8 +24-11-19 20:40:17 | D | + x: None +24-11-19 20:40:17 | D | + y: None +24-11-19 20:40:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:40:17 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:40:17 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:40:17 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:17 | D | - range ratio = [ 1.0000] +24-11-19 20:40:17 | D | sum error = [ 1.3492] +24-11-19 20:40:17 | D | best error = [ 1.3492] +24-11-19 20:40:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:18 | D | sum error = [ 1.3382, 1.3239, 1.3171, 1.3114, 1.3057] +24-11-19 20:40:18 | D | best error = [ 1.2919, 1.2619, 1.2426, 1.2284, 1.2167] +24-11-19 20:40:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:18 | D | sum error = [ 1.3047, 1.3120, 1.3168, 1.3302, 1.3473] +24-11-19 20:40:18 | D | best error = [ 1.2073, 1.2005, 1.1950, 1.1910, 1.1880] +24-11-19 20:40:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:18 | D | sum error = [ 1.3742, 1.4017, 1.4397, 1.4830, 1.5366] +24-11-19 20:40:18 | D | best error = [ 1.1858, 1.1841, 1.1829, 1.1821, 1.1815] +24-11-19 20:40:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:18 | D | sum error = [ 1.5985, 1.6692, 1.7515, 1.8444, 1.9461] +24-11-19 20:40:18 | D | best error = [ 1.1811, 1.1809, 1.1808, 1.1807, 1.1807] +24-11-19 20:40:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:18 | D | sum error = [ 2.0596, 2.1840, 2.3227, 2.4738, 2.6371] +24-11-19 20:40:18 | D | best error = [ 1.1807, 1.1807, 1.1807, 1.1806, 1.1806] +24-11-19 20:40:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:18 | D | sum error = [ 2.8147, 3.0063, 3.2101, 3.4354, 3.6739] +24-11-19 20:40:18 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 20:40:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:18 | D | sum error = [ 3.9281, 4.2026, 4.4962, 4.8064, 5.1398] +24-11-19 20:40:18 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 20:40:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:18 | D | sum error = [ 5.4947, 5.8731, 6.2717, 6.6943, 7.1465] +24-11-19 20:40:18 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 20:40:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:18 | D | sum error = [ 7.6254, 8.1319, 8.6690, 9.2373, 9.8361] +24-11-19 20:40:18 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 20:40:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:18 | D | sum error = [ 10.4696, 11.1394, 11.8458, 12.5902, 13.3730] +24-11-19 20:40:18 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 20:40:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:18 | D | sum error = [ 14.1981, 15.0673, 15.9828, 16.9437, 17.9532] +24-11-19 20:40:18 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 20:40:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:18 | D | sum error = [ 19.0132, 20.1249, 21.2927, 22.5155, 23.7977] +24-11-19 20:40:18 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 20:40:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:18 | D | sum error = [ 25.1362, 26.5379, 28.0006, 29.5311, 31.1302] +24-11-19 20:40:18 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 20:40:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:18 | D | sum error = [ 32.7950, 34.5323, 36.3423, 38.2279, 40.1898] +24-11-19 20:40:18 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 20:40:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:18 | D | sum error = [ 42.2299, 44.3515, 46.5530, 48.8384, 51.2096] +24-11-19 20:40:18 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 20:40:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:18 | D | sum error = [ 53.6677, 56.2157, 58.8524, 61.5802, 64.4018] +24-11-19 20:40:18 | D | best error = [ 1.1806, 1.1806, 1.1806, 1.1806, 1.1806] +24-11-19 20:40:18 | D | + error = [1.1806] +24-11-19 20:40:19 | D | - Quantizing model.layers.26.self_attn.q_proj.weight +24-11-19 20:40:19 | D | - Quantizing model.layers.26.self_attn.k_proj.weight +24-11-19 20:40:20 | D | - Quantizing model.layers.26.self_attn.v_proj.weight +24-11-19 20:40:21 | D | - Quantizing model.layers.26.self_attn.o_proj.weight +24-11-19 20:40:22 | D | - Quantizing model.layers.26.mlp.up_proj.weight +24-11-19 20:40:23 | D | - Quantizing model.layers.26.mlp.gate_proj.weight +24-11-19 20:40:24 | D | - Quantizing model.layers.26.mlp.down_proj.weight +24-11-19 20:40:34 | D | - Quantizing layer model.layers.27 +24-11-19 20:40:34 | D | - Calibrating model.layers.27.self_attn.q_proj.weight +24-11-19 20:40:34 | D | + w: sint8 +24-11-19 20:40:34 | D | + x: None +24-11-19 20:40:34 | D | + y: None +24-11-19 20:40:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:40:34 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:40:34 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:40:34 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:34 | D | - range ratio = [ 1.0000] +24-11-19 20:40:34 | D | sum error = [ 7.1721] +24-11-19 20:40:34 | D | best error = [ 7.1721] +24-11-19 20:40:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:46 | D | sum error = [ 7.1315, 7.2399, 7.1428, 7.6355, 7.6340] +24-11-19 20:40:46 | D | best error = [ 7.1315, 7.1315, 7.1315, 7.1315, 7.1315] +24-11-19 20:40:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:46 | D | sum error = [ 7.8985, 7.6561, 8.5153, 8.5329, 9.2429] +24-11-19 20:40:46 | D | best error = [ 7.1315, 7.1315, 7.1315, 7.1315, 7.1315] +24-11-19 20:40:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:46 | D | sum error = [ 9.4497, 10.1764, 11.1549, 11.7957, 12.7191] +24-11-19 20:40:46 | D | best error = [ 7.1315, 7.1315, 7.1315, 7.1315, 7.1315] +24-11-19 20:40:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:46 | D | sum error = [ 13.7559, 15.2427, 16.0253, 16.9679, 19.4545] +24-11-19 20:40:46 | D | best error = [ 7.1315, 7.1315, 7.1315, 7.1315, 7.1315] +24-11-19 20:40:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:46 | D | sum error = [ 20.9492, 22.2764, 24.3649, 26.4382, 28.7067] +24-11-19 20:40:46 | D | best error = [ 7.1315, 7.1315, 7.1315, 7.1315, 7.1315] +24-11-19 20:40:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:46 | D | sum error = [ 30.7440, 33.6101, 36.5176, 39.5295, 42.3947] +24-11-19 20:40:46 | D | best error = [ 7.1315, 7.1315, 7.1315, 7.1315, 7.1315] +24-11-19 20:40:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:46 | D | sum error = [ 46.3355, 50.0748, 54.1627, 58.3978, 63.4271] +24-11-19 20:40:46 | D | best error = [ 7.1315, 7.1315, 7.1315, 7.1315, 7.1315] +24-11-19 20:40:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:46 | D | sum error = [ 68.6756, 74.1333, 80.2929, 86.8843, 93.8806] +24-11-19 20:40:46 | D | best error = [ 7.1315, 7.1315, 7.1315, 7.1315, 7.1315] +24-11-19 20:40:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:46 | D | sum error = [ 101.5760, 110.3248, 119.2788, 129.0796, 139.6270] +24-11-19 20:40:46 | D | best error = [ 7.1315, 7.1315, 7.1315, 7.1315, 7.1315] +24-11-19 20:40:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:46 | D | sum error = [ 151.1932, 163.4707, 176.8240, 190.4748, 206.0755] +24-11-19 20:40:46 | D | best error = [ 7.1315, 7.1315, 7.1315, 7.1315, 7.1315] +24-11-19 20:40:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:46 | D | sum error = [ 222.5029, 240.2507, 259.3014, 279.7378, 301.9615] +24-11-19 20:40:46 | D | best error = [ 7.1315, 7.1315, 7.1315, 7.1315, 7.1315] +24-11-19 20:40:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:46 | D | sum error = [ 326.5479, 352.6151, 381.4333, 412.1652, 445.4852] +24-11-19 20:40:46 | D | best error = [ 7.1315, 7.1315, 7.1315, 7.1315, 7.1315] +24-11-19 20:40:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:46 | D | sum error = [ 483.0135, 523.4137, 568.2342, 617.1338, 672.6135] +24-11-19 20:40:46 | D | best error = [ 7.1315, 7.1315, 7.1315, 7.1315, 7.1315] +24-11-19 20:40:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:46 | D | sum error = [ 732.4712, 799.8641, 873.2426, 955.4484, 1046.5515] +24-11-19 20:40:46 | D | best error = [ 7.1315, 7.1315, 7.1315, 7.1315, 7.1315] +24-11-19 20:40:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:46 | D | sum error = [ 1147.0258, 1257.9134, 1381.5398, 1515.2855, 1657.3412] +24-11-19 20:40:46 | D | best error = [ 7.1315, 7.1315, 7.1315, 7.1315, 7.1315] +24-11-19 20:40:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:46 | D | sum error = [ 1809.4578, 1972.1741, 2144.0250, 2316.4716, 2493.4314] +24-11-19 20:40:46 | D | best error = [ 7.1315, 7.1315, 7.1315, 7.1315, 7.1315] +24-11-19 20:40:46 | D | + error = [7.1315] +24-11-19 20:40:46 | D | - Calibrating model.layers.27.self_attn.k_proj.weight +24-11-19 20:40:46 | D | + w: sint8 +24-11-19 20:40:46 | D | + x: None +24-11-19 20:40:46 | D | + y: None +24-11-19 20:40:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:40:46 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:40:46 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:40:47 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:40:47 | D | - range ratio = [ 1.0000] +24-11-19 20:40:47 | D | sum error = [ 6.9598] +24-11-19 20:40:47 | D | best error = [ 6.9598] +24-11-19 20:40:59 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:40:59 | D | sum error = [ 7.0727, 7.0314, 7.2690, 7.5975, 8.1124] +24-11-19 20:40:59 | D | best error = [ 6.9598, 6.9598, 6.9598, 6.9598, 6.9598] +24-11-19 20:40:59 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:40:59 | D | sum error = [ 7.1993, 8.1672, 8.0404, 8.6613, 10.6263] +24-11-19 20:40:59 | D | best error = [ 6.9598, 6.9598, 6.9598, 6.9598, 6.9598] +24-11-19 20:40:59 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:40:59 | D | sum error = [ 9.9372, 10.1553, 11.0127, 11.3096, 13.4458] +24-11-19 20:40:59 | D | best error = [ 6.9598, 6.9598, 6.9598, 6.9598, 6.9598] +24-11-19 20:40:59 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:40:59 | D | sum error = [ 14.7548, 15.0656, 16.5570, 18.2713, 18.6503] +24-11-19 20:40:59 | D | best error = [ 6.9598, 6.9598, 6.9598, 6.9598, 6.9598] +24-11-19 20:40:59 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:40:59 | D | sum error = [ 20.3733, 20.9971, 23.5841, 24.2220, 25.9533] +24-11-19 20:40:59 | D | best error = [ 6.9598, 6.9598, 6.9598, 6.9598, 6.9598] +24-11-19 20:40:59 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:40:59 | D | sum error = [ 28.3041, 30.1081, 33.0051, 35.7587, 38.9222] +24-11-19 20:40:59 | D | best error = [ 6.9598, 6.9598, 6.9598, 6.9598, 6.9598] +24-11-19 20:40:59 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:40:59 | D | sum error = [ 41.1746, 45.1746, 47.9992, 52.6325, 56.6255] +24-11-19 20:40:59 | D | best error = [ 6.9598, 6.9598, 6.9598, 6.9598, 6.9598] +24-11-19 20:40:59 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:40:59 | D | sum error = [ 61.7629, 65.9712, 72.1174, 77.8865, 84.0888] +24-11-19 20:40:59 | D | best error = [ 6.9598, 6.9598, 6.9598, 6.9598, 6.9598] +24-11-19 20:40:59 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:40:59 | D | sum error = [ 91.5639, 99.2589, 107.3961, 116.2228, 125.0843] +24-11-19 20:40:59 | D | best error = [ 6.9598, 6.9598, 6.9598, 6.9598, 6.9598] +24-11-19 20:40:59 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:40:59 | D | sum error = [ 135.7105, 147.3035, 157.6510, 169.4053, 182.2244] +24-11-19 20:40:59 | D | best error = [ 6.9598, 6.9598, 6.9598, 6.9598, 6.9598] +24-11-19 20:40:59 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:40:59 | D | sum error = [ 197.7555, 213.0403, 230.1551, 249.8323, 268.9836] +24-11-19 20:40:59 | D | best error = [ 6.9598, 6.9598, 6.9598, 6.9598, 6.9598] +24-11-19 20:40:59 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:40:59 | D | sum error = [ 293.7194, 319.5589, 346.6281, 377.9255, 410.8322] +24-11-19 20:40:59 | D | best error = [ 6.9598, 6.9598, 6.9598, 6.9598, 6.9598] +24-11-19 20:40:59 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:40:59 | D | sum error = [ 447.5792, 488.9415, 534.4336, 585.3434, 642.1186] +24-11-19 20:40:59 | D | best error = [ 6.9598, 6.9598, 6.9598, 6.9598, 6.9598] +24-11-19 20:40:59 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:40:59 | D | sum error = [ 707.0315, 779.7932, 858.5156, 946.8265, 1043.0815] +24-11-19 20:40:59 | D | best error = [ 6.9598, 6.9598, 6.9598, 6.9598, 6.9598] +24-11-19 20:40:59 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:40:59 | D | sum error = [ 1147.8813, 1265.4367, 1391.9224, 1535.3223, 1687.5376] +24-11-19 20:40:59 | D | best error = [ 6.9598, 6.9598, 6.9598, 6.9598, 6.9598] +24-11-19 20:40:59 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:40:59 | D | sum error = [ 1852.4881, 2026.5529, 2205.4374, 2385.2460, 2569.1009] +24-11-19 20:40:59 | D | best error = [ 6.9598, 6.9598, 6.9598, 6.9598, 6.9598] +24-11-19 20:40:59 | D | + error = [6.9598] +24-11-19 20:41:00 | D | - Calibrating model.layers.27.self_attn.v_proj.weight +24-11-19 20:41:00 | D | + w: sint8 +24-11-19 20:41:00 | D | + x: None +24-11-19 20:41:00 | D | + y: None +24-11-19 20:41:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:00 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:41:00 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:41:00 | D | + finished calculating the original outputs, ram usage: 13.4 +24-11-19 20:41:00 | D | - range ratio = [ 1.0000] +24-11-19 20:41:00 | D | sum error = [ 2.8438] +24-11-19 20:41:00 | D | best error = [ 2.8438] +24-11-19 20:41:00 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:00 | D | sum error = [ 2.8470, 2.8217, 2.8617, 2.8917, 2.9298] +24-11-19 20:41:00 | D | best error = [ 2.5791, 2.4737, 2.4216, 2.3971, 2.3821] +24-11-19 20:41:00 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:00 | D | sum error = [ 3.0268, 3.1050, 3.2660, 3.4134, 3.5480] +24-11-19 20:41:00 | D | best error = [ 2.3731, 2.3690, 2.3677, 2.3675, 2.3673] +24-11-19 20:41:00 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:00 | D | sum error = [ 3.8006, 4.0423, 4.2361, 4.5295, 4.8174] +24-11-19 20:41:00 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 20:41:00 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:00 | D | sum error = [ 5.2143, 5.5331, 5.9921, 6.3636, 6.8299] +24-11-19 20:41:00 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 20:41:00 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:00 | D | sum error = [ 7.3034, 7.8224, 8.3135, 8.9209, 9.5157] +24-11-19 20:41:00 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 20:41:00 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:00 | D | sum error = [ 10.1718, 10.8624, 11.5933, 12.3098, 13.1390] +24-11-19 20:41:00 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 20:41:00 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:00 | D | sum error = [ 13.9499, 14.8479, 15.7990, 16.7772, 17.7979] +24-11-19 20:41:00 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 20:41:00 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:00 | D | sum error = [ 18.8991, 20.0690, 21.2853, 22.5942, 23.9043] +24-11-19 20:41:00 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 20:41:00 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:00 | D | sum error = [ 25.3140, 26.7916, 28.3030, 29.9325, 31.6330] +24-11-19 20:41:00 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 20:41:00 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:00 | D | sum error = [ 33.4237, 35.2605, 37.2276, 39.2153, 41.3594] +24-11-19 20:41:00 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 20:41:00 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:00 | D | sum error = [ 43.5383, 45.8564, 48.2639, 50.7603, 53.3674] +24-11-19 20:41:00 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 20:41:00 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:00 | D | sum error = [ 56.0701, 58.9030, 61.8105, 64.8755, 68.0406] +24-11-19 20:41:00 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 20:41:00 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:00 | D | sum error = [ 71.3435, 74.7328, 78.2826, 81.9151, 85.7111] +24-11-19 20:41:00 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 20:41:00 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:00 | D | sum error = [ 89.6385, 93.6642, 97.8454, 102.1617, 106.6403] +24-11-19 20:41:00 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 20:41:00 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:00 | D | sum error = [ 111.2458, 116.0270, 120.9536, 126.0164, 131.2298] +24-11-19 20:41:00 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 20:41:00 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:00 | D | sum error = [ 136.6077, 142.1438, 147.8448, 153.6985, 159.7157] +24-11-19 20:41:00 | D | best error = [ 2.3672, 2.3672, 2.3672, 2.3672, 2.3672] +24-11-19 20:41:00 | D | + error = [2.3672] +24-11-19 20:41:00 | D | - Calibrating model.layers.27.self_attn.o_proj.weight +24-11-19 20:41:00 | D | + w: sint8 +24-11-19 20:41:00 | D | + x: None +24-11-19 20:41:00 | D | + y: None +24-11-19 20:41:00 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:00 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:41:00 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:41:00 | D | + finished calculating the original outputs, ram usage: 13.4 +24-11-19 20:41:00 | D | - range ratio = [ 1.0000] +24-11-19 20:41:00 | D | sum error = [ 0.6494] +24-11-19 20:41:00 | D | best error = [ 0.6494] +24-11-19 20:41:01 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:01 | D | sum error = [ 0.6453, 0.6425, 0.6443, 0.6530, 0.6581] +24-11-19 20:41:01 | D | best error = [ 0.5934, 0.5697, 0.5562, 0.5480, 0.5422] +24-11-19 20:41:01 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:01 | D | sum error = [ 0.6742, 0.6977, 0.7195, 0.7476, 0.7832] +24-11-19 20:41:01 | D | best error = [ 0.5384, 0.5362, 0.5347, 0.5337, 0.5331] +24-11-19 20:41:01 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:01 | D | sum error = [ 0.8237, 0.8683, 0.9199, 0.9762, 1.0380] +24-11-19 20:41:01 | D | best error = [ 0.5328, 0.5324, 0.5323, 0.5321, 0.5321] +24-11-19 20:41:01 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:01 | D | sum error = [ 1.1030, 1.1722, 1.2504, 1.3311, 1.4218] +24-11-19 20:41:01 | D | best error = [ 0.5320, 0.5320, 0.5320, 0.5320, 0.5319] +24-11-19 20:41:01 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:01 | D | sum error = [ 1.5123, 1.6129, 1.7202, 1.8336, 1.9556] +24-11-19 20:41:01 | D | best error = [ 0.5319, 0.5319, 0.5319, 0.5319, 0.5319] +24-11-19 20:41:01 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:01 | D | sum error = [ 2.0793, 2.2119, 2.3514, 2.5010, 2.6554] +24-11-19 20:41:01 | D | best error = [ 0.5319, 0.5319, 0.5319, 0.5319, 0.5319] +24-11-19 20:41:01 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:01 | D | sum error = [ 2.8170, 2.9908, 3.1731, 3.3652, 3.5662] +24-11-19 20:41:01 | D | best error = [ 0.5319, 0.5319, 0.5319, 0.5319, 0.5319] +24-11-19 20:41:01 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:01 | D | sum error = [ 3.7757, 3.9976, 4.2289, 4.4710, 4.7262] +24-11-19 20:41:01 | D | best error = [ 0.5319, 0.5319, 0.5319, 0.5319, 0.5319] +24-11-19 20:41:01 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:01 | D | sum error = [ 4.9935, 5.2759, 5.5661, 5.8742, 6.1969] +24-11-19 20:41:01 | D | best error = [ 0.5319, 0.5319, 0.5319, 0.5319, 0.5319] +24-11-19 20:41:01 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:01 | D | sum error = [ 6.5314, 6.8843, 7.2534, 7.6384, 8.0433] +24-11-19 20:41:01 | D | best error = [ 0.5319, 0.5319, 0.5319, 0.5319, 0.5319] +24-11-19 20:41:01 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:01 | D | sum error = [ 8.4666, 8.9070, 9.3664, 9.8469, 10.3476] +24-11-19 20:41:01 | D | best error = [ 0.5319, 0.5319, 0.5319, 0.5319, 0.5319] +24-11-19 20:41:01 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:01 | D | sum error = [ 10.8704, 11.4159, 11.9847, 12.5812, 13.1998] +24-11-19 20:41:01 | D | best error = [ 0.5319, 0.5319, 0.5319, 0.5319, 0.5319] +24-11-19 20:41:01 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:01 | D | sum error = [ 13.8498, 14.5249, 15.2250, 15.9535, 16.7133] +24-11-19 20:41:01 | D | best error = [ 0.5319, 0.5319, 0.5319, 0.5319, 0.5319] +24-11-19 20:41:01 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:01 | D | sum error = [ 17.5021, 18.3223, 19.1744, 20.0606, 20.9781] +24-11-19 20:41:01 | D | best error = [ 0.5319, 0.5319, 0.5319, 0.5319, 0.5319] +24-11-19 20:41:01 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:01 | D | sum error = [ 21.9334, 22.9224, 23.9488, 25.0157, 26.1178] +24-11-19 20:41:01 | D | best error = [ 0.5319, 0.5319, 0.5319, 0.5319, 0.5319] +24-11-19 20:41:01 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:01 | D | sum error = [ 27.2616, 28.4441, 29.6684, 30.9335, 32.2398] +24-11-19 20:41:01 | D | best error = [ 0.5319, 0.5319, 0.5319, 0.5319, 0.5319] +24-11-19 20:41:01 | D | + error = [0.5319] +24-11-19 20:41:01 | D | - Calibrating model.layers.27.mlp.up_proj.weight +24-11-19 20:41:01 | D | + w: sint8 +24-11-19 20:41:01 | D | + x: None +24-11-19 20:41:01 | D | + y: None +24-11-19 20:41:01 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:01 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:41:01 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:41:01 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:41:01 | D | - range ratio = [ 1.0000] +24-11-19 20:41:01 | D | sum error = [ 9.0154] +24-11-19 20:41:01 | D | best error = [ 9.0154] +24-11-19 20:41:02 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:02 | D | sum error = [ 8.9423, 8.9583, 8.9570, 9.0525, 9.2330] +24-11-19 20:41:02 | D | best error = [ 8.0265, 7.6849, 7.5095, 7.4143, 7.3622] +24-11-19 20:41:02 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:02 | D | sum error = [ 9.4771, 9.7982, 10.1742, 10.6346, 11.2299] +24-11-19 20:41:02 | D | best error = [ 7.3343, 7.3208, 7.3154, 7.3137, 7.3134] +24-11-19 20:41:02 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:02 | D | sum error = [ 11.8621, 12.6054, 13.4196, 14.2946, 15.2925] +24-11-19 20:41:02 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 20:41:02 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:02 | D | sum error = [ 16.3531, 17.5199, 18.7942, 20.1136, 21.5417] +24-11-19 20:41:02 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 20:41:02 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:02 | D | sum error = [ 23.0962, 24.7720, 26.4878, 28.3160, 30.2943] +24-11-19 20:41:02 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 20:41:02 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:02 | D | sum error = [ 32.3499, 34.5588, 36.8701, 39.3224, 41.9036] +24-11-19 20:41:02 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 20:41:02 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:02 | D | sum error = [ 44.6522, 47.4534, 50.5116, 53.6619, 57.0262] +24-11-19 20:41:02 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 20:41:02 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:02 | D | sum error = [ 60.5048, 64.1937, 68.0080, 72.0596, 76.2574] +24-11-19 20:41:02 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 20:41:02 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:02 | D | sum error = [ 80.6635, 85.3327, 90.1496, 95.2270, 100.5101] +24-11-19 20:41:02 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 20:41:02 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:02 | D | sum error = [ 106.0336, 111.7533, 117.7767, 124.0355, 130.5682] +24-11-19 20:41:02 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 20:41:02 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:02 | D | sum error = [ 137.3561, 144.4349, 151.7842, 159.4342, 167.3748] +24-11-19 20:41:02 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 20:41:02 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:02 | D | sum error = [ 175.6508, 184.1928, 193.0906, 202.3340, 211.8635] +24-11-19 20:41:02 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 20:41:02 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:02 | D | sum error = [ 221.7459, 231.9858, 242.5589, 253.4859, 264.8025] +24-11-19 20:41:02 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 20:41:02 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:02 | D | sum error = [ 276.5052, 288.5588, 301.0147, 313.8986, 327.1310] +24-11-19 20:41:02 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 20:41:02 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:02 | D | sum error = [ 340.7716, 354.8258, 369.2870, 384.1489, 399.4403] +24-11-19 20:41:02 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 20:41:02 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:02 | D | sum error = [ 415.1452, 431.2780, 447.8801, 464.9093, 482.4012] +24-11-19 20:41:02 | D | best error = [ 7.3133, 7.3133, 7.3133, 7.3133, 7.3133] +24-11-19 20:41:02 | D | + error = [7.3133] +24-11-19 20:41:02 | D | - Calibrating model.layers.27.mlp.gate_proj.weight +24-11-19 20:41:02 | D | + w: sint8 +24-11-19 20:41:02 | D | + x: None +24-11-19 20:41:02 | D | + y: None +24-11-19 20:41:02 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:02 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:41:02 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:41:02 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:41:02 | D | - range ratio = [ 1.0000] +24-11-19 20:41:02 | D | sum error = [ 12.0515] +24-11-19 20:41:02 | D | best error = [ 12.0515] +24-11-19 20:41:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:04 | D | sum error = [ 11.9799, 12.0102, 11.9303, 12.1165, 12.3575] +24-11-19 20:41:04 | D | best error = [ 10.7415, 10.2841, 10.0484, 9.9215, 9.8506] +24-11-19 20:41:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:04 | D | sum error = [ 12.6952, 13.1133, 13.6411, 14.2712, 15.0513] +24-11-19 20:41:04 | D | best error = [ 9.8168, 9.8010, 9.7938, 9.7911, 9.7905] +24-11-19 20:41:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:04 | D | sum error = [ 15.8988, 16.9130, 18.0256, 19.2344, 20.5998] +24-11-19 20:41:04 | D | best error = [ 9.7904, 9.7904, 9.7904, 9.7904, 9.7904] +24-11-19 20:41:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:04 | D | sum error = [ 22.0491, 23.6121, 25.3707, 27.1577, 29.1515] +24-11-19 20:41:04 | D | best error = [ 9.7904, 9.7904, 9.7904, 9.7904, 9.7904] +24-11-19 20:41:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:04 | D | sum error = [ 31.2068, 33.5223, 35.8762, 38.4274, 41.2092] +24-11-19 20:41:04 | D | best error = [ 9.7904, 9.7904, 9.7904, 9.7904, 9.7904] +24-11-19 20:41:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:04 | D | sum error = [ 44.1090, 47.1367, 50.3590, 53.8311, 57.4963] +24-11-19 20:41:04 | D | best error = [ 9.7904, 9.7904, 9.7904, 9.7904, 9.7904] +24-11-19 20:41:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:04 | D | sum error = [ 61.3053, 65.3981, 69.7222, 74.2665, 79.1335] +24-11-19 20:41:04 | D | best error = [ 9.7904, 9.7904, 9.7904, 9.7904, 9.7904] +24-11-19 20:41:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:04 | D | sum error = [ 84.1897, 89.5530, 95.2784, 101.2682, 107.6291] +24-11-19 20:41:04 | D | best error = [ 9.7904, 9.7904, 9.7904, 9.7904, 9.7904] +24-11-19 20:41:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:04 | D | sum error = [ 114.2842, 121.3566, 128.7437, 136.6243, 144.8724] +24-11-19 20:41:04 | D | best error = [ 9.7904, 9.7904, 9.7904, 9.7904, 9.7904] +24-11-19 20:41:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:04 | D | sum error = [ 153.5884, 162.7508, 172.3908, 182.5430, 193.2325] +24-11-19 20:41:04 | D | best error = [ 9.7904, 9.7904, 9.7904, 9.7904, 9.7904] +24-11-19 20:41:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:04 | D | sum error = [ 204.4188, 216.1477, 228.4828, 241.4318, 254.9942] +24-11-19 20:41:04 | D | best error = [ 9.7904, 9.7904, 9.7904, 9.7904, 9.7904] +24-11-19 20:41:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:04 | D | sum error = [ 269.2186, 284.1784, 299.7177, 316.0665, 333.2219] +24-11-19 20:41:04 | D | best error = [ 9.7904, 9.7904, 9.7904, 9.7904, 9.7904] +24-11-19 20:41:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:04 | D | sum error = [ 351.1207, 369.8719, 389.4225, 409.9470, 431.3063] +24-11-19 20:41:04 | D | best error = [ 9.7904, 9.7904, 9.7904, 9.7904, 9.7904] +24-11-19 20:41:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:04 | D | sum error = [ 453.6259, 476.8101, 500.9046, 525.9686, 551.9908] +24-11-19 20:41:04 | D | best error = [ 9.7904, 9.7904, 9.7904, 9.7904, 9.7904] +24-11-19 20:41:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:04 | D | sum error = [ 579.0282, 607.0454, 636.1579, 666.2420, 697.3383] +24-11-19 20:41:04 | D | best error = [ 9.7904, 9.7904, 9.7904, 9.7904, 9.7904] +24-11-19 20:41:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:04 | D | sum error = [ 729.4893, 762.7090, 796.9527, 832.2663, 868.6201] +24-11-19 20:41:04 | D | best error = [ 9.7904, 9.7904, 9.7904, 9.7904, 9.7904] +24-11-19 20:41:04 | D | + error = [9.7904] +24-11-19 20:41:04 | D | - Calibrating model.layers.27.mlp.down_proj.weight +24-11-19 20:41:04 | D | + w: sint8 +24-11-19 20:41:04 | D | + x: None +24-11-19 20:41:04 | D | + y: None +24-11-19 20:41:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:04 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:41:04 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:41:04 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:41:04 | D | - range ratio = [ 1.0000] +24-11-19 20:41:04 | D | sum error = [ 1.6194] +24-11-19 20:41:04 | D | best error = [ 1.6194] +24-11-19 20:41:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:05 | D | sum error = [ 1.6074, 1.6014, 1.5858, 1.5800, 1.5645] +24-11-19 20:41:05 | D | best error = [ 1.5002, 1.4519, 1.4202, 1.3996, 1.3835] +24-11-19 20:41:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:05 | D | sum error = [ 1.5620, 1.5605, 1.5612, 1.5728, 1.5867] +24-11-19 20:41:05 | D | best error = [ 1.3703, 1.3599, 1.3519, 1.3456, 1.3409] +24-11-19 20:41:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:05 | D | sum error = [ 1.6025, 1.6352, 1.6653, 1.7091, 1.7572] +24-11-19 20:41:05 | D | best error = [ 1.3374, 1.3353, 1.3336, 1.3324, 1.3316] +24-11-19 20:41:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:05 | D | sum error = [ 1.8196, 1.8908, 1.9708, 2.0639, 2.1683] +24-11-19 20:41:05 | D | best error = [ 1.3311, 1.3306, 1.3303, 1.3302, 1.3302] +24-11-19 20:41:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:05 | D | sum error = [ 2.2859, 2.4212, 2.5652, 2.7236, 2.8929] +24-11-19 20:41:05 | D | best error = [ 1.3301, 1.3301, 1.3301, 1.3301, 1.3300] +24-11-19 20:41:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:05 | D | sum error = [ 3.0862, 3.2926, 3.5135, 3.7582, 4.0154] +24-11-19 20:41:05 | D | best error = [ 1.3300, 1.3300, 1.3300, 1.3300, 1.3300] +24-11-19 20:41:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:05 | D | sum error = [ 4.2888, 4.5850, 4.9031, 5.2393, 5.6044] +24-11-19 20:41:05 | D | best error = [ 1.3300, 1.3300, 1.3300, 1.3300, 1.3300] +24-11-19 20:41:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:05 | D | sum error = [ 5.9919, 6.4018, 6.8363, 7.2980, 7.7901] +24-11-19 20:41:05 | D | best error = [ 1.3300, 1.3300, 1.3300, 1.3300, 1.3300] +24-11-19 20:41:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:05 | D | sum error = [ 8.3103, 8.8629, 9.4474, 10.0700, 10.7240] +24-11-19 20:41:05 | D | best error = [ 1.3300, 1.3300, 1.3300, 1.3300, 1.3300] +24-11-19 20:41:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:05 | D | sum error = [ 11.4248, 12.1564, 12.9292, 13.7465, 14.6120] +24-11-19 20:41:05 | D | best error = [ 1.3300, 1.3300, 1.3300, 1.3300, 1.3300] +24-11-19 20:41:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:05 | D | sum error = [ 15.5239, 16.4821, 17.4912, 18.5503, 19.6650] +24-11-19 20:41:05 | D | best error = [ 1.3300, 1.3300, 1.3300, 1.3300, 1.3300] +24-11-19 20:41:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:05 | D | sum error = [ 20.8369, 22.0654, 23.3534, 24.7053, 26.1246] +24-11-19 20:41:05 | D | best error = [ 1.3300, 1.3300, 1.3300, 1.3300, 1.3300] +24-11-19 20:41:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:05 | D | sum error = [ 27.6095, 29.1684, 30.7966, 32.5028, 34.2853] +24-11-19 20:41:05 | D | best error = [ 1.3300, 1.3300, 1.3300, 1.3300, 1.3300] +24-11-19 20:41:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:05 | D | sum error = [ 36.1518, 38.1018, 40.1355, 42.2631, 44.4818] +24-11-19 20:41:05 | D | best error = [ 1.3300, 1.3300, 1.3300, 1.3300, 1.3300] +24-11-19 20:41:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:05 | D | sum error = [ 46.7953, 49.2117, 51.7333, 54.3564, 57.0884] +24-11-19 20:41:05 | D | best error = [ 1.3300, 1.3300, 1.3300, 1.3300, 1.3300] +24-11-19 20:41:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:05 | D | sum error = [ 59.9310, 62.8879, 65.9589, 69.1474, 72.4553] +24-11-19 20:41:05 | D | best error = [ 1.3300, 1.3300, 1.3300, 1.3300, 1.3300] +24-11-19 20:41:05 | D | + error = [1.3300] +24-11-19 20:41:05 | D | - Quantizing model.layers.27.self_attn.q_proj.weight +24-11-19 20:41:06 | D | - Quantizing model.layers.27.self_attn.k_proj.weight +24-11-19 20:41:07 | D | - Quantizing model.layers.27.self_attn.v_proj.weight +24-11-19 20:41:08 | D | - Quantizing model.layers.27.self_attn.o_proj.weight +24-11-19 20:41:09 | D | - Quantizing model.layers.27.mlp.up_proj.weight +24-11-19 20:41:10 | D | - Quantizing model.layers.27.mlp.gate_proj.weight +24-11-19 20:41:10 | D | - Quantizing model.layers.27.mlp.down_proj.weight +24-11-19 20:41:20 | D | - Quantizing layer model.layers.28 +24-11-19 20:41:20 | D | - Calibrating model.layers.28.self_attn.q_proj.weight +24-11-19 20:41:20 | D | + w: sint8 +24-11-19 20:41:20 | D | + x: None +24-11-19 20:41:20 | D | + y: None +24-11-19 20:41:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:41:20 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:41:20 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:41:20 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:41:21 | D | - range ratio = [ 1.0000] +24-11-19 20:41:21 | D | sum error = [ 7.3903] +24-11-19 20:41:21 | D | best error = [ 7.3903] +24-11-19 20:41:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:32 | D | sum error = [ 7.2130, 7.4282, 7.2431, 7.2239, 7.6825] +24-11-19 20:41:32 | D | best error = [ 7.2130, 7.2130, 7.2130, 7.2130, 7.2130] +24-11-19 20:41:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:32 | D | sum error = [ 7.7722, 8.0434, 8.4212, 8.5020, 8.8849] +24-11-19 20:41:32 | D | best error = [ 7.2130, 7.2130, 7.2130, 7.2130, 7.2130] +24-11-19 20:41:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:32 | D | sum error = [ 9.7969, 10.3115, 10.9124, 11.8101, 12.5291] +24-11-19 20:41:32 | D | best error = [ 7.2130, 7.2130, 7.2130, 7.2130, 7.2130] +24-11-19 20:41:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:32 | D | sum error = [ 14.0647, 14.6111, 15.5416, 17.4856, 18.8315] +24-11-19 20:41:32 | D | best error = [ 7.2130, 7.2130, 7.2130, 7.2130, 7.2130] +24-11-19 20:41:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:32 | D | sum error = [ 20.3497, 21.9707, 23.8128, 25.7474, 28.2609] +24-11-19 20:41:32 | D | best error = [ 7.2130, 7.2130, 7.2130, 7.2130, 7.2130] +24-11-19 20:41:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:32 | D | sum error = [ 30.4861, 34.0470, 36.2487, 39.0868, 42.7437] +24-11-19 20:41:32 | D | best error = [ 7.2130, 7.2130, 7.2130, 7.2130, 7.2130] +24-11-19 20:41:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:32 | D | sum error = [ 46.8188, 50.5950, 54.4519, 58.8834, 63.6334] +24-11-19 20:41:32 | D | best error = [ 7.2130, 7.2130, 7.2130, 7.2130, 7.2130] +24-11-19 20:41:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:32 | D | sum error = [ 68.8071, 75.0465, 80.9271, 86.7486, 93.9523] +24-11-19 20:41:32 | D | best error = [ 7.2130, 7.2130, 7.2130, 7.2130, 7.2130] +24-11-19 20:41:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:32 | D | sum error = [ 101.2925, 109.1709, 117.3341, 126.3259, 135.4484] +24-11-19 20:41:32 | D | best error = [ 7.2130, 7.2130, 7.2130, 7.2130, 7.2130] +24-11-19 20:41:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:32 | D | sum error = [ 145.6910, 156.0737, 167.5805, 179.8873, 193.2135] +24-11-19 20:41:32 | D | best error = [ 7.2130, 7.2130, 7.2130, 7.2130, 7.2130] +24-11-19 20:41:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:32 | D | sum error = [ 206.5252, 221.8271, 237.7537, 254.9414, 273.8141] +24-11-19 20:41:32 | D | best error = [ 7.2130, 7.2130, 7.2130, 7.2130, 7.2130] +24-11-19 20:41:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:32 | D | sum error = [ 293.6797, 315.0145, 337.2043, 362.2306, 387.8098] +24-11-19 20:41:32 | D | best error = [ 7.2130, 7.2130, 7.2130, 7.2130, 7.2130] +24-11-19 20:41:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:32 | D | sum error = [ 415.7129, 446.1283, 478.4248, 513.8499, 551.8723] +24-11-19 20:41:32 | D | best error = [ 7.2130, 7.2130, 7.2130, 7.2130, 7.2130] +24-11-19 20:41:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:32 | D | sum error = [ 593.0762, 637.5638, 686.1267, 738.6359, 793.7706] +24-11-19 20:41:32 | D | best error = [ 7.2130, 7.2130, 7.2130, 7.2130, 7.2130] +24-11-19 20:41:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:32 | D | sum error = [ 853.4065, 916.7809, 984.3250, 1056.6099, 1132.7544] +24-11-19 20:41:32 | D | best error = [ 7.2130, 7.2130, 7.2130, 7.2130, 7.2130] +24-11-19 20:41:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:32 | D | sum error = [ 1212.3899, 1296.9179, 1384.4110, 1474.4513, 1566.3984] +24-11-19 20:41:32 | D | best error = [ 7.2130, 7.2130, 7.2130, 7.2130, 7.2130] +24-11-19 20:41:32 | D | + error = [7.2130] +24-11-19 20:41:33 | D | - Calibrating model.layers.28.self_attn.k_proj.weight +24-11-19 20:41:33 | D | + w: sint8 +24-11-19 20:41:33 | D | + x: None +24-11-19 20:41:33 | D | + y: None +24-11-19 20:41:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:41:33 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:41:33 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:41:33 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:41:33 | D | - range ratio = [ 1.0000] +24-11-19 20:41:33 | D | sum error = [ 8.1858] +24-11-19 20:41:33 | D | best error = [ 8.1858] +24-11-19 20:41:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:46 | D | sum error = [ 7.3032, 7.9651, 7.3685, 7.7245, 7.6001] +24-11-19 20:41:46 | D | best error = [ 7.3032, 7.3032, 7.3032, 7.3032, 7.3032] +24-11-19 20:41:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:46 | D | sum error = [ 7.6663, 8.7163, 7.8230, 8.5756, 8.8143] +24-11-19 20:41:46 | D | best error = [ 7.3032, 7.3032, 7.3032, 7.3032, 7.3032] +24-11-19 20:41:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:46 | D | sum error = [ 9.4292, 10.3363, 10.9996, 11.4922, 12.8141] +24-11-19 20:41:46 | D | best error = [ 7.3032, 7.3032, 7.3032, 7.3032, 7.3032] +24-11-19 20:41:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:46 | D | sum error = [ 12.8909, 14.3464, 15.1239, 15.8538, 17.0866] +24-11-19 20:41:46 | D | best error = [ 7.3032, 7.3032, 7.3032, 7.3032, 7.3032] +24-11-19 20:41:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:46 | D | sum error = [ 17.8777, 20.6211, 21.9429, 23.2055, 25.0804] +24-11-19 20:41:46 | D | best error = [ 7.3032, 7.3032, 7.3032, 7.3032, 7.3032] +24-11-19 20:41:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:46 | D | sum error = [ 27.3939, 29.0340, 31.5174, 33.1001, 36.1787] +24-11-19 20:41:46 | D | best error = [ 7.3032, 7.3032, 7.3032, 7.3032, 7.3032] +24-11-19 20:41:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:46 | D | sum error = [ 38.9108, 41.6565, 44.8279, 48.5319, 52.3277] +24-11-19 20:41:46 | D | best error = [ 7.3032, 7.3032, 7.3032, 7.3032, 7.3032] +24-11-19 20:41:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:46 | D | sum error = [ 56.5300, 60.6345, 64.7905, 69.9792, 76.4354] +24-11-19 20:41:46 | D | best error = [ 7.3032, 7.3032, 7.3032, 7.3032, 7.3032] +24-11-19 20:41:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:46 | D | sum error = [ 81.2136, 87.4586, 93.7689, 100.1141, 108.2570] +24-11-19 20:41:46 | D | best error = [ 7.3032, 7.3032, 7.3032, 7.3032, 7.3032] +24-11-19 20:41:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:46 | D | sum error = [ 116.1374, 124.4500, 133.9556, 143.6602, 154.6731] +24-11-19 20:41:46 | D | best error = [ 7.3032, 7.3032, 7.3032, 7.3032, 7.3032] +24-11-19 20:41:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:46 | D | sum error = [ 166.3091, 178.9098, 192.6807, 206.8905, 223.4221] +24-11-19 20:41:46 | D | best error = [ 7.3032, 7.3032, 7.3032, 7.3032, 7.3032] +24-11-19 20:41:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:46 | D | sum error = [ 239.8653, 258.2972, 278.2772, 300.2571, 323.5949] +24-11-19 20:41:46 | D | best error = [ 7.3032, 7.3032, 7.3032, 7.3032, 7.3032] +24-11-19 20:41:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:46 | D | sum error = [ 349.0141, 376.3041, 406.8619, 440.8541, 476.1170] +24-11-19 20:41:46 | D | best error = [ 7.3032, 7.3032, 7.3032, 7.3032, 7.3032] +24-11-19 20:41:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:46 | D | sum error = [ 516.7011, 558.9564, 604.6286, 654.4831, 708.2655] +24-11-19 20:41:46 | D | best error = [ 7.3032, 7.3032, 7.3032, 7.3032, 7.3032] +24-11-19 20:41:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:46 | D | sum error = [ 768.0059, 831.2145, 900.3033, 974.0791, 1054.7330] +24-11-19 20:41:46 | D | best error = [ 7.3032, 7.3032, 7.3032, 7.3032, 7.3032] +24-11-19 20:41:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:46 | D | sum error = [ 1140.3257, 1229.5128, 1323.1971, 1418.4630, 1518.2869] +24-11-19 20:41:46 | D | best error = [ 7.3032, 7.3032, 7.3032, 7.3032, 7.3032] +24-11-19 20:41:46 | D | + error = [7.3032] +24-11-19 20:41:46 | D | - Calibrating model.layers.28.self_attn.v_proj.weight +24-11-19 20:41:46 | D | + w: sint8 +24-11-19 20:41:46 | D | + x: None +24-11-19 20:41:46 | D | + y: None +24-11-19 20:41:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:46 | D | + finished parsing calibration arguments, ram usage: 13.1 +24-11-19 20:41:46 | D | + finished reseting calibrator, ram usage: 13.1 +24-11-19 20:41:46 | D | + finished calculating the original outputs, ram usage: 13.1 +24-11-19 20:41:46 | D | - range ratio = [ 1.0000] +24-11-19 20:41:46 | D | sum error = [ 2.8252] +24-11-19 20:41:46 | D | best error = [ 2.8252] +24-11-19 20:41:46 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:46 | D | sum error = [ 2.8423, 2.8018, 2.8359, 2.8518, 2.9119] +24-11-19 20:41:46 | D | best error = [ 2.5299, 2.4138, 2.3663, 2.3407, 2.3253] +24-11-19 20:41:46 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:46 | D | sum error = [ 3.0066, 3.0513, 3.2091, 3.3513, 3.5653] +24-11-19 20:41:46 | D | best error = [ 2.3180, 2.3136, 2.3125, 2.3119, 2.3119] +24-11-19 20:41:46 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:46 | D | sum error = [ 3.7432, 3.9895, 4.2432, 4.5461, 4.8122] +24-11-19 20:41:46 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:41:46 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:46 | D | sum error = [ 5.1426, 5.5566, 5.9171, 6.3235, 6.7956] +24-11-19 20:41:46 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:41:46 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:46 | D | sum error = [ 7.2331, 7.7773, 8.2772, 8.8718, 9.4661] +24-11-19 20:41:46 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:41:46 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:46 | D | sum error = [ 10.1429, 10.8066, 11.4884, 12.2828, 13.0565] +24-11-19 20:41:46 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:41:46 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:46 | D | sum error = [ 13.8716, 14.7359, 15.6563, 16.6175, 17.6499] +24-11-19 20:41:46 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:41:46 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:46 | D | sum error = [ 18.7078, 19.8503, 21.0346, 22.3095, 23.6327] +24-11-19 20:41:46 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:41:46 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:46 | D | sum error = [ 25.0505, 26.4795, 27.9938, 29.5764, 31.2157] +24-11-19 20:41:46 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:41:46 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:46 | D | sum error = [ 32.9286, 34.7223, 36.5609, 38.5014, 40.5079] +24-11-19 20:41:46 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:41:46 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:46 | D | sum error = [ 42.6295, 44.8214, 47.0910, 49.4653, 51.8946] +24-11-19 20:41:46 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:41:46 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:46 | D | sum error = [ 54.4458, 57.0749, 59.8265, 62.6307, 65.5649] +24-11-19 20:41:46 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:41:46 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:46 | D | sum error = [ 68.6000, 71.7360, 74.9625, 78.3047, 81.7258] +24-11-19 20:41:46 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:41:46 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:46 | D | sum error = [ 85.2910, 88.9699, 92.7689, 96.6830, 100.7127] +24-11-19 20:41:46 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:41:46 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:46 | D | sum error = [ 104.8621, 109.1258, 113.5325, 118.0523, 122.6971] +24-11-19 20:41:46 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:41:46 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:46 | D | sum error = [ 127.4749, 132.3650, 137.3746, 142.5507, 147.8550] +24-11-19 20:41:46 | D | best error = [ 2.3119, 2.3119, 2.3119, 2.3119, 2.3119] +24-11-19 20:41:46 | D | + error = [2.3119] +24-11-19 20:41:46 | D | - Calibrating model.layers.28.self_attn.o_proj.weight +24-11-19 20:41:46 | D | + w: sint8 +24-11-19 20:41:46 | D | + x: None +24-11-19 20:41:46 | D | + y: None +24-11-19 20:41:46 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:46 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:41:46 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:41:46 | D | + finished calculating the original outputs, ram usage: 13.2 +24-11-19 20:41:46 | D | - range ratio = [ 1.0000] +24-11-19 20:41:46 | D | sum error = [ 0.8159] +24-11-19 20:41:46 | D | best error = [ 0.8159] +24-11-19 20:41:47 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:47 | D | sum error = [ 0.8090, 0.8124, 0.8155, 0.8262, 0.8439] +24-11-19 20:41:47 | D | best error = [ 0.7612, 0.7390, 0.7260, 0.7176, 0.7124] +24-11-19 20:41:47 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:47 | D | sum error = [ 0.8655, 0.8962, 0.9336, 0.9790, 1.0324] +24-11-19 20:41:47 | D | best error = [ 0.7090, 0.7068, 0.7055, 0.7046, 0.7040] +24-11-19 20:41:47 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:47 | D | sum error = [ 1.0876, 1.1550, 1.2247, 1.3036, 1.3896] +24-11-19 20:41:47 | D | best error = [ 0.7035, 0.7033, 0.7032, 0.7031, 0.7030] +24-11-19 20:41:47 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:47 | D | sum error = [ 1.4770, 1.5748, 1.6799, 1.7897, 1.9077] +24-11-19 20:41:47 | D | best error = [ 0.7030, 0.7030, 0.7030, 0.7030, 0.7030] +24-11-19 20:41:47 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:47 | D | sum error = [ 2.0336, 2.1668, 2.3056, 2.4478, 2.6032] +24-11-19 20:41:47 | D | best error = [ 0.7030, 0.7030, 0.7030, 0.7030, 0.7030] +24-11-19 20:41:47 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:47 | D | sum error = [ 2.7657, 2.9344, 3.1144, 3.3023, 3.5017] +24-11-19 20:41:47 | D | best error = [ 0.7030, 0.7030, 0.7030, 0.7030, 0.7030] +24-11-19 20:41:47 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:47 | D | sum error = [ 3.7100, 3.9276, 4.1555, 4.3961, 4.6460] +24-11-19 20:41:47 | D | best error = [ 0.7030, 0.7030, 0.7030, 0.7030, 0.7030] +24-11-19 20:41:47 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:47 | D | sum error = [ 4.9071, 5.1831, 5.4736, 5.7743, 6.0874] +24-11-19 20:41:47 | D | best error = [ 0.7030, 0.7030, 0.7030, 0.7030, 0.7030] +24-11-19 20:41:47 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:47 | D | sum error = [ 6.4193, 6.7629, 7.1277, 7.5022, 7.8996] +24-11-19 20:41:47 | D | best error = [ 0.7030, 0.7030, 0.7030, 0.7030, 0.7030] +24-11-19 20:41:47 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:47 | D | sum error = [ 8.3141, 8.7466, 9.1965, 9.6659, 10.1525] +24-11-19 20:41:47 | D | best error = [ 0.7030, 0.7030, 0.7030, 0.7030, 0.7030] +24-11-19 20:41:47 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:47 | D | sum error = [ 10.6651, 11.1965, 11.7522, 12.3315, 12.9364] +24-11-19 20:41:47 | D | best error = [ 0.7030, 0.7030, 0.7030, 0.7030, 0.7030] +24-11-19 20:41:47 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:47 | D | sum error = [ 13.5631, 14.2218, 14.9039, 15.6167, 16.3586] +24-11-19 20:41:47 | D | best error = [ 0.7030, 0.7030, 0.7030, 0.7030, 0.7030] +24-11-19 20:41:47 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:47 | D | sum error = [ 17.1297, 17.9331, 18.7683, 19.6342, 20.5377] +24-11-19 20:41:47 | D | best error = [ 0.7030, 0.7030, 0.7030, 0.7030, 0.7030] +24-11-19 20:41:47 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:47 | D | sum error = [ 21.4749, 22.4481, 23.4582, 24.5073, 25.5945] +24-11-19 20:41:47 | D | best error = [ 0.7030, 0.7030, 0.7030, 0.7030, 0.7030] +24-11-19 20:41:47 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:47 | D | sum error = [ 26.7228, 27.8941, 29.1055, 30.3614, 31.6628] +24-11-19 20:41:47 | D | best error = [ 0.7030, 0.7030, 0.7030, 0.7030, 0.7030] +24-11-19 20:41:47 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:47 | D | sum error = [ 33.0079, 34.3995, 35.8372, 37.3229, 38.8604] +24-11-19 20:41:47 | D | best error = [ 0.7030, 0.7030, 0.7030, 0.7030, 0.7030] +24-11-19 20:41:47 | D | + error = [0.7030] +24-11-19 20:41:47 | D | - Calibrating model.layers.28.mlp.up_proj.weight +24-11-19 20:41:47 | D | + w: sint8 +24-11-19 20:41:47 | D | + x: None +24-11-19 20:41:47 | D | + y: None +24-11-19 20:41:47 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:47 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:41:47 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:41:47 | D | + finished calculating the original outputs, ram usage: 13.2 +24-11-19 20:41:47 | D | - range ratio = [ 1.0000] +24-11-19 20:41:47 | D | sum error = [ 9.6318] +24-11-19 20:41:47 | D | best error = [ 9.6318] +24-11-19 20:41:48 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:48 | D | sum error = [ 9.5567, 9.5064, 9.5502, 9.6608, 9.8352] +24-11-19 20:41:48 | D | best error = [ 8.4920, 8.0928, 7.9057, 7.8069, 7.7497] +24-11-19 20:41:48 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:48 | D | sum error = [ 10.0984, 10.4524, 10.8705, 11.4011, 11.9497] +24-11-19 20:41:48 | D | best error = [ 7.7225, 7.7096, 7.7051, 7.7033, 7.7028] +24-11-19 20:41:48 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:48 | D | sum error = [ 12.6815, 13.4628, 14.2889, 15.2716, 16.3324] +24-11-19 20:41:48 | D | best error = [ 7.7026, 7.7026, 7.7025, 7.7025, 7.7025] +24-11-19 20:41:48 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:48 | D | sum error = [ 17.4767, 18.6778, 20.0325, 21.4528, 22.9761] +24-11-19 20:41:48 | D | best error = [ 7.7025, 7.7025, 7.7025, 7.7025, 7.7025] +24-11-19 20:41:48 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:48 | D | sum error = [ 24.6700, 26.3946, 28.2245, 30.1737, 32.3110] +24-11-19 20:41:48 | D | best error = [ 7.7025, 7.7025, 7.7025, 7.7025, 7.7025] +24-11-19 20:41:48 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:48 | D | sum error = [ 34.4963, 36.8268, 39.3246, 41.9149, 44.7004] +24-11-19 20:41:48 | D | best error = [ 7.7025, 7.7025, 7.7025, 7.7025, 7.7025] +24-11-19 20:41:48 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:48 | D | sum error = [ 47.5960, 50.6247, 53.8892, 57.2811, 60.8380] +24-11-19 20:41:48 | D | best error = [ 7.7025, 7.7025, 7.7025, 7.7025, 7.7025] +24-11-19 20:41:48 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:48 | D | sum error = [ 64.6305, 68.5892, 72.7399, 77.0995, 81.7495] +24-11-19 20:41:48 | D | best error = [ 7.7025, 7.7025, 7.7025, 7.7025, 7.7025] +24-11-19 20:41:48 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:48 | D | sum error = [ 86.5714, 91.6468, 96.9811, 102.4892, 108.2976] +24-11-19 20:41:48 | D | best error = [ 7.7025, 7.7025, 7.7025, 7.7025, 7.7025] +24-11-19 20:41:48 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:48 | D | sum error = [ 114.3947, 120.7459, 127.4132, 134.3392, 141.5867] +24-11-19 20:41:48 | D | best error = [ 7.7025, 7.7025, 7.7025, 7.7025, 7.7025] +24-11-19 20:41:48 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:48 | D | sum error = [ 149.1140, 157.0546, 165.2534, 173.8089, 182.7051] +24-11-19 20:41:48 | D | best error = [ 7.7025, 7.7025, 7.7025, 7.7025, 7.7025] +24-11-19 20:41:48 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:48 | D | sum error = [ 191.9503, 201.5840, 211.5595, 221.9371, 232.6732] +24-11-19 20:41:48 | D | best error = [ 7.7025, 7.7025, 7.7025, 7.7025, 7.7025] +24-11-19 20:41:48 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:48 | D | sum error = [ 243.8270, 255.3764, 267.3735, 279.8106, 292.6447] +24-11-19 20:41:48 | D | best error = [ 7.7025, 7.7025, 7.7025, 7.7025, 7.7025] +24-11-19 20:41:48 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:48 | D | sum error = [ 305.9467, 319.7022, 333.9261, 348.6497, 363.8419] +24-11-19 20:41:48 | D | best error = [ 7.7025, 7.7025, 7.7025, 7.7025, 7.7025] +24-11-19 20:41:48 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:48 | D | sum error = [ 379.5486, 395.7491, 412.4764, 429.7189, 447.4902] +24-11-19 20:41:48 | D | best error = [ 7.7025, 7.7025, 7.7025, 7.7025, 7.7025] +24-11-19 20:41:48 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:48 | D | sum error = [ 465.8054, 484.6645, 504.0415, 523.9844, 544.4630] +24-11-19 20:41:48 | D | best error = [ 7.7025, 7.7025, 7.7025, 7.7025, 7.7025] +24-11-19 20:41:48 | D | + error = [7.7025] +24-11-19 20:41:48 | D | - Calibrating model.layers.28.mlp.gate_proj.weight +24-11-19 20:41:48 | D | + w: sint8 +24-11-19 20:41:48 | D | + x: None +24-11-19 20:41:48 | D | + y: None +24-11-19 20:41:48 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:48 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:41:49 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:41:49 | D | + finished calculating the original outputs, ram usage: 13.4 +24-11-19 20:41:49 | D | - range ratio = [ 1.0000] +24-11-19 20:41:49 | D | sum error = [ 12.5617] +24-11-19 20:41:49 | D | best error = [ 12.5617] +24-11-19 20:41:50 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:50 | D | sum error = [ 12.4409, 12.4298, 12.4571, 12.6163, 12.8295] +24-11-19 20:41:50 | D | best error = [ 11.0527, 10.5568, 10.3075, 10.1794, 10.1051] +24-11-19 20:41:50 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:50 | D | sum error = [ 13.1827, 13.6852, 14.1404, 14.8336, 15.6468] +24-11-19 20:41:50 | D | best error = [ 10.0674, 10.0496, 10.0427, 10.0396, 10.0388] +24-11-19 20:41:50 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:50 | D | sum error = [ 16.5431, 17.5643, 18.7158, 19.9920, 21.4127] +24-11-19 20:41:50 | D | best error = [ 10.0387, 10.0386, 10.0385, 10.0385, 10.0385] +24-11-19 20:41:50 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:50 | D | sum error = [ 22.9222, 24.5769, 26.3451, 28.2871, 30.3196] +24-11-19 20:41:50 | D | best error = [ 10.0385, 10.0385, 10.0385, 10.0385, 10.0385] +24-11-19 20:41:50 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:50 | D | sum error = [ 32.5123, 34.9022, 37.3584, 40.0517, 42.8264] +24-11-19 20:41:50 | D | best error = [ 10.0385, 10.0385, 10.0385, 10.0385, 10.0385] +24-11-19 20:41:50 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:50 | D | sum error = [ 45.9025, 49.0825, 52.4689, 56.0807, 59.8530] +24-11-19 20:41:50 | D | best error = [ 10.0385, 10.0385, 10.0385, 10.0385, 10.0385] +24-11-19 20:41:50 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:50 | D | sum error = [ 63.8825, 68.1588, 72.7695, 77.5008, 82.6201] +24-11-19 20:41:50 | D | best error = [ 10.0385, 10.0385, 10.0385, 10.0385, 10.0385] +24-11-19 20:41:50 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:50 | D | sum error = [ 87.9479, 93.6740, 99.6648, 106.0383, 112.7127] +24-11-19 20:41:50 | D | best error = [ 10.0385, 10.0385, 10.0385, 10.0385, 10.0385] +24-11-19 20:41:50 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:50 | D | sum error = [ 119.8608, 127.3800, 135.2976, 143.7424, 152.5283] +24-11-19 20:41:50 | D | best error = [ 10.0385, 10.0385, 10.0385, 10.0385, 10.0385] +24-11-19 20:41:50 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:50 | D | sum error = [ 161.8719, 171.6987, 182.1395, 193.0945, 204.5334] +24-11-19 20:41:50 | D | best error = [ 10.0385, 10.0385, 10.0385, 10.0385, 10.0385] +24-11-19 20:41:50 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:50 | D | sum error = [ 216.6275, 229.3795, 242.7815, 256.8583, 271.6986] +24-11-19 20:41:50 | D | best error = [ 10.0385, 10.0385, 10.0385, 10.0385, 10.0385] +24-11-19 20:41:50 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:50 | D | sum error = [ 287.2080, 303.5129, 320.6034, 338.5493, 357.3297] +24-11-19 20:41:50 | D | best error = [ 10.0385, 10.0385, 10.0385, 10.0385, 10.0385] +24-11-19 20:41:50 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:50 | D | sum error = [ 376.9409, 397.5096, 419.0872, 441.5708, 465.0495] +24-11-19 20:41:50 | D | best error = [ 10.0385, 10.0385, 10.0385, 10.0385, 10.0385] +24-11-19 20:41:50 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:50 | D | sum error = [ 489.5316, 515.1185, 541.7393, 569.4134, 598.1572] +24-11-19 20:41:50 | D | best error = [ 10.0385, 10.0385, 10.0385, 10.0385, 10.0385] +24-11-19 20:41:50 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:50 | D | sum error = [ 627.9406, 658.8221, 690.8590, 724.0053, 758.3959] +24-11-19 20:41:50 | D | best error = [ 10.0385, 10.0385, 10.0385, 10.0385, 10.0385] +24-11-19 20:41:50 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:50 | D | sum error = [ 793.9475, 830.6743, 868.5957, 907.7676, 948.1980] +24-11-19 20:41:50 | D | best error = [ 10.0385, 10.0385, 10.0385, 10.0385, 10.0385] +24-11-19 20:41:50 | D | + error = [10.0385] +24-11-19 20:41:50 | D | - Calibrating model.layers.28.mlp.down_proj.weight +24-11-19 20:41:50 | D | + w: sint8 +24-11-19 20:41:50 | D | + x: None +24-11-19 20:41:50 | D | + y: None +24-11-19 20:41:50 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:41:50 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:41:50 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:41:50 | D | + finished calculating the original outputs, ram usage: 13.1 +24-11-19 20:41:50 | D | - range ratio = [ 1.0000] +24-11-19 20:41:50 | D | sum error = [ 1.8314] +24-11-19 20:41:50 | D | best error = [ 1.8314] +24-11-19 20:41:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:41:51 | D | sum error = [ 1.8175, 1.7948, 1.7823, 1.7744, 1.7616] +24-11-19 20:41:51 | D | best error = [ 1.7115, 1.6609, 1.6298, 1.6082, 1.5911] +24-11-19 20:41:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:41:51 | D | sum error = [ 1.7594, 1.7631, 1.7663, 1.7762, 1.7965] +24-11-19 20:41:51 | D | best error = [ 1.5777, 1.5675, 1.5587, 1.5519, 1.5472] +24-11-19 20:41:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:41:51 | D | sum error = [ 1.8224, 1.8547, 1.8861, 1.9364, 1.9928] +24-11-19 20:41:51 | D | best error = [ 1.5437, 1.5408, 1.5386, 1.5370, 1.5358] +24-11-19 20:41:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:41:51 | D | sum error = [ 2.0649, 2.1430, 2.2353, 2.3478, 2.4633] +24-11-19 20:41:51 | D | best error = [ 1.5351, 1.5344, 1.5342, 1.5340, 1.5338] +24-11-19 20:41:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:41:51 | D | sum error = [ 2.5967, 2.7474, 2.9091, 3.0908, 3.2832] +24-11-19 20:41:51 | D | best error = [ 1.5338, 1.5338, 1.5338, 1.5337, 1.5337] +24-11-19 20:41:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:41:51 | D | sum error = [ 3.4945, 3.7277, 3.9743, 4.2461, 4.5365] +24-11-19 20:41:51 | D | best error = [ 1.5337, 1.5337, 1.5337, 1.5337, 1.5337] +24-11-19 20:41:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:41:51 | D | sum error = [ 4.8392, 5.1779, 5.5254, 5.9119, 6.3131] +24-11-19 20:41:51 | D | best error = [ 1.5337, 1.5337, 1.5337, 1.5337, 1.5337] +24-11-19 20:41:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:41:51 | D | sum error = [ 6.7457, 7.2102, 7.6977, 8.2161, 8.7693] +24-11-19 20:41:51 | D | best error = [ 1.5337, 1.5337, 1.5337, 1.5337, 1.5337] +24-11-19 20:41:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:41:51 | D | sum error = [ 9.3519, 9.9748, 10.6354, 11.3305, 12.0740] +24-11-19 20:41:51 | D | best error = [ 1.5337, 1.5337, 1.5337, 1.5337, 1.5337] +24-11-19 20:41:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:41:51 | D | sum error = [ 12.8534, 13.6816, 14.5561, 15.4777, 16.4549] +24-11-19 20:41:51 | D | best error = [ 1.5337, 1.5337, 1.5337, 1.5337, 1.5337] +24-11-19 20:41:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:41:51 | D | sum error = [ 17.4819, 18.5713, 19.7176, 20.9272, 22.1990] +24-11-19 20:41:51 | D | best error = [ 1.5337, 1.5337, 1.5337, 1.5337, 1.5337] +24-11-19 20:41:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:41:51 | D | sum error = [ 23.5410, 24.9511, 26.4327, 27.9860, 29.6208] +24-11-19 20:41:51 | D | best error = [ 1.5337, 1.5337, 1.5337, 1.5337, 1.5337] +24-11-19 20:41:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:41:51 | D | sum error = [ 31.3363, 33.1327, 35.0184, 36.9953, 39.0653] +24-11-19 20:41:51 | D | best error = [ 1.5337, 1.5337, 1.5337, 1.5337, 1.5337] +24-11-19 20:41:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:41:51 | D | sum error = [ 41.2322, 43.5008, 45.8736, 48.3615, 50.9598] +24-11-19 20:41:51 | D | best error = [ 1.5337, 1.5337, 1.5337, 1.5337, 1.5337] +24-11-19 20:41:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:41:51 | D | sum error = [ 53.6734, 56.5086, 59.4668, 62.5482, 65.7603] +24-11-19 20:41:51 | D | best error = [ 1.5337, 1.5337, 1.5337, 1.5337, 1.5337] +24-11-19 20:41:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:41:51 | D | sum error = [ 69.1045, 72.5862, 76.2102, 79.9791, 83.8942] +24-11-19 20:41:51 | D | best error = [ 1.5337, 1.5337, 1.5337, 1.5337, 1.5337] +24-11-19 20:41:51 | D | + error = [1.5337] +24-11-19 20:41:51 | D | - Quantizing model.layers.28.self_attn.q_proj.weight +24-11-19 20:41:52 | D | - Quantizing model.layers.28.self_attn.k_proj.weight +24-11-19 20:41:53 | D | - Quantizing model.layers.28.self_attn.v_proj.weight +24-11-19 20:41:54 | D | - Quantizing model.layers.28.self_attn.o_proj.weight +24-11-19 20:41:55 | D | - Quantizing model.layers.28.mlp.up_proj.weight +24-11-19 20:41:56 | D | - Quantizing model.layers.28.mlp.gate_proj.weight +24-11-19 20:41:57 | D | - Quantizing model.layers.28.mlp.down_proj.weight +24-11-19 20:42:07 | D | - Quantizing layer model.layers.29 +24-11-19 20:42:07 | D | - Calibrating model.layers.29.self_attn.q_proj.weight +24-11-19 20:42:07 | D | + w: sint8 +24-11-19 20:42:07 | D | + x: None +24-11-19 20:42:07 | D | + y: None +24-11-19 20:42:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:42:07 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:42:07 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:42:07 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:42:07 | D | - range ratio = [ 1.0000] +24-11-19 20:42:07 | D | sum error = [ 9.8532] +24-11-19 20:42:07 | D | best error = [ 9.8532] +24-11-19 20:42:19 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:42:19 | D | sum error = [ 8.6938, 8.6340, 9.5319, 8.9270, 9.0737] +24-11-19 20:42:19 | D | best error = [ 8.6938, 8.6340, 8.6340, 8.6340, 8.6340] +24-11-19 20:42:19 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:42:19 | D | sum error = [ 9.0615, 9.8241, 10.1753, 10.2475, 12.2740] +24-11-19 20:42:19 | D | best error = [ 8.6340, 8.6340, 8.6340, 8.6340, 8.6340] +24-11-19 20:42:19 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:42:19 | D | sum error = [ 12.2537, 13.2191, 13.8104, 14.6375, 15.9696] +24-11-19 20:42:19 | D | best error = [ 8.6340, 8.6340, 8.6340, 8.6340, 8.6340] +24-11-19 20:42:19 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:42:19 | D | sum error = [ 17.9543, 19.5066, 19.9573, 22.8966, 25.1309] +24-11-19 20:42:19 | D | best error = [ 8.6340, 8.6340, 8.6340, 8.6340, 8.6340] +24-11-19 20:42:19 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:42:19 | D | sum error = [ 27.0860, 30.1504, 31.2743, 35.0138, 36.7649] +24-11-19 20:42:19 | D | best error = [ 8.6340, 8.6340, 8.6340, 8.6340, 8.6340] +24-11-19 20:42:19 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:42:19 | D | sum error = [ 39.6038, 42.1336, 45.8708, 49.0181, 53.2265] +24-11-19 20:42:19 | D | best error = [ 8.6340, 8.6340, 8.6340, 8.6340, 8.6340] +24-11-19 20:42:19 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:42:19 | D | sum error = [ 56.4323, 60.9882, 65.2288, 70.3873, 74.6943] +24-11-19 20:42:19 | D | best error = [ 8.6340, 8.6340, 8.6340, 8.6340, 8.6340] +24-11-19 20:42:19 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:42:19 | D | sum error = [ 81.2034, 86.5844, 93.0527, 99.9488, 106.5164] +24-11-19 20:42:19 | D | best error = [ 8.6340, 8.6340, 8.6340, 8.6340, 8.6340] +24-11-19 20:42:19 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:42:19 | D | sum error = [ 114.1025, 122.6099, 130.7741, 140.3785, 151.1246] +24-11-19 20:42:19 | D | best error = [ 8.6340, 8.6340, 8.6340, 8.6340, 8.6340] +24-11-19 20:42:19 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:42:19 | D | sum error = [ 161.7825, 173.6913, 186.9254, 200.8944, 216.0480] +24-11-19 20:42:19 | D | best error = [ 8.6340, 8.6340, 8.6340, 8.6340, 8.6340] +24-11-19 20:42:19 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:42:19 | D | sum error = [ 231.8162, 247.9598, 265.3686, 285.0470, 304.8224] +24-11-19 20:42:19 | D | best error = [ 8.6340, 8.6340, 8.6340, 8.6340, 8.6340] +24-11-19 20:42:19 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:42:19 | D | sum error = [ 325.6077, 349.4102, 375.0999, 402.3950, 432.3642] +24-11-19 20:42:19 | D | best error = [ 8.6340, 8.6340, 8.6340, 8.6340, 8.6340] +24-11-19 20:42:19 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:42:19 | D | sum error = [ 464.7964, 500.1562, 537.9918, 579.0401, 625.4615] +24-11-19 20:42:19 | D | best error = [ 8.6340, 8.6340, 8.6340, 8.6340, 8.6340] +24-11-19 20:42:19 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:42:19 | D | sum error = [ 675.0466, 728.8774, 789.2307, 854.1317, 925.8583] +24-11-19 20:42:19 | D | best error = [ 8.6340, 8.6340, 8.6340, 8.6340, 8.6340] +24-11-19 20:42:19 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:42:19 | D | sum error = [ 1003.6038, 1088.0608, 1180.8077, 1281.8920, 1389.7406] +24-11-19 20:42:19 | D | best error = [ 8.6340, 8.6340, 8.6340, 8.6340, 8.6340] +24-11-19 20:42:19 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:42:19 | D | sum error = [ 1507.4484, 1633.7540, 1766.7428, 1905.9969, 2051.1282] +24-11-19 20:42:19 | D | best error = [ 8.6340, 8.6340, 8.6340, 8.6340, 8.6340] +24-11-19 20:42:19 | D | + error = [8.6340] +24-11-19 20:42:19 | D | - Calibrating model.layers.29.self_attn.k_proj.weight +24-11-19 20:42:19 | D | + w: sint8 +24-11-19 20:42:19 | D | + x: None +24-11-19 20:42:19 | D | + y: None +24-11-19 20:42:19 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:42:19 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:42:19 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:42:20 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:42:20 | D | - range ratio = [ 1.0000] +24-11-19 20:42:20 | D | sum error = [ 9.3767] +24-11-19 20:42:20 | D | best error = [ 9.3767] +24-11-19 20:42:32 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:42:32 | D | sum error = [ 9.5604, 9.4031, 8.9856, 10.1327, 9.1285] +24-11-19 20:42:32 | D | best error = [ 9.3767, 9.3767, 8.9856, 8.9856, 8.9856] +24-11-19 20:42:32 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:42:32 | D | sum error = [ 9.2713, 11.6937, 10.4341, 10.9296, 11.3663] +24-11-19 20:42:32 | D | best error = [ 8.9856, 8.9856, 8.9856, 8.9856, 8.9856] +24-11-19 20:42:32 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:42:32 | D | sum error = [ 12.8169, 15.5029, 15.7624, 17.6743, 17.2796] +24-11-19 20:42:32 | D | best error = [ 8.9856, 8.9856, 8.9856, 8.9856, 8.9856] +24-11-19 20:42:32 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:42:32 | D | sum error = [ 15.5863, 17.1789, 22.1280, 25.8293, 22.9477] +24-11-19 20:42:32 | D | best error = [ 8.9856, 8.9856, 8.9856, 8.9856, 8.9856] +24-11-19 20:42:32 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:42:32 | D | sum error = [ 25.5140, 26.0680, 26.7911, 29.4612, 31.9463] +24-11-19 20:42:32 | D | best error = [ 8.9856, 8.9856, 8.9856, 8.9856, 8.9856] +24-11-19 20:42:32 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:42:32 | D | sum error = [ 33.5825, 37.1068, 39.5357, 42.2011, 44.8604] +24-11-19 20:42:32 | D | best error = [ 8.9856, 8.9856, 8.9856, 8.9856, 8.9856] +24-11-19 20:42:32 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:42:32 | D | sum error = [ 47.5263, 51.8894, 55.0920, 58.8267, 62.4687] +24-11-19 20:42:32 | D | best error = [ 8.9856, 8.9856, 8.9856, 8.9856, 8.9856] +24-11-19 20:42:32 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:42:32 | D | sum error = [ 66.0019, 71.1007, 75.7762, 81.5298, 88.7104] +24-11-19 20:42:32 | D | best error = [ 8.9856, 8.9856, 8.9856, 8.9856, 8.9856] +24-11-19 20:42:32 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:42:32 | D | sum error = [ 95.0382, 105.1203, 114.7050, 122.8853, 136.8757] +24-11-19 20:42:32 | D | best error = [ 8.9856, 8.9856, 8.9856, 8.9856, 8.9856] +24-11-19 20:42:32 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:42:32 | D | sum error = [ 148.9557, 161.6027, 177.6197, 197.3681, 216.8523] +24-11-19 20:42:32 | D | best error = [ 8.9856, 8.9856, 8.9856, 8.9856, 8.9856] +24-11-19 20:42:32 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:42:32 | D | sum error = [ 236.0339, 259.7898, 283.0989, 310.2325, 337.3010] +24-11-19 20:42:32 | D | best error = [ 8.9856, 8.9856, 8.9856, 8.9856, 8.9856] +24-11-19 20:42:32 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:42:32 | D | sum error = [ 365.4281, 395.2568, 424.6067, 457.3309, 489.7145] +24-11-19 20:42:32 | D | best error = [ 8.9856, 8.9856, 8.9856, 8.9856, 8.9856] +24-11-19 20:42:32 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:42:32 | D | sum error = [ 524.8263, 563.1869, 605.4440, 652.2242, 698.5424] +24-11-19 20:42:32 | D | best error = [ 8.9856, 8.9856, 8.9856, 8.9856, 8.9856] +24-11-19 20:42:32 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:42:32 | D | sum error = [ 750.4899, 807.6314, 866.0240, 931.8487, 1001.1436] +24-11-19 20:42:32 | D | best error = [ 8.9856, 8.9856, 8.9856, 8.9856, 8.9856] +24-11-19 20:42:32 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:42:32 | D | sum error = [ 1074.2515, 1156.5336, 1247.1042, 1341.5336, 1444.8736] +24-11-19 20:42:32 | D | best error = [ 8.9856, 8.9856, 8.9856, 8.9856, 8.9856] +24-11-19 20:42:32 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:42:32 | D | sum error = [ 1556.0132, 1674.6300, 1798.7332, 1929.2512, 2065.3454] +24-11-19 20:42:32 | D | best error = [ 8.9856, 8.9856, 8.9856, 8.9856, 8.9856] +24-11-19 20:42:32 | D | + error = [8.9856] +24-11-19 20:42:32 | D | - Calibrating model.layers.29.self_attn.v_proj.weight +24-11-19 20:42:32 | D | + w: sint8 +24-11-19 20:42:32 | D | + x: None +24-11-19 20:42:32 | D | + y: None +24-11-19 20:42:32 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:42:32 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:42:32 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:42:33 | D | + finished calculating the original outputs, ram usage: 13.4 +24-11-19 20:42:33 | D | - range ratio = [ 1.0000] +24-11-19 20:42:33 | D | sum error = [ 3.1150] +24-11-19 20:42:33 | D | best error = [ 3.1150] +24-11-19 20:42:33 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:42:33 | D | sum error = [ 3.0925, 3.1117, 3.1180, 3.1330, 3.2178] +24-11-19 20:42:33 | D | best error = [ 2.7894, 2.6827, 2.6256, 2.5871, 2.5714] +24-11-19 20:42:33 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:42:33 | D | sum error = [ 3.3543, 3.4153, 3.5191, 3.7242, 3.9555] +24-11-19 20:42:33 | D | best error = [ 2.5638, 2.5611, 2.5595, 2.5591, 2.5590] +24-11-19 20:42:33 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:42:33 | D | sum error = [ 4.1553, 4.3855, 4.6795, 5.0064, 5.3164] +24-11-19 20:42:33 | D | best error = [ 2.5590, 2.5590, 2.5590, 2.5590, 2.5590] +24-11-19 20:42:33 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:42:33 | D | sum error = [ 5.6995, 6.1311, 6.5305, 7.0235, 7.5362] +24-11-19 20:42:33 | D | best error = [ 2.5590, 2.5590, 2.5590, 2.5590, 2.5590] +24-11-19 20:42:33 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:42:33 | D | sum error = [ 8.0196, 8.6528, 9.2420, 9.9587, 10.5964] +24-11-19 20:42:33 | D | best error = [ 2.5590, 2.5590, 2.5590, 2.5590, 2.5590] +24-11-19 20:42:33 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:42:33 | D | sum error = [ 11.3255, 12.1101, 12.8956, 13.7195, 14.6768] +24-11-19 20:42:33 | D | best error = [ 2.5590, 2.5590, 2.5590, 2.5590, 2.5590] +24-11-19 20:42:33 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:42:33 | D | sum error = [ 15.6529, 16.6095, 17.7045, 18.7649, 19.9495] +24-11-19 20:42:33 | D | best error = [ 2.5590, 2.5590, 2.5590, 2.5590, 2.5590] +24-11-19 20:42:33 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:42:33 | D | sum error = [ 21.1998, 22.4882, 23.8510, 25.2751, 26.7292] +24-11-19 20:42:33 | D | best error = [ 2.5590, 2.5590, 2.5590, 2.5590, 2.5590] +24-11-19 20:42:33 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:42:33 | D | sum error = [ 28.2838, 29.9463, 31.6353, 33.4238, 35.3310] +24-11-19 20:42:33 | D | best error = [ 2.5590, 2.5590, 2.5590, 2.5590, 2.5590] +24-11-19 20:42:33 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:42:33 | D | sum error = [ 37.3279, 39.3787, 41.5178, 43.8072, 46.2378] +24-11-19 20:42:33 | D | best error = [ 2.5590, 2.5590, 2.5590, 2.5590, 2.5590] +24-11-19 20:42:33 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:42:33 | D | sum error = [ 48.6434, 51.2390, 53.9408, 56.7271, 59.6313] +24-11-19 20:42:33 | D | best error = [ 2.5590, 2.5590, 2.5590, 2.5590, 2.5590] +24-11-19 20:42:33 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:42:33 | D | sum error = [ 62.6969, 65.8295, 69.0931, 72.4989, 75.9879] +24-11-19 20:42:33 | D | best error = [ 2.5590, 2.5590, 2.5590, 2.5590, 2.5590] +24-11-19 20:42:33 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:42:33 | D | sum error = [ 79.6560, 83.4536, 87.3660, 91.4356, 95.6332] +24-11-19 20:42:33 | D | best error = [ 2.5590, 2.5590, 2.5590, 2.5590, 2.5590] +24-11-19 20:42:33 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:42:33 | D | sum error = [ 100.0010, 104.5095, 109.1730, 114.0243, 119.0023] +24-11-19 20:42:33 | D | best error = [ 2.5590, 2.5590, 2.5590, 2.5590, 2.5590] +24-11-19 20:42:33 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:42:33 | D | sum error = [ 124.1567, 129.4582, 134.9229, 140.5589, 146.3729] +24-11-19 20:42:33 | D | best error = [ 2.5590, 2.5590, 2.5590, 2.5590, 2.5590] +24-11-19 20:42:33 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:42:33 | D | sum error = [ 152.3377, 158.4873, 164.7968, 171.3028, 177.9767] +24-11-19 20:42:33 | D | best error = [ 2.5590, 2.5590, 2.5590, 2.5590, 2.5590] +24-11-19 20:42:33 | D | + error = [2.5590] +24-11-19 20:42:33 | D | - Calibrating model.layers.29.self_attn.o_proj.weight +24-11-19 20:42:33 | D | + w: sint8 +24-11-19 20:42:33 | D | + x: None +24-11-19 20:42:33 | D | + y: None +24-11-19 20:42:33 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:42:33 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:42:33 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:42:33 | D | + finished calculating the original outputs, ram usage: 13.4 +24-11-19 20:42:33 | D | - range ratio = [ 1.0000] +24-11-19 20:42:33 | D | sum error = [ 0.9300] +24-11-19 20:42:33 | D | best error = [ 0.9300] +24-11-19 20:42:34 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:42:34 | D | sum error = [ 0.9242, 0.9300, 0.9297, 0.9375, 0.9486] +24-11-19 20:42:34 | D | best error = [ 0.8409, 0.8043, 0.7831, 0.7689, 0.7602] +24-11-19 20:42:34 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:42:34 | D | sum error = [ 0.9734, 0.9996, 1.0290, 1.0752, 1.1220] +24-11-19 20:42:34 | D | best error = [ 0.7539, 0.7490, 0.7457, 0.7433, 0.7414] +24-11-19 20:42:34 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:42:34 | D | sum error = [ 1.1820, 1.2409, 1.3168, 1.3840, 1.4703] +24-11-19 20:42:34 | D | best error = [ 0.7402, 0.7392, 0.7385, 0.7381, 0.7378] +24-11-19 20:42:34 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:42:34 | D | sum error = [ 1.5603, 1.6653, 1.7760, 1.8849, 2.0048] +24-11-19 20:42:34 | D | best error = [ 0.7376, 0.7374, 0.7372, 0.7371, 0.7371] +24-11-19 20:42:34 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:42:34 | D | sum error = [ 2.1385, 2.2797, 2.4140, 2.5787, 2.7460] +24-11-19 20:42:34 | D | best error = [ 0.7370, 0.7370, 0.7370, 0.7370, 0.7369] +24-11-19 20:42:34 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:42:34 | D | sum error = [ 2.9151, 3.1004, 3.2929, 3.5000, 3.7110] +24-11-19 20:42:34 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:42:34 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:42:34 | D | sum error = [ 3.9390, 4.1778, 4.4294, 4.6918, 4.9679] +24-11-19 20:42:34 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:42:34 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:42:34 | D | sum error = [ 5.2609, 5.5714, 5.8903, 6.2376, 6.5899] +24-11-19 20:42:34 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:42:34 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:42:34 | D | sum error = [ 6.9727, 7.3722, 7.7878, 8.2382, 8.6995] +24-11-19 20:42:34 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:42:34 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:42:34 | D | sum error = [ 9.1901, 9.7060, 10.2479, 10.8195, 11.4184] +24-11-19 20:42:34 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:42:34 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:42:34 | D | sum error = [ 12.0555, 12.7334, 13.4444, 14.1937, 14.9889] +24-11-19 20:42:34 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:42:34 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:42:34 | D | sum error = [ 15.8186, 16.6985, 17.6190, 18.5902, 19.6076] +24-11-19 20:42:34 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:42:34 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:42:34 | D | sum error = [ 20.6818, 21.8082, 22.9946, 24.2407, 25.5463] +24-11-19 20:42:34 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:42:34 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:42:34 | D | sum error = [ 26.9190, 28.3565, 29.8678, 31.4499, 33.1056] +24-11-19 20:42:34 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:42:34 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:42:34 | D | sum error = [ 34.8339, 36.6421, 38.5274, 40.4920, 42.5411] +24-11-19 20:42:34 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:42:34 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:42:34 | D | sum error = [ 44.6784, 46.8986, 49.2130, 51.6117, 54.1078] +24-11-19 20:42:34 | D | best error = [ 0.7369, 0.7369, 0.7369, 0.7369, 0.7369] +24-11-19 20:42:34 | D | + error = [0.7369] +24-11-19 20:42:34 | D | - Calibrating model.layers.29.mlp.up_proj.weight +24-11-19 20:42:34 | D | + w: sint8 +24-11-19 20:42:34 | D | + x: None +24-11-19 20:42:34 | D | + y: None +24-11-19 20:42:34 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:42:34 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:42:34 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:42:34 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:42:34 | D | - range ratio = [ 1.0000] +24-11-19 20:42:34 | D | sum error = [ 10.0568] +24-11-19 20:42:34 | D | best error = [ 10.0568] +24-11-19 20:42:35 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:42:35 | D | sum error = [ 9.9563, 9.9988, 9.9804, 10.0940, 10.2839] +24-11-19 20:42:35 | D | best error = [ 8.8174, 8.4242, 8.2229, 8.1153, 8.0555] +24-11-19 20:42:35 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:42:35 | D | sum error = [ 10.5881, 10.9227, 11.3834, 11.8719, 12.4706] +24-11-19 20:42:35 | D | best error = [ 8.0241, 8.0091, 8.0034, 8.0012, 8.0003] +24-11-19 20:42:35 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:42:35 | D | sum error = [ 13.2923, 14.0662, 14.9315, 15.9728, 17.1438] +24-11-19 20:42:35 | D | best error = [ 8.0002, 8.0002, 8.0002, 8.0002, 8.0002] +24-11-19 20:42:35 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:42:35 | D | sum error = [ 18.3095, 19.5582, 21.0150, 22.5720, 24.1445] +24-11-19 20:42:35 | D | best error = [ 8.0002, 8.0002, 8.0002, 8.0002, 8.0002] +24-11-19 20:42:35 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:42:35 | D | sum error = [ 25.8795, 27.7167, 29.6488, 31.8077, 33.9738] +24-11-19 20:42:35 | D | best error = [ 8.0002, 8.0002, 8.0002, 8.0002, 8.0002] +24-11-19 20:42:35 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:42:35 | D | sum error = [ 36.3133, 38.7941, 41.4478, 44.1963, 47.1650] +24-11-19 20:42:35 | D | best error = [ 8.0002, 8.0002, 8.0002, 8.0002, 8.0002] +24-11-19 20:42:35 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:42:35 | D | sum error = [ 50.2275, 53.5448, 56.9263, 60.5388, 64.3846] +24-11-19 20:42:35 | D | best error = [ 8.0002, 8.0002, 8.0002, 8.0002, 8.0002] +24-11-19 20:42:35 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:42:35 | D | sum error = [ 68.4033, 72.6572, 77.0942, 81.7903, 86.7182] +24-11-19 20:42:35 | D | best error = [ 8.0002, 8.0002, 8.0002, 8.0002, 8.0002] +24-11-19 20:42:35 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:42:35 | D | sum error = [ 91.9053, 97.3365, 102.9695, 108.9873, 115.1840] +24-11-19 20:42:35 | D | best error = [ 8.0002, 8.0002, 8.0002, 8.0002, 8.0002] +24-11-19 20:42:35 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:42:35 | D | sum error = [ 121.7347, 128.5930, 135.7545, 143.2420, 151.1013] +24-11-19 20:42:35 | D | best error = [ 8.0002, 8.0002, 8.0002, 8.0002, 8.0002] +24-11-19 20:42:35 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:42:35 | D | sum error = [ 159.3330, 167.9365, 176.9112, 186.3040, 196.1014] +24-11-19 20:42:35 | D | best error = [ 8.0002, 8.0002, 8.0002, 8.0002, 8.0002] +24-11-19 20:42:35 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:42:35 | D | sum error = [ 206.2847, 216.9664, 228.0823, 239.6945, 251.7449] +24-11-19 20:42:35 | D | best error = [ 8.0002, 8.0002, 8.0002, 8.0002, 8.0002] +24-11-19 20:42:35 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:42:35 | D | sum error = [ 264.2800, 277.3568, 290.9097, 304.9541, 319.5528] +24-11-19 20:42:35 | D | best error = [ 8.0002, 8.0002, 8.0002, 8.0002, 8.0002] +24-11-19 20:42:35 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:42:35 | D | sum error = [ 334.6940, 350.4383, 366.7314, 383.6386, 401.1312] +24-11-19 20:42:35 | D | best error = [ 8.0002, 8.0002, 8.0002, 8.0002, 8.0002] +24-11-19 20:42:35 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:42:35 | D | sum error = [ 419.2682, 437.9873, 457.3789, 477.3677, 497.9890] +24-11-19 20:42:35 | D | best error = [ 8.0002, 8.0002, 8.0002, 8.0002, 8.0002] +24-11-19 20:42:35 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:42:35 | D | sum error = [ 519.2505, 541.1431, 563.7304, 586.9743, 610.9077] +24-11-19 20:42:35 | D | best error = [ 8.0002, 8.0002, 8.0002, 8.0002, 8.0002] +24-11-19 20:42:35 | D | + error = [8.0002] +24-11-19 20:42:35 | D | - Calibrating model.layers.29.mlp.gate_proj.weight +24-11-19 20:42:35 | D | + w: sint8 +24-11-19 20:42:35 | D | + x: None +24-11-19 20:42:35 | D | + y: None +24-11-19 20:42:35 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:42:35 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:42:35 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:42:35 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:42:35 | D | - range ratio = [ 1.0000] +24-11-19 20:42:35 | D | sum error = [ 12.6723] +24-11-19 20:42:35 | D | best error = [ 12.6723] +24-11-19 20:42:37 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:42:37 | D | sum error = [ 12.6271, 12.6184, 12.6615, 12.7896, 13.0663] +24-11-19 20:42:37 | D | best error = [ 11.1781, 10.6703, 10.4196, 10.2808, 10.2115] +24-11-19 20:42:37 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:42:37 | D | sum error = [ 13.4138, 13.8509, 14.3321, 15.0838, 15.9334] +24-11-19 20:42:37 | D | best error = [ 10.1730, 10.1541, 10.1438, 10.1406, 10.1395] +24-11-19 20:42:37 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:42:37 | D | sum error = [ 16.8201, 17.8233, 19.0299, 20.3275, 21.7959] +24-11-19 20:42:37 | D | best error = [ 10.1392, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:42:37 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:42:37 | D | sum error = [ 23.2848, 24.9620, 26.7620, 28.7049, 30.8315] +24-11-19 20:42:37 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:42:37 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:42:37 | D | sum error = [ 33.0874, 35.4769, 37.9877, 40.6886, 43.6873] +24-11-19 20:42:37 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:42:37 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:42:37 | D | sum error = [ 46.6632, 49.9487, 53.3806, 57.0254, 60.9559] +24-11-19 20:42:37 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:42:37 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:42:37 | D | sum error = [ 65.0789, 69.4994, 74.1649, 79.0767, 84.3355] +24-11-19 20:42:37 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:42:37 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:42:37 | D | sum error = [ 89.8274, 95.7198, 101.9162, 108.4521, 115.3688] +24-11-19 20:42:37 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:42:37 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:42:37 | D | sum error = [ 122.7738, 130.5431, 138.7542, 147.4753, 156.7429] +24-11-19 20:42:37 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:42:37 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:42:37 | D | sum error = [ 166.4199, 176.7214, 187.5989, 199.0653, 211.1492] +24-11-19 20:42:37 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:42:37 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:42:37 | D | sum error = [ 223.9059, 237.2762, 251.3673, 266.2426, 281.8561] +24-11-19 20:42:37 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:42:37 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:42:37 | D | sum error = [ 298.3487, 315.5438, 333.7057, 352.8113, 372.7925] +24-11-19 20:42:37 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:42:37 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:42:37 | D | sum error = [ 393.7591, 415.7596, 438.8588, 462.9886, 488.2315] +24-11-19 20:42:37 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:42:37 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:42:37 | D | sum error = [ 514.5720, 542.0836, 570.7690, 600.6045, 631.5846] +24-11-19 20:42:37 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:42:37 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:42:37 | D | sum error = [ 663.8548, 697.3434, 732.0314, 767.9413, 805.0882] +24-11-19 20:42:37 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:42:37 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:42:37 | D | sum error = [ 843.5115, 883.1638, 924.1202, 966.3435, 1009.8060] +24-11-19 20:42:37 | D | best error = [ 10.1391, 10.1391, 10.1391, 10.1391, 10.1391] +24-11-19 20:42:37 | D | + error = [10.1391] +24-11-19 20:42:37 | D | - Calibrating model.layers.29.mlp.down_proj.weight +24-11-19 20:42:37 | D | + w: sint8 +24-11-19 20:42:37 | D | + x: None +24-11-19 20:42:37 | D | + y: None +24-11-19 20:42:37 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:42:37 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:42:37 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:42:37 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:42:37 | D | - range ratio = [ 1.0000] +24-11-19 20:42:37 | D | sum error = [ 2.3909] +24-11-19 20:42:37 | D | best error = [ 2.3909] +24-11-19 20:42:38 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:42:38 | D | sum error = [ 2.3695, 2.3537, 2.3537, 2.3568, 2.3598] +24-11-19 20:42:38 | D | best error = [ 2.2138, 2.1402, 2.1009, 2.0718, 2.0489] +24-11-19 20:42:38 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:42:38 | D | sum error = [ 2.4009, 2.4189, 2.4711, 2.5233, 2.5746] +24-11-19 20:42:38 | D | best error = [ 2.0313, 2.0181, 2.0062, 1.9959, 1.9878] +24-11-19 20:42:38 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:42:38 | D | sum error = [ 2.6617, 2.7409, 2.8461, 2.9726, 3.0816] +24-11-19 20:42:38 | D | best error = [ 1.9821, 1.9772, 1.9731, 1.9708, 1.9688] +24-11-19 20:42:38 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:42:38 | D | sum error = [ 3.2222, 3.3784, 3.5421, 3.7244, 3.9087] +24-11-19 20:42:38 | D | best error = [ 1.9674, 1.9665, 1.9657, 1.9655, 1.9653] +24-11-19 20:42:38 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:42:38 | D | sum error = [ 4.1143, 4.3330, 4.5671, 4.8109, 5.0751] +24-11-19 20:42:38 | D | best error = [ 1.9651, 1.9651, 1.9650, 1.9650, 1.9649] +24-11-19 20:42:38 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:42:38 | D | sum error = [ 5.3659, 5.6564, 5.9780, 6.3259, 6.6837] +24-11-19 20:42:38 | D | best error = [ 1.9649, 1.9649, 1.9649, 1.9649, 1.9649] +24-11-19 20:42:38 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:42:38 | D | sum error = [ 7.0559, 7.4598, 7.8899, 8.3394, 8.8197] +24-11-19 20:42:38 | D | best error = [ 1.9649, 1.9649, 1.9649, 1.9649, 1.9649] +24-11-19 20:42:38 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:42:38 | D | sum error = [ 9.3315, 9.8770, 10.4464, 11.0545, 11.6965] +24-11-19 20:42:38 | D | best error = [ 1.9649, 1.9649, 1.9649, 1.9649, 1.9649] +24-11-19 20:42:38 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:42:38 | D | sum error = [ 12.3799, 13.1074, 13.8726, 14.6830, 15.5381] +24-11-19 20:42:38 | D | best error = [ 1.9649, 1.9649, 1.9649, 1.9649, 1.9649] +24-11-19 20:42:38 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:42:38 | D | sum error = [ 16.4415, 17.3991, 18.4060, 19.4790, 20.6060] +24-11-19 20:42:38 | D | best error = [ 1.9649, 1.9649, 1.9649, 1.9649, 1.9649] +24-11-19 20:42:38 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:42:38 | D | sum error = [ 21.7948, 23.0509, 24.3753, 25.7693, 27.2463] +24-11-19 20:42:38 | D | best error = [ 1.9649, 1.9649, 1.9649, 1.9649, 1.9649] +24-11-19 20:42:38 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:42:38 | D | sum error = [ 28.7951, 30.4345, 32.1536, 33.9648, 35.8768] +24-11-19 20:42:38 | D | best error = [ 1.9649, 1.9649, 1.9649, 1.9649, 1.9649] +24-11-19 20:42:38 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:42:38 | D | sum error = [ 37.8924, 40.0058, 42.2255, 44.5527, 46.9971] +24-11-19 20:42:38 | D | best error = [ 1.9649, 1.9649, 1.9649, 1.9649, 1.9649] +24-11-19 20:42:38 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:42:38 | D | sum error = [ 49.5563, 52.2389, 55.0607, 58.0043, 61.0936] +24-11-19 20:42:38 | D | best error = [ 1.9649, 1.9649, 1.9649, 1.9649, 1.9649] +24-11-19 20:42:38 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:42:38 | D | sum error = [ 64.3214, 67.7015, 71.2319, 74.9251, 78.7774] +24-11-19 20:42:38 | D | best error = [ 1.9649, 1.9649, 1.9649, 1.9649, 1.9649] +24-11-19 20:42:38 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:42:38 | D | sum error = [ 82.7949, 86.9831, 91.3514, 95.8866, 100.6170] +24-11-19 20:42:38 | D | best error = [ 1.9649, 1.9649, 1.9649, 1.9649, 1.9649] +24-11-19 20:42:38 | D | + error = [1.9649] +24-11-19 20:42:38 | D | - Quantizing model.layers.29.self_attn.q_proj.weight +24-11-19 20:42:39 | D | - Quantizing model.layers.29.self_attn.k_proj.weight +24-11-19 20:42:40 | D | - Quantizing model.layers.29.self_attn.v_proj.weight +24-11-19 20:42:41 | D | - Quantizing model.layers.29.self_attn.o_proj.weight +24-11-19 20:42:42 | D | - Quantizing model.layers.29.mlp.up_proj.weight +24-11-19 20:42:43 | D | - Quantizing model.layers.29.mlp.gate_proj.weight +24-11-19 20:42:43 | D | - Quantizing model.layers.29.mlp.down_proj.weight +24-11-19 20:42:53 | D | - Quantizing layer model.layers.30 +24-11-19 20:42:53 | D | - Calibrating model.layers.30.self_attn.q_proj.weight +24-11-19 20:42:53 | D | + w: sint8 +24-11-19 20:42:53 | D | + x: None +24-11-19 20:42:53 | D | + y: None +24-11-19 20:42:53 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:42:53 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:42:53 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:42:53 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:42:53 | D | - range ratio = [ 1.0000] +24-11-19 20:42:53 | D | sum error = [ 10.5909] +24-11-19 20:42:53 | D | best error = [ 10.5909] +24-11-19 20:43:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:43:05 | D | sum error = [ 10.7556, 10.7812, 10.7105, 11.1577, 11.5709] +24-11-19 20:43:05 | D | best error = [ 10.5909, 10.5909, 10.5909, 10.5909, 10.5909] +24-11-19 20:43:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:43:05 | D | sum error = [ 11.0637, 12.2688, 12.1768, 12.6965, 13.8912] +24-11-19 20:43:05 | D | best error = [ 10.5909, 10.5909, 10.5909, 10.5909, 10.5909] +24-11-19 20:43:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:43:05 | D | sum error = [ 14.2601, 14.9505, 15.8521, 17.0573, 18.3506] +24-11-19 20:43:05 | D | best error = [ 10.5909, 10.5909, 10.5909, 10.5909, 10.5909] +24-11-19 20:43:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:43:05 | D | sum error = [ 19.6173, 21.6470, 23.6995, 25.5539, 27.6323] +24-11-19 20:43:05 | D | best error = [ 10.5909, 10.5909, 10.5909, 10.5909, 10.5909] +24-11-19 20:43:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:43:05 | D | sum error = [ 30.0197, 32.5485, 34.9522, 38.3693, 41.7077] +24-11-19 20:43:05 | D | best error = [ 10.5909, 10.5909, 10.5909, 10.5909, 10.5909] +24-11-19 20:43:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:43:05 | D | sum error = [ 45.5539, 49.0932, 53.7238, 57.7661, 62.5101] +24-11-19 20:43:05 | D | best error = [ 10.5909, 10.5909, 10.5909, 10.5909, 10.5909] +24-11-19 20:43:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:43:05 | D | sum error = [ 67.6435, 73.9526, 78.8607, 85.6940, 92.2024] +24-11-19 20:43:05 | D | best error = [ 10.5909, 10.5909, 10.5909, 10.5909, 10.5909] +24-11-19 20:43:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:43:05 | D | sum error = [ 99.6693, 107.3651, 115.7747, 124.5949, 134.0546] +24-11-19 20:43:05 | D | best error = [ 10.5909, 10.5909, 10.5909, 10.5909, 10.5909] +24-11-19 20:43:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:43:05 | D | sum error = [ 143.9651, 154.8090, 166.3188, 179.4484, 192.6615] +24-11-19 20:43:05 | D | best error = [ 10.5909, 10.5909, 10.5909, 10.5909, 10.5909] +24-11-19 20:43:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:43:05 | D | sum error = [ 206.1862, 221.0278, 237.5141, 254.3701, 273.7797] +24-11-19 20:43:05 | D | best error = [ 10.5909, 10.5909, 10.5909, 10.5909, 10.5909] +24-11-19 20:43:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:43:05 | D | sum error = [ 293.1373, 314.8735, 337.6635, 363.3273, 390.8097] +24-11-19 20:43:05 | D | best error = [ 10.5909, 10.5909, 10.5909, 10.5909, 10.5909] +24-11-19 20:43:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:43:05 | D | sum error = [ 419.8612, 451.8947, 484.8851, 521.0474, 559.3575] +24-11-19 20:43:05 | D | best error = [ 10.5909, 10.5909, 10.5909, 10.5909, 10.5909] +24-11-19 20:43:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:43:05 | D | sum error = [ 601.8672, 645.6440, 693.2448, 743.9449, 798.5240] +24-11-19 20:43:05 | D | best error = [ 10.5909, 10.5909, 10.5909, 10.5909, 10.5909] +24-11-19 20:43:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:43:05 | D | sum error = [ 856.3110, 918.9571, 984.9229, 1055.3385, 1129.6353] +24-11-19 20:43:05 | D | best error = [ 10.5909, 10.5909, 10.5909, 10.5909, 10.5909] +24-11-19 20:43:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:43:05 | D | sum error = [ 1210.0025, 1294.6598, 1383.1594, 1477.0427, 1574.5012] +24-11-19 20:43:05 | D | best error = [ 10.5909, 10.5909, 10.5909, 10.5909, 10.5909] +24-11-19 20:43:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:43:05 | D | sum error = [ 1675.2052, 1779.1112, 1883.4601, 1988.3595, 2093.1609] +24-11-19 20:43:05 | D | best error = [ 10.5909, 10.5909, 10.5909, 10.5909, 10.5909] +24-11-19 20:43:05 | D | + error = [10.5909] +24-11-19 20:43:05 | D | - Calibrating model.layers.30.self_attn.k_proj.weight +24-11-19 20:43:05 | D | + w: sint8 +24-11-19 20:43:05 | D | + x: None +24-11-19 20:43:05 | D | + y: None +24-11-19 20:43:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:05 | D | + finished parsing calibration arguments, ram usage: 13.1 +24-11-19 20:43:05 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:43:05 | D | + finished calculating the original outputs, ram usage: 13.2 +24-11-19 20:43:06 | D | - range ratio = [ 1.0000] +24-11-19 20:43:06 | D | sum error = [ 12.1269] +24-11-19 20:43:06 | D | best error = [ 12.1269] +24-11-19 20:43:17 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:43:17 | D | sum error = [ 9.8978, 10.6532, 10.5025, 11.2603, 11.0180] +24-11-19 20:43:17 | D | best error = [ 9.8978, 9.8978, 9.8978, 9.8978, 9.8978] +24-11-19 20:43:17 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:43:17 | D | sum error = [ 11.4373, 13.8420, 12.0586, 12.5232, 13.8413] +24-11-19 20:43:17 | D | best error = [ 9.8978, 9.8978, 9.8978, 9.8978, 9.8978] +24-11-19 20:43:17 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:43:17 | D | sum error = [ 14.3252, 14.8716, 16.4747, 16.9866, 18.2889] +24-11-19 20:43:17 | D | best error = [ 9.8978, 9.8978, 9.8978, 9.8978, 9.8978] +24-11-19 20:43:17 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:43:17 | D | sum error = [ 20.6589, 21.1668, 22.8241, 24.0242, 25.6139] +24-11-19 20:43:17 | D | best error = [ 9.8978, 9.8978, 9.8978, 9.8978, 9.8978] +24-11-19 20:43:17 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:43:17 | D | sum error = [ 28.6558, 30.2517, 31.3470, 34.2849, 36.6862] +24-11-19 20:43:17 | D | best error = [ 9.8978, 9.8978, 9.8978, 9.8978, 9.8978] +24-11-19 20:43:17 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:43:17 | D | sum error = [ 39.1454, 41.9485, 45.4776, 50.8872, 53.1998] +24-11-19 20:43:17 | D | best error = [ 9.8978, 9.8978, 9.8978, 9.8978, 9.8978] +24-11-19 20:43:17 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:43:17 | D | sum error = [ 58.7493, 62.5656, 68.8191, 72.2598, 78.3534] +24-11-19 20:43:17 | D | best error = [ 9.8978, 9.8978, 9.8978, 9.8978, 9.8978] +24-11-19 20:43:17 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:43:17 | D | sum error = [ 83.9343, 89.4594, 97.2967, 104.7339, 112.8263] +24-11-19 20:43:17 | D | best error = [ 9.8978, 9.8978, 9.8978, 9.8978, 9.8978] +24-11-19 20:43:17 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:43:17 | D | sum error = [ 121.3970, 132.5650, 141.2867, 152.5924, 163.5986] +24-11-19 20:43:17 | D | best error = [ 9.8978, 9.8978, 9.8978, 9.8978, 9.8978] +24-11-19 20:43:17 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:43:17 | D | sum error = [ 179.0145, 192.6036, 206.4121, 222.9968, 240.9307] +24-11-19 20:43:17 | D | best error = [ 9.8978, 9.8978, 9.8978, 9.8978, 9.8978] +24-11-19 20:43:17 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:43:17 | D | sum error = [ 259.4427, 279.0390, 300.2819, 322.9884, 348.0928] +24-11-19 20:43:17 | D | best error = [ 9.8978, 9.8978, 9.8978, 9.8978, 9.8978] +24-11-19 20:43:17 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:43:17 | D | sum error = [ 375.3868, 403.9578, 436.1656, 470.0781, 505.6213] +24-11-19 20:43:17 | D | best error = [ 9.8978, 9.8978, 9.8978, 9.8978, 9.8978] +24-11-19 20:43:17 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:43:17 | D | sum error = [ 543.6077, 583.8017, 626.6709, 670.6378, 718.0023] +24-11-19 20:43:17 | D | best error = [ 9.8978, 9.8978, 9.8978, 9.8978, 9.8978] +24-11-19 20:43:17 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:43:17 | D | sum error = [ 768.1152, 822.7130, 880.9451, 943.2009, 1009.7013] +24-11-19 20:43:17 | D | best error = [ 9.8978, 9.8978, 9.8978, 9.8978, 9.8978] +24-11-19 20:43:17 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:43:17 | D | sum error = [ 1080.2316, 1155.4482, 1237.0794, 1323.6985, 1414.9231] +24-11-19 20:43:17 | D | best error = [ 9.8978, 9.8978, 9.8978, 9.8978, 9.8978] +24-11-19 20:43:17 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:43:17 | D | sum error = [ 1512.0790, 1613.7099, 1720.5722, 1829.7049, 1940.3989] +24-11-19 20:43:17 | D | best error = [ 9.8978, 9.8978, 9.8978, 9.8978, 9.8978] +24-11-19 20:43:17 | D | + error = [9.8978] +24-11-19 20:43:17 | D | - Calibrating model.layers.30.self_attn.v_proj.weight +24-11-19 20:43:17 | D | + w: sint8 +24-11-19 20:43:17 | D | + x: None +24-11-19 20:43:17 | D | + y: None +24-11-19 20:43:17 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:43:17 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:43:17 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:43:17 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:43:17 | D | - range ratio = [ 1.0000] +24-11-19 20:43:17 | D | sum error = [ 3.5818] +24-11-19 20:43:17 | D | best error = [ 3.5818] +24-11-19 20:43:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:43:18 | D | sum error = [ 3.5417, 3.5693, 3.5478, 3.5820, 3.7175] +24-11-19 20:43:18 | D | best error = [ 3.1896, 3.0587, 2.9833, 2.9482, 2.9283] +24-11-19 20:43:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:43:18 | D | sum error = [ 3.8242, 3.9140, 4.0930, 4.2653, 4.4558] +24-11-19 20:43:18 | D | best error = [ 2.9181, 2.9133, 2.9114, 2.9109, 2.9104] +24-11-19 20:43:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:43:18 | D | sum error = [ 4.7647, 5.0933, 5.3039, 5.7911, 6.1630] +24-11-19 20:43:18 | D | best error = [ 2.9104, 2.9104, 2.9104, 2.9104, 2.9104] +24-11-19 20:43:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:43:18 | D | sum error = [ 6.5850, 7.0691, 7.6120, 8.1764, 8.7576] +24-11-19 20:43:18 | D | best error = [ 2.9104, 2.9104, 2.9104, 2.9104, 2.9104] +24-11-19 20:43:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:43:18 | D | sum error = [ 9.4522, 10.0883, 10.7927, 11.5209, 12.3034] +24-11-19 20:43:18 | D | best error = [ 2.9104, 2.9104, 2.9104, 2.9104, 2.9104] +24-11-19 20:43:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:43:18 | D | sum error = [ 13.1819, 14.0474, 14.9998, 15.9813, 17.0099] +24-11-19 20:43:18 | D | best error = [ 2.9104, 2.9104, 2.9104, 2.9104, 2.9104] +24-11-19 20:43:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:43:18 | D | sum error = [ 18.0624, 19.1981, 20.3932, 21.5915, 22.9230] +24-11-19 20:43:18 | D | best error = [ 2.9104, 2.9104, 2.9104, 2.9104, 2.9104] +24-11-19 20:43:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:43:18 | D | sum error = [ 24.2762, 25.6699, 27.1606, 28.6845, 30.3049] +24-11-19 20:43:18 | D | best error = [ 2.9104, 2.9104, 2.9104, 2.9104, 2.9104] +24-11-19 20:43:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:43:18 | D | sum error = [ 32.0435, 33.8559, 35.7540, 37.6781, 39.7535] +24-11-19 20:43:18 | D | best error = [ 2.9104, 2.9104, 2.9104, 2.9104, 2.9104] +24-11-19 20:43:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:43:18 | D | sum error = [ 41.9462, 44.1777, 46.5500, 48.9899, 51.5443] +24-11-19 20:43:18 | D | best error = [ 2.9104, 2.9104, 2.9104, 2.9104, 2.9104] +24-11-19 20:43:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:43:18 | D | sum error = [ 54.1458, 56.9151, 59.8203, 62.8050, 65.8836] +24-11-19 20:43:18 | D | best error = [ 2.9104, 2.9104, 2.9104, 2.9104, 2.9104] +24-11-19 20:43:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:43:18 | D | sum error = [ 69.0578, 72.3475, 75.7314, 79.2640, 82.8961] +24-11-19 20:43:18 | D | best error = [ 2.9104, 2.9104, 2.9104, 2.9104, 2.9104] +24-11-19 20:43:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:43:18 | D | sum error = [ 86.6653, 90.5495, 94.5307, 98.6539, 102.8901] +24-11-19 20:43:18 | D | best error = [ 2.9104, 2.9104, 2.9104, 2.9104, 2.9104] +24-11-19 20:43:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:43:18 | D | sum error = [ 107.2633, 111.7829, 116.4406, 121.2639, 126.2142] +24-11-19 20:43:18 | D | best error = [ 2.9104, 2.9104, 2.9104, 2.9104, 2.9104] +24-11-19 20:43:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:43:18 | D | sum error = [ 131.2796, 136.5046, 141.8940, 147.4378, 153.1162] +24-11-19 20:43:18 | D | best error = [ 2.9104, 2.9104, 2.9104, 2.9104, 2.9104] +24-11-19 20:43:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:43:18 | D | sum error = [ 158.9554, 164.9312, 171.0582, 177.3134, 183.7114] +24-11-19 20:43:18 | D | best error = [ 2.9104, 2.9104, 2.9104, 2.9104, 2.9104] +24-11-19 20:43:18 | D | + error = [2.9104] +24-11-19 20:43:18 | D | - Calibrating model.layers.30.self_attn.o_proj.weight +24-11-19 20:43:18 | D | + w: sint8 +24-11-19 20:43:18 | D | + x: None +24-11-19 20:43:18 | D | + y: None +24-11-19 20:43:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:43:18 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:43:18 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:43:18 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:43:18 | D | - range ratio = [ 1.0000] +24-11-19 20:43:18 | D | sum error = [ 1.0639] +24-11-19 20:43:18 | D | best error = [ 1.0639] +24-11-19 20:43:18 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:43:18 | D | sum error = [ 1.0498, 1.0495, 1.0489, 1.0600, 1.0738] +24-11-19 20:43:18 | D | best error = [ 0.9750, 0.9389, 0.9176, 0.9045, 0.8957] +24-11-19 20:43:18 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:43:18 | D | sum error = [ 1.0877, 1.1213, 1.1578, 1.2033, 1.2539] +24-11-19 20:43:18 | D | best error = [ 0.8893, 0.8851, 0.8826, 0.8811, 0.8798] +24-11-19 20:43:18 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:43:18 | D | sum error = [ 1.3113, 1.3808, 1.4521, 1.5394, 1.6380] +24-11-19 20:43:18 | D | best error = [ 0.8788, 0.8783, 0.8779, 0.8776, 0.8775] +24-11-19 20:43:18 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:43:18 | D | sum error = [ 1.7341, 1.8443, 1.9600, 2.0890, 2.2236] +24-11-19 20:43:18 | D | best error = [ 0.8774, 0.8773, 0.8773, 0.8773, 0.8772] +24-11-19 20:43:18 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:43:18 | D | sum error = [ 2.3708, 2.5219, 2.6838, 2.8595, 3.0454] +24-11-19 20:43:18 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 20:43:18 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:43:18 | D | sum error = [ 3.2312, 3.4363, 3.6551, 3.8868, 4.1238] +24-11-19 20:43:18 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 20:43:18 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:43:18 | D | sum error = [ 4.3711, 4.6420, 4.9192, 5.2172, 5.5368] +24-11-19 20:43:18 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 20:43:18 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:43:18 | D | sum error = [ 5.8667, 6.2104, 6.5717, 6.9598, 7.3613] +24-11-19 20:43:18 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 20:43:18 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:43:18 | D | sum error = [ 7.7914, 8.2383, 8.7066, 9.2036, 9.7244] +24-11-19 20:43:18 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 20:43:18 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:43:18 | D | sum error = [ 10.2755, 10.8491, 11.4564, 12.0912, 12.7598] +24-11-19 20:43:18 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 20:43:18 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:43:18 | D | sum error = [ 13.4650, 14.2036, 14.9710, 15.7841, 16.6315] +24-11-19 20:43:18 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 20:43:18 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:43:18 | D | sum error = [ 17.5194, 18.4507, 19.4281, 20.4526, 21.5260] +24-11-19 20:43:18 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 20:43:18 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:43:18 | D | sum error = [ 22.6439, 23.8172, 25.0425, 26.3209, 27.6621] +24-11-19 20:43:18 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 20:43:18 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:43:18 | D | sum error = [ 29.0649, 30.5339, 32.0669, 33.6684, 35.3373] +24-11-19 20:43:18 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 20:43:18 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:43:18 | D | sum error = [ 37.0775, 38.8904, 40.7812, 42.7465, 44.7885] +24-11-19 20:43:18 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 20:43:18 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:43:18 | D | sum error = [ 46.9087, 49.1104, 51.3969, 53.7651, 56.2220] +24-11-19 20:43:18 | D | best error = [ 0.8772, 0.8772, 0.8772, 0.8772, 0.8772] +24-11-19 20:43:18 | D | + error = [0.8772] +24-11-19 20:43:18 | D | - Calibrating model.layers.30.mlp.up_proj.weight +24-11-19 20:43:18 | D | + w: sint8 +24-11-19 20:43:18 | D | + x: None +24-11-19 20:43:18 | D | + y: None +24-11-19 20:43:18 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:43:18 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:43:18 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:43:19 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:43:19 | D | - range ratio = [ 1.0000] +24-11-19 20:43:19 | D | sum error = [ 10.3653] +24-11-19 20:43:19 | D | best error = [ 10.3653] +24-11-19 20:43:20 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:43:20 | D | sum error = [ 10.3163, 10.2791, 10.3298, 10.4654, 10.6409] +24-11-19 20:43:20 | D | best error = [ 9.1120, 8.6780, 8.4645, 8.3497, 8.2898] +24-11-19 20:43:20 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:43:20 | D | sum error = [ 10.9357, 11.2734, 11.7295, 12.2768, 12.9658] +24-11-19 20:43:20 | D | best error = [ 8.2579, 8.2417, 8.2352, 8.2327, 8.2320] +24-11-19 20:43:20 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:43:20 | D | sum error = [ 13.7146, 14.5802, 15.5507, 16.5545, 17.7350] +24-11-19 20:43:20 | D | best error = [ 8.2317, 8.2317, 8.2316, 8.2316, 8.2316] +24-11-19 20:43:20 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:43:20 | D | sum error = [ 19.0015, 20.3824, 21.8208, 23.4448, 25.1544] +24-11-19 20:43:20 | D | best error = [ 8.2316, 8.2316, 8.2316, 8.2316, 8.2316] +24-11-19 20:43:20 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:43:20 | D | sum error = [ 26.9491, 28.8905, 30.9654, 33.1904, 35.5050] +24-11-19 20:43:20 | D | best error = [ 8.2316, 8.2316, 8.2316, 8.2316, 8.2316] +24-11-19 20:43:20 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:43:20 | D | sum error = [ 38.0193, 40.6582, 43.4850, 46.4260, 49.6122] +24-11-19 20:43:20 | D | best error = [ 8.2316, 8.2316, 8.2316, 8.2316, 8.2316] +24-11-19 20:43:20 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:43:20 | D | sum error = [ 52.9820, 56.5452, 60.2916, 64.2427, 68.4840] +24-11-19 20:43:20 | D | best error = [ 8.2316, 8.2316, 8.2316, 8.2316, 8.2316] +24-11-19 20:43:20 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:43:20 | D | sum error = [ 72.9067, 77.6140, 82.5702, 87.7574, 93.2640] +24-11-19 20:43:20 | D | best error = [ 8.2316, 8.2316, 8.2316, 8.2316, 8.2316] +24-11-19 20:43:20 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:43:20 | D | sum error = [ 99.0845, 105.2072, 111.6643, 118.5008, 125.6701] +24-11-19 20:43:20 | D | best error = [ 8.2316, 8.2316, 8.2316, 8.2316, 8.2316] +24-11-19 20:43:20 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:43:20 | D | sum error = [ 133.2528, 141.2986, 149.7410, 158.6686, 168.0448] +24-11-19 20:43:20 | D | best error = [ 8.2316, 8.2316, 8.2316, 8.2316, 8.2316] +24-11-19 20:43:20 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:43:20 | D | sum error = [ 177.8904, 188.2617, 199.1562, 210.5517, 222.5576] +24-11-19 20:43:20 | D | best error = [ 8.2316, 8.2316, 8.2316, 8.2316, 8.2316] +24-11-19 20:43:20 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:43:20 | D | sum error = [ 235.1505, 248.3544, 262.1746, 276.7073, 291.9808] +24-11-19 20:43:20 | D | best error = [ 8.2316, 8.2316, 8.2316, 8.2316, 8.2316] +24-11-19 20:43:20 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:43:20 | D | sum error = [ 307.9129, 324.5944, 341.9932, 360.2148, 379.1631] +24-11-19 20:43:20 | D | best error = [ 8.2316, 8.2316, 8.2316, 8.2316, 8.2316] +24-11-19 20:43:20 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:43:20 | D | sum error = [ 398.9887, 419.6634, 441.1945, 463.6046, 486.9104] +24-11-19 20:43:20 | D | best error = [ 8.2316, 8.2316, 8.2316, 8.2316, 8.2316] +24-11-19 20:43:20 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:43:20 | D | sum error = [ 511.0760, 536.1750, 562.1986, 589.1960, 617.0975] +24-11-19 20:43:20 | D | best error = [ 8.2316, 8.2316, 8.2316, 8.2316, 8.2316] +24-11-19 20:43:20 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:43:20 | D | sum error = [ 645.9316, 675.7523, 706.5062, 738.2094, 770.8086] +24-11-19 20:43:20 | D | best error = [ 8.2316, 8.2316, 8.2316, 8.2316, 8.2316] +24-11-19 20:43:20 | D | + error = [8.2316] +24-11-19 20:43:20 | D | - Calibrating model.layers.30.mlp.gate_proj.weight +24-11-19 20:43:20 | D | + w: sint8 +24-11-19 20:43:20 | D | + x: None +24-11-19 20:43:20 | D | + y: None +24-11-19 20:43:20 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:43:20 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:43:20 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:43:20 | D | + finished calculating the original outputs, ram usage: 13.6 +24-11-19 20:43:20 | D | - range ratio = [ 1.0000] +24-11-19 20:43:20 | D | sum error = [ 13.2770] +24-11-19 20:43:20 | D | best error = [ 13.2770] +24-11-19 20:43:21 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:43:21 | D | sum error = [ 13.1998, 13.1619, 13.2527, 13.3745, 13.5824] +24-11-19 20:43:21 | D | best error = [ 11.6505, 11.1165, 10.8482, 10.6978, 10.6178] +24-11-19 20:43:21 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:43:21 | D | sum error = [ 14.0227, 14.4814, 15.0498, 15.7266, 16.6067] +24-11-19 20:43:21 | D | best error = [ 10.5765, 10.5563, 10.5485, 10.5455, 10.5439] +24-11-19 20:43:21 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:43:21 | D | sum error = [ 17.5888, 18.6763, 19.9720, 21.3863, 22.7309] +24-11-19 20:43:21 | D | best error = [ 10.5437, 10.5437, 10.5436, 10.5436, 10.5436] +24-11-19 20:43:21 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:43:21 | D | sum error = [ 24.4161, 26.1991, 28.2114, 30.2674, 32.4591] +24-11-19 20:43:21 | D | best error = [ 10.5436, 10.5436, 10.5436, 10.5436, 10.5436] +24-11-19 20:43:21 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:43:21 | D | sum error = [ 34.9224, 37.5044, 40.1966, 43.1804, 46.2326] +24-11-19 20:43:21 | D | best error = [ 10.5436, 10.5436, 10.5436, 10.5436, 10.5436] +24-11-19 20:43:21 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:43:21 | D | sum error = [ 49.6220, 53.2019, 56.9155, 60.8896, 65.2031] +24-11-19 20:43:21 | D | best error = [ 10.5436, 10.5436, 10.5436, 10.5436, 10.5436] +24-11-19 20:43:21 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:43:21 | D | sum error = [ 69.7349, 74.4371, 79.6081, 84.9964, 90.7246] +24-11-19 20:43:21 | D | best error = [ 10.5436, 10.5436, 10.5436, 10.5436, 10.5436] +24-11-19 20:43:21 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:43:21 | D | sum error = [ 96.8709, 103.3778, 110.2331, 117.5397, 125.3655] +24-11-19 20:43:21 | D | best error = [ 10.5436, 10.5436, 10.5436, 10.5436, 10.5436] +24-11-19 20:43:21 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:43:21 | D | sum error = [ 133.5795, 142.3254, 151.5865, 161.4234, 171.8424] +24-11-19 20:43:21 | D | best error = [ 10.5436, 10.5436, 10.5436, 10.5436, 10.5436] +24-11-19 20:43:21 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:43:21 | D | sum error = [ 182.9205, 194.6334, 207.0432, 220.1503, 234.0216] +24-11-19 20:43:21 | D | best error = [ 10.5436, 10.5436, 10.5436, 10.5436, 10.5436] +24-11-19 20:43:21 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:43:21 | D | sum error = [ 248.7039, 264.1656, 280.5121, 297.7681, 315.9377] +24-11-19 20:43:21 | D | best error = [ 10.5436, 10.5436, 10.5436, 10.5436, 10.5436] +24-11-19 20:43:21 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:43:21 | D | sum error = [ 335.0904, 355.2690, 376.5511, 398.9259, 422.3867] +24-11-19 20:43:21 | D | best error = [ 10.5436, 10.5436, 10.5436, 10.5436, 10.5436] +24-11-19 20:43:21 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:43:21 | D | sum error = [ 447.0929, 473.0310, 500.2287, 528.7170, 558.4202] +24-11-19 20:43:21 | D | best error = [ 10.5436, 10.5436, 10.5436, 10.5436, 10.5436] +24-11-19 20:43:21 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:43:21 | D | sum error = [ 589.5704, 622.1127, 656.1111, 691.5952, 728.5364] +24-11-19 20:43:21 | D | best error = [ 10.5436, 10.5436, 10.5436, 10.5436, 10.5436] +24-11-19 20:43:21 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:43:21 | D | sum error = [ 766.9579, 806.8908, 848.4896, 891.5373, 936.1659] +24-11-19 20:43:21 | D | best error = [ 10.5436, 10.5436, 10.5436, 10.5436, 10.5436] +24-11-19 20:43:21 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:43:21 | D | sum error = [ 982.3408, 1030.0707, 1079.3645, 1130.1069, 1182.4593] +24-11-19 20:43:21 | D | best error = [ 10.5436, 10.5436, 10.5436, 10.5436, 10.5436] +24-11-19 20:43:21 | D | + error = [10.5436] +24-11-19 20:43:21 | D | - Calibrating model.layers.30.mlp.down_proj.weight +24-11-19 20:43:21 | D | + w: sint8 +24-11-19 20:43:21 | D | + x: None +24-11-19 20:43:21 | D | + y: None +24-11-19 20:43:21 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:43:21 | D | + finished parsing calibration arguments, ram usage: 13.1 +24-11-19 20:43:21 | D | + finished reseting calibrator, ram usage: 13.1 +24-11-19 20:43:21 | D | + finished calculating the original outputs, ram usage: 13.2 +24-11-19 20:43:21 | D | - range ratio = [ 1.0000] +24-11-19 20:43:21 | D | sum error = [ 3.9132] +24-11-19 20:43:21 | D | best error = [ 3.9132] +24-11-19 20:43:23 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:43:23 | D | sum error = [ 3.9152, 3.9558, 4.0144, 4.1530, 4.3186] +24-11-19 20:43:23 | D | best error = [ 3.5766, 3.4407, 3.3618, 3.3110, 3.2725] +24-11-19 20:43:23 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:43:23 | D | sum error = [ 4.5290, 4.7807, 5.0759, 5.3750, 5.7498] +24-11-19 20:43:23 | D | best error = [ 3.2404, 3.2121, 3.1886, 3.1689, 3.1515] +24-11-19 20:43:23 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:43:23 | D | sum error = [ 6.1259, 6.5433, 6.9788, 7.4286, 7.9287] +24-11-19 20:43:23 | D | best error = [ 3.1370, 3.1236, 3.1125, 3.1050, 3.0984] +24-11-19 20:43:23 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:43:23 | D | sum error = [ 8.4044, 8.9275, 9.4637, 10.0303, 10.6114] +24-11-19 20:43:23 | D | best error = [ 3.0929, 3.0875, 3.0842, 3.0813, 3.0791] +24-11-19 20:43:23 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:43:23 | D | sum error = [ 11.2088, 11.8269, 12.4693, 13.1192, 13.8062] +24-11-19 20:43:23 | D | best error = [ 3.0773, 3.0755, 3.0742, 3.0736, 3.0729] +24-11-19 20:43:23 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:43:23 | D | sum error = [ 14.4982, 15.2214, 15.9578, 16.7360, 17.5176] +24-11-19 20:43:23 | D | best error = [ 3.0727, 3.0725, 3.0723, 3.0723, 3.0722] +24-11-19 20:43:23 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:43:23 | D | sum error = [ 18.3488, 19.1891, 20.0598, 20.9640, 21.8986] +24-11-19 20:43:23 | D | best error = [ 3.0722, 3.0721, 3.0721, 3.0721, 3.0721] +24-11-19 20:43:23 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:43:23 | D | sum error = [ 22.8655, 23.8549, 24.8975, 25.9523, 27.0543] +24-11-19 20:43:23 | D | best error = [ 3.0721, 3.0721, 3.0721, 3.0721, 3.0721] +24-11-19 20:43:23 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:43:23 | D | sum error = [ 28.1940, 29.3836, 30.6201, 31.8984, 33.2385] +24-11-19 20:43:23 | D | best error = [ 3.0721, 3.0721, 3.0721, 3.0721, 3.0721] +24-11-19 20:43:23 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:43:23 | D | sum error = [ 34.6276, 36.0804, 37.5978, 39.1589, 40.8017] +24-11-19 20:43:23 | D | best error = [ 3.0721, 3.0721, 3.0721, 3.0721, 3.0721] +24-11-19 20:43:23 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:43:23 | D | sum error = [ 42.5311, 44.3331, 46.2211, 48.2076, 50.2816] +24-11-19 20:43:23 | D | best error = [ 3.0721, 3.0721, 3.0721, 3.0721, 3.0721] +24-11-19 20:43:23 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:43:23 | D | sum error = [ 52.4698, 54.7779, 57.2173, 59.7747, 62.4870] +24-11-19 20:43:23 | D | best error = [ 3.0721, 3.0721, 3.0721, 3.0721, 3.0721] +24-11-19 20:43:23 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:43:23 | D | sum error = [ 65.3417, 68.3482, 71.5174, 74.8772, 78.4164] +24-11-19 20:43:23 | D | best error = [ 3.0721, 3.0721, 3.0721, 3.0721, 3.0721] +24-11-19 20:43:23 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:43:23 | D | sum error = [ 82.1563, 86.1029, 90.2754, 94.6937, 99.3676] +24-11-19 20:43:23 | D | best error = [ 3.0721, 3.0721, 3.0721, 3.0721, 3.0721] +24-11-19 20:43:23 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:43:23 | D | sum error = [ 104.3002, 109.5192, 115.0414, 120.8887, 127.0826] +24-11-19 20:43:23 | D | best error = [ 3.0721, 3.0721, 3.0721, 3.0721, 3.0721] +24-11-19 20:43:23 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:43:23 | D | sum error = [ 133.6327, 140.5510, 147.8638, 155.5947, 163.7571] +24-11-19 20:43:23 | D | best error = [ 3.0721, 3.0721, 3.0721, 3.0721, 3.0721] +24-11-19 20:43:23 | D | + error = [3.0721] +24-11-19 20:43:23 | D | - Quantizing model.layers.30.self_attn.q_proj.weight +24-11-19 20:43:24 | D | - Quantizing model.layers.30.self_attn.k_proj.weight +24-11-19 20:43:24 | D | - Quantizing model.layers.30.self_attn.v_proj.weight +24-11-19 20:43:25 | D | - Quantizing model.layers.30.self_attn.o_proj.weight +24-11-19 20:43:26 | D | - Quantizing model.layers.30.mlp.up_proj.weight +24-11-19 20:43:27 | D | - Quantizing model.layers.30.mlp.gate_proj.weight +24-11-19 20:43:28 | D | - Quantizing model.layers.30.mlp.down_proj.weight +24-11-19 20:43:38 | D | - Quantizing layer model.layers.31 +24-11-19 20:43:38 | D | - Calibrating model.layers.31.self_attn.q_proj.weight +24-11-19 20:43:38 | D | + w: sint8 +24-11-19 20:43:38 | D | + x: None +24-11-19 20:43:38 | D | + y: None +24-11-19 20:43:38 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:38 | D | + finished parsing calibration arguments, ram usage: 13.0 +24-11-19 20:43:38 | D | + finished reseting calibrator, ram usage: 13.1 +24-11-19 20:43:38 | D | + finished calculating the original outputs, ram usage: 13.1 +24-11-19 20:43:38 | D | - range ratio = [ 1.0000] +24-11-19 20:43:38 | D | sum error = [ 8.7587] +24-11-19 20:43:38 | D | best error = [ 8.7587] +24-11-19 20:43:51 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:43:51 | D | sum error = [ 8.6290, 8.7936, 9.2897, 8.7684, 9.2866] +24-11-19 20:43:51 | D | best error = [ 8.6290, 8.6290, 8.6290, 8.6290, 8.6290] +24-11-19 20:43:51 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:43:51 | D | sum error = [ 9.5356, 9.7971, 10.1895, 10.5837, 11.6525] +24-11-19 20:43:51 | D | best error = [ 8.6290, 8.6290, 8.6290, 8.6290, 8.6290] +24-11-19 20:43:51 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:43:51 | D | sum error = [ 12.1460, 12.8498, 14.0141, 15.8858, 17.2831] +24-11-19 20:43:51 | D | best error = [ 8.6290, 8.6290, 8.6290, 8.6290, 8.6290] +24-11-19 20:43:51 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:43:51 | D | sum error = [ 17.3657, 18.8734, 20.5344, 22.8394, 24.0233] +24-11-19 20:43:51 | D | best error = [ 8.6290, 8.6290, 8.6290, 8.6290, 8.6290] +24-11-19 20:43:51 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:43:51 | D | sum error = [ 27.1028, 28.9616, 31.4470, 33.4158, 36.3960] +24-11-19 20:43:51 | D | best error = [ 8.6290, 8.6290, 8.6290, 8.6290, 8.6290] +24-11-19 20:43:51 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:43:51 | D | sum error = [ 39.4292, 42.5136, 46.1198, 49.9370, 53.0307] +24-11-19 20:43:51 | D | best error = [ 8.6290, 8.6290, 8.6290, 8.6290, 8.6290] +24-11-19 20:43:51 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:43:51 | D | sum error = [ 57.4237, 62.3566, 67.4977, 72.7461, 79.0798] +24-11-19 20:43:51 | D | best error = [ 8.6290, 8.6290, 8.6290, 8.6290, 8.6290] +24-11-19 20:43:51 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:43:51 | D | sum error = [ 85.2597, 92.3901, 99.0826, 107.3492, 115.5494] +24-11-19 20:43:51 | D | best error = [ 8.6290, 8.6290, 8.6290, 8.6290, 8.6290] +24-11-19 20:43:51 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:43:51 | D | sum error = [ 124.8835, 134.9531, 144.8835, 156.3952, 168.2235] +24-11-19 20:43:51 | D | best error = [ 8.6290, 8.6290, 8.6290, 8.6290, 8.6290] +24-11-19 20:43:51 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:43:51 | D | sum error = [ 180.9949, 194.9965, 210.0993, 226.1789, 243.9744] +24-11-19 20:43:51 | D | best error = [ 8.6290, 8.6290, 8.6290, 8.6290, 8.6290] +24-11-19 20:43:51 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:43:51 | D | sum error = [ 262.5695, 282.8872, 305.3828, 328.9988, 354.8059] +24-11-19 20:43:51 | D | best error = [ 8.6290, 8.6290, 8.6290, 8.6290, 8.6290] +24-11-19 20:43:51 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:43:51 | D | sum error = [ 382.6029, 412.7757, 444.6592, 480.6421, 518.5414] +24-11-19 20:43:51 | D | best error = [ 8.6290, 8.6290, 8.6290, 8.6290, 8.6290] +24-11-19 20:43:51 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:43:51 | D | sum error = [ 560.4763, 606.0473, 656.1583, 710.7569, 769.8058] +24-11-19 20:43:51 | D | best error = [ 8.6290, 8.6290, 8.6290, 8.6290, 8.6290] +24-11-19 20:43:51 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:43:51 | D | sum error = [ 834.1659, 904.1179, 980.8584, 1063.9377, 1154.5197] +24-11-19 20:43:51 | D | best error = [ 8.6290, 8.6290, 8.6290, 8.6290, 8.6290] +24-11-19 20:43:51 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:43:51 | D | sum error = [ 1253.1046, 1360.5095, 1476.3623, 1601.4565, 1735.1922] +24-11-19 20:43:51 | D | best error = [ 8.6290, 8.6290, 8.6290, 8.6290, 8.6290] +24-11-19 20:43:51 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:43:51 | D | sum error = [ 1878.2725, 2029.4756, 2189.6260, 2354.0235, 2524.1765] +24-11-19 20:43:51 | D | best error = [ 8.6290, 8.6290, 8.6290, 8.6290, 8.6290] +24-11-19 20:43:51 | D | + error = [8.6290] +24-11-19 20:43:51 | D | - Calibrating model.layers.31.self_attn.k_proj.weight +24-11-19 20:43:51 | D | + w: sint8 +24-11-19 20:43:51 | D | + x: None +24-11-19 20:43:51 | D | + y: None +24-11-19 20:43:51 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:43:51 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:43:51 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:43:51 | D | + finished calculating the original outputs, ram usage: 13.9 +24-11-19 20:43:51 | D | - range ratio = [ 1.0000] +24-11-19 20:43:51 | D | sum error = [ 9.8257] +24-11-19 20:43:51 | D | best error = [ 9.8257] +24-11-19 20:44:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:44:04 | D | sum error = [ 12.1170, 10.0690, 10.9889, 13.8287, 12.4489] +24-11-19 20:44:04 | D | best error = [ 9.8257, 9.8257, 9.8257, 9.8257, 9.8257] +24-11-19 20:44:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:44:04 | D | sum error = [ 11.6431, 10.8913, 11.5616, 12.7836, 13.0606] +24-11-19 20:44:04 | D | best error = [ 9.8257, 9.8257, 9.8257, 9.8257, 9.8257] +24-11-19 20:44:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:44:04 | D | sum error = [ 14.0348, 15.3293, 16.4160, 16.6541, 18.8029] +24-11-19 20:44:04 | D | best error = [ 9.8257, 9.8257, 9.8257, 9.8257, 9.8257] +24-11-19 20:44:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:44:04 | D | sum error = [ 19.2449, 20.8748, 22.7058, 23.7043, 25.2916] +24-11-19 20:44:04 | D | best error = [ 9.8257, 9.8257, 9.8257, 9.8257, 9.8257] +24-11-19 20:44:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:44:04 | D | sum error = [ 26.4899, 28.4307, 30.9212, 33.1289, 35.2021] +24-11-19 20:44:04 | D | best error = [ 9.8257, 9.8257, 9.8257, 9.8257, 9.8257] +24-11-19 20:44:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:44:04 | D | sum error = [ 38.0601, 40.1322, 43.0587, 46.8304, 50.8255] +24-11-19 20:44:04 | D | best error = [ 9.8257, 9.8257, 9.8257, 9.8257, 9.8257] +24-11-19 20:44:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:44:04 | D | sum error = [ 55.3335, 58.8638, 64.6795, 71.0291, 75.5080] +24-11-19 20:44:04 | D | best error = [ 9.8257, 9.8257, 9.8257, 9.8257, 9.8257] +24-11-19 20:44:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:44:04 | D | sum error = [ 82.7940, 90.5180, 98.8045, 108.0645, 118.4133] +24-11-19 20:44:04 | D | best error = [ 9.8257, 9.8257, 9.8257, 9.8257, 9.8257] +24-11-19 20:44:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:44:04 | D | sum error = [ 126.0821, 137.8517, 148.7510, 162.1288, 175.6045] +24-11-19 20:44:04 | D | best error = [ 9.8257, 9.8257, 9.8257, 9.8257, 9.8257] +24-11-19 20:44:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:44:04 | D | sum error = [ 191.2409, 207.1309, 224.2548, 242.7967, 264.3817] +24-11-19 20:44:04 | D | best error = [ 9.8257, 9.8257, 9.8257, 9.8257, 9.8257] +24-11-19 20:44:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:44:04 | D | sum error = [ 285.2126, 309.7240, 335.0346, 362.5695, 390.3703] +24-11-19 20:44:04 | D | best error = [ 9.8257, 9.8257, 9.8257, 9.8257, 9.8257] +24-11-19 20:44:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:44:04 | D | sum error = [ 425.5154, 458.2935, 494.2572, 532.5793, 575.1769] +24-11-19 20:44:04 | D | best error = [ 9.8257, 9.8257, 9.8257, 9.8257, 9.8257] +24-11-19 20:44:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:44:04 | D | sum error = [ 619.3210, 667.9669, 719.9230, 776.3170, 837.9353] +24-11-19 20:44:04 | D | best error = [ 9.8257, 9.8257, 9.8257, 9.8257, 9.8257] +24-11-19 20:44:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:44:04 | D | sum error = [ 905.4281, 981.5568, 1062.7571, 1151.3537, 1246.2596] +24-11-19 20:44:04 | D | best error = [ 9.8257, 9.8257, 9.8257, 9.8257, 9.8257] +24-11-19 20:44:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:44:04 | D | sum error = [ 1349.6138, 1461.8032, 1579.5373, 1707.6563, 1844.7605] +24-11-19 20:44:04 | D | best error = [ 9.8257, 9.8257, 9.8257, 9.8257, 9.8257] +24-11-19 20:44:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:44:04 | D | sum error = [ 1991.2319, 2142.9694, 2299.7089, 2462.8181, 2627.7504] +24-11-19 20:44:04 | D | best error = [ 9.8257, 9.8257, 9.8257, 9.8257, 9.8257] +24-11-19 20:44:04 | D | + error = [9.8257] +24-11-19 20:44:04 | D | - Calibrating model.layers.31.self_attn.v_proj.weight +24-11-19 20:44:04 | D | + w: sint8 +24-11-19 20:44:04 | D | + x: None +24-11-19 20:44:04 | D | + y: None +24-11-19 20:44:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:44:04 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:44:04 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:44:04 | D | + finished calculating the original outputs, ram usage: 13.7 +24-11-19 20:44:04 | D | - range ratio = [ 1.0000] +24-11-19 20:44:04 | D | sum error = [ 2.8080] +24-11-19 20:44:04 | D | best error = [ 2.8080] +24-11-19 20:44:04 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:44:04 | D | sum error = [ 2.7909, 2.8029, 2.8059, 2.8525, 2.8778] +24-11-19 20:44:04 | D | best error = [ 2.5453, 2.4517, 2.4059, 2.3814, 2.3664] +24-11-19 20:44:04 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:44:04 | D | sum error = [ 2.9987, 3.0661, 3.1912, 3.3455, 3.5051] +24-11-19 20:44:04 | D | best error = [ 2.3566, 2.3535, 2.3518, 2.3510, 2.3510] +24-11-19 20:44:04 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:44:04 | D | sum error = [ 3.6935, 3.9354, 4.1821, 4.4599, 4.7828] +24-11-19 20:44:04 | D | best error = [ 2.3510, 2.3510, 2.3510, 2.3510, 2.3510] +24-11-19 20:44:04 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:44:04 | D | sum error = [ 5.0930, 5.4607, 5.8726, 6.2768, 6.7035] +24-11-19 20:44:04 | D | best error = [ 2.3510, 2.3510, 2.3510, 2.3510, 2.3510] +24-11-19 20:44:04 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:44:04 | D | sum error = [ 7.1941, 7.7316, 8.2799, 8.8889, 9.5334] +24-11-19 20:44:04 | D | best error = [ 2.3510, 2.3510, 2.3510, 2.3510, 2.3510] +24-11-19 20:44:04 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:44:04 | D | sum error = [ 10.1736, 10.9189, 11.6295, 12.4053, 13.2511] +24-11-19 20:44:04 | D | best error = [ 2.3510, 2.3510, 2.3510, 2.3510, 2.3510] +24-11-19 20:44:04 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:44:04 | D | sum error = [ 14.1353, 15.1214, 16.0959, 17.1673, 18.2715] +24-11-19 20:44:04 | D | best error = [ 2.3510, 2.3510, 2.3510, 2.3510, 2.3510] +24-11-19 20:44:04 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:44:04 | D | sum error = [ 19.5060, 20.7550, 22.0611, 23.4548, 24.8851] +24-11-19 20:44:04 | D | best error = [ 2.3510, 2.3510, 2.3510, 2.3510, 2.3510] +24-11-19 20:44:04 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:44:04 | D | sum error = [ 26.4671, 28.0664, 29.7676, 31.5375, 33.4216] +24-11-19 20:44:04 | D | best error = [ 2.3510, 2.3510, 2.3510, 2.3510, 2.3510] +24-11-19 20:44:04 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:44:04 | D | sum error = [ 35.4000, 37.4815, 39.6440, 41.9308, 44.3237] +24-11-19 20:44:04 | D | best error = [ 2.3510, 2.3510, 2.3510, 2.3510, 2.3510] +24-11-19 20:44:04 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:44:04 | D | sum error = [ 46.8491, 49.5002, 52.2530, 55.1426, 58.1979] +24-11-19 20:44:04 | D | best error = [ 2.3510, 2.3510, 2.3510, 2.3510, 2.3510] +24-11-19 20:44:04 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:44:04 | D | sum error = [ 61.3715, 64.7183, 68.2194, 71.8730, 75.7064] +24-11-19 20:44:04 | D | best error = [ 2.3510, 2.3510, 2.3510, 2.3510, 2.3510] +24-11-19 20:44:04 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:44:04 | D | sum error = [ 79.6714, 83.8441, 88.1894, 92.7042, 97.4290] +24-11-19 20:44:04 | D | best error = [ 2.3510, 2.3510, 2.3510, 2.3510, 2.3510] +24-11-19 20:44:04 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:44:04 | D | sum error = [ 102.3209, 107.4141, 112.7112, 118.2006, 123.9594] +24-11-19 20:44:04 | D | best error = [ 2.3510, 2.3510, 2.3510, 2.3510, 2.3510] +24-11-19 20:44:04 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:44:04 | D | sum error = [ 129.9021, 136.1300, 142.5450, 149.1567, 156.0104] +24-11-19 20:44:04 | D | best error = [ 2.3510, 2.3510, 2.3510, 2.3510, 2.3510] +24-11-19 20:44:04 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:44:04 | D | sum error = [ 163.0794, 170.3840, 177.8970, 185.6612, 193.6411] +24-11-19 20:44:04 | D | best error = [ 2.3510, 2.3510, 2.3510, 2.3510, 2.3510] +24-11-19 20:44:04 | D | + error = [2.3510] +24-11-19 20:44:04 | D | - Calibrating model.layers.31.self_attn.o_proj.weight +24-11-19 20:44:04 | D | + w: sint8 +24-11-19 20:44:04 | D | + x: None +24-11-19 20:44:04 | D | + y: None +24-11-19 20:44:04 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:44:04 | D | + finished parsing calibration arguments, ram usage: 13.9 +24-11-19 20:44:04 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:44:05 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:44:05 | D | - range ratio = [ 1.0000] +24-11-19 20:44:05 | D | sum error = [ 2.6016] +24-11-19 20:44:05 | D | best error = [ 2.6016] +24-11-19 20:44:05 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:44:05 | D | sum error = [ 2.5754, 2.5867, 2.5560, 2.5187, 2.5265] +24-11-19 20:44:05 | D | best error = [ 2.1183, 1.9667, 1.8784, 1.8242, 1.7876] +24-11-19 20:44:05 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:44:05 | D | sum error = [ 2.5289, 2.4782, 2.4945, 2.5074, 2.5375] +24-11-19 20:44:05 | D | best error = [ 1.7578, 1.7360, 1.7173, 1.7026, 1.6898] +24-11-19 20:44:05 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:44:05 | D | sum error = [ 2.5449, 2.5877, 2.6272, 2.6894, 2.7930] +24-11-19 20:44:05 | D | best error = [ 1.6812, 1.6725, 1.6636, 1.6587, 1.6533] +24-11-19 20:44:05 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:44:05 | D | sum error = [ 2.8534, 2.9249, 3.0683, 3.2171, 3.3343] +24-11-19 20:44:05 | D | best error = [ 1.6497, 1.6459, 1.6434, 1.6407, 1.6386] +24-11-19 20:44:05 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:44:05 | D | sum error = [ 3.5230, 3.7088, 3.9181, 4.1455, 4.4090] +24-11-19 20:44:05 | D | best error = [ 1.6371, 1.6358, 1.6343, 1.6335, 1.6329] +24-11-19 20:44:05 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:44:05 | D | sum error = [ 4.6462, 4.9632, 5.2855, 5.6250, 6.0082] +24-11-19 20:44:05 | D | best error = [ 1.6321, 1.6313, 1.6309, 1.6306, 1.6304] +24-11-19 20:44:05 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:44:05 | D | sum error = [ 6.3942, 6.8232, 7.2929, 7.7857, 8.2910] +24-11-19 20:44:05 | D | best error = [ 1.6302, 1.6301, 1.6300, 1.6300, 1.6299] +24-11-19 20:44:05 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:44:05 | D | sum error = [ 8.8824, 9.4940, 10.1224, 10.8565, 11.5833] +24-11-19 20:44:05 | D | best error = [ 1.6299, 1.6299, 1.6299, 1.6299, 1.6297] +24-11-19 20:44:05 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:44:05 | D | sum error = [ 12.3864, 13.2302, 14.1262, 15.0584, 16.0575] +24-11-19 20:44:05 | D | best error = [ 1.6297, 1.6297, 1.6297, 1.6297, 1.6297] +24-11-19 20:44:05 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:44:05 | D | sum error = [ 17.1418, 18.2808, 19.5015, 20.7780, 22.1363] +24-11-19 20:44:05 | D | best error = [ 1.6297, 1.6297, 1.6297, 1.6297, 1.6297] +24-11-19 20:44:05 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:44:05 | D | sum error = [ 23.5960, 25.1356, 26.7433, 28.4275, 30.2211] +24-11-19 20:44:05 | D | best error = [ 1.6297, 1.6297, 1.6297, 1.6297, 1.6297] +24-11-19 20:44:05 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:44:05 | D | sum error = [ 32.1155, 34.1183, 36.2315, 38.4775, 40.8358] +24-11-19 20:44:05 | D | best error = [ 1.6297, 1.6297, 1.6297, 1.6297, 1.6297] +24-11-19 20:44:05 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:44:05 | D | sum error = [ 43.3082, 45.8876, 48.6476, 51.5214, 54.5463] +24-11-19 20:44:05 | D | best error = [ 1.6297, 1.6297, 1.6297, 1.6297, 1.6297] +24-11-19 20:44:05 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:44:05 | D | sum error = [ 57.7061, 61.0179, 64.4872, 68.1403, 71.9546] +24-11-19 20:44:05 | D | best error = [ 1.6297, 1.6297, 1.6297, 1.6297, 1.6297] +24-11-19 20:44:05 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:44:05 | D | sum error = [ 75.9439, 80.1394, 84.4969, 89.0278, 93.7576] +24-11-19 20:44:05 | D | best error = [ 1.6297, 1.6297, 1.6297, 1.6297, 1.6297] +24-11-19 20:44:05 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:44:05 | D | sum error = [ 98.6817, 103.7995, 109.1176, 114.6271, 120.3703] +24-11-19 20:44:05 | D | best error = [ 1.6297, 1.6297, 1.6297, 1.6297, 1.6297] +24-11-19 20:44:05 | D | + error = [1.6297] +24-11-19 20:44:05 | D | - Calibrating model.layers.31.mlp.up_proj.weight +24-11-19 20:44:05 | D | + w: sint8 +24-11-19 20:44:05 | D | + x: None +24-11-19 20:44:05 | D | + y: None +24-11-19 20:44:05 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:44:05 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:44:05 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:44:05 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:44:05 | D | - range ratio = [ 1.0000] +24-11-19 20:44:05 | D | sum error = [ 9.9781] +24-11-19 20:44:05 | D | best error = [ 9.9781] +24-11-19 20:44:07 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:44:07 | D | sum error = [ 9.9418, 9.9151, 9.9321, 10.0522, 10.2355] +24-11-19 20:44:07 | D | best error = [ 8.8114, 8.3984, 8.2036, 8.0951, 8.0353] +24-11-19 20:44:07 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:44:07 | D | sum error = [ 10.4989, 10.8623, 11.3127, 11.8559, 12.5116] +24-11-19 20:44:07 | D | best error = [ 8.0026, 7.9868, 7.9808, 7.9788, 7.9780] +24-11-19 20:44:07 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:44:07 | D | sum error = [ 13.3094, 14.0735, 15.0813, 16.1357, 17.2847] +24-11-19 20:44:07 | D | best error = [ 7.9779, 7.9777, 7.9777, 7.9777, 7.9777] +24-11-19 20:44:07 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:44:07 | D | sum error = [ 18.6155, 19.9834, 21.4492, 23.0420, 24.7493] +24-11-19 20:44:07 | D | best error = [ 7.9777, 7.9777, 7.9777, 7.9777, 7.9777] +24-11-19 20:44:07 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:44:07 | D | sum error = [ 26.6414, 28.6501, 30.7340, 33.0283, 35.4963] +24-11-19 20:44:07 | D | best error = [ 7.9777, 7.9777, 7.9777, 7.9777, 7.9777] +24-11-19 20:44:07 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:44:07 | D | sum error = [ 38.1202, 40.9311, 43.8883, 47.1024, 50.5452] +24-11-19 20:44:07 | D | best error = [ 7.9777, 7.9777, 7.9777, 7.9777, 7.9777] +24-11-19 20:44:07 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:44:07 | D | sum error = [ 54.2145, 58.0417, 62.2247, 66.6769, 71.4153] +24-11-19 20:44:07 | D | best error = [ 7.9777, 7.9777, 7.9777, 7.9777, 7.9777] +24-11-19 20:44:07 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:44:07 | D | sum error = [ 76.4659, 81.8903, 87.6534, 93.8184, 100.3507] +24-11-19 20:44:07 | D | best error = [ 7.9777, 7.9777, 7.9777, 7.9777, 7.9777] +24-11-19 20:44:07 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:44:07 | D | sum error = [ 107.3251, 114.7840, 122.6995, 131.1445, 140.1149] +24-11-19 20:44:07 | D | best error = [ 7.9777, 7.9777, 7.9777, 7.9777, 7.9777] +24-11-19 20:44:07 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:44:07 | D | sum error = [ 149.7085, 159.9162, 170.8077, 182.3164, 194.5661] +24-11-19 20:44:07 | D | best error = [ 7.9777, 7.9777, 7.9777, 7.9777, 7.9777] +24-11-19 20:44:07 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:44:07 | D | sum error = [ 207.5581, 221.3217, 235.8537, 251.3471, 267.7408] +24-11-19 20:44:07 | D | best error = [ 7.9777, 7.9777, 7.9777, 7.9777, 7.9777] +24-11-19 20:44:07 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:44:07 | D | sum error = [ 285.0340, 303.2841, 322.5463, 342.8168, 364.1823] +24-11-19 20:44:07 | D | best error = [ 7.9777, 7.9777, 7.9777, 7.9777, 7.9777] +24-11-19 20:44:07 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:44:07 | D | sum error = [ 386.8187, 410.5533, 435.6245, 461.8608, 489.4813] +24-11-19 20:44:07 | D | best error = [ 7.9777, 7.9777, 7.9777, 7.9777, 7.9777] +24-11-19 20:44:07 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:44:07 | D | sum error = [ 518.3467, 548.5620, 580.0948, 613.0507, 647.4937] +24-11-19 20:44:07 | D | best error = [ 7.9777, 7.9777, 7.9777, 7.9777, 7.9777] +24-11-19 20:44:07 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:44:07 | D | sum error = [ 683.3297, 720.6763, 759.4708, 799.8488, 841.7248] +24-11-19 20:44:07 | D | best error = [ 7.9777, 7.9777, 7.9777, 7.9777, 7.9777] +24-11-19 20:44:07 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:44:07 | D | sum error = [ 885.1035, 930.0041, 976.4319, 1024.3719, 1073.7798] +24-11-19 20:44:07 | D | best error = [ 7.9777, 7.9777, 7.9777, 7.9777, 7.9777] +24-11-19 20:44:07 | D | + error = [7.9777] +24-11-19 20:44:07 | D | - Calibrating model.layers.31.mlp.gate_proj.weight +24-11-19 20:44:07 | D | + w: sint8 +24-11-19 20:44:07 | D | + x: None +24-11-19 20:44:07 | D | + y: None +24-11-19 20:44:07 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:44:07 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:44:07 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:44:07 | D | + finished calculating the original outputs, ram usage: 13.5 +24-11-19 20:44:07 | D | - range ratio = [ 1.0000] +24-11-19 20:44:07 | D | sum error = [ 12.5642] +24-11-19 20:44:07 | D | best error = [ 12.5642] +24-11-19 20:44:08 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:44:08 | D | sum error = [ 12.4311, 12.4515, 12.4928, 12.6189, 12.9078] +24-11-19 20:44:08 | D | best error = [ 11.0480, 10.5551, 10.3028, 10.1623, 10.0874] +24-11-19 20:44:08 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:44:08 | D | sum error = [ 13.2028, 13.5901, 14.2481, 15.0139, 15.7638] +24-11-19 20:44:08 | D | best error = [ 10.0479, 10.0272, 10.0197, 10.0166, 10.0152] +24-11-19 20:44:08 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:44:08 | D | sum error = [ 16.7047, 17.7761, 18.9991, 20.2864, 21.7090] +24-11-19 20:44:08 | D | best error = [ 10.0152, 10.0150, 10.0150, 10.0150, 10.0150] +24-11-19 20:44:08 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:44:08 | D | sum error = [ 23.3328, 25.0236, 26.7520, 28.8076, 30.9085] +24-11-19 20:44:08 | D | best error = [ 10.0150, 10.0150, 10.0150, 10.0150, 10.0150] +24-11-19 20:44:08 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:44:08 | D | sum error = [ 33.2207, 35.7606, 38.3680, 41.1757, 44.2516] +24-11-19 20:44:08 | D | best error = [ 10.0150, 10.0150, 10.0150, 10.0150, 10.0150] +24-11-19 20:44:08 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:44:08 | D | sum error = [ 47.4619, 50.9381, 54.6800, 58.6202, 62.8906] +24-11-19 20:44:08 | D | best error = [ 10.0150, 10.0150, 10.0150, 10.0150, 10.0150] +24-11-19 20:44:08 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:44:08 | D | sum error = [ 67.4827, 72.3915, 77.6046, 83.2018, 89.2014] +24-11-19 20:44:08 | D | best error = [ 10.0150, 10.0150, 10.0150, 10.0150, 10.0150] +24-11-19 20:44:08 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:44:08 | D | sum error = [ 95.6166, 102.4378, 109.7455, 117.5631, 125.9280] +24-11-19 20:44:08 | D | best error = [ 10.0150, 10.0150, 10.0150, 10.0150, 10.0150] +24-11-19 20:44:08 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:44:08 | D | sum error = [ 134.9324, 144.5655, 154.7654, 165.7975, 177.5463] +24-11-19 20:44:08 | D | best error = [ 10.0150, 10.0150, 10.0150, 10.0150, 10.0150] +24-11-19 20:44:08 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:44:08 | D | sum error = [ 190.0763, 203.4796, 217.7709, 233.0915, 249.4856] +24-11-19 20:44:08 | D | best error = [ 10.0150, 10.0150, 10.0150, 10.0150, 10.0150] +24-11-19 20:44:08 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:44:08 | D | sum error = [ 266.8729, 285.3954, 305.1870, 326.2134, 348.7296] +24-11-19 20:44:08 | D | best error = [ 10.0150, 10.0150, 10.0150, 10.0150, 10.0150] +24-11-19 20:44:08 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:44:08 | D | sum error = [ 372.4672, 397.7669, 424.6169, 453.1339, 483.3436] +24-11-19 20:44:08 | D | best error = [ 10.0150, 10.0150, 10.0150, 10.0150, 10.0150] +24-11-19 20:44:08 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:44:08 | D | sum error = [ 515.3663, 549.1522, 584.8049, 622.3676, 661.9512] +24-11-19 20:44:08 | D | best error = [ 10.0150, 10.0150, 10.0150, 10.0150, 10.0150] +24-11-19 20:44:08 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:44:08 | D | sum error = [ 703.5676, 747.2361, 793.0439, 841.0477, 891.1261] +24-11-19 20:44:08 | D | best error = [ 10.0150, 10.0150, 10.0150, 10.0150, 10.0150] +24-11-19 20:44:08 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:44:08 | D | sum error = [ 943.6385, 998.3743, 1055.4311, 1114.7904, 1176.6580] +24-11-19 20:44:08 | D | best error = [ 10.0150, 10.0150, 10.0150, 10.0150, 10.0150] +24-11-19 20:44:08 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:44:08 | D | sum error = [ 1240.9059, 1307.3877, 1376.4295, 1447.7941, 1521.5598] +24-11-19 20:44:08 | D | best error = [ 10.0150, 10.0150, 10.0150, 10.0150, 10.0150] +24-11-19 20:44:08 | D | + error = [10.0150] +24-11-19 20:44:08 | D | - Calibrating model.layers.31.mlp.down_proj.weight +24-11-19 20:44:08 | D | + w: sint8 +24-11-19 20:44:08 | D | + x: None +24-11-19 20:44:08 | D | + y: None +24-11-19 20:44:08 | D | + tensor_type: TensorType.Weights, objective: SearchBasedCalibObjective.ProductsError, granularity: SearchBasedCalibGranularity.Group +24-11-19 20:44:08 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:44:08 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:44:08 | D | + finished calculating the original outputs, ram usage: 13.8 +24-11-19 20:44:08 | D | - range ratio = [ 1.0000] +24-11-19 20:44:08 | D | sum error = [ 26.9268] +24-11-19 20:44:08 | D | best error = [ 26.9268] +24-11-19 20:44:10 | D | - range ratio = [ 0.9900, 0.9800, 0.9700, 0.9600, 0.9500] +24-11-19 20:44:10 | D | sum error = [ 26.6197, 26.5377, 25.8841, 26.1671, 25.6840] +24-11-19 20:44:10 | D | best error = [ 20.1387, 17.3432, 15.8784, 14.8688, 14.1724] +24-11-19 20:44:10 | D | - range ratio = [ 0.9400, 0.9300, 0.9200, 0.9100, 0.9000] +24-11-19 20:44:10 | D | sum error = [ 25.7715, 25.3886, 25.6141, 25.2780, 25.7489] +24-11-19 20:44:10 | D | best error = [ 13.6355, 13.1782, 12.7817, 12.4515, 12.1620] +24-11-19 20:44:10 | D | - range ratio = [ 0.8900, 0.8800, 0.8700, 0.8600, 0.8500] +24-11-19 20:44:10 | D | sum error = [ 26.1703, 26.4910, 27.3377, 28.0625, 28.8810] +24-11-19 20:44:10 | D | best error = [ 11.8909, 11.6745, 11.4394, 11.2352, 11.0499] +24-11-19 20:44:10 | D | - range ratio = [ 0.8400, 0.8300, 0.8200, 0.8100, 0.8000] +24-11-19 20:44:10 | D | sum error = [ 29.6657, 31.2833, 32.8753, 33.8749, 35.6540] +24-11-19 20:44:10 | D | best error = [ 10.8920, 10.7469, 10.6134, 10.4951, 10.3595] +24-11-19 20:44:10 | D | - range ratio = [ 0.7900, 0.7800, 0.7700, 0.7600, 0.7500] +24-11-19 20:44:10 | D | sum error = [ 37.7734, 39.3670, 41.7868, 44.8603, 47.1866] +24-11-19 20:44:10 | D | best error = [ 10.2303, 10.1241, 10.0079, 9.9074, 9.8034] +24-11-19 20:44:10 | D | - range ratio = [ 0.7400, 0.7300, 0.7200, 0.7100, 0.7000] +24-11-19 20:44:10 | D | sum error = [ 50.6110, 54.2890, 57.5487, 61.7765, 66.2454] +24-11-19 20:44:10 | D | best error = [ 9.7094, 9.6363, 9.5533, 9.4837, 9.4303] +24-11-19 20:44:10 | D | - range ratio = [ 0.6900, 0.6800, 0.6700, 0.6600, 0.6500] +24-11-19 20:44:10 | D | sum error = [ 70.8975, 75.9928, 81.2388, 87.3431, 93.8579] +24-11-19 20:44:10 | D | best error = [ 9.3718, 9.3344, 9.2960, 9.2646, 9.2212] +24-11-19 20:44:10 | D | - range ratio = [ 0.6400, 0.6300, 0.6200, 0.6100, 0.6000] +24-11-19 20:44:10 | D | sum error = [ 100.7451, 107.9046, 115.5925, 123.6948, 132.1481] +24-11-19 20:44:10 | D | best error = [ 9.1925, 9.1720, 9.1473, 9.1284, 9.1179] +24-11-19 20:44:10 | D | - range ratio = [ 0.5900, 0.5800, 0.5700, 0.5600, 0.5500] +24-11-19 20:44:10 | D | sum error = [ 141.4203, 151.1348, 161.2208, 172.0307, 183.4984] +24-11-19 20:44:10 | D | best error = [ 9.1053, 9.0975, 9.0923, 9.0857, 9.0726] +24-11-19 20:44:10 | D | - range ratio = [ 0.5400, 0.5300, 0.5200, 0.5100, 0.5000] +24-11-19 20:44:10 | D | sum error = [ 195.3658, 208.2921, 221.4289, 235.6290, 250.8731] +24-11-19 20:44:10 | D | best error = [ 9.0651, 9.0621, 9.0576, 9.0513, 9.0494] +24-11-19 20:44:10 | D | - range ratio = [ 0.4900, 0.4800, 0.4700, 0.4600, 0.4500] +24-11-19 20:44:10 | D | sum error = [ 266.9072, 283.9846, 302.4869, 321.8744, 342.6270] +24-11-19 20:44:10 | D | best error = [ 9.0457, 9.0426, 9.0416, 9.0402, 9.0369] +24-11-19 20:44:10 | D | - range ratio = [ 0.4400, 0.4300, 0.4200, 0.4100, 0.4000] +24-11-19 20:44:10 | D | sum error = [ 365.1782, 389.0941, 414.3550, 441.2266, 470.1097] +24-11-19 20:44:10 | D | best error = [ 9.0351, 9.0342, 9.0314, 9.0307, 9.0286] +24-11-19 20:44:10 | D | - range ratio = [ 0.3900, 0.3800, 0.3700, 0.3600, 0.3500] +24-11-19 20:44:10 | D | sum error = [ 500.5560, 532.7019, 566.5431, 602.4566, 640.4921] +24-11-19 20:44:10 | D | best error = [ 9.0269, 9.0268, 9.0268, 9.0268, 9.0268] +24-11-19 20:44:10 | D | - range ratio = [ 0.3400, 0.3300, 0.3200, 0.3100, 0.3000] +24-11-19 20:44:10 | D | sum error = [ 680.5585, 722.5105, 767.1504, 814.0852, 863.5227] +24-11-19 20:44:10 | D | best error = [ 9.0267, 9.0267, 9.0267, 9.0267, 9.0267] +24-11-19 20:44:10 | D | - range ratio = [ 0.2900, 0.2800, 0.2700, 0.2600, 0.2500] +24-11-19 20:44:10 | D | sum error = [ 915.5075, 970.4319, 1027.7158, 1087.6429, 1150.1449] +24-11-19 20:44:10 | D | best error = [ 9.0267, 9.0267, 9.0267, 9.0267, 9.0267] +24-11-19 20:44:10 | D | - range ratio = [ 0.2400, 0.2300, 0.2200, 0.2100, 0.2000] +24-11-19 20:44:10 | D | sum error = [ 1215.4002, 1283.4137, 1354.1803, 1427.6598, 1503.5904] +24-11-19 20:44:10 | D | best error = [ 9.0267, 9.0267, 9.0267, 9.0267, 9.0267] +24-11-19 20:44:10 | D | + error = [9.0267] +24-11-19 20:44:10 | D | - Quantizing model.layers.31.self_attn.q_proj.weight +24-11-19 20:44:10 | D | - Quantizing model.layers.31.self_attn.k_proj.weight +24-11-19 20:44:11 | D | - Quantizing model.layers.31.self_attn.v_proj.weight +24-11-19 20:44:12 | D | - Quantizing model.layers.31.self_attn.o_proj.weight +24-11-19 20:44:13 | D | - Quantizing model.layers.31.mlp.up_proj.weight +24-11-19 20:44:14 | D | - Quantizing model.layers.31.mlp.gate_proj.weight +24-11-19 20:44:15 | D | - Quantizing model.layers.31.mlp.down_proj.weight +24-11-19 20:44:19 | I | - Saving weight quantizer settings to runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/wgts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt +24-11-19 20:44:19 | I | - Linking weight quantizer settings to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.201603.RUNNING/model/wgts.pt +24-11-19 20:44:19 | I | - Saving model checkpoint to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.201603.RUNNING/model +24-11-19 20:44:37 | I | * Quantizing activations +24-11-19 20:44:37 | I | - Generating activation quantizer settings +24-11-19 20:44:37 | D | Starting new HTTPS connection (4): huggingface.co:443 +24-11-19 20:44:43 | D | Starting new HTTPS connection (5): huggingface.co:443 +24-11-19 20:44:55 | D | Starting new HTTPS connection (2): s3.amazonaws.com:443 +24-11-19 20:45:07 | W | Repo card metadata block was not found. Setting CardData to empty. +24-11-19 20:45:07 | D | Starting new HTTPS connection (6): huggingface.co:443 +24-11-19 20:45:20 | W | Using the latest cached version of the dataset since mit-han-lab/pile-val-backup couldn't be found on the Hugging Face Hub +24-11-19 20:45:20 | W | Found the latest cached dataset configuration 'default' at /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4 (last modified on Tue Oct 8 18:58:39 2024). +24-11-19 20:45:20 | D | Attempting to acquire lock 23438376288128 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:45:20 | D | Lock 23438376288128 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:45:20 | D | open file: /home/yujunlin/.cache/huggingface/datasets/mit-han-lab___pile-val-backup/default/0.0.0/2f5e46ae6a69cf0dce4b12f78241c408936ca0e4/dataset_info.json +24-11-19 20:45:20 | D | Attempting to release lock 23438376288128 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:45:20 | D | Lock 23438376288128 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_mit-han-lab___pile-val-backup_default_0.0.0_2f5e46ae6a69cf0dce4b12f78241c408936ca0e4.lock +24-11-19 20:45:33 | D | - Quantizing layer model.layers.0 +24-11-19 20:45:33 | D | - Calibrating model.layers.0.self_attn.v_proj.input +24-11-19 20:45:33 | D | - Calibrating model.layers.0.self_attn.k_rotary_emb.output +24-11-19 20:45:33 | D | + w: None +24-11-19 20:45:33 | D | + x: None +24-11-19 20:45:33 | D | + y: sint8 +24-11-19 20:45:33 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:33 | D | + finished parsing calibration arguments, ram usage: 13.0 +24-11-19 20:45:33 | D | + finished reseting calibrator, ram usage: 13.1 +24-11-19 20:45:34 | D | - range ratio = [ 1.0000] +24-11-19 20:45:34 | D | sum error = [ 4.3764] +24-11-19 20:45:34 | D | best error = [ 4.3764] +24-11-19 20:45:34 | D | + error = [4.3764] +24-11-19 20:45:34 | D | - Calibrating model.layers.0.self_attn.v_proj.output +24-11-19 20:45:34 | D | + w: None +24-11-19 20:45:34 | D | + x: None +24-11-19 20:45:34 | D | + y: sint8 +24-11-19 20:45:34 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:34 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:45:34 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:45:35 | D | - range ratio = [ 1.0000] +24-11-19 20:45:35 | D | sum error = [ 2.7431] +24-11-19 20:45:35 | D | best error = [ 2.7431] +24-11-19 20:45:35 | D | + error = [2.7431] +24-11-19 20:45:35 | D | - Calibrating model.layers.0.self_attn.o_proj.input +24-11-19 20:45:35 | D | - Calibrating model.layers.0.mlp.up_proj.input +24-11-19 20:45:35 | D | - Calibrating model.layers.0.mlp.down_proj.input +24-11-19 20:45:35 | D | - Quantizing model.layers.0.self_attn.q_proj (inputs) +24-11-19 20:45:35 | D | - Quantizing model.layers.0.self_attn.k_proj (inputs) +24-11-19 20:45:35 | D | - Quantizing model.layers.0.self_attn.v_proj (inputs and outputs) +24-11-19 20:45:35 | D | - Quantizing model.layers.0.self_attn.o_proj (inputs) +24-11-19 20:45:35 | D | - Quantizing model.layers.0.self_attn.k_rotary_emb (outputs) +24-11-19 20:45:35 | D | - Quantizing model.layers.0.mlp.gate_proj (inputs) +24-11-19 20:45:35 | D | - Quantizing model.layers.0.mlp.up_proj (inputs) +24-11-19 20:45:35 | D | - Quantizing model.layers.0.mlp.down_proj (inputs) +24-11-19 20:45:42 | D | - Quantizing layer model.layers.1 +24-11-19 20:45:42 | D | - Calibrating model.layers.1.self_attn.v_proj.input +24-11-19 20:45:42 | D | - Calibrating model.layers.1.self_attn.k_rotary_emb.output +24-11-19 20:45:42 | D | + w: None +24-11-19 20:45:42 | D | + x: None +24-11-19 20:45:42 | D | + y: sint8 +24-11-19 20:45:42 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:42 | D | + finished parsing calibration arguments, ram usage: 12.9 +24-11-19 20:45:42 | D | + finished reseting calibrator, ram usage: 12.9 +24-11-19 20:45:42 | D | - range ratio = [ 1.0000] +24-11-19 20:45:42 | D | sum error = [ 11.4434] +24-11-19 20:45:42 | D | best error = [ 11.4434] +24-11-19 20:45:42 | D | + error = [11.4434] +24-11-19 20:45:42 | D | - Calibrating model.layers.1.self_attn.v_proj.output +24-11-19 20:45:42 | D | + w: None +24-11-19 20:45:42 | D | + x: None +24-11-19 20:45:42 | D | + y: sint8 +24-11-19 20:45:42 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:42 | D | + finished parsing calibration arguments, ram usage: 13.0 +24-11-19 20:45:43 | D | + finished reseting calibrator, ram usage: 13.0 +24-11-19 20:45:43 | D | - range ratio = [ 1.0000] +24-11-19 20:45:43 | D | sum error = [ 14.4365] +24-11-19 20:45:43 | D | best error = [ 14.4365] +24-11-19 20:45:43 | D | + error = [14.4365] +24-11-19 20:45:43 | D | - Calibrating model.layers.1.self_attn.o_proj.input +24-11-19 20:45:43 | D | - Calibrating model.layers.1.mlp.up_proj.input +24-11-19 20:45:43 | D | - Calibrating model.layers.1.mlp.down_proj.input +24-11-19 20:45:43 | D | - Quantizing model.layers.1.self_attn.q_proj (inputs) +24-11-19 20:45:43 | D | - Quantizing model.layers.1.self_attn.k_proj (inputs) +24-11-19 20:45:43 | D | - Quantizing model.layers.1.self_attn.v_proj (inputs and outputs) +24-11-19 20:45:43 | D | - Quantizing model.layers.1.self_attn.o_proj (inputs) +24-11-19 20:45:43 | D | - Quantizing model.layers.1.self_attn.k_rotary_emb (outputs) +24-11-19 20:45:43 | D | - Quantizing model.layers.1.mlp.gate_proj (inputs) +24-11-19 20:45:43 | D | - Quantizing model.layers.1.mlp.up_proj (inputs) +24-11-19 20:45:43 | D | - Quantizing model.layers.1.mlp.down_proj (inputs) +24-11-19 20:45:50 | D | - Quantizing layer model.layers.2 +24-11-19 20:45:50 | D | - Calibrating model.layers.2.self_attn.v_proj.input +24-11-19 20:45:50 | D | - Calibrating model.layers.2.self_attn.k_rotary_emb.output +24-11-19 20:45:50 | D | + w: None +24-11-19 20:45:50 | D | + x: None +24-11-19 20:45:50 | D | + y: sint8 +24-11-19 20:45:50 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:50 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:45:50 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:45:51 | D | - range ratio = [ 1.0000] +24-11-19 20:45:51 | D | sum error = [ 10.5441] +24-11-19 20:45:51 | D | best error = [ 10.5441] +24-11-19 20:45:51 | D | + error = [10.5441] +24-11-19 20:45:51 | D | - Calibrating model.layers.2.self_attn.v_proj.output +24-11-19 20:45:51 | D | + w: None +24-11-19 20:45:51 | D | + x: None +24-11-19 20:45:51 | D | + y: sint8 +24-11-19 20:45:51 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:51 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:45:51 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:45:51 | D | - range ratio = [ 1.0000] +24-11-19 20:45:51 | D | sum error = [ 24.0530] +24-11-19 20:45:51 | D | best error = [ 24.0530] +24-11-19 20:45:51 | D | + error = [24.0530] +24-11-19 20:45:51 | D | - Calibrating model.layers.2.self_attn.o_proj.input +24-11-19 20:45:51 | D | - Calibrating model.layers.2.mlp.up_proj.input +24-11-19 20:45:51 | D | - Calibrating model.layers.2.mlp.down_proj.input +24-11-19 20:45:52 | D | - Quantizing model.layers.2.self_attn.q_proj (inputs) +24-11-19 20:45:52 | D | - Quantizing model.layers.2.self_attn.k_proj (inputs) +24-11-19 20:45:52 | D | - Quantizing model.layers.2.self_attn.v_proj (inputs and outputs) +24-11-19 20:45:52 | D | - Quantizing model.layers.2.self_attn.o_proj (inputs) +24-11-19 20:45:52 | D | - Quantizing model.layers.2.self_attn.k_rotary_emb (outputs) +24-11-19 20:45:52 | D | - Quantizing model.layers.2.mlp.gate_proj (inputs) +24-11-19 20:45:52 | D | - Quantizing model.layers.2.mlp.up_proj (inputs) +24-11-19 20:45:52 | D | - Quantizing model.layers.2.mlp.down_proj (inputs) +24-11-19 20:45:58 | D | - Quantizing layer model.layers.3 +24-11-19 20:45:58 | D | - Calibrating model.layers.3.self_attn.v_proj.input +24-11-19 20:45:58 | D | - Calibrating model.layers.3.self_attn.k_rotary_emb.output +24-11-19 20:45:58 | D | + w: None +24-11-19 20:45:58 | D | + x: None +24-11-19 20:45:58 | D | + y: sint8 +24-11-19 20:45:58 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:58 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:45:58 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:45:58 | D | - range ratio = [ 1.0000] +24-11-19 20:45:58 | D | sum error = [ 16.8924] +24-11-19 20:45:58 | D | best error = [ 16.8924] +24-11-19 20:45:58 | D | + error = [16.8924] +24-11-19 20:45:59 | D | - Calibrating model.layers.3.self_attn.v_proj.output +24-11-19 20:45:59 | D | + w: None +24-11-19 20:45:59 | D | + x: None +24-11-19 20:45:59 | D | + y: sint8 +24-11-19 20:45:59 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:45:59 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:45:59 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:45:59 | D | - range ratio = [ 1.0000] +24-11-19 20:45:59 | D | sum error = [ 58.0030] +24-11-19 20:45:59 | D | best error = [ 58.0030] +24-11-19 20:45:59 | D | + error = [58.0030] +24-11-19 20:45:59 | D | - Calibrating model.layers.3.self_attn.o_proj.input +24-11-19 20:46:00 | D | - Calibrating model.layers.3.mlp.up_proj.input +24-11-19 20:46:00 | D | - Calibrating model.layers.3.mlp.down_proj.input +24-11-19 20:46:00 | D | - Quantizing model.layers.3.self_attn.q_proj (inputs) +24-11-19 20:46:00 | D | - Quantizing model.layers.3.self_attn.k_proj (inputs) +24-11-19 20:46:00 | D | - Quantizing model.layers.3.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:00 | D | - Quantizing model.layers.3.self_attn.o_proj (inputs) +24-11-19 20:46:00 | D | - Quantizing model.layers.3.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:00 | D | - Quantizing model.layers.3.mlp.gate_proj (inputs) +24-11-19 20:46:00 | D | - Quantizing model.layers.3.mlp.up_proj (inputs) +24-11-19 20:46:00 | D | - Quantizing model.layers.3.mlp.down_proj (inputs) +24-11-19 20:46:06 | D | - Quantizing layer model.layers.4 +24-11-19 20:46:06 | D | - Calibrating model.layers.4.self_attn.v_proj.input +24-11-19 20:46:06 | D | - Calibrating model.layers.4.self_attn.k_rotary_emb.output +24-11-19 20:46:06 | D | + w: None +24-11-19 20:46:06 | D | + x: None +24-11-19 20:46:06 | D | + y: sint8 +24-11-19 20:46:06 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:06 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:46:06 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:46:07 | D | - range ratio = [ 1.0000] +24-11-19 20:46:07 | D | sum error = [ 26.8225] +24-11-19 20:46:07 | D | best error = [ 26.8225] +24-11-19 20:46:07 | D | + error = [26.8225] +24-11-19 20:46:07 | D | - Calibrating model.layers.4.self_attn.v_proj.output +24-11-19 20:46:07 | D | + w: None +24-11-19 20:46:07 | D | + x: None +24-11-19 20:46:07 | D | + y: sint8 +24-11-19 20:46:07 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:07 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:46:07 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:46:08 | D | - range ratio = [ 1.0000] +24-11-19 20:46:08 | D | sum error = [ 38.9309] +24-11-19 20:46:08 | D | best error = [ 38.9309] +24-11-19 20:46:08 | D | + error = [38.9309] +24-11-19 20:46:08 | D | - Calibrating model.layers.4.self_attn.o_proj.input +24-11-19 20:46:08 | D | - Calibrating model.layers.4.mlp.up_proj.input +24-11-19 20:46:08 | D | - Calibrating model.layers.4.mlp.down_proj.input +24-11-19 20:46:08 | D | - Quantizing model.layers.4.self_attn.q_proj (inputs) +24-11-19 20:46:08 | D | - Quantizing model.layers.4.self_attn.k_proj (inputs) +24-11-19 20:46:08 | D | - Quantizing model.layers.4.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:08 | D | - Quantizing model.layers.4.self_attn.o_proj (inputs) +24-11-19 20:46:08 | D | - Quantizing model.layers.4.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:08 | D | - Quantizing model.layers.4.mlp.gate_proj (inputs) +24-11-19 20:46:08 | D | - Quantizing model.layers.4.mlp.up_proj (inputs) +24-11-19 20:46:08 | D | - Quantizing model.layers.4.mlp.down_proj (inputs) +24-11-19 20:46:14 | D | - Quantizing layer model.layers.5 +24-11-19 20:46:14 | D | - Calibrating model.layers.5.self_attn.v_proj.input +24-11-19 20:46:14 | D | - Calibrating model.layers.5.self_attn.k_rotary_emb.output +24-11-19 20:46:14 | D | + w: None +24-11-19 20:46:14 | D | + x: None +24-11-19 20:46:14 | D | + y: sint8 +24-11-19 20:46:14 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:14 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:46:14 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:46:15 | D | - range ratio = [ 1.0000] +24-11-19 20:46:15 | D | sum error = [ 27.7926] +24-11-19 20:46:15 | D | best error = [ 27.7926] +24-11-19 20:46:15 | D | + error = [27.7926] +24-11-19 20:46:15 | D | - Calibrating model.layers.5.self_attn.v_proj.output +24-11-19 20:46:15 | D | + w: None +24-11-19 20:46:15 | D | + x: None +24-11-19 20:46:15 | D | + y: sint8 +24-11-19 20:46:15 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:15 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:46:15 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:46:16 | D | - range ratio = [ 1.0000] +24-11-19 20:46:16 | D | sum error = [ 30.8044] +24-11-19 20:46:16 | D | best error = [ 30.8044] +24-11-19 20:46:16 | D | + error = [30.8044] +24-11-19 20:46:16 | D | - Calibrating model.layers.5.self_attn.o_proj.input +24-11-19 20:46:16 | D | - Calibrating model.layers.5.mlp.up_proj.input +24-11-19 20:46:16 | D | - Calibrating model.layers.5.mlp.down_proj.input +24-11-19 20:46:16 | D | - Quantizing model.layers.5.self_attn.q_proj (inputs) +24-11-19 20:46:16 | D | - Quantizing model.layers.5.self_attn.k_proj (inputs) +24-11-19 20:46:16 | D | - Quantizing model.layers.5.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:16 | D | - Quantizing model.layers.5.self_attn.o_proj (inputs) +24-11-19 20:46:16 | D | - Quantizing model.layers.5.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:16 | D | - Quantizing model.layers.5.mlp.gate_proj (inputs) +24-11-19 20:46:16 | D | - Quantizing model.layers.5.mlp.up_proj (inputs) +24-11-19 20:46:16 | D | - Quantizing model.layers.5.mlp.down_proj (inputs) +24-11-19 20:46:23 | D | - Quantizing layer model.layers.6 +24-11-19 20:46:23 | D | - Calibrating model.layers.6.self_attn.v_proj.input +24-11-19 20:46:23 | D | - Calibrating model.layers.6.self_attn.k_rotary_emb.output +24-11-19 20:46:23 | D | + w: None +24-11-19 20:46:23 | D | + x: None +24-11-19 20:46:23 | D | + y: sint8 +24-11-19 20:46:23 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:23 | D | + finished parsing calibration arguments, ram usage: 13.1 +24-11-19 20:46:23 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:46:24 | D | - range ratio = [ 1.0000] +24-11-19 20:46:24 | D | sum error = [ 24.7823] +24-11-19 20:46:24 | D | best error = [ 24.7823] +24-11-19 20:46:24 | D | + error = [24.7823] +24-11-19 20:46:24 | D | - Calibrating model.layers.6.self_attn.v_proj.output +24-11-19 20:46:24 | D | + w: None +24-11-19 20:46:24 | D | + x: None +24-11-19 20:46:24 | D | + y: sint8 +24-11-19 20:46:24 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:24 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:46:24 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:46:25 | D | - range ratio = [ 1.0000] +24-11-19 20:46:25 | D | sum error = [ 24.8700] +24-11-19 20:46:25 | D | best error = [ 24.8700] +24-11-19 20:46:25 | D | + error = [24.8700] +24-11-19 20:46:25 | D | - Calibrating model.layers.6.self_attn.o_proj.input +24-11-19 20:46:25 | D | - Calibrating model.layers.6.mlp.up_proj.input +24-11-19 20:46:25 | D | - Calibrating model.layers.6.mlp.down_proj.input +24-11-19 20:46:25 | D | - Quantizing model.layers.6.self_attn.q_proj (inputs) +24-11-19 20:46:25 | D | - Quantizing model.layers.6.self_attn.k_proj (inputs) +24-11-19 20:46:25 | D | - Quantizing model.layers.6.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:25 | D | - Quantizing model.layers.6.self_attn.o_proj (inputs) +24-11-19 20:46:25 | D | - Quantizing model.layers.6.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:25 | D | - Quantizing model.layers.6.mlp.gate_proj (inputs) +24-11-19 20:46:25 | D | - Quantizing model.layers.6.mlp.up_proj (inputs) +24-11-19 20:46:25 | D | - Quantizing model.layers.6.mlp.down_proj (inputs) +24-11-19 20:46:32 | D | - Quantizing layer model.layers.7 +24-11-19 20:46:32 | D | - Calibrating model.layers.7.self_attn.v_proj.input +24-11-19 20:46:32 | D | - Calibrating model.layers.7.self_attn.k_rotary_emb.output +24-11-19 20:46:32 | D | + w: None +24-11-19 20:46:32 | D | + x: None +24-11-19 20:46:32 | D | + y: sint8 +24-11-19 20:46:32 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:32 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:46:32 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:46:33 | D | - range ratio = [ 1.0000] +24-11-19 20:46:33 | D | sum error = [ 31.8543] +24-11-19 20:46:33 | D | best error = [ 31.8543] +24-11-19 20:46:33 | D | + error = [31.8543] +24-11-19 20:46:33 | D | - Calibrating model.layers.7.self_attn.v_proj.output +24-11-19 20:46:33 | D | + w: None +24-11-19 20:46:33 | D | + x: None +24-11-19 20:46:33 | D | + y: sint8 +24-11-19 20:46:33 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:33 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:46:33 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:46:33 | D | - range ratio = [ 1.0000] +24-11-19 20:46:33 | D | sum error = [ 23.6040] +24-11-19 20:46:33 | D | best error = [ 23.6040] +24-11-19 20:46:33 | D | + error = [23.6040] +24-11-19 20:46:33 | D | - Calibrating model.layers.7.self_attn.o_proj.input +24-11-19 20:46:34 | D | - Calibrating model.layers.7.mlp.up_proj.input +24-11-19 20:46:34 | D | - Calibrating model.layers.7.mlp.down_proj.input +24-11-19 20:46:34 | D | - Quantizing model.layers.7.self_attn.q_proj (inputs) +24-11-19 20:46:34 | D | - Quantizing model.layers.7.self_attn.k_proj (inputs) +24-11-19 20:46:34 | D | - Quantizing model.layers.7.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:34 | D | - Quantizing model.layers.7.self_attn.o_proj (inputs) +24-11-19 20:46:34 | D | - Quantizing model.layers.7.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:34 | D | - Quantizing model.layers.7.mlp.gate_proj (inputs) +24-11-19 20:46:34 | D | - Quantizing model.layers.7.mlp.up_proj (inputs) +24-11-19 20:46:34 | D | - Quantizing model.layers.7.mlp.down_proj (inputs) +24-11-19 20:46:41 | D | - Quantizing layer model.layers.8 +24-11-19 20:46:41 | D | - Calibrating model.layers.8.self_attn.v_proj.input +24-11-19 20:46:41 | D | - Calibrating model.layers.8.self_attn.k_rotary_emb.output +24-11-19 20:46:41 | D | + w: None +24-11-19 20:46:41 | D | + x: None +24-11-19 20:46:41 | D | + y: sint8 +24-11-19 20:46:41 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:41 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:46:41 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:46:41 | D | - range ratio = [ 1.0000] +24-11-19 20:46:41 | D | sum error = [ 28.5600] +24-11-19 20:46:41 | D | best error = [ 28.5600] +24-11-19 20:46:41 | D | + error = [28.5600] +24-11-19 20:46:42 | D | - Calibrating model.layers.8.self_attn.v_proj.output +24-11-19 20:46:42 | D | + w: None +24-11-19 20:46:42 | D | + x: None +24-11-19 20:46:42 | D | + y: sint8 +24-11-19 20:46:42 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:42 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:46:42 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:46:42 | D | - range ratio = [ 1.0000] +24-11-19 20:46:42 | D | sum error = [ 22.1969] +24-11-19 20:46:42 | D | best error = [ 22.1969] +24-11-19 20:46:42 | D | + error = [22.1969] +24-11-19 20:46:42 | D | - Calibrating model.layers.8.self_attn.o_proj.input +24-11-19 20:46:43 | D | - Calibrating model.layers.8.mlp.up_proj.input +24-11-19 20:46:43 | D | - Calibrating model.layers.8.mlp.down_proj.input +24-11-19 20:46:43 | D | - Quantizing model.layers.8.self_attn.q_proj (inputs) +24-11-19 20:46:43 | D | - Quantizing model.layers.8.self_attn.k_proj (inputs) +24-11-19 20:46:43 | D | - Quantizing model.layers.8.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:43 | D | - Quantizing model.layers.8.self_attn.o_proj (inputs) +24-11-19 20:46:43 | D | - Quantizing model.layers.8.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:43 | D | - Quantizing model.layers.8.mlp.gate_proj (inputs) +24-11-19 20:46:43 | D | - Quantizing model.layers.8.mlp.up_proj (inputs) +24-11-19 20:46:43 | D | - Quantizing model.layers.8.mlp.down_proj (inputs) +24-11-19 20:46:50 | D | - Quantizing layer model.layers.9 +24-11-19 20:46:50 | D | - Calibrating model.layers.9.self_attn.v_proj.input +24-11-19 20:46:50 | D | - Calibrating model.layers.9.self_attn.k_rotary_emb.output +24-11-19 20:46:50 | D | + w: None +24-11-19 20:46:50 | D | + x: None +24-11-19 20:46:50 | D | + y: sint8 +24-11-19 20:46:50 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:50 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:46:50 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:46:51 | D | - range ratio = [ 1.0000] +24-11-19 20:46:51 | D | sum error = [ 35.1792] +24-11-19 20:46:51 | D | best error = [ 35.1792] +24-11-19 20:46:51 | D | + error = [35.1792] +24-11-19 20:46:51 | D | - Calibrating model.layers.9.self_attn.v_proj.output +24-11-19 20:46:51 | D | + w: None +24-11-19 20:46:51 | D | + x: None +24-11-19 20:46:51 | D | + y: sint8 +24-11-19 20:46:51 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:51 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:46:51 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:46:52 | D | - range ratio = [ 1.0000] +24-11-19 20:46:52 | D | sum error = [ 59.3898] +24-11-19 20:46:52 | D | best error = [ 59.3898] +24-11-19 20:46:52 | D | + error = [59.3898] +24-11-19 20:46:52 | D | - Calibrating model.layers.9.self_attn.o_proj.input +24-11-19 20:46:52 | D | - Calibrating model.layers.9.mlp.up_proj.input +24-11-19 20:46:52 | D | - Calibrating model.layers.9.mlp.down_proj.input +24-11-19 20:46:52 | D | - Quantizing model.layers.9.self_attn.q_proj (inputs) +24-11-19 20:46:52 | D | - Quantizing model.layers.9.self_attn.k_proj (inputs) +24-11-19 20:46:52 | D | - Quantizing model.layers.9.self_attn.v_proj (inputs and outputs) +24-11-19 20:46:52 | D | - Quantizing model.layers.9.self_attn.o_proj (inputs) +24-11-19 20:46:52 | D | - Quantizing model.layers.9.self_attn.k_rotary_emb (outputs) +24-11-19 20:46:52 | D | - Quantizing model.layers.9.mlp.gate_proj (inputs) +24-11-19 20:46:52 | D | - Quantizing model.layers.9.mlp.up_proj (inputs) +24-11-19 20:46:52 | D | - Quantizing model.layers.9.mlp.down_proj (inputs) +24-11-19 20:46:59 | D | - Quantizing layer model.layers.10 +24-11-19 20:46:59 | D | - Calibrating model.layers.10.self_attn.v_proj.input +24-11-19 20:46:59 | D | - Calibrating model.layers.10.self_attn.k_rotary_emb.output +24-11-19 20:46:59 | D | + w: None +24-11-19 20:46:59 | D | + x: None +24-11-19 20:46:59 | D | + y: sint8 +24-11-19 20:46:59 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:46:59 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:46:59 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:46:59 | D | - range ratio = [ 1.0000] +24-11-19 20:46:59 | D | sum error = [ 29.8842] +24-11-19 20:46:59 | D | best error = [ 29.8842] +24-11-19 20:46:59 | D | + error = [29.8842] +24-11-19 20:47:00 | D | - Calibrating model.layers.10.self_attn.v_proj.output +24-11-19 20:47:00 | D | + w: None +24-11-19 20:47:00 | D | + x: None +24-11-19 20:47:00 | D | + y: sint8 +24-11-19 20:47:00 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:00 | D | + finished parsing calibration arguments, ram usage: 13.5 +24-11-19 20:47:00 | D | + finished reseting calibrator, ram usage: 13.6 +24-11-19 20:47:00 | D | - range ratio = [ 1.0000] +24-11-19 20:47:00 | D | sum error = [ 34.7971] +24-11-19 20:47:00 | D | best error = [ 34.7971] +24-11-19 20:47:00 | D | + error = [34.7971] +24-11-19 20:47:00 | D | - Calibrating model.layers.10.self_attn.o_proj.input +24-11-19 20:47:00 | D | - Calibrating model.layers.10.mlp.up_proj.input +24-11-19 20:47:01 | D | - Calibrating model.layers.10.mlp.down_proj.input +24-11-19 20:47:01 | D | - Quantizing model.layers.10.self_attn.q_proj (inputs) +24-11-19 20:47:01 | D | - Quantizing model.layers.10.self_attn.k_proj (inputs) +24-11-19 20:47:01 | D | - Quantizing model.layers.10.self_attn.v_proj (inputs and outputs) +24-11-19 20:47:01 | D | - Quantizing model.layers.10.self_attn.o_proj (inputs) +24-11-19 20:47:01 | D | - Quantizing model.layers.10.self_attn.k_rotary_emb (outputs) +24-11-19 20:47:01 | D | - Quantizing model.layers.10.mlp.gate_proj (inputs) +24-11-19 20:47:01 | D | - Quantizing model.layers.10.mlp.up_proj (inputs) +24-11-19 20:47:01 | D | - Quantizing model.layers.10.mlp.down_proj (inputs) +24-11-19 20:47:07 | D | - Quantizing layer model.layers.11 +24-11-19 20:47:07 | D | - Calibrating model.layers.11.self_attn.v_proj.input +24-11-19 20:47:07 | D | - Calibrating model.layers.11.self_attn.k_rotary_emb.output +24-11-19 20:47:07 | D | + w: None +24-11-19 20:47:07 | D | + x: None +24-11-19 20:47:07 | D | + y: sint8 +24-11-19 20:47:07 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:07 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:47:08 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:47:08 | D | - range ratio = [ 1.0000] +24-11-19 20:47:08 | D | sum error = [ 34.3829] +24-11-19 20:47:08 | D | best error = [ 34.3829] +24-11-19 20:47:08 | D | + error = [34.3829] +24-11-19 20:47:08 | D | - Calibrating model.layers.11.self_attn.v_proj.output +24-11-19 20:47:08 | D | + w: None +24-11-19 20:47:08 | D | + x: None +24-11-19 20:47:08 | D | + y: sint8 +24-11-19 20:47:08 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:08 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:47:09 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:47:09 | D | - range ratio = [ 1.0000] +24-11-19 20:47:09 | D | sum error = [ 27.2182] +24-11-19 20:47:09 | D | best error = [ 27.2182] +24-11-19 20:47:09 | D | + error = [27.2182] +24-11-19 20:47:09 | D | - Calibrating model.layers.11.self_attn.o_proj.input +24-11-19 20:47:09 | D | - Calibrating model.layers.11.mlp.up_proj.input +24-11-19 20:47:09 | D | - Calibrating model.layers.11.mlp.down_proj.input +24-11-19 20:47:09 | D | - Quantizing model.layers.11.self_attn.q_proj (inputs) +24-11-19 20:47:09 | D | - Quantizing model.layers.11.self_attn.k_proj (inputs) +24-11-19 20:47:09 | D | - Quantizing model.layers.11.self_attn.v_proj (inputs and outputs) +24-11-19 20:47:09 | D | - Quantizing model.layers.11.self_attn.o_proj (inputs) +24-11-19 20:47:09 | D | - Quantizing model.layers.11.self_attn.k_rotary_emb (outputs) +24-11-19 20:47:09 | D | - Quantizing model.layers.11.mlp.gate_proj (inputs) +24-11-19 20:47:09 | D | - Quantizing model.layers.11.mlp.up_proj (inputs) +24-11-19 20:47:09 | D | - Quantizing model.layers.11.mlp.down_proj (inputs) +24-11-19 20:47:17 | D | - Quantizing layer model.layers.12 +24-11-19 20:47:17 | D | - Calibrating model.layers.12.self_attn.v_proj.input +24-11-19 20:47:17 | D | - Calibrating model.layers.12.self_attn.k_rotary_emb.output +24-11-19 20:47:17 | D | + w: None +24-11-19 20:47:17 | D | + x: None +24-11-19 20:47:17 | D | + y: sint8 +24-11-19 20:47:17 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:17 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:47:17 | D | + finished reseting calibrator, ram usage: 13.5 +24-11-19 20:47:17 | D | - range ratio = [ 1.0000] +24-11-19 20:47:17 | D | sum error = [ 42.4076] +24-11-19 20:47:17 | D | best error = [ 42.4076] +24-11-19 20:47:17 | D | + error = [42.4076] +24-11-19 20:47:17 | D | - Calibrating model.layers.12.self_attn.v_proj.output +24-11-19 20:47:17 | D | + w: None +24-11-19 20:47:17 | D | + x: None +24-11-19 20:47:17 | D | + y: sint8 +24-11-19 20:47:17 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:17 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:47:18 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:47:18 | D | - range ratio = [ 1.0000] +24-11-19 20:47:18 | D | sum error = [ 22.8474] +24-11-19 20:47:18 | D | best error = [ 22.8474] +24-11-19 20:47:18 | D | + error = [22.8474] +24-11-19 20:47:18 | D | - Calibrating model.layers.12.self_attn.o_proj.input +24-11-19 20:47:18 | D | - Calibrating model.layers.12.mlp.up_proj.input +24-11-19 20:47:18 | D | - Calibrating model.layers.12.mlp.down_proj.input +24-11-19 20:47:19 | D | - Quantizing model.layers.12.self_attn.q_proj (inputs) +24-11-19 20:47:19 | D | - Quantizing model.layers.12.self_attn.k_proj (inputs) +24-11-19 20:47:19 | D | - Quantizing model.layers.12.self_attn.v_proj (inputs and outputs) +24-11-19 20:47:19 | D | - Quantizing model.layers.12.self_attn.o_proj (inputs) +24-11-19 20:47:19 | D | - Quantizing model.layers.12.self_attn.k_rotary_emb (outputs) +24-11-19 20:47:19 | D | - Quantizing model.layers.12.mlp.gate_proj (inputs) +24-11-19 20:47:19 | D | - Quantizing model.layers.12.mlp.up_proj (inputs) +24-11-19 20:47:19 | D | - Quantizing model.layers.12.mlp.down_proj (inputs) +24-11-19 20:47:25 | D | - Quantizing layer model.layers.13 +24-11-19 20:47:25 | D | - Calibrating model.layers.13.self_attn.v_proj.input +24-11-19 20:47:25 | D | - Calibrating model.layers.13.self_attn.k_rotary_emb.output +24-11-19 20:47:25 | D | + w: None +24-11-19 20:47:25 | D | + x: None +24-11-19 20:47:25 | D | + y: sint8 +24-11-19 20:47:25 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:25 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:47:26 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:47:26 | D | - range ratio = [ 1.0000] +24-11-19 20:47:26 | D | sum error = [ 35.1875] +24-11-19 20:47:26 | D | best error = [ 35.1875] +24-11-19 20:47:26 | D | + error = [35.1875] +24-11-19 20:47:26 | D | - Calibrating model.layers.13.self_attn.v_proj.output +24-11-19 20:47:26 | D | + w: None +24-11-19 20:47:26 | D | + x: None +24-11-19 20:47:26 | D | + y: sint8 +24-11-19 20:47:26 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:26 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:47:26 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:47:27 | D | - range ratio = [ 1.0000] +24-11-19 20:47:27 | D | sum error = [ 26.6708] +24-11-19 20:47:27 | D | best error = [ 26.6708] +24-11-19 20:47:27 | D | + error = [26.6708] +24-11-19 20:47:27 | D | - Calibrating model.layers.13.self_attn.o_proj.input +24-11-19 20:47:27 | D | - Calibrating model.layers.13.mlp.up_proj.input +24-11-19 20:47:27 | D | - Calibrating model.layers.13.mlp.down_proj.input +24-11-19 20:47:27 | D | - Quantizing model.layers.13.self_attn.q_proj (inputs) +24-11-19 20:47:27 | D | - Quantizing model.layers.13.self_attn.k_proj (inputs) +24-11-19 20:47:27 | D | - Quantizing model.layers.13.self_attn.v_proj (inputs and outputs) +24-11-19 20:47:27 | D | - Quantizing model.layers.13.self_attn.o_proj (inputs) +24-11-19 20:47:27 | D | - Quantizing model.layers.13.self_attn.k_rotary_emb (outputs) +24-11-19 20:47:27 | D | - Quantizing model.layers.13.mlp.gate_proj (inputs) +24-11-19 20:47:27 | D | - Quantizing model.layers.13.mlp.up_proj (inputs) +24-11-19 20:47:27 | D | - Quantizing model.layers.13.mlp.down_proj (inputs) +24-11-19 20:47:34 | D | - Quantizing layer model.layers.14 +24-11-19 20:47:34 | D | - Calibrating model.layers.14.self_attn.v_proj.input +24-11-19 20:47:34 | D | - Calibrating model.layers.14.self_attn.k_rotary_emb.output +24-11-19 20:47:34 | D | + w: None +24-11-19 20:47:34 | D | + x: None +24-11-19 20:47:34 | D | + y: sint8 +24-11-19 20:47:34 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:34 | D | + finished parsing calibration arguments, ram usage: 13.8 +24-11-19 20:47:34 | D | + finished reseting calibrator, ram usage: 13.8 +24-11-19 20:47:35 | D | - range ratio = [ 1.0000] +24-11-19 20:47:35 | D | sum error = [ 45.4742] +24-11-19 20:47:35 | D | best error = [ 45.4742] +24-11-19 20:47:35 | D | + error = [45.4742] +24-11-19 20:47:35 | D | - Calibrating model.layers.14.self_attn.v_proj.output +24-11-19 20:47:35 | D | + w: None +24-11-19 20:47:35 | D | + x: None +24-11-19 20:47:35 | D | + y: sint8 +24-11-19 20:47:35 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:35 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:47:36 | D | + finished reseting calibrator, ram usage: 13.9 +24-11-19 20:47:36 | D | - range ratio = [ 1.0000] +24-11-19 20:47:36 | D | sum error = [ 25.1251] +24-11-19 20:47:36 | D | best error = [ 25.1251] +24-11-19 20:47:36 | D | + error = [25.1251] +24-11-19 20:47:37 | D | - Calibrating model.layers.14.self_attn.o_proj.input +24-11-19 20:47:37 | D | - Calibrating model.layers.14.mlp.up_proj.input +24-11-19 20:47:37 | D | - Calibrating model.layers.14.mlp.down_proj.input +24-11-19 20:47:37 | D | - Quantizing model.layers.14.self_attn.q_proj (inputs) +24-11-19 20:47:37 | D | - Quantizing model.layers.14.self_attn.k_proj (inputs) +24-11-19 20:47:37 | D | - Quantizing model.layers.14.self_attn.v_proj (inputs and outputs) +24-11-19 20:47:37 | D | - Quantizing model.layers.14.self_attn.o_proj (inputs) +24-11-19 20:47:37 | D | - Quantizing model.layers.14.self_attn.k_rotary_emb (outputs) +24-11-19 20:47:37 | D | - Quantizing model.layers.14.mlp.gate_proj (inputs) +24-11-19 20:47:37 | D | - Quantizing model.layers.14.mlp.up_proj (inputs) +24-11-19 20:47:37 | D | - Quantizing model.layers.14.mlp.down_proj (inputs) +24-11-19 20:47:44 | D | - Quantizing layer model.layers.15 +24-11-19 20:47:44 | D | - Calibrating model.layers.15.self_attn.v_proj.input +24-11-19 20:47:44 | D | - Calibrating model.layers.15.self_attn.k_rotary_emb.output +24-11-19 20:47:44 | D | + w: None +24-11-19 20:47:44 | D | + x: None +24-11-19 20:47:44 | D | + y: sint8 +24-11-19 20:47:44 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:44 | D | + finished parsing calibration arguments, ram usage: 13.7 +24-11-19 20:47:44 | D | + finished reseting calibrator, ram usage: 13.7 +24-11-19 20:47:45 | D | - range ratio = [ 1.0000] +24-11-19 20:47:45 | D | sum error = [ 40.1380] +24-11-19 20:47:45 | D | best error = [ 40.1380] +24-11-19 20:47:45 | D | + error = [40.1380] +24-11-19 20:47:45 | D | - Calibrating model.layers.15.self_attn.v_proj.output +24-11-19 20:47:45 | D | + w: None +24-11-19 20:47:45 | D | + x: None +24-11-19 20:47:45 | D | + y: sint8 +24-11-19 20:47:45 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:45 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:47:45 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:47:46 | D | - range ratio = [ 1.0000] +24-11-19 20:47:46 | D | sum error = [ 45.8668] +24-11-19 20:47:46 | D | best error = [ 45.8668] +24-11-19 20:47:46 | D | + error = [45.8668] +24-11-19 20:47:46 | D | - Calibrating model.layers.15.self_attn.o_proj.input +24-11-19 20:47:46 | D | - Calibrating model.layers.15.mlp.up_proj.input +24-11-19 20:47:46 | D | - Calibrating model.layers.15.mlp.down_proj.input +24-11-19 20:47:46 | D | - Quantizing model.layers.15.self_attn.q_proj (inputs) +24-11-19 20:47:46 | D | - Quantizing model.layers.15.self_attn.k_proj (inputs) +24-11-19 20:47:46 | D | - Quantizing model.layers.15.self_attn.v_proj (inputs and outputs) +24-11-19 20:47:46 | D | - Quantizing model.layers.15.self_attn.o_proj (inputs) +24-11-19 20:47:46 | D | - Quantizing model.layers.15.self_attn.k_rotary_emb (outputs) +24-11-19 20:47:46 | D | - Quantizing model.layers.15.mlp.gate_proj (inputs) +24-11-19 20:47:46 | D | - Quantizing model.layers.15.mlp.up_proj (inputs) +24-11-19 20:47:46 | D | - Quantizing model.layers.15.mlp.down_proj (inputs) +24-11-19 20:47:52 | D | - Quantizing layer model.layers.16 +24-11-19 20:47:52 | D | - Calibrating model.layers.16.self_attn.v_proj.input +24-11-19 20:47:53 | D | - Calibrating model.layers.16.self_attn.k_rotary_emb.output +24-11-19 20:47:53 | D | + w: None +24-11-19 20:47:53 | D | + x: None +24-11-19 20:47:53 | D | + y: sint8 +24-11-19 20:47:53 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:53 | D | + finished parsing calibration arguments, ram usage: 13.6 +24-11-19 20:47:53 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:47:53 | D | - range ratio = [ 1.0000] +24-11-19 20:47:53 | D | sum error = [ 50.3394] +24-11-19 20:47:53 | D | best error = [ 50.3394] +24-11-19 20:47:53 | D | + error = [50.3394] +24-11-19 20:47:53 | D | - Calibrating model.layers.16.self_attn.v_proj.output +24-11-19 20:47:53 | D | + w: None +24-11-19 20:47:53 | D | + x: None +24-11-19 20:47:53 | D | + y: sint8 +24-11-19 20:47:53 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:47:53 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:47:54 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:47:54 | D | - range ratio = [ 1.0000] +24-11-19 20:47:54 | D | sum error = [ 37.8089] +24-11-19 20:47:54 | D | best error = [ 37.8089] +24-11-19 20:47:54 | D | + error = [37.8089] +24-11-19 20:47:54 | D | - Calibrating model.layers.16.self_attn.o_proj.input +24-11-19 20:47:55 | D | - Calibrating model.layers.16.mlp.up_proj.input +24-11-19 20:47:55 | D | - Calibrating model.layers.16.mlp.down_proj.input +24-11-19 20:47:55 | D | - Quantizing model.layers.16.self_attn.q_proj (inputs) +24-11-19 20:47:55 | D | - Quantizing model.layers.16.self_attn.k_proj (inputs) +24-11-19 20:47:55 | D | - Quantizing model.layers.16.self_attn.v_proj (inputs and outputs) +24-11-19 20:47:55 | D | - Quantizing model.layers.16.self_attn.o_proj (inputs) +24-11-19 20:47:55 | D | - Quantizing model.layers.16.self_attn.k_rotary_emb (outputs) +24-11-19 20:47:55 | D | - Quantizing model.layers.16.mlp.gate_proj (inputs) +24-11-19 20:47:55 | D | - Quantizing model.layers.16.mlp.up_proj (inputs) +24-11-19 20:47:55 | D | - Quantizing model.layers.16.mlp.down_proj (inputs) +24-11-19 20:48:01 | D | - Quantizing layer model.layers.17 +24-11-19 20:48:01 | D | - Calibrating model.layers.17.self_attn.v_proj.input +24-11-19 20:48:01 | D | - Calibrating model.layers.17.self_attn.k_rotary_emb.output +24-11-19 20:48:01 | D | + w: None +24-11-19 20:48:01 | D | + x: None +24-11-19 20:48:01 | D | + y: sint8 +24-11-19 20:48:01 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:01 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:48:01 | D | + finished reseting calibrator, ram usage: 13.3 +24-11-19 20:48:02 | D | - range ratio = [ 1.0000] +24-11-19 20:48:02 | D | sum error = [ 41.0035] +24-11-19 20:48:02 | D | best error = [ 41.0035] +24-11-19 20:48:02 | D | + error = [41.0035] +24-11-19 20:48:02 | D | - Calibrating model.layers.17.self_attn.v_proj.output +24-11-19 20:48:02 | D | + w: None +24-11-19 20:48:02 | D | + x: None +24-11-19 20:48:02 | D | + y: sint8 +24-11-19 20:48:02 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:02 | D | + finished parsing calibration arguments, ram usage: 13.4 +24-11-19 20:48:02 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:48:03 | D | - range ratio = [ 1.0000] +24-11-19 20:48:03 | D | sum error = [ 57.8941] +24-11-19 20:48:03 | D | best error = [ 57.8941] +24-11-19 20:48:03 | D | + error = [57.8941] +24-11-19 20:48:03 | D | - Calibrating model.layers.17.self_attn.o_proj.input +24-11-19 20:48:03 | D | - Calibrating model.layers.17.mlp.up_proj.input +24-11-19 20:48:03 | D | - Calibrating model.layers.17.mlp.down_proj.input +24-11-19 20:48:03 | D | - Quantizing model.layers.17.self_attn.q_proj (inputs) +24-11-19 20:48:03 | D | - Quantizing model.layers.17.self_attn.k_proj (inputs) +24-11-19 20:48:03 | D | - Quantizing model.layers.17.self_attn.v_proj (inputs and outputs) +24-11-19 20:48:03 | D | - Quantizing model.layers.17.self_attn.o_proj (inputs) +24-11-19 20:48:03 | D | - Quantizing model.layers.17.self_attn.k_rotary_emb (outputs) +24-11-19 20:48:03 | D | - Quantizing model.layers.17.mlp.gate_proj (inputs) +24-11-19 20:48:03 | D | - Quantizing model.layers.17.mlp.up_proj (inputs) +24-11-19 20:48:03 | D | - Quantizing model.layers.17.mlp.down_proj (inputs) +24-11-19 20:48:10 | D | - Quantizing layer model.layers.18 +24-11-19 20:48:10 | D | - Calibrating model.layers.18.self_attn.v_proj.input +24-11-19 20:48:10 | D | - Calibrating model.layers.18.self_attn.k_rotary_emb.output +24-11-19 20:48:10 | D | + w: None +24-11-19 20:48:10 | D | + x: None +24-11-19 20:48:10 | D | + y: sint8 +24-11-19 20:48:10 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:10 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:48:10 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:48:10 | D | - range ratio = [ 1.0000] +24-11-19 20:48:10 | D | sum error = [ 33.7181] +24-11-19 20:48:10 | D | best error = [ 33.7181] +24-11-19 20:48:10 | D | + error = [33.7181] +24-11-19 20:48:10 | D | - Calibrating model.layers.18.self_attn.v_proj.output +24-11-19 20:48:10 | D | + w: None +24-11-19 20:48:10 | D | + x: None +24-11-19 20:48:10 | D | + y: sint8 +24-11-19 20:48:10 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:10 | D | + finished parsing calibration arguments, ram usage: 13.3 +24-11-19 20:48:11 | D | + finished reseting calibrator, ram usage: 13.4 +24-11-19 20:48:11 | D | - range ratio = [ 1.0000] +24-11-19 20:48:11 | D | sum error = [ 66.4837] +24-11-19 20:48:11 | D | best error = [ 66.4837] +24-11-19 20:48:11 | D | + error = [66.4837] +24-11-19 20:48:11 | D | - Calibrating model.layers.18.self_attn.o_proj.input +24-11-19 20:48:11 | D | - Calibrating model.layers.18.mlp.up_proj.input +24-11-19 20:48:11 | D | - Calibrating model.layers.18.mlp.down_proj.input +24-11-19 20:48:11 | D | - Quantizing model.layers.18.self_attn.q_proj (inputs) +24-11-19 20:48:11 | D | - Quantizing model.layers.18.self_attn.k_proj (inputs) +24-11-19 20:48:11 | D | - Quantizing model.layers.18.self_attn.v_proj (inputs and outputs) +24-11-19 20:48:11 | D | - Quantizing model.layers.18.self_attn.o_proj (inputs) +24-11-19 20:48:11 | D | - Quantizing model.layers.18.self_attn.k_rotary_emb (outputs) +24-11-19 20:48:11 | D | - Quantizing model.layers.18.mlp.gate_proj (inputs) +24-11-19 20:48:11 | D | - Quantizing model.layers.18.mlp.up_proj (inputs) +24-11-19 20:48:11 | D | - Quantizing model.layers.18.mlp.down_proj (inputs) +24-11-19 20:48:18 | D | - Quantizing layer model.layers.19 +24-11-19 20:48:18 | D | - Calibrating model.layers.19.self_attn.v_proj.input +24-11-19 20:48:18 | D | - Calibrating model.layers.19.self_attn.k_rotary_emb.output +24-11-19 20:48:18 | D | + w: None +24-11-19 20:48:18 | D | + x: None +24-11-19 20:48:18 | D | + y: sint8 +24-11-19 20:48:18 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:18 | D | + finished parsing calibration arguments, ram usage: 13.1 +24-11-19 20:48:18 | D | + finished reseting calibrator, ram usage: 13.1 +24-11-19 20:48:19 | D | - range ratio = [ 1.0000] +24-11-19 20:48:19 | D | sum error = [ 28.8116] +24-11-19 20:48:19 | D | best error = [ 28.8116] +24-11-19 20:48:19 | D | + error = [28.8116] +24-11-19 20:48:19 | D | - Calibrating model.layers.19.self_attn.v_proj.output +24-11-19 20:48:19 | D | + w: None +24-11-19 20:48:19 | D | + x: None +24-11-19 20:48:19 | D | + y: sint8 +24-11-19 20:48:19 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:19 | D | + finished parsing calibration arguments, ram usage: 12.9 +24-11-19 20:48:19 | D | + finished reseting calibrator, ram usage: 12.9 +24-11-19 20:48:20 | D | - range ratio = [ 1.0000] +24-11-19 20:48:20 | D | sum error = [ 62.4905] +24-11-19 20:48:20 | D | best error = [ 62.4905] +24-11-19 20:48:20 | D | + error = [62.4905] +24-11-19 20:48:20 | D | - Calibrating model.layers.19.self_attn.o_proj.input +24-11-19 20:48:20 | D | - Calibrating model.layers.19.mlp.up_proj.input +24-11-19 20:48:20 | D | - Calibrating model.layers.19.mlp.down_proj.input +24-11-19 20:48:20 | D | - Quantizing model.layers.19.self_attn.q_proj (inputs) +24-11-19 20:48:20 | D | - Quantizing model.layers.19.self_attn.k_proj (inputs) +24-11-19 20:48:20 | D | - Quantizing model.layers.19.self_attn.v_proj (inputs and outputs) +24-11-19 20:48:20 | D | - Quantizing model.layers.19.self_attn.o_proj (inputs) +24-11-19 20:48:20 | D | - Quantizing model.layers.19.self_attn.k_rotary_emb (outputs) +24-11-19 20:48:20 | D | - Quantizing model.layers.19.mlp.gate_proj (inputs) +24-11-19 20:48:20 | D | - Quantizing model.layers.19.mlp.up_proj (inputs) +24-11-19 20:48:20 | D | - Quantizing model.layers.19.mlp.down_proj (inputs) +24-11-19 20:48:27 | D | - Quantizing layer model.layers.20 +24-11-19 20:48:27 | D | - Calibrating model.layers.20.self_attn.v_proj.input +24-11-19 20:48:27 | D | - Calibrating model.layers.20.self_attn.k_rotary_emb.output +24-11-19 20:48:27 | D | + w: None +24-11-19 20:48:27 | D | + x: None +24-11-19 20:48:27 | D | + y: sint8 +24-11-19 20:48:27 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:27 | D | + finished parsing calibration arguments, ram usage: 12.7 +24-11-19 20:48:27 | D | + finished reseting calibrator, ram usage: 12.7 +24-11-19 20:48:28 | D | - range ratio = [ 1.0000] +24-11-19 20:48:28 | D | sum error = [ 31.4349] +24-11-19 20:48:28 | D | best error = [ 31.4349] +24-11-19 20:48:28 | D | + error = [31.4349] +24-11-19 20:48:28 | D | - Calibrating model.layers.20.self_attn.v_proj.output +24-11-19 20:48:28 | D | + w: None +24-11-19 20:48:28 | D | + x: None +24-11-19 20:48:28 | D | + y: sint8 +24-11-19 20:48:28 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:28 | D | + finished parsing calibration arguments, ram usage: 12.8 +24-11-19 20:48:28 | D | + finished reseting calibrator, ram usage: 12.8 +24-11-19 20:48:28 | D | - range ratio = [ 1.0000] +24-11-19 20:48:28 | D | sum error = [ 62.7481] +24-11-19 20:48:28 | D | best error = [ 62.7481] +24-11-19 20:48:28 | D | + error = [62.7481] +24-11-19 20:48:29 | D | - Calibrating model.layers.20.self_attn.o_proj.input +24-11-19 20:48:29 | D | - Calibrating model.layers.20.mlp.up_proj.input +24-11-19 20:48:29 | D | - Calibrating model.layers.20.mlp.down_proj.input +24-11-19 20:48:29 | D | - Quantizing model.layers.20.self_attn.q_proj (inputs) +24-11-19 20:48:29 | D | - Quantizing model.layers.20.self_attn.k_proj (inputs) +24-11-19 20:48:29 | D | - Quantizing model.layers.20.self_attn.v_proj (inputs and outputs) +24-11-19 20:48:29 | D | - Quantizing model.layers.20.self_attn.o_proj (inputs) +24-11-19 20:48:29 | D | - Quantizing model.layers.20.self_attn.k_rotary_emb (outputs) +24-11-19 20:48:29 | D | - Quantizing model.layers.20.mlp.gate_proj (inputs) +24-11-19 20:48:29 | D | - Quantizing model.layers.20.mlp.up_proj (inputs) +24-11-19 20:48:29 | D | - Quantizing model.layers.20.mlp.down_proj (inputs) +24-11-19 20:48:36 | D | - Quantizing layer model.layers.21 +24-11-19 20:48:36 | D | - Calibrating model.layers.21.self_attn.v_proj.input +24-11-19 20:48:36 | D | - Calibrating model.layers.21.self_attn.k_rotary_emb.output +24-11-19 20:48:36 | D | + w: None +24-11-19 20:48:36 | D | + x: None +24-11-19 20:48:36 | D | + y: sint8 +24-11-19 20:48:36 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:36 | D | + finished parsing calibration arguments, ram usage: 12.7 +24-11-19 20:48:36 | D | + finished reseting calibrator, ram usage: 12.7 +24-11-19 20:48:36 | D | - range ratio = [ 1.0000] +24-11-19 20:48:36 | D | sum error = [ 49.4348] +24-11-19 20:48:36 | D | best error = [ 49.4348] +24-11-19 20:48:36 | D | + error = [49.4348] +24-11-19 20:48:36 | D | - Calibrating model.layers.21.self_attn.v_proj.output +24-11-19 20:48:36 | D | + w: None +24-11-19 20:48:36 | D | + x: None +24-11-19 20:48:36 | D | + y: sint8 +24-11-19 20:48:36 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:36 | D | + finished parsing calibration arguments, ram usage: 12.8 +24-11-19 20:48:37 | D | + finished reseting calibrator, ram usage: 12.8 +24-11-19 20:48:37 | D | - range ratio = [ 1.0000] +24-11-19 20:48:37 | D | sum error = [ 64.9919] +24-11-19 20:48:37 | D | best error = [ 64.9919] +24-11-19 20:48:37 | D | + error = [64.9919] +24-11-19 20:48:37 | D | - Calibrating model.layers.21.self_attn.o_proj.input +24-11-19 20:48:37 | D | - Calibrating model.layers.21.mlp.up_proj.input +24-11-19 20:48:37 | D | - Calibrating model.layers.21.mlp.down_proj.input +24-11-19 20:48:37 | D | - Quantizing model.layers.21.self_attn.q_proj (inputs) +24-11-19 20:48:37 | D | - Quantizing model.layers.21.self_attn.k_proj (inputs) +24-11-19 20:48:37 | D | - Quantizing model.layers.21.self_attn.v_proj (inputs and outputs) +24-11-19 20:48:37 | D | - Quantizing model.layers.21.self_attn.o_proj (inputs) +24-11-19 20:48:37 | D | - Quantizing model.layers.21.self_attn.k_rotary_emb (outputs) +24-11-19 20:48:37 | D | - Quantizing model.layers.21.mlp.gate_proj (inputs) +24-11-19 20:48:37 | D | - Quantizing model.layers.21.mlp.up_proj (inputs) +24-11-19 20:48:37 | D | - Quantizing model.layers.21.mlp.down_proj (inputs) +24-11-19 20:48:44 | D | - Quantizing layer model.layers.22 +24-11-19 20:48:44 | D | - Calibrating model.layers.22.self_attn.v_proj.input +24-11-19 20:48:44 | D | - Calibrating model.layers.22.self_attn.k_rotary_emb.output +24-11-19 20:48:44 | D | + w: None +24-11-19 20:48:44 | D | + x: None +24-11-19 20:48:44 | D | + y: sint8 +24-11-19 20:48:44 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:44 | D | + finished parsing calibration arguments, ram usage: 13.2 +24-11-19 20:48:44 | D | + finished reseting calibrator, ram usage: 13.2 +24-11-19 20:48:45 | D | - range ratio = [ 1.0000] +24-11-19 20:48:45 | D | sum error = [ 38.4587] +24-11-19 20:48:45 | D | best error = [ 38.4587] +24-11-19 20:48:45 | D | + error = [38.4587] +24-11-19 20:48:45 | D | - Calibrating model.layers.22.self_attn.v_proj.output +24-11-19 20:48:45 | D | + w: None +24-11-19 20:48:45 | D | + x: None +24-11-19 20:48:45 | D | + y: sint8 +24-11-19 20:48:45 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:45 | D | + finished parsing calibration arguments, ram usage: 12.8 +24-11-19 20:48:45 | D | + finished reseting calibrator, ram usage: 12.8 +24-11-19 20:48:46 | D | - range ratio = [ 1.0000] +24-11-19 20:48:46 | D | sum error = [ 70.9346] +24-11-19 20:48:46 | D | best error = [ 70.9346] +24-11-19 20:48:46 | D | + error = [70.9346] +24-11-19 20:48:46 | D | - Calibrating model.layers.22.self_attn.o_proj.input +24-11-19 20:48:46 | D | - Calibrating model.layers.22.mlp.up_proj.input +24-11-19 20:48:46 | D | - Calibrating model.layers.22.mlp.down_proj.input +24-11-19 20:48:46 | D | - Quantizing model.layers.22.self_attn.q_proj (inputs) +24-11-19 20:48:46 | D | - Quantizing model.layers.22.self_attn.k_proj (inputs) +24-11-19 20:48:46 | D | - Quantizing model.layers.22.self_attn.v_proj (inputs and outputs) +24-11-19 20:48:46 | D | - Quantizing model.layers.22.self_attn.o_proj (inputs) +24-11-19 20:48:46 | D | - Quantizing model.layers.22.self_attn.k_rotary_emb (outputs) +24-11-19 20:48:46 | D | - Quantizing model.layers.22.mlp.gate_proj (inputs) +24-11-19 20:48:46 | D | - Quantizing model.layers.22.mlp.up_proj (inputs) +24-11-19 20:48:46 | D | - Quantizing model.layers.22.mlp.down_proj (inputs) +24-11-19 20:48:52 | D | - Quantizing layer model.layers.23 +24-11-19 20:48:52 | D | - Calibrating model.layers.23.self_attn.v_proj.input +24-11-19 20:48:52 | D | - Calibrating model.layers.23.self_attn.k_rotary_emb.output +24-11-19 20:48:52 | D | + w: None +24-11-19 20:48:52 | D | + x: None +24-11-19 20:48:52 | D | + y: sint8 +24-11-19 20:48:52 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:52 | D | + finished parsing calibration arguments, ram usage: 12.8 +24-11-19 20:48:53 | D | + finished reseting calibrator, ram usage: 12.8 +24-11-19 20:48:53 | D | - range ratio = [ 1.0000] +24-11-19 20:48:53 | D | sum error = [ 40.4494] +24-11-19 20:48:53 | D | best error = [ 40.4494] +24-11-19 20:48:53 | D | + error = [40.4494] +24-11-19 20:48:53 | D | - Calibrating model.layers.23.self_attn.v_proj.output +24-11-19 20:48:53 | D | + w: None +24-11-19 20:48:53 | D | + x: None +24-11-19 20:48:53 | D | + y: sint8 +24-11-19 20:48:53 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:48:53 | D | + finished parsing calibration arguments, ram usage: 12.8 +24-11-19 20:48:53 | D | + finished reseting calibrator, ram usage: 12.8 +24-11-19 20:48:54 | D | - range ratio = [ 1.0000] +24-11-19 20:48:54 | D | sum error = [ 75.5964] +24-11-19 20:48:54 | D | best error = [ 75.5964] +24-11-19 20:48:54 | D | + error = [75.5964] +24-11-19 20:48:54 | D | - Calibrating model.layers.23.self_attn.o_proj.input +24-11-19 20:48:54 | D | - Calibrating model.layers.23.mlp.up_proj.input +24-11-19 20:48:54 | D | - Calibrating model.layers.23.mlp.down_proj.input +24-11-19 20:48:54 | D | - Quantizing model.layers.23.self_attn.q_proj (inputs) +24-11-19 20:48:54 | D | - Quantizing model.layers.23.self_attn.k_proj (inputs) +24-11-19 20:48:54 | D | - Quantizing model.layers.23.self_attn.v_proj (inputs and outputs) +24-11-19 20:48:54 | D | - Quantizing model.layers.23.self_attn.o_proj (inputs) +24-11-19 20:48:54 | D | - Quantizing model.layers.23.self_attn.k_rotary_emb (outputs) +24-11-19 20:48:54 | D | - Quantizing model.layers.23.mlp.gate_proj (inputs) +24-11-19 20:48:54 | D | - Quantizing model.layers.23.mlp.up_proj (inputs) +24-11-19 20:48:54 | D | - Quantizing model.layers.23.mlp.down_proj (inputs) +24-11-19 20:49:01 | D | - Quantizing layer model.layers.24 +24-11-19 20:49:01 | D | - Calibrating model.layers.24.self_attn.v_proj.input +24-11-19 20:49:01 | D | - Calibrating model.layers.24.self_attn.k_rotary_emb.output +24-11-19 20:49:01 | D | + w: None +24-11-19 20:49:01 | D | + x: None +24-11-19 20:49:01 | D | + y: sint8 +24-11-19 20:49:01 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:01 | D | + finished parsing calibration arguments, ram usage: 12.8 +24-11-19 20:49:01 | D | + finished reseting calibrator, ram usage: 12.8 +24-11-19 20:49:01 | D | - range ratio = [ 1.0000] +24-11-19 20:49:01 | D | sum error = [ 47.9508] +24-11-19 20:49:01 | D | best error = [ 47.9508] +24-11-19 20:49:01 | D | + error = [47.9508] +24-11-19 20:49:02 | D | - Calibrating model.layers.24.self_attn.v_proj.output +24-11-19 20:49:02 | D | + w: None +24-11-19 20:49:02 | D | + x: None +24-11-19 20:49:02 | D | + y: sint8 +24-11-19 20:49:02 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:02 | D | + finished parsing calibration arguments, ram usage: 12.8 +24-11-19 20:49:02 | D | + finished reseting calibrator, ram usage: 12.6 +24-11-19 20:49:02 | D | - range ratio = [ 1.0000] +24-11-19 20:49:02 | D | sum error = [ 87.2707] +24-11-19 20:49:02 | D | best error = [ 87.2707] +24-11-19 20:49:02 | D | + error = [87.2707] +24-11-19 20:49:02 | D | - Calibrating model.layers.24.self_attn.o_proj.input +24-11-19 20:49:02 | D | - Calibrating model.layers.24.mlp.up_proj.input +24-11-19 20:49:02 | D | - Calibrating model.layers.24.mlp.down_proj.input +24-11-19 20:49:03 | D | - Quantizing model.layers.24.self_attn.q_proj (inputs) +24-11-19 20:49:03 | D | - Quantizing model.layers.24.self_attn.k_proj (inputs) +24-11-19 20:49:03 | D | - Quantizing model.layers.24.self_attn.v_proj (inputs and outputs) +24-11-19 20:49:03 | D | - Quantizing model.layers.24.self_attn.o_proj (inputs) +24-11-19 20:49:03 | D | - Quantizing model.layers.24.self_attn.k_rotary_emb (outputs) +24-11-19 20:49:03 | D | - Quantizing model.layers.24.mlp.gate_proj (inputs) +24-11-19 20:49:03 | D | - Quantizing model.layers.24.mlp.up_proj (inputs) +24-11-19 20:49:03 | D | - Quantizing model.layers.24.mlp.down_proj (inputs) +24-11-19 20:49:09 | D | - Quantizing layer model.layers.25 +24-11-19 20:49:09 | D | - Calibrating model.layers.25.self_attn.v_proj.input +24-11-19 20:49:09 | D | - Calibrating model.layers.25.self_attn.k_rotary_emb.output +24-11-19 20:49:09 | D | + w: None +24-11-19 20:49:09 | D | + x: None +24-11-19 20:49:09 | D | + y: sint8 +24-11-19 20:49:09 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:09 | D | + finished parsing calibration arguments, ram usage: 12.8 +24-11-19 20:49:09 | D | + finished reseting calibrator, ram usage: 12.8 +24-11-19 20:49:09 | D | - range ratio = [ 1.0000] +24-11-19 20:49:09 | D | sum error = [ 59.7888] +24-11-19 20:49:09 | D | best error = [ 59.7888] +24-11-19 20:49:09 | D | + error = [59.7888] +24-11-19 20:49:10 | D | - Calibrating model.layers.25.self_attn.v_proj.output +24-11-19 20:49:10 | D | + w: None +24-11-19 20:49:10 | D | + x: None +24-11-19 20:49:10 | D | + y: sint8 +24-11-19 20:49:10 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:10 | D | + finished parsing calibration arguments, ram usage: 12.4 +24-11-19 20:49:10 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 20:49:10 | D | - range ratio = [ 1.0000] +24-11-19 20:49:10 | D | sum error = [ 103.2094] +24-11-19 20:49:10 | D | best error = [ 103.2094] +24-11-19 20:49:10 | D | + error = [103.2094] +24-11-19 20:49:10 | D | - Calibrating model.layers.25.self_attn.o_proj.input +24-11-19 20:49:10 | D | - Calibrating model.layers.25.mlp.up_proj.input +24-11-19 20:49:10 | D | - Calibrating model.layers.25.mlp.down_proj.input +24-11-19 20:49:11 | D | - Quantizing model.layers.25.self_attn.q_proj (inputs) +24-11-19 20:49:11 | D | - Quantizing model.layers.25.self_attn.k_proj (inputs) +24-11-19 20:49:11 | D | - Quantizing model.layers.25.self_attn.v_proj (inputs and outputs) +24-11-19 20:49:11 | D | - Quantizing model.layers.25.self_attn.o_proj (inputs) +24-11-19 20:49:11 | D | - Quantizing model.layers.25.self_attn.k_rotary_emb (outputs) +24-11-19 20:49:11 | D | - Quantizing model.layers.25.mlp.gate_proj (inputs) +24-11-19 20:49:11 | D | - Quantizing model.layers.25.mlp.up_proj (inputs) +24-11-19 20:49:11 | D | - Quantizing model.layers.25.mlp.down_proj (inputs) +24-11-19 20:49:17 | D | - Quantizing layer model.layers.26 +24-11-19 20:49:17 | D | - Calibrating model.layers.26.self_attn.v_proj.input +24-11-19 20:49:17 | D | - Calibrating model.layers.26.self_attn.k_rotary_emb.output +24-11-19 20:49:17 | D | + w: None +24-11-19 20:49:17 | D | + x: None +24-11-19 20:49:17 | D | + y: sint8 +24-11-19 20:49:17 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:17 | D | + finished parsing calibration arguments, ram usage: 12.5 +24-11-19 20:49:17 | D | + finished reseting calibrator, ram usage: 12.4 +24-11-19 20:49:18 | D | - range ratio = [ 1.0000] +24-11-19 20:49:18 | D | sum error = [ 58.1479] +24-11-19 20:49:18 | D | best error = [ 58.1479] +24-11-19 20:49:18 | D | + error = [58.1479] +24-11-19 20:49:18 | D | - Calibrating model.layers.26.self_attn.v_proj.output +24-11-19 20:49:18 | D | + w: None +24-11-19 20:49:18 | D | + x: None +24-11-19 20:49:18 | D | + y: sint8 +24-11-19 20:49:18 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:18 | D | + finished parsing calibration arguments, ram usage: 12.5 +24-11-19 20:49:18 | D | + finished reseting calibrator, ram usage: 12.5 +24-11-19 20:49:18 | D | - range ratio = [ 1.0000] +24-11-19 20:49:18 | D | sum error = [ 89.1065] +24-11-19 20:49:18 | D | best error = [ 89.1065] +24-11-19 20:49:18 | D | + error = [89.1065] +24-11-19 20:49:18 | D | - Calibrating model.layers.26.self_attn.o_proj.input +24-11-19 20:49:19 | D | - Calibrating model.layers.26.mlp.up_proj.input +24-11-19 20:49:19 | D | - Calibrating model.layers.26.mlp.down_proj.input +24-11-19 20:49:19 | D | - Quantizing model.layers.26.self_attn.q_proj (inputs) +24-11-19 20:49:19 | D | - Quantizing model.layers.26.self_attn.k_proj (inputs) +24-11-19 20:49:19 | D | - Quantizing model.layers.26.self_attn.v_proj (inputs and outputs) +24-11-19 20:49:19 | D | - Quantizing model.layers.26.self_attn.o_proj (inputs) +24-11-19 20:49:19 | D | - Quantizing model.layers.26.self_attn.k_rotary_emb (outputs) +24-11-19 20:49:19 | D | - Quantizing model.layers.26.mlp.gate_proj (inputs) +24-11-19 20:49:19 | D | - Quantizing model.layers.26.mlp.up_proj (inputs) +24-11-19 20:49:19 | D | - Quantizing model.layers.26.mlp.down_proj (inputs) +24-11-19 20:49:25 | D | - Quantizing layer model.layers.27 +24-11-19 20:49:25 | D | - Calibrating model.layers.27.self_attn.v_proj.input +24-11-19 20:49:25 | D | - Calibrating model.layers.27.self_attn.k_rotary_emb.output +24-11-19 20:49:25 | D | + w: None +24-11-19 20:49:25 | D | + x: None +24-11-19 20:49:25 | D | + y: sint8 +24-11-19 20:49:25 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:25 | D | + finished parsing calibration arguments, ram usage: 12.5 +24-11-19 20:49:25 | D | + finished reseting calibrator, ram usage: 12.5 +24-11-19 20:49:26 | D | - range ratio = [ 1.0000] +24-11-19 20:49:26 | D | sum error = [ 59.6149] +24-11-19 20:49:26 | D | best error = [ 59.6149] +24-11-19 20:49:26 | D | + error = [59.6149] +24-11-19 20:49:26 | D | - Calibrating model.layers.27.self_attn.v_proj.output +24-11-19 20:49:26 | D | + w: None +24-11-19 20:49:26 | D | + x: None +24-11-19 20:49:26 | D | + y: sint8 +24-11-19 20:49:26 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:26 | D | + finished parsing calibration arguments, ram usage: 12.6 +24-11-19 20:49:26 | D | + finished reseting calibrator, ram usage: 12.6 +24-11-19 20:49:26 | D | - range ratio = [ 1.0000] +24-11-19 20:49:26 | D | sum error = [ 116.0709] +24-11-19 20:49:26 | D | best error = [ 116.0709] +24-11-19 20:49:26 | D | + error = [116.0709] +24-11-19 20:49:26 | D | - Calibrating model.layers.27.self_attn.o_proj.input +24-11-19 20:49:27 | D | - Calibrating model.layers.27.mlp.up_proj.input +24-11-19 20:49:27 | D | - Calibrating model.layers.27.mlp.down_proj.input +24-11-19 20:49:27 | D | - Quantizing model.layers.27.self_attn.q_proj (inputs) +24-11-19 20:49:27 | D | - Quantizing model.layers.27.self_attn.k_proj (inputs) +24-11-19 20:49:27 | D | - Quantizing model.layers.27.self_attn.v_proj (inputs and outputs) +24-11-19 20:49:27 | D | - Quantizing model.layers.27.self_attn.o_proj (inputs) +24-11-19 20:49:27 | D | - Quantizing model.layers.27.self_attn.k_rotary_emb (outputs) +24-11-19 20:49:27 | D | - Quantizing model.layers.27.mlp.gate_proj (inputs) +24-11-19 20:49:27 | D | - Quantizing model.layers.27.mlp.up_proj (inputs) +24-11-19 20:49:27 | D | - Quantizing model.layers.27.mlp.down_proj (inputs) +24-11-19 20:49:33 | D | - Quantizing layer model.layers.28 +24-11-19 20:49:33 | D | - Calibrating model.layers.28.self_attn.v_proj.input +24-11-19 20:49:33 | D | - Calibrating model.layers.28.self_attn.k_rotary_emb.output +24-11-19 20:49:33 | D | + w: None +24-11-19 20:49:33 | D | + x: None +24-11-19 20:49:33 | D | + y: sint8 +24-11-19 20:49:33 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:33 | D | + finished parsing calibration arguments, ram usage: 12.6 +24-11-19 20:49:33 | D | + finished reseting calibrator, ram usage: 12.6 +24-11-19 20:49:34 | D | - range ratio = [ 1.0000] +24-11-19 20:49:34 | D | sum error = [ 75.0876] +24-11-19 20:49:34 | D | best error = [ 75.0876] +24-11-19 20:49:34 | D | + error = [75.0876] +24-11-19 20:49:34 | D | - Calibrating model.layers.28.self_attn.v_proj.output +24-11-19 20:49:34 | D | + w: None +24-11-19 20:49:34 | D | + x: None +24-11-19 20:49:34 | D | + y: sint8 +24-11-19 20:49:34 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:34 | D | + finished parsing calibration arguments, ram usage: 12.6 +24-11-19 20:49:34 | D | + finished reseting calibrator, ram usage: 12.7 +24-11-19 20:49:34 | D | - range ratio = [ 1.0000] +24-11-19 20:49:34 | D | sum error = [ 120.0427] +24-11-19 20:49:34 | D | best error = [ 120.0427] +24-11-19 20:49:34 | D | + error = [120.0427] +24-11-19 20:49:34 | D | - Calibrating model.layers.28.self_attn.o_proj.input +24-11-19 20:49:35 | D | - Calibrating model.layers.28.mlp.up_proj.input +24-11-19 20:49:35 | D | - Calibrating model.layers.28.mlp.down_proj.input +24-11-19 20:49:35 | D | - Quantizing model.layers.28.self_attn.q_proj (inputs) +24-11-19 20:49:35 | D | - Quantizing model.layers.28.self_attn.k_proj (inputs) +24-11-19 20:49:35 | D | - Quantizing model.layers.28.self_attn.v_proj (inputs and outputs) +24-11-19 20:49:35 | D | - Quantizing model.layers.28.self_attn.o_proj (inputs) +24-11-19 20:49:35 | D | - Quantizing model.layers.28.self_attn.k_rotary_emb (outputs) +24-11-19 20:49:35 | D | - Quantizing model.layers.28.mlp.gate_proj (inputs) +24-11-19 20:49:35 | D | - Quantizing model.layers.28.mlp.up_proj (inputs) +24-11-19 20:49:35 | D | - Quantizing model.layers.28.mlp.down_proj (inputs) +24-11-19 20:49:41 | D | - Quantizing layer model.layers.29 +24-11-19 20:49:41 | D | - Calibrating model.layers.29.self_attn.v_proj.input +24-11-19 20:49:41 | D | - Calibrating model.layers.29.self_attn.k_rotary_emb.output +24-11-19 20:49:41 | D | + w: None +24-11-19 20:49:41 | D | + x: None +24-11-19 20:49:41 | D | + y: sint8 +24-11-19 20:49:41 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:41 | D | + finished parsing calibration arguments, ram usage: 12.6 +24-11-19 20:49:41 | D | + finished reseting calibrator, ram usage: 12.6 +24-11-19 20:49:42 | D | - range ratio = [ 1.0000] +24-11-19 20:49:42 | D | sum error = [ 121.7204] +24-11-19 20:49:42 | D | best error = [ 121.7204] +24-11-19 20:49:42 | D | + error = [121.7204] +24-11-19 20:49:42 | D | - Calibrating model.layers.29.self_attn.v_proj.output +24-11-19 20:49:42 | D | + w: None +24-11-19 20:49:42 | D | + x: None +24-11-19 20:49:42 | D | + y: sint8 +24-11-19 20:49:42 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:42 | D | + finished parsing calibration arguments, ram usage: 12.7 +24-11-19 20:49:42 | D | + finished reseting calibrator, ram usage: 12.7 +24-11-19 20:49:42 | D | - range ratio = [ 1.0000] +24-11-19 20:49:42 | D | sum error = [ 151.3235] +24-11-19 20:49:42 | D | best error = [ 151.3235] +24-11-19 20:49:42 | D | + error = [151.3235] +24-11-19 20:49:42 | D | - Calibrating model.layers.29.self_attn.o_proj.input +24-11-19 20:49:42 | D | - Calibrating model.layers.29.mlp.up_proj.input +24-11-19 20:49:43 | D | - Calibrating model.layers.29.mlp.down_proj.input +24-11-19 20:49:43 | D | - Quantizing model.layers.29.self_attn.q_proj (inputs) +24-11-19 20:49:43 | D | - Quantizing model.layers.29.self_attn.k_proj (inputs) +24-11-19 20:49:43 | D | - Quantizing model.layers.29.self_attn.v_proj (inputs and outputs) +24-11-19 20:49:43 | D | - Quantizing model.layers.29.self_attn.o_proj (inputs) +24-11-19 20:49:43 | D | - Quantizing model.layers.29.self_attn.k_rotary_emb (outputs) +24-11-19 20:49:43 | D | - Quantizing model.layers.29.mlp.gate_proj (inputs) +24-11-19 20:49:43 | D | - Quantizing model.layers.29.mlp.up_proj (inputs) +24-11-19 20:49:43 | D | - Quantizing model.layers.29.mlp.down_proj (inputs) +24-11-19 20:49:49 | D | - Quantizing layer model.layers.30 +24-11-19 20:49:49 | D | - Calibrating model.layers.30.self_attn.v_proj.input +24-11-19 20:49:49 | D | - Calibrating model.layers.30.self_attn.k_rotary_emb.output +24-11-19 20:49:49 | D | + w: None +24-11-19 20:49:49 | D | + x: None +24-11-19 20:49:49 | D | + y: sint8 +24-11-19 20:49:49 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:49 | D | + finished parsing calibration arguments, ram usage: 12.7 +24-11-19 20:49:49 | D | + finished reseting calibrator, ram usage: 12.7 +24-11-19 20:49:50 | D | - range ratio = [ 1.0000] +24-11-19 20:49:50 | D | sum error = [ 97.6837] +24-11-19 20:49:50 | D | best error = [ 97.6837] +24-11-19 20:49:50 | D | + error = [97.6837] +24-11-19 20:49:50 | D | - Calibrating model.layers.30.self_attn.v_proj.output +24-11-19 20:49:50 | D | + w: None +24-11-19 20:49:50 | D | + x: None +24-11-19 20:49:50 | D | + y: sint8 +24-11-19 20:49:50 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:50 | D | + finished parsing calibration arguments, ram usage: 12.8 +24-11-19 20:49:50 | D | + finished reseting calibrator, ram usage: 12.8 +24-11-19 20:49:50 | D | - range ratio = [ 1.0000] +24-11-19 20:49:50 | D | sum error = [ 187.7211] +24-11-19 20:49:50 | D | best error = [ 187.7211] +24-11-19 20:49:50 | D | + error = [187.7211] +24-11-19 20:49:50 | D | - Calibrating model.layers.30.self_attn.o_proj.input +24-11-19 20:49:50 | D | - Calibrating model.layers.30.mlp.up_proj.input +24-11-19 20:49:51 | D | - Calibrating model.layers.30.mlp.down_proj.input +24-11-19 20:49:51 | D | - Quantizing model.layers.30.self_attn.q_proj (inputs) +24-11-19 20:49:51 | D | - Quantizing model.layers.30.self_attn.k_proj (inputs) +24-11-19 20:49:51 | D | - Quantizing model.layers.30.self_attn.v_proj (inputs and outputs) +24-11-19 20:49:51 | D | - Quantizing model.layers.30.self_attn.o_proj (inputs) +24-11-19 20:49:51 | D | - Quantizing model.layers.30.self_attn.k_rotary_emb (outputs) +24-11-19 20:49:51 | D | - Quantizing model.layers.30.mlp.gate_proj (inputs) +24-11-19 20:49:51 | D | - Quantizing model.layers.30.mlp.up_proj (inputs) +24-11-19 20:49:51 | D | - Quantizing model.layers.30.mlp.down_proj (inputs) +24-11-19 20:49:57 | D | - Quantizing layer model.layers.31 +24-11-19 20:49:57 | D | - Calibrating model.layers.31.self_attn.v_proj.input +24-11-19 20:49:57 | D | - Calibrating model.layers.31.self_attn.k_rotary_emb.output +24-11-19 20:49:57 | D | + w: None +24-11-19 20:49:57 | D | + x: None +24-11-19 20:49:57 | D | + y: sint8 +24-11-19 20:49:57 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:57 | D | + finished parsing calibration arguments, ram usage: 12.8 +24-11-19 20:49:57 | D | + finished reseting calibrator, ram usage: 12.8 +24-11-19 20:49:58 | D | - range ratio = [ 1.0000] +24-11-19 20:49:58 | D | sum error = [ 141.6907] +24-11-19 20:49:58 | D | best error = [ 141.6907] +24-11-19 20:49:58 | D | + error = [141.6907] +24-11-19 20:49:58 | D | - Calibrating model.layers.31.self_attn.v_proj.output +24-11-19 20:49:58 | D | + w: None +24-11-19 20:49:58 | D | + x: None +24-11-19 20:49:58 | D | + y: sint8 +24-11-19 20:49:58 | D | + tensor_type: TensorType.Outputs, objective: SearchBasedCalibObjective.OutputsError, granularity: SearchBasedCalibGranularity.Layer +24-11-19 20:49:58 | D | + finished parsing calibration arguments, ram usage: 12.8 +24-11-19 20:49:58 | D | + finished reseting calibrator, ram usage: 12.8 +24-11-19 20:49:58 | D | - range ratio = [ 1.0000] +24-11-19 20:49:58 | D | sum error = [ 148.2115] +24-11-19 20:49:58 | D | best error = [ 148.2115] +24-11-19 20:49:58 | D | + error = [148.2115] +24-11-19 20:49:58 | D | - Calibrating model.layers.31.self_attn.o_proj.input +24-11-19 20:49:59 | D | - Calibrating model.layers.31.mlp.up_proj.input +24-11-19 20:49:59 | D | - Calibrating model.layers.31.mlp.down_proj.input +24-11-19 20:49:59 | D | - Quantizing model.layers.31.self_attn.q_proj (inputs) +24-11-19 20:49:59 | D | - Quantizing model.layers.31.self_attn.k_proj (inputs) +24-11-19 20:49:59 | D | - Quantizing model.layers.31.self_attn.v_proj (inputs and outputs) +24-11-19 20:49:59 | D | - Quantizing model.layers.31.self_attn.o_proj (inputs) +24-11-19 20:49:59 | D | - Quantizing model.layers.31.self_attn.k_rotary_emb (outputs) +24-11-19 20:49:59 | D | - Quantizing model.layers.31.mlp.gate_proj (inputs) +24-11-19 20:49:59 | D | - Quantizing model.layers.31.mlp.up_proj (inputs) +24-11-19 20:49:59 | D | - Quantizing model.layers.31.mlp.down_proj (inputs) +24-11-19 20:49:59 | I | - Saving activation quantizer settings to runs/shang/llm/cache/quant/pileval.128x1024.[0-0]/acts/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/w.skip.[]-x.skip.[]-y.skip.[attn_q]/rotate.hadamard.[out_proj]/w.kernel.gptq.d0p01.b128/w.range.OutputsError.GridSearch.Group.d2.e512.sn1/w.range.r.[0p2.1].g80/w.range.skip.[]/y.range.OutputsError.Manual.Layer.d2.en1.sn1/y.range.r.[1]/y.range.skip.[]/llama-3-8b-instruct-gradient-1048k.pt +24-11-19 20:49:59 | I | - Linking activation quantizer settings to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0].RUNNING/run-241119.201603.RUNNING/model/acts.pt +24-11-19 20:49:59 | I | * Evaluating model +24-11-19 20:49:59 | W | `pretrained` model kwarg is not of type `str`. Many other model arguments may be ignored. Please do not launch via accelerate or use `parallelize=True` if passing an existing model this way. +24-11-19 20:49:59 | I | Using model type 'default' +24-11-19 20:49:59 | W | Passed an already-initialized model through `pretrained`, assuming single-process call to evaluate() or custom distributed integration +24-11-19 20:49:59 | I | - Evaluator: gptq +24-11-19 20:49:59 | I | - Tasks: ['wikitext'] +24-11-19 20:49:59 | I | - Batch_size: 8 +24-11-19 20:49:59 | I | + Max_seq_length: 2048 +24-11-19 20:49:59 | D | Starting new HTTPS connection (7): huggingface.co:443 +24-11-19 20:50:05 | W | Using the latest cached version of the dataset since wikitext couldn't be found on the Hugging Face Hub +24-11-19 20:50:05 | W | Found the latest cached dataset configuration 'wikitext-2-raw-v1' at /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3 (last modified on Tue Oct 8 19:51:38 2024). +24-11-19 20:50:05 | D | Attempting to acquire lock 23438670002320 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:50:05 | D | Lock 23438670002320 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:50:05 | D | open file: /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3/dataset_info.json +24-11-19 20:50:05 | D | Attempting to release lock 23438670002320 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:50:05 | D | Lock 23438670002320 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:50:37 | I | - Results: +24-11-19 20:50:38 | I | | Task |Version| Metric |Value | |Stderr| +24-11-19 20:50:38 | I | |--------|------:|---------------|-----:|---|-----:| +24-11-19 20:50:38 | I | |wikitext| 1|word_perplexity|7.9956|± |7.9956| +24-11-19 20:50:38 | I | +24-11-19 20:50:38 | I | + Max_seq_length: 4096 +24-11-19 20:50:38 | D | Starting new HTTPS connection (8): huggingface.co:443 +24-11-19 20:50:54 | W | Using the latest cached version of the dataset since wikitext couldn't be found on the Hugging Face Hub +24-11-19 20:50:54 | W | Found the latest cached dataset configuration 'wikitext-2-raw-v1' at /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3 (last modified on Tue Oct 8 19:51:38 2024). +24-11-19 20:50:54 | D | Attempting to acquire lock 23438409937216 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:50:54 | D | Lock 23438409937216 acquired on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:50:54 | D | open file: /home/yujunlin/.cache/huggingface/datasets/wikitext/wikitext-2-raw-v1/0.0.0/b08601e04326c79dfdd32d625aee71d232d685c3/dataset_info.json +24-11-19 20:50:54 | D | Attempting to release lock 23438409937216 on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:50:54 | D | Lock 23438409937216 released on /home/yujunlin/.cache/huggingface/datasets/_home_yujunlin_.cache_huggingface_datasets_wikitext_wikitext-2-raw-v1_0.0.0_b08601e04326c79dfdd32d625aee71d232d685c3.lock +24-11-19 20:51:21 | I | - Results: +24-11-19 20:51:21 | I | | Task |Version| Metric |Value | |Stderr| +24-11-19 20:51:21 | I | |--------|------:|---------------|-----:|---|-----:| +24-11-19 20:51:21 | I | |wikitext| 1|word_perplexity|7.4037|± |7.4037| +24-11-19 20:51:21 | I | +24-11-19 20:51:21 | I | * Saving results to runs/shang/llm/llama-3/llama-3-8b-instruct-gradient-1048k/w.8-x.8-y.8/w.sint8-x.sint8-y.sint8/w.gchn.fp16-x.gchn.fp16-y.tsnr.fp16/rotate-w.static.gptq.range-y.static/skip.y.[q]-gptq-rot.[+out]-w.range.[0p2.1.g80]-pileval.128x1024.[0-0]/run-241119.201603